Chakraborti D, Mukherjee SC, Pati S, Sengupta MK, Rahman MM, Chowdhury UK, Lodh D,
Chanda CR, Chakraborti AK, Basu GK (2003) Arsenic groundwater contamination in Middle
Ganga Plain, Bihar, India: a future danger? Environ Health Perspect 111(9):1194–1198
Chakraborti D, Rahman MM, Chatterjee A, Das D, Das B, Nayak B, Pal A, Chowdhury UK,
Ahmed S, Biswas BK (2016) Fate of over 480 million inhabitants living in arsenic and fluoride
endemic Indian districts: magnitude, health, socio-economic effects and mitigation approaches.
J Trace Ele Med Biol 38:33–45
Chakraborti D, Singh SK, Rashid HM, Rahman MM (2017) Arsenic: occurrence in groundwater.
Encyclopedia of environmental health, vol 2. Elsevier, Burlington, pp 1–17. https://doi.org/10.
1016/B978-0-12-409548-9.10634-7
Chakraborti D, Singh SK, Rahman MM, Dutta RN, Mukherjee SC, Pati S, Kar PB (2018)
Groundwater arsenic contamination in the Ganga River basin: a future health danger. Int J
Environ Res Pub Health 15(2):180. https://doi.org/10.3390/ijerph15020180
Chapi K, Singh VP, Shirzadi A, Shahabi H, Bui DT, Pham BT, Khosravi K (2017) A novel hybrid
artificial intelligence approach for flood susceptibility assessment. Environ Model Softw
95:229–245
Chapman DV (1996) Water quality assessments: a guide to the use of biota, sediments, and water in
environmental monitoring
Chau K (2006) A review on integration of artificial intelligence into water quality modelling.
Marine Pollut Bullet 52(7):726–733
Chen W, Pradhan B, Li S, Shahabi H, Rizeei HM, Hou E, Wang S (2019) Novel hybrid integration
approach of bagging-based fisher’s linear discriminant function for groundwater potential
analysis. Nat Resour Res 28(4):1239–1258
Cho KH, Sthiannopkao S, Pachepsky YA, Kim KW, Kim JH (2011) Prediction of contamination
potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural
network. Water Res 45(17):5535–5544
Crocker J, Bartram J (2014) Comparison and cost analysis of drinking water quality monitoring
requirements versus practice in seven developing countries. Int J Environ Res Pub Health 11
(7):7333–7346
Eckhardt DAV, Stackelberg PE (1995) Relation of ground-water quality to land use on Long Island,
New York. Groundwater 33(6):1019–1033
Elío J, Crowley Q, Scanlon R, Hodgson J, Long S (2017) Logistic regression model for detecting
radon prone areas in Ireland. Sci Total Environ 599:1317–1329
Erickson ML, Elliott SM, Christenson CA, Krall AL (2018) Predicting geogenic arsenic in drinking
water wells in glacial aquifers, North-Central USA: accounting for depth-dependent features.
Water Resour Res 54(12):172–187
Evans S, Campbell C, Naidenko OV (2019) Cumulative risk analysis of carcinogenic contaminants
in United States drinking water. Heliyon 5(9):e02314
Focazio MJ (2002) Assessing ground-water vulnerability to contamination: providing scientifically
defensible information for decision makers. Vol. 1224: US Department of the Interior, US
Geological Survey
Gamble A (2019) Ullmann’s encyclopedia of industrial chemistry. Charleston Advisor 20(4):46–50
Grandjean P (2019) Developmental fluoride neurotoxicity: an updated review. Environ Health 18
(1):1–17
Jha SK, Singh RK, Damodaran T, Mishra VK, Sharma DK, Rai D (2013) Fluoride in groundwater:
toxicological exposure and remedies. J Toxicol Environ Health B 16(1):52–66
Kabir H, Gupta AK, Tripathy S (2020) Fluoride and human health: systematic appraisal of sources,
exposures, metabolism, and toxicity. Crit Rev Environ Sci Technol 50(11):1116–1193
Keeney DR (1989) Sources of nitrate to ground water. In: Developments in agricultural and
managed forest ecology. Elsevier, pp 23–34
Khosravi K, Barzegar R, Miraki S, Adamowski J, Daggupati P, Alizadeh MR, Pham BT, Alami MT
(2019) Stochastic modeling of groundwater fluoride contamination: introducing lazy learners.
Groundwater. https://doi.org/10.1111/gwat.12963
102
S. K. Singh et al.
Chanda CR, Chakraborti AK, Basu GK (2003) Arsenic groundwater contamination in Middle
Ganga Plain, Bihar, India: a future danger? Environ Health Perspect 111(9):1194–1198
Chakraborti D, Rahman MM, Chatterjee A, Das D, Das B, Nayak B, Pal A, Chowdhury UK,
Ahmed S, Biswas BK (2016) Fate of over 480 million inhabitants living in arsenic and fluoride
endemic Indian districts: magnitude, health, socio-economic effects and mitigation approaches.
J Trace Ele Med Biol 38:33–45
Chakraborti D, Singh SK, Rashid HM, Rahman MM (2017) Arsenic: occurrence in groundwater.
Encyclopedia of environmental health, vol 2. Elsevier, Burlington, pp 1–17. https://doi.org/10.
1016/B978-0-12-409548-9.10634-7
Chakraborti D, Singh SK, Rahman MM, Dutta RN, Mukherjee SC, Pati S, Kar PB (2018)
Groundwater arsenic contamination in the Ganga River basin: a future health danger. Int J
Environ Res Pub Health 15(2):180. https://doi.org/10.3390/ijerph15020180
Chapi K, Singh VP, Shirzadi A, Shahabi H, Bui DT, Pham BT, Khosravi K (2017) A novel hybrid
artificial intelligence approach for flood susceptibility assessment. Environ Model Softw
95:229–245
Chapman DV (1996) Water quality assessments: a guide to the use of biota, sediments, and water in
environmental monitoring
Chau K (2006) A review on integration of artificial intelligence into water quality modelling.
Marine Pollut Bullet 52(7):726–733
Chen W, Pradhan B, Li S, Shahabi H, Rizeei HM, Hou E, Wang S (2019) Novel hybrid integration
approach of bagging-based fisher’s linear discriminant function for groundwater potential
analysis. Nat Resour Res 28(4):1239–1258
Cho KH, Sthiannopkao S, Pachepsky YA, Kim KW, Kim JH (2011) Prediction of contamination
potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural
network. Water Res 45(17):5535–5544
Crocker J, Bartram J (2014) Comparison and cost analysis of drinking water quality monitoring
requirements versus practice in seven developing countries. Int J Environ Res Pub Health 11
(7):7333–7346
Eckhardt DAV, Stackelberg PE (1995) Relation of ground-water quality to land use on Long Island,
New York. Groundwater 33(6):1019–1033
Elío J, Crowley Q, Scanlon R, Hodgson J, Long S (2017) Logistic regression model for detecting
radon prone areas in Ireland. Sci Total Environ 599:1317–1329
Erickson ML, Elliott SM, Christenson CA, Krall AL (2018) Predicting geogenic arsenic in drinking
water wells in glacial aquifers, North-Central USA: accounting for depth-dependent features.
Water Resour Res 54(12):172–187
Evans S, Campbell C, Naidenko OV (2019) Cumulative risk analysis of carcinogenic contaminants
in United States drinking water. Heliyon 5(9):e02314
Focazio MJ (2002) Assessing ground-water vulnerability to contamination: providing scientifically
defensible information for decision makers. Vol. 1224: US Department of the Interior, US
Geological Survey
Gamble A (2019) Ullmann’s encyclopedia of industrial chemistry. Charleston Advisor 20(4):46–50
Grandjean P (2019) Developmental fluoride neurotoxicity: an updated review. Environ Health 18
(1):1–17
Jha SK, Singh RK, Damodaran T, Mishra VK, Sharma DK, Rai D (2013) Fluoride in groundwater:
toxicological exposure and remedies. J Toxicol Environ Health B 16(1):52–66
Kabir H, Gupta AK, Tripathy S (2020) Fluoride and human health: systematic appraisal of sources,
exposures, metabolism, and toxicity. Crit Rev Environ Sci Technol 50(11):1116–1193
Keeney DR (1989) Sources of nitrate to ground water. In: Developments in agricultural and
managed forest ecology. Elsevier, pp 23–34
Khosravi K, Barzegar R, Miraki S, Adamowski J, Daggupati P, Alizadeh MR, Pham BT, Alami MT
(2019) Stochastic modeling of groundwater fluoride contamination: introducing lazy learners.
Groundwater. https://doi.org/10.1111/gwat.12963
102
S. K. Singh et al.