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.

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Siruvani watershed with a surface area of 205.54 km 2 (20,554 hectare), forming a part of the Western Ghats in Attapady valley, Kerala, was chosen for testing RUSLE methodology in conjunction with remote sensing and GIS for soil loss prediction and identifying areas with high erosion potential. The RUSLE factors (R, K, LS, C and P) were computed from local rainfall, topographic, soil classification and remote sensing data. This study proved that the integration of soil erosion models with GIS and remote sensing is a simple and effective tool for mapping and quantifying areas and rates of soil erosion for the development of better soil conservation plans. The resultant map of annual soil erosion shows a maximum soil loss of 14.917 t h -1 year -1 and the computations suggest that about only 5.76% (1,184 hectares) of the area comes under the severe soil erosion zone followed by the higherosion zone (11.50% of the total area). The dominant high soil erosion areas are located in the central and southern portion of the watershed and it is attributed to the shifting cultivation, and forest degradation along with the combined effect of K, LS and C factor. The RUSLE model in combination with GIS and remote sensing techniques also enables the assessment of pixel based soil erosion rate.

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