Geomorphic Control on Soil Erosion – a Case Study in the Subarnarekha Basin, India

Amar Kumar Kathwas, Nilanchal Patel

Abstract


Geomorphology depicts the qualitative and quantitative characteristics of both terrain and landscape features combined with the processes responsible for its evolution. Soil erosion by water involves processes, which removes soil particles and organic matter from the upper sheet of the soil surface, and then transports the eroded material to distant location under the action of water. Very few studies have been conducted on the nature and dynamics of soil erosion in the different geomorphologic features. In the present investigation, an attempt has been made to assess the control of geomorphologic features on the soil loss. Universal Soil Loss Equation (USLE) was used to determine soil loss from the various geomorphological landforms. Principal component analysis (PCA) was implemented on the USLE parameters to determine the degree of association between the individual principal components and the USLE-derived soil loss. Results obtained from the investigation signify the influence of the various landforms on soil erosion. PC5 is found to be significantly correlated with the USLE-derived soil loss. The results ascertained significant association between the soil loss and geomorphological landforms, and therefore, suitable strategies can be implemented to alleviate soil loss in the individual landforms.


Keywords


geomorphological feature; soil erosion; USLE; principal component analysis

Full Text:

PDF

References


Abdel Rahman, M.A.E., Shalaby, A., Essa, E.F., 2018. Quantitative land evaluation based on fuzzy-multi-criteria spatial model for sustainable land-use planning. Modeling Earth Systems and Environment, 4(4): 1341–1353. doi:10.1007/s40808-018-0478-1.

Champagnac, J.-D., Molnar, P., Sue, C., Herman, F., 2012. Tectonics, climate, and mountain topography. Journal of Geophysical Research: Solid Earth, 117, B2. doi:10.1029/2011JB008348

Chatterjee, S., Krishna, A.P., Sharma, A.P., 2014. Geospatial assessment of soil erosion vulnerability at watershed level in some sections of the Upper Subarnarekha river basin, Jharkhand, India. Environmental Earth Sciences, 71(1): 357–374. doi:10.1007/s12665-013-2439-3.

Conoscenti, C., Di Maggio, C., Rotigliano, E., 2008. Soil erosion susceptibility assessment and validation using a geostatistical multivariate approach: a test in Southern Sicily. Natural Hazards, 46(3): 287–305. doi:10.1007/s11069-007-9188-0.

Council, N.R., 2010. Landscapes on the Edge: New Horizons for Research on Earth's Surface. Washington, DC: The National Academies Press.

Estornell, J., Marti Gavilá, J., Sebastiá, M.T., Mengual, J., 2013. Principal component analysis applied to remote sensing. Modelling in Science Education and Learning, 6(2): 83–89. doi:10.4995/msel.2013.1905.

Gelagay, H.S., Minale, A.S., 2016. Soil loss estimation using GIS and Remote sensing techniques: A case of Koga watershed, Northwestern Ethiopia. International Soil and Water Conservation Research, 4(2): 126–136. https://doi.org/10.1016/j.iswcr.2016.01.002.

Huang, C., Wylie, B.K., Yang, L., Homer, C.G., Zylstra, G., 2002. Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance. International Journal of Remote Sensing, 23(8): 1741–1748. doi:10.1080/01431160110106113.

Kim, H.S., 2006. Soil Erosion Modeling Using RUSLE and GIS on the Imha Watershed, South Korea: Colorado State University.

Lin, C.Y., Lin, W.T., Chou, W.C., 2002. Soil Erosion Prediction and Sediment Yield Estimation: The Taiwan Experience. Soil and Tillage Research, 68(2): 143–152.

Mainuri, Z.G., Owino, J.O., 2014. Linking landforms and land use to land degradation in the Middle River Njoro Watershed. International Soil and Water Conservation Research, 2(2): 1–10. https://doi.org/10.1016/S2095-6339(15)30001-0.

Marston, R.A., 2010. Geomorphology and vegetation on hillslopes: Interactions, dependencies, and feedback loops. Geomorphology, 116, 3: 206–217. doi: https://doi.org/10.1016/j.geomorph.2009.09.028

McGrath, G., Paik, K., Hinz, C., 2011. Complex landscapes from simple ecohydrological feedbacks. Paper presented at the MODSIM2011, Proceedings of the 19th International Congress on Modelling and Simulation, Australia.

Mondal, A., Khare, D., Kundu, S., 2018. A comparative study of soil erosion modelling by MMF, USLE and RUSLE. Geocarto International, 33(1): 89–103. doi:10.1080/10106049.2016.1232313.

Morgan, R.P.C., Nearing, M., 2016. Handbook of Erosion Modelling: Wiley.

Morgan, R.P.C., Rickson, R.J., 2003. Slope Stabilization and Erosion Control: A Bioengineering Approach: Taylor & Francis.

Mukherjee, S., Mukherjee, S., Garg, R.D., Bhardwaj, A., Raju, P.L.N., 2013. Evaluation of topographic index in relation to terrain roughness and DEM grid spacing. Journal of Earth System Science, 122(3): 869–886. doi:10.1007/s12040-013-0292-0.

Patel, N., Kathwas, A.K., 2012. Assessment of spatio-temporal dynamics of soil erosional severity through geoinformatics AU - Patel, Nilanchal. Geocarto International, 27(1): 3–16. doi:10.1080/10106049.2011.614359.

Patton, N.R., Lohse, K.A., Godsey, S.E., Crosby, B.T., Seyfried, M.S., 2018. Predicting soil thickness on soil mantled hillslopes. Nature communications, 9(1): 3329–3329. doi:10.1038/s41467-018-05743-y.

Pelletier, J.D., Barron-Gafford, G.A., Breshears, D.D., Brooks, P.D., Chorover, J., Durcik, M., ... Troch, P.A., 2013. Coevolution of nonlinear trends in vegetation, soils, and topography with elevation and slope aspect: A case study in the sky islands of southern Arizona. Journal of Geophysical Research: Earth Surface, 118(2): 741–758. doi:10.1002/jgrf.20046.

Pennock, D.J., 2003. Terrain attributes, landform segmentation, and soil redistribution. Soil and Tillage Research, 69(1): 15–26. https://doi.org/10.1016/S0167-1987(02)00125-3.

Saco, P., Willgoose, G., Hancock, G., 2007. Eco-geomorphology of banded vegetation patterns in arid and semi-arid regions. Hydrology and Earth System Sciences, 11. doi:10.5194/hess-11-1717-2007.

Schoonover, J.E., Crim ,J.F., 2015. An Introduction to Soil Concepts and the Role of Soils in Watershed Management. Journal of Contemporary Water Research & Education, 154(1): 21–47. doi:10.1111/j.1936-704X.2015.03186.x.

Schwab, G.O., Frevert, R.K., 1981. Soil and water conservation engineering: Wiley.

Seetharaman, D.K., Selvaraju, S., 2016. Statistical Tests of Hypothesis-Based Color Image Retrieval. Journal of Data Analysis and Information Processing, 4: 90–99. doi:10.4236/jdaip.2016.42008.

Segundo Métay, I.G., Bocco, G., Velázquez, A., Gajewski, K., 2017. On the relationship between landforms and land use in tropical dry developing countries. A GIS and multivariate statistical approach. Investigaciones Geográficas, Boletín del Instituto de Geografía, 93: 3–19. https://doi.org/10.14350/rig.56438.

Shin, G.J., 1999. The analysis of soil erosion analysis in watershed using GIS. Gang-won National University.

Simms, A.D., Woodroffe, C.D., Jones, B.G., 2003 July 14–17. Application of RUSLE for erosion management in a coastal catchment, Southern NSW. Paper presented at the Proceedings of the international congress on modeling and simulation: integrative modeling of biophysical, social and economic systems for resource management solutions, Townsville, Australia.

Stone, R.P., Hilborn, D., 2012. Universal Soil Loss Equation (USLE) factsheets. Ontario: Queen’s Printer.

Tang, H., Dubayah, R., 2017. Light-driven growth in Amazon evergreen forests explained by seasonal variations of vertical canopy structure. Proceedings of the National Academy of Sciences of the USA, 114(10): 2640–2644. doi:10.1073/pnas.1616943114.

Whipple, K.X., 2009. The influence of climate on the tectonic evolution of mountain belts. Nature Geoscience, 2: 97. doi:10.1038/ngeo413.

Wischmeier, W.H., Smith D.D., 1978. Predicting rainfall erosion losses – a guide to conservation planning. Hyattsville, Maryland: USDA, Science and Education Administration.

Yang, X., Chapman, G., 2006. Soil erosion modelling for NSW coastal catchments using RUSLE in a GIS environment. Paper presented at the Geoinformatics 2006: GNSS and Integrated Geospatial Applications.




DOI: http://dx.doi.org/10.17951/pjss.2021.54.1.1-24
Date of publication: 2021-06-29 19:03:01
Date of submission: 2020-04-09 22:03:23


Statistics


Total abstract view - 1381
Downloads (from 2020-06-17) - PDF - 660

Indicators



Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Amar Kumar Kathwas, Nilanchal Patel

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.