基于力学过程的蓄滞洪区洪水风险评估模型及应用

为定量评估分蓄洪工程启用过程中蓄滞洪区的洪水风险等级,创建了基于力学过程的蓄滞洪区洪水风险评估模型。该模型采用二维水动力学模块计算蓄滞洪区的洪水演进过程,利用洪水中人体跌倒失稳公式及洪水中房屋、农作物损失的计算关系式,评估各类受淹对象的洪水风险等级。然后将二维水动力学模块计算的洪水要素与两个物理模型试验值进行对比,表明二维水动力学模块的计算精度良好。最后计算了荆江分洪工程启用时分洪区内洪水的演进过程,并评估洪灾中群众的危险等级和财产损失。计算结果表明:洪水演进至140 h时,蓄滞洪区群众、房屋、水稻和棉花的平均损失率分别为85%、59%、63%和72%。模型中提出的采用基于受淹对象失稳机制的洪水风险分析方法,比以往经验水深法划分风险等级的适用性更好,不仅能为洪水风险管理及蓄滞洪区启用标准制定提供参考,也能推广应用于溃坝或堰塞湖溃决等极端洪水风险评估。     

城市洪涝中人体失稳机理与判别标准研究进展

受全球气候变化和人类活动影响,近年来极端降水事件增多,由此引发的城市洪涝灾害频发。行人在洪水作用下易失去稳定,威胁生命安全,研究洪水中人体的失稳机理与判别标准,能为城市洪涝灾害的风险评估与管理提供科学依据。本文首先总结了国内外城市洪涝中人体失稳机理研究的相关成果,评估了现有人体失稳判别标准的适用范围及优缺点。基于力学分析和实测数据率定的计算公式虽然在推导过程中有一定的简化,但能较好地反映洪水中人体失稳的动力学机理,可以评估不同人群与不同洪水条件下的人体稳定性。针对当前城市洪涝中人体稳定性研究存在的不足,需要开展真实洪水中行人逃生以及沿漫水楼梯行走时的失稳机理与判别标准研究,并深入研究行人站立姿势调整对洪水中人体稳定性的影响;还需基于大数据等手段获取互联网上洪水中人体失稳的影像资料,构建洪水中人体失稳的实测数据库;同时还需推动人体失稳判别标准在洪水风险管理中的具体应用,最大程度地降低城市洪涝灾害带来的不利影响。     

WUIVAC: a wildland-urban interface evacuation trigger model applied in strategic wildfire scenarios

An evacuation trigger is a point on the landscape that, once crossed by a wildfire, triggers an evacuation for a community. The Wildland-Urban Interface Evacuation (WUIVAC) model can be used to create evacuation trigger buffers around a community using fuels, weather, and topographic inputs. A strategic, community-scale application of WUIVAC for the town of Julian, California was investigated. Eight years of wind measurements were used to determine the worst-case (strongest) winds in 16 directions. Surface fire rate of spread was used to calculate evacuation trigger buffers for the communities of Julian and nearby Whispering Pines, and for three potential evacuation routes. Multiple trigger buffers were combined to create fire planning areas, and trigger buffers that predict the closure of all evacuation routes were explored. WUIVAC trigger buffers offer several potential benefits for strategic evacuation planning, including determination of when to evacuate and locating potential evacuation routes.     

An agent-based model for risk-based flood incident management

Effective flood incident management (FIM) requires successful operation of complex, interacting human and technological systems. A dynamic agent-based model of FIM processes has been developed to provide new insights which can be used for policy analysis and other practical applications. The model integrates remotely sensed information on topography, buildings and road networks with empirical survey data to fit characteristics of specific communities. The multiagent simulation has been coupled with a hydrodynamic model to estimate the vulnerability of individuals to flooding under different storm surge conditions, defence breach scenarios, flood warning times and evacuation strategies. A case study in the coastal town of Towyn in the United Kingdom has demonstrated the capacity of the model to analyse the risks of flooding to people, support flood emergency planning and appraise the benefits of flood incident management measures.     

The decision method of emergency supplies collection with fuzzy demand constraint under background of sudden disaster

As the stages of emergency response shift, it is an important task in the early stage of emergency response to handle emergency supply (ES) collection with fuzzy demand and multi-hub ES collection network. Taking into consideration the constraints such as no limit to collection time, capacity constraint to single hubs and different demand levels to be met by collection, this paper aims at establishing a mathematic planning model with two objectives, namely the shortest collection time and the optimal collection cost. In terms of algorithm design, the sequential enumeration method (SEM) was employed to solve the model, for higher iteration efficiency and lower difficulty level of the algorithm. The first step was to find the optimal ES collection time, collection route and allocation program in the direct shipment mode, the hub-and-spoke mode and the mixed mode. Then, the three modes were compared in terms of the collection route planning, the shortest collection time, the shortest collection route and the optimal collection cost of the entire ES collection network. The numerical example showed that compared with the simulated annealing (SA) algorithm, the result of SEM is basically the same with that of SA algorithm; however, SEM is simpler, more practical and easier to operate, so that it is of better promotional value.     

Computer-based Model for Flood Evacuation Emergency Planning

A computerized simulation model for capturing human behavior during flood emergency evacuation is developed using a system dynamics approach. It simulates the acceptance of evacuation orders by the residents of the area under threat; number of families in the process of evacuation; and time required for all evacuees to reach safety. The model is conceptualized around the flooding conditions (physical and management) and the main set of social and mental factors that determine human behavior before and during the flood evacuation. The number of families under the flood threat, population in the process of evacuation, inundation of refuge routes, flood conditions (precipitation, river elevation, etc.), and different flood warnings and evacuation orders related variables are among the large set of variables included in the model. They are linked to the concern that leads to the danger recognition, which triggers evacuation decisions that determine the number of people being evacuated. The main purpose of the model is to assess the effectiveness of different flood emergency management procedures. Each procedure consists of the choice of flood warning method, warning consistency, timing of evacuation order, coherence of the community, upstream flooding conditions, and set of weights assigned to different warning distribution methods. Model use and effectiveness are tested through the evaluation of the effectiveness of different flood evacuation emergency options in the Red River Basin, Canada.     

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation.     

A macro-scale flood risk model for Jamaica with impact of climate variability

Floods account for more than half of the global hydrometeorological risks. Severe floods cause significant economic shocks and loss of lives, particularly for developing countries such as Jamaica. There is need for more information on the present and projected flood risks to justify macro-scale planning for climate change adaptation and facilitate the decision-making processes. In this study, a catalogue of 198 flood events occurring between 1678 and 2010 is compiled for Jamaica and used to examine the climatology, occurrence, trends, causes and duration of the island’s severe events. The annual flood risk is estimated to be a loss of life rate of 4 persons and estimated annual damage of USD96.3 million per annum in 2010 values and approximately 0.84 % of GDP per annum. Macro-scale models for flood risks (deaths and damages) are also developed using data from the flood catalogue and maximum precipitation at the town and parish level. The models examine the relationship between flood risks (death and damages) and extreme rainfall depths and intensities. Future climate risks of loss of lives and damages are predicted to increase 11 and 9 %, respectively, to 4.4 persons and USD105.2 million per annum.     

Application of wave model for weather routing of ships in the North Indian Ocean

Weather routing of ships is used to establish the shortest time route or the most economical route from a departure to arrival point by applying available information of the weather condition viz. wind, wave and current. Information on ship speed loss due to these effects is pre-computed using sea-keeping computing tools, which are then suitably employed in the optimum ship routing algorithm. This developed algorithm was investigated using the wave height information from GEOSAT altimeter records. Dijkstra’s path optimization scheme, which employs optimal control theory and dynamic programming technique, is used to obtain reliable optimum route in a given random sea-state.     

Methods for the estimation of loss of life due to floods: a literature review and a proposal for a new method

This article deals with methods for the estimation of loss of life due to flooding. These methods can be used to assess the flood risks and to identify mitigation strategies. The first part of this article contains a comprehensive review of existing literature. Methods have been developed for different types of floods in different regions. In general these methods relate the loss of life in the flooded area to the flood characteristics and the possibilities for evacuation and shelter. An evaluation showed that many of the existing methods do not take into account all of the most relevant determinants of loss of life and that they are often to a limited extent based on empirical data of historical flood events. In the second part of the article, a new method is proposed for the estimation of loss of life caused by the flooding of low-lying areas protected by flood defences. An estimate of the loss of life due to a flood event can be given based on: (1) information regarding the flood characteristics, (2) an analysis of the exposed population and evacuation, and (3) an estimate of the mortality amongst the exposed population. By analysing empirical information from historical floods, new mortality functions have been developed. These relate the mortality amongst the exposed population to the flood characteristics. Comparison of the outcomes of the proposed method with information from historical flood events shows that it gives an accurate approximation of the number of observed fatalities during these events. The method is applied to assess the consequences for a large-scale flooding of the area of South Holland, in the Netherlands. It is estimated that the analysed coastal flood scenario can lead to approximately 3,200 fatalities in this area.

Flood events, fatalities and damages in India from 1978 to 2006

High temporal and spatial variability of rainfall qualifies India to be highly vulnerable to floods. Recurring floods of various magnitudes play havoc with the lives and property of the people, leading to unplanned development and unchecked environmental degradation, thwarting and retarding the overall development of the country. Therefore, the purpose of the present study is to analyze the types and trends in terms of flood events, frequency, number of people killed, injured, missing and economic damage both in space and time on the basis of a nationwide database published by India Meteorological Department, Pune, from 1978 to 2006. Analysis of these long-term data has revealed that 2,443 flood events claimed about 44,991 lives with the average of 1,551 lives each year. In terms of population size, these figures translate into a loss of 1.5 human lives per million of the population. A majority (56 %) of flood fatalities were caused during severe flood events. However, the frequency of these events was just 19 % in comparison with heavy rainfall events (65 %). In spatial context, flood-related fatalities are distributed all over the country with highest fatalities in Uttar Pradesh (17 %), Maharashtra (13 %), and Bihar and Gujarat (10 % each). Most fatalities occurred during the summer season monsoon months of August (30 %) followed by July (29 %) and September (20 %). The country suffered a cumulative flood-related economic loss of about 16 billion US$ between 1978 and 2006 and a maximum economic loss of 1.6 billion US$ in the year 2000 alone. The study further suggests that both flood events and fatalities have increased in India over a period of time.     

基于OpenGL曲面最短路径可视化的实现

路径分析是GIS空间分析中的重要组成部分,但目前一些最短路径应用结果主要还是基于二维平面的线状显示。随着三维可视化技术的广泛应用,曲面最短路径可视化是GIS最短路径分析的一个热点。通过简化处理实现曲面近似最段路径的求解与三维可视化表达。首先根据逐点插入法生成了三角网曲面,并在此基础上构建三角网之间的拓扑关系．最后利用可视化开发语言VC＋＋6．0,并结合OpenGL编程实现了曲面上两离散点间的最短路径三维显示。实验证明,该算法计算速度快,表达效果良好。     

A novel agent-based model for tsunami evacuation simulation and risk assessment

Tsunami evacuation is an effective way to save lives from the near-field tsunami. Realistic evacuation simulation can provide valuable information for accurate evacuation risk assessment and effective evacuation planning. Agent-based modeling is ideal for tsunami evacuation simulation due to its capability of capturing the emergent phenomena and modeling the individual-level interactions among agents and the agents’ interactions with the environment. However, existing models usually neglect or simplify some important factors and/or mechanisms in tsunami evacuation. For example, uncertainties in seismic damages to the transportation network are not probabilistically considered (e.g., by simply removing the damaged links (roads/bridges) from the network). Typically a relatively small population (i.e., evacuees) is considered (due to computational challenges) while neglecting population mobility. These simplifications may lead to inaccurate estimation of evacuation risk. Usually, only single traffic mode (e.g., on foot or by car) is considered, while pedestrian speed adjustment and multi-modal evacuation (e.g., on foot and by car) are not considered concurrently. Also, pedestrian–vehicle interaction is usually neglected in the multi-modal evacuation. To address the above limitations, this study proposes a novel and more realistic agent-based tsunami evacuation model for tsunami evacuation simulation and risk assessment. Uncertainties in seismic damages to all links in the transportation network as well as uncertainties in other evacuation parameters are explicitly modeled and considered. A novel and more realistic multi-modal evacuation model is proposed that explicitly considers the pedestrian–vehicle interaction, walking speed variability, and speed adjustment for both the pedestrian and car according to traffic density. In addition, several different population sizes are used to model population mobility and its impact on tsunami evacuation risk. The proposed model is applied within a simulation-based framework to assess the tsunami evacuation risk assessment for Seaside, Oregon.

     

Space-based monitoring of severe flooding of a southern state in India during south-west monsoon season of 2018

Kerala, a southern state of India, experienced a severe flooding due to multi-day extreme rain events during July and August months of 2018. This disaster was one of the worst floods to hit the state and resulted in heavy losses of lives and property. Natural Disaster Management Authority of India reported that 483 people lost their lives and more than 50 lakhs population were affected severely. This short communication focuses on examining this flood event using satellite remote sensing. It is reported that Kerala received an excess of about 56% rainfall during July and August from multi-day extreme rainfall episodes. Few regions of Kerala received the rainfall in the range of 270–300 mm on August 14 and 15. Hourly rainfall events in the excess of 25 mm have also been reported during heavy rainy days. The present study reports that multi-day heavy rainy events during July and August brought an accumulated rainfall of about 1600 mm, which resulted in extreme flooding over Kerala.

     

A GIS-based analysis of constraints on pedestrian tsunami evacuation routes: Cascais case study (Portugal)

Tsunami hazard in coastal areas susceptible to flooding, although reduced (in terms of probability of occurrence), may pose a high risk. Therefore, in these areas, a detailed evacuation planning of the affected population is required as a risk mitigation measure. The knowledge and enforcement of evacuation routes may reduce the population vulnerability, making it more resilient and reducing risk. This paper presents a GIS approach for modelling evacuation routes based on the optimal path search problem, of the graph theory, which is implemented on ArcCasper tool. The methodology proposed considers the elements involved in the evacuation process, the worst credible tsunami inundation scenario (hazard extent and travel time), the number of people that needs to be evacuated in different time scenarios, the safe areas or destination points of the evacuation routes, the roads network characteristics and finally the time available to evacuate. The knowledge of those elements allows predicting some possible outcomes of the evacuation, such as the arrival time of the evacuees to a shelter and the identification of congestion hot spots resulting from the application of a flocking model which simulates the path to be used by evacuees avoiding obstacles. The municipality of Cascais was used to test the methodology proposed in this study. Cascais is one of the largest urban centres located about 25 km west of Lisbon, Portugal, with a high density of infrastructure along the coastline whereby most of the population and economic activities are exposed to a tsunami. The results, presented in the form of maps, allow identifying the optimal evacuation routes as well as the unfeasible routes. This crucial information could be used to the evacuation optimization regarding the location of meeting points and vertical shelters as well as to improve the accessibility of the areas to be evacuated.     

Flood susceptibility mapping using integrated bivariate and multivariate statistical models

Flooding can have catastrophic effects on human lives and livelihoods and thus comprehensive flood management is needed. Such management requires information on the hydrologic, geotechnical, environmental, social, and economic aspects of flooding. The number of flood events that took place in Busan, South Korea, in 2009 exceeded the normal situation for that city. Mapping the susceptible areas helps us to understand flood trends and can aid in appropriate planning and flood prevention. In this study, a combination of bivariate probability analysis and multivariate logistic regression was used to produce flood susceptibility maps of Busan City. The main aim of this research was to overcome the weakness of logistic regression regarding bivariate probability capabilities. A flood inventory map with a total of 160 flood locations was extracted from various sources. Then, the flood inventory was randomly split into a testing dataset 70 % for training the models and the remaining 30 %, which was used for validation. Independent variables datasets included the rainfall, digital elevation model, slope, curvature, geology, green farmland, rivers, slope, soil drainage, soil effect, soil texture, stream power index, timber age, timber density, timber diameter, and timber type. The impact of each independent variable on flooding was evaluated by analyzing each independent variable with the dependent flood layer. The validation dataset, which was not used for model generation, was used to evaluate the flood susceptibility map using the prediction rate method. The results of the accuracy assessment showed a success rate of 92.7 % and a prediction rate of 82.3 %.     

Evaluating typical flood risks in Yangtze River Economic Belt: application of a flood risk mapping framework

The Yangtze River Economic Belt is one of the three national strategies of China, while flood risk is one of the most important concerns in the development of Yangtze River Economic Belt. In order to decrease the risks caused by floods, complete flood management system and adequate pre-arranged planning are desiderated to be researched in advance. This study considers two typical situations of flood risk, in which one is sluice-control situation in flood detention area and another is dike-break situation in flood-protected area, and proposes a framework for flood risk mapping. The results show that the losses caused by flood hazards are massive both in the two typical cases when extreme floods happen. The economic losses of different indicators are of great difference in flood detention area and flood-protected area, respectively. The framework effectively handles the complex boundaries in the Yangtze River Economic Belt and provides more accurate flood routing information. The evacuation plan module which has been incorporated in the framework also provides informative assistance for emergent action of evacuation under urgent condition.     

Changes in population evacuation potential for tsunami hazards in Seward, Alaska, since the 1964 Good Friday earthquake

Pedestrian evacuation modeling for tsunami hazards typically focuses on current land-cover conditions and population distributions. To examine how post-disaster redevelopment may influence the evacuation potential of at-risk populations to future threats, we modeled pedestrian travel times to safety in Seward, Alaska, based on conditions before the 1964 Good Friday earthquake and tsunami disaster and on modern conditions. Anisotropic, path distance modeling is conducted to estimate travel times to safety during the 1964 event and in modern Seward, and results are merged with various population data, including the location and number of residents, employees, public venues, and dependent care facilities. Results suggest that modeled travel time estimates conform well to the fatality patterns of the 1964 event and that evacuation travel times have increased in modern Seward due to the relocation and expansion of port and harbor facilities after the disaster. The majority of individuals threatened by tsunamis today in Seward are employee, customer, and tourist populations, rather than residents in their homes. Modern evacuation travel times to safety for the majority of the region are less than wave arrival times for future tectonic tsunamis but greater than arrival times for landslide-related tsunamis. Evacuation travel times will likely be higher in the winter time, when the presence of snow may constrain evacuations to roads.     

Influence of hydrate exploitation on stability of submarine slopes

Urban pluvial flash floods have become a matter of widespread concern, as they severely impact people’s lives in urban areas. Hydrological and hydraulic models have been widely used for urban flood management and urban planning. Traditionally, to reduce the complexity of urban flood modelling and simulations, simplification or generalization methods have been used; for example, some models focus on the simulation of overland water flow, and some models focus on the simulation of the water flow in sewer systems. However, the water flow of urban floods includes both overland flow and sewer system flow. The overland flow processes are impacted by many different geographical features in what is an extremely spatially heterogeneous environment. Therefore, this article is based on two widely used models (SWMM and ANUGA) that are coupled to develop a bi-directional method of simulating water flow processes in urban areas. The open source overland flow model uses the unstructured triangular as the spatial discretization scheme. The unstructured triangular-based hydraulic model can be better used to capture the spatial heterogeneity of the urban surfaces. So, the unstructured triangular-based model is an essential condition for heterogeneous feature-based urban flood simulation. The experiments indicate that the proposed coupled model in this article can accurately depict surface waterlogged areas and that the heterogeneous feature-based urban flood model can be used to determine different types of urban flow processes.

     

Natural disasters in China: 1900–2011

China is a country prone to high frequency of natural catastrophic events. According to the natural disaster data from 1900 to 2011, the major disaster types include drought, earthquake, epidemic, extreme temperature, flood, mass movement wet and storm. The occurrence of natural disaster and economic loss is increased during the studied period. However, the death toll induced by natural disaster is decreased significantly. A new frame of social development and natural disaster is proposed to discuss the impact of population and GDP on the influence of disaster through the recording and reduction efforts. The results indicated that economic development contributes to the reduction in the impact of natural disaster on the people lives and society. New comprehensive integrated management, including international cooperation, should be established.