Characterisation of weathered clayey soils responsible for shallow landslides

Shallow earth translational slides and earth flows, affecting colluvial soils derived by the weathering of the clayey bedrock, are a recurrent problem causing damage to buildings and roads in many areas of Apennines. The susceptibility assessment, e.g. slope stability models, requires the preliminary characterization of these superficial covers (lithology, geotechnical and hydraulic parameters). <P> The aim of the work is to develop and test a methodology for the identification and mapping of weathered clayey soils responsible for shallow landslides. <P> A test site in Northern Apennines (Province of Pavia) was selected. Argillaceous and marly successions characterize the area. Shallow landslides occurred periodically due to high intensity rainfalls. Trench pits were used for the soil profile description (lithology, structure, grade of weathering, thickness) and sampling. The main geological, topographic and geomorphologic parameters of shallow landslides were analysed. Field surveys were integrated with some geotechnical laboratory tests (index properties, suction and volumetric characteristic determination, methylene blue adsorption test, linear shrinkage, swell strain). <P> Engineering geological zoning was carried out by grouping the superficial soils on the basis of the following attributes: topographic conditions (slope angle), landslide occurrence, lithology (grain size), geometry (thickness), lithology of the bedrock, hydrogeological and geotechnical characteristics. The resulting engineering-geological units (areas that may be regarded as homogeneous from the geomorphologic and engineering &ndash; geological point of view) were analysed in terms of shallow slope instability

PSI-based methodology to land subsidence mechanism recognition

Abstract. A methodology based on Persistent Scatterer Interferometry (PSI) is proposed in order to disentangle the contribution of different processes that act at different spatio-temporal scales in land subsidence (i.e. vadose zone processes as swelling/shrinkage of clay soils, soil consolidation and fluid extraction). The methodology was applied in different Italian geological contexts characterized by natural and anthropic processes (i.e. a Prealpine valley and the Po Plain in northern Italy)

Comparison between different approaches to modeling shallow landslide susceptibility: a case history in Oltrepo Pavese, Northern Italy

Abstract. On the 27 and 28 April 2009, the area of Oltrepo Pavese in northern Italy was affected by a very intense rainfall event that caused a great number of shallow landslides. These instabilities occurred on slopes covered by vineyards or recently formed woodlands and caused damage to many roads and one human loss. Based on aerial photographs taken immediately after the event and field surveys, more than 1600 landslides were detected. After acquiring topographical data, geotechnical properties of the soils and land use, susceptibility analysis on a territorial scale was carried out. In particular, different physically based models were applied to two contiguous sites with the same geological context but different typologies and sizes of shallow landslides. This paper presents the comparison between the ex-post results obtained from the different approaches. On the basis of the observed landslide localizations, the accuracy of the different models was evaluated, and the significant results are highlighted

Characterisation of hydraulic head changes and aquifer properties in the London Basin using Persistent Scatterer Interferometry ground motion data

In this paper, Persistent Scatterer Interferometry was applied to ERS-1/2 and ENVISAT satellite data covering 1992–2000 and 2002–2010 respectively, to analyse the relationship between ground motion and hydraulic head changes in the London Basin, United Kingdom. The integration of observed groundwater levels provided by the Environment Agency and satellite-derived displacement time series allowed the estimation of the spatio-temporal variations of the Chalk aquifer storage coefficient and compressibility over an area of ∼1360 km2. The average storage coefficient of the aquifer reaches values of 1 × 10−3 and the estimated average aquifer compressibility is 7.7 × 10−10 Pa−1 and 1.2 × 10−9 Pa−1 for the periods 1992–2000 and 2002–2010, respectively. Derived storage coefficient values appear to be correlated with the hydrogeological setting, where confined by the London Clay the storage coefficient is typically an order of magnitude lower than where the chalk is overlain by the Lambeth Group. PSI-derived storage coefficient estimates agree with the values obtained from pumping tests in the same area. A simplified one-dimensional model is applied to simulate the ground motion response to hydraulic heads changes at nine piezometers. The comparison between simulated and satellite-observed ground motion changes reveals good agreement, with errors ranging between 1.4 and 6.9 mm, and being 3.2 mm on average

Observations on soil-atmosphere interactions after long-term monitoring at two sample sites subjected to shallow landslides

Soil-atmosphere interaction has implications in different scientific research contexts and is increasingly investigated through field measurements. This paper reports a detailed description of interaction between shallow soil and atmosphere at two test sites in Oltrepò Pavese area (Northern Italy). The two test sites are in the same climatic area but are characterised by different geological features. In fact, the first objective is to compare the behaviour of two different soils, namely a clayey-sandy silt (CL) and a silty clay (CH), under similar meteorological events. Soil-atmosphere interaction is studied on the basis of long-term (about 87 and 42&nbsp;months for the two test sites, respectively) monitoring data of both volumetric water content and soil water potential, recorded at different depths along two vertical soil profiles in the first two metres from ground level. Field measurements, together with meteorological data such as precipitation and air temperature, allow for clear identification of the seasonal fluctuations of unsaturated soil hydraulic properties. To infer detailed information, the recorded data were processed and relationships between soil water potential and water content were investigated. Different time spans, from several months to a few days, even including single rainy events, are considered to show the hydraulic soil behaviour. The hysteretic cycles of water content with respect to soil water potential and non-equilibrium flow are highlighted. In particular, the measured soil water potential is in the range of 0–800&nbsp;kPa and of 0–1500&nbsp;kPa for the CL and CH soil, respectively. At both sites, the observed hysteretic cycles are more frequent in the hot season (summer) than in the cold season (winter) and tend to reduce with depth. The experimental results are compared with the soil water characteristic curves (SWCCs) to assess whether and to what extent the SWCCs are reliable in modelling the hydraulic behaviour of partially saturated soils, under atmospheric forcing, at least in the considered climatic contexts

A data-driven method for the temporal estimation of soil water potential and its application for shallow landslides prediction

Soil water potential is a key factor to study water dynamics in soil and for estimating the occurrence of natural hazards, as landslides. This parameter can be measured in field or estimated through physically-based models, limited by the availability of effective input soil properties and pre-liminary calibrations. Data-driven models, based on machine learning techniques, could overcome these gaps. The aim of this paper is then to develop an innovative machine learning methodology to assess soil water potential trends and to implement them in models to predict shallow landslides. Monitoring data since 2012 from test-sites slopes in Oltrepò Pavese (northern Italy) were used to build the models. Within the tested techniques, Random Forest models allowed an outstanding recon-struction of measured soil water potential temporal trends. Each model is sensitive to meteorological and hydrological characteristics according to soil depths and features. Reliability of the proposed models was confirmed by correct estimation of days when shallow landslides were triggered in the study areas in December 2020, after implementing the modeled trends on a slope stability model, and by the correct choice of physically-based rainfall thresholds. These results confirm the potential application of the developed methodology to estimate hydrological scenarios that could be used for decision-making purposes

Improving spatial landslide prediction with 3d slope stability analysis and genetic algorithm optimization: Application to the oltrepò pavese

In this study, we compare infinite slope and the three-dimensional stability analysis performed by SCOOPS 3D (software to analyze three-dimensional slope stability throughout a digital landscape). SCOOPS 3D is a model proposed by the U. S. Geological Survey (USGS), the potentialities of which have still not been investigated sufficiently. The comparison between infinite slope and 3D slope stability analysis is carried out using the same hydrological analysis, which is performed with TRIGRS (transient rainfall infiltration and grid-based regional slope-stability model)—another model proposed by USGS. The SCOOPS 3D model requires definition of a series of numerical parameters that can have a significant impact on its own performance, for a given set of physical properties. In the study, we calibrate these numerical parameters through a multi-objective optimization based on genetic algorithms to maximize the model predictability performance in terms of statistics of the receiver operating characteristics (ROC) confusion matrix. This comparison is carried out through an application on a real case study, a catchment in the Oltrepò Pavese (Italy), in which the areas of triggered landslides were accurately monitored during an extreme rainfall on 27–28 April 2009. Results show that the SCOOPS 3D model performs better than the 1D infinite slope stability analysis, as the ROC True Skill Statistic increases from 0.09 to 0.37. In comparison to other studies, we find the 1D model performs worse, likely for the availability of less detailed geological data. On the other side, for the 3D model we find even better results than the two other studies present to date in the scientific literature. This is to be attributed to the optimization process we proposed, which allows to have a greater gain of performance passing from the 1D to the 3D simulation, in comparison to the above-mentioned studies, where no optimization has been applied. Thus, our study contributes to improving the performances of landslide models, which still remain subject to many uncertainty factors

Robust Statistical Processing of Long-Time Data Series to Estimate Soil Water Content

The research presented in this paper aims at providing a statistical model that is capable of estimating soil water content based on weather data. The model was tested using a long-time series of field experimental data from continuous monitoring at a test site in Oltrepò Pavese (northern Italy). An innovative statistical function was developed in order to predict the evolution of soil–water content from precipitation and air temperature. The data were analysed in a framework of robust statistics by using a combination of robust parametric and non-parametric models. Specifically, a statistical model, which includes the typical seasonal trend of field data, has been set up. The proposed model showed that relevant features present in the field of experimental data can be obtained and correctly described for predictive purposes

The survey and mapping of sand-boil landforms related to the Emilia 2012 earthquakes: preliminary results.

Sand boils, which are also known as sand blows or sand volcanoes, are among the most common superficial effects induced by high-magnitude earthquakes. These generally occur in or close to alluvial plains when a strong earthquake (M >5) strikes on a lens of saturated and unconsolidated sand deposits that are constrained between silt-clay layers, where the sediments are converted into a fluid suspension. The liquefaction phenomena requires the presence of saturated and uncompacted sand, and a groundwater table near the ground surface. This geological\u2013geomorphological setting is common and widespread for the Po Plain (Italy). The Po Plain (ca. 46,000 km2) represents 15% of the Italian territory. It hosts a population of about 20 million people (mean density of 450 people/km2) and many infrastructures. Thus, the Po Plain is an area of high vulnerability when considering the liquefaction potential in the case of a strong earthquake. Despite the potential, such phenomena are rarely observed in northern Italy, because strong earthquakes are not frequent in this region; e.g., historical data report soil liquefaction near Ferrara in 1570 (M 5.3) and in Argenta 1624 (M 5.5). In the Emilia quakes of May 20 and 29, 2012, the most widespread coseismic effects were soil liquefaction and ground cracks, which occurred over wide areas in the Provinces of Modena, Ferrara, Bologna, Reggio Emilia and Mantov

The survey and mapping of sand-boil landforms related to the Emilia 2012 earthquakes: preliminary results.

Sand boils, which are also known as sand blows or sand volcanoes, are among the most common superficial effects induced by high-magnitude earthquakes. These generally occur in or close to alluvial plains when a strong earthquake (M >5) strikes on a lens of saturated and unconsolidated sand deposits that are constrained between silt-clay layers, where the sediments are converted into a fluid suspension. The liquefaction phenomena requires the presence of saturated and uncompacted sand, and a groundwater table near the ground surface. This geological–geomorphological setting is common and widespread for the Po Plain (Italy). The Po Plain (ca. 46,000 km2) represents 15% of the Italian territory. It hosts a population of about 20 million people (mean density of 450 people/km2) and many infrastructures. Thus, the Po Plain is an area of high vulnerability when considering the liquefaction potential in the case of a strong earthquake. Despite the potential, such phenomena are rarely observed in northern Italy, because strong earthquakes are not frequent in this region; e.g., historical data report soil liquefaction near Ferrara in 1570 (M 5.3) and in Argenta 1624 (M 5.5). In the Emilia quakes of May 20 and 29, 2012, the most widespread coseismic effects were soil liquefaction and ground cracks, which occurred over wide areas in the Provinces of Modena, Ferrara, Bologna, Reggio Emilia and Mantov