Scafidi, Davide

In this paper, the new dynamic geophysical and geochemical MUltiparametric DAtabase (MUDA) is presented. MUDA is a new infrastructure of the National Institute of Geophysics and Volcanology (INGV), published online in December 2023, with the aim of archiving and disseminating multiparametric data collected by multidisciplinary monitoring networks. MUDA is a MySQL relational database with a web interface developed in PHP, aimed at investigating possible correlations between seismic phenomena and variations in endogenous and environmental parameters in quasi real time. At present, MUDA collects data from different types of sensors such as hydrogeochemical probes for physical–chemical parameters in waters, meteorological stations, detectors of air radon concentration, diffusive flux of carbon dioxide (CO2) and seismometers belonging both to the National Seismic Network of INGV and to temporary networks installed in the framework of multidisciplinary research projects. MUDA publishes data daily, updated to the previous day, and offers the chance to view and download multiparametric time series selected for different time periods. The resultant dataset provides broad perspectives in the framework of future high-frequency and continuous multiparametric monitoring as a starting point to identify possible seismic precursors for short-term earthquake forecasting. MUDA can be accessed at https://doi.org/10.13127/muda (Massa et al., 2023).

The protracted nature of the 2016-2017 central Italy seismic sequence, with multiple damaging earthquakes spaced over months, presented serious challenges for the duty seismologists and emergency managers as they assimilated the growing sequence to advise the local population. Uncertainty concerning where and when it was safe to occupy vulnerable structures highlighted the need for timely delivery of scientifically based understanding of the evolving hazard and risk. Seismic hazard assessment during complex sequences depends critically on up-to-date earthquake catalogues-i.e., data on locations, magnitudes, and activity of earthquakes-to characterize the ongoing seismicity and fuel earthquake forecasting models. Here we document six earthquake catalogues of this sequence that were developed using a variety of methods. The catalogues possess different levels of resolution and completeness resulting from progressive enhancements in the data availability, detection sensitivity, and hypocentral location accuracy. The catalogues range from real-time to advanced machine-learning procedures and highlight both the promises as well as the challenges of implementing advanced workflows in an operational environment.

We present the Istituto Nazionale di Geofisica e Vulcanologia Strong‐Motion Data‐quality (ISMDq)—a new automatic system designed to check both continuous data stream and event strong‐motion waveforms before online publication. The main purpose of ISMDq is to ensure accurate ground‐motion data and derived products to be rapidly shared with monitoring authorities and the scientific community. ISMDq provides data‐quality reports within minutes of the occurrence of Italian earthquakes with magnitude ≥3.0 and includes a detailed daily picture describing the performance of the target strong‐motion networks. In this article, we describe and discuss the automatic procedures used by ISMDq to perform its data‐quality check. Before an earthquake, ISMDq evaluates the selected waveforms through the estimation of quality indexes employed to reject bad data and/or to group approved data into classes of quality that are useful to quantify the level of reliability. The quality indexes are estimated based on comparisons with the background ambient noise level performed both in the time and frequency domains. As a consequence, new high‐ and low‐noise reference levels are derived for the overall Italian strong‐motion network, for each station, and for groups of stations in the same soil categories of the Eurocode 8 (Eurocode 8 [EC8], 2003). In absence of earthquakes, 24 hr streaming of ambient noise recordings are analyzed at each station to set an empirical threshold on selected data metrics and data availability, with the goal to build a station quality archive, which is daily updated in a time span of six months. The ISMDq is accessible online (see Data and Resources) from August 2020, providing rapid open access to ∼10,000 high‐quality checked automatically processed strong‐motion waveforms and metadata, relative to more than 160 Italian earthquakes with magnitude in the 3.0–5.2 range. Comparisons between selected strong‐motion data automatically processed and then manually revised corroborate the reliability of the proposed procedures.

We present Rapid Assessment of MOmeNt and Energy Service (RAMONES), a service for disseminating through a web interface, the estimates of seismic moment (⁠M0⁠) and radiated energy (⁠ER⁠) for earthquakes occurring in central Italy with local magnitudes above 1.7. The service is based on a fully‐automatic procedure developed for downloading and processing open seismological data from the European Integrated Data Archive, Italian Civil Protection repository, and Incorporated Research Institutions for Seismology (IRIS). In its actual configuration, RAMONES uses the seismic catalog generated through the event webservice of the Italian Institute of Geophysics and Volcanology (compliant with International Federation of Digital Seismograph Networks standards) to guide the data download. The concept of RAMONES is to estimate M0 and ER from features extracted directly from recordings, namely the S‐wave peak displacement (⁠PDS⁠) and the integral of the squared velocity (⁠IV2S⁠) evaluated over the S‐wave window at local distances. A data set composed of 6515 earthquakes recorded in central Italy between 2008 and 2018 was used to calibrate the attenuation models relating M0 to PDS and ER to IV2S⁠, including station corrections. The calibration values for M0 and ER were extracted from the source spectra obtained by applying a decomposition approach to the Fourier amplitude spectra known as the generalized inversion technique. To test the capabilities of RAMONES, we validate the attenuation models by performing residual analysis over about 60 earthquakes occurring in 2019 that were used for the spectral decomposition analysis but not considered in the calibration phase. Since January 2020, a testing operational phase has been running, and RAMONES has analyzed about 800 earthquakes by September 2020. The distribution of the source parameters and their relevant scaling relationships are automatically computed and disseminated in the form of maps, parametric tables, figures, and reports available through the RAMONES web interface.

The 2016–17 central Italy earthquake sequence began with the first mainshock near the town of Amatrice on August 24 (MW 6.0), and was followed by two subsequent large events near Visso on October 26 (MW 5.9) and Norcia on October 30 (MW 6.5), plus a cluster of 4 events with MW > 5.0 within few hours on January 18, 2017. The affected area had been monitored before the sequence started by the permanent Italian National Seismic Network (RSNC), and was enhanced during the sequence by temporary stations deployed by the National Institute of Geophysics and Volcanology and the British Geological Survey. By the middle of September, there was a dense network of 155 stations, with a mean separation in the epicentral area of 6–10 km, comparable to the most likely earthquake depth range in the region. This network configuration was kept stable for an entire year, producing 2.5 TB of continuous waveform recordings. Here we describe how this data was used to develop a large and comprehensive earthquake catalogue using the Complete Automatic Seismic Processor (CASP) procedure. This procedure detected more than 450,000 events in the year following the first mainshock, and determined their phase arrival times through an advanced picker engine (RSNI-Picker2), producing a set of about 7 million P- and 10 million S-wave arrival times. These were then used to locate the events using a non-linear location (NLL) algorithm, a 1D velocity model calibrated for the area, and station corrections and then to compute their local magnitudes (ML). The procedure was validated by comparison of the derived data for phase picks and earthquake parameters with a handpicked reference catalogue (hereinafter referred to as ‘RefCat’). The automated procedure takes less than 12 hours on an Intel Core-i7 workstation to analyse the primary waveform data and to detect and locate 3000 events on the most seismically active day of the sequence. This proves the concept that the CASP algorithm can provide effectively real-time data for input into daily operational earthquake forecasts, The results show that there have been significant improvements compared to RefCat obtained in the same period using manual phase picks. The number of detected and located events is higher (from 84,401 to 450,000), the magnitude of completeness is lower (from ML 1.4 to 0.6), and also the number of phase picks is greater with an average number of 72 picked arrival for a ML = 1.4 compared with 30 phases for RefCat using manual phase picking. These propagate into formal uncertainties of ± 0.9km in epicentral location and ± 1.5km in depth for the enhanced catalogue for the vast majority of the events. Together, these provide a significant improvement in the resolution of fine structures such as local planar structures and clusters, in particular the identification of shallow events occurring in parts of the crust previously thought to be inactive. The lower completeness magnitude provides a rich data set for development and testing of analysis techniques of seismic sequences evolution, including real-time, operational monitoring of b-value, time-dependent hazard evaluation and aftershock forecasting.

In recent years, new approaches for developing earthquake rupture forecasts (ERFs) have been proposed to be used as an input for probabilistic seismic hazard assessment (PSHA). Zone- based approaches with seismicity rates derived from earthquake catalogs are commonly used in many countries as the standard for national seismic hazard models. In Italy, a single zone- based ERF is currently the basis for the official seismic hazard model. In this contribution, we present eleven new ERFs, including five zone-based, two smoothed seismicity-based, two fault- based, and two geodetic-based, used for a new PSH model in Italy. The ERFs were tested against observed seismicity and were subject to an elicitation procedure by a panel of PSHA experts to verify the scientific robustness and consistency of the forecasts with respect to the observations. Tests and elicitation were finalized to weight the ERFs. The results show a good response to the new inputs to observed seismicity in the last few centuries. The entire approach was a first attempt to build a community-based set of ERFs for an Italian PSHA model. The project involved a large number of seismic hazard practitioners, with their knowledge and experience, and the development of different models to capture and explore a large range of epistemic uncertainties in building ERFs, and represents an important step forward for the new national seismic hazard model.

This paper describes the seismological analyses performed within the framework of the seismic microzonation study for the reconstruction of 138 municipalities damaged by the 2016–2017 sequence in Central Italy. Many waveforms were recorded over approximately 15 years at approximately 180 instrumented sites equipped with permanent or temporary stations in an area that includes all the damaged localities. Site response was assessed using earthquake and noise recordings at the selected stations through different parameters, such as spectral amplification curves, fundamental resonance frequencies, site-specific response spectra, and average amplification factors. The present study was a collaboration of many different institutions under the coordination of the Italian Center for Seismic Microzonation and its applications. The results were homogenized and gathered into site-specific forms, which represent the main deliverable for the benefit of Italian Civil Protection. It is remarkable that the bulk of this study was performed in a very short period (approximately 2 months) to provide quantitative information for detailed microzonation and future reconstruction of the damaged municipalities.

The compilation of reliable and complete seismic catalogs represents a fundamental issue for most studies in seismology. Nowadays, the availability of an ever-increasing number of stations and, therefore, the huge amount of recordings to be processed and analyzed require a lot of effort in terms of man-hours. In the present work, we present a fully automatic procedure for compiling seismic catalogs starting from continuous recordings. The procedure relies on a multistep algorithm that includes event detection tool, automatic P- and S-phase picker, hypocenter locator, and magnitude and strong-motion parameter calculator. This automatic procedure is applied for compiling seismic catalogs for two real-world usage scenarios starting from the openaccess waveform database provided by European Integrated Data Archive. The first scenario concerns the monitoring of the seismicity of northwestern Italy; the second one concerns the analysis of the data recorded during the first month of the 2016 sequence in central Italy. The comparison between reference manually revised and automatic seismic catalogs points out negligible differences in terms of both P- and S-phase pickings, hypocentral coordinates, and local magnitude values, thus showing the overall reliability of the procedure. The ability of the proposed automatic procedure in detecting and locating very low-magnitude events is prominent to compile automatic catalogs characterized by a magnitude of completeness significantly lower than that of reference manual catalogs.

Since the beginning of the 1980s, when Mandelbrot observed that earthquakes occur on 'fractal' self-similar sets, many studies have investigated the dynamical mechanisms that lead to self-similarities in the earthquake process. Interpreting seismicity as a self-similar process is undoubtedly convenient to bypass the physical complexities related to the actual process. Self-similar processes are indeed invariant under suitable scaling of space and time. In this study, we show that long-range dependence is an inherent feature of the seismic process, and is universal. Examination of series of cumulative seismic moment both in Italy and worldwide through Hurst's rescaled range analysis shows that seismicity is a memory process with a Hurst exponent H ≈ 0.87. We observe that H is substantially space- and time-invariant, except in cases of catalog incompleteness. This has implications for earthquake forecasting. Hence, we have developed a probability model for earthquake occurrence that allows for long-range dependence in the seismic process. Unlike the Poisson model, dependent events are allowed. This model can be easily transferred to other disciplines that deal with self-similar processes.

The zonation presented in this study has been developed with the aim of applying it as a branch of the logic tree that will be used for the new Italian seismic hazard map, presently in preparation according to the approach of seismotectonic probabilism. With respect to the zonation used for the present official seismic hazard map of Italy, the zonation proposed here considers narrower sources and is based on new and updated seismological data. In particular, some new seismogenic zones are proposed here, introducing areas that were not considered seismogenic until now (e.g., the narrow sources characterised by the presence of transform faults which are almost normal to the trend of the northern Apennines). The preliminary seismic hazard estimates produced with this new zonation aim to identify possible problems that the zonation introduces in the seismicity characterization of the seismogenic zones. As the present seismic hazard assessment was computed by considering a different attenuation model with respect to the one applied for the previous national seismic hazard maps, a re-elaboration of the most recent map referring to Italy has been developed: the comparison of the two maps is a good indicator of the areas where additional seismological investigation is needed to support the zonation presented here. In particular, some zones are not adequately documented with regard to seismicity and a different computation of the seismicity rates is suggested.