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Fecal indicator organisms (FIOs), such as Escherichia coli and enterococci, are often used as surrogates of contamination in the context of beach management; however, bacteriophages may be more reliable indicators than FIO due to their similarity to viral pathogens in terms of size and persistence in the environment. In the past, mechanistic modeling of environmental contamination has focused on FIOs, with virus and bacteriophage modeling efforts remaining limited. In this paper, we describe the development and application of a fate and transport model of somatic and F-specific coliphages for the Washington Park beach in Lake Michigan, which is affected by riverine outputs from the nearby Trail Creek. A three-dimensional model of coliphage transport and photoinactivation was tested and compared with a previously reported E. coli fate and transport model. The light-based inactivation of the phages was modeled using organism-specific action spectra. Results indicate that the coliphage models outperformed the E. coli model in terms of reliably predicting observed E. coli/coliphage concentrations at the beach. This is possibly due to the presence of additional E. coli sources that were not accounted for in the modeling. The coliphage models can be used to test hypotheses about potential sources and their behavior and for predictive modeling.

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter-elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network-Daily (GHCN-D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN-D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN-D based SWAT-simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge-based measurements can improve hydrologic model performance, especially for extreme events.

We present results of a multiyear study of the Everglades (Florida, USA) detailing how differences in environmental variables can alter mercury concentrations in the food web. About 1000 random locations throughout the freshwater Everglades marsh have been sampled for the United States Environmental Protection Agency's Everglades Regional Environmental Monitoring and Assessment Program (“REMAP”) since 1995. REMAP sampling is synoptic and multimedia, including an abundant prey fish (eastern mosquitofish, Gambusia holbrooki) as an indicator of mercury bioaccumulation. Amplifying an approach we reported to Everglades National Park, we used Generalized Boosted Models on the REMAP data to estimate how much of the mercury concentration in mosquitofish could be explained by water quality constituents or indicators of ecological health (covariates). The resulting model accounts for 60% of the environmental influence on variation in mosquitofish mercury, a robust outcome for a large, disturbed ecosystem such as the Everglades, given its seasonal, annual, and spatial differences. Of the eight most influential covariates, two were methyl mercury in periphyton and water, two can be indicators of trophic state (alkaline phosphatase and chlorophyll-a), one can be a marker of stormwater transport (conductivity), and two can be enablers of mercury methylation (sulfate in soil and water). While these covariates had an average individual influence ranging from 4.0% to 10.1%, together they accounted for 52.2% of the total relative influence. Water with low phosphorus, but with sulfur and carbon above background, moved into the less disturbed parts of the Everglades via modifications to the existing water management system, could increase mercury bioaccumulation in those parts of the marsh.

Coliphages can indicate contamination of recreational waters and previous studies show that sunlight is important in altering densities of coliphages, other indicator microorganisms, and pathogens in aquatic environments. Here, we report on laboratory studies of light-induced inactivation of two coliphage groups-male-specific (F+) and somatic coliphage-under various conditions in phosphate-buffered water (PBW). Strains isolated from wastewater treatment facilities and laboratory strains (MS2 and phiX174 coliphages) were evaluated. Inactivation rates were determined in a series of irradiations using simulated solar radiation passed through light filters that blocked different parts of the ultraviolet spectral region. Inactivation rates and spectral irradiance from these experiments were then analyzed to develop biological weighting functions (BWFs) for the light-induced inactivation. BWFs were used to model the inactivation of coliphages over a range of conditions in aquatic environments that included two beach sites in Lake Michigan and one in Lake Erie. For example, modeled effects of sunlight attenuation, using UV absorption data from the three Great Lakes beach sites, inferred that direct photoinactivation rate constants, averaged over a one-meter water column in swimmable areas, were reduced 2- to 5-fold, compared to near-surface rate constants.

Regional fishery conditions of Mid-Atlantic wadeable streams in the eastern United States are estimated using the Bioaccumulation and Aquatic System Simulator (BASS) bioaccumulation and fish community model and data collected by the US Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP). Average annual biomasses and population densities and annual productions are estimated for 352 randomly selected streams. Realized bioaccumulation factors (BAF) and biomagnification factors (BMF), which are dependent on these forecasted biomasses, population densities, and productions, are also estimated by assuming constant water exposures to methylmercury and tetra-, penta-, hexa-, and hepta-chlorinated biphenyls. Using observed biomasses, observed densities, and estimated annual productions of total fish from 3 regions assumed to support healthy fisheries as benchmarks (eastern Tennessee and Catskill Mountain trout streams and Ozark Mountains smallmouth bass streams), 58% of the region's wadeable streams are estimated to be in marginal or poor condition (i.e., not healthy). Using simulated BAFs and EMAP Hg fish concentrations, we also estimate that approximately 24% of the game fish and subsistence fishing species that are found in streams having detectable Hg concentrations would exceed an acceptable human consumption criterion of 0.185 μg/g wet wt. Importantly, such streams have been estimated to represent 78.2% to 84.4% of the Mid-Atlantic's wadeable stream lengths. Our results demonstrate how a dynamic simulation model can support regional assessment and trends analysis for fisheries. Integr Environ Assess Manag 2015;X:000–000. Published 2015 SETAC. This article is a US Government work and, as such, is in the public domain in the United States.

Four seasonal rainfall simulations in 2009 and 2010 were applied to a field containing 36 plots (0.75 × 2 m each), resulting in 144 runoff events. In all simulations, a constant rate of rainfall was applied then halted 60 min after initiation of runoff, with plot-scale monitoring of runoff every 5 min during that period. Runoff was simulated with the Kinematic Runoff and Erosion/Simulator of Transport with Infiltration and Runoff (KINEROS2/STWIR) field-scale model, whose hydrodynamics are based on the kinematic wave equation. Because of the non-linear nature of the model and a highly parameterized model with respect to the available data, several approaches were investigated to upscale nine runoff-related parameters from a series of small monitored plots to the field scale. Inverse modeling was performed using the model-independent Parameter ESTimation (PEST) algorithm to individually calibrate the nine KINEROS2/STWIR parameters on 36 plots. The parameters were averaged, and bootstrapping was used to assess uncertainty of the parameters via estimation of confidence intervals (CI). A Monte Carlo simulation using the bootstrap results showed reasonable field-scale representation of flow rates. Median values of calibrated parameters were within the 95% CI obtained with bootstrapping. The simulated results for the median values associated with the 90% CI flow rates produced similar trends as those exhibited with the observed data, suggesting that median values of the calibrated parameters from the PEST inverse modeling could be used to represent the field scale. Copyright © 2013 John Wiley & Sons, Ltd.

A series of simulated rainfall-runoff experiments with applications of different manure types (cattle solid pats, poultry dry litter, swine slurry) was conducted across four seasons on a field containing 36 plots (0.75 × 2 m each), resulting in 144 rainfall-runoff events. Simulating time-varying release of Escherichia coli, enterococci, and fecal coliforms from manures applied at typical agronomic rates evaluated the efficacy of the Bradford–Schijven model modified by adding terms for release efficiency and transportation loss. Two complementary, parallel approaches were used to calibrate the model and estimate microbial release parameters. The first was a four-step sequential procedure using the inverse model PEST, which provides appropriate initial parameter values. The second utilized a PEST/bootstrap procedure to estimate average parameters across plots, manure age, and microbe, and to provide parameter distributions. The experiment determined that manure age, microbe, and season had no clear relationship to the release curve. Cattle solid pats released microbes at a different, slower rate than did poultry dry litter or swine slurry, which had very similar release patterns. These findings were consistent with other published results for both bench- and field-scale, suggesting the modified Bradford–Schijven model can be applied to microbial release from manure.

The U.S. Environmental Protection Agency uses environmental models to inform rulemaking and policy decisions at multiple spatial and temporal scales. As decision-making has moved towards integrated thinking and assessment (e.g. media, site, region, services), the increasing complexity and interdisciplinary nature of modern environmental problems has necessitated a new generation of integrated modeling technologies. Environmental modelers are now faced with the challenge of determining how data from manifold sources, types of process-based and empirical models, and hardware/software computing infrastructure can be reliably integrated and applied to protect human health and the environment. In this study, we demonstrate an Integrated Modeling Framework that allows us to predict the state of freshwater ecosystem services within and across the Albemarle-Pamlico Watershed, North Carolina and Virginia (USA). The Framework consists of three facilitating technologies: Data for Environmental Modeling automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation is a hardware and software parallel-computing interface with pre/post-processing analysis tools, including parameter estimation, uncertainty and sensitivity analysis. In this application, five environmental models are linked within the Framework to provide multimedia simulation capabilities: the Soil Water Assessment Tool predicts watershed runoff; the Watershed Mercury Model simulates mercury runoff and loading to streams; the Water quality Analysis and Simulation Program predicts water quality within the stream channel; the Habitat Suitability Index model predicts physicochemical habitat quality for individual fish species; and the Bioaccumulation and Aquatic System Simulator predicts fish growth and production, as well as exposure and bioaccumulation of toxic substances (e.g., mercury). Using this Framework, we present a baseline assessment of two freshwater ecosystem services–water quality and fisheries resources–in headwater streams throughout the Albemarle-Pamlico. A stratified random sample of 50 headwater streams is used to draw inferences about the target population of headwater streams across the region. Input data is developed for a twenty-year baseline simulation in each sampled stream using current land use and climate conditions. Monte Carlo sampling ( n = 100 iterations per stream) is also used to demonstrate some of the Framework's experimental design and data analysis features. To evaluate model performance and accuracy, we compare initial (i.e., uncalibrated) model predictions (water temperature, dissolved oxygen, fish density, and methylmercury concentration within fish tissue) against empirical field data. Finally, we ‘roll-up’ the results from individual streams, to assess freshwater ecosystem services at the regional scale.

Management of aquatic resources requires meaningful assessment endpoints on which to base decisions. In freshwater streams, assessment endpoints are often defined as fish communities. Given the limited resources available for environmental monitoring, having a means of predicting fish assemblages in streams where no sampling has yet occurred would be useful. Such a tool could be used for regional screening-level analyses of fish communities and could be input into local-scale model applications for evaluating management scenarios of stream degradation or restoration. In this study, a set of fish assemblages (a list of fish species and their corresponding relative abundances) representative of different stream types in the Mid-Atlantic Highlands region of the United States was defined by use of a k-means cluster analysis performed on relative abundance estimates. The cluster analysis produced 18 fish assemblages, and the following 14 species had the greatest relative abundance in at least one of t...

Prey supply to predators is limited by the morphology, behavior, and spatial distributions of both predator and prey. To be eaten, prey must co-occur spatially and temporally with the predator (distribution), the predator must recognize the prey as potential food and successfully capture it (behavior), and the predator must have a mouth large enough to ingest its target (morphology). We quantified the cumulative effect of these three factors on clupeid prey availability to both largemouth bass Micropterus salmoides and striped bass Morone saxatilis in Smith Mountain Lake, Virginia. As expected, morphological constraints were more severe for small predators. Alewives Alosa pseudoharengus were morphologically more available than gizzard shad Dorosoma cepedianum. Incongruent spatial distributions, the result of lake stratification, prevented striped bass from feeding on gizzard shad during summer and limited largemouth bass consumption of alewives. For unknown behavioral reasons, largemouth bass and...

Exposure to feces in two watersheds with different management histories was assessed by tracking cattle feces bacterial populations using multiple host-specific PCR assays. In addition, environmental factors affecting the occurrence of these markers were identified. Each assay was performed using DNA extracts from water and sediment samples collected from a watershed directly impacted by cattle fecal pollution (WS1) and from a watershed impacted only through runoff (WS2). In WS1, the ruminant-specific Bacteroidales 16S rRNA gene marker CF128F was detected in 65% of the water samples, while the non-16S rRNA gene markers Bac1, Bac2, and Bac5 were found in 32 to 37% of the water samples. In contrast, all source-specific markers were detected in less than 6% of the water samples from WS2. Binary logistic regressions (BLRs) revealed that the occurrence of Bac32F and CF128F was significantly correlated with season as a temporal factor and watershed as a site factor. BLRs also indicated that the dynamics of fecal-source-tracking markers correlated with the density of a traditional fecal indicator ( P < 0.001). Overall, our results suggest that a combination of 16S rRNA gene and non-16S rRNA gene markers provides a higher level of confidence for tracking unknown sources of fecal pollution in environmental samples. This study also provided practical insights for implementation of microbial source-tracking practices to determine sources of fecal pollution and the influence of environmental variables on the occurrence of source-specific markers.