An Innovative Method For Modeling, Analysis, And Prediction Of Structural Stormwater BMP Performance

Many stormwater structural Best Management Practices (BMPs) rely on gravitational particle settling for sediment removal. The University of Minnesota's St. Anthony Falls Laboratory (SAFL) and BaySaver Technologies, Inc. (BaySaver), a manufacturer of hydrodynamic structural BMPs, have been able to establish statistically valid empirical correlations between the dimensionless Peclet Number (Pe) and sediment removal efficiencies in BaySaver's hydrodynamic separators. The Pe is defined here as the ratio of advection (particle settling velocity) to diffusion (turbulence) in the hydrodynamic environment.

The use of the Pe has practical significance in areas such as stormwater treatment because it provides a basic dimensionless framework for sediment removal efficiency prediction that is independent of the specific dimensions of a given BMP design. Hence, the performance of a particular design can be adequately predicted once the underlying Pe-sediment removal functionality is established via experimental measurements. This article outlines the use of Pe-sediment removal relationships and experimental data to develop models for projecting BMP sediment removal performance. The use of the Pe in stormwater treatment is a new approach useful towards both characterizing and predicting the sediment removal efficiency of a hydrodynamic BMP.