Flood Vulnerability Assessment Research Articles

Flood vulnerability assessment using a fuzzy rule-based index in Melbourne, Australia

The City of Moreland is a densely populated urban area in Melbourne and has suffered from riverine and overland flooding during the past few years. Therefore, it is necessary to conduct a flood vulnerability analysis in the region to determine the necessary measures for better flood risk management. A fuzzy rule based flood vulnerability index was developed in this study considering hydrological, social, and economic aspects of flood damages to assess and map the flood vulnerability of MC. It was found that 51.6% of the area (corresponds to 26.21 km2) falls under very low and low flood vulnerability zones, whereas 7.6% of the total area are classified as high and very high flood vulnerable zones. The outcomes of the present study will help the concerned authorities in the study area to identify flood prone areas and develop flood mitigation strategies to minimise the damages caused by floods.

Assessment of flood vulnerability in some communities in Lokoja, Kogi State, Nigeria, using Participatory Geographic Information Systems

Lokoja, the capital of Kogi State, Nigeria, experiences seasonal flooding with devastating consequences on the people and the natural and built environments. In contrast with developed countries, researchers and flood managers in Nigeria have largely ignored Participatory Geographic Information System, which integrates the perceptions and experiences of the people affected by flood events with technical, conventional methods, as a flood management strategy, with flood managers employing a reactive, top-bottom post-flood strategy of relief and rescue. This study employed PGIS to conduct a vulnerability assessment in Lokoja as a pre-flood strategy that involves the communities. Datasets utilized include Landsat imageries, DEM, and soil samples. Spatial multi-criteria evaluation using the analytical hierarchy process was employed to analyze flood parameters determined through community participation to evaluate vulnerability while consistency ratio was also calculated to ensure that the comparison of criteria made was consistent. Results revealed that elevation is the most important factor, and land use, among other parameters of flood vulnerability. Out of a total area of 6, 258 Ha, 4, 445 Ha are highly vulnerable and 1, 815 Ha being moderately vulnerable. Comparison consistency ratio was determined to be 0.08 which is acceptable. Based on the results, this study concludes that the perception of affected communities can complement conventional flood research for a more effective response and mitigation strategy. The research therefore recommends the integration of geospatial techniques and participatory approaches for flood vulnerability studies for a proactive, bottom-up approach to flood management.

A GIS-based Approach for Flood Vulnerability Assessment in Hoa Vang District, Danang City, Vietnam

Danang is a coastal city in the Central Region, VietNam which is considered as a sensitive area under the high risks of natural disasters and climate change. Located in downstream of Vu Gia - Thu Bon river system, Da Nang city is often inundated in flood season. Hoa Vang district is considered as the most flood damaged region in Danang City due to its location and topography. Assessing socio-economic vulnerability of floods is important in the management of natural disaster risks, from that developing solutions to mitigate the damage caused by floods. This study develops a flood vulnerability assessment method for the Hoa Vang district, Danang City based on the Geographic Information System (GIS). Through analyzing the inundation situation and local socio-economic conditions, the research has selected and developed a set of criteria to assess the flood vulnerability for the study area and presented in GIS environment. Based on the spatial analysis methods in GIS, the study has identified Flood Vulnerability Index (FVI) and generated the flood vulnerability map for Hoa Vang district, Danang city. The results from this study are important in order to propose the solutions for responding to flood hazard in Da Nang City.

Effects of Different Normalization, Aggregation, and Classification Methods on the Construction of Flood Vulnerability Indexes

Index-based approaches are widely employed for measuring flood vulnerability. Nevertheless, the uncertainties in the index construction are rarely considered. Here, we conducted a sensitivity analysis of a flood vulnerability index in the Maquiné Basin, Southern Brazil, considering distinct normalization, aggregation, classification methods, and their effects on the model outputs. The robustness of the results was investigated by considering Spearman’s correlations, the shift in the vulnerability rank, and spatial analysis of different normalization techniques (min-max, z-scores, distance to target, and raking) and aggregation methods (linear and geometric). The final outputs were classified into vulnerability classes using natural breaks, equal interval, quantiles, and standard deviation methods. The performance of each classification method was evaluated by spatial analysis and the Akaike’s information criterion (AIC). The results presented low sensitivity regarding the normalization step. Conversely, the geometric aggregation method produced substantial differences on the spatial vulnerability and tended to underestimate the vulnerability where indicators with low values compensated for high values. Additionally, the classification of the vulnerability into different classes led to overly sensitive outputs. Thus, given the AIC performance, the natural breaks method was most suitable. The obtained results can support decision-makers in reducing uncertainty and increasing the quality of flood vulnerability assessments.

Flood vulnerability assessment using GIS at Fetam watershed, upper Abbay basin, Ethiopia

Flood is a danger to human beings and their properties because less consideration is given for risk analysis and assessment of risk areas. The main aim of this study was to assess the flood vulnerability areas of Fetam watershed. For analyzing this issue, flood generating factors: slope, elevation, land use/land cover, drainage density, rainfall, and soil types were rated and collected to mark out flood vulnerability zones using a multi-criteria evaluation technique within the Geographic Information System (GIS). Maps were constructed using past data on river banks and discharge of earlier floods along with topographic data to illustrate areas susceptible to flood for various discharges. The influences of all overflow distribution factors were calculated using pair-wise evaluation techniques for decisive weighted-overlay investigation of each factor in flood vulnerability assessment. The flood vulnerability valuation map showed that 67.54, 634.11, 280.89, 121.28, and 2.81 km2 areas correspond to very high, high, moderate, low, and very low flood vulnerabilities respectively. Residential areas and farming fields are located along with the flood hazard areas, which are susceptible to flooding. Hence, these areas are vulnerable to social and economic development due to loss of life and damage to properties of resident people. The main result of this study showed that the upstream and center part of Fetam watershed is highly sighted than the downstream part.

Flood Vulnerability Assessment by Flood Vulnerability Index (FVI) Method: A Study on Sirajganj Sadar Upazila

Flood Vulnerability Assessment by Flood Vulnerability Index (FVI) Method: A Study on Sirajganj Sadar Upazila

Climate Change Vulnerability and Disaster Risk Assessment Using Remote Sensing Technology and Adaptation Strategies for Resiliency and Disaster Risk Management in Selected Coastal Municipalities of Zambales, Philippines

The Philippines is one of the most hazard prone and vulnerable countries in the world to climate change effects due to its geographical location. Climate change is already happening and affecting many places causing huge problems to coastal ecosystems. Vulnerability and disaster assessment and mapping in coastal areas are essential tasks and undertakings for coastal disaster risk management. The objectives of this study were to assess the climate change vulnerability and disaster risks in the four municipalities (Sta. Cruz, Candelaria, Masinloc and Palauig) of Zambales and to determine the climate change community-based adaptation (CBA) and ecosystem-based adaptation (EBA) strategies. Remote sensing, GIS, secondary data gathering and key informant interview were used to assess vulnerability and disaster risks and mapping in the four municipalities. Survey questionnaire, focus group discussion and key informant interview were utilized in gathering data for the determination of climate change adaptation strategies. Using remote sensing technology, it was revealed that coastline changes have occurred in the shorelines of the four coastal municipalities after a decade. Sea level rise happened in Sta. Cruz and Masinloc, Zambales while there was build-up of soil in the coastline of Candelaria and Palauig, Zambales. Twelve hazard maps, 12 vulnerability maps and 12 disaster risk maps were generated for the three major disasters (flood, landslide, storm surge) in the four coastal municipalities. Based on the flood vulnerability and disaster risk assessment, the municipality of Palauig was found to be the most prone to flooding while the municipality of Candelaria was found to be the most vulnerable to landslide compared to other municipalities. All coastal barangays in the four municipalities were susceptible to storm surge. The four coastal municipalities were conducting community-based adaptation (CBA) and ecosystem-based adaptation (EBA) approaches in order to protect their coastal resources from the damaging impacts of climate change and improve the resilience of their local communities.

System approach for flood vulnerability and community resilience assessment at the local level – a case study of Sakon Nakhon Province, Thailand

System approach for flood vulnerability and community resilience assessment at the local level – a case study of Sakon Nakhon Province, Thailand

Assessing Flood Vulnerability Index for Policy Implications Towards Flood Risk Management Along the Atlantic Coast of Limbe, Cameroon

Floods along the Atlantic coast of Limbe are the most predominant natural disaster posing serious threats to man and the environment. Without adequate information about the risk levels and why the implementation of locally appropriate adaptation measures are less effective, flood disasters will continue to become more rampant and disastrous. The ability to accurately identify, measure and evaluate the various vulnerabilities of affected people and communities is a right step towards reducing disaster risk. This article focuses on developing a Flood Vulnerability Index (FVI) based on exposure, susceptibility and resilience factors that will guide putting in place specific adaptation plans targeted at reducing the impacts of floods. The study made use of the mixed research design method. Reponses were gathered from 183 respondents using questionnaires and focus group discussions (FGD) from household heads to construct an integrated vulnerability index made up of 22 indicators grouped into susceptibility indicators (15), resilience (5) and exposure (2). A handheld Global Positioning System (GPS) was used in the measurement of distance and elevation. Data collected was subjected to analysis of variance to test if significant differences in vulnerability exist within the neighborhoods and the level of success of adaptation strategies was also investigated. Findings show that Motowo and Church Street have very small vulnerability to floods, Cassava Farm and Clerks Quarters have high vulnerability to floods and Down Beach with an index of 0.84 has a very high vulnerable to floods. From the results coastal communities are significantly different (p < 0.01) in terms of vulnerability to flood hazards. A total of 19.39% of the population highlighted that the adaptation strategies put in place to help combat floods in their neighborhoods are effective while 80.61% of the respondents decried that the measures were not effective. Coping strategies need to take into consideration the myriad of factors involved in the determination of vulnerability so as to help putting in place a comprehensive multi-risk adaptation strategy. Policies implications of the results warrant a conscious effort by the council to clear chocked gutters, culverts and major drains to ease water flow especially during the rainy seasons and local authorities and ministries must make sure proper land use plans are in place and are enforced without any fear or favor so as to ensure resilience to flood risks.

Development of Flood Vulnerability Assessment Method considering Urban Characteristics: Daegu Metropolitan City

This study intends to develop a flood vulnerability assessment method and flood damage reduction measures in urban areas for Daegu Metropolitan City. The proxy variables for the flood vulnerability assessment were calculated using the previously investigated proxy variables for urban areas. The Flood Vulnerability Index (FVI) of the urban area was proposed using the Regional Significance Index (RSI), which indicates the importance of each region, and the Damage Possibility Index (DPI) for flood damage data. The RSI selected four proxy variables: population density, vulnerable population ratio, property density, and area ratio of major facilities. The DPI also selected four proxy variables: area ratio of low land, the impervious area ratio, status of domestic disaster risk district, and flood occurrence record. Eight proxy variables were selected and the FVI of urban areas calculated using multiplicative utility functions. As a result of the calculation, the FVI of Daegu Metropolitan City was found to be high in the central urban areas and by the streams. The results of this study are expected to be used for flood vulnerability assessments in urban areas and establishing flood damage reduction measures.

A model taxonomy for flood fragility and vulnerability assessment of buildings

In the last two decades, probabilistic approaches to flood risk modeling have emerged, often as an extension of more consolidated methods used in probabilistic seismic risk assessment. Nonetheless, only a few studies deal with best-practice methodologies for flood physical vulnerability assessment, and existing approaches/models often lack appropriate guidance for their selection/rating and use. These concerns underline the need for a rational, integrated and comprehensive compendium of existing flood-related fragility (i.e., the likelihood of various damage states as a function of hazard intensity measure(s)) and vulnerability (i.e., the likelihood of loss levels as a function of hazard intensity measure(s)) models to be used in probabilistic flood risk assessment. To this aim, and following the approach used in the guidelines recently developed by the Global Earthquake Model (GEM) project, this paper proposes a model taxonomy for flood fragility and vulnerability assessment of buildings. A review of state-of-the-art large-scale models for flood vulnerability assessment is first carried out. A discussion on the main factors affecting the reliability of empirical fragility and vulnerability relationships is presented, focusing on data sources, building classification, statistical techniques for data collection/fitting, and damage scales/loss metrics. As a proof of concept, a compendium of existing studies dealing with empirical fragility and vulnerability models for buildings is finally developed and discussed based on the proposed model taxonomy. This type of database can benefit (re)insurance companies interested in flood loss assessment and various decision-makers (e.g., governmental agencies) committed to mitigate flood risk and communicate its level to different stakeholders.

Geospatial approach for assessment of vulnerability to flood in local self governments

Recent years have shown a significant increase in the occurrence of floods globally, with an impact on habitation and different sectors of the economy. This, in turn, necessitates the use of different flood mitigation strategies, wherein flood vulnerability assessment plays a significant role. The proposed work presents a methodology that combines vulnerability under physical-environmental and socio-economic domains to assess the overall flood vulnerability at the local self-government level. The methodology was illustrated to the case of Aluva municipality, located on the banks of River Periyar, in Kerala state, India. The spatial variation of hazard inducing factors and population statistics were analysed using Geographic Information System (GIS) tools. The machine learning algorithm, Random Forest, which uses hazard inducing factors as input was implemented for the evaluation of physical-environmental vulnerability. The social vulnerability of the region was analysed using the GIS Multi-criteria decision analysis approach (MCDA), with criteria weights to incorporate the interests of different stakeholders. The critical combinations of the two domains of vulnerability in the assessment of the vulnerability to flood, to have efficient flood management in local self-government was demonstrated in this study and can be made use of for any flood event.

New neural fuzzy-based machine learning ensemble for enhancing the prediction accuracy of flood susceptibility mapping

ABSTRACT High-accuracy flood susceptibility maps play a crucial role in flood vulnerability assessment and risk mitigation. This study assesses the potential application of three new ensemble models, which are integrations of the adaptive neuro-fuzzy inference system (ANFIS), analytic hierarchy process (AHP), certainty factor (CF) and weight of evidence (WoE). The experimental area is the Trotuș River basin in Romania. The database for the present research consisted of 12 flood-related factors and 172 flood locations. The quality of the models was evaluated using root mean square error (RMSE) values and the ROC curve (AUC). The results showed that the ANFIS-CF model and the ANFIS-WOE model have a high prediction capacity (accuracy > 91.6%). Therefore, we concluded that ANFIS-CF and ANFIS-WoE are two new tools that should be considered for future studies related to flood susceptibility modelling.

Physical flood vulnerability assessment of buildings in Kota Bharu, Malaysia: an indicator-based approach

Purpose The purpose of this paper is to introduce a geospatial approach for buildings flood vulnerability assessment using an indicator-based method (IBM) to support flood risk assessment and mapping of physical elements at risk in Kota Bharu District, Kelantan, Malaysia. Design/methodology/approach The study developed an indicator-based approach to undertake physical flood vulnerability assessment of buildings. The approach takes into consideration flood hazard intensity, building characteristics and structures surrounding the environment as factors that influence flood vulnerability. The aggregation of the total flood vulnerability index is carried out in a geographic information system (GIS) environment. Findings The results provide a spatial representation of buildings flood vulnerability index in Kota Bharu Malaysia, and the degree of expected vulnerability is expressed on a scale between 0 to 1 (low damage to total damage). Mapping flood vulnerability index of buildings should be considered in future flood mitigation and evacuation planning. Originality/value Unlike other indicator-based methods (IBMs) developed for physical flood vulnerability assessment, in the current study, hazard intensity has been considered and incorporated in the physical flood vulnerability model.

Flood Vulnerability Assessment of Settlements in the Niger-benue Trough, Central Nigeria

Flooding has become a household phenomenon, particularly for communities in close proximity or situated in floodplain areas, although only on extreme cases that serious alarms are given. The brunt of this study assessed the flood vulnerability levels of settlements located in the Niger-Benue Trough of Central Nigeria by considering their livelihood assets. Data were sourced via a random administration of questionnaire in 36 communities in the study area earmarked; water level and discharge data obtained; communities were mapped; and remotely sensed data (Spot 5 and the Shuttle Radar Topographic Mission (SRTM) data were retrieved and analyzed using ArcGIS 10.5 and the Statistical Package for Social Sciences (SPSS 25) software. The simulated worst-case scenario of flooding revealed 22 settlements were inundated in the 2019 flood between July – September, covering larger areas before the confluence with more than 50% of the area under the high and moderately high-risk zones. Natural and physical livelihood assets were vulnerable and seriously damaged with indices greater than 3.0, while human, financial and social assets were all below 3.0. Generally, vulnerability index computed for all communities was 2.82, indicating moderate vulnerability of the communities to the flood event of 2019. Also, the Pearson correlation test revealed a strong, positive relationship (r = .769, α = .036) between the level of communities’ flood vulnerability and the livelihood assets in the study. It was therefore recommended that yearly flood events are worth simulating to aid prioritization of decisions and development of a comprehensive flood management plan for the area.

Flood vulnerability assessment using an integrated approach of multi-criteria decision-making model and geospatial techniques

Floods are one of the most devastating natural catastrophes, always associated with massive disruption to humans, land, and the economy. The current research focusses on the identification of Flood Vulnerable Zones (FVZ) of Kanyakumari district with the integration of Remote Sensing (RS) and Geographic Information System (GIS), and the Multi-criteria Decision-Making Analysis (MCDM)-based Analytical Hierarchy Process (AHP) model in the geospatial environment. The weights derived from 10 × 10 decision matrix of AHP model for the flood inducing factors are reflecting their varied priorities from high to low priority as rainfall (0.22), slope (0.124), drainage density (0.154), Land Use Land Cover (LULC) (0.153), Digital Elevation Model (DEM) (0.109), Soil (0.068), geology (0.052), geomorphology (0.048), Surface Runoff (0.042) and Topographic Wetness Index (TWI) (0.03), respectively. Consistency Ratio (CR) value obtained in this case is equal to 0.093 (< 0.1) signifies the acceptance of the derived weights. The more is the weightage given to the parameters, more significance is of the factor towards the occurrence of the flood hazard. The outcomes of the research found that the very high and highly vulnerable zones are spreading over a vast expanse of the district, which are situated in the south, south-east, south-west, and in some pockets of middle and north-east. The use of such a decision-making model-based approach is helpful in the identification and prediction of the susceptible sites, further helps the policymakers in hazard mitigation and decision-making planning.

A local scale flood vulnerability assessment in the flood-prone area of Khyber Pakhtunkhwa, Pakistan

The central part of Khyber Pakhtunkhwa, Pakistan, is a highly flood-prone area of the province. The lives and assets of local communities are deeply vulnerable, attributed to the recurrence of seasonal floods. This concern has motivated decision-makers and the research community to develop and adopt best management practices to address flood vulnerability issues. One of the commonly used methods for evaluating flood vulnerability is empirical investigation using composite indicators. However, there are several issues with the available flood vulnerability literature, using composite indicators in the study area. The objectives of the current study are therefore twofold. On the one hand, it demonstrated in a comprehensive step-by-step approach to develop flood vulnerability composite indicator taking into account the broad range of stakeholders and the reliability of research. On the other hand, the flood vulnerability profile of the selected communities is being developed. Households’ survey was conducted in the selected communities using random sampling. The composite indicators of flood vulnerability were developed as the relative measure of flood vulnerability across the selected communities. A robustness check was also carried out using convenient techniques to address the problem of uncertainty. For such a purpose, the composite indicators of flood vulnerability were developed through various data rescaling, weighting, and aggregation schemes. The relative levels of flood vulnerability are identified across the selected communities, and the findings are illustrated by colored matrices. Different factors were identified for being responsible for the relative vulnerability of various communities. Jurisdiction-wise assessment of flood vulnerability reveals that communities located in Charsadda district are more vulnerable to flooding compared to those in Nowshera district. The study can facilitate a wide range of stakeholders and decision-makers not only to develop composite indicators for flood vulnerability but also to scientifically justify it as a management tool for flood risk reduction.

Assessment of Wave Storm-Induced Flood Vulnerability in Rhodes Island, Greece

Coastal areas are threatened by extreme meteorological phenomena, such as wave storms. Therefore, the analysis of such events, such as providing information for their potential hazards assessment, is a key element in coastal management. In this study, a preliminary assessment of flood vulnerability due to storms was performed in Rhodes Island, Greece. Firstly, storm events were defined in terms of significant wave height, peak period, and duration, and they were grouped by means of cluster analysis into five classes (from weak to extreme) reflecting the intensity of each event. Subsequently, flood hazard was assessed by using an empirical formula for wave run-up calculations on cross-shore profiles and storm surge data at the region. Finally, a Flood Vulnerability Index (FVI) was used for assessing vulnerability according to a scale from very low to very high. The most intense storms were found to occur in the eastern, southeastern, and southern part of the island. More than 60% of storms were classified as weak, while extreme events were found to occur with a frequency of less than 2.5%. Regarding flood hazard and vulnerability, the maximum values of wave run-up were calculated in the southeastern region, but the most vulnerable part was found to be the northwestern region, as the FVI was assessed as very high for weak and extreme events.

Flood vulnerability and risk assessment of urban traditional buildings in a heritage district of Kuala Lumpur, Malaysia

Abstract. Flood hazard is increasing in frequency and magnitude in major South East Asian metropolitan areas due to fast urban development and changes in climate, threatening people's property and life. Typically, flood management actions are mostly focused on large-scale defences, such as river embankments or discharge channels or tunnels. However, these are difficult to implement in town centres without affecting the value of their heritage districts and might not provide sufficient mitigation. Therefore, urban heritage buildings may become vulnerable to flood events, even when they were originally designed and built with intrinsic resilient measures, based on the local knowledge of the natural environment and its threats at the time. Their aesthetic and cultural and economic values mean that they can represent a proportionally high contribution to losses in any event. Hence it is worth investigating more localized, tailored mitigation measures. Vulnerability assessment studies are essential to inform the feasibility and development of such strategies. In this study we propose a multilevel methodology to assess the flood vulnerability and risk of residential buildings in an area of Kuala Lumpur, Malaysia, characterized by traditional timber housing. The multiscale flood vulnerability model is based on a wide range of parameters, covering building-specific parameters, neighbourhood conditions and catchment area conditions. The obtained vulnerability index shows the ability to reflect different exposure by different building types and their relative locations. The vulnerability model is combined with high-resolution fluvial and pluvial flood maps providing scenario events with 0.1 % annual exceedance probability (AEP). A damage function of generic applicability is developed to compute the economic losses at individual building and sample levels. The study provides evidence that results obtained for a small district can be scaled up to the city level, to inform both generic and specific protection strategies.

A generic physical vulnerability model for floods: review and concept for data-scarce regions

Abstract. The use of different methods for physical flood vulnerability assessment has evolved over time, from traditional single-parameter stage–damage curves to multi-parameter approaches such as multivariate or indicator-based models. However, despite the extensive implementation of these models in flood risk assessment globally, a considerable gap remains in their applicability to data-scarce regions. Considering that these regions are mostly areas with a limited capacity to cope with disasters, there is an essential need for assessing the physical vulnerability of the built environment and contributing to an improvement of flood risk reduction. To close this gap, we propose linking approaches with reduced data requirements, such as vulnerability indicators (integrating major damage drivers) and damage grades (integrating frequently observed damage patterns). First, we present a review of current studies of physical vulnerability indicators and flood damage models comprised of stage–damage curves and the multivariate methods that have been applied to predict damage grades. Second, we propose a new conceptual framework for assessing the physical vulnerability of buildings exposed to flood hazards that has been specifically tailored for use in data-scarce regions. This framework is operationalized in three steps: (i) developing a vulnerability index, (ii) identifying regional damage grades, and (iii) linking resulting index classes with damage patterns, utilizing a synthetic “what-if” analysis. The new framework is a first step for enhancing flood damage prediction to support risk reduction in data-scarce regions. It addresses selected gaps in the literature by extending the application of the vulnerability index for damage grade prediction through the use of a synthetic multi-parameter approach. The framework can be adapted to different data-scarce regions and allows for integrating possible modifications to damage drivers and damage grades.