E3S Web of Conferences 415, 07004 (2023)
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https://doi.org/10.1051/e3sconf/202341507004

Risk Assessment of Transport Linear Infrastructures to Debris
FlowFrancesco Castelli1, Enrico Foti2, Valentina Lentini1* and Marina Pirulli3
1Faculty of Engineering and Architecture, University Kore of Enna, 94100 Enna, Italy
2DICAR, Department of Civil Engineering and Architecture, University of Catania, 95125 Catania, Italy
3Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, 10129, Torino, Italy

Abstract. For the assessment of debris flow risk, it is essential to consider not only the triggering andpropagation stages but also to perform analyses of its effects and consequences. The study aims atdeveloping a procedure based on a quantitative risk assessments able to estimate the different levels of risk
with reference to transport linear infrastructures. This includes numerical modelling for debris flows todetermine the zones where the elements at risk could suffer an impact. A detailed comparison between theperformances of two different approaches to debris flow modelling was carried out. In particular, the resultsof a mono-phase Bingham model (FLO-2D) and that of a single-phase model (RASH-3D) with reference tothe Enna area (Sicily). The results can be applied for the risk calculations. The purpose is to define a priority
of intervention for the identification of the infrastructures exposed at risk, leading to the choice of safetymeasures.

1 Introduction
Linear transport infrastructure systems are often
subjected to landslide and debris flow events. Hazard
maps, as well as, direct risk estimation play an importantrole to mitigate related effects.
Landslides have also a strong impact on the road andrailway systems, creating the need to define criteria formanagement and mitigation of risk through landslide
zoning correlated with transport infrastructure network[1-2]. In particular, the risk evaluation requires analysisof the spatial and temporal probabilities that a given
element is hit by a landslide of a particular type andmagnitude [3], the estimation of rainfall and triggeringfactors, the dynamic of the event, the area ofpropagation, etc.
The destructive potential of a landslide mainly
depends on velocity. As a consequence “rapidlandslides”, such as debris flows and rock-slide debris
avalanches, are the most dangerous for transport
infrastructure systems.
The state of the art of prevention is performed thanks
to development of hazard maps, built with the data takenfrom historical records, numerical simulations and small
and/or medium scale physical modelling. With this aim,several numerical models have been developed for
simulating landslide propagation and run-out [4-7].
The choice of the rheology is a fundamental aspectof numerical simulation. To derive useful information
for the calibration of model parameters, the backanalysis of a debris flows occurred in Enna (Italy), isreported. In order to understand the real behaviour of thepropagation of a debris flow on a large scale, a realdebris flow event was analysed by means of two

different models: the FLO-2D [8-9] and the RASH-3D[10]. Comparison among obtained results underlinesthat the validation of a rheology requires not only a good
agreement between the numerical simulation results andthe run out area boundaries but also in term of depth
distribution of the mass.

2 Case study: the 2014 Enna debris
flow
During the night between the 1st and the 2nd of February
2014 a heavy rainfall struck the city of Enna (Italy),causing several damages. Very large amount of soil
deposited on the road (Figure 1), providing theinterruption of the infrastructure connecting Enna at thehighway “A19 Palermo-Catania”. About 150 mm ofrainfall in less of 1 hour characterized the event. This
area is characterized by a morphology with high hillslope angles (within a range of 30  60°) and withcatchment areas of small extension (about 0.158 km2).

Fig. 1. Flow mass in the deposition area close to the main road(“SS117bis“): a) plan view and b) detail of the connecting withthe highway.

© 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, 07004 (2023)
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3 Numerical modelling
analysis procedures

https://doi.org/10.1051/e3sconf/202341507004

andThe computed maximum flow depths during theevent are presented in Figure 4a. The highest predictedflow depth is about 4.0 m. Figure 4b represents the final
flow depths. The highest value of the predicted final
flow depth is about 1.4 m. It has been found that themaximum velocities are registered in correspondence of
the upper part of the basins and the slope is the highest,with values ranging from 1 to 2 m/s.
The predicted values are, in general, in good
agreement with those observed. This is supported by thecomparison between the computed volume and themeasurement of the deposited sediment after the event
resulting from the surveys of the Regional Civil
Protection.

backIn order to understand the behaviour of their propagation
on a large scale, the mentioned real debris flow event,
was analyzed by means of two different models.
The first one is FLO-2D code, which is based on a
mono-phasic Bingham scheme, modelled through thequadratic rheological law developed by O’Brien andJulien and, the second is RASH3D code based on asingle-phase continuum mechanics approach and on
depth-averaged St. Venant equations.
The presented numerical analyses, in particular,
intended to investigate: (i) the capability of the codes tosimulate the dynamics of the debris flow (propagationand deposition) and, (ii) the influence of the associatedcalibrated rheological parameters on the numericalresults.

3.2 Results of RASH-3D numerical simulations
To RASH-3D model was applied referring to theevent occurred on 1-2 February 2014. The trigger
volume to be used as input data in the numerical analysisof propagation via the model RASH-3D is of about 1400
m3 (Figure 3), according to the on-site survey reportedby [11].
Numerical simulations have been carried onchoosing the Voellmy rheology and the values of thefriction coefficient μ and the turbulence coefficient 
reported in Table 1.
The results obtained by RASH-3D model aresummarized in terms of final flow depth (Figure 4),
representing the maximum flow height in the depositionarea, and the maximum flow velocity (Figure 4).

3.1 Results of FLO-2D numerical simulations
3.1.1 Enna debris flow
In order to model the debris flows occurred in Ennathree principal data sets are needed: a digital terrain
model (DTM), hydrological data, and rheologicalproperties of the sediment - water mixture. For theconstruction of the DTM a grid system with cell size 2.0
m x 2.0 m was implemented by FLO-2D model. The
hydrological input is applied at the upstream section of
the basin where the triggering was observed. The
discharge rate value of the debris flows for the basin has
been calculated.
A reconstruction of the inundated area was obtained
as output of the simulations performed by the FLO-2D
code (Figure 2).

Fig. 3 Comparison between: a) measured [12] and b)
computed maximum flow depth(a)(b)Fig. 2 Scenarios simulated with FLO-2D code for Enna debris
flow: (a) maximum flow depth, (b) final flow depth.

2E3S Web of Conferences 415, 07004 (2023)
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Fig. 4 Comparison between: a) measured [12] and b)
computed maximum flow depth
Table 1. Rheological parameters used in numerical analyses
carried out by RASH-3D code (Enna event).
Analysis
Friction coefficient μ[-]Turbulence coefficient [m/s2]12340.1

0.1

0.05

0.055001000500

2000

Fig. 6 Maximum flow velocity simulated with the RASH-3D
code: (a) analysis 1, (b) analysis 2, (c) analysis 3 and d)analysis 4.

4 Debris Flow Susceptibility
Estimation of Direct Risk

In particular, the results reported in Figure 5 and 6
correspond to the best-fit between predicted andobserved values both as concern the depth than thevelocity of the flow mass, especially in the depositionarea close to the main road SS117bis interrupted due tothe debris flow, connecting the city of Enna at thehighway A19.

andThe results obtained from numerical modelling of
the propagation phase of debris flows can be used todraw the debris flow susceptibility maps and/or torepresent a preliminary level of landslide susceptibility
zoning of a study area. In particular, the path, the travel
distance and the velocity of flowing mass are useful toevaluate also the consequences in terms of effects of theexpected events.
In the last few years, quantitative risk assessments(QRA) has become an essential tool for management oflandslide hazard and for planning risk mitigationmeasures at a detailed scale.
According to [13], the framework for the use ofQRA
for landslides and engineered slopes comprises threemain components, i.e., risk analysis, risk assessment andrisk management. Risk analysis includes hazard andconsequence analyses. Risk estimation is the final stepof the risk analysis and essentially consists in the risk
calculation through a probabilistic equation.
The second step of the procedure is represented by
the quantitative risk assessments (QRA), relating flow
volume to damage probabilities.
Following the procedure proposed by [13], suitably
modified, the risk estimation can be related to the annual
probability Pi(LOL) that a particular person may lose
his/her life calculated as a function of: the frequency ofthe landslide events of a given i-magnitude; theprobability of the landslide reaching the element at risk;
the temporal spatial probability of the element at risk;
the vulnerability of the element to the landslide event.
The procedure, described in detail in [1], has been
applied to the case of the debris flow event occurred on
February 2014 close to the city of Enna (Italy).

Fig. 5 Maximum debris flow height simulated with the RASH3D code: (a) analysis 1, (b) analysis 2, (c) analysis 3 and d)analysis 43

E3S Web of Conferences 415, 07004 (2023)
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The quantitative risk assessment involved theestimation of the annual probability Pi(LOL), by assuminga return period (T=10 years) equal to the period of thetriggering rainfall.
Assuming that an infrastructure has an unacceptablestate, and no longer compatible with social needs when
the probability of loss of human life is higher than thethreshold value of 10-4 (Table 2), a “Severity Index” (Is)can be defined as an indicator of the level of weaknessof the infrastructure, connected to the risk to which users
are exposed for a landslide occurrence. Thus the valuesof the Severity Index (Is) reported in Table 2 can besuggested to evaluate the different level of risk.

References
1.

V. Lentini, G. Distefano, F. Castelli, Bull. Eng.
Geol. Environ. 78, (2019)
2. V. Lentini, F. Castelli, G. Distefano, Managementof transport infrastructures: A procedure to assess
the landslide risk, in Proceedings of VII Convegno
Nazionale Ricercatori Ingegneria Geotecnica,
CNRIG, 3-5 July 2019, Lecco Italy (2019)
3. R. Fell, J. Corominas, C.H. Bonnard, L.Cascini, E.
Leroi, W.Z. Savage, Eng Geol 102, (2008)
4. M. Pastor, B. Haddad, G. Sorbino, S. Cuomo, V.
Drempetic, Int. J. for Numerical and Analytical
Methods in Geomechanics 33, 2 (2009)
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6. L. Montrasio, L. Schilirò, J. of Eng. Geol. andEnv. 2, (2018)
7. L. Schilirò, L. Montrasio, G. Scarascia Mugnozza,
Sci. Total Environ., 569-570 (2016).
8. J.D. O’Brien, FLO-2D User’s Manual, FLO
Engineering, Nutrioso
9. J.S. O’Brien, P.Y. Julien, J. Hydrol. Eng. 114(1988)
10. M. Pirulli, M.O. Bristeau, M.B. Mangeney, C.
Scavia, Env. Model. & Soft. 22, 10 (2007)
11. F. Castelli, G. Freni, V. Lentini, A. Fichera,
Modelling of a debris flow event in the Enna areafor hazard assessment, in Proceedings of 1stInternational Conference on the Material Point
Method, MPM, 10-13 January 2017, Delft, The
Netherlands, (2017)
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Sci. 15, (2015)
13. R. Fell, K.S. Ho, S. Lacasse, E. Leroi, A
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Table 2. Severity Index values.

LevelP(LOL)

Very High.

HighModerateIS-3P(LOL) > 1 10 /annum50.

-4.

-340.

-5.

-430.

-6.

-5

1 10 < P(LOL) < 1 10 /annum
1 10 < P(LOL) < 1 10 /annumLow

1 10 < P(LOL) < 1 10 /annum

20Very Low.

10-6P(LOL) < 1 10 /annum

5 Concluding remarks
This study aims at developing numerical modellingfor debris flows able to calculate physical outputs(extension, depths, velocities) and to determine thezones where the elements at risk could suffer an impact
with reference to the transport linear infrastructures.
These results can then be applied to risk calculations,reproducing in thematic maps by different risk levels thedistribution of the flow mass on the propagation path, itsintensity, and the zone where the elements will
experience an impact.
The following step is the risk estimation adopting,for example, a procedure based on a quantitative risk
assessments. In fact, a quantifiable integrated approachof both hazard and vulnerability is becoming a required
practice in risk reduction management.
In this paper a Severity Index has been defined as anindicator of the level of weakness of the infrastructure,and values for this index have been suggested toevaluate the different level of risk.
The final purpose is to define a priority ofintervention for the identification of the ex-posed
infrastructures at risk (accurate and objective), leading
to the choice of safety measures in view of an effectiveandsustainableinfrastructure
planningandmanagement.
The authors gratefully acknowledge the financial support of
the MUR (Ministry of Universities and Research [Italy])through the research Project entitled “TEMI MIRATI: Criticalinfrastructure safety due to fast moving landslide risk” (ProjectCode: ARS01_00158), financed with the PNR 2015 - 2020(National Research Program).

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