Temporally dense monitoring of pathogen occurrence at four drinking-water well sites - Insights and Implications.

Yearlong, event based, microbiological and chemical sampling was conducted at four public water supply well sites spanning a range of geologic settings and well depths to look for correlation between precipitation events and microbial occurrence. Near-continuous monitoring using autosamplers occurred just before, during, and after 5-7 sampling events triggered by rainfall and/or snowmelt. Microbial genetic material was noted at all four locations during all but one sampling event, but was exceedingly variable in time, where one sample would have no detections and the next sample could be a relatively high concentration. The highest microbial sums (microbial concentrations summed over an event) were observed during months in which precipitation exceeded historical averages. Extended wet conditions through the spring thaw resulted in the highest percentage of microbial positive samples, though at relatively low concentrations. Sampling events that followed drier than normal periods showed longer lag times between the onset of precipitation and microbial occurrence, as well as lower microbial detection rates. Although a general lag time pattern was observed at each site, the largest offset in time was observed at the site with the greatest depth to water. The study's temporally dense representation of drinking water pathogen characterization suggests that single event or infrequent periodic sampling of a drinking water supply cannot provide a representative characterization of the probability that pathogens are present, which likely has ramifications for calculating health risk assessments.

Source and transport of human enteric viruses in deep municipal water supply wells.

Until recently, few water utilities or researchers were aware of possible virus presence in deep aquifers and wells. During 2008 and 2009 we collected a time series of virus samples from six deep municipal water-supply wells. The wells range in depth from approximately 220 to 300 m and draw water from a sandstone aquifer. Three of these wells draw water from beneath a regional aquitard, and three draw water from both above and below the aquitard. We also sampled a local lake and untreated sewage as potential virus sources. Viruses were detected up to 61% of the time in each well sampled, and many groundwater samples were positive for virus infectivity. Lake samples contained viruses over 75% of the time. Virus concentrations and serotypes observed varied markedly with time in all samples. Sewage samples were all extremely high in virus concentration. Virus serotypes detected in sewage and groundwater were temporally correlated, suggesting very rapid virus transport, on the order of weeks, from the source(s) to wells. Adenovirus and enterovirus levels in the wells were associated with precipitation events. The most likely source of the viruses in the wells was leakage of untreated sewage from sanitary sewer pipes.

New Capabilities in MT3D-USGS for Simulating Unsaturated-Zone Heat Transport.

Changes in climate and land use will alter groundwater heat transport dynamics in the future. These changes will in turn affect watershed processes (e.g., nutrient cycling) as well as watershed characteristics (e.g., distribution and persistence of cold-water habitat). Thus, groundwater flow and heat transport models at watershed scales that can characterize and quantify thermal impacts of surface temperature change on groundwater system temperatures may support forecasting changes to groundwater-linked ecosystems in riparian zones, streams, and lakes. Including unsaturated zone processes has previously been shown to be important for properly determining the timing and magnitude of groundwater recharge (Hunt et al. 2008). Similarly, heat transport dynamics in the saturated-zone, as well as connected surface-water systems, can be appreciably influenced by unsaturated-zone processes; in this way the unsaturated zone forms an inextricable link between the land surface where change occurs and the groundwater system that transmits that change. This paper presents new capabilities for the existing MT3D-USGS transport simulator by adding functionality for simulating heat transport through the unsaturated zone. New simulation capabilities are verified through comparison of simulation results with those of the variably saturated heat transport simulator VS2DH under steady and transient conditions for both water and heat flow. The new capabilities are assessed using a number of conceptualizations and include evaluations of convective and conductive heat flow. These additional capabilities increase the utility for applied watershed-scale simulations, which in turn may facilitate more realistic characterizations of temperature change on thermally sensitive ecosystems, such as stream habitat.

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 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 an 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.

Risk-Based Wellhead Protection Decision Support: A Repeatable Workflow Approach.

Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real world application of delineating risk-based (probabilistic) sources of water to supply wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries. These specific data are available in the United States but the tools can be applied to similar datasets worldwide. The workflow builds the model, performs ensemble-based history matching, and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing source water to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems.

Evaluating Lower Computational Burden Approaches for Calibration of Large Environmental Models.

Realistic environmental models used for decision making typically require a highly parameterized approach. Calibration of such models is computationally intensive because widely used parameter estimation approaches require individual forward runs for each parameter adjusted. These runs construct a parameter-to-observation sensitivity, or Jacobian, matrix used to develop candidate parameter upgrades. Parameter estimation algorithms are also commonly adversely affected by numerical noise in the calculated sensitivities within the Jacobian matrix, which can result in unnecessary parameter estimation iterations and less model-to-measurement fit. Ideally, approaches to reduce the computational burden of parameter estimation will also increase the signal-to-noise ratio related to observations influential to the parameter estimation even as the number of forward runs decrease. In this work a simultaneous increments, an iterative ensemble smoother (IES), and a randomized Jacobian approach were compared to a traditional approach that uses a full Jacobian matrix. All approaches were applied to the same model developed for decision making in the Mississippi Alluvial Plain, USA. Both the IES and randomized Jacobian approach achieved a desirable fit and similar parameter fields in many fewer forward runs than the traditional approach; in both cases the fit was obtained in fewer runs than the number of adjustable parameters. The simultaneous increments approach did not perform as well as the other methods due to inability to overcome suboptimal dropping of parameter sensitivities. This work indicates that use of highly efficient algorithms can greatly speed parameter estimation, which in turn increases calibration vetting and utility of realistic models used for decision making.

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.

Sources and Risk Factors for Nitrate and Microbial Contamination of Private Household Wells in the Fractured Dolomite Aquifer of Northeastern Wisconsin.

BACKGROUND: Groundwater quality in the Silurian dolomite aquifer in northeastern Wisconsin, USA, has become contentious as dairy farms and exurban development expand. OBJECTIVES: We investigated private household wells in the region, determining the extent, sources, and risk factors of nitrate and microbial contamination. METHODS: Total coliforms, Escherichia coli, and nitrate were evaluated by synoptic sampling during groundwater recharge and no-recharge periods. Additional seasonal sampling measured genetic markers of human and bovine fecal-associated microbes and enteric zoonotic pathogens. We constructed multivariable regression models of detection probability (log-binomial) and concentration (gamma) for each contaminant to identify risk factors related to land use, precipitation, hydrogeology, and well construction. RESULTS: Total coliforms and nitrate were strongly associated with depth-to-bedrock at well sites and nearby agricultural land use, but not septic systems. Both human wastewater and cattle manure contributed to well contamination. Rotavirus group A, Cryptosporidium, and Salmonella were the most frequently detected pathogens. Wells positive for human fecal markers were associated with depth-to-groundwater and number of septic system drainfield within 229m. Manure-contaminated wells were associated with groundwater recharge and the area size of nearby agricultural land. Wells positive for any fecal-associated microbe, regardless of source, were associated with septic system density and manure storage proximity modified by bedrock depth. Well construction was generally not related to contamination, indicating land use, groundwater recharge, and bedrock depth were the most important risk factors. DISCUSSION: These findings may inform policies to minimize contamination of the Silurian dolomite aquifer, a major water supply for the U.S. and Canadian Great Lakes region. https://doi.org/10.1289/EHP7813.

Assessment of sewer source contamination of drinking water wells using tracers and human enteric viruses.

This study investigated the source, transport, and occurrence of human enteric viruses in municipal well water, focusing on sanitary sewer sources. A total of 33 wells from 14 communities were sampled once for wastewater tracers and viruses. Wastewater tracers were detected in four of these wells, and five wells were virus- positive by qRT-PCR. These results, along with exclusion of wells with surface water sources, were used to select three wells for additional investigation. Viruses and wastewater tracers were found in the groundwater at all sites. Some wastewater tracers, such as ionic detergents, flame retardants, and cholesterol, were considered unambiguous evidence of wastewater. Sampling at any given time may not show concurrent virus and tracer presence; however, given sufficient sampling over time, a relation between wastewater tracers and virus occurrence was identified. Presence of infectious viruses at the wellhead demonstrates that high-capacity pumping induced sufficiently short travel times for the transport of infectious viruses. Therefore, drinking-water wells are vulnerable to contaminants that travel along fast groundwater flowpaths even if they contribute a small amount of virus-laden water to the well. These results suggest that vulnerability assessments require characterization of "low yield-fast transport" in addition to traditional "high yield-slow transport", pathways.

Revisiting "An Exercise in Groundwater Model Calibration and Prediction" After 30 Years: Insights and New Directions.

In 1988, an important publication moved model calibration and forecasting beyond case studies and theoretical analysis. It reported on a somewhat idyllic graduate student modeling exercise where many of the system properties were known; the primary forecasts of interest were heads in pumping wells after a river was modified. The model was calibrated using manual trial-and-error approaches where a model's forecast quality was not related to how well it was calibrated. Here, we investigate whether tools widely available today obviate the shortcomings identified 30 years ago. A reconstructed version of the 1988 true model was tested using increasing parameter estimation sophistication. The parameter estimation demonstrated the inverse problem was non-unique because only head data were available for calibration. When a flux observation was included, current parameter estimation approaches were able to overcome all calibration and forecast issues noted in 1988. The best forecasts were obtained from a highly parameterized model that used pilot points for hydraulic conductivity and was constrained with soft knowledge. Like the 1988 results, however, the best calibrated model did not produce the best forecasts due to parameter overfitting. Finally, a computationally frugal linear uncertainty analysis demonstrated that the single-zone model was oversimplified, with only half of the forecasts falling within the calculated uncertainty bounds. Uncertainties from the highly parameterized models had all six forecasts within the calculated uncertainty. The current results outperformed those of the 1988 effort, demonstrating the value of quantitative parameter estimation and uncertainty analysis methods.

A Simple Method for Simulating Groundwater Interactions with Fens to Forecast Development Effects.

Protection of fens-wetlands dependent on groundwater discharge-requires characterization of groundwater sources and stresses. Because instrumentation and numerical modeling of fens is labor intensive, easy-to-apply methods that model fen distribution and their vulnerability to development are desirable. Here we demonstrate that fen areas can be simulated using existing steady-state MODFLOW models when the unsaturated zone flow (UZF) package is included. In cells where the water table is near land surface, the UZF package calculates a head difference and scaled conductance at these "seepage drain" cells to generate average rates of vertical seepage to the land. This formulation, which represents an alternative to blanketing the MODFLOW domain with drains, requires very little input from the user because unsaturated flow-routing is inactive and results are primarily driven by easily obtained topographic information. Like the drain approach, it has the advantage that the distribution of seepage areas is not predetermined by the modeler, but rather emerges from simulated heads. Beyond the drain approach, it takes account of intracell land surface variation to explicitly quantify multiple surficial flows corresponding to infiltration, rejected recharge, recharge and land-surface seepage. Application of the method to a basin in southeastern Wisconsin demonstrates how it can be used as a decision-support tool to first, reproduce fen distribution and, second, forecast drawdown and reduced seepage at fens in response to shallow pumping.

Automated Time Series Measurement of Microbial Concentrations in Groundwater-Derived Water Supplies.

Fecal contamination by human and animal pathogens, including viruses, bacteria, and protozoa, is a potential human health hazard, especially with regards to drinking water. Pathogen occurrence in groundwater varies considerably in space and time, which can be difficult to characterize as sampling typically requires hundreds of liters of water to be passed through a filter. Here we describe the design and deployment of an automated sampler suited for hydrogeologically and chemically dynamic groundwater systems. Our design focused on a compact form to facilitate transport and quick deployment to municipal and domestic water supplies. We deployed a sampler to characterize water quality from a household well tapping a shallow fractured dolomite aquifer in northeast Wisconsin. The sampler was deployed from January to April 2017, and monitored temperature, nitrate, chloride, specific conductance, and fluorescent dissolved organic matter on a minute time step; water was directed to sequential microbial filters during three recharge periods that ranged from 5 to 20 days. Results from the automated sampler demonstrate the dynamic nature of the household water quality, especially with regard to microbial targets, which were shown to vary 1 to 2 orders of magnitude during a single sampling event. We believe assessments of pathogen occurrence and concentration, and related assessments of drinking well vulnerability, would be improved by the time-integrated characterization provided by this sampler.

Comparison of total mercury and methylmercury cycling at five sites using the small watershed approach.

The small watershed approach is well-suited but underutilized in mercury research. We applied the small watershed approach to investigate total mercury (THg) and methylmercury (MeHg) dynamics in streamwater at the five diverse forested headwater catchments of the US Geological Survey Water, Energy, and Biogeochemical Budgets (WEBB) program. At all sites, baseflow THg was generally less than 1ng L(-1) and MeHg was less than 0.2ng L(-1). THg and MeHg concentrations increased with streamflow, so export was primarily episodic. At three sites, THg and MeHg concentration and export were dominated by the particulate fraction in association with POC at high flows, with maximum THg (MeHg) concentrations of 94 (2.56)ng L(-1) at Sleepers River, Vermont; 112 (0.75)ng L(-1) at Rio Icacos, Puerto Rico; and 55 (0.80)ng L(-1) at Panola Mt., Georgia. Filtered (<0.7microm) THg increased more modestly with flow in association with the hydrophobic acid fraction (HPOA) of DOC, with maximum filtered THg concentrations near 5ng L(-1) at both Sleepers and Icacos. At Andrews Creek, Colorado, THg export was also episodic but was dominated by filtered THg, as POC concentrations were low. MeHg typically tracked THg so that each site had a fairly constant MeHg/THg ratio, which ranged from near zero at Andrews to 15% at the low-relief, groundwater-dominated Allequash Creek, Wisconsin. Allequash was the only site with filtered MeHg consistently above detection, and the filtered fraction dominated both THg and MeHg. Relative to inputs in wet deposition, watershed retention of THg (minus any subsequent volatilization) was 96.6% at Allequash, 60% at Sleepers, and 83% at Andrews. Icacos had a net export of THg, possibly due to historic gold mining or frequent disturbance from landslides. Quantification and interpretation of Hg dynamics was facilitated by the small watershed approach with emphasis on event sampling.

Are models too simple? Arguments for increased parameterization.

The idea that models should be as simple as possible is often accepted without question. However, too much simplification and parsimony may degrade a model's utility. Models are often constructed to make predictions; yet, they are commonly parameterized with a focus on calibration, regardless of whether (1) the calibration data can constrain simulated predictions or (2) the number and type of calibration parameters are commensurate with the hydraulic property details on which key predictions may depend. Parameterization estimated through the calibration process is commonly limited by the necessity that the number of calibration parameters be smaller than the number of observations. This limitation largely stems from historical restrictions in calibration and computing capability; we argue here that better methods and computing capabilities are now available and should become more widely used. To make this case, two approaches to model calibration are contrasted: (1) a traditional approach based on a small number of homogeneous parameter zones defined by the modeler a priori and (2) regularized inversion, which includes many more parameters than the traditional approach. We discuss some advantages of regularized inversion, focusing on the increased insight that can be gained from calibration data. We present these issues using reasoning that we believe has a common sense appeal to modelers; knowledge of mathematics is not required to follow our arguments. We present equations in an Appendix, however, to illustrate the fundamental differences between traditional model calibration and a regularized inversion approach.

Ground water modeling applications using the analytic element method.

Though powerful and easy to use, applications of the analytic element method are not as widespread as finite-difference or finite-element models due in part to their relative youth. Although reviews that focus primarily on the mathematical development of the method have appeared in the literature, a systematic review of applications of the method is not available. An overview of the general types of applications of analytic elements in ground water modeling is provided in this paper. While not fully encompassing, the applications described here cover areas where the method has been historically applied (regional, two-dimensional steady-state models, analyses of ground water-surface water interaction, quick analyses and screening models, wellhead protection studies) as well as more recent applications (grid sensitivity analyses, estimating effective conductivity and dispersion in highly heterogeneous systems). The review of applications also illustrates areas where more method development is needed (three-dimensional and transient simulations).

Scale effects of hydrostratigraphy and recharge zonation on base flow.

Uncertainty regarding spatial variations of model parameters often results in the simplifying assumption that parameters are spatially uniform. However, spatial variability may be important in resource assessment and model calibration. In this paper, a methodology is presented for estimating a critical basin size, above which base flows appear to be relatively less sensitive to the spatial distribution of recharge and hydraulic conductivity, and below which base flows are relatively more sensitive to this spatial variability. Application of the method is illustrated for a watershed that exhibits distinct infiltration patterns and hydrostratigraphic layering. A ground water flow model (MODFLOW) and a parameter estimation code (UCODE) were used to evaluate the influence of recharge zonation and hydrostratigraphic layering on base flow distribution. Optimization after removing spatial recharge variability from the calibrated model altered base flow simulations up to 53% in watersheds smaller than 40 km(2). Merging six hydrostratigraphic units into one unit with average properties increased base flow residuals up to 83% in basins smaller than 50 km(2). Base flow residuals changed <5% in watersheds larger than 40 and 50 km(2) when recharge and hydrostratigraphy were simplified, respectively; thus, the critical basin size for the example area is approximately 40 to 50 km(2). Once identified for an area, a critical basin size could be used to guide the scale of future investigations. By ensuring that parameter discretization needed to capture base flow distribution is commensurate with the scope of the investigation, uncertainty caused by overextending uniform parameterization or by estimating extra parameter values is reduced.

Stepwise use of GFLOW and MODFLOW to determine relative importance of shallow and deep receptors.

A stepwise modeling approach is implemented in which a regional one-layer analytic element model is used to simulate the flow system and to furnish boundary conditions for an extracted local three-dimensional model. In this case study the stepwise approach is used to evaluate the fate of recharge in the Menomonee Valley adjacent to Lake Michigan. Two major receptors exist for recharge that flows through contaminated valley fill: the surface water estuary and a tunnel system constructed approximately 75 to 110 m below land surface to store storm runoff. The primary objective of the modeling is to delineate the contributing areas of recharge to each receptor. Of interest is the ability of the one-layer regional model to furnish flux boundary conditions to the local three-dimensional model despite the presence of vertical flow conditions at the boundaries of the local model. Sensitivity analysis suggests that the local model was insensitive to the vertical distribution of the flux. Each step of the modeling approach demonstrates that both receptors play an important role in capturing valley recharge. The pattern of capture of the one-layer model differed in shape from that delineated by the multi-layer local model in the presence of a flow system with pronounced vertical anisotropy and with sinks drawing water from different elevations.

Using high hydraulic conductivity nodes to simulate seepage lakes.

In a typical ground water flow model, lakes are represented by specified head nodes requiring that lake levels be known a priori. To remove this limitation, previous researchers assigned high hydraulic conductivity (K) values to nodes that represent a lake, under the assumption that the simulated head at the nodes in the high-K zone accurately reflects lake level. The solution should also produce a constant water level across the lake. We developed a model of a simple hypothetical ground water/lake system to test whether solutions using high-K lake nodes are sensitive to the value of K selected to represent the lake. Results show that the larger the contrast between the K of the aquifer and the K of the lake nodes, the smaller the error tolerance required for the solution to converge. For our test problem, a contrast of three orders of magnitude produced a head difference across the lake of 0.005 m under a regional gradient of the order of 10(-3) m/m, while a contrast of four orders of magnitude produced a head difference of 0.001 m. The high-K method was then used to simulate lake levels in Pretty Lake, Wisconsin. Results for both the hypothetical system and the application to Pretty Lake compared favorably with results using a lake package developed for MODFLOW (Merritt and Konikow 2000). While our results demonstrate that the high-K method accurately simulates lake levels, this method has more cumbersome postprocessing and longer run times than the same problem simulated using the lake package.

Improving a regional model using reduced complexity and parameter estimation.

The availability of powerful desktop computers and graphical user interfaces for ground water flow models makes possible the construction of ever more complex models. A proposed copper-zinc sulfide mine in northern Wisconsin offers a unique case in which the same hydrologic system has been modeled using a variety of techniques covering a wide range of sophistication and complexity. Early in the permitting process, simple numerical models were used to evaluate the necessary amount of water to be pumped from the mine, reductions in streamflow, and the drawdowns in the regional aquifer. More complex models have subsequently been used in an attempt to refine the predictions. Even after so much modeling effort, questions regarding the accuracy and reliability of the predictions remain. We have performed a new analysis of the proposed mine using the two-dimensional analytic element code GFLOW coupled with the nonlinear parameter estimation code UCODE. The new model is parsimonious, containing fewer than 10 parameters, and covers a region several times larger in areal extent than any of the previous models. The model demonstrates the suitability of analytic element codes for use with parameter estimation codes. The simplified model results are similar to the more complex models; predicted mine inflows and UCODE-derived 95% confidence intervals are consistent with the previous predictions. More important, the large areal extent of the model allowed us to examine hydrological features not included in the previous models, resulting in new insights about the effects that far-field boundary conditions can have on near-field model calibration and parameterization. In this case, the addition of surface water runoff into a lake in the headwaters of a stream while holding recharge constant moved a regional ground watershed divide and resulted in some of the added water being captured by the adjoining basin. Finally, a simple analytical solution was used to clarify the GFLOW model's prediction that, for a model that is properly calibrated for heads, regional drawdowns are relatively unaffected by the choice of aquifer properties, but that mine inflows are strongly affected. Paradoxically, by reducing model complexity, we have increased the understanding gained from the modeling effort.