Verification of a New Spatial Distribution Function of Soil Water Storage Capacity Using Conceptual and SWAT Models
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 3
Abstract
The Soil Conservation Service Curve Number (SCS-CN) method is widely used in conceptual rainfall-runoff models for describing the runoff response with a curve, which is a function of the cumulative storm rainfall and antecedent wetness conditions. To improve the SCS-CN method, a new distribution function was recently proposed to unify the surface runoff modeling of the SCS-CN method and probability-distributed functions in the variable infiltration capacity (VIC) and Xin’anjiang models. This study aims to verify the new distribution function in a conceptual rainfall-runoff model and in the Soil and Water Assessment Tool (SWAT) by using real catchments. The Xunhe River basin in China and other basins in the United States were used as case studies. Results show that more observed variability in streamflow is captured when using the new spatial distribution function of soil water storage capacity in the conceptual runoff model. Specifically, there is a 9.8% average increase in the Nash-Sutcliffe efficiency (NSE), while simultaneously reducing the bias and mean relative absolute error (MRAE). When using the new distribution in SWAT, the model is able to better estimate the observed streamflow as indicated by higher NSE values for most of the basins. Akaike information criterion (AIC) is used for validating the goodness-of-fit when the number of parameters and model structure change. Further findings suggest that the estimated variance is more sensitive to the value of the new shape parameter when soil water content is low in the early stage of rainfall. Therefore, the proposed new distribution function is shown to be effective in improving the accuracy of simulating streamflow for both conceptual and SWAT models.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request.
Acknowledgments
This study was partially supported by the National Natural Science Foundation of China (51861125102), the Innovative Research Groups of the Natural Science Foundation of Hubei, China (2017CFA015) and Innovation Team in Key Field of the Ministry of Science and Technology (2018RA4014). The authors would like to thank the editor and the anonymous reviewers for their comments that helped improve the quality of the paper.
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Journal of Hydrologic Engineering
Volume 25 • Issue 3 • March 2020
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©2020 American Society of Civil Engineers.
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Received: Feb 20, 2019
Accepted: Sep 24, 2019
Published online: Jan 10, 2020
Published in print: Mar 1, 2020
Discussion open until: Jun 10, 2020
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