Effects of elevated arsenic and nitrate concentrations on groundwater resources in deltaic region of Sundarban Ramsar site, Indo-Bangladesh region. (March 2023)

• Record Type: Journal Article
• Authors: Biswas, Tanmoy; Pal, Subodh Chandra; Chowdhuri, Indrajit; Ruidas, Dipankar; Saha, Asish; Islam, Abu Reza Md. Towfiqul; Shit, Manisa
• Is Part Of: Marine pollution bulletin. Volume 188(2023)
• Publication Date: 2023-03
• Subjects: As Arsenic -- BIS Bureau of Indian Standard -- Cl− Chlorine -- EC Electrical Conductivity -- F− Fluoride -- GW Groundwater -- GWQ Groundwater Quality -- HCO3− Bicarbonate -- IDW Inverse Distance Weighted -- K+ Potassium -- LULC Land Use and Land Cover -- MCA Multi-Collinearity Analysis -- Mg2+ Magnesium -- ML Machine Learning -- MSL Mean Sea Level -- Na+ Sodium -- NB Naïve Bayes -- NB-Bagging Naïve Bayes - Bagging -- NB-RF Naïve Bayes - Random Forest -- NB-SVM Naïve Bayes - Support Vector Machine -- NO3− Nitrate -- PCM Pearson Correlation Matrix -- pH Potential of Hydrogen -- PMS Plasma Mass Spectrometry -- PO42− Phosphate -- RF Random Forest -- ROC-AUC Receiver Operating Characteristic Curve – Area Under Curve -- SEE Standard Error of Estimation -- SO42− Sulphate -- SVM Support Vector Machine -- TOL Tolerance -- UN United Nations -- VIF Variance Inflation Factor -- VWR Vulnerability of Water Resource -- WHO World Health Organization; Indo-Bangladesh Ramsar site -- As and NO3− concentration -- Vulnerability assessment -- Taylor diagram -- ROC-AUC; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2023.114618
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: An attempt has been adopted to predict the As and NO3 − concentration in groundwater (GW) in fast-growing coastal Ramsar region in eastern India. This study is focused to evaluate the As and NO3 − vulnerable areas of coastal belts of the Indo-Bangladesh Ramsar site a hydro-geostrategic region of the world by using advanced ensemble ML techniques including NB-RF, NB-SVM and NB-Bagging. A total of 199 samples were collected from the entire study area for utilizing the 12 GWQ conditioning factors. The predicted results are certified that NB-Bagging the most suitable and preferable model in this current research. The vulnerability of As and NO3 − concentration shows that most of the areas are highly vulnerable to As and low to moderately vulnerable to NO3 . The reliable findings of this present study will help the management authorities and policymakers in taking preventive measures in reducing the vulnerability of water resources and corresponding health risks. Graphical abstract: Unlabelled Image Highlights: Most important factors influencing As and NO3 - concentration are Mg2, pH and depth. Sundarban islands regions have been identified as As and NO3 - pollution hotspot. NB-Bagging was the best model for achieving high prediction precision.