An innovative micro-scale approach for vulnerability and flood risk assessment with the application to property-level protection adoptions

Economic damage assessment for flood risk estimation is established in many countries, but attentions have been focused on macro- or meso-scale approaches and less on micro-scale approaches. Whilst the macro- or meso-scale approaches of flood damage assessment are suitable for regional- or national-oriented studies, micro-scale approaches are more suitable for cost–benefit analysis of engineered protection measures. Furthermore, there remains lack of systematic and automated approaches to estimate economic flood damage for multiple flood scenarios for the purpose of flood risk assessment. Studies on flood risk have also been driven by the assumption of stationary characteristic of flood hazard, hence the stationary-oriented vulnerability assessment. This study proposes a novel approach to assess vulnerability and flood risk and accounts for adaptability of the approach to nonstationary conditions of flood hazard. The approach is innovative in which an automated concurrent estimation of economic flood damage for a range of flood events on the basis of a micro-scale flood risk assessment is made possible. It accounts for the heterogeneous distribution of residential buildings of a community exposed to flood hazard. The feasibility of the methodology was tested using real historical flow records and spatial information of Teddington, London. Vulnerability curves and residual risk associated with a number of alternative extents of property-level protection adoptions are estimated by the application of the proposed methodology. It is found that the methodology has the capacity to provide valuable information on vulnerability and flood risk that can be integrated in a practical decision-making process for a reliable cost–benefit analysis of flood risk reduction options.     

Micro-scale flood risk analysis based on detailed 2D hydraulic modelling and high resolution geographic data

The paper presents a consistent micro-scale flood risk analysis procedure, relying on detailed 2D inundation modelling as well as on high resolution topographic and land use database. The flow model is based on the shallow-water equations, solved by means of a finite volume scheme on multi-block structured grids. Using highly accurate laser altimetry, the simulations are performed with a typical grid spacing of 2 m, which is fine enough to represent the flow at the scale of individual buildings. Consequently, the outcomes of hydraulic modelling constitute suitable inputs for the subsequent exposure analysis, performed at a micro-scale using detailed land use maps and geographic database. Eventually, the procedure incorporates social flood impact analysis and evaluation of direct economic damage to residential buildings. Besides detailing the characteristics and performance of the hydraulic model, the paper describes the flow of data within the overall flood risk analysis procedure and demonstrates its applicability by means of a case study, for which two different flood protection measures were evaluated.     

极端洪水灾害损失评估方法及应用

极端洪水灾害具有频率低、影响范围大、损失高等特点,一般常遇洪水的灾害损失评估方法难以适用。分析了极端洪水灾害的自然属性与社会属性,认为极端洪水灾害损失具有时空分布的特性,因此借鉴空间信息格网技术,分别形成了极端洪水水文特性格网与社会经济特性格网,并将其叠加得到具有空间拓扑关系和属性信息的基于GIS的极端洪水损失空间信息格网模型,从而有效地反映了极端洪水灾害的时空特性。结合极端洪水损失率数据库,可评估极端洪水灾害损失。利用该方法评估了1998年特大洪水造成哈尔滨市江南主城区的直接经济损失,实证说明该方法可用于极端洪水灾害损失的评估。     

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。     

Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates

With the recent transition to a more risk-based approach in flood management, flood risk models—being a key component in flood risk management—are becoming increasingly important. Such models combine information from four components: (1) the flood hazard (mostly inundation depth), (2) the exposure (e.g. land use), (3) the value of elements at risk and (4) the susceptibility of the elements at risk to hydrologic conditions (e.g. depth–damage curves). All these components contain, however, a certain degree of uncertainty which propagates through the calculation and accumulates in the final damage estimate. In this study, an effort has been made to assess the influence of uncertainty in these four components on the final damage estimate. Different land-use data sets and damage models have been used to represent the uncertainties in the exposure, value and susceptibility components. For the flood hazard component, inundation depth has been varied systematically to estimate the sensitivity of flood damage estimations to this component. The results indicate that, assuming the uncertainty in inundation depth is about 25 cm (about 15% of the mean inundation depth), the total uncertainty surrounding the final damage estimate in the case study area can amount to a factor 5–6. The value of elements at risk and depth–damage curves are the most important sources of uncertainty in flood damage estimates and can both introduce about a factor 2 of uncertainty in the final damage estimates. Very large uncertainties in inundation depth would be necessary to have a similar effect on the uncertainty of the final damage estimate, which seem highly unrealistic. Hence, in order to reduce the uncertainties surrounding potential flood damage estimates, these components deserve prioritisation in future flood damage research. While absolute estimates of flood damage exhibit considerable uncertainty (the above-mentioned factor 5–6), estimates for proportional changes in flood damages (defined as the change in flood damages as a percentage of a base situation) are much more robust.     

Probabilistic flood risk analysis considering morphological dynamics and dike failure

A comprehensive flood risk assessment should aim not only at quantifying uncertainties but also the variability of risk over time. In this study, an efficient modelling framework was proposed to perform probabilistic hazard and risk analysis in dike-protected river systems accounting for morphological variability and uncertainty. The modelling framework combined the use of: (1) continuous synthetic discharge forcing, (2) a stochastic dike breach model dynamically coupled to a stochastic unsteady one-dimensional hydraulic model (MIKE1D) describing river flows, (3) a catalogue of pre-run probabilistic inundation maps (MIKE SHE) and (4) a damage and loss model (CAPRA). The methodology was applied using continuous simulations to a 45-km reach of the Upper Koshi River, Nepal, to investigate the changes in breach and flood hazards and subsequent risks after 2 and 5 years of probable river bed aggradation. The study results indicated an increase in annual average loss of 4% per year driven by changes in loss distribution in the most frequent loss return periods (20–500 years). The use of continuous simulations and dike breach model also provided a more robust estimation of risk metrics as compared to traditional binary treatment of flood defence and/or the direct association of flow with loss return periods. The results were helpful to illustrate the potential impacts of dynamic river morphology, dike failure and continuous simulation and their significance when devising flood risk study methodologies.     

Probabilistic disaggregation of a spatial portfolio of exposure for natural hazard risk assessment

In natural hazard risk assessment situations are encountered where information on the portfolio of exposure is only available in a spatially aggregated form, hindering a precise risk assessment. Recourse might be found in the spatial disaggregation of the portfolio of exposure to the resolution of the hazard model. Given the uncertainty inherent to any disaggregation, it is argued that the disaggregation should be performed probabilistically. In this paper, a methodology for probabilistic disaggregation of spatially aggregated values is presented. The methodology is exemplified with the disaggregation of a portfolio of buildings in two communes in Switzerland and the results are compared to sample observations. The relevance of probabilistic disaggregation uncertainty in natural hazard risk assessment is illustrated with the example of a simple flood risk assessment.     

Up-scaling of impact dependent loss distributions: a hybrid convolution approach for flood risk in Europe

This paper introduces a new method to up-scale dependent loss distributions from natural hazards to higher spatial levels, explicitly incorporating their dependency structure over the aggregation process. The method is applied for flood risk in Europe. Based on this “hybrid convolution” approach, flood loss distributions for nearly all European countries are calculated and presented. Such risk-based estimates of extreme event losses are useful for determining suitable risk management strategies on various spatial levels for different risk bearers. The method is not only applicable for natural disaster risk but can be extended for other cases as well, i.e., where comonotonic risks have to be “summed up” without loss of risk information.     

Preliminary flood risk assessment: the case of Athens

Flood mapping, especially in urban areas, is a demanding task requiring substantial (and usually unavailable) data. However, with the recent introduction of the EU Floods Directive (2007/60/EC), the need for reliable, but cost effective, risk mapping at the regional scale is rising in the policy agenda. Methods are therefore required to allow for efficiently undertaking what the Directive terms “preliminary flood risk assessment,” in other words a screening of areas that could potentially be at risk of flooding and that consequently merit more detailed attention and analysis. Such methods cannot rely on modeling, as this would require more data and effort that is reasonable for this high-level, screening phase. This is especially true in urban areas, where modeling requires knowledge of the detailed urban terrain, the drainage networks, and their interactions. A GIS-based multicriteria flood risk assessment methodology was therefore developed and applied for the mapping of flood risk in urban areas. This approach quantifies the spatial distribution of flood risk and is able to deal with uncertainties in criteria values and to examine their influence on the overall flood risk assessment. It can further assess the spatially variable reliability of the resulting maps on the basis of the choice of method used to develop the maps. The approach is applied to the Greater Athens area and validated for its central and most urban part. A GIS database of economic, social, and environmental criteria contributing to flood risk was created. Three different multicriteria decision rules (Analytical Hierarchy Process, Weighted Linear Combination and Ordered Weighting Averaging) were applied, to produce the overall flood risk map of the area. To implement this methodology, the IDRISI Andes GIS software was customized and used. It is concluded that the results of the analysis are a reasonable representation of actual flood risk, on the basis of their comparison with historical flood events.     

A multi-component flood risk assessment in the Maresme coast (NW Mediterranean)

Coastal regions are the areas most threatened by natural hazards, with floods being the most frequent and significant threat in terms of their induced impacts, and therefore, any management scheme requires their evaluation. In coastal areas, flooding is a hazard associated with various processes acting at different scales: coastal storms, flash floods, and sea level rise (SLR). In order to address the problem as a whole, this study presents a methodology to undertake a preliminary integrated risk assessment that determines the magnitude of the different flood processes (flash flood, marine storm, SLR) and their associated consequences, taking into account their temporal and spatial scales. The risk is quantified using specific indicators to assess the magnitude of the hazard (for each component) and the consequences in a common scale. This allows for a robust comparison of the spatial risk distribution along the coast in order to identify both the areas at greatest risk and the risk components that have the greatest impact. This methodology is applied on the Maresme coast (NW Mediterranean, Spain), which can be considered representative of developed areas of the Spanish Mediterranean coast. The results obtained characterise this coastline as an area of relatively low overall risk, although some hot spots have been identified with high-risk values, with flash flooding being the principal risk process.     

A structured approach to enhance flood hazard assessment in mountain streams

An evidence-based flood hazard analysis in mountain streams requires the identification and the quantitative characterisation of multiple possible processes. These processes result from specific triggering mechanisms on the hillslopes (i.e. landslides, debris flows), in-channel morphodynamic processes associated with sudden bed changes and stochastic processes taking place at critical stream configurations (e.g. occlusion of bridges, failure of levees). From a hazard assessment perspective, such possible processes are related to considerable uncertainties underlying the hydrological cause-effect chains. Overcoming these uncertainties still remains a major challenge in hazard and risk assessment and represents a necessary condition for a reliable spatial representation of process intensities and the associated probabilities. As a result of an accurate analysis of the conceptual flaws present in the procedures currently employed for hazard mapping in South Tyrol (Italy) and Carinthia (Austria), we propose a structured approach as a means to enhance the integration of hillslope, morphodynamic and stochastic processes into conventional flood hazard prediction for mountain basins. To this aim, a functional distinction is introduced between prevailing one-dimensional and two-dimensional process propagation domains, i.e., between confined and semi- to unconfined stream segments. The former domains are mostly responsible for the generation of water, sediment and wood fluxes, and the latter are where flooding of inactive channel areas (i.e. alluvial fans, floodplains) can occur. For the 1D process propagation domain, we discuss how to carry out a process routing along the stream system and how to integrate numerical models output with expert judgement in order to derive consistent event scenarios, thus providing a consistent quantification of the input variables needed for the associated 2D domains. Within these latter domains, two main types of spatial sub-domains can be identified based on the predictability of their dynamics, i.e., stochastic and quasi-deterministic. Advantages and limitations offered by this methodology are finally discussed with respect to hazard and risk assessment in mountain basins.     

Flood risk analyses—how detailed do we need to be?

Applied flood risk analyses, especially in urban areas, very often pose the question how detailed the analysis needs to be in order to give a realistic figure of the expected risk. The methods used in research and practical applications range from very basic approaches with numerous simplifying assumptions up to very sophisticated, data and calculation time demanding applications both on the hazard and on the vulnerability part of the risk. In order to shed some light on the question of required model complexity in flood risk analyses and outputs sufficiently fulfilling the task at hand, a number of combinations of models of different complexity both on the hazard and on the vulnerability side were tested in a case study. The different models can be organized in a model matrix of different complexity levels: On the hazard side, the approaches/models selected were (A) linear interpolation of gauge water levels and intersection with a digital elevation model (DEM), (B) a mixed 1D/2D hydraulic model with simplifying assumptions (LISFLOOD-FP) and (C) a Saint-Venant 2D zero-inertia hyperbolic hydraulic model considering the built environment and infrastructure. On the vulnerability side, the models used for the estimation of direct damage to residential buildings are in order of increasing complexity: (I) meso-scale stage-damage functions applied to CORINE land cover data, (II) the rule-based meso-scale model FLEMOps+ using census data on the municipal building stock and CORINE land cover data and (III) a rule-based micro-scale model applied to a detailed building inventory. Besides the inundation depths, the latter two models consider different building types and qualities as well as the level of private precaution and contamination of the floodwater. The models were applied in a municipality in east Germany, Eilenburg. It suffered extraordinary damage during the flood of August 2002, which was well documented as were the inundation extent and depths. These data provide an almost unique data set for the validation of flood risk analyses. The analysis shows that the combination of the 1D/2D model and the meso-scale damage model FLEMOps+ performed best and provide the best compromise between data requirements, simulation effort, and an acceptable accuracy of the results. The more detailed approaches suffered from complex model set-up, high data requirements, and long computation times.     

Assessing flood hazard using flood marks and analytic hierarchy process approach: a case study for the 2013 flood event in Quang Nam,Vietnam

The production of flood hazard assessment maps is an important component of flood risk assessment. This study analyses flood hazard using flood mark data. The chosen case study is the 2013 flood event in Quang Nam, Vietnam. The impacts of this event included 17 deaths, 230 injuries, 91,739 flooded properties, 11,530 ha of submerged and damaged agricultural land, 85,080 animals killed and widespread damage to roads, canals, dykes and embankments. The flood mark data include flood depth and flood duration. Analytic hierarchy process method is used to assess the criteria and sub-criteria of the flood hazard. The weights of criteria and sub-criteria are generated based on the judgements of decision-makers using this method. This assessment is combined into a single map using weighted linear combination, integrated with GIS to produce a flood hazard map. Previous research has usually not considered flood duration in flood hazard assessment maps. This factor has a rather strong influence on the livelihood of local communities in Quang Nam, with most agricultural land within the floodplain. A more comprehensive flood hazard assessment mapping process, with the additional consideration of flood duration, can make a significant contribution to flood risk management activities in Vietnam.     

Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province,China

This study presents the methodology and procedure for risk assessment of flood disasters in central Liaoning Province, which was supported by geographical information systems (GIS) and technology of natural disaster risk assessment. On the basis of the standard formulation of natural disaster risk and flood disaster risk index, of which weights were developed using combined weights of entropy, the relative membership degree functions of variable fuzzy set (VFS) theory were calculated using improved set pair analysis, while level values were calculated using VFSs, including hazard levels, exposure levels, vulnerability levels and restorability levels, and the flood risk level for each assessment unit was obtained using the natural disaster index method. Consequently, integrated flood risk map was carried out by GIS spatial analysis technique. The results show that the southwestern and central parts of the study area possess higher risk, while the northwestern and southeastern parts possess lower risk. The results got by the assessment model fits the area of historical flood data; this study offer new insights and possibility to carry out an efficient way for flood disaster prevention and mitigation. The study also provides scientific reference in flood risk management for local and national governmental agencies.     

Characterizing flood hazard risk in data-scarce areas,using a remote sensing and GIS-based flood hazard index

The frequency in occurrence and severity of floods has increased globally. However, many regions around the globe, especially in developing countries, lack the necessary field monitoring data to characterize flood hazard risk. This paper puts forward methodology for developing flood hazard maps that define flood hazard risk, using a remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in western Uganda. The FHI was compiled using analytical hierarchy process and considered slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover and rainfall intensity as the flood causative factors. These factors were derived from Landsat, SRTM and PERSIANN remote sensing data products, except for geology that requires field data. The resultant composite FHI yielded a flood hazard map pointing out that over 11 and 18% of the study area was very highly and highly susceptible to flooding, respectively, while the remaining area ranged from medium to very low risk. The resulting flood hazard map was further verified using inundation area of a historical flood event in the study area. The proposed methodology was effective in producing a flood hazard map at the watershed local scale, in a data-scarce region, useful in devising flood mitigation measures.     

基于遥感空间信息的洪水风险识别与动态模拟研究进展

对地观测卫星遥感能够提供广泛可靠的空间信息，是洪水风险识别与动态模拟的重要支撑技术之一。为阐明卫星遥感技术对洪水研究的推动作用，回顾了洪水风险识别与动态模拟研究的发展历程及技术需求，以对地观测卫星遥感三大阶段的发展轨迹为主线，分析了遥感空间信息在洪水研究中的历史性贡献和阶段性效用，讨论总结了危险分区法、水文模型和微波遥感监测等3种洪水研究典型方法的应用进展。提出未来洪水风险识别与动态模拟研究的重点：遥感空间信息与模型算法的深度结合，遥感反演算法与系统的开发及应用，典型洪水研究方法集成系统的开发与应用，大数据方法与手段的应用。以期为提升洪水应急响应能力与灾害风险管理水平提供有效参考。     

基于遥感空间信息的洪水风险识别与动态模拟研究进展

对地观测卫星遥感能够提供广泛可靠的空间信息,是洪水风险识别与动态模拟的重要支撑技术之一。为阐明卫星遥感技术对洪水研究的推动作用,回顾了洪水风险识别与动态模拟研究的发展历程及技术需求,以对地观测卫星遥感三大阶段的发展轨迹为主线,分析了遥感空间信息在洪水研究中的历史性贡献和阶段性效用,讨论总结了危险分区法、水文模型和微波遥感监测等3种洪水研究典型方法的应用进展。提出未来洪水风险识别与动态模拟研究的重点:遥感空间信息与模型算法的深度结合,遥感反演算法与系统的开发及应用,典型洪水研究方法集成系统的开发与应用,大数据方法与手段的应用。以期为提升洪水应急响应能力与灾害风险管理水平提供有效参考。     

Simulation-based decision support system for flood damage assessment under uncertainty using remote sensing and census block information

The level of damage of flood events does not solely depend on exposure to flood waters. Vulnerabilities due to various socio-economic factors such as population at risk, public awareness, and presence of early warning systems, etc. should also be taken into account. Federal and state agencies, watershed management coalitions, insurance companies, need reliable decision support system to evaluate flood risk, to plan and design flood damage assessment and mitigation systems. In current practice, flood damage evaluations are generally carried out based on results obtained from one dimensional (1D) numerical simulations. In some cases, however, 1D simulation is not able to accurately capture the dynamics of the flood events. The present study describes a decision support system, which is based on 2D flood simulation results obtained with CCHE2D-FLOOD. The 2D computational results are complemented with information from various resources, such as census block layer, detailed survey data, and remote sensing images, to estimate loss of life and direct damages (meso or micro scale) to property under uncertainty. Flood damage calculations consider damages to residential, commercial, and industrial buildings in urban areas, and damages to crops in rural areas. The decision support system takes advantage of fast raster layer operations in a GIS platform to generate flood hazard maps based on various user-defined criteria. Monte Carlo method based on an event tree analysis is introduced to account for uncertainties in various parameters. A case study illustrates the uses of the proposed decision support system. The results show that the proposed decision support system allows stake holders to have a better appreciation of the consequences of the flood. It can also be used for planning, design, and evaluation of future flood mitigation measures.     

Integrated methodology for flood risk assessment and application in urban communities of Pakistan

Flood disasters and its consequent damages are on the rise globally. Pakistan has been experiencing an increase in flood frequency and severity along with resultant damages in the past. In addition to the regular practices of loss and damage estimation, current focus is on risk assessment of hazard-prone communities. Risk measurement is complex as scholars engaged in disaster science and management use different quantitative models with diverse interpretations. This study tries to provide clarity in conceptualizing disaster risk and proposes a risk assessment methodology with constituent components such as hazard, vulnerability (exposure and sensitivity) and coping/adaptive capacity. Three communities from different urban centers in Pakistan have been selected based on high flood frequency and intensity. A primary survey was conducted in selected urban communities to capture data on a number of variables relating to flood hazard, vulnerability and capacity to compute flood risk index. Households were categorized into different risk levels, such as can manage risk, can survive and cope, and cannot cope. It was found that risk levels varied significantly across the households of the three communities. Metropolitan city was found to be highly vulnerable as compared to smaller cities due to weak capacity. Households living in medium town had devised coping mechanisms to manage risk. The proposed methodology is tested and found operational for risk assessment of flood-prone areas and communities irrespective of locations and countries.     

Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment

Natural Hazards - Urban flood hazard model needs rainfall with high spatial and temporal resolutions for flood hazard analysis to better simulate flood dynamics in complex urban...