Search Results (46)

Under climate warming, frequent short-duration extreme precipitation events in coastal megacities exacerbate urban waterlogging, whereas the associated convective mechanisms over complex underlying surfaces remain poorly understood. On 21 July 2023, an extreme short-duration rainfall event (14:00–19:00 LST, peak intensity 127.3 mm h⁻¹) struck Shanghai under weak vertical wind shear (VWS) conditions that cannot be fully explained by classic storm dynamics. Based on multi-source observations, this study shows that the middle and lower troposphere was controlled by warm, moist southwesterly flows, with highly favorable thermodynamic conditions (CAPE ~3300 J kg⁻¹, CIN near zero) that only required weak local lifting to trigger convection. Both 0–1 km and 0–6 km VWS were below 7 m s⁻¹, maintaining stable, upright updrafts that favored high precipitation efficiency. The formation and maintenance of the quasi-linear convective system and the resultant extreme precipitation depended critically on the southerly sea breeze, local mesoscale convergence, and cold pool feedback. Convergence induced by the complex underlying surface (urban friction, high-rise building blocking) played important roles in initiating convective cells, while the interaction between cold pool outflows and the sea breeze from the East China Sea and Hangzhou Bay sustained the system, which evolved into a unique “fish-shaped” rainstorm. Driven by dominant convective propagation toward unstable inland areas, the system moved west–southwestward across the coastal zone into central urban Shanghai. This mechanism differs from both the cold pool–VWS balance under strong shear and the urban convective relay propagation mode under weak VWS documented in previous studies. These findings provide new observational insights into the formation and maintenance of weak-shear, short-duration extreme rainfall in coastal megacities, and carry important implications for identifying convectively prone zones, optimizing spatial development patterns, and improving climate-resilient land management and urban planning practices. Full article

The underground urban rail transit (URT) is usually vulnerable to waterlogging caused by rainstorms, and floods run into the URT systems mainly via stations. Because of the increasing rainstorms due to global warming, assessing and improving the waterlogging resilience of URT stations is essential for preventing flooding disasters in URT. Here, an entropy weight–TOPSIS method is proposed to assess the waterlogging resilience of metro stations in Changsha, China. Firstly, 20 assessment indicators were selected from stability, resistance, and recovery of the system, respectively. Then, the entropy weight method was used to determine the objective weight of each indicator, and the TOPSIS method was applied to calculate the resilience index of metro stations. The results indicate that among the 137 metro stations, there are 26 low-resilience ones, 64 medium-resilience ones, and 47 high-resilience ones. The waterlogging resilience of metro stations shows a decreasing trend from the urban periphery to the urban center, and the low-resilience stations are predominantly located in the eastern low-altitude flat areas of Changsha. Finally, the countermeasures are proposed to improve the resilience of metro stations. Full article

Urban flood information enables managers to rapidly synthesize comprehensive flood event profiles, serving as critical evidence for flood control decision making. Compared with traditional methods, public data offer unprecedented spatiotemporal granularity due to its high volume, multidimensionality, and real-time nature. In this paper, we investigated public data’s usefulness and generalizability of spatial feature differences using multi-source social media data as an entry point. We selected rainstorm events that occurred in three cities located in the North China Plain, the Southeast Coastal Region, and the Western Region of China, with vastly different developmental statuses in 2023. Then, multi-platform data from the events were collected and analyzed through crawling and topic mining. The results indicate that: (1) social media data from different sources are complementary to each other and can collectively extract plenty of neglected waterlogging points to supplement official data, with a supplementary rate reaching 171% on average; and (2) social media data has significant value in spatial characterization, which means that its availability remains constant despite geographical differences and can self-adapt to local geography, inhabitant profiles and social development levels. To address the issues of limited available data and essential information lacking during the analysis process, we propose recommendations for data processing and city managers to enhance the scientific value of social media data utilized in practice. Full article

With the accelerating pace of urbanization, cities are increasingly affected by rainstorm and flood disasters, which pose severe threats to the safety of residents’ lives and property. Existing models are increasingly inadequate in meeting the accuracy requirements for flood simulation in highly urbanized regions. Thus, it is urgent to develop a new method for flood inundation simulation based on high-resolution urban hydrological units. The novelty of the model lies in the novel structure of the high-resolution Urban Hydrological Units model (HRGM), which replaces coarse sub-catchments with a fine-grained network of urban hydrological units. The primary innovation is the node-based coupling strategy, in which the HRGM provides precise overflow hydrographs at drainage inlets as point sources for LISFLOOD-FP, rather than relying on diffuse runoff inputs from larger areas. In this paper, a high-resolution hydraulic model (HRGM) based on urban hydrological units coupled with a 2D hydrodynamic model (LISFLOOD-FP) was constructed and successfully applied in the Chebeichong watershed. Results show that the model’s simulations align well with observed data, achieving a Nash efficiency coefficient above 0.8 under typical rainfall events. Compared with the SWMM model, the simulation results of HRGM were significantly improved and more consistent with measured results. Taking the rainstorm event on 10 August 2021 as an example, the Nash coefficient increased from 0.7 to 0.85, while the peak flow error decreased markedly from 15.8% to 3.1%. It should be emphasized that urban waterlogging distribution is not continuous but appears as patchy, discontinuous, and fragmented patterns due to the segmentation and blocking effects of roads and buildings in urban areas. The framework presented in this study shows potential for application in other regions requiring flood risk assessment at urban agglomeration scales, offering a valuable reference for advancing flood prediction methodologies and disaster mitigation strategies. Full article

Against the backdrop of rapid urbanization and an increase in extreme rainfall, the impermeable expansion caused by land use changes is significantly altering the urban property convergence process and intensifying the risk of waterlogging. To reveal the impact of land use change on the urban flooding processes, this study takes the main urban area of Wuhan (MUAW) as an example. Based on land use data from 2006 and 2020, it designs rainfall events with return periods of 5, 50, and 100 years. The NewFlood two-dimensional hydrodynamic model is employed to simulate flood evolution, with results validated against flood-prone locations. Flow velocity changes at typical flood-prone points are grouped and statistically analyzed according to land use conversion types. The results showed the following: (1) Between 2006 and 2020, land use transfer in MUAW is primarily influenced by urban sprawl and cropland reduction. (2) Urban expansion led to an increase in the area and depth of rainwater accumulation during rainstorms, which was highly aligned with the direction of urban sprawl, thereby increasing the risk of urban flooding during rainstorms. (3) Land use transfer has a limited impact on the maximum water depth and flow direction in MUAW. However, it can increase peak flow velocity or shift the peak time earlier, reducing the city’s available emergency response time and increasing the difficulty of emergency response. The contribution of this paper lies in quantifying the waterlogging effect of land use change from dynamic dimensions such as “flow velocity—peak occurrence time”, providing process evidence for the assessment of urban early warning advance, the allocation of drainage capacity and land use control, and offering a reference for prioritizing the layout of nature-based solutions and green infrastructure in low-lying catchment areas and key catchment channels to reduce flood risks. Full article

Urban metro systems (UMSs) primarily consist of underground structures and are therefore highly susceptible to disasters, such as rainstorms and waterlogging. The damages caused by such events are often substantial and difficult to recover from, highlighting the urgent need to enhance the resilience of metro networks against waterlogging. Based on the principles of urban hydrology, this paper constructs scenarios to analyze the risk of waterlogging under varying rainstorm recurrence intervals and intensities. The ArcGIS geographic information system was employed to improve the existing passive inundation algorithm, enabling more accurate identification of flood-prone areas during heavy rainfall, which supports the topological modeling of UMSs. Structural connectivity was used as an external indicator of network resilience, and tools such as Gephi and NetworkX were applied to evaluate network performance. Using the Nanjing Metro as a case study, the resilience of the UMS under different risk scenarios was assessed by analyzing the impact of waterlogging events. Subsequently, recovery sequences following disruptions were prioritized to optimize post-disaster restoration, and targeted strategies for improving network resilience were proposed. The calculation results indicate that the overall resilience of the Nanjing UMS network is at a relatively high level. When connectivity is used as the performance indicator, the operating network resilience value is between 0.78 and 0.952, while the planned network resilience value is between 0.887 and 0.939. Full article

In response to the increasing frequency of urban rainstorms, this study focuses on investigating the friction coefficient related to pedestrian instability under urban road flooding conditions. The objective is to conduct an in-depth analysis of the friction coefficient between pedestrians and the ground in actual flood scenarios and its variations, providing practical data to support future pedestrian safety assessments under flood conditions. Wet friction coefficient experiments were conducted under waterlogged conditions, with real human subjects tested across various operational scenarios. A buoyancy calculation formula was introduced to explore the impact of pressure changes caused by buoyancy on the human body in water, influencing the friction coefficient. An exponential relationship between pressure and the friction coefficient was established. Furthermore, by considering factors such as outsole hardness, ground type, and pressure variations with water depth, a dynamic method for selecting the friction coefficient was proposed, offering a scientific basis for determining friction coefficient thresholds associated with pedestrian instability risks. Experimental results indicate that, in the combination of hydrophilic materials with experimental asphalt and cement pavements, the friction coefficient under waterlogged conditions is generally higher than under dry conditions. However, as pressure increases, the friction coefficient of rubber materials decreases. This study concludes that the selection of the friction coefficient in pedestrian instability analysis should be treated as a dynamic process, and relying on a fixed friction coefficient for force analysis of pedestrian instability may lead to significant inaccuracies. Full article

Currently, one of the major threats to cities is the escalating risk of flooding, which is attributed to the alteration of climate and hastened urbanization. The purpose of this study was to introduce the Strahler ordering method for simplifying drainage networks and to avoid randomness in developing flooding models. A coupled hydrodynamic model that combines SWMM and LISFLOOD-FP was developed to simulate urban inundation. Results showed that the coupled model had satisfactory applicability for waterlogging simulation. The Strahler ordering method could construct clear topological relations of the drainage network and showed good performance in drainage network simplification. Higher-density drainage networks could increase peak discharge and total volume of discharge, while decreasing the maximum water depth and the total inundation area. Taking “5.29” rainstorm events as an example, compared to Level 3, the relative rates of change in the total flow and peak flow of Level 2 and Level 1 networks are −33.18% and −23.29%. The total inundation area was decreased from 14.14 ha to 1.43 ha when the level of drainage network hierarchy was increased from Level 1 to Level 3. This study highlights the importance of re-assessment of current and future urban drainage networks for coping with the changes in urban floods induced by local and large-scale changes. Full article

The identification of waterlogging driving factors and the assessment of associated risks are of utmost importance to enable cities to sustain their development. Initially, this paper utilizes the kernel density estimation (KDE) technique to visually display the spatial distribution features of waterlogging points within the downtown region of City B. Employing a spatial analysis method, the examination through the application of Global Moran’s I reveals that the central urban area of City B exhibits a spatial clustering distribution. Moreover, nine influencing factors, including terrain characteristics, land cover features, and infrastructure construction aspects, are chosen as the elements that drive the continual occurrences of waterlogging due to rainstorms incidents. By applying the geographic detector (GD) and random forest regression (RF) models, an in-depth exploration into the agents leading to rainstorm waterlogging is conducted. The outcomes demonstrate that the surface impervious rate stands out as the primary factor. Additionally, under the geographic detector model, it has been verified that the integrated effect of two factors is more significant than that of a solitary factor, with the interaction between the surface impervious rate and community density having the most prominent influence on waterlogging situations within the investigated area. Finally, through the utilization of the random forest model, the sensitive areas inclined to experience waterlogging in the investigated area are demarcated. The findings of this research can offer valuable references for the management of urban rainstorm waterlogging as well as the sustainable development of cities. Full article

Urban flooding disasters are increasingly prevalent because of global climate change and urbanization. University campuses, as independent functional zones, exhibit complex rainfall–runoff dynamics. This study focuses on the China University of Geosciences, using data from two extremely heavy rainfall events and on-site waterlogging investigations in Wuhan in 2020 and 2021. A stormwater management model was employed to simulate campus catchment runoff and pipe network performance under rainstorm scenarios of various return periods, illustrating the spatial and temporal evolution of waterlogging on the campus. The simulation results indicate that the discharge at the main outlets aligned with rainfall patterns but exhibited a delayed response. During an overload period exceeding one hour, the ratios of overflow nodes and overloaded conduits reached 72.22% and 57.94%, respectively. Ponding was concentrated mainly in the southwest region of the campus, with the maximum ponding depth reaching 0.5 m. Future flood mitigation measures, such as enhancing permeable surfaces, upgrading pipeline infrastructure, and promoting rainwater reuse, could support the development of a “sponge campus” layout to alleviate flood pressure and enhance campus sustainability and resilience. Full article

With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. In this study, the Dongsi Community in the functional core area of Beijing was explored, and the risk assessment of high temperatures and rainstorm waterlogging was implemented at the community scale. Local navigation observations were integrated into a theoretical framework for traditional disaster risk assessment. The risk assessment indicator system for community-scale high-temperature and rainstorm waterlogging disasters was established and improved from a microscopic perspective (a total of 22 indicators were selected from the three dimensions of hazard, exposure, and vulnerability). Geographic Information Systems (GIS) technology was used to integrate geographic information, meteorological, planning, municipal, socioeconomic and other multisource information layers, thus enabling more detailed spatial distribution characteristics of the hazard, exposure, vulnerability, and risk levels of community-scale high temperatures and rainstorm waterlogging to be obtained. The results revealed that the high-risk area and slightly high-risk area of high-temperature disasters accounted for 13.5% and 15.1%, respectively. The high-risk area and slightly high-risk area of rainstorm waterlogging disasters accounted for 9.8% and 31.6%, respectively. The high-risk areas common to high temperatures and waterlogging accounted for 3.9%. In general, the risk of high-temperature and rainstorm waterlogging disasters at the community scale showed obvious spatial imbalances; that is, the risk in the area around the middle section of Dongsi Santiao was the lowest, while a degree of high temperatures or rainstorm waterlogging was found in other areas. In particular, the risk of high-temperature and rainstorm waterlogging disasters along Dongsi North Street, the surrounding areas of Dongsi Liutiao, and some areas along the Dongsi Jiutiao route was relatively high. These spatial differences were affected to a greater extent by land cover (buildings, vegetation, etc.) and population density within the community. This study is a useful exploration of climate risk research for resilient community construction, and provides scientific support for the planning of climate-adaptive communities, as well as the proposal of overall adaptation goals, action frameworks, and specific planning strategies at the community level. Full article

The impact of flooding on cities is becoming increasingly significant in the context of climate change and rapid urbanization. Based on the analysis of the land use changes and rainstorm waterlogging inundation scenarios of Jiangqiao Town from 1980 to 2020, a scenario analysis was conducted to simulate and assess the rainstorm waterlogging disaster risk in 2040 under three land use scenarios (a natural development scenario, Scenario ND; an economic growth scenario, Scenario EG; and an ecological development priority scenario, Scenario EP) and three rainstorm scenarios with return periods of 10, 50, and 100 years. The following results were found: (1) Land use change is a significant factor in the risk of urban rainstorm waterlogging disaster caused by surface runoff and inundation depth change. In particular, the resultant increase in impermeable surfaces such as residential land and industrial land and the decrease in farmland during urbanization would lead to an increase in urban rainstorm waterlogging disaster risk. (2) Under three rainstorm scenarios, the future land use exposure elements and losses are consistent in terms of spatial distribution; from 10-year to 100-year return periods, they manifest as an expansion from the south to the surroundings, especially to the central region of the study area. The locations at risk are mainly distributed in the central and southern regions of Jiangqiao Town. (3) The economic losses are different in different land use scenarios and rainstorm scenarios. In the context of rainstorm scenarios with return periods of 10, 50, and 100 years, the total losses in land use scenario ND are CNY 560 million, CNY 890 million, and CNY 1.07 billion; those in land use scenario EG are CNY 630 million, CNY 980 million, and CNY 1.19 billion; and those in land use scenario EP are CNY 480 million, CNY 750 million, and CNY 910 million. The total losses of land use EP are the lowest by comparison. So, the influence of land use change on the rainstorm waterlogging disaster risk shows obvious differences among different rainstorm scenarios. This study has important reference value for decision making on land use management and flood disaster risk management in rapidly urbanizing areas. Full article

With the increase in global extreme climate events, the frequency of urban waterlogging caused by extreme rainstorms is increasing, resulting in serious economic losses and risk to local residents. Understanding the influence of impervious surfaces on urban waterlogging is of great significance for reducing urban waterlogging disasters. Based on InfoWorks ICM, the urban waterlogging model of Lin’an City was established, and the multi-scenario design method was used to analyze the characteristics and causes of urban waterlogging under different designed rainfall return periods. The results show that the maximum stagnant water depth and area are positively correlated with the proportion of impervious surfaces and rainfall return periods. In addition, urban waterlogging is related to the fragmentation of impervious surfaces, pipeline network, and so on. Based on the findings, it is suggested that impervious surfaces should be placed upstream and along roads where feasible. It is also recommended that the aggregation of impervious surfaces is minimized to prevent urban waterlogging. The results provide technical support and reference for local governments to prevent waterlogging disasters. Full article

Climate change has resulted in an increase in extreme rainstorm events, posing the challenges of urban waterlogging and runoff pollution. Low Impact Development (LID) is widely used to address the issues above, but its effectiveness is unknown in mountainous areas. Due to a flash flood and high flood peak, storage pumping stations are also needed to drain. Thus, a framework composed of storage pumping stations and Low Impact Developments (LIDs) was proposed based on the topography and the regional upstream and downstream relationships. The water quantity in this framework is applied to YI County in Hebei Province, China. The results showed that individual LIDs effectively reduced runoff volume, with the implementation area being more crucial than the location. Combining storage pumping stations with LIDs significantly reduces peak outflow and delays it by 5 to 51 min. The combined downstream implementation of storage pumping stations and LIDs yielded the most effective results. These findings offer important insights and management strategies for controlling waterlogging in mountainous cities of developing countries. Full article

This article addresses the challenge of simulating rainstorm waterlogging in urban-scale areas where reliable drainage pipe network data are often lacking. Although methods have been developed to tackle this issue, there remains a gap in their effectiveness. We present a novel approach, the modified equivalent infiltration (MEI) method, by building upon the foundation of the Equivalent Infiltration (EI) method. This study focuses on the outer ring area of Shanghai, utilizing data from the “In-Fa” typhoon period for simulation and comparison. Our findings reveal that the MEI method, requiring the same data inputs as the EI method, surpasses its predecessor in both principle and simulation results. Additionally, the MEI method demonstrates robustness in handling rainstorm waterlogging scenarios. Full article