Glacial Aquifer Research Articles

Three‐Dimensional Probabilistic Hydrofacies Modeling Using Machine Learning

AbstractCharacterizing the 3D distribution of hydraulic properties in glacial sediments is challenging due to fine‐scale heterogeneity and complexity. Borehole lithological data provide high vertical resolution but low horizontal resolution. Geophysical methods can fill gaps between boreholes, providing improved horizontal resolution but low vertical resolution. Machine learning can combine borehole and geophysical data to overcome these challenges. However, few studies have compared multiple machine learning methods for predicting hydrofacies in glacial aquifer systems. This study uses colocated airborne electromagnetic resistivity and borehole lithology data to train multiple machine learning models and predict the 3D distribution of hydrofacies in glacial deposits of eastern Nebraska, USA. Random Forest, Gradient Boosting Classifier, Extreme Gradient Boosting, Multilayer Perceptron, and Stacking Classifier were used to model 3D probabilistic distributions of hydrofacies (sand and clay) at a grid size of 200 m × 200 m × 3 m. Comparison of the predicted 3D hydrofacies models shows that the probability distributions and the contrasts between hydrofacies vary. The classification metrics show that the Stacking Classifier model performed better than other machine learning models in predicting hydrofacies. Multi‐Layer Perceptron and Stacking Classifier models show sharp vertical transitions between the low and high sand probability while other machine learning models show gradual transitions. K‐means clustering was used to translate the Stacking Classifier model into a 4‐class hydraulic conductivity model. This study shows that machine learning methods advance our understanding of glacial hydrogeology by improving the vertical and horizontal resolution of hydrofacies distribution and resolving aquifer‐aquifer and stream‐aquifer connections.

Multiple-point statistical modeling of three-dimensional glacial aquifer heterogeneity for improved groundwater management

Quaternary glacial aquifers are important water sources for irrigation in many agricultural regions, including eastern Nebraska, USA. Quaternary glacial aquifers are heterogeneous, with juxtaposed low-permeability and high-permeability hydrofacies. Managing groundwater in such aquifers requires a realistic groundwater-flow model parameterization, and characterization of the aquifer geometry, spatial distribution of aquifer properties, and local aquifer interconnectedness. Despite its importance in considering uncertainty during decision-making, hydrofacies probabilities generated from multiple-point statistics (MPS) are not widely applied for groundwater model parameterization and groundwater management zone delineation. This study used a combination of soft data, a cognitive training image, and hard data to generate 100 three-dimensional (3D) conditional aquifer heterogeneity realizations. The most probable model (probability of hydrofacies) was then computed at node spacing of 200 × 200 × 3 m and validated using groundwater-level hydrographs. The resulting hydrofacies probability grids revealed variations in aquifer geometry, locally disconnected aquifer systems, recharge pathways, and hydrologic barriers. The profiles from hydrofacies probability at various locations show spatial variability of the streambed and aquifer connectivity. Groundwater-level hydrographs show evidence of these aquifer characteristics, verifying the general structure of the model. Using the MPS-generated 3D hydrofacies probability and hydrologic data, a novel workflow was developed in order to better define high-resolution groundwater management zones and strategies. In general, the conditional probability of hydrofacies helps improve the understanding of glacial aquifer heterogeneity, the characterization of aquifer-to-aquifer and streambed-aquifer connections, and the delineation of groundwater management zones. This MPS workflow can be adapted to other areas for modeling 3D aquifer heterogeneity using multisource data.

Evaluation of models for estimating hydraulic conductivity in glacial aquifers with NMR logging.

Nuclear magnetic resonance (NMR) logging is a promising method for estimating hydraulic conductivity (K). During the past ~60 years, NMR logging has been used for petroleum applications, and different models have been developed for deriving estimates of permeability. These models involve calibration parameters whose values were determined through decades of research on sandstones and carbonates. We assessed the use of five models to derive estimates of K in glacial aquifers from NMR logging data acquired in two wells at each of two field sites in central Wisconsin, USA. Measurements of K, obtained with a direct push permeameter (DPP), KDPP , were used to obtain the calibration parameters in the Schlumberger-Doll Research, Seevers, Timur-Coates, Kozeny-Godefroy, and sum-of-echoes (SOE) models so as to predict K from the NMR data; and were also used to assess the ability of the models to predict KDPP . We obtained four well-scale calibration parameter values for each model by using the NMR and DPP measurements in each well; and one study-scale parameter value for each model by using all data. The SOE model achieved agreement with KDPP that matched or exceeded that of the other models. The Timur-Coates estimates of K were found to be substantially different from KDPP . Although the well-scale parameter values for the Schlumberger-Doll, Seevers, and SOE models were found to vary by less than a factor of 2, more research is needed to confirm their general applicability so that site-specific calibration is not required to obtain accurate estimates of K from NMR logging data. This article is protected by copyright. All rights reserved.

Impact of climate change on groundwater recharge in shallow young glacial aquifers in northern Poland

We investigated the influence of climate change in the period 1951–2020 on shallow aquifers in the Brda and Wda outwash plains (Pomeranian Region, Northern Poland). There was a significant temperature rise (0.3 °C/10 years), which accelerated after 1980 (0.66 °C/10 years). Precipitation became increasingly irregular – extremely rainy years occurred right after or before extremely dry years, and intensive rainfall events became more frequent after 2000. The groundwater level decreased over the last 20 years, even though the average annual precipitation was higher than in the previous 50 years. We carried out numerical simulations of water flow in representative soil profiles for the years 1970–2020 using the HYDRUS-1D model, developed and calibrated during our earlier work at an experimental site in the Brda outwash plain (Gumuła-Kawęcka et al., 2022). We used a relationship between the water head and flux at the bottom of the soil profiles (the third-type boundary condition) to reproduce groundwater table fluctuations caused by recharge variability in time. The calculated daily recharge showed a decreasing linear trend for the last 20 years (0.05–0.06 mm d−1/10 years), and dropping trends in water table level and soil water content in the entire profile of vadose zone. Field tracer experiments were performed to estimate impact of extremely rain events on water flux in vadose zone. The results suggest that tracer travel times are strongly determined by water content in the unsaturated zone which is determined by precipitation amount in span of weeks, rather than extremely high precipitation events.

Evaluation of 1,4-dioxane attenuation processes at the Gelman Site, Michigan, USA

1,4-Dioxane released at the Gelman Site in Washtenaw County, Michigan, produced a series of contaminant plumes migrating up to 3 km through a heterogenous glacial aquifer system. An analysis of 1,4-dioxane concentrations in the Eastern Area of the Gelman Site between 2011 and 2017 documented a mass balance deficit of 2200 kg in excess of 2100 kg of 1,4-dioxane removed via remediation. Five mechanisms were evaluated to account for the mass deficiency: sorption, matrix diffusion, biodegradation, surface discharge, and bypass of the existing monitoring well network.The mass of 1,4-dioxane sorbed to aquifer and aquitard materials and the mass of 1,4-dioxane diffused into low permeability zones were estimated. However, decreasing aqueous concentrations across most of the contaminated area between 2011 and 2017 are expected to induce desorption and back diffusion during this period. Surface water discharge to a storm drain in the downgradient portion of the site was analyzed using concentration measurements and stream gage data. Results suggest that 1,4-dioxane mass entering the drain during the period between 2011 and 2017 was insufficient to account for the mass deficiency.Although available geochemical measurements indicate predominantly anaerobic aquifer conditions at the Gelman Site, biodegradation of 1,4-dioxane was estimated using first order decay rate constants from other sites where conditions may be more favorable. Results suggest that biodegradation could explain some but not all of the missing mass.Bypass of the downgradient monitoring well network is the most parsimonious explanation for the 1,4-dioxane mass deficit. This conclusion is supported by documented flow path complexity through the aquifer system and the sparse density of monitoring wells in the downgradient Eastern Area. These findings underscore the importance of characterizing aquifer heterogeneity when modeling and remediating persistent groundwater contaminants such as 1,4-dioxane.

Impact of Climate Change on Groundwater Recharge in Shallow Young Glacial Aquifers in Northern Poland

Impact of Climate Change on Groundwater Recharge in Shallow Young Glacial Aquifers in Northern Poland

Populations using public-supply groundwater in the conterminous U.S. 2010; Identifying the wells, hydrogeologic regions, and hydrogeologic mapping units

Most Americans receive their drinking water from publicly supplied sources, a large portion of it from groundwater. Mapping these populations consistently and at a high resolution is important for understanding where the resource is used and needs to be protected. The results show that 269 million people are supplied by public supply, 107 million are supplied by groundwater and 162 million are supplied by surface water. The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across populated census blocks, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations. In addition, a two-dimensional polygon dataset was created for the conterminous U.S. that identifies 177 unique Hydrogeologic Mapping Units (HMUs) with similar hydrogeologic characteristics. The HMUs do not overlap, but they can delineate areas where stacked hydrogeologic regions (HRs) contribute drinking water from below the surface. HRs are waterbearing geologic regions identified as either a principal aquifers (PA) or secondary hydrogeologic regions (SHR). Within each HMU, the wells were used to determine the proportion of each HR that is providing groundwater to the HMU. In 63% of the HMUs, a single HR is providing water to the public supply wells located within it, while the rest of the HMUs show that the wells are tapping up to a maximum of four stacked HRs. In total, groundwater from 108 HRs provide drinking water for public supply, six of which provide more than 50% of the groundwater used for public supply drinking water. The aquifer serving the largest number of equivalent people (>17 million) is the glacial aquifer. The HR providing the greatest number of people per km2 is the Biscayne aquifer in Florida at nearly 453 people per km2.

Impacts of Event-Based Recharge on the Vulnerability of Public Supply Wells

Dynamic recharge events related to extreme rainfall or snowmelt are becoming more common due to climate change. The vulnerability of public supply wells to water quality degradation may temporarily increase during these types of events. The Walkerton, ON, Canada, tragedy (2000) highlighted the threat to human health associated with the rapid transport of microbial pathogens to public supply wells during dynamic recharge events. Field research at the Thornton (Woodstock, ON, Canada) and Mannheim West (Kitchener, ON, Canada) well fields, situated in glacial overburden aquifers, identified a potential increase in vulnerability due to event-based recharge phenomena. Ephemeral surface water flow and local ponding containing microbial pathogen indicator species were observed and monitored within the capture zones of public supply wells following heavy rain and/or snowmelt. Elevated recharge rates beneath these temporary surface water features were estimated to range between 40 and 710 mm over two-week periods using analytical and numerical modelling based on the water level, soil moisture, and temperature data. Modelling also suggested that such events could reduce contaminant travel times to a supply well, increasing vulnerability to water quality degradation. These studies suggest that event-based recharge processes occurring close to public supply wells may enhance the vulnerability of the wells to surface-sourced contaminants.

Machine-Learning Predictions of High Arsenic and High Manganese at Drinking Water Depths of the Glacial Aquifer System, Northern Continental United States

Globally, over 200 million people are chronically exposed to arsenic (As) and/or manganese (Mn) from drinking water. We used machine-learning (ML) boosted regression tree (BRT) models to predict high As (>10 μg/L) and Mn (>300 μg/L) in groundwater from the glacial aquifer system (GLAC), which spans 25 states in the northern United States and provides drinking water to 30 million people. Our BRT models' predictor variables (PVs) included recently developed three-dimensional estimates of a suite of groundwater age metrics, redox condition, and pH. We also demonstrated a successful approach to significantly improve ML prediction sensitivity for imbalanced data sets (small percentage of high values). We present predictions of the probability of high As and high Mn concentrations in groundwater, and uncertainty, at two nonuniform depth surfaces that represent moving median depths of GLAC domestic and public supply wells within the three-dimensional model domain. Predicted high likelihood of anoxic condition (high iron or low dissolved oxygen), predicted pH, relative well depth, several modeled groundwater age metrics, and hydrologic position were all PVs retained in both models; however, PV importance and influence differed between the models. High-As and high-Mn groundwater was predicted with high likelihood over large portions of the central part of the GLAC.

Machine Learning Predicted Redox Conditions in the Glacial Aquifer System, Northern Continental United States

AbstractGroundwater supplies 50% of drinking water worldwide and 30% in the United States. Geogenic and anthropogenic contaminants can, however, compromise water quality, thus limiting groundwater availability. Reduction/oxidation (redox) processes and redox conditions affect groundwater quality by influencing the mobility and transport of common geogenic and anthropogenic contaminants. In the glacial aquifer system, northern United States (GLAC, 1.87 million km2), groundwater with high arsenic or manganese concentration is associated with reducing conditions and high nitrate with oxidizing conditions. This study uses machine learning to identify the relative influence of drivers of redox conditions (e.g., residence time vs. reactivity) across the glacial landscape. We developed three‐dimensional boosted regression tree models to predict redox conditions using the likelihood of low dissolved oxygen or high iron as indicators of anoxic conditions. Results indicate that variation in redox condition is controlled primarily by residence time (e.g., groundwater age and relative depth) and to a lesser extent by geochemical reactivity (e.g., subsurface contact time, soil carbon). Older water and deeper wells, along with more water storage or slower water movement was associated with higher probability of anoxic conditions. Mapped model results illustrate regions where anoxic redox conditions may mobilize geogenic contaminants or oxic conditions may limit denitrification potential. Results may also provide simplified redox input for process or predictive models of, for example, arsenic, manganese, or nitrate. Machine learning modeling methods can lead to improved understanding of contaminant occurrence and what drives redox conditions, and the methods may be transferable to other settings.

Surface water‐groundwater exchange dynamics in buried‐valley aquifer systems

AbstractGroundwater is a primary source of drinking water worldwide, but excess nutrients and emerging contaminants could compromise groundwater quality and limit its usage as a drinking water source. As such contaminants become increasingly prevalent in the biosphere, a fundamental understanding of their fate and transport in groundwater systems is necessary to implement successful remediation strategies. The dynamics of surface water‐groundwater (hyporheic) exchange within a glacial, buried‐valley aquifer system are examined in the context of their implications for the transport of nutrients and contaminants in riparian sediments. High conductivity facies act as preferential flow pathways which enhance nutrient and contaminant delivery, especially during storm events, but transport throughout the aquifer also depends on subsurface sedimentary architecture (e.g. interbedded high and low conductivity facies). Temperature and specific conductance measurements indicate extensive hyporheic mixing close to the river channel, but surface water influence was also observed far from the stream‐aquifer interface. Measurements of river stage and hydraulic head indicate that significant flows during storms (i.e., hot moments) alter groundwater flow patterns, even between consecutive storm events, as riverbed conductivity and, more importantly, the hydraulic connectivity between the river and aquifer change. Given the similar mass transport characteristics among buried‐valley aquifers, these findings are likely representative of glacial aquifer systems worldwide. Our results suggest that water resources management decisions based on average (base) flow conditions may inaccurately represent the system being evaluated, and could reduce the effectiveness of remediation strategies for nutrients and emerging contaminants.

Machine Learning Predictions of pH in the Glacial Aquifer System, Northern USA.

A boosted regression tree model was developed to predict pH conditions in three dimensions throughout the glacial aquifer system of the contiguous United States using pH measurements in samples from 18,386 wells and predictor variables that represent aspects of the hydrogeologic setting. Model results indicate that the carbonate content of soils and aquifer materials strongly controls pH and, when coupled with long flowpaths, results in the most alkaline conditions. Conversely, in areas where glacial sediments are thin and carbonate‐poor, pH conditions remain acidic. At depths typical of drinking‐water supplies, predicted pH >7.5—which is associated with arsenic mobilization—occurs more frequently than predicted pH <6—which is associated with water corrosivity and the mobilization of other trace elements. A novel aspect of this model was the inclusion of numerically based estimates of groundwater flow characteristics (age and flowpath length) as predictor variables. The sensitivity of pH predictions to these variables was consistent with hydrologic understanding of groundwater flow systems and the geochemical evolution of groundwater quality. The model was not developed to provide precise estimates of pH at any given location. Rather, it can be used to more generally identify areas where contaminants may be mobilized into groundwater and where corrosivity issues may be of concern to prioritize areas for future groundwater monitoring.

Assessment of NMR Logging for Estimating Hydraulic Conductivity in Glacial Aquifers.

Glacial aquifers are an important source of groundwater in the United States and require accurate characterization to make informed management decisions. One parameter that is crucial for understanding the movement of groundwater is hydraulic conductivity, K. Nuclear magnetic resonance (NMR) logging measures the NMR response associated with the water in geological materials. By utilizing an external magnetic field to manipulate the nuclear spins associated with 1 H, the time-varying decay of the nuclear magnetization is measured. This logging method could provide an effective way to estimate K at submeter vertical resolution, but the models that relate NMR measurements to K require calibration. At two field sites in a glacial aquifer in central Wisconsin, we collected a total of four NMR logs and obtained measurements of K in their immediate vicinity with a direct-push permeameter (DPP). Using a bootstrap algorithm to calibrate the Schlumberger-Doll Research (SDR) NMR-K model, we estimated K to within a factor of 5 of the DPP measurements. The lowest levels of accuracy occurred in the lower-K (K <10-4 m/s) intervals. We also evaluated the applicability of prior SDR model calibrations. We found the NMR calibration parameters varied with K, suggesting the SDR model does not incorporate all the properties of the pore space that control K. Thus, the expected range of K in an aquifer may need to be considered during calibration of NMR-K models. This study is the first step toward establishing NMR logging as an effective method for estimating K in glacial aquifers.

Sulfur Hexafluoride and Potassium Bromide as Groundwater Tracers for Managed Aquifer Recharge.

Sulfur hexafluoride (SF6 ) is an established tracer for use in managed aquifer recharge projects. SF6 exsolves from groundwater when it encounters trapped air according to Henry's law. This results in its retardation relative to groundwater flow, which can help determine porous media saturation and flow dynamics. SF6 and the conservative, nonpartitioning tracer, bromide (Br- added as KBr), were introduced to recharge water infiltrated into stacked glacial aquifers in Thurston County, Washington, providing the opportunity to observe SF6 partitioning. Br- , which is assumed to travel at the same velocity as the groundwater, precedes SF6 at most monitoring wells (MWs). Average groundwater velocity in the unconfined aquifer in the study area ranges from 3.9 to 40 m/d, except in the southwestern corner where it is slower. SF6 in the shallow aquifer exhibits an average retardation factor of 2.5 ± 3.8, suggesting an air-to-water ratio on the order of 10-3 to 10-2 in the pore space. Notable differences in tracer arrival times at adjacent wells indicate very heterogeneous conductivity. One MW exhibits double peaks in concentrations of both tracers with different degrees of retardation for the first and second peaks. This suggests multiple flowpaths to the well with variable saturation. The confining layer between the upper two aquifers appears to allow intermittent connection between aquifers but serves as an aquitard in most areas. This study demonstrates the utility of SF6 partitioning for evaluating hydrologic conditions at prospective recharge sites.

Evaluation of soil zone processes and a novel radiocarbon correction approach for groundwater with mixed sources

Estimates of groundwater age based on 14C are often limited by the uncertainty in geochemical processes that alter the 14C concentration measured in water and the composition (δ13C and 14C) of carbon sources needed to appropriately parametrize 14C adjustment models. Estimated ages for samples that contain a mixture of young and old groundwater will be particularly sensitive to model parametrization as relatively small additions of modern 14C from recent recharge can mask the presence and amount of old groundwater. A novel multi-model approach based on inverse geochemical modeling and lumped parameter modeling of age tracers (3H, 3Hetrit, and SF6) was used to better constrain 14C dilution caused by dissolution of carbonates in the unsaturated zone or shallow parts of the Glacial aquifer, which extends over 2000 miles across the northern contiguous United States. Calibration of 14C inverse geochemical models to LPM computed 14C concentrations in modern water indicated that 14C of soil zone and shallow aquifer carbonates were not 14C-dead (0 pmC), as is typically assumed for 14C correction models. 14C of such carbonates was on average about 53 pmC (ranged 0–110 pmC, n = 72). This information was used to correct 14C concentrations for water recharged entirely before 1950 and water that is a mixture of pre- and post-1950 water. The multi-model approach developed here was compared to an analytical 14C-adjustment model (Revised Fontes and Garnier) that assumed solid carbonates were 14C-dead. 14C corrections using the analytical adjustment model tended to over-correct final 14C concentrations by 21 pmC and underestimates mean ages by 40% for groundwater mixtures. In fact, 14C corrections based on analytical model yielded negative ages (14C > 120 pmC) in nearly 36% of mixed samples. This work presents a new approach to constraining 14C corrections and age estimates of mixtures of young and old groundwater. The new method is applied to three well networks distributed across the spatially expansive Glacial aquifer.

Environmental tracer evidence for connection between shallow and bedrock aquifers and high intrinsic susceptibility to contamination of the conterminous U.S. glacial aquifer

Covering a large portion of the northern conterminous United States (1.87 × 106 km2), the glacial aquifer serves as the primary water supply for 30 million public and domestic water users. Mean groundwater age, groundwater age distribution, and susceptibility to land surface contamination, using a new metric (Susceptibility Index; SI) based on the full age distribution and less prone to bias than estimated mean age, is reported for 168 public and domestic wells across the aquifer. Comparison of groundwater age metrics between well networks of varying spatial scale suggest an extensive sample network of equally spaced, long screened interval wells can be used to characterize aquifer wide groundwater age. Estimated mean age ranges from 1 to 50,000 years and, according to the composite age distribution, approximately 63 percent of all sampled water recharged after 1950 (i.e., modern) and 18 percent of the sampled water was recharged greater than 10,000 years ago. The later finding strongly suggests a connection between the glacial aquifer and underlying bedrock aquifers. Statistical analysis of glacial aquifer hydrogeology and age metrics show groundwater ages are young (less than few 100 years) and more susceptible to land surface contamination (larger SI) in unconfined and shallow portions of the aquifer. Old groundwater (greater than 1,000 years) is more often associated with thicker sequences of fine grain sediments and/or shallow bedrock. Calculated SI is shown to be more strongly related to the number of land surface contaminants detected than mean age or fraction modern. Statistical analysis of SI and hydrogeology indicates SI is largely dictated by well depth and confinement. This study demonstrates how sample network design can be used to characterize groundwater age of large aquifers with a limited number of samples and how interpretation of environmental tracers can be used to improve conceptual models of groundwater aquifers and identify groundwater susceptible to contamination.

Time scales of arsenic variability and the role of high-frequency monitoring at three water-supply wells in New Hampshire, USA

Groundwater geochemistry, redox process classification, high-frequency physicochemical and hydrologic measurements, and climate data were analyzed to identify controls on arsenic (As) concentration changes. Groundwater was monitored in two public-supply wells (one glacial aquifer and one bedrock aquifer), and one bedrock-aquifer domestic well in New Hampshire, USA, from 2014 to 2018 to identify time scales of and controls on As concentration changes. Concentrations of As and other geochemical constituents were measured bimonthly. Specific conductance (SC), pH, dissolved oxygen, and pumping rate/water level were measured at high frequency (every 5 to 15 min). Median (and 95% confidence interval) As concentrations at the three wells were 4.1 (3.7–4.6), 18.9 (17.2–23.6), and 37.5 (30.4–42.9) μg/L. Arsenic variability in each of the three wells, in relative standard deviation, ranged from 9 to 12%. Median quarterly As concentrations were highest in all wells in the spring. The bedrock-aquifer public-supply well As concentration increased over the period of study while pumping rate decreased. In the public-supply wells, As variability was correlated with SC and pH, and As species were related to SC, pH, pumping, precipitation, and changes in redox process. Specific conductance also had a seasonal pattern in the two public-supply wells and was correlated with Na and Cl. Excess Na in water samples suggests possible ion exchange with dissolved Ca, creating more capacity to dissolve CaCO3 from calcareous rocks, which can increase pH and in turn, As concentrations in wells. High-frequency monitoring data are cost effective to collect, which could be advantageous in other parts of the United States and in the many parts of the world where glacial aquifers are in direct contact with other water supply aquifers or where water from different aquifers have potential to mix.

Geogenic groundwater solutes: the myth

What is the source of geogenic (natural or native) solutes in groundwater? The orthodox explanation suggests it is largely a function of water–rock interaction (weathering of the soil zone and aquifer mineral framework). It is proposed herein that atmospheric deposition (combination of wet and dry aerosols from ocean spray, smoke, volcanoes, continental dust, and lightning) is a significant source, and in many cases the dominant source, of the major and minor geogenic solutes in groundwater. Solute mass-balance analyses suggest that much of the mass of major and minor ions must be transported into the aquifer from an external source. Example case studies are presented: analysis of groundwater in a coastal marine aquifer located in an arid area (United Arab Emirates) suggests that over 50% of several major ions potentially originate from atmospheric deposition; in an alluvial fan in a semi-arid system (High Plains, USA), 100% of most solutes potentially originate from atmospheric deposition; and in a humid glacial aquifer system (Michigan, USA), 20–30% of many major ions are potentially from atmospheric deposition. These observations contrast with many hydrogeologic textbooks, which still propose the origin to be water–rock interaction—hence, the myth.

Evidence for natural attenuation of 1,4-dioxane in a glacial aquifer system

Although 1,4-dioxane is generally thought to be recalcitrant, recent studies suggest it may degrade in the subsurface under ideal conditions. A fuller understanding of natural attenuation processes affecting 1,4-dioxane is therefore needed to assess its potential for in situ bioremediation. This investigation employed multiple lines of evidence to evaluate attenuation of 1,4-dioxane at the Gelman Site beneath the city of Ann Arbor, Michigan, USA. Data from a network of groundwater monitoring wells were used to determine attenuation metrics at individual wells and at the scale of a prominent 1,4-dioxane plume. A series of plume maps and historical remediation data were used to calculate changes in aqueous phase mass storage, mass influx rates, and mass removal rates over a 12-year period (2005–2017). Individual point and plume-scale metrics indicate that attenuation may be occurring at rates too small to meaningfully contribute to remediation results at the site. Conversely, plume-scale mass balance calculations reveal a 1,4-dioxane storage surplus for the first 6 years, followed by a storage deficit during the remaining 6 years that cannot be explained by mass influx or removal estimates, respectively. Mass balance deficits observed in this aquifer system are attributable to biodegradation and/or unrecognized discharge to surface water and storm drain systems at rates similar to remedial pump-and-treat mass removal during 2011–2017.

Drinking water quality in the glacial aquifer system, northern USA

Groundwater supplies 50% of drinking water worldwide, but compromised water quality from anthropogenic and geogenic contaminants can limit usage of groundwater as a drinking water source. Groundwater quality in the glacial aquifer system, USA (GLAC), is presented in the context of a hydrogeologic framework that divides the study area into 17 hydrogeologic terranes. Results are reported at aquifer-system scale and regional (terrane) scale. This paper presents a quantitative assessment of groundwater quality in the GLAC using data from numerous sources for samples collected 2005–2013, compared to health-based and aesthetic (non-health) benchmarks, and evaluated with areal and population metrics. Concentrations above a benchmark are considered high. Trace elements are widespread across the study area, with an estimated 5.7 million people relying on groundwater with high concentrations of one or more trace elements; manganese and arsenic are most often at high concentration. Nitrate is found at high concentration in 4.0% of the study area, serving about 740 thousand people. Organic compounds including pesticides and volatile organic compounds are high in 2.0% of the assessed study area, with about 870 thousand people relying on groundwater with high concentrations of an organic compound. High arsenic and manganese concentrations occur primarily in the terranes with thick, stratigraphically complex, fine-grained glacial sediment, coincident with groundwater under reducing conditions (indicated by iron concentrations >100 μg/L); high nitrate is uncommon in those same terranes. When nitrate is high in thick, fine-grained, complex terranes, though, it is much more commonly associated with groundwater under more oxidizing conditions. Common geogenic trace elements occur at high concentration due to characteristic geologic and geochemical conditions. Conversely, anthropogenic nitrate and organic compounds are introduced at or near the land surface. High concentrations of nitrate or organic compounds are generally limited to areas in proximity where people live and use the chemicals.