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Where debris flows can impinge on the built environment, early detection of flow events is necessary in order to issue warnings and initiate countermeasures like road or train track closure. In this contribution, previously published work at Illgraben, Switzerland, is compiled, which shows how seismic measurements can be used for debris flow monitoring and warning. The advantage of the seismic approach is that debris flow signals can be detected at large distances eliminating the need for installations within or close to torrents, which are usually difficult to access. It is shown that seismic data contain important information about debris flows, including initiation, propagation, and particle sizes. However, machine learning algorithms, which are tuned with example data rather than physical principles, so far offer the best performance for debris flow detection with continuous real‐time data. Such algorithms pave the way for a new class of warning systems, based on data science techniques rather than in‐torrent instrumentation. [ABSTRACT FROM AUTHOR]

Automatic identification of debris flow signals in continuous seismic records remains a challenge. To tackle this problem, we use machine learning, which can be applied to continuous real‐time data. We show that a machine learning model based on the random forest algorithm recognizes different stages of debris flow formation and propagation at the Illgraben torrent, Switzerland, with an accuracy exceeding 90 %. In contrast to typical debris flow detection requiring instrumentation installed in the torrent, our approach provides a significant gain in warning times of tens of minutes to hours. For real‐time data from 2020, our detector raises alarms for all 13 independently confirmed Illgraben events, giving no false alarms. We suggest that our seismic machine‐learning detector is a critical step toward the next generation of debris‐flow warning, which increases warning times using simpler instrumentation compared to existing operational systems. Plain Language Summary: Debris flows are fast‐moving masses of mud, soil, fragmented rock, and water transporting large volume of material in mountainous areas. They pose a significant danger to human life, property, and infrastructure. It is crucial to detect debris flows early enough to send an alarm message to local communities. We propose a novel approach for debris‐flow detection using recorded ground vibrations generated by 22 debris flows at the Illgraben torrent, Switzerland. We use a machine‐learning algorithm that learns to distinguish between debris flow generated ground vibrations and other seismic signals. At the Illgraben torrent, this increases warning times by at least 20 min compared to existing detection systems. Key Points: A novel debris‐flow detector is developed using a machine‐learning model and seismic data from a Swiss torrent channelSignals of 22 debris‐flow events recorded by six seismic stations are used to train and test the machine‐learning modelA detector ran on continuous real‐time 2020 data stream detecting all 13 observed hazardous flows in 3 months and raising no false alarms [ABSTRACT FROM AUTHOR]

Debris flows are one of the most dangerous landslide types in mountainous regions. Their destructiveness is strongly controlled by their high peak discharge, which can be orders of magnitude larger than for floods. In order to reduce the associated hazards, detailed field measurements of natural debris flows are required to better constrain discharge and volume of these events. In this study, we used a high-frequency 3D LiDAR (light detection and ranging) scanner in combination with video cameras to measure key properties of a debris flow that occurred in the Illgraben catchment (Switzerland). Based on the LiDAR and video data, we directly measured i) front velocity ii) surge velocity iii) surface velocity and iv) cross-sectional area at sub-second intervals. We then estimated discharge and volume using these direct measurements and considering different channel bed geometry scenarios. We compared our results to estimates based on conventional methods and found that these more established methods substantially underestimate the (peak) discharge and volume for this event. Our results will be assessed in the future by analyzing more events, but our LiDAR-based method has the potential to provide much more detailed information on hazard-related debris-flow parameters, which will have important implications for understanding debris-flow processes and ultimately reducing their risk. • A debris flow was recorded using high-resolution 3D LiDAR point clouds. • The LiDAR data allowed for detailed measurements of discharge and volume. • The results presented here deviate from estimates based on conventional methods. • The detailed LiDAR-derived measurements can lead to a better process understanding. [ABSTRACT FROM AUTHOR]

The principal objective of this study was to investigate the types of large-scale meteorological situations that are conducive to the precipitation and temperature conditions most likely to trigger debris flows in the Zermatt valley, Switzerland, under current and future climates. A two-dimensional Bayesian probability calculation was applied to take account of uncertainties in debris-flow triggering. Precipitation quantities exceeding the 95th percentile of daily precipitation amounts were found to have a significantly higher probability to coincide with observed debris flows. A different relationship exists for extreme temperatures, however. Southerly air flows, weak horizontal pressure gradients over Europe, and westerly flows are mostly associated with observed debris flows and 95th precipitation percentile exceedances. These principal flow directions are well represented in the regional climate model (RCM) HIRHAM control simulations for events exceeding the 95th precipitation percentile and the 30th temperature percentile. Under the IPCC A2 emission scenario, westerly and southerly flows are mostly responsible for these precipitation and temperature conditions under the hypothesis of slow adaptation to climate change (HS1/HC1). Under the hypothesis of rapid adaptation to climate change (HS1/HS1), southerly flows and weak horizontal pressure gradients are likely to gain in importance. In both scenarios for the future, southeasterly flows are among the principal flow directions responsible for the joint exceedance of the 95th precipitation percentile and the 30th temperature percentile, while these were absent in observations and the control simulation. [ABSTRACT FROM AUTHOR]

We present a probabilistic sediment cascade model to simulate sediment transfer in a mountain basin (Illgraben, Switzerland) where sediment is produced by hillslope landslides and rockfalls and exported out of the basin by debris flows and floods. The model conceptualizes the fluvial system as a spatially lumped cascade of connected reservoirs representing hillslope and channel storages where sediment goes through cycles of storage and remobilization by surface runoff. The model includes all relevant hydrological processes that lead to runoff formation in an Alpine basin, such as precipitation, snow accumulation, snowmelt, evapotranspiration, and soil water storage. Although the processes of sediment transfer and debris flow generation are described in a simplified manner, the model produces complex sediment discharge behavior which is driven by the availability of sediment and antecedent wetness conditions (system memory) as well as the triggering potential (climatic forcing). The observed probability distribution of debris flow volumes and their seasonality in 2000-2009 are reproduced. The stochasticity of hillslope sediment input is important for reproducing realistic sediment storage variability, although many details of the hillslope landslide triggering procedures are filtered out by the sediment transfer system. The model allows us to explicitly quantify the division into transport and supply-limited sediment discharge events. We show that debris flows may be generated for a wide range of rainfall intensities because of variable antecedent basin wetness and snowmelt contribution to runoff, which helps to understand the limitations of methods based on a single rainfall threshold for debris flow initiation in Alpine basins. [ABSTRACT FROM AUTHOR]

Abstract: Debris flows strongly control sediment transfer patterns in mountainous catchments. We quantify sediment transfer at the Illgraben, Switzerland, where debris flows are frequent and geomorphic change is rapid. Four sequential aerial image series (from fall 2007 to fall 2009) were used to measure landscape change in relation to debris flows. The debris, often originating from bedrock landslides, was transported in patterns of erosion, storage, and remobilization. The landslides typically stopped on the downslope hillslope or in the channel, and they did not transform directly into debris flows. The magnitude and nature of sediment transfer patterns show large spatial and temporal variability, and the storage time of the deposits was shorter than one year. Landslide volumes were an order of magnitude smaller than the debris flows at the catchment outlet. While the mechanism of debris flow initiation could not be determined unambiguously, clearly debris flows must entrain substantial amounts of sediment along the flow path to attain the volumes estimated at the distal end of the fan. [ABSTRACT FROM AUTHOR]

IFKIS-Hydro is an information and warning system for hydrological hazards in small- and medium-scale catchments. The system collects data such as weather forecasts, precipitation measurements, water level gauges, discharge simulations and local observations of event-specific phenomena. In addition, IFKIS-Hydro incorporates a web-based information platform, which serves as a central hub for the submission and overview of data. Special emphasis is given to local information. This is accomplished particularly by human observers. In medium-scale catchments, discharge forecast models have an increasing importance in providing valuable information. IFKIS-Hydro was developed in several test regions in Switzerland and the first results of its application are available now. The system is constantly extended to additional regions and may become the standard for warning systems in smaller catchments in Switzerland. [ABSTRACT FROM AUTHOR]

Abstract: A widespread risk in high mountains is related to the accumulation of loose sediments on steep slopes, which represent potential sources of different types of geomorphic processes including debris flows. This paper combines data on 50yr of permafrost creep at the Ritigraben rock glacier (Valais, Swiss Alps) with magnitude–frequency (M–F) relationships of debris flows recorded in the Ritigraben torrent originating at the rock-glacier front. Debris production and volumetric changes at the rock-glacier front are compared with debris-flow activity recorded on the cone and potential couplings and feedbacks between debris sources, channel processes and debris sinks. The dataset existing for the Ritigraben rock glacier and its debris-flow system is unique and allows prime insights into controls and dynamics of permafrost processes and related debris-flow activity in a constantly changing and warming high-altitude environment. Acceleration in rock-glacier movement rates is observed in the (1950s and) 1960s, followed by a decrease in flow rates by the 1970s, before movements increase again after the early 1990s. At a decadal scale, measured changes in rock-glacier movements at Ritigraben are in concert with changes in atmospheric temperatures in the Alps. Geodetic data indicates displacement rates in the frontal part of the rock glacier of up to 0.6–0.9myr− 1 since the beginning of systematic measurements in 1995. While the Ritigraben rock glacier has always formed a sediment reservoir for the associated debris-flow system, annual horizontal displacement rates of the rock-glacier body have remained quite small and are in the order of decimeters under current climatic conditions. Sediment delivery from the rock-glacier front alone could not therefore be sufficient to support the 16 debris flows reconstructed on the cone since 1958. On the contrary, debris accumulated at the foot of the rock glacier, landslide and rockfall activity as well as the partial collapse of oversteepened channel walls have to be seen as important sediment sources of debris flows at Ritigraben and would represent 65–90% of the material arriving on the Ritigraben cone. There does not seem to exist a direct coupling between displacement rates of and sediment delivery by the rock-glacier body and the frequency of small- and medium-magnitude debris flows. In contrast, a direct link between source and sink processes clearly exists in the case of active-layer failures. In this case, failure processes at the rock-glacier snout and debris-flow events in the channel occur simultaneously and are both triggered by the rainfall event. [Copyright &y& Elsevier]

Abstract: Debris-flow activity in a watershed is usually defined in terms of magnitude and frequency. While magnitude–frequency (M–F) relations have long formed the basis for risk assessment and engineering design in hydrology and fluvial hydraulics, only fragmentary and insufficiently specified data for debris flows exists. This paper reconstructs M–F relationships of 62 debris flows for an aggradational cone of a small (<5km2), high elevation watershed in the Swiss Alps since A.D. 1863. The frequency of debris flows is obtained from tree-ring records. The magnitude of individual events is given as S, M, L, XL, and derived from volumetric data of deposits, grain size distributions of boulders, and a series of surrogates (snout elevations, tree survival, lateral spread of surges). Class S and M debris flows (<5×103 m3) encompass a typical size of events and have mean recurrence intervals of 5.4 (SD: 3.2) and 7.4years (SD: 6.7), respectively. Class XL events (104–5×104 m3) are, in contrast, only identified three times over the past 150years, and major erosional activity on the cone was restricted to two of these events in 1948 and 1993. A comparison of results with hydrometeorological records shows that class L and XL events are typically triggered by advective storms (rainfall >50mm) in August and September, when the active layer of the rock glacier in the source area of debris flows is largest. Over the past ∼150years, climate has exerted control on material released from the source area and prevented triggering of class XL events before 1922. With the projected climatic change, permafrost degradation and the potential increase in storm intensity are likely to produce “class XXL” events in the future with volumes surpassing 5×104 m3 at the level of the debris-flow cone. [Copyright &y& Elsevier]

Abstract: Debris flows are a major threat in many parts of the Alps, where they repeatedly cause severe damage to infrastructure and transportation corridors or even loss of life. Nonetheless, the spatial behavior of past debris-flow activity and the analysis of areas affected during particular events have been widely neglected in reconstructions so far. It was therefore the purpose of this study to reconstruct spatio-temporal patterns of past debris flows on a forested cone in the Swiss Alps (Bruchji torrent, Blatten, Valais). The analysis of past events was based on a detailed geomorphic map (1:1000) of all forms related to debris flows as well as on tree-ring series from 401 heavily affected trees (Larix decidua Mill. and Picea abies (L.) Karst.) growing in or next to deposits. The samples were analyzed and growth disturbances related to debris-flow activity assessed, such as tangential rows of traumatic resin ducts, the onset of reaction wood or abrupt growth suppression or release. In total, 960 growth disturbances were identified in the samples, belonging to 40 different event years between A.D. 1867 and 2005. In addition, the coupling of tree-ring data with the geomorphic map allowed reconstruction of eleven formerly active channels and spatial representation of individual events. Based on our results we believe that before 1935, debris flows preferentially used those channels located in the western part of the cone, whereas the eastern part of the cone remained widely unaffected. The spatial representation of the 40 events also allowed identification of five different spatial patterns for debris flows at the study site. [Copyright &y& Elsevier]

Abstract: Natural hazards like landslides, avalanches, floods and debris flows can result in enormous property damage and human casualties in mountainous regions. Switzerland has always been exposed to a wide variety of natural hazards mostly located in its alpine valleys. Recent natural disasters comprising avalanches, floods, debris flows and slope instabilities led to substantial loss of life and damage to property, infrastructure, cultural heritage and environment. In order to offer a solid technical infrastructure, a new concept and expert-tool based on an integrated web-based database/GIS structure is being developed under HazNETH. Given the HazNETH database design contemplates the detection and mapping of diagnostic features from remote sensors (e.g., ground, air and space borne) this paper analyses the use of remote sensing data in landslides studies during the 1980s, 1990s and 2000s, including a discussion of its potential and research challenges as result of new operational and forthcoming technologies such as the very high spatial resolution optical and infrared imagery of Ikonos, Quickbird, IRS CartoSat-1, ALOS, the satellite based interferometric SAR (InSAR and DInSAR of Radarsat, ERS, Envisat, TerraSAR-X, Cosmo/SkyMed, ALOS), micro-satellites like the Plèiades, DMC, RapidEye, airborne LASER altimetry or ground-based differential interferometric SAR. The use of remote sensing data, whether air-, satellite- or ground-based varies according to three main stages of a landslide related study, namely a) detection and identification; b) monitoring; c) spatial analysis and hazard prediction. Accordingly, this paper presents and discusses previous applications of remote sensing tools as related to these three main phases, proposing a conceptual framework for the contribution of remote sensing to the design of databases for natural hazards like debris flows, and identifying areas for further research. [Copyright &y& Elsevier]

• A 3.0 × 106 m3 rock slope accelerated measurably before failure. • Slope stability changed rapidly before failure. • 15 debris flows occurred within 7 days after failure (13 in absence of rainfall). • First debris flow initiated within 30 s after rock avalanche deposition. • Wet sediment entrainment and impact loading enhanced deposit mobility. Catastrophic collapse of large rock slopes ranks as one of the most hazardous natural phenomena in mountain landscapes. The cascade of events, from rock-slope failure, to rock avalanche and the near-immediate release of debris flows has not previously been described from direct observations. We report on the 2017, 3.0 × 106 m3 failure on Pizzo Cengalo in Switzerland, which led to human casualties and significant damage to infrastructure. Based on remote sensing and field investigations, we find a change in critical slope stability prior to failure for which permafrost may have played a destabilizing role. The resulting rock avalanche traveled for 3.2 km and removed over one million m3 of glacier ice and debris deposits from a previous rock avalanche in 2011. Whereas this entrainment did not lead to an unusually large runout distance, it favored debris flow activity from the 2017 rock avalanche deposits: the first debris flow occurred with a delay of 30 s followed by ten debris flows within 9.5 h and two additional events two days later, notably in the absence of rainfall. We hypothesize that entrainment and impact loading of saturated sediments explain the initial mobility of the 2017 rock avalanche deposits leading to a near-immediate initiation of debris flows. This explains why an earlier rock avalanche at the same site in 2011 was not directly followed by debris flows and underlines the importance of considering sediment saturation in a rock avalanche's runout path for Alpine hazard assessments. [ABSTRACT FROM AUTHOR]