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Al Neelian University (2020)

Soil Classification and Variability Analysis based GIS Technique for Engineering Geological Practice, Gedarif Area, Sudan

Abuelgasim Ali Gumaa Mukhtar

Titre : Soil Classification and Variability Analysis based GIS Technique for Engineering Geological Practice, Gedarif Area, Sudan

Auteur Abuelgasim Ali Gumaa Mukhtar

Université de soutenance : Al Neelian University

Grade : Master’s Degree in Engineering Geology. 2020

Résumé
This research was done to classify the soil and evaluate special variability of some properties using GIS technique. The Geostatistical tool, Kriging, was used to provide soil information for safe and cost-effective design of structures. The study focuses on utilizing the available spatial data such as Grain size analysis and Atterberg limits examine the soils characteristics and Geostatistical analysis. The soil classified using Unified Soil Classification System (USCS) and (AASHTO). special variability of some properties studied using descriptive statistics to test the normal distribution and find the statistical parameters of the data and suitability of the data to perform Geostatistics analysis. The possible spatial structure of the different soil properties identified by calculating the semi-variograms and the best model that describes these spatial structures was identified, the model with the best fit was applied to each soil properties. The activity of soil was determined using Skempton’s description of soil activity and the clay minerals in the soils identified using activity values. soil of the study area mostly contains montmorillonite & Illite. Grain size Analysis showed that, the area characterized by fine grained (cohesive) soils and the main problems in the area were the existence of expansive soil of high plasticity characteristics. result show that most soil sample classified as MH and CH types by (USCS) and fall under different groups by AASHTO and most samples classified as A-7-5. The samivarigram showed the zones of higher variability which indirectly helped in identification of soil sample locations precisely. Geostatistical interpolation identified strong spatial variability for some soil properties (25%>) and moderate spatial variability (25-75 %) for another property. Spatial distribution maps using ordinary Kriging interpolation were used to describe Concentration location of the soil properties in the study area. This study showed that the ordinary Kriging interpolation model is very effective land management approach as it provides reliable probability distributions of soil engineering geological properties. The framework developed can be extended to the analysis of different parameters in engineering geological and spatial variability models can be developed for different soil properties for performing prediction analysis

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Page publiée le 16 mai 2021