This session aims at a better understanding of the vulnerability of the built environment (building envelop, building content and infrastructure) to different types of natural hazards. The main focus herein is to present different models and approaches to bridge the gap between ex-post loss and damage assessment and ex-ante predictive models. Studies on loss, damage and vulnerability often address different scales and spatial patterns obstructing the comparison and transfer of results and methods. Moreover, although existing models (matrices, indices and functions) demonstrate high variance, analysis of the associated uncertainties remains fragmentary. We invite contributions addressing vulnerability, loss and damage assessment and we provide a platform for scientific exchange and implementation for successful disaster risk reduction strategies focusing on building back better, mitigation and adaptation.

Co-organized by GM12
Convener: Maria Papathoma-Koehle | Co-conveners: Sven Fuchs, Margreth Keiler
| Attendance Fri, 08 May, 14:00–15:45 (CEST)

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Chat time: Friday, 8 May 2020, 14:00–15:45

Chairperson: Maria Papathoma-Köhle, Margreth Keiler, Sven Fuchs
D1723 |
Mirjam Mertin, Mattia Brughelli, Andreas Zischg, Veronika Röthlisberger, Matthias Schlögl, and Margreth Keiler

Implementing effective flood risk strategies is an essential task for policy-makers which will gain in importance as flood losses are expected to increase due to socio-economic and climatic drivers in near future. Flood risk mitigation incorporates structural and non-structural measures such as the declaration of flood hazard zones, both of which are associated with high financial expenses. Essential information to ensure maximum effectiveness and cost efficiency of flood protection measures is provided by quantitative flood loss analyses based, for example, on data from insurance claims.

This project aims to model the expected flood damage, thus the vulnerability to buildings by examining country-wide, empirical flood loss data of Switzerland of the past 35 years. The developed method includes several steps: First, the loss data are statistically analysed, second the spatial distribution of the loss data in the different hazard zones is assessed and third, vulnerability models for each hazard zone are developed including further parameters such as building values or building zones. A further objective is to provide an overview of possible methods which differ in complexity and data requirement and can be adapted for other applications outside of Switzerland. First results show that the extent of loss increases as the degree of hazard rises. In contrast, however, the number of damage events is highest in flood zones with a lower degree of hazard. Further possibilities how risk adaptation strategies can be supported or complemented by flood loss data are presented within this project.

How to cite: Mertin, M., Brughelli, M., Zischg, A., Röthlisberger, V., Schlögl, M., and Keiler, M.: Do hazard maps mirror loss data? – A vulnerability assessment based on loss data and hazard maps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19685, https://doi.org/10.5194/egusphere-egu2020-19685, 2020.

D1724 |
Chih-Hao Hsu, Ting-Chi Tsao, and Chuan-Yi Huang

In this study, several debris flow physical vulnerability curves and the even-based inundation depth were applied to a mountainous community hit by debris flow in 2015 to estimate the various possible loss ratio of each building. Then the comparison between estimated possible loss ratio and loss ratio determined by expert in the field is made to map out the distribution and deviation.

Vulnerability is commonly related to the consequences of natural hazard. For debris flow hazard these consequences are generally measured in terms of losses (Fuchs et al., 2007). In risk management vulnerability is an essential component for analyzing natural hazard risks (Lo et al., 2012). It is expressed on a scale from 0 (no damage) to 1 (total loss) and increasing with the intensity of hazard.

The Taoyuan DF034 debris flow potential torrent is located in northern Taiwan. In 2015, during Typhoon Soudelor the rainfall caused a shallow landslide which was transformed instantly into a debris flow. 13,000 cubic-meter of debris were washed out and deposited in 5,200 sq-meter area. Because of the evacuation before debris flow event, only 15 residential houses were inundated and no one was injured fortunately. In order to understand the inundation depth, the field investigation was executed shortly after the event. The building dimension, floor, structure type, location, and inundation depth were well documented and the loss ratio of each building was determined by expert as well.

The comparison of loss ratio based on inundation depth and impact pressure between Kang and Kim (2016), Papathoma-Köhle et al. (2015) and Lo et al. (2012) is made. The result shows building characters and debris flow velocity affect the loss ratio significantly.

Key Words: Debris flow, Vulnerability, Loss ratio, Taiwan

How to cite: Hsu, C.-H., Tsao, T.-C., and Huang, C.-Y.: Building loss ratio comparison based on physical vulnerability and event-based data in Taiwan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6619, https://doi.org/10.5194/egusphere-egu2020-6619, 2020.

D1725 |
Lea Dosser, Maria Papathoma-Köhle, Marco Borga, and Sven Fuchs

Because effects of climate change and an increase in elements at risk in many mountain areas, loss increased throughout Europe. Yet, factors influencing loss, i.e. physical vulnerability of elements at risk, have gained less attention to date. Here, vulnerability is defined as the degree of loss resulting from the hazard impact on the building envelope. Recent studies have focused on evaluating vulnerability to dynamic flooding using proxies from case studies and based on empirical ex-post approaches (Papathoma-Köhle et al., 2011; Papathoma-Köhle et al., 2017; Fuchs et al., 2019a). However, the transferability of resulting vulnerability functions or curves to other case studies and, therefore, the ability of such models to actually predict future losses, is limited.

Existing vulnerability curves for the expression of the physical vulnerability of buildings to dynamic flooding in the alpine space are associated with a large number of uncertainties. The updating of the existing curves with data from recent events is necessary in order to make existing curves more reliable. In the present study damage data from three torrential events in Italy (Campolongo, Province of Trento, 2010; Braies, Province of Bolzano, 2017; Rotian river creek, Province of Trento, 2018) are used to update existing curves that have been developed for similar settlement types and similar hazard events in the Austrian Alps. At first a new vulnerability curve is developed only for the new study sites and is being compared with existing vulnerability curves in the Austrian Alps. As a second step the new data are fed to the existing vulnerability models (Fuchs et al., 2019b) in order to update them. Preliminary results are presented.



Fuchs, S., Keiler, M., Ortlepp, R., Schinke, R., and Papathoma-Köhle, M.: Recent advances in vulnerability assessment for the built environment exposed to torrential hazards: challenges and the way forward, Journal of Hydrology, 575, 587-595, https://doi.org/10.1016/j.jhydrol.2019.05.067, 2019a.

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, 2019b.

Papathoma-Köhle, M., Kappes, M., Keiler, M., and Glade, T.: Physical vulnerability assessment for alpine hazards: state of the art and future needs, Natural Hazards, 58, 645-680, https://doi.org/10.1007/s11069-010-9632-4, 2011.

Papathoma-Köhle, M., Gems, B., Sturm, M., and Fuchs, S.: Matrices, curves and indicators: a review of approaches to assess physical vulnerability to debris flows, Earth-Science Reviews, 171, 272-288, https://doi.org/10.1016/j.earscirev.2017.06.007, 2017.

How to cite: Dosser, L., Papathoma-Köhle, M., Borga, M., and Fuchs, S.: Updating of existing vulnerability curves with data from recent events in the European Alps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1650, https://doi.org/10.5194/egusphere-egu2020-1650, 2020.

D1726 |
Florian Roesch, Maria Papathoma-Köhle, and Sven Fuchs

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.

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.



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.

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.

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.

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.

How to cite: Roesch, F., Papathoma-Köhle, M., and Fuchs, S.: Vulnerability curves vs. vulnerability indices. Which method explains loss best?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1571, https://doi.org/10.5194/egusphere-egu2020-1571, 2020.

D1727 |
Sven Fuchs, Maria Papathoma-Köhle, Reinhard Schinke, Regine Ortlepp, and Margreth Keiler

Regardless of the frequency and magnitude, the consequences of flood hazards are strongly connected to the vulnerability of elements at risk (e.g. buildings, people, and infrastructure). It is, therefore, obvious that an analysis and quantification of vulnerability is required for successful risk reduction. Vulnerability is multidimensional (physical, social, economic, institutional, etc.), however, the primary driver of direct costs and threat to human lives is the physical one. We focus here on the physical vulnerability of buildings subject to dynamic flooding occurring in mountain environments. These processes include debris floods, fluvial sediment transport, and debris flows. Furthermore, we included flash flood hazards if these are related to torrential catchments.

Physical vulnerability to dynamic flooding in mountain areas is a topic that has been under scientific investigation over the last 20 years. Several methods to assess physical vulnerability of buildings towards flash floods, debris flows and hyper-concentrated flows can be found in the literature. The plethora of methods and approaches may be classified under the following three categories: vulnerability matrices, vulnerability curves and vulnerability indices. We provide a short review of these methods which became available over the last decade and which dominate the scientific debate in mountain hazard risk management, giving an emphasis to vulnerability curves. The approaches presented herein are highlighted through case studies from the mountain areas of Europe and beyond, and challenges in vulnerability assessment including data requirements, need for improved event documentation, uncertainties and challenges related to future climate and socio-economic changes are outlined. Finally, a discussion on progress-driving factors such as new technologies (e.g. mobile apps, drones), citizen science and new innovative assessment methods is provided.

How to cite: Fuchs, S., Papathoma-Köhle, M., Schinke, R., Ortlepp, R., and Keiler, M.: Recent advances in vulnerability assessment for the built environment exposed to dynamic flooding, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17379, https://doi.org/10.5194/egusphere-egu2020-17379, 2020.

D1728 |
Simantini Shinde, Juan Camilo Gomez- Zapata, Massimiliano Pittore, Orlando Arroyo, Yvonne Merino- Peña, Paula Aguirre, and Hernán Santa María

The modelling of residential building portfolio exposure model for risk and loss estimations due to natural hazards often do not receive as much attention as other components in the risk chain (e.g. hazard intensity distribution, physical vulnerability). Large-scale (nation or region-wide) exposure models, for instance, are often based on information derived from census and aggregated over geographical administrative units. Moreover, it is customary to employ specific exposure/vulnerability schemas that entail a set of mutually exclusive, collectively exhaustive (MECE) building classes, each associated with a fragility/vulnerability model focusing on the specific reference hazard (e.g. HAZUS).

In order to improve the reliability of these models, particularly when the composition of the portfolio is expected to be heterogeneous, individual building observations may be required. This process is relevant in order to constrain and validate the underlying model assumptions. The assignment of  single-hazard building classes within a given schema is usually obtained through expert elicitation (e.g., a skilled surveyor). However, if the very same building has to be classified under another vulnerability schema, either for the same hazard (e.g. EMS98 and HAZUS for seismic risk) or, in a multi-risk context, for a different hazard (e.g. tsunami, lahars), this might require a different expertise and the uncertainty of the resulting models could even increase.

We propose an innovative method to decouple the collection of exposure information from the development of exposure models in terms of specific vulnerability classes (schemas). Taking advantage of the methodology suggested by Pittore et al., 2018, individual building attributes are observed in the field for a set of surveyed buildings and described in terms of the GEM v2.0 taxonomy,  a widely used and well-established faceted building taxonomy (Brzev et al., 2013). The assignment of a class is carried out in a post-processing stage and within a fully probabilistic framework by evaluating the level of compatibility between the observed building attributes and the classes available within the considered schema.

The proposed methodology has been exemplified in Chile and Peru within the framework of the RIESGOS project. Expert structural engineers from CIGIDEN (Chile) and the Universidad de la Sabana (Colombia) carried out a Rapid Remote Visual Screening Survey using the RRVS web tool (e.g. Haas et al., 2016). In the case of seismic risk we focused on three schemas, namely SARA (a custom schema developed within the GEM-SARA Project in South America), and the well-known EMS-98 and HAZUS. The tsunami-focused schema proposed by Suppasri et al. (2013) has been also implemented.

Preliminary results for Gran Valparaiso (Chile) and Metropolitan Lima (Peru) study areas show the potential of the proposed methodology for streamlining the development of multi-hazard exposure models and significantly improving the transparency of the risk assessment procedures and the propagation of related uncertainties. The importance of extending the building taxonomy to encompass multi-hazard attributes is also discussed.

How to cite: Shinde, S., Gomez- Zapata, J. C., Pittore, M., Arroyo, O., Merino- Peña, Y., Aguirre, P., and Santa María, H.: Development of multi-hazard exposure models from individual building observations for multi-risk assessment purposes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11719, https://doi.org/10.5194/egusphere-egu2020-11719, 2020.

D1729 |
Unni Eidsvig, Nikola Tanasic, Rade Hajdin, Christina Ekeheien, and Luca Piciullo

Our modern society relies on well-functioning transport systems providing mobility, transport safety and regularity. Maintaining the operational state of roads and railways during extreme weather events or other natural events is an important and demanding task. Natural events may cause damage to transportation assets, which can immediately or over time result in functional loss of a transportation line. For instance, a reduced culvert capacity due to debris deposition and clogging, could cause flooding of a road/rail. Some natural events can lead directly to loss of service, even without damaging an asset, like the occurrence of avalanches on a transportation line, blocking the related traffic. To reduce risks of failures posed by natural hazards, it is essential to assess vulnerability of transportation networks to such events.

A well-established way to analyse vulnerability is to use damage-, loss- or fragility functions. Such functions can express both functional vulnerability, representing the functional loss for a transportation line, and structural vulnerability representing damage degree or the exceedance probability of damage levels pertinent to a transportation asset. These functions can all be expressed in terms of event intensity, which is a parameter characterizing the damaging potential of a natural event.

In order to analyse functional vulnerability, various asset types with their interdependencies i.e. network topology and geographical coincidence must be considered. Here, the applied damage and fragility functions for evaluating structural vulnerability must account for location specific data on assets and asset properties. The review of existing damage-, loss- and fragility functions showed that these are not sufficient for intended analysis and need to be updated to consider various natural events and related failure modes. Recommendations are provided on how to elaborate new damage-, loss- and fragility functions to overcome a large number of uncertainties related to impacts of natural events on infrastructure and account for resistance of infrastructure. These recommendations concern both the choice of intensity parameters for different types of hazards and definition of possible failure modes, the methods for developing the functions and the assessment of the relationship between structural vulnerability of the asset and functional vulnerability.

The research leading to these and future results receives funding from the European Community’s H2020 Programme MG-7-1-2017 Resilience to extreme (natural and man-made) events, under Grant Agreement number: 769255 - "GIS-based infrastructure management system for optimized response to extreme events of terrestrial transport networks (SAFEWAY)".

How to cite: Eidsvig, U., Tanasic, N., Hajdin, R., Ekeheien, C., and Piciullo, L.: Vulnerability of terrestrial transportation lines to natural events, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9542, https://doi.org/10.5194/egusphere-egu2020-9542, 2020.

D1730 |
Bernhard Ullrich, Maria Papathoma-Köhle, and Sven Fuchs

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.

How to cite: Ullrich, B., Papathoma-Köhle, M., and Fuchs, S.: Mountain hazards and Building Back Better (BBB) – focus on the Austrian Alps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1572, https://doi.org/10.5194/egusphere-egu2020-1572, 2020.

D1731 |
Susanne Repanelis, Sven Fuchs, and Maria Papathoma-Köhle

The North Aegean Sea prefecture consists of nine islands, Lesvos being the biggest of them and the institutional and political centre with approximately 85,000 inhabitants, and Agios Efstratios the smallest island with 280 inhabitants. Lesvos is often confronted with earthquakes, floods, flash floods, wildfires, and unstable slopes (landslides). Agios Efstratios experienced one of the largest earthquakes ever recorded in Greece (7.1 Richter in 1968) and recently (2017) was in a state of emergency due to the extreme overpopulation of locusts resulting to serious environmental degradation, leading to mass death of dairy animals which are essential for agriculture in a remote island. Apart from natural hazards, both islands under study are confronted with challenges linked to the refugee influx and their remoteness including isolation, fragmentation and population decline. The study aims at exploring different dimensions of vulnerability (physical, social, institutional and economic) and risk perception among citizens on both islands and their connection to remoteness. Preliminary results from individual case studies on both islands (Eressos, Mesotopos, Sykamia in Lesvos and Agios Efstratios) will be presented.

How to cite: Repanelis, S., Fuchs, S., and Papathoma-Köhle, M.: Vulnerability to natural hazards and risk perception in remote islands – the case of Lesvos and Agios Efstratios, Greece, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1570, https://doi.org/10.5194/egusphere-egu2020-1570, 2020.

D1732 |
Maria Papathoma-Koehle, Fotis Maris, and Sven Fuchs

To a great extent, literature concerning efforts to assess vulnerability to natural hazards focuses on the vulnerability of mega-cities and urban areas due to the significant concentration of vital assets and high population density in a relatively small area. However, the antipode of this condition, the one of remoteness, insularity and isolation also constitutes a major drive of vulnerability to natural hazards. Remote areas are often dependent on decisions that are taken somewhere else, such as central governments, and they have limited funds for preparedness but also limited material and human resources to respond to natural hazards. Remote areas can be found in many regions across Europe including the European Alps, the Scandinavian tundra and small islands in the North Sea but also in the Mediterranean. However, in the European south, the capacities of remote areas have deteriorated further due to the recent financial crisis and austerity measures.

An integrated approach to vulnerability is attempted for the island of Samothraki, Greece. The specific island is located in the northeast part of the country, and despite the relatively short distance to the coast of Greece and Turkey, it is particularly isolated due to the poor transport connections to the mainland, demographic problems, the effects of the financial crisis and governance particularities. In September 2017 Samothraki was affected by a major torrential event that revealed its vulnerabilities and the vulnerabilities of remote areas in general. The vulnerabilities investigated in this study include physical, social, economic and institutional. A framework for the assessment of these vulnerabilities in remote areas and some preliminary results are presented.

How to cite: Papathoma-Koehle, M., Maris, F., and Fuchs, S.: Remoteness and austerity: a major driver of vulnerabilities to natural hazards, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1577, https://doi.org/10.5194/egusphere-egu2020-1577, 2020.

D1733 |
Marleen de Ruiter, Jens de Bruijn, James Daniell, Johanna Englhardt, Philip Ward, and Hans de Moel

Many countries face the risk of multiple hazards. The UNDRR’s Global Platform for Disaster Risk Reduction have called upon the science community for an increased understanding of the complexities of multi-hazard risk (UNDRR 2019). Nonetheless, in the currently prevailing risk assessment paradigm, risk is often represented as static and fragmented in terms of hazard types. While positively influencing the risk of one hazard, DRR measures can have adverse effects on the risk of another hazard type thereby increasing the vulnerability of the built environment, exacerbating impacts and potentially causing compound or cascading disasters. For example, wood-frame buildings tend to perform well under ground shaking but are likely to sustain higher damages due to an inundation than concrete buildings. We refer to these negative impacts between hazards as the asynergy of a DRR measure. Due to the predominantly single-hazard approach, the potential asynergies of DRR measures remain poorly understood.

In a case study of Afghanistan, we calculate the asynergies of building level DRR measures for floods and earthquakes. To this extent, we develop two increased-resilience scenarios where a decrease in flood and earthquake vulnerability are mimicked. These scenarios are used to assess the asynergies and to illustrate to what degree a risk reduction of one risk may actually be offset by an increase of the other risk. This can then be used to show which type of measure is worthwhile in which area.

An improved capability of understanding risk more holistically would strongly benefit first responders, aid organizations, urban planners and decision makers in designing sustainable DRR measures. We discuss several key potential asynergies of building level DRR measures for floods and earthquakes tailored to decrease the risk of one hazard on the risk of the other hazard. Finally, we outline a roadmap highlighting key future research and policy directions, and possible ways to strengthen coherent policies for DRR.

How to cite: de Ruiter, M., de Bruijn, J., Daniell, J., Englhardt, J., Ward, P., and de Moel, H.: The asynergies of disaster risk reduction measures in Afghanistan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-79, https://doi.org/10.5194/egusphere-egu2020-79, 2020.

D1734 |
Diana Popovici, Iuliana Armaș, Dragoș Toma-Dănilă, and Alexandru Gavriș

Big cities are prone to suffer important losses, both economic and human, in case of a risk occurrence. Bucharest is the most vulnerable European capital to earthquakes due to its exposure, being located about 130 km from the main seismic region of the country – Vrancea Region, and also due to its high physical and social vulnerability.

Based on the past experiences and on the present development of the city, there is an urge to find and to develop measures and policies for seismic risk mitigation. The first step in this direction, which is also the aim of the present work, is to assess the current situation regarding the vulnerability of the city and to understand the dimension of the losses throughout the city in case of a major earthquake event.

In this study we discuss the best locations to deploy shelters which can provide first-aid and temporary residence for those who lost their homes after an earthquake event. Our research is based on estimating the losses at a detailed scale and by knowing the limitations of the infrastructure (including emergency hospitals and roads) and of the public services (like the firefighters, ambulances, police, medical care etc.).

Social, economic and housing quality criteria were integrated in a multicriteria analysis in order to assess the most vulnerability hotspots at city level and to estimate losses. The results showed the presence of two extended areas, situated in the south-west and the western part of the city, with high vulnerability scores and high potential losses. These two areas were introduced into a new multicriteria analysis for finding suitable locations that can be used as indoor and outdoor shelters.

Our study is a step forward to increase the preparedness of the population, that will know where to go in case of need. It will also help the authorities that will better allocate their resources and overall mitigate the seismic risk.

How to cite: Popovici, D., Armaș, I., Toma-Dănilă, D., and Gavriș, A.: Emergency shelter selection in the context of seismic risk. Case study – Bucharest, Romania, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11321, https://doi.org/10.5194/egusphere-egu2020-11321, 2020.

D1735 |
Giuseppe Nicodemo, Massimiliano Pittore, Angelo Masi, and Vincenzo Manfredi

Post-earthquake damage and usability surveys are fundamental in managing the emergency phase in the aftermath of a strong seismic event, for instance deciding whether the people could safely come back to their houses or be hosted in temporary shelters. In Italy, in addition to the damage and usability evaluation, this survey enables the collection of geometrical and structural attributes highly related to seismic vulnerability. These data are collected for individual buildings in the order of many tens of thousands for recent events and represent a unique source of exposure and vulnerability information and a very useful tool for Disaster Risk Reduction (DRR) and prevention activities. With the development of the “Observed Damage Database” (Da.D.O.; Dolce et al., 2017) web-based platform, most of the data collected during the post-earthquake inspections carried out over the last 50 years has been harmonized and made freely available to the scientific community. These data constitute an important heritage for scientific purposes but, until now, their potential for seismic risk assessment has not been fully exploited, partly because the format specifications are very particular to the environmental conditions to be found in Italy, and the collected attributes are not directly related to existing risk-oriented classifications. In order to reliably extract the exposure, vulnerability and damage information collected for Italian earthquakes and harmonize it according to recognized international standards, an innovative methodology has been developed to convert the information collected through the “1° level form for post-earthquake damage and safety assessment and short term countermeasures in residential buildings” (AeDES form; Baggio et al., 2007; Masi et al., 2016) to different formats more suitable for a large-scale risk evaluation and comparison. In the proposed approach, the information on the typological characteristics is firstly described according to the taxonomy proposed by “Global Earthquake Model” (GEM) (v2.0, Brzev et al., 2013). In a following processing step, using a score-based methodology (Pittore et al., 2018), we can assign EMS-98 building classes (Grünthal, 1998) on the basis of the GEM attributes. The proposed method allows for an extensive characterization of the uncertainty underlying the conversion process, encoded by the use of a probabilistic framework. A similar approach can be used to map the damage data into the categories defined by the EMS-98 scale. This methodology has been exemplified with the data of the Mw 6.3 2009 L´Aquila earthquake as provided by the Da.D.O. platform, and the results highlight the great potential for post-event surveys to provide relevant information also for DRR and risk prevention activities.

Keywords: seismic risk, post-earthquake survey, exposure, taxonomy

How to cite: Nicodemo, G., Pittore, M., Masi, A., and Manfredi, V.: Modelling exposure and vulnerability from post-earthquake surveys with risk-oriented taxonomies: AeDES form, GEM taxonomy and EMS-98 typologies, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20572, https://doi.org/10.5194/egusphere-egu2020-20572, 2020.

D1736 |
A GRaph-based Assessment Model (GRAM) for natural hazard risk of complex built environment: case study in Monza city
not presented
Marcello Arosio, Luigi Cesarini, Giacomo Galuppini, Margherita Dayala, Mario L.V. Martina, and Enrico Creaco
D1737 |
Zaharatu Babika, Thomas Kjeldsen, and Lee bryant

Groundwater is a scarce yet vital resource in many arid and semi-arid regions of the world. where it serves as water supply for a majority of the population. The quality of this resource is depreciating, however due to pollution levels reaching intolerable limits as a result of unplanned urbanization and industrialization. In this study, the capabilities of two commonly used groundwater vulnerability models, DRASTIC and GOD, are assessed for correctly classifying the risk of hydrocarbon pollution within the city of Kano, located in semi-arid northern Nigeria. Most existing groundwater vulnerability assessment tools have been developed for use in Europe and North America under generally humid conditions; conversely, vulnerability assessment of groundwater in arid and semi-arid is much less developed.
 Combined analysis of large-scale existing data sources on hydro-meteorological, environmental and anthropogenic factors will be used to evaluate the vulnerability of groundwater resources in Kano, a city of ~4 million people within 137 square kilometres.  In this study, the two models (DRASTIC and GOD) are assessed based on data provided by Nigerian water resources administrations and obtained via field monitoring to detect areas that are vulnerable to groundwater contamination based on the hydrogeological structure and local sources of hydrocarbon contamination. Several groundwater contamination sources have been identified such as automobile shops, household dumpsites, and petrol dispensing stations.Mapping of environmental factors was conducted within the framework of Geographical information systems (GIS), and  preliminary results show a range of very high to moderate vulnerability classes exist within the build-up areas of Kano. A sensitivity evaluation of the various parameters required for each of these models has also been performed to identify the controlling parameters within this semi-arid environment. Building on these results, the next phase of this research will focus on development of a modified vulnerability model based on these identified controlling parameters and model validation using field observations.

How to cite: Babika, Z., Kjeldsen, T., and bryant, L.: Mapping Groundwater Vulnerability and Risk of hydro-carbon Contamination in a Semi-Arid Region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-532, https://doi.org/10.5194/egusphere-egu2020-532, 2020.