In this study, we modify and extend a data analysis technique to determine the stress orientations between data clusters by adding an additional constraint governing the probability algorithm. We apply this technique to produce a map of the maximum horizontal compressive stress (S_Hmax) orientations in the greater European region (including Europe, Turkey and Mediterranean Africa). Using the World Stress Map data set release 2008, we obtain analytical probability distributions of the directional differences as a function of the angular distance, θ. We then multiply the probability distributions that are based on pre-averaged data within θ < 3° of the interpolation point and determine the maximum likelihood estimate of the S_Hmax orientation. At a given distance, the probability of obtaining a particular discrepancy decreases exponentially with discrepancy. By exploiting this feature observed in the World Stress Map release 2008 data set, we increase the robustness of our S_Hmax determinations. For a reliable determination of the most likely S_Hmax orientation, we require that 90 per cent confidence limits be less than ±60° and a minimum of three clusters, which is achieved for 57 per cent of the study area, with uncertainties of less than ±30° for 19 per cent of the area. When the data density exceeds 0.8 × 10⁻³ data km^–2, our method provides a means of reproducing significant local patterns in the stress field. Several mountain ranges in the Mediterranean display 90° changes in the S_Hmax orientation from their crests (which often experience normal faulting) and their foothills (which often experience thrust faulting). This pattern constrains the tectonic stresses to a magnitude similar to that of the topographic stresses.

The lithosphere of Italy is exposed to a number of different short‐term strain transients, including but not limited to landslides, postseismic relaxation, and volcanic inflation/deflation. These transients affect GPS velocities and complicate the assessment of the long‐term tectonic component of the surface deformation. In a companion paper we present a method for anticipating the principal patterns of nontectonic, short‐term strains and building this information into the covariance matrix of the geodetic velocities. In this work we apply this method to Italian GPS velocities to build an augmented covariance matrix that characterizes all expected discrepancies between short‐ and long‐term velocities. We find that formal uncertainties usually reported for GPS measurements are smaller than the variability of the same benchmarks across a geologic time span. Furthermore, we include in our modeling the azimuths of most compressive horizontal principal stresses (SH_max) because GPS data cannot resolve the active kinematics of coastal and offshore areas. We find that the final tectonic model can be made relatively insensitive to short‐term interfering processes if the augmented covariance matrix and SH_maxdata records are used in the objective function. This results in a preferred neotectonic model that is also in closer agreement with independent geologic and seismological constraints and has the advantage of reducing short‐term biases in forecasts of long‐term seismicity.

We present a neotectonic model of ongoing lithosphere deformation and a corresponding estimate of long‐term shallow seismicity across the Africa‐Eurasia plate boundary, including the eastern Atlantic, Mediterranean region, and continental Europe. GPS and stress data are absent or inadequate for the part of the study area covered by water. Thus, we opt for a dynamic model based on the stress equilibrium equation; this approach allows us to estimate the long‐term behavior of the lithosphere (given certain assumptions about its structure and physics) for both land and sea areas. We first update the existing plate model by adding five quasirigid plates (the Ionian Sea, Adria, Northern Greece, Central Greece, and Marmara) to constrain the deformation pattern of the study area. We use the most recent data sets to estimate the lithospheric structure. The models are evaluated in comparison with updated data sets of geodetic velocities and the most compressive horizontal principal stress azimuths. We find that the side and basal strengths drive the present‐day motion of the Adria and Aegean Sea plates, whereas lithostatic pressure plays a key role in driving Anatolia. These findings provide new insights into the neotectonics of the greater Mediterranean region. Finally, the preferred model is used to estimate long‐term shallow seismicity, which we retrospectively test against historical seismicity. As an alternative to reliance on incomplete geologic data or historical seismic catalogs, these neotectonic models help to forecast long‐term seismicity, although requiring additional tuning before seismicity rates are used for seismic hazard purposes.

Earthquake hazard analyses rely on seismogenic source models. These are designed in various fashions, such as point sources or area sources, but the most effective is the three-dimensional representation of geological faults. We here refer to such models as fault sources. This study presents the European Fault-Source Model 2020 (EFSM20), which was one of the primary input datasets of the recently released European Seismic Hazard Model 2020. The EFSM20 compilation was entirely based on reusable data from existing active fault regional compilations that were first blended and harmonized and then augmented by a set of derived parameters. These additional parameters were devised to enable users to formulate earthquake rate forecasts based on a seismic-moment balancing approach. EFSM20 considers two main categories of seismogenic faults: crustal faults and subduction systems, which include the subduction interface and intraslab faults. The compiled dataset covers an area from the Mid-Atlantic Ridge to the Caucasus and from northern Africa to Iceland. It includes 1248 crustal faults spanning a total length of ∼95 100 km and four subduction systems, namely the Gibraltar, Calabrian, Hellenic, and Cyprus arcs, for a total length of ∼2120 km. The model focuses on an area encompassing a buffer of 300 km around all European countries (except for Overseas Countries and Territories) and a maximum of 300 km depth for the subducting slabs. All the parameters required to develop a seismic source model for earthquake hazard analysis were determined for crustal faults and subduction systems. A statistical distribution of relevant seismotectonic parameters, such as faulting mechanisms, slip rates, moment rates, and prospective maximum magnitudes, is presented and discussed to address unsettled points in view of future updates and improvements. The dataset, identified by the DOI https://doi.org/10.13127/efsm20 (Basili et al., 2022), is distributed as machine-readable files using open standards (Open Geospatial Consortium).