Geology ReportsSearch

USGS · 70203402

Peak ground displacement saturates exactly when expected: Implications for earthquake early warning

Abstract

The scaling of rupture properties with magnitude is of critical importance to earthquake early warning (EEW) systems that rely on source characterization using limited snapshots of waveform data. ShakeAlert, a prototype EEW system that is being developed for the western United States, provides real-time estimates of earthquake magnitude based on P-wave peak ground displacements measured at stations triggered by the event. The algorithms used in ShakeAlert assume that the displacement measurements at each station are statistically independent and that there exists a linear and time-independent relation between log peak ground displacement and earthquake magnitude. Here we challenge this basic assumption using a comprehensive database of more than 130,000 vertical component waveforms from M4.5-M9 earthquakes occurring near Japan from 1997 through 2017 and recorded by the K-NET and KiK-net strong-motion networks. By analyzing the time-evolution of P-wave peak ground displacements for these earthquakes, we show that there is a break, or saturation, in the magnitude-displacement scaling that depends on the length of the measurement time window. We demonstrate that the magnitude at which this saturation occurs is well-explained by a simple and non-deterministic model of earthquake rupture growth. We then use the predictions of this saturation model to develop a Bayesian framework for estimating posterior uncertainties in real-time magnitude estimates which incorporates the expected time-dependence of the peak displacement measurements.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 29.57345707301757° to 45.82879925192134° latitude; 128.2763671875° to 146.42578125° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Daniel T. Trugman, Morgan T. Page, Sarah E. Minson, Elizabeth S. Cochran. 2019. Peak ground displacement saturates exactly when expected: Implications for earthquake early warning. https://doi.org/10.1029/2018jb017093

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia

During a volcanic crisis, high-rate, localized deformation can indicate magma close to the surface, with important implications for eruption forecasting. However, only a few such examples have been reported, because frequent, dense monitoring is needed. High-resolution Synthetic Aperture Radar (SAR) is capable of achieving <1 m spatial resolution and sub-weekly revisit times, but is under-used. Here we use high-resolution satellite SAR imagery from COSMO-SkyMed, TerraSAR-X, and Sentinel-1 to detect intra-crater uplift preceding the November 2017 onset of eruptive activity at Agung, Indonesia. Processing the SAR imagery with an up-to-date, accurate, high-resolution digital elevation model was crucial for preventing aliasing of the deformation signal and for accurate georeferencing. We show that >15 cm of line-of-sight shortening occurred over a 400-by-400 m area on the crater floor in September-October 2017, accompanying a deep seismic swarm and flank dyke intrusion. We attribute the deformation to the pressurization of a shallow (<200 m deep) hydrothermal system by the injection of magmatic gases and fluids. We also observe a second pulse of intra-crater deformation of 3–5 cm within 4 days to 11 hr prior to the first phreatomagmatic eruption, which is consistent with interaction between the hydrothermal system and the ascending magma. This phreatomagmatic eruption created the central pathway used during the final stages of magma ascent. Our observations have important implications for understanding unrest and eruption forecasting, and demonstrate the potential of monitoring with high-resolution SAR.

Agung Volcano, Bali

Identification of seismo-volcanic regimes at Whakaari/White Island (New Zealand) via systematic tuning of an unsupervised classifier

We present an algorithm based on Self-Organizing Maps (SOM) and k-means clustering to recognize patterns in a continuous 12.5-year tremor time series recorded at Whakaari/White Island volcano, New Zealand (hereafter referred to as Whakaari). The approach is extendable to a variety of volcanic settings through systematic tuning of the classifier. Hyperparameters are evaluated by statistical means, yielding a combination of “ideal” SOM parameters for the given data set. Extending from this, we applied a Kernel Density Estimation approach to automatically detect changes within the observed seismicity. We categorize the Whakaari seismic time series into regimes representing distinct volcano-seismic states during recent unrest episodes at Whakaari (2012/2013, 2016, and 2019). There is a clear separation in classification results between background regimes and those representing elevated levels of unrest. Onset of unrest is detected by the classifier 6 weeks before the August 2012 eruption, and ca. 3.5 months before the December 2019 eruption, respectively. Regime changes are corroborated by changes in commonly monitored tremor proxies as well as with reported volcanic activity. The regimes are hypothesized to represent diverse mechanisms including: system pressurization and depressurization, degassing, and elevated surface activity. Labeling these regimes improves visualization of the 2012/2013 and 2019 unrest and eruptive episodes. The pre-eruptive 2016 unrest showed a contrasting shape and nature of seismic regimes, suggesting differing onset and driving processes. The 2016 episode is proposed to result from rapid destabilization of the shallow hydrothermal system, while rising magmatic gases from new injections of magma better explain the 2012/2013 and 2019 episodes.

Whakaari, White Island

Microgravity change during the 2008-2018 Kı̄lauea summit eruption: Nearly a decade of subsurface mass accumulation

Results from nine microgravity campaigns from Kı̄lauea, Hawaiʻi, spanning most of the volcano's 2008–2018 summit eruption, indicate persistent mass accumulation at shallow levels. A weighted least squares approach is used to recover microgravity results from a network of benchmarks around Kı̄lauea's summit, eliminate instrumental drift, and restore suspected data tares. A total mass of 1.9 × 10 11 kg was determined from these microgravity campaigns to have accumulated below Kı̄lauea Caldera during 2009–2015 at an estimated depth of 1.3 km below sea level. Only a fraction of this mass is reflected in surface deformation, and this is consistent with previously reported discrepancies between subsurface mass accumulation and observed surface deformation. The discrepancy, amongst other independent evidence from gas emissions, seismicity, and continuous gravimetry, indicate densification of magma in the reservoirs below the volcano summit. This densification may have been driven by degassing through the summit vent. It is hypothesized that during the final years of the summit eruption, magma densification resulted in a buildup of pressure in the reservoirs that may have contributed to the lower East Rift Zone outbreak of 2018. The observed mass accumulation beneath Kı̄lauea could not have been detected through other techniques and illustrates the importance of microgravity measurements in volcano monitoring.

Hawai'i