Waterlogging Disasters Research Articles

Dual-assessment of resilience and recovery strategies of road networks under rainstorm-induced waterlogging disasters

The dynamic resilience of road networks, threatened by rainstorm-induced waterlogging disasters, is crucial for recovering and reconstructing urban functions. We established a dynamic event impact mechanism by dividing the process of this disaster impact on the road network into four stages. To ensure that we can accurately evaluate the resilience of the road network during this disaster, we constructed a dual-resilience model based on performance and topology with two angles. On this basis, we compare four different recovery strategies including the average recovery strategy, key recovery strategy, two recovery strategies stacked, and opening low-altitude routes. The results show that resilience recovery is better in the short term by choosing to open low-altitude routes, and in the long term by choosing an average recovery strategy. In addition, the average recovery strategy and the essential recovery strategy are implemented best during the rainstorm occurrence stage.

Risk Assessment of Community-Scale High-Temperature and Rainstorm Waterlogging Disasters: A Case Study of the Dongsi Community in Beijing

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.

Modeling and application of urban waterlogging resilience assessment based on PSR–NES framework and analysis of driving mechanisms

ABSTRACT Extreme weather events are escalating globally, intensifying urban waterlogging disasters and endangering inhabitants and assets while hindering socio-economic progress. This study explores factors hindering cities' waterlogging disaster mitigation using urban resilience theory. It introduces a pressure–state–response (PSR)–natural–economic–social (NES) assessment model to evaluate urban waterlogging resilience, focusing on Nanjing as a key city in flood control. Flood scenarios are simulated using the MIKE model for different rainstorm recurrence periods. Urban flooding resilience is assessed with a hybrid approach. Geodetector analysis identifies primary resilience drivers. Results validate the PSR–NES composite resilience index, showing complex resilience patterns across the study area. High-resilience areas are mainly in the east and southeast, while low-resilience areas cluster along roads and low-lying communities. Key resilience indicators include waterlogging duration, inundation depth, warning capacity, economic density, and road accessibility. These factors interact with nonlinear enhancements and synergies. The study's insights can identify urban management or flood defense infrastructure deficiencies, guiding tailored flood defense strategies for stakeholders.

Assessment of Rainstorm Waterlogging Disaster Risk in Rapidly Urbanizing Areas Based on Land Use Scenario Simulation: A Case Study of Jiangqiao Town in Shanghai, China

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.

Two-Dimensional Hydrodynamic Simulation of the Effect of Stormwater Inlet Blockage on Urban Waterlogging

The drainage capacity of stormwater inlets, which serve as the connection between the surface and the underground drainage system, directly affects surface runoff and the drainage capacity of underground drainage systems. However, in reality, stormwater inlets are often blocked due to the accumulation of leaves, human waste disposal and other factors, resulting in a greatly reduced drainage capacity of the drainage network and, in turn, urban waterlogging disasters. In view of the problem of stormwater inlet blockage, employing a typical waterlogging point in the Lianjiang Middle Road area of Fuzhou city as the research object, the stormwater inlet equivalent drainage method was adopted in this paper to characterize the drainage capacity of the pipe network and enable the control of the stormwater inlet blockage state. Coupled with the stormwater inlet drainage equation, an improved ITF-FLOOD two-dimensional hydrodynamic model was constructed, and the influence of stormwater inlet blockage on urban waterlogging under different rainfall return periods was simulated and analyzed. With increasing rainfall return period, the influences of stormwater inlet blockage on both the maximum area and the depth of accumulated water in the study area gradually decreased compared with those of a nonblocked stormwater inlet, and the growth proportions decreased from 43.35% and 34.58% under the 1-year rainfall scenario to 3.34% and 9.76% under the 50-year rainfall scenario, respectively. However, in terms of the change in the accumulated water level, stormwater inlet blockage will cause an increase, and the influence will always be significant. Overall, stormwater inlet blockage aggravated the waterlogging risk and the extent of waterlogging. Therefore, the results provided a reference for the construction of an urban waterlogging model and have certain guiding significance for waterlogging prevention and control in the study area prone to stormwater inlet blockage.

Construction of a High-Resolution Waterlogging Disaster Monitoring Framework Based on the APSIM Model: A Case Study of Jingzhou and Bengbu

This study investigates waterlogging disasters in winter wheat using the Agricultural Production Systems Simulator (APSIM) model. This research explores the effects of soil hypoxia on wheat root systems and the tolerance of wheat at different growth stages to waterlogging, proposing a model to quantify the degree of waterlogging in wheat. Remote sensing data on soil moisture and wheat distribution are utilized to establish a monitoring system for waterlogging disasters specific to winter wheat. The analysis focused on affected areas in Bengbu and Jingzhou. Experimental results from 2017 to 2022 indicate that the predominant levels of waterlogging disasters in Bengbu and Jingzhou were moderate and mild, with the proportion of mild waterlogging ranging from 30.1% to 39.3% and moderate waterlogging from 14.8% to 25.6%. A combined analysis of multi-source remote sensing data reveals the key roles of precipitation, evapotranspiration, and altitude in waterlogging disasters. This study highlights regional disparities in the distribution of waterlogging disaster risks, providing new strategies and tools for precise assessment of waterlogging disasters.

Analyzing the Mitigation Effect of Urban River Channel Flood Diversion on Waterlogging Disasters Based on Deep Learning

Analyzing the Mitigation Effect of Urban River Channel Flood Diversion on Waterlogging Disasters Based on Deep Learning

Assessing the scale effect of urban vertical patterns on urban waterlogging: An empirical study in Shenzhen

Waterlogging disasters seriously affect residents' lives. Investigating the factors affecting waterlogging is crucial for mitigating waterlogging. Although waterlogging is closely related to land-use patterns, most of the previous studies have analyzed only the impact of urban horizontal patterns on waterlogging at a single scale. Few studies have focused on the role of urban vertical patterns from a multiscale perspective. Therefore, this study investigated the influence of various factors on the density of waterlogging points at grid scales of 1–5 km using Pearson correlation analysis and the random forest model. We conducted a case study for Shenzhen City, and the results show that the building coverage ratio, building crowding degree, building density, proportion of impervious surfaces, proportion of green space, and population density are the most important factors. Moreover, the urban horizontal and vertical patterns have significant scale effects on waterlogging. The influence of horizontal patterns on waterlogging is maximum at a scale of 3 km, while the influence and dominance of the vertical patterns increase with scale. Therefore, controlling building congestion is necessary for alleviating waterlogging, and the rational planning of urban horizontal and vertical patterns is important for the construction of sponge cities. Our results provide decision support for urban land-use optimization and waterlogging mitigation, thereby facilitating sustainable environmental management.

Strategies for Improving the Resiliency of Distribution Networks in Electric Power Systems during Typhoon and Water-Logging Disasters

Coastal cities often face typhoons and urban water logs, which can cause power outages and significant economic losses. Therefore, it is necessary to study the impact of these disasters on urban distribution networks and improve their flexibility. This paper presents a method for predicting power-grid failure rates in typhoons and water logs and suggests a strategy for improving network elasticity after the disaster. It is crucial for the operation and maintenance of power distribution systems during typhoon and water-logging disasters. By mapping the wind speed and water depth at the corresponding positions in the evolution of wind and water logging disasters to the vulnerability curve, the failure probability of the corresponding nodes is obtained, the fault scenario is generated randomly, and the proposed dynamic reconstruction method, which can react in real-time to the damage the distribution system received, has been tested on a modified 33-node and a 118-node distribution network, with 3 and 11 distribution generators loaded, respectively. The results proved that this method can effectively improve the resiliency of the distribution network after a disaster compared with the traditional static reconstruction method, especially in the case of long-lasting wind and flood disasters that have complex and significant impacts on the distribution system, with about 26% load supply for the 33-node system and nearly 95% for the 118-node system.

Assessment and Improvement of Emergency Rescue Service Accessibility under Urban Waterlogging Disasters

With the acceleration of urbanization and the impact of climate change, the frequent occurrence of urban waterlogging not only leads to road closures and traffic congestion but also severely affects the timeliness of urban emergency rescue. To accurately assess and enhance the response capability of urban emergency rescue under storm-induced waterlogging scenarios, a hydrodynamic model of urban waterlogging was developed to simulate waterlogging conditions under various design rainfall scenarios. By identifying road waterlogging risks and blocked roads, as well as combining the Two-Step Floating Catchment Area (2SFCA) method, the accessibility of emergency rescue services for points of interest (POIs) with different vulnerabilities was evaluated. The Liwan District of Guangzhou City was selected as a case study for accessibility impact assessment and improvement simulation. The results indicate that with the increase in the return period of rainfall, both the area and depth of waterlogged regions increased and the number of roads affected by waterlogging rose, leading to an increase in the length of blocked roads from 11 km to 49 km, an increase of over 300%. Additionally, the number of POIs inaccessible to emergency rescue increased, while the number of accessible POIs decreased, resulting in a significant downward trend in overall accessibility. By deploying mobile pumping vehicles, the depth and area of waterlogging under different rainfall return periods were reduced by over 10%, the number of blocked roads decreased by more than 10%, and the number of accessible POIs increased by more than 12%. The findings highlight that storm-induced waterlogging not only hinders traffic flow but also reduces the response capability of emergency rescue services. Through the strategic deployment of mobile pumping vehicles, the accessibility of urban emergency rescue services under waterlogging conditions can be effectively improved, mitigating the impact of waterlogging on urban functions and public safety.

Quantifying the direct and indirect impacts of urban waterlogging using input‒output analysis

Increasingly frequent urban waterlogging disasters are having profound social and economic consequences. An appropriate and integrated evaluation of the total economic impacts of such disasters is crucial for achieving effective urban disaster risk management and sustainable development. However, existing metrics are inadequate for measuring the economic impacts of rainfall events of different intensities and their ripple effects across regions. Moreover, their ecological impacts have received insufficient attention. To address these gaps, we developed an integrated assessment framework for analyzing urban waterlogging losses and evaluating their various impacts. Taking Beijing as a case study, we used the InfoWorks ICM model to simulate urban waterlogging disaster risks, quantified direct economic losses, and assessed their environmental impacts. Additionally, we estimated indirect economic losses using input-output analysis and explored spillover effects. The results revealed increasing trends of direct economic losses and environmental losses corresponding to a longer return period. We observed synergies between these losses and their spatial heterogeneity. However, indirect impacts far outweighed direct impacts, with the former being 2.43 times larger than the latter. The cascading effect resulting from damage to infrastructure was also particularly pronounced. The industrial and spatial heterogeneity of interregional impacts was striking, with eastern provinces evidencing the most significant effects. By mapping the transmission paths of disaster losses along industrial chains and across regions, this study provides inputs that could assist policymakers in developing more effective measures for preventing and mitigating urban waterlogging disasters.

Cascading failure mechanism of major drainage system in mountainous city: Taking the basin of the main urban area of Chongqing as an example, China

Failure of major drainage systems is almost always accompanied by waterlogging. Understanding the operation and failure mechanism of major drainage systems is an important prerequisite for understanding and managing waterlogging. The natural and artificial environments in mountainous cities are more complex, and the major drainage system, as an open system for excessive surface runoff discharge and storage, is more prone to local overload and cascading failure. Existing theories and methods are difficult to explain and analyze the cascading failure characteristics and principles of major drainage systems in mountainous cities. Based on the complex network technology and the principle of runoff balance, the cascade failure model of major drainage system was constructed, and the characteristics and laws of cascade failure under six kinds of terrain, six kinds of short duration rainstorm and two kinds of surface environments were quantitatively analyzed. Research has found that the cascading failure of major drainage systems and waterlogging in mountainous cities should be the same phenomenon from different perspectives, and the simulated matching degree between the two can reach 79.5%. Meanwhile, 456 potential waterlogging locations were discovered in the study area, which is much larger than the actual 73 locations. When urban construction and rainfall conditions change, these unstable potential waterlogging locations are easily apparent. Among them, terrain is the main factor restricting the cascading failure of major drainage systems. Low lying valley areas often quickly accumulate a large amount of overflow, while flat areas are prone to overflow spreading to the surrounding areas; Slope areas are not prone to overflow, but are prone to local flooding. The change of short duration rainstorm and the difference of surface environmental openness will further interfere with the cascade failure of the major drainage system. The longer the return period of the short duration rainstorm or the increase of the peak value of the rainfall pattern, the greater the discharge and storage pressure of the major drainage system per unit time, resulting in intensified waterlogging. The open and unobstructed surface environment will lead to the small-scale spread of waterlogging, but this will significantly reduce the overall degree of waterlogging in the late rainstorm. The study revealed the spatiotemporal principles and basic laws of cascading failure of major drainage systems in mountainous cities. The conclusion is helpful for mountainous cities to formulate urban construction management strategies and climate change adaptation strategies, and to cope with current and future potential waterlogging disasters.

Evaluation of Flooding Disaster Risks for Subway Stations Based on the PSR Cloud Model

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.

Evaluating the Impacts of Waterlogging Disasters on Wheat and Maize Yields in the Middle and Lower Yangtze River Region, China, by an Agrometeorological Index

Waterlogging disasters severely restrict crop production. The middle and lower Yangtze River region (MLYRR) is an important grain-producing region in China but suffers from severe waterlogging disasters. In this study, an agriculture-specific index called the accumulative humidity index was introduced to analyze the spatiotemporal characteristics of waterlogging during different wheat and maize growth stages in the MLYRR from 1960 to 2020. Additionally, the relationships between waterlogging intensities and crop yield fluctuations were revealed. The results showed that over the past 60 years, the intensity of wheat and maize waterlogging in the central and eastern MLYRR have increased; crop waterlogging was more intense in the 1990s–2010s than during the 1960s–1980s, and waterlogging intensity peaked in the 1990s. For both crops, waterlogging was more intense during the early growth stages, but its yield-reducing impacts were more significant during middle and late growth stages. The southern MLYRR (especially southern Anhui) was the region where both crops were most prone to waterlogging, but yields in this region were not severely affected by waterlogging. Compared with wheat, maize was more prone to waterlogging, and its yield was more significantly reduced by waterlogging. In conclusion, this study provides guidance for agricultural waterlogging risk reduction in the MLYRR.

Assessing urban pluvial waterlogging resilience based on sewer congestion risk and climate change impacts

Urban waterlogging is a critical issue in urban governance, as without proper preventive measures, stagnant water can lead to damage or even casualties. Identifying waterlogging risk points is often desired in urban waterlogging management. Evaluation strategies should be tailored due to the dynamic features of climate warming and high uncertainty in rainfall patterns. An urban pluvial waterlogging resilience (UPWR) analysis framework is proposed as the basis and the tool for dynamically evaluating the spatial distribution of urban waterlogging resilience. UPWR combines hydrological modelling with drainage capacity calculation, extending the original urban waterlogging analysis into a spatial–temporal resilience analysis paradigm for urban waterlogging management in a future climate. An area in Wuhan city, which has suffered from severe waterlogging disaster events for years, was selected for a case study to test the effectiveness and applicability of the proposed approach. This study found that (1) as the drainage network congestion situation intensifies, the UPWR grade decreases in 14% of the study areas; (2) from 2030 to 2100, the UPWR in Wuhan shows a worsening trend under each Representative Concentration Pathway (RCP), and the UPWR under the RCP45 scenario is the worst; and (3) the analysis results can be used to predict future UPWR changes and determine in advance which areas require special maintenance. The novelty of this research lies in the following: (a) the two levels of precipitation and drainage are combined to construct an UPWR assessment framework, providing a quantitative spatial distribution that lays the foundation for exploring urban waterlogging management solutions; and (b) consideration is given to the dynamic change in climate and urban resistance to waterlogging when predicting the future UPWR via a continuous time series, which can provide a basis for urban waterlogging control planning.

Assessing and enhancing urban road network resilience under rainstorm waterlogging disasters

Assessing and enhancing urban road network resilience under rainstorm waterlogging disasters

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.

An approach of using social media data to detect the real time spatio-temporal variations of urban waterlogging

Urban waterlogging has occurred frequently in recent years due to the impact of climate change and human activities. Real-time waterlogging information is crucial for disaster emergency management, but how to quickly obtain such information remains challenging. Social media data has been widely used to derive damage information because of its high real-time response, low acquisition cost, and high content integration. In this study, we propose an approach to extract real-time waterlogging points from social media data (Sina Weibo). First, social media data is obtained through web crawler technology; Then, de-duplication and de-noising methods are used to filter the data; Finally, a waterlogging point extraction method based on deep learning BERT-BiLSTM-CRF model is proposed to extract waterlogging points. Taking the “7.20” rainstorm in Zhengzhou as an example, there was a rapid increase in the number of social media data during urban waterlogging. Social media data is highly sensitive to urban waterlogging disasters caused by extreme rainstorms. On the day with the heaviest rainfall (July 20), the number of Weibo waterlogging points (331) in the central city was 267 more than the official waterlogging points (64). There were many more Weibo-derived waterlogging points than the real-time official published waterlogging points. The waterlogging points obtained by this approach covered the official published real-time waterlogging points accounted for no less than 82% and they were mostly located around roads, especially in low-lying areas. In general, we demonstrate the feasibility and accuracy of social media data on rapid detection of real-time spatiotemporal variations of waterlogging caused by extreme rainstorms. Urban waterlogging disaster information extracted from social media data can rapidly reflect the real-time spatiotemporal variations of urban waterlogging disasters, and can effectively cover and supplement data reported by government agencies, and can provide data support for urban waterlogging disaster prevention.

Analyzing the impacts of topographic factors and land cover characteristics on waterlogging events in urban functional zones

Rapid urbanization and climate changes result in frequent occurrence of urban waterlogging disasters, which cause serious economic damage and pose a threat to residents' safety. Understanding the spatial characteristic and the key influencing factors of urban waterlogging has significant implications for mitigating waterlogging. In this study, the officially issued representative waterlogging points were obtained, as well as the topographic factors and land cover characteristics were selected to compare their impacts on the waterlogging event density in a highly urbanized area at urban functional zone (UFZ) scale, and to quantify the contributions of the key influencing factors on urban waterlogging events. Results showed the average density of urban waterlogging events in the study area is 9.2 points/km2, and 38.4 % of the waterlogging events are distributed in REZ. The distribution of waterlogging points in the study area revealed a significant multi-core and multilevel spatial aggregation pattern, and 12.1 % of the study area was high-density waterlogging area. In the total UFZs, the correlation coefficients of topographic indices with waterlogging density were relatively weaker than the other land cover characteristic metrics. The impervious surface ratio had significant contributions in all UFZ types. The larger ratio of impervious surface significantly increased the density of waterlogging events. The increase in the ratio of green space can effectively decrease the density of urban waterlogging. In the total UFZs, the top 3 key influencing factors of urban waterlogging were PR (35.9 %), COHESION (32.5 %) and DIVISION (11.8 %). The higher connectivity of landscape patches in REZ, INZ and COZ, as well as the increase of landscape dispersion or diversity in REZ, EGZ, INZ and GSZ can effectively reduce the occurrence of urban waterlogging. This study provides a better understanding of the formation mechanism of urban waterlogging disasters and potential implications for prioritized waterlogging mitigation strategies.

Nature-based solutions: Establishing a comprehensive framework for addressing urban waterlogging management.

Due to the impact of global climate change, many cities in China have been hit by severe rainstorms, leading to increasingly frequent urban waterlogging disasters. In recent years, nature-based solutions (NbS) have received widespread attention and recognition, providing new ideas and approaches to addressing urban waterlogging issues. First, this article reviews the development process and concept of NbS and analyzes its core ideas and principles. Second, it analyzes the guiding role of NbS in urban waterlogging management and compares the commonalities and differences between NbS and three related waterlogging concepts. To ensure that urban waterlogging management is operational and dynamic, and that there is effective communication among stakeholders, this article proposes a comprehensive framework for the application of NbS in urban waterlogging management. Finally, this article analyzes the opportunities and potential of NbS applied to urban environmental issues. Integr Environ Assess Manag 2023;19:1414-1421. © 2023 SETAC.