Site-specific Soil Research Articles

Effect of Precision Nitrogen Fertilization of Grassland on Soil Microbial Structure

The synergistic application of advanced technologies enables precise determination of plant growth, health, and nutritional requirements. However, despite the widespread use of modern technologies, the microbial status of the soil is often neglected, even though it significantly impacts soil productivity. Soil microbial activity serves as a crucial indicator of site-specific soil conditions. This article presents efforts to explore the quantitative and qualitative relationships between identified actinomycetes and soil nitrate content, as well as their distribution within the soil profile. Field data analysis facilitated the assessment of nitrate concentrations and the evaluation of the quantitative and species composition of actinomycetes in the soil profile at depths ranging from 0.05 to 0.35 m. The highest nitrate concentration (22 mg/100 g of soil) and actinomycete abundance (1076 CFU/g of soil) were observed in the topsoil layer. Additionally, spatial correlations between these parameters were analyzed for each soil layer. The correlation coefficients were approximately −0.6, indicating an inverse relationship. Areas with low nitrogen content corresponded to reduced microbial abundance within the soil profile, as supported by the spatial correlation data. These findings demonstrate the potential to predict actinomycete abundance in the soil profile based on nitrate content, offering valuable insights into soil health and productivity.

Application of Soil Remediation Techniques: A Case Study of Rice in a High-Selenium and High-Cadmium Soil Background Area in the Enshi Area

Seeking effective measures for the improvement of high-selenium and high-cadmium soils holds significant theoretical and practical importance for sustainable agricultural development. This paper focuses on conducting a site-specific soil survey in the characteristic agricultural product production area of Hefeng County, Enshi Prefecture, Hubei Province. Through field experiments, we compared 14 soil improvement methods across three techniques: chemical passivation remediation, agronomic regulation, and microbial remediation. The study investigated their impacts on rice Cd content, rice Se content, yield, and quality and conducted a comprehensive evaluation of the remediation effects of the different treatments. The experimental results indicate that (1) increasing the content of soil conditioners can enhance rice yields, with Treatment 14 showing the most significant increase, yielding an additional 257.3 kg per mu, representing a 55.62% increase. Treatment 12 also demonstrated a notable yield increase of 95.1 kg per mu, or a 20.55% increase. Lime, sepiolite, and shell powder can effectively reduce rice’s absorption of Cd. Treatment 9 resulted in the lowest Cd content in the rice, at 0.03 mg/kg, with a Cd reduction rate of 92%. The optimal application rates for this Cd reduction were 200 kg/mu of lime, 125 mL/mu of foliar inhibitor, and 50 kg/mu of carbon-silicon fertilizer. Treatment 12 achieved a rice Cd content of 0.11 mg/kg, with a 70% reduction in Cd, bringing the rice Cd content down to below 0.2 mg/kg, which meets the requirements of the National Food Safety Standard: Maximum Levels of Contaminants in Foods. In the comprehensive scoring of all treatments, considering four evaluation indicators—rice Cd content, rice yield, rice quality, and cost—Treatment 12 (300 kg/mu of soil conditioner + 50 kg/mu of carbon-silicon fertilizer) was found to be the optimal treatment through comparative scoring. It demonstrates good potential for ensuring safe rice production and can serve as a reference standard for repairing Cd-contaminated rice paddies in the local area, with promotional value.

Reappraisal of reliability of a slope through hybridisation of regional and site-specific soil shear strength information

Reappraisal of reliability of a slope through hybridisation of regional and site-specific soil shear strength information

Abundance of Human Pathogenic Microorganisms in the Halophyte Salicornia europaea L.: Influence of the Chemical Composition of Shoots and Soils

Salicornia europaea L. is a halophilic plant species belonging to Chenopodiaceae, whose shoots are used as a vegetable. Since the shoots can be eaten raw, the objective of the present study was to investigate possible controls on the abundance of human pathogenic microorganisms (HPMOs) in the shoots as a health risk. For this reason, the molecular-chemical composition of shoots, site-specific soil organic matter (bulk and rhizosphere), and soil pH and salinity were analyzed. Plant and soil samples were taken from two test sites with differing salinity levels in France (a young and an old marsh). We hypothesized that the chemical traits of plants and soils could suppress or promote HPMOs and, thus, serve as risk indicators for food quality. The chemical traits of shoots and bulk and rhizosphere soil were measured through thermochemolysis using gas chromatography/mass spectrometry (GC/MS). The densities of cultivable HPMOs (Salmonella enterica, Escherichia coli, and Listeria monocytogenes) were determined in plant shoots, rhizosphere soil, and bulk soil using selective media. Negative correlations between lignin content in the shoots and the abundance of S. enterica, as well as between lignin content in bulk soil and the abundance of E. coli, are explained by the lignin-based rigidity and its protective effect on the cell wall. In the shoot samples, the content of lipids was positively correlated with the abundance of E. coli. The abundance of E. coli, S. enterica, and L. monocytogenes in bulk soil decreased with increasing soil pH, which is linked to increased salinity. Therefore, soil salinity is proposed as a tool to decrease HPMO contamination in S. europaea and ensure its food safety.

Calibration and implementation of a design tool for drag anchors in clay

Abstract Drag anchors are considered as one of the most applicable anchor solutions for floating offshore wind as they can be used for a wide range of soil conditions. For feasibility studies of floating offshore wind farms different anchor concepts needs to be compared in order to select the most proper anchor solution. To do so, the level of details in the analysis for the various anchor types must be similar. Currently design charts are adopted as a simple design method for drag anchors. However, design charts are developed for specific soil conditions, and do not account for site specific soil conditions. To have similar precision, as analytical solutions for suction anchors, a simple design methodology that can account for site specific soil conditions for drag anchors must be adopted. This paper presents an example for how a simple analytical solution can be calibrated against design charts, which makes it possible to account for site specific soil conditions, resulting in a better basis for comparing early stage drag anchor design to other anchor solutions.

Spatial Variability in Soil Water-Physical Properties in Southern Subtropical Forests of China

Quantification of soil water-physical properties and their spatial variation is important to better predict soil structure and functioning, as well as associated spatial patterns in the vegetation. The provision of site-specific soil data further facilitates the implementation of enhanced land use and management practices. Using geostatistical methods, this study quantified the spatial distribution of soil bulk density (SBD), soil moisture (SM), capillary water-holding capacity (CWHC), capillary porosity (CP), non-capillary porosity (NCP), and total porosity (TP) in southern subtropical forests located at the Tropical Forest Research Center in Pingxiang City, China. A topographic map (scale = 1:10,000) was used to create a grid of l km squares across the study area. At the intersections of the grid squares, the described soil water-physical properties were measured. By calculating the coefficient of variation for each soil water-physical property, all measured soil water-physical properties were found to show moderate spatial heterogeneity. Exponential, gaussian, spherical, and linear models were used to fit the semivariograms of the measured soil water-physical properties. Across all soil water-physical properties, the range A0 variable (i.e., the separation distance between the semivariance and the sill value) measured between 3419 m and 14,156 m. The nugget-to-sill ratio ranged from 9 to 41%, indicating variations in the level of spatial autocorrelation among the soil water-physical properties. Many of the soil water-physical properties were strongly correlated (as assessed using Pearson correlation coefficients). Spatial distribution maps of the soil water-physical properties created via ordinary kriging (OK) showed that most water-physical properties had clumped (aggregated) distributions. SBD showed the opposite spatial pattern to SM and CWHC. Meanwhile, CP and TP showed similar distributions.

Multistep procedure for estimating non-linear soil response in low seismicity areas—a case study of Lucerne, Switzerland

SUMMARY The impact of non-linear soil behaviour on seismic hazard in low-to-moderate seismicity areas is often neglected; however, it may become relevant for long return periods. In this study, we used fully non-linear 1-D simulations to estimate the site-specific non-linear soil response in the low seismicity area, using the city of Lucerne in Switzerland as an example. The constitutive model considers the development of pore pressure excess and requires calibration of complex soil models, including the soil dilatancy parameters. In the absence of laboratory measurements, we mainly used the cone penetration test data to estimate the model variables and perform inversion for the dilatancy parameters. Our findings, using Swiss building code-compatible input ground motions, suggest a high probability of strong non-linear behaviour and the possibility of liquefaction at high ground motion levels in the case study area. While the non-linearity observations from strong-motion recordings are not available in Lucerne, the comparison with empirical data from other sites and other methods shows similarity with our predictions. Moreover, we show that the site response modelled is largely influenced by the strong pore pressure effects produced in thin sandy water-saturated layers. In addition, we demonstrate that the variability of the results due to the input motion and the soil parameters is significant, but within reasonable bounds.

Climate change induced heat and drought stress hamper climate change mitigation in German cereal production

ContextAgricultural production and climate change strongly influence each other and there are significant efforts to minimize negative impacts in both directions. In particular, breeding progress has succeeded in reducing the carbon footprint (CFP) of cereals over time. However, there is widespread certainty that climate change-related weather extremes have led to stagnation of cereal yields in many global production regions. Research questionWe assume that climate change-related yield stagnation is also evident in variety trials in Germany, which has to date only been shown for on-farm yields. Furthermore, we expect that the stagnation in yields also leads to a stagnation in the downward trend of CFP, and that heat and drought stress in particular increase the CFP of cereals. In addition, we hypothesize that the site-specific soil quality largely determines stress induced increases in CFP. MethodsWe conduct a partial life cycle assessment (LCA) with German variety trial data from 1993 to 2021 and determine the greenhouse gas emissions per unit of land (GHGL), as well as the CFP of winter wheat, winter rye, and winter barley. Further, we evaluate the time trends of yield, GHGL, and CFP using linear and quadratic plateau models. In addition, we calculate spatio-dynamic weather indices (WIs) for moderate, severe and extreme heat and drought stress. Using mixed models, we estimate the explanatory power and effect size of heat and drought WIs on the CFP. Finally, we present the spatial differences of heat and drought on the CFP at different soil qualities. ResultsWe show yield plateaus in all crops and stagnating GHGL trends, resulting in a stagnation of the downward trend of CFP, especially for rye and barley. We highlight that heat and drought increase the CFP of all crops. However, the impact of heat and drought on the CFP varies greatly with soil quality across all crops. ConclusionsWe conclude that climate change-induced weather extremes are major challenges not only for cereal production and food security but also for climate change mitigation in the agricultural sector, highlighting the importance of high-yield locations, alongside variety selection and resource-efficient management, for climate change mitigation. SignificanceThis study is the first that proves significant yield stagnation in German variety trials. Moreover, this study is the first to analyze the impact of heat and drought stress on cereal CFP, with novel results that proof that climate adaptation will become a crucial aspect of climate change mitigation in field crops.

Quantitative Analysis of Iron Activity in Agricultural Soils Using X-ray Fluorescence Spectrometry: Comparative Study with an Undisturbed Reference Site in Niankhene, Senegal

An essential micronutrient for plant growth and development, iron (Fe) affects a number of physiological processes, including respiration and photosynthesis. This study compare the amounts of iron in agricultural zones and reference zones, describe the geographic distribution of iron, and assess its accessibility to cultures. The aim is to assess the deficiencies and excess soil disturbance in the Niankhène agricultural site while maintaining a stable site. Soil samples were taken at 0–20 cm and 20–40 cm depths from 47 agricultural stations and three reference points using X-ray fluorescence (XRF) spectroscopy. Significant variation in Fe concentrations was found by the research, with an average of roughly 3310.95 ppm and moderate variation between samples. An analysis conducted in comparison with reference locations revealed a widespread lack of Fe in the research area, with 85.71% of samples displaying depletion and only 14.29% displaying accumulation of Fe. This discrepancy emphasizes the necessity of focused soil management techniques to raise Niankhene's agricultural output. The results highlight how crucial it is to use site-specific soil management strategies in order to overcome Fe deficits and raise crop yields. This research highlights the possibility for establishing targeted fertilization and corrective procedures to maximize Fe availability by utilizing XRF technology for reliable soil nutrient monitoring. The study's findings offer insightful information for enhancing fertilization techniques and improving soil management techniques, which will support sustainable farming methods and increased crop yield in the area.

Changes in microbial physiology and carbon-use efficiency upon improving soil habitat conditions in conservation farming systems

The interplay between soil microbial anabolism and metabolism has recently been postulated as an important lever for carbon sequestration in soils. Theoretical considerations suggest that high microbial growth rates and a high carbon-use efficiency (CUE) are associated with increased soil organic carbon (SOC) build-up in arable soils. Nature-oriented conservation agricultural practices are believed to facilitate this microbial-driven process of SOC accrual; a practical validation of this postulation is however missing. Against this background, we evaluated the effect of agricultural management and site-specific soil chemical and physical properties on microbial physiology (i.e., respiration, bacterial and fungal growth rates, and microbial biomass turnover) and CUE by an on-farm comparison of conventional farming, conservation farming and unmanaged reference soil systems (i.e., adjacent field margins) at twenty-one sites across three soil depths. We show that a change in agricultural management towards soil health regeneration has a significant impact on microbial physiology. Bacterial growth, respiration and microbial biomass turnover increased from conventional farming towards conservation farming systems to reference soils. The opposite trend however was found for fungal growth and microbial CUE, with highest values observed in conventional farming systems. This clearly contradicts the prevailing idea that higher microbial CUE in conservation farming systems may be associated with higher SOC contents. Our results further show that soil physical and chemical parameters such as soil pH, texture and dissolved carbon compounds strongly predict microbial CUE. In line with these results, functional pore domains showed specific optima for microbial growth and CUE. For example, a high share of small pore domains hampered fungal growth and reduced microbial CUE but facilitated microbial biomass turnover at the same time. Thus, we suggest that – superimposed upon agricultural management effects – habitat structural conditions and microbial carbon limitation mainly shape microbial physiology and CUE in arable soil systems.

Mapping of on-field soil nutrient variabilities as a guiding force for smart farming: a case study from FarmerZone sentinel-1 from three potato agroecological zones of India.

Mapping of soil nutrient parameters using experimental measurements and geostatistical approaches to assist site-specific fertiliser advisories is anticipated to play a significant role in Smart Agriculture. FarmerZone is a cloud service envisioned by the Department of Biotechnology, Government of India, to provide advisories to assist smallholder farmers in India in enhancing their overall farm production. As a part of the project, we evaluated the soil spatial variability of three potato agroecological zones in India and provided soil health cards along with field-specific fertiliser recommendations for potato cultivation to farmers. Specifically, 705 surface samples were collected from three representative potato-growing districts of Indian states (Meerut, UP; Jalandhar, Punjab and Lahaul and Spiti, HP) and analysed for soil parameters such as organic carbon, macronutrients (NPK), micronutrients (Zn, Fe, Mn, and Cu), pH, and EC. The soil parameters were integrated into a geodatabase and subjected to kriging interpolation to create spatial soil maps of the targeted potato agroecological zones through best-fit experimental semivariograms. The spatial distribution showed a deficiency of soil organic carbon in two studied zones and available nitrogen among all studied zones. The available phosphorus and potassium varied among the agroecological zones. The micronutrient levels were largely sufficient in all the zones except at a few specific sites where nutrient advisories are recommended to replenish. The general management strategies were recommended based on the nutrient status in the studied area. This study clearly supports the significance of site-specific soil analytics and interpolated spatial soil mapping over any targeted agroecological zones as a promising strategy to deliver reliable advisories of fertiliser recommendations for smart farming.

Derivation of ecotoxicologically acceptable Cu concentrations in soil from different land uses in South Korea

This study aimed to establish ecotoxicologically acceptable Cu concentrations for soil-residing species by integrating the biotic ligand model and the species sensitivity distribution. Statistical analyses were performed on 35 soil solution samples collected from four distinct land use sites: residential, agricultural, forested, and industrial regions. The environmental parameters of these samples, including pH, dissolved organic carbon (DOC), Ca2⁺, Mg2⁺, K⁺, and Na⁺ concentrations, exhibited wide variations across the four regions. Specifically, pH and the concentrations of Mg2⁺, K⁺, and Na⁺ showed significant variability. Additionally, a strong correlation was observed between pH and Ca2⁺, as well as between the DOC concentration and Mg2⁺ and Na⁺. Using the biotic ligand model, we derived the half-maximal effective activities of Cu (EC50{Cu2+}) for 10 soil organisms based on the chemical compositions of the soil solution samples. Additionally, a species sensitivity distribution approach was employed to determine the 5% hazardous concentration (HC5) for soil biota, which was closely associated with DOC and Na⁺ concentrations, with Mg2⁺ playing a secondary role. We attributed these relationships to the formation of DOC complexes that mitigate Cu toxicity, along with competitive interactions with cations. Notably, HC5 values did not differ significantly across sampling sites (p = 0.523). Clustering based on environmental factors grouped the samples into four clusters, each containing soils from different land use types. However, the third cluster included an outlier from agricultural soil due to its unusually high pH and DOC levels. These findings suggest that it is crucial to consider site-specific soil characteristics when determining ecotoxicologically acceptable Cu concentrations, and soil solution characteristics do not always align with specific land use patterns.

Soil Physicochemical Properties under Selected Avocado Cultivars in Ethiopian Smallholder Agroforestry

This study investigated the impact of three avocado cultivars on selected soil physicochemical properties in Central Ethiopia, to enhance the knowledge on the influence of avocado cultivars on soil physicochemical properties, and assist smallholders in cultivar selection in agroforestry. Trees planted in farmers´ fields 8 years earlier were revisited. Soil samples were collected from 0–20 cm and 20–40 cm depth at three radial distances from trees (1 m and 2 m from tree trunk, and at 5 m from the canopy edge as a control). Soil texture, bulk density, moisture content, pH, electrical conductivity, soil organic carbon, total nitrogen and available phosphorus were determined. Soil moisture content and electrical conductivity were overall higher and bulk density was lower (p < 0.05) under the canopies of the avocado trees than in the control and soil organic carbon, total nitrogen and available phosphorus tended to increase in spite of nutrient inputs to the control whilst the trees were unfertilized. Differences between the studied cultivars were small, but Hass tended to have the largest impact on soil nutrient levels, whilst Ettinger and Nabal tended to have a somewhat larger effect on the soil organic carbon concentration. Integrating these avocado cultivars on farms can improve soil fertility in the study area. However, for optimal agricultural soil health and sustainable avocado production, cultivar and site-specific soil management practices must be applied.

Evaluating the effects of the CERES-Rice model to simulate upland rice (Oryza sativa L.) yield under different plant density and nitrogen management strategies in Fogera Plain, Northwest Ethiopia

This study assessed the optimal nitrogen (N) fertilizer rate and planting density for the well-adapted upland rice cultivar NERICA_4 on the Fogera Plain. The primary objective was to evaluate the effects of varied planting densities and N-fertilizer rates on upland rice yield and other agronomic parameters. A two-year field study (2020 and 2021) was conducted at the Fogera Rice Research Field Station, testing nine plant densities (75, 87, and 98; 72, 82, and 91; 70, 79, and 89 plants per m2 and two N rates (115 and 138 kg N ha−1). The Crop Simulation Model Crop Environment Resource Synthesis (CSM-CERES-Rice) within the Decision Support System for Agrotechnology Transfer (DSSAT) framework was calibrated and validated using site-specific weather, soil, crop, and agronomic management data from the experiment. Results on the subsequent RMSE, RMSEn, and d index values during the calibration phase were 0.074 t ha−1, 1.82 %, and 0.86 of grain yield; 0.307 t ha−1, 3.36 %, and 0.87 of by-product yield; 0.489 t ha−1, 3.74 %, and 0.79 of top dry biomass yield; and 0.28, 8.24 %, and 0.63 of leaf area index values, respectively. Whereas results on the corresponding RMSE, RMSEn, and d index values during the evaluation phase were: 0.58 t ha−1, 1.33 %, and 0.90 of grain yield; 0.69 t ha−1, 0.58 %, and 0.99 of by-product yield; 0.678 t ha−1, 4.36 %, and 0.67 of top dry biomass yield; and 0.75, 13.92 %, and 0.74 of leaf area index, respectively. The findings of the long-term simulation showed that a 23 % increase in grain yield was achieved with 138 kg N ha−1 and 87 plants per m2 of planting density, as compared to 115 kg N ha−1 and 75 plants per m2 of plant density. The recommended optimum plant density and N fertilizer rate were 138 kg N ha−1 with PD2 of plant density for upland rice production in the Fogera Plain.

Comparative Effects of Site-specific and Blanket Fertilizer Application on Soil Physicochemical properties and Maize (Zea mays L.) Yield at Mikalango in Chikwawa District, Southern Malawi

Malawi's economy predominantly relies on agriculture. However, continuous soil degradation threatens crop production, food security, and nutrition. The use of fertilizers in soil fertility amendment has not been as effective due to blanket application, which does not adequately address Malawi's diverse soil nutrient deficiencies. This can also lead to over-fertilization, which can generate greenhouse gas emissions contributing to climate change. The experiment, set up in a randomized complete block design, compared site-specific and blanket fertilizer applications having 5 treatments and 5 replications, where a single maize seed variety was planted uniformly. Data was collected from the site's soil physicochemical properties, maize growth, and yield components and analyzed using JMP SAS software version 14.0.0. Results indicated that site-specific fertilizer application significantly differed from blanket fertilizer application at a 5% level of significance. Phosphorus (0.31 ppm), Sulphur (24.2 ppm), and Zinc (1.92 ppm) were significantly higher due to site-specific fertilizer application. Similarly, plant biomass (3.41 t/ha) and grain yield (7.03 t/ha) were also significantly higher due to site-specific fertilizer application. Hence, the study concluded that site-specific soil fertility management is ideal for efficient nutrient replenishment and attaining optimum yields while mitigating climate change in maize farming systems

A comprehensive analytical and computational assessment of soil water characteristics curves in Atlantic Canada: Application of a novel SelectKbestbased GEP model

For sustainable agriculture, irrigation is one of the most important management practices in a semi-arid climate. Determining the site-specific soil type-based irrigation water requirements requires the development of a soil water characteristics curve (SWCC). This study focuses on exploring the suitability of analytical SWCC models based on the observed data of SWCC developed using the pressure membrane apparatus. A novel SelectKbest gene expression programming (GEP) model is used to create the generalized machine learning SWCC model for Atlantic Canadian soils. The composite soil samples with representative soil textures of loamy sand, loam, and sandy loam are collected from the selected locations in Prince Edward Island and New Brunswick provinces of Canada. The suitability of models at three regions shows that at all sites, including PEI-1 (loam soil) 1, PEI-2 (loamy sand), and NB-3 (sandy loam) if SWCC data has four measured suction potential levels, then McBee & Bomb and Tani exponential models may be selected. Van Genuchten, double exponential, Ruso, Kosuki, and Gardner's four parameters models should be a good choice for five-section potential. Similarly, for six measured suction potential values, the Fredlund & Xing, Omuto, and Van Genuchten models having parameters should be selected for determining the optimum soil hydraulic parameters. The HydroMe program with Brooks and Corey, four, and five parameters Van Genuchten models performed well. The HydroMe program is calibrated and validated with standard RETC for selected regions of Atlantic Canada, which suggests that the HydroMe program is flexible in developing efficient agricultural water management algorithms. Various performance metrics like R2 and RMSE are employed to assess the robustness of the model. A generalized SWCC model (R2=0.976 and RMSE=0.04) is developed using a novel SelectKbest-based GEP modeling approach for Atlantic Canadian soils. These novel approaches can significantly improve site-specific agricultural water management and decision support systems.

Precision Irrigation Soil Moisture Mapper: A Thermal Inertia Approach to Estimating Volumetric Soil Water Content Using Unmanned Aerial Vehicles and Multispectral Imagery

To address the issue of estimating soil moisture at a hyper-resolution scale, a methodology referred to as Precision Irrigation Soil Moisture Mapper (PrISMM), that includes three key components, is developed: high-resolution remotely sensed optical and thermal data, surface energy balance modeling, and site-specific soil analysis. An Unmanned Aerial Vehicle/System (UAV or UAS) collects high-resolution multispectral imagery in the Dallas–Fort Worth metropolitan study area. Orthomosaics are converted to thermal inertia estimates in a spatially distributed format using the remotely sensed data combined with a set of surface energy balance modeling equations. Using thermal and physical properties of soil gained from site-specific soil analysis, thermal inertia estimates were further converted from thermal inertia to daily volumetric soil water content (VSWC) with a horizonal resolution of 8.6 cm. A ground truthing dataset of measured VSWC values taken from a Time Domain Reflectometer was compared with model results, producing a reasonable correlation with an average coefficient of determination of (R2) = 0.79, an average root mean square error (RMSE) = 0.0408, and mean absolute error (MAE) = 0.0308. This study highlights a practical approach of estimating VSWC for irrigation purposes while providing superior spatio-temporal coverage over in situ methods. The authors envision that PrISMM can be implemented in water usage management by relating VSWC with weather forecasts and evapotranspiration rates to develop time-based spatially distributed irrigation management plans.

Interpretable machine learning for selection of site-specific soil constitutive models and consolidation settlement analysis

Machine learning (ML) has achieved great breakthroughs in many fields, such as computer vision and speech recognition, and it also gains an increasing attention in geotechnical engineering. However, it is often criticized for a lack of interpretability. This study proposes an interpretable sparse dictionary learning (ISDL) approach for selection of suitable soil constitutive models (SCMs) and geotechnical consolidation analysis in a specific site. ISDL is inherently interpretable since it expresses prediction of geotechnical responses (e.g., consolidation settlement) as a weighted summation of many elementary datasets (i.e., dictionary atoms in ISDL). The dictionary atoms are constructed using numerical analyses (e.g., finite element model) with different candidate SCMs and parameters. Interpretability of ISDL is improved by a small number of non-trivial atoms (or SCMs) selected for model prediction using site-specific monitoring data and further enhanced by contribution ranking of the selected SCMs using a game theory-based approach. The proposed method is illustrated using a real reclamation project in Hong Kong, and it is shown to effectively select the most suitable constitutive models for the given site, quantify contributions of the selected models, and significantly improve settlement predictions with rigorously quantified prediction uncertainty, particularly at locations without monitoring or future time steps.

Neural network prediction model for site response analysis based on the KiK-net database

Currently, the most widely used site response analysis methods include linear, equivalent linear and nonlinear approaches. However, the results of these analyses gradually deviate from the true values as the site softens or the earthquake intensity increases. To overcome this issue, this study employs a 1D Convolutional Neural Network model to simulate the relationships between the surface and downhole motions. To ensure comprehensive coverage of various sites and earthquake conditions, a careful selection of stations and seismic intensities resulted in 56 stations and 34,538 seismic records from KiK-net. Additionally, 30 seismic intensity measures and three site condition parameters were chosen. The convolutional operation was utilized to consider the correlations between the parameters, enabling the prediction of surface motion intensity measures. The performance of the neural network model was assessed based on residual analysis, and the model’s generalization ability was tested using samples that were not included in the training dataset. The results demonstrate that the neural network can effectively predict surface motion intensity measures. Furthermore, in comparison with the equivalent linear and nonlinear methods that do not rely on site-specific detailed soil data, the 1D Convolutional Neural Network exhibits superior performance and maintains high prediction accuracy even for soft soil and strong earthquake scenarios, confirming the enhanced predictive capability of the proposed model.

Arbuscular Mycorrhizal Fungi and Rhizobium Improve Nutrient Uptake and Microbial Diversity Relative to Dryland Site-Specific Soil Conditions.

Arbuscular mycorrhizal fungi (AMF) and rhizobium play a significant role in plant symbiosis. However, their influence on the rhizosphere soil microbiome associated with nutrient acquisition and soil health is not well defined in the drylands of Montana (MT), USA. This study investigated the effect of microbial inoculants as seed treatment on pea yield, nutrient uptake, potential microbial functions, and rhizosphere soil microbial communities using high-throughput sequencing of 16S and ITS rRNA genes. The experiment was conducted under two contrasting dryland conditions with four treatments: control, single inoculation with AMF or Rhizobium, and dual inoculations of AMF and Rhizobium (AMF+Rhizobium). Our findings revealed that microbial inoculation efficacy was site-specific. AMF+Rhizobium synergistically increased grain yield at Sidney dryland field site (DFS) 2, while at Froid site, DFS 1, AMF improved plant resilience to acidic soil but contributed a marginal yield under non-nutrient limiting conditions. Across dryland sites, the plants' microbial dependency on AMF+Rhizobium (12%) was higher than single inoculations of AMF (8%) or Rhizobium (4%) alone. Variations in microbial community structure and composition indicate a site-specific response to AMF and AMF+Rhizobium inoculants. Overall, site-specific factors significantly influenced plant nutrient uptake, microbial community dynamics, and functional potential. It underscores the need for tailored management strategies that consider site-specific characteristics to optimize benefits from microbial inoculation.