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Adapting the WEPP hillslope model to predict unpaved road soil erosion in southern China
  • Longxi Cao,
  • Ting Zhang,
  • Yi Wang
Longxi Cao
Chengdu University of Technology
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Ting Zhang
Chengdu University of Technology
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Yi Wang
Sichuan Normal University
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Abstract

Process-based erosion models are efficient tools that can be used to predict where and when erosion occurs. On unpaved roads that have been recognized as important sediment sources, soil loss along road segments should be precisely predicted. This study was performed using the hillslope version of the Water Erosion Prediction Project (WEPP) to estimate soil loss from 20 typical road segments in the red soil region of South China. Terrestrial laser scanning (TLS)-measured soil losses were used to validate the model simulations. The results showed that the WEPP model could reasonably predict the total soil loss in relatively short (less than 100 m) and gentle (slope gradient lower than 10%) road segments. In contrast, the WEPP-simulated soil loss was underestimated for long or steep road segments. Detailed outputs along roads revealed that most of the peak soil loss rates could not be adequately calculated. The linear critical shear stress and the sediment equilibrium theory in the WEPP model for soil detachment simulation might be responsible for the underestimation. Additionally, the lack of upslope flow and the curved road tortuosity were found to be connected to the relatively low efficiency of the model outputs. Nevertheless, the WEPP simulation could accurately fit the trend of soil loss variation along road segments despite underestimation. Furthermore, the simulated results could provide a reliable prediction of the maximum soil loss positions. Therefore, the WEPP model could be adopted to evaluate the erosion risk of unpaved roads in the red soil region of South China.

Peer review status:UNDER REVIEW

30 Jul 2021Submitted to Hydrological Processes
03 Aug 2021Assigned to Editor
03 Aug 2021Submission Checks Completed
04 Aug 2021Reviewer(s) Assigned