A Semi-distributed Model for Predicting Faecal Coliform in Urban Stormwater by Integrating SWMM and MOPUS

Area of Science:

• Environmental Microbiology
• Urban Hydrology
• Water Quality Modeling

Background:

• Microbial contamination in urban stormwater poses risks to human health and limits water reuse.
• Accurate simulation of microbial loads is crucial for effective urban stormwater management.

Purpose of the Study:

• To develop and evaluate MOPUS_S, a semi-distributed model for simulating fecal coliform levels in urban sewer systems.
• To assess the influence of different microbial processes on model performance.

Main Methods:

• Coupling the Storm Water Management Model (SWMM) with the microbial MOPUS model to create MOPUS_S.
• Analyzing the impact of deposition, wash-off, and survival parameters on microbial simulation.
• Evaluating model performance using Nash-Sutcliffe efficiency (NSE) and R² across various rainfall events.

Main Results:

• Deposition and wash-off parameters were more influential than survival parameters for microorganisms.
• MOPUS_S demonstrated comparable performance to existing bacterial models.
• Model accuracy varied significantly between rainfall events, with better predictions for low/medium concentrations than peaks.

Conclusions:

• MOPUS_S is a capable tool for predicting fecal coliform loads in urban catchments.
• The model can aid in urban stormwater management planning and assessing risks associated with stormwater reuse.