Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties

In this study, an interactive two-stage fuzzy stochastic programming (ITFSP) method is developed for supporting crop planning and water resource allocation under uncertainty. ITFSP can effectively address uncertainties expressed as probability distributions and fuzzy-boundary intervals. It can also be utilized for in-depth analyzing different policy scenarios that are integrated with various economic implications since penalties are executed with recourse actions. ITFSP enables decision makers to identify a tradeoff between higher objective values and feasibility of constraints. The ITFSP method is applied to a real case of Hetao irrigation district, one of the largest irrigation districts for food production in China. Different scenarios for crop planning targets which reflect the attitudes of local authority to the available water resources are examined. Results discover that different scenarios lead to changed irrigation patterns, water shortages, penalties, as well as system benefits. Results also reveal that decision makers would be more positive to water allocation to crops of wheat and oil than maize; oil crop always possesses the priority of water allocation and would be partly satisfied even under the low flow. Solutions are useful for determining optimized cropland use and water allocation patterns in such an agricultural system in the arid region, which could hedge appropriately against future available water levels in more profitable and sustainable ways.