Soil Layer Research Articles

How did ancient human activities influence the properties and development of soil?—a case study of the Yangshao Village cultural relic site, Henan Province

Introduction: What were the effects of paleoanthropogenic activities on the physicochemical properties and degree of the development of soil? To search for this answer, we can not only understand the different types of ancient human activities but also explore the intensity and characteristics of the activities.Methods: In this study, soil samples from different soil layers and two profiles in the Yangshao Village cultural site in Henan Province were collected. Their physicochemical properties and the sporophyte phyllosilicates they contain were analyzed and compared.Results: We found that the paleoanthropogenic activities started in the relatively low-lying area, in which the slash-and-burn activities resulted in the soil being filled with intrusions such as charcoal debris and ceramic shards. At the same time, the coarse-grained matter was affected by the plowing activities and mostly decomposed into fine particles, and the content of clay particles reached an extreme value. The total nitrogen, phosphorus, and calcium carbonate content exceeded the average value of the natural profile, indicating that ancient humans had used human and animal feces to a certain extent to restore the fertility of arable land.Discussion: Overall, ancient human activities hindered the development of the soil, especially the ground created due to habitation activities. From the type and content of clay minerals, it could be seen that the soil in this layer has been transported from other places, has a high content of clay particles, and has experienced fire baking. It was assumed that the ground was used to cover the grain or bury the garbage and lay with clay in order to achieve the effect of sealing. As a result, the soil voids and structure had been damaged to some extent, which prevented the downward leaching or precipitation of soil particles and minerals to a certain extent, thus affecting soil development.

Compositional-geochemical characterization of lead (Pb) anomalies and Pb-induced human health risk in urban topsoil.

Urban areas are characterized by a constant anthropogenic input, which is manifested in the chemical composition of the surface layer of urban soil. The consequence is the formation of intense anomalies of chemical elements, including lead (Pb), that are atypical for this landscape. Therefore, this study aims to explore the compositional-geochemical characteristics of soil Pb anomalies in the urban areas of Yerevan, Gyumri, and Vanadzor, and to identify the geochemical associations of Pb that emerge under prevalent anthropogenic influences in these urban areas. The results obtained through the combined use of compositional data analysis and geospatial mapping showed that the investigated Pb anomalies in different cities form source-specific geochemical associations influenced by historical and ongoing activities, as well as the natural geochemical behavior of chemical elements occurring in these areas. Specifically, in Yerevan, Pb was closely linked with Cu and Zn, forming a group of persistent anthropogenic tracers of urban areas. In contrast, in Gyumri and Vanadzor, Pb was linked with Ca, suggesting that over decades, complexation of Pb by Ca carbonates occurred. These patterns of compositional-geochemical characteristics of Pb anomalies are directly linked to the socio-economic development of cities and the various emission sources present in their environments during different periods. The human health risk assessment showed that children are under the Pb-induced non-carcinogenic risk by a certainty of 63.59% in Yerevan and 50% both in Gyumri and Vanadzor.

Influence of spatial variability of soil shear-wave velocity considering intralayer correlation on seismic response of engineering site

Shear-wave velocity uncertainty significantly impacts seismic response analysis at engineering sites. Previous studies focused on the correlations of shear-wave velocities within soil layers. However, the influence of the vertical spatial variability of shear-wave velocity within individual soil layers was not considered. This study selected a typical Site Class II engineering site to investigate this influence based on the equivalent linear seismic response analysis method of layered soil deposits. Existing field test data on shear-wave velocity were used to discretize the shear-wave velocity within soil layers into a one-dimensional (1D) random field through covariance matrix decomposition and local average process theory. Monte Carlo simulations generated random shear-wave velocity profiles with different vertical correlation distances. Three artificial records with different earthquake return periods were used as input motions at the engineering bedrock for the 1D free-field model. Considering soil shear-wave velocity uncertainty, the peak shear strain increased by 19–27% with the input ground motion amplitude. Moreover, the site peak shear strain variability increased by 25–34% with the vertical correlation distance. The proposed 1D random field model effectively simulated the interlayer correlation and spatial variability of shear-wave velocity within soil layers, demonstrating its significance in seismic response analysis.

The effects of elevated CO2 and temperature on soil organic carbon and total nitrogen contents and mineralization in the 0 to 50 cm paddy soil layer were masked by different land use history

Global warming can accelerate soil organic matter (SOM) decomposition resulting in faster carbon loss and positive climate-C feedback. Previous studies on response of SOM decomposition to climate change mainly focus on plow soil layer. However, the effects of elevated CO2 and soil warming on soil organic carbon (SOC) and total nitrogen (TN) contents and mineralization are rarely studied in subsoil layer. In this study, soil samples were collected from the 0–50-cm paddy soil layer of the Tsukuba free-air CO2 enrichment experimental site with elevated CO2 (+200 ppm) and soil warming (+2 °C), Japan, after 5-year rice growth season. The amounts of SOC, TN, δ13C, and δ15N were analyzed. A 4-week anaerobic incubation experiment was conducted to measure C decomposition and N mineralization potentials. Due to the intrinsic variation in SOC and TN contents in soil layers and fields, the effects of elevated CO2 and soil warming on C decomposition and N mineralization potentials could not be determined here. However, the effect of elevated CO2 on δ13C was only found in 0‒10-cm soil layer. In the 0–50-cm soil profiles, significant correlations were observed among SOC and TN, δ13C and δ15N, decomposed C and mineralized N, and δ13C in decomposed C. The variables associated with soil C and N pools, and dynamics showed large spatial heterogeneity within paddy field, due to variation in the original land use history. Therefore, great caution should be exercised when evaluating the effects of elevated CO2 and temperature on SOM decomposition and sequestration in paddy soil profiles.

Long-term cotton stubble return and subsoiling improve soil organic carbon by changing the stability and organic carbon of soil aggregates in coastal saline fields

Cotton stubble return and subsoiling significantly enhanced soil fertility and cotton yield in coastal saline soils. Despite these benefits, the mechanisms influencing soil organic carbon (SOC) sequestration remain poorly understood. To address this gap, a comprehensive ten-year study was undertaken, focusing on the effects of stubble management (either removal or return) and tillage (either non-subsoiling or subsoiling) on the physicochemical properties of both topsoil (0–20 cm) and subsoil (20–40 cm) layers, as well as on cotton yield. The objectives were to (i) quantify interannual variability (2013–2022), stubble return, and subsoiling on the soil physicochemical properties of the topsoil (0–20 cm) and subsoil (20–40 cm) and cotton yield and (ii) elucidate the mechanism by which these agricultural practices affect SOC sequestration. Findings from this decade-long investigation indicated that ten consecutive years of cotton stubble return and subsoiling at three-year intervals significantly ameliorated soil conditions by reducing the salt content, pH, and the proportion of silt plus clay, while increasing macro-aggregates, mean weight diameter (MWD), aggregates organic carbon (AOC) across various particle sizes, SOC, total nitrogen (TN) in both soil layers, and ultimately, the cotton lint yield. Interestingly, the effect of stubble return on micro-aggregates varied between the two soil layers, leading to a reduction in micro-aggregates by 11.16% in the topsoil, in contrast to a 5.7% increase in the subsoil, when compared to conditions where stubble was removed. The partial least squares path modeling (PLS-PM) indicated that the enhancements in MWD attributable to stubble return and subsoiling were primarily due to significant reductions in soil pH and salt content in both layers, which in turn fostered an increase in AOC, ultimately contributing to higher SOC levels. However, the pathways through which AOC influenced SOC varied significantly between the topsoil and subsoil, with stubble return and subsoiling increasing SOC through an increase in the macro-AOC in the topsoil, and micro-AOC in the subsoil. In summary, long-term cotton stubble return and subsoiling significantly optimize the aggregate particle size distribution and enhance the carbon sequestration potential in coastal saline cotton fields.

Soil health indicators in oil palm agroforestry systems in the eastern Amazon, Brazil

Agroforestry systems (AFSs) are generally recognized for improving soil health and increasing soil carbon (C) stock. In the Amazon region, oil palm AFSs have been promoted as a productive strategy and may offer an additional benefit of recovering degraded areas. Our objective was to evaluate whether the management practices adopted in oil palm AFSs affect soil health indicators and C stock. We carried out a study in Tomé-Açu, state of Pará, eastern Amazon, through which we evaluated two oil palm AFSs that differed in species diversity: higher diversity (AFShigh) and lower diversity (AFSlow). We used a regenerating forest (FOR) to compare with the oil palm AFSs, as regenerating forests are also a model of environmental recovery in the eastern Amazon. In the 0–10, 10–20 and 20–30 cm soil layers, we evaluated chemical indicators (active acidity (pH), calcium (Ca), magnesium (Mg), potassium (K), phosphorus (P), and aluminum (Al)), (b) physical indicators (density (SD) and stability of aggregates (AGGRE)), and (c) biological indicators (permanganate oxidizable carbon (POXC), particulate organic carbon (POC), total soil carbon (SOC content) and root stock (ROOT)). We also evaluated the total soil carbon stock (SOC stock). The values of the biological indicators in the most superficial layer, especially the C indicators, were higher in the AFSlow (C content: 1.63 ± 0.13%, POXC: 568 ± 17 mg kg−1, POC: 0.63 ± 0.10 g kg−1) and the AFShigh (C: 1.84 ± 0.04%, POXC: 656 ± 24 mg kg−1, POC: 0.83 ± 0.06 g kg−1) than in FOR (C: 1.35 ± 0.09%, POXC: 336 ± 10 mg kg−1, POC: 0.44 ± 0.03 g kg−1). In general, the values of chemical indicators were higher in the AFSs than in FOR, except for the Al content, which was higher in FOR than in the AFSs. The physical indicators did not show a specific pattern of variation between the AFSs and FOR; aggregate stability was higher in FOR (range throughout the soil profile: 5.57 ± 0.09 to 5.38 ± 0.24 mm) than in the AFSlow (5.41 ± 0.03 to 3.79 ± 0.07 mm) and the AFShigh (5.07 ± 0.01 to 3.79 ± 0.11 mm) in all the soil layers, and soil density was higher in the AFShigh and FOR than in the AFSlow in most subsurface layers. Therefore, oil palm AFSs improve the chemical and biological health of the soil, especially in the more superficial layers, but it does not improve the physical health of the soil when compared to the forest.

Carbon sequestration potential and its main drivers in soils under alfalfa (Medicago sativa L.)

As a perennial forage crop, alfalfa (Medicago sativa L.) has been extensively utilized for the vegetation restoration of degraded soil and provides feedstock for forage. Its high usage can be attributed to its high yield potential and the increasing soil organic carbon (SOC) sequestration of alfalfa cultivation. However, the impact of land conversion to alfalfa on SOC content and its underlying drivers remain unclear. We performed a meta-analysis at the global scale to explore the quantified effects of alfalfa cultivation on SOC content and identify its controlling factors. We employed 1699 pairwise data points from 90 publications based on cropland/abandoned land conversion to alfalfa. Globally, cropland (cropland-alfalfa) and abandoned land (abandoned land-alfalfa) conversion to alfalfa enhanced SOC content by 12.1 % and 13.7 %, respectively. Alfalfa exhibited greater SOC content benefits in the surface soils (0–20 cm) with a lower level of initial SOC (<16 g kg−1), regardless of the land conversion type. Cropland-alfalfa was observed to increase SOC content with fertilization, irrigation, and conventional tillage in the long term (>5 years). Furthermore, abandoned land-alfalfa enhanced SOC content in the absence of alfalfa biomass removal and for longer cultivation durations (>5 years). Boosted regression tree analyses indicated variations in soil properties (75 % for cropland-alfalfa and 65 % for abandoned land-alfalfa) as the primary factors driving changes in SOC content. The dominant drivers were determined as the soil layer (51.6 %), cultivation duration (13.1 %), and initial SOC (12.9 %) for cropland-alfalfa, and initial SOC (43.7 %), soil layer (24.6 %) and cultivation duration (17.1 %) for abandoned land-alfalfa. Land conversion to alfalfa has great potential for SOC sequestration, particularly in low-fertility soils. Therefore, alfalfa cultivation is highly recommended for degraded lands due to its SOC sequestration benefits in vegetation restoration.

Distribution coefficients Kd of cobalt ions in soil samples of Anarak near-surface radioactive waste repository studied by batch and three different column methods

The selection of appropriate transport parameters of radionuclides is of utmost importance in the safety assessment of radioactive waste disposal sites. Both batch and column methods are widely performed to determine the transport parameters of radionuclides through soil layers. In this paper, the distribution coefficients Kd of Co ions in sandy mixtures containing soil samples taken from Anarak near-surface repository (Iran) were determined by batch and 3 different column methods namely, breakthrough curve, thin-section, and gamma spectroscopy methods. The distribution coefficients Kd of the mixture was obtained as 160 L kg−1 for the batch method, 23 L kg−1, 19 L kg−1, and 18 L kg−1 for the breakthrough curve, the thin-section, and the gamma spectroscopy methods, respectively. These results emphasize proper selection of transport data for using in the safety assessment programs.

Long-term straw return enhanced crop yield by improving ecosystem multifunctionality and soil quality under triple rotation system: An evidence from a 15 years study

ObjectiveRice-rice-oilseed rape rotation is a typical triple cropping system in Asia, and the development of rice-oilseed rape rotation plays an important role in ensuring global food and oil security. With the intensive cropping rotation and frequent changes between paddy and upland farming under anaerobic and aerobic conditions, whether tillage and straw return would be benefit for both agronomic and environmental perspectives remained to be tested. MethodTherefore, we used a long-term locational experiment (15 years) employing four treatments of conventional tillage without straw incorporation (CT); conventional tillage with straw incorporation (CTS); no-tillage without straw mulching (NT); no-tillage with straw mulching (NTS), to assess the relationships among soil quality, ecosystem multifunctionality, and crop yields under the straw-returning and tillage strategies, based on both agronomic and environmental perspectives. ResultThe results showed that long-term straw return to the field could increase the yield of early rice by 6.24–8.80%, late rice by 3.81–7.13%, and oilseed rape by 9.55–14.45%. Long-term straw return enhanced soil quality index (SQI) by 22.21–40.74% and ecosystem multifunctionality (EMF) by 104.19–141.14% in the 0–20 cm soil layer. Long-term conventional tillage (i.e., CT and CTS) showed higher SQI and EMF values especially in the oilseed rape season. Structural equation modelling (SEM) indicated that straw return and tillage mainly increased crop yield by increasing the SQI in the oilseed rape season. ConclusionIn conclusion, long-term straw return with conventional tillage would be more benefit for the improvement of soil quality and the multifunctionality of soil ecosystems under triple paddy-upland rotation system, offering an effective approach for sustainable soil management and crop production.

Temporal and spatial evolution of different heavy metal fractions and correlation with environmental factors after prolonged acid mine drainage irrigation: A column experiment

Acid mine drainage (AMD) has global significance due to its low pH and elevated heavy metal content, which have received widespread attention. After AMD irrigation in mining areas, heavy metals are distributed among soil layers, but the influencing factors and mechanisms remain unclear. AMD contamination of surrounding soil is primarily attributed to surface runoff and irrigation and causes significant environmental degradation. A laboratory soil column experiment was conducted to investigate the temporal and spatial distribution of the heavy metals Cd and Cu, as well as the impact of key environmental factors on the migration and transformation of these heavy metals following long-term soil pollution by AMD. After AMD addition, the soil exhibited a significant increase in acidity, accompanied by notable alterations in various environmental parameters, including soil pH, Eh, Fe(II) content, and iron oxide content. Over time, Cd and Cu in the soil mainly existed in the exchangeable and carbonate-bound fractions. In spatial terms, exchangeable Cu increased with increasing depth. Pearson correlation analysis indicated significant negative correlations between pH and Cu, Cd, and Eh in pore water, as well as negative correlations between pH and the exchangeable fraction of Cd (F1), carbonate-bound fraction of Cd (F2), and exchangeable fraction of Cu (F1) in the solid phase. Additionally, a positive correlation was observed between pH and the residual fraction of Cu (F5). Furthermore, the soil total Cd content exhibited a positive correlation with pyrophosphate-Fe (Fep) and dithionite-Fe (Fed), while CdF1, CdF2, total Cu, and CuF1 displayed positive correlations with Fep. Our findings indicate that the presence of AMD in soil leads to alterations in the chemical fractions of Cd and Cu, resulting in enhanced bioavailability. These results offer valuable insights for developing effective remediation strategies for soils near mining sites.

Soil classification based on unsupervised learning using cone penetration test data

Borehole data obtained during geological surveys are the most essential source for understanding soil stratification. It is a prerequisite to know the soil classes up to some depths prior to any construction. However, the direct method to identify the soil classes by drilling boreholes and testing soil samples is costly. A cost-effective alternative is the Cone Penetration Testing (CPT), which is one of the most popular soil investigation methods. This paper explores the intelligent classification of soil layers based on CPT data using three unsupervised machine learning methods: K-means, Gaussian Mixture Process, and BIRCH. The research investigates the classification performance of different models in scenarios with 2 combinations, 3 combinations, 4 combinations, and 5 combinations. The results indicate that the Gaussian Mixture Process method exhibits the best classification performance, followed by the BIRCH method, while K-means performs relatively poorly. Using unsupervised learning for intelligent soil layer classification offers a fast and clear process, but the accuracy still requires further improvement. This study provides a valuable reference for future soil classification studies.

Modeling the carbon dynamics of ecosystem in a typical permafrost area

Climate change poses mounting threats to fragile alpine ecosystem worldwide. Quantifying changes in carbon stocks in response to the shifting climate was important for developing climate change mitigation and adaptation strategies. This study utilized a process-based land model (Community Land Model 5.0) to analyze spatiotemporal variations in vegetation carbon stock (VCS) and soil organic carbon stock (SOCS) across a typical permafrost area - Qinghai Province, China, from 2000 to 2018. Multiple potential factors influencing carbon stocks dynamics were analyzed, including climate, vegetation, soil hydrothermal status, and soil properties. The results indicated that provincial vegetation carbon storage was 0.22 PgC (0.32 kg/m2) and soil organic carbon pool was 9.12 PgC (13.03 kg/m2). VCS showed a mild increase while SOCS exhibited fluctuating uptrends during this period. Higher carbon stocks were observed in forest (21.74 kg/m2) and alpine meadow (18.08 kg/m2) compared to alpine steppes (9.63 kg/m2). Over 90 % of the carbon was stored in the 0-30 cm topsoil layer. The contribution rates of soil carbon in the 30-60 cm and 60-100 cm soil layers were significantly small, despite increasing stocks across all depths. Solar radiation, temperature, and NDVI emerged as primary influential factors for overall carbon stocks, exhibiting noticeable spatial variability. For SOCS at different depths, the normalized differential vegetation index (NDVI) was the foremost predictor of landscape-level carbon distributions, which explained 52.8 % of SOCS variability in shallow layers (0-30 cm) but dropped to just 12.97 % at the depth of 30-60 cm. However, the dominance of NDVI diminished along the soil depth gradients, superseded by radiation and precipitation. Additionally, with an increase in soil depth, the influence of inherent soil properties also increased. This simulation provided crucial insights for landscape-scale carbon responses to climate change, and offered valuable reference for other climate change-sensitive areas in terms of ecosystem carbon management.

Investigation of cable current carrying capacity improvement and its effects on transmit power between Egypt and Saudi Arabia project

This paper presents an investigation for current carrying capacity improvement of high voltage cable laid in unfavorable regions crowded with groups of high and extra high voltage power cables. A proposed MATLAB program is developed to predict the ampacity of these cables at 220 kV and 500 kV. The cables are laid in various formats and under various laying conditions. Temperature distribution inside cable layers and through soil layers are studied using a finite element model (FEM) with COMSOL software during full load operation. Calculations are based on Neher-McGrath methods in accordance with IEC 60,287. The results are compared with the manufacturer's technical guarantee. Furthermore, this paper presents a proposed cable ampacity calculation that is applied to determine the ideal cross section area for four circuits of 500 kV underground cables that will serve for future power transmission between Saudi Arabia and Egypt.

Effect of hydrogen isotopic offset and input data on the isotope-based estimation of plant water sources

The stable isotope of water has been widely used to investigate plant water resources with the assumption that root water uptake and plant water transport is a non-isotopic fractionation process. However, recent research revealed that significant isotopic offsets between xylem water and potential water sources, which may result in errors when estimating plant water sources. We test five different input data modes in Bayesian isotope mixing model [only δ18O (M−O), only δD (M−D), δD after subtracting the deviation with respect to the soil water line (SW-excess) from the δD of xylem samples (M−SD), δD and δ18O (M−OD), and δD and δ18O after subtracting the SW-excess from the δD of xylem samples (M−OSD)] to identify sources of water absorbed by Chinese wolfberries (Lycium chinense Miller). The results showed that there was significant difference (p < 0.05) between the M−O and M−D modes. The evaluation indexes (RESE, N, MaxE, MinE, MAPE) performed well in the M−SD, M−O, and M−OSD modes. Furthermore, the M−SD, M−OSD, and M−O had consistent contribution proportions for the three soil layers. In addition, the corrected δD values in the dual and single isotope modes performed better than the original δD in quantifying water source contribution. This study provides critical insights into choosing a suitable method for isotope-based identification of plant water sources.

Maps of Soil Organic Carbon Sequestration Potential in the Russian Croplands

Adoption of the farming systems that aim to sequester carbon in agricultural soils is one of the ways to mitigate global climate change. This study focuses on the estimation of organic carbon sequestration potential of the Russian croplands in the upper (0–30 cm) soil layer by creating a set of maps using the data from global and national databases as the input data. The maps are generated within the FAO Global Soil Organic Carbon Sequestration Potential Map (GSOCseq) project according to the unified methodology using the RothC model to predict the rate of carbon sequestration in 2020–2040 under a business as usual scenario (BAU), as well as under sustainable soil management scenarios with additional different C input (+5, +10, and +20%) resulting from the use of sustainable soil management (SSM) scenarios. The total potential sequestration rate by the croplands of the Russian Federation in the 0–30-cm layer under a BAU scenario is assessed at 8.5 Mt/year and the estimate under SSM scenarios, up to 25.5 Mt/year. The carbon sequestration by the cropland of each soil ecological zone (except for the light chestnut (Eutric Cambisols (Protocalcic)) and brown semidesert (Luvic Calcisols) soils, where it is around zero) and on a national scale is positive. The Altai krai, Omsk oblast, Novosibirsk oblast, and Krasnoyarsk krai have the greatest potential for sequestration. Several subjects of the Russian Federation—Krasnodar krai, Republic of Crimea, Rostov oblast, Primorskii krai, Republic of Adygea, and Kaliningrad oblast—demand the adoption of sustainable management of soil resources.

Determining the number of soil layers using the surface wave method based on decision tree and random forest

The surface wave method is an efficient non-invasive technique to infer shear wave velocity profiles and has wide applications in civil engineering, earthquake engineering, and geophysics. Inversion analysis is a key step in this method. However, inferring the soil layer number is a challenging problem in inversion analysis and needs improvement. Machine-learning algorithms, including decision tree and random forest, are used in this study to infer the number of soil layers based on the dispersion curve of the surface wave. This process includes two steps for obtaining the model. In Step 1, a large set of synthetic dispersion curves is produced, and in Step 2, a model using machine-learning algorithms is trained based on the synthetic data. The analysis results showed that the obtained model could gain more than 75% accuracy in the test data. Comparing the results from the two machine learning models indicated that the random forest method produced a more favorable prediction. Furthermore, investigating the importance of features implied that the longest and shortest wavelengths were more important than other features.

Inverse modeling of frequency domain-based one-dimensional soil water flow in layered soils

Soils are heterogeneous at multiple scales. Estimates of spatially varying saturated hydraulic conductivity (Ks) of soils dictate the resolution of modeling water flux based on the Richardson-Richards equation (RRE), but direct measurements of Ks everywhere in a field are practically impossible. As a result, this study develops an inverse approach to estimate spatially varying Ks utilizing soil moisture observations driven by periodic weather variability at different frequencies. Using a numerical solution to vertical, one-dimensional RRE based on Gardner-Kozeny (GK) model in a heterogeneous soil with periodic flux, we investigate the spatial cross-correlation between Ks and observations (the amplitude or phase shift) of soil moisture fluctuation at different frequencies without high computational cost in the conventional time-domain model. These correlation patterns vary with the spatial location and frequency, suggesting that soil moisture fluctuations at different frequencies at one monitoring location carry non-redundant information about the heterogeneous distribution of Ks. Guided by cross-correlation maps, several inverse experiments reveal the effectiveness of multi-frequency data of soil moisture fluctuation for mapping the heterogeneous distribution of Ks. Monte Carlo simulations suggest that multi-frequency data can provide non-redundant and useful information about the estimation of heterogeneous Ks. Synthetic data based on a commonly-applied nonlinear van Genuchten-Mualem (VG) model is then tested in our inversion algorithm. The results indicate that the spatial pattern of the inverted GK Ks is very similar to that of the VG Ks, although these two parameters are inherently not identical since they are used in two different models. In addition, the inverted GK Ks can successfully predict the soil moisture fluctuation of frequencies that were not used in the inversion. Despite having no field experiments to validate this model, we believe this is the first attempt to conduct frequency-domain inverse modeling in vadose zone hydrology using soil moisture fluctuation.

LESSONS LEARNT FROM SOIL IMPROVEMENT CASE STUDIES

In Saudi Arabia two methods of soil improvement have been customarily employed. They are soil improvement by means of stone columns, and soil improvement by means of controlled modulus columns, that is CMC. Each of these methods have their own challenges to offer. Experience has shown that the sub-surface geology of the coastal areas of Saudi Arabia are marked with deep layers of poor soil termed locally as sabkha soil. Test results have determined that sabkha soil is known to have low shear strength, high soil compressibility, and high concentration of chlorides and sulphates which are corrosive to concrete, steel, and other construction materials. Design of foundations over a sabkha deposit remains a challenge and requires soil improvement. The CMC installation utilizes reverse flight augers, which displaces the soil laterally. However, it offers a huge challenge of post-operation trimming and cutting of CMCs. for stone columns, soil is removed during the drilling operation creating environmental issue. It also offers challenges as the huge impact during its operation are likely to damage the underground utilities. The environmental issues thus created can pose yet other challenge. This research paper is a case study that collates the experiences of soil improvement methods employed on a project in Saudi Arabia – vis-à-vis their advantages and the challenges encountered.

Semi-analytical solution for one-dimensional coupling consolidation of original soil and electro-osmotic layer using horizontal electrodes

The application of horizontal electro-kinetic geosynthetics for electro-osmotic consolidation is becoming increasingly widespread. Such horizontal electrodes are typically arranged at intervals, allowing pore water in original soil to pass through the intervals and penetrate into the electro-osmotic layer. In this study, a one-dimensional semi-analytical solution for a double-layered electro-osmotic system incorporating the original soil was presented and verified. The effects of the soil properties on the consolidation process were investigated. Results revealed that original soil can achieve a significant consolidation effect, even better than electro-osmotic dredged soil. A smaller permeability coefficient of original soil significantly prolongs the consolidation time, while a thicker original soil can improve the average consolidation effect of the two layers. The proposed model provides new electrode arrangement ideas and theoretical support for horizontal electro-kinetic geosynthetics for electro-osmotic reinforcement.

Design, construction, and monitored behavior of two large-diameter cylindrical diaphragm walls on an offshore reclamation island

Two semi-underground liquefied natural gas (LNG) storage tanks with an excavation depth of 25.6 m were constructed on an offshore reclamation island in Dapeng Bay, Shenzhen, China. Two cylindrical retaining diaphragm walls with a diameter of 100 m were adopted for the deep excavation. This paperpresents detailed information on the design and construction of these two cylindrical retaining diaphragm walls. As the elevation changes in the soil and rock layers were very severe, the non-axisymmetric distribution of the lateral pressure was significant. Diaphragm walls with different embedded depths were designed to cut off the seepage paths inside and outside the retaining structure. The strength of the rock was extremely high; therefore, a combination of predrilling using a rotary excavator and grooving using a milling machine was adopted in the trenching construction of the diaphragm wall. The monitored soil and rock pressures acting on the diaphragm wall are discussed. The lateral deformation of the diaphragm wall was described, and the hoop force and vertical bending moment of the retaining diaphragm wall were analyzed, which could be a reference for similar projects.