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by the activity on another fault in a different tectonic province. On the other hand, the
Gaussian model will have a more regular distribution with a smaller standard deviation,
and would be more applicable to a single fault zone. Also, for a model that requires a
standard deviation close to its mean, a Poisson model may be be more useful, whereas
the Gaussian or time–dependent model will apply more readily in the case of a standard
deviation significantly less than the mean.
Figure 3.1 shows expected probabilities of major earthquakes on the San Andreas
Fault in California. It is worth recalling that a relatively small earthquake with a mag-nitude
of about 6 was predicted in the 1980s to occur near Parkfield by 1993 with a
95% probability. It did not occur until 2004, 11 years later with respect to its date of
maximum likelihood in its alleged 22 year cycle (Harris and Arrowsmith, 2006).
3.3 Probabilistic Tsunami Studies
Wiegel (1970) and Ritter and Dupre (1972) appear to be the first published studies
in probabilistic tsunami estimates. Wiegel (1970) prepared a frequency of occurrence
graph using the observed runup data from five big earthquakes: 1946, 1952, 1957, 1960
and 1964. His work included Crescent City and San Francisco Bay. However, the San
Francisco figure did not present any results beyond a runup of about 2m, and did not
have sufficient information for tsunami runup heights for return periods greater than 50
years. Ritter and Dupre (1972) extrapolated Wiegel’s San Francisco Bay curve. They
did not explain how their extrapolation was estimated. Figure 3.2 shows their results.
Geist and Parsons (2005) reviewed the existing probabilistic studies on tsunami haz-ards.
They described how Soloviev and Go (1969) introduced a probabilistic frequency
118
Object Description
| Title | Deterministic and probabilistic tsunami studies in California from near and farfield sources |
| Author | Uslu, Burak |
| Author email | uslu@usc.edu; burak.uslu@noaa.gov |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Civil Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2007-09-21 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-30 |
| Advisor (committee chair) | Synolakis, Costas E. |
| Advisor (committee member) |
Bardet, Jean-Pierre Okal, Emile A. Moore, James Elliott, II |
| Abstract | California is vulnerable to tsunamis from both local and distant sources. While there is an overall awareness of the threat, tsunamis are infrequent events and few communities have a good understanding of vulnerability. To quantitatively evaluate the tsunami hazard in the State, deterministic and probabilistic methods are used to compute inundation and runup heights in selected population centers along the coast.; For the numerical modeling of tsunamis, a two dimensional finite difference propagation and runup model is used. All known near and farfield sources of relevance to California are considered. For the farfield hazard analysis, the Pacific Rim is subdivided into small segments where unit ruptures are assumed, then the transpacific propagations are calculated. The historical records from the 1952 Kamchatka, 1960 Great Chile, 1964 Great Alaska, and 1994 and 2006 Kuril Islands earthquakes are compared to modeled results. A sensitivity analysis is performed on each subduction zone segment to determine the relative effect of the source location on wave heights off the California Coast.; Here, both time-dependent and time-independent methods are used to assess the tsunami risk. In the latter, slip rates are obtained from GPS measurements of the tectonic motions and then used as a basis to estimate the return period of possible earthquakes. The return periods of tsunamis resulting from these events are combined with computed waveheight estimates to provide a total probability of exceedance of given waveheights for ports and harbors in California. The time independent method follows the practice of past studies that have used Gutenberg and Richter type relationships to assign probabilities to specific tsunami sources.; The Cascadia Subduction Zone is the biggest nearfield earthquake source and is capable of producing mega-thrust earthquake ruptures between the Gorda and North American plates and may cause extensive damage north of Cape Mendocino, to Seattle. The present analysis suggests that San Francisco Bay and Central California are most sensitive to tsunamis originating from the Alaska and Aleutians Subduction Zone (AASZ). An earthquake with a magnitude comparable to the 1964 Great Alaska Earthquake on central AASZ could result in twice the wave height as experienced in San Francisco Bay in 1964.; The probabilistic approach shows that Central California and San Francisco Bay have more frequent tsunamis from the AASZ, while Southern California can be impacted from tsunamis generated on Chile and Central American Subduction Zone as well as the AASZ. |
| Keyword | assessment; California; hazard; model; probability; tsunami |
| Geographic subject | capes: Kamchatka; islands: Kuril Islands; fault zones: Cascadia Subduction Zone |
| Geographic subject (state) | California; Alaska |
| Geographic subject (country) | Chile |
| Coverage date | 1952/2008 |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1706 |
| Contributing entity | University of Southern California |
| Rights | Uslu, Burak |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-uslu-2434 |
| Archival file | uscthesesreloadpub_Volume40/etd-uslu-2434.pdf |
Description
| Title | Page 133 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | by the activity on another fault in a different tectonic province. On the other hand, the Gaussian model will have a more regular distribution with a smaller standard deviation, and would be more applicable to a single fault zone. Also, for a model that requires a standard deviation close to its mean, a Poisson model may be be more useful, whereas the Gaussian or time–dependent model will apply more readily in the case of a standard deviation significantly less than the mean. Figure 3.1 shows expected probabilities of major earthquakes on the San Andreas Fault in California. It is worth recalling that a relatively small earthquake with a mag-nitude of about 6 was predicted in the 1980s to occur near Parkfield by 1993 with a 95% probability. It did not occur until 2004, 11 years later with respect to its date of maximum likelihood in its alleged 22 year cycle (Harris and Arrowsmith, 2006). 3.3 Probabilistic Tsunami Studies Wiegel (1970) and Ritter and Dupre (1972) appear to be the first published studies in probabilistic tsunami estimates. Wiegel (1970) prepared a frequency of occurrence graph using the observed runup data from five big earthquakes: 1946, 1952, 1957, 1960 and 1964. His work included Crescent City and San Francisco Bay. However, the San Francisco figure did not present any results beyond a runup of about 2m, and did not have sufficient information for tsunami runup heights for return periods greater than 50 years. Ritter and Dupre (1972) extrapolated Wiegel’s San Francisco Bay curve. They did not explain how their extrapolation was estimated. Figure 3.2 shows their results. Geist and Parsons (2005) reviewed the existing probabilistic studies on tsunami haz-ards. They described how Soloviev and Go (1969) introduced a probabilistic frequency 118 |
