Thursday July 2, Poster session
10:00 - 11:00 / 13:45 - 14:30
GIS–RS-based methodology for multipurpose SuDS planning with machine-learning integration in complex urban environments
Large-scale assessment and prioritization of combined sewer overflows in Flanders
We present a large-scale assessment of combined sewer overflow (CSO) emissions across Flanders based on InfoWorks ICM® hydrodynamic simulations for 2021 and proprietary software Cockle® pollutant-load calculations. Approximately 8 300 CSOs were modelled, covering 85% of connected inhabitants, revealing substantial variability in overflow behaviour. Total CSO emissions amount to ~400,000 equivalent inhabitants (IE), ≈7% of system input. At the agglomeration level, 54% comply with the EU Urban Wastewater Directive’s 2% rule. CSOs dominate emissions of BOD and suspended solids, whereas WWTP effluents dominate TN and TP. Cockle® applies concentration statistics from multiple pre-registered, high-frequency sampled CSOs and combines them with simulated spill flows (corrected for infiltration and inflow) to estimate annual pollutant loads consistently. Comprehensive maps were produced for each drainage area and surface water body, showing all impact points—including WWTPs, pending connections, planned individual treatment systems, and CSOs—with circles scaled to discharge magnitude. Findings support targeted prioritization under evolving climate and regulatory constraints and provide actionable insights for compliance planning
Techno-economic optimization of works programs derived from a sewerage master plan using the Optimizer™ tool : Feedback from Colmar Agglomération
Regulatory requirements applicable to wastewater and stormwater collection systems (UWWTD and WFD) encourage the identification of solutions that are both hydraulically effective and financially sustainable. However, conventional approaches generally rely on modeling a limited number of scenarios, often selected empirically. In this context, a central question arises: how can we be sure that the chosen option actually leads to the optimal solution? As part of Colmar Agglomération’s Sewerage Master Plan, we explored this question and proposed an innovative approach using our Optimizer™ tool, designed to test thousands of scenarios and identify the most effective and most cost-efficient strategy. The results highlighted significant gains, with an approximately 45% reduction in discharged volumes, achieved by optimizing targeted sectors identified as priorities. This feedback shows that integrating an optimization approach into sewerage studies improves wet-weather performance and helps pinpoint the most relevant techno-economic solution by precisely locating solution optima.
SuDS at the street-scale: Aggregation modelling methods
Sustainable Drainage Systems (SuDS) are increasingly being implemented to mitigate flooding, improve water quality, and restore urban hydrological function, yet real-world retrofits typically occur at small, fragmented scales. Assessing the combined performance of SuDS at the street scale requires detailed hydraulic modelling, which can be computationally intensive. This study evaluates two aggregation strategies—LumpN, which groups SuDS by type, and LumpOne, which represents all SuDS as a single composite system—against a fully disaggregated baseline using a 1D hydrological modelling framework based on SWMM LID concepts. A Monte Carlo approach generated 500 synthetic street-scale catchments containing varying configurations of green roofs and bioretention systems. Continuous rainfall from a full year was applied to compare outflow predictions across aggregation strategies. Results indicate that LumpN preserves hydrological behaviour with high accuracy, achieving strong Nash–Sutcliffe Efficiency values and reasonable peak flow and volume estimates. In contrast, LumpOne introduces substantial errors, particularly in systems with mixed SuDS types or heterogeneous physical characteristics, largely due to overestimated exfiltration in the aggregated representation. The findings show that type-based aggregation offers a computationally efficient yet reliable alternative to fully detailed modelling, while full aggregation should be applied cautiously when the diversity of the modelled SuDS is high.
