Improving stream solute load estimation by the composite method: a comparative analysis using data from the Panola Mountain Research Watershed

The setting and attainment of total maximum daily load (TMDL) has become an important criterion for protecting the water quality of surface waters. Accurately estimating streamwater solute loads during short-time intervals with limited resources is crucial to the implementation of TMDLs. The two most common techniques for estimating streamwater loads have shortcomings. The period-weighted approach requires comprehensive sampling to obtain unbiased load estimates, whereas the regression-model method does not accurately estimate loads during short-time intervals and typically does not model unusual events such as combined sewer overflows (a critical input for the TMDL approach). An improved load estimation technique known as the composite method, which combines aspects of both the period-weighted approach and the regression model method, can more accurately estimate loads during short-time intervals and with fewer sampling requirements. This paper demonstrates the usefulness of the composite method for estimating streamwater loads using data from the Panola Mountain Research Watershed near Atlanta, Georgia.Sponsored by: Georgia Environmental Protection Division U.S. Geological Survey, Georgia Water Science Center U.S. Department of Agriculture, Natural Resources Conservation Service Georgia Institute of Technology, Georgia Water Resources Institute The University of Georgia, Water Resources Facult