Flowing over erodible beds, channelized granular avalanches can alter their volume by entraining or detraining basal grains. In detail, entrainment results from a gradual adjustment of stress and velocity profiles over depth, bringing bed material past yield (and vice versa for detrainment). To capture this process, we propose new depth-integrated equations that balance kinetic energy in addition to mass and momentum. The equations require a local granular rheology, assumed viscoplastic, but no extra erosion law. Entrainment rates are instead deduced from the depth-integrated layer dynamics. To check the approach, we obtain solutions for non-equilibrium heap flows, and compare them with experiments conducted in a seesaw channel.

Granular flows in rotating drums transition between two regimes characterized by straight and curved free surfaces. Here we predict this behavior using a depth-integrated theory applicable to general eroding flows. Closure is achieved by a local $\mu \left(I\right)$ rheology and an equation for kinetic energy. Spanning the transition, the theory yields relations for all flow properties in terms of a single dimensionless rotation rate. In accord with experiments, distinct scaling laws are obtained for slow and fast rates, dominated respectively by local energy dissipation and longitudinal energy transfer.

Using theory and experiments, we investigate granular surface avalanching due to material outflow from a narrow silo. The assumed silo geometry is a deep rectangular box, of moderate spanwise width and small gap thickness between smooth front and back walls. A small orifice deep below the free surface lets grains drain out at a constant rate. The resulting granular flows can therefore be assumed quasi-two-dimensional and quasi-steady over most of the surface descent history. To model these flows, we couple a kinematic model of deep granular flow with a dynamic model of shallow surface avalanching. We then compare the calculated flow fields with detailed particle tracking measurements, letting the silo ascend relative to the high-speed camera to increase spatial resolution. The results show that the avalanching surface shape and near-surface flow are controlled by the spanwise gradient in subsidence velocity, and how this gradient is in turn controlled by the height above orifice and the gap thickness. Whereas the deep flow pattern is rate independent, shallow avalanching is paced by the granular rheology.

To predict the morphology of debris flow deposits, a control volume finite-element model (CVFEM) is proposed, balancing material fluxes over irregular control volumes. Locally, the magnitude of these fluxes is taken proportional to the difference between the surface slope and a critical slope, dependent on the thickness of the flow layer. For the critical slope, a Mohr–Coulomb (cohesive-frictional) constitutive relation is assumed, combining a yield stress with a friction angle. To verify the proposed framework, the CVFEM numerical algorithm is first applied to idealized geometries, for which analytical solutions are available. The Mohr–Coulomb constitutive relation is then checked against debris flow deposit profiles measured in the field. Finally, CVFEM simulations are compared with laboratory experiments for various complex geometries, including canyon–plain and canyon–valley transitions. The results demonstrate the capability of the proposed model and clarify the influence of friction angle and yield stress on deposit morphology. Features shared by the field, laboratory, and simulation results include the formation of steep snouts along lobe margins.

Seismic signals, with their remote and continuous monitoring advantages, have been instrumental in unveiling various landslide characteristics and have been widely applied in the past decades. However, a few studies have extended these results to provide geologists with pre-survey information, thus enhancing the understanding of the landslide process. In this research, we utilize the deep-seated Cilan landslide (CL) as a case study and employ a series of seismic analyses, including spectrogram analysis, single-force inversion, and geohazard location. These techniques enable us to determine the physical processes, sliding direction, mass amount estimation, and location of the deep-seated landslide. Through efficient discrete Fourier transforms for spectrograms, we identified three distinct events, with the first being the most substantial. Further analysis of spectrograms using a semi-log frequency axis generated by discrete Stockwell transform revealed that Event 1 consisted of four sliding failures occurring within 30 s with decreasing sliding mass. Subsequent Events 2 and 3 were minor toppling and rockfalls, respectively. Geohazard location further constrained the source location, indicating that Events 1 and 2 likely originated from the same slope. Subsequently, the sliding direction retrieved from single-force inversion and the volume estimation were determined to be 153.67° and 557 118 m³, respectively, for the CL. Geological survey data with drone analysis corroborated the above seismological findings, with the sliding direction and source volume estimated to be around 148° and 664 926 m³, respectively, closely aligning with the seismic results. Furthermore, the detailed dynamic process observed in the spectrogram of Event 1 suggested a possible failure mechanism of CL involving advancing, retrogressing, enlarging, or widening. By combining the above mechanism with geomorphological features identified during field surveys, such as the imbrication-like feature in the deposits and the gravitational slope deformation, with video from the event, we can infer the failure mechanism of retrogression of Event 1 after shear-off from the toe. Then, the widening activity was caused by the failure process for subsequent events, like Events 2 and 3. This case study underscores the significance of remote and adjacent seismic stations in offering seismological-based landslide characteristics and a time vision of the physical processes of landslides, thereby assisting geologists in landslide observation and deciphering landslide evolution.