Spatial-temporal variations of water poverty in rural China considered through the KDE and ESDA models

Water shortage is a common problem around the world, especially in rural areas of developing countries. Water shortage is closely linked to natural and social conditions, and the linkages between these natural and social conditions and their underlying spatial and temporal variations are less well explored in rural areas. The water poverty index (WPI) is a holistic tool for resource planning and management and is an effective tool in solving water shortage problems in developing countries through water resources managements. This study defines five components and 19 indicators using the WPI and assigns integrated weights to measure water poverty in rural China from 1997 to 2016. The results show that the level of water poverty has been gradually declining over time, and the improvements in the coastal and inland water poverty situation are not harmonious. This study also analyzes spatial and temporal variations of water poverty in rural China by the kernel estimation (KDE) and the exploratory spatial data analysis (ESDA) models. Hence, specific areas require special policy interventions. The research findings are intended to provide a new insight for the evaluation of water poverty in the context of sustainable development and to provide a strategy for regional water resource management to relieve rural water poverty in developing countries.