Hydrodynamic modelling of the influence of stormwater and combined sewer overflows on receiving water quality: Benzo(a)pyrene and copper risks to recreational water

Abstract

The risk from chemical substances in surface waters is often increased during wet weather, due to surface runoff, combined sewer overflows (CSOs) and erosion of contaminated land. There are strong incentives to improve the quality of surface waters affected by human activities, not only from ecotoxicity and ecosystem health perspectives, but also for drinking water and recreational purposes. The aim of this study is to investigate the influence of urban stormwater discharges and CSOs on receiving water in the context of chemical health risks and recreational water quality. Transport of copper (Cu) and benzo[a]pyrene (BaP) in the Göta River (Sweden) was simulated using a hydrodynamic model. Within the 16 km modelled section, 35 CSO and 16 urban stormwater point discharges, as well as the effluent from a major wastewater treatment plant, were included. Pollutant concentrations in the river were simulated for two rain events and investigated at 13 suggested bathing sites. The simulations indicate that water quality guideline values for Cu are exceeded at several sites, and that stormwater discharges generally give rise to higher Cu and BaP concentrations than CSOs. Due to the location of point discharges and the river current inhibiting lateral mixing, the north shore of the river is better suited for bathing. Peak concentrations have a short duration; increased concentrations of the pollutants may however be present for several days after a rain event. Monitoring of river water quality indicates that simulated Cu and BaP concentrations are in the same order of magnitude as measured concentrations. It is concluded that hydrodynamic modelling is a useful tool for identifying suitable bathing sites in urban surface waters and areas of concern where mitigation measures should be implemented to improve water quality.

Catchment-wide validated assessment of combined sewer overflows (CSOs) in a mediterranean coastal area and possible disinfection methods to mitigate microbial contamination

“…One of the alternatives to assess the impact of pollutant loads on receiving water bodies can be water quality modelling, that is a useful approach to address mitigation and management of CSOs. The fate and effect of pollutants within the river catchment can be simulated using hydraulic modelling limits (Björklund et al, 2018;Morales et al, 2017;Taghipour et al, 2019). This approach can help to understand the role of CSOs to alter the hydrodynamics and water quality of receiving water bodies under different precipitation events (Quijano et al, 2017) and further complement monitoring and addressing the limitations of analytical methods to some extent (Björklund et al, 2018).…”

“…The fate and effect of pollutants within the river catchment can be simulated using hydraulic modelling limits (Björklund et al, 2018;Morales et al, 2017;Taghipour et al, 2019). This approach can help to understand the role of CSOs to alter the hydrodynamics and water quality of receiving water bodies under different precipitation events (Quijano et al, 2017) and further complement monitoring and addressing the limitations of analytical methods to some extent (Björklund et al, 2018). Furthermore, the integrated models need to be properly calibrated/validated with focus on the impacts, which should be mitigated (Riechel et al, 2016).…”

Hydrodynamic modelling of traffic-related microplastics discharged with stormwater into the Göta River in Sweden

“…This hydrodynamic model of the Göta River was validated ( Fig. S5) and then used to simulate the microbial water quality (Tyréns 2016) and the concentrations of benzo[a]pyrene and copper (Björklund et al 2018) in the river. In this study, the model was further implemented to study the fate and transport of traffic-related MP released with stormwater into the river.…”

Pollution Source Apportionment and Water Quality Risk Evaluation of a Drinking Water Reservoir during Flood Seasons

“…Due to data limitations and the dynamics of the environment, the quantitative evaluation of water quality risk is complicated and difficult. Water quality risk assessment models can be divided into mechanistic, statistical, fuzzy mathematical, grey system, and coupling models based on different theories [ 30 , 31 , 32 , 33 , 34 ]. The Bayesian networks (BNs) model, developed based on Bayesian theory, is a widely-employed risk analysis model [ 35 ].…”