Rapid groundwater decline and some cases of recovery in aquifers globally.

Groundwater resources are vital to ecosystems and livelihoods. Excessive groundwater withdrawals can cause groundwater levels to decline1-10, resulting in seawater intrusion11, land subsidence12,13, streamflow depletion14-16 and wells running dry17. However, the global pace and prevalence of local groundwater declines are poorly constrained, because in situ groundwater levels have not been synthesized at the global scale. Here we analyse in situ groundwater-level trends for 170,000 monitoring wells and 1,693 aquifer systems in countries that encompass approximately 75% of global groundwater withdrawals18. We show that rapid groundwater-level declines (>0.5 m year-1) are widespread in the twenty-first century, especially in dry regions with extensive croplands. Critically, we also show that groundwater-level declines have accelerated over the past four decades in 30% of the world's regional aquifers. This widespread acceleration in groundwater-level deepening highlights an urgent need for more effective measures to address groundwater depletion. Our analysis also reveals specific cases in which depletion trends have reversed following policy changes, managed aquifer recharge and surface-water diversions, demonstrating the potential for depleted aquifer systems to recover.

Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model.

Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep-rooted soil and groundwater storage estimates is then used to compute 0.5∘ standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003-2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multi-year water storage fluctuations and those affected by climate teleconnections.

Groundwater recharge estimation using in-situ and GRACE observations in the eastern region of the United Arab Emirates.

The intensive agricultural expansion and rapid urban development in Abu Dhabi Emirate, United Arab Emirates (UAE) have resulted in a major decline in local and regional groundwater levels. By using the latest release (RL06) of Gravity Recovery and Climate Experiment (GRACE) satellite measurements and Global Land Data Assimilation System (GLDAS) products, the groundwater storage change was computed and compared with the time series of in-situ monitoring wells over the period of 2010-2016. The RL06 GRACE products from Jet Propulsion Laboratory (JPL), University of Texas Center for Space Research (CSR), German Research Center for Geosciences (GFZ), and JPL mass concentrations (MASCON) were assessed and have shown satisfactory agreements with the monitoring wells. The JPL MASCON reflected the in-situ groundwater storage change better than the other GRACE products (R = 0.5, lag =1 month, RMSE = 13 mm). The groundwater recharge is estimated for the study area and compared with the in-situ recharge method that considers multi recharge components from the rainfall, irrigation return flow and internal fluxes. The results show that the agreements between in-situ and GRACE-derived recharge estimates are highly agreeable (e.g., R2 = 0.91, RMSE = 1.5 Mm3 to 7.8 Mm3, and Nash-Sutcliff Efficiency = 0.7). Using the Mann-Kendall trend test and Sen's slope, the analyses of policies, number of wells, and farm areal expansion with groundwater time series derived from GRACE helped to validate GRACE and emphasize the importance of regulations for sustainable development of groundwater resources. The impacts of subsidy cuts after 2010 can be captured from the GRACE data in the eastern region of Abu Dhabi Emirate. The linear trend of groundwater storage anomaly obtained from GRACE over the period from 2003 to 2010 is -6.36 ± 0.6 mm/year while it showed a decline trend of -1.2 ± 0.6 mm/year after the subsidy cut. The proposed approach has a potential application for estimating groundwater recharge in other arid regions where in-situ monitoring wells are limited or absent.

The Bengal Water Machine: Quantified freshwater capture in Bangladesh.

Global food security depends on the sustainability of irrigated agriculture. Rising groundwater withdrawals from seasonally humid, alluvial plains across tropical Asia have enabled dry-season rice cultivation. This groundwater pumpage increases available subsurface storage that under favorable conditions amplifies groundwater replenishment during the subsequent monsoon. We empirically quantified this nature-based solution to seasonal freshwater storage capture described as the "Bengal Water Machine," revealing its potential and limitations. On the basis of a million piezometric observations from 465 monitoring wells, we show that the collective operation of ~16 million smallholder farmers in the Bengal Basin of Bangladesh from 1988 to 2018 has induced cumulative freshwater capture that volumetrically (75 to 90 cubic kilometers) is equivalent to twice the reservoir capacity of the Three Gorges Dam.

Consequences of access to water from managed aquifer recharge systems for blood pressure and proteinuria in south-west coastal Bangladesh: a stepped-wedge cluster-randomized trial.

BACKGROUND: Drinking-water salinity has been associated with high blood pressure (BP) among communities in south-west coastal Bangladesh. We evaluated whether access to water from managed aquifer recharge (MAR)-a hydrogeological intervention to lower groundwater salinity by infiltrating rainwater into the aquifers-can reduce community BP. METHODS: We conducted a stepped-wedge cluster-randomized trial with five monthly visits between December 2016 and April 2017 in 16 communities. At each visit following baseline, four communities were randomized to access MAR water. Systolic BP was the primary outcome, measured during each visit using Omron® HEM-907 devices. We also measured participants' 24-hour urinary sodium and households' drinking- and cooking-water salinity each visit. We used multilevel regression models to estimate the effects of MAR-water access on participants' BP. The primary analysis was intention-to-treat. RESULTS: In total, 2911 person-visits were conducted in communities randomized to have MAR-water access and 2834 in communities without MAR-water access. Households without MAR-water access predominantly used low-salinity pond water and 42% (range: 26-50% across visits) of households exclusively consumed MAR water when access was provided. Communities randomized to MAR-water access had 10.34 [95% confidence interval (CI): 1.11, 19.58] mmol/day higher mean urinary sodium, 1.96 (95% CI: 0.66, 3.26; p = 0.004) mmHg higher mean systolic BP and 1.44 (95% CI: 0.40, 2.48; p = 0.007) mmHg higher mean diastolic BP than communities without MAR-water access. CONCLUSIONS: Our findings do not support the scale-up of MAR systems as a routine drinking-water source, since communities that shifted to MAR water from the lower-salinity pond-water source had higher urinary sodium and BP.

Modeling regional-scale groundwater arsenic hazard in the transboundary Ganges River Delta, India and Bangladesh: Infusing physically-based model with machine learning.

For the last few decades, toxic levels of arsenic (As) in groundwater from the aquifers of the Ganges River delta, India and Bangladesh, have been known to cause serious public health concerns. Innumerable studies have advocated the control of geomorphologic, geologic, hydrogeologic, biogeochemical, and anthropogenic factors on arsenic mobilization, flow, and distribution patterns within the Ganges River delta. We have developed transboundary regional-scale models for computing the probability of groundwater As concentrations to exceed the WHO permissible thresholds for drinking water of 10 µg/L within the Ganges River delta as a function of the various geomorphologic-(hydro)geologic-hydrostratigraphic-anthropogenic controlling factors, using statistical methods and artificial intelligence (AI) [i.e., machine learning] techniques namely, Random Forest (RF), Boosted Regression Trees (BRT) and Logistic Regression (LR) algorithms, followed by probabilistic delineation the high As-hazard zones within the delta. A "hybrid multi-modeling approach" was adapted for this study, which involved the introduction of hydrostratigraphic parameters (aquifer connectivity and surficial aquitard thickness) derived from a high-resolution transboundary hydrostratigraphic model developed for the Ganges River delta aquifer system, as predictors for modeling groundwater As probabilities within the delta. The RF model outperforms the BRT and LR model in terms of model performance. Model outputs suggest the dominant influence of surficial aquitard thickness and groundwater-fed irrigated area (%) on groundwater As. While, the north-central and southern regions of the Ganges River delta show low As-hazard (<10 µg/L), the western and north-eastern regions demonstrate elevated hazard level (>10 µg/L). An estimated 30.3 million people are found to be exposed to elevated groundwater As within the study area. Thus, our study demonstrates that such hybrid, predictive models are not only helpful in delineating the regional-scale distribution of groundwater As-hazard zones in the areas with limited As data but is also useful in identifying the possible exogenous forcing that may have led to the worst, natural pollution in human history.

Modeling the Relationship of Groundwater Salinity to Neonatal and Infant Mortality From the Bangladesh Demographic Health Survey 2000 to 2014.

We evaluated the relationship of drinking water salinity to neonatal and infant mortality using Bangladesh Demographic Health Surveys of 2000, 2004, 2007, 2011, and 2014. Point data of groundwater electrical conductivity (EC)- a measure of salinity-were collated from the Bangladesh Water Development Board and digitizing salinity contour map. Data for groundwater dissolved elements (sodium, calcium, magnesium, and potassium) data came from a national hydrochemistry survey in Bangladesh. Point EC and dissolved minerals data were then interpolated over entire Bangladesh and extracted to each cluster location, the primary sampling unit of Bangladesh Demographic Health Surveys. We used restricted cubic splines and survey design-specific logistic regression models to determine the relationship of water salinity to neonatal and infant mortality. A U-shaped association between drinking water salinity and neonatal and infant mortality was found, suggesting higher mortality when salinity was very low and high. Compared to mildly saline (EC ≥0.7 and < 2 mS/cm) water drinkers, freshwater (EC < 0.7 mS/cm) drinkers had 1.37 (95% CI: 1.01, 1.84) times higher neonatal mortality and 1.43 (95% CI: 1.08, 1.89) times higher infant mortality. Compared to mildly saline water drinkers, severe-saline (EC ≥10 mS/cm) water drinkers had 1.77 (95% CI: 1.17, 2.68) times higher neonatal mortality and 1.93 (95% CI: 1.35, 2.76) times higher infant mortality. We found that mild-salinity water had a high concentration of calcium and magnesium, whereas severe-salinity water had a high concentration of sodium. Freshwater had the least concentrations of salubrious calcium and magnesium.

Associations of drinking rainwater with macro-mineral intake and cardiometabolic health: a pooled cohort analysis in Bangladesh, 2016-2019.

This study explores the associations of drinking rainwater with mineral intake and cardiometabolic health in the Bangladeshi population. We pooled 10030 person-visit data on drinking water sources, blood pressure (BP) and 24-h urine minerals. Fasting blood glucose (FBG) was measured in 3724 person-visits, and lipids in 1118 person-visits. We measured concentrations of sodium (Na), potassium (K), calcium (Ca) and magnesium (Mg) in 253 rainwater, 935 groundwater and 130 pond water samples. We used multilevel linear or gamma regression models with participant-, household- and community-level random intercepts to estimate the associations of rainwater consumption with urine minerals and cardiometabolic biomarkers. Rainwater samples had the lowest concentrations of Na, K, Ca and Mg. Rainwater drinkers had lower urine minerals than coastal groundwater drinkers: -13.42 (95% CI: -18.27, -8.57) mmol Na/24 h, -2.00 (95% CI: -3.16, -0.85) mmol K/24 h and -0.57 (95% CI: -1.02, -0.16) mmol Mg/24 h. The ratio of median 24-hour urinary Ca for rainwater versus coastal groundwater drinkers was 0.72 (95% CI: 0.64, 0.80). Rainwater drinkers had 2.15 (95% CI: 1.02, 3.27) mm Hg higher systolic BP, 1.82 (95% CI: 1.19, 2.54) mm Hg higher diastolic BP, 0.59 (95% CI: 0.17, 1.01) mmol/L higher FBG and -2.02 (95% CI: -5.85, 0.81) mg/dl change in high-density lipoprotein cholesterol compared with the coastal groundwater drinkers. Drinking rainwater was associated with worse cardiometabolic health measures, which may be due to the lower intake of salubrious Ca, Mg and K.

Observed controls on resilience of groundwater to climate variability in sub-Saharan Africa.

Groundwater in sub-Saharan Africa supports livelihoods and poverty alleviation1,2, maintains vital ecosystems, and strongly influences terrestrial water and energy budgets3. Yet the hydrological processes that govern groundwater recharge and sustainability-and their sensitivity to climatic variability-are poorly constrained4,5. Given the absence of firm observational constraints, it remains to be seen whether model-based projections of decreased water resources in dry parts of the region4 are justified. Here we show, through analysis of multidecadal groundwater hydrographs across sub-Saharan Africa, that levels of aridity dictate the predominant recharge processes, whereas local hydrogeology influences the type and sensitivity of precipitation-recharge relationships. Recharge in some humid locations varies by as little as five per cent (by coefficient of variation) across a wide range of annual precipitation values. Other regions, by contrast, show roughly linear precipitation-recharge relationships, with precipitation thresholds (of roughly ten millimetres or less per day) governing the initiation of recharge. These thresholds tend to rise as aridity increases, and recharge in drylands is more episodic and increasingly dominated by focused recharge through losses from ephemeral overland flows. Extreme annual recharge is commonly associated with intense rainfall and flooding events, themselves often driven by large-scale climate controls. Intense precipitation, even during years of lower overall precipitation, produces some of the largest years of recharge in some dry subtropical locations. Our results therefore challenge the 'high certainty' consensus regarding decreasing water resources4 in such regions of sub-Saharan Africa. The potential resilience of groundwater to climate variability in many areas that is revealed by these precipitation-recharge relationships is essential for informing reliable predictions of climate-change impacts and adaptation strategies.

Groundwater Chemistry and Blood Pressure: A Cross-Sectional Study in Bangladesh.

Background: We assessed the association of groundwater chemicals with systolic blood pressure (SBP) and diastolic blood pressure (DBP). Methods: Blood pressure data for ≥35-year-olds were from the Bangladesh Demographic and Health Survey in 2011. Groundwater chemicals in 3534 well water samples from Bangladesh were measured by the British Geological Survey (BGS) in 1998-1999. Participants who reported groundwater as their primary source of drinking water were assigned chemical measures from the nearest BGS well. Survey-adjusted linear regression methods were used to assess the association of each groundwater chemical with the log-transformed blood pressure of the participants. Models were adjusted for age, sex, body mass index, smoking status, geographical region, household wealth, rural or urban residence, and educational attainment, and further adjusted for all other groundwater chemicals. Results: One standard deviation (SD) increase in groundwater magnesium was associated with a 0.992 (95% confidence interval (CI): 0.986, 0.998) geometric mean ratio (GMR) of SBP and a 0.991 (95% CI: 0.985, 0.996) GMR of DBP when adjusted for covariates except groundwater chemicals. When additionally adjusted for groundwater chemicals, one SD increase in groundwater magnesium was associated with a 0.984 (95% CI: 0.972, 0.997) GMR of SBP and a 0.990 (95% CI: 0.979, 1.000) GMR of DBP. However, associations were attenuated following Bonferroni-correction for multiple chemical comparisons in the full-adjusted model. Groundwater concentrations of calcium, potassium, silicon, sulfate, barium, zinc, manganese, and iron were not associated with SBP or DBP in the full-adjusted models. Conclusions: Groundwater magnesium had a weak association with lower SBP and DBP of the participants.

Drinking Water Salinity, Urinary Macro-Mineral Excretions, and Blood Pressure in the Southwest Coastal Population of Bangladesh.

Background Sodium (Na+) in saline water may increase blood pressure ( BP ), but potassium (K+), calcium (Ca2+), and magnesium (Mg2+) may lower BP . We assessed the association between drinking water salinity and population BP . Methods and Results We pooled 6487 BP measurements from 2 cohorts in coastal Bangladesh. We used multilevel linear models to estimate BP differences across water salinity categories: fresh water (electrical conductivity, <0.7 mS/cm), mild salinity (electrical conductivity ≥0.7 and <2 mS/cm), and moderate salinity (electrical conductivity ≥2 and <10 mS/cm). We assessed whether salinity categories were associated with hypertension using multilevel multinomial logistic models. Models included participant-, household-, and community-level random intercepts. Models were adjusted for age, sex, body mass index ( BMI ), physical activity, smoking, household wealth, alcohol consumption, sleep hours, religion, and salt consumption. We evaluated the 24-hour urinary minerals across salinity categories, and the associations between urinary minerals and BP using multilevel linear models. Compared with fresh water drinkers, mild-salinity water drinkers had lower mean systolic BP (-1.55 [95% CI : -3.22-0.12] mm Hg) and lower mean diastolic BP (-1.26 [95% CI : -2.21--0.32] mm Hg) adjusted models. The adjusted odds ratio among mild-salinity water drinkers for stage 1 hypertension was 0.60 (95% CI : 0.43-0.84) and for stage 2 hypertension was 0.56 (95% CI : 0.46-0.89). Mild-salinity water drinkers had high urinary Ca2+, and Mg2+, and both urinary Ca2+ and Mg2+ were associated with lower BP. Conclusions Drinking mild-salinity water was associated with lower BP , which can be explained by higher intake of Ca2+ and Mg2+ through saline water.

Arsenic and fasting blood glucose in the context of other drinking water chemicals: a cross-sectional study in Bangladesh.

GOAL: The goal of this study was to evaluate the association between groundwater arsenic and fasting blood glucose in the context of other groundwater chemicals, in Bangladesh. METHODS: Fasting blood glucose, gender, body mass index, sociodemographic variables, and diabetes medication use were measured among adults ≥ 35 years of age (n = 6587) participating in the Bangladesh Demographic and Health Survey (BDHS) 2011. Groundwater chemicals in 3534 well water samples were measured in the British Geological Survey (BGS) and Department of Public Health Engineering (DPHE) 1998-99 survey. We assigned the nearest BGS-DPHE well's chemical exposure to each BDHS participant. We used survey-estimation linear regression methods to model natural log-transformed fasting blood glucose, among those using groundwater as their primary drinking-water source, as a function of groundwater arsenic. We considered possible interactions between categorical arsenic exposure and each of 14 other groundwater chemicals dichotomized at their medians. The chemicals considered as possible effect modifiers included: aluminum, barium, calcium, iron, potassium, lithium, magnesium, manganese, sodium, phosphorous, silicon, sulfate, strontium, and zinc. RESULTS: Compared to persons exposed to groundwater arsenic ≤ 10 µg/L, the adjusted geometric mean ratio (GMR) of fasting blood glucose was 1.01 (95% confidence interval: 0.98, 1.04) for individuals exposed to groundwater arsenic concentrations > 10 µg/L and ≤ 50 µg/L, and was 1.01 (0.97, 1.03) for those with > 50 µg/L arsenic. There were no Bonferroni-significant interactions with other chemicals, after accounting for the large number of chemicals tested as modifiers. CONCLUSIONS: In our analysis of groundwater chemistry data from 1998/99 and fasting blood glucose outcomes measured in nearby populations approximately a decade later, there was no overall association of fasting blood glucose with nearby historical groundwater arsenic. This null association was not significantly modified by the historical levels of other groundwater chemicals. These null results are inconclusive regarding shorter-term potential toxicity of arsenic for glucose regulation, if there are differences between the historical concentrations measured in nearby groundwater and the actual drinking water chemical exposures in the population during the etiologically relevant period for more acute phenotypes like fasting blood glucose. Drinking water supply-relevant, longitudinal exposure assessment with less measurement error is needed to more precisely evaluate the joint impacts of drinking water chemicals and establish if there is a sensitive time window for glycemic outcomes.

Stepped-wedge cluster-randomised controlled trial to assess the cardiovascular health effects of a managed aquifer recharge initiative to reduce drinking water salinity in southwest coastal Bangladesh: study design and rationale.

INTRODUCTION: Saltwater intrusion and salinisation have contributed to drinking water scarcity in many coastal regions globally, leading to dependence on alternative sources for water supply. In southwest coastal Bangladesh, communities have few options but to drink brackish groundwater which has been associated with high blood pressure among the adult population, and pre-eclampsia and gestational hypertension among pregnant women. Managed aquifer recharge (MAR), the purposeful recharge of surface water or rainwater to aquifers to bring hydrological equilibrium, is a potential solution for salinity problem in southwest coastal Bangladesh by creating a freshwater lens within the brackish aquifer. Our study aims to evaluate whether consumption of MAR water improves human health, particularly by reducing blood pressure among communities in coastal Bangladesh. METHODS AND ANALYSIS: The study employs a stepped-wedge cluster-randomised controlled community trial design in 16 communities over five monthly visits. During each visit, we will collect data on participants' source of drinking and cooking water and measure the salinity level and electrical conductivity of household stored water. At each visit, we will also measure the blood pressure of participants ≥20 years of age and pregnant women and collect urine samples for urinary sodium and protein measurements. We will use generalised linear mixed models to determine the association of access to MAR water on blood pressure of the participants. ETHICS AND DISSEMINATION: The study protocol has been reviewed and approved by the Institutional Review Boards of the International Centre for Diarrheal Disease Research, Bangladesh (icddr,b). Informed written consent will be taken from all the participants. This study is funded by Wellcome Trust, UK. The study findings will be disseminated to the government partners, at research conferences and in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT02746003; Pre-results.

A generalized regression model of arsenic variations in the shallow groundwater of Bangladesh.

Localized studies of arsenic (As) in Bangladesh have reached disparate conclusions regarding the impact of irrigation-induced recharge on As concentrations in shallow (≤50 m below ground level) groundwater. We construct generalized regression models (GRMs) to describe observed spatial variations in As concentrations in shallow groundwater both (i) nationally, and (ii) regionally within Holocene deposits where As concentrations in groundwater are generally high (>10 µg L-1). At these scales, the GRMs reveal statistically significant inverse associations between observed As concentrations and two covariates: (1) hydraulic conductivity of the shallow aquifer and (2) net increase in mean recharge between predeveloped and developed groundwater-fed irrigation periods. Further, the GRMs show that the spatial variation of groundwater As concentrations is well explained by not only surface geology but also statistical interactions (i.e., combined effects) between surface geology and mean groundwater recharge, thickness of surficial silt and clay, and well depth. Net increases in recharge result from intensive groundwater abstraction for irrigation, which induces additional recharge where it is enabled by a permeable surface geology. Collectively, these statistical associations indicate that irrigation-induced recharge serves to flush mobile As from shallow groundwater.