An inexact stochastic-fuzzy optimization model for agricultural water allocation and land resources utilization management under considering effective rainfall

Agricultural water management faces challenges from ecological environment stress (e.g. water scarcity issues, land resources pressure, and climate conditions) and uncertainties exist among multifarious activities in agricultural water resources management systems. In this study, an inexact stochastic-fuzzy programming model was proposed for irrigation water resources allocation and land resources utilization management under considering multiple uncertainties. In the model, uncertainties can be directly integrated into the optimization process through reflecting parameters and coefficients as interval values, fuzzy sets, random variables, and their combinations. The developed method is applied to planning irrigation water resources allocation and cropland pattern under considering the limited surface water and groundwater, the random effective rainfall, and the imprecise crops water requirements in Jining City. A number of scenarios corresponding to different fuzzy probability of violating constraint are examined in order to obtain the best management program under various scenarios, and search reasonable tradeoffs between varied system benefit and system-failure risk. The results indicated that agricultural water allocation is explicitly affected by uncertainties expressed as randomness and fuzziness, and the results are valuable for supporting the adjustment or justification of the existing water resources management schemes and a desired land utilization plan for regions socioeconomic development under uncertainty.