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Soil Loss Estimation Using Different Empirical and Semi-empirical Models

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Climate Change Impact on Soil Erosion in Sub-tropical Environment

Abstract

“Soil erosion” caused by water is one of the most severe aspects of land degradation processes. This type of problem is more acute in the “subtropical environment” than in other parts of the world. The erosion of the topsoil is influenced by rainfall variability and anthropogenic activities. Soil erosion is presently recognized as a separate field for large-scale land degradation caused by soil loss across the world. Many academics from several disciplines have emphasized the need of using multiple approaches to assess the quantity of soil erosion. The empirical model can estimate the amount of soil loss from ground-based observations of the field site, but it takes a long time and is expensive. Apart from this most of the areas of the world are ungauged in nature facing the challenges for incorporating the necessary relevant data. For this purpose, the use of this model in a “GIS” integrated platform is rapidly increasing. This integrated model can produce nearly identical results across a wide range of variables, making it a reliable predictor. In recent times, the use of multiple predictive models in identical work has increased significantly, with the aim of determining which one is more reliable in terms of incorporating primary data. In this study, the application of “Universal Soil Loss Equation (USLE)”, “Revised Universal Soil Loss Equation (RUSLE)” and “Modified Universal Soil Loss Equation (MUSLE)” has been done to estimate the annul “soil loss” in Bengal Basin. From the analysis, the “RUSLE” gives the better outcome in comparison with “USLE” and “MUSLE”.

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References

  • Amsalu T, Mengaw A (2014) GIS based soil loss estimation using RUSLE model: the case of Jabi Tehinan Woreda, ANRS, Ethiopia. Nat Resour 2014

    Google Scholar 

  • Angima S, Stott D, O’Neill M et al (2003) Soil erosion prediction using RUSLE for central Kenyan highland conditions. Agric Ecosyst Environ 97:295–308

    Google Scholar 

  • Arekhi S, Niazi Y (2010) Assessment of GIS and RS applications to estimate soil erosion and sediment loading by using RUSLE model (case study: upstream basin of Ilam dam). J Soil Water Conserv 17:1–27

    Google Scholar 

  • Arnalds O, Barkarson B (2003) Soil erosion and land use policy in Iceland in relation to sheep grazing and government subsidies. Environ Sci Policy 6:105–113

    Article  Google Scholar 

  • Batista PV, Davies J, Silva ML, Quinton JN (2019) On the evaluation of soil erosion models: are we doing enough? Earth Sci Rev 197:102898

    Article  Google Scholar 

  • Belasri A, Lakhouili A (2016) Estimation of soil erosion risk using the universal soil loss equation (USLE) and geo-information technology in Oued El Makhazine watershed, Morocco. J Geogr Inf Syst 8:98

    Google Scholar 

  • Biesemans J, Van Meirvenne M, Gabriels D (2000) Extending the RUSLE with the Monte Carlo error propagation technique to predict long-term average off-site sediment accumulation. J Soil Water Conserv 55:35–42

    Google Scholar 

  • Blanco H, Lal R (2008) Principles of soil conservation and management. Springer, New York

    Google Scholar 

  • Boix-Fayos C, Martínez-Mena M, Arnau-Rosalén E et al (2006) Measuring soil erosion by field plots: understanding the sources of variation. Earth Sci Rev 78:267–285

    Article  ADS  Google Scholar 

  • Borrelli P, Robinson DA, Panagos P et al (2020) Land use and climate change impacts on global soil erosion by water (2015–2070). Proc Natl Acad Sci 117:21994–22001

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  • Butzer KW (2005) Environmental history in the Mediterranean world: cross-disciplinary investigation of cause-and-effect for degradation and soil erosion. J Archaeol Sci 32:1773–1800

    Article  Google Scholar 

  • Calhoun RS, Fletcher CH III (1999) Measured and predicted sediment yield from a subtropical, heavy rainfall, steep-sided river basin: Hanalei, Kauai, Hawaiian Islands. Geomorphology 30:213–226

    Article  ADS  Google Scholar 

  • Cantón Y, Solé-Benet A, De Vente J et al (2011) A review of runoff generation and soil erosion across scales in semiarid south-eastern Spain. J Arid Environ 75:1254–1261

    Article  Google Scholar 

  • Chakrabortty R, Pal SC, Chowdhuri I et al (2020) Assessing the importance of static and dynamic causative factors on erosion potentiality using SWAT, EBF with uncertainty and plausibility, logistic regression and novel ensemble model in a sub-tropical environment. J Indian Soc Remote Sens 48:765–789. https://doi.org/10.1007/s12524-020-01110-x

    Article  Google Scholar 

  • Chen G, Zhang Z, Guo Q et al (2019) Quantitative assessment of soil erosion based on CSLE and the 2010 national soil erosion survey at regional scale in Yunnan Province of China. Sustainability 11:3252

    Article  Google Scholar 

  • Csáfordi P, Pődör A, Bug J, Gribovszki Z (2012) Soil erosion analysis in a small forested catchment supported by ArcGIS model builder. Acta Silv Lignaria Hung 8:39–55

    Article  Google Scholar 

  • De Vente J, Poesen J, Arabkhedri M, Verstraeten G (2007) The sediment delivery problem revisited. Prog Phys Geogr 31:155–178

    Article  Google Scholar 

  • Doetterl S, Berhe AA, Nadeu E et al (2016) 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 154:102–122

    Article  ADS  CAS  Google Scholar 

  • Dotterweich M (2008) The history of soil erosion and fluvial deposits in small catchments of central Europe: deciphering the long-term interaction between humans and the environment—a review. Geomorphology 101:192–208

    Article  ADS  Google Scholar 

  • Dumas P, Printemps J (2010) Assessment of soil erosion using USLE model and GIS for integrated watershed and coastal zone management in the South Pacific Islands, pp 856–866

    Google Scholar 

  • El Kateb H, Zhang H, Zhang P, Mosandl R (2013) Soil erosion and surface runoff on different vegetation covers and slope gradients: a field experiment in Southern Shaanxi Province, China. CATENA 105:1–10

    Article  Google Scholar 

  • Foster GR, Meyer L, Onstad C (1977) A runoff erosivity factor and variable slope length exponents for soil loss estimates. Trans ASAE 20:683–687

    Article  Google Scholar 

  • García-Ruiz JM, Beguería S, Nadal-Romero E et al (2015) A meta-analysis of soil erosion rates across the world. Geomorphology 239:160–173

    Article  ADS  Google Scholar 

  • Hoffmann T, Erkens G, Cohen K et al (2007) Holocene floodplain sediment storage and hillslope erosion within the Rhine catchment. The Holocene 17:105–118

    Article  ADS  Google Scholar 

  • Hudson NW (2015) Soil conservation. Scientific Publishers

    Google Scholar 

  • Hui L, Xiaoling C, Lim KJ et al (2010) Assessment of soil erosion and sediment yield in Liao watershed, Jiangxi Province, China, using USLE, GIS, and RS. J Earth Sci 21:941–953

    Article  Google Scholar 

  • Jat ML, Stirling CM, Jat HS et al (2018) Soil processes and wheat cropping under emerging climate change scenarios in South Asia. Adv Agron 148:111–171

    Article  Google Scholar 

  • Jena R, Padua S, Ray P et al (2018) Assessment of soil erosion in sub tropical ecosystem of Meghalaya, India using remote sensing, GIS and RUSLE

    Google Scholar 

  • Jetten V, Govers G, Hessel R (2003) Erosion models: quality of spatial predictions. Hydrol Process 17:887–900

    Article  ADS  Google Scholar 

  • Keesstra S, Mol G, de Leeuw J et al (2018) Soil-related sustainable development goals: four concepts to make land degradation neutrality and restoration work. Land 7:133. https://doi.org/10.3390/land7040133

    Article  Google Scholar 

  • Kouli M, Soupios P, Vallianatos F (2009) Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environ Geol 57:483–497. https://doi.org/10.1007/s00254-008-1318-9

    Article  ADS  Google Scholar 

  • Larson WE, Pierce FJ, Dowdy RH (1983) The threat of soil erosion to long-term crop production. Science 219:458–465

    Article  ADS  CAS  PubMed  Google Scholar 

  • Leopold LB, Wolman MG, Miller JP, Wohl E (2020) Fluvial processes in geomorphology. Courier Dover Publications

    Google Scholar 

  • Liu B, Guo S, Li Z et al (2013) Sampling program of water erosion inventory in China. Soil Water Conserv China 10:26–34

    Google Scholar 

  • Mairura FS, Mugendi DN, Mwanje J et al (2007) Integrating scientific and farmers’ evaluation of soil quality indicators in Central Kenya. Geoderma 139:134–143

    Article  ADS  CAS  Google Scholar 

  • Maji A, Reddy GO, Sarkar D (2010) Degraded and wastelands of India: status and spatial distribution

    Google Scholar 

  • Mbanzamihigo E (2021) Spatial-temporal relationships between crops production and soil erosion: case of Western Province of Rwanda

    Google Scholar 

  • McCool DK, Foster GR, Mutchler C, Meyer L (1989) Revised slope length factor for the universal soil loss equation. Trans ASAE 32:1571–1576

    Article  Google Scholar 

  • Mekonnen M, Keesstra SD, Stroosnijder L et al (2015) Soil conservation through sediment trapping: a review: individual, combined and integrated sediment trapping. Land Degrad Dev 26:544–556. https://doi.org/10.1002/ldr.2308

    Article  Google Scholar 

  • Mohammad AG, Adam MA (2010) The impact of vegetative cover type on runoff and soil erosion under different land uses. CATENA 81:97–103

    Article  Google Scholar 

  • Morbidelli R, Saltalippi C, Flammini A, Govindaraju RS (2018) Role of slope on infiltration: a review. J Hydrol 557:878–886

    Article  Google Scholar 

  • Morgan R, Quinton J, Smith R et al (1998) The European soil erosion model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments. Earth Surf Process Landf J Br Geomorphol Group 23:527–544

    Article  ADS  Google Scholar 

  • National Research Council (1993) Soil and water quality: an agenda for agriculture. National Academies Press

    Google Scholar 

  • Nearing M, Jetten V, Baffaut C et al (2005) Modeling response of soil erosion and runoff to changes in precipitation and cover. CATENA 61:131–154

    Article  Google Scholar 

  • Nearing M, Lane LJ, Lopes VL (2017) Modeling soil erosion. In: Soil erosion research methods. Routledge, pp 127–158

    Google Scholar 

  • Nunes J, De Lima J, Singh V et al (2006) Numerical modeling of surface runoff and erosion due to moving rainstorms at the drainage basin scale. J Hydrol 330:709–720

    Article  Google Scholar 

  • Pal SC, Chakrabortty R (2019) Simulating the impact of climate change on soil erosion in sub-tropical monsoon dominated watershed based on RUSLE, SCS runoff and MIROC5 climatic model. Adv Space Res 64:352–377

    Article  ADS  Google Scholar 

  • Pal SC, Shit M (2017) Application of RUSLE model for soil loss estimation of Jaipanda watershed, West Bengal. Spat Inf Res 25:399–409

    Article  Google Scholar 

  • Pal SC, Chakrabortty R, Roy P et al (2021) Changing climate and land use of 21st century influences soil erosion in India. Gondwana Res 94:164–185. https://doi.org/10.1016/j.gr.2021.02.021

    Article  ADS  Google Scholar 

  • Pan J, Wen Y (2014) Estimation of soil erosion using RUSLE in Caijiamiao watershed, China. Nat Hazards 71:2187–2205

    Article  Google Scholar 

  • Pandey S, Kumar P, Zlatic M et al (2021) Recent advances in assessment of soil erosion vulnerability in a watershed. Int Soil Water Conserv Res 9:305–318

    Article  Google Scholar 

  • Peterson GD, Cumming GS, Carpenter SR (2003) Scenario planning: a tool for conservation in an uncertain world. Conserv Biol 17:358–366

    Article  Google Scholar 

  • Pham TG, Degener J, Kappas M (2018) Integrated universal soil loss equation (USLE) and geographical information system (GIS) for soil erosion estimation in A Sap basin: Central Vietnam. Int Soil Water Conserv Res 6:99–110

    Article  Google Scholar 

  • Pimentel D, Allen J, Beers A et al (1993) Soil erosion and agricultural productivity. In: World soil erosion and conservation, pp 277–292

    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. Geosci Front 3:209–215. https://doi.org/10.1016/j.gsf.2011.11.003

    Article  Google Scholar 

  • Ranzi R, Le TH, Rulli MC (2012) A RUSLE approach to model suspended sediment load in the Lo river (Vietnam): effects of reservoirs and land use changes. J Hydrol 422:17–29

    Article  Google Scholar 

  • Renard KG, Foster GR, Weesies GA, Porter JP (1991) RUSLE: revised universal soil loss equation. J Soil Water Conserv 46:30–33

    Google Scholar 

  • Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (eds) (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). Washington, DC

    Google Scholar 

  • Renschler CS, Harbor J (2002) Soil erosion assessment tools from point to regional scales—the role of geomorphologists in land management research and implementation. Geomorphology 47:189–209

    Article  ADS  Google Scholar 

  • Rodríguez-Caballero E, Cantón Y, Chamizo S et al (2013) Soil loss and runoff in semiarid ecosystems: a complex interaction between biological soil crusts, micro-topography, and hydrological drivers. Ecosystems 16:529–546

    Article  Google Scholar 

  • Sadeghi S, Mizuyama T (2007) Applicability of the modified universal soil loss equation for prediction of sediment yield in Khanmirza watershed, Iran. Hydrol Sci J 52:1068–1075

    Article  Google Scholar 

  • Sarvade S, Upadhyay V, Kumar M, Khan MI (2019) Soil and water conservation techniques for sustainable agriculture. In: Sustainable agriculture, forest and environmental management. Springer, pp 133–188

    Google Scholar 

  • Schmidt S, Alewell C, Meusburger K (2018) Mapping spatio-temporal dynamics of the cover and management factor (C-factor) for grasslands in Switzerland. Remote Sens Environ 211:89–104

    Article  ADS  Google Scholar 

  • Shinde V, Tiwari K, Singh M (2010) Prioritization of micro watersheds on the basis of soil erosion hazard using remote sensing and geographic information system. Int J Water Resour Environ Eng 5:130–136

    Google Scholar 

  • Srinivas C, Maji A, Chary G (2002) Assessment of soil erosion using remote sensing and GIS in Nagpur district, Maharashtra for prioritisation and delineation of conservation units. J Indian Soc Remote Sens 30:197–212

    Article  Google Scholar 

  • Tanyaş H, Kolat Ç, Süzen ML (2015) A new approach to estimate cover-management factor of RUSLE and validation of RUSLE model in the watershed of Kartalkaya Dam. J Hydrol 528:584–598

    Article  Google Scholar 

  • Toy TJ, Foster GR, Renard KG (2002) Soil erosion: processes, prediction, measurement, and control. Wiley

    Google Scholar 

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

    Google Scholar 

  • Vrieling A, de Jong SM, Sterk G, Rodrigues SC (2008) Timing of erosion and satellite data: a multi-resolution approach to soil erosion risk mapping. Int J Appl Earth Obs Geoinf 10:267–281

    Google Scholar 

  • Wang G, Gertner G, Fang S, Anderson AB (2003) Mapping multiple variables for predicting soil loss by geostatistical methods with TM images and a slope map. Photogramm Eng Remote Sens 69:889–898

    Article  Google Scholar 

  • Williams J, Berndt H (1977) Sediment yield prediction based on watershed hydrology. Trans ASAE 20:1100–1104

    Article  Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses: a guide to conservation planning. Department of Agriculture, Science and Education Administration

    Google Scholar 

  • Yang D, Kanae S, Oki T et al (2003) Global potential soil erosion with reference to land use and climate changes. Hydrol Process 17:2913–2928. https://doi.org/10.1002/hyp.1441

    Article  ADS  Google Scholar 

  • Yin S, Zhang W, Xie Y et al (2013) Spatial distribution of rainfall erosivity in China based on high-density station network. Soil Water Conserv 10:45–51

    Google Scholar 

  • Zhang W, Fu J (2003) Rainfall erosivity estimation under different rainfall amount. Resour Sci 25:35–41

    Google Scholar 

  • Zhou Z, Chu S, Wang Z, Chen Q (2008) Analysis of vegetation coverage change based on NDVI—a case study in Ganzhou area, Zhangye city, Gansu. Pratacult Sci 12

    Google Scholar 

  • Zuazo VHD, Pleguezuelo CRR (2009) Soil-erosion and runoff prevention by plant covers: a review. Sustain Agric 785–811

    Google Scholar 

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Pal, S.C., Chakrabortty, R. (2022). Soil Loss Estimation Using Different Empirical and Semi-empirical Models. In: Climate Change Impact on Soil Erosion in Sub-tropical Environment . Geography of the Physical Environment. Springer, Cham. https://doi.org/10.1007/978-3-031-15721-9_5

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