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Prediction Modeling and Mapping of Groundwater Fluoride Contamination throughout India

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Title Prediction Modeling and Mapping of Groundwater Fluoride
Contamination throughout India
 
Creator Podgorski, Joel E.
Labhasetwar, P. K.
Saha, Dipankar
Berg, Michael
 
Subject Water Treatment
 
Description 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.
 
Publisher American Chemical Society
 
Date 2018
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://neeri.csircentral.net/1235/1/acs.est.8b01679.pdf
Podgorski, Joel E. and Labhasetwar, P. K. and Saha, Dipankar and Berg, Michael (2018) Prediction Modeling and Mapping of Groundwater Fluoride Contamination throughout India. Environmental Science and Technology, 52 (17). pp. 9889-9898. ISSN 0013-936X, ESSN: 1520-5851
 
Relation https://pubs.acs.org/journal/esthag
http://neeri.csircentral.net/1235/