Validation of methods for the assessment of physical vulnerability to dynamic flooding

2021 ◽  
Author(s):  
Maria Papathoma-Koehle ◽  
Lea Dosser ◽  
Florian Roesch ◽  
Matthias Schlögl ◽  
Marco Borga ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Natural Hazards ◽  
Vulnerability Index ◽  
Insurance Companies ◽  
Flood Events ◽  
Physical Vulnerability ◽  
Vulnerability Indicators ◽  
Damage Data ◽  
Using Data ◽  
Physical Vulnerability Index

<p>The importance of assessing the physical vulnerability of assets to natural hazards is indisputable. Recent extreme events have shown that the severity of natural hazards is strongly linked to the vulnerability of the population and the built environment. Physical vulnerability, in particular, is directly connected to monetary damages and interruptions that are in the centre of the interests of several stakeholders including governments, authorities, insurance companies, engineers, and homeowners. A plethora of different approaches is available in the literature, nevertheless, two categories of approaches are the most prominent: vulnerability curves and vulnerability indicators. In this study, both are put to the test by using data from two relatively recent dynamic flood events. In more detail, a physical vulnerability index (PVI) and a Beta model based on damage data from Italy and Austria are validated using recent damage data from an event in Dimaro Folgarida (Trento, Italy) in 2018 and an event in Schallerbach (Tirol, Austria) in 2015. The study does not just validate the methods but also investigates remaining uncertainties related to the assessment of the process intensity on buildings and the calculation of the building value by conducting a sensitivity analysis. </p>

Vulnerability curves vs. vulnerability indices. Which method explains loss best?

2020 ◽  
Author(s):  
Florian Roesch ◽  
Maria Papathoma-Köhle ◽  
Sven Fuchs
Keyword(s):  
Natural Hazards ◽  
Vulnerability Index ◽  
European Alps ◽  
Mountain Rivers ◽  
Mountain Areas ◽  
Vulnerability Curve ◽  
Impact Forces ◽  
Vulnerability Model ◽  
Vulnerability Indicators ◽  
Damage Data

<p>Mountain rivers are characterized by dynamic flooding with variable amounts of sediment erosion, deposition and remobilisation (Sturm et al., 2018); typical hazard processes include fluvial sediment transport, debris flows and related phenomena. In Europe, such processes repeatedly result in considerable damage to infrastructure and buildings on a local and regional level.</p><p>The physical vulnerability of buildings to dynamic flooding has been approached mainly with two methods until now: vulnerability curves and vulnerability indices. Each approach has its drawbacks and advantages (Papathoma-Köhle, 2016; Papathoma-Köhle et al., 2019). In the present study, damage data from a relatively recent event in the European Alps are used for the application of both methods. The event occurred in the municipality of See situated in the Paznaun valley in Tirol, Austria, in 2015. A new vulnerability curve is developed based on data from 21 buildings. An existing vulnerability index is also applied in the area. The results of both methods are compared with each other and with the actual loss of the event. Additionally, a sensitivity analysis regarding two input parameters (intensity and degree of loss) is performed for both the vulnerability curve and the vulnerability index. The results are mirrored against a recently developed vulnerability model for dynamic flooding in mountain areas (Fuchs et al., 2019), and possible model improvements are discussed.</p><p> </p><p>References</p><p>Fuchs, S., Heiser, M., Schlögl, M., Zischg, A., Papathoma-Köhle, M., and Keiler, M.: Short communication: A model to predict flood loss in mountain areas, Environmental Modelling and Software, 117, 176-180, https://doi.org/10.1016/j.envsoft.2019.03.026, 2019.</p><p>Papathoma-Köhle, M.: Vulnerability curves vs. vulnerability indicators: application of an indicator-based methodology for debris-flow hazards, Natural Hazards and Earth System Sciences, 16, 1771-1790, https://doi.org/10.5194/nhess-16-1771-2016, 2016.</p><p>Papathoma-Köhle, M., Schlögl, M., and Fuchs, S.: Vulnerability indicators for natural hazards: an innovative selection and weighting approach, Scientific Reports, 9, Article 15026, https://doi.org/10.1038/s41598-019-50257-2, 2019.</p><p>Sturm, M., Gems, B., Keller, F., Mazzorana, B., Fuchs, S., Papathoma-Köhle, M., and Aufleger, M.: Experimental analyses of impact forces on buildings exposed to fluvial hazards, Journal of Hydrology, 565, 1-13, https://doi.org/10.1016/j.jhydrol.2018.07.070, 2018.</p>

Mountain hazards and Building Back Better (BBB) – focus on the Austrian Alps

2020 ◽  
Author(s):  
Bernhard Ullrich ◽  
Maria Papathoma-Köhle ◽  
Sven Fuchs
Keyword(s):  
Land Use ◽  
Local Adaptation ◽  
Natural Hazards ◽  
Vulnerability Index ◽  
Physical Vulnerability ◽  
Adaptation Measures ◽  
Reconstruction Process ◽  
Structural Measures ◽  
Building Level ◽  
Physical Vulnerability Index

<p>Natural hazards cause often material damages and loss of life. Human efforts are concentrated not only on the time preceding the occurrence of a hazard (forecast, evacuation, response, land use planning and structural measures) but also during (response, emergency operations) and after the occurrence of a catastrophic process (reconstruction of damaged buildings and infrastructure). As far as the reconstruction phase in concerned, authorities and citizens tend to rebuild their houses and infrastructure in the same way and location they were before the hazard strikes. The present study outlines the reconstruction efforts of two municipalities and the changes that they made following a torrential event in order to increase their resilience to natural hazards and to reduce future loss.  In more detail, a physical vulnerability index is used to assess the Build Back Better (BBB) of two alpine villages in Austria that experienced significant damages during the event of 2005. The BBB is investigated at three levels: the municipal level (structural measures and land use changes), the building level (physical vulnerability index) and the community level (public awareness). At the building level, the vulnerability index used is based on a number of indicators (building characteristics) including the height of windows, the existence, material and height of surrounding walls, the orientation of the building and the shielding of neighboring structures. The index compares the pattern of the physical vulnerability of buildings for both municipalities in 2005 and in the present. Both villages have now completed the reconstruction process, however, a similar event in the future could still cause significant damage. Changes in the building design and development of local adaptation measures have decreased the physical vulnerability of some buildings, however, some others remain equally vulnerable.  Based on the investigation of the reconstruction process recommendations regarding local adaptation measures are presented.</p>

scholarly journals Vulnerability indicators for natural hazards: an innovative selection and weighting approach

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Maria Papathoma-Köhle ◽  
Matthias Schlögl ◽  
Sven Fuchs
Keyword(s):  
Feature Selection ◽  
Natural Hazards ◽  
Vulnerability Assessment ◽  
Empirical Data ◽  
Vulnerability Index ◽  
European Alps ◽  
Physical Vulnerability ◽  
Building Stock ◽  
Mountain Areas ◽  
Vulnerability Indicators

Abstract To prepare for upcoming extreme events, decision makers, scientists and other stakeholders require a thorough understanding of the vulnerability of the built environment to natural hazards. A vulnerability index based on building characteristics (indicators) rather than empirical data may be an alternative approach to a comprehensive physical vulnerability assessment of the building stock. The present paper focuses on the making of such an index for dynamic flooding in mountain areas demonstrating the transferability of vulnerability assessment approaches between hazard types, reducing the amount of required data and offering a tool that can be used in areas were empirical data are not available. We use data from systematically documented torrential events in the European Alps to select and weight the important indicators using an all-relevant feature selection algorithm based on random forests. The permutation-based feature selection reduced the initial number of indicators from 22 to seven, decreasing in this way the amount of required data for assessing physical vulnerability and ensuring that only relevant indicators are considered. The new Physical Vulnerability Index (PVI) may be used in the mountain areas of Europe and beyond where only few empirical data are available supporting decision-making in reducing risk to dynamic flooding.

scholarly journals An Assessment of Social and Physical Vulnerability to Hydroclimate Extremes in Appalachia

2021 ◽  
Author(s):  
Leah R. Handwerger ◽  
Jennifer R. Runkle ◽  
Ronald Leeper ◽  
Elizabeth Shay ◽  
Kara Dempsey ◽  
...  
Keyword(s):  
Social Vulnerability ◽  
Scientific Community ◽  
Vulnerability Index ◽  
Precipitation Variability ◽  
Mitigation Strategies ◽  
Climate Projections ◽  
Social Vulnerability Index ◽  
Physical Vulnerability ◽  
Vulnerable Communities ◽  
Vulnerability Indicators

Abstract Appalachia is a cultural region in the southern and central Appalachian Mountains that lags behind the nation in several social vulnerability indicators. Climate projections over this region indicate that precipitation variability will increase in both severity and frequency in future decades, suggesting that the occurrence of natural hazards related to hydroclimate extremes will also increase. The objective of this study was to investigate the spatiotemporal patterns of drought and precipitation and determine how trends overlap with vulnerable communities across Appalachia. The study utilized trend analysis through Mann-Kendall calculations and a Social Vulnerability Index, resulting in a bivariate map that displays areas most susceptible to adverse effects from hydroclimate extremes. Results show the southwestern portion of the region as most vulnerable to increased precipitation, and the central-southeast most vulnerable to an increase in drought-precipitation variability. This study is among the first to utilize the boundaries defined by the Appalachian Regional Commission from a climatological perspective, allowing findings to reach audiences outside the scientific community and bring more effective mitigation strategies that span from the local to federal levels.

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

2020 ◽  
Vol 20 (7) ◽  
pp. 2067-2090 ◽  
Author(s):  
Mark Bawa Malgwi ◽  
Sven Fuchs ◽  
Margreth Keiler
Keyword(s):  
Risk Reduction ◽  
Flood Risk ◽  
Vulnerability Index ◽  
Flood Damage ◽  
Flood Hazards ◽  
Physical Vulnerability ◽  
Damage Models ◽  
Vulnerability Indicators ◽  
Damage Grades ◽  
Observed Damage

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.

scholarly journals MAPPING TSUNAMI VULNERABILITY FOR MATARAM CITY IN LOMBOK ISLAND – INDONESIA: A PHYSICAL AND SOCIOECONOMIC ASSESSMENT

2015 ◽  
Vol 3 (1) ◽  
pp. 60
Author(s):  
Andhi Pratama Putra
Keyword(s):  
Social Vulnerability ◽  
Composite Index ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Physical Vulnerability ◽  
Economic Vulnerability ◽  
Physical Vulnerability Index ◽  
Lombok Island

<p><span style="font-family: Calibri;">Letak kedekatan lokasi geografis dengan lempeng tektonik <em>Eurasian</em> dan <em>Indo-Australian</em> membawa konsekuensi logis terhadap tingginya resiko kebencanaan, terutama gempa dan tsunami, bagi Indonesia. Kota Mataram yang merupakan ibukota Provinsi Nusa Tenggara Barat merupakan salah satu wilayah yang perlu mendapatkan perhatian khusus terhadap resiko bencana tsunami. Sebagai langkah awal, identifikasi lokasi yang paling rentan terhadap resiko bencana tsunami perlu dilakukan dengan memadukan aspek-aspek fisik, sosial dan ekonomi. Penelitian ini bertujuan mengidentifikasikan lokasi paling rentan terhadap resiko bencana tsunami di Kota Mataram dengan menggunakan analisa sistem informasi geografis (<em>GIS</em>). Penilaian dilakukan dengan mengembangkan Indeks Gabungan (<em>Composite Index</em>) berupa <em>Total Vulnerability Index</em> (<em>TVI</em>) yang merupakan kombinasi Indeks Kerentanan Fisik/ <em>Physical Vulnerability Index</em> (<em>PVI</em>), Indeks Kerentanan Sosial/ <em>Social Vulnerability Index</em> (<em>SVI</em>) dan Indeks Kerentanan Ekonomi/ <em>Economic Vulnerability Index</em> (<em>EVI</em>). Hasil analisis berhasil menemukenali bahwa Kota Tua Ampenan merupakan wilayah di Kota Mataram dengan nilai indeks gabungan tertinggi yang mencerminkan tingkat kerentanan yang paling tinggi.</span></p>

scholarly journals Spatial Scope of the Regional Hazard Mitigation Plan

2020 ◽  
Vol 20 (1) ◽  
pp. 61-70
Author(s):  
Jaeweon Yeom ◽  
Seungwon Kang ◽  
Pilsung Jung ◽  
Juchul Jung
Keyword(s):  
Natural Hazards ◽  
Natural Hazard ◽  
Hazard Mitigation ◽  
Vulnerability Index ◽  
Adjacent Area ◽  
Zone Boundary ◽  
Spatial Correlations ◽  
Spatial Characteristics ◽  
Spatial Influence ◽  
Using Data

This study suggests the spatial scope of the regional hazard mitigation plan, reflecting the feature of natural hazards occurring beyond the administrative zone boundary. The damage caused by natural hazards is not randomly distributed across a space but has interdependent characteristics with the nearby area; therefore, the spatial influence of an adjacent area should be considered. In particular, as damage due to natural disasters is increasing in Korea, it is necessary to establish a regional hazard mitigation plan considering the spatial characteristics of hazards. However, the current hazard mitigation plan sets the scope of the plan based on administrative boundaries. In this study, we measured the vulnerability index of each area using data spanning 10 years from 2008 to 2017 and verified spatial correlations through LISA (Local Indicator of Spatial Autocorrelation). According to LISA analysis, we found that a link exists between si/gun/gu and we identified the spatial characteristics of natural disaster damage. The results confirmed that natural hazard characteristics occur beyond the boundaries of administrative areas.

Efficiency Analysis of Malaysian General Insurance Companies Using Data Envelopment and Super-efficiency Approach

2021 ◽  
Vol 11 (10) ◽  
Author(s):  
Jamilah Mohd Mahyideen ◽  
Nur Azlina Abd Aziz ◽  
Hafisah Yaakob ◽  
Nurhanani Aflizan Mohamad Rusli ◽  
Wan Normila Mohamad
Keyword(s):  
Efficiency Analysis ◽  
Insurance Companies ◽  
Data Envelopment ◽  
Super Efficiency ◽  
General Insurance ◽  
Using Data

Mediator Analysis of Job Satisfaction: Relationship between Servant Leadership and Employee Engagement

Metamorphosis ◽  
2018 ◽  
Vol 17 (2) ◽  
pp. 76-85 ◽  
Author(s):  
Prabhjot Kaur
Keyword(s):  
Job Satisfaction ◽  
Quantitative Analysis ◽  
Servant Leadership ◽  
Employee Engagement ◽  
Service Provider ◽  
Insurance Companies ◽  
Servant Leaders ◽  
Call Centres ◽  
Using Data ◽  
Satisfaction Relationship

Servant leaders attempt altruistically and selflessly to help others before themselves, believe in developing their followers to their greatest potential, and seek to benefit the wider community. The main purpose of the present article is to examine servant leadership as the antecedent to employee engagement, mediated by job satisfaction, in Punjab, using data from 190 employees from different service provider companies (banks, colleges, call centres, insurance companies). Quantitative analysis shows that when employees observe positive levels in servant leadership, they are fundamentally encouraged towards exercising significantly higher levels of engagement and satisfaction.

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