Browsing University of Alaska Fairbanks by Subject "Strike-slip faults (Geology)"
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Modeling the coseismic and postseismic deformation of the 2002 Mw7.9 Denali, AK earthquakeThe 2002 Mw7.9 Denali fault earthquake was among the largest intraplate earthquakes on record, and the ongoing crustal deformation of the event is still observed today. Understanding the deformation patterns in the years following the earthquake can give insight into the viscoelastic properties of the crust and upper mantle. Additionally, an accurate and predictive model of this deformation is essential to developing and increasingly complete tectonic model of Alaska. Using primarily GPS measurements, deformation can be measured to millimeter-level precision. To develop a coseismic and postseismic model of the earthquake, 224 GPS coseismic displacement measurements (along with SAR and geologic measurements from past studies) are inverted for fault slip distribution. Coseismic slip and consequent stress changes drive the forward postseismic deformation model, which is constrained by 119 postseismic GPS time series. Both models use a 1D elastic structure. The preferred 1D coseismic model fits the coseismic data with a weighted residual sum of squares (WRSS) of 4.86e3 m², with more deep slip than a homogeneous model and a geodetic moment of 8.92e20 N m (Mw 7.97). The Maxwell viscoelastic parameters used for the first postseismic model run are 3e19 Pa s for the lower crust; 5e18 Pa s for the viscoelastic shear zone; and 10e19 and 10e20 south and north of the fault, respectively, for the asthenosphere. The respective Kelvin parameters are all an order of magnitude less. The deep coseismic slip (a product of the 1D elastic model) eliminates the need to add deep slip, which was done in past studies. Based on time series analysis, the decade-plus of data will certainly improve the model prediction relative to previous models, but future observations will be needed to verify this. No preferred postseismic model is developed, and more postseismic models will be run to better fit the observations.