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Process-based modelling of soil erosion: scope and limitation in the Indian context


Affiliations
1 ICAR-Indian Institute of Soil and Water Conservation, Dehradun 248 195, India; Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221 005, India
2 Indian Institute of Remote Sensing, Indian Space Research Organization, Dehradun 248 001, India
3 ICAR-Indian Institute of Soil and Water Conservation, Dehradun 248 195, India
4 Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221 005, India
 

The conservation and sustainability of natural resources, particularly soil and water, are crucial for agricultural yield and livelihood. Soil erosion models simulate the influence of existing farm management patterns as well as soil conservation interventions affecting soil erosion rates and accordingly recommend appropriate management techniques. The erosion models might be helpful for forecasting soil erosion, sediment load and evaluating the effectiveness of conservation measures. Although numerous empirical, conceptual or physical process-based models are used to study soil erosion, they differ in respect of input data requirements, representation of physical processes, sediment yield, and limitations due to their spatial and temporal variations. Due to limitations in empirical models in describing the erosion process, some pro­cess-based models may be used to quantify the state of soil erosion in a region. Before use, the available erosion models must be evaluated and validated for local circumstances. In this respect, the present study has been carried out to provide a critical review of various soil erosion models used worldwide, having different climatic parameters for determining soil erosion rate, run-off and sediment yield status.

Keywords

Conservation measures, natural resources, process-based models, run-off, sediment yield, soil erosion.
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  • Lal, R., Soil erosion and the global carbon budget. Environ. Int., 2003, 29(4), 437–450.

  • Maji, A. K., Reddy, G. O. and Sarkar, D., Degraded and wastelands of India: status and spatial distribution. Indian Council of Agricultural Research and National Academy of Agricultural Science, New Delhi, 2010, p. 158.

  • Narayana, D. V. and Babu, R., Estimation of soil erosion in India. J. Irrig. Drain. Eng., 1983, 109(4), 419–434.

  • Sehgal, J. L. and Abrol, I. P., Soil Degradation in India: Status and Impact, Oxford and IBH Publishing Company Pvt Ltd, New Delhi, 1994, p. 80.

  • Singh, R. K., Panda, R. K., Satapathy, K. K. and Ngachan, S. V., Simulation of runoff and sediment yield from a hilly watershed in the eastern Himalaya, India using the WEPP model. J. Hydrol., 2011, 405(3–4), 261–276.

  • Sharda, V. N. and Ojasvi, P. R., A revised soil erosion budget for India: role of reservoir sedimentation and land-use protection measures. Earth Surf. Process. Landf., 2016, 41(14), 2007–2023.

  • Sharda, V. N., Dogra, P. and Prakash, C., Assessment of production losses due to water erosion in rainfed areas of India. J. Soil Water Conserv., 2010, 65(2), 79–91.

  • Montgomery, D. R., Soil erosion and agricultural sustainability. Proc. Natl. Acad. Sci., 2007, 104(33), 13268–13272.

  • Toy, T. J., Foster, G. R. and Renard, K. G., Soil Erosion: Processes, Prediction, Measurement, and Control, John Wiley, 2002. 10. Jain, S. K., Kumar, S. and Varghese, J., Estimation of soil erosion for a Himalayan watershed using GIS technique. Water Resour. Manage., 2001, 15(1), 41–54.

  • Morgan, R. P. C., Soil Erosion and Conservation, Blackwell, Oxford, UK, 2005.

  • Bhattacharyya, R., Ghosh, B., Mishra, P., Mandal, B., Rao, C., Sarkar, D. and Franzluebbers, A., Soil degradation in India: challenges and potential solutions. Sustainability, 2015, 7, 3528–3570.

  • Quine, T. A. and Van Oost, K., Quantifying carbon sequestration as a result of soil erosion and deposition: retrospective assessment using caesium‐137 and carbon inventories. Global Change Biol., 2007, 13(12), 2610–2625.

  • Berhe, A. A., Harte, J., Harden, J. W. and Torn, M. S., The significance of the erosion-induced terrestrial carbon sink. BioScience, 2007, 57(4), 337–346.

  • Doetterl, S., Berhe, A. A., Nadeu, E., Wang, Z., Sommer, M. and Fiener, P., Erosion, deposition and soil carbon: a review of process-level controls, experimental tools and models to address C cycling in dynamic landscapes. Earth-Sci. Rev., 2016, 154, 102–122.

  • VanOost, K. et al., The impact of agricultural soil erosion on the global carbon cycle. Science, 2007, 318(5850), 626–629.

  • Lal, R., Accelerated soil erosion as a source of atmospheric CO2. Soil Till. Res., 2019, 188, 35–40.

  • Lal, R. and Pimentel, D., Letter on ‘Soil erosion: a carbon sink or source?’ Science, 2008, 319, 1040–1041.

  • Harden, J. W., Sharpe, J. M., Parton, W. J., Ojima, D. S., Fries, T. L., Huntington, T. G. and Dabney, S. M., Dynamic replacement and loss of soil carbon on eroding cropland. Global Biogeochem. Cycles, 1999, 13(4), 885–901.

  • Sankar, M., Soil redistribution impacts on the spatial variation of nutrients, net carbon exchange with the atmosphere and soil respiration rates in highly eroding agricultural fields from the foothills of the Indian Himalaya. Ph.D. thesis submitted to the University of Exeter, UK, 2016.

  • Doetterl, S., Six, J., Van Wesemael, B. and VanOost, K., Carbon cycling in eroding landscapes: geomorphic controls on soil organic C pool composition and C stabilization. Global Change Biol., 2012, 18(7), 2218–2232.

  • Sankar, M., Hartley, I. P., Cressey, E. L., Dungait, J. A. and Quine, T. A., Soil burial reduces decomposition and offsets erosion-induced soil carbon losses in the Indian Himalaya. Global Change Biol., 2021, 28(4), 1643–1658.

  • Patra, S. et al., Watershed-scale runoff–erosion–carbon flux dynamics: current scope and future direction of research. Curr. Sci., 2015, 109(10), 1773.

  • Kumar, S., Geospatial approach in modeling soil erosion processes in predicting soil erosion and nutrient loss in hilly and mountainous landscape. In Remote Sensing of Northwest Himalayan Ecosystems, Springer, Singapore, 2019, pp. 355–380.

  • Tiwari, A. K., Risse, L. M. and Nearing, M. A., Evaluation of WEPP and its comparison with USLE and RUSLE. Trans. ASAE, 2000, 43(5), 1129.

  • Kumar, S., Harjadib, B. and Patel, N. R., Modeling approach in soil erosion risk assessment and conservation planning in hilly watershed using remote sensing and GIS. ISPRS Arch., 2006, 36(4), 25–30.

  • Chandramohan, T., Venkatesh, B. and Balchand, A. N., Evaluation of three soil erosion models for small watersheds. Aquat. Procedia, 2015, 4, 1227–1234.

  • Galy, A. and Lanord, C. F., Higher erosion rates in the Himalaya: geochemical constraints on riverine fluxes. J. Conf. Abstr., 2000, 5, 423.

  • Wischmeier, W. H. and Smith, D. D., Predicting Rainfall Erosion Losses: A Guide to Conservation Planning, USDA Handbook No. 537, Washington DC, USA, 1978.

  • Bera, A., Assessment of soil loss by universal soil loss equation (USLE) model using GIS techniques: a case study of Gumti River Basin, Tripura, India. Model. Earth Syst. Environ., 2017, 3(1), 29.

  • Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K. and Yoder, D. C., Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE), Agriculture Hand Book No. 703, USDA, Washington DC, USA, 1997.

  • Jain, M. K. and Das, D., Estimation of sediment yield and areas of soil erosion and deposition for watershed prioritization using GIS and remote sensing. Water Resour. Manage., 2010, 24(10), 2091– 2112.

  • Thomas, J., Joseph, S. and Thrivikramji, K. P., Estimation of soil erosion in a rain shadow river basin in the southern Western Ghats, India using RUSLE and transport limited sediment delivery function. Int. Soil Water Conserv. Res., 2018, 6(2), 111–122.

  • Williams, J. R., Sediment-yield prediction with universal equation using runoff energy factor. In Present and Prospective Technology for Predicting Sediment Yield and Sources, Agricultural Research Service, S-40, USDA, Washington DC, USA, 1975.

  • Kumar, P. S., Praveen, T. V., Prasad, M. A. and Rao, P. S., Identification of critical erosion prone areas and computation of sediment yield using remote sensing and GIS: a case study on Sarada River Basin. J. Inst. Eng. (India): Ser. A, 2018, 99(4), 719–728.

  • Pandey, A., Chowdary, V. M. and Mal, B. C., Sediment yield modelling of an agricultural watershed using MUSLE, remote sensing and GIS. Paddy Water Environ., 2009, 7(2), 105–113.

  • Morgan, R. P. C., Morgan, D. D. V. and Finney, H. J., A predictive model for the assessment for the soil erosion risk. J. Agric. Eng. Res., 1984, 30, 245–253.

  • Mitasova, H., Hofierka, J., Zlocha, M. and Iverson, L. R., Modelling topographic potential for erosion and deposition using GIS. Int. J. Geogr. Inf. Syst., 1996, 10, 629–641.

  • Kumar, S. and Kushwaha, S. P. S., Modelling soil erosion risk based on RUSLE-3D using GIS in a Shivalik sub-watershed. J. Earth Syst. Sci., 2013, 122(2), 389–398.

  • Nearing, M. A., Foster, G. R., Lane, L. J. and Finkner, S. C., A process-based soil erosion model for USDA-Water Erosion Prediction Project technology. Trans. ASAE, 1989, 32(5), 1587–1593.

  • Majhi, A., Shaw, R., Mallick, K. and Patel, P. P., Towards improved USLE-based soil erosion modelling in India: a review of prevalent pitfalls and implementation of exemplar methods. EarthSci. Rev., 2021, 221, 103786.

  • Yu, B. and Rosewell, C. J., Evaluation of WEPP for runoff and soil loss prediction at Gunnedah, NSW, Australia. Aust. J. Soil Res., 2001, 39, 1131–1145.

  • Bowen, W., Baigorria, G., Barrera, V., Cordova, J., Muck, P. and Pastor, R., A process based model (WEPP) for simulation of soil erosion in the Andes. Critical Infrastructure Protection (CIP) Program Report, International Potato Center, Peru, 1998, pp. 403–408.

  • Sankar, M. et al., Nationwide soil erosion assessment in India using radioisotope tracers 137Cs and 210Pb: the need for fallout mapping. Curr. Sci., 2018, 115(3), 388–390.

  • Singh, R. K., Mishra, A. K. and Satapathy, K. K., Application of WEPP hydrologic simulation model for prediction of rainfall and runoff from hilly watersheds in Meghalaya. J. Agric. Eng., 2009, 46(1), 16–22.

  • Beasley, D. B., Huggins, L. F. and Monke, A., ANSWERS: a model for watershed planning. Trans. ASAE, 1980, 23(4), 938–944.

  • Williams, J. R., Jones, C. A. and Dyke, P. T., A modeling approach to determine the relationship between erosion and soil productivity. Trans. ASAE, 1984, 27(1), 129–144.

  • Lopes, V. L., A numerical model of watershed erosion and sediment yield (Dissertation of Doctoral degree), University of Arizona Graduate College, USA, 1987.

  • Young, R. A., Onstad, C. A., Bosch, D. D. and Anderson, W. P., AGNPS: a nonpoint-source pollution model for evaluating agricultural watersheds. J. Soil Water Conserv., 1989, 44(2), 168–173.

  • Woolhiser, D. A., Smith, R. E. and Goodrich, D. C., KINEROS – A Kinematic Runoff and Erosion Model: Documentation and User Manual, Report No. ARS-77. USDA, Washington, DC, USA, 1990.

  • Morgan, R. P. C., Quinton, I. N. and Rickson, R. J., EUROSEM: A User Guide, Silsoe College, Cranfield University, UK, 1993, p. 83.

  • Flanagan, D. C. and Nearing, M. A. (eds), USDA-Water Erosion Prediction Project: Hillslope Profile and Watershed Model Documentation, NSERL Report No. 10, USDA-ARS National Soil Erosion Research Laboratory, West Lafayette, Indiana, USA, 1995.

  • Williams, J. R. and Izaurralde, R. C., The APEX model. In Watershed Models (eds Singh, V. P. and Frevert, D. K.), CRC Press, Boca Raton, Fla, USA, 2006, pp. 437–482.

  • Bhuyan, S. J., Kalita, P. K., Janssen, K. A. and Barnes, P. L., Soil loss predictions with three erosion simulation models. Environ. Modell. Software, 2002, 17(2), 137–146.

  • Pandey, A., Himanshu, S. K., Mishra, S. K. and Singh, V. P., Physically based soil erosion and sediment yield models revisited. Catena, 2016, 147, 595–620.

  • Dun, S., Wu, J. Q., Elliot, W. J., Robichaud, P. R. and Flanagan, D. C., Adapting the Water Erosion Prediction Project (WEPP) model to forest conditions. In International Meeting of the American Society of Agricultural and Biological Engineers, Portland, USA, 2006, pp. 9–12.

  • Soto, B. and Fierros, F., Runoff and soil erosion from areas of burnt scrub: comparison of experimental results with those predicted by the WEPP model. Catena, 1998, 31(4), 257–270.

  • Huggins, L. F. and Monke, E. J., The mathematical simulation of the hydrology of small watersheds. Technical Report 1, Water Resources Research Center, Purdue University, West Lafayette, IN, USA, 1966, p. 130.

  • Meyer, L. D. and Wischmeier, W. H., Mathematical simulation of the processes of soil erosion by water. Trans. ASAE, 1969, 12(6), 754–758.

  • Morgan, R. P. C. et al., The European Soil Erosion Model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments. Earth Surf. Process. Landf., 1998, 23(6), 527–544.

  • Mein, R. G. and Larson, C. L., Modeling infiltration during a steady rain. Water Resour. Res., 1973, 9(2), 384–394.

  • Ramsankaran, R., Kothyari, U. C. and Rawat, J. S., Simulation of surface runoff and sediment yield using the water erosion prediction project (WEPP) model: a study in Kaneli watershed, Himalaya, India/Simulation de ruissellement de surface et d’érosion àl’aide du modèle WEPP: cas du bassin versant de Kaneli, Himalaya, Inde. Hydrol. Sci. J., 2009, 54(3), 513–525.

  • Pandey, A., Chowdary, V. M., Mal, B. C. and Billib, M., Application of the WEPP model for prioritization and evaluation of best management practices in an Indian watershed. Hydrol. Process. Int. J., 2009, 23(21), 2997–3005.

  • Pandey, A., Chowdary, V. M., Mal, B. C. and Billib, M., Runoff and sediment yield modeling from a small agricultural watershed in India using the WEPP model. J. Hydrol., 2008, 348(3–4), 305–319.

  • Chen, V. J. and Kuo, C. Y., A study on synthetic sediment graphs for ungauged watersheds. J. Hydrol., 1986, 84, 35–54.

  • Kumar, S. and Sterk, G., Process based modeling in understanding erosion processes and soil erosion assessment at hillslope scale in the lesser Himalayas, India. In Proceedings of the International Conference on Hydrological Perspectives for Sustainable Development, Roorkee, 2005, pp. 420–427.

  • Kumar, S., Sterkb, G. and Dadhwal, V. K., Process based modeling for simulating surface runoff and soil erosion at watershed basis. Commission VI, WG VI/4, Indian Institute of Remote Sensing, Dehradun, 2005.

  • Sharma, S. P., Simulation of runoff from small watersheds in Shivalik foot-hills using WEPP model. Master of Technology, College of Agricultural Engineering and Technology, PAU, Ludhiana, 2012.

  • Sharma, K. D. and Singh, S., Satellite remote sensing for soil erosion modelling using the ANSWERS model. Hydrol. Sci. J., 1995, 40(2), 259–272.

  • Singh, R., Tiwari, K. N. and Mal, B. C., Hydrological studies for small watershed in India using the ANSWERS model. J. Hydrol., 2006, 318(1–4), 184–199.

  • Li, P., Mu, X., Holden, J., Wu, Y., Irvine, B., Wang, F., Gao, P., Zhao, G. and Sun, W., Comparison of soil erosion models used to study the Chinese Loess Plateau. Earth-Sci. Rev., 2017, 170, 17–30.

  • Flanagan, D. C., Frankenberger, J. R. and Ascough II, J. C., WEPP: Model use, calibration, and validation. Trans. ASABE, 2012, 55(4), 1463–1477.

  • Lier, Q. D. J., Sparovek, G., Flanagan, D. C., Bloem, E. M. and Schnug, E., Runoff mapping using WEPP erosion model and GIS tools. Comput. Geosci., 2005, 31(10), 1270–1276.

  • Flanagan, D. C., Frankenberger, J. R., Cochrane, T. A., Renschler, C. S. and Elliot, W. J., Geospatial application of the water erosion prediction project (WEPP) model. Trans. ASABE, 2013, 56(2), 591–601.

  • Flanagan, D. C. and Livingston, S. J., WEPP User Summary (Vol. 11), NSERL Report, 1995.

  • Wainwright, J. and Mulligan, M., Environmental Modelling: Finding Simplicity in Complexity, Wiley-Blackwell Publishing Ltd, Chichester, UK, 2013.


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  • Process-based modelling of soil erosion: scope and limitation in the Indian context

Abstract Views: 362  |  PDF Views: 159

Authors

Saswat Kumar Kar
ICAR-Indian Institute of Soil and Water Conservation, Dehradun 248 195, India; Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221 005, India
Suresh Kumar
Indian Institute of Remote Sensing, Indian Space Research Organization, Dehradun 248 001, India
M. Sankar
ICAR-Indian Institute of Soil and Water Conservation, Dehradun 248 195, India
S. Patra
ICAR-Indian Institute of Soil and Water Conservation, Dehradun 248 195, India
R. M. Singh
Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221 005, India
S. S. Shrimali
ICAR-Indian Institute of Soil and Water Conservation, Dehradun 248 195, India
P. R. Ojasvi
ICAR-Indian Institute of Soil and Water Conservation, Dehradun 248 195, India

Abstract


The conservation and sustainability of natural resources, particularly soil and water, are crucial for agricultural yield and livelihood. Soil erosion models simulate the influence of existing farm management patterns as well as soil conservation interventions affecting soil erosion rates and accordingly recommend appropriate management techniques. The erosion models might be helpful for forecasting soil erosion, sediment load and evaluating the effectiveness of conservation measures. Although numerous empirical, conceptual or physical process-based models are used to study soil erosion, they differ in respect of input data requirements, representation of physical processes, sediment yield, and limitations due to their spatial and temporal variations. Due to limitations in empirical models in describing the erosion process, some pro­cess-based models may be used to quantify the state of soil erosion in a region. Before use, the available erosion models must be evaluated and validated for local circumstances. In this respect, the present study has been carried out to provide a critical review of various soil erosion models used worldwide, having different climatic parameters for determining soil erosion rate, run-off and sediment yield status.

Keywords


Conservation measures, natural resources, process-based models, run-off, sediment yield, soil erosion.

References





DOI: https://doi.org/10.18520/cs%2Fv122%2Fi5%2F533-541