Comparative Analysis of Topographic Factor (LS Factor) Estimation Methods for Soil Erosion Risk Assessment in the Netravati Watershed, India
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Date
2024
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Springer Science and Business Media Deutschland GmbH
Abstract
Soil erosion models are crucial for soil conservation planning and environmental assessments globally. The Universal Soil Loss Equation (USLE)-based models are most popular empirical models for estimating soil erosion. The topographic factor (LS factor), which combines slope length and slope steepness, significantly affects soil loss among the input parameters. This study aimed to estimate the LS factor for the Netravati watershed in Karnataka, India, which has a high elevation variation (0–1719 m) and diverse terrain, posing soil erosion and local landslide risks that require conservation planning. Three different methods were employed for dimensionless LS factor estimation: Wischmeier and Smith equation (Method I), Moore and Burch equation (Method II), and Desmet and Govers equation (Method III) along with Geographic Information System (GIS) techniques and a high-resolution (12.5 m) ALOS-PALSAR Digital Elevation Model (DEM). The LS factor values ranged from 0.06 to 1549.39 for Method I, 0 to 191.72 for Method II, and 0.03 to 149.09 for Method III. The results showed that Method III produced values that were evenly distributed throughout the spatial domain, with a mean value of 3.31 and a standard deviation of 4.87. Method I generated very high LS factor values along the flow path and almost uniform values for the rest of the study area. The mean LS factor values for Method I and Method II were 8.31 and 7.41, respectively, with standard deviations of 18.74 and 9.88. The findings of this research suggest that Method III is preferable approach for estimating LS factor values in a spatial domain due to its even distribution of values and low standard deviation. This study demonstrates that estimating the LS factor is impacted by the availability and accuracy of topographic data and the technique used. The findings can be used to support sustainable land management practices in the study area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
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Keywords
ALOS-PALSAR DEM, Geoinformatics, LS factor, Soil erosion, USLE
Citation
Lecture Notes in Civil Engineering, 2024, Vol.529 LNCE, , p. 779-788
