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.

No abstract

Representative hazard scenarios are essential for many tasks in risk management, such as preparedness and emergency response planning. However, criteria and methods for systematically selecting such scenarios for natural hazards are lacking. From a risk perspective, such scenarios should be selected considering the losses they incur. Hence, we propose to define a scenario that is representative for a certain degree of loss, for example, the 100‐year loss, as the most likely one among all possible scenarios leading to this loss. Taking basis in a generic model of natural hazards and their impact on engineering systems, we formally introduce the representative scenarios. We then develop algorithms that enable an efficient evaluation of these scenarios. The method and algorithms are demonstrated on a hypothetical example considering a spatially distributed infrastructure system subjected to earthquakes.

Risk analysis of power networks under natural hazards requires a model of the power flow following initial failures in the network caused by the hazard. The model should include cascading failures through the network, for which different models have been proposed in the literature. Past studies have compared widely used models for assessing the performance of power networks, such as the topological, betweenness-based and power flow models, and found correlations among the model outcomes. However, they do not compare them for systems subjected to natural hazards, where other factors (e.g., seismic intensity and resulting ground motions) also affect the system performance. Ultimately, the choice of the appropriate model depends on the analysis purposes, the type of power network (e.g., transmission vs. distribution), the available amount of information, and computing resources. In this contribution, we investigate the effect of the cascading failure model on a seismic risk evaluation. To this end, we perform numerical investigations on the power network in the central coastal area of Valparaíso Region, Chile. Specifically, we compute and compare loss-exceedance functions for two models: Origin-destination betweenness centrality (ODBCM) and DC linear power flow (DCLPFM), for different representative seismic scenarios. We also compare the models with and without considering the uncertainty in the ground motion field.

Risk analysis of power networks under natural hazards requires a model of the power flow following initial failures in the network caused by the hazard. The model should include cascading failures through the network, for which different models have been proposed in the literature. Past studies have compared widely used models for assessing the performance of power networks, such as the topological, betweenness-based and power flow models, and found correlations among the model outcomes. However, they do not compare them for systems subjected to natural hazards, where other factors (e.g., seismic intensity and resulting ground motions) also affect the system performance. Ultimately, the choice of the appropriate model depends on the analysis purposes, the type of power network (e.g., transmission vs. distribution), the available amount of information, and computing resources. In this contribution, we investigate the effect of the cascading failure model on a seismic risk evaluation. To this end, we perform numerical investigations on the power network in the central coastal area of Valparaíso Region, Chile. Specifically, we compute and compare loss-exceedance functions for two models: Origin-destination betweenness centrality (ODBCM) and DC linear power flow (DCLPFM), for different representative seismic scenarios. We also compare the models with and without considering the uncertainty in the ground motion field.