Long‐Term Time‐Dependent Probabilities for the Third Uniform California Earthquake Rupture Forecast (UCERF3) 论文

摘要

The 2014 Working Group on California Earthquake Probabilities (WGCEP 2014) presents time-dependent earthquake probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3). Building on the UCERF3 time-in- dependent model published previously, renewal models are utilized to represent elastic- rebound-implied probabilities. A new methodology has been developed that solves applicability issues in the previous approach for unsegmented models. The new meth- odology also supports magnitude-dependent aperiodicity and accounts for the historic open interval on faults that lack a date-of-last-event constraint. Epistemic uncertainties are represented with a logic tree, producing 5760 different forecasts. Results for a variety of evaluation metrics are presented, including logic-tree sensitivity analyses and comparisons to the previous model (UCERF2). For 30 yr M ! 6:7 probabilities, the most significant changes from UCERF2 are a threefold increase on the Calaveras fault and a threefold decrease on the San Jacinto fault. Such changes are due mostly to differences in the time-independent models (e.g., fault-slip rates), with relaxation of segmentation and inclusion of multifault ruptures being particularly influential. In fact, some UCERF2 faults were simply too long to produce M 6.7 size events given the segmentation assumptions in that study. Probability model differences are also influential, with the implied gains (relative to a Poisson model) being generally higher in UCERF3. Accounting for the historic open interval is one reason. Another is an effective 27% increase in the total elastic-rebound-model weight. The exact factors influencing differences between UCERF2 and UCERF3, as well as the relative im- portance of logic-tree branches, vary throughout the region and depend on the evalu- ation metric of interest. For example, M ! 6:7 probabilities may not be a good proxy for other hazard or loss measures. This sensitivity, coupled with the approximate nature of the model and known limitations, means the applicability of UCERF3 should be evaluated on a case-by-case basis.