Earthquake Cycle Effects in the Eastern California Shear Zone
G. Schmalze and T. Dixon
We use the 3 dimensional finite element program G-TECTON to study earthquake cycle effects in the Eastern California Shear zone (ECSZ). The model shown below encompasses the major faults in the region: the San Andreas (SAF), Owens Valley (OV), Panamint Valley (PV) and Death Valley faults (DV). Also included in this model are the Deep Springs (DS) and Eureka (EU) faults. The faults separate major tectonic blocks known as the Basin and Range and Sierra Nevada Blocks and the Pacific plate. The model includes an elastic layer that is coupled, or welded, to the underlying viscoelastic layer. We compare GPS data that has been processed at the University of Miami Geodesy Lab to the model, and interpret fault rate, earthquake recurrence, and other fault and material properties. Studies such as this one are important in determining seismic hazard.
Figure 16: Panel A displays the initial conditions of the model. Red arrows represent boundary conditions and point in the fixed model directions. For example, the bottom of the model cannot move vertically, so the red arrows point up. The green arrow represents the direction of overall plate motion. Panel B is an example result of the velocity field for this model. Warmer colors represent faster rates. Surface fault traces for both figures are displayed as black lines.
Studying Volcanoes and Earthquakes using Interferometric Synthetic Aperture Radar (InSAR)
S. Baker and F. Amelung
We study active volcanoes and earthquakes using a remote sensing technique called Interferometric Synthetic Aperture Radar (InSAR). In this technique multiple satellite radar images (from the same area on the Earth) are combined to precisely measure surface displacements, such as due to subsurface magma migration and fault movements. At volcanoes, interpretation of the detected deformation in terms of magma chamber models and magma pathways leads to a better understanding of how, when, and why volcanoes erupt. The measurement accuracy increases with the number of available satellite images. The simultaneous analysis of many radar images (for some volcanoes we have more than 100 images) is computationally very challenging. Inflation of Mauna Loa volcano, Hawaii, during 2002-2005 measured with satellite radar interferometry is shown in Figure 17
Figure 17: Inflation of Mauna Loa volcano, Hawaii, during 2002-2005 measured with satellite radar interferometry. One color cycle corresponds to 3 cm change in distance between the Earth’s surface and the satellite. The image shows that up to 20 cm ground deformation occurred during this time period, caused by the intrusion of new magma into the volcanoes’ interior. Credit: Scott Baker and Falk Amelung.