Risk efficiency of optimal water allocation within a single- and multi-stage decision-making framework

The South African government has put legislation in place to exercise better control over irrigation water usage. Thus, proper planning of irrigation areas and scheduling of irrigation events in order to stay within water quotas has become more important. Currently, the available methodologies to assist irrigation farmers overlook the complexities and interrelated relationships between crop-area planning and the multi-stage nature of irrigation-scheduling decisions within a stochastic dynamic environment. This paper contributes to knowledge through the development of a bio-economic model that uses evolutionary algorithms to optimise water use, taking cognisance of the complex interrelationships between crop-area planning, the multistage decision-making nature of irrigation-scheduling decisions, and the stochastic dynamic environment under conditions of limited water supply. The results show that gross margin variability is reduced and the expected outcomes are improved due to improved irrigation-scheduling decisions made sequentially in multiple stages. Multi-stage decisions tend to make the impact of risk aversion less profound because taking account of unfolding weather information is risk reducing. Ignoring the risk-reducing impact of sequential decision-making will over-estimate the cost of water restrictions. Caution is hence necessary when formulating agricultural water-allocation policies based on crop water optimisation models that overlook the complex nature of irrigation decisions.