Jessica L. Kozarek

Simulation-Based Approach for Stream Restoration Structure Design: Model Development and Validation

AbstractWe develop, validate, and demonstrate the potential of Virtual StreamLab (VSL3D), a novel three-dimensional hydromorphodynamics computational model capable of simulating turbulent flow and sediment transport in natural waterways with embedded and arbitrarily complex hydraulic structures under live-bed conditions. The numerical model is based on the curvilinear immersed boundary (CURVIB) approach and can solve the unsteady Reynolds-averaged Navier-Stokes (URANS) equations closed with the k−ω turbulence model in arbitrarily complex waterways with mobile sediment beds. Bed material transport is simulated by solving the nonequilibrium Exner equation for the bed surface elevation coupled with a transport equation for suspended load. Field-scale measurements obtained from experiments carried out in the St. Anthony Falls Laboratory Outdoor StreamLab are employed to validate the predictive capabilities of the numerical model. The VSL3D is used to develop a virtual testing environment of unprecedented reso...

Hydraulic Complexity Metrics for Evaluating In-Stream Brook Trout Habitat

A two-dimensional hydraulic model (River2D) was used to investigate the significance of flow complexity on habitat preferences of brook trout (Salvelinus fontinalis) in the high-gradient Staunton River in Shenandoah National Park, Virginia. Two 100-m reaches were modeled where detailed brook trout surveys (10–30-m resolution) have been conducted annually since 1997. Spatial hydraulic complexity metrics including area-weighted circulation and kinetic energy gradients (KEG) were calculated based on modeled velocity distributions. These metrics were compared to fish density in individual habitat complexes (10–30-m subreaches) to evaluate relationships between fish location and average flow complexity. In addition, the fish density was compared to additional habitat variables including percent cascade (CS), pool (PL) and riffle, and in-stream ( ISCN ) and riparian cover. There were negative correlations between modeled mean velocity (VEL) and maximum depth (MAXD) and fish density; however, there were no stati...

Terrestrial laser scanning for delineating in-stream boulders and quantifying habitat complexity measures

0099-1112/12/7804–363/

Sorption of estrogen to three agricultural soils from Virginia, USA

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Simulation-based optimization of in-stream structures design: J-hook vanes

Land-applied manures and grazing livestock are sources of estrogens to the environment. Natural steroid estrogens such as 17s-estradiol (E2) in low concentrations (ng L-1) can adversely affect the reproductive health of aquatic organisms. The goal of this research was to quantify the sorption of E2 to three agricultural soils from different physiographic regions in Virginia, a critical step in predicting transport of estrogens in runoff from agricultural fields. Batch equilibrium experiments were conducted with a range of E2 concentrations (50 to 2000 µg L-1) in a background solution of 5 mM calcium chloride and 100 mg L-1 sodium azide added to samples of Groseclose loam, Myatt sandy loam, and Cecil loam soils collected from the plow layer (0 to 15 cm) in addition to a Cecil soil sample from the Bt horizon. The concentration of E2 in the liquid phase was measured by gas chromatography/mass spectrometry (GC-MS) and was used to develop sorption isotherms for each soil. The time required to reach apparent equilibrium for all soils was less than 24 h. In general, the linear isotherm provided a good fit to model the sorption of E2 to agricultural soils from the plow layer (R2 > 0.9). The sorption of E2 to agricultural soil was correlated to the organic carbon content of each soil (Pearson coefficient, 0.79) with log Koc values ranging from 2.90 to 3.99.

Video observations of bed form morphodynamics in a meander bend

ABSTRACT J-hook vanes are geometrically complex rock structures that are used extensively in stream and river restoration. We employ the St Anthony Falls Laboratory Virtual StreamLab (VSL3D) code to elucidate the flow and transport phenomena induced by such structures in large rivers and develop design guidelines based on this physical understanding. The unsteady Reynolds averaged Navier–Stokes module of the VSL3D model with the k – ω closure is used to carry out coupled hydro-morphodynamic simulations in waterways with complex hydraulic structures. We construct two virtual river geometries, representative of gravel and sand-bed rivers in nature, and employ them for developing design guidelines for J-hook vanes. We systematically simulate numerous arrangements of J-hook vanes to understand physical mechanisms via which such structures modify turbulent flow and sediment transport processes depending on river environment and structure layout. The resulting physical insights are then distilled into a set of physics-based design guidelines for optimal structure design and placement in large rivers.

Environmental drivers of denitrification rates and denitrifying gene abundances in channels and riparian areas

A new optical remote sensing technique for estimating water depth from an oblique camera view is described. The water surface and the bed were imaged simultaneously to create time-dependent maps of the water surface velocities and the bed elevations that can be used to validate numerical models at high spatial and temporal resolution. The technique was applied in a sandy meander bend at the University of Minnesota Saint Anthony Falls Laboratory Outdoor StreamLab. The root mean square differences between optical estimates of the bed and in situ observations ranged between 0.01 and 0.03 m. Mean bed form wavelength was 0.73 m and mean crest height was 0.07 m, but both varied with distance around the meander bend. Bed form classification varied with distance downstream, and sinuosity of bed forms varied with local radius of curvature. Bed form roughness scaled similarly to other natural riverine environments although wavelength and height magnitude and variability were larger than predicted by empirical formulations for straight reaches. Bed form translation rate varied between 1 and 5 mm s−1. Estimates of velocity from particle image velocimetry (PIV) on the water surface were ∼10% higher than in situ observations collected ∼0.05 m below the water surface. Using the PIV observations to drive simple equations for bed load sediment flux, we explained up to 72% of the observed variance in downstream sediment flux. The new methodology described here provides nonintrusive, high spatial and temporal resolution measurements of both the bed and the flow.

Measurement and modeling of denitrification in sand-bed streams under various land uses

Intensive agriculture in the Midwestern United States contributes to excess nitrogen in surface water and groundwater, negatively affecting human health and aquatic ecosystems. Complete denitrification removes reactive nitrogen from aquatic environments and releases inert dinitrogen gas. We examined denitrification rates and the abundances of denitrifying genes and total bacteria at three sites in an agricultural watershed and in an experimental stream in Minnesota. Sampling was conducted along transects with a gradient from always inundated (in-channel), to periodically inundated, to non-inundated conditions to determine how denitrification rates and gene abundances varied from channels to riparian areas with different inundation histories. Results indicate a coupling between environmental parameters, gene abundances, and denitrification rates at the in-channel locations, and limited to no coupling at the periodically inundated and non-inundated locations, respectively. Nutrient-amended potential denitrification rates for the in-channel locations were significantly correlated (α = 0.05) with five of six measured denitrifying gene abundances, whereas the periodically inundated and non-inundated locations were each only significantly correlated with the abundance of one denitrifying gene. These results suggest that DNA-based analysis of denitrifying gene abundances alone cannot predict functional responses (denitrification potential), especially in studies with varying hydrologic regimes. A scaling analysis was performed to develop a predictive functional relationship relating environmental parameters to denitrification rates for in-channel locations. This method could be applied to other geographic and climatic regions to predict the occurrence of denitrification hot spots.

Increased denitrification rates associated with shifts in prokaryotic community composition caused by varying hydrologic connectivity

Although many studies have measured denitrification in stream sediments, few have utilized these data with local water column and sediment measurements to develop a predictive model for NO uptake. In this study, sediment denitrification was measured from cores in five streams under various land uses in south-central Minnesota using denitrification enzyme activity (DEA) assays and amplification of the gene via real-time, quantitative polymerase chain reaction. Hydraulic and environmental variables were measured in the vicinity of the sediment cores to evaluate the influence of fluid flow and chemical variables on denitrification activity. Potential denitrification rates measured using DEA assays ranged from 0.02 to 10.1 mg N m h, and the abundance of the denitrifier gene was positively correlated with these measurements ( = 0.79, < 0.001) for most of the streams studied. A predictive model to determine NO uptake via denitrification was derived, implementing dimensional analysis of variables that mediate denitrification in sand-bed streams. The proposed model explained 75% of the variability in DEA rates. The results of this study show that denitrification is most dependent on the distribution of sediment organic matter, interstitial pore space, and stream hydraulic characteristics, including shear velocity at the sediment-water interface and stream depth.

Simulation-based optimization of in-stream structures design: rock vanes

While modern developments in agriculture have allowed for increases in crop yields and rapid human population growth, they have also drastically altered biogeochemical cycles, including the biotransformation of nitrogen. Denitrification is a critical process performed by bacteria and fungi that removes nitrate in surface waters, thereby serving as a potential natural remediation strategy. We previously reported that constant inundation resulted in a coupling of denitrification gene abundances with denitrification rates in sediments, but these relationships were not maintained in periodically-inundated or non-inundated environments. In this study, we utilized Illumina next-generation sequencing to further evaluate how the microbial community responds to these hydrologic regimes and how this community is related to denitrification rates at three sites along a creek in an agricultural watershed over 2 years. The hydrologic connectivity of the sampling location had a significantly greater influence on the denitrification rate (P = 0.010), denitrification gene abundances (P < 0.001), and the prokaryotic community (P < 0.001), than did other spatiotemporal factors (e.g., creek sample site or sample month) within the same year. However, annual variability among denitrification rates was also observed (P < 0.001). Furthermore, the denitrification rate was significantly positively correlated with water nitrate concentration (Spearmans ρ = 0.56, P < 0.0001), denitrification gene abundances (ρ = 0.23–0.47, P ≤ 0.006), and the abundances of members of the families Burkholderiaceae, Anaerolinaceae, Microbacteriaceae, Acidimicrobineae incertae sedis, Cytophagaceae, and Hyphomicrobiaceae (ρ = 0.17–0.25, P ≤ 0.041). Prokaryotic community composition accounted for the least amount of variation in denitrification rates (22%), while the collective influence of spatiotemporal factors and gene abundances accounted for 37%, with 40% of the variation related to interactions among all parameters. Results of this study suggest that the hydrologic connectivity at each location had a greater effect on the prokaryotic community than did spatiotemporal differences, where inundation is associated with shifts favoring increased denitrification potential. We further establish that while complex interactions among the prokaryotic community influence denitrification, the link between hydrologic connectivity, microbial community composition, and genetic potential for biogeochemical cycling is a promising avenue to explore hydrologic remediation strategies such as periodic flooding.