Flood Damage Costs Research Articles

Nationwide evaluation of changes in fluvial and pluvial flood damage and the effectiveness of adaptation measures in Japan under population decline

To implement strategic countermeasures against flood damage, assessing flood damage and its countermeasures is necessary. However, in Japan, there is a lack of scientific knowledge on how to implement strategic measures considering climate and demographic changes. In this study, we aimed to evaluate the impacts of climate and demographic changes on fluvial and pluvial flood damage and the effectiveness of adaptation measures across Japan. The main novelty of our methodology is the incorporation of Coupled Model Intercomparison Project Phase 6-based climate scenario data and the Japanese version of shared socioeconomic pathways into damage cost calculations based on inundation analysis to consider both climate and demographic changes. Our results showed that although fluvial and pluvial flood damage could increase in almost all prefectures due to climate change, damage could decrease in approximately 70 % or more of prefectures by the end of the 21st century after considering demographic changes. In contrast, flood countermeasures are necessary, as the per capita fluvial and pluvial flood damage costs are estimated to increase. Furthermore, our assessment of adaptation measures suggested that demographic change causes a reduction in the effectiveness of adaptation measures. Therefore, we emphasise the need to consider not only climate change but also demographic change in adaptation planning.

Flood damage cost prediction using random forest

Floods are one of nature's deadliest catastrophes, causing permanent and catastrophic damage on the socioeconomic system, agriculture and human life. The problems arise when floods could cause a lot of economic damage such as damage to buildings, agriculture and others. Flood damage estimation is a subject of study that has not received much attention. The objective of this research is to explore the Random Forest algorithm in the flood damage cost prediction. The damages specified by the Malaysia’s Department of Irrigation (JPS) are structures such as culverts, MTB bridges, riverbank ruins, concrete main channels, farm roads, hydrological stations, agricultural and water drainage, JPS pump houses and tyres in Terengganu. Terengganu is one of the states in Malaysia which has to endure floods during the monsoon season by the end of the year. The methods employed in this research include data collection, data pre-processing, backend engine coding and user interface design. This project was implemented using the Python programming language. The data were collected from the annual flood report provided by the JPS Negeri Terengganu. The research used the rainfall and streamflow data from the year 2012 to 2022 as attributes to forecast the cost of the JPS structures damages in Terengganu. The prediction results showed that the best model achieved the accuracy of 91.47% with a Mean Squared Logarithmic Error (MSLE) of 0.48 and Coefficient of Determination (R2) of 0.92. In the performance evaluation, the model with 80:20 training and testing data ratio produced the best result in predicting the flood damage cost. The potential enhancements to this research involve extending the scope to encompass all Malaysian states, incorporating diverse flooded structures and adding more input variables for a more improved and more reliable flood prediction system.

Flood Impacts on Agriculture under Climate Change: The case of the Awanui Catchment, New Zealand

We assess the economic and environmental impacts on agriculture of flooding under projected climate change, including land-use change as an adaption response to floods. Our case study area is the Awanui catchment located in the far north of New Zealand, where flooding is a significant hazard. The study uses an integrated approach and combines spatial information on agricultural exposure and damage from flooding, economic land-use modelling, and valuation approaches. We analyse direct tangible and direct intangible flood impacts under various extents, frequencies, and water depth levels. Our results show areas with flood exposure and damage costs increase with projected climate change. As an adaptation measure to reduce flood damage costs, pastoral farms convert to other land uses, mainly to unfarmed land. Flooding reduces the net revenue for the catchment, while it can result in some reduction of environmental pollution. When the probability of all possible flood events are considered, the value of the changes in greenhouse gas emissions are equivalent to approximately 18% of the change in total net revenue, while the value of changes in other environmental outputs is equivalent to less than 1% of the change in total net revenue. Based on this study, the assessment of various flood impacts and adaptation responses to them can help to develop resilience strategies for the agricultural sector to future climate-induced flooding.

A decentralized multi-agent framework for urban flood management

The management of water resources in urban environments is challenging due to the existence of numerous stakeholders and the large number of affected people. In this paper, agents in an urban environment are categorized as active, passive, and monitoring agents, and a new mechanism is proposed to determine the flood control motivation functions (FCMFs) of active agents. An FCMF shows the motivation of an agent for investing and participating in a flood control activity. Also, for the first time, the effectiveness of a conflict resolution model based on asynchronous distributed constraint optimization (ADOPT) is evaluated for urban flood management. To evaluate the effectiveness of the proposed framework, it is applied to the eastern drainage catchment of Tehran, the capital city of Iran. The FCMFs of active stakeholders are modeled using some mathematical functions. To determine the FCMFs of active agents, an economic optimum point is suggested. This point is determined based on the construction costs of flood control infrastructures and flood damage costs. The utility functions of passive agents are modeled using a regression analysis. Flood management scenarios include a combination of water transfer canals, pipes, and ponds with real-time operating methods. ADOPT is used for solving Distributed Constraint Optimization Problems (DCOPs). The goal in DCOPs is to assign values to these variables in an approach that maximizes a global objective function while satisfying the constraints of each agent. The results show that by using the ADOPT-based conflict resolution model, the average depth of flooding is reduced from 24 cm to about 10 cm, and this is associated with the satisfaction of more than 90 percent of stakeholders. A decline in Average Flood Depth (AFD) has been observed with increased usage of technological methods such as constructing ponds or transferring water outside the basin. However, stakeholder desirability is critical and both technical and stakeholder interests should be taken into account to ensure project viability.

Flood Risk Management in the Upper Caroni River Basin

Flooding is more common than earthquakes and hurricanes, leaving casualties, infrastructure damage, and economic losses in its wake. The October 2018 floods in Trinidad heightened public concern about the ability of public authorities to manage floods. This study investigates the impact of five combinations of detention basins and embankments on the cost of physical damage to residential buildings in the Caroni River Basin. Further comparison of the maximum flood depth before and after the implementation of structural mitigation combinations was conducted for typical design return periods of 5, 25, 50, and 100 years. The results showed that strategically introducing detention ponds along the Aripo and Guanapo Rivers caused the greatest reduction in flood damage cost (12.86%). Evidence also suggests that attenuation of flood waters by detention ponds is a better alternative to flood protection by embankment-only options

The value of advanced flood models, damage costs and land use data in cost-effective climate change adaptation

Damage costs from coastal flooding are high and are expected to increase further due to rising sea levels. The associated risks suggest a need for developing methodologies and models to assess damage costs in coastal areas as a basis for decision-making on climate change adaptation. The accuracy of damage cost estimates is critical in cost-effective decision-making on adaptation measures, reflecting climate hazards, flood levels, and associated damage costs. However, detailed models require extended work compared to simpler models due to demands on input data, including land use, damage costs, and adaptation options and costs. In the paper, varying levels of resolution, damage costs and flood models are assessed for coastal flooding risks for two Danish urban areas. Two damage cost models are used: a detailed, context-specific model using local high-resolution land use- and flood damage cost data and a less detailed model with lower-resolution land use data and damage costs based on generic European cost curves. Two flood models are used for the assessment using the detailed damage cost model based on a dynamic and a static flood approach, respectively. For the coarser model, only a static flood model is used. Significant differences are identified between the modelling approaches: The flood area varies up to a factor of ten for static floods due to the digital elevation map (DEM) model alone and a factor of 17 when changing both the DEM and using a dynamic flood. Corresponding factors for resulting damage costs are four and five, respectively.

Evaluation of an Adaptation Strategy for Flood Damage Mitigation Under Climate Change Through the Use of Irrigation Reservoirs in Japan

AbstractThis study performed flood analysis, considering the water storage of irrigation reservoirs, to realize flood control by reservoirs, which are traditional irrigation facilities. The effect on flood control was determined through flood analysis performed by varying the reservoir storage rates. Based on the flood analysis results, Japan’s flood damage costs were estimated. Using three Shared Socioeconomic Pathways (SSPs) (SSP1-2.6, SSP2-4.5, and SSP5-8.5), we evaluated the flood control potential of reservoirs under future climate conditions. When the reservoirs were empty, the damage cost reduction rate resulting from the use of reservoirs across Japan was small, ranging from 1.1% to 2.3%, but as the damage cost reduction rate did not change under all future scenarios, reductions in flood damage were not affected by changes in rainfall under future climate conditions. Moreover, some prefectures showed high damage cost reduction effects. In northern part of Japan and numerous prefectures in western Japan, the potential to reduce damage through flood control by irrigation reservoirs was high. Some prefectures experienced similar reduction levels as those under alternative adaptation strategies. In the Kanto region, flood control by irrigation reservoirs had low potential for reducing damages. Even among prefectures with low water storage capacities of irrigation reservoirs, the potential to mitigate the effect of damage was high.

Investigating the causal impacts relationship between economic flood damage and extreme precipitation indices based on ARDL-ECM framework: A case study of Chungcheong region in South Korea

The attribution of climate change to various natural disasters, including flood events, has continued to receive a considerable attention as it impacts the socioeconomic sustainability of society. However, the existing knowledge on the influential role of extreme precipitation on flood events and subsequent economic damage is limited. Thus, this study investigates the causal relationship between flood damage cost, flooded area, and extreme precipitation indices in the Chungcheong region of South Korea using the autoregressive distributed lag-error correction model (ARDL-ECM) framework and pairwise Granger causality analysis. Four extreme precipitation indices: consecutive wet days (CWD), number of very heavy precipitation days (R30mm), maximum 1-day precipitation amount (Rx1day), and simple daily precipitation intensity (SDII) that measure precipitation frequency, intensity, and duration were selected with time series data on the flooded areas and estimated flood damage cost from 1985 to 2020. The ARDL-ECM bound test indicates an existence of a long-run relationship among all the variables. The empirical results of pairwise Granger causality analysis further reveal that flooded area, R30mm, and Rx1day have significant positive causal impacts on the flood damage cost in both short and long-runs, in the current period. This implies that any increase in any of these variables will cause an increase in the flood damage cost. Unidirectional causality exists from the flooded area, R30mm, Rx1days, and SDII to flood damage cost, and from R30mm and SDII to flooded area. These extreme precipitation variables could serve as indicators of flood events and economic flood damage. This study advances the knowledge of the causal link between extreme precipitation indices and economic damage from flood events.

Estimating coastal flood damage costs to transit infrastructure under future sea level rise

Future sea level rise (SLR) and associated increases in the frequency and intensity of coastal flooding poses significant threats to coastal communities and transit systems. Yet current literature and practice lack methods for estimating flood damage costs to transit systems. Here, we construct an event-specific flood damage cost estimation framework for transit systems, simulating separately flood ingress into underground spaces. We apply this framework to the MBTA rail transit system in Boston, estimating damages under several coastal flood events with SLR and project expected annualized losses (EAL) through 2100 with uncertain SLR. We estimate EALs to the MBTA system have doubled since 2008 to $24.4 M/year and are expected to reach $58 M/year by 2030 under all SLR scenarios. Our results suggest that absent adaptation schemes, particularly at tunnel ingress locations, coastal flood risk will continue to accelerate, potentially resulting in permanent inundation of underground and low-lying sections of the transit system.

Estimation of the effect of future changes in precipitation in Japan on pluvial flood damage and the damage reduction effect of mitigation/adaptation measures

This study estimated the effect of changes in the amount of precipitation associated with climate change on pluvial flood damage and the effectiveness of mitigation and adaptation measures throughout Japan. First, the cost of damage caused by pluvial flooding was calculated based on extreme rainfall, assuming a situation in which river levels are high, and rainwater does not drain into the rivers. Additionally, extreme rainfall in future climates was estimated from the output values of five general circulation models. Then, using these figures for extreme rainfall, the cost of pluvial flood damage in future climates was estimated. Improving the maintenance level of inland water drainage facilities and converting buildings to a piloti design were selected as adaptation measures. The results showed that in the Representative Concentration Pathway (RCP) 8.5 scenario, the expected annual damage cost (EADC) in the late 21st-century climate (2081–2100) scenario increases to approximately 2.3 times that of the baseline climate (1981–2000). If climate change is mitigated to RCP 2.6, the EADC in the late 21st-century climate scenario is estimated to be reduced by 28% compared to the EADC in the RCP 8.5 scenario. It is also estimated that the EADC in future climates could be kept lower than in the baseline climate by taking multiple rather than single measures. However, in the RCP 8.5 scenario for the late 21st-century climate, even if multiple adaptation measures are taken, the EADC was estimated to increase by 9% compared to the EADC in the baseline climate.

Surrogate Global Optimization for Identifying Cost‐Effective Green Infrastructure for Urban Flood Control With a Computationally Expensive Inundation Model

AbstractOptimization algorithms and urban inundation models are powerful tools to identify cost‐effective designs of urban green infrastructures such as low‐impact developments (LIDs). Most previous LID design optimization studies are based on one‐dimensional (1D) inundation models, which cannot provide spatial information of flooding. The LID design optimization on two‐dimensional (2D) models or coupled 1D‐2D models was rarely explored due to the expensive computing time. This work investigates the effectiveness of surrogate optimization methods for LID design, which have not been used for the LID design problems. We propose a general LID design optimization framework that searches the optimal LID configurations based on both the spatial flood damage under a series of probable flood events and the life cycle costs (LCCs) of LID. We demonstrate the framework using a case study for an urban catchment with 55 sub‐catchments and 103 LID decision variables. We tested two different surrogate optimization methods designed for high‐dimensional problems: DYnamic COordinate search using Response Surface models (DYCORS) and Trust Region Bayesian Optimization (TuRBO), and one popular non‐surrogate method particle swarm (PSO). The result indicates that: (a) DYCORS is a promising method (significantly faster than TuRBO and PSO) for identifying the optimal LID design to minimize the flood damage cost and LID LCC; (b) Optimized LID design could reduce damage cost by as much as $12.14 million for the urban catchment after eliminating its own LCC compared with no LID implementation; (c) LID is effective in reducing the imperviousness of lands in urban areas.

Green infrastructure for coastal flood protection: The longitudinal impacts of green infrastructure patterns on flood damage

The importance of implementing green infrastructure (GI) for flood protection is supported by multiple substantial cross-sectional analyses. Yet, limited longitudinal research has been conducted which addresses how to maintain and improve the configuration of GI in order to minimize the cost of losses resulting from flooding. Structural damage from devastating storm events has repeatedly imposed substantial financial burdens on local governments in coastal regions. This study longitudinally examines the impacts of changes in GI patterns on flood damage cost in coastal Texas areas. Major flood events in the 36 Texan coastal watershed counties along the Gulf of Mexico were monitored from 2000 to 2017. Along with non-spatially weighted panel data models, we developed an advanced statistical model controlling for spatially correlated errors in flood loss and predicting flood loss with a set of time-series socioeconomic and environmental control variables. The results of the spatial panel data model reveal that long-term maintenance of larger, more irregular, more dispersed, less fragmented, and less connected patterns of GI will help to reduce county-level flood damage costs per capita over time. Most importantly, protecting larger patches within a closer proximity was found to be of the utmost importance for retaining the flood regulation services provided by GI. These findings suggest that planners and natural resource managers should enhance supportive land use policies to preserve existing GI and strategically locate new implementations in order to achieve long-term flood protection.

Rising Seas, Rising Inequity? Communities at Risk in the San Francisco Bay Area and Implications for Adaptation Policy

AbstractIncreasing coastal flooding threatens urban centers worldwide. Projections of physical damages to structures and their contents can characterize the monetary scale of risk, but they lack relevant socioeconomic context. The impact of coastal flooding on communities hinges not only on the cost, but on the ability of households to pay for the damages. Here, we repurpose probabilistic risk assessment to analyze the monetary and social risk associated with coastal flooding in the San Francisco Bay Area for 2020–2060. We show that future coastal flooding could financially ruin a substantial number of households by burdening them with flood damage costs that exceed discretionary household income. We quantify these impacts at the census block group scale by computing the percentage of households without discretionary income, before and after coastal flooding costs. We find that for several coastal communities in San Mateo County more than 50% of households will be facing financial instability, highlighting the need for immediate policy interventions that target existing, socially produced risk rather than waiting for potentially elusive certainty in sea level rise projections. We emphasize that the percentage of financially unstable households is particularly high in racially diverse and historically disadvantaged communities, highlighting the connection between financial instability and inequity. While our estimates are specific to the San Francisco Bay Area, our granular, household‐level perspective is transferable to other urban centers and can help identify the specific challenges that different communities face and inform appropriate adaptation interventions.

Global costs of protecting against sea-level rise at 1.5 to 4.0 °C

Sea levels will rise, even with stringent climate change mitigation. Mitigation will slow the rate of rise. There is limited knowledge on how the costs of coastal protection vary with alternative global warming levels of 1.5 to 4.0 °C. Analysing six sea-level rise scenarios (0.74 to 1.09 m, 50th percentile) across these warming levels, and five Shared Socioeconomic Pathways, this paper quantifies the economic costs of flooding and protection due to sea-level rise using the Dynamic Interactive Vulnerability Assessment (DIVA) modelling framework. Results are presented for World Bank income groups and five selected countries from the present to 2100. Annual sea flood damage costs without additional adaptation are more influenced by socio-economic development than sea-level rise, indicating that there are opportunities to control risk with development choices. In contrast, annual sea dike investment costs are more dependent on the magnitude of sea-level rise. In terms of total costs with adaptation, upper middle, low middle and low income groups are projected to have higher relative costs as a proportion of GDP compared with high income groups. If low income countries protected now, flood costs could be reduced after 2050 and beyond. However, without further adaptation, their coasts will experience growing risks and costs leaving them increasingly reliant on emergency response measures. Without mitigation or adaptation, greater inequalities in damage costs between income groups could result. At country level, annual sea flood damage costs without additional adaptation are projected to rapidly increase with approximately 0.2 m of sea-level rise, leaving limited time to plan and adapt.

Analysis of pluvial flood damage costs in residential buildings – A case study in Malmö

Pluvial flood damage to residential buildings causes a significant part of direct tangible flood losses. In this study, we investigate the non-hazard variables and sewer system types in relation to damage costs in the city of Malmö, Sweden. A comprehensive data set of around 1000 records of direct damage to residential buildings from a cloudburst event on 31 August 2014 in Malmö, Sweden has been analysed at property scale with no lumping together of data. The results show that properties connected to combined sewer systems are much more exposed to pluvial flood damage than properties connected to separated sewer systems, with the ratio of the number of claims being close to three. The analysis of building-specific variables shows no clear statistical relationships to the damage costs. To further the understanding of damage costs caused by urban pluvial flooding, it is necessary to extend the group of explanatory variables to include information about the socio-economic background of households, the actual value of assets in basements and the precautionary measures taken by house owners.

Evaluation of flood damage reduction throughout Japan from adaptation measures taken under a range of emissions mitigation scenarios

This study aimed to evaluate the impact of climate change on flood damage and the effects of mitigation measures and combinations of multiple adaptation measures in reducing flood damage. The inundation depth was calculated using a two-dimensional unsteady flow model. The flood damage cost was estimated from the unit evaluation value set for each land use and prefectures and the calculated inundation depth distribution. To estimate the flood damage in the near future and the late twenty-first century, five global climate models were used. These models provided daily precipitation, and the change of the extreme precipitation was calculated. In addition to the assessment of the impacts of climate change, certain adaptation measures (land-use control, piloti building, and improvement of flood control level) were discussed, and their effects on flood damage cost reduction were evaluated. In the case of the representative concentration pathway (RCP) 8.5 scenario, the damage cost in the late twenty-first century will increase to 57% of that in the late twentieth century. However, if mitigation measures were to be undertaken according to RCP2.6 standards, the increase of the flood damage cost will stop, and the increase of the flood damage cost will be 28% of that in the late twentieth century. By implementing adaptation measures in combination rather than individually, it is possible to keep the damage cost in the future period even below that in the late twentieth century. By implementing both mitigation and adaptation measures, it is possible to reduce the flood damage cost in the late twenty-first century to 69% of that in the late twentieth century.

Unravelling the Importance of Uncertainties in Global-Scale Coastal Flood Risk Assessments under Sea Level Rise

Global scale assessments of coastal flood damage and adaptation costs under 21st century sea-level rise are associated with a wide range of uncertainties, including those in future projections of socioeconomic development (shared socioeconomic pathways (SSP) scenarios), of greenhouse gas concentrations (RCP scenarios), and of sea-level rise at regional scale (RSLR), as well as structural uncertainties related to the modelling of extreme sea levels, data on exposed population and assets, and the costs of flood damages, etc. This raises the following questions: which sources of uncertainty need to be considered in such assessments and what is the relative importance of each source of uncertainty in the final results? Using the coastal flood module of the Dynamic Interactive Vulnerability Assessment modelling framework, we extensively explore the impact of scenario, data and model uncertainties in a global manner, i.e., by considering a large number (>2000) of simulation results. The influence of the uncertainties on the two risk metrics of expected annual damage (EAD), and adaptation costs (AC) related to coastal protection is assessed at global scale by combining variance-based sensitivity indices with a regression-based machine learning technique. On this basis, we show that the research priorities in terms of future data/knowledge acquisition to reduce uncertainty on EAD and AC differ depending on the considered time horizon. In the short term (before 2040), EAD uncertainty could be significantly decreased by 25 and 75% if the uncertainty of the translation of physical damage into costs and of the modelling of extreme sea levels could respectively be reduced. For AC, it is RSLR that primarily drives short-term uncertainty (with a contribution ~50%). In the longer term (>2050), uncertainty in EAD could be largely reduced by 75% if the SSP scenario could be unambiguously identified. For AC, it is the RCP selection that helps reducing uncertainty (up to 90% by the end of the century). Altogether, the uncertainty in future human activities (SSP and RCP) are the dominant source of the uncertainty in future coastal flood risk.

Annual flood damage influenced by El Niño in the Kan River basin, Iran

Abstract. Although many studies have explored the effect of teleconnection patterns on floods, few investigations have focused on the assessment of expected flood damage under such large-scale atmospheric signals. This study aims to determine the effect of the most emblematic teleconnection, El Niño, on the expected damage due to floods with short return periods in the Kan River basin, Iran. To determine the flood damage costs, the median of annual precipitation changes (ΔP) during El Niño conditions was used, although ΔP cannot necessarily be transferred to extreme values. Then the flooded area was determined under the increased rainfall due to El Niño for 5-, 10-, and 50-year return periods. The results showed that El Niño has increased the annual precipitation by 12.2 %. Flood damage assessment using damage–depth curves showed that the relative increase in expected damage during El Niño conditions is much higher for short return period floods than that for long return period floods. In general, a 12.2 % increase in the annual precipitation would increase the damage by 1671 % and 176 %, respectively, for the return periods of 5 and 10 years. However, in the case of a 50-year flood, this increased percentile decreased to 52 %. These results indicate the importance of small flood events in flood management planning during El Niño.

On the complexity of solving a decision problem with flow-depending costs: The case of the IJsselmeer dikes

We consider a fundamental integer programming (IP) model for cost–benefit analysis and flood protection through dike building in the Netherlands, due to Zwaneveld and Verweij (2017). Experimental analysis with data for the IJsselmeer shows that the solution of the linear programming relaxation of the IP model is integral. This naturally leads to question whether the polytope associated to the IP is always integral.In this paper we first give a negative answer to this question by proving the non-integrality of the polytope. Secondly, we establish natural conditions that guarantee the linear programming relaxation of the IP model is integral. We show that these conditions are indeed satisfied by the recent data on flood probabilities, damage and investment costs of IJsselmeer. Finally, we show that the IP model can be solved in polynomial time when the number of dike segments, or the number of feasible barrier heights, are bounded.

Flood damage cost estimation in 3D based on an indicator modelling framework

Flooding and other natural disasters pose risks to cities and residential homes, and these are set to increase in the face of climate change. Single-family residential buildings are of particular interest because they are difficult to insure and often highlight wealth discrepancies in society in the wake of natural disasters. Calculating building replacement cost based on a specific natural disaster is of interest to municipalities and city planners who are working to prepare their cities for potential future costs of recovery. There are models designed by flood modellers, and there are models designed by city planners. This paper presents a novel Indicator Modelling Framework (IMF) by bringing together a model from the flooding domain (HAZUS) and a model from the geospatial application domain (e.g. CityGML) and weaving them together. The weaving process automatically calculates the building replacement cost for buildings based on a flood scenario as well as generates domain-specific metadata. The weaving process capitalizes on the strengths of both models, and future work will focus on weaving between models in other domains.