Developing the First Intensity Prediction Equation Based on the Environmental Scale Intensity

Developing the First Intensity Prediction Equation Based on the Environmental Scale Intensity

29/06/2020 Perigeo 0
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The Perigeo research group is excited for the second paper published in one week! In this paper, we analyze earthquake effects through the ESI (Environmental Seismic Intensity) scale for 14 events in the Central and Southern Apennines… this is one of the strong points of the group, so no surprise at all!

We develop an intensity prediction equation (IPE), which computes the decay of ESI intensity with distance. IPEs are widely adopted for traditional intensity scales (MCS, MM…) and tons of IPEs are available for many regions in the world; but this is the first time ever that an IPE was developed for the ESI intensity!

Before developing an IPE, we assessed if ESI intensity is reliable when analyzing different events; thus, we compare the well-established MCS intensity with the ESI one (Figure 1). We plot MCS and ESI data points as a function of distance and compared the intensity decay: results are strikingly stable because for 12 out of the 14 analyzed events, ESI intensity decreases more rapidly than MCS. The intensity expected at the epicenter (intercept of the attenuation regression, see right side of Figure 1) is higher for ESI than for MCS.

Figure 1: Macroseismic Data Points (left) and median values (right) for the MCS and ESI intensities. The Irpinia 1930 and L’Aquila 2009 events are shown.

In order to compare different events and develop the IPE, we introduced ΔI, that is the difference between epicentral intensity, and the intensity recorded at each macroseismic data point. We selected a log-linear functional form and obtained the following values:

Figure 2: ESI Macroseismic Data Points, median values derived from the intensity binning and the proposed intensity prediction equation.

A good IPE should be stable through time, that is events with similar characteristics occurred decades or centuries apart should show the same attenuation. Since our dataset comprises events occurred between 1688 and 2016, we checked if MCS and ESI satisfy this requisite. This time data was binned according to distance and we obtain the results summarized in Figure 3.

All the events occurred before 2000 show a similar MCS attenuation; this is nothing new, because available IPEs developed from the MCS dataset already analyzed this issue. But we found a surprise for XXI century events!

All the 3 events later than 2000 (L’Aquila 2009, Amatrice 2016 and Norcia 2016) have a clearly distinct attenuation (Figure 3a); we argue that the most reasonable cause is a decrease in the vulnerability of the built environment in the past 20 yr. This result suggests that caution should be exerted when comparing modern (and future earthquakes, in perspective) to historical and early instrumental ones. Such time-dependent bias casts doubt on the appropriateness of processing the recent events in the same manner as the older ones and whether to integrate both in the next generation of IPEs.

On the contrary, the ESI scale shows a consistent behavior through time, suggesting that earthquake environmental effects are reliable indicators even when analyzing events occurred in different periods.

Figure 3: ΔI as a function of hypocentral distance for the (a) MCS and (b) ESI datasets. Events are coded according to the period of occurrence (twenty-first century vs. previous events).


Ferrario, M. F., F. Livio, S. S. Capizzano, and A. M. Michetti (2020). Developing the First Intensity Prediction Equation Based on the Environmental Scale Intensity: A Case Study from Strong Normal-Faulting Earthquakes in the Italian Apennines, Seismol. Res. Lett. XX, 1–13, doi: 10.1785/0220200044.

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