Practical Earthquake Forecasting – What is it and how is it implemented?

Editors' Vox is a blog from the AGU Publishing Department.

Our understanding of earthquakes has improved greatly over the past few decades, but their exact location, timing, and magnitude are still not predictable. However, by using the sequence of past earthquakes as a guide, scientists can assess the likelihood of future earthquakes.

A new article in Reviews of Geophysics looks at operational earthquake prediction (OEF) systems around the world and how they are being used to inform decision-making. We asked the lead author to give us an overview of OEF systems, what experts are saying about them, and where they need improvement.

Simply put, what is Operational Earthquake Forecasting (OEF)?

In operational earthquake forecasting, a certified entity calculates the probability of earthquakes occurring within a specified area and time frame.

In operational earthquake forecasting, a certified entity calculates the probability of earthquakes occurring in a specific area and time frame. These probabilities are calculated based on current earthquake activity and are shared with civil protection, government agencies, or the public to help them make informed decisions.

It is important to distinguish between earthquake prediction and forecasting. It is not possible to predict the exact location, time, and magnitude of future earthquakes. However, the occurrence patterns observed in previous earthquake sequences can be used to say something about what is expected in an ongoing earthquake sequence. The most important components of earthquake prediction models are knowledge of the clustering behavior of earthquakes in space and time, and of the frequency distribution of earthquake magnitudes.

What are some examples of OEF systems around the world and how do they differ from each other?

There are not many countries currently implementing OEF systems. In our review, we discuss three examples: the OEF systems of Italy, New Zealand, and the United States. These three systems differ from each other in various ways, which we categorize into aspects related to the underlying models, how the models are tested, and how the predictions are communicated.

Each country uses different models of varying complexity, but the basic principles underlying the models are similar. Models have been evaluated using different types of tests, and using different test schemes. Communications about forecasts also vary widely. In Italy, forecasts are produced on a regular weekly basis, while New Zealand and the United States produce forecasts for specific sequences. The way probabilities are visualized or translated into actionable information ranges from interactive maps, tables and time series, to descriptions of the most and least likely future scenarios, to summary sheets containing a range of useful information.

Screenshot of the graphical interface of the OEF-Italy system. Left: Map of the current weekly probabilities of at least one earthquake with magnitude ML ≥ 4.0. Right: Timeline of the history of the probabilities in the rectangular area specified in central Italy (black box in the map). Copyright: Mizrahi et al. [2024]Figure 5

Why are there so few countries with OEF systems?

There are many factors that may prevent the creation of OpenF systems including insufficient data, knowledge gaps, resource constraints, or lack of required guidance.

There are many factors that may prevent the creation of OpenF systems including insufficient data, knowledge gaps, resource constraints, or lack of required guidance.

As demonstrated by the widely different open disaster assessment systems in Italy, New Zealand, and the United States, there is no clear agreed-upon default model to use, no agreed-upon tests that a model must pass in order to be considered suitable for earthquake prediction, and no single agreed-upon way to communicate earthquake predictions or earthquake loss forecasts.

For this reason, our review also includes an analysis of an expert opinion poll, in which a group of earthquake forecasting experts from around the world were asked their views on developing, testing, and communicating earthquake forecasts.

What general recommendations do experts make regarding the development, testing and communication of earthquake forecasts?

In general, the experts were somewhat reluctant to endorse specific models or tests. However, they noted that the Epidemic Aftershock Sequence (ETAS) model is a good default model. This model takes into account the fact that aftershocks from an earthquake can themselves produce aftershocks, etc., leading to a series of aftershocks. The group of experts considers this an important model feature. They also encourage combining several models into model ensembles.

Regarding model testing, experts encourage comparisons with comparable models, prospective testing (i.e. testing against future data that did not exist when the forecast was made), transparency, and reproducibility. Sharing model source code and archived forecasts for use by the community is desirable. Regarding forecast communication, experts agree that communication products should be developed in collaboration with forecast users.

Schematic of the Epidemic Aftershock Sequence (ETAS) model. (a) All earthquakes can produce aftershocks, and each can produce its own aftershocks, and so on. (b) The model describes the earthquake rate as the sum of background earthquakes (turquoise) plus sequences of aftershocks (black), which follow certain patterns in time, space, and magnitude. Copyright: Mizrahi et al. [2024]Figure 1

What are some of the key challenges and opportunities in improving practical earthquake prediction?

The models currently used in the OEF suffer from a common limitation: they fail to predict future large earthquakes with high probability. Recent efforts to enhance prediction capabilities include incorporating knowledge about physical processes into existing models, identifying early signals, leveraging insights from laboratory earthquakes, or applying machine learning techniques and new high-resolution datasets. However, it is not known whether deterministic earthquake prediction will ever be possible.

The Collaborative Center for Earthquake Predictability is dedicated to facilitating long-term open research in earthquake predictability. This includes providing open source software tools and reproducibility packages, as well as research that supports diversification of approaches used in future third-party testing of existing models. With regard to forecast communication, future efforts are needed to examine how to better communicate low-probability, high-impact events to societal stakeholders. This would support policymakers’ decision-making processes and individuals’ perceptions and reactions to forecasts.

—Leila Mizrahi ([email protected]; 0000-0002-5262-3168), Swiss Seismic Service, ETH Zurich, Switzerland

Citation: Mizrahi, L. (2024), Operational Earthquake Forecasting – what is it and how is it done?, Eos, 105, https://doi.org/10.1029/2024EO245024. Published 29 August 2024. This article does not represent the opinion of AGU, Eos, or any of its affiliates. It expresses only the opinion of the author(s). Text © 2024. The Authors. CC BY-NC-ND 3.0 Except where otherwise noted, images are subject to copyright. Any reuse without express permission of the copyright owner is prohibited.

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