## 5 Discussion  
The three considered approaches to data analysis (OBA, SBA and SEA) have been compared here to evaluate their reliability for analysing and deducing relations among _preparatory factors_ and the related strain effects, on micro-fractures and open joints of the outcropping rock mass, through different time windows (taking into account already well-known relations with the aim to testing these approaches with expected results). To this aim, each forcing action (i.e., temperature, rainfall, wind and induced vibrations) has been related to the induced rock mass strains using the three proposed approaches deriving inferences considering different time windows. The OBA allows clearly deriving cause-to-effect relations due to continuous or impulsive forcing actions and related strain effects (Figure 12). The temperature shows a cyclical behaviour at different wavelengths over daily and seasonal time windows, whereas rainfall is characterised by cyclical recurrence over a seasonal time window only. The actions of these _preparatory factors_ are reflected in a composed cyclic trend of the strain that, little by little, accumulates inelastic deformation (due to the daily net strain rate) over a longer time window (several seasons). For each daily thermal cycle, the OBA allowed outputting of the elastic contributions due to thermomechanical behaviour of the rock mass and defining and characterising the heating and cooling phases over daily and seasonal time windows. Figure 12: Results from the OBA experienced at the Acuto test-site with the associated severity levels from objective cause-to-effect relations. Regarding the impulsive actions, objective cause-to-effect relations have also been deduced according to vibrations generated under controlled conditions (i.e., regularly emitted by engines), since the strain effects of the rock mass were evident in terms of the dynamic mobility and block resonance. On the contrary, impulsive but irregular forcing actions due to wind did not allow objective cause-to-effect relations with the strain effects measured in the rock mass, except for very intense events such as storms. By the OBA, the highest severity levels which could correspond to alert signals are related to the strongest and clearest cause-to-effect objective evidence, as in the cases of the air-to-rock temperature, rock temperature-to-strain, and man-induced vibrations-to-strain. The SBA was carried out to define which rate series are cross correlated with each other over medium- to long time windows (i.e., daily tending towards seasonal). The main benefit of such a statistical approach is to automatically verify the occurrence of correlations among several data series, also allowing the estimation of the time lag over which two rate series are cross-correlated. All the data series of forcing actions have been cross correlated by considering the resulting rates of strain values to point out the redundancy of transgressive series, which can detect conditions leading towards failure. The results demonstrated that very high correlations exist between continuous and regular forcing actions and the induced strains, such as for rock temperature and thermomechanical effects over daily time windows, tending to seasonal. On the other hand, the data series are poorly cross correlated in the cases of irregular and discontinuous forcing actions, such as for rainfall or wind and the induced rock mass strain. The results show a high cross-correlation between the air temperature and the rock temperature, which implies a relevant correlation between the rock temperature rate and the strain rates, indicating the main role of heating and cooling cycles in destabilising the rock mass monitored at the Acuto test-site (Figure 13).