Search USGSSearch

USGS · 70023301

Resolution analysis of finite fault source inversion using one- and three-dimensional Green's functions 2. Combining seismic and geodetic data

Abstract

Using numerical tests for a prescribed heterogeneous earthquake slip distribution, we examine the importance of accurate Green's functions (GF) for finite fault source inversions which rely on coseismic GPS displacements and leveling line uplift alone and in combination with near-source strong ground motions. The static displacements, while sensitive to the three-dimensional (3-D) structure, are less so than seismic waveforms and thus are an important contribution, particularly when used in conjunction with waveform inversions. For numerical tests of an earthquake source and data distribution modeled after the 1994 Northridge earthquake, a joint geodetic and seismic inversion allows for reasonable recovery of the heterogeneous slip distribution on the fault. In contrast, inaccurate 3-D GFs or multiple 1-D GFs allow only partial recovery of the slip distribution given strong motion data alone. Likewise, using just the GPS and leveling line data requires significant smoothing for inversion stability, and hence, only a blurred vision of the prescribed slip is recovered. Although the half-space approximation for computing the surface static deformation field is no longer justifiable based on the high level of accuracy for current GPS data acquisition and the computed differences between 3-D and half-space surface displacements, a layered 1-D approximation to 3-D Earth structure provides adequate representation of the surface displacement field. However, even with the half-space approximation, geodetic data can provide additional slip resolution in the joint seismic and geodetic inversion provided a priori fault location and geometry are correct. Nevertheless, the sensitivity of the static displacements to the Earth structure begs caution for interpretation of surface displacements, particularly those recorded at monuments located in or near basin environments.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

D.J. Wald, R.W. Graves. 2001-05-10. Resolution analysis of finite fault source inversion using one- and three-dimensional Green's functions 2. Combining seismic and geodetic data. https://doi.org/10.1029/2000jb900435

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