Search Results (28)

The extreme rainstorm flood disaster in Beijing on 31 July 2023 resulted in 33 fatalities and 18 missing persons, with direct economic losses across the Beijing–Tianjin–Hebei metropolitan area exceeding RMB 10 billion. Despite its inland location, which is not conventionally classified as a flood-prone zone, Beijing is not conventionally considered a flood-prone region, yet it frequently experiences flood disasters, which has led to confusion and perplexity. This article collects records of historical flooding disasters in Beijing over the past 1000 years, spanning the Jin, Yuan, Ming, and Qing dynasties, the Republics of China, and the founding of New China up to the present, aiming to analyze the basic patterns and characteristics of regional historical flooding disasters. Taking the extreme rainstorm flood disaster in Beijing on 31 July 2023 as an example, this research employs a multidisciplinary approach, including field investigations and numerical simulations, to dissect the disaster-causing mechanisms. The study shows that the significant characteristics of historical flood disasters in Beijing are concentrated in the plain area and the high-frequency outbreaks (below the 3-year return period). Flood disaster events under the participation of typhoons accounted for a high proportion and caused great harm. The extreme rainstorm flood disaster in Beijing on 31 July 2023 was an extreme weather event under the complex coupling of typhoons and terrain. The residual typhoon circulation stayed on the mainland for nearly 70 h, providing abundant precipitation conditions for Beijing. Water vapor is blocked by the Yanshan–Taihang Mountains, uplifting and converging, forming a strong precipitation center in the Piedmont, which aggravates the regional local precipitation intensity. The research results can provide a reference for the scientific prevention and control of typhoon rainstorm flood disasters in Beijing. Full article

Currently, one of the major threats to cities is the escalating risk of flooding, which is attributed to the alteration of climate and hastened urbanization. The purpose of this study was to introduce the Strahler ordering method for simplifying drainage networks and to avoid randomness in developing flooding models. A coupled hydrodynamic model that combines SWMM and LISFLOOD-FP was developed to simulate urban inundation. Results showed that the coupled model had satisfactory applicability for waterlogging simulation. The Strahler ordering method could construct clear topological relations of the drainage network and showed good performance in drainage network simplification. Higher-density drainage networks could increase peak discharge and total volume of discharge, while decreasing the maximum water depth and the total inundation area. Taking “5.29” rainstorm events as an example, compared to Level 3, the relative rates of change in the total flow and peak flow of Level 2 and Level 1 networks are −33.18% and −23.29%. The total inundation area was decreased from 14.14 ha to 1.43 ha when the level of drainage network hierarchy was increased from Level 1 to Level 3. This study highlights the importance of re-assessment of current and future urban drainage networks for coping with the changes in urban floods induced by local and large-scale changes. Full article

Due to model errors caused by local variations in cloud precipitation processes, there are still significant uncertainties in current predictions and simulations of short-duration heavy rainfall. To tackle this problem, the effects of warming on cloud-precipitation efficiency was analyzed utilizing a weather research and forecasting (WRF) model. The analysis focused on a rainstorm corridor event that took place in July 2020. Rainstorm events from 4–6 July formed a narrow rain belt with precipitation exceeded 300 mm in the middle and lower reaches of the Yangtze River. Temperature sensitivity tests revealed that warming intensified the potential temperature gradient between north and south, leading to stronger upward motion on the front. It also strengthened the southwest wind, which resulted in more pronounced precipitation peaks. Warming led to a stronger accumulation and release of convective instability energy. Convective available potential energy (CAPE) and convective inhibition (CIN) both increased correspondingly with the temperature. The precipitation efficiency increased sequentially with 2 °C warming to 27.4%, 31.2%, and 33.1%. Warming can affect the cloud precipitation efficiency by both promoting and suppressing convective activity, which may be one of the reasons for the enhancement of extreme precipitation under global warming. The diagnostic relationship between upward moisture flux and lower atmospheric stability during precipitation evolution was also revealed. Full article

In the context of global climate change, shallow landslides induced by strong typhoons and the ensuing rainstorms have increased significantly in China’s eastern coastal areas. On 27 May 2022, more than 700 liquefied landslides were induced by the rain gush in Wuping County, Longyan City, Fujian Province, SE China. In light of their widespread occurrence and the severe damage caused, detailed field investigations, UAV surveys, trench observations, in situ tests, and numerical simulation are conducted in this work. The cascading landslides are classified as channelized landslides and hillslope landslides. Long-term rainfall, the influence of vegetation roots under wind load, and differences in the strength and structure of surficial soil are the dominant controlling factors. The sliding surface is localized to be the interface at a depth of 1–1.5 m between the fully weathered granite and the strongly weathered granite. Kinetic analysis of a channelized landslide shows that it is characterized by short runout, rapid velocity, and strong impact energy. The maximum velocity, impact energy, and impact force of the Laifu landslide are 29 m/s, 4221.35 J, and 2110 kPa. Effective excavation is usually impossible in this context. This work highlights the escalating issue of shallow landslides in eastern China’s coastal areas, exacerbated by climate change and extreme weather events like typhoons. By conducting comprehensive investigations and analyses, the research identifies key factors influencing landslide occurrence, such as rainfall patterns and soil characteristics. Understanding the dynamics and impact of these landslides is vital for improving risk assessment, developing effective early warning systems, and informing land management policies in this region. Further exploration concerning hydro-meteorological hazard early warning should be encouraged in this region. 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

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

In recent years, heavy rainfall events have occurred frequently in the Qinba region. Forecasting and predicting heavy rainfall in the Qinba region is difficult due to the unique underlying terrain and complicated mechanisms involved. One significant weather system that might bring significant rainfall to the region is the southwest vortex (SWV); however, its different positions, intensities, and interaction with other weather systems might result in precipitation with different intensities and distributions. In this study, ERA-5 reanalysis data, FY-4A satellite data, and conventional observation data were used to examine heavy rainstorms that occurred in the Qinba region in the periods of 3–4 September 2021 (referred to as Stage I) and 4–5 September 2021 (referred to as Stage II), while the SWV was in effect. During Stage I, the northwest vortex (NWV) and SWV generated a mesoscale shear line and mesoscale convective complex (MCC) in the Qinba region. This led to a considerable area of heavy rainfall, with a maximum hourly precipitation of 129 mm and heavy precipitation at 15 stations. During Stage II, a mesoscale convective system (MCS) influenced by the SWV was initiated by a low-level jet, resulting in a localized heavy downpour with a maximum hourly precipitation of 72 mm. Significant topography-forced uplift was found in both Stages I and II in the high-altitude Qinba region. Furthermore, the rainfall was stronger during Stage I due to the secondary circulation that developed in the middle and lower levels. These findings will improve our capability to predict rainstorms and prevent disasters in the Qinba region. Full article

Extreme precipitation events have been occurring frequently worldwide, and their causative factors and convection initiation (CI) mechanisms have been attracting more and more attention in recent years. As a comprehensive study on the CI mechanisms of extreme rainstorms over the northern slope of the Kunlun Mountains (KLM), Xinjiang, based on both observational and high tempo-spatial numerical simulation, the major findings of this work are as follows: A cold pool (CP) was formed in the northwestern Tarim Basin under the influence of early precipitation evaporation, and it moved towards the northern slope of the KLM several hours before the CI. With the movement of the CP, a significant vertical temperature gradient was formed close to the leading edge of the CP, thereby enhancing local convective instability (up to ~10 PVU). In addition, the vertical shear of the horizontal winds at the leading edge of the CP led to a notable increase in the baroclinic component of moist potential vorticity, thus reinforcing the local conditional symmetric instability (up to ~8 PVU), providing another important unstable energy for the CI. In addition, the combined effect of the convergent lifting of a boundary layer jet (BLJ, the maximum wind speed below 1 km exceeding 10 m s⁻¹) and the significant frontogenetical forcing (up to ~100 × 10⁻⁸ K m⁻¹ s⁻¹) at the leading edge of the CP were the causes of the release of the unstable energies. Further analysis of the frontogenetical forcing associated with the CP indicates that the convergence (up to ~2 × 10⁻³ s⁻¹), diabatic heating and slantwise terms (indicates the baroclinicity and inhomogeneity of the vertical momentum in horizontal direction) were the major contributors, whereas the deformation term at the leading edge of the CP provided a relatively weaker contribution. Full article

High-impact weather affects the safety and economic operation of power systems. In this study, to provide regional microclimate of high-impact weather for the local power grid system in the northern Heibei province (known as the Jibei region in China), ERA5-Land global reanalysis data during 1981–2020 with a 0.1° grid size (about 9 km) are adopted to analyze the climate statistics and changes of the disastrous weather that affects the power grids. The results show that there have been significant climate changes in the region, including a temperature increase of about 1 °C, evident humidity and precipitation reductions, for the Jibei region and the six sub-regions that concentrated with wind and solar energy development in the 40 years. Due to the differences in terrain, the climate changes differ significantly among the six renewable energy development regions. The main types of high-impact weather that affect the power grid in the region are heavy fog and icing events, followed by cold waves, snowstorms, and rainstorms. In general, with climate changes in the last several decades, the weather disasters in Jibei region have become more frequent. Since most high-impact weather events have a small scale, it is necessary to simulate the weather processes with high-resolution models to accurately quantify the characteristics of the weather processes that affect the power grid. Therefore, a refined regional meteorological model (with grid size of 2 km) based on four-dimensional data assimilation (JB-FDDA) is established for the Jibei region. With one year of model reanalysis data, we found that JB-FDDA can significantly improve the accuracy of the local meteorological fields, and properly depicted the details of severe weather that affect the power grid operation. This study provide an analytical approach for regional electricity meteorological disasters by using reanalysis data. Full article

By using various skill scores and spatial characteristics of spatial verification methods and traditional techniques of the model evaluation tool, the gridded precipitation observation, known as Climate Prediction Center Morphing Technique, gauge observation and three datasets that were derived from local, Shanghai, and Grapes models, respectively, were conducted to assess the 3 lead day rainfall forecast with 0.5 day intervals during the summer of 2020 over Central East China. Results have shown that the local model generally outperforms the other two for the most skill scores but usually with relatively larger uncertainties than the Shanghai model, and it has the least displacement errors for moderate rainfall among the three datasets. However, the rainfall of the Grapes model has been heavily underestimated and is accompanied with a large displacement error. Both the local and Shanghai model can effectively forecast the large-scale convection and rainstorms but over forecast the local convection, while the local model likely over forecasts the local rainstorms. In addition, the Shanghai model slightly favors over forecasting on a broad scale range and a broad threshold range, and the local model slightly misses the rainfall exceeding 100 mm. Generally, for a broadly comparative evaluation on rainfall, the popular dichotomous methods should be recommended when considering reasonable classification of thresholds if the accuracy is highly demanding. In addition, most spatial methods are suggested to conduct with proper pre-handling of non-rainfall event cases. Especially, the verification metrics including spatial characteristic difference information should be recommended to emphasize rewarding the severe events forecast under a global warming background. 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

Local climates are responding to global warming differently, and the changes in rainstorms in mountainous areas of Southwest China are of particular interest. This study, using monthly NCEP/NCAR reanalysis and daily precipitation observation of 90 meteorological stations from 1961 to 2021, analyzed the temporal and spatial variation characteristics of rainstorms and floods in Southwest China and their relationship with atmospheric circulations. The results led us to the following five conclusions: (1) Rainstorms and floods in southwest China mainly occur from June to August, during which time July has the most weather events, followed by August. (2) The southwest of Guizhou province, the southern edge of Yunnan province, and regions from the east of the Sichuan Basin to the north of Guizhou have experienced more rainstorms and floods, while the northwest regions of Southwest China have had fewer. (3) Over the last 61 years, rainstorms and floods have exhibited an overall rising trend, especially in the last 10 years. The year 2012 was an abrupt inflection point in rainstorms and floods in Southwest China, from low to high frequency, while the correlation coefficient between rainstorms and floods and the global surface temperature is above the 95% significance level. (4) Rainstorms and floods exhibit changes at periods of 8 years, 16 years, and 31 years. (5) Rainstorms and floods show a good correlation with multiple variables, such as South Asian high-pressure systems west of 90°E, the upper trough front, the northwest side of the western Pacific subtropical high, and the convergence of warm and wet air in the middle and lower layers with cold air on the ground. Full article

Recent years have seen a rise in the frequency and severity of extreme rainstorm events, which have caused widespread damage and death in numerous cities. The manufacture and use of storm drainage materials result in numerous environmental concerns in the construction industry. Green materials for storm drainage networks are environmentally friendly compared to their traditional counterparts. Identifying and assessing sustainability criteria for green materials for storm drain networks has been challenging. This study aims to determine the critical criteria for selecting green materials for storm drainage networks using a stationary analysis approach. To this end, a questionnaire survey was administered to Egyptian storm engineers to assess their importance based on a selection criteria 29 green materials. From the results obtained, “Operation and maintenance cost” and “Use of local material” were seen to be the “stationary materials”. The obtained findings in this research pave the way for the Egyptian storm industry towards becoming environmentally friendly, which will in turn improve the functioning mechanism of sewer networks. Full article

Canopy interception is an important part of forest ecosystem hydrological processes. It is the first stage of water distribution when rainfall reaches the canopy and has an important impact on nutrient inputs and water exchange. Pinus tabulaeformis is a main tree species in the rocky mountain areas of Northern China, and it is also a primary species for artificial afforestation. In previous studies of canopy interception, applications of the revised Gash model did not take rainfall characteristics into account. Therefore, in this study, rainfall patterns were divided according to the local rainfall characteristics in the rocky mountainous areas of Northern China. Rainfall was divided into three patterns. Rain pattern A was the main rainfall type. Rainfall patterns B and C were two types of rainstorms. Next, the revised Gash model was used to simulate Pinus tabulaeformis plantations under different rainfall patterns. The results showed that the canopy interception rate of Pinus tabulaeformis plantations in this area ranged from 14.7% to 17.9%. The revised Gash model can be used to simulate Pinus tabulaeformis plantations in the rocky mountainous areas of Northern China, with good simulation results for more than 80% of the conventional rainfall patterns. Furthermore, the canopy interception effect of simulated cumulative rainfall events was better than the individual rainfall event. The simulation effect for special rainfall patterns was not good, so it is necessary to improve the model parameters or collect more rainfall samples. These results can be used to explore the applicability of the revised Gash model in Pinus tabulaeformis plantations in the rocky mountain areas of Northern China. They also demonstrate different applicability of the model under different rainfall characteristics. Full article

Shallow landslides due to the soil saturation induced by intense rainfall events are very common in northern Italy, particularly in the Alps and Prealps. They are usually triggered during heavy rainstorms, causing severe damage to property, and sometimes causing casualties. A historical study and analysis of shallow landslides and mud-debris flows triggered by rainfall events in Lombardy was carried out for the period of 1911–2010, over an area of 14,019 km². In this study, intensity–duration rainfall thresholds have been defined using the frequentist approach, considering some pedological characteristics available in regional soil-related databases, such as the soil region, the textural class, and the dominant soil typological units (STU). The soil-based empirical rainfall thresholds obtained considering the soil regions of the study area were significantly different, with a lower threshold for landslide occurrence in the soil region M1 (Alps), where soils developed over siliceous parent material, with respect to the whole study area and the soil region M2 (Prealps), where soils developed over calcareous bedrocks. Furthermore, by considering textural classes, the curves were differentiated, with coarse-textured soils found more likely to triggerlandslides than fine soils. Finally, considering both texture and main soil groups, given the same rainfall duration, the rainfall amount and intensity needed to initiate a landslide increased in the following order: “coarse-skeletal” Cambisols < Umbrisols < Podzols < “fine” Cambisols. The results of this study highlighted the relevant role of pedological conditioning factors in differentiating the activation of rainfall-induced shallow landslides in a definite region. The information on soils can be used to define more precise rainfall–pedological thresholds than empirical thresholds based solely on meteorological conditions, even when they are locally defined. This knowledge is crucial for forecasting and preventing geo-hydrological processes and in developing better warning strategies to mitigate risks and to reduce socio-economic damage. Full article