E3S Web of Conferences 415, 01010 (2023)
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https://doi.org/10.1051/e3sconf/202341501010

Entrainment maps considering hydrological conditions formass movement runout modelling: application to debris-flowbulking at Pizzo Cengalo
Jacob Hirschberg1,2*, Brian W. McArdell1, Anna L. Könz1,4, Marc Christen3, Peter Molnar4, and Perry Bartelt3
1

Swiss Federal Research Institute for Forest, Snow and Landscape Research WSL, CH-8903 Birmensdorf, Switzerland
Geological Institute, ETH Zurich, CH-8092 Zurich, Switzerland
3WSL Institute for Snow and Avalanche Research SLF, CH-7260 Davos, Switzerland
4Institute of Environmental Engineering, ETH Zurich, CH-8093 Zurich, Switzerland
2Abstract. 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 withnumerical 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 fromrock 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. Suchhydrologically-informed entrainment maps will be useful to assess the probability of certain runout
distances.

1 Introduction
Debris flows can significantly grow in size asmaterial is entrained along their flow path (e.g., [1]). The
flow may grow by entraining material from the bed orby bank collapse, but the exact mechanism and how it
affects the flow is still debated [2]. Therefore, numericalmodelling for hazard and risk assessment remains achallenging task. Models neglecting erosion may
misestimate peak discharge, and the locations andextents of channel overtopping [3].
Theoreticalwork,large-scalelaboratory
experiments and field studies have shown theimportance of the degree of water saturation forsediment entrainment [4]–[7]. All studies support thetheory that positive pore pressures in the sediments
being entrained aid in entraining material when basal
sediments are overridden by the flow. Other types oflandslides, such as rock avalanches, are also affected by
the degree of saturation along the flow path as theirmobility can be significantly higher when flowing overa saturated substrate [8].
In rare yet destructive cases, a process transition
from rock avalanche to debris flow has been reported(e.g., [9–11]). At Pizzo Cengalo, Switzerland, two majorrock avalanches occurred in December 2011 and August
2017. The earlier of the two deposited sediment in theupstream reaches of the Bondasca valley (Fig. 1). The
later rock avalanche (3x106 m3) entrained glacial ice andalso sediments with interstitial water from the earlier
deposits. This stored water likely played an importantrole in the process cascade [11]. In other cases,
additionally the entrainment and melting of snow may
be relevant for increasing saturation of the flow [9].
Therefore, to improve the hazard and risk assessment ofmass movement runout, there is a need for an objective
method to define numerous zones, each withhomogeneous properties, to describe the entrainabilityof the sediment. To this end we produce “entrainmentmaps”, which are characterized by static properties suchas soil depth or hydraulic conductivity, but also byvariables such as soil water content or snow waterequivalent which can be predicted using hydrologicalmodels. We use publicly-available data on land coverand lithology to characterize the entrainment zones anddetermine entrainment hot spots. Hydrologicalmodelling (e.g., [12]) will be used to assess probabilities
of saturated conditions. The entrainment maps serve asinputs for runout modelling, herein with RAMMS, toconstrain the entrainment with information on* Corresponding author: jacob.hirschberg@erdw.ethz.ch© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0(https://creativecommons.org/licenses/by/4.0/).

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saturation, land cover and lithology. We test ourframework at Pizzo Cengalo because it is well
documented (see [11]–[13]).

mins), corresponding to a moving momentum of ~10%of the maximum value.
We used two end-member scenarios to describe theerodibility of the alluvial sediment on the valley bottom:
dry sediment and wet/loose saturated sediment as
described in [17]. Experience from RAMMS users
indicate that these end-member entrainment scenarios
are generally useful at other field sites. However,additional research is being conducted in a parallel
project to better constrain the erodibility of sediment
related to the water content.

2 Methods
The numerical model RAMMS [14] is used tocompute the debris-flow runout. RAMMS treats thedebris flow as a one-phase fluid and solves 2D depthaveraged equations for mass and momentum
conservation. The Voellmy frictional relation is usedherein. Hence, the two parameters for Coulomb friction(μ) and turbulent friction (ξ) need to be calibrated. The
flow initiates either as single or multiple user-definedlandslide releases or hydrographs. RAMMS has anerosion module which relates the maximum erosion
depth to maximum shear stress [3]. The final erosion
depth can be additionally constrained if e.g. the depth to
bedrock is known. The terrain is not updated during thesimulation. Although RAMMS also has a rockavalanche module, we focus on the debris-flow moduleand model two end-member scenarios of debris flow
entrainment for a flow starting from the toe of the 2017rock avalanche deposit.
We use publicly available data for Switzerland,provided by the Federal Office of Topography(swisstopo), to produce entrainment maps: a land covermap (LC) and a geo cover map (GC). LC divides surface
features into 14 classes (e.g., forest, scree, glacier,bedrock, etc.) with an accuracy of <3 m and is updated
every ~6 years. Hence, dynamic features such as glacierand forest outlines are accurately represented and preand post-conditions of rare events can be analysed (e.g.,mass movement deposits). GC is not as accurate anduses smoothed outlines. However, it is based on theGeological Atlas of Switzerland [15] and provides
information on the lithosphere (e.g., bedrock, mass
movement deposit, alluvial deposit, etc.). We used
QGIS to combine LC and GC. This helped to constrain
e.g. the max erosion depth (Fig. 1). For example, thedepth to bedrock must be shallower if GC is bedrockcompared to a rock avalanche deposit. Furthermore, GC
could potentially be used to roughly characterize soil
water storage and soil hydraulic properties.
Simulations with RAMMS were made on a 2m grid,corresponding to the native resolution of the DTM, andwithin a small region constructed to have an aerial extent
somewhat larger than that of the observed flow path (thecomputational domain; Fig. 1A). Because the details of
the initial debris flow leaving the rock avalanche deposit
are not well constrained, we iteratively tried several
volumes until we converged on a plausible estimate of
50,000 m3. The model was setup with an input
hydrograph with a maximum discharge corresponding
to the envelope curve for events of this volume [16].
Because the GC map is provisional, and to demonstrate
the concept, we used the outline of the alluvial sedimentat the valley bottom to set the extent of the erodible area
(red polygon in Fig. 1A). Downstream of the erosion
polygon, the flow enters a bedrock gorge before entering
the village Bondo. We do not consider erosion within
the gorge. Simulations were run for 3000 seconds (50Fig. 1. Overview of the Bondasca basin spanning from Pizzo
Cengalo to the village of Bondo. A) Modelling domain usedfor debris flow simulation with RAMMS with a hydrographinput at the toe of the 2017 rock avalanche deposit. B)
Entrainment map with max erosion depth for mass movementsin the Bondasca valley. These depths were inferred by using
the combined LC/GC information. The red line shows thecatchment outlines and the blue line the modelling domain
which would be considered for a rock avalanche with atransition to a debris flow using RAMMS.

3 Results and Discussion
The scenario with saturated sediment eroded 3-4 mof the alluvial deposits along the flow path, while theunsaturated scenario typically eroded < 1 m (Fig. 2). The
amount of additionally entrained material in the wet bed
is significant and the provisional entrainment map
confirms that these amounts of erosion are possible (Fig.

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1B). As seen in the downstream depositional area, theconsequences of the two scenarios are also significantly
different (Fig. 3). In the dry scenario, most sediments
remain in the retention basin just upstream of the bridgeat the basin outlet. In the wet scenario, however, theretention basin is smaller than the debris-flow volumeand parts of the village are inundated.
These differences highlight the need of delineatingareas of entrainment. Frank et al. [3] showed that such

Fig. 2. Modelled erosion pattern for end-member entrainment
scenarios: A) dry alluvial sediment, erosion depth up to 1.5 m;and B) wet alluvial sediment, with a maximum erosion depth
up to 9.2 m.

Fig. 3. Modelled maximum flow depth near Bondo village, forend-member entrainment scenarios: A) dry alluvial sediment;and B) wet alluvial sediment.

amounts of erosion are possible when the bed is exposedto the magnitude of maximum shear stress simulated
here. However, to improve debris-flow hazard
assessment, further developments need to be done toquantify probabilities of hydrological conditions
enhancing such erosional events, i.e. the likelihood ofhigh soil saturation. This will decrease the uncertainties
in hazard assessment.

4 Conclusions and Outlook
We have presented a framework to include
entrainment maps for more objectively constrained
erosion in numerical runout modelling of mass
movements. Because the work is ongoing and not yet
incorporated into the RAMMS runout model, weillustrated two scenarios representing wet and dry
conditions for debris flows initiating upstream of thevillage of Bondo. We have planned a series of next steps
which include:

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https://doi.org/10.1051/e3sconf/202341501010

Fully developing the entrainment maps in a
general way and then specifically into RAMMS.
Improving the empirical erosion-depth relation
by studying a series of well-documented eventswith erosion data at Illgraben, Switzerland.
Setting up a hydrological model to obtain
estimates of duration curves for soil water
saturation and snow water equivalent(analogous to flow-duration curves for riverdischarge).
Applyingthehydrologically-informed
entrainment map concept to the village ofKandersteg, Switzerland, where citizens andinfrastructure are threatened by a potential
cascading process starting with a large landslidefrom Spitze Stei.
Exploring climate change impacts on theduration curves and therefore on theprobabilities of certain runout distances.

11. F. Walter, F. Amann, A. Kos, R. Kenner, M.
Phillips, A. de Preux, M. Huss, C. Tognacca, J.
Clinton, T. Diehl, Y. Bonanomi., Geomorphology,351, 106933 (2020)
12. S. Demmel, Water Balance in Val Bondasca
Initial hydrological conditions for debris flows
triggered by the 2017 rock avalanche at Pizzo
Cengalo, Master Thesis, ETH Zurich, 50 (2019)
13. WSL, SLF Gutachten G2017.20: Modellierungdes Cengalo Bergsturzes mit verschiedenen
Rahmenbedingungen, Bondo , GR, available at:https://www.gr.ch/DE/institutionen/verwaltung/diem/awn/dokumentenliste_afw/SLF_G2017_20_Mo
dellierung_Cengalo_Bergsturz_030418_A.pdf,(2018)
14. M. Christen, Y. Bühler, P. Bartelt, R. Leine, J.
Glover, A. Schweizer, C. Graf, B.W. McArdell,W. Gerber, Y. Deubelbeiss, T. Feistl, and A.
Volkwein, Integral Hazard Management Using a
Unified Software Environment Numerical
Simulation Tool ‘RAMMS’, in 12th Congress
Interpaevent, 77–86 (2012)15. J. H. Gabus, M. Weidmann, P. C. Bugnon, M.
Burri, M. Sartori, and M. Marthaler, Feuille 1287
Sierre—Atlas géologique de la Suisse 1: 25 000”,111 (2008)
16. D. Rickenmann, Nat. Hazards, 19, 47–77, 1 (1999)
17. P. Bartelt, RAMMS:: DEBRIS FLOW User
Manual v1. 7.0, available at:https://ramms.slf.ch/ramms/downloads/RAMMS_
DBF_Manual.pdf, (2017)

This study was partly funded by the WSL research programme
CCAMM (Climate Change Impacts on Alpine Mass
Movements).

References
1.

C. Berger, B. W. McArdell, and F. Schlunegger,Geomorphology, 125, 421–432, 3 (2011).
2. O. Hungr, S. Mcdougall, and M. Bovis,
Entrainment of Material by Debris Flows, inDebris-Flow Hazards Related Phenomena, 135–155 (2005)
3. F. Frank, B. W. McArdell, C. Huggel, and A.
Vieli, Nat. Hazards Earth Syst. Sci., 15, 2569–2583, 11 (2015)
4. R. M. Iverson, M. E. Reid, M. Logan, R. G.
LaHusen, J. W. Godt, and J. P. Griswold, Nat.
Geosci., 4, 116–121, 2 (2011)
5. S. W. McCoy, J. W. Kean, J. A. Coe, G. E.
Tucker, D. M. Staley, and T. A. Wasklewicz, J.
Geophys. Res. Earth Surf., 117, 3 (2012)
6. J. Hirschberg, B. W. McArdell, A. Badoux, and P.
Molnar, Analysis of rainfall and runoff for debris
flows at the Illgraben catchment, Switzerland, in
Debris-Flow Hazards Mitigation: Mechanics,
Monitoring, Modeling, and Assessment Proceedings of the 7th International Conference on
Debris-Flow Hazards Mitigation, 693–700 (2019)
7. J. Aaron and S. McDougall, Eng. Geol., 257,105126 (2019)
8. K. Sassa and G. hui Wang, Mechanism oflandslide-triggered debris flows: Liquefaction
phenomena due to the undrained loading of
torrent deposits, in Debris-flow Hazards andRelated Phenomena, 81–104 (2005)
9. A. Hauser, in Catastrophic Landslides (GeologicalSociety of America, 2002)
10. C. Huggel, Quat. Sci. Rev., 28, 1119–1130, 11-12(2009)

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