Storm-induced risk assessment: Evaluation of two tools at the regional and hotspot scale

Ferreira, Óscar; Viavattene, Christophe; Jiménez, José A.; Bolle, Annelies; Neves, Luciana das; Plomaritis, Theocharis A.; McCall, Robert; Dongeren, Ap van

doi:10.1016/j.coastaleng.2017.10.005

Cited by 39 publications

(22 citation statements)

References 20 publications

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“…However, many of the above factors still remain not fully quantified, especially in a unified framework which would allow the assessment of their relative importance. Flood risk estimation exhibits methodological differences depending on the scale of application (Apel et al, 2009;Ferreira et al, 2017;de Moel et al, 2015). Local studies benefit from high-quality digital elevation models (DEMs) (Vousdoukas et al, 2012) and exposure data (Christie et al, 2017), as well as detailed numerical models, resolving several scales (Bertin et al, 2014;Giardino et al, 2018) and including complex processes like dune or dike breaching de Moel et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Vousdoukas

Bouziotas

Giardino

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policymaking, and harmonization of climate change adaptation strategies. There is, however, limited insight into the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the coastal flood risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea level (ESL), (ii) the underlying uncertainty in the digital elevation model (DEM), (iii) flood defence information, (iv) the assumptions behind the use of depth-damage functions that express vulnerability, and (v) different climate change projections. The impact of these uncertainties on estimated expected annual damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal, and on the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, and their absolute and relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large datasets with sufficient resolution and accuracy, the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

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Section: Introductionmentioning

confidence: 99%

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Vousdoukas

Bouziotas

Giardino

et al. 2018

Nat. Hazards Earth Syst. Sci.

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“…However, a brief summary of the main equations and assumptions used in the model are presented in the following sections. For other applications of the model in different case study sites the reader is invited to refer to Christie et al (2018), De Angeli et al (2018), and Ferreira et al (2018). The calculation of each indicator requires the collection of specific data on exposed assets and their characteristics.…”

Section: Inundation Modeling and Extreme Events Selectionmentioning

confidence: 99%

From Hazard to Consequences: Evaluation of Direct and Indirect Impacts of Flooding Along the Emilia-Romagna Coastline, Italy

2019

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Managing coastal flood risk at the regional scale requires a prioritization of economic resources along the shoreline. Advanced modeling assessment and open-source tools are now available to support transparent and rigorous risk evaluation and to inform managers and stakeholders in their choices. However, the issues lay in data availability and data richness to estimate coastal vulnerability and impacts. The Coastal Risk Assessment Framework (CRAF) has been developed as part of the Resilience Increasing Strategies for Coasts -Toolkit (RISC-KIT) EU FP7 project. The framework provides two levels of analysis. In the first phase, a coastal index approach is applied to identify a restricted number of potential critical areas for different hazards (i.e., erosion and flooding). In the second phase, an integrated hazard and impact modeling approach is applied in the critical areas to assess the direct and indirect impacts of storm events using a matrix-based approach and a systemic analysis. The framework was tested on the coastline of the Emilia-Romagna region (northern Italy) for two probabilistic coastal storms with representative return periods of 10 and 100 years. In this work, the application of the second phase of the CRAF is presented for two sites, Lido degli Estensi-Spina (Ferrara province) and Milano Marittima (Ravenna province). The hazard modeling of floods was implemented using a coupling between XBeach and Lisflood-FP. The Integrated Disruption Assessment (INDRA) model was applied to quantify direct and indirect impacts. The impact assessment focused on household's financial recovery, business disruption and financial recovery, transport network disruption and risk to life. The considered business sector comprised the key economic activities related to the sun-and-beach tourism, which is one of the main drivers of the regional economy. A Multi-Criteria Analysis was applied to support decision-makers to identify the most critical site. The importance of detailed physical and socio-economic data collected at the regional and local levels is highlighted and discussed, together with the importance to involve different stakeholders in the process (e.g., through interviews and surveys). The limitations of the applied approach due to data quality and availability and to the assumptions introduced in the hazard and disruption models are highlighted.

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“…Eight of the articles dealt with flooding and coastal risks (e.g. flooding, storms and erosion) and their effect on infrastructure and land use [24,[36][37][38][39][40][41][42]. Two of the articles also considered other events such as heat wave, drought, wildfire and windstorm.…”

Section: Multi-criteria Decision Analysis (Mcda)mentioning

confidence: 99%

Tools and Methods for Supporting Regional Decision-Making in Relation to Climate Risks

Hanski¹,

Keränen²,

Molarius³

2019

Climate Change and Global Warming

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Climate change has had a major impact on the Nordic region. For example, the mean temperature rise is expected to be 4-6°C by 2080. In Finland, the regional authorities are responsible for climate change adaptation. Some of the most vulnerable sectors include energy, tourism, transport and water supply. Currently, it appears that the authorities are not familiar with the tools for assessing climate risks and lack knowledge about the impact of climate change. In this paper, we provide a review of risk assessment methods and decision-making tools, focusing on adapting to climate change in a Finnish context. Our research method comprises a systematic qualitative literature review dealing with relevant journals, dissertations and deliverables of relevant EU projects since 2005.

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Storm-induced risk assessment: Evaluation of two tools at the regional and hotspot scale

Cited by 39 publications

References 20 publications

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

From Hazard to Consequences: Evaluation of Direct and Indirect Impacts of Flooding Along the Emilia-Romagna Coastline, Italy

Tools and Methods for Supporting Regional Decision-Making in Relation to Climate Risks

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