Spatial mapping is one of the most useful methods to display information about the seismic parameters of a certain area. As in b-value time series, there is a certain arbitrariness regarding the function selected as smoothing kernel (which plays the same role as the window size in time series). We propose a new method for the calculation of the smoothing kernel as well as its parameters. Instead of using the spatial cell-event distance we study the distance between events (event-event distance) in order to calculate the smoothing function, as this distance distribution gives information about the event distribution and the seismic sources. We examine three different scenarios: two shallow seismicity settings and one deep seismicity catalog. The first one, Italy, allows calibration and showcasing of the method. The other two catalogs: the Lorca region (Spain) and Vrancea County (Romania) are examples of different function fits and data treatment. For these two scenarios, the prior to earthquake and after earthquake b-value maps depict tectonic stress changes related to the seismic settings (stress relief in Lorca and stress build-up zone shifting in Vrancea). This technique could enable operational earthquake forecasting (OEF) and tectonic source profiling given enough data in the time span considered.

For the assessment of seismic effects on RC buildings, the real structural condition has to be modelled as accurately as possible. Medical facilities and hospitals have to resist seismic actions and remain operational after seismic events. For this reason, a detailed seismic vulnerability assessment of a hospital building located in Orihuela, Spain, is presented in this paper using a combination of field monitoring data and numerical analysis. Ambient noise measurements from field monitoring using Raspberry Shake-based sensors are used to capture dynamic characteristics that describe the building behaviour. Data from these sensors were used to update and refine the finite element model of the structure for a detailed analysis of the building’s seismic performance. The different analytical procedures included both elastic and inelastic modelling, as well as static and dynamic assessments, to provide an exhaustive evaluation of the building’s behaviour under seismic loads. In the numerical model, the effect of masonry infill walls is considered, taking into account detailed material properties and structural configurations. Furthermore, the study carefully selects ground motion records representing two limit states—Damage Limitation (DL) and Severe Damage (SD)—to conduct an extensive seismic analysis. In each limit state applied to the structure, there are 14 bidirectional ground motions with components alternately directed along the two principal directions of the building. This analysis evaluated the structural response, focusing on torsional effects, inter-storey drift ratios, and the seismic performance of individual components. The results were compared to other analysis types, considering both overall and localised behaviour, to determine the reliability of different approaches. The findings support the idea that field monitoring data should be combined with advanced modelling techniques to achieve a more accurate evaluation of the building’s seismic vulnerability, considering bidirectional effects.

The southern and south-eastern parts of Spain exhibit the highest seismicity rate in the country. However, although the recently developed Quaternary Active Fault database of Iberia (QAFI, García-Mayordomo et al., 2012 ) collected the available information existing in the study area regarding fault data for their use in seismic hazard applications, this information is of limited use since data quality is very heterogeneous: few earthquakes are associated with specific fault segments, and occurrence time periods (when indicated) are affected by high uncertainties (Gaspar-Escribano et al., 2015). This has motivated the definition of alternative tectonic zonation models, to be used for evaluating the seismic hazard. So far, the clustering properties have not been considered in this regard, though they can provide essential information about the features of seismic energy release, depending on the tectonic style of a region (Talebi et al., 2024). This is why in this work the properties of the seismicity in terms of clustering are evaluated by applying the nearest-neighbour (NN) algorithm to the south-eastern Spain region. The scale parameters needed for the NN algorithm are optimised through the study of the z score and the temporal anomalies between events in the identified clusters for each run. The tree structure, using graph theory notation, has proved useful in the determination of the critical threshold that separates the background (independent) seismicity from the clustered (dependent) seismicity in the NN algorithm. Once the clusters have been identified, their properties have been quantified in terms of a selection of complexity measures: outdegree, closeness and average node depth. This procedure has been applied by considering two different completeness magnitudes: M_w 3.0 (the mean completeness magnitude for the entire catalogue) and M_w 2.1 (accounting for the most recent part of the catalogue). The results are similar in terms of proportion of foreshocks, mainshocks and aftershocks, and indicate a clear distinction between the western-most part (higher complexity) and eastern-most part (lower complexity). To check this result, three different zonation models have been examined and cross-compared; two of them passed the Kolmogorov–Smirnov (KS) test, meaning the distributions of the selected complexity measures are not the same for the different zones defined in the models. These zonations can be used in order to assess the seismic hazard, as they account for the influence of the tectonic setting on the patterns of earthquake occurrence, including the features of background and clustered seismicity components.

Radon gas anomalies have been investigated as potential earthquake precursors for many years. In this work, we have studied the possible correlations between radon emissions and the seismic activity rate for a given region to test if the existing correlation may be later used to forecast the occurrence of earthquakes larger than a given magnitude. The Vrancea region (Romania) was chosen as a study area since it is being surveilled by a multidisciplinary real-time monitoring network, and at least seven earthquakes with magnitudes greater than 4.5 Mw have occurred in this area in the period from 2016 to 2020. Our research followed several steps: First, the recorded radon signals were preprocessed (detrended, deseasoned and smoothed). Then, the station’s signals were correlated in order to check which stations are recording radon anomalies due to the same regional tectonic process. On the other hand, the seismic activity rate was computed using the earthquakes in the main catalogue of the region that are able to generate radon emissions and can be registered at several stations. The obtained results indicate a significant correlation between the seismic activity rate and the temporal series of radon anomalies. A temporal lag between the seismic activity rate and the radon anomalies was found, which can be related to the proximity to the epicentre of the main earthquake in each of the studied subperiods. Changes in the regional tectonic stress field could explain why the seismic activity rate and radon anomalies are correlated over time. Further research could focus on obtaining a function to forecast the seismic activity rate using the following as dependent variables: the radon anomalies recorded at several stations, the distance from the stations, and tectonic factors such as the fault system, azimuth, type of soil, etc.

Probabilistic Seismic Hazard Analysis (PSHA) typically requires tectonic b-values and seismic activity rates using declustered catalogues to compute the annual probability of exceedance of a given ground motion (for example, the Peak Ground Acceleration or PGA). In this work, we propose a methodology that includes the spatially-gridded time-dependent b-value and activity rate computation using seismic clusters in PSHA calculations. To account for the the spatial variability and the relationship of the earthquakes with the seismic sources, we incorporate the distance from the grid cell to the closest fault and the epicentre's uncertainty into the smoothing kernel as the average distance and the variance, respectively. To illustrate this methodology, we selected two scenarios, one in central Italy where L'Aquila earthquake happened and one in south-eastern Spain, where several earthquakes with a moment magnitude (Mw) greater than 4.0 have taken place over the last 30 years, including two earthquakes with greater than or equal to 5.0 Mw. We compared three different seismic activity models based on the parameters considered in the calculations (distance from spatial cells to faults and epicentral distance uncertainty) and we defined and calculated the changes of the annual probability of exceedance for a given background PGA value. The results reveal an oscillation of the changes of the annual probability of exceedance in the proximity of the occurrence of significant events. The increase is more significant in high seismicity areas, such as Italy, but it is no so evident in moderate seismicity regions as Spain. However, we have observed how, for moderate to low seismicity regions, the use of a non-declustered catalogue can be appropriate when computing time-dependent PSHA, as in the case of Spain.