Anatomy of Flood Risk

Flood risk and its reduction in China

A comparative study of Machine Learning and Deep Learning methods for flood forecasting in the Far-North region, Cameroon

Spatially-explicit assessment of flood risk caused by climate change in South Korea

Urban flooding is an increasingly important issue. Disaster statistics appear to show flood events are becoming more frequent, with medium-scale events increasing fastest. The impact of flooding is driven by a combination of natural and human-induced factors. As recent flood events in Pakistan, Brazil, Sri Lanka and Australia show, floods can occur in widespread locations and can sometimes overwhelm even the best prepared countries and cities. There are known and tested measures for urban flood risk management, typically classified as structural or engineered measures, and non-structural, management techniques. A combination of measures to form an integrated management approach is most likely to be successful in reducing flood risk. In the short term and for developing countries in particular, the factors affecting exposure and vulnerability are increasing at the fastest rate as urbanization puts more people and more assets at risk. In the longer term, however, climate scenarios are likely to be one of the most important drivers of future changes in flood risk. Due to the large uncertainties in projections of climate change, adaptation to the changing risk needs to be flexible to a wide range of future scenarios and to be able to cope with potentially large changes in sea level, rainfall intensity and snowmelt. Climate uncertainty and budgetary, institutional and practical constraints are likely to lead to a combining of structural and non-structural measures for urban flood risk management, and arguably, to a move away from what is sometimes an over-reliance on hard-engineered defenses and toward more adaptable and incremental non-structural solutions.

Details are given herein of the current main proposals for tidal energy provision from the Severn Estuary, in the UK, with particular emphasis being focused on the Severn Barrage project, as originally promoted by the Severn Tidal Power Group. In particular, emphasis has focused on assessing the potential hydro-environmental impacts and power outputs of a barrage across the estuary, with an unstructured grid, high resolution, model being developed and applied to the estuary to assess the implications of each of five shortlisted proposed schemes on the hydrodynamic, geomorphologic, flood risk and faecal indicator organism changes within the estuary. An outline is given of recent research on power refinements to the model to assess the options for power generation. The results show that the Severn Barrage has the potential to reduce the tidal currents in a highly dynamic estuary. This leads to the reduction of suspended sediment loads (particularly upstream of the barrage), an increase of light penetration within the water column and, potentially, an increase in the benthic bio-diversity and the level of aquatic life in the estuary. The results also show that the Severn Barrage will reduce markedly the risk of flooding upstream of the barrage and to a lesser extent downstream of the structure. In contrast the alternative options have far less impact on flood risk changes. In addition to the Severn Barrage some results are shown herein for a typical lagoon option, namely the Fleming Lagoon.

The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities, leading to severe flooding and significant economic losses for civilians. This trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians, which is often overlooked in traditional flood hazard analyses. This study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods, with a specific focus on Cúcuta, Colombia. The methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological modeling. Advanced computational algorithms for image recognition were used to measure water levels at 5‐s intervals on November 6, 2020, using drones for digital elevation model data collection. In Cúcuta, where flood risk is high and drainage infrastructure is limited, the PCSWMM (Computer‐based Urban Stormwater Management Model) was calibrated and validated to simulate extreme flood events. The model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban basin. Four return periods (5, 10, 50, 100), with extreme rainfall of 3 h, were used to estimate the variability of the risk map. The output of the model was analyzed, and an integrated and time‐varying comparison of the results was done. Results show that the regions of high‐water depth and high velocity could vary significantly along the duration of the different extreme events. Also, from 5 to 100 years return period, the percentage of area at risk increased from 9.6% to 16.6%. The pedestrian sensitivity appears much higher than the increase in velocities or water depth individually. This study identified medium to high‐risk locations, which are dynamic in time. We can conclude dynamics are spatiotemporal, and the added information layer of pedestrians brings vulnerability information that is also dynamic. Areas of immediate concern in Cúcuta can enhance pedestrian safety during flash flood events. The spatiotemporal variation of patterns requires further studies to map trajectories and sequences that machine learning models could capture.

Basin geomorphology is a complete system of landforms and topographic features that play a crucial role in the basin-scale flood risk evaluation. Nepal is a country characterized by several rivers and under the influence of frequent floods. Therefore, identifying flood risk areas is of paramount importance. The East Rapti River, a tributary of the Ganga River, is one of the flood-affected basins, where two major cities are located, making it crucial to assess and mitigate flood risk in this river basin. A morphometric calculation was made based on the Shuttle Radar Topographic Mission (SRTM) 30-m Digital Elevation Model (DEM) in the Geographic Information System (GIS) environment. The watershed, covering 3037.29 km2 of the area has 14 sub-basins (named as basin A up to N), where twenty morphometric parameters were used to identify flash flood potential sub-basins. The resulting flash flood potential maps were categorized into five classes ranging from very low to very high-risk. The result shows that the drainage density, topographic relief, and rainfall intensity have mainly contributed to flash floods in the study area. Hence, flood risk was analyzed pixel-wise based on slope, drainage density, and precipitation. Existing landcover types extracted from the potential risk area indicated that flash flood is more frequent along the major Tribhuvan Rajpath highway. The landcover data shows that human activities are highly concentrated along the west (Eastern part of Bharatpur) and the east (Hetauda) sections. The study concludes that the high human concentrated sub-basin “B” has been categorized as a high flood risk sub-basin; hence, a flood-resilient city planning should be prioritized in the basin.

A geographic information system (GIS)‐based analysis tool, the Taihu Basin Risk Assessment System (TBRAS), is developed to perform scenario analysis of future flood risk changes in the Taihu Basin. The TBRAS integrates modules of climate modelling, hydrological and hydraulic modelling, dyke reliability analysis, socioeconomic analysis, and damage assessment. The results indicate that the TBRAS can provide a broad‐scale simulation of the flooding processes and damage evaluation for the entire Taihu Basin. Future climate change by 2050 in precipitation alone can approximately result in four or five times of risk increase compared with the 2005 baseline risk. Socioeconomic changes alone can increase flood risk by four to six times. The paper reveals that, without any proactive responses, the combination of socioeconomic change, sea‐level rise, and other climate changes can substantially increase the overall flood risks to 15–37 times of the present situation. We therefore conclude that both structural and non‐structural measures for reducing flood risks are required and provide a set of response options for managing and adapting future flood risk changes.

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.

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.

Chapter 1 - Introduction

Tropical cyclones have a big impact on flood risk, and understanding how their activity interacts with population exposure under climate change is critical. Here we investigate spatiotemporal changes in flood risk using numerical models together with historical observations and future projections of tropical cyclone tracks. We find that tropical cyclone-related flood risk shifts from the Mekong Delta to the eastern lower Mekong Basin, driven by the interaction between tropical cyclones and population exposure. Historically, extreme precipitation from tropical cyclones increased flood risk in about 14% and decreased in 7% of the basin. Future tropical cyclones may increase flood risk in about 7% and reduce in nearly 18% of the basin. Moreover, population exposure growth has historically increased flood risk in 3% of the basin and is projected to result in a 1% increase. These findings highlight the complex interactions of tropical cyclone hazards and socioeconomic factors influencing flood risk.

19 - Changes in Flood Risk: Retrospective and Prospective Approach

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.

The changing frequency of extreme rain events in the past few decades over the Indian river basins (IRBs) contributed to floods and drought and resulted in economic losses and gross domestic product. In this study, we evaluated the performance of 12 Global Circulation Models from the Coupled Model Intercomparison Project Phase 6‐ experiment with India Meteorological Department observed data sets to reproduce the extreme rainfall events as well as project the changes in frequency and intensity of the hydroclimate extremes in future. We found that under low emission scenarios (SSP1‐2.6), the frequency of extreme rainfall is going to increase over the western ghat and northeast IRBs, while an increase in heavy rainfall intensity (14.3%) noticed under SSP2‐4.5 in the upper Ganga and Indus basin. Also, approximately 4%–10% of the heavy rainfall is projected to increase over the western part of IRBs during the Near (2021–2040) and Mid (2041–2060) future. The study explored the new hotspot regions for future urban flooding due to increasing pattern of heavy rainfall in future. Moreover, the lower Ganga basin will experience agricultural drought in near future due to decreasing areal mean rainfall, which needs to be seen by policymakers for managing the excess (less) water. Also, India's northern, central, and western river basins may experience more extremes under high‐emission (SSP5‐8.5) scenarios that indicate challenges to mitigation. The findings of this study highlight the importance of developing long‐term adaptation and mitigation strategies aimed at reducing hydroclimate vulnerability. It emphasizes the need to implement measures that enhance resilience and minimize risks associated with hydroclimate extremes at the basin level.