Messages about ‘severity’ of earthquakes via app can help early disaster management – ScienceDaily

After an earthquake, it is crucial in the early phase of disaster management to obtain a rapid assessment of the severity of the impact on the affected population in order to be able to initiate appropriate emergency measures. Often the first quick and good assessment of whether an earthquake is causing major or minor damage can be given after only 10 minutes with information from the affected persons about the ‘feeling’ of the earthquake. This appeared in a recent study by researchers led by Henning Lilienkamp and Fabrice Cotton of the German GFZ Research Center for Geosciences, which is now published in the journal The Seismic Record. In their new approach, they assess the information that people conveyed after an earthquake via a website or app for the Euro-Mediterranean Seismological Center’s recent earthquake service. Since no seismometric data is needed, this low-cost approach may help disaster management in the future, especially in areas where there are few seismographs.

BACKGROUND: Evaluation of earthquake impact

The ability to assess the impact of an earthquake as quickly as possible is essential for decision makers and disaster managers, as it directly affects the measures taken to protect lives and limit further damage.

In some cases, such as the series of catastrophic earthquakes that struck Turkey and Syria in February 2023, it is immediately apparent that a large-scale emergency response is urgently needed. But this is not always true.

“For example, in the 5.9-magnitude earthquake that struck remote areas of Afghanistan and Iran on June 12, 2022, and killed more than 1,000 people, it was not clear for hours whether or not significant impacts were expected, according to the Center. European Mediterranean Seismological Monitoring Center (EMSC), “explains Henning Lilienkamp, ​​PhD student in the Department of ‘Earthquake Hazards and Dynamic Hazards’ at the German GFZ Research Center for Geosciences and lead author of the current study.

There are rapid assessment systems such as PAGER, developed by the USGS. However, it currently takes an average of about 30 minutes to give very comprehensive estimates of the effects of an earthquake. It is based on the ShakeMap method, so it needs ground acceleration data and other seismic observations as well as reports from residents.

A new approach based exclusively on felt reports

“Many types of data can be included in an earthquake assessment and its immediate consequences, and differentiated analysis is critical to successful long-term disaster management,” Lillenkamp stresses. He and his colleagues have now been able to demonstrate that an initial but faster initial assessment is indeed possible based on information from only the affected population. In addition to Henning Lilienkamp and Fabrice Cotton, Head of the Department of “Earthquake Hazards and Dynamic Hazards” at the GFZ and Professor at the University of Potsdam, other researchers from the University of Potsdam, EMSC and the University of Bergamo took part in the study, which was published in the journal Seismic Record.

In their new approach, they use data on the “intensity of feeling” of the earthquake from the people affected. They relay their personal post-earthquake assessment based on a graph and commentary via the EMSC’s LastQuake service website or app. It was developed to warn people as soon as possible immediately after an earthquake. Already in the first ten minutes after the event, a large body of data may be available for evaluation, although this number of cycles depends on the strength of the earthquake and the level of participation of the population.

For example, for the February 6 earthquake sequence in Turkey, LastQuake collected about 6,500 reports of the first 7.8-magnitude quake and about 4,800 reports of the second 7.5-magnitude quake, according to Lilienkamp. For the first quake, it took about 4.5 minutes to collect 50 reports—the minimum required to run the model developed here—and after 10 minutes, 1,232 reports were already available.

“We were convinced that this database is too valuable to ignore in the long term, because it is collected so efficiently and on a global scale, including in regions that lack expensive seismographs,” says Lillenkamp.

Develop a model for rapid assessment of earthquake impacts

The researchers had access to more than 1.5 million globally collected reports on the perceived intensity of more than 10,000 earthquakes of any size from 2014 to 2021. Based on “crowdsourced data,” they developed a probabilistic model that can be used to estimate whether an earthquake is high impact or low.

For this purpose, in the first step, the perceived intensity data of previous earthquakes were converted into representative parameters, such as a ‘pseudo-intensity value’ that defines the extent of shaking. The other value describes the spatial extent of the area where the ground shaking was felt.

In a second step, associated earthquakes were classified using more detailed information from global earthquake impact databases. The study defines earthquakes with strong impacts as those associated with at least one of the following effects: a destroyed building, at least 50 damaged buildings, at least two documented deaths or financial losses.

Ultimately, this results in a statement about how likely an earthquake together with the “felt” information transmitted will have strong effects.

The first step can also be used to classify new earthquakes.

Endorsement and limitation of the new approach

The researchers then tested their model on eleven earthquakes from 2022. “One of the main strengths of our approach is that it is able very quickly to correctly and unambiguously assess a large number of low-impact events,” sums up Henning Lillenkomp.

In their paper, the researchers note that being able to identify an earthquake as low impact could provide some relief to the public, as these types of earthquakes – although not very strong – can still be felt and may cause anxiety as a result.

“We see with high-impact events that it remains a challenge to clearly distinguish them from lower-impact events as well,” says Lillenkamp. This may also be due to the fact that the underlying data set from which the model “learns” naturally has fewer severe earthquakes. The researchers estimate that with data collected over time, this could improve further.

A natural limitation of this approach – especially during strong earthquakes – is the lack of very early reports from the area where the shaking was most intense. “This effect is well known and represents the fact that people under such extreme conditions of course prioritize finding shelter and rescuing people in danger, rather than making physical reports on their smartphones,” Lillenkamp explains. Moreover, the global analysis shows that currently LastQuake is still used mostly in Europe (75 percent of the data comes from there).

“We view our method as a cost-effective addition to the suite of earthquake impact assessment tools that are completely independent of seismic data and can be used in many populated areas around the world. Although it remains an open task to further develop our method into a tool for practical use, we show the potential to support management disasters in areas that currently lack expensive seismic tools,” says Fabrice Cotton of the GFZ.

Prospects: application potential

Lillenkamp and colleagues suggest that their method could be used to develop a system of “traffic lights” based on affect scores, where green-level scores require no additional action by decision-makers, yellow will trigger further investigation, and red can trigger an alert.

“As seismologists, we need a better understanding of exactly how decision-makers and emergency services such as fire departments act in an emergency, what kind of information is useful, and in what high-impact possibilities they prefer to raise, accurately communicating the capabilities of our model and the individual needs of potential end-users,” Lillenkamp said. It will be key to the practical implementation of traffic light systems.”

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