This research contributes to the landslide forecast debate, analyzing the relationship between rainfall and slope failures in the eastward section of the Esino river basin, located in the Marche region (central Italy). Post-orogenic quaternary sediments, prone to rainfall-induced shallow landslides, characterize this 550 km2 wide area. In order to determine rainfall thresholds for the possible occurrence of slope failures, an innovative approach that consider both empirical and physical models has been described. The novelty consisted in the parallel application of these methodologies after integrating some of the each other features. First, the correlation between historical landslides and rainfall series was verified. Afterwards, empirical models such as the cumulative event rainfall – duration, the maximum intensity – duration, the mean intensity – duration, and the Bayesian approach were applied to the study area. These techniques were employed for the same landslides and rainfall databases and for the same zone, which is characterized by comparable hydrogeological properties. This allowed (i) the development of local rainfall thresholds that consider the geological framework and (ii) the choice of the critical rainfall parameters for the area of investigation. Next, the USGS Transient Rainfall Infiltration and Grid-based Regional Slope-stability (TRIGRS) physical model (Baum et al., 2002), was used to compute infiltration-driven changes in the factor of safety of the study area. This work presented an original methodology for the application of a physical model over a broad area, where detailed and continuous soil data inputs are difficult to obtain. Finally, all the developed models were tested during a recent rainfall event that affected the study area on 2-4 May 2014 and triggered several landslides. Results of this research are proposed as decision tools for landslide hazard forecasting that is one of the primary activity of the Civil Protection.
Questa ricerca analizza il rapporto tra precipitazioni e frane nella porzione est del bacino del fiume Esino, situato nella regione Marche (Italia centrale). Sedimenti quaternari post-orogenici, soggetti a frane superficiali indotte da pioggia, caratterizzano quest’ area di 550 km2. Al fine di determinare le soglie per il possibile innesco di frane, è stato descritto un approccio innovativo che considera sia modelli empirici che fisici. La novità consiste nell'applicazione parallela di queste metodologie mediante l’integrazione di alcune delle caratteristiche di uno nell’altro, e viceversa. In primo luogo, è stata verificata la correlazione tra frane storiche e precipitazioni. In seguito, modelli empirici quali metodo cumulata – durata, intensità massima – durata, intensità media – durata e approccio bayesiano sono stati applicati all'area di studio. Queste tecniche sono state impiegate per gli stessi database di piogge e frane e sull’area di studio, che è caratterizzata da proprietà idrogeologiche comparabili. Questo ha permesso di (i) sviluppare delle soglie di innesco locali che considerano il quadro geologico e (ii) scegliere i parametri critici di precipitazione per l'area di indagine. Successivamente, il modello fisico TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-stability) (Baum et al. 2002), sviluppato da USGS, è stato utilizzato nell’area di studio per calcolare le oscillazioni del fattore di stabilità dei versanti, derivanti dall’infiltrazione di acqua nel suolo. Questo lavoro rappresenta un'originale metodologia per l'applicazione di un modello fisico su una vasta area, dove dettagliati e continui dati sulle caratteristiche del suolo sono difficili da ottenere. Infine, tutti i modelli sviluppati sono stati testati durante un recente evento di pioggia che ha colpito l'area di studio il 2-4 maggio 2014 innescando numerose frane. I risultati della ricerca vengono proposti come strumenti decisionali per la previsione del pericolo frana, una delle principali attività di Protezione Civile.
Landslide forecast: empirical and physical predictive models applied to the Marche region (central Italy)
GIOIA, Eleonora
2015
Abstract
This research contributes to the landslide forecast debate, analyzing the relationship between rainfall and slope failures in the eastward section of the Esino river basin, located in the Marche region (central Italy). Post-orogenic quaternary sediments, prone to rainfall-induced shallow landslides, characterize this 550 km2 wide area. In order to determine rainfall thresholds for the possible occurrence of slope failures, an innovative approach that consider both empirical and physical models has been described. The novelty consisted in the parallel application of these methodologies after integrating some of the each other features. First, the correlation between historical landslides and rainfall series was verified. Afterwards, empirical models such as the cumulative event rainfall – duration, the maximum intensity – duration, the mean intensity – duration, and the Bayesian approach were applied to the study area. These techniques were employed for the same landslides and rainfall databases and for the same zone, which is characterized by comparable hydrogeological properties. This allowed (i) the development of local rainfall thresholds that consider the geological framework and (ii) the choice of the critical rainfall parameters for the area of investigation. Next, the USGS Transient Rainfall Infiltration and Grid-based Regional Slope-stability (TRIGRS) physical model (Baum et al., 2002), was used to compute infiltration-driven changes in the factor of safety of the study area. This work presented an original methodology for the application of a physical model over a broad area, where detailed and continuous soil data inputs are difficult to obtain. Finally, all the developed models were tested during a recent rainfall event that affected the study area on 2-4 May 2014 and triggered several landslides. Results of this research are proposed as decision tools for landslide hazard forecasting that is one of the primary activity of the Civil Protection.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/97898
URN:NBN:IT:UNIVPM-97898