Impact of C factor of USLE technique on the accuracy of soil erosion modeling in elevated mountainous area (case study: the Tibetan plateau)

• Published in: Environment, development and sustainability Vol. 23; no. 8; pp. 12615 - 12630
• Main Authors: Fan, Jihui, Motamedi, Artemis, Galoie, Majid
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2021; Springer Nature B.V
• Subjects: Accuracy; Annual rainfall; Case Study; Earth and Environmental Science; Ecology; Economic Geology; Economic Growth; Environment; Environmental Economics; Environmental Management; Fertility; Flood hazards; Fragments; Land cover; Mathematical models; Model accuracy; Mountain regions; Mountainous areas; Mountains; Normalized difference vegetative index; Numerical methods; Parameters; Rainfall; Rainfall-runoff relationships; Remote sensing; Rill erosion; Rock properties; Rocks; Runoff; Snow; Snow cover; Soil erosion; Soil types; Sustainable Development; Vegetation; Vegetation index; Tibetan Plateau; USLE; Mountainous area; Tibetan plateau; Soil erosion; factor; NDVI
• ISSN: 1387-585X; 1573-2975
• DOI: 10.1007/s10668-020-01133-x

The soil loss caused by rainfall-runoff process is a global issue which can decrease the lands fertility and increase the flood hazards. There are many different empirical relationships and numerical methods available for soil loss estimation. One of the most commonly used methods is the Universal Soil Loss Equation (USLE), which is widely used to estimate the amount of annual rill erosion. The main aim of this paper was to evaluate the accuracy and applicability of the USLE method in the estimation of soil loss in elevated and rocky mountainous areas of Tibetan plateau. To do this, some of the observed and modeled soil loss data that were available in some Chinese researches, were selected. Land slope, soil type, land cover, Normalized Difference Vegetation Index (NDVI), aspect, monthly and annual rainfall and runoff maps from GIS were derived and investigated to calculate the USLE parameters. The results showed that the accuracy of the USLE model was decreased significantly in regions with high soil loss risk due to ignoring the rock properties and snow cover in K parameter. Also, the results showed that parameters which can decrease the soil loss significantly such as rock fragments content and low height vegetation have to be considered in NDVI calculation. Hence, it is recommended to improve the accuracy of the model by adjusting C factor for elevated mountainous areas based on the rock properties and snow cover which can be derived from the remote sensing maps.