Using seasonal climate outlook to advise on sorghum production in the Central Rift Valley of Ethiopia - Diga, Girma Mamo (University of the Free State, 2005)
Seasonal rainfall is an important source of water for rainfed farming in the semi-arid regions of the world, where rainfall is marginal and variable. However, as rains are unpredictable in terms of onset, amount and distribution, there is a need to understand the variability and other basic rainfall features in order to use the information in agricultural decision making. More specifically, combining the seasonal rainfall prediction with crop water requirement and soil water information is the core component to successful agriculture. The ultimate objective of this study was to characterize and obtain a better understanding of the most important rainfall features that form the basis for classifying the areas into homogenous rainfall zones and then to develop a seasonal rainfall prediction model for the Central Rift Valley (CRV) of Ethiopia. The source data for the analyses was primarily obtained from the National Meteorological Services Agency (NMSA) and partly from Melkassa Agricultural Research Centre (MARC) and the web site of the International Research Institute for Climate and Society (IRI). Rainfall variability and time series analyses were done using INSTAT 2.51 and coded time method, respectively. Rainfall onset and March-April- May (MAM) rainfall totals are the two most variable features both at Miesso and Abomssa. For both stations, rainfall end date displays the least variability. Rainfall onset date at Miesso ranges from the lower quartile (25 percentile) of DOY 61 to the upper quartile (75 percentile) of DOY 179 with a 42% coefficient of variation (cv). At Miesso, the main rainy season terminates during the last days of September (DOY 272 - 274) once in four years and terminates before DOY 293 in three out of four years. At Abomssa, the c.v for the lower quartile (DOY 61) to the upper quartile (DOY 134) was found to be 40.5%. At both locations, planting earlier than 15 March (DOY 75) only proves successful once in every four years. Further, at Miesso this upper quartile statistic can extend up to the DOY 179, whereas at Abomssa planting earlier than 15 April (DOY 134) is possible in three out of four years (75 percentile). At Abomssa, rainfall terminates by DOY 286 and the end of October (DOY 305) for the 25 and 75 percentile points respectively. From the time series analyses, there was no conclusive evidence for the existence of a trend for both Miesso and Abomssa, information which is useful for long-term research and development planning, as well as seasonal rainfall prediction for the study area. The classification study for the spatial rainfall pattern resulted in four homogenous rainfall zones that form distinct development and research units, using the FORTRAN- 90 based NAVORS2 program. The south facing Alem Tena-Langano zone has a better rainfall pattern than drier zones and thus formed zone 1. The southern, southwestern and southeastern area has formed the wet zone (zone 2), the northwestern to northeastern facing part (Debre-Zeit-Nazerth-Dera) that receives a higher rainfall amount than zone 1 has formed zone 3 and finally, the drier northeastern part constituted zone 4. Twenty seven seasonal rainfall prediction models with varied performance skills that can be used for the operational farming were developed for the March-September monthly rainfall using the Climate Predictability Tool (CPT v.4.01) from IRI. It was understood that with increased observing networks and data availability, useful operational climate prediction could be achieved for a smaller spatial unit and with a short lead-time. The tempo-spatial water requirement satisfaction pattern analyses were conducted using AGROMETSHELL v.1.0 of the FAO. Fourteen concurrent sorghum-growing seasons that give a general picture of crop water requirement satisfaction were mapped. The southern, southwestern and southeastern parts (zone 2) of the CRV constitute the most favourable location for growing a range of sorghum maturity groups. The northwestern and central (zone 3) parts constitute the next most suitable zone. The wide northeastern drylands (zone 4) of the study area, except the pocket area of Miesso-Assebot plain, does not warrant economic farming of sorghum under rainfed conditions. From the growth stage-based Water Requirement Satisfaction Index (WRSI) analyses, mid-season / flowering stage of the sorghum cultivars was found to be three times more sensitive to changes in sorghum yields for both cultivars and experimental sites as compared to the WRSI from the rest of growth stages. The results from the water production function analyses (WPF) also indicated the potential of WRSI for prediction of the long-term sorghum yields. The cumulative density function (CDF) and stochastic dominance analyses for the 120-day grain sorghum cultivar grown at Miesso show the June planting to be the most efficient set by first degree stochastic dominance (FSD), while May was found efficient for Melkassa. The CDF for Arsi Negele shows April planting date to be the best set. Therefore, these planting dates are to be preferred by farmers seeking ‘more’ yield at the respective locations, regardless of their attitude towards risk. The sensitivity analyses conducted using different levels of the seasonal rainfall related input variable combinations (sorghum planting date, maturity date, number of rainy days and WRSI) for Miesso, Melkassa and Arsi Negele provide useful information. By keeping input variables other than WRSI at the most preferred level (i.e. early planting date, extended maturity date, and greater number of rainy days) and only changing WRSI from 100% to 75% resulted in a 49.7% yield reduction in case of Miesso, 40.8% in case of Melkassa and 24.3% in case of Arsi Negele. Further, when WRSI was reduced down to 50%, there was a total crop failure in the case of Miesso and Melkassa, while the reduction was 48.6% for the Arsi Negele case. Similar results were found when WRSI was varied across other input level combinations. Visual Basic v.6.0 was used to write the algorithm for the decision support tool (DST) relating sorghum planting dates in CRV, to which the name ABBABOKA 1.0 was given. By using the rainfall prediction information from three different sources (the new prediction model developed in chapter 3, NMSA and ICPAC), ABBABOKA suggests the best possible planting alternatives for a given homogenous rainfall zone and planting season. When decision making under this predictive information alone is not sufficient, soil water parameters need to be consulted for more reliable decision making. This simple and briefly constructed ABBABOKA is expected to provide a suite of guidelines to the users. Certainly, this constitutes a significant departure from the fixed ‘best bet’ recommendations I learned from research systems in the past. It is recommended that the time-space classification of agricultural areas into homogeneous zones needs to be extended to the rest of the country together with the tailored rainfall prediction information. Research needs to be geared towards crop water requirements, climate risks and simulation modelling aspects. A network of weather stations and soil database needs to be developed in order to promote the soilcrop- climate research in Ethiopian agriculture. More importantly, the use of decision support tools and the well-established models (like APSIM) need to be included in agricultural research and development efforts.

Seisoenale reënval is ‘n belangrike bron van water vir droëlandboerdery in die semiariede gebiede van die wêreld waar reënval beide marginaal en veranderlik is. Alhoewel reën minder voorspelbaar is in terme van aanvangstyd, hoeveelheid en verspreiding, is daar nogtans ‘n behoefte om die basiese eienskappe van die reënval, en spesifiek die veranderlikheid daarvan, te verstaan ten einde hierdie inligting in landboukundige besluitneming te kan gebruik. Die kombinering van die seisoenale reënvalvoorspelling met gewas-waterbehoefte en grondwaterinligting is ‘n belangrike sleutel tot suksevolle landbou. Die uiteindelike doel van hierdie studie was om ‘n beter begrip te verkry van die belangrikste reënval-eienskappe wat die basis sou vorm vir die klassifisering van die Sentrale Skeurvallei (SSV) van Ethiopië in homogene reënvalsones, en om dan ‘n seisoenale reënvalvoorspellingsmodel vir hierdie gebied te ontwikkel. Die brondata vir die analise is vanaf die Nasionale Meteorologiese Dienste Agentskap (NMSA) en gedeeltelik vanaf Melkassa Navorsingsentrum (MARC) en die Internasionale Navorsingsinstituut vir Klimaatsvoorspelling (IRI) verkry. Reënval veranderlikheid en tydreeksanalise is respektiewelik deur INSTAT 2.51 en die gekodeerde tydsmetode verkry. Die begin- en einddatums van die reënval vir Maart-April-Mei (MAM) reënvaltotale is die twee mees veranderlike reënvalkenmerke van beide Miesso en Abomssa. Vir beide stasies toon die einddatum die minste veranderlikheid. Die begindatum vir die reën by Miesso strek vanaf die onderste kwartiel (25 persentiel) van dag van die jaar (DVJ) 61 tot die boonste kwartiel (75 persentiel) van DVJ 179 met ‘n variansiekoëffisiënt (vk) van 42%. By Miesso eindig die hoof reënseisoen gedurende die laaste dae van September (DVJ 272 - 274) een maal elke vier jaar en voor DVJ 293 in drie uit vier jaar. By Abomssa is gevind dat ‘n vk van 40.5% die onderste kwartiel (DVJ 61) tot die boonste kwartiel (DVJ 134) beskryf. By albei plekke is gevind dat aanplanting voor 15 Maart (DVJ 75) in slegs een uit vier jaar sukses sal lewer. By Miesso kan hierdie boonste kwartiel statistiek tot by DVJ 179 verleng word, maar by Abomssa is aanplanting voor 15 April (DVJ 134) in drie uit elke vier jaar moontlik. By Abomssa staak die reën respektiewelik teen DVJ 286 en die einde van Oktober (DJV 305) vir die 25 en 75 persentiel punte. Die tydreeksontledings het geen konkrete bewyse gelewer vir die bestaan van enige neigings by òf Miesso òf Abomssa nie – inligting wat nuttig is vir langtermyn navorsing- en ontwikkelingsbeplanning, sowel as die seisoenale reënvalvoorspelling vir die studiegebied. Die klassifikasie-studie vir die ruimtelike reënvalpatroon het gelei tot die totstandkoming van vier homogene reënvalsones met duidelike ontwikkelings- en navorsingseenhede. Die FORTRAN-90 gebaseerde program NAVORS2 is vir hierdie doel gebruik. So het die Alem Tena-Langano sone met ‘n suidelike aansig en beter reënvalpatrone as die droër sones, sone 1 gevorm. Die suidelike, suidwestelike en suidoostelike streek vorm die nat sone (sone 2), terwyl die Debre-Zeit-Nazerth-Dera area met sy noordwestelike tot noordoostelike aansig en ‘n hoër reënval as sone 1, sone 3 vorm. Die droër noordoostelike streek vorm sone 4. Sewe-en-twintig seisoenale reënvalvoorspellings-modelle met verskillende prestasievaardighede wat vir operasionele boerdery gebruik kan word, is ontwikkel vir die Maart-September maandelikse reënval met gebruik van die klimaat voorspelligshulpmiddel oftewel Climate Predictability Tool (CPT v.4.01) vanaf IRI. Dit het aan die lig gekom dat met verhoogde waarnemingsnetwerke en data beskikbaarheid dit moontlik is om bruikbare operasionele klimaatvoorspelling te behaal vir kleiner ruimtelike eenhede met ‘n korter voorgeetyd. Die tydelike-ruimtelike waterbehoefte vervullingspatroon-ontledings is met AGROMETSHELL v.1.0 van die FAO uitgevoer. Veertien opeenvolgende sorghum groeiseisoene wat ‘n algemene prentjie van gewaswaterbehoefte vervullingskets, is gekarteer. Die suidelike, suidwestelike en suidoostelike dele (sone 2) van die SSV het die mees gunstige ligging vir die verbouing van ‘n reeks volwasse sorghumgroepe. Die noordwestelike en sentrale dele (sone 3) het die naasbeste klimaat. Die uitgestrekte droë lande van die noordooste van die studiegebied (sone 4) is, met die uitsondering van die Miesso-Assebot vlakte, nie gepas vir ekonomiese boerdery met sorghum onder droëlandtoestande nie. Met die groeistadiumgebaseerde waterbehoefte vervullingsindeks (WBVI) ontledings is gevind dat die middel-seisoen/blomstadium van die sorgum kultivars drie keer meer sensitief is vir veranderings in sorghum opbrengs vir beide kultivars en eksperimentele gebiede vergeleke met die WBVI van die ander groeistadiums. Die uitslae van die waterproduksiefunksie (WPF) ontledings het ook gedui op die potensiaal van WBVI om langtermyn sorghum opbrengs te voorspel. Die kumulatiewe digtheidsfunksie (KDF) en stogastiese dominansie-analises vir die 120-dag sorgum kultivar wat by Miesso verbou is, toon dat die Junie plantdatum die mees effektiewe stel is wat betref eerstegraad stogastiese dominansie (ESD), terwyl Mei die effektiefste vir Melkassa was. Die KDF vir Arsi Negele wys die April plantdatum as die beste stel aan. Dus word hierde plantdatums verkies deur boere wat ‘hoër’ opbrengste by die verskeie gebiede verlang, ongeag die houding teenoor risiko. Die sensitiwiteitsanalises wat uitgevoer is deur gebruik te maak van verskillede vlakke van seisoenale reënval en inset veranderlike kombinases (sorgum plantdatum, datum waarop volwasse stadium bereik word, aantal reëndae en WBVI) vir Miesso, Melkassa en Arsi Negele, verskaf bruikbare inligting. Deur inset veranderlikes, met die uitsondering van WBVI, op die verkieslike vlak te hou (d.w.s. vroeë plantdatum, verlengde volwasse stadium datum en ‘n groter aantal reëndae), en slegs WBVI te verander vanaf 100% tot 75%, het gelei tot ‘n 49.7% opbrengsverlaging by Miesso, 40.8% by Melkassa en 24.3% by Arsi Negele. Verder is daar gevind dat ‘n verlaging van WBVI tot 50% sou lei tot ‘n totale gewasmislukking by Miesso en Melkassa, terwyl daar ‘n afname van 48.6% in die opbrengs by Arsi Negele sal voorkom. Soortgelyke resultate is verkry waar WBVI toegelaat is om oor ander insetvlak-kombinasies te varieer. Visual Basic v.6.0 is gebruik om die algoritme vir die besluitneming ondersteuningshulpmiddel (BOH) te skryf wat sorgum plantdatums in die SSV bereken. Dié program is ABBABOKA 1.0 genoem. Deur gebruik te maak van die reënvalvoorspellingsinligting vanaf drie verskillende bronne (die nuwe voorspellingsmodel ontwikkel in hoofstuk 3, NMSA en ICPAC) stel ABBABOKA die beste moontlike plantdatum-alternatiewe vir ‘n gegewe homogene reënval sone en plantseisoen voor. Wanneer besluitneming met behulp van hierdie voorspellingsinligting alleen nie genoeg is nie, moet grondwater-eienskappe geraadpleeg word vir meer betroubare besluitneming. Dit word verwag dat die eenvoudige en kort gestruktueerde ABBABOKA ‘n hele klompie riglyne aan verbruikers sal verskaf. Dit dui verseker op ‘n noemenswaardige afwyking van die vaste “beste raai” aanbevelings wat deur navorsingstelsels tevore verskaf is. Daar word aanbeveel dat die tydelik-ruimtelike klassifikasie van landboukundige gebiede tot homogene sones tot die res van die land uitgebrei moet word tesame met die aangemete reënvalvoorspellingsinligting. Daar is ‘n behoefte vir navorsing wat gemik is op gewas-waterbehoeftes, klimaatrisikos en simulasie modelleringsaspekte. Die waarnemingsnetwerk en klimaat en gronddatabasisse behoort ontwikkel te word om grond-gewas-klimaatnavorsing in Ethiopië se landbou te bevorder. Wat van meer belang is, is dat die gebruik van besluitneming ondersteuningshulpmiddels asook gevestigde modelle (soos APSIM) by landboukundige navorsing en ontwikkelingsprojekte ingesluit behoort te word.
Thesis (Ph.D. (Agrometeorology))--University of the Free State, 2005
Keywords: Long-range weather forecasts -- Ethiopia; Sorghum -- Climate factors -- Ethiopia; Crops and climate -- Ethiopia