Flood Vulnerability Assessment Research Articles

Developing Composite Indicators for Flood Vulnerability Assessment: Effect of Weight and Aggregation Techniques

Developing Composite Indicators for Flood Vulnerability Assessment: Effect of Weight and Aggregation Techniques

An assessment of flood vulnerability and adaptation: A case study of Hamutsha-Muungamunwe village, Makhado municipality.

This study assesses flood vulnerability, levels of vulnerability, determinants of flood vulnerability and coping strategies for flood hazards. The vulnerability and resilience of the local communities are key concepts in this study. Most households are vulnerable to flood hazards. It is therefore important to measure their levels of vulnerability and assess their responses for current and future planning. A flood vulnerability index was used to measure the extent of flood vulnerability. Key informant interviews, field surveys and household questionnaires were used to collect the data. The results show that vulnerability to flood in this community is determined by the nature of soil, dwelling type, employment, education and amount of rainfall in a season. Social and economic components scored higher than the physical environment, while social factors are higher than the economic factors. Contextual coping strategies in this community were temporary relocation, evacuation to a safe area and waiting for government and neighbours to help. The study recommends that public awareness campaigns, early warning systems and improved disaster management strategies must take into consideration differentiated levels of vulnerability and community coping mechanisms and preferences.

Flood Vulnerability Assessment of Afikpo South Local Government Area, Ebonyi State, Nigeria

The study was conducted in Afikpo South Local Government covering a total area of 331.5km2. Remote sensing and Geographic Information System (GIS) were integrated with multicriteria analysis to delineate the flood vulnerable areas. Seven criteria were considered; rainfall, runoff, slope, distance to drainage, drainage density, landuse and landcover, and soil. The various criteria were fit into fuzzy membership classes based on their effect in causing flood. The fuzzy members of all criteria were then overlaid to generate the flood vulnerability map. The result of the flood vulnerability map shows that very low vulnerable zones cover 86.7% of the total area, low vulnerable zones cover 1.6% of the total area, moderate vulnerable zones cover 2.17% of the total area, highly vulnerable zones cover 2.3% of the total area while very highly vulnerable zones cover 7.3% of the total area. Built up was used as a measure of the effect of flooding on human lives and properties in Afikpo South Local Government. Built up covers a total area of 38.6km2. Over sixty eight (69.8%) of built up lies in very low vulnerable zone, 3% lies in low vulnerable zone, 3.7% lies in moderate vulnerable zone, 0.6% lies in highly vulnerable zone and 17.9% lies in very highly vulnerable zone. The study provides information on target areas that may be affected by flood in Afikpo South Local Government. This information is useful for decision making on flood early warning and preparedness as well as in mitigation preparedness within Afikpo LGA.

Ensemble-based flood vulnerability assessment for probable maximum flood in a changing environment

The magnitude and frequency of hydro-meteorological extremes are expected to increase in a changing environment in ways that threaten the security of US energy-water assets. These include probable maximum precipitation (PMP) and probable maximum flood (PMF), which are used as hydraulic design standards for highly sensitive infrastructures such as nuclear power plants and main dams. To assess the flood vulnerability due to PMP/PMF, an integrated high-resolution process-based hydro-meteorologic modeling framework was used to develop ensemble-based probabilistic flood maps based on best-available historic observations and future climate projections. A graphics processing unit–accelerated 2-dimensional hydrodynamic model was used to simulate the surface inundation areas corresponding to a total of 120 PMF hydrographs. These ensemble-based PMF maps were compared with flood maps obtained from the conventional deterministic PMP/PMF approach, revealing added information about conditional probability of flooding. Further, a relative sensitivity test was conducted to explore the effects of various factors in the framework, such as meteorological forcings, antecedent hydrologic conditions, reservoir storage, and flood model input resolution and parameters. The proposed framework better illustrates the uncertainties associated with model inputs, parameterization, and hydro-meteorological factors, allowing more informed decision-making for future emergency preparation.

Comparative Analysis of Flood Vulnerability Indicators by Aggregation Frameworks for the IPCC’s Assessment Components to Climate Change

As severe flood damages have been increasing due to climate change, the flood vulnerability assessment is needed in the flood mitigation plans to cope with climate-related flood disasters. Since the Intergovernmental Panel on Climate Change Third Assessment Report (IPCC TAR) presented the three assessment components, such as exposure, sensitivity, and adaptability for the vulnerability to climate change, several aggregation frameworks have been used to compile individual components into the composite indicators to measure the flood vulnerability. It is therefore necessary to select an appropriate aggregation framework for the flood vulnerability assessments because the aggregation frameworks can have a large influence on the composite indicator outcomes. For a comparative analysis of flood vulnerability indicators across different aggregation frameworks for the IPCC’s assessment components, the composite indicators are derived by four representative types of aggregation frameworks with all the same proxy variable set in the Republic of Korea. It is found in the study site that there is a key driver component of the composite indicator outcomes and the flood vulnerability outcomes largely depend on whether the key component is treated independently or dependently in each aggregation framework. It is concluded that the selection of an aggregation framework can be based on the correlation and causality analysis to determine the relative contribution of the assessment components to the overall performance of the composite indicators across different aggregation frameworks.

Urban flood vulnerability assessments: the case of Dire Dawa city, Ethiopia

Dire Dawa city is identified as one of the most flood-affected cities in Ethiopia. Classifying village-level flood vulnerability using flood indicators is a new approach to Dire Dawa city. Analysis of different flood vulnerability factors underpins sustainable flood risk management and the application of Flood Vulnerability Index (FVI) approach is the hub of this study. Relevant data were collected from 110 households sampled from purposely selected 10 villages found in Dire Dawa city. The flood vulnerability index was used to compare, classify and rank villages in terms of their flood vulnerability levels. For this purpose, 24 sets of indicators which are strongly affecting the levels of flood vulnerability were assessed from social, economic and physical perspectives. The FVI of each village was computed with unequal method of weighting indicators. The findings of the study revealed that Dire Dawa city villages were experiencing varying levels of flood vulnerability. Accordingly, villages 05, 06, 07 and 09 were identified with high flood vulnerability level while villages 03, 04 and 08 and villages 01, 02 and extension village were identified with medium and low level of vulnerability, respectively. Interestingly, the findings of the study confirmed that social factors contributed much for flood vulnerability in Dire Dawa city. Hence, future urban flood risk planning and management endeavors in the city of Dire Dawa must be underpinned by proper utilization of the flood vulnerability map developed addressing social vulnerability component through both structural and non-structural urban flood risk management measures.

Integrated urban flood vulnerability assessment using local spatial dependence-based probabilistic approach

Vulnerability assessment is an essential step for urban flood risk management. Due to the objective existence of statistical errors in the variables and spatial heterogeneity, as well as the similarity of flood experience, precautionary status and environments for neighbouring areas, an urban flood vulnerability assessment essentially entails a multi-factor decision-making process that accounts for uncertainties and the local spatial dependence of neighbourhoods. To address these issues, an uncertainty-based vulnerability assessment approach embedded with an improved moving split-window (IMSW) analysis and probabilistic method is proposed. To develop an integrated urban flood vulnerability assessment model, three technical issues need to be resolved: (1) the development of damage curves of land-use types, (2) an uncertainty model and spatial dependence model of damages based on an IMSW analysis, and (3) an uncertainty-based framework to quantify vulnerability considering the uncertainties and local spatial dependence of the damage curves as well as the spatial heterogeneity of risky assets simultaneously. The proposed method is applied to an urban area in China and provides an integrated vulnerability assessment for different land-use types. Moreover, uncertainty and sensitivity analyses were performed to analyse the spatial differentiation and the dominant parameters of vulnerability. Compared with two other commonly used methods, the proposed local-correlated method (LCM) is more in line with reality, and provides more reasonable information for making a better-informed decision.

A methodology for urban micro-scale coastal flood vulnerability and risk assessment and mapping

One of the most dangerous challenges to settlements in the UK comes from flooding. Currently, there is extensive map coverage of flood hazards zones in the UK; however, it is increasingly recognised that risk associated with natural hazards cannot be reduced solely by focussing on the hazard. There is also an urgent need for methods of evaluating and mapping flood vulnerability and risk in detail. Despite its significance, conventional flood risk assessment methodologies often underestimate likely levels of vulnerability in areas prone to hazards, yet it is the degree of vulnerability within a community that determines the consequences of any given hazard. The research presented proposes a general methodology to assess and map Coastal Flood Vulnerability and Risk at a detailed, micro-scale level. This captures aspects that are considered crucial and representative of reality (socio-economic, physical and resilient features). The methodology is then applied to a UK case study (city of Portsmouth). Environment Agency flood hazard data, National Census socio-economic data and Ordnance Survey topographic map data have been used to evaluate and map coastal flood vulnerability, examining neighbourhoods within census wards. This led to a subsequent analysis of Coastal Flood Risk, via the combination of a Coastal Flood Vulnerability Index and a Coastal Flood Hazard Index, for the Portsmouth ward Hilsea. This, consequently, identifies potential weaknesses that could lead to more effective targeting of interventions to improve resilience and reduce vulnerability in the long term and provides a basis for hazard and environmental managers/planners to generate comprehensive national/international vulnerability and risk assessments.

Spatially-explicit sensitivity and uncertainty analysis in a MCDA-based flood vulnerability model

ABSTRACTThis study presents a methodology for conducting sensitivity and uncertainty analysis of a GIS-based multi-criteria model used to assess flood vulnerability in a case study in Brazil. The paper explores the robustness of model outcomes against slight changes in criteria weights. One criterion was varied at-a-time, while others were fixed to their baseline values. An algorithm was developed using Python and a geospatial data abstraction library to automate the variation of weights, implement the ANP (analytic network process) tool, reclassify the raster results, compute the class switches, and generate an uncertainty surface. Results helped to identify highly vulnerable areas that are burdened by high uncertainty and to investigate which criteria contribute to this uncertainty. Overall, the criteria ‘houses with improper building material’ and ‘evacuation drills and training’ are the most sensitive ones, thus, requiring more accurate measurements. The sensitivity of these criteria is explained by their weights in the base run, their spatial distribution, and the spatial resolution. These findings can support decision makers to characterize, report, and mitigate uncertainty in vulnerability assessment. The case study results demonstrate that the developed approach is simple, flexible, transparent, and may be applied to other complex spatial problems.

Flood Vulnerability Assessment in Gashua: Issues and Prospectives

In most developing economies, destruction of lives and properties are common especially the riverine communities along the Lake Chad area of Africa where flooding are annual disaster routine. Gashua is a riverine community with gentle slope terrain and have recently witnessed rapid growth and development. This community have being witnessing torrential rainfall coupled with budding anthropogenic activities. Thus, the development of the area has being facing serious risk of flood vulnerability which were largely as a result of it location along river Yobe. This study focused on examining flood risk vulnerability in Gashua through the concurrently use of quantitative and qualitative data. The study utilizes geo-referenced data with the aid of Geographic Information System (GIS) technique for flood vulnerability analysis. The study revealed that soil type and terrain of this area contributed to poor draining of rain which subsequently leads to water overflow in the area. Moreover, this study also uncovered that poor drainage systems as well as poorly planned street layout in the build up areas has contributed to increasing magnitudes of destruction during flood events in this area. The study finally recommended that the need for immediate essential upgrade of urban renewal and immediate re-construction of the town drainage system.

A systematic review on approaches and methods used for flood vulnerability assessment: framework for future research

Floods have always been associated with widespread devastation and destruction since the emergence of human civilization. The intensity of this disaster has been increasing due to accelerated impact of human activities. Flood vulnerability is very diverse in nature and is multidimensional and a topic of vital significance. Hence, flood vulnerability assessment assumes greater significance since magnitude of destructions varies over space and time. The study makes a credible attempt to present a coherent review on the approaches and methodologies used for assessing flood and its vulnerability. A time frame of 1990–2018 was chosen for analyzing varied works carried out flood vulnerability and susceptibility assessment. Articles from Scopus and other reputed journals were used to review the works on flood assessments. Methods and approaches were examined by considering most-cited authors and keywords used in their works. The study revealed a gap existing between methods and approaches for evaluating flood vulnerability which can be incorporated by using high-resolution data along with using multidimensional approach for assessing vulnerability. Furthermore, this study calls for comprehensive flood assessment using artificial neural network, hydrodynamic models and geospatial techniques to provide a vivid visualization of flood susceptibility. The study may prove helpful in analyzing different components of vulnerability and guiding research gaps in methodology to be used for assessing flood vulnerability at spatial scales.

Integrating a resilience scorecard and landscape performance tools into a Geodesign process

ABSTRACTUncertainty about the impacts of sea-level rise make the ability to forecast future spatial conditions a necessary planning/design tool. Geodesign integrates multiple fields of science with change/impact models and planning/design strategies. Proactive planning analyses such as newly developed scorecards allow for plan evaluation; design strategies can now be quantitatively assessed using landscape performance calculators. Neither have been explored as Geodesign tools. A Geodesign process was developed using the resilience scorecard to assess flood vulnerability using projections for the 100-year floodplain with sea-level rise by 2100. Projections were used as a guide to develop a resilient master plan for League City, TX, USA. Future impacts of the plan are projected using landscape performance measures.

A simplified approach for flood vulnerability assessment of historic sites

In the last decades, floods have increased in frequency all over the world due to diverse phenomena such as climate change, extended urbanization, land use, etc. Their social, cultural, economic and environmental impacts have also grown significantly, highlighting the need for the development of further studies and improved methods to manage and mitigate flood risk, mainly in urban areas. Historic sites need particular attention in this field, not only because the high and irreplaceable cultural value of these areas, but also taking into account that the constructive typologies that they host are particularly vulnerable to natural hazards. In consequence of that, the analysis of the phenomena, the evaluation of their consequences and the adoption of adequate mitigation and preparedness measures are presently a fundamental societal challenge. Having this in mind, the present paper aims at proposing an innovative methodology focused on the assessment of flood vulnerability in historic sites through the evaluation of a set of exposure and sensitivity indicators. From the analysis of these indicators, it is possible to obtain a Flood Vulnerability Index capable of measuring the spread of flood vulnerability over an extended area. The historic centre of Guimaraes, in Portugal, declared by UNESCO as a World Heritage Site in 2001, is used here as a pilot case study to apply and discusses the preliminary version of the approach. Although some improvements are still needed, this approach can be already used to provides preliminary vulnerability scenarios and to point the way to the definition of more efficient and customized strategies for managing and mitigating flood risk in historic sites. Moreover, with further improvements and calibrations resorting to larger and more diverse data, it will be possible to reduce some of the uncertainties currently involved in the assessment process and to make its application wider and more robust.

A Case Study on Flood Vulnerability Results of Different Assessment Methods in the Nakdong Watershed

A variety of flood vulnerability assessments have been carried out in many previous studies to prioritize flood damage mitigation plans. However, domestic and foreign studies have not analyzed the influence of vulnerability assessment components in different methods for determining flood vulnerability outcomes. Therefore, this study investigated the differences in flood vulnerability results for the 54 administrative districts in the Nakdong Watershed that implemented widely used methods, such as the OECD PSR, IPCC concept, and MOLIT PFD. It was found that the three analysis methods could result in very different flood vulnerability index outcomes in a considerable number of districts. This case study on flood vulnerability outcomes of different assessment methods can help to select a proper method for assessment purposes. Keywords: Flood Vulnerability Assessment, OECD PSR, IPCC Concept, MOLIT PFD

Influence of Construction Schemes for a Non-compensatory Composite Indicator on Flood Vulnerability Assessments in the Korean Peninsula

This study aims to investigate the influence of construction schemes for non-compensatory composite indicators by multiplicative utility functions on the flood vulnerability assessment. The flood vulnerability outcomes are evaluated and compared for the 231 administrative districts in the Republic of Korea, based on the two composite indicators by different aggregation schemes from the three assessment components such as exposure, sensitivity, and coping, presented in The IPCC Third Assessment Report. The one scheme uses the coping component having a negative functional relationship with vulnerability as a divisor, and the other scheme employs the lack of coping component in the opposite concept to coping as a multiplier. As a result of comparison analysis, some districts show markedly large differences in the flood vulnerability ranking orders by the two different aggregation schemes using the same proxy variables. For robustness of flood vulnerability assessment outcomes, it is necessary to compile a non-compensatory composite indicator under the condition that all constituent assessment components have the same directional elasticity to vulnerability. This study can help to select a proper aggregation framework in constructing flood vulnerability indicators to provide useful information for supporting policy and decision-making on complex issues.

Editorial

Editorial

도시계획 적용을 위한 도시홍수 취약성 및 리스크 평가

도시계획 적용을 위한 도시홍수 취약성 및 리스크 평가

A Study on the Selection of Representative Indicators of Flood Vulnerability Assessment

A Study on the Selection of Representative Indicators of Flood Vulnerability Assessment

MAPPING OF HIGHLY HETEROGENEOUS URBAN STRUCTURE TYPE FOR FLOOD VULNERABILITY ASSESSMENT

Abstract. Vulnerability plays an important role in risk assessment. For flood vulnerability assessment, the map and characteristics of elements-at-risk at different scales are strongly required depending on the risk and vulnerability assessment requirements. This study proposes a methodology to classify urban structure type by combining object-based image classification and different high resolution remote sensing data. In this study, a high resolution satellite image and LiDAR have been acquired over Kota Bharu, Kelantan which consists of highly heterogeneous urban structure type (UST) classes. The first stage is data pre-processing that includes orthorectification and pansharpening of Geoeye satellite image, image resampling for normalised Digital Surface Model (nDSM) and followed by image segmentation for creating meaningful objects. The second stage comprises of derivation of image features, generation of training and testing datasets, and classification of UST. The classification was based on three types of machine learning classifiers, i.e. Random Forest (RF), Support Vector Machine (SVM) and Classification and Regression Tree (CART). The results obtained from the classification processes were compared using individual omission and commission error, overcall accuracy and Kappa coefficient. The results show that Random Forest classifier with all image features achieved the highest overall accuracy (93.5%) and Kappa coefficient (0.94). This is followed by CART classifier with overall accuracy of 93.7% and Kappa coefficient of 0.92. Finally, SVM classifier produced the lowest overall accuracy and Kappa coefficient with 88.6% and 0.86, respectively. The UST classification result can be further used to assist detailed building characterisation for large scale flood vulnerability assessment.

Urban neighbourhood flood vulnerability and risk assessments at different diurnal levels

Diurnal changes within communities can significantly alter the level of impacts during a flood, yet these essential daily variations are not currently catered for within flood risk assessments. This paper develops a flood vulnerability and risk model that captures crucial features of flood vulnerability; integrating physical and socio‐economic vulnerability data, combined with a flood hazard analysis, to give overall flood risk at neighbourhood scale, at two different times of day, for floods of different magnitudes. The flood vulnerability and risk model, the resulting diurnal coastal flood vulnerability and risk indexes, and corresponding maps for the ward of Hilsea (Portsmouth, United Kingdom), presented within this paper, highlight three previously unidentified neighbourhoods in particular in the northwest of the Hilsea ward, which have the highest levels of risk during both time zones and for flood events of different magnitude. Critically, these neighbourhoods lie further inland and not directly on the Hilsea coastline, yet by analysing at this resolution (including diurnal impacts), substantial levels of underlying vulnerability were identified within these areas.