196,266 research outputs found
A Simplified Approach to Assess the Soil Saturation Degree and Stability of a Representative Slope Affected by Shallow Landslides in Oltrepò Pavese (Italy)
Get PDFThe identification of the triggering mechanism of rainfall-induced, shallow landslides requires a complete understanding of the hydro-mechanical response of soil, which can be represented through the trends of the degree of soil saturation. In this paper, multiple annual cycles of soil saturation obtained through field monitoring were used to validate an empirical model based on climate data. Both field measurements and model outputs were used to conduct simplified slope stability analysis to evaluate the model chain capability in predicting the temporal occurrence of shallow failures. Field data were collected on a testsite slope located in Oltrepò Pavese (Northern Italy), where a shallow landslide occurred during the monitoring period. The experimental trends of the degree of saturation at various depths in the soil profile were compared with the calculated values and showed good agreement. Landslide triggering is reached when the soil is completely saturated. Both measured and modeled trends of soil saturation correctly identified the triggering time of the shallow landslide and the depth of the sliding surface, 1.0 m below the ground surface, in the test slope. The obtained results indicated the possibility of extending this approach for theassessment of the initiation time and the depth of shallow landslides, particularly for preliminary susceptibility evaluations, based on widely available climate data
The impact of hydrological parameters on modelling slope safety factor towards shallow landslides: a case study from Oltrepò Pavese
No full textHydrological monitoring of slope susceptible to shallow landslides allows for identifying the triggering conditions of shallow failures and implementing slope stability analysis at site-specific scale. In this work, a case study of a long-term hydrological monitoring in a slope susceptible to shallow landslides of Oltrepò Pavese (Northern Italy) is presented. The triggering mechanism develops in wet seasons (winter and spring) due to the uprise of a perched water table at about 1 m from ground surface, in consequence of the most intense rainfalls (about > 60 mm in 48 h). Unstable conditions (safety factor < 1.0) are correctly modeled on the basis of both water content and pore water pressure, with a better prediction considering hysteresis effects. Safety factor on the basis of water content can correctly assess the triggering conditions for unsaturated and completely saturated soils. It is possible estimating shallow landslides triggering caused by positive pore water pressures only considering this parameter
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
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
Assessment of topsoil evolution associated with land use change in Val Camonica subalpine grasslands
Get PDFAlpine pastures and meadows are agroecosystems with biological and landscape importance, protected by the European Union. Grassland areas had a rapid decline in the last decades due to changes in management and/or abandonment of traditional mountain farming in the Alps.
The aim of our study is the characterization of the relationship between historical and present-day subalpine grassland management, their plant diversity, soil properties and humus forms. Humus forms are important indicators of biological functioning of soils and of organic matter degradation pathways, easily affected by land use change.
We chose two areas in Alta Valle Camonica (Rhaetian Alps, Lombardy), between 1800-2000 m a.s.l., on sialic glacial till, characterized by strong land use changes, as visible in historical aerial photographs. Since the 70s, large herbaceous surfaces are being colonized by subalpine heath and forests, because of a decreased and more localized grazing pressure. We selected 21 sites across six dynamic phases from grazed grassland to forest, in which we performed phytosociological surveys (10x10 m) according to the Braun-Blanquet method, a soil profile and a characterization of topsoil and organic horizons to detect humus forms and properties. Standard physico/chemical soil properties were analyzed in the lab.
The widespread decrease in grazing intensity led to an expansion of less palatable grasses (e.g., Nardus stricta L.), shrubs and trees, and thus changes in plant diversity and vegetation structure.
Soils are mostly Entic/Umbric Podzols, Histosols in bogs. Humus forms are more varied: we observed Rhizo humus systems where grass roots were a main source of organic matter in soils. Mull and Amphi are the main forms in grazed areas, Dysmoders and Hemimoders in abandoned soils colonized by trees, Tangels in bogs; no Mors have been detected.
Thus, humus forms and biological activity/organic matter degradation pathways can describe the gradients in land use change. Some more differences might be observed in the experimental phases, with microbial analysis and topsoil thin section observations
Improving the estimation of complete field soil water characteristic curves through field monitoring data
Get PDFIn this work, Soil Water Characteristic Curves (SWCCs) were reconstructed through simultaneous field measurements of soil pore water pressure and water content. The objective was to evaluate whether field-based monitoring can allow for the improvement of the accuracy in SWCCs estimation with respect to the use of laboratory techniques. Moreover, field assessment of SWCCs allowed to: a) quantify the hydrological hysteresis affecting SWCCs through field data; b) analyze the effect of different temporal resolution of field measures; c) highlight the differences in SWCCs reconstructed for a particular soil during different hydrological years; d) evaluate the reliability of field reconstructed SWCCs, by the comparison between assessed and measured trends of a component of the soil water balance. These aspects were fundamental for assessing the reliability of the field reconstructed SWCCs. Field data at two Italian test-sites were measured. These test-sites were used to evaluate the goodness of field reconstructed SWCCs for soils characterized by different geomorphological, geological, physical and pedological features. Field measured or laboratory measured SWCCs data of 5 soil horizons (3 in a predominantly silty soil, 2 in a predominantly clayey one) were fitted by Van Genuchten model. Different field drying and wetting periods were identified, based on monthly meteorological conditions, in terms of rainfall and evapotranspiration amounts, of different cycles. This method allowed for a correct discrimination of the main drying and the main wetting paths from field data related and for a more reliable quantification of soil hydrological properties with respect to laboratory methodologies. Particular patterns of changes in SWCCs forms along depth could be also identified. Field SWCCs estimation is not affected by the temporal resolution of the acquisition (hours or days), as testified by similar values of Van Genuchten equation fitting parameters. Instead, hourly data may offer a clearer vision of the drying and wetting paths, due to the highest number of experimental data points. Moreover, in temperate climate situations as those of the test-sites, main drying curves and main wetting curves of a particular soil were substantially similar also for different hydrological cycles with peculiar meteorological conditions. SWCCs parameters were implemented in a numerical code (HYDRUS-1D) to simulate soil water storage for different soil horizons. Field reconstructed SWCCs allowed for simulating with a higher precision these trends, confirming the reliability of the reconstructed field curves by a quantitative point of view. Moreover, best results were obtained considering hysteresis in the modeling
Monitoring of hydrological parameters for the identification of shallow landslides triggering: A case study from Northern Italy
No full textLong-term continuous hydrological monitoring of slope susceptible to shallow landslides is a fundamental tool for analyzing the main soil hydrological behaviors and identifying the conditions which lead to shallow failures. In this work, a case study of a long-term hydrological monitoring, in the period 2012–2015, of a slope susceptible to shallow landslides located in Oltrepò Pavese (Northern Italy) is presented. The soil is characterized by different hydrological behaviors along the year, due to rainfall trends. The main triggering mechanism develops in wet seasons (winter and spring), when soil approaches saturated conditions, for uprising of a perched water table at about 1 m from ground surface, in consequence of the most intense rainfalls (about > 60 mm in 48 h). Slope stability analysis shows that unstable conditions (safety factor < 1.0) are reached in correspondence of similar events. Safety factor trends allow to catch unstable conditions on the basis of both water content and pore water pressure
Extreme heat exposure in pregnancy and risk for preterm birth, low birth weight and stillbirths
No full textBöckmann M, Chersich MF, Pham MD, et al. Extreme heat exposure in pregnancy and risk for preterm birth, low birth weight and stillbirths. In: 16th World Congress on Public Health 2020 Public Health for the future of humanity: analysis, advocacy and action. European Journal of Public Health. Vol 30. Oxford: Oxford Univ Press; 2020
Coupling geophysical modelling and geodesy to unravel the physics of active faults
No full textThe major requirements of seismic hazard assessment must address mainly the information about the expected location, time and magnitude of the impending strong earthquakes, as well as the scenarios ground motion associated with the possible future seismic events. While the quick notification of seismic events, appears nowadays pretty well established, thanks to the development of regional and local seismic networks, in terms of prevention more and more importance is devoted to studies of the inter- and pre- seismic earthquake cycle. To improve the intra seismic and pre-seismic information, which may lead to an effective mitigation of seismic risk, we are proposing an innovative approach, that combines Earth Observation data (GPS and SAR) and new advanced approaches in seismological and geophysical data analysis. The employed EO data are the observations acquired by means of SAR sensors, treated by Differential Interferometric techniques, the data observation acquired by permanent GPS stations or ldquoad-hocrdquo campaigns of the observations done over earthquake prone area. The aim is to combine the geophysical modelling of the faults with the surface displacement measured with the two mentioned techniques. In particular, application of the DInSAR techniques, using a stacking of interferograms, makes it possible, under the classical interferometric constraints (coherence, baseline, etc.), to retrieve a vertical displacements map, referred to a temporal interval, over areas where seismic fault system are localized. The displacements fields coming from GPS/DInSAR and other additional information, constitute the input for the geophysical model which shall indicate whether the fault is in a ldquocritical situationrdquo
Site-specific to local-scale shallow landslides triggering zones assessment using TRIGRS
Get PDFRainfall-induced shallow landslides are common phenomena in many parts of
the world, affecting cultivation and infrastructure and sometimes causing
human losses. Assessing the triggering zones of shallow landslides is
fundamental for land planning at different scales. This work defines a
reliable methodology to extend a slope stability analysis from the
site-specific to local scale by using a well-established physically based
model (TRIGRS-unsaturated). The model is initially applied to a sample slope
and then to the surrounding 13.4 km2 area in Oltrepò Pavese (northern
Italy). To obtain more reliable input data for the model, long-term
hydro-meteorological monitoring has been carried out at the sample slope,
which has been assumed to be representative of the study area. Field
measurements identified the triggering mechanism of shallow failures and
were used to verify the reliability of the model to obtain pore water
pressure trends consistent with those measured during the monitoring
activity. In this way, more reliable trends have been modelled for past
landslide events, such as the April 2009 event that was assumed as a
benchmark. The assessment of shallow landslide triggering zones obtained
using TRIGRS-unsaturated for the benchmark event appears good for both the
monitored slope and the whole study area, with better results when a
pedological instead of geological zoning is considered at the regional
scale. The sensitivity analyses of the influence of the soil input data show
that the mean values of the soil properties give the best results in terms
of the ratio between the true positive and false positive rates. The scheme
followed in this work allows us to obtain better results in the assessment
of shallow landslide triggering areas in terms of the reduction in the
overestimation of unstable zones with respect to other distributed models
applied in the past
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