Spatial analysis of dual-scale water stresses based on water footprint accounting in the Haihe River Basin, China

• Published in: Ecological indicators Vol. 92; pp. 254 - 267
• Main Authors: Li, Chunhui, Xu, Meng, Wang, Xuan, Tan, Qian
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2018
• Subjects: autocorrelation; basins; Blue water footprint; China; cities; developing countries; environmental indicators; Exploratory spatial data analysis; Gray water footprint; Haihe River Basin; spatial data; wastewater; water footprint; Water footprint accounting; water management; water quality; water shortages; watersheds; China; Water footprint accounting; Gray water footprint; Exploratory spatial data analysis; Haihe River Basin; Blue water footprint
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2017.02.046

[Display omitted] •Conduct an in-depth WF accounting for different economic sectors and cities at river basins.•Improve the evaluation accuracy of WFs for river basins via accounting efforts downscaled to cities.•Enhance the WF-based methods of water stress analyses via applying an exploratory spatial data analysis (ESDA) model.•Reveal the spatial distributions of water stress and water pollution stress within the study area. Water scarcity and degradation of water quality in river basins are among the major issues addressed by water resources management authorities. Moreover, two typical challenges associated with water resources management include naturally unbalanced distribution and administrative disparities under multiple jurisdictions at the watershed scale. Effective accounting and management methods are thus desired to deal with such challenges. Water footprint accounting is widely used for assessing natural water resources availability and supporting optimal allocation among multiple jurisdictions, representing a useful tool for improving watershed sustainability. Not only will this enable successful revealing of the direct water consumption by relevant agents, but also indirect water consumption by concerning users. Such a method is particularly useful for addressing water-related issues in numerous watersheds of developing countries, which are subject to diverse water stressors. Hence, this study aimed at conducting water footprint accounting under city/regional and basin scales for the investigation of the amounts of blue and gray water in the Haihe River Basin (HRB), China. The Blue Water Footprint Index (BWFI) and the Gray Water Footprint Capacity Coefficient (K) were introduced to comprehensively evaluate water scarcity in terms of quantity and quality. The results revealed that all cities of the HRB suffered from extreme water scarcity. The industrial sector was identified as the primary contributor to the blue water footprint at the watershed. The agricultural gray-water footprint of the HRB accounted for 54% of the total. The exploratory spatial data analysis (ESDA) was adopted to analyze the spatial auto-correlation features of blue and gray water in the HRB. The results indicated that Dezhou and Binzhou had the highest water deficiency in both of the water stresses, and that Xinxiang, Puyang, Anyang and Jiaozuo had the highest water problem predominantly due to water quality stress.