Stone Content Research Articles

Numerical Simulation Study on Compression Characteristics of Gravelly Soil Mixture Based on Soft Servo Method

Because of complex mechanical properties and deformation mechanism, gravel soil mixture is an important medium of concern in the field of geotechnical engineering. Based on the continuous-discontinuous coupling algorithm formed by the structure shell elements and the particle discrete element method (PFC3D), the soft servo loading of the sample is realized, and the typical triaxial compression test data are used to calibrate mesoscale parameters. Furthermore, the numerical tests under different rock contents and confining pressure are carried out. The change rule of shear strength of mixed medium is discussed. It shows that the continuous-discontinuous coupling algorithm achieves a good effect in reflecting the deformation process. Under the mechanism of the flexible servo, the failure mode of the sample takes on drum-failure mode, and the internal of the damaged sample forms an obvious asymmetric X-shaped shear band. With the increase of stone content, the internal friction angle and cohesive force distribution of the sample have certain discreteness, but on the whole, the internal friction angle and cohesive force increase with the increase of stone content. The results can provide a reference for the parameter determination of mixed mediums such as gravel soil.

Invitro: Evaluasi Aktifitas Peluruhan Batu Ginjal Ekstrak Daun Kemangi (Ocimum Basilicum) Menggunakan Spektrofotometer Serapan Atom

A kidney stone is a disease that is quite often found in the community. Kidney stone disease is characterized by the formation of small stones due to precipitation in the urine. This stone can clog urethra and cause pain. The most common kidney stone content is calcium oxalate. Kemangi (Ocimum basilicum) contains several secondary metabolites such as flavonoids, saponins, phenols, and tannins. The content of secondary metabolites is thought to shed kidney stone. This study aims to reveal other properties of kemangi plant as anticalculi. Method: The stages in this study consisted of making kemangi leaf ethanol extract, extract characterization, phytochemical extract screening, kidney stone calcium making, and kidney stone calcium decay test stage. Testing the effect of the destruction of kidney stone is carried out in vitro by testing the rate of decay of kidney stone calcium components in various concentrations of ethanol extracts of kemangi leaf in physiological NaCl. Kidney stone calcium decay was analyzed by atomic absorption spectrophotometer (ASS). Data were analyzed with one-way ANOVA and continued with the LSD test. Results: ethanol extract of kemangi leaf at a concentration of 600 ? x ?1600 ppm could shed kidney stone calcium significantly greater than negative controls. Conclusion: the kemangi leaf ethanol extract has potential as the destruction of kidney stone.

Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile

Societal demands on soil functionality in agricultural soil-landscapes are confronted with yield losses and environmental impact. Soil functional information at national scale is required to address these challenges. On behalf of the well-known theory that soils and their site-specific characteristics are the product of the interaction of the soil-forming factors, pedometricians seek to model the soil-landscape relationship using machine learning. Following the rationale that similarity in soils is reflected by similarity in landscape characteristics, we defined soil functional types (SFTs) which were projected into space by machine learning. Each SFT is described by a multivariate soil parameter distribution along its depth profile. SFTs were derived by employing multivariate similarity analysis on the dataset of the Agricultural Soil Inventory. Soil profiles were compared on behalf of differing sets of soil properties considering the top 100 and 200 cm, respectively. Various depth weighting coefficients were tested to attribute topsoil properties higher importance. Support vector machine (SVM) models were then trained employing optimization with a distributed multiple-population hybrid Genetic algorithm for parameter tuning. Model training, tuning, and evaluation were implemented in a nested k-fold cross-validation approach to avoid overfitting. With regards to the SFTs, organic soils were differentiated from mineral soils of various particle size distributions being partly influenced by waterlogging and groundwater. Further SFTs reflect soils with a depth limitation within the top 100 cm and high stone content. Altogether, with SVM predictive model accuracies between 0.7 and 0.9, the agricultural soil-landscape of Germany was represented with eight SFTs. Soil functionality with regards to the soil’s capacity to store plant-available water and soil organic carbon is well characterized. Four additional soil functions are described to a certain extent. An extension of the approach to fully cover soil functions such as nutrient cycling, agricultural biomass production, filtering of contaminants, and soil as a habitat for soil biota is possible with the inclusion of additional soil properties. Altogether, the developed data product represents the 3D multivariate soil parameter space. Its agglomerated simplicity into a limited number of spatially allocated process units provides the basis to run agricultural process models at national scale (Germany).

Root architecture development in stony soils

AbstractSoils with high stone content represent a challenge to root development, as each stone is an obstacle to root growth. A high stone content also affects soil properties such as temperature or water content, which in turn affects root growth. We investigated the effects of all soil properties combined on root development in the field using both experiments and modeling. Field experiments were carried out in rhizotron facilities during two consecutive growing seasons (wheat [Triticum aestivum L.] and maize [Zea mays L.]) in silty loam soils with high (>50%) and low (<4%) stone contents. We extended the CPlantBox root architecture model to explicitly consider the presence of stones and simulated root growth on the plot scale over the whole vegetation period. We found that a linear increase of stone content resulted in a linear decrease of rooting depth across all stone contents and developmental stages considered, whereas rooting depth was only sensitive to cracks below a certain crack density and at earlier growth stages. Moreover, the impact of precipitation‐influenced soil strength had a relatively stronger impact on simulated root arrival curves during the vegetation periods than soil temperature. Resulting differences between stony and non‐stony soil of otherwise the same crop and weather conditions show similar trends as the differences observed in the rhizotron facilities. The combined belowground effects resulted in differences in characteristic root system measures of up to 48%. In future work, comparison of absolute values will require including shoot effects—in particular, different carbon availabilities.

Triaxial Discrete Element Simulation of Soil–Rock Mixture with Different Rock Particle Shapes under Rigid and Flexible Loading Modes

Three-dimensional scanning technology was used to construct the database of natural block stone shapes with different particle sizes. On the basis of Particle Flow Code 3D, a discrete element random model of soil–rock mixtures with different stone contents and shapes was established. A flexible boundary loading method of multisection wall was adopted to simulate the flexible film constraint mode of indoor triaxial test. Large-scale triaxial numerical simulation tests were carried out on the soil–rock mixture with different stone contents, stone shapes, and loading modes to analyze the macromechanics, microscopic deformation, and failure laws under various working conditions. Results showed that under the flexible loading mode, the stress curve of the samples with low stone content (0%–20%) has no obvious peak value and the deformation is mainly shear shrinkage. The stress curve of the samples with high stone content (40%–60%) showed the obvious peak value, and the dilatancy was prominent. Under the action of vertical load, the specimen bulged and formed multiple fork shear bands. Compared with the flexible loading mode, the rigid loading mode showed that the strength of the specimen increased in the rigid loading mode, and the cohesion and internal friction angle improved overall, but the friction energy was basically the same. During shearing, no obvious bulging was noted at the edge of the sample, and the shear bands were K-shaped and diagonal. The shape of block stone had significant influence on the strength, friction energy, and shear band shape of the soil–rock mixture.

Field-saturated hydraulic conductivity estimated using class numbers of soil survey

Readily available field data were used to estimate field-saturated hydraulic conductivity (Kfs). Kfs determinaion is laborious, however crucial for various applications, e.g. evaluation of soil functions or groundwater protection. Alluvial soils are close to the groundwater body and thus of special concern with respect to allochthonous contamination. A pedotransfer function (PTF) was developed for 11 alluvial soils. Response variable were 43 Kfs-values determined using a borehole permeameter. Qualitative and semi-quantitative data obtained in the field at 11 near-by soil pits were classified. These classifications comprise texture, humus content, stone content and soil structure as well as hydromorphic indicators such as iron molds, anoxic molds, concretions and soil color. 9 non-multicollinear input variables were selected via factor analysis. In 100 randomized regression realizations the class values were implemented applying 67% of the total data set for training to describe the Kfs-value. While the individual realizations showed considerable deviation to the measured Kfs-values, the averaged linear regression with mean values of intercepts and coefficients provided an acceptable accurracy. The quality criteria of the developed PTF consisted of the root mean square error (RMSE = 0,37), the Nash-Sutcliffe efficiency (NSE = 0,59), and the measure of determination (R2 = 0,59). Despite class thresholds of basic soil properties originally are not linked to soil hydraulic characteristics in the first instance, class values of soil survey can be utilized to estimate the field-saturated hydraulic conductivity in soils with homogeneous horizons.

Reassessment of the hydrologic soil group for runoff modelling

The hydrologic soil group (HSG) is required for the determination of curve numbers (CN), which are used in a large number of hydrological models to calculate surface runoff during rain events of ungauged catchments. Despite the paramount importance of HSG, it is still based on an assumption made in 1955. We assessed HSG using 249 rainfall simulation experiments carried out in two sets of experiments examining seedbed conditions. One set analyzed the variation within a small (60 ha) catchment while the other examined 32 benchmark soils selected to cover the full range of arable soils on sloping land in temperate humid areas. The assumption made in 1955 that sandy and stony soils have a low HSG (A), while clayey soils of low permeability have a high HSG (D), cannot be supported. Instead, HSG appeared to be governed by surface sealing because CN increased with increasing silt content in the bulk soil and decreasing soil organic matter content in the fine earth fraction. An equation for calculating CN and, in turn, a HSG from these two parameters is provided. This equation also avoids classification-induced errors. The relation holds true for a wide range of rain properties (e.g., rain amount between 0.2 mm and 103 mm; event intensities between 2 mm h−1 and 80 mm h−1), slope gradients (2 %–24 %) and various soil properties (e. g., stone contents up to 40 %, clay contents up to 61 %, sand contents up to 87 %). The CN and, in turn, HSG remained constant throughout the events from the start of runoff until the end of the event, which was up to 49 h later in 32 cases. Autocorrelation within the catchment was strong and the full variation was found within 600 m. Even small catchments are, hence, heterogeneous and their runoff cannot be assigned to a single HSG or a single CN. Rejecting the assumption developed in 1955, which had not been verified since then, has important implications for hydrological modelling but also for the development, implementation and assessment of water conserving land use.

Assessing new sensor‐based volume measurement methods for high‐throughput bulk density estimation in the field under various soil conditions

AbstractSoil bulk density (BD) is a key soil property in soil science. BD is measured at the scale of the soil horizon with conventional methods: core sampling and rubber balloon. Regardless of the method, BD measurement in the field is cumbersome and time consuming, especially in stony soils, and new, less invasive methods have emerged, but their measurement quality needs to be compared with conventional methods. The photogrammetric technique (SfM) consists of the reconstruction of a given scene in 3D from multi‐view photographs. The aim of the present work is to assess the SfM as a rapid, accurate method of measuring the volume of undisturbed soil for BD measurements, regardless of the soil depth and stone content. Ten soil horizons were investigated from various types of soils with different soil properties, especially texture (10 to 48% of clay) and stone content (0 to 73%). The bulk density of each horizon was measured with a reference method (core sampling), an excavation method (rubber balloon) and two recently developed sensor‐based methods: SfM and a lightweight flash LiDar. For the sensor‐based methods, an automated post‐processing method was developed to reduce the human operating time. The BDs measured from the SfM were significantly similar to those measured from core sampling. At this stage, the lightweight flash LiDar is not sufficient to measure the BD with high accuracy. Finally, we recommend the use of SfM to measure BD regarding its robustness in varying soil conditions, especially stony soils, and we discuss the potential of the method regarding the recent advances in its field use with smartphones.Highlights Soil bulk density (BD) is a key soil property in soil science The photogrammetric technique and flash Lidar were applied to measure BD in the field The photogrammetric technique and flash Lidar were compared to classical methods The flash lidar is not sufficient to measure the BD with high accuracy The photogrammetric technique is recommended especially in stony soils

African soil properties and nutrients mapped at 30\xa0m spatial resolution using two-scale ensemble machine learning

Soil property and class maps for the continent of Africa were so far only available at very generalised scales, with many countries not mapped at all. Thanks to an increasing quantity and availability of soil samples collected at field point locations by various government and/or NGO funded projects, it is now possible to produce detailed pan-African maps of soil nutrients, including micro-nutrients at fine spatial resolutions. In this paper we describe production of a 30 m resolution Soil Information System of the African continent using, to date, the most comprehensive compilation of soil samples (N approx 150,000) and Earth Observation data. We produced predictions for soil pH, organic carbon (C) and total nitrogen (N), total carbon, effective Cation Exchange Capacity (eCEC), extractable—phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), zinc (Zn)—silt, clay and sand, stone content, bulk density and depth to bedrock, at three depths (0, 20 and 50 cm) and using 2-scale 3D Ensemble Machine Learning framework implemented in the mlr (Machine Learning in R) package. As covariate layers we used 250 m resolution (MODIS, PROBA-V and SM2RAIN products), and 30 m resolution (Sentinel-2, Landsat and DTM derivatives) images. Our fivefold spatial Cross-Validation results showed varying accuracy levels ranging from the best performing soil pH (CCC = 0.900) to more poorly predictable extractable phosphorus (CCC = 0.654) and sulphur (CCC = 0.708) and depth to bedrock. Sentinel-2 bands SWIR (B11, B12), NIR (B09, B8A), Landsat SWIR bands, and vertical depth derived from 30 m resolution DTM, were the overall most important 30 m resolution covariates. Climatic data images—SM2RAIN, bioclimatic variables and MODIS Land Surface Temperature—however, remained as the overall most important variables for predicting soil chemical variables at continental scale. This publicly available 30-m Soil Information System of Africa aims at supporting numerous applications, including soil and fertilizer policies and investments, agronomic advice to close yield gaps, environmental programs, or targeting of nutrition interventions.

Analysis of Strength and Compression Damage Characteristics of Soil Rock Mixture Based on Geopolymeric Reaction

Geopolymers was a common means of solidifying soil which can improve the overall strength of the soil. In order to further explore the strength and damage characteristics of the soil-rock mixture under the action of gel coagulation, this paper analyzed the compressive strength of the soil-rock mixture under different stone content through the unconfined compressive strength test. The results illustrated that when the amount of stone was small, the compressive strength decreases linearly with the increase of the amount of stone, and increased with the increase of the amount of geopolymer; According to discrete element method, using PFC2D software, to simulate the microscopic deformation and mechanical properties of the specimen during compression. The increase of stone content would magnify the damage of the soil when it reached the failure, but it did not necessarily increase the overall soil mass numerically. The strength of the soil would be greatly improved when the stone content reached a state that could form a skeleton structure.

Performance evaluation of SVM and GBM in predicting compressive and splitting tensile strength of concrete prepared with ceramic waste and nylon fiber

Waste management has become a new challenge for the construction industries since rapid urbanization is taking place worldwide. Ceramic waste is one such material which is being originated from construction sites and industries, imposing a significant risk to the environment due to its non-biodegradable nature. With the goal of waste utilization, this study aims to predict the compressive and splitting tensile strength of concrete made with waste Coarse Ceramic aggregate (CCA) and Nylon Fiber (NF) by using two distinct machine learning algorithms, namely, Support Vector Machine (SVM) and Gradient Boosting Machine (GBM). A comprehensive data set for testing and training the models containing 162 records of compressive and splitting tensile strength test results were considered from nine mix proportions. For training the dataset, parameters like cement content, sand content, stone content, ceramic content, nylon fiber content, curing duration, and concrete strength were taken as input variables. The predicted strengths obtained from the SVM and GBM based models are found to be in close agreement with the experimental results. In terms of coefficient of determination (R2), GBM showed significantly better result for both compressive strength (e.g., SVM Overall R2 = 0.879 & GBM Overall R2 = 0.981) and tensile strength (e.g., SVM Overall R2 = 0.706 & GBM Overall R2 = 0.923) prediction. Furthermore, based on the statistical accuracy measures like the mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), it has been observed that GBM has yielded much better performance compared to SVM in predicting the mechanical strength of concrete.

Stability Analysis of Rock-soil Mixture Slope

This research provides a method of random generation of Soil-rock Mixture (SRM) model depends on digital imaging technology and rock stone database technology. With processed rock shape diagrams, database of rock shape had been built and a method of random generation depend on this database had been provided. The SRM backfilled slope models were generated with random generation method. Couples of SRM slope models had been simulated with ABAQUS CAE to study the stability of SRM slope with different parameters variations. The influence of block stones on the slope stability is main caused by rock stones’ slipresistance effect. When the stone content is 40%-50%, the block stones gradually contact with each other and form a framework. The safety factor gradually increases. The spatial distribution of rock stones at the foot of the slope has the most obvious influence on the stability of SRM slope. With the increase of maximum block size, the slope stability decreases firstly and then increase. The sliding resistance effect is the key factor of the SRM slope stability. Aggregation of small size stones or large size stones can change the shape of the sliding surface and have great influence on the stability of the slope.

Earthworm community development in soils of a reclaimed steelworks

Long-term studies are essential to learn earthworm community development and soil formation post reclamation. Investigations were undertaken at a former steelworks site at Hallside, near Glasgow, UK, reclaimed in the 1990s using a mixture of colliery spoil and sewage sludge. The site was largely planted for production of short rotation coppice willow (Salix spp.). Earthworm inoculation formed a part of the restoration process. Minimal monitoring occurred in the interim, but some records of earthworm sampling existed in 2000 and 2005. This study focused on monitoring earthworms and soil properties across the site, drawing comparisons with adjacent unspoiled soil. Results showed that after 22 years, a species-rich community of earthworms (n = 16) colonized the site, with endogeic Aporrectodea caliginosa being dominant by number and anecic A. longa by mass. Across the site, earthworm community density and biomass were 208 individuals m-2 and 71 g m-2, respectively. The Shannon diversity index for earthworms was 1.89, with an evenness of 0.68. The sewage sludge increased the soil organic matter, but the stone content of the colliery spoil prevented digging in some locations. Soil chemistry had no negative effect on earthworms, but the compacted substrate did hinder water infiltration. Earthworms colonized the reclaimed site from adjacent areas, and community structure and density below well-drained, scrub-free willow, birch, and grassland were not significantly different (P > 0.05) from those of the adjacent unspoiled areas. The results show that the historical earthworm inoculation was unnecessary and badly timed. Future reclamations of similar sites can learn from this investigation.

The Impact of Historical Agricultural Landuse on Selected Site Conditions in the Traditional Landscape of the West Carpathians

Abstract This article is focused on the site conditions of the cultural mountainous West Carpathian landscape (Liptovská Teplička village, Central Slovakia) affected by historical agricultural land use, which also included relief and soil modifications leading to the formation of specific mosaic of agrarian landforms – AL (narrow productive plots separated by balks having character of terraces and mounds). It is based on a pair comparison of sites located side by side; the former is located on the productive plot (former arable land), while the latter is a balk. The pairs were selected in order to capture the representative sample of AL within diverse natural conditions, land cover and management. In order to assess the differences between individual AL, continuous soil water content (SWC) measurements using EC-5 soil moisture sensors were performed. The sensors provided continuous measurements of hourly soil volumetric water content rates (VWC, m3/m3). The data were recorded from April 2018 until December 2018. These data were used to assess individual monitoring localities in terms of SWC temporal stability. Furthermore, at each sampling location, an analysis of soil organic matter content, soil texture and stone content was performed. This research was also supplemented by indirect estimation of some site conditions based on phytoindication method using Ellenberg’s indicator values for moisture, soil reaction, nutrient content, continentality, temperature and light. Our results can be concluded as follows: i) the SWC temporal stability assessment revealed the clear effect of AL, however, it was difficult to identify which factors associated with AL typology were the most significant. The high differences between similar AL types revealed the fact that land use, management and rock content (both at productive plots and balks) affect the SWC temporal stability rather than AL typology and their orientation within the slope, ii) phytoindication method did not show statistically significant differences in site conditions between productive plots and balks, despite the fact that there were some significant differences confirmed in species composition, especially between productive plots and dolomite mounds. These differences are related to a higher number of calciphilous and termophilous species preferring ecotones and forests in mounds and group of mesophilous meadow species in productive plots. In summary, it seems that identified differences in both SWC temporal stability and floristic composition between productive plots and balks reflect the management regime rather than site conditions and formation of mounds represents relatively the most significant impact of traditional agricultural land use on the local environment.

Tree species identity drives soil organic carbon storage more than species mixing in major two-species mixtures (pine, oak, beech) in Europe

Mixed forests are usually associated with higher aboveground carbon storage compared to the corresponding monocultures but information on the impact of tree species mixing on soil organic carbon (SOC) is still limited. Yet, maximizing SOC storage is crucial for ecosystem C sequestration and many other ecosystem services. This study used a triplet approach (ie. two-species mixed stand and respective pure stands at the same site) to assess the impact of tree species identity and mixing on SOC storage in eight pine-oak, eight pine-beech and five beech-oak triplets in Europe. We sampled the forest floor (FF) and 0–40 cm in the mineral soil per 10 cm interval. For each triplet type, we fitted basal area (BA) proportion of one component species (for species identity) and a BA-based plot-level True Shannon Diversity index (for species mixing) as explanatory variables for SOC stocks in linear mixed effects models, which included stone content and plot BA as covariates, and site as a random intercept. Considering the total soil depth (FF + 0–40 cm), species identity effect on SOC stocks was only significant for pine-beech and pine-oak triplets but explained more variability in SOC stocks than species mixing across triplet types. Species mixing effect was not significant for any triplet type in the total soil depth. While species identity consistently drove SOC storage in the topsoil layers across triplet types, species mixing explained more variability in SOC stocks in the deeper soil layers except for pine-oak triplets. The results showed that species identity is a stronger driver of SOC storage than species mixing. While tree species identity effect was strongly related to a conifers vs broadleaves signature, the drivers behind mixing effects remained elusive. The results suggest that targeted selection of tree species could better enhance SOC storage in European forests than a mere increase in species richness.

Effect of large broken stone content on properties of roller compacted concrete based on fractal theory

The effect of large broken stone content with maximum particle size of 120 mm on the four-graded roller compacted concrete (RCC) is investigated by mechanical properties and freeze-thaw cycles tests. Using fractal geometry, the quantitative relationships of large broken stone content, mechanical behavior, and damage degree of concrete are established, which reveal the influence of large broken stone content on the mechanical properties and frost resistance of RCC. The results of fitting analyses indicate that the compressive strength and the age of RCC are significantly correlated. In addition, the correlations of different mechanical properties of RCC are established. After 150 freeze-thaw cycles, the cross-cutting cracks appear in four-graded RCC, which lead to the failure of samples, while the wet-screened RCC can reach anti-freezing level of F300. The total surface areas of four-graded RCC and wet-screened RCC with different large broken stone contents are calculated by fractal theory, which reveal the positive and negative effects of large broken stone content on the properties of RCC. Based on fractal dimension, the freezing-thawing damage model of RCC was established, which describes the correlation between the damage degree and the total surface area of four-graded RCC.

Deformation Characteristics of the Shear Zone and Movement of Block Stones in Soil–Rock Mixtures Based on Large-Sized Shear Test

Soil–rock mixtures (SRM) have the characteristics of distinct heterogeneity and an obvious structural effect, which make their physical and mechanical properties very complex. This study aimed to investigate the deformation properties and failure mode of the shear zone as well as the movement of block stones in SRM experimentally, not only considering SRM shear strength. The particle composition and proportion of specimens were based on field samples from an SRM slope along national highway 318 in Xigaze, Tibet. Shear zone deformation tests were carried out using an SRM-1000 large-sized geotechnical apparatus controlled by a motor servo, considering the effects of different stone contents by mass (0, 30%, 50%, 70%), vertical pressures (50, 100, 200, 300, and 400 kPa), and block stone sizes (9.5–19.0, 19.0–31.5, and 31.5–53.0 mm). The characteristics of the shear zone deformation and block stone interactions were monitored by placing aluminum wires and dry ash in holes in the specimens. The results showed that the stone content 30% and 70% were two critical thresholds to determine the deformation characteristics of SRM. Under the conditions of high stone content and large particle size, the stones throughout the shear surface tended to extrude and roll during the shear process. The block stones around the shear surface were mainly affected by dilatancy and exhibited extrusion, particle breakage, and redistribution. The deformation pattern could be considered as be analogous to push-type shear deformation from the back to front or composite shear deformation from the front and back to the middle of the slope. It is of great importance to study the shear characteristics and deformation evolution of SRM to understand the progressive shear process of the sliding zone and the failure mode of landslides.

Prediction model of the collapse of bank slope under the erosion effect of wind-induced wave in the Three Gorges Reservoir Area, China

During the storage period of the Three Gorges Reservoir, the bank erosion caused by wind-induced wave is getting more serious, especially for the crushed stone soil bank. The continuous wave scouring and erosion destabilize the bank slope and even induce the occurrence of landslides. Based on the energy conservation theory, the bank slope will reach a stable state after continuous wave erosion. Regarding this, this paper derives the prediction formula of the stable slope angle and erosion width when the wave erodes the crushed stone soil bank slope. Model tests on bank slopes with different dry densities and different crushed stone contents under the action of waves were conducted to observe the erosion process of wave-induced crushed stone soil bank slope and verify the proposed prediction formula. The results show that under the action of wave erosion, erosion ridge and collapse steep angle would form at the upper edge of the bank slope and the controlling factors of this process are the dry density of the crushed stone soil and the wave energy. When the content of crushed stone soil gradually increases, the ability of the bank slope to resist wave erosion weakens at first and then gradually strengthens. Comparing the erosion stable slope angle obtained from the model tests with the calculated results using the proposed prediction formula, a linear relationship could be observed, indicating that the proposed prediction formula is reliable for further analysis.

Mechanical characteristics of soil-rock mixtures containing macropore structure based on 3D modeling technology

Soil-rock mixtures containing macropore (SRMCM) is a kind of geological material with special mechanical properties. Located in the project area of Lenggu hydropower station on the Yalong River, Sichuan Province, China, there is an extremely unstable Mahe talus slide with a total volume of nearly 160 million cubic meters, which is mainly composed of SRMCM. The study on the mechanical properties of SRMCM is of great significance for the engineering construction and safe operation. In this paper, laboratory tests and discrete element numerical tests based on three-dimensional scanning technology were conducted to study the influence of stone content, stone size, and the angle of the macropore structure on shear characteristics of SRMCM. The failure mechanism of SRMCM was discussed from a microscopic perspective. This work explains the internal mechanism of the influence of stone content, stone size, and the angle of the macropore structure on the strength of SRMCM through the microscopic level of stone rotation, force chain distribution, and crack propagation. As the macropore structure that intersects with the preset shear plane at a large angle could act as a skeleton-like support to resist the shear force, the fracture of the weak cemented surface of soil and stone in the macropore structure is an important cause of SRMCM destruction.

Stone Content Influence on Land Surface Model Simulation of Soil Moisture and Evapotranspiration at Reynolds Creek Watershed

AbstractConsiderable advancement in spatiotemporal resolution of remote sensing and ground-based measurements has enabled refinement of parameters used in land surface models for simulating surface water fluxes. However, land surface modeling capabilities are still inadequate for accurate representation of subsurface properties and processes, which continue to limit the accuracy of land surface model simulation. Our objective in this study was to examine the performance of the variously parameterized Noah land surface model with multiphysics option (Noah-MP) in simulating evapotranspiration (ET) and soil moisture dynamics in stony soils using verification from eddy covariance ET and in situ soil moisture data during the growing season of year 2015, obtained from the Lower Sheep subcatchment within the Reynolds Creek Experimental Watershed in southwestern Idaho. We evaluated the performance of Noah-MP considering four different scenarios with 1) a one-layer soil profile with Noah-MP default soil hydraulic parameters and three more five-layer soil profiles using 2) Noah-MP default soil hydraulic parameters; 3) soil hydraulic parameters derived from a pedotransfer function using field observations; and 4) hydraulic parameters from scenario 3, which also accounted for stone content in each layer. Each modeling experiment was forced with the same set of initial conditions, atmospheric input, and vegetation parameters. Our results indicate that enhanced representation of soil profile properties and stone content information noticeably improve the Noah-MP land surface model simulation of soil moisture content and evapotranspiration.