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Identification of soil erosion-prone areas and annual average soil loss of Siddheswari River basin, Eastern India

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Abstract

Soil erosion is one of the major environmental issues influencing productivity and soil deterioration. Various erosion agents have contributed to soil erosion in recent years, but flowing water continues to be the primary cause. This study used ten key factors, including the Analytic Hierarchy Process (AHP) and Revised Universal Soil Loss Equation (RUSLE) methodologies, to assess erosion risk in the Siddheswari River basin. The final erosion map is produced by integrating ten factors within the ArcGIS environment. Results indicate that the extreme soil erosion zone covers 168.70 km2 area (19.30%) and scattered over the upper and middle catchment; the high soil erosion region covers 172.58 km2 (19.75%) area of the upper, middle, and lower catchment; low and very low erosion vulnerable zones covering 201.07 km2 (23.01%) and 100.47 km2 (11.50%) areas respectively of the basin’s total area and mainly located near the western boundaries of a watershed and some neglected portions of the upper and middle catchment of the basin. Moderate soil erosion region covering 231.06 km2 areas (26.44%) characterized by moderate slope steepness and low-to-moderate vegetation. Spatial predicted soil erosion rate using the RUSLE method also shows a higher erosion rate. The high annual soil loss is observed in the high altitude and sloping regions, precisely in the side slope plateau fringe and denudational slope. The predicted results using AHP and RUSLE methods show that higher altitude areas near upper and upper–middle catchments are more vulnerable to erosion. The conclusion demonstrates that the Siddheswari basin's upper and upper–middle catchment areas have the highest soil erosion concerns.

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References

  • Adiat, K. A. N., Nawawi, M. N. M., & Abdullah, K. (2012). Assessing the accuracy of GIS-based elementary multi-criteria decision analysis as a spatial prediction tool—a case of predicting potential zones of sustainable groundwater resources. Journal of Hydrology, 440–441, 75–89. https://doi.org/10.1016/j.jhydrol.2012.03.028.

    Article  Google Scholar 

  • Akinci, H., Ozalp, A. Y., & Turgut, B. (2013). Agricultural land use suitability analysis using GIS and AHP technique. Computers and Electronics in Agriculture, 97, 71–82. https://doi.org/10.1016/j.compag.2013.07.006.

    Article  Google Scholar 

  • Althuwaynee, O. F., Pradhan, B., Park, H. J., & Lee, J. H. (2014). A novel ensemble bivariate statistical evidential belief function with knowledge based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. CATENA, 114, 21–36. https://doi.org/10.1016/j.catena.2013.10.011.

    Article  Google Scholar 

  • Arabameri, A., Pradhan, B., Rezaei, K., Yamani, M., Pourghasemi, H. R., & Lombardo, L. (2018). Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function-logistic regression algorithm. Land Degradation & Development, 29(11), 4035–4049. https://doi.org/10.1002/ldr.3151.

    Article  Google Scholar 

  • Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large-area hydrologic modeling and assessment: Part I. Model development. Journal of the American Water Resources Association, 34(1), 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x.

    Article  Google Scholar 

  • Barakat, A., Ennaji, W., Jazouli, A. E., Amediaz, R., & Touhami, F. (2017). Multivariate analysis and GIS-based soil suitability diagnosis for sustainable intensive agriculture in Beni-Moussa irrigated sub perimeter (Tadla plain, Morocco). Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-017-0272-5.

    Article  Google Scholar 

  • Basu, T., & Pal, S. (2017). Exploring landslide susceptible zones by analytic hierarchy process (AHP) for the Gish River Basin, West Bengal, India. Spatial Information Research. https://doi.org/10.1007/s41324-017-0134-2.

    Article  Google Scholar 

  • Bera, A., Mukhopadhyay, B. P., & Biswas, S. (2020). Assessment of gully erosion and estimation of sediment yield in Siddheswari River Basin, Eastern India, Using SWAT Model. In P. Shit, H. Pourghasemi, & G. Bhunia (Eds.), Gully erosion studies from india and surrounding regions. Advances in science, technology & innovation. Cham: Springer. https://doi.org/10.1007/978-3-030-23243-6_17.

    Chapter  Google Scholar 

  • Bhattacharya, A. (2013). Evolution of the Hydro-geonomic characteristics of flood in the Mayurakshi River basin of Eastern India. Doctoral dissertation, The University of Visva-Bharati, West Bengal, India. Retrieved April 8, 2017 from http://hdl.handle.net/10603/19911.

  • Bhatt, S., & Ahmed, S. A. (2014). Morphometric analysis to determine floods in the Upper Krishna basin using Cartosat DEM. Geocarto International, 29(8), 878–894. https://doi.org/10.1080/10106049.2013.868042.

    Article  Google Scholar 

  • Biswas, S., Sudhakar, S., & Desai, V. R. (1999). Prioritisation of subwatersheds based on morphometricanalysis of drainage basin: a remote sensing and gis approach. Journal of the Indian Society of Remote Sensing, 27, 155. https://doi.org/10.1007/BF02991569.

    Article  Google Scholar 

  • Chandniha, S. K., & Kansal, M. L. (2017). Prioritization of sub-watersheds based on morphometric analysis using geospatial technique in Piperiya watershed, India. Applied Water Science, 7, 329–338. https://doi.org/10.1007/s13201-014-0248-9.

    Article  Google Scholar 

  • Chen, M. F., Tzeng, G. H., & Ding, C. G. (2008). Combining fuzzy AHP with MDS in identifying the preference similarity of alternatives. Applied Soft Computing, 8(1), 110–117. https://doi.org/10.1016/j.asoc.2006.11.007.

    Article  Google Scholar 

  • Conoscenti, C., Angileri, S., Cappadonia, C., Rotigliano, E., Agnesi, V., & Märker, M. (2013). Gully erosion susceptibility assessment by means of GIS-based logistic regression: A case of Sicily (Italy). Geomorphology. https://doi.org/10.1016/j.geomorph.2013.08.021.

    Article  Google Scholar 

  • 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 Resources Management, 22(12), 1783–1798. https://doi.org/10.1007/s11269-008-9253-9.

    Article  Google Scholar 

  • Daneshvar, M. R., Khatami, F., & Shirvani, S. (2017). GIS-based land suitability evaluation for building height construction using an analytical process in the Mashhad city, NE Iran. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-017-0286-z.

    Article  Google Scholar 

  • Danumah, J. H., Odai, S. N., Saley, B. M., Szarzynski, J., Thiel, M., Kwaku, A., et al. (2016). Flood risk assessment and mapping in Abidjan district using multi-criteria analysis (AHP) model and geoinformation techniques, (cote d’ivoire). Geoenviron Disasters, 3, 10. https://doi.org/10.1186/s40677-016-0044-y.

    Article  Google Scholar 

  • Das, B., Bordoloi, R., Thungon, L. T., Paul, A., Pandey, P. K., Mishra, M., & Tripathi, O. P. (2020). An integrated approach of GIS, RUSLE and AHP to model soil erosion in West Kameng watershed, Arunachal Pradesh. Journal of Earth System Science. https://doi.org/10.1007/s12040-020-1356-6.

    Article  Google Scholar 

  • Debanshi, S., & Pal, S. (2018). Assessing gully erosion susceptibility in Mayurakshi river basin of eastern India. Environment, Development and Sustainability, 22, 1–32. https://doi.org/10.1007/s10668-018-0224-x.

    Article  Google Scholar 

  • Deng, L., Shangguan, Z. P., & Li, R. (2012). Effects of the grain-for-green program on soil erosion in China. Int J Sediment Res, 27(1), 120–127. https://doi.org/10.1016/S1001-6279(12)60021-3.

    Article  Google Scholar 

  • Flanagan, D. C., & Nearing, M. A. (1995). USDA-water erosion prediction project: hillslope profile and watershed model documentation. NSERL Report no. 10, USDA-ARS National Soil Erosion Research Laboratory, West Lafayette.

  • 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. https://doi.org/10.1016/j.gsf.2015.10.007.

    Article  Google Scholar 

  • Ghosh, K. G., & Saha, S. (2015). Identification of soil erosion susceptible areas in Hinglo river basin, eastern India based on geo-statistics. Universal Journal of Environmental Research and Technology, 5(3), 152–164.

    Google Scholar 

  • Ghosh, S., & Guchhait, S. K. (2015). Characterization and evolution of laterites in West Bengal: Implication on the geology of northwest Bengal Basin. Transactions, 37(1), 93–119.

    Google Scholar 

  • Govindaraj, T., & Baskaran, R. (2017). Identification of soil erosion prone zones in parts of Nichabanadhi Sub Basin Tamilnadu, India—using remote sensing and GIS. Asian Journal of Applied Science and Technology, 1(8), 157–159.

    Google Scholar 

  • G.S.I. (1985). Geological quadrangle map, Barddhaman Quadrangle (72P, 73 M). West Bengal: Geological Survey of India, Printing div. Hydrabad, Govt. of India.

    Google Scholar 

  • Guerra, C. A., Maces, J., Geijzendorffer, I., & Metzger, M. J. (2015). An assessment of soil erosion prevention by vegetation in Mediterranean Europe: Current trends of ecosystem service provision. Ecological Indicators, 60, 213–222. https://doi.org/10.1016/j.ecolind.2015.06.043.

    Article  Google Scholar 

  • Gupita, D. D., & Sigit Heru Murti, B. S. (2017). Soil erosion and its correlation with vegetation cover: An assesment using multispectral imagery and pixel-based geographic information system in Gesing Sub-Watershed, Central Java, Indonesia. IOP Conference Series: Earth and Environmental Science, 54, 012047. https://doi.org/10.1088/1755-1315/54/1/012047.

    Article  Google Scholar 

  • Hembram, T. K., & Saha, S. (2018). Geo-environmental evaluation for exploring potential soil erosion areas of Jainti River Basin using AHP Model, Eastern India. Univer J Env Res Tec, 7(1), 38–55.

    Google Scholar 

  • Horton, R. E. (1932). Drainage basin characteristics. Transactions American Geophysical Union, 13, 350–361. https://doi.org/10.1029/TR013i001p00350.

    Article  Google Scholar 

  • Horton, R. E. (1945). Erosional development of streams and their drainage basins: Hydro-physical approach to quantitative morphology. Geological Society of America Bulletin, 56, 275–370.

    Article  Google Scholar 

  • Islam, K. R., & Weil, R. R. (2000). Land use effects on soil quality in a tropical forest ecosystem of Bangladesh. Agriculture, Ecosystems & Environment, 79(1), 9–16. https://doi.org/10.1016/S0167-8809(99)00145-0.

    Article  Google Scholar 

  • I.W.D. (2015). Annual flood report for the year 2015. Irrigation and Waterways Department (IWD), Govt of West Bengal: Kolkata, India. Retrieved April 8, 2017 from https://wbiwd.gov.in/uploads/anual_flood_report/ANNUAL_FLOOD_REPORT_2015.pdf.

  • I.W.D. (2016). Annual flood report for the year 2016. Irrigation and Waterways Department (IWD), Govt of West Bengal: Kolkata, India. Retrieved April 8, 2017 from http://www.wbiwd.gov.in/uploads/ANNUAL_FLOOD_REPORT_2016.pdf.

  • Jain, M. K., & Kothyari, U. C. (2000). Estimation of soil erosion and sediment yield using GIS. Hydrological Sciences Journal, 45(5), 771–786. https://doi.org/10.1080/02626660009492376.

    Article  Google Scholar 

  • Jain, S. K., & Goel, M. K. (2002). Assessing the vulnerability to soil erosion of the Ukai Dam catchments using remote sensing and GIS. Hydrological Sciences Journal, 47(1), 31–40. https://doi.org/10.1080/02626660209492905.

    Article  Google Scholar 

  • Javadian, M., Shamskooshki, H., & Momeni, M. (2011). Application of sustainable urban development in environmental suitability analysis of educational land use by using AHP and GIS in Tehran. Procedia Engineering, 21, 72–80. https://doi.org/10.1016/j.proeng.2011.11.1989.

    Article  Google Scholar 

  • Jha, V. C., & Kapat, S. (2003). Gully erosion and its implications on land use: A case study of Dumka block, Dumka district, Jharkhand. In V. C. Jha (Ed.), Land degradation and desertification (pp. 156–178). Rawat Publications.

    Google Scholar 

  • Jha, V. C., & Kapat, S. (2011). Degraded lateritic soils cape and land uses in Birbhum district, West Bengal, India. Revista Sociedade and Natureza, 23(3), 545–556.

    Article  Google Scholar 

  • Jothibasu, A., & Anbazhagan, S. (2016). Modeling groundwater probability index in Ponnaiyar river basin of South India using analytic hierarchy process. Modeling Earth Systems and Environment, 2, 109. https://doi.org/10.1007/s40808-016-0174-y.

    Article  Google Scholar 

  • Kabo-bah, K. J., Guoan, T., Yang, X., Na, J., & Xiong, L. (2021). Erosion potential mapping using analytical hierarchy process (AHP) and fractal dimension. Heliyon, 7(6), e07125. https://doi.org/10.1016/j.heliyon.2021.e07125.

    Article  Google Scholar 

  • Kale, V. S., & Gupta, A. (2001). Introduction to Geomorphology. Orient Blackswan Private Limited.

    Google Scholar 

  • Kaliraj, S., Chandrasekar, N., & Magesh, N. S. (2013). Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique. Arabian Journal of Geosciences, 7, 1385. https://doi.org/10.1007/s12517-013-0849-x.

    Article  Google Scholar 

  • Khatun, S. (2017). Detection of soil erosion potential zones and estimation of soil loss in Kushkarani River Basin of Eastern India. Environment and Earth Science International, 12(4), 1–17. https://doi.org/10.9734/JGEESI/2017/37296.

    Article  Google Scholar 

  • Kheir, R. B., Wilson, J., & Deng, Y. (2007). Use of terrain variables for mapping gully erosion susceptibility in Lebanon. Earth Surface Processes and Landforms, 32(12), 1770–1782. https://doi.org/10.1002/esp.1501.

    Article  Google Scholar 

  • Knisel, W. G. (1980). CREAMS: a field scale model for chemicals, runoff, and erosion from agricultural management systems. US Department of Agriculture, Conservation Report 26.

  • Korada Rao, H. V. D., & Vala Rao, V. (2014). Soil erosion assessment in Rangit catchment, India through a process based model in the geospatial environment. Geocarto International, 29(5), 507–519. https://doi.org/10.1080/10106049.2013.798359.

    Article  Google Scholar 

  • Kucuker, D. M., & Cedano Giraldo, D. (2022). Assessment of soil erosion risk using an integrated approach of GIS and Analytic Hierarchy Process (AHP) in Erzurum. Turkiye. Ecological Informatics, 71, 101788. https://doi.org/10.1016/j.ecoinf.2022.101788.

    Article  Google Scholar 

  • Lal, R. (2001). Soil degradation by erosion. Land Degradation & Development, 12(6), 519–539. https://doi.org/10.1002/ldr.472.

    Article  Google Scholar 

  • Lal, R. (2003). Soil erosion and the global carbon budget. Environment International, 29(4), 437–450. https://doi.org/10.1016/S0160-4120(02)00192-7.

    Article  Google Scholar 

  • Lee, S. (2004). Soil erosion assessment and its verification using the Universal Soil Loss Equation and Geographic Information System: A case study at Boun, Korea. Environmental Geology, 45(4), 457–465. https://doi.org/10.1007/s00254-003-0897-8.

    Article  Google Scholar 

  • Le Cozannet, G., Garcin, M., Bulteau, T., Mirgon, C., Yates, M., Méndez, M., et al. (2013). An AHP-derived method for mapping the physical vulnerability of coastal areas at regional scales. Natural Hazards and Earth System Sciences, 13, 1209–1227. https://doi.org/10.5194/nhess-13-1209-2013.

    Article  Google Scholar 

  • Mahapatra, M., Ramakrishnan, R., & Rajawat, A. S. (2015). Coastal vulnerability assessment using analytical hierarchical process for South Gujarat coast, India. Natural Hazards, 76, 139–159. https://doi.org/10.1007/s11069-014-1491-y.

    Article  Google Scholar 

  • Meshram, S. G., Powar, P. L., & Singh, V. P. (2017). Modelling soil erosion from a watershed using cubic splines. Arabian Journal of Geosciences, 10(155), 1–11. https://doi.org/10.1007/s12517-017-2908-1.

    Article  Google Scholar 

  • Meshram, S. G., & Sharma, S. K. (2017). Prioritization of watershed through morphometric parameters: A PCA-based approach. Applied Water Science, 7(3), 1505–1519. https://doi.org/10.1007/s13201-015-0332-9.

    Article  Google Scholar 

  • Mikoš, M., Jošt, D., & Petkovšek, G. (2006). Rainfall and runoff erosivity in the alpine climate of north Slovenia: A comparison of different estimation methods. Hydrological Sciences Journal, 51(1), 115–126. https://doi.org/10.1623/hysj.51.1.115.

    Article  Google Scholar 

  • Milliman, J. D., & Syvitski, J. P. M. (1992). Geomorphic/tectonic control of sediment discharge to the ocean: The importance of small mountainous rivers. The Journal of Geology, 100(5), 525–544. https://doi.org/10.1086/629606.

    Article  Google Scholar 

  • Molina-Navarro, E., Martínez-Pérez, S., Sastre-Merlín, A., & Bienes-Allas, R. (2014). Catchment erosion and sediment delivery in a limno-reservoir basin using a simplemethodology. Water Resour Manag, 28(8), 2129–2143. https://doi.org/10.1007/s11269-014-0601-7.

    Article  Google Scholar 

  • Morgan, R. P. C., Morgan, D. D. V., & Finney, H. J. (1984). A predictive model for the assessment of soil erosion risk. Journal of Agricultural Engineering Research, 30, 245–253.

    Article  Google Scholar 

  • Morgan, R. P. C., Quinton, J. N., Smith, R. E., Govers, G., Poesen, J. W. A., Auerswald, K., Chisci, G., Torri, D., & Styczen, M. E. (1998). The European Soil Erosion Model (EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments. Earth Surf Processes, 23, 527–544. https://doi.org/10.1002/(SICI)1096-9837(199806)23:6%3C527::AID-ESP868%3E3.0.CO;2-5.

    Article  Google Scholar 

  • Murali, R. M., Ankita, M., Amrita, S., & Vethamony, P. (2013). Coastal vulnerability assessment of Puducherry coast, India, using the analytical hierarchical process. Natural Hazards and Earth System Sciences, 13(12), 3291–3311. https://doi.org/10.5194/nhess-13-3291-2013.

    Article  Google Scholar 

  • Pal, S. (2016). Identification of soil erosion vulnerable areas in chandrabhaga river basin: A multi-criteria decision approach. Modeling Earth Systems and Environment, 2(5), 1–11. https://doi.org/10.1007/s40808-015-0052-z.

    Article  Google Scholar 

  • Pal, S., & Debanshi, S. (2018). Influences of soil erosion susceptibility toward overloading vulnerability of the gully head bundhs in Mayurakshi River basin of eastern Chottanagpur Plateau. Environment, Development and Sustainability, 20(4), 1739–1775. https://doi.org/10.1007/s10668-017-9963-3.

    Article  Google Scholar 

  • Pareta, K., & Pareta, U. (2012). Integrated watershed modeling and characterization using GIS and remote sensing techniques. Ind. J. Eng., 84–85.

  • Phillips, J. D. (1990). Relative importance of factors influencing fluvial soil loss at the global scale. American Journal of Science, 290(5), 547–568. https://doi.org/10.2475/ajs.290.5.547.

    Article  Google Scholar 

  • Pimentel, D. (2006). Soil erosion: A food and environmental threat. Environment, Development and Sustainability, 8, 119–137. https://doi.org/10.1007/s10668-005-1262-8.

    Article  Google Scholar 

  • Pourghasemi, H. R., Pradhan, B., & Gokceoglu, C. (2012). Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Natural Hazards, 63(2), 965–996. https://doi.org/10.1007/s11069-012-0217-2.

    Article  Google Scholar 

  • Pramanik, M. K. (2016). Site suitability analysis for agricultural land use of Darjeeling district using AHP and GIS techniques. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-016-0116-8.

    Article  Google Scholar 

  • Rahaman, S. A., & Aruchamy, S. (2017). Geoinformatics based landslide vulnerable zonation mapping using analytical hierarchy process (AHP), a study of Kallar river sub watershed, Kallar watershed, Bhavani basin, Tamil Nadu. Modeling Earth Systems and Environment, 3, 41. https://doi.org/10.1007/s40808-017-0298-8.

    Article  Google Scholar 

  • Rao, Y. P. (1981). Evaluation of Cropping Management Factor in Universal Soil Loss Equation under Natural Rainfall Condition of Kharagpur, India. In: Proceedings of the south–east Asian Regional Symposium on Problems of Soil Erosion and Sedimentation. Bangkok, pp 241–254.

  • Rao Malleswara, B. N., Umamahesh, N. V., & Reddy Thimma, G. (2005). GIS based soil erosion modelling for conservation planning of watersheds. Journal of Hydraulic Engineering Division of the American Society of Civil Engineers, 11(3), 11–23. https://doi.org/10.1080/09715010.2005.10514797.

    Article  Google Scholar 

  • Razandi, Y., Pourghasemi, H. R., Neisani, N. S., & Rahmati, O. (2015). Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS. Earth Science Informatics, 8, 867–883. https://doi.org/10.1007/s12145-015-0220-8.

    Article  Google Scholar 

  • Reddy, G. P. O., Maji, A. K., & Gajbhiye, K. S. (2004). Drainage morphometry and its influence on landform characteristics in a basaltic terrain, Central India—a remote sensing and GIS approach. International Journal of Applied Earth Observation and Geoinformation, 6, 1–16. https://ui.adsabs.harvard.edu/link_gateway/2004IJAEO...6....1R/https://doi.org/10.1016/j.jag.2004.06.003.

  • Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., & Yoder, D. C. (1997). Predicting rainfall erosion losses: a guide to conservation planning with the revised universal soil loss equation (RUSLE) US. Department of Agriculture, Agricultural Handbook 703, Washington, DC, p 404.

  • Renard, K. G., Foster, G. R., Weesies, G. A., & Porter, J. P. (1991). RUSLE: Revised universal soil loss equation. Journal of Soil and Water Conservation, 46(1), 30–33.

    Google Scholar 

  • Rimba, A. B., Setiawati, M. B., Sambah, A. B., & Miura, F. (2017). Physical flood vulnerability mapping applying geospatial techniques in Okazaki City, Aichi Prefecture, Japan. Urban Science, 1, 7. https://doi.org/10.3390/urbansci1010007.

    Article  Google Scholar 

  • Robert, P. S. (2000). Engineer Soil Management/OMAFRA, Byproduct Management/OMAFRA. www.omafra.gov.on.ca/english/engineer/facts/12-051.htm.

  • Roig-Tierno, N., Baviera-Puig, A., Buitrago-Vera, J., & Mas-Verdu, F. (2013). The retail site location decision process using GIS and the analytical hierarchy process. Applied Geography, 40, 191–198. https://doi.org/10.1016/j.apgeog.2013.03.005.

    Article  Google Scholar 

  • Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical Modelling, 9(3–5), 161–176. https://doi.org/10.1016/0270-0255(87)90473-8.

    Article  Google Scholar 

  • Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234–281. https://doi.org/10.1016/0022-2496(77)90033-5.

    Article  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw Hill International.

    Google Scholar 

  • Shaban, A., Khawlie, M., Abdallah, C., & Awad, M. (2005). Hydrological and watershed characteristics of the El-Kabir River, North Lebanon. Lakes & Reservoirs Research & Management, 10, 93–101.

    Article  Google Scholar 

  • Sharma, S. K., Gajbhiye, S., Nema, R. K., & Tignath, S. (2014). Assessing Vulnerability to Soil Erosion of a Watershed of Tons River Basin in Madhya Pradesh using Remote Sensing and GIS. International Journal of Environmental Research and Development, 4(2), 153–164. http://www.ripublication.com/ijerd.htm.

  • Shit, P. K., Bhunia, G. S., & Maiti, R. (2014). Morphology and development of selected Badlands in South Bengal (India). Indian Journal of Geography and Environment, 13, 161–171.

    Google Scholar 

  • Shit, P. K., Bhunia, G. S., & Maiti, R. (2016). An experimental investigation of rill erosion processes in lateritic upland region: A pilot study. Eurasian Journal of Soil Science, 5(2), 121–131.

    Google Scholar 

  • Singh, O., & Singh, J. (2018). Soil erosion susceptibility assessment of the lower Himachal Himalayan Watershed. Journal of the Geological Society of India, 92, 157–165. https://doi.org/10.1007/s12594-018-0975-x.

    Article  Google Scholar 

  • Stathopoulos, N., Lykoudi, E., Vasileiou, E., Rozos, D., & Dimitrakopoulos, D. (2017). Erosion Vulnerability Assessment of Sperchios River Basin, in East Central Greece—a GIS based analysis. Open Journal of Geology, 7, 621–646. https://doi.org/10.4236/ojg.2017.75043.

    Article  Google Scholar 

  • Strahler, A. N. (1964). Quantitative geomorphology of drainage basins and channel networks. In V. T. Chow (Ed.), Handbook of applied hydrology (pp. 411–476). McGraw-Hill.

    Google Scholar 

  • Šurda, P., Šimonides, I., & Antal, J. (2007). A determination of area of potential erosion by geographic information systems. Journal of Environmental Engineering and Landscape Management, 15(3), 144–152. https://doi.org/10.1080/16486897.2007.9636922.

    Article  Google Scholar 

  • Sutradhar, H. (2018). Surface Runoff Estimation Using SCS-CN Method in Siddheswari River Basin, Eastern India. Journal of Geography, Environment and Earth Science International, 17(2), 1–9. https://doi.org/10.9734/JGEESI/2018/44076n.

    Article  Google Scholar 

  • Thomas, J., Joseph, S., & Thrivikramji, K. P. (2018). Assessment of soil erosion in a tropical mountain river basin of the southern Western Ghats, India using RUSLE and GIS. Geoscience Frontiers, 9(3), 893–906. https://doi.org/10.1016/j.gsf.2017.05.011.

    Article  Google Scholar 

  • Townshend, J. R., & Justice, C. O. (1986). Analysis of the dynamics of African vegetation using the normalized difference vegetation index. International Journal of Remote Sensing, 7(11), 1435–1445.

    Article  Google Scholar 

  • USDA-SCS (US Department of Agriculture-Soil Conservation Service) (1972). SCS National Engineering Handbook, Section 4, Hydrology. Chapter 10, Estimation of Direct Runoff from Storm Rainfall. US Department of Agriculture, Soil Conservation Service, Washington, DC, pp 10.1–10.24.

  • Valentin, C., Poesen, J., & Li, Y. (2005). Gully erosion: Impacts, factors and control. CATENA, 63(2–3), 132–153. https://doi.org/10.1016/j.catena.2005.06.001.

    Article  Google Scholar 

  • Van der-Knijff, J. M., Jones, R. J. A., & Montanarella, L. (2000). Soil erosion risk assessment in Europe. EUR 19044 EN. Office for official publications of the European Communities, Luxembourg, p 34.

  • Vohra, B. B. (1985). Land and water: towards a policy for life-support systems (Vol. 2). INTACH, Indian National Trust for Art and Cultural Heritage.

  • Walling, D. E., & Webb, B. W. (1996). Erosion and sediment yield: a global overview. In: Walling DE and Webb BW (Eds.), Erosion and sediment yield: global and regional perspectives (Proceedings of the Exeter Symposium, July 1996). IAHS Publication, No. 236, 3–19. http://hydrologie.org/redbooks/a236/iahs_236_0003.pdf.

  • Williams, J. R. (1975). Sediment-yield prediction with Universal Equation using runoff energy factor. In: Present and prospective technology for predicting sediment yield and sources. US Department of Agriculture ARS-S40, 244–252.

  • Williams, J. R., & Renard, K. G. (1983). EPIC: A new method for assessing erosion’s effects on soil productivity. Journal of Soil and Water Conservation, 38(5), 381–383.

    Google Scholar 

  • Wischmeir, W. H., & Smith, D. (1978). Predicting rainfall erosion losses: a guide to conservation planning. US Department of Agriculture, Agriculture Handbook No. 537.

  • Wu, Q., & Wang, M. (2007). A framework for risk assessment on soil erosion by water using an integrated and systematic approach. Journal of Hydrology, 337(1–2), 11–21. https://doi.org/10.1016/j.jhydrol.2007.01.022.

    Article  Google Scholar 

  • Xu, Y., Sun, J., Zhang, J., Xu, Y., Zhang, M., & Liao, X. (2012). Combining AHP with GIS in synthetic evaluation of environmental suitability for living in China’s 35 major cities. International Journal of Geographical Information Science, 26(9), 1603–1623. https://doi.org/10.1080/13658816.2011.642800.

    Article  Google Scholar 

  • Yadav, M., & Vaishya, R. C. (2023). GIS-based assessment of soil loss using AHP with RUSLE model: A case study of Kaushambi-Prayagraj Watershed in the Ganga Basin, U.P. (India). Water, Air, & Soil Pollution, 234(7), 426. https://doi.org/10.1007/s11270-023-06396-4.

    Article  Google Scholar 

  • Yalew, S. G., Griensven, A. V., Mul, M. L., & Zaag, P. V. (2016). Land suitability analysis for agriculture in the Abbay basin using remote sensing, GIS and AHP techniques. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-016-0167-x.

    Article  Google Scholar 

  • Yang, Q., Xie, Y., Li, W., Jiang, Z., Li, H., & Qin, X. (2013). Assessing soil erosion risk in karst area using fuzzy modeling and method of the analytical hierarchy process. Environment and Earth Science, 71(1), 287–292. https://doi.org/10.1007/s12665-013-2432-x.

    Article  Google Scholar 

  • Ying, X., Guang-Ming, Z., Gui-Qiu, C., Lina, T., Ke-Lin, W., & Dao-You, H. (2007). Combining AHP with GIS in syntheti, evaluation of eco-environment quality—a case study of Hunan Province, China. Ecological Modelling, 209(2–4), 97–109. https://doi.org/10.1016/j.ecolmodel.2007.06.007.

    Article  Google Scholar 

  • Zhang, Y., Degroote, J., Wolter, C., & Sugumaran, R. (2009). Integration of modified universal soil loss equation (MUSLE) into a gis framework to assess soil erosion risk. Land Degradation and Development, 20(1), 84–91. https://doi.org/10.1002/ldr.893.

    Article  Google Scholar 

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  1. Department of Geography, Suri Vidyasagar College, Suri, West Bengal, India

    Hemanta Sutradhar

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Sutradhar, H. Identification of soil erosion-prone areas and annual average soil loss of Siddheswari River basin, Eastern India. J. Sediment. Environ. 8, 587–604 (2023). https://doi.org/10.1007/s43217-023-00149-3

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