A multidimensional stability model for predicting shallow landslide size and shape across landscapes

Analysis of Shear Constitutive Models of the Slip Zone Soil Based on Various Statistical Damage Distributions

The shear constitutive model of the slip zone soil can be used to quantitatively describe the relationship between shear stress and shear displacement, which is of great significance for the analysis of deformation mechanism and stability evaluation of landslides. The conventional shear constitutive models were usually proposed based on statistical damage theory with the Weibull distribution function, which is widely used in the field of rock material. However, there are great differences in the structure and mechanical properties of soil and rock; therefore, the suitability of the damage distribution functions for the slip zone soil needs to be further investigated. In this study, eight distribution functions are introduced to describe the damage evolution process of the slip zone soil and applied to two groups of shear stress–shear displacement curves (named shear curves) with different softening characteristics, i.e., strong softening type and weak softening type. The results show that: (1) the applicability of the various damage distribution functions to the two softening types of shear curves is obviously different; (2) the commonly used Weibull distribution is only suitable for the weak softening shear curves; (3) the shear constitutive models based on Gamma, Exponential, and Logistic distributions are the best three models for the strong softening curve; the shear constitutive models based on Gamma, Weibull, and Exponential distributions are the best three models for the weak softening curve; (4) Gamma distribution function is the optimal model in both strong softening and weak softening types of shear curves, and the parameters of the function have clear physical meaning in the shear constitutive model. In general, the Gamma distribution function can more objectively reflect the whole shear damage evolution process of the slip zone soil than other distribution functions.

Canyon Wall and Floor Debris Deposits in Aeolis Mons, Mars

Aeolis Mons (informally, Mount Sharp) exhibits a number of canyons, including Gediz and Sakarya Valles. Poorly sorted debris deposits are evident on both canyon floors and connect with debris extending down the walls for canyon segments that cut through sulphate-bearing strata. On the floor of Gediz Vallis, debris overfills a central channel and merges with a massive debris ridge located at the canyon terminus. One wall-based debris ridge is evident. In comparison, the floor of Sakarya Vallis exhibits a complex array of debris deposits. Debris deposits on wall segments within Sakarya Vallis are mainly contained within chutes that extend downhill from scarps. Lateral debris ridges are also evident on chute margins. We interpret the debris deposits in the two canyons to be a consequence of one or more late-stage hydrogeomorphic events that increased the probability of landslides, assembled and channelized debris on the canyon floors, and moved materials down-canyon. The highly soluble nature of the sulphate-bearing rocks likely contributed to enhanced debris generation by concurrent aqueous weathering to produce blocky regolith for transport downslope by fluvial activity and landslides, including some landslides that became debris flows. Subsequent wind erosion in Gediz Vallis removed most of the debris deposits within that canyon and partially eroded the deposits within Sakarya Vallis. The enhanced wind erosion within Gediz Vallis was a consequence of the canyon's alignment with prevailing slope winds.

A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties

Landslides can be triggered by natural and human activities, threatening the safety of buildings and infrastructures. Mapping potential landslide runout zones are critical for regional risk evaluation. Although remote sensing technology has been widely used to discover unstable areas, an entire landslide runout zone is difficult to identify using these techniques alone. Some simplified methods based on empirical models are used to simulate full-scale movements, but these methods do not consider the kinematic uncertainties caused by random particle collisions in practice. In this paper, we develop a semi-empirical landslide dynamics method considering kinematic uncertainties to solve this problem. The uncertainties caused by the microtopography and anisotropy of the material are expressed by the diffusion angle. Monte Carlo (MC) simulations are adopted to calculate the probability of each cell. Compared with the existing Flow-R model, this method can more accurately and effectively estimate runout zones of the Yigong landslide where random particle collisions are intense. Combining the D-InSAR technique, we evaluate the runout zones in the Jinsha River from June 2019 to December 2020. This result shows that the method is of great significance in early warning and risk mitigation, especially in remote areas. The source area of the landslide and DEM resolution together affect the number of MC simulations required. A landslide with a larger volume requires a larger diffusion angle and more MC simulations.

Improving Spatial Landslide Prediction with 3D Slope Stability Analysis and Genetic Algorithm Optimization: Application to the Oltrepò Pavese

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.

Controls on the size distributions of shallow landslides

Rainfall-triggered shallow landslides are destructive hazards and play an important role in landscape processes. A theory explaining the size distributions of such features remains elusive. Prior work connects size distributions to topography, but field-mapped inventories reveal pronounced similarities in the form, mode, and spread of distributions from diverse landscapes. We analyze nearly identical distributions occurring in the Oregon Coast Range and the English Lake District, two regions of strikingly different topography, lithology, and vegetation. Similarity in minimum sizes at these sites is partly explained by theory that accounts for the interplay of mechanical soil strength controls resisting failure. Maximum sizes, however, are not explained by current theory. We develop a generalized framework to account for the entire size distribution by unifying a mechanistic slope stability model with a flexible spatial-statistical description for the variability of hillslope strength. Using hillslope-scale numerical experiments, we find that landslides can occur not only in individual low strength areas but also across multiple smaller patches that coalesce. We show that reproducing observed size distributions requires spatial strength variations to be strongly localized, of large amplitude, and a consequence of multiple interacting factors. Such constraints can act together with the mechanical determinants of landslide initiation to produce size distributions of broadly similar character in widely different landscapes, as found in our examples. We propose that size distributions reflect the systematic scale dependence of the spatially averaged strength. Our results highlight the critical need to constrain the form, amplitude, and wavelength of spatial variability in material strength properties of hillslopes.

Scaling the Roots Mechanical Reinforcement in Plantation of Cunninghamia R. Br in Southwest China

The degree of mechanical reinforcement provided by plants depends upon its roots distribution in the soil and mechanical properties of the roots. The mechanical properties and distribution of root traits (root diameter and number) in the soil of the standing forest depends on the tree stem diameter. This variation of root traits with tree stem diameter is rarely investigated. Therefore, this research presents the effect of tree stem diameter on the distribution of roots within the standing forest of Cunninghamia in the Longchi forest area, Sichuan province, China. In this area, shallow landslides take place frequently. We investigated the root traits distribution for trees with different stem diameters, i.e., 220 mm, 320 mm, 450 mm, and 468 mm, to show the variation of roots distribution in the soil with stem diameter. The root architecture of the selected trees was studied by step excavation method of the root zone accompanied by measurement of roots physical parameters (roots number and roots diameter) and indices (roots area ratio (RAR), roots biomass (RB), and roots distribution (RD)). We measured the root’s maximum tensile strength by performing root tensile tests in the laboratory. The field and laboratory-measured data were used to estimate the root cohesion by both the commonly used model Wu and Waldron Model (WWM) and Fiber Bundle Model (FBM). The results indicate that the tree stem diameter correlates with both the root distribution and the tensile strength. The roots indices and root cohesion increase with an increase in the diameter of the tree. Further, RAR decreases with depth and lateral distance from the tree stem, while the maximum values were observed in 10 cm depth. The relationship between roots diameter and roots tensile strength is established through power function. The average root cohesion estimated for a tree with stem diameter 220 mm is 23 kPa, 29 kPa for 320 mm, 54 kPa for 450 mm, and 63 kPa for 460 mm. This effect of stem diameter on the increase of soil shear resistance should be considered while evaluating the stability of slopes in standing forests. The comparison between WWM and FBM for investigated species suggests that WWM estimates the cohesion values greater than FBM by 65%.

Geological and tectonic controls on morphometrics of submarine landslides of the Spanish margins

A geomorphological analysis of the submarine landslides geographical information system catalogue of the Geological Survey of Spain has revealed three main groups of submarine landslides associated with (1) deep-ocean seamount ridges (extinct spreading centres), (2) volcanic islands and (3) continental margins. These three groups have statistically significant morphometric differences, as determined from analysis of variance (ANOVA) and Tukey's HSD Tests, in total length (runout), total area, maximum deposit width and bathymetric depth. Volcanic island-related slope failures affect larger areas of the seafloor and their headwall escarpments often extend above sea-level. Slope failures associated with seamount ridges are the deepest, between 3500 and 5500 m, and display relatively high width-to-length ratios. Finally, landslides on continental margins show two sub-groups. Landslides on tectonically controlled margins have smaller runouts and total area and larger average slope gradients than margins where tectonic controls are limited. These results demonstrate that submarine landslide morphology is strongly controlled by the geological-tectonic setting.

Source areas, connectivity, and delivery rate of sediments in mountainous-forested hillslopes: A probabilistic approach

In mountainous-forested landscape, quantifying the materials produced at hillslope scale that effectively reach the channel network with a given probability is currently challenging, due to the uncertainties in modelling the frequency-magnitude distribution of failures and in determining the sediment connectivity between unstable areas and channel network. The purpose of this study is to develop a modular approach to assess the sediment source areas and the probability of mobilization from hillslope, and to estimate the probability of sediment input to the streams proposing a new connectivity index. The first goal was faced adopting a 3D probabilistic slope stability method that includes the spatially distributed characteristics of forest coverage. The second aim was tackled by comparing sediment travel distance and the minimum-topographic distance to reach the nearest stream. A simple deposition model was applied to estimate the percentage of the sediment entering into the stream network. The methodology was tested on three headwater catchments in northern Italian Alps. The outputs were landslide susceptibility maps, which showed robust performances when compared to the available landslide inventories (AUC > 0.726), and maps of the probability that sediment reaches the channel network. In this way, it was possible to identify which areas are the most susceptible to landsliding, how many sediment materials can be mobilised with a given probability, and which is the degree of sediment connectivity with the channel system. Results obtained for the tested catchments, compared with data available from the literature, showed that the proposed methodology is of general validity, especially for those territories characterized by rainfall-triggered landslides and forest coverage. This study, then, provides a robust framework to improve debris-flow risk management and to implement watershed management strategies, such as planning forestry operations or positioning retention structures addressed to increase slope stability and to reduce sediment delivery.