Monitoring and Early Warning Systems: Applications and Perspectives

Statistical Insights on the Eruptive Activity at Stromboli Volcano (Italy) Recorded from 1879 to 2023

“…This small change would have been sufficient to allow efficient mixing between the gas-rich magma rising from the deep storage [52,73,74,123] and the gas-poor magma residing within the uppermost conduit [124,125], resulting in a greater number of major explosions and a smaller number of paroxysms, and in a greater number of small overflows and fewer flank eruptions [91]. This result is further demonstrated by our analysis of the eruptive activity at Stromboli, extended until June 2023, and can be only partially attributed to an improved monitoring system, which was completely rebuilt in 2003 [39,[88][89][90]. The statistical models reported in this work represent a contribution to the hazard assessment of both explosive and effusive events.…”

“…However, an intrinsic irregularity of the Stromboli volcano's activity should not be overlooked, as testified by the low number of total events (12) recorded during 24 years (0.50 event/year) of relatively recent activity, from 1961 to 1984, compared with the 48 events recorded during 15 years of activity from 1985 to 2000 (3.2 event/year). If we do not consider the first interval of time, ranging from 1879 to 1960, when for at least 40 years Stromboli craters were monitored daily by the Italian Navy from the Semaforo Labronzo lighthouse [23], the increase in the total number of events recorded between 1961 and 2023 strongly suggests improvements in the monitoring systems, especially following the 2002-03 flank eruption, landslide and tsunami that heavily impacted the island [44,[87][88][89][90]. As we can see in Table 1(b), P and U classes have a maximum inter-event time that is similar (~26-27 years) and almost twice that of ME and of all explosive classes (ME + U + P) considered together (~12 years), whereas the median inter-event time value is about ~1 year for P and U and ~2 months for ME and for all explosive classes together, respectively.…”

An approach for prospective forecasting of rock slope failure time

“…Our PFTF model uses a common 25 linear simplification of Fukuzono's method. Although this can theoretically lead to mistakes, the linear application is mathematically least complex and therefore more likely used in practise 16 .…”

“…We implemented the concept into an operational prospective failure time forecast model (PFTF) complying with the requirements for real-time failure forecasting. PFTF iterates with every new available data point 24,25 , including only past observations without knowing the time of failure. It exclusively uses preaccessible data in a forward model.…”

“…In the accelerating phase, more or less accurate failure time forecasts are so far calculated with several methods 9,[17][18][19][20][21][22] . The most common prediction method is the inverse velocity method after Fukuzono 19 , possibly due to its relatively simple graphical solution [23][24][25] . Here, the inverse velocity of a failing mass is plotted against time during tertiary creep and the intersection of the extrapolated trend with the abscissa, i.e.…”