Urban Rainstorm Research Articles

Effect of Changing the Shape and Size of Inlet Area of Grates on the Hydraulic Efficiency of Urban Rainstorm Drainage Systems

Urban rainstorm drainage systems are used to collect the surface runoff from streets and other land surfaces through grate or curb openings that convey it to the drains. The quantity of surface runoff that is not discharged to the urban rainstorm drainage systems due to inadequate grate size or because the grate capacity is exceeded can cause flooding, immoderate hazards to drivers and pedestrians, and disrupt urban activities. This study aims to carry out experimental work to investigate the hydraulic efficiency of urban rainstorm drainage systems using different types of grates (shape and size of inlet area) for harvesting excess rainwater. Different grate shapes (five) with different inlet areas were investigated, as well as using three relative grate inlet areas (26%, 51%, and 64%). The results of the experimental work indicated that the best grate shape is the grate type 4 which provided the smallest reduction in discharge efficiency within 8.7%. The results specified that changing the size of the inlet area of grates from (26%) to (64%) has a significant impact on urban rainstorm drainage systems efficiency which decreased by 4%. In addition, the dimensional analysis principle with multi regression analysis were used to develop an empirical equation to compute the efficiency of urban rainstorm drainage systems. The relation between grate shapes and the relative inlet area with the efficiency of grate capture provides an indication to the decisionmakers to increase the time period for maintenance which will save the cost for further maintenance. The presented empirical equation can help decisionmakers for monitoring the current situation of grate blockage (relative grate inlet areas) and the corresponding efficiency. This study is beneficial for future road drainage system construction to avoid problems by assessing the performances of the current drainage systems and proposing mitigation measures to avoid improper functioning. Finally, this methodology can help to improve the efficiency of urban rainstorm drainage systems that can reduce the risks of urban floods.

A METHOD FOR RECOGNIZING RAINFALL-SENSITIVE URBAN ROADS BASED ON TRAJECTORY DATA

Abstract. Rainfall has a substantial impact on urban traffic. Due to climate change and urbanization, rain and associated flooding will become an increasing hazard to urban traffic. Therefore, it is significant to detect road traffic anomalies and analyze their evolution. This study focuses on rainfall-sensitive roads, which have significant changes in speed and an apparent trend of change during multiple rainfalls. Firstly, the trajectory data are converted into road traffic time-series data, and the box plot is applied to determine whether there are significant outliers in roads speed. Secondly, the Mann-Kendall Trend Test is used to judge whether there is a noticeable trend change in the rainfall process. The proposed method is applied to Nanjing City in China. Based on the trajectory data from June to August 2019, the percentage of urban roads with significant changes in rainfall events is between 30% and 50%, with 217 roads that reveal significant changes every time. A total of 24 rainfall-sensitive roads are extracted by the trend test. This study will provide additional assistance for crucial road monitoring of urban rainstorm hazards.

Spatially Disaggregated Assessment of Environmental Inequalities Among Vulnerable Groups due to Urban Rainstorm Flooding

Spatially Disaggregated Assessment of Environmental Inequalities Among Vulnerable Groups due to Urban Rainstorm Flooding

Risk Assessment and Prediction of Rainstorm and Flood Disaster Based on Henan Province, China

To reasonably evaluate and predict the loss of rainstorm and flood disaster, this study is based on the rainfall data and rainstorm and flood disaster data of 18 cities in Henan Province from 2010 to 2020, using GIS technology and weighted comprehensive evaluation method to analyze the risk of rainstorm and flood disaster factors in various regions. The four risk factors of hazard risk, hazard-pregnant environment sensitivity, hazard-bearing body vulnerability, and disaster resilience were analyzed in compartment analysis. At the same time, a new rainstorm and flood disaster prediction model was constructed in combination with the hybrid PSO-SVR algorithm. The research results show that there are many rivers in Henan Province, the terrain tends to be higher in the west and lower in the east, and most areas are low plains, making most cities in Henan Province at a moderate risk level. For the more developed cities such as Zhengzhou, Luoyang, and Nanyang, the hazard risk, sensitivity, vulnerability, and disaster resistance are high, and they are prone to heavy rains and floods. For the economically underdeveloped, the terrain is high or hills, such as Sanmenxia City; Xinyang City and other places have low hazard risk and are not prone to rainstorms and floods. By constructing a hybrid PSO-SVR model, selecting two representative cities of Zhengzhou and Luoyang, and predicting the daily rainfall, the number of disasters, and the direct economic loss, the calculated RMSE and MAPE values are both less than GA-SVR, the traditional SVR, and BPNN models, which have verified the superiority of the model proposed in this study and the practical value it brings. To further verify the prediction accuracy of the hybrid model, the average value of RMSE and MAPE of other 16 cities are calculated, and the result is still smaller than other three models, and the study can provide some decision-making references for the urban rainstorm and flood management.

Study on urban rainstorm pattern of short-duration double-peak

At present, researches on urban short-duration rainstorm patterns mainly focus on single-peak rainstorm patterns, and rarely involve double-peak rainstorm patterns, or convert double-peak patterns into single-peak patterns directly, even ignore the impact of double-peak patterns, which directly affects the urban flood planning and early warning and rescue. To scientifically and rationally deduce the urban short-duration double-peak rain pattern, this paper proposes a new function fitting rain pattern method by constructing double-peak virtual rain peak rainfall and virtual rain peak coefficient, based on the idea of convert double-peak to single-peak, then revert to the double-peak, directly deducing the double-peak rain pattern. The results show that (1) The rain pattern derived by the function fitting rain pattern method (FFRPM) can effectively improve the accuracy of the double-peak rain pattern and is also more practical; (2) The fitting degree of function fitting rainfall pattern and actual rain pattern is more than 90%, accounting for 80%, the fitting degree of main and secondary peak rainfall is more than 90%, with an average of about 95%; the accuracy of the main and secondary peak positions is also relatively high; (3) Compared with the P&C rain pattern method, whether the overall accuracy or local peak rainfall, the FFRPM has the higher accuracy, especially more accurate on rain peak rainfall.

A GPU-Accelerated Hydrodynamic Model for Urban Rainstorm Inundation Simulation: A Case Study in China

Frequent urban rainstorm inundations can cause serious damages to human life and social economy. Reliable simulation of urban rainstorm inundation is an effective approach for performing flood risk analysis to reduce losses. In this work, a full 2D high-performance hydrodynamic model for urban rainstorm inundation simulation based on Graphic Processing Unit (GPU) was developed. The idealized V-shape catchment and sponge city district of Fengxi New City were selected as the study areas to assess performance of the model. The model was validated against analytical benchmark results of the idealized V-catchment test which show good agreement between the modelled flow and analytical solutions. The model was then applied to simulate actual urban rainstorm inundation process under measured rainfall. The results indicated that the model can be applied to high-resolution urban region simulations. Specifically, the validation results indicated that the proposed model had a good performance, with an accepted error of less than 15%. When applied to compute the Fengxi New city under design rainstorms with different annual return periods of 1, 5, 10, 20, 50, and 100 years, it was found that the model effectively evaluated the temporal and spatial variation process of urban inundation, and quantitatively investigated flood risks according to the water depth change. The model has been substantially accelerated on GPU to quickly predict urban inundation. The accuracy and rapid simulation speed of the model were verified based on the actual study area. Therefore, the proposed model can help to predict the dynamic processes of urban flood inundation and thus reduce flood inundation disasters. This is essential for future optimal sponge urban construction planning in China.

Assessment of climate change impacts and urban flood management schemes in central Shanghai

Increasing urbanization combined with climate change has resulted in the increased risk of flooding in cities. Thus, assessing the effect of future climate change on urban flooding and adopting effective flood management measures is becoming increasingly important. In this study, an urban rainstorm model and a scenario simulation method were applied to central Shanghai, China. We first examined the risks of flooding in the study area under the impact of future climate change using a simulation with different rainfall return periods. We then evaluated the benefits of traditional drainage system adaptation measures and Low Impact Development (LID) practices on alleviating the current urban flood hazard. Finally, we explored the effectiveness of using an integrated flood management scheme to adapt to climate change. The results show that the urban flood volume increases non-linearly with increasing rainfall intensity under climate change. The maximum flooding area also increases accordingly, and is much more sensitive to smaller rainfall events. Both traditional drainage system adaptation measures and LID practices can effectively alleviate flooding, while an integrated flood management scheme that emphasizes the combination of the two methods is shown to be the most effective in reducing flooding under future climate change.

Weighted clustering-based risk assessment on urban rainstorm and flood disaster

In recent years, the rainstorm and flood disasters frequently happened in cities and posed increasingly wide challenges. Therefore, the whole development process of urban rainstorm and flood disaster should be carried out for the reasonable and quantitative assessment on cities' ability to respond to rainstorm and flood disasters, and the index system of risk assessment on regional flood disaster is constructed based on the three attributes of vulnerability, adaptability and restorability. 3 first-class and 14 s-class indexes are set up accordingly. The weight of each index is calculated by weighting methods which are both subjective and objective based on entropy-weight order relation. Then, the theoretical model for risk assessment is established by weighted clustering assessment. Finally, the empirical analysis was conducted on the current situation of rainstorm and flood disaster in 8 regions of a city in China. The results show that among the risk grade of rainstorm and flood disaster in 8 regions, there are 2 regions with grade-II higher risk, 5 regions with grade-III general risk and 1 region with grade-IV low risk. The consistency between assessment results and actual operation of cities indicates this model can be applied and effective to some extent.

Study on the Improvement of Ecological Environment in the Space of Shanghai Primary and Secondary Schools by Rain Gardens

Low Impact Development (LID) is a technology of rainstorm management and water pollution treatment developed in the late 1990s. As one of the LID measures, rain gardens can alleviate the urban rainstorm in Shanghai. Aiming at the low rate of environment utilization in the spaces of Shanghai primary and secondary schools, this paper proposes to collect the rainwater runoff from buildings and roads in the form of rain garden. We try to use artistic design techniques, and establish the campus environment with the value of rain and flood management, sustainability and biodiversity. The study results show that the sample rain garden covers an area of 310m2 with a water storage depth of 30mm, and has recorded 6 short-term heavy rainfalls and 1 overflow in 1 year. The biodiversity has increased by 70%.

Identification of sensitivity indicators of urban rainstorm flood disasters: A case study in China

Urban rainstorm floods have become one of the most significant natural disasters that restrict the healthy development of the economy and society. It is imperative to reduce the risk of urban rainstorm flood disasters, which is growing along with urbanization, during the process of urban planning and construction. However, because of the complexity of urban elements, it is quite difficult to identify sensitive indicators of urban rainstorm flood disasters to provide effective guidance on flood control. In this study, the composition of urban elements was systematically proposed based on Descriptive Framework for Cities and Communities, including natural, structural, and social elements, and then a specific indicator system was established. Furthermore, Random Forest Model was used to determine the relative importance of the indicators that are closely related to the direct economic loss that reflects the severity of urban rainstorm flood disasters. Considering four cities in China, Beijing, Tianjin, Chongqing, and Shanghai, with different topographical and hydrological conditions, as examples, the sensitivity indicators of urban rainstorm flood disasters were identified, and the results were verified based on the catastrophe evaluation method. The results indicate that urban rainstorm flood disasters are the most sensitive to surface water resources, and are the least sensitive to relief degree of land surface. Finally, specific measures to mitigate urban rainstorm flood disasters were proposed.

Understanding China’s Urban Rainstorm Waterlogging and Its Potential Governance

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.

An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China

Effective management of rainstorm risk is essential for reducing regional rainstorm disaster risks and losses. In this paper, we discussed the influencing factors of urban rainstorm disaster (URSD) risk from four aspects and then constructed the index system of URSD risk assessment which includes 16 influencing factors. Furtherly, important indexes were extracted as the input of deep belief nets (DBN) model after analyzing the types and risk characteristics of URSD. As well as a coupling risk assessment model of URSD based on random forest and deep belief nets (RF–DBN) was established due to the capacity of high-dimensional data processing of RF and robustness of DBN. To test the validity of this risk assessment model, it was applied to evaluate the rainstorm disaster risk in 11 districts of Nanjing, China, from May to September during 2009 and 2017. Finally, the risk grade map of rainstorm disaster in Nanjing was drawn and the corresponding countermeasures for the regulation and control of URSD were put forward. The results show that the rainstorm risk in Nanjing is generally high during the period of rainy season and the risk of rainstorm disaster has egional features during the flood season.

Identification of Urban Rainstorm Waterlogging Based on Multi-source Information Fusion：A Case Study in Futian District, Shenzhen

Flood disasters have become one of the most threatening natural disasters in the world, in which waterlogging is the most common form in the context of highly urbanized megacities. The formation of flood disaster is related to many factors and involves information from multiple sources, making it difficult be predicted. This paper integrates multi-source information data, classifies the study area into different categories according to hydrological analysis results, and combines hydrodynamic theory and ArcGIS to get the quantitative prediction of the range and depth of waterlogging under different rainfall inputs. The evaluation results provide the government with accurate and timely information of waterlogging risks and locations in order to improve promptness of emergency management such as evacuation and managing traffics.

Analysis on Impact of Land Use Change on Urban Waterlogging Caused by Floods

In recent years, ultra-high-intensity rainfall at home and abroad has caused frequent urban waterlogging disasters, posing a severe threat to people’s lives, property and city’s safety. Based on the satellite image data of Shanghai Waigaoqiao Free Trade Zone in different periods and the Storm Water Management Model (SWMM), this paper establishes a model of heavy rainfall under the underlying surface of a complex city, and analyses topographic features, different land use types, rainfall infiltration intensity and the characteristics of the drainage pipe network. The rainwater accumulation under different rainstorms and urbanization levels is simulated and analysed. The research results show that urban rainstorm accumulation is closely related to land use changes. With the increase of surface impermeability and rainfall intensity, the risk of waterlogging in the study area tends to increase: From 1994 to 2019, the construction area has increased from 2.5096km2 to 5.8662km2 in the study area. Compared with 1994, under the same rainfall conditions, the simulated flooding node and runoff coefficient in 2019 both increased significantly.

MAS-Based Interaction Simulation within Asymmetric Information on Emergency Management of Urban Rainstorm Disaster

The frequent occurrence of urban waterlogging constantly affects resident living and urban construction. Improved adaptive prevention and control strategies are highly requested due to huge economic losses and casualties caused by flood and waterlogging in China. The urban waterlogging may evolve into a serious emergency, generally characterized by high complexity, uncertainty, and time pressure. Coupled with the asymmetric information, waterlogging often exacerbates the impact of urban rainstorm disasters. Through the multi-agent system simulation with given geographic information, government and residents interact under dynamic risk distribution in rainstorm disaster. The results show that the proactive attitude of residents and the government towards disaster relief could have a promoting effect for both, thereby increasing the disaster relief efficiency. Obviously, rapid accurate information collection and analysis facilitate disaster relief to a large extent. Meanwhile, appropriate supply rather than excessive supply may mobilize residents’ self-help and balance replenishment of relief supplies.

Risk Assessment of Urban Rainstorm Disaster Based on Multi-Layer Weighted Principal Component Analysis: A Case Study of Nanjing, China.

Nanjing city is taken as a case in this urban rainstorm disaster risk research. Using the data of meteorology and social-economy statistics of Nanjing area, the paper selected ten indicators to establish the risk assessment system of urban rainstorm disaster from the aspects of the vulnerability of hazard-affected body, the fragility of disaster-pregnant environment, and the danger of hazard factors. Multi-layer weighted principal component analysis (MLWPCA) is an extension of the principal component analysis (PCA). The MLWPCA is based on factor analysis for the division subsystem. Then the PCA is used to analyze the indicators in each subsystem and weighted to synthesize. ArcGIS is used to describe regional differences in the urban rainstorm disaster risk. Results show that the MLWPCA is more targeted and discriminatory than principal component analysis in the risk assessment of urban rainstorm disaster. Hazard-affected body and disaster-pregnant environment have greater impacts on the risk assessment of rainstorm disaster in Nanjing, but the influence of hazard factors is few. Spatially, there is a large gap in the rainstorm disaster risk in Nanjing. The areas with high-risk rainstorm disaster are mainly concentrated in the central part of Nanjing, and the areas with low-risk rainstorm disaster are in the south and north of the city.

Using Multiple Index Comprehensive Method to Assess Urban Rainstorm Disaster Risk in Jiangsu Province, China

An integrated index system for urban rainstorm risk evaluation has been developed. Meanwhile, an information diffusion method (IDM) and variable fuzzy sets (VFSs) were employed to evaluate the dangerousness, sensitivity, and vulnerability risk of urban rainstorm disasters, respectively. Then, the comprehensive risk zoning map was drawn. Finally, Jiangsu Province has been taken as a case study area. Due to heavy rainfall in short-term and low rainstorm resistance ability, Wuxi, Changzhou, Nanjing, and Suzhou have higher dangerousness while Wuxi, Changzhou, and Nanjing have higher sensitivity. And because of potential losses in urban rainstorm disaster, Wuxi and Suzhou have higher vulnerability than other cities. The comprehensive risk zoning map showed that most cities of Jiangsu Province are at the moderate risk level, and the northwestern cities have lower risk level than the southern cities. The results are consistent with the actual situation of Jiangsu Province, and the study can provide some decision-making references for the urban rainstorm management.

Multi-Agent Simulation of Individuals’ Escape in the Urban Rainstorm Context Based on Dynamic Recognition-Primed Decision Model

The urban rainstorm can evolve into a serious emergency, generally characterized by high complexity, uncertainty, and time pressure. It is often difficult for individuals to find the optimal response strategy due to limited information and time constraints. Therefore, the classical decision-making method based on the “infinite rationality” assumption is sometimes challenging to reflect the reality. Based on the recognition-primed decision (RPD) model, a dynamic RPD (D-RPD) model is proposed in this paper. The D-RPD model assumes that decision-makers can gain experience in the escaping process, and the risk perception of rainstorm disasters can be regarded as a Markov process. The experience of recent attempts would contribute more in decision-making. We design the agent according to the D-RPD model, and employ a multi-agent system (MAS) to simulate individuals’ decisions in the context of a rainstorm. Our results show that experience helps individuals to perform better when they escape in the rainstorm. Recency acts as a one of the key elements in escaping decision making. We also find that filling the information gap between individuals and real-time disaster would help individuals to perform well, especially when individuals tend to avoid extreme decisions.

Traffic Impact Area Detection and Spatiotemporal Influence Assessment for Disaster Reduction Based on Social Media: A Case Study of the 2018 Beijing Rainstorm

The abnormal change in the global climate has increased the chance of urban rainstorm disasters, which greatly threatens people’s daily lives, especially public travel. Timely and effective disaster data sources and analysis methods are essential for disaster reduction. With the popularity of mobile devices and the development of network facilities, social media has attracted widespread attention as a new source of disaster data. The characteristics of rich disaster information, near real-time transmission channels, and low-cost data production have been favored by many researchers. These researchers have used different methods to study disaster reduction based on the different dimensions of information contained in social media, including time, location and content. However, current research is not sufficient and rarely combines specific road condition information with public emotional information to detect traffic impact areas and assess the spatiotemporal influence of these areas. Thus, in this paper, we used various methods, including natural language processing and deep learning, to extract the fine-grained road condition information and public emotional information contained in social media text to comprehensively detect and analyze traffic impact areas during a rainstorm disaster. Furthermore, we proposed a model to evaluate the spatiotemporal influence of these detected traffic impact areas. The heavy rainstorm event in Beijing, China, in 2018 was selected as a case study to verify the validity of the disaster reduction method proposed in this paper.

Exploring the Relationships between Impervious Surface Percentage and Frequency of Urban Waterlogging: A Case Study in Hanoi, Vietnam

In developing countries, rapid urbanization reduces the natural land area and increases the impervious surface. At the same time, urban rainstorm waterlogging is also becoming more frequent and serious. Therefore, one of the important works to be done is to elucidate the relationship between impervious surface expansion and waterlogging frequency (WF) causes of urban waterlogging. To move forward, we used ENVI to classify land cover types and applied the spatial analysis methods integrated in ArcGIS with internet open data to explore these relationships in Hanoi, Vietnam in 2018. The results show that waterlogging frequency was positively related to impervious surface percentage (ISP), indicating that if the median values of ISP increased then the waterlogging frequency would increase as well with a confidence level of 63.2%. This study demonstrates the importance for controlling the impervious surface expansion in urban waterlogging risk management and urban planning.