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Quantitative Determination of Soil Erosion and Prioritization of Micro-Watersheds Using Remote Sensing and GIS

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Abstract

Soil erosion which occurs at spatially varying rate is a widespread threat to sustainable resource management at watershed scale. Thus estimation of soil loss and identification of critical area for implementation of best management practice is central to success of soil conservation programme. The present study focuses application of most widely used Universal Soil Loss Equation (USLE) to determine soil erosion and prioritization of micro-watersheds of Upper Damodar Valley Catchment (UDVC) of India. Annual average soil loss for the entire basin is 23.17 t/ha/yr; for micro-watersheds. High soil loss is observed in 345 micro-watersheds, medium in 159 micro-watersheds and low soil loss is observed in 201 micro-watersheds. It is found that, out of 705 micro-watersheds of UDVC, 453 micro-watersheds are in agreement with AISLUS suggested priority which is based on observed sediment yield, 116 micro-watersheds under predict and 136 micro-watersheds over predict the priority. Geographic Information System (GIS) is applied to prepare various layers of USLE parameters which interactively estimate soil erosion at micro-watershed level. The main advantage of the GIS methodology is in providing quick information on the estimated value of soil loss for any part of the investigated area.

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References

  • Bali, Y. P., & Karale, R. L. (1977). A sediment yield index for choosing priority basins. IAHS-AISH Publication, 222, 180.

    Google Scholar 

  • Carpenter, S. R. (1996). Microcosm experiments have limited relevance for community and ecosystem ecology. Journal of Ecology, 77, 677–680.

    Article  Google Scholar 

  • Chowdary, V. M., Yatindranath, S., & Adiga, S. (2004). Modelling of non-point source pollution in a watershed using remote sensing and GIS. Journal of the Indian Society of Remote Sensing, 32(1), 59–73.

    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, 1783–1798.

    Article  Google Scholar 

  • Deore, S. J. (2005). Prioritization of Micro-watersheds of Upper Bhama Basin on the Basis of Soil Erosion Risk Using Remote Sensing and GIS Technology. Ph. D. thesis submitted to Department of Geography, University of Pune, India.

  • Dickinson, A., & Collins, R. (1998). Predicting erosion and sediment yield at the catchment scale. In Penning de Vries FWT, F. Agus, & J. Kerr (Eds.), Soil erosion at multiple scales, principles and methods for assessing causes and impact (pp. 317–342). Wallingford, UK: CABI. in association with the International Board for Soil Research and Management.

    Google Scholar 

  • European Environment Agency. (1995). CORINE Soil erosion risk and important land resources - in the southern regions of the European Community, Commission of the European Communities.

  • Fistikoglu, O., & Harmancioglu, N. B. (2002). Integration of GIS with USLE in assessment of soil erosion. Water Resources Management, 16, 447–467.

    Article  Google Scholar 

  • Griffin, M. L., Beasley, D. B., Fletcher, J. J., & Foster, G. R. (1988). Estimating soil loss on topographically non-uniform field and farm units. Journal of Soil and Water Conservation, 43, 326–331.

    Google Scholar 

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

    Article  Google Scholar 

  • Jain, S. K., Kumar, S., & Varghese, J. (2001). Estimation of soil erosion for a Himalayan watershed using GIS technique. Water Resources Management, 15, 41–54.

    Article  Google Scholar 

  • Javed, A., Khanday, M. Y., & Ahmed, R. (2009). Prioritization of sub-watersheds based on Morphometric and land use analysis using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing, 37, 261–274.

    Article  Google Scholar 

  • Mani, P., & Chakravorty, B. (2007). Remote sensing based sedimentation study of Maithon reservoir. Journal of the Indian Society of Remote Sensing, 35(1), 118–120.

    Article  Google Scholar 

  • Martin, D., & Saha, S. K. (2007). Integrated approach of using remote sensing and GIS to study watershed prioritization and productivity. Journal of the Indian Society of Remote Sensing, 35(1), 21–30.

    Article  Google Scholar 

  • Misra, N., Satyanarayana, T., & Mukherjee, R. K. (1984). Effect of top elements on the sediment production rate from Sub-watershed in Upper Damodar Valley. Journal of Agricultural Engineering, 21(3), 65–70.

    Google Scholar 

  • Ni, S. X., Ma, G. B., Wei, Y. C., & Jiang, H. F. (2004). An indicator system for assessing soil erosion in the Loess Plateau gully regions: a case study in the Wangdonggou watershed of China. Pedosphere, 14, 37–44.

    Google Scholar 

  • Pandey, A., Chowdary, V. M., & Mal, B. C. (2004). Morphological analysis and watershed management using GIS. Hydrology Journal India, 27(3–4), 71–84.

    Google Scholar 

  • Pandey, V. K., Panda, S. N., Raghuwanshi, N. S., & Sudhakar, S. (2006). Delineation and parameterization of Banikdih watershed using remote sensing and AVSWAT model. Journal of the Indian Society of Remote Sensing, 34(2), 143–152.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Panigrahi, B., Senapati, P., & Behera, B. (1996). Development of erosion index model from daily rainfall data. Journal of Applied Hydrology, 9(1 and 2), 17–22.

    Google Scholar 

  • Quine, T. A., & Zhang, Y. (2002). An investigation of spatial variation in soil erosion, soil properties, and crop production within an agricultural field in Devon, United Kingdom. Journal of Soil and Water Conservation, 57, 55–65.

    Google Scholar 

  • Renschler, C., Diekkruger, B., & Mannaerts, C. (1997). Regionalization in surface runoff and soil erosion risk evaluation in regionalization of hydrology. IAHS-AISH Publ, 254, 233–241.

    Google Scholar 

  • Wischmeier, W. H. (1959). A rainfall erosion index for universal soil loss equation. Proceedings of American Soil Science Society, 23, 246–249.

    Article  Google Scholar 

  • Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses- a guide to conservation planning. Agricultural Handbook No. 537, USDA.

  • Wischmeier, W. H., Johnson, C. B., & Cross, B. V. (1971). A soil erodibility nomograph from farmland and construction sites. Journal of Soil and Water Conservation, 26, 189–193.

    Google Scholar 

  • Yoshino, K., & Ishioka, Y. (2005). Guidelines for soil conservation towards integrated basin management for sustainable development: a new approach based on the assessment of soil loss risk using remote sensing and GIS. Journal of Paddy and Water Environment, 3, 235–247.

    Article  Google Scholar 

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Acknowledgements

Authors are thankful to Sanjay Kumar, Joydeep Biswas of Soil Conservation office, Damodar Valley Corporation (DVC), Hazaribag for providing necessary field data.

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Correspondence to Arabinda Sharma.

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Shinde, V., Sharma, A., Tiwari, K.N. et al. Quantitative Determination of Soil Erosion and Prioritization of Micro-Watersheds Using Remote Sensing and GIS. J Indian Soc Remote Sens 39, 181–192 (2011). https://doi.org/10.1007/s12524-011-0064-8

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