Thursday Poster Session - Catchment perspective

This study develops a GIS-based Multi-Criteria Analysis (MCA) capable of integrating six socio-environmental criteria—such as stormwater runoff, social vulnerability, and thermal regulation—to support the equitable allocation of Nature-Based Solutions (NBS). Applied to a medium-sized Brazilian city, the approach demonstrates how spatial decision-support tools can reveal critical mismatches between ecosystem service demand and supply in dense urban centers. The analysis identifies areas with high soil sealing (CN > 90 in 44% of the territory) and intense Urban Heat Islands, which coincide with a severe deficit of green spaces (0.39%). To address these issues, the study recommends prioritizing building-integrated NBS in densely built districts, thereby enhancing climate resilience and promoting social equity through data-driven planning. 

Urban Sustainable Drainage Systems (SuDS) are key solutions for addressing the challenges associated with rapid urban expansion and increasing imperviousness. This study presents a GIS–RS-based methodology combined with adaptive multicriteria analysis to identify priority implementation zones across nine functional purposes. Results reveal a wide range of potential configurations and highlight the environmental, social and economic benefits SuDS can deliver. The work also establishes the basis for a Decision Support System enhanced with unsupervised machine-learning algorithms such as K-means and HDBSCAN for improved selection and prioritization of SuDS. 

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 

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. 

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.