Flood Risk Index Research Articles

Association of Flood Risk Patterns with Waterborne Bacterial Diseases in Malaysia

Flood risk has increased distressingly, and the incidence of waterborne diseases, such as diarrhoeal diseases from bacteria, has been reported to be high in flood-prone areas. This study aimed to evaluate the flood risk patterns and the plausible application of flow cytometry (FCM) as a method of assessment to understand the relationship between flooding and waterborne diseases in Malaysia. Thirty years of secondary hydrological data were analysed using chemometrics to determine the flood risk patterns. Water samples collected at Kuantan River were analysed using FCM for bacterial detection and live/dead discrimination. The water level variable had the strongest factor loading (0.98) and was selected for the Flood Risk Index (FRI) model, which revealed that 29.23% of the plotted data were high-risk, and 70.77% were moderate-risk. The viability pattern of live bacterial cells was more prominent during the monsoon season compared to the non-monsoon season. The live bacterial population concentration was significantly higher in the midstream (p < 0.05) during the monsoon season (p < 0.01). The flood risk patterns were successfully established based on the water level control limit. The viability of waterborne bacteria associated with the monsoon season was precisely determined using FCM. Effective flood risk management is mandatory to prevent outbreaks of waterborne diseases.

Development of convenient flood risk assessment method to community level: the case in the Deduru Oya basin in Sri Lanka

Purpose Floods have been identified as the most frequent and threatening disaster in Sri Lanka amidst an increasing trend of natural and man-made disasters in the world. Subject experts state that disaster risk management should be based on the results of risk assessments, but flood risk management in Sri Lanka is seemingly not based on community-level flood risk assessments. Accordingly, the purpose of this paper is to introduce a community-level flood risk assessment method to the local context of Sri Lanka. Design/methodology/approach The sample (n = 425) for the study was selected using the stratified random sampling method, and the Deduru Oya basin was selected as the study area. The risk assessment model introduced by Bollin et al. (2003) was used for the current study, but with some modifications. Accordingly, 16 variables were selected for the risk assessment. Descriptive data analysis methods were used in the study. Findings Community-level flood risk assessment method was introduced. Variable index, flood risk index and flood risk map were developed for the study area. The Grama Niladari Divisions (GNDs) were grouped into five categories from very high risk to very low risk. The GNDs named Wirakumandaluwa, Thimbilla, Deduru Oya, Bangadeniya and Elivitiya were ranked as the most flood-risk GNDs, respectively. Originality/value This paper produces a flood risk assessment method for the local context. Flood risk in the study area was assessed based on people’s perceptions. Accordingly, the flood risk index and flood risk map for the study area were developed based on the empirical data. GNDs were ranked based on the flood risk index.

Quantifying the flood risk index of the Malaysian “rice bowl”

Study regionSg. Kedah basin, Malaysia. Study focusThis study proposed a novel method to estimate the flood susceptibility index based on topographical conditions using Multi Criteria Decision Making approach with a specific hazard classification, to determine the paddy flood vulnerability index considering all paddy growth periods and to establish risk classification by integrating flood inundation and damage, as risk is a combination of probability and impact of an event to occur. New hydrological insightsFlood occurrences at paddy fields are not uncommon and pose a serious threat, because rice is a staple food for most Asian countries. In a tropical environment, paddy cultivation normally undergoes three growth stages, namely vegetation, reproductive and ripening. These stages have different water requirements. Therefore, it is essential to include the paddy growth stages in the risk assessment, as well as the inundated duration and depth which are unique to the specific location and the paddy seed variety. These parameters have not been investigated in previous studies. The risk indices were classified into 5 major classes, namely very low, low, moderate, high and very high. A comprehensive flood risk map developed in this study can be used by all relevant authorities and stake holders to evaluate the level of flood risk.

Flood Risk Assessment and Mapping: A Case Study from Australia’s Hawkesbury-Nepean Catchment

Floods are the most common and costliest natural disaster in Australia. Australian flood risk assessments (FRAs) are mostly conducted on relatively small scales using modelling outputs. The aim of this study was to develop a novel approach of index-based analysis using a multi-criteria decision-making (MCDM) method for FRA on a large spatial domain. The selected case study area was the Hawkesbury-Nepean Catchment (HNC) in New South Wales, which is historically one of the most flood-prone regions of Australia. The HNC’s high flood risk was made distinctly clear during recent significant flood events in 2021 and 2022. Using a MCDM method, an overall Flood Risk Index (FRI) for the HNC was calculated based on flood hazard, flood exposure, and flood vulnerability indices. Inputs for the indices were selected to ensure that they are scalable and replicable, allowing them to be applied elsewhere for future flood management plans. The results of this study demonstrate that the HNC displays high flood risk, especially on its urbanised floodplain. For the examined March 2021 flood event, the HNC was found to have over 73% (or over 15,900 km2) of its area at ‘Severe’ or ‘Extreme’ flood risk. Validating the developed FRI for correspondence to actual flooding observations during the March 2021 flood event using the Receiver Operating Characteristic (ROC) statistical test, a value of 0.803 was obtained (i.e., very good). The developed proof-of-concept methodology for flood risk assessment on a large spatial scale has the potential to be used as a framework for further index-based FRA approaches.

Combined basin-scale and decentralized flood risk assessment: a methodological approach for preliminary flood risk assessment

In this study, we focused on a combined basin-scale and decentralized (localized) approach (municipalities) to riverine flood risk mapping and assessment in the Gidra River Basin (Slovakia). The methodology applies direct spatial and probabilistic relation among the physical processes of riverine flooding with a given vulnerability. Flood hazard mapping at basin scale was based on ungauged conditions. First, we calculated the design peak discharges using the rainfall generation model and rainfall-runoff model, in particular, the Stochastic Rainfall Generator (STORAGE) and the Continuous Simulation Model for Small and Ungauged Basins (COSMO4SUB). After that, we used the obtained flood scenarios for Hydrologic Engineering Center´s River Analysis System (HEC-RAS) hydraulic modelling. The modelled flood extent, flow depth, and velocity were considered as hazard indicators. The results were expressed in terms of flood hazard (FHI), vulnerability (FVI), and risk index (FRI): the highest values were obtained for municipalities located in the northern-central part of the investigated area. The proposed methodology can constitute a conceptual basis for updating the Preliminary Flood Risk Assessment (PFRA) in Slovakia.

Development of Flood Vulnerability and Risk Indices for Kelantan District, Peninsular Malaysia

Natural hazards are inevitable which required proper monitoring and application of mitigation measures to reduce vulnerability and risk. Flood is one of the most common atural hazards in Malaysia. The present study was conducted to identify vulnerable flood zones using flood vulnerability and risk indices and to minimize flood damage by suggesting mitigation measures. Four sub-districts of the Kelantan state, Peninsular Malaysia were selected based on the availability of the data and flooding history. For this urpose, demographic, social, economic, and flood event data were collected to develop flood vulnerability and risk index. Descriptive and inferential statistics were used to analyze the results. The results revealed that developed flood vulnerability and risk indices accurately predict high-priority zones. Overall, it was found that flood risk is relatively higher in a rural area compared to an urban area.

Methodological framework for territorial planning of urban areas: Analysis of socio-economic vulnerability and risk associated with flash flood hazards

• Risk analysis from a socio-natural viewpoint optimizes territorial planning. • Flash flood characteristics were verified during fieldwork. • The Flash flood risk index includes the behavior of the process. • The socioeconomic vulnerability index integrates aspects of the people affected. • Risk index identifies attention priority areas for strengthening local strategies.

Risk Assessment of Flash Flood to Buildings Using an Indicator-Based Methodology: A Case Study of Mountainous Rural Settlements in Southwest China

In southwest China, flash floods occur frequently and often cause severe damage to residential building areas, especially in mountainous rural settlements. Risk assessment is crucial in the hazard mitigation policies and measures. However, the study on the quantitative assessment of flash flood risk for buildings is still less explored. In this study, an indicator-based assessment approach is proposed to assess the risk of buildings threatened by flash floods. The flood hazard is first simulated with 1D/2D hydrodynamic model to determine the buildings exposed to the flood and flood inundation indicators. Then, a combination of virtual surveys and building census information is used to collect information on indicators of exposed buildings and their surroundings. The indicator scores are calculated using the building flash flood risk indicator system constructed in this study which includes the flood hazard and building vulnerability indicators. A flood risk index (FRI) combining flood hazard index (FHI) and building vulnerability index (VI) is developed by weighted aggregation of indicators using combination weights calculated by the game theory approach. Based on FRI, the flash flood risk of mountainous buildings is quantitatively assessed. Taken a key mountainous rural settlement in southwest China as an example, the proposed methodological framework enables the quantitative calculation and assessment of the risk of rural buildings to flash flood. The overall framework can provide an applicable approach for flood mitigation decisions in mountainous settlements.

A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level

Floods are frequently occurring events in the Assam region due to the presence of the Brahmaputra River and the heavy monsoon period. An efficient and reliable methodology is utilized to prepare a GIS-based flood risk map for the Assam region, India. At the regional and administrative level, the flood hazard index (FHI), flood vulnerability index (FVI), and flood risk index (FRI) are developed using multi-criteria decision analysis (MCDA) – analytical hierarchy process (AHP). The selected indicators define the topographical, geological, meteorological, drainage characteristics, land use land cover, and demographical features of Assam. The results show that more than 70%, 57.37%, and 50% of the total area lie in moderate to very high FHI, FVI, and FRI classes, respectively. The proposed methodology can be applied to identify high flood risk zones and to carry out effective flood risk management and mitigation strategies in vulnerable areas.

Flood risk index development at the municipal level in Costa Rica: A methodological framework

Floods constitute one of the most damaging natural hazards in the world. Seasonal and extraordinary rainfall recurrently trigger different types of floods in Costa Rica. An integrated and efficient flood risk management requires comprehensive understanding on the flood driving variables. This study analyzes and classifies the 82 Costa Rican municipalities in terms of hazard, exposure, and vulnerability to floods. Then, an index for flood risk is designed to comprehend the risk driver’s role (hazard, exposure, and vulnerability) at a local level. The present method provides a flood risk index on a municipal scale done through a statistical validation of different sources of municipal-level data. Higher flood risk values mostly occur in municipalities located in extensive flatlands, medium to large areas in both the Pacific and Caribbean basins, as well as borderlands and coastal regions. The results can promote flood risk assessment plans in developing countries or regions where baseline information is limited. This approach has been absent in most of the national flood risk policies, specifically the plans analyzing the likelihood of short, mid, and long-term decline of risk conditions influencing flood disasters.

Development of a Method for Assessing Country-Based Flood Risk at the Global Scale

International frameworks such as the Sustainable Development Goals and the Sendai Framework for Disaster Risk Reduction 2015−2030 require the quantification of country-based flood risk. However, few approaches at the global scale include the three necessary components (hazard, exposure, and vulnerability) for determining disaster risk and are country-based assessments, owing to major challenges such as limited data availability and vulnerability proxy selection. Therefore, in this study, a method was developed with the following features: Incorporating the hazard, exposure, and vulnerability components; Applicable to the vast majority of countries in the world; Visualizing priority countries and illustrating effective measures and strategies; Clear and easy to understand by leaders and decision makers of international organizations, governments, and other stakeholders; Identifying each country’s challenges and providing guidance on specific issues for more detailed investigation and policy creation; Including more extensive factors compared with past studies. In Asia and the Pacific, the Flood Risk Index computed by the developed method is compared with the fatality ratio, and the results show that improving flood resilience secures people and society regardless of the magnitude and frequency of floods. Analysis at the global scale visualizes regional tendencies and indicates that countries closer to the equator have higher flood risk. Analysis of country-based flood risk based on five indicators demonstrates that the developed method can assist international organizations, governments, and other stakeholders to further examine country-specific conditions and establish and implement policies and strategies toward building a resilient society and achieving international targets.

Support for Decision-Making on the Resilience of Incheon Metropolitan City Using Flood Risk Assessment

Since it was recognized as a UNDRR international safety city in 2020, Incheon Metropolitan City has been promoting policies aiming to strengthen resilience strategies for the next 10 years. For the resilience assessment, a Quick Risk Estimation (QRE), which is a risk assessment tool for various disasters, can also be used to support the decision-making of experts on strengthening resilience strategies. However, QRE is unable to provide a detailed risk assessment of a specific disaster such as flood. Therefore, in this study, a flood risk assessment was performed from 2016 to 2019 using the Indicator Based Approach for the 10 cities and counties in Incheon city. The aforementioned method can also support the decision-making of experts for disaster management alongside QRE results. The flood risk assessment in this study consists of four items (hazard, exposure, vulnerability, and capacity) and 11 detailed indicators. The details for each index, item, and flood risk indices were calculated for each evaluation stage. As of 2019, the flood risk index had been calculated for Ganghwa-gun (county), Michuhol-gu (district), Jung-gu, Seo-gu, and Ongjin-gun, among others. The flood risk assessment conducted in this study is believed to be beneficial for a rational decision-making that can support the strengthening of resilience strategies by identifying changes in city- and county-specific situations and risk-exposed indicators in response to flood risks.

Flood risk index in data-scarce river basins using the AHP and GIS approach

Flood risk index in data-scarce river basins using the AHP and GIS approach

A mixed approach for urban flood prediction using Machine Learning and GIS

Extreme weather conditions, as one of many effects of climate change, is expected to increase the magnitude and frequency of environmental disasters. In parallel, urban centres are also expected to grow significantly in the next years, making necessary to implement the adequate mechanisms to tackle such threats, more specifically flooding.This project aims to develop a flood prediction system using a combination of Machine Learning classifiers along with GIS techniques to be used as an effective tool for urban management and resilience planning. This approach can establish sensible factors and risk indices for the occurrence of floods at the city level, which could be instrumental for outlining a long-term strategy for Smart Cities.The most performant Machine Learning model was a Random Forest, with a Matthew's Correlation Coefficient of 0.77 and an Accuracy of 0.96.To support and extend the capabilities of the Machine Learning model, a GIS model was developed to find areas with higher likelihood of being flooded under critical weather conditions. Therefore, hot spots were defined for the entire city given the observed flood history. The scores obtained from the Random Forest model and the Hot Spot analysis were then combined to create a flood risk index.

Flood Risk Assessment Based on Flood Hazard and Vulnerability Indexes

Abstract Within this paper, a methodology for assessing the flood risk was developed by extracting the essential factors that favor the generation of flood risk. These factors, that had a sufficient number of data for a proper comparative analysis, are: potentially affected population based on population density, total agricultural area, total built-up area and the historical maximum amount of precipitation recorded in 24 hours. The flood risk assessment is presented in the form of indices calculation for all these factors and maps generated which representing the results of the calculation of the above-mentioned factors and the results of the flood risk index calculation. Urban floods have particularities that must be presented in detail to understand the flood phenomenon, which is why this paper takes into consideration these areas. In order to determine the probability of urban floods, all disturbing factors that may affect the urban area must be taken into account. The method presented in this paper can be used in sectoral planning activities and integrated planning studies, and for damage assessment.

Flood Risk Index for Land-Use Changes: Case Study of Pakpanang River Basin

Flood Risk Index (FRI) is the multi-criteria linked with the factors of vulnerability; exposure, susceptibility, and resilience. In order to establish local FRI, crucial local information have to be accumulated. However, under the limitation of land-use data, particular techniques were applied in this study. CA Markov model was used to analyze the past missing land-use data and, also forecast the future land-use of Pakpanang river basin under conditions of plan and without plan. The ratio changes of forest, agriculture, wetland and water, and urban areas were considered. Then, the result of LULC spatial-temporal changes was then applied to Hec-HMS and Hec-Ras , with Arc GIS extension of Hec-GeoHMS and Hec-GeoRas software, in order to evaluate the flood hydrographs and flood severity in three municipalities corresponding to 100-year return period rainfall. Afterward, the FRI of Pakpanang, Chianyai, and Hua-sai, which ranges from 0 to 1, were evaluated by using the modified FRI equations. It was found that sensitivity analysis in the area of forest on flood depth and inundation areas is incoherent. Nevertheless, without land-use planning, the changes in these three cities cause higher flood risk, where Chianyai is the riskiest as the FRIE is 0.58. Further consideration of FRIE and FRIP proportion that reveals the FRI deviation indicates that to reduce flood risk, Chianyai would need the most resources and highest effort comparison to Pakpanang and Hua-sai.

A risk analysis framework for transmission towers under potential pluvial flood - LiDAR survey and geometric modelling

The failure of transmission towers often causes widespread blackouts and results in electrical shock to people and animals via water bodies especially in areas prone to river floods and storm surges. To ensure safety operation of the power networks, the structural health of transmission towers should be maintained and investigated under the potential of flood hazards. We propose a comprehensive risk assessment framework for the transmission towers affected by the pluvial flood, based on the geometry of the tower and the terrain. The geometry is first obtained from 3D point clouds derived from airborne Light Detection And Ranging (LiDAR). The framework consists of a series of new point cloud segmentation and fitting algorithms, designed to accurately estimate the inclination angles of the transmission towers. In addition, the framework includes an existing flood risk index (Topographic Control Index, TCI) and a new risk index for the transmission towers (Transmission Tower Risk Index, TTRI) which reflects the risk for tower damages under the pluvial flooding. The framework is applied to Hengman, situated on the Pearl River estuary, Southern China. Based on our results, high TTRI were shown to be often associated with high flooding risk. This coincides with our hypothesis that the floods weaken foundation settlements and thus trigger tower inclinations. The TTRI and TCI analyses reveal that 8 towers out of ~60 in total are with low-risk (13.8%); 2 with medium-risk (3.5%) and 1 tower is at high-risk. The total area affected by the risk tower is ~2.7 km2, accounting for 5.5% of the study area. The results suggested that the proposed framework is implementable and reliable. The resultant analysis can help decision makers to pinpoint the affected transmission towers along with the peripheral affected areas for precaution.

Operational Flood Risk Index Mapping for Disaster Risk Reduction Using Earth Observations and Cloud Computing Technologies: A Case Study on Myanmar

People, livelihoods, and infrastructure in Myanmar suffer from devastating monsoonal flooding on a frequent basis. Quick and effective management of flood risk relies on planning and preparedness to ensure the availability of supplies, shelters and emergency response personnel. The mandated government agency Department of Disaster Management (DDM) as well as local and international organizations play roles in producing, disseminating, and using accurate and timely information on flood risk. Currently, systematic flood risk maps are lacking, which leaves DDM to rely on inconsistent historic reports and local knowledge to inform their emergency planning. Although these types of knowledge are critical, they can be complemented to reduce bias and human error to planning processes and decisions. As such, the present situation has led to ineffective distribution of emergency response resources prior to flooding, leaving vulnerable populations less-than-prepared for inevitable flood events. Given these issues, we have developed a flood risk decision-support tool in collaboration with DDM. The tool uses surface water maps developed by the Joint Research Center (JRC), which were derived from more than 30 years of Landsat imagery. We have also incorporated population data, land cover data, and other information on flood exposure and vulnerability to create the first scalable and replicable Flood Risk Index (FRI) for flood risk reduction in Myanmar.

Calculation of Flood Risk Index for Yesilirmak Basin-Turkey

Flood risk, in the sense of damage that a ‘flood event’ can cause, was globally indexed and quantified to show the relationship between various natural and social factors. The Pressure and Release (PAR) model consisting of five key indexes; hazard, exposure, vulnerability, capacity soft countermeasures, and capacity hard countermeasures along with the entropy method was used to measure the uncertainty in information gathered. In this study, flood risk index was calculated for Yesilirmak Basin of Turkey based on PAR. The basin is one of the coastal watersheds of Turkey experiencing frequent flood events.
 Damage data covering years from 2000 to 2015 have been obtained from the Ministry of Agriculture and Forestry for Turkey. Candidate data for hazard, vulnerability, counter-measures and exposure were collected in accordance with temporal and spatial scales, and the collected data were compiled on a watershed basis. When grouping the sub-indicators, AWDO (Asian Water Development Outlook) was used and selected from a group of parameters covering a wide range of characteristics such as economy, health, vegetation, population, river according to their global presence, and data consistency. As long-term data accessibility was highly limited under basin conditions, data was obtained from relatively more reliable global sources such as United Nations’ databases on which data has been collected annually. The correlation among the collected parameter values was calculated based on the amount of damage that had occurred, and data with high correlation was included in the index account. Parameters that were not screened were rather weighted by using the entropy method and their effect on flood damage were determined. The calculated flood risk index based on PAR model was named as Yesilirmak Basin Flood Risk Index (Y-FRI).
 The resulting Y-FRI radar charts indicated that the most important variation occurred for the soft countermeasure index. In addition, the five main indices and the flood risk index was positively correlated with hazard, exposure and vulnerability indices, while negatively correlated with the countermeasures. This study showed that not only the hazard parameters directly contribute to flood formation, but also the vulnerability, exposure and countermeasure parameters that reflected the conditions of the region where the flood occurred have quantitatively influenced the flood damage.

Assessing flood risk using analytical hierarchy process (AHP) and geographical information system (GIS): application in Coochbehar district of West Bengal, India

Floods are recurrent events in the floodplains of Coochbehar district inundating and damaging considerable quantities of standing crops and hampering the livelihoods of thousands of peoples. This paper addresses an efficient and reliable methodology for preparing flood risk map for the Coochbehar district based on two essential concepts of hazard and vulnerability. With the aid of analytical hierarchy process, a variety of hazard and vulnerability defining criteria have been weighted according to their contributions and were further processed in the geographical information system environment to observe and assess spatial characters of flood hazard index (FHI) and flood vulnerability index (FVI) that collectively have defined the flood risk index (FRI). Accordingly, the eastern, southeastern, southern, central and north-central parts of the district are prone to frequent floods while vulnerability levels are higher at areas locating particularly along the India-Bangladesh international border in the south, southeast and southwest and in some isolated clusters in the central and north-central parts. The influences of these FHI and FVI in shaping the FRI distribution were observed to be varying at places. The Tufanganj subdivision is found to be the least safe administrative unit followed by the Coochbehar Sadar, Mathabhanga and Dinhata subdivisions. The rest, i.e., the Mekliganj subdivision is observed to be relatively safe but is not immune at all. The flood risk distribution yielded the information of 58 (4.91%) settlements with higher FRI scores followed by 145 (12.29%) villages/towns with moderate and 456 (38.64%) villages/towns under low flooding risks.