# Wavelet-Based P-Wave Detection in High-Rate GNSS Data: A Novel Approach for Rapid Earthquake Monitoring in Tsunamigenic Settings

## TL;DR

This paper introduces a wavelet-based method for detecting P-waves in high-rate GNSS data to improve rapid earthquake monitoring and tsunami warnings.

## Contribution

A novel wavelet-based approach using a Mexican hat wavelet and dynamic threshold for P-wave detection in GNSS data is proposed.

## Key findings

- The method reliably detected horizontal P-waves with less than 90 seconds delay.
- P-wave energy was identified in the 0.02–0.5 Hz pseudo-frequency range.
- Vertical component detection was inconsistent due to noise, suggesting room for improvement.

## Abstract

Rapid and accurate detection of primary waves (P-waves) using high-rate Global Navigation Satellite System (GNSS) data is essential for earthquake monitoring and tsunami early warning systems, where traditional seismic methods are less effective in noisy environments. We applied a wavelet-based method using a Mexican hat wavelet and dynamic threshold to thoroughly analyze the three-component displacement waveforms of the 2009 Padang, 2012 Simeulue, and 2018 Palu Indonesian earthquakes. Data from the Sumatran GPS Array and Indonesian Continuously Operating Reference Stations were analyzed to determine accurate displacements and P-waves. Validation with Indonesian geophysical agency seismic records indicated reliable detection of the horizontal component, with a time delay of less than 90 s, whereas the vertical component detection was inconsistent, owing to noise. Spectrogram analysis revealed P-wave energy in the pseudo-frequency range of 0.02–0.5 Hz and confirmed the method’s sensitivity to low-frequency signals. This approach illustrates the utility of GNSS data as a complement to seismic networks for the rapid characterization of earthquakes in complex tectonic regions. Improving the vertical component noise suppression might further help secure their utility in real-time early warning systems.