Samuele Segoni

University of Firenze
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Articles (14)

Year:

2025

Year:

2024

This dataset collects tabular and geographical information about all hydrogeological disasters (landslides and floods) that occurred in Italy from 2013 to 2022 that caused such severe impacts as to require the declaration of national-level emergencies. The severity and spatiotemporal extension of each emergency are characterized in terms of duration and timing, funds requested by local administrations, funds approved by the national government, and municipalities and provinces hit by the event (further subdivided between those included in the emergency and those not, depending on whether relevant impacts were ascertained). Italian exposure to hydrogeological risk is portrayed strikingly: in the covered period, 123 emergencies affected Italy, all regions were struck at least once, and some provinces were struck more than 10 times. Damage declared by local institutions adds up to EUR 11,000,000,000, while national recovery funds add up to EUR 1,000,000,000. The dataset may foster further research on risk assessment, econometric analysis, public policy support, and decision-making implementation. Moreover, it provides systematic evidence helpful in raising awareness about hydrogeological risks affecting Italy.

Year:

2023

Performing a reliable stability analysis of a landslide slope requires a good understanding of the internal geometries and an accurate characterisation of the geotechnical parameters of the identified strata. Geotechnical models are commonly based on geomorphological data combined with direct and intrusive geotechnical investigations. However, the existence of numerous empirical correlations between seismic parameters (e.g., S-wave velocity) and geotechnical parameters in the literature has made it possible to investigate areas that are difficult to reach with direct instrumentation. These correlations are often overlooked even though they enable a reduction in investigation costs and time. By means of geophysical tests, it is in fact possible to estimate the N-SPT value and derive the friction angle from results obtained from environmental seismic noise measurements. Despite the empirical character and a certain level of uncertainty derived from the estimation of geotechnical parameters, these are particularly useful in the preliminary stages of an emergency, when straight data are not available and on all those soils where other direct in situ tests are not reliable. These correlations were successfully applied to the Theilly landslide (Western Alps, Italy), where the geotechnical model was obtained by integrating the results of a multi-parameter geophysical survey (H/V seismic noise and ground-penetrating radar) with stratigraphic and geomorphological observations, digital terrain model and field survey data. The analysis of the triggering conditions of the landslide was conducted by means of hydrological–geotechnical modelling, evaluating the behaviour of the slope under different rainfall scenarios and considering (or not) the stabilisation interventions present on the slope. The results of the filtration analyses for all events showed a top-down saturation mechanism, which led to the formation of a saturated face with a maximum thickness of 5 m. Stability analyses conducted for the same events showed the development of a shallow landslide in the first few metres of saturated soil. The modelling results are compatible with the actual evolution of the phenomenon and allow us to understand the triggering mechanism, providing models to support future interventions.

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Collaborators (7)

Filippo Catani

Prof.

University of Padova

ITALY
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Stefano Clò

Associate Professor

University of Florence

ITALY
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Veronica Pazzi

University of Florence

ITALY
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Ascanio Rosi

University of Florence

ITALY
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Nicola Casagli

University of Firenze

ITALY
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silvia bianchini

University of Firenze

ITALY
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Matteo Del Soldato

University of Florence

ITALY
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