Environmental Science & Technology
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Item Evaluation of the effects of wetland restoration design on hydraulic residence time and nutrient retention(2009) Strano, Stephen; Felton, Gary K; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Hydraulic residence time (HRT) is a critical factor that can be integrated into wetland restoration designs to promote nutrient retention, but HRT in the context of wetlands with storm-driven hydrology is not well understood. A model for nutrient retention optimization based on HRT was evaluated using three indicators of HRT and nutrient stocks in above-ground plant biomass. Results indicated that a commonly used indicator of HRT, the ratio of wetland to watershed area, may be insufficient, while nominal HRT provided an overestimate for wetlands receiving storm runoff. While there was little relationship between total nitrogen and HRT, results suggested that HRT may explain some variation in total phosphorus. Results also indicated that the studied wetland restorations were not designed to provide sufficient HRT to promote the retention of dissolved nutrients, and that staged outlets could be used to provide significant HRT's for a range of storm events.Item Modeling Approaches for Treatment Wetlands(2009) Carleton, James N.; Montas, Hubert J; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Although treatment wetlands can reduce pollutant loads, reliably predicting their performance remains a challenge because removal processes are often complex, spatially heterogeneous, and incompletely understood. Although initially popular for characterizing wetland performance, plug flow reactor models are problematic because their parameters exhibit correlation with hydraulic loading. One-dimensional advective-dispersive-reactive (ADE) models are also inadequate because longitudinal dispersion in wetlands is often non-Fickian as a result of steep velocity gradients. Models that make use of residence time distributions have shown promise in improving performance characterization, particularly when interdependencies of stream-tube scale velocities and reaction rate coefficients are considered (the "DND" approach). However this approach is limited to steady-state conditions, and to an assumption that transverse mixing is nil. This dissertation investigates three aspects of wetland modeling and is organized in a journal paper format. The first paper describes development of a DND model which accommodates non-steady-state conditions. The model processes flow and inlet concentration time series, and calculates as output effluent concentration time series. A version of the code allows optimization of model parameters by minimization of summed squared deviations between predicted and measured effluent concentrations. In example comparisons, model results compare favorably with measured data. The second paper develops an analytical solution to a two-dimensional advective-dispersive-reactive equation, in which all flux terms are expressed as power functions of the transverse dimension. For uniform inlet concentration this idealized heterogeneity model is similar to a DND model, but with the inclusion of transverse diffusion. An example is used to illustrate the beneficial impact that transverse mixing has on reactor performance. The third paper describes development of a model based upon a stochastic interpretation of the ADE. The solution technique that is employed results in a bicontinuum model that for steady-state conditions becomes a weighted sum of two exponential decline functions. For low and intermediate degrees of mixing, model results nicely match those of the corresponding idealized heterogeneity model, and for high mixing they match results of the corresponding one-dimensional ADE. Comparisons against data suggest the bicontinuum model may represent wetland performance better than the DND model in some but not all cases.Item Pedogenesis in Rain Gardens: The Role of Earthworms and Other Organisms in Long-Term Soil Development(2009) Ayers, Emily Mitchell; Kangas, Patrick; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As bioretention comes into widespread use, it has become increasingly important to understand the development of bioretention soils over time. The objective of this research is to investigate the development of bioretention soils and the importance of ecological processes in the performance of rain gardens. The research includes descriptive studies of pre-existing rain garden soil profiles, laboratory experiments quantifying the effect of earthworms on infiltration rates, and a simulation model describing the influence of earthworms and soil organic matter on infiltration. Surveys of several different rain gardens of various ages provide the first detailed descriptions of rain garden soil profiles. The study revealed a great deal of biological activity in rain gardens, and evidence of pedogenesis even in very young sites. The uppermost soil layers were found to be enriched with organic matter, plant roots, and soil organisms. The field sites surveyed showed no signs of clogging due to the trapping of suspended solids carried in stormwater runoff. Some evidence was found of higher than expected infiltration rates at the field sites, which may be attributable to the effects of bioturbation by living organisms. The ability of earthworms to mitigate the effects of trapped suspended solids on bioretention soils was assessed in the laboratory. Results show that earthworms are capable of maintaining the infiltration rate of bioretention soils, but that their effects have a high degree of variability. This variability is attributed to soil aggregate instability caused by the oversimplification of the ecosystem. Other organisms play a significant role in stabilizing earthworm burrows and casts, and may be essential ingredients in a self-maintaining bioretention ecosystem. A simulation model of the action of earthworms on soil infiltration rates was developed in order to illustrate the physical processes taking place as a result of earthworm activity. The model was calibrated using data from the field study and microcosm experiment. This research is intended to provide a first glimpse into the biological processes at work in rain garden soils. The research shows that soil organisms are present in rain gardens, and suggests that their impact on bioretention performance may be significant.Item Use of Macroinvertebrate Predictive Models to Evaluate Stream Restoration Effect(2008-09-03) Tsang, Yin-Phan; Felton, Gary K; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Multivariate analysis was used to build macroinvertebrate predictive models for stream assessment in Britain, Australia, and the west coast of the United States. The philosophy behind these predictive models was similar, but variations exist and have been adapted for different regions. The macroinvertebrate predictive model in Maryland has been improved using Region-style models, including the Assessment by Nearest Neighbour Analysis (ANNA), the Burn's Region of Influence (BROI), and the New Datum Region of Influence (NROI) predictive schemes. For better prediction precision, different parameter selection methods (stepwise AIC, exhaustive AIC, and exhaustive BIC) and rational multiple regression function checking have been used to prevent overfitting. Root mean squared error (RMSE) was used to select the final best model. The calibration results from the Region-Style models are better than those from previously built River InVertebrate Prediction And Classification System (RIVPACS)-style model. The different parameter selection criteria along with rational regression function checking discourage overfitting and improve the prediction results. Region-style methods can be alternative methods for building predictive model. GISHydro2000 is a GIS-based program for performing hydrologic analysis in Maryland. This tool was used to determine numerous hydrologic characteristics as potential predictors to be used in the macroinvertebrate predictive model. The best performing ANNA, BROI, and NROI predictive models can be automated in the GISHydro2000 environment. Theses multivariate analyses (i.e., Observed/Expected (O/E) scores), as well as multimetric analysis (i.e., Benthic Index of Biotic Integrity (IBI) metrics), were applied to evaluate the stream restoration sites in Montgomery County, Maryland. The evaluation results show most stream habitat conditions were still degraded after stream restoration projects. The environmental stressors at the stream site were not immediately alleviated by the restoration design, or the stressors overshadowed the restoration efforts. At many sites, the stream condition starts to recover at the 3rd- or 4th- year post-restoration. More time may be needed for monitoring the recovery of stream ecosystems. The benthic IBI metrics response to not only environmental stressor, but also other natural variances. The results suggested that O/E scores from multivariate analysis provides valuable supplemental information for evaluating stream health.Item Evaluation of SWAT Model Applicability for Waterbody Impairment Identification and TMDL Analysis(2007-10-30) Sexton, Aisha M; Shirmohammadi, Adel; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The U.S. EPA's Total Maximum Daily Load (TMDL) program has encountered hindrances in its implementation partly because of its strong dependence on mathematical models to set limitations on the release of impairing substances. The uncertainty associated with predictions of such models is often not formally quantified and typically assigned as an arbitrary safety factor to the margin of safety (MOS) portion of TMDL allocations. AVSWAT-X, a semi-distributed, watershed-scale model, was evaluated to determine its applicability to identify the impairment status and tabulate a nutrient TMDL for a waterbody located in the Piedmont physiographic region of Maryland. The methodology for tabulating the nutrient TMDL is an enhancement over current methods used in Maryland. The mean-value first-order reliability method (MFORM) was used to calculate variance in output variables with respect to input parameter variance and the MOS value was derived based on the level confidence in meeting the water quality standard. A calibration, validation and an uncertainty analysis was conducted on the AVSWAT-X model. Monthly results indicated that AVSWAT-X is a good predictor of streamflow, a moderate (at best) predictor of nutrient loading and a poor predictor of sediment loading. Improved performance was observed on an annual basis for nitrate and sediment loadings, indicating the most appropriate use of SWAT for long-term simulations. The most pronounced reason for discrepancies in model performance was the use of the SCS curve number method to tabulate surface runoff. Uncertainty results indicated that input parameters that are highly sensitive may not necessarily contribute the largest amount of uncertainty to model output. The largest amount of variance in output variables occurred during wet periods. Predicted sediment output had the largest amount of variability around its mean, followed by nitrate, phosphate, and streamflow as indicated by average annual coefficients of variation of 28%, 19%, 17%, and 15%, respectively. The methodology used in this study to quantify the nitrate TMDL and the MOS associated with it, was a useful tool and an improvement over current methods of nutrient TMDL analysis in Maryland. Overall, AVSWAT-X is a moderate to good model for estimating waterbody impairment and conducting TMDL analysis of waterbodies impaired by nutrients.Item Ecologically Inspired Design of Green Roof Retrofit(2007-08-13) Schumann, Laura Marie; Tilley, David R; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Green roofs are becoming popular in the United States for their runoff and energy reduction abilities. However, current designs have high installation costs, heavy load-bearing requirements, and restrictions to low-sloped roofs. We designed a novel retrofit technology, the green cloak, which uses fast-growing vine species and a trellis to suspend vegetation above a roof. We conducted field experiments, prototype testing, and mathematical modeling to determine the effect of the green cloak on stormwater runoff and indoor summertime building temperature reduction. We assessed energy and monetary cost-benefits. The green cloak reduced July indoor building temperature by 11.3°C which saved 73% of cooling energy costs. The green cloak delayed the peak storm runoff from a 0.15mm/min storm by 100 minutes. The green cloak costs 38% less than a green roof. The green cloak demonstrated great potential for mitigating runoff impacts of impervious surfaces, reducing summer temperatures of buildings, and creating urban greenery.Item Evaluation of the Effects of Bioaugmentation and Biostimulation on Natural Attenuation and Biodegradation Pathways of Chlorinated Compounds in a Tidal Wetland(2006-12-12) Devillier, Emily Nicole; Becker, Jennifer G; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The usefulness of bioaugmentation and biostimulation in enhancing the natural attenuation of chlorinated compounds at a seep site at Aberdeen Proving Ground, MD was tested. The biodegradation of (1) a mixture of 1,1,2,2-tetrachloroethane, tetrachloroethene, and carbon tetrachloride, or (2) TeCA alone was compared in microcosms amended with chlorinated substrates alone, chlorinated substrates and electron donor, and chlorinated substrates, electron donor, and a TeCA-degrading enrichment culture. A third experiment evaluated the usefulness of H2 thresholds in determining the importance of co-metabolic and metabolic processes in biodegradation. TeCA biodegradation was significantly enhanced by bioaugmentation and biostimulation. However, the presence of other contaminants inhibited TeCA biodegradation, even in the presence of electron donors and the enrichment culture. H2 thresholds did not prove useful in determining the importance of metabolic and co-metabolic processes; however, evaluating each chlorinated compound individually provided insight regarding biodegradation pathways and the effects of electron donor substrates on degradation rates.Item Fate and Transport of Nitrogen at a Deep Row Biosolids Application Hybrid Poplar Tree Farm(2006-08-10) Buswell, Carrie Ursula; Felton, Gary K; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study focused on a gravel mine reclamation site using biosolids in deep rows as a nutrient source and hybrid poplar trees as the stabilizing crop. Biosolids application rates of 481, 962, and 1443 dry Mg/ha and tree densities of 0, 716, and 1074 trees/ha and controls (0 dry Mg/ha - 0 trees/ha) were studied. Total nitrogen, ammonium, nitrite and nitrate in soil water samples from pan and suction lysimeters under and around the biosolids rows were evaluated. Total nitrogen was predominantly in the form of ammonium. Ammonium concentrations in more than half the samples were above 100 mg/L, reflecting the average biosolids concentration of 2,300 mg/kg. No significant differences (a = 0.05) were determined between application rates or tree densities, but ammonium concentration significantly decreased with distance below the biosolids row. Nitrite and nitrate nitrogen concentrations were predominantly non-detects or less than 1 mg/L, indicating that nitrification was not occurring.Item A Comparison Of Artificial Neural Networks And Statistical Regression With Biological Resources Applications(2006-08-07) Resop, Jonathan Patrick; Montas, Hubert J; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Artificial neural networks (ANNs) have been increasingly used as a model for streamflow forecasting, time series prediction, and other applications. The high interest in ANNs comes from their ability to approximate complex nonlinear functions. However, the "black-box" nature of ANN models makes it difficult for researchers to design network structure or to physically interpret the variables involved. Recent investigations in ANN research have found connections linking ANNs and statistics-based regression modeling. By comparing the two modeling structures, new insight can be gained on the functionality of ANNs. This study investigates two primary relationships between ANN and statistical models: the potential equivalence between feed-forward neural networks (FNN) and multiple polynomial regression (MPR) models and the potential equivalence between recurrent neural networks (RNN) and auto-regressive moving average (ARMA) models. Equivalence is determined through both formal and empirical methods. The real-world phenomenon of streamflow forecasting is used to verify the equivalences found. Results indicate that both FNNs and RNNs can be designed to replicate many regression equations. It was also found that the optimal number of hidden nodes in an ANN is directly dependant on the order of the underlying physical equation being modeled. These simple relationships can be expanded to more complex models in future research.Item Assessment of nitrogen status and vegetation composition in tidal freshwater marshes using partial least squares regression models of hyperspectral canopy reflectance(2006-04-28) Jenkins, Emily Poynter; Tilley, David R; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Hyperspectral canopy reflectance was used to predict sub-surface water nutrients, vegetation composition, and canopy nutrients, which could lead to more useful means for assessing the status of wetlands. Thirty field quadrats at two tidal freshwater marsh sites on the Nanticoke River (Maryland) were treated with five nitrogen levels. During the 2004-05 growing seasons, hyperspectral canopy reflectance was measured using a spectroradiometer with 1nm resolution across the visible and near - infrared spectrum (350-1075 nm), water samples were collected using lysimeters, species cover was quantified, and biomass was collected and analyzed for canopy nutrients. ANOVA was used to determine whether nitrogen affected reflectance, species composition, canopy N and P, and partial least squares regression was used to develop reflectance models predictive of these ecosystem properties. Results indicated that hyperspectral radiometry could be used as a remote sensing tool for quantifying sub-surface water nitrogen, vegetation composition, and canopy nutrients in tidal freshwater marshes.