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Y. Zhou [1] and Y. P. Li [1] and G. H. Huang [1] and Y. Huang [2]

Academic Editor: Xiaosheng Qin

, 1, , MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, , Resources and Environmental Research Academy, , North China Electric Power University, , Beijing 102206, , China, , ncepu.edu.cn,

, 2, , State Key Laboratory of Desert and Oasis Ecology, , Xinjiang Institute of Ecology and Geography, , Chinese Academy of Sciences, , Urumqi 830011, , China, , .cas.cn,

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

The combined pressures from increasing water demands and limited water supplies have forced planners to contemplate comprehensive and efficient schemes for water resources management, especially in arid and semiarid regions [1, 2]. Nowadays, continuing economic growth and rapid population increase are likely to aggravate water-shortage problems that may lead to controversial and conflict-laden water-allocation issues among multiple competing interests (e.g., municipal, industrial, stockbreeding, forestry, ecological, and agricultural). Moreover, more and more arid inland watersheds suffer from ecological degradation and vegetation losses as a result of limited water resources, severe weather conditions, poor management practices, and failed policy instructions [3–5]. Consequently, the conflicts between environmental protection and economic development in arid and semiarid regions have been pressing challenges for decision makers. Efficient and equitable water-resources management is required for regional socioeconomic and environmental sustainability.

Previously, a  large number of modeling approaches based on stochastic mathematical programming (SMP) were advanced for allocating and managing water resources in more effective and sustainable ways [6–14]. For example, Watkins Jr et al. [15] proposed a scenario-based multistage stochastic programming model for planning water supplies from highland lakes. By explicitly considering a number of inflow scenarios, the stochastic model could help determine a contract for water delivery in the coming year. Harrison [16] advanced a chance-constrained linear programming model to allocate available land and water resources optimally on seasonal basis so as to maximize the net annual return from the study area, where net irrigation water requirements of crops were considered as stochastic variable. Li et al. [17] proposed a multistage fuzzy-stochastic programming model for supporting water...

                                  

     

                                      

                                                      

                                                                      

       
 
 

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