STATIC AND DYNAMIC STRESS CHANGE AT 27 VOLCANOES OF THE CENTRAL AMERICAN VOLCANIC ARC AFTER THE MW. 7.6 COSTA RICA EARTHQUAKE OF 5 SEPTEMBER 2012

Large earthquakes may strongly influence the activity of volcanoes through static and dynamic processes. In this study, we quantify the static and dynamic stress change on 27 volcanoes in Central America, after the Mw 7.6 Costa Rica earthquake of 5 September 2012. Following this event, 8 volcanoes showed signs of activity. We calculated the static stress change due to the earthquake on hypothetical faults under these volcanoes with Coulomb 3.3. For the dynamic stress change, we computed synthetic seismograms to simulate the waveforms at these volcanoes. We then calculated the Peak Dynamic Stress (PDS) from the modeled peak ground velocities. The resulting values are from moderate to minor changes in stress (10-1-10-2 MPa) with the PDS values generally an order of magnitude larger than the static stress change. Although these values are small, they may be enough to trigger a response by the volcanoes, and are on the order of stress changes implicated in many other studies of volcano and earthquake triggering by large earthquakes. This study provides insight into the poorly-constrained mechanism for remote triggering.

Triggering of volcanic activity by large earthquakes

Statistical analyses of temporal relationships between large earthquakes and volcanic eruptions suggest seismic waves may trigger eruptions even over great (>1000 km) distances, although the causative mechanism is not well constrained. In this study the relationship between large earthquakes and subtle changes in volcanic activity was investigated in order to gain greater insight into the relationship between dynamic stresses propagated by surface waves and volcanic response. Daily measurements from the Ozone Monitoring Instrument (OMI), onboard the Aura satellite, provide constraints on volcanic sulfur-dioxide (SO2) emission rates as a measure of subtle changes in activity. Time series of SO2 emission rates were produced from OMI data for thirteen persistently active volcanoes from 1 October 2004 to 30 September 2010. In order to quantify the affect of earthquakes at teleseismic distances, we modeled surface-wave amplitudes from the source mechanisms of moment magnitude (Mw) ≥7 earthquakes, and calculated the Peak Dynamic Stress (PDS). We assessed the influence of earthquakes on volcanic activity in two ways: 1) by identifying increases in the SO2 time series data and looking for causative earthquakes and 2) by examining the average emission rate before and after each earthquake. In the first, the SO2 time series for each volcano was used to calculate a baseline threshold for comparison with post-earthquake emission. Next, we generated a catalog of responses based on sustained SO2 emission increases above this baseline. Delay times between each SO2 response and each prior earthquake were analyzed using both the actual earthquake catalog, and a randomly generated catalog of earthquakes. This process was repeated for each volcano. Despite varying multiple parameters, this analysis did not demonstrate a clear relationship between earthquake-generated PDS and SO2 emission. However, the second analysis, which was based on the occurrence of large earthquakes indicated a response at most volcanoes. Using the PDS calculations as a filtering criterion for the earthquake catalog, the SO2 mass for each volcano was analyzed in 28-day windows centered on the earthquake origin time. If the average SO2 mass after the earthquake was greater than an arbitrary percentage of pre-earthquake mass, we identified the volcano as having a response to the event. This window analysis provided insight on what type of volcanic activity is more susceptible to triggering by dynamic stress. The volcanoes with very open systems included in this study, Ambrym, Gaua, Villarrica, Erta Ale and, Turrialba, showed a clear response to dynamic stress while the volcanoes with more closed systems, Merapi, Semeru, Fuego, Pacaya, and Bagana, showed no response.

EVALUATION OF THE EVOLVING STRESS FIELD OF THE YELLOWSTONE VOLCANIC PLATEAU FROM 1988 TO 2010 FROM EARTHQUAKE FIRST MOTIONS INVERSION

Within the Yellowstone National Park, Wyoming, the silicic Yellowstone volcanic field is one of the most active volcanic systems all over the world. Although the last rhyolite eruption occurred around 70,000 years ago, Yellowstone is still believed to be volcanically active, due to high hydrothermal and seismic activity. The earthquake data used in this study cover the period of time between 1988 and 2010. Earthquake relocations and a set of 369 well-constrained, double-couple, focal mechanism solutions were computed. Events were grouped according to location and time to investigate trends in faulting. The majority of the events has oblique, normal-faulting solutions. The overall direction of extension throughout the 0.64 Ma Yellowstone caldera looks nearly ENE, consistently with the direction of alignments of volcanic vents within the caldera, but detailed study revealed spatial and temporal variations. Stress-field solutions for different areas and time periods were calculated from earthquake focal mechanism inversion. A well-resolved rotation of σ3 was found, from NNE-SSW near the Hebgen Lake fault zone, to ENE-WSW near Norris Junction. In particular, the σ3 direction changed throughout the years in the Norris Junction area, from being ENE-WSW, as calculated in the study by Waite and Smith (2004), to NNE-SSW, while the other σ3 directions are mostly unchanged over time. The Yellowstone caldera was subject to periods of net uplift and subsidence over the past century, explained in previous studies as caused by expanding or contracting sills, at different depths. Based on the models used to explain these deformation periods, we investigated the relationship between variability in aseismic deformation and seismic activity and faulting styles. Focal mechanisms and P and T axes were divided into temporal and depth intervals, in order to identify spatial or temporal trends in deformation. The presence of “chocolate tablet” structures, with composite dilational faults, was identified in many stages of the deformation history both in the Norris Geyser Basin area and inside the caldera. Strike-slip component movement was found in a depth interval below a contracting sill, indicating the movement of magma towards the caldera.

Performance-Based Engineering Framework for Earthquake and Fire Following Earthquake

The objective for this thesis is to outline a Performance-Based Engineering (PBE) framework to address the multiple hazards of Earthquake (EQ) and subsequent Fire Following Earthquake (FFE). Currently, fire codes for the United States are largely empirical and prescriptive in nature. The reliance on prescriptive requirements makes quantifying sustained damage due to fire difficult. Additionally, the empirical standards have resulted from individual member or individual assembly furnace testing, which have been shown to differ greatly from full structural system behavior. The very nature of fire behavior (ignition, growth, suppression, and spread) is fundamentally difficult to quantify due to the inherent randomness present in each stage of fire development. The study of interactions between earthquake damage and fire behavior is also in its infancy with essentially no available empirical testing results. This thesis will present a literature review, a discussion, and critique of the state-of-the-art, and a summary of software currently being used to estimate loss due to EQ and FFE. A generalized PBE framework for EQ and subsequent FFE is presented along with a combined hazard probability to performance objective matrix and a table of variables necessary to fully implement the proposed framework. Future research requirements and summary are also provided with discussions of the difficulties inherent in adequately describing the multiple hazards of EQ and FFE.

DOING MORE WITH SHORT PERIOD DATA: DETERMINING MAGNITUDES FROM CLIPPED AND OVER-RUN SEISMIC DATA AT MOUNT ST. HELENS

How can we calculate earthquake magnitudes when the signal is clipped and over-run? When a volcano is very active, the seismic record may saturate (i.e., the full amplitude of the signal is not recorded) or be over-run (i.e., the end of one event is covered by the start of a new event). The duration, and sometimes the amplitude, of an earthquake signal are necessary for determining event magnitudes; thus, it may be impossible to calculate earthquake magnitudes when a volcano is very active. This problem is most likely to occur at volcanoes with limited networks of short period seismometers. This study outlines two methods for calculating earthquake magnitudes when events are clipped and over-run. The first method entails modeling the shape of earthquake codas as a power law function and extrapolating duration from the decay of the function. The second method draws relations between clipped duration (i.e., the length of time a signal is clipped) and the full duration. These methods allow for magnitudes to be determined within 0.2 to 0.4 units of magnitude. This error is within the range of analyst hand-picks and is within the acceptable limits of uncertainty when quickly quantifying volcanic energy release during volcanic crises. Most importantly, these estimates can be made when data are clipped or over-run. These methods were developed with data from the initial stages of the 2004-2008 eruption at Mount St. Helens. Mount St. Helens is a well-studied volcano with many instruments placed at varying distances from the vent. This fact makes the 2004-2008 eruption a good place to calibrate and refine methodologies that can be applied to volcanoes with limited networks.