Mapping of soil erosion for soil and water conservation measures in Kolleru lake catchment area
DOI:
https://doi.org/10.53550/Keywords:
GIS, Kolleru lake, Soil erosion, Universal soil loss equationAbstract
Mapping of soil erosion assumes significance for land use planning and watershed management. Erosion can be predicted by integrating meteorological, topographical, field survey and satellite data in GIS environment. The spatial and temporal variation of soil erosion map has been generated for the Kolleru lake catchment. The areas under different classes of soil erosion risk have been worked out. The Kolleru lake catchment area is 6252 km2. The elevation of the catchment varies from 0 to 532 m. The catchment has been divided into subbasins based on the outlet points of drains and rivers (Budameru, Ramileru Tammileru and Gunderu) flowing into the Kolleru Lake. Majority of soils are sandy clay loam (45%) in texture. There are 12 types of land uses in the catchment with major area under agriculture. Soil erosion has been estimated for a period of 23 years (1990 to 2012). The quantitative potential soil loss through erosion in the catchment was estimated by universal soil loss equation with the relevant information on factors like erosivity (R), soil erodibility (K), topographic factor (LS), cover and land management factor (C) and conservation practice factor (P). The values of R, K, LS, C and P factors were used for generating maps of each factor. About 16% area is under the slight erosion (5 t ha-1yr-1). Moderate erosion (5-10 t ha-1yr-1) occurs in about 37% area. High and very high erosion occurs in 13% and 14% area, respectively. Severe erosion (>20 t ha-1yr-1) occurs in 20% area of the catchment. Based on severity of soil erosion, suitable sites for check dams and percolation tanks on 2nd/3rd order streams were identified using thematic maps of the catchment area.
References
Babatunde, J. Fagbohun, Adeleye, Y.B., Anifowose, Chris Odeyemi, Olabanji, O. Aladejana, Adegoke, Aladeboyeje, I. 2016. GISbased estimation of soil erosion rates and identification of critical areas in Anambra sub-basin, Nigeria, Model. Earth Syst. Environ., 2:159.
Balasubramani, K., Mohan, Veena, Kumaraswamy, K. and Saravanabavan, V. 2015. Estimation of soil erosion in a semiarid watershed of Tamil Nadu (India) using revised universal soil loss equation (RUSLE) model through GIS, Model. Earth Syst. Environ., 1:10.
Beasley, D.B., Huggins, L.F. and Monke, E.J. 1980. ANSWERS: A model for watershed planning. Trans. ASAE, 23(4): 938-944.
Dhruva Narayana, V.V. and Ram Babu, 1983. Estimation of soil erosion in India. J. Irrig. Drain. Eng. ASCE, 109(4): 419-433.
Mandal, D. and Sharda, V.N. 2011. Assessment of permissible soil loss in India employing a quantitative bio-physical model. Curr. Sci., 100(3): 383-390.
Mandal, D., Sharda, V. N. and Tripathi, K.P. 2010. Relative efficacy of two biophysical approaches to assess soil loss tolerance for Doon Valley soils of India. J. Soil Water Cons., 65: 42-49.
NBSS&LUP. 2015. Agro-Ecological regions of India (Rev. Ed.). NBSS Pub., 170: 2015. ISBN:978-81-89043-46-9.
Nearing, M.A., Foster, G.R., Lane, L.J. and Finkner, S.C. 1989. A process based soil erosion model for USDA-water Erosion Prediction Project technology. Trans. Am. Soc. Agri. Eng., 32: 1587-1593.
Pandey, A., Chowdary, V.M., Mal, B.C. and Dabral, P.P. 2011. Remote sensing and GIS for identification of suitable sites for soil and water conservation structures. Land Degrad. Dev., 22(3): 359-372.
Prasad, H.C., Parul Bhalla and Sarvesh Palria. 2014. Site suitability analysis water harvesting structures using Remote Sensing and GIS – A Case Study of Pisangan Watershed, Ajmer District, Rajasthan.The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL- 8. ISPRS Technical Commission VIII Symposium, 09-12 December 2014, Hyderabad, India, pp1471-1482.
Reddy G.P. Obi, Kurothe, R.S., Sena, D.R., Harindranath, C.S., Niranjana, K.V., Naidu, L.G.K., Singh, S.K., Sarkar, Dipak, Mishra, P.K., Sharda, V.N. 2016. Assessment of soil erosion in tropical ecosystem of Goa, India using Universal Soil Loss Equation, geostatistics and GIS. Indian J. Soil Cons., 44(1): 1-7.
Renard, K.G., Foster, G.R., Weesies, G.A. and Porter, J.P. 1991. RUSLE: Revised Universal Soil Loss Equation. J. Soil Water Cons., 46: 30-33.
Parveen, Reshma and Kumar, Uday. 2012. Integrated approach of Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) for Soil loss risk assessment in Upper South Koel Basin, Jharkhand. J. Geogra. Infor. Syst., (4): 588-596.
Sakthivel, R., Jawahar, Raj, N., Pugazhendi, V., Rajendran, S. and Alagappamoses, A., 2011. Remote Sensing and GIS for Soil
Erosion Prone areas Assessment: A case study from Kalrayan hills, Part of Eastern Ghats, Tamil Nadu India Arch. Appli. Sci. Res., 3(6): 369-376.
Saygin, S.D., Ozcan, A.U., Basaran, M., Timur, O.B., Dolarslan, M., Yilman, F.E. and Erpul, G. 2014. The combined RUSLE/SDR approach integrated with GIS and geostatistics to estimate annual sediment flux rates in the semi-arid catchment, Turkey.Environ. Earth Sci., 71: 1605-1618.
Sheikh, A.H., Palria, H. and Alam, A. 2011. Integration of GIS and Universal Soil Loss Equation (USLE) for Soil Loss estimation in a Himalayan Watershed. Recent Res. Sci. Tech., 3(3): 51-57.
Singh, G., Chandra, S. and Babue, R. 1981. Soil Loss and Prediction Research in India, Central Soil and Water Conservation Research Training Institute, Bull. No. T- 12/D9.
Singh, G., Ram Babu and Chandra, Subhash. 1981. Soil Loss Prediction Research in India. Central Soil & Water Conservation Research & Training Institute, Dehradun, Bull. No. T-12ID-9 70 p.
Vemu, S. and Pinnamaneni. 2012. Sediment yield estimation and prioritization of watershed using RS and GIS, Intenational archives of the photogrammetry, Remote Sens. Spat. Infor. Sci., doi: 10.5194/isprsarchives-XXXIX-B8-529-2012.
Vemu, S. and Pinnamaneni, U.B., 2011. Estimation of spatial patterns of soil erosion using remote sensing and GIS: A case study of Indravati catchment. Nat. Hazards, 59: 1299-1315.
Williams, J.R. 1975. Sediment routing for agricultural watersheds. Water Resour. Bull., 11: 965-974.
Wischmeier, W.H. and Smith, D.D. 1978. Predicting Rainfall Erosion Losses - A Guide to Conservation Planning, Agriculture Handbook No. 537, Agriculture Science and Education Administration, Washington, District of Colum, USA.
Woolhiser, D.A., Smith, R.E. and Goodrich, D.C. 1990. KINEROS – A kinematic runoff and erosion model: documentation and user manual. USDA-Agricultural Research Service, ARS-77: 130 p.
