Simulation-based optimization method for water resources management in Tarim River Basin, China

Abstract

In this study, a simulation-based optimization method (SOM) is developed for supporting water resources planning and management under uncertainty in Tarim River Basin, China. The modeling system couples a lumped rainfall runoff model and an inexact multistage stochastic programming (IMSP) into the general framework. The SOM extends upon the existing multistage stochastic programming method by allowing uncertainties expressed as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. Its random parameter is provided by the statistical analysis of simulation outcomes of the rainfall runoff model. Moreover, it can also reflect dynamic features of the system conditions through transactions at discrete points in time over the planning horizon. The results indicate that reasonable solutions have been generated. The results are helpful for water resources managers in not only making decisions of water allocation but also gaining insight into the tradeoffs between environmental and economic objectives.