Prediction of landslide hazard risk at hill slope induced by intense rainfall requires the appropriate modeling of the interactions between soil and weather phenomena, leading to failure as well as a reliable prediction of post-failure dynamics. In the peculiar case of fast shallow landslides behaving like dense granular flows, a suitable modeling approach for large and rapid deformations is necessary to estimate potential related damage. The impact force exerted by the leading edge of the earth-flow on the downstream structure should be estimated for both damage prediction and design of effective protection measures. In this paper, a free open source 3D research code based on standard weakly compressible smoothed particle hydrodynamics (WCSPH) method is validated by modeling a full-scale rainfall-induced shallow landslide which occurred in Oltrepò Pavese (Northern Italy). The code allows resolving the vertical velocity gradients, potentially providing a more reliable representation of the landslide dynamics and impact force. Mechanical parameters are consistent with average soil characteristics, avoiding calibration analysis. The final landslide profile is compared with an experimental survey for model validation, showing good fit. Influence of uncertainties of geotechnical parameters on the landslide front velocity and impact force on the downstream wall is evaluated.

In this study, we compare infinite slope and the three-dimensional stability analysis performed by SCOOPS 3D (software to analyze three-dimensional slope stability throughout a digital landscape). SCOOPS 3D is a model proposed by the U. S. Geological Survey (USGS), the potentialities of which have still not been investigated sufficiently. The comparison between infinite slope and 3D slope stability analysis is carried out using the same hydrological analysis, which is performed with TRIGRS (transient rainfall infiltration and grid-based regional slope-stability model)—another model proposed by USGS. The SCOOPS 3D model requires definition of a series of numerical parameters that can have a significant impact on its own performance, for a given set of physical properties. In the study, we calibrate these numerical parameters through a multi-objective optimization based on genetic algorithms to maximize the model predictability performance in terms of statistics of the receiver operating characteristics (ROC) confusion matrix. This comparison is carried out through an application on a real case study, a catchment in the Oltrepò Pavese (Italy), in which the areas of triggered landslides were accurately monitored during an extreme rainfall on 27–28 April 2009. Results show that the SCOOPS 3D model performs better than the 1D infinite slope stability analysis, as the ROC True Skill Statistic increases from 0.09 to 0.37. In comparison to other studies, we find the 1D model performs worse, likely for the availability of less detailed geological data. On the other side, for the 3D model we find even better results than the two other studies present to date in the scientific literature. This is to be attributed to the optimization process we proposed, which allows to have a greater gain of performance passing from the 1D to the 3D simulation, in comparison to the above-mentioned studies, where no optimization has been applied. Thus, our study contributes to improving the performances of landslide models, which still remain subject to many uncertainty factors.

Abstract. A key component for landslide early warning systems (LEWSs) is constituted by thresholds providing the conditions above which a landslide can be triggered. Traditionally, thresholds based on rainfall characteristics have been proposed, but recently, the hydrometeorological approach, combining rainfall with soil moisture or catchment storage information, is becoming widespread. Most of the hydrometeorological thresholds proposed in the literature use the soil moisture from a single layer (i.e., depth or depth range). On the other hand, multi-layered soil moisture information can be measured or can be available from reanalysis projects as well as from hydrological models. Approaches using this multi-layered information are lacking, perhaps because of the need to keep the thresholds simple and two-dimensional. In this paper, we propose principal component analysis (PCA) as an approach for deriving two-dimensional hydrometeorological thresholds that use multi-layered soil moisture information. To perform a more objective assessment we also propose a piecewise linear equation for the identification of the threshold's shape, which is more flexible than traditional choices (e.g., power law or bilinear). Comparison of the receiver operating characteristic (ROC) (true skill statistic, TSS) of thresholds based on single- and multi-layered soil moisture information also provides a novel tool for identifying the significance of multi-layered information on landslide triggering in a given region. Results for Sicily island, considering the ERA5-Land reanalysis soil moisture data (available at four different depth layers), corroborate the advantages of the hydrometeorological approach gained in spite of the coarse spatial resolution and the limited accuracy of reanalysis data. Specifically, the TSS of traditional precipitation intensity–duration thresholds is equal to 0.5, while those of the proposed hydrometeorological thresholds is significantly higher (TSS=0.71). For the analyzed region, however, multi-layered information seems not to be relevant, as performances in terms of TSS are similar to those obtained with single-layer soil moisture at the upper depths, namely 0–7 and 7–28 cm, which can imply that in Sicily landslide phenomena are mainly influenced by soil moisture in most shallow soil layers.

<p>Physically based models based on the combination of hydrological and slope stability models are important tools in spatial and temporal prediction of landslides, since they can be used for hazard mapping as an aid for land planning. In many applications, hydrological models are combined with very simple infinite slope stability analysis, given that multi-dimensional analysis is more computationally demanding. Only a few studies have attempted to apply such algorithms to the catchment scale. Thus, there is a need for more studies on this issue, also to understand the real advantages of applying multi-dimensional slope stability analysis in comparison with the one-dimensional. </p><p>This study aims to compare the performance of two different forecasting models, namely the infinite slope and the three-dimensional stability analysis by SCOOPS3D (Software to analyze three-dimensional slope stability throughout a digital landscape), a very efficient model proposed by USGS to be applied to the catchment scale, which has seldom been applied so far in the literature. In particular, TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-stability Model) is used for hydrological analysis.  Then the resulting pressure head field is used first as input to the infinite slope stability model embedded into TRIGRS program itself and then as input to SCOOPS3D. To calibrate the terrain stability-related parameters of either piece of software, a multi-objective optimization is proposed in this work to maximize the model predictability performance, in an attempt to optimize ROC performance statistics, i.e. to maximize the true positive rate while simultaneously minimizing the false positive rate.</p><p>The approach was applied to a real case study, a catchment in the Oltrepò Pavese (northern Italy), in which the areas of triggered landslides were accurately monitored during an extreme rainfall on 27-28 April, 2009, featuring 160 mm in 48 h. Compared to other works in the scientific literature, in which only a generic point of location of landslides was known, the present work benefits from the availability of a detailed landslide inventory containing observed landslide shapes.</p><p>The results point out the significantly better performance of  SCOOPS3D, in comparison with the infinite slope stability. Though SCOOPS3D seems to overestimate landslide prone areas, the 3D method is more realistic than the 1D method as far as the slip surface definition is concerned. Therefore, the proposed methodology, lying in the use of SCOOPS 3D with optimized parameters, can be a helpful tool for providing multiple landslide hazard maps for planning.</p>