Articles | Volume 19, issue 4
https://doi.org/10.5194/nhess-19-757-2019
https://doi.org/10.5194/nhess-19-757-2019
Research article
 | 
12 Apr 2019
Research article |  | 12 Apr 2019

Dangerous degree forecast of soil loss on highway slopes in mountainous areas of the Yunnan–Guizhou Plateau (China) using the Revised Universal Soil Loss Equation

Yue Li, Shi Qi, Bin Liang, Junming Ma, Baihan Cheng, Cong Ma, Yidan Qiu, and Qinyan Chen

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Cited articles

Alexakis, D., Diofantos, G., and Hadjimitsis, A.: Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus, Atmos. Res., 131, 108–124, 2013. 
Alkharabsheh, M. M., Alexandridis, T. K., Bilasb, G., and Misopolinos, N.: Impact of land cover change on soil erosion hazard in northern Jordan using remote sensing and GIS, Four decades of progress in monitoring and modeling of processes in the soil-plant-atmosphere system: applications and challenges, Procedia Environ. Sci., 19, 912–921, 2013. 
Angulo-Martínez, M. and Beguería, S.: Estimating rainfall erosivity from daily precipitation records: a comparison among methods using data from the ebro basin (NE spain), J. Hydrol., 379, 111–121, 2009. 
Bakr, N., Weindorf, D. C., Zhu, Y. D., Arceneaux, A. E., and Selim, H. M.: Evaluation of compost/mulch as highway embankment erosion control in louisiana at the plotscale, J. Hydrol., 468, 257–267, 2012. 
Bosco, C., de Rigo, D., Dewitte, O., Poesen, J., and Panagos, P.: Modelling soil erosion at European scale: towards harmonization and reproducibility, Nat. Hazards Earth Syst. Sci., 15, 225–245, https://doi.org/10.5194/nhess-15-225-2015, 2015. 
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Short summary
This study fully considers the characteristics of expressways in mountain areas. The catchment area is considered a prediction unit. The method of slope division is improved, and a method of improving the parameters in the model is proposed. Comparison and analysis with actual observation data show that the method of soil and water loss prediction adopted in this paper has less error and higher prediction accuracy than other models and can satisfy prediction requirements.
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