Modeling of soil parameters spatial uncertainty by geostatistics

Davidović, Nebojša; Prolović, Verka; Stojic, Dragoslav

doi:10.2298/fuace1001111d

Cited by 12 publications

(4 citation statements)

References 4 publications

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“…For these reasons, many authors have adopted geostatistical methods to predict the spatial distributions of soil properties; however, this requires extensive field observation (e.g. Aşkın et al ; Davidovic et al ; Griffiths et al ; Kerry and Oliver ; Raspa et al ). Under the probabilistic approach, the probability distributions of geotechnical parameters are generally considered normal (e.g.…”

Section: Methodsmentioning

confidence: 99%

Including root reinforcement variability in a probabilistic 3D stability model

Cislaghi

Chiaradia

Bischetti

2017

Earth Surf Processes Landf

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Forests play a significant role in protecting people, settlements in mountainous terrains from hydrogeomorphic hazards, including shallow landslides. Although several studies have investigated the interactions between forests and slope instabilities, a full understanding of them has not yet been obtained. Additionally, models that incorporate forest stand properties into slope failure probability analyses have not been developed. In principle, physical-based models, which are powerful tools for landslide hazard analyses, represent an appropriate approach to linking stand properties and slope stability. However, the reliability of these models depends on numerous parameters that describe highly complex geotechnical and hydrological processes (e.g. potential failure depth, saturation ratio, root reinforcement, etc.) that are difficult to measure and model. In particular, the spatial heterogeneity of root reinforcement remains a problem, and the use of physically based models from a forest management perspective has been limited.This paper presents a procedure for assessing slope stability in terms of the Factor of Safety that accounts for forest stand characteristics such as tree density, average diameter at breast height and minimum distance between trees. The procedure combines a three-dimensional (3D) slope stability model with an evaluation of the variability of root reinforcement in terms of a probability distribution, according to forest characteristics. Monte Carlo simulation is used to account for the residual uncertainties in both stand characteristics and 3D stability model parameters.The proposed method was applied in a subalpine catchment in the Italian Alps, mainly covered by coniferous forest and characterized by steep slopes and high landslide risk. The results suggest that the procedure is highly reliable, according to landslide inventory maps [area under the ROC curve (AUC) is 0.82 and modified success rate (MSR) is 0.70]. Thus, it represents a promising tool for studying the role of root reinforcement in landslide hazard mapping and guiding forest management from a slope stability perspective.A 3D approach to hillslope stability modelling was selected to overcome the limitations of infinite slope analysis and to 1790 A. CISLAGHI ET AL.

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Section: Methodsmentioning

confidence: 99%

Including root reinforcement variability in a probabilistic 3D stability model

Cislaghi

Chiaradia

Bischetti

2017

Earth Surf Processes Landf

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“…The system is subjected to a small force which does not induce slip. Thus, for the tangential component, rough interaction is assumed as there is no slip between the surfaces [6]. Thus, for the normal behavior and the tangential behavior hard and rough contacts were used in all interactions.…”

Section: S Dzmentioning

confidence: 99%

“…This base worksheet was copied three more times, each representing a varying parameter [6]. Each of the varied parameters were randomized down the column using the "ran between" function, with the other parameters being held constant at their average (Young's Modulus had its range divided into three, one for each layer, so it was average of the layer's range).…”

Section: Parameter Distributionmentioning

confidence: 99%

Numerical simulation for soil-superstructure interactive system

Hussaini¹,

Vogelsang²

2017

J Civil Environ Eng

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Geotechnical performances of soil superstructure systems are strongly dependent on the properties of the soil, and prediction of the performance of these systems in real conditions requires accurate modelling of soil parameter. It is vital to determine the risk of damage to structures, due to soil displacement by differing some of the soil parameters. The core objective of this project is to study the response of a soil-structure subjected to uniform loading. From this, the soil-structure stiffness can be easily obtained. For the basis of the analysis, the soil has been assumed first elastic with individual random variables such as Young's modulus and Poisson's ratio simultaneously. After the elastic displacement, known the plastic analysis conducted. For the analysis of this project, finite element models are developed in ABAQUS to simulate vertical uniform load of 3 kilo-Pascal (kPa) for elastic and 100 kPa for plastic deformation. Results from the analysis discussed and comparison between the experimental values and theoretical values examined. The difference between elastic and plastic analysis checked against the displacement. The parametric study has indicated that the E-modulus of the soil and structure load have larger impact on the soil-structure response. Due to various variables of certain soil parameters, the selection of specific soil with few important variables were the centre of this study, to achieve more realistic results.©

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“…Geostatistics is a branch of practical statistics science that is able to provide a wide range of statistical estimators to for the desired property at areas without sampling data, using information from the areas with sampling information (Bahri & Khosravi, 2017;Davidovic et al, 2010;Hengl, 2007). Due to geological conditions, data are not independent in geostatistics and have correlation to a certain distance.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneity Evaluation of Soil Engineering Properties Based on Kriging Interpolation Method. Case Study: North East of Iran, West of Mashhad

Etemadifar¹,

Vaziri²,

Aghamolaie³

et al. 2018

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Many sciences are confronted with uncertainty in their application field. Therefore, the use of statistics plays an important role for creating a partial model of the whole in most practical cases. Preparing a dispersion map, merging spatial statistics and geographic information systems (GIS), is very useful in geotechnical engineering. Interpolation is one of the usual methods to prepare these maps that has many different types. The ordinary kriging which is used in this paper is one of the most popular interpolation methods. This method is usually used to predict possible changes of an unknown variable using known parameters. In general, geostatistical estimation is a process by which one can obtain the value of a quantity in points with unknown coordinates using the same quantity in other points with definite coordinates. In this paper with information about the boreholes drilled in West Mashhad (North East of Iran), the specification of areas without borehole log is determined using interpolation method, drawing of kriging maps including soil texture, percentage of passing No. 200 sieve, standard penetration numbers, dry density, effective SPT area and the use of geostatistical techniques.

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Modeling of soil parameters spatial uncertainty by geostatistics

Cited by 12 publications

References 4 publications

Including root reinforcement variability in a probabilistic 3D stability model

Including root reinforcement variability in a probabilistic 3D stability model

Numerical simulation for soil-superstructure interactive system

Heterogeneity Evaluation of Soil Engineering Properties Based on Kriging Interpolation Method. Case Study: North East of Iran, West of Mashhad

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