Water quality management at a critical checkpoint by coordinated multi-catchment urban-rural load allocation

Abstract

Improving river water quality at critical checkpoints, defined as locations with significant impacts on water use, to satisfy regulation standards is an important goal of sustainable catchment management. Challenges remain in investigating pollution hotspots, designing efficient target reduction, and evaluating management performance. To address these challenges, we develop a systems approach for water quality management that integrates natural physical processes with human activities and their environmental impacts. In this approach, we firstly expand the concepts of headroom (amount under a permitted value) and excess (amount exceeding a permit) onto the source, spatial, and temporal domains for water quality management. We evaluate system-wide pollution contributions by simulating physical processes in a semi-distributed integrated representation using the CatchWat-SD model. We apply the model to the Upper Thames River basin and validate it using available monitoring data. We then incorporate the evaluated headroom-excess into a coordinated load allocation to enhance the efficiency and feasibility of interventions. Load allocation scenarios where headroom-excess is coordinated at different domains are generated and simulated. Finally, we evaluate the performance of these scenarios using multi-criteria metrics to demonstrate the advantages of headroom-excess coordination. Results show that urban sources, downstream sub-catchments, and dry season flows are associated with excess, thus, enabling managers to identify which cases (pollution sources, locations, and times) to focus load reductions towards. The more a load allocation strategy coordinates headroom-excess across domains, the more target reduction is allocated to the cases with excess, and the better performance it obtains in all the criteria. The study emphasises the need to incorporate headroom-excess in load allocation, which helps to improve systems-level water quality performance more efficiently. The approach can be further expanded to water quality management at multiple checkpoints for sustainable management of regional water systems.