Frequent Flood Disasters Research Articles

SPATIAL DISTRIBUTION PATTERNS OF POVERTY AND ECONOMIC GROWTH FOR ACHIEVING SUSTAINABLE DEVELOPMENT TARGETS IN EAST JAVA PROVINCE

<p>Poverty and economic growth are still indicators of a country's success in managing its resources and population. Countries in the world have agreed to make poverty alleviation the first sustainable development priority. This article aims to look at the spatial distribution pattern of poverty and regional characteristics, as well as the pattern and structure of economic growth in city districts in East Java Province. The methods used include spatial autocorrelation analysis, regional financial capability analysis, Klassen typology, and regional characteristics analysis. Based on the pattern of poverty distribution for the period 2014 – 2023, poverty in East Java Province tends to change with the dominance of class 2 poverty. Sampang, Pamekasan and Sumenep regencies tend to experience a stable poverty pattern in Class 3. Pockets of poverty are clustered on Madura Island with a percentage poverty is above 18% and the characteristics of a low Human Development Index (HDI) value, low number of (people’s business credit (KUR) recipients, inadequate sanitation, not very high economic growth, and frequent flood disasters. As many as 65.78% of areas in East Java Province have high financial capacity, so that policy direction can be focused on poverty pocket areas with a high percentage of poverty, through increasing HDI, optimizing KUR, fulfilling adequate sanitation, increasing disaster response, and developing leading sectors. for increasing Original Regional Income (PAD) and economic growth.</p>

A framework for using event evolutionary graphs to rapidly assess the vulnerability of urban flood cascade compound disaster event networks

Increasingly frequent flood disasters have caused great losses in recent years. Urban floods induce not only natural geological disasters but also social accidents. These disaster events, called urban flood cascade compound disaster events (UFCCDEs) in this study, have significant cascade, superposition, and amplification effects. However, conventional data sources and processing methods make it difficult to analyze the detailed course of disaster events caused by urban floods, thereby hindering the vulnerability assessment of UFCCDE networks (UFCCDENs). Herein, we propose a framework considering the interactions between disaster events caused by urban floods for rapidly and comprehensively assessing the vulnerability of the UFCCDEN. First, social media data (Sina Weibo) are processed to analyze the spatio-temporal distribution of UFCCDEs and construct a UFCCDEN based on an event evolutionary graph. Second, complex network theory is applied to evaluate the importance of disaster events and the vulnerability of disaster causal chains in the constructed UFCCDEN. Finally, the global efficiency of the network is calculated to assess the propagation efficiency of the UFCCDEN before and after implementing disaster mitigation strategies based on the assessment results to demonstrate the performance of the assessment framework. The coastal megacity Guangzhou was selected as an example. The results showed that, social media data can provide detailed and valid information about UFCCDEs, which can be used to construct the UFCCDEN based on the event evolutionary graph. Waterlogging is found to be the most important disaster event in the UFCCDEN. Furthermore, power facilities, drainage facilities, and roads should be given top priority in the prevention and mitigation of urban floods because of their significant cascading amplification effects. The proposed framework can make the propagation efficiency of the UFCCDEN markedly decrease by 37–62% and 44%, based on the assessment results of disaster events and causal chains, respectively.

Knowledge Management Model for Urban Flood Emergency Response Based on Multimodal Knowledge Graphs

Recently, frequent flood disasters in China have seriously threatened economic development and public safety. This paper addresses the need for a dynamic urban flood emergency knowledge management system in emergency management departments and the lack of systematic knowledge among emergency managers regarding urban flood control. A multimodal knowledge graph-based urban flood emergency knowledge management model was constructed to enhance the decision-making capabilities of emergency management departments, improve the efficiency of public emergency evacuation, and reduce losses from urban flood disasters by analyzing the shortcomings of the existing emergency management system. An intelligent and dynamic flood emergency knowledge management model was built. This paper integrates multimodal knowledge graph technology to establish a multimodal emergency knowledge management framework for urban flood control. It develops and simulates the proposed model’s application scenarios for urban flood emergency evacuation using the Flocking algorithm on the NetLogo platform. Through simulation experiments, the practicality and effectiveness of the model in real flood disaster situations were examined, particularly in simulating crowd evacuation behavior. The study found that the model significantly improves the accuracy of information and decision-making speed during emergency responses and supports emergency management departments in conducting targeted and personalized emergency decisions. This research provides a scientific basis for emergency management departments to optimize their emergency response strategies to flood disasters and serves as a reference and example for the application of multimodal knowledge graph technology in emergency management.

Exploring Herbaceous Plant Biodiversity Design in Chinese Rain Gardens: A Literature Review

Amidst rapid urbanization and escalating environmental degradation in China’s urban areas due to climate change, traditional drainage systems struggle to cope with rainfall, resulting in frequent flood disasters. In response, rain gardens have emerged as ecologically practical stormwater management solutions that integrate urban flood control with landscape design. Leveraging the dual benefits of rainwater purification and aesthetic enhancement provided by vegetation, herbaceous plant-based rain gardens have assumed a pivotal role in green infrastructure. However, dedicated research on the application of herbaceous plants in rain garden design is limited, especially within China’s water-stressed context. This study employs a literature review and case analysis to explore this critical issue. Initially, it delineates the concept of the sponge city introduced by the Chinese government. Subsequently, it reviews concepts and methods of plant biodiversity design in urban settings and rain gardens and elucidates the structure and function of rain gardens. Four Chinese rain gardens in different urban environments (old industrial areas, university campuses, urban villages, and urban highway green belts) were selected to examine the selection and arrangement of herbaceous plants while identifying deficiencies in their designs. Finally, feasibility suggestions are provided for the design of herbaceous plant diversity in Chinese rain gardens. This study’s findings can provide a reference for the planting design of herbaceous plants in rain gardens for other countries and regions with similar climates and environmental conditions.

Research and design of urban flood control and drainage dispatching system

In order to solve the problem of frequent flood disasters in urban areas, water conservancy models such as hydrological forecast, flood simulation and operation decision-making were studied and constructed for the waterway-region-urban flood control and drainage engineering facilities, and urban flood control and drainage operation system was designed with the model as the core. The overall structure of the system is "five horizontal and two vertical". The "five horizontal" bottom up are respectively the intelligent perception layer, cloud infrastructure layer, data layer, service layer and application layer, and the "two vertical" are respectively the security system and the standard specification system. On this basis, the function customization of the system is completed to achieve comprehensive display, early warning and forecast, flood simulation, risk assessment, project scheduling and intelligent decision-making functions.

Climate Change-Related Drivers of Migration in East Africa: An Integrative Review of the Literature

Despite the growing academic concern and policy interest in climate change drivers of migration, scientific evidence on the topic remains contested, with divergent claims of positive and negative contributions of climate change on human migration and displacement. This review seeks to assess the climate change-related drivers of migration with a focus on three East African countries: Tanzania, Kenya, and Uganda. They are among the most vulnerable countries in Africa, with one of the most mobile populations. The study used the available literature on climate change and migration as the data source. About 22 research articles on climate change and migration were sourced from the Web of Science and Scopus databases and critically reviewed. The review generally indicates that climate change effects such as frequent drought and flood disasters, livestock pests, and crop diseases influence migration and displacement in the region. On the other hand, rising sea levels pose imminent risks that can cause migration if adaptation measures are not taken. The review has also revealed that responses to drought or livestock and crop diseases, be it localized adjustment or out-migration, are determined by households' adaptive capacity. For rapid onset climate events such as floods, the most vulnerable are the less fortunate living in poorly constructed structures in flood-prone zones. This review proposes strengthening the climate policy framework by mainstreaming climate change migration in East African nations’ adaptation plans. It also calls for promoting alternative livelihood activities as an adaptation strategy in areas prone to climate change to lessen human-forced migration and displacement.

Landscape patterns and quantified attribution to runoff changes based on the Budyko framework in Nanning, China

ABSTRACT The urban stormwater flood and its ecological effects are becoming increasingly prominent underlying the rapid urbanization of China. Nanning is a typical southern city with frequent flood disasters and an urgent need to conduct quantitative research and explore effective countermeasures. Therefore, the quantitative contributions of rainfall, evapotranspiration (ET), and landscape patterns to urban stormwater runoff are analysed using the Budyko framework in this paper. The results show that the rainfall, landscape pattern, evapotranspiration and runoff in Nanning have significant synergistic interaction. The change of rainfall has a positive effect on runoff increment, accounting for 5.9~12.3% of the annual rainfall. The change of the underlying surface parameter (n) has a negative effect on runoff decrement, accounting for −14.8%. Evidently, the blue (water space), green and grey infrastructure of the underlying surface and its spatial pattern largely determine the quantity and spatial distribution of storm runoff in Nanning City.

Combining Landsat, VIIRS Night-time Light, and Sentinel-1 SAR for Spatial Flood Risk Assessment in Coastal Area: an Earth Engine Cloud Computing Process

The intensity of development in coastal areas stimulates various potential issues such as flood disasters. This study aims to demonstrate the importance of latest methods and geospatial data as inputs for coastal spatial planning policies in efforts to reduce flood disaster risks. Leveraging spatial analysis with cloud computing through Google Earth Engine (GEE), this research assesses flood risk components—hazards, vulnerability, and capacity. The method involves processing SAR Sentinel-1 data to map flood inundation as a representation of hazards, analyzing Landsat and WorldPop data to evaluate vulnerability, and assessing capacity by utilizing VIIRS nighttime light level imagery to determine economic activities. The chosen research study location is the coastal area of Pekalongan due to frequent flood disasters throughout the year. The results demonstrate that cloud computing is capable of assessing flood risks. The flood inundation model using SAR data covers an area of 2,780 hectares with an accuracy of 96.75%. The analysis also reveals the highest vulnerability level, reaching 15.7% (946.32 hectares) of the total area. The capacity analysis indicates a medium to high level of 15% (913.6 hectares). The assessment of flood risks in the coastal area is dominated by the medium to very high-risk class, covering 43% (2,631.84 hectares) of the area. In conclusion, integrating cloud-based flood risk modeling into spatial planning is crucial, considering disaster resilience for sustainable human habitats.

Climate change increases the instability of the water supply for hydropower stations on the Tibetan Plateau

In recent decades, global warming has had a significant impact on the streamflow across the Tibetan Plateau. As the largest tributary in the upper reaches of the Yangtze River, the Yalong river is known for its abundant hydropower resources, and the world’s largest multi-energy complementary base has been built in the Yalong River Basin. However, prudent water resource planning is limited by the lack of long-term, detailed and reliable streamflow records over the Yalong river basin. Here, we develop an October–June streamflow reconstruction for the Yalong River, based on composite tree-ring chronology of Picea likiangensis from seven sampling sites. The reconstruction goes back to 1480 CE, and accounts for 46.5% of the instrumental streamflow variance during 1962–2012. This record indicates that the Interdecadal Pacific Oscillation and the Atlantic Multi-decadal Oscillation were the major contributing factors to streamflow variations. A significant and stable correlation with temperature was found over the past few centuries on the interannual scale. Projections suggest that future climate change may lead to more frequent flood disasters in the Yalong River Basin.

A Framework on Fast Mapping of Urban Flood Based on a Multi-Objective Random Forest Model

Fast and accurate prediction of urban flood is of considerable practical importance to mitigate the effects of frequent flood disasters in advance. To improve urban flood prediction efficiency and accuracy, we proposed a framework for fast mapping of urban flood: a coupled model based on physical mechanisms was first constructed, a rainfall-inundation database was generated, and a hybrid flood mapping model was finally proposed using the multi-objective random forest (MORF) method. The results show that the coupled model had good reliability in modelling urban flood, and 48 rainfall-inundation scenarios were then specified. The proposed hybrid MORF model in the framework also demonstrated good performance in predicting inundated depth under the observed and scenario rainfall events. The spatial inundated depths predicted by the MORF model were close to those of the coupled model, with differences typically less than 0.1 m and an average correlation coefficient reaching 0.951. The MORF model, however, achieved a computational speed of 200 times faster than the coupled model. The overall prediction performance of the MORF model was also better than that of the k-nearest neighbor model. Our research provides a novel approach to rapid urban flood mapping and flood early warning.

Evaluation of the Sustainable Development of Macau, Based on the BP Neural Network

(1) Background: the rapid development of cities and the process of industrialization has improved the level of economic development for all humanity, accompanied by a series of problems, such as the waste of ecological resources and the environmental destruction. Macau has long been one of the regions with the most active economic activities. However, the phenomenon of economic recession, unreasonable land use, and frequent flood disasters have appeared in the past few decades, which violate the concept of sustainable development; (2) Methods: this paper uses the BP neural network model to evaluate the sustainable development of Macau; (3) Results: the weight ranking of sustainable development is: economic > social > ecological environment. A correlation analysis shows that ecology and economy have a significant negative correlation; (4) Conclusions: In Macau, economic growth is given priority while social and ecological environment development lags behind. Macau has problems, such as a unitary economic structure and a high population density. This paper advocates that investment in ecological protection should be increased, environmental resources should be optimized and saved, and the concept of sustainable development should be strengthened in the application of Macau’s urban development.

Geospatial analysis of flood emergency evacuation sites in Accra.

This research is useful as mapping could increase awareness of evacuation sites to speed up rapid response to immediate impacts of flood events. The findings of the study will facilitate future decisions for demarcating potential flood emergency evacuation sites. The overall aim of this study is to contribute to literature, policy, spatial analysis and the practice of flood risk management in the study area. The research findings can also be applied to other flood-prone areas with similar contexts as the study site.

Extreme precipitation over northern China in autumn 2021 and joint contributions of tropical and mid-latitude factors

Frequent heavy precipitation and severe flood disasters struck northern China in early autumn 2021, with seven provinces/municipalities surpassing their precipitation records since 1961. Causes for such extreme events from the climate perspective are unclear because the variability of autumn precipitation in northern China is poorly understood. This study revealed that the event was directly caused by the extremely north-westward location of the western Pacific subtropical high (WPSH), which was jointly induced by several tropical and mid-latitude factors. The developing La Niña and warmer than normal tropical Atlantic sea surface temperature altered the Pacific Walker Circulation and enhanced the convection over the tropical western Pacific. Meanwhile, the Madden–Julian Oscillation stagnated for a long time in its phases 3–5 in early autumn and contributed constructively to the active convection over the tropical eastern Indian Ocean and western Pacific. These effects altogether excited a lower-tropospheric cyclone anomaly to the west of the Philippines and shifted the WPSH northwestwards in early autumn. A mid-latitude cyclonic centre was also observed upstream of East Asia. It dispersed Rossby wave energy southeastwards in the form of cold air invasions. The resultant convergence of cold and dry air from the north with warm and moist air from the south together caused extreme precipitation over northern China in autumn 2021. Relevant conclusions can enhance our current understanding of the causes of autumn extreme precipitation events in northern China and improve our ability to predict such events and prevent resultant disasters.

Research hotspots and trends of urban stormwater management in China based on resilience theory.

Under the context of frequent flood disasters in China, stormwater management practices such as sponge cities can play a role in flood mitigation and improve the 'resilience' of cities to flood. Resilient city is a concept related with adaptation to disasters, which is increasingly applied to stormwater and flood risk management in some countries. Based on the theory of resilience, we used the scientific metrological analysis tool CiteSpace to review the actualities of Chinese research on rainfall flood, analyzed the hot spots and related technologies of stormwater management from three aspects including ecology, engineering and society of stormwater resilience. Results showed the shortcomings in cross-sectoral stormwater management, and water regulation and storage management of land use at different scales from region to block. We proposed that 'ecology-engineering-society' should be set as the core to establish an adaptive and resilient stormwater management system that offers service to 'region-city-block' with the support of multi-technology integration in the future.

Driving Effects and Spatial-Temporal Variations in Economic Losses Due to Flood Disasters in China

The economic loss caused by frequent flood disasters poses a great threat to China’s economic prosperity. This study analyzes the driving factors of flood-related economic losses in China. We used the extended Kaya identity to establish a factor decomposition model and the logarithmic mean Divisia index decomposition method to identify five flood-related driving effects for economic loss: demographic effect, economic effect, flash flood disaster control effect, capital efficiency effect, and loss-rainfall effect. Among these factors, the flash flood disaster control effect most obviously reduced flood-related economic losses. Considering the weak foundation of flash flood disaster prevention and control in China, non-engineering measures for flash flood prevention and control have been implemented since 2010, achieving remarkable results. Influenced by these measures, the loss-rainfall effect also showed reduction output characteristics. The demographic, economic, and capital efficiency effects showed incremental effect characteristics. China’s current economic growth leads to an increase in flood control pressure, thus explaining the incremental effect of the economic effect. This study discusses the relationship between flood-related economic loss and flash flood disaster prevention and control in China, adding value for the adjustment and formulation of future flood disaster prevention policies.

A Numerical Simulation of the Development Process of a Mesoscale Convection Complex Causing Severe Rainstorm in the Yangtze River Delta Region behind a Northward Moving Typhoon

In recent years, due to the influence of global warming, extreme weather events occur frequently, such as the continuous heavy precipitation, regional high temperature, super typhoon, etc. Tropical cyclones make frequent landfall, heavy rains and flood disasters caused by landfall typhoons have a huge impact, and typhoon rainstorms are often closely related to mesoscale and small-scale system activities. The application 2020 NCEP (National Centers for Environmental Prediction) final operational global analysis data and WRF (Weather Research and Forecasting model, version 3.9) mesoscale numerical prediction model successfully simulates the evolution characteristics of the mesoscale convective complex (MCC) that caused an extreme rainstorm in the Yangtze River delta region behind a northwards typhoon in this article. The results show that a meso-β-scale vortex existed in the mid- to upper troposphere in the region where the MCC occurred; accompanied by the occurrence of the meso-β-scale vortex, the convective cloud clusters developed violently, and its shape is a typical vortex structure. The simulation-sensitive experiment shows that the development of the meso-β-scale cyclonic vortex is the main reason for the enhancement of MCC. The occurrence and development of the MCC is manifested as a vertical positive vorticity column and a strong vertical ascending motion region in the dynamic field. In the development and maturity stage of the MCC, the vorticity and vertical rising velocity in the MCC area are significantly greater than those in the weakened typhoon circulation, which shows significant mesoscale convective system characteristics. The diagnostic analysis of the vorticity equation shows that the positive vorticity advection caused by the meso-β-scale cyclonic vortex in the mid- to upper troposphere plays important roles in the development of the MCC. Enhanced low-level convergence enhances vertical ascending motion. The convective latent heat release also plays an important role on the development of the MCC, changes the atmospheric instability by heating, enhances the upward movement, and delivers positive vorticity to the upper level, making the convection develop higher, forming a positive feedback mechanism between low-level convergence and high-level divergence. The simulation-sensitive experiment also shows that the meso-β-scale cyclonic vortex formation in this process is related to convective latent heat release.

Simulation and Optimization Strategy of Storm Flood Safety Pattern Based on SCS-CN Model.

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.

Ensemble Flood Risk Assessment in the Yangtze River Economic Belt under CMIP6 SSP-RCP Scenarios

The Yangtze River Economic Belt (YREB) is an important part of China’s “two screens and three belts” strategic ecological security barrier, and the urban agglomeration along the YREB is the core of its economic development. However, it has suffered the most from frequent and severe flood disasters that were affected by torrential rains, urbanization, and human activities, with climate change intensifying the potential occurrence of flood disasters in this area. Based on the CMIP6 climate data, this study constructed a flood risk assessment index system and assessed the temporal and spatial changes of the flood risk in the YREB during 2020–2050 under four shared socioeconomic pathways (SSP) scenarios, including SSP126, SSP245, SSP370, and SSP585. From the perspective of temporal change, the results showed that at the grid level, the area of middle-low risk (0.55 < R ≤ 0.65) accounted for 60% of the total area of the YREB and area of high-risk (R > 0.85) fluctuated first and then decreased under the four scenarios, with the area of high-risk being largest in the future under the SSP585 scenario. Specifically, at the city level, around half of the cities in the YREB had faced high flood risk and the risk showed an increasing trend during 2020–2050 under the SSP370 scenario. From the perspective of spatial change, the flood risk of the YREB presented a spatial pattern of low in the west and high in the east, with high risk mainly concentrated in the cities in the lower reaches of the YREB and also Chongqing and Sichuan. Compared with SSP126 and SSP245 scenarios, it showed that high-risk areas were larger under high emission scenarios SSP370 and SSP585, which were mostly concentrated in middle and lower reaches of the YREB and the cities of Chongqing and Chengdu during 2020–2050. Especially, flood risk showed an increasing trend in the middle and lower reaches of the YREB during 2020–2050, and the regions with high vulnerability would have greater socio-economic losses. The finding would provide scientific support for resilience improvement, risk reduction and management, and formulating policies to achieve green and sustainable development in the YREB.

A Flood Damage and Shelter Need Assessment: A Case Study of Mueang Sing Buri, Thailand

Flooding is one of the main disasters in Thailand and Mueang Sing Buri is among those areas hit. Located on the Chao Phraya River Basin, in the central region of Thailand, the area receives a large amount of runoff during monsoon seasons which causes frequent flood disasters. The aims of this research are to create a flood hazard map and to estimate the number of people that may need shelter after the occurrence of a flood, and to evaluate whether the shelter capacity is adequate in Mueang Sing Buri. To explore the potential locations of emergency shelters, the relevant information related to flooding was initially recorded, such as building detail, flood depth, elevation map, and flood risk map. The available space of each building varies by the characteristics of building types. The calculation of shelter capacity thus depends on characteristics of the buildings, accessibility, and percent of vacant area. The emergency shelter assessment benefits many sectors in the design of preparation plans for hazard management.

Impacts of climate change-related flood events in the Yangtze River Basin based on multi-source data

Global losses caused by floods are gradually increasing under the influence of climate change and human activities. The Yangtze River (YR) economic belt has continued to experience frequent flood disasters over the years; therefore, clarifying the significant flood risk factors is highly relevant for the development of the region. In this study, we investigated the flood risk factors in the Yangtze River Basin (YRB) during 2002–2018 based on meteorological data, reconstructed terrestrial water storage (TWS) data from Gravity Recovery Climate Experiment (GRACE) (GRACE-TWS), and Landsat data. The major conclusions were as follows: (1) the principal components (i.e., the first, third, and fourth principal components (PC1, PC3, and PC4)) of Standardized Precipitation Evapotranspiration Index (SPEI) at a 12-month scale (SPEI12) were more significantly (P < 0.05) correlated with teleconnection indices (i.e., Atlantic Multi-decadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), Southern Oscillation Indices (SOI), and Multivariate El Niño-Southern Oscillation (ENSO) Index (MEI)), than the SPEI at 6-month scale (SPEI6) in the YRB during 2002–2018; (2) the changes in water bodies reflected by Landsat data (i.e., Landsat 5, Landsat 7, and Landsat 8 OLI) for the YRB confirmed the wet periods (i.e., 2002–2005, 2010, 2012–2013, and 2015–2018) monitored by SPEI (i.e., SPEI6 and SPEI12); and (3) while the Pearson correlation coefficients indicated a significant linear relationship between the major hydrological factors (e.g., precipitation, runoff, GRACE-TWS, flood potential index (FPI), and soil moisture (SM)) in the YRB, the precipitation detected by the GRACE-TWS and SM with one-month lag phase, had the maximum correlation coefficients of 0.83 and 0.85, respectively. Significant relationships (r2 = 0.48 and r2 = 0.92, P < 0.05) were found between variable infiltration capacity (VIC)-runoff and predicted runoffs based on these factors (i.e., precipitation, GRACE-TWS, flood potential index (FPI), and SM) and the random forest regression. This study provides significant hydrological information and contributes to approaches aimed at supporting climate resilience and investments in the YRB.