Flood damage and loss estimation Research Papers (original) (raw)

2025, Research Article

Malaysia, particularly Pahang, experiences devastating floods annually, causing significant damage. The objective of the research was to create a flood susceptibility map for the designated area by employing an Ensemble Machine Learning (EML) algorithm based on geographic information system (GIS). By analyzing nine key factors from a geospatial database, flood susceptibility map was created with the ArcGIS software (ESRI ArcGIS Pro v3.0.1 x64). The Random Forest (RF) model was employed in this study to categorize the study area into distinct flood susceptibility classes. The Feature selection (FS) method was used to ranking the flood influencing factors. To validate the flood susceptibility models, standard statistical measures and the Area Under the Curve (AUC) were employed. The FS ranking demonstrated that the primary attributes to flooding in the study region are rainfall and elevation, with slope, geology, curvature, flow accumulation, flow direction, distance from the river, and land use/land cover (LULC) patterns ranking subsequently. The categories of 'very high' and 'high' class collectively made up 37.1% and 26.3% of the total area, respectively. The flood vulnerability assessment of Pahang found that the Eastern, Southern, and central regions were at high risk of flooding due to intense precipitation, low-lying topography with steep inclines, proximity to the shoreline and rivers, and abundant flooded vegetation, crops, urban areas, bare ground, and rangeland. Conversely, areas with dense tree canopies or forests were less susceptible to flooding in this research area. The ROC analysis demonstrated strong performance on the validation datasets, with an AUC value of >0.73 and accuracy scores exceeding 0.71. Research on flood susceptibility mapping can enhance risk reduction strategies and improve flood management in vulnerable areas. Technological advancements and expertise provide opportunities for more sophisticated methods, leading to better prepared and resilient communities.

2025, Climate

Flood risk mapping is spreading in the Global South due to the availability of high-resolution/high-frequency satellite imagery, volunteered geographic information, and hydraulic models. However, these maps are increasingly generated without the participation of exposed communities, contrary to the Sendai Framework for Disaster Risk Reduction 2015-2030 priorities. As a result, the understanding of risk is limited. This study aims to map flood risk with citizen science complemented by hydrology, geomatics, and spatial planning. The Niger River floods of 2024–2025 on a 113 km2 ar-ea upstream of Niamey are investigated. The novelty of the work is the integration of local and technical knowledge in the micro-mapping of risk in a large area. We con-sider risk the product of a hazard and damage in monetary terms. Focus groups in flooded municipalities, interviews with irrigation perimeter managers, and statistical river flow and rainfall analysis identified the hazard. The flood plain was extracted from Sentinel-2 images using MNDWI and validated with ground control points. Six classes of assets were identified by visual photo interpretation of very high-resolution satellite imagery. Damage was ascertained through interviews with a sample of farmers. Floods of 2024–2025 may occur again in the next 12–19 years. Farmers cannot crop safer sites, raising significant environmental justice issues. Damage depends on the strength of the levees, the crop, and the season. From January to February, horticulture is at a higher risk. Flooding does not bring benefits. Risk maps highlight hot spots, are validated, and can be linked to observed flood levels.

2024, Springer Nature

Long-term flood loss archieve data synthesis and spatial mapping

2024, Environmental Science & Policy

Flooding is the most common natural disaster in Europe. Modern flood risk management relies not only infrastructure development but also on governmental and non-governmental actors applying legal, economic and communicative water management instruments. Within the European Union (EU), flood management closely relies on policy set at the EU and national levels. It is now recognized that a sound understanding of climate change is required in addition to current management by taking into account land use change and socio-political context, as climate and land use changes have major impacts on hydrological responses. This paper investigates the hydrological behavior due to urbanization under current and future climate scenarios of high summer and high winter rainfall for 20 sub-catchments of the Schijn River, located in the Flanders region near Antwerp, Belgium. As urbanization increases and existing rainfall-runoff models neglecting the specific behavior of urban runoff, a hydrological model was developed based on a basic reservoir concept and applied to the existing rainfall-runoff model (PDM) flow to examine the specific urban contribution. Results revealed that peak flow for urban runoff and the total peak flow (i.e. rural and urban runoff) were significantly higher (i.e. ranges from 200% to 500%) than the existing rainfall-runoff model (PDM) flows, because of faster and more peaked urban runoff response. The impact of climate change on current and future conditions was also assessed by estimating peak flows with respect to return periods from the flood frequency curve. The predicted peak flow of high summer future climate scenario was significantly higher (i.e. ranges from 200% to 250%) than that of the current climatic condition for this region. Furthermore, hourly peak flow and daily volume ratios of 100-year return period for the highest, lowest and average impervious area were projected for the time horizon of the year 2100. It is concluded that climate change impacts contribute the most in producing peak flow in coming years, while increased urbanization takes the second place for both hourly and daily values. Results on urbanization effect and climate change impact assessment are useful to the water managers for spatial planning, emergency planning and insurance industry.

2023, Journal of Water Resources Planning and Management

Floods in both riverine and coastal zones can cause significant damage to infrastructure, including possible structural failure of buildings. Methodologies commonly used to estimate flood damage to buildings are typically based on aftermath surveys and statistical analyses of insurance claims data. These methodologies rarely account for flooding hydrodynamics, and thus do not differentiate between the damage caused by floodwater contact and those caused by floodwater velocity. A new stochastic methodology has been developed to estimate the direct impact of flood actions on buildings and to determine the expected damage. Building vulnerability is modeled based on analytical representations of the failure mechanisms of individual building components. The flood actions generated during different flooding events are assessed and compared to the resistance of each building component. The assessed flood actions include: hydrostatic and hydrodynamic forces, waves, turbulent bores, debris impacts, and time-dependent local soil scour. Monte Carlo simulation was used to synthetically expand the available building data, to perform load-resistance analysis, and to account for the uncertainty of input parameters. The primary result from this study is the expected flood damage to individual buildings, and it is expressed as a threedimensional functions dependent on both floodwater depth and floodwater velocity. The results show how floodwater velocity can increase the magnitude of the flood damage outcome compared to those that solely consider water depth. This demonstrates the real need for considering floodwater hydrodynamics in the vulnerability assessment of buildings located in flood prone areas. Although the present study focuses on the vulnerability of reinforced concrete frame buildings with infill concrete-block walls, the methodology can also be applied to other types of structures. This methodology could serve as a decision-making tool to assist engineers and emergency management agencies to identify zones of high risk, and to implement the necessary preventive measures and mitigation strategies to minimize the adverse impact of potential flooding events.

2023, Natural Hazards and Earth System Sciences

2023, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Knowledge of surface albedo at individual roof scale is important for mitigating urban heat islands and understanding urban climate change. This study presents a method for quantifying surface albedo of individual roofs in a complex urban area using the integration of Landsat 8 and airborne LiDAR data. First, individual roofs were extracted from airborne LiDAR data and orthophotos using optimized segmentation and supervised object based image analysis (OBIA). Support vector machine (SVM) was used as a classifier in OBIA process for extracting individual roofs. The user-defined parameters required in SVM classifier were selected using v-fold cross validation method. After that, surface albedo was calculated for each individual roof from Landsat images. Finally, thematic maps of mean surface albedo of individual roofs were generated in GIS and the results were discussed. Results showed that the study area is covered by 35% of buildings varying in roofing material types and conditions. The calculated surface albedo of buildings ranged from 0.16 to 0.65 in the study area. More importantly, the results indicated that the types and conditions of roofing materials significantly effect on the mean value of surface albedo. Mean albedo of new concrete, old concrete, new steel, and old steel were found to be equal to 0.38, 0.26, 0.51, and 0.44 respectively. Replacing old roofing materials with new ones should highly prioritized.

2023

One of the key challenges for risk, vulnerability and resilience research is how to address the role of risk perceptions and how perceptions influence behaviour. It remains unclear why people fail to act adaptively to reduce future losses, even when there is ever-richer information available on natural and human-made hazards (flood, drought, etc.). The current fragmentation of the field makes it an uphill battle to cross-validate the results of existing independent case studies. This, in turn, hinders comparability and transferability across scales and contexts and hampers recommendations for policy and risk management. To improve the ability of researchers in the field to work together and build cumulative knowledge, we question whether we could agree on (1) a common list of minimal requirements to compare studies, (2) shared criteria to address context-specific aspects of countries and regions, and (3) a selection of questions allowing for comparability and long-term monitoring. To map current research practices and move in this direction, we conducted an international survey-the Risk Perception and Behaviour

2023, Engineering Structures

This paper presents a methodology to develop hurricane induced coastal flood vulnerability functions for residential construction based on empirical tsunami fragility functions. A force equivalency mapping procedure first transforms the tsunami fragility functions into coastal flood fragility functions. Following the quantification of the damage states and the incorporation of repair costs, the coastal flood fragility functions translate into coastal flood vulnerability functions. Insurance claims data from the National Flood Insurance Program and vulnerability functions independently derived by the US Army Corps of Engineers are employed to validate single-story on-grade timber and reinforced masonry structure model outputs. The limitations of the model and future developments are discussed.

2023

In urban areas, topography data without above ground objects are typically preferred in wide-area flood simulation, but are not yet available for many locations globally. Highresolution satellite photogrammetry DEMs, like ArcticDEM, are now emerging and could prove extremely useful for global urban flood modelling, however approaches to generate bareearth DEMs from them have not yet been fully investigated. In this paper, we test the use of two morphological filters (Simple Morphological Filter-SMRF and Progressive Morphological Filter-PMF) to remove surface artefacts from ArcticDEM using the city of Helsinki (192 km 2) as a case study. The optimal filter is selected and used to generate a bare-earth version of ArcticDEM. Using a LIDAR DTM as a benchmark, the elevation error and flooding simulation performance for a pluvial event were then evaluated at 2 m and 10 m spatial resolution, respectively. The SMRF was found to be more effective at removing artefacts than PMF over a broad parameter range. For the optimal ArcticDEM-SMRF the elevation RMSE was reduced by up to 70% over the uncorrected DEM, achieving a final value of 1.02 m. The simulated water depth error was reduced to 0.3 m, which is comparable to typical model errors using LIDAR DTM data. This paper indicates that the SMRF can be directly applied to generate a bare-earth version of ArcticDEM in urban environments, although caution should be exercised for areas with densely packed buildings or vegetation. The results imply that where LIDAR DTMs do not exist, widely available high-resolution satellite photogrammetry DEMs could be used instead. For wide-area flood simulation in urban areas, a bare-earth DEM (i.e., a terrain model without surface artefacts) is preferable in most circumstances to a Digital Surface Model (DSM) which includes them. This is because the decision to include above terrain artefacts or not is a consequence of the selected simulation resolution. Only when the simulation is conducted at grid sizes allowing the resolution of building shapes and the street layout (typically < 5 m in most urban topologies worldwide) does a DSM become useful. When aggregated to coarser resolutions, the height of the surface artefacts contained in the DSM can block or alter flow pathways in ways that lead to anomalous results when these data are used in hydrodynamic modelling (Neal et al., 2009). Inundation simulations over regional and national scales usually only become feasible with non-building resolving grid resolutions because of the exponentially increased computational cost of running fine grid models and the limited availability of national DEMs with resolutions finer than 5 m. Even at city and sub-city scales, non-building resolving models may be preferable for ensemble and event set simulations (Mason et al., 2007; Schubert and Sanders, 2012). As a result, bare-earth DEMs (also known as Digital Terrain Models or DTMs) are essential for flood inundation simulations in urban areas and can also be beneficial to a broad range of other research fields. Unlike traditional, ground-based field survey, modern wide-area DEM collection techniques rely on remote sensing from ground vehicle, airborne and satellite platforms. All DEMs derived in this way include the heights of built-up area artefacts and vegetation to some extent and require significant post-processing to obtain a bare-earth DEM. Commonly used DEMs are collected using techniques including Interferometric Synthetic Aperture Radar (i.e., InSAR), optical stereo mapping and LIDAR. These different techniques, combined with the platforms and the specific instrument characteristics, offer DEMs with varied coverage, resolution, and accuracy (Lakshmi and Yarrakula, 2018; Zaidi et al., 2018). For example, spaceborne and globally available InSAR DEMs offer wide coverage but they are constrained by the geometry of the interferometric baseline and the temporal sampling of the spaceborne platform and InSAR technique. The derived DEMs therefore have limited horizontal resolution and accuracy (SRTM at ~30 m spatial resolution has reported mean absolute vertical error of 6 m, TanDEM-X at ~12 m spatial resolution has 90% linear error (i.e., LE90) in the vertical of around 2 m) (Rodriguez et al., 2006; Wessel et al., 2018). Such vertical errors are significant compared to the amplitude of most river flood waves, which typically range from 1-2 m up to ~12 m for the Amazon River at Manaus in Brazil (Trigg et al., 2009; Bates et al., 2013). Whilst global InSAR DEM errors can be reduced by intelligent processing (O'Loughlin et al., 2016;

2023, American Journal of Environmental Sciences

The paper describes a study conducted in 2021-2022 in the Shire River Basin (SRB) of Chikwawa District, Malawi to evaluate how flood forecasting is currently performed and to provide recommendations for improvement. Flooding often occurs in the basin, endangering people's lives and property. A case in point is the 2015 flood and 2019 Tropical Cyclone Idai, which were so devastating that Malawi required international assistance. This showed that the Flood Forecasting System (FFS) in the basin has not been as robust as needed to adequately warn and prepare communities before the flood occurrence. For this purpose, a study was conducted in four Traditional Authorities (T/As) of Chikwawa District, namely Mlilima, Kasisi, Makhuwira and Lundu. Individual and group interviews were conducted with 114 residents and government officials, and a survey of 270 households was conducted by 5 research assistants. Several types of research methods were used: (1) Case study (2019 flood), (2) Phenomenological (live experiences of local people), and (3) Quantitative analysis (by users of the FFS). The results showed that a sophisticated Indigenous Flood Forecasting System (IFFS) exists in the SRB to improve both flood detection and early warning systems, however, it is not used by the Malawian government officials tasked with Flood Forecasting (FF). Based on these findings, we recommend the development and implementation of a new "Integrated Flood Forecasting System" in the Shire River Basin, which combines both scientific and indigenous FFS to combat flood impacts.

2023, E3S Web of Conferences

The flood hazard/risk maps do not allow a non-expert audience an immediate perception of the flooding impacts. Therefore, we need to modernize maps providing new communication approaches. In this context, 3-D representations of flood inundation through emerging formats in virtual and augmented realities may be considered as a powerful tool to engage users with flood hazards. The challenge of the research is to create a virtual 3-D environment aimed at supporting the public, practitioners and decision-makers in interpreting and understanding the impact of simulated flood hazards. For this purpose, the paper aims to perform a comparative analysis of two techniques to carry out the 3-D realistic visualizations of a flood map for representing a potential flooding of the Crati River, in the old town of Cosenza (South of Italy). The first approach develops a simple and quick workflow that provides an overall look at a neighbourhood level, but reveals some limits in water level visualizati...

2023, Resources

The provision of detailed information on the impact of potential fluvial floods on urban population health, quantifying the impact magnitude and supplying the location of areas of the highest risk to human health, is an important step towards (a) improvement of sustainable measures to minimise the impact of floods, e.g., by including flood risk as a design parameter for urban planning, and (b) increase public awareness of flood risks. The three new measures of the impact of floods on the urban population have been proposed, considering both deterministic and stochastic aspects. The impact was determined in relation to the building’s function, the number of residents, the probability of flood occurrence and the likely floodwater inundation level. The building capacity concept was introduced to model population data at the building level. Its proposed estimation method, an offshoot of the volumetric method, has proved to be successful in the challenging study area, characterised by a ...

2023, Journal of Applied Geospatial Information

Flood is one of the most frequently occurring natural disasters in Indonesia. At the end of 2017, Tropical Cyclones Cempaka and Dahlia formed over the Indian Ocean, inducing extreme rains and floods in some parts of Java Island. The Special Region of Yogyakarta was among the most affected areas, especially along the Oyo River section in Imogiri District. This research was designed to identify and map the flood-prone areas in the district as part of flood mitigation measures. For this purpose, The Unmanned Aerial Vehicle (UAV) technology was used to not only provide a detailed and up-to-date description but also produce aerial photographs (orthoimages) and Digital Elevation Model (DEM). These two products were inputted to the inundation modeling developed with a geomorphic approach and simulated in a Geographic Information System (GIS). In terms of accuracy, the resulting models were quite reliable for mapping on a detailed scale and only slightly deviated from the traced inundation ...

2023

2023, Remote Sensing

With natural disasters continuing to become more prevalent in recent years, the need for effective disaster management efforts becomes even more critical. Specifically, flooding is an extremely common natural disaster which can cause significant damage to homes and other property. In this article, we look at an area in Hurley, Virginia which suffered a significant flood event in August 2021. A drone is used to capture aerial imagery of the area and reconstructed to produce 3-dimensional models, Digital Elevation Models, and stitched orthophotos for flood modeling and damage assessment. Pre-flood Digital Elevation Models and available weather data are used to perform simulations of the flood event using HEC-RAS software. These were validated with measured water height values and found to be very accurate. After this validation, simulations are performed using the Digital Elevation Models collected after the flood and we found that a similar rainfall event on the new terrain would cau...

2023, International Journal of Disaster Risk Reduction

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 major 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 various stakeholders.

2023, Natural Hazards and Earth System Sciences Discussions

2023, ISPRS International Journal of Geo-Information

Timely mapping of flooded areas is critical to several emergency management tasks including response and recovery activities. In fact, flood crisis maps embed key information for an effective response to the natural disaster by delineating its spatial extent and impact. Crisis mapping is usually carried out by leveraging data provided by satellite or airborne optical and radar sensors. However, the processing of these kinds of data demands experienced visual interpretation in order to achieve reliable results. Furthermore, the availability of in situ observations is crucial for the production and validation of crisis maps. In this context, a frontier challenge consists in the use of Volunteered Geographic Information (VGI) as a complementary in situ data source. This paper proposes a procedure for flood mapping that integrates VGI and optical satellite imagery while requiring limited user intervention. The procedure relies on the classification of multispectral images by exploiting ...

2023

Flood damage assessment is crucial to address the challenges of climate and socioeconomic changes. Researchers and practitioners have developed several damage models to tackle local and regional situations. Particularly for direct damages to the residential sector, these models rely on numerous hypothesis (e.g. zero damage threshold) and parameters (e.g. recovery costs) assumed to fit specific local conditions and available data. Thus, transferability of damage models and reliability of observed losses have become key topics in the debate.This work aims at understanding the behaviour of different residential building damage models through their application to a case study in order to compare assumptions, estimated exposure values and losses. The research work is designed as a "blind" exercise where different research groups make a damage assessment starting from the same building dataset. Nine models are applied to estimate exposure and damage at the single-building scale. The results are compared in terms of exposure values, total damage and individual building damage. Although damage models differ in assumptions and parameters, the application highlights a good correlation among models in terms of exposure and relative damage, while correlation with monetary damage recorded in claims is low.

2023, Journal of Flood Risk Management

In flood risk management, the choice of vulnerability functions has a remarkable impact on the overall uncertainty of modelling flood damage. The spatial transferability of empirical vulnerability functions is limited, leading to the need for computation and validation of region-specific vulnerability functions. In data-scarce regions however, this option is not feasible. In contrast, the physical processes of flood impact model chains can be developed in these regions because of the availability of global datasets. Here we evaluated the implementation of a synthetic vulnerability function into a flood impact model. The function bases on expert heuristics on a targeted sample of representative buildings (targeted heuristics). We applied the vulnerability function in a meso-scale river basin and evaluated the new function by comparing the resulting flood damage with the damage computed by other approaches, (1) an ensemble of vulnerability functions available from the literature, (2) an individual vulnerability function calibrated with region-specific data, and (3) the vulnerability function used in flood risk management by the Swiss government. The results show that targeted heuristics can be a valuable alternative for developing flood impact models in regions without any data or only few data on flood damage.

2023, Water

Beside the flood hazard analysis, a comprehensive flood risk assessment requires the analysis of the exposure of values at risk and their vulnerability. Currently, the main focus of such analysis is on losses on building structure. However, loss on household contents accounts for up to 30% of the total losses on buildings due to floods. Based on insurance claim records, we developed and (cross-)validated two functions. The models based on linear regressions estimate the monetary loss and the degree of loss of household contents by the monetary and degree of loss for building structure, respectively. The main focus herein is to develop functions which provide robustness in prediction and transferability to other regions. Both models generate appropriate results with a comparative advantage of the relative over the absolute loss model. Our results indicate that the ratio of household content to building structure loss is decreasing relatively in regions with comparatively high losses ...

2023, MethodsX

Flood risk assessments in the Global South have increased since the adoption of the United Nations Sendai Framework for Disaster Risk Reduction 2015-2030. However, they often fail to meet disaster risk reduction needs at the local scale, because they typically consider only one hazard (fluvial or pluvial floods). Furthermore, hazard and exposure are considered as stationary conditions, flood-prone assets are rarely identified, risk reduction measures are not identified in detail for specific locations, and the convenience of reducing or accepting risk is not evaluated. This paper describes a flood risk assessment method that is innovative in that it considers three hazard types (backwater, fluvial, and pluvial floods) and multiple risk scenarios; it uses orthophotos generated from images captured by an unmanned aerial vehicle and very high-resolution satellite images, and it involves communities in risk assessment. The method was applied to four rural settlements along the Sirba River, Niger. The assessment identifies the benefit of reducing risk in monetary terms, as well as the intangible benefits that reducing risk could generate, and it detects opportunities that flooding offers for rural development. The method can be replicated in all contexts where decision-making support is needed for flood risk assessment planning. • Risk analysis and evaluation is participatory. • Risk assessment is improved by combining local and technical knowledge. • Assets are identified using very-high-resolution satellite and drone images.

2022, Physics and Chemistry of the Earth, Parts A/B/C

The study area, Fogera-Dera Floodplain, has experienced frequent flooding events in the past several decades related to the topography of the region, mainly during the rainy season. In this study, Four Sentinel-1A Synthetic Aperture Radar (SAR) data was utilized to detect, map, and analyze flood water inundations in the 2020 extreme wet season. Besides this, HEC-RAS 2D (Hydrologic Engineering Center-River Analysis System) hydrodynamic model was utilized for result validation and comparison. Doing so, Sentinel-1A VV polarized SAR data sets were selected, and histogram-based thresholding method was applied to extract flood and non-flood inundated areas. The result showed that flood inundated area was about 32.02 km 2

2022, Natural Hazards and Earth System Sciences

The vulnerability of flood-prone areas is determined by the susceptibility of the exposed assets to the hazard. It is a crucial component in risk assessment studies, both for climate change adaptation and disaster risk reduction. In this study, we analyse patterns of vulnerability for the residential sector in a frequently hit urban area of Milan, Italy. The conceptual foundation for a quantitative assessment of the structural dimensions of vulnerability is based on the modified source-pathway-receptor-consequence model. This conceptual model is used to improve the parameterization of the flood risk analysis, describing (i) hazard scenario definitions performed by hydraulic modelling based on past event data (source estimation) and morphological features and land-use evaluation (pathway estimation) and (ii) the exposure and vulnerability assessment which consists of recognizing elements potentially at risk (receptor estimation) and event losses (consequence estimation). We characterized flood hazard intensity on the basis of variability in water depth during a recent event and spatial exposure also as a function of a building's surroundings and buildings' intrinsic characteristics as a determinant vulnerability indicator of the elements at risk. In this sense the use of a geographic scale sufficient to depict spatial differences in vulnerability allowed us to identify structural vulnerability patterns to inform depth-damage curves and calculate potential losses from mesoscale (land-use level) to microscale (building level). Results produces accurate estimates of the flood characteristics, with mean error in flood depth estimation in the range 0.2-0.3 m and provide a basis to obtain site-specific damage curves and damage mapping. Findings show that the nature of flood pathways varies spatially, is influenced by landscape characteristics and alters vulnerability spatial distribution and hazard propagation. At the mesoscale, the "continuous urban fabric" Urban Atlas 2018 land-use class with the occurrence of at least 80 % of soil sealing shows higher absolute damage values. At microscale, evidence demonstrated that even events with moderate magnitude in terms of flood depth in a complex urbanized area may cause more damage than one would expect.

2022, WITPress

In recent years, floods in Germany have caused billions of Euros in property damage. As part of the project 'Innovative Vulnerability and Risk Assessment of Urban Areas Against Flood Events' (INNOVARU), a realistic, practical model for the monetary assessment of potential flood damage to residential building stock was developed, which also allows the prognosis of structural damage. The structural damage can be predicted in the form of mean damage grades using vulnerability functions, which take into account the vulnerability of the different building types depending on the inundation level and flow velocity. So far, the scatter in the damage has not been taken into account. The paper presents 'fragility functions' which enable the quantification of the exceedance probability of certain damage grades depending on inundation level and flow velocity. These functions allow the identification and implementation of the scatter of structural damage. They also enable a simulative damage prognosis using the Monte Carlo method, which provides the basis for loss calculations and serve to quantify the scatter within the financial loss indicators. This can introduce a new level of cost-benefit analyses for the planning of new flood protection measures. For lower flow velocities, typical for river floods, the study is based on a comprehensive qualified damage dataset compiled after the 2002 flood in Germany. The lack of reliable damage data caused by high flow velocities during flash flood events is compensated by an innovative approach. For this purpose, damage data from the tsunami of the Tohoku earthquake in Japan in 2011 are re-evaluated and included in the analysis. The developed 'fragility functions' are applied to the re-interpretation of the August 2002 flood damage and loss in six different study areas in the Free State of Saxony. An outlook to the application for flash flood events is given.

2022, Water

The floods in 2002 and 2013, as well as the recent flood of 2021, caused billions Euros worth of property damage in Germany. The aim of the project Innovative Vulnerability and Risk Assessment of Urban Areas against Flood Events (INNOVARU) involved the development of a practicable flood damage model that enables realistic damage statements for the residential building stock. In addition to the determination of local flood risks, it also takes into account the vulnerability of individual buildings and allows for the prognosis of structural damage. In this paper, we discuss an improved method for the prognosis of structural damage due to flood impact. Detailed correlations between inundation level and flow velocities depending on the vulnerability of the building types, as well as the number of storeys, are considered. Because reliable damage data from events with high flow velocities were not available, an innovative approach was adopted to cover a wide range of flow velocities. The proposed approach combines comprehensive damage data collected after the 2002 flood in Germany with damage data of the 2011 Tohoku earthquake tsunami in Japan. The application of the developed methods enables a reliable reinterpretation of the structural damage caused by the August flood of 2002 in six study areas in the Free State of Saxony.

2022

Kuantan River basin (KRB) is important watershed passing through Kuantan city of state Pahang. Usually, it receives massive precipitation during north east monsoon season start from November to March. Since past years, it is experiencing severe floods with increased frequency by perceiving heavy rainfall, which produces surpass flow rate than river capacity resulting inundation of low- laying or flood plain areas hampered the human social and economic life. KRB has experienced the worst flood events during recent years that caused massive destruction of land use infrastructure, agriculture and irrigation system, loss of lives and properties, which ultimately affect the revenue loss suffered by Government in recovery of survival and loss. The change in climatic condition and anthropogenic activities following change in nature of flood seems occurrence getting more frequent in urbanized areas. The rapid urbanization leads land degradation and deforestation, which result high flow of s...

2022, Science and practice for an uncertain future

Climate change is likely to cause a change in frequency and intensity of convective thunderstorms and associated heavy precipitation. Typical consequences of such events are a rapid generation of surface runoff with high flow velocities in hilly and mountainous areas as well as the unexpected and abrupt occurrence of inundation in areas currently not known as flood-prone. The mapping of such pluvial flash flood events is still a developing field especially with regard to the post-processing of raw hydrodynamic model output data. Moreover, challenges include the derivation of indicators needed for quantification and visualisation of the impact dynamics on elements at risk such as buildings and infrastructures. This is important to support the understanding of vulnerabilities including uncertainties as well as to ensure a targeted interpretation of possible consequences and planning of mitigation measures. We present a three-step approach which includes (i) the calculation of surface runoff dynamics with a 2D hydrodynamic model, (ii) the derivation of impact indicators based on the modelling results as well as (iii) the presentation and mapping of key indicators in innovative hazard maps and diagrams.

2022, Natural Hazards and Earth System Sciences Discussions

Remote sensing analysis is routinely used to map flooding extent either retrospectively or in near-real-time. For flood emergency response, remote sensing-based flood mapping is highly valuable as it can offer continued observational information about the flood extent over large geographical domains. Information about the floodwater depth across the inundated domain is important for damage assessment, rescue, and to prioritize relief resource allocation, but cannot be readily estimated from remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was developed to augment remote sensing analysis by calculating water depth based solely on an inundation map with an associated Digital Elevation Model (DEM). The tool was shown to be accurate and was used in flood response activations by the Global Flood Partnership. Here we present a new version of the tool, FwDET v2.0, which enables water depth estimation for coastal flooding. FwDET v2.0 features a new flood boundary identification scheme which accounts for the lack of confinement of coastal flood domains at the shoreline. A new algorithm is used to calculate the local floodwater elevation for each cell, which improves the tool's runtime by a factor 15 and alleviates inaccurate local boundary assignment across permanent water bodies. FwDET v2.0 is evaluated against physically-based hydrodynamic simulations in both riverine and coastal case studies. The results show good correspondence, with an average difference of 0.18 m and 0.31 m for the coastal (using a 1-m DEM) and riverine (using a 10-m DEM) case studies respectively. A FwDET v2.0 application of using remote sensing derived flood maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater. Limitations include challenges in obtaining high-resolution DEMs and increases in uncertainty when applied for highly fragmented flood inundation domains. 1 Introduction Flooding is the most destructive natural disaster on Earth. About 100,000 people lost their lives due to floods in the last decade of the 20th century (Higgins et al., 2014). The highest loss proportion of the global insured catastrophes in 2017 (144 billion USD) came from Hurricanes Harvey, Irma, and Maria, resulting in combined insured losses of $92 billion (Swiss Re, 2018). Of the global disasters between 1994 and 2013, 43% were floods, affecting approximately 2.5 billion people (CRED, 2015). Coastal regions are particularly susceptible to flooding due to their low gradient terrain and exposure to storm surges and tsunamis (Li et al., 2018). Sea level rise, coupled with land subsidence and rapid urbanization, has led to increased flood risk in many coastal regions worldwide (Tessler et al., 2015). Monitoring, analyzing, and forecasting floods are commonly based on numerical models of hydrodynamic and meteorological processes, in situ gaging, and remote sensing analysis. The application of these tools and techniques for the unique topography of coastal flooding events is often problematic due to the low topographic gradients, greater diversity in flooding mechanisms, and complex riverine-coastal interactions. Hydrodynamic models typically rely on terrain data to simulate flood fluid dynamics (e.g. the GSSHA and LISFLOOD-FP models). Low variability in coastal topography heightens

2022, Remote Sensing

Damage caused by flood events is expected to increase in the coming decades driven by increased land use pressures and climate change impacts. The insurance sector needs accurate and efficient loss adjustment methodologies for flood events. These can include remote sensing approaches that enable the rapid estimation of (i) damage caused to property as well as (ii) the number of affected properties. Approaches based on traditional remote sensing methods have limitations associated with low-cloud cover presence, oblique viewing angles, and the resolution of the geomatic products obtained. Unmanned aerial vehicles (UAVs) are emerging as a potential tool for post-event assessment and provide a means of overcoming the limitations listed above. This paper presents a UAV-based loss-adjustment framework for the estimation of direct tangible losses to residential properties affected by flooding. For that purpose, features indicating damage to property were mapped from UAV imagery collected a...

2022, E3S Web of Conferences

Klaten Regency is one of the regencies in Central Java Province that has an increasing population every year. This can cause an increase in built-up land for human activities. The built-up land needs to be monitored so that the construction is in accordance with the regional development plan so that it does not cause problems such as the occurrence of critical land. Therefore, it is necessary to monitor land use regularly. One method for monitoring land use is the remote sensing method. The remote sensing method is much more efficient in mapping land use because without having to survey the field. The remote sensing method utilizes satellite imagery data that can be processed for land use classification. This study uses the sentinel 2 satellite image data with the Object-Based Image Analysis (OBIA) algorithm to obtain land use classification. Sentinel 2 satellite imagery is a medium resolution image category with a spatial resolution of 10 meters. The land use classification can be ...

2022, Water

Floods in the Mekong delta are recurring events and cause substantial losses to the economy. Sea level rise and increasing precipitation during the wet season result in more frequent floods. For effective flood risk management, reliable losses and risk analyses are necessary. However, knowledge about damaging processes and robust assessments of flood losses in the Mekong delta are scarce. In order to fill this gap, we identify and quantify the effects of the most important variables determining flood losses in Can Tho city through multi-variate statistical analyses. Our analysis is limited to the losses of residential buildings and contents. Results reveal that under the specific flooding characteristics in the Mekong delta with relatively well-adapted households, long inundation durations and shallow water depths, inundation duration is more important than water depth for the resulting loss. However, also building and content values, floor space of buildings and building quality are important loss-determining variables. Human activities like undertaking precautionary measures also influence flood losses. The results are important for improving flood loss modelling and, consequently, flood risk assessments in the Mekong delta.

2022, Journal of Geography, Environment and Earth Science International

Flood has been a serious hazard for the past decades in Nigeria at large. The incidence of 2012 and 2018 flood disaster in Yenagoa, Amassoma and other parts of the state have not been recover till date and the government is not consigned about the well been of the people. The major causes of the flood are attributed to increased rainfall and lack of drainages including dredging of rivers and disobeying of environmental law and infrastructure failure. Coastal Towns or communities are one of the most affected areas of flood and their farms and fishing implements were washed away by the floodwater in 2012 and 2018 in Bayelsa State. Flood management is needed for provision of time information so quick response can be done as soon as possible. Using SRTM data to produce digital elevation model and IDW Contour, the 3D model from ground data of Yenagoa metropolis using ArcGIS 10.6 to generate and analyze them. As a result of field survey, flood level calculation was made to classified floo...

2022, Remote Sensing

The use of high resolution ground-based light detection and ranging (LiDAR) datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs). As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN). The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i) generation an urban TIN from LiDAR data with a density of 0.5 points¨m´2, complemented with the river bathymetry obtained from a field survey with a density of 0.3 points¨m´2. The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii) implementation of a two-dimensional (2D) hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings); and (iii) determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m) show that this parameter has to be neatly characterized in order to obtain reliable assessments of flood damage assessments and implement realistic risk management.

2022, ISPRS International Journal of Geo-Information

As the world is digitizing fast, the increase in Big and Small Data offers opportunities to enrich official statistics for reporting on Sustainable Development Goals (SDG). However, survey data coming from an increased number of organizations (Small Data) and Big Data offer challenges in terms of data heterogeneity. This paper describes a methodology for combining various data sources to create a more comprehensive dataset on SDG 6.1.1. (proportion of population using safely managed drinking water services). We enabled digital volunteers to trace buildings on satellite imagery and used the traces on OpenStreetMap to facilitate visual detection of water points on Unmanned Aerial Vehicle (UAV) imagery and estimate the number of people served per water point. Combining data on water points identified on our UAV imagery with data on water points from field surveys improves the overall quality in terms of removal of inconsistencies and enrichment of attribute information. Satellite image...

2022, ISPRS International Journal of Geo-Information

2022, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

This paper examines recovery after major floods in the UK and Germany. It focuses on two areas that were badly hit by flooding: Catcliffe, near Sheffield in the UK, and Passau in Bavaria, Germany. It reports on surveys of residents and businesses in each place and on surveys of national flood experts in both countries. The two events were comparable in terms of impacts, levels of preparedness and government response and show similar patterns of speed and quality of recovery. In Germany, it took about 18 months for 90% or more of residents to get back to normal, while in the UK it took a year longer. This difference may be related to funding; in the UK, over 90% of funding came from household insurance while in Germany over 60% came from federal aid, which may have been quicker. In both countries, the economy had recovered to near normal within 12–18 months. The majority of people surveyed in both countries (74% in Germany and 67% in the UK) believe that their homes and businesses ar...

2022, E3S Web of Conferences

Detection and characterization of territorial elements exposed to flood is a key component for flood risk analysis. Land-use description works well for small scales of representation but it becomes too coarse while increasing the scale. ³6ingle-HOHPHQW´ FKDUDFWHUL]DWLRQ LV XVXDOO\ DFKLHYHG through surveys, which become prohibitive as the amount of elements to be characterized increases. Mapping schemes represent a compromise between level of description and efforts for data collection. The basic idea is to determine the statistical distribution of building characteristics inside a homogeneous class starting from a sample area and to apply this distribution to the whole area, realizing a statistical extrapolation. An innovative approach was developed, merging the mapping scheme methodologies developed by the Global Earthquake Model [1] and Blanco±Vogt and Schanze [2], in which homogeneous classes are not development areas but building clusters. The approach was applied to the buildings in the Bisagno River floodplain, Genoa (Italy). Buildings were classified according to a building taxonomy. Once the percentage of basement presence was assigned to each class by surveying a limited subset of the exposed assets, a series of possible basement distributions was simulated to calculate the corresponding damage distributions for a real flood event. The total average damage obtained is very close to the refund claims, with a percentage error lower than 2%.

2022, Environmental Research, Engineering and Management

The importance of flood damage assessment has been highlighted by the government as well as by many researchers. Nevertheless, the effort in performing the damage studies is less to be found due to the lack of awareness and some other limitations related to the data and its methodologies. The flood damage data in fact is part of an essential ingredient in developing the flood mitigation policy as well as in evaluating the effectiveness of the current flood reduction measures. However, unlike other kinds flood risk quantification study, damage assessment is the one that less concerned by the researchers. This paper has mainly provides a brief introduction towards the flood damage assessment and certain essential element need to be taken into consideration have been highlighted. An analysis of previous flood damage assessment studies and discussion towards some critical issues are presented in this paper other than proposing granular fuzzy system for enhancement in flood assessment fo...

2022, Advances in Water Resources

Remote Sensing technologies are capable of providing high-resolution spatial data needed to set up advanced flood simulation models. Amongst them, aerial Light Detection and Ranging (LiDAR) surveys or Airborne Laser Scanner (ALS) systems have long been used to provide digital topographic maps. Nowadays, Remote Sensing data are commonly used to create Digital Terrain Models (DTMs) for detailed urban-flood modelling. However, the difficulty of relying on top-view LiDAR data only is that it cannot detect whether passages for floodwaters are hidden underneath vegetated areas or beneath overarching structures such as roads, railroads, and bridges. Such (hidden) small urban features can play an important role in urban flood propagation. In this paper, a complex urban area of Kuala Lumpur, Malaysia was chosen as a study area to simulate the extreme flooding event that occurred in 2003. Three different DTMs were generated and used as input for a two-dimensional (2D) urban flood model. A top-view LiDAR approach was used to create two DTMs: (i) a standard LiDAR-DTM and (ii) a Filtered LiDAR-DTM taking into account specific ground-view features. In addition, a Structure from Motion (SfM) approach was used to detect hidden urban features from a sequence of ground-view images; these ground-view SfM data were then combined with top-view Filtered LiDAR data to create (iii) a novel Multidimensional Fusion of Views-Digital Terrain Model (MFV-DTM). These DTMs were then used as a basis for the 2D urban flood model. The resulting dynamic flood maps are compared with observations at six measurement locations. It was found that when applying only top-view DTMs as input data, the flood simulation results appear to have mismatches in both floodwater depths and flood propagation patterns. In contrast, when employing the top-ground-view fusion approach (MFV-DTM), the results not only show a good agreement in floodwater depth, but also simulate more correctly the floodwater dynamics around small urban feature. Overall, the new multi-view approach of combining top-view LiDAR data with ground-view SfM observations shows a good potential for creating an accurate digital terrain map which can be then used as an input for a numerical urban flood model.

2022, Postprints der Universität Potsdam: Mathematisch-Naturwissenschaftliche Reihe

Social inequalities lead to flood resilience inequalities across social groups, a topic that requires improved documentation and understanding. The objective of this paper is to attend to these differences by investigating self-stated flood recovery across genders in Vietnam as a conceptual replication of earlier results from Germany. This study employs a regression-based analysis of 1,010 respondents divided between a rural coastal and an urban community in Thua Thien-Hue province. The results highlight an important set of recovery process-related variables. The set of relevant variables is similar across genders in terms of inclusion and influence, and includes age, social capital, internal and external support after a flood, perceived severity of previous flood impacts, and the perception of stress-resilience. However, women were affected more heavily by flooding in terms of longer recovery times, which should be accounted for in risk management. Overall, the studied variables pe...

2022, International journal of georesources and environment

Flood is an annual event in the district of Jalpaiguri. Almost all the administrative blocks of the district are more or less flood prone. Numerous rivers and rivulets are originated and pass through this district, which create floods mainly on account of rainfall in the source regions of these rivers, apart from rainfalls in the district itself. The shivering rivers during monsoon periods carry massive discharge and frequently cross danger levels. Danger level is the threshold level of water from which the event is considered as a flood. The probability of the occurrence of flood can be calculated with the past records of flood events in flood prone areas. On the other hand, the vulnerability of flood events is entirely dependent on the exposure of the area. Exposure of the area and the probability of the adjacent rivers can explain how much this area is subject to floods. In this paper, the authors tried to prepare a spatial flood potential map for the entire district based on probability analysis and an exposure indicator.

2022, Journal of Geography, Environment and Earth Science International

2022, The Journal of Social Sciences Research

Floods are one of the most common natural disasters worldwide. In Malaysia, floods cause significant economic damage and loss of human life. The frequency and magnitude of floods are increasing due to climate change and related anthropogenic activities. This study surveyed 280 respondents living in the Temerloh district which is in the midstream zone of the Pahang River Basin. This paper highlights their flood experience and identifies the cause of floods from the view of lay people. Results show that respondents are experienced in flood and flood-related damages. However, their perception of the causes of floods focused on natural causes while ignoring anthropogenic activities such as land use changes. To identify the land use changes, we used a classified shapefile for the years 2000 and 2010 from the Department of Agriculture, Malaysia and used overlay procedure in ArcGIS 10.1. Within the ten years, significant land use changes took place which could increase future flood risks. ...

2022, Journal of Flood Risk Management

This study focuses on the physical vulnerability of buildings to flash floods using an indicator-based methodology. A physical vulnerability index (PhVI) that combines intrinsic vulnerability (IV) of buildings and flash flood intensity (FFI) is proposed. IV evaluates the propensity to suffer damage, resulting from indicators related to building properties. FFI estimates the potential to cause damage, resulting from indicators related to flow parameters. PhVI was applied to a critical section of a small drainage basin in Portugal where flash floods are frequent. Evaluating IV and the intensity of natural hazards is essential in physical vulnerability assessments. This study addresses two problems found in the literature: the lack of flash flood-dedicated physical vulnerability assessments and the difficulties in assembling building properties and the intensity of natural hazards in a vulnerability index defined from indicatorbased methodologies. PhVI is a useful tool where damage records are rare or non-existent, allowing the prioritisation of resources and application of local protection measures. This index can be adapted to other study areas and natural hazards, although more research is needed to improve the knowledge on the indicators and weights of IV and FFI.

2022, Int. J. Exp. Res. Rev.

Flood is the most common and natural phenomena of any flood prone region and damage is also very common event related to flood hazard of any magnitude. Impact of flood in any particular area is always concerned with the damage created by the flood. Flood (Damage) Impact Assessment (FIA) is a technique to assess flood impact in flood prone regions. It helps to quantify and understand the extent of a given society will compromise with damage and the extent of the said society accepts the flood event as or a hazard, such that flood can be viewed either as flood threshold limit or as flood hazard. The threshold limits to predict or indicates how far the society will take flood as an event with its corresponding damages. Jalpaiguri is a district of West Bengal, which has faced flood almost every year. This flood causes damage over the district. However, the intensities of damage vary from year to year. Analysis of the actual amount of expost damage calculation of human effect, property and environment loss is too hard. Present papers have been analysed flood damage of the district or the flood impact assessment and assess the original hazardous condition of the district in past 43 years. It's also expressed in high flood situation (1998) the block-wise damage impact assessment of flood.

2022, Remote Sensing

While remotely sensed images of various resolutions have been widely used in identifying changes in urban and peri-urban environments, only very high resolution (VHR) imagery is capable of providing the information needed for understanding the changes taking place in remote rural environments, due to the small footprints and low density of man-made structures in these settings. However, limited by data availability, mapping man-made structures and conducting subsequent change detections in remote areas are typically challenging and thus require a certain level of flexibility in algorithm design that takes into account the specific environmental and image conditions. In this study, we mapped all buildings and corrals for two remote villages in Mozambique based on two single-date VHR images that were taken in 2004 and 2012, respectively. Our algorithm takes advantage of the presence of shadows and, through a fusion of both spectra- and object-based analysis techniques, is able to diff...