ESTIMATION OF TIDAL MARSH LOADING EFFECTS IN A COMPLEX ESTUARY

Water Resources of South Carolina Publication

ESTIMATION OF TIDAL MARSH LOADING EFFECTS IN A COMPLEX ESTUARY

By Paul A. Conrads¹, Edwin A. Roehl² , and John B. Cook³

¹ U.S. Geological Survey, Gracern Road, Suite 129, Columbia, SC, 29210
² Advanced Data Mining, 116 Sugar Mill Lane, Greer, SC, 29650,
³ Charleston Commissioners of Public Works, P.O. Drawer B. Charleston SC, 29402

Conference Paper

Proceeding Paper from 2002 AWRA Spring Specialty Conference
on Coast Water Resources

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Abstract

The Cooper River is a complex estuarine system amidst the greater Charleston, SC, area. It experiences semi-diurnal tides, extensive flooding and drying of abandoned rice fields and marshes, and flow releases from a hydroelectric dam. The river is also heavily used as a receiving stream for industrial and municipal wastewater treatment plants. Much controversy has existed for years about the relative roles that point-source and non-point source (both anthropogenic and non-anthropogenic) oxygen-consuming constituent loads have on the river.s water quality, as measured by dissolved-oxygen concentration (DO). From 1993 to 1995, the U.S. Geological Survey operated a real-time stream-gaging network that collected DO, water-level, water temperature, and specific conductance data at 15-minute intervals at several sites. One site in an upper branch of the Cooper River was known to be largely unaffected by anthropogenic sources, offering an opportunity to evaluate the impact that non-anthropogenic, non-point sources have on DO variability. Monitoring data were combined with rainfall measurements from area weather stations, and subjected to signal processing and artificial neural network (ANN) modeling techniques. Two distinct causes of DO variability were found and quantified. Rainfall was found to decrease DO concentration at a rate of approximately 0.25 mg/L per inch of rain. Depending on hydrodynamic and meteorological conditions, DO was also found to decrease 2.0 mg/L or more due to tidal flooding of the wetlands proximal to the gaging station. The approach that was used provided the benefit of an extensive accounting of the causes and DO variability under a broad range of hydrological and meteorological conditions.

Abstract
Introduction
Description of Study Area
Approach
Results
Conclusions
References

FIGURES

Figure 1. The Cooper and Wando River, SC.
Figure 2. DO_f and WT_f for East Branch of the Cooper River (station 02172037).
Figure 3. DO versus WT and least-squares regression. R² = 0.846.
Figure 4. RAINAA and DOD_f,d versus Days.
Figure 5. Actual and ANN prediction of DOD_f,d.
Figure 6. DOD_f,d versus RAINAA @ = 1 and 3
Figure 7. ANN response surface of DOD_f,d versus XWL_f,d and SC_f,d.

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Water Resources of South Carolina Publication