Site Investigation Program Research Articles

Advanced characterisation of groundwater contamination at a dumpsite: Methodology and assessment - Case study of a municipal solid waste dumpsite in India.

Groundwater (GW) contamination due to municipal solid waste (MSW) disposal in open dumpsites is a pressing global issue. Traditional GW assessment studies are limited to single-depth sampling from nearby wells/handpumps, providing limited insights into subsurface soil characteristics and are prone to cross-contamination. The present study introduces an innovative methodology integrating advanced techniques: Cone Penetration Testing (CPT), Hydraulic Profiling Tool (HPT), Continuous Soil Sampling, and Discrete GW Sampling. Conducted at an operational dumpsite in New Delhi, India, from January to February 2023, the site investigation program covered seven distinct locations to incorporate the entire dumpsite area. The investigation proceeded in stages, starting with subsurface soil characterisation using CPT and HPT, followed by extracting soil and GW samples using CPT and HPT data. Due to restrictions in the northeast direction, GW samples were directly extracted from borewells. The results revealed maximum and minimum concentrations of 171 items/l and 26 items/l of MPs, while ionic concentration reached 13,200ppm for Cl- and 4437ppm for SO4-2. A maximum of 0.721ppm, 0.663ppm and 0.948ppm concentration was observed for Ni, Cu and Mo in GW samples. Spearman correlation and principal component analysis underscore the influence of Ec, TDS, Na+1 and Cl-1 on GW quality. This integrated approach effectively identifies high-permeability layers, which are crucial for understanding contaminant dispersion, and ensures precise sampling at various depths with minimal cross-contamination. This research demonstrates the proposed methodology's effectiveness in providing more profound and precise insights into GW contamination dynamics and suggests its utility in forming the basis for more effective remediation and regulatory strategies.

A multiobjective optimization framework for site investigation program based on Bayesian approach and NSGA‐II

AbstractSite investigation provides essential geotechnical parameter information for analysis and design. However, three conflicting objectives, namely exploration effort, robustness and parameter uncertainty, pose a challenge to the development of an optimal site investigation program. In this study, a three objective optimization framework for the site investigation program is proposed based on the Bayesian approach and the non‐dominated sorting genetic algorithm (NSGA‐II). The only inputs required by the proposed framework are prior distribution of geotechnical parameters and error information. The prior distribution of geotechnical parameters is derived from integrating engineering experience and measurements from basic exploration boreholes. The error information is obtained based on literature and expert judgment related to the specific project. Firstly, a design pool of candidate investigation programs is generated using Bayesian approach to determine the locations and number of exploration boreholes. The NSGA‐II is then applied to identify the optimal program that balances lower cost, higher robustness, and lower uncertainty. The proposed multiobjective optimization framework is illustrated and validated through a real site investigation case in Chongqing, China, aimed at determining the ultimate bearing capacity of the rock foundation. The spatial correlation of parameters within the study area is also considered. The optimal program is represented by the location and number of exploration boreholes. By comparing measurements with predictions from different site investigation programs, the efficiency of the proposed multiobjective framework is demonstrated. Additionally, the influence of engineering experience and random field modeling on the investigation program is discussed.

Soil liquefaction sites following the February 6, 2023, Kahramanmaraş-Türkiye earthquake sequence

AbstractSeismically induced soil liquefaction was listed as one of the major causes of damage observed in the natural and built environment during the 2023 Türkiye-Kahramanmaraş earthquake sequence. Reconnaissance field investigations were performed to collect perishable data and document the extent of damage immediately after the events. The sites with surface manifestations of seismic soil liquefaction in the form of soil ejecta, excessive foundation and ground deformations were identified and documented. The deformations were mapped, and samples from ejecta were retrieved. The ejecta samples were predominantly classified as sands with varying degrees of fines. Laboratory test results performed on liquefied soil ejecta revealed that the fines-containing liquefied ejecta samples are mostly classified as low plasticity clays (CL). Most of CL soil type ejecta were retrieved from Gölbaşı–Adıyaman region. The liquid limits of these samples varied in between 32 and 38%, their plasticity index values were estimated in the range of 16–23%. Surprisingly, two ejecta samples with plasticity indices higher than 30% were retrieved from Hatay airport, one of which was classified as high plasticity clay (CH). The majority of the fine-grained ejecta samples fall either on “Zone B: Testing Recommended” region of the Seed et al. (Keynote presentation, 26th Annual ASCE Los Angeles Geotechnical Spring Seminar, Long Beach, CA, 2003) susceptibility chart. Moreover, 12 out of 74 samples fall outside the susceptible limits defined by Seed et. These preliminary results suggest that clayey soils can produce liquefied ejecta when subjected to cyclic loading. Detailed site investigation and laboratory testing programs are ongoing to further investigate this rather unexpected response. Until their findings become available, the liquefaction susceptibility of silty-clayey soils’ mixtures is recommended to be assessed conservatively with caution.

PERFORMANCE EVALUATION OF VERY LOW FREQUENCY (VLF) TECHNIQUES FOR AQUIFER CONTAMINATION ASSESSMENT

This study explores the efficacy of VLF techniques in mapping aquifer contamination. Conducted in Agbor, a city within Delta State, Nigeria, the study focuses on a contaminated aquifer of approximately 5 km² known for nitrate, petroleum hydrocarbon, and heavy metal contamination. The methodology involves VLF data collection using a Geonics EM-16 VLF receiver and transmitter, subsequent analysis using Geonics VLF2XYZ software, and comparison with traditional groundwater monitoring methods. The results indicated that VLF surveys effectively differentiate between contaminated and clean areas based on subsurface conductivity. The study demonstrates the cost-effectiveness and efficiency of VLF techniques compared to traditional methods, as VLF surveys cover larger areas in less time without drilling. Interpreting VLF resistivity maps reveals potential contamination areas, aiding in identifying contaminant sources and pathways. The validation framework assesses VLF techniques' accuracy, precision, sensitivity, and robustness, emphasizing the need for careful interpretation and validation with traditional methods. Implications for aquifer contamination assessment include mapping contamination extent, identifying new contamination areas, and monitoring remediation efforts. The study concludes that VLF techniques offer a promising and cost-effective method for aquifer contamination assessment. Recommendations include incorporating VLF techniques into site investigation programs, further research to optimize VLF technologies, site-specific investigations based on VLF survey results, and regular VLF surveys for ongoing monitoring and risk assessment. Overall, the findings contribute to alternative methods for aquifer contamination assessment, enhancing understanding and managing groundwater resources.

Fusion of sparse non-co-located measurements from multiple sources for geotechnical site investigation

A profile of geotechnical properties is often needed for geotechnical design and analysis. However, site-specific data might be characterized as MUSIC-X (i.e., Multivariate, Uncertain and Unique, Sparse, Incomplete, and potentially Corrupted with “X” denoting the spatial/temporal variability), posing a significant challenge in accurately interpreting geotechnical property profiles. Different sources, or types, of data are commonly available from a specific site investigation program, and they are usually cross-correlated, and thus can provide complementary information. This leads to an important question in geotechnical site investigation: how to integrate multiple sources of sparse data for enhancing the profiling of different geotechnical properties. To address this issue, this study proposes a novel method, called fusion Bayesian compressive sampling (Fusion-BCS), for integrating sparse and non-co-located geotechnical data. In the proposed method, the auto- and cross-correlation structures of different sources of data are exploited in a data-driven manner through a joint sparse representation. Then, profiles of different geotechnical properties are jointly reconstructed from all measurements under a framework of compressive sampling/sensing. The proposed method is illustrated using simulated and real geotechnical data. The results indicate that the accuracy of the interpreted geotechnical property profiles may be significantly improved by integrating multiple sources of site investigation data.

Meter-scale MICP improvement of medium graded very gravelly sands: Lab measurement, transport modelling, mechanical and microstructural analysis

Microbially induced carbonate precipitation (MICP) is a promising biogrouting method for ground improvement. Most studies to date have focused on MICP treatment of uniform clean sands, with few studies having been conducted at large-scale on well-graded soils more representative of in situ deposits. This study presents a laboratory meter-scale MICP test on medium-graded very gravelly sands. The MICP treatment was conducted in a radial flow cell (diameter: ∼1 m; thickness: ∼0.15 m) with an injection well located at the centre and a constant hydraulic head at the outer boundary to replicate field conditions. Aqueous chemistry of the effluent samples inside the flow cell was continuously monitored. Transport modelling and effluent sampling monitoring of the electrical conductivity and pH show that, in general, there was good delivery and reaction of the bacteria and chemicals in the radial flow cell, with some preferential flow paths being present. The MICP-treated soil was subjected to a series of hydraulic and mechanical tests and microstructural analysis. Interestingly, the biocemented medium-graded very gravelly sands had higher strengths (UCS values of 2.6–7.4 MPa) for a given calcite content (9.2–15.1%) than those in comparable studies where uniform soils have been treated. This can be attributed to the higher initial density of grain-to-grain contact points in the medium-graded soil, and a high grain angularity which resulted in particle interlocking and longer grain-to-grain contact surfaces, as can be seen from Scanning Electron Microscopy images. Consolidated-drained triaxial tests on two cores showed peak deviatoric strengths of 5.9 MPa and 3.7 MPa under an effective confining stress of 100 kPa, with the clear formation of shear bands during shearing, compared to a peak deviatoric strength of 0.5 MPa determined for the untreated soil. MICP treatment clearly enhanced the shear strength and stiffness of the material. The study shows that formation of preferential flow paths may be a challenge for producing uniform biocementation in field applications of MICP. We propose that successful MICP treatment in heterogeneous soils will require a well-designed and well-executed site investigation programme that can identify, a priori, the geometry of any significant high or low permeability features within the soil body to inform the final MICP treatment strategy.

Performance assessment of borehole arrangements for the design of rectangular shallow foundation systems

This study proposes a framework to evaluate the performance of borehole arrangements for the design of rectangular shallow foundation systems under spatially variable soil conditions. Performance measures are introduced to quantify, for a fixed foundation layout and given soil sounding locations, the variability level of the foundation system bearing capacities in terms of their mean values and standard deviations. To estimate these measures, the recently proposed random failure mechanism method (RFMM) has been adopted and extended to consider any arrangement of rectangular foundations and boreholes. Hence, three-dimensional bearing capacity estimation under spatially variable soil can be efficiently performed. Several numerical examples are presented to illustrate the applicability of the proposed framework, including diverse foundation arrangements and different soil correlation structures. Overall, the proposed framework represents a potentially useful tool to support the design of geotechnical site investigation programs, especially in situations where very limited prior knowledge about the soil properties is available.

Bayesian Framework for Assessing Effectiveness of Geotechnical Site Investigation Programs

Site investigation data can play an important role in not only site characterization but also the improvement of engineering design. It is tempting to predict the potential benefit of a site investigation before it is actually conducted. In this study, a Bayesian framework to assess the effectiveness of a site investigation program is proposed. The expected reduced variance (ERV) is employed to measure the uncertainty reduction owing to site investigation data. The uncertain outcomes of all possible site investigation data are considered through their probabilistic distributions. Then a framework to calculate the ERV is established. Monte Carlo simulation is adopted and the statistical uncertainty can be analyzed through the bootstrap method. Two examples of a shallow foundation on sand and an undrained slope are illustrated in this paper. Based on the examples studied, the optimal sampling layout is also discussed. The proposed method is promising to be applied in optimization of the sampling layout for various geotechnical practices.

Optimization of site investigation program for reliability assessment of undrained slope using Spearman rank correlation coefficient

Site investigation programs (e.g., boreholes) are crucial in characterizing soil properties and stratigraphic configurations. However, the traditional borehole patterns are generally of equally spaced distribution for the slope design, and the locations and total number of boreholes are considerably determined depending on engineers’ experience, which may lead to cost-inefficient geotechnical design, especially considering the soil spatial variability. To address this dilemma, this paper presents a Spearman rank correlation coefficient-based scheme to optimize site investigation in slope design, where both locations and total number of boreholes are optimized. Conditional random field simulations are performed to consider the effect of the borehole data on the estimation of the soil property distribution. The superiority of the proposed method to the traditional method is illustrated by a comparison study in an undrained slope example. In this example, the accuracy of the characteristics of the slope (i.e., the factor of safety, location of slip surface, and sliding volume), robustness of the estimated characteristics of the slope, and risk reduction are examined. The comparison results show the effectiveness of the proposed method in accurately estimating the characteristics of the slope without prior knowledge about the slip surface, since the slip surface is unknown for most practical cases prior to the site investigation. The most robust estimate results and risk reduction are obtained using the proposed method. This study can also provide useful references to build an adaptive unequally spaced borehole pattern in practice.

Stress-rate dependency of uniaxial compressive strength of hard rock with regard to test procedure standards

The uniaxial compressive strength test of hard rock is one of the most worldwide applied tests for characterization of hard rock in rock engineering and engineering geology. The uniaxial compressive strength as the results of this test is a basic parameter, used, for example, for the design of rock engineering structures. In the commonly applied standards, stress-controlled test procedures using constant stress rates are recommended by a wide range of stress rates varying between 2 and 60 MPa/min and/or a specific minimum test time. Though the effect of stress-rate dependency of hard rock is generally known, most investigation is focused on dynamic action behavior using high stress rates and/or fast actions. Strain-controlled test procedures are often used as well. For stress-controlled test procedures within the recommended range of stress-rates, the data base is rather poor, the effects to the results are reported by only very few researchers. The research described in this paper aims to close this gap and focuses on the stress-rate dependency of uniaxial compressive strength of hard rock. Seven different stress rates varying between 1 and 100 MPa/min on five different types of hard rock (quartzite, granodiorite, gabbro, sandstone, basalt) using five to fifteen single tests per stress rate have been executed. A significant increase of uniaxial compressive strength by increasing stress rates has been stated; the increase may not be ignored in assessing rock strength in rock engineering projects. The effect has to be considered especially when different parties are involved in the site investigation programs.

Assessing site investigation program for design of shield tunnels

In the design of shield tunnels, it is expected that a design can be more economical as more site investigation data are available. Nevertheless, the cost of site investigation will also increase as more site investigation data are required. It is thus important to assess the potential benefit of a site investigation program before it is conducted considering the uncertainty in the soil properties and the site investigation outcomes. In this paper, a probabilistic framework is suggested to assess the effectiveness of a site investigation program for the design of shield tunnels through the random field theory. An efficient method based on the generalized extreme value distribution is used to calculate the failure probability of the tunnel, through which the expected benefit from a site investigation program can be estimated conveniently. The result shows that a site investigation program is more valuable when a greater target design reliability index is needed. The expected benefit from a site investigation program increases as the borehole intensity increases, and it also increases as the scale of fluctuation of the soil properties increases. The method suggested in this paper provides a useful tool for planning borehole layout for the design of shield tunnels, which is promising for the optimization of site investigation.

Site Selection for a Deep Geological Repository in Switzerland: The Role of Performance Assessment Modeling

In the development of deep geological repositories (DGRs), performance assessment modeling is used to evaluate the integrity and performance of the engineered and geological barriers for thousands or millions of years of evolution of the disposal system. To evaluate the suitability of a site for a DGR, geoscientific data from dedicated site investigation programs are integrated into site-specific assessments. This paper presents the development and implementation of a modeling workflow aimed at comparing three potential siting areas for a DGR in Switzerland from the viewpoint of long-term safety and technical feasibility. The workflow follows the guidelines of the national regulator addressing safety relevant criteria such as the barrier efficiency of the host rock and its mechanical and chemical integrity in response to repository-induced influences and the long-term stability of the repository site over geological scales. In the regulatory requirements, the role of parametric, conceptual, and scenario uncertainty has been identified as an issue of special importance in the site selection process. The assessment approach comprises a portfolio of numerical models for the simulation of solute, gas and heat transport in the repository nearfield. The modeling was performed with deterministic as well as probabilistic variants integrated in an indicator-based approach that allows the consistent comparison of the candidate sites using quantitative dimensionless performance indices. The model-based assessment of the sites allows a traceable, transparent, and verifiable implementation of the site selection process.

Assessing expected benefit of site investigation program for reliability-based design of slope

The site investigation (SI) is important to reduce the uncertainty of the slope soil properties. Its effectiveness is highly related to the planning of an SI program such as borehole layout. It is thus tempting to assess the potential uncertainty reduction of an SI program. This paper presents a method to assess the expected benefit (EB) of an SI program for slope. The cost saving of reliability-based design under unknown observations is considered. Compared with the previous methods, this method can take into consideration the uncertainty of the scale of fluctuation (SOF) of the soil, and the knowledge about the consequence of slope failure is not required. A subset logistic regression method is suggested to approximate the probability of slope failure. The SI program can be optimized by selecting the borehole layout with the maximal EB. For the example in this paper, it is found that the EB of an SI program depends on the SOF of the soil. If the uncertainty in the SOF is not considered, the EB may be underestimated or overestimated. The proposed method provides a practical and efficient way to assess the effectiveness of SI program for design of slopes.

Development of two-dimensional ground models by combining geotechnical and geophysical data

Geotechnical and geophysical testing data are conventionally considered as separated information or combined based on deterministic methods in site investigation programs, which causes loss of information and introduces additional uncertainties. This study aims to reduce the uncertainties and costs in inhomogeneous soil profile characterization and geotechnical analysis by quantitatively integrating these data. The intrinsic collocated co-kriging method (ICCK) is utilized to integrate Multi-channel analysis surface wave (MASW) and CPT data. This research shows the potential of using the MASW data to explore the horizontal scale of fluctuation (SOF) of the cone tip resistance (qc) field which is very difficult to get using the conventional methods due to the limited CPTs. The Markov model is used to avoid the tedious modeling of the cross-covariance relationship in the ICCK method. A series of synthetic case studies show that the combined soil profile is in good agreement with the “true” qc field with significantly reduced uncertainties. Based on estimating the uncertainties, the optimal distance between CPTs is suggested to be 1–2 horizontal SOF. This framework is also applied to a real case in the Christchurch area, which involves integration of CPTs and MASW tests. Cross validation and edge detection methods are used to quantitatively compare the integration results, confirming that the proposed framework is fully applicable to field data and can provide realistic and reliable estimations of qc field.

A systematic approach for surface exploration of sites – analysis of international exploration programs

Abstract. The site selection procedure for a high-level radioactive waste repository in Germany is based on the Repository Site Selection Act (StandAG, 2017), which comprises three phases. In phase 2 the Federal Company for Radioactive Waste Disposal (BGE) will conduct surface exploration. Based on the exploratory findings, the further developed preliminary safety analyses, the common requirements and criteria, and potential socioeconomic analyses will be applied feeding into proposed sites for underground exploration. Commissioned by the BGE, the Federal Institute for Geosciences and Natural Resources (BGR) contributes to this procedure with the projects GeoMePS and ZuBeMErk, which collate and assess geoscientific and geophysical methods and programs for surface exploration. Their common goal is to develop recommendations for surface exploration of siting regions. For this purpose, the BGR has developed a systematic approach that includes (1) deducing exploration targets, (2) compilation of geoscientific and geophysical exploration methods in a database structure, and (3) analysis of case studies of national and international exploration programs for high-level radioactive waste disposal. Exploration targets are based on the common criteria and requirements as defined by the StandAG. The identified exploration targets (Kneuker et al., 2020) together with a large number of geoscientific and geophysical exploration methods were integrated and linked within the BGR database “GeM-DB”. All methods were evaluated according to their suitability and applicability for (a) the three defined host rocks (crystalline rock, claystone, rock salt) and (b) the previously defined exploration targets. In step (3) the BGR reviews national and international waste disposal programs exploring for crystalline rock, claystone, and rock salt. Here, the focus is on nondestructive and minimally invasive surface exploration techniques, such as geophysical airborne and ground-based methods or investigations in drill holes and on drill cores. The aims are to identify gaps in the method catalogue of the GeM-DB and to infer exploration directives for surface exploration during phase 2. An example is the analysis of the Swedish site selection process, especially the site investigation program. There, the site investigations are, e.g. the basis for the discipline-specific site descriptive models, which were applied for design and safety assessments (SKB, 2001). The Swedish site investigation program along with programs of other countries considering crystalline host rocks, such as Finland and Canada, show a common ground, which could be adapted for surface exploration of crystalline host rock regions in Germany. The assessment and evaluation of selected programs exploring for rock salt and claystone is currently in progress. The entire systematic approach of the projects GeoMePS and ZuBeMErk aims to develop recommendations for a nondestructive and minimally invasive surface exploration program of siting regions in Germany, regarding the lithological, structural, mechanical, and hydrogeological characterization of the different host rock formations.

Investigations and stability analysis of San Marcellino cavities in the historical centre of Naples

The historical centre of the city of Naples is characterised by a network of underground anthropogenic cavities. Most of these cavities are stable and safe but sometimes for several reasons they are at least partially responsible of the occurrence of instability phenomena such as sinkholes and collapses. The opening of a sinkhole in the cloister of the Ancient Royal Boarding School (known as Educandato Reale of San Marcellino) led to fears of instability in the known underlying cavities. Therefore, a site investigation program was carried out to ascertain the causes of the event. The investigation concluded that the sinkhole was not related to the underneath cavities, located in tuff between 12 and 20 m beneath the main building. Nevertheless, due to the interest raised by the preliminary safety assessment, such a cavity system was selected within the MOSCAS project for further studies. The results of the site investigations and the stability of the cavities determined via FEM code Plaxis 2D are presented and discussed in this paper.

CPT Data Interpretation Employing Different Machine Learning Techniques

The classification of soils into categories with a similar range of properties is a fundamental geotechnical engineering procedure. At present, this classification is based on various types of cost- and time-intensive laboratory and/or in situ tests. These soil investigations are essential for each individual construction site and have to be performed prior to the design of a project. Since Machine Learning could play a key role in reducing the costs and time needed for a suitable site investigation program, the basic ability of Machine Learning models to classify soils from Cone Penetration Tests (CPT) is evaluated. To find an appropriate classification model, 24 different Machine Learning models, based on three different algorithms, are built and trained on a dataset consisting of 1339 CPT. The applied algorithms are a Support Vector Machine, an Artificial Neural Network and a Random Forest. As input features, different combinations of direct cone penetration test data (tip resistance qc, sleeve friction fs, friction ratio Rf, depth d), combined with “defined”, thus, not directly measured data (total vertical stresses σv, effective vertical stresses σ’v and hydrostatic pore pressure u0), are used. Standard soil classes based on grain size distributions and soil classes based on soil behavior types according to Robertson are applied as targets. The different models are compared with respect to their prediction performance and the required learning time. The best results for all targets were obtained with models using a Random Forest classifier. For the soil classes based on grain size distribution, an accuracy of about 75%, and for soil classes according to Robertson, an accuracy of about 97–99%, was reached.

Value of information analysis of site investigation program for slope design

Site investigation is widely used for uncertainty reduction and design improvement in slope engineering. Before the site investigation is implemented, it is important to assess and compare the effectiveness of different site investigation programs. In this paper, an efficient method for analyzing the effectiveness of a site investigation program for slope stability assessment through value of information analysis is proposed. In this method, a logistic regression model is developed to approximate the relationship between failure probability of the slope and the site investigation data, through which the evaluation of posterior distribution and slope reliability analyses are both avoided. The suggested method is illustrated and verified with an example. For the example studied in this paper, the number of slope stability analyses required is only 1% of that reported in the literature. The suggested method can be used to study the effects of locations of the boreholes, the number of boreholes, and the depth of boreholes on the effectiveness of a site investigation program.

Probabilistic 3D modelling of shallow soil spatial variability using dynamic cone penetrometer results and a geostatistical method

ABSTRACT Since soils are natural and non-homogeneous materials, spatial variability of their properties has been recognised as one of the main sources of uncertainties affecting geotechnical analyses. However, soil testing is limited and the description and quantification of the resulting soil variability still remain largely subjective in practice. In this paper, anapproach is proposed to rationally evaluate the soil spatial variability using field data provided by a site investigation programme based on a lightweight dynamic cone penetrometer test. The first part deals with the boundary identification of statistically mechanical homogeneous soil units. The second part focuses on modelling spatial variability through 3D conditional random fields in the homogeneous soil units previously identified. This approach has been applied to and studied in a real site investigation carried out in an alluvial Mediterranean deltaic environment.

On the optimization of site investigation programs using centroidal Voronoi tessellation and random field theory

This work proposes a centroidal Voronoi tessellation (CVT)-based site investigation scheme, which is applicable to arbitrary site geometries and arbitrary numbers of investigation locations. A modified Lloyd algorithm is developed to generate CVT-based site investigation programs. With the data from prior site investigations, the random field statistics of a site property are estimated using a Markov chain Monte Carlo simulation-based Bayesian inference approach, and the site property at each location is estimated using Kriging interpolation. The performance of the CVT-based site investigation programs and optimization are demonstrated using two illustrative examples, namely, a square site and an irregular site.