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Abstract
Rivers are among the most diverse, dynamic, and productive ecosystems on Earth. River flow regimes are constantly changing, but characterizing and understanding such changes have been challenging from a long-term and global perspective. By analyzing water extent variations observed from four-decade Landsat imagery, we here provide a global attribution of the recent changes in river regime to morphological dynamics (e.g., channel shifting and anabranching), expansion induced by new dams, and hydrological signals of widening and narrowing. Morphological dynamics prevailed in ~20% of the global river area. Booming reservoir constructions, mostly skewed in Asia and South America, contributed to ~32% of the river widening. The remaining hydrological signals were characterized by contrasting hotspots, including prominent river widening in alpine and pan-Arctic regions and narrowing in the arid/semi-arid continental interiors, driven by varying trends in climate forcing, cryospheric response to warming, and human water management. Our findings suggest that the recent river extent dynamics diverge based on hydroclimate and socio-economic conditions, and besides reflecting ongoing morphodynamical processes, river extent changes show close connections with external forcings, including climate change and anthropogenic interference.
Rivers are among the most diverse, dynamic, and productive ecosystems on Earth. Here, using Landsat imagery, the authors provide a global attribution of the recent changes in river regime to morphological dynamics, dam-induced widening, and hydrological signals.
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1 Chinese Academy of Sciences, Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Nanjing, China (GRID:grid.9227.e) (ISNI:0000000119573309); The University of Hong Kong, School of Biological Sciences and Institute for Climate and Carbon Neurality, Hong Kong, China (GRID:grid.194645.b) (ISNI:0000000121742757)
2 Hohai University, College of Hydrology and Water Resources, Nanjing, China (GRID:grid.257065.3) (ISNI:0000 0004 1760 3465); Hohai University, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing, China (GRID:grid.257065.3) (ISNI:0000 0004 1760 3465)
3 Kansas State University, Department of Geography and Geospatial Sciences, Manhattan, USA (GRID:grid.36567.31) (ISNI:0000 0001 0737 1259)
4 University of North Carolina, Department of Earth, Marine and Environmental Sciences, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720)
5 Virginia Polytechnic Institute and State University, Department of Geosciences, Blacksburg, USA (GRID:grid.438526.e) (ISNI:0000 0001 0694 4940)
6 University of California, Department of Geography, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718)
7 Chinese Academy of Sciences, Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Nanjing, China (GRID:grid.9227.e) (ISNI:0000000119573309)
8 Chinese Academy of Sciences, State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309)
9 The University of Hong Kong, School of Biological Sciences and Institute for Climate and Carbon Neurality, Hong Kong, China (GRID:grid.194645.b) (ISNI:0000000121742757)
10 Nanjing University, School of Geography and Ocean Science, Nanjing, China (GRID:grid.41156.37) (ISNI:0000 0001 2314 964X)
11 Chinese Academy of Sciences, Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Nanjing, China (GRID:grid.9227.e) (ISNI:0000000119573309); University of Chinese Academy of Sciences, Nanjing (UCASNJ), Nanjing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419)