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J. Jeffrey Starn

Publications and source records attributed to J. Jeffrey Starn.

At least 19 recordsLinked to original sources
USGS2023

Groundwater residence times in glacial aquifers—A new general simulation-model approach compared to conventional inset models

Groundwater is important as a drinking-water source and for maintaining base flow in rivers, streams, and lakes. Groundwater quality can be predicted, in part, by its residence time in the subsurface, but the residence-time distribution cannot be measured directly and must be inferred from models. This report compares residence-time distributions from four areas where groundwater flow and travel time were simulated with conventional simulation-inset models (IMs) and with a new automated model-construction method called general simulation models (GSMs). The comparison provides an opportunity to explore controls on travel time and improve the methods used in the creation of GSMs. These models can be useful for three main-use cases: (1) rapid testing of relationships that govern groundwater flow and age, (2) generation of consistent examples for training a machine-learning metamodel, and (3) serving as a starting point for more detailed models. Comparison of the GSMs to IMs indicated a qualified pattern of agreement for residence-time distributions as indicated by the Nash-Sutcliffe efficiency and Spearman’s correlation coefficient. The agreement was best for the median values of the simulated residence times in young fractions of groundwater (defined as the fractions of groundwater in samples less than 65 years old) at the scale of the eight-digit hydrologic-unit code. Generally, the median values of the young fractions in the IMs were correlated with the median values from the GSMs. The relative trends across the four areas also were similar for the other residence-time metrics. The medians of residence-time metrics at finer scales show a fair degree of scatter. The GSM results compared most poorly for median travel times in the older fraction of groundwater (older than 65 years). The GSM approach is intended as a flexible framework for developing models that can be useful individually as screening tools or collectively to support projects in statistical learning. Although one set of GSM algorithms was presented here, the approach can accommodate many types of data and also different categories of prior information. Comparison of GSMs and IMs suggests ways in which the GSMs, while remaining easy to construct and calibrate, can be improved for estimating groundwater travel times. IMs do not yield exact travel times, and matching GSMs to IMs does not guarantee an improvement; however, IMs provide a convenient benchmark against which to explore relations between physical characteristics of watersheds and the distribution of travel times within them. This effort was undertaken as part of the National Water Quality Program of the U.S. Geological Survey to assist in determining the susceptibility of groundwater in glacial aquifers to a variety of natural and anthropogenic contaminants.

Illinois, Indiana, Michigan, Wisconsin↗
USGS2022

Predicted uranium and radon concentrations in New Hampshire (USA) groundwater—Using Multi Order Hydrologic Position as predictors

Two radioactive elements, uranium (U) and radon (Rn), which are of potential concern in New Hampshire (NH) groundwater, are investigated. Exceedance probability maps are tools to highlight locations where the concentrations of undesirable substances in the groundwater may be elevated. Two forms of statistical analysis are used to create exceedance probability maps for U and Rn in NH groundwater. The first, Boosted Regression Tree (BRT), was selected for estimating U exceedance values. It computes exceedance values directly using the Bernoulli distribution function. The second method of statistical analysis used for Rn to determine exceedance probabilities is ordinary least squares (OLS) regression. In the process of determining exceedance probabilities for U and Rn, the utility of a new dataset is investigated. That new predictor dataset is the Multi-Order Hydrologic Position (MOHP) dataset. MOHP raster datasets have been produced nationally for the conterminous United States at a 30-m resolution. The concept behind MOHP is that, for any given point on the earth's surface, there is the potential for a longer groundwater flow path as one goes deeper beneath the land surface. MOHP predictors were tested in both models. Three MOHP predictors were found useful in the BRT model and two in the OLS model. MOHP data were found useful as predictors along with other site characteristics in predicting U and Rn exceedance probabilities in New Hampshire groundwater.

New Hampshire↗
USGS2022

Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale

Predicting baseflow dynamics, protecting aquatic habitat, and managing legacy contaminants requires explicit characterization and prediction of groundwater discharge patterns throughout river networks. Using handheld thermal infrared (TIR) cameras, we surveyed 47 km of stream length across the Farmington River watershed (1,570 km 2 ; CT and MA, USA), mapping locations of bank and waterline groundwater discharges based on their thermal signature. Using the observed groundwater discharge locations and predicted groundwater discharge rates from 6 variations of a numerical groundwater-flow model (MODFLOW-NWT), we compared 1) predicted groundwater-discharge rates in areas with and without observed groundwater discharge, 2) spatial patterns of observed and predicted groundwater discharge locations, and 3) density of observed groundwater discharge locations with predicted discharge rates. Five of six models reasonably predicted the spatial patterns of discharge locations along the 5th order mainstem, but fewer models predicted groundwater discharge patterns in smaller streams. Our results highlight 1) the feasibility of using TIR observations to evaluate groundwater models, 2) model parameters that influence discharge prediction accuracy (riverbed sediment and bedrock hydraulic conductivity and river-aquifer connections), and 3) current strengths and future opportunities for improved modeling of groundwater-discharge patterns.

Connecticut, Massachusetts↗
USGS2021

Re‐purposing groundwater flow models for age assessments: Important characteristics

Groundwater flow model construction is often time‐consuming and costly, with development ideally focused on a specific purpose, such as quantifying well capture from water bodies or providing flow fields for simulating advective transport. As environmental challenges evolve, the incentive to re‐purpose existing groundwater flow models may increase. However, few studies have evaluated which characteristics of groundwater flow models deserve greatest consideration when re‐purposing models for groundwater age and advective transport simulations. In this paper, we compare simulated age metrics produced by three MODFLOW‐MODPATH models of the same area but with differing levels of complexity (layering and heterogeneity). Comparisons are made at three watershed scales (HUC 8 to HUC 12). Groundwater age metrics, specifically the young fraction and median age of the young and old fractions, are used for evaluation because they relate to intrinsic susceptibility of aquifers and are simpler to interpret than full age distributions used for advective transport. Results indicate that: 1. the young fraction is less sensitive to model layering than the median age of young and old fractions, suggesting that simple models may suffice for basic intrinsic susceptibility assessments; 2. water table mounding and associated discharge into partially penetrating boundaries, such as head‐water streams, is important for simulating both the young fraction and the median age of the young fraction; and 3. the influence of partially penetrating head‐water streams is maintained regardless of the porosity distribution. Results of this work should aid modelers with evaluating the appropriateness of re‐purposing existing groundwater flow models for age simulations.

Groundwater↗
USGS2021

Three-dimensional distribution of residence time metrics in the glaciated United States using metamodels trained on general numerical models

Residence time distribution (RTD) is a critically important characteristic of groundwater flow systems; however, it cannot be measured directly. RTD can be inferred from tracer data with analytical models (few parameters) or with numerical models (many parameters). The second approach permits more variation in system properties but is used less frequently than the first because large‐scale numerical models can be resource intensive. Using a novel automated approach, a set of 115 inexpensive general simulation models (GSMs) was used to create RTD metrics (fraction of young groundwater, defined as < 65 years old; mean travel time of young fraction; median travel time of old fraction; and mean path length). GSMs captured the general trends in measured tritium concentrations in 431 wells. Boosted Regression Tree metamodels were trained to predict these RTD metrics using available wall‐to‐wall hydrogeographic digital sets as explanatory features. The metamodels produced a three‐dimensional distribution of predictions throughout the glacial system that generally matched with the numerical model RTD metrics. In addition to the expected importance of aquifer thickness and recharge rate in predicting RTD metrics, two new data sets, Multi‐Order Hydrologic Position (MOHP) and hydrogeologic terrane were important predictors. These variables by themselves produced metamodels with Nash‐Sutcliffe efficiency close to the full metamodel. Metamodel predictions showed that the volume of young groundwater stored in the glaciated U.S. is about 6,000 km 3 , or about 0.5% of globally stored young groundwater.

Water Resources Research↗
USGS2020

Improved prediction of management-relevant groundwater discharge characteristics throughout river networks

Groundwater discharge zones connect aquifers to surface water, generating baseflow and serving as ecosystem control points across aquatic ecosystems. The influence of groundwater discharge on surface flow connectivity, fate and transport of contaminants and nutrients, and thermal habitat depends strongly on hydrologic characteristics such as the spatial distribution, age, and depth of source groundwater flow paths. Groundwater models have the potential to predict spatial discharge characteristics within river networks, but models are often not evaluated against these critical characteristics and model equifinality with respect to discharge processes is a known challenge. We quantify discharge characteristics across a suite of groundwater models with commonly used frameworks and calibration data. We developed a base model (MODFLOW‐NWT) for a 1,570‐km 2 watershed in the northeastern United States and varied the calibration data, control of river‐aquifer exchange directionality, and resolution. Most models ( n = 11 of 12) fit similarly to calibration metrics, but patterns in discharge location, flow path depth, and subsurface travel time varied substantially. We found (1) a 15% difference in the percent of discharge going to first‐order streams, (2) threefold variations in flow path depth, and (3) sevenfold variations in the subsurface travel times among the models. We recalibrated three models using a synthetic discharge location data set. Calibration with discharge location data reduced differences in simulated discharge characteristics, suggesting an approach to improved equifinality based on widespread field‐based mapping of discharge zones. Our work quantifying variation across common modeling approaches is an important step toward characterizing and improving predictions of groundwater discharge characteristics.

Connecticut, Massachusetts↗
USGS2019

Multiorder hydrologic position in the conterminous United States: A set of metrics in support of groundwater mapping at regional and national scales

The location of a point on the landscape within a stream network (hydrologic position) can be an important predictive measure in hydrology. Hydrologic position is defined here by two metrics: lateral position and distance from stream to divide, both measured horizontally. Lateral position (dimensionless) is the relative position of a point between the stream and its watershed divide. Distance from stream to divide (units of length) is an indicator of position within a watershed: generally small near a confluence and generally large in headwater areas. Watersheds and watershed divides are defined here by Thiessen polygons rather than topographic divides. Lateral position and distance from stream to divide are also defined in the context of hydrologic order. Hydrologic order “ n ” is defined as the network of streams, and associated divides, of order n and higher. And given that a point can have different positions in different hydrologic orders the term multiorder hydrologic position (MOHP) is used to describe the ensemble of hydrologic positions. MOHP was mapped across the conterminous United States for nine hydrologic orders at a spatial resolution of 30 m (about 8.7 billion pixels). There are 18 metrics for each pixel. Four case studies are presented that use MOHP metrics as explanatory factors in random forest machine learning models. The case studies show that lower order MOHP metrics can serve as indicators of hydrologic process while higher‐order metrics serve as indicators of location. MOHP is shown to have utility as a predictor variable across a large range of scales (50,000 to 8,000,000 km 2 ).

Water Resources Research↗
USGS2018

Regionalization of groundwater residence time using metamodeling

Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to degradation. A novel combination of numerical modeling and statistical methods allows estimation of regional RTDs with unprecedented speed. In this method, particle RTDs are generated in 30 type locales in the northeastern glaciated U.S using automated generalized finite-difference groundwater flow and advective transport models. Targets for statistical learning were created from particle RTDs by fitting Weibull, gamma, and inverse Gaussian distributions. Whole-basin flux-weighted RTDs were well fit by one-component Weibull distributions. Flux-weighted RTDs at stressed receptors such as wells often produced more complicated RTDs that required a two-component mixture to fit. A Multitask Lasso regression was trained on the parametric RTDs using hydrogeographic features of the modeled areas as explanatory features. In this way, RTDs are regionalized using mappable physical features such as recharge and aquifer volume. The shape, location, and scale parameters of the parametric RTDs are strongly related to the mean exponential age. The shape parameter of the distribution, which controls deviation from exponential, is additionally a function of aquifer heterogeneity and hydrologic features. Regionalized RTDs provide useful metrics with respect to groundwater lag times and solute loading to streams. The lag time between input and output contained in the RTD is critical to understanding the relation between the land surface and human and ecological receptors.

Water Resources Research↗
USGS2014

Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection

Analytical models of the travel time distribution (TTD) from a source area to a sample location are often used to estimate groundwater ages and solute concentration trends. The accuracies of these models are not well known for geologically complex aquifers. In this study, synthetic datasets were used to quantify the accuracy of four analytical TTD models as affected by TTD complexity, observation errors, model selection, and tracer selection. Synthetic TTDs and tracer data were generated from existing numerical models with complex hydrofacies distributions for one public-supply well and 14 monitoring wells in the Central Valley, California. Analytical TTD models were calibrated to synthetic tracer data, and prediction errors were determined for estimates of TTDs and conservative tracer (NO 3 −) concentrations. Analytical models included a new, scale-dependent dispersivity model (SDM) for two-dimensional transport from the watertable to a well, and three other established analytical models. The relative influence of the error sources (TTD complexity, observation error, model selection, and tracer selection) depended on the type of prediction. Geological complexity gave rise to complex TTDs in monitoring wells that strongly affected errors of the estimated TTDs. However, prediction errors for NO3− and median age depended more on tracer concentration errors. The SDM tended to give the most accurate estimates of the vertical velocity and other predictions, although TTD model selection had minor effects overall. Adding tracers improved predictions if the new tracers had different input histories. Studies using TTD models should focus on the factors that most strongly affect the desired predictions.

California↗
USGS2014

Simulating water-quality trends in public-supply wells in transient flow systems

Models need not be complex to be useful. An existing groundwater-flow model of Salt Lake Valley, Utah, was adapted for use with convolution-based advective particle tracking to explain broad spatial trends in dissolved solids. This model supports the hypothesis that water produced from wells is increasingly younger with higher proportions of surface sources as pumping changes in the basin over time. At individual wells, however, predicting specific water-quality changes remains challenging. The influence of pumping-induced transient groundwater flow on changes in mean age and source areas is significant. Mean age and source areas were mapped across the model domain to extend the results from observation wells to the entire aquifer to see where changes in concentrations of dissolved solids are expected to occur. The timing of these changes depends on accurate estimates of groundwater velocity. Calibration to tritium concentrations was used to estimate effective porosity and improve correlation between source area changes, age changes, and measured dissolved solids trends. Uncertainty in the model is due in part to spatial and temporal variations in tracer inputs, estimated tracer transport parameters, and in pumping stresses at sampling points. For tracers such as tritium, the presence of two-limbed input curves can be problematic because a single concentration can be associated with multiple disparate travel times. These shortcomings can be ameliorated by adding hydrologic and geologic detail to the model and by adding additional calibration data. However, the Salt Lake Valley model is useful even without such small-scale detail.

Utah↗
USGS2013

Uncertainty in simulated groundwater-quality trends in transient flow

In numerical modeling of groundwater flow, the result of a given solution method is affected by the way in which transient flow conditions and geologic heterogeneity are simulated. An algorithm is demonstrated that simulates breakthrough curves at a pumping well by convolution-based particle tracking in a transient flow field for several synthetic basin-scale aquifers. In comparison to grid-based (Eulerian) methods, the particle (Lagrangian) method is better able to capture multimodal breakthrough caused by changes in pumping at the well, although the particle method may be apparently nonlinear because of the discrete nature of particle arrival times. Trial-and-error choice of number of particles and release times can perhaps overcome the apparent nonlinearity. Heterogeneous aquifer properties tend to smooth the effects of transient pumping, making it difficult to separate their effects in parameter estimation. Porosity, a new parameter added for advective transport, can be accurately estimated using both grid-based and particle-based methods, but predictions can be highly uncertain, even in the simple, nonreactive case.

Hydrogeology Journal↗
USGS2013

The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio

Statistical models of nitrate occurrence in the glacial aquifer system of the northern United States, developed by the U.S. Geological Survey, use observed relations between nitrate concentrations and sets of explanatory variables—representing well-construction, environmental, and source characteristics— to predict the probability that nitrate, as nitrogen, will exceed a threshold concentration. However, the models do not explicitly account for the processes that control the transport of nitrogen from surface sources to a pumped well and use area-weighted mean spatial variables computed from within a circular buffer around the well as a simplified source-area conceptualization. The use of models that explicitly represent physical-transport processes can inform and, potentially, improve these statistical models. Specifically, groundwater-flow models simulate advective transport—predominant in many surficial aquifers— and can contribute to the refinement of the statistical models by (1) providing for improved, physically based representations of a source area to a well, and (2) allowing for more detailed estimates of environmental variables. A source area to a well, known as a contributing recharge area, represents the area at the water table that contributes recharge to a pumped well; a well pumped at a volumetric rate equal to the amount of recharge through a circular buffer will result in a contributing recharge area that is the same size as the buffer but has a shape that is a function of the hydrologic setting. These volume-equivalent contributing recharge areas will approximate circular buffers in areas of relatively flat hydraulic gradients, such as near groundwater divides, but in areas with steep hydraulic gradients will be elongated in the upgradient direction and agree less with the corresponding circular buffers. The degree to which process-model-estimated contributing recharge areas, which simulate advective transport and therefore account for local hydrologic settings, would inform and improve the development of statistical models can be implicitly estimated by evaluating the differences between explanatory variables estimated from the contributing recharge areas and the circular buffers used to develop existing statistical models. The larger the difference in estimated variables, the more likely that statistical models would be changed, and presumably improved, if explanatory variables estimated from contributing recharge areas were used in model development. Comparing model predictions from the two sets of estimated variables would further quantify—albeit implicitly—how an improved, physically based estimate of explanatory variables would be reflected in model predictions. Differences between the two sets of estimated explanatory variables and resultant model predictions vary spatially; greater differences are associated with areas of steep hydraulic gradients. A direct comparison, however, would require the development of a separate set of statistical models using explanatory variables from contributing recharge areas. Area-weighted means of three environmental variables—silt content, alfisol content, and depth to water from the U.S. Department of Agriculture State Soil Geographic (STATSGO) data—and one nitrogen-source variable (fertilizer-application rate from county data mapped to Enhanced National Land Cover Data 1992 (NLCDe 92) agricultural land use) can vary substantially between circular buffers and volume-equivalent contributing recharge areas and among contributing recharge areas for different sets of well variables. The differences in estimated explanatory variables are a function of the same factors affecting the contributing recharge areas as well as the spatial resolution and local distribution of the underlying spatial data. As a result, differences in estimated variables between circular buffers and contributing recharge areas are complex and site specific as evidenced by differences in estimated variables for circular buffers and contributing recharge areas of existing public-supply and network wells in the Great Miami River Basin. Large differences in areaweighted mean environmental variables are observed at the basin scale, determined by using the network of uniformly spaced hypothetical wells; the differences have a spatial pattern that generally is similar to spatial patterns in the underlying STATSGO data. Generally, the largest differences were observed for area-weighted nitrogen-application rate from county and national land-use data; the basin-scale differences ranged from -1,600 (indicating a larger value from within the volume-equivalent contributing recharge area) to 1,900 kilograms per year (kg/yr); the range in the underlying spatial data was from 0 to 2,200 kg/yr. Silt content, alfisol content, and nitrogen-application rate are defined by the underlying spatial data and are external to the groundwater system; however, depth to water is an environmental variable that can be estimated in more detail and, presumably, in a more physically based manner using a groundwater-flow model than using the spatial data. Model-calculated depths to water within circular buffers in the Great Miami River Basin differed substantially from values derived from the spatial data and had a much larger range. Differences in estimates of area-weighted spatial variables result in corresponding differences in predictions of nitrate occurrence in the aquifer. In addition to the factors affecting contributing recharge areas and estimated explanatory variables, differences in predictions also are a function of the specific set of explanatory variables used and the fitted slope coefficients in a given model. For models that predicted the probability of exceeding 1 and 4 milligrams per liter as nitrogen (mg/L as N), predicted probabilities using variables estimated from circular buffers and contributing recharge areas generally were correlated but differed significantly at the local and basin scale. The scale and distribution of prediction differences can be explained by the underlying differences in the estimated variables and the relative weight of the variables in the statistical models. Differences in predictions of exceeding 1 mg/L as N, which only includes environmental variables, generally correlated with the underlying differences in STATSGO data, whereas differences in exceeding 4 mg/L as N were more spatially extensive because that model included environmental and nitrogen-source variables. Using depths to water from within circular buffers derived from the spatial data and depths to water within the circular buffers calculated from the groundwater-flow model, restricted to the same range, resulted in large differences in predicted probabilities. The differences in estimated explanatory variables between contributing recharge areas and circular buffers indicate incorporation of physically based contributing recharge area likely would result in a different set of explanatory variables and an improved set of statistical models. The use of a groundwater-flow model to improve representations of source areas or to provide more-detailed estimates of specific explanatory variables includes a number of limitations and technical considerations. An assumption in these analyses is that (1) there is a state of mass balance between recharge and pumping, and (2) transport to a pumped well is under a steady state flow field. Comparison of volumeequivalent contributing recharge areas under steady-state and transient transport conditions at a location in the southeastern part of the basin shows the steady-state contributing recharge area is a reasonable approximation of the transient contributing recharge area after between 10 and 20 years of pumping. The first assumption is a more important consideration for this analysis. A gradient effect refers to a condition where simulated pumping from a well is less than recharge through the corresponding contributing recharge area. This generally takes place in areas with steep hydraulic gradients, such as near discharge locations, and can be mitigated using a finer model discretization. A boundary effect refers to a condition where recharge through the contributing recharge area is less than pumping. This indicates other sources of water to the simulated well and could reflect a real hydrologic process. In the Great Miami River Basin, large gradient and boundary effects—defined as the balance between pumping and recharge being less than half—occurred in 5 and 14 percent of the basin, respectively. The agreement between circular buffers and volume-equivalent contributing recharge areas, differences in estimated variables, and the effect on statisticalmodel predictions between the population of wells with a balance between pumping and recharge within 10 percent and the population of all wells were similar. This indicated process-model limitations did not affect the overall findings in the Great Miami River Basin; however, this would be model specific, and prudent use of a process model needs to entail a limitations analysis and, if necessary, alterations to the model.

Ohio↗
USGS2012

Methods for simulating solute breakthrough curves in pumping groundwater wells

In modeling there is always a trade-off between execution time and accuracy. For gradient-based parameter estimation methods, where a simulation model is run repeatedly to populate a Jacobian (sensitivity) matrix, there exists a need for rapid simulation methods of known accuracy that can decrease execution time, and thus make the model more useful without sacrificing accuracy. Convolution-based methods can be executed rapidly for any desired input function once the residence-time distribution is known. The residence-time distribution can be calculated efficiently using particle tracking, but particle tracking can be ambiguous near a pumping well if the grid is too coarse. We present several embedded analytical expressions for improving particle tracking near a pumping well and compare them with a finely gridded finite-difference solution in terms of accuracy and CPU usage. Even though the embedded analytical approach can improve particle tracking near a well, particle methods reduce, but do not eliminate, reliance on a grid because velocity fields typically are calculated on a grid, and additional error is incurred using linear interpolation of velocity. A dilution rate can be calculated for a given grid and pumping well to determine if the grid is sufficiently refined. Embedded analytical expressions increase accuracy but add significantly to CPU usage. Structural error introduced by the numerical solution method may affect parameter estimates.

Computers & Geosciences↗
USGS2011

Programs for calibration‐based Monte Carlo simulation of recharge areas

One use of groundwater flow models is to simulate contributing recharge areas to wells or springs. Particle tracking can be used to simulate these recharge areas, but in many cases the modeler is not sure how accurate these recharge areas are because parameters such as hydraulic conductivity and recharge have errors associated with them. The scripts described in this article (GEN_LHS and MCDRIVER_LHS) use the Python scripting language to run a Monte Carlo simulation with Latin hypercube sampling where model parameters such as hydraulic conductivity and recharge are randomly varied for a large number of model simulations, and the probability of a particle being in the contributing area of a well is calculated based on the results of multiple simulations. Monte Carlo simulation provides one useful measure of the variability in modeled particles. The Monte Carlo method described here is unique in that it uses parameter sets derived from the optimal parameters, their standard deviations, and their correlation matrix, all of which are calculated during nonlinear regression model calibration. In addition, this method uses a set of acceptance criteria to eliminate unrealistic parameter sets.

Ground Water↗
USGS2011

USGS library for S-PLUS for Windows -- Release 4.0

Release 4.0 of the U.S. Geological Survey S-PLUS library supercedes release 2.1. It comprises functions, dialogs, and datasets used in the U.S. Geological Survey for the analysis of water-resources data. This version does not contain ESTREND, which was in version 2.1. See Release 2.1 for information and access to that version. This library requires Release 8.1 or later of S-PLUS for Windows. S-PLUS is a commercial statistical and graphical analysis software package produced by TIBCO corporation(http://www.tibco.com/). The USGS library is not supported by TIBCO or its technical support staff.

Open-File Report↗
USGS2010

Assessing the vulnerability of public-supply wells to contamination: Glacial aquifer system in Woodbury, Connecticut

This fact sheet highlights findings from the vulnerability study of a public-supply well in Woodbury, Connecticut. The well typically produces water at the rate of 72 gallons per minute from the glacial aquifer system in the Pomperaug River Basin. Water samples were collected at the public-supply well and at monitoring wells installed in or near the simulated zone of contribution to the supply well. Samples of untreated water from the public-supply wellhead contained several types of undesirable constituents, including 11 volatile organic compounds (VOCs), nitrate, pesticides, uranium, and radon. Most of these constituents were detected at concentrations below drinking-water standards, where such standards exist. Only concentrations of the VOC trichlorethylene exceeded the Maximum Contaminant Level (MCL) of 5 micrograms per liter (ug/L) established by U.S. Environmental Protection Agency for drinking water. Radon concentrations exceeded a proposed-but not finalized-MCL of 300 picocuries per liter (pCi/L). Overall, the study findings point to four main factors that affect the movement and fate of contaminants and the vulnerability of the public-supply well in Woodbury: (1) groundwater age (how long ago water entered, or recharged, the aquifer); (2) the percentage of recharge received through urban areas; (3) the percentage of recharge received through dry wells and their proximity to the public-supply well; and (4) natural geochemical processes occurring within the aquifer system; that is, processes that affect the amounts and distribution of chemical substances in aquifer sediments and groundwater. A computer-model simulation of groundwater flow to the public-supply well was used to estimate the age of water particles entering the well along the length of the well screen. About 90 percent of the simulated flow to the well consists of water that entered the aquifer 9 or fewer years ago. Such young water is vulnerable to contaminants resulting from human activities, as indicated by the solvents, fuel components, road salt, and septic-system leachate that were detected in the glacial aquifer system during the current study. Age-dating combined with chemical modeling suggests that less than 2 percent of water produced by the public-supply well is water from the deep bedrock that is "old" (water that recharged, or entered, the aquifer before 1952). Such a small percentage of old groundwater entering the public-supply well offers little potential for dilution of young waters containing contaminants from human activities. Shallow groundwater that originated as recharge through urban areas generally had higher median concentrations and more detections of volatile organic compounds (VOCs) than did groundwater from the deep glacial deposits or fractured bedrock that originated mainly as recharge through agricultural and undeveloped land. Shallow groundwater was also found to be affected by road salt and septic-system leachate. A chemical mixing model indicates that up to 15 percent of nitrate in water from the supply well is likely from septic-system leachate. The Connecticut Department of Public Health has identified several potential sources of contamination in the commercial area of Woodbury (several light industrial or commercial properties where hazardous materials and petroleum products are used and stored). To reduce stormwater runoff in the commercial area, water from the parking lots and pavement is channeled into dry wells-drains that shunt water directly into the aquifer system, bypassing the soil and unsaturated zones. A computer-model simulation of groundwater flow indicates that approximately 16 percent of the water produced by the public-supply well is derived from runoff captured by these drains. Traveltime for water from the dry wells to the public-supply well ranges from about 1.5 to less than 4 years. Dry wells have the potential to enhance contaminant movement to the supply well, suggesting that stormwater-control methods cannot be considered separately from groundwater quality—they are linked. Water-quality protection in this setting depends on the entire community. If residents and businesses take steps to reduce input of manmade contaminants to groundwater, a positive effect on quality of the supply-well water might begin to be seen in less than 10 years, owing to the short residence time of water in the aquifer.

Connecticut↗
USGS2010

Estimation of the effects of land use and groundwater withdrawals on streamflow for the Pomperaug River, Connecticut

A precipitation runoff model for the Pomperaug River watershed, Connecticut was developed to address issues of concern including the effect of development on streamflow and groundwater recharge, and the implications of water withdrawals on streamflow. The model was parameterized using a strategy that requires a minimum of calibration and optimization by establishing basic relations between the parameter value and physical characteristics of individual hydrologic response units (HRUs) that comprise the model. The strategy was devised so that the information needed can be obtained from Geographic Information System and other general databases for Connecticut. Simulation of groundwater recharge enabled evaluation of the temporal and spatial mapping of recharge variation across the watershed and the spatial effects of changes in land cover on base flow and surface runoff. The modeling indicated that over the course of a year, groundwater provides between 60 and 70 percent of flow in the Pomperaug River; the remainder is generated by more rapid flow through the shallow subsurface and runoff from impermeable surfaces and saturated ground. Groundwater is recharged primarily during periods of low evapotranspiration in the winter, spring, and fall. The largest amount of recharge occurs in the spring in response to snowmelt. During floods, the Weekeepeemee and Nonnewaug Rivers (tributaries that form the Pomperaug River) respond rapidly with little flood peak attenuation due to flood-plain storage. In the Pomperaug River, flood-plain storage is more important in attenuating floods; abandoned quarry ponds (O&G ponds) adjacent to the river provide substantial flood storage above specific river stages when flow from the river spills over the banks and fills the ponds. Discharge from the ponds also helps to sustain low flows in the Pomperaug River. Similarly, releases from the Bronson-Lockwood reservoir sustain flow in the Nonnewaug River and tend to offset the effect of groundwater withdrawals from a well field adjacent to the river during periods of natural low flow. The model indicated that under the current zoning, future development could reduce low flows by as much as 10 percent at the 99 percent exceedance level (99 percent of flows are greater than or equal to this flow), but would not substantially increase the highest flows. Simulation of projected and hypothetical development in the watershed shows, depending on how stormwater is managed, that between 10 and 20 percent effective impervious area in an HRU results in streamflow becoming dominated by the surface-runoff component. This shift from a groundwater-dominated system would likely result in substantial changes in water quality and instream habitat characteristics of the river. Base flow to streams in the Pomperaug River watershed is reduced by both increased impervious surface and increased groundwater withdrawals. For the watershed as a whole, increasing groundwater withdrawals have the potential for causing greater overall reductions in flow compared to increased development and impervious surfaces. Additionally, on the basis of groundwater-modeling simulations, the projected increase in development across the watershed and, to a lesser extent the increase in groundwater withdrawals, will increase the number of local losing reaches experiencing dry conditions and the duration of these dry periods. The location of the losing reaches tends to be in areas near the transition from the uplands to the valley bottoms that are filled with coarse glacial stratified deposits. The simulated increase in the duration and extent of localized dry stream reaches is most sensitive to local increase in impervious surface. Conversion of land from forest or developed land cover to pasture or agricultural land increases groundwater recharge and discharge to streams, while at the same time increasing overall streamflow (the opposite effect as increased impervious surface). These resu

Scientific Investigations Report↗