Dr. Perry Bartelt

This study investigates the runout and depositional behavior of the Tangni debris flow in the Garhwal Himalaya, India, through a series of controlled experiments conducted at the newly developed facility at CSIR-Central Building Research Institute, Roorkee. The experiments focused on evaluating the influence of water content, initial volume, and grain size distribution on debris flow dynamics. Debris flow experiments reveal that small changes in water content can trigger abrupt transitions in flow regimes, significantly altering runout distances and deposition patterns. Additionally, dimensionless parameters were calculated to characterize flow regimes, and granulometric analysis was performed on the deposited material. The results show that runout distance and deposition area increase with higher water content and larger initial volumes, whereas finer content reduces runout. Granulometric analysis revealed a clear segregation of coarse particles, with enrichment at the margins and towards the flow front, indicating that coarse particles enhance the destructive potential of debris flows. Dimensionless analysis identified the experimental flows as predominantly frictional in nature. The findings demonstrate consistency with natural debris flows and align with global experimental studies, providing valuable insights into the behavior of debris flows in the Indian Himalayas. Despite limitations due to scaling effects and reconstruction challenges, this study highlights the importance of experimental approaches in advancing our understanding of debris flows, particularly in regions lacking extensive historical data and monitoring infrastructure.

The Indian Himalayan region is the origin of numerous natural hazards, including landslides, earthquakes, floods, cloudbursts, etc. (Dash et al. 2021; Falae et al. 2021; Kanungo and Sharma 2014). Uttarakhand, located in the northwest Indian Himalayas, is one of the most landslide-prone states in India. In a recently published report by the National Remote Sensing Centre (NRSC) India, all the 13 districts of Uttarakhand state are severely affected by landslides and the Chamoli district ranks 3 among 13 districts of Uttarakhand and ranks 19 among 147 landslide-prone districts in the country according to the landslide density (Jain et al. 2023). Over the past three decades, Chamoli has experienced several destructive mass movement events, including the 2013 Kedarnath tragedy, the Chamoli rock and ice avalanche on February 7, 2021, land subsidence in Joshimath during 2023, etc. In 1999, Chamoli was struck by an earthquake with a magnitude of 6.8 on the Richter scale, with its epicenter near Gopeswar township. In addition to landslides and earthquakes, Chamoli has also faced numerous disasters caused by cloudbursts and flash floods. National Highway 58 connects Uttarakhand with the rest of the country, entering Chamoli district through Karnaprayag and extending to Badrinath. This highway passes through the Alakananda Valley, traversing many landslide-prone zones. In a recent study, Ramiz et al. (2023) found that about 27% of the areas along the highway corridor from Rishikesh to Badrinath is highly susceptible to landslides. Frequent landslides, including debris flows, rockfalls, debris slides, and subsidence, disrupt traffic and deposit materials in the river, increasing the likelihood of river damming (Dash et al. 2022, 2023) and traffic disruption. A similar traffic disruption occurred due to a rock avalanche near Patalganga Langsi Tunnel on the Badrinath Highway of Chamoli district on July 10, 2024. This is an area known for frequent rockfall, and debris slide events, as noted by earlier researchers.

Glide avalanches present a significant and repetitive challenge to many operational forecasting programs, and they are likely to become more frequent. While the spatial location of glide release areas is extremely consistent, the onset of glide avalanche release is notoriously difficult to forecast, and their destructive potential can be immense. Thus, the timing and dynamics of glide avalanches is an important area of study. To better understand these processes, and to improve assessments of risk to transportation corridors and infrastructure, event documentation is key. Here, we survey a large glide avalanche event along the Going-to-the-Sun Road in Glacier National Park, Montana, USA, during road opening operations in the spring of 2022. Using three sets of terrestrial lidar data (pre-event, post-event, and snow-off), we quantified key aspects of the avalanche and created powerful visualizations for analysis. Further, we evaluated meteorological data from automated weather stations between the onset of glide cracking and avalanche release. Last, we synthesized lidar data with a numerical dynamics model to replicate the event in a simulated environment. Using the tuned model, we determined the critical mean snow depth in the release area necessary for an avalanche to reach the road (4.2 m). Our method may be of particular use for glide avalanches, which tend to release in roughly the same place and time each year at a known interface. This could make the calculated critical depths more consistently reliable and preclude the need for additional tuning in dynamics models. As 1) lidar technology continues to improve and reduce in cost, 2) transportation corridors continue to extend into avalanche terrain, and 3) glide avalanches potentially become increasingly frequent, the synthesis outlined here provides a valuable tool for operational forecasters considering infrastructure threatened by glide events.

This paper explores the application of grain flow theory to snow avalanche dynamics, focusing on the interrelation between shear stress and fluctuation energy. The study employs a system of differential equations to model the mean velocity (U) and fluctuation energy (R) within snow avalanches. The key physical constraint highlighted is the relationship dR · S = −R₀ · dS, which provides a physical constraint on the  omplex relationship between avalanche shear stress and the production of fluctuation energy. When fluctuation energy is produced by shearing, it generates not only directionless random kinetic energy but also directional energy fluxes that alter the configuration of the granular ensemble, leading to changes in shear stress. The analysis of the R-U phase plane reveals that avalanche behavior can be characterized by equilibrium points that shift with slope angle, highlighting the role of fluctuation energy in determining the flow regime. The R-U phase plane not only advances our understanding of avalanche dynamics but also facilitates the examination of flow regime transitions, driven by changes in the potential energy of the granular ensemble, and the emergence of different avalanche types.

Die Ereignisse Ende Juni 2024 haben gezeigt, dass neue, konsistente Methoden zur Bewertung von Murgang- Schutzmassnahmen benötigt werden. Die Wahl geeigne­ter Gefahrenszenarien und die Modellierung der Mur­gänge sind zentral, um Schutzmassnahmen effektiv zu planen. Ein neues numerisches Zwei-Schichten-Modell, das feste und flüssige Phasen trennt, wurde eingesetzt, um die komplexe Dynamik von Murgängen besser nachzu­bilden. Zwei Fallstudien im Val Greva (GR) und in Sorte (GR) zeigen realistische Ergebnisse und verdeutlichen die Bedeutung der Erosion für die Mobilität von Mur­gängen. Die Ergebnisse weisen darauf hin, dass künftige Schutzmassnahmen differenziertere Informationen zum Fliessverhalten erfordern. Eine stetige Verbesserung der Modelle durch eine gründliche Analyse vergangener Er­eignisse ist entscheidend, um die Genauigkeit und Zu­verlässigkeit der Gefahrenbewertung zu gewährleisten.

Predicting snow pressure forces exerted by the snow cover on structures on sloping terrain remains a challenging task. Especially with the increasing interest in alpine solar parks with little financial margin for safety, the demand for monitoring systems as well as accurate prediction models for snow pressure acting on slender supports is higher than ever before. This paper presents an experimental setup for measuring the reaction forces of the snow cover on various support and pressure bars of an snow supporting structure made of steel using strain gauges. In combination with the material properties and the entire static system of the structure, we can back calculate the pressure exerted by the snow cover. In order to interpret the measured forces correctly, additional field campaigns in winter are important to determine the local snow distribution, the snow temperature and the density of the snow cover. We extensively address challenges encountered during the measurement campaign, including eliminating temperature-induced strain, amplifying the signal in low strain ranges, handling combined bending and restraint stresses, and protecting sensors and cables against settlement and creep forces. Having overcome these challenges, the key advantages of using strain gauges are that the system is cost effective and non-invasive and therefore allows rapid installation on a large number of sections of interest. We discuss results obtained from the first winter of the campaign (2023/2024). The high measurement frequency of one measurement every five minutes provides an insight into the daily cycle of the forces. Most notably, on warm spring days with cold nights, we observed a continuous increase in forces starting at sunset, peaking at sunrise, followed by a rapid decline thereafter. The measurement data can be used to calibrate newly developed viscoelastic 3D snow creep models with various constitutive laws for the prediction of creep and glide forces on supporting structures. These models as well as the presented experimental setup show great potential to further optimise the design of supporting structures and installations of alpine solar parks.

We present a first attempt of probabilistic event-based rockfall simulations with RAMMS::Rockfall for deriving continuous intensity-frequency curves at the base of the slope. The simulations are based on a probabilistic definition of rocks and their properties in the release area. The combination of the simulations and the trajectory probabilities is used for determining the hazard at several return periods and for calculating continuous intensity-frequency curves. The results of this probabilistic rockfall hazard modelling are significantly different compared to the current approaches, where all possible rocks with only a specific release volume are considered.

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.

Glacier lake outburst floods (GLOFs) initiate with the rapid outburst of a glacier lake, endangering downstream populations, land, and infrastructure. The flow initiates as a mud flow; however, with the entrainment of additional solid material, the flood will often transform into a debris flow. As the run-out slope flattens, the coarse solid material deposits and the flow de-waters. The flow transforms back into a muddy, hyperconcentrated flow of fine sediments in suspension. These flow transitions change the flow composition dramatically and influence both the overall mass balance and flow rheology of the event. In this paper, we apply a two-phase/layer model to simulate flow transitions, solid–fluid phase separations, entrainment, and run-out distances of glacier lake outburst floods. A key feature of the model is the calculation of dilatant actions in the solid–fluid mixture which control flow transitions and phase separations. Given their high initial amount of fluid within the flow, GLOFs are sensitive to slope changes inducing flow transitions, which also implies changes in the flow rheology. The changes in the rheology are computed as a function of the flow composition and do not need any adaptation by ad-hoc selection of friction coefficients. This procedure allows the application of constant rheological input parameters from initiation to run-out. Our goal is to increase the prediction reliability of debris flow modeling. We highlight the problems associated with initial and boundary (entrainment) conditions. We test the new model against the well-known Lake 513 (Peru, 2010), Lake Palcacocha (Peru, 1941), and Lake Uchitel in the Aksay Valley (Kyrgyzstan) GLOF events. We show that flow transition modeling is essential when studying areas that have significant variations in slope.

The rapid melting of glaciers and thawing of permafrost in mountainous regions have heightened the danger of rock-ice avalanches. These avalanches pose a severe threat due to their potential to transform into water-saturated debris flows. The catastrophic event in Chamoli, India, on 7 February 2021, illustrates the devastating consequences of such processes. Developing a model capable of predicting the dynamics and extent of these events is imperative for natural hazard science and disaster mitigation. In response, we propose a depth-averaged rock-ice avalanche model encompassing four distinct materials: rock, ice, snow, and water. The model integrates crucial physical processes, including frictional heating, phase changes, ground material entrainment, and air-blast hazards. Through a system of mass and momentum balance equations extended with grain flow and internal energy equations, the model captures heat exchanges and resulting phase changes as the fragmented material flows. Focusing on identifying the primary water source in the flow and testing the model on the 2021 Chamoli event, we quantify water's influence on flow dynamics and regime transitions. However, uncertainties persist in heat transfer physics and quantifying the hydro-meteorological state of the flow path. Our thermo-mechanical model enables the simulation of complex avalanches and identifies key flow transitions: powder cloud formation and potential debris flow transformation. The study underscores the pivotal role of water in avalanche dynamics and the challenge of accurately quantifying water content within the flow, necessitating comprehensive ground assessments for effective disaster management.

Flow transitions from rock avalanches to multi-material flows and water saturated debris flows are frequently observed. In 2017, a rock mass of Piz Cengalo (CH) collapsed on a glacier triggering a rock/ice avalanche that resulted into a series of debris flows. At Flüela Wisshorn (CH), in 2019, a rock face collapsed in winter, resulting in a snow avalanche. These transitions depend on the composition of the release and entrainment zones, and on the terrain as ice and snow can melt via frictional heating, increasing the flow water content.
Here, we compute the water content and localisation for the Piz Cengalo event depending on the input parameters. We show that water localizes at the front of the flow, favoring a transition to a debris flow. At Flüela Wisshorn, we show the transition from a rock/snow release to a snow avalanche. We highlight the importance of field and remote sensing data for models, as entrainment is critical for the simulations' outcome and hazard assessment.

Between January 6 and 15, 2019, South Tyrol, Italy, experienced a series of remarkably large and infrequent powder snow avalanches, marking some of the most significant occurrences in the region over the past five decades. These avalanches, characterized by their immense scale, decimated 200-year-old trees, left alpine huts in ruins and destroyed avalanche protection structures. Fortunately, no human casualties were reported. The relentless snowfall, which persisted for 17 days, was exacerbated by persistent northwesterly winds at high altitudes, resulting in an accumulation of 1.3 to 2.5 meters of new snow above the timberline along the eastern main ridge of the Alps. With consistently low temperatures in the first half of January and the lingering effects of unfavorable snow cover from early winter, the avalanche threat intensified. Several large avalanches occurred on January 14, when the perilous conditions escalated to an avalanche danger level of 4 along the northern border ridge with Austria. In nearby regions of Tyrol, Austria, the avalanche danger level reached 5.
In this paper, we compare 100-year calculation scenarios with an extreme powder snow avalanche from 2019. Our goal is to test existing hazard mapping procedures to determine how advanced avalanche dynamics models can be effectively employed to predict extreme avalanche hazards. Rather than  backcalculating the documented avalanche, we adopt the approach of a hazard engineer who must construct a hazard map without reference data, relying mainly on historical snow and weather data from the region. We conclude that it is possible to expand existing avalanche calculation procedures that utilize statistical extreme value snow cover data to include snow temperature and snow cover distribution.

Am 14. April 2024 um 06:56 Uhr ereignete sich in der Westflanke des Piz Scerscen (Berninamassiv, Engadin, Graubünden) auf einer Höhe von 3640 m ü. M. ein grosser Bergsturz. Rund 5.5 Millionen m³ Fels und Gletschereis lösten sich, stürzten auf den darunter liegenden Vadret da Tschierva und rissen in der Sturzbahn eine dicke Schneedecke und grosse Mengen Gletschereis mit sich. Dieses Gemisch aus Gestein, Eis und Schnee floss über das Gletscherplateau, durch die darunterliegenden Eisfälle und zwischen den Seitenmoränen des Gletschers hinunter und erzeugte eine grosse Staubwolke, bevor es sich auf rund 2100 m ü. M. im Val Roseg, fast 6 km vom Anriss ablagerte. Das Ereignis forderte glücklicherweise keine Opfer und verursachte keine Infrastrukturschäden. In diesem Bericht beschreiben wir die Bedingungen, die zum Zeitpunkt des Ereignisses herrschten und nutzen die verfügbaren Informationen, um die Prozesse zu analysieren, die vor und während des Ereignisses stattfanden.

Avalanche engineers use scenario-based simulations to predict avalanche runout and quantify impact  ressures. An important input parameter for such simulations is the avalanche return period. In Switzerland, 10-, 30-, 100-, 300- and > 300-year avalanche return periods are taken into account for hazard assessment. Another important input parameter is the fracture depth which is determined with a procedure developed by SLF in 1990. Presently, the procedure provides no methodology to include snow entrainment, snow temperatures or snow density. This limitation hampers the application of advanced models that incorporate snow entrainment.
The fracture depth is based on the determination of measured 3-day snow height increase using extreme
value statistical approaches. The statistical values are modified to include the effects of altitude, snow drift accumulations and terrain (slope angle). The procedure provides fracture depths d0 for e.g. 10-, 30-, 100- and 300-year avalanche return periods. In this paper, we modify this well-known SLF procedure to determine snow entrainment depths d0* (erodible snow) which are associated with measured 3-day snow height increase. The erodible snow along the track is modified including altitude gradients and the slope angle.
Within the framework of the proposed methodology, we demonstrate how to specify snow temperatures that are suitable for typical winter storms in the Alps, depending also on the altitude of the release area. These recommendations are based on snow profiles recorded during storm periods with heavy snow fall of February 1999 and January 2018, 2019 and 2021. The final component of the procedure is to provide a realistic snow density for the fracture slab.
The procedure is straightforward, easily integrated into existing workflows, and benefits from relying on measurement data, ensuring realistic predictions of entrainment and deposition heights. Crucially, this method enables the examination of avalanche runout in a shifting climate marked by rising temperatures.

On 25 April 2015, the Gorkha earthquake triggered a large rock-ice avalanche and an air blast disaster in the Langtang Valley, Nepal. More than 350 people were killed or left missing. Here we reconstruct the evolution of the Langtang avalanche-air blast using field investigations and numerical modeling and examine the influence of two primary climate-related phenomena: snowfall anomalies and warm temperatures. Our findings suggest a deep snow cover fosters the formation of a dispersed avalanche, which increases the mobility and destructive power of the powder cloud air blast. Elevated air temperatures intensify meltwater production and lubricate the flowing mass. Both mechanisms contributed to the Langtang disaster. Our study underscores the essential impact of snow cover and air temperature on the risk assessment of high-altitude rock-ice avalanches, highlighting how seasonal and climatic variations affect avalanche runout and air blast dynamics.

Rock avalanche-induced air blasts are widespread, damaging, and deadly. They can add to the destructive potential of avalanches far beyond the avalanche zone, but no landslide risk assessment in practice to date has accounted for the potential air blast danger. Here, field investigations and numerical studies were employed to quantitively analyze the initiation and propagation mechanism of air blasts triggered by the 2008 Wenjia Valley rock avalanche in Sichuan, China. Our findings indicate that the most significant air blast triggered by the Wenjia Valley avalanche was near bends in the valley, with a maximum pressure of over 25 kPa and a maximum velocity of 73 m/s. The avalanche violently collided with the valley wall at bends, generating multiple destructive air blasts and avalanche deflection. Subsequently, the separated air blast propagated as inertia flows and caused huge forest destruction. A systematic parametric study combined with case studies was further performed to investigate the possible contribution of topography and sliding mass properties to the air blast power. Large avalanche volume and high velocity both appear to be necessary conditions to generate a destructive air blast, while the sudden topography change is also greatly influential. Our work provides new insights into the initiation and propagation of rock avalanche-induced air blasts, compelling to consider this sort of cascading effect during landslide risk assessment in mountainous regions.

Snow avalanche run-out is controlled by flow regime, which is heavily dependent on snow temperature and water content. Existing avalanche models calculate temperature change and snow melting arising from frictional work, snowcover entrainment and particle collisions, but ignore the influence of the ambient air temperature. Here, we propose an experimentally-based relationship to describe the sensible heat flux between the flowing avalanche and the ambient air. A snow avalanche case study and a sensitivity analysis are performed using the proposed model. Modeling results suggest a marginal contribution of heat to the avalanche core, but one, that nonetheless can have significant effect on avalanche runout. For wet (warm) avalanches, higher air temperature will amplify water lubrication effects, leading to longer avalanche run-out. Warmer air temperatures also influence the behaviour of dry, cold avalanches, as the presence of meltwater increases snow cohesion, restricting the formation of strong powder clouds and reducing the avalanche run-out. Colder air temperatures facilitate the formation of more fluidized powder snow avalanches with long run-out and strong air-blasts. The proposed model quantifies the temperature change in the avalanche and can be included in avalanche hazard assessments in which temperature and flow regime are important elements, including the understanding of air temperature and avalanche flow in a changing climate.

Calculating contact/impact pressures with numerical finite element software remains a difficult task. It is especially difficult for highly compactable, plastic materials where the elastic fraction of the strain is very small. This is the case in most impact problems in natural hazards. One example is the impact of rockfall dams by large, rotating rocks. Another is the impact of pylons, walls and other obstacles by snow avalanches. We embed work-energy methods within numerical avalanche and rockfall models to make the calculation of impact pressures in natural hazards more applicable for engineering practice. Firstly, we can greatly reduce the computation time and secondly, the input parameters are much more intuitive for practitioners due to the use of purely plastic compactive material behaviour.

Extreme rainfall intensities, degrading permafrost and glacier melt in combination with ongoing construction of hydropower plants and settlement growth are leading to an everincreasing amount of mass movements in alpine terrain. Geologically young mountain ranges such as the Indian Himalaya are experiencing severe consequences due to the combination of climatic changes and anthropogenic expansion, leading to higher risk for human lives and infrastructures. We present an approach to generate hazard indication maps of mass movements in high alpine areas using a combination of remote sensing and numerical simulations. We use satellite radar interferometry from Sentinel-1 and geomorphological feature classification based on optical satellite data. We show two exemplary case studies and model one of these to assess its hazard potential using the newly developed RAMMS::ROCKICE module.