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We review changes in groundwater chemistry as precursory signs for earthquakes. In particular, we discuss pH, total dissolved solids (TDS), electrical conductivity, and dissolved gases in relation to their significance for earthquake prediction or forecasting. These parameters are widely believed to vary in response to seismic and pre-seismic activity. However, the same parameters also vary in response to non-seismic processes. The inability to reliably distinguish between changes caused by seismic or pre-seismic activities from changes caused by non-seismic activities has impeded progress in earthquake science. Short-term earthquake prediction is unlikely to be achieved, however, by pH, TDS, electrical conductivity, and dissolved gas measurements alone. On the other hand, the production of free hydroxyl radicals (•OH), subsequent reactions such as formation of H2O2 and oxidation of As(III) to As(V) in groundwater, have distinctive precursory characteristics. This study deviates from the prevailing mechanical mantra. It addresses earthquake-related non-seismic mechanisms, but focused on the stress-induced electrification of rocks, the generation of positive hole charge carriers and their long-distance propagation through the rock column, plus on electrochemical processes at the rock-water interface.

The catastrophic magnitude of life and monetary losses associated with earthquakes deserve serious attention and mitigation measures. However, in addition to the pre-earthquake and post-earthquake alleviation actions, the scientific community indeed needs to reconsider the possibilities of earthquake predictions using non-seismic precursors. A significant number of studies in the recent decades have reported several possible earthquake precursors such as anomalies in electric field, magnetic field, gas/aerosol emissions, ionospheric signals, ground water level, land surface temperature, surface deformations, animal behaviour, thermal infrared signals, atmospheric gravity waves, and lightning. Such substantial number of scientific articles and reported anomalous signals cannot be overlooked without a thoughtful appraisal. Here, we provide an opinion on the way forward for earthquake prediction in terms of challenges and possibilities while using non-seismic precursors. A general point of concern is the widely varying arrival times and the amplitudes of the anomalies, putting a question mark on their universal applicability as earthquake markers. However, a unifying concept which does not only define the physical basis of either all or most of these anomalies but which also streamlines their characterisation procedure must be the focus of future earthquake precursory research. Advancements in developing the adaptable instrumentation for in-situ observations of the claimed non-seismic precursors must be the next step and the satellite observations should not be taken as a replacement for field-based research. We support the need to standardise the precursor detection techniques and to employ a global-scale monitoring system for making any possible earthquake predictions reliable.

The transition from stable to unstable states in geological systems, such as landslides and fault zones, remains poorly understood. Seismic precursors and foreshocks related to the transition, if present, are often difficult to observe, and their interpretation remains challenging. Here, we report observations consistent with a nucleation process preceding the glacier collapse on 28 May 2025 in the village of Blatten, Switzerland. We identify three main groups of events using an unsupervised machine learning approach applied to 20 days of continuous seismic data recorded before the main event. We separate rockfalls from the seismic signatures associated with sliding‐related processes in the glacier. The observations are consistent with slip‐weakening behavior, with seismic activity accelerating during the final 2 days before failure. These results highlight the potential of unsupervised learning to identify such seismic precursors prior to collapse.

This study explores the feasibility of using fluctuations in the recurrence magnitude dispersion factor (b-value) as a seismic precursor for the Mizoram earthquake that occurred on November 26, 2021, in the Indo-Burma region of northeast India. Employing a comprehensive and homogeneous earthquake catalog spanning from 1900 to 2020, the seismic analysis involved delustering and completeness testing. The research implements a sub-sectional b-value calculation method, dividing the study area into uniformly sized grid cells (2° × 2°) and performing temporal b-value mapping for each grid. The epicenter of the Mizoram earthquake was located within a grid cell characterized by an intermediate b-value. Time-series analysis of the b-value indicated a notable decline preceding the main event, suggesting its potential as a seismic precursor. The study also examines depth-dependent variations in the b-value, revealing an inverse relationship between the b-value and crustal stress. To evaluate the significance of b-value anomalies, the Kolmogorov–Smirnov (K-S) statistic was employed instead of visual inspection. Additionally, the research provides probabilistic estimates of seismic hazard parameters, including the most probable maximum yearly earthquake, mean return period, and probabilities of earthquakes of varying magnitudes. These findings contribute to a deeper understanding of the complex seismotectonic framework and high lithospheric variability in the investigated region.

Rockbursts pose serious threats to the safety of personnel and equipment in tunnels of the Hanjiang-to-Weihe River Diversion Project. Small-scale structural planes around the tunnel play an important role in controlling the occurrence and intensity of rockbursts. To study the characteristics and evolution of rockbursts along a structural plane, three successive, intense rockbursts in the #4 sub-tunnel were summarized in detail and investigated by analyzing 492 recorded microseismic events. The rockbursts were closely related to the structural plane, because most events had a ratio of S-wave energy to P-wave energy larger than 10 and were associated with shearing along the existing structural plane. The statistical parameters, which include the energy index, cumulative apparent volume, and b value, were used to analyze the evolution of the three rockbursts. Quantitative interpretation of the source parameter and statistical parameters for a given microseismic data set provided a significant insight into characterization of rockbursts along the structural plane. In addition, some distinctive seismic precursors for rockbursts along the structural plane were acquired; therefore, rockbursts along the structural plane may be effectively predicted based on these seismic precursors. Preliminary results in the current study are valuable for predicting and mitigating rockburst hazards in tunnels with similar conditions.

Electromagnetic emissions from earthquakes are known as precursors and are of considerable importance for the purpose of early alarms. The propagation of low-frequency waves is favored, and the range between tens of mHz to tens of Hz has been heavily investigated in the last thirty years. This work describes the self-financed Opera 2015 project that initially consisted of six monitoring stations over Italy, equipped with electric and magnetic field sensors, among others. Insight of the designed antennas and low-noise electronic amplifiers provides both characterization of performance (similar to the best commercial products) and the elements to replicate the design for our own independent studies. Measured signals through data acquisition systems were then processed for spectral analysis and are available on the Opera 2015 website. Data provided by other world-known research institutes have also been considered for comparison. The work provides examples of processing methods and results representation, identifying many exogenous noise contributions of natural or human-made origin. The study of the results occurred for some years and led us to think that reliable precursors are confined to a short area around the earthquake due to the significant attenuation and the effect of overlapping noise sources. To this aim, a magnitude-distance indicator was developed to classify the detectability of the EQ events observed during 2015 and compared this with some other known earthquake events documented in the scientific literature.

This study investigates the implementation of Schreider’s quiescence algorithm and two variants that utilize spatiotemporal data to identify patterns of seismic quiescence. These patterns are of particular interest as they may serve as precursors to major seismic events, specifically large earthquakes (M>7), within the Mexican subduction zone associated with the Cocos Plate. We identify two characteristic stages: the α-stage, where a notable deviation is observed in the Schreider convolutions, and the β-stage, where the convolutions return to their background levels. In addition, we identify that the Schreider algorithm cannot discern quiescence patterns when earthquakes M>7 are too close in space and time. Consequently, we explore the behavior of the convolutions in three cases where the algorithm is restarted after the mainshocks, and we find apparent advantages for the spatiotemporal variants of the convolutions. The findings contribute to a more profound understanding of the stages preceding large subduction earthquakes and aid in the identification of precursor patterns in this region.

Forecasting earthquakes implies that there are time-varying processes, which depend on the changing conditions deep in the Earth's crust prior to major seismic activity. These processes may be linearly or non-linearly correlated. In seismology, the research has traditionally focused on mechanical variables, including precursory ground deformation (revealing the build-up of stress deep below) and on prior seismic events (past earthquakes may be related to or even trigger future earthquakes). Since the results have been less than convincing, there is a general consensus in the seismology community that earthquake forecasting on time scales comparable to meteorological forecasts is still quite far in the future, if ever attainable. The starting point of the present review is to acknowledge that there are innumerable reports of other types of precursory phenomena observable on the ground or in near-Earth space ranging from the emission of electromagnetic waves from ultralow frequency (ULF) to near-infrared (NIR) and visible (VIS) light, electric field and magnetic field anomalies of various kinds (see below), all the way to widely reported but never fully understood unusual animal behavior. These precursory signals are intermittent and seem not to occur systematically before every major earthquake. As a result they are not widely accepted, because no one could fully explain their origins. In addition, the diversity of these signals makes them look unrelatable, hampering any progress. In the first part, we review evidence for a solid-state mechanism based on decades of research bridging semi-conductor physics, solid state chemistry and rock physics, that is capable of providing explanations for the diversity of reported pre-earthquake phenomena. In fact, it appears that all pre-earthquake phenomena might be traceable to a single fundamental process on the atomic scale: the rupture of peroxy bonds via activation of electronic charges, electrons and positive holes, in rocks subjected to tectonic stresses prior to seismic activity. The positive holes are defect electrons in the O 2- sublattice. They are unusual inasmuch as they are able to flow out of the stressed rock volume, into and through the surrounding unstressed or less stressed rocks. They form electric currents that travel fast and far, causing along the way a wide range of physical and chemical follow-on processes: electrical ground potentials, stimulated infrared emission, massive air ionization, radon emanation, increased levels of ozone, toxic levels of carbon monoxide (CO) and more. In the second part, we critically examine satellite and ground station data, recorded before a selection of past large earthquakes. Some of the phenomena can be directly related to the peroxy defect theory, namely, radon gas emanations, corona discharges, thermal infrared emissions, air ionization, ion and electron content in the ionosphere, and electro-magnetic anomalies. Of course there is a need for further systematic investigations, continuing statistical examination of the relevance and confidence levels of the observable precursors. Only then will the scientific community be able to assess and eventually improve the performance of earthquake forecasts.

This paper explores multi-instrument space-borne observations in order to validate physical concepts of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) in relation to a selection of major seismic events. In this study we apply some validated techniques to observations in order to identify atmospheric and ionospheric precursors associated with some of recent most destructive earthquakes: M8.6 of March 28, 2005 and M8.5 of Sept. 12, 2007 in Sumatra, and M7.9 of May 12, 2008 in Wenchuan, China. New investigations are also presented concerning these three earthquakes and for the M7.2 of March 2008 in the Xinjiang-Xizang border region, China (the Yutian earthquake). It concerns the ionospheric density, the Global Ionospheric Maps (GIM) of the Total Electron Content (TEC), the Thermal Infra-Red (TIR) anomalies, and the Outgoing Longwave Radiation (OLR) data. It is shown that all these anomalies are identified as short-term precursors, which can be explained by the LAIC concept proposed in [S. Pulinets, D. Ouzounov, J. Asian Earth Sci. 41 , 371 (2011)].

Focusing on major earthquakes (EQs; MS ≥ 7) in Western China, this study primarily analyzes the fluctuation in Atmospheric Chemical Potential (ACP) before and after the Wenchuan, Yushu, Lushan, Jiuzhaigou, and Maduo EQs via Climatological Analysis of Seismic Precursors Identification (CAPRI). The distribution of vertical ACP revealed distinct altitude-dependent characteristics. The ACP at lower atmospheric layers (100–2000 m) exhibited a high correlation, and this correlation decreased with increasing altitude. Anomalies were detected within one month prior to each of the five EQs studied, with the majority occurring 14 to 30 days before the events, followed by a few additional anomalies. The spatial distribution of anomalies is consistent with the distribution of fault zones, with noticeable fluctuation in surrounding areas. The ACP at an altitude of 200 m gave a balance between sensitivity to seismic signals and minimal surface interference and proved to be optimal for EQ monitoring in Western China. The results offer a significant reference for remote sensing studies related to EQ monitoring and the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) model, thereby advancing our understanding of pre-seismic atmospheric variations in Western China.