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The positive influence of surface compost application without incorporation on soil physical properties is known but remains underexplored. This study evaluated the effects of surface-applied stable and mature compost on basic soil physical and chemical properties, including saturated hydraulic conductivity, aggregate stability, and penetration resistance. Conducted as a semi-operational field experiment in two Czech agricultural sites (A: Blatnice at Jaroměřice and B: Jevíčko; Cambisols with loam and silty clay loam textures, respectively), the plots were treated with compost (SCA) at rates of 4 × 30 t/ha (A) and 1 × 200 t/ha (B) or left untreated as controls (CON). The crops were wheat (A), maize (A, B) and intercrops. Surface compost application began in 2022, and soil sampling and field measurements were conducted during the 2023 and 2024 growing seasons. Results showed significant positive changes (P < 0.05 or lower) in SCA plots compared to CON. Soil organic matter content increased by 27.8% at locality A and by 58.1% at locality B, while saturated water content increased by 5.3% (A) and 11.0% (B) in the latter season. Similarly, pH and electrical conductivity showed increases. Water-stable aggregate ratios increased by 6% to 30% at both localities. Dry bulk density decreased by 10.5% (A) and 15.7% (B). Improvements in saturated hydraulic conductivity (by 28.6%) and penetration resistance were observed only at locality B. These findings show the potential of surface-applied stable and mature compost to enhance soil properties effectively.

Most studies of agroforestry system biodiversity focus on assessing visible, aboveground biodiversity, largely ignoring soil biodiversity. To fill this gap, a preliminary assessment of soil biodiversity in an agroforestry system was undertaken based on changes in soil enzyme activity. The study was conducted in the village of Maziarnia, Lubelskie Voivodeship, Poland, Europe. Arable fields with spring wheat, mid-field trees and perennial mixed forest were selected for the study. Soil material for physicochemical analyses (pH_H2O, pH_KCl, sorption properties, total carbon and total nitrogen) and biochemical analyses (activity of acid phosphatase, alkaline phosphatase, urease and dehydrogenases) was collected in the spring and autumn of 2022. The present study showed that the biochemical properties of the soils of the selected study sites varied depending on the type of ecosystem determining habitat conditions. Each ecosystem that makes up the agroforestry system studied is characterised by a distinctive microbiome composition and its own level of enzymatic activity. The obtained results support the thesis that agroforestry systems significantly increase the functional diversity and overall biodiversity of agricultural landscapes. However, a full, objective characterisation of the processes taking place in agroforestry systems requires long-term monitoring.

Soil is a valuable resource for food production, and it demands a long time to recover itself. Soil erosion is one of the most important issues for countries based on agriculture. This review article analyzed articles published on the topic of general soil erosion in Central Asian countries in 1993–2022. More than 50% of the articles reflect the results of the conducted practical work. The main content of these scientific works is aimed at the prevention of erosion processes, their evaluation and the development of countermeasures. During the considered period, the number of publications on soil erosion has increased in the last years compared to the first years, which indicates that the attention to the topic has increased in recent years. The purpose of this article is to get accurate information about the state of soil erosion in the countries of Central Asia and to get acquainted with the practical works carried out against erosion in these countries. For this aim, the contents of the articles were reviewed and the results of the scientific works conducted on the topic of erosion in each country were presented. According to the content of the articles, the use of modern techniques and technologies in the evaluation and prevention of soil erosion gives effective results.

Open-cast coal mining presents a big global issue because of the large areas the mines occupy, which get entirely changed. Their ecosystems lose most of their functions, and a huge amount of fertile soil gets utterly destroyed. Reclamation is a process of returning the functions of the soil after the excavation is finished, most commonly achieved by establishing vegetation, which can sometimes be very difficult. This happens due to the physical, chemical and biological changes that occur on these sites, which are described in this paper. Also, some directions for mitigating these problems are given. Once the vegetation is successfully introduced, natural cycles that were compromised by the mining are established once again, and the process of soil formation begins. Some trends and problems related to pedogenesis research on reclaimed mine sites are presented and discussed, along with presumptions of how the process of soil formation evolves on afforested clayey Technosols of central Europe. The potential future research which would confirm these presumptions is discussed, with the emphasis on the need of research performed on older reclamation sites, as well as sites with similar ecological conditions and different tree species cover.

Soil erosion resistance is influenced by intrinsic soil properties and multiple external factors. This study investigated the effect of tea planting age on soil resistance to flowing water erosion (reflected by rill erodibility (K_r) and critical shear stress (τ_c)) in Three Gorges Reservoir Area. One slope farmland (as the control) and five tea plantations cultivated for 3 to 34 years were selected for sampling sites. The results indicated that bulk density (BD), soil cohesion (Coh), water stable aggregate (WSA), mean weight diameter (MWD), soil organic carbon (SOC), litter density (LD), and root mass density (RMD) increased generally with tea planting age. Compared to the control, K_r of tea plantations reduced by 71.1%–85.3%. The temporal variation in soil erosion resistance was controlled greatly by the variations in most near-surface characteristics. K_r decreased with WSA, Coh, LD, RMD, and SOC following a power function (P < 0.01); τ_c increased with MWD, LD, RMD, and SOC as an exponential function, with BD a power function, and Coh a logarithmic function (P < 0.01). In this study, K_r could be simulated well by WSA and LD with a power function, and τ_c could be simulated well by MWD and RMD with an exponential function.

Reliable indicators of early soil biological change remain limited in tropical agroecosystems, where soil organic carbon (SOC) stocks may respond more slowly than microbial processes. We evaluated whether seasonal vegetation dynamics derived from Sentinel-2 fractional vegetation cover (FVC) are associated with spatial variation in SOC stock and microbial indicators in Jembrana, Bali, Indonesia. We mapped seasonal FVC from 2019 to 2024 and derived site-level metrics of mean cover and temporal variability (standard deviation, anomaly, coefficient of variation, and a temporal stability index). In July 2023, we sampled topsoil (0–30 cm) at 12 sites representing contrasting land uses and topographic settings. We calculated SOC stock from organic carbon concentration, bulk density, and sampling depth, and measured basal respiration and culturable microbial density (colony-forming units, CFU). Vegetation cover peaked consistently during the wet season (December to February), and mean site FVC ranged from 0.31 to 0.99. Mean FVC showed positive but non-significant associations with culturable microbial density (Spearman’s ρ = 0.48, P = 0.114) and basal respiration (ρ = 0.29, P = 0.361), whereas higher vegetation variability metrics tended to coincide with lower culturable microbial density (ρ = –0.43 to –0.51, P = 0.090 to 0.163). SOC stock showed near-zero coefficients and no statistical evidence of association with vegetation metrics (ρ = 0.09, P = 0.781) or microbial indicators (ρ = 0.01, P = 0.975). Principal component analysis of FVC traits explained 99.65% of the variance and separated sites along a gradient from stable, high cover to more variable, lower cover. Overall, FVC stability metrics captured spatial differences that were directionally consistent with microbial indicators, but associations were not statistically significant in this dataset (n = 12). Larger, replicated studies with repeated soil sampling are required to evaluate whether seasonal FVC metrics have robust predictive utility for SOC stock and soil biological indicators.

Sorption of organic contaminants in soils and sediments is a crucial factor affecting their mobility in the vadose zone environment. Freundlich sorption isotherms were evaluated for six micropollutants identified in areas irrigated with river-water and sixteen soils. The highest Freundlich sorption coefficients, K_F, were obtained for 1,3-diphenylguanidine (11.6 ± 5.0 cm^3/nμg^1−1/n/g) followed by triethyl citrate (4.57 ± 4.91), 4-acetamidoantipyrine (1.43 ± 0.24), 6 : 2 fluorinated telomer sulfonate (1.18 ± 0.42), benzo(d)thiazole-2-sulfonic acid (1.12 ± 0.33), and naphthalene-2-sulfonic acid (0.28 ± 0.17). The K_F values for the individual compounds were correlated with soil properties. Multiple linear regressions were used to derive equations for predicting the K_F values using the soil properties. Sorption of cationic molecules was positively affected by cation exchange capacity or clay content, indicating strong sorption of cations on negatively charged sorption sites. Sorption of anionic molecules was positively correlated with organic carbon content and wettability index, suggesting hydrophobic interactions with soil organic matter. Anion sorption was also positively influenced by magnetic susceptibility, which could indicate sorption of anions on the positively charged sorption sites. Sorption of acids was in some cases also positively affected by cation exchange capacity, which could imply their sorption via cation bridges.

This study aims to compare the chromium (Cr) mobility in two soils with different Cr sources. The first one is an anthropogenically contaminated soil from an area of a piston ring production factory, and the second one is a serpentine soil with a naturally increased Cr level from the National Nature Reserve Mohelno serpentine steppe in the Czech Republic. To assess the influence of naturally occurring environmental factors on the Cr mobility, two sets of column leaching experiments were constructed, namely an acidified water treatment (AW) and a simulated root exudate treatment (SRE). It was found that the anthropogenically contaminated soil leached out many times more Cr for both (the AW and SRE) treatments in comparison with the serpentine soil. Generally, all the samples showed enhanced leaching from the bottom layer, respectively the horizon, for both treatments. Only the anthropogenic soil showed some differences in the bottom layer, which was more susceptible to the AW treatment than to the SRE one. These findings show the high dependence of the leachability of Cr on the Cr content origin. It has been proven that naturally enriched sites where elevated levels of Cr originate from the bedrock are more resistant to Cr leaching than anthropogenically contaminated soils. Feasible causes of these differences are discussed in this study.

Forest soils have a high potential to store carbon and thus mitigate climate change. The information on spatial distribution of soil organic carbon (SOC) stocks is thus very important. This study aims to analyse the importance of environmental predictors for forest SOC stock prediction at the regional and national scale in the Czech Republic. A big database of forest soil data for more than 7 000 sites was compiled from several surveys. SOC stocks were calculated from SOC content and bulk density for the topsoil mineral layer 0-30 cm. Spatial prediction models were developed separately for individual natural forest areas and for four subsets with different altitude range, using random forest method. The importance of environmental predictors in the models strongly differs between regions and altitudes. At lower altitudes, forest edaphic series and soil classes are strong predictors, while at higher altitudes the predictors related to topography become more important. The importance of soil classes depends on the pedodiversity level and on the difference in SOC stock between the classes. The contribution of forest types as predictors is limited when one (mostly coniferous) type dominates. Better prediction results can be obtained in smaller, but consistent regions, like some natural forest areas.

The estimation of the level of the soil organic carbon (SOC) content plays an important role in assessing the soil health state. Visible and Near Infrared Diffuse Reflectance Spectroscopy (Vis-NIR DRS) is a fast and cheap tool for measuring the SOC. However, when this technology is applied on a larger area, the soil prediction accuracy decreases due to the heterogeneity of the samples. In this paper, we first investigate the global model performance in the LUCAS EU-wide topsoil database. Then, different clustering strategies were tested, including the k-means clustering based on the principal component analysis (PCA) and hierarchical clustering, combined with the partial least squares regression (PLSR) models, and a clustering based on a local PLSR approach. The best validation results were obtained for the local PLSR approach with R² = 0.75, root mean squared error of prediction (RMSEP) = 13.38 g/kg and ratio of performance to interquartile range (RPIQ) = 2.846, but the algorithm running time was 30.05 s. Similar results were obtained for the k-means clustering method with R² = 0.75, RMSEP = 14.61 g/kg and RPIQ = 2.844, at only 4.52 s. This study demonstrates that the PLSR approach based on k-means clustering is able to achieve similar prediction accuracy as the local PLSR approach, while significantly improving the algorithm speed. This provides the theoretical basis for adapting the spectral soil model to the needs of real-time SOC quantification.

This study aimed to examine the changes in selected soil properties at Lítov spoil heap (Sokolov, Czech Republic) and compare the current situation with the situation described twenty years ago. A total of 110 soil samples were taken at Lítov at the same sites as in 1998. The analyses of basic soil characteristics involved: exchangeable soil pH (pH_KCl), organic carbon content (C_ox), quality of humic substances (A_400/A₆₀₀), exchangeable acidity (E_a), and two types of aluminium contents in the soil. Changes in all soil characteristics between 1998 and 2018 were statistically evaluated, compared, and visualized using Geographical Information Systems (GIS). We have observed an increase of pH_KCl, C_ox and a slight improvement in humus quality compared to the results from 1998. The temporal changes of soil characteristics were evident in the whole area, and the influence of reclamation methods was also pronounced. Soil development close to the regional common natural conditions was found in the area where agricultural reclamation measures (i.e., covering with topsoil) were carried out. Furthermore, afforestation – mainly by deciduous trees – supported the improvement of soil characteristics favourable for plant growth. High pyrite content and marshland were identified as the main causes that led to vegetation cover mortality.

This work presents the advantages and risks of selected soil quality criteria using data from the monitoring of agricultural soils in the Czech Republic. Soil samples were taken from 71 sites covering various soil types. Basic soil parameters and mid-infrared spectra were measured. Indicators describing the quality of soil organic matter (SOM), and soil were calculated. The results show that soil types differ significantly in the qualitative indicators of soil organic matter. More acidic soils with lower clay content contain lower proportions of aromatic and higher proportions of aliphatic organic compounds than neutral soils with higher clay particles content. These soils differ little in total carbon content and C/N ratio but considerably in C/clay ratio. Cambisols are the least degraded soils in the Czech Republic in terms of C/clay ratio, which is controversial in many respects. The results indicate that more aliphatic organic matter is important for the SOM content in the upper part of the agricultural soil, and more aromatic organic matter is mainly bound to the clay fraction. The results raise questions about the suitability of uniform C/clay target values proposed in European legislation as a criterion for assessing soil degradation due to carbon loss.

Strip tillage is a very popular form of conservation tillage that is used in places with a higher risk of soil erosion. It is commonly accepted that strip tillage reduces the effects of water erosion; however, the exact way this effect is produced is very hard to quantify. This study focuses on the way strip tillage influences soil moisture and the way it changes with different intensities of rainfall, in comparison with conventional tillage. This study was conducted near Petrovice, Středočeský kraj, Czechia, over the course of four years (2021–2024). The conditions of all four test sites were comparable, both in terms of slope and soil type present. The soil moisture of strip tillage in a depth of 15 cm was changing differently in comparison with conventional tillage. During lower intensity rainfall events, the soil moisture of the strip tilled plot changed significantly less in comparison with conventional tillage. On the contrary, when more intense precipitation occurred, the soil moisture in the strip-tilled plot responded with significantly higher changes in comparison with conventional tillage. Soil drying after precipitation was also studied, with the speed of drying of strip tillage being higher than that of conventional tillage. These findings help better understand the changes strip tillage introduces into the soil and to the crops it is used with.

Climate change has increased attention paid in the research to forest soils and tree species composition, in respect to the potential for carbon sequestration. It is known that forest stands are able to store soil organic carbon (SOC), but little is known about the effect of forest naturalness on SOC content. This is important in relation of dying of unnatural spruce stands. It is necessary to determine a suitable composition of tree species which will replace them. This research is based on 248 plots with oak, beech, and spruce stands and mixtures of these species, with measured values of SOC. Our results show that autochthonous and mixed stands, in terms of tree species composition, in the study area had a higher SOC content than allochthonous and pure stands. In addition, it was found that autochthonous oak and beech stands, especially in mixtures, had a higher SOC content than allochthonous spruce stands (monocultures). On the basis of the presented results, it is possible to optimize the future tree species composition of stands in the study area, which currently have an allochthonous representation of spruce, to provide better function of carbon sequestration and resistance to climate change.

Soil pore is an important part of soil structure. According to the causes of formation, soil pores can be divided into biological pores formed by animal movement and plant root development and non-biological pores formed by dry-wet and freeze-thaw alternation or artificial tillage. The soil pore structure affects the migration of water, gas, nutrients and so on in the soil, especially the macropores can also produce water or solute preferential migration. Studying soil pores is of great significance for predicting soil hydraulic properties, reducing groundwater pollution and soil nutrient loss. Based on previous studies on soil pore structure, this paper systematically summarized the role of soil pores, influencing factors and the advantages and disadvantages of various research methods. This paper not only introduces traditional methods (including direct and indirect methods), but also summarizes the new research on soil pores combined with computed tomography (CT) technology and other science and technology in recent years. Finally, the prospect and development trend of soil pore research in the future were predicted, so as to provide reference for further research on soil pore structure.

The paper proposes a new soil evaluation system using the principle of the Saaty method. The Saaty method has been modified and named Soil Assessment System (SAS). Significance weights are assigned to individual soil characteristics (indicators). This provides a more detailed differentiation of the significance of the indicator on soil quality and a more accurate assessment, especially in marginal cases where the assessment by the methods used so far has not been fully conclusive. In addition to physico-chemical properties, other criteria are taken into account to assess not only productional but also non-productional functions. The possibility of using indicators referring to a broader context (e.g., soil sealing value) is also important, thus enabling a comprehensive assessment of the quality of the land. This results in points for individual sampling locations. Soils are categorized according to the number of points and results are shown on maps.

Preferential water flow in soil significantly affects runoff, water infiltration, storage, groundwater environment, and soil stability. Plant roots positively affect preferential flow development. This study explored the relationship between the root system of Paulownia fortunei (Seem.) Hemsl. and preferential flow using dyeing tracer test and image analysis techniques. A typical red soil hilly region on the outskirts of Guilin City (Guangxi, China) was selected as the study area. A Bright Blue solution was used to visualize the pathways followed by the infiltrated water in simulated rainfall experiments, and Image Analyzer of Plants was used to analyze the root length, surface area, and volume. The results revealed significant differences in the root surface area density of coarse roots (RSAD-CR) and length index of preferential flow (LI) among soil profiles at various distances from the tree trunk. The root volume density of coarse (RVD-CR) and total roots (RVD-TR), the root length density of coarse roots (RLD-CR), and RSAD-CR were significantly correlated with the characteristics of dyeing morphology. Conversely, the root length density and root surface area density of fine (RLD-FR and RSAD-FR, respectively) and total roots (RLD-TR and RSAD-TR, respectively), and the root volume density of fine roots (RVD-FR) were not significantly correlated with the characteristic parameters of dyeing morphology. The root systems of P. fortunei were critical for enhancing soil water infiltration and developing preferential flow in red soil hilly regions. Coarse roots had a greater impact on the development of preferential flow than fine roots, and root volume had a greater influence on preferential flow development than root length and root surface area. This study contributes to a better understanding of the hydrological cycle at the plant-soil interface in red soil hilly regions.

Soil salinization is one of the most widespread soil degradation processes, especially in arid and semi-arid regions. In such climatic conditions, soluble salts accumulate in the soil, leading to deterioration in soil properties and ultimately reduced crop yield. The purpose of this study was to analyse the relationship between the level of soil salinity and the main spectral indicators obtained from Landsat satellite data. The studied area was the Maisky district, which is located in the southeastern part of the Pavlodar region of Kazakhstan. The variants of the research were agricultural lands using sprinkler irrigation and flood irrigation, as well as sites without irrigation. To analyse the relationships, we used the normalized difference vegetation index (NDVI), salinity indices (SI) and soil indices such as SI 1, SI 2, SI 3, SI 4, normalized difference salinity index (NDSI), soil adjusted vegetation index (SAVI), and brightness index (BI). The normalized difference salinity index (R-NIR)/(R + NIR), using a quadratic statistical relationship, showed the best correlation with the laboratory data. The vegetation index NDVI showed the weakest correlation due to dryness or poor crop growth. As a result of the lack of clear control over irrigation and agrotechnical measures, the indicators of cation exchange capacity in irrigated plots using the flooding method were higher than in other irrigation methods. During irrigation, it is necessary to ensure clear rules, according to which the supplied water and fertilizers will have a positive effect on the soil and the entire agroecosystem. The methods used in this research can be useful in mapping and studying saline soils using satellite data in natural and climatic conditions of arid and semi-arid regions.

Erratum in: Soil & Water Res., 20: 69. Doi: 10.17221/2/2025-SWR

Soil organic matter and pores distribution within aggregates were studied using X-ray computed tomography (XCT; Nikon XT H 225ST and GE Phoenix L240) and advanced 2D/3D measurements by the digital Keyence VHX-6000 microscope (Japan). A new methodological approach with computed tomography involvement for studying the spatial arrangement of pores, porosity, and soil morphology is presented. Changes in studied parameters are documented along the transect of intensively used Haplic Chernozem. Soil disturbance due to erosion and colluvial soil profile formation is reported. Moreover, soil organic matter quality and aggregate stability were evaluated. Obtained results showed statistically significant differences between the control and eroded sites and between eroded and accumulated sites. The correlation coefficients were the highest for soil organic carbon (SOC) and humic substances C_HS (r = 0.805) and C_HS and C_HA/C_FA (r = 0.764). The highest porosity, aggregates stability and coefficients stability were confirmed on the eroded site. The computed tomography measurements also document the high disturbance of Haplic Chernozem on the control site and the newly formed profile of Colluvisol. Despite excellent complementary technique further research is necessary to improve micro-XCT resolution and capacity for the soil micromorphological study.

This study was conducted to find out the seasonal evapotranspiration (ET_c) and crop coefficient (K_c) for walnut trees (ages one to nine) that were grown with drip irrigation in Türkiye’s semi-arid climate. Three different irrigation levels were applied at five-day intervals based on cumulative Class A pan evaporation using irrigation treatment coefficients (K_t = 0.75, 1.00, and 1.25) during the 2015, 2016, 2017, 2018, 2019, 2021, 2022, and 2023 growing seasons. The amount of irrigation water applied to the treatments varied from year to year according to the measured Class A pan evaporation amounts. The total amount of irrigation water applied to the treatment subjects varied between 371.7 mm and 619.6 mm as an average of eight years. Total ET_c of walnut trees varied over the years depending on the applied irrigation water and measured rainfall. The total evapotranspiration estimated from the I₂ treatment, representing the irrigation regime in which 100% of Class A pan evaporation was applied, fluctuated between 676.5 and 585.9 mm over the study years. The daily reference evapotranspiration (ET₀) values are calculated as between 1.85 and 7.07 mm/day. The K_c values for walnut trees were calculated as 0.55 for April, 0.71 for May, 1.02 for June, 1.07 for July, 1.01 for August, and 0.74 for September on average. The research revealed that seasonal evapotranspiration and plant coefficient values can assist in calculating the water requirements of walnut trees and improve water management in semi-arid regions.

More than 50% of agricultural land is threatened by water erosion in the Czech Republic. With respect to soil erosion, maize (Zea mays L.) belongs to the most problematic crops; one of the possibilities to increase protection against erosion is intercropping. In this study, we attempted to find out the effects of individual intercrops and their mixtures (sown 4-6 weeks after sowing maize) or a mixed culture (maize plus lupine) on the soil losses and surface runoff in the period 2019-2021. The study was realised in a sugar beet growing region (Haplic Luvisol); a field rainfall simulator was used. From the used variants with Lolium perenne L., Trifolium repens L., Vicia villosa Roth, Lolium multiflorum Lam., Festuca arundinacea Schreb., Triticum aestivum L. or a mixture (Vicia villosa plus a Trifolium hybrid diploid), the variants with Lolium perenne, Lolium multiflorum, Vicia villosa or Vicia villosa plus the Trifolium hybrid diploid, established between the maize rows (hybrid maize, cultivar Walterinio) on May 27, were the most efficient in case of both the soil losses and runoff reductions in the year 2019. For example, Triticum aestivum between the maize rows mostly reduced the soil losses and the surface runoff was similar (or higher) compared with the control (maize without any intercrop). The variant with Trifolium repens had mostly higher (or similar) soil loss values (compared with the control); in this variant, the runoff was lower compared with the control. We proved our hypothesis with regards to the higher reduction in the soil losses than with the runoff in the variant with Lolium perenne. The results from the years 2020 (the used variants with Lolium multiflorum, Secale cereale L., Trifolium incarnatum L., Phacelia tanacetifolia Benth., Lolium multiflorum plus Trifolium incarnatum, Lolium multiflorum plus Vicia pannonica Crantz) and 2021 (the variants with Lolium multiflorum, Lolium multiflorum - early sowing, Secale cereale, Trifolium incarnatum, Phacelia tanacetifolia, Lolium multiflorum plus Trifolium incarnatum, a mixed culture = maize plus Lupinus albus L.) showed the variants with Trifolium incarnatum, the mixture (Lolium multiflorum plus Trifolium incarnatum), Phacelia tanacetifolia (in the year 2020) or the mixture (Lolium multiflorum plus Trifolium incarnatum) and a mixed culture (maize plus Lupinus albus) (2021) had the most positive effect - the soil loss and surface runoff values were lower when the maize was > 2 m compared with the maize < 1 m. The results obtained in the period 2019-2021 showed the grasses were the most efficient in decreasing the soil losses when the maize was < 1 m and when the maize was > 2 m with the used mixtures.

Soil and water losses in purple soil area is becoming an increasingly severe problem, bringing enormous challenges to environmental protection in rural areas. In this study, simulated rainfall experiments were conducted to analyse the effects of rainfall and the slope conditions on the soil and water loss. Purple soil from a typical slope in the Beibei District of Chongqing was selected as the experimental soil. Twenty rainfall scenarios with varying rainfall intensities and slope conditions were created in the simulation. The results indicate that the runoff initiation time shortened with an increased rainfall intensity and slope gradient. There was a logarithmic relationship between the effect of the rainfall amount on both the runoff intensity and sediment yield intensity. Generally, both the runoff and sediment yield showed a positive linear relationship with the rainfall intensity under different slope gradient conditions. In terms of the same rainfall intensity, both the runoff intensity and sediment yield intensity increased with the slope. Furthermore, a critical slope gradient for the soil and water loss was found between 20° and 25°. This study aimed to provide a reference for soil and water conservation research in a purple soil area.

Machine learning can handle an ever-increasing amount of data with the ability to learn models from the data. It has been widely used in a variety of disciplines and is gaining increasingly more attention nowadays. As it is challenging to map soil and hydrological information that are characterised with high spatial and temporal variability, applications of machine learning in soil science and hydrology (AMLSH) have become popularised. To better understand the current state of AMLSH research, a scientific and quantitative approach was performed to statistically analyse publication information from 1973 to 2021 archived in the Scopus database using scientometric analysis tools, including VOSviewer, CiteSpace, and the open-source R package “bibliometrix”. The results show a significant increase in the number of publications on AMLSH since 2006. The major contributions were identified based on country origins (China, the USA, and India), institutions (Hohai University, Islamic Azad University, and Wuhan University), and journals (Journal of Hydrology, Remote Sensing, and Geoderma). The keywords analysis of the AMLSH research demonstrates four research hotspots: neural network, artificial intelligence, machine learning, and soil. The most frequently utilised machine learning (ML) methods are neural networks, decision trees, random forests and other methods for image processing and predictive analysis. McBratney et al. 2003 is the most highly cited article. Our research sheds light on the research process on AMLSH and concludes with future research perspectives.

The establishment of the reference ambient background concentrations (ABCs) and quality reference values (QRVs) for trace metal (TM) concentrations in soils are required for the environmental assessment and any implementation of a protective action. This information is lacking for soils of the eastern Mitidja plain, which is an important agricultural production area in Algeria. Data for the aqua regia extractable Cd, Cr, Cu, Fe, Ni, Pb and Zn concentrations from 180 composite topsoil samples taken across the Mitidja plain in a stratified random pattern were statistically analysed. Descriptive statistical methods and linear regression equations were applied to determine the upper limit of the ABCs for the TMs. After removal of outliers, the derived QRVs were: Cd 0.24, Cr 62.1, Cu 99.3, Fe 45 590, Ni 47.7, Pb 33 and Zn 115 mg/kg. Iron is a macro element in the soils, but is included as its concentration can be used to normalise the concentrations of the other elements. The derived QRVs are similar or less than those reported for other regions of the world, apart from Cu, where a wide range (36 to 206 mg/kg) is reported. These reference values can be used to identify areas that may require follow-up surveys or to identify priority sites for decision making.

The development and provision of soil spectral library (SSL) could facilitate the application of near infrared (NIR) spectroscopy for economical, accurate, and efficient determination of soil organic matter (SOM). In this work, the performances of partial least squares regression (PLSR) and convolutional neural network (CNN) combined with the datasets of Zhejiang provincial SSL (ZSSL) and the feature subset (FS) were compared for the prediction of SOM at the target field. The FS dataset was chosen from ZSSL based on similarity to the spectral characteristics of the target samples. The results showed that compared with modelling using ZSSL, modelling using FS can greatly improve the prediction accuracy of the PLSR model, but the impact on the performance of the CNN model was limited. The method of mean squared Euclidean distance (MSD) was an effective way for determining the optimal spiking sample size for the PLSR model only using the spectral data of the spiking subset and the prediction set. The PLSR model combined with the FS dataset and the spiking subset determined by MSD achieved the optimal prediction results among all developed models, which is an accurate and easy-to-implement solution for the SOM determination based on ZSSL.

The aim of this study is to present the seasonal variation of organic matter (OM), total organic carbon (TOC), total nitrogen (TN), and total phosphorus (TP) in the bottom sediments of Marchica Lagoon, a post-restorated lagoon located in the Moroccan Mediterranean, and to estimate the potential role of the geochemistry and granulometry of bottom sediments in the retention of old eutrophication. The organic index of bottom sediment was found generally higher in old-eutrophic and enclosed areas. The surface sediments show variable levels of OM, TOC, TP, and TN; high in some cases (12.3%, 6.71%, 0.70%, and 0.30% respectively). These high levels were recorded in the central part of the lagoon and in areas subjected to high anthropogenic pressure, including wastewater discharges. Our results indicated that sediments are an excellent immobilizer of organic matter (C, N, and P), although, there was no correlation between sediment grain size and organic matter content. The absence of correlation might be explained by currentology and hydrodynamics, but also by the bathymetry of the lagoon. Therefore, sediments must be implicated in any lagoon restoration strategy and the site development plan.

Soil organic carbon (SOC) and clay, as indicators of soil fertility, are mainly used to determine the ability of soil to retain water and store the nutrients that are necessary for plant growth. However, the distribution of SOC and clay is influenced by topography and land-use. In the present study, the relationships between SOC, clay, altitude, and slope in the topsoil of two different districts in the Czech Republic including the Liberec (71 samples) and Domažlice (67 samples) districts were investigated. To analyse the relationships between slope and SOC, linear regression was used. Results showed that SOC content increased when slope, clay, or altitude increased; however, there were no significant correlations between SOC and clay in both districts. Clay increased with decreasing slope, but clay and altitude were not correlated well in both areas. Then, study areas were divided into three land-use types including arable land, forest, and complex system of agriculture, parcels, and forests. Consequently, the correlations between SOC and slope and clay and slope were generally improved, indicating the importance of land-use on SOC and clay content. Additionally, using multiple regression with several topographic factors can provide a better prediction of SOC and clay content in each land-use for both districts, indicating the complex effects of topography on SOC and clay.

Knowledge of the issue of water movement in the soil is the basis for agricultural activity, but also for many other sectors. One of the basic indicators that is evaluated in soil science is the rate of water infiltration into the soil. The article specifically states how soil texture and soil moisture affect the rate of water infiltration. The results show that changes in water infiltration can be significant and certain trends can be traced. The rate of water infiltration into the soil is most affected by the sand fraction (soil particles 0.05–2 mm). The higher the percentage of these soil particles in the soil, the lower the changes in infiltration rate depending on the degree of saturation. The article further evaluates soil moisture in relation to texture. The results were obtained at several research locations within the period 2014–2021 in the territory of the Czech Republic. The above findings are primarily applicable to the region of Central Europe or can be used as comparative values for regions in the rest of the world.

Advancements in technology have recently enabled to assess soil aggregate stability (SAS) using digital devices. To address the need for a faster and more efficient method of measuring SAS, we have developed a simple yet effective approach using a specialized device. The innovative method named SlakeLight involves measuring the changes in light transmittance as aggregates undergo slaking. The device consists of the measuring chamber, which is placed on a LED light source with a surface-homogeneous distribution of luminosity. During the disintegration process of aggregates immersed in water, reduction in the light emitted to the photodiodes is proportional to SAS. The functionality of the device was tested using topsoil samples from two field fertilization trials. The recorded SAS_trans values were compared with the wet sieving method (WSA) and SLAKE test. The new method showed a strong correlation with both reference methods (r = 0.89 for WSA, r = –0.86 for SLAKE). The device was able to detect a statistically significant differences in SAS between the grassland and the cropland at both sites. Although differences in SAS_trans were not significant between different fertilization treatments unlike WSA, the simplicity and speed of the measurement increase the potential of the method for practical implementation in agriculture, surpassing the limitations of traditional and labor-intensive laboratory techniques.

Forest headwater streams serve as critical interfaces between terrestrial forests and downstream aquatic ecosystems, playing essential roles in the storage and movement of carbon (C) and nutrients. However, despite their importance, our understanding of the dynamics of plant litter calcium (Ca) and magnesium (Mg) stocks within these streams remains limited. In this study, we conducted a quantitative analysis of the spatiotemporal dynamics of plant litter Ca and Mg concentrations and stocks in a subtropical forest headwater stream from March 2021 to February 2022. We found that: (1) the average concentrations of litter Ca and Mg were 9.9 and 0.7 mg/g, respectively, with mean stocks of 8 792.3 and 620.8 mg/m², respectively; (2) significant variations in litter Ca and Mg concentrations were observed among non-woody debris (13.1 and 0.9 mg/g), fine woody debris (9.0 and 0.5 mg/g), and coarse woody debris (6.1 and 0.4 mg/g), though plant litter type did not significantly affect the stocks of Ca and Mg; and (3) the stocks of Ca and Mg were positively correlated with factors such as rainfall amount, rainfall frequency, water temperature, flow velocity, water depth, electrical conductivity, and discharge, while negatively correlated with stream water alkalinity and dissolved oxygen levels. These findings highlight the critical role of plant litter in headwater streams as a component of forest nutrient stocks and provide empirical support for incorporating headwater streams into the assessment of nutrient stocks and fluxes in forest ecosystems.