89 Estimation of Soil Loss Under Changing Climatic Scenarios in Semi-Arid Watersheds K.V. Rao, R. Rejani*, P. Yogitha, M. Osman, G.R. Chary, K. Sammi Reddy and Ch. Srinivasa Rao ICAR-Central Research Institute for Dryland Agriculture, Hyderabad-500 059, Telangana Email: rrejani10@gmail.com ABSTRACT: Spatial and temporal estimation of soil loss is very essential for the sustainable planning and management of watersheds. In the present study, an attempt was made to estimate the soil loss spatially and temporally using RUSLE from a dry semi-arid watershed (Goparajpalli in Warangal District) and a wet semi-arid watershed (Seethagondi in Adilabad District) under changing climatic scenarios using PRECIS data. In the dry semi-arid watershed, the annual rainfall varied from 390 to 1181 mm with a mean value of 735 mm and a mean erosivity of 6260 MJ mm/ha/h/y. The mean annual rainfall during the base line period (1961-1990), mid (2021-2050) and end centuries (2071-2098) in this watershed were 738, 835 and 777 mm, respectively. The mean erosivity during these periods were 5657, 9253 and 7170 MJ mm/ha/h/y and soil loss from crop land were 2.39, 4.02 and 3.14 t/ha/y, respectively. In the wet semi-arid watershed, the annual rainfall varied from 508 to 1351 mm with a mean value of 950 mm and a mean erosivity of 6789 MJ mm/ha/h/y. The mean annual rainfall during base line, mid and end centuries in this wet semi-arid watershed were 956,1088 and 1124 mm and erosivities were 10547,14437 and 14755 MJ mm/ha/h/y, respectively. Similarly, the soil loss from crop land during these periods were 9.18, 13.11 and 14.11 t/ha/y. Even though, the soil loss from the dry semi-arid watershed was relatively lower than the wet semi-arid watershed, it showed an increasing trend in the mid century and a decreasing trend in the end century whereas, in the wet semi-arid watershed, it showed an increasing trend in both mid and end centuries. Considerable spatial variation in the mean annual soil loss was observed in both the wet and dry semi-arid watersheds during base line period, mid and end centuries. Key words: Climate change, GIS, RUSLE, semi-arid watershed and soil loss Introduction Soil erosion results in 85% of the land degradation in the world and causing 17% reduction in crop productivity (Vaezi et al., 2010). Land degradation resulting from soil erosion from water is a serious problem in India which results in many economic problems. In India, 53% of total geographical area suffers from soil erosion with an average rate of 16 t/ha/y (Pandey et al., 2009; Prasannakumar et al., 2011). The intensive cultivation and socio-economic pressure for more land for feeding the increasing population have accelerated the rate of soil erosion on sloping lands (Shi et al., 2004). The soil erosion removes the fertile top soil and organic matter from the soil surface which in turn affect the soil fertility and the reduction of crop yields (Ismail and Ravichandran, 2008). In semi-arid countries like India, the decline in soil fertility brings a series of negative impacts of environmental problems, and has become a threat to sustainable agricultural production and water quality in this region (Prasanna kumar et al., 2012). The spatial estimation of runoff and soil loss are essential for evaluating the risk of sediment transport and sustainable planning of in-situ and ex-situ soil and water conservation interventions for management of watersheds (Rejani et al., 2016a; Rejani et al., 2015a). The estimation of soil loss in sub watersheds were carried out using different prediction techniques (Shrestha, 1997; Dougals, 2006; Van De et al., 2008). Watershed forms a natural boundary to focus on runoff, and hence a systematic assessment of runoff and soil erosion within the watershed would provide reliable information to draw strategies for sustainable development of watershed resources (Balasubramani et al., 2015). The major models applied worldwide to estimate soil loss are Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), Water Erosion Prediction Project (WEPP), Soil Erosion Model for Mediterranean Regions (SEMMED), Soil and Water Assessment tool (SWAT), European Soil Erosion Model (EUROSEM), Agricultural Non- Point Source Pollution Model (AGNPS) etc. Among these, USLE and RUSLE are widely used to predict long term average annual soil loss using rainfall, soil type, topography, crop systems and management practices. RUSLE helps to predict the soil erosion from unguaged watersheds at reasonable cost and better accuracy by considering the hydro climatic conditions and spatial heterogeneity of the soil (Angima et al., 2003). The RUSLE has been widely adopted for soil loss estimation at watershed scale because of its convenience in computation and application (Balasubramani et al., 2015). The impacts of climate change are global, but countries like India are more vulnerable in view of the high population depending on agriculture. The changes in the intensity of rainfall and prolonged dry spells attributes to the climate change effects in Indian agriculture (Srinivasarao et al., 2014). In India, the surface temperature is predicted to increase by 2 to 40 o C (Ranuzzi and Srivastava, 2012). Also, changes in the distribution and frequency of rainfall, decrease in the number of rainy days, increase in rainfall intensities and intensity of cyclonic storms are also projected by 2030. The soil erosion rates may be expected to change in response to changes in the erosive power of rainfall (Nearing, 2001; Nearing et al., 2004) and changes in plant biomass. The prediction of future soil erosion can help in the management of valuable cropland by suggesting the need for changing soil conservation strategies (Neal et al., 2005). The objective of the study is to estimate the impact of climate change on soil erosion rates in a dry semi-arid watershed and wet semi -arid watershed for its sustainable planning and management. Indian J. Dryland Agric. Res. & Dev. 2016 31(1) : 89-95 DOI 10.5958/2231-6701.2016.00015.4