Abstract
As a basic natural and strategic resource, water is of great significance to the sustainable development of economies and societies. Owing to population growth, industrialization, the acceleration of urbanization, and global warming, water poverty is gradually increasing in some parts of the world. Effectively assessing water poverty from different dimensions is still a serious challenge for global water resources planning. This paper establishes a framework of multidimensional water poverty (MWP) from six dimensions: water management, water technology, water assets, water welfare, water resources, and water environment. The measurement model of MWP is built based on the Back Propagation Neural Network (BPNN), and the Spatial Correlation Analysis tool is used to visualize the spatial effects of MWP. The Yangtze River Economic Belt (YREB) was used as a case study and the main factors affecting the MWP of the YREB were determined by the Geodetector. When analyzing the results the following observations were made: (1) In terms of time distribution, the level of MWP in the YREB has gradually increased, and the poverty gap between the upper reaches, as well as the middle and lower reaches, shows an increasing trend. (2) With respect to spatial distribution, there is a continuously increasing agglomeration effect that shows a gradient-increasing distribution pattern of “West-Central-East.” (3) The MWP in the YREB is mainly affected by these indicators in the three dimensions consisting of water resources, water technology, and water management. Specifically, R&D expenditure as a percentage of GDP, the proportion of water-saving irrigation area in the cultivable land area, the urban daily wastewater treatment capacity, the land surface water resources per capita, and the groundwater resources per capita play an important role in the MWP. Based on the above findings, targeted policy recommendations are proposed to alleviate the MWP in the YREB.
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