Veranstaltungsprogramm

Current social needs demand for a multifunctional management of urban water systems, ensuring a full provision of ecosystem services by urban streams. This type of multi-objective management must be supported by model-based decision support tools, whose development relies on a very good knowledge of the hydraulic and ecological features of water systems. The LASA group of the University of Padua conducted an integrated environmental monitoring work on the network of urban canals of Padua (NE Italy), to understand the hydraulic and ecological processes in the system and collect the data required to develop a modelling tool to simulate them. Monitoring results evidenced a negative impact of wet-weather flows from combined sewers on the environmental status of the canals, and detected a significant influence of the hydraulic management on their water quality status. A preliminary model formulation to simulate drainage dynamics in one of the key nodes of the local hydraulic network gave promising results. Collected information will represent the basis for the future development of a decision support system accounting for the different ecosystem services provided by the urban canals of Padua.

Climate change and urbanization are intensifying pressures on urban water, energy, food, and ecosystem resources, manifesting in more severe challenges—such as floods and water scarcity—that threaten urban well-being. To address these issues, cities should transition from conventional water management to circular schemes that recover resources and mimic natural processes to restore the water cycle. This study introduces a planning support system using GIS and MCDA to optimize the siting of Water Management Units (WMUs) designed for circularity and greening, integrating supply, wastewater, and stormwater systems. The methodology uses R and QGIS to integrate 15 green infrastructure and 10 circularity criteria. The prioritization framework supports decisions at macro (neighbourhoods) and micro (allotment) scales, promoting equitable resource distribution and maximizing environmental benefits. The case study in Girona, Spain, explores 62 city sectors and 997 allotments to assess context suitability and identify priority sites. Transition scenarios are then analysed to evaluate their impact on the water-energy-food-ecosystem nexus and the social dimension of hydrosocial urban systems. The findings provide actionable insights for urban planners and policymakers, supporting the shift to resilient, circular urban water systems.

In the last decade, green and blue roofs have gained ground as distributed solutions in urban areas, given that roofs cover a large percentage of cities land and climate change is often producing heavier stormwater events, not always properly handled by existing centralised infrastructures. The design of such type of distributed infrastructure involves some challenges, such as the identification of the design hyetograph, characterized by certain rainfall duration and return time. The simulation of the process dynamics related to the water storage and release in and from these tanks allows an appropriate selection of the outflow devices which could ensure the compliance with the maximum water level and downstream flow to avoid any flood damage or the occurrence of structural and operational issues on the roof. An Excel-based tool has been developed to support the simulation and selection of outflow devices which release the outflow into the receiving stormwater systems. The tool highlights for which rain duration a certain outflow device satisfies the requirements in terms of maximum outflow and water level in the roof. A case study in Norway was adopted for demonstration purposes of the tool usage.

Climate change imposes challenges on drainage systems and citizens in urban environments due to more frequent and severe extreme weather events. These challenges can be addressed by incorporating blue-green infrastructure (BGI) into urban environments, for which BGI provides multifunctional benefits beyond the domain of stormwater management. The multifunctionality of BGI and the involvement of multiple stakeholders with heterogeneous interests makes the process of designing BGI and deciding between different options a complex planning problem. We evaluate the performance of BGI options for a Swiss municipality against technical, environmental, social and economic objectives via multi-criteria decision analysis (MCDA). BGI options consist of single BGI elements or combinations; the elements are green roofs, bioretention cells, detention ponds and pervious pavement. We adopt a value-focused approach that integrates model-based and expert-derived performance predictions with preference information elicited from stakeholders. In sensitivity analyses, we investigate the impact of uncertainty in performance predictions and in preference information on the robustness of results. Preliminary results indicate that BGI options featuring bioretention cells perform well for a wide range of typical stakeholders. Reducing uncertainty in preference information has higher impact on the evaluation results than resolving uncertainty in performance prediction.

Rapid urbanization and climate change have exposed the limitations of traditional grey infrastructure (e.g., UDN and DR), which often lack the resilience needed to address urban water management challenges. The integrated optimal design of green-grey infrastructure is a promising solution, with studies verifying the effectiveness of green infrastructure—such as Low Impact Development (LID)—in reducing runoff and enhancing sustainability, as well as the efficiency and flood mitigation benefits of grey infrastructure. However, previous methodologies have overlooked spatial constraints in integrating green and grey infrastructures, resulting in suboptimal site-specific designs. In this study, a multi-objective optimal design framework is proposed for the integrated green-grey infrastructure. The framework enhances efficiency by identifying feasible locations, narrowing the optimization space, and preventing overlaps. Based on GIS data (e.g., land use maps, slopes, and digital elevation model) and UDN information, the framework identifies potential installation locations for LID and DRs according to the UDN. Additionally, the framework prioritizes facilities based on flood reduction effectiveness to prevent overlaps and maximize efficiency. The results showed that the types of LID and the feasible installation locations for DR significantly decreased, while the design cost of UDN tended to increase further.