We describe the development, implementation, and first analyses of the performance of a debris-flow warning system for the Illgraben catchment and debris fan area. The Illgraben catchment (9.5 km 2 ), located in the Canton of Valais, Switzerland, in the Rhone River valley, is characterized by frequent and voluminous sediment transport and debris-flow activity, and is one of the most active debris-flow catchments in the Alps. It is the site of an instrumented debris-flow observation station in operation since the year 2000. The residents in Susten (municipality Leuk), tourists, and other land users, are exposed to a significant hazard. The warning system consists of four modules: community organizational planning (hazard awareness and preparedness), event detection and alerting, geomorphic catchment observation, and applied research to facilitate the development of an early warning system based on weather forecasting. The system presently provides automated alert signals near the active channel prior to (5-15 min) the arrival of a debris flow or flash flood at the uppermost frequently used channel crossing. It is intended to provide data to support decision-making for warning and evacuation, especially when unusually large debris flows are expected to leave the channel near populated areas. Firstyear results of the detection and alert module in comparison with the data from the independent debris-flow observation station are generally favorable. Twenty automated alerts (alarms) were issued, which triggered flashing lights and sirens at all major footpaths crossing the channel bed, for three debris flows and 16 flood flows. Only one false alarm was issued. The major difficulty we encountered is related to the variability and complexity of the events (e.g., events consisting of multiple surges) and can be largely solved by increasing the duration of the alarm. All of the alarms for hazardous events were produced by storms with a rainfall duration and intensity larger than the threshold for debris-flow

Debris flow is a common process in the Swiss Alps and in other mountainous parts of the world. The understanding of debris-flow behaviour is essential to assess the hazards they present. An important approach towards improving the knowledge of debris-flow processes is the gathering of real-time data by debris-flow observation stations. Observation stations were established in three Swiss debris flow prone watersheds and equipped with video cameras, ultrasonic devices, a radar device, geophones, and rain gauges. In 2000, four significant debris flows were observed. The data provided useful information on the mechanics of debris flows and on the efficiency of the measuring devices. The observed debris flows are characterized by volumes between 5 000 and 35 000 m3, front velocities ranging from 2 to 5 m/s, and peak discharges between 20 and 125 m3/s. The analysis of the monitoring data revealed that ultrasonic and radar devices are very helpful tools, whereas the quality of the geophone signal strongly depends on the substrate on which the instrument is installed (i.e., bedrock versus unconsolidated material). Video images are useful to verify the data obtained by the other devices. A dynamic analysis of one debris flow was carried out and the simulated results are in fair agreement with the observed data.Key words: debris flow, Swiss Alps, monitoring, dynamic analysis.

Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ~10 km 2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristics of the monitoring systems is the differentiation between a continuous mode that samples at low frequency ("non-event mode") and another mode that records the measurements at high frequency ("event mode"). The event detection algorithm, used to switch into the "event mode" depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systems.

Abstract. Predicting potential deposition areas of future debris-flow events is important for engineering hazard assessment in alpine regions. To this end, numerical simulation models are commonly used tools. However, knowledge of appropriate model parameters is essential but often not available. In this study we use two numerical simulation models, RAMMS-DF (rapid mass movement system-debris-flow) and DAN3D (dynamic analysis of landslides in three dimensions), to back-calculate two well-documented debris-flow events in Austria and to compare the range and sensitivity of input parameters for the Voellmy flow model. All simulations are based on the same digital elevation models and similar boundary conditions. Our results show that observed deposition patterns are best matched with a parameter set of µ [-] and ξ [m s −2 ], ranging between 0.07 to 0.11 and 200 to 300 m s −2 , respectively, for RAMMS-DF, and between 0.07 to 0.08 and 300 to 400 m s −2 , respectively, for DAN3D. Sensitivity analysis shows a higher sensitivity of model parameters for the DAN3D model than for the RAMMS-DF model. This contributes to the evaluation of realistic model parameters for simulation of debris-flows in steep mountain catchments and highlights the sensitivity of the models.

Debris flows are fast mass movements formed by a mix of water and solid materials, which occur in steep torrents, and are a source of high risks for human settlements. Geophones are widely used to detect the ground vibration induced by passing debris flows. However, the recording of geophone signals usually requires storing a huge amount of data, which leads to problems in storage capacity and power consumption. This paper presents a method to transform and simplify the signals measured by geophones. The key input parameter is the ground velocity threshold, which removes the seismic noise that is not related to debris flows. A signal conditioner was developed to implement the transformation and the ground velocity threshold was set by electrical resistors. The signal conditioner was installed at various European monitoring sites to test the method. Results show that data amount and power consumption can be greatly reduced without losing much information on the main features of the debris flows. However, the outcome stresses the importance of choosing a ground vibration threshold, which must be accurately calibrated. The transformation is also suitable to detect other rapid mass movements and to distinguish among different processes, which points to a possible implementation in alarm systems.

We use pairs of parallel mounted laser profile scanners to measure main debrisflow variables in two debris-flow channels in central and southern Switzerland. The scanners measure the instantaneous cross-sectional geometry of debris flows at rates of 25-100 Hz, and we apply large-scale particle image velocimetery to estimate velocity. The scanners also provide direct measurements of flow depth. From these data, we were able to estimate debris-flow depth, velocity and discharge for 16 out of 17 events. These results are consistent with discharge estimated from a system of geophones and a radar gauge for two available datasets. We also investigated debris-flow geometry to quantify rheology-controlled cross-flow convexity and found that four events manifest strong surface convexity at their surge fronts where we expect the largest boulders and low pore-fluid pressures. The scanners provide a completely new view of debris-flow dynamics and channel morphology and present novel opportunities to measure discharge and investigate debris-flow geometries.

Debris flows are extremely rapid surging flows that can reach velocities in excess of 5 m s −1 , and travel for thousands of meters (Hungr et al., 2014). Despite decades of research into debris flows, these natural hazards cause costly disasters every year (Andres & Badoux, 2019;Petley, 2012). The destructiveness of debris flows is often amplified by their surging behavior, whereby peak discharge and impact pressure can be highly magnified (e.g., Hungr, 2000;Kean et al., 2016). Previous work has shown that understanding the interaction between coarse components of the flow, often manifest as a boulder-rich front, and a trailing slurry, which is composed of a mixture of soil and water, is critical for understanding this destructive surging behavior (Hungr, 2000;Iverson, 1997;Johnson et al., 2012). One major factor limiting our understanding of this interaction is a lack of high-quality field data that can be used to constrain numerical and physical models. In the present work, we leverage time-lapse LiDAR sensors, originally developed for autonomous vehicles, to estimate critical debrisflow properties at high spatial and temporal resolution, enabling us to analyze debris-flow propagation at the field scale.Coarse-grained boulder fronts are the product of longitudinal sorting, a mechanism which results in the characteristic grain size of flowing particles varying depending on the position within the flow (

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