Hydrological models are usually calibrated to in-situ streamflow observations with reasonably long and uninterrupted records. This is challenging for poorly gage or ungaged basins where such information is not available. Even for gaged basins, the single-objective calibration to gaged streamflow cannot guarantee reliable forecasts because, as has been documented elsewhere, the inverse problem is mathematically ill-posed. Therefore, the inclusion of other observations, and the reproduction of other hydrological variables beyond streamflow, become critical components of accurate hydrological forecasting. In this study, six single- and multi-objective model calibration schemes based on different combinations of gaged streamflow, global-scale gridded soil moisture, actual evapotranspiration (ET), and runoff products are used for the calibration of a process-based hydrological model for 20 catchments located within the Lake Michigan watershed, of the Laurentian Great Lakes. Results show that the addition of gridded soil moisture to gaged streamflow in model calibration improves the ET simulation performance for most of the catchments, leading to the overall best-performing models. The monthly streamflow simulation performance for the experiments using gridded runoff products to inform the model is outperformed by those using the gaged streamflow, but the discrepancy is mitigated with increasing catchment scale. A new visualization method that effectively synthesizes model performance for the simulations of streamflow, soil moisture, and ET was also proposed. Based on the method, it is revealed that the streamflow simulation performance is relatively weak for baseflow-dominated catchments; overall, the 20 catchment models simulate streamflow and ET better than soil moisture.

First posted July 27, 2021 For additional information, contact: Water Resources Mission AreaU.S. Geological Survey12201 Sunrise Valley DriveReston, VA 20192Contact Pubs Warehouse The United States faces growing challenges to its water supply, infrastructure, and aquatic ecosystems because of population growth, climate change, floods, and droughts. To help address these challenges, the U.S. Geological Survey Water Resources Mission Area is integrating recent advances in monitoring, research, and modeling to improve assessments of water availability throughout the United States. A key part of this effort is the intensive study of 10 Integrated Water Science (IWS) basins across the Nation between 2019 and 2028.The goal is to study 10 IWS basins that are representative of large geographic regions across the United States and that encompass a variety of potential threats to the amount and quality of water across the Nation. Lessons learned from these smaller IWS basins (10,000–20,000 square miles in size) about the interactions among climate, human effects, surface water, groundwater, water quality, and water supply and demand will be used to help quantify and forecast water availability in the larger regions and ultimately the Nation.

The United States faces growing challenges to its water supply, infrastructure, and aquatic ecosystems because of population growth, climate change, floods and droughts, and aging water delivery systems.To help address these challenges, the U.S. Geological Survey (USGS) Water Resources Mission Area (WMA) has established the Integrated Water Availability Assessments (IWAAs) to capitalize on the operational and scientific strengths of the USGS and engage in these complex societal issues.Substantial advances in water science,

First posted August 21, 2019 For additional information, contact: U.S. Geological SurveyWater Resources Mission AreaGroundwater and Streamflow Information Program3916 Sunset Ridge RoadRaleigh, North Carolina 26707 The challenges of providing safe and sustainable water supplies for human and ecological uses and protecting lives and property during water emergencies are well recognized. The U.S. Geological Survey (USGS) plays an essential role in meeting these challenges through its observational networks and renowned water science and research activities (National Academies of Science, Engineering, and Medicine, 2018). Substantial advances in water science, together with emerging breakthroughs in technical and computational capabilities, have led the USGS to develop a Next Generation Water Observing System (NGWOS). The NGWOS will provide real-time data on water quantity and quality in more affordable and rapid ways than previously possible, and in more locations. The data will be served through a modernized USGS National Water Information System that will be coupled to advanced modeling tools to inform daily water operations, decision-making during water emergencies (like floods, droughts, and contaminant spills), assessments of past trends in water quantity and quality, and forecasts of future water availability.

In the late 1800s, John Wesley Powell, second Director of the U.S. Geological Survey (USGS), proposed gaging the flow of rivers and streams in the Western United States to evaluate the potential for irrigation. Around the same time, several cities in the Eastern United States established primitive streamgages to help design water-supply systems. Streamgaging technology has greatly advanced since the 1800s, and USGS hydrographers have made at least one streamflow measurement at more than 37,000 sites throughout the years. Today, the USGS Groundwater and Streamflow Information Program supports the collection and (or) delivery of both streamflow and water-level information for more than 8,500 sites (continuous or partial record) and water-level information alone for more than 1,700 additional sites. The data are served online—most in near realtime—to meet many diverse needs; more than 640 million requests for streamflow information were fulfilled during the 2017 water year (October 1, 2016‒ September 30, 2017).

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50ppb and probability of dissolved oxygen concentration to be below 0.5ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971-2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.

First posted September 29, 2016 Revised December 18, 2017 For additional information, contact: Coordinator, National Water Quality Program U.S. Geological Survey12201 Sunrise Valley DriveReston, VA 20192https://www.usgs.gov Cyanobacterial harmful algal blooms (CyanoHABs) are increasingly a global concern because CyanoHABs pose a threat to human and aquatic ecosystem health and cause economic damages. Despite advances in scientific understanding of cyanobacteria and associated compounds, many unanswered questions remain about occurrence, environmental triggers for toxicity, and the ability to predict the timing, duration, and toxicity of CyanoHABs. U.S. Geological Survey (USGS) scientists are leading a diverse range of studies to address CyanoHAB issues in water bodies throughout the United States, using a combination of traditional methods and emerging technologies, and in collaboration with numerous partners. By providing practical applications of cutting edge CyanoHAB research, USGS studies have advanced scientific understanding, enabling the development of approaches to help protect ecological and human health.

In a recent study of public-supply-well water quality in the United States, nearly two-thirds of all samples from 932 public wells tapping 30 regionally extensive aquifers contained detectable amounts of drinking-water contaminants that originated entirely or primarily from manmade sources. Twenty-two percent of the samples contained at least one contaminant (manmade or naturally occurring) at concentrations greater than drinking-water standards or other human health benchmarks (Toccalino and Hopple 2010). These findings imply that water from nearly one in five public-supply wells in the United States may need to be treated or blended with more dilute water sources to decrease concentrations of drinking-water contaminants before delivery to the public. Removing contaminants from water intended for drinking is difficult and expensive. It also is becoming increasingly necessary (Job 2011). Consequently, understanding factors affecting public-supply-well vulnerability to contamination is important. Public-supply-well vulnerability to contamination is not the same as groundwater vulnerability, but the two cannot be decoupled. Groundwater vulnerability is the tendency or likelihood for contaminants to reach a specified position in the groundwater system (National Research Council 1993). Groundwater vulnerability depends on three factors: (1) the presence of manmade or natural contaminant sources, (2) the combination of chemical and physical processes in the subsurface that affect contaminant concentrations, and (3) the ease of water and contaminant movement to and through an aquifer, or its intrinsic susceptibility (Focazio et al. 2002). When mapping groundwater or “resource” vulnerability, the target is frequently the water table or top of the aquifer (Frind et al. 2006); however, trace elements and radionuclides derived from aquifer solids may account for the majority of drinking-water standard or other human health benchmark exceedances in raw water from public wells (Toccalino and Hopple 2010). Public-supply-well vulnerability depends on all of the above factors (contaminant input, contaminant mobility and persistence, and intrinsic susceptibility) but is further affected by the location, design, construction, operation, and maintenance of the well. This is because groundwater vulnerability, and thus water quality, is not uniform throughout an aquifer, and wells “sample” only part of an aquifer. In other words, well location determines whether a particular contaminant source is in the capture zone for the well. Screen placement determines which chemical and physical processes in the aquifer will have influenced the water before it is pumped from the well and, therefore, which contaminants might be present in the water as it enters the well, and at what concentrations. Well depth and pumping rate determine how quickly water and contaminants can travel from the water table to the well, and from what distance. The interaction of a well with the surrounding aquifer determines whether the well intercepts water moving along preferential flow pathways, which can affect the relative importance of each of the other factors contributing to its vulnerability. Finally, the pumping schedule determines when poor quality water can migrate between aquifer units by way of wellbore flow, thereby influencing the mix of contaminated and uncontaminated water that enters the well at different points in time (Eberts et al. 2013). To summarize, a well affects its own vulnerability by drawing in water from a unique combination of flow pathways that are associated with different combinations of water and contaminant sources, aquifer geochemical conditions, and travel times, giving rise to the flux-averaged contaminant concentrations that occur in the produced water. Thus, the vulnerability and water quality of every well is unique to itself. This is true even for wells within the same aquifer and wellfield (Eberts et al. 2013).

Aquifer vulnerability models were developed to map groundwater nitrate concentration at domestic and public-supply well depths in the Central Valley, California. We compared three modeling methods for ability to predict nitrate concentration >4 mg/L: logistic regression (LR), random forest classification (RFC), and random forest regression (RFR). All three models indicated processes of nitrogen fertilizer input at the land surface, transmission through coarse-textured, well-drained soils, and transport in the aquifer to the well screen. The total percent correct predictions were similar among the three models (69-82%), but RFR had greater sensitivity (84% for shallow wells and 51% for deep wells). The results suggest that RFR can better identify areas with high nitrate concentration but that LR and RFC may better describe bulk conditions in the aquifer. A unique aspect of the modeling approach was inclusion of outputs from previous, physically based hydrologic and textural models as predictor variables, which were important to the models. Vertical water fluxes in the aquifer and percent coarse material above the well screen were ranked moderately high-to-high in the RFR models, and the average vertical water flux during the irrigation season was highly significant (p < 0.0001) in logistic regression.

The age distribution of water from a public-supply well in a deep alluvial aquifer was estimated and used to help explain arsenic variability in the water. The age distribution was computed using a ternary mixing model that combines three lumped parameter models of advection-dispersion transport of environmental tracers, which represent relatively recent recharge (post-1950s) containing volatile organic compounds (VOCs), old intermediate depth groundwater (about 6500 years) that was free of drinking-water contaminants, and very old, deep groundwater (more than 21,000 years) containing arsenic above the USEPA maximum contaminant level of 10 µg/L. The ternary mixing model was calibrated to tritium, chloroflorocarbon-113, and carbon-14 (14C) concentrations that were measured in water samples collected on multiple occasions. Variability in atmospheric 14C over the past 50,000 years was accounted for in the interpretation of (14) C as a tracer. Calibrated ternary models indicate the fraction of deep, very old groundwater entering the well varies substantially throughout the year and was highest following long periods of nonoperation or infrequent operation, which occured during the winter season when water demand was low. The fraction of young water entering the well was about 11% during the summer when pumping peaked to meet water demand and about 3% to 6% during the winter months. This paper demonstrates how collection of multiple tracers can be used in combination with simplified models of fluid flow to estimate the age distribution and thus fraction of contaminated groundwater reaching a supply well under different pumping conditions.

Trends in concentrations of nonpoint-source contaminants in wells, springs, and streams are related to the history of contamination in groundwater recharge and the age distribution in the groundwater discharge. The age distribution in discharge depends on the groundwater age distribution in the aquifer and the subset of flowpaths that are sampled by the discharge. Groundwater travel times from recharge to discharge are variable; consequently, responses at discharge locations to changing contaminant loading in recharge can include delayed initial responses, dilution of peak concentrations, and prolonged flushing times. These effects are well understood in principle and have important consequences for water resource management (Eberts et al. 2013), but their implications may not be easy to visualize or communicate. Here we introduce GAMACTT: Groundwater Age Mixtures and Contaminant Trends Tool (Version 1)—an interactive webtool that can be used to explore the effects of basic aquifer properties (saturated thickness, porosity, and recharge rate) and well configurations (tops and bottoms of screened intervals) on groundwater age mixtures in groundwater discharge and on contaminant trends from varying nonpoint-source contaminant input scenarios. The webtool is based on the concept of groundwater stratigraphy whereby changes in contaminant concentrations in recharge may be recorded as a vertical concentration gradient in the aquifer that is related to groundwater age (Cook and Böhlke 2000). The webtool provides a groundwater stratigraphy model that derives age distributions for wells from well construction data by using a partial exponential model (PEM) (Jurgens et al. 2012). By varying the webtool input data (basic aquifer properties, well configuration, contaminant input scenario, and contaminant decay), users can explore concepts such as delays (lag times), dilution factors, and flushing times in hypothetical wells responding to changing contamination of surficial aquifers. In some configurations, results may be applicable to contaminant trends in discharge to surface water bodies like springs and streams. The webtool also illustrates spatial relations between wells and their contributing recharge areas, which are important considerations for point-source and nonpoint-source contaminants. Important limitations of this webtool include: (1) groundwater model does not include transport through the unsaturated zone; (2) basic aquifer properties do not account for aquifer heterogeneity, flow discontinuities, or dispersion; (3) steady-state model by definition does not provide for transient flow conditions; (4) PEM assumes that the groundwater flow system is not perturbed by pumping or wellbore flow; (5) first-order contaminant degradation model may not be appropriate for some biogeochemical reactions. The webtool is not intended to be used as a prediction tool for real-world applications. Rather, it is presented as an illustrative (educational) tool that enables scientists, hydrogeology professionals, educators, and other interested persons to explore, understand, visualize, and explain various processes affecting how public-supply wells respond to groundwater contamination. The webtool is freely available and can be accessed at http://cida.usgs.gov/gamactt/. The authors are grateful for useful comments from USGS colleague Bruce Lindsey and three anonymous reviewers. Support for this project was provided by the USGS National Water Quality Assessment Program, the USGS Center for Integrated Data Analytics, and the USGS National Research Program. Although this software program has been used by the U.S. Geological Survey (USGS), no warranty, expressed or implied, is made by the USGS or the U.S. Government as to the accuracy and functioning of the program and related program material nor shall the fact of distribution constitute any such warranty, and no responsibility is assumed by the USGS in connection therewith. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

As part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program, a study was conducted from 2001 to 2011 to shed light on factors that affect the vulnerability of water from public-supply wells to contamination (referred to hereafter as “public-supply-well vulnerability”). The study was designed as a follow-up to earlier NAWQA studies that found mixtures of contaminants at low concentrations in groundwater near the water table in urban areas across the Nation and, less frequently, in deeper groundwater typically used for public supply. Beside the factors affecting public-supply-well vulnerability to contamination, this circular describes measures that can be used to determine which factor (or factors) plays a dominant role at an individual public-supply well. Case-study examples are used throughout to show how such information can be used to improve water quality. In general, the vulnerability of the water from public-supply wells to contamination is a function of contaminant input within the area that contributes water to a well, the mobility and persistence of a contaminant once released to the groundwater, and the ease of groundwater and contaminant movement from the point of recharge to the open interval of a well. The following measures described in this circular are particularly useful for indicating which contaminants in an aquifer might reach an individual public-supply well and when, how, and at what concentration they might arrive: * Sources of recharge—Information on the sources of recharge for a well provides insight into contaminants that might enter the aquifer with the recharge water and potentially reach the well. * Geochemical conditions—Information on the geochemical conditions encountered by groundwater traveling to a well provides insight into contaminants that might persist in the water all the way to the well. * Groundwater-age mixtures—Information on the ages of the different waters that mix in a well provides insight into the time lag between contaminant input at the water table and contaminant arrival at the well. It also provides insight into the potential for in-well dilution of contaminated water by unaffected groundwater of a different age that simultaneously enters the well. Preferential flow pathways—pathways that provide little resistance to flow—can influence how all other factors affect public-supply-well vulnerability to contamination. For example, preferential flow pathways can influence whether a contaminant source is physically linked to a well, whether contaminant concentrations are substantially altered before contaminated groundwater reaches a well, and whether contaminated groundwater can arrive at a well within a timeframe of concern to the well owner. Methods for recognizing the influence of preferential flow pathways on the quality of water from a public-supply well are presented in this circular and can provide opportunities to prevent or mitigate the deterioration of a water supply. Knowing what water-quality variables to measure, what spatial and temporal scales on which to measure them, and how to interpret the resulting data makes it possible for samples from public-supply wells to provide a broad window into a well’s past and present water quality—and possibly future water quality. Such insight can enable resource managers to prioritize actions for sustaining a high-quality groundwater source of drinking water.

TracerLPM is an interactive Excel® (2007 or later) workbook program for evaluating groundwater age distributions from environmental tracer data by using lumped parameter models (LPMs). Lumped parameter models are mathematical models of transport based on simplified aquifer geometry and flow configurations that account for effects of hydrodynamic dispersion or mixing within the aquifer, well bore, or discharge area. Five primary LPMs are included in the workbook: piston-flow model (PFM), exponential mixing model (EMM), exponential piston-flow model (EPM), partial exponential model (PEM), and dispersion model (DM). Binary mixing models (BMM) can be created by combining primary LPMs in various combinations. Travel time through the unsaturated zone can be included as an additional parameter. TracerLPM also allows users to enter age distributions determined from other methods, such as particle tracking results from numerical groundwater-flow models or from other LPMs not included in this program. Tracers of both young groundwater (anthropogenic atmospheric gases and isotopic substances indicating post-1940s recharge) and much older groundwater (carbon-14 and helium-4) can be interpreted simultaneously so that estimates of the groundwater age distribution for samples with a wide range of ages can be constrained. TracerLPM is organized to permit a comprehensive interpretive approach consisting of hydrogeologic conceptualization, visual examination of data and models, and best-fit parameter estimation. Groundwater age distributions can be evaluated by comparing measured and modeled tracer concentrations in two ways: (1) multiple tracers analyzed simultaneously can be evaluated against each other for concordance with modeled concentrations (tracer-tracer application) or (2) tracer time-series data can be evaluated for concordance with modeled trends (tracer-time application). Groundwater-age estimates can also be obtained for samples with a single tracer measurement at one point in time; however, prior knowledge of an appropriate LPM is required because the mean age is often non-unique. LPM output concentrations depend on model parameters and sample date. All of the LPMs have a parameter for mean age. The EPM, PEM, and DM have an additional parameter that characterizes the degree of age mixing in the sample. BMMs have a parameter for the fraction of the first component in the mixture. An LPM, together with its parameter values, provides a description of the age distribution or the fractional contribution of water for every age of recharge contained within a sample. For the PFM, the age distribution is a unit pulse at one distinct age. For the other LPMs, the age distribution can be much broader and span decades, centuries, millennia, or more. For a sample with a mixture of groundwater ages, the reported interpretation of tracer data includes the LPM name, the mean age, and the values of any other independent model parameters. TracerLPM also can be used for simulating the responses of wells, springs, streams, or other groundwater discharge receptors to nonpoint-source contaminants that are introduced in recharge, such as nitrate. This is done by combining an LPM or user-defined age distribution with information on contaminant loading at the water table. Information on historic contaminant loading can be used to help evaluate a model's ability to match real world conditions and understand observed contaminant trends, while information on future contaminant loading scenarios can be used to forecast potential contaminant trends.

Environmental age tracers have been used in various ways to help assess vulnerability of drinking-water production wells to contamination. The most appropriate approach will depend on the information that is available and that which is desired. To understand how the well will respond to changing nonpoint-source contaminant inputs at the water table, some representation of the distribution of groundwater ages in the well is needed. Such information for production wells is sparse and difficult to obtain, especially in areas lacking detailed field studies. In this study, age distributions derived from detailed groundwater-flow models with advective particle tracking were compared with those generated from lumped-parameter models to examine conditions in which estimates from simpler, less resource-intensive lumped-parameter models could be used in place of estimates from particle-tracking models. In each of four contrasting hydrogeologic settings in the USA, particle-tracking and lumped-parameter models yielded roughly similar age distributions and largely indistinguishable contaminant trends when based on similar conceptual models and calibrated to similar tracer data. Although model calibrations and predictions were variably affected by tracer limitations and conceptual ambiguities, results illustrated the importance of full age distributions, rather than apparent tracer ages or model mean ages, for trend analysis and forecasting.

This fact sheet highlights findings from the vulnerability study of a public-supply well in Albuquerque, New Mexico (hereafter referred to as “the study well”). The study well produces about 3,000 gallons of water per minute from the Rio Grande aquifer system. Water samples were collected at the study well, at two other nearby public-supply wells, and at monitoring wells installed in or near the simulated zone of contribution to the study well. Untreated water samples from the study well contained arsenic at concentrations exceeding the Maximum Contaminant Level (MCL) of 10 micrograms per liter (µg/L) established by the U.S. Environmental Protection Agency for drinking water. Volatile organic compounds (VOCs) and nitrate also were detected, although at concentrations at least an order of magnitude less than established drinking-water standards, where such standards exist. Overall, study findings point to four primary influences on the movement and (or) fate of contaminants and the vulnerability of the public-supply well in Albuquerque: (1) groundwater age (how long ago water entered, or recharged, the aquifer), (2) groundwater development (introduction of manmade recharge and discharge sources), (3) natural geochemical conditions of the aquifer, and (4) seasonal pumping stresses. Concentrations of the isotope carbon-14 indicate that groundwater from most sampled wells in the local study area is predominantly water that entered, or recharged, the aquifer more than 6,000 years ago. However, the additional presence of the age tracer tritium in several groundwater samples at concentrations above 0.3 tritium units indicates that young (post-1950) recharge is reaching the aquifer across broad areas beneath Albuquerque. This young recharge is mixing with the thousands-of-years-old water, is migrating to depths as great as 245 feet below the water table, and is traveling to some (but not all) of the public-supply wells sampled. Most groundwater samples containing a fraction of young water also contain manmade VOCs, including chloroform (a byproduct of drinking-water chlorination), which indicates that the source of young recharge is, at least in part, infiltration of chlorinated municipal-supply water from leaking waterlines and sewerlines or from turf watering. Other likely manmade, urban recharge sources are seepage from constructed ponds and unlined portions of a stormwater diversion channel. A regional-scale computer-model simulation of groundwater flow and transport to the public-supply well shows that manmade sources of recharge and discharge that were added after about 1930 have greatly altered directions of groundwater flow near Albuquerque and have caused water levels to decline by as much as 120 feet. Local-scale simulations show that seasonal changes in the pumping schedule of the study well affect the age and quality of water produced by the well. Increased pumping during the summer causes significant volumes of water to flow downward from the shallow to the intermediate zones of the aquifer, causing a higher fraction of young water to be produced by the well in the summer than in the winter months and a corresponding increase in VOC detections in the summer relative to the winter. During the winter when the study-well pump is idle for several hours each day, old, high-arsenic water from the deep zone of the aquifer travels up the wellbore and exits into the intermediate zone of the aquifer. When the pump is activated in the winter (for a relatively short time each day), some of the leaked, high-arsenic water is recaptured by the well. This results in a higher arsenic concentration (commonly more than 12 µg/L) in water produced in the winter than in the summer, and a smaller fraction of young water being produced by the well in the winter than in the summer (6 percent in the winter, compared to 11 percent in the summer). Knowledge of the vertical flow direction (both natural and pumping-enhanced) in the vicinity of a long-screened well, coupled with understanding of variations in contaminant concentrations with depth in the aquifer, can help water managers predict the positive or negative effect that wellbore flow will have on water quality and can lead to development of strategies to mitigate contamination (such as changes in pumping schedules or development of devices to inhibit wellbore flow when the pump is off).

The effects of human-induced alteration of groundwater flow patterns on concentrations of naturally-occurring trace elements were examined in five hydrologically distinct aquifer systems in the USA. Although naturally occurring, these trace elements can exceed concentrations that are considered harmful to human health. The results show that pumping-induced hydraulic gradient changes and artificial connection of aquifers by well screens can mix chemically distinct groundwater. Chemical reactions between these mixed groundwaters and solid aquifer materials can result in the mobilization of trace elements such as U, As and Ra, with subsequent transport to water-supply wells. For example, in the High Plains aquifer near York, Nebraska, mixing of shallow, oxygenated, lower-pH water from an unconfined aquifer with deeper, confined, anoxic, higher-pH water is facilitated by wells screened across both aquifers. The resulting higher-O-2, lower-pH mixed groundwater facilitated the mobilization of U from solid aquifer materials, and dissolved U concentrations were observed to increase significantly in nearby supply wells. Similar instances of trace element mobilization due to human-induced mixing of groundwaters were documented in: (1) the Floridan aquifer system near Tampa, Florida (As and U), (2) Paleozoic sedimentary aquifers in eastern Wisconsin (As), (3) the basin-fill aquifer underlying the California Central Valley near Modesto (U), and (4) Coastal Plain aquifers of New Jersey (Ra). Adverse water-quality impacts attributed to human activities are commonly assumed to be related solely to the release of the various anthropogenic contaminants to the environment. The results show that human activities including various land uses, well drilling, and pumping rates and volumes can adversely impact the quality of water in supply wells, when associated with naturally-occurring trace elements in aquifer materials. This occurs by causing subtle but significant changes in geochemistry and associated trace element mobilization as well as enhancing advective transport processes. Published by Elsevier Ltd.

Wells screened across multiple aquifers can provide pathways for the movement of surprisingly large volumes of groundwater to confined aquifers used for public water supply (PWS). Using a simple numerical model, we examine the impact of several pumping scenarios on leakage from an unconfined aquifer to a confined aquifer and conclude that a single inactive multi-aquifer well can contribute nearly 10% of total PWS well flow over a wide range of pumping rates. This leakage can occur even when the multi-aquifer well is more than a kilometer from the PWS well. The contribution from multi-aquifer wells may be greater under conditions where seasonal pumping (e.g., irrigation) creates large, widespread downward hydraulic gradients between aquifers. Under those conditions, water can continue to leak down a multi-aquifer well from an unconfined aquifer to a confined aquifer even when those multi-aquifer wells are actively pumped. An important implication is that, if an unconfined aquifer is contaminated, multi-aquifer wells can increase the vulnerability of a confined-aquifer PWS well.

This fact sheet highlights findings from the vulnerability study of a public-supply well field in San Antonio, Texas. The well field consists of six production wells that tap the Edwards aquifer. Typically, one or two wells are pumped at a time, yielding an average total of 20-21 million gallons per day. Water samples were collected from public-supply wells in the well field and from monitoring wells installed along general directions of flow to the well field. Samples from the well field contained some constituents of concern for drinking-water quality, including nitrate; the pesticide compounds atrazine, deethylatrazine, and simazine; and the volatile organic compounds tetrachloroethene (also called perchloroethene, or PCE), chloroform, bromoform, and dibromochloromethane. These constituents were detected in untreated water at concentrations much less than established drinking-water standards, where such standards exist. Overall, the study findings point to four primary factors that affect the movement and fate of contaminants and the vulnerability of the public-supply well field in San Antonio, Texas: (1) groundwater age (how long ago water entered, or recharged, the aquifer), (2) fast pathways for flow of groundwater through features formed or enlarged by dissolution of bedrock, (3) recharge characteristics of the aquifer, and (4) natural geochemical processes within the aquifer. A computer-model simulation of groundwater flow and transport was used to estimate the traveltime (or age) of water particles entering public-supply well W4 in the well field. Modeled findings show that almost half of the water reaching the public-supply well is less than 2 years old. Such a large percentage of very young water indicates that (1) contaminants entering the aquifer may be transported rapidly to the well, (2) there is limited time for chemical reactions to occur in the aquifer that may attenuate contaminants, and (3) should recharge water become contaminated with pathogenic microorganisms (which have limited survival times in aquifers), the microorganisms may be able to persist to the well. Features formed or enlarged by dissolution of bedrock allow most of the water reaching the well field to travel rapidly from the recharge zone to the supply wells along fast pathways rather than through the aquifer matrix. Supporting evidence includes (1) geophysical logging and flowmeter measurements in public-supply well W4 and in nearby monitoring wells showing that most of the flow volume into and out of the wells occurs in three horizontal zones, thought to be dissolution-enlarged bedding planes; and (2) fluctuations in groundwater chemistry that can be correlated to individual precipitation events. Analysis of water samples collected from shallow, intermediate, and deep zones of the Edwards aquifer at public-supply well W4 and from nearby monitoring wells reveal that water in the vicinity of the selected well field is notably well mixed throughout the sampled thickness of the Edwards aquifer, showing little of the chemical variation with depth that is commonly seen in other aquifers. Contaminants were found at all depths, and they did not enter the well through a specific horizon. The well-mixed nature of the Edwards aquifer is caused by the recharge characteristics of the area combined with fast flow paths through karst features. Constituents of concern in the Edwards aquifer for the long-term sustainability of the groundwater resource include the nutrient nitrate and anthropogenic contaminants such as atrazine, PCE, and chloroform. A scenario of hypothetical contaminant loading in the aquifer recharge zone was evaluated by using results from groundwater-flow-model particle tracking to assess the response of the aquifer to potential contamination. Results indicate that the concentrations at public-supply well W4 would begin to respond to contaminant loading in the recharge zone within 1 year because of short traveltimes through fast flow paths. Within 10 years, contaminant concentrations in the public-supply well would be equal to 90 percent of the input concentration for a contaminant (such as nitrate) that does not degrade in the oxic conditions of the Edwards aquifer.