Alluvial valleys generate strong effects on earthquake ground motion (EGM). These effects are rarely accounted for even in site-specific studies because of (a) the cost of the required geophysical surveys to constrain the site model, (b) lack of data for empirical prediction, and (c) poor knowledge of the key controlling parameters. We performed 3D, 2D and 1D simulations for six typical sedimentary valleys of various width and depth, and for a variety of modifications of these 6 ''nominal models'' to investigate sensitivity of EGM characteristics to impedance contrast, attenuation, velocity gradient and geometry. We calculated amplification factors, and 2D/1D and 3D/2D aggravation factors for 10 EGM characteristics, using a representative set of recorded accelerograms to account for input motion variability. The largest values of the amplification and aggravation factors are found for the Arias intensity and cumulative absolute velocity, the lowest for the rootmean-square acceleration. The aggravation factors are largest for the vertical component. For each model, at least one EGM characteristic exhibits a significant 2D/1D aggravation factor, while all EGM characteristics exhibit significant 2D/1D aggravation factor on the vertical component. For all investigated sites, there is always an area in the valley for which 1D estimates are not sufficient. 2D estimates are insufficient at several sites. The key Electronic supplementary material The online version of this article (

We present methodology of calculating acceleration and corresponding earthquake ground motion characteristics at a site of interest assuming acceleration at a reference site for two basic configurations. In one configuration we assume that the reference ground motion is not affected by the local structure beneath the site of interest. In the other configuration we assume that the reference ground motion is affected by the local structure. Consequently, the two configurations differ from each other by the presence of the reference site within the computational model. For each of the two configurations we assume two wavefield excitations: a vertical plane-wave incidence and a point double-couple source. We illustrate the methodology on the example of the Grenoble valley. The extensive investigation of effects of local surface sedimentary structures based on the developed methodology is presented in the accompanying article by Moczo et al. (Bull Earthq Eng, 2018) in this volume.

<p>The presence of thick soft alluvial sediment-filled basins, like in river’s deltas, can significantly amplify and prolongate the earthquake ground motion. Moreover, the high-water saturation of such soft sediments and cyclic earthquake loading can lead to liquefaction. The basin and liquefaction effect can contribute to substantial modification of the seismic motion and increase of the potential losses at a particular location. Well-known examples of such high financial losses during earthquakes for basin effect is Mw 8.1 Mexico City 1985 and for liquefaction is Darfield and Christchurch earthquakes series in 2010 and 2011. Thus, the quantification of these effects is particularly important for the current underwriting products and the industry requires their further detailed consideration in the catastrophe models and pricing approaches. Impact Forecasting, Aon’s catastrophe model development center of excellence, has been committed to help (re)insurers on that matter.</p><p>This paper presents case study of the quantification of the basin effect and liquefaction for Vancouver region, Canada for specific scenario Mw 7.5 Strait of Georgia crustal earthquake. The southern part of the Vancouver region is located on a deep sedimentary basin created in the Fraser River delta. In case of deep Vancouver sedimentary basin considering amplification only due to shallow site response Vs30-dependent site term is not sufficient. Therefore, we derived (de)amplification function for different periods to quantify basin effect. We used NGA – West 2 ground motion prediction equations (GMPEs) for crustal events which include basin depth term. Amplification function was derived with respect to standard GMPEs for crustal events in western Canada. Amplification, considering site response including Vs30 and basin depth term at period 0.5 s can reach values as high as 3 at the softest and deepest sediments. The liquefaction potential was based on HAZUS and Zhu et al. (2017) methodologies calibrated to better reflect local geological conditions and liquefaction observations (Monahan et al. 2010, Clague 2002). We used USGS Vs30 data, enhanced by local seismic and geologic measurements, to characterize soil conditions, and topographical data and IF proprietary flow accumulation data to characterize water saturation. Liquefaction hazard is calculated in terms of probability of liquefaction occurrence and permanent ground deformation. For the chosen scenario the potential contribution to mean loss due to basin effect could be in the range 15% - 30% and 35% - 75% due to liquefaction depending on structural types of the buildings.</p>

Catastrophe models are important tools to provide proper assessment and financial management of earthquake-related emergencies, which still create the largest protection gap across all perils. Earthquake catastrophe models include three main components, namely: (1) the earthquake hazard model, (2) the exposure model and, (3) the vulnerability model. Simulating spatially distributed ground-motion fields within either deterministic or probabilistic seismic hazard assessments poses a major challenge when site-related financial protection products are required. In this framework, we develop ad hoc correlation models for different Italian regions (specifically northern, central and southern Italy) and thereafter we perform both deterministic scenario-based and probabilistic event-based hazard and risk assessments in order to advance the understanding of spatial correlations within the catastrophe modelling process. We employ the OpenQuake engine for our calculations. This is an open-source tool suitable for accounting for the spatial correlation of earthquake ground-motion residuals. Our outcomes, albeit preliminary, demonstrate the importance of considering not only the spatial correlation of ground motions, but also its associated uncertainty in risk analyses. Although loss exceedance probability curves for the return periods of interest for the (re)insurance industry show similar trends, both hazard and risk footprints in terms of average annual losses feature less noisy and more realistic patterns if spatial correlation is taken into account. Such results will have implications for (re)insurance companies evaluating the risk to high-value civil engineering infrastructures.

<p>Fire following earthquake (FFE) can pose considerable threat in densely populated urban area with significant earthquake hazard and presence of non-fire-resistant buildings typology. Severe building damage and consequently broken pipelines can lead to release of flammable gasses and liquid, which increase possibility of fire occurrence when they come into contact with ignition sources, like short circuits or open flames. Numerous simultaneous ignitions followed by uncontrolled fire spread to adjacent buildings can lead to major fires and conflagrations, whose damage can substantially exceed the earthquake shaking damage. Well-known example of such high financial losses due to FFE is Mw 7.9 San Francisco 1906, where Great Fire losses were 10 times higher than due to earthquake shaking itself. Thus, the quantification of FFE losses has particularly important role for the current underwriting products and the industry requires their further detailed consideration in the catastrophe models and pricing approaches. Impact Forecasting, Aon’s catastrophe model development centre of excellence, has been committed to help (re)insurers on that matter.</p><p>This paper presents quantification of FFE contribution to mean losses for case study of the Vancouver region, Canada for specific scenario Mw 7.5 Strait of Georgia crustal earthquake. FFE methodology encompasses 3 phases: ignitions, fire spread and suppression and loss estimation. Number of ignitions (fires that require fire department response) and their location were calculated using HAZUS empirical equation with input variables earthquake shaking intensity and estimated total building floor area. An urban fire spread is a complicated phenomenon that includes numerous uncertainties. An advanced cellular automata (CA) engine is used for simulation of the fire spread and suppression based on Zhao 2011. The CA engine represents collection of grid-arranged cells, where each grid cell changes state as a function of time according to a defined set of rules that includes the states of adjacent cells. The CA simulations include only matrix mathematical operations that allow us to take into account building construction types and their damage due to earthquake shaking, meteorological and environmental data and fire suppression modifiers. Unlike in older empirical approach, the fire spread CA engine enable to consider fire spread not only from initially ignited building as well as fire developing within a single building, building-to-building fire spread, and fire extinguishing works at the same time. An output of CA engine is the building fire-state grades based on which damage functions are created with PGA as input parameter at the level of 3-digit postal codes. For the chosen scenario potential contribution to mean loss due to FFE could be up to 75% depending on typical buildings setting within 3-digit postal codes.</p>