Sand Content Research Articles

Meta-analysis of Organic Carbon in Sandy Soil in Response to Amendment Application

Proper application of soil amendments can effectively increase the accumulation of soil organic carbon （SOC） in poor soils, thereby enhancing soil fertility level. The impacts of different types of amendments on the SOC content of sandy soils varies widely. Investigating the effects of various amendments on the SOC content of sandy soils and associated key controlling factors provides a scientific basis for formulating strategies to enhance the fertility of sandy soils. A data set was established with 617 pairs of data from 114 published studies that reported the effects of amendment application on SOC content of sandy soil during 1987 and 2023. Meta-analysis was used to quantitatively analyze the effects of amendment application on the SOC content of sandy soil globally under the conditions of various amendment types and application rates, climates, and soil properties. This study also investigated the major controlling factors for the changes in SOC in sandy soil after amendment application using regression analysis and random forest model. The research results showed that： ① Amendment application significantly increased SOC content by 61% on average in sandy soils and the application of inorganic amendment increased SOC in sandy soils （161%） to a significantly greater extent than that of organic amendment （37%） and compound amendment （54%）. ② The application amount and duration of inorganic amendments had no significant effect on the increase of SOC in sandy soil. Among the organic amendments, the increase of SOC in sandy soil was enhanced with the increase in the application amount of biomass carbon and organic fertilizer and decreased with the application duration of the amendment. ③ Climatic conditions, the amount and duration of amendments, and soil physicochemical properties combined explained 88% of the variability in SOC response in sandy soils. The magnitudes of SOC change due to amendment application significantly decreased with increased average annual temperature, initial SOC content, and soil pH, however, positively correlated with aridity, soil bulk density, and sand content. The application of amendments significantly increased SOC content in sandy soils. The type and application amounts of amendments, climatic conditions, and soil properties strongly regulated SOC in response to amendments. Therefore, the type and amounts of amendment, climate, and soil conditions should be comprehensively considered when applying amendments to effectively increase the organic carbon content and fertility level of sandy soils.

Health Risk Assessment of Heavy Metals in Soil-crop System in Different Ecological Regions of Ningxia

Heavy metals are characterized by toxicity，non-biodegradability，and accumulation in the food chain；hence，o the distribution of heavy metals in farmland soils and crop food safety have attracted much attention. A total of 1 274 soil samples and crop samples were collected from farmland in Ningxia from 2017 to 2021 and bioconcentration coefficients were used based on the analysis of the elemental contents of Zn，Cr，Ni，Cu，Pb，As，Cd，and Hg. The ecological risk index and correlation analysis were used to characterize the heavy metal content and health risk assessment of the soil-crop system in Ningxia. The results showed that the soils in the study area were alkaline and the mechanical composition was dominated by pulverized and sandy grains，with a relatively small content of clay grains. The heavy metal contents in the soils were in the following order：Zn>Cr>Ni>Cu>Pb>As>Cd> Hg. Except for that of Cu and Ni，the contents of other heavy metals in the soils of the northern region were higher than those of the central and southern regions. The ecological risk index of soil heavy metals was Hg>Cd>As>Cu>Pb>Ni>Cr>Zn and the proportion of points with low and medium ecological risk index levels was high（98.58%），indicating that the soil environment was generally good. The average content of the eight heavy metals in crops did not exceed the limit value，and the average health risk index value was <1. However， the health risk index（HRI）of As in individual crops existed at points >1 in all three sub-regions and individual points with high values of HRI（HRI>1）for Cu and Ni were observed in crops in the northern region and for Pb in the north and south of the country，which require further attention. From the bioconcentration factor，crops showed no accumulation effect （BCF<1）for heavy metals such as As，Cd，Cr，Cu，Ni，Pb，and Zn and although the average uptake of Hg by crops did not show accumulation，a total of 31 crops in the three ecological zones showed some accumulation（BCF>1），which also requires further monitoring. Analysis using the Mantel's test showed that except for As and Ni in crops，which had a weak correlation with Cu content in the soil（0.05>Mantel's P>0.01），the other heavy metals in crops did not have a significant correlation with the corresponding soil heavy metals （Mantel's P≥0.05），indicating that the heavy metal contents in crops were less affected by soil heavy metals. RDA analysis showed that the sand content had a strong positive correlation with the transfer coefficients of heavy metals such as Hg，Ni，Pb，and Cd，while the powder content showed a strong negative correlation；however，the transfer coefficients of Cu，Zn，As，and Cr were not much affected by the mechanical composition of soils，and the correlation between the soil organic matter content and the transfer coefficients of heavy metals was also small. In summary，the quality of the soil environment and crops in the study area is generally good；however，attention must still be paid to the areas with high heavy metal content or exceeding the standard value to strictly control the input of pollutants，and at the same time，establishing long-term monitoring of the quality status of soil and agricultural products in the crop production area is a necessary control initiative.

Simulation of sand and mud transport processes in currents and waves by time-dependent 2DV model

This paper presents a time-dependent, two-dimensional vertical model for the simulation of sand and mud concentrations, transport and bed level changes in tidal conditions with or without surface waves. The model solves the advection-diffusion equation for suspended sediment. The horizontal velocities and the sediment mixing coefficients are modelled as function of x, z and t. The settling velocity is constant or modelled as function of the sediment concentration. The sediment mixing coefficient over the water depth is described by flexible expressions based on current and wave parameters which can be modified easily in the input file. To represent mud flocculation and hindered settling processes, the settling velocity can be set as constant or concentration-dependent (input). The bed boundary condition is modelled as a bed concentration as function of the bed-shear stress. The model is valid for low and high sand and mud concentrations including fluid mud concentrations. The numerical SUSTIM2V-model is herein used to simulate sand and mud transport as measured in tidal waters. The model is also successfully used for simulation of high mud concentrations in the near-bed region as measured in the mouth of the Amazon River. The model has also been used to simulate scour along an offshore caisson-type foundation structure.

A Novel Heat Pulse Method in Determining “Effective” Thermal Properties in Frozen Soil

AbstractAccurate and fast measurements of thermal properties are frequently required for characterizing the heat‐water dynamics in frozen soil. Measuring the thermal properties of frozen soil without inducing ice thaw has proven challenging with conventional heat pulse (HP) methods. In this study, based on an Infinite Line Source (ILS) semi‐analytical model that applies a constant temperature lower than the freezing point at the heat source to prevent the initiation of ice thaw in the frozen soil, we propose a novel HP‐based approach to measure thermal properties, applicable at temperatures below or above 0°C. Laboratory experiments and numerical modeling were utilized to validate the applicability of the approach and optimization strategies of the measurement. We found that the proposed HP‐based approach effectively maintained the maximum spatial temperature below the freezing point and therefore estimated the bulk thermal properties of quartz sand and ice contents. An optimized measurement strategy was proposed to monitor the temperature variations 2–4 cm away from the center of the heat probe after 60 s. This progress can largely facilitate the determination of the thermal properties of multi‐phase and ‐component frozen soil such as thermal conductivity, heat flux, and ice content in cold areas across soil science, hydrology, engineering, and climate science.

Relationship between soil structure and hydrological properties of the active layer in the permafrost region of the Qinghai–Tibet Plateau based on fractal theory

Soil structure and hydrological properties influence ecosystem stability and hydrological cycles. Fractal theory has been widely used in the quantitative analysis of soil particle-size distribution (PSD), aggregate and pore distribution, and evaluation of soil degradation, desertification, and wind erosion. However, the complex relationships between soil physiochemical properties and soil hydrological processes based on fractal theory have not been thoroughly investigated. This study focused on the correlation among soil structure, physicochemical properties, and hydrological properties in the active layers of various soil types and vegetation coverages in the permafrost region of the Qinghai–Tibet Plateau (QTP) using the principles of fractal theory. The results showed that the fractal dimension of soil PSD (DPSD) in the active layer of the QTP was predominantly within the range of 2.13–2.70, which is notably smaller than the fractal dimension of the soil water retention curve (DWRC: 2.72–2.93). With decreased vegetation coverage, the alpine soil particles exhibit gradual fineness, increasing the DPSD. Soil physicochemical properties were affected by the interactions among internal factors and the external environment, such as geographical locations, slope orientations, vegetation coverages, and soil freeze–thaw cycles. The results of correlation analysis indicated that the fractal dimension of PSD and the soil water retention curve (WRC) were significantly correlated with soil textural, physicochemical, and hydraulic properties, particularly in clay, silt, and very fine sand content. Finally, a fractal model of WRC in the permafrost region was established based on DPSD and WRC parameters of the Gardner and van Genuchten models. The study provides an improved perspective for revealing the transport process and influencing mechanism of soil water and salt in the active layer of the QTP and a more accurate prediction of soil physiochemical and hydrological properties for climate warming and wetting.

Influence of climatic variables on biome transitions in the COLOMBIAN and PANAMANIAN Caribbean region

Disentangling the environmental determinants of tropical biomes is crucial for understanding their response to climate change. This study investigated the effect of climate and soil-related variables on biome transitions in the Caribbean region of Colombia and Panama, focusing on xerophytic forest (XF), tropical dry forest (TDF), and tropical rainforest (TRF). We analyzed the climatic variables at different time scales (daily, seasonal, and annual) and their interaction with soil properties. We performed an ordinal logistic regression to assess the combined effect of the most important variables in biome transitions. Our results showed that climate variables are major discriminators in our study region, particularly precipitation at a seasonal and annual scale. The ordinal logistic regression highlighted the significance of annual precipitation and dry-season length in biome transitions, with maximum temperature impacting TDF-TRF transitions. Soil differences, although present (e.g., higher sand content in XF), played a marginal role. Overall, our findings emphasize the dominance of climate over soil in shaping tropical biome distributions in the northern Caribbean part of South America. These findings contribute to a deeper understanding of tropical biome responses to climate change.

Biotic and abiotic drivers of seedling density in Polylepis rugulosa forests across east- and west-facing slopes in the Peruvian Andes

ABSTRACT Background Polylepis forests are highly endangered tropical high Andean ecosystems. P. rugulosa has had the most significant decrease in spatial distribution compared to other Polylepis species and requires adequate restoration measures. Aims This study evaluated the relationship between P. rugulosa seedling density and biotic and abiotic factors across east- and west-facing slopes to identify optimum conditions for the regeneration and restoration of the species. Methods We assessed structural, edaphic, and topographic variables in 58 plots of 600 m2, microsite characteristics in 204 quadrats of 1 m2 and related them observed to P. rugulosa seedling density. Results The density and basal area of P. rugulosa adults were higher on west-facing slopes than on east-facing slopes. On both aspects, seedling density was positively related to the height and basal area of the adult trees and negatively related to sand content and the cover of ground vegetation (shrubs and herbs). Seedling density on east-facing slopes was positively related to soil organic matter content, and it was negatively related to it on west-facing slopes. Regarding microsite characteristics, the height of the nearest adult tree and litter cover were positively related to seedling density. Conclusions Restoration of P. rugulosa should consider the contrasting effects of abiotic and biotic factors on seedling density on east- vs. west-facing slopes to optimise the recruitment and growth.

Review of Analytical Studies on The Failure of Granular Anchor Piles in Expansive Soil

Abstract: Soft ground, characterized by a high content of clay, silt, peat, and loose sand, is generally unsuitable for constructing large structures due to insufficient stability. Ground improvement techniques, such as the use of stone columns (or granular piles), are often implemented in these areas to enhance load-bearing capacity and minimize settlement. The Granular Anchor Pile (GAP) is an advanced version of the stone column that includes an anchor to boost its tensile load-bearing or pullout capacity. In this study, formulations from various authors regarding the pullout capacity of anchors embedded in clayey soils are analyzed to assess the contributions of pile failure and anchor failure to overall GAP failure. The results indicate that GAP failure occurs due to two main factors: 50%–65% of the anchor length failing, and 35%–50% of the pile length failing. This breakdown helps in understanding the role of each component in the overall pullout capacity of GAP

Factors governing crusting formation in soils in Southern Mali, West Africa: Evaluation of susceptibility indices

In Southern Mali and neighboring semi-arid Sahel regions, soil crusting and sealing are common and significant phenomena for people who depend on agriculture for their livelihoods. These processes form hard, impermeable layers on the soil surface, reducing water infiltration, increasing runoff and erosion, and hindering germination, seedling emergence, and productivity. Factors such as rainfall intensity, topography, soil attributes, and poor management practices contribute to these phenomena. Here, we aimed to analyze soil attributes affecting crust formation and evaluate them using indicators like the structural stability index (StI), particle separability index (PSI), and crusting susceptibility index (CSI). Soils samples from agricultural and native areas in Southern Mali were analyzed for physical, chemical, mineralogical, and micromorphological attributes. Results revealed that the soils in these regions have high silt and fine sand content and low organic carbon content. Poor soil management, leading to prolonged periods of bare soils, significantly contributes to crusting. Kaolinitic clays, Ca2+ and Mg2+ contents did not appear to affect crusting. The PSI revealed a high risk of aggregate disruption in both agricultural and native lands, demonstrating soil vulnerability to degradation. The StI showed limited risk of structural degradation in native lands, while agricultural soils were more susceptible to crusting. The CSI indicated moderate crusting susceptibility across the regions. By examining the three indices related to texture attributes and organic carbon, this study provides insights into estimating susceptibility to crusting through the evaluation of the risk of soil structural degradation, particle separation, and overall soil susceptibility to surface crusting, all of which underscore the need for improved soil attributes. It emphasizes the importance of implementing effective soil management strategies, particularly the adoption of cover crops, to enhance organic carbon content and increase vegetation cover. These measures are essential for improving soil health and minimizing the risk of crusting.

Quantitative relationships between Munsell colour attributes and organic carbon in highly weathered tropical soils

Soil organic carbon (SOC) is a very important parameter for assessing the quality of agricultural soils. However, the availability and use of such data by resource-poor farmers, especially in Sub-Saharan Africa, remains a major challenge due to the financial and time constrains involved. Thus, there is need to assess and adopt reliable methods for the rapid estimation of soil organic carbon content by indigenous farmers and field users. The objective of this study was to evaluate the quantitative relationships between soil organic carbon and Munsell colour attributes (value and chroma) in highly weathered tropical soils of the Northwestern Highlands of Cameroon. Forty-six soil profiles (28 Acrisols and 18 Ferralsols), including 46 surface (A) horizons and 181 subsurface horizons (Bo, Bt) were used. Soil organic carbon data and Munsell colour attributes, obtained through standard procedures, were subjected to descriptive statistical, correlation, regression and principal components analyses, in order to evaluate the relationships existing between SOC and Munsell colour attributes. In general, there were negative and significant (p < 0.001) correlations between SOC and all Munsell colour attributes (chroma, value, value + chroma, and value +0.5 chroma). The best models relating SOC and Munsell colour attributes were logarithmic models, with soil colour explaining >70 % of the variance. The results indicate that SOC in highly weathered tropical soils can be conveniently estimated using Munsell soil colour attributes (value + chroma). Better estimates were obtained using logarithmic models for surface (A horizon) soil samples having a sand content >50 %.

Mapping the exposure to outdoor radon in the German population

IntroductionData on outdoor radon are generally scarce compared to indoor radon. However, knowledge of the spatial distribution of outdoor radon is necessary to estimate the overall exposure of the population to radon, it supports the prediction of indoor radon and characterizes the natural radon background. Germany has a comprehensive dataset on long-term outdoor radon concentration and the equilibrium factor at national level, which allowed to produce what is probably the only spatially continuous outdoor radon map at national level so far. DataIn this study, outdoor radon concentration measurement data (n = 172) and equilibrium factors (n = 25) from a national survey from 2003 to 2006 were reanalyzed using state-of-the-art machine learning routines. Spatially comprehensive maps of distance to the sea, radon concentration in soil, sand content in topsoil and a terrain-based wind exposure index are used as predictors. MethodsQuantile regression forest was used to map the conditional distribution of outdoor radon concentration at 500 m grid resolution. The equilibrium factor was mapped using a linear regression model. Both maps were combined to derive the equivalent outdoor radon equilibrium concentration. Population weighting of the results was achieved by explicitly accounting for the population distribution using a probabilistic sampling procedure from the estimated conditional distributions. ResultsThe arithmetic mean and the interquartile range (25th to 75th percentile) for the population-weighted outdoor radon concentration for Germany are 9.3 Bq/m³ and 5.8 Bq/m³ to 11.2 Bq/m³, respectively. The mean equilibrium factor is 0.49. The arithmetic mean and the interquartile range (25th to 75th percentile) for the population-weighted outdoor radon equilibrium equivalent concentration are 4.7 Bq/m³ and 2.7 Bq/m³ to 5.9 Bq/m³ respectively. The estimated inhalation dose due to outdoor exposure to radon is 0.056 mSv/a (arithmetic mean), with less than 10 % of the population exceeding a value of 0.1 mSv/a. The unavoidable inhalation dose due to radon exposure (outdoors plus indoors) in Germany is estimated at an arithmetic mean of 0.37 mSv/a. The spatial distribution of radon outdoors is mainly determined by the distance to the sea. The predictors radon concentration in soil, sand in topsoil and wind exposure still have a significant influence, especially at local to regional level. ConclusionKnowledge about the spatial distribution of outdoor radon and its local variability for Germany was improved using a modern regression technique and relevant predictive information. The results confirm a low outdoor radon concentration with a small contribution to the effective dose received by the population from outdoor radon exposure.

Spatial distribution pattern of soil organic matter in the wind erosion region of northeastern China based on the cokriging method

Soil wind erosion triggers complex particle migration from the source to downwind regions. During this process, soil organic matter (SOM), primarily adsorbed onto particle surfaces, exhibits distinct spatial differentiation across affected areas. Knowledge about the spatial distribution of SOM and its impact factors in wind erosion regions is essential for a deep understanding of global carbon cycling. In the wind erosion region of northeastern China, a crucial base for livestock and commercial grain production, profound changes in land quality driven by climate change and human activities have intricately altered SOM spatial patterns. However, detailed studies on the spatial variability of surface SOM in this region remain scarce. A total of 374 surface soil samples from this region were analyzed for SOM and soil pH. Combined with spatial data sets including particle-size distribution, soil moisture (SM), air temperature (T), and the normalized difference vegetation index (NDVI), the regional spatial distribution patterns of SOM were revealed and mapped using the ordinary kriging (OK) and cokriging (CK) approaches. The results indicated strong variations of SOM in space, with corresponding coefficients of variation exceeding 35 % across the entire region and each land use. According to the semivariogram analysis, SOM demonstrates moderate spatial dependency in the study region, exhibiting spatially positive correlations with clay content (CLAY), SM, and NDVI, and negative correlations with pH, soil sand content (SAND), and T. Among the various impact factors, incorporating SAND as an auxiliary variable in CK interpolation achieved the greatest improvement in the accuracy of SOM spatial distribution simulation compared to the OK model, increasing the explained variance from 35 % to 75 %. This simulation showed a general downward trend of SOM from the northeast to the southwest of the study region, with 65.24 % of the area displaying SOM ranging from 10-30 g·kg−1. The values of SOM greater than 30 g·kg−1, comprising 19.43 % of the total region, were primarily located in the humid and semi-humid meadow steppes and forests. In contrast, areas with SOM below 10 g·kg−1 accounted for only 15.33 %, mainly situated in the arid desert steppe and the Horqin sandy lands. These findings provide a scientific basis for understanding regional SOM loss and developing efficient measures for sand prevention and control.

The influence of soil properties on essential oil components of Hypericum perforatum L. growing in Turkey

Hypericum perforatum L. is a medicinally and commercially important plant with a long history of traditional use. It is used for conditions such as depression, wound healing, ulcers, and the common cold. The medicinal properties of H. perforatum are primarily attributed to its essential oil (EO). Various soil conditions, such as pH, soil texture (sand, silt, and clay content), nutrient content (potassium, magnesium, calcium, sodium, iron, copper, zinc, and manganese), and organic matter, can influence the composition and concentration of EO in plants. In this study, these conditions were investigated aiming to understand the influence of soil’s physical and chemical properties on the EOs extracted from H. perforatum collected from various localities. Dried aerial parts of H. perforatum from 20 different locations in Eskişehir, Turkey, were hydrodistilled using a Clevenger-type apparatus. The EO components were analyzed using GC-FID and GC-MS systems. Soil samples were collected from the same 20 local habitats and subjected to physical and chemical analyses. The results were then correlated with the main EO components. GC-MS results identified 119 compounds, representing 71-96.6% of the volatiles in all samples. The findings revealed that specific soil parameters, including Mg, Ca, dust, lime, clay, and pH, had a significant impact on the yield and chemical composition of H. perforatum EO, particularly affecting the levels of α-pinene, caryophyllene oxide, 1-dodecanol, and 1-tetradecanol. Further research is needed to fine-tune these soil parameters in conjunction with other ecological factors to maximize the qualitative and quantitative yield of EO from H. perforatum.

Geotechnical response of Strip footing resting on oil-contaminated sand improved with stone columns: numerical study

Ground improvement techniques are frequently employed in construction sites characterized by weak soil conditions that may result in suboptimal performance. The use of ordinary and encased stone columns aims to enhance endurance, shear strength, and soil hardness, thereby mitigating settlement issues and expediting the consolidation of contaminated sand soils. In this research, a comprehensive investigation involving 74 cases was conducted to assess the behavior of both ordinary stone columns and encased stone columns under strip footing in contaminated sand subgrade. The objective was to discern the impact and characteristics of encapsulation in comparison to encapsulated stone columns, employing a Finite Element Model (FEM) within the PLAXIS 3D software package. The study focused on stone columns with two different diameters (D = 0.5 m and 0.6 m), while the column length was 12 m across all cases. As the contamination level increases—at the variable contaminated sand levels of (2%, 5%, and 10%)—the viscosity of the soil rises, leading to a reduction in cohesion between soil granules. Consequently, the internal friction angle decreases, with values diminishing from 31° to 27° and then to 24°, respectively. The clean sand was placed to achieve relative density, a medium dense sand state (Dr = 50%). The two categories of stone columns examined were ordinary stone columns (OSC) without encapsulation and encased stone columns (ESC) encapsulated with varying degrees of hardening. Results obtained at variable internal friction angles (35, 40, and 45 degrees) revealed a notable increase in the endurance of ordinary stone columns on untreated soil conditions, reaching 100%, 125%, and 148% for column diameters (D = 0.5 m) and 130%, 145%, and 180% for column diameters (D = 0.6 m), respectively. The corresponding increase in the endurance of encased stone columns under untreated soil conditions was found to be 275%, 33%, and 345% for column diameters (D = 0.5 m) and reached 313%, 350%, and 375% for column diameters (D = 0.6 m), respectively. All preceding results were obtained under the condition of a contaminated sand content of 5%. The investigation aimed to provide valuable insights into the performance and efficacy of ordinary stone columns (OSC) and encased stone columns (ESC) as a geotechnical solution for improving soil conditions in construction projects.

Heavy metals in core sediments from the western Bay of Bengal: implications on historical pollution, eco-environmental risks, and potential sources

The western Bay of Bengal is particularly susceptible to the harmful impacts of increasing coastal pollution, as coastal population and urban development are occurring at unprecedented rates. The rapid urbanization and industrialization along the east coast of India coupled with the transfer of contaminants into the Bay of Bengal through riverine systems, causing a direct impact on marine ecosystems. In the present study, an attempt has been made to understand the heavy metal distribution on shelf sediments in the western part of the Bay of Bengal to infer their source, processes, and historical changes in marine pollution. Three short sediment core samples were collected and analysed for sediment texture, organic matter, and heavy metals. Cores 1 and 2 contain a high amount of sand content, representing shallow marine with moderate to high-energy conditions, and were deposited at a recent time. Core 3 was dominated by muddy sand to sandy mud, which denotes calm sedimentation without any turbulence, and these sediments were deposited under relatively low-energy conditions. The higher concentration of organic matter in the top layers of the core indicates both marine and terrestrial input. The heavy metal contents show quite heterogeneous and variable distributions from one element to another and from one core to another. The calculated pollution indices such as Contamination Factor (CF), and Geoaccumulation Index (Igeo) and Pollution Load Index (PLI) values indicate that all the core sub-samples are severely enriched and highly polluted by Cd and moderately polluted by Pb. The increased heavy metal concentration in the upper portion of the sediment cores and moderate to considerable ecological risks indicate that these metals have been deposited in the study area for the past few decades.

Identification of Key Soil Quality Indicators for Predicting Mean Annual Increment in Pinus patula Forest Plantations in Tanzania

There is an unexplored knowledge gap regarding the relationship between soil quality and mean annual increment (MAI) in forest plantations in Tanzania. Therefore, this study aimed to identify soil quality indicators and their impact on the mean annual increment (MAI) of Pinus patula at Sao Hill (SHFP) and Shume forest plantations (SFP) in Tanzania. The forests were stratified into four site classes based on management records. Tree growth data were collected from 3 quadrat plots at each site, resulting in 12 plots in each plantation, while soil samples were taken from 0 to 40 cm soil depth. Analysis of variance examined the variation in soil quality indicators between site classes at two P. patula plantation sites. Covariance analysis assessed the differences in MAI and stand variables across various site classes, taking into account the differing ages of some stands, with stand age serving as a covariate. Linear regression models explored the relationship between soil quality indicators and MAI, while partial least squares regression predicted MAI using soil quality indicators. The results showed that, at SHFP, sand, organic carbon (OC), cation exchange capacity, calcium (Ca), magnesium (Mg), and available P varied significantly between site classes, while silt, clay, and available P varied significantly at SFP. At SHFP, sand and clay content were positively correlated with MAI, while at SFP, silt content, available P (Avail P), potassium (K), Ca, and Mg showed significant positive correlations. Soil quality indicators, including physical and chemical properties (porosity, clay percentages, sand content, and OC) and only chemical (K, Mg, Avail P, and soil pH) properties were better predictors of the forest mean annual increment at SHFP and SFP, respectively. This study underscores the importance of monitoring the quality of soils in enhancing MAI and developing soil management strategies for long-term sustainability in forests production.

Reconstruction of unstable atmospheric surface layer streamwise turbulence based on multi-layer perceptron neural network architecture

The accurate simulation of sand-laden turbulence under different stratification stabilities remains a critical challenge in turbulence research. This study presents an innovative approach to reconstructing streamwise turbulence in an unstable atmospheric surface layer (ASL) using a multi-layer perceptron (MLP) neural network architecture. Leveraging high-resolution measurements of three-dimensional wind velocity and temperature from multiple observational sites, the study develops prediction models for streamwise wind velocity at varying heights in the unstable ASL. The predictive model integrates large-scale motions (LSMs) generated by the MLP, small-scale motions (SSMs) derived from the Kaimal spectrum, and mean wind velocity, providing a comprehensive representation of turbulence. The impact of sand content and stratification stability on model performance is analyzed, with discussion highlighting the model's strengths and limitations under weak instability conditions. Validation is conducted through cross-site comparison, statistical analysis, and power spectrum assessment, demonstrating the model's ability to capture the temporal and spectral characteristics of wind velocity in sand-laden, unstable ASL conditions. The study also reveals that, under weak instability, shear forces dominate the formation of coherent structures, while buoyancy effects enhance vertical mixing as instability increases. Compared to existing models, the proposed prediction model is applicable over a broader range of conditions, offering a valuable data source for the study of atmospheric sand-laden turbulence and serving as a reference for practical sand control projects.

Numerical investigation on erosion characteristics of elevated pile cap in high concentration sediment flow environment

The objective of this investigation is to study the erosion process and characteristics of elevated pile cap in high concentration sediment flow environment, taking into account the influence of multiple factors. Firstly, a three-dimensional model of elevated pile cap was established and used for numerical simulation of erosion. Subsequently, the validity of the elevated pile cap erosion numerical model was corroborated through a comparison with the results of existing physical model tests. Finally, the influence of hydrological conditions, structure geometric characteristics, and material properties on the erosion characteristics of the elevated pile cap were investigated. The numerical results demonstrate that the sand content, flow velocity and pile longitudinal clearance diameter ratio are positively correlated with the abrasion thickness and erosion rate of the elevated pile cap. The pile diameter, the pile transverse clearance diameter ratio, and the compressive strength have a negative correlation with the abrasive thickness and erosion rate of the elevated pile cap. When the particle diameter increases from 0.2 to 2.0 mm, the erosion rate of the pile foundation first decreases and then increases. If the bearing platform is not fully submerged, the erosion rate of the elevated pile cap decreases with the increase of water depth. As the water gradually submerges the bearing platform, the erosion rate of the pile foundation increases with the increase of water depth. And with the change of impact angle, the shielding effect of the front pile on the back pile will also change, which has a great influence on the downstream piles erosion. This study not only enriches existing erosion theories but also guides erosion protection of the elevated pile cap.

An interpretable (explainable) model based on machine learning and SHAP interpretation technique for mapping wind erosion hazard.

Soil erosion by wind poses a significant threat to various regions across the globe, such as drylands in the Middle East and Iran. Wind erosion hazard maps can assist in identifying the regions of highest wind erosion risk and are a valuable tool for the mitigation of its destructive consequences. This study aims to map wind erosion hazards by developing an interpretable (explainable) model based on machine learning (ML) and Shapley additive exPlanation (SHAP) interpretation techniques. Four ML models, namely random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB), and quadratic discriminant analysis (QDA) were used. Thirteen features associated with wind erosion were mapped spatially and then subjected to a multivariate adaptive regression spline (MARS) feature selection algorithm, and then, tolerance coefficient (TC) and variance inflation factor (VIF) statistical tests were used to explore multicollinearity among the variables. MARS analysis shows that eight features consisting of elevation (or DEM), soil bulk density, precipitation, aspect, slope, soil sand content, vegetation cover (or NDVI), and lithology were the most effective for wind erosion, while no collinearity existed among these variables. The ML models were used for ranking the effective features, and the research introduces the application of an interpretable ML model for the interpretation of predictive model's output. The ranking of effective features by RF-as the most typical ML model-revealed that elevation and soil bulk density were the two most important features. According to the area under the receiver operating characteristic curve (AUROC) (with a value > 90%) and precision-recall (PR) (with a value > 90%) curves, all four ML models performed with great accuracy. According to the PR curve, the SVM model performed slightly better than others, and its results revealed that 20.9%, 23%, and 16.6% of the total area in Hormozgan Province is characterized by moderate, high, and very high hazard classes to wind erosion, respectively. SHAP revealed that soil sand content and elevation are the most important variables contributing to the predictive model output. Overall, our research is one of the pioneering applications of interpretable ML models in mapping wind erosion hazards in Southern Iran. We recommend that future research should address the aspect of interpretability in order to better understand predictive model outputs.

Relationship Between Salt Accumulation and Soil Structure Fractals in Cotton Fields in an Arid Inland Basin

The relationship between soil structure and salt accumulation is unclear; thus, experiments on salt accumulation under different soil structures were conducted in cotton fields in arid areas of northwest China. Thirty-nine sets of soil samples were collected from the 0 to 180 cm profile of three experimental areas. The total salt content of the soil extracts and the particle size distribution of the soil samples were determined using a JENCO TDS and a laser particle size analyzer, respectively, and the fractal dimension of the soil structure was obtained using fractal theory. Pearson’s correlation analysis and Tukey’s test (p &lt; 0.01) were used to analyze the correlation between soil salinity, soil particle size distribution, and fractal dimensions in the three profiles. The results showed soil salinity accumulation was affected mutually by soil texture and soil structure, and soil salinity tended to accumulate in fine-grained soil. The soil fractal dimension (D) could indicate soil texture and quantify soil salinity content. When the sand content was more than 50%, there was a significant positive correlation between the soil fractal dimension and soil salinity (correlation coefficient R = 0.943). The results provide valuable insights into cotton production in arid areas.