Applied Geomatics

, Volume 4, Issue 1, pp 21–32 | Cite as

Mapping spatial distribution of pollutants in groundwater of a tropical area of India using remote sensing and GIS

  • Prashant K. SrivastavaEmail author
  • Manika Gupta
  • Saumitra Mukherjee
Original Paper


Fresh and clean water is a vital commodity of need for the well-being of human societies, and damage of these aquifers is one of the most serious environmental problems of the past century. The regular monitoring and management of groundwater resources is very important for the sustainable development. The present study monitors the groundwater quality relation to the land use/land cover (LULC) using remote sensing and GIS techniques. Physico-chemical analysis data of groundwater samples collected at different locations forms the attribute database for the study. LULC categories, such as agricultural and built-up area, associated with human activities, incorporated maximum change in groundwater quality. In this study, weighting analysis of Water Quality Index (WQI) and Land Cover Index (LCI) have been performed to map the Suitability Index (SI) of water for drinking purpose in the area. Spatial interpolation technique was used for generation of pollution potentiality map of the area. Cluster analysis was performed for delineating and grouping the similar pollution causing area. The overall view of the results indicates that most of the study area exhibited very low SI for the drinking purpose due to very high groundwater pollution.


Land cover index Suitability index Water quality index Cluster analysis Spatial interpolation 



The authors thank the chief editor and anonymous reviewers for their illuminating comments. Authors are also grateful to the Department of Science and Technology (DST), New Delhi, India, for providing the necessary data and funding this project. The first author is grateful to the Council for Scientific and Industrial Research (CSIR), New Delhi, India, for providing the Junior Research Fellowship (JRF). We are also grateful to the dean of the School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, India, for providing us all the necessary laboratory facilities.


  1. APHA (1985) Standard methods for the examination of water and wastewater. WPCF American Public Health Association, American Water Workers Association, Water Pollution Control FederationGoogle Scholar
  2. Basnyat P, Teeter L, Lockaby B, Flynn K (2000) The use of remote sensing and GIS in watershed level analyses of non-point source pollution problems. For Ecol Manage 128(1–2):65–73CrossRefGoogle Scholar
  3. Basnyat P, Teeter LD, Flynn KM, Lockaby BG (1999) Relationships between landscape characteristics and nonpoint source pollution inputs to coastal estuaries. Environ Manage 23(4):539–549CrossRefGoogle Scholar
  4. Behera S, Panda R (2006) Evaluation of management alternatives for an agricultural watershed in a sub-humid subtropical region using a physical process based model. Agricult Ecosyst Environ 113(1–4):62–72CrossRefGoogle Scholar
  5. Bhaduri B, Minner M, Tatalovich S, Harbor J (2001) Long-term hydrologic impact of urbanization: a tale of two models. J Water Resour Plann Manage 127(1):13–19CrossRefGoogle Scholar
  6. Bruland KW, Franks George A, Robert P (1979) Sampling and analytical methods for the determination of copper, cadmium, zinc, and nickel at the nanogram per liter level in sea water. Anal Chim Acta 105:233–245CrossRefGoogle Scholar
  7. Carrol D (1962) Rain water as a chemical agent of geologic processes. A review. US Geol Surv Water Supply Pap, 97–104Google Scholar
  8. Chang K (2002) Introduction to geographic information systems. New YorkGoogle Scholar
  9. Chatterjee R, Tarafder G, Paul S (2010) Groundwater quality assessment of Dhanbad district, Jharkhand, India. B Eng Geol Environ 69(1):137–141. doi: 10.1007/s10064-009-0234-x CrossRefGoogle Scholar
  10. Chowdary V, Ramakrishnan D, Srivastava Y, Chandran V, Jeyaram A (2009) Integrated water resource development plan for sustainable management of Mayurakshi watershed, India using remote sensing and GIS. Water Resour Manage 23(8):1581–1602CrossRefGoogle Scholar
  11. Chowdhury A, Jha MK, Chowdary V (2010) Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environ Earth Sci 59(6):1209–1222CrossRefGoogle Scholar
  12. Eastman JR, Worcester M (2001) Guide to GIS and image processing, Volume 2. Idrisi ManualGoogle Scholar
  13. Fewtrell L (2004) Drinking-water nitrate, methemoglobinemia, and global burden of disease: a discussion. Environ Health Perspect 112(14):1371CrossRefGoogle Scholar
  14. Gupta M, Srivastava PK (2010) Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India. Water Int 35(2):233–245CrossRefGoogle Scholar
  15. Hanratty MP, Stefan HG (1998) Simulating climate change effects in a Minnesota agricultural watershed. J Environ Qual 27(6):1524–1532CrossRefGoogle Scholar
  16. Hedges LV, Olkin I (1985) Statistical methods for meta-analysis. Academic, New YorkGoogle Scholar
  17. Hespanhol I, Prost A (1994) WHO guidelines and national standards for reuse and water quality. Water Res 28(1):119–124CrossRefGoogle Scholar
  18. Jaiswal R, Mukherjee S, Krishnamurthy J, Saxena R (2003) Role of remote sensing and GIS techniques for generation of groundwater prospect zones towards rural development—an approach. Int J Remote Sens 24(5):993–1008CrossRefGoogle Scholar
  19. Jaiswal RK, Saxena R, Mukherjee S (1999) Application of remote sensing technology for land use/land cover change analysis. J Indian Soc Remote Sens 27(2):123–128CrossRefGoogle Scholar
  20. Jha MK, Chowdary V, Chowdhury A (2010) Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques. Hydrogeol J 1–16Google Scholar
  21. Johnson R, Wichern D (2002) Applied multivariate statistical analysis. Prentice-Hall, LondonGoogle Scholar
  22. Kaufman L, Rousseeuw PJ, Corporation E (1990) Finding groups in data: an introduction to cluster analysis, vol. 39. Wiley Online LibraryGoogle Scholar
  23. Kaurish FW, Younos T (2007) Developing a standardized water quality index for evaluating surface water quality. J Am Water Resour As 43(2):533–545. doi: 10.1111/j.1752-1688.2007.00042.x CrossRefGoogle Scholar
  24. Kazi T, Arain M, Jamali M, Jalbani N, Afridi H, Sarfraz R, Baig J, Shah AQ (2009) Assessment of water quality of polluted lake using multivariate statistical techniques: a case study. Ecotoxicol Environ Saf 72(2):301–309CrossRefGoogle Scholar
  25. Lerner DN, Harris B (2009) The relationship between land use and groundwater resources and quality. Land Use Policy 26:S265–S273. doi: 10.1016/j.landusepol.2009.09.005 CrossRefGoogle Scholar
  26. Lillesand TM, Kiefer RW, Chipman JW (2004) Remote sensing and image interpretation. vol Ed. 5. WileyGoogle Scholar
  27. Mukherjee S (2008) Role of satellite sensors in groundwater exploration. Sensors 8(3):2006–2016CrossRefGoogle Scholar
  28. Mukherjee S, Sashtri S, Gupta M, Pant MK, Singh C, Singh SK, Srivastava PK, Sharma KK (2007) Integrated water resource management using remote sensing and geophysical techniques: Aravali quartzite, Delhi, India. J Environ Hydrol 15Google Scholar
  29. Mukherjee S, Shashtri S, Singh C, Srivastava PK, Gupta M (2009) Effect of canal on land use/land cover using remote sensing and GIS. J Indian Soc Remote Sens 37(3):527–537CrossRefGoogle Scholar
  30. Nagelkerke NJD (1991) A note on a general definition of the coefficient of determination. Biometrika 78(3):691CrossRefGoogle Scholar
  31. Neely KW (2005) Nitrate overview for the statewide ambient ground water quality monitoring program, 1990–2003. Idaho Dept. of Water ResourcesGoogle Scholar
  32. Patel DP, Dholakia MB, Naresh N, Srivastava PK (in press) Water harvesting structure positioning by using geo-visualization concept and prioritization of mini-watersheds through morphometric analysis in the Lower Tapi Basin. J Indian Soc Remote Sens. doi: 10.1007/s12524-011-0147-6
  33. Rai SC, Sharma E (1998) Comparative assessment of runoff characteristics under different land use patterns within a Himalayan watershed. Hydrol Process 12(13–14):2235–2248CrossRefGoogle Scholar
  34. Scanlon BR, Reedy RC, Stonestrom DA, Prudic DE, Dennehy KF (2005) Impact of land use and land cover change on groundwater recharge and quality in the southwestern US. Global Change Biol 11(10):1577–1593CrossRefGoogle Scholar
  35. Schroeder HA (1960) Relations between hardness of water and death rates from certain chronic and degenerative diseases in the United States. J Chronic Dis 12(6):586–591CrossRefGoogle Scholar
  36. Scott A, Knott M (1974) A cluster analysis method for grouping means in the analysis of variance. Biometrics 30(3):507–512CrossRefGoogle Scholar
  37. Sener E, Davraz A, Ozcelik M (2005) An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Hydrogeol J 13(5):826–834CrossRefGoogle Scholar
  38. Shrestha S, Kazama F (2007) Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin, Japan. Environ Modell Software 22(4):464–475CrossRefGoogle Scholar
  39. Shuval HI, Gruener N (1977) Infant methemoglobinemia and other health effects of nitrates in drinking water. Prog Water Technol 8(4–5):183Google Scholar
  40. Singh KP, Malik A, Mohan D, Sinha S (2004) Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Res 38(18):3980–3992CrossRefGoogle Scholar
  41. Singh SK, Singh CK, Kumar KS, Gupta R, Mukherjee S (2009) Spatial-temporal monitoring of groundwater using multivariate statistical techniques in Bareilly District of Uttar Pradesh, India. J Hydrol Hydromech 57(1):45–54CrossRefGoogle Scholar
  42. Singh SK, Singh CK, Mukherjee S (2010) Impact of land-use and land-cover change on groundwater quality in the Lower Shiwalik hills: a remote sensing and GIS based approach. Central Eur J Geosci 2(2):124–131CrossRefGoogle Scholar
  43. Srivastava PK, Kiran G, Gupta M, Sharma N, Prasad K (2012) A atudy on distribution of heavy metal contamination in the vegetables using GIS and analytical technique. Int J Ecol Dev 21(1):89–99Google Scholar
  44. Srivastava PK, Mukherjee S, Gupta M (2008) Groundwater quality assessment and its relation to land use/land cover using remote sensing and GIS. pp 19–22Google Scholar
  45. Srivastava PK, Mukherjee S, Gupta M, Singh S (2011) Characterizing monsoonal variation on water quality index of river Mahi in India using Geographical Information System. Water Qual Expos Health:1–11Google Scholar
  46. Srivastava PK, Mukherjee S, Gupta M (2010) Impact of urbanization on land use/land cover change using remote sensing and GIS: a case study. Int J Ecol Econ Stat 18(S10):106–117Google Scholar
  47. Štambuk-Giljanovi N (1999) Water quality evaluation by index in Dalmatia. Water Res 33(16):3423–3440CrossRefGoogle Scholar
  48. Stigter T, Ribeiro L, Carvalho Dill A (2006) Application of a groundwater quality index as an assessment and communication tool in agro-environmental policies-two Portuguese case studies. J Hydrol 327(3–4):578–591CrossRefGoogle Scholar
  49. Thakur JK, Srivastava PK, Singh S, Vekerdy Z (in press) Ecological monitoring of wetlands in semi-arid region of Konya closed Basin, Turkey. Reg Environ Change 1–12. doi: 10.1007/s10113-011-0241-x
  50. Tiwari T, Mishra M (1985) A preliminary assignment of water quality index of major Indian rivers. Indian J Environ Protect 5(4):276–279Google Scholar
  51. Tong STY, Chen W (2002) Modeling the relationship between land use and surface water quality. J Environ Manage 66(4):377–393CrossRefGoogle Scholar
  52. Tryon CMC (1939) Evaluations of adolescent personality by adolescents. Monogr Soc Res Child Dev 4(4)Google Scholar
  53. Tweed SO, Leblanc M, Webb JA, Lubczynski MW (2007) Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia. Hydrogeol J 15(1):75–96CrossRefGoogle Scholar
  54. Vermunt JK, Magidson J (2002) Latent class cluster analysis. In Applied latent class analysis. pp 89–106Google Scholar
  55. Xiuwan C (2002) Using remote sensing and GIS to analyse land cover change and its impacts on regional sustainable development. Int J Remote Sens 23(1):107–124CrossRefGoogle Scholar
  56. Wunderlin DA, Diàz MP, Amé MV, Pesce SF, Hued AC, Bistoni MA (2001) Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study: Suquía River Basin (Córdoba-Argentina). Water Res 35(12):2881–2894CrossRefGoogle Scholar
  57. Yeh HF, Lee CH, Hsu KC, Chang PH (2009) GIS for the assessment of the groundwater recharge potential zone. Environ Geol 58(1):185–195CrossRefGoogle Scholar

Copyright information

© Società Italiana di Fotogrammetria e Topografia (SIFET) 2011

Authors and Affiliations

  • Prashant K. Srivastava
    • 1
    • 2
    • 5
    Email author
  • Manika Gupta
    • 3
  • Saumitra Mukherjee
    • 4
  1. 1.Department of Civil EngineeringUniversity of BristolBristolUK
  2. 2.Department of Biological and Environmental ScienceNVPASGujaratIndia
  3. 3.Water Resource Engineering, Department of Civil EngineeringIITNew DelhiIndia
  4. 4.School of Environmental SciencesJawaharlal Nehru UniversityNew DelhiIndia
  5. 5.Water and Environment Management Research Centre, Department of Civil EngineeringUniversity of BristolBristolUK

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