STRALERT: STRain and wArning signaLs in nEar Real-Time at Etna for volcano surveillance operation

The Sacks-Evertson strainmeters are fundamental instruments to monitor deformation of the shallow crust produced by volcanic processes since they can record volumetric strain signals with a nominal high resolution of about 10^-11. However, the recorded strain signal is affected by the effects of different disturbing sources such as earth tides, local barometric pressure variations, precipitations and underground water circulation. The disturbing signals (amplitude ranges 10^-8-10^-7) reduce the signal accuracy and can mask smaller strain transients (10^-9-10^-8) due to volcano processes [1] preventing thus the correct monitoring of the volcano activity.

The effects of the disturbing sources on the recorded strain signal can be filtered by employing dedicated softwares developed to this scope. However, such programs were not designed to be run automatically and thus cannot be directly employed for near real-time signal filtering. To fill this lack, we developed the software STRALERT (STRain and wArning signaLs in nEar Real-Time) to provide in near real-time both the strain signal recorded by a strainmeter station installed at the Etna volcano and the respective filtered signal to the Surveillance Room of the “Istituto Nazionale di Geofisica e Vulcanologia – Osservatorio Etneo”. The software embeds a modified version of the program BAYTAP-G [2] for the filtering operation that allows using a set of optimally defined filter parameters as inputs. The accuracy of the strain signal is improved reaching values of ≈10^-10 and allowing thus the detection of ultra-small strain changes.

Examples of the output of STRALERT are presented for the 2021 period, when frequent eruptive events took place at the Etna volcano. Significant strain changes are clearly observed during the main lava fountain episodes. Thanks to the good accuracy warranted by STRALERT, it was also possible to unravel tiny strain changes due to weak eruptive activity that would have been completely hidden by the tidal and the pressure variations in the recorded raw signal. Moreover, the filtered signal better shows the onset and the end of the transient strain variations allowing to easily mark the timing of the associated eruptive events. Alert thresholds have been defined on the filtered signals to recognize these transient strain changes and automatically deliver a warning signal for the surveillance operations.     

 

[1] Currenti, G. and Bonaccorso A. (2019). Cyclic magma recharge pulses detected by high-precision strainmeter data: the case of 2017 inter-eruptive activity at Etna volcano, Sci. Rep.-Uk., 9(1), 1–7.

[2] Tamura, Y., T. Sato, M. Ooe and M. Ishiguro (1991). A procedure for tidal analysis with a Bayesian information criterion, Geophys. J. Int., 104(3), 507–516.