Faculty Publications
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Item Comparative Analysis of Topographic Factor (LS Factor) Estimation Methods for Soil Erosion Risk Assessment in the Netravati Watershed, India(Springer Science and Business Media Deutschland GmbH, 2024) Makhdumi, W.; Shwetha, H.R.; Dwarakish, G.S.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.Item Soil erosion in diverse agroecological regions of India: a comprehensive review of USLE-based modelling(Springer Science and Business Media Deutschland GmbH, 2023) Makhdumi, W.; Shwetha, H.R.; Dwarakish, G.S.Soil erosion caused by water refers to the removal of topsoil by rainfall and runoff. Proper selection of an assessment method is crucial for quantifying the spatial variance of soil erosion. The Universal Soil Loss Equation (USLE) and its revised version (RUSLE) are widely used for modelling soil erosion. This study aimed to evaluate the effectiveness of the USLE-based soil erosion modelling in different agroecological regions of India, identify potential issues, and provide suggestions for future applications. The review revealed that little attention has been given to estimate soil erosion in high-priority land degradation regions of India. Additionally, many studies failed to thoroughly verify the authenticity of stated soil loss rates in their research regions either by overestimating or underestimating at least one of the five soil loss parameters. Furthermore, flaws in the application of methods to calculate these parameters leading to erroneous values were identified and suggestions for improvement were made. The USLE-based soil erosion modelling is an effective tool for quantifying soil erosion risk, but researchers should put emphasis on thoroughly verifying the methodologies adopted, unit conversions, and data availability for the estimation of soil loss parameters to improve the accuracy of their final results. This paper provides valuable insights to assist researchers in implementing USLE-based erosion models in diverse agroecological regions in India and elsewhere. However, for effective soil conservation and sustainable agriculture, further research is necessary to develop efficient techniques for using USLE-based soil erosion modelling to achieve a comprehensive understanding of erosion risk across different agroecological regions. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.