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Categorization of house types in the flood-prone areas of the study basin: (a) one-story permanent house, (b) two-story permanent house, (c) two-story semipermanent house, (d) elevated semi-permanent house, and (e) elevated temporary house.
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Development of a flood damage estimation method that considers house type is important to evaluate the effectiveness of different adaptation options. This study aimed to analyze flood impact on residential areas and household damage, to develop a new, more accurate, method for flood damage assessment, considering different house types. To do this i...
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... such as construction materials of walls and roof, number of stories, height of plinth level from the ground, and floor height, were analyzed using the survey data. The houses in the study area can be mainly categorized into two types: (1) normal houses (referring to houses without stilts) and (2) elevated houses (referring to houses with stilts) (Fig. 5). Based on construction materials of walls and number of stories, normal houses can be further categorized into three groups: (i) one-story permanent house (one-story houses with concrete, brick or stone walls), (ii) two-story permanent house (two-story houses with concrete, brick or stone walls), (iii) two-story semi-permanent house ...
Citations
... loss was positively correlated with inundation duration along with household income and inundation depth. Shrestha et al. (2021) used household surveys in Myanmar's Bago region to create new local flood damage functions based on building characteristics. Ahadzie et al. (2022) studied flood impacts on residential buildings in urban settlements across five floodprone regions in southern Ghana, with data showing significant damage to contents, such as furniture and clothes. ...
This paper introduces INSYDE-content, a novel, probabilistic multi-variable synthetic flood damage model designed to analyze physical damage to household contents on a component-by-component basis. The model addresses a critical gap in current modeling tools, which often overlook the significance of household contents in overall damage assessments. Developed through an expert-based approach and grounded in the scientific and technical literature, INSYDE-content leverages desk-based data to characterize model features, including uncertainty treatment arising from incomplete input data. A sensitivity analysis and a benchmark test against observed losses demonstrate the robust performance of the model and highlight the contribution of different features to damage mechanisms affecting house contents. While in this study INSYDE-content is tailored for illustrative purposes to the hazard, vulnerability and exposure characteristics of Northern Italy, the model is highly adaptable, allowing for its application to different regional contexts through appropriate customization.
... In contrast, inadequate disaster response, especially in flood-prone areas, may lead to increased mental health symptoms. Different regions experience varying levels of flood damage depending on housing quality and the vulnerability of exposed elements (80). Participants living in kacha houses, for example, were found to have higher levels of depression, anxiety, and stress compared to those living in pucca houses, likely due to the hazardous conditions associated with kacha housing. ...
Disasters can pose significant risks to mental health, often resulting in both temporary and long-lasting psychological distress. This study explores the impact of floods on mental health. A survey was conducted shortly after the 2022 flash flood, in which 452 male participants from the Ajmiriganj and Dharmapasha Upazilas in Bangladesh were surveyed. Mental health was assessed using the DASS-21 instrument, and we examined the variables associated with mental health issues. Descriptive statistics and multiple linear regression analysis were employed. Around 47% of participants reported severe or extremely severe depression, 41% reported severe or extremely severe anxiety, and 36% reported severe or extremely severe stress. Factors such as age, marital status, type of home, occupation, flood safety rating, and property loss during the 2022 flood were all found to be associated with depression. Anxiety was linked to flood safety, occupation, housing type, education level, and marital status. Additionally, all anxiety-related variables were also associated with stress. Mental health issues were more prevalent among older, married, illiterate participants living in kacha (temporary) housing, as well as among agricultural workers and fishers with low safety ratings. Psychological interventions and disaster risk reduction strategies could help mitigate the mental health impact of floods. The findings of this study have important implications for global disaster management and public health.
... Flood damage assessment has been conducted at the city and local levels with limited coverage areas [24][25][26][27] , as well as at the global scale with low resolution 22,28 . However, few studies have focused on impact-based forecasting at the regional and national levels, with some exceptions in East Africa and Philippine 21,23 . ...
Typhoon Hagibis (2019), one of the most powerful storms to strike Japan in recent years, caused widespread flooding and significant damage. Impact-based forecasting is crucial for planning effective mitigation measures and enhancing future disaster responses. This study employs the Integrated Land Simulator (ILS) coupled with the Weather Research and Forecasting (WRF) Model to evaluate flood damage induced by Typhoon Hagibis (2019) by using Impact-Based Typhoon Track Ensemble Forecasting. These findings underscore the critical influence of typhoon tracks on flood risk. Impact-based typhoon track ensemble simulation can enhance our understanding of high-risk flood-prone areas and improve disaster preparedness and mitigation strategies.
... Inundation depth is consistently identified as the most decisive factor, as highlighted by Merz et al. [31] from an analysis of 2158 post-flood interviews, and confirmed by Aribisala et al. [22]. These latter authors also include water flow velocity, the flow rate and speed of the rising waters, as well as the duration of the event, a factor also noted by Shrestha et al. [32]). Beyond the characteristics of the flood itself, the structure and quality of the building significantly influence the level of damage. ...
... Duhamel et al. [35] further emphasize the importance of site access via the road network and the presence of mitigation measures such as water evacuation systems, backflow preventers, and foundation waterproofing. Water turbidity (contamination) is also an aggravating factor, mentioned by Amirebrahami et al. [17] and Shrestha et al. [32]. Finally, the probability of occurrence of the flood, although not a direct damage factor, influences prevention and adaptation choices, as emphasized by Balica et al. [9], Messner and Meyer [36], and Towfiqul Islam et al. [37]. ...
... Deep uncertainty refers to situations where the future is highly uncertain, and traditional probability distribution functions cannot adequately represent or predict the range of possible outcomes. However, the results of uncertainty modelling are challenging to validate or confirm when compared to empirical field data [32,42]. Other authors have used Bayesian multilevel models to estimate the normalized damage for different flood types. ...
... This modeling approach cannot simultaneously simulate evapotranspiration, flood runoff and inundation processes. Recently, some other studies have used the rainfall-runoff-inundation (RRI) hydrologic-hydraulic model developed by Sayama et al. (2012) for flood runoff and inundation simulations (Try et al. 2020;Shrestha and Kawasaki 2020;Shrestha et al. 2021b;Yamamoto et al. 2021b). However, the RRI model cannot consider the complete process of evapotranspiration and soil-vegetation-atmospheric interactions. ...
... Therefore, this study also suggested the necessity of river basin management by implementing preventive and adaptation measures such as land use change or regulation, draingae capacity improvement and implementation of flood control measures to further reduce the losses in the future. Furthermore, FD to residential households can also be reduced by adapting their houses to floods, such as elevating the plinth level of the house or constructing elevated houses with stilts, or adding an additional story in the house as mentioned in Shrestha et al. (2021b). ...
Providing quantitative information on expected flood damage due to climate change is essential for minimizing the future risk through climate change adaptation and mitigation measures. Understanding changes in flood damage in the future due to climate change impact considering regional or local characteristics is also crucial for better manage flood risk in the future. However, the climate change impact on flood damage to exposed elements and the effectiveness of our effort of climate change mitigation and adaptation to build resilient society for future are still not well understood. We thus focused on quantitative assessment of flood damage under climate change with different scenarios of projected population in the future, focusing in the Solo River basin, Indonesia. Flood damage was quantitatively assessed using the hydrologic-hydraulic numerical model and depth-damage flood loss model. Flood damage was assessed focusing on damage to residential buildings and contents for the past and future periods using MRI-AGCM3.2S climate model outputs. The social flood exposures such as number of exposed population and inundated houses in the flood-prone areas were also analyzed. Results show that large areas will be frequently flooded with greater flood inundation volume in future due to climate change impact. The residential building and content damage in the study basin may increase in future by more than twofold times due to climate change (increase by 121–259%, depending on population growth) if climate change mitigations and adaptations are not implemented. The results presented in this study also provide evidence-based information for establishing flood preventive and adaptation measures.
... However, these solutions may require replanting trees, creating retention ponds and wetlands, and preserving natural floodplains; and also, they may not be effective for large-scale flooding. Moreover, elevating and floodproofing solutions by households living in the flood-prone areas (e.g., elevating the building by raising the plinth level, building new houses on elevated ground above the flood level, building houses with flood resistance materials, and building barrier walls) are also other possible feasible options for reducing the flood impact [49,50]. In the case of agricultural damage reduction, establishment of adequate drainage capacity, the use of submergence-tolerant rice varieties in flood-prone areas during the monsoon season, and changing the cropping pattern or schedule to avoid the flood can also help in reducing the crop loss [51]. ...
... Quantifying exposed people in flood-prone areas spatiotemporally and evaluating the effectiveness of flood control measures provide scientific information that can be useful for preparing, planning, and implementing flood preventive measures and reducing property and human risks. The quantitative results of flood exposure and damage can be used to build a resilient society and also to help policy-and decision-makers establish flood adaptation measures and policies required for risk reduction, such as land use regulations, guidelines for building constructions, and restrictions on development activities in flood-prone areas [49]. A comprehensive flood management strategy combining both structural measures (like those presented in this study) with non-structural approaches, like hazard and risk mapping, land use planning, urban-planning regulations, and resilient infrastructure investments, is crucial for long-term flood mitigation. ...
... Land use planning, such as land use restrictions in flood-prone areas through land use zoning with building restrictions also plays a key role in reducing damage by extreme flood events. Relocating existing buildings from flood-prone areas can be expensive, but restrictions on constructing new buildings in flood-prone areas anticipating high flood depths can help reduce damage [49]. Flood damage reduction is also possible in paddy fields in flood-prone areas with high flood depths by introducing submergence-tolerant rice varieties, new cropping practices, or different rice-cropping calendars, avoiding flooding and other adverse effects taking place potentially due to climate change. ...
The frequent occurrence of floods puts additional pressure on people to change their activities and alter land use practices, consequently making exposed lands more vulnerable to floods. It is thus crucial to investigate dynamic changes in flood exposures and conduct quantitative evaluations of flood risk-reduction strategies to minimize damage to exposed items. This study quantitatively assessed dynamics of flood exposure and flood risk, and evaluated the effectiveness of flood control measures in the Bengawan Solo River basin, Indonesia. The Water and Energy Budget-Based Rainfall–Runoff–Inundation Model was employed for flood simulation for different return periods, and then dynamics of flood exposures and flood risk were assessed. After that, the effectiveness of flood control measures was quantitively evaluated. The results show that settlement/built-up areas and population are increasing in flood-prone areas. The flood-exposed paddy field and settlement areas for 100-year flood were estimated to be more than 950 and 212.58 km², respectively. The results also show that the dam operation for flood control in the study area reduces the flood damage to buildings, contents, and agriculture by approximately 21.2%, 20.9%, and 25.1%, respectively. The river channel improvements were also found effective to reduce flood damage in the study area. The flood damage can be reduced by more than 60% by implementing a combination of a flood control dam and river channel improvements. The findings can be useful for planning and implementing effective flood risk reduction measures.
... SDDFs are tailored to specific asset categories, such as residential buildings, commercial structures, and industrial facilities, with their accuracy contingent upon how well the characteristics of the assessed assets match those used to develop the functions. In a study conducted by Shrestha et al. (2021), the effectiveness of SDDFs in estimating flood-induced damage across various building types in Nepal was demonstrated, achieving a 10% accuracy. Similarly, Nofal et al. (2020) showcased the skill of SDDFs in assessing the impacts of flooding on diverse infrastructure in Egypt, achieving a 15% accuracy. ...
Urban flooding can lead to significant economic and social repercussions. To effectively understand and mitigate these impacts, conducting a flood risk assessment is crucial. This research focuses on evaluating flood damage in the flood-prone areas of the Koramangala-Challaghatta (KC) Valley in Bengaluru, India. The study involved surveying these regions to gather data on population characteristics, demographics, economic status, property details, and repair costs following a flood for both residential and commercial properties. Utilising Random Forest and multivariate regression analyses, the study identified the primary factors that influence flood damage. These factors were then employed to develop distinct flood damage functions for the residential and commercial sectors. The research underscores the vital role of flood depth in contributing to damage in both types of properties. It reveals that flood depth has a significant impact on structural damage as well as damage to the contents within these properties. Furthermore, a positive correlation was found between flood depth and residential property prices, indicating that more valuable properties in flood-prone areas are likely to incur more severe damage. Conversely, a negative correlation observed in the commercial sector suggests that higher property prices may be linked to better flood protection measures. These findings offer valuable insights that can assist policymakers and urban planners in making informed decisions. They highlight the importance of economic resilience in flood-prone regions and guide future flood risk management strategies.
... Therefore, proactive policy actions for adaptation and flood risk reduction are required in these locations. To establish the necessary preventative measures and policies for reducing flood damage, useful information on the physical and economic impacts of floods on residential areas would be required by planners, policy makers, and decision-makers (Shrestha et al., 2021a). ...
... The depth-damage function method (Penning-Rowsell & Fordham, 1994;Pistrika et al., 2014;Smith, 1994) is a common method for estimating direct flood damage to building structures and contents. Most previous flood damage function studies concentrated on a single type of building structure, with only a few studies taking into account building structure types, construction materials (Shrestha et al., 2021a), and the presence or absence of a basement floor. Flood damage functions are typically established based on the depth of the floodwater, but damages and losses from floods are also influenced by a number of other factors, including the velocity of flow, the duration of floods, sediment concentration, leadtime, warning systems, flood experience, structures and quality of buildings, etc. (Chinh et al., 2015). ...
... In this study, an empirical approach via questionnaire survey was adopted to obtain flood damage data for the establishment of flood damage functions for the residential basement floor and the contents. Asset damages were connected to the costs of replacing the damaged contents, whereas residential building damages were linked to replacement and repair costs (Dias et al., 2018;Komolafe, Herath, et al., 2019;Komolafe, Srikantha, et al., 2019;Pistrika et al., 2014;Shrestha et al., 2021a). The structure damages ratio and content damages ratio were calculated as the ratio of the total cost to repair the flood-damaged property's components (Structure and Content) to the market value or estimated value of rebuilding/ replacement of the structure and content, respectively (Pistrika et al., 2014). ...
To evaluate the effectiveness of various adaptation strategies, it is critical to develop a flood damage function that considers building characteristics for future risk evaluation. This study analysed the contributions of some important flood and household characteristics in flood damage processes and developed a new, more accurate, multi-variable flood loss model for flood damage assessment for residential buildings and contents, considering different house types in Ogun River Basin, Nigeria. A detailed household questionnaire survey was conducted to collect data (149 samples). Depth-damage functions were developed to estimate direct flood damage to building structures and contents using the nonlinear logistic and power (concave) models, and the model parameters were estimated using the Gauss-Newton algorithm. The performance of all flood damage regression analysis functions for building structures and building contents under different construction materials and basement floors was evaluated by comparing predicted damages and after-flood survey damages, which demonstrated acceptable comparativeness. In the event of a flood disaster in the area, the models can be used to forecast future damages and devise risk-mitigation strategies.
... Extreme rainfall increasingly influences many parts of the world under climate warming, and rainfall-induced floods usually result in serious casualties and property damage (Davenport et al. 2021), particularly in developing countries (Doan et al. 2022;Shrestha et al. 2021). China faces frequent heavy rainfall and flood risks on an annual basis. ...
... Present studies have identified two distinct types of methods for estimating flood damage caused by rainfall: depth-damage models and rainfall-damage models, each method has its own advantages and disadvantages. Depth-damage models are typically constructed using self-reported flood depth as the independent variable and self-reported damage as the dependent variable (Penning-Rowsell et al. 2005;McGrath et al. 2019;Nguyen et al. 2021;Shrestha et al. 2021;Porter et al. 2023). However, these models do not incorporate any control variables and lack specificity regarding the type of damage or flood (Van Ootegem et al. 2018). ...
Developing a regional damage function to quickly estimate direct economic losses (DELs) caused by heavy rain and floods is crucial for providing scientific supports in effective disaster response and risk reduction. This study investigated the factors that influence regional rainfall-induced damage and developed a calibrated regional rainfall damage function (RDF) using data from the 2016 extreme rainfall event in Hebei Province, China. The analysis revealed that total precipitation, asset value exposure, per capita GDP, and historical geological disaster density at both the township and county levels significantly affect regional rainfall-induced damage. The coefficients of the calibrated RDF indicate that doubling the values of these factors leads to varying increases or decreases in rainfall-induced damage. Furthermore, the study demonstrated a spatial scale dependency in the coefficients of the RDF, with increased elasticity values for asset value exposure and per capita GDP at the county level compared to the township level. The findings emphasize the challenges of applying RDFs across multiple scales and highlight the importance of considering socioeconomic factors in assessing rainfall-induced damage. Despite the limitations and uncertainties of the RDF developed, this study contributes to our understanding of the relationship between physical and socioeconomic factors and rainfall-induced damage. Future research should prioritize enhancing exposure estimation and calibrating RDFs for various types of rainfall-induced disasters to improve model accuracy and performance. The study also acknowledges the variation in RDF performance across different physical environments, especially concerning geological disasters and slope stability.
... Hazard research can be summarized into three aspects: simulation analysis based on probability distribution theory [18,19], inundation simulation analysis based on runoff modeling [20][21][22], and hazard evaluation based on remote sensing monitoring [23,24]. Research on exposure mainly focuses on elements exposed to risk, including populations [25], buildings [26], agriculture [27], etc. Vulnerability research primarily involves establishing damage curves of exposed elements through methods such as questionnaire surveys or experimental simulations [28][29][30] to further analyze the potential losses caused by hazards. The above studies have formed a relatively integrated framework for disaster risk assessment. ...
The impact of flooding on cities is becoming increasingly significant in the context of climate change and rapid urbanization. Based on the analysis of the land use changes and rainstorm waterlogging inundation scenarios of Jiangqiao Town from 1980 to 2020, a scenario analysis was conducted to simulate and assess the rainstorm waterlogging disaster risk in 2040 under three land use scenarios (a natural development scenario, Scenario ND; an economic growth scenario, Scenario EG; and an ecological development priority scenario, Scenario EP) and three rainstorm scenarios with return periods of 10, 50, and 100 years. The following results were found: (1) Land use change is a significant factor in the risk of urban rainstorm waterlogging disaster caused by surface runoff and inundation depth change. In particular, the resultant increase in impermeable surfaces such as residential land and industrial land and the decrease in farmland during urbanization would lead to an increase in urban rainstorm waterlogging disaster risk. (2) Under three rainstorm scenarios, the future land use exposure elements and losses are consistent in terms of spatial distribution; from 10-year to 100-year return periods, they manifest as an expansion from the south to the surroundings, especially to the central region of the study area. The locations at risk are mainly distributed in the central and southern regions of Jiangqiao Town. (3) The economic losses are different in different land use scenarios and rainstorm scenarios. In the context of rainstorm scenarios with return periods of 10, 50, and 100 years, the total losses in land use scenario ND are CNY 560 million, CNY 890 million, and CNY 1.07 billion; those in land use scenario EG are CNY 630 million, CNY 980 million, and CNY 1.19 billion; and those in land use scenario EP are CNY 480 million, CNY 750 million, and CNY 910 million. The total losses of land use EP are the lowest by comparison. So, the influence of land use change on the rainstorm waterlogging disaster risk shows obvious differences among different rainstorm scenarios. This study has important reference value for decision making on land use management and flood disaster risk management in rapidly urbanizing areas.
