Soil Variability Research Articles

Design of poured earth construction materials from the elementary characteristics of tropical soils

Sustainable construction materials and local solutions are crucial for meeting urbanisation demands in tropical regions like French Guiana. Poured earthen construction, primarily composed of local soil, offers a cost-effective and environmentally friendly alternative. To ensure good consistency for pouring, the use of dispersants to deflocculate clay particles is an effective strategy that reduces water demand while enhancing the material's physical and mechanical properties. However, the variability of soil impacts the effectiveness of dispersants and the earth's material properties. It is currently unknown how the specific properties of tropical soils can influence the mix design of poured earth and how it impacts their resulting physical and mechanical characteristics. This work examines the soil properties that could help select suitable soil for poured earth construction. Four tropical soils of French Guiana were characterised in detail and used to prepare mortars with varying amounts of water and dispersant (sodium hexametaphosphate). The consistency and compressive strength of the mortars correlated with the mineralogical and geotechnical characteristics of the soils. In particular, soils with high levels of metal oxides produced mortars with the highest compressive strength. Using a dispersant consistently increased the compressive strength and dry density of the mortars and enabled a reduction in water content. Importantly, the analysis revealed that two easily measurable soil properties, the passing at 63 µm and the pH measured in potassium chloride (pH KCl), could predict the mechanical properties of the mortars and the amount of dispersant needed. Specifically, the pH KCl correlated with the proportion of iron and aluminium oxide and showed a positive linear correlation with the compressive strength. Overall, this study identifies easily measurable soil properties, in particular the pH KCl, for selecting and designing high-performance earth materials with tropical soils. It offers promising prospects for industrialising poured earth construction.

Digital soil characteristics mapping for aiding site-specific management practices in the West Nile Delta, Egypt

Soil survey system is the key word for sustainable soil use and management. This study aimed to generate a digital soil mapping (DSM) using various spatial resolutions of freely available digital elevation models (DEMs) i.e., (30 m ALOS “Advanced Land Observing Satellite”, 12.5 m ALOS, 30 m SRTM “Shuttle Radar Topography Mission”, and 90 m SRTM) to assess the spatial variability of soil physio-chemical characteristics in El-Beheira Province, Western Nile Delta. A total of 196 geo-referenced soil profiles were collected from agricultural fields, and the soil's contents of total nitrogen (TN), potassium (K), available phosphorous (P), calcium (Ca), sulfur (S), magnesium (Mg), zinc (Zn), copper (Cu), manganese (Mn), and boron (B) were analyzed. The study revealed that the soil's contents of TN, P, S, B, and Cu were low, and Mg was suspected to be higher than K, leading to an Mg-induced K shortage. The study also found wide-ranging spatial variability structures of inverse distance weight (IDW) interpolated maps for several soil physio-chemical characteristics. The DSM further revealed that poor status was present in 85.4% of TN, 91.7% of P, 76.9% of S, and 87% of both B and Cu. The conclusion is that soil variability, as demonstrated in DSM, outweighs uniform treatment, and this discovery will assist extension workers, scientists, and decision-makers in implementing site-specific nutrient management strategies. Validation of the DSM is recommended for crop and variety-specific nutrient treatment rates. Understanding the geographical variance in the soil is critical for long-term nutrient management and higher output.

Stochastic numerical analyses to investigate the effects of the spatial nonuniformity of offshore ground on the serviceability of monopile foundations

ABSTRACT The evidence of soil nonuniformity has been reported in several site investigation reports and is well-confirmed for any soil in general. However, studies related to the spatial soil variability of offshore ground are somewhat limited, and current design practices for monopile foundations also overlook the uncertainty of the offshore ground. This paper presents the probabilistic evaluation of the serviceability limit state of monopile foundations considering the spatial variability of offshore ground. The nonuniformity of the ground is modeled utilizing the site-specific undrained shear strength (su) as a stochastic variable, using a spatially correlated Gaussian random field. A hardening soil constitutive model is utilized in 3D finite element analysis of offshore ground, with a focus on parameter calibration. The reliability of the serviceability limit state is assessed based on the allowable load on the pile head. The stochastic behavior of the maximum bending moment and maximum shear force along the depth of the monopile is also investigated. Besides, the paper also highlights the importance of incorporating ground nonuniformity during the design process of a monopile foundation.

Damage mechanism and failure risk analysis of offshore pipelines subjected to impact loads from falling object, considering the soil variability

Trench and burial, as a primary and effective protection measurement for offshore pipelines from impact loads, has received much research attention recently. Previous studies were usually performed based on the assumption that the soil material was homogeneous with deterministic mechanical properties. The soil spatial variability, which is demonstrated to have significant influences on the soil capacity in marine geotechnical analysis, has not been included. This study was motivated to investigate the response of the buried pipelines subjected to the impact loads, with special address on the soil variability. Firstly, a three-dimensional random large deformation finite element analysis model was developed, which was implemented by the field variable (FV) technique to map the non-stationary random field (NSRF) into the verified Coupled Eulerian-Lagrangian (CEL) model (Hereafter referred to as FVRCEL). Then the FVRCEL model was integrated with the Monte-Carlo simulation (MCS) to obtain the statistical characteristics of the pipeline structural response. The failure mechanisms of the pipeline in the random soil with different fluctuation scales were investigated, and a parametric study was performed to identify the influential factors. Finally, the failure probability curves and surfaces were presented, providing clues for the pipeline safety design. The results revealed that in general, more than 50 % of the realized NSRF scenarios in the random analysis yielded more severe dent damage than the deterministic result, indicating that the latter would underestimate the damage degree, which was more pronounced when the increasing gradient of soil strength was high. The horizontal fluctuation scale had a remarkable influence on the pipeline damage behaviours and the corresponding statistical characteristics, of which the inner mechanisms were discussed. From the probabilistic perspective, at most an extra failure probability of 75 % would be suffered if the soil variability was ignored.

Optimizing Pre-emergence Herbicide Oxyfluorfen Dose based on Its Sorption and Desorption for Effective Weed Management under Different Soil Types

Background: Adsorption and subsequent release of pre-emergence herbicide into the soil solution decides the herbicide availability to kill the weeds. Herbicides applied on clay or organic rich soil type, absorb more results in lowering its availability in soil solution become sub lethal to kill the weeds, whereas sandy soil adsorb less and desorb more, sometime it increases the herbicide concentration to toxic level to crop. Effective weed control could be achieved by studying the variability of soil and deciding the dose based on the sorption and desorption properties of the soil. Methods: With this information on the background a laboratory experiment was conducted at the Department of Agronomy, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai, India during 2021 to study the optimum level of oxyflourfen concentration in soil solution required to kill the weeds effectively. The study on sorption and desorption was carried out with pre-emergence herbicide oxyflourfen with five different concentrations in five different soil types. Result: The highest sorption of 98.53 per cent was observed with clayey soils followed by sandy clay loam soils with high organic matter content (96.97 per cent). The lowest sorption (77.96 per cent) was recorded with sandy loam soils. The highest desorption of 57.44 per cent was recorded with sandy loam soil and the lowest desorption percentage (13.18 per cent) was obtained with sandy clay loam soil with higher organic matter. Based on the analytical results of sorption and desorption, oxyflourfen dose was optimized as 0.53 kg ha-1 for sandy clay loam soils with high organic matter, 0.34 kg ha-1 for clay soil, 0.29 kg ha-1 for sandy clay, 0.21 kg ha-1 for sandy clay loam soil and 0.12 kg ha-1 for sandy loam soils. In conclusion, the clay soil required more quantity of oxyflourfen compared to other types of soil for effective management of weeds under irrigated condition.

A simple approach to probabilistic CPTu-based geotechnical stratigraphic profiling

Geotechnical profile delineation is an important aspect of the geotechnical engineering design process. The Cone Penetration Test (CPTu) is widely used for this purpose, as it is simple to classify soils based on their different responses to the cone. However, CPTu-based delineations typically involve engineering interpretation, as they are affected by the classification scheme applied, by inherent soil variability and by measurements error. A semi-automated CPTu data treatment tool is here presented aiming to simplify the soil delineation task, adding consistency and transparency to the involved engineering interpretation process and facilitating the transference of information between the different parties involved in design. The tool fits bivariate normal distributions to interpreted CPTu data according to some user specified criteria that quantify estimated classification and measurement uncertainties. Classification makes use of conventional class boundaries –here taken from Robertson, 1990 chart-, which are applied with user-specified refinement. Thin layers are consolidated into adjacent ones to further simplify the resulting profile. The operation of the proposed algorithm is illustrated by interpreting CPTu records from a deltaic sedimentary environment. The outputs of this simple method may be used as input for more advanced probabilistic methodologies, helping thus to bridge the gap between qualitative practice and quantitative research methods.

Spatial Variability in Soil Micronutrients and Soil Separates of Ujjain Tehsil of Ujjain District of Madhya Pradesh, India

Mapping of soil properties is an important operation as it plays an important role in the knowledge about soil properties and how it can be used sustainably. Knowledge of soil variability of any region is crucial for development of site-specific management practices for that region as this will enhance the crop productivity and maintain the good soil health. With this background, present study was conducted to quantify the spatial variability of different soil physical properties and soil available micronutrients in Ujjain tehsil (Ujjain) district of Madhya Pradesh state, India. A total one hundred fifty geo-coded surface (0-15 cm depth) soil samples, were collected across the study area. These samples were analyzed using standard method for different some soil properties viz: soil texture (sand, silt and clay) and soil available micronutrients, viz. extractable zinc (Zn), copper (Cu), manganese (Mn) and iron (Fe) in laboratory. The range of sand, silt, clay, Zn, Cu, Fe and Mn in the study region were varied from 9.15 to 24.06 %, 24.00 to 41.55 %, 40.20 to 58.60 %, 0.12 to 1.66 mg kg-1, 2.06 to 6.22 mg kg-1, 3.70 to 10.40 mg kg-1, and 2.41 to 14.64 mg kg-1, respectively. The data were analyzed using standard statistical methods and geostatistics, which included creating semi-variograms and mapping by standard kriging procedures. Semi-variograms were produced for soil properties and their regional distributions were plotted. The observed soil parameters were best represented by four models: Exponential, Circular, Gaussian, and Hole effect. The modelled variables showed strong and moderate spatial dependencies, as demonstrated by the Nugget/Sill (Co/Co+C) ratio. The distribution maps of soil features may serve as a reference for implementing site-specific crop management in soils with comparable characteristics. Further, this research indicates the relevance of GIS- application in soil variability investigations.

Evaluating Spatial Soil Parameters of an Apple Orchard in ‘R’ Software: A Study from Kashmir Valley

Maintaining the ecological balance of the physical and biological environment depends greatly on the spatial variation of soil parameters across a given region and its elucidation using remote sensing and GIS applications. R software was used to apply the geostatistical methods of Ordinary Kriging and Inverse Distance Weightage to the study of the spatial distribution and variability of the soil parameters of an apple orchard in the Valley of Kashmir. Average values for available phosphorus (P), potassium (K), calcium (Ca), available nitrogen (N), and soil organic carbon (OC) were 1.15 percent, 315 percent, 22.5 kg, 221.4 kg, and 250 mg, respectively. Ordinary kriging (OK) and IDW were used to plot the spatial distribution of soil parameters using spherical (pH, OC, and Ca), steradian (EC, N, P, and K), and mean square error (MSE) values. According to the semi-variogram analysis, there was a strong to moderate spatial dependence. The interpolated maps showed various soil distribution patterns for pH (5.4-5.7), EC (0.46-0.56 DSM-1), OC (0.9-1.4 percent), N (296-335) kg ha-1, P (20-25 kg ha-1), K (221-221.8 kg ha-1), and Ca (100-400 mg kg-1) at the regional scale. This study represented a wide range of spatial soil variability. The estimation of MSE for Ordinary Kriging and IDW was used to predict the best model after performing a validation accuracy assessment. The best fit model for interpolation was the standard kriging model with low MSE. The maps of soil spatial distribution created to serve as an effective tool for policymakers and those planning farms.

Modelling and prediction of major soil chemical properties with Random Forest: Machine learning as tool to understand soil-environment relationships in Antarctica

Digital Soil Mapping includes quantitative estimations of soil attributes in areas with little or no soil information, being important in remote landscapes such as the Antarctic ice-free areas. Our objective was to predict the spatial distribution of major soil chemical attributes in two important Antarctic Peninsula regions; as well as to identify the main environmental drivers of these attributes. For this, we compiled one of the largest soil databases of Antarctica and applied the machine learning algorithm Random Forest to predict seven soil chemical attributes. We also used covariates selection and partial dependence analysis to better understand the relationships of the attributes with the environmental covariates. Bases sum was the attribute which presented the highest prediction performance, whereas Na and P predictions presented the lowest. Both accuracy and uncertainty indicators showed the difficulties of Random Forest in handling natural outliers. The soil attributes distribution was related to the mean annual temperature and annual precipitation, multispectral bands and indexes related to the vegetation response, rookeries distance expressing the birds’ activity, and topographic attributes. The attributes showed a climatic gradient, with higher values of bases sum, pH, and Na in Northern Antarctic Peninsula, and higher total organic carbon, H + Al and P in Maritime Antarctic. This shows the climate covariates influence the soil variability in a macroscale, whereas terrain predictors control the soil at local scales. This study showed the Digital Soil Mapping potential to surpass the limitations of conventional mapping and indicated the feasibility in obtaining interpretable predictions which can be directly associated with the soil forming factors. Finally, the data generated can be used as reference to monitor the impacts of the climate changes on the soils of Antarctica.

Laterally loaded pile response in spatially variable soil

The spatial variability of soil has long been recognised, yet there is a dearth of research on the response of piles under lateral loading that considers this variability, especially for the lateral load transfer (P-y) curve in spatially variable clay. To address this gap, the study presents a three-dimensional random finite element analysis utilising a non-stationary random field to model soil variability with a linearly increasing trend. The results reveal that the spatial variability significantly affects the lateral capacity of the pile, emphasising the importance of accounting for this variability in pile design. Additionally, the study finds that while the spatial variability affects the failure mechanism, the mechanism remains comparable to that observed in deterministic analyses. The spatial variability has a substantial effect on ultimate soil resistance pressure, which can be fitted using a normal probability distribution function. An adjust factor is suggested to calculate the characteristic value, and from this characteristic value, the fractiles of ultimate soil resistance pressure can be calculated. This study provides an evaluation method for the spatial variability effect of soil, facilitating a cost-effective design of pile foundation.

Transport of bisphenol A, bisphenol S, and three bisphenol F isomers in saturated soils.

With the limitation of the use of bisphenol A (BPA), the production of its substitutes, bisphenol S (BPS), and bisphenol F (4,4'-BPF) is increasing. Understanding the fate and transport of BPA and its substitutes in porous media can help reduce their risk of contaminating soil and groundwater systems. In this study, column and batch adsorption experiments were performed with 14C-labeled bisphenol analogs and combined with mathematical models to investigate the interaction of BPA, BPS, 4,4'-BPF, 2,2'-BPF, and 2,4'-BPF with four standard soils with different soil organic matter (SOM) contents. The results show that the transport capacity of BPS and 4,4'-BPF in the saturated soils is significantly stronger than that of BPA. Meanwhile, the mobility of the three isomers of bisphenol F exhibits variability in saturated soils with high SOM content. The two-site nonequilibrium sorption model was applied to simulate and interpret column experimental data, and model simulations described the interactions between the bisphenol analogs and soil very well. The fitting results underscore SOM's role in providing dynamic adsorption sites for bisphenol analogs. Hydrophobicity primarily accounts for the disparity in adsorption affinity between BPA, BPS, 4,4'-BPF, and soil, whereas hydrogen bonding forces may predominantly influence the differential adsorption affinity between 4,4'-BPF and its isomers and soil. The results of this study indicate that BPS and three isomers of BPF, as alternatives to BPA, have higher mobility in saturated soils and may pose a substantial risk to groundwater quality. This study enhances our understanding of bisphenol analogs' behavior in natural soils, facilitating an assessment of their environmental implications, particularly regarding groundwater contamination.

Managing geotechnical uncertainty and risk in mining

The science of soil mechanics is 100 years old, and rock mechanics is about 80 years old. While methods of analysis and design have been developed and have evolved over time, these are relatively young sciences. The rapid increases in computing power and new technologies have enabled more sophisticated modelling and monitoring. However, there are still many aspects of soil and rock mechanics that are not well understood. Geotechnical failures, which have major consequences, still occur. These consequences may include environmental damage, major production holdups and associated loss of revenue, damage to infrastructure, and loss of life. High-consequence events, which are rare, are more difficult to anticipate and to design for, because by their nature they involve extraordinary circumstances or conditions, often geological in nature. The risks are usually mitigated by conservative designs and monitoring. Detailed geotechnical investigations help us to understand the natural variability of soil and rock masses and identify unusual or unexpected conditions. Investigating and researching major geotechnical failures is essential to enable these unusual circumstances to be anticipated. In the past, severe unanticipated events may have been treated as natural events or 'acts of God'. However, society now has much greater expectations and it is essential to have policies and procedures in place that enable appropriate management of these rare, high-consequence risks. A good example is the Global Industry Standard on Tailings Management (GISTM), which was introduced after the catastrophic dam collapse at Vale's Corrego de Feijao mine in Brumadinho, Brazil. The address will explain the concepts of uncertainty and variability, and how they should be taken into account in geotechnical design. The challenges facing geotechnical engineers, mine owners, and managers will be discussed. referencing a number of real case studies.

Climate and soil-based constraints to rainfed cotton yield in the Northern Territory, Australia – A modelling approach using APSIM-OZCOT

Cotton production in Australia is expanding to the northern semi-arid tropical regions as a means to droughtproof the industry. The majority of expansion is expected to come from rainfed farming systems. However, little is known on tropical rainfed cotton, particularly on climate and soil-based constraints that determine cotton production. Using the Northern Territory (NT) as case study, we investigated the effects of between and intra seasonal rainfall variability and key soil types on soil moisture dynamics,timely operations, lint yield, and industry viability. We examined several regions with greatest potential for rainfed agriculture in the NT, including sites in the Daly Basin, Mataranka and Larrimah. To this purpose we applied a locally calibrated and validated cotton growth model (APSIM-OZCOT) using weather files sourced from the SILO database of Australian climate data, and soil profile parameters for three red Kandosols: Blain, Oolloo and Tippera. Our study shows that simulated median lint yields ranged from 570 to 996 kg ha−1, with larger yields achieved on soils that hold more moisture (Blain > Oolloo > Tippera), and at locations that received greater amounts of seasonal rainfall. Planting window largely governed soil-moisture availability and thus sowing opportunities. An early planting (1–15 December) increased yields (greater available soil-moisture) but reduced planting opportunities due to insufficient mulch cover at planting. A late planting (15 Jan to 1 Feb) reduced cotton yields due to less seasonal rainfall, but increased the number of sowing opportunities in the drier regions since more time was allowed to establish sufficient cover crop. Availability of deep soil-moisture was important, particularly in the later crop phases when the roots reach deeper layers, and sufficient soil moisture is required to grow and finish bolls. Our assessment further highlights the potential impact of excessively wet conditions on cotton production. Short periods of intense rainfall (known as “burst” events); a typical characteristic of the monsoon, reduce cotton yield through waterlogging. Scaling our simulated yields to the potential area of suitable soils in the NT shows considerable benefits to the regional economy and should be considered when planning industry development, including the establishment of cotton gins. The insights gained from this study are relevant to industry developments in similar environments, such as in parts of Brazil, India, and Sahelian Africa

Spatial Variability of Soil Macronutrients and Chemical Properties in Ujjain Tehsil of Ujjain District of Madhya Pradesh, India

Understanding the characteristics of soil and how it may be utilised sustainably makes soil property mapping a crucial process. To improve crop yield and preserve healthy soil, it is essential to understand the heterogeneity of the soil in each location in order to establish site-specific nutrient management strategies for that area. The current research was carried out in the Ujjain tehsil (Ujjain) district of Madhya Pradesh state, India, with the aim of measuring the spatial variability of several soil macronutrients and soil chemical characteristics. Throughout the research region, 150 geo-coded surface soil samples with a depth of 0 to 15 cm were collected. The soil characteristics, namely pH, electrical conductivity (EC), soil organic carbon (SOC), available nitrogen (Av-N), available phosphorous (Av-P), available potassium (Av-K), and available sulphur (Av-S), were assessed in these samples using standard methods. The research region's ranges for soil pH, EC, SOC, Av-N, Av-P, and Av-K were 7.01 to 8.15, 0.10 to 0.79 dSm-1, 0.30-0.60%, 139.00 – 235.00 kg ha-1, 8.00 – 25.60 kg ha-1, and 301.00 – 463.00 kg ha-1, in that order. The data were analysed using classic statistics and geo--statistics by constructing semi-variograms and mapping by ordinary kriging techniques. Semi-variograms were calculated for soil characteristics and their spatial distributions were mapped. Best-fit models for measured soil properties were Exponential, Circular, Gaussian and Hole effect with Nugget/Sill (Co/Co+C) ratio for modelled variables indicated strong and moderate spatial dependences. The distribution maps of soil attributes could be utilized as a guide for site-specific crop management in similar soils. Further, this study demonstrates the usefulness of GIS- application in soil variability studies.

Influence of Weather, Soil Variability, and Vegetation on Seasonal Ground Movement: A Field Study

Influence of Weather, Soil Variability, and Vegetation on Seasonal Ground Movement: A Field Study

Yield stability and weed dry matter in response to field-scale soil variability in pea-oat intercropping

Abstract Background and aims Intercropping of grain legumes and cereals in European agriculture can provide benefits, such as an increase in yields, yield stability and weed suppression. Interactions between crops in intercropping may depend on spatial heterogeneity in soil conditions, which are present on farmers’ fields. Understanding the effect of within-field variation in soil conditions on interspecific interactions might increase the benefits of intercropping by within-field adjustment of the agronomic management. Methods Crop performance and weed dry matter were assessed together with several soil properties in grids within three large field experiments at two sites (Germany and Sweden) and during two years. Each experiment was comprised of several strips sown either with the two sole crops oat (Avena sativa L.) and field pea (Pisum sativum L.) or an oat-pea intercrop. Results The response of crop performance to within-field variability in soil conditions was mostly species-specific. Yield stability of intercropping was consistently higher compared with pea, but not compared to oat. The highest land equivalent ratio was found for an additive intercropping design under a higher water availability. In this experiment, yield stability of both intercropped pea and oat were lower, which might be expected as a result of within-field variation in interspecific interactions. Intercropping reduced weed dry matter compared to pea, for which one experiment indicated an increase in weed dry matter with nutrient availability. Conclusion The experimental design and the developed statistical analysis can contribute to further research about spatial variations in interspecific interactions in intercropping, which will improve the understanding of plant-plant and plant-soil interactions.

Nitrification and Denitrification Gene Abundances under Stable Soil Chemical Properties Established by Long-Term Compost Fertilization

Rice paddies are dynamic areas for microbe-mediated nitrogen cycling and this could be driven by the long-term alteration of paddy soil edaphic factors. The objective of this study is to evaluate the lasting impact of long-term compost fertilization on the soil chemical properties of paddy fields, determining the size of the microbial guilds involved in nitrification and denitrification. Soil sampling was done on paddy fields without fertilizer, with NPK + compost, and with compost application, and the soil chemical properties of the fields were determined from 2018 to 2021. The abundance of genes related to nitrogen cycling was measured using quantitative PCR (qPCR). Annual analyses showed that the studied soils have attained stable, baseline chemical properties with significantly increased phosphorus (P2O5), potassium (K), SOM, and total nitrogen (TN) due to decades of fertilization with NPK + compost and compost. Consequently, the genes related to bacterial amoA, nosZI, and nosZII were significantly increased in Com- and NPKCom-amended soils compared to the NF paddy field. The nirK gene abundance was unaffected after long-term amendment with compost. A positive correlation was found between the archaeal amoA gene abundance and DOC, while SOM and TN were consistently positively correlated with the abundances of bacterial amoA, nosZI, and nosZII genes, in addition to interactions with potassium and DOC. Principal component analysis (PCA) indicated soil variabilities across treatments, where the unfertilized paddy field contained lower SOM and nutrient contents with a characteristic nirK gene abundance. Similar variabilities in terms of the SOM, TN, K, nosZI, and nosZII gene abundances were observed in the Com and NPKCom paddy fields. Long-term amendment with NPK + compost and compost created soil paddy fields with stable soil chemical properties with higher SOM and nutrient contents, which established higher abundances of genes associated with denitrification and nitrification that were observed during the fallow period.

Predicting subsurface classification in 2D from cone penetration test data

Uncertainty is inevitable in the characterisation of a geotechnical site, especially due to the inherently heterogeneous nature of the ground. In this paper, a method for characterising a subsurface with limited cone penetration test (CPT) data is proposed. The method is based on integrating predictions of CPT parameters with a probabilistic approach for subsoil classification at the CPTs. The predicted stratigraphy is able to capture the spatial variability of soil measured via CPTs and takes account of the uncertainties that arise from transforming CPT measurements into soil units as well as errors in the measurements themselves. The applicability of the proposed method is demonstrated for a site in the Netherlands. The results show that the proposed approach can identify the most likely classification in the domain with good accuracy. Furthermore, the significance of considering the uncertainties in predicting the most likely classification is illustrated via finite element stability analyses of a slope cut-out in the domain.

Spectral Variability of Rocks and Soils on the Jezero Crater Floor: A Summary of Multispectral Observations From Perseverance's Mastcam‐Z Instrument

AbstractNASA's Mars‐2020 Perseverance rover spent its first year in Jezero crater studying the mafic lava flows of the Máaz formation and the ultramafic cumulates of the Séítah formation, both of which have undergone minor alteration and are variably covered by coatings, dust, and/or soil deposits. Documenting the rock and soil characteristics across the crater floor is critical for establishing the geologic context of Perseverance's cached samples—which will eventually be returned to Earth—and for interpreting the deposition and modification of the Máaz and Séítah formations. Mastcam‐Z, a pair of multispectral, stereoscopic zoom‐lens cameras, provides broadband red/green/blue and narrowband visible to near‐infrared images (VNIR, 440–1,020 nm). From multispectral observations from sols 0 to 380, we compiled a database of ∼2,400 representative Mastcam‐Z spectra. We analyzed principal components, spectral parameters, and laboratory spectra of pure minerals and natural rock surfaces to interpret the spectral diversity of rocks and soils. We define eight spectral classes of rocks: Dusty, Hematite‐like, Coated, Low‐Ca Pyroxene‐like, Olivine‐like, Weathered Olivine‐like, Fe‐rich Pyroxene‐like, and Dark Oxide‐like. The variability of soil spectra in the Jezero crater floor is controlled primarily by the amount of dust and indicates a largely consistent soil mineralogy across the traverse, with the exception of the area disturbed by the landing event. In comparison to rock spectra from the Curiosity rover's Mastcam instrument in Gale crater, rocks on the Jezero crater floor are generally less spectrally diverse, but the Olivine‐like rocks within the Séítah formation represent a new spectral rock class in Mars surface exploration.

An experimental study on the effect of particle size and non-homogeneity on the shear strength of soil

Soil deposits available in nature are often present as homogeneous mixtures of particles of different sizes and base minerals or as a combination of soils in different layers forming a non-homogeneous configuration. This variability in soil has great influence on the shear strength behaviour. In this study, different naturally occurring soil particle sizes and shapes (angular and flaky) have been utilized as reinforcements in the form of layers to determine their influence on the soil shear strength. Therefore, triaxial tests have been conducted on homogeneous sand (where particles are mixed proportionately), and on non-homogeneous sand (different layer combinations of different particle sizes as well as the inclusion of angular and flaky particles). It has been observed that there was a substantial increase in the shear strength for non-homogeneous arrangement compared to homogeneous sand sample. Furthermore, the addition of flaky particles from 10% to 30% by weight of fine grained sand increased the angle of internal friction (ϕ) and cohesion (c) values thereby increasing the shear strength. However, for angular-fine sand layer combination, the addition of 10-20% of angular particles by weight shows a significant increase in shear strength in comparison to 30-100% of angular particles.