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A stationary criterion to identify the duration of efficient rainfalls to trigger shallow landslides
Full text linkEven though rainfall is considered a well known trigger of natural slope instability, its effective role in initiating
landsliding phenomena cannot be easily distinguished due to many time- and space- variable interactions among
several factors (i.e. slope geometry, mechanical and hydraulic characters of superficial layers and the basin, etc.).
A common approach to relate rainfall to the onset of shallow landslides is to plot effective rainfall intensity vs
duration to draw intensity threshold lines. Since the earliest work by Caine (1980) on this topic, several researchers
have tried to establish intensity thresholds by means of deterministic and probabilistic approaches from a
number of worldwide and regional rainfall-landslide inventories. With respect to this intensity-duration threshold
approach, information about rainfall-induced landslides are generally collected from chronicles or historical
landslide time series, whilst no data about the hydraulic and geometric features of soils and rocks involved into
the natural slope instability is commonly taken into account. On the contrary, rainfall heights at different time lag
(even every 30 min) are available at different stations by rain gauges. As rain gauge measurements are concerned,
these can suffer many problems such as temporary saturation, temporary lack of data transmission and anomalous
geographical distribution of the rainfall. Recently, satellite data have been employed to quantify the rainfall event
related to landslide occurrence but their correlation to the effective rainfall height at a site is not guaranteed yet.
So far, rain gauge measures still represent the most used option. Moreover, the physical simplification introduced
by such “rainfall based” approach on landslide prediction can be accepted due to the assumption that only shallow
landslides are considered for drawing a regional intensity-duration threshold from the considered data.
Starting from the above considerations, and within the framework of a nationwide project by CNR-IRPI, under
funds from the National Civil Department, the authors propose in this article a new criterion to identify from rain
gauge measures the duration of the rainfalls triggering shallow landslides. The new criterion represents an attempt
to identify the duration of the “effective rainfall event” responsible for the landslide occurrence, as reported by
newspaper clips and/or in real time web newspapers. At this regard, antecedent precipitations are not taken into
account, since the model considers only that amount of rainfall that effectively triggers the slope failure. The
model analyses the hourly rainfall time series for at least one month before occurrence of the shallow landslide,
using a historical landslide archive covering the time range between 2002 and 2011 in the Lazio Region, central
Italy. This archive was obtained by a procedure consisting of the following steps: i) critical scrutiny of chronicles,
ii) identification of the landslide site, and iii) retrieval of the rainfall data from the nearest rain gauge station within
the pluviometric network provided by the National Department of Civil Protection. The proposed method, for
each reported landslide, uses the cumulative function of the rainfall heights and rainfall intensity calculated for
different time lag. Then, in order to identify the beginning of the effective rainfall event, two conditions have to be
satisfied: (1) the difference in rainfall intensity between two adjacent windows must be very low, and (2) the time
series of lack of rainfall must be stationary. When these conditions are met, the initial time of the efficient rainfall
necessary to trigger the landslide is established. Such criterion is statistically based according to the rainfall time
distribution only.
No assumption is needed on the probabilistic distributions of time series of rain/not rain. Such approach has been
successfully applied to medium-to-long rainfalls, for which rain/not rain datasets are statistically significant. Very
short rainfall durations (i.e. a few hours), due to the small number of data, are not suitable to this approach, but, on
the other hand, their onset is generally easily recognizable by visual inspection of the height pluviometric trends
Liquefaction damage potential for seismic hazard evaluation in urbanized areas
No full textThe liquefaction susceptibility of granular soils under seismic actions is commonly estimated by means of the liquefaction safety factor and recently by the potential index also. Since its original formulation the potential index has been developed and modified according to both deterministic and probabilistic approaches in order to draw liquefaction microzonation maps. In this study a new approach to potential index definition is proposed in order to relate the liquefaction potential prediction to the loss of bearing capacity for shallow foundation. Such new method has been used to estimate the so called liquefaction damage potential PDL at Barletta site, located in Puglia Region, where strong seismic events may occur. © 2011 Elsevier Ltd
GIS-based landslide hazard evaluation at the regional scale: some critical points in the permanent displacement approach for seismically-induced landslide maps
Full text linkLandslide susceptibility and hazard are commonly developed by means of GIS (Geographic Information Systems)
tools. Many products such as DTM (Digital Terrain Models), and geological, morphological and lithological
layers (often, to be downloaded for free and integrated within GIS) are nowadays available on the web and ready
to be used for urban planning purposes. The multiple sources of public information enable the local authorities
to use these products for predicting hazards within urban territories by limited investments on technological
infrastructures. On the contrary, the necessary expertise required for conducting pertinent hazard analyses is high,
and rarely available at the level of the local authorities. In this respect, taking into account the production of
seismically-induced landslide hazard maps at regional scale drawn by GIS tool, these can be performed according
to the permanent displacement approach derived by Newmark’s sliding block method (Newmark, 1965). Some
simplified assumptions are considered for occurrence of a seismic mass movement, listed as follows: (1) the
Mohr-Coulomb criterion is used for the plastic displacement of the rigid block; (2) only downward movements are
accounted for; (3) a translative sliding mechanism is assumed. Under such conditions, several expressions have
been proposed for predicting permanent displacements of slopes during seismic events (Ambresys and Menu,
1988; Luzi and Pergalani 2000; Romeo 2000; Jibson 2007, among the others). These formulations have been
provided by researchers for different ranges of seismic magnitudes, and for indexes describing the seismic action,
such as peak ground acceleration, peak ground velocity, Arias Intensity, and damage potential. With respect to the
resistant properties of the rock units, the critical acceleration is the relevant strength variable in every expressions;
it is a function of local slope, groundwater level, unit weight shear resistance of the surficial sediments, and the
assumed depth of the sliding surface. Thus, it is of paramount relevance to correctly understand and describe the
dynamic behavior of the lithologies affected by the earthquake. Accordingly, we put here in evidence some critical
points in the application of the permanent displacement formulations by considering the case study of Santa
Susana Mountains (California, USA) shaken by the Northridge earthquake in 1994. During this earthquake, a high
number of registrations has been collected, whilst soon after a careful inventory of the mass movements triggered
by the shaking has been produced, together with analysis of the related failure mechanisms. Hence, these data
allow to perform a back analysis in order to verify the reliability of some numerical expressions, such as those
proposed by Ambraseys and Menu (1988), Romeo (2000), and Jibson (2007), with respect to the possible dynamic
behavior of the lithologies affected by landslides. In this sector of California, the following lithologies crop out,
that were involved in shallow landslides: (1) Quaternay deposits; (2) Saugus Formation; (3) Towsley Formation;
(4) Pico Formation; (5) Topanga Formation; (6) Modelo Formation; (7) Simi Conglomerate; (8) Santa Susana
Formation; (9) Llajas and Chatsworth Formations. The surveys carried out after the Northridge earthquake (Harp
and Jibson, 1995), and the analysis of landslide distribution (Parise and Jibson 2000) pointed out that the strongest
formations with slopes higher than 50 mainly suffered toppling or fall failures: thus, our hazard maps based on
permanent displacements did not take into account such range of slopes. Further, areas with slopes lower than
10 were not affected by relevant mass movements. Thus, a limited range of slopes (between 10 and 45) was
considered in the analyses, with depth of the sliding surface varying between 1 and 3 m, and using the resistance
parameters of involved lithologies obtained from in situ and laboratory tests performed by local practitioners.
Seismically-induced landslide hazard maps have been drawn using the aforementioned three expressions. The
preliminary results show Quaternary deposits (including alluvium deposits, slope wash, and terrace deposits) as
the lithologies most affected by permanent displacement. Moreover, Towsley and Modelo formations, that are
stiffer than the previous rock units, and consist mostly of shales, siltstones and subordinate sandstones, show
high hazard value where the slopes increase. The relevant role of local slope in permanent displacement extent
is evident where lithologies are characterized by both cohesive and frictional resistance components
Spatially variable soils affecting geotechnical strip foundation design
No full textNatural soil variability is a well-known issue in geotechnical design, although not frequently managed in practice.
When subsoil must be characterised in terms of mechanical properties for infrastructure design, random finite
element method (RFEM) can be effectively adopted for shallow foundation design to gain a twofold purpose: (1)
understanding how much the bearing capacity is affected by the spatial variability structure of soils, and (2)
optimisation of the foundation dimension (i.e. width B). The present study focuses on calculating the bearing
capacity of shallow foundations by RFEM in terms of undrained and drained conditions. The spatial variability
structure of soil is characterized by the autocorrelation function and the scale of fluctuation (). The latter has
been derived by geostatistical tools such as the ordinary Kriging (OK) approach based on 182 cone penetration
tests (CPTs) performed in the alluvial plain in Bologna Province, Italy. Results show that the increase of the B/
ratio not only reduces the bearing capacity uncertainty but also increases its mean value under drained
conditions. Conversely, under the undrained condition, the autocorrelation function strongly affects the mean
values of bearing capacity. Therefore, the authors advise caution when selecting the autocorrelation function
model for describing the soil spatial variability structure and point out that undrained conditions are more
affected by soil variability compared to the drained ones
Random field theory applied to the prediction of a pile bearing capacity and settlement measured at Araquari site (Brazil)
No full textThis contribution discusses the application of the Random Field theory to geotechnical variables for making prediction on the ultimate bearing capacity
and the final settlement of a single pile of 1 m diameter and 24 m length through a piezocone penetration test CPTu drilled into sandy soils at Araquari site (Brazil). From this study the calculated ratio between the measured and the predicted bearing capacity is about two. The distribution of the load along the pile shaft is similar to the measured one although the absolute value of the calculated load is about the half. Thus, in the case of the Araquari sand and silt mixture the characteristic value approach performed by the evaluation of the mean trend and the spatial variability structure of the residuals is highly conservative
Modeling 3D soil lithotypes variability through geostatistical data fusion of CPT parameters
No full textThe Cone Penetration Test (CPT) measures enable to recognize vertical lithological sequence at each investigated point. From the tip resistance qc and sleeve resistance fs profiles, the Soil Behavior Type index ISBT has been calculated, in order to identify the lithotypes alongside depth. The present study focuses on the combination of different variables to provide a lithological and mechanical subsoil characterization. The main objectives of the paper are: (1) to model the 3D spatial variability structure of the soil lithotypes and mechanical properties using qc and fs profiles; 2) to evaluate the uncertainties of the estimates for designing purposes. 182 CPTs were collected in a 900 km2 area (corresponding to a subsoil volume of about 12 km3) located in the study site in the Bologna province (Italy). The study area is made up of fine-grained soils, silt and clay mixtures that are intercalated at different depths by sandy and gravelly soils. These variations of each soil fraction affect the engineering properties of these alluvial deposits. For 3D modeling, two geostatistical methods, Ordinary Kriging (stationary method), and Intrinsic Random Function theory (non-stationary method) have been used. The results show that the non-stationary method allows to obtain more reliable qc and fs predicted values. The final stochastic mechanical and lithological model enables engineers and geologists to detect the emerging of fan and paleochannels bodies where mean resistance values can abruptly change in terms of bearing capacity, liquefaction potential and static and dynamic settlement occurrence
Calculating Reliable Engineering Geological Model through Stochastic Co-Simulation Applied to CPTu Data
No full textTo perform a geotechnical reliable design, the spatial variability and the uncertainties related to the adopted engineering geological model (EGM) must be taken into account. However, any conceived EGM is characterized by uncertainties covering (1) the bias in the mathematical expression that transforms the measured parameters into design ones; and (2) the uncertainty associated with the variability of the soil and rock parameters in the prediction equations. Hereinafter, the sequential Gaussian co-simulation method (SGCS) has been applied to propagate the uncertainty in the calculation of the undrained shear resistance su from measured CPTu profiles (i.e., qc, fs, u2) through a linear model of co-regionalization. The studied area is located in the Po River alluvial plain (Bologna Province, Italy), where the mixture of silts, sands, and clays gets thicknesses of hundreds of meters. These heterogeneous deposits have been mechanically characterized through a 3D EGM to be used in reliability-based designing
3D SPATIAL VARIABILITY OF MECHANICAL PROPERTIES OF EMILIA ROMAGNA ALLUVIAL DEPOSITS AND ITS IMPLICATIONS IN GEOTECHNICAL DESIGNING OF FOUNDATIONS
No full textStatistical description of large datasets of cumulated and duration values related to shallow landslides initiated by rainfalls
Full text linkEmpirical rainfall thresholds are a well established method to draw information about Duration (D) and Cumulated
(E) values of the rainfalls that are likely to initiate shallow landslides. To this end, rain-gauge records
of rainfall heights are commonly used. Several procedures can be applied to address the calculation of the
Duration-Cumulated height and, eventually, the Intensity values related to the rainfall events responsible for
shallow landslide onset. A large number of procedures are drawn from particular geological settings and climate
conditions based on an expert identification of the rainfall event. A few researchers recently devised automated
procedures to reconstruct the rainfall events responsible for landslide onset. In this study, 300 pairs of D, E
couples, related to shallow landslides that occurred in a ten year span 2002-2012 on the Italian territory, have been
drawn by means of two procedures: the expert method (Brunetti et al., 2010) and the automated method (Vessia
et al., 2014). The two procedures start from the same sources of information on shallow landslides occurred
during or soon after a rainfall. Although they have in common the method to select the date (up to the hour of the
landslide occurrence), the site of the landslide and the choice of the rain-gauge representative for the rainfall, they
differ when calculating the Duration and Cumulated height of the rainfall event. Moreover, the expert procedure
identifies only one D, E pair for each landslide whereas the automated procedure draws 6 possible D,E pairs
for the same landslide event. Each one of the 300 D, E pairs calculated by the automated procedure reproduces
about 80% of the E values and about 60% of the D values calculated by the expert procedure. Unfortunately,
no standard methods are available for checking the forecasting ability of both the expert and the automated
reconstruction of the true D, E pairs that result in shallow landslide. Nonetheless, a statistical analysis on marginal
distributions of the seven samples of 300 D and E values are performed in this study. The main objective of
this statistical analysis is to highlight similarities and differences in the two sets of samples of Duration and
Cumulated values collected by the two procedures. At first, the sample distributions have been investigated:
the seven E samples are Lognormal distributed, whereas the D samples are all distributed Weibull like. On E
samples, due to their Lognormal distribution, statistical tests can be applied to check two null hypotheses: equal
mean values through the Student test, equal standard deviations through the Fisher test. These two hypotheses
are accepted for the seven E samples, meaning that they come from the same population, at a confidence level
of 95%. Conversely, the preceding tests cannot be applied to the seven D samples that are Weibull distributed
with shape parameters k ranging between 0.9 to 1.2. Nonetheless, the two procedures calculate the rainfall
event through the selection of the E values; after that the D is drawn. Thus, the results of this statistical analysis
preliminary confirms the similarities of the two D,E pair set of values drawn from the two different procedures
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