Flood Risk Management Research Articles

A Novel Modeling Approach to Quantify the Flood Resilience of Cities

In recent years, large-scale flood events have occurred more frequently, and the concept of resilience has become a prevalent approach to managing flood risk in many regions. This has led to an increased interest in how to effectively measure a city’s flood resilience levels. This study proposes a novel modeling approach to quantify urban flood resilience by developing D-number theory and analytical hierarchy process (AHP) models, which are applied to three cities in China using the VIse Kriterijumski Optimizacioni Racun (VIKOR) method. The findings reveal that Hefei City has the most effective level of flood resilience, Hangzhou City was ranked second, while Zhengzhou City has the least effective level of flood resilience. This study provides a new scientific basis on how to quantify flood resilience at the city scale and provides a useful reference for these three specific cities. The methods and approaches developed in this study have the potential to be applied to other cities and in the related aspects of disaster prevention, recovery, and reconstruction.

Advanced floodplain mapping: HEC-RAS and ArcGIS pro application on Swat River

AbstractFloods stand out as one of the most devastating environmental threats worldwide resulting in the tragic loss of human lives and significant damage to our essential infrastructure. This study focuses on creating floodplain maps for the two important reaches of Swat River in the Khyber Pakhtunkhwa Province of Pakistan, namely, Kalam–Khwazakhela and Khwazakhela–Chakdara reaches. The Advanced Land Observing Satellite Phased Array Type L-band Synthetic Aperture Radar (ALOS PALSAR) 12.5 m Digital Elevation Model (DEM) data has been used for this purpose. Furthermore, the sensitivity of the flood model was assessed for the Flood 2022 event, considering simulated flood depth, extent, and velocity in relation to various terrains derived from the 12.5-m ALOS PALSAR data. To estimate extreme flows for different return periods (2, 5, 10, 25, 50, and 100 years), the Log Normal (LN), Log Pearson III (LP3), and Generalized Extreme Value (GEV) distributions were employed for the frequency analysis. The GEV distribution turned out to be the best fit for modeling the Swat River for both the Chakdara and Khwazakhela gauge stations. To predict flood levels for the peak floods identified through frequency analysis and for the specific return periods the Hydrologic Engineering Center's River Analysis System (HEC-RAS) 2D simulations were performed. Subsequently the outcomes of this model were used to create floodplain maps using Geographic Information System Professional (ArcGIS Pro) software customized for various return periods. The analysis revealed a linear increase in flood inundation area with longer return periods. The floodplain maps developed hold significant importance for the governing authorities of the Swat region. These maps serve as essential tools for implementing proactive measures against potential infrastructure damage, thereby protecting against economic losses and enhancing public safety. This research effectively combines hydrological modeling and geospatial technology offering practical solutions for managing flood risks. It serves as a valuable guide for making well-informed decisions and promoting sustainable development in flood-prone areas.

Unveiling flood vulnerability in the Vietnamese Mekong Delta: A case study of an Giang province

Flood risk management is a critical concern worldwide, as communities and regions face increasing threats of flooding due to climate change, urbanization, and natural variability. As a headwater province of the Vietnamese Mekong Delta, An Giang is considered the most vulnerable to the impacts of floods. We thus applied a flood assessment framework that combines natural disaster (floods), economic, social, environmental factors with a set of 42 criteria in terms of hazard, exposure, and vulnerability. The Analytic Hierarchy Process method was used to weight these criteria before flood risk maps were made to assess their scales. Our results revealed that Khanh An and Long Binh communes, primarily located in An Phu District at the border between Vietnam and Cambodia, are at the highest hazard levels with scores of 0.68. Tinh Bien District where is relatively far from An Phu, although not heavily inundated, has a high level of vulnerability. Overall, 10 out of the 155 communes in the province (6.5%) were at high flood risk since these communes, mostly located in An Phu, have predominantly agricultural areas with a relatively poor population. In addition, 121 communes (78%) demonstrated a moderate flood risk level while the rest (15.5%) is very low or not at any risk. Mitigation measures should be developed to reduce flood risk across the province within the VMD context while this study sheds light to worldwide deltas on developing similar methods for flood risk management.

Identifying proactive and reactive policy entrepreneurs in collaborative networks in flood risk management

A policy entrepreneur is a distinct political actor aiming to affect change. The theoretical narrative regarding policy entrepreneurs is underpinned by their commitment to a policy solution, the multi-dimensional strategies they use to promote that solution, and a suite of attributes and skills facilitating their actions. Policy entrepreneurs reveal themselves through their attempts to transform policy ideas into policy innovations and, hence, disrupt status quo policy arrangements. Indeed, policy entrepreneurs share sensibilities with entrepreneurs in the market, whose conceptualisation serves as a heuristic for their counterparts in policy and politics. The emphasis on change borne out of innovative solutions distinguishes policy entrepreneurs from many other actors who aim to maintain current institutional settings and power relations. The growing scholarship on policy entrepreneurship assumes intentionality as inherent to the policy entrepreneur and their actions, foregrounding the image of the tenacious political actor set on steering their a priori pet policy to a suitable problem. This article draws from the market theory on entrepreneurship, contrasting proactive policy entrepreneurship (entrepreneurship by opportunity) and reactive policy entrepreneurship (entrepreneurship by necessity). We conduct a comparative social network analysis of three municipalities in southern Sweden focused on flood risk mitigation. We demonstrate two different logics of policy entrepreneurship (as a result of seizing opportunities versus as a reaction to vertical pressure), and we explore the consequences for enhancing our understanding of policy entrepreneurship.

Deep learning for automated trash screen blockage detection using cameras: Actionable information for flood risk management

ABSTRACT Trash screens are used to prevent debris from entering critical parts of rivers. However, debris can accumulate on the screen and generate floods. This makes their monitoring critical both for maintenance and flood modeling purposes (e.g., local forecasts may change because the trash screen is blocked). We developed three novel deep learning methods for trash screen maintenance management consisting of automatically detecting trash screen blockage using cameras: a method based on image classification, a method based on image similarity matching, and a method based on anomaly detection. To facilitate their use by end users, these methods are designed so that they can be directly applied to any new trash screen camera installed by the end users. We have built a new dataset of labeled trash screen images to train and evaluate the efficiency of our methods, in terms of both accuracy and implications for end users. This dataset consists of 80,452 trash screen images from 54 cameras installed by the Environment Agency (UK). This work demonstrates that trash screen blockage detection can be automated using trash screen cameras and deep learning, which could have an impact on both trash screen management and flood modeling.

Gendered flood risk perception and mental health of urban households in Ghana: Insights from the Oforikrom municipality

It is important to understand gendered impacts of flood risks on mental health in developing countries. This study examines the gender-differentiated impacts of flood risk on the mental health of households in Ghana. Utilizing a mixed-methods approach, we collected data through questionnaire survey and in-depth interviews. Descriptive statistics and Student's t-test were used to analyze the data. The study revealed that both male and female headed households in the communities had experienced floods and associated impacts. However, flood risk perceptions of households were gender differentiated. The independent samples t-test result shows that the difference between male and female households' perceived mental health impacts of flooding are not significantly different. The impacts, include increased stress, anxiety, depression, and post-traumatic stress symptoms. Additionally, the results show divergent coping strategies, with male headed households preferring temporal relocation and female headed households seeking support from family and friends. Further distinctions emerged in adaptation strategies, as male headed households constructed floodwalls, while female headed households opted for desilting drainage systems. The findings have theoretical and practical implications for flood risk management in urban Ghana and other developing countries, especially in sub-Saharan Africa.

Tracking the spatial footprints of extreme storm surges around the coastline of the UK and Ireland

Storm surges are the most important driver of flooding in many coastal areas. Understanding the spatial extent of storm surge events has important financial and practical implications for flood risk management, reinsurance, infrastructure reliability and emergency response. In this paper, we apply a new tracking algorithm to a high-resolution surge hindcast (CODEC, 1980–2017) to characterize the spatial dependence and temporal evolution of extreme surge events along the coastline of the UK and Ireland. We quantify the severity of each spatial event based on its footprint extremity to select and rank the collection of events. Several surge footprint types are obtained based on the most impacted coastal stretch from each particular event, and these are linked to the driving storm tracks. Using the collection of the extreme surge events, we assess the spatial distribution and interannual variability of the duration, size, severity, and type. We find that the northeast coastline is most impacted by the longest and largest storm surge events, while the English Channel experiences the shortest and smallest storm surge events. The interannual variability indicates that the winter seasons of 1989-90 and 2013–14 were the most serious in terms of the number of events and their severity, based on the return period along the affected coastlines. The most extreme surge event and the highest number of events occurred in the winter season 1989–90, while the proportion of events with larger severities was higher during the winter season 2013–14. This new spatial analysis approach of surge extremes allows us to distinguish several categories of spatial footprints of events around the UK/Ireland coast and link these to distinct storm tracks. The spatial dependence structures detected can improve multivariate statistical methods which are crucial inputs to coastal flooding assessments.

Geospatial analysis of flood risk hazard in Zambezi Region, Namibia

The recent decade has seen an increase in frequency and intensity of flood risk globally especially in less developed countries. This has been attributed to many factors such as population growth, urbanization, climate change, increasing precipitation, and poor solid waste management among others. This study used quantitative analysis to identify and characterise flood-prone areas in Kabbe and Kaltima in the Zambezi region. We estimated major factors influencing flood events in the study area. We estimated this by incorporating the analytical hierarchy process (AHP) and GIS-based multi-criteria decision-making to map and identify flood-prone areas in Kabbe and Katima. AHP was employed to ascertain the weight of each criterion taken into consideration for the susceptibility mapping. We analysed ten factors elevation, slope, distance to river, rainfall, topographic wetness index, distance to road, drainage density, land use land cover, modified soil adjusted vegetation index, and soil which are closely associated with flood occurrence in the study area. The flood factors maps were categorized into five susceptibility levels. We used field data by interviewing key informants and community members to validate the GIS analysis. The result from the flood susceptibility map indicates that 46 % of areas in Kaltima and Kabbe have a low susceptibility to flood, 56.04 % are moderate, 43.33 % are high and 17 % are very highly susceptible to flood. The areas susceptible to flooding are mostly low-laying areas in Kabbe which are gentle slopes and are sitting at approximately 921–935 m below sea level. Speaking with stakeholders in the area, they confirmed that communities such as Ihaha, Isize, Mbalasinte, and Kalumnesa are highly susceptible to flooding. The community members confirm that they experience flooding every year with devastating impacts on their lives and livelihoods. We recommend localized flood management strategies that cater to the needs of the communities and develop strategies to improve preparedness, response, and mitigation. Increasing government funding for flood risk management in the area can increase the capacity of the community for flood risk management through training and awareness

Utilizing the HEC-HMS Model for Hydrological Modelling of the Rambiara Watershed: Rainfall and Runoff Estimation

Abstract: Hydrological modelling and flood prediction are essential components of the Rambiara watershed's water resource management. To improve disaster preparedness and reduce the danger of flooding in the area, the effectiveness of the HEC HMS model in flood forecasting must be assessed. In this study, various techniques for estimating rainfall are examined, and a customized hydrological model tailored to the hydrological complexities of the Rambiara watershed is developed. The goal of this project is to provide practical insights for better flood risk reduction and water resource management through the integration of cutting-edge modelling tools and rigorous analysis. This work advances our knowledge of watershed dynamics and provides guidance for sustainable water resource planning projects in the Rambiara watershed and beyond by thoroughly examining precipitation patterns and hydrological processes. In addition, the research takes into account a number of factors related to flood behaviour, such as determining places that are vulnerable to flooding, analysing the size of floods, and estimating how frequently they occur. By taking a holistic approach, it is possible to gain a thorough understanding of the dynamics of flooding in the Rambiara watershed, which paves the way for the development of efficient flood risk management techniques. This study looks into the temporal and spatial variability of rainfall in the Rambiara watershed in addition to research on floods. Through the comparison of several methods for estimating rainfall, including deterministic and geostatistical approaches, the study offers valuable insights into the precision and dependability of rainfall data, which are essential for hydrological modelling and flood forecasting. The hydrological processes of the Rambiara watershed can be more accurately represented by creating a bespoke hydrological model with the HEC HMS program. Informed decision-making and proactive flood risk reduction strategies are made possible by the study's model calibration and validation, which guarantee the model's dependability in simulating runoff and forecasting flood events. Overall, this study advances our knowledge of flood dynamics in the Rambiara watershed and advances hydrological modelling tools. The goal of this study is to promote sustainability and resilience in the face of hydrological hazards by offering practical insights for managing water resources and reducing the danger of flooding.

Flood Routing and Dam Breach Parameter Calculation on Sepaku Semoi Dam

Flood Routing and Dam Breach Parameter Calculation on Sepaku Semoi Dam

Unveiling Torrential Flood Dynamics: A Comprehensive Study of Spatio-Temporal Patterns in the Šumadija Region, Serbia

This paper presents a comprehensive analysis of flood frequency and a spatio-temporal characterization of historical torrential floods in the Šumadija region using water discharge datasets and documented events. A chronology of 344 recorded torrential flood events, spanning from 1929 to 2020, illustrates the region’s vulnerability, with a death toll exceeding 43. The study defines the intra-annual primary and secondary peaks of torrential flood occurrences and explains their spatial distribution. Furthermore, the identification of suitable probability distribution functions underscores the necessity of tailored approaches for effective flood risk management in this diverse geographical environment. The study employed Flood Frequency Analysis (FFA) and goodness-of-fit tests, including the Kolmogorov–Smirnov (K-S) and Cramér–von Mises (CvM) tests, to assess the frequency and magnitude of flood events and evaluate diverse distribution functions. The main results include the identification of suitable probability distribution functions for each river within the region, emphasizing the need for tailored approaches in flood risk management. Additionally, discharge values for various return periods offer crucial insights for informed decision-making in flood risk management and infrastructure planning.

Reevaluating the benefit of flood risk management for flood-prone livelihoods

As flood risk is projected to increase, effective flood risk management (FRM) is crucial not only for mitigating direct flood damage but also for contributing to the long-term improvement of livelihoods and hence the socioeconomic development of flood-prone areas in developing countries. While many studies have assessed avoided damage as the benefit of flood countermeasures, few recognize the impact on improvements in livelihood resulting from risk reduction. We present a novel framework that captures the dynamic relationship between decreasing flood risk perception and improvements in household livelihoods. Using the case of flood-prone Bago, Myanmar, we apply this framework to evaluate 127 flood management strategies under different assumptions of future climate change and socioeconomic features. We show that the benefits of improved livelihoods, when quantified alongside avoided flood losses, have a significant impact enough to change the cost-efficiency rankings of flood management strategies. The findings highlight the importance of incorporating livelihood improvements into FRM decision making to promote the sustainable development in flood-prone areas.

Development of Green Disaster Management Toolkit to Achieve Carbon Neutrality Goals in Flood Risk Management

Current flood risk management projects have been criticized for their high carbon emissions, raising the need for carbon emission reduction and carbon absorption efforts to mitigate environmental impacts and achieve carbon neutrality goals. The research develops a comprehensive green disaster risk management toolkit to calculate the carbon emissions and absorption quantitatively based on the unit volume of materials and processes employed in a flood risk management project. As a result of applying the developed toolkit to a about 22,300 small stream restoration projects in Korea, the total carbon emissions were estimated to be 1,158,840.7 tons of CO2, of which 89.4% of the total carbon emissions originated from concrete-related construction activities, such as cement and ready-mixed concrete pouring. As a result of evaluating the nationwide carbon absorption results of all small stream restoration projects, total absorption by 2030 is expected to be 3.0 to 10.2 times higher than carbon emissions. The comprehensive toolkits are expected to support the selection of customized processes, materials, and methods by providing a systematic approach to calculate and minimize carbon emissions, ultimately contributing to the achievement of carbon neutrality goals in flood risk management projects.

A cost-benefit ‘source-receptor’ framework for implementation of Blue-Green flood risk management

As floods are a major and growing source of risk in urban areas, there is a necessity to improve flood risk management frameworks and civil protection through planning interventions that modify surface flow pathways and introduce storage. Despite the complexity of densely urbanised areas (topography, buildings, green spaces, roads), modern flood models can represent urban features and flow characteristics in order to help researchers, local authorities, and insurance companies to develop and improve efficient flood risk frameworks to achieve resilience in cities. A cost-benefit driven ‘source-receptor’ flood risk framework is developed in this study to identify (1) locations contributing to surface flooding (sources), (2) buildings and locations at high flood risk (receptors), (3) the cost-benefit nexus between the ‘source’ and the ‘receptor’, and finally (4) ways to mitigate flooding at the ‘receptor’ by adding Blue-Green Infrastructure (BGI) in critical locations. The analysis is based on five steps to identify the ‘source’ and the ‘receptor’ in a study area based on the flood exposure of buildings, damages arising from flooding and available green spaces with the best potential to add sustainable and resilient solutions to reduce flooding. The framework was developed using the detailed hydrodynamic model CityCAT in a case study of the city centre of Newcastle upon Tyne, UK. The novelty of this analysis is that firstly, multiple storm magnitudes (i.e. small and large floods) are used combined with a method to locate the areas and the buildings at flood risk and a prioritized set of best places to add interventions upstream and downstream. Secondly, planning decisions are informed by considering the benefit from reduced damages to properties and the cost to construct resilient BGI options rather than a restricted hydraulic analysis considering only flood depths and storages in isolation from real world economics.

Decision trees in cost–benefit analysis for flood risk management plans

ABSTRACT According to the European Directive 2007/60/CE, flood risk evaluation should include a cost–benefit analysis (CBA) on a long-term time horizon to evaluate the impact of mitigation measures. The standard CBA assumes to know in advance the events observed in the time horizon and a priori compares all mitigation measures by an economic metric. No change is supposed to be made to these measures throughout the time horizon. This modus operandi is not appropriate in the domain of flood risk management because several conditions are uncertain when the CBA is made (e.g., urban policies). This article faces these challenges by the integration of cost–benefit analysis and decision trees, to prescribe mitigation measures under uncertainty on the budget for mitigation actions because their funding can be modified after the conclusion of the CBA. The former integration is discussed in the real case of the lowland valley of the Coghinas River (Sardinia, Italy), for which the classical CBA compared five mitigation measures of infrastructural works. The integration into the decision tree also allows evaluation of mitigation measures with changes in infrastructural works and a lamination action. The outcomes advise decreasing the maximum storage level and increase the peak lamination.

Flood Risk Assessment for an Irrigation Project in Odissa, India

Objectives: Flood risk assessment is a fundamental aspect of disaster management, particularly in regions heavily reliant on irrigation infrastructure for agriculture. This study employs advanced hydrological and hydraulic modeling techniques to evaluate flood risk for the Lower Suktel region in Odisha, India. Methods: The methodology integrates Intensity-Duration-Frequency (IDF) curves, Isopluvial maps, and the Hydrologic Engineering Center-River Analysis System (HEC-RAS) to comprehensively analyze flood risk and its implications. Findings: IDF curves further reveal that the design rainfall intensity for a one-hour duration with a 100-year return period is 152 mm/h, aiding in characterizing rainfall intensity for specific return periods. Model simulation identifies the pump house's susceptibility to flooding, with maximum flood depths ranging from 0 to 2 meters. These findings underscore the significance of employing advanced modeling techniques and Isopluvial maps for precise flood risk assessment. Novelty: The novelty of this paper lies in its pioneering effort to introduce a comprehensive flood risk assessment in an area where it has not been previously conducted. The integration of advanced modeling techniques and spatial analysis tools contributes to the novelty of the research, making it a valuable and innovative contribution to the field of flood risk management. Understanding extreme rainfall events, hydraulic behavior, and potential flood depths is imperative for developing effective flood mitigation strategies. Keywords: Flood risk assessment, Irrigation infrastructure, IDF curves, Hydrological modeling, Hydraulic modeling, GIS

A policy instruments palette for spatial quality: lessons from Dutch flood risk management

ABSTRACT Worldwide, more integrated and spatially embedded forms of flood risk management have been advocated. In the Netherlands, this ‘spatial turn’ can be associated with a quest for spatial quality, i.e. making use of existing landscape values to create more liveable, aesthetic and sustainable flood risk management solutions. Reflecting on Dutch flood risk management practice, this paper inventorizes which policy instruments are currently used to strengthen spatial quality, and how involved actors view these instruments. We present empirical insights on common concerns, standpoints and dilemmas from the Dutch Flood Protection Programme (DFPP), a large-scale reinforcement operation to climate-proof the Netherlands’ main flood defences by 2050. Spatial quality here remains a rather ambiguous policy objective, lacking a legally binding framework. Using the NATO-policy instruments’ typology as a starting point, and based on a co-learning process between science and practice, we present an instruments palette that can be used to strengthen spatial quality in flood risk management. Our findings reveal that the DFPP makes use of rather ‘soft’ policy instruments. The actual achievement of spatial quality goals seems to depend largely on the combined project team competencies, guidance and support provided by responsible water authorities, and commitment of other project partners.

Effects of high-quality elevation data and explanatory variables on the accuracy of flood inundation mapping via Height Above Nearest Drainage

Abstract. Given the availability of high-quality and high-spatial-resolution digital elevation maps (DEMs) from the United States Geological Survey's 3D Elevation Program (3DEP), derived mostly from light detection and ranging (lidar) sensors, we examined the effects of these DEMs at various spatial resolutions on the quality of flood inundation map (FIM) extents derived from a terrain index known as Height Above Nearest Drainage (HAND). We found that using these DEMs improved the quality of resulting FIM extents at around 80 % of the catchments analyzed when compared to using DEMs from the National Hydrography Dataset Plus High Resolution (NHDPlusHR) program. Additionally, we varied the spatial resolution of the 3DEP DEMs at 3, 5, 10, 15, and 20 m (meters), and the results showed no significant overall effect on FIM extent quality across resolutions. However, further analysis at coarser resolutions of 60 and 90 m revealed a significant degradation in FIM skill, highlighting the limitations of using extremely coarse-resolution DEMs. Our experiments demonstrated a significant burden in terms of the computational time required to produce HAND and related data at finer resolutions. We fit a multiple linear regression model to help explain catchment-scale variations in the four metrics employed and found that the lack of reservoir flooding or inundation upstream of river retention systems was a significant factor in our analysis. For validation, we used Interagency Flood Risk Management (InFRM) Base Level Engineering (BLE)-produced FIM extents and streamflows at the 100- and 500-year event magnitudes in a sub-region in eastern Texas.

Overcoming barriers to integrate more justice into climate change policies. Lessons from adaptation policies and flood risk management in Flanders and France

The paper aims to improve the general and practical understanding of justice in climate change policies, both in terms of how policymakers integrate justice elements in political intentions and policy implementation. The paper is based on social scientific and qualitative research on justice in climate change policies, with a focus on both the study of climate adaptation policies and, more concretely, the study of flood risk management. The main objective is to identify obstacles to the definition and implementation of justice in policies. The article offers a cross-national analysis of the issue of justice in Flanders and France, between 2000 and 2020, of the issue of justice in climate adaptation policies, with a particular focus on flood management. Based on policy documents’ analysis, the study helps to clarify barriers to pragmatically embed justice in policies’ decision making, at the formulation stage through four cross-cutting issues: leadership, resources, information and values.

Advancing Flood Risk Assessment through Integrated Hazard Mapping: A Google Earth Engine-Based Approach for Comprehensive Scientific Analysis and Decision Support

This study utilises a comprehensive, multi-layered approach to assess flooding susceptibility in a specific area, integrating diverse environmental datasets such as JRC Global Surface Water, Landsat 8 images, and SRTM elevation data. Employing the GEE FMA, a powerful tool leveraging Google Earth Engine capabilities, the analysis covers water occurrence, permanent water, elevation, distance to water, topographic hazard score, and vegetation indices (NDVI and NDWI). The Water Occurrence layer establishes a foundational understanding of water-body distribution’s correlation with flood vulnerability, while Permanent Water refines this understanding. Distance to Water measures proximity for targeted risk evaluation, and Elevation identifies vulnerable regions based on topography. The GEE FMA synthesises these layers into a Flood Hazard Susceptibility map, categorising vulnerability into Very Low, Low, Medium, High, and Very High. This nuanced understanding is crucial for prioritising interventions. The GEE FMA’s rapid processing speed makes it an invaluable tool for short-term decision support in flood hazard disaster management, offering insights for informed decision-making and resilient infrastructure development. The Topographic Hazard Score provides information on how topography influences flood risk, while the Wetness Hazard Score categorises moisture conditions for identifying flood-prone locations. Decision-makers rely on these values for quick and precise flood susceptibility assessments. In an era of climate uncertainties and urbanisation, the GEE FMA emerges as a reliable tool for decision-making, mitigating flood impacts, and developing effective flood risk management strategies.