CONTINUOUS HYDROLOGIC MODELING FOR ANALYZING THE EFFECTS OF DROUGHT ON THE LOWER COLORADO RIVER IN TEXAS

A physically based hydrologic model, the HEC-Hydrologic Modeling System (HMS), developed by the U.S. Army Corps of Engineers, has been parameterized using the Soil Moisture Accounting (SMA) algorithm, calibrated, and validated for the Lake Travis and Lake Lyndon B. Johnson (LBJ) contributing basins in central Texas. The basins are divided into a total of 15 sub-basins, and HEC-HMS with the SMA algorithm represents each sub-basin with five water storage layers involving twelve parameters--surface depression storage, canopy interception storage, upper zone soil storage, tension zone soil storage, infiltration rate, and soil percolation rate, along with storage depths, storage coefficients and percolation rates for one shallow and one deep groundwater layer. The first six parameters and the percolation rate for the interflow were estimated objectively using a combination of the National Land Cover Database 2011 (NLCD 2011) and Soil Survey Geographic Database (SSURGO). The next four parameters were estimated based on analysis of historical streamflow records, and the last parameter was determined through model calibration. The parameter analysis shows that the tension zone storage, interflow storage coefficient and the baseflow percolation rate are the most sensitive parameters for this watershed model. Comparison of simulated and observed streamflows showed that the estimated parameters can be used with meteorological data to simulate flows into the Highland Lakes system in central Texas. The results of the statistical analysis indicate that the simulated flows and observed flows are reasonably well correlated. The model performance is rated as good to very good for all the metrics. The PBIAS coefficient is 9.6 and the Nash-Sutcliffe efficiency value is 0.71 for the entire simulation period, 2004-2016. The model performance can potentially be improved through further calibration and by using the hourly climatic input data instead of daily data. xi In future work, the validated HEC-HMS model can be employed with seasonal climate forecasts and under long-range land-use and climate projections. In addition, radar-based precipitation data can be used to represent the climatic variability on a grid-based scale