Experimental Concepts for Testing Seismic Hazard Models

Abstract:

Seismic hazard analysis is the primary interface through which useful information about earthquake rupture and wave propagation is delivered to society. To account for the randomness (aleatory variability) and limited knowledge (epistemic uncertainty) of these natural processes, seismologists must formulate and test hazard models using the concepts of probability. In this presentation, we will address the scientific objections that have been raised over the years against probabilistic seismic hazard analysis (PSHA). Owing to the paucity of observations, we must rely on expert opinion to quantify the epistemic uncertainties of PSHA models (e.g., in the weighting of individual models from logic-tree ensembles of plausible models). The main theoretical issue is a frequentist critique: subjectivity is immeasurable; ergo, PSHA models cannot be objectively tested against data; ergo, they are fundamentally unscientific. We have argued (PNAS, 111, 11973-11978) that the Bayesian subjectivity required for casting epistemic uncertainties can be bridged with the frequentist objectivity needed for pure significance testing through “experimental concepts.” An experimental concept specifies collections of data, observed and not yet observed, that are judged to be exchangeable (i.e., with a joint distribution independent of the data ordering) when conditioned on a set of explanatory variables. We illustrate, through concrete examples, experimental concepts useful in the testing of PSHA models for ontological errors in the presence of aleatory variability and epistemic uncertainty. In particular, we describe experimental concepts that lead to exchangeable binary sequences that are statistically independent but not identically distributed, showing how the Bayesian concept of exchangeability generalizes the frequentist concept of experimental repeatability. We also address the issue of testing PSHA models using spatially correlated data.