Flood Risk Index Research Articles

Developing a flood risk assessment model with genetic algorithm-based weights

To reduce flood risk efficiently within constrained disaster prevention budgets, governments employ economic analyses and qualitative flood risk assessments. However, conventional methods, such as entropy weight and the Analytic Hierarchy Process method, have limitations in terms of the accuracy of the flood risk index. Here, we overcome these limitations by applying a genetic algorithm (GA) – an optimization method mimicking a natural selection process and biological genetic evolution. We developed a new flood risk index by using GA to calculate weights to indicators associated with four items (Hazard, Exposure, Vulnerability, and Capacity) for 161 Korean cities and counties from 2016 to 2021. The indicators (number of buildings, farmland area, dependent population, etc.) for the Exposure and Vulnerability items were reflected in the evaluation only for damaged targets directly exposed to flood risk, using grid cells of indicators overlaid on the flood risk map. Our GA-based method aimed to optimize each indicator’s weights to minimize errors between damage rankings and flood risk index rankings. Results show that our method reduced errors by 21.42 % during 2016–2021, outperforming traditional methods. Therefore, it is easy to identify municipalities that lack disaster prevention capabilities and are vulnerable to flood risk by comparing flood risk indices under the same conditions, such as maximum rainfall index. Our proposed method could better aid local government in decision-making for flood risk mitigation by allocating constrained budgets efficiently.

Flood Susceptibility and Risk Mapping of Kathmandu Valley Watershed, Nepal

Comprehensive flood risk assessment is often constrained by a lack of appropriate data in high-altitude watersheds, particularly in developing countries like Nepal, where institutional capacities are limited for mapping and monitoring flood-prone communities. This study, one of the first of its kind, produced spatial multi-criteria-based flood susceptibility, vulnerability, and risk index maps for the Kathmandu Valley (KV) watershed in Nepal using an Analytical Hierarchy Process (AHP) approach and Geographical Information System (GIS). The result shows that most parts of the KV (around 80%) have moderate to low flood susceptibility around the watershed but susceptibility is prominent in southern areas. Highly flood-susceptible regions (about 14%) are found mainly along the riverbanks. Flood vulnerability, primarily influenced by population density and literacy rate, is moderate to low in most areas of the watershed (around 86%), predominantly higher in the central urban areas, and gradually lower towards the edge of the watershed. Flood risks in the major portion of the watershed (around 72%), mainly in the southern and eastern parts, are estimated as moderate to low risk, whereas higher risk zones are found in the central urban areas. The high contrast in flood vulnerability scores across the watershed has mainly contributed to the variation of flood risk zones, as flood susceptibility scores are fairly distributed over the watershed. The study findings will help policymakers develop location-specific sustainable flood risk management strategies for the flood-vulnerable communities in the KV watershed.

A comprehensive approach for assessing social flood vulnerability and social flood risk: The case of Denmark

Flood risk assessment approaches have traditionally been dominated by measures of economic damage. However, the importance of understanding the social impacts of flooding are increasingly being acknowledged. Social vulnerability indices have been constructed in diverse geographical contexts to understand relative susceptibility of different social groups to flood hazards. However, integrated assessments of social vulnerability, exposure, and hazard information are lacking. Here, we construct a national social vulnerability index (SVI) for Denmark and combine this with direct and indirect social exposure data and coastal flood hazard data to construct a national social flood risk index (SFRI). Results show the spatial distribution of social flood vulnerability and social flood risk in Denmark. Our findings illustrate that including social data in flood risk assessment could significantly change our understanding of flood risk on a national scale. Methodologically, our work introduces a comprehensive flood risk modelling approach that explicitly considers the social impacts of flooding in all model components. The application of this model in Denmark reveals that the social impacts of flooding extend far beyond flooded areas, thus highlighting the importance of explicitly considering direct and indirect social exposure in addition to social vulnerability in flood risk assessment. By introducing a comprehensive, socially specific approach to flood risk assessment that is usable within existing risk management frameworks such as the EU Floods Directive, our work aims to mainstream social wellbeing, resilience, and justice as central considerations in decision making on flood risk management.

Flood risk assessment in Kogi State Nigeria through the integration of hazard and vulnerability factors

Annually, Kogi State in Nigeria experiences significant flooding events, leading to serious fatalities, the destruction of livelihoods, and damage to vital infrastructure. This study presents a multi-faceted approach and methodology to generate a state-wide flood risk map by analyzing both flood vulnerability and flood hazard factors. Seven flood hazard factors (drainage length, distance to river, elevation, slope, rainfall, distance from confluence/dam area, and geomorphology) and vulnerability factors (population density, female population, land cover, road length, distance from hospitals, literacy rate, and employment rate) were ranked and weighted based on their contributions to flooding within the state using the Fuzzy Analytical Hierarchy Process (FAHP). From these, the Flood Hazard Index (FHI), Flood Vulnerability Index (FVI), and Flood Risk Index (FRI) were derived. Results showed that Kabba, Idah, Olamabor, Kotonkar, and the southern part of Ajaokuta LGAs exhibit high flood vulnerability due to dense populations, remoteness from roads and critical infrastructure, and considerable distances from healthcare facilities. Likewise, LGAs exhibiting a very high FHI occur along the geographic zones bounded by the confluence of the Niger and Benue rivers, specifically along the Lokoja area, and the Kotonkar, Kogi, Bassa, and Ibaji LGAs. Five flood risk classes—very low, low, moderate, high, and very high FRI classes—occupy 26.82, 31.12, 22.07, 15.26, and 4.71% of the area, respectively. Out of 295 villages, 65 villages are spread across the high flood risk zone. The safest LGAs include Ankpa, Omala, Dekina, Ijumu, Kabba, and Mopa-Muro LGAs.

Evaluation of potentially susceptible flooding areas leveraging geospatial technology with multicriteria decision analysis in Edo State, Nigeria

Floods have claimed lives and devastated societal and ecological systems. Because of their catastrophic tendency and the financial and fatalities they cause, floods have become more and more significant on a global scale in recent years. In Edo State, Nigeria, flooding is a frequent threat that happens annually and seriously damages both lives and property. While the potential of flooding cannot entirely be eliminated, geospatial-based technologies can greatly lessen its effects. In Nigeria's flood-prone Edo State, the study's objectives are to identify inundated places and provide nuanced mapping of the flood risk. To facilitate the determination of the flood risk index (FRI), the study's fundamental flood-predictive features were determined by taking into consideration elevation, slope, distance from the river, rainfall intensity, land use/land cover, soil texture, topographic roughness index, topographic wetness index, normalized difference vegetation index (NDVI), runoff coefficient, aspect, drainage capacity, flow accumulation, the sediment transport index, and the stream power index. The significance of each predictive factor in the analytic hierarchy procedure (AHP) was determined by gathering expert views and perspectives from public entities. A flood threat map was created by processing the gathered data using the AHP and the ArcGIS 10.5 framework. The multicollinearity (MC) estimation was applied to assess the model's predictability. The results of the FRI showed that there were high and extremely severe flood risk zones that affected roughly 26 and 9% of the area, respectively. Flood risks have been identified as predominant in the Edo south region of the study area, which is characterized by low elevation and slope, high drainage capacity, distance from the river, topographic wetness, and index. It showed that the model's resultant vulnerability to flooding maps agreed with past flood occurrences that were previously experienced in the research area, demonstrating the technique's efficacy in locating and mapping locations plagued by flooding. Linear regression (R2) analysis was further conducted on the FRI to evaluate the scientific reliability of the utilized methodology; this shows 0.816 (81.6%) dependability. Consequently, frequent and long-lasting implementation of flooding predictions, warning systems, and mitigation strategies may be achieved.

Flood hazard analysis in Mumbai using geospatial and multi-criteria decision-making techniques

ABSTRACT Flood risk assessment remains a crucial element, particularly within locations highly susceptible to repeated flood occurrences. This study seeks to conduct an elaborate flood risk analysis for Mumbai, India based on an integrated method of geographic information systems and analytic hierarchy process (AHP). In this study, land use/land cover, average annual rainfall, elevation, drainage density, normalized difference vegetation index, distance from rivers as well as distance from roads are identified and considered. For this reason, the expert survey utilizes the AHP weights so as to find out the significance of these factors towards flooding danger. Investigations show a flood risk index and a corresponding map for Mumbai, where all areas are divided into risk zones very low to very high. Very high risks are particularly situated along rivers. Such details offer critical knowledge to policymakers who will undertake informed emergency preparedness measures designed to shield Mumbai's citizens and assets. Therefore, this research is considered as one of the modern techniques for flood risk assessment, which can be applied in other flood-affected areas worldwide.

Planning scale flood risk assessment and prediction in ultra-high density urban environments: The case of Hong Kong

Climate change has significantly increased the risks associated with urban flooding. However, most research on flood risk assessment focuses on large-scale climate changes and impacts, leaving a research gap in the high spatial resolution of flood risk assessment in inter-urban areas. This gap makes it difficult to guide regional planning for the government. Therefore, this study aims to explore the risks of floods in ultra-high-density cities under climate change at the planning scale, using Hong Kong as a case study. We comprehensively assessed the flood risk index (FRI) in the built environment in 211 tertiary planning units (TPUs) from the three dimensions of vulnerability, exposure, and hazard from 2006 to 2021. We also employed a prediction model to forecast the spatial–temporal patterns of FRI in the next 5, 10, and 15 years and evaluated the uneven distribution of flood risks. The results show that the FRI of TPUs increased yearly, which poses higher threats to agglomerative areas of transportation and functional facilities. Additionally, future FRI will further impact coastal TPUs in western Hong Kong, resulting in more negative impacts on high-building areas. Therefore, urban planning should prioritize integrating flood management and risk mitigation measures.

Integrated GIS and analytic hierarchy process for flood risk assessment in the Dades Wadi watershed (Central High Atlas, Morocco)

Flood risk assessment is crucial for delineating flood hazard zones and formulating effective mitigation strategies. Employing a multi-criteria decision support system, this study focused on assessing a Flood Risk Index (FHI) at the Dades Wadi watershed scale. Seven main flood-causing criteria were broadly selected, namely flow accumulation, distance from hydrographic network, drainage network density, land use, slope, rainfall, and permeability. The relative importance of each criterion prioritized as per their contribution toward flood risk, which were employed a blend of the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS)/Remote Sensing (RS) techniques. The significance of each criterion was determined based on their contribution to flood hazard, and their relative importance was established through an AHP pair-wise comparison matrix. The efficacy of the AHP model was performed with a consistency ratio of 0.08, which indicated that each flood criterion weight is confirmed. Among the flood-causing criteria, the hydrologic flow accumulation factor was identified as the most influential (weight: 3.11), while permeability exhibited the least prominence (weight: 0.58). Approximately 40.36% of the total area, equivalent to around 1319, 89 km2, was concentrated within very high flood-risk zones situated near rivers. In contrast, an area of approximately 399,943 km2 (56.33%) exhibited a low to very low flood risk zone. The validation of the FHI map encompassed the application of the Receiver Operating Characteristic Curve (ROC) technique, revealing an Area Under the Curve (AUC) of 85%.

Flood risk index mapping in data scarce region by considering GIS and MCDA (FRI mapping in data scarce region by considering GIS and MCDA)

Flood risk index mapping in data scarce region by considering GIS and MCDA (FRI mapping in data scarce region by considering GIS and MCDA)

Synergizing flood risk and road network dynamics for optimized evacuation strategies

In response to escalating climatic threats, this research innovatively integrates flood risk assessment with road network dynamics to formulate optimized evacuation strategies in flood-susceptible regions. Employing a path-based traffic model and flood risk index, our method significantly decreases travel durations by 25% and vehicle hours by 20% compared to traditional frameworks. Complexities arise in intricate evacuation systems. Zone 4 was a critical node due to a 15% rise in vehicular inflow and unique flood risks, emphasizing the necessity for tailored evacuation plans considering variable traffic and flood risks. Our approach enhanced evacuation efficiency and also resulted in a 10% increase in fuel consumption while highlighting areas for further optimization. This study proposes a refined, sustainable evacuation model that harmonizes flood risks and traffic dynamics and offers insights for resilient urban development amid climatic uncertainties.

National Flood Risk Index in climate change scenarios

National Flood Risk Index in climate change scenarios

National flood risk index in climate change scenarios

National flood risk index in climate change scenarios

MAPEAMENTO DE ÍNDICE DE RISCO DE INUNDAÇÃO DE ÁREA A JUSANTE DE UMA BARRAGEM EM CASO DE ROMPIMENTO

We aimed to evaluate the flood risk index due to the hypothetical break of the São Bento dam (SC, Brazil). The risk index was obtained by combining the hazard and vulnerability indices. The hazard index was obtained by multiplying the velocity by the depth of the water, simulated with HEC-RAS 2D. The simulated flood extent was 64.8 km², with a maximum flow of 3586.60 m³·s-1, a depth of up to 2.0 m, and a velocity of up to 2.0 m·s-1 in most of the area. The formation of the breach occurred in 2.85 h, and the peak flow occurred at 1.67 h. The volume that overflowed with the break was 44.75 hm³. The flood wave reached 22.0 km in length, where the municipality of Forquilhinha is located. The risk index map showed that the risk is high up to 6 km from the dam since most people were at least 60 years old and had low incomes. In this location, the people were not safe inside buildings because they had a high probability of being destroyed. Thus, risk mapping may be adopted as a preventive measure to assist in preparing an emergency action plan and serve for environmental education and territorial planning. Keywords: Dam Break; HEC-RAS 2D; Risk Mapping.

Flood risk assessment of the naeseongcheon stream basin, Korea using the grid-based flood risk index

Study RegionNaeseongcheon Stream Basin, Korea Study focusWe conducted a flood risk assessment using grid data for each indicator and a flood risk map. Using a grid-based flood risk map, grid data for the nine indicators included in the Hazard, Exposure, and Vulnerability items from 2016 to 2020 were selected and indexed by scoring each quantile interval. The entropy weight and Euclidean distance were then applied to calculate the grid-based item indices and flood risk index. Finally, the Expected Annual Damage (EAD) ranking calculated using the Korean flood risk assessment model was compared with the flood risk assessment ranking using grid data for 17 sub-basins in the Naeseongcheon Stream Basin for 2018. New hydrological insights for the regionThe analysis showed that the absolute error was improved by the application of the flood damage rate and selection of the grid cells including damage targets. When comparing the flood risk assessment ranking of each of the 17 sub-basins with the EAD ranking, the mean absolute error was 1.882, and the root mean square error was 3.009. This confirms that qualitative flood risk assessment using grid data and flood risk maps can provide as much basin-level risk analysis as quantitative flood risk assessment. Therefore, the method presented in this study can be utilized as a useful decision-support tool for the government’s basin-level disaster prevention projects.

Flood inundation assessment of UNESCO World Heritage Sites using remote sensing and spatial metrics in Hoi An City, Vietnam

Flooding is the most frequent and damaging threat to The United Nations Educational, Scientific, and Cultural Organization (UNESCO) World Heritage Sites, and has been exacerbated by climate change. Hoi An Ancient Town, one of the world's cultural heritage sites in Vietnam, is facing inundation risks from increasing extreme flood events due to anthropogenic and natural processes. This study combines Geospatial Information System (GIS), remote sensing data, and landscape ecology metrics to assess the flood risk of Hoi An City. The analysis includes (1) classification of land-use/land-cover (LULC) using Sentinel-2 data; (2) computation of a flood risk index using hazard characteristics, physical and demographic exposures, and physical and socioeconomic vulnerabilities, together with adaptive capacity and spatial metrics, and the Fuzzy-Analytic Hierarchy Process (AHP) method to determine the weight of each index and ranking; and (3) determination of flood risks for the UNESCO World Heritage Sites of Hoi An City and the surrounding areas. By comparing model outputs with historical flood locations (N = 330), the study finds that >75% of past floods occurred at high or very high-risk areas forecasted by the model. Results from the model verified by true flood incidents show that the inundation hotspots are concentrated in the city's heritage sites, where human and climate changes have impacted landscape structure. The flood inundation risk mapping obtained from the synthesis analysis, encompasses hazard, exposure, and vulnerability, offering holistic knowledge to help reduce and manage flood risks at Hoi An World Heritage Sites. This method can be applicable to other sites with similar characteristics.

Flood risk assessment using an indicator based approach combined with flood risk maps and grid data

The increasing frequency of tropical cyclones, such as typhoons and localized heavy rainfall, increases the risk of flood damage in urban areas around the world. Countries implementing flood prevention projects use qualitative risk assessments, such as flood risk assessments, to support decision-making. However, existing flood risk assessment methods are not able to select and reflect only the damage targets that are directly exposed to flood risk. In addition, existing indexing methods are limited in improving the skewness of the raw data distribution, which distorts the calculated flood risk index. This study conducted a flood risk assessment based on an indicator-based approach using flood risk maps and grid data utilizing indicators (buildings, road area, etc.) from 2016 to 2019 for 44 cities and counties in the Gyeongsang-do Province. The flood risk assessment in this study consists of four items (Hazard, Exposure, Vulnerability, and Capacity) and nine indicators. Instead of using statistical data, we used the overlapped grids with the flood risk map for Exposure and Vulnerability indicators to reflect the flood risk exposed targets in the risk assessment. The limitations of existing indexing methods, such as min–max normalization, were improved by dividing the distribution into ten quantiles and scoring each quantile interval when indexing the indicators. Finally, entropy weights and Euclidean distance were applied to calculate the annual flood risk index of 44 cities and counties. The annual flood risk indices for local governments were arranged in descending order and then, the rankings of flood damage amount in 2019 were compared with the calculated index rankings. The sum and mean of absolute errors were 386 and 9.897, and the root mean square error was calculated as 11.930, which showed an improvement over the existing method. Using the calculated indices, it is possible to create Hazard vs. Capacity graph, Exposure vs. Vulnerability graph, or annual flood risk index graph. These graphs can be utilized to understand the level of exposure to flood risk of local governments and to assess the level of response through the Capacity index that contributes to damage reduction. It is believed that the flood risk assessment method presented in this study not only accurately identify the flood risk for local governments but can also be used to support decision-making processes to strengthen the government’s disaster prevention capabilities.

Employing a local framework and GIS to evaluate the flood risk index maps of Makassar City, Indonesia

Employing a local framework and GIS to evaluate the flood risk index maps of Makassar City, Indonesia

Urban flood risk assessment under rapid urbanization in Zhengzhou City, China

With accelerated urbanization and climate change, urban flooding is becoming more and more serious. Flood risk assessment is an important task for flood management, so it is crucial to map the spatial and temporal distribution of flood risk. This paper proposed an urban flood risk assessment method that takes into account the influences of hazard, vulnerability, and exposure, by constructing a multi-index urban flood risk assessment framework based on Geographic Information System (GIS). To determine the weight values of urban flood risk index factors, we used the analytic hierarchy process (AHP). Also, we plotted the temporal and spatial distribution maps of flood risk in Zhengzhou City in 2000, 2005, 2010, 2015, and 2020. The analysis results showed that, the proportion of very high and high flood risk zone in Zhengzhou City was 1.362%, 5.270%, 4.936%, 12.151%, and 24.236% in 2000, 2005, 2010, 2015, and 2020, respectively. It is observed that the area of high flood risk zones in Zhengzhou City showed a trend of increasing and expanding, of which Dengfeng City, Xinzheng City, Xinmi City, and Zhongmu County had the fastest growth rate and the most obvious increase. The flood risk of Zhengzhou City has been expanding with the development of urbanization. The method is adapted to Zhengzhou City and will have good adaptability in other research areas, and its risk assessment results can provide a scientific reference for urban flood management personnel. In the future, the accuracy of flood risk assessment can be further improved by promoting the accuracy of basic data and reasonably determining the weight values of index factors. The risk zoning map can better reflect the risk distribution and provide a scientific basis for early warning of flood prevention and drainage.

Proactive intervention of green infrastructure on flood regulation and mitigation service based on landscape pattern

Green infrastructure (GI) could reduce surface runoff and provide essential ecosystem service (ES) in flood management. More frequent flooding necessitated GI intervention to promote flood regulation and mitigation service. This study presented the Supply-Demand-Intervention framework of ES for flood mitigation in Nanjing, and aimed to explore flood interventions of GI that improve ES supply and satisfy ES demand from the perspective of landscape pattern. This study quantified ES supply by runoff reduction capacity and assessed ES demand by flood risk index, respectively. Stepwise regression analysis revealed the association between landscape pattern and ES supply and demand. We found the mismatch between ES supply and demand in Nanjing, as well as the spatial heterogeneity between ES supply and demand during various design storms. Urban central areas showed the low ES supply, high ES demand and high priority rank of intervention. Current GI conditions had the difficulty in dealing with more severe floods in Nanjing. And landscape elongation, shape, fragmentation, and segmentation were found to have significant effect on ES supply and demand. More elongated and segmented landscape, with less continuity and connectedness, could promote ES supply, while less fragmentated landscape, with complex shape, could reduce ES demand. Different intervention strategies were proposed to adapt to different areas for promoting ES delivered by GI. In Gulou and Qinhuai district, it was suggested to apply well-shaped elongated cropland and water areas to segment and disperse the built-up land. These findings could provide critical implications for reasonable GI planning and management in flood mitigation and adaption.

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.