On April 6, 2009, 01:32:39 GMT, the city of L'Aquila was struck by a Mw 6.3 earthquake that killed 307 people, causing severe destruction and ground cracks in a wide area around the epicenter. Four days before the main shock we augmented the existing permanent GPS network with five GPS stations of the Central Apennine Geodetic Network (CaGeoNet) bordering the L'Aquila basin. The maximum horizontal and vertical coseismic surface displacements detected at these stations was 10.39 ± 0.45 cm and −15.64 ± 1.55 cm, respectively. Fixing the strike direction according to focal mechanism estimates, we estimated the source geometry with a non linear inversion of the geodetic data. Our best fitting fault model is a 13 × 15.7 km2 rectangular fault, SW‐dipping at 55.3 ± 1.8°, consistent with the position of observed surface ruptures. The estimated slip (495 ± 29 mm) corresponds to a 6.3 moment magnitude, in excellent agreement with seismological data.

We propose a procedure for uncertainty quantification in Probabilistic Tsunami Hazard Analysis (PTHA), with a special emphasis on the uncertainty related to statistical modelling of the earthquake source in Seismic PTHA (SPTHA), and on the separate treatment of subduction and crustal earthquakes (treated as background seismicity). An event tree approach and ensemble modelling are used in spite of more classical approaches, such as the hazard integral and the logic tree. This procedure consists of four steps: (1) exploration of aleatory uncertainty through an event tree, with alternative implementations for exploring epistemic uncertainty; (2) numerical computation of tsunami generation and propagation up to a given offshore isobath; (3) (optional) site-specific quantification of inundation; (4) simultaneous quantification of aleatory and epistemic uncertainty through ensemble modelling. The proposed procedure is general and independent of the kind of tsunami source considered; however, we implement step 1, the event tree, specifically for SPTHA, focusing on seismic source uncertainty. To exemplify the procedure, we develop a case study considering seismic sources in the Ionian Sea (central-eastern Mediterranean Sea), using the coasts of Southern Italy as a target zone. The results show that an efficient and complete quantification of all the uncertainties is feasible even when treating a large number of potential sources and a large set of alternative model formulations. We also find that (i) treating separately subduction and background (crustal) earthquakes allows for optimal use of available information and for avoiding significant biases; (ii) both subduction interface and crustal faults contribute to the SPTHA, with different proportions that depend on source-target position and tsunami intensity; (iii) the proposed framework allows sensitivity and deaggregation analyses, demonstrating the applicability of the method for operational assessments.

The 2016-2017 seismic sequence, in central Italy, was caused by the Mt. Vettore-Mt. Bove active fault system, which generated three mainshocks, the largest one of M w 6.

Glacial Isostatic Adjustment (GIA) modelling has recently seen a significant development, stimulated by the need of understanding past, current and future sea level variations and geodetic signals associated with climate change. Our main motivation is that albeit its importance is well recognized within the climate science community, the problem of classifying and quantifying GIA modelling uncertainties has so far received little attention. Here, we consider two possible ways of defining and evaluating these uncertainties. The first is associated with limited knowledge of input model parameters (e.g. the viscosity profile of the Earth's mantle or the deglaciation history), once it is assumed that the ice margins are known and a unique set of relative sea level (RSL) data are used to constrain the model. We also discuss a second and more problematic source of uncertainty, associated with structural differences in GIA models, stemming from distinct eustatic curves and ice margins geometries, different RSL constraints, non-identical input parameters and different numerical solution schemes. By analysing the present-day 'GIA fingerprints' of relative and absolute sea level change, and exploring the GIA contribution to secular sea level rise and to the time-variations of the Earth's gravity field, here we evaluate the two types of uncertainty showing that they are (i) of significant amplitude and (ii) of comparable importance.

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