东南沿海水库下游地区基于动态模拟的洪涝风险评估

我国东南沿海地区大多为一些中小流域,这些流域上游多建有水库工程,下游则为人口稠密的平原区,流域调蓄能力小,汇流时间短.同时,随着近年来城镇化快速发展,洪涝风险不断加大.因此,迫切需要开展水库下游不同暴雨重现期下的洪涝风险评估研究,以便为防洪决策提供技术支撑.为此,本文利用遥感、GIS、水文水动力学模型等相关技术方法,建立洪涝动态模拟模型来评估洪涝危险性;采用层次分析法和因子叠加法,从洪涝危险性和洪涝易损性两方面开展洪涝风险综合评估分析.研究表明,通过多学科与多技术手段相结合方法,来模拟预测不同暴雨重现期洪水动态淹没过程,再结合相关社会经济属性,可以有效地评估研究区洪涝灾害的风险,从而为水库调度及流域防洪减灾提供有力支撑.     

Impact assessment of urbanization on flood risk in the Yangtze River Delta

The Yangtze River Delta region is the region with highest urbanization speed in China. In this study, 6 typical urbanization areas in Yangtze River Delta were selected as the objectives of study. Flood risk assessment index system was established based on the flood disaster formation mechanism, and analytic hierarchy process was utilized to define the weight of indices. The flood hazard, the exposure of disaster bearing body, the vulnerability of disaster bearing body and the comprehensive flood risk corresponding to three typical years in different urbanization stages, 1991, 2001 and 2006 were assessed. The results show that the flood hazard and the exposure of disaster bearing body in the 6 areas are all with an increasing trend in the process of urbanization, among which, the increasing trend of the exposure of disaster bearing body is especially obvious. Though the vulnerabilities of disaster bearing body in the 6 areas are all with decreasing trend owe to the enhancement of flood control and disaster mitigation capability, the comprehensive flood risks in the 6 areas increased as a whole, which would pose a serious threat to urban sustainable development. Finally, effective countermeasures for flood risk management of urbanization areas in Yangtze River Delta were put forward based on the assessment results.     

Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP

On the basis of the disaster system theory and comprehensive analysis of flood risk factors, including the hazard of the disaster-inducing factors and disaster-breeding environment, as well as the vulnerability of the hazards-bearing bodies, the primary risk assessment index system of flood diversion district as well as its assessment standards were established. Then, a new model for comprehensive flood risk assessment was put forward in this paper based on set pair analysis (SPA) and variable fuzzy sets (VFS) theory, named set pair analysis-variable fuzzy sets model (SPA-VFS), which determines the relative membership degree function of VFS by using SPA method and has the advantages of intuitionist course, simple calculation and good generality application. Moreover, the analytic hierarchy process (AHP) was combined with trapezoidal fuzzy numbers to calculate the weights of assessment indices, thus the weights for flood hazard and flood vulnerability were determined by the fuzzy AHP procedure, respectively. Then SPA-VFS were applied to calculate the flood hazard grades and flood vulnerability grades with rank feature value equation and the confidence criterion, respectively. Under the natural disasters risk expression recommended by the Humanitarian Affairs Department of United Nations, flood risk grades were achieved from the flood hazard grades and flood vulnerability grades with risk grade classification matrix, where flood hazard, flood vulnerability and flood risk were all classified into five grades as very low, low, medium, high and very high. Consequently, integrated flood risk maps could be carried out for flood risk management and decision-making. Finally, SPA-VFS and fuzzy AHP were employed for comprehensive flood risk assessment of Jingjiang flood diversion district in China, and the computational results demonstrate that SPA-VFS is reasonable, reliable and applicable, thus has bright prospects of application for comprehensive flood risk assessment, and moreover has potential to be applicable to comprehensive risk assessment of other natural disasters with no much modification.     

Assessment of social vulnerability to natural hazards in the Yangtze River Delta, China

China is exposed to a wide range of natural hazards, and disaster losses have escalated over the past decade. Owing to the pressure from natural disasters, along with changes in climate, social conditions, and regional environment, assessment of social vulnerability (SV) to natural hazards has become increasingly urgent for risk management and sustainable development in China. This paper presents a new method for quantifying SV based on the projection pursuit cluster (PPC) model. A reference social vulnerability index (SVI) at the county level was created for the Yangtze River Delta area in China for 1995, 2000, 2005, and 2009. The result of social vulnerability assessment was validated using data of actual losses from natural disasters. The primary findings are as follows: (i) In the study area, the major factors that impact SVI are regional per capita GDP and per capita income. (ii) The study area was more vulnerable in 1995 than in later years. SV of the whole region had decreased over the study period. (iii) Most part of Shanghai and the southeast part of Jiangsu Province had been the least vulnerable within the region. From this least vulnerable zone to the periphery of the region, the situation deteriorated. The highest SVI values in all evaluated years were found in the northern, western, or southern tips of the Yangtze River Delta.     

A new nonlinear risk assessment model based on an improved projection pursuit

Experience has shown that researchers and engineers are unable to construct ideal models for risk assessment and make optimal decisions in situations with insufficient data. A nonlinear risk assessment model is therefore proposed in this study based on an improved projection pursuit model (IPPM) for use in situations where insufficient data are available. A new projection index is initially proposed based on the maximum entropy principle in order to extract more information from original multidimensional data before a nonlinear risk assessment function is constructed using differential equation modeling. This function can be applied to all risk assessment problems after performing standardization and dimension reduction for the indicators. Five marine environmental risk assessment experiments for naval activity are then performed to train and validate the IPPM, as well as a traditional projection pursuit model using different numbers of training samples. The results of this analysis show that the IPPM is reliable, robust, and consistent, and can improve risk assessments by between 4.3 and 43.7% depending on performance criteria. Satisfactory results are obtained from the IPPM using just 12 training samples, and an acceptable result is still obtained if this number is reduced to just ten. Application of an IPPM therefore represents a valuable tool for risk assessment in situations where data is insufficient.     

Changing of flood risk due to climate and development in Huaihe River basin,China

Assessing the response of flood risk caused by climate change and social development is very important in terms of determining high risk areas in different periods as well as making disaster mitigating plans. We establish a flood risk assessment model based on geographic information system and natural disaster risk assessment theory. In order to compare the index value in different periods and spaces, we utilize the spatial and temporal standardization method to standardized index. To avoid one-sidedness caused by using one weight calibration method only, we employ the least square method to synthesize weights determine by the Analytic Hierarchy Process (AHP) method and the Entropy weight method. We adopt the observed data of the Huaihe River basin from 1960 to 2010 to assess the changing of flood risk between period I (1960–1980) and period II (1980–2010). After pre-processing the atmosphere–ocean coupled global circulation models (AOGCM) data, including bias correction and downscaling, we use the corrected data to predict the flood risk during future period III (2010–2040). The results show that high risk areas and moderate to high risk areas during period I take up 17.68 and 33.88 % of the total area of the Huaihe River basin, respectively. During period II, the high risk areas show an increasing percent change of 1.93 % and a decreasing trend in moderate to high risk areas of 3.8 %. Compared with period II, the high risk areas and the moderate to high risk areas during period III show an increasing trend of 8.02 and 0.77 %, which is the result of the combined effects of climate change and social development. The results presented here can provide useful information for decision-makers.     

四川省城市地震灾害脆弱性综合评价研究

城市化进程的不断推进使得城市的地震灾害脆弱性日益加剧,而城市承灾体的脆弱性受复杂因素影响。本文针对评价指标受主观性影响较大的问题,基于人口、工程、经济及社会4个方面,构建了城市震害综合脆弱性评价指标体系;并构建基于实码加速遗传算法优化投影寻踪（RAGA-PP）的城市震害脆弱性评价模型;最后,对四川省21个市、州进行了震害脆弱性评价。结果表明:巴中、南充等地脆弱性较高,成都、攀枝花等地脆弱性较低;经济因素对城市震害脆弱性影响较大;该评价模型能够克服人为主观性,有效可行。     

Application of the hidden Markov model in a dynamic risk assessment of rainstorms in Dalian,China

Disaster risk evolves spatially and temporally due to the combined dynamics of hazards, exposure and vulnerability. However, most previous risk assessments of natural disasters were static and typically based on historical disaster events. Dynamic risk assessments are required to effectively reduce risks and prevent future losses. Based on rainstorm disaster data and meteorological information collected in Dalian, China, from 1976 to 2015, the hidden Markov model (HMM) was used to detect inter-annual changes in rainstorm disaster risks. An independent sample test was conducted to assess the reliability of the HMM in dynamic risk assessments. The dynamic rainstorm risk in Dalian was simulated based on the observation probability matrix, which characterized the relationship dependence between rainstorm hazard and risk, and the probability matrix of state transition, which reflected the probability of changes for the risk level. High rainstorm risk was associated with high-hazard rainstorms and continuously appeared with little probability in several successive years. The reliability applied the HMM to simulate the rainstorm disaster risk was approximately 67% in the dynamic risk assessment. Additionally, the rainstorm disaster risk in Dalian is predicted to be at a medium-risk level in 2017, with a probability of 0.685. Our findings suggest that the HMM can be effectively used in the dynamic risk assessment of natural disasters. Notably, future risk levels can be predicted using the current hazard level and the HMM.     

基于指标法的建筑物理脆弱性评估研究进展

承灾体脆弱性评估是科学进行灾害风险评估和预测的基础，房屋建筑作为面大量广的承灾体，众多学者对建筑物理脆弱性指标模型进行了研究。基于单灾种和多灾种2个维度，针对指标模型构建的各环节，全面梳理了几种典型单灾种物理脆弱性指标体系和评估模型构建情况，发现指标选取理论依据不明确，模型构建主观性较强，不能准确表征建筑特点与抗灾能力间的内在联系。系统总结了多灾种指标体系和耦合物理脆弱性指标模型研究现状，发现多灾种之间及其对承灾体影响的复杂耦合效应在现有指标模型中未得到充分体现。研究结果表明，明晰指标依据、优化模型构建是提升单灾种物理脆弱性评估准确性的关键；改进脆弱性耦合模型、拓展综合脆弱性评估方法是健全多灾种脆弱性评估研究的核心。     

Comprehensive assessment of flood risk using the classification and regression tree method

The Evaluation of flood risk is a difficult task due to its numerous and complex impact factors. This article built a classification and regression tree (CART) model for the flood risk assessment with the available data of Hunan Province. This model is able to extract the major impact factors from many complex variables, determine the factors’ thresholds, and evaluate the levels of flood risk objectively. To construct the model, 18 explanatory variables were selected as the influential factors, including meteorological conditions, surface conditions and social vulnerability. Economic loss density from flood was chosen as the response variable for the quantitative and comprehensive evaluation of flood risk. The final model showed that meteorological conditions have the most significant influence on flood risk. Additionally, the relationship between meteorological factors and flood risk is rather complex. The variability of rainstorm days during the seasonal alternate period from the end of spring (May) to the early summer (June) is the source of the highest flood risk. In addition, the regional embankment density and population density as social vulnerability indicators and the relief degree of land surface as a surface condition indicator were also included in the flood risk assessment for Hunan. A region with dense dams appeared at a relatively higher risk. Densely inhabited areas with greater topographical relief also demonstrated a higher flood risk in the study area. The conditions obtained from the final tree for different levels of risk demonstrate the objectivity of selecting impact factors and a reduction of complexity for the risk evaluation process. Furthermore, the evaluation of high-level risk using the proposed method requires fewer conditions, which allows for a rapid risk assessment of serious floods. The CART method shows a decreased root mean squared error compared with that of a multiple linear regression model. In addition, the cross-validation error was improved for the high-risk levels that represent the most important classes in risk management. The verification with the available historical records showed that the output of the model is reliable. In summary, the CART method is feasible for extracting the main impact factors and their associated thresholds for the comprehensive assessment of regional flood risk.     

Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period

Risk assessment plays an important role in disaster risk management. Existing multi-hazard risk assessment models are often qualitative or semi-quantitative in nature and used for comparative study of regional risk levels. They cannot estimate directly probability of disaster losses from the joint impact of several hazards. In this paper, a quantitative approach of multi-hazard risk assessment based on vulnerability surface and joint return period of hazards is put forward to assess the risk of crop losses in the Yangtze River Delta region of China. The impact of strong wind and flood, the two most prominent agricultural hazards in the area, is analyzed. The multi-hazard risk assessment process consists of three steps. First, a vulnerability surface, which denotes the functional relationship between the intensity of the hazards and disaster losses, was built using the crop losses data for losses caused by strong wind and flood in the recent 30 years. Second, the joint probability distribution of strong wind and flood was established using the copula functions. Finally, risk curves that show the probability of crop losses in this multi-hazard context at four case study sites were calculated according to the joint return period of hazards and the vulnerability surface. The risk assessment result of crop losses provides a useful reference for governments and insurance companies to formulate agricultural development plans and analyze the market of agricultural insurance. The multi-hazard risk assessment method developed in this paper can also be used to quantitatively assess multi-hazard risk in other regions.     

新疆天山地区 PP回归综合预报模型研究及预报效能评价

运用基于 PP回归理论的数值型地震综合预报软件系统, 对新疆天山地区进行了 PP回归建模研究。 通过回顾性 PP回归动态建模预测检验,对其预报效能进行了评价。 结果认为,该模型作为时序性数值预报模型具有较好的中短期预报效能。 尤其对地震样本量大、震级分布完备的地区,其预报效能更好。     

地震重灾区诱发次生地质灾害风险评价研究

为了揭示地震重灾区与次生地质灾害的关联性,以某地震灾区为例,在分析次生地质灾害类型与危害的基础上,通过计算一次泥石流总量及流量确定其危险度,并引入易损性指数,确定各评价单元次生山地灾害的易损性大小,设置评价指标;结合研究区实际,采用层次分析法构建次生地质灾害风险评价模型,对地震重灾区诱发次生地质灾害风险进行评价。实验以次生地质灾害中的泥石流产生的灾害风险为例进行研究,结果表明,采用本文研究方法可在有效确定地震重灾区诱发次生地质灾害的位置方面具有一定优势,但在纵向地震造成次生地质灾害风险评价方面需进一步进行研究。     

铁路梁式桥地震灾害损失评估

针对铁路桥梁地震灾害评估中多因素影响问题,结合铁路桥梁地震灾害的复杂特点和各结构层次的震害表现形式,从桥面系、上部结构和下部结构3个方面构建铁路梁式桥地震灾害评估指标体系.基于改进的层次分析法计算了各评估指标的权重,以桥梁承灾系统为研究主体,运用多级综合模糊理论,建立铁路梁式桥震害评估模型.结合汶川地震中一座铁路混凝土...     

基于地震动参数的城市建筑物震害模拟——以兰州市城关区为例

首先利用最短断层法烈度衰减模型分别模拟两次地震的地震动参数空间分布,并通过与实际地震的极震区对比,验证该模型模拟地震烈度的可靠性.然后,基于模拟的地震烈度空间分布和建筑物的结构类型、层高等信息,采用结构弹塑性时程分析方法对兰州市城关区建筑物进行三维震害模拟.研究结果表明:最短断层法是一个模拟历史地震烈度空间分布较好的模...     

地震灾害风险评估方法的对比分析——以乌鲁木齐市为例

基于指标体系的风险建模与评估是目前灾害风险分析与评估中应用最广泛的方法。本文首先分析评价不同学者的地震灾害风险评估指标体系;在此基础上,选取指标体系相对简单的城市防震减灾能力法和考虑因素较多的地震灾害风险系数法对乌鲁木齐市各区县开展地震灾害风险评估。评估结果表明:不同评价方法的侧重点不同,造成评估结果有一定的差异性,评估体系指标大而全并不意味着评估结果更加合理。地震灾害风险评估指标体系的建立需要兼顾可操作性、实用性、全面性及可量化性等要求。     

重大自然灾害灾后重建可持续发展评价模型研究

针对发生重大自然灾害地区重建工作的现状及特点,依据可持续发展原则构建了灾区的可持续发展指标体系,并且结合熵值法——改进型蚁群算法建立了可持续发展评价模型。以5·12相关地震灾区为例,对汶川、北川、绵竹、都江堰、青川五个地区灾后重建可持续发展程度进行综合评价,并将评价结果与5·12相关地震灾区的应用与灰色关联投影法的评价结果进行对比,验证了该模型在这方面研究的科学性和有效性。     

Extension of observed flood series by combining a distributed hydro-meteorological model and a copula-based model

Long flood series are required to accurately estimate flood quantiles associated with high return periods, in order to design and assess the risk in hydraulic structures such as dams. However, observed flood series are commonly short. Flood series can be extended through hydro-meteorological modelling, yet the computational effort can be very demanding in case of a distributed model with a short time step is considered to obtain an accurate flood hydrograph characterisation. Statistical models can also be used, where the copula approach is spreading for performing multivariate flood frequency analyses. Nevertheless, the selection of the copula to characterise the dependence structure of short data series involves a large uncertainty. In the present study, a methodology to extend flood series by combining both approaches is introduced. First, the minimum number of flood hydrographs required to be simulated by a spatially distributed hydro-meteorological model is identified in terms of the uncertainty of quantile estimates obtained by both copula and marginal distributions. Second, a large synthetic sample is generated by a bivariate copula-based model, reducing the computation time required by the hydro-meteorological model. The hydro-meteorological modelling chain consists of the RainSim stochastic rainfall generator and the Real-time Interactive Basin Simulator (RIBS) rainfall-runoff model. The proposed procedure is applied to a case study in Spain. As a result, a large synthetic sample of peak-volume pairs is stochastically generated, keeping the statistical properties of the simulated series generated by the hydro-meteorological model. This method reduces the computation time consumed. The extended sample, consisting of the joint simulated and synthetic sample, can be used for improving flood risk assessment studies.     

辽西北地区农业干旱灾害风险评价与风险区划研究

以辽西北29个农业县（市、区）为研究区域,选取辽西北最主要的玉米作物作为研究对象,从造成农业干旱灾害的致灾因子危险性、承灾体暴露性、脆弱性和抗旱减灾能力4个方面着手,利用自然灾害风险指数法、加权综合评价法和层次分析法,建立了农业干旱灾害风险指数（ADRI）,用以表征农业干旱灾害风险程度;借助GIS技术,绘制辽西北农业干旱灾害风险评价区划图,将风险评价区划图与2006年辽西北受干旱影响粮食减产系数区划图对比,发现两者可以较好的匹配。研究结果可为当地农业干旱灾害预警、保险,以及有关部门的旱灾管理、减灾决策制定提供理论依据和指导。     

Seismic comprehensive forecast based on modified project pursuit regression

In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression (PPR) is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation: to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.