Water Column Model
The unstructured grid finite-volume water quality model (WQ) was developed based on the framework of the water quality analysis simulation program (called WASP5) ctreated by Ambrose et al. (1993). Modification is made to included the nutrient fluxes due to sediment resuspension via sedimantion process at the bottom (Zheng et al., 2004). In the water quality, the water quality variables include 1) dissolved oxygen (DO); 2) phytoplankton as carbon (PHYT); 3) carbonaceous biochemical oxygen demand (CBOD); 4) ammonium nitrogen (NH4); 5) nitrate and nitrite nitrogen (NO3); 6) ortho-phosphorus or inorganic phosphorus (OPO4), 7) organic nitrogen (ON), and 8) organic phosphorus (OP).
The water column wate quality model describes a basic transformation process including photosynthesis, uptake, respiration, nitrification, denitrification, benthic flux, sediment suspension, and external loads, etc. This model is driven by the computed flow and mixing fields from FVCOM, with inclusion of external loading of nutrients along with freshwater discharge at the upstream end of the river, surface and bottom fluxes of nutrients due to wind mixing and bottom sediment resuspension, MM5-predicted short-wave radiation and light attenuation, and FVCOM assimilated fields of water temperature and salinity. The initial condition are specified by using the climatologic biological fields built based on previous field measurements.
The water quality model described above include 51 biological parameters that must be specified. These parameters are determined based on either observational values from previous field measurements in the Satilla and other estuaries or literature. A sensitivity analysis has been made to estimate the uncertainty of the model-predicted temporal and spatial distributions due to the variation range of biological parametrs.
DO is one of the most important water quality indicators. In the water column, one source for DO is photosynthesis carbon fixation, which is proportional to the density of phytoplankton and their growth rate. Reaeration can be either a source or sink for DO. In an under-satuaration condition, it functions as a source for DO. In turn, it acts as a sink for DO. In the water column, DO is diminished mainly due to the processes of SOD, phytoplankton respiration, nitrification, and oxidation of CBOD.
Unlike other estuarine region, the Satilla River estuary contains a large area of the intertidal salt marsh. Previous observations suggest that the sediment orygen demand (SOD) is higher in the intertidal salt marsh than in the estuarine bed (Pomeroy et al., 1972). To characterize this difference, the SOD in the Satilla River water quality is specified to be 2.5 g O2 m-2 day-1 over the inertidal salt marsh and 1.2 g O2 m-2 day-1 in the estuarine bed.
Previous field measurements also revealed that nitrification rate in estuaries varies with salinity, which is higher in a region with low salinity and high turbidity (Pakuiski et al., 2000). The values of nitrification rate used in the model is specified as a function of the salinity (Zheng et al., 2004).
The selection of biological parameters are made with helps of biologists at the University of Georgia, Skidaway Institution of Oceanography, and Enironmental Protection Agency (EPA) in Athens.