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Increasing wetland restoration in the Lower Mississippi Alluvial Valley has been identified as a method to reduce nutrient loading in the Gulf of Mexico. Wetlands have historically been used to treat water through processes facilitated by wetland plants, and relatively few species and plant traits have been identified as important in carrying out these processes. This study focuses on some of those species and traits and aims to identify species differences and plant traits that may be important for wetland nutrient mitigation. Chapter I provides background information on nutrient pollution, wetland biogeochemical mechanisms for nutrient sequestration, and the focal species of the study. Chapters II and III cover the design and methods for this mesocosm study and the experimental results, while Chapter IV provides a discussion of these findings and identifies other questions that need to be addressed to better understand wetland nutrient removal dynamics.

This study investigates the impact on water quality of combined agricultural best management practices cover crop and minimum tillage, alongside an examination of techniques used to collect those samples. Edge-of-field (EOF) water quality samples were collected from 11 working farms during a two-year paired field experiment. Results showed significant reductions in nutrient concentrations, increased discharge, and mixed findings regarding nutrient mass transport post-treatment. A suite of EOF collection techniques were compared using in-situ automated water sampling systems sampling the same runoff events. Sampling protocols influenced nutrient concentrations in composite samples, but unexpected variance in velocity sensors affected measured discharge, making it challenging to confidently attribute differences in nutrient loading estimates to sampling protocol. The findings provide regionally specific evidence for mitigating on-farm nutrient enrichment in the Lower Mississippi Alluvial Valley and enhancing monitoring techniques.

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Animal and human wastes introduce pathogens into rivers and streams, creating human health and economic burdens. While direct monitoring for pathogens is possible, it is impractical due to the sporadic distribution of pathogens, cost to identify, and health risks to laboratory workers. To overcome these issues, fecal indicator organisms are used to estimate the presence of pathogens. Although fecal indicators generally protect public health, they fall short in their utility because of difficulties in public health risk characterization, inconsistent correlations with pathogens, weak source identification, and their potential to persist in environments with no point sources of fecal pollution. This research focuses on characterizing the ecology of fecal indicators using both modeling and metabolic indicators to better understand the processes that drive fecal pollution. Fecal indicator impairment was modeled in Sinking Creek, a 303 (d) listed stream in Northeast Tennessee, using the ecological niche model, Maxent, for two different fecal indicators. While the use of Maxent has been well demonstrated at the macroscale, this study introduces its application to ecological niches at the microscale. Stream impairment seasonality was exhibited in two different indicators over multiple years and different resolutions (quarterly versus monthly sampling programs). This stresses the need for multiple year and month sampling to capture heterogeneity in fecal indicator concentrations. Although discharge is strongly associated with dissolved solutes, fecal indicator impairment was governed by other ecological factors such as populations of heterotrophic bacteria, enzyme activity, nutrient conditions, and other metabolic indicators. This research also incorporated metabolic indicators to characterize spatiotemporal variability in microbial community function, making connections to fecal and other pollution gradients. Communities differed in their ability to use a wide variety of substrates, and metabolic inhibition in sediments captured most of the interaction of aquatic and benthic communities. Sediment substrate activity was also indicative of degrees of pollution, suggesting that sediment is a potential reservoir for Escherichia coli in this stream, and there is possibility for resuspension, extended residence times, and increased duration for exposure. This research highlights the benefit of using models and other microbial indicators to better understand how environment shapes the niche of fecal indicators.

As the human population increases, the way we use and manage our supply of drinking water becomes even more important. The purpose of this study was to determine residents’ satisfaction level of and performance rating of new water savings devices installed in their apartments. Specifically the investigation focused on ratings of shower heads, kitchen faucet aerators, bath faucet aerators, and fill valve and flapper systems. This quantitative survey included residents at 4 apartment complexes in Tennessee using a paper questionnaire (N = 626). The participants were grouped by age, ethnicity, gender, and whether or not they had experienced both nonrestrictive devices or restrictive low flow devices within their apartment. An independent samples t test was conducted from the research questions for each of these 4 groups. The testing variables for each group consisted of the overall performances of the low flow devices, and the satisfaction of the time to get hot water to shower heads and faucets. There was no significant difference between the 4 grouping variables; residents aged 62 and over compared to 61 and younger, males compared to females, whites compared to nonwhites, and those who had experienced both nonrestrictive and restrictive devices while living in the same apartment when compared to these variables; performance rating of low flow shower heads, kitchen faucet aerators, bath faucet aerators, and low flow toilet devices. The variables also included the satisfaction rating of the time needed to get hot water to the new low flow shower heads and kitchen and bath faucet aerators. These findings support the effort to save clean water and reduce water and sewer costs by installing low flow shower heads, bath and faucet aerators, and water saving toilets. Mean score suggest satisfactory ratings were encountered in every testing category and within every group. In particular, the satisfactory mean score of residents who experienced both nonrestrictive and low flow devices while in the same apartment led to the conclusion that the reduction of water can be achieved satisfactorily in all types of residences.

Recent advances in remote-sensing technologies and analysis methods, specifically airborne-LiDAR elevation data and corresponding geographical information system (GIS) tools, present new opportunities for automated and rapid fluvial geomorphic (FGM) assessments that can cover entire watersheds. In this thesis, semi-automated GIS tools are used to extract channel centerlines and bankfull width values from digital elevation models (DEM) for five New England watersheds. For each study site, four centerlines are mapped. LiDAR and NED lines are delineated using ArcGIS spatial analyst tools with high-resolution (1-m to 2-m) LiDAR DEMs or USGS National Elevation Dataset (NED) DEMs, respectively. Resampled LiDAR decreases LiDAR DEM resolution and then runs spatial analyst tools. National Hydrography Dataset (NHD) lines are mapped by the USGS. All mapped lines are compared to centerlines delineated from photography and LiDAR DEMs. Bankfull widths at each site are determined through three methods. Regional regression equations are applied using variables derived from LiDAR and NED DEMs separately, producing two sets of width results. Additionally, the Hydrogeomorphological Geoprocessing Toolset (HGM) is used to extract widths from LiDAR data. Widths are also estimated visually from aerial photos and LiDAR DEMs. Widths measured directly in the field or derived from field-data are used as a baseline for comparison. I find that with a minimal amount of preprocessing, specifically through DEM resampling, LiDAR data can be used to model a channel that is highly correlated with the shape and location of the mapped channel. NED-derived channels model the mapped channel shape with even greater accuracy, and model the channel location only minimally less accurately. No tool used in this study accurately extracted bankfull width values, but analysis of LiDAR data by the HGM toolset did capture details that could not be resolved using regression equations. Overall, I conclude that automated, computerized LiDAR interpretation needs to improve significantly for the expense of data collection to be cost-effective at a watershed scale.

Monitoring the heterogeneous aquatic environment such as the Stormwater Treatment Areas (STAs) located at the northeast of the Everglades is extremely important in understanding the land processes of the constructed wetland in its capacity to remove nutrient. Direct monitoring and measurements of ecosystem evolution and changing velocities at every single part of the STA are not always feasible. Integrated remote sensing, monitoring, and modeling technique can be a state-of-the-art tool to estimate the spatial and temporal distributions of flow velocity regimes and ecological functioning in such dynamic aquatic environments. In this presentation, comparison between four computational intelligence models including Extreme Learning Machine (ELM), Genetic Programming (GP) and Artificial Neural Network (ANN) models were organized to holistically assess the flow velocity and direction as well as ecosystem states within a vegetative wetland area. First the local sensor network was established using Acoustic Doppler Velocimeter (ADV). Utilizing the local sensor data along with the help of external driving forces parameters, trained models of ELM, GP and ANN were developed, calibrated, validated, and compared to select the best computational capacity of velocity prediction over time. Besides, seasonal images collected by French satellite Pleiades have been analyzed to address the seasonality effect of plant species evolution and biomass changes in the constructed wetland. The key finding of this research is to characterize the interactions between geophysical and geochemical processes in this wetland system based on ground-based monitoring sensors and satellite images to discover insight of hydraulic residence time, plant species variation, and water quality and improve the overall understanding of possible nutrient removal in this constructed wetland.