Integrated Modelling to Support Analysis of COVID-19 Impacts on London's Water System and In-river Water Quality

Abstract

Due to the COVID-19 pandemic, citizens of the United Kingdom were required to stay at home for many months in 2020. In the weeks before and months following lockdown, including when it was not being enforced, citizens were advised to stay at home where possible. As a result, in a megacity such as London, where long-distance commuting is common, spatial and temporal changes to patterns of water demand are inevitable. This, in turn, may change where people's waste is treated and ultimately impact the in-river quality of effluent receiving waters. To assess large scale impacts, such as COVID-19, at the city scale, an integrated modelling approach that captures everything between households and rivers is needed. A framework to achieve this is presented in this study and used to explore changes in water use and the associated impacts on wastewater treatment and in-river quality as a result of government and societal responses to COVID-19. Our modelling results revealed significant changes to household water consumption under a range of impact scenarios, however, they only showed significant impacts on pollutant concentrations in household wastewater in central London. Pollutant concentrations in rivers simulated by the model were most sensitive in the tributaries of the River Thames, highlighting the vulnerability of smaller rivers and the important role that they play in diluting pollution. Modelled ammonia and phosphates were found to be the pollutants that rivers were most sensitive to because their main source in urban rivers is domestic wastewater that was significantly altered during the imposed mobility restrictions. A model evaluation showed that we can accurately validate individual model components (i.e., water demand generator) and emphasised need for continuous water quality measurements. Ultimatly, the work provides a basis for further developments of water systems integration approaches to project changes under never-before seen scenarios.

The Value of Aggregated City Scale Models to Rapidly Assess SuDS in Combined Sewer Systems

“…The coefficient of determination values indicate a high variation between CityWatStorm and InfoWorks ICM timeseries, which is mainly due to CityWatStorm rapid response to surface runoff. We expect a further improvement when the CityWatStorm is upgraded to a semi-distributed representation, as is performed in Dobson et al (2021). However, the results can still provide excellent value-for-effort when running large catchment models especially in the context of designing long-term planning interventions, optimisation against various climate projection scenarios or undertaking uncertainty analysis as the frequency of CSOs.…”

“…The results from the 2-month simulation are influenced by the initial conditions and we expect a better agreement between CityWatStorm and InfoWorks ICM when running a longer timeseries rainfall (e.g., decades or centuries) with higher magnitude as once the volume available within the network is fully utilised, the time of concentration becomes irrelevant, and the spatially distributed drainage system will have a closer hydraulic behaviour to the spatially aggregated system. In future work approaches such as increasing the spatial resolution of the CityWatStorm model (Dobson et al, 2021) should be tested along with running longer timeseries rainfall.…”

“…Meanwhile, Dobson and Mijic (2020) presented an integrated model, called CityWat, that represents water supply and wastewater infrastructure to simulate downstream river water quality. The CityWat model (Dobson and Mijic, 2020;Dobson et al, 2021) is an open-source lumped water management model of London water cycle processes. Each process is represented within CityWat at a city scale and the lumping helps with creating efficiency, enabling of sharing parameter information openly without national security concerns and providing the industry with easy-to-understand water management model.…”

A reduced complexity model with graph partitioning for rapid hydraulic assessment of sewer networks

“…CWSD is an open source integrated urban water modelling framework and software designed for easy setup, efficient computation times achieved by spatial aggregation (hence semi-distributed) and flexibility to accommodate a wide range of system types (Dobson, Jovanovic, et al, 2021). The Python source code used in this study is provided at (Dobson, Watson-Hill, et al, 2021).…”

“…We run the experiments (Section 3.2) for two particularly wet month-long storm timeseries, January 2017 and August 2018. These storms were produced from a radar composite, described in (Dobson, Jovanovic, et al, 2021). The Cranbrook stormwater catchment, and its InfoWorks modelled representation, has been presented and validated in a range of studies (Ochoa-Rodriguez et al, 2015;Babovic & Mijic, 2019;Muhandes et al, 2021).…”