Estimation of Soil Erosion by RUSLE Model Using Geoinformatics Techniques: A Case Study of Mulshi Reservoir Catchment, Pune District, Western Maharashtra.

Authors

  • M S Khobragade Post Graduate Teaching and Research Center, Department of Geography, Sir Parashurambhau College (Autonomous), Tilak Road, Pune-411 030, India.
  • Gajanan Dhobale Head, Department of Geography, Arts, science and commerce College, Indapur-413 106, India.

DOI:

https://doi.org/10.58825/jog.2024.18.2.150

Keywords:

Soil Erosion, RUSLE, Land Use and Land Cover, Geoinformatics, GIS, Reservoir Sedimentation, Western maharashtra

Abstract

In the western part of Maharashtra, where the Western Ghat highlands are located, soil erosion is a serious and persistent environmental issue. To make matters worse, the majority of the dams in this region run the risk of sedimenting their reservoirs, which is a serious concern. This research was being conducted on the Mulshi reservoir catchment area, Pune district of western Maharashtra having area of 250.25 km2. It is fact that the surface runoff of seasonal rainfall is more in this region due to the presence of western ghats. In this study, high resolution satellite images were used to estimate average annual soil erosion based on the five factors defined in the Revised Universal Soil Loss Equation (RUSLE) with the help of Geoinformatics techniques. Overlay of five parameters, viz., rainfall erosivity factor (R), soil erodibility factor (K), slope length and steepness factor (LS), cover and management factor (C) and support & conservations practices factor (P) has been done in ArcGIS (version 10.8) software. Annual average soil erosion of the catchment is 0 to 433.43 tons/hector/year and has been classified into Six categories, defined as very high, high, moderate, low, and very low and negligible according to the severity of erosion. The high values of soil erosion (>20 tons/hector/year) found on the highlands due to the high slope and bare lands. however, low values (<10 tons/hector/year) are found on the area occupied by reservoir and dense vegetation.

References

Ashiagbor G., E. K. Forkuo and R. Aabeyir (2013). Modeling soil erosion using RUSLE and GIS tools. International Journal of Remote Sensing & Geoscience (IJRSG), 2(4). www.ijrsg.com

Benavidez R., B. Jackson, D. Maxwell K. Norton (2018). A review of the (Revised) Universal Soil Loss Equation ((R)USLE): With a view to increasing its global applicability and improving soil loss estimates. Hydrology and Earth System Sciences, 22(11), 6059–6086. https://doi.org/10.5194/hess-22-6059-2018

Djoukbala O., M. Hasbaia, O. Benselama and M. Mazour (2019). Comparison of the erosion prediction models from USLE, MUSLE and RUSLE in a Mediterranean watershed, case of Wadi Gazouana (N-W of Algeria). Modeling Earth Systems and Environment,5(2),725–743. https://doi.org/10.1007/s40808-018-0562-6

Durigon V. L., D. F. Carvalho, M. A. H. Antunes, P. T. S. Oliveira and M. M. Fernandes (2014). NDVI time series for monitoring RUSLE cover management factor in a tropical watershed. International Journal of RemoteSensing,35(2),441–453. https://doi.org/10.1080/01431161.2013.871081

Eng M. (2001). Application of RUSLE model on global soil erosion estimate Thai Nam PHAM1, Dawen YANG2, Shinjiro KANAE3, Taikan OKI4, and Katumi musiake5 1 Student Member. In Annual Journal of Hydraulic Engineering (Vol. 45).

Ghosal K. and S. D. Bhattacharya (2020). A Review of RUSLE Model. In Journal of the Indian Society of Remote Sensing (Vol. 48, Issue 4, pp.689–707). Springer.https://doi.org/10.1007/s12524-019-01097-0

Ghosh A., S. Rakshit, S. Tikle., S. Das., U. Chatterjee, C. B. Pande, A. Alataway, A. A. Al-Othman, A. Z. Dewidar and M. A. Mattar (2023). Integration of GIS and Remote Sensing with RUSLE Model for Estimation of SoilErosion.Land,12(1). https://doi.org/10.3390/land12010116

Hurni H., K. Herweg, B. Portner and H. Liniger (2008.). Chapter 4 Soil Erosion and Conservation in Global Agriculture.

Kalman R (1967) Essai d’évaluation pour le pré-Rif du facteur couver- ture végétale de la formule de Wischmeier de calcul de l’érosion. Rapport Rabat 1–12.

Karthick P. and R. Periyasamy (2017). Estimation of soil erosion vulnerability in Perambalur Taluk, Tamilnadu using revised universal soil loss equation model (RUSLE) and geo information technology. www.isca.in

Kurothe R. S., O. Challa, J. S. Sharma and M. Velayatham (2001) Assessment of soil erosion in Maharashtra. Indian J. Soil Cons. 29(2): 133-137.

Mahabaleshwara H. and H. M. Nagabhushan (2014). A study on soil erosion and its impacts on floods and sedimentation.IJRET: International Journal of Research in Engineering and Technology. http://www.ijret.org

Marondedze A. and S. Brigitta (2020). Assessment of Soil Erosion Using the RUSLE Model for the Epworth District of the Harare Metropolitan Province, Zimbabwe. Sustainability. 12. 8531. 10.3390/su12208531.

Parveen R and U. Kumar (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. Journal of Geographic Information System 4: 588–96.

Raj R., M. Saharia and S. Chakma (2024). Geospatial modeling and mapping of soil erosion in India. CATENA,107996.https://doi.org/10.1016/j.catena.2024.107996

Renard K., G. Foster, G. Weesies, D. McCool and D. Yoder (1997). Predicting Soil Erosion by Water: a Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). US Government Printing Office, Washington, DC.

Saha A. (2018). GIS Based Soil Erosion Estimation Using Rusle Model: A Case Study of Upper Kangsabati Watershed, West Bengal, India. International Journal of Environmental Sciences & Natural Resources, 13(5). https://doi.org/10.19080/ijesnr.2018.13.555871.

Simms A. D., C. D. Woodroffe and B. G. Jones (2003) Application of RUSLE for erosion management in a costal catchment, Southern NSW. In: Proceedings of the international congress on modeling and simulation: integrative modeling of biophysical, social and eco-nomic systems for resource management solutions, Australia, pp 678–683.

Singh G, S. Chandra and R. Babu (1981). Soil Loss and Pre-diction Research in India. Bulletin No T-12/D9 Central Soil and Water Conservation Research Training Institute Dehradun.

Thapa P. (2020). Spatial estimation of soil erosion using RUSLE modeling: a case study of Dolakha district, Nepal.EnvironmentalSystemsResearch,9(1).https://doi.org/10.1186/s40068-020-00177-2.

Williams J. R. (1975). Sediment-yield prediction with Universal Equation using runoff energy factor, present and prospective technology for predicting sediment yield and sources. ARS-S-40. Brooksville, FL: US Department of Agriculture, Agricultural Research Service, 244–252.

Williams J. R. (1995). The EPIC model. In V. P. Singh (Ed.), Computer models of watershed hydrology (pp. 909-1000). Water Resouces publication, Highlands Ranck, CO.

Wischmeier W. H. and D. D. Smith (1978). Predicting Rainfall Erosion Losses: a Guide to Conservation Planning. Agriculture Handbook 282. USDA-ARS, USA

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Published

2024-10-30

How to Cite

Khobragade, M., & Dhobale, G. (2024). Estimation of Soil Erosion by RUSLE Model Using Geoinformatics Techniques: A Case Study of Mulshi Reservoir Catchment, Pune District, Western Maharashtra. Journal of Geomatics, 18(2), 89–96. https://doi.org/10.58825/jog.2024.18.2.150