Application of a DPSIR Modeling Framework to Assess Spatial–Temporal Differences of Water Poverty in China

Abstract

AbstractWater shortage is a common problem around the world, especially in developing countries. Water shortage is closely linked to natural and social conditions, but the linkages between these natural and social conditions and their underlying temporal and spatial variation are less well explored. This paper details an application of the Driving‐Force‐Pressure‐State‐Impact‐Response (DPSIR) model, a holistic and sustainable tool for resources planning and management, and uses comprehensive weights to evaluate the water poverty (wp) in China from 1997 to 2014. This study applies the Kernel density estimation model to analyze the temporal variation trend and uses the least square error model to analyze the spatial pattern of wp. The results show the level of wp is gradually declining over time and the improvements in the coastal and inland wp situation are not spatially harmonious, and there are four primary types of wp in China based on drivers and causal mechanisms: D‐P‐I, D‐P‐I‐R, D‐P‐S‐I, and D‐P‐S‐I‐R. Furthermore, we analyze the main causes of spatial difference of wp and put forward corresponding countermeasures. The research findings are intended to provide a new insight for the evaluation of wp in the context of sustainable development, breaking past limitations that arise in simplified analyses using a single method, and to provide a strategy for regional water resources management to relieve wp.