A hybrid fuzzy-stochastic programming method for water trading within an agricultural system

In this study, a hybrid fuzzy-stochastic programming method is developed for planning water trading under uncertainties of randomness and fuzziness. The method can deal with recourse water allocation problems generated by randomness in water availability and, at the same time, tackle uncertainties expressed as fuzzy sets in the trading system. The developed method is applied to a water trading program within an agricultural system in the Zhangweinan River Basin, China. Results can reflect the decisions for water allocation and crop irrigation under various flow levels; this allows corrective actions to be taken based on the predefined policies for cropping patterns and can thus help minimize the penalty due to water deficit. The results indicate that trading can release excess water while still keeping the same agricultural revenue obtained in a non-trading scheme. This implies that trading scheme is effective for obtaining high economic benefit, particularly for one water-resources scarcity region. Results also indicate that the effectiveness of the trading program is explicitly affected by uncertainties expressed as randomness and fuzziness, which challenges the users to make decisions of their water demands due to uncertain water availability. Sensitivity analysis is also conducted to analyze the impacts of trading costs, demonstrating that the trading efforts could become ineffective when the trading costs are too high.