@article{ref1,
title="Handling uncertainty in models of seismic and postseismic hazards: toward robust  methods and resilient societies",
journal="Risk analysis",
year="2020",
author="MacGillivray, Brian H.",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="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.<p /> <p>Language: en</p>",
language="en",
issn="0272-4332",
doi="10.1111/risa.13663",
url="http://dx.doi.org/10.1111/risa.13663"
}