Groundwater modeling using NEXRAD-generated data and MODFLOW: Evaluating the parameters of rainfall and recharge in a GIS framework
Glenn, Stephanie Michelle
Bedient, Philip B.
Doctor of Philosophy
Recharge is one of the most difficult input parameters to evaluate accurately in ground water modeling; this research focuses on analyzing an existing numerical MODFLOW model's accuracy by using more advanced technology for calculating aquifer recharge. The MODFLOW model is of the Northern Tampa Bay (NTB) area (1500 km2) of Florida and monitors the effects of ground water pumping. Ground water overpumping is a serious problem, producing such drastic negative impacts as land subsidence, sinkholes, lowered surface water depths, and seawater intrusion. Improved ground water models will lead to better planning and management of ground water resources. Recharge is a function of several factors, the most important of which is precipitation. This research focused on evaluating the spatial and temporal variability of recharge measurements by incorporating the use of radar rainfall. NEXRAD radar is typically used in hydrologic projects for real-time monitoring and flood prediction. NEXRAD can accurately measure and depict the spatial and temporal patterns of rainfall, leading to spatial improvements in the rainfall measurement since a 4 x 4 km cell-based grid will provide more specific and accurate spatial distribution of rain data than individual rain gages several miles apart. Bias calculations for radar data on a daily basis were analyzed to determine the best method for evaluation of daily data (historical use of NEXRAD calculates bias on storm events). Using a GIS-integrated spatial model with NEXRAD input data, it was determined that NEXRAD could successfully be used for evaluating rainfall in a hydrologic model of the Floridan aquifer.
Hydrology; Environmental science; Environmental engineering