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 30.5% to 28% and polluted water increased from 44% to 45%. ANOVA and Friedman tests revealed statistically significant differences (p < 0.0001) in year-wise water quality parameters as well as group comparisons for both years. Landsat 7 and 8 satellite images were used to classify the LULC types applying machine learning tools for both years, and were coupled with response surface methodology (RSM) for the first time, which revealed that the alteration of groundwater quality were attributed to LULC changes, e.g. WPI showed a positive correlation with built-up areas, village-vegetation cover, agricultural lands, and a negative correlation with surface water, barren lands, and forest cover. Expansion in built-up areas by 0.7%, and village-vegetation orchards by 2.3%, accompanied by a reduction in surface water coverage by 0.6%, and 2.4% in croplands caused a 1.5% drop in excellent water and 1% increase in polluted water category. However, ecological risks through the ecological risk index (ERI) exhibited a lower risk in 2021 attributed to reduced high-risk potential zones. This study highlights the potentiality in linking LULC and water quality changes using some advanced statistical tools like GIS and RSM for better management of water quality and landscape ecology.

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 17.6 mg/L, with 70% of samples reported beyond the modified regional optimal fluoride level (0.7 mg/L) with a statistically significant level of p < 1.7E-24. The average cation and anion concentrations exhibited a descending order of Ca2+ > Mg2+ > Na+ > K+ and HCO3- > Cl- > SO42- > NO3- > F-, respectively. Notably, groundwater quality in 50% of the places ranged from poor to unfit for drinking purposes in terms of water quality index. The mean total hazard index (THI) was 1.1 for adults and 1.9 for children, signifying a greater chance of non-carcinogenic threats to both age groups. In calculating the THI, ingestion and dermal pathways accounted for approximately 96% and 3% health hazards, respectively. The Monte Carlo simulation and sensitivity analysis identified that the diurnal water ingestion rate, exposure duration, and fluoride concentration were the significant sensitive variables that triggered most groundwater-associated non-carcinogenic health issues, signifying more risks among children. Further, dental health surveys (N = 746), following Dean's norms for classification based on regional optimal fluoride level, designated the borderline grade of the community dental hazard. The subsequent hydrogeochemical characterization directed that dissolution from fluoride-bearing minerals and water-rock interaction, such as halite dissolution and calcite-dolomite precipitation, were the governing factors for F- enrichment in groundwater. This study will serve as baseline data for delineating fluoride-induced dental and other health hazards through sensitivity and spatial analysis in the GIS platform for hazard zonation and effective groundwater quality management.

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). The mean concentration of TEs were found as Fe (855.88 µg/L)> Zn (204.0 µg/L)> Cu(84.9 µg/L)> Ni(47.31 µg/L)> Pb(14.43 µg/L)> Co(10.58 µg/L)> Cd (7.88 µg/L). It indicated serious contamination by Fe, Cd. Pb and Ni according BIS, 2012. Pollution indicators such as heavy metal pollution index (HPI) revealed that study area is heavily contaminated by these TEs. Incremental lifetime cancer risk (ILCR) value of TEs showed that Cd is the main offender for cancer risk. Average value of total hazard index (THI), was found to be 2.48. THI through ingestion pathways was found to be more risky than dermal contacts accounting for 88% and 12% health hazard respectively. The sensitivity analysis indicated ingestion rate, exposure time, and TEs concentration were the most influential parameters for all groundwater associated health hazards. The TEs affected areas were mapped through Empirical Bayesian Kriging geostatistical model and health risk prone zones were projected. The study demonstrated that Monte Carlo simulation and EBK can provide better accuracy in health risks prediction and spatial distribution analysis of contaminants in any geographical area. The TEs and their hazard zonation mapping with geostatistical modelling will be helpful for the policy makers and researchers to improve groundwater quality management practices.

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. The groundwater samples (N = 368) were grouped based on their hydrochemical properties and aquifer geology for hydro-geochemical characterization. Friedman's test showed p < 0.0001 confidence level which indicates that fluoride concentration among geological groups and water groups are independent. Bland-Altman plot was used to study the inter-relationships among the groups through bias value (∂) and limit of agreement (LoA). Among the geological groups, laterites and granite-gneiss groups exhibited statistically significantly difference in fluoride geochemistry; whereas the younger and older alluvium groups displayed similar characteristics. The fluoride concentration was found to be in the order Lateritic > Granite-gneiss > Older alluvium ≥ Younger alluvium. Dissolution of minerals (such as fluorite, biotite) in laterite sheeted basalt, and granite-gneiss is the main source of groundwater fluoride in the region. Fluoride concentration is also influenced by depth of water table. Hydrochemical study indicated that fluoride concentration was higher in Na-HCO3 than in Ca-SO4 and Ca-HCO3 type of groundwater. The fluoride concentration were positively correlated with Na+ and pH and negatively correlated with the Ca2+ and Mg2+ signifying linkage with halite dissolution and calcite, dolomite precipitation. Geostatistical mapping of WQI through empirical bayesian kriging (EBK) with respect to regional optimal guideline value (0.73 mg/L) classified that groundwater in some parts of the district are unfit for drinking purpose. Health survey (N = 1767) based on Dean's criteria for dental fluorosis indicated presence of slight to moderate dental hazard. Besides, providing baseline data for management of groundwater quality in the study area, the study demonstrated the applicability of Bland-Altman analysis and empirical bayesian kriging (EBK) in delineation and interpolation of fluoride contaminated region.

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. The Empirical Bayesian Kriging geostatistical model was employed to determine fluoride endemic areas. Amongst all blocks, Nalhati-1 had exhibited the highest fluoride level (18.25 mg/L). The study revealed that most of the blocks are vulnerable to groundwater fluoride due to its occurrences in excess level. The average and 95th percentile values of total hazard index indicate that the infants and children populations of the district are more susceptible than the adults and teens. The sensitivity analysis revealed that water ingestion rate and fluoride concentration are the most influential parameters for higher risk of fluoride-related health hazards. Health risks were evaluated through ingestion and dermal exposure routes for infants, children, teens, and adult residents. The exposure was much higher through ingestion than dermal contacts. Ingestion of defluoridated water will reduce the health risks associated with groundwater fluoride exposure.