Affiliation:
1. Institute of Soil and Water Conservation Northwest A&F University Yangling China
2. Institute of Soil and Water Conservation Chinese Academy of Sciences and Ministry of Water Resources Yangling China
3. Research Center on Soil and Water Conservation Ministry of Water Resources Yangling China
4. Esri Canada Limited Ottawa Ontario Canada
5. Xi'an Engineering Investigation and Design Research Institute of China National Nonferrous Metals Industry CO., LTD Xi'an China
6. Powerchina Northwest Engineering Corporation Limited Xi'an China
7. College of Water Resources and Architectural Engineering Northwest A&F University Yangling China
Abstract
AbstractSoil erosion is an important cause of global land degradation, and accurate monitoring of it is essential. The Soil and Water Assessment Tool (SWAT), a distributed hydrological model, is an advanced technique for predicting soil erosion at watershed scale. However, as the erosion framework was established in gently sloping land, SWAT is limited in predicting soil erosion in some highland and mountainous regions. Therefore, this study suggested a method to integrate the sediment transport theoretical formula that can reflect the morphology of gully regions into SWAT to obtain SWAT‐S to enhance the calculation performance of sediment load, and the SWAT‐S was evaluated according to the coefficient of determination (R2), Nash‐Sutcliffe coefficient (NSE), Percent‐Bias (P‐BIAS) and root mean square errors (RMSE)‐observations SD ratio (RSR) in the Yanhe basin on the Chinese Loess Plateau. The results showed that SWAT‐S is more successful in reproducing the monthly sediment load, with R2, NSE, |P‐BIAS| and RSR were changed by 5.08%, 17.65%, −2.92% and −10.00% in the calibration, as well as by 1.18%, 10.39%, 45.45% and −18.75% in the validation of the SWAT‐S compared to SWAT. Meanwhile, SWAT‐S estimates 2.66 × 106 t more sediment than SWAT during the June–September flood season and better matches observed data. In total, the revised SWAT can improve the performance of sediment estimation, which is beneficial for the wider application of the model in more regions of the world.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Subject
Soil Science,General Environmental Science,Development,Environmental Chemistry
Cited by
3 articles.
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