Effects of urban structures on spatial and temporal flood distribution

Rapid urbanization has brought great productivity, prosperity and challenges to Shanghai in the last few decades. This paper focuses on the influence of urbanization on urban pluvial flooding, which frequently occurs and causes severe losses, especially in the central urban areas. We quantitatively evaluate the flood risk using scenario simulation methods. The involved scenarios were designed by incorporating two environmental variables (land subsidence and land use/land cover (LULC) change), three time points (2000, 2006 and 2012) and four degrees of rainfall magnitude, with 5-, 10-, 50- and 100-year return periods, respectively. A toolset was developed to model the hydrodynamic process of pluvial flooding in each scenario. The inundation area and average depth were selected as metrics to estimate the severity of flooding, and the corresponding F statistic and root-mean-square deviation were employed to quantify the inundation changes with the impact of all variables. Results suggest that the impacts of land subsidence and LULC change are a function of rainfall magnitude and display a spatial disparity across the entire study area. LULC change is the key factor contributing to the flood risk, which largely affects the inundation extent at a regional scale. Nonetheless, the effects of different land use types are distinctive. The inundation intensifies within industry and transportation land uses and alleviates within green space and waters. Furthermore, except for a slight change captured in the local water depth, the overall flood risk is less sensitive to the impact of land subsidence with varying rainfall magnitudes when compared to the LULC change.

Spatial heterogeneity of controlling factors’ impact on urban pluvial flooding in Cincinnati, US

Planning Nature Based Solutions against urban pluvial flooding in heritage cities: A spatial multi criteria approach for the city of Florence (Italy)

Increasing urban flood risk in China over recent 40 years induced by LUCC

Urban pluvial flooding is influenced by rainfall intensity, drainage capacity, and urban infrastructure. While prior studies mapped flood extents, the spatiotemporal dynamics of drainage saturation and overflow remain underexplored. This study introduces the percentage of node in flood assessment (PNFA) and flood expansion rate (FER) to quantify flood spread within drainage networks. Using EPA SWMM, three historical storms (2008, 2019, and 2020) and seven return-period scenarios were simulated in Do Lo, Hanoi, Vietnam. The results show that despite rainfall variability, spatiotemporal flood patterns remain stable, indicating predictable propagation pathways. FER values ranged from 0.17 (slow) to 0.902 (rapid), reflecting flood expansion speed under light to heavy rainfall. Spatiotemporal analysis produced hazard maps, capturing both spatial and temporal dimensions, revealing not only a persistent critical hotspot near AH13 but also consistent flood evolution patterns across various scenarios. These findings shift perspectives on flood preparedness by emphasizing timing, sequence, and hotspot stability. This study advances urban flood risk assessment through spatiotemporal hazard mapping, offering insights essential for mitigation, urban planning, and drainage resilience. Incorporating time-sensitive models is crucial for managing flood risks amid increasing extreme weather events.

Urban pluvial flooding is a complex process shaped by rainfall intensity, drainage system capacity, and urban infrastructure. While previous studies have mapped flood extents, the spatiotemporal evolution of drainage saturation and overflow propagation remain insufficiently explored. This study introduces the Percentage of Node in Flood Assessment (PNFA), integrating the Flood Expansion Rate (FER) to measure flood spread within drainage networks. Using the EPA Storm Water Management Model (SWMM), three historical storms (2008, 2019, 2020) and seven returned period scenarios were simulated in Do Lo, Hanoi, Vietnam. Results reveal that despite variations in rainfall intensity, spatiotemporal flood patterns remain stable, suggesting predictable flood propagation pathways. FER values range from 0.17 (slow) to 0.902 (rapid), indicating that system response is highly sensitive to storm intensity. Key flood-prone areas consistently experience early drainage saturation, pinpointing critical intervention points. Flood propagation speed and saturation timing are crucial for early warning systems and emergency response strategies. This study enhances urban flood risk assessment by incorporating spatiotemporal flood hazard mapping, which considers the sequence and timing of flood events. These insights are crucial for flood mitigation, urban planning, and drainage system resilience, highlighting the importance of time-sensitive flood risk models amid rising extreme weather events.

Can urban pluvial flooding be predicted by open spatial data and weather data?

Floods are the most common disaster in Canada. As results of rapid urbanization and climate changes, both frequency and risks of floods have been increased in Canadian urbanized areas, where the disasters have usually costlier impacts than in rural areas. Imagery data and technologies of optical remote sensing are helpful and can be applied for urban flood response and pre-disaster preparation. Especially high and very high optical remote sensing can be used for precise mapping of the floodwater distribution in dense urban areas and providing key information for disaster response management. In addition, the geospatial information about urban land surface and urban growth derived from optical remote sensing imagery can be the key inputs for urban flood risk analyses. In recent years, several case studies for different urban flood types, including fluvial (Calgary 2013, Ottawa-Gatineau 2017) and pluvial (the Greater Toronto Area) floods in Canada, have been carried out at Canada Centre for Mapping and Earth Observation, Natural Resources Canada. Methodologies/framework for urban floodwater mapping have been developed based on high resolution optical data, as well as the impacts of urban growth on the urban flash flood risks have been investigated using model simulations with remote sensing derived maps as inputs. This presentation demonstrates results from three Canadian urban flood case studies and introduces remote-sensing-based methodologies for different types of urban floods.

Multi-method combined analysis of urban flood risks and its influencing factors under low impact development

Pluvial floods are frequent phenomena in Romania occurring during torrential rainfall, causing significant damage. Pluvial floods occur due to extreme rainfall when the natural infiltration of excess water into the ground is artificially reduced and when runoff into urban areas exceeds the capacity of existing drainage systems. In urban areas, pluvial flooding is more frequent due to extended impermeable areas, buildings, and undersized drainage systems. Tulcea municipality is characterized by periodic rainfall flooding events with consequences on properties and communities, infrastructure, and on the economic activities. In the second cycle of implementation of the Floods Directive 2007/60/EC, 17 Areas of Potential Significant Flood Risk (APFSR) pluvial source areas were identified, covering 19 municipalities and towns, for which pluvial hydraulic models were carried out. Tulcea municipality was one of the cities designated as having areas of potential significant pluvial flood risk. Hydraulic modelling results have been used for the construction of pluvial flood hazard and risk maps, these being the first pluvial maps reported by Romania to the European Commission. Based on these maps, critical drainage areas have been identified at the level of Tulcea Municipality and some potential flood risk reduction measures have been recommended.

A city-wide approach to reduce the uncertainty regarding the spatial variability of urban flooding events is required in urban catchments. The goal of this study is the development of a modelling framework independent of the spatial scale to address the most hazardous areas in the current state and the future. The framework starts with the definition of the study objectives (e.g. reducing flood risk), which have a direct impact on the spatial and temporal scale, the used model approach, the data requirement and the level of detail. Furthermore, potentially hazardous areas will be identified with the potential flood risk index (PFRIi). The determination of this is a risk-based approach (R=E*V*H) which combines the exposition (E) with the vulnerability (V) and the hazard (H). The population density of each object and the total number of persons in the catchment will quantify the exposition. The vulnerability includes the number of past damage events and the object use. How accurate the modelled hazard is considered, depends on the used model approach: i) GIS-based; ii) only 1D; iii) only 2D; iv) 1D/2D models. The combination of H and V resulted in the risk factor (RFi) in four levels of detail depending on the used model approach. This allows both, the quantification of hazardous areas at the current state and the change of the PFRIi by future scenarios such as climate change and urbanization.PFRIi = nP,k * RFi / (Ak * ∑P)                                                                                                                                                                                     PFRIi=Potential Flood Risk Index; nP,k= number of Persons on a private ground k; Ak=total object area; =total number of persons in the catchment; Rfi= risk factor depending on the used model approach kThe GIS-based flow path analysis as the first level of detail can be used to identify the urban flooding hot spots. This allows the identification of hazardous sub-catchments in a city or high-risk private ground in a catchment quantified by the PFRIGIS. This is useful for further detailed analysis with other model approaches (e.g. 1D/2D model). The next steps are the implementation of the demonstrated framework for each level of detail in the city of Graz in Austria. Furthermore, the framework will integrate different climate scenarios based on a high-resolution climate model to address the impact of climate change on the urban drainage system quantified by the PFRIi.Keywords: urban flooding, urban flood modelling, risk assessment, future changes

Research on improving an overland flow model is presented for urban pluvial flooding under the dual-drainage concept where sewer flow dynamically interacts with overland flow. This occurs during heavy storms when the sewer system is surcharged. The system becomes pressurised and overland flow increases by the additional volume flowing out from the sewer. To represent the overland flow realistically, a new methodology was developed to automatically create the overland flow network which can interact with the drainage system. Use is made of high-resolution, accurate Digital Elevation Model data collected by the LiDAR technique. This approach updates the current urban drainage models to urban flood models with detailed representation of overland flow processes such as pond forming, flow through preferential surface pathways and surface drainage capacity. This work advances new areas of urban flood management including improvement in real-time control and of links with rainfall now-casting, and short term urban flood forecasting. The dual-drainage approach is appropriate for real-time applications.

A rapid urban flood inundation and damage assessment model

Pluvial flooding: High-resolution stochastic hazard mapping in urban areas by using fast-processing DEM-based algorithms

Integrated community-based approaches to urban pluvial flooding research, trends and future directions: A review