Liu, Yingmei2014-03-142014-03-142011-12-05etd-12082011-142806http://hdl.handle.net/10919/40398The 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.In CopyrightWatershed modelHSPFPQUALAGCHEMsensitivity analysiswater quality modelCE-QUAL-W2Effective Modeling of Nutrient Losses and Nutrient Management Practices in an Agricultural and Urbanizing WatershedDissertationhttp://scholar.lib.vt.edu/theses/available/etd-12082011-142806/