Multi-vulnerability analysis for flash flood risk management

Karagiorgos, Konstantinos; Thaler, Thomas; Hübl, Johannes; Maris, Fotios; Fuchs, Sven

doi:10.1007/s11069-016-2296-y

Cited by 60 publications

(33 citation statements)

References 56 publications

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“…It is clear that although predicting, monitoring and assessing the hazardous process is essential, the analysis of the vulnerability of the elements at risk may be the key to risk reduction. To address vulnerability in a holistic way, all its dimensions (social, economic, physical, environmental, institutional) should be addressed and analysed Karagiorgos et al, 2016). However, herein the focus is solely on the physical vulnerability of buildings.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability curves vs. vulnerability indicators: application of an indicator-based methodology for debris-flow hazards

Papathoma-Köhle

2016

Nat. Hazards Earth Syst. Sci.

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Abstract. The assessment of the physical vulnerability of elements at risk as part of the risk analysis is an essential aspect for the development of strategies and structural measures for risk reduction. Understanding, analysing and, if possible, quantifying physical vulnerability is a prerequisite for designing strategies and adopting tools for its reduction. The most common methods for assessing physical vulnerability are vulnerability matrices, vulnerability curves and vulnerability indicators; however, in most of the cases, these methods are used in a conflicting way rather than in combination. The article focuses on two of these methods: vulnerability curves and vulnerability indicators. Vulnerability curves express physical vulnerability as a function of the intensity of the process and the degree of loss, considering, in individual cases only, some structural characteristics of the affected buildings. However, a considerable amount of studies argue that vulnerability assessment should focus on the identification of these variables that influence the vulnerability of an element at risk (vulnerability indicators). In this study, an indicator-based methodology (IBM) for mountain hazards including debris flow ) is applied to a case study for debris flows in South Tyrol, where in the past a vulnerability curve has been developed. The relatively "new" indicator-based method is being scrutinised and recommendations for its improvement are outlined. The comparison of the two methodological approaches and their results is challenging since both methodological approaches deal with vulnerability in a different way. However, it is still possible to highlight their weaknesses and strengths, show clearly that both methodologies are necessary for the assessment of physical vulnerability and provide a preliminary "holistic methodological framework" for physical vulnerability assessment showing how the two approaches may be used in combination in the future.

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Section: Introductionmentioning

confidence: 99%

Vulnerability curves vs. vulnerability indicators: application of an indicator-based methodology for debris-flow hazards

Papathoma-Köhle

2016

Nat. Hazards Earth Syst. Sci.

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“…Moreover, the single-family dwellings that abound in the study area tend to have basements and ground floor rooms (i.e. living rooms, kitchens and sometimes bedrooms; "Exposure in the Urban Built-up Environment" and "Constructive Exposure" factors), spaces which are both prone to flooding (Bodoque et al, 2016b;Karagiorgos et al, 2016). With regard to the vulnerability factors that make up the sensitivity component (see Fig.…”

Section: Integrated Social Vulnerability and Variables Involvedmentioning

confidence: 99%

“…those of global environmental change and natural hazards). However, not many studies have focused exclusively on the context of flood risk (Tapsell et al, 2002;Burton and Cutter, 2008;Fekete, 2010;Mollah, 2016), and only a very few of these relate to flash floods (Balteanu et al, 2015;Karagiorgos et al, 2016). Overall, in social vulnerability analysis a separate assessment of vulnerability (Tapsell et al, 2002;Cutter et al, 2003;Nelson et al, 2015) and resilience is made (Cutter et al, , 2010Siebeneck et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Construction of an integrated social vulnerability index in urban areas prone to flash flooding

Aroca‐Jiménez

Pozo

Garcı́a

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Among the natural hazards, flash flooding is the leading cause of weather-related deaths. Flood risk management (FRM) in this context requires a comprehensive assessment of the social risk component. In this regard, integrated social vulnerability (ISV) can incorporate spatial distribution and contribution and the combined effect of exposure, sensitivity and resilience to total vulnerability, although these components are often disregarded. ISV is defined by the demographic and socio-economic characteristics that condition a population's capacity to cope with, resist and recover from risk and can be expressed as the integrated social vulnerability index (ISVI). This study describes a methodological approach towards constructing the ISVI in urban areas prone to flash flooding in Castilla y León (Castile and León, northern central Spain, 94 223 km 2 , 2 478 376 inhabitants). A hierarchical segmentation analysis (HSA) was performed prior to the principal components analysis (PCA), which helped to overcome the sample size limitation inherent in PCA. ISVI was obtained from weighting vulnerability factors based on the tolerance statistic. In addition, latent class cluster analysis (LCCA) was carried out to identify spatial patterns of vulnerability within the study area. Our results show that the ISVI has high spatial variability. Moreover, the source of vulnerability in each urban area cluster can be identified from LCCA. These findings make it possible to design tailor-made strategies for FRM, thereby increasing the efficiency of plans and policies and helping to reduce the cost of mitigation measures.

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“…Kerentanan fisik direpresentasikan melalui hubungan antara tinggi genangan dan lokasi infrastruktur. Sehubungan dengan kerentanan sosial, penilaian dilakukan dengan pengumpulan data berdasarkan survei dari rumah ke rumah (Karagiorgos, et al, 2016).…”

Section: Pendahuluanunclassified