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Multi-decadal groundwater variability analysis using geostatistical method for groundwater sustainability

Author

Listed:
  • Zubairul Islam

    (Adigrat University)

  • Muthukumarasamy Ranganathan

    (CSSH, Adigrat University)

  • Murugesan Bagyaraj

    (Debre Berhan University)

  • Sudhir Kumar Singh

    (University of Allahabad)

  • Sandeep Kumar Gautam

    (University of Lucknow)

Abstract

The general aim of the present study was to understand the groundwater level change of period 2001–2020 using geostatistical analysis at village level of Cuddalore district, Tamil Nadu, India. Further, three specific objectives were delineated as follows: to find the spatial pattern of groundwater level change, to estimate hot and cold spots of groundwater level change, and to model spatially varying relationship between change in groundwater level and population density. The groundwater level data have been downloaded from Central Ground Water Board (CGWB), Government of India. Gridded Population version 4 (GPWv4.11) dataset was downloaded for population density analysis. The Moran’s I method was applied to remove spatial autocorrelation as it is a correlation coefficient that measures the spatial autocorrelation present in a data. Hotspot analysis was performed to create statistically significant map of hot and cold spots with the help of Getis-Ord Gi* statistic. Geographically weighted regression (GWR) tool was implemented for modeling spatially varying relationship. The analysis results show the spatial pattern of groundwater level change is highly clustered, the z-score (57.53), which verify that the clustered sequence could be the outcome of random chance due to less than 1% likelihood. Groundwater level is found decreasing in 75% of the study area. The results of the GWR model show more groundwater level change than expected in relation to change in population density as 143 villages were classified within the band of 0.5–1.5 standard deviation, 35 villages were classified within the band of 1.5–2.5 standard deviation and 25 villages were classified in the band of > 2.5 standard deviation. Further, results indicate that groundwater level is decreasing at an alarming rate in the area. Hence, it is particularly important for policy makers to formulate policies, programs and projects specific to this region and to minimize groundwater level depletion.

Suggested Citation

  • Zubairul Islam & Muthukumarasamy Ranganathan & Murugesan Bagyaraj & Sudhir Kumar Singh & Sandeep Kumar Gautam, 2022. "Multi-decadal groundwater variability analysis using geostatistical method for groundwater sustainability," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3146-3164, March.
    • Handle: RePEc:spr:endesu:v:24:y:2022:i:3:d:10.1007_s10668-021-01563-1
    DOI: 10.1007/s10668-021-01563-1
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    References listed on IDEAS

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    1. B. Anand & D. Karunanidhi & T. Subramani & K. Srinivasamoorthy & M. Suresh, 2020. "Long-term trend detection and spatiotemporal analysis of groundwater levels using GIS techniques in Lower Bhavani River basin, Tamil Nadu, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(4), pages 2779-2800, April.
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    4. Sudhir Singh & Prashant Srivastava & Avinash Pandey & Sandeep Gautam, 2013. "Integrated Assessment of Groundwater Influenced by a Confluence River System: Concurrence with Remote Sensing and Geochemical Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4291-4313, September.
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