E3S Web of Conferences 415, 02002 (2023)
DFHM8

https://doi.org/10.1051/e3sconf/202341502002

Simulations of the occurrence of runoff-generated debris flows
by means of hydrological models in headwater rocky basins
Martino Bernard1*, Matteo Barbini1, Leonardo Battistel2, Matteo Berti2, Alessandro Simoni2, and Carlo Gregoretti1
1University of Padova, Land Environment Agriculture and Forestry Department, 35020 Legnaro (PD), Italy
2University of Bologna, Biological, Geological and Environmental Sciences Department, 40126 Bologna, Italy

Abstract. The simulation of the occurrence of the runoff-generated debris flows can be approached bymeans of hydrological models. In this work, we show that a rainfall-runoff model designed for the simulationof runoff in headwater rocky basins can capture both the transit timing of the first debris-flow surge and its
hydrograph. We successfully compared the stage hydrograph of debris flows with that of the simulated
runoff in two headwater rocky basins of Dolomites.

1 Introduction
In the Dolomites area (Eastern Italian Alps), sub-vertical
rocky cliffs generate notable discharges during summer
thunderstorms, often triggering debris flows on thescrees at their base. Cliffs are incised by several chutes
where runoff usually concentrates. At their base, debris
flow channels start, originated by the erosive activity ofboth runoff and mass transport phenomena. The
forecasting of such events has great significance for
reducing damages and victims in the exposed areas.
Predictions could be performed by the combined use ofhydrological models and debris-flow triggering
thresholds, distinctive for each watershed. In fact,according to [1], rainfall-runoff models can emulate thetiming of debris-flow transit. Herein, we show that themodel of [2] can approach the hydrograph of the firstdebris-flow surge, downstream of the initiation area ofdifferent scale basins in a dolomitic environment.

runoff in the considered basin, are the curve number CN,
the infiltration rate fC, the along-slope velocity U and the
Gauckler-Strickler coefficient KS.
The model has been calibrated against runoff
discharges estimated at the outlet of a channel incised ona rocky cliff, not too far from the investigated basins(Dimai catchment in the inset of Figure 1). All the valuesof the parameters are shown in Table 1. The initial
abstraction Ia of the SCS-CN method is assumed equal
to 0.1S (S is the potential maximum retention and it
depends on CN). The value of fC, in the case of rocky
terrain, is provided by the following equation [4]:fC = 3.12 - 0.15 P(1)

where P denotes the cumulated rainfall recorded in the
2 days preceding the event (in mm). This relation iseffective only for AMC I events.
Table 1. Calibrated parameters for the hydrological model.

2 Material and methods
2.1 The rainfall-runoff model
The rainfall-runoff model of [2] is a distributedhydrological model that computes the excess rainfall
and routes it to the outlet for each cell of the digital
elevation model of the considered catchment. The flow
path is subdivided into slope and channel paths. Alongslope paths, it is assumed a constant velocity, U,depending on the terrain land use, whereas alongchannel paths the routing is modelled using the matcheddiffusivity kinematic model of [3]. Excess rainfall iscomputed through either a simplified Horton’s law
when rainfall intensity exceeds infiltration rate fC or byusing the SCS ‐ CN method. The model parameters,
which refer to the generation and the propagation ofParameter

Rockysurface

Mountainpine slopes

Screeslopes

CN

90.4

61

65-70

U (m/s)

0.7

0.05

0.1

KS (m1/3/s)

99

9fC (cm/hr)

Eq. (1)

5.5

10.8

2.2 The debris-flow sites with the monitoring
activities
The debris-flow monitored sites are those of Rovina diCancia (hereinafter Cancia) [5] and Rio Gere [4,6]. In
these sites, two monitoring stations are operating since2014 and 2021 respectively. The two stations are* Corresponding author: martino.bernard@unipd.it© 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/).

E3S Web of Conferences 415, 02002 (2023)
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Table 2. Morphological features of the monitoredcatchments.

positioned in the upper part of the catchments, justdownstream of the initiation area of the debris flows.
Both stations are equipped with a rain gauge, flow levelsensors and cameras. The sampling interval of all
sensors but the cameras is five minutes. If the rainfall
depth estimated at intervals of 2.5 minutes overpasses
the cumulative threshold value of 0.6 mm, the samplinginterval decreases to five seconds for the following twohours and cameras start a continuous image acquisition.
The monitored headwater basins represent the typicalsizes of dolomitic watersheds, ranging in the interval 0.5– 1.0 km2 (their morphological features are resumed inTable 2). The presence of other standalone rain gauges
completes the instrumentations of the areas, allowing
better observation of the spatial distribution of rainfall
in the watersheds. Figure 1 shows the two basins withthe position of rain gauges and monitoring stations.

CanciaRio Gere

Area (km2)

0.65

0.93

Min elevation (m a.s.l.)

1662

1932

Mean elevation (m a.s.l.)

2213

2500

Max elevation (m a.s.l.)

3067

3220

Mean slope (o)

54.2

50.6

Max slope (o)

87.8

89.3

Channel mean slope (o)

36.5

34.3

Bare rock

50%

70%

Scree and active erosion

28%

23%

Moors and heathland

22%7%Land use

2.3 The recorded debris flows
Since their setting up, various debris-flow eventsoccurred in the monitored catchments. In the Cancia
basin, eight debris flows occurred since 2014 but only inthree cases, a stage hydrograph has been recorded: on
July 23rd, 2015; on August 1st, 2018; on July 1st, 2020. In
the Rio Gere catchment, one hyper-concentrated event
occurred on July 8th, 2021. In this work, we focused ourattention on the last three events because the debris flowthat occurred in Cancia on July 23rd, 2015, has been
analysed in detail in [5]. In Table 3, we indicate thecharacteristics of the precipitation, which triggered thereported debris-flow events, as recorded by themonitoring stations. Rainfalls have been identified assuggested by [7], i.e., storms with gaps between
consecutive rain gauge tips lower than 10 min.
Table 3. Characteristics of the precipitations that triggered
the phenomena occurred on August 1st, 2018; July 1st, 2020;
July 8th, 2021, as recorded by the monitoring stations. D andP indicate the duration and depth of rainfall, I the mean
intensity, IMAX,t the max intensity recorded in a t-minutes
interval, DTRIG and PTRIG the duration and depth of rainfall up
to the triggering of the hydrogeomorphic processes.

Fig. 1. Rio Gere (top) and Rovina di Cancia (down) basinsclosed at the triggering areas of debris flows with the positionof monitoring stations and standalone rain gauges. In theinsert, the location of the basins in the province of Belluno(Italy) with reference to the Dimai basin where thehydrological model was calibrated.

2

August 1st,
2018

July 1st,
2020

July 8th,2021D (h)1.08330.83332.0833P (mm)

37.8

18.2

29.6

I (mm h-1)

34.89

21.84

14.21

IMAX,5 (mm h-1)

129.6

96.0

81.6-1

IMAX,15 (mm h )

99.2

65.6

46.4

DTRIG (h)0.50000.50000.5833

PTRIG (mm)

30.2

17.2

13.6

E3S Web of Conferences 415, 02002 (2023)
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flow occurrence. An application could be the estimationof the solid-liquid hydrograph, after assuming acharacteristics value for the solid volumetricconcentration of the phenomenon: runoff contributing to
the debris-flow initiation and the corresponding solidliquid hydrograph could be determined and propagatedby means of debris-flow routing models. A reliable
estimate of entrainable sediment volume and,
consequently, of the potentially inundated areas isfundamental to hazard assessment and risk evaluation,
the design of appropriate structural countermeasures,and the development of efficient emergency
management regulation.

3 Results
In Figure 2, we plot the hydrographs simulated by therainfall-runoff model of [2] against the stagehydrographs recorded by the two monitoring stations.
The stage hydrographs were measured differently,
depending on the operative sensors at the time of theevents: in Cancia, stages have been derived by apressure transducer for the event that occurred on
August 1st, 2018 (Figure 2a), whereas by a video
reconstruction for the debris flow on July 1st, 2020(Figure 2b). For the hyper-concentrated flow that
occurred in Rio Gere on July 8th, 2021 stages have beenrecorded by a laser-level sensor. Each sensor has pros
and cons: the pressure transducer is quite reliable interms of the transit timing of an event but its recording
duration is generally short because it risks being torn off
by the phenomenon. The video reconstruction of adebris-flow event permits a correct detection of thetransit timing of an event but it is the least reliable interms of stage values due to the uncertainties indetermining the heights of the phenomenon; moreover,footages recorded at night are hardly usable. Lastly, thelaser sensor detects the timing with precision and thestages with continuity but it could give wrong heightvalues when the surface of flow is highly irregular.
The comparison between simulated discharges andrecorded stage hydrographs is made in terms of time andshape. The lag time between the peaks of simulated
runoff and the transit of the first surge of observed debris
flows (estimated as the time that maximizes the crosscorrelation between the two series) ranges in the interval[-2.5, 1.5] minutes. These outcomes are consistent with
the inception mechanisms of debris flows that arestrictly related to the destabilizing action exerted byrunoff on in-channel sediment layers. Hence, a small
time lag between the hydrograph peak simulation andthe triggering instant of debris flow implies a rather
robust performance of the rainfall-runoff model.
Moreover, the simulated discharges reproduce quite
entirely the stage hydrographs except for the last part of
the recordings. In these segments, modelled runoff islower than the considered critical threshold. Hence,
runoff cannot entrain sediments and, consequently,
should not be considered in the evaluation of liquidvolume contributing to the debris-flow solid-liquid
wave.
These findings completely agree with those of [1],who compared the peak times of modelled discharges
with those of corresponding stage hydrographs ofoccurred debris flows, concluding that hydrologicalmodels can emulate the initiation time of runoffgenerated debris flows. This similar behaviour took
place although the difference in the implemented excess
rainfall generating process, due to the distinct featuresof the analysed catchments. [1] evaluated excess rainfall
by means of the Green-Ampt approach, i.e. a saturationexcess runoff production mechanism, whereas we used
an infiltration-excess method, as the Horton equation.
The capability of the developed model to catch therunoff peak time and the evolution of the debris-flow
first-surge stage with good accuracy suggests a potential
use in early warning systems for evaluating the debris-Fig. 2. Events recorded by the monitoring stations of Rovina
di Cancia on (a) August 1st, 2018 and (b) July 1st, 2020 and ofRio Gere on (c) July 8th, 2021 and relative hydrologicalsimulations. The stage hydrographs have been derived from(a) pressure transducer, (b) video cameras, and (c) laser levelsensor.

3E3S Web of Conferences 415, 02002 (2023)
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4 Conclusions
The impervious morphology of dolomitic headwater
catchments makes monitoring activities challenging.
The knowledge of discharge behaviour is fundamental
both for improving the comprehension of debris flow
triggering and for modelling the initiation dynamics on
the scree slopes at the base of rocky cliffs. We
documented the hydrological response of two
catchments to three convective rainfall events. Observed
debris-flow hydrographs exhibit an impulsive character.
A hydrological model has been tested to reproduce thisbehaviour. Simulated discharges have been compared tothe stage hydrographs of observed debris flows in theCancia and Rio Gere catchments. The robustness of themodel has been tested by comparing the simulated
runoff peak times and the timing of debris flows.
Differences in timing result in a few minutes. Moreover,runoff replicates quite entirely the recorded stages,
except when discharges decrease below the triggering
threshold of debris flows. These results ensure
reasonably good predictability of the model, permittingits potential use in the evaluation of debris-flow solidliquid waves in early warning systems.
The authors wish to thank the Regional Agency for
Environmental Prevention and Protection of Veneto for themeteorological data; the association “Regole d'Ampezzo”,
which permitted to set up of rain gauges and monitoringstations; the Public Work Department of Veneto Region for
the LiDAR data.

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