Source Parameters Inversion for Recent Large Undersea Earthquakes from GRACE Data

This Report was prepared for and submitted to the Graduate School of the Ohio State University as a dissertation in partial fulfillment of the requirements for the PhD degree.This research is conducted under the supervision of Professor C.K. Shum, Division of Geodetic Science, School of Earth Sciences, The Ohio State University. This research is primarily supported by NASA’s Earth and Space Science Fellowship (ESSF) Program (Grant NNX12AO06H), partially supported by National Science Foundation (NSF) Division of Earth Sciences (Grant EAR-1013333). GRACE data products are from NASA’s PODAAC via Jet Propulsion Laboratory/California Institute of Technology (JPL), University of Texas Center for Space Research (CSR), and GeoForschungsZentrum Potsdam (GFZ). Preliminary GPS time series provided by the ARIA team at JPL and Caltech. All original GEONET RINEX data were provided to California Institute of Technology by the Geospatial Information Authority (GSI) of Japan. Some figures in this paper were generated using the Generic Mapping Tools (GMT) [Wessel and Smith, 1991]. This work was also supported in part by an allocation of computing resources from the Ohio Supercomputer Center (http://www.osc.edu).The north component of gravity and gravity gradient changes from the Gravity Recovery And Climate Experiment (GRACE) are used to study the coseismic gravity change for five earthquakes over the last decade: the 2004 Sumatra-Andaman earthquake, the 2007 Bengkulu earthquake, the 2010 Maule, Chile earthquake, the 2011 Tohoku earthquake, and the 2012 Indian Ocean earthquakes. We demonstrate the advantage of these north components to reduce north-south stripes and preserve higher spatial resolution signal in GRACE Level 2 (L2) monthly Stokes Coefficients data products. By using the high spherical harmonic degree (up to degree 96) data products and the innovative GRACE data processing approach developed in this study, the retrieved gravity change is up to – 34±1.4 μGal for the 2004 Sumatra and 2005 Nias earthquakes, which is by far the highest coseismic signal retrieved among published studies. Our study reveals the detectability of earthquakes as small as Mw 8.5 (i.e., the 2007 Bengkulu earthquake) from GRACE data. The localized spectral analysis is applied as an efficient method to determine the practical spherical harmonic truncation degree leading to acceptable signal-to-noise ratio, and to evaluate the noise level for each component of gravity and gravity gradient change of the seismic deformations. By establishing the linear algorithm of gravity and gravity gradient change with respect to the double-couple moment tensor, the point source parameters are estimated through the least squares adjustment combined with the simulated annealing algorithm. The GRACE-inverted source parameters generally agree well with the slip models estimated using other data sets, including seismic, GPS, or combined data. For the 2004 Sumatra- Andaman and 2005 Nias earthquakes, GRACE data produce a shallower centroid depth (9.1 km) compared to the depth (28.3 km) from GPS data, which may be explained by the closer-to-trench centroid location and by the aseismic slip over the shallow region. For the 2011 Tohoku earthquake, the inversions from two different GRACE data products and two different forward modeling produce similar source characteristics, with the centroid location southwest of and the slip azimuth 10° larger than the GPS/seismic solutions. The GRACE-estimated dip angles are larger than that from GPS/seismic data for the 2004 Sumatra-Andaman and 2005 Nias earthquakes, the 2010 Maule, Chile earthquake, and the 2007 Bengkulu earthquake. These differences potentially show the additional offshore constraint from GRACE data, compared to GPS/seismic data. With more accurate and higher spatial resolution measurements anticipated from the GRACE Follow-on mission, with a scheduled launch date in 2017, we anticipate the data will be sensitive to even smaller earthquake signals. Therefore, GRACE type observations will hopefully become a more viable measurement to further constrain earthquake focal mechanisms

Deep Learning Models for River Classification at Sub-Meter Resolutions from Multispectral and Panchromatic Commercial Satellite Imagery

Remote sensing of the Earth's surface water is critical in a wide range of environmental studies, from evaluating the societal impacts of seasonal droughts and floods to the large-scale implications of climate change. Consequently, a large literature exists on the classification of water from satellite imagery. Yet, previous methods have been limited by 1) the spatial resolution of public satellite imagery, 2) classification schemes that operate at the pixel level, and 3) the need for multiple spectral bands. We advance the state-of-the-art by 1) using commercial imagery with panchromatic and multispectral resolutions of 30 cm and 1.2 m, respectively, 2) developing multiple fully convolutional neural networks (FCN) that can learn the morphological features of water bodies in addition to their spectral properties, and 3) FCN that can classify water even from panchromatic imagery. This study focuses on rivers in the Arctic, using images from the Quickbird, WorldView, and GeoEye satellites. Because no training data are available at such high resolutions, we construct those manually. First, we use the RGB, and NIR bands of the 8-band multispectral sensors. Those trained models all achieve excellent precision and recall over 90% on validation data, aided by on-the-fly preprocessing of the training data specific to satellite imagery. In a novel approach, we then use results from the multispectral model to generate training data for FCN that only require panchromatic imagery, of which considerably more is available. Despite the smaller feature space, these models still achieve a precision and recall of over 85%. We provide our open-source codes and trained model parameters to the remote sensing community, which paves the way to a wide range of environmental hydrology applications at vastly superior accuracies and 2 orders of magnitude higher spatial resolution than previously possible.Comment: 21 pages, 10 figures, 3 table

The 28 November 2020 landslide, tsunami, and outburst flood – a hazard cascade associated with rapid deglaciation at Elliot Creek, British Columbia, Canada

We describe and model the evolution of a recent landslide, tsunami, outburst flood, and sediment plume in the southern Coast Mountains, British Columbia, Canada. On November 28, 2020, about 18 million m3 of rock descended 1,000 m from a steep valley wall and traveled across the toe of a glacier before entering a 0.6 km2 glacier lake and producing >100-m high run-up. Water overtopped the lake outlet and scoured a 10-km long channel before depositing debris on a 2-km2 fan below the lake outlet. Floodwater, organic debris, and fine sediment entered a fjord where it produced a 60+km long sediment plume and altered turbidity, water temperature, and water chemistry for weeks. The outburst flood destroyed forest and salmon spawning habitat. Physically based models of the landslide, tsunami, and flood provide real-time simulations of the event and can improve understanding of similar hazard cascades and the risk they pose

A Study on the Susceptibility to SCC of 7050 Aluminum Alloy by DCB Specimens

The stress corrosion cracking (SCC) of different aging states for 7050 aluminum alloy in 3.5% sodium chloride aqueous solution has been studied by means of double cantilever beam (DCB) specimens, cathodic polarization, scanning electron microscope (SEM), transmission electron microscope (TEM) and time-of-flying second ion mass spectrometer (ToF-SIMS). The results showed that the susceptibility to SCC (Iscc) of 7050 aluminum alloy decreases with increasing the aging time. When a cathodic polarization potential of −1100 mV was applied to DCB specimens, the ion current intensity of hydrogen (IH+) near the crack tip and Iscc increased obviously, thus the degree of the diffusion of hydrogen into the grain boundary become more serious. The observation of microstructure indicated that the precipitates on the grain boundary become coarse and are sparsely distributed with increasing the aging time of 7050 aluminum alloy

SUMOylation of SMAD4 by PIAS1 in Conjunction with Vimentin Upregulation Promotes Migration Potential in Non-Small Cell Lung Cancer

Background: The expression of vimentin as a marker of epithelial-to-mesenchymal transition (EMT) has been speculated to be associated with tissue heterogeneity and metastases of non-small cell lung cancer (NSCLC). Methods: This study utilized in vitro co-immunoprecipitation with small interfering RNAs (siRNAs) against protein inhibitors of STAT system type 1 (PIAS1) or SMAD4 in transforming growth factor-beta (TGF-β) signaling pathway in combination with SUMOylation assay. Results: We successfully demonstrated that PIAS1 enhanced SUMOylation of SMAD4 by forming a complex PIAS1-SUMO1-SMAD4 protein complex. This, in accordance with subsequently increased production of vimentin microfilaments, led to enhanced migration ability of non-small cell lung cancer (NSCLC) A549 line, observed from wound healing assay. Conclusions: Our results further supported the positive correlation of SUMOylated SMAD4 mediated by PIAS1 and downstream overexpression of vimentin. In addition, the observation that overexpression of vimentin in this certain cell line was not necessarily linked with accelerated relative wound closure raised concerns that further exploration will be needed to confirm if the causal relationship exists between vimentin expression and the metastases of NSCLC, and if so, to what extent vimentin contributes to it