Urban Rainstorm Research Articles

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.

Rainstorm-induced flood risk assessment in developed urban area using a data-driven approach with watershed units

Rainstorm flooding in developed urban areas has become a global focus. This study proposes a data-driven approach to urban rainstorm flood risk assessment. In contrast to the existing research, this study focuses on terrain watersheds as an assessment unit. Using Changsha as the study area, an inventory of 238 historical rainstorm flood locations was produced using automatic web crawling and literature data mining. Subsequently, an assessment model was developed based on a Bayesian algorithm and 16 influencing factors, and its accuracy was verified using a receiver operating characteristic curve. Because underground infrastructure is prone to backflow at its entrances and exits during rainstorms, the developed model was used to assess the backflow risk of two typical underground structures subjected to three rainstorm return periods: 5 (scenario 1), 10 (scenario 2), and 100 years (scenario 3). The conclusions are as follows: (1) The proposed method has a prediction accuracy of 88 % for flood risk. The most influential factors were H11 (proportion of impervious surface), H4 (mean elevation), and H1 (rainfall), contributing 52 %, 14.3 %, and 11.9 %, respectively. (2) Watersheds are classified into “Very Low,” “Low,” “High,” and “Very High” based on the degree of flooding impact, accounting for 83.6 %, 11.9 %, 3.9 %, and 0.7 %, respectively. Watersheds classified as “Very High” are mainly distributed in the central region. (3) A total of 48 subway stations (7.9 % of the total) and 148 underground parking lots (6.5 % of the total) in the study area are located in “Very High” risk areas. (4) Compared to that in scenario 1, the proportion of underground entrances and exits with a “Very high” protection level in scenario 3 increased by approximately 10 %. In conclusion, this framework can assist urban planners in understanding the risks of urban flooding and mitigating potential flooding impacts.

The Construction of Urban Rainstorm Disaster Event Knowledge Graph Considering Evolutionary Processes

Rainstorm disasters pose a significant threat to the sustainable development of urban areas, and effectively organizing diverse information sources about them is crucial for emergency management. In light of recent advances in knowledge graph theory and application technology, their notable knowledge integration and representation capabilities may offer support for dynamic monitoring and decision-making processes concerning urban rainstorm disaster events. However, conventional models do not adequately capture the spatiotemporal characteristics of these events. To fill this gap, we analyze the essence of urban rainstorm disaster events and divide their evolution into four stages, namely, pregnant, development, continuous, and decline stages. On this basis, a multilevel knowledge representation model is proposed from four layers, which are event, object–state, feature, and relationship layers, by analyzing the components and dynamic characteristics from the mechanism of urban rainstorm disaster events. The proposed model can not only express the comprehensive structure and relationships within urban rainstorm events, but also emphasize the evolution of disaster events through a series of ordered states. Moreover, we test the utility of the constructed knowledge graph through a case study of the Zhengzhou 720 rainstorm. The case study first validates that the selected machine learning models can extract the urban rainstorm disaster event information accurately by comparing them with some mainstream models. Then, it demonstrates that the knowledge graph is practical in the field of disaster knowledge representation, and disaster condition retrieval. Additionally, since the knowledge graph can show the evolution of a disaster event throughout its full life cycle, it can promote the understanding of the mechanisms of urban rainstorm disasters and pave the way for future applications of disaster prevention and reduction.

The rainstorm waterlogging resistance of a novel fiber-reinforced self-compacting recycled pervious concrete after freeze-thaw cycles

The poor permeability of pervious concrete after freeze-thaw (F-T) cycles is a difficult issue in the face of frequent extreme rainstorms, causing urban rainstorm waterlogging problems (stagnant water depth exceeds 150 mm). A novel fiber-reinforced self-compacting recycled pervious concrete (NSPC) with low tortuosity artificial pore channel (APC) is a pervious material with high permeability and strength, and has potential application in pervious pavement at the coupling action of F-T cycles and rainstorm. In this study, the frost resistance, mechanical properties and permeability of C60 NSPC (pore diameter of 3 mm, porosity of 1.13%) with various steel fiber contents (0 vol%, 0.5 vol%, 1 vol%, 1.5 vol% and 2 vol%) were investigated, and then the rainstorm waterlogging resistance of NSPC after 300 F-T cycles was examined under 20-, 50- and 100-year rainstorm. Results showed that the macroscopic destruction of NSPC surface after F-T cycles always started near the APCs, and the existence of APCs aggravated the mass loss and the decrease of the relative dynamic modulus of elasticity. As the increase of steel fiber content, the compressive strength loss of NSPC decreased first and then increased after F-T cycles. The use of steel fiber enhanced the integrality inside the APCs of NSPC and reduced the APC clogging rate, which improved hydraulic-conductivity properties after F-T cycles. After 300 F-T cycles, NSPC with 2% steel fiber achieved an excellent rainstorm waterlogging resistance (stagnant water depth of 0 mm), regardless of the rainstorm return period. Through F-T damage analysis, in order to cope with waterlogging, the maximum FT failure thresholds of NSPC to prevent stagnant water of 50, 70 and 100 mm are 0.097, 0.125 and 0.161 respectively, equivalent to 196, 243 and 264 F-T cycles. This study designed a NSPC that can dissipate stagnant water after F-T cycles, which provided a promising route towards solving urban rainstorm waterlogging.

Study on multiscale-multivariate prediction and risk assessment of urban flood

Few studies have explored the impact of drivers on urban flood at multi-time scales, and few studies have assessed the urban flood risk based on accurate description and quantification of the intrinsic correlation between urban flood and its drivers. Therefore, this study develops a multiscale-multivariate prediction model for flood volume (FV) using wavelet transform, and a flood risk assessment model based on the joint distribution of FV and its key drivers using the Copula method. The downtown area of Zhengzhou City, a typical city in North China, is taken as the study area. The results reveal that land use change is the key driver for variation of urban rainstorm flood, and rapid urbanization led to the variation observed in 2005. The impact of land use change on FV primarily manifests at the long cycle scale, and the multiscale-multivariate prediction model demonstrates effective simulation (NSE = 0.957, R2 = 0.958, MAPE = 13.47%) and prediction capabilities (relative errors are all below 20%). Taking the FV exceeding the threshold corresponding to the frequency of 37.5% as an example, the maximum conditional risk probability under nine combinations of key drivers is 88.34%, while the minimum probability is only 6.83%, intuitively indicating the impact of rainstorm and urbanization on this risk. These findings can provide technical references for urban flood forecasting, urban water resources management and urban development planning.

A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations

Abstract The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and they improve the time and efficiency of urban flood emergency decision-making.

Urban rainstorm and waterlogging scenario simulation based on SWMM under changing environment.

Urban rainstorm and waterlogging occurred more frequently in recent years, causing huge economic losses and serious social harms. Accurate rainstorm and waterlogging simulation is of significant value for disaster prevention and mitigation. This paper proposed a numerical model for urban rainstorm and waterlogging based on the Storm Water Management Model (SWMM) and Geographic Information System (GIS), and the model was applied in Lianhu district of Xi'an city of China. Furthermore, the effects of rainfall characteristics, pipe network implementation level and urbanization level on waterlogging were explored from the perspectives of spatial distribution of waterlogging points, drainage capacity of pipe network and surface runoff generation and confluence. The results show that: (1) with the increase of rainfall recurrence period, the peak of total water accumulating volume, the average decline rate of water accumulating volume and the number of waterlogging nodes increase; (2) optimizing the pipe diameter can shorten the average overload time of the pipe network from the entire pipe network, but for a single pipe, optimizing the pipe diameter may lead to overloading of unoptimized downstream pipeline; (3) the lower the imperviousness, the less the number of waterlogging nodes and average time of water accumulating, and (4) the west, northwest and southwest areas are relatively affected by the imperviousness, only improving the underlying surface conditions has limited influence on waterlogging in the study area. This study can provide reference for urban waterlogging prevention and reduction and pipe network reconstruction.

A research on urban disaster resilience assessment system for rainstorm and flood disasters: A case study of Beijing.

Under the background of global climate change, rainstorm and flood disasters have become the most serious cataclysm. Under the circumstances of an increasingly severe risk situation, it is necessary to enhance urban disaster resilience. Based on the disaster resilience process of prevention, absorption, and enhancement, and considering the safety factors such as personnel, facility, environment and management, this paper forms a dual dimension of the urban disaster resilience assessment model covering the key elements of urban disaster response and the core capacity of urban disaster recovery. Furthermore, if taking into account the characteristics of rainstorm and flood disasters, the paper screens the key indicators to build up an assessment index system of an urban rainstorm and flood disaster. The practical application was implemented in Beijing to have an assessment of the ability to recover from rainstorm and flood disasters in all districts of Beijing. And then, some pertinent suggestions for enhancing the resilience of Beijing to rainstorm and flood disasters were proposed.

Research on urban waterlogging risk prediction based on the coupling of the BP neural network and SWMM model

Abstract Scientific and effective urban waterlogging risk prediction can help improve urban waterlogging disaster prevention capabilities. Combining the numerical simulation model with the data-driven model, the construction of the urban waterlogging risk predictive model can satisfy the prediction accuracy and improve the prediction timeliness. Thus, this paper established an urban waterlogging risk predictive model based on the coupling of the BP neural network and SWMM model, and set five input patterns, finally selected the accumulative precipitation process and precipitation characteristics as input to predict the regional waterlogging risks under different urban rainstorm scenarios. The results show that the overall performance of the pipe drainage system in the study area is lower, and it cannot resist the rainstorm with a higher return period. Moreover, the total waterlogging risk of the southern old city is higher than that of the northern new city in the study area. The calculation speed of the prediction model constructed in this paper is thousands of times higher than that of the numerical model, so the calculation speed is very fast, which meets the requirements of the forecast timeliness.

Risk Simulation of Urban Rainstorm Flood Disasters Considering Crowd Activities

Social activities have a significant impact on the rainstorm flood disaster risk. It is crucial to explore the dynamic changes of urban rainstorm flood disaster risk caused by crowd activities. In this study, a risk simulation method of urban rainstorm flood disasters is proposed, composed of an urban rainstorm flood model based on SWMM and LISFLOOD-FP and a crowd activities model based on ABM. Taking the Futian District of Shenzhen as an example, the temporal and spatial changes in rainstorm flood disaster risk for buildings and roads are analyzed under three scenarios: midnight, morning peak, and evening peak. The results show that: (1) Although the overall risk of urban rainstorm flood disasters increases as the inundation area expands, the average risks of roads and buildings increase rapidly and then stabilize during the morning peak due to commuting activities, while the average risk of roads remains high level during the evening peak due to commuting activities, while; (2) The risk of urban rainstorm flood varies significantly at different time periods. The average risk of buildings is the largest during the morning peak, about twice that during the evening peak. The number of high-risk roads during the evening peak is much higher than in the morning peak, and both buildings and roads have the least risk during midnight; (3) The spatial distribution of urban rainstorm flood disaster risk changes with the crowd activities, shifting from residential areas to industrial areas, schools, shopping malls, etc., during the morning peak, while the evening peak shows the reverse.

A System Dynamics Model of Urban Rainstorm and Flood Resilience to Achieve the Sustainable Development Goals

The combined effects of climate change and accelerated urbanization have increased the risk of urban rainstorm and flood disasters, which seriously affects the achievement of the Sustainable Development Goals (SDGs) in cities. Improving urban flood resilience is one of main ways to deal with flooding. This study established an urban rainstorm and flood resilience model to sort out the behavioral mechanisms of multiple subjects (government, flood control department, residents and media) and the internal action mechanisms from different dimensions (economic, social, natural, infrastructure and information) of urban rainstorm and flood resilience using system dynamics approach, and to investigate the urban rainstorm and flood resilience in Xi'an city. The results show that the damage losses rate reduced by 44.44%, 10.8%, 9.48% and 3.37% by improving flood resilience, resident engagement, government attention degree and information construction level, respectively. The degree of improvement of urban rainstorm and flood resilience varied for six development scenarios when predict flood resilience. The development pattern can be divided into the beginning phase, preparation phase and development phase, and three improvement strategies are proposed based on the development pattern of flood resilience. This study helps to provide refined strategies for urban rainstorm and flood resilience assessment construction.

System comprehensive risk assessment of urban rainstorm–induced flood-water pollution disasters

The urban rainstorm-induced flood-water pollution disaster is a kind of systematic risk, which may induce secondary disasters that can lead to more serious damage, so this paper first adopts the fuzzy comprehensive evaluation method to determine the flood risk by combining with the submergence depth derived from the risk field and other factors data, and then the grid environmental risk evaluation method, which is improved by increasing the induced possibility based on Bayesian theory, is used to evaluate the flood-induced water pollution risk, and the system comprehensive risk of rainstorm-induced flood-water pollution disasters is finally obtained by constructing risk level matrix, which can well depict the coupling superposition effect. Shenzhen City is selected as the study area, and the results showed that the area with high-risk of both flood and water pollution only accounts for about 0.14% of the total area, mainly distributed in the eastern junction of Longgang district and Pingshan district, where the rainstorms occur frequently and the enterprise risk sources are dense. The system comprehensive risk is mostly very low-low and very high-low, accounting for more than 76% of the total area. It is always necessary to pay attention not only to the areas with high risk level of both disasters, but also to the areas with high risk level of one disaster. The method proposed in this study can not only quantitatively reveal the formation of the induced risk, but also provide reference for early warning.

Regional geographical and climatic environments affect urban rainstorm perception sensitivity across China

Extreme weather events become more frequent in the context of global climate change. Understanding how the public sense and perceive extreme weather events such as rainstorms is crucial for rainstorm-induced hazard mitigation. However, it is not clear how public's rainstorm perception and sensitivity vary across a large geographic scale. In this study, we examined over 210 million microblogs and studied rainstorm perception and perception sensitivity across China in 2017. Our results show that, on average, when the rainstorm-derived rainfall increase 1 mm, city dwellers would post 0.178 more rainstorm-related microblogs. There are also significant variations in rainstorm perception sensitivity across our study area. Dwellers living in the cities in the southeastern coast are not as sensitive to rainstorms as those in the north. Such spatial variations could be explained by annual rainfall and terrain relief variables. Dwellers who live in cities with annual rainfall less than 839 mm and terrain relief greater than 264 m show more attention to rainstorms by posting more microblogs.

Urban flooding response to rainstorm scenarios under different return period types

• A new urban rainstorm pattern design method. • Realization of design value of characteristic rainstorm elements in multivariate environment. • The effects of various return period definitions on urban flooding results. Urban flooding research cannot be overemphasized due to its environmental, economic and societal concern. Research on the response of urban flooding under different rainstorm scenarios would be conducive to the design of drainage projects, and helps the government department to master the waterlogging process in advance. Thus, this paper introduces a new rainstorm pattern designing method using Copula theory, Most-Likely design realization method and Monte Carlo simulation based on the rainfall data in a Chinese megacity, Zhengzhou. Furthermore, a coupled one-dimensional and two-dimensional hydrodynamic model, MIKE FLOOD, was used to determine the urban flooding response to various rainstorm scenarios. The results show that more than 75 percent of waterlogging disasters in Zhengzhou city were caused by short duration rainstorms within 3 hours, and the one-hour single-peak rainstorm process plays a main role. The rainstorm volume (RV) under Kendall return period type decreased significantly compared with the radical “Or” return period. And the RV under survival Kendall return period type was improved compared to the conservative “And” return period. Moreover, the rainstorm scenario corresponding to “Or” return period brought about the most serious waterlogging disaster, with the peak inundation volume of 1.8 × 10 5 m³ and the maximum water depth of 1.86 m.

Risk assessment of urban rainstorm flood disaster based on land use/land cover simulation

AbstractUnder the urbanization context, land use/land cover (LULC) changes rapidly which affects both the probability of urban flood disaster and its consequence. In order to explore the impact of LULC changes on rainstorm flood disaster risk in the future, a framework of rainstorm flood disaster risk assessment is constructed from natural‐social perspective through LULC simulation based on the patch‐generating land use simulation (PLUS) model in this study. Specifically, the spatial LULC under three future development scenarios (inertia development scenario, economic priority scenario and sustainable development scenario) for the year 2030 is simulated, and then assessment model of rainstorm flood disaster risk is constructed through obtaining inundation depth and social vulnerability based on simulated LULC. Jingdezhen City in China is selected as an example. The results show that proposed risk assessment framework based on PLUS model can be used to detect the risk changes in different development scenarios. The risk of urban rainstorm flood disaster under economic priority scenario is most severe and risk under the sustainable development scenario is the lowest under the same return period rainstorm. Under the sustainable development scenario, green land including forest land, grassland and open water increases, which reduces the surface runoff and decrease the risk of rainstorm flood disaster effectively, however the reduction is limited with the greater rainstorm return period. Therefore, adaptive measures should be implemented together with land use planning to prevent and control urban flood risk. This study provides a framework to predict the future risk of urban rainstorm flood under different development scenarios, which can support for flood disaster risk prevention and urban sustainable development.

Dominance of terrestrial moisture supply for the record-breaking extreme precipitation in Hubei, China on August 12, 2021

A record-breaking heavy rainfall swept across Suizhou of Hubei province in China on August 12, 2021. It was characterized by suddenness and extremeness and caused severe socio-economic losses. To deepen the understanding of such an urban rainstorm and to improve the forecasting ability, this study revealed the dominant atmospheric circulation and moisture sources for this event. We performed a Lagrangian model FLEXPART to understand this event in terms of moisture sources and transport trajectories. Three key circulation systems affecting this extreme event were identified, including the western Pacific subtropical high (WPSH), the low-level southwesterly jet and an anticyclone over northern China. The low-level jet was lifted along the northern dry and cold air mass to form a front, resulting in the heavy rain. The moisture sources located on land contributed about 64% of the moisture. The development of the low-level southwesterly jet in southern China was strengthened near the time of the precipitation occurrence, providing the main moisture supply. Southern China (23°–32.5°N, 98°–122°E) was the most important source region, which contributed the most to the precipitation (43.6%). The results highlight the prominent role of the terrestrial water cycle in this extreme precipitation event over Hubei.

City Flood Disaster Scenario Simulation Based on 1D–2D Coupled Rain–Flood Model

In order to realize the reproduction and simulation of urban rainstorm and waterlogging scenarios with complex underlying surfaces, based on the 1D–2D coupled models, we constructed an urban storm–flood coupling model considering one-dimensional river channels, two-dimensional ground and underground pipe networks. Luoyang City, located in the western part of Henan Province, China was used as a pilot to realize the construction of a one-dimensional and two-dimensional coupled urban flood model and flood simulation. The coupled model was calibrated and verified by the submerged water depths of 16 survey points in two historical storms flood events. The average relative error of the calibration simulated water depth was 22.65%, and the average absolute error was 13.93 cm; the average relative error of the verified simulated water depth was 15.27%, the average absolute error was 7.54 cm, and the simulation result was good. Finally, 28 rains with different return periods and different durations were designed to simulate and analyze the rainstorm inundation in the downtown area of Luoyang. The result shows that the R2 of rainfall and urban rainstorm inundation is 0.8776, and the R2 of rainfall duration and urban rainstorm inundation is 0.8141. The study results have important practical significance for urban flood prevention, disaster reduction and traffic emergency management.

Emergency management decision of urban rainstorm and flood disasters based on similar cases analysis

Under the background of global climate change and rapid development of urbanization, urban extreme occurs more frequently. In consideration of the existing problems in the emergency management decision-making of urban rainstorm and flood disasters in China, this study put forward the decision-making method of urban rainstorm and flood disaster emergency management based on similar cases analysis method. Based on the evolution process of urban waterlogging disaster, the problem attribute system of urban rainstorm and flood disasters was established. The case-based reasoning (CBR) method was used to calculate the global similarity to determine the best historical case. The case-based decision theory (CBDT) method was used to calculate the comprehensive utility value of alternative cases to determine the optimal alternative cases. The empirical analysis was took in Xi'an city, one of the national center cities of China. Results show that the CBR method was used to obtain the highest similarity of historical case P3, which is 0.481. The CBDT method was used to calculate the high similarity of historical cases P3 and P4 to form the similar case set, with the similarity of 0.820 and 0.851, respectively. Combined with the event development, the comprehensive utility values were calculated. When the decision-maker pays the same attention to the emergency effect and response cost, the comprehensive utility value of P3 and P4 is 0.922 and 0.900, respectively, and P3 is the best reference scheme. By comparison, the latter is more suitable. The results can provide scientific basis for emergency management of urban rainstorm and flood disasters.

Real-time urban rainstorm and waterlogging disaster detection by Weibo users

Abstract. With the process of urbanization in China, the urban waterlogging caused by rainstorms occurs frequently and often leads to serious damage to the natural environment, human life, and the city economy. Rapid detection of rainstorm and urban waterlogging disasters is an essential step to minimize these losses. Weibo, a popular microblog service in China, can provide many real-time Weibo posts for rapid detection. In this paper, we propose a method to identify microblogs with rainstorm and waterlogging information and apply them to waterlogging risk assessment. After pre-processing the microblog texts, we evaluate the performance of clustering (k-means) and classification (support vector machine, SVM) algorithms in the classification task. Apart from word vector features, we also introduce sentiment and publisher features for more real-time and accurate results. Furthermore, we build a waterlogging intensity dictionary to assess the waterlogging risk from the Weibo texts and produce a risk map with ArcGIS. To examine the efficacy of this approach, we collect Weibo data from two rainstorms and waterlogging disasters in Beijing city as examples. The results indicate that the SVM algorithm can be applied for a real-time rainstorm and waterlogging information detection. Compared to official-authentication and personal-certification users, the microblogs posted by general users can better indicate the intensity and timing of rainstorms. The location of waterlogging points is consistent with the risk assessment results, which proves our proposed risk assessment method can be used as a reference for timely emergency response.

Evaluation of evacuation difficulty of urban resident during storm water‐logging based on walking experiment

Frequent water-logging disasters in cities are serious threats to urban residents. When a water-logging disaster occurs, it is essential for residents to evacuate, taking refuge to reduce losses and to ensure safety. This project studied evacuation difficulty for residents in the Daoli District of Harbin during storm water-logging. Starting from external factors and internal factors influencing resident evacuation, the study screened indicators for assessing the difficulty of evacuation during urban rainstorm water-logging, constructed an evaluation index system and evaluation models to assess the difficulty of evacuation of residents. Results showed that residents in the vicinity of the three streets, Xinyang Road and Minqing Street, Zhaolin Street and Anfeng Street in the study area have difficulty in evacuation in the case of a 5-year torrential rain disaster. Other areas had little impact. In a 100-year torrential rain situation, it is more difficult for residents in Stone Road Bridge, the intersection of Market Street and Toulong Street, the intersection of Touloing Street and Zhaolin Street, the intersection of Anfa Street and JingweiErdao Street, and Anguo Street, while other areas were not seriously affected. The research results can provide new ideas for the study of evacuation of residents during urban water-logging, and can also provide decision-making basis for disaster prevention and mitigation for urban emergency departments.