Estimation of Soil Erosion and Identification of Critical Areas for Soil Conservation Measures using RS and GIS-based Universal Soil Loss Equation

Present study aimed at estimating soil erosion potential and identification of critical areas for soil conservation measures in an ungauged catchment situated in Aravalli hills of Udaipur district, Rajasthan (India). Also, impact of rainfall on soil erosion is evaluated. The soil erosion is estimated for 10 year period (2001–2010) by Universal Soil Loss Equation (USLE) model using Geographical information system (GIS) and remote sensing techniques for every 12 m × 12 m area. Thematic maps of six USLE model parameters, i.e., rainfall erosivity (R-factor), soil erodibility (K-factor), slope length (L-factor), slope steepness (S-factor), crop and management (C-factor), and support practice (P-factor), were prepared in GIS platform. The R-factor ranged from 1,522.93 to 10,225.88 MJ mm ha−1 h−1 year−1 in the years 2006 and 2008, respectively, when the annual rainfall was 984.3 and 572.2 mm, and number of rainy days were 58 and 47, respectively. The K-factor was highest for fine loam soil covering 56 % area, while the lowest value was for coarse loamy sand in 22 % area. The lowest value of the L-factor (0.736) was in accordance with the high slopes nearby catchment boundary; whereas the highest value (0.832) was for almost zero slopes in 34 % area nearby waterbodies. Opposite to the L-factor, the S-factor values were high (>4) for the higher slopes nearby catchment boundary and the lowest values for the zero slopes. The C-factor value in 170.36 km2 or 48.91 % of the area is 0.1 while the value is zero for waterbodies and builtup lands. The P-factor value in 250.36 km2 or 71.87 % of the area is 0.8. The mean annual soil erosion in the major portion of the catchment (231.13 km2 or 66.38 %) exceeds 10 t ha−1 year−1 indicating high to very severe soil erosion conditions prevailing in the catchment. It is apparent that vast quantities of the soil are getting eroded from the catchment, and the annual rainfall amount and rainfall intensity have the profound effect on the soil erosion potential. This study emphasizes that USLE model coupled with GIS and remote sensing techniques are promising and cost-effective tools for mapping critical areas of soil erosion in ungauged catchments especially in developing countries. © 2015, NAAS (National Academy of Agricultural Sciences).