Handling Uncertainty in Models of Seismic and Postseismic Hazards: Toward Robust Methods and Resilient Societies

Earthquakes, tsunamis, and landslides take a devastating toll on human lives, critical infrastructure, and ecosystems. Harnessing the predictive capacities of hazard models is key to transitioning from reactive approaches to disaster management toward building resilient societies, yet the knowledge that these models produce involves multiple uncertainties. The failure to properly account for these uncertainties has at times had important implications, from the flawed safety measures at the Fukushima power plant, to the reliance on short-term earthquake prediction models (reportedly at the expense of mitigation efforts) in modern China. This article provides an overview of methods for handling uncertainty in probabilistic seismic hazard assessment, tsunami hazard analysis, and debris flow modeling, considering best practices and areas for improvement. It covers sensitivity analysis, structured approaches to expert elicitation, methods for characterizing structural uncertainty (e.g., ensembles and logic trees), and the value of formal decision-analytic frameworks even in situations of deep uncertainty.