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ISSN  2096-3955

CN  10-1502/P

Citation: Rao, W. L., and Sun, W. K. (2022). Runoff variations in the Yangtze River Basin and sub-basins based on GRACE, hydrological models, and in-situ data. Earth Planet. Phys., 6(3), 228–240.

2022, 6(3): 228-240. doi: 10.26464/epp2022021


Runoff variations in the Yangtze River Basin and sub-basins based on GRACE, hydrological models, and in-situ data

University of Chinese Academy of Sciences, Beijing 100049, China

Corresponding author: WenKe Sun,

Received Date: 2021-12-05
Web Publishing Date: 2022-03-11

Water budget closure is a method used to study the balance of basin water storage and the dynamics of relevant hydrological components (e.g., precipitation, evapotranspiration, and runoff). When water budget closure is connected with terrestrial water storage change (TWSC) estimated from Gravity Recovery and Climate Experiment (GRACE) data, variations in basin runoff can be understood comprehensively. In this study, total runoff variations in the Yangtze River Basin (YRB) and its sub-basins are examined in detail based on the water budget closure equation. We compare and combine mainstream precipitation and evapotranspiration models to determine the best estimate of precipitation minus evapotranspiration. In addition, we consider human water consumption, which has been neglected in earlier studies, and discuss its impact. To evaluate the effectiveness and accuracy of the combined hydrological models in estimating subsurface runoff, we collect discharge variations derived from in situ observations in the YRB and its sub-basins and compare these data with the models’ final estimated runoff variations. The estimated runoff variations suggest that runoff over the YRB has been increasing, especially in the lower sub-basins and in the post-monsoon season, and is accompanied by apparent terrestrial water loss.

Key words: runoff; discharge; Yangtze River Basin; water budget closure; GRACE

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Runoff variations in the Yangtze River Basin and sub-basins based on GRACE, hydrological models, and in-situ data

WeiLong Rao, WenKe Sun