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Assessing groundwater quality for drinking water supply using hybrid fuzzy-GIS-based water quality index

Geographical Information System (GIS)-based groundwater quality evaluation using Groundwater Quality Index (GQI) has been proved to be a cost-effective tool for assessing groundwater quality and its variability at a larger scale.

Researchers:

  • Madan Kumar Jha
  • Ankit Shekar
  • M. Annie Jenifer

Abstract: 

Groundwater is a vital source of freshwater in both urban and rural regions of the world. However, its injudicious abstraction and rapidly increasing contamination are posing a severe threat for sustainable water supply worldwide. Geographical Information System (GIS)-based groundwater quality evaluation using Groundwater Quality Index (GQI) has been proved to be a cost-effective tool for assessing groundwater quality and its variability at a larger scale. However, the conventional GQI approach is unable to deal with uncertainties involved in the assessment of environmental problems. To overcome this limitation, a novel hybrid framework integrating Fuzzy Logic with the GIS-based GQI is proposed in this study for assessing groundwater quality and its spatial variability. The proposed hybrid framework is demonstrated through a case study in a hard-rock terrain of Southern India using ten prominent groundwater-quality parameters measured during pre-monsoon and post-monsoon seasons.

Two con- ventional GIS-based GQI models GQI-10 (using all the ten groundwater-quality parameters) and GQI-7 (using seven ‘concerned/critical’ groundwater-quality parameters) as well as hybrid Fuzzy-GIS-based GQI (FGQI) models (using seven critical parameters) were developed for the two seasons and the re- sults were compared. The Trapezoidal membership functions classified the model input parameters into ‘desirable’, ‘acceptable’ and ‘unacceptable’ classes based on the experts’ knowledge and water quality standards for drinking purposes.

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Citation:

Kumar Jha, Madan., Shekhar, Ankit., Jenifer, M. Annie. Assessing groundwater quality for drinking water supply using hybrid fuzzy-GIS-based water quality index. (2020) doi:10.1016/j.watres.2020.115867