Advanced search

Natural And Human-Induced Land Degradation And Its Impact Using Geospatial Approach In The Kallar Watershed Of Tamil Nadu, India

Full Text:


Land degradation is human-induced and natural process that adversely affects the land, to function effectively within a complex ecosystem. In recent years, the Kallar watershed has encountered various kinds of multifarious problems on both land and water in the urban and its environs. The upper part of the study area is facing water scarcity problems in the past few years, but which included no such rare occurrences in the past. The mid-portion in the vicinity of foothills are highly affected by soil erosion, whereas the lower portion of the area has faced problems like land degradation, such as an unusual increase of wastelands and conversion of good agriculture lands into construction plots. Apart from these, the study area is frequently affected by nature induced disasters like a landslide, forest fire, flooding, and drought. In this complex situation, the qualitative assessment of human-induced land degradation and its impact is essential. For this, Geospatialbased Multi-Criteria Evaluation (MCE) as a multidisciplinary approach has been adopted. To assess land degradation, six major criterions are preferred such as terrain (slope, elevation), environment (landuse/land cover, NDVI), soil erosion, and demography (population density). Considerable weights and ranks were assigned through an empirical MCE method. Based on the criteria, the land degradation was carefully delineated into five significant categories such as low (38.3%), moderately (23.6%), marginally (15.4%), highly (4.8%), and severely degraded (17.8%). The depletion of vegetation cover on hilly terrain and subsequent cultivation without proper protection measures constitute the possible reason for severe soil erosion and land degradation.

About the Authors

Abdul Rahaman S.
Department of Geography, School of Earth Science, Bharathidasan University
Tiruchirappalli – 620024 Tamil Nadu

Aruchamy Solavagounder
Department of Geography, School of Earth Science, Bharathidasan University
Tiruchirappalli – 620024 Tamil Nadu


1. Abdul Rahaman S., Aruchamy S. and Jegankumar R. (2014). Geospatial approach on landslide hazard zonation mapping using multicriteria decision analysis: a study on Coonoor and Ooty, part of Kallar watershed, The Nilgiris, Tamil Nadu, Int. Arch. Photo. Remot Sens. Spatial Inf. Sci., XL-8, 1417-1422, DOI: 10.5194/isprsarchives-XL-8-1417-2014.

2. Abdul Rahaman S., Aruchamy S., Jegankumar R. and Abdul Ajeez S. (2015). Estimation of annual average soil loss, based on rusle model in Kallar watershed, Bhavani basin, Tamil Nadu, India, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-2/W2, 207–214, DOI: 10.5194/isprsannals-II-2-W2-207-2015.

3. Abhijeet Ghadge, Sjoerd van der Werf, Merve Er Kara, Mohit Goswami, Pankaj Kumar, Michael Bourlakis (2020). Modelling the impact of climate change risk on bioethanol supply chains, Technological Forecasting & Social Change 160, DOI: 10.1016/j.techfore.2020.120227.

4. Arnoldus H.M.J. (1980). An approximation of the rainfall factor in the Universal Soil Loss Equation.

5. Angima S.D., Stott D.E., O’Neill M.K., Ong C.K. and Weesies G.A. (2003). Soil erosion prediction using RUSLE for central Kenyan highland conditions agriculture. Ecosystems and Environment, 97(1-3), 295-308.

6. Barzani and Khairulmaini (2013). Desertification risk mapping of the Zayandeh Rood Basin in Iran. Journal of Earth System Science 122(5), 1269-1282, DOI: 10.1007/s12040-013-0348-1.

7. Bhattacharyya R., Ghosh B.N., Mishra P.K., Mandal B., Rao C.S. and Sarkar D. (2015). Soil degradation in India: challenges and potential solutions. Sustainability 7, 3528-3570.

8. Barrow C. (1994). Land degradation development and breakdown of terrestrial environments. Cambridge University Press, New York.

9. Brevik E.C., Cerda A., Mataix-Solera J., Pereg L., Quinton J.N. Six, J. and Van Oost K. (2015). The interdisciplinary nature of soil, Soil, 1, 117- 129, DOI: 10.5194/soil-1-117-2015.

10. Camprubi A., Zarate I.A., Adholeya A., Lovato P.E. and Calvet C. (2015). Field performance and essential oil production of mycorrhizal rosemary in restoration low-nutrient soils, Land Degrad. Dev., 26, 793-799, DOI: 10.1002/ldr.2229.

11. Cerda A., Gonzalez-Pelayo O., Gimenez-Morera A., Jordan A., Pereira P., Novara A., Brevik E.C., Prosdocimi M., Mahmoodabadi M., Keesstra S., Garcia Orenes F. and Ritsema C. (2016). The use of barley straw residues to avoid high erosion and runoff rates on persimmon plantations in Eastern Spain under low frequency – high magnitude simulated rainfall events, Soil Res., 54, 154-165, DOI: 10.1071/SR15092.

12. Christopher Morgan (1983). The non-independence of rainfall erosivity and soil erodibility, Earth Surface Processes and Landforms, 8, 323-338.

13. Chen Guangwei (1994). Land Degradation Approach – Methodology and Practice, CISNAR, China.

14. Dabral P.P., Baithuri N. and 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.

15. De Boodt M. and Gabriels D. (Eds.) (1980). Assessment of Erosion, Wiley, Chichester, UK, 127-132.

16. Desertification and Land Degradation Atlas of India (2016). (Based on IRS AWiFS data of 2011–13 and 2003-05), Space Applications Centre, ISRO, Ahmedabad, India.

17. D’Odorico P.; Bhattachan A., Davis K.F., Ravi S. and Runyan C.W. (2013). Global desertification: Drivers and feedbacks. Adv. Water Resour., 51, 326-344.

18. Eisfelder C., Kuenzer C. and Dech S. (2012). Derivation of biomass information for semi-arid areas using remote-sensing data. Int. J. Remote Sens., 33, 2937-2984.

19. Eliasson K., Lindgren U. and Westerlund O. (2003). Geographical labour mobility: Migration or commuting. Regional Studies 37, 827-37.

20. El-Swaify S.A. (1997). Factors affecting soil erosion hazards and conservation needs for tropical steeplands. Soil Technology 11, 3-6.

21. FAO (1976). A Framework for Land Evaluation. FAO Soil Bulletin No. 32. ILRI Publication No. 22. Rome, Italy.

22. FAO (1980). Natural resources and the human environment for food and agriculture. Environment Paper No 1. Rome.

23. FAO (1990). Rural area development planning; A review and synthesis of approaches. FAO training materials for agricultural planning. Rome.

24. FAO (2018). LDN – Restoring degraded lands.

25. Feizizadeh B. and Blaschke T. (2014). An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping, International Journal of Geographical Information Science, 28:3, 610-638, DOI: 10.1080/13658816.2013.869821.

26. Gessesse B., Bewket W. and Brauning A. (2015). Model-based characterization and monitoring of runoff and soil erosion in response to landuse/land cover changes in the Modjo Watershed, Ethiopia, Land Degrad. Dev., 26, 711-724, DOI: 10.1002/ldr.2276.

27. Higginbottom T.P. and Symeonakis E. (2014). Assessing land degradation and desertification using vegetation index data: Current frameworks and future directions. Remote Sensing, 6(10), 9552-9575, DOI: 10.3390/rs6109552

28. Helldén U. (2008). Tottrup C. Regional desertification: A global synthesis. Glob. Planet. Chang. 64, 169-176.

29. Haboudane D., Bonn F., Royer A., Sommer S. and Mehl W. (2002). Land degradation and erosion risk mapping by fusion of spectrallybased information and digital geomorphometric attributes. Int. J. Remote Sens., 23, 3795-3820.

30. ICAR (Indian Council of Agricultural Research) (2010). State of Indian Agriculture, 2012–2013, A report of Department of Agriculture and Cooperation, New Delhi, 9.

31. IPCC (2001). Intergovernmental Panel on Climatic Change, «Impacts, Adaptation and Vulnerability».

32. Jong R.D., Bruin S.D. and Dent M.S.D. (2011). Quantitative mapping of global land degradation using earth observations. Int. J. Remote Sens., 32, 6823-6853.

33. Jasrotia A.S. and Singh R. (2006). Modeling runoff and soil erosion in a catchment area, using the GIS, in the Himalayan region, India. Environ Geol 51, 29-37, DOI: 10.1007/s00254-006-0301-6.

34. Khaledian Y., Kiani F., Ebrahimi S., Brevik E.C. and Aitkenhead-Peterson J. (2017). Assessment and monitoring of soil degradation during landuse change using multivariate analysis, Land Degrad. Dev., 28, 128-141, DOI: 10.1002/ldr.2541.

35. Kouli M., Soupios P. and Vallianatos F. (2009). Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece Environmental Geology, 57, 483-497.

36. Leh M., Bajwa S. and Chaubey I. (2013). Impact of landuse change on erosion risk: an integrated remote sensing, geographic information system and modelling methodology, Land Degrad. Dev., 24, 409-421, DOI: 10.1002/ldr.1137.

37. Lin D.G., Yu H., Lian F., Wang J.A., Zhu A.X. and Yue Y.J. (2016). Quantifying the hazardous impacts of human-induced land degradation on terrestrial ecosystems: A case study of karst areas of south China. Environ. Earth Sci., 75, 1127.

38. Masoudi M. (2010). Risk Assessment and Remedial Measures of Land Degradation, in Parts of Southern Iran, Lambert Academic Publishing (LAP), Germany, 220.

39. Masoudi M. (2014). Risk assessment of vegetation degradation using GIS J. Agr. Sci. Tech.-Iran, 16, 1711-1722.

40. Masoudi M. and Amiri E. (2015). A new model for hazard evaluation of vegetation degradation using DPSIR framework, a case study: Sadra region, Iran, Pol. J. Ecol., 63, 1-9, DOI: 10.3161/15052249PJE2015.63.1.001.

41. Masoud Masoudi, Parviz Jokar, and Biswajeet Pradhan (2018). A new approach for land degradation and desertification assessment using geospatial techniques. Nat. Hazards Earth Syst. Sci., 18, 1133-1140.

42. Mendoza G.A., Martins H. (2006). Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms. Forest Ecology and Management 230, 1-22.

43. McCool D.K., Brown L.C., Foster G.R., Mutchler C.K. and Meyer L.D. (1987). Revised slope steepness factor for the Universal Soil Loss Equation. TRANSACTIONS of the ASAE 30(5), 1387-1396.

44. McCool D.K., George G.O., Freckleton M., Douglas C.L., Jr. and Papendick R.I. (1993). Topographic effect on erosion from crop land in the northwestern wheat region. TRANSACTIONS of the ASAE 36(4), 1067-1071.

45. Metternicht G., Zinck J.A., Blanco P.D. & Del Valle H.F. (2010). Remote sensing of land degradation: Experiences from Latin America and the Caribbean. Journal of Environmental Quality, 39(1), 42-61, DOI: 10.2134/jeq2009.0127.

46. Morgan R.P.C. (1983). The impact of recreation on mountain soils: towards a predictive model for soil erosion. Conference on the ecological impacts of outdoor recreation on mountain areas in Europe and North America, Recreation Ecology Research Group, Ambleside, Cumbria.

47. Millennium Ecosystem Assessment (MEA 2005). Ecosystems and Human-Being: Desertification Synthesis; World Resources Institute: Washington, DC, USA.

48. Millward A.A. and Mersey J.E. (1999). Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena, 38(2), 109-129.

49. Nicholson S.E. Tucker C.J., Ba M.B. (1998). Desertification, drought, and surface vegetation: An example from the West African Sahel. Bull. Am. Meteorol. Soc., 79, 815-830.

50. Naseer Ahmad and Puneeta Pandey (2018). Assessment and monitoring of land degradation using geospatial technology in Bathinda district, Punjab, India. Solid Earth, 9, 75-90, DOI: 10.5194/se-9-75-2018.

51. Nitheshnirmal S. Ashutosh Bhardwaj, Dineshkumar C. and Abdul Rahaman S. (2019). Prioritization of Erosion Prone Micro-watersheds using Morphometric Analysis coupled with Multi-Criteria Decision Making. Proceedings MDPI, 2nd International Electronic Conference on Geosciences (IECG 2019).

52. Abdi O.A.,. Glover E.K. and Luukkanen O. (2013). Causes and Impacts of Land Degradation and Desertification: Case Study of the Sudan. International Journal of Agriculture and Forestry 2013, 3(2), 40-51.

53. Ghorbanzadeh O., Feizizadeh B. and Blaschke T. (2017). Multi-criteria risk evaluation by integrating an analytical network process approach into GIS based sensitivity and uncertainty analyses, Geomatics, Natural Hazards and Risk, DOI: 10.1080/19475705.2017.1413012.

54. Olena D. (2017). The role of Remote Sensing in land degradation assessments: opportunities and challenges, European Journal of Remote Sensing, 50(1), 601-613, DOI: 10.1080/22797254.2017.1378926.

55. Pan J.H. and Li T.Y. (2013). Extracting desertification from LANDSAT imagery based on spectral mixture analysis and Albedo- Vegetation feature space, Nat. Hazards, 25, 915-927, DOI: 10.1007/s11069-013-0665-3.

56. Pankaj K., Wei Liu, Xi Chu, Yue Zhang, Zhihui Li (2019). Integrated water resources management for an inland river basin in China. Watershed Ecology and the Environment 1, 33-38, DOI: 10.1016/j.wsee.2019.10.002.

57. Prasannakumar V., Vijith H., Abinod S. and 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(2), 209-215.

58. Prince S., Becker-Reshef I. and Rishmawi K. (2009). Detection and mapping of long-term land degradation using local net production scaling: Application to Zimbabwe. Remote Sens. Environ., 113, 1046-1057.

59. Rahaman S.A., Ajeez S.A., Aruchamy S. and Jegankumar R. (2015). Prioritization of Sub Watershed based on morphometric characteristics using fuzzy analytical hierarchy process and geographical information system — a study of Kallar watershed, Tamil Nadu. International conference on water resources, coastal and ocean. Aquatic Proc. 4, 1322-1330, DOI: 10.1016/j.aqpro.2015.02.172.

60. Rahaman S.A., Aruchamy S., Balasubramani K. and Jegankumar R. (2017a). Landuse / land cover changes in semi-arid mountain landscape in southern India: a geoinformatics based markov chain approach. Int. Arch. Photo. Remote Sens. Spatial Inf. Sci., Vol XLII-1/W1. 231-237, DOI: 10.5194/isprs-archives-XLII-1-W1-231-2017.

61. Rahaman S.A. and Aruchamy S. (2017b). Geoinformatics based landslide vulnerable zonation mapping using analytical hierarchy process (AHP), a study of Kallar river sub watershed, Kallar watershed, Bhavani basin, Tamil Nadu. Model. Earth Syst. Environ., 3(41), 13, DOI: 10.1007/s40808-017-0298-8.

62. Rahaman S., Aruchamy S. and Jegankumar R. (2016). Geospatial Approach for forest cover change and vulnerability analysis through MCE in Kallar watershed, Part of Nilgiri Biosphere Reserve. Geo Eye, 5(2), 40-50.

63. Rahaman S., Kumar P., Chen R., Meadows M.E. and Singh R.B. (2020). Remote Sensing Assessment of the Impact of Land Use and Land Cover Change on the Environment of Barddhaman District, West Bengal, India. Front. Environ. Sci. 8:127, DOI: 10.3389/fenvs.2020.00127.

64. Rahaman S.A. and Venkatesh R. (2020). Application of remote sensing and google earth engine for monitoring environmental degradation in the Nilgiri biosphere reserve and its ecosystem of Western Ghats, India. Int. Arch. Photo. Remote Sens. Spatial Inf. Sci., Volume XLIII-B3, 933-940, DOI: 10.5194/isprs-archives-XLIII-B3-2020-933-2020.

65. Renard K.G and Ferreira V.A. (1993). RUSLE model description and database sensitivity. Journal of Environmental Quality 22(3), 458-466.

66. Rhoad R., Milauskas G. and Whipple R. (1991). Geometry for enjoyment and challenge. McDougal Littell, Evanston, IL.

67. Röder A., Udelhoven T., Hill J., del Barrio G. and Tsiourlis G. (2008). Trend analysis of landsat-tm and -etm+ imagery to monitor grazing impact in a rangeland ecosystem in northern greece. Remote Sensing of Environment 112(6), 2863-2875.

68. Saaty T.L. (1980). The Analytic Hierarchy Process. McGraw-Hill, New York. Scott S. and Conacher A. (2008). Land degradation and poverty. Geographical Research 46, 1-3.

69. Sharma A. (2010). Integrating terrain and vegetation indices for identifying potential soil erosion risk area Geo-Spatial Information Science, 13 (3), 201-209.

70. Stephanie W., Timo K., Ana Frelih-Larsen., Keighley M F. and Stefanie A. (2018). Report on Implementing SDG target 15.3 on «Land Degradation Neutrality» Ecologic Institut, Berlin. Umweltbundesamt, Germany.

71. Svenson L. (2005). Socio-economic Indicators for Causes and Consequences of Land degradation. LADA Technical paper, FAO, Rome.

72. Taddese Y. (2001). Land degradation: a challenge to Ethiopia, Environ. Manage., 27, 815-824, DOI: 10.1007/s002670010190.

73. Temiz F., Bozdag A., Durduran S.S, Gumus M.G. (2017). Monitoring Coastline Change Using Remote Sensing and Gis Technology: A Case Study of Burdur Lake, Turkey. Fresen. Environ. Bull. 26, 7235-7242.

74. Taguas E.V., Arroyo C., Lora A., Guzmán G., Vanderlinden K. and Gómez J.A. (2015). Exploring the linkage between spontaneous grass cover biodiversity and soil degradation in two olive orchard microcatchments with contrasting environmental and management conditions, SOIL, 1, 651-664, DOI: 10.5194/soil-1-651-2015.

75. UNCCD (1999). United Nations Convention to Combat Desertification in Those Countries Experiencing Serious Drought and/or Desertification, Particularly in Africa. Text with Annexes. Secretariat of the Convention to Combat Desertification, Bonn.

76. United Nations General Assembly (2015). Transforming our world: The 2030 agenda for sustainable development. Retrieved from

77. Uzun A., Somuncu M. (2013). Using Remote Sensing Method to Evaluate the Change of the Land Cover/Land Use in Time in Madra Mountain. Balikesir University Journal of Social Sciences Institute.16(30), 1-21.

78. Van der Knijff J.M., Jones R.J.A. and Montanarella L. (2000). Soil Erosion Risk Assessment in Europe. EUR 19044 EN Office for Official Publications of the European Communities, Luxembourg 34.

79. Venkatesh R., Abdul Rahaman S., Jegankumar R. and Masilamani P. (2020). Eco-environmental vulnerability zonation in essence of environmental monitoring and management, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 149-155, DOI: 10.5194/isprs-archives-XLIII-B5-2020-149-2020.

80. Wessels K., Prince S., Zambatis N., MacFadyen S., Frost P. and van Zyl D. (2006). Relationship between herbaceous biomass and 1 km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa. Int. J. Remote Sens., 27, 951-973.

81. Wischmeier W.H. (1974). New developments in estimating water erosion. 29e Meeting Soil Cons. Soc. Amer. Syracuse, New York. 179-186.

82. Wischmeier W.H. and Smith D.D. (1978). Predicting Rainfall Erosion Losses: A Guide to Conservation Planning, Agricultural Handbook No. 537, US Department of Agriculture, Washington DC.

83. Xie H., Zhang Y., Wu Z. and Lv T. (2020). A Bibliometric Analysis on Land Degradation: Current Status, Development, and Future Directions. Land, 9, 28.

84. Yu C., Liu K., Meng W., Wu Z. and Rishe N. (2002). A methodology for retrieving text documents from multiple databases. IEEE TKDE 14(6), 1347-1361.

85. Zhou W., Gang C., Zhou F., Li J., Dong X. and Zhao C. (2015). Quantitative assessment of the individual contribution of climate and human factors to desertification in northwest China using net primary productivity as an indicator. Ecol. Indic., 48, 560-569.

86. Zuazo V.H.D. and Pleguezuelo C.R.R. (2009). Soil-erosion and runoff prevention by plant covers: a review. In Lichtfouse, Eric; et al. Sustainable agriculture. Springer. 785.

For citation:

Rahaman S. A., Solavagounder A. Natural And Human-Induced Land Degradation And Its Impact Using Geospatial Approach In The Kallar Watershed Of Tamil Nadu, India. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2020;13(4):159-175.

Views: 97

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

ISSN 2071-9388 (Print)
ISSN 2542-1565 (Online)