Estimation of soil erosion vulnerability in Perambalur Taluk, Tamilnadu using revised universal soil loss equation model (RUSLE) and geo information technology
- 1Centre for Remote Sensing Bharathidasan University, Tiruchirappalli, Tamilnadu, India
- 2Centre for Remote Sensing Bharathidasan University, Tiruchirappalli, Tamilnadu, India
- 3Centre for Remote Sensing Bharathidasan University, Tiruchirappalli, Tamilnadu, India
Int. Res. J. Earth Sci., Volume 5, Issue (8), Pages 8-14, September,25 (2017)
Soil loss is a universal land degradation problem arises from agricultural intensification, land degradation as its economic use, environmental impacts in addition to other anthropogenic activities. A widespread method of RUSEL and Geo information techniques used to make a decision of the soil erosion vulnerability of the study area. The spatial analysis of the annual soil erosion rate was obtained through the integrating of good environmental variables in a GIS based raster method. The present study was five major factors were used are R, K, LS, C and P factors were computed to decide their effect on average annual soil loss. The soil erosion map is reclassified according to the sing et. al. Soil erosion risk classes for Indian condition such as Low (>5), Moderate (5-10), High (10-20), Very high (20-40), Sever (40-80). The study area 68.95 % has low erosion risk and 16.80% moderate erosion risk of the total area. The other erosion risk classes such as high, very high and sever erosion range occurred in the percentage of 7.48 %, 4.52% and 2.26 % of the total area respectively. The resulting of the annual soil erosion map shows a maximum soil loss of 52.25 ton/ha/year, and the mean annual soil loss for the entire study area about 0.16 ton/ha/year. Its consequently the close relation to forests on the steep side slopes along with slope gradient and length followed by soil erodability factor were found to be the main factor of soil erosion.
- Fistikoglu O. and Harmancioglu N.B. (2002)., Integration of GIS with USLE in assessment of soil erosion., Water Resources management, 16(6), 447-467.
- Hoyos N. (2005)., Spatial modeling of soil erosion potential in a tropical watershed of the Colombian Andes., CATENA, 63(1), 85-108.
- Pandey A., Mathur A., Mishra S.K. and Mal B.C. (2009)., Soil erosion modeling of a Himalayan watershed using RS and GIS., Environmental Earth Sciences, 59(2), 399-410.
- Narayana D. and Babu R. (1983)., Closure to Estimation of soil erosion in India., Journal of Irrigation Drain Eng, 109(4), 408-410.
- Singh G., Babu R., Narain P., Bhusan L.S and Ab-rol I.P. (1992)., Soil Erosion Rates in India., Journal of Soil and Water Conservation, 47(1), 97-99.
- Pandey A., Chowdary V.M. and Mal B.C. (2007)., Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing., Water Resource Management, 21(4), 729-746.
- Angima S.D., Stott D.E., O,Neill M.K., Ong C.K. and Weesies G.A. (2003)., Soil erosion prediction using RUSLE for central Kenyan highland conditions., Agriculture Ecosystems and Environment, 97(1-3), 259-308.
- Ganasri B.P and Ramesh H. (2016)., Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin., Geoscience Frontiers, 7(6), 953-961.
- Millward A.A. and Mersey J.E. (1999)., Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed., CATENA, 38(2), 109-129.
- Jasrotia A.S. and Singh R. (2006)., Modeling runoff and soil erosion in a catchment area, using the GIS, in the Himalayan region, India., Environmental Geology, 51, 29-37.
- Sharma A. (2010)., Integrating terrain and vegetation indices for identifying potential soil erosion risk area., Geo-Spatial Information Sciences, 13(3), 201-209.
- Jain S.K., Kumar S. and Varghese J. (2001)., Estimation of soil erosion for a Himalayan watershed using GIS technique., Water Resource Management, 15, 41-54.
- Kouli M., Soupios P. and Vallianatos F. (2009)., Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece., Environmental Geology, 57(3), 483-497.
- Williams J.R. (1975)., Sediment routing for agricultural watersheds., Water Res Bull, 11(5), 965-974.
- Wischmeier W.H. and Smith D.D. (1978)., Predicting Rainfall Erosion Losses - A Guide to Conservation Planning., Agriculture Handbook No.537.US Dept of Agriculture Science and Education Administation, Washington, D.C, USA. 163.
- Renard K.G., Foster G.R., Weesies G.A., Mccool D.K. and Yoder D.C. (1997)., Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE)., Agriculture Handbook, 703, US Department of Agriculture, Washington, DC. 1-251.
- Sing (1981)., Soil Loss and Pre-diction Research in India., Bulletin No.T-12/D9, Central Soil and Water Conservation Research Training Institute, Dehradun.
- Beskow S., Mello C.R., Norton L.D., Cur N., Viola M.N and Avanazi J.C. (2009)., Soil erosion prediction in the Grande River Basin, Brazil using distributed modeling., Catena, 79, 49-59.
- Risse L.M., Nearing M.A., Nicks A.D. and Laflen J.M. (1993)., Error assessment in the Universal Soil Loss Equation., Soil Science Society of American Journal, 57(3), 825-833.DOI:10.2136/sssaj1993.03615995005700030032x.
- Lu D., Li G., Valladares G.S. and Batistella M. (2004)., Mapping soil erosion risk in Rondonia, Brazilian Amazonia: using RUSLE, remote sensing and GIS., Land Degradation and Development, 15, 499-512.
- Krishna bahadur K.C. (2009)., Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Watershed, Nan Province, Thailand., Environmental Geology, 57, 695-705.
- Balasubramani K., Veena M., Kumaraswamy K. and Saravanabavan V. (2015)., Estimation of soil erosion in a semi-arid watershed of Tamil Nadu (India) using revised universal soil loss equation (rusle) model through GIS., Model Earth System Environment, 1(3), 1-17.
- Moore D. and Wilson J.P. (1992)., Length Slope Factor for the Revised Universal Soil Loss Equation: Simplified Method of Solution., Journal of Soil and Water Conservation, 47(5), 423-428.
- Singh R. and Phadke V.S. (2006)., Assessing soil loss by water erosion in Jamni River Basin, Bundelkhand region, India, adopting universal soil loss equation using GIS., Current Science, 90(10), 1431-1435.
- Wischmeier W.H. and Smith D.D. (1965)., Predicting rainfall erosion losses from Cropland East of the Rocky Mountains., Handbook no 282, United States Department of Agriculture, Washington DC.
- Wischmeier W.H. (1975)., Estimating the soil loss equations cover and a management factor for undisturbed lands., Present and Prospective Technology for Predicting Sediment Yields and Sources. ARS-S-40, Agr.Res. Scrv, U.S. Dept .of Agr., Washington, D.C, 118-125.
- Dabral P.P., Baithuri N. and Pandey A. (2008)., Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing., Water Resource Management, 22(12), 1783-1798.
- Ranzi R., Le T.H. and Rulli M.C. (2012)., A RUSLE approach to model suspended sediment load in the Lo River (Vietnam): effects of reservoirs and land use changes., Journal of Hydrology, 422, 17-29. DOI:10.1016/ j.jhydrology.2011.12.2009.
- Devathaa C.P., Deshpande Vaibhav and Renukaprasad M.S. (2015)., Estimation of Soil loss using USLE model for Kulhan Watershed, Chattisgarh- A case study., Aquatic Procedia, 4, 1429-1436.
- Srinivas C.V., Maji A.K., Reddy G.P.O. and Chary G.R. (2002)., Assessment of soil erosion using remote sensing and GIS in Nagpur district, Maharashtra for prioritization and delineation of conservation units., Journal Indian Society of Remote Sensing, 30(4), 197-212.
- Singh R.K., Aggarwal S.P., Turdukulov U. and Prasad V.H. (2002)., Prioritization of Bata river basin using RS and GIS techniques., Indian Journal of Soil Conservation, 30(3), 200-205.