This study involved a geographic information systems (GIS) approach to modeling ground water pollution potential in the Southern Edwards Aquifer Region in Texas. The DRASTIC ground water model was analyzed using two methods. First, the effects of adding land cover data to the drastic model were evaluated. In the second approach, the effects of the removal of DRASTIC variables were evaluated. Six, five, and four variable models were generated and analyzed.

The Santa Rosa Creek watershed is one of the most pristine watersheds on California’s Central Coast. Preserving this watershed is of great interest because it provides rich soils for agriculture, vast rangelands for cattle, and flowing streams for federally threatened species such as steelhead trout. Soil erosion could impact these resources. Using prediction tools, it is possible to study the erosion that could be occurring in a watershed and identify locations which could contribute the highest amounts of sediment. The objectives of this study were to use RUSLE2 and Geographic Information Systems (GIS) to predict soil erosion rates for each soil map unit in every drainage of the upper Santa Rosa Creek watershed and to determine areas where soil erosion could surpass a soil development rates. Environmental and anthropogenic factors that influence soil erosion such as topography, climate, soil, geology, vegetation, and land use, were described for the entire watershed to provide supplementary data used in the RUSLE2 model and to explain erosion in highly erosive areas. Predicted soil erosion rates were studied to determine if correlations exist between other factors such as slope, existing erosion features, and vegetation. Predicted soil erosion rates calculated using RUSLE2 confirmed that the watershed is healthy and that 98 percent of the drainages are within sustainable soil erosion rates (five tons/acre/year). There were 37 soil map units totaling 1,617 acres (5.6 percent of the entire upper watershed area) with predicted soil erosion rates above a sustainable rate. In Perry Creek watershed, these sites were located on steep slopes tangent to streams. Along the main-stem of Santa Rosa Creek these sites were found in the headwaters where on average slopes are steep, soils are shallow, and rock outcrops exist. There appeared to be no relationship between predicted high soil erosion rates and mapped upland erosion sites, however upland erosion features could not be identified where vegetation canopy restricted view of the soil surface. Additionally, RUSLE2 predicts rill and interrill erosion while upland erosion sites identified using GIS identified larger erosion features, such as gullies. Correlations between predicted soil erosion rates and vegetation formations were confirmed with shrub and tree formations having the highest average predicted soil erosion values. In addition, there was a moderate positive correlation between slope percent and predicted soil erosion (r=0.76), affirming that predicted soil erosion rates increased with increasing slopes.

This research is focused on explaining the concentrations of mercury found in juvenile bald eagles (Halieattus leucocephallus) as a function of the physical and anthropogenic landscape. Due to it's location in the food chain this species is susceptible to a wide range of contaminants (xenobiotics), particularly those that bioaccumulate and biomagnify as they move through the food chain. Previous research has indicated that areas in coastal environments are less susceptible to methylation than those in freshwater environments. Sampling efforts for this research were conducted in such a manner as to obtain an equivalent number of samples from the coastal plain (expected to be low mercury) and the inland regions (expected to be statistically significantly higher). In all cases, results indicated that both feather and blood mercury concentrations were higher in the inland population (Blood: Prob > t = 0.0003, Feather: Prob > t = 0.0002). Utilizing classification and regression tree models (CART), we were able to relate metrics such as the percent of deciduous forest, percent of mixed forest, percent of pasture, and percent of wetland to measured blood mercury concentrations. We also found that the best models were produced using the USGS HUC 12 watersheds (the smallest watershed produced by the USGS). Moreover, we found that metrics describing the amount and type of fragmentation within the watersheds exhibited a significant influence on measured blood mercury concentrations. Contrary to previous research, we found wetlands to be negatively associated with higher blood mercury, whereas the abundance of core forest and a larger patch density (PD) in the deciduous and mixed land cover classes was positively associated with higher blood mercury concentrations. We also found that a higher percentage of pasture was associated with higher blood mercury. / Ph. D.

Federal, state and local governments are increasingly focused on the effects of development on water quality and quantity. With waterbodies being especially sensitive to certain pollutants, such as sediment and nutrients, regulations have been put in place to control the amount of pollutant that gets discharged. Sediment is a cause for concern as it originates during both rural and urban activities, and often carries other pollutants (metals, nutrients, etc.) with it. Existing erosion models focus primarily on estimating erosion from agricultural watersheds. Methods are needed to predict areas with high erosive potential (EP) in urban watersheds. Highlighting highly erosive areas in urbanized watersheds allows for the prioritization of maintenance and installation of Stormwater Control Measures (SCMs), and monitoring of sediment by municipal planners and engineers. This study utilizes commonly available geospatial layers in conjunction with a computational procedure to compute relative EP risk throughout a target urban watershed. A case study of the developed methodology was performed on a watershed in Blacksburg, VA, to generate EP risk maps. Results of the study indicate areas of erosive potential within the target watershed and provide a methodology for creating erosion potential risk maps for use by municipal planners and engineers / Master of Science

Thermal pollution of waterbodies occurring from heated stormwater runoff in urban catchments is a growing concern among municipalities in the United States. The U.S. Environmental Protection Agency (EPA) maintains regulatory criteria for temperature of waters of the U.S. as many species of aquatic life depend on an environment that maintains water temperatures below a certain threshold. Thermal pollution from urban stormwater runoff threatens the livelihoods of cold-water fish species, like trout, among other species of wildlife. In order to reduce thermal pollution loading to its streams, a municipality or regulatory authority must first identify the sources of thermal pollution in its waterbodies. This study predicts areas within an urban watershed in the Town of Blacksburg, VA that may be sources of thermal pollution in stormwater runoff by investigating indicators of thermal pollution potential (TPP) through and analysis of land cover types and runoff flow patterns in a geographic information system (GIS) environment. Results of the study provide a theoretical foundation for TPP risk mapping with recommendations for authorities interested in pursuing TPP risk mapping as a tool to guide and focus efforts toward reduction of thermal pollution and land planning. / Master of Science

Sediment is a major impairment in many streams and rivers in the drainage basins along the northern Gulf of Mexico. The use of geospatial technologies improves assessment and decision making for the management of environmental resources and conditions for coastal watersheds. This research focuses on the development of a conceptual qualitative model enhanced with expert input for the assessment of soil erosion potential in coastal watersheds. The conceptual model is built upon five layers (slope, precipitation, soil brightness or exposure, Kactor, and stream density) like those in a standard numerical soil loss model such as the Revised Universal Soil Loss Equation (RUSLE). The conceptual model produced a continuous surface to index erosion potential. Pearson’s correlation coefficient was used to identify variable sensitivity. The model was most sensitive to Kactor variable, followed by soil brightness, stream density, and slope. The model was not sensitive to the precipitation variable due to the lack of variability across the watershed. Expert input was added to the conceptual model for erosion potential with the Analytical Hierarchy Process (AHP). The AHP is used to value the importance of criteria, providing a quantitative weight for the qualitative data. The expert input increased the overall importance of topographic features and this increased cell counts in the upper erosion potential classes. The AHP weights were altered in 1% increments ranging from plus to minus 20% producing 201 unique runs. A quartile analysis of the runs was used to define areas of model agreement. The quartile analysis allowed for the application of an analysis mask to identify areas of increased erosion potential for improved management related decisions. The conceptual and AHP erosion potential output data, including watershed management priority rankings, were published as web mapping services for story map development as a transition to a decision support system. The limits of the story map to allow user interactions with model output rendered an unacceptable platform for decision support. The story map does offer an alternative to static reports and could serve to improve dissemination of spatial data as well as technical reports and plans like a watershed management plan.

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