Application of Revised Universal Soil Loss Equation (RUSLE) model for the estimation of soil erosion and prioritization of erosion-prone areas in Majuli Island, Assam, India
Article Main
Abstract
Soil erosion is a serious issue, causing loss of agricultural productivity, increase in sediment deposit in the riverbeds, and damage to the ecological balance of the affected areas. Proper assessment of the soil erosion rate is essential for managing natural resources. The present study employs a GIS-based RUSLE (Revised Universal Soil Loss Equation) model to estimate annual soil loss in Majuli River Island of Assam, India. Annual average rainfall, soil properties, topographic characteristics, and LULC were taken as inputs to identify the soil erosion susceptible areas. The result revealed that annual soil loss of the study area ranges between 0 to 711 t ha−1 yr−1, with a mean annual soil loss of 23.02 t ha−1 yr−1. The entire region was classified into six soil loss severity classes, around 90 % of the area was found to be very slightly affected (< 5 t ha−1 yr−1) by soil erosion, around 5 % slightly affected (5 – 10 t ha−1 yr−1), roughly 3% moderately affected (10 – 20 t ha−1 yr−1), around 1% moderate high (20 – 40 t ha−1 yr−1), nearly 0.3 % area affected severely (40 -80 t ha−1 yr−1) and very severely affected areas (> 80 t ha−1 yr−1) contributes 0.1 %. A total of six priority levels of conservation were demarcated village-wise; priority level I requires immediate attention, and so on. The research outcome can help effectively implement conservation and management practices to check soil erosion in the study area.
Article Details
Article Details
Keywords
Geographical Information System (GIS), , Majuli Island, Remote Sensing, Revised Universal Soil Loss Equation (RUSLE) , Soil Erosion
References
Ayalew, D. A., Deumlich, D., Šarapatka, B. & Doktor, D. (2020). Quantifying the sensitivity of NDVI-based C factor estimation and potential soil erosion prediction using Spaceborne earth observation data. Remote Sensing. 12 (7), 1136. doi.org/10.3390/rs12071136
Barman, B. K., Rao, K. S., Sonowal, K., Prasad, N. S. R. & Sahoo, U. K. (2020). Soil erosion assessment using revised universal soil loss equation model and geo-spatial technology: A case study of upper Tuirial river basin, Mizoram, India. AIMS Geosciences, 6(4), 525-545. https://doi.org/10.3934/geosci.2020030
Batjes, N. H., Ribeiro, E. & van Oostrum, A. (2020).Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019). Earth Syst. Sci. Data, 12, 299–320. doi.org/10.5194/essd-12-299-2020
Benkobi, L., Trlica, M. & Smith, J. (1994). Evaluation of a redefined surface cover sub-factor for use in RUSLE. Journal of Range Management, 47, 74–78. http://dx.doi.org/10.2307/4002845
Bhattacharyya, R., Ghosh, B. N., Mishra, P. K., Mandal, B., Rao, C. S., Sarkar, D., Das, K., Anil, K. S., Lalitha, M., Hati, K. M. & Franzluebbers, A. J. (2015). Soil degradation in India: Challenges and potential solutions. Sustainability, 7(4), 3528–3570. https://doi.org/10.3390/su7043528
Bhattarai, R. & Dutta, D. (2007). Estimation of soil erosion and sediment yield using GIS at catchment scale. Water Res Manage. 21(10),1635–1647. doi.org/10.1007/s11269-006-9118-z
Bhatt, B. P., Mondal, S., Saurabh, K., Naik, S. K., Rao, K. K., & Ahmed, A. (2020). Soil Health and Fertilizer Use in India. In: Soil and Fertilizers (pp. 183-207). CRC Press
Biggelaar, C. D., Lal, R., Eswaran, H., Breneman, V. E. & Reich, P. F. (2003). Crop yield losses to soil erosion at regional and global scales: evidence from plot-level and GIS data. In: Land quality, agricultural productivity, and food security: Biophysical processes and economic choices at local, regional, and global levels, (pp 262-279). Edward Elgar Publishing Ltd, United Kingdom
Buraka, T., Elias, E., Suryabhagavan, V.K. & Lelago, A. (2022). Assessment of soil erosion risks in response to land-use and land-cover changes in Coka watershed, Southern Ethiopia. Geology, Ecology, and Landscapes. https://doi.org/10.1080/24749508.2022.2109825
Chang, T.J., Zhou, H. & Guan, Y. (2016). Applications of Erosion Hotspots for Watershed Investigation in the Appalachian Hills of the United States. J. Irrig. Drain Eng, 142. doi.org/10.1061/(ASCE)IR.1943-4774.0000974
Dabral, P.P., Baithuri, N. & Pandey, A. (2008). Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing. Water Resource Management, 22, 1783–1798. doi.org/10.1007/s11269-008-9253-9
Demirci, A. & Karaburun, A. (2012). Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed, northwest Turkey. Environ Earth Sci. 66(3), 903–913. doi.org/10.1007/s12665-011-1300-9
Ditzler, C., Scheffe, K. & Monger, H.C. (1951). Soil Survey Manual. In: Soil Conservation Service, Soil Survey Staff, U.S. Dept. of Agricultural handbook 18, (p 503). U.S. Govt. Print Office, Washington D.C., USA
Duarte, L., Teodoro, A.C., Gonçalves, J.A., Soares, D. & Cunha, M. (2016). Assessing soil erosion risk using RUSLE through a GIS open-source desktop and web application. Environ Monit Assess, 188, 351 doi.org/10.1007/s10661-016-5349-5
Dutta, M. K., Barman, S. & Aggarwal, S. P. (2010). A study of erosion-deposition processes around Majuli Island, Assam. Earth Science India, 3 (4), 206-216
Food and Agriculture Organization (2019). Proceedings of the Global Symposium on Soil Erosion. Outcome Document. Retrieved from https://www.fao.org/3/ca5582en/CA5582EN
Erencin, Z. (2000). C-Factor Mapping Using Remote Sensing and GIS; A case Study of Lom Sak/Lom Kao, Thailand. International Institute for Aerospace Survey and Earth Sciences (ITC): Upper Aise, The Netherlands. Retrieved July 31, 2023, http://geb.uni-giessen.de/geb/volltexte/2004/1537/
Fu, B.J., Zhao, W.W., Chen. L.D., Zhang, Q.J., Lü, Y.H., Gulinck, H. & Poesen, J. (2005). Assessment of soil erosion at large watershed scale using RUSLE and GIS: a case study in the Loess Plateau of China. Land Degrad Dev. 16(1), 73–85. doi.org/10.1002/ldr.646
Ganasri, B. P. & 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. doi.org/10.1016/j.gsf.2015.10.007
Ghosal, K.& Das Bhattacharya, S. (2020). A Review of RUSLE Model. J Indian Soc Remote Sens, 48, 689–707. doi.org/10.1007/s12524-019-01097-0
Ghosh, A., Rakshit, S., Tikle, S., Das, S., Chatterjee, U., Pande, C. B., Alataway, A., Al-Othman, A. A., Dewidar, A. Z. & Mattar, M. A. (2022). Integration of GIS and Remote Sensing with RUSLE Model for Estimation of Soil Erosion. Land, 12(1), 116. https://doi.org/10.3390/land12010116
Goswami, R. (2011). Arsenic in the groundwater of Majuli-the largest river island of the Brahmaputra: prevalence, exposure impacts and removal using a novel nano adsorbent. Department of Environmental Science, Tezpur University. Retrieved from http://hdl.handle.net/10603/99696
Groenendyk, D.G., Ferre, T.A., Thorp, K.R. & Rice, A.K. (2015). Hydrologic-process-based soil texture classifications for improved visualization of landscape function. PLoS One. 10(6),1-17. doi.org/10.1371/journal.pone.0131299
Guo, Y., Peng, C., Zhu, Q., Wang, M., Wang, H., Peng, S., & He, H. (2019). Modelling the impacts of climate and land use changes on soil water erosion: Model applications, limitations, and future challenges. Journal of Environmental Management, 250, 109403. https://doi.org/10.1016/j.jenvman.2019.109403
Issaka, S. & Ashraf, M. A. (2017). Impact of soil erosion and degradation on water quality: a review. Geology, Ecology and Landscapes. 1(1), 1-11. DOI: 10.1080/24749508.2017.1301053
Jamal, S., Ahmad, W. S., Ajmal, U., Aaquib, M., Ali, M.A., Ali, M.B. & Ahmed, S. (2022). An integrated approach for determining the anthropogenic stress responsible for degradation of a Ramsar Site-Wular Lake in Kashmir, India”. Marine Geodesy, 45(4), 407-434. https://doi.org/10.1080/01490419.2022.2034686
Jiang, L., Yao, Z., Liu, Z., Wu, S., Wang, R. & Wang, L. (2015). Estimation of soil erosion in some sections of Lower Jinsha River based on RUSLE. Nat Hazards. 76(3),1831–1847. https://doi.org/10.1007/ s11069-014-1569-6.
Karamage, F., Zhang, C., Liu, T., Maganda, A. & Isabwe, A. (2017). Soil erosion risk assessment in Uganda. Forests. 8(2),1–20. doi.org/10.3390/f8020052
Kouli, M., Soupios, P. & Vallianatos, F. (2009). Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete. Greece Environ Geol. 57(3), 483–497. doi.org/10.1007/s00254-008-1318-9
Makhdumi, W., Shwetha, H.R. & Dwarakish, G.S. (2023). Soil erosion in diverse agroecological regions of India: a comprehensive review of USLE-based modeling. Environmental Monitoring and Assessment, 195, 1112. https://doi.org/10.1007/s10661-023-11687-8
Meiyappan, P., Roy, P. S.,Soliman, A., Li, T., Mondal, P., Wang, S. &Jain, A. K. (2018). India Village-Level Geospatial Socio-Economic Data Set: 1991, 2001. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). Retrived on July, 16, 2023, doi.org/10.7927/H4CN71ZJ
Mohapatra, R. (2022). Application of revised universal soil loss equation model for assessment of soil erosion and prioritization of ravine infested sub basins of a semi-arid river system in India. Model. Earth Syst. Environ, 8, 4883–4896. doi.org/10.1007/s40808-022-01388-5
Pandey, A., Chowdary, V. M. & Mal, B. C. (2007). Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water resources management, 21, 729-746. doi.org/10.1007/s11269-006-9061-z
Parysow, P.; Wang, G.X., Gartner, G.& Anderson, A.B. (2003). Spatial uncertainty analysis for mapping soil erodibility based on joint sequential simulation. Catena, 53, 65–78. doi.org/10.1016/S0341-8162(02)00198-4
Pham, T. G., Degener, J. & Kappas, M. (2018). Integrated universal soil loss equation (USLE) and Geographical Information System (GIS) for soil erosion estimation in A Sap basin: Central Vietnam. International Soil and Water Conservation Research, 6 (2), 99-110. doi.org/10.1016/j.iswcr.2018.01.001
Rajbanshi, J. & Bhattacharya, S. (2020). Assessment of soil erosion, sediment yield and basin specific controlling factors using RUSLE-SDR and PLSR approach in Konar river basin, India. Journal of Hydrology, 587, 124935. https://doi.org/10.1016/j.jhydrol.2020.124935
Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K. & Yoder, D.C. (1996). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). In: Agriculture Handbook 703, (p 25–28), Washington DC, USA
Renard, K.G., Foster, G., Weesies, G., McCool, D. & Yoder, D. (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (Rusle). Agriculture Handbook No.703, (pp 404). United States Government Printing, United States Department of Agriculture, Washington, DC, USA.
Sankhua, R. N., Sharma, N., Garg, P. K. & Pandey, A. D. (2005). Use of remote sensing and ANN in assessment of erosion activities in Majuli, the world's largest river island. International Journal of Remote Sensing. 26 (20), 4445-4454. doi.org/10.1080/01431160500185474
Schwab, G. O., Fangmeier, D. D., Elliot, W. J., Frevert, R. K. & Leonard, R. A. (1994). Soil and water conservation engineering. Journal of Environmental Quality, 23(2), 390. doi.org/10.1017/S0021859600068611
Sharpley, A.N. & Williams, J.R. (1990). Erosion/Productivity Impact Calculator: 1. Model Documentation. In: Technical bulletin, 1768 (235), US Department of Agriculture. Washington DC, USA
Singh, G., Babu, R., Narain, P., Bhushan, L. S. & Abrol, I. P. (1992). Soil erosion rates in India. Journal of Soil and water Conservation, 47(1), 97-99
Srinivas, C.V., Maji, A.K., Obi Reddy GP. & Chary, G.R. (2002). Assessment of soil erosion using remote sensing and GIS in Nagpur district, Maharashtra for prioritisation and delineation of conservation units. Journal of the Indian Society of Remote Sensing. 30(4),197–212. doi.org/10.1007/BF03000363
Sujatha, E. & Sridhar, V. (2018). Spatial Prediction of Erosion Risk of a Small Mountainous Watershed Using RUSLE: A Case-Study of the Palar Sub-Watershed in Kodaikanal, South India. Water. 10 (11), 1608. doi.org/10.3390/w10111608
United States, (1972). SCS National Engineering Handbook, section 4. Hydrology. Govt. Print. Off. United States Department of Agriculture, Washington DC, USA
Wischmeier, W. & Smith, D. (1957). Factors affecting sheet and rill erosion. Transactions. American Geophysical Union, 38(6), 889–896. https://doi.org/10.1029/TR038i006p00889
Wischmeier, W. H. & Smith, D. D. (1978). Predicting rainfall erosion losses: a guide to conservation planning. Agriculture Handbook No. 537. United States Government Printing, Department of Agriculture, Science, and Education Administration, Wahington, DC, USA
Yue-Qing, X., Xiao-Mei, S., Xiang-Bin, K., Jian, P. & Yun-Long, C. (2008). Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China. Environ Monit Assess. 141(1), 275– 286. doi.org/10.1007/s10661-007-9894-9
Zhao, J., Yang, Z. & Govers, G. (2019). Soil and water conservation measures reduce soil and water losses in China but not down to background levels: evidence from erosion plot data. Geoderma, 337, 729-741. https://doi.org/10.1016/j.geoderma.2018.10.023
Zonunsanga, R. (2016), Estimation of Soil loss in Teirei watershed of Mizoram by using the USLE Model. Sci Technol J 4, 43–47. https://doi.org/10.22232/stj.2016.04.01.06
Barman, B. K., Rao, K. S., Sonowal, K., Prasad, N. S. R. & Sahoo, U. K. (2020). Soil erosion assessment using revised universal soil loss equation model and geo-spatial technology: A case study of upper Tuirial river basin, Mizoram, India. AIMS Geosciences, 6(4), 525-545. https://doi.org/10.3934/geosci.2020030
Batjes, N. H., Ribeiro, E. & van Oostrum, A. (2020).Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019). Earth Syst. Sci. Data, 12, 299–320. doi.org/10.5194/essd-12-299-2020
Benkobi, L., Trlica, M. & Smith, J. (1994). Evaluation of a redefined surface cover sub-factor for use in RUSLE. Journal of Range Management, 47, 74–78. http://dx.doi.org/10.2307/4002845
Bhattacharyya, R., Ghosh, B. N., Mishra, P. K., Mandal, B., Rao, C. S., Sarkar, D., Das, K., Anil, K. S., Lalitha, M., Hati, K. M. & Franzluebbers, A. J. (2015). Soil degradation in India: Challenges and potential solutions. Sustainability, 7(4), 3528–3570. https://doi.org/10.3390/su7043528
Bhattarai, R. & Dutta, D. (2007). Estimation of soil erosion and sediment yield using GIS at catchment scale. Water Res Manage. 21(10),1635–1647. doi.org/10.1007/s11269-006-9118-z
Bhatt, B. P., Mondal, S., Saurabh, K., Naik, S. K., Rao, K. K., & Ahmed, A. (2020). Soil Health and Fertilizer Use in India. In: Soil and Fertilizers (pp. 183-207). CRC Press
Biggelaar, C. D., Lal, R., Eswaran, H., Breneman, V. E. & Reich, P. F. (2003). Crop yield losses to soil erosion at regional and global scales: evidence from plot-level and GIS data. In: Land quality, agricultural productivity, and food security: Biophysical processes and economic choices at local, regional, and global levels, (pp 262-279). Edward Elgar Publishing Ltd, United Kingdom
Buraka, T., Elias, E., Suryabhagavan, V.K. & Lelago, A. (2022). Assessment of soil erosion risks in response to land-use and land-cover changes in Coka watershed, Southern Ethiopia. Geology, Ecology, and Landscapes. https://doi.org/10.1080/24749508.2022.2109825
Chang, T.J., Zhou, H. & Guan, Y. (2016). Applications of Erosion Hotspots for Watershed Investigation in the Appalachian Hills of the United States. J. Irrig. Drain Eng, 142. doi.org/10.1061/(ASCE)IR.1943-4774.0000974
Dabral, P.P., Baithuri, N. & Pandey, A. (2008). Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing. Water Resource Management, 22, 1783–1798. doi.org/10.1007/s11269-008-9253-9
Demirci, A. & Karaburun, A. (2012). Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed, northwest Turkey. Environ Earth Sci. 66(3), 903–913. doi.org/10.1007/s12665-011-1300-9
Ditzler, C., Scheffe, K. & Monger, H.C. (1951). Soil Survey Manual. In: Soil Conservation Service, Soil Survey Staff, U.S. Dept. of Agricultural handbook 18, (p 503). U.S. Govt. Print Office, Washington D.C., USA
Duarte, L., Teodoro, A.C., Gonçalves, J.A., Soares, D. & Cunha, M. (2016). Assessing soil erosion risk using RUSLE through a GIS open-source desktop and web application. Environ Monit Assess, 188, 351 doi.org/10.1007/s10661-016-5349-5
Dutta, M. K., Barman, S. & Aggarwal, S. P. (2010). A study of erosion-deposition processes around Majuli Island, Assam. Earth Science India, 3 (4), 206-216
Food and Agriculture Organization (2019). Proceedings of the Global Symposium on Soil Erosion. Outcome Document. Retrieved from https://www.fao.org/3/ca5582en/CA5582EN
Erencin, Z. (2000). C-Factor Mapping Using Remote Sensing and GIS; A case Study of Lom Sak/Lom Kao, Thailand. International Institute for Aerospace Survey and Earth Sciences (ITC): Upper Aise, The Netherlands. Retrieved July 31, 2023, http://geb.uni-giessen.de/geb/volltexte/2004/1537/
Fu, B.J., Zhao, W.W., Chen. L.D., Zhang, Q.J., Lü, Y.H., Gulinck, H. & Poesen, J. (2005). Assessment of soil erosion at large watershed scale using RUSLE and GIS: a case study in the Loess Plateau of China. Land Degrad Dev. 16(1), 73–85. doi.org/10.1002/ldr.646
Ganasri, B. P. & 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. doi.org/10.1016/j.gsf.2015.10.007
Ghosal, K.& Das Bhattacharya, S. (2020). A Review of RUSLE Model. J Indian Soc Remote Sens, 48, 689–707. doi.org/10.1007/s12524-019-01097-0
Ghosh, A., Rakshit, S., Tikle, S., Das, S., Chatterjee, U., Pande, C. B., Alataway, A., Al-Othman, A. A., Dewidar, A. Z. & Mattar, M. A. (2022). Integration of GIS and Remote Sensing with RUSLE Model for Estimation of Soil Erosion. Land, 12(1), 116. https://doi.org/10.3390/land12010116
Goswami, R. (2011). Arsenic in the groundwater of Majuli-the largest river island of the Brahmaputra: prevalence, exposure impacts and removal using a novel nano adsorbent. Department of Environmental Science, Tezpur University. Retrieved from http://hdl.handle.net/10603/99696
Groenendyk, D.G., Ferre, T.A., Thorp, K.R. & Rice, A.K. (2015). Hydrologic-process-based soil texture classifications for improved visualization of landscape function. PLoS One. 10(6),1-17. doi.org/10.1371/journal.pone.0131299
Guo, Y., Peng, C., Zhu, Q., Wang, M., Wang, H., Peng, S., & He, H. (2019). Modelling the impacts of climate and land use changes on soil water erosion: Model applications, limitations, and future challenges. Journal of Environmental Management, 250, 109403. https://doi.org/10.1016/j.jenvman.2019.109403
Issaka, S. & Ashraf, M. A. (2017). Impact of soil erosion and degradation on water quality: a review. Geology, Ecology and Landscapes. 1(1), 1-11. DOI: 10.1080/24749508.2017.1301053
Jamal, S., Ahmad, W. S., Ajmal, U., Aaquib, M., Ali, M.A., Ali, M.B. & Ahmed, S. (2022). An integrated approach for determining the anthropogenic stress responsible for degradation of a Ramsar Site-Wular Lake in Kashmir, India”. Marine Geodesy, 45(4), 407-434. https://doi.org/10.1080/01490419.2022.2034686
Jiang, L., Yao, Z., Liu, Z., Wu, S., Wang, R. & Wang, L. (2015). Estimation of soil erosion in some sections of Lower Jinsha River based on RUSLE. Nat Hazards. 76(3),1831–1847. https://doi.org/10.1007/ s11069-014-1569-6.
Karamage, F., Zhang, C., Liu, T., Maganda, A. & Isabwe, A. (2017). Soil erosion risk assessment in Uganda. Forests. 8(2),1–20. doi.org/10.3390/f8020052
Kouli, M., Soupios, P. & Vallianatos, F. (2009). Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete. Greece Environ Geol. 57(3), 483–497. doi.org/10.1007/s00254-008-1318-9
Makhdumi, W., Shwetha, H.R. & Dwarakish, G.S. (2023). Soil erosion in diverse agroecological regions of India: a comprehensive review of USLE-based modeling. Environmental Monitoring and Assessment, 195, 1112. https://doi.org/10.1007/s10661-023-11687-8
Meiyappan, P., Roy, P. S.,Soliman, A., Li, T., Mondal, P., Wang, S. &Jain, A. K. (2018). India Village-Level Geospatial Socio-Economic Data Set: 1991, 2001. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). Retrived on July, 16, 2023, doi.org/10.7927/H4CN71ZJ
Mohapatra, R. (2022). Application of revised universal soil loss equation model for assessment of soil erosion and prioritization of ravine infested sub basins of a semi-arid river system in India. Model. Earth Syst. Environ, 8, 4883–4896. doi.org/10.1007/s40808-022-01388-5
Pandey, A., Chowdary, V. M. & Mal, B. C. (2007). Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water resources management, 21, 729-746. doi.org/10.1007/s11269-006-9061-z
Parysow, P.; Wang, G.X., Gartner, G.& Anderson, A.B. (2003). Spatial uncertainty analysis for mapping soil erodibility based on joint sequential simulation. Catena, 53, 65–78. doi.org/10.1016/S0341-8162(02)00198-4
Pham, T. G., Degener, J. & Kappas, M. (2018). Integrated universal soil loss equation (USLE) and Geographical Information System (GIS) for soil erosion estimation in A Sap basin: Central Vietnam. International Soil and Water Conservation Research, 6 (2), 99-110. doi.org/10.1016/j.iswcr.2018.01.001
Rajbanshi, J. & Bhattacharya, S. (2020). Assessment of soil erosion, sediment yield and basin specific controlling factors using RUSLE-SDR and PLSR approach in Konar river basin, India. Journal of Hydrology, 587, 124935. https://doi.org/10.1016/j.jhydrol.2020.124935
Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K. & Yoder, D.C. (1996). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). In: Agriculture Handbook 703, (p 25–28), Washington DC, USA
Renard, K.G., Foster, G., Weesies, G., McCool, D. & Yoder, D. (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (Rusle). Agriculture Handbook No.703, (pp 404). United States Government Printing, United States Department of Agriculture, Washington, DC, USA.
Sankhua, R. N., Sharma, N., Garg, P. K. & Pandey, A. D. (2005). Use of remote sensing and ANN in assessment of erosion activities in Majuli, the world's largest river island. International Journal of Remote Sensing. 26 (20), 4445-4454. doi.org/10.1080/01431160500185474
Schwab, G. O., Fangmeier, D. D., Elliot, W. J., Frevert, R. K. & Leonard, R. A. (1994). Soil and water conservation engineering. Journal of Environmental Quality, 23(2), 390. doi.org/10.1017/S0021859600068611
Sharpley, A.N. & Williams, J.R. (1990). Erosion/Productivity Impact Calculator: 1. Model Documentation. In: Technical bulletin, 1768 (235), US Department of Agriculture. Washington DC, USA
Singh, G., Babu, R., Narain, P., Bhushan, L. S. & Abrol, I. P. (1992). Soil erosion rates in India. Journal of Soil and water Conservation, 47(1), 97-99
Srinivas, C.V., Maji, A.K., Obi Reddy GP. & Chary, G.R. (2002). Assessment of soil erosion using remote sensing and GIS in Nagpur district, Maharashtra for prioritisation and delineation of conservation units. Journal of the Indian Society of Remote Sensing. 30(4),197–212. doi.org/10.1007/BF03000363
Sujatha, E. & Sridhar, V. (2018). Spatial Prediction of Erosion Risk of a Small Mountainous Watershed Using RUSLE: A Case-Study of the Palar Sub-Watershed in Kodaikanal, South India. Water. 10 (11), 1608. doi.org/10.3390/w10111608
United States, (1972). SCS National Engineering Handbook, section 4. Hydrology. Govt. Print. Off. United States Department of Agriculture, Washington DC, USA
Wischmeier, W. & Smith, D. (1957). Factors affecting sheet and rill erosion. Transactions. American Geophysical Union, 38(6), 889–896. https://doi.org/10.1029/TR038i006p00889
Wischmeier, W. H. & Smith, D. D. (1978). Predicting rainfall erosion losses: a guide to conservation planning. Agriculture Handbook No. 537. United States Government Printing, Department of Agriculture, Science, and Education Administration, Wahington, DC, USA
Yue-Qing, X., Xiao-Mei, S., Xiang-Bin, K., Jian, P. & Yun-Long, C. (2008). Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China. Environ Monit Assess. 141(1), 275– 286. doi.org/10.1007/s10661-007-9894-9
Zhao, J., Yang, Z. & Govers, G. (2019). Soil and water conservation measures reduce soil and water losses in China but not down to background levels: evidence from erosion plot data. Geoderma, 337, 729-741. https://doi.org/10.1016/j.geoderma.2018.10.023
Zonunsanga, R. (2016), Estimation of Soil loss in Teirei watershed of Mizoram by using the USLE Model. Sci Technol J 4, 43–47. https://doi.org/10.22232/stj.2016.04.01.06
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Application of Revised Universal Soil Loss Equation (RUSLE) model for the estimation of soil erosion and prioritization of erosion-prone areas in Majuli Island, Assam, India. (2023). Journal of Applied and Natural Science, 15(4), 1667-1678. https://doi.org/10.31018/jans.v15i4.5176
