Using Stochastic Dynamic Programming to Support Water Resources Management in the Ziya River Basin, China

Abstract

Water scarcity and rapid economic growth have increased the pressure on water resources and environment in Northern China, causing decreased groundwater tables, ecosystem degradation, and direct economic losses due to insufficient water supply. The authors applied the water value method, a variant of stochastic dynamic programming, to optimize water resources management in the Ziya River basin. Natural runoff from the upper basin was estimated with a rainfall-runoff model autocalibrated using in situ measured discharge. The runoff serial correlation was described by a Markov chain and used as input for the optimization model. This model was used to assess the economic impacts of ecosystem minimum flow constraints, limited groundwater pumping, and the middle route of the South–North Water Transfer Project (SNWTP). A regional climate shift has exacerbated water scarcity and increased water values, resulting in stricter water management. The results show that the SNWTP reduces the impacts of water scarcity and impacts optimal water management in the basin. The presented modeling framework provides an objective basis for the development of tools to avoid overpumping groundwater resources at minimum costs.