Assessing TMDL effectiveness using flow-adjusted concentrations: a case study of the Neuse River, North Carolina.
Integrated control of both point and nonpoint source water pollution using Total Maximum Daily Load (TMDL) assignments will be a major regulatory focus over the next decade. We propose the use of "flow-adjusted" pollutant concentrations to evaluate the effectiveness of management actions taken to meet approved TMDLs. Pollutant concentrations are usually highly correlated with streamflow, and flow is strongly weather-dependent. Thus, pollutant loads, which are calculated as pollutant concentration multiplied by streamflow, have a large weather-dependent variance component. This natural variation can be removed by calculating flow-adjusted concentrations. While such values are not a direct measure of pollutant load, they make it easier to discern changes in streamwater quality. Additionally, they are likely to be a better predictor of pollutant concentrations in the receiving waterbody. We demonstrate the use of this technique using long-term nutrient data from the Neuse River in North Carolina. The Neuse River Estuary has suffered many eutrophication symptoms, and a program to reduce nutrient loading has been in place for several years. We show that, in addition to revealing recent reductions in nutrient inputs, annual flow-adjusted riverine nutrient concentrations show a more pronounced relationship with estuarine nutrient concentrations than do annual nutrient loads. Thus, we suggest that the calculation of flow-adjusted concentrations is a useful technique to aid in assessment of TMDL implementation.
Stow
Craig A
CA
Environmental Science and Policy Division, Nicholas School of the Environment and Earth Sciences, Duke University, Durham, North Carolina 27708, USA. cstow@duke.edu
Borsuk
Mark E
ME
D004784:Environmental Monitoring / Q000379:methods*; D005068:Eutrophication; D005618:Fresh Water / Q000737:chemistry*; D008962:Models, Theoretical; D009584:Nitrogen / Q000032:analysis; D009657:North Carolina; D010758:Phosphorus / Q000032:analysis; D012044:Regression Analysis; D014877:Water Pollution, Chemical / Q000032:analysis* / Q000706:statistics & numerical data; D014887:Weather
D010758:Phosphorus; D009584:Nitrogen