Abstract
This paper describes an efficient and systematic process for using geophysical computer model simulations to guide efforts in probabilistic hazard mapping. The framework being proposed requires the simultaneous construction of many ($10^2$--$10^4$) statistical emulators, e.g., cheap model surrogates. This paper describes an automation process for choosing designs for and fitting these emulators. Throughout the description of this process, several useful modifications to standard emulators are explored. Additionally, this approach enables a fast and flexible uncertainty quantification for multiple sources of aleatory variability (natural randomness) and epistemic uncertainty (uncertainty in geophysical and statistical models) in the context of probabilistic hazard mapping. This process is illustrated through an application to granular volcanic flows.
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