Application of data-mining technique and hydro-chemical data for evaluating vulnerability of groundwater in Indo-Gangetic Plain. (15th September 2022)

• Record Type: Journal Article
• Authors: Chandra Pal, Subodh; Towfiqul Islam, Abu Reza Md; Chakrabortty, Rabin; Islam, Md Saiful; Saha, Asish; Shit, Manisa
• Is Part Of: Journal of environmental management. Volume 318(2022)
• Publication Date: 2022-09-15
• Subjects: Vulnerability -- Water resource -- Groundwater development -- Machine learning -- Indo-gangetic plain; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2022.115582
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Vulnerability of groundwater is critical for the sustainable development of groundwater resources, especially in freshwater-limited coastal Indo-Gangetic plains. Here, we intend to develop an integrated novel approach for delineating groundwater vulnerability using hydro-chemical analysis and data-mining methods, i.e., Decision Tree (DT) and K-Nearest Neighbor (KNN) via k-fold cross-validation (CV) technique. A total of 110 of groundwater samples were obtained during the dry and wet seasons to generate an inventory map. Four K-fold CV approach was used to delineate the vulnerable region from sixteen vulnerability causal factors. The statistical error metrics i.e., receiver operating characteristic-area under the curve (AUC-ROC) and other advanced metrices were adopted to validate model outcomes. The results demonstrated the excellent ability of the proposed models to recognize the vulnerability of groundwater zones in the Indo-Gangetic plain. The DT model revealed higher performance (AUC = 0.97) followed by KNN model (AUC = 0.95). The north-central and north-eastern parts are more vulnerable due to high salinity, Nitrate (NO3 − ), Fluoride (F − ) and Arsenic (As) concentrations. Policy-makers and groundwater managers can utilize the proposed integrated novel approach and the outcome of groundwater vulnerability maps to attain sustainable groundwater development and safeguard human-induced activities at the regional level. Graphical abstract: Image 1 Highlights: Assessing groundwater vulnerability in coastal aquifers of lower Bengal basin. Sundarban islands region is recognized as groundwater vulnerability hotspot zone. Decision Tree was the best model for achieving high prediction precision.