Warning algorithms based on ground vibration

The transformation of the raw seismic data is only the first step needed to employ GVDs in debris flow EWSs. The information retrieved from the signal has then to be integrated in a set of rules that precisely defines a sequence of operations that govern the EWS, namely in a warning algorithm. To this aim, specific parameters driving the warning algorithm must be identified in the signal.

Most part of warning algorithms from debris flow proposed so far use static intensity threshold as main warning parameter (Abancó et al., 2012; Badoux et al., 2008; Gianora et al., 2013; Schimmel and Hübl, 2015). Then the algorithm activates the alarm only if the threshold is exceeded for a specific time interval (Badoux et al., 2008) or when another intensity threshold is reached by a different sensor (Schimmel and Hübl, 2015). Static intensity thresholds are intuitive and simple to adopt using a transformed Amplitude or Impulses signal but they has a number of limitations that mainly depend from the choice of the threshold values. In general, warning algorithms integrating static intensity thresholds are: (i) event-sensitive, because the

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magnitude and the dynamics (i.e. the velocity) of the debris flow event have a strong impact on the ground vibrations; (ii) network-sensitive, because the joint effect of the distance of the GVD from the channel and the geometry of the channel (e.g. presence of check dams or deposits) influences the signal intensity; (iii) prone to a high number of false alarms dues to impulsive signals produced by other ground vibration sources (e.g. earthquakes, seismic noise produced by vehicles, slope instabilities and torrential processes occurring in basins nearby).

Figure 44 - The Amplitude curve and the inflection point that can be identified between the two lines that best fit the Amplitude curve before and after the change of slope (first panel); slope of the Amplitude curve calculated with a moving window of 10 seconds (second panel); slope of the Amplitude curve calculated with a moving window of 100 seconds (third panel).

In previous studies, another parameter was identified that can be used in warning algorithms, i.e. the slope of the Amplitude curve (Arattano, 2003). As mentioned before, the signal preceding the arrival of the debris flow wave at the cross section where the GVD is installed shows a gradual increase of its intensity. Some tens of seconds after, the signal presents a well defined change in slope, when a rapid

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increase of the signal takes place. An inflection point between the two lines that best fit the Amplitude curve before and after the change of slope can be identified, as well as a slope threshold that could be used as warning parameter Figure 44. The slope threshold could detect the arrival of the debris flow front some second before its passage at the cross section where the GVD is installed. However, the time window used to calculate the slope strongly affects the result. A short window (10 seconds) allows to detect the debris flow front with more advance then a long window (100 seconds) while this latter window is more effective if used to filter minor events or external seismic noise. Even if such an algorithm based on the slope of the Amplitude curve could be less case-sensitive and network-depended than one based on a static intensity threshold, the problem of the high number of false alarms would not be solved. A number of external disturbance and periodic fluctuations affect the seismic signal recorded along a torrent reach that can produce important changes of the Amplitude slope.

Figure 45 - The STA and the LTA calculated on a classical seismic signal with a moving window of 10 seconds and 100 seconds respectively (second and third panels) and the ratio STA/LTA (fourth panel).

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Afterwards, a warning parameter that takes into account the velocity of variation of the seismic signal intensity and filters as much as possible any external impulsive noise source is needed. The Signal-to-Noise Ratio (SNR) is a measure widely used in geophysics that compares the level of a desired signal to the level of background noise. SNR generically is the dimensionless ratio of the signal power to the noise power contained in a recording. More in general, we would refer to SNR as the ratio of two averages of energy calculated on a short-term window (STA) and on a long- term window (LTA). STA/LTA plots are useful for finding glitches associated with seismic events (Figure 45). A pair of consecutive windows, one short window and a second longer window, are passed over the seismic data. For each window the average deviation from the signal mean is computed. The ratio of the short window's average deviation to the long window's average deviation (STA/LTA) tends to jump up when a glitch is encountered. For purely random white noise, the nominal ratio is one. Because seismic data is not white and because no filtering is applied to the data before calculating STA/LTA, the nominal ratio tends to be above unity.

A comparison among these three warning parameter is presented in Figure 46. The raw seismic signal produced by a debris flow that occurred in the Gadria basin has been transformed in an Amplitude curve, the slope of this latter curve has been obtained using a moving window of 100 seconds and the STA/LTA has been calculated with moving windows of 10 seconds and 100 seconds respectively. The three warning parameters are compared choosing thresholds equal to the midpoint of the distance between the first local maximum and minimum. Adopting a static intensity threshold, the choice of the threshold has a strong impact on the early detection of the debris flow arrival. A threshold slightly higher of lower would results in tens of seconds of advance or delay. Moreover, the Amplitude peaks produced by the different surges are highly variable and this suggests how this method can be case-sensitive. The issue of the threshold selection is also visible in the slope graph, that allows to detect earlier the debris flow arrival but at the same time presents higher peak values in correspondence of secondary waves. On the contrary, using the STA/LTA ratio the first onset arrival is clearly highlighted in significant advance and the peaks and the fluctuation of the signal that follow the debris flow front are then significantly damped. This allows to easily set a reliable threshold that would effectively detect the debris flow arrival after a proper calibration of the STA and LTA time windows lengths. Furthermore, the STA/LTA represents a measure of the SNR and this necessarily make it less event- and network-sensitive. In conclusion, the STA/LTA has been selected as the most effective warning parameter to integrate in a warning algorithm for debris flow EWSs. A systematic application of such an algorithm to a large Amplitude dataset will be presented in the following to investigate the potential of this method for filtering external seismic noise sources.

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Figure 46 - The raw seismic signal produced by a debris flow that occurred in the Gadria basin, the Amplitude curve with a static intensity threshold equals to 68 um/sec, the slope of the Amplitude curve with a slope threshold equals to 1.57, the ratio STA/LTA with a threshold equals to 2.92.

6.2.4 ALMOND-F: an integrated debris flow monitoring and warning