Climate change, as well as increasing urbanization, lead to an increase in urban flooding events around the world. Accurate urban flood models are an established tool to predict flooding areas in urban as well as peri-urban catchments, to derive suitable measures to increase resilience against urban flooding. The high computational cost and complex processes of urban flooding with numerous subprocesses are the reason why many studies ignore the discussion of model uncertainties as well as model calibration and validation. In addition, the influence of steep surface (hillside) conditions on calibration parameters such as surface roughness are frequently left out of consideration. This study applies a variance-based approach to analyze the impact of three uncertainty sources on the two variables—flow and water depth—in a steep peri-urban catchment: (i) impact of DEM validation; (ii) calibration of the model parameter; (iii) differences between 1D/2D and 2D models. The results demonstrate the importance of optimizing sensitive model parameters, especially surface roughness, in steep catchments. Additional findings of this work indicate that the sewer system cannot be disregarded in the context of urban flood modeling. Further research with real heavy storm events is to be pursued to confirm the main results of this study.

This study employs a comprehensive multi-objective efficiency index (EI) to assess urban flood mitigation strategies. The EI enables the simple interpretation of a mitigation strategy’s efficiency with a value range between −1 (low efficiency) and 1 (high efficiency), which represents a practical communication tool for decision makers, engineers, and researchers. This was tested at the study site of Feldbach (Austria) with an integrated 1D–2D urban flood model and a distributed hydrological model. A total of 112 scenarios were analysed for six mitigation strategies, which were built from three future challenge scenarios, two observed heavy storm events, and two hydrological pre-conditions. For the given study site, the analysis identifies mitigation strategies implemented in rural boundary areas as the most effective. A novel aspect of this study is the consideration of the urban water balance change, highlighting its impact on the EI. The analysis highlights the importance of analysing each relevant process separately to determine the EI in order to understand why a mitigation strategy is more or less efficient.

The article presents an innovative method for simplifying urban drainage models. This approach strategically reduces complexity while preserving accuracy in large-scale, high-resolution models such as those of the city of Graz. It involves the selective removal and aggregation of sewer network elements like subcatchments and conduits, ensuring vital features like storage nodes and flow controls remain intact for precise simulations. Despite significant reductions in model components, the simplified version maintains high accuracy in hydrological and hydraulic aspects, including water balance components like infiltration loss, surface runoff, and external outflow. The method proves equally effective across both land cover and sewer shed-based models, offering computational efficiencies that speed-up processing by 20–45 times for the study site. This is particularly beneficial for rapid decision-making and resource optimization in urban planning. The model also adeptly predicts flood events, especially from larger, infrequent rainfall, although an overly restrictive flow capacity can refine flood predictions at the expense of other flow characteristics. Ultimately, this streamlined approach allows for the quick creation of simplified, yet accurate, models from high-resolution city-scale hydrodynamic data or digital twins, facilitating efficient and timely analyses in urban drainage management.

Owing to climate change, heavy rainfall events have increased in recent years, often resulting in urban flooding. Urban flood models usually consider buildings to be closed obstacles, which is not the case in reality. To address this research gap, an existing 1D/2D model was extended with underground structures. The underground structures were located using site visits, Google Earth, and information provided by the city administration. Control strategies were used to represent partially open doors or tilted windows. The model was simulated with three measured rainfall events in three different scenarios. Scenarios with underground structures resulted in small storage volumes in the structures and a slightly less flooded area on the surface. The assumptions made were analysed using sensitivity analysis. Varying the number and location of underground structures resulted in small variations in the stored volume and surface flood volume. The sensitivity analysis also showed that the thresholds for height and velocity had a large impact, whereas the opening percentage did not influence the number of buildings affected. The conclusion of the study is that the inclusion of underground structures has little effect on the predicted flooded areas but can be useful in quantifying the water depth in potentially vulnerable buildings.

Due to the ongoing climate and energy crisis, wastewater is becoming increasingly important as a source of renewable energy. In urban areas, heat recovery from the sewer is considered a promising approach, as the locations of supply and demand are close to each other. In this context, it is crucial that negative impacts on temperature-sensitive processes in the downstream wastewater treatment plant are strictly avoided. To support the necessary planning and authorization, this paper presents a model-based approach to assess the thermal energy level of the wastewater at any given location in the sewer, taking into account the influent temperature constraints of the wastewater treatment plant. The entire modelling is based on the open-source software SWMM 5, which was extended by a temperature model. The concept showed its practicability and informative value during a full-scale field application in the sewer systems of the Austrian city of Graz. All modelling is based on freely available software, which makes the approach easy transferable to other cities with comparable infrastructural boundary conditions.