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Understanding the initial and flow conditions of contemporary flows in Martian gullies, generally believed to be triggered and fluidized by CO2sublimation, is crucial for deciphering climate conditions needed to trigger and sustain them. We employ the RAMMS (RApid Mass Movement Simulation) debris flow and avalanche model to back calculate initial and flow conditions of recent flows in three gullies in Hale crater. We infer minimum release depths of 1.0–1.5 m and initial release volumes of 100–200 m3. Entrainment leads to final flow volumes that are ∼2.5–5.5 times larger than initially released, and entrainment is found necessary to match the observed flow deposits. Simulated mean cross‐channel flow velocities decrease from 3–4 m/s to ∼1 m/s from release area to flow terminus, while flow depths generally decrease from 0.5–1 to 0.1–0.2 m. The mean cross‐channel erosion depth and deposition thicknesses are ∼0.1–0.3 m. Back‐calculated dry‐Coulomb friction ranges from 0.1 to 0.25 and viscous‐turbulent friction between 100 and 200 m/s2, which are values similar to those of granular debris flows on Earth. These results suggest that recent flows in gullies are fluidized to a similar degree as are granular debris flows on Earth. Using a novel model for mass flow fluidization by CO2sublimation we are able to show that under Martian atmospheric conditions very small volumetric fractions of CO2of ≪1% within mass flows may indeed yield sufficiently large gas fluxes to cause fluidization and enhance flow mobility. We use RAMMS to back calculate initial and flow conditions of recent flows in three gullies in Hale craterRecent flows in gullies are fluidized to a similar degree as are wet granular debris flows on EarthVery small volumetric fractions of CO2of ≪1% may yield sufficiently large gas fluxes to fluidize contemporary flow in Martian gullies

Debris flows constitute a severe natural hazard and studies are performed to investigate triggering mechanisms and to identify and evaluate early warning systems. We present a seismoacoustic analysis of debris flow activity at Illgraben, Switzerland, with infrasound data collected with a small aperture array. Events are recorded as emergent signals of long duration, with seismic and infrasound amplitudes scaling with the flow discharge. The spectral content is stable and peaking at 8 Hz for the seismic and at 5 Hz for the infrasound that suggests two separate processes of elastic energy radiation, most likely bed‐load transport for the seismic and waves at the free surface for the infrasound. Although amplitude and frequency content of the infrasound signal are well within the processing limits, most of the signal is not showing any correlation among the array elements. We suggest that this is a consequence of the contribution of multiple sources of infrasound acting with variable amplitude and phase along the surface of the debris flow. At Illgraben, coherent infrasound is recorded only from fixed sources, corresponding to check dams within the channel. Here infrasound radiation is increased and the dams turn into predominant sources of energy. This allows to unambiguously identify the occurrence of debris flow at Illgraben with the infrasound array, from a remote and safe position and with a timing that is similar to the early warning system based on in‐channel sensors. This clearly shows how infrasound arrays could be used as an efficient early warning systems. Debris flows constitute a severe natural hazard in alpine environments, and studies are currently performed to investigate triggering mechanisms and to identify and evaluate early warning systems. We present a seismoacoustic analysis of debris flow activity at Illgraben, Switzerland, with infrasound data collected for the first time with an array of infrasound sensors deployed outside the channel in a safe position. This seimoacoustic experiment is providing interesting constraints on the mutual radiation of energy in the ground and in the atmosphere by the flow. Moreover, the use of the infrasound antenna allowed for the first time to carefully analyze the mechanism of infrasound radiation that we model as an extended source of energy with variable phase. Moreover, the array is able to detect the debris flow when it crosses dams or topography steps, even if this occurs at large distance (>2 km) and despite not being visible from the recording site. For the specific case of Illgraben, this allows to unambiguously identifying the occurrence of debris flow with a timing that is similar to the early warning system based on in‐channel sensors. This clearly shows how infrasound arrays could be used as new early warning systems for debris flow activity. Infrasound array analysis shows that debris flows can be modeled as an extended source of infrasound with variable phaseSeismic and infrasound spectra of debris flows at Illgraben are decoupled and suggest two different mechanisms of energy radiationWhen sharp topography is present, infrasound arrays can be used as an efficient early warning systems for debris flows remotely

Debris flows can grow greatly in size and hazardous potential by eroding bed and bank materials. However, erosion mechanisms are poorly understood because debris flows are complex hybrids between a fluid flow and a moving mass of colliding particles, bed erodibility varies between events, and field measurements are hard to obtain. Here, we identify the key controls on debris‐flow erosion based on a field data set that combines information on flow properties, bed conditions, and bed and bank erosion. We show that flow conditions and bed wetness jointly control debris‐flow erosion. Flow conditions describing the cumulative forces exerted at the bed during an event best explain erosion. Shear forces and particle‐impact forces are strongly correlated and act in conjunction in the erosion process. A shear‐stress approach accounting for bed erodibility may therefore be applicable for modeling and predicting debris‐flow erosion. This work provides a foundation for developing effective debris‐flow erosion models. Debris flows are water‐laden masses of soil and rock, which are common geological hazards in mountainous regions worldwide. They can grow greatly in size and hazardous potential by eroding bed and bank materials. Limited understanding of these erosion processes, however, hampers effective hazard assessment and mitigation. Improving our understanding of erosion is challenging because debris flows are complex hybrids between a fluid flow and a moving mass of colliding particles, bed erodibility varies between events, and field measurements are hard to obtain. Here, we identify the key controls on debris‐flow erosion based on a field data set that combines information on flow properties, bed conditions, and bed and bank erosion. We show that flow properties and bed wetness jointly control debris‐flow erosion. Flow conditions that describe the cumulative forces exerted at the bed during an event best explain erosion. Shear forces and particle‐impact forces are strongly correlated and act in conjunction in the erosion process. A shear‐stress approach accounting for bed erodibility may therefore be applicable for modeling and predicting debris‐flow erosion. This work provides a foundation for developing effective debris‐flow erosion models. Flow conditions and bed wetness jointly control debris‐flow erosion and depositionShear forces and particle‐impact forces are strongly correlated and together determine erosionA shear‐stress approach accounting for bed erodibility may be applicable for modeling debris‐flow erosion Flow conditions and bed wetness jointly control debris‐flow erosion and deposition Shear forces and particle‐impact forces are strongly correlated and together determine erosion A shear‐stress approach accounting for bed erodibility may be applicable for modeling debris‐flow erosion

Hazard assessment for post‐wildfire debris flows, which are common in the steep terrain of the western United States, has focused on the susceptibility of upstream basins to generate debris flows. However, reducing public exposure to this hazard also requires an assessment of hazards in downstream areas that might be inundated during debris flow runout. Debris flow runout models are widely available, but their application to hazard assessment for post‐wildfire debris flows has not been extensively tested. Necessary inputs to these models include the total volume of the mobilized flow, flow properties (either inherent material properties or calibration coefficients), and site topography. Estimates of volume are possible in post‐event (“back calculation”) studies, yet before an event, volume is an uncertain quantity. We simulated debris flow runout for the well‐constrained 9 January 2018 Montecito event using three models (RAMMS, FLO2D, and D‐Claw) to determine the relative importance of volume and flow properties. We broke the impacted area into three domains, and for each model‐domain combination, we performed a numerical sampling study in which volume and flow properties varied within a wide, but plausible range. We assessed model performance based on inundation patterns and peak flow depths. We found all models could simulate the event with comparable results. Simulation performance was most sensitive to flow volume and less sensitive to flow properties. Our results emphasize the importance of reducing uncertainty in pre‐event estimates of flow volume for hazard assessment. Changes in soil properties after fire mean rain can more easily erode the surface and initiate debris flows—mixtures of water, soil, and rock that rapidly move from steep source areas to downstream regions. The combination of frequent fire, steep landscapes, dense population, and intense rain makes southern California prone to debris flows. The scientific community has established methods linking debris flow likelihood and volume to rainfall intensity and burned area characteristics. We presently lack a basis for understanding how flow volume, flow material properties, representation of flow physics, and site topography all combine to produce an inundation hazard. We begin to address this by using observations from the 9 January 2018 Montecito, California, debris flow event to test three candidate models for debris flow inundation. We found that all models can simulate the event and that the largest source of uncertainty in inundated area is the flow volume. The 2018 Montecito event was successfully simulated with three debris flow inundation models that vary in model physicsModel performance was more sensitive to flow volume and site morphology than to flow propertiesEstimated volumes were lower than rainfall‐based predictions, and observed inundation areas were larger than volume‐based predictions The 2018 Montecito event was successfully simulated with three debris flow inundation models that vary in model physics Model performance was more sensitive to flow volume and site morphology than to flow properties Estimated volumes were lower than rainfall‐based predictions, and observed inundation areas were larger than volume‐based predictions

Three two-dimensional (2D) debris-flow simulation models are applied to two large well-documented debris-flow events which caused major deposition of solid material on the fan. The models are based on a Voellmy fluid rheology reflecting turbulent-like and basal frictional stresses, a quadratic rheologic formulation including Bingham, collisional and turbulent stresses, and a Herschel–Bulkley rheology representing a viscoplastic fluid. The rheologic or friction parameters of the models are either assumed a priori or adjusted to best match field observations. All three models are capable of reasonably reproducing the depositional pattern on the alluvial fan after the models have been calibrated using historical data from the torrent. Accurate representation of the channel and fan topography is especially important to achieve a good replication of the observed deposition pattern.Three two-dimensional (2D) debris-flow simulation models are applied to two large well-documented debris-flow events which caused major deposition of solid material on the fan. The models are based on a Voellmy fluid rheology reflecting turbulent-like and basal frictional stresses, a quadratic rheologic formulation including Bingham, collisional and turbulent stresses, and a Herschel–Bulkley rheology representing a viscoplastic fluid. The rheologic or friction parameters of the models are either assumed a priori or adjusted to best match field observations. All three models are capable of reasonably reproducing the depositional pattern on the alluvial fan after the models have been calibrated using historical data from the torrent. Accurate representation of the channel and fan topography is especially important to achieve a good replication of the observed deposition pattern.

The beds of steep streams are typically composed of relatively immobile boulders and more mobile patches of gravel and cobbles. Little is known about how variability in flow and sediment flux affect the area, thickness, composition, and grain mobility of sediment patches. To better understand patch dynamics, we measured flow, sediment transport, and bed properties in two steep channels. Patches close to the thalweg varied in area, thickness, and grain size, whereas those outside the thalweg did not. Local variations in transport of several orders of magnitude occurred, even on a patch with a spatially homogeneous grain size distribution. During moderate flow events, partial to selective transport dominated on the entire channel bed and all individual patches. Tracer particles moved freely between different patch classes (e.g., fine and coarse patches exchanged particles), and relatively fine sediment on all patch classes began motion at the same shear stress. Therefore, the selective transport observed for the entire bed was not a result of the preferential transport of only fine patches, but the high relative mobility of finer sediment on all patches. Our results suggest that local flow and sediment supply, and not spatial grain size variations, were the primary drivers of local bed load transport variability. The use of reach‐averaged flow properties to understand local patch dynamics may not be applicable. Patch transport is controlled by local flow and sediment supplyAll patch classes start motion at the same reach‐averaged shear stressSpatial variability in grain size may be possible to neglect