A Geographic Information System (GIS) and Remote Sensing Approach for Delineation of Groundwater Quality Index

DOI

10.2991/978-94-6463-940-7_2How to use a DOI?

Keywords

Water Quality Index; Spatial distribution; Geographic information system; Groundwater

Abstract

All living things need water, a basic and accessible element. Humans benefit much from groundwater. In the preceding years, landfills, factories, and non-point sources including fertilizer and pesticides impacted groundwater levels. It's crucial to analyze the water's quality for current and future use because it may provide a long-term supply. Rural India relies on groundwater for drinking water. Groundwater is a major alternative to surface water for household use, therefore its quality is crucial in rural Khordha District, where drinking water safety is a major issue. This study uses remote sensing and GIS to examine sgroundwater quality and distribution. Water quality parameters like total hardness (TH), pH, bicarbonate, sodium, potassium, calcium, magnesium, nitrate, fluoride, chloride, sulfate, and bicarbonate were measured at 13 sites. Results were utilized to establish water quality index. Except for a few areas in the south and north that have “poor water,” the spatial distribution map classifies the whole study region as having “excellent water” or “good water.” The current investigation found that excessive fluoride and nitrate induced high “Water Quality Index” (WQI) values in groundwater samples. Combining GIS with WQI to assess groundwater quality is effective, as shown by this study’s results. Understanding the best groundwater quality areas may help decision-makers prepare for groundwater resource maintenance and operation.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Emmanuel Gaen
AU  - Smruti Pragyan Parija
AU  - Atulya Kumar Mohanty
AU  - Somnath Khaoash
AU  - Priyajit Samal
AU  - Patitapaban Mishra
PY  - 2025
DA  - 2025/12/31
TI  - A Geographic Information System (GIS) and Remote Sensing Approach for Delineation of Groundwater Quality Index
BT  - Proceedings of the Conference on Social and Sustainable Innovation in Technology & Engineering (SASI-ITE 2025)
PB  - Atlantis Press
SP  - 4
EP  - 15
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-940-7_2
DO  - 10.2991/978-94-6463-940-7_2
ID  - Gaen2025
ER  -