Modelling the clogging of a field filtration system used for stormwater harvesting

Abstract

Non-vegetated high-flow stormwater filters have had widespread implementation in urban areas for stormwater management due to their small footprints. Relevant studies on investigation and modelling of the clogging of these systems, however, are quite limited, especially where they are based on real field observations. In this study, the infiltration rates (IR) of a field stormwater harvesting system, consisting of individual high-flow modules for water filtration, were monitored over a 2.5-year time period. A simple conceptual model, comprising a rainfall runoff model and a water balance model (that includes a water distribution model and a linear/exponential regression model), was developed to simulate the evolution of the IR of each filter module. The field observations show that the IR of the entire system dropped from 2000 mm h⁻¹ to an average of 711 mm h⁻¹ after 2.5 years of operation, with the filters closer to the inlet having the lowest IR at the end of testing (i.e., only 167 mm h⁻¹). The models were calibrated highly satisfactorily against a different number of field observation events, with an average Nash–Sutcliffe coefficient (E) value of 0.64 and mean absolute error (MAE) value of 11.8. The validation results show that the linear regression model had better performance, with E mostly being positive (0.03–0.60) and MAE values (15.0–18.9) smaller than the exponential regression model (E < 0 in many cases, and MAE = 14.5–20.7). Compared to the results of previous laboratory experiments, data from this study indicate a slower decline rate of IR in field conditions, showing the importance of natural wetting/drying regimes for the longevity of such filters. The model could be very useful for optimisation of the design and long-term maintenance (e.g., replacement of clogged filter modular components) of modular filtration systems.