The April 16, 2016M7.8 earthquake occurred at 23:58:37 (UTC), offshore of the west coast of northern Ecuador. The earthquake occurred near the plate boundary between the Nazca and Pacific plates on a shallow thrust faulting.


Figure 1: Location of EQ Epicenter and Dobrovolsky area.


The earthquake was preceded by a magnitude 4.8 foreshock eleven minutes before the occurrence of the mainshock.

At the location of the earthquake, the Nazca plate subducts eastward beneath the South America plate at a velocity of 61 mm/yr. The location and mechanism of the earthquake are consistent with slip on the primary plate boundary interface, or megathrust, between these two major plates. In this plate boundary occurred the 1960 M9.5 earthquake, the largest earthquake ever recorded in the world.






    1. Accelerated Moment Release (AMR) & Revised-AMR

The analysis of the USGS seismic catalogue was extended back in time of 10 years before the EQ  date. R-AMR analysis confirms the findings that no acceleration preceded the main rupture.


Figure 2: Reduced Cumulative strain for 10-year data. It confirms that no acceleration preceded the mainshock.




Two different approaches were developed to search EQ precursor using geomagnetic Swarm data: MASS method and Wavelet method. Both analyses are based on Level 1B MAGxLR Swarm product.


  1. MASS algorithm (Magnetic Swarm anomaly detection by Spline analysis)

The algorithm MASS (Magnetic Swarm anomaly detection by Spline analysis) was applied to M7.8Ecuador 2016 earthquake with different thresholds, while the moving window was fixed at 3.0°. The algorithm analyses all tracks in DbA (Dobrovolsky Area) one month before and one after the EQ. The tracks are marked as “anomaly” only if the center of the moving window is in DbA and if geomagnetic conditions are quiet. Figure 3 shows an example of anomalous tracks detected by MASS method for Ecuador EQ.


Figure 3:Example of anomalous track in Y magnetic component (Satellite A- March 27, 2016).

The cumulative number of anomalies detected by MASS one month before and afterEcuador 2016 EQ (threshold  kt= 3.0) is shown in Figure 4. It is interesting to note that the graph of the cumulative number of anomaly windows of Y component presents an acceleration about 7 days before the EQ.



Figure 4: Cumulative number of anomaly detected by MASS one month before and one month after the Ecuador EQ. Threshold is kt = 3 and the anomalies are selected only with geomagnetic quiet time (|Dst| ≤ 20 nT and ap≤ 10 nT).



  1. Wavelet Analysis


The Wavelet spectral analysis has evidenced the existence of different anomalous families, each characterized by some particular features.

Figure 5 shows a family of anomaly already encountered in the same region (i.e. for the case study of Chile 2014, M8.2) characterized by the symmetric structure around the magnetic equator.


Figure 5:The figure shows a kind of anomaly already encountered in the same region (i.e. for Chile 2014, M8.2): it appears as a couple of wave packets symmetric with respect to the magnetic equator.


On the day of the mainshock (Figure 6) an anomaly arises in the upper part of the two adjacent tracks: a long-term signal emerging from the background and persisting for at least 1 hour and a half. In addition, the next Figure 7 shows about the same anomaly emerging from data on different days and in the same latitudes. This means that it is probably a characteristic feature of that sector of the ionosphere.

Thus, even in this case, the discrimination of the source of emerging signals from the background by applying this method alone may need the adoption of some other more complex scheme.



Figure 6: On the day when the mainshock stroke, some anomalies emerge from data involving the upper part of the track.


Figure 7: An anomaly resembling that on the day of the mainshock affects data on different days.


  1. SWARM – IONOSPHERE from Satellite

Satellite-based data for the ionospheric characterization of the EQ-related events are mainly those referred to the LP (Langmuir Probe) instrument aboard the SWARM satellites. The electron density Ne is the relevant parameter used for the ionospheric characterization in the frame of SAFE project. Two different methods were developed to analyze Swarm ionospheric data: NeSTAD and NeLOG.


  1. Method I: NeSTAD

No tagged anomalies were found for this event by means of the tagging criteria applied on the NeSTAD anomaly parameters.


  1. Method II: NeLOG

The automatic search NeLOG of ionosphere electron density anomaly from Swarm data is applied to Ecuador  case study.A sample is classified as anomaly if the residual value exceeds a threshold kt times the RMS of the residual after the polynomial fit (in this case kt=3.0). A track is selected as an “anomaly” if it has more than 10 anomaly samples in DbA and if geomagnetic indices are |Dst|<20 nT and ap<10 nT. Tracks are selected within a mean local time between 22 and 6.



Figure 8: Anomaly detected by NeLOG (satellite Bravo, 16 April 2015) few hours before the M7.8 Ecuador EQ.

Figure 8 shows an example of anomaly track in the date of the mainshock, while Figure 9 reports the cumulative number of anomaly windows detected by NeLOG. It interesting that around EQ it is possible to distinguish a sigmoid shape. Unfortunately all these anomalies are revealed by Bravo satellite (Bravo is located at an higher altitude). Despite the C factor is normalized, for NeLOG it is not possible in general make considerations about the 3 satellites as the selection is driven by their corresponding different local time coverage and less from physical conditions.


Figure9:Cumulative number of anomaly samples detected by NeLOG 1 month before and 1 month after the Ecuador EQ.).


  1. IONOSPHERE Ground-based

Ionosondes& GNSS

For this event, no suitable Ionosonde data were available. For GNSS analysis, the period before the event was characterised by high geomagnetic activity and not useful for the SAFE scope.



The M7.8 Ecuador EQ was analyzed using both Swarm geomagnetic and ionospheric data searching for earthquake-related anomalies in the frame of LAIC theory.

Considering MASS results, the cumulative number of Y anomaly tracks is not compatible with a linear regression (R2= 0.947). This is good as this factor could be a positive indication for a possible LAIC effect. The number of anomalies before EQ is greater (twice) than the anomaly tracks after EQ, so also nEQ is also a good indication for a correlation of these anomalies with the EQ.

For this case study NeSTAD method did not found any tagged anomalies, while ionosonde and GNSS data were not available.