Skip to main content

Advertisement

SpringerLink
Log in

Mapping of Soil erosion and Probability Zones using Remote Sensing and GIS in Arid part of South Deccan Plateau, India

  • Research Article
  • Published:
Journal of the Indian Society of Remote Sensing Aims and scope Submit manuscript

Abstract

The Revised Universal Soil Loss Equation (RUSLE) model by using a large-scale soil mapping dataset, remote sensing, and GIS techniques were adopted to determine the soil erosion vulnerability in part of South Deccan Plateau, India. Based on the detailed soil survey information, 11 soil series were identified, and R, K, LS, C, P factors were computed to assess the soil erosion. Results revealed that annual soil loss was extremely severe (> 40 t/ha/yr) and very severe (20–40 t/ha/yr) in 447.2 ha (15.19%) and 314.3 ha (10.68%) in kharif and 502.73 ha (17.1%) and 907.74 ha (30.8%) in rabi season, respectively. Among the soil series, Mittapalle (MTP) series (17.9%) was highly prone to erosion followed by Venukayagayyapalle (VGP) (16.55%) and Inagalur (IGR) (13.57%) series in both seasons. The Weighted Index Overlay technique was adopted to estimate the soil erosion probability zones and the result showed that erosion risk was high in 8.90% area, medium in 55%, and low in 35% area. Spatial assessment of soil erosion using plot-wise information is a key factor for identifying site-specific suitable soil conservation measures for sustainable crop production.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig.7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Atalay, I. (2016). A new approach to the land capability classification: Case study of Turkey. Procedia Environmental Sciences, 32, 264–274.

    Article  Google Scholar 

  • Ayoubi, S., Mokhtari, J., Mosaddeghi, M. R., & Zeraatpisheh, M. (2018). Erodibility of calcareous soils as influences by land use and intrinsic soil properties in a semi-arid region of central Iran. Environmental Monitoring and Assessment, 190(4), 192.

    Article  Google Scholar 

  • Babur, E., Uslu, Ö. S., Battaglia, M. L., Diatta, A., Fahad, S., Datta, R., Zafar-ul-Hye, M., Hussain, G. S., & Danish, S. (2021). Studying soil erosion by evaluating changes in physico-chemical properties of soils under different land-use types. Journal of the Saudi Society of Agricultural Sciences. https://doi.org/10.1016/j.jssas.2021.01.005

    Article  Google Scholar 

  • Bennett, J. P., Palmer, A., & Blackett, M. (2012). Range degradation and land tenure change: Insights from a ‘released’ communal area of Eastern Cape Province South Africa. Land Degradation & Development, 23(6), 557–568.

    Article  Google Scholar 

  • Biswas, H., Raizada, A., Mandal, D., Kumar, S., Srinivas, S., & Mishra, P. K. (2015). Identification of areas vulnerable to soil erosion risk in India using GIS methods. Solid Earth, 6, 1247–1257. https://doi.org/10.5194/se-6-1247-2015

    Article  Google Scholar 

  • Boardman, J., & Poesen, J. (2006). Soil Erosion in Europe. Wiley.

    Book  Google Scholar 

  • Brady, N. C., & Weil, R. R. (2002). The Nature and Properties of Soils, 74. Prentice Hall.

    Google Scholar 

  • Choudhury, M. K., & Nayak, T. (2003). Estimation of soil erosion in Sagar Lake catchment of Central India. In Proceedings of the international conference on water and environment (pp. 387–392). Bhopal, India.

  • D’Odorico, P., Okin, G. S., & Bestelmeyer, B. T. (2012). A synthetic review of feedbacks and drivers of shrub encroachment in arid grasslands. Ecohydrology, 5, 520–530.

    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.

    Article  Google Scholar 

  • Efe, R., Ekincl, D., & Curebal, I. (2008). Erosion analysis of Sahin Creek Watershed (NW of Turkey) using GIS based on RUSLE (3D) Method. Journal of Applied Sciences, 8, 49–58. https://doi.org/10.3923/jas.2008.49.58.

    Article  Google Scholar 

  • FAO. (2011). The state of the world’s land and water resources for food and agriculture (SOLAW). Managing systems at risk. Rome and Earth scan, London: Food and Agriculture Organization of the United Nations.

  • Fu, B., Liu, Y., Lu, Y., He, C., Zeng, Y., & Wu, B. (2011). Assessing the soil erosion control service of ecosystems change in the Loess Plateau of China. Ecological Complexity, 8(4), 284–293.

    Article  Google Scholar 

  • Fu, B. J., Zhao, W. W., Chen, L. D., Zhang, Q. J., Lu, 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 Degradation and Development, 16(1), 73–85.

    Article  Google Scholar 

  • Ganasri, B. P., & Ramesh, H. (2015). Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin. Geoscience Frontiers, 7(6), 1–9. https://doi.org/10.1016/j.gsf.2015.10.007

    Article  Google Scholar 

  • Gates, J. B., Scanlon, B. R., Mu, X., & Zhang, L. (2011). Impacts of soil conservation on groundwater recharge in the semi-arid Loess Plateau China. Hydrogeology Journal, 19(4), 865–875.

    Article  Google Scholar 

  • Hegde, R., Niranjana, K. V., Srinivas, S., Danorkar, B. A., & Singh, S. K. (2018). Site-Specific Land Resource Inventory for Scientific Planning of Sujala Watersheds in Karnataka. Current Science, 115(4), 644–652.

    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(1), 41–54.

    Article  Google Scholar 

  • Jasinski, M. F. (1990). “Sensitivity of the Normalized Difference Vegetation Index to Subpixel Canopy Cover, Soil Albedo, and Pixel Scale. Remote Sensing of Environment, 32(2–3), 169–187. https://doi.org/10.1016/0034-4257(90)90016-F

    Article  Google Scholar 

  • Karaburun, A. (2010). Estimation of C factor for soil erosion modeling using NDVI in Buyukcekmece watershed. Ocean Journal of Applied Sciences, 3(1), 77–85.

    Google Scholar 

  • Kim, H. S. (2006). Soil erosion modeling using RUSLE and GIS on the IMHA watershed, South Korea. Doctoral dissertation. Colorado State University, USA.

  • Kirkby, M. J., & Morgan, R. P. C. (1980). Soil Erosion, John Wiley and Sons, Chichester, West Sussex, UK, pp 312.

  • Kumar, S., & Kushwaha, S. P. S. (2013). Modelling soil erosion risk based on RUSLE-3D using GIS in a Shivalik sub-watershed. Journal of Earth System Science, 122, 389–398.

    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, 457–465.

    Article  Google Scholar 

  • Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2004). Remote Sensing and Image Interpretation (5th ed.). John Wiley & Sons Inc.

    Google Scholar 

  • Lu, D., Valladares, G. S., & Batistella, M. (2004). Mapping soil erosion risk in Rondonia, Brazilian Amazonia: Using RUSLE, remote sensing and GIS. Land Degradation and Development, 15, 499–512.

    Article  Google Scholar 

  • Maji, A. (2007). Assessment of degraded and wastelands of India. Journal of the Indian Society of Soil Science, 55, 427–435.

    Google Scholar 

  • Maji, A. K., Reddy, G. P. O., & Sarkar, D. (2010). Degraded and wastelands of India: Status and spatial distribution (p. 158). Directorate of Information and Publications of Agriculture.

    Google Scholar 

  • Manchanda, M. L., Kudrat, M., & Tiwari, A. K. (2002). Soil survey and mapping using remote sensing. Tropical Ecology, 43(1), 61–74.

    Google Scholar 

  • Mandal, D., & Sharda, V. N. (2011). Assessment of permissible soil loss in India employing a quantitative bio-physical model. Current Science, 100, 383–390.

    Google Scholar 

  • Maximillian, J., Brusseau, M.L., Glenn, E. P., & Matthias, A. D. (2019). Chapter 25—Pollution and environmental perturbations in the global system. In M. L. Brusseau, I. L. Pepper, C. P. Gerba (Eds.), Environmental and Pollution Science (3rd Edn, pp. 457–476), Academic Press.

  • Millward, A. A., & Mersey, J. E. (1999). Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. CATENA, 38, 109–129.

    Article  Google Scholar 

  • Moges, S. A., & Gebregiorgis, A. S. (2013). Climate Vulnerability on the Water Resources Systems and Potential Adaptation Approaches in East Africa: The Case of Ethiopia. Climate Vulnerability, 5, 335–345.

    Article  Google Scholar 

  • Moore, D., & 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.

    Google Scholar 

  • Moore, I. D., & Burch, G. J. (1986). Modeling Erosion and Deposition: Topographic Effects Transactions ASAE, 29, 1624.

    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 

  • Parveen, R., & Kumar, U. (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, 588–596.

    Article  Google Scholar 

  • Prasannakumar, V., Vijith, H., Abinod, S., & Geetha, N. (2012). Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, Using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology. Geoscience Frontiers, 3, 209–215.

    Article  Google Scholar 

  • Quinton, J. N., Govers, G., Van Oost, K., & Bardgett, R. D. (2010). The Impact of Agricultural Erosion on Biogeochemical Cycling. Nature Geo Science, 3, 311–314. https://doi.org/10.1038/ngeo838

    Article  Google Scholar 

  • Reddy, R. S., Nalatwadmath, S. K., & Krishnan, P. (2005). Soil Erosion Andhra Pradesh, NBSS Publ. No. 114, NBSSLUP, Nagpur, pp 76.

  • Reddy, R. S., Shiva Prasad, C. R., & Harindranath, C. S. (1996). Soils of Andhra Pradesh for optimizing land use, NBSS Publ. No. 69, Soils of India Series 8. Nagpur: NBSSLUP.

  • Renard, K. G., Foster, G. A., Weesies, D. A., Mccool, D. K., & Yoder, D. C. (1997). Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE) (agriculture handbook No. 703). Washington, DC: USDA.

  • Robert, P. S., & Hilborn, D. (2000). Factsheet: universal soil loss equation (USLE). Queen's printer for Ontario.

  • Sahu, N., Singh, S. K., Obi Reddy, G. P., Kumar, N., Nagaraju, M. S. S., & Srivastava, R. (2016). Large-Scale Soil Resource Mapping Using IRS-P6 LISS-IV and Cartosat-1 DEM in Basaltic Terrain of Central India. Journal of the Indian Society of Remote Sensing, 44(5), 811–819. https://doi.org/10.1007/s12524-015-0540-7

    Article  Google Scholar 

  • Scholes, M. C., & Scholes, R. J. (2013). Dust unto dust. Science, 342, 565–566. https://doi.org/10.1126/science.1244579

    Article  Google Scholar 

  • Sehgal, J., Mandal, D. K., Mandal, C., & Vadivelu, S. (1992). Agro-ecological regions of India, 2nd edn, Tech. Bull. No. 24, NBSSLUP, Nagpur, 130.

  • Senanayake, S., Pradhan, B., Huete, A., & Brennan, J. (2020). Assessing soil erosion hazards using land-use change and landslide frequency ratio method: A case study of sabaragamuwa province Sri Lanka. Remote Sensing, 12, 1483. https://doi.org/10.3390/rs12091483.

    Article  Google Scholar 

  • Sepuru, K., & Dube, T. (2018). An appraisal on the progress of remote sensing applications in soil erosion mapping and monitoring Terrence. Remote Sensing Applications: Society and Environment, 9, 1–9. https://doi.org/10.1016/j.rsase.2017.10.005

    Article  Google Scholar 

  • Shinde, V., Tiwari, K. N., Singh, M., & Anjushree. . (2010). Prioritization of micro watersheds on the basis of soil erosion hazard using remote sensing and geographic information system. International Journal of Water Resources and Environmental Engineering, 2(3), 130–136.

    Google Scholar 

  • Singh, G., Chandra, S., & Babu, R. (1981). Soil loss and prediction research in India. Central Soil and Water Conservation Research Training Institute, Bulletin No. T-12/D9.

  • Soil Survey Staff. (1999). Soil Taxonomy: a basic system of soil classification for making and interpreting soil surveys. In: Natural resources conservation service (agriculture handbook no. 436). 2nd edn. Washington, DC: USDA

  • Srivastava, R., & Saxena, A. K. (2004). Technique of large-scale soil mapping in basaltic terrain using satellite remote sensing data. International Journal of Remote Sensing, 25, 679–688.

    Article  Google Scholar 

  • Stanchi, S., Zecca, O., Hudek, C., Pintaldi, E., Viglietti, D., D’Amico, M. E., Colombo, N., Goslino, D., Letey, M., & Freppaz, M. (2021). Effect of Soil Management on Erosion in Mountain Vineyards (N-W Italy). Sustainability, 13, 1991. https://doi.org/10.3390/su13041991

    Article  Google Scholar 

  • Surya, J. N., Walia, C. S., Singh, H., Yadav, R. P., & Singh, S. K. (2020). Soil Suitability Evaluation Using Remotely Sensed Data and GIS: A Case Study from Kumaon Himalayas. Journal of the Indian Society of Remote Sensing. https://doi.org/10.1007/s12524-020-01143-2

    Article  Google Scholar 

  • Swarnkar, S., Malini, A., Tripathi, S., & Sinha, R. (2018). Assessment of uncertainties in soil erosion and sediment yield estimates at ungauged basins: An application to the Garra River basin, India. Hydrology and Earth System Sciences, 22, 2471–2485.

    Article  Google Scholar 

  • Thompson, M., Vlok, J., Rouget, M., Hoffman, M., Balmford, A., & Cowling, R. (2009). Mapping grazing-induced degradation in a semi-arid environment: A rapid and cost-effective approach for assessment and monitoring. Environmental Management, 43(4), 585–596.

    Article  Google Scholar 

  • Tirkey, A. S., Pandey, A. C., & Nathawat, M. S. (2013). Use of satellite data, GIS and RUSLE for estimation of average annual soil loss in Daltonganj watershed of Jharkhand (India). Journal of Remote Sensing Technology, 1(1), 20–30.

    Article  Google Scholar 

  • Tufa, M., Melese, A., & Tena, W. (2019). Effects of land use types on selected soil physical and chemical properties: The case of Kuyu District Ethiopia. Eurasian Journal of Soil Science, 8(2), 94–109.

    Google Scholar 

  • UNCCD secretariat. (2013). A Stronger UNCCD for a Land-Degradation Neutral World, Issue Brief, Bonn, Germany.

  • Verachtert, E., Van Den Eeckhaut, M., Poesen, J., & Deckers, J. (2010). Factors controlling the spatial distribution of soil piping erosion on loess-derived soils: A case study from central Belgium. Geomorphology, 118(3), 339–348.

    Article  Google Scholar 

  • Wang, L., Zheng, F., Liu, G., Zhang, X. J., Wilson, G. V., Shi, H., & Liu, X. (2021). Seasonal changes of soil erosion and its spatial distribution on a long gentle hillslope in the Chinese Mollisol region. International Soil and Water Conservation Research. https://doi.org/10.1016/j.iswcr.2021.02.001

    Article  Google Scholar 

  • Wang, L., Zheng, F., Zhang, X. J., Wilson, G. V., Qin, C., He, C., et al. (2020). Discrimination of soil losses between ridge and furrow in longitudinal ridge-tillage under simulated upslope inflow and rainfall. Soil and Tillage Research, 198, 104541.

    Article  Google Scholar 

  • Wawer, R., Nowocieñ, E., & Podolski, B. (2005). Real and Calculated K USLE Erodibility Factor for Selected Polish Soils. Polish Journal of Environmental Studies, 14(5), 655–658.

    Google Scholar 

  • Wieschmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses—A guide to conservation planning (agriculture handbook no. 537). Washington DC: USDA

  • Williams, J. R. (1995). Chapter 25: The EPIC model. In V.P. Singh (ed.) Computer models of watershed hydrology (pp. 909–1000). Water Resources Publications.

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

    Google Scholar 

  • Wischmeier, W. H., & Smith, D. D. (1978). Predicting Rainfall Erosion Losses: a Guide to Conservation Planning (agriculture handbook 282). USA: USDA-ARS.

  • Xu, Y., Shao, X., Kong, X., Peng, J., & Cai, Y. (2008). Adapting the RUSLE and GIS to model soil erosion risk in a mountain’s karst watershed, Guizhou Province, China. Environmental Monitoring and Assessment, 141, 275–286.

    Article  Google Scholar 

  • Zhang, J., Yang, M., Deng, X., Liu, Z., Zhang, F., & Zhou, W. (2018). Beryllium-7 measurements of wind erosion on sloping fields in the wind-water erosion crisscross region on the Chinese Loess Plateau. Science of the Total Environment, 615, 240–252.

    Article  Google Scholar 

  • Zhang, K., Li, S., Peng, W., & Yu, B. (2004). Erodibility of agricultural soils on the Loess Plateau of China. Soil & Tillage Research, 76(2), 157–165.

    Article  Google Scholar 

  • Zhang, X. C. (2017). Evaluating water erosion prediction project model using Cesium-137-derived spatial soil redistribution data. Soil Science Society of America Journal, 81(1), 179–188.

    Article  Google Scholar 

Download references

Acknowledgements

The present study is a part of the research project of “Andhra Pradesh Drought Mitigation Project” (APDMP) funded by the International Fund for Agricultural Development (IFAD). The authors thank to Government of Andhra Pradesh for their financial support.

Author information

Authors and Affiliations

  1. ICAR-National Bureau of Soil Survey & Land Use Planning, Regional Centre, Hebbal, Bangalore, 560024, Karnataka, India

    R. Srinivasan, K. S. Karthika, S. Amar Suputhra, M. Chandrakala & Rajendra Hegde

Authors
  1. R. Srinivasan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. S. Karthika
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Amar Suputhra
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. Chandrakala
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rajendra Hegde
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R. Srinivasan.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Srinivasan, R., Karthika, K.S., Suputhra, S.A. et al. Mapping of Soil erosion and Probability Zones using Remote Sensing and GIS in Arid part of South Deccan Plateau, India. J Indian Soc Remote Sens 49, 2407–2423 (2021). https://doi.org/10.1007/s12524-021-01396-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12524-021-01396-5

Keywords

Search

Navigation