[1] Aggregation of data collected in 28 controlled experiments reveals reproducible debris-flow behavior that provides a clear target for model tests. In each experiment ∼10 m 3 of unsorted, water-saturated sediment composed mostly of sand and gravel discharged from behind a gate, descended a steep, 95-m flume, and formed a deposit on a nearly horizontal runout surface. Experiment subsets were distinguished by differing basal boundary conditions (1 versus 16 mm roughness heights) and sediment mud contents (1 versus 7 percent dry weight). Sensor measurements of evolving flow thicknesses, basal normal stresses, and basal pore fluid pressures demonstrate that debris flows in all subsets developed dilated, coarse-grained, high-friction snouts, followed by bodies of nearly liquefied, finer-grained debris. Mud enhanced flow mobility by maintaining high pore pressures in flow bodies, and bed roughness reduced flow speeds but not distances of flow runout. Roughness had these effects because it promoted debris agitation and grain-size segregation, and thereby aided growth of lateral levees that channelized flow. Grain-size segregation also contributed to development of ubiquitous roll waves, which had diverse amplitudes exhibiting fractal number-size distributions. Despite the influence of these waves and other sources of dispersion, the aggregated data have well-defined patterns that help constrain individual terms in a depth-averaged debris-flow model. The patterns imply that local flow resistance evolved together with global flow dynamics, contradicting the hypothesis that any consistent rheology applied. We infer that new evolution equations, not new rheologies, are needed to explain how characteristic debris-flow behavior emerges from the interactions of debris constituents.

[1] Various methods have been proposed in the literature to predict the rainfall conditions that are likely to trigger landslides in a given area. Most of these methods, however, only consider the rainfall events that resulted in landslides and provide deterministic thresholds with a single possible output (landslide or no-landslide) for a given input (rainfall conditions). Such a deterministic view is not always suited to landslides. Slope stability, in fact, is not ruled by rainfall alone and failure conditions are commonly achieved with a combination of numerous relevant factors. When different outputs (landslide or no-landslide) can be obtained for the same input a probabilistic approach is preferable. In this work we propose a new method for evaluating rainfall thresholds based on Bayesian probability. The method is simple, statistically rigorous, and returns a value of landslide probability (from 0 to 1) for each combination of the selected rainfall variables. The proposed approach was applied to the Emilia-Romagna Region of Italy taking advantage of the historical landslide archive, which includes more than 4000 events for which the date of occurrence is known with daily accuracy. The results show that landsliding in the study area is strongly related to rainfall event parameters (duration, intensity, total rainfall) while antecedent rainfall seems to be less important. The distribution of landslide probability in the rainfall duration-intensity shows an abrupt increase at certain duration-intensity values which indicates a radical change of state of the system and suggests the existence of a real physical threshold.

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Debris flow initiation by channel bed mobilization is a common process in high mountainous areas. Initiation is more likely to occur at the outlet of small, steeply sloping basins where concentrated overland flow feeds an ephemeral channel incised in slope deposits. Such geological conditions are typical of the Dolomite region (Italian Alps), which is characterized by widespread debris flow activity triggered by severe summer thunderstorms. Real-time data and field observations for one of these catchments (Acquabona catchment, Belluno, Italian Alps) were used to characterize the hydrological response of the initiation area to rainfalls of varying intensity and duration. The observed behaviour was then reproduced by means of a simple hydrological model, based on the kinematic wave assumption, to simulate the generation of channel runoff. The model is capable of predicting the observed hydrological response for a wide range of rainfall impulses, thus providing a physical basis for the understanding of the debris flow triggering threshold.

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