Digitized by Kansas Correctional Industries

Digitized by Kansas Correctional Industries

This study localizes dimensions of freshwater salinization by directly measuring chloride concentrations in ungauged urban streams, assessing the relationship between chloride, copper and zinc in sample data, measures statewide trends for Iowa, and considers the regulatory and cultural environment of managing winter roads. Chloride concentrations in local, urban streams generally persist at higher levels than what is typical of natural Iowa waters. Runoff from snow melt events violate water quality standards, with chloride concentrations more closely resembling sea water than freshwater. Meanwhile, long-term trends at the statewide scale suggest levels are decreasing over time. Dissolved ions in groundwater from limestone aquifers encourage chemical buffering. Surface runoff in urban areas does not contain groundwater but does contain a large amount of salt from roads and other sources. More salt present year-round in streams influenced by surface water hydrology likely increases the potential for storm sewers, bridge decks and other urban infrastructure to corrode. Public agencies take varied approaches to freshwater salinization and related concerns. Regulation focuses on drinking water protection, and accounts for both household and industrial chloride sources. Snow and ice “fighters” see chloride as a tool, whereas scientists and regulated agencies consider it a pollutant of concern. This split leads to inconsistent patterns in decision-making and prioritization. Salt is a commodity, generating billions of dollars for suppliers throughout North America. Industry can play a significant role in solving what may ultimately become one of the most challenging water quality problems of the 21st Century.

Thesis (M.S.)--Oregon State University, 1983. / Typescript (photocopy). Includes bibliographical references (leaves 109-114). Also available on the World Wide Web.

Riparian wetlands are believed to play an important role in mitigating non-point source pol- lution, acting as physical and biochemical buffers between diffuse pollution sources and receiving waters. Many studies examined riparian wetlands at the field scale, but there is a dearth of re- search at the watershed scale, particularly in the region of Southern Ontario, where agricultural land use predominates. This study examined the impacts of riparian wetlands on surface water quality at the water- shed scale. A field study was conducted on two sub-watersheds at the northern headwaters of the Canagagigue Creek within the Grand River Watershed in Southern Ontario. The two watersheds were similar in area and land use but with differing riparian wetland extent adjacent to the sub- watershed main channels. A two-year study was conducted examining the hydrology, hydraulics, water quality and nutrient fluxes from the two sub-basins. Water quality data were obtained at the outlet of each sub-basin during base-flow conditions and during 16 rainfall and snow melt runoff events. The hydrology was simulated using the WatFlood model and the water quality (nitrate and total suspended solids) was simulated using an enhancedWatFlood/AGNPS model that was modified to account for continuous simulation, in-stream contaminant fate/transport and riparian wetland influences. The hydraulics and hydrological characteristics of the two basins were distinct. The basin without riparian wetland protection (“West Basin”) exhibited ephemeral tendencies, going dry for several months in the summer, whereas the basin with extensive riparian wetland protection (“East Basin”) showed a persistent base-flow throughout the year with a consistently more rapid hydrological response. This study showed higher nutrient concentrations including nitrate, total nitrogen (TN), and total phosphorus (TP) in the West basin than the East basin, attributed to the lack of riparian wetland protection in the West sub-basin. Total Suspended Solids (TSS) concentration were higher in the east sub-basin than the west sub-basin attributed to differences in sediment grain size distributions and differences in local stream bed slope. Constituent loading estimates from the two sub-basins were conducted on an event-basis and on an average monthly load basis. This study showed that during events most constituents (Nitrate, TP, and TSS) were discharged in greater quantities from the East sub-basin than the West sub-basin for both rainfall and snowmelt events. Event-based TN loading was also higher for the East sub-basin but the difference was not statistically significant. Monthly average loading was significantly higher in the East sub-basin than the West sub-basin for Nitrate, TN and TSS. Monthly average loading was higher in the East basin than the West basin for TP as well, but the difference was not statistically significant. In spite of the generally higher nutrient concentrations in the West sub- basin, the east sub-basin exhibits higher loads due to the differing hydrological conditions in that basin. The persistent stream flow in the East basin continuously transports nutrients of a lower concentration than the West, but the consistent flow dominates the loading calculations resulting in a greater constituent mass transported. The modelling of sediment and nitrogen loading was conducted over the study period. Sedi- ment modelling results showed that the dominant process in the model was in-channel transport with the calibrated model showing very little sensitivity to overland transport parameters and riparian wetland retention. The ability to hydrologically model the basin accurately dictated the performance of the sediment transport model. Nitrogen modelling results demonstrated an ability to generally simulate the nitrogen profiles trends during storm events. However, the WatFlood groundwater storage model provided limitations in terms matching the nutrient concentration variability observed in the measured data. The processes that dominated model performance were fertilizer loading and nitrogen mineralization coefficients, with the riparian wetlands playing a small role in nitrogen removal in the calibrated model.

Riparian wetlands are believed to play an important role in mitigating non-point source pol- lution, acting as physical and biochemical buffers between diffuse pollution sources and receiving waters. Many studies examined riparian wetlands at the field scale, but there is a dearth of re- search at the watershed scale, particularly in the region of Southern Ontario, where agricultural land use predominates. This study examined the impacts of riparian wetlands on surface water quality at the water- shed scale. A field study was conducted on two sub-watersheds at the northern headwaters of the Canagagigue Creek within the Grand River Watershed in Southern Ontario. The two watersheds were similar in area and land use but with differing riparian wetland extent adjacent to the sub- watershed main channels. A two-year study was conducted examining the hydrology, hydraulics, water quality and nutrient fluxes from the two sub-basins. Water quality data were obtained at the outlet of each sub-basin during base-flow conditions and during 16 rainfall and snow melt runoff events. The hydrology was simulated using the WatFlood model and the water quality (nitrate and total suspended solids) was simulated using an enhancedWatFlood/AGNPS model that was modified to account for continuous simulation, in-stream contaminant fate/transport and riparian wetland influences. The hydraulics and hydrological characteristics of the two basins were distinct. The basin without riparian wetland protection (“West Basin”) exhibited ephemeral tendencies, going dry for several months in the summer, whereas the basin with extensive riparian wetland protection (“East Basin”) showed a persistent base-flow throughout the year with a consistently more rapid hydrological response. This study showed higher nutrient concentrations including nitrate, total nitrogen (TN), and total phosphorus (TP) in the West basin than the East basin, attributed to the lack of riparian wetland protection in the West sub-basin. Total Suspended Solids (TSS) concentration were higher in the east sub-basin than the west sub-basin attributed to differences in sediment grain size distributions and differences in local stream bed slope. Constituent loading estimates from the two sub-basins were conducted on an event-basis and on an average monthly load basis. This study showed that during events most constituents (Nitrate, TP, and TSS) were discharged in greater quantities from the East sub-basin than the West sub-basin for both rainfall and snowmelt events. Event-based TN loading was also higher for the East sub-basin but the difference was not statistically significant. Monthly average loading was significantly higher in the East sub-basin than the West sub-basin for Nitrate, TN and TSS. Monthly average loading was higher in the East basin than the West basin for TP as well, but the difference was not statistically significant. In spite of the generally higher nutrient concentrations in the West sub- basin, the east sub-basin exhibits higher loads due to the differing hydrological conditions in that basin. The persistent stream flow in the East basin continuously transports nutrients of a lower concentration than the West, but the consistent flow dominates the loading calculations resulting in a greater constituent mass transported. The modelling of sediment and nitrogen loading was conducted over the study period. Sedi- ment modelling results showed that the dominant process in the model was in-channel transport with the calibrated model showing very little sensitivity to overland transport parameters and riparian wetland retention. The ability to hydrologically model the basin accurately dictated the performance of the sediment transport model. Nitrogen modelling results demonstrated an ability to generally simulate the nitrogen profiles trends during storm events. However, the WatFlood groundwater storage model provided limitations in terms matching the nutrient concentration variability observed in the measured data. The processes that dominated model performance were fertilizer loading and nitrogen mineralization coefficients, with the riparian wetlands playing a small role in nitrogen removal in the calibrated model.

Many of the findings of previous studies have indicated that there is a direct correlation between water quality and urbanization. Increasing impervious coverage typically results in a decrease in water quality. The purpose of this study was to adapt an automated tool for assessing the Pollutant Load Application (PLOAD). Created by CH2M HILL, a fullservice engineering and construction enterprise, PLOAD is a simplified GIS-based model used to calculate pollutants within a watershed. The so-called “simple method” implemented by PLOAD and discussed in this thesis has been endorsed by the EPA as a viable screening tool for National Pollutant Discharge Elimination System (NPDES) stormwater projects. This model was designed to be used with ArcView 3.3. ArcView 3.3 is a depreciated product, the capabilities of which have been replaced by ArcGIS 9.1. Using the same GIS data and tabular data required by PLOAD and custom ArcObjects scripting, a replacement, ArcGIS-PLOAD, was created. The current version of ArcGISPLOAD implements the “simple method” to calculate total pollutant load in pounds per year based on basin boundaries, precipitation in inches per year, ratio of storms producing runoff, parcel land use and parcel area, runoff coefficient for each land use, event mean pollutant concentrations for each land use. Time comparisons between the original PLOAD and the new ArcGIS-PLOAD revealed significant improvements. Both versions of PLOAD produce an intersection between the basin boundary and the land use layer. Calculations are actually done to the intersect layer. It was also found that the original PLOAD disregarded an albeit small portion of the intersection polygons. The new version does not. With the creation of ArcGIS-PLOAD, it is anticipated that it will become a small step in assist the State of Texas in improving water quality.

The ubiquitous use of antibiotics has led to an increasing number of antibioticresistant bacterial strains, including strains that are multidrug resistant, pathogenic, or both. Numerous studies have been conducted showing the presence of antibioticresistance genes (ARGs) and antibiotic-resistant and multidrug resistant bacteria in wastewater and drinking water treatment plants. There is also evidence to suggest that ARGs spread to the environment, and to humans and animals, through wastewater effluents. The overall objective of this study was to investigate the effect of UV light disinfection on ARGs and antibiotic resistant bacteria. Wastewater effluent samples from a wastewater treatment plant (WWTP) in Texas were evaluated for differences in abundance and diversity of tetracycline resistant bacteria before and after UV treatment. The effects of photoreactivation or dark repair on the reactivation of bacteria present in WWTP effluent after UV disinfection were also examined. Culture based methods were used to characterize viable heterotrophic, tetracycline resistant heterotrophic, E. coli, and tetracycline resistant E. coli bacteria present before and after UV treatment. Molecular methods were used to characterize the diversity of organisms present and to test for the presence of tet(Q), a tetracycline resistance gene associated with human origins. UV disinfection was found to be as effective at reducing concentrations of resistant heterotrophs and E. coli as it was at reducing total bacterial concentrations. The lowest survival ratio following UV disinfection was observed in tetracycline-resistant E. coli, showing it to be particularly susceptible to UV treatment. Photoreactivation and dark repair rates were found to be comparable to each other for all bacterial populations. UV disinfection was found to significantly alter the community composition of tetracycline-resistant bacteria, though it did not have the same effect on the total bacterial community.

Free-ranging wildlife are an important contributor of fecal pollution in the form of Escherichia coli (E. coli) to water bodies. Currently, details of this contribution are nebulous and understudied. Much of the related research has not focused on freeranging wildlife; instead investigations examine entire systems while estimating wildlife contribution indirectly or with data of inconsistent quality and source. I began my research by conducting a meta-analysis of existing research to determine the current state of knowledge of wildlife’s specific contribution. Data were sparse, fragmented, of variable quality, and difficult to access. Researchers relied on a variety of outside sources (e.g., state natural resource agencies). Making comparison between studies was nearly impossible because methodologies differed greatly or were described inconsistently. I then calculated wildlife population densities, undertook fecal collection, and conducted spatial analyses of fecal deposition to gather accurate and relevant data of the study area. I augmented field data collection with data derived from my meta-analysis (i.e., fecal deposition rates). I was able to estimate the relative role of individual species (e.g., raccoons [Procyon lotor], white-tailed deer [Odocoileus virginianus], and feral hogs [Sus scrofa]). Finally, I created a model using these data to determine important parameters for future research (e.g., fecal deposition rates) and simulate various management strategies. Although all parameters need more research focus, I found defecation rates were especially important but little researched. I found raccoons were the greatest determiner of potential E. coli load in the floodplain though adjustment of other parameters would greatly impact these findings.

This study explored the relationship between increased proportions of imperviousness in a watershed on surface water quality and examined the effectiveness of using remote sensing to systematically and accurately determine impervious surfaces. A supervised maximum likelihood algorithm was used to classify the 2008 high resolution National Agriculture Imagery Program (NAIP) imagery into six classifications. A stratified random sampling scheme was conducted to complete an accuracy assessment of the classification. The overall accuracy was 85%, and the kappa coefficient was 0.80. Additionally, field sampling and chemical analysis techniques were used to examine the relationship between impervious surfaces and water quality in a rainfall simulation parking lot study. Results indicated that day since last rain event had the most significant effect on surface water quality. Furthermore, concrete produced higher dissolved organic carbon (DOC), dissolved organic nitrogen (DON), potassium and calcium in runoff concentrations than did asphalt. Finally, a pollutant loading application model was used to estimate pollutant loadings for three watersheds using two scenarios. Results indicated that national data may overestimate annual pollutant loads by approximately 700%. This study employed original techniques and methodology to combine the extraction of impervious surfaces, utilization of local rainfall runoff data and hydrological modeling to increase planners' and scientists' awareness of using local data and remote sensing data to employ predictive hydrological modeling.