## 3 Results  
In Figure 5, the ROC plots for the SUFRA_1 models, both for the validation in the whole Torto basin and the Sciara sub-basin, are shown. The AUC values for SUFRA_1 models were outstanding for validation in the Torto basin (Figure 5a,b). However, the values decreased when the validation was focused on the Sciara sub-basin with respect to the systematic inventories (Figure 5c,d). This lowering was more marked for the flow model whose performance went from outstanding to good (0.77). Confusion matrices (Table 2) confirmed these behaviors, with very high values of sensitivity (Sens. values of 1 and 0.98 for slide and flow model, respectively). However, a limited specificity (Spec. values of 0.69 and 0.67 for slide and flow model, respectively) resulted due to the high number of false positives (FPs) produced. These very low values of specificity also affected the accuracy (Acc. ), which showed just sufficient values (~0.7). Figure 5: ROC plots of the two SUFRA_1 models validated in the whole Torto River basin (**a,b**) and in the Sciara sub-basin (**c,d**). AUC mean values were computed through one-hundred replicates given by extraction of different random negatives. On the other hand, the validation in the Sciara sub-basin revealed that the sensitivity suffered in the prediction images produced for both the slide and flow models when a systematic high-resolution archive was detected. This limit was more evident for the flow model for which the sensitivity was markedly insufficient (<0.6). The ROC plots relative to the validation of the SUFRA_2 models for slide and flow movements are shown in Figure 6. In this case, outstanding AUC values (>0.9) were achieved for both the whole Torto basin (Figure 6a,b) and the Sciara sub-basin (Figure 6c,d). Confusion matrices (Table 3) confirmed the high performance in validation within a coeval/homogeneous inventory of calibration with sensitivity values of 1 for slide and 0.95 for flow. Again, the specificity was just over 0.7 due to the high number of FPs produced. However, the validation in the Sciara sub-basin confirmed the better performance of the prediction images produced: the sensitivity was 1 for both flows and slides and, at the same time, the specificity was 0.75 for slides and 0.8 for flows; better values of accuracy (0.77 and 0.82 for slides and flows, respectively) were consequently obtained. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & & **Positive** & **Negative** & **TN** & **FN** & **FP** & **TP** & **Acc.** & **Sens.** & **Spec.** \\ \hline \multirow{4}{*}{**SIFRA\_1**} & SUFRA\_1 & \multirow{2}{*}{45} & \multirow{2}{*}{968} & \multirow{2}{*}{666} & \multirow{2}{*}{0} & \multirow{2}{*}{302} & \multirow{2}{*}{45} & \multirow{2}{*}{0.70} & \multirow{2}{*}{1} & \multirow{2}{*}{0.69} \\  & Slide & & & & & & & & & \\ \cline{2-2} \cline{6-11}  & SUFRA\_1 & \multirow{2}{*}{78} & \multirow{2}{*}{935} & \multirow{2}{*}{627} & \multirow{2}{*}{1} & \multirow{2}{*}{308} & \multirow{2}{*}{77} & \multirow{2}{*}{0.69} & \multirow{2}{*}{0.98} & \multirow{2}{*}{0.67} \\  & Flow & & & & & & & & \\ \hline \multirow{4}{*}{**SIFRA\_1**} & SUFRA\_1 & \multirow{2}{*}{9} & \multirow{2}{*}{90} & \multirow{2}{*}{70} & \multirow{2}{*}{3} & \multirow{2}{*}{20} & \multirow{2}{*}{6} & \multirow{2}{*}{0.77} & \multirow{2}{*}{0.67} & \multirow{2}{*}{0.78} \\  & Slide & & & & & & & & & \\ \cline{2-2} \cline{6-11}  & SUFRA\_1 & \multirow{2}{*}{7} & \multirow{2}{*}{92} & \multirow{2}{*}{72} & \multirow{2}{*}{3} & \multirow{2}{*}{20} & \multirow{2}{*}{4} & \multirow{2}{*}{0.77} & \multirow{2}{*}{0.57} & \multirow{2}{*}{0.78} \\ \cline{2-2} \cline{6-11}  & Flow & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Confusion matrix of the SUFRA_1 models in the Torto basin and in the Sciara sub-basin. Figure 6: ROC plot of the two SUFRA_2 models validated in the whole Torto River basin (**a**,**b**) and in the Sciara sub-basin (**c**,**d**). AUC mean values were computed through one-hundred replicates given by extraction of different random negatives.