ESTIMATION OF TIDAL MARSH LOADING EFFECTS IN A COMPLEX ESTUARY

Abstract

A bstract.A critical element of a dissolved oxygen (DO) Total Maximum Daily Load (TMDL) is the determination of the relative impacts of point and nonpoint source impacts on the DO of an impaired stream.It is not uncommon that the ultimate oxygen demand for non-point sources during a rain event can be much greater than the effects of the fully permitted point-source loading to the stream.Traditionally, the loading of oxygenconsuming constituents is often estimated with a watershed model which is then coupled with a mechanistic model of the receiving stream.Calibrating coastal system applications of watershed models and mechanistic models to match the behavioral variability observed in actual field data is particularly difficult due to low watershed gradients, poorly defined drainage areas, chaotic forcing functions, and insufficient understanding of watershed and marsh process physics and chemistry.Data mining offers an alternative approach for analyzing and modeling tidal DO signals to quantify their responses to point-and nonpoint-source loadings.Data mining can be used to extract DO signal components of nonpoint loading caused by rainfall events and tidally entrained organics from marshes and mudflats.At one gaging station on the Cooper River, rainfall was found to decrease DO concentrations at an average rate of approximately 0.25 milligrams per liter (mg/L) per inch of rainfall.Similarly, it was found that specific conductance, water level, and tidal range, which indicate tidal forcing, modulate DO in the range of 3.1 mg/L.This paper examines the approach of using data-mining techniques to improve models for coastal applications and more accurately quantifies the effects of nonpoint-source loading.