Integration of remotely sensed C factor into SWAT for modelling sediment yield |
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| Authors: | Xianfeng Song Zheng Duan Yasuyuki Kono Mingyu Wang |
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| Institution: | 1. College of Resources and Environment, Graduate University of Chinese Academy of Sciences, Beijing 100049, China;2. Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands;3. Center for Southeast Asian Studies, Kyoto University, Kyoto 606‐8501, Japan |
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| Abstract: | The C factor, representing the impact of plant and ground cover on soil loss, is one of the important factors of the Modified Universal Soil Loss Equation (MUSLE) in the Soil and Water Assessment Tool (SWAT) to model sediment yield. The daily update of C factors in SWAT was originally determined by land use types and plant growth cycles. This does not reflect the spatial variation of C values that exists within a large land use area. We present a new approach to integrate remotely sensed C factors into SWAT for highlighting the effect of detailed vegetative cover data on soil erosion and sediment yield. First, the C factor was estimated using the abundance of ground components extracted from remote sensing images. Then, the gridding data of the C factor were aggregated to hydrological response units (HRUs), instead of to land use units of SWAT. In the end, the C factor values in HRUs were integrated into SWAT to predict sediment yield by modifying the ysed subroutine. This substitution work not only increases the spatial variation of the C factor in SWAT, but also makes it possible to utilize other sources of C databases rather than those from the United States. The demonstration in the Dage basin shows that the modified SWAT produces reasonable results in water flow simulation and sediment yield prediction using remotely sensed C values. The Nash–Sutcliffe efficiency coefficient (ENS) and R2 for surface runoff range from 0·69 to 0·77 and 0·73 to 0·87, respectively. The coefficients ENS and R2 for sediment yield were generally above 0·70 and 0·60, respectively. The soil erosion risk map based on sediment yield prediction at the HRU level illustrates instructive details on spatial distribution of soil loss. Copyright © 2011 John Wiley & Sons, Ltd. |
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| Keywords: | C factor remote sensing sediment yield SWAT Dage basin |
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