A modelling framework to assess urban flood risk on the city scale

The phenomenon of urban flooding due to rainfall exceeding the design capacity of drainage systems is a global problem and can have significant economic and social consequences. This is even more extreme in developing countries, where poor sanitation still causes a high infectious disease burden and mortality, especially during floods. At present, there are no software tools capable of combining hydrodynamic modelling and health risk analyses, and the links between urban flooding and the health risk for the population due to direct contact with the flood water are poorly understood. The present paper outlines a novel methodology for linking dynamic urban flood modelling with quantitative microbial risk assessment (QMRA). This provides a unique possibility for understanding the interaction between urban flooding and health risk caused by direct human contact with the flood water and hence gives an option for reducing the burden of disease in the population by use of intelligent urban flood risk management. The model linking urban flooding and health risk is applied to Dhaka City in Bangladesh, where waterborne diseases including cholera are endemic. The application to Dhaka City is supported by measurements of pathogens in the urban drainage system. The outcome of the application indicates that direct contact with polluted flood water is a plausible route of primary transmission of cholera and demonstrates the applicability and the potential for linking urban flood models with QMRA in order to identify interventions to reduce the burden of disease on the population in Dhaka City.

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.

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.

Within urban centres, underground spaces such as storage areas, transportation corridors, basement car parks, public facilities, retail & office as well as private spaces (e.g., residential basements), present priority risk areas during flood events with respect to timely evacuation.  However, often the location, geometry and volume of these underground spaces is not well known.  Furthermore, these underground spaces are commonly not considered in flood prediction models for urban centres.  At the same time, communicating flood risks and enhancing emergency preparedness poses further challenges.  Thus emergency planners need engaging communication tools to increase community resilience and preparedness to flooding events. Low-cost Mobile Laser Scanning (MLS) and Airborne Laser Scanning (ALS) technologies as well as other remote sensing applications and street view imagery data are becoming increasingly available and affordable, providing high-resolution data for the urban environment.  The presented project focusses on gaining better knowledge of the location and internal geometry of underground spaces in urban centres by using low-cost MLS data. The presented project is developing efficient database approaches to handle the large data sets and to integrate the information into flood prediction models.  These models provide refined information on urban flood levels and flooding rates into the underground spaces, which in turn may be used as part of risk communication tools using low-cost virtual reality applications which provide an immersive experience of flood risk with the aim to better engage communities in emergency preparedness.  The comparison of rapid low-cost high-resolution terrestrial MLS with ALS data for an urban case study site in Belfast (Northern Ireland) highlights the advantages of the rapid low-cost MLS approaches and their use for the detection and surveying of urban underground spaces and the integration of these identified priority flood risks into urban flood models.  Incorporating the identified underground spaces provides more realistic inundation scenarios and enhanced information with regard to accessible evacuation routes to inform flood risk mitigation plans.

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA), Directly Connected Impervious Area (DCIA), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Qt and Qp; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management.

Flood risk and its reduction in China

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.

A rapid urban flood inundation and damage assessment model

Dhaka, the capital city of Bangladesh, is one of the most densely populated cities in South Asia. Urban flooding from extreme rainfall is a recurring phenomenon, with historic floods in 1988, 1998, and 2004 amongst the most catastrophic events in Dhaka. Prolonged urban flooding or water logging is a major concern for both Dhaka North City Corporation (DNCC) and Dhaka South City Corporation (DSCC) areas. This research investigates how “Citizen Science (CS)” could help individuals, communities, and stakeholders understand and manage the risk of current and future urban flooding, integrating formal flood risk management along with the affected area’s respondents’ self-perceived perception, concerns, experience, awareness, and opinions about flood risk management, and ability to cope with the flood risk. Fieldwork data were collected through the administration of a purposely designed questionnaire to 500 respondents in the water logging affected wards of the two city corporations’ areas in Dhaka. Preliminary findings from the fieldwork revealed that every year approximately 45.6% and 29.4% respondents in the study area experienced 1-3 days of urban flooding/water logging, mostly during the monsoon season (June – September), with a work time loss of 3-4 hours respectively. Respondents in the study area are aware and concerned about flooding and its associated risk, and approximately 36.9% respondents think that the frequency of urban flooding will increase in Dhaka in the next 10 years. In terms of the vulnerability, approximately 51.5% respondents mentioned that they are vulnerable to urban flooding and small business holders (Entrepreneurs) are most affected (61.5% respondents) by flooding. Although almost 61.2% respondents were not familiar with the “Citizen Science” concept, but approximately 42.8% of respondents expressed an eagerness to involve themselves in any Citizen Science based project to promote awareness and mitigation of urban flood risk/water logging issues in their community or in Dhaka City. In addition, preliminary findings from Key Informant Interviews (KII) and Focus Group Discussion (FGD) Meetings suggested that unplanned urbanisation, poor and inadequate drainage system management, and recent extreme rainfall events were the major drivers behind the urban flooding/water logging situation in Dhaka.The study also explored annual and seasonal trends of rainfall in Dhaka (using observed datasets from the Bangladesh Meteorological Department) over the period from 1953-2019 using extreme precipitation indices [Climate Change Detection and Indices (ETCCDI)]. It is revealed that over these 67 years, Annual Maximum Daily Rainfall has increased during winter (0.021 mm/year) but statistically significantly decreased during the monsoon (-0.636 mm/year). The overall annual rainfall has significantly decreased (-0.718 mm/year). Trends in Consecutive Dry Days, heavy, and very heavy precipitation days indicate an annual increasing rate of 0.158 days/year for CDD, 0.077 days/year with >= 10 mm rainfall and 0.019 days/year with >= 20 mm rainfall, respectively. Results from the rainfall datasets are now being integrated with the fieldwork findings and other secondary datasets to set up a Hydrodynamic Model (CityCAT) to investigate current and future flood risk in Dhaka in more detail.

Innovative solutions are needed for urban flooding exacerbated by climate change. In light of this, this study developed an integrated framework for urban wetland flood control that combines Morphospatial Pattern Analysis (MSPA), minimum cumulative resistance (MCR) modeling, and complex network theory for optimizing an ecological network of flood control and mitigation wetlands in Changchun, China. The results show that the optimized ecological network significantly improved connectivity and flood mitigation efficiency. The node degree increased from 2.737 to 3.433, and the average clustering coefficient exhibited an increase from 0.074 to 0.231, enhancing material flow efficiency. Robustness analysis revealed that the optimized network’s connectivity robustness improved by 12.6%, 18.4%, and 24.1% under random, malicious, and controlled attack scenarios, respectively. Additionally, ecological corridors with a width of 30–50 m were identified as the optimal range for water conveyance potential, effectively dispersing peak runoff and reducing flood risk. This study provides both a transferable methodology for flood-resilient planning and specific policy actions, including priority conservation of high-betweenness nodes and restoration of fragmented wetlands, offering practical solutions for high-density cities facing similar climate challenges.

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

Urban pluvial flooding is a modern, growing global disaster, particularly in developing countries with inadequate infrastructure. It remains a challenge to accurately model the runoff behavior in urban areas with a complex topography and to quantify the impact of spatial urban patterns on changing urban rainfall-runoff response. The question to be addressed is how varying the urban spatial configurations can quantitatively influence the overland flow response in relation to the spatiotemporal hydrodynamic variables such as water depth, velocity, and outflow discharge. We use a 2D shallow water model to indicate the influence of changing spatial urban factors (such as the orientation of streets and buildings, and adding sidewalks) in small idealized (synthetic) urban catchments during a single pluvial flood event. The domain layout extends over a size of 267.5m*267.5m with a 3% longitude slope. We differentiate mainly between two street networks: i) the two-way main street with of 14-m width with sidewalks, and ii) side streets of 10m width (Fig.1). We then define novel spatially integrated indicators over the domain at the steady state to analyze quantitatively runoff variables in correlation with the urban features (Fig.1). Additionally, local hotspot maps were created to assess the flood-risk thresholds, such as human stability and failure of buildings. Hotspots are defined as the places with the highest flow velocity magnitudes and water depths (> 90%). The results of the modeling showed that, with respect to the flow velocities in small-scale urban catchments, the main street layout is the dominant urban factor, followed by the side street widths, which were decisively determined by the geometry of the sidewalks. The comparison with real flood risk thresholds shows that the lower part of the main road is the most sensitive to flood risk in the domain with a high-risk hazard for human stability. However, the riskiest case is not corresponding to the fastest hydrograph response. Varying the spatial urban configurations, especially the rotation of the main roads, changes the flood risk thresholds and delays runoff. On the other hand, spatially integrated indicators of the flow variables in the domain are showing low sensitivity to the spatial urban features. Our findings offer a new important perspective on the development of urban flood risk assessment, especially for rapidly urbanizing cities, and provide a better understanding of the spatiotemporal rainfall-runoff generation in a small urban catchment considering the spatial layout of the urban structures.Fig.1 Overview of the modelling approach and evaluation of the runoff data

This study applied the interaction of social vulnerability and hazard to assess flood risk in three urbanized areas within the Pasig‐Marikina‐Laguna‐Lake catchment: Manila, Marikina, and Parañaque in Metro Manila, Philippines. This study examined risk patterns across different flood return periods (5, 50, and 100 years) in these urban river environments and provided both city‐wide and localized risk assessments. The social vulnerability to flood index (SVFI) was calculated using socioeconomic indicators, while the hazard index was derived from flood depth categories. Results show that city‐level risk indices are low to moderate, with Marikina consistently having the highest risk, followed by Manila and Parañaque. However, localized assessments reveal high‐risk areas within cities, with Manila being the most vulnerable to frequent floods (5‐year return period) and Marikina to less frequent but extreme events (50‐ and 100‐year return periods). Parañaque maintains the lowest risk profile across all scenarios. This study highlights the importance of considering both citywide trends and localized high‐risk areas in flood risk management. It provides valuable insights for disaster management planners and policymakers, enabling the development of targeted strategies for sustainable urban river management and flood risk reduction in rapidly urbanizing river systems. The methodology presented applies to other urban areas that face similar flood risks.

Urban flooding presents a complex challenge driven by urbanization, changing land use patterns, and climate variability, particularly in monsoon-dominated developing countries like India. According to the WMO, the world is rapidly urbanizing, especially in the flood plains. As a result, the global population is at risk, with the number of people living in flood-prone areas rising by 24% from 58 million to 86 million between 2000 and 2015. This study develops a comprehensive methodology for flood hazard mapping in the Bagjola area( Kolkata, India), integrating Markov Chain and Cellular Automata (Markov-CA) Land Use and Land Cover (LULC) prediction models with hydrodynamic simulations. The Markov-CA model predicted the 2050 land use changes after employing the land use data from 1990, 2005, and 2020. The predicted LULC changes were incorporated into the calibrated and validated MIKE+ hydrodynamic model (2020 data) for flood simulations, and the simulation results depicted the flood hazard maps, highlighting vulnerable areas under different land use scenarios.The Markov-CA model achieved a Kappa coefficient of 0.84, indicating reasonably good agreement. The results reveal a growing trend of urbanization in the Bagjola Canal region, with 6.1% of vegetation and 29.06% of barren land projected to be urbanized by 2050 compared to 2020. Compared to the situations observed in 2020, under the future scenarios for 2050, the total flood hazard area is expected to increase by 15-40% in the Bagjola Canal region.This methodology provides a practical framework for assessing the spatial impacts of urbanization on flood risk, offering valuable insights for urban planning and flood management in rapidly developing regions. The resulting floodplain and hazard maps can assist local municipal bodies in preparing flood mitigation and evacuation plans and serve as a criterion for property insurance evaluations.

Public health risks from urban floods are a global concern. A typhoon is a devastating natural hazard that is often accompanied by heavy rainfall and high storm surges and causes serious floods in coastal cities. Affected by the same meteorological systems, typhoons, rainfall, and storm surges are three variables with significant correlations. In the study, the joint risk of rainfall and storm surges during typhoons was investigated based on principal component analysis, copula-based probability analysis, urban flood inundation model, and flood risk model methods. First, a typhoon was characterized by principal component analysis, integrating the maximum sustained wind (MSW), center pressure, and distance between the typhoon center and the study area. Following this, the Gumbel copula was selected as the best-fit copula function for the joint probability distribution of typhoons, rainfall, and storm surges. Finally, the impact of typhoons on the joint risk of rainfall and storm surges was investigated. The results indicate the following: (1) Typhoons can be well quantified by the principal component analysis method. (2) Ignoring the dependence between these flood drivers can inappropriately underestimate the flood risk in coastal regions. (3) The co-occurrence probability of rainfall and storm surges increases by at least 200% during typhoons. Therefore, coastal urban flood management should pay more attention to the joint impact of rainfall and storm surges on flood risk when a typhoon has occurred. (4) The expected annual damage is 0.82 million dollars when there is no typhoon, and it rises to 3.27 million dollars when typhoons have occurred. This indicates that typhoons greatly increase the flood risk in coastal zones. The obtained results may provide a scientific basis for urban flood risk assessment and management in the study area.