Soil Erosion Estimation of Palasbari in Northeast India by RUSLE Model
DOI:
https://doi.org/10.48165/Keywords:
Soil erosion, RUSLE, Remote sensing, GIS, PalasbariAbstract
Soil erosion is a serious problem and its estimation at a large scale is an urgent need. This study aims to estimate the annual soil loss in Palasbari town (639 km2) applying the Revised Universal Soil Loss Equation (RUSLE) model on a GIS platform. The study area comprising Palasbari town is located in the state of Assam in Northeast India. The annual soil loss rate varies from 0 to 3779t ha-1 yr-1 and the mean annual rate of soil loss is 42 t ha-1 yr-1. The soil loss values are categorised into four classes of severity i.e. slight, moderate, severe and extreme soil erosion. Based on spatial analysis, it is found that areas with high slope length and steep slope with heavy and high intensity precipitation are more prone to soil erosion. It is concluded that steep slopes, frequent flooding, sandy soil, destruction of vegetation cover are the main causes of soil erosion in the study area.
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Babu, R., Dhyani, B.L. and Kumar, N., (2004). Assessment of erodibility status and refined iso-erodent map of India. Indian Journal of Soil Conservation, 32(3), 171-177
Borrelli, P., Alewell, C., Alvarez, P., Anache, J. A. A., Baartman, J., Ballabio, C., et al., (2021). Soil erosion modelling: A global review and statistical analysis. Science of the Total Environment, 780, 146494.
https://doi.org/10.1016/j.scitotenv.2021.1 46494.
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 Resources Management, 22, 1783–1798. https://doi.org/10.1007/s11269-008-9253-
FAO and ITPS (2015) Status of the world’s soil resources (SWSR) – main report. Food and agriculture Organization of the United Nations and Intergovernmental Technical Panel on soils, Rome, Italy. Available online: http://www.fao.org/3/a-i5199e.pdf
Jahn, R., Blume, H. P., Asio, V. B., Spaargaren, O. and Schad P., (2006). Guidelines for soil description, 4th edition. Food and Agriculture Organization of the United Nations, Rome, pp. 67-71. Available online: http://www.fao.org/docrep/019/a0541e
/a0541e.pdf
Jain, S. K., Kumar, S. and Varghese, J., (2001). Estimation of soil erosion for a Himalayan watershed using GIS technique. Water Resources Management, 15: 41–54.
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. https://doi.org/10.1007/s00254-006-0301-
Merritt, W.S., Letcher, R.A. and Jakeman, A.J., (2003). A review of erosion and sediment transport models. Environmental Modelling & Software, 18 (8–9), 761–799. https://doi.org/10.1016/S1364-
(03)00078-1
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. https://doi.org/10.1016/S0341-
(99)00067-3
Moore, I. D. and Wilson, J. P., (1992). Length-slope factors for the Revised Universal Soil Loss Equation: simplified method of estimation. Journal of Soil and Water Conservation, 47(5), 423–428.
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, 399–410. https://doi.org/10.1007/s12665-009-0038- 0
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 N.703,
U.S. Department of Agriculture Research Service, Washington, DC, USA. 348 pp. 13. Shin, G. J., (1999). The analysis of soil erosion analysis in a watershed using GIS. Ph.D. Dissertation. Department of Civil Engineering, Gang-won National University.
Shivhare, N., Dikshit, P. K. S. and Dwivedi, S. B., (2018). A Comparison of SWAT Model calibration techniques for hydrological modeling in the Ganga river watershed. Engineering, 4(5), 643-652. https://doi.org/10.1016/j.eng.2018.08.012
Sulistyo, B., (2016). The effect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling. IOP Conf. Series: Earth and Environmental Science, 47, 012030. https://doi.org/:10.1088/1755-
/47/1/012030
Williams, J. R., (1995). The EPIC model. In: Computer Models of Watershed Hydrology, Singh, V. P. (Ed.). Highlands Ranch, Colorado: Water Resources Publications, pp: 909-1000.
Wischmeier, W. H. and Smith, D. D., (1978). Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. Agriculture Handbook, n. 537, Agriculture Research Service, US Department of Agriculture, Washington, DC, USA. 58 pp.
Zhou, Q., Yang, S., Zhao, C., Cai, M. and Ya, L., (2014). A soil erosion assessment of the upper Mekong River in Yunnan province, China. Mountain Research and Development, 34(1), 36-47. https://doi.org/10.1659/MRD
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