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• W3120342413 abstract "Abstract In land surface models, the ability to simulate runoff is a good diagnostic for the hydrological cycle and other surface parameterizations; however, the partitioning of total runoff into surface and subsurface runoff shows considerable uncertainties. The interaction between soil moisture and groundwater plays an important role in simulating the surface and subsurface runoff. Specific yield ( S y ) is widely used to calculate water table depths, in which the error comes mainly from uncertainty in determining the S y value. This study developed a new soil moisture‐dependent model (SMD‐model) to improve the simulations of water table depths and partitioning total runoff into subsurface and surface components. The validations against observations and the Community Noah Land Surface Model with MultiParameterization Options (Noah‐MP) in three basins indicate that the SMD‐model can simulate a realistic and stable water table series, which shows the detailed variations of observed water tables, avoiding the uncertainties in determining S y ; and it can generate accurate proportions of surface and subsurface runoff. However, when S y is used to calculate the water table depth, keeping other processes the same as in the SMD‐model, it produces a series of smoother and deeper water tables, and underestimates the proportion of subsurface runoff to total runoff by 24%–28%. Noah‐MP captures the overall variation of observed water tables and overestimates the proportion of subsurface runoff by 20%–33%. This study can provide relatively accurate estimations of water tables and surface and subsurface runoff, and benefit the study of land‐atmosphere interactions." @default.
• W3120342413 created "2021-01-18" @default.
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• W3120342413 date "2021-02-16" @default.
• W3120342413 modified "2023-10-16" @default.
• W3120342413 title "A Soil Moisture‐Dependent Model to Simulate Water Table Depth and Proportions of Surface and Subsurface Runoff and Its Validation at the Basin Scale" @default.
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• W3120342413 doi "https://doi.org/10.1029/2020jd033661" @default.
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