Physics-Based Seismic Hazard and Risk Assessment: A New Paradigm for Earthquake Forecasting

TL;DR

This paper introduces SHARP, a physics-based framework for seismic hazard assessment that quantifies model inadequacy using the Model Adequacy Distance, aiming to improve the accuracy and reliability of earthquake forecasts.

Contribution

The paper proposes a novel framework, SHARP, which shifts focus from model selection to quantifying model inadequacy using MAD, integrating physics and observational data.

Findings

MAD effectively measures model inadequacy in seismic hazard models.

Application to Southern California seismicity demonstrates SHARP's practical utility.

Framework enhances understanding of uncertainties in earthquake risk assessment.

Abstract

Epistemic uncertainty in probabilistic seismic hazard assessment (PSHA) is commonly addressed through a logic-tree framework that combines weighted alternative models to characterize the range of plausible hazard outcomes. Implicit in this approach is a critical assumption: that the available model class provides an adequate representation of the underlying physics governing fault networks. Yet current formulations remain highly simplified, neglecting nonlinear interactions, diverse fault slip modes, multi-scale coupling, and the emergent dynamics that govern the nucleation and evolution of large earthquakes. As a result, the standard treatment of epistemic uncertainty may introduce systematic hazard bias and substantially underestimate forecast uncertainty. To formalize this limitation, we introduce SHARP (Seismic Hazard Assessment and Risks with Physics), a new framework that shifts the focus from selecting among imperfect models to quantifying their collective distance from physical and observational constraints. Central to SHARP is the Model Adequacy Distance (MAD), a quantitative metric of model inadequacy. MAD combines (i) a moment-weighted scoring function scaling with seismic moment to reflect the disproportionate social and economic impact of large events and (ii) compatibility measures derived from geodetic observations and statistical properties of seismicity. We illustrate the approach with an application to the frequency-magnitude distribution of Southern California seismicity. SHARP establishes a rigorous foundation for moving beyond conventional epistemic uncertainty toward a physics-grounded framework for seismic hazard and risk assessment.