The influences of the tectonic subsidence and the siltation on the situation of preventing flood disasters in the Dongting Lake area

With the long-term data of the geodetic sea level measurements undertaken in the Dongting Basin and the recent sediment data of Dongting Lake, we analyze the tectonic subsidence rate of the Dongting Basin and the sedimentary rate of Dongting Lake. From the point of view of geomorphology and hydrogeology, we distinguish the two different spatial concepts between 'the basin of Dongting Lake' and 'the Dongting Basin'. Then, we discuss the influences of the tectonic subsidence and the siltation on the levees and the space of storing flood. The better quality of levees is required due to the tectonic subsidence and the siltation, and the difficulties of preventing flood disasters are increasing. The space of storing flood is not affected by the tectonic subsidence, but by the siltation. At present, the sedimentary rate of Dongting Lake is higher than the tectonic subsidence rate of the Dongting Basin. The tectonic subsidence capacity of the Dongting Basin counteracts a part of sedimentary capacity, and the shrinking tendency of Dongting Lake is restrained to a certain extent, but the tectonic subsidence is harmful to the situation of preventing flood disasters in the Dongting Lake area.

Risk Identification for the Ecological Environment of Flood Disasters Based on the Life Cycle

Aiming at the complexity of ecological environment risk of flood disaster, the life cycle of flood disaster is defined based on the relevant literatures, which is divided into incubation period, development period, outbreak period, recession period and extinction period. The characteristics of each period are analyzed. Further, the main risks for ecological environment faced at each stage under the life cycle of flood disaster are studied systematically to form the systematic ecological environment risk system for flood disaster.

A comprehensive framework for assessing the spatial drivers of flood disasters using an Optimal Parameter-based Geographical Detector-machine learning coupled model

Flood disasters pose serious threats to human life and property worldwide.Exploring the spatial drivers of flood disasters on a macroscopic scale is of great significance for mitigating their impacts.This study proposes a comprehensive framework for integrating driving-factor optimization and interpretability,while considering spatial heterogeneity.In this framework,the Optimal Parameter-based Geographic Detector(OPGD),Recursive Feature Estimation(RFE),and Light Gradient Boosting Machine(LGBM)models were utilized to construct the OPGD–RFE–LGBM coupled model to identify the essential driving factors and simulate the spatial distribution of flood disasters.The SHapley Additive ExPlanation(SHAP)interpreter was employed to quantitatively explain the driving mechanisms behind the spatial distribution of flood disasters.Yunnan Province,a typical mountainous and plateau area in Southwest China,was selected to implement the proposed framework and conduct a case study.For this purpose,a flood disaster inventory of 7332 historical events was prepared,and 22 potential driving factors related to precipitation,surface environment,and human activity were initially selected.Results revealed that flood disasters in Yunnan Province exhibit high spatial heterogeneity,with geomorphic zoning accounting for 66.1%of the spatial variation in historical flood disasters.The OPGD–RFE–LGBM coupled model offers clear advantages over a single LGBM in identifying essential driving factors and quantitatively analyzing their impacts.Moreover,the simulation performance shows a slight improvement(a 6%average decrease in RMSE and an average increase of 1%in R2)even with reduced factor data.Factor explanatory analysis indicated that the combination of the essential driving factor sets varied across different subregions;nevertheless,precipitation-related factors,such as precipitation intensity index(SDII),wet days(R10MM),and 5-day maximum precipitation(RX5day),were the main driving factors controlling flood disasters.This study provides a quantitative analytical framework for the spatial drivers of flood disasters at large scales with significant heterogeneity,offering a reference for disaster management authorities in developing macro-strategies for disaster prevention.

The Dynamics of Interorganizational Collaboration in Disaster Management:A Network Study Based on Flood Disasters in China

Interorganizational collaboration networks have become an important tool for disaster management.However,research on how different organizations can effectively collaborate throughout the entire disaster management process in centralized states such as China is scarce.This study begins to fill this lacuna by investigating interorganizational collaboration in different phases of disaster management and analyzing changes in the structure of the networks constructed during the preparedness and response phases of the 2020 flood disaster in Hubei Province,China.Building on the complex adaptive systems(CAS)theory,we argue that interorganizational collaboration changes dynamically according to its tasks and requirements.In the preparedness phase,interorganizational collaborations primarily follow established plans and choose horizontal selforganized collaboration mechanisms.However,when the urgent information and resource requirements increase in the response phase,many organizations choose vertical mandatory collaboration mechanisms.We found that organizations at the central and provincial levels in China were well positioned to coordinate information and resources and strengthen the interorganizational collaboration and communication that is crucial in disaster management.These findings contribute to the study of interorganizational collaboration networks in disaster management.

Risk assessment of coastal flooding disaster by storm surge based on Elevation-Area method and hydrodynamic models:Taking Bohai Bay as an example

The future inundation by storm surge on coastal areas are currently ill-defined.With increasing global sealevel due to climate change,the coastal flooding by storm surge is more and more frequently,especially in coastal lowland with land subsidence.Therefore,the risk assessment of such inundation for these areas is of great significance for the sustainable socio-economic development.In this paper,the authors use Elevation-Area method and Regional Ocean Model System(ROMS)model to assess the risk of the inundation of Bohai Bay by storm surge.The simulation results of Elevation-Area method show that either a 50-year or 100-year storm surge can inundate coastal areas exceeding 8000 km^(2);the numerical simulation results based on hydrodynamics,considering ground friction and duration of the storm surge high water,show that a 50-year or 100-year storm surge can only inundate an area of over 2000 km^(2),which is far less than 8000 km^(2);while,when taking into account the land subsidence and sea level rise,the very inundation range will rapidly increase by 2050 and 2100.The storm surge will greatly impact the coastal area within about 10-30 km of the Bohai Bay,in where almost all major coastal projects are located.The prompt response to flood disaster due to storm surge is urgently needed,for which five suggestions have been proposed based on the geological background of Bohai Bay.This study may offer insight into the development of the response and adaptive plans for flooding disasters caused by storm surge.

Glacial Lake Outburst Flood Disasters and Integrated Risk Management in China

High-risk areas for glacial lake outburst flood(GLOF) disasters in China are mainly concentrated in the middle-eastern Himalayas and Nyainqe?ntanglha(Nyenchen Tanglha Mountains), Tibetan Plateau. In the past 20 years, glaciers in these regions have retreated and thinned rapidly as a response to regional climate warming,leading to the formation of new glacial lakes and the expansion of existing glacial lakes. These areas are located in the border belt between the Indian and the Eurasian plates, where tectonic seismic activity is also frequent and intense. Earthquakes have often compromised the stability of mountain slopes, glaciers, and moraine dams, resulting in an imbalance in the state of glacial lakes and an increase of loose materials in valleys. It is foreseeable that the possibility of GLOFs and disaster occurrence will be great in the context of frequent earthquakes and continued climate warming. This article presents the temporal and spatial characteristics of GLOF disasters, as well as the conditions and mechanisms of GLOF disaster formation,and proposes an integrated risk management strategy to cope with GLOF disasters. It aims to facilitate the mitigation of the impacts of GLOF disasters on mountain economic and social systems, and improve disaster risk analysis, as well as the capability of risk management and disaster prevention and reduction.

Estimation of Critical Rainfall for Flood Disasters in the Qinghai-Tibet Plateau

According to the results of The Second Comprehensive Scientific Expedition on the Qinghai-Tibet Plateau,the balance of solid and liquid water on the Qinghai-Tibet Plateau is disturbed,and a large amount of solid water,such as glaciers and perpetual snow,is transformed into liquid water,which aggravates the risk of flood disasters in the Plateau.Based on the historical flood disaster records of the Qinghai-Tibet Plateau,this paper analyzed the temporal and spatial distribution characteristics of the flood disasters in the Plateau,and estimated the critical rainfall for the flood disasters combined with precipitation data from the meteorological stations in each basin of the Qinghai-Tibet Plateau.The results show that most of the flood disaster events in the Plateau are caused by precipitation,and the average annual occurrence of flood disasters is more than 30 cases and their frequency is on the rise.The high frequency areas of flood disasters in the Qinghai-Tibet Plateau are mainly in the Hehuang Valley and the Hengduan Mountains area;the secondary high frequency areas are located in the valley area of South Tibet and the peripheral area of the Hehuang valley.Finally,we found that the highest critical rainfall value of flood disasters in the Qinghai-Tibet Plateau is in the southern area of the plateau,followed by the eastern and southeastern parts of the plateau,and the lowest values are in the central,western and northern parts of the Plateau.

Dryness-wetness change and regional differentiation of flood-drought disasters in Guangdong during 1480-1940AD

Based on the historical records of the drought and flood disasters during 1480-1940AD, this paper reconstructs the sequences of wetness index （WI） and drought and flood disasters. We find a good identical relationship between the fluctuation of WI sequence and the δ^18O record of the GISP2 ice core in Greenland, which shows an apparent monsoonal disposal pattern of moisture and temperature. By applying the Morlet Wavelet Transform Method to deal with the data, several apparent periodicities, such as 7-8a, 11-15a, 20-23a and ca 50a, are revealed, among which some can be attributed to the solar forcing. Based on results of Cluster Analysis of dry-wet changes, we resume the regional differentiation pattern of flood-drought disasters all over Guangdong during different climatic intervals in the LIA and, find the western and northern parts of Guangdong have undergone drastic changes in drought-flood regional differentiation, but the eastern part is relatively stable, and the area of the Pearl River Delta shows stable condition of more flood disasters.

Spatiotemporal Characteristics of Droughts and Floods in Shandong Province,China and Their Relationship with Food Loss

Mastering the pattern of food loss caused by droughts and floods aids in planning the layout of agricultural production,determining the scale of drought and flood control projects,and reducing food loss.The Standardized Precipitation Evapotranspiration Index is calculated using monthly meteorological data from 1984 to 2020 in Shandong Province of China and is used to identify the province’s drought and flood characteristics.Then,food losses due to droughts and floods are estimated separately from disaster loss data.Finally,the relationship between drought/flood-related factors and food losses is quantified using methods such as the Pearson correlation coefficient and linear regression.The results show that:1)there is a trend of aridity in Shandong Province,and the drought characteristic variables are increasing yearly while flood duration and severity are decreasing.2)The food losses caused by droughts in Shandong Province are more than those caused by floods,and the area where droughts and floods occur frequently is located in Linyi City.3)The impact of precipitation on food loss due to drought/flood is significant,followed by potential evapotranspiration and temperature.4)The relationship between drought and flood conditions and food losses can be precisely quantified.The accumulated drought duration of one month led to 1.939×10^(4)t of grain loss,and an increase in cumulative flood duration of one month resulted in1.134×10^(4)t of grain loss.If the cumulative drought severity and average drought peak increased by one unit,food loss due to drought will increase by 1.562×10^(4)t and 1.511×10^(6)t,respectively.If the cumulative flood severity and average flood peak increase by one unit,food loss will increase by 8.470×103t and 1.034×10^(6)t,respectively.

Analysis of Forecast and Early Warning of Flood in Medium and Small Rivers

Flooding of small and medium rivers is caused by environmental factors like rainfall and soil loosening.With the development and application of technologies such as the Internet of Things and big data,the disaster supervision and management of large river basins in China has improved over the years.However,due to the frequent floods in small and medium-sized rivers in our country,the current prediction and early warning of small and medium-sized rivers is not accurate enough;it is difficult to realize real-time monitoring of small and medium-sized rivers,and it is also impossible to obtain corresponding data and information in time.Therefore,the construction and application of small and medium-sized river prediction and early warning systems should be further improved.This paper presents an analysis and discussion on flood forecasting and early warning systems for small and medium-sized rivers in detail,and corresponding strategies to improve the effect of forecasting and early warning systems are proposed.

Relationship between Regional Rainstorm Index and Flood Disaster Ratio of Crop

According to the daily precipitation data in Beijing area from 1985 to 2008,rainstorm weather index （10.4-38.8 mm） and climate index （daily precipitation ≥27.5 mm） in Beijing area were obtained by using the determination method of extreme climate event index recommended by IPCC. Based on rainstorm weather index,rainstorm climate index and national rainstorm standard,the number of rainstorm days and rainfall amount in past years were calculated,and the correlation of annual number of rainy days,rainstorm days,precipitation and rainstorm amount with the flood disaster ratio of crop was analyzed,and the results showed that annual number of rainy days and rainstorm days couldn＇t reflect flood disaster ratio of crop truly,while annual precipitation and rainstorm amount had obvious linear positive correlation with the flood disaster ratio of crop. In addition,the correlation degree between rainstorm amount calculated by regional climate index and flood disaster ratio of crop was the highest,so it was suggested that rainstorm amount calculated by regional rainstorm climate index could be used to predict and evaluate flood disaster.

Measurement assessment of forest benefit in reducing flood disaster

Based on the analysis of forest inner mechanism, forest benefit in re ducing flood disaster is defined. Through the characteristic analysis of forest benefit in reducing flood disaster, it is suggested that it is impossible to ado pt the microanalysis method for studying the forest benefit in reducing flood, t he macro analysis is the only method to be adopted. With the special case of dis aster flooding of Changjiang River happened in 1998, the forest benefit in reduc ing flood disaster was scientifically assessed. The estimated results of forest benefit in reducing flood shows that forest vegetation establishment is the radi cal way to control flood, but it only equals to 5 percent of the total benefits of water conservancy facilities.

A High Precision Comprehensive Evaluation Method for Flood Disaster Loss Based on Improved Genetic Programming

Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming (GP) solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss (EGFD) on the basis of improved genetic programming (IGP) is presented (IGP-EGFD). The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance. Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.

RESEARCH ON SYSTEM OF FLOOD DISASTER CONTROL AND REDUCTION SUPPORTED BY GIS IN MEDIUM AND SMALL BASINS

Southeast China coastal areas belong to subtropical monsoon climatic zone, thus easily affected by floods resulted from typhoons and rainstorms. Since the areas of river basins are small, rivers flood regulation capacities are low, and therefore flood hazard is grave. In this paper, taking the Yongjiang basin in southeast China as an example, the approaches and methods of geographic information system(GIS) applied to flood disaster control and reduction research on small basin are explored. On GIS help the rainfall runoff calculation model and the river channel flood routing model are developed. And the evaluating flood submerged area and the damage assessment models are built supported by digit elevation models. Lastly the decision support system on GIS supported for flood control in research basin has been set up. This greatly improves flood proofing decision making capacities in river basin, and provides valuable information and a mode for flood prevention and reduction in the medium and small basin. Meanwhile, the research indicates that technologies of GIS provide a powerful tool for flood disaster control.

GIS-based Risk Zone of Flood Hazard in Anhui Province

[Objective] The aim was to study the flood disaster risks in Anhui Province based on GIS. [Method] Taking country as basic unit, the 1∶ 250 000 basic geographic data in Anhui Province as basis, from the angle of flood disaster hazard and economic vulnerability, and by dint of the calculation of the weight of each impact factor with entropy-based fuzzy AHP method, flood risk assessment model was established to study the flood disaster risks zoning in Anhui Province. Using nearly 10 years of disaster information in Anhui Province, the flood risk zoning of Anhui Province was studied. And the risks evaluation results of flood disaster risks in Anhui Province in recent 10 years were checked. [Result] The regional difference of flood disaster in Anhui Province was large. The most serious area of flood disaster was in Lingquan in Fuyang and Lingbi in Huaibei. The risks degree degraded from south mountainous area in north Anhui Plain to the mountainous area of west Anhui Province, from Huaibei Plain to the hilly area of Jianghuai and mountainous area of south Anhui Province. The disaster situation in Anhui Province in recent 10 years suggested that the areas suffering from serious economic losses were in Lingbi, Guzheng and Huainan in the south part of Huaibei Plain. The places having serious agricultural crops damages were in Tangshan and Xiao County in Huaibei Plain. Besides, the Jingzhai area in the Dabieshan in west Anhui Province also had serious agricultural crops in Jinzhai. Other places had limited disaster-stricken impacts; the distribution of disaster-stricken population and impacted area of agricultural crops were basically consistent. Therefore, the risk evaluation of flood disaster of Anhui Province based on GIS was basically consistent with reality. [Conclusion] This GIS-based flood risk zoning method had good practicability.

An AMSR-E Data Unmixing Method for Monitoring Flood and Waterlogging Disaster

Spectral remote sensing technique is usually used to monitor flood and waterlogging disaster.Although spectral remote sensing data have many advantages for ground information observation,such as real time and high spatial resolution,they are often interfered by clouds,haze and rain.As a result,it is very difficult to retrieve ground information from spectral remote sensing data under those conditions.Compared with spectral remote sensing tech-nique,passive microwave remote sensing technique has obvious superiority in most weather conditions.However,the main drawback of passive microwave remote sensing is the extreme low spatial resolution.Considering the wide ap-plication of the Advanced Microwave Scanning Radiometer-Earth Observing System(AMSR-E) data,an AMSR-E data unmixing method was proposed in this paper based on Bellerby's algorithm.By utilizing the surface type classifi-cation results with high spatial resolution,the proposed unmixing method can obtain the component brightness tem-perature and corresponding spatial position distribution,which effectively improve the spatial resolution of passive microwave remote sensing data.Through researching the AMSR-E unmixed data of Yongji County,Jilin Provinc,Northeast China after the worst flood and waterlogging disaster occurred on July 28,2010,the experimental results demonstrated that the AMSR-E unmixed data could effectively evaluate the flood and waterlogging disaster.

Spatio-temporal changes of exposure and vulnerability to floods in China

A socio-economic data set on China＇s historical flood losses for the period 1984--2012 was compiled to analyze the exposed population, economy, and crop area as well as the vulnerabilities of the population and economy to floods. The results revealed that the exposed population was approximately 126 persons km-2 per year when taking China as a whole; in terms of the economy, potential losses due to floods were estimated to be approximately 1.49 million C/W4 km 2 and the crop area exposed to floods covered 153 million hm2 per year. China＇s total exposure to floods significantly increased over the analysis period. The areas that showed the higher exposure were mainly located along the east coast. The population＇s vulnerability to floods showed a significantly increasing trend, however, the economic vulnerability showed a decreasing trend. The populations and economies that were most vulnerable to floods were in Hunan, Anhui, Chongqing, Jiangxi, and Hubei provinces. The municipalities of Shanghai, Beijing, and Tianjin showed the lowest vulnerabilities to floods.

Constrction of watershed flood disastermanagement information system and its application to the catastrophic flood of theYangtze River in 1998

This paper introduces a general method of establishing Watershed Flooding Disaster Management Information System (WFDMIS). The functions, database, models, user interface, software and hardware are considered. An application example in Poyang Lake Basin was given.

Comprehensive Evaluation of Flood and Flood in the Yellow River Basin Based on Gray Correlation Analysis

Due to the concentrated rainfall and serious soil erosion in July and August in the Yellow River Basin, the flood discharge is not timely leading to serious floods. Therefore, a reasonable assessment of the flood-affected areas, advance arrangements for the deployment of the Yellow River basin flood disaster prevention and control plays a decisive role. For this purpose, this paper proposes a level assessment method based on the flood which analyzes three factors related to flooding disaster (disaster impact range, social index, and property index) through the gray correlation analysis method, to evaluate the level of flood disaster. Different from the traditional assessment method, which evaluates the nature of flood from the perspective of indicators such as frequency, duration, and magnitude, or indirect factors such as rainfall and soil loss, this paper conducts qualitative calculation of macro-scale indicators from the perspective of post-disaster losses in previous years. This study provides a new way of thinking and method for the classification of the flood disaster, which has certain practical application value under the condition of conforming to its own use.

Flood disaster monitoring based on Sentinel-1 data:A case study of Sihu Basin and Huaibei Plain,China

Summer floods occur frequently in many regions of China,affecting economic development and social stability.Remote sensing is a new technique in disaster monitoring.In this study,the Sihu Basin in Hubei Province of China and the Huaibei Plain in Anhui Province of China were selected as the study areas.Thresholds of backscattering coefficients in the decision tree method were calculated with the histogram analysis method,and flood disaster monitoring in the two study areas was conducted with the threshold method using Sentinel-1 satellite images.Through satellite-based flood disaster monitoring,the flooded maps and the areas of expanded water bodies and flooded crops were derived.The satellite-based monitoring maps were derived by comparing the expanded area of images during a flood disaster with that before the disaster.The difference in spatiotemporal distribution of flood disasters in these two regions was analyzed.The results showed that flood disasters in the Sihu Basin occurred frequently in June and July,and flood disasters in the Huaibei Plain mostly occurred in August,with a high interannual vari-ability.Flood disasters in the Sihu Basin were usually widespread,and the affected area was between Changhu and Honghu lakes.The Huaibei Plain was affected by scattered disasters.The annual mean percentages of flooded crop area were 14.91%and 3.74% in the Sihu Basin and Huaibei Plain,respectively.The accuracies of the extracted flooded area in the Sihu Basin in 2016 and 2017 were 96.20% and 95.19%,respectively.