It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Data and knowledge of the spatial-temporal dynamics of surface water area (SWA) and terrestrial water storage (TWS) in China are critical for sustainable management of water resources but remain very limited. Here we report annual maps of surface water bodies in China during 1989–2016 at 30m spatial resolution. We find that SWA decreases in water-poor northern China but increases in water-rich southern China during 1989–2016. Our results also reveal the spatial-temporal divergence and consistency between TWS and SWA during 2002–2016. In North China, extensive and continued losses of TWS, together with small to moderate changes of SWA, indicate long-term water stress in the region. Approximately 569 million people live in those areas with deceasing SWA or TWS trends in 2015. Our data set and the findings from this study could be used to support the government and the public to address increasing challenges of water resources and security in China.
The authors of this study compile data on spatial and temporal dynamics of surface water bodies across China, covering a time span from 1989 – 2016. The study describes hot-spot areas with strongly decreasing trends in surface water area and terrestrial water storage in North China and discusses implications of water resources and security in China.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details






1 Fudan University, Coastal Ecosystems Research Station of the Yangtze River Estuary, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, School of Life Sciences, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); University of Oklahoma, Department of Microbiology and Plant Biology, Center for Spatial Analysis, Norman, USA (GRID:grid.266900.b) (ISNI:0000 0004 0447 0018)
2 University of Oklahoma, Department of Microbiology and Plant Biology, Center for Spatial Analysis, Norman, USA (GRID:grid.266900.b) (ISNI:0000 0004 0447 0018)
3 University of Maryland, Department of Geographical Sciences, College Park, USA (GRID:grid.164295.d) (ISNI:0000 0001 0941 7177)
4 Chinese Academy of Sciences, Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309)
5 LinkedIn Corporation, Sunnyvale, USA (GRID:grid.266900.b)
6 Chinese Academy of Tropical Agricultural Sciences, Rubber Research Institute, Danzhou, China (GRID:grid.453499.6) (ISNI:0000 0000 9835 1415)
7 Chinese Academy of Sciences, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309)
8 Fudan University, Coastal Ecosystems Research Station of the Yangtze River Estuary, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, School of Life Sciences, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)