نوع مقاله : مقاله تحقیقی (پژوهشی)
1 دانشجوی دکتری، گروه فیزیک، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران
2 دانشیار، گروه فیزیک، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران
3 استادیار، گروه فیزیک، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران
4 استادیار، موسسه ملی ژئوفیزیک و آتش فشان شناسی، شعبه کاتانیا، کاتانیا، ایتالیا
عنوان مقاله [English]
Volcanic eruptions are usually done by increasing magma pressure. Monitoring this process in real-time can provide useful information for predicting eruptions. The cross-correlation function of ambient seismic noises has been used many times to monitor the activity of volcanoes around the world. Still, this method is usually limited to volcanoes equipped with large networks and broadband stations.
In this article, a technique has been proposed that automatically and without the need for advanced equipment or lots of data can calculate a cross-correlation function of seismic waves, then using the calculated cross-correlation function, it analyzes and examines the temporary changes in the relative velocity of seismic waves as well as the anomaly of the amplitude ratio of continuous data recorded in all pairs of stations as two eruption attributes.
The SARA (Seismic Amplitude Ratio Analysis) method was used to investigate the changes in the amplitude ratio, and the MWCS (Moving-Window Cross-Spectral) method was used to calculate the relative speed of environmental seismic wave data. Both methods have been implemented using MSNoise software package.
In order to validate these methods, the continuous data of 5 seismic stations near Etna volcano in Italy were used. First, in order to process the data, daily vertical recordings of all stations were divided into 30-minute segments. Then, the segments were demeaned, tapered and normalized to three times the root-mean-square (RMS). Next, the daily cross-correlation between all pairs of stations was calculated and the cross-correlation function was filtered in different frequency ranges. Finally, the velocity variations were measured with the MWCS method. The results showed a decrease of about 0.2 percent in the velocity before the main eruption and an increase rapidly after the eruption.
In the second step, the amplitude ratio of all pairs of stations was calculated with the SARA method. The increasing trend of the amplitude ratio was observed from three hours before the main eruption. To quantify the results, the Mann-Kendall trend analysis test was used for all pairs of stations. By using Sen's slope estimation test, the slope value of each figure was calculated separately. The results showed a temporary increase in the seismic amplitude ratio in 90 percent of pairs of stations before the main eruption. Automatic and continuous measurement of these attributes and combining their results can show the potential of this method to improve volcano monitoring and eruption early warning for active volcanoes.