Search Results (219)

Superabsorbent polymers (SAPs), such as sodium polyacrylate (PAAS), are the neutralized form of poly (acrylic acid) and belong to a class of materials characterized by three-dimensional networks of flexible polymer chains with exceptional water absorption and retention capacities. Due to these properties, PAAS has been widely used in agriculture as a soil water conditioner. This study investigates the potential of PAAS as a soil stabilizer for infrastructure applications. Three suction measurement techniques, namely the axis translation method, osmotic technique, and vapor equilibrium method, were employed to determine the suction behavior of PAAS and soil–PAAS mixtures over a wide range of water contents and to develop their soil–water characteristic curves (SWCCs). The investigation covers the full suction spectrum, from near-complete dryness to full saturation. Experimental results show that the SWCC of PAAS exhibits the three characteristic zones commonly observed in soils: boundary, transition, and residual zones. However, when PAAS is mixed with soil, the boundary and transition zones disappear from the SWCCs of the soil–PAAS mixtures. This behavior is attributed to the suppression of PAAS suction capacity caused by soil confinement. Unlike agricultural applications, where SAP particles are relatively unconstrained, engineering applications typically involve highly compacted soils that restrict polymer expansion and water absorption. The study also evaluates the feasibility of predicting the suction behavior of soil–PAAS mixtures using numerical modeling techniques based on limited experimental datasets. Among the methods considered, Lagrange interpolation and K-nearest neighbors (KNN) produced prediction models with errors below 10%. In contrast, deep neural network models demonstrated lower predictive accuracy, primarily due to the limited size of the available dataset. Full article

Water retention availability remains a primary constraint on both vegetation restoration and agricultural productivity across the Chinese Loess Plateau. Attapulgite (ATP) has considerable potential as a soil amendment for improving soil water retention and crop performance, yet its effectiveness is likely to depend on soil texture and climatic water availability. Here, we evaluated the effects of five ATP application rates (0%, 1%, 2%, 3%, and 4%, w/w) on soil hydraulic properties and maize (Zea mays L.) grain yield in three representative soils: clay loam, loam, and sandy loam. Soil water retention curves and field maize experiments were conducted to quantify the hydrological and agronomic responses to ATP addition. The classical van Genuchten (VG) model was further modified by incorporating ATP-dependent parameter relationships to better characterize the water retention behavior of ATP-amended soils. The modified model consistently provided a more accurate representation of the relationship between soil water content and matric suction than the original VG model. The derived soil hydraulic parameters were subsequently incorporated into the DSSAT cropping system model, which was calibrated and evaluated against field observations from Yangling in 2019 and 2020. The calibrated model was then used to simulate maize yield responses to ATP application from 2011 to 2020 at three representative sites: Yangling (clay loam), Changwu (loam), and Yan’an (sandy loam). Simulated yield responses varied markedly with soil texture and interannual climatic conditions. In clay loam, maize yield generally decreased with increasing ATP application, although positive responses occurred in relatively dry years. In sandy loam, ATP application generally increased maize yield across most years, whereas the loam soil exhibited stronger interannual variability in yield response. These contrasting responses indicate that the agronomic effectiveness of ATP is governed by the balance between enhanced soil water retention and local climatic water availability. Overall, the coupled soil hydraulic–crop modeling framework provides a mechanistic basis for developing site-specific ATP management strategies and highlights the importance of matching soil amendments to both soil texture and climatic conditions in water-limited agroecosystems. Full article

The surface soil in the Shendong mining area is dominated by aeolian sand and sandy sediment, while precipitation is limited, and evaporation is intense. Under these conditions, shallow reconstructed soil has difficulty retaining plant-available water, which constrains vegetation restoration. This study evaluated how low-range increases in fine-particle clay content affect both water retention and upward water conduction in sandy reconstructed soil. Sandy material from the Shangwan mining area and exogenous river clay were mixed into four treatments, and soil water characteristic curves (SWCCs) were determined by centrifuge over 10–1000 kPa matric suction. The data were fitted with the Van Genuchten model and combined with capillary-rise tests. The results showed that increasing fine-particle content shifted the SWCC upward and raised both saturated and residual volumetric water contents. SN10 reached 17.18% and 5.55% volumetric water content at 10 and 1000 kPa, respectively, and its effective water capacity in the 33–1500 kPa range was 17.9% higher than that of ST. At the same time, fine-particle enrichment in the bottom layer reduced wetting-front rise during capillary testing, indicating a trade-off between water storage and upward replenishment. Within the tested fine-particle range, moderate clay addition improved the hydraulic performance of sandy reconstructed soil, but soil design should balance precipitation retention, infiltration, and capillary supply. Because each treatment and soil-column configuration was represented by only one independently prepared experimental unit, experimental variability and reproducibility could not be evaluated. This study should therefore be regarded as a preliminary and exploratory laboratory assessment conducted under a specific set of material-preparation procedures, specimen geometries, and boundary conditions. The results describe specimen-level hydraulic contrasts rather than reproducible treatment effects and should not be directly generalized to field-scale soil reconstruction. They support a preliminary hypothesis for future replicated testing: fine-particle enrichment may increase water retention while slowing upward capillary replenishment. Full article

This paper reports a research work on assessing clay content effect on the water retention capacity of clayey sandy soils. At first, experimental tests were conducted to measure the soil water retention curves (SWRCs) of clayey sandy soils. A total of four different soil samples, which have clay content of 0, 15, 30 and 50%, respectively, by total soil sample weight, were measured. Secondly, a revision of a physical–chemical (PC) analytical model previously proposed has been reviewed and adopted to represent the SWRC measurements and compared for its predictive performance against the classic van Genuchten model and the original PC model. The experimental results demonstrated that clay content has a significant influence on soil water retention capacity, showing that a positive correlation generally exists between them. The modelling results showed that the revised analytical model not only produced a good representation for the soil water retention curves over whole range of soil water content, particularly at low water content side, but also provided advanced insight into the fundamental physics underlying soil water retention mechanisms. The analysis of its parametric data highlights the functions of the involved physics and their roles shaping the SWRCs, which intrinsically relate to specific surface area, pore size distribution, and particle size and shape. At last, the model was used to describe the pore size distribution from a revised concept against conventional approach. However, the revised concept and approach needs further wide verification and is open for discussion. Full article

Biochar is a porous, carbon-rich soil amendment that can enhance soil water retention capacity by modifying pore structure and physicochemical properties. Understanding the soil−water characteristic curve (SWCC) of biochar-amended soils is essential for evaluating their hydrological behavior and promoting the application of biochar in engineering practice. Given the demonstrated feasibility and accuracy of machine learning methods for predicting soil parameters, this study employed six machine learning models, namely, decision tree, random forest, XGBoost, LightGBM, CatBoost, and artificial neural network, to predict the SWCC of biochar-amended soils based on a constructed dataset. Feature importance analysis and partial dependence analysis were further conducted to reveal the influence patterns of key variables. The results indicate that all six models exhibit good predictive capability, with gradient boosting models (XGBoost, CatBoost, and LightGBM) performing best. Suction is the dominant factor controlling the volumetric water content variation, while soil particle-size distribution and dry density provide the physical basis for water retention. Biochar content, pyrolysis temperature, and feedstock type further modulate the water retention capacity of amended soils. Overall, the findings demonstrate that machine learning approaches can effectively predict the SWCC of biochar-amended soils and provide insights into the controlling mechanisms of soil water retention. Full article

The possibility of implementing intelligent irrigation has a number of undeniable advantages, mainly including the fact that the time can be determined and the volume of irrigation water can be adapted to specific plant types on a specific soil. A neural network has been trained to describe the dynamics of soil moisture based on the basic soil water retention curve (SWRC). It is able to take into account a wide range of input data, such as the specific surface area of the solid phase of soils, porosity, humidity, etc., for a given initial soil moisture profile. Preference is given to a recurrent neural network, since this type works well with sequential data and is able to take into account time dependence and solve the problem of decaying gradients of soil hydrophysical properties. The neural network processes the vector of incoming signs—humidity, temperature, volume of incoming/outgoing water, etc.—and connects them with the dynamics of humidity from sensors located at different depths. When modeling mass–salt transfer with different boundary and initial conditions, the dependence of moisture retention on the moisture conductivity function is used, which allows us to calculate how moisture with dissolved nutrients moves through the soil under the influence of pressure and concentration gradients. Since the SWRC is constructed as a function of directly measured data, it is easy to set it for each point of interest in the field and at each depth. During modeling, the soil is divided into elementary volumes (from 2–3 mm to 1 cm), and an array with data sets is compiled at each point. The research was conducted in a real hop plantation (the village of Opytny, Tsivilsky district, Republic of Chuvashia). The values of the soil moisture sensors at different depths, together with the data from the portable weather station, are sent to the input of the neural network. According to the minimum allowable humidity for hops, the model predicts situations when humidity reaches critical values and initiates watering. Thus, the implemented approach makes it possible to automate irrigation management, increase water use efficiency and ensure optimal conditions for plants. Full article

This study presents the development and evaluation of a hydrogel-based superabsorbent polymer sensor (HSPS) for measuring soil suction and establishing the soil–water characteristic curve (SWCC) of unsaturated soils. Polyacrylamide (PAM) hydrogels were synthesized via UV-induced free radical polymerization using acrylamide with varying crosslinking degrees. The polymers were characterized through FT-IR and TGA analyses, confirming successful synthesis and high thermal stability. Swelling, water retention, and kinetic behavior were systematically investigated. Results indicated that lower crosslinking density significantly enhanced swelling capacity, reaching up to 3000% in distilled water, while saline environments reduced absorption due to ionic screening effects. Swelling kinetics followed anomalous (non-Fickian) diffusion behavior and were well described by the pseudo-second-order Schott model. The synthesized polymers were integrated into a modified high-sensitivity pressure sensor operating on the osmotic principle to measure matric suction. The system was validated using natural soil. Among the tested formulations, the HSPS-3 demonstrated the most reliable suction measurements, reaching values up to approximately 1 MPa without significant temperature sensitivity. The resulting SWCC exhibited bimodal characteristics consistent with the soil’s dual pore structure. The proposed method provides a cost-effective, simple, and efficient alternative for suction measurement, expanding the practical range of SWCC determination in unsaturated soil mechanics. Full article

As a critical alpine transition zone linking the Qinghai–Tibet Plateau and the Loess Plateau, Gannan Prefecture acts as an important water conservation area in the upper Yellow River basin of China. Based on GLDAS-2.1 surface soil moisture (SSM) datasets spanning 2000–2022 and interpretable machine learning tools (SHAP and ALE), this paper analyzes the spatiotemporal evolution, future trend sustainability, and nonlinear statistical associations between environmental predictors and SSM. The main results were as follows: (1) SSM exhibited a significant upward trend with an annual growth rate of 0.18 kg·m⁻²·a⁻¹ (p < 0.001), and an abrupt turning point occurred in 2017. The spatial pattern of high SSM in the southeast and low SSM in the northwest remained relatively stable, with the centroid migration distance being less than 1.81 km; most regions presented statistically significant moistening trends (p < 0.05). (2) Natural environmental predictors jointly carried 95.79% of the total statistical explanatory weight for modeled SSM variability. Precipitation possessed the highest explanatory proportion (37.93%), followed by temperature (27.30%), potential evapotranspiration (ET_p, 12.26%), elevation (10.44%), and fractional vegetation cover (FVC, 7.77%). One-dimensional ALE curves identified sample-limited statistical breakpoints: SSM gradually plateaued when precipitation reached 650–700 mm, while modeled SSM decreased substantially once ET_p exceeded 800 mm·a⁻¹. Two-dimensional ALE further characterized combined statistical correlations among precipitation, temperature, and ET_p. Model outputs also indicated that FVC above 0.45 corresponded to enhanced soil water retention within the observed sample range, which only reflects statistical patterns captured in this dataset rather than universal regulatory standards. This study offers quantitative statistical understanding of SSM variations across alpine transition zones. Full article

Soil hydraulic hysteresis—the divergence between drying and wetting trajectories of the water retention curve—encodes quantitative information on soil structural organization that traditional modelling approaches do not explicitly capture. This study introduces the State Resilience Index (SRI), a dimensionless descriptor defined as the normalized area enclosed between the drying and wetting branches of a hysteresis loop and evaluates its interpretive value across five contrasting datasets from the published literature. The datasets encompass compaction gradients, repeated wetting–drying cycles, depth-resolved soil profiles, and water vapor sorption isotherms from soils differing in clay content and mineralogy. SRI values ranged from 0.023 to 0.333, responding consistently to the dominant structural drivers of hysteresis in each system. High values were associated with heterogeneous, structurally complex pore networks characteristic of productive soils; declining values reflected progressive loss of structural memory under compaction, repeated cycling, or mineralogical rigidity. A provisional interpretive framework is proposed, linking SRI ranges to soil structural quality and agronomic potential. The index is dimensionless, model-free, and applicable across measurement domains and forcing regimes, positioning it as a broadly transferable tool for the comparative assessment of soil hydraulic path asymmetry. Full article

Red clay in humid-hot environments suffers from severe water sensitivity and rainfall-induced slope instability, while traditional cement/lime stabilization faces high carbon emission challenges. Existing studies on plant ash-modified red clay mainly focus on basic mechanical properties, while systematic research on water retention characteristics and slope stability under extreme rainfall in humid-hot climates remains insufficient. To address this gap, this study proposes a sustainable stabilization method using agricultural waste-derived plant ash for red clay modification in humid-hot regions. Red clay exhibits distinct engineering behaviors owing to its unique physicochemical properties, leading to compromised slope stability and reduced resistance to rainwater infiltration. In this study, red clay was stabilized with 5%, 10%, 15%, and 20% plant ash. Laboratory tests evaluated compaction characteristics, shear strength, and water retention, supported by microstructural analysis via scanning electron microscopy (SEM). Slope stability under rainfall conditions was further simulated using ABAQUS 2022 software. Key findings include: (1) The addition of plant ash significantly altered the compaction properties. As the plant ash content increased from 0% to 20%, the maximum dry density of the modified red clay decreased linearly from 1.68 g/cm³ (unmodified soil) to 1.53 g/cm³, while the optimum moisture content rose from 21.86% to 23.85%. (2) The mechanical properties exhibited a non-linear response, peaking at 10% ash content. At this optimum dosage, the unconfined compressive strength, cohesion, and internal friction angle increased by 70.4%, 83.0%, and 37.1%, respectively, compared to untreated soil. (3) Plant ash enhanced water retention capacity, shifting the soil-water characteristic curve (SWCC). The modified soil demonstrated faster dehydration at low suction but improved water retention at high suction. The permeability coefficient decreased by an order of magnitude. Microstructural analysis revealed reduced porosity and fracture infilling by cementitious gels. (4) Numerical simulations confirmed that 10% plant ash reduced maximum slope displacement from 0.96 m to 0.61 m under heavy rainfall (90 mm total precipitation over 36 h, peak intensity 90 mm/day), elevating the safety factor from 0.85 to 1.45. Failure modes transitioned from deep-seated slip to localized shallow erosion. These results demonstrate that plant ash is a sustainable and effective additive for red clay slope stabilization in tropical climates. Full article

Soil water retention curves (SWRCs) are fundamental inputs for simulating vadose-zone processes, yet their direct measurement is labor-intensive and often impractical across large spatial domains. Pedotransfer functions (PTFs), therefore, provide an essential alternative for estimating SWRCs from readily measured soil properties. This study developed machine learning-based PTFs to estimate SWRCs using the UNSODA 2.0 database. An extreme gradient boosting (XGB) model was implemented and optimized using two Bayesian hyperparameter tuning frameworks, Hyperopt and Optuna, across eleven input scenarios incorporating combinations of textural, structural, and compositional soil attributes. Model performance was assessed using RMSE, R², and Kling–Gupta efficiency (KGE). To prevent data leakage from the hierarchical structure of the UNSODA 2.0 database, a nested grouped cross-validation framework was employed, ensuring an unbiased assessment of model generalization performance across independent soil samples. The Optuna-tuned XGB model trained on the full feature set achieved the highest accuracy, with a test RMSE of 0.0183, R² of 0.9815, and KGE of 0.9825, outperforming both the baseline and Hyperopt-optimized models. Feature importance and SHAP analyses indicated that soil texture dominated the estimations, while porosity, bulk density, and organic matter provided complementary improvements and particle density contributed marginally. These findings demonstrate that advanced hyperparameter optimization enhances the accuracy and interpretability of XGB-based PTFs, offering a robust framework for improved estimation of SWRCs in hydrological and soil-management applications. Full article

The measurement and/or evaluation of unsaturated hydraulic conductivity (USHC) is time-consuming and, at the same time, requires the deployment of specialized equipment. Due to this problem, several studies have used analytical methods to evaluate and predict the USHC of soil and modified soil matrix. Since there is a lack of adequate data on studies or cases of USHC in bio-treated soil specimens, this research examines the subject, though not without limitation. This research examines the USHC behaviour of bio-modified lateritic soil using fitting parameters of the soil-water retention curve. These parameters were fitted into the relative permeability function, k_r, for van Genuchten (VG), Brooks–Corey (BC), and Fredlund–Xing (FX). The numerical measure of the USHC is the product of k_r and the measured saturated permeability value. The saturated hydraulic conductivity and soil–water retention curve of specimens were prepared at −2, 0, and +2% moulding water content relative to optimum (MWCRO), 0 to 2.4 × 10⁹ cells/mL bacteria suspension densities, and RBSL to BSH compactive efforts. At higher suction stress, USHC in most instances decreased as MWCRO increased, culminating in its lowest value of 1.4 × 10⁻¹⁹ m/s for BC at +2% wet of optimum, while increased microbial suspension resulted in a slight decrease and/or variations that translated to the lowest value of 3.32 × 10⁻³⁰ m/s for BC at 1.5 × 10⁸ cells/mL. The USHC decreased with suction in the order BC ˂ FX ˂ VG, presenting how moisture condition, bio-treatment, and compaction interact to govern USHC and confirm the relevance of SWCC-based models in bio-stabilized soil assessment. Full article

Environmental changes driven by land use and climate variability profoundly affect basin water balance, yet their separate and combined effects remain poorly understood in data-scarce regions. This study investigates the individual and combined impacts of land use/land cover (LULC) and climate change on seasonal runoff in the Rokel-Seli River Basin (RSRB), Sierra Leone, over two periods (1965–1990 and 1991–2016). Using LULC maps derived from 1988 and 2013 Landsat imagery and the Soil and Water Assessment Tool (SWAT), we simulated hydrological responses under four scenario frameworks. The results reveal a marked expansion of urban, bare, and agricultural land at the expense of forest cover. The SWAT model satisfactorily captured streamflow dynamics during calibration and validation. Land use change alone increased wet-season runoff by 6.55% and decreased dry-season runoff by −13.15%, whereas climate change contributed changes of +24.87% and −31.43%, respectively. A double mass curve analysis and Budyko framework further revealed a regime shift toward higher runoff efficiency (runoff coefficient increased from 0.67 to 0.69), indicating a loss of basin retention capacity. Notably, land use change partially masked the full hydrological deficit induced by climate change, acting as a counter-buffering mechanism. This study provides critical evidence for water resource authorities and local stakeholders to develop adaptive land use and water conservation strategies in data-scarce tropical basins, emphasizing the need to consider both climatic and anthropogenic drivers in seasonal water availability assessments. Full article

Drying in granular porous media is governed by coupled thermal and hydraulic processes that can be substantially modified by biological activity. This proof-of-concept study investigated how surface heating and fungal colonization influence the evolution of thermal conductivity (λ) and matric suction (ψ) as functions of volumetric water content ${\theta }_v$ in Ottawa 20/30 sand. Four treatments were examined: sterile sand at 22 °C (T1), sterile sand at 28 °C (T2), fungal-amended sand with 10% biomass and 9-day incubation (T3), and fungal-amended sand with 15% biomass and 30-day incubation (T4). Samples were instrumented to monitor ${\theta }_v$, λ, and ψ during controlled evaporation using synchronized HYPROP and VARIOS measurements on the same specimen. Across all treatments, λ increased with ${\theta }_v$ (that is, λ declined as drying progressed), and ψ reflected the transition from hydraulically connected to disconnected pore water. Heating shortened the drying time but did not materially change the form of the λ–${\theta }_v$ relationship or generate strong matric gradients in sterile sand. Low biomass (T3) produced thermal and hydraulic responses comparable to the heated sterile control (T2), indicating limited pore-scale modification at early colonization. In contrast, high biomass (T4) widened the effective saturation range, maintained low and nearly uniform ψ across depth, and exhibited the steepest mid-range λ–${\theta }_v$ slope with a higher peak λ (~4 Wm⁻¹K⁻¹), consistent with hyphae and extracellular polymers stabilizing thin water films. A soil water retention curve (SWRC) analysis using the van Genuchten model further indicated increased water retention and delayed air entry with an increasing fungal biomass, with approximate air-entry values increasing from ~1.8 kPa (T3) to ~3.0 kPa (T4). Tests were terminated upon tensiometer cavitation rather than complete gravimetric dryness, constraining observations at very low ${\theta }_v$. These results indicate that heating primarily affects the rate of drying, whereas fungal networks alter the pathway by preserving hydraulic and thermal continuity at relatively high ${\theta }_v$. This behavior suggests a potential role of bio-mediated structuring in influencing near-surface thermo-hydraulic processes relevant to energy foundations, soil covers, and desiccation management in biologically active or bio-engineered soils. Full article

Increasing total soil porosity and optimizing pore distribution improve soil water-holding capacity, thereby alleviating drought impacts on crop yields in semi-arid regions. A three year split-plot field experiment was conducted, with organic fertilizer (sheep manure) rates as main plots and water-retaining agent (WRA) rates as subplots. Four organic fertilizer (0, 45, 60, and 75 Mg hm⁻²) and four WRA rates (0, 0.3, 0.6, and 0.9 Mg hm⁻²) were set, resulting in 16 combined treatments. Undisturbed soil samples were collected to analyze pore distribution and water availability using the soil water retention curve. The results showed significant variations in ameliorative effects with soil depth. Individual applications of either organic fertilizer or WRA significantly improved topsoil pore distribution and water availability but exerted negative effects on the subsoil. Combined application enhanced both soil layers, with a stronger synergistic effect in the subsoil. The combination of 45 Mg ha⁻² organic fertilizer + 0.9 Mg ha⁻² WRA achieved optimal soil improvement in the 0–20 cm layer, increasing aeration porosity by 21.89% compared to organic fertilizer alone; this improvement led to 14.99% and 15.65% increases in plant available water (PAW) and readily available water (RAW), respectively. For the 20–40 cm layer, the combination of 60 Mg ha⁻² organic fertilizer + 0.9 Mg ha⁻² WRA was optimal, increasing total, aeration, and capillary porosity by 24.18%, 183.50%, and 56.73%, respectively, compared to organic fertilizer alone. Consequently, subsoil water availability was enhanced, resulting in 57.53% and 61.18% higher PAW and RAW than the control without WRA. These findings highlight the necessity of layer-specific regulation and differentiated management. The optimal combinations (OF45+W0.9 for 0–20 cm and OF60+W0.9 for 20–40 cm) effectively optimize pore distribution and increase water availability through the complementary synergistic effects of organic fertilizer and WRA. Consequently, this strategy alleviates drought stress on crop yields in semi-arid regions. Full article