Multiscale Water Use Driving Effects and Dynamic Water Demand Research Based on the Kaya-LMDI-STIRPAT Model

Abstract

A better understanding of the driving effects of socio-economic water use is essential to obtain accurate water demand prediction and to implement water resources management. In this study, six driving effects, including scale effect, structure effect, economic level effect, policy rationality effect, water price policy effect, and scientific and technological level effect, are considered. A Kaya-LMDI model is constructed to identify the driving effects of domestic, industrial and agricultural water use, and then a STIRPAT model is established for water demand production. Annual precipitation is introduced into the model for predicting agricultural water demand. The model is applied to Hebei province, China. The main conclusions are summarized as follows: ① The economic level effect plays a role in promoting the socio-economic water use in all prefecture-level cities of Hebei province; The water price policy effect plays a role in inhibiting the domestic and agricultural water use, while the scientific and technological level effect plays a role in inhibiting the industrial water use. ② The water use is mainly inhibited by the effects of policy rationality and water price policy before 2015 but mainly by the effects of water price policy and scientific and technological level after 2015; ③ There is a clear spatial difference in the driving effects of the socio-economic water use among the prefecture-level cities, and the economic level effect plays a major role in promoting the socio-economic water use in all prefecture-level cities; the water price policy effect plays an inhibitory role in nine cities; while the policy rationality effect plays an inhibitory role in two cities; ④ The water demand prediction results suggest that the water demand of Hebei province in 2030 is 22.01 billion m³ in normal years (P = 50%) and 24.33 billion m³ in medium-dry years(P = 75%), which are consistent with the red line set by the government. This study may contribute to optimizing the economic structure and provides guidance for water use management.