No description available.

No description available.

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.

The Occoquan Watershed is a 1515 square kilometer basin located in northern Virginia and contains two principal waterbodies: the Occoquan Reservoir and Lake Manassas. Both waterbodies are principal drinking water supplies for local residents and experience eutrophication and summer algae growth. They are continuously threatened by new development from the rapid expansion of the greater Washington D.C. region. The Occoquan model, consisting of six HSPF and two CE-QUAL-W2 submodels linked in a complex way, has been developed and applied to simulate hydrology and water quality activities in the two major reservoirs and the associated drainage areas. The studied water quality constituents include temperature, dissolved oxygen, ammonium nitrogen, oxidized nitrogen, orthophosphate phosphorus, and algae. The calibration of the linked model is for the years 1993-95, with a validation period of 1996-97. The results show that a successful calibration can be achieved using the linked approach, with moderate additional effort. The spatial and temporal distribution of hydrology processes, nutrient detachment and transport, stream temperature and dissolved oxygen were well reproduced by HSPF submodels. By using the outputs generated by HSPF submodels, the CE-QUAL-W2 submodels adequately captured the water budgets, hydrodynamics, temperature, temporal and spatial distribution of dissolved oxygen, ammonium nitrogen, oxidized nitrogen, orthophosphate phosphorus, and algae in Lake Manassas and Occoquan Reservoir. This demonstrates the validity of linking two types of state of the art water quality models: the watershed model HSPF and the reservoir model CE-QUAL-W2. One of the advantages of the linked model approach is to develop a direct cause and effect relationship between upstream activities and downstream water quality. Therefore, scenarios of various land use proposals, BMP implementation, and point source management can be incorporated into HSPF applications, so that the CE-QUAL-W2 submodels can use the boundary conditions corresponding with these scenarios to predict the water quality variations in the receiving waterbodies. In this research, two land use scenarios were developed. One represented the background condition assuming all the land covered by forest and the other represented the environmental stress posed by future commercial and residential expansion. The results confirm the increases of external nutrient loads due to urbanization and other human activities, which eventually lead to nutrient enrichment and enhanced algae growth in the receiving waterbodies. The increases of external nutrient loads depend on land use patterns and are not evenly spread across the watershed. The future development in the non urban areas will greatly increase the external nutrient production and BMPs should be implemented to reduce the potential environmental degradation. For the existing urban areas, the model results suggest a potential threshold of nutrient production despite future land development. The model results also demonstrate the catchment function of Lake Manassas in reducing nutrient transport downstream. / Ph. D.

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.

Among other sources of uncertainties in hydrologic modeling, spatial rainfall variability, channel hydraulic variability, and model parameter uncertainty were evaluated. The Monte Carlo and Harr methods were used to assess 90% certainty bounds on simulated flows. The lumped watershed model, Hydrologic Simulation Program FORTRAN ? HSPF, was used to simulate streamflow at the outlet of the Luxapallila Creek watershed in Mississippi and Alabama. Analysis of parameter uncertainty propagation on streamflow simulations from 12 HSPF parameters was accomplished using 5,000 Monte Carlo random samples and 24 Harr selected points for each selected parameter. Spatial rainfall variability propagation on simulated flows was studied using six random grid point sets of Next Generation Weather Radar (NEXRAD) rainfall data (i.e., 109, 86, 58, 29, 6, and 2 grid points) from the baseline scenario (115 NEXRAD grid points). Uncertainty in channel hydraulic properties was assessed comparing the baseline scenario (USGS FTABLE) versus the EPA RF1 FTABLE scenario. The difference between the baseline scenario and the remaining scenarios in this study was evaluated using two criteria: the percentage of observed flows within the HSPF 90% certainty bounds (Reliability) and the width of the HSPF 90% certainty bounds (Sharpness). Daily observed streamflow data were clustered into three groups to assess the model performance by each class: below normal, normal, and above normal flows. The parameter uncertainty propagation results revealed that the higher the model Sharpness the lower the model Reliability. The model Sharpness and Reliability results using 2 NEXRAD grid points were markedly different from those results using the remaining NEXRAD data sets. The hydraulic property variability of the main channel affected storm event paths at the watershed outlet, especially the time to peak flow and recessing limbs of storm events. The comparison showed that Harr?s method could be an appropriate initial indicator of parameter uncertainty propagation on streamflow simulations, in particular for hydrology models with several parameters. Parameter uncertainty was still more important than those sources of uncertainty accomplished in this study because all of the median relative errors of model Reliability and Sharpness were lower than +/- 100%.

No description available.

To propose a methodology for the uncertainty estimation in water quality modeling as related to TMDL development, four Monte Carlo (MC) based techniques—single-phase MC, two-phase MC, Generalized Likelihood Uncertainty Estimation (GLUE), and Markov Chain Monte Carlo (MCMC) —were applied to a Hydrological Simulation Program–FORTRAN (HSPF) model developed for the Mossy Creek bacterial TMDL in Virginia. Predictive uncertainty in percent violations of instantaneous fecal coliform concentration criteria for the prediction period under two TMDL pollutant allocation scenarios was estimated. The average percent violations of the applicable water quality criteria were less than 2% for all the evaluated techniques. Single-phase MC reported greater uncertainty in percent violations than the two-phase MC for one of the allocation scenarios. With the two-phase MC, it is computationally expensive to sample the complete parameter space, and with increased simulations, the estimates of single and two-phase MC may be similar. Two-phase MC reported significantly greater effect of knowledge uncertainty than stochastic variability on uncertainty estimates. Single and two-phase MC require manual model calibration as opposed to GLUE and MCMC that provide a framework to obtain posterior or calibrated parameter distributions based on a comparison between observed and simulated data and prior parameter distributions. Uncertainty estimates using GLUE and MCMC were similar when GLUE was applied following the log-transformation of observed and simulated FC concentrations. GLUE provides flexibility in selecting any model goodness of fit criteria for calculating the likelihood function and does not make any assumption about the distribution of residuals, but this flexibility is also a controversial aspect of GLUE. MCMC has a robust formulation that utilizes a statistical likelihood function, and requires normal distribution of model errors. However, MCMC is computationally expensive to apply in a watershed modeling application compared to GLUE. Overall, GLUE is the preferred approach among all the evaluated uncertainty estimation techniques, for the application of watershed modeling as related to bacterial TMDL development. However, the application of GLUE in watershed-scale water quality modeling requires further research to evaluate the effect of different likelihood functions, and different parameter set acceptance/rejection criteria. / Ph. D.

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