Soil Model Research Articles

Investigating soil erosion vulnerable zones based on clustered geoinformatics approach: a case study of Tyume River Catchment, Eastern Cape, South Africa

Rigorous field surveys, environmental specificity, and data paucity hamper detailed soil erosion assessments, model selection, ecological monitoring, and prioritization against soil erosion. To address this in a topographically complex environment, the present study presents a novel selection of physiographic factors integrated geospatially with the land use/cover and geology data to prioritize the soil erosion vulnerable areas within a watershed, using Tyume River Catchment, Eastern Cape, South Africa as a case study. A quantitative morphometric analysis involving parameters such as the drainage density, topographic wetness index, terrain ruggedness index, topographic position index, and vector roughness measure was computed using a digital elevation model based on their inference of watershed's morphogenetic response to anthropic factors and pluviometric processes. Based on expert judgment for thematic ranking and weightage, the soil erosion prioritization area map was generated through weighted overlay analysis of the morphometric parameters with land use land cover and surficial lithology themes. The results depicted a catchment-scale soil erosion vulnerability map, classified into very high (40 km2), high (135 km2), medium (209 km2), low (186 km2), and non-vulnerable (113 km2) zones. Using Google Earth image analyses through the coefficient of determination (R2 = 0.563) and Receiver Operating Characteristics Curve (AUC = 0.899), the model corroboration indicated that the soil erosion vulnerability assessment is reliable and highly predictive. The study identified free-range animal operation and hillslope overgrazing, especially in riparian zones, as the environmental practices aggravate the catchment's terrain susceptibility to soil erosion. The assessment showed that some of the selected morphometric parameters could be used to improve the validated soil erosion models in mountainous regions. Due to the high precision of the engaged approach and the identified environmental concerns, the method can be adopted in similar environments.

Study of the Shear Strength Model of Unsaturated Soil in the Benggang Area of Southern China

Benggangs are a unique type of soil erosion commonly found in southern China, with the gully wall being the most dynamic component of the Benggang system and is crucial for assessing its overall progression. The unsaturated shear strength of soil in Benggang areas is a key factor influencing the stability of the gully wall. However, quantitative analyses of the unsaturated shear strength in the gully walls of Benggangs remain limited. In this study, the soil–water characteristic curves (SWCC) and shear strengths of undisturbed soil samples from four different soil layers in the gully wall of Benggang were measured using a pressure membrane meter and a quadruple direct shear apparatus. The results revealed that the water holding capacity of the soil decreased gradually with increasing matrix suction, and the order of the water holding capacity was the sandy soil layer > transition layer > laterite layer > clastic layer. With an increasing soil water content (SWC), the shear strength, cohesion (c), and internal friction angle (φ) of the four soil layers decreased significantly, and the φ showed a power function decreasing curve (p < 0.05), whereas c in the laterite layer and transition layer exhibited a power function decreasing curve (p < 0.01). The c of the sandy soil layer and clastic layer decreased linearly and logarithmically (p < 0.01) with increasing SWC, respectively. The unsaturated shear strength model for the four soil layers was developed based on the Vanapalli model. The root mean square error (RMSE) of the simulated and measured values was less than 29.349, while the Nash–Sutcliffe efficiency (NSE) and R2 values were greater than 0.638 and 0.788, respectively. The model can be used to analyze and predict the unsaturated shear strength in different layers of Benggang gully walls, providing a theoretical foundation for studying the erosion mechanisms of Benggangs.

A Thermomechanical Coupled Model for Unsaturated Soils

A Thermomechanical Coupled Model for Unsaturated Soils

Potentially mineralizable nitrogen: Estimation of the labile and stabilized pools under woodland and cultivated soils in Mexico

Objective: The aim of this work was to evaluate nitrogen pool and its variation due to land uses in different soil orders. Design/methodology/approach: Alfisols, Entisols and Inceptisols under different uses (woodland and cultivated soils) were incubated for 20 weeks under controlled temperature and humidity. The mineralizable N (NO3--N and NH4+-N) was obtained and the potentially mineralizable nitrogen (N0) was estimated by the method of iterative adjustment. Nitrogen from 0 to 5 weeks was considered as labile nitrogen, and from 5 to 20 weeks was the stabilized nitrogen. The labile nitrogen was described by a potential model, while the stabilized nitrogen was described by a logistic model. The labile nitrogen and stabilized nitrogen pools were estimated after obtaining the first derivate and solving the integral of the potentially mineralizable nitrogen equation. Results: The greatest estimated amounts of labile and stabilized nitrogen were detected in an Alfisol under woodland use, and the minimum values were obtained in an Entisol under agricultural use. Similar results were obtained for the estimated amount of labile and stabilized nitrogen pool. Limitations on study/implications: It is important to measure the labile and stabilized fraction of nitrogen, which requires long-term incubations to obtain models of soil N pools, so other methods realiable and faster need to be considered. Findings/conclusions: The potentially mineralizable nitrogen was positively related to the different fractions of labile and stabilized nitrogen under the different land uses.

Uncovering soil compaction: performance of electrical and electromagnetic geophysical methods

Abstract. Monitoring soil structure is of paramount importance due to its key role in the critical zone as the foundation of terrestrial life. Variations in the arrangement of soil components significantly influence its hydro-mechanical properties and therefore its impact on the surrounding ecosystem. In this context, soil compaction resulting from inappropriate agricultural practices not only affects soil ecological functions, but also decreases the water-use efficiency of plants by reducing porosity and increasing water loss through superficial runoff and enhanced evaporation. In this study, we compared the ability of electric and electromagnetic geophysical methods, i.e., electrical resistivity tomography (ERT) and frequency-domain electromagnetic (FDEM) method, to assess the effects caused by both heavy plastic soil deformations generated by a super-heavy vehicle and the more common tractor tramlines on silty-loam soils. We then tested correlations between geophysical response and soil variables (i.e., penetration resistance, bulk density, and volumetric water content on collected samples) at different homogeneous areas defined by k-means clustering. This work is intended to be a contribution to clarify expectations about the use of geophysical techniques to rapidly investigate soil compaction at various spatial scales, dissecting their suitability and limitations. It also aims to contribute to the methodological optimization of agrogeophysical acquisitions and data processing in order to obtain accurate soil models through a non-invasive approach. Electrical prospecting has finer spatial resolution and allows a tomographic approach, requiring higher logistic demands and the need for ground galvanic contact. On the other hand, contactless electromagnetic induction methods can be quickly used to define the distribution of electrical conductivity in the shallow subsoil in an easier way. In general, compacted soil portions are imaged as high-electrical-conductivity anomalies relative to the context. Results, validated with traditional soil characterization, show the pros and cons of both techniques and how differences in their spatial resolution heavily influence the ability to characterize compacted areas with good confidence.

Elasto-plastic solution for undrained cylindrical cavity expansion in refuse soil

To address geotechnical engineering issues such as pile driving, lateral pressure tests, and static cone penetration tests on increasing number of infrastructure projects being constructed on landfills, an elasto-plastic theoretical solution for the undrained cylindrical cavity expansion in refuse soil is proposed in this paper based on an elasto-plastic constitutive model for refuse soil considering the reinforcement effect of fibers, along with a large deformation theory. The correctness of the results is validated through comparison with existing solutions based on the modified Cam-clay model. The results indicate that the response of columnar pore expansion in refuse soil is significantly different from that in ordinary soil. Near the pore, refuse soil does not enter a critical state, only the slurry-like components do. Subsequently, the reinforcement effect of the fiber material begins to manifest. Refuse soils with different fiber contents undergo both elastic and plastic stages before reaching the critical state line of the slurry-like components in the soil. They then move a certain distance along this line to reach a maximum. Given the rarity of engineering construction on similar sites in the past, the unique response of refuse soil during cylindrical cavity expansion should be given special attention.

Enhancing Discrete Element Model Accuracy for Lunar Soil: Calibration and Validation of Mesoscopic Parameters

To enhance the precision of the discrete element model for lunar soil-tool simulation work, this paper introduces a novel discrete element model of lunar soil incorporating particle shape and the van der Waals forces between particles. The effect of mesoscopic parameters on peak stress and failure point are systematically calibrated in the model by triaxial compression stress-strain curves. The results show that six meso-parameters have significant impact on the mechanical response of the model, including effective modulus, rolling friction coefficient, normal-to-shear stiffness ratio, damping coefficient, maximum attractive force and attraction range. The model accurately simulates complex mechanical behavior in both loose, dense lunar soils and soil-tool interaction. This study lays a foundation for future lunar soil-anchor interaction simulation and the interpretation of lunar soil mechanical parameters.

A thermo-mechanical model for saturated and unsaturated soil–structure interfaces

Shear behaviour of soil–structure interfaces greatly affects the performance of geotechnical structures. The soil–structure interfaces in geothermal structures (e.g., energy pile and energy wall) are often subjected to varying temperature and suction conditions. However, there is no constitutive model to simulate the coupled effects of suction and temperature on the shear behaviour of soil–structure interfaces. In this study, a thermo-mechanical model was newly developed based on the bounding surface plasticity framework to predict the thermo-mechanical behaviour of saturated and unsaturated interfaces. A power function was used to calculate the degree of saturation at the interface and improve the evaluation of suction effects on interface shear strength. A linear relationship between temperature and interface critical state friction angle was proposed to incorporate thermal effects. New equations were also proposed to describe the critical state lines (CSLs) in the void ratio versus stress plane ( e-[Formula: see text]) and to model the shearing-induced deformation at various temperatures and suctions. The experimental data from different interfaces in the literature were used to evaluate the model capability. Comparisons between measured and computed results suggest that this model can well capture the coupled effects of temperature, suction, and net normal stress on the shear behaviour of interfaces.

A novel thermodynamic constitutive model of coarse-grained soils considering the particle breakage

A novel thermodynamic constitutive model of coarse-grained soils considering the particle breakage

Stream flow modeling using SWAT model and performance evaluation in Adhaim watershed

https://ejuow.uowasit.edu.iq Understanding the hydrological cycle and finding data crucial for water management require a foundational understanding of basin-scale simulation. To create the most accurate stream flow modeling possible, data from the weather stations was combined with input from other maps of the research area, such as soil, land cover, land use (LCLU), and digital elevation model (DEM). Regarding Adhaim Watershed, period 2000 to 2013SWAT model calibration was done using the Sequential Uncertainty Fitting (SUFI–2) technique and the Nash–Sutcliffe simulation efficiency (NSE) and coefficient of determination (R2). This included an initial calibration from 2000/1/1 to 31/9/2009 which was then validated for 1/10/2010 to 31/12/2013 using daily streamflow values. Adhaim Watershed's whole area was determined to be 11816.82 km2. Grasslands make up 41.01% of the total area. Additionally, 28% of LCLU came from croplands and desolate regions in equal measure. A hydrological type D clay soil was discovered, along with the watershed's primary slope (0–5). The mean streamflow of Adhaim was determined to be 22.m3/????????????, and upon calibration, it was found to be 30 ????3/????????????.

Attributing climate variability, land use change, and other human activities to the variations of the runoff-sediment processes in the Upper Huaihe River Basin, China

Study regionsThe Wangjiaba (WJB) watershed, located in the upper Huaihe River Basin in China. Study focusAn attributing framework has been proposed combining the Double Mass Curve (DMC) and the Soil and Water Assessment Tools (SWAT) model to identify the contributions of climate variability, Land use (LU) change, and Other Human Activities (OHA) to the variations in runoff-sediment processes within the WJB. New hydrological insights for the regionThe studied period was able to be separated into three sub-periods (P1: 1981~1991, P2: 1992~2009, and P3: 2010~2019) using the DMC, and the SWAT model could simulate runoff and Sediment Yields Load (SYL) properly during different sub-periods after calibration. Generally, the runoff, SYL, and Suspended Sediment Concentration (SSC) within the WJB exhibited a decrease trend with a change rate of −1.3mm a-1, −8.49×104 t a-1, and −0.01kgm-3 a-1, respectively. Substantially, climate variability decreases runoff, SYL, and SSC from P1 to P3; LU change decreases runoff, SYL, and SSC from P2 to P3; OHA decreases SYL and SSC from P1 to P2, but increases SYL and SSC from P2 to P3. It should be noticed that the OHA has increased the SYL significantly especially over the downstream of WJB from P2 to P3. It is essential to enhance soil erosion prevention measures in the future under the background of global climate change.

Attribution analysis of hydrological drought after the impoundment of the Danjiangkou reservoir in the Hanjiang River basin

Study regionHanjiang River Basin, China Study focusUnder the joint influences of human activities and climate change, droughts frequently occur in the Hanjiang River Basin (HRB). Quantifying the driving forces contribution on hydrological drought is crucial to enhance the early warning ability. This study employed the standardized streamflow index (SSI) to assess hydrological drought. The Soil and Water Assessment Tool (SWAT) model was utilized to reconstruct natural streamflow based on hydrological and meteorological data. By comparing the variations of drought characteristics in simulated and observed scenarios, the impacts of human activities and climate change to hydrological drought were quantified. New hydrological insights for the study regionThe SWAT model is capable of effectively simulating the natural streamflow conditions of the HRB with NSE>0.7, R2>0.8, logNSE>0.7 and |PBIAS|<20%. Hydrological drought has intensified as a prolonged duration and greater severity affected by human activities and climate change. During the whole impact period (1968-2022), the duration and severity increased by 66.22% and 81.16% compared to baseline period (1956-1967). The year 1991 is detected as the mutation point. From 1968 to 1990 climate change has been the main factor in exacerbating hydrological drought. Since 1991, the influence of human activities has gradually exceeded the influence of climate change. These findings provide valuable insights for watershed integrated water resources management and water security.

A study of soil modelling methods based on line-structured light—Preparing for the subsoiling digital twin

A study of soil modelling methods based on line-structured light—Preparing for the subsoiling digital twin

Spatial Assessment of Soil Erosion Risk Using RUSLE and GIS in Dhumuga Watershed, Ambo, Ethiopia

Soil erosion has become a critical problem leading to land degradation and environmental risks globally. To grasp the rates of soil loss and identify the main factors driving these issues, it is vital to examine the specific impacts of soil erosion across different locations. Therefore, between 2021 and 2023, a research initiative was undertaken to assess, rank, identify, and map sections of the watershed that are particularly susceptible to soil erosion. The RUSLE components for factors R, K, L, S, C, and P were integrated using the ArcGIS 10.4.1 spatial analyst&amp;apos;s raster calculator tool to calculate and create maps that illustrate the risk and intensity of soil erosion in the Dhumuga watershed. The Dhumuga watershed was categorized into five groups based on average annual soil loss: 0–5 ton/ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; year&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; (very slight), 5–10 ton/ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; year&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; (slight), 10–20 ton/ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; year&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; (moderate), 20–50 ton/ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; year&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; (high), and &amp;gt; 50 ton/ha-1 year-1 (very high). The assessment of soil erosion severity was influenced by factors such as rainfall, soil type, DEM, land use, and land cover, employing the GIS-based RUSLE equation. The spatial risk of soil erosion was sorted into five categories based on severity, with 11.58% of the area categorized as very high risk (&amp;gt;50 ton ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; year&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt;), and 54.2% in the very low to low-risk category. On average, the watershed yielded an annual sediment production of up to 13.94 tons/ha/year, which is within an acceptable range. Considering these research findings, GIS-based analyses can be utilized to pinpoint areas at risk of soil erosion and identify vulnerable zones, offering crucial insights for future soil conservation and model enhancement.

Heat Stress assessment using an urban microclimate zonal model at the block scale coupled with building models

This contribution presents a toolchain consisting of a microclimate zonal model (HeatScape) coupled with a building energy model (BEM) and a radiative model developed to characterize the thermal environments within buildings and their immediate surroundings for daily and seasonal heat stress assessments. HeatScape comprises an outdoor mean radiant temperature model, a soil model, and an airflow zonal model (AZM). The phenomena involved in the coupling between HeatScape model and the BEM include convective heat exchanges and heat transfers induced by airflow related to mechanical ventilation, natural ventilation, and infiltration. A case study representing a block of buildings highlights the effects of urban form and thermal surfaces properties on the spatial distribution of the indoor and outdoor climatic variables affecting heat stress. Indoors, heat stress is mostly dependent on the air temperature and a significant positive effect is observed when natural ventilation is activated. Outdoors, the heat stress distribution is strongly correlated to the mean radiant temperature distribution. Even in the absence of direct solar radiation, overheating is observed in narrow airzones between buildings facing each other.

Response of offshore large-diameter pipe piles in layered poroelastic soil to lateral dynamic loading

The analytical solution for the lateral dynamic response of offshore large-diameter pipe piles embedded in seawater and layered saturated seabed soil is proposed. The hydrodynamic pressures of the outer and inner seawater are derived based on the inviscid compressible assumption of fluid, and the dynamic soil resistances of the outer and inner layered saturated seabed soil are derived based on Biot's poroelastic theory. The analytical expressions of the lateral dynamic response of the pile are obtained by using the transfer matrix method, and the dynamic characteristics of the lateral response of offshore pipe piles are parametrically investigated. It is concluded from the analysis results that the outer and inner hydrodynamic pressures significantly affect the natural frequency of the pile–water–soil system. Additionally, employing a homogeneous soil model with the same average modulus to represent the layered seabed soil can lead to significantly inaccurate estimations of the natural frequency and pile-head displacement of offshore pipe piles.

Impacts of land use changes on water conservation in the Songhuajiang River basin in Northeast China using the SWAT model

The Songhuajiang River basin (SRB) in Northeast China underwent obvious changes in land use in recent years, which might lead to intense changes in basin hydrology and water conservation. Therefore, to evaluate the effects of land use changes on the hydrological cycle and associated water conservation in the SRB, a calibrated Soil and Water Assessment Tool (SWAT) model was used. The model auto-calibration was conducted using the SWAT-CUP (SWAT Calibration and Uncertainty Procedures) tool. Results revealed that calibration of three crop yields of corn (Zea mays L.), rice (Oryza sativa L.), and soybean (Glycine max L.) during the study period (2001–2018) had the Percent BIAS (PBIAS) values of −8.7 %∼3.0 %, 6.2 %∼19.7 %, and −8.7 %∼7.2 %, respectively in 15 zones. Good agreements were obtained for simulated results of streamflow in comparison with measured data from 12 hydrological stations, in which the overall Nash-Sutcliffe Efficiency (NSE) values for the calibration (2009–2012) and validation (2013–2015) periods were 0.60 and 0.64, respectively, and the overall PBIAS values were 7.7 % and 15.4 %. For the land use changes, the hydrological cycle of corn to rice (all hydrological variables change by more than 18 %) was more complex and intense than that of corn to soybean (all hydrological variables change not exceed 5 %). According to the simulation results of water conservation, this study found that the implementation of the policy-driven replacement of corn with soybean in the SRB was feasible. As for the economy-driven conversion from corn to rice, it is necessary to consider the substantial impacts on the hydrological cycle and the decline in water conservation. Based on simulation results, it is not recommended that producers in the Western SRB promote corn to rice conversion.

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data

BackgroundThe preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potential of machine learning models for understanding the connections between soil and biological phenotypes. We investigate an integrative framework performing accurate machine learning-based prediction of plant performance from biological, chemical, and physical properties of the soil via two models: random forest and Bayesian neural network.ResultsPrediction improves when we add environmental features, such as soil properties and microbial density, along with microbiome data. Different preprocessing strategies show that human decisions significantly impact predictive performance. We show that the naive total sum scaling normalization that is commonly used in microbiome research is one of the optimal strategies to maximize predictive power. Also, we find that accurately defined labels are more important than normalization, taxonomic level, or model characteristics. ML performance is limited when humans can’t classify samples accurately. Lastly, we provide domain scientists via a full model selection decision tree to identify the human choices that optimize model prediction power.ConclusionsOur study highlights the importance of incorporating diverse environmental features and careful data preprocessing in enhancing the predictive power of machine learning models for soil and biological phenotype connections. This approach can significantly contribute to advancing agricultural practices and soil health management.

Dynamic response analysis of monopile-supported offshore wind turbine on sandy ground under seismic and environmental loads

Monopiles are the most widely adopted foundation type for Offshore Wind Turbines (OWTs) in shallow waters. With the expansion of the construction of OWT, the number of OWT farms in seismic regions increases globally including the coastal areas of Japan and China. It is necessary to evaluate the impact of earthquakes including the vibration and soil liquefaction on the OWTs supported by the monopile foundation, while the effects of liquefaction on offshore structures, especially for OWTs with monopiles, have not been sufficiently studied. This study investigates the seismic response of the monopile-supported OWTs with the use of an advanced soil model. A three-dimensional numerical model is built, and dynamic analyses are carried out using the OpenSees framework. The pressure-dependent multi-yield (PDMY03) constitutive model is used to simulate the dynamic soil behavior. The applicability of the large-diameter pile modeling method for proper soil-pile interaction modeling in this numerical analysis is first validated through centrifuge tests on monopiles subjected to lateral loading. The dynamic analyses are then carried out to demonstrate the seismic response of the entire OWT system. The numerical results indicate that the contribution of higher modes of vibration is becoming of increased importance for large wind turbines and soil-structure interaction plays a significant role in the dynamic response. Moreover, the monopile-supported OWT in dense sand deposits experiences substantial lateral displacement and rotation under the combined action of wind and earthquake loads when liquefaction occurs.

Seismic response of pile group embedded in unsaturated soil considering the coupling of kinematic and inertia pile-pile interactions

Both inertia and kinematic pile-soil-pile interaction should be considered during the seismic response analysis of a pile group. This study established a novel mathematical framework which is capable of considering the coupling of inertia and kinematic interactions, the complex constitutive of unsaturated soil, and the secondary wave effect within a pile group. By comparisons with existing analytical and numerical answers, the validity and advancement of the proposed model is exhibited. The main findings can be summarized as: (1) Simplified soil constitutive models, such as the BDWF model and the saturated soil model, would fail to reveal the authentic response of pile group. The saturation and porosity would significantly influence the kinematic pile-pile response factor, while the inertia pile-pile response factor is less influenced; (2) increases of pile numbers within a pile group would impose severe fluctuations on the kinematic response of the pile group, whereas the increase of pile spacing would significantly diminish this effect; (3) secondary wave effect should never be overlooked in seismic analysis but can be neglected in inertia analysis.