Groundwater vulnerability assessment using GIS-based DRASTIC model in Nangasai River Basin, India with special emphasis on agricultural contamination

Ecotoxicol Environ Saf. 2021 May:214:112085. doi: 10.1016/j.ecoenv.2021.112085. Epub 2021 Mar 6.

Abstract

Nangasai basin is a semi-arid watershed where agriculture is the main source of economy. In present day, increasing population demands increase in food productivity which leads to increase use of fertilizers and chemical pesticides in agriculture. These fertilizers on the other hand mix up with the groundwater and increase the pollution, which affects human health adversely. So, for controlling the groundwater contamination risk proper water resource management and assessment of groundwater vulnerability is extremely important. Total 7 hydrogeological parameters have been considered for this study, and the final groundwater vulnerability map has been prepared by overlay weighted method with the help of DRASTIC index, which is classified into 5 vulnerable classes (very high, high, moderate, low, and very low). In the south and south-eastern regions of the basin namely Deghi, Bankada, Baram, Macha, Katin, Tilabani high groundwater contamination is been observed. For validating the model, the water quality parameters-nitrate and TDS have been used with the accuracy of 89% and 86% respectively. Using effective as well as scientifically approved methods, the anthropogenic and agricultural contamination can be controlled and managed which will lower the risk of contamination. This map can be further utilized as a base map for management of groundwater pollution and its planning.

Keywords: DRASTIC; GIS; Groundwater contamination; Nangasai basin; Nitrate and TDS concentration; Thematic layers.

MeSH terms

  • Agriculture*
  • Environmental Monitoring / methods*
  • Geographic Information Systems
  • Groundwater
  • Humans
  • India
  • Nitrates
  • Pesticides
  • Rivers
  • Water Pollutants, Chemical / analysis
  • Water Pollution / analysis
  • Water Pollution / statistics & numerical data*
  • Water Resources

Substances

  • Nitrates
  • Pesticides
  • Water Pollutants, Chemical