Soil Indicators Research Articles

Stain removal performance of moisture-wicking fabric during home laundry

Abstract Moisture-wicking clothes are widely used in various sports or athletic activities due to their function of moisture absorption and perspiration. In this study, the washing and decontamination of moisture-wicking fabrics, especially the performance and decontamination effect of moisture-wicking fabrics after washing were investigated. The results showed that the physical morphology of moisture-wicking fabric is very different from that of an ordinary polyester fabric. The cross-section of the moisture-wicking fabric is hexagonal, and this fabric has good hydrophilicity. After the degreasing & thermosetting process, the air permeability of the moisture-wicking fabric is increased from 1013 mm/s to 2911 mm/s. However, the air permeability is decreased after one washing, but it has little effect during the subsequent washing cycles. Moreover, the degreasing & thermosetting process also improve the stains removal index. If the moisture-wicking fabric was washed before the preparation of stained fabric, the stain removal index of carbon black soil and sebum stains is increased. Although most of the aggregated particles on the surface of the fibers are removed after washing, a small amount of sebum still remains in the spaces between the fibers. These results indicate that most of the carbon black in the stained area is removed after washing, while oil components are hardly removed from the moisture-wicking fabric during home laundry. Compared to other surfactants, C18 fatty acid methyl ester ethoxylates and nonionic surfactants with long carbon chains can effectively reduce the surface tension of water and improve the wettability of moisture-wicking fabric, so that water molecules can diffuse well between fibers and stains, the binding force between stains and fabric is weakened, and the decontamination of the fabric is improved.

Energy multi-scale method to analyze the scale effect of soil particles

As a common geological material, soil is a key aspect of construction engineering. Soil has typical multi-scale characteristics, but current multi-scale methods analyze these characteristics only in regard to geometric space. More exploration of the coupling influence mechanism of the basic properties of particles on the microstructure and macroscopic properties of soil is needed. This study analyzed the influence of geometric scale and mineral composition on the surface energy of particles at the microscopic level for development of the energy multi-scale method. Experiments were performed to determine the influence of mineral composition and particle size on the plasticity index (Ip) of the soil, and experimental results are discussed and interpreted quantitatively using the energy multi-scale method. The conclusions derived from this work are as follows: 1) the mineral composition and particle size of the soil can cause interface and surface effects; 2) the comprehensive ratio of micro-force to weight (CRFW) of the particles can be determined using the energy multi-scale method and quantitatively reflects the influence of particle size and mineral composition on the microscopic properties of the soil; and 3) the energy multi-scale method explains the mechanism of the plasticity index of soil and has allowed identification of a new division of soil plasticity. When the CRFW was used as the control index, the plasticity index of the three materials was practically the same, even if the mineral composition and particle sizes of the three materials were different.

Impact of land-use systems on fertility parameters and deterioration indices of soil in the sub humid Southern Plains of Rajasthan, India

Aim: This investigation was carried out to appraise the effect of different prevailing land-use systems (LUSs) on nutrient status along with deterioration indices of soil under sub-humid Southern Plains of Rajasthan. Methodology: Six dominant land-use systems: barren, agricultural, agri-horticulture, horticultural, grass, and natural forest were selected in the sub-humid Southern Plains of Rajasthan. A total of 120 composite soil samples [6-LUSs, 4- soil depths (0-20, 20-40, 40-60, and 60-80 cm), and five replications] were collected for laboratory analysis. The two-way analysis of variance was used to test the effect of different LUSs and soil depths on available nutrients, essential properties with deterioration indices of soil. Results: The results of the study showed that soil organic carbon (SOC), DTPA extractable Zn, Mn, available nitrogen, and CEC are the most degraded soil fertility parameters under studied LUSs. Barren land-use has led to the highest decline in Zn (͌75%), SOC (71%), N (66%), Cu (62%) and Fe (57%), followed by Agricultural land-use that has led to a decline in SOC (53%), Zn (46%), N (43%) and Mn (38%). The use of soil deterioration indices revealed that soils deteriorated slightly under grassland and horticultural LUSs (-11.05 and -11.81 %). However, moderate deterioration was observed in the agri-horticulture land-use soil (-22.51 %) while severe (-28.11%) and extremely severe deterioration (-47.50%) occurred under agricultural and barren LUSs, respectively. Interpretation: The result of this study implies that consistent cultivation without appropriate land-use management practices in the cultivated LUS aggravates the deterioration of soil organic carbon and essential soil fertility parameters. These results suggested that restoration of barren and agricultural lands into horticultural, agri-horticulture, and grassland-uses consequently decreased soil disturbance which could be an effective strategy for improving or maintaining the soil quality and sustainability in the study area. Key words: Deterioration indices, Land-use system, Soil depth, Soil nutrients

The Contribution of the Hulene-B Waste Dump (Maputo, Mozambique) to the Contamination of Rhizosphere Soils, Edible Plants, Stream Waters, and Groundwaters

The contamination of ecosystems in areas around waste dumps is a major threat to the health of surrounding populations. The aim of this study is to understand the contribution of the Hulene-B waste dump (Maputo, Mozambique) to the contamination of edible plants, rhizosphere soils, stream waters, and groundwater, and to assess human health risk. Soil and plant samples were analyzed by XRD and XRF for mineralogical and chemical composition characterization, respectively. Mineral phases identified in rhizosphere soil samples were ranked, calcite (CaCO3) > quartz (SiO2) > phyllosilicates (micas and kaolinite) > anhydrite (CaSO4) > K feldspar (KAlSi3O8) > opal (SiO2·nH2O) > gypsum (CaSO4·2H2O), suggesting potential toxic elements low mobility. Soil environmental indices showed pollution by Pb > Cu > Zn > Zr. The chemical composition of edible plants revealed contamination by Ni, Cr, Mn, Fe, Ti, and Zr. Groundwaters and stream waters showed a potential health risk by Hg and, in one irrigation water sample, by Pb content. The health hazard index of rhizosphere soils was higher by ingestion, with children being the ones more exposed. Results suggested a combined health risk by exposure to edible plants, rhizosphere soils, stream waters, and groundwaters.

Ecological risk assessment and heavy metals accumulation in agriculture soils irrigated with treated wastewater effluent, river water, and well water combined with chemical fertilizers

Contaminated irrigation water can increase trace heavy metals concentration in agricultural soil. The present research aimed to investigate the effect of three types of irrigation water sources, including treated wastewater effluent, Gharasoo river water, and well water with chemical fertilizer, on the accumulation and ecological risk of heavy metals in agricultural soils. Soil samples were collected before and after crop irrigation to evaluate heavy metal concentrations. The samples were analyzed to determine the presence of arsenic, nickel, cadmium, iron, chromium, zinc, lead, copper, and manganese. Based on the results, the concentration of essential metals in the soil before the irrigation process was more than toxic metals. The different irrigation sources increased the concentration of all heavy metals in the soil, and the accumulation of Cr, Ni, and Cd significantly elevated more than others. Irrigation resources' effectiveness in transferring heavy metals to the soil was obtained as treated wastewater effluent < well water with fertilizer < river water. Furthermore, the potential ecological risk index (RI) for irrigated soil was in a high-risk category. Therefore, it is recommended that the river water should not be used to irrigate vegetables to the utmost possible. Finally, the low heavy metals concentration and the presence of nutrients in treated wastewater effluent make this source the most suited source of irrigation because it eliminates the need for chemical fertilizers by farmers and transfers fewer heavy metals to the soil.

Determination of the Physicochemical Parameters and Pollution Indices in Soils of Obodo Community in Delta State, Nigeria

Oil and gas activities are one of the environmental concerns in the crude oil-rich areas of the Niger Delta. This study aimed to determine the physicochemical level and some pollution indices in the soils of the Obodo community in Delta State to ascertain if there is an anthropogenic influence on the soil quality. Soil samples were collected from 14 sampling stations and 2 control stations during the wet and dry seasons from two soil depths (topsoil, 0 - 15cm) and (subsoil, 15-30cm) according to standard methods and procedures. The study results revealed elevated concentrations of total hydrocarbon content, polyaromatic hydrocarbon, total petroleum hydrocarbon and sulphate with mean values of 138.45 mg/kg (topsoil) and 147.66 mg/kg (subsoil); 52.62 mg/kg (topsoil) and 30.01 mg/kg (subsoil); 229.95 mg/kg (topsoil) and 160.33 mg/kg (subsoil); 54.89 mg/kg (topsoil) and 44.88 mg/kg (subsoil) during the wet season respectively; and mean values of 172.94 mg/kg (topsoil) and 151.46 mg/kg (subsoil); 11.11 mg/kg (topsoil) and 10.25 mg/kg (subsoil); 19.63 mg/kg (topsoil) and 17.99 mg/kg (subsoil); 22.57 mg/kg (topsoil) and 19.95 mg/kg (subsoil) during the dry season respectively. The high concentrations observed in this study indicates anthropogenic influence that may be due to oil spillage, emission from vehicle exhaust, incomplete combustion of coal, and the use of inorganic fertilizer. The results of the index of geo-accumulation and contamination factor showed that the levels of heavy metals were those of unpolluted soil except for the cadmium concentration observed in the topsoil of the study area, which showed moderate pollution during the wet season. The low pH values and a higher percentage of sand in the soil infer that the low heavy metals concentration observed in this study may be due to cations leaching down the aquifer which requires further studies to examine the groundwater quality.

Design and development of hydraulic controlled tractor front mounted twin conveyor onion (Allium cepa) digger

In India and many developing countries harvesting of onion (Allium cepa L.) crop is done manually which is cumbersome and time-consuming. The tractor-operated front-mounted twin conveyor onion digger was designed and developed during 2019 in Divisional Workshop (Farm Machinery and Power Engineering) at Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand. It had five blades made of mild steel (320 mm × 150 mm × 12 mm size) bolted to the base plate instead of one single share to strengthen the share. Onion and soil were separated over conveying unit. Power from the rear PTO (Power take-off) of a tractor to the front-mounted digging unit was conveyed through a power transmission unit which consisted of a gear reduction unit, V-belt and pulley arrangement, and 40 mm diameter of the propeller shaft. The lifting, lowering, and depth were controlled with the help of two single-acting hydraulic cylinders. The biometric and physical properties of onion bulbs (Agri found light red) were found average with equatorial and polar diameter, plant height, neck thickness, and weight of onion dry leaves as 36.19 and 37.19 mm, 284.05 mm, 6.80 mm and 30.19 g respectively. The average soil cone index, moisture content, and bulk density (before transplanting and harvesting) of soil were observed to be 1 kg/cm2, 17.22,12.58%, and 1.50, 1.38 g/cm3 respectively. The performance evaluation in the field found a maximum percentage of exposed and minimum damaged bulbs as 82.55% and 13.51% respectively, at a forwarding speed of 1.5 kmph and conveyor speed of 2 kmph. The field efficiency of the machine was 87.46%.

Soil organic carbon stability mediate soil phosphorus in greenhouse vegetable soil by shifting phoD-harboring bacterial communities and keystone taxa

Addition of organic amendments, such as manure and straw, to arable fields as a partial substitute for mineral phosphorus (P), are a sustainable practice in high-efficiency agricultural production. Different organic inputs may induce varied soil organic carbon (OC) stability and phoD harboring microbes, subsequently regulate P behavior, but the underlying mechanisms are poorly understood. A 11-year field experiment examined P forms by 31P-nuclear magnetic resonance (NMR), OC chemical composition by 13C NMR, and biologically-based P availability methods, phoD bacterial communities, and their co-occurrence in soils amended with chemical P fertilizer (CF), chemical P partly substituted by organic amendments including pig manure (CM), a mixture of pig manure and corn straw (CMS), and corn straw (CS), with equal P input in all treatments. Organic amendments significantly increased soil labile Pi (CaCl2-P, citrate-P, 2.91–3.26 and 1.16–1.32 times higher than CF) and Po (enzyme-P, diesters, 4.08–7.47 and 1.71–2.14 times higher than CF) contents and phosphatase activities, while significantly decreased aromaticity (AI) and recalcitrance indexes (RI) of soil C, compared with CF. The keystone genera in manured soils (Alienimomas and Streptomyces) and straw-applied soils (Janthinobacterium and Caulobacter) were significantly correlated with soil enzyme-P, microbial biomass P (MBP), diesters, and citrate-P. Soil AI and RI were significantly correlated with the phoD keystone and soil P species. It suggested that the keystone was impacted by soil OC stability and play a role in regulating P redistribution in amended soils. This study highlights how manure and straw incorporation altered soil OC stability, shaped the phoD harboring community, and enhanced soil P biological processes promoted by the keystone taxa. The partial substitution of mineral P by mixture of manure and straw is effectively promote soil P availability and beneficial for environmental sustainability.

Metabolomics analysis of the effect of acidification on rhizosphere soil microecosystem of tea tree.

Acidification can seriously affect the growth of tea trees and the yield and quality of tea leaves. In this study, we analyzed the effects of acidification on the physicochemical properties, microorganisms and metabolites of tea rhizosphere soils with different pH values, and the results showed that with the increase of soil pH, the organic matter content, cation exchange capacity, microbial biomass carbon, microbial biomass nitrogen, microbial respiration intensity, bacterial number and actinomyces number in tea rhizosphere soil all showed an increasing trend, while the fungi number decreased. The results of soil metabolite analysis showed that 2376, 2377 and 2359 metabolites were detected in tea rhizosphere soil with pH values of 3.29, 4.74 and 5.32, respectively, and the number of similar compounds reached 2331, accounting for more than 98%. The results of soil metabolite content analysis showed that with the increase of soil pH, the total contents of metabolite of tea rhizosphere soil increased significantly. The results of correlation analysis between physicochemical indexes of soil and microorganisms and soil metabolites showed that physicochemical indexes of soil and microorganisms were significantly correlated with 221 soil metabolites, among which 55 were significantly positively correlated and 166 were significantly negatively correlated. Based on correlation interaction network analysis, 59 characteristic compounds were obtained and divided into 22 categories, among which 7 categories compounds showed a significant increasing trend with the increase of soil pH, while the other 15 categories compounds showed the opposite trend. Based on the functional analysis of characteristic metabolites, this study found that with the increase of soil pH in tea rhizosphere, the diversity and number of soil microorganisms increased, and the cyclic ability of C and N of tea rhizosphere soil was enhanced, which in turn might lead to the enhancement of resistance of tea tree and promote the growth of tea tree.

Analyzing Geotechnical Characteristics of Soils in Erbil via GIS and ANNs

The aim of this study is to analyze and model the geotechnical characteristics of soils in Erbil city using Geographic Information Systems (GIS) and Artificial Neural Networks (ANNs). The study used GIS to analyze the geotechnical properties of soils by collecting data from 102 boreholes in three different depth levels (1.5 m–3.5 m, 3.5 m–6.5 m and 6.5 m–9.5 m) to visualize and analyze soil characteristics such as fines content, moisture content, soil plasticity, shear strength parameters, compressibility, Standard penetration test (SPT), and bearing capacity. The paper also establishes the prediction of SPT-N value and bearing capacity based on geotechnical properties of soils using ANN methods and made correlations between SPT values and shear strength parameters with the bearing capacity of the soil. The results analyzed via GIS indicated that the soil classification was silty clay with a small amount of sandy gravel (CL) in most of the study area. According to the SPT–N values, most of the soils in Erbil City ranged between 33 and 50; a higher SPT value generally indicates denser and stronger soil. The value of the shear strength parameter for the maximum friction angle of the soil layers was found to be 36°, and the predominant cohesion was approximately 100 kPa. The compression index of soils ranged between 0.11 to 0.31. The results showed that the ANN models were able to accurately predict the geotechnical parameters of the soil types in the study area. In addition, the use of GIS and ANN techniques allowed for a comprehensive analysis of the geotechnical characteristics of the soils in Erbil, providing valuable information for future construction and development projects.

Prediction of the Freezing Temperature of Saline Soil Using Neural Network Methods

Freezing temperature is an important physical index of saline soil in permafrost and seasonal frozen area, and it is difficult to be predicted with a formula when saline soil contains multiple salts. In this study, we used a backpropagation neural network (BPNN) and a radial basis function neural network (RBFNN) to predict the freezing temperature of saline soil from the Qinghai–Tibet Plateau and Lanzhou. Several variables (ion content, soluble salt content, and water content) were adopted based on previous studies and experimental conditions. After the above two neural network models were established, the parameters were input into the two models to obtain the predicted values of the freezing temperature. Then, the measured and predicted values were compared to evaluate the accuracy of the two neural network models. Additionally, three statistical indicators were used to quantify the reliability of the two neural networks. Our results showed that BPNN had a stronger ability to predict freezing temperatures. Moreover, the established BPNN model was applied to analyze the sensitivity of the freezing temperature to the content of different ions under two different water content conditions. Finally, it was concluded that the influence of main ions on the freezing temperature in descending order was Cl− &gt; K+ ≈ Na+ &gt; SO42− &gt; CO32− &gt; Ca2+ under the condition of 10% water content, and K+ &gt;Cl− &gt; SO42− &gt; Na+ &gt; CO32− &gt; Ca2+ when the water content was 30%. This study offers a new prediction method for the freezing temperature of multicomponent saline soil and can be used as a reference to investigate the factors affecting freezing temperatures.

Microbiome of abandoned soils of former agricultural cryogenic ecosystems of central part of Yamal region

Microbial activity plays a crucial role in the development and formation of soil properties. The active and abandoned agricultural soils in the Arctic zone represent a valuable resource that can play a crucial role in providing food security in the northern regions. The reuse of abandoned land for agriculture will reduce environmental risks in the context of a changing climate. Therefore, there is a need for monitoring studies to assess changes in soil parameters after long-term abandonment (taxonomic diversity, agrochemical and physico-chemical qualities). In the study, we evaluated the taxonomic diversity of the microbiome in abandoned (postagrogenic) and pristine soils of the Central part of the Yamal region. In the process of taxonomic analysis, more than 30 different bacterial and archaeal phyla were identified. The formation of a specific microbiome associated with anthropogenic influence in post-agrogenic sites has been shown. Most common types of soil microorganisms in samples collected from pristine and postagrogenic soils were Firmicutes (average 26.86%), Proteobacteria (average 23.41%), and Actinobacteria (average 15.45%). Firmicutes phylum was found mainly in the agrocenoses soils, Proteobacteria were mainly described in the mature tundra soils, Actinobacteria in humid conditions. An increase in diversity indices in postagrogenic soils was shown.

Soil quality assessment based on hybrid computational approach with spatial multi-criteria analysis and geographical information system for sustainable tea cultivation

AbstractLong-term intensive tea cultivation is suspected of deteriorating soil quality status and degrading land sustainability. This study aimed to determine the soil quality index of soils in a micro-catchment in Rize Province, Turkey, used for long-term intensive tea cultivation, by means of spatial multi-criteria analysis (SMCA) and standard scoring function (SSF) integrated with geographical information system (GIS) and geostatistics, considering bio-physical-chemical properties of a detailed soil dataset. Soil samples (102) were collected from the surface layer (0–20 cm). In the soil quality index for tea-cultivated soils (TSQI), soil indicators were weighted by an analytical hierarchy. Various indicator units were normalized with the SSF. The TSQI model was divided into five main criteria: (i) physical properties, (ii) chemical properties, (iii) fertility, (iv) biological indicators and (v) soil erosion susceptibility parameters. Principal components analysis (PCA) was applied and minimum dataset (MDS) created to determine the most effective indicators. The spatial distribution pattern of the tea total dataset soil quality index (TSQITDS) and tea minimum dataset soil quality index (TSQIMDS) values were statistically similar. TSQITDS low and very low-class areas accounted for 34.1% of the total area, while TSQIMDS low and very low-class areas constituted 33.6%. These areas, especially those with low soil quality properties, were in the northern and north-western parts of the micro-catchment. TSQITDS very high and high-class areas accounted for 56.2% of the total area, while TSQIMDS very high and high-class areas were found in 55.3% of the total area. These areas are located in the south of the micro-catchment.

A Novel Mine-Specific Eco-Environment Index (MSEEI) for Mine Ecological Environment Monitoring Using Landsat Imagery

The excessive exploitation of mineral resources will lead to environmental pollution, resource depletion, environmental disaster, and other problems. The contradiction between the environment and development, and the management of the ecological environment in mining areas are urgent p-problems to be solved. An ecological environment assessment is an important part of the ecological environment in a mining area. The accurate evaluation of the ecological environment is the premise behind environmental governance in a mining area. However, current ecological assessment indicators were not developed specifically for mine environment monitoring and, thus, cannot provide an effective and comprehensive assessment of the mineral environment. To this end, in order to improve the environmental monitoring performance in mining areas, a novel Mine-Specific Eco-Environment Index (MSEEI) was proposed, integrating factors from five main aspects associated with minerals, including temperature, vegetation, soil moisture, atmospheric environment, and mining scale. Meanwhile, a widely concerned mine—Luanchuan mine—was used as the case area to test the performance of our MSEEI. The results showed a significant correlation between RSEI and MSEEI (p &lt; 0.01). The mean correlation achieved between RSEI and MSEEI was 0.91, which was much higher than the correlations between RSEI and enhanced vegetation index (EVI), soil moisture monitoring index (SMMI), normalized difference built-up and soil index (NDBSI), PM2.5 concentration (DI), and heat (LST). In addition, based on our long-term MSEEI results of Luanchuan mine from 1997 to 2021, the ecological status of Luanchuan mine showed a trend of first declining and then rising. Specifically, the MSEEI first declined from 0.85 to 0.77 between 1997 and 2012, and then rebounded to about 0.8 in recent years. The MSEEI exhibited a good applicability in the ecological assessment of mining areas. Our MSEEI can provide useful guidance for mine environment monitoring. MSEEI can directly reflect the ecological damage after mining, provide scientific guidance for the exploitation and utilization of mineral resources, and promote the protection and sustainable development of Earth’s resources and mine ecological environments.

Effect of Pre-Test Drying Temperature on the Properties of Lateritic Soils.

The properties of residual soils, according to literature, are sensitive to the pre-test drying method given to the sample prior to testing. Similarly, residual soils such as laterites/lateritic soils are formed under various climatic conditions, hence they show different degrees of sensitivity to pretest drying method. This work is therefore carried out to elucidate the influence of pre-test drying temperature or method on the properties of three lateritic soils that developed over three different Pre-Cambrian basement complex rocks from Ado-Ekiti, SW, Nigeria. The soils were subjected to three pre-test drying temperature before conducting laboratory tests. The pre-test drying temperature considered in this study include air-drying, oven-drying at 60° C, and oven-drying at 110° C. Pre-test drying at 60° and 110° C caused particle aggregation (which reduced the soil surface are) and loss of cohesion. Consequently, this reduced the specific gravity, optimum moisture content, clay content, consistency limits, and unconfined compressive strength of the lateritic soils. The maximum dry density and sand content increased as the pre-test drying temperature increases. The pre-test drying temperature did not significantly change the plasticity classification of the soils, however, at higher pre-test temperature the soils become less plastic. The free swell index of the lateritic soils increased with increasing pre-test drying temperature (up to 60° C) before decreasing when the temperature rose to 110° C. This study has revealed the effect pre-test drying temperature may have on the properties of lateritic soils and these may produce soil properties that may not likely indicate the actual field performance of the tested soils.

Changes in salinity, aggregates and physicomechanical quality induced by biochar application to coastal soil

ABSTRACT Coastal clayey soil has a great potential for food production and safety while poor physico-mechanical properties have impeded its sustainable utilization. A field experiment was conducted to assess the influence of biochar on physicomechanical properties of coastal clayey soil. The biochars were applied to the coastal soil with the rate of 0, 1%, and 3% (w/w), respectively. Compared with control treatment, the application of three biochars (at the rate of 3%) had significantly improved soil fertility, i.e. organic carbon, total nitrogen, available nitrogen and available phosphate, respectively. Biochar treatments significantly increased soil porosity, and aggregates stability, while reduced the soil salinity compared to the control treatment. Meanwhile, biochar application significantly increased the plastic index of coastal clayey soil while decreased soil tensile strength and shrink swell properties compared to the control. Biochar clearly altered soil pore characteristics, consequently rebuilding the new ions leaching channels. Overall, the cow manure biochar (650 °C) at the rate of 3% treatment showed maximum efficiency on soil salinity, fertility, physicomechanical properties, and crop yield. The biochar amendment improved coastal soil by ameliorating soil pore space and structure, improving soil tillage operation and rice yield, decreasing salt stress, and reducing mechanical strength.

Development of MLR and variedly optimized ANN models for forecasting the detachability and liquefaction potential index of erodible soils

• DLPI which quantifies soil erodibility potentials, was computed for southern Anambra. • MLR and four ANNs successfully predicted the DLPI of the study area. • Low modeling errors were obtained in the developed MLR and ANN models. • Soft computing algorithms can enhance soil erosion risk assessment and management. Artificial intelligence modeling techniques, such as artificial neural network (ANN) and multiple linear regression (MLR), have been found useful in the prediction of environmental hazard indicators, even in areas with data scarcity. The detachability and liquefaction potential index ( DLPI ) is a numerical model that quantifies soil erodibility potential. This paper aims to design ANN and MLR models that can predict the DLPI of erodible soils in southeastern Nigeria. Feedforward back-propagated ANN models (ANN1, ANN2, ANN3 and ANN4) optimized using different algorithms and output layer activation functions were proposed. To implement the four models, the geotechnical data of the eroding soils, which were used for the DLPI calculation, were utilized. Sixteen geotechnical variables analyzed on the soils were used as input variables. While ANN1 and ANN3 were optimized using scaled conjugate gradient algorithm, ANN2 and ANN4 were optimized using gradient descent algorithm. However, the output layers of the ANN1 and ANN2 were activated using identity function while those for the ANN3 and ANN4 were activated using hyperbolic tangent function. The results of the four models showed high performance with determination coefficient (R 2 ) values of 0.971 (ANN1), 0.998 (ANN2), 0.987 (ANN3), and 0.992 (ANN4). Further, low modeling errors were detected from the residual plots, sum of square errors (0.000-0.024), and relative errors (0.003-0.080); thus, confirming the reliability of the models. The MLR gave a perfect model for the DLPI prediction, with its multiple correlation coefficient = 1.000, R 2 = 1.000, R 2 adjusted = 1.000, and standard error of estimate = 0.000. Therefore, it suffices to say that the ANN and MLR algorithms are suitable for DLPI prediction.

Experimental-Correlative Framework to Evaluate Critical State Deformability Parameters and Free Swelling Index of Cohesive Soils Using Gene Expression Programming

Expansive soils stimulate serious problems for infrastructures and the near surface facilities due to volume change patterns it experiences during the wet and dry seasons. This research study is intended to implement Gene Expression Programming (GEP) scheme and the Multiple Linear Regression (MLR) method in order to assess the swelling aspects and deformability parameters of moderately expansive soils based on a comprehensive exploration and testing program for the Northeastern areas of Zarqa Governate in Jordan. Representative soil samples have been collected from twenty different locations in the area. The soil has been tested for free swelling, matric suction, permeability, consolidation, water content, hydrometer, and soil index properties. The free swelling index and critical state deformability parameters, obtained from the consolidation test, are the primary focus of this research. Several models that account for different situations based on opportunities of the data availability using an extensive GEP modeling scheme have been successfully developed. MLP method has been managed to develop one reasonable formula with less efficiency than the ones schemed by GEP procedure. The successful models have been validated using test results and error analysis procedures. The models have been ordered according to their according to a proposed ranking procedure. GEP method has showed higher performance for the given conditions.

Dust source clay content and salinity estimation using VNIR spectrometry

The spectral behavior of soil will change through degradation, which makes it difficult to retrieve soil properties using previously developed models. This study aims to use linear [including partial least squares regression (PLSR) and ratio soil index (RSI)] and nonlinear [including partial least squares-backpropagation neural network (PLS-BPNN) and partial least squares-random forest (PLS-RF)] models to estimate soil electrical conductivity (EC) and clay content in dust sources. For this purpose, 142 soil samples were collected in Khuzestan province. After laboratory spectroscopic analysis, the area and depth of diagnostic absorption features (AFs) of continuum removed (CR) spectra were calculated. The results revealed that with increasing clay content, the depth of AFs at 1400, 1900, and 2200 nm will increase. Meanwhile, an increase in the soil salinity will increase the depth and area of AFs in 1450 and 1915 nm and decrease the depth and area of AF in 2200 nm. Spectral ranges of 2100–2300 and 1400–1600 nm were identified as the most important portions of the visible and near-infrared spectrum for analyzing clay content and EC, respectively. The RSI method performed poorly in soil salinity and clay content estimation. PLSR and PLS-RF methods overestimated clay content and salinity in low values. The PLS-BPNN model had the best performance for estimating clay content (RPIQ = 4.51) and EC (RPIQ = 4.76). Considering the expected non-linear relationship between soil properties and corresponding spectral reflectance, the results of this study were acceptable.

IMPROVING CLAY SOIL STABILITY WITH THE ADDITION OF RICE HUSKS THROUGH CHEMICAL METHODS

Soil stability is a mixture of soil with a certain material, the aim is to improve the technical properties of the soil so that it can technically meet certain requirements. Soil stability is a mixture of soil and other materials, for the purpose of achieving the correct gradation, so that the technical properties of the soil are better. Chemical stability is the addition of chemical elements to the clay with the addition of other ingredients, namely rice husk ash (ASP), so that a physical change is achieved and a change in the physical properties of the soil occurs, with an increase in the size of the soil load capacity (CBR). This study aims to obtain the appropriate variable for adding rice husk ash to the stability of clay as a stabilizer seen from the unconfined compressive strength test to obtain a capacity value of high load. The research method was carried out by testing the properties of soil index, soil compaction tests (standard proctor) and unconfined compression strength tests (Unconfined Compression Strength) in the laboratory. 200 with variations of 5%, 10% and 15%. Index property tests such as water content tests refer to ASTM D2216:2010, Sieve Analysis (ASTM D-422), Atterberg Limit, Liquid Limit (LL) (ASTM D-4318), and Specific Gravity (Gs) (ASTM D-854). Soil mechanical properties test (proctor standard) (ASTM D 698), free compression resistance test (ASTM D 2166). The conclusive results show that the free compressive strength value increased in the mass without hardening with a 10% husk ash percentage of 1.0005 kg/cm2 and a Cu value of 0.502 kg/cm3. While the results of the free compression strength test with curing for 24 hours, the highest bearing value occurred, in the original soil variation of 1.000 kg/cm3 and a Cu value of 0.500 kg/ cm3. For the value of the free compressive strength, there is a decrease, namely at variations of 5%, 10% and 15% with a time of 24 hours.