Dr. Jacob Hirschberg

Anthropogenic climate change is rapidly altering high mountain environments, including changing the frequency, dynamic behavior, location, and magnitude of alpine mass movements. Here, we review three decades of scientific literature (1995 to early 2024) to assess to what degree observational records from the European Alps – as the region with the most comprehensive records – reveal these changes. We do this for the processes that are most common in this region, namely rockfall, rock avalanches, debris flows, ice avalanches, and snow avalanches. The systematic literature search and review yielded 335 publications, of which we omitted publications that did not focus primarily on observational records. The remaining 103 publications used observations from over 100 sites and 30 inventories to investigate the connection between climate change and mass movements. About one third of the relevant studies found a measurable impact of climate change on the investigated alpine mass movement processes (with the exception of large rock avalanches). The clearest climate-controlled trends are (i) increased rockfall frequency in high-alpine areas due to higher temperatures, (ii) fewer and smaller snow avalanches due to scarcer snow conditions at low and mid elevations, and (iii) a shift towards avalanches with more wet snow and fewer powder clouds. While there is (iv) despite a clear increase in debris-flow triggering precipitation, debris-flow activity has not been found to uniformly increase, though there is some evidence for increasing activity above treeline and at locations without historical precedence. The trends for (v) ice avalanches are spatially very variable with no clear direction. Ice temperatures are measurably increasing, but – despite a theoretical expectation – this has not impacted ice avalanche activity to date. The reviewed literature also reveals that quantifying the impact of climate change on these mass movements remains difficult in part due to the complexities of the natural system, but also because of limitations in the available datasets, confounding effects, and existing statistical processing techniques. Better assessments could be achieved if we would more broadly support the compilation and maintenance of large standardized data catalogs, bring together various dispersed datasets (in said catalogs), including from social and citizen science projects, invest in long-term natural observatories, and develop suitable processing techniques. Better observations will additionally support the development and performance of process-based models. If we can advance natural hazard research on these fronts, more quantitative predictions of future change are well within our reach.

Debris-flow volumes can increase along their flow path by entraining sediment stored in the channel bed and banks, thus also increasing hazard potential. Theoretical considerations, laboratory experiments and field investigations all indicate that the saturation conditions of the sediment along the flow path can greatly influence the amount of sediment entrained. However, this process is usually not considered for practical applications. This study aims to close this gap by combining runout and hydrological models into a predictive framework that is calibrated and tested using unique observations of sediment erosion and debris-flow properties available at a Swiss debris-flow observation station (Illgraben). To this end, hourly water input to the erodible channel is predicted using a simple, process-based hydrological model, and the resulting water saturation level in the upper sediment layer of the channel is modelled based on a Hortonian infiltration concept. Debris-flow entrainment is then predicted using the RAMMS debris-flow runout model. We find a strong correlation between the modelled saturation level of the sediment on the flow path and the channel-bed erodibility for single-surge debris-flow events with distinct fronts, indicating that the modelled water content is a good predictor for erosion simulated in RAMMS. Debris-flow properties with more complex flow behaviour (e.g., multiple surges or roll waves) are not as well predicted using this procedure, indicating that more physically complete models are necessary. Finally, we demonstrate how this modelling framework can be used for climate change impact assessment and show that earlier snowmelt may shift the peak of the debris-flow season to earlier in the year. Our novel modelling framework provides a plausible approach to reproduce saturation-dependent entrainment and thus better constrain event volumes for current and future hazard assessment.

Les laves torrentielles peuvent gagner considérablement en volume et donc en potentiel de menace par l'érosion le long de leur parcours. Il est prouvé que ces processus d'érosion sont liés aux conditions de saturation des sédiments avant l'événement. De tels facteurs d'influence hydrologiques n'ont toutefois pas encore été explicitement pris en compte dans la modélisation des laves torrentielles. Le présent article présente une approche permettant de combler cette lacune.
Le programme de simulation utilisé (RAMMS) est en mesure de bien représenter les caractéristiques d'écoulement et d'érosion pour une majorité des laves torrentielles. De plus, dans ces cas, il est possible d'établir une relation claire entre l'érodabilité et la saturation précédente du parcours d'écoulement. La méthode présentée constitue une base prometteuse pour une évaluation plus complète des processus de danger ainsi que de leur influence par le changement climatique.

Murgänge können durch Erosion entlang ihres Fliessweges erheblich an Volumen und damit an Gefährdungspotenzial gewinnen. Diese Erosionsprozesse hängen erwiesenermassen mit den Sättigungsbedingungen des Sediments vor dem Ereignis zusammen. Solche hydrologischen Einflussfaktoren werden bei der Murgangmodellierung bisher jedoch nicht explizit berücksichtigt. Im vorliegenden Beitrag wird ein Ansatz vorgestellt, um diese Lücke zu schliessen.
Das verwendete Simulationsprogramm (RAMMS) ist in der Lage, für eine Mehrheit der Murgangereignisse die Fliess- und Erosionseigenschaften gut abzubilden. Darüber hinaus kann in diesen Fällen ein klarer Zusammenhang zwischen der Erodierbarkeit und der vorhergehenden Sättigung des Fliesspfades festgestellt werden. Die vorgestellte Methode stellt eine vielversprechende Grundlage für eine umfassendere Beurteilung von Gefahrenprozessen sowie deren Beeinflussung durch den Klimawandel dar.

Différents systèmes de surveillance sont utilisés dans le monde entier pour l'observation et la saisie de paramètres importants des laves torrentielles, mais ils ont tous une résolution limitée dans le temps et/ou dans l'espace. Dans cet article, nous présentons une nouvelle méthode de surveillance basée sur des scanners laser 3D (LiDAR), qui fournit des données à haute résolution temporelle et spatiale sur les laves torrentielles. Dans l'Illgraben, plusieurs scanners LiDAR de ce type ont été installés le long du chenal et ont déjà enregistré onze événements de laves torrentielles. Grâce à ces données 3D, nous avons pu mesurer avec une grande précision la vitesse d'objets individuels dans le mélange des laves torrentielles et déterminer les débits et les volumes. Nos analyses montrent que la technologie LiDAR peut apporter une contribution essentielle à une description plus détaillée de la dynamique des laves torrentielles, d'autant plus que les premiers résultats indiquent des différences significatives, par exemple dans la détermination du débit, entre cette méthode et les méthodes conventionnelles.

Zur Beobachtung und Erfassung wichtiger Kenngrössen von Murgängen kommen weltweit verschiedene Monitoring-Systeme zum Einsatz, die alle eine zeitlich und/oder räumlich beschränkte Auflösung haben. In diesem Artikel präsentieren wir eine neue Monitoring- Methode basierend auf 3D-Laserscannern (LiDAR), die zeitlich und räumlich hochaufgelöste Daten von Murgängen liefert. Im Illgraben wurden mehrere solche LiDAR-Scanner entlang des Gerinnes installiert und haben bereits elf Murgangereignisse erfasst. Anhand dieser 3D-Daten konnten wir Geschwindigkeiten einzelner Objekte in der Murgangmischung mit hoher Genauigkeit messen sowie Abflüsse und Volumina ermitteln. Unsere Analysen zeigen, dass die LiDAR-Technologie einen wesentlichen Beitrag zur detaillierteren Beschreibung der Murgangdynamik leisten kann, zumal erste Resultate auf massgebliche Unterschiede etwa in der Bestimmung des Abflusses zwischen dieser Methode und konventionellen Verfahren hindeuten.

Study region: Four perialpine lakes in Switzerland, with different degrees of lake level management.
Study focus: Alpine regions are particularly sensitive to climate change due to the pronounced effect on snow and glacial melt. In this context, large perialpine lakes play a crucial role in modulating climate change impacts on water resources, which brings together diverse interests. However, climate change studies on river systems rarely include lakes or lake level management. An open question is how to incorporate lake level management effects into hydrologic simulations to project climate change impacts. We combine the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate lake level and outflow scenarios from 1981 to 2099, using the Swiss climate change scenarios CH2018.
New hydrological insights for the region: The hydrological projections at the end of the century show pronounced seasonal changes in lake levels, characterised by an increase in winter and a decrease in summer when water demand is highest. Without climate mitigation measures, this summer decrease ranges from −0.04 m for a regulated lake to −0.4 m for an unregulated lake. In addition, the simulations indicate more frequent drought events. The projected changes intensify with time and missing climate mitigation measures. Future work could focus on interannual variability to explore regulatory strategies under changing conditions.

Estimating flow velocities is key to assessing hazards associated with debris flows. One approach to post-event velocity estimation is the superelevation method, which uses debris-flow mudlines to measure the cross-channel surface inclination, or superelevation, produced by centripetal forces acting on the flow in a bend. Flow velocities are then calculated using a subjective parameterization of the forced vortex equation modified to include a debris-flow specific correction factor. Subjective parameterization of this equation leads to substantial variability and uncertainty in the resulting flow velocities. We present an analysis of the reliability of the superelevation method using a large UAV-based data set of 14 debris flows with front velocities of ∼0.8–6.5 m s⁻¹ and cross-channel surface inclinations of ∼0.6–8.5°, as well as a validation for a single debris flow measured using high-resolution, high-frequency 3D lidar data fused to video imagery. The validation event indicates that when the flow surface inclination can be measured directly, the forced vortex equation produces excellent results without needing a correction factor for Froude numbers ranging from 0.7 to 1.5. This finding indicates that the main challenge with the superelevation method lies in obtaining accurate measurements of superelevation from the mudlines, and that a correction factor may serve to compensate for measurement difficulties rather than variable flow properties. For very small and highly subcritical flows, the superelevation method may generate a large overestimation of flow velocities.

Debris flows entrain sediments and water along their flow path and grow significantly in size. Because the entrainment process isn’t well understood and data is rare, hazard and risk assessment with numerical models is challenging. It is known, however, that both for debris flows and rock avalanches, interstitial pore water in flow path substrate can cause increases in pore water pressures when overridden by the flow, which enhances erosion. The entrained water likely also plays a role in the process transition from rock avalanche to debris flow, like in the Pizzo Cengalo event in 2017. We present a framework for producing entrainment maps serving as an input for runout modelling, here illustrated using RAMMS. The entrainment maps consist of spatially-distributed entities with properties such as max erosion depth, and soil water content inferred from land cover and lithology maps. This study serves as a basis for producing duration curves of subsurface water available for entrainment and include it into the entrainment maps. Such hydrologically-informed entrainment maps will be useful to assess the probability of certain runout distances.

Gravitational mass wasting prediction requires understanding of the factors controlling failure. Prior to slope failure, cracks in the weakened rock are thought to grow and coalesce, eventually forming a continuous failure plane. Here, we apply a hidden Markov machine learning model to seismic data, revealing the temporal evolution of cracks prior to a major rockslide event in the Swiss Alps. After prolonged linear increase of the crack cumulative number, an S-shaped crack rate pattern occurred in the day before the rockslide. A simple mechanistic model can explain this behaviour, showing that total crack boundary length is the key factor controlling failure plane evolution immediately before mass movement. Our findings imply that cracks should be treated as 2-D, rather than 1-D objects, and that slope failure can be driven predominantly by internal rather than external processes. Our model offers a novel, physically based approach for early warning of slope failures.

The volume of a debris flow is a critical parameter in hazard analysis, yet accurate estimates of volume are often unavailable due to mixing with larger rivers at the downstream end of alluvial fans. We describe a method to calculate the volume of debris flows using flow depth data collected at a check dam, using a Manning friction relation to describe the velocity of the debris flow as a function of flow depth, and the geometry of the channel cross section. The method is evaluated using a published data set from the USGS debris-flow flume where event volume and stage information have been accurately measured, and results in volume estimates either somewhat smaller than or up to 50% larger than observed volumes. We further demonstrate the method to single-surge and a multiple-surge debris flows observed at Illgraben.

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 (i) quantify the spatio-temporal patterns of erosion and deposition and (ii) identify the key controls on debris-flow erosion in the Illgraben (CH). We use a dataset that combines information on flow properties, antecedent rainfall, and bed and bank erosion for 13 debris flows that occurred between 2019 and 2021. We show that spatio-temporal patterns of erosion and deposition in natural debris-flow torrents can be highly variable and dynamic, and we identify a memory effect where erosion is strong at locations of strong deposition during previous flows and vice versa. We find that flow conditions and antecedent rainfall (affecting bed wetness) jointly control debris-flow erosion. We find statistically significant correlations between channel erosion/deposition and a wide range of flow conditions, including frontal flow depth, velocity, and discharge, and flow volume, cumulative shear stress and seismic energy, as well as antecedent rainfall. Overall, flow conditions describing the cumulative forces exerted at the bed during an event, such as cumulative shear stress and flow volume, best explain erosion. A shear-stress approach accounting for bed erodibility may therefore be applicable for modelling and predicting debris-flow erosion. This work can provide input for model development by identifying correlations of flow and bed conditions with erosion that models should oblige.

The forced vortex equation, based on the cross-stream inclination of a flow surface as it passes through a bend, is a common approach to estimating debris flow velocities. Here, we present the preliminary results of a study of superelevation and the correction factor k, used to adapt the forced vortex equation to debris flows, based on data from the Illgraben torrent in Switzerland. The definition of the radius of curvature, a factor in the calculation of superelevation velocities, is not found to exercise a large influence on the calculated velocities when using high resolution aerial images, with the choice of cross-section location and k-factor exercising a more significant influence. The k-factors found here fall within the range previously reported in the literature, ranging from approximately 1 to 7, and a previously suggested non-linear relationship with Froude numbers is evident in the dataset. Following the debris flow season of 2022, the study will be continued with additional debris flow events and the investigative methods will be extended to include high-resolution LiDAR sensors installed along the Illgraben torrent.

Climate and sediment supply are critical for geomorphic systems. It is known that complex relations between such forcings and sediment mobilization may lead to dampened or erased environmental signals in sediment records. But it is unclear under which circumstances environmental signals are transmitted and measurable downstream. We used a numerical approach consisting of a sediment cascade model and a stochastic weather generator to quantify climate forcing effects under a range of sediment supply regimes in a debris-flow catchment in the Swiss Alps (Illgraben). We show that sediment yields estimated from short records are highly uncertain both in terms of mean and interannual variability. Furthermore, sediment yields tend to be underestimated in supply-limited systems, where also long-term memory effects, driven by the history of sediment storage, are evident. Consequently, determining geomorphic system response from short records may be grossly inaccurate and should be extended with sediment supply detection and uncertainty analysis.

Debris flows threaten communities in mountain regions worldwide. Combining modern photogrammetric processing with autonomous unoccupied aerial vehicle (UAV) flights at sub-weekly intervals allows mapping of sediment dynamics in a debris flow catchment. This provides important information for sediment disposition that pre-conditions the catchment for debris flow occurrence. At the Illgraben debris flow catchment in Switzerland, our autonomous UAV launched nearly 50 times in the snow-free periods in 2019-2021 with typical flight intervals of 2-4 d, producing 350-400 images every flight. The observed terrain changes resulting from debris flows exhibit preferred locations of erosion and deposition, including memory effects as previously deposited material is preferentially removed during subsequent debris flows. Such data are critical for the validation of geomorphological process models. Given the remote terrain, the mapped short-term erosion and deposition structures are difficult to obtain with conventional measurements. The proposed method thus fills an observational gap, which ground-based monitoring and satellite-based remote sensing cannot fill as a result of limited access, reaction time, spatial resolution, or involved costs.

A change in surface loading causes the Earth’s surface to deform. Mass movements, such as debris flows, can cause a tilt large enough to be recorded by nearby instruments, but the signal is strongly dependent on the mass loading and subsurface parameters. Specifically designed sensors for such measurements (tiltmeters) are cumbersome to install. Alternatively, broadband seismometers record translational motion and also tilt signals, often at periods of tens to hundreds of seconds. Their horizontal components are thereby the most sensitive to tilt. In this study, we show how to obtain tilt caused by the passing by of debris flows from seismic measurements recorded within tens of meters of the flow and investigate the usefulness of this signal for flow characterization. We investigate the problem on three scales (1) large‐scale laboratory experiments at the U.S. Geological Survey debris‐flow flume, where broadband seismometers and tiltmeters were installed for six 8-10  m³ experiments, (2) the Illgraben torrent in Switzerland, one of the most active mass wasting sites in the European Alps, where a broadband seismometer placed within a few meters of the channel recorded 15 debris‐flow events with volumes up to 10⁵  m³⁠, and (3) Volcán de Fuego, Guatemala, where a broadband seismometer recorded two lahars. We investigate how the tilt signals compare to debris‐flow parameters such as mean normal stresses, usually measured by expensive force plates, and debris‐flow height. We model the elastic ground deformation as the response of an elastic half‐space to a moving surface load. In addition, we use the model with some simplifications to determine the maximum debris‐flow heights of Volcán de Fuego events, where no force plate measurements are available. Finally, we address how and under what assumptions the relatively affordable and straightforward tilt measurements may be utilized to infer debris‐flow parameters, as opposed to force plates and other complicated instrument setups.

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.

Climate change impacts on sediment production and transfer processes on hillslopes and through channels are governed by possible changes in precipitation, runoff, and air temperature. These hydrological and geomorphological impacts are difficult to predict in temperature-sensitive Alpine environments. In this study, we combined a stochastic weather generator model with the most current climate change projections to feed a hillslope-channel sediment cascade model for a major debris-flow system in the Swiss Alps (the Illgraben). This allowed us to quantify climate change impacts and their uncertainties on sediment yield and the number of debris flows at hourly temporal resolution. We show that projected changes in precipitation and air temperature lead to a reduction in both sediment yield (−48%) and debris-flow occurrence (−23%). This change is caused by a decrease in sediment supply from hillslopes, which is driven by frost-weathering. Additionally, we conduct model experiments that show the sensitivity of projected changes in sediment yield and debris-flow hazard to basin elevation, with important implications for assessing natural hazards and risks in mountain environments. Future changes in hydrological and sediment fluxes are characterized by high uncertainty, mainly due to irreducible internal climate variability. Therefore, this stochastic uncertainty needs to be considered in climate change impact assessments for geomorphic systems.

The prediction of debris flows is relevant because this type of natural hazard can pose a threat to humans and infrastructure. Debris-flow (and landslide) early warning systems often rely on rainfall intensity-duration (ID) thresholds. Multiple competing methods exist for the determination of such ID thresholds but have not been objectively and thoroughly compared at multiple scales, and a validation and uncertainty assessment is often missing in their formulation. As a consequence, updating, interpreting, generalizing and comparing rainfall thresholds is challenging. Using a 17-year record of rainfall and 67 debris flows in a Swiss Alpine catchment (Illgraben), we determined ID thresholds and associated uncertainties as a function of record duration. Furthermore, we compared two methods for rainfall definition based on linear regression and/or true-skill-statistic maximization. The main difference between these approaches and the well-known frequentist method is that non-triggering rainfall events were also considered for obtaining ID-threshold parameters. Depending on the method applied, the ID-threshold parameters and their uncertainties differed significantly. We found that 25 debris flows are sufficient to constrain uncertainties in ID-threshold parameters to ±30% for our study site. We further demonstrated the change in predictive performance of the two methods if a regional landslide data set with a regional rainfall product was used instead of a local one with local rainfall measurements. Hence, an important finding is that the ideal method for ID-threshold determination depends on the available landslide and rainfall data sets. Furthermore, for the local data set we tested if the ID-threshold performance can be increased by considering other rainfall properties (e.g. antecedent rainfall, maximum intensity) in a multivariate statistical learning algorithm based on decision trees (random forest). The highest predictive power was reached when the peak 30min rainfall intensity was added to the ID variables, while no improvement was achieved by considering antecedent rainfall for debris-flow predictions in Illgraben. Although the increase in predictive performance with the random forest model over the classical ID threshold was small, such a framework could be valuable for future studies if more predictors are available from measured or modelled data.

In alpinen Einzugsgebieten beeinflussen Klimaveränderungen die Sedimentproduktion und deren Transfer über steile Hänge und durch die Gerinne - und somit auch die Murgangaktivität. Im Rahmen des WSL Forschungsprogramms CCAMM (Climate Change Impacts on Alpine Mass Movements) haben wir die CH2018 Klimaszenarien mit einem stochastischen Wettergenerator und einem Sedimentkaskadenmodell kombiniert, um für den Illgraben (VS) die limawandelauswirkungen einschliesslich deren Unsicherheiten zu quantifizieren. Prognostiziert wird eine Reduktion sowohl der jährlichen Gesamtsedimentfracht (-48%) als auch der Murganghäufigkeit (-23%) bis ins Jahr 2100. Diese Entwicklungen sind auf eine verminderte Sedimentverfügbarkeit durch Frostverwitterung zurückzuführen. Zusätzliche numerische Modellexperimente geben Aufschluss über mögliche Veränderungen in der Sedimentproduktion auf unterschiedlichen Höhenlagen sowie über die Quellen der Unsicherheiten. Insbesondere sollte in der Bewertung von Naturgefahren die nicht reduzierbare interne Klimavariabilität berücksichtigt werden. Ansonsten droht eine Überbewertung der Signifikanz der prognostizierten Klimawandelauswirkungen.

Dans les bassins versants alpins, les changements climatiques influencent la production de sédiments et leur transfert sur les pentes raides et dans les lits de cours d’eau - et donc aussi l'activité des laves torrentielles. Dans le cadre du programme de recherche du WSL CCAMM (Climate Change Impacts on Alpine Mass Movements), nous avons combiné les scénarios climatiques CH2018 avec un générateur météo stochastique et un modèle de cascades de sédiments pour quantifier les impacts du changement climatique, y compris leurs incertitudes, pour l'Illgraben (VS). On prévoit une réduction de la charge sédimentaire totale annuelle (-48%) et de la fréquence des laves torrentielles (-23%) d'ici à 2100. Ces évolutions sont dues à la réduction de la disponibilité des sédiments causée par l'altération par le gel. Des expériences supplémentaires par modèles numériques fournissent des informations sur les changements possibles dans la production
de sédiments à différentes altitudes ainsi que sur les sources d'incertitude. En particulier, la variabilité interne irréductible du climat doit être prise en compte dans l'évaluation des dangers naturels. Sinon, il y a un risque de surestimer l'importance des impacts prévus du changement climatique.

For hazard analysis, scenario design and mitigation there is a need to accurately and objectively predict the volume of debris flows. One approach is to base the calculation on rainfall properties. Herein we present an analysis of rainfall and debris-flow volume using data from the Illgraben catchment in Switzerland. The Illgraben debris-flow observation station, operated starting in the year 2000, has successfully recorded 75 debris flows and debris floods, with volume and bulk density estimates available for most of these events since 2000 and 2004, respectively. Here we describe results for 52 debris flows with sufficient data. Runoff coefficients determine the proportion of precipitation discharged from a catchment and support estimates on flow magnitudes. For each debris flow, runoff coefficients were determined by considering the event rainfall and the water contained in the debris flow. The events can further be characterized by the 14-day antecedent wetness. Runoff coefficients comprise a wide range from near 0 to close to 1. Clear trends are apparent, such as larger runoff coefficients during the snowmelt season. Furthermore, the debris-flow volumes are more sensitive to the antecedent rainfall than to the rainfall amount that triggered the event, likely because a wet channel bed enhances entraining. This study gives insights on which climate variables control the debris-flow volume. This will be further investigated and incorporated into the SedCas (Sediment Cascade) model (Bennett et al., 2014) to improve prediction of debris-flow activity.