The critical flow-storm approach and uncertainty: Analysis for the TMDL development process

Federal clean water regulations have mandated the integration of nonpoint source (NPS) loads into the Total Maximum Daily Load (TMDL) development process in watershed management studies. One of the key challenges in the TMDL development is how to define the critical condition for a receiving water body. The traditional low flow condition (i.e. 7Q10) does not satisfy the need for the TMDL development due to the fact that the pollutant loads come from both constant flow point sources and storm-driven, time-varying nonpoint sources. The purpose of this study is to develop a practical event-based Critical Flow-Storm (CFS) approach for determining the TMDL for a water body impacted by both point and nonpoint source pollution. The CFS approach was developed from the Critical Flow-Storm (CFS) concept, which was based on the notion that when combining point and nonpoint sources, there could be a critical scenario in which an initial low flow combined with a small storm would cause the worst pollutant concentration levels in the river. The event-based CFS approach, in which only a limited number of storm events need to be simulated, was demonstrated successfully as a viable alternative for TMDL development. The CFS approach explicitly addresses the critical condition as a combination of stream flow, magnitude of the storm event and the initial condition of a watershed. Most importantly, statistical estimate of the return period associated with the critical condition can be determined. The state-of-the-art watershed model BASINS/HSPF was used as the modeling tool for both event-based and continuous simulations. Comparison of these two approaches was made using a case study entitled “Nitrate TMDL Development for Muddy Creek/Dry River, Virginia”.; The First-Order Error Analysis (FOEA) was applied for estimating the Margin of Safety (MOS) term in the TMDL formulation. Besides computational efficiency, FOEA allows the consideration of the combined effects of parameter sensitivity and parameter uncertainty in the determination of the key parameters affecting model output uncertainty. In this study, uncertainty associated with precipitation data was found to be most prominent. The use of the FOEA was an improvement over the current EPA simple explicit and implicit method in estimating margin of safety.