The WATERMAN system for daily beach water quality forecasting: a ten-year retrospective

Beach water quality forecast models can be useful tools for public health protection. Despite two decades of research, there has been hitherto no comparative field validation of statistical vs mechanistic model forecasts against operational data for marine beaches. This paper reports a novel performance assessment of a three-dimensional (3D) deterministic hydrodynamic model versus a multiple linear regression (MLR) over a wide range of hydro-meteorological and pollution source conditions. The two models are used concurrently to provide continuous daily water quality forecasts for eight marine bathing beaches directly impacted by a major sewage outfall discharging 2.5 million m3/d of chemically enhanced primary treatment effluent. The predicted Escherichia coli concentrations on the beaches located in complex flow environments are studied over a period of significant changes in treatment levels and sewage flows (2011–2018). The performance of both models is found to be superior to the current advisory based purely on past observations. While the 3D model is process-based and the MLR model is data-driven, both models have comparable performance with about 70–80% accuracy. The model forecasts of E. coli concentrations are significantly correlated with field data. In general, MLR models have slightly higher overall accuracy, while the 3D model provides better prediction for the observed exceedances of water quality standard (model sensitivity). The 3D model is however indispensable in addressing issues of emergency response, setting of effluent standards and disinfection dosage optimisation. The two models serve useful complementary roles in a real time beach water quality forecast system for smart environmental management. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.