Dynamic catchment-scale modelling of wet weather stormwater-sewage interactions: Supporting Integrated Urban Wastewater Management Plans

Abstract

Effective urban wastewater management is frequently hindered by complex, unintended interactions between stormwater and sanitary sewer systems, especially within separate sewer systems (SSSs). Rainfall-Derived Inflow and Infiltration (RDII) constitute the primary mechanism driving these interactions. This phenomenon is intensified by ongoing urbanization and the impacts of climate change, often resulting in system overflows and environmental pollution. Responding to these operational pressures and the requirements outlined in the recently revised EU Urban Wastewater Treatment Directive (UWTD) concerning Integrated Urban Wastewater Management Plans (IUWMPs), this thesis addresses the need for improved city-scale modelling methods capable of explicitly representing, and thereby enhancing the holistic understanding of, stormwater-sewage interactions within urban drainage systems (UDSs) during wet weather.

To meet this need, this research developed and evaluated a comprehensive modelling framework incorporating multiple pathways, centring on a unified 1D-2D modelling method. This method, implemented with Fluidit Storm software, physically combines both sewer net-works into a single model. It enables simultaneous dynamic analysis of the networks by coupling 1D network hydraulics and 2D surface flow dynamics to effectively capture the interdependent behaviour resulting from hydraulic exchange between the networks during wet weather. Successful application of this methodology, however, depends on the availability of well-parameterized hydraulic models for both networks, access to suitable modelling software, and specialized expertise.

The developed method, applied to the case study of the city of Vaasa, demonstrated its capabilities to produce advanced interaction analyses compared to conventional 1D separate network analyses. The method produced spatially nuanced predictions of sanitary sewer network overflows caused by interactions during wet weather, identifying five potential overflow hotspots underestimated by conventional 1D analysis alone. Furthermore, the approach enabled the quantification of substantial flow exchange between the networks and the associated pollutant loads. For instance, during a simulated 120-minute event with a 1% Annual Exceedance Probability (AEP), the stormwater inflow entering the sanitary sewer network was estimated to reach approximately 9,700 m³, while associated overflows were predicted to release approximately 40.2 kg of suspended solids (SS). Additionally, the method demonstrated its capacity to incorporate the effects of local topography and evaluate potential impacts under climate change scenarios, highlighting its applicability to a variety of planning and assessment contexts.

In conclusion, this thesis delivers a noteworthy, software-independent, and scalable framework beneficial for urban drainage stakeholders seeking to improve their understanding and management of stormwater-sewage interactions in UDSs. Despite the prerequisites for its application, the developed methodology provides an adaptable tool for evaluating diverse mitigation strategies, quantifying pollution risks, and directly supporting the development of UWTD-compliant IUWMPs, ultimately contributing to more sustainable and resilient UDS management practices. Future research using this or similar methods could focus on aspects not addressed here, such as calibration with observed data, incorporation of systematic uncertainty analysis, and exploration of potential expansion to real-time control applications and long-term continuous simulations for enhanced climate change impact assessments.