A machine learning approach to investigate the impact of land use land cover (LULC) changes on groundwater quality, health risks and ecological risks through GIS and response surface methodology (RSM).

Groundwater resources are enormously affected by land use land cover (LULC) dynamics caused by increasing urbanisation, agricultural and household discharge as a result of global population growth. This study investigates the impact of decadal LULC changes in groundwater quality, human and ecological health from 2009 to 2021 in a diverse landscape, West Bengal, India. Using groundwater quality data from 479 wells in 2009 and 734 well in 2021, a recently proposed Water Pollution Index (WPI) was computed, and its geospatial distribution by a machine learning-based 'Empirical Bayesian Kriging' (EBK) tool manifested a decline in water quality since the number of excellent water category decreased from 30.

Sensitive assessment of groundwater-associated, multi-exposure health hazards in a fluoride-enriched region of West Bengal, India.

Ninety groundwater samples were collected from Khayrasole and Rajnagar blocks of Birbhum district, West Bengal, India, during pre-monsoon and post-monsoon in 2016 to assess the hazards of fluoride in groundwater. Fluoride concentration fluctuated from 0.3 to 17.

Contamination zoning and health risk assessment of trace elements in groundwater through geostatistical modelling.

Trace elements (TEs) concentration in groundwater is a key factor for health risk assessment (HRA). To achieve high level of accuracy in HRA, the present study performed Monte Carlo simulations, sensitivity analysis and uncertainty analysis to a total of 184 (N = 184) groundwater samples, collected during December 2016 from Birbhum district. TEs in samples were detected by anodic stripping voltammetry (ASV).

Hydrogeochemical characterisation and health hazards of fluoride enriched groundwater in diverse aquifer types.

High concentration of fluoride (up to 20.9 mg/L) in groundwater with significant variation (p = 5.9E-128) among samples was reported from Birbhum district, an acknowledged fluoride endemic region in India.

Exploring a multi-exposure-pathway approach to assess human health risk associated with groundwater fluoride exposure in the semi-arid region of east India.

Human health risks associated with groundwater fluoride have been assessed using USEPA method in few parts of India, but those assessments were conducted based on a single value for each parameter, which may lead to certain inaccuracy and uncertainties in results. In this study, a higher degree of accuracy in health risk assessment was achieved through Monte Carlo simulations, sensitivity analysis and uncertainty analysis. As fluoride hazards to human health are chronic, a total of 4560 water samples (N = 4560) were collected during consecutive four seasons (2 pre-monsoon and 2 post-monsoon seasons; 1140 samples/season) from the entire Birbhum district, covering all the blocks and geological settings to obtain the spatiotemporal variation of fluoride level.