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Abstract
In the context of China’s freshwater crisis high-resolution data are critical for sustainable water management and economic growth. Yet there is a dearth of data on water withdrawal and scarcity regardless of whether total or subsector amount, for prefectural cities. In administrative and territorial scope, we accounted for water withdrawal of all 63 economic-socio-environmental sectors for all 343 prefectural cities in China, based on a general framework and 2015 data. Spatial and economic-sector resolution is improved compared with previous studies by partitioning general sectors into industrial and agricultural sub-sectors. Construction of these datasets was based on selection of 16 driving forces. We connected a size indicator with corresponding water-withdrawal efficiency. We further accounted for total blue-water withdrawal and quantitative water scarcity status. Then we compared different scopes and methods of official accounts and statistics from various water datasets. These disaggregated and complete data could be used in input-output models for municipal design and governmental planning to help gain in-depth insights into subsector water-saving priorities from local economic activities.
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1 Beijing Institute of Technology, School of Management and Economics, Beijing, China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246); Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790); University of East Anglia, Water Security Research Centre, School of International Development, Norwich, UK (GRID:grid.8273.e) (ISNI:0000 0001 1092 7967)
2 University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham, UK (GRID:grid.6572.6) (ISNI:0000 0004 1936 7486)
3 Aalto University, Water & Development Research Group, Department of Built Environment, Espoo, Finland (GRID:grid.5373.2) (ISNI:0000 0001 0838 9418)
4 University of Leeds, School of Civil Engineering, Leeds, UK (GRID:grid.9909.9) (ISNI:0000 0004 1936 8403)
5 Chinese Academy for Environmental Planning, Centre for Climate and Environmental Policy, Beijing, China (GRID:grid.464275.6) (ISNI:0000 0001 1998 1150)
6 University of East Anglia, Water Security Research Centre, School of International Development, Norwich, UK (GRID:grid.8273.e) (ISNI:0000 0001 1092 7967); Southern University of Science and Technology, Department of Statistics and Data Science, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790)
7 University College London, The Bartlett School of Sustainable Construction, London, UK (GRID:grid.83440.3b) (ISNI:0000 0001 2190 1201)
8 Hohai University, Business School, Nanjing, China (GRID:grid.257065.3) (ISNI:0000 0004 1760 3465)
9 Tsinghua University, Department of Earth System Science, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178); University College London, The Bartlett School of Construction and Project Management, London, UK (GRID:grid.83440.3b) (ISNI:0000 0001 2190 1201)
10 Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790)
11 Beijing Institute of Technology, School of Management and Economics, Beijing, China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246); Beijing Institute of Technology, Center for Energy and Environmental Policy Research, Beijing, China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246); Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246); Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246)