This page has only limited features, please log in for full access.
We propose the use of variable resolution boundaries based on Central Voronoi Tessellations (CVT) to spatially aggregate building exposure models for risk assessment to various natural hazards. Such a framework is especially beneficial when the spatial distribution of the considered hazards present intensity measures with contrasting footprints and spatial correlations such as in coastal environments. This proposal avoids the incorrect assumption that a single intensity value from hazards with low spatial correlation (e.g. tsunami) are considered as representative within large sized geocells for physical vulnerability assessment, without, at the same time, increasing the complexity of the overall model. We present decoupled earthquake and tsunami scenario-based risk estimates for the residential building stock of Lima (Peru). We observe that earthquake loss models for far-field subduction sources are practically insensitive to the exposure resolution. Conversely, tsunami loss models and associated uncertainties depend on the spatial correlations of the hazard intensities as well as on the resolution of the exposure models. We observe that for the portfolio located in the coastal area exposed to both perils in Lima, the ground-shaking dominates the losses for lower magnitudes whilst the tsunami does for the larger ones. For the latter, two sets of existing empirical flow-depth fragility models are used, finding large differences in the losses. This study arises awareness about the uncertainties in the selection of fragility models and aggregations entities for exposure modelling and loss mapping.
Juan Camilo Gomez-Zapata; Nils Brinckmann; Sven Harig; Raquel Zafrir; Massimilano Pittore; Fabrice Cotton; Andrey Babeyko. Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment. An application case in Lima, Peru. 2021, 2021, 1 -30.
AMA StyleJuan Camilo Gomez-Zapata, Nils Brinckmann, Sven Harig, Raquel Zafrir, Massimilano Pittore, Fabrice Cotton, Andrey Babeyko. Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment. An application case in Lima, Peru. . 2021; 2021 ():1-30.
Chicago/Turabian StyleJuan Camilo Gomez-Zapata; Nils Brinckmann; Sven Harig; Raquel Zafrir; Massimilano Pittore; Fabrice Cotton; Andrey Babeyko. 2021. "Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment. An application case in Lima, Peru." 2021, no. : 1-30.
Exposure describes elements which are imperiled by natural hazards and susceptible to damage. The affiliated vulnerability characterizes the likelihood to experience damage regarding a given level of hazard intensity. Frequently, the compilation of exposure information is the costliest component (in terms of time and labor) in risk assessment. Existing data sets and models often describe exposure in an aggregated manner, e.g., by relying on statistical/census data for given administrative entities. Nowadays, earth observation techniques allow to collect spatially continuous information for large geographic areas while enabling a high geometric and temporal resolution. In parallel, modern data interpretation tools based on Artificial Intelligence concepts enable the extraction of thematic information from such data with a high accuracy and detail. Consequently, we exploit measurements from the earth observation missions TanDEM-X and Sentinel-2, which collect data on a global scale, to characterize the built environment in terms of fundamental morphologic properties, namely built-up density and height. Subsequently, we use this information to constrain existing exposure data in a spatial disaggregation approach. Thereby, we compare different methods for disaggregation and evaluate how different resolution properties of the earth observation data affect the risk assessment result. Results are presented for the city of Santiago de Chile, Chile, which is prone to natural hazards such as earthquakes. We present loss estimations and corresponding sensivity with respect to the resolution properties of the exposure data used in the model. Thereby, it can be noted how loss estimations vary substantially and that aggregated exposure information underestimates losses in our scenarios. As such, this study underlines the benefits of deploying modern earth observation technologies for refined exposure estimation and related loss estimation.
Christian Geiß; Patrick Aravena Pelizari; Peter Priesmeier; Angélica Rocio Soto Calderon; Elisabeth Schoepfer; Michael Langbein; Torsten Riedlinger; Hernán Santa María; Juan Camilo Gómez Zapata; Massimiliano Pittore; Hannes Taubenböck. Earth Observation Techniques for Spatial Disaggregation of Exposure Data . 2021, 1 .
AMA StyleChristian Geiß, Patrick Aravena Pelizari, Peter Priesmeier, Angélica Rocio Soto Calderon, Elisabeth Schoepfer, Michael Langbein, Torsten Riedlinger, Hernán Santa María, Juan Camilo Gómez Zapata, Massimiliano Pittore, Hannes Taubenböck. Earth Observation Techniques for Spatial Disaggregation of Exposure Data . . 2021; ():1.
Chicago/Turabian StyleChristian Geiß; Patrick Aravena Pelizari; Peter Priesmeier; Angélica Rocio Soto Calderon; Elisabeth Schoepfer; Michael Langbein; Torsten Riedlinger; Hernán Santa María; Juan Camilo Gómez Zapata; Massimiliano Pittore; Hannes Taubenböck. 2021. "Earth Observation Techniques for Spatial Disaggregation of Exposure Data ." , no. : 1.
Knowledge on the key structural characteristics of exposed buildings is crucial for accurate risk modeling with regard to natural hazards. In risk assessment this information is used to interlink exposed buildings with specific representative vulnerability models and is thus a prerequisite to implement sound risk models. The acquisition of such data by conventional building surveys is usually highly expensive in terms of labor, time, and money. Institutional data bases such as census or tax assessor data provide alternative sources of information. Such data, however, are often inappropriate, out-of-date, or not available. Today, the large-area availability of systematically collected street-level data due to global initiatives such as Google Street View, among others, offers new possibilities for the collection of in-situ data. At the same time, developments in machine learning and computer vision – in deep learning in particular – show high accuracy in solving perceptual tasks in the image domain. Thereon, we explore the potential of an automatized and thus efficient collection of vulnerability related building characteristics. To this end, we elaborated a workflow where the inference of building characteristics (e.g., the seismic building structural type, the material of the lateral load resisting system or the building height) from geotagged street-level imagery is tasked to a custom-trained Deep Convolutional Neural Network. The approach is applied and evaluated for the earthquake-prone Chilean capital Santiago de Chile. Experimental results are presented and show high accuracy in the derivation of addressed target variables. This emphasizes the potential of the proposed methodology to contribute to large-area collection of in-situ information on exposed buildings.
Patrick Aravena Pelizari; Christian Geiß; Elisabeth Schoepfer; Torsten Riedlinger; Paula Aguirre; Hernán Santa María; Yvonne Merino Peña; Juan Camilo Gómez Zapata; Massimiliano Pittore; Hannes Taubenböck. Street-Level Imagery and Deep Learning for Characterization of Exposed Buildings. 2021, 1 .
AMA StylePatrick Aravena Pelizari, Christian Geiß, Elisabeth Schoepfer, Torsten Riedlinger, Paula Aguirre, Hernán Santa María, Yvonne Merino Peña, Juan Camilo Gómez Zapata, Massimiliano Pittore, Hannes Taubenböck. Street-Level Imagery and Deep Learning for Characterization of Exposed Buildings. . 2021; ():1.
Chicago/Turabian StylePatrick Aravena Pelizari; Christian Geiß; Elisabeth Schoepfer; Torsten Riedlinger; Paula Aguirre; Hernán Santa María; Yvonne Merino Peña; Juan Camilo Gómez Zapata; Massimiliano Pittore; Hannes Taubenböck. 2021. "Street-Level Imagery and Deep Learning for Characterization of Exposed Buildings." , no. : 1.
The inhabitants of Latacunga living in the surrounding of the Cotopaxi volcano (Ecuador) are exposed to several hazards and related disasters. After the last 2015 volcanic eruption, it became evident once again how important it is for the exposed population to understand their own social, physical, and systemic vulnerability. Effective risk communication is essential before the occurrence of a volcanic crisis. This study integrates quantitative risk and semi-quantitative social risk perceptions, aiming for risk-informed communities. We present the use of the RIESGOS demonstrator for interactive exploration and visualisation of risk scenarios. The development of this demonstrator through an iterative process with the local experts and potential end-users increases both the quality of the technical tool as well as its practical applicability. Moreover, the community risk perception in a focused area was investigated through online and field surveys. Geo-located interviews are used to map the social perception of volcanic risk factors. Scenario-based outcomes from quantitative risk assessment obtained by the RIESGOS demonstrator are compared with the semi-quantitative risk perceptions. We have found that further efforts are required to provide the exposed communities with a better understanding of the concepts of hazard scenario and intensity.
Juan Gomez-Zapata; Cristhian Parrado; Theresa Frimberger; Fernando Barragán-Ochoa; Fabio Brill; Kerstin Büche; Michael Krautblatter; Michael Langbein; Massimiliano Pittore; Hugo Rosero-Velásquez; Elisabeth Schoepfer; Harald Spahn; Camilo Zapata-Tapia. Community Perception and Communication of Volcanic Risk from the Cotopaxi Volcano in Latacunga, Ecuador. Sustainability 2021, 13, 1714 .
AMA StyleJuan Gomez-Zapata, Cristhian Parrado, Theresa Frimberger, Fernando Barragán-Ochoa, Fabio Brill, Kerstin Büche, Michael Krautblatter, Michael Langbein, Massimiliano Pittore, Hugo Rosero-Velásquez, Elisabeth Schoepfer, Harald Spahn, Camilo Zapata-Tapia. Community Perception and Communication of Volcanic Risk from the Cotopaxi Volcano in Latacunga, Ecuador. Sustainability. 2021; 13 (4):1714.
Chicago/Turabian StyleJuan Gomez-Zapata; Cristhian Parrado; Theresa Frimberger; Fernando Barragán-Ochoa; Fabio Brill; Kerstin Büche; Michael Krautblatter; Michael Langbein; Massimiliano Pittore; Hugo Rosero-Velásquez; Elisabeth Schoepfer; Harald Spahn; Camilo Zapata-Tapia. 2021. "Community Perception and Communication of Volcanic Risk from the Cotopaxi Volcano in Latacunga, Ecuador." Sustainability 13, no. 4: 1714.
In seismic risk assessment the sources of uncertainty associated to building exposure modelling have not received as much attention as other components related to hazard and vulnerability. We are introducing that the degree of knowledge of a building portfolio can be described within a Bayesian probabilistic approach to acknowledge the epistemic uncertainty of its composition (i.e. proportions per building class). We are investigating the impact of such uncertainty on earthquake loss models through a novel approach based on an exposure-oriented logic tree arrangement and scenario-based seismic risk simulations. We have found that the building class reconnaissance either from prior assumptions by desktop studies with aggregated data (top-down approach) or from building-by-building data collection (bottom-up approach), plays a fundamental role in statistical modelling of exposure. We successively show that the selection of the basic set of building classes is a major contribution to the uncertainties in the loss estimations given their dependence on specific fragility functions. If the set of fragility functions handle multiple spectral periods, cross-correlated ground motion fields are required for the vulnerability assessment which ultimately control the variability of the losses. When the exposure composition is poorly known due to, for instance, simplifications and assumptions over aggregated data, its absolute contribution to the loss uncertainties has been found to be larger than the one imposed by the spatially distributed cross-correlated ground motion fields. This work invites to redesign desktop exposure studies, while it also highlights the importance of a standardized iterative approach to exposure data collection and modelling.
Juan Camilo Gomez-Zapata; Massimiliano Pittore; Fabrice Cotton; Henning Lilienkamp; Simantini Shinde; Paula Aguirre; Hernan Santa Maria. Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models. 2021, 1 .
AMA StyleJuan Camilo Gomez-Zapata, Massimiliano Pittore, Fabrice Cotton, Henning Lilienkamp, Simantini Shinde, Paula Aguirre, Hernan Santa Maria. Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models. . 2021; ():1.
Chicago/Turabian StyleJuan Camilo Gomez-Zapata; Massimiliano Pittore; Fabrice Cotton; Henning Lilienkamp; Simantini Shinde; Paula Aguirre; Hernan Santa Maria. 2021. "Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models." , no. : 1.
Residential building exposure models for risk and loss estimations related to natural hazards are usually defined in terms of specific schemas describing mutually exclusive, collectively exhaustive (MECE) classes of buildings. These models are derived from: (1) the analysis of census data or (2) by means of individual observations in the field. In the first case, expert elicitation has been conventionally used to classify the building inventory into particular schemas, usually aggregated over geographical administrative units whose size area and shape are country-specific. In the second case, especially for large urban areas, performing a visual inspection of every building in order to assign a class according to the specific schema used is a highly time- and resource intensive task, often simply unfeasible.
Remote sensing data based on the analysis of satellite imagery has proved successful in integrating large-scale information on the built environment and as such can provide valuable vulnerability-related information, although often lacking the level of spatial and thematic resolution requested by multi-hazard applications. Volunteered Geo Information (VGI) data can also prove useful in this context, although in most cases only geometric attributes (shape of the building footprint) and some occupancy information are recorded thus leaving out most of the building attributes controlling the vulnerability of the structures to the different hazards. An additional drawback of VGI is the incompleteness of the information, which is based on the unstructured efforts of voluntary mappers.
Former efforts have been proposing a top-down/bottom-up approach moving from regional scale to neighbourhood and per-building scale, based on the analysis and integration of different data sources at increasing spatial resolutions and thematic detail. Following the same principle, this work focuses on the downscaling of already existing building exposure models based on census data making use of a probabilistic approach based on Bayesian updating. Different aggregation models can be taken into account to increase the spatial resolution of the building exposure model, also including variable-resolution models based on geostatistical approaches. Land-use masks are first generated after a supervised classification of Sentinel-2 images, in order to better relate the built- up area to meaningful geographical entities. Two independent statistical models are then created based on prior input information. Maximum likelihood estimations are obtained for each model. Two types of auxiliary data have been employed in order to constrain the downscaling via a specific likelihood term in the Bayesian updating: 1) building footprints area from the open-source-volunteered geo-information OpenStreetMaps and 2) built-up height and density estimators based on remote sensing developed by the DLR (the German Aerospace Agency).
This approach, developed within the scope of the RIESGOS, was tested in Valparaiso and Viña del Mar (Chile) where the residential building exposure model proposed by the GEM-SARA project has been downscaled. The performance of the different auxiliary data were separately tested and compared. An independent building survey has also been carried out by experts from CIGIDEN (Chile) using a Rapid Remote Visual Screening Survey and used for preliminary validation of the approach.
Raquel Zafrir; Massimiliano Pittore; Juan Camilo Gomez- Zapata; Patrick Aravena; Christian Geiß. Bayesian downscaling of building exposure models with remote sensing and ancillary information. 2020, 1 .
AMA StyleRaquel Zafrir, Massimiliano Pittore, Juan Camilo Gomez- Zapata, Patrick Aravena, Christian Geiß. Bayesian downscaling of building exposure models with remote sensing and ancillary information. . 2020; ():1.
Chicago/Turabian StyleRaquel Zafrir; Massimiliano Pittore; Juan Camilo Gomez- Zapata; Patrick Aravena; Christian Geiß. 2020. "Bayesian downscaling of building exposure models with remote sensing and ancillary information." , no. : 1.
In order to assess the building portfolio composition for a particular natural hazard risk assessment application, it is necessary to classify the built environment into schemas containing building classes. The building classes should also address the attributes which may control their vulnerability towards the different hazards associated with their failure mechanisms, which along with their respective fragility functions are representative of a particular study area. In the case of volcanic risk, former efforts have been carried out in developing volcanic related fragility functions, this has been done mostly for European, Atlantic islands and South Asian building types (SEDIMER, MIA VITA, VOLDIES, EXPLORIS, SAFELAND projects). However, in other parts of the globe, particular construction practices, materials, and even occupancies may describe very diverse building types with different degrees of vulnerability which may or not be compatible with the existing schemas and fragility functions (Spence et al. 2005, Zuccaro et al. 2013, Mavrouli et al. 2013, Jenkins et al. 2014, Torres-Corredor et al. 2017).
As highlighted by Zuccaro et al. 2018, since in the case of volcanic active areas, the built environment will not only be exposed to a single hazard but to several compound or cascading hazards (e.g. tephra fall, pyroclastic flows, lahars), with different time intervals between them, a dynamic vulnerability with cumulated damage on the physical assets would be the baseline upon a multi-risk- volcanic framework should be described. In this similar context, single- hazard but still multi-state fragility functions have been very recently used in order to set up damage descriptions independently on the reference building schema. We propose to generalize this novel approach and further extend it in the volcanic risk assessment context. To do so, the very first step was to generate a multi-hazard- building- taxonomy containing a set of exhaustive mutually exclusive building attributes. Upon that framework, a probabilistic mapping across single- hazards- building- schemas and damage states has been achieved.
This methodological approach has been tested under the RIESGOS project over a selected study area of the Latin American Andes Region. In this region, cities close to active volcanos have been experienced a non-structured grow, which is translated into a significantly vulnerable population living in non- engineering buildings that are highly exposed to volcanic hazards. The Cotopaxi region in Ecuador has been chosen in order to explore the ash falls and lahars damage contributions with several scenarios in terms of volcanic explosivity index (VEI). Local lahars simulations have been obtained at different resolutions. Moreover, probabilistic ash- fall maps have been recently obtained after exhaustive ash fall and wind direction measurements. Lahar flow- velocity and ash- fall load pressure were respectively used as intensity measures. Furthermore, local and foreign building schemas that define the building exposure models have been constrained through ancillary data, cadastral information, and remote individual building inspections, to then been associated with a multi-state fragility function. These ingredients have been integrated into this novel methodological scenario-based- multi-risk- volcanic assessment.
Michael Langbein; Juan Camilo Gomez- Zapata; Theresa Frimberger; Nils Brinckmann; Roberto Torres- Corredor; Daniel Andrade; Camilo Zapata- Tapia; Massimiliano Pittore; Elisabeth Schoepfer. Scenario- based multi- risk assessment on exposed buildings to volcanic cascading hazards. 2020, 1 .
AMA StyleMichael Langbein, Juan Camilo Gomez- Zapata, Theresa Frimberger, Nils Brinckmann, Roberto Torres- Corredor, Daniel Andrade, Camilo Zapata- Tapia, Massimiliano Pittore, Elisabeth Schoepfer. Scenario- based multi- risk assessment on exposed buildings to volcanic cascading hazards. . 2020; ():1.
Chicago/Turabian StyleMichael Langbein; Juan Camilo Gomez- Zapata; Theresa Frimberger; Nils Brinckmann; Roberto Torres- Corredor; Daniel Andrade; Camilo Zapata- Tapia; Massimiliano Pittore; Elisabeth Schoepfer. 2020. "Scenario- based multi- risk assessment on exposed buildings to volcanic cascading hazards." , no. : 1.
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.
Simantini Shinde; Juan Camilo Gomez- Zapata; Massimiliano Pittore; Orlando Arroyo; Yvonne Merino- Peña; Paula Aguirre; Hernán Santa María. Development of multi-hazard exposure models from individual building observations for multi-risk assessment purposes. 2020, 1 .
AMA StyleSimantini Shinde, Juan Camilo Gomez- Zapata, Massimiliano Pittore, Orlando Arroyo, Yvonne Merino- Peña, Paula Aguirre, Hernán Santa María. Development of multi-hazard exposure models from individual building observations for multi-risk assessment purposes. . 2020; ():1.
Chicago/Turabian StyleSimantini Shinde; Juan Camilo Gomez- Zapata; Massimiliano Pittore; Orlando Arroyo; Yvonne Merino- Peña; Paula Aguirre; Hernán Santa María. 2020. "Development of multi-hazard exposure models from individual building observations for multi-risk assessment purposes." , no. : 1.
In scenario-based and probabilistic single-hazard risk and loss estimation over urban building portfolios, it is customary to use 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., In a multi-risk application, where the same built structure can be subjected to the action of different natural hazards, possibly in close succession, a number of different schemas should be then jointly applied. Another option would be using a single set of building classes with as many fragility / vulnerability models as the considered natural hazards, as in the case for instance of the HAZUS multi-hazard framework. Unfortunately the latter approach requires a multi-hazard calibration that is rarely attainable with consistent results, while the former approach is complicated by the need for harmonizing different types of building classes. Furthermore, although fragility surfaces for independent hazards have been recently reported, they do not consider the nonlinear contribution of the different failure mechanisms (e.g. earthquake and tsunami) to the overall damage of a single asset. A timely update of the exposure model accounting for the progressive damage accumulation, thus describing a dynamic vulnerability framework, is then required.
We propose an alternative, innovative approach based on three main components: 1) a comprehensive multi-hazard building taxonomy able to address most of the building attributes driving the vulnerability with respect to different hazards, 2) a generalized description of the damage state of a building based on a set of low-level observable damage types and 3) a methodology to implement probabilistic mapping across different hazard-dependent building schemas and damage states.
A matrix describing the degree of compatibility between building types from two different schemas is estimated, partially making use of the fuzzy scores methodology suggested by Pittore et al., 2018. Since two building schemas may have different number of damage states (e.g. four in seismic, and six in tsunami), and are associated to different physical damage descriptions, the probability of the damage states conversion between the different schemas is also required.
This transparent and flexible formulation allows the implementation of multi-risk scenario assessment exploiting single-risk fragility/vulnerability models available in literature for a wide range of natural hazards. A preliminary state-dependency of these fragility models is based on expert knowledge. This work has been carried out within the scope of the RIESGOS project and exemplified in a study area in South America and further highlights the importance of defining accurate exposure models and compatible damage states descriptions in a multi- hazard-risk context.
Juan Camilo Gomez- Zapata; Massimiliano Pittore; Nils Brinckmann; Simantini Shinde. Dynamic physical vulnerability: a Multi-risk Scenario approach from building- single- hazard fragility- models. 2020, 1 .
AMA StyleJuan Camilo Gomez- Zapata, Massimiliano Pittore, Nils Brinckmann, Simantini Shinde. Dynamic physical vulnerability: a Multi-risk Scenario approach from building- single- hazard fragility- models. . 2020; ():1.
Chicago/Turabian StyleJuan Camilo Gomez- Zapata; Massimiliano Pittore; Nils Brinckmann; Simantini Shinde. 2020. "Dynamic physical vulnerability: a Multi-risk Scenario approach from building- single- hazard fragility- models." , no. : 1.
A significant percentage of disasters qualify as complex, multi-hazard events. Either when extreme events trigger additional phenomena (for instance in the case of particularly strong earthquakes generating tsunamis and landslides), or when different compounded hazards significantly amplify their joint impact (e.g., if an earthquake would occur during a typhoon). Further cascading effects can also occur due to systemic interdependency in the exposed infrastructure, for example water or power distribution lines. The quantitative estimation of the consequences associated to such multi-hazard scenarios is referred to as multi-risk estimation and can be relevant in supporting civil protection authorities and decision makers to plan medium and long-term disaster risk reduction (DRR) and prevention measures.
Exploring the multi-risk associated to a complex event is challenging, partly due to the inherent model complexity, partly because is a strongly interdisciplinary matter, where skills and expertise from heterogeneous scientific and technical areas have to converge, and they rarely can be found in a single institutions nor managed by single-domain experts. In order to streamline this process, and at the same time unleash the potential of different institutions to bridge the gap between science and practice, an innovative conceptual and operational framework for multi-risk scenario assessment has been developed within the project RIESGOS (https://www.riesgos.de). The proposed solution is based on a dynamic, multi-hazard exposure and vulnerability model, which provides the geography-aware structural description of different types of assets (e.g. residential buildings) compatible with vulnerability models related to different hazards.
A novel methodology for describing inter- and intra-hazard damage accumulation also allows the modelling of scenarios composed by sequences of hazardous events. The processing framework is based on processing modules that are implemented as distinct web-processing-services (WPS), possibly hosted remotely by different institutions. Each WPS is fully complying with the OGC WPS directives, and implemented in a flexible and scalable architecture based on Docker containers. The interoperability among the different services is ensured by a careful harmonization of input and output format and the use of on-the-fly converters. Standard and de-facto standards (e.g., community standards) are supported. Specific WPS provide the simulation of intensity maps for the considered hazards, either on the fly (e.g., for the earthquake shake-map generation) or by querying portfolios of pre-simulated events (e.g., for tsunami inundation maps).
The proposed framework can be used to explore the direct damage and loss to assets as a result of a sequence of consecutive events, and also includes a specific processing module for the analysis and simulation of cascading effects on extended infrastructure such as power lines. A graph-based topological model of the network along with the physics-inspired modelling of the load- shedding allows the estimation of potential outages caused by non-linear cascading effects triggered by damage accumulation during the events sequence.
The approach has been exemplified in several study areas in South America, considering a wide range of natural hazards including earthquakes, tsunamis and volcanic phenomena (lahar, ash-fall). The cases of Gran Valparaiso (Chile) and Cotopaxi region (Ecuador) are shown and discussed.
Massimiliano Pittore; Juan Camilo Gómez Zapata; Nils Brinckmann; Graeme Weatherill; Andrey Babeyko; Sven Harig; Alireza Mahdavi; Benjamin Proß; Hugo Fernando Rosero Velasquez; Daniel Straub; Michael Krautblatter; Theresa Frimberger; Michael Langbein; Christian Geiß; Elisabeth Schoepfer. Towards an integrated framework for distributed, modular multi-risk scenario assessment. 2020, 1 .
AMA StyleMassimiliano Pittore, Juan Camilo Gómez Zapata, Nils Brinckmann, Graeme Weatherill, Andrey Babeyko, Sven Harig, Alireza Mahdavi, Benjamin Proß, Hugo Fernando Rosero Velasquez, Daniel Straub, Michael Krautblatter, Theresa Frimberger, Michael Langbein, Christian Geiß, Elisabeth Schoepfer. Towards an integrated framework for distributed, modular multi-risk scenario assessment. . 2020; ():1.
Chicago/Turabian StyleMassimiliano Pittore; Juan Camilo Gómez Zapata; Nils Brinckmann; Graeme Weatherill; Andrey Babeyko; Sven Harig; Alireza Mahdavi; Benjamin Proß; Hugo Fernando Rosero Velasquez; Daniel Straub; Michael Krautblatter; Theresa Frimberger; Michael Langbein; Christian Geiß; Elisabeth Schoepfer. 2020. "Towards an integrated framework for distributed, modular multi-risk scenario assessment." , no. : 1.
The integration of site effects into Probabilistic Seismic Hazard Assessment (PSHA) is still an open issue within the seismic hazard community. Several approaches have been proposed varying from deterministic to fully probabilistic, through hybrid (probabilistic-deterministic) approaches. The present study compares the hazard curves that have been obtained for a thick, soft non-linear site with two different fully probabilistic, site-specific seismic hazard methods: (1) The analytical approximation of the full convolution method (AM) proposed by Bazzurro and Cornell 2004a,b and (2) what we call the Full Probabilistic Stochastic Method (SM). The AM computes the site-specific hazard curve on soil, HC(Sas(f)), by convolving for each oscillator frequency the bedrock hazard curve, HC(Sar(f)), with a simplified representation of the probability distribution of the amplification function, AF(f), at the considered site The SM hazard curve is built from stochastic time histories on soil or rock corresponding to a representative, long enough synthetic catalog of seismic events. This comparison is performed for the example case of the Euroseistest site near Thessaloniki (Greece). For this purpose, we generate a long synthetic earthquake catalog, we calculate synthetic time histories on rock with the stochastic point source approach, and then scale them using an adhoc frequency-dependent correction factor to fit the specific rock target hazard. We then propagate the rock stochastic time histories, from depth to surface using two different one-dimensional (1D) numerical site response analyses, while using an equivalent-linear (EL) and a non-linear (NL) code to account for code-to-code variability. Lastly, we compute the probability distribution of the non-linear site amplification function, AF(f), for both site response analyses, and derive the site-specific hazard curve with both AM and SM methods, to account for method-to-method variability. The code-to-code variability (EL and NL) is found to be significant, providing a much larger contribution to the uncertainty in hazard estimates, than the method-to-method variability: AM and SM results are found comparable whenever simultaneously applicable. However, the AM method is also shown to exhibit severe limitations in the case of strong non-linearity, leading to ground motion “saturation”, so that finally the SM method is to be preferred, despite its much higher computational price. Finally, we encourage the use of ground-motion simulations to integrate site effects into PSHA, since models with different levels of complexity can be included (e.g., point source, extended source, 1D, two-dimensional (2D), and three-dimensional (3D) site response analysis, kappa effect, hard rock …), and the corresponding variability of the site response can be quantified.
Claudia Aristizábal; Pierre-Yves Bard; Céline Beauval; Juan Camilo Gómez. Integration of Site Effects into Probabilistic Seismic Hazard Assessment (PSHA): A Comparison between Two Fully Probabilistic Methods on the Euroseistest Site. Geosciences 2018, 8, 285 .
AMA StyleClaudia Aristizábal, Pierre-Yves Bard, Céline Beauval, Juan Camilo Gómez. Integration of Site Effects into Probabilistic Seismic Hazard Assessment (PSHA): A Comparison between Two Fully Probabilistic Methods on the Euroseistest Site. Geosciences. 2018; 8 (8):285.
Chicago/Turabian StyleClaudia Aristizábal; Pierre-Yves Bard; Céline Beauval; Juan Camilo Gómez. 2018. "Integration of Site Effects into Probabilistic Seismic Hazard Assessment (PSHA): A Comparison between Two Fully Probabilistic Methods on the Euroseistest Site." Geosciences 8, no. 8: 285.