Seismic Precursors Research Articles

Seismotectonics of Andaman-Sumatra Region: Seismic Quiescence and B Value as Possible Precursors

Objectives: a) To analyze the long-term seismicity and understand the potential of seismic quiescence study to use it as a reliable seismic precursor b) To estimate B value and understand the variation in B value as earthquake precursor in seismically active region. Methods: The present study analyses the seismicity pattern from the Andaman- Sumatra region for a period of 1964 to 2018. The area has been divided into epicentral blocks. Earthquakes preceding and succeeding a major earthquake with different seismic phases of quiescence and pattern of seismicity have been studied carefully. All quiescence periods are characterized by high b values and period of major shocks has a low b value. Main shock events for each epicentral block with different phases of quiescence (Q1, Q2 and Q3) and active seismicity have been identified and analyzed. Findings: The study suggests that there is generally approximately 6-12 years of gap between major earthquakes. There are 28 years of quiescence before the major earthquake of the stature of Dec 26, 2004 mega earthquake, suggesting that long term quiescence leads to great earthquakes. The study also proposes that the area between 20 and 60N latitudes shows a long-term quiescence which may lead to a major earthquake in the near future. A thorough analysis of long-term seismicity and seismic quiescence can be used as an earthquake precursor, though with limitations. The latest post seismic quiescence period Q2 after the greater events of 2004 and 2005, may yield an impending event of 6.5 M or even greater. Novelty: The present study deals with the precursor studies of one of the most important tectonic zone. Extensive analysis of 54 Years of data has been done and the scope of using seismicity and b value for the long-term prediction of earthquakes has been examined. The periodicity of seismicity has been used to quantify the precursors. Though various statistical studies have been attempted for this zone, methodology adopted here proved one of the reliable methods to check for the possible mega earthquakes of this seismically active zone, which can be applied to other seismically active areas as well. Keywords: Seismicity; Andaman-Sumatra; Seismic quiescence; B-value; Precursors

Analytical solution for the influence of irregular shape loads on near borehole strain observations

Borehole strain observations are widely used to research slow earthquakes, volcanic activity and seismic precursors. Due to the high resolution and sensitivity, borehole strain monitoring records not only tectonic signals, but also signals from environmental disturbances. Based on the analytical solution of the displacement caused by the punctate load model, this paper derives the equation of the peripheral strain field, which provides a theoretical basis for the quantitative calculation of the load effect of borehole strain observation, and proposes a method for calculating the strain effect of two-dimensional and three-dimensional irregularly shaped loads. The results show that, 1) For the two-dimensional irregular shape load model, we can calculate it by vector superposition after load scattering. 2) For the three-dimensional irregular shape load model, we can calculate by assigning different weights to the scattering points after load scattering using two-dimensional irregular shape load method. The convergence process during the vector superposition shows the correctness and feasibility of the method, and the study can provide a research basis for the quantitative analysis of the influence of peripheral load disturbance in borehole strain observation.

Atmospheric plasmas research linked to electromagnetic signals and earthquakes

This paper presents the outcome of monitoring aimed at studying seismic precursor candidates with a multi-parameter system, carried out at a Science Camp in July 2022 in the northwestern Italian Apennines, in the province of Parma. Pre seismic signals, closely related to the preparatory stages of an earthquake, were detected with a crustal diagnosis, based on physical signals, generated by tectonic stress. The instrumental results show a potential temporal concatenation, which describe, at the level of hypothesis, the phases of the ongoing tectonic stress. The model followed Zou’s theories who which associate the formation of plasmas in the atmosphere with the piezoelectricity of rocks under stress. According to his model, rocks placed under tectonic stress and in the presence of moisture can produce both charged particles and radio electromagnetic waves, at high and low frequencies. A spherical plasmoid would originate from this combination as a wave-particle interaction effect. According to Teodorani’s description High-Frequency radio waves-particularly microwaves-would heat and ionize the surrounding air, while low-frequency waves, particularly Very Low Frequencies and Extremely Low Frequency, would help condense the plasma, which in turn would immediately go into swirling motions within it, until it formed the «self-contained» structure seen in the sky as a light phenomenon. Monitoring, therefore, involved the detection of low-frequency waves preceding plasmas in the atmosphere, directional electromagnetic signals from the Radio Direction Finding (RDF) network, and the occurrence of an earthquake within the 5/6 days’ time window along the same fracture line. A study model that, if confirmed, could be applied to other seismic zones for crustal monitoring.

Nucleation Process of the 2017 Nuugaatsiaq, Greenland Landslide

Seismic precursors prior to the failure of rocks are essential for probing the nucleation process and mitigating hazards. However, such precursory events before large landslides are rarely reported possibly due to the lack of near-source observations. The 2017 Nuugaatsiaq, Greenland landslide that was preceded by an abundance of small earthquakes and captured by a local seismic station is a notable exception and offers us a valuable opportunity to investigate how a large landslide initiated. Prior work suggests that accelerated creeping plays an important role during the landslide nucleation process. However, by analyzing the temporal evolution of the waveform similarities, waveform amplitudes, and inter-event times of the seismic precursors, we find that the Nuugaatsiaq landslide was very likely triggered by a series of accelerated and migratory small earthquakes approaching the nucleation area of the upcoming landslide, thus providing important insights into the failure initiation of massive landslides.

Adsorption behavior of molecular hydrogen in forsterite

Recent experimental studies have already discussed the existence of molecular hydrogen in mantle minerals. Here, we investigate the adsorption behavior of molecular hydrogen in forsterite with 0–15 Å intercrystalline pore at 0–519 MPa and 300–1800 K by using the Grand Canonical Monte Carlo (GCMC) method. Molecular hydrogen fills the interstitial positions of nonporous forsterite in an adsorbed state, whereas the filling of intercrystalline pore includes the adsorbed and free states. The adsorption of molecular hydrogen on the crystal surface of forsterite intercrystalline pore belongs to physisorption. The interaction between the adsorbate molecular hydrogen and the adsorbent forsterite framework weakens with pressure and strengthens with temperature, which is a crucial factor, and intercrystalline pore size. The adsorption capacity of molecular hydrogen in the intercrystalline pore of forsterite increases with pressure and intercrystalline pore size and decreases with temperature. By contrast, the adsorption capacity of molecular hydrogen in nonporous forsterite is controlled by pressure above 1200 K. Variations in intercrystalline pore size above 5 Å have a negligible effect on the capacity of adsorbed state molecular hydrogen at a given temperature and pressure. The adsorption of molecular hydrogen on different crystal faces of forsterite is anisotropic, with stronger adsorption on (001) and (100) than on (010) crystal faces. The adsorption capacity of molecular hydrogen in the intercrystalline pore decreases with the increase in oxygen fugacity at a given pressure, temperature, or intercrystalline pore sizes. The significant amount of molecular hydrogen stored in forsterite can provide a rich material basis for the short-term seismic precursor anomaly of hydrogen concentration and the formation of water through the reaction of silica with molecular hydrogen in the mantle.

Prospective Neural Network Model for Seismic Precursory Signal Detection in Geomagnetic Field Records

We designed a convolutional neural network application to detect seismic precursors in geomagnetic field records. Earthquakes are among the most destructive natural hazards on Earth, yet their short-term forecasting has not been achieved. Stress loading in dry rocks can generate electric currents that cause short-term changes to the geomagnetic field, yielding theoretically detectable pre-earthquake electromagnetic emissions. We propose a CNN model that scans windows of geomagnetic data streams and self-updates using nearby earthquakes as labels, under strict detectability criteria. We show how this model can be applied in three key seismotectonic settings, where geomagnetic observatories are optimally located in high-seismicity-rate epicentral areas. CNNs require large datasets to be able to accurately label seismic precursors, so we expect the model to improve as more data become available with time. At present, there is no synthetic data generator for this kind of application, so artificial data augmentation is not yet possible. However, this deep learning model serves to illustrate its potential usage in earthquake forecasting in a systematic and unbiased way. Our method can be prospectively applied to any kind of three-component dataset that may be physically connected to seismogenic processes at a given depth.

Eruption Forecasting of Strokkur Geyser, Iceland, Using Permutation Entropy

AbstractA volcanic eruption is usually preceded by seismic precursors, but their interpretation and use for forecasting the eruption onset time remain a challenge. A part of the eruptive processes in open conduits of volcanoes may be similar to those encountered in geysers. Since geysers erupt more often, they are useful sites for testing new forecasting methods. We tested the application of Permutation Entropy (PE) as a robust method to assess the complexity in seismic recordings of the Strokkur geyser, Iceland. Strokkur features several minute‐long eruptive cycles, enabling us to verify in 63 recorded cycles whether PE behaves consistently from one eruption to the next one. We performed synthetic tests to understand the effect of different parameter settings in the PE calculation. Our application to Strokkur shows a distinct, repeating PE pattern consistent with previously identified phases in the eruptive cycle. We find a systematic increase in PE within the last 15 s before the eruption, indicating that an eruption will occur. We quantified the predictive power of PE, showing that PE performs better than seismic signal strength or quiescence when it comes to forecasting eruptions.

Analysis of Potential Precursory Pattern at Earth Surface and the Above Atmosphere and Ionosphere Preceding Two Mw ≥ 7 Earthquakes in Mexico in 2020–2021

AbstractComprehensive analyses of seismic precursory characteristics may provide evidence for the possible mechanisms of lithosphere‐atmosphere‐ionosphere coupling (LAIC). The integrated monitoring data from space and ground measurements makes it possible to reveal the potential earthquake precursory pattern obeying LAIC. In this paper, we study seismic precursors from air temperature data of the National Center for Environmental Prediction (NCEP), Global Navigation Satellite System (GNSS) based Total Electron Content (TEC) and electron density retrieved from Swarm satellite (Alpha) data in two Mw 7.0 earthquakes in Mexico in 2020–2021. We find seismic thermal anomalies can be identified from temperature variation in the lithosphere and atmosphere by improved tidal force fluctuant analysis (TFFA). The spatial‐temporal evolution of seismic thermal anomalies is significantly different from that of non‐seismic thermal anomalies. In addition, synergistic observations of the Swarm Alpha satellite and GNSS stations can provide more comprehensive information about perturbations in the ionosphere. The results show that anomalies originate along fault lineaments near the epicenter, leading to air pressure gradient and ionization process in the atmosphere, followed by ionospheric perturbations. Furthermore, composite anomalies of LAIC first appear around a month before earthquakes and tend to recur several times over earthquake preparation phases. Our study provides more evidence for understanding the characteristics of earthquake precursors.

A 20-Year Journey of Forecasting with the “Every Earthquake a Precursor According to Scale” Model

Nearly 20 years ago, the observation that major earthquakes are generally preceded by an increase in the seismicity rate on a timescale from months to decades was embedded in the “Every Earthquake a Precursor According to Scale” (EEPAS) model. EEPAS has since been successfully applied to regional real-world and synthetic earthquake catalogues to forecast future earthquake occurrence rates with time horizons up to a few decades. When combined with aftershock models, its forecasting performance is improved for short time horizons. As a result, EEPAS has been included as the medium-term component in public earthquake forecasts in New Zealand. EEPAS has been modified to advance its forecasting performance despite data limitations. One modification is to compensate for missing precursory earthquakes. Precursory earthquakes can be missing because of the time-lag between the end of a catalogue and the time at which a forecast applies or the limited lead time from the start of the catalogue to a target earthquake. An observed space-time trade-off in precursory seismicity, which affects the EEPAS scaling parameters for area and time, also can be used to improve forecasting performance. Systematic analysis of EEPAS performance on synthetic catalogues suggests that regional variations in EEPAS parameters can be explained by regional variations in the long-term earthquake rate. Integration of all these developments is needed to meet the challenge of producing a global EEPAS model.

Lineament analysis as a seismic precursor: The El Mayor Cucapah earthquake of April 4, 2010 (MW7.2), Baja California, Mexico

An earthquake called the MW7.2 “El Mayor Cucapah” earthquake on April 4, 2010 has been analyzed for seismic precursor. The changes in the lineament system concerning its pattern and time intervals were analyzed during the earthquake preparation period and occurrence using the automated lineament detection method. The Landsat 5 TM images were processed using LESSA and ADALGEO software obtaining similar results. The statistical analysis revealed the stress accumulation due to plate interaction during earthquake formation. The study shows that the number of extracted lineaments changes rapidly about 23 months before the earthquake, and the systems return to the initial stage after 23 months. Most lineaments coincide with the extension of the San Andreas Fault as NW direction is the dominant trend. Thus, it can be concluded that the featural changes within the Rose diagram corresponding to the different strokes direction along with oriented elongation lines as disclosed in the present study using satellite images could be identified as a mid-term and/or short-term precursors of the earthquake. However, even though the dynamism of the El Mayor Cucapah earthquake is found in the extracted lineaments, it is possible to isolate more significant earthquakes even if new ones appear near the zone. Moreover, using two algorithms for lineament detection allows for the tectonics to corroborate the obtained lineaments and dynamism.

Acoustic monitoring and analyses of air gun, pile driving, vessel, and ambient sounds during the 2015 seismic surveys on the Sakhalin shelf

During the summer of 2015, four 4D seismic surveys were conducted on the northeastern Sakhalin shelf near the feeding grounds of the Korean-Okhotsk (western) gray whale (Eschrichtius robustus) population. In addition to the seismic surveys, onshore pile driving activities and vessel operations occurred. Forty autonomous underwater acoustic recorders provided data in the 2 Hz to15 kHz frequency band. Recordings were analyzed to evaluate the characteristics of impulses propagating from the seismic sources. Acoustic metrics analyzed comprised peak sound pressure level (PK), mean square sound pressure level (SPL), sound exposure level (SEL), T100%, T90% (the time intervals that contain the full and 90% of the energy of the impulse), and kurtosis. The impulses analyzed differed significantly due to the variability and complexity of propagation in the shallow water of the northeast Sakhalin shelf. At larger ranges, a seismic precursor propagated in the seabed ahead of the acoustic impulse, and the impulses often interfered with each other, complicating analyses. Additional processing of recordings allowed evaluation and documentation of relevant metrics for pile driving, vessel sounds, and ambient background levels. The computed metrics were used to calibrate acoustic models, generating time resolved estimates of the acoustic levels from seismic surveys, pile driving, and vessel operations on a gray whale distribution grid and along observed gray whale tracks. This paper describes the development of the metrics and the calibrated acoustic models, both of which will be used in work quantifying gray whale behavioral and distribution responses to underwater sounds and to determine whether these observed responses have the potential to impact important parameters at the population level (e.g., reproductive success).

Numerical precursory study on strong earthquakes in southern and Baja California

We examined the spatio-temporal variation of correlation fractal dimension (DC) for M≥2.5 earthquakes in southern and Baja California to ascertain the incidence of seismic precursors before strong earthquakes. The unforeseen 2019 Ridgecrest events have restructured the crustal stress patterns in the adjacent regions signifying the prerequisite for a caveat. The current research attempts to discern the existence of numerical precursors of strong earthquakes (Mw > 7) based on the correlation integral method. A time window of three decades (1990–2020) was analyzed to study the relative changes in the distribution of earthquake clusters and the subsequent variations reflected in DC values. We have successfully demonstrated the numerical precursors for four stronger main shocks (1992 Landers Mw 7.3, 1999 Hectormine Mw 7.1, 2010 El-Mayor Cucapah Mw 7.2, and 2019 Ridgecrest Mw 7.1) through the relative changes in DC. In addition, our study has confirmed the remarkable correlation between low values of DC and spatio-temporal clustering of earthquakes for the study region. Though the present study confers the application of DC on the recognition of seismicity patterns before major events, the constant monitoring of the same can give insights into earthquake forecasting and seismic risk analysis of unstable tectonic terrains.

Thermal and seismic precursors to the explosive eruption at La Soufrière Volcano, St. Vincent in April 2021

High temporal resolution, geostationary, thermal infrared data from the Advanced Baseline Imager combined with seismic data of La Soufrière Volcano, St. Vincent provide empirical insights into the volcanic processes and mechanisms that occurred from November 2020 until the explosive phase in April 2021. An overall increase in intensity of thermal output and seismicity are observed during the effusive phase; however, the intensity of the thermal data increased ∼20 days earlier than the seismicity. During the effusive phase, the daily radiant heat flux increased from 0.01 to >100 MW and the seismicity increased from 1 to 647 events. The climax of both records occurred during the explosive eruptions on April 9-14, 2021. Strong correlations are observed between these datasets in the weeks leading to the explosive eruptions. A significant (∼5 day) decrease in thermal and seismic activity is observed ∼12 days prior to the explosive phase, which could reveal a hiatus in magma migration prior to the eruption. Periods of decoupling between these datasets are also observed and are attributed to different mechanisms during the volcanic unrest. Occurrences with high seismicity and low heat flux may indicate deeper magmatic migration where no significant surface thermal response could be detected, for example. Recognizing correlations, or lack thereof, between high-temporal resolution thermal infrared and seismic data expands potential insights to subsurface volcanic processes by providing a second, complementary vantage. Such seismic-thermal analysis can improve our community's capability to monitor and evaluate new volcanic eruptions. Indeed, extensive seismic networks (local and regional) and multiple geostationary weather satellites now provide near global coverage. A similar analysis to our work at La Soufrière Volcano, St. Vincent is feasible, and should become routine, at other volcanoes worldwide using combined high-temporal, ground and orbital data where available. The 2022 eruption at Hunga-Tonga-Hunga-Ha'apai volcano, Tonga, illustrates the important potential for these high cadence data and subsequent analysis even at extremely remote volcanoes.

A Multi-Network based Hybrid LSTM model for ionospheric anomaly detection: A case study of the Mw 7.8 Nepal earthquake

We propose a Multi-Network-based Hybrid Long Short Term Memory (N-LSTM) model for ionospheric anomaly detection to forecast highly irregular data of the ionospheric Total Electron Content (TEC). Previously purposed models were suffering from the problems of vanishing gradient, exploding gradient, uncertainty, and parameter bias. LSTM is used to overcome the vanishing and exploding gradient problems and the remaining two (uncertainty and parameter bias) are subjugated by N-LSTM. We have also discussed the implementation of the model by using the Mw 7.8 Nepal Earthquake (EQ) that occurred on April 25, 2015. The proposed model detects a significant negative anomaly about 14 days before the impending EQ. Furthermore, we find gradual increments in the TEC time-series, where the TEC values gradually increased, in terms of positive anomalies, for four continuous days (April 21–24, 2015) till the mainshock. Further analysis revealed that the nighttime TEC enhancements are more dominant than the daytimes, which persisted for 10 h (22:00–08:00 LT) in the absence of the solar flux, we named them the absolute seismic precursors. These gradual enhancements establish a perfect correlation with several atmospheric anomalies, reported in the previous studies, where the variations in different atmospheric parameters like Outgoing Longwave Radiation (OLR), air temperature, Ozone, and sub-ionospheric Very-Low Frequency (VLF), were reported for 4 consistent days till the EQ day. The N-LSTM result was compatible with a 30-day running median, which is the classical method of ionospheric anomaly detection. We also examined the planetary K-index (Kp), disturbance storm-time (Dst), solar radio flux (F10.7), and solar wind speed (VSW) indices to check the possible attribution of space weather on the ionosphere during the analysis. The results showed that the anomalies of the ionospheric TEC were more dominantly caused by the EQ phenomenon than the space weather during the nighttime hours. Also, N-LSTM provided sufficient short-term prediction performance of the ionospheric TEC and anomaly detection.

Seismic precursors to the Whakaari 2019 phreatic eruption are transferable to other eruptions and volcanoes

Volcanic eruptions that occur without warning can be deadly in touristic and populated areas. Even with real-time geophysical monitoring, forecasting sudden eruptions is difficult, because their precursors are hard to recognize and can vary between volcanoes. Here, we describe a general seismic precursor signal for gas-driven eruptions, identified through correlation analysis of 18 well-recorded eruptions in New Zealand, Alaska, and Kamchatka. The precursor manifests in the displacement seismic amplitude ratio between medium (4.5–8 Hz) and high (8–16 Hz) frequency tremor bands, exhibiting a characteristic rise in the days prior to eruptions. We interpret this as formation of a hydrothermal seal that enables rapid pressurization of shallow groundwater. Applying this model to the 2019 eruption at Whakaari (New Zealand), we describe pressurization of the system in the week before the eruption, and cascading seal failure in the 16 h prior to the explosion. Real-time monitoring for this precursor may improve short-term eruption warning systems at certain volcanoes.

Testing Earthquake Nucleation Length Scale with Pawnee Aftershocks

Abstract The interpretation of precursory seismicity can depend on a critical nucleation length scale h*, yet h* is largely unconstrained in the seismogenic crust. To estimate h* and associated earthquake nucleation processes at 2–7 km depths in Oklahoma, we studied seismic activity occurring prior to nine M 2.5–3.0 earthquakes that are aftershocks of the 3 September 2016 M 5.8 Pawnee, Oklahoma, earthquake. Four of the nine M 2.5–3.0 aftershocks studied did not have detectable seismicity within a 2 km radius of their hypocenters in the preceding 16 hr time windows. For the other five events, which did exhibit foreshock sequences, we estimated the static stress changes associated with each event of each sequence based on precise earthquake relocations and magnitude estimates. By carefully examining the spatiotemporal characteristics, we found all five of these M 2.5–3.0 aftershocks, and 70% of our studied events were plausibly triggered via static stress transfer from nearby earthquakes occurring hours to seconds earlier, consistent with the cascade nucleation model and a small h* in this region. The smallest earthquakes we could quantitatively study were M −1.5 events, which likely have 1–2 m rupture dimensions. The existence of these small events also supports a small nucleation length scale h*≤1 m, consistent with laboratory estimates. However, our observations cannot rule out more complicated earthquake initiation processes involving interactions between foreshocks and slow slip. Questions also remain as to whether aftershocks initiate differently from more isolated earthquakes.

Interaction Between Aseismic Slip and Fluid Invasion in Earthquake Swarms Revealed by Dense Geodetic and Seismic Observations

AbstractRecent seismic and geodetic observations suggest the involvement of pressurized fluid and aseismic slip during earthquake swarms. However, the interaction between these two factors is not fully understood. In this study, we show geodetic signals induced by aseismic opening and shear dislocation on a fault, accompanied by hypocenter migration during an earthquake swarm in the Hakone volcano, central Japan. The hypocenters were concentrated on a vertical plane, and the focal mechanisms were strike‐slip faults whose nodal planes were consistent with the hypocenter distribution. Precursory seismicity occurred 1 week before the main swarm. We observed a complex pattern of hypocenter migration during the seismic sequence; namely, the lower limit of the seismicity appears to expand downward during the precursory seismicity, followed by an upward hypocenter diffusion. We also observed tilt changes that could be explained by opening and shear dislocation on the fault plane inferred from the planar hypocenter distribution. Furthermore, we identified several groups of repeating earthquakes. The average aseismic slip history inferred from the repeating earthquakes indicated a minor aseismic slip of 0.4 mm during the precursory seismic activity, which accelerated by up to 3 mm during the main swarm. The total cumulative slip was consistent with the geodetic model results. These observations may suggest that fluid intrusion caused the aseismic slip, and the complex migration of the hypocenters reflects the aseismic slip propagation. We hypothesize that aseismic deformation acts as the driving force for the earthquake swarms together with the intrusion of pressurized fluid.

Potential seismic precursors and surficial dynamics of a deadly Himalayan disaster: an early warning approach

On 7 February 2021, Chamoli district (Uttarakhand, India) was devastated by a deadly rock-ice avalanche that led to a large causality of more than 200 people and a huge economic loss. We found noteworthy sequence of precursory signals of main failure/detachment preceded by a dynamic nucleation phase. The rock-ice avalanche appears to have been initiated by seismic precursors which were continuously active for 2:30 h prior to main detachment. The seismic amplitude, frequency characteristics and signal-to-noise ratio variation of detected tremors indicate static to dynamic changes in nucleation phase located at the source of detached wedge. The characteristics of seismic data distinguished debris flow and hitting obstacles from other seismic sources and allowed the estimations of debris flow speed. We analyzed and verified the seismic signals with field evidences to estimate the associated impacts and velocity of dynamic flow. The proximal high-quality seismic data allowed us to reconstruct the complete chronological sequence and evaluate impacts since the initiation of nucleation phase to its advancement. Furthermore, we suggest that real-time seismic monitoring with existing network and future deployment of integrated dense network can be used for forecasting of flow events and hazard mitigation in the downstream.

Hydrogeochemical changes before and during the 2019 Benevento seismic swarm in central-southern Italy

Insights into seismic precursors have been obtained in the last decades. However, a detailed understanding of hydrogeochemical anomalies prior to earthquakes still remains the aim of many research teams worldwide. In order to investigate the earthquake-groundwater relationship, between 2018 and 2020, we performed sampling surveys coupled with continuous multiparametric monitoring in Grassano spring fed by the Matese aquifer (central-southern Apennines, Italy). Hydrogeochemical changes were observed before the onset and during the 2019 Benevento seismic sequence, including dissolved CO2 increase, pH lowering, and anomalies in major ions (i.e., Ca2+, Na+, HCO3–) that later recovered to their typical concentrations. We suggest that variations in groundwater geochemistry were induced by dilatative preparatory phases of earthquakes, typical of the extensional setting. This condition allowed the deep CO2 upwelling along tectonic discontinuities, as testified by the Cext (carbon from external sources) behaviour detected in Grassano groundwater during the 2019 year. Despite the small-intermediate magnitude of the mainshock, results highlight and confirm the occurrence of a potential pre-seismic geochemical process in the fractured carbonate aquifers, similar to the one proposed in literature for the stronger 2016–2017 Amatrice-Norcia seismic sequence.

Space–Time Trade-Off of Precursory Seismicity in New Zealand and California Revealed by a Medium-Term Earthquake Forecasting Model

The ‘Every Earthquake a Precursor According to Scale’ (EEPAS) medium-term earthquake forecasting model is based on the precursory scale increase (Ψ) phenomenon and associated scaling relations, in which the precursor magnitude MP is predictive of the mainshock magnitude Mm, precursor time TP and precursory area AP. In early studies of Ψ, a relatively low correlation between TP and AP suggested the possibility of a trade-off between time and area as a second-order effect. Here, we investigate the trade-off by means of the EEPAS model. Existing versions of EEPAS in New Zealand and California forecast target earthquakes of magnitudes M > 4.95 from input catalogues with M > 2.95. We systematically vary one parameter each from the EEPAS distributions for time and location, thereby varying the temporal and spatial scales of these distributions by two orders of magnitude. As one of these parameters is varied, the other is refitted to a 20-year period of each catalogue. The resulting curves of the temporal scaling factor against the spatial scaling factor are consistent with an even trade-off between time and area, given the limited temporal and spatial extent of the input catalogue. Hybrid models are formed by mixing several EEPAS models, with parameter sets chosen from points on the trade-off line. These are tested against the original fitted EEPAS models on a subsequent period of the New Zealand catalogue. The resulting information gains suggest that the space–time trade-off can be exploited to improve forecasting.