In probabilistic seismic hazard analysis (PSHA), the standard practice is to select a set of appropriate GMPEs and assign weights on the logic tree, especially for regions where strong motion data are sparse and where no indigenous GMPE exists. Subjectively assigning weights to a set of models usually has the disadvantage of not obtaining mutually exclusive and collectively exhaustive models because of sparse or unavailable data. Therefore, the development of logic tree weightings in PSHA remains a major challenge. The objective of this thesis is to develop GMC models that capture the center body and range (CBR) of the technically defensible interpretation (TDI) of ground motion model distribution with their weighting for use in PSHA studies under the framework of SSHAC level 3 project. This study focuses on the development GMPE either for crustal source or subduction source and the development of the median weight on the logic tree for PHSA in Taiwan.
In probabilistic seismic hazard analysis (PSHA), the standard practice is to select a set of appropriate GMPEs and assign weights on the logic tree, especially for regions where strong motion data are sparse and where no indigenous GMPE exists. Subjectively assigning weights to a set of models usually has the disadvantage of not obtaining mutually exclusive and collectively exhaustive models because of sparse or unavailable data. Therefore, the development of logic tree weightings in PSHA remains a major challenge. The objective of this thesis is to develop GMC models that capture the center body and range (CBR) of the technically defensible interpretation (TDI) of ground motion model distribution with their weighting for use in PSHA studies under the framework of SSHAC level 3 project. This study focuses on the development GMPE either for crustal source or subduction source and the development of the median weight on the logic tree for PHSA in Taiwan.