Rapid magnitude estimation of the <i>M</i> _<i>W</i> 7.1 2023 Mentawai earthquake using high-rate GNSS data

Abstract Rapid and reliable earthquake source characterization is essential for seismic hazard mitigation in subduction environments. This study integrates high-rate (1 Hz) and daily GNSS observations to analyze the 24 April 2023 M w 7.1 Mentawai earthquake, Indonesia. High-rate GNSS data from stations operated by the Geospatial Information Agency of Indonesia (BIG) were processed using Precise Point Positioning with Ambiguity Resolution (PPP-AR) to obtain three-component displacement time series. Peak ground displacement (PGD) values were calculated and converted to moment magnitude using empirical scaling relations proposed by Melgar et al. (Earthquake magnitude calculation without saturation from the scaling of peak ground displacement. Geophys Res Lett 2015;42:5197–205), Ruhl et al. (A global database of strong-motion displacement GNSS recordings and an example application to PGD scaling. Seismol Res Lett 2019;90:271–9), and Crowell et al. (Demonstration of the Cascadia G-FAST geodetic earthquake early warning system for the Nisqually, Washington, earthquake. Seismological Research Letters 2016;87:930–43). Static GNSS solutions were used to derive coseismic offsets, which were subsequently inverted using an elastic half-space model to estimate the slip distribution. All empirical approaches detected rapid magnitude growth within seconds, significantly earlier than institutional releases. The Crowell formulation provides the best agreement with the official magnitude evolution. The static inversion reproduces observed displacements with a mean absolute error of 0.530 mm and yields a seismic moment of 6.1 × 10 19 N m ( M w ∼ 7.12), consistent with the reference magnitude. These results highlight the effectiveness of integrated GNSS analysis for rapid and robust earthquake source characterization in Indonesian subduction zones.