Delineation of Groundwater Potential Zones in Chengalpattu District using Integrated Geoinformatics and Analytical Hierarchy Process

IJEP 44(8): 687-694 : Vol. 44 Issue. 8 (August 2024)

Kamalanandhini Mohan1* and Surendar Natarajan2

1. SRM Institute of Science and Technology, Department of Civil Engineering, Faculty of Engineering and Technology, Kattankulathur – 603 203, Tamil Nadu, India
2. Sri Sivasubramaniya Nadar College of Engineering (SSN), Department of Civil Engineering, Kalavakkam – 603 110, Tamil Nadu, India

Abstract

The demand and need for the vital water resources for various human activities is constantly increasing and surface water supplies are rapidly declining and becoming inadequate. Significant issues, such as depletion of water tables, scarcity of water, low water quality and groundwater drought are caused by excessive groundwater extraction. Chengalpattu district in Tamil Nadu is one of the places that has been impacted by hydrological droughts which has affected the availability of freshwater resources. Groundwater capacity is one of the critical factors responsible for the occurrence of hydrological drought. This research study aims to classify the groundwater potential zones in the selected study area using geoinformatics and analytical hierarchy process (AHP). Landsat 8 OLI/TIRS and SRTM DEM were used for the preparation of various thematic maps. The AHP technique was adopted to prioritize influential features for delineating the groundwater potential zones. Weighted overlay analysis was performed by assigning weights to each influential parameter. Five classes of groundwater potential were seen at the study area: very poor (0.40%), poor (2.55%), medium (55.24%), good (33.94%) and very good (7.87%). The study reveals that about 55.24% of district falls under medium groundwater potential zone.

Keywords

Geoinformatics, Thematic maps, Analytical hierarchy process, Weighted overlay, Groundwater potential zone

References

  1. Hughes, J.D., K.C. Peltrone and R.P. Silberstein. 2012. Draught, groundwater storage and steam flow decline in southwestern Australia. Geophysical Res. Letters. 39(3): L03408. DOI: 10.1029/2011GL050 797.
  2. Ganapuram, S., et al. 2009. Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Adv. Eng. Software. 40(7): 506-518. DOI: 10.1016/j.advengsoft.2008. 10.001.
  3. Fishman, R.M., et al. 2011. Over-extraction from shallow bedrock versus deep alluvial aquifers: Reliability versus sustainability considerations for India’s groundwater irrigation. Water Resour. Res., 47(6). DOI: 10.1029/2011WR010617.
  4. Van Lanen, H.A.J. and E. Peters. 2000. Definition, effects and assessment of groundwater droughts. In Drought and drought mitigation in Europe. Ed J.V. Vogt and F. Somma. Springer, Dordrecht. pp 49-61. DOI : 10.1007/978-91-015-9472-1_4.
  5. Jeyaraj, E.M., R. Annadurai and M. Kamalanand-hini. 2020. Indentification of soil moisture for drought assessment- A case study in Chengalpattu district, Tamil Nadu, India. Int. J. Adv. Sci. Tech., 29(4s): 699-704.
  6. Kamalanandhini, M., et al. 2021. Assessment of hydrological drought condition and its impact on water quality- A case study in parts of Chengal-pattu district, Tamil Nadu, India. Rasayan J. Chem., 14(1): 51-57. DOI: 10.31788/RJC.2021.14160 957.
  7. Kamalanandhini, M. and R. Annadurai. 2022. Landuse and land cover change detection using geospatial techniques for drought studies in Chengalpattu district, Tamil Nadu, India. Lecture Notes Civil Eng., 207: 563-570. DOI: 10.1007/978-981-16-7509-6_43/COVER.
  8. Kamalanandhini, M. 2023. Scientometric analysis-based review of drought indices for assessment and monitoring of drought. Geographica Pannomica. 27(2): 404-418.
  9. Teeuw, R.M. 1995. Groundwater exploration using remote sensing and a low-cost geographical information system. Hydrogeol. J., 3(3): 21-30. DOI: 10.1007/S100400050057.
  10. Sander, P., M.M. Chesley and T.B. Minor. 1996. Groundwater assessment using remote sensing GIS in a rural groundwater project in Ghana: Lessons learned. Hydrogeol. J., 4(3): 40-49. DOI: 10.1007/S1004000 50086.
  11. Sener, E., A. Davraz and M. Ozcelik. 2005. An integration of GIS and remote sensing in groundwater investigation: A case study in Burdur, Turkey. Hydrogeol. J., 13(5-6): 826-834. DOI: 10.1007/S10040-004-0378-5/TABLES/2.
  12. Shekhar, S. and A.C. Pandey. 2015. Delineation of groundwater potential zone in hard rock terrain of India using remote sensing, geographical information system (GIS) and analytic hierarchy process (AHP) techniques. Geocarto. Int., 30(1): 402-421. DOI: 10.1080/10106049.2014.894584.
  13. Jha, M.K., et al. 2006. Groundwater management and development by integrated remote sensing and geographic information systems: Prospects and constraints. Water Resour. Manage., 21(2): 427-467. DOI: 10.1007/S11269-006-9024-4.
  14. Mallick, J., et al. 2014. Landscape dynamic characteristics using satellite data for a mountainous watershed of Abha, Kingdom of Saudi Arabia. Env. Earth Sci., 72(12): 4973-4984. DOI: 10.1007/S12665-014-3408-I.
  15. Singh, L.K., M.K. Jha and N.M. Chowdary. 2017. Multi-criteria analysis and GIS modelling for identifying prospective water harvesting and artificial recharge sites for sustainable water supply. J. Clean. Prod., 142: 1436-1456. DOI: 10.1016/JJ CLEPRO.2016.11.163.
  16. Chowdhury, A., M.K. Jha and V.M. Chowdhary. 2010. Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Env. Earth Sci., 59(6): 1209-1223. DOI: 10.1007/S12665-009-0110-9/FIGURES/11.
  17. Haikowicz, S. and K. Collins. 2006. A review of multiple criteria analysis for water resource planning and management. Water Resour. Manage., 21(9): 1553-1566. DOI: 10.1007/S11269-006-9112-5.
  18. Murthy, K.S.R. and A.G. Mamo. 2009. Multi-criteria decision evaluation in groundwater zones identification in Moyate-Teltele subbasin, South Ethiopia. Int. J. Remote Sens., 30(11): 2729-2740. DOI: 10.1080/01431160802468255.
  19. Kamalanadhini, M., et al. 2019. Effect of flood event on water quality. Rasayan J. Chem., 12(2): 849-854. DOI: 10.31788/RJC.2019.1225232.
  20. Kamalanandhini, M. and R. Annadurai. 2021a. Assessment of drought condition based on standarized precipitation index and soil moisture condition: A case study in parts of Chengalpattu district, Tamil Nadu, India. J. Green Eng., 11(1): 262-273.
  21. Kamalanandhini, M. and R. Annadurai. 2021b. Assessment of five mateorological indices for monitoring the drought condition in Chengalpattu districts, Tamil Nadu, India. Mater. Today Proceedings. 46(9): 3699-3703. DOI: 10.1016/j.MATPR. 2021.01.850.
  22. Mohan, K., A. Ramasamy and J. Varghese. 2021. Drought severity assessment using automated land surface tempeature retrievel technique. Arbain J. Geosci., 14(22): 1-19. DOI: 10.1007/S12517-021-08672-1.
  23. Saaty, T.L. 1980. The analytic hierachy process. McGraw-Hill, New York.
  24. Rao, B.V. and B.H. Briz-Kishore. 1991. A methodology for locating potential aquifers in a typical semi-arid region India using resistivity and hydrogeologic parameters. Geoexploration. 27(1-2): 55-64. DOI: 10.1016/0016-7142(91)90014-4.
  25. Saaty, T.L. 2008. Decision making with the analytic hierarchy process. Int. J. Services Sci., 1(1): 83-98.
  26. Saaty, T.L. and L.G. Vargas. 1991. Prediction and forecasting. Kluwer Academic Publisher, Amsterdam. DOI: 10.1007/978-91-015-7952-0.