Group B, Poster #160, Earthquake Forecasting and Predictability (EFP)

Developing, testing and communicating earthquake forecasts: an expert elicitation for good practice recommendations

Leila Mizrahi, Irina Dallo, Lorena D. Kuratle, Annemarie Christophersen, Nicholas J. van der Elst, Maximilian J. Werner, Ilaria Spassiani, Giuseppe Falcone, Marcus Herrmann, Max Schneider, Morgan T. Page, Pablo C. Iturrieta, Matthew C. Gerstenberger, José A. Bayona, Warner Marzocchi, iunio iervolino, & Stefan Wiemer
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Poster Presentation

2023 SCEC Annual Meeting, Poster #160, SCEC Contribution #13156 VIEW PDF
Earthquakes occur in clusters, that is, they tend to concentrate in time and space. Damaging events are typically followed by aftershocks, which can cause or aggravate losses. Operational earthquake forecasting (OEF) systems aim to provide a probabilistic assessment of earthquake occurrence in near-real time, enabling informed decision-making for civil protection, authorities, the public, or other user groups. Only few agencies worldwide have systems in place which fall under this OEF definition, which could be attributed to factors such as insufficient data, knowledge gaps, resource constraints, or a lack of guidance required for their establishment.

To address the latter, we...
conducted an elicitation of expert views, aiming to provide good practice recommendations for the development, testing and communication of earthquake forecasts. We applied the Delphi method – with two surveys and one workshop – to identify consensus and dissent on these issues among a group of 20 international earthquake forecasting experts.

We found agreement among the expert group that earthquake forecast communication products should be developed together with the intended users. However, there was disagreement on whether the forecasting models themselves and how they are tested should be user-dependent. No recommendations of strict model requirements could be elicited, but benchmark comparisons, prospective testing, reproducibility, and transparency are encouraged.