An indexing approach to assess flood vulnerability in the western coastal cities of Mazandaran, Iran

Sadeghi-Pouya, Alireza; Nouri, J.; Mansouri, Nabiollah; Kia-Lashaki, Ali

doi:10.1016/j.ijdrr.2017.02.013

Cited by 41 publications

(23 citation statements)

References 22 publications

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“…level of agreement), as is the case for performance analysis using a comparison of the deduced index and observed damage data (e.g. Godfrey et al, 2015;Sadeghi-Pouya et al, 2017) or based on visualizations of the spatial agreement using GIS maps by comparing hotspots and observed damage (e.g. Fernandez et al, 2016).…”

Section: Challenges and Gaps In Physical Vulnerability Indicators Andmentioning

confidence: 99%

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A generic physical vulnerability model for floods: review and concept for data-scarce regions

Malgwi

Fuchs

Keiler

2020

Nat. Hazards Earth Syst. Sci.

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Abstract. The use of different methods for physical flood vulnerability assessment has evolved over time, from traditional single-parameter stage–damage curves to multi-parameter approaches such as multivariate or indicator-based models. However, despite the extensive implementation of these models in flood risk assessment globally, a considerable gap remains in their applicability to data-scarce regions. Considering that these regions are mostly areas with a limited capacity to cope with disasters, there is an essential need for assessing the physical vulnerability of the built environment and contributing to an improvement of flood risk reduction. To close this gap, we propose linking approaches with reduced data requirements, such as vulnerability indicators (integrating major damage drivers) and damage grades (integrating frequently observed damage patterns). First, we present a review of current studies of physical vulnerability indicators and flood damage models comprised of stage–damage curves and the multivariate methods that have been applied to predict damage grades. Second, we propose a new conceptual framework for assessing the physical vulnerability of buildings exposed to flood hazards that has been specifically tailored for use in data-scarce regions. This framework is operationalized in three steps: (i) developing a vulnerability index, (ii) identifying regional damage grades, and (iii) linking resulting index classes with damage patterns, utilizing a synthetic “what-if” analysis. The new framework is a first step for enhancing flood damage prediction to support risk reduction in data-scarce regions. It addresses selected gaps in the literature by extending the application of the vulnerability index for damage grade prediction through the use of a synthetic multi-parameter approach. The framework can be adapted to different data-scarce regions and allows for integrating possible modifications to damage drivers and damage grades.

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Section: Challenges and Gaps In Physical Vulnerability Indicators Andmentioning

confidence: 99%

“…Penning-Rowsell et al, 2005;Neubert et al, 2008;Naumann et al, 2009) that aim to reduce the dependency on empirical damage and loss data. However, synthetic approaches often use flood depth as the only damage-influencing parameter, leading to increased un-certainty in damage prediction (Pistrika et al, 2014;Schröter et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A generic physical vulnerability model for floods: review and concept for data-scarce regions

Malgwi

Fuchs

Keiler

2020

Nat. Hazards Earth Syst. Sci.

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“…Barroca et al (2006) emphasized that indicators are context-dependent and it will be ineffective to adopt an indicator, or a set of indicators, that are non-existent in a target region. For example, several vulnerability indices use the number of storeys in assessing the impact of floods to buildings 185 (e.g., Kappes et al, 2012;Blanco-Vogt and Schanze, 2014;Thouret et al, 2014;Godfrey et al, 2015;Fernandez et al, 2016;Sadeghi-Pouya et al, 2017). The underlying theory is well-founded based on the prevalence of multi-storey buildings in these regions and from an engineering standpoint since the additional weight of more storeys helps in resisting the impact from flood.…”

Section: Region Of Applicationmentioning

confidence: 99%

“…Papathoma et al, 2003;Kappes et al, 2012;Blanco-Vogt and Schanze, 2014), or to semi-aggregated scales such as entire building blocks (e.g. Müller et al, 2011;Krellenberg and Welz, 2017;Sadeghi-Pouya et al, 2017) or neighborhoods 220 (e.g. Fernandez et al, 2016;Percival et al, 2018).…”

Section: Spatial Scalementioning

confidence: 99%

An adaptive regional vulnerability assessment model: Review and concepts for data-scarce regions

Malgwi¹,

Fuchs²,

Keiler³

2019

Preprint

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10Although the vulnerability indicator method has been applied to several data-scarce regions, a missing linkage with damage grades had hindered its application for loss evaluation to complement disaster risk reduction efforts. To address this gap, we present a review of physical vulnerability indicators and flood damage models to gain insights on best practice. Thereafter, we present a conceptual framework for linking the vulnerability indicators and damage grades using three phases (i) developing a vulnerability index, (ii) identifying regional damage grades, and (iii) linking vulnerability index classes with 15 damage grades. The vulnerability index comprehensively integrates elements of the hazard using a Building Impact Index (BII) on one hand, and exposure, susceptibility and local protection elements using a Building Resistance Index (BRI) on the other hand. For the damage grades, local expert assessments are used for identifying and categorizing frequently observed regional damage patterns. Finally, by means of synthetic what-if analysis, experts are asked to estimate damage grades for each interval of the BII and class of BRI to develop a vulnerability curve. The proposed conceptual framework can be used 20 for damage prediction in data-scarce regions to support loss assessment and to provide guidance for disaster risk reduction.

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“…Initially, coastal vulnerability index (CVI) was developed by Gornitz et al [28] and then later modified by, again, Gornitz et al [29] through the addition of new parameters. Subsequently, several scientists have established many CVI methodological frameworks to identify and assess the world's coastal vulnerability hotspots [14,28,29,34,36,[42][43][44][45][46][47]. However, the majority of the coastal vulnerability assessments are evaluated at the macro level (city scale) but not at the micro level (small town scale), particularly in the United Kingdom (UK).…”

Section: Introductionmentioning

confidence: 99%

Building Blocks: A Quantitative Approach for Evaluating Coastal Vulnerability

Kantamaneni

Aher

et al. 2017

Water

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Climate change and associated factors such as global and regional sea-level rise; the upsurge in high-intensity flooding events; and coastal erosion are pulse and press disturbances that threaten to increase landslides in coastal regions. Under these circumstances; a rigorous framework is required to evaluate coastal vulnerability in order to plan for future climate change scenarios. A vast majority of coastal vulnerability assessments across the globe are evaluated at the macro level (city scale) but not at the micro level (small town scale); particularly in the United Kingdom (UK). In order to fill this vital research gap; the current study established a coastal vulnerability index termed here as the Micro Town Coastal Vulnerability Index (MTCVI) and then applied it to Barton-on-Sea; which is a small coastal town of the Hampshire region; England; UK. MTCVI was evaluated for Barton-on-Sea coastal vulnerability by integrating both novel and existing parameters. Results suggest that the entire shoreline frontage (2 km) exhibits very high coastal vulnerability and is prone to various coastal hazards such as landslides; erosion; and wave intrusion. This suggests that Barton-on-Sea coastal amenities will require a substantial improvement in shoreline protection measures. In this study; GIS (geographic information system) coastal vulnerability and landslide maps were generated; and these maps can be used by the local authorities; district councils; coastal engineers; and planners to improve and design coastal management strategies under the climate change scenarios. Meanwhile; the methodology used in this study could also be applied to any other suitable location in the world depending on the availability of the data.

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An indexing approach to assess flood vulnerability in the western coastal cities of Mazandaran, Iran

Cited by 41 publications

References 22 publications

A generic physical vulnerability model for floods: review and concept for data-scarce regions

A generic physical vulnerability model for floods: review and concept for data-scarce regions

An adaptive regional vulnerability assessment model: Review and concepts for data-scarce regions

Building Blocks: A Quantitative Approach for Evaluating Coastal Vulnerability

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