Urban Flood Disaster Research Articles

Runoff Simulation and Waterlogging Analysis of Rainstorm Scenarios with Different Return Periods on Campus: A Case Study at China University of Geosciences

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.

Resilience Assessment of Flood Disasters in Zhengzhou Metropolitan Area Based on the PSR Model

Flood disasters occur frequently and cause great losses. Improving the resilience of urban flood disasters is of great significance to improving disaster prevention and mitigation in the region. The metropolitan area is the center of regional economic development and the key to strengthening the construction of local resilience. However, there is little research on resilience in the metropolitan area. Taking nine cities in the Zhengzhou metropolitan area as the research object, this paper uses the pressure state response (PSR) model to build the evaluation system of the Zhengzhou metropolitan area’s flood disaster resilience and comprehensively uses the entropy weight method, analytic hierarchy process, kernel density estimation method, and factor contribution model to measure the temporal and spatial evolution characteristics of Zhengzhou metropolitan area’s flood disaster resilience from 2010 to 2022, excavating the development trend of the level of flood disaster resilience of members in the Zhengzhou metropolitan area, and explore the driving factors affecting the resilience of the Zhengzhou metropolitan area’s flood disaster. The results show that (1) from 2010 to 2022, the development trend of flood disaster resilience among the Zhengzhou metropolitan area members has obvious differences, the change of pressure resilience is stable, and the state resilience and response resilience increase as a whole; (2) the results show that the resilience of flood disaster in the Zhengzhou metropolitan area has obvious change characteristics in time and space, and the overall trend is to take Zhengzhou as the core to drive the surrounding members’ upward development; (3) in the driving factor analysis, the number of ordinary colleges and universities and the proportion of public security expenditure in fiscal expenditure are the main influencing factors in the resilience evaluation index. The Zhengzhou metropolitan area is the key area of economic development in Henan Province. The research results provide a reference for improving the resilience level of the Zhengzhou metropolitan area and strengthening the prevention and control of flood disasters.

Climate Change and Urban Flooding: Assessing Remote Sensing Data and Flood Modeling Techniques: A Comprehensive Review

This review critically examines the current understanding of climate change impacts on urban flooding, synthesizing recent findings to provide a comprehensive overview of how rising temperatures, sea-level rise, and increased extreme weather events influence urban floods. Additionally, it discusses various flood modeling techniques, outlining their advantages and disadvantages. Covering a broad spectrum of studies published between 2007 and 2024, selected for their relevance and methodology, this review highlights several key findings. Climate change significantly exacerbates urban flood disasters, with remote sensing emerging as an indispensable tool for climate change and flood monitoring and prediction. Despite these advancements, notable gaps remain in the literature. There is a conspicuous lack of long-term impact studies and limited discourse on the efficacy of existing mitigation strategies. Additionally, the review underscores the deficiency of real-time flood monitoring systems specifically designed for urban areas. These gaps highlight an urgent need for targeted research and the development of adaptive management practices to enhance flood prediction and management in urban settings. Future research must focus on advancing real-time monitoring systems, integrating remote sensing technologies more effectively, and developing comprehensive flood models. The review also emphasizes the importance of interdisciplinary approaches that merge hydrology, climatology, urban planning, and technology. By consolidating existing research, this review serves as a valuable resource for researchers and policymakers. It underscores the critical need for innovative flood modeling techniques and adaptive management strategies to tackle the challenges posed by climate change. This synthesis not only enriches the current body of knowledge, but also provides clear directions for future investigations, emphasizing the imperative for improved prediction, preparedness, and response mechanisms in urban flood management.

EVALUACIÓN EN LA NUBE DE LA CAPACIDAD DE GESTIÓN DE EMERGENCIAS DEL GOBIERNO ANTE CATÁSTROFES POR INUNDACIONES URBANAS: DATOS DE CHINA

A relevant evaluation index system was established in this study for the objective measurement of emergency management capability for urban flood disasters based on the four stages of emergency response, namely, “prevention, early warning, response, and recovery.” The weight distribution of different evaluation indices was calculated by using the CRITIC method, which generated an evaluation cloud and a result cloud based on the cloud model. A case study on the emergency management of Zhengzhou City in Henan Province of the “7.20 Flood Disaster” was conducted, and the evaluation results were displayed intuitively as the digital features of the cloud model and in the computational cloud diagrams. The evaluation results of the emergency management capability of Zhengzhou City for the “7.20 Flood Disaster” were obtained, and a new direction for emergency management capability improvement was proposed based on a capability enhancement priority matrix. Results showed that Zhengzhou City exhibited only the “simple level - system management mode” in coping with the “7.20 Flood Disaster.” Zhengzhou City can improve its emergency management capability against flood disasters by improving the reliability of its monitoring and communication systems, the effectiveness of its publicity and education measures, and the timeliness of its provision of postdisaster information statistics and reports. The conclusions disclose a new direction for the scientific judgment of emergency management capability for flood disasters and the formulation of capability enhancement strategies. Key Words: Flood disasters; emergency management capability; cloud model; CRITIC method; capability enhancement matrix

Urban Flooding Disaster Risk Assessment Utilizing the MaxEnt Model and Game Theory: A Case Study of Changchun, China

This research employs the maximum entropy (MaxEnt) model alongside game theory, integrated with an extensive framework of natural disaster risk management theory, to conduct a thorough analysis of the indicator factors related to urban flooding. This study conducts an assessment of the risks associated with urban flooding disasters using Changchun city as a case study. The validation outcomes pertaining to urban flooding hotspots reveal that 88.66% of the identified flooding sites are situated within areas classified as high-risk and very high-risk. This finding is considered to be more reliable and justifiable when contrasted with the 77.73% assessment results derived from the MaxEnt model. Utilizing the methodology of exploratory spatial data analysis (ESDA), this study applies both global and local spatial autocorrelation to investigate the disparities in the spatial patterns of flood risk within Changchun. This study concludes that urban flooding occurs primarily in the city center of Changchun and shows a significant agglomeration effect. The region is economically developed, with a high concentration of buildings and a high percentage of impervious surfaces. The Receiver Operating Characteristic (ROC) curve demonstrates that the MaxEnt model achieves an accuracy of 90.3%. On this basis, the contribution of each indicator is analyzed and ranked using the MaxEnt model. The primary determinants affecting urban flooding in Changchun are identified as impervious surfaces, population density, drainage density, maximum daily precipitation, and the Normalized Difference Vegetation Index (NDVI), with respective contributions of 20.6%, 18.1%, 13.1%, 9.6%, and 8.5%. This research offers a scientific basis for solving the urban flooding problem in Changchun city, as well as a theoretical reference for early warnings for urban disaster, and is conducive to the realization of sustainable urban development.

Projecting urban flood risk through hydrodynamic modeling under shared socioeconomic pathways

Under future climate change, accurate risk assessment of urban flooding disasters is paramount for effective adaptation and mitigation strategies. However, conventional indicator-based assessment methods often fall short of accurately capturing the complexity of flooding dynamics. Current research predominantly focuses on predicting future hazard shifts while overlooking changes in other critical indicators. In this study, we establish a comprehensive index system for risk assessment, and quantified future changes in most indicators, utilizing the InfoWorks ICM model for hazard simulation and the CLUMondo model for land use predictions. Based on risk assessment results and regional characteristics, we further analyze the key factors driving future risk and discuss corresponding measures. The results indicate an exacerbation of future urban flood risk, with an 18% increase in high risk areas, primarily concentrated in the center of the study area. The dominant indicators are inundation depth and land use over the whole study area. However microtopography significantly affects risk in low-lying areas. Overall, under higher emission scenarios, the influence of GDP and population rises. These findings offer methodological insights for future urban flood risk assessment research and provide policymakers with valuable guidance to develop targeted adaptation measures in response to climate change.

Dynamic vulnerability assessment framework for urban flood disasters considering real-time population changes

ABSTRACT Flood vulnerability assessment is an important means to cope with urban flood disasters. However, urban population mobility and land-use changes bring significant uncertainty to vulnerability assessments. In order to respond to the refined and dynamic needs of urban flood disaster prevention and control, a multi-scale and multi-categorized urban flood dynamic vulnerability assessment framework that considers real-time population changes was proposed in this study. The framework used the comprehensive function of exposure, sensitivity, and coping ability under population dynamic changes to characterize urban flood dynamic vulnerability, and constructed urban flood disaster vulnerability assessment models at both grid and regional scales. The results show that population mobility has a significant impact on the vulnerability of urban flood disasters. The vulnerability of flood disasters in Zhengzhou City is highest at 8:00 and 18:00, and high-vulnerability areas are mainly concentrated in residential areas in the central part of the city and main transportation channels. From 10:00 to 15:00, the high-vulnerability areas migrate to public service areas in the eastern part of Zhengzhou City. In the evening, the vulnerability degree of flood disasters is relatively low. The research results can provide a theoretical basis for urban flood managers to prevent and control flood disasters.

Analysis of Short-Term Heavy Rainfall-Based Urban Flood Disaster Risk Assessment Using Integrated Learning Approach

Accurate and timely risk assessment of short-term rainstorm-type flood disasters is very important for ecological environment protection and sustainable socio-economic development. Given the complexity and variability of different geographical environments and climate conditions, a single machine learning model may lead to overfitting issues in flood disaster assessment, limiting the generalization ability of such models. In order to overcome this challenge, this study proposed a short-term rainstorm flood disaster risk assessment framework under the integrated learning model, which is divided into two stages: The first stage uses microwave remote sensing images to extract flood coverage and establish disaster samples, and integrates multi-source heterogeneous data to build a flood disaster risk assessment index system. The second stage, under the constraints of Whale Optimization Algorithm (WOA), optimizes the integration of random forest (RF), support vector machine (SVM), and logistic regression (LR) base models, and then the WRSL-Short-Term Flood Risk Assessment Model is established. The experimental results show that the Area Under Curve (AUC) accuracy of the WRSL-Short-Term Flood Risk Assessment Model is 89.27%, which is 0.95%, 1.77%, 2.07%, 1.86%, and 0.47% higher than RF, SVM, LR, XGBoost, and average weight RF-SVM-LR, respectively. The accuracy evaluation metrics for accuracy, Recall, and F1 Score have improved by 5.84%, 21.50%, and 11.06%, respectively. In this paper, WRSL-Short-Term Flood Risk Assessment Model is used to carry out the risk assessment of flood and waterlogging disasters in Henan Province, and ArcGIS is used to complete the short-term rainstorm city flood and waterlogging risk map. The research results will provide a scientific assessment basis for short-term rainstorm city flood disaster risk assessment and provide technical support for regional flood control and risk management.

Runoff Control Performance of Three Typical Low-Impact Development Facilities: A Case Study of a Community in Beijing

The development of sponge cities advocates for sustainable urban rainwater management, effectively alleviating urban flood disasters, reducing non-point-source pollution, and promoting the recycling of rainwater resources. Low-Impact Development (LID) serves as a key strategy in this context, providing essential support for urban rainwater control and pollution reduction. To investigate the runoff control effects of LID measures and to reveal the relationship between facility runoff control performance and installation scale, this study focuses on a sponge community in Beijing. A SWMM model was constructed to analyze the rainwater flood control and pollutant load reduction effects of different LID facilities, including bio-retention cells, green roofs, and permeable pavements. Using evaluation indicators such as surface runoff, node overflow, and pollutant control rates, this study examined how facility performance varies with installation scale under different rainfall conditions. The combination scheme of LID equipment optimal configuration is designed by using multiple criteria decision analysis (MCDA) and cost–benefit theory. The results indicate significant differences in performance among the various LID facilities across different rainfall scenarios. Specifically, the optimal installation proportion for runoff and overflow control of permeable pavements were found to be between 30% and 70%. Green roofs demonstrate superior performance in handling extreme rainfall events, while bio-retention cells exhibit significant effectiveness in controlling Total Suspended Solids (TSSs). Through comprehensive performance evaluation, this study identified the optimal combination scale under a 3-year rainfall recurrence interval as 30% permeable pavements, 20% green roof, and 60% bio-retention cells. This combination effectively leverages the strengths of each facility, ensuring system stability and efficiency while also demonstrating optimal management efficiency in cost–benefit analyses. The findings of this research provide valuable insights for future urban water management and infrastructure development.

Analysis on the ‘Jul.20’ extreme rainstorm and flood control countermeasures in Zhengzhou, China

ABSTRACT The Jul.20 extreme rainstorm (July 20, 2021) and flood disaster were the most serious urban flood disaster in Zhengzhou, the capital city of Henan Province, China. The Jul. 20 extreme rainstorm had both extreme and unpredictable features, during which both single-day and 3-day cumulative rainfall exceeded the historical records. First, the theoretical analysis methods are proposed, which include rainstorm anomaly analysis and the construction of a rainstorm frequency calculation model. Second, the characteristics of rainstorm frequency and recurrence, spatial and temporal distribution, and formation mechanism are analyzed. Third, urban flood disasters and waterlogging distribution are studied. The studied results show that the coupling actions of typhoons, topography, and urban rain island effect are the natural causes that result in extreme rainstorm weather processes. The results also show from the investigations that poor urban drainage infrastructure, low flood control criteria, shortage of flood emergency plans, and management are human factors. Finally, the paper puts forward flood control countermeasures.

A multicriteria decision model to improve emergency preparedness: Locating-allocating urban shelters against floods

The increasing prominence of natural disasters in recent years has made emergency disaster management one of the main challenges for building resilient societies. This way, the warming combination with human-induced urban interventions with climate change reshapes the strategic decision-making that public managers must deal with to promote safety and preparedness. Consequently, it implies complex situations under uncertainty that comprise conflicting dilemmas about which decision-makers (DMs) should establish trade-offs. Given this backdrop, this work proposes a risk-based multidimensional model for assessing urban shelter location against flood risk with Decision Analysis and Multi-Attribute Utility Theory. By using principles of the Queue Theory, the decision model undertakes four criteria that measure in a probabilistic manner the alternatives’ performance when considering urban flood disaster evacuation routes in affected areas. Altogether, it enables the DM to establish his/her preferences with views to rank potential locations for mounting temporary shelters and for planning emergency preparedness in risky areas. Being replicable to any urban context, our proposal has the potential to support and promote the development and implementation of crisis protocols consisting of measures to reduce flood impacts and adapt critical areas to climate change. From a numerical application of the proposed model, the DM is encouraged to explore graphical and tabular visualization tools, as well as sensitivity analysis, to establish in strategic terms how to design and implement emergency shelters to reduce flood risks in urban areas effectively.

A new two-stage emergency material distribution framework for urban rainstorm and flood disasters to promote the SDGs

Under the coupled effects of climate change and urbanization, urban rainstorm and flood has become more frequent and intense. The effect of the flood disasters emergency response has a direct impact on the success or failure of the rescue. Emergency material distribution is one of the most critical steps in the emergency response phase and is crucial to achieve the Sustainable Development Goals (SDGs). This study proposes a two-stage emergency material distribution framework for urban rainstorm and flood disasters. The entropy weight method and technique for order preference by similarity to ideal solution (EWM-TOPSIS) was adopted to incorporate the difference in relief-demand urgency into the emergency material distribution principle. The mathematical model was established by minimizing emergency travel time, inequity and social costs (logistic costs and deprivation costs) as objective functions. The gamultiobj algorithm was used to solve the model. The proposed framework is further applied in Xi'an city of China. The results showed that the affected sites were categorized into disaster risk levels I, II and III. The Pareto solution set was obtained by optimizing each conflicting objective. The emergency material distribution plan was selected from the Pareto solution set based on the actual situation. In the plan, the flood disasters emergency travel time totaled 6.48 h, the inequity totaled 3.69, and the total social costs reached 226,584 CNY. The proposed framework is more consistent with the needs of the actual rescue by comparing the four models generated plans. Decision-makers should not only consider minimizing dispatch time and social costs, but also the trade-off between equity and prioritization of distribution. This study helps to provide new ideas for sustainable urban development and emergency management. Urban rainstorm and flood disasters change with the changing environment dynamically, and it is difficult to collect dynamic disaster information on the affected sites. Thus our further study will focus on improving the prediction accuracy of dynamic urban rainstorm and flood disasters.

A combined qualitative–quantitative method for adaptive configuration of urban flood mitigation measure

Inappropriately selecting flood mitigation measures can lead to ineffective governance and wastage of social resources. To address this issue, this research proposes a framework for adaptive configuration of urban flood mitigation measure. This framework aims to achieve a two-sided matching between the disaster reduction capacity of measures and the specific demands of the construction site. The framework was employed to the urban flood mitigation strategy in Longkungou drainage system, an optimal allocation scheme for addressing urban flood disasters under the design rainfall with 50-year return period was determined. The results revealed that green mitigation measures are primarily concentrated in the drainage system within the upstream catchment. Stormwater pumping stations are mainly situated at the drainage outlets and adjacent river channels in the study area. By reducing the water level in the river channel, these stations effectively prevent and manage flood volume resulting from river overflow. As a result of the flood mitigation strategy, the flood volume in the Longkungou drainage system was reduced by 591,186 m3, representing a peak total flood volume reduction rate of 42.44%. The severity of flood disasters in each sub-catchment has significantly diminished, indicating that the flood mitigation strategy has successfully achieved the desired improvement.

Knowledge Management Model for Urban Flood Emergency Response Based on Multimodal Knowledge Graphs

Recently, frequent flood disasters in China have seriously threatened economic development and public safety. This paper addresses the need for a dynamic urban flood emergency knowledge management system in emergency management departments and the lack of systematic knowledge among emergency managers regarding urban flood control. A multimodal knowledge graph-based urban flood emergency knowledge management model was constructed to enhance the decision-making capabilities of emergency management departments, improve the efficiency of public emergency evacuation, and reduce losses from urban flood disasters by analyzing the shortcomings of the existing emergency management system. An intelligent and dynamic flood emergency knowledge management model was built. This paper integrates multimodal knowledge graph technology to establish a multimodal emergency knowledge management framework for urban flood control. It develops and simulates the proposed model’s application scenarios for urban flood emergency evacuation using the Flocking algorithm on the NetLogo platform. Through simulation experiments, the practicality and effectiveness of the model in real flood disaster situations were examined, particularly in simulating crowd evacuation behavior. The study found that the model significantly improves the accuracy of information and decision-making speed during emergency responses and supports emergency management departments in conducting targeted and personalized emergency decisions. This research provides a scientific basis for emergency management departments to optimize their emergency response strategies to flood disasters and serves as a reference and example for the application of multimodal knowledge graph technology in emergency management.

Evaluation and Spatial–Temporal Pattern Evolution of Synergy Degree of Emergency Management for Urban Flood Disasters from the Perspective of Sustainable Development—The Case of Henan, China

The management of urban flood disasters is a systematic engineering project that requires a great amount of manpower, material resources, and financial resources, and the interaction and coordination degrees of various elements in the system deeply affect the efficiency of the final governance. According to the theories of synergy, composite systems, and sustainable development, this research first established an evaluation index system to determine the synergy degree of urban flood disaster emergency management from the four dimensions of prevention and preparation, monitoring and early warning, response and rescue, and recovery and reconstruction. Then, the synergy degree was explored by using the developed composite system synergy degree model on the basis of the panel data of 18 prefecture-level cities in Henan Province from 2013 to 2021, and synergy level change characteristics were analyzed from the perspectives of time and space. Finally, the obstacle degree model was applied to explore the obstacle factors affecting synergy degree development. The results showed that the overall level of the urban flood disaster emergency management coordination degree in Henan Province was relatively low, and there were significant differences in synergy among cities. Among them, 12 cities presented mild synergy, and 6 cities showed mild nonsynergy. The spatial correlation of the synergy degree was not stable, which revealed a lack of mature coordination mechanisms for flood disaster emergency management among cities. The analysis of obstacle factors showed that recovery and reconstruction subsystems were the main obstacle systems that affected the synergy degree.

Institutional vulnerability to urban flood risk management: A case study of the 7·20 flooding disaster in Zhengzhou, China

AbstractThe ‘vulnerability’ approach highlights institutional factors as the primary drivers of flooding risk. However, the intricate connections between institutional vulnerability and urban flood disaster risk have not been extensively explored until now. This study aims to address this gap by examining the case of the 7·20 heavy rainfall disaster in Zhengzhou. Employing a hybrid analysis methodology that integrates text coding, fault tree analysis and analytic hierarchy process methods, the study seeks to identify and assess the distinct contributions of various institutional factors and their interplay, culminating in ineffective urban flood risk management. In contrast to previous research findings that emphasize the determinant role of policy‐making and organizational coordination, this study demonstrates that inadequate legislative compliance constitutes the root cause determining the ineffectiveness of urban flood risk management. It is further exacerbated by insufficient policy attention, resulting in inadequate allocation of resources that ensure the legislative quality, risk coping skills and knowledge and stakeholders' coordination and collaboration. By emphasizing the significance of legislative compliance and policy attention, the study offers a fresh conceptual perspective to understand the factors influencing the efficiency of urban flood risk management. It provides valuable insights to develop targeted countermeasures for mitigating similar urban flood risks in the future.

Application of pervious concrete pavement in the "breathe in-breathe out" design for sponge cities in China.

Sponge city construction is an ideal approach to mitigate the degradation of urban water environments. Among road materials, permeable concrete pavement stands out due to its unique structure that allows rainwater runoff to flow through its pores. This paper analyzes the current application status and the prospect of different permeable pavement designs in China's sponge cities, aiming to offer valuable insights for urban planning and construction. Statistical analysis summarizes the spatial-temporal distribution patterns of urban flooding disasters in China and their causes. By comparing the characteristics and advantages of pervious concrete pavement with traditional concrete pavement, the potential of permeable concrete pavement in sponge city construction is summarized through case studies. The findings highlight that by adjusting the pore size, permeable concrete pavement can collect rainwater while filtering impurities, thereby purifying surface runoff. The range of the pervious coefficient should ideally fall within the range of 4~8 mm/s. In addition, the pavement's large contact area with the air and internal water evaporation contributes to its self-regulating capability, reducing the occurrence of extreme temperatures. Related experiments have shown that from 8 am to 12 pm, pervious concrete pavement can reduce the temperature by approximately 1 °C compared to conventional concrete. From 12 pm to 8 pm, this temperature difference increases to approximately 3 °C. To meet the needs of environmental protection and resource utilization, permeable concrete pavement can serve as an ideal tool to achieve green and low-carbon development.

Sponge City Development from the Perspective of Sustainability: A Case Study of China

Traditional urban construction methods often result in the inability of rainwater to penetrate and store effectively, increasing the risk of urban flooding disasters. At the same time, due to the rapid development of urbanization, the problem of water shortage has become increasingly prominent. The sponge city policy aims to transform the urban construction mode, make full use of natural resources and ecological means, realize the natural accumulation, infiltration and purification of rainwater, and improve the city's absorption, storage and release capacity of rainwater, so as to reduce urban flood disasters and alleviate the shortage of water resources. This paper takes China as an example to explore the construction of a sponge city from the perspective of sustainable development. This paper analyzes the current situation and existing problems of sponge cities development in China, and puts forward the development prospect of PPP model, in order to promote sponge cities construction and sustainable urban development.

Flood Disaster Risk Assessment in Wuhan City Based on GIS Analysis and Indicator Ranking Using Random Forest

In recent years, with the acceleration of urbanization and the frequent occurrence of extreme weather globally, the risk of urban flood disasters has gradually increased, and its potential consequences are immeasurable. Therefore, conducting risk assessment of urban flood disasters is of great significance, as it is one of the foundations and decision-making means for Disaster Prevention and Mitigation, and has become a hot topic and trend in current research. This paper starts by exploring the concept and formation mechanism of urban flood disasters, taking Hazard Factors, Disaster-prone Environment sensitivity, Vulnerability of Exposed Bodies, and Disaster Prevention and Mitigation Capabilities as primary indicators. Based on this, a risk assessment index system is established with 14 secondary indicators, such as annual average rainfall, distance to water systems, elevation, and terrain undulation. The spatialization of each indicator data point is processed through ArcGIS10.7, and the importance of hazard and sensitivity indicators is ranked using the Random Forest algorithm. The indicators are then weighted using a combination of the Analytic Hierarchy Process (AHP) and the entropy method, and the combined weights of each assessment indicator are calculated. Taking Wuhan City as the research area, the weights of each indicator are input into the established risk assessment model. ArcGIS spatial analysis techniques and raster calculation functions are utilized to solve the fuzzy comprehensive evaluation of the assessment model, obtaining zoning maps of risk levels for hazard, sensitivity, vulnerability, disaster prevention, and mitigation capabilities, as well as the distribution of comprehensive risk levels. The validity and rationality of the model results are verified by actual disaster data, providing important reference for urban flood disaster prevention in the future.

Development of an Integrated Urban Flood Model and Its Application in a Concave-Down Overpass Area

Urban floods caused by extreme rainstorm events have increased in recent decades, particularly in concave-down bridge zones. To simulate urban flooding processes accurately, an integrated urban flood model (IUFM) was constructed by coupling a distributed urban surface runoff model based on the cellular automata framework (CA-DUSRM), a widely used pipe convergence module in the storm water management model (SWMM), with an inundation module that describes the overflow expansion process associated with terrain and land-cover. The IUFM was used in a case study of the Anhua Bridge (a typical concave-down overpass) study area in Beijing, China. The spatial-temporal variations in flood depth modeled by the IUFM were verified to be reliable by comparison with actual measurements and other simulations. The validated IUFM was used to obtain temporal variations in flood range, depth, and volume under four rainstorm scenarios (return periods of 3-year, 10-year, 50-year, and 100-year). The results showed that the surface runoff process, overflow from drainage networks, and overflow expansion process could affect the flooding status by changing the composition and spatial configuration of pervious or impervious patches, drainage capacity, and underlying surface characteristics (such as terrain and land-cover). Overall, although the simulation results from the IUFM contain uncertainties from the model structures and inputs, the IUFM is an effective tool that can provide accurate and timely information to prevent and control urban flood disasters and provide decision-making support for long-term storm water management and sponge city construction.