Abstract:
Reliable approaches for accurately assessing the performance of stormwater treatment systems is essential for their effective design, including filter media selection which can be a significant constituent in stormwater treatment systems. This study presents an innovative modelling approach integrating the Tank Model with the adsorption-desorption characteristics of the filter media. The resulting modelling approach was applied to simulate a field-scale bioretention basin where biochar was used as filter media with over ten years of rainfall records. The resulting outflow and overflow volumes were compared with observed data for calibration. The Stormwater Treatment Tank Model (STTM) was validated using the Leave-One-Out-Cross-Validation (LOOCV) method. The simulation outcomes include water outflow and overflow (quantity) from the bioretention basin as well as outflow water quality represented by three heavy metals (Pb, Cu, and Zn). The modelling approach developed was found to be capable of accurately simulating outflow and overflow volumes, with outlet water quantity being significantly influenced by the total rainfall depth. The modeling results also suggested that a sole treatment system would not be adequate, particularly for large rainfall events (>100 mm) and a treatment train would be more effective. Simulating long-term (over ten years) pollutant removal performance in the bioretention basin indicated that heavy metals outflow event mean concentration (EMCs) values calculated using simulated results of 30% biochar application rate generated the best pollutant removal with consistent values (2.7 μg/L, 3.0 μg/L, 17.2 μg/L for Pb, Cu, and Zn, respectively). These results confirm that the modelling approach is reliable for assessing long-term treatment performance, as well as a robust tool able to contribute to more effective treatment system design, particularly filter media selection and evaluation