Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology

Abstract

A comprehensive methodology that integrates Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) techniques was adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala, India. The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method. GIS data layers including, rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed to determine their effects on average annual soil loss in the area. The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h -1 y -1 with a close relation to grass land areas, degraded forests and deciduous forests on the steep side-slopes (with high LS ). The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas. ª 2011, China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. All rights reserved.

Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan

“…Many accurate soil erosion models were developed over the last four decades to assess soil erosion risk at different levels: single slope, river/wadi catchment, regional and global scales [29,30]. Among these, the Univeral Soil Loss Equation (USLE) [31,32], European Soil Erosion Model (EUROSEM) [33], Soil Erosion Model for the Mediterranean Region (SEMMED) [34], Water Erosion Prediction Model (WEPP) [35,36], the Soil and Water Assessment Tool (SWAT) [37], and the Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) [38].…”

“…Information on factors leading to soil erosion can be utilized as a guide for formulating appropriate soil conservation and land management plans. The Revised Universal Soil Loss Equation (RUSLE) is frequently used to estimate the magnitude of soil erosion loss from watershed areas, the spatial distribution of soil erosion severity, and delimiting sites vulnerable to soil erosion for both agricultural and forested watersheds [30,[42][43][44][45][46][47][48]. Finally, the RUSLE model has several advantages: 1) it is easy to implement and understand from a functional perspective [32], 2) is compatible with the Geographic Information System (GIS), and 3) the data requirements to implement the model are not too complex or unattainable especially in a developing country [49].…”

“…In the present study, grid cells of 30 m × 30 m size were determined before making the computation of the physical characteristics of these cells such as: slope, land use, and soil type all of which affect soil erosion processes in different cells of the watershed. Such a procedure is essential to create a uniform spatial analysis environment for GIS modeling [30,42].…”

Soil erosion risk mapping using RUSLE model on jhargram sub-division at West Bengal in India

“…Soil erosion by water has been an important global issue and major challenge for human sustainability in last decades (Prasannakumar et al 2012). The importance of soil erosion is enhanced because of its adverse impact on agricultural production, water quality, hydrological systems and infrastructure due to both on-site and off-site damages (Pimentel 2006).…”

“…Spatial and quantitative information on soil erosion prediction and assessment has been a challenge to researchers since the 1930s (Prasannakumar et al 2012). The methods of quantifying soil loss based on erosion plots possess many limitations in terms of cost, representativeness and reliability of the resulting data.…”