Irrigation technology choices under hydrologic uncertainty: A case study from Maipo River Basin, Chile

The effect of hydrologic uncertainty on field irrigation technology (FIT) choices is studied within this paper. A two-stage stochastic programming model (SPM) is developed to incorporate hydrologic uncertainties related to both water requirements and water availability through a probabilistic scenario-based approach. The SPM can provide a mechanism with which model solutions can be adjusted to account for variations in water availability and water requirements. Moreover, the two-stage decision process is combined with risk aversion analysis in field irrigation choices, which helps balance the risk of profit loss in dry years and the risk of excess capital cost in wet years. The model can be used to generate decision information to individual farmers or farmer associations, regarding long-term field irrigation technology choices and crop pattern planning and short-term water allocation among crops under specific hydrologic scenarios. The model is applied to an irrigation district in the Maipo River Basin, Chile. It is found that higher levels of FIT are more profitable for higher-valued crops and decisions on FIT choices for low-valued crops are less sensitive to hydrologic uncertainties. The annualized capital cost per hectare in the district should be within in range of US$105-130, which is a range for tradeoff analysis between maximizing the expected profit and minimizing the risk of profit loss under drought conditions.