Expected Annual Damage Research Articles

Flood damage and risk assessment for urban area in Malaysia

Abstract In recent years, flood risk map has been widely accepted as a tool for flood mitigation. The risk of flooding is normally illustrated in terms of its hazard (flood inundation maps), while vulnerability emphasizes the consequences of flooding. In developing countries, published studies on flood vulnerability assessment are limited, especially on flood damage. This paper attempts to establish a flood damage and risk assessment framework for Segamat town in Johor, Malaysia. A combination of flood hazard (flood characteristics), exposure (value of exposed elements), and vulnerability (flood damage function curve) were used for estimating the flood damage. The flood depth and areal extent were obtained from flood modeling and mapping using HEC-HMS/RAS and Arc GIS, respectively. Expected annual damage (EAD) for residential areas (50,112 units) and commercial areas (9,318 premises) were RM12.59 million and RM2.96 million, respectively. The flood hazard map shows that Bandar Seberang area (46,184 properties) was the most affected by the 2011 flood. The flood damage map illustrates similar patterns, with Bandar Seberang suffering the highest damage. The damage distribution maps are useful for reducing future flood damage by identifying properties with high flood risk.

The effects of changing land use and flood hazard on poverty in coastal Bangladesh

The construction of polders in the coastal region of Bangladesh has significantly modified the patterns of flooding, as well as leading to significant land use/land cover (hereinafter, LULC) changes. The impact of LULC change and flooding on poverty is complex and poorly understood. This study presents a spatiotemporal appraisal of poverty in relation to LULC change and pluvial flood risk in the south western embanked area of Bangladesh. A combination of logistic regression (LR), cellular automata (CA), and Markov Chain models were utilised to predict future LULC based on historical data. Flood risk assessment was performed at present and for future LULC scenarios. A spatial regression model was developed, incorporating multiple parameters to estimate the wealth index (WI) for present-day and future scenarios. In the study area, agricultural lands reduced from 34 % in 2005 to 8% in 2010, while aquaculture land cover increased from 17 % to 39 % during the same time. The rate of LULC change was relatively low between 2010 and 2019. Based on the recent trend, LULC was predicted for the year 2030. Flood risk was positively correlated with LULC and the expected annual damage (EAD) was estimated at $903 million in 2005, which is likely to increase to $2096 million by 2030, considering changes in LULC scenarios. The analysis further showed that the EAD and LULC change were negatively associated with the WI. Despite consistent national GDP growth in Bangladesh in recent years, the rate of increase of WI is likely to be low in the future because flood risk and patterns of LULC change have a negative effect on WI.

Socio-Economic Assessment of Green Infrastructure for Climate Change Adaptation in the Context of Urban Drainage Planning

Green infrastructure (GI) contributes to improve urban drainage and also has other societal and environmental benefits that grey infrastructure usually does not have. Economic assessment for urban drainage planning and decision making often focuses on flood criteria. This study presents an economic assessment of GI based on a conventional cost-benefit analysis (CBA) that includes several benefits related to urban drainage (floods, combined sewer overflows and waste water treatment), environmental impacts (receiving water bodies) and additional societal and environmental benefits associated with GI (air quality improvements, aesthetic values, etc.). Benefits from flood damage reduction are monetized based on the widely used concept of Expected Annual Damage (EAD) that was calculated using a 1D/2D urban drainage model together with design storms and a damage model based on tailored flood depth–damage curves. Benefits from Combined Sewer Overflows (CSO) damage reduction were monetized using a 1D urban drainage model with continuous rainfall simulations and prices per cubic meter of spilled combined sewage water estimated from literature; other societal benefits were estimated using unit prices also estimated from literature. This economic assessment was applied to two different case studies: the Spanish cities of Barcelona and Badalona. The results are useful for decision making and also underline the relevancy of including not only flood damages in CBA of GI.

The role of spatial dependence for large-scale flood risk estimation

Abstract. Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100 % for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments.

Climatic and socioeconomic controls of future coastal flood risk in Europe

Rising extreme sea levels (ESLs) and continued socioeconomic development in coastal zones will lead to increasing future flood risk along the European coastline. We present a comprehensive analysis of future coastal flood risk (CFR) for Europe that separates the impacts of global warming and socioeconomic development. In the absence of further investments in coastal adaptation, the present expected annual damage (EAD) of €1.25 billion is projected to increase by two to three orders of magnitude by the end of the century, ranging between 93 and €961 billion. The current expected annual number of people exposed (EAPE) to coastal flooding of 102,000 is projected to reach 1.52–3.65 million by the end of the century. Climate change is the main driver of the future rise in coastal flood losses, with the importance of coastward migration, urbanization and rising asset values rapidly declining with time. To keep future coastal flood losses constant relative to the size of the economy, flood defence structures need to be installed or reinforced to withstand increases in ESLs that range from 0.5 to 2.5 m. Climate change is the main driver for future coastal flood risk in Europe. However, in the absence of increased flood protection, damages may rise by two to three orders of magnitude by the end of the century.

Methodology for the damage assessment of vehicles exposed to flooding in urban areas

Within urban areas, humans carry out a great diversity of activities, and some of them require the use of vehicles. Floods, especially in urban areas, can generate significant tangible direct damages to vehicles themselves and to the urban elements in case of loss of stability and collision, which cannot be dismissed. In this paper, after a state‐of‐the‐art review on damage curves for vehicles, a methodology to assess the direct economic impact for vehicles exposed to flooding has been described, and applied within a study carried out in the framework of the BINGO H2020 EU Project. Only three different studies focused on damages to vehicles in contact with floodwater have been found. Contrasting damage curves for vehicles are found when comparing the three approaches, however, the ones proposed by the U.S. Army Corps of Engineers (USACE) offer a high level of completeness and accuracy. Moreover, USACE's development is the most current research and all the steps for the development of the damage curves are comprehensively described. Finally, after the description of a detailed methodology for flood damage mapping for vehicles, a procedure to evaluate the Expected Annual Damage for vehicles is offered.

Comparing Methods of Calculating Expected Annual Damage in Urban Pluvial Flood Risk Assessments

Estimating the expected annual damage (EAD) due to flooding in an urban area is of great interest for urban water managers and other stakeholders. It is a strong indicator for a given area showing how vulnerable it is to flood risk and how much can be gained by implementing e.g., climate change adaptation measures. This study identifies and compares three different methods for estimating the EAD based on unit costs of flooding of urban assets. One of these methods was used in previous studies and calculates the EAD based on a few extreme events by assuming a log-linear relationship between cost of an event and the corresponding return period. This method is compared to methods that are either more complicated or require more calculations. The choice of method by which the EAD is calculated appears to be of minor importance. At all three case study areas it seems more important that there is a shift in the damage costs as a function of the return period. The shift occurs approximately at the 10 year return period and can perhaps be related to the design criteria for sewer systems. Further, it was tested if the EAD estimation could be simplified by assuming a single unit cost per flooded area. The results indicate that within each catchment this may be a feasible approach. However the unit costs varies substantially between different case study areas. Hence it is not feasible to develop unit costs that can be used to calculate EAD, most likely because the urban landscape is too heterogeneous.

Assessing Financial Loss due to Pluvial Flooding and the Efficacy of Risk-Reduction Measures in the Residential Property Sector

A novel quantitative risk assessment for residential properties at risk of pluvial flooding in Eindhoven, The Netherlands, is presented. A hydraulic model belonging to Eindhoven was forced with low return period rainfall events (2, 5 and 10-year design rainfalls). Three scenarios were analysed for each event: a baseline and two risk-reduction scenarios. GIS analysis identified areas where risk-reduction measures had the greatest impact. Financial loss calculations were carried out using fixed-threshold and probabilistic approaches. Under fixed-threshold assessment, per-event Expected Annual Damage (EAD) reached €38.2 m, with reductions of up to €454,000 resulting from risk-reduction measures. Present costs of flooding reach €1.43bn when calculated over a 50-year period. All net-present value figures for the risk-reduction measures are negative. Probabilistic assessment yielded EAD values up to more than double those of the fixed-threshold analysis which suggested positive net-present value. To the best of our knowledge, the probabilistic method based on the distribution of doorstep heights has never before been introduced for pluvial flood risk assessment. Although this work suggests poor net-present value of risk-reduction measures, indirect impacts of flooding, damage to infrastructure and the potential impacts of climate change were omitted. This work represents a useful first step in helping Eindhoven prepare for future pluvial flooding. The analysis is based on software and tools already available at the municipality, eliminating the need for software upgrading or training. The approach is generally applicable to similar cities.

Editorial: steps towards global flood risk modelling

Editorial: steps towards global flood risk modelling

Assessment of the effectiveness of flood adaptation strategies for HCMC

Abstract. Coastal cities are vulnerable to flooding, and flood risk to coastal cities will increase due to sea-level rise. Moreover, Asian cities in particular are subject to considerable population growth and associated urban developments, increasing this risk even more. Empirical data on vulnerability and the cost and benefits of flood risk reduction measures are therefore paramount for sustainable development of these cities. This paper presents an approach to explore the impacts of sea-level rise and socio-economic developments on flood risk for the flood-prone District 4 in Ho Chi Minh City, Vietnam, and to develop and evaluate the effects of different adaptation strategies (new levees, dry- and wet proofing of buildings and elevating roads and buildings). A flood damage model was developed to simulate current and future flood risk using the results from a household survey to establish stage–damage curves for residential buildings. The model has been used to assess the effects of several participatory developed adaptation strategies to reduce flood risk, expressed in expected annual damage (EAD). Adaptation strategies were evaluated assuming combinations of both sea-level scenarios and land-use scenarios. Together with information on costs of these strategies, we calculated the benefit–cost ratio and net present value for the adaptation strategies until 2100, taking into account depreciation rates of 2.5% and 5%. The results of this modelling study indicate that the current flood risk in District 4 is USD 0.31 million per year, increasing up to USD 0.78 million per year in 2100. The net present value and benefit–cost ratios using a discount rate of 5 % range from USD −107 to −1.5 million, and from 0.086 to 0.796 for the different strategies. Using a discount rate of 2.5% leads to an increase in both net present value and benefit–cost ratio. The adaptation strategies wet-proofing and dry-proofing generate the best results using these economic indicators. The information on different strategies will be used by the government of Ho Chi Minh City to determine a new flood protection strategy. Future research should focus on gathering empirical data right after a flood on the occurring damage, as this appears to be the most uncertain factor in the risk assessment.

Annualised risk analysis approach to recommend appropriate level of flood control: application to Swannanoa river watershed

AbstractThis study presents an analysis approach using an existing Monte Carlo (MC) flood risk framework to compare annualised risk reductions from flood control alternatives targeting various recurrence interval events. The annualised risk approach is demonstrated by analysing the relative flood risk mitigation benefits of flood proofing in Swannanoa watershed, North Carolina. Using the MC framework, 54 design flows are sampled from the flow distribution and used to drive a graphics card based two‐dimensional flood model. The computed flood depths are used to create flood damage frequency and annualised risk curves. It was hypothesised that flood proofing for a higher probability event would result in a greater relative level of damage reduction for lower cost compared with the traditional use of a 1% annual exceedance flood event. The MC framework was used to test the hypothesis by producing a distribution of annualised risk over various return periods. Confirming the hypothesis, the 12% flood event was found to have the highest annualised risk for the case study in this paper. Simulations were executed to determine the relative costs and benefits of the 12% flood proofing (alternate case) and 1% flood proofing (base case) alternatives. The results showed that the base case reduced the expected annual damage (EAD) by 98.9% compared with the status quo. The alternate case reduced the EAD by 80.4% compared with the status quo. Comparing estimated annual implementation cost with flood damage reductions, annually, for every dollar spent on flood proofing, the 12% design resulted in twice the reduction in flood damages compared with the 1% design. This preliminary study thus confirms the potential of an alternative analysis approach that may be applied for identifying desired flood control level based on flood risk mitigation potential.

Flood Damage Estimate (Quantity), Using HEC-FDA Model. Case Study: The Neka River

The cost of damages due to flooding depends on several factors. However, several methods, using different approaches, can be used to estimate flood damages. In this study, the residential area of Neka river, in the East of Mazandaran province (north of Iran), is considered. The most important part of the river basin is the Neka city that is located in intersection of the foothills and coastal zone (Caspian Sea). According to Francou-Rodier Formula, this basin is potentially at the high risk of flooding. During past decades, several floods have been observed, resulting in costly property damages and human casualties. Therefore, flood damages need to be estimated basing on different scenarios, to be able to propose engineering optimized options for flood controls and to better manage the subsequent crisis. In this research, using GIS models, HEC-RAS, and HEC-GEORAS software, hydraulic conditions of flood were simulated and flood prone areas were determined for different return periods. Based on the output of this step, using HEC-FDA, a risk analysis was performed and flood damages were estimated quantitatively. Finally, the Expected Annual Damage (EAD)was obtained.

Uncertainty and sensitivity of flood risk calculations for a dike ring in the south of the Netherlands

A central tool in risk management is the exceedance-probability loss (EPL) curve, which denotes the probabilities of damages being exceeded or equalled. These curves are used for a number of purposes, including the calculation of the expected annual damage (EAD), a common indicator for risk. The model calculations that are used to create such a curve contain uncertainties that accumulate in the end result. As a result, EPL curves and EAD calculations are also surrounded by uncertainties. Knowledge of the magnitude and source of these uncertainties helps to improve assessments and leads to better informed decisions. This study, therefore, performs uncertainty and sensitivity analyses for a dike-ring area in the Netherlands, on the south bank of the river Meuse. In this study, a Monte Carlo framework is used that combines hydraulic boundary conditions, a breach growth model, an inundation model, and a damage model. It encompasses the modelling of thirteen potential breach locations and uncertainties related to probability, duration of the flood wave, height of the flood wave, erodibility of the embankment, damage curves, and the value of assets at risk. The assessment includes uncertainty and sensitivity of risk estimates for each individual location, as well as the dike-ring area as a whole. The results show that for the dike ring in question, EAD estimates exhibit a 90% percentile range from about 8 times lower than the median, up to 4.5 times higher than the median. This level of uncertainty can mainly be attributed to uncertainty in depth–damage curves, uncertainty in the probability of a flood event and the duration of the flood wave. There are considerable differences between breach locations, both in the magnitude of the uncertainty, and in its source. This indicates that local characteristics have a considerable impact on uncertainty and sensitivity of flood damage and risk calculations.

Estimating the benefits of single value and probability forecasting for flood warning

Abstract. Flood risk can be reduced by means of flood forecasting, warning and response systems (FFWRS). These systems include a forecasting sub-system which is imperfect, meaning that inherent uncertainties in hydrological forecasts may result in false alarms and missed events. This forecasting uncertainty decreases the potential reduction of flood risk, but is seldom accounted for in estimates of the benefits of FFWRSs. In the present paper, a method to estimate the benefits of (imperfect) FFWRSs in reducing flood risk is presented. The method is based on a hydro-economic model of expected annual damage (EAD) due to flooding, combined with the concept of Relative Economic Value (REV). The estimated benefits include not only the reduction of flood losses due to a warning response, but also consider the costs of the warning response itself, as well as the costs associated with forecasting uncertainty. The method allows for estimation of the benefits of FFWRSs that use either deterministic or probabilistic forecasts. Through application to a case study, it is shown that FFWRSs using a probabilistic forecast have the potential to realise higher benefits at all lead-times. However, it is also shown that provision of warning at increasing lead-time does not necessarily lead to an increasing reduction of flood risk, but rather that an optimal lead-time at which warnings are provided can be established as a function of forecast uncertainty and the cost-loss ratio of the user receiving and responding to the warning.

Multiple Flood Source Expected Annual Damage Computations

For flood damage reduction analysis, the standard for measuring risk is expected annual damage. This index represents a long-term average annual flood damage for a given structure or area. We compute this index by integrating a probability-damage function. In practice, we develop the required function by developing a water level (stage)-probability function and an elevation-damage relationship. The analysis becomes complex when the stage-probability function is dependent upon multiple flooding sources. For example, this occurs when an area is protected by multiple leveed reaches or can be flooded from more than one stream. Here we propose alternative analysis frameworks for computing expected annual damage considering this complicating factor. An example illustrates that appropriate methods depend on the alternatives evaluated, the correlation of discharges, and the number of levee reaches.

Estimating Expected Annual Damage for Levee Retrofits

The U.S. Army Corps of Engineers (USACE) has instituted a new analysis methodology for estimating the expected annual damage (EAD) and resulting economic benefits accruing to proposed flood damage-reduction projects. Although the methodology is new, it still, in effect, uses expected probability to estimate the frequency of flooding and EAD. The National Research Council (NRC) in a review of USACE's study of the American River levees stated that the use of expected probability results in significantly biased estimates of EAD. An alternative damage model to that proposed by NRC is used to show that expected probability leads to an unbiased estimate of EAD. The damage model proposed requires that an unbiased estimate of damage results when applied to many projects. A simulation study demonstrates that EAD estimated with expected probability is unbiased, whereas the NRC's recommended estimator is biased.