E3S Web of Conferences 415, 04005 (2023)
DFHM8

https://doi.org/10.1051/e3sconf/202341504005

Rainfall-induced shallow landslides triggered after vegetation
removed because of fires: G-XSLIP application to Gioiosa Marea(Sicily, Italy)
Michele Placido Antonio Gatto1*, Valentina Lentini2, Lorella Montrasio 1 and Francesco Castelli2
1 University of Brescia, Department of Civil, Environmental, Architectural Engineering, and Mathematics, 25123 Brescia, Italy
2University Kore of Enna, Faculty of Engineering and Architecture, 94100 Enna, Italy

Abstract. The paper analyses how vegetation prevents the triggering of rainfall-induced shallow landslides
by using the G-XSLIP platform, which is based on G-SLIP model, i.e., the SLIP model updated withvegetation parameters for root reinforcement and rain interception due to canopy. G-XSLIP is applied to anarea in Gioiosa Marea (Sicily, Italy), where on 9th September 2016 shallow landslides occurred, depositingon the state road SS 113. The analyses demonstrate that the triggering of these phenomena is related to theremoval of vegetation after summer fires some months before, which decreases computed safety factors by
about half.

1 Introduction
Rainfall-induced shallow landslides are natural
phenomena involving layers of shallow soil (topsoil);they are triggered by intense and/or prolongated rain
which, infiltrating through macropores, causes anincrease in the degree of saturation and a reduction inshear strength [1,2]. One of the mathematical models
used to study the triggering of rainfall-induced shallow
landslides is SLIP (Shallow Landslide Instability
Prediction), i.e., a physically-based model whichanalyses the topsoil’s stability through an infinite slope
scheme, including in a simplified way the effect of rainon soil apparent cohesion [3,4].
Due to its simplicity and reliability, SLIP wasadopted in analyses at different scales: from slope scale
to large areas [5-9]. In the latter case, the application waspossible thanks to its implementation in DEWETRA,i.e., the multi-risk platform owned by the Italian
Department of Civil Protection (DCP), where SLIP wasimplemented for real-time large-scale analyses [10].
Recently, Gatto and Montrasio [11] developed analgorithm to perform large-scale stability analyses
independently of the DCP, suitable for insights withresearch purposes: this is the X-SLIP platform.
One of the aspects focused on by X-SLIP is thevegetation’s contribution to slope stability. The
scientific interest in this topic started in the 60s, from theexperimental observation of an increased number ofphenomena related to deforestation [12]. Over the years,
two aspects have been studied: the soil reinforcement
provided by roots and the rainfall interception due tovegetation canopy. In the first case, literature generally
quantifies a root cohesion cr through experimental tests,
numerical and theoretical modelling; it is a cohesion to

be added in the well-known Mohr-Coulomb criterion forsoil strength. As regards rainfall interception, empiricalobservations on the water rate β* intercepted by plants,
which depends on species and foliage type, are the mostcommon. A useful state-of-art review is provided byMontrasio and Gatto [13].
Both vegetation effects have been recently
introduced in the SLIP formulation and the X-SLIP
platform, which have been updated accordingly in GSLIP and G-XSLIP [14]. The presence of vegetation has
been shown to improve the territorial stability and theprediction quality of the G-SLIP model in analyses withvegetation effects is even better, due to more realistic
modelling. It follows that the vegetation removal fromanthropic or natural decreases stability.
This paper shows the G-XSLIP application to anarea of Gioiosa Marea (Sicily, Italy), where rainfallinduced shallow landslides occur with high frequency.
In September 2016, some of these phenomena weretriggered and debris were deposited on the state road
SS113; local newspapers ascribed their occurrence tosummer fires which have determined the vegetation
removal exactly in the triggered points. G-XSLIPanalyses are therefore performed with or without theeffect of vegetation coverage to quantify thecontribution of vegetation on stability.

2 Brief overview of the G-SLIP model
The G-SLIP model analyses the stability of the topsoil(thickness H) by evaluating the safety factor FS througha relationship derived from the infinite slope scheme,
together with simplified assumptions considering theeffects of rainfall on soil shear strength:* Corresponding author: michele.gatto@unibs.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, 04005 (2023)
DFHM8

https://doi.org/10.1051/e3sconf/202341504005

*FS=

tanφ'
tanβ+-k ∆t
λ1-β∑ω h e t j ]c'+cr+ASr (1-Sr) [1-nH(1-S) j=1 jαsafety factor evaluated through the G-SLIP model)
when vegetation is removed.

rγH cos β sin β(1)3.1 Morphology,parameters

FS depends therefore on morphological parameters(slope angle β), physical and mechanical soil parameters(unit weight γ, porosity n, effective cohesion c’ andfriction angle φ’), vegetation parameters (rootreinforcement cr and rainfall interception β*). The
summation of Eq. (1) allows us to evaluate the effects ofω rainfall events on the actual stability (and soil apparent
cohesion), through the slope drainage coefficient kt andaccording to the time gap Δtj between the generic rainfall
event hj and the instant of stability analysis. Sr is theinitial degree of saturation and A, α and λ are modellingparameters. A detailed description of the model can befound in [3,4,9].
To evaluate the stability over large areas, the GXSLIP multi-approach algorithm has been recentlypresented, for the application of G-SLIP formulation topixels of a reference grid. A complete description of thealgorithm can be found in [11,14]. All the parameters ofEq. (1) need to be evaluated spatially and this is possible
by knowing some basic geographic data, easily available
in the territorial databases (e.g., Digital Terrain Model,
Geology Map, Land Uses, etc.). Specifically, mean soil
strength parameters, experimentally derived, areassociated with each geologic unit.

soilandvegetation

We have derived slope angles by applying a finitedifference algorithm to the Digital Terrain Model(DTM); due to the small dimension of the study area, ahigh-resolution DTM (0.5x0.5 meter) can be adopted
with good computational efficiency. Figure 2 shows themap of the calculated slope angles.

Fig. 2. Map of slope angles derived from the 0.5m-resolution
DTM (From Sicilian Region Database [15])Spatially distributed soil parameters are assigned
through a geology-based approach, depending on thegeologic map. Figure 3 shows that the area under
examination is underlain by two geologic materials:
debris and metamorphic rock. A specific parameter set
is adopted for each geologic type and reported in Table
1. Effective cohesion is initially assumed null for bothmaterials.

3 The case study of Gioiosa Marea –September 2016
Gioiosa Marea is a small Italian municipality (26 km2)
in the province of Messina (Sicily). This territory has
high hydrogeological risk and many landslides(including rainfall-induced shallow landslides) occur
causing inconvenience for years, especially wheninteracting with infrastructure.
Several rainfall-induced shallow landslides
occurred on 9th September 2016, depositing debris on asegment of the state road SS113, as evidenced by Figure
1.

Fig. 3. Simplified geologic map (Gagliano et al. [16])Table 1. Set of soil parameters adopted for each geology
classes.

Fig. 1. Orthophoto of the study area and rainfall-induced
shallow landslides detected from the 9th September 2016
event.

According to local newspapers, different fires had
affected this area the previous summer, causing theremoval of vegetation coverage. This could have been
responsible for the landslide triggering. We have applied
the G-XSLIP to investigate any change in stability (and2

Description

n(-)

φ'(°)

A(kPa)

kt(h-1)

Metamorphic
Rocks

0.3

36.5

800.0025

Debris0.4

25.0

400.0065

E3S Web of Conferences 415, 04005 (2023)
DFHM8

https://doi.org/10.1051/e3sconf/202341504005

For vegetation, a map-based approach is used also todifferentiate the parameters. Information on vegetation
types and their spatial distribution is derived from theLand Use Map, shown in Figure 4. Four vegetation
types are recognized in the study area. Since our maininterest is in the area near SS113, we have considered
two main vegetation types: Mediterranean shrub(including lenses of shrub and Cistus and rosemary) andConifers. Vegetation parameters are derived fromprevious literature studies [17-20]; values adopted in theanalyses “with vegetation” are shown in Table 2.

Fig. 5. Rain recorded at Patti Station ([21])4 Results and Discussion
The safety factor is evaluated on 9th September at 2 AM(time occurrence of the maximum rainfall recorded atPatti station) for the pixels covering the study area. We
consider two cases 1) with the original vegetation(Figure 6) and 2) with the removal of the Mediterranean
shrub (vegetation type near SS113) because of fires(Figure 7).

Fig. 4. Land Use Map (From Sicilian Region Database [15])Table 2. Vegetation parameters adopted in X-SLIP analysis“with vegetation”.

MediterraneanshrubConifers

cr(kPa)

β*(%)

1021

1030Fig. 6. Map of safety factors with vegetation (case 1) – Eventof 9th September 2016

3.2 Rainfall data
To analyse the stability on 9th September 2016, rains
recorded from 8th August to 9th September 2016 areconsidered. Data are provided by the AgroMeteorological Information Service of Sicily ([21]):hourly recordings at the gauging stations of Patti,
Militello Rosmarino, Mistretta, San Fratello,
Torregrotta, Antillo and Leni are considered. After theirinterpolation, these data are used to evaluate stability
through the sum in Eq. (1) [11]. Figure 5 shows the time
history of rainfall recorded in Patti (the closest station tothe study area).

Fig. 7. Map of safety factors after removal of vegetation
close to SS113 (case 2) - Event of 9th September 2016

Our analyses show the lack of vegetation causes anincrease of unstable areas. This result is aligned withprevious empirical observation [12]. Since the summer
fires did not completely remove the Mediterranean
shrub shown in Figure 4, we focus on the observed soilslips. The FS varying with time is represented for thetwo points indicated in Figure 1: Figure 8 is related tothe orange point P1, while Figure 9 represents the bluepoint P2.

3

E3S Web of Conferences 415, 04005 (2023)
DFHM8

https://doi.org/10.1051/e3sconf/202341504005

vegetation in slopes (e.g., deforestation) an analysis of
the effects on slope stability should be performed.
Furthermore, when vegetation is removed due to fires,its restoration may be essential to prevent future
landslides.

ReferencesFig. 8. Trend of the safety factor FS obtained for observed
soil slip P1 (orange point in Figure 1)

Fig. 9. Trend of the safety factor FS obtained for observed
soil slip P2 (blue point in Figure 1)

1.

D.G. Fredlund, H. Rahardjo, Soil mechanics for unsaturated
soils(Wiley,NewYork,1993)https://doi.org/10.1002/9780470172759

2.

F. Castelli, V. Lentini, Landsliding Events Triggered byRainfalls in the Enna Area (South Italy), in Landslide
Science and Practice: Early Warning, Instrumentation andMonitoring 2, 39–47 (2013)

3.

L. Montrasio, Stability analysis of soil slip, in Brebbia CA(eds) Proceedings of the International Conference Risk 2000,
Wit press, Southampton (2000)

4.

L. Montrasio, R. Valentino, Nat. Hazards Earth. Syst. Sci. 8:
1149-1159 (2008) https://doi.org/10.5194/nhess-8-11492008

5.

L. Montrasio, R. Valentino, Landslides 4: 291–296 (2007)https://doi.org/10.1007/s10346-007-0082-3

6.

L. Montrasio, R. Valentino, G.L. Losi, Nat. Hazards Earth.
Syst.
Sci.
11:
1927-1947(2011)
https://doi.org/10.5194/nhess-11-1927-2011

7.

L. Montrasio, R. Valentino, G.L. Losi, Nat. Hazards
60: 1231–1254 (2012) https://doi.org/10.1007/s11069-0119906-5

8.

L. Montrasio, L. Schilirò, A. Terrone, Landslides 13: 873–883 (2016) https://doi.org/10.1007/s10346-015-0642-x

9.

L. Montrasio, L. Schilirò, Italian J. Eng. Geol. Environ. 2:77–85 (2018) https://doi.org/10.4408/IJEGE.2018-02.O-06

10. L. Montrasio, R. Valentino, A. Corina, L. Rossi, R. Rudari,Nat.
Hazards
74: 1263–1290
https://doi.org/10.1007/s11069-014-1239-8

Figure 8 indicates that the safety factor issignificantly reduced by vegetation removal. Its value is
1.71 with vegetation, and 0.78 without vegetation; it is
not only reduced by about half, but its reduction
determines a change from stability (FS>1) to instability(FS<1). For P2 (Figure 9) instability is predicted by theSLIP model but no variation occurs between the twoanalyses. This is because it is a point with no vegetationaccording to the land use map (Figure 4).
Generally, if there had been vegetation, it would
have reduced the instability during the analysed rainfall
event. Further analyses will define which contribution(root reinforcement or rainfall interception) is more
relevant in terms of stability. Stabilisation through theplanting of proper vegetation will be also assessed.

(2014).

11. M.P.A. Gatto, L. Montrasio, Comput. Geotech. 154 (2023).
https://doi.org/10.1016/j.compgeo.2022.105175

12. D.M. Bishop, M.E. Stevens, Landslides on logged areas insoutheast Alaska (Northern Forest Experiment Station,
Forest Service, U.S. Dept. of Agriculture, 1964).

13. L. Montrasio, M.P.A. Gatto, Il contributo degli apparati

radicali nei fenomeni di instabilità di coltri superficiali, inAtti del XXVII CNG. Reggio Calabria (2020)

14. L. Montrasio, M.P.A. Gatto, C. Miodini,Landslides(Submitted)

15. https://www.sitr.regione.sicilia.it
16. AL Gagliano, N Costa, Perricone M, et al. Da CAD a
Shapefile: Processamento e correzione spaziale di geodati
obsoleti. In: Conferenza ASITA. Trieste (2019)17. C. Mattia, G.B. Bischetti, F. Gentile, Plant Soil 278, 23–32(2005) https://doi.org/10.1007/s11104-005-7930-5

5 Conclusion

18. L. P. H. van Beek, J. Wint, L.H. Cammeraat, Plant
Soil 278, 55–74 (2005) https://doi.org/10.1007/s11104-0057247-4

We analysed the stability of an area in Gioiosa Marea(Italy) frequently affected by rainfall-induced shallow
landslides, with a focus on past events which wereattributed to vegetation removal due to fires. Vegetation
has a beneficial effect on slope stability, due to roots andfoliage. Its removal is responsible for a strength loss andan increase in triggering of landslides. These changes
can halve the safety factor, sometimes inducinginstability. This means that when planning removal of

19. L. Dong, H. Han, F. Kang, X. Cheng, J. Zhao, X. Song,Forests
11(2):
https://doi.org/10.3390/f11020243

243(2020)

20. P. García Estringana, M. Nieves Alonso-Blázquez, A.
Alegre, A. Cerdà, Mediterranean shrub vegetation: soil
protection vs. water availability, in EGU General Assembly
Conference Abstracts (2014)

21. http://www.sias.regione.sicilia.it

4