Effects of Different Methods for Calculation of Topographic Factor on Precision of Storm-Wise Soil Loss Estimation

Soil erosion reduces soil fertility, weakens vegetation, deposits sediments, deforms and fills rivers due to floods, and reduces water quality. Therefore, the precision of soil erosion estimation is essential for proper watershed management. Among all-soil erosion prediction models proposed for storm-scale, one of the most widely used is the Revised Universal Soil Loss Equation (RUSLE). Due to the importance of the LS factor in small watersheds with complex topography on the final estimation of the RUSLE model, in this current research, the soil erosion results were obtained from four different LS factor methods were investigated.

Soil erosion obtained by the RUSLE model and four methods of LS factor calculation including the Moore et al. (1991), Desmet and Govers (1996), Boehner and Selige (2006), and manual method; for 38 storm events recorded during 2011 to 2019 for the Galazchai Watershed, West Azerbaijan Province, Iran.

The results showed that the mean of the topographic factor for Moore et al. (1991), Desmet and Govers (1996), Boehner and Selige (2006), and manual methods were 9.91, 5.26, 13.29, and 6.54, respectively. Comparison analysis of the methods used by the manual method showed that the ratio of the estimated mean values varied from 0.80 to 2.03. Comparing the mean of LS maps with the manual method as the basic method and calculating error estimation found that Desmet and Govers' (1996) method was more successful in the LS factor estimation, resulting in better estimation of soil erosion for the study storm events. Despite the difference in soil erosion values, almost the same spatial pattern was observed in all methods.

Analysis of the results obtained from different LS factor methods in the Galazchai Watershed verified the significant effect of the studied methods on the estimated soil erosion. Therefore, soil erosion studies need to select an appropriate method to achieve precise soil erosion to prevent errors and minimize uncertainties. Incorrect estimation of soil erosion leads to erroneous management of watersheds and loss of money and energy. The present study is new in term of comparative evaluation of one of the sensetive factors in USLE and its different versions on the estimated storm-wise soil loss at the watershed scale. It is also innovative in viewpoint of focusing on the necessity of selection of appropriate computational methods for the local managers and experts. Extensive studies are recommended to investigate other methods of calculating LS, and even other RUSLE factors at different scales are recommended for a better conclusion.