**5. Conclusions**

The reconstruction of reliable thresholds with a high predictive capability becomes very important, especially if their implementation in an earlywarning system is proposed. In regard to the Oltrepò Pavese hilly area, which can be assumed representative of the geological, geomorphological, and land-use settings prone to shallow landslides also of the whole Northern Apennines, empirically and physicallybased thresholds were estimated. These were evaluated by quantifying their predictive capability through the comparison between modeled and real triggering or non-triggering conditions, identified in a validation dataset covering a five-year time span.

The role played by the soil hydrological conditions at the beginning of a rainfall event is fundamental in making this rainfall able to trigger or not trigger shallow landslides. The lower the pore-water pressure is at the beginning of an event, the higher the amount of rainfall required to trigger shallow failures is. When shallow landslides occur as a consequence of rain fallen on previously saturated soil (nil pore-water pressure), as in the study area, physicallybased thresholds provide a better reliability in discriminating the event which could or could not trigger slope failures. Besides a good capability in identifying correctly the triggering conditions, empirical thresholds, based only on rainfall data and neglecting the antecedent soil hydrological conditions, provide a significant number of false positives. These are events similar to the ones that provoked observed shallow failures, but with initial soil conditions drier than those corresponding to the real triggering events.

Main conclusions of this work can be summarized as follows:


into account the intrinsic variability of these parameters, also within small areas, probabilistic models will be applied to reconstruct this type of threshold in future developments.

**Author Contributions:** Conceptualization, M.B. (Massimiliano Bordoni) and C.M.; methodology, M.B. (Massimiliano Bordoni), B.C.,and C.M.; software, M.B. (Massimiliano Bordoni) and B.C.; validation, M.B. (Massimiliano Bordoni), and B.C.; formal analysis, M.B. (Massimiliano Bordoni), B.C., L.L., and V.V.; investigation, M.B. (Massimiliano Bordoni), B.C., L.L., R.V., M.B. (Marco Bittelli), V.V., and C.M.; resources, M.B. (Massimiliano Bordoni), R.V., M.B. (Marco Bittelli), and C.M.; data curation, M.B. (Massimiliano Bordoni), R.V., M.B. (Marco Bittelli), and C.M.; writing—original draft preparation, M.B. (Massimiliano Bordoni); writing—review and editing, M.B. (Massimiliano Bordoni), B.C., L.L., R.V., M.B. (Marco Bittelli), V.V., and C.M.; supervision, C.M.; project administration, C.M.

**Funding:** This work has been in the frame of the ANDROMEDA project, which has been supported by Fondazione Cariplo, grant n◦2017-0677.

**Acknowledgments:** We thank Marco Tumiati for the assistance on the executions of the laboratory geotechnical tests of the soil horizons of the testsite.

**Conflicts of Interest:** The authors declare no conflicts of interest.
