1,720,983 research outputs found
Preliminary results of continuous monitoring of a slope with clayey soils prone to shallow landslides
No full textRainfall-induced shallow landslides are one of the most common type of landslides of the entire world. Besides the
limited volume of soil mobilized by these phenomena, they can provoke serious damages to cultivations, infrastructures
and buildings due to their high speed of development and their high density in small areas.
Shallow landslides triggering is strictly linked with the hydrological and mechanical responses of a usually unsaturated
soil to rainfalls. When these phenomena occur in clayey soils, hydro-mechanical behaviors are more complex because of
other different physico-chemical processes affecting soil shear strength, such as softening caused by repeated cycles of
shrinking-swelling.
Thus, to identify the physical and hydrological conditions leading to landslide triggering, a continuous monitoring of
unsaturated soil is needed, in particular related to the change in soil hydrological properties related to different rainy or
dry periods. This becomes fundamental also for correctly modeling slope safety factor.
In this work, the preliminary results of the continuous monitoring of a slope prone to shallow landslides with clayey
soils are presented. The test-site is located in Ardivestra catchment (central Oltrepò Pavese, northern Apennines, northwestern
Italy). It was affected by several shallow failures in the years 2009-2014.
The main aims of this work were: i) to characterize the slope soils by a multidisciplinary point of view; ii) to identify
the main soil hydrological behaviors; iii) to recognize the processes and the mechanisms which could promote the
triggering of shallow landslide.
The test-site soils were characterized by a multidisciplinary point of view, for identifying the features that can
influence the soil hydro-mechanical behavior. Soil geotechnical characterization allowed to measure the physical
parameters (grain size distribution, Atterberg Limits, volumetric index properties), the shear strength (direct shear tests,
oedometric tests), the shrinking-swelling potential. Hydrological characterization determined the water retention and
hydraulic conductivity properties. Pedological and mineralogical characterizations were also carried out.
Field monitoring allowed to identify the soil hydrological behaviors, linked to different meteorological conditions.
The station integrated field devices for measuring soil hydrological parameters (water content, pore water pressure, water
electrical conductivity) at different depths, with data of rainfall, air temperature, wind speed and direction. The monitoring
period has started in November 2015.
These results allowed also for recognizing the predisposing factors and the hydro-mechanical conditions that can lead
to trigger shallow landslides. Moreover, these analyses provided important indications for the correct application of slope
stability models in slopes with clayey soils
Soil water content estimated by Support Vector Machine for the assessment of shallow landslides triggering conditions: the role of antecedent meteorological conditions
No full textSoil water content is a key parameter for representing water dynamics in soils. Its prediction is fundamental for different practical
applications, such as identifying shallow landslides triggering. Support vector machine (SVM) is a machine learning technique,
which can be used to predict the temporal trend of a quantity since training from past data. SVM was applied to a test slope of
Oltrepò Pavese (northern Italy), where meteorological parameters coupled with soil water content at different depths (0.2, 0.4,
0.6, 1.0, 1.2, 1.4 m) were measured. Two SVM models were developed for water content assessment: (i) model 1, considering
rainfall amount, air temperature, air humidity, net solar radiation, and wind speed; (ii) model 2, considering the same predictors of
model 1 together with antecedent condition parameters (cumulated rainfall of 7, 30, and 60 days; mean air temperature of 7, 30,
and 60 days). SVM model 2 showed significantly higher satisfactory results than model 1, for both training and test phases and
for all the considered soil levels. SVM models trends were implemented in a methodology of slope safety factor assessment. For a
real event occurred in the tested slope, the triggering time was correctly predicted using data estimated by SVM model based on
antecedent meteorological conditions. This confirms the necessity of including these predictors for building a SVM technique
able to estimate correctly soil moisture dynamics in time. The results of this paper show a promising potential application of the
SVM methodologies for modeling soil moisture required in slope stability analysis
Exploiting Sentinel 1 and 2 data for geo-environmental monitoring of sandy coastal areas
No full textAnalysis of Hydro-meteorological Monitoring Data Collected in Different Contexts Prone to Shallow Landslides of the Oltrepò Pavese (Northern Italy)
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Soil Water Content Estimated by Support Vector Machine for the Assessment of Shallow Landslides Triggering: the Role of Antecedent Meteorological Conditions
No full textSoil water content is a key parameter for representing water dynamics in soils. Its prediction is fundamental for different practical applications, such as identifying shallow landslides triggering. Support vector machine (SVM) is a machine learning technique, which can be used to predict the temporal trend of a quantity since training from past data. SVM was applied to a test slope of OltrepÃ2 Pavese (northern Italy), where meteorological parameters coupled with soil water content at different depths (0.2, 0.4, 0.6, 1.0, 1.2, 1.4 m) were measured. Two SVM models were developed for water content assessment: (i) model 1, considering rainfall amount, air temperature, air humidity, net solar radiation, and wind speed; (ii) model 2, considering the same predictors of model 1 together with antecedent condition parameters (cumulated rainfall of 7, 30, and 60 days; mean air temperature of 7, 30, and 60 days). SVM model 2 showed significantly higher satisfactory results than model 1, for both training and test phases and for all the considered soil levels. SVM models trends were implemented in a methodology of slope safety factor assessment. For a real event occurred in the tested slope, the triggering time was correctly predicted using data estimated by SVM model based on antecedent meteorological conditions. This confirms the necessity of including these predictors for building a SVM technique able to estimate correctly soil moisture dynamics in time. The results of this paper show a promising potential application of the SVM methodologies for modeling soil moisture required in slope stability analysis
Validation of a short-term shoreline evolution model and coastal risk management implications
No full textVariations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
- …
