Graduate Thesis Or Dissertation

 

Probabilistic Geospatial Analyses, Uncertainty Modeling, and Mapping of Seismically-induced Ground Failures Public Deposited

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  • Ground failures, in particular landsliding, liquefaction and lateral spreading can be triggered by seismic sources. The frequency, magnitude, and impact of these ground failures are highly dependent on the topography and geology of the site including its slope, depositional environment, and geotechnical properties as well as the proximity of the site to seismic sources. Many available models for estimating these variables have high epistemic uncertainty given the extreme challenge to fully characterize seismic sources and subsurface conditions. Nevertheless, this high uncertainty must be considered when mapping ground failure hazards for a large area using geologic, geotechnical, topographical, and seismic hazard data of limited availability.Many hazard maps do not fully consider uncertainty from the seismic sources, subsurface testing, and empirical models developed for estimating ground failures. Often, previously developed maps are qualitative based on judgment due to the lack of detailed subsurface geotechnical investigations.This research presents new mapping methods to address these challenges, resulting in ground failure hazard maps for evaluation and risk assessment. It explores both deterministic and probabilistic methods of mapping ground failure hazards for large study areas. Available geospatial data are incorporated in this research including digital elevation models (DEMs) acquired from lidar and photogrammetric data, DEM derivatives such as slope, geologic mapping, shear wave velocity tests and other geotechnical subsurface investigations, and seismic hazard curves.First, efficient algorithms were developed to map estimates of the peak ground acceleration, landslide and liquefaction triggering probability, and horizontal displacement as a result of landslides or lateral spreading across the state of Oregon for several earthquake scenarios associated with the Cascadia Subduction Zone (CSZ). These algorithms utilize site classification and site geology maps provided by the Oregon Department of Geology and Mineral Industries (DOGAMI).Second, a performance-based, landslide-induced, displacement hazard mapping technique is proposed and implemented for Western Oregon. This approach computes landslide displacement hazard curves across the regional area. The approach utilizes a detailed landslide inventory database and high-resolution topographical data to estimate the soil strength and associated uncertainty in the general geologic units. Third, in an effort to characterize the uncertainty of the geotechnical properties of geologic units, a geospatial geotechnical database was developed and evaluated. In this evaluation, available geologic maps and geotechnical subsurface databases from three counties in the State of Utah were compiled. Then, several distributions of geotechnical properties for the general geologic units were developed, and these distributions enabled the determination of which geologic units were most susceptible to liquefaction and lateral spreading. A statistical approach was also developed to provide a framework for simplifying geologic units based on soil properties.Lastly, a new and fully probabilistic framework is developed for mapping the liquefaction-induced lateral spread displacement hazard at a regional scale. This framework is demonstrated by producing lateral spread hazard maps for Utah County, Utah. By performing numerous Monte Carlo simulations, the method accounts for uncertainties in the soil properties, seismic loading, and the empirical models for predicting horizontal displacements due to lateral spreading.
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  • description.provenance : Submitted by Mahyar Sharifi Mood (sharifim@oregonstate.edu) on 2017-06-16T21:39:39ZNo. of bitstreams: 2license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5)SharifimoodMahyar2017.pdf: 12728930 bytes, checksum: 433adc160fdcdc432f1df313b1dff005 (MD5)
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