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This study systematically investigated the synergistic improvement of expansive soil using organic fertiliser (OF), slow-release fertiliser (SRF), and rice straw (RS) through Box-Behnken design (BBD) and response surface methodology (RSM). Key findings include: the quadratic models demonstrated high statistical significance (root density: R² = 0.765, F = 25.84; shear strength: R² = 0.885, F = 18.65; swelling rate: R² = 0.20, F = 15.23; all P < 0.001) with low prediction errors (root content: ± 0.08 mg/cm³; shear strength: ± 0.58 kPa; swelling rate: ± 0.38%); The combination of 12.30% OF + 0.7 kg/m³ SRF + 0.4% RS achieved 58% improvement in shear strength, 32% improvement in root content, 42.7% reduction in swelling rate; OF exhibited negative linear effects on root density (β = – 0.18, P = 0.002) with >10% dosage reducing root growth by 9.0%; SRF showed positive linear impacts on shear strength (β = +0.25, P = 0.001) and root density (β = + 0.12, P = 0.023); RS enhanced shear strength below 0.5% (β = + 0.08, P = 0.042) but impaired root density due to pore clogging (β = – 0.15, P = 0.008). The optimised formulation, validated by triplicate centre-point tests (coefficient of variation ≤ 2.1%), is recommended for slope stabilisation while limiting OF to ≤ 10% to prevent performance degradation. This data-driven approach provides actionable insights for balancing agricultural waste utilisation and geotechnical performance in expansive soil improvement.

This study investigated, for the first time, the efficacy of citric acid (CA) and ethylenediaminetetraacetic acid (EDTA) as electrolytes in electrokinetic remediation (EKR) for removing lead (Pb) and cadmium (Cd) from three distinct soils (Anthrosols soil, AT; Acrisols soil, AC; and Chernozems soil, CH). Under a voltage gradient of 2 V/cm and a remediation duration of 4 days, EDTA proved most effective for Anthrosols, achieving removal rates of 17.8% for Cd and 12.8% for Pb-lower than those observed for Acrisols and Chernozems, likely due to AT’s high pH background. These results suggest that combining EKR with other remediation techniques could enhance efficiency for such soils. For Acrisols soil, extending the remediation time to 10 days significantly improved metal removal: Cd removal reached 91.1% with CA, while Pb removal attained 62.7% with EDTA. Chernozems soil exhibited higher sensitivity to EKR, with pronounced focusing phenomena. In CH1, Cd removal in anode-proximal (S1) zone reached 99%, but accumulation in the cathode-adjacent (S4 and S5) reduced the average removal rate to 22%, indicating the potential for improvement through cathodic control. Similarly, in CH2, Pb removal in S5 achieved 84.8%, while focusing in S1 suggested the need for anodic optimisation. These findings highlight the influence of soil properties and operational parameters on EKR efficiency, providing insights for tailored remediation strategies.

Machine learning makes geochemical mapping highly adaptable, as its data-driven nature allows predictions to evolve with new information. In this study, topsoil nickel (Ni) data were compiled from various sources, each with different sampling times and analytical methods. To effectively use such imbalanced data into spatial modelling, it was necessary to test how the data uncertainty propagated through the final maps. A comprehensive benchmark of the quantile random forest algorithm was conducted to identify conditions under which the model performs optimally. Predictive maps of topsoil Ni at a 20-metre resolution were subsequently generated and compared using a multi-faceted evaluation strategy. This approach assessed how model adjustments – particularly those addressing the uncertainty introduced by the regression-based conversion of legacy measurements – affected the performance. Extensive benchmarking revealed that while out-of-sample validation showed only modest improvements (e.g., root mean square error (RMSE) reduced from 12.6 to 11.2 mg/kg) when modifying training data, covariates, or algorithm parameters, the resulting prediction grids differed substantially. The analysis also demonstrated that output variability across model scenarios occurred at different spatial scales: weighting approaches had localised effects, whereas high variability in the input data propagated more broadly across the region.

The current erosion protection set up in the Czech Republic (CZ) is based on the long-term soil loss due to water erosion using the Universal Soil Loss Equation (USLE). The range of recommended values of tolerable soil loss by water varies among different authors and approaches, depending on the specific area and its parameters. It is, therefore, important to ask the following questions. What is the real range of soil loss by water erosion in CZ. To determine the range of soil loss, a model extrapolation was carried out. The model extrapolation was based on the results from two main experimental measurements. Both from the evaluated volume soil loss of real erosion events and field experiments based on measurements of erosion induced by artificial rainfall. The results of modelled extrapolation of the range of long-term soil loss are in the range 6.9–13.8 t/ha per year.

Ground heat flux (G) is often an overlooked component of the surface energy balance, and its accurate determination remains challenging. In the present study, the accuracy of various G estimation methods is examined using long-term measurements from the Central European mountain meadow. The impact of different G approximation on calculated evapotranspiration by the Penman-Monteith method (ET) is analysed. Soil heat flux measurements and surface temperature data were used to determine G, while net radiation was used to approximate G. Neglecting G led to an overestimation of ET in the daily timestep. On the contrary, the FAO-recommended hourly approximation overestimated G, underestimating ET. Site-specific calibrations of G prediction models improved their accuracy. For daily average G, as well as for hourly average G, simple constant parameter models (i.e., models including a single parameter specifying the fraction of net radiation directly) provide satisfactory accuracy of ET evaluation. However, in an hourly timestep, net radiation fails as a predictor of G shortly after sunrise and before sunset. The findings emphasise the importance of considering G in ET calculations and the need for site-specific calibrations of G estimation models.

Several experimental methods have been developed to fractionate soil organic carbon (SOC) into functional sub-pools. However, which fractions had the potential to better reflect the SOC dynamics responding to fertilisation are still under discussion. Thus, we compared different SOC fractions (microbial biomass carbon, MBC; dissolved organic carbon, DOC; permanganate-oxidisable carbon, POXC; particle organic carbon, POC, and aggregation organic carbon fractions) and the soil respiration rate in a wheat-corn rotation field after 40 years of manure and N fertilisation in North China to search for the most sensitive SOC fractions to fertilisation. Manure increased the organic carbon (OC) contents of all the soil fractions (26.5 to 362.8%) and the POC (18.0 to 43.7%) and macro-aggregation percentages (3.0 to 4.4%), which indicated an increasing physical-protected aggregated OC fraction. N fertilisation alone slightly increased the OC contents of all the soil fractions and DOC percentage, but decreased the macro-aggregation OC percentage, which suggests the increasing possibility that the SOC is exposed to microbial communities causing a decreasing aggregation formation. However, when a high level of both the manure and N fertiliser were applied, the excessive N in the soil stimulates the soil microbial activity and decreases the SOC content comparing it to the same level of the manure fertiliser addition.

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.

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.

Life Cycle Assessment (LCA) is normally used independently of the physical and temporal location of the product, process or service under analysis. This makes LCA results more easily comparable and globally accepted. At the same time, it has drawbacks though, e.g. land use will have the same impact regardless of location. However, the use of certain terrains in high erosion risk areas as compared to others in low erosion risk areas will have a different impact on the ecosystem. The availability of airborne Light Detection and Ranging (LiDAR) data (ALS) allows a quick and accurate morphogeometric analysis of any terrain. For this reason, this article offers a methodology, based on Revised Universal Soil Loss Equation (RUSLE) method and airborne LiDAR data, for the straightforward detection of zones with high vulnerability to erosion problems. Based on these local erosion risk data, a method is developed to assess the environmental impact of land use, based on its location. In this way, the LCA methodology is incorporated to gather local data, dependent on the specific location of the activity under analysis. The methodology developed has been applied, as a case study, to a specific municipality in the high mountains of the Autonomous Community of La Rioja (Spain).

A precise measurement of evapotranspiration (ET) and soil water storage (SWS) is necessary for crop management and understanding hydrological processes in agricultural catchments. In this study, we extracted the vegetative indices (VIs, including normalised difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and enhanced vegetation index (EVI)) from satellite images of the Nučice catchment. We found a consistent seasonal pattern of VIs across the catchment with higher values and variation ranges during spring and summer and lower values and variation ranges during autumn and winter. Spatial variation of VIs also followed a seasonal trend, decreasing during crop growth and increasing after crop harvesting. Seasonal correlations were observed between monthly average ET and SWS with VIs throughout one crop season, which can be expressed mathematically as exponential functions. We propose that VIs can be used as a surrogate measure for ET and SWS in catchments with poor monitoring capabilities. Further studies are required to investigate the spatial distribution of ET and SWS throughout the watershed and their relationship with VIs. Furthermore, our research emphasises the importance of subsurface recharge in the water balance of the investigated fields. It suggests that subsurface flow may be influenced by potential gradients of the water table, driving its seasonal behaviour in response to bedrock morphology.

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.

Electrokinetic remediation (EKR) is a powerful technique aimed at pollutant removal in soil, sludge, mine tailings, and so on. In the current work, we performed a bibliometric analysis of the research on EKR for the period of 1900-2018 on the basis of the core database of the Science Citation Index Expanded. In addition to a basic analysis of the research characteristics, keywords were analysed for four major participants: USA, China, Spain, and South Korea. The periods of 1990-2001, 2002-2008, and 2009-2018 were studied using the keyword analysis method to gain insights into the development of EKR and predict its future trends. The results revealed that the related research field in the USA was broad during the study periods. Meanwhile, China was interested in fluorine pollution and contamination in red soil. Spain paid close attention to pollution due to agricultural contamination. South Korea focused on radioactive element pollution. The number of papers published over a period of 28 years increased steadily and continued to rise after 2008. The combined techniques of EKR + phytoremediation and EKR + bioremediation were successively utilised by scholars over time, and the latter is expected to demonstrate vitality in the future.

The objective of this contribution is to provide information on a generally applicable optimisation procedure intended for designing a system of terraces and retention reservoirs within integrated territory protection from the harmful effects of soil erosion. The formulated procedure is a universal tool which can be used for any territory. An optimisation mathematical model was used to find the most suitable combination of various elaborated pre-optimisation variants of the soil conservation and flood prevention measures under the given conditions of each particular habitat. This model was created on the basis of a mixed discrete programming. The model compilation and its analysis on a high performance computer was performed using the model and calculation system GAMS. The model solution was controlled by one or more simultaneously operating optimisation criteria. A system of terraces as an important part of the soil erosion and flood control was chosen to verify the possibilities of the described optimisation procedure utilisation. The system was proposed within the land consolidation in the case study areas of Hustopeče and Starovice cadastral areas. First, the model function and performance were verified. Then the possibilities of experimentation on the model of the solved system of complex conservation measures were tested. The main results of the real and some experimental solutions are summarised. The results of practical applications of the integrated territory protection model validate its functionality and universal applicability.

Currently, agriculture in many countries including the Czech Republic is increasingly facing the problem of drought. The lack of precipitation results in a reduced harvest, which implies added irrigation and freshwater requirements. One of the ways to overcome the scarcity of fresh water is to search for alternative sources of irrigation water. The paper deals with a water source, which has not been preferred yet, but theoretically provides a wide application - treated municipal wastewater. Under a pilot plant, several selected soils were tested, placed in 2.0 m high filtration columns. Our observation was focused on ammonia nitrogen and its gradual decline during the flow through the soil profile. Samples from the filtration columns (inflow = irrigation; outflow = drainage water) were periodically taken, while the collected data were used for calibration of the numerical model. The model was calibrated in two successive separate steps, both were compiled in HYDRUS-2D. In the first step the model was calibrated according to the measured soil water content of materials. Subsequently, a second calibration was performed using the measured seepage concentrations of ammonia. Despite certain simplifications caused by the focus only on ammonia nitrogen, the model shows very favourable results. The hydraulic model's goodness of fit (between observed vs. measured values of water content) is R² = 0.88 for sand, 0.76 for loam, 0.72 for sandy-loam with vegetation on surface and 0.74 for sandy-loam without vegetation. The calibrated hydraulic model for solute transport (between observed vs. measured values of NH₄⁺-N concentration) showed the value of R² = 0.89 for sand, 0.95 for loam, 0.95 for sandy-loam with vegetation on surface and 0.92 for sandy-loam without vegetation. The model provides significant information on the dependence of decrease of ammonia pollution by the depth. Inflow concentration of ammonia on surface 17 ± 1 mg/l is reduced to the value of 2.0 mg/l at a depth of 110 cm. It is crucial for real application to maintain the hydraulic criteria - the field capacity should not be exceeded in praxis. The value of field capacity was deliberately slightly exceeded because of understanding of the situation: how the pollution proceeds below if this rule is not followed. As a result, if wastewater is applied, the groundwater level should not be at a depth of less than 1.5 m.

The article demonstrates a multilevel method of soil degradation analysis on land within South Moravia (Czech Republic (CZ)), in the Hodonín region, which is among the highest producing agricultural regions in CZ. The analysis takes a top-down approach, from a regional scale, through cadastres, to individual blocks of land. In the initial (rough) phase, selection was based on the Soil Degradation Model created for the Czech Republic, which classifies the extent of soil degradation to a cadastral level. Within the chosen region, the Čejkovice cadastre is the most burdened in terms of the combination of various degradation factors, and was therefore chosen for a further level of analysis in the form of remote sensing. The results of remote sensing and image classification identify areas with a high level of water erosion, which is the most significant degradation factor within CZ. Pedological research was then carried out in these identified areas. The results of both approaches were compared, and showed significant differences between erosional areas and depositional areas of slopes, which confirms their suitability for the given form of research and analysis. A combination of the given general (Degradation Model) and more detailed methods (erosion modelling, image classification and soil sample analysis) can find practical application in the optimization of farm production in the rural landscape.

The paper deals with optimisation of threshold suction pressure of soil water on light soils for early potatoes, early cabbage, late cauliflower and celery on the basis of results of small-plot field experiments with differentiated irrigation regime. Experiments were conducted in 2003-2005. Threshold suction pressures of soil water were identical for all crops: 15 kPa in treatment I, 30 kPa in treatment II, 60 kPa in treatment III, and 120 kPa in treatment IV. Precipitation, air temperature and relative humidity, global solar radiation, wind speed and direction were measured by an automated meteorological station. Reference and actual evapotranspiration was determined for the experimental crops according to FAO Paper No. 56 and by means of a biological curve (BC) in 2003-2005. To compare these two methods of calculation of actual evapotranspiration the soil moisture balance was found out. Based on the influence on marketable yield and proportion of the crop quality grades it is possible to determine the optimum threshold suction pressure on light loamy-sand soils in early potatoes, late cauliflower and cabbage 30 kPa and in celery 15 kPa. 80% of available soil water capacity (ASWC) corresponds to the threshold suction pressure 30 kPa, and as much as 96% of ASWC corresponds to 15 kPa. The seasonal irrigation depths determined on the basis of soil moisture balance, in which the crop evapotranspiration (ETc) is calculated either according to FAO 56 or by the BC, are substantially different from the really achieved irriga­tion depths in the treatments where optimal suction pressure is maintained. For potatoes, the really achieved values of seasonal irrigation depths are nearer to the depths calculated by the BC, while for the other vegetables (cauliflower, cabbage and celery) they are more similar to the depths calculated by FAO 56 methodology. The theoretical irrigation depths calculated by the BC method sometimes differ substantially from those based on FAO 56. These differences are at maximum for cauliflower and celery and at minimum for cabbage and decrease with the decreasing irrigation depths.

Each society wishes to create favourable living conditions for its members. Life quality criteria are formulated in different ways by various societies or individuals, depending on the given geographical and socio-economic conditions, living standards; national, ethnical, and religious traditions; history, policy; age, sex, educational level, position in the social hierarchy; etc. Sustainable development is a global objective that includes efficient multifunctional agriculture: using environment-friendly, energy- and material-saving technologies and paying special attention to quality; and a socially acceptable rural development, simultaneously. The given land resources have to be used and managed in harmony with the production and protection.

The article presents an overview and brief characteristics of the selected soil information systems in the Czech Republic. It suggests synchronisation of their development, particularly some convergence of the Land Evaluation Information System and Soil and Terrain Digital Database. In the pilot area of Litoměřice district, it demonstrates the application of the SOTER methodology for the construction of middle- and detail-scale soil maps, using the data from the General survey of agricultural soils. It not only shows the variety of the district soil conditions, but it also supplements them with the data gathered in the 2006 soil survey.

This paper is focused on the Jizera Mountains as a region strongly influenced by man in the past. The structure of the natural forest was changed. Species monocultures with similar tree ages were planted. High acidificants concentrations in atmosphere led to the decline of these monoculture forests in the top parts of the mountains and the high acidificants deposition damaged the soils in the whole region. The goals of this study are to describe the distribution of the soil properties in altitude transects, where temperature, precipitation, and vegetation gradients are recorded, and to compare the soil properties in spruce and beech forests. The soil samples were collected from soil pits in a surviving nature-close beech forest, in a production spruce forest, and also in the top dead forest area with a grass cover. Soil samples from sufficiently deep diagnostic horizons were taken for the study of chemical properties. The basic soil characteristics were determined by the commonly used methods (pH, effective cation exchange capacity - eCEC, and the contents of cations in the sorption complex, A₄₀₀/A₆₀₀ as humus quality parameter, the contents of available Ca, Mg, K and P, pseudototal content of Ca and Mg, and two differently extracted Fe and Al forms contents). The soils of the Jizera Mts. are strongly acid with a low eCEC which is the result of the natural and anthropogenic acidification processes. Soil chemical properties of the most affected top mountainous parts are in some aspects more favourable than lower parts (binding of potentially toxic Al in organic matter, slightly higher pH), but in other aspects they are still endangered by the acidification symptoms (higher leaching of base cations, especially Mg). The soils of nature-close beech forests represent more favourable soil properties than those of planted spruce forests. Generally, it can be concluded that the natural systems have higher resilience, and that natural mechanisms are able to mitigate slightly the soil degradation.