The study delves into the relationship between ionospheric total electron content (TEC) anomalies and seismic activity, with a focus on Morocco’s 6.8 Mw earthquake on 8 September 2023, lying within a tectonically active region at the convergence of the African and Eurasian Plates. To enhance the reliability of our findings, we incorporate space weather conditions, utilizing indices (Dst, Kp, and F10.7) to pinpoint periods of stable space weather. This minimizes the possibility of erroneously attributing natural ionospheric fluctuations to seismic events. Notably, our TEC analysis unveils positive and negative anomalies, with some occurring up to a week before the earthquake. These anomalies, exceeding predefined thresholds, provide compelling evidence of significant deviations from typical ionospheric conditions. Spatial mapping techniques employing both station-specific vTEC data and pseudorandom noise codes (PRNs) from multiple global navigation satellite system (GNSS) stations highlight a strong correlation between ionospheric anomalies and the earthquake’s epicenter. The integration of PRNs enhances coverage and sensitivity to subtle anomalies. Additionally, the analysis of satellite imagery and ground displacement data using Sentinel-1 confirms significant ground uplift of approximately 15 cm following the earthquake, shedding light on surface responses to seismic events. These findings underscore the potential of ionospheric science in advancing earthquake early warning systems and deepening our understanding of earthquake precursors, thus contributing to the mitigation of seismic event impacts and the protection of lives and infrastructure.

The influence of solar activity on the ionosphere, a critical area of investigation due to its relevance to the Sun–Earth relationship, has been extensively examined through various methodologies. The ability of solar events to induce disturbances in both the ionosphere and the geomagnetic field is widely acknowledged. This specific study focused on sporadic incidents resulting from X-class solar flares that occurred between 2021 and 2022. Utilizing a methodology that involved analyzing data at 5Hz intervals using wavelet algorithms, the data from the GNSS stations of the National Autonomous University of Mexico (UNAM) were investigated. The primary emphasis was on deducing the Total Electron Content (TEC) within the ionosphere. Subsequently, this parameter for each satellite during instances of solar flares was analyzed. The approach uncovered disruptions in the ionosphere triggered by solar flares, even in cases where events transpired at the periphery of the solar disk and were of magnitudes smaller than X2.

This study provides a comprehensive investigation into ionospheric perturbations associated with the Mw 7.5 earthquake on the Noto Peninsula in January 2024, utilizing data from the International GNSS Service (IGS) network. Focusing on Total Electron Content (TEC), the analysis incorporates spatial mapping and temporal pattern assessments over a 30-day period before the earthquake. The time series for TEC at the closest station to the epicenter, USUD, reveals a localized decline, with a significant negative anomaly exceeding 5 TECU observed 22 and 23 days before the earthquake, highlighting the potential of TEC variations as seismic precursors. Similar patterns were observed at a nearby station, MIZU, strengthening the case for a seismogenic origin. Positive anomalies were linked to intense space weather episodes, while the most notable negative anomalies occurred under geomagnetically calm conditions, further supporting their seismic association. Using Kriging interpolation, the anomaly zone was shown to closely align with the earthquake’s epicenter. To assess the consistency of TEC anomalies in different seismic events, the study also examines the Mw 7.1 Nichinan earthquake in August 2024. The results reveal a prominent negative anomaly, reinforcing the reliability of TEC depletions in seismic precursor detection. Additionally, spatial correlation analysis of Pearson correlation across both events demonstrates that TEC coherence diminishes with increasing distance, with pronounced correlation decay beyond 1000–1600 km. This spatial decay, consistent with Dobrovolsky’s earthquake preparation area, strengthens the association between TEC anomalies and seismic activity. This research highlights the complex relationship between ionospheric anomalies and seismic events, underscoring the value of TEC analysis as tool for earthquake precursor detection. The findings significantly enhance our understanding of ionospheric dynamics related to seismic events, advocating for a comprehensive, multi-station approach in future earthquake prediction efforts.

The identification of areas that are susceptible to damage due to earthquakes is of utmost importance in tectonically active regions like Northeast India. This may provide valuable inputs for seismic hazard analysis; however, it poses significant challenges. The present study emphasized the integration of Interferometric Synthetic Aperture Radar (InSAR) deformation rates with conventional geological and geophysical data to investigate earthquake damage susceptibility in the Barapani Shear Zone (BSZ) region of Northeast India. We used MintPy v1.5.1 (Miami INsar Timeseries software in PYthon) on the OpenSARLab platform to derive time series deformation using the Small Baseline Subset (SBAS) technique. We integrated geology, geomorphology, gravity, magnetic field, lineament density, slope, and historical earthquake records with InSAR deformation rates to derive earthquake damage susceptibility using the weighted overlay analysis technique. InSAR time series analysis revealed distinct patterns of ground deformation across the Barapani Shear Zone, with higher rates in the northern part and lower rates in the southern part. The deformation values ranged from 6 mm/yr to about 18 mm/yr in BSZ. Earthquake damage susceptibility mapping identified areas that are prone to damage in the event of earthquakes. The analysis indicated that about 46.4%, 51.2%, and 2.4% of the area were low, medium, and high-susceptibility zones for earthquake damage zone. The InSAR velocity rates were validated with Global Positioning System (GPS) velocity in the region, which indicated a good correlation (R² = 0.921; ANOVA p-value = 0.515). Additionally, a field survey in the region suggested evidence of intense deformation in the highly susceptible earthquake damage zone. This integrated approach enhances our scientific understanding of regional tectonic dynamics, mitigating earthquake risks and enhancing community resilience.