1. Maria Teresa Brunetti, Silvia Peruccacci
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Definition & Use of Empirical Rainfall Thresholds for Possible Landslide Occurrence
Maria Teresa Brunetti, Silvia Peruccacci
Maria Teresa Brunetti
CNR IRPI (via della Madonna Alta 126, 06128, Perugia, Italy)
Silvia Peruccacci
CNR IRPI (via della Madonna Alta 126, 06128, Perugia, Italy)

2. Empirical Rainfall Thresholds
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DEFINITIONS
A landslide is the movement of a mass of rock, debris, or earth down a slope, under the influence of gravity. (Varnes 1978, Cruden & Varnes 1996) A threshold is the minimum or maximum level of some quantity needed for a process to take place or a state to change. (White et al., 1996)
We start giving you some basic definitions:
a landslide is the movement of a mass of rock, debris, or earth down a slope, under the influence of gravity, and
a threshold is the minimum or maximum level of some quantity needed for a process to take place or a state to change (White et al, ). A minimum threshold defines the lowest level below which a process does not occur. A maximum threshold represents the level above which a process always occurs.
References:
Varnes, D.J., Slope movements: types and processes. In: Schuster, R.L., Krizek, R.J. (Eds.), Landslide Analysis and Control, National Academy of Sciences, Special Re- port 176. Transportation Research Board, Washington D.C., pp. 11–33.
Cruden, D.M., Varnes, D.J., Landslide types and processes. In: Turner, A.K., Schuster, R.L. (Eds.), Landslides, Investigation and Mitigation, Special Report Transportation Research Board, Washington D.C., pp. 36–75. ISSN: X, ISBN: X.
White, I.D., Mottershead, D.N,. Harrison, J.J., Environmental systems, 2nd ed. London: Chapman & Hall, pp. 616.
M.T. Brunetti & S. Peruccacci

3. Empirical Rainfall Thresholds
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DEFINITIONS
For rainfall-induced landslides, a threshold may define the amount of rainfall that, when reached or exceeded, is likely to trigger landslides.
UNLIKELY LANDSLIDE OCCURRENCE
LIKELY LANDSLIDE OCCURRENCE
THRESHOLD
Rainfall Duration
Cumulated Rainfall
Physically based thresholds
Empirically based thresholds
For rainfall-induced landslides, a threshold may define the amount of rainfall that, when reached or exceeded, is likely to trigger landslides.
Rainfall thresholds can be defined on physical or empirical (or statistical) bases.
M.T. Brunetti & S. Peruccacci

4. Empirical Rainfall Thresholds
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RAINFALL THRESHOLDS
Physically based thresholds are calculated using slope stability models combined with infiltration models. Physical models require detailed spatial information on the hydrological, lithological, morphological, and soil characteristics that control the initiation of landslides. (Montgomery & Dietrich, 1994; Iverson, 2000)
Physically based thresholds are calculated using slope stability models combined with infiltration models. Physical models require detailed spatial information on the hydrological, lithological, morphological, and soil characteristics that control the initiation of landslides. This information is difficult to collect precisely over large areas, and is rarely available outside specifically equipped test fields.
References:
Montgomery, D.R. & Dietrich, W.E.:, A physically based model for the topographic control of shallow landsliding. Water Resources Research, 30(4), –1171.
Iverson, R.M., Landslide triggering by rain infiltration. Water Resources Research, 36(7), 1897–1910.
M.T. Brunetti & S. Peruccacci

5. Empirical Rainfall Thresholds
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RAINFALL THRESHOLDS
Empirical rainfall thresholds are defined by analyzing past rainfall events that have resulted in landslides. The thresholds are obtained by drawing lower-bound lines to the rainfall conditions that resulted in landslides plotted in Cartesian, semi-logarithmic, or logarithmic coordinates. (Caine 1980, Aleotti 2004, Guzzetti et al., 2007, 2008)
Empirical rainfall thresholds are calculated analyzing past rainfall events that have resulted in landslides. The thresholds are usually obtained by drawing lower-bound lines to the rainfall conditions that resulted in landslides plotted in Cartesian, semi-logarithmic, or logarithmic coordinates. In this lesson, we will talk only about empirical rainfall thresholds.
References:
Caine, N., The rainfall intensity-duration control of shallow landslides and debris flow. Geografiska Annaler A, 62,
Aleotti, P., A warning system for rainfall-induced shallow failures. Engineering Geology, 73,
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C.P., Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorology and Atmospheric Physics, 98, 239–267.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C.P., The rainfall intensity- duration control of shallow landslides and debris flows: an update, Landslides, 5(1), 3–17.
M.T. Brunetti & S. Peruccacci

6. Empirical Rainfall Thresholds
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EMPIRICAL THRESHOLDS
Type
Area
Characteristics
Pro
Cons
Global
World
Are independent of local conditions and rainfall pattern
Useful where other thresholds are not available
May result in numerous
false positives
Regional
From few to several thousands of km2
Group areas with similar meteorological,
climatic, and physiographic characteristics
Suited for landslide warning systems
Cannot be easily exported to neighboring
areas
Local
From few to some hundreds of km2
Dependent on the local climatic regime and geomorphological setting
Suited for warning systems on a single or a group of landslides
Empirical thresholds can be subdivided in global, regional, or local thresholds.
A global threshold attempts to establish a general (‘‘universal’’) minimum level below which landslides do not occur, independently of local morphological, lithological and land-use conditions and of local or regional rainfall pattern and history. Regional thresholds are defined for areas extending from a few to several thousand square kilometers of similar meteorological, climatic, and physiographic characteristics, and are potentially suited for landslide warning systems based on quantitative spatial rainfall forecasts, estimates, or measurements. Local thresholds are dependent on the local climatic regime and geomorphological setting, and are applicable to single landslides or to group of landslides in areas extending from a few to some hundreds of square kilometers.
Regional and local thresholds perform reasonably well in the area where they were developed, but cannot be easily exported to neighboring areas. Global thresholds are relevant where local or regional thresholds are not available, but may result in false positives, i.e., prediction of landslides that do not occur.
M.T. Brunetti & S. Peruccacci

7. Empirical Rainfall Thresholds
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EMPIRICAL THRESHOLDS
At least 25 rainfall and climate variables are used in the literature for the definition of empirical thresholds.
The table lists 25 rainfall and climate variables used in the literature for the definition of empirical thresholds for the initiation of landslides.
References:
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C.P., Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorology and Atmospheric Physics, 98, 239–267.
(Guzzetti et al., 2007)
M.T. Brunetti & S. Peruccacci

8. Empirical Rainfall Thresholds
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EMPIRICAL THRESHOLDS
Thresholds using combinations of rainfall measurements can be subdivided in four subcategories:
Rainfall mean Intensity-Duration (ID) thresholds
Thresholds based on the Total Event rainfall
Cumulated Event rainfall-Duration (ED) thresholds
Cumulated Event rainfall-Intensity (EI) thresholds
Thresholds using combinations of rainfall measurements can be subdivided in four subcategories:
Rainfall mean Intensity-Duration (ID) thresholds
Thresholds based on the Total Event rainfall
Cumulated Event rainfall-Duration (ED) thresholds
Cumulated Event rainfall-Intensity (EI) thresholds
References:
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C.P., Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorology and Atmospheric Physics, 98, 239–267.
(Guzzetti et al., 2007)
M.T. Brunetti & S. Peruccacci

9. INTENSITY-DURATION THRESHOLDS
Empirical Rainfall Thresholds
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INTENSITY-DURATION THRESHOLDS
Rainfall mean Intensity-Duration (ID) are the most common thresholds in the literature.
ID thresholds have the general form of a negative power law:
I = α · D –β, β > 0
where I is in mm/h and D in h.
Intensity-duration thresholds are the most common type of thresholds proposed in the literature. ID thresholds have the general form of a negative power law. In the equation, I is the rainfall mean intensity, D is the duration of the rainfall event, α is a scaling parameter (the intercept), and  is the shape parameter that controls the slope of the threshold curve.
M.T. Brunetti & S. Peruccacci

10. EVENT-DURATION THRESHOLDS
Empirical Rainfall Thresholds
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EVENT-DURATION THRESHOLDS
Cumulated Event rainfall-Duration (ED) thresholds are also common in the literature.
ED thresholds have the general form of a power law:
E = α · Dγ, γ > 0
where E is in mm and D in h.
Cumulated Event rainfall-Duration (ED) thresholds are also common in the literature. ED thresholds have also the forma of a power law. In the equation, E is the cumulated event rainfall, D is the duration of the rainfall event, α is a scaling parameter (the intercept), and γ is slope of the threshold curve.
M.T. Brunetti & S. Peruccacci

11. “ID” AND “ED” THRESHOLDS
Empirical Rainfall Thresholds
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“ID” AND “ED” THRESHOLDS
The slide shows two examples of ID and ED rainfall thresholds for Italy, which are the blue lines in the left and right graph, respectively.
References:
Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., Guzzetti, F., Rainfall thresholds for the possible occurrence of landslides in Italy. Natural Hazards and Earth System Sciences, 10, , doi: /nhess
(Brunetti et al., 2010)
M.T. Brunetti & S. Peruccacci

12. DEFINITION OF A THRESHOLD
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DEFINITION OF A THRESHOLD ?
How to define an objective and reproducible threshold?
Defining a rainfall threshold is not trivial, because, for the same dataset, different investigators adopting different approaches may obtain different thresholds…and this is a problem.
Therefore, the question is: ”How to define an objective and reproducible threshold?”
M.T. Brunetti & S. Peruccacci

13. Empirical Rainfall Thresholds
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A FREQUENTIST METHOD
Log(D)
Log(I)
Power-law fit of D-I
rainfall conditions
Differences d between
D-I data and the fit
Gaussian model of the d distribution
Thresholds for different
exceeding probabilities
Here, is shown a Frequentist method for the objective definition of rainfall thresholds proposed by Brunetti et al. (2010).
First, the ensemble of rainfall intensity-duration conditions that resulted in landslides is fitted (in logarithmic coordinates) with a power law.
References:
Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., Guzzetti, F., Rainfall thresholds for the possible occurrence of landslides in Italy. Natural Hazards and Earth System Sciences, 10, , doi: /nhess
(Brunetti et al., 2010)
M.T. Brunetti & S. Peruccacci

14. Empirical Rainfall Thresholds
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A FREQUENTIST METHOD
Log(D)
Log(I)
Power-law fit of D-I
rainfall conditions
Differences d between
D-I data and the fit
Gaussian model of the d distribution
Thresholds for different
exceeding probabilities
Next, for each event, the difference between the cumulated event rainfall and the fit is calculated.
References:
Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., Guzzetti, F., Rainfall thresholds for the possible occurrence of landslides in Italy. Natural Hazards and Earth System Sciences, 10, , doi: /nhess
(Brunetti et al., 2010)
M.T. Brunetti & S. Peruccacci

15. Empirical Rainfall Thresholds
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A FREQUENTIST METHOD
Log(D)
Log(I)
Power-law fit of D-I
rainfall conditions
Differences d between
D-I data and the fit
Gaussian model of the d distribution
Thresholds for different
exceeding probabilities
Next, the probability density of the differences is determined using a Kernel Density approach, and the result is modelled with a Gaussian function.
References:
Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., Guzzetti, F., Rainfall thresholds for the possible occurrence of landslides in Italy. Natural Hazards and Earth System Sciences, 10, , doi: /nhess
(Brunetti et al., 2010)
M.T. Brunetti & S. Peruccacci

16. Empirical Rainfall Thresholds
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A FREQUENTIST METHOD
Log(D)
Log(I)
Power-law fit of D-I
rainfall conditions
Differences d between
D-I data and the fit
Gaussian model of the d distribution
Thresholds for different
exceeding probabilities
Then, using the modeled distribution, different thresholds corresponding to different exceedence probabilities can be calculated.
References:
Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., Guzzetti, F., Rainfall thresholds for the possible occurrence of landslides in Italy. Natural Hazards and Earth System Sciences, 10, , doi: /nhess
(Brunetti et al., 2010)
M.T. Brunetti & S. Peruccacci

17. Empirical Rainfall Thresholds
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A FREQUENTIST METHOD
Log(D)
Log(I)
Power-law fit of D-I
rainfall conditions
Differences d between
D-I data and the fit
Gaussian model of the d distribution
Thresholds for different
exceeding probabilities
For example, the figure shows the 5% rainfall threshold for the possible initiation of landslides in Italy. This means that, if we assume that this catalogue is representative for the Italian territory, the 5% threshold leaves 5% of the (D,E) points below the curve.
References:
Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., Guzzetti, F., Rainfall thresholds for the possible occurrence of landslides in Italy. Natural Hazards and Earth System Sciences, 10, , doi: /nhess
(Brunetti et al., 2010)
M.T. Brunetti & S. Peruccacci

18. THRESHOLD UNCERTAINTY
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Empirical Rainfall Thresholds
THRESHOLD UNCERTAINTY
The mean values of α (intercept) and γ (slope), and the associated uncertainties Δα and Δγ, can be estimated adopting a “bootstrap” statistical technique.
E = (Δ) · D(γΔγ)
E = (Δ) · D(γΔγ)
Adopting a bootstrapping statistical technique, as reported in Peruccacci et al. (2012), the uncertainty Δα and Δγ associated with the parameters that define the power law threshold curve can be determined.
The shaded area around the threshold line represents the uncertainty associated with the definition of the threshold, given the empirical data. The two plots show the same threshold, and the same associated uncertainty, in logarithmic coordinates (to the left) and in linear coordinates (to the right).
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

19. THRESHOLD UNCERTAINTY
Empirical Rainfall Thresholds
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THRESHOLD UNCERTAINTY
Δα, and Δγ decrease as the number of events increases.
The uncertainty associated with the model parameters, represented by the red and green error bars in the two figures, decrease as the number of events, reported in the abscissa, increases. For a number of events less than 75, the uncertainties of the two parameters α and γ are high.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

20. THRESHOLD UNCERTAINTY
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Empirical Rainfall Thresholds
THRESHOLD UNCERTAINTY
Δα, and Δγ decrease as the number of events increases.
n = 75
n =75
For a number of events between 75 and 175, α and γ do not change significantly (e.g., α varies less than 0.2 mm), but the relative uncertainties Δα/α and Δγ/γ remain high.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

21. THRESHOLD UNCERTAINTY
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Empirical Rainfall Thresholds
THRESHOLD UNCERTAINTY
Δα, and Δγ decrease as the number of events increases.
n = 175
n =175
For practical purposes, including the application of the ED thresholds in a landslide warning system, we accept a 10% relative uncertainty i.e., Δα/α ≤ Adopting this criterion, the minimum number of rainfall events required to establish a threshold with the available data set is n = 175. For this number of events, the corresponding relative uncertainty in the scaling exponent of the power law threshold curve is Δγ/γ = 0.06 (6%).
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

22. Empirical Rainfall Thresholds
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A CASE STUDY
Abruzzo
Marche
Umbria
(AMU)
Central Italy
 28,600 km2
Here, we will present some results for three regions in central Italy, Abruzzo, Marche and Umbria. The study area is about 28,600 square kilometers.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

23. Empirical Rainfall Thresholds
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STUDY AREA
442 rainfall events
573 landslides
Feb Aug 2010
150 rain gauges
For the Abruzzo, Marche, and Umbria regions a catalogue of rainfall events with 573 landslides was compiled, between February and August 2010.
For each event, the duration D (in hours) and the total event rainfall E (in mm) was determined using rainfall measurements obtained from a dense network of 150 rain gauges, shown by black triangles in the map.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

24. LANDSLIDE INFORMATION SOURCES
Empirical Rainfall Thresholds
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LANDSLIDE INFORMATION SOURCES
National, regional and local newspapers
Blogs and on-line sources
Reports of local Fire Brigades
Reports of CCISS (Italian agency that provides traffic and travel information)
The information on rainfall induced landslides was obtained searching:
National, regional and local newspapers;
Blogs and on-line sources;
Reports of local Fire Brigades;
Reports of CCISS (Italian agency that provides traffic and travel information).
M.T. Brunetti & S. Peruccacci

25. THRESHOLDS FOR THE STUDY AREA
Empirical Rainfall Thresholds
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THRESHOLDS FOR THE STUDY AREA
T5,AMU E=(7.40.5)D0.380.02
T5,AMU
Marche, 188 events
Umbria, 170 events
Abruzzo, 84 events
T5,AMU
A preliminary ED threshold for the entire study area was defined.
The main plot shows, in log–log coordinates, the distribution of rainfall duration and cumulated event rainfall conditions that have resulted in landslides in Abruzzo (blue dots), Marche (grey dots), and Umbria (red dots). The brown line is the 5% ED threshold for the entire data set and the inset shows the same threshold in linear coordinates, with the shaded area showing the uncertainty associated to the threshold.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

26. Empirical Rainfall Thresholds
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Empirical Rainfall Thresholds
REGIONAL THRESHOLDS
T5,U
T5,A
T5,M
M, 188 events
U, 170 events
A, 84 events
Thresholds for Marche, Abruzzo and Umbria are equivalent and statistically indistinguishable
T5,A E=(6.41.2)D0.420.05
T5,M E=(8.60.8)D0.350.02
The figure shows, in linear coordinates, the 5% ED thresholds and their uncertainties for the three individual regions. In the figure, the uncertainty depends mainly on the size of the catalogue (for instance, compare 84 events in Abruzzo to 188 events in Marche.
The ED thresholds for the Abruzzo, Marche, and Umbria regions are statistically indistinguishable.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
T5,U E=(6.60.8)D0.410.02
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

27. LITHOLOGICAL CLASSIFICATION
Empirical Rainfall Thresholds
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LITHOLOGICAL CLASSIFICATION
PO: Post-Orogenic sediments
CC: Carbonate rocks
FD: Flysch deposits
CH: Chaotic complex
VR: Volcanic rocks
To investigate the relationships between lithology and rainfall thresholds, each landslide in the catalogue was attributed to a lithology type using a 1:500,000 scale lithological map that shows five main complexes, namely Chaotic, Carbonate, and Volcanic rocks, Post-Orogenic sediments, and Flysch deposits. The pie chart shows the extent and the percentage of the lithological complexes, and the histogram shows the number and the proportion of landslides in each lithological complex.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

28. LITHOLOGICAL CLASSIFICATION
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Empirical Rainfall Thresholds
LITHOLOGICAL CLASSIFICATION
PO: Post-Orogenic sediments
CC: Carbonate rocks
FD: Flysch deposits
CH: Chaotic complex
VR: Volcanic rocks
P1 < 1 km2 => A = 0.5 km2
P2 < 10 km2 => A = 5 km2
Landslides, mapped as single points, were attributed a level of mapping accuracy P, in three classes. Each landslide was represented by a circle, with the area of the circle dependent on the mapping accuracy. The values were selected heuristically, as a compromise between the landslide mapping accuracy and the scale of the lithological map. The landslide circles were then intersected with the lithological map, and a lithological type was attributed to each landslide if it covered 75% of more of the circle. Landslides that did not satisfy this criterion were excluded from the analysis.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
P3 < 100 km2 => A = 50 km2
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

29. LITHOLOGICAL THRESHOLDS
Empirical Rainfall Thresholds
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LITHOLOGICAL THRESHOLDS
PO, 211 events
FD, 82 events
CC, 88 events
T5,CC
T5,PO
Post-Orogenic sediments
Carbonate rocks
Flysch deposits
Using this procedure, 381 events were attributed to a specific lithological type. ED thresholds for three main lithological complexes (Post-Orogenic sediments, Flysch deposits and Carbonate rocks) were determined. For the other rock types, the number of events was too small to determine specific thresholds.
The figure shows, in log-log coordinates, the distribution of the rainfall conditions that have resulted in landslides in Post-Orogenic sediments (orange dots), in Flysch deposits (green dots), and in Carbonate rocks (purple dots) together with the 5% thresholds for the same three lithological complexes.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

30. LITHOLOGICAL THRESHOLDS
Empirical Rainfall Thresholds
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LITHOLOGICAL THRESHOLDS
FD threshold is persistently higher than PO and CC thresholds
T5,CC
T5,FD
T5,PO
PO, 211 events
FD, 82 events
CC, 88 events
PO and CC thresholds are statistically indistinguishable
T5,FD E=(10.31.5)D0.370.03
T5,CC E=(9.01.5)D0.320.04
The same ED lithological thresholds in linear coordinates with their relative uncertainties. The green threshold for Flysch terrains is systematically higher than (and statistically different from) the equivalent thresholds for the Post-Orogenic sediments (in orange) and the Carbonate rocks (in purple). This means that the cumulated amount of rainfall necessary to trigger landslides in Flysch deposits is higher than in the other two lithological complexes. Moreover, the thresholds for the Post-Orogenic sediments and for the Carbonate rocks are indistinguishable in the study area.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
T5,PO E=(7.40.6)D0.370.02
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

31. SEASONAL CLASSIFICATION
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Empirical Rainfall Thresholds
SEASONAL CLASSIFICATION
MS, May-September
OA, October-April
AMU: Abruzzo-Marche-Umbria
A: Abruzzo
M: Marche
U: Umbria
PO: Post-Orogenic sediments
CC: Carbonate rocks
FD: Flysch deposits
In the study area, the different seasons are characterized by different types of meteorological events. In the summer, rainfall is associated primarily with convective events characterized by short duration and high intensity. In the period from autumn to spring, abundant rainfall is associated with regional frontal systems, characterized by long duration and low mean intensity. To investigate possible seasonal effects of different rainfall types on the ED thresholds, the catalogue of rainfall events was segmented by the month of occurrence, and two datasets were obtained: one for the period from May to September and a second for the period from October to April.
The left bar chart shows the proportion of rainfall events for different rainfall durations. The right bar chart the proportion of rainfall events with landslides for different subsets.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

32. Empirical Rainfall Thresholds
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SEASONAL THRESHOLDS
MS, May-September 160 events
OA, October-April 282 events
T5,MS
T5,OA
The figure shows, in log-log coordinates, the ensemble of the rainfall conditions that have resulted in landslides in the periods May to September (light blue dots), and October to April (grey dots) together with the 5% thresholds for the two seasonal periods. Light blue dots predominate for rainfall duration less than 24 hours, and grey dots are more abundant for rainfall duration larger than 24 hours.
Bar charts show number of rainfall events with landslides in the different months.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

33. Empirical Rainfall Thresholds
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Empirical Rainfall Thresholds
SEASONAL THRESHOLDS
MS, 211 events
OA, 82 events
T5,MS
T5,OA = ≠
MS and OA thresholds are statistically different for D<12 h and D>100 h
The thresholds are indistinguishable for 12<D<100 h
T5,MS E=(8.30.7)D0.330.02
The figure shows the same seasonal thresholds, in linear coordinates, with the uncertainty portrayed by the shaded areas.
Due to the uncertainty, the seasonal thresholds are statistically different only for rainfall durations shorter than 12 hours and longer than 4 days. In the intermediate range of durations, the seasonal thresholds are statistically indistinguishable.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
T5,OA E=(5.50.6)D0.460.02
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

34. Empirical Rainfall Thresholds
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THRESHOLD COMPARISON
This figure compares cumulated event rainfall – rainfall duration thresholds for possible landslide occurrence in Italy, and worldwide.
New thresholds are in color.
The dashed black line is the 5% Frequentist threshold for Italy reported in Brunetti et al. (2010).
The dotted black line is the global ED threshold for debris flows proposed by Innes in 1983.
The new ED thresholds for central Italy indicate that landslides in the study area are triggered by less severe rainfall conditions than previously recognized. This has consequences for landslide forecasting, and for hazard and risk assessment.
References:
Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, ,
(Peruccacci et al., 2012)
M.T. Brunetti & S. Peruccacci

35. Empirical Rainfall Thresholds
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CONCLUSIONS
Empirical rainfall thresholds can contribute to forecasting the possible occurrence of rainfall- induced landslides
Use of objective and reproducible methods allows comparison of thresholds defined for different areas
Robustness of the thresholds depends on the size of the empirical data set
To conclude:
Empirical rainfall thresholds can contribute to forecast the possible occurrence of rainfall-induced landslides;
Use of objective and reproducible methods allows to compare thresholds defined for different areas;
Robustness of the thresholds depends on the size of the empirical data set, and …
M.T. Brunetti & S. Peruccacci

36. Empirical Rainfall Thresholds
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CONCLUSIONS
Knowing the uncertainty associated to the thresholds is important for their use in landslide warning systems
Knowing the uncertainty associated to the thresholds is important for their use in landslide warning systems.
M.T. Brunetti & S. Peruccacci

37. Empirical Rainfall Thresholds
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M.T. Brunetti & S. Peruccacci

38. Empirical Rainfall Thresholds
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REFERENCES 1/2
Aleotti, P., A warning system for rainfall-induced shallow failures. Engineering Geology, 73, 247–265. Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., Guzzetti, F., Rainfall thresholds for the possible occurrence of landslides in Italy. Natural Hazards and Earth System Sciences, 10, 447–458, doi: /nhess Caine, N., The rainfall intensity-duration control of shallow landslides and debris flow. Geografiska Annaler A, 62, 23–27. Cruden, D.M., Varnes, D.J., Landslide types and processes. In: Turner, A.K., Schuster, R.L. (Eds.), Landslides, Investigation and Mitigation, Special Report 247. Transportation Research Board, Washington D.C., pp. 36–75. ISSN: X, ISBN: X. Guzzetti, F., Peruccacci, S., Rossi, M., Stark, C.P., Rainfall thresholds for the initiation of landslides in central and southern Europe. Meteorology and Atmospheric Physics, 98, 239–267, doi: /s Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C.P., The rainfall intensity-duration control of shallow landslides and debris flows: an update, Landslides, 5(1), 3–17.
Here are the references used in this lesson.
M.T. Brunetti & S. Peruccacci

39. Empirical Rainfall Thresholds
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REFERENCES 2/2
Iverson, R.M., Landslide triggering by rain infiltration. Water Resources Research, 36(7): 1897–1910. Innes, J.L., Debris flows. Progress in Physical Geography, 7, 469–501. Montgomery, D.R. & Dietrich, W.E.:, A physically based model for the topographic control of shallow landsliding. Water Resources Research, 30(4), 1153–1171. Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C, Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology, , 79–90. Varnes, D.J., Slope movements: types and processes. In: Schuster, R.L., Krizek, R.J. (Eds.), Landslide Analysis and Control, National Academy of Sciences, Special Re- port 176. Transportation Research Board, Washington D.C., pp. 11–33. White, I.D., Mottershead, D.N,. Harrison, J.J., Environmental systems, 2nd ed. London: Chapman & Hall, pp. 616.
M.T. Brunetti & S. Peruccacci