An economic analysis of salinity management with evolutionary algorithms in Vaalharts

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Date
2017-01
Authors
Haile, Berhane Okubay
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University of the Free State
Abstract
The main objective of this research was to develop a bio-economic salinity management model to evaluate the stochastic efficiency, water-use efficiencies and environmental impact of optimal irrigation-scheduling practices while taking cognisance of irrigation-water quality, soil conditions, irrigation-technology constraints, crops and stochastic weather. A bio-economic salinity management simulation model was developed in MATLAB through the integration of the Soil WAter Management Program (SWAMP), by combining electricity-cost calculations with enterprise budgets to evaluate the impact of current irrigation schedules used by irrigators. The resulting SWAMP-ECON model was linked to an evolutionary algorithm to determine the benefits of following an optimised irrigation-scheduling strategy for each field crop. The model was also extended to model inter-seasonal allocation of water between two consecutive crops grown on the same field, to evaluate changes in the irrigation schedule of the first crop to manage the impact of soil salinity on the second crop. Risk was included in the analyses through the use of a state-general characterisation, where decisions are made without any knowledge of which state will occur. The models were applied to a case study farm in Vaalharts Irrigation Scheme with a 30.1 ha centre-pivot irrigation-system. The farm is characterised by Bainsvlei soil type and a shallow water table close to or below the root zone. The scenarios considered to run the model were two water qualities (low and high), two irrigation-system delivery capacities (10 mm day-1 and 12 mm day-1), and three field crops (maize, wheat, and peas) with different salinity-tolerance levels. The field crops constitute the crops grown for intra-seasonal and one-year inter-seasonal applications. Stochastic efficiency, low water-use efficiencies and environmental-impact indicators were calculated to interpret results of irrigation-management options for achieving economic and environmental sustainability. The results show that the farmer's existing irrigation schedules for the field crops in the study were over-irrigation strategies characterised by low water-use efficiencies, which are the direct result of farmers ignoring the contribution of the shallow water table to crop water-use. Over-irrigation resulted in large amounts of drainage water releasing between 11 000 and 26 600 kg ha-1 of salt into the environment. Decreasing water quality increases the risk of failing to reach potential production levels of the more salt-sensitive crops (maize and peas), however, the impact on expected margin above specified costs was low. Peas is the most profitable enterprise, followed by maize, and then wheat. On average, the expected margin above specified costs for peas, maize, and wheat, respectively, is ZAR 448 370, ZAR 321 909 and ZAR 245 885. The conclusion is that the current irrigation strategy is inefficient, has a large impact on the environment and presents the opportunity to improve profitability through better irrigation-scheduling practices that acknowledge the contribution of the shallow water table. Results of the optimised irrigation schedules show significant increases in expected margin above specified costs, associated risk exposure, water-use efficiencies and water productivity, as well as decreases in environmental impact due to a reduction in the amount of salt leached (SL). The main contributing factor to the results is the fact that the amount of irrigation water could be reduced because the shallow water table contributed 40% to 62% to crop water-use evapotranspiration, depending on crop type, water quality, and irrigation-system delivery capacity scenario selected. The largest benefits were observed for the highly salt-tolerant crop (wheat), because no leaching was necessary to manage salt levels. Consequently, a large salt build-up in the soil was observed. Decreasing water quality, compared to good quality water, impacted more negatively on MAS, risk exposure and the extent of drainage losses by the more salt-sensitive crops. Irrigation-system delivery capacity did not affect water-application rates significantly, but the results show that it is easier to manage electricity costs with the larger capacity by using a time-of-use electricity tariff. The conclusion is that the benefit of an optimised irrigation strategy is considerable, though careful consideration should be given to the trade-off between decreasing water applications and increasing salinity levels in the soil. Results of the inter-seasonal optimised irrigation-scheduling strategy water-use show that the leaching needs to increase during the production of the first crop to reduce the starting soil-salinity level when the follow-up crop is planted, especially when the second crop is sensitive to high salinity levels. Low WUE, WP and profitability are the consequences, taking the follow-up crop into account. In conclusion, a risk-neutral farmer should only consider increasing the water applied to the first crop (e.g. maize) if the plan is to plant a salt-sensitive crop (e.g. peas) in the second season. In both the intra-seasonal and the inter-seasonal applications, a risk-averse decision-maker will use more irrigation water to reduce the variability of outcome. The main recommendation from this research is that alternative institutional arrangements should be considered to ensure that irrigators do not lose their water-use entitlements if the water that is not used is deemed a non-productive use. A scheme-level hydrology analysis is necessary to determine the impact on the water table if all water-users start mining the water table. Future research should focus on extending the model to include the long-term problem of salinity and enhancing the model to deal with state-specific applications of water to crops as new information becomes available to farmers about a state of nature.
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Keywords
Stochastic efficiency, Water-use efficiency, Water productivity, Environmental impact, Evolutionary algorithms, Salinity, Simulation, Irrigation schedule, Production risk, Optimisation, Water salinization -- South Africa -- Northern Cape -- Vaalharts, Thesis (Ph.D. (Agricultural Economics))--University of the Free State, 2017
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