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Managing urban flood risk is a key global challenge of the twenty-first century. Drivers of future UK flood risk were identified and assessed by the Flood Foresight project in 2002–2004 and 2008; envisaging flood risk during the 2050s and 2080s under a range of scenarios for climate change and socio-economic development. This paper qualitatively reassesses and updates these drivers, using empirical evidence and advances in flood risk science, technology and practice gained since 2008. Of the original drivers, five have strengthened, three have weakened and 14 remain within their 2008 uncertainty bands. Rainfall, as impacted by climate change, is the leading source driver of future urban flood risk. Intra-urban asset deterioration, leading to increases in a range of consequential flood risks, is the primary pathway driver. Social impacts (risk to life and health, and the intangible impacts of flooding on communities) and continued capital investment in buildings and contents (leading to greater losses when newer buildings of higher economic worth are inundated) have strengthened as receptor drivers of urban flood risk. Further, we propose two new drivers: loss of floodable urban spaces and indirect economic impacts, which we suggest may have significant impacts on future urban flood risk. This article is part of the theme issue ‘Urban flood resilience’.

Urban pluvial flooding in China has become one of the major challenges for sustainable development. This paper analyzes the impact of climate change, urbanization, and integrated disaster drivers on urban pluvial flooding hazards, starting from the disaster-causing mechanisms of urban pluvial flooding in China. This paper then analyzes the main features and progress of urban pluvial flooding governance in China. In particular, this paper describes the progress of sponge cities in China. On the basis of the above contents, this paper describes three manifestations of the fragmentation dilemma at the level of governance, namely, fragmentation in value integration due to conflicting management orders and service values, fragmentation in resource and power allocation due to the lack of vertical top-level design and blurred horizontal departmental management boundaries, and fragmentation in policy formulation and implementation due to outdated urban flood control standards and interdepartmental information compartmentalization. In response to the fragmentation dilemma in urban pluvial flooding management in China, this paper introduces the concept of holistic governance and clarifies the path of urban waterlogging management, i.e., forming a collaborative and diversified governance subjects, deeply optimizing the organizational structure of urban waterlogging management, creating a mature information-based governance platform, and improving the legal and rule of law construction model. This paper is informative for understanding the governance of urban pluvial flooding in China from a government-led management level.

Appropriately characterizing future changes in regional-scale precipitation requires assessment of the interactive effect owing to greenhouse gas-induced climate change and the physical growth of the built environment. Here we use a suite of medium resolution (20 km grid spacing) decadal scale simulations conducted with the Weather Research and Forecasting model coupled to an urban canopy parameterization to examine the interplay between end-of-century long-lived greenhouse gas (LLGHG) forcing and urban expansion on continental US (CONUS) precipitation. Our results show that projected changes in extreme precipitation are at least one order of magnitude greater than projected changes in mean precipitation; this finding is geographically consistent over the seven CONUS National Climate Assessment (NCA) regions and between the pair of dynamically downscaled global climate model (GCM) forcings. We show that dynamical downscaling of the Geophysical Fluid Dynamics Laboratory GCM leads to projected end-of-century changes in extreme precipitation that are consistently greater compared to dynamical downscaling of the Community Earth System Model GCM for all regions except the Southeast NCA region. Our results demonstrate that the physical growth of the built environment can either enhance or suppress extreme precipitation across CONUS metropolitan regions. Incorporation of LLGHGs indicates compensating effects between urban environments and greenhouse gases, shifting the probability spectrum toward broad enhancement of extreme precipitation across future CONUS metropolitan areas. Our results emphasize the need for development of management policies that address flooding challenges exacerbated by the twin forcing agents of urban- and greenhouse gas-induced climate change.

Recent studies have demonstrated the effectiveness of low impact development (LID) in preventing urban flooding in urban catchments. Majority of the past research focuses on the overall effects of LID on urban flood reduction in various configurations. However, how urban drainage system (UDS) performance changes at spatial scale under LID effectiveness within urban catchment is rarely explored. This study evaluates performance of UDS under different spatial placement strategies of LID to understand how urban flood dynamics of drainage system changes at catchment and local-scales. A practical UDS in China was chosen as a case study and divided into three sections (upstream, center, and downstream), with a combination of four LID practices installed on one of these sections or the entire catchment under six different rainfall scenarios and five different setting scales. An evaluation of individual LID practices demonstrated bioretention cell takes first place, followed by rain garden and green roof, and permeable pavement ranked at last place based on their overall performances. Results also confirmed the significant impact of the placement location of LID on UDS performance. Uniform placement strategy proves to be the best among four strategies because of the maximum potential for flood mitigation and improvement of UDS performance. Other investigated spatial placement strategies have approximately similar performances but are relatively poorer compared to the uniform strategy. Furthermore, the placement of LID facilities nearer to the flooded locations maximizes the benefits in terms of flood reduction and also reduces probability of transferring hydraulic load to other parts of UDS.

Urban flooding is a pervasive global risk, posing a great challenge to urban planners, policymakers, and particularly communities. This paper reviews the literature to analyze how urban flooding is defined across scientific disciplines. Our objectives are to uncover the elements used to define urban flooding and evaluate how these elements can impact future research and practice. A key difficulty is the lack of a consistent, comprehensive definition that captures both physical and social dimensions of urban flooding. Current definitions often focus solely on physical aspects (e.g., rainfall, infrastructure) or social impacts, rarely integrating both. This fragmentation hinders effective flood risk management and interdisciplinary collaboration. Our contribution is a multifaceted definition incorporating spatial and social concerns, including water origins, built environment characteristics, and local community aspects. We introduce the ‘Urban Water Transect’ concept to illustrate the continuum of flood risk across urban zones, addressing a gap in the literature. The analysis reveals that many papers discuss flooding causes without providing an explicit definition. Urban flooding is predominantly defined based on water source, imperviousness, and drainage infrastructure. Future research should adopt an interdisciplinary perspective considering both physical and social aspects, potentially transforming urban flood risk management.

Urban flooding intensifies with escalating urbanization. This study focuses on Xiong'er river as the study area and couples a 1D/2D urban flooding model using InfoWorks ICM (Integrated Catchment Modeling). Ten scenarios are set respectively with a rainfall return period of 5a 10a, 20a, 50a, and 100a, alongside rainfall durations of 1 and 24 h. Subsequently, the H-V (hazard–vulnerability) method was applied to evaluate urban flooding risk. Three indicators were selected for each of hazard factors and vulnerability factors. The relative weight values of each indicator factor were calculated using the AHP method. The result shows that (1) flood depth, rate, and duration escalate with longer rainfall return periods, yet decrease as the duration of rainfall increases; (2) as the rainfall return period lengthens, the proportion of node overflow rises, whereas it diminishes with longer rainfall durations, leading to an overall overloaded state in the pipeline network; and (3) the distribution in the research area is mainly low-risk areas, with very few extremely high-risk. Medium to high-risk areas are mainly distributed on both sides of the river, in densely built and low-lying urban areas. This study demonstrates that the model can accurately simulate urban flooding and provide insights for flood analyses in comparable regions.

Flooding area records have been available since 1993 in Japan; however, there have been no studies that have utilised these records to elucidate urban pluvial flooding formation mechanisms. Therefore, frequent urban pluvial flooding areas using 20 years of urban pluvial flooding area records during 1993–2012 were identified and analysed using the principal component analysis of their topographical characteristics in Osaka and Nagoya Cities, Japan. The results showed that the topographical characteristics of the frequent urban pluvial flooding areas in both cities were different, with particularly conflicting trends in principal component 1. Furthermore, the urban pluvial flooding in Osaka City could not be described solely by topographical characteristics, and the influence of anthropogenic factors such as dominant structures that may influence inundated water flows in and around frequent urban pluvial flooding areas and stormwater drainage improvements on the occurrence of urban pluvial flooding were shown to be influential. In addition, most of the frequent urban pluvial flooding areas in Nagoya City were located on almost no gradient with a slope of less than 1 degree, and thus, the mere presence of dominant structures around it would dam up the inundated water and cause urban pluvial flooding. The results of this study quantitatively showed the paradigm shift of urban pluvial flooding factors from topographical characteristics to anthropogenic characteristics by the statistical analysis of newly defined urban pluvial flooding frequency areas.

In this study, we present the first findings of the potential utility of miniaturized light and detection ranging (LiDAR) scanners mounted on unmanned aerial vehicles (UAVs) for improving urban flood modelling and assessments at the local scale. This is done by generating ultra-high spatial resolution digital terrain models (DTMs) featuring buildings and urban microtopographic structures that may affect floodwater pathways (DTMbs). The accuracy and level of detail of the flooded areas, simulated by a hydrologic screening model (Arc-Malstrøm), were vastly improved when DTMbs of 0.3 m resolution representing three urban sites surveyed by a UAV-LiDAR in Accra, Ghana, were used to supplement a 10 m resolution DTM covering the region’s entire catchment area. The generation of DTMbs necessitated the effective classification of UAV-LiDAR point clouds using a morphological and a triangulated irregular network method for hilly and flat landscapes, respectively. The UAV-LiDAR data enabled the identification of archways, boundary walls and bridges that were critical when predicting precise run-off courses that could not be projected using the coarser DTM only. Variations in a stream’s geometry due to a one-year time gap between the satellite-based and UAV-LiDAR data sets were also observed. The application of the coarser DTM produced an overestimate of water flows equal to 15% for sloping terrain and up to 62.5% for flat areas when compared to the respective run-offs simulated from the DTMbs. The application of UAV-LiDAR may enhance the effectiveness of urban planning by projecting precisely the locations, extents and run-offs of flooded areas in dynamic urban settings.

At present, urban flood risk analysis and forecasting and early warning mainly use numerical models for simulation and analysis, which are more accurate and can reflect urban flood risk well. However, the calculation speed of numerical models is slow and it is difficult to meet the needs of daily flood control and emergency. How to use artificial intelligence technology to quickly predict urban flooding is a key concern and a problem that needs to be solved. Therefore, this paper combines a numerical model with good computational accuracy and an LSTM artificial neural network model with high computational efficiency to propose a new method for fast prediction of urban flooding risk. The method uses the simulation results of the numerical model of urban flooding as the data driver to construct the LSTM neural network prediction model of each waterlogging point. The results show that the method has a high prediction accuracy and fast calculation speed, which can meet the needs of daily flood control and emergency response, and provides a new idea for the application of artificial intelligence technology in the direction of flood prevention and mitigation.

Cities in South Asia are experiencing storm water drainage problems due to a combination of urban sprawl, structural, hydrological, socioeconomic and climatic factors. The frequency of short duration, high-intensity rainfall is expected to increase in the future due to climate change. Given the limited capacity of drainage systems in South Asian cities, urban flooding and waterlogging is expected to intensify. The problem gets worse when low-lying areas are filled up for infrastructure development due to unplanned urban growth, reducing permeable areas. Additionally, solid waste, when dumped in canals and open spaces, blocks urban drainage systems and worsens urban flooding and waterlogging. Using hydraulic models for two South Asian cities, Sylhet (in Bangladesh) and Bharatpur (in Nepal), we find that 22.3% of the land area in Sylhet and 12.7% in Bharatpur is under flooding risk, under the current scenario. The flood risk area can be reduced to 3.6% in Sylhet and 5.5% in Bharatpur with structural interventions in the drainage system. However, the area under flood risk could increase to 18.5% in Sylhet and 7.6% in Bharatpur in five years if the cities' solid waste is not managed properly, suggesting that the structural solution alone, without proper solid waste management, is almost ineffective in reducing the long-term flooding risk in these cities.