Prototype model developed to open ‘black box’ of BMP mechanistic processes

SCCWRP and its partners have developed an initial prototype of a modeling tool for predicting how a ubiquitous class of stormwater BMPs known as biofiltration systems removes dissolved copper from stormwater runoff – a key milestone in an ongoing study working to improve understanding of the specific mechanistic internal processes driving BMP pollutant removal.

The prototype mechanistic model, which SCCWRP completed an initial validation phase on in October in partnership with researchers at the Catholic University of America, shows promise for being capable of predicting how biofiltration systems treat dissolved copper in Southern California.

Researchers compared modeling predictions to data collected during the ongoing study’s laboratory phase, when researchers identified two easily measurable biofiltration media properties – cation exchange capacity and bulk density – as strong indicators of the media’s capacity to remove dissolved copper from stormwater runoff.

Based on the initial model validation work, researchers have moved into a second phase that involves scaling up and validating the model using field-collected BMP performance data.

The mechanistic inner processes by which structural BMPs like biofiltration systems remove contaminants have historically been a “black box” – with researchers routinely measuring the runoff entering and exiting the BMP, but not focusing what happens inside the BMP as this runoff is being treated, including understanding the influence that different BMP design specifications have on performance.