Sensitivity analysis of flood damage estimates: A case study in Fredericton, New Brunswick

McGrath, Heather; Stefanakis, Emmanuel; Nastev, Miroslav

doi:10.1016/j.ijdrr.2015.09.003

Cited by 42 publications

(30 citation statements)

References 14 publications

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“…In order to effectively prevent massive losses, disaster risk management requires estimation well in advance of the frequency and magnitude of potential flood events, and their consequences in terms of economic damages (Elmer et al, 2010;Hammond et al, 2015;Kaplan and Garrick, 1981;Neale and Weir, 2015;Thieken et al, 2008;UNISDR, 2004). Therefore, it is indispensable to provide decision makers with reliable assessment tools that are able to produce such knowledge, after which an efficient risk reduction strategy can be adequately planned (Emanuelsson et al, 2014;McGrath et al, 2015;Merz et al, 2010;Penning-Rowsell et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…Relative functions have an advantage over absolute functions, namely that they are more flexible for transfer to different regions or years since the damage ratio is independent of the changes in market values . Still, both types are developed on sample areas which have particular geographical characteristics that affect both the quality of the exposed value and the flood phenomena (McGrath et al, 2015;Proverbs and Soetanto, 2004). Therefore, transferred models may carry a high level of uncertainty, unless they are calibrated with an empirical dataset collected from the new study area (Cammerer et al, 2013;Hasanzadeh Nafari et al, 2015;Molinari et al, 2014b).…”

Section: Introductionmentioning

confidence: 99%

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Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

Nafari

Amadio

Ngo

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth-damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a threefold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

Nafari

Amadio

Ngo

et al. 2017

Nat. Hazards Earth Syst. Sci.

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“…In most studies i.e. [4], [5], [8], [9], the estimation of flood damage was obtained using the combination of flood characteristics, flood exposure, and flood damage function curve.…”

Section: Introductionmentioning

confidence: 99%

Application of Hec-Ras and Arc Gis for Floodplain Mapping in Segamat Town, Malaysia

Romali¹

2018

GEOMATE

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Nowadays, a risk-based flood mitigation concept has received more attention rather than the conventional flood control approach in reducing the impacts of flooding. With the intention to assist in the management of flood risk, flood modeling is useful in providing information on the flood extent and flood characteristics. This paper presents the application of HEC-RAS model to the development of floodplain maps for an urban area in Segamat town in Malaysia. The analysis used Interferometric Synthetic Aperture Radar (IFSAR) as the main modeling input data. Five distribution models, namely Generalized Pareto, Generalized Extreme Value, Log-Pearson 3, Log-Normal (3P) and Weibull (3P) were tested in flood frequency analysis to calculate extreme flows with different return periods. Using Kolmogorov-Smirnov (KS) test, the Generalized Pareto was found to be the best distribution for the Segamat River. The peak floods from frequency analysis for selected return periods were input into the HEC-RAS model to find the expected corresponding flood levels. Results obtained from HEC-RAS model were used in ArcGIS to prepare floodplain maps for different return periods. The results indicated that most of the inundated areas in the simulated 100 year return period were also affected by 2011 historical floods. For 100 years flood simulation, the inundated area was almost 5 times larger than the simulated 10 years' flood.

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“…Government officials, GIS specialists, emergency managers, and responders require tools to develop mitigation and recovery plans as well as preparedness and response procedures for natural disasters (McGrath, Stefanakis, & Nastev, 2015;Neighbors, Cochran, Caras, & Noriega, 2013). Evaluation of risk involves the combination of three components: the potential flood hazard, inventory of the built environment, and representative vulnerability functions -which relate the inundation depth to a percent damage of the asset.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the input data requirements and data manipulation required for these models to run may exceed the technical capabilities of the broader non-expert safety community (Nastev et al 2015). These existing models therefore leave a gap between what is needed (and when) by decision makers and the output a model is able to provide (Leskens et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

RAPID RISK EVALUATION (ER²) USING MS EXCEL SPREADSHEET: A CASE STUDY OF FREDERICTON (NEW BRUNSWICK, CANADA)

McGrath

Stefanakis

Nastev

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Conventional knowledge of the flood hazard alone (extent and frequency) is not sufficient for informed decision-making. The public safety community needs tools and guidance to adequately undertake flood hazard risk assessment in order to estimate respective damages and social and economic losses. While many complex computer models have been developed for flood risk assessment, they require highly trained personnel to prepare the necessary input (hazard, inventory of the built environment, and vulnerabilities) and analyze model outputs. As such, tools which utilize open-source software or are built within popular desktop software programs are appealing alternatives. The recently developed Rapid Risk Evaluation (ER 2 ) application runs scenario based loss assessment analyses in a Microsoft Excel spreadsheet. User input is limited to a handful of intuitive drop-down menus utilized to describe the building type, age, occupancy and the expected water level. In anticipation of local depth damage curves and other needed vulnerability parameters, those from the U.S. FEMA's Hazus-Flood software have been imported and temporarily accessed in conjunction with user input to display exposure and estimated economic losses related to the structure and the content of the building. Building types and occupancies representative of those most exposed to flooding in Fredericton (New Brunswick) were introduced and test flood scenarios were run. The algorithm was successfully validated against results from the Hazus-Flood model for the same building types and flood depths.

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Sensitivity analysis of flood damage estimates: A case study in Fredericton, New Brunswick

Cited by 42 publications

References 14 publications

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

Application of Hec-Ras and Arc Gis for Floodplain Mapping in Segamat Town, Malaysia

RAPID RISK EVALUATION (ER²) USING MS EXCEL SPREADSHEET: A CASE STUDY OF FREDERICTON (NEW BRUNSWICK, CANADA)

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Sensitivity analysis of flood damage estimates: A case study in Fredericton, New Brunswick

Cited by 42 publications

References 14 publications

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

Application of Hec-Ras and Arc Gis for Floodplain Mapping in Segamat Town, Malaysia

RAPID RISK EVALUATION (ER2) USING MS EXCEL SPREADSHEET: A CASE STUDY OF FREDERICTON (NEW BRUNSWICK, CANADA)

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Product

Resources

About

RAPID RISK EVALUATION (ER²) USING MS EXCEL SPREADSHEET: A CASE STUDY OF FREDERICTON (NEW BRUNSWICK, CANADA)