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An Inexact Fuzzy Optimization Programming with Hurwicz Criterion (IFOPH) for Sustainable Irrigation Planning in Arid Region
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Abstract: In the past decades, sustainability in irrigation planning has been of concern to many researchers and managers. However, uncertainties existed in irrigation planning system can bring about enormous difficulties and challenges in generating desired decision alternatives to attain the aim of sustainability. In this study, an inexact fuzzy optimization programming with Hurwicz criterion (IFOPH) is developed for sustainable irrigation planning under uncertainty, which incorporate two-stage stochastic programming (TSP), interval-parameter programming (IPP), fuzzy credibility-constraint programming (FCP) and Hurwicz criterion (TCP-CH) within an framework. The IFOPH approach can not only provide an effective linkage between conflicting economic benefits and the associated penalties attributed to the violation of the pre-regulated policies, but also tackle uncertainties expressed as probabilistic distributions, fuzzy sets and interval values. The developed method is applied to the real case of planning sustainable irrigation in Tarim Basin, which is one of the aridest regions of China. The results based on confidence degrees and Hurwicz parameters are obtained, which can permit in-depth analyses of various policy scenarios of that are associated with different levels of economic penalties. Meanwhile, the results reveal that appropriate irrigation planning can improve the efficiency of water allocations, which has brought positive effects on remedying water deficit and promoting the sustainable development of agricultural production activities. Moreover, tradeoffs between economic benefit and system-failure risk based on Hurwicz criterion can support generating an increased robustness in risk control, which can facilitate the local decision makers in adjusting water-allocation pattern to satisfy the increasing water demand.
Keywords: Sustainable irrigation planning; water resources management; two-stage stochastic programming; fuzzy credibility-constraint programming; Hurwicz criterion; uncertainty; arid region.