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DEVELOPMENT OF A WATER MANAGEMENT DECISION MODEL
FOR LIMPOPO PROVINCE, SOUTH AFRICA
K.A. TSHIKOLOMO
DEVELOPMENT OF A WATER MANAGEMENT DECISION MODEL FOR LIMPOPO
PROVINCE, SOUTH AFRICA
BY
KHATHUTSHELO ALFRED TSHIKOLOMO
Thesis submitted to the Faculty of Natural and Agricultural Sciences,
Centre for Sustainable Agriculture,
University of the Free State
In accordance with the requirements for the degree
PHILOSOPHIAE DOCTOR
Promoter: Professor A.E. Nesamvuni
Co-Promoters: Professor S. Walker
Professor A. Stroebel
July 2012
2
~------------------------------~.~I--------------------------------------~
DECLARATION
I declare that this thesis hereby submitted for the degree of Doctor of Philosophy in Sustainable
Agriculture at the University of the Free State, is my own independent work and has not been
submitted for the purposes to any other university. I further cede copyright of this thesis in
favour of the University of the Free State.
...................................................... . .
Khathutshelo Alfred Tshikolomo Date
ACKNOWLEDGEMENTS
I would like to gratefully acknowledge the following for their valuable contribution to the
success of this study:
• My promoter, Professor Edward Nesamvuni, and eo-promoters, Professors: Sue Walker
and Aldo Stroebel, for their invaluable supervision, guidance and encouragement
throughout the study. Your constructive comments and ideas were critical for the
completion of this study;
• The Department of Water and Environmental Affairs for the valuable information
provided through departmental plans and reports and in interpersonal discussions;
• The South African Weather Services, the Water Research Commission, and the
Agricultural Research Council for important climatic and water related information they
provided;
• Staff of the Centre for Sustainable Agriculture, the Director- Prof. Izak Groenewald and
his team, for the administration work and support during my consultation visits.
• Specialist staff of the Limpopo Department of Agriculture (LDA), Dr. K.A. Nephawe for
assistance with data analysis and other IT expertise and Messrs James Mulaudzi and
Maanda Dagada who assisted with data analysis and interpretation Dr. B.M. Petja and
Mr. R.G. Lekalakala helped refine hydrological concepts, while Mr. M.S. Nevhutanda
developed the maps.
• Extension Officers of the LDA who served as enumerators for collection of household
data, namely: B. Maranele, M. Mmbengeni, T.S. Khabe, M.K. Nkuna, H.A. Mashimbye,
K.P. Dlomu, H.E. Sambo, M.S. Mulelu, N.S. Ramakhumisa, A.D. Nengovhela, N.R.
Matodzi, L.C. Netshisaulu, and N.C. Netshithuthuni .
• Municipal water managers of the 10 municipalities selected for the study and members of
the 467 sampled households, who were interviewed and provided information, are
gratefully acknowledged. It is sincerely hoped that the results of the study will contribute
to the improvement of your situation.
DEDICATION
For the conception and completion of this study, I am thankful to the Almighty God who
provided life, good health, peace and wisdom, without which there could have been no study.
My father, Thomani Phanuel Tshikolomo (late) and my mother, Nkhanedzeni Tshavhungwe
ignited an ever burning desire for education in my life and this inspired me to conduct this study.
My wife, Humbulani was very supportive throughout the study and her encouragement made it
possible for this work to reach completion. Our three children, Wavhudi, Thikho and Masana
were able to go on without some of the privileges as I could not provide due to my deep
commitment to this study.
It is hoped that the successful completion of this work will serve as a source of inspiration, not
only to the Tshikolomo or broader Mutolo family, but to all who allow this work to ignite a
desire for education in their life.
ii
ABSTRACT
The study was conducted in the Limpopo Province with a focus on the Limpopo and Luvuvhu-
Letaba Water Management Areas. The main issues investigated were (1) water resources, mainly
runoff and storage capacity of the target Water Management Areas and municipalities, and the
water gain and loss of the Middle Letaba Dam, (2) water management issues, mainly perceptions
of municipal water managers on the water resource and its uses, and their perceptions on
stakeholder participation, and (3) household water supply and requirement. A water management
decision model was proposed based on the results of the investigations.
The results of the investigations revealed that: (1) The Limpopo WMA has a MAR of 611.4
million m3 for possible development of new dams compared to only 365.2 million m3 for the
Luvuvhu-Letaba WMA, and related results were recorded for municipalities in these WMAs.
The storage volumes of the Middle Letaba Dam were very small compared to design capacity;
(2) The municipal water managers lacked knowledge on water resources and were relatively
more knowledgeable on water use. Water management decisions were made by government
based stakeholders while community based stakeholders had little influence on water
management decisions; (3) There was a lack of access to safe water sources, only half (50.1%) of
households obtained water from street taps. The quantity of water fetched ranged from 25 to
more than 200 litres per household per day and the amount fetched was more for households
located near the water sources. As a result of scarcity, water was mostly used for basic activities
such as drinking, preparing food and bathing. Half (51. 7%) of the households fetched less water
than the 25 litres per capita per day supply standard which itself did not meet the average
requirement of 37.5 litres per capita per day; and (4) A water management decision model was
proposed based on the framework of the Congruence Model. The proposed model stated the
main challenges faced by the water sector in the study area and assessed the capacity of the
service organisations to address them by analysing the congruence between the challenges and
the capacity. All assessed water service organisations only had moderate capacity to address the
iii
challenges. The lack of filling of some posts was the most significant constraint to the
effectiveness of the organisations.
It is therefore recommended that: (1) The Limpopo WMA be the focus for possible construction
of new dams, especially the Mogalakwena, Lephalale and Mokoio catchments in the WMA as
they showed to have more available mean annual runoff for possible development of new dams.
Although the Luvuvhu-Letaba WMA was shown to be well developed in terms of storage dams,
the Mutale Catchment had more available mean annual runoff for possible development of new
dams. Regular investigations of runoff and dam storage capacity should be conducted as the
current status will change due to changing rainfall patterns and dam siltation. Water should be
transferred to the Middle Letaba Dam from other catchments in order to maintain this dam at a
full level and consequently to improve the supply of the resource to planned areas; (2).
Municipal water managers should be trained on water resources and to a lesser extent on
resource uses for them to make relevant decisions on the management and use of the resource.
Community based stakeholders should be involved in water management decisions and should
be capacitated to be reliable sources of water information; (3) The Department of Water Affairs
should reconsider the 25 litres per capita per day as a supply standard as it does not suffice for
the average requirement of 37.5 litres per capita per day proposed in this study. (4) Guided by
the proposed water management decision model, service organisations should improve their
capacity to address water sector problems.
Key words: water management area, municipality, water resources, rainfall, runoff, dam storage
capacity, water supply, water use, stakeholder participation, congruence model, water service
organization, water management decision model.
iv
TABLE OF CONTENTS
DECLARA TION
ACKNOWLEDGEMENTS
DEDICATION II
ABSTRACT III
1 INTRODUCTION AND BACKGROUND 1
1.1 Introduction 1
1.2 Overview of national water resources
1.3 Description of the study area 2
1.3.1 Geographic description 2
, 1.3.2 Socio-economic description 5
1.3.3 Environment 11
1.4 Purpose of the study 15
1.5 Summary 16
1.6 Outline of the thesis 17
1.7 Publication of research work 19
2 RESEARCH METHODOLOGY 21
2.1 Introduction 21
2.2 Description of knowledge 21
2.2.1 Kinds of knowledge 21
2.2.2 Scientific knowledge 23
2.3 Research approach 25
v
2.3.1 Main approaches
2.3.2 25Rationale for a mixed approach 27
2.4 Research design 28
2.5 Research methods 31
2.5.1 Literature review methods
2.5.2 31Secondary data analyses
2.5.3 32Survey methods
2.5.4 33Content analyses 34
2.6 Elimination of error 35
2.7 Research process 36
2.7.1 Orientation and planning 37
2.7.2 Design of survey questionnaires 38
2.7.3 Sample frame and sampling procedure 38
2.7.4 Data collection and analysis 41
2.9 Summary and conclusion 42
3 LITERATURE REVIEW 44
3.1 Introduction 44
3.2 Water resources 45
3.2.1 Rainfall and runoff generation 47
3.2.2 Water supply system 48
3.3 Water resource management 50
3.3.1 Resource knowledge and its implementation 50
3.3.2 Stakeholder participation 53
3.4 Water supply and requirement 56
3.4.1 Household water supply 57
3.4.2 Household requirement of water 58
3.5 Models for water resource management 59
3.5.1 Description of the modelled world 59
3.5.2 Characterization of models 61
3.5.3 Types of models 67
3.5.4 Organisational diagnostic models 69
3.5.5 Suitability of organisational diagnostic models to guide water decisions 71
3.6 Summary and conclusion 77
vi
4 RUNOFF AND STORAGE CAPACITY OF RIVER CATCHMENTS AND
MUNICIPALITIES 79
4.1 Introduction 79
4.2 Methodology 80
4.2.1 Study area 80
4.2.2 Sampling procedure 82
4.2.3 Data collection and analysis 82
4.3 Results and discussion 82
4.3.1 Runoff and storage capacity ofriver catchments in the study area 82
4.3.2 Runoff and storage capacity of municipalities in the study area 89
4.4. Summary and conclusion 92
5 RAINFALL INFLUENCE ON WATER GAIN AND LOSS FROM MIDDLE
LETABA DAM 94
5.1 Introduction 94
5.2 Methodology 95
5.2.1 Dam location and physical characteristics 95
5.2.2 Sampling procedure 96
5.2.3 Data collection and analysis 97
5.3 Results and discussion 97
5.3.1 Rainfall received over the surface area of the dam 97
5.3.2 The influence of rainfall on inflow from source river 98
5.3.3 Rainfall influence on evaporation from the dam surface 100
5.3.4 The influence of rainfall on outflow from the dam 102
5.3.5 Rainfall and dam water storage volume 104
5.4. Summary and conclusion 107
6 PERCEPTIONS OF MUNICIPAL WAT,ERMANAGERS ON WATER
RESOURCES, USES AND RESTRICTIONS 108
6.1 Introduction 108
6.2 Research methods 109
vii
6.2.1 Description of study area 109
6.2.2 Sampling procedure lID
6.2.3 Data collection and analysis lID
6.3 Results and discussion 111
6.3.1 Perceptions on municipal water resources III
6.3.2 Perceptions on municipal water uses 114
6.3.3 Perceptions on water restrictions 124
6.4 Summary and conclusion 127
7 MUNICIPALITY PERCEPTIONS OF STAKEHOLDER PARTICIPATION AND
INFLUENCE ON WATER MANAGEMENT DECISIONS 128
7.1 Introduction 128
7.2 Research methods 129
7.2.1 Study area 129
7.2.2 Sampling procedure 130
7.2.3 Data collection and analysis 130
7.3 Results and discussions 131
7.3.1 Stakeholder organisations and their roles 131
7.3.2 Stakeholder participation in water management decisions 133
7.3.3 Stakeholder influence on water management decisions 139
7.4 Summary and conclusion 146
8 HOUSEHOLD WATER SUPPLY AND REQUIREMENTS 149
8.1 Introduction 149
8.2 Research methodology 150
8.2.1 Description of study area 150
8.2.2 Smpling procedure 151
8.2.3 Data collection and analysis 151
8.3 Results and discussion 152
8.3.1 Characterisation of households 152
8.3.2 Household water supplies 158
8.3.3 Household water uses 164
8.4. Summary and conclusion 168
viii
9 CHALLENGE AND CAPACITY CONGRUENCE ANALYSIS FOR
DEVELOPMENT OF A WATER MANAGEMENT DECISION MODEL 169
9.1 Introduction 169
9.2 Description of the Congruence Model 170
9.2.1 Congruence between units across components: Person-Environment Fit 173
9.2.2 Congruence between units within a component: The example of transformation 174
9.2.3 Congruence and water sector effectiveness 176
9.3 Research methodology 176
9.3.1 Rationale for selecting the Congruence Model 176
9.3.2 Sampling procedure 177
9.3.3 Description of the study area 178
9.3.4 Data collection and analysis 179
9.4 Results and discussion 180
9.4.1 Input components and their influence on the water sector 180
9.4.2 Major challenges faced by the water sector 186
9.4.3 Organisational strategies and their congruence with water sector challenges 187
9.4.4 Transformation components and their congruence with strategies 190
9.4.5 Congruence between allocated and utilized organisational resources 194
9.4.6 Congruence flow analysis 197
9.4.7 Proposal ofa water management decision model 198
9.5 Summary and conclusion 204
10 POLICY RECOMMENDATIONS 205
10.1 Focus of the study 205
10.2 Main findings 205
10.2.1 Water resources 205
10.2.2 Water management 205
10.2.3 Household water supply and requirement 206
10.3 Policy recommendations 206
10.3.1 Water resources 206
10.3.2 Water management 207
10.3.3 Household water supply and requirement 208
10.3.4 Water management decision model 209
11 LIST OF REFERENCES 210
ix
LIST OF TABLES
Table 1.1 Mean monthly rainfall (mm) distribution of sampled municipalities in the study area
(SAWS, undated) 12
Table 1.2 Mean monthly evapotranspiration (ET mm) of sampled municipalities in the study area
(SAWS, undated) 14
Table 1.3 Real-life problems of the water sector in Limpopo Province and corresponding
research objectives to address them 16
Table 2.1 Comparison of quantitative and qualitative research approaches (Leedy and Ormrod,
2010) 26
Table 2.2 Research objectives and matching attributes of research approaches 27
Table 2.3 Research designs for different chapters included in the study 29
Table 2.4 Main sources of errors for the five research methods used in the study (Mouton, 2001)
and strategies used to eliminate the errors , 36
Table 3.1 Conceptualisation of four HPP framework systems (Nelson and Burns, 1984) 73
Table 3.2 Conceptualisation ofIndividual and Group Levels in DIGB model (Harrison, 1987).74
Table 3.3 Issues for describing congruence between different pairs of internal transformational
components of the Congruence Model (Nadler and Tushman, 1980) 75
Table 3.4 Evaluation of described diagnostic models based on their inclusion of aspects defining
a well-functioning and responsive organisation (Gill, 2000; Mertikas, 2008) 76
Table 4.1 Storage capacity and available MAR for possible development of new dams in river
catchments of the Limpopo and Luvuvhu-Letaba WMAs (DWAF, 2003; DWAF, 2004b) 86
Table 4.2 Storage capacity and available MAR for possible strategic water related projects in
selected municipalities of the Limpopo and Luvuvhu-Letaba WMAs (DWAF, 2003; DWAF,
2004b) 91
Table 6.1 Perceptions of municipal water managers on number and sizes of rivers flowing
through their municipal areas 112
Table 6.2 Perceptions of municipal water managers on major uses of the resource according to
quantities consumed 115
x
Table 6.3 Perceptions of municipal water managers on household uses of water according to
quantities consumed by activity 118
Table 6.4 Perceptions of municipal water managers on industrial uses of water according to
quantity consumed by activity 120
Table 6.5 Perceptions of municipal water managers on agricultural uses of water according to
quantity consumed by activity 122
Table 7.1 Issues discussed in water stakeholder meetings of the study municipalities in the
Limpopo and Luvuvhu-Letaba WMAs 136
Table 7.2 Perceived levels of influence of water stakeholders on broad water management
decisions in study municipalities under Limpopo and Luvuvhu-Letaba WMAs 141
Table 8.1 Distribution of heads of household in the study municipalities under the Luvuvhu-
Letaba WMA according to age 153
Table 8.2 Monthly incomes of households in the study municipalities of the Luvuvhu-Letaba
WMA 156
Table 8.3 Sizes of houses owned by households in study municipalities in the Luvuvhu-Letaba
WMA 157
Table 8.4 Sources of water for households in the study municipalities of the Luvuvhu-Letaba
WMA enlisted from unsafe (1) to safer (6) sources 159
Table 8.5 Distribution of households in the study municipalities of the Luvuvhu-Letaba WMA
according to quantity of water fetched 162
Table 8.6 Distribution of households in study municipalities of the Luvuvhu-Letaba WMA
according to uses of water for basic household and productive activities 165
Table 8.7 Distribution of households in the study municipalities of the Luvuvhu-Letaba WMA
according to their daily water requirements for different uses 167
Table 9.1 Water sector environment of the Limpopo Province 181
Table 9.2 The impact of the Water Act of 1956 and of the National Water Act of 1998 on water
sector performance (RSA, 1956; RSA, 1998a; de Coning, 2006; Woodhouse, 2008) 185
Table 9.3 Congruence rating between water sector challenges and responsive organisational
strategies of Limpopo Regional Office of DWA and the WSAs of MDM, VDM and PLM ..... 189
xi
Table 9.4 Analysis of congruence between strategies and tasks of water service organisations of
Limpopo Regional Office ofDWA, MDM, VDM and PLM 192
Table 9.5 Analysis of congruence between allocation and utilisation of human (posts) and
financial (budget) resources of water service organisations of Limpopo DWA, MDM, VDM and
PLM (DWAF, undated; MDM, 2009; VDM, 2009 and PLM, 2009) 195
Table 9.6 Congruence flow analysis of input and transformation components of four water
service organisations: DWA, MDM, VDM and PLM 197
xii
LIST OF FIGURES
Figure 1.1 Map of Limpopo Province showing the Water Management Areas (brown lines) and
the main rivers (blue lines) (DWAF, 2004a) 3
Figure 1.2 Map of Limpopo Province showing the Water Management Areas (brown lines),
district (grey lines) and local municipalities (different colour shadings) 4
Figure 4.1 Map of the Limpopo Province showing the Limpopo and Luvuvhu-Letaba Water
Management Areas (red border line) and the ten municipalities (hatchings) sampled for the study
(DWAF, 2004a) 81
Figure 4.2 Mean annual runoff (MAR) ofriver catchments of the Limpopo and Luvuvhu-Letaba
WMA (DWAF, 2003; DWAF, 2004b) 84
Figure 4.3 Influence of runoff on storage capacity of river catchments of Limpopo and Luvuvhu-
Letaba WMAs 88
Figure 4.4 Mean annual runoff (MAR) of municipalities of the Limpopo and Luvuvhu-Letaba
WMA (Midgley ef al., 1994) 90
Figure 5.1 Location of the Middle Letaba Dam (blue water body) in the Middle Letaba
Catchment (grey line) within the Luvuvhu-Letaba WMA (red line) 96
Figure 5.2 Mean monthly rainfall received over the surface area of the Middle Letaba Dam
during 1990- 2009 (DWAF, undated) 98
Figure 5.3 Mean monthly rainfall and inflow to the Middle Letaba Dam during 1990 - 2009
(DWAF, undated) 100
Figure 5.4 Mean monthly rainfall and evaporation from the Middle Letaba Dam during 1990 -
2009 (DWAF, undated) 101
Figure 5.5 Mean monthly rainfall and outflows from the Middle Letaba Dam during 1990-2009
(DWAF, undated) 103
Figure 5.6 Mean monthly rainfall and dam storage volume of Middle Letaba Dam during 1990-
2009 (DWAF, undated) 105
Figure 5.7 Correlation between mean monthly rainfall with a 2-month lag and dam storage
volume of Middle Letaba Dam during 1990-2009 (DWAF, undated) 106
Figure 6.1 Map of the Limpopo Province showing the Limpopo and the Luvuvhu- Leataba
WMAs (red line) and the study municipalities (hatchings) 109
xiii
Figure 6.2 Perceptions of municipal water managers on water restrictions across the months of
the year 124
Figure 6.3 Influence of monthly rainfall on number of municipalities imposing water restrictions
..................................................................................................................................................... 126
Figure 7.1 Map of Limpopo Province with Water Management Areas (red lines) and
municipalities (hatchings) comprising the study area 129
Figure 7.2 Frequency of stakeholder meetings and number of water management issues
discussed in each meeting 134
Figure 7.3 Water stakeholders and ratings of their reliability as sources of water management
information 140
Figure 7.4 Rating of different stakeholders according to their level of influence on specific topics
discussed in meetings 144
Figure 7.5 Relationship between stakeholder reliability as sources of water management
information and their level of influence on resource management decisions 146
Figure 8.1 Map of Luvuvhu-Letaba WMA showing the location of the study municipalities and
villages : 150
Figure 8.2 Distribution of households in study municipalities in the Luvuvhu-Letaba WMA
according to their sizes 154
Figure 8.3 Distribution of households in study municipalities of the Luvuvhu-Letaba WMA
according to the distance of water source from residential sites 160
Figure 8.4 Influence of distance of water source from residential site on quantity fetched ....... 163
Figure 9.1 Adjusted Congruence Model ofNadler and Tushman (1980) 171
Figure 9.2 Map of Limpopo Province showing the Limpopo and the Luvuvhu-Letaba WMA (red
line), Mopani and Vhembe District Municipalities and the Polokwane Local Municipality
(hatchings) 178
Figure 9.3 Assessment of water service organisations of Limpopo Province using the adjusted
Congruence Model 201
xiv
CHAPTER1
1 INTRODUCTION AND BACKGROUND
1.1 Introduction
This introduction outlines the issues discussed in the rest of the chapter, namely: (1) an overview
of national water resources to provide the context in which the study area exists; (2) a description
of the study area (geographic, socio-economic, and environmental description) with an analysis
of the macro-environment and identification of water related problem areas that guide the focus
of the research project; (3) the purpose of the study, presenting the study objectives which
respond to the problems experienced by the water sector in the study area; and (4) outline of the
thesis which serves as a guide to the reader.
1.2 Overview of national water resources
South Africa is located in a predominantly semi-arid part of the world. The climate varies from
arid in the west to humid along the eastern coastal area. The country mean annual rainfall is
about 450mm which is well below the world average of about 860mm while evaporation is
comparatively high (DWAF, 2004a). As a result, the country's water resources are scarce.
According to DWAF (2004a), the combined flow of all the rivers in South Africa is
approximately 49 000 million m3 per annum and is less than half of that of the Zambezi River
alone.
The view that South Africa is a water scarce country was supported by CIWA (1970) who
projected that the country's water requirement would exceed resource supply in 2000. According
to Weaver (1990), the country's water requirement will only exceed supply in 2020 while
Odendaal (1992) argued that this will occur sometime between 2020 and 2030. Muller (2002)
and Inocencio et al. (2003) predicted that South Africa is likely to run out of water in 2025. It
may be concluded from these projections that the water resources in our country are not
inexhaustible.
1
Itwas in fact affirmed by Greeff (2010) that there is not enough water for South Africa's current
and planned socio-economic development. Efficient management of the water resources is
therefore crucial to sustain future water supply. According to Greeff (2010), efficient water
management should consider the nexus between our scarce water resources, potential climate
change impacts, and issues of long term food security. Informed by these links among the water
resources, impacts of climate change and issues of food security, efficient management of water
resources should promote sustainable development.
Four of South Africa's main rivers are shared with other countries. These shared rivers are the
Limpopo, Inkomati, Pongola and Orange River. The four rivers together drain about 60% of the
country's land area and contribute about 40% of its total surface runoff (DWAF, 2004a). As
stated by DWAF (2004a), these four rivers contribute to approximately 70% of our country's
gross domestic product (GDP). Judicious joint management of these rivers between South Africa
and the neighbouring countries with which they are shared is of paramount importance for
regional peace and stability.
It is clear from the above discussion that South Africa is a water scarce country and has to
manage the available water resources efficiently. The fact that 60% of the country's land area is
drained by shared rivers suggests that management of the water resources should be compliant
with relevant international protocols. The national resource scarcity and the occurrence of shared
rivers constitute an important context for managing water resources in the study area.
1.3 Description of the study area
1.3.1 Geographic description
The study was conducted in the Limpopo Province of South Africa. Selection of study sites
within the province was based on two geographic aspects, (1) Water Management Areas and
their river catchments, and (2) district and local municipalities. The geographic description of the
study area will therefore be made in terms of these aspects.
2
(a) Water Management Areas and their river catchments
The province has four Water Management Areas (WMAs) located in it. The Limpopo and the
Luvuvhu-Letaba WMAs are fully located while the Olifants and the Crocodile West and Marico
are partially located in the province (Figure 1.1). The two WMAs that are fully located within the
province entirely represent the province and were the focus of the study.
-t·
0.....
Figure 1.1 Map of Limpopo Province showing the Water Management Areas (brown lines) and
the main rivers (blue lines) (DWAF, 2004a)
The main river catchments within the WMAs targeted by the study are the Matlabas, MokoIo,
Lephalale, Mogalakwena, Sand, Nzhelele and Nwanedi in the Limpopo WMA and the Mutale,
3
Luvuvhu, Klein Letaba, Middle Letaba and Groot Letaba in the Luvuvhu-Letaba WMA (Figure
LI). The river catchments are discussed to different extents in the various chapters of the study.
(b) District and local municipalities
The province is politically divided into five district municipalities (referred to as districts), the
Vhembe, Waterberg, Capricorn, Mopani and Sekhukhune District (Figure 1.2). The study
covered four of the districts with only Sekhukhune excluded.
o.scrlCI"".r"CIO.~h ..
Pro v 11'IC111 Boundarle.
INKOMATI
Figure 1.2 Map of Limpopo Province showing the Water Management Areas (brown lines),
district (grey lines) and local municipalities (different colour shadings)
The districts are politically divided into local municipalities (referred to as municipalities) with
each district having between four and six such municipalities. The number of municipalities
4
selected for the study is 10 with four (Makhado, Thulamela, Musina and Mutale) in Vhembe,
three (Letaba, Tzaneen and Giyani) in Mopani, two (Polokwane and Aganang) in Capricorn and
one (Lephalale) in Waterberg District.
Of the 10 municipalities selected for the study, five are in the Limpopo WMA, namely: Makhado
and Musina in Vhembe District, Polokwane and Aganang in Capricorn and Lephalale in
Waterberg District. The other five municipalities included in the study are in the Luvuvhu-
Letaba WMA, the Thulamela and Mutale in Vhembe and the Letaba, Tzaneen and Giyani in
Mopani District.
Investigations in the study will focus on different combinations of the geographic aspects of
water management areas (with their river catchments), districts and municipalities. Some of the
investigations will be limited to only one of these WMAs and only some of the catchments,
districts and municipalities.
1.3.2 Socio-economic description
In order to provide a comprehensive socio-economic description of the Limpopo Province, its
socio-economic environment was properly scanned. Environmental scanning is the acquisition
and use of information about events, trends, and relationships in an organisation's external
environment, the knowledge of which would assist management in planning the organisation's
future course of action (Auster and Choo, 1993; Choo 1998). Organisations scan their socio-
economic environment in order to understand external forces of change so that they may develop
effective responses which secure or improve their position in the future.
Meaningful scanning of the socio-economic environment should be guided by some framework
that highlights pertinent issues to be targeted by the scan. The PESTEL framework was adopted
for guiding the scan of the socio-economic environment for this study. Pertinent issues
highlighted in the PESTEL framework are the Political, Economic, Social, Technological,
5
Environmental and Legal factors (Fahey and Narayanan, 1986). Guided by the PESTEL
framework, the socio-economic description of the study area follows.
(a) Political situation
In accordance with the constitution of the Republic of South Africa (RSA, 1996), the Limpopo
Province has a legislature with 49 seats. In the fourth legislature of 2009, 43 seats were won by
the African National Congress (ANC), 4 by the Congress of the People (COPE) and 2 by the
Democratic Alliance (DA) (IEC, 2009). The legislature elects the Premier from the majority
party. The Premier appoints the Members of the Executive Council from among members of the
provincial legislature (RSA, 1996). The executive council runs the provincial government within
the mandate of the ruling party.
In the same way that the provincial legislature elects a premier, the municipal council elects a
mayor who is referred to as executive mayor for a district municipality. The mayor appoints the
mayoral committee from among the members of the municipal council, and the committee serves
as the executive of the municipal government (RSA, 1996).
The political leaders of these spheres of government influence strategic direction and hence the
allocation of budgetary and other resources. The political system also exerts influence through
the legislature and municipal councils who approve government strategic and annual plans and
also play an oversight role of ensuring that the plans are properly implemented (RSA, 1996). The
communities in the study area are mostly active politically and have an influence on their
political parties who hold the government to account.
The water programmes run by the provincial and municipal governments include facilitation and
funding infrastructure development. The building of dams is an important strategy for improving
water supply in the study area. Dams are mostly funded by the national Department of Water
Affairs with provincial and municipal governments leading local facilitation (RSA, 1998a).
Reticulation infrastructure and water services are mostly funded by municipalities (RSA, 1997).
6
The availability of adequate well maintained water infrastructure has a strong influence on the
supply of water (Randall, 1981; Backeberg and Groenewald, 1991).
Major dams in the study area are the Mokolo, Doorndraai, and Nzhelele in the Limpopo WMA
and the Albasini, Vondo, Nandoni, Middle Letaba, Nsami, Ebenezer and Tzaneen in the
Luvuvhu-Letaba WMA (DWAF, 2003; DWAF, 2004b). The dams store water in the wet season
when and where the marginal value of the resource is low and reallocates it to the dry season
when and where the marginal value is high (Keller et al., 2000). a Prior to building more dams in
the Limpopo Province, planners should know the quantity of water that can be stored in the
existing dams and the amount of water that could remain available for future storage, and these
were investigated in this study.
The extent of development of infrastructure in the Limpopo Province varies from one locality to
another. The general trend is for urbanised areas to have better infrastructure than their rural
counterparts although access to services provided by such infrastructure is influenced by the
economic status of individuals (DANIDA, 2000). Although the issue of water reticulation
infrastructure is important for water management in the study area, it is not the focus of this
study and will not be further investigated.
(b) Economic condition
Limpopo is one of the poorest provinces in South Africa (RSA, 2000). The province only
contributes 6.9% of the GDP (Stats SA, 2008). The poverty is affirmed by the lack of
infrastructure, including water reticulation infrastructure. According to Stats SA (2009), only
18% of households had piped water inside the house compared to 47.2% nationally. The smaller
number of households with piped water suggests a lack of infrastructure for water services and
affirms RSA (2000) that the province is poor. As a result of poverty, most households are
registered as indigents in order to qualify for social grants and free services such as water
services (Stats SA, 20IIa). Up to 57.9% of households in the province receive grants compared
to the national figure of 28.4% (Stats SA, 20 11b).
7
With this state of poverty, increased development of the water resource could make it possible
for new economic development projects to be initiated. Further development of the water
resource may only be possible if relevant stakeholders have adequate knowledge about the
resource and its current use. It is only when the stakeholders are knowledgeable that they will be
able to make informed decisions about the prospects of further development of the resource for
future use. Among the critical stakeholders for the water sector are the municipal water
managers. The responsibilities of the municipal water managers are to broaden as the
Department of Water Affairs continues with its restructuring in which most implementation
functions will be transferred to municipalities for the department to focus on policy issues
(DWAF, 2007).
Although the water managers report directly to municipal managers (administrative head of
district or municipality), they also report indirectly to the mayors of their municipalities. The
water managers advice both the municipal managers and the majors on water issues and have a
lot of influence on water management decisions. The managers' knowledge of their water
resources is therefore crucial for them to ~ake informed resource management decisions. b There
is a lack of information about these managers knowledge of the water resources and hence it was
necessary for this study to conduct some focussed research on this issue.
(c) Social situation
The social environment includes social services such as health and education (Barnett and
Casper, 2001), communication networks and the participation of people in decision making. On
the issue of health services, Limpopo Province has 40 public hospitals distributed in the five
districts of Capricorn (9 hospitals), Mopani (8), Sekhukhune (7), Waterberg (8) and Vhembe (8)
(OTP, 2009). In addition to the shortage of health professionals, the hospitals mostly have
dilapidated infrastructure with old equipment which result in poor services.
With regards to education, the province still faces challenges of poor classroom infrastructure
and shortage of educators and equipment for learning areas such as mathematics and science.
8
The shortage of classroom infrastructure has made the Department of Education introduce
mobile classes (Nduvheni, 2007). In terms of the educational status of the population, 19.4% had
no schooling compared to only 9.4% nationally. Some 5.9% of the population had primary
education compared to 7% nationally, 12.5% had grade 12 compared to 18% nationally, while
6.4% had tertiary education compared to 8.8% nationally (Stats SA, 2009). The above statistics
indicate that the province is educationally under-developed compared to the national situation.
Other than the written media, communication of water sector information would require access
to media such as radio and television. With a population of 5.2 million, Limpopo Province has a
radio listenership of 3.3 million and a television viewership of 2.7 million (MDDA, 2009). The
population is therefore well exposed to information communicated through both radio and
television media.
Water sector information communicated through radio and television should reach the majority
of the population and may promote public participation in resource management decisions. The
participation of all relevant stakeholders in water decisions is important for broader community
acceptance of the decisions. The National Water Act (Act No. 36 of 1998) provides for the
formation of institutions such as the Water Users Associations (WUAs) and Catchment
Management Agencies (CMA), (RSA, 1998b) to allow for stakeholder participation.
Communities in the province occasionally embark on public protests against the government's
performance in delivering water services. These protests may be indicative of poor participation
of the communities in water management decisions. There is a lack of information on major
stakeholders of the water sector in the province and their level of participation in resource
decision making. eTo address the stakeholder information gap, this research project conducted a
focussed investigation of the existing stakeholders and their level of participation in resource
management decisions.
9
(d) Technological situation
Associated with poor economic development and low educational status, the province has low
capacity to generate relevant technologies to respond to water challenges. The low capacity to
generate technologies is also associated with lack of research capacity. Factors associated with
the lack of capacity to conduct research include the scarcity of research skills and requisite
infrastructure. It is important for the province to build research capacity in order to generate
appropriate technologies to respond to the challenges faced by the water sector. Initiatives to
develop research capacity should be focus sed at the two universities in the province, the
University of Limpopo and the University of Vend a as they already have some basic resources.
Water sector problems for possible research should include those related to the hydrology of
catchments and reservoirs. Reservoir problems demanding research would include that of the
Middle Lataba Dam that seldom fills up. The dam is one of the large reservoirs in the province
and its persistent low water levels contribute to the problem of shortage of water supply. The
area planned to be supplied from this dam has experienced frequent shortages of water.
. The shortage of water supply from the Middle Letaba Dam has resulted in a situation where the
limited water available is reserved only for household use. Other planned uses such as irrigation
are not supplied and therefore multi-million rand worth of irrigation infrastructure installed in
some farming projects is not used. Major investments in irrigation infrastructure were made at
the Homu and the Middle Letaba Irrigation Schemes. These schemes have scaled down
agricultural production because of shortage of water. dIt is not clear whether the Middle Letaba
Dam will ever fill up to its capacity and allow for increased supply of water to target
communities. It was therefore necessary to conduct a focussed investigation of the hydrology of
this dam. There may be more cases in the province that require research intervention and
development of responsive information and technologies, and this necessitates some
improvement of research capacity.
10
(e) Legal situation
Similar to the situation in the broader South Africa, the legal environment of the Limpopo
Province is characterized by having some of the undesired water decisions taken under the 1956
Water Act (RSA, 1956) continuing to apply. This results in frustration among users who would
like the changes stated in the Water Act of 1998 (RSA, 1998b) to be implemented. This delay in
implementing certain aspects of the Water Act of 1998 creates disgruntled water users.
Among the major problems caused by the 1956 Water Act (RSA, 1956) is the inequitable
allocation of water. Such inequitable allocations results in certain areas such as most rural
communities and some uses being under-supplied while other areas and uses have more water
than they need. Some of these inequitable allocations continue to apply even though there is a
new Water Act of 1998 in place (RSA, 1998b) and this result in some communities lacking water
for household use while others have the resource for luxury consumption.
Unfortunately, there is not much information on household water supply in the study area, more
so for rural households. In some cases there may be information but that is mostly outdated
information as new water schemes are developed annually. Some water taps are often dry due to
shortage of supply from the storage while some reticulation systems with abundant supply from
storage are non-operational due to poor maintenance. Estimation of water supply to the
households based on availability of infrastructure may therefore be misleading. eWith this dearth
of information on water supply to households in the study area, the study included an
investigation of household water supply with a focus on rural households.
1.3.3 Environment
Rainfall and evapotranspiration are the major factors of the environment that influence the
availability of water resources in an area and are therefore the focus for this discussion.
11
(a) Rainfall
Rainfall is the fundamental driving force and pulsar input behind most hydrological processes
(Schulze, 1995). The rainfall of Limpopo Province is highly variable from one place to another
and this has led to a climate that is semi-arid in some parts and sub-humid in other parts of the
province. The rainfall of the study area was calculated based on the rainfall figures of the ten
municipalities selected for the study (Table 1.1) obtained from the South African Weather
Services (SAWS, undated) for weather stations located in those municipalities.
Table 1.1 Mean monthly rainfall (mm) distribution of sampled municipalities in the study area
(SAWS, undated)
Municipalities in WMAs and their mean monthly rainfall (MMR)
LimpopoWMA Luvuvhu-Letaba WMA
Month 0 ~ ~= bJ) ~ MMR"~0 ~ ~ ~ ~.c 'r= =;; ~ ~ ~= .
~ ~=
.~.c.. e ~= =~ -
~;
~~ ~=
.c ~ .. ....
~Q, 0
~
bJ) ~
~ "0 -0( .J .=
::! ~ .~
c NEo< c ~=.J ~ Eo<
Jan 134 58 76 82 109 185 74 131 115 93 106
Feb 157 57 78 60 79 184 108 147 119 105 109
Mar 109 39 56 52 51 120 75 115 70 58 75
Apr 40 27 21 33 30 54 47 42 30 26 35
May 20 10 3 11 9 18 15 17 15 Il 13
Jun 11 4 . 8 5 3 9 17 11 2 6 8
Jul 11 1 3 3 6 8 14 10 7 7 7
Aug 11 1 4 6 3 9 Il 11 5 8 7
Sep 28 12 10 17 12 17 39 17 25 19 20
Oct 71 24 43 43 44 53 93 66 37 33 51
Nov 93 49 53 85 88 96 76 87 76 60 76
Dec 122 57 80 81 87 150 128 109 86 91 99
MAP 807 339 435 478 519 902 697 762 588 515 604
516 693 604
12
As shown in Table 1.1, more rainfall is received during summer months and less is received
during winter months. The rainfall season begins in spring with an average across the area of
20mm in September where three municipalities recorded> 25mm. By October the rainy season
has begun and all stations are receiving more than 50mm on average with Thulamela recording
the highest monthly rainfall of 93mm. The mean across the area increased through November
(76mm) and December (99mm) with January and February representing the peak rainy months
with more than 100mm each. Thereafter the mean rainfall across the area declines through
March (74mm), April (35mm), May (13mm), June (8mm), and then July and August are the
months with the lowest rainfall of 7 mm each.
Considering the municipal mean annual rainfall (MAP in mm per annum), Letaba (902mm) >
Makhado (807) > Tzaneen (762) > Thulamela (697mm) > Giyani (588) > Aganang (519) >
Mutale (514.9) > Polokwane (478) > Lephalale (435) > Musina (339). Generally, the
municipalities in the Luvuvhu-Letaba WMA have higher MAP (all> 500 mm) than those in the
Limpopo WMA where three have MAP<500 mm. The average MAP for the Limpopo WMA
was 516 mm while that of the Luvuvhu-Letaba WMA was 693mm. The average rainfall of the
province is estimated at 500 - 600mm per annum which is low compared to the world average of
860mm per annum (DWAF, 2004a). With this rainfall pattern, the question is how much water is
actually available for use in the study area?
(b) Evapotranspiration
Evapotranspiration (ET) is the major loss of water from a hydrologic system (Schulze, 1995).
Methods of estimating ET include evaporation pans, monitoring soil water under controlled
conditions, and applying known rates of potential ET to an area based on its land use and
vegetative cover (Webb, 2005). The ET of the study area was calculated based on the ET figures
of the ten study municipalities based on ET data obtained from the SAWS (undated) for weather
stations located in those municipalities (Table 1.2).
13
Table 1.2 Mean monthly evapotranspiration (ET mm) of sampled municipalities in the study
area (SAWS, undated)
Municipalities
LimpopoWMA Luvuvhu-Letaba WMA
Month ~~ c ~0 ~ Q:j Mean ET"~0 ~ ~
OIl
~ c ~ ë ~c.c .;c;; ~ ~ ~
~
~ .c e ~c
.Q ~ ~ c -
~ = C- ..~... = ~c .~.... ...
;..
OIl
~ ~ ~ '0 < ~ .c tool...:l ~ ...:l E-o E-o G ~=
Jan 175 166 155 161 157 132 158 133 150 161 155
Feb 146 144 130 153 136 112 133 112 127 136 133
Mar 141 140 129 149 133 105 132 123 124 BO 131
Apr III III 108 108 III 86 107 86 96 108 103
May 93 96 84 92 92 70 93 73 84 88 86
Jun 75 78 77 78 81 60 83 60 72 74 74
Jul 82 84 84 85 88 65 85 65 74 82 80
Aug 110 107 113 107 113 81 109 81 93 104 102
Sep 143 126 144 134 141 99 137 101 120 122 126
Oct 163 154 163 164 169 118 152 118 141 152 149
Nov 164 162 165 161 168 120 155 120 143 153 151
Dec 171 167 166 161 171 129 160 129 147 166 157
1572 1534 1517 1552 1559 1176 1501 1199 1372 1475 1446
Annual ET
1547 1345
As shown in Table 1.2, ET is generally lower during the winter months of May to July where the
mean monthly ET ranged between 74mm and 86mm. The ET is higher during summer months of
November to January with mean monthly ET ranging between 151mm and 157mm. The study
area losses more water through ET during summer months despite this being the season in which
more rainfall is received.
Considering municipal ET (mm per annum), Makhado (1572.3mm) > Aganang (1559.1) >
Polokwane (1551.8) > Musina (1534.2) > Lephalale (1516.5) > Thulamela (1501.2) > Mutale
(1475.3) > Giyani (1371.7) > Tzaneen (1198.8) > Letaba (1175.6). The five municipalities with
higher ET are from Limpopo WMA while those with lower ET are from Luvuvhu-Letaba WMA.
14
As a result, the Limpopo WMA has a higher average annual ET (1546.8) than the Luvuvhu-
Letaba WMA (1344.5mm). The ET for the Limpopo Province is generally high having a
negative influence on water resource availability; the question remains how much water is
actually available for use in the study area.
(c) Water supply situation
Despite all the river catchments and the rainfall and ET patterns as described above, Limpopo is
a water scarce province. As alluded to by Molden et al. (2002) the shortage of water in the
province is a result of physical scarcity of the resource. The scarcity was affirmed by RSA
(2003) statement that the province is one of those depending on other areas for water supplies
and by OTP (2009) who revealed that the scarcity of the resource is a major constraint for
development. The scarcity of water in the province has constrained supplies to different users
and is a major problem.
The scarce supply of water in the Limpopo Province has necessitated this study. The rest of
;;:South Africa experiences a physical scarcity of the water resource to some extent, but little can
be done to change this type of scarcity in the province. The water supply of the province may be
improved through management interventions that promote resource storage and efficient use, and
such interventions require water service organisations with relevant capacity. 'n was therefore
necessary for the study to identify water service organisations and to assess their capacity to
address water sector challenges.
1.4 Purpose of the study
The above description of the Limpopo Province was based on 'real-life' issues that prevail in the
area with some highlights of information gaps (a - f) that may be influencing the water sector
negatively. These information gaps constitute 'real-life' problems of the water sector in the area
and were used to inform the definition of the purpose of the study (Mouton, 2001).
15
As guided by Mouton (2001), reflection about the macro-environment of the study area and its
'real-life' problems was done in a non-scientific manner, and therefore a more rigorous and
systematic reflection was necessary to formulate the research objectives. It was subsequent to
this rigorous and systemic reflection that the research objectives were presented alongside the
real-life problems identified when describing the macro-environment of the study area (Table
1.3).
Table 1.3 Real-life problems of the water sector in Limpopo Province and corresponding
research objectives to address them
Level Real-life problem Research objective
Specific • ... planners should know the quantity of water that To determine the prospects for developing
1 can be stored in existing dams and the amount that water storage through analysis of runoff and
could remain available for future storage ... storage capacity of river catchments and
municipalities
Specific D There is a lack of information about water To conduct an inquiry on the perceptions of
2 managers knowledge of the water resources ... municipal water managers on water resources,
uses and restrictions
Specific C Need focussed investigation of the existing To investigate municipal water managers
3 stakeholders and their level of participation In perceptions of stakeholder participation and
resource management decisions. influence on water management decisions
Specific o It is not clear whether the Middle Letaba Dam will To investigate the influence of rainfall on
4 ever fill up to its capacity and allow for increased water gain and loss from the Middle Letaba
supply of water ... Dam
Specific e ... lack of information on water supply to rural To investigate the water supply and
5 households in the study area ... requirements of rural households in the study
area
Ultimate f ...It was necessary to identify water service To develop a water management decision
organisations and to assess their capacity to address model informed by the challenges and
water sector challenges. opportunities revealed by focussed
investigations listed above.
1.5 Summary
This chapter presented the study foundation focusing on the overview of the national water
resources, description of the study area (geographic, socio-economic and environmental), and the
purpose of the study. The study posits that there are 'real-life' issues that prevail in the area with
some highlight of information gaps that may be influencing the water sector rather negatively.
These information gaps constitute 'real-life' problems of the water sector in the area and
informed the definition of the purpose of the study. The research objectives were presented
16
alongside the real-life problems identified when describing the macro-environment of the study
area.
1.6 Outline of the thesis
The study objectives cover thematic issues of water resource, resource management, household
water supply and requirement, and finally the development of a water management decision
model (Table 1.3). The outline of the thesis inclusive of specific chapters based on the research
objectives is as follows:
Chapter One (which is this chapter) is introductory and presents: (1) chapter introduction; (2)
overview of national water resources; (3) description of the study area (geographic, socio-
economic and environmental); (4) purpose of the study; and (5) summary and (6) outline of the
thesis.
Chapter Two discusses the design and methods used in conducting the research. The discussion
includes: (1) orientation and planning of the study; (2) the design of survey questionnaires; (3)
sample frame and sampling procedure; (4) collection of data; (5) data analysis; (6) restrictions of
the study; (7) time schedule; (8) description of the study area.
Chapter Three discusses the literature review with a focus on: (1) mathematical models; (2)
social models; and (3) experiences of using the congruence model.
Chapter Four discusses runoff and storage capacity of catchment and municipalities in the
study area. The discussion focuses on: (1) introduction of the concepts runoff and storage
capacity; (2) study methods with special attention given to (a) description of the study area, (b)
sample frame and sampling procedure and (c) data collection and analysis; and (3) results and
their discussion with a focus on (a) runoff and storage capacity of river catchments and (b) runoff
and storage capacity of municipalities; and (4) conclusions.
17
Chapter Five discusses rainfall influence on water gain and loss from Middle Letaba Darn with
major topics discussed being: (1) introduction of concepts of water gain and loss by reservoirs;
(2) research methods with a focus on (a) darn location and physical characteristics, (b) sampling
procedure and (c) data collection and analysis; and (3) results and their discussion under major
topics on (a) rainfall received over the surface area of the dam, (b) the influence of rainfall on
inflow from source river, (c) rainfall influence on evaporation from the dam surface, (d) the
influence of rainfall on outflow from the dam and (e) rainfall and dam water storage volume; and
(4) conclusions.
Chapter Six discusses the perceptions of municipal water managers on water resources, uses and
restrictions. The specific topics covered by the discussions were: (1) introductions of the
concepts water resources, uses and restrictions; (2) study methods with a focus on: (a) area
covered by the study, (b) sample frame and sampling procedure and (c) data collection and
analysis; (3) results and discussion with particular attention on: (a) perceptions on municipal
water resources, (b) perceptions on water uses, (c) perceptions on water restrictions; and (4)
conclusions.
Chapter Seven discusses stakeholder participation and their influence in water management
decisions as perceived by local municipal water managers. Specific issues discussed included:
(1) introduction of the concepts stakeholders and stakeholder participation; (2) research methods
with a focus on (a) description of the area covered by the study, (b) sample frame and sampling
procedure and (c) data collection and analysis; (3) results and their discussion under the sub-
headings: (a) stakeholder organisations and their roles, (b) stakeholder participation in water
management decisions and (c) stakeholder influence on water management decisions; and (4)
conclusions.
Chapter Eight discusses water supplies and uses by households in the study area. The topics
covered by the discussions were: (1) introduction of household water supply and uses; (2)
research methods focusing on (a) description of the area covered by the study (b) sample frame
18
and sampling procedure and (c) data collection and analysis; (3) results and discussion with a
focus on (a) characterization of the households, (b) household water supplies, (c) household
water uses and (d) household rating of the water services; and (4) conclusions.
Chapter Nine analyses the water sector challenges and research conclusions of chapter three to
eight and accordingly proposes a water management decision model to address these challenges.
The discussions of this chapter focussed on: (1) introduction highlighting the water sector
challenges; (2) study methods with special attention on (a) description of the Congruence Model
as a framework of a proposed water management decision model, (b) sample frame and sampling
procedure, (c) description of study area and (d) data collection and analysis; (3) results and their
discussion with special attention on (a) input components and their influence on water sector, (b)
major challenges faced by the water sector, (b) organisational strategies and their congruence
with water sector challenges, (c) transformation components and their congruence with water
sector challenges, (d) congruence flow analysis and proposed capacity improvement and (e)
proposed water management decision model adapted from the Congruence Model.
Chapter Ten provides a highlight of the main findings and their implications for policy. These
were followed by policy recommendations for (1) catchment runoff and storage capacity, (2)
dam hydrology, (3) water managers' knowledge of the resource and its uses, (4) stakeholder
participation in water decision making, (5) household water supply and requirement, and (6)
water management decision model.
1.7 Publication of research work
It must be noted that several of the chapters of this study were written in the form of self-
contained published scientific articles (chapters 4 to 9). The scientific publications that arise
from this study are as follows:
19
Chapter 4: Runoff and storage capacity of municipalities and rivers of Limpopo and
Luvuvhu-Letaba WMA of South Africa - Abstract was published in Proceedings of the 10th
WaterNet/WARFSA/GWP Symposium in Entebbe, Uganda, in 2009.
Chapter 5: Rainfall influence on water gain and loss from Middle Letaba Dam in Luvuvhu-
Letaba WMA - Abstract was published in Proceedings of the 11th WaterNet/WARFSA/GWP
Symposium in Victoria Falls, Zimbabwe, in 2010. Full text was published in the International
Journalof Applied Science and Technology, 2(3): 24-33.
Chapter 6: Perceptions of rural municipal water managers on water resources, uses and
restrictions - Abstract was published in Proceedings of the io' WaterNet/WARFSA/G WP
Symposium in Entebbe, Uganda in 2009. Full text was published in the International Journal of
Business and Social Science, 3(5): 8-20.
Chapter 7: Perceptions of rural municipal water managers on stakeholder participation in
water issues in Limpopo and Luvuvhu-Letaba WMAs - Abstract was published in Proceedings
of the 10th WaterNet/WARFSA/GWP Symposium in Entebbe, Uganda in 2009. Full text was
published in the American International Journal of Contemporary Research, 2(9):26-37
Chapter 8: Household water supply and uses by rural households in the Limpopo Province of
South Africa - Abstract was published in Proceedings of the CTA Annual Seminar in
Johannesburg, South Africa in 2010. Full text was published in the International Journal of
Business and Social Science, 3(3): 37-49.
Chapter 9: Challenge and capacity congruence analysis for development of a water
management decision model - Accepted for full text publication in the American International
Journal of Contemporary Research, Vol. 2 No. 10 (scheduled to be published on 10 December
2012).
20
CHAPTER2
2 RESEARCH METHODOLOGY
2.1 Introduction
This chapter discusses the research methods followed in conducting the study to achieve the
objectives outlined in Chapter 1. The choice of the methods was determined by the commitment
to generate truthful knowledge as this is the overriding goal of science (Mouton, 1996). The
quest for truth in this research has made choice of the correct methodology very important.
The study used available knowledge from various disciplines to produce relevant scientific
knowledge to address water sector problems in the Limpopo Province. It was therefore regarded
important to provide some description of 'knowledge' in general and 'scientific knowledge' in
particular. The different types of knowledge obtainable in the study area define the context of the
study and hence their proper description provides guidance for selection of the most suitable
research methods.
2.2 Description of knowledge
The description of knowledge focused on the kinds of knowledge and some highlights of
scientific knowledge.
2.2.1 Kinds of knowledge
There are three kinds of knowledge, namely: (1) folk or lay knowledge, (2) scientific knowledge
and (3) meta-scientific knowledge (Mouton, 1996; Mouton, 2001). Lay knowledge is obtained
from sources such as authority, opinions of peers, traditions, debating, and accidental
observations (Welman et al., 2005) and is acquired through learning, experience and self-
reflection and enables us to live a human life (Mouton, 1996).
21
In order to generate scientific knowledge, scientists make phenomena (politics, economics, etc.)
of folk knowledge objects of systematic and rigorous inquiry and investigation with the goal of
searching for truth (Mouton, 1996; Leedy and Ormrod, 2010). The essence of research
methodology in searching for truth was highlighted by Welman et al. (2005) who argued that the
scientific approach is concerned with the way in which findings are acquired.
Meta-scientific knowledge on the other hand covers reflections on the nature and dynamics of
scientific knowledge, and this has led to the development of disciplines such as philosophy of
science and research methodology. Meta-science makes scientific knowledge an object of critical
inquiry and reflection with the purpose of dissecting, deconstructing or analysing what scientists
do toward the ultimate improvement of science (Mouton, 1996).
From the above discussion, folk knowledge serves as data (objects) for analysis and
interpretation to generate scientific knowledge. At a different level, scientific knowledge also
serves as data for higher level analysis and interpretation referred to as 'reflection' to generate
updated scientific knowledge. Through their different levels of data analysis and interpretation,
both the scientific and the meta-scientific processes generate scientific knowledge with the
scientific process using folk knowledge as its data while the meta-scientific process uses
scientific knowledge as its data.
This study used all the three kinds of knowledge. Folk knowledge included the secondary data
mostly on climate and hydrological issues obtained from reports of the Department of Water
Affairs (DWA) (chapters 4 and 5) and those of different water service organisations (Chapter
9). The folk knowledge was also in the form of perceptions of respondents to interview
questions. The respondent perceptions were recorded in chapters where information was
collected through interviews (chapters 6 to 8).
Also, folk knowledge was recorded from meetings with officers of different institutions involved
in the water sector, and those included the Department of Water Affairs (DWA), Limpopo
22
Department of Agriculture (LDA) and different municipalities (chapters 4 to 9). Discussions
were conducted with peer researchers at water conferences where some of the chapters were
presented as research articles and some folk knowledge was recorded. Scientific knowledge was
mainly collected through literature study where relevant scientific documents served as sources
of the information.
The study subjected the collected folk knowledge to a systematic and rigorous inquiry (scientific
process) to generate new scientific knowledge (Mouton, 1996; Leedy and ,Ormrod, 2010). In
addition to folk knowledge, the research also collected existing scientific knowledge and this was
mainly through literature. The existing scientific knowledge was subjected to critical inquiry and
reflection (meta-scientific process) to generate updated (meta-) scientific knowledge. The
updated scientific knowledge consisted of scientific statements that were upheld after the critical
inquiry and reflection as well as those amended after rejection of the original statement. The use
of all the three types of knowledge in this research project was necessary to have appropriate
information for development of a water management decision model.
2.2.2 Scientific knowledge
The rationale for this study was to subject both folk knowledge and existing scientific knowledge
to systematic and rigorous inquiry and reflection to generate new valid scientific knowledge
relevant to address the water challenges in the study area. In-depth understanding of the nature of
scientific knowledge was necessary for correct methodology to be used to generate the
knowledge and for it to be properly used to solve problems.
Scientific knowledge was described as a 'house of science' with the foundation built of factual
statements that are easily verifiable and seemingly irrefutable and the walls built of statements
that are difficult to verify (Mouton, 1996). The easily verifiable statements are those that are
objective and are often quantitative while those that are difficult to verify are subjective and are
often qualitative. These different types of statements (quantitative and qualitative) informed the
research approaches used and were discussed more under section 2.3.
23
In the same way that a house needs both the foundation and walls, scientific knowledge requires
both the easily verifiable statements and those that are difficult to verify. As stated by Mouton
(1996), the description of scientific knowledge as the house of science regards science as a
phenomenon that progresses slowly but surely as additional bricks become more cemented.
These additional bricks would be the new statements that are easily verifiable for the foundation
and those that are difficult to verify for the walls of the house of science.
In addition to being described as a house (of science), scientific knowledge was also described as
something that evolves, suggesting that it changes over time. In the cause of evolution, the
scientific statements that withstand attempts at rejection emerge stronger and are accepted as part
of the body of knowledge. The acceptance is always provisional until attempts at falsification
succeed (Mouton, 1996; Terre Blanche et al., 2009). The upholding and rejection of scientific
statements occur as a result of the critical inquiry and reflection on existing scientific knowledge
which in this study was mostly collected through literature survey.
The fact that scientific knowledge is only accepted provisionally results in the history of science
being comprised of a period of normal science where a particular research paradigm (or
tradition) dominates followed by a scientific revolution when the dominant paradigm is rejected,
and this results in scientific knowledge consisting of sets of paradigms (Mouton, 1996). While
this study made reference to knowledge from previous research work, it never regarded such
knowledge to be the final truth (Walsham, 1995) as this would uphold the knowledge even when
it should be rejected. Regarding existing scientific knowledge as the final truth limits the
possibility of such knowledge being subjected to meta-scientific activities of analyses, dissection
and deconstruction (Mouton, 1996) and the opportunity for ushering in new paradigms.
The two components of scientific knowledge (verifiable vs non-verifiable) are mutually inclusive
and complementary and hence this study adopted both of them in its attempt to contribute to the
generation of knowledge for addressing water sector challenges in the Limpopo Province. By
subjecting existing folk and scientific knowledge to (meta-) scientific processes of systematic
24
and rigorous inquiry and reflection, the study aimed to generate new scientific knowledge that
will introduce new thinking in the water sector. The new knowledge should remain relevant not
only spatially for the areas with similar socio-economic and hydrologic environment, but also
temporally for the times when such hydrologic and socio-economic environment occurs. When
such spatial or temporal relevance is lost, application of the knowledge and the subsequent water
management decision model will inevitably also be lost to the historic sets of paradigms of
scientific knowledge.
2.3 Research approach
The description of knowledge and the focussed description of scientific knowledge provided the
context for selection of relevant research methods used in this study. Selection of relevant
research methods was critical to produce credible knowledge to solve water sector problems in
the Limpopo Province. Before considering specific research methods, it was considered
necessary to select appropriate research approaches for the context described by the different
kinds of available knowledge in order to generate truthful knowledge worthy to fulfil the
epistemie interest of this scientific study.
2.3.1 Main approaches
There are two main approaches to research, the positivist and the anti-positivist approach
(Welman et al., 2005). The positivist is also known as the quantitative approach and underlies
the natural-scientific method in human behavioural research. According to the positivist
approach, research must be limited to what we can observe and measure objectively, i.e. that
which exists independently of the feelings and opinions of individuals (Welman et al., 2005).
Anti-positivists are also known as qualitative researchers and share a resistance to upholding the
natural-scientific method as the norm in human behavioural research (Welman et al., 2005). For
the purpose of simplicity, the two approaches were referred to in this study as the quantitative
and qualitative approaches.
25
The quantitative approach emphasizes the measurement and analysis of causal relationships
between variables (Denzin and Lincoln, 1994). This emphasis on measurement was upheld by
Leedy and Ormrod (2010) who indicated that the approach quantifies behaviour in terms of such
things as number of occurrence and ratings for accuracy or other dimensions.
The qualitative approach on the other hand emphasizes on processes and meanings that are not
measured in terms of quantity, intensity or frequency (Denzin and Lincoln, 1994). This was
supported by Leedy and Ormrod (2010) who described qualitative research as an approach that
considers characteristics or qualities that cannot easily be reduced to numerical values.
The decision of whether this research study should adopt a quantitative or qualitative approach or
both necessitated deep insight on these approaches. Important aspects for guiding the selection of
an approach included the purpose and nature of research and data description, collection and
analysis (Table 2.1).
Table 2.1 Comparison of quantitative and qualitative research approaches (Leedy and Ormrod,
2010)
Aspect of Quantitative Qualitative
comparison
Purpose of research • To test theory • To build theory
Nature of research • Somewhat context-free • Context-boundprocess • Detached view • Personal view
Data description • Numerical data • Textual, image based data
and collection • Large representative sample • Small informative samples
• Standardized instruments • Loosely structured interviews
Data analysis • Statistical analysis • Search for themes and categories
• Stress on objectivity • Subjective with potential bias
As shown in Table 2.1, the quantitative and qualitative research approaches contradict each other
in all the aspects of comparison. Choice of the research approach for the current study had to
consider these opposing views of the two approaches on the four aspects. The study included
investigations using each of the two approaches and is therefore regarded as using a mixed
approach.
26
2.3.2 Rationale for a mixed approach
Having gained more insight from the companson of quantitative with qualitative research
approaches by Leedy and Ormrod (2010), the attributes of the approaches were matched with the
research objectives (Table 2.2) in order to select the correct approach for each objective. A
research approach was decided for each research objective based on how well the attributes of
the approach matched the statement of the objective.
As shown in Table 2.2, the selected approach for each objective was described as a dominant
approach. This was necessary because the objectives would practically not entirely match one
approach but would include a limited amount of the attributes of the unmatched approach. Itwas
on the basis of the dominant matching attributes that the approach for each objective was
selected.
Table 2.2 Research objectives and matching attributes of research approaches
Research objective Major attributes Dominant
approach
1. To determine the prospects for developing water • To test theory Quantitative
storage through analysis of amount of runoff and • Numerical data
storage capacity of river catchments and • Statistical analysis
municipalities • Stress on objectivi!Y_
2. To investigate the influence of rainfall on water • To test theory Quantitative
gain and loss from the Middle Letaba Dam • Numerical data
• Statistical analysis
• Stress on obj_ectivi!Y_
3. To conduct an inquiry on the perceptions of • To build theory Qualitative
municipal water managers on water resources, uses • Textual data
and restrictions • Loose structured interview
4. To investigate municipal water managers • To build theory Qualitative
perceptions of stakeholder participation and • Textual data
influence on water management decisions • Loose structured interview
5. To investigate the amount of water supply and • To test theory Quantitative
requirements of rural households in the study area • Numerical data
• Statistical analysis
• Stress on objectivi!Y_
6. To develop a water management decision model • To build theory Qualitative
informed by the challenges and opportunities • Textual data
revealed by focussed investigations listed above. • Search for themes Subj_ective
27
As shown in Table 2.2, the quantitative and qualitative research approach was each selected for
three of the study objectives. The study will therefore use both research approaches. According
to Hurmerinta-Peltomaki and Nummela (2006), this study that uses both quantitative and
qualitative approaches is referred to as a mixed study.
2.4 Research design
To develop a credible 'research design', it was important for the concept to be defined. A
'research design' is a set of guidelines and instructions to be followed in addressing the research
problem (Weiman et al., 2005). The research design provides the overall structure for the
procedures the researcher follows, the data collected and the data analysis conducted (Leedy and
Ormrod, 2010). In simpler terms, the research design is like a route planner; it is a set of
guidelines and instructions on how to reach the goal of the research (Mouton, 1996; Mouton,
2001). According to Mouton (1996) the rationale for a research design is to plan and structure a
research project in such a way that the validity of the research findings is maximized through
minimising or eliminating errors.
Development of an appropriate research design for this study necessitated a guiding framework.
A comprehensive framework was developed by Mouton (2001) and includes factors such as
design classification, type of sampling, data collection and data analysis and interpretation. The
research designs for the different chapters of this thesis were developed based on these factors
(Table 2.3). The development of chapter based research designs was necessitated by the fact that
each chapter is based on a specific research objective with a dominant research approach (Table
2.2).
The design classification used for the current chapter (Chapter 2) was non-empirical and
entailed the use of secondary textual data (Table 2.3). The decision to classify the design of this
chapter as non-empirical was informed by the fact that the units of analysis were mainly objects
in the world of science and not those in the world of everyday life (Mouton, 1996).
28
Table 2.3 Research designs for different chapters included in the study
Chapter Desig_n classification Type of sampling Data collection Analysis & interpretation
2.Research Non-empirical, Non-probability, Existing Qualitative analysis with
methodology secondary, textual study documents literature and subjective interpretation
data and texts selected stakeholder
based on consultation
theoretical
considerations
3.Literature Non-empirical, Non-probability, Existing Qualitative analysis with
review secondary textual or documents and literature subjective interpretation
numerical data texts selected collection based
based on on main themes
theoretical
considerations
~.Building new Empirical, secondary, Random Existing data Statistical analysis with
dams through numerical data (probability) obtained mainly objective interpretation
analysis of runoff sampling from DWA
& storage
capacity
5.Rainfall Empirical, Purposive (non- Existing data Statistical analysis with
influence on water secondary, numerical probability) obtained mainly objective interpretation
gain and loss data sampling from DWA
6. Municipal Empirical, primary, Random Respondent Qualitative analysis with
manager textual data (probability) interviews using subjective interpretation
perceptions on sampling semi-structured
water resources questionnaire
7. Municipal Empirical, primary, Random Respondent Qualitative analysis with
manager textual data (probability) interviews using subjective interpretation
perceptions on sampling semi-structured
stakeholder questionnaire
j>_articipation
8.Water supply & Empirical, primary, Random Respondent Statistical analysis with
requirements of textual & numerical (probability) interviews using objective interpretation
household data sampling semi-structured
questionnaire
9:Water Empirical, secondary, Purposive (non- Existing strat- Qualitative analysis with
management textual data probability) egic plans and subjective interpretation
decision model sampling annual reports
of selected
organisations
As shown in Table 2.3, the chapter was based on secondary textual data. The chapter presented
mainly non-probability sampling where the study methods were selected based on their
attributes. In non-probability sampling the researcher has no way of guaranteeing that each
element of the population will be represented in the sample (Leedy and Ormrod, 2010). The data
29
used in the chapter is mainly from literature. Data analysis is qualitative and the interpretation
highly subjective.
Qualitative analysis of data was described by Creswell (1998) who revealed that the process
entails: (1) organizing the data where large bodies of text are broken into smaller units; (2)
perusing the entire data set several times to have a sense of what it contains as a whole and to
note major categories; (3) identifying general categories or themes and classifying them
accordingly; and (4) integrating and summarising the data, a step that may include description of
relationships among categories. These guidelines were followed in conducting the qualitative
analysis of the data.
Chapter 3 is on literature review which used scientific knowledge in the form of literature as the
object of analysis and therefore the design was also non-empirical with secondary data that was
mainly textual. Non-probability sampling was again used where documents and texts were
selected based on theoretical considerations. Data was in the form of existing literature and was
analysed qualitatively with subjective interpretations.
As shown in Table 2.3, the research design used in chapters 4 and 5 was empirical and used
secondary data that was mainly numerical. The secondary data was composed of unpublished
reports mainly from the Department of Water Affairs (DWA) that provided statistics of issues
such as catchment runoffs, dam storage capacity and the hydrological factors of water gain and
loss from the Middle Letaba Dam. While Chapter 4 used random (probability) sampling to
select the study units, Chapter 5 used purposive (non-probability) sampling (Leedy and Ormrod,
2010). The data for both chapters were analysed statistically with objective interpretations.
Statistical analysis involved the use of statistical calculations to analyse numerical data in order
to establish the meaning beneath the numbers.
The designs used in Chapters 6 to 8 were classified as empirical where primary mainly textual
data was used for Chapters 6 and 7 with both textual and numerical data used for Chapter 8.
30
Study units for these three chapters were selected using random (probability) sampling and data
was collected using semi-structured questionnaires. The data was analysed using qualitative
methods and interpreted subjectively for chapters 6 and 7 while mixed (qualitative and
statistical) analysis was used for Chapter 8. The research design for Chapter 9 was also
empirical with secondary textual data. Sampling was purposive (non-probabilistic) and the data
was in the form of strategic plans and annual reports of selected water service organisations.
Data analysis was through qualitative methods where interpretation was subjective.
2.5 Research methods
The concept of 'research method' refers to the techniques used to collect and analyse data. As a
result, the method to be used for a particular research problem must always take into account the
nature of the data that will be collected in the resolution of the problem (Leedy and Ormrod,
2010). With the adoption of a mixed research approach and multiple designs, the study also used
multiple methods. The use of multiple methods was advocated for on literature on social science
(Kock, 2002; Yoong and Pauleen, 2004; and Dick, 2006) and therefore the concept is not
unusual. The different methods used in this study were literature review, secondary data
analysis, survey method and content analysis.
2.5.1 Literature review methods
Literature reviews are studies that provide an overview of literature in a certain discipline
through an analysis of trends and debates. The importance of literature review is that it provides
lessons from other researchers on (l) how they have theorised and conceptualized on issues, (2)
what they have found empirically-and (3) what instrumentation they have used and to what effect
(Mouton,2001).
A review of literature is essentially an exercise where the researcher works from a 'sample' of
texts that he / she reads in order to come to a proper understanding of a specific domain of
knowledge. As a result, the sources of the literature must be representative to achieve good
quality review (Mouton, 2001). A comprehensive and well-integrated literature review provides
31
a good understanding of the issues and debates in the area of study, current theoretical thinking
and definitions, as well as previous studies and their results.
A literature review can, at best, only summarise and organize the existing knowledge. Even a
critical review of the literature cannot produce new, or validate existing empirical insights.
Although literature reviews often lead to theoretical insights, we still need to undertake an
empirical study to test our new insights.
In this study, Chapter 3 was dedicated to literature review and therefore discussion of the broad
review of the literature was done in this chapter. Each of the subsequent chapters was presented
as an independent research paper and hence chapter specific literature reviews were presented. In
conducting the literature review, much attention was given to most recent sources. This was
necessary to capture the latest research findings. Also, the literature review attempted to treat the
authors fairly by providing each of them an opportunity to be assessed without pre-set
interpretation. The review was organized according to themes so as to address the research
objective to be achieved.
2.5.2 Secondary data analyses
Secondary data analyses aim at re-analysing existing data in order to test hypotheses or to
validate models. The type of data used in this method is mostly quantitative and therefore
quantitative analyses are mostly used. The strength of this method is that it saves on time and
costs because of the use of existing data or the possibility of re-analysing previous findings. The
limitation is that secondary data analysts are not able to control for data collection errors and are
constrained in analysis by original objectives of the research (Mouton, 2001).
This study used secondary data analysis in Chapter 4 which focusses on runoff and storage
capacity of catchment and municipalities in the study area and in Chapter 5 which discusses
rainfall influence on water gain and loss from Middle Letaba Dam. In both chapters the
secondary data was numerical and was obtained from the DWA.
32
2.5.3 Survey methods
The survey methods entail the researcher collecting data by posing a series of questions to
willing participants after whom he/she summarises the responses with percentages, frequency
counts, or more sophisticated statistical indexes. The researcher then draws inferences about a
particular population from the responses of the sample (Leedy and Ormrod, 2010). This method
allows respondents to tell the researcher what they believe to be true and sometimes what they
think the researcher wants to hear and this may not have been thought until the researcher posed
the question (Schwarz, 1999). As stated by Leedy and Ormrod (2010), the survey research
typically uses a face-to-face interview, a telephone interview or a written questionnaire.
In this research project, a survey method was used to collect data for perceptions of municipal
water managers on water resources, uses and restrictions (Chapter 6) and on stakeholder
participation and their influence on water management decisions (Chapter 7) and to collect data
for water supplies and uses by households in the study area (Chapter 8). Relevant questionnaires
were developed for collecting data to address specific research objectives. The questionnaires
included both closed-ended and open-ended questions and were piloted and accordingly
amended to ensure correct and accurate data was collected.
The sample frames were defined and representative samples were drawn using relevant sampling
procedures. The extent of trustworthiness of the results was informed by the degree of
representativeness of the samples (WeIman et al., 2005). Where necessary, multi stage sampling
was conducted as described by Leedy and Ormrod (2010) and involved selection of such units as
WMAs (primary units), municipalities (secondary units), villages (tertiary) and households
(quaternary units). As highlighted in the focus chapters, combinations of purposive and random
sampling were used.
The researcher personally collected the data for chapters 6 and 7 where smaller samples were
used and trained enumerators to collect the data for chapter 8 which had a larger sample. The
quantitative data was collected by the closed-ended questions while the open-ended questions
33
recorded qualitative data (Leedy and Ormrod, 2010) making these investigations mixed studies
(Hurmerinta-Peltomaki and Nummela, 2006). The data was analysed using the SAS Package
(SAS Institute Inc, 2009). The Proe FREQ of SAS was used to generate simple frequency tables
for each variable of interest. Selected data was summarized in Excel Spreadsheet.
2.5.4 Content analyses
Content analyses studies analyse the content of texts or documents. 'Content' refers to words,
meanings, pictures, symbols, themes or any message that can be communicated. The analysis of
the texts and documents is a non-reactive method and therefore errors associated with interaction
between the researchers and subjects are avoided. Limitations in authenticity of data sources and
representativeness of texts analysed may influence the validity of the findings negatively
(Mouton, 2001).
Data collection in content analysis entails: (1) identification of the specific body of material to be
studied; (2) definition of the characteristics or qualities to be examined; (3) breaking down of
lengthy complex material into small, manageable segments that are analysed separately; and (4)
scrutiny of the material for instances of each characteristic or quality defined in step 2 (Leedy
and Ormrod, 2010). The analysis of the data entails tabulation of the frequency of each
characteristic found in the material being studied making content analysis both qualitative and
quantitative. In some cases, statistical analysis are performed on the frequencies or percentages
obtained to determine whether significant differences exist.
In the current study, content analysis was used as the main research method in Chapter 9 which
analysed the water sector challenges and planned solutions to inform development of a water
management decision model. The focus for the content analysis was the service organisations of
DWA and three WSAs, the Mopani District Municipality, Vhembe District Municipality and
Polokwane Local Municipality. The body of material was the strategic plan of DWA and the
integrated development plans of the WSAs. The characteristics focused by the investigation
included the strategies for addressing identified problems and the allocation and utilisation of
34
resources in addressing those problems. The analysis focussed on the assessment of the degree of
congruence between the challenges and the strategies and between the strategies and the
resources allocated and those utilized. With the degree of congruence presented as numerical
ratings and some characteristics presented as text, the content analysis was both a quantitative
and qualitative inquiry.
2.6 Elimination of error
This thesis was the culmination of a study in which phenomena from the disciplines of
hydrological and of social sciences were selected and made objects of inquiry. These objects
were subjected to systematic and rigorous inquiry, and hence the study was a scientific research.
The over-riding goal of science is the search for 'truth' or 'truthful knowledge' that is valid and
reliable (Mouton, 1996).
Although it is not possible to produce scientific results that are infallible and 'absolutely' true for
all times and contexts, scientists are motivated to constantly strive for the most truthful and the
most valid results (Mouton, 2001). It is this quest for producing truthful knowledge that
necessitates that errors be minimized if not completely eliminated in research processes.
In order to eliminate errors from the research process, it was necessary to recognise their
occurrence and to know their sources. Each research method has its sources of error and
therefore the discussion of the sources of error and the strategies used to eliminate such errors
was based on the research methods used. As shown in Table 2.4, necessary precautions were
taken to minimize errors in this study. Multiple sources were used for collecting data for some of
the research methods and this assisted in minimizing error.
35
Table 2.4 Main sources of errors for the five research methods used in the study (Mouton, 2001)
and strategies used to eliminate the errors
Research Common sources of error Strategies to eliminate the errors
method
Literature Selectivity in the sources; Selection of literature sources was done according to the main
review unfair treatment of authors; themes covered by the investigation. Each author was assessed
misunderstanding the source; fairly with minimum prejudices. The reviews were well
selective interpretation to suit organized according to themes.
own view point; poor
organisation and integration of
review.
Secondary Contextual analysis; The type of secondary data obtained is hydrological and
data analysis misunderstanding of original numerical and is less affected by context and original object of
objects of the principal principal investigator.
investigator.
Survey Sampling error; questionnaire Both the sampling and questionnaire design was done with
method error; high refusal rates; high guidance of relevant literature and with consultation of
non-response; interviewer experienced researchers. Interviews of municipal managers
effects; respondent effects; were done by researcher and those of households by trained
data capturing error. enumerators with minimal non-response, interviewer and
respondent effects. Data capturing and analysis was done by an
experienced capturer.
Content Selection effects in sampling Texts were cautiously sampled according to pre-determined
analysis texts; lack of information on themes. The texts were from strategic plans and annual reports
intentions or background; for which the researcher is clearly aware of the intention and
limited interpretation of texts background. Additional literature was also studied to broaden
by original authors. the understanding and make up for limited interpretation by
original authors.
The use of multiple methods of data collection was referred to as triangulation and was reported
to increase the reliability of observations (Leedy and Ormrod, 2010). The precautions taken in
this study are important for the epistemie interest of scientific research to be achieved. Although
some errors may have remained, the precautions taken are reasonably sufficient for the results of
the study to be considered credible.
2.7 Research process
The major steps of the research process as used III this study included (1) orientation and
planning, (2) design of survey questionnaires, (3) definition of sample frames and sampling
procedures, (4) data collection, analysis and interpretation, (5) report writing (scientific articles)
and presentation in conferences, (6) publication of the scientific articles and (7) thesis writing.
36
2.7.1 Orientation and planning
The orientation and planning of the study began in 2006 with preliminary interactions with
strategic offices of the Department of Water Affairs and Forestry (DWAF). The interactions
were a result of experiences of frequent water shortages in Thohoyandou were the researcher
stays, and complaints of similar situations in other areas, especially rural areas. The need for
understanding the challenges regarding the supply and uses of water in the province became
more evident when reports came of severe shortages of irrigation water in projects where the
Limpopo Department of Agriculture (LDA) already made huge investments in irrigation
infrastructure.
Interactions with DWAF introduced the researcher to some of the challenges faced by the
department in its initiative to allocate and deliver water to the different use sectors and this
served as a motivation for the researcher to decide to embark on a detailed study of the water
supply and use systems in the Limpopo Province with the intention of developing a resource
management decision model. A comprehensive literature review was conducted in search for
more information about the challenges regarding water supply and uses.
Further discussions were made with a team of academics from the University of the Free State
who visited the province during the same year (2006) to interact with officers of the LDA
wishing to register with the University to further their studies. It was after the discussion with
this team that work commenced to formulate the serious questions regarding the supply and uses
of water into a research proposal. The proposal was thoroughly discussed with Professor Edward
Nesamvuni who was responsible for research and training in the LDA for his inputs, and was
subsequently sent to the University of the Free State for further advice. In 2007 the researcher
registered with the University of the Free State for a Ph.D. Subsequent to this registration, the
university appointed a team of study supervisors who assessed the proposal and guided on issues
for improvement before finally approving it.
37
2.7.2 Design of survey questionnaires
Two survey questionnaires were developed, the first being for interviewing municipal water
managers while the second was for interviewing members of rural households affected by the
water scarcity in the study area. The questionnaire for interviewing municipal water managers
was to collect information on two major areas, one on perceptions of the water managers on
water resources, uses and restrictions (Chapter 6) and the other on stakeholder participation and
influence on resource management decisions (Chapter 7). The questionnaire for the survey of
households, on the other hand was designed to collect data on the socio-economic situation of the
households, their livelihoods and their water supply and uses (Chapter 8).
2.7.3 Sample frame and sampling procedure
(a) The sample frame
Before researchers draw a sample of the population for analysis, they should obtain clarity about
the population, or units of analysis to which their research hypotheses apply, and this involves
compiling a sample frame. A sample frame is a complete list in which each unit of analysis is
mentioned only once (Welman et al., 2005). Unless such a sample frame is borne in mind, it is
impossible to judge the representativeness of the obtained sample properly. The sample should
be representative of the sample frame which ideally is the same as the population (WeIman et al.,
2005).
In this study the sample frame was stratified into five different levels, namely: WMA with their
river catchments, district, municipality, village and household. The sample frame increased in
size from WMAs through districts, municipalities, villages to households. Four WMAs overlay
the Limpopo Province, partially or in full. The WMA fully overlaying the province are the
Limpopo and Luvuvhu-Letaba WMAs while those partially overlaying the province are the
Crocodile West and Marico and the Olifants WMAs making a sample frame of four units of
analysis.
38
The province has five districts, namely: Vhembe, Waterberg, Capricorn, Mopani and
Sekhukhune (Figure 1.2, section 1.3.l(b)) making a sample frame of five units of analysis. As
shown in Figure 1.2, the province has 25 municipalities of which 19 are fully or partially located
in the Limpopo WMA and the Luvuvhu-Letaba WMA. The Limpopo WMA has seven
municipalities fully overlaying it, namely: Musina, Aganang, Lephalale, Blouberg, Molemole,
Mogalakwena, and Modimolle and five municipalities partially overlaying it, namely: Makhado,
Polokwane, Mutale, Mokgopong and Thabazimbi, making a total of twelve municipalities
overlaying this WMA. The Luvuvhu-Letaba WMA has three municipalities fully overlaying it,
namely: Thulamela, Letaba and Giyani, and four municipalities partially overlaying it, namely:
Mutale, Tzaneen, Makhado, and Baphalaborwa, making a total of seven municipalities
overlaying this WMA. The two WMAs were selected for the study and therefore the sample
frame at the level of municipalities was composed of the 19 municipalities fully or partially
located in these WMAs.
A sample frame of villages was developed for three of the municipalities selected for the study
from the Luvuvhu-Letaba WMA. As stated by Welman et al. (2005), this sample frame
comprised of a list of villages in each municipality. The sizes of sample frames of villages for the
study municipalities were 210 for Thulamela, 85 for Giyani, and 118 for Mutale making a total
sample frame of 413 units of analysis.
As for households, the sample frames for the villages selected for the study were 476 for
Muyexe, 521 for Siyandane, 524 for Makosha, 152 for Sigonde, 108 for Makwilidza, 324 for
Lukau, 581 for Djilongo, 389 for Mavunde, 1025 for Dopeni, and 567 for Xigamani, making a
total sample frame of 4667 units of analysis.
(b) Sampling procedure
Probability and non-probability sampling procedures can be distinguished. In probability
sampling the probability that any element or member of the population will be included in the
39
sample can be determined while in non-probability sampling such probability cannot be specified
(WeIman et al., 2005).
As stated by Welman et al. (2005), the advantage of probability sampling is that it enables the
researcher to indicate the probability with which sample results (e.g. means) deviate in differing
degrees from the corresponding population values (e.g. population means). Probability sampling
allows for estimation of sampling error which non-probability sampling cannot do, making non-
probability sampling to be frequently used for reasons of convenience and economy. Examples
of probability samples used in this study were simple random samples and stratified random
samples while those of non-probability samples were purposive samples.
(i) Simple random sampling
Simple random sampling gives each member of the population the same chance of being
included in the sample and each sample of a particular size has the same probability of being
chosen (Welman et al., 2005). As stated by Welman et al. (2005), this type of sampling involves
two steps: (1) identification of all the units of analysis in the sampling frame and assigning them
consecutive numbers and (2) sampling the units of analysis using mechanisms such as a table of
random numbers or a computer program to ensure that each assigned number has an equal
chance of being selected.
Simple random sampling was used in this study to select villages in targeted municipalities and
also to sample households in each village selected for inclusion in the study (Chapter 6). The
process used for sampling of both the villages and households started with the assigning of
numbers to the units of analysis. The numbers were written in small equal pieces of paper. The
papers were put in a basket and this was closed and thoroughly shaken to allow for a good mix of
the pieces of paper. Some people outside the research team were invited to sample, and this was
done by putting a hand in the basket and picking up one piece of paper at a time from the shaken
basket without looking inside the container. The numbers written on each of the selected pieces
of paper were recorded as they represented certain units of analysis.
40
(ii) Stratified random sampling
As stated by WeIman et al. (2005), stratified random sampling is used where the population is
composed of various clearly recognisable, non-overlapping sub-populations (referred to as
strata). This study used stratified random sampling to select villages and households for inclusion
in the household survey (Chapter 6). The strata here were the villages and the households with
their various socio-economic conditions. The stratified random sampling entailed the definition
of the strata after which simple random sampling was used within each stratum.
(iii) Purposive sampling
WeIman et al. (2005) regarded purposive sampling as the most important type of non-probability
sampling. According to WeIman et al. (2005), researchers rely on their experience, ingenuity and
/ or previous research findings to deliberately obtain units of analysis in such a manner that the
sample they obtain may be regarded as being representative of the relevant population. However,
different researchers may proceed in different ways to obtain such sample and hence it is
difficult to evaluate the extent to which such samples are representative of the relevant
population.
Purposive sampling was used in this study to select the Limpopo and Luvuvhu-Letaba WMAs
because of their being administered by the Limpopo Regional Office of DWA which is within
the Province and can be quickly reached for information on these WMAs. The Middle Letaba
Dam was purposively sampled for detailed hydrological study (case study) because of its unique
challenge of not filling up even during rainy seasons (except for years of floods). The Luvuvhu-
Letaba WMAs was purposively sampled for household survey because the researcher stays in
this WMA and hence the municipalities (and villages) were in close proximity for monitoring the
work of the enumerators.
2.7.4 Data collection and analysis
This research project used a mixed approach that included quantitative and qualitative research.
Accordingly, multiple research designs were involved in the study. It is therefore
41
comprehendible that the study also used multiple methods of collecting and analysing data as
revealed under research methods.
2.8 Limitations of the study
The major limitation of this research project was that it covered two large WMAs and therefore it
was difficult to cover both of them in adequate details. As a result more investigations were
conducted in the Luvuvhu-Letaba WMA where the researcher stays and lesser work was done in
the Limpopo WMA.
Limpopo Province is generally rural (OTP, 2009) and hence lacked the technologies at different
levels of the study for recording information. Some municipalities, for instance did not have
weather stations or the stations were too new for the climate data generated from them to be
considered reliable. Actual records of water distributed from dams to different users were not
always available and this presented itself as a limitation to the study. Water supplied to users was
mostly not metered and hence the data in this regard was only limited to perceptions of
respondents which could be very rough estimates.
2..9 Summary and conclusion
The chapter presented a broad discussion of the research methods used in the study. Discussion
of the research methods included description of knowledge and was focused on research
approaches, designs and methods. The issue of research error, process and limitations of the
study are important for the research to accomplish its purpose and were also discussed.
The study used each of the two major research approaches in its various chapters, namely: the
quantitative and the qualitative approach. The study therefore used a mixed research approach.
Different research designs were used for the various chapters and these were influenced by the
type of research approach used.
42
Also, different research methods were used for the different chapters. The type of research
methods used for each chapter was influenced by the type of approach and design used. The
research methods used included literature review, secondary data analysis, survey method and
content analysis. The types of sampling used were simple random sampling, stratified random
sampling and purposive sampling.
43
CHAPTER3
3 LITERATURE REVIEW
3.1 Introduction
Water resources are scarce in semi-arid regions such as most of Southern Africa where the study
area is located. Small changes in precipitation in these regions can cause significant changes in
natural recharge of both surface and ground water (de Wit and Stankiewicz, 2006) The negative
effects of water scarcity in semi-arid areas are increased by population growth and higher living
standards that increase the demand for the resource for household and industrial uses. Also,
population growths are associated with increased water requirement for environmental concerns
such as aquatic life and recreation (Bouwer, 2003). According to Bouwer (2003), the world
population is projected to almost double in this century, and this will increase the demand for
water and exacerbate the scarcity of supply of the resource.
To protect water supplies against these changes in surface and ground water recharge, storage is
needed to build water reserves during times of surplus for use in times of shortage (KeIler et al.,
2000; Bouwer, 2003). The storage of water is mostly achieved with dams and unfortunately,
catchment runoff is becoming limited to allow for construction of more dams. Also, sustainable
supply of water under this situation of scarcity requires service organisations with good capacity
to address the challenges that characterise the water sector. In order to be effective, the service
organisations should promote participation by all stakeholders in water management decisions.
The focus of this study is to formulate the current status of water resources and the available
capacity among water service organisations and finally to develop a model to help improve
decision making by these water service organisations. In order to achieve this task, the researcher
should have sound knowledge of the main themes defining the research objectives, namely: (1)
water resources, (2) water resource management, and (3) household water supply and
requirement, and (4) available models for addressing water sector challenges. These four themes
44
provide the foundation for development of a water management decision model for Limpopo
Province and are the focus of this literature review.
3.2 Water resources
In many areas of the world, growing human populations are rapidly depleting available fresh
water supplies. The global human population increased fourfold to more than six billion during
the zo" century, and water withdrawn from natural fresh water resources increased eightfold
during the same period (Gleick, 1998). Water is therefore a scarce resource globally and
increasing its productivity is a growing concern within the international research and
development community (Twomlowet al., 2008).
Natural freshwater resources are strongly influenced by issues such as seasonal high and low
flows, and occasional floods and droughts (Sparks, 1995; Walker et al., 1995; Stanford et al.,
1996; Poff et al., 1997; Richter et al., 1997). The occurrence of low flows and droughts result in
reduced supply of water and this can have serious implications (World Bank, 2003).Further
occurrence of low flows would be devastating as 1.8 billion people are already predicted to
experience absolute water scarcity by 2025 with two-thirds of the world's population projected to
be under water stressed conditions by this time (FAO, 2007). In fact water demand already
exceeds supply in many parts of the world and indeed more areas are expected to experience this
imbalance in the near future (Vairavamoorthy et al., 2008). This statement was supported by
Komnenic et al. (2009) who revealed that almost one quarter of the human population lack
adequate access to water. Inocencio et al. (2003) predicted that all countries in Africa will be
either physically or economically water scarce by 2025.
The scarce supply of water contributes to the limited access, both in the broader South Africa
and in Limpopo Province. About 11.4% of South Africans (close to 6 million people) do not
have access to a reliable source of water (Stats SA, 2009; Manase et al., 2009) with 16.4% of
residents of Limpopo Province (859 079 people) in this situation (Stats SA, 2009). Residents in
the Limpopo and Luvuvhu-Letaba WMAs fully located within the province experience water
4S
scarcity which also affects those in the other river catchments and municipalities in Limpopo
Province.
Excessive abstractions for human survival have negative effects on the river ecosystems. A
comprehensive model for water management decision making should therefore be informed by
human requirement while also making provision for ecological needs. The inclusion of
information on water resources when developing a water management decision model is critical
when considering that water is a scarce resource, be it globally (Twomlowet al., 2008), country-
wide in South Africa (DWAF, 2004a) or within the Limpopo Province (DWAF, 2003; DWAF,
2004a).
The scarcity of water has negative effects on the socio-economic conditions of rural
communities. Women and children are responsible for the collection of water in rural areas and
are hence most affected by the scarcity of this resource (Nankhuni and Findeis, 2004). For
example, children aged 6-14 in Malawi are involved in domestic work and spend the most hours
of their domestic work time taking care of other children followed by water collection (Nankhuni
and Findeis, 2004) and this would reduce their success at school. The effect of water scarcity on
the schooling of children has a negative influence on the future of a nation. Households with
more women had increased likelihood of their children attending school, affirming the fact that it
is female household members who are principally involved in household responsibilities
(Nankhuni and Findeis, 2004). The effects of number of women increasing their children's
school attendance and reducing their work burdens were also reported for Peru (Levison and
Moe, 1998) and Egypt (Assaad et al., 2001).
In order to quantify the components of the hydrological balance, important information about the
water resources of an area including (a) rainfall and runoff generation and (b) resource storage
and distribution systems need to be considered.
46
3.2.1 Rainfall and runoff generation
The supply of water for human survival is much dependent on the quantity of runoff and this is
in turn influenced by the amount of rainfall. Runoff is defined as the water yield from a given
catchment that consists of mainly stormflowand baseflow (Schulze, 1995; DWAF, 2004a).
Runoff is the water that is seen on the land surface and can potentially be stored for abstraction
for use (DWAF, 2004a). Stormflow is defined as the water that is generated on or near the
surface of a catchment from a rainfall event and it contributes to flow in the streams within that
catchment (Schulze, 1995). On the other hand, baseflow is regarded as water from previous
rainfall events that has percolated through the soil horizons into the intermediate and
groundwater zones and then contributes to the streams within a catchment as a delayed flow
(Schulze, 1995; Fargo, 2002; Webb, 2005).
Analysis of African river systems identifies three climatic regimes, namely: (a) low rainfall
areas, (b) intermediate rainfall range, and (c) high rainfall areas. The low rainfall areas have
virtually no perennial runoff (drainage) generation. The intermediate range regimes have a
perennial runoff with a drainage density that increases with increasing rainfall. The intermediate
range regime is referred to as unstable and a change in climate would directly result in a change
in surface water supply. In high rainfall areas other factors, such as vegetation, play a role, and a
slight decrease in drainage density with increasing rainfall is observed (de Wit and Stankiewicz,
2006).
As a result of climate change, it is estimated that by 2050 rainfall in much of sub-Saharan Africa
could drop by 10% leading to major water shortages. A 10% decrease in rainfall in regions on
the intermediate regime's upper boundary (1000 mm year") would reduce runoff by 17%,
whereas in regions receiving 500 to 600 mm year" such a drop would cut 50 to 30%,
respectively of surface runoff (de Wit and Stankiewicz, 2006). South Africa falls mostly into the
region receiving about 500 mm year" with Limpopo Province receiving approximately 450mm
year" (DWAF, 2004a) and could therefore experience in excess of 50% reduction in runoff.
47
3.2.2 Water supply system
In addition to the amount of runoff, the amount of water supply can be increased by increasing
the availability of storage infrastructure such as dams (Mostert, 2008). Man can therefore
enhance water storage by constructing reservoirs such as dams to impound the water (Keller et
al., 2000; Muller, 2000). Water storage infrastructure plays a key role in water management
(Mostert, 2008), and the ability of a nation to invest in it usually determines its ability to develop
its water resources. According to Inocencio et al. (2003), developing storage infrastructure is an
obvious response to the problem of water scarcity. Dams are the common infrastructure for water
storage in the study area and were therefore the focus of this investigation.
Dams are classified as small or large. Small dams are those with an embankment volume
generally less than 0.75 million m3 (BOR, 1987; ICOLD, 1998). These small dams have the
advantage of being operationally efficient and being flexible and often closer to the point of use.
However, the high surface area to volume ratio of most small dams leads to high evaporative
losses. Small dams lose, on average, 50 % of their impoundment to evaporation in arid and semi-
arid areas, and this becomes a great disadvantage (Gleick, 1993; Sakthivadivel et al., 1997).
Large dams are the most costly to build to impound huge quantities of water. However, large
dams provide larger quantities of water for allocations for different uses and hence play a more
important role in promoting national water security.
In addition to investment in storage infrastructure, improved access to water requires
construction of sufficient reticulation infrastructure. The storage dams and reticulation
infrastructure constitute important water supply systems, where necessary, it is advisable to
invest in new supply systems (Rietveld et al., 2009). The water supply system should (a) have
sufficient capacity, be in good condition and durable, and (b) should ensure availability of water
(Ashley et al., 2004; Lundie et al., 2005) at all times.
(a) System capacity, condition and durability
System capacity pertains to the adequacy of the storage and distribution facilities to supply water
to the community. Problems related to capacity will typically arise when a village grows in size,
per capita demand and population to the point where a previously good system will begin to be
48
inadequate (Rietveld et al., 2009). The main indicators of capacity are (1) pumping capacity
from the source, (2) storage volume to overcome differences between demand and pumping
capacity calamities, (3) distance of water points from consumers and (4) the number of points
with inadequate flow rates (Rietveld et al., 2009). The condition of a water supply system refers
to the status of the system in terms of its serviceability. To determine the condition of a water
supply system, components such as reservoir, pumps and stand pipes must be assessed. A
detailed examination of all the elements of the water supply system is often time consuming and
impractical and therefore the condition of the water outlet points (tap at a communal standpipe)
is often selected as an indicator of the condition of the system (Rietveld et al., 2009).
As stated by Ashley et al. (2004), durability refers to the expected lifetime of a system. Despite
the robustness of the system, the expected lifetime of a system is heavily dependent on the level
of service and maintenance. Generally speaking, a system may not live up to its expected
lifetime because of lack of service and poor maintenance, and in some cases because of a number
of other external factors such as vandalism (Rietveld et al., 2009). Durability assessments
evaluate the readiness of the components of a system to perform their required function (Grigg,
2006).
(b) Water availability and supply continuity.
Availability pertains to the adequacy of the source in terms of quantity of the water that can be
obtained from a supply system. Also, availability pertains to the quality of water the system
supplies which should be according to the standard for drinking water (Rietveld et al., 2009).
Assessment of availability based on quantity includes storage and distribution network, taking
into account the adequacy of both pressure at individual nodes and the subsequent flow
(Fujiwara and Ganesharajah, 1993).
Supply continuity refers to the consistency of water supply from the source to the water point.
Water supply can be interrupted when: (a) a pump is broken, (b) there is a shortage of diesel /
electrical or other energy, (c) pipes are damaged or (d) taps cannot be opened (Rietveld et al.,
2009). Lack of continuity may lead to total or partial system failure. System failure can result in
49
a prolonged period without water supply. According to Rietveld et al. (2009), households may
have sufficient water stored for use during short time periods without water, while for prolonged
periods without the resource; the households may have to search for alternative sources. The
main indicators for continuity are: (a) number of hours per day without interruption of water
supply and (b) number of days per month without interruption of water supply to the households.
Schreiner et al. (2002) revealed that millions of South Africans are still dependent on water from
open streams and stagnant sources. This is a result of inadequate development and poor
maintenance of the water supply systems faced by the country. In particular, water delivery to
the rural areas is very poor and hence need for development of water supply system is more
serious in these areas.
3.3 Water resource management
Apart from the situation regarding the status of water resources, the way in which the resource is
managed is important for development of an appropriate water management decision model. The
status regarding water resource knowledge and the degree of stakeholder participation are
important aspects of water resource management.
3.3.1 Resource knowledge and its implementation
Important aspects about resource knowledge include the availability of credible knowledge and
the issue of whether it is used or not. The use of water resource knowledge is influenced by the
extent to which it is accessed by relevant stakeholders, and this is in turn influenced by the
success of knowledge transfer.
(a) Knowledge availability and extent of use
Economic growth, rapid technological change, and the expansion of scientific knowledge have
made societies more confident in their abilities to manage water resources. In order to address
the challenge of water scarcity, it is very important for the resource to be managed efficiently
based on expert knowledge. Environmental experts often express their concern over the fact that
their knowledge is not adequately used by decision makers (Hermans, 2008) and the same may
50
be said by water experts. The experts spend time and effort to develop and give advice on
policies that should ensure sustainable management of natural resources, and their advice is not
implemented by decision makers. Important decision makers for water management in the study
area include municipal water managers and relevant government departments. In order to make
appropriate resource management decisions, the water managers need expert knowledge about
the resource and its uses.
Other than expert knowledge which is produced scientifically, traditional (local) knowledge is
also important for water resource management and should also be considered in policy decision-
making. The importance of traditional response to inadequate water supply is relevant to the
concept of social adaptive capacity referred to by Ashton and Haasbroek (2002) as the ability of
a society to adapt its patterns of (water) resource use to increasingly scarce supplies and achieve
a sustainable measure of social stability.
Relevant strategies should therefore be developed to improve the connection between experts,
policy decision makers and relevant traditional authorities. Such strategies should include the
process of learning where knowledge is adopted and used by relevant actors. It is envisaged that
a participatory process of social learning (lCS, 2002; Gunderson and Light, 2006) would be a
most appropriate approach and hence a focused discussion of the concept 'social learning' is
necessary.
(b) Socialleaming
Social learning refers to the learning that individuals obtain by observing others and their own
social interactions within a group (Bandura, 1977) and hence assumes an interactive feedback
between learners and their environment. The term has been used extensively in the field of public
policy to refer to policy change and the role of ideas in this process (Hall, 1993; Greener, 2001).
Social learning is also linked to concepts such as public participation, polycentric governance,
collaborative governance, and eo-management of natural resources (Webler et al., 1995; Pretty
51
~-'"'"""::'UJ':":V:---IJ-IF-S--
b.-blO;EMFtONTEgi\l
";":;!~~}Jf,EK - 'lI-§3-IR~AR~Y
and Ward, 2001; Olsson et al., 2004), all of which are relevant for effective water resource
management.
The process of social learning in natural resources such as water resources is informed by two
important ideas, namely: (1) all stakeholders should be involved in water resource management
as no single stakeholder has all necessary information (legal, financial, technical etc.); and (2)
water resource management requires a form of organisation based on which stakeholders could
enter into long-term working relationships (Meinzen-Dick, 1997), multi-stakeholder platforms
(Leach and Pelky, 2001; Warner, 2006) , or informal policy networks (Klijn and Koppenjan,
2006).
In order to initiate social learning, stakeholders should first realize their interdependence and
agree that participation in the process can yield better results. Success of the process requires the
development of trust, joint problem definition, joint fact finding and verification, the
development and assessment of different alternatives, joint decision making, and joint planning
for implementation (Gray, 1989). To be effective, social learning should allow experts to find out
the main concerns of decision makers and should focus on analytical activities that fit the
demands of policy making process (de Bruijn and ten Heuvelhof, 2002). The experts should use
participatory research methods where stakeholder platforms are implemented (Pahl- Wostl and
Hare, 2004), i.e. representatives from different stakeholder groups are assembled. The
participatory research should include activities such as stakeholder analysis to study the
characteristics of actors and policy networks (Grimble and Wellard, 1997) and to map actor
perceptions and values (Stone, 2002; Mouratiadou and Moran, 2007).
Social learning would enable water service organisations to improve their methods used to
pursue their objectives over time and tackle new objectives as the context changes (Adger et al,
2005; Brooks et al., 2005). The ability to tackle new objectives will be influenced by the
capacity to build and maintain social and ecological diversity as this serves as a source of
renewal and reorganisation (Peterson, 2000). According to Gunderson (2000), the success of
S2
building knowledge about water issues into organisations should improve the fit between policies
and environmental realities.
3.3.2 Stakeholder participation
Apart from the issue of resource knowledge, the level of stakeholder participation is important
for effective management of water resources. Effective stakeholder participation requires
involvement of relevant stakeholders at all levels in decision making.
(a) Stakeholder selection
It is sometimes difficult to select relevant stakeholders for inclusion in a participatory process.
The complexity in the selection of stakeholders is from cases where, for instance, (l) certain
categories of stakeholders may be historically marginalized from management decisions and may
therefore be reluctant to actively participate; (2) conflicts exist between different groups making
them reluctant to join a deliberation process; or (3) participatory processes tend to focus on small
groups for in-depth deliberation and mutual learning, which excludes some stakeholders and
results in lack of representativeness (Daniels and Walker, 2001; GrimbIe and Wellard, 1997).
Informed selection of stakeholders for a participatory process therefore requires an appropriate
process of stakeholder analysis. Stakeholder analysis has become popular in the management of
natural resources such as water and land, and this shows an increasing recognition of the extent
to which stakeholders should influence water decision making- processes (Burroughs, 1999;
Duram and Brown, 1999; Selin et al., 2000). A properly conducted stakeholder analysis should
define important aspects of the system under study, identify the actors who have a stake in those
aspects of the system, and prioritize stakeholders for involvement in decisions about those
aspects of the system (Grimble and Wellard, 1997; Mushove and Vogel, 2005). Without a proper
definition of the aspects of the system under study, it would be difficult to know which
stakeholders should be involved (Dougill, 2006).
53
Innovative methods for assessing and analysing conflicts between stakeholders should be used
(Hjortso et al., 2005; Kilgour and Hipel, 2005). With proper assessment of conflicts among
prospective stakeholders, their concerns, objectives, and priorities can be identified (Grimbie and
Wellard, 1997; Borsuk et al., 2001). Information from stakeholder analysis provides useful
insight into the feasibility of policy measures based on interests, potential conflicts, and
influences of various role-players (Brugha and Varvasovszky, 2000).
A well planned process of stakeholder selection in a study area should also include those
historically marginalized from management decisions. Mitchell et al. (1997) mentions common
approaches where stakeholders are selected based on assessment of the urgency, legitimacy and
power of potential stakeholders in relation the aspects under study. These approaches tend to
prioritize economically high-ranked, more powerful stakeholders resulting in under-
representation of those economically low-ranked, less powerful groups (Grimble and Chan,
1995; MacArthur, 1997).
(b) Extent of stakeholder participation
Water stakeholders are people or groups of people with a legitimate interest in water resource
issues (Van Hofwegen, 2001). The necessity of stakeholder participation in water management
decisions was well stated by Mashau (2001) who indicated that greater participation by
stakeholders is important for sound management of the water resource. Participation by all
stakeholders in the management of the water resources is important to ensure its fair allocation
(Shah et al., 2001) and increased productivity. Schreiner and Van Koppen (2000) argued that
water scarcity is more severe among the poor and this makes it important for them to be
represented among stake holders responsible for water management decisions.
The amount of participation by non-governmental stakeholders in decision-exploring processes
through to implementation, monitoring, and sanctioning varies from the provision of information
by authorities to various levels of consultation, collaboration, and empowerment (IAP2, 2004).
During stakeholder participation, the ways in which stakeholders frame the issues can explain
54
collaborative success or failure (Gray, 2004) depending on their degree of convergence or
divergence. According to Gray (2004), the frames of stakeholders may refer to issues such as
risk and attitudes. Rayner (2003), for instance, regards expert knowledge as incomplete and
biased and with such a view meaningful participation may not occur.
Effective participation entails deliberation, a process of open communication, discussion, and
reflection among stakeholders who have different viewpoints and understandings (Leeuwis,
2000). Deliberation allows for stakeholders to learn from the views and motivations of others
(Schusler et al., 2003) and can take place in many settings, both formal and informal, including
through networks when actors are more dispersed (Dryzek, 1999). Deliberative processes can
help policy decision makers and experts better understand each other's point of view or approach
(Backstrand, 2003).
A noteworthy example of successful stakeholder participation in a natural resource programme is
that of the Australian Landcare Programme launched in 1989. This program was reported to have
been voluntary and participatory, and was based on education (Curtis and Lockwood, 2000).
According to Curtis and Loekwood (2000), the three attributes (voluntary, participatory, and
education based) contributed to the creation of stewardship. Central to the landcare programme
were the ideas of empowerment and participation (PanneIl, 2002) and issues such as skill and
level of facilitation that made it a success. Craps and Prins (2004) reported a participatory project
in which a riverine floodplain in a densely populated area in Belgium was successfully restored.
In order to be effective in managing water' resources over large areas, the water service
organisations should have multiple centres with each having sufficient capacity. Availability of
multiple centres is thought to create opportunities for understanding and for servicing needs in
large often spatially heterogeneous contexts (Imperial, 1999; Cash, 2000). The capacity of the
organisations to persist enables them to maintain and recreate their identity without having to be
continually invested in, subsidized or replenished from outside (Carpenter et al., 2001; Holling,
2001). Also, the water service organis)ations should have a sense of accountability and should
55
therefore be obliged to provide information and explain decisions and actions or inactions
(Agrawal and Ribot, 1999).
3.4 Water supply and requirement
Water is indispensable for human daily life and survival (Aiga and Umenai, 2002) and therefore
access to an adequate supply of this resource is a universal indicator of human well-being and
development (Potter and Darmame, 2010). Lack of access to safe water supplies in developing
countries is a major concern since water is a basic need for sustenance (Mazvimavi and
Mmopelwa, 2006).
The focus on water as a necessity for life obscures the fact that in most present societies, only a
very small fraction of water consumption is used for drinking and for sustaining human life. A
large proportion of water usage is for convenience, comfort and aesthetics (Inocencio et al.,
1999). Although it is only a small fraction of water consumption that is used for sustaining
human life, a large number of people lacks adequate supply of the resource. Some 900 million
people in the world do not have access to safe drinking water (Manase et al., 2009), and almost
one sixth of the world population of 6.1 billion remains without access to improved water
supplies (Potter and Darmame, 2010). According to Manase et al. (2009), close to 6 million
people do not have access to a reliable source of safe drinking water in South Africa.
Relevant decisions on water resource management require reliable information about the basic
requirement and supplies for different uses. The UN, as part of its Millenium Development Goals
(MDGs), has set a target of halving the proportion of people without access to safe drinking
water by 2015 (Sachs, 2005; Dungumaro, 2007). The World Health Organisation (WHO) has
therefore declared 2005-15 the decade of water, with the goal of establishing the framework of
eventually providing full access to water supply and sanitation for all people (Rietveld et al.,
2009).
56
In accordance with the declaration by WHO, the South African government has listed water
supply as one of its priority service delivery programmes (RSA, 2011), and the main focus is
basic household use. Despite the inclusion of water supply among the RSA government priority
service delivery programmes, drinking water supply remains a problem in South Africa,
especially in rural areas. According to Rietveld (2009), it is important to deliver sufficient
quantities of water to all South Africans. In order to develop an appropriate water management
decision model, accurate information about household supply and consumption of water is
required and hence focussed discussions on these issues are necessary.
3.4.1 Household water supply
Literature with information on how much water is supplied to a household is very limited
(Merrett, 2002; Whittington, 2002) and supplies would vary for different countries. Estimates of
water use in the Manila Metro show that daily per capita consumption ranges from a low of 20
litres up to a high of 400 litres (Inocencio et al., 1999). The lower end of this range exhibits a
limited supply possibly due to non-availability or excessively high prices while the upper bound
illustrates supply beyond the basic water requirement. The volume of water collected by a
household in informal settlements in Botswana also varied from 20 to 400 litres with an average
of 100 litres per day (Mazvimavi and Mmopelwa, 2006) and is similar to the range of use per
capita inthe Manila Metro. According to Mazvimavi and Mmopelwa (2006), the supply of water
to some households in Botswana made provision for less than 20 litres per capita per day, and
with this provision, basic personal and food hygiene requirements for water could not be
satisfied.
The amounts of water supplied for household consumption are dependent on availability of water
sources and distance of the water sources from residential sites. The quantity supplied usually
increases with an increase in the availability of water sources. The quality of water supplied is
influenced by the safety of the sources used and is dependent on the economic status of the
household. Poor households in South Africa obtained water from less safe sources of wells,
57
vendors or kiosks while wealthier residents had safer piped connections (Goldblatt, 1999, Aiga
and Umenai, 2002, Manase et al., 2009).
The distance of water sources from residential sites was influenced by the level of social and
economic development of a community. The distance generally shortened with more
development (Makoni et al., 2004) and therefore water was more accessible in economically
developed areas. According to Mazvimavi and Mmopelwa (2006), the water sources located
more than a kilometre from residential sites might be considered inaccessible and would
adversely affect the amount of water used to satisfy basic personal needs. In order to gain
knowledge of the quantity of water needed to satisfy personal needs, a focussed discussion of
household resource requirement is necessary.
3.4.2 Household requirement of water
The concern for determining the basic or minimum household water requirement comes about in
the light of the current state of water resources and the growing scarcity against a rapidly
growing population (Inocencio et al., 1999; Gleick, 1998). There is a lack of reliable information
on quantity of water required by households for different purposes (Merrett, 2002). Household
water demand forecasts are difficult to make partly because of the general lack of empirical data
on domestic water consumption. As stated by Young (1996), simplistic extrapolation of trends in
per capita requirements in water system planning often gives misleading results. A range of
socio-economic and demographic variables such as occupancy and subtle ones such as occupant
age determine the demand for water by households (Fox et al., 2009) and these vary across
countries. For example, in Mvunyane Village in KwaZulu-Natal Province of South Africa, 43%
of households used less than 50 litres and a further 49% used between 50 and 100 litres of water
per day. With the average household size of five people in Mvunyane Village, the average
quantity of 15 litres of water used per capita per day was far less than the design standard of 25
litres per capita per day (DWAF, 1994 and Goldblatt, 1999).
58
Households in the study area of Limpopo Province had no metered connections and that made it
difficult to have accurate figures of the quantities of water they used. Whittington et al. (2002)
revealed that even villages with household connections could lack or have broken meters making
it difficult to estimate precisely how much of the water supplied actually reaches the customers.
As stated by Whittington et al. (2002), households with connections could also use alternative
sources of water such as wells and public taps which would complicate calculation of the amount
of water consumed. The household water consumption as reported for Mvunyane Village
(DWAF, 1994 and Goldblatt, 1999) could probably provide a fair estimate of the requirement in
the study area.
Water use in rural areas may be classified into basic household use or productive use. Basic
household uses refer to water used for drinking, preparing food and personal hygiene (Merrett,
2002; Keshavarzi et al., 2006; Katsi et al., 2007). Productive consumption on the other hand
highlights economic activities that are highly dependent on availability of water supplies, namely
vegetable gardens, animal drinking, traditional beer making and brick making (Makoni et al.,
2004; Mazvimavi and Mmopelwa, 2006) and car washing (Arbues et al., 2003; Keshavarzi et al.,
2006).
3.5 Models for water resource management
Development of a water management decision model requires understanding of the concept
'model'. In order to ensure a comprehensive coverage, discussion of water resource models will
include (1) description of the modelled world, (2) characterization of models, (3) types of
models, (4) organisational diagnostic models and (5) rationale for selecting the Congruence
Model to provide a framework for a water management decision model for Limpopo Province.
3.5.1 Description of the modelled world
Comprehensive treatment of the topic of models necessitates sound description of the world that
is modelled. Such description is important because the modelled world determines the nature and
character of models. Various authors describe the modelled world differently. The following
59
aspects present but some of the descriptions of the modelled world and are by no means
exhaustive:
(a) Object, event or process
The modelled world may be described as an object, event or process indicating how the world
works (Oh & Oh, 2011). Understanding of the modelled world as described by these three words
necessitates examination of the meanings of the words. As stated by Homby (2005), an object is
a thing that can be seen and touched; an event is a thing that happens, especially something
important; while a process is a series of things that are done in order to achieve a certain result.
The modelled world therefore includes things that are tangible as well as those that are not.
(b) Phenomenon
The modelled world may be referred to as a phenomenon (Cartwright, 1983; McMullin, 1985;
Bailer-Jones, 2003; Shen and Confrey, 2007; Giere et al., 2006). A phenomenon is an observable
event (Massimi, 2009) The description of the modelled world using the concept of phenomenon
is therefore focused on things that may not be tangible.
(c) Base, target or referent
The modelled world may also be described as a base, a target or a referent (Maki, 1992; Grune-
Yanoff, 2011). As was stated by Maki (1992), a base may be any description of the actual world.
The target is an aspect focussed at (Homby, 2005) and in this case would be an aspect of the
world selected to be modelled. A referent is something that is referred to (Homby, 2005) and is
therefore an aspect of the world referred to by a model. The concept 'base' therefore allows a
modelled world to be either tangible or intangible while 'target' and 'referent' emphasize referral
relationship of a model to the modelled world.
(d) System
The world that is modelled is also described as a system (Ingham and Gilbert, 1991; Giere,
1999a; Gilbert and Ireton, 2003; Krohs, 2008; Maki, 2009). The concept of 'system' was defined
60
by Hornby (2005) as an organized set of ideas or theories or a particular way of doing something,
and this suggests a modelled world to be intangible. As stated by Hornby (2005), a system may
also be defined as a group of things or pieces of equipment that are connected or work together,
and this accommodates a fact that a modelled world may be something tangible.
These different concepts describing a modelled world will be used throughout this chapter.
Having provided this description of the modelled world, it will be possible to present a
comprehensive characterization of models. The characterization of models is mostly in relation
to the modelled world and is discussed in detail as the next topic.
3.5.2 Characterization of models
Models were initially neglected and were only intensively studied from the 1960s as the focus
before then were on theory (Bailer-Jones, 1999; Cartwright, 1999). New positions have
developed and models are no longer regarded inferior to theory (Bailer-Jones, 2002). The
thought of proposing solutions to challenges experienced by the water sector through a model is
therefore in line with the importance currently attached to models. The characterization of
models in this study will focus on their definition, main characteristics and on their relations with
theory.
(a) Definition of models
Although there is wide agreement that models are important elements in scientific practice, no
unique definition of models has been established. Even scientists who consider models to be
central to their research have different meanings of these models (Van der Valk et al., 2007).
With this wide variation of the perceptions on models, it is not the intention of this study to
provide exhaustive definition of models. The definition of models will focus on the aspects that
are important for guiding the development of a water management decision model.
(i) Model as an interpretive description
A model is an interpretative description of a phenomenon (Bailer-Jones, 2003). As stated by
Bailer-Jones (2003), the word 'description' in this definition includes various forms of
61
representation. The ability of a model to describe a specific phenomenon depends on the
interpretation that goes beyond pure phenomenological reality (Bulle, 2009). The phrase
'interpretive description' is therefore key in this definition.
(ii) Model as a representation
A model is a representation of how some aspect of the world works (Windschitl and Thompson,
2006). There is a great variance in what can be represented by a model, and this includes the
different descriptors of the modelled world, e.g. targets and systems (Oh & Oh, 2011). A model
is a representation of some target in the sense that it stands for that target as its substitute. Instead
of obtaining information about the target by examining it directly, one may therefore examine
the properties of the model and indirectly acquire information about the target (Grune- Yanoff,
2011).
A model is a simplified representation of a system and focusses attention on specific aspects of
the system (Ingham and Gilbert, 1991). A model is therefore an abstract structure which
represents systems in the world (Giere, 1999a), and this may be via a relationship of similarity. A
model enables aspects of the system (objects, events or ideas) to be rendered visible (Gilbert,
1995).
(iii) Model as a mediator
A model is a mediator between the abstract and the concrete or between theory and a
phenomenon in the world (Cartwright, 1983). A model stands in an intermediate position
between theory and the features of the world it is meant to model (Glennan, 2005). Although
models are defined as interpretive descriptions, representations and mediators, discussions in the
rest of this chapter will use one concept at a time.
(b) Main characteristics of models
The definition of models provides a good indication of what models are and hence present some
understanding of these important scientific entities. An increased understanding of models may
however be obtained by providing detailed descriptions of their characteristics. The main
62
characteristics of models will be discussed in this study in terms of concepts such as isolation,
selection, representation and propositions.
(i) Isolation as a characteristic of models
Isolation is a process that leads from a base to an isolated product (Grune- Yanoff, 2011) and is
an important characteristic of models. The isolation occurs in modelling when some feature of
the base is excluded and has no impact in the isolated product. The word 'base' describes the
environment the isolation seeks to manipulate and control and is the actual world (Maki, 1992).
In addition to being a model, the product yielded by isolation may be a concept or theory (Grune-
Yanoff, 2011) and represents the base in some sense.
(ii) Selection as a characteristic of models
The focus of selection as a characteristic of models is on features of the phenomenon that are
chosen for the purpose of modelling. The assumption is that the features of a phenomenon that
are not currently subject to modelling can be disregarded. Other models may later be developed
to complement the first model by addressing those features that were ignored in the first model
(Bailer-Jones, 1999).
Similar to the rationale for use of isolation, the use of selection is based on the fact that models
practically never aim to describe a phenomenon in its entirety. The models set themselves
smaller, manageable tasks and focus only on selected aspects of phenomena or of the system.
The task of modelling only an aspect of a phenomenon is easier and less complex than trying to
model the entire phenomenon with all its features and properties (Bailer-Jones, 2003). It is
therefore possible to have different models of one and the same phenomenon that do not
necessarily relate to each other as they may each address a different aspect of the phenomenon
(Bailer-Jones, 2003).
(iii) Representation as a characteristic of models
As reflected in some of the definitions, one of the major characteristics of models is that they
represent something. In fact representation is a key term in the current debate about models The
issue of representation as a characteristic of models was affirmed by Grune- Yanoff (2011) who
63
mentioned that a model is representative of a target in the sense that it stands for that target as its
surrogate.
The word 'representation' as used in models does not mean 'resemblance' and therefore a model
does not need to resemble the target. According to Suarez (1999) a resemblance is not necessary
for representation and a model is typically representational. This was supported by Maki (2006)
who revealed that models are simpler representations of the target system and are devoid of most
properties of the system. Also, Giere ef al. (2006) revealed that a model is similar to the target
only in the intended respect and to the intended degree of accuracy. This was further affirmed by
Weisberg (2007) who revealed that models represent only those factors that make a difference to
the occurrence and essential character of the target.
The fact that models only represent the target in certain respects has allowed for multiple
modelling of each target. The reasons for such multiple modelling as highlighted by Oh & Oh
(2011) are: (1) different models can be built to represent different aspects of the same system or
target; (2) models only represent selected features of targets and have limitations and therefore
various models are needed to provide a full-fledged explanation of the real world system; (3) two
or more rival models may coexist because there are multiple ways of explaining or
conceptualizing the same thing; and (4) models may be created in multiple forms of
representation.
The representational relationship may be described as a fit between a model and the world
represented (Giere, 1999b). The fit between the model and the real word can be explained in
terms of that between a map and the world where a map aspires to represent only some and not
all aspects of the world. Targets such as space shuttle and volcanic mountain may be represented
by scale models that are perceptually similar but are enlarged or reduced at different rates
(Harrison and Treagust, 2000). Again it should be mentioned that models only focus on certain
aspects of a phenomenon and allow some other aspects of the same phenomenon to be excluded.
64
(iv) Models entail propositions
Among the important characteristics of models is that they can be expressed as propositions
about the empirical world (Bulle, 2009). Even if large parts of a model are described by means of
images, there is often a commentary on these images that relates the images to the empirical
world in the way intended in the model, and such a commentary would be propositional (Bailer-
Jones,2003).
It is not easy to determine the number of propositions made through models about the empirical
world. Where the number of propositions could be determined, the ratio of the number of true
and false propositions made by the model is an indicator of weather the model should be
regarded true or false (Bailer-Jones, 2003). As revealed by Bailer-Jones (2003): (1) model users
assess propositions made by a model and determine the balance between true and false
propositions; and (2) the propositions that are crucial for meeting the intended function of the
model are not allowed to be false while those less central to the function can be false without
doing much damage.
(c) Relations between model and theory
Among the definitions of models is that they are mediators between the real world and theory
(Glennan, 2005). The relations between a model and the real world were discussed in detail as
part of a definition and main characteristics of models (Section 3.5.2 (a) and (b)). A
comprehensive discussion of the relations between a model and a theory is however necessary.
The concept 'model' was already defined and to present a meaningful description of the
relationship between a model and theory, it is necessary to also define the concept of 'theory'.
Theory is an abstract, coherent and causal representation of features of described objects (Gopnik
and Meltzoff, 1997). The theory is coherent and causal in the sense that it presents systematic
and causal relationships with the described objects (Glennan, 2005).
65
According to Gopnik and Meltzoff (1997), the function of a theory is to predict, interpret and
explain data. It is through the predictive and interpretive function that theory helps scientists
understand a mass of unreconstructed data. A theory is explanatory because its abstract, coherent
and causal structure promotes an understanding of the data connected with the theory (Glennan,
2005).
The definitions of theory reveal lots of similarity with model. This view was affirmed by
Cartwright (1983) who regarded a theory to be a resemblance of a model. The distinction
between model and theory is hard to determine, and this is especially because philosophers and
scientists use the two terms in a variety of ways with scientists sometimes using the words
interchangeably (Glennan, 2005).
However, some distinctions do occur between model and theory, and those include:
(i) A model is applied to concrete empirical phenomena whereas a theory is not. A theory, in
turn, has the capacity for being applied to empirical phenomena when specific conditions
belonging to a concrete case are satisfied and corresponding variables are inserted (into the
theory). Subsequent to insertion of specific conditions of the concrete phenomenon, a theory can
be moulded and adjusted to address the real and concrete empirically observed situation (Bailer-
Jones, 2003).
(ii) A model aims to match specific empirical situation while a theory aims to be general. As
stated by Bailer-Jones (2003), a model is more specific and is locally valid while a theory aims at
addressing the empirical world through general principles and is globally valid. According to
Bulle (2009), a model is a subset of a theory and is a more comprehensive system of explanation
while a theory is in fact represented as sets of models.
(iii) A theory is reported to develop from a model, implying that a theory is a good model.
The theory is regarded as a model that has been tried and tested and has indeed proved to be a
good model (Bailer-Jones, 2002). It is assumed from this description that the theory is the best
we can do, the state of the art. A theory may contain approximations, but usually only well
controlled approximations while a model may include rough approximations. As a result, Bailer-
66
Jones (2002) concluded that there is a more definite truth claim associated with a theory than
with a model.
3.5.3 Types of models
Description of different types of models is necessary to make an appropriate choice of the type to
be adopted. Various authors classify models differently and therefore there is no single method
for model classification. While models may be classified into many different types, this study
will only highlight a few to introduce the reader to the Congruence Model that will be used to
develop a water management decision model.
(a) Models as semiotic resources
The classification of models as semiotic resources emphasizes their presentation of features of
the world through the use of signs. This categorization of models was alluded to by Bailer-Jones
(2002) who mentioned that the content of a model is expressed through a range of different
means that include diagrams, mathematical equations and language sentences written on a piece
of paper. These different means reflect various forms of semiotic resources.
Affirmation of the classification of models as semiotic resources was provided by Gilbert and
Ireton (2003) and Ramadas (2009) who described them as linguistic entities, pictures,
diagrammes, graphs, concrete materials, animations, actions and their combinations. The
classification was further supported by Oh & Oh (2011) who indicated that models are often
characterized as the use of visual resources such as pictures, diagrammes, animations, or material
objects which simplify and highlight certain aspects of the targeted system. As revealed by Oh &
Oh (2011), there are four different types of models under semiotic resources, namely: scale
model, analogue model, mathematical model and theoretical model.
(i) Scale model
A scale model may be regarded a representation or copy of the object that is larger or smaller
than the actual size of the object, which seeks to maintain the relative proportions of the physical
size of the original object. It is the relation between the actual size of something and its size on a
67
map, diagramme or model that represents it (Hornby, 2005). Material objects and pictures are
larger or smaller and seek to maintain the relative proportions of the physical size of the original
object and are perhaps the common examples of scale models.
(ii) Analogue model
The concept of 'analogue' refers to a thing that is similar to another thing (Hornby, 2005). An
analogue model as used by Koons and Henderson (1995) is for modelling the mechanics of a
large scale problem at a scale that is applicable to a laboratory setting. Diagrammes and
animations are possible examples of analogue models.
(iii) Mathematical model
A mathematical model may be considered an abstract model that uses mathematical language to
describe the behaviour of a system. As alluded to by Hornby (2005), a mathematical language
involves the use of numbers and shapes, so mathematical models therefore entail the use of
mathematical equations and graphs to represent the real world.
(iv) Theoretical model
A theoretical model is based on the use of theory to explain something. The theoretical model
explains an entire situation or behaviour to the level of eventually being able to predict the
behaviour. A theoretical model entails the use of various semiotic resources such as linguistic
entities and diagrammes.
Among the examples of a theoretical model would be a conceptual model. This category of
model is important for attainment of conceptual understanding in science at a level that goes
beyond memorized facts, equations or procedures (Clement, 2000). The conceptual model
provides simplified description and explanation of concepts thereby promoting better
understanding of the concepts.
(b) Diagnostic models
Other than classification as semiotic resources, models may also be categorized as diagnostic
tools. Diagnostic models can be probabilistic, confirmatory and multidimensional (Rupp and
Templin, 2008). The models are suitable for modelling observable categorical response
68
variables. As revealed by Rupp and Templin (2008), diagnostic models enable multiple
interpretations and associated feedback for diagnostic purposes. The diagnostic models can be
used to make sense of some data (Leighton, 2008).
This study is to use an organisational diagnostic model to develop a water management decision
model specifically being the Congruence Model of Nadier and Tushman (1980). As a result, a
dedicated section is necessary to provide a detailed discussion of organisational diagnostic
models.
3.5.4 Organisational diagnostic models
With the concept 'model' already defined, a comprehensive discussion of organisational
diagnosis should first describe the concept 'organisation'.
(a) Organisation
An organisation is the planned coordination of the collective activities of two or more people
who, functioning on a relatively continuous basis and through the division of labour and a
hierarchy of authority, seek to achieve a common goal or a set of goals (Robbins, 1983). From
this definition, the achievement of a common goal is the ultimate purpose of the existence of
organisations. It could have been a result of this emphasis on goal that March and Sutton (1997)
regarded organisations simply as instruments that are coordinated by intentions and goals. The
ability of organisations to achieve their goals is influenced by a number of factors, and those
include organisational environment and leadership.
Literature on organisational decision making shows that organisations must continually monitor
their environment and make strategic decisions to keep the firm strengths aligned with new
opportunities and threats in the environment (BaIT and Huff, 1997). The continual monitoring
makes it possible for the organisations to update their strategies to remain competitive in a
changing environment.
69
(b) Organisational diagnosis
The main purpose of organisation development strategies is to improve the effectiveness
(Cummings and Worley, 1993) and sustainability (Kiron et al., 2012) and hence organisations
commit a lot of resources to achieve this purpose (Haanaes et al., 2011; Kruschwitz and
Haanaes, 2011). Among the factors determining the sustainability of an organisation is its impact
on the environment, and this is also influenced by the political situation (Schendler and Toffel,
2011).
Organisational diagnosis is one of the organisational development strategies and involves
'diagnosing', or assessing an organisation's current level of functioning in order to design
appropriate change interventions. The organisational diagnostician uses specialized procedures to
collect vital information about the organisation, to analyze this information, and to design
appropriate organisational interventions (Salvatore and Falletta, 2005).
Diagnosis identifies organisational factors that necessitate change of strategy to create
competitive advantage (Kiron and Shockley, 2011; Simchi-Levi et aI., 2012). These
organisational factors may include information technology (Brynjolfsson and McAfee, 2012) and
factors related to building and sustaining a strong talent pipeline (Stahl et aI., 2012).
Organisational factors associated with building talent are important for generating more value
from employees (Schweer et al., 2012). The advance of information technology makes it
necessary for managers to cope with innovations in this technology (Swanson, 2012) often
acquired from external sources (Lichtenthaler et al., 2011). The change of strategies should aim
at influencing markets (Von Hippel et al., 2012; Murrayand Haubl, 2012) locally and
internationally (Baaij et al., 2012). Correct diagnosis is important for relevant strategies to be
adopted to 'treat organisational wounds' (Kahn, 2011).
Within an organisation, the diagnostic process often facilitates an admission by top management
that the organisation does indeed have problems or needs that should be addressed (Harrison,
1987; Manzini, 1988). In order to develop the most appropriate interventions, organisational
70
diagnosis continues at a detailed level to search for the underlying problems (Fordyce and Weil,
1983). The results of the diagnosis are fed back to the members of the organisation in order to
begin the process of organisational change (French and Bell, 1995; Harrison, 1987).
3.5.5 Suitability of organisational diagnostic models to guide water decisions
(a) Selected examples of organisational diagnostic models
Five examples of organisational diagnostic models were selected based on the variability of the
aspects they cover. These models are (a) the McKinsey 7S Framework, (b) Tichy's Technical
Political Cultural Framework, (c) High Performance Programming, (d) Diagnosing Individual
and Group Behaviour, and (e) the Congruence Model. Selection of a model to guide water
management decision making in the study area is based on the model that allows for
responsiveness to the situation in this area.
(i) McKinsey 7S Framework
The M7SF was developed by McKinsey Consulting (Salvatore and Falletta, 2005) and provides a
useful framework for reviewing the impact of change (Noolan, 2004). The M7SF was created as
a recognisable model in business and is composed of seven variables (also called levers). The
variables all begin with the letter'S' and were described by Noolan (2004) as follows:
• Strategy: States how an organisation will attain its vision and respond to the threats and
opportunities of the new mediums.
• Shared Values and Beliefs: This imparts to the organisation (and externally) what the
organisation stands for and what it believes in.
• Systems, including Processes: Capabilities are required in information technology, sales
and service, legal and actuarial science.
• Staff: Human resource management for developing the skills and aptitude for building
lifetime customer relationships.
• Style: This refers to the management style best suited for the organisation. The challenge
for management is to use appropriate styles for the situation without confusing staff.
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• Structure: Changes to processes and style inevitably require changes to organisational
structure (e.g. centralised vs decentralised, structure).
• Skills: The degree to which necessary skills exist is the core of workforce planning. Staff
acquisition of necessary skills requires appropriate learning environment.
As revealed by the description of the variables, the M7SF focuses on the internal aspects of an
organisation with little focus on external input and output aspects and this suggests lack of
responsiveness to the situation outside the organisation.
(ii) Tichy's Technical Political Cultural Framework
The Tichy's Technical Political Cultural Framework (TTPCF identifies key variables that are
important to the change management process. The variables of the TTPCF were defined by
Salvatore and Falletta (2005) as follows:
• The environment and history are two major categories of input to the organisation
whereas resources are a third category of input.
• The mission/strategy variable is the organisation's approach to carrying out its mission
and strategy and criteria for effectiveness.
• The tasks variable refers to the technology by which the organisation's work IS
accomplished.
• The prescribed networks refer to designed structure of the organisation, such as the
organisation of departments and the communication and authority networks.
• The people variable refers to the characteristics of organisational members, including
their background, motivation, and managerial style.
• The organisational processes are the mechanisms which enable the formal organisation to
carry out the work and these include organisational communication, decision-making,
conflict management, control, and reward systems.
,
• The final throughput variable, emergent networks, refers to the structures and processes
in the organisation which emerges informally.
72
The issues emphasized in TTPCF include the externally located aspects of input and the internal
organisational aspects with no attention provided to the external outputs of organisations.
(iii) High Performance Programming
The High Performance Programming (HPP) framework focuses on organisation performance.
Table 3.1 Conceptuaiisation of four HPP framework systems (Nelson and Bums, 1984)
Organisation Characterisation
al system
High Leaders focus on empowering members to achieve organisational excellence. Communication
performing throughout the organisation is relatively unrestrictive. Organisational evolution is guided by a
organisation common vision. Members prise their identity with the organisation highly. Opportunities for
Leve/4 self-actualisation are substantial.
Proactive The organisation focusses on the future. Leadership focusses on developing purpose for the
organisation organisation. Members focus on quality of contribution to organisational successes. The
Level3 organisation is actively involved in planning and developing strategies.
Responsive The organisation is more functional, achieves clarity of purpose and goal and has capability to
organisation adapt to changing environment. Leaders actively coach members to achieve organisational
Leve/2 goals, and there is cohesion among work teams.
Reactive The organisation is badly in need of renewal. There is lack of shared focus, and management is
Organisation preoccupied with assigning blame for poor outcomes. Members spend time avoiding aversive
Leve/l consequences, and leaders spend time enforcing policies that often lack relevance to any
commonpurpose.
The HPP framework assesses the current level of performance of an organisation in order to plan
interventions to transform the organisation into a high performing system (Nelson and Bums,
1984). As stated by Salvatore and Falletta (2005), the HPP framework is described in terms of
four systems that are more or less effective, namely: high-performing organisation (level 4),
proactive organisation (level 3), responsive organisation (level 2), and reactive organisation
(level I) as shown in Table 3.1. As revealed by the conceptualisation of the systems of the HPP
framework, this model is more focussed on internal aspects influencing organisational
performance with no illustration of linkage with the external environment and may be little
responsive.
(iv) Diagnosing Individual and Group Behaviour
The Diagnosing Individual and Group Behaviour (DIGB) model represents an open systems
perspective with minimal boundaries between the organisation and external environment. The
73
external environment in the model is represented by resources and feedback loops (Salvatore and
Falletta, 2005). The variables accounted for in the model are conceptualised at individual and
group levels (Harrison, 1987) as shown in Table 3.2.
Table 3.2 Conceptualisation of Individual and Group Levels in DIGB model (Harrison, 1987)
Factors affecting Description
performance
Individual Level
Individual Physical and mental state, social background and traits, training and education,
characteristics individual needs
Individual attitudes, Motivation, rewards experienced, job felt to be intrinsically rewarding, expectations,
belieft & motivation equity, trust, specific attitudes (e.g., satisfaction with current procedures, attitudes
toward proposed changes)
Group Level
Group composition, Social and occupational composition, structure (e.g. nature and extent of rules and
structure, and work procedures, flexibility, clarity of tasks and assignments, responsibilities),
technology technology (e.g. impact of work procedures and physical arrangements, types of
workflow interdependencies)
Group behaviour, Relationships among group members (e.g. cohesiveness, feelings of attachment to
processes, and culture group, similarity of views), processes (e.g. communication, cooperation and conflict,
decision making, problem solving), supervisory behaviour, culture
The emphasis of this model is on the internal organisational transformation component with
particular focus on the behaviour of people that work in an organisation. Broad organisational
issues and the external components of input and output are not provided for in this model.
(v) The Congruence Model
The Nadler- Tushman Congruence Model is a comprehensive model, specifying inputs,
throughputs, and outputs, which is consistent with open systems theory (Katz & Kahn, 1978).
The inputs within the Nadler- Tushman Congruence model include such factors as the
environment, resources, history (i.e. patterns of past behaviour), and organisational strategies.
Nadier and Tushman (1980) are explicit in their conceptualisation of each of the factors. For
example, they describe the resources available to the organisation as human resources,
technology, capital, information, and other less tangible resources. Strategy is an input in the
model as it is the single most important input to the organisation (Salvatore and Falletta, 2005).
74
The internal transformational components are informal organisational arrangements, task, formal
organisational arrangements, and human resources (Nadler and Tushman, 1980). Similarly, the
outputs of the model include individual, group, and organisational outputs. The Congruence
Model emphasizes a degree of congruence or fit between each pair of components of the model.
The congruence between two components is defined as the degree to which the needs, demands,
goals, objectives, and structures of one component are consistent with those of the other (Nadler
and Tushman, 1980). The greater the degree of congruence between the various components, the
more effective will be the organisation. Effectiveness was defined as the degree to which actual
organisational outputs are similar to expected outputs (Nadler and Tushman, 1980; Wyman,
2003; Bezboruah, 2008). Different aspects are used to describe congruence between different
pairs of internal transformational components of the model (Table 3.3).
Table 3.3 Issues for describing congruence between different pairs of internal transformational
components of the Congruence Model (Nadler and Tushman, 1980)
Component pair Issues for describing congruence
Individual - Formal How are individual needs met by the organisational arrangements? Do
Organisational Arrangements individuals hold clear or distorted perceptions of organisational structures? Is
there a convergence of individual and organisational_g~als?
Individual - Task How are individual needs met by the tasks? Do individuals have skills and
abilities to meet task demands?
Individual - Informal How are individual needs met by the informal organisation? How does the
Organisation informal organisation make use of individual resources consistent with informal
_goals?
Task - Formal Organisational Are organisational arrangements adequate to meet the demands of the task? Do
Arrangements organisational arrangements motivate behaviour that is consistent with
demands?
Task - Informal Organisation Does the informal organisation structure facilitate task performance or not?
Does it hinder or help meet the demands of the task?
Formal Organisational Are the goals, rewards, and structures of the informal organisation consistent
Arrangements - Informal with those of the formal organisation?
Organisation
The Nadler- Tushman Congruence Model is indeed a comprehensive model specifying inputs,
transformation and outputs. The model provides a fair emphasis of both internal transformational
75
issues and external input and output issues and would likely result in responsive water service
organisations.
(b) Selection of model for water management decision making
A decision on which of the described diagnostic models should be selected for adaptation into a
water management decision model necessitates that the described models be evaluated. The
evaluation will be guided by the extent to which the models provide attention to the aspects of
inputs and outputs that are external to the organisation and to transformational issues that are
internal. The evaluation is based on these components because they define a well-functioning
organisation (Gill, 2000; Mertikas, 2008) that is responsive to the challenges presented by the
external environment (Table 3.4).
Table 3.4 Evaluation of described diagnostic models based on their inclusion of aspects defining
a well-functioning and responsive organisation (Gill, 2000; Mertikas, 2008)
Model Input Transforma Output Total rating
tion
McKinsey 7S Framework 1 2 0 3
Tichy's Technical Political Cultural 2 2 0 4
High Performance Programmign 0 2 0 2
Diagnostic Individual & Group 0 2 0 2
Congruence Model 2 2 2 6
Key: O=Not included; 1=Uncertain, little inclusion; 2=lncluded
As shown in Table 3.4, the Congruence Model is the only one that includes all the aspects
(external input, organisational transformation, and output) that define a well-functioning
organisation and hence attained the maximum rating (of 6). All the models included
transformational issues which suggests more focus on internal organisational as opposed to a
balance of external input and output issues. After the Congruence Model, the TTPCF is the
second best model well-functional organisation (rating=4) followed by the M7SF (rating=3).
76
As the Congruence Model is the only model surveyed that included all aspects defining a well-
functional organisation, it was selected for adaptation into a water management decision model
for Limpopo Province. In addition to inclusion of all necessary aspects, the model also puts
emphasis on the necessity of congruence between pairs of aspects which is important to ensure
the effectiveness of the organisation.
3.6 Summary and conclusion
This chapter presented the literature survey which enabled the researcher acquire new ideas and
perspectives about the research topic and helped with the interpretation of the findings of this
study. Interpretation of the findings of this study was improved by comparing the results of the
study with those of other researchers.
The literature survey discussed the water resources, water resource management, household
water supply and requirement, and the use of models in water resource management. Discussion
of water resources included on rainfall and its influence on runoff generation and it was shown
that an increase in rainfall results in increase in the generation of runoff. Water supply system is
an important aspect of the water resource and the literature survey indicated that adequate system
capacity, maintenance to ensure good condition and durability of the system are important for
improved water supply, and this depends on water availability.
The discussion of water resource management focussed on the issue of resource knowledge and
stakeholder participation. Experts claimed to have valuable knowledge which is not used by
policy decision makers, and non-government stakeholders where shown to be excluded from
water decision making, and participatory social learning was highlighted as a strategy to bring
the stakeholders together to learn from each other. The household water supply was shown to be
inadequate to meet the demand.
Discussion of models was to indicate the prospects of using them to make relevant water
management decisions to address the challenges faced by the sector. Focussed discussion was
77
made of organisational diagnostic models, and these were assessed for suitability to guide water
management decision making with the Congruence Model proving to be the most suitable. The
issues covered in the literature survey were all necessary to inform the development of a water
management decision model for the Limpopo Province.
78
CHAPTER4
4 RUNOFF AND STORAGE CAPACITY OF RIVER CATCHMENTS AND
MUNICIPALITIES
4.1 Introduction
The supply of water in an area is dependent on the quantity of runoff and this is in turn
influenced by rainfall. The importance of rainfall was stated by Schulze (1995) who described it
as the fundamental driving force and important input behind most hydrological processes.
Occurrence of low rainfall and subsequent runoff in an area results in water shortage described in
terms of resource stress or scarcity. An area is water stressed when annual supplies per capita
drop below 1 700 nr', is water scarce when the supplies decrease below 1 000 m3 and has
absolute scarcity when the supplies are below 500 m3 (FAO, 2007).
The rainfall of an area is influenced by the climatic region in which it is located. Three climatic
regimes were identified in Africa, namely: the low rainfall areas, those of intermediate range and
the high rainfall areas (de Wit and Stankiewicz, 2006). South Africa is located in a
predominantly low rainfall area. The climate is relatively arid in the west and humid in the east.
The average annual rainfall is 450mm, and is well below the world average of about 860mm
(DWAF, 2004a). Accordingly, the Limpopo Province is also situated in a low rainfall area with
lesser rainfall recorded in the western located Limpopo WMA compared to that received by the
eastern located Luvuvhu-Letaba WMA (DWAF, 2003; DWAF, 2004b). The river catchments
and the municipalities located in these WMAs are therefore affected by the water scarcity.
To mitigate against the challenge of scarcity, water resources should be more efficiently
managed, and this should begin with an assessment of the amount of runoff in a specific area.
Runoff was described as the water yield from a given area and consists of mainly stormflowand
baseflow, and is in fact the water that can be seen on land surfaces and can potentially be stored
for use (Schulze, 1995; DWAF, 2004a). Stormflow is the water that is generated on or near the
79
surface of a catchment from the occurrence of rainfall and contributes to flow in the streams
within that catchment (Schulze, 1995). On the other hand, baseflow is regarded as water from
previous rainfall events that has percolated through the soil horizons into the intermediate and
ground water zones and then contributes to the streams within a catchment as a delayed flow
(Schulze, 1995; Fargo, 2002; Webb, 2005).
In addition to the amount of runoff, the amount of water supply depends on the availability of
storage infrastructure such as dams (Mostert, 2008). Water is stored in dams during high rainfall
seasons when and where the economic value of the resource is low and is reallocated to times
and places when and where its economic value is high. The concept of 'economic value' includes
both the social and environmental value of water (KeIler et al., 2000). The dam storage capacity
of a river catchment refers to the quantity of water that can be stored in man-made dams in that
catchment and availed for different uses.
The objective of this study was to investigate the amount of available water by assessing the
runoff and storage capacity relationships of river catchments and municipalities in the Limpopo
and Luvuvhu-Letaba WMAs. The water storage capacity within the area is compared to the
runoff to assess the possibility of constructing new dams in some catchments and of
implementing new strategic water projects such as rain water harvesting in municipalities
(Section 1.4, Table 1.3, specific objective 1).
4.2 Methodology
4.2.1 Study area
The study was based in two WMAs located in the Limpopo Province and administered by the
Limpopo Regional Office of Department of Water Affairs and Forestry (DWAF), the Limpopo
and Luvuvhu-Letaba WMAs (Figure 4.1).
80
toc.u.rrr MÁ'
loc.1 Munlelp.url ••
00-
//' .... '.. G'I'"
[r-: .....i· are.." lellblDor..t.. TLWIttnOM---
c::J1hli1n1l
~'j"".1t
D-'"
'/' Tl'Uamr.
0"'"
OD/LE WEST AND MAR/CO /NKOMAT/
Figure 4.1 Map of the Limpopo Province showing the Limpopo and Luvuvhu-Letaba Water
Management Areas (red border line) and the ten municipalities (hatchings) sampled for the study
(DWAF,2004a)
Ten municipalities under the two WMAs were sampled for the study, five from each WMA. The
five municipalities sampled from the Limpopo WMA include three which are fully contained in
the WMA, namely: Musina, Aganang, and Lephalale and two which have a large part of their
land area located in the WMA, namely: Makhado and Polokwane. As for the Luvuvhu-Letaba
WMA, the five municipalities sampled were the Letaba and Giyani which are fully contained
and Mutale, Thulamela and Tzaneen with larger part of their land areas located in the WMA.
81
4.2.2 Sampling procedure
The study units were selected from the sample frame (Section 2.7.3(a), Chapter 2). Sampling was
done using the multi stage approach for WMAs and municipalities (Leedy and Ormrod, 2010).
Purposive sampling was used to select the Limpopo and Luvuvhu-Letaba WMAs as they are
managed by the nearby Limpopo Regional Office of DWAF that is more accessible for
information (WeIman ef al., 2005; Leedy and Ormrod, 2010). All main river catchments for each
WMA were included in the study, seven for Limpopo and six for Luvuvhu-Letaba WMA.
Informed by the ease of availability of information, 10 municipalities were also purposively
chosen, five in each of the WMAs (Figure 4.1).
4.2.3 Data collection and analysis
Data for runoff and storage capacities of river catchments (1960-1996) was obtained from
DWAF (2003) for the Limpopo and from DWAF (2004b) for the Luvuvhu-Letaba WMA. The
data for municipal runoff was calculated from that of representative quaternary catchments as
presented by Midgley ef al. (1994). As guided by Leedy and Ormrod (2010), the data was
properly organized for ease of analysis by classifying them into main themes covered by the
investigation, namely: runoff and storage capacity of the study area. As mentioned earlier, the
study area was categorized into WMAs, river catchments and municipalities.
Interpretations were objective and precise to specific situations and generalizations were made
only in strict accordance with the data. The data was related to the purpose of the study and pre-
existing literature while also determining the practical significance of relationships among
variables (Leedy and Ormrod, 2010).
4.3 Results and discussion
4.3.1 Runoff and storage capacity ofriver catchments in the study area
The occurrence of runoff determines the extent to which man will access water for various uses,
including domestic, industrial and agricultural uses. Several authors highlighted the benefits of
practices such as conservation tillage in improving the agricultural productivity of water (Kongo
82
and Jewitt, 2006; Mutiro et al., 2006; Ngigi et al., 2006; Mupangwa et al., 2008; Munodawafa
and Zhou, 2008; and Sturm et al., 2009). With conservation tillage, dryland farming is therefore
possible without runoff impoundments in reservoirs that tend to be more necessary for irrigated
agriculture.
Other than conservation tillage, man can enhance water storage by constructing reservoirs such
as dams to impound the water (KeIler et al., 2000; Muller, 2000). Water storage infrastructure
plays a key role in water management (Mostert, 2008), and the ability of a nation to invest in it
determines its ability to develop its water resources. According to Inocencio et al. (2003),
developing storage infrastructure is an obvious response to the problem of water scarcity. Dams
are the common infrastructure for water storage in the study area and were therefore the focus of
investigation.
Dams are classified as small or large with small dams characterised by a storage volume
generally less than 0.75 million m3 (BOR, 1987; ICOLD, 1998). Although small dams have an
advantage of being operationally efficient and being flexible and often closer to the point of use,
the high surface area to volume ratio of these small dams leads to high evaporation loss. Small
dams lose, on average, 50% of their impoundment to evaporation in arid and semi-arid areas, and
this becomes a disadvantage (Gleick, 1993; Sakthivadivel et al., 1997). On the other hand, large
dams are costly to build for huge quantities of water to be impounded. Large dams provide larger
quantities of water for allocations for different uses and hence play a bigger role in promoting
national water security.
(a) Runoffs of catchments in the study area
The amount of runoff from a catchment influences the stream flows and hence the sizes of rivers
flowing through that catchment. In fact the size of a river at a catchment is determined by runoff
from the catchment under consideration plus the runoff contribution from all upstream
catchments (Schulze, 1995). Many of the rivers flowing through the study area are permanently
flowing at their headwaters and then pass through drier regions and become seasonal rivers due
83
to natural losses as well as abstractions (Gorgens and Boroto, 2003). The mean annual runoff of
river catchments of the Limpopo and Luvuvhu-Letaba WMA is presented in Fig. 4.2 (DWAF,
2003; DWAF, 2004b).
As shown in Fig. 4.2, the total MAR of river catchments in the Limpopo WMA was 985.9
million rrr' while that of the catchments in the Luvuvhu-Letaba WMA was 1 183.9 million nr'.
Considering MAR, this result indicated that the Luvuvhu-Letaba WMA had more available
water than the Limpopo WMA. It would therefore be expected for the Luvuvhu-Letaba to have
more potential for development of dam storage than the Limpopo WMA .
............................]............I......................................
Nwanedi ~ 24.5
W~ _~7:99;i
a g_ Mogalakwena ~~ 268.8
n ~ .·..·~·~·~~'--"~·~·_·~·.,.I--i
d:3 ·--Le-ph-a_lale,r~;; i~ 149.4I
r MokoIo ~ ~... ~ 315.6
_--_-_-M-a-t~.b.: as _~ 66.31
v
e WMATOTAL ~~~~, ::~;; ;;;m
r ~~~=.~.~:=::=:~=41~.3=I
c Groot Letaba ~~ ~ 380.9
a ----I
Middle Letaba .i.,_ I~ 151.989.S'
Shingwedzi ~~
-- lUVUvl-..l-;,_-~l _~I~
e
n Mutale
t
WMATOTAl 1.183.9
o 200 400 600 800 1000 1 2.00 1 400
Mean annual runoff in millIon m3 (1960-1996)
Figure 4.2 Mean annual runoff (MAR) of river catchments of the Limpopo and Luvuvhu-Letaba
WMA (DWAF, 2003; DWAF, 2004b)
84
Assuming a MAR requirement of at least 100 million m3 for a river catchment to accommodate
major dams, seven catchments had enough water to accommodate such dams. The seven river
catchments are Mogalakwena with MAR of 268.8 million nr', Lephalale (149.4 million m') and
Mokolo (315.6 million rrr') in the Limpopo WMA and the Groot Letaba (380.9 million nr'),
Middle Letaba (151.9 million rrr'), Luvuvhu (362.9 million nr') and Mutale (157.1 million nr') in
the Luvuvhu- Letaba WMA. Of the seven catchments, three are in the Limpopo WMA and four
are in the Luvuvhu-Letaba WMA and this affirms the point that the latter WMA had more
available water.
The range of MAR is from 24.5 million m3 for Nwanedi River to 315.6 million m3 for the
Mokolo River in the Limpopo WMA and 41.3 million rrr' for the Lower Letaba to 380.9 million
m3 for the Groot Letaba in the Luvuvhu-Letaba WMA. These wide ranges show a large variation
of MAR from one river catchment to the other, thereby revealing large differences in potential
for development of dam storage across the catchments.
(b) Water storage capacity of major catchments under study
KeIler et al. (2000) alluded to the fact that dam storage captures water when and where its
marginal value is low and can then reallocate it to times and places when and where its marginal
value is high. For the area under study, the MAR of river catchments varies from one season to
the other, and also differs from one catchment to the other (Figure 4.2) and this necessitates the
development of dam storage.
The river catchments for the two WMAs under study were semi-closed with larger outflows to
the oceans during rainy seasons and less during dry seasons. As a result, dam storage allowed for
this scarce resource to be captured during the rainy season when the MAR was high, thereby
reducing the amount of water lost to the oceans, and availing it to be stored for the dry season
when the MAR is low, thereby increasing the supply during this time of scarcity. The storage
capacity for all the dams in each river catchment was added up to obtain the total storage
capacity of the catchment, referred to as catchment storage capacity (Table 4.1).
85
Table 4.1 Storage capacity and available MAR for possible development of new dams in river
catchments of the Limpopo and Luvuvhu-Letaba WMAs (DWAF, 2003; DWAF, 2004b)
Storage
capacity + Available MAR
5% MAR for for possible
Water Storage ecological development of
Management MAR capacity reserve new dams
Area Catchment (million mj) (million mj) _(million mj) (million mj)
Limpopo Nwanedi 24.5 20.6 21.8 2.7
Nzhelele 89.4 57.8 62.3 27.1
Sand 71.9 22.1 25.7 46.2
Mogalakwena 268.8 73.6 87.0 181.8
Lephalale 149.4 5.2 12.7 136.7
Mokoio 315.6 145.9 161.7 153.9
Matlabas 66.3 0 3.3 63.0
WMA total 985.9 325.2 374.5 611.4
Luvuvhu-
Letaba Lower Letaba 41.3 0.0 2.1 39.2
Groot Letaba 380.9 265.7 284.7 96.2
Middle Letaba 151.9 250.0 257.6 -105.7
Shingwedzi 89.9 0.0 4.5 85.4
Luvuvhu 362.9 240.0 258.1 104.8
Mutale 157.1 3.9 11.8 145.3
WMA total 1184 759.6 818.8 365.2
In order to establish accurate estimates of available catchment MAR for possible development of
additional storage, provision was made for the requirements of the ecological reserve. In
accordance with the findings by Hughes (2005), this was calculated at 5% of existing catchment
MAR.
The total storage capacity ofriver catchments in the Limpopo WMA was 325.2 million m3 (33%
of MAR) while that of the catchments in the Luvuvhu-Letaba WMA was 759.6 million rrr'
(64.2% of MAR). Four river catchments had a storage capacity> 100 million m3 and had major
dams. The four rivers are the Mokolo in the Limpopo WMA with a storage capacity of 145.9
million m3 and the Groot Letaba (265.7 million rrr'), Middle Letaba (250 million nr') and
Luvuvhu (240 million m3) in the Luvuvhu-Letaba WMA. The results reveal that more runoff is
86
stored in the Luvuvhu-Letaba than that in the Limpopo WMA (Table 4.1) suggesting that the
latter WMA was less developed in terms of water storage infrastructure.
Accordingly, the Limpopo WMA had 611.4 million rrr' of available MAR for possible
development of new dams compared to only 365.2 million m3 for the Luvuvhu-Letaba WMA.
These results show that opportunities for development of additional storage infrastructure are
more in the Limpopo than in the Luvuvhu-Letaba WMA, and this is contradictory to the view of
DWAF (2004a). Based on these results, the Limpopo WMA should be given more priority for
development of new darns than the Luvuvhu-Letaba WMA.
Five river catchments in the study area had available MAR > 100 million rrr' for possible
development of the new dams and should be targeted for this purpose. The five rivers are the
Mogalakwena (181.8 million m3), Lephalale (136.7 million rrr') and Mokalo (153.9 million nr')
in the Limpopo WMA and the Luvuvhu (104.8 million m3) and Mutale (145.3 million nr') in the
Luvuvhu-Letaba WMA.
For the Luvuvhu-Letaba WMA, it was revealed that the Middle Letaba catchment had available
MAR of -105.7 million m3 for possible development of additional storage. This negative figure
occurred as the present storage capacity is larger than the catchment MAR. As revealed by
DWAF (2004b), the major contributor to the storage capacity that exceeded the catchment MAR
was the 184.2 million m3 Middle Letaba Darn built in a catchment with MAR of 151.9 million
m3, with smaller darns in the catchment exacerbating the situation. The situation was reported to
have been caused by the misplacement of the darn due to the political situation of the time.
On the contrary, the Mutale catchment had the highest available MAR (145.3 million rrr') in the
WMA for possible development of new darns as only a small storage capacity of 3.9 million m3
had been developed. It is therefore recommended that priority for development of new dams be
given to the Mogalakwena, Lephalale and Mokalo river catchments in the Limpopo WMA and
to the Luvuvhu and Mutale catchments in the Luvuvhu-Letaba WMA.
87
(c) Influence of catchment runoff on storage capacity
As stated by Mostert (2008), the degree of water availability depends on the magnitude of
storage capacity in addition to the amount of runoff. For water stressed countries, it would be
expected that the development of storage infrastructure should be influenced by the amount of
runoff, and this would be the situation in the study area (Figure 4.3).
300
250
Ë
c
~ 200
'Ë
':v:- 150
c""..
'.."..
<U
"" 100.es
V') SO
0
0 so 100 150 200 250 300 350 400
Mean annual runoff (million m'))
Figure 4.3 Influence of runoff on storage capacity of river catchments of Limpopo and
Luvuvhu-Letaba WMAs
There was a moderate to strong correlation (R2=0.6752) between runoff and storage capacity of
the river catchments in the Limpopo WMA (Figure 4.3). As revealed by the graph (Y=0.382x -
7.3388), an increase in MAR was accompanied by an increase in water storage capacity. The
results indicate that more storage infrastructure was developed in catchments with more runoff.
Storage infrastructure was therefore properly planned taking catchment runoff into consideration.
A moderate to strong correlation (R2=0.6228) was also recorded between runoff and storage
capacity of catchments in the Luvuvhu-Letaba WMA. The graph (Y=0.7647x - 24.309) also
shows an increase of storage capacity with an increase in catchment runoff. The steeper gradient
of the graph for the Luvuvhu-Letaba WMA suggests a larger increase of storage capacity per
increase of catchment runoff and is in accordance with the fact that 64.2% of runoff was stored
in this WMA compared to only 33% in the Limpopo WMA. Contrary to the picture presented by
88
the Middle Letaba Dam, the rest of the dams in the Luvuvhu-Letaba WMA were well designed
with due consideration made of available runoff.
4.3.2 Runoff and storage capacity of municipalities in the study area
The runoff and storage capacity of municipalities are important determinants of their water
availability.
(a) Runoffs of municipalities in the study area
Although water in South Africa is a national resource (RSA, 1998a; DWAF, 2004a), analysis of
the amount of runoff across the area of a municipality is important. Knowledge of runoff of
municipalities assists in identifying those in which strategic water projects could be initiated for
developmental activities. The projects would be of economic benefit to municipalities that would
otherwise have to be supplied from storage infrastructure that is a long distant away, and this
could be costly.
Adoption of rainwater harvesting practices improves water supply for domestic and productive
purposes. For instance, on-farm storage ponds and in situ rainwater conservation systems such as
conservation tillage are possible strategies for upgrading rainfed agriculture in semi-arid
environments (Ngigi ef al., 2006). The runoffs of study municipalities was calculated from those
of quaternary catchments located in the municipalities (Figure 4.4).
The total MAR of the study municipalities in the Limpopo WMA was 602.7 million rrr' while
that of the Luvuvhu-Letaba WMA was 898.3 million m3 The MAR of Luvuvhu-Letaba WMA is
larger than that of Limpopo WMA by almost 50%, suggesting that the former had a larger
quantity of available water.
89
Makhado ig~~Hg~ll~~~H~Ii~J~~gH26~9~.~2t~~~~~i~~i I---M-u-s-in-a---' ii 2:1
0
C-
nl o L.eph a Ia Ie IHHHi!lliHHHHniHH~aHHiUiH 282.1
0.. I
U E::::; POlokwane H 17.9
n
W _._-_A_gan-an-g - :i 12..5M c ...
A ~WMA TO;TAL:Ëii1!Hilif.il;!i!mj~iliiihliiiiliiimjitilii11iij~!11ii!miiilijiili:liillljlli;i1jl!!,;.;6027a pn ad .mc .l:.".
t ~:::.
y .s:::;>
:::0 Giyani nm 37.5
_=>>,
Mutale mmli 61.2
~~~:~~~~~J~~~!~~~!i~~~~l~~!~.~~~ili!~~l~!!~~~i!~!!!~~!~!~~!:~i!~:!l~I±'~I~!ti~1~t.!!~!t.!~~~i~~~~!~~~!ï!!!~~~~~I!~!~i!~!~!!~!!t.t~~i~:~!!i:!~~.~~~!
o 200 400 600 800 1000 J
Mean ann_ual runoff In rnlllion m3 (1960-1996)'-----------_ .._._-- --_._. __ .. ..- . -_.__._--_.__ ..__._-----
Figure 4.4 Mean annual runoff (MAR) of municipalities of the Limpopo and Luvuvhu-Letaba
WMA (Midgley et al., 1994)
Four municipalities had MAR> 100 million m3 and were the locations of the larger quantities of
available water. The four municipalities are Makhado (269.2 million rrr') and Lephalale (282
million nr') in the Limpopo WMA and Thulamela (359.1 million nr') and Tzaneen (352.3 million
nr') in the Luvuvhu-Letaba WMA. Of the four municipalities, the two in the Luvuvhu-Letaba
WMA had larger amounts of available water than their counterparts in the Limpopo WMA.
(b) Water storage capacity of municipalities under study
The water storage capacity of a municipality determines the available MAR for possible
development of new strategic water related projects not fed from major impoundments. These
strategic water projects would include on-farm ponds and conservation tillage for upgrading
rainfed agriculture in semi-arid environments (Ngigi et al., 2006). When more storage capacity is
available in a municipality, less MAR remains to justify development of such strategic water
projects.
90
Dam storage capacity refers to the full supply capacity of a dam and therefore represents the
maximum capacity that the dam has to store water. Municipal storage capacity was calculated as
the total of the storage capacity of dams in a municipality and therefore represents the maximum
capacity that a municipality has to store water (Table 4.2).
Table 4.2 Storage capacity and available MAR for possible strategic water related projects in
selected municipalities of the Limpopo and Luvuvhu- Letaba WMAs (DWAF, 2003; DWAF,
2004b)
Storage
capacity with Available MAR for
ecological possible
Water Storage reserve at 5% development of new
Management MAR (million capacity of MAR strategic water
Area Municipality m3) _(_millionm1_ _(million m3) projects (million m3)
Limpopo Makhado 269.2 32.9 46.4 222.8
Musina 21.0 0.0 I.l 20.0
Lephalale 282.1 145.9 160.0 122.1
Polokwane 17.9 13.2 14.1 3.8
Aganang 12.5 0.0 0.6 11.9
WMA total 602.7 192.0 222.1 380.6
Luvuvhu-
Letaba Letaba 88.2 2.0 6.4 81.8
Thulamela 359.1 218.8 236.8 122.3
Tzaneen 352.3 243.3 260.9 91.4
Giyani 37.5 213.5 215.4 -177.9
Mutale 61.2 20.6 23.7 37.5
WMA total 898.3 698.2 743.1 155.2
The total storage capacity was 192 million m3 (31.9% of municipal MAR) for Limpopo WMA
and 698.2 million m3 (78.2% of MAR) for Luvuvhu-Letaba WMA (Table 4.2) implying that the
latter WMA is more developed in terms of storage capacity. Four municipalities had storage
capacity> 100 million nr', and those were Lephalale (145.9 million nr') in the Limpopo WMA
and Thulamela (218.8 million nr'), Tzaneen (243.3 million nr') and Giyani (213.5 million rrr') in
the Luvuvhu-Letaba WMA. The results reveal that municipalities in Luvuvhu-Letaba WMA
were more developed in terms of water storage infrastructure than those in Limpopo WMA.
91
The available MAR for possible development of new strategic water related projects was 380.6
million m' (63.1% of total MAR) for Limpopo WMA and 155.2 million m' (17.3% of total
MAR) for Luvuvhu-Letaba WMA. These results imply that the Limpopo WMA offers a larger
opportunity than the Luvuvhu-Letaba WMA for development of new strategic water related
projects. Such water related projects should be prioritized for municipalities with larger available
MAR ( > 100 milliom nr'), namely: Makhado (222.8 million rrr') and Lephalale (122.1 million
nr') in the Limpopo WMA and Thulamela (122.3 million nr') in the Luvuvhu-Letaba WMA.
The reduction of the available MAR for the Luvuvhu- Letaba WMA was worsened by the
anomaly at the Giyani Municipality were storage capacity exceeded MAR, resulting in available
MAR for possible development of additional storage being -177.9 million nr'. This anomaly was
a result of the large Middle Letaba Dam with storage capacity of 184.2 million m3 built in a
catchment with a lesser MAR of only 151.9 million nr'. In terms of the plan, the dam was to have
been built downstream from its current position, and this had to be changed because of lack of
political consensus on the original site.
4.4. Summary and conclusion
The results of the investigation in this chapter revealed that there is more available water in the
Luvuvhu-Letaba (total MAR=1 183.9 million rrr') than in the Limpopo (985.9 million nr')
WMA. There was a wide range of MAR from one catchment within a WMA to the other and this
indicated large differences in potential for development of dam storage across the catchments.
The total storage capacity of river catchments in the Limpopo WMA was 33% of MAR while
that of the catchments in the Luvuvhu-Letaba WMA was 64.2% of MAR, revealing that the
latter WMA had more storage capacity. Accordingly, the Limpopo WMA had a larger available
MAR of611.4 million m3 for possible development of new dams compared to only 365.2 million
m3 for the Luvuvhu-Letaba WMA. Also, the municipalities in the Limpopo WMA had a larger
\ available MAR of 380.6 million m3 for implementation of strategic water related projects
compared to 155.2 million m3 of those in the Luvuvhu-Letaba WMA.
92
The results suggest that the Limpopo WMA should be prioritized for development of new dams
and strategic water related projects. The development of new dams should prioritize the
Mogalakwena, Lephalale and Mokoio river catchments in the Limpopo WMA and the Luvuvhu
and Mutale catchments in the Luvuvhu-Letaba WMA. As for strategic water related projects,
priority should be given to Makhado and Lephalale municipalities in the Limpopo WMA and
Thulamela municipality in the Luvuvhu-Letaba WMA. Although the Limpopo Province is water
scarce, adequate runoff still occurs in some catchments to warrant the construction of new dams
for increased water storage.
93
CHAPTERS
5 RAINFALL INFLUENCE ON WATER GAIN AND LOSS FROM MIDDLE
LETABADAM
5.1 Introduction
The demand for water exceeds supply in many parts of the world, and more areas are expected to
experience this imbalance in the near future. Increased scarcity of water is predicted to occur as a
result of increasing population and resource demand per capita. The increased scarcity of water
will continue to affect life negatively as the resource is required for domestic, industrial,
agricultural, recreational and environmental uses (Vairavamoorthy ef al., 2008).
Water storage has become important, and man enhances the storage by constructing dams to
impound water (KeIler ef al., 2000; Muller, 2000). According to KeIler ef al. (2000), storage of
water in dams allows for the resource to be captured in periods and places of abundance and
availed for use in periods and places of scarcity. Dams support economic, social and cultural
activities and the functioning of ecosystems (Saiko andZonn, 2000; Mostert, 2008) through their
water supplies for household, industrial, irrigation and ecological requirements (Katambara and
Ndiritu, 2009). As revealed by Inocencio ef al. (2003), construction of dams is an obvious
response to the problem of water scarcity.
Dams are often characterised on the basis of their storage volume as small or large. According to
BOR (1987) and ICOLD (1998), small dams are those with storage volumes generally less than
0.75 million m3 while large dams have storage volumes of 1 million m3 or more. Some dams are
excessively large, for example, the total annual withdrawal of the world's largest dam is 3 800
krrr' (Gleick, 1998) while the design storage capacity of the largest dam was recorded to be about
6 000 krrr' (LeComu, 1998).
94
The ability of a dam to supply water for different uses is dependent on its water gain and loss and
these are influenced by the amount of rainfall it receives. The water gains are inputs (rainfall and
inflows) while the losses are outputs (evaporation, abstractions, and outflows), and these result in
changes in storage (ORMCP, undated).
The purpose of this study was to investigate the influence of rainfall received over the surface
area of the dam on water gain and loss and on water storage volume of the Middle Letaba Dam
in the Luvuvhu-Letaba WMA. The gain components investigated were the rainfall itself and
inflow from the source river while the loss components were potential evaporation from the dam
and outflow (inclusive of domestic and industry supplies, irrigation and normal flows). The study
was necessary to assess whether the dam would ever fill up to its capacity and allow for
increased supply of water (Section 1.4, Table 1.3, specific objective 4).
5.2 Methodology
5.2.1 Dam location and physical characteristics
The Middle Letaba Dam is on the Middle Letaba River which is part of the Letaba catchment of
the Luvuvhu-Letaba WMA. The catchment is located in a semi-arid region in the north-eastern
part of South Africa. The western part of the catchment is mountainous with an altitude higher
than 2 OOOmabove mean sea level, and that decreases gradually towards the eastern part to
slightly below 450m above mean sea leve'. The Middle Letaba River originates from the
mountainous region and flows towards the lower eastern part of the catchment (Katambara and
Ndiritu, 2009).
The dam is located within the South African Quaternary Catchment (QC) number B82D with an
area of 632km2 while its total catchment area is 1 806km2 (Midgley et al., 1994). Specifically,
the dam is located at 30024'4.68"E and 23°16'16.967"S. Smaller dams such as Lorna Dawn and
Altenzur Dam occur in the same catchment upstream of the Middle Letaba Dam (Figure 5.1).
95
LOCALrr,' :'tU,
Figure 5.1 Location of the Middle Letaba Dam (blue water body) in the Middle Letaba
Catchment (grey line) within the Luvuvhu-Letaba WMA (red line)
At full supply, the dam has a surface area of 1 926ha and a head of 18m with the lowest outlet at
-0.520m. The gross full supply capacity is 184210 000m3 while the net supply capacity is 171
930 000m3 (DWAF, 2004a), making the Middle Letaba the largest dam in the WMA when full
supply capacity is considered.
5.2.2 Sampling procedure
The Middle Letaba Dam was purposively sampled for the study because of its water storage
volume that was persistently low making water use communities to experience continued
shortage of the resource. Leedy and Ormrod (2010) described purposive sampling as the
selection of study units for a particular purpose. The purpose of selecting the Middle Letaba Dam
96
was to investigate the influence of the rainfall received over the surface area of the dam on its
water gain and loss components and to subs~quently identify the causes of persistent low storage
volume.
As a result of the low water storage volume, the dam completely failed to supply water during
July 1994 to February 1995 (DWAF, 2004b). Domestic demand in this period was met by
pumping water from dead storage into the outlet tower. The dam continues to fail to supply water
to the targeted communities of Giyani Municipality, making it arguably the most water stressed
municipality in the Limpopo Province.
5.2.3 Data collection and analysis
The data for rainfall and related water gain and loss components of the Middle Letaba Dam was
obtained from the Department of Water Affairs. The department collected the data at the dam
site over a period of 20 years from 1990 to 2009 (DWAF, undated).
The data was organized using spread sheet to perform relevant calculations and to draw graphs to
illustrate relationships between rainfall and the water gain and loss components. This method of
data analysis was in accordance with Leedy and Ormrod (2010) who indicated that electronic
spreadsheets can quickly and easily organize the data and make simple calculations once the data
is entered into the sheets.
5.3 Results and discussion
5.3.1 Rainfall received over the surface area of the dam
Rainfall is the fundamental driving force and pulsar input behind most hydrological processes
(Schulze, 1995) and is in fact a major source of water for a dam (Nath and Bolte, 1998).
According to Kongo and Jewitt (2006), the hydrological response of a dam can generally be
defined as its reaction to rainfall. The mean monthly rainfall received over the surface area of the
Middle Letaba Dam varies across different seasons of the year (Figure 5.2).
97
140 --.----- -.-.----.- --- .-..- -- --.--.----..---------- .-.- - -..
120 115 119
I ~ ~ .100 .-.~ .."~. ..-. . ..-.- _-.- .-..-.-.. . - --···--·s7···
~ 80· --~-- ..~... '70---···· -- .. _ _.. - _. ._.._ _ _ 76. _ ..~.
S 60 _ ~_. .~ _.__~ .. _... .. __ _._ .._ _._. ~- ..-.-~ --
~ ~ ~ ~ 37 ~ ~
~ 40 -
20 -~I-~--I~--3I0---~-- ~ " ~-~---~---7,--- 5~-i-1-1--1-
o .~ 1 ~·r·~ r·~ 1 ~ 1 .,,,. r;SS: 1 ~~ 1 ~ r ~ T~··T·~l
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Time (months)
Figure 5.2 Mean monthly rainfall received over the surface area of the Middle Letaba Dam
during 1990- 2009 (DWAF, undated)
According to Figure 5.2, the rainfall received over the surface area of the dam was high for
summer months with 76mm recorded for November, 87mm for December, and 115mm for
January. High rainfalls were also received during February (119mm) and March (70mm) with
lesser amounts received in the rest of the months. The least rainfalls occurred in June (2mm).
The rainfall increased through spring from September (25mm) to October (37mm), and
continued to increase in the summer months. The dam received high rainfall in summer with
higher falls coming later during the early to mid-autumn. This pattern of rainfall is similar to the
general trend in the WMA. It would be expected for the dam to gain more water from direct
rainfall during the higher rainfall months.
5.3.2 The influence of rainfall on inflow from source river
The rainfall received over the surface area of the dam would likely also occur in some parts of
the catchment and this would be expected to influence inflow from the source river. This inflow,
often referred to as streamflow, consists of the above-dam runoff from the catchment where the
dam is located and the runoffs from all upstream catchments. Runoff was defined as the water
98
yield from a given catchment and consists of stormflow, baseflow and seepage (Schulze, 1995;
Fargo, 2002; Webb, 2005).
The magnitudes of stormflowand baseflow after a rainfall event are influenced by the condition
of the land surface. Land with more vegetative cover promotes baseflow while that with lesser
vegetative cover promotes stormflow (Chandler, 2006; Heck et al., 2006) and this could have
some effect on the amount of inflow at a given time. Land use in the catchment upstream of the
Middle Letaba Dam is characterized by irrigated crop farming where tomato is the major crop.
The irrigated area varies during the cropping season from 2 100ha to 3 700ha with irrigation
water pumped directly from the river (DWAF, 2004b). This type of land use results in lesser
vegetative cover which promotes storm flow. The monthly inflows from the source river were
calculated based on dam surface area to determine the extent to which the inflows would affect
the level of the dam (Figure 5.3).
Although rainfall started to increase in September (25mm), inflow remained low at 114mm. It
was only when rainfall continued to increase in October (37mm) that the inflow from the source
river increased from to 271mm, showing a time lag of inflow response to rainfall increase. As
rainfall continued to increase through November to February, inflow increased up to March.
While the peak of rainfall was recorded in February (119mm), that of inflow only occurred in
March (8 764mm), presenting a time lag of one month from the highest rainfall received over the
surface area of the dam to maximum inflow from the source river.
As revealed in Figure 5.3, occurrence (or increase) of rainfall received over the surface area of
the Middle Letaba Dam was accompanied by an increase of inflow from the source river with a
time lag of one month. With the catchment area upstream of the dam often under irrigated
cropping with sparse cover, land use patterns may not adequately explain the one month time lag
from peak rainfall to peak inflow. The time lag could have resulted from a number of factors,
and these include spatial distribution of rain gauges and the occurrence of small dams in the
catchment upstream of the Middle Letaba Dam (Figure 5.1).
99
10000 ..-.-.-.-- -.----.-.-. - --.------.-..---.-. - _- .-.--...... -_ .-..---.-.--.-.-..--.- - --.--.-. -.-.- --- ------ -.-.-.-. - - -
~ 9000 +------------87-6~4-------------------------------------------
Ee 8000 ·--···-·-·--···-·--·--·-·-·····-·····-ll!J! --- -..--.---- ---.-.- ..- -.-.--------- ..-------- ..--- ..------.- ..-.... ..-.--- ..--.- - - -.-.-- ..---
~ 7000
É. 6000 -+-------
:~.;5: 5000 ..- ---.-.--
4.-8.5-3---
] 4000
IV
~
.~ 2000·· --"---
Ens
Q
Jan Feb Mar Apr May Jun Jul Aug Sep act Nov Dec
Time (months)
II Rainfall III Inflow
-- ---.-.--- .-..-.---.-.----.-.--------i--- .-.- -~--._-.-.---_.-..-. _--_._.-.--._--.--N._. . _ _ .__ ._. ·· ._· __.J
Figure 5.3 Mean monthly rainfall and inflow to the Middle Letaba Dam during 1990 - 2009
(DWAF, undated)
The occurrence of other dams in the catchment upstream of the Middle Letaba Dam supports
Katambara and Ndiritu (2009) who revealed that there are many farm dams in the Letaba River
system. The time lag from peak rainfall to peak inflow is probably a result of the need for filling
time for these upstream dams before the runoff may flow over to the downstream Middle Letaba
Dam. The time lag may also be a result of spatial variation of rainfall upstream of the dam.
5.3.3 Rainfall influence on evaporation from the dam surface
The term evaporation includes potential and actual evaporation where the former is defined as
the evaporative demand of the atmosphere and occurs when there is unlimited supply of water
while the latter reflects the actual amount of water evaporated from the soil and includes
situations of limited supply of the resource (de Silva, 1999). The evaporation from dam surface
reflects a situation of unlimited supply and is therefore regarded as potential evaporation.
100
The estimates of the amount and rate of potential evaporation are required in water resource
management for a variety of purposes such as the design of dams, catchment water balance
studies and municipal and industrial water supply (Mengistu and Savage, 2010). An investigation
of the influence of rainfall on potential evaporation from the Middle Letaba Dam is important for
better understanding the hydrology of the dam. The influence of temperatures on potential
evaporation is important and hence temperature in included in the investigation (Figure 5.4).
TIme (months)
Figure 5.4 Mean monthly rainfall and evaporation from the Middle Letaba Dam during 1990 -
2009 (DWAF, undated)
Figure 5.4 reveals that potential evaporation from the surface area of the Middle Letaba Dam
was higher than rainfall for the twelve months of the year and this could be reason for levels of
the dam to be often low and for its failure to supply water during July 1994 to February 1995
(DWAF, 2004b). Actual evaporation from the dam surface increased with rainfall and was
accordingly higher during summer compared to winter months. The potential evaporation (in
rnm/month) could not have been influenced by changes in the surface area of the dam due to
101
changes in rainfall as the evaporation was based on the existing dam surface area. The results
reveal that rainfall had no influence on the potential evaporation from the Middle Letaba Dam.
As shown in Figure 5.4, the temperatures (both maximum and minimum) at the dam changed
with months of the year with higher temperature recorded in the summer compared to winter
months. Higher temperatures were associated with higher potential evaporation. The higher
temperatures resulted in more energy being available to evaporate the water and hence the
changes in potential evaporation across the months were caused by temperature changes.
5.3.4 The influence of rainfall on outflow from the dam
Outflow from the Middle Letaba Dam includes supplies to households and industry, irrigation
and normal flow. The water supplied to households and industry is for primary consumption and
is regarded as a priority. The water supplied for household is used for domestic and productive
activities while that for industry is used for processing activities. In order to understand the uses
of household and industrial water supplies, it is important to consider the population and
economic activities (Johnson, 2001; Kojiri, 2008).
A total of 2 400ha has been developed for irrigation from the Middle Letaba Dam. The irrigation
water demand to serve this area is estimated at 21 million m3la. As a result of water shortages
and the increased use of the resource for household purposes, the area irrigated is estimated at
1 300ha with a mean annual field edge requirement of 10.3 million m3/a (DWAF, 2004b). With
the continued increase of water demanded for household use, the amount of the resource
available for irrigation and hence the area covered could currently be much lesser.
Normal flow also comprises an important part of outflow. Most streams contain, in legal terms,
'public' water, and therefore downstream riparian and other users have a right to a certain
amount of water that would likely have been available as stream flow, had the dam not been
constructed. As a result, a compulsory release of water from the dam called 'normal flow' has to
be discharged downstream (Schulze, 1995). A portion of the normal flow is used to satisfy the
102
requirements for the ecology. The relationship between monthly rainfall and outflow from the
Middle Letaba Dam should be assessed for one to understand the hydrology of the dam (Figure
5.5).
800
~ 700
;05;: ? 600
"C0 .c.
_nl- E
0 500
.......
..:s! E 400.n.l. _E_
E 300
nl
Q 200
100
0
Rainfall l15 119 70 I 2 7 I I 37 76 87
House+industrv 12 10 11 10 11 10 11
I 11J11I11 11 D
80 71 ; 77 I 73 80 69 74
I 74 I 76 80 77 77
4 1 676 I 130 27 8 3 1 I 1 I 1 1 1
Time (months)
Figure 5.5 Mean monthly rainfall and outflows from the Middle Letaba Dam during 1990-2009
(DWAF, undated)
Abstractions for household and industry and for irrigation were almost constant throughout the
year (Figure 5.5). According to Nyabeze et al. (2007), the operating rules of the Middle Letaba
Dam indicate that 100% of the water demand for household and industry and for irrigation would
be supplied when the dam is full. When the reservoir is 30-50% full, 70% of the water
requirements for household and industry would be supplied while 35% of water demand for
irrigation would be supplied. The fact that the abstractions for the use sectors were constant
throughout the year suggests that rainfall did not result in adequate rise in dam level to allow for
increase in water supply as guided by the operating rules.
103
Contrary to the other components of outflow, normal flow seemed to have been influenced by
rainfall. While the rainfall increased from September to December, normal flow remained
constant at 1 mm/month. With continued increase in rainfall in January, normal flow picked up
to 4 mm, but this was followed by a drop back to 1 mm in February, a month in which the
highest rainfall was recorded. The highest amount of normal flow occurred in March with a
mean of 676 mm recorded. This flow was exceptionally high and resulted from the floods in the
years 2000 and 2001.
5.3.5 Rainfall and dam water storage volume
The dam water storage volume reflects the quantity of water stored in a dam at a particular time.
The dam storage volume is a product of the interactions of water gain with water loss
components. If water gain components bring more water to the dam with water loss components
remaining constant, the dam storage volume will increase and vice versa.
Rainfall is an important water gain component which has a positive influence on the other gain
component of inflow and different influences on loss components. An investigation of the
relationship between the rainfall and dam storage volume is therefore necessary for proper
planning of water supply and use issues (Figure 5.6). The dam storage volume was presented as
dam level (in mm/month) based on the dam surface area of 1926 ha.
Figure 5.6 seems to be showing an inverse relationship between rainfall and dam storage volume.
As the rainfall increased from September to December, dam storage volume decreased. This
trend discontinued in January to February in which case a positive relationship occurred, i.e. dam
storage volume increased with an increase in rainfall. The inverse relationship generally recurred
from March through to the winter months.
104
4500 ."._ -.-. _.--.-.- -.-.-- -.-.--- -.--- .-.-.-.-.------.--.-.-.-.--.-.- -.-. ----- --.-.-.--.-.----- -- -.----.- .-.-.----.
Figure 5.6 Mean monthly rainfall and dam storage volume of Middle Letaba Dam during 1990-
2009 (DWAF, undated)
Increases in rainfall during September to December were accompanied by decreases in dam
storage volume. As rainfall continued to increase in January (115mm), dam storage volume also
increased (3 280mm). As rainfall increased to its peak in February (119 mm), further increased
dam storage volume was recorded (3 494mm), with larger storage volume registered in March (4
104mm) when rainfall actually started to drop. As the rainfall dropped sharply in April (30mm),
dam storage volume increased slightly to a peak of 4 184mm. With the rainfall remaining low
through winter months, dam storage volume gradually decreased. The peak storage volume of
4 184 mm represents 80.6 million m3 which is far less than the 184,210,000m3 design storage
capacity of the dam, an assertion of the view that the dam levels are persistently low.
The peak of rainfall was recorded in February, that of inflow was in March and the highest dam
storage volume was in April (Figure 5.6). The results reveal a time lag of two months from the
peak of rainfall to that of darn storage volume. Again the time lag could have resulted from
factors such as the spatial distribution of rain gauges, spatial variation of rainfall and the
occurrence of small darns in the catchment upstream of the Middle Letaba Dam.
lOS
The apparent inverse relationship between rainfall and dam storage volume should be a result of
the two months time lag between the two factors of the hydrology of the dam. Detailed analysis
is necessary to clearly show the effect of the two months time lag between peak rainfall and
storage volume (Figure 5.7).
90 rww.w.w •••• wwmm._m.m ••• m ••••••••••••_•m•m_ ••••• mm •••••••••••• _m ••m __ mm.mm ••••mm ••m •• _m •• _mm_ •••••_ ••• m ••• mm __ •• _mmmm ••• m •••
~ 80 -~~.:::+--- ._. --_.------------. __ .-.-..-.-------.---.--- ...
~ 70 _ ~=-~ __~_~~ __
g 60 .-.-- -.-..-.--- ...........-...•..•.•- -_ .........•_.._... __ __ ..__.•.........._.._..._..............._.._...._..•............._.._•.....•......_..~.._. ..__.........._..._•.•.._.. .
.:.
al 50 --!--- ---.---.-.--- __ _._... ._. ._. _._._.._.._ w •••• __ •__ ._ ••••• __ _ •••• _ •••••• _._ .. __ ••••••• _._
E
ë:5:J 40 -1------------ . .__. . _
::::.
~ 30 ·····.··.·····w· •••••• _..... ••••••••••••••••••••••••••••••••••••• ·····················y··=····;;;0·;·r4·1·9x··.+···77·;·.S7.9
~ 20 -1--- ...:.R..:_2_=---=0:..:...8:=;..O=8.;;;:6 _
E
1'0
Cl 1° ---.-.--.-.----- ._._._.__. _._.
0· ." 1' ········.·.············1··.·.···· ··············..···..,." j ·················f ·······",,·· ..·,,··················r ..... ···············r······ ····················.·.·············..··t
o 20 40 60 80 .100 120 140
2-mont:h lag rainfall (mm)
L-- . . __.. .._ _._. .__. _._
Figure 5.7 Correlation between mean monthly rainfall with a 2-month lag and dam storage
volume of Middle Letaba Dam during 1990-2009 (DWAF, undated)
A strong correlation (R2=0.8086) occurred between rainfall lagged by two months and dam
storage volume. This result shows that occurrence of rainfall had a strong influence on dam
storage volume although this influence would usually be evident after two months from the
rainfall event when the rainfall itself had stopped (or decreased). Consequently, the slope of the
graph is negative, suggesting an inverse relationship in which occurrence of rainfall would lead
to a decrease in dam storage volume and vice versa.
The peak water storage volume of 80.6 million m3 compared to dam design storage capacity of
184,210,OOOm3suggest that the dam can never be filled from rainfall, but will require transfer of
water from other catchments to fill up. It is recommended that a detailed study of the water
106
balance of the dam be carried out to obtain more information about the water status of the
reservoir.
5.4. Summary and conclusion
The rainfall received over the surface area of the Middle Letaba Dam was high in summer and
low in winter months with the peak in February (119mm) and the least in June (2mm). The
rainfall had a positive influence on inflow from the source river with a time lag of one month
from the peak of rainfall to that of inflow.
Although there seemed to be a positive relationship between rainfall received over the dam
surface area and the potential evaporation from the dam, the two hydrological factors had no
influence over each other. The potential evaporation was rather influenced by the temperatures at
the dam site. The rainfall influenced normal flow as a component of outflow and such influences
were only evident during years of large rainfalls (floods). Abstractions for household and
industry and for irrigation were not influenced by rainfall and this was because these components
of outflow are controlled under strict operation rules of the dam.
Dam storage volume also increased with increasing rainfall with a time lag of two months from
peak rainfall to maximum storage volume. There was a strong correlation (R2=O.8086) between
rainfall lagged by two months and dam storage volume. The time lag between rainfall and inflow
from the source river and that between rainfall and storage volume were probably a result of the
spatial distribution of rain gauges, spatial variation of rainfall and the occurrence of small dams
within the catchment upstream of the dam.
The dam storage volumes were very low compared to dam design capacity suggesting that the
dam cannot be maintained at a desirable full level from only the rainfall (including inflow), but
will need to be filled through transfers from other catchments.
107
CHAPTER6
6 PERCEPTIONS OF MUNICIPAL WATER MANAGERS ON WATER
RESOURCES, USES AND RESTRICTIONS
6.1 Introduction
The perceptions of municipal water managers on water resources and their uses reflect the
amount of knowledge they have on the resources and have a strong influence on their decisions
regarding the management of the resource. To make appropriate water management decisions,
the water managers must be exposed to relevant knowledge usually scientifically generated by
experts. According to Hermans, (2008) water experts expressed concern that their knowledge is
insufficiently used (Section 3.3.1(a». The lack of use of knowledge makes the task of
overcoming the world water scarcity one of the most formidable challenges on the road to
sustainable development (Alexander, 2002).
In addition to expert knowledge produced scientifically, municipal water managers should also
have local based traditional knowledge in order to respond appropriately to community needs.
Traditional response to inadequate water supply is associated with social adaptive capacity
described by Ashton and Haasbroek (2002) as the ability of a society to adapt its patterns of
water resource use to increasingly scarce supplies and achieve a sustainable measure of stability.
In situations where water policy decision makers such as water managers lack knowledge on
water resource or its uses, it is necessary that they be helped to acquire the knowledge. The
participatory process of social learning is one of the relevant approaches for knowledge
acquisition (ICS, 2002; Gunderson and Light, 2006). The concept of 'social learning' refers to
learning by observing others and their social interactions within a group (Bandura, 1977)
(Section 3.3.l(b».
108
The objective of the study was to investigate the perceptions of municipal water managers of
Limpopo Province on water supply, uses and restrictions (Section 1.4, Table 1.3, specific
objective 2) as the perceptions will, upon translation into municipal programs, influence the
management of the water resource and hence the prospects for its availability for socio-economic
development.
6.2 Research methods
6.2.1 Description of study area
The study focused on ten municipalities from two WMAs, the Limpopo and the Luvuvhu-Letaba
WMAs. The municipalities covered by the study were Makhado, Musina, Lephalale, Polokwane
and Aganang for the Limpopo WMA and Letaba, Thulamela, Tzaneen, Giyani, and Mutale for
Luvuvhu-Letaba WMA (Figure 6.1).
LOCAUTl' MAP
·t·
Loe.1 Munlclp.IIU ••
00 "-"'"~ ......
~·:.:·.:_~ .. lAtlDl
~1I. ... f1~
CJ-·
§104.~
l::Juu •
~uU( ...
CJ-....
'/)ll •.ulMl.
ao.,,,
-U""A;'~
c::::Iv........~Aral
Figure 6.1 Map of the Limpopo Province showing the Limpopo and the Luvuvhu-Leataba
WMAs (red line) and the study municipalities (hatchings)
109
6.2.2 Sampling procedure
Purposive sampling was used to select both the WMAs and the municipalities. The Limpopo and
Luvuvhu- Letaba WMAs were chosen because they are managed under the nearby Limpopo
Regional Office of the Department of Water Affairs (DWA) that would be easily accessible for
information. The five municipalities in each of the WMAs were selected for their readily
available information on runoff and water storage capacity (Section 4.3.2). The municipal
information on runoff and storage capacity was necessary to assess the level of knowledge
managers had on water resources.
6.2.3 Data collection and analysis
A questionnaire was developed for interviewing the water managers of the municipalities
sampled for the study. The questionnaire had two major types of questions, the closed-ended
questions that collected quantitative data and the open-ended questions collecting qualitative data
(Leedy and Ormrod, 2010). The interviews were more structured when dealing with closed-
ended questions and provided limited opportunities for respondents to give more insight on the
aspects covered by the questions. As for open-ended questions, the interviews were less
structured and probed respondents to give more insight on the aspects covered. The study
therefore fit into Hurmerinta-Peltomaki and Nurnmela (2006)'s description of a mixed research.
The focus of the questionnaire was on a range of water supply and use issues, and these included
perceptions on sizes of rivers in the municipalities, water uses for domestic, industrial and
agricultural purposes and issues of resource supply restrictions. The researcher conducted the
interviews himself and this allowed for clarification of the questions that were not immediately
understood by the respondents, ensuring good quality of the data.
Quantitative data was captured and analysed using the SAS package (SAS Institute Inc, 2009).
The Proe FREQ procedure of SAS was used to generate simple frequency tables of occurrence in
each class utilizing one-way tables. The procedure is appropriate to give descriptive statistics
about categorical data such as the demographic datasets. The syntax is provided to the SAS
110
software, which automatically calculates the percentage of observations falling within each
category of response. The output contains both the actual and the cumulative frequencies.
Qualitative data was summarised and analysed using subjective interpretations (Leedy and
Ormrod, 2010).
6.3 Results and discussion
6.3.1 Perceptions on municipal water resources
The perceptions of municipal water managers on water resources have strong influence on how
they will manage the resources and as alluded to by Vairavamoorthy et al. (2008), determines the
extent of availability of water for social and economic uses such as agricultural, industrial,
household, recreational and environmental uses. Surface resources such as rivers are major
sources of water in the study area and their availability and sizes are easier to assess and were
therefore the focus of discussion of the perceptions of water managers.
The number and sizes of rivers are influenced by the direction of flow and amount of catchment
runoffs described by Schulze (1995) as the water yield from a given catchment that consists of
stormflow, baseflow, seepage, normal flow and overflow from any reservoirs within the
catchment. The perceptions of municipal water managers on the number and sizes of rivers in
their municipal areas indicate the managers' knowledge of the water resources (Table 6.1).
Considering the municipalities in the Limpopo WMA, three rivers were reported by the water
manager of Makhado to be flowing through the municipality, namely: Luvuvhu, Mutshedzi and
Nzhelele while two were omitted, the Sand and the Klein Letaba River (Table 6.1). The omitted
rivers are major and were accordingly included among the rivers of the study WMAs (Chapter
4).
The Luvuvhu River was perceived to be the largest, followed by Mutshedzi and last Nzhelele.
The rating of Mutshedzi River as larger than Nzhelele is incredible because the Mutshedzi River
111
is in fact a tributary of the Nzhelele River and as opposed to the Nzhelele River, is not even
included among major rivers in the study WMAs
Table 6.1 Perceptions of municipal water managers on number and sizes of rivers flowing
through their municipal areas
Water Management Municipality Catchment rating
Area
Lim_j)opo Makhado Luvuvhu> Mutshedzi ....s Nzhelele - (Klein Letaba, Sand)
Musina Limpopo> Nzhelele> Nwanedi-S Sand
Lephalale Mokoio > Lephalale ....s M~galakwena - (Matlabas)
Polokwane Sand
Aganang -
Luvuvhu-Letaba Letaba Molototsi
Thulamela Luvuvhu > Mutshindudi > Mbwedi ? Nzhelele - (Shingwedzi)
Tzaneen Groot Letaba> Letsitele
Giyani Klein Letaba> Msami
Mutale Nwanedi ....s Mutale
Key: > means correctly rated larger than; ...s means incorrectly rated larger than;
? means no data to assess rating of larger than; 0 means not enlisted
The incorrect rating of the Mutshedzi River as being larger than the Nzhelele River could have
resulted from the former having a well-known dam, the Mutshedzi Dam which supplies water for
domestic use. The Nzhelele Dam on the Nzhelele River only supplies water for irrigation and is
therefore lesser known.
For Musina Municipality, four rivers were mentioned, namely: the Limpopo River perceived the
largest followed by Nzhelele which was rated the second largest. The Nwanedi was rated the
third largest while the Sand was regarded the smallest river flowing through the municipality.
According to DWAF (2003), the mean annual runoff (MAR) of the Nwanedi River is 24.5
million m3 while that of the Sand River is 71.9 million rrr', implying that the Sand is larger than
the Nwanedi River, and this is contrary to the perception of the municipal water manager. The
rating of the Nwanedi River as larger than Sand could have resulted from the former having a
large Nwanedi Dam built on it while there was no major dam on the Sand River.
112
Three rivers were mentioned for Lephalale Municipality, and those were Mokoio rated the
largest, Lephalale regarded the second largest and lastly Mogalakwena. Although it is one of the
major rivers in the Limpopo WMA (Chapter 4, Section 4.3.1.1), the Matlabas was not
mentioned. The MAR of Lephalale River is 149.4 million m3 while that of Mogalakwena is
268.8 million m3 (DWAF, 2003), revealing Mogalakwena as larger than Lephalale and is
contrary to the perception of the municipal water manager. Polokwane Municipality only has
Sand River flowing through it while Aganang Municipality has no major river flowing through
it, and these were correctly reported by the water managers.
As for municipalities in the Luvuvhu-Letaba WMA, the water manager for Thulamela mentioned
four rivers, the Luvuvhu River rated the largest, Mutshindudi regarded the second largest,
Mbwedi perceived the third largest and Nzhelele viewed the smallest, with the Shingwedzi River
omitted from the list. The Luvuvhu River has MAR of 362.9 million m3 (DWAF, 2004b) and is
confirmed the largest. The Mutshindudi and Mbwedi (catchment MAR of 138.1 million rrr')
were presented as a combined river system forming a tributary of the Luvuvhu River. When the
two rivers are considered as a combined river system, they are larger than the Nzhelele River
(catchment MAR of 89.4 million rrr'). If the Mutshindudi and Mbwedi were to be rated as
separate rivers however, a different result would likely be reported. The rating of the
Mutshindudi River as the second largest was likely influenced by its having a well-known Vondo
Dam which supplies water for domestic use to the municipality. The rating of Mbwedi River as
larger than Nzhelele is rather inexplicable.
The Tzaneen and Giyani municipalities had two rivers mentioned for each, and those seemed to
be correctly rated. The water manager for Mutale Municipality rated the Nwanedi larger than
Mutale River. The MAR of the Nwanedi River is 24.5 million m3 while that of the Mutale River
is 157.1 million m3 (DWAF, 2004b), implying that the Nwanedi is in fact much smaller than
Mutale River as opposed to the perception of the water manager.
113
The omission of major rivers by municipal water managers and the incorrect ratings of the sizes
of the rivers imply that the water managers had limited knowledge of the water resources of their
areas. Based on these inaccurate perceptions, the water managers are likely to make water
management decisions that are not appropriate. Inappropriate water management decisions will
negatively influence the availability of the resource for socio-economic development in the study
area. It is therefore necessary for the water managers to be equipped with relevant knowledge of
water resources for them to make appropriate decisions that will promote resource availability
for socio-economic development.
6.3.2 Perceptions on municipal water uses
Water is required for agricultural, industrial, household, recreational and environmental uses
(Vairavamoorthy et al., 2008). Growing national, regional and seasonal water scarcities in much
of the world pose severe challenges for national governments and international development and
environmental communities (Rosegrant et al., 2002). According to Winstanley and Wendland
(2007), adequate supplies of clean water are fundamental requirements for human welfare and
economic development. Conversely, water shortages and polluted waters limit human and
economic growth.
Water is consumed by multiple uses, often referred to as domestic and productive uses. Domestic
uses of water refer to water used in the homes for drinking, cooking, personal hygiene and
household cleaning, while productive uses highlight the fact that in rural areas people engage in
economic activities that are highly dependent on the availability of secure and reliable water
supplies (Mori arty et al., 2004). Perez de Mendiguren Castresana (2003) mentioned that specific
multiple uses of water in Bushbuckridge in the Mpumalanga province of South Africa include
drinking, washing, cooking, irrigation, manufacturing, brick making and beer making.
For municipal water managers to manage this scarce resource well, they should have some
knowledge of the major uses of the resource in their areas of jurisdiction. Schreiner and van
Koppen (2000) state that poor people's water needs for multiple uses should be the starting point
114
for meaningful management of the resource, confirming the importance of water managers'
knowledge of the multiple water uses by the poor.
Seven out of ten (70%) of the water managers claimed they have knowledge of the relative
quantities of the water consumed by each of the major uses in their municipalities. Knowledge of
the perceptions of municipal managers on major uses of water is necessary as it influences the
managers' decisions on the management of the resource (Table 6.2).
Table 6.2 Perceptions of municipal water managers on major uses of the resource according to
quantities consumed
Water Municipality Perceived quantity of water consumed
Management Ecological Household Industrial Agricultura Recreational
Area I
Limpopo Makhado 2 5 3 4 1
Musina 0 5 3 4 0
Lephalale 2 5 1 4 3
Polokwane 0 5 4 3 0
Aganang 0 5 0 4 0
Luvuvhu- 3 5 2 4 1
Letaba Letaba
Thulamela '3 4 1 5 2
Tzaneen 3 4 2 5 1
Giyani 3 5 2 4 0
Mutale 4 5 2 3 1
Average 2.0 4.8 2.0 4.0 0.9
Key: O=None consumed, l=Very small, 2=Small, 3=Medium, 4=Large, 5=Very large quantity
consumed
According to Table 6.2, domestic use was perceived to have consumed a very large quantity of
water (rating=4.8), followed by agriculture that consumed a large quantity (rating=4.0). The
quantities of water consumed for ecological and for industrial purposes was regarded small
(rating=2.0) while that used for recreational purposes was reportedly very small (rating=0.9).
The ratings of the major water uses by the respondents differ to some extent from that reported
by DWAF (2004a) who presented agriculture as the largest consumer of the resource in the study
area at 62%. The respondents reported agriculture to be a large consumer of water and to be
115
second after domestic use, and the sector is still highly rated considering the quantity of water
consumed.
The perception of the managers that agriculture was the second and not the largest consumer of
water could have resulted from the fact that they were not involved in supplying the major
agricultural sector which received allocations directly from DWA. Municipalities were mainly
rural with less industrial and recreational facilities and this could be reason for these sectors
being perceived to be small consumers of water.
Three municipalities in the Limpopo WMA (Musina, Polokwane and Aganang) and one in the
Luvuvhu-Letaba WMA (Giyani) reported lack of water consumption by some use sectors. The
report of non-consumption could be an indication of the water managers' lack of knowledge of
the consumed amounts. Each of the five major water use sectors was further discussed to better
understand their perceived water consumption.
(a) Perceptions on household uses of water
Household use of water is essential for human health and indeed for survival. Water for
household use is supplied for domestic and for productive purposes. Domestic water was
described as the supply which caters for health and hygiene, covering specific issues such as
water for drinking, cooking, sanitation and washing (Soussan et al., 2002; Pollard et al., 2002).
Productive water caters for household economic activities.
The 2003 Johannesburg Symposium on Poverty and Water resolved that the quantity of water
sufficient for domestic use would typically be between 50 and 150 litres per person per day.
Moriarty et al. (2004) stated that the benchmark target for South Africa was 25 litres per person
per day and this was clearly insufficient, especially if needs for productive activities were
considered. The recommended minimum supply of water should be 50 litres per person per day
if we were to cater for both domestic and productive uses (Gleick, 1993).
116
The inclusion of productive uses in household water budgeting is important as it provides
opportunities to turn water into cash needed to buy spare parts and to pay for routine
maintenance of the water supply infrastructure (LovelI, 2000). As a result, water supply systems
that are designed to provide only domestic norms with exclusion of productive uses would most
likely fail. The failure would be a result of the water supply system not being able to meet the
demand of the water users and this may bring about economic and political instability (Schouten
and Moriarity, 2003).
Perez de Mendiguren Castresana (2003) revealed the kind of benefits in monetary values for the
various productive uses of water. Ice-block making provided the highest return (RI,70 per liter),
followed by beer brewing (RI,05 per liter) and hair saloons (RO,84 per liter). Brick laying was
next (RO,30 per liter), followed by livestock rearing (RO,025 per liter) and fruit production
(RO,02 per liter). Vegetable production provided the lowest return (RO,OI3 per liter).
Knowledge of household uses of water would therefore be necessary for water managers to make
appropriate decisions in investing in the development of the resource and in allocating the
resource to different major use sectors.
All the water managers in the study area mentioned drinking, cooking, washing and processing
food for sale as important household uses of water. Nine out of ten (90%) of them mentioned
processing drinks for sale as an important household use of water. On the basis of their
knowledge of household water use, the respondents rated the uses of the resource according to
the quantity consumed (Table 6.3).
Washing was perceived to have consumed a large quantity of water (rating=3.9), followed by
agricultural activities (rating=3.4), drinking (rating=3.l) and cooking (rating=2.8) with perceived
medium consumptions (Table 6.3). Very small quantities of water were reportedly consumed by
processing of food (rating=1.2) and drinks (rating=0.9) for sale.
117
The rating of water uses according to the quantity of water consumed suggests that more water
was used for domestic activities such as washing, drinking and cooking than the amount of water
used for productive activities such as processing food and drinks for sale. Although agricultural
activities are productive, they were reportedly medium consumers of water. This perceived
distribution of water where basic domestic activities use more water than their productive
counterparts are indicative of short supplies forcing households to allocate more water to basic
life activities.
Table 6.3 Perceptions of municipal water managers on household uses of water according to
quantities consumed by activity
Water Municipality Perceived quantity of water consumed by household activity
Management Drinkin Cooking Washing Agricult Process Process food
Area g ural drink
Limpopo Makhado 3 4 5 2 I I
Musina 5 3 2 4 I 1
Lephalale 5 3 4 2 1 1
Polokwane 4 3 5 2 0 0
Aganang 1 1 2 4 0 3
Luvuvhu- 2 3 4 5 1 1
Letaba Letaba
Thulamela 3 1 5 4 2 1
Tzaneen 5 4 3 2 1 1
Giyani 1 3 4 5 1 2
Mutale 2 3 5 4 1 1
Average 3.1 2.8 3.9 3.4 0.9 1.2
Key: O=None consumed, l=Very small, 2=Small, 3=Medium, 4=Large, 5=Very large quantity
consumed
The fact that agriculture was perceived to consume the second largest amount of water implied
that communities had realized the critical role played by the agricultural sector, both in
promoting food security and in earning incomes for the rural households. This result supports
Schreiner and Van Koppen (2000) who mentioned that water is vital to increase incomes above
one US dollar per day. The reason for agriculture not being regarded the largest consumer of
118
water could be the small scale of practice and the fact that it is not all families that practice
agriculture at household level.
Two municipalities in the Limpopo WMA reported that there was no water consumption by
some use sectors. These were the Polokwane Municipality who reported non-consumption for
drink and for food processing and the Aganang Municipality indicating non-consumption for
drink processing. The report of non-consumption suggests that the water managers did not have
knowledge of the quantities consumed by the sectors.
(b) Perceptions on industrial uses of water
Vairavamoorthy et al. (2008) indicated that national water policies of many countries place
industrial alongside household water needs. The use of water for industrial purposes in a
municipality is dependent on the extent to which the municipality has developed industrially.
The number and sizes of industries in a municipality determine the quantity of water that is
consumed for these industrial purposes.
Nine often (90%) water managers reported that some water in their municipalities was used by
industries. Different types of industries which consumed water were identified. Food processing
at industrial level was identified by seven of the ten (70%) municipalities as a user of water.
Drink processing and manufacturing was each regarded by half of the municipalities as a user of
water. Sound management of the water resource requires the municipal water managers to have
knowledge of the quantities consumed by different industrial activities (Table 6.4).
Food processing was perceived to have consumed a large quantity of water (rating=3.6) and was
followed by drink processing whose water use was rated medium (rating=2.6). The water uses
for manufacturing (rating=1.3) and mining (rating=0.9) were perceived to be very small while
that for power generation (rating=O.4) by the Electricity Supply Commission (Eskom) was
regarded almost non-existent (Table 6.4).
119
Table 6.4 Perceptions of municipal water managers on industrial uses of water according to
quantity consumed by activity
Water Management Municipality Perceived_9uantity of water consumed by industrial activity
Area Process Process Manufactu Mining Eskom
food drinks ring
Limpopo Makhado 5 3 4 0 0
Musina 5 0 0 0 0
Lephalale 0 0 0 5 4
Polokwane 3 5 0 4 0
Aganang 0 0 0 0 0
Luvuvhu-Letaba Letaba 5 4 3 0 0
Thulamela 5 4 3 0 0
Tzaneen 4 5 3 0 0
Giyani 5 0 0 0 0
Mutale 4 5 0 0 0
Average 3.6 2.6 1.3 0.9 0.4
Key: O=None consumed, l=Very small, 2=Small, 3=Medium, 4=Large, 5=Very large quantity
consumed
The results suggest that more water in the study area was consumed by the processing of food
and drinks, often for sale. Food and beverage industries were more common in the study area and
this could have been reason for more water being consumed by these industrial activities. Mining
and Eskom power generation only occurred in some municipalities and hence the perception of
less amount of water being consumed by these activities was not surprising.
All municipalities had some industrial water uses that perceivably did not use water. This report
of non-consumption of water by a lot of industrial activities was probably a result of the fact that
the study area is rural and has few such industries. It is possible that the managers lacked the
knowledge of the water used by some of the industrial activities. In municipalities where food
processing industries occurred, they were mostly bakeries, maize mills and abattoirs. With
regards to drinks, the major industries involved in the study area included the processing of soft
drinks, mainly by Coca-cola, processing juice mostly from fruits, and the processing of beer,
both by the South African Breweries and by rural households who brew traditional beer.
120
(c) Perceptions on agricultural water use
Among the various use sectors, agriculture is the world's largest user of water. Rosegrant ef al.
(2002) estimated the consumption of water by agriculture at about 80% of global and 86% of
developing country water use in 1995. The global agricultural water consumption was affirmed
by Molden ef al. (2002) who revealed it to be almost 80% of total withdrawals from water
sources. Cosgrove and Rijsberman (2000) had estimated the 80% consumption to be for irrigated
agriculture alone.
To properly understand the quantity of water consumed by agriculture, we need to examine the
amount of water we 'eat' compared to what we use for other purposes. A person's food
requirement is estimated at 300 kg/year of cereal equivalent which is sufficient to furnish a daily
average per capita caloric intake of about 2 900 kcal. Water productivity on the other hand is
estimated at one kg/cubic meter, and subsequently 300 cubic meters of water are consumed per
year to grow this annual food requirement (Inocencio ef al., 2003). As stated by Inocencio ef al.
(2003), the consumption by agriculture is equivalent to about 850 litres per person per day,
which is much more than the 50 litres per person per day needed for household use.
Two out of five (40%) of the municipal water managers could estimate the amount of water used
for agricultural purposes in their municipalities. All the respondents identified irrigation as a
major agricultural water user. Nine out of ten (90%) of the water managers identified animal
drinking while four out of five (80%) identified livestock dipping as a major agricultural water
use. With agriculture being a major consumer of water in South Africa (DWAF, 2004a), it is
important for municipal water managers to know the relative amounts consumed by different
agricultural activities in order to make relevant resource management decisions (Table 6.5).
Irrigation was perceived to have consumed large quantities of water in all the municipalities The
amount of water used for animal drinking was perceived to be medium in 90% of municipalities
while it was regarded effectively non-significant in 10%. Dipping of animals was perceived to
121
have consumed small quantities of water in 80% of the municipalities and 20% reported the
quantity used as non-existent.
Table 6.S Perceptions of municipal water managers on agricultural uses of water according to
quantity consumed by activity
Perceived quantity of water consumed by
agricultural activity
Water Management Area Municipality DiJ!l1ing_ Drinking_ Irrigation
Limpopo Makhado 1 2 3
Musina 1 2 3
Lephalale 1 2 3
Polokwane 0 0 3
Aganang 0 2 3
Luvuvh u-Leta ba Letaba 1 2 3
Thulamela 1 2 3
Tzaneen 1 2 3
Giyani 1 2 3
Mutale 1 2 3
Key: O=None consumed, 1=Small, 2=Medium, 3=Large quantity consumed
These findings confirmed a statement by Cosgrove and Rijsberman (2000) who reported that
irrigated agriculture is the dominant user of water, accounting for about 80% of global and 86%
of developing country water consumption. Also, DWAF (2004a) reported that irrigation is the
largest user of water in South Africa, accounting for 62% of the total water consumed.
Considering the assertion by Inocencio et al. (2003) that the productivity of water for cereal
production is estimated at one kg/cubic meter and that a person's food requirement is estimated
at 300 kg/year of cereal equivalent, it may be understood why irrigation uses that largest amount
of water. The study areas are mainly rural with agriculture being the main economic activity and
irrigation being an important agricultural activity.
122
The quantity of water used for livestock drinking and dipping tends to be influenced by such
factors as the number of animals in an area and the proportion of the different types of animals.
Areas with more animals use more water for livestock drinking and dipping, and the same occurs
where large stock comprises a bigger proportion of the livestock in the study area.
A livestock census revealed that four of the municipalities under study had more than 50 000
cattle, namely: Makhado (64 686), Letaba (53 744), Giyani (83 726), and Lephalale (52 885)
municipality (LDA, 2008). Based on the consumption rate of 68 litres/head/day (Lowe et al.,
2009), the daily amount of water used for cattle drinking in these municipalities would be 4
3
398.65 m for Makhado, 3 654.59 m3 for Letaba, 5 693.37 rrr' for Giyani and 3 596.18 m3 for
Lephalale. The other municipalities had fewer cattle each and would accordingly use lesser
amounts of water for cattle drinkiI?-g.For livestock drinking, however, the municipalities used
more water than the quantities shown here as other animals would be accounted for, namely
donkeys, mules, goats, sheep, pigs etc.
In areas where there are rivers, the animals drink directly from the rivers, and where there are
none the water for animal drinking is mostly pumped from boreholes. In some cases the animals
drink from the portion of water soureed for household uses. Two municipalities in the Limpopo
WMA reported non-consumption of water by agricultural activities of livestock dipping and
drinking. These are the Polokwane Municipality that reported non-consumption dipping and
drinking and the Aganang Municipality that reported non-consumption for dipping. This report
of non-consumption suggests that the water managers had a dearth of knowledge of the amount
of water used in these agricultural activities.
The perceptions of municipal water managers that there were activities from various sectors that
did not use water suggest that they lacked knowledge of the quantities of water consumed by
these activities. This dearth of knowledge was confirmed by the perception that the amount of
water used in agriculture is less than that consumed by households contrary to reports that
agriculture uses as much as 62% of the water in the study area (DWAF, 2004a). The ratings of
123
the amounts of water used by some activities were rather credible. Objective assessment of the
correctness of the ratings of water uses by the municipal water managers would, however,
require a detailed study of the actual quantities of water consumed between and within each of
the different use sectors.
6.3.3 Perceptions on water restrictions
South Africa is a water scarce country (DWAF, 2004a) and this situation is very true in the
WMAs under study. Due to the problem of water scarcity, different municipalities have to
impose restrictions during certain months of the year (Figure 6.2).
70 -r----------- __
o 0
F M A M A s o N o
Month of the year
Figure 6.2 Perceptions of municipal water managers on water restrictions across the months of
the year
Up to 90% of the municipal water managers interviewed experienced water shortages in their
municipalities. All the respondents indicated that water restrictions were imposed in their
municipalities during certain months of the year. Municipal water managers' knowledge of the
124
months of the year in which restrictions are imposed guides them in making relevant resource
management decisions (Figure 6.2).
As reported by the managers, no municipality imposed water restrictions in the months of
January to April. Some 40% of the municipalities imposed restrictions during May to August and
in October and November. Up to 60% of municipalities imposed restrictions in September while
20% had restrictions in December (Figure 6.2).
According to the SAWS (undated) the WMAs under study are within a summer rainfall area with
low rainfalls reported for May (12.9mm), June (7.6mm), July (7.0mm), August (6.9mm) and
September (19.5mm). The imposition of restrictions by 40% of municipalities during May to
August and by 60% of them in September could have resulted from water shortage due to the
low rainfall during these months. Although rainfall would generally have picked up, 40% of
municipalities retained the restrictions in October and November and 20% did so even in
December, and that could suggest delayed rainfall in those municipalities or caution not to lift
the restrictions until the rainy season had fully set in. The results suggest that the imposition of
water restriction was influenced by the occurrence of rainfall (Figure 6.3).
There was a moderate correlation (R2=0.4555) between monthly rainfall and the number of
municipalities that had imposed water restrictions (Figure 6.3). The graph reveals that the
number of municipalities that imposed restrictions declined when the rainfall increased. Rainfall
is the fundamental driving force of hydrological processes (Schulze, 1995) and is therefore
important for water supply, which could be reason for its negative relationship with the
imposition of water restrictions.
125
70
ê
VI 60
c
0
'Z
..u;.:
VI SO
..G._I.c.:
'§ 40
VI
GI
:2
'is
Cl. 30
'u
'ë
::l
..E... 20
0...
GI
.Q
E 10
::l
Z
0
0 20 40 60 80 100 120
Monthly rainfall (mm)
Figure 6.3 Influence of monthly rainfall on number of municipalities imposing water restrictions
From the above discussion, it appears that some municipalities apply restrictions immediately
when the rainy season is ending during May to July, others apply the restrictions at the beginning
of the rainy season with yet others applying them at the transition from end of dry season to the
beginning of the rainy season. Municipal decisions on when to impose water restrictions could
be influenced by such factors as the main sources of water (i.e direct from rivers or from dams
or from boreholes), the position of the area of the municipality in the catchment (i.e near sources
of rivers or mountains or further down) and the average start of the rainy season.
The impositions of restrictions on water supplies are very necessary in the water scarce areas
such as the Limpopo Province. The imposition of restrictions results in smaller supplies of water
and lesser socio-economic activities. Non-imposition of restrictions could lead to disastrous
consequences as a point could be reached were there would be completely no supply of water in
some areas. The municipal water managers seemed to know when to impose restrictions in their
126
specific areas. There is a continued need for research on water restrictions as a way of improving
the efficiency of water use during times of scarcity.
6.4 Summary and conclusion
The perceptions of the water managers on the water resources of their municipal areas revealed a
dearth of knowledge of these resources. This lack of knowledge was shown by the water
managers omitting major rivers in their enlisting of the water resources and by their incorrect
ratings of the mentioned rivers according to size. With this limited knowledge of the water
resources, the water managers are likely to make inappropriate water management decisions that
will negatively influence the availability of the resource for socio-economic development in the
study area. To avoid this situation, the water managers should be equipped with relevant
knowledge of the water resources.
With regards to water uses, the managers had perceptions that activities in some sectors did not
use the resource in their municipal areas. While the perceptions of non-consumption could be
true for some activities, they may not be credible for other activities. For instance, reports by
water managers that there was no water consumed by ecological activities and by livestock
)
dipping and drinking sound incredible. The perceptions suggest that the managers could have
lacked knowledge of the amounts of water consumed by these uses.
The lack of knowledge on various water uses was confirmed by the managers' perceptions that
the quantity of water used by the agricultural sector was less than that consumed by household
activities. For the municipal water managers to make appropriate decisions in their rendering of
water services, it is very important for them to be equipped with requisite knowledge of the
water uses. The water managers seemed to know when to impose restrictions in their specific
areas. It is necessary to further improve the efficiency of water use in the area, and this requires
more research on issues of water restrictions.
127
CHAPTER 7
7 MUNICIPALITY PERCEPTIONS OF STAKEHOLDER PARTICIPATION AND
INFLUENCE ON WATER MANAGEMENT DECISIONS
7.1 Introduction
The perception of municipal water managers on stakeholder participation reflects the type of
stakeholders that are invited to water management meetings. It is often difficult to select relevant
stakeholders for inclusion in community based meetings. The complication results from cases
where (1) some categories of stakeholders may be historically marginalized from decisions and
may be difficult to identify, (2) conflicts exist among different groups making them reluctant to
join a deliberative process, and (3) participatory process accommodate a small group resulting in
lack of representativeness (Daniels and Walker, 2001; GrimbIe and Wellard, 1997).
Appropriate stakeholder selection should be preceded by stakeholder analysis which recognises
the role that stakeholders should play in water management decisions (Burroughs, 1999; Selin et
al., 2000). According to Mitchell (1997), stakeholders are sometimes selected on the basis of
assessment of the urgency, legitimacy and power of potential stakeholders in relation to the
aspects under study. These approaches prioritize powerful stakeholders and neglect the lower
ranked group and are not desirable (GrimbIe and Chan, 1995; MacArthur, 1997).
A fair allocation of water requires participation by all stakeholders in the management of the
resource (Shah et al., 2001). Effective stakeholder participation entails deliberation, a process of
open communication, discussion and reflection among stakeholders who have different
viewpoints and understandings (Leeuwis, 2000). According to Schusler et al (2003), the
deliberation allows for stakeholders to learn from the views and motivations of others. These
deliberative processes help policy decision makers and experts to better understand each other
(Backstrand, 2003). Community based role players also have legitimate interest in water
128
resources issues and are therefore important stakeholders (Van Hofwegen, 200 I) whose views
should be considered for sound management of the water resource (Mashau, 200 I).
Municipal water managers are important decision makers in the management of water resources
in their areas of operation. As a result, the perceptions of the managers on stakeholder
participation are important for knowing the stakeholders that are active in water management
decision making. The objective of the study was to investigate the perceptions of the managers
on water stakeholders and their participation and influence on resource management decision
making (Section 1.4, Table 1.3, specific objective 3). The study was necessitated by community
discontent about lack of involvement in water management decisions.
7.2 Research methods
7.2.1 Study area
LOC"AUT\' 'UP
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Loul Munk:lp.llti ••
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INKOMATI
Figure 7.1 Map ofLimpopo Province with Water Management Areas (red lines) and
municipalities (hatchings) comprising the study area
129
The study covered ten local municipalities in the Limpopo and the Luvuvhu- Letaba WMAs
located in the Limpopo Province of South Africa. Five municipalities were sampled from each
WMA (Figure 7.1). The local municipalities covered by the study were Makhado, Musina,
Lephalale, Polokwane and Aganang in the Limpopo WMA and Letaba, Thulamela, Tzaneen,
Giyani, and Mutale in the Luvuvhu-Letaba WMA.
7.2.2 Sampling procedure
The units of analysis for the study were selected through purposive sampling defined by Welman
et al. (2005) as a sampling where researchers rely on their experience, ingenuity and / or previous
research findings to deliberately obtain units of analysis that are regarded representative of the
relevant population. The two sampled WMAs were administered by the Limpopo Regional
Office of the Department of Water Affairs (DWA) and were selected for ease of access to their
information while the ten municipalities were purposively sampled for their available
information on runoff (Section 4.3.2)
7.2.3 Data collection and analysis
The information for the WMAs was obtained through semi-structured interviews with relevant
officers of the Limpopo Regional Office of DWA. The data for the municipalities was collected
using a structured questionnaire used to interview water managers of each of the 10
municipalities sampled for the study. A questionnaire may be used to obtain information on
opinions, beliefs, convictions and attitudes (Welman et al., 2005) and was therefore relevant for
collecting information on perceptions of the water managers on stakeholder participation and
influence on water management decisions.
The questionnaire had both closed-ended questions that collected quantitative data and open-
ended questions that collected qualitative data and the study was therefore described as a mixed
research (Leedy and Orrnrod, 2010). The interviews on closed-ended questions were more
structured with less flexibility while those on open-ended questions were less structured with
more flexibility for respondents to provide information that the researcher had not anticipated.
130
The interviews with DWA officers dealt with broad policy issues affecting the water sector in the
two WMAs. The questionnaire used to interview municipal water managers covered perceptions
on stakeholders in water management decisions and their participation in resource management
forums with a focus on frequency of meetings and issues discussed. Also covered were the
stakeholder influence on water management decisions with particular attention given to their
reliability as sources of water management information and their level of influence, both on
broad water management decisions and on specific topics discussed in meetings.
Quantitative data was captured and analysed using the SAS package (SAS Institute Inc, 2009).
The Proe FREQ procedure of SAS was used to generate simple frequency tables of occurrence in
each class utilizing one-way tables. The procedure is appropriate to give descriptive statistics
about categorical data such as the demographic datasets. The syntax is provided to the SAS
software, which automatically calculates the percentage of observations falling within each
category of response. The output contains both the actual and the cumulative frequencies.
Qualitative data was summarised and analysed using subjective interpretations (Lee, 1999;
Leedy and Ormrod, 2010).
7.3 Results and discussions
7.3.1 Stakeholder organisations and their roles
Stakeholders in water resource management were defined by Van Hofwegen (2001) as people or
groups of people with a legitimate interest in water resource issues. Some 90% of the municipal
water managers perceived DWA to be a stakeholder, 40% regarded the Limpopo Department of
Agriculture (LDA), the same number (40%) identified community based organisations (CBOs),
and 80% viewed Water Users Associations (WUAs) as stakeholders in their water management
decisions. District Municipalities (DMs) and the Local Municipalities (LMs) themselves were
also mentioned as stakeholders participating in water management decisions.
In terms of the roles of the stakeholders, DWA is responsible for administering all aspects of the
National Water Act (Act No. 36 of 1998) on behalf of the Minister. The major responsibilities of
131
the department include the development and implementation of strategies and internal policies,
plans and procedures, and regulatory instruments. The department is also responsible for
planning, developing, operating and maintaining state-owned water resource management
infrastructure, and for overseeing the activities of all water management institutions (RSA,
1998a; DWAF, 2004a).
The main interest of the LDA, on the other hand is the availability of water for agricultural use
particularly for irrigation purposes. The role of the department is therefore mainly to lobby for
water allocations for the agricultural sector directly from DWA with no involvement of the
interviewed municipal managers. The CBOs would mostly form part of WUAs and participate in
the activities of the associations. The roles of the WUAs differ according to the purpose for
which they were formed, and those may include water use for recreational purposes and that for
agricultural use (DWAF, 2004a).
The DMs and LMs compose local government, a constitutionally distinct sphere of government.
While the DMs are responsible for development of water reticulation infrastructure, the LMs are
the sphere of government closest to the communities and according to DWAF (2004a) they were
designated as water services authorities and are responsible for the provision of water services in
their areas of jurisdiction. The stakeholders identified therefore ranged from national department
involved with policy and strategy issues through to local authorities involved with the provision
of water services to communities.
The water stakeholder organisations as identified by the municipal water managers seem to have
covered all major stakeholders. At the level of individual municipalities, some omissions were
noted where, for instance one municipality excluded DWA and 60% of them excluded LDA
from their lists of stakeholders. Municipalities should therefore convene public consultative
water summits to update their stakeholder databases.
132
7.3.2 Stakeholder participation in water management decisions
The participation of stakeholders in water management decisions determines the quality of
decisions made and the extent to which the stakeholders contribute to the productivity of the
water resource. The participation of stakeholders in water management is informed by the
frequency of meetings attended, the number of issues discussed and the actual topics discussed in
the meetings.
(a) Frequency of stakeholder meetings and number of issues discussed
As indicated by Mashau (2001), greater participation by stakeholders is essential for sound water
resource management and therefore the frequency of stakeholder meetings and the range of
issues discussed are important. The frequency of meetings reflects the opportunity created for
participation by the stakeholders in water management decisions. The frequency of stakeholder
meetings for the local municipalities involved in the study and the number of water management
issues discussed in those meetings are important indicators of the extent of stakeholder
involvement (Figure 7.2).
As shown in Figure 7.2, stakeholders in 60% of municipalities reportedly met monthly (twelve
meetings in a year), and those municipalities were Lephalale and Aganang in the Limpopo
WMA and Letaba, Thulamela, Giyani and Mutale in the Luvuvhu-Letaba WMA. Monthly
meetings in municipalities under the Luvuvhu-Letaba WMA were double those in municipalities
under the Limpopo WMA. Stakeholders met quarterly in 30% of the municipalities where all of
them (Makhado, Musina and Polokwane) were in the Limpopo WMA. Stakeholder meetings in
the Tzaneen Municipality were once in a year with their meetings not having a fixed schedule.
The stakeholder forum without a fixed schedule of meetings could have been newly formed and
not having strong issues to regularly communicate.
Considering the number of water management issues discussed in meetings in the Limpopo
WMA, two municipal stakeholder meetings (Musina and Polokwane) had only one issue each,
133
one municipality (Makhado) had three issues, the other (Lephalale) had four and the last
(Aganang) had five issues to discuss.'
12
12
12
12
5
12
Mutale 12
o 2 4 6 8 10 12 14
Meetings in a year & no of issues discussed in a meeting
$ill Meetings in a year u No of issues discussed in a meeting
Figure 7.2 Frequency of stakeholder meetings and number of water management issues
discussed in each meeting
In the Luvuvhu-Letaba WMA, one municipality (Letaba) reportedly discussed only one issue in
their stakeholder meetings, two (Thulamela and Giyani) discussed three issues and another two
(Tzaneen and Mutale) discussed five issues. The results suggest that more water management
issues were discussed in stakeholder meetings in the Luvuvhu-Letaba (18 issues) than in the
Limpopo WMA (14 issues).
With proper planning, quarterly stakeholder meetings would be adequate for good consultative
management of the water resource. The Tzaneen municipality convened stakeholder meetings
based on need and this would need to improve. The municipality should convene properly
planned meetings quarterly with a pre-arranged schedule agreed upon. Monthly meetings as
134
convened by 60% of the municipalities are rather too frequent and could provide too little time
for participants to implement the water management decisions made in meetings. This frequency
of meetings may be recommended at the start of operation of stakeholder forums for participants
to know each other and for systems to be established. The number of issues discuss would
continue to vary among stakeholder fora and among different meetings within a forum.
(b) Water management issues discussed in stakeholder meetings
The water management issues discussed in the meetings of water stakeholders would likely be
the ones included in strategic and annual performance plans of stakeholder organisations and
should therefore receive due attention. The issues reportedly discussed in the stakeholder
meetings are those regarded by the stakeholders to be important for the water sector (Table 7.1).
Three municipalities were reported to have discussed five water management issues in their
stakeholder meetings, namely: Aganang in Limpopo WMA and Tzaneen and Mutale in
Luvuvhu-Letaba WMA. The issues discussed were the same for the three municipalities and
'l'
were reported to be policy, infrastructure, water allocations, water charges and water use issues.
This could be indicative that these municipalities had matters of concern with the five water
management issues. The Lephalale Municipality discussed four water management issues and
they only left out water charges from the five issues enlisted for Aganang, Tzaneen and Mutale
municipalities.
Three municipalities (Makhado, Thulamela and Giyani) reportedly discussed three water
management issues in their meetings and they all included infrastructure and water charges. The
third issue discussed by each of the three municipalities was water use for Makhado and
Thulamela and water allocations for Giyani.
135
Table 7.1 Issues discussed in water stakeholder meetings of the study municipalities in the
Limpopo and Luvuvhu- Letaba WMAs
Water Municipality Issues discussed
Management Policy Infrastructure Water Water Water use issues
Area allocations charges
Limpopo Makhado 2 1 2 1 1
Musina 2 1 2 2 2
Lephalale 1 I I 2 1
Polokwane 2 I 2 2 2
Aganang 1 1 1 I I
Luvuvhu- Letaba 2 I 2 2 2
Letabe
Thulamela 2 I 2 I 1
Tzaneen I I I I 1
Giyani 2 1 1 1 2
Mutale 1 1 1 1 1
Key: 1- Issue was discussed; 2- Issue was not discussed
Infrastructure was reported to have been discussed at meetings of all municipalities. This
suggested that all municipalities had issues of concern with the water infrastructure, and this
could have included siltation of dams, breaking down of boreholes and repeated bursting of
reticulation pipes. The stakeholder meetings could therefore have focussed on required
interventions such as the development and maintenance of the infrastructure.
Issues of water charges were discussed at water stakeholder meetings of 60% of the
municipalities. The water charges were discussed in municipalities that seemed rural with some
relatively newly proclaimed urban centres, either towns or townships. Relatively new towns
occurred in Aganang, Thulamela, Giyani and Mutale while newly proclaimed townships would
be in Makhado and Tzaneen. The systems for implementing the charges in the new urban areas
could still not be well established and therefore residents would be over- or under-charged. The
discussion of water charges could be a result of the dwellers not used to these charges or being
136
unhappy with the water charge systems themselves. Residents in municipalities with long
proclaimed urban centres would be much used to the water charges and their charge systems
would be well established and will therefore not have to discuss the charges in stakeholder
meetings.
As was the case with water charges, water use issues were also discussed in 60% of the
municipalities. Municipalities that discussed water use issues in their stakeholder meetings
seemed to be those that had major economic activities that demanded water thereby creating
competition with domestic demand. The municipalities of Makhado, Thulamela, and Tzaneen are
strong in irrigated agriculture while Lephalale and Mutale are strong in mining.
Water allocations were discussed in meetings in half of the municipalities and these could be
where some stakeholders had concerns with this water management issue. Municipalities that
discussed water allocations mostly also discussed policy. This suggests a strong link between
policy and the implementation of water allocations.
Policy issues were discussed in meetings in only 40% of the municipalities. With DWA being
the custodian of water policies, these could be municipalities where the department was most
active. Merrey (2000) stated that rural communities were unaware of the provisions of the new
water law, and this could be reason for policy issues having been discussed in stakeholder
meetings of fewer municipalities.
(c) Relationship between stakeholder participation and municipal runoff
Pretty (1995) argues that the concept of stakeholder participation remains as vague as concepts
like sustainability. For this analysis the number of water stakeholder meetings attended is
assumed to be an important indicator of stakeholder participation (Figure 7.2). The amount of
municipal runoff determines the amount of water naturally available in the municipality and
could influence stakeholder participation in resource decision making. The runoffs of the study
municipalities (in million rrr') were 269.2 for Makhado, 21.0 for Musina, 282.1 for Lephalale,
137
17.9 for Polokwane and 12.5 for Aganang in the Limpopo WMA and were 88.2 for Letaba,
359.1 for Thulamela, 352.3 for Tzaneen, 37.5 for Giyani and 61.2 for Mutale in the Luvuvhu-
Letaba WMA (Section 4.3.2.1).
There was no correlation noted between the level of water stakeholder participation and the
amount of municipal runoff (R2==O.032).The result reveals that the number of stakeholder
meetings was not influenced by the amount of municipal runoff. While stakeholders in wetter
municipalities could have had more meetings to discuss strategies of taking advantage of the
available water resource, those in drier municipalities could also have had more meetings to
discuss strategies of coping with the scarcity of the resource. This could have led to the number
of meetings remaining unchanged even though the amount of runoff was changing across
municipalities.
A very weak correlation (R2==O.3474) occurred between participation of external water
stakeholders and the amount of municipal runoff. External stakeholders were mostly composed
of national and provincial organisations and were more knowledgeable on water resource
management. The municipalities with more runoff are of strategic importance and were therefore
prioritized by these higher level stakeholders who sought to influence their water management
decisions.
It would be necessary for the external stakeholders to also give attention to drier municipalities
to assist in programmes such as rainwater harvesting and on efficient use of the water resource.
These would reduce the demand for water from runoff collected in wetter municipalities. The
DWA is the custodian of water in the country (RSA, 1998a, DWAF, 2004a) and should lead the
mobilization of the knowledgeable external stakeholders to the drier municipalities for
introduction of efficient water access and use programmes.
138
7.3.3 Stakeholder influence on water management decisions
The number of stake holder meetings attended alone does not reflect on the effective contribution
of stakeholders to water management decisions. The effective contribution of stakeholders to the
water management decisions is determined by their level of influence which is itself dependent
on the reliability of the information they provide.
(a) Stakeholder reliability as sources of water management information
Availability of reliable information is necessary for informed decision making. Reliability of the
information is dependent on the source of the. information. This was confirmed by Bembridge
and Tshikolomo (1992) who indicated that communication is more effective when the source of
information is considered reliable.
It would be expected for stakeholders that are perceived to be reliable sources of water
management information to better influence decisions in the sector. Participation of stakeholders
perceived to be reliable sources of water management information would therefore result in them
influencing the decisions made. The extent to which water stakeholders are regarded reliable
sources of water information is therefore important for them to successfully influence the
management decisions of the water resource (Figure 7.3).
DWA was perceived to be a more reliable source of water management information (rating=3.7)
followed by LMs who were regarded less reliable (2.3). The rest of the water stakeholders were
reported to be least reliable as sources of water management information. Government based
stakeholders of DWA, LDA, DMs and LMs provided more reliable water information than their
community based counterparts ofWUAs and CBOs (Figure 7.3).
139
4.0
3.5
g
-i; 3.0
Ë
-.=2 2.5
~ 2.0
:il::
'0
.~ 1.5:s
-;n;;o; 1.0
cc:
0.5
0.0 - ,
OVVA LOA OlV1s LlV1s VVUAS CBOs
S1:akeholder
Figure 7.3 Water stakeholders and ratings of their reliability as sources of water management
information
Key: 1- Least reliable, 2- Less reliable, 3- Reliable, 4- More reliable, 5- Most reliable
This result suggests that community based stakeholders could not have influenced decisions in
water stakeholder meetings as they would reportedly not have reliable information to present.
Water management decisions would be made by government based stakeholders perceived to be
reliable sources of water information. Communities were therefore justified in their perceptions
that municipalities were not taking them on board when making water management decisions.
With the weaker formation of the community based stakeholders, it is likely that they may not
have the capacity and the expertise to provide quality and reliable information. These
stakeholders are representative of the communities to be served by the government and their
views should inform decisions for managing the water resource. Government should therefore
develop and empower these community based stakeholders through lead agents such as DWA
and the Department of Local Government and Housing.
(b) Stakeholder influence on broad water management decisions
The level of influence a water sector stakeholder has over the other role-players determines the
extent to which he/she can influence water management decisions. Lord and Israel (1996)
140
mentioned the need for influential stakeholders to make decisions that take into account the
needs and desires of all the different water users and role players. The perceived levels of
influence of the stakeholders on broad water management issues determines the degree to which
their decisions on the resource will be accepted (Table 7.2).
Table 7.2 Perceived levels of influence of water stakeholders on broad water management
decisions in study municipalities under Limpopo and Luvuvhu- Letaba WMAs
Water Perceived levels of stakeholder influence
Management
Area
Municipality DWA LDA DMs LMs WUAs CBOs
Limpopo Makhado 4 1 2 3 2 5
Musina 1 1 1 1 1 1
Lephalale 5 1 1 1 3 I
Polokwane 5 I 1 4 1 1
Aganang 4 1 5 3 1 1
Luvuvhu-Letaba 2 1 3 1 4 5
Letaba
Thulamela 5 4 1 3 2 2
Tzaneen 5 1 4 3 2 1
Giyani 5 2 4 3 1 1
Mutale 5 2 4 3 2 1
Mean 4.1 1.5 2.6 2.5 1.9 1.9
Key: 1- Least influential, 2- Less influential, 3- Influential, 4- More influential 5- Most
influential
The municipal water manager ratings of the stakeholders according to their levels of influence in
water management decisions as presented in Table 7.2 revealed DWA to be more influential
(rating=4.1). The department was followed by three other main groupings - firstly the
municipalities that were perceived to be influential (ratings were 2.6 for DMs and 2.5 for LMs);
secondly community based groups regarded less influential (rating was 1.9 for WUAs and for
CBOs); and lastly LDA also perceived less influential (rating=I.5).
141
With DWA being the custodian of water in the country, it is not surprising that the department
was perceived to be more influential. Municipalities also play important roles in water resource
management with DMs being responsible for reticulation infrastructure and LMs for water
services and it was logical for them to be reported to be influential stakeholders.
Although agriculture consumes the largest quantity (62%) of water in South Africa (DWAF,
2004a), the municipalities rated LDA least in terms of level of influence. This low rating was a
result of the interviewed municipal managers having no responsibility for provision of
agricultural water. The LDA is therefore more active as a water stakeholder at national and
provincial levels. At a provincial level, a Coordinating Committee on Agricultural Water
(CCAW) was established where LDA and DWA discuss issues of agricultural water for
emerging farmers. Agricultural water for commercial farmers was discussed at meetings of
irrigation boards.
As opposed to good ratings of government based stakeholders of DWA and municipalities, the
community based group composed of WUAs and CBOs was perceived less influential. DWAF
(undated) stated that there were ten WUAs at different stages of establishment in the study area
(Mid 2010). Only the Groot Letaba WUA under the Luvuvhu-Letaba WMA was established and
operational. Three WUAs were established but were not yet operational, namely: Nzhelele in
Limpopo WMA and Mutale and Middle Letaba in Luvuvhu-Letaba WMA. Six WUAs were at
different stages of establishment, namely: MokoIo, Glen Alpine and Mogalakwena in Limpopo
WMA and Mutshimbwe, Letsitele, and Tzaneen in Luvuvhu-Letaba WMA. It is possibly
because the WUAs were not yet operational that they rated so poorly in terms of the level of
influence. The results placed stakeholders representing government institutions at the top
positions of influence, and this justifies the feeling of exclusion on the part of communities.
For the WUAs to be more influential stakeholders the process of their formation has to be
concluded and they must be operational entities as a matter of urgency. Those already formed
should be capacitated to function properly, and this could be achieved through funding for
142
training and institutional establishment. The process of formation of the WUAs and their
capacitation should be led by DWA and should be regarded critical for communities to actively
participate in decisions on water resource management.
(c) Stakeholder influence on specific topics discussed
The influence of stakeholders on specific water management topics discussed is as important to
development as the overall influence of the stakeholders on water management issues in general.
As is the case with broad water management issues, the perceived levels of influence of the
stakeholders on specific water management topics also determines the degree to which the
stakeholders' decisions on the resource will be accepted (Figure 7.4).
The results presented in Figure 7.4 revealed that DWA was more influential on policy
(rating=3.7) and was influential on water allocations (2.6). The results are not surprising as the
department has the mandate of developing the water policies and accordingly transforming the
allocations (RSA, 1998a and DWAF, 2004a). The department had less influence on use
(rating=2.3) and charges (1.8) for water and on infrastructure (1.5). While the results for use and
charges for water would be understood, it would be expected for the department to be influential
on infrastructure as they champion the development of major dams. The perception of the
department being less influential on infrastructure issues suggests that respondents were less
involved in these operations.
The LDA was perceived to have least influence on all the topics discussed. This result could
again have been caused by the fact that interviewed municipal managers have no role in
agricultural water provision and would therefore not regard LDA an important stakeholder for
their water management decisions.
143
4.0 r
3.7
3.S
2.9
2.6
t--
O.S
0.0
CB Os WUAs LMs OMs LOA OWA
Water rtakeholder
• Policy :SIInfrastructure IS! Allocation >,} Charge _ Use
Figure 7.4 Rating of different stakeholders according to their level of influence on specific
topics discussed in meetings
Key: 1- Least influential, 2- Less influential, 3- Influential, 4- More influential, 5- Most
influential
The DMs were reportedly influential on infrastructure (rating=2.6) and this was logical as the
districts were responsible for development of water reticulation infrastructure. The districts had
less influence on the rest of the topics discussed as they had lesser roles in those issues. The LMs
were influential on the charges (rating=2.9) and use (2.7) of water. Municipalities were mandated
to be water services authorities (RSA, 1997) and that would be reason for their influence on
water charges and uses. The WUAs were least influential on all topics discussed while CBOs
were less influential on policy (rating=1.6) and least influential on the rest of the topics
discussed.
144
The more influential stakeholders on the water management topics discussed were still
government in its different spheres, namely: DWA, LMs and DMs. Community based
stakeholders such as WUAs and CBOs were not perceived as important leaders of decisions on
the water management topics discussed. Kgomotso and Swatuk (2006) revealed that
communities have high level of interest for participating in decision making for water projects
and their exclusion from this process could be frustrating to them. Accordingly, Nare et al.
(2006) reported a lot of frustration for communities in Mzingwane catchment in Zimbabwe
arising from their marginalization in a water quality management project.
For sound management of the water resource, stakeholders should be representative and should
consider those that were disadvantaged when they make decisions (UNDP, 1995; Chancellor,
1996; Camey, 1988; and Van Koppen, 1990) and these results affirm that communities were not
properly represented and could not be catered for by the decisions made. The situation could lead
to deeper disgruntlement among members of community expecting improved delivery of water
services.
(d) Relationships between perceived reliability of stakeholders as sources of water
information and their level of influence
Stakeholders perceived to be reliable sources of water management information would likely
have more influence on the water management decisions made. The reliability of the
stakeholders as sources of water management information would determine the credibility of the
information they provide and subsequently their influence on water management decisions made
(Figure 7.5).
145
3
2.S
<I)
u
!: 2
<I)
:J
;;::
.c... 1.5
0
~
<I) 1
...I
0.5
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
Reliability as source of water information
Figure 7.5 Relationship between stakeholder reliability as sources of water management
information and their level of influence on resource management decisions
A moderate to strong correlation (R2=O.6997) was revealed between the reliability of
stakeholders as sources of water management information and their level of influence on
resource management decision making. An increase in the reliability of a stakeholder as a source
of water management information was accompanied by an increase in the level of influence the
stakeholder had on resource management decision making (Figure 7.5). The results suggest that
stakeholders should be capacitated to be reliable sources of water management information in
order for them to influence decision making in the sector. Effectively, sound management of the
water resource would be influenced by building the capacity of stakeholders to be reliable
sources of water information, and this could be achieved through training these role players on
pertinent water issues.
7.4 Summary and conclusion
The organisations perceived to be stakeholders in water management decision making were
Department of Water Affairs (DWA), Limpopo Department of Agriculture (LDA), district
146
municipalities (DMs), local municipalities (LMs), Water Users Associations (WUAs) and
Community Based Organisations (CBOs).
The issues discussed in stakeholder meetings were reportedly policy, infrastructure, water
allocations, water charges and water use issues. Only the three municipalities of Aganang,
Tzaneen and Mutale discussed all the five with the rest discussing fewer issues. Infrastructure
was the only discussion topic that was discussed by all municipalities and this suggests that it is
the most important water management issues in the study area.
DWA was rated a more reliable source of water management information (rating=3.7) followed
by LMs rated less reliable (2.3). The rest of the stakeholders were reported least reliable.
Government based stakeholders such as DWA were perceived more reliable sources of water
information than their community based counterparts of WUAs and CBOs. There was a
moderate to strong. correlation (R2=O.6997) between the reliability of stakeholders as sources of
water management information and their level of influence on resource management decisions.
Accordingly, DWA was reported more influential (rating=4.1) in broad water management
issues, followed by the influential district municipalities (rating=2.6) and local municipalities
(rating=2.5) and last the less influential community based stakeholders of WUAs and CBOs
(rating=1.9). Considering specific topics discussed, DWA was more influential on policy
(rating=3.7) and was influential on water allocations (2.6). The department had less influence on
water use (rating=2.3) and charges (1.8) as it had less to do with these topics.
The DMs were reportedly influential on infrastructure (rating=2.6) due to their involvement in
developing reticulation infrastructure. The LMs were influential on water charges (rating=2.9)
and uses (2.7) as a result of their roles as water services authorities. The WUAs were least
influential on all topics discussed while CBOs were less influential on policy (rating=1.6) and
least influential on the rest of the topics discussed. Based on this result, community based
stakeholders should be empowered to be reliable sources of water information and to
147
subsequently influence decision making in the sector. The government based stakeholders have
different complementary roles and should work together to generate better decisions for water
resource management.
148
CHAPTER8
8 HOUSEHOLD WATER SUPPLY AND REQUIREMENTS
8.1 Introduction
Water is one of the most indispensable substances for human daily life and survival (Aiga and
Umenai, 2002). Access to 'adequate supplies of water is a universal indicator of human well-
being and development (Potter and Darmame, 2010). Lack of access to safe and improved water
supplies in developing countries is a major concern since water is a basic need for sustenance
(Mazvimavi and Mmopelwa, 2006).
Considering the occurrence of natural phenomena such as global warming and the increasing
need for water to supply communities that were historically excluded the demand for water is
ever increasing (Saleth and Dinar, 2003), in both the Limpopo Province and the broader South
Africa. Safe water is important for good health (Mwendera, 2006) and survival, but problems of
access to portable water remain high (Jimu, 2008).
The issue of water demand and supply may be explained according to the theory of eo-evolution
comprised of the policy system which produces supply and the household system which
produces demand. Demand and supply are inter-related through positive feedbacks. After a
major surface water project is completed, supply capacity exceeds demand and there is a strong
economic incentive to utilities to set price to cover only the operating costs. Low water prices
instigate consumption, and as consumption increases and reaches the limit of supply, there is a
positive feedback to the policy system to expand supply. Continued feedbacks between the
policy and household systems result in perpetual urbanization and growth of water consumption
(Kallis, 2010).
Household water demand is influenced by socio-economic variables such as user age and these
determine the demand for water by households (Fox et al., 2009). The purpose of the study was
149
to characterize the households in the Luvuvhu-Letaba WMA and to investigate their water
supply with a focus on sources, proximity of sources to residential sites and quantity fetched.
The study will also assess the water requirements of the households and will compare them with
the quantity fetched to determine the adequacy of the supply (Section 1.4, Table 1.3, specific
objective 5).
8.2 Research methodology
8.2.1 Description of study area
The study was based on the Thulamela, Giyani, and Mutale municipalities under the Luvuvhu-
Letaba WMA of South Africa (Figure 8.1).
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Figure 8.1 Map of Luvuvhu-Letaba WMA showing the location of the study municipalities and
villages
The Giyani Municipality is under the Mopani Water Services Authority (WSA) while Mutale
and Thulamela are under the Vhembe WSA. Specific villages selected for the study in each of
150
the municipalities were Siyandani, Makosha and Muyexe in Giyani; Sigonde, Makwilidza, and
Lukau in Mutale; and Mavunde, Djilongo, Xigamani, and Dopeni in Thulamela (Figure 8.1).
8.2.2 Smpling procedure
The Luvuvhu-Letaba WMA was purposively selected for the study for its proximity as it is the
place of residence of the researcher. Within the WMA, multi stage sampling was conducted as
described by Leedy and Ormrod (2010) and involved primary area selection of municipalities,
location selection of villages and housing unit selection of households.
For area selection of municipalities, the sampling frame was composed of the five municipalities
that were representative of the Luvuvhu-Letaba WMA, namely: Letaba and Giyani which were
contained in the WMA and Mutale, Thulamela and Tzaneen with larger portion of land area
within the WMA (Section 4.2.1). Three municipalities were purposively sampled for their
accessibility with lesser transport costs, and those were Giyani, Mutale and Thulamela.
As for location selection of villages, the sampling frame was composed of 413 villages of which
85 were in Giyani, 118 in Mutale and 210 in Thulamela Municipality. From this sample frame,
ten villages were randomly sampled for the study (Figure 8.1). Although Dopeni is on the little
portion of Thulamela that is outside the WMA, it was included in the study because of its severe
challenge of shortage of water supply. For households, the sample frame and randomly selected
sample sizes (10% of sample frame) for villages selected for the study were: Siyandane - 521,
52; Makosha - 524, 52; Muyexe - 476,48; Sigonde - 152, 15; Makwilidza - 108, 11; Lukau-
324,32; Mavunde - 389,39; Djilongo - 581,58; Xigamani - 567,57; and Dopeni - 1025, 103.
The total sample frame was 4667 with a total sample size of 467.
8.2.3 Data collection and analysis
Data was collected from the 467 sampled households through interviews which were conducted
by trained enumerators using a structured questionnaire. The questionnaire contained both open-
and closed-ended questions which included household socio-economic questions as well as those
151
on water supply and demand. As revealed by Leedy and Ormrod (2010), the closed-ended
questions collected quantitative data while the open-ended questions recorded qualitative data.
This research method that combines the collection and analysis of quantitative data with that of
qualitative data is referred to as a mixed study (Hurmerinta-Peltomaki and Nummela, 2006). The
inclusion of open-ended questions was to enable respondents to speak for themselves, voice the
constraints they faced, articulate their own accounts of what their routines were and how they
satisfied their family's needs.
The data was captured in MS Excel Package and analysed statistically using the SAS Package
(SAS, 2009). The Proe FREQ of SAS was used to generate simple frequency tables for each
variable of interest. Selected data was summarized in Excel Spreadsheet.
8.3 Results and discussion
8.3.1 Characterisation of households
(a) Age of heads of household
Keshavarzi ef al. (2006) revealed that there was a significant relationship (r=0.17, p<0.05)
between head of household's age and the amount of water consumed by the household. This
could be a result of attitudes toward environmental issues where older individuals possess less
information about and give less attention to water conservation. Schleich and Hillenbrand (2009)
argued that the cause of the increase of water consumption with age may be the fact that retired
people spend more time at home and are likely to use water more frequently, or because health
reasons may force older people to use the bathroom more frequently. The profiles of heads of
household in the study area with regard to age will therefore influence their expectations
regarding water supply to their families (Table 8.1).
Table 8.1 shows Giyani to be the only municipality that had child heads of household (4% under
18 years) and these could be orphans. The municipality also had the most heads of household
(28.5%) aged 19-35, suggesting the population there to be more youthful. Mutale had the most
heads of household in the middle ages (36-50) with close to half (48.2%) of them belonging to
152
this category. Thulamela on the other hand had most (17.6%) household heads under retirement
age (>65 years).
Table 8.1 Distribution of heads of household in the study municipalities under the Luvuvhu-
Letaba WMA according to age
Luvuvhu-Letaba
Giyani Mutale Thulamela WMA
A~e f % f % f % f %
< 18 6 4 0 0 0 0 6 1.3
19 - 35 43 28.5 7 12.5 55 22.5 105 23.3
36 - 50 49 32.5 27 48.2 81 33.2 157 34.8
51 - 65 37 24.5 18 32.1 65 26.6 120 26.6
> 65 16 10.6 4 7.1 43 17.6 63 14
Total 151 lOO 56 100 244 100 451 lOO
The distribution of heads of household in the study area was such that the least were children
(1.3% <18) with the number increasing through youth (23.3% aged 19-35) to the middle aged
(34.8% aged 36-50). Thereafter the number declined through the elderly (26.6% aged 51-65) to
those of retirement age (14% aged> 65). According to Schleich and Hillenbrand (2009), the
14% of households with heads on retirement would consume more water and these were more in
Thulamela.
(b) Size of household
The quantity of water used increased with an increase in the number of people living in a
household. However, the increase in water use was less than proportional to the increase in
household size (Arbues et al, 2003 and Keshavarzi et al., 2006). The relationship between
household size and per capita water consumption was further articulated by Schleich and
Hillenbrand (2009) who revealed that per capita water consumption decreased as the number of
household members increased. This was said to be a result of the fact that several water uses
such as laundry, gardening or even preparing food increased less than proportional to the
increase in household size. As stated by Schleich and Hillenbrand (2009), an increase in the
153
number of household members by 50%, i.e. from two to three, raised per capita water demand by
22%.
An investigation of the sizes of households is therefore important to obtain an idea of water
consumption by the households. Mazvimavi and Mmopelwa (2006) revealed that household
sizes in rural villages of Botswana varied from 1 to 10persons per household. Household sizes in
the Luvuvhu-Letaba WMA were reported to be relatively smaller (Figure 8.2).
60 ..._--_ .......-l -
50 49.1
40
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Size of household (number of members) ~I
_Giyani III!i Mutak' mThulan1cla == t.uvuvbo-t.etaba
Figure 8.2 Distribution of households in study municipalities in the Luvuvhu-Letaba WMA
according to their sizes
One in five (20%) households in the study area had one member each with Mutale having the
most (22.6%) and Giyani the least (17.9%) number of households in this category. Communities
in this area still attach value to a self-sustaining family where members perform different roles
and complement each other, and it is uncommon to have households with one member each. The
persons who stayed alone could be the widowed or divorced who did not have children or those
whose children could have relocated because of work or other socio-economic demands. There
154
could also be cases where a child remained orphaned when parents passed on, more so in Giyani
where child heads of household where reported.
Some 45% of households had two members each with most (49.1%) of those in Mutale and least
(41.1%) in Giyani. These could be youthful families who did not have children yet or those
affected by death, divorce, separation, or relocation. About a quarter (26.1%) of the households
had three members each. Mutale which had the most households with one member and those
with two members each had the least households (18.9%) for this group. The largest household
was reported to have only four members where 8.9% of households were of this size and were
most (13.3%) in Giyani and least (6.1%) in Thulamela.
With this maximum membership, households in the study area could be described as very small
compared to those of villages in Botswana that had up to 10members each (Mazvimavi and
Mmopelwa, 2006). According to Stats SA (2009), the household size of four would be an
average for the study area and not the maximum. For some reason, the respondents could have
reported fewer members of households than the actual figures and this resulted in this impression
that the households were small. For purposes of water services planning, the sizes of households
should be assumed to average four as reported by Stats SA (2009).
(c) Household income
Household income is a strong determinant of the supply and use of water. It was argued that
people could be water poor not because there is no safe water in their area but because they are
income poor. In other words, despite water being available within their area, people may fail to
get connected and access safe water because they cannot afford the cost of doing so
(Dungumaro, 2007).
According to Dungumaro (2007), 99.7% of households that belonged to a poor category in South
Africa obtained water from unsafe sources. For the middle income category, a lesser number of
56.8% obtained water from unsafe sources while the rich category had no household obtaining
155
water from those sources. The pattern observed in this analysis was that the number of
households depending on unsafe water sources increased with the level of poverty.
Questions about income are not always welcomed by respondents. As a result, estimates of
household income could be made on the basis of types and quantities of products consumed by
the households (Olvera ef al., 2008). As an attempt to increase the quality of responses,
respondents were asked to only indicate the income categories as opposed to specific incomes
and they responded accordingly (Table 8.2).
Table 8.2 Monthly incomes of households in the study municipalities of the Luvuvhu-Letaba
WMA
Luvuvhu-Letaba
Giyani Mutale Thulamela WMA
Income f 0/0 f % f % f 0/0
No response 24 15.7 0 0.0 10 4.0 34 7.4
RO- RIOOO 64 41.8 25 44.6 99 39.8 188 4.1.1
RIOOl - R5000 48 31.4 20 35.7 117 47.0 185 40.4
R5001 - 10000 12 7.8 9 16.1 17 6.8 38 8.3
>RIOOOO 5 3.3 2 3.6 6 2.4 13 2.8
Total 153 100.0 56 100.0 249 100.0 458 100.0
Some respondents (7.4%) did not provide information even when they were asked to only
indicate the income categories, and those were mostly in Giyani where 15.7% did not disclose
their incomes. Two in five (41.1%) households almost evenly distributed across municipalities
earned RO-R1000 per month. Those could be households that depended mainly on casual jobs
and those reliant on social grants, especially child support paying R250 and disability paying
R750 per person per month for the 2010-11 tax year. The same number (40.4%) of households
had monthly incomes of R1001-R5000 with most (47%) of them located in Thulamela. The old
age grant was the most paying at R1080 per month and therefore some of these households could
be reliant on those grants.
156
Based on a United Nations poverty line of US$1.25 per capita per day (World Bank, 2008) at a
US$ : Rand exchange rate of 8, the poverty threshold income in the study area will be RIO per
capita per day or RI 200 per four member household per month. Based on this information, the
41.1% of households with monthly incomes of RO-l 000 will all be poor with some of those with
monthly income of RlOOl-R5000 also falling in this category. In the absence of government
interventions on water supply, the households will generally not afford to pay for water and
according to Dungumaro (2007) will rely a lot on unsafe water sources.
(d) Size of house owned
Ownership of assets has strong links with the economic well-being of households. An inverse
relationship was recorded between ownership of assets and poverty, implying that poverty can be
alleviated by increasing people's asset base (Fox et al., 2009; Erenstein et al., 2010). A house is
an important asset for any household and its size determines the economic status and
subsequently the supply and use of water by the household. The sizes of houses owned by
households in selected municipalities in the Luvuvhu- Letaba WMA were much variable (Table
8.3).
Table 8.3 Sizes of houses owned by households in study municipalities in the Luvuvhu-Letaba
WMA
Giyani Mutale Thulamela Luvuvhu-Letaba WM.ANumber of
rooms f 0/0 f 0/0 f 0/0 f 0/0
I 3 2.0 3 5.4 16 6.4 22 4.8
2 15 9.8 4 7.1 37 14.9 56 12.2
3 13 8.5 14 25.0 39 15.7 66 14.4
4 35 22.9 11 19.6 52 20.9 98 21.4
5 25 16.3 9 16.1 41 16.5 75 16.4
6 16 10.5 6 10.7 23 9.2 45 9.8
7 20 13.1 6 10.7 15 6.0 41 9.0
>7 25 16.4 3 5.4 21 8.4 49 10.7
Total 152 99.4 56 100.0 244 98.0 452 98.7
157
Table 8.3 shows that 4.8% of the households had only one room each. This room would be used
as a kitchen, dining, lounge and bedroom, reflecting a desperate state of lack of housing
accommodation and indeed of poverty. One in eight (12.2%) households had two room houses
and that still suggested shortage. Most (14.9%) households with one and two room houses were
in Thulamela, implying severe lack of housing development in this municipality.
The majority of houses were 3-4 rooms in Mutale and 4-5 rooms in both Giyani and Thulamela.
Some households (29.5%) in the study area had bigger houses with more than five rooms. Some
houses were built for the communities by government under its Reconstruction and Development
Programme (RDP) at no cost to occupants. The sizes of houses owned by households in the
study area could therefore not be a reliable indicator of their economic status.
8.3.2 Household water supplies
(a) Water sources and their safety
The quality of water fetched is influenced by the safety of the sources used and is dependent on
the economic status of the household. Poor households in South Africa obtained water from less
safe sources of wells, vendors or kiosks while wealthier residents had safer piped connections
(Goldblatt, 1999, Aiga and Umenai, 2002, Manase et al., 2009). Household water sources in the
area under study were variable and ranged from unsafe to safe sources (Table 8.4).
Some 2.7% of households still obtained water from unsafe rivers with most (5.2%) of these
located in the water scarce Giyani Municipality. Fewer (1.4%) households relied on less safe
wells for water. Some 5.7% of the households bought water from neighbours again with most
(16.5%) of them residing in Giyani, and the safety of such water would depend on the primary
source. Up to 15.8% of the households relied on fairly safe boreholes for water with most
(21.3%) located in Thulamela Municipality. Although truck delivery was not an important
source, its safety would also depend on the primary source of the water. Half (50.l %) of the
households obtained water from the safer street taps supplying treated water with most (83.9%)
of them located in Mutale and least (33.0%) in Giyani. Combinations of sources supplied 24% of
158
households with water and might have been unsafe or safer depending on the sources used at any
time (Table 8.4).
Table 8.4 Sources of water for households in the study municipalities of the Luvuvhu-Letaba
WMA enlisted from unsafe (1) to safer (6) sources
Luvuvhu-Letaba
Water source Giyani Mutale Thulamela WMA
f 0/0 f 0/0 f 0/0 f 0/0
1. River 6 5.2 I 3.2 3 1.4 10 2.7
2. Well 1 0.9 0 0.0 4 1.8 5 1.4
3. Buy 19 16.5 0 0.0 2 0.9 21 5.7
4. Borehole 11 9.6 0 0.0 47 21.3 58 15.8
5. Truck delivery 0 0.0 1 3.2 0 0.0 1 0.3
6. Street tap 38 33.0 26 83.9 120 54.3 184 50.1
7. Combinations 40 34.8 3 9.7 45 20.4 88 24.0
Total 115 100.0 31 100.0 221 100.0 367 100.0
The fact that safe water sources of street taps and fairly safe boreholes were common in the study
area suggests that some public investment was made in water infrastructure. This intervention
was necessary for the poor community to access safe water; else they would not afford to pay for
access to the resource. The development of water infrastructure in an area would depend on
availability of water resources. Giyani was highly limited in water resource availability and
therefore little infrastructure could be developed.
The supply of quality water still needs to be improved in all the municipalities, and this requires
availability of the resource. Rivers in this WMA were already much exploited in terms of
construction of darns (Section 4.3.l(b)), and little opportunities would be available for further
development of the storage infrastructure. An exception was the Mutale River as it was strongly
flowing with catchment mean annual runoff of 157.1 million m3 and had small storage capacity
of only 3.9 million rrr'. The Department of Water Affairs (DWA) should explore opportunities
for construction of a new darn on this river together with a water treatment facility. The
159
department should also do more seoping for underground water and drill more community
boreholes where possible.
(b) Distance of water source from residential site
The distance of water sources from residential sites was influenced by the level of social and
economic development of a community. The distance generally shortened with more
development (Makoni et al., 2004). Less than half (46.7%) of households in the study area were
located less than 1 km from the water sources (Figure 8.3), suggesting a state of under-
development.
60 T
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:P: Giyani I Mutale Thulamela. Luvuvhu-Letaba
-------
Figure 8.3 Distribution of households in study municipalities of the Luvuvhu-Letaba WMA
according to the distance of water source from residential sites
The water sources within 0-1 km of residential sites were more (53%) in Thulamela and fewer in
the other municipalities and could be mostly street taps. The water sources were located within
160
1-2 km from residential sites of 17.9% of the households. These sources were also more (20.9%)
in Thulamela and fewer (8.9%) in Mutale. The sources located in this distance could be mainly
boreholes as these were reported by more (21.3%) households in Thulamela and by fewer in
other municipalities (Figure 8.3).
Less than half (46.7%) of the households in the study area used water sources located within a
distance of 1 km from the residential sites. Water sources were mostly located more than 1 km
away from residential sites of the majority of the households. According to Mazvimavi and
Mmopelwa (2006), the water sources located more than 1km from residential sites as was the
case here might be considered inaccessible and would adversely affect the per capita volume of
water used to satisfy basic personal hygiene. The Mopani and Vhembe WSAs should develop
more reticulation infrastructure to improve access of water in the study area.
(c) Quantity of water fetched
Literature with information on how much water is supplied to a household is very limited
(Whittington, 2002). The volume of water collected by a household in rural settlements in
Botswana varied from 20 to 400 litres with an average of 100 litres per day. The supply of water
to some households in Botswana made provision of less than 20 litres per capita per day, and
with this provision, basic personal and food hygiene requirements for water could not be
satisfied (Mazvimavi and Mmopelwa, 2006). The supplies of water to households in the study
municipalities were variable with some reporting 0-25 litres per day while others received more
.than 200 litres per day (Table 8.5).
According to Table 8.5, some 7.4% of households in the study area fetched a maximum of 25
litres of water per day with 10.5% located in Giyani, 16.1% in Mutale and 4.6% in Thulamela.
One in nine (11.3%) households fetched 26-50 litres per day with Mutale being home to 45.2%
of them. Mutale had the most (83.9%) households supplied from street taps (Table 8.4) and those
could be closer to residential units, and yet it had the highest numbers that fetched lesser
quantities ofO-25 and 26-50 litres per day.
161
Table 8.5 Distribution of households in the study municipalities of the Luvuvhu-Letaba WMA
according to quantity of water fetched
Quantity of Luvuvhu-Letaba
water fetched Giyani Mutale Thulamela WMA
(litres per day) f 0/0 f 0/0 f 0/0 f 0/0
0-25 12 10.5 5 16.1 10 4.6 27 7.4
26 - 50 10 8.8 14 45.2 17 7.8 41 11.3
51 - 75 37 32.5 6 19.4 45 20.5 88 24.2
76 - 100 15 13.2 0 0.0 17 7.8 32 8.8
101 - 150 Il 9.6 1 3.2 49 22.4 61 16.8
151 - 200 8 7.0 3 9.7 27 12.3 38 10.4
> 200 21 18.4 2 6.5 54 24.7 77 21.2
Total 114 100.0 31 100.0 219 100.0 364 100.0
The lesser amounts fetched could have resulted from the fact that the municipality had smaller
households where 22.6% had one and 49.1% had two members (Figure 8.2). With more street
taps in the municipality, households could have connected own pipes to convey water to their
yards where uses such as crop watering would be catered for directly without the water having to
be stored in containers. Only water for important uses such as drinking and cooking would be
stored in containers and would accordingly be reported as water fetched and this would result in
the impression that households in the municipality fetched lesser amounts of water.
Most households (24.2%) fetched 51-75 litres per day with 32.5% in Giyani, 19.4% in Mutale
and 20.5% in Thulamela. Some 8.8% of households fetched 76-100 litres while 16.8% fetched
101-150 litres of water per day. Some 10.4% of households fetched 151-200 litres while 21.2%
had daily quantities of water in excess of 200 litres with most of them (24.7%) in Thulamela
followed by Giyani (18.4%) and least (6.5%) in Mutale. Such households had water supplies
exceeding double the recommended minimum of 25 litres per capita per day for a four person
household (DWAF, 1994).
The results indicate that half (51.7%) of the households fetched :S 100 litres of water planned for
a four member household per day and this affirms the need for improvement of water supplies in
162
the study area to ensure adequate provision for all households. The prospects for constructing a
dam in the currently under-utilized Mutale River should be considered. The new Nandoni Dam
in Thulamela should improve supplies in the municipality and other needy areas with planned
transfers to Nsami Dam likely to address the scarcity in Giyani.
(d) Influence of distance of water sources from residential sites on quantity fetched
A study of household water consumption in Nicaragua revealed that a decrease in the distance to
the water source from 1000m to 10m was associated with an increase in per capita water
consumption of 20% (Keshavarzi et al., 2006). This view was affirmed by Katsi et al. (2007)
who stated that water sources nearer to residential sites provided respondents with easy access to
water, making it possible for the households to fetch more water. The relationship between
distance to water source and the resource consumption per capita as reported by Keshavarzi
(2006) and Katsi et al. (2007) occurred in the study area (Figure 8.4).
"0 30
<..l.i.t::-Gi..... 25<11
-n
..s.
.3 20
-0.>~- 15.c
a'':"J 10
s
0
0 10 20 30 40 SO GO 70
Distance of water source from residential site
.......................................
Figure 8.4 Influence of distance of water source from residential site on quantity fetched
There was a medium to strong correlation (R2=0.6988) between the distance of water sources
from residential sites and the quantity of water fetched (Figure 8.4). As revealed by the graph
163
(Y= -0.409 x + 28.2), the quantity of water fetched increased with a decrease in the distance of
the water sources from residential sites. This affirmed Katsi et al. (2007) statement that water
sources nearer to residential sites provided respondents with easy access to the resource. Where
adequate runoff is stored, installation of reticulation pipes will reduce the distance of the water
sources to residential sites and will lead to more quantities being fetched by households.
8.3.3 Household water uses
(a) Water use activities
The water use is influenced by population growth and types of socio-economic activities
performed (Molden et al., 2000; Saleth and Dinar, 2003). Rural households use water for both
indoor and outdoor activities. Indoor water uses include consumption for drinking, preparing
food and hygiene activities such as bathing and laundry (Merrett, 2002; Keshavarzi et al., 2006;
Katsi et al., 2007). Outdoor activities include car washing, livestock drinking and garden
watering (Arbues et aI., 2003; Keshavarzi et al., 2006).
Also, water use in rural areas may be classified into basic household and productive uses. Basic
household uses refer to water used for drinking, preparing food and personal hygiene. Productive
consumption on the other hand highlights economic activities that are highly dependent on
availability of water supplies, namely vegetable gardens, animal drinking, traditional beer
making and brick making (Makoni et al., 2004; Mazvimavi and Mmopelwa, 2006). The majority
of households in the study area used water for basic as opposed to productive consumption
(Table 8.6).
The basic household activities reported to have consumed water were drinking by people (95.9%
of households), preparing food for home consumption (95.4%), bathing (92.8%) and laundry
(90.8%). Most households were reported to have used water for these activities in Thulamela
followed by Mutale and Giyani. These activities are the basic requirements for life and it would
therefore be expected for all households to have allocated some water to them. The impression
that certain households did not use water for some of these activities is incomprehensible, more
164
so for drinking by people and preparing food and this could have been exaggeration of the water
scarcity by some respondents.
Table 8.6 Distribution of households in study municipalities of the Luvuvhu-Letaba WMA
according to uses of water for basic household and productive activities
Luvuvhu-
Water use Giyani Mutale Thulamela Letaba WMA
Basic household f 0/0 f 0/0 f 0/0 f 0/0
1. Drinking by people 141 92.2 52 92.9 246 98.8 439 95.9
2. Cooking for home consumption 141 92.2 52 92.9 244 98.0 437 95.4
3. Bathing 134 87.6 52 92.9 239 96.0 425 92.8
4. Laundry 130 85.0 46 82.1 240 96.4 416 90.8
Productive
5. Washing car 5 3.3 9 16.1 16 6.4 30 6.6
6. Irrigating crops 2 2.6 8 16.1 7 5.2 17 5.7
7. Livestock drinking 1 0.7 6 10.7 9 3.6 16 3.5
8. Cooking food for sale 0 0.0 0 0.0 3 1.2 3 0.7
9. Brewing drinks for sale 0 0.0 0 0.0 8 3.2 8 1.8
Fewer households used water for productive activities and this confirmed the scarcity of the
resource in the study area. The Mutale Municipality was reported to have used more water for
productive purposes than Thulamela and Giyani. Water supply for the productive activities such
as car washing and crop watering could have been soureed through connecting own pipes to
street taps by the 83.9% of households who relied on these taps (Table 8.4). Such water might
not have to be stored in containers and would not be measured, hence the households in the
municipality would report having fetched lesser quantities of water (Table 8.5). After Mutale,
more households soureed water from street taps in Thulamela than those in Giyani, and
accordingly more households used the resource for productive purposes in Thulamela compared
to Giyani. Improving access to water would increase the use of the resource for productive
activities in all municipalities and would trigger growth of the rural economy.
165
(b) Quantity of water required by households
There is a dearth of reliable information on quantity of water required by households for
different purposes (Merrert, 2002). In Mvunyane village in South Africa, 43% of households
used less than 50 litres and a further 49% used between 50 and 100 litres of water per day. With
the average household size in Mvunyane being five people, the average quantity of 15 litres of
water used per capita per day was far less than the design standard of 25 litres per capita per day
(DWAF, 1994 and Goldblart, 1999).
Households in the study area had no metered connections and that made it difficult to have
accurate figures of the quantities of water they used. Whittington et al. (2002) revealed that even
villages with household connections could lack or have broken meters making it difficult to
estimate precisely how much of the water supplied actually reaches the customers. As stated by
Whirtington et al. (2002), households with connections could also use alternative sources of
water such as wells and public taps which would complicate calculation of the amount of water
consumed. It was for this reason that this study accepted estimates of the quantities of water
required as provided by respondents (Table 8.7).
As presented in Table 8.7, the majority of respondents estimated the household water
requirements to be 0-25 litres each for drinking (95.6% of households), cooking (91.5%) and
bathing (63.1%). Laundry was reported by most households (43.6%) to require more than 50
litres per day and this could be estimated at 75 litres based on the fact that a 25 litre container is
commonly used to fetch water. The requirement of more than 50 litres could mean one or more
additional containers. Based on these results, a household would require 150 litres of water per
day. The 150 litre household water budget could be under- or over-estimated and would require
comparison with results of related studies before acceptance.
166
Table 8.7 Distribution of households in the study municipalities of the Luvuvhu-Letaba WMA
according to their daily water requirements for different uses
Quantity of Luvuvhu-
water needed Giyani Mutale Thulamela Letaba WMA
Specific water use (litres) f 0/0 f 0/0 f 0/0 f 0/0
Drinking 0-25 149 97.4 53 94.7 236 94.8 438 95.6
26 - 50 4 2.6 2 3.6 13 5.2 19 4.2
> 50 0 0.0 1 1.8 0 0.0 1 0.2
Cooking 0-25 143 93.5 53 94.7 223 89.6 419 91.5
26 - 50 8 5.2 3 5.4 26 10.4 37 8.1
> 50 2 1.3 0 0.0 0 0.0 2 0.4
Bathing 0-25 95 62.1 43 76.8 151 60.6 289 63.1
26 - 50 35 22.9 6 10.7 57 22.9 98 21.4
> 50 23 15.0 7 12.5 41 16.5 71 15.5
Laundry 0-25 93 60.8 34 60.7 65 26.5 192 42.3
26 - 50 17 11.1 13 23.2 34 13.9 64 14.1
> 50 43 28.1 9 16.1 146 59.6 198 43.6
The ideal amount of water required per capita per day was estimated at 1.7 (Ershow and Cantor,
1989) to 21itres (WHO, 1996) for drinking, 10 to 20 litres for cooking (Inocencio et al., 1999),5
to 15 litres for bathing and 8 to 10 litres for laundry (Gleick, 1996). This makes a lower estimate
total water requirement of 24.7 and a higher estimate total requirement of 47 litres per capita per
day suggesting an average requirement of 35.85 litres per capita per day. The average water
requirement for a four member household is therefore estimated at 143.4 litres and is very close
to the 150 litres reported by the respondents. The estimate water demand of 150 litres per day
reported for households in the study area may therefore be regarded as credible for an average
household.
Rural households are currently supplied based on design standard of 25 litres per capita per day
(DWAF, 1994) and for the average household of four members this translates to 100 litres per
household per day. Supplies of 150 litres per household would provide 37.5 litres per capita per
day. The current design standard for rural water supply is therefore less than the requirement
presented by respondents by 50 litres per household per day or 12.5 litres per capita per day.
167
8.4. Summary and conclusion
Heads of household were mostly in the middle ages of 36-50 (34.8%) years old. Households
were poor with low monthly incomes of RO-R1000 for 41.1% and R1001-R5000 for 40.4% of
the families.
The study area has a scarcity of water supply exacerbated by the dearth of infrastructure for its
reticulation. Half (50.1%) of households obtained water from street taps and 46.7% had good
access to water sources with elderly households having better access than their youthful
counterparts. The quantity fetched was widely variable, 7.4% of households fetched 0-25 litres
and 21.2% fetched > 200 litres per day. Households that are located nearer to water sources
fetched more water than those away from the sources.
As a result of the scarcity of the water supply, more households only used water for basic
activities such as drinking (95.9%), preparing food (95.4%) and bathing (92.8%) compared to
those who used it for productive activities such as washing cars (6.6%) and watering crops
(5.7%). Half (51. 7%) of the households fetched less water than the 25 litres per capita per day
supply standard. Analysis of the requirements revealed that the 25 litres per capita per day did
not meet the average requirement of 37.5 litres per capita per day.
168
CHAPTER9
9 CHALLENGE AND CAPACITY CONGRUENCE ANALYSIS FOR
DEVELOPMENT OF A WATER MANAGEMENT DECISION MODEL
9.1 Introduction
Periodic droughts and population growth have placed burdens on water supply and demand. This
results in communities being faced with challenges such as resource scarcity resulting in
negative socio-economic impacts. In order to successfully address water challenges, an
appropriate resource management decision model that takes into account the relevant capacity of
service organisations is required.
The major challenges affecting the water sector in the Limpopo Province include resource
scarcity exacerbated by inadequate storage (Chapter 4), failure of some reservoirs to fill up
which confounds water management decisions by resource managers (Chapter 5), poor resource
knowledge of managers (Chapter 6), lack of effective stakeholder participation in water
decisions (Chapter 7) and ultimately inadequate water supply to rural households (Chapter 8).
These challenges were investigated (chapters 4 to 8) and proposals made on how they may be
addressed.
The purpose of this study was to (1) highlight the challenges faced by the water sector in the
study area, (2) identify relevant water service organisations authorised to address these
challenges and assess their capacity to do so, (3) analyse the degree of congruence between the
challenges and the capacity of identified water service organisations, and (4) to subsequently
propose a water management decision model (Section 1.4, Table 3, ultimate objective). High
levels of congruence between the challenges and the capacity of water service organisations to
address these challenges suggest future improvement of water supply and vice versa and
therefore the Congruence Model of NadIer and Tushman (1980) provides a suitable framework
for developing the water management decision model.
169
9.2 Description of the Congruence Model
The Congruence Model views organisations as made up of components that interact with each
other (Figure 9.1). These components are inputs that include environment, resources, history and
strategy; transformation that is influenced by tasks, human resources, financial resources and
formal and informal organisational arrangements; and outputs that may be organisational, group
or individual (Nadler and Tushman, 1980) as alluded to in Section 3.5.5(b).
The model provides for information flow from a source component to a recipient component and
this information may (or not) be subjected to congruence rating to assess its relevance (Figure
9.1). Also, the model provides for flow of action which is rated for congruence with the available
challenge to assess the degree to which the action is relevant. Interactions within a service
organisation influence its performance and are therefore also included in the model. The model
provides for feedback which informs improved strategy for the next cycle of action. The
description ofNadler and Tushman (1980) was affirmed by Gill (2000) and Mertikas (2008) who
indicated that an organisation as represented by the Congruence Model take input, put them
through transformation and produce outputs.
170
Illnput II II Transformation II II Output II
Situation analysis
Desired results
, ,
Environment r
Task
, based-., on
____I, strate/7~ OrganisationalI
Resources I a ,,I gy
1- , , Strategy 1 ~ .. [Human ) cfJ I GroupI' ~ I
\..
History , ~ -. Organisation I Individual
/('C arrangement I
Strategy 2 I~----- --,I ----------------------~---I
---_- I Feed back
\... -,.. _
I ---_~ ~----------------------------ï---I II I
I -
Figure 9.1 Adjusted Congruence Model of Nadier and Tushman (1980)
171
Meanings of diagrams in the model as adapted from Forrester diagrams
Component of Congruence Model
A state variable; Final results of what happened
Element of a state variable
I I Auxiliary or intermediate variable
Element of auxiliary or intermediate variable
------ ",
1 X ')
1- .. ; Unidirectional flow of information with congruence rating (x)
"I
; ----- ," ..
~ ,~ I1 Unidirectional flow of information without congruence rating
Unidirectional flow of action with congruence rating (x)
Two directional flow of action with congruence rating (x)
Interaction
Future flow of action
172
A relative degree of congruence or fit exists between each pair of components of the model. The
congruence between two components is defined as the degree to which the needs, demands,
goals, objectives, and structures of one component satisfy (or not) those of the other (Nadier and
Tushman, 1980). Congruence therefore is a measure of how well pairs of components fit
together.
9.2.1 Congruence between units across components: Person-Environment Fit
According to the Congruence Model, the achievement of positive outputs is dependent upon the
degree of congruence between the inputs and the transformation components. A high degree of
congruence is realised between inputs and transformation when a similar extent of congruence
occurs between pairs of units across these components. Knowledge of congruence between pairs
of units across components of the model is therefore necessary to understand the congruence
. between components themselves. The unit of environment under input and person or individual
under transformation component was used as example to discuss the issue of congruence
between units.
The concept of 'person-environment (P-E) fit' refers to similarity or convergence between a
particular set of person-related attributes and a set of environment-related attributes (Schneider et
al., 1992). The underlying assumption is that organisations will be more effective when the
attributes of a person and those of environment match or are highly congruent (Ostroff, 1993).
The P-E fit has been positively related to job satisfaction, organisational commitment and career
success (Bretz and Judge, 1994; Chatman, 1991 and Kristof, 1996).
Considering the water sector, a high degree of congruence between the unit of environment
under input and that of person under transformation (within the water service organisation) will
contribute to a more effective service organisation. Similarly, high degrees of fit between pairs of
other units across the two components of environment and transformation in water service
organisations will make the organisation to be more effective.
173
9.2.2 Congruence between units within a component: The example of transformation
In addition to congruence between units across components of the model, the effectiveness of
organisations is also dependent on the degree of congruence between pairs of units within a
component. With the transformation component playing a critical role of converting inputs to
outputs, it was used as an example for discussing the congruence between pairs of units within
the component. Again the person or individual was adopted as a key unit that was matched with
other units such as organisation, group and job to assess the degree of congruence.
(a) Person-organisation fit
The concept of 'person-organisation (P-O) fit' refers to a match between individual and
organisational characteristics (Kristof, 1996). The P-O fit may be defined as the congruence
between individual values and organisational values (Boxx et al., 1991; Chatman, 1989, 1991;
Judge and Bretz, 1992; O'Reilly et al., 1991). Organisational values include such aspects as
culture which informs people about the appropriate way things are done in the organisation
(Balkin and Schjoedt, 2012). Some organisational cultures are rigid and do not provide for
employees to make independent decisions while others are flexible and allows the employees to
make decisions.
Self-motivated employees (persons) would want to decide on their own goals, work schedules,
methods of work and outputs (Cascio, 1999; Sparrow and Daniels, 1999) and would therefore fit
in flexible work situation such as that offered by virtual organisations (Boudreau et al., 1998;
Jarvenpaa and Leidner, 1999). These organisations that offer a flexible work situation are often
multi cultural (DeSanctis et al., 1999; Jarvenpaa and Leidner, 1999) and are therefore able to
accommodate employees from different cultural backgrounds.
The attainment of P-O fit is very necessary for water service organisations to be effective. Lack
of P-O fit results in disharmony between employees and the water service organisations and this
leads to poor performance of the organisations.
174
(b) Person-group fit
The person-group (P-G) fit is defined as the compatibility between an individual and his or her
workgroup (Kristof, 1996). The P-G fit is a measure of the similarity in personality among group
members (Ferris ef al., 1985) or possession of effective interpersonal skills (Werbel and
Gilliland, 1999).
Models such as the Congruence Model that advocate for P-G fit promote (1) congruence between
the demographic characteristics of an individual and those of their workgroups (Jackson ef al.,
1991); (2) similarity among group members personality, values, and goals (Klimoski and Jones,
1995); and possession of interpersonal skills that are necessary for effective cooperation with
other group members (Werbel and Gilliland, 1999). It may be inferred that attainment of a high
degree of similarity among the personality and values of different group members requires
regular communication among the members. The regular communication allows the group
members to share their diverse personality and values and to gradually establish a state of
homogeneity with regards to these personality and values.
(c) Person-job fit
The concept of 'person-job (P-J) fit' refers to the degree of congruence between individual
characteristics and job requirements (Edwards, 1991; CaldweIl and O'Reilly, 1990). The P-J fit
commonly lacks where employees have a shortage of competence that is critically required by
the job (Cascio, 2000).
Issues resulting in employees lacking critical competence required by their jobs could include
problems at recruitment. In situations where employees do not have the required competence for
their jobs, attainment of P-J fit will require the organisations to invest in interventions such as
human resource development or to outsouree the lacking expertise. Persistent lack of P-J fit will
result in the organisation not performing to its plans and subsequently being ineffective.
175
9.2.3 Congruence and water sector effectiveness
The effectiveness of an organisation in achieving its output requires some degree of congruence
between pairs of components such as input and transformation and between pairs of units within
each component. Effectiveness was defined as the degree to which actual organisational outputs
are similarto expected outputs (Nadler and Tushman, 1980; Wyman, 1998; Bezboruah, 2008).
For this study, the congruence between the water challenge and the capacity of service
organisations as described by their strategies, tasks and the allocation and use of resources is
critical.
A higher degree of congruence between the water sector challenge and the capacity of service
organisation to address the challenge will result in increased effectiveness of the water sector.
The capacity of the service organisations to address water challenges is dependent upon the level
of congruence between the pairs of components defined by the Congruence Model and between
pairs of units within each component.
The expected outputs of the water sector in the Limpopo Province are a well-managed, water
resource with appropriate storage and other water infrastructure, availability of research
knowledge for resource management, active participation by all relevant stakeholders and
adequate supply of water to communities. If the capacities of relevant service organisations are
congruent with the sector challenges, they should be focussed on achieving these outputs.
9.3 Researchmethodology
9.3.1 Rationale for selecting the Congruence Model
The research identified major challenges experienced by the water sector in the study area, and
relevant research objectives were developed (Section 1.4, Table 1.3). The investigations
conducted in chapters 4 to 8 were based on the identified research objectives and had each
important recommendation(s). In order to successfully address the water sector challenges, water
service organisations would have to implement the recommendations of the investigations and
this would depend on availability of relevant organisational capacity.
176
Deciding on whether a water service organisation has relevant capacity to resolve a water sector
challenge or not necessitated matching of appropriate attributes of the organisation with the
water challenge to determine the degree of fit. A high degree of fit would suggest that the
organisation has relevant and adequate capacity to resolve the water challenge and vice versa.
The Congruence Model emphasizes the essence of fit between relevant components for
organisations to be effective in producing desired outputs. Upon evaluation of different models
(Section 3.5.5(b)), the Congruence Model proved to be suitable for assessing the degree of fit
between the water sector challenges and subsequent strategies of service organisations and
between strategies and transformation components (within organisations) and was therefore
selected.
The proposed congruence based model for water management decision making for Limpopo
(Figure 9.3) highlights the three main components of the Congruence Model, namely: input,
transformation and output. Under the input component, focus was provided to environment
which was considered under the Political, Environment, Social, Technology, Economic and
Legal (PESTEL ) framework to highlight the water sector challenges. The symbols used were as
defined under the description of the model (Section 9.2, Figure 9.1). Although the model was
recommended at a provincial level, it may be used to assess the capacity of water service
organisations to address sector challenges at all levels, e.g. catchment, WMA or nationally by
DWA.
9.3.2 Sampling procedure
Purposive sampling was used to select the water service organisations to be evaluated for
development of a water management decision model within the framework of the Congruence
Model. The Limpopo Regional Office of DWA was selected as it is the custodian of water in the
province. The WSAs of Mopani District Municipality (MDM) largely in the Luvuvhu-Letaba
WMA, Vhembe District Municipality (VDM) across both Limpopo and Luvuvhu-Letaba WMAs
and the Polokwane Local Municipality (PLM) in the Limpopo WMAs were deliberately selected
for their proximity to the place of stay of the researcher.
177
9.3.3 Description of the study area
In addition to the Limpopo Regional Office of OW A located in Polokwane, three WSAs were
targeted by the study: MOM, VDM and PLM which cover both the Limpopo and Luvuvhu-
Letaba WMAs (Figure 9.2). Mainly due to topography, rainfall in the WMAs varies from well
over 1000 to less than 300 mm per annum. The mean annual runoff of the Limpopo WMA is
985.9 million m3 while that of the Luvuvhu-Letaba WMA is 1 183.9 million m3 (section
4.3.1(a». The water resource is more used in the Luvuvhu-Letaba WMA.
wt·
M.oln__Town.....
-Ji,lalnAMtn
CWlJler",.n(fJlJmerw"rees
OI.tl1ct MunIcIpalities
LIMPOPO ~-IDZ2"l""""PoIoIovr.,.., MunC_1es
t::IPnMI'C~ So.,m.,ne
INKOMATI
Figure 9.2 Map ofLimpopo Province showing the Limpopo and the Luvuvhu-Letaba WMA (red
line), Mopani and Vhembe District Municipalities and the Polokwane Local Municipality
(hatchings)
178
The current shortfalls and the future growth in requirements will be supplied from water which
becomes available as a result of interventions such as improved water management (DWAF,
2004a). Such interventions require the water services organisations to have relevant capacities
that are congruent to the challenges faced by the sector.
9.3.4 Data collection and analysis
Proposed solutions of challenges faced by the water sector in the province was obtained from the
results of investigations in chapters 4 to 8 while information on capacity of water service
organisations came from the strategic and integrated development plans and annual reports of
these organisations. The WSAs are newly developing organisations without some of the
necessary information available over the years, especially that on resource allocations and
utilisation. Where information was provided, the plans and reports dealt with different issues
across the WSAs and across the years and this made analysis difficult.
A fair amount of information with some degree of convergence on issues covered was obtained
for the 2009-10 financial year and hence analysis was based on this year. The documents used to
obtain information on the capacity of water service organisations were the 2007/08-2009/10
Strategic Plan for DWA (DWA, 2007), 2006-12 Integrated Development Plan for MDM (MDM,
2009), 2009-10 Integrated Development Plan for VDM (VDM, 2009) and 2009-11 Integrated
Development Plan for PLM (PLM, 2009). Information was also obtained from other relevant
literature.
In order to ensure consistence in the type of information collected from the plans of the water
service organisations, the major challenges experienced by the water sector were highlighted.
The statements in the plans of water service organisations that proposed solutions to the sector
problems were noted and used to assess the congruence between the capacity of the organisation
and the water sector challenge. The congruence analysis is based on the plans of the water
service organisation and hence estimates the prospects for the organisations to successfully
address the water sector challenges.
179
Although the information was mainly qualitative, some quantitative data was used and that
included data on the amount of resources allocated and those utilized by the organisations.
Spread sheet calculations were performed on quantitative data and objective rating of congruence
between planned and utilized human and financial resources was conducted. The qualitative
information on different aspects of organisational capacity was properly summarized, organised
and subjectively rated for congruence with the water sector challenges (Lee, 1999; Leedy and
Ormrod,2010).
Arbitrary numerical scores were decided upon and used for the rating of the degree of
congruence between aspects of capacity of water organisations and the sector challenges. The
scores were in a scale of 0-3 where 0 indicated no congruence, 1 indicated low, 2 indicated
moderate and 3 indicated a high degree of congruence. This type of research where both
quantitative and qualitative data is collected and analysed is described as a mixed study
(Hurmerinta-Peltomaki and Nummela, 2006).
The congruence scores were accordingly interpreted in the context of determining the prospects
for water service organisations to successfully address sector challenges. Higher congruence
scores for both quantitative and qualitative aspects suggested a higher degree of fit between the
water sector challenge and the capacity of the service organisation to address it and vice versa.
9.4 Results and discussion
9.4.1 Input components and their influence on the water sector
Inputs are factors that characterise the water sector and include the environment, resources and
history (Nadler and Tushman, 1980; Wyman, 2003; Bezboruah, 2008). These inputs define the
conditions of the water sector and are described as follows:
(a) Environment
Analysis of the water sector environment highlights the demands, constraints and opportunities
availed to water service organisations (Nadler and Tushman, 1980). Sound description of the
180
water environment includes factors such as resource scarcity and storage development, reservoir
hydrology, knowledge systems acquired by different stakeholders, stakeholder interactions and
resource allocations to different users etc. The status of these factors in the study area has some
influence on the performance of relevant water service organisations (Table 9.1).
As presented in Table 9.1, water service organisations in the study area operate under a stressful
environment. Well thought through logical strategies would be necessary for the situation to be
turned around. Important strategies to address water scarcity would include the development of
storage capacity to capture water in the season of abundance and make it available during that of
scarcity (KeIler et al., 2000).
Table 9.1 Water sector environment of the Limpopo Province
Environment Status in the water sector in Limpopo Province Influence on performance of water
al factor service organisations
Water Physically water scarce confirmed by low rainfall Water scarcity with inadequate storage
scarcity and and runoffs but still has opportunity for storage reduces economic activities and threatens
storage development. Poot in water conservation. political stability. This stresses the service
development organisations as users keep demanding
more water.
Reservoir Dams were built in different river catchments Inappropriate water management
hydrology with more In the Luvuvhu-Letaba than the decisions, exacerbates the effect of
Limpopo WMA. Some dams never fill up and this resource scarcity. Relevant information /
confuses stakeholders in decision making. technologies are needed to guide reliable
decision making.
Resource Water managers have little knowledge of the The managers make decisions that do not
knowledge of water resources but are more knowledgeable on promote availability of water to the
water resources uses. economy and this threatens social and
managers political stability.
Sector Government stakeholders dominate in meetings Communities feel excluded and do not
stakeholder and other social events of provincial and district support the decisions made. This
participation water sector forums, coordinate committee on negatively influences the performance of
agricultural water, and water summits. the service organisations.
Water Water is non-equitably allocated across sectors As a result of inequitable resource
allocations to and geographic areas (rural vs urban) based on allocations, some people have little or no
different users political power and legal instruments such as the supply at all, and this makes them
1956 Water Act. Equitable allocation requires disgruntled.
allocation reform which is constrained by
uncontrolled water trading
181
The water economy in South Africa is characterized by high demand for the resource and
competition among use sectors (Randall, 1981; Backeberg and Groenewald, 1991) and hence
development of storage capacity should be accompanied by efficient use of the water resource
for the strategy to be more effective.
Sound management of the water resource necessitate knowledge of the hydrologic responses of
the developed storage facilities (Kongo and Jewitt, 2006). The water managers are important
decision makers in water resource management and are among those who should be
knowledgeable in various water supply and use issues. Other relevant stakeholders should also
have knowledge of the hydrologic response of storage facilities as the stakeholders play an
important role in water management decisions such as resource allocation (Shah et al., 2001). It
is when all these stakeholders are equipped with relevant knowledge that they will be able to
make correct resource management decisions. Lack of such knowledge resulted in inappropriate
water management decisions being made and resource scarcity exacerbated.
(b) Resources
Resources are the assets available to water service organisations and include human, finance,
technology and information (Nadler and Tushman, 1980; Gill, 2000; Wyman, 2003). Availability
of human and financial resources differs across the water service organisations and will be
discussed separately for each organisation under section 9.4.2(b). The situation regarding
technology, information and public perceptions on water service organisations in the study area
is described as follows:
(i) Technology
Major technologies necessary for the water sector to function properly include that for
measurement of climatic factors, geo-hydrological monitoring, mechanization and equipment for
infrastructure development and maintenance as well as information technology. Important
climatic factors to be measured would include temperature and rainfall which determine the
amount of runoff and hence water availability. Proper geohydrological monitoring provides
182
information on ground water fluctuation and in this way shows the status of ground water
availability. Mechanization and equipment for development and maintenance of water
infrastructure are important for the water supply system to be there in operational condition.
Measurement of all these aspects of water management requires availability of relevant
technologies. Computation and analysis of the collected data requires information technology.
Although the technologies are available on the South African market, their supply in the study
area is limited and this constrains the performance of water service organisations.
The weather stations are sparsely distributed across Limpopo Province and certain agro-climatic
zones in the study area do not have a representative weather station. Climate information such as
rainfall and temperature must therefore be estimated. Limited supplies of facilities for geo-
hydrological monitoring in some areas make knowledge of the underground water resources very
limited. Scarce supply of mechanization and equipment coupled with lack of expertise limit the
capacity of water service organisations to develop new water infrastructure and to maintain the
existing ones. Scarcity of required information technology on the other hand makes collection of
information such as weather data expensive as a person often has to go to a manual weather
station to record the measurements. The dearth of a wide range of technology supplies therefore
constrains the performance of water service organisations in the Limpopo Province.
(ii) Information
Information is critical for all stakeholders to make correct decisions on water issues. The
information may be of the water resource itself or of its uses. According to Schreiner and van
Koppen (2000), the water stakeholders should be informed about poor people's water needs for
multiple uses in order to make appropriate decisions for meaningful management of the resource.
The essence of information about the water needs of all resource users was affirmed by Lord and
Israel (1996) who mentioned that influential stakeholders should make decisions that take into
account the needs and desires of all the different water users and role players. Without the
183
information about the resource needs of the different water users and role players, the
stakeholders are likely to take decisions that do not address the needs of these groups.
Although communities represented by non-governmental stakeholders have high levels of
interest for participating in decision making for water projects (Kgomotso and Swatuk, 2006),
they were often excluded from water meetings and were not informed about the challenges and
other issues faced by the sector (section 7.3.3.(a), Chapter 7). Sound management of water
requires stakeholders to be representative (UNDP, 1995; Chancellor, 1996; Carney, 1998; and
Van Koppen, 1990) and well informed about the challenges facing the sector.
The community based water stakeholders in the study area were uninformed about the issues
facing the sector and had less influence on water issues discussed (section 7.3.3.(c)). As a result,
the stakeholders could not be representative of the communities and subsequently water
decisions did not address the needs of the communities. It could be a result of this lack of
informed influential representation that communities often embarked on protests to demand
water supplies. Also, the communities were often not effectively informed when dam levels were
very low and hence they continued to expect regular supplies of the resource.
(iii) Public perceptions of service organisations
Public perceptions of water service organisations were generally negative. Up to 84.2% of
households were not satisfied with the water services in the area under study. Also, the exclusion
of rural communities from water sector decision making, (section 7.3.3.(a)) could have
exacerbated the situation. The poor public perceptions of water service organisations therefore
constituted an unfavourable input for the operation of these organisations. The situation could
have been different if the water service organisations had outreach or public education
programmes.
184
(c) History
The water sector in South Africa is greatly influenced by historical events and key strategic
decisions (Nadler and Tushman, 1980; Gill, 2000). The history that influenced the water sector
includes the change of political order and therefore legislation over time. Having had changes of
water legislation over time, it was necessary to analyse the impact of past and current laws on the
sector (Table 9.2).
As revealed in Table 9.2, the Water Act of 1956 provided for water to be managed as a
fragmented resource with some recognised as private and the balance public with no provision
for environmental nor for international obligations. Water was prioritised for irrigation,
commerce and mining due to highly centralised decisions with no system for disseminating
information on those decisions (RSA, 1956).
Table 9.2 The impact of the Water Act of 1956 and of the National Water Act of 1998 on water
sector performance (RSA, 1956; RSA, 1998a; de Coning, 2006; Woodhouse, 2008)
Water Act of1956 National Water Act of 1998 Expected impact of reform
Provides for both public and Declares all water a national asset, Equitable access independent of
private water linked to land abolishes riparian rights and private land ownership
ownership ownership
No priority for water for Water prioritised and reserved for Resource sustainability and
environmental and international environmental and international harmony with neighbouring states
obligations obligations;
Legislate for only public water on Legislates for all water as indivisible Holistic quality management of
effluent handling-Return to public national asset-All polluters pays water resources
stream
Minister may establish and operate Minister may establish and operate Environmental and social
government water works. government water works after EIA and sustainability
public involvement.
Decisions mostly centralised to Decisions de-centralised to CMAs, Stakeholder involvement results
President and Minister WUAs and public, Minister overall in social stability
responsible
No provision for national Provides for national information Public information results in
information system systems social stabili!Y_
Prioritises water for irrigation, Water prioritised and reserved for basic Improved rural supply allows for
commerce and mining human needs socio-economic development
185
The National Water Act of 1998 provided for reversal of the negative stipulations of the Water
Act of 1956. The Act described water as an indivisible national asset with some reserved for
environment to provide for sustainable supplies and for international obligation to promote
regional stability. Decisions were decentralised to CMAs and WUAs. Provision was made for
national information systems and water was prioritised and reserved for basic human needs.
9.4.2 Major challenges faced by the water sector
In accordance with the negative influences brought by the different components of input to the
water sector, various challenges were identified which require major attention. The challenges
were presented as real life problems and informed the development of research objectives
(Section 1.4, Table 1.3) were mentioned as environmental factors (Section 9.4.1(a)) in this
chapter.
These water challenges are:
(a) Scarce water resource availability and inadequate storage
A study on runoff and storage capacity revealed the study area to be water scarce (Chapter 4) and
yet the storage capacity was not adequately developed, especially in the Limpopo WMA. As a
result, the supply of the resource is insufficient for meeting the demands for social and economic
activities in the province.
(b) Some darn never filled up
Some dam never filled up except during floods and this confused water managers who could not
reliably predict the supply and as a result could not make appropriate resource management
decisions. The darn of concern in this regard is the Middle Letaba Dam in the Luvuvhu-Letaba
WMA (Chapter 5). Inappropriate water management decisions were made and these did not
improve the effectiveness of the water sector.
186
(c) Poor resource knowledge of water managers
Water managers lacked knowledge of the water resources in their areas (Chapter 6). They did not
know all the major rivers and dams from which water is supplied in their areas. Instead of
understanding the entire value chain of the water resource, the managers only had a fair
understanding of the consumption of the resource and would therefore not make comprehensive
decisions on management of the resource.
(d) Lack of stakeholder participation
In a survey of the perceptions of rural municipal water managers on stakeholder participation on
water issues in the area under study, it was shown that the involvement of stakeholders in
decision making for water issues is very poor. Government based stakeholders were more
influential in water issues than their counterparts from communities (Chapter 7).
(e) Poor resource allocations to rural communities
A study of water supplies and uses by rural households in the province revealed that the supplies
were very low. As found in Chapter 7, more households in the study area reserved water for only
basic activities of drinking by people (95.9% of households), preparing food (95.4%), bathing
(92.8%) and laundry (90.8%) compared to those who used the resource for productive activities
of washing car (6.6%), irrigating crops (5.7%) and livestock drinking (3.5%) due to scarcity of
supply. Water supply to urban centres is generally higher. Inequitable allocations were also
recorded across different use sectors.
9.4.3 Organisational strategies and their congruence with water sector challenges
Strategy entails the whole set of decisions that are made about how a water service organisation
will configure its resources taking into consideration the demands, constraints, and opportunities
of the environment within the context of its history. The strategy refers to the issue of matching
the service organisation's resources to sector inputs, or making a fundamental decision of the
business the organisation is in (Nadler and Tushman, 1980) and should address the needs of the
clients.
187
The DWA and the three WSAs of MDM, VDM and PLM presented the strategies in their
planning documents that sought to address the needs of the water sector through responding to
the major challenges presented by the stakeholders. The extent to which the strategies were
relevant to solving the sector challenges is illustrated by the analysis of congruence between
these two factors (Table 9.3).
There was a high degree of congruence (rating=J) between the challenge of water resource
scarcity and inadequate storage and the responsive strategies of each of the water service
organisations. The DWA and MDM reported in their strategies the need for resource
conservation, the VDM mentioned resource protection while PLM identified the use of rainwater
harvesting to reduce resource scarcity. The DWA reported the establishment of an infrastructure
agency to manage infrastructure development and this includes storage infrastructure. Although
MDM and PLM reported the building of dams, this is the mandate ofDWA (DWAF, 2004a) and
the WSAs' involvement is mainly in community mobilization. The infrastructure construction by
VDM included community participation in development of storage facilities.
The MDM and VDM are largely located in the Luvuvhu-Letaba WMA where available storage
capacity constitutes 64.2% of mean annual runoff (Section 4.3.l(b)). The decision to develop
additional storage in this area should consider the availability of water for further impoundment
without contravening international agreements with neighbouring Mozambique located
downstream of the rivers flowing through this WMA. As revealed in Section 4.3.l(b), the
available storage capacity of the Limpopo WMA where the PLM is located is only 33% of mean
annual runoff which suggests a higher potential for development of additional storage capacity.
As for the challenge of dams not filling up, the strategies of DWA, MDM and PLM were to
conduct research and to properly manage information and were highly congruent (3) with the
challenge. The strategy of VDM was 'proper planning' and was rather broad and was not
specific to the challenge and hence the congruence was low (1), resulting in a mean congruence
rating for this challenge to be between moderate and high (2.5).
188
Table 9.3 Congruence rating between water sector challenges and responsive organisational
strategies of Limpopo Regional Office ofDWA and the WSAs of MDM, VDM and PLM
Challenge Strategy and congruence rating Mean
DWA Rate MDM Rate VDM Rate PLM Rate
Water Conserve 3 Conserve 3 Protect 3 Promote 3 3.00
resource water water resource; use of
scarcity & resources; resources; Build rainwater
inadequate Establish Build dams infrastruct harvesting;
storage infrastruct and raise ure Build
ure agency dam walls reservoirs
Some Research 3 Research 3 Proper 1 Undertake 3 2.50
dams do by WRC; & planning; research &
not fill up Water developme developme
and water resource nt; nt
supply plan & informatio Implement
remains informatio n e-
low n manageme goverrune-
manageme nt nt strategy
nt
Poor Establish 3 Capacity 2 Work 2 Ensure 2 2.25
resource academy building place skills municipal it
knowledge for water and planning y has
of water sector training and capable
managers skills reporting; managers
developme
nt
Lack of Involve 3 Involve 3 Involve 3 Municipali 3 3.00
stakeholde stakeholde stakeholde stakeholde ty to have
r rs rs In IDP rs in IDP functional
participati throughout and and community
on implement implement participatio
ation ation n
Poor Promote 3 Water 3 Water 3 Provision 3 3.00
resource access to provision provision of water to
supply to basic water made top made top those with
rural supply by priority priority no access
household all
s
Mean 3.00 2.80 2.40 2.80 2.75
Congruence Rating: 0 =None; 1= Low; 2 =Moderate; 3 =High
For the challenge of poor resource knowledge of water managers, the strategy of DWA of
establishing an institution for skills development for water engineering and science was highly
congruent (3) with the challenge. Although the strategies recorded by the three WSAs (MDM,
189
VDM, PLM) were about human resource development, they were not specific on water resource
issues and hence moderate congruence (2) occurred between each strategy and the challenge
resulting in a moderate mean congruence (2.25). The strategies of the four water service
organisations were highly congruent (3) with the challenge of lack of stakeholder participation
and with that of poor resource supply to rural households.
With DWA being the custodian of water resources (DWAF, 2004a), it would be expected that
the department should have a full understanding of the challenges faced by the water sector. It
was therefore not surprising that all the strategies of DWA were highly congruent (3) with the
corresponding challenges faced by the water sector. This resulted in a high mean congruence (3)
for the department, suggesting that it had highly relevant strategies for addressing the water
challenges. Although smaller than that of DWA, the mean ratings of strategies of MDM and
PLM were each also highly congruent (2.8) with the challenges faced by the water sector while
the mean rating of congruence of VDM strategies was moderate (2.4). With the exception of the
VDM whose strategies were moderately relevant, the water service organisations had highly
relevant strategies to address the challenges of the water sector.
9.4.4 Transformation components and their congruence with strategies
The transformation process in water service organisations entails the use of inputs to produce a
set of outputs. Some components influence transformation within water service organisations,
and those include: (1) tasks, (2) human and (3) financial resources (Nadler and Tushman, 1980;
Gill, 2000; Wyman, 1998; Wyman, 2003). According to Nadier and Tushman (1980), the
formulation of strategies should take into account the sector challenges which are in turn
informed by the other inputs of environment, resources and history. Analysis of the congruence
of transformation components with organisational strategies therefore indirectly addresses the
sector challenges.
The importance of congruence between a person as a unit under the transformation component
and environment as a unit under input on the effectiveness of a water service organisation cannot
190
be over-emphasized (section 9.2.1). Water service organisations will be more effective when the
attributes of a person and those of environment and subsequently the broad components of input
and transformation are highly congruent (Ostroff, 1993). The environment and strategy are both
units of input in the Congruence Model. A high degree of fit between the strategy and a unit
under transformation will promote congruence between the components of input and
transformation and hence the effectiveness of water service organisations.
(a) Congruence between strategies and tasks
Although the water service organisations used different statements to reflect their strategies to
address the challenges faced by the water sector, the strategies generally captured similar
messages. The strategies of the water service organisations may be summarized as: (1) conserve
water and develop storage capacity, (2) research and manage information on dam hydrology (3)
build managers' knowledge of water resources, (4) promote stakeholder participation, and (5)
improve water supply to rural households.
In addition to development of strategies to address water sector challenges, the service
organisations also identified specific tasks to be performed to implement the strategies. The
success of implementation of the tasks will depend on the degree to which the tasks are aligned
to the strategies. The alignment of the tasks with strategies is determined through analysis of
congruence between the two components, i.e. tasks and strategies (Table 9.4).
As shown in Table 9.4, the DWA and of PLM recorded tasks of promoting efficient water use to
provide for resource conservation while also including tasks of storage development and were
highly congruent (rating=3) with the strategy of conserving water and developing storage
capacity. The tasks of MDM and VDM only focused on promotion of efficient resource use with
no provision for development of storage capacity and were moderately congruent (2) with the
strategy.
191
Table 9.4 Analysis of congruence between strategies and tasks of water service organisations of
Limpopo Regional Office of DWA, MDM, VDM and PLM
Strategy Task and con ruenee rating Mean
DWA Rate MDM Rate VDM Rate PLM Rate
Conserve Promote 3 Prioritise 2 Adopt user 2 Educate on 3 2.50
water and efficient use; domestic use pay principle efficient
develop Increase for non- use; proper
storage storage indigents pricing;
capacity
Research and Research on 3 Manage 2 Develop 2 Identify 3 2.50
manage water; information credible & research
information on Manage effectively; reliable areas; Use
dam knowledge Manage data geographic informatio
hydrology on water & keep information n
records technology
Build Skilling In 3 Ensure 1 Develop 3 Introduce 2 2.25
managers' water skilled & officials' planning &
knowledge of engineering capacitated competence; technical
water & science; workforce water and developme
resources Graduate sewerage nt program
training skilling
Promote Form CMAs 3 Form IDP 1 Form IDP 1 Communit 3 2.00
stakeholder and WUAs forums and forums and youtreach;
participation facilitate facilitate Participati
imbizos imbizos on in water
issues
Improve water Provide 3 Expand 3 Improve 3 Upgrade 3 3.00
supply to rural support to reticulation supply of reticulation
households districts and and improve free basic & improve
municipalitie access water, access to
s increase use all; Free
of tankers. basic water
Mean 3.00 1.80 2.20 2.80 2.45
Congruence Rating: 0 = None; 1 = Low; 2 = Moderate; 3 = High
The omission of development of storage capacity by these WSAs was possibly due to the fact
that they are located in the Luvuvhu-Letaba WMA· with highly developed water resources
(Chapter 4). The subsequent mean congruence rating for the tasks planned by the water service
organisations and this strategy was moderate to high (2.5).
The tasks of DWA and PLM were highly congruent (3) with the strategy of investigating and
managing information on dam hydrology. The tasks of the MDM and VDM only focused on
192
issues of information management with no provision for research and were therefore rated
moderately congruent (2) with the strategy. The mean congruence rating for the tasks planned by
the water service organisations and this strategy was also moderate to high (2.5).
As for the strategy of building managers' knowledge of water resources, it was the DWA and the
VDM that stated specifically issues of water resources in their human resource development
interventions and hence their tasks were rated highly congruent (3) with the strategy. The tasks
of the PLM highlighted the essence of technical development and were rated moderately
congruent (2) with the strategy as they will possibly include water resources. The task pledged
by the MDM was too broad with no sense of focus on water resources and was therefore rated
lowly congruent (1) with the strategy. The mean congruence rating for the tasks recorded by the
water service organisations and the strategy of building managers' knowledge of water resources
was therefore moderate (2.25).
The task of DWA of forming CMAs and WUAs and those of PLM of reaching out to
communities and promoting active participation in water issues were highly congruent (3) with
the strategy of promoting stakeholder participation. The MDM and VDM pledged to form IDP
forums and facilitate politically driven community gatherings and these are often too broad to
give the water sector fair attention. The tasks of these WSAs were general and not focused on
water and so were given low congruence (1) with the strategy. A moderate mean congruence (2)
rating was recorded for the tasks planned by the service organisations and this strategy. The tasks
of the four water service organisations were highly congruent (3) with the strategy of improving
water supply to rural households. Although the tasks were different, they complemented each
other.
The mean rating of congruence between the tasks recorded by water service organisations and
I the strategies for addressing water sector challenges was high for DWA (3.00) and for PLM
(2.80). The mean rating was moderate for MDM (1.80) and VDM (2.20). The high congruence
rating for DWA could be due to the fact that the department has water resource management as
193
its only mandate while the high rating for PLM could have resulted from the WSA being
relatively more urbanized and with financially sound basis. In addition to water services, the
MDM and VDM have a lot of other functions to take care of and are relatively more rural with
limited financial and personnel resources. The role of DWA of supporting the municipalities is
therefore critical for these WSAs to successfully.manage the challenges faced by the water sector
in the Limpopo Province.
9.4.5 Congruence between allocated and utilized organisational resources
According to Nadier and Tushman (1980), human and financial resources are very important for
water service organisations to implement their strategies. The allocation and utilisation of these
resources according to the five water service strategies was only available for DWA and not for
the three WSAs. The WSAs neither included resource allocation nor used information according
to water service strategies in their integrated development plans for the period under
investigation (2010).
With regards to hu.man resources, the allocations and utilisation for the three WSAs was done
according to departments such as (1) Corporate Services, (2) Financial Management, (3)
Development Planning, (4) Technical Services and (5) Community Services without revealing
the resources specifically for water services. With financial resources, however, the WSAs
reported allocations and utilisations for water services separately, but without apportioning the
resource to the five strategies addressing the water sector challenges.
As shown in Table 9.5, the analysis of the allocation and utilisation of human resources by DWA
revealed a low degree of congruence (1). Only 64.9% of the 37 posts allocated were filled
(2009), suggesting a probability that the water service organisation would under-perform as a
result of 35.1% of the posts being vacant. The analysis of the allocation and utilisation of
financial resources revealed that the department over-spent its R143 million budget for water
issues by 39.9% and this resulted in a negative and low degree of congruence (-1) between the
allocation and the expenditure.
194
Table 9.5 Analysis of congruence between allocation and utilisation of human (posts) and
financial (budget) resources of water service organisations of Limpopo DWA, MDM, VDM and
PLM (DWAF, undated; MDM, 2009; VDM, 2009 and PLM, 2009)
Water Human resource Financial resource
service
organisati
on Allocation Use % Use Rate Allocation Use % Use Rate
DWA 37 24 64.90 I 142963037 200012993 139.90 -I
MDM 283 133 47.00 I 323470851 323470851 100.00 3
VDM 314 263 83.80 2 270750271 213892714 79.00 2
PLM I 796 1463 81.50 2 116276917 163593034 140.70 -I
Total 2430 1883 77.49 1.50 853461076 900969592 105.57 -1.75
Congruence Rating: 0 = None, ~ 67% gap from 100%; 1= Low, 66 - 33% gap from 100%
2 = Moderate, 33 -10% gap from 100%; 3 = High, < 10% gap from 100%
+ = Allocation ~ utilisation; - = Allocation < utilisation
With some posts not filled, the department still exceeded the planned financial spending for
water services, suggesting that the available personnel had a high spending capacity in order to
surpass the budgeted financial resources. The high capacity to spend with only 65% of the posts
filled could be a result of some functions being outsourced. It would therefore be advised that the
department fills the vacant posts, especially if there are functions that they are not doing
themselves due to under-staffing. With the plan of decentralising some functions (DWAF,
2004a), it may be necessary to conducts an organisational restructuring to review the number and
levels of posts linked to the water services function.
As for the MDM, the human resource allocation was 283 posts of which only 133 (47%) were
filled and hence the degree of congruence between the allocation and the use was low (1). With
this low (47%) post filling rate, the WSA spent all (100%) of its allocated water budget ofR323
million revealing the degree of congruence between the budget allocation and its spending to be
high (3). As was the case with DWA, the congruence analysis for MDM suggests that the WSA
195
could be outsourcing some of its functions for them to spend the entire budget with only 47% of
the posts filled.
The VDM had a human resource allocation of 314 posts of which 263 (83.8%) were filled,
suggesting a moderate degree of congruence (2) between the allocation and the filling of the
posts. With more posts filled and lower budget allocated compared to the MDM, the VDM only
spent 79% of its budget allocation of R270 million, resulting in a moderate congruence (2)
between the budget allocation and its spending. The result of the congruence analysis of the
VDM reveals that non-filling of some posts leads to poor spending and subsequently poor
performance. The VDM probably relied on their staff for job performance and did not outsource,
hence the underperformance when some posts are vacant.
The human resource allocation of 1 796 posts for PLM far exceeds those of the other WSAs of
MDM and VDM. This large number of posts for PLM includes those allocated for non- and
semi-skilled jobs such as gardening and cleaning while those of the other WSAs are only for
high skills jobs. Of the allocated posts in the PLM, 81.5% are filled and this translates to a
moderate level of congruence (2) between the allocation and the filling. The WSA over-spent its
water services budget of RI16 million by 40.7% and this resulted in a negative low degree of
congruence (-1). With this very large staff complement, the over-spending of the budget is not
surprising as part of it could have been consumed by personnel related activities. With the
allocation seeming too large, it would be advised that this WSA undergoes an organisational
restructuring to review the number and level of posts necessary for the municipality to operate
smoothly.
As shown in Table 9.5, a total of 2430 posts were allocated among the four water service
organisations and 77.49% of them were filled. The mean congruence rating was low to moderate
for human resource allocation and use (1.50) and moderate for financial resource allocation and
use (-1.75) and therefore the non-filling of posts (human resource) was the most significant
constraint to organisational effectiveness.
196
9.4.6 Congruence flow analysis
The purpose of congruence flow analysis was to assess the variation in levels of congruence
along the input and transformation components. High levels of congruence along the input and
transformation components of a service organisation imply better capacity for the organisation to
successfully execute strategies to address water challenges. Various levels of congruence were
noted between input and transformation components of the service organisations (Table 9.6).
Table 9.6 Congruence flow analysis of input and transformation components of four water
service organisations: DWA, MDM, VDM and PLM
Component of capacity Water service organisations and congruence ratings of Component
components mean
DWA MDM VDM PLM
Strategy 3.0 2.8 2.4 2.8 2.75
Task 3.0 1.8 2.2 2.8 2.45
Human resource 1.0 1.0 2.0 2.0 1.50
Financial resource -1.0 3.0 2.0 -1.0 -1.75
WSA mean 2.0 2.15 2.15 2.15
Congruence Rating: 0 = None; 1 = Low; 2 = Moderate; 3 = High
The congruence for DWA was high for strategy (3) and for tasks (3) and was low for both human
(1) and financial (-1) resources (Table 9.6) and hence the last two components were the most
significant constraints to successful implementation of water programmes by DWA. For MDM,
the congruence was high (2.8) for strategy and financial resource management (3), moderate
(1.8) for task and low (1) for human resources, implying that the human resource provision was
the largest constraint to successful implementation of water programs. Similarly, the largest
constraints to successful implementation of water programmes were human and financial
resources for VDM and were financial resource for PLM.
With DWA being the custodian of water resources (RSA, 1998a; DWAF, 2004a), it would be
expected for the Department to have appropriate allocation and utilisation of the human and
financial resources and subsequently a high degree of fit between the supply and use of these
resources. The resources in the department are units within the transformation component of the
197
Congruence Model and the lack of congruence between their provision and use reduces the
effectiveness of the Department in rendering its functions (Wyman, 1998; Bezboruah, 2008).
Similarly, the components with low congruence in the WSAs need attention; else they render
these service organisations less effective.
Considering the different components defining the capacity of service organisations, congruence
was high (2.75) for strategy, moderate for task (2.45) and financial resources (-1.75) and low
(1.50) for human resources. According to these results, the human resources were the most
significant constraint to successful implementation of water programmes. Moderate congruence
was recorded for all the four water service organisations ofDWA (2), MDM (2.15), VDM (2.15)
and PLM (2.15). With DWA being the custodian of water resources in South Africa, it would be
expected for the department to have shown a higher degree of congruence to indicate higher
capacity for addressing water sector challenges.
As revealed in Table 9.6, the congruence rating for all the water service organisations
investigated was only moderate, suggesting that the organisations have moderate capacity to
address water sector challenges. The study area is water scarce (DWAF, 2003; DWAF, 2004b)
and subsequently community access to water is limited (Stats SA, 2009; Manase et aI, 2009).
The water economy in South Africa is characterized by high demand for the resource due to
intensive competition among users (Randall, 1981; Backeberg and Groenewald, 1991) which
exacerbate the scarcity of the water resource. It is important that the capacity of the service
organisations be improved for these organisations to adequately address sector challenges. The
strategies for improving the capacity of the water service organisations constitute a proposal of a
water management decision model for the study area.
9.4.7 Proposal of a water management decision model
In accordance with the results of congruence analysis, an appropriate water management
decision model for Limpopo Province should address the following issues:
198
(a) Strategy
Although there was an overall high degree of congruence (2.75) between strategies and
challenges, some issues require attention, e.g. (i) VDM should develop focused strategies
involving research and information management to address the challenge of dams not filling up;
(ii) MDM, VDM and PLM should have in place human resource development strategies that are
specific to water resources.
(b) Tasks
There was overall a moderate degree of congruence (2.45) between tasks and strategies and: (i)
MDM and VDM should develop specific tasks on research aspects of dam hydrology (in addition
to information management) and promote stakeholder participation on water issues; (ii) As was
the case with strategies, MDM and PLM should implement human resource development tasks
that are specifically focussed on water resources.
(c) Human resources
There was overall a low degree of congruence (1.50) between human resource (post) allocation
and their utilisation (filling), and: (i) All the water service organisations had vacant posts which
should be filled. The DWA should review its post allocation as part of its restructuring where
some functions will be decentralised while the PLM should do the same check if the large
number of posts is indeed needed. (ii) In addition to allocation according to departments within
WSAs, human resources should also be allocated according to types of services to be executed
such as water and electricity and according to major strategies within each type of service.
(d) Financial resources
The degree of congruence between the allocation and spending of financial resources was poor (-
1.75) in overall. The service organisations except MDM should allocate financial resources
according to needs and informed by the capacity to spend, more so for DWA and PLM. In
addition to service areas such as water and electricity, the three WSAs should also reveal the
allocation of funds according to strategies (activities) within a service.
199
In accordance with the above proposals based on the congruence analysis, a water management
decision model as shown in Figure 9.3 is proposed for Limpopo Province.
200
II,nput II II Transformation D II Output II
--- ----
Situational analysis r Strategy 1 '" Desired results
Political: Water Scarce water reso- 1---" " Conserve water Water scarcity1 3.00 }
allocations & access urce & inadequate reduced;1- - _,1 & develop
storage II storage capacity < ~ storage
increased
Research & ma-
Environmental: Rain- Complex dam 1---"1 2.50 " } nage information Research
fall & temperatures; hydrology 1- - _,1 on dam information
II ~
hydrology < well managed
Poor resource & 1---" " , Build managers KnowledgeablSocial: Stakeholder use knowledge of 1 2.25 I knowledge of < e water1participation - - _ ..Iwater managers II water resources ~ managers
lack of stakeholder 1---" " Promote Active
participation 1 3.00 }1- __ ~I stakeholder
Technological: < ~ stake holderII participationWater research & participation
I,
information Poor supply to rural 1---" Improve water
1 3.00 }
management households supply to rural < Improved1- - _ .. III households supply to rural~
'- households,
(Strategy 2] -_ ~1-----------------------------------------I- - - - - - -- Fee-d--b-ac-k------------- 1
Figure 9.3 Capacity assessment of water service organisations of Limpopo Province using the adjusted Congruence Model
201
(e) Model discussion
The degree of congruence was mostly high between challenges and strategies, moderate to
high between strategies and tasks (which are important part of transformation) and low to
moderate between transformation and output (Figure 9.3). Results for challenge-strategy
assessment show a high degree of congruence (rating=3) between the challenge of scarce
water resource and the strategies presented by service organisations to address the challenge.
This suggests that accurate situational analysis was conducted and correct information
obtained about the problem, hence an appropriate strategy.
The degree of congruence between the strategy and the tasks (transformation) was moderate
to high (2.50), indicating a reduced congruence compared to that between the strategy and the
water challenge. The appropriate strategic plan was therefore not translated to fully relevant
tasks and hence the reduction in congruence. The cause of the strategic plan not being highly
congruent with the implementation tasks could be planners not adequately informing
implementers about the plan. Without adequate understanding, the implementers could have
misinterpreted portions of the strategy and therefore developed some irrelevant tasks.
Strategic planning is often done by managers of water service organisations while
implementation is done by field staff.
As revealed under transformation, the implementation of tasks was influenced by their
interaction with human resources, financial resources and organisational systems. A low to
moderate congruence (1.50) was noted between allocation and use of human resources due to
some allocated posts remaining unfilled. A moderate congruence (-1.75) was registered
between the allocation and use of financial resources and this mostly resulted from
overspending (Section 9.4.2(b), Table 9.5).
The existence of vacant posts suggests that the human resource was limiting to the
implementation of the tasks while the overspending suggests that the allocation of financial
resources was also limiting. As revealed by the congruence ratings, the human resource was
the most significant constraint to the implementation of tasks and was therefore adopted as
the congruence rating between transformation and output.
202
The organisational system influences the implementation of tasks by defining organisational
values which control the work environment of a water service organisation. Organisations are
more effective in implementing tasks where a high level of congruence occurs between
preferences of human resources and organisational values (Boxx ef al., 1991; Chatman, 1989,
1991; Judge and Bretz, 1992; O'Reilly ef al., 1991). As stated by Balkin and Schjoedt (2012),
organisational values include such aspects as culture which informs people about the
appropriate way things are done in the organisation. Some organisational cultures are rigid
and do not provide for employees to make independent decisions while others are flexible
and allows the employees to make decisions.
As shown in Figure 9.3, moderate to high degree of congruence (2.50) occurred between the
challenge of dams not filling up and strategy and between the strategy and tasks. The
situational analysis by water service organisations was probably not fully accurate in defining
the challenge and hence the congruence between the challenge and the strategy could not be
high. With the congruence between challenge and strategy being only moderate to high, the
congruence between strategy and tasks was also only moderate to high.
The interactions among human resource, financial resource and organisational systems and
the subsequent influence on task implementation were similar to those for the challenge of
scarce water resource and inadequate storage. A similar degree of congruence was therefore
recorded between the transformation and output for the challenge of dams not filling up.
Related results were obtained for the challenge of poor resource and use knowledge where
the congruence rating between the challenge and strategy and between the strategy and tasks
was 2.25.
Related to the situation with the challenge of scarce water resource and inadequate storage,
the degree of congruence between the challenge of lack of stakeholder participation and
strategy was high (3.00) while that between strategy and tasks was moderate (2.00). As for
the challenge of poor supply to rural households, the degree of congruence was high (3.00)
between the challenge and the strategy and between the strategy and the tasks. The
congruence between transformation and output was low to moderate (1.50) for all the
challenges. The output generates a feedback which is used by planners to formulate revised
strategies (Strategy 2) and these are implemented through the next cycle of transformation.
203
While finance is often cited as the most limiting factor for water service delivery, the results
revealed that the human resource is in fact the most limiting factor. The posts that are vacant
are likely those requiring people with scarce skills such as engineering and hydrology. With
the scarce supply of such skills, it would be necessary for relevant learning institutions to be
supported to train in those skills areas. Without such interventions, the water service
organisations will continue to affirm that they have service delivery plans while the public
will remain impatiently waiting for such services.
9.5 Summary and conclusion
The results of the congruence analysis revealed the service organisations to have achieved
overall ratings of 2.00 for DWA, 2.15 for MDM, 2.15 for VDM and 2.15 for PLM, implying
a moderate ability of all organisations to address the water sector challenges. The overall
degree of congruence was high (2.75) between strategies and challenges, moderate between
tasks and strategies (2.45) and between allocation and use of financial resources (-1.75) and
low between allocation and use of human resources (1.50).
Although the service organisations mentioned the challenges faced by the water sector and
presented strategies and tasks to address them, it was noted that some strategies and tasks
were either not focused or did not address the challenge in its entirety. The service
organisations seemed to experience major challenges with resource allocations and their
subsequent utilisations. Although posts were created by the water service organisations, they
were mostly not all filled and that resulted in the low level of congruence (1.50) between the
allocation and the use of the posts. The under-filling of posts was the most significant
constraint to the performance of water service organisations. The proposed water
management decision model takes into account the major challenges experienced by the
sector, the relevant strategies and tasks to address them as well as the proper allocation and
use of resources to execute the strategies and tasks.
204
CHAPTERlO
10 POLICY RECOMMENDATIONS
10.1 Focus of the study
The investigation was on the water situation of the Limpopo Province with a focus on:
(a) Water resources, mainly runoff and storage capacity of the target Water Management
Areas and municipalities, and the water gain and loss factors of the Middle Letaba
Dam;
(b) Water management, mainly perceptions of municipal water managers on the water
resource and its uses, and their perceptions on stakeholder participation; and
(c) Household water supply and requirement.
10.2 Main findings
10.2.1 Water resources
The Limpopo WMA has a MAR of 611.4 million m3 for possible development of new dams
compared to only 365.2 million m3 for the Luvuvhu-Letaba WMA with similar results for
municipal implementation of strategic water related projects.
Storage volume for the Middle Letaba Dam increased with rainfall with a time lag of two
months from peak rainfall to maximum storage volume. The dam storage volumes were very
small compared to design capacity, affirming that the dam could not be filled from only
rainfall, but will need to be filled through transfers from other catchments.
10.2.2 Water management
The municipal water managers lacked knowledge on water resources and were relatively
more knowledgeable on water use. In order to make appropriate water management
decisions, the water managers should be equipped with required knowledge.
Water management decisions were made by government based stakeholders, mainly of
Department of Water Affairs, Limpopo Department of Agriculture, District Municipalities
205
and Local Municipalities. Community based stakeholders such as Water Users Associations
and Community Based organisations did not influence water management decisions.
10.2.3 Household water supply and requirement
There was a lack of access to safe water sources with only half (50.1%) of households
obtaining water from street taps. The quantity of water fetched ranged from approximately 25
to more than 200 litres per household per day, and the amount fetched increased with a
decrease of distance of the water source from the residential site. As a result of scarcity, water
was mostly used for basic activities such as drinking, preparing food and bathing. Half
(51.7%) of the households fetched less water than the 25 litres per capita per day supply
standard. The 25 litres per capita per day did not meet the average requirement of 37.5 litres
per capita per day.
10.3 Policy recommendations
10.3.1 Water resources
(a) Catchment runoff and storage capacity
Catchment runoff and available dam storage capacity are important indicators for decision
making on whether additional storage should be built or not. The occurrence of runoff in
excess of the available dam storage suggests availability of additional water for development
of more storage capacity. The occurrence of runoff in excess of the available dam storage
also presents an opportunity for community based projects to be initiated at a municipal level,
and these include rainwater harvesting for households, agriculture and for industrial uses of
water.
Based on the results of the analysis of runoff and storage capacity, it is recommended that the
Limpopo WMA be the focus for possible construction of new dams. The Mogalakwena,
Lephalale and Mokoio catchments were shown to have more available mean annual runoff
for possible development of new dams. Although the Luvuvhu-Letaba WMA was shown to
be well developed in terms of storage dams, the Mutale Catchment had more available mean
annual runoff for possible development of new dams.
206
It is also recommended that regular investigations be conducted of runoff and available dam
storage capacity. Such investigations are necessary as the phenomenon of climate change is
negatively influencing the rainfall and temperature regimes such that the results of previous
audits may not always be relevant. The occurrence of dam silting reduces the storage capacity
of existing dams, making it indeed necessary for regular audits to be conducted. Decisions to
build new dams or to initiate new water related projects should be based on credible results of
new runoff and dam storage capacity audits.
(b) Dam not filling up except during floods
Time lags were recorded from the occurrence of rainfall on the Middle Letaba Dam to the
increase of inflow from the source river (1 month) and the increase of dam storage volume (2
months). The increase of dam storage volume inform the operation rules of the dam and
therefore it is recommended that investigations be conducted on the extent of the time lag in
other reservoirs and the possible causes of such lags.
The dam storage volume of the Middle Letaba Dam was very low compared to the design
capacity. It is therefore recommended that water be transferred to the dam from other'
catchments in order to maintain this dam at a full level and consequently to improve the
supply of the resource to planned areas. Initiatives of transferring water from the Nandoni
Dam in the Luvuvhu Catchment are in order.
10.3.2 Water management
(a) Municipal water managers' knowledge of the resource and its uses
Appropriate water resource planning and use requires that relevant decision makers have
adequate knowledge of the water resource and its current uses. From the results of the study it
was shown that the municipal water managers are important decision makers and had little
knowledge about the water resources and their consumptions.
In order to address the municipal water managers' relative lack of knowledge of water
resources and uses, it is recommended that appropriate training be implemented. The training
should build adequate knowledge capacity of the water managers for them to make correct
decisions on the management and use of the resource.
207
(b) Stakeholder participation in water decision making
Water decision makers should have the participation of all relevant stakeholders in order to
make appropriate water resource management decisions that are acceptable to the broader
community. The study revealed that government based stakeholders were perceived to be
more reliable sources of water information than their community based counterparts of Water
Users Associations and Community Based Organisations. The government based
stakeholders were resultantly more influential in water sector decision making than the
community based stakeholders who had very little if any influence at all.
It is therefore recommended that community based stakeholders be empowered to be reliable
sources of water information for them to subsequently have some influence in the sector
decision making. Empowerment of community based stakeholders could be achieved through
involving them more in meetings where decisions about water resource planning and uses are
made and through improving their access to important information about the sector.
10.3.3 Household water supply and requirement
The amount of water supply has a strong influence on living conditions among rural
households where more supply results in improved living conditions. The rural households in
the study area have scarce supply water. Half of the households actually fetched less than the
25 litres per capita per day supply standard. Analysis of water requirement revealed the
average demand in the study area to be 37.5 litres per capita per day and therefore the
households that fetched less water than the supply standard had much less resource than the
actual demand. The households therefore resorted to mostly using the water for basic
activities of drinking, preparing food and bathing with less resource being used for productive
activities of washing cars and crop watering.
It is therefore recommended that the Department of Water Affairs reconsider the 25 litres per
capita per day as a supply standard as it does not suffice for the average requirement of37.5
litres per capita per day proposed in this study. Also, programmes for increasing the supply of
water to rural households should be strengthened to be more effective.
208
10.3.4 Water management decision model
Implementation of the policy recommendations made in items 10.3.1-10.3.3 require
appropriate actions by relevant water service organisations, namely: Department of Water
Affairs and Water Services Authorities such as Mopani District Municipality, Vhembe
District Municipality and the Polokwane Local Municipality. The appropriate actions by
these water service organisations include understanding the challenges faced by the water
sector and developing relevant strategies and tasks to address them. Development of
appropriate strategies and tasks should be followed by correct allocation and use of resources,
both human and financial resources.
The study revealed that some strategies and tasks developed by the water service
organisations were either not sufficiently focused or did not adequately address the challenge.
Also, the service organisations had shortcomings with the allocation and use of their human
and financial resources. The human resources were not sufficiently provided for as there were
posts that were not filled, hence the allocation (posts) and use (filling) of human resources
recorded the lowest degree of congruence. Human resources and not financial resources were
the most significant constraint to the performance of water service organisations. Improved
performance by the service organisations requires the vacant posts to be filled by adequately
qualified and competent personnel.
The other pairs of components with low congruence ratings should be attended for the water
service organisations to be effective in rendering quality water services. Initiatives for
improving the performance of water service organisations should be guided by the proposed
congruence based model for water management decision making (Figure 9.3) and should be
.aimed at increasing the congruence between (1) Challenges and strategies (Table 9.3); (2)
strategies and tasks (Table 9.4); and (3) allocated and utilised organisational resources (Table
9.5).
209
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