Expected Flood Damage Research Articles

Assessing 40 Years of Flood Risk Evolution at the Micro-Scale Using an Innovative Modeling Approach: The Effects of Urbanization and Land Planning

The present work is aimed at assessing the change in time of flood risk as a consequence of landscape modifications. The town of San Donà di Piave (Italy) is taken as a representative case study because, as most parts of the North Italy floodplains, it was strongly urbanized and anthropized in the last several decades. As a proxy for flood risk, we use flood damage to residential buildings. The analysis is carried out at the local scale, accounting for changes to single buildings; GIS data such as high-resolution topography, technical maps, and aerial images taken over time are used to track how the landscape evolves over time, both in terms of urbanized areas and of hydraulically relevant structures (e.g., embankments). Flood hazard is determined using a physics-based, finite element hydrodynamic code that models in a coupled way the flood routing within the Piave River, the formation of levee failures, and the flooding of adjacent areas. The expected flood damage to residential buildings is estimated using an innovative method, recently proposed in the literature, which allows estimating how the damage evolves during a single flood event. The decade-scale change in the expected flood damage reveals the detrimental effect of urbanization, with flood risk growing at the pace of a fraction of urbanized areas. The within-event time evolution of the flood damage, i.e., how it progresses in the course of past or recent flood events, reflects changes in the hydrodynamic process of flooding. The general methodology used in the present work can be viewed as a promising technique to analyze the effects on the flood risk of past landscape evolution and, more importantly, a valuable tool toward an improved, well-informed, and sustainable land planning.

“Can seawalls help American cities adapt to coastal flooding?”

PurposeThis study aims to combine information about sea level rise (SLR), the probability distribution of storm surge, a flood damage function and the value of property by elevation along the coast of selected cities to measure expected flood damage. The selected six cities all have nearby long-term tidal stations that can be used to estimate the probability distribution of floods. The model is calibrated to each city. The study then compares the cost of building higher seawalls today along the coast versus the benefit of each wall (the reduction in expected flood damage).Design/methodology/approachThe combination of coastal storms and SLR has led to extensive flood damage across American cities. This study creates a simple generic model that evaluates whether seawalls would be effective at addressing this flooding problem. The paper develops an approach that readily measures the expected flood benefits and costs of alternative coastal seawalls. The approach takes account of near term SLR and the probability distribution of storm surge. The model finds seawalls are effective only in cities where many buildings are in the 25-year flood plain.FindingsCities with many buildings built on land below 2 m in elevation (the 25-year flood plain) have high expected flood damage from storms and SLR. Cities which already have many buildings in this flood plain would benefit from seawalls. Assuming seawalls are built above the high tide line, the optimal wall height that maximizes net benefits is between 0.9 to 1.2 m. These relatively low seawalls block 70%–83% of expected flood damage in these cities. Fair flood insurance is the least cost strategy for handling the remaining damages that overtop the optimal seawalls.Research limitations/implicationsThe analysis evaluates whether or not to build a seawall the length of each city at high tide lines. However, the analysis also finds several long stretches of coast in two cities where a wall is not warranted because there are few vulnerable buildings. Future analyses should consider seawalls in more spatially detailed sections of each city. Each section could then be analyzed independently. Whether or not more complex hydrodynamic models are needed to evaluate coastal resilience planning should also be explored. Alternative solutions such as planned retreat and nature-based solutions should be compared with seawalls in future studies as well.Practical implicationsCities should be careful to avoid development in the 25-year flood plain because of high expected flood damage. Cities that have low elevation areas subject to frequent flooding should consider seawalls to reduce frequent flooding. Because they are very costly and have low expected benefits, high walls that can stop a one-hundred-year storm are generally not worth building.Social implicationsThe analysis reveals that the most important factor determining the vulnerability of cities along the eastern coastline of the USA is the number of buildings built below 2 m in elevation (the 25-year flood plain). Cities should use zoning to discourage further development in the 25-year flood plain. Cities which already have many buildings in this flood plain would benefit from city-wide seawalls. Assuming these walls are built at mean high-high tide, the optimal height of current seawalls should be relatively modest – averaging about 0.9–1.2 m above ground. Using fair insurance for the remaining risk is less expensive than building taller walls. In particular, the cost of seawalls that protect against a major hurricane surge are over three times the expected benefit and should not be built. As decades pass and observed sea level progresses, seawalls and the boundary of the 25-year flood plain should be reevaluated.Originality/valueThis paper develops a coastal flood model that combines SLR and the probability distribution of storm surges with the value of property by elevation to estimate the expected damage from storm surge. The model is relatively easy to calibrate making it a practical tool to guide city flood planning. The authors illustrate what insights such a model gives about coastal resilience to flooding across six cities along the Eastern US coastline.

Evaluating the Risk and Complexity of Pluvial Flood Damage in the U.S.

Flood hazard in the U.S. is typically separated into two categories: storm surge and inland. Inland flooding is frequently represented as fluvial, stemming from overflow of rivers and streams. However, significant inland flood risk also exists in the form of pluvial flooding, resulting from ponding of water, and often occurring due to insufficient drainage in urban areas. Pluvial flood risk can be complex to model and is often not shown on floodplain maps, leading to significant uninsured risk. While pluvial and fluvial flooding are sometimes lumped together for purposes of modeling, insurance, and risk management, we hypothesize that key differences exist in damage associated with these types of inland flooding. We investigate and quantify these differences through study of three datasets: (i) Tropical cyclone (TC) flood insurance claims; (ii) non-Tropical Cyclone (non-TC) flood insurance claims; and (iii) Hurricane Harvey flood insurance claims in the Houston area. From our data analyses, we find that fluvial claims involve greater damage on average and are more likely to occur within the mapped Special Flood Hazard Area (i.e., 100-year floodplain) than pluvial claims. However, pluvial flooding is more frequent overall being the cause of 74% of TC and 60% of non-TC flood insurance claims in the U.S. TC floods have a higher percentage of pluvial flood insurance claims and higher average pluvial damage than non-TC floods. Analysis of Hurricane Harvey claims shows that zip codes with higher-than-expected losses tend to have high percentages of pluvial claims. Pluvial flooding and its local nuances exhibit the potential to reduce the accuracy of catastrophe models of expected flood damage.

Poorly adapted but nothing to lose? A study on the flood risk – income relationship with a focus on low-income households

Flood risk may differ across income levels. In this paper, I employ unique survey data from more than 8000 households in Germany to derive an integrated flood risk indicator that accounts for local flood exposure, assets-at-risk, housing characteristics, and household coping behavior. The results suggest that low-income households, due to their smaller homes and less valuable assets, face lower monetary flood risks than wealthier households despite the former’s limited capacity to implement protection measures and purchase insurance. Relative to the available financial budget, however, expected flood damage weighs higher for low-income households.

Flood Risk Assessment for Coastal Cities Considering Sea Level Rise due to Climate Change

The purpose of this study was to present disaster prevention performance targets for Korean coastal cities, given the rise in sea level due to climate change. The disaster prevention performance targets for coastal cities are used to assess flood risk caused by increased sea levels. The proposed disaster prevention performance targets give additional consideration for design tide level or design flood level, which are design factors for hydraulic structures located along the coast. The rate of sea level rise in the West Sea was 0.61 ㎝/year. It was the fastest rise rate of all of Korea's seas. The sea level rise rate in the East Sea was calculated at 0.58 ㎝/year. This study also quantitatively confirmed that flood damage increases according to sea level rise using the United States' Environmental Protection Agency-Storm Water Management Model (EPA-SWMM). This study suggested a method for setting the disaster prevention performance targets of expected flood damage in coastal cities. Therefore, suggested disaster prevention performance targets should be highly specialized for coastal cities. However, sea level rise and rainfall are key factors that cause floods. Therefore, further research on disaster prevention in coastal cities should be carried out to consider the combined effects of sea level rise and rainfall.

Floods, flood policies and changes in welfare and inequality: Evidence from Germany

Floods in Germany have caused significant economic damage and are expected to become more frequent. The economic damage expected as a result of floods will affect households differently across income levels. A method, rooted in economic theory, is proposed to estimate changes in household welfare and income inequality resulting from expected flood damage. It is found that welfare losses after floods disproportionately harm low income households and increase inequality by 0.14%. Families with dependent children and householders of retirement age in the lowest income quartile are the most affected. In order to collect additional resources to cover the cost of the financial relief, the of additional income, real estate and energy taxes are investigated. These instruments yield a reduction in income inequality. It is also shown that rewarding investment in mitigation and insurance, and supporting low income households can be jointly achieved when re-allocating additional energy-tax revenues.

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.

A Flood Damage Allowance Framework for Coastal Protection With Deep Uncertainty in Sea Level Rise.

Deep uncertainty describes situations when there is either ignorance or disagreement over (1) models used to describe key system processes and (2) probability distributions used to characterize the uncertainty of key variables and parameters. Future projections of Antarctic ice sheet (AIS) mass loss remain characterized by deep uncertainty. This complicates decisions on long‐lived coastal protection projects when determining what margin of safety to implement. If the chosen margin of safety does not properly account for uncertainties in sea level rise, the effectiveness of flood protection could decrease over time, potentially putting lives and properties at a greater risk. To address this issue, we develop a flood damage allowance framework for calculating the height of a flood protection strategy needed to ensure that a given level of financial risk is maintained. The damage allowance framework considers decision maker preferences such as planning horizons, protection strategies, and subjective views of AIS stability. We use Manhattan—with the population and built environment fixed in time—to illustrate how our framework could be used to calculate a range of damage allowances based on multiple plausible scenarios of AIS melt. Under high greenhouse gas emissions, we find that results are sensitive to the selection of the upper limit of AIS contributions to sea level rise. Design metrics that specify financial risk targets, such as expected flood damage, allow for the calculation of avoided flood damages (i.e., benefits) that can be combined with estimates of construction cost and then integrated into existing financial decision‐making approaches (e.g., benefit‐cost analysis).

Conditional Value-at-Risk for Nonstationary Streamflow and Its Application for Derivation of the Adaptive Reservoir Flood Limited Water Level

AbstractThe existing risk-based approaches for quantifying expected flood damage loss may not be suitable in the changing environment when streamflow becomes nonstationary. Conditional value-at-ris...

Rival framings: A framework for discovering how problem formulation uncertainties shape risk management trade‐offs in water resources systems

AbstractManaging water resources systems requires coordinated operation of system infrastructure to mitigate the impacts of hydrologic extremes while balancing conflicting multisectoral demands. Traditionally, recommended management strategies are derived by optimizing system operations under a single problem framing that is assumed to accurately represent the system objectives, tacitly ignoring the myriad of effects that could arise from simplifications and mathematical assumptions made when formulating the problem. This study illustrates the benefits of a rival framings framework in which analysts instead interrogate multiple competing hypotheses of how complex water management problems should be formulated. Analyzing rival framings helps discover unintended consequences resulting from inherent biases of alternative problem formulations. We illustrate this on the monsoonal Red River basin in Vietnam by optimizing operations of the system's four largest reservoirs under several different multiobjective problem framings. In each rival framing, we specify different quantitative representations of the system's objectives related to hydropower production, agricultural water supply, and flood protection of the capital city of Hanoi. We find that some formulations result in counterintuitive behavior. In particular, policies designed to minimize expected flood damages inadvertently increase the risk of catastrophic flood events in favor of hydropower production, while min‐max objectives commonly used in robust optimization provide poor representations of system tradeoffs due to their instability. This study highlights the importance of carefully formulating and evaluating alternative mathematical abstractions of stakeholder objectives describing the multisectoral water demands and risks associated with hydrologic extremes.

Large-scale application of the flood damage model RAilway Infrastructure Loss (RAIL)

Abstract. Experience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than EUR 100 million due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate (1) the expected structural flood damage and (2) the resulting repair costs of railway infrastructure due to a 30-, 100- and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed against the background of climate change and possibly resulting changes in flood risk. The findings indicate that the RAIL model is capable of supporting decision-making in risk management by providing comprehensive risk information on the catchment level. It is furthermore demonstrated that an increased risk aversion of the railway operator has a marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies.

Homeowners’ perceptions of property-level flood risk adaptation (PLFRA) measures: the case of the summer 2007 flood event in England

© 2015 WIT Press. Flood events have far-reaching consequences, not only in economic or financial terms but also in social and health-related impacts. There is a growing body of research that suggests that property-level flood risk adaptation (PLFRA) measures have the potential to benefit homeowners by reducing the impact of flooding on households. Emphasis has, therefore, been placed on the implementation of PLFRA measures, and yet despite this, the take-up among the at-risk residents in England is low. One of the reasons identified in the literature is that homeowners do not clearly recognise the benefits of the measures. This research uses a survey of households affected by the summer 2007 flood event in England to investigate the perception of homeowners in connection with the benefits of PLFRA measures. The results highlight that there is a consensus among respondents that implementing adaptation measures has the potential to reduce health-related flood impacts such as worrying, stress and strain between families. However, there was a high level of uncertainty with regard to potential financial benefits from investing in adaptation measures, in the form of premium reduction by insurers. It was evident from the analysis that knowledge of the frequency of future flood events and expected flood damage rated highly among the factors perceived by homeowners to influence the uptake of PLFRA measures. Furthermore, the results show that there is a wide range of opinion among the respondents as to who is responsible for protecting homes against flood risk. For instance, the government flood protection scheme has the potential to provide a confusing message to floodplain residents as to whose responsibility it is to protect properties against flood risk. It is, therefore, recommended that at-risk population should be made aware of the limits of the responsibilities of other stakeholders in the domain of flood risk management at household levels. However, it is anticipated that the introduction of the new UK flood insurance scheme, Flood Re, may help to bring more clarity. There is a need to increase the motivation of homeowners to invest in PLFRA measures, which could be achieved through a range of actions, including the provision of subsidies and incentives, which would help in promoting more sustainable behaviour.

Risk-based zoning for urbanizing floodplains.

Urban floodplain development brings economic benefits and enhanced flood risks. Rapidly growing cities must often balance the economic benefits and increased risks of floodplain settlement. Planning can provide multiple flood mitigation and environmental benefits by combining traditional structural measures such as levees, increasingly popular landscape and design features (green infrastructure), and non-structural measures such as zoning. Flexibility in both structural and non-structural options, including zoning procedures, can reduce flood risks. This paper presents a linear programming formulation to assess cost-effective urban floodplain development decisions that consider benefits and costs of development along with expected flood damages. It uses a probabilistic approach to identify combinations of land-use allocations (residential and commercial development, flood channels, distributed runoff management) and zoning regulations (development zones in channel) to maximize benefits. The model is applied to a floodplain planning analysis for an urbanizing region in the Baja Sur peninsula of Mexico. The analysis demonstrates how (1) economic benefits drive floodplain development, (2) flexible zoning can improve economic returns, and (3) cities can use landscapes, enhanced by technology and design, to manage floods. The framework can incorporate additional green infrastructure benefits, and bridges typical disciplinary gaps for planning and engineering.

Optimal prioritisation of watershed management measures for flood risk mitigation on a watershed scale

AbstractWatershed management includes methods to create, enhance, and maintain vegetation to reduce run‐off and provide flood control in the watershed. The assignment of priority for watershed management measures requires the use of mathematical techniques to attain the most suitable strategies. In the present study, a framework was presented for assigning the optimal combinations of watershed management measures based on simulation‐based optimisation approach. For this purpose, a one‐dimensional hydrodynamic model was used to calculate the potential damages of different flood scenarios under various combinations of watershed management measures and was coupled with the NSGA‐II multi‐objective optimisation model to provide the optimal Pareto solutions between two conflicting objectives of minimising the investment costs of flood mitigation measures and the expected flood damages of the watershed. The proposed model was then applied to a small watershed in the centre of Iran as a case study, and the optimal trade‐off solutions were calculated for flood risk mitigation. Using these trade‐offs, for each level of funding, decision makers can select the optimal combination of watershed management measures considering decision criteria.

Optimal management of the flood risks of floodplain development

This paper presents a model of the problem on floodplain development, exploring the conditions that are both necessary and sufficient for development to be optimal. The model is calibrated for a particular catchment, the Ouse catchment in the United Kingdom, and is used both to estimate the expected impact of floodplain development and to explore the impact of alternative policy instruments. We find that the use of price-based instruments that signal the expected flood damage cost of floodplain development has the potential to lead to outcomes close to the social optimum. The finding is robust to two types of uncertainty: model error about the relation between precipitation and flood-risk and measurement error about the benefits of developed floodplains.

Optimal design of flood-control multi-reservoir system on a watershed scale

Flood events have the highest damage costs and losses among natural hazards. There are different types of measures to mitigate flood damage costs and their negative consequences. Application of flood-control reservoirs or detention dams, as one of the main measures, may decrease devastating flood effects or even may cause to intensify flood damages in the watershed by a poor design with tremendous construction costs. Optimal design of a flood-control multi-reservoir system can simultaneously minimize investment costs of constructions and potential flood damage costs. This study proposes a simulation-based optimization approach to optimize the design of multi-reservoirs for flood control in the watershed by coupling the MIKE-11 hydrodynamic model and the NSGA-II multi-objective optimization model. The present approach provides the Pareto optimal solutions between two conflict objectives of minimizing total investment costs and the expected flood damage costs in the watershed. Application of the proposed model for a small watershed in central part of Iran as a case study shows that optimal designs of multi-reservoir systems can efficiently reduce construction costs, flood peaks and their corresponding damage costs at the downstream reaches of the basin.

Multi-objective optimisation of cost–benefit of urban flood management using a 1D2D coupled model

This paper presents a multi-objective optimisation (MOO) tool for urban drainage management that is based on a 1D2D coupled model of SWMM5 (1D sub-surface flow model) and BreZo (2D surface flow model). This coupled model is linked with NSGA-II, which is an Evolutionary Algorithm-based optimiser. Previously the combination of a surface/sub-surface flow model and evolutionary optimisation has been considered to be infeasible due to the computational demands. The 1D2D coupled model used here shows a computational efficiency that is acceptable for optimisation. This technological advance is the result of the application of a triangular irregular discretisation process and an explicit finite volume solver in the 2D surface flow model. Besides that, OpenMP based parallelisation was employed at optimiser level to further improve the computational speed of the MOO tool. The MOO tool has been applied to an existing sewer network in West Garforth, UK. This application demonstrates the advantages of using multi-objective optimisation by providing an easy-to-comprehend Pareto-optimal front (relating investment cost to expected flood damage) that could be used for decision making processes, without repeatedly going through the modelling-optimisation stage.

Ranking solutions of multi-objective reservoir operation optimization models using multi-criteria decision analysis

In this paper, ELECTRE-TRI method has been used for ranking the optimal solutions of Non-dominated Sorting Genetic Algorithm-II (NSGA-II) which has been developed for multi-objective operation optimization of a cascade system of reservoirs. In the multi-objective optimization model, flood control and water supply have been considered as short-term and long-term objectives, respectively. The flood control objective function has been formulated to minimize the expected flood damages in different flooding months. A short-term reservoir optimization model which provides the optimal hourly releases during floods has been developed and linked to a flood damage estimation model. The water supply objective function minimizes water deficit damages in agricultural areas. The losses associated with deficit in supplying agricultural water demands have been calculated based on crop yield responses to deficit irrigation. Selection of the most practical solution among the optimal Pareto set of solutions, which is addressed using ELECTRE-TRI method, is a challenging issue. The proposed methodology provides an opportunity for further incorporation of decision makers’ preferences in ranking the NSGA-II optimal set of solutions. The results of applying the developed models to the cascade system of the Dez and Bakhtiari Reservoirs in southwest of Iran show that ELECTRE-TRI method has the ability to rank the non-dominated solutions of the multi-objective operation optimization model and provides a suitable framework for considering the preferences of decision makers (DMs).

Implementation issues for total risk calculation for groups of sites

For flood events in a large territory, different locations will have their own distinct probability distribution for flooding. However, if these locations are linked through shared meteorological and/or hydrological processes, then these probability distributions are likely to be correlated. This implies that simple summation of calculation results for flood risks or expected flood damage for the separate locations will give a distorted view of the risk or expected damage for the region as a whole. The question examined in this paper is the extension of the concept of a link between a once in N years event and the resulting damage from one dimension to multiple dimensions. Copulas are shown to represent this link.

Uncertainty in flood damage estimation*

The aim of this article is to incorporate uncertainty into the currently used method for estimating the economic damage of floods in the Netherlands. Using a high‐water information system, this so‐called Standard Method computes the expected flood damage per damage category on the basis of the number of objects subject to flooding, the maximum damage per object, and the relative damage depending on the water depth. Using a probabilistic approach, the Standard Method is extended by taking account of the uncertainties in the maximum damage per object (maximum possible damage per unit object; e.g., house, production facility, meter road) and the damage function (describing the proportion of the maximum damage incurred to an object due to flooding as a function of the water depth). In estimating the damage in a flooded area, it is also important to take account of the spatial dependence between flood damages at different locations. For this purpose, the following three types of spatial dependence are considered: complete spatial dependence, spatial independence, and partial spatial dependence (for which the damage functions are completely dependent for independent water‐depth classes). Using Monte‐Carlo simulation, probability distributions of the flood damage are determined. The new uncertainty‐based model for predicting flood damage is applied in a case study and the results of a sensitivity analysis are reported.