It is well-known that the degree of saturation is a soil state condition able to represent the hydrological response of a shallow soil to weather conditions. One of the oldest models that referred on the degree of saturation to carry out the slope stability analysis at different scales, was the Shallow Landslide Instability (SLIP) Model. This paper shows how the SLIP model can be used to derive a simplified method to estimate multiple seasonal cycles of the mean degree of saturation of soil and to carry out the time-varying stability analysis of a test site slope. The simplified method to assess the degree of saturation uses easily available climatic data, such as air temperature and rainfall depth, and is validated through the comparison with long-term field measurements on a slope in Canneto Pavese, northern Italy. The SLIP model is also applied to obtain the safety factor of the slope, that was subjected to a rainfall-induced shallow landslide during the field monitoring period. Comparisons between field measurements and model outputs are used to validate the capability of the model of predicting both the mean degree of saturation of the topsoil and the observed unstable condition.
Soil Saturation and Stability Analysis of a Test Site Slope Using the Shallow Landslide Instability Prediction (SLIP) Model
Montrasio, Lorella;
2018-01-01
Abstract
It is well-known that the degree of saturation is a soil state condition able to represent the hydrological response of a shallow soil to weather conditions. One of the oldest models that referred on the degree of saturation to carry out the slope stability analysis at different scales, was the Shallow Landslide Instability (SLIP) Model. This paper shows how the SLIP model can be used to derive a simplified method to estimate multiple seasonal cycles of the mean degree of saturation of soil and to carry out the time-varying stability analysis of a test site slope. The simplified method to assess the degree of saturation uses easily available climatic data, such as air temperature and rainfall depth, and is validated through the comparison with long-term field measurements on a slope in Canneto Pavese, northern Italy. The SLIP model is also applied to obtain the safety factor of the slope, that was subjected to a rainfall-induced shallow landslide during the field monitoring period. Comparisons between field measurements and model outputs are used to validate the capability of the model of predicting both the mean degree of saturation of the topsoil and the observed unstable condition.File | Dimensione | Formato | |
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