829-840 Gw N-d 04

Numerical models that account for the effects of fluid density on ground water flow are being used more frequently to address scientific, engineering, and water resource management problems (Voss and Wood 1993; Voss 1999; Voss and Andersson 1993; Simmons et al. 1999; Simmons et al. 2002; Shoemaker and Edwards 2003; Langevin 2001). Also being used more frequently are inverse modeling routines based on nonlinear regression methods documented by Hill (1992, 1998), Hill et al. (2000), Poeter and Hill (1998), and Doherty (1990, 2002). However, there has been little application of inverse modeling sensitivity methods to density-dependent ground water flow simulators because of limitations in computing power and the unique technical skills individuals must learn. As computing power increases and expertise grows, modeling studies will likely use both inverse methods and density-dependent ground water flow simulations to solve complicated water resource or ground water contamination problems. Both technologies contain powerful capabilities that can help modelers better understand complex flow systems and make better use of available data. A practical problem that could benefit from the combined use of these methods is salt water intrusion. Salt water intrusion is important because (1) ~70% of the earth’s population lives near a coast, and (2) ~95% of the earth’s water lies in the oceans and seas at high levels of salinity (Freeze and Cherry 1979). To study salt water intrusion, densitydependent ground water flow dynamics are needed to simulate flow in the transition zone between fresh water and salt water. Nonlinear regression methods for calibrating and Abstract Sensitivity analysis with a density-dependent ground water flow simulator can provide insight and understanding of salt water intrusion calibration problems far beyond what is possible through intuitive analysis alone. Five simple experimental simulations presented here demonstrate this point. Results show that dispersivity is a very important parameter for reproducing a steady-state distribution of hydraulic head, salinity, and flow in the transition zone between fresh water and salt water in a coastal aquifer system. When estimating dispersivity, the following conclusions can be drawn about the data types and locations considered. (1) The “toe” of the transition zone is the most effective location for hydraulic head and salinity observations. (2) Areas near the coastline where submarine ground water discharge occurs are the most effective locations for flow observations. (3) Salinity observations are more effective than hydraulic head observations. (4) The importance of flow observations aligned perpendicular to the shoreline varies dramatically depending on distance seaward from the shoreline. Extreme parameter correlation can prohibit unique estimation of permeability parameters such as hydraulic conductivity and flow parameters such as recharge in a density-dependent ground water flow model when using hydraulic head and salinity observations. Adding flow observations perpendicular to the shoreline in areas where ground water is exchanged with the ocean body can reduce the correlation, potentially resulting in unique estimates of these parameter values. Results are expected to be directly applicable to many complex situations, and have implications for model development whether or not formal optimization methods are used in model calibration.