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  • Reanalysis of soil moisture used for rainfall thresholds for rainfall-induced landslides [Elektronski vir] : the Italian case study
    Bezak, Nejc, hidrologija ; Jemec Auflič, Mateja ; Mikoš, Matjaž
    Landslides are one of the most frequent natural disasters that can endanger human lives and property. Therefore, prediction of landslides is essential to reduce economic damage and save human lives. ... Numerous methods have been developed for the prediction of landslides triggering, ranging from simple methods that include empirical rainfall thresholds, to more complex ones that use sophisticated physically- or conceptually-based models. Reanalysis of soil moisture data could be one option to improve landslide forecasting accuracy. This study used the publicly available FraneItalia database hat contains almost 9000 landslide events that occurred in the 2010%2017 period in Italy. The Copernicus Uncertainties in Ensembles of Regional Reanalyses (UERRA) dataset was used to obtain precipitation and volumetric soil moisture data. The results of this study indicated that precipitation information is still a much better predictor of landslides triggering compared to the reanalyzed (i.e., not very detailed) soil moisture data. This conclusion is valid both for local (i.e., grid) and regional (i.e., catchment-based) scales. Additionally, at the regional scale, soil moisture data can only predict a few landslide events (i.e., on average around one) that are not otherwise predicted by the simple empirical rainfall threshold approach; however, this approach on average, predicted around 18 events (i.e., 55% of all events). Despite this, additional investigation is needed using other (more complete) landslide databases and other (more detailed) soil moisture products.
    Vir: Water [Elektronski vir]. - ISSN 2073-4441 (Letn. 13, št. 14, 1977, 2021, str. 1-16)
    Vrsta gradiva - e-članek
    Leto - 2021
    Jezik - angleški
    COBISS.SI-ID - 70755075

    Povezava(-e):

    https://www.mdpi.com/2073-4441/13/14/1977
    Repozitorij Univerze v Ljubljani – RUL
    DOI

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