Analysis of GNSS Data for Earthquake Precursor Studies Using IONOLAB-TEC in the Himalayan Region

Abstract

Earthquake precursors are the indicators that appear before an earthquake. The release of radon gas, ionospheric disturbances, anomalous animal behavior, and so on are examples of seismic and aseismic events. Ionospheric perturbations can be proved to be a reliable method in earthquake prediction. The GNSS data detect changes in the ionosphere through the time lag of the transmitted GPS signals recorded at the Earth-based receivers. A negative TEC anomaly is caused by the stress released from the rocks before the earthquake, which elevates positive ions or p-holes in the atmosphere and decreases the ions in the ionosphere. A positive TEC anomaly follows this because of the increase in ions in the ionosphere. The ionospheric disruption in the Himalayan region is examined before five random earthquakes. For this, data from 15 separate GNSS stations are investigated using IONOLAB-TEC. A promising total electron content (TEC) data estimate with a temporal resolution of 30 s was analyzed. The results of the TEC data analysis depict the anomaly a month before the five earthquakes, followed by the later perturbation in the earthquake preparation zone. TEC anomalies are enhanced more by the uniform spatial distribution of GNSS stations in the epicentral region than by randomly distributed stations. The results of IONOLAB-TEC and the widely used GPS-TEC software were compared. Owing to its temporal resolution, IONOLAB-TEC has edge over the GPS-TEC software in that it can identify even the slightest negative anomalies before an earthquake.

Keywords

• earthquake precursor
• ionospheric perturbation
• TEC
• GNSS
• IONOLAB-TEC