Literature DB >> 30052029

Prediction Modeling and Mapping of Groundwater Fluoride Contamination throughout India.

Joel E Podgorski1, Pawan Labhasetwar2, Dipankar Saha3, Michael Berg1.   

Abstract

For about the past eight decades, high concentrations of naturally occurring fluoride have been detected in groundwater in different parts of India. The chronic consumption of fluoride in high concentrations is recognized to cause dental and skeletal fluorosis. We have used the random forest machine-learning algorithm to model a data set of 12 600 groundwater fluoride concentrations from throughout India along with spatially continuous predictor variables of predominantly geology, climate, and soil parameters. Despite only surface parameters being available to describe a subsurface phenomenon, this has produced a highly accurate prediction map of fluoride concentrations exceeding 1.5 mg/L at 1 km resolution throughout the country. The most affected areas are the northwestern states/territories of Delhi, Gujarat, Haryana, Punjab, and Rajasthan and the southern states of Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana. The total number of people at risk of fluorosis due to fluoride in groundwater is predicted to be around 120 million, or 9% of the population. This number is based on rural populations and accounts for average rates of groundwater consumption from nonmanaged sources. The new fluoride hazard and risk maps can be used by authorities in conjunction with detailed groundwater utilization information to prioritize areas in need of mitigation measures.

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Year:  2018        PMID: 30052029     DOI: 10.1021/acs.est.8b01679

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  6 in total

1.  Tracing geochemical sources and health risk assessment of uranium in groundwater of arid zone of India.

Authors:  P Pandit; Atul Saini; Sabarathinam Chidambaram; Vinod Kumar; Banjarani Panda; A L Ramanathan; Netrananda Sahu; A K Singh; Rohit Mehra
Journal:  Sci Rep       Date:  2022-06-01       Impact factor: 4.996

2.  Version 3 of the Global Aridity Index and Potential Evapotranspiration Database.

Authors:  Robert J Zomer; Jianchu Xu; Antonio Trabucco
Journal:  Sci Data       Date:  2022-07-15       Impact factor: 8.501

3.  Predicting the Distribution of Arsenic in Groundwater by a Geospatial Machine Learning Technique in the Two Most Affected Districts of Assam, India: The Public Health Implications.

Authors:  Bibhash Nath; Runti Chowdhury; Wenge Ni-Meister; Chandan Mahanta
Journal:  Geohealth       Date:  2022-03-01

4.  Global analysis and prediction of fluoride in groundwater.

Authors:  Joel Podgorski; Michael Berg
Journal:  Nat Commun       Date:  2022-08-01       Impact factor: 17.694

5.  A Systems Approach to Remediating Human Exposure to Arsenic and Fluoride From Overexploited Aquifers.

Authors:  P S K Knappett; P Farias; G R Miller; J Hoogesteger; Y Li; I Mendoza-Sanchez; R T Woodward; H Hernandez; I Loza-Aguirre; S Datta; Y Huang; G Carrillo; T Roh; D Terrell
Journal:  Geohealth       Date:  2022-07-01

6.  Groundwater Arsenic Distribution in India by Machine Learning Geospatial Modeling.

Authors:  Joel Podgorski; Ruohan Wu; Biswajit Chakravorty; David A Polya
Journal:  Int J Environ Res Public Health       Date:  2020-09-28       Impact factor: 3.390

  6 in total

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