Christopher D. Knightes

Review: Hydrologic connectivity between geographically isolated wetlands and surface water systems: A review of select modeling methods

Geographically isolated wetlands (GIW), depressional landscape features entirely surrounded by upland areas, provide a wide range of ecological functions and ecosystem services for human well-being. Current and future ecosystem management and decision-making rely on a solid scientific understanding of how hydrologic processes affect these important GIW services and functions, and in turn on how GIWs affect downstream surface water systems. Consequently, quantifying the hydrologic connectivity of GIWs to other surface water systems (including streams, rivers, lakes, and other navigable waters) and the processes governing hydrologic connectivity of GIWs at a variety of watershed scales has become an important topic for the scientific and decision-making communities. We review examples of potential mechanistic modeling tools that could be applied to further advance scientific understanding concerning: (1) The extent to which hydrologic connections between GIWs and other surface waters exist, and (2) How these connections affect downstream hydrology at the scale of watersheds. Different modeling approaches involve a variety of domain and process conceptualizations, and numerical approximations for GIW-related questions. We describe select models that require only limited modifications to model the interaction of GIWs and other surface waters. We suggest that coupled surface-subsurface approaches exhibit the most promise for characterizing GIW connectivity under a variety of flow conditions, though we note their complexity and the high level of modeling expertise required to produce reasonable results. We also highlight empirical techniques that will inform mechanistic models that estimate hydrologic connectivity of GIWs for research, policy, and management purposes. Developments in the related disciplines of remote sensing, hillslope and wetland hydrology, empirical modeling, and tracer studies will assist in advancing current mechanistic modeling approaches to most accurately elucidate connectivity of GIWs to other surface waters and the effects of GIWs on downstream systems at the watershed scale. Hydrologic connectivity of isolated wetlands is an emerging focus for research.We review models for simulating hydrologic connectivity of isolated wetlands.Model selection for connectivity research depends upon location and model structure.Coupled surface water-groundwater models are complex yet often appropriate.Watershed and groundwater models are appropriate for specific flow regimes.

Application of ecosystem‐scale fate and bioaccumulation models to predict fish mercury response times to changes in atmospheric deposition

Management strategies for controlling anthropogenic mercury emissions require understanding how ecosystems will respond to changes in atmospheric mercury deposition. Process-based mathematical models are valuable tools for informing such decisions, because measurement data often are sparse and cannot be extrapolated to investigate the environmental impacts of different policy options. Here, we bring together previously developed and evaluated modeling frameworks for watersheds, water bodies, and food web bioaccumulation of mercury. We use these models to investigate the timescales required for mercury levels in predatory fish to change in response to altered mercury inputs. We model declines in water, sediment, and fish mercury concentrations across five ecosystems spanning a range of physical and biological conditions, including a farm pond, a seepage lake, a stratified lake, a drainage lake, and a coastal plain river. Results illustrate that temporal lags are longest for watershed-dominated systems (like the coastal plain river) and shortest for shallow water bodies (like the seepage lake) that receive most of their mercury from deposition directly to the water surface. All ecosystems showed responses in two phases: A relatively rapid initial decline in mercury concentrations (20-60% of steady-state values) over one to three decades, followed by a slower descent lasting for decades to centuries. Response times are variable across ecosystem types and are highly affected by sediment burial rates and active layer depths in systems not dominated by watershed inputs. Additional research concerning watershed processes driving mercury dynamics and empirical data regarding sediment dynamics in freshwater bodies are critical for improving the predictive capability of process-based mercury models used to inform regulatory decisions.

Sources of Mercury Exposure for U.S. Seafood Consumers: Implications for Policy

Background Recent policies attempting to reduce adverse effects of methylmercury exposure from fish consumption in the United States have targeted reductions in anthropogenic emissions from U.S. sources. Objectives To analyze the prospects for future North American and international emissions controls, we assessed the potential contributions of anthropogenic, historical, and natural mercury to exposure trajectories in the U.S. population over a 40-year time horizon. Methods We used models that simulate global atmospheric chemistry (GEOS-Chem); the fate, transport, and bioaccumulation of mercury in four types of freshwater ecosystems; and mercury cycling among different ocean basins. We considered effects on mercury exposures in the U.S. population based on dietary survey information and consumption data from the sale of commercial market fish. Results Although North American emissions controls may reduce mercury exposure by up to 50% for certain highly exposed groups such as indigenous peoples in the Northeast, the potential effects of emissions controls on populations consuming marine fish from the commercial market are less certain because of limited measurements. Conclusions Despite uncertainties in the exposure pathway, results indicate that a combination of North American and international emissions controls with adaptation strategies is necessary to manage methylmercury risks across various demographic groups in the United States.

Statistical Analysis of Nonlinear Parameter Estimation for Monod Biodegradation Kinetics Using Bivariate Data

A nonlinear regression technique for estimating the Monod parameters describing biodegradation kinetics is presented and analyzed. Two model data sets were taken from a study of aerobic biodegradation of the polycyclic aromatic hydrocarbons (PAHs), naphthalene and 2-methylnaphthalene, as the growth-limiting substrates, where substrate and biomass concentrations were measured with time. For each PAH, the parameters estimated were: q(max), the maximum substrate utilization rate per unit biomass; K(S), the half-saturation coefficient; and Y, the stoichiometric yield coefficient. Estimating parameters when measurements have been made for two variables with different error structures requires a technique more rigorous than least squares regression. An optimization function is derived from the maximumlikelihood equation assuming an unknown, nondiagonal covariance matrix for the measured variables. Because the derivation is based on an assumption of normally distributed errors in the observations, the error structures of the regression variables were examined. Through residual analysis, the errors in the substrate concentration data were found to be distributed log-normally, demonstrating a need for log transformation of this variable. The covariance between ln C and X was found to be small but significantly nonzero at the 67% confidence level for NPH and at the 94% confidence level for 2MN. The nonlinear parameter estimation yielded unique values for q(max), K(S), and Y for naphthalene. Thus, despite the low concentrations of this sparingly soluble compound, the data contained sufficient information for parameter estimation. For 2-methylnaphthalene, the values of q(max) and K(S) could not be estimated uniquely; however, q(max)/K(S) was estimated. To assess the value of including the relatively imprecise biomass concentration data, the results from the bivariate method were compared with a univariate method using only the substrate concentration data. The results demonstrated that the bivariate data yielded a better confidence in the estimates and provided additional information about the model fit and model adequacy. The combination of the value of the bivariate data set and their nonzero covariance justifies the need for maximum likelihood estimation over the simpler nonlinear least squares regression.

Development and test application of a screening-level mercury fate model and tool for evaluating wildlife exposure risk for surface waters with mercury-contaminated sediments (SERAFM)

Complex chemical cycling of mercury in aquatic ecosystems means that tracing the linkage between anthropogenic and natural loadings of mercury to watersheds and water bodies and associated concentrations in the environment are difficult to establish without the assistance of numerical models that describe biogeochemical controls on mercury distribution and availability to organisms. This paper presents an overview of a process-based, steady-state model developed for state and water quality managers and scientists to assist in ecological risk assessments for mercury in aquatic environments. SERAFM (Spreadsheet-based Ecological Risk Assessment for the Fate of Mercury) incorporates the chemical, physical, and biological processes governing mercury transport and fate in a surface water including atmospheric deposition, watershed transport and transformation, solid transport and cycling within the water body, and water body mercury processes. This modelling framework was designed to assist risk assessors in evaluating wildlife risk at the screening-level for an aquatic ecosystem with mercury-contaminated sediments. An example application of the model that is used to inform a regional risk assessment is presented in this manuscript. In the example provided, hazard quotients for exposed wildlife and humans are calculated by the model for three scenarios: historical case of mercury-contaminated sediments, required clean-up levels to protect the most sensitive species, and background conditions. The spreadsheet structure of SERAFM permits dismantling and reassembling of specific sub-modules, while maintaining transparency to permit flexibility in use and application.

Aqueous phase biodegradation kinetics of 10 PAH compounds

Biodegradation kinetics were individually studied for 10 polycyclic aromatic hydrocarbons (PAHs): naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 2-ethylnaphthalene, acenaphthene, fluorene, ...

Multisubstrate biodegradation kinetics for binary and complex mixtures of polycyclic aromatic hydrocarbons

Biodegradation kinetics were studied for binary and complex mixtures of nine polycyclic aromatic hydrocarbons (PAHs): Naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 2-ethylnaphthalene, phenanthrene, anthracene, pyrene, fluorene, and fluoranthene. Discrepancies between the observed biodegradation rates and those predicted by a sole-substrate model indicate that significant substrate interactions occurred in both the binary and complex-mixture experiments. For all compounds except naphthalene, biodegradation was enhanced. The observations were compared to predictions from two multisubstrate biodegradation kinetic models: One that accounts for competitive inhibition, and one that does not. Both models are fully predictive in that parameters had been determined from an independent set of sole-substrate experiments. In the binary experiments, the major multisubstrate effect was biomass enhancement as a result of growth on naphthalene. Substrate interactions were orders of magnitude larger for most compounds in the complex mixtures, but significant competitive inhibition effects counteracted some of the biomass enhancement effect. The present study has demonstrated that the sole-substrate model is inadequate to describe multisubstrate biodegradation kinetics for a broad range of PAH mixtures. Whereas the multisubstrate model without inhibition did an adequate job of predicting the observed effects in some cases, we advocate the use of the multisubstrate model with inhibition for similar modeling efforts in light of the evidence that the model was correct more often than not. Theory supports its use because of the common enzyme pathways for biodegradation of PAHs.

Multicomponent NAPL Solidification Thermodynamics

Nonaqueous phase liquid (NAPL) contaminants that are chemical mixtures often contain compounds that are solids in their pure states. In the environment, weathering processes cause shifts in multicomponent NAPL composition, thereby enriching the NAPL in the less soluble compounds which may result in their eventual solidification. In this paper, we review the thermodynamic theory governing solid–liquid phase equilibria for the multicomponent NAPLs, and we present experimental observations of such phase equilibria for binary, ternary, and quaternary mixtures of polycyclic aromatic hydrocarbons (PAHs). If the NAPL phase behaves as an ideal solution and if the solid precipitate is pure, then a compounds mole fraction solubility limit in the NAPL phase equals its solid–liquid reference fugacity ratio. This value is a constant at the temperature of the system. If the NAPL phase is a non‐ideal solvent or if the solid is a solid solution, prediction of NAPL solidification in the environment is considerably more difficult. Experimental results indicate that for compounds such as naphthalene and acenaphthene, the solid–liquid reference fugacity ratio serves as a good indicator of the solubility limits in the NAPL phase. For phenanthrene, the solids that form when this compound exceeds its solubility limit are solid solutions that consistently include large portions of 2‐methylnaphthalene. These results suggest that the independent behavior implied by ideal solubility theory may not be an accurate descriptor of NAPL solidification phenomena for all PAH‐containing NAPLs.

Urban Stream Burial Increases Watershed-Scale Nitrate Export.

Nitrogen (N) uptake in streams is an important ecosystem service that reduces nutrient loading to downstream ecosystems. Here we synthesize studies that investigated the effects of urban stream burial on N-uptake in two metropolitan areas and use simulation modeling to scale our measurements to the broader watershed scale. We report that nitrate travels on average 18 times farther downstream in buried than in open streams before being removed from the water column, indicating that burial substantially reduces N uptake in streams. Simulation modeling suggests that as burial expands throughout a river network, N uptake rates increase in the remaining open reaches which somewhat offsets reduced N uptake in buried reaches. This is particularly true at low levels of stream burial. At higher levels of stream burial, however, open reaches become rare and cumulative N uptake across all open reaches in the watershed rapidly declines. As a result, watershed-scale N export increases slowly at low levels of stream burial, after which increases in export become more pronounced. Stream burial in the lower, more urbanized portions of the watershed had a greater effect on N export than an equivalent amount of stream burial in the upper watershed. We suggest that stream daylighting (i.e., uncovering buried streams) can increase watershed-scale N retention.

Simulated watershed mercury and nitrate flux responses to multiple land cover conversion scenarios

Water quality and toxic exposure science is transitioning towards analysis of multiple stressors rather than one particular environmental concern (e.g., mercury) or a group of similarly reacting chemicals (e.g., nutrients). However, two of the most important water quality constituents affecting both human and ecosystem health today, reactive nitrogen (N(r) ) and methylmercury (MeHg), are often assessed separately for their independent effects on water quality. With the continued pressure of landscape modifications on water quality, a challenge remains in understanding the concurrent watershed flux response of both N(r) and MeHg to such physical stressors, particularly at the spatial scale (regional watersheds) and within the mixed land cover type systems that most decision-making processes are conducted. We simulate the annual average and monthly flux responses of Hg (MeHg and total mercury [HgT]), NO(3) -N, and runoff to four land cover change scenarios in the Haw River Watershed (NC, USA), a headwater system in the Cape Fear River Basin. Fluxes are simulated using a process-based, spatially explicit watershed Grid-Based Mercury Model (GBMM) and a NO(3) -N watershed flux model we developed to link to GBMM. Results suggest that annual NO(3) -N and Hg fluxes increase and decrease concomitantly to land cover change; however, the magnitude of the changes in NO(3) -N, MeHg, HgT, and water fluxes vary considerably between different land cover conversion scenarios. Converting pasture land to a suburbanized landscape elicited the greatest increase in runoff and MeHg, HgT, and NO(3) -N fluxes among all four conversion scenarios. Our findings provide insight for multi-stressor ecological exposure research and management of coastal eutrophication resulting from elevated N(r) loadings and exposure risk due to elevated concentrations of MeHg in fish tissue.