Optimal allocation model of water resources based on the prospect theory

Abstract

The rational allocation of water resources in the basin/region can be better assisted and performed using a suitable water resources allocation model. Rule-based and optimization-based simulation methods are utilized to solve medium- and long-term water resources allocation problems. Since rule-based allocation methods requires more experience from expert practice than optimization-based allocation methods, it may not be utilized by users that lack experience. Although the optimal solution can be obtained via the optimization-based allocation method, the highly skilled expert experience is not taken into account. To overcome this deficiency and employ the advantages of both rule-based and optimization-based simulation methods, this paper proposes the optimal allocation model of water resources where the highly skilled expert experience has been considered therein. The "prospect theory" is employed to analyze highly skilled expert behavior when decision-making events occur. The cumulative prospect theory value is employed to express the highly skilled expert experience. Then, the various elements of the cumulative prospect theory value can be taken as the variables or parameters in the allocation model. Moreover, the optimal water allocation model developed by the general algebraic modeling system (GAMS) has been improved by adding the decision reversal control point and defining the inverse objective function and other constraints. The case study was carried out in the Wuyur River Basin, northeast of China, and shows that the expert experience considered as the decision maker's preference can be expressed in the improved optimal allocation model. Accordingly, the improved allocation model will contribute to improving the rationality of decision-making results and helping decision-makers better address the problem of water shortage.