## 4 Results
### Pore Water Pressure Data  
The temporal distribution of pore water pressure measurements covers 94% of the monitoring window, with three short data gaps caused by either some malfunctions in data acquisition or power supply interruptions (Figure 9a). In general, at the measuring depth, the pore water pressure data showed no significant long-term variations, with a mean value of 14.3 kPa and a standard deviation of approximately \(\pm\)2.5 kPa over the acquisition period (Figure 9a). The highest pore pressure value (26.8 kPa) was recorded in early March 2016, whereas the lowest one (7.0 kPa) was recorded in mid-March 2016. Conversely, short-term changes were more frequently observed, albeit typically small in magnitude. The largest pore water pressure oscillations were recorded between February and early March 2016 during the multi-day rainy period characterized by the concomitant occurrence of extremely high and moderate rainfall levels (Figure 9a). As outlined by the diagram showing the daily variation in pore water pressure, following single-day extreme precipitation, no relevant pore water pressure build-up developed (Figure 9b). For example, in December 2017, more than 100 mm of cumulated daily rainfall produced a slight increase in water pressure (i.e., 2.0 kPa). \begin{table}
\begin{tabular}{c c c c c} \hline
**Time Interval** & **2015** & **2016** & **2017** & **2015–2017** \\ \hline Data coverage (\%) & 100 & 99.7 & 100 & 99.8 \\ Total cumulative rainfall (mm) & 591.2 & 1139.8 & 720.0 & 2451.0 \\ Maximum daily rainfall (mm) & 87.8 & 130.4 & 107.0 & 130.4 \\ Maximum monthly rainfall (mm) & 338.4 & 335.6 & 218.6 & 338.4 \\ Mean daily rainfall (mm) & 2.9 & 3.1 & 2.0 & 2.6 \\ Mean monthly rainfall (mm) & 89.4 & 94.2 & 57.2 & 78.8 \\ \hline \end{tabular}
\end{table} 
Table 1: Summary of statistics of rainfall data measured by the Sara rain gauge over the investigated period. The general pattern of the piezometric data was consistent with the graph of the deviation of the daily pore water pressure from the mean of the observation period (Figure 9c). Indeed, the acquired time-series of pore water pressure data were largely characterized by small fluctuations around the mean value. The overall piezometric trend was further pointed out by the shape of both the histogram and the boxplot of the deviation of daily values from the mean pore water pressure: the data distribution was unimodal, with 75% of the deviations between \(-1.4\) and \(1.7\) kPa, and approximately normally distributed, showing a slight right asymmetry and a positive kurtosis (Figure 10). Nevertheless, some high outliers corresponding to major positive deviations were visible (Figure 10b). Figure 9: Pore water pressure data plotted together with daily rainfall: (**a**) daily pore water pressure (the continuous horizontal grey line indicates the mean pore water pressure value of the entire period, whereas the dashed horizontal grey lines show values that are one standard deviation above and below the mean); (**b**) daily change in pore water pressure; (**c**) deviations from daily mean pore water pressure. In all panels, the largest pore water pressure changes are highlighted in grey while main data gaps are indicated by black arrows. These anomalous deviations arose from two pore water pressure pulses generated during the rainy phase that occurred between February and early March 2016 (Figure 9a). These two pressure fluctuations appeared to be characterized by relatively similar behaviour: the maximum values achieved at the ascending limbs were comparable, namely 26.0 and 26.8 kPa, respectively, and both were followed by descending limbs indicating a progressive dissipation of excess pressure (Figure 11a). However, the pore water pressure evolution following the first peak was only partially detected because of technical problems that affected the data acquisition system. After the second peak, the pore water pressure dropped to a lower value than before the start of precipitation (Figure 11a).