Search Results (15)

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

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 recent years, power outages due to typhoon-induced rainstorms, waterlogging, and other extreme weather events have become increasingly common, and accurately assessing the risk of damage to the distribution system during a disaster is critical to enhancing the resilience of the power system. Therefore, a risk assessment method for power distribution systems considering the spatiotemporal characteristics of the typhoon disaster chain is proposed. The mechanism of forming the typhoon disaster chain is first analyzed and its spatiotemporal characteristics are modeled. Secondly, the failure probability of the distribution system equipment during the evolution process of the disaster chain is modeled. Then, the non-sequential Monte Carlo state sampling method combined with the distribution system risk assessment index is proposed to establish the disaster risk assessment system of the distribution system. Finally, based on the IEEE 33-bus power system, the proposed distribution system disaster risk assessment method is verified. Simulation solutions show that the proposed assessment method can effectively assess the disaster risk of the distribution system under the influence of the typhoon disaster chain. The simulation results show that at the time step of typhoon landfall, the load shedding reaches 1315.3 kW with a load shedding rate of 35.4%. The total economic loss at the time step is 2,289,200 CNY. These results demonstrate the effectiveness of the proposed method in assessing disaster risks and improving the resilience of power systems during typhoon events. Full article

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. 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

This study aims to scientifically evaluate the risk of rainstorm waterlogging disasters in urban subway stations, improve the management of disaster prevention and control, and mitigate the impact of such disasters. To achieve this, a risk assessment analysis was conducted using the Pressure-State-Response (PSR) cloud model. The analysis involved examining the components of the subway station rainstorm waterlogging disaster system, including the disaster-prone environment, disaster-affected body, and disaster-causing factors. Based on the PSR framework, a risk assessment index system for rainstorm waterlogging disasters in subway stations was developed. The entropy weight method and cloud model algorithm were then combined to establish a risk assessment method. By utilizing a cloud generator, the digital characteristics of the risk cloud were calculated, and a risk cloud map was generated to determine the level of risk. Finally, an empirical analysis was carried out at Jin’anqiao Station of the Beijing Subway, providing valuable insights for the evaluation of rainstorm waterlogging disasters in subway stations. Full article

The complex formation mechanism and numerous influencing factors of urban waterlogging disasters make the identification of their risk an essential matter. This paper proposes a framework for identifying urban waterlogging risk that combines multi-source data fusion with hydrodynamics (MDF-H). The framework consists of a source data layer, a model parameter layer, and a calculation layer. Using multi-source data fusion technology, we processed urban meteorological information, geographic information, and municipal engineering information in a unified computation-oriented manner to form a deep fusion of a globalized multi-data layer. In conjunction with the hydrological analysis results, the irregular sub-catchment regions are divided and utilized as calculating containers for the localized runoff yield and flow concentration. Four categories of source data, meteorological data, topographic data, urban underlying surface data, and municipal and traffic data, with a total of 12 factors, are considered the model input variables to define a real-time and comprehensive runoff coefficient. The computational layer consists of three calculating levels: total study area, sub-catchment, and grid. The surface runoff inter-regional connectivity is realized at all levels of the urban road network when combined with hydrodynamic theory. A two-level drainage capacity assessment model is proposed based on the drainage pipe volume density. The final result is the extent and depth of waterlogging in the study area, and a real-time waterlogging distribution map is formed. It demonstrates a mathematical study and an effective simulation of the horizontal transition of rainfall into the surface runoff in a large-scale urban area. The proposed method was validated by the sudden rainstorm event in Futian District, Shenzhen, on 11 April 2019. The average accuracy for identifying waterlogging depth was greater than 95%. The MDF-H framework has the advantages of precise prediction, rapid calculation speed, and wide applicability to large-scale regions. Full article

Among the various natural disasters encountered by cities, rainstorm waterlogging has become a serious disaster, affecting the sustainable development of cities. Taking Guangzhou as the research object, based on disaster system theory and risk triangle theory, the evaluation framework “risk of hazard causing factors—sensitivity of disaster environment—vulnerability of hazard bearing body” was selected to construct the waterlogging risk assessment model of Guangzhou. The weighted comprehensive evaluation method (AHP) was used to determine the index weight, and the rainfall runoff inundation range under different rainstorm scenarios was deduced through a Soil Conservation Service (SCS) runoff generation model and GIS local equal volume passive inundation simulation. The results show that when the precipitation in 2 h is less than 100 mm, the inundation range increases by 3.4 km² for every 10 mm increase in precipitation; When the precipitation in 2 h is greater than 100 mm, the inundation range will increase by 18 km² for every 10 mm increase in precipitation. The total area of medium and high flood risk in Guangzhou is 441.3 km², mainly concentrated in Yuexiu District, Liwan District, Haizhu District and Tianhe District. Full article

The contradiction between rapid urbanization’s demand for land resources and the ecological environment is increasing, which has led to large-scale hardening of the underlying surface of the city and reduction of land for storage. In addition, construction land occupies rainwater confluence land, resulting in a significant decline in urban stormwater control capabilities. The increasingly frequent flood disasters in recent years have exposed the contradiction between urban construction and stormwater safety that cannot be ignored. Therefore, this article takes the central city of Harbin as the research object, uses ArcGIS for spatial analysis and SCS (Soil Conservation Service) hydrological model simulation to construct the rain and flood safety pattern in the research area, and proposes targeted optimization suggestions and strategies based on the evaluation results to achieve the purpose of coordinating the water ecosystem service function with social and economic development. The research shows that protecting the original stormwater corridor and strengthening the connection between the stormwater control patches can effectively guarantee the connectivity of the stormwater corridor, build the natural stormwater regulation and storage system, and then increase the ability of the city to resist the risk of rainstorm, reduce the disaster caused by urban waterlogging, and achieve the goal of sponge city construction. Full article

Land suitability assessment is fundamental in space control planning and land development because of its effects on land use and urban layout. Rainstorms and waterlogging have become one of the most common natural disasters in the coastal areas of China. As a result, the concept of an ecological sponge city was incorporated into the construction of cities in the future. Taking Shenzhen–Shantou special cooperation zone (SSCZ), we constructed a storm flooding model based on the SCS flow generation model and GIS to explore the spatial distribution characteristics of the flooding risk in a rainstorm of 100-year lasting 1 h. Combined with population and economic indicators, a radial basis function (RBF) network was utilized to evaluate the environmental risk, the vulnerability of disaster-bearing bodies, and the rain–flood resilience of sponge cities. The self-organizing feature mapping (SOFM) model was used for cluster analysis. Spatial differences were found in the construction suitability of the study area. A suitable construction area (73.59% of the entire area) was located downtown. The construction of the artificial spongy body in the highest vulnerable area (3.25%) needs to be strengthened. The control construction area (3.3%) is located along the banks of the river, with relatively high risk and low resilience of flood control engineering. Ecological construction (19.85%) serves as the sponge body of ecological buffer. The factors of waterlogging, ecology, population, and economy could be integrated comprehensively by applying neural network methods for urban planning and construction. Full article

Urban rainstorm waterlogging is one of the most important problems in urban development and a comprehensive embodiment of urban diseases. China is facing a severe risk of rainstorm waterlogging disasters, which is affecting sustainable development. Urban rainstorm waterlogging in China is caused by many factors, including natural factors and human factors, such as climate warming, unreasonable urban construction, inadequate upgrading of urban fortification standards, etc. Based on the analysis of the current strategies to deal with urban waterlogging around the world, including an increase in surface infiltration, and a reduction in runoff (and its various impacts), this paper holds that the connotation and goal of these measures are highly consistent with the construction of a sponge city in China. Based on the analysis of the problems, including construction of an urban rainwater recovery system, construction of urban rainwater storage facilities, and construction of data platforms faced by China’s sponge city, this paper puts forward the guiding principles of promoting the construction of a sponge city. The guiding principles are to cooperate to deal with climate change and ecological civilization construction, to study the foreign experience, and to unite multiple subjects, integrate multiple elements, design multiple processes, form a joint force, and create an all-round response system to deal with urban rainstorm waterlogging. Then, this paper gives policy recommendations on how to deal with the urban rainstorm waterlogging disasters, which include improving the defense standards, encouraging social participation, popularizing the construction of sponge cities, perfecting the monitoring and early warning system, strengthening the scientific planning of cities, strengthening the ability of dealing with catastrophes in metropolitan areas, the overall planning of cross-regional responses, and enhancing the awareness of decision makers. Finally, this paper expounds the reference significance of urban rainstorm waterlogging control in China to the global audience. This paper explores the significance of comprehensively and scientifically understanding urban rainstorm waterlogging disasters, and provides support for long-term planning and high-quality construction of future safe cities. Full article

Confronting the frequent flood disasters triggered by torrential downpour, the vulnerability of urban rainstorm flood disasters was analyzed with one highly popular area of research in mind: big data. Web crawler technology was used to extract text information related to floods from Internet and popular social media platforms. Combining these text data with traditional statistical data, a flood disaster vulnerability assessment model based on Analytic Hierarchy Process (AHP) was established to evaluate rainstorm and flood disaster vulnerability, and the spatial distribution characteristics of vulnerability to pluvial flooding were analyzed based on Geographic Information System (GIS). The established model was applied in Zhengzhou, a city that often suffers from heavy rainstorms. The results show that the areas located near downtown Zhengzhou were more vulnerable to rainstorm and flooding than others, and most of the city could be at moderate and high vulnerability. Finally, the waterlogging spots extracted from various sources were used to evaluate the performance of the proposed model. The results show that most of waterlogging spots were located in very-high and high risk zones, while less waterlogging spots were found in districts with low vulnerability, which demonstrates the discriminative power of the established model based on big data sources. This study overcomes limited data in flood disaster vulnerability assessment methods and provides a basis for flood control and management in cities. Full article

China’s coastal areas suffer from typhoon attacks every year. Rainstorms induced by typhoons characteristically are high intensity with a large amount of rain and usually induce floods and waterlogging in the affected area. Guangdong province has the highest frequency of typhoon hits in China. It has a special geographical position as well as unique climatic features, but the typhoon flood disaster risk has not been fully assessed in this area. This article attempts to fill this gap by providing a comprehensive risk assessment for the area. By combining the Analytical Hierarchy Process (AHP) and multi-factor analysis through geographic information system (GIS) and the comprehensive weighted evaluation, the typhoon flood disaster risk is evaluated from four different aspects with seventeen indicators. A comprehensive study of the typhoon flood disaster risk is carried out, and the risk maps with a resolution of 1 km² have been made. There is a good coherence between the typhoon flood risk map and historical records of typhoon floods in Guangdong province. The results indicate that the comprehensive typhoon flood disaster risk in the coastal regions of Guangdong province is obviously higher than in the Northern mountainous areas. Chaoshan plain and Zhanjiang city have the highest risk of typhoon flood disaster. Shaoguan and Qingyuan cities, which are in the Northern mountainous areas, have the lowest risk. The spatial distribution of typhoon flood disaster risks shows that it has certain regulations along the coast and rivers, but it may be affected by economic and human activities. This article is significant for environmental planning and disaster management strategies of the study area as well as in similar climatic regions in other parts of the world. Full article