title: An inexact two-stage stochastic programming model for water resources management in Nansihu Lake Basin, China.
abstract: In this study, an inexact two-stage water resources management model was developed for multi-regional water resources planning in the Nansihu lake Basin, China. Four planning districts, four water users, and five water sources were considered in the optimization model, with net system benefit, recourse cost, water supply cost, and wastewater treatment cost being analyzed. Methods of interval-parameter programming (IPP) and two-stage stochastic programming (TSP) were incorporated into the model to tackle uncertainties described by both interval values and probability distributions. A number of scenarios corresponding to different river inflow levels were examined, and the results indicated that different inflow levels could lead to different water allocation schemes with varied system benefit and system-failure risk. In general, the developed model can provide an effective linkage between economic benefits and the associated penalties attributed to the violation of predefined policies. The modeling results were valuable for supporting the adjustment or justification of the existing water allocation schemes within a complicated water resources system under uncertainty.
authors.affiliation: MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206, China. xieyulei850228@yahoo.com.cn
authors.forename: Y L
authors.initials: YL
authors.lastname: Xie
authors.forename: G H
authors.initials: GH
authors.lastname: Huang
authors.forename: W
authors.initials: W
authors.lastname: Li
authors.forename: J B
authors.initials: JB
authors.lastname: Li
authors.forename: Y F
authors.initials: YF
authors.lastname: Li
mesh_terms: D002681:China; D008962:Models, Theoretical; D013269:Stochastic Processes; D018508:Water Purification / Q000379:methods*; D014881:Water Supply
keywords: Inexact two-stage stochastic programming; Multi-regional; Multi-users; Uncertainty; Water resources allocation