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Adapting the WEPP Hillslope Model and the TLS Technology to Predict Unpaved Road Soil Erosion

Author

Listed:
  • Yi Wang

    (Key Laboratory of Ministry of Education on Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China)

  • Wei He

    (Institute of Geography and Resources Science, Sichuan Normal University, Chengdu 610101, China)

  • Ting Zhang

    (College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China)

  • Yani Zhang

    (College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China)

  • Longxi Cao

    (College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China)

Abstract

Unpaved road erosion have been recognized as important sediment sources in a watershed. To evaluate where and when road erosion occurs, the soil loss along road segments should be precisely predicted with process-based erosion models. Methods: The hillslope version of the Water Erosion Prediction Project (WEPP) was used 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, soil loss would be underestimated for long or steep road segments. Detailed outputs along roads revealed that most of the peak soil loss rates were underestimated. It might due to the linear critical shear stress theory in the WEPP model. Additionally, the lack of upstream flow was found to be connected to the relatively low model efficiency. Nevertheless, the WEPP simulation could accurately fit erosion trend and predict the peak soil loss positions along road segments. Conclusions: The WEPP model could be adopted to evaluate the erosion risk of unpaved roads in the red soil region of South China.

Suggested Citation

  • Yi Wang & Wei He & Ting Zhang & Yani Zhang & Longxi Cao, 2022. "Adapting the WEPP Hillslope Model and the TLS Technology to Predict Unpaved Road Soil Erosion," IJERPH, MDPI, vol. 19(15), pages 1-15, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9213-:d:873783
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    References listed on IDEAS

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    1. Revuelta-Acosta, J.D. & Flanagan, D.C. & Engel, B.A. & King, K.W., 2021. "Improvement of the Water Erosion Prediction Project (WEPP) model for quantifying field scale subsurface drainage discharge," Agricultural Water Management, Elsevier, vol. 244(C).
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    Cited by:

    1. Chao Liu & Han Li & Jiuzhe Xu & Weijun Gao & Xiang Shen & Sheng Miao, 2023. "Applying Convolutional Neural Network to Predict Soil Erosion: A Case Study of Coastal Areas," IJERPH, MDPI, vol. 20(3), pages 1-21, January.

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