The detrimental influence of humans on the environment is of increasing concern. Humans, their livestock, and their pets have caused fecal contamination of waterways throughout the United States. Understanding the sources of fecal indicator bacteria (FIB) and the environmental processes that affect them can be crucial to reducing the number of impaired streams and limiting the negative impacts on the environment. Antibiotic resistance is an emerging issue facing human health in the United States and across the world. Antibiotic resistant bacteria (ARB) have antibiotic resistance genes (ARGs) that prevent antibiotics from killing them. Limited research has been done on the role of the environment in the propagation of antibiotic resistance. As the use of antibiotics increases, it is critical to examine how this impacts human health through the environment. Models of watersheds in Patillas, Puerto Rico and Christiansburg, Virginia were created using the Soil and Water Assessment Tool (SWAT) to compare how the differences in spatial and temporal sampling of FIB, climate, and population affect FIB movement. The performances of the calibrated bacteria models were comparable to other published studies. A primary challenge faced in this study was the use of grab samples taken months apart as monthly averages of FIB. The high precipitation and constant warm climate made the model for Patillas more difficult to fit because of the high variability in the observed data. While the Patillas watershed had a lower population of people and livestock, the Christiansburg watershed had more available data on wildlife. The lack of spatial variance of data and the use of data from 1993-2018, hindered the ability for the model for Patillas to model FIB. Additionally, the model's performance was limited due to the strong hurricanes that affect land use, soils, and populations of humans and animals in the watershed. Using open-source data needs to be explored further as a faster and more cost-effective way of developing SWAT FIB models. The feasibility to use data collected in the Christiansburg and Patillas watershed to calibrate a SWAT-ARB model was determined based on available ARG data. The results indicate that the bacteria models need to be improved before an effective SWAT-ARB model can be calibrated. One limitation in the available ARG data for the two watersheds was that they were only sampled once. Out of the ARGs sampled, sul1 was the best modeled in both watersheds because it has the highest normalized values and correlated with the amount of developed land. / Master of Science / Humans negatively impact the environment. Humans and animals contribute to the bacteria contamination of waterways. Investigation into where the contamination sources are and environmental processes that contribute can help researchers limit the impact on the environment. Bacteria can build resistance to antibiotics, which can be especially dangerous to humans and livestock when exposed. Little research has been done on how the environment has contributed to the spread of antibiotic resistance in bacteria. The Soil and Water Assessment Tool (SWAT) was used to investigate bacteria in the Patillas, Puerto Rico and Christiansburg, Virginia watershed. These models used data published by the United States Geological Survey (USGS) and Environmental Protection Agency (EPA) to improve performance. When comparing simulated data to observed data, the performances of the models were comparable to other published studies. The Patillas watershed was particularly difficult to model because of the warm climate and high precipitation that caused high variability in bacteria concentrations. Strong weather events including hurricanes and a lack of available data on wildlife were other hinderances to the Patillas model. In comparison, more published data on wildlife was available in the Christiansburg watershed and it had a more temperate climate. The SWAT-ARB model was reviewed and recommendations were made to improve the model. Using the previously collected antibiotic resistance bacteria data in the Christiansburg and Patillas watersheds, it would be impossible to create accurate models. More antibiotic resistance data needs to be taken across as a greater time period before the performance of the models can be assessed.

No description available.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20352号 / 工博第4289号 / 新制||工||1664(附属図書館) / 京都大学大学院工学研究科都市環境工学専攻 / (主査)教授 清水 芳久, 教授 米田 稔, 准教授 KIM,SUNMIN / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

In the development of the watershed, hydrodynamic, and water quality models for St. Louis Bay in Mississippi, the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS 2.0) - Nonpoint Source Model (NPSM) was selected as the watershed model and the Environmental Fluid Dynamics Code (EFDC) which includes hydrodynamic and water quality models was selected as the Bay model. Watershed model calibration was initially accomplished utilizing historical data collected by the U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), Mississippi Department of Environmental Quality (MDEQ), and Gulf Coast Research Laboratory (GCRL). The watershed model simulated nonpoint source flow and pollutant loadings for all sub-watersheds, routed flow and water quality, and accounted for all major point source discharges in the St Louis Bay watershed. The model was executed for the period of time spanning from 1965 through 1999 in order to quantify flow and pollutant loadings under a variety of hydrologic conditions. Time varying output from the watershed model was applied directly to the St. Louis Bay model. The Bay model, in turn, simulated hydrodynamics and water quality, including water depth, velocities, salinity, temperature, and fecal coliforms. Final Bay model calibration was performed utilizing a set of site specific data acquired on St. Louis Bay during the period July 14-18, 1998. Model verification was conducted against another set of field data taken in the Bay, during April 18-27, 1999. Fecal coliform was modeled in each of the 750 segments of a three-dimensional system. Comparisons of the predicted and observed data are made qualitatively by using spatial and temporal comparisons. The response of model prediction calculations is consistent with trends of the observed data ranges. The applicability of the mathematical models is also demonstrated for the development of Total Maximum Daily Load (TMDL) for fecal coliform in the St. Louis Bay. The calibrated/verified model will be used as a planning tool to assess the water quality in the Watershed and the Bay as well as for calculating TMDL and Waste Load Allocation (WLA).

The Lake Manassas Watershed is a 189 km2 basin located in the Northern Virginia suburbs of Washington, DC. Lake Manassas is a major waterbody in the watershed and serves as a drinking water source for the City of Manassas. Lake Manassas is experiencing eutrophication due to nutrient loads associated with agricultural activities and urban development in its drainage areas. Two watershed model applications using HSPF, and one receiving water quality model application using CE-QUAL-W2, were linked to simulate Lake Manassas as well as its drainage areas: the Upper Broad Run (126.21 km2) and Middle Broad Run (62.79 km2) subbasins. The calibration of the linked model was for the years 2002-05, with a validation period of 2006-07. The aspects of effective modeling of nutrient losses and nutrient management practices in the Lake Manassas watershed were investigated. The study was mainly conducted in the Upper Broad Run subbasin, which was simulated with an HSPF model. For nutrient simulation, HSPF provides two algorithms: PQUAL (simple, empirically based) and AGCHEM (detailed, process-based). This study evaluated and compared the modeling capabilities and performance of PQUAL and AGCHEM, and investigated significant inputs and parameters for their application. Integral to the study was to develop, calibrate and validate HSPF/PQUAL and HSPF/AGCHEM models in the Upper Broad Run subbasin. "One-variable-at-a-time" sensitivity analysis was conducted on the calibrated Upper Broad Run HSPF/PQUAL and HSPF/AGCHEM models to identify significant inputs and parameters for nutrient load generation. The sensitivity analysis results confirmed the importance of accurate meteorological inputs and flow simulation for effective nutrient modeling. OP (orthophosphate phosphorus) and NH4-N (ammonium nitrogen) loads were sensitive to PQUAL parameters describing pollutant buildup and washoff at land surface. The significant PQUAL parameter for Ox-N (oxidized nitrogen) load was groundwater nitrate concentration. For the HSPF/AGCHEM model, fertilizer application rate and time were very important for nutrient load generation. NH4-N and OP loads were sensitive to the AGCHEM parameters describing pollutant adsorption and desorption in the soil. On the other hand, plant uptake of nitrogen played an important role for Ox-N load generation. A side by side comparison was conducted on the Upper Broad Run HSPF/PQUAL and HSPF/AGCHEM models. Both PQUAL and AGCHEM provided good-to-reasonable nutrient simulation. The comparison results showed that AGCHEM performed better than PQUAL for OP simulation, but PQUAL captured temporal variations in the NH4-N and Ox-N loads better than AGCHEM. Compared to PQUAL, AGCHEM is less user-friendly, requires a lot more model input parameters and takes much more time in model development and calibration. On the other hand, use of AGCHEM affords more model capabilities, such as tracking nutrient balances and evaluating alternative nutrient management practices. This study also demonstrated the application of HSPF/AGCHEM within a linked watershed-reservoir model system in the Lake Manassas watershed. By using the outputs generated by the HSPF/AGCHEM models in the Upper Broad Run and Middle Broad Run subbasins, the Lake Manassas CE-QUAL-W2 model adequately captured water budget, temporal and spatial distribution of water quality constituents associated with summer stratification in the lake. The linked model was used to evaluate water quality benefits of implementing nutrient management plan in the watershed. The results confirmed that without the nutrient management plan OP loads would be much higher, which would lead to OP enrichment and enhanced algae growth in Lake Manassas. / Ph. D.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / Kyle R. Douglas-Mankin / Water quality trading (WQT) is a market-based approach to improve water quality. It is an innovative, voluntary program that connects point source (PS) dischargers who need to reduce their pollutant loads with land managers who could offset those loads with nonpoint source (NPS) reductions to economically achieve water quality improvements in a watershed. The potential issues impeding WQT are its inability to address trading risks and quantify the uncertainty of potential load reduction in trades between PS and NPS. Recent research has also shown that trading information level and transaction costs cause problems in implementing WQT. Therefore, the goals of this study were to quantify the uncertainties of pollutant load reduction and delivery effect for potential trades, to estimate their spatiotemporal variations, and to provide information for stakeholders to reduce intangible costs of WQT. This study simulated agricultural cropland with more than 225 alternative land management practices to identify trends among these scenarios. Both total nitrogen and total phosphorus loads were modeled with SWAT and EUTROMOD for 36 years to analyze the potential load reduction, in-field uncertainty ratio, in-stream delivery ratio, and overall trading ratio (TR) in Lower Kansas watershed, Kansas. The analyses of site-specific effects in both geospatial and temporal aspects were also applied on subbasin level. The variant loading patterns and time distributions of each subbasin showed strong site-specific phenomena. The ANOVA of in-field nutrient load showed significant differences among the design criteria of scenarios. The results also showed a significant delivery and lake effects within the subbasins. The overall TR ranged from 1 to 2.2 or more in different scenarios. The advanced cluster analysis presented a potential method to eliminate the problems involved in fixed TRs while keeping the method simpler than finer-resolution floating TR system. Based on WQT geospatial data model, a three-tier GIS-based web interface Water Quality Trading Information Platform System (WQTIPS) was then developed for WQT information and assessment. A case study demonstrated WQTIPS can provide systematic, spatially information for stakeholders to assess the potential environmental benefit changes from the land management shifts using a simple interface. This study demonstrated that it is possible to automate water-quality trades, use watershed models to minimize trading risk and maximize water-quality benefits, and prioritize among possible trades both spatially and by BMP.

Thesis (M.S.)--University of Tennessee, Knoxville, 2003. / Title from title page screen (viewed Mar. 22, 2004). Thesis advisor: Carol P. Harden. Document formatted into pages (x, 149 p. : col. ill., col. maps). Vita. Includes bibliographical references (p. 72-78).

This dissertation presents the design of an integrated watershed model, WASH123D version 3.0, a first principle, physics-based watershed-scale model of integrated hydrology/hydraulics and water quality transport. This numerical model is comprised of three modules: (1) a one-dimensional (1-D) simulation module that is capable of simulating separated and coupled fluid flow, sediment transport and reaction-based water quality transport in river/stream/canal networks and through control structures; (2) a two-dimensional (2-D) simulation module, capable of simulating separated and coupled fluid flow, sediment transport, and reactive biogeochemical transport and transformation in two-dimensional overland flow systems; and (3) a three-dimensional (3-D) simulation module, capable of simulating separated and coupled fluid flow and reactive geochemical transport and transformation in three-dimensional variably saturated subsurface systems. The Saint Venant equation and its simplified versions, diffusion wave and kinematic wave forms, are employed for surface fluid flow simulations and the modified Richards equation is applied for subsurface flow simulation. The reaction-based advection-dispersion equation is used as the governing equation for water quality transport. Several physically and mathematically based numerical options are provided to solve these governing equations for different application purposes. The surface-subsurface water interactions are considered in the flow module and simulated on the basis of continuity of interface. In the transport simulations, fast/equilibrium reactions are decoupled from slow/kinetic reactions by the decomposition of reaction networks; this enables robust numerical integrations of the governing equation. Kinetic variables are adopted as primary dependent variables rather than biogeochemical species to reduce the number of transport equations and simplify the reaction terms. In each time step, hydrologic/hydraulic variables are solved in the flow module; kinetic variables are then solved in the transport module. This is followed by solving the reactive chemical system node by node to yield concentrations of all species. Application examples are presented to demonstrate the design capability of the model. This model may be of interest to environmental scientists, engineers and decision makers as a comprehensive assessment tool to reliably predict the fluid flow as well as sediment and contaminant transport on watershed scales so as to evaluate the efficacy and impact of alternative watershed management and remediation techniques prior to incurring expense in the field.

Nutrient enrichment, which can be detrimental to the health of aquatic systems, is one of the leading causes of impairment of our Nations? waters. Development and initial calibration of a hydrologic, hydrodynamic, and water quality model of dissolved oxygen and nutrient concentration for the St. Louis Bay watershed in coastal Mississippi is documented herein. The model was developed using the USEPA BASINS 3.0 analysis system and WinHSPF, a comprehensive watershed loading and transport modeling software. The resulting model simulates significant watershed and instream physical, chemical and biological processes including rainfall runoff and associated water quality from a variety of land use categories. Extensive data describing the study area, land use practices, hydrology and water quality are presented, analyzed and discussed relative to model development and adequacy to support future modeling projects. Integration of this data into a valuable water quality assessment model and preliminary model calibration is also presented.

Water is a primary shared resource that connects all species across the landscape and can facilitate shared exposure to a community of waterborne pathogens. Despite remarkable global progress in sanitation and hygiene development in the past two decades, infectious diarrhea remains a prominent public health threat in sub-Saharan Africa. This thesis identifies and discusses persistent challenges limiting the success of current waterborne disease management strategies and several existing research hurdles that continue to impede characterization of microbial transmission and transport. In this work, the Chobe River watershed in Northern Botswana serves as a target study site for the application of hydrological modeling tools to quantify emergent water quality and health challenges in Southern Africa. A watershed model with extensive data requirements, the Hydrological Simulation Program – Fortran (HSPF), is used to identify primary data gaps and model assumptions that limit the progress of model development, and guide opportunities for data collection, tool development, and research direction. Environmental pathogen exposure risk and epidemiological outbreak dynamics are best described by interactions between the coupled human and environmental processes within a system. The challenge of reducing diarrheal disease incidence strengthens a call for research studies and management plans that join multiple disciplines and consider a range of spatiotemporal scales. / Master of Science