The City of Savannah operates an industrial and domestic water-supply intake on Abercorn Creek approximately 2 miles from the confluence with the Savannah River upstream from the Interstate 95 bridge. Chloride concentrations are a major concern for the city because industrial customers require water with low chloride concentrations, and elevated chloride concentrations require additional water treatment in order to meet those needs. The proposed deepening of Savannah Harbor could increase chloride concentrations (the major ion in seawater) in the upper reaches of the lower Savannah River estuary, including Abercorn Creek. To address this concern, mechanistic and empirical modeling approaches were used to simulate chloride concentrations at the city's intake to evaluate potential effects from deepening the Savannah Harbor. The first approach modified the mechanistic Environmental Fluid Dynamics Code (EFDC) model developed by Tetra Tech and used for evaluating proposed harbor deepening effects for the Environmental Impact Statement. Chloride concentrations were modeled directly with the EFDC model as a conservative tracer. This effort was done by Tetra Tech under a separate funding agreement with the U.S. Army Corps of Engineers and documented in a separate report. The second approach, described in this report, was to simulate chloride concentrations by developing empirical models from the available data using artificial neural network (ANN) and linear regression models. The empirical models used daily streamflow, specific conductance (field measurement for salinity), water temperature, and water color time series for inputs. Because there are only a few data points that describe the relation between high specific conductance values at the Savannah River at Interstate 95 and the water plant intake, there was a concern that these few data points would determine the extrapolation of the empirical model and potentially underestimate the effect of deepening the harbor on chloride concentrations at the intake. To accommodate these concerns, two ANN chloride models were developed for the intake. The first model (ANN M1e) used all the data. The second model (ANN M2e) only used data when specific conductance at Interstate 95 was less than 175 microsiemens per centimeter at 25 degrees Celsius. Deleting the conductivity data greater than 175 microsiemens per centimeter removed the "plateau" effect observed in the data. The chloride simulations with the ANN M1 model have a low sensitivity to specific conductance (salinity) at Interstate 95, whereas the chloride simulations with the ANN M2 model have a high sensitivity to salinity at Interstate 95. The two modeling approaches (Tetra Tech's EFDC model and the one described in this report) were integrated into a decision support system (DSS) that combines the historical database, output from EFDC, ANN models, ANN model simulation controls, streaming graphics, and model output. The DSS was developed as a Microsoft ExcelTM/Visual Basic for Applications program, which allowed the DSS to be prototyped, easily modified, and distributed in a familiar spreadsheet format. The EFDC and ANN models were used to simulate various harbor deepening scenarios. To accommodate the geometry changes in the harbor, the ANN models used the EFDC model-simulated salinity changes for a historical condition as input. The DSS uses a graphical user interface and allows the user to interrogate the ANN models and EFDC output. Two scenarios were simulated using the Savannah Chloride Model DSS to demonstrate different input options. One scenario decreased winter streamflows to a constant streamflow for 45 days. Streamflows during the period January 1 to February 15 were set to a constant 3,600 cubic feet per second for the simulation period of October 1, 2006, to October 1, 2009. The decreased winter streamflow resulted in predictions of increased specific conductance by as much as 50 microsiemens per centimeter and chlorid