Search Results (230)

Optimizing water resource utilization is a critical challenge to meet the dramatic increase in food demand. Therefore, continuous studies to minimize water demand for plants are highly needed. This study aims to employ HYDRUS (2D/3D) software to simulate the effects of continuous and intermittent water flow on soil water distribution under a subsurface point source. The constant parameters included loamy sand soil, a water application time of 30 min, and an emitter discharge of 3.41 L/h. The variable parameters consisted are two pipe depths (25 cm and 35 cm), three ratios of ON:OFF times (1ON:1OFF, 1ON:3OFF, and 1ON:5OFF), and five water application cycles (WF1C, WF2C, WF3C, WF4C, and WF5C, with WF1C as for the continuous water flow). The results revealed that, in 30 min of water application, continuous water flow and ON:OFF ratios of 1ON:1OFF and 1ON:3OFF achieved maximum water retention in the vicinity of the emitter. In 60 min, increasing cycles enhanced retention for 1ON:1OFF and 1ON:3OFF, yet the 1ON:5OFF time ratio achieved the highest water content near the emitter. In 120 min, the 1ON:1OFF ratio showed an insignificant effect with cycle variations, but 1ON:3OFF and 1ON:5OFF exhibited increased retention. Similarly, in 180 min, 1ON:1OFF was unaffected by cycles, whereas 1ON:3OFF and 1ON:5OFF significantly improved retention. After 360 min, all treatments displayed equal water retention relative to the emitter position. Also, the results revealed that increasing water application cycles and ON:OFF time ratios lead to more holding soil water content, especially at soil levels of 20, 30, and 40 cm. These results affirm that positioning the emitters line at 25 cm enhances water retention more effectively than at 35 cm. Ultimately, statistical analysis confirmed that the combination of pipe depth, water application cycles, and ON:OFF ratios significantly affects the retention of soil water content in the vicinity of the emitter. Full article

The main goal of our work was to evaluate approaches for modeling lateral outflow from shallow unconfined aquifers in a one-dimensional model of vertical variably-saturated flow. The HYDRUS-1D model was modified by implementing formulas representing lateral flow in an aquifer, with linear or quadratic drainage functions describing the relationship between groundwater head and flux. The results obtained by the modified HYDRUS-1D model were compared to the reference simulations with HydroGeoSphere (HGS), with explicit representation of 2D flow in unsaturated and saturated zones in a vertical cross-section of a strip aquifer, including evapotranspiration and plant water uptake. Four series of simulations were conducted for sand and loamy sand soil profiles with deep (6 m) and shallow (2 m) water tables. The results indicate that both linear and quadratic drainage functions can effectively capture groundwater table fluctuations and soil water dynamics. HYDRUS-1D demonstrates notable accuracy in simulating transient fluctuations but shows higher variability near the surface. The study concludes that both quadratic and linear drainage boundary conditions can effectively represent horizontal aquifer flow in 1D models, enhancing the ability of such models to simulate groundwater table fluctuations. Full article

This study investigates the impact of biogas slurry ratio, hole diameter and depth under hole irrigation on the soil wetting front migration distance and cumulative infiltration. In this study, a model describing the water transport characteristics of biogas slurry hole irrigation was developed based on the HYDRUS model. Results demonstrated that the HYDRUS model can be used for biogas slurry hole irrigation (NSE > 0.952, PBIAS ≤ ±0.34). Furthermore, the study revealed that the soil cumulative infiltration and soil wetting front migration distance decreased gradually with an increase in the biogas slurry ratio, while they increased gradually with an increase in the hole diameter and depth. The lateral and vertical wetting front migration distances exhibited a well-defined power function relationship with the soil’s stable infiltration rate and infiltration time (R² ≥ 0.977). The soil wetting front migration distance curve can be represented by an elliptic curve equation (R² ≥ 0.957). Additionally, there was a linear relationship between the cumulative infiltration and soil wetted body area (R² ≥ 0.972). Soil wetting front migration distance model ($X=4.442f_0^{0.375}{t}^{0.24}, Z=11.988f_0^{0.287}{t}^{0.124}, f_0=96.947K_s^{1.151}{D}^{0.236}{H}^{1.042}$, NSE > 0.976, PBIAS ≤ ±0.13) and cumulative infiltration model ($I=0.3365S$, NSE > 0.982, PBIAS ≤ ±0.10) established under biogas slurry hole irrigation exhibited good reliability. This study aims to determine optimal hole diameter, depth, and irrigation volume for biogas slurry hole irrigation by establishing a model for soil wetting front migration distance and cumulative infiltration based on crop root growth patterns, thereby providing a scientific basis for its practical application. Full article

Reliable soil moisture projections are critical for optimizing crop productivity and water savings in irrigation in arid and semi-arid regions. However, capturing their spatial and temporal variability is difficult when using individual observations, modeling, or satellite-based methods. Here, we present an integrated framework that combines satellite-derived soil moisture estimates, ground-based observations, the HYDRUS-1D vadose zone model, and the ensemble Kalman filter (EnKF) data assimilation method to improve soil moisture simulations over saline-affected farmland in the Hetao irrigation district. Vegetation effects were first removed using the water cloud model; after correction, a cubic regression using the vertical transmit/vertical receive (VV) signal retrieved surface moisture with an R² value of 0.7964 and a root mean square error (RMSE) of 0.021 cm³·cm⁻³. HYDRUS-1D, calibrated against multi-depth field data (0–80 cm), reproduced soil moisture profiles at 17 sites with RMSEs of 0.017–0.056 cm³·cm⁻³. The EnKF assimilation of satellite and ground observations further reduced the errors to 0.008–0.017 cm³·cm⁻³, with the greatest improvement in the 0–20 cm layer; the accuracy declined slightly with depth but remained superior to either data source alone. Our study improves soil moisture simulation accuracy and closes the knowledge gaps in multi-source data integration. This framework supports sustainable land management and irrigation policy in vulnerable farming regions. Full article

Accurately determining the hydraulic properties of soilless growing media is essential for optimizing water management in container-based horticulture and agriculture. The very rapid estimation of hydraulic properties using a Mini Disk Infiltrometer has great potential for practical use compared to the very time-consuming standard methods. The objectives of this study were (1) to calibrate simulated cumulative stepwise infiltration under different suctions with the measured data from Mini Disk Infiltrometer, (2) to evaluate the efficiency of the Hydrus-2D inverse model to predict water dynamics through substrates, (3) to compare the substrate hydraulic parameters obtained through the numerical inversion model to those obtained via laboratory methods, and (4) to provide recommendations on how to effectively use the MDI-based method for practical applications. This study employs numerical inversion of Mini Disk Infiltrometer (MDI) data to estimate the hydraulic parameters of three different growing media, namely white peat, thermally treated wood fibre (WF4), and Seedling substrate. Infiltration experiments were conducted under suction-controlled conditions using varying initial moisture contents, followed by numerical simulations using the Hydrus-2D model and the Van Genuchten equation to describe the hydraulic parameters. The results demonstrated strong agreement between observed and simulated infiltration data, particularly under moistened conditions, with high R² > 0.9 values indicating the model’s effectiveness. However, discrepancies were observed for substrates in their initial dry state, suggesting limitations in capturing early-stage infiltration dynamics. The findings highlighted the potential of numerical inversion methods for estimating substrate hydraulic properties but also revealed the need for methodological refinements. Modifying the Van Genuchten model or exploring alternative approaches such as the Brooks and Corey model may enhance accuracy. Extending the suction range of measurement techniques is also recommended to improve parameter estimation. This study provides important evidence that the inverse method based on MDI is an effective tool for rapidly determining the hydraulic functions of substrates, which are important in promoting sustainable horticultural practices. Future research should focus on refining parameter estimation methods and addressing model limitations to enhance the reliability of hydraulic property assessments in soilless growing media. Full article

This study employed the HYDRUS-2D model to simulate soil water movement and water productivity (WP) in an apple–soybean alley cropping system in the Loess Plateau region, Shanxi Province, China, under four irrigation methods: mulched drip irrigation, subsurface drip irrigation, bubbler irrigation, and rainwater-harvesting ditch irrigation, with varying water management treatments. Field experiments provided 2022 data for model calibration and 2023 data for validation using soil water content (SWC) measurements, achieving R² = 0.80–0.87 and RMSE = 0.011–0.017 cm³·cm⁻³, confirming robust simulation accuracy. The simulation results indicated that different irrigation methods had a significant impact on the soil water distribution. Mulched drip irrigation enhanced the water content in the surface layer (0–20 cm), while subsurface drip irrigation increased the moisture in the middle soil layer (20–40 cm). Bubbler irrigation was most effective in replenishing both the surface (0–20 cm) and middle (20–40 cm) layers. Rainwater-harvesting ditch irrigation significantly improved the soil water content in both the surface (0–20 cm) and middle (20–40 cm) layers, with minimal changes observed in the deep layer (40–120 cm). Furthermore, soil water variations were significantly influenced by the water uptake of tree roots. In 2022, soil moisture initially increased with distance, then decreased, and subsequently increased again, while in 2023, it increased initially and then stabilized. When the irrigation amount was limited to 75% of the field capacity in the 0–60 cm soil layer, water productivity (WP) reached its optimum, with values of 4.79 kg/m³ (2022) and 5.56 kg/m³ (2023). Based on the simulation results, it is recommended that young apple trees be irrigated using subsurface drip irrigation with a soil layer depth of 30 cm, while soybeans should be irrigated with mulched drip irrigation. Both crops should be irrigated at the podding and filling stages of soybeans, and the irrigation amount should be limited to 75% of the field water capacity in the 0–60 cm soil layer. This study was designed to aid orchard growers in precision irrigation and water optimization. Full article

Soil moisture content has a direct effect on the growth rate and survival rate of trees. However, previous studies on soil moisture have often focused on the topsoil, lacking effective monitoring of long-term dynamic changes in deep soil layers. In this study, 16 time-domain reflectometer (TDR) probes were installed in the Haikou plantation in Kunming to conduct long-term continuous monitoring of soil moisture within a depth range of 0 to 300 cm. The results indicate that the vertical distribution of soil moisture can be classified into three levels: the active layer from 0 to 70 cm ($\theta =0.23\pm 0.08\mathrm{c}{\mathrm{m}}^3{\mathrm{c}\mathrm{m}}^{-3})$, where the moisture content fluctuates significantly due to precipitation events; the transitional accumulation layer from 70 to 170 cm $(\theta =0.26\pm 0.06\mathrm{c}{\mathrm{m}}^3{\mathrm{c}\mathrm{m}}^{-3})$, where moisture content increases with depth and peaks at 170 cm; and the deep dissipative layer from 170 to 300 cm $(\theta =0.24\pm 0.08\mathrm{c}{\mathrm{m}}^3{\mathrm{c}\mathrm{m}}^{-3})$, where moisture content decreases with depth, forming a noticeable steep drop zone at 290 cm. The Hydrus-1D (Version 4.xx) model demonstrated high simulation capabilities (${\mathrm{R}}^2=0.58$) in shallow (10 to 50 cm) and deep (280 to 300 cm) layers, while its performance decreased (${\mathrm{R}}^2=0.39$) in the middle layer (110 to 200 cm). This study systematically reveals the dynamics of soil moisture from the surface active zone to the deep transition zone and evaluates the simulation ability of the Hydrus-1D model in this specific environment, which is also significant for assessing the groundwater resource conservation function of plantation ecosystems. Full article

In early 2018, Cape Town, South Africa, experienced severe water shortages during the worst drought in nearly a century (2015–2017), underscoring the need to diversify water resources, including groundwater. This study evaluated infiltration rates and hydraulic properties of three representative stormwater ponds in the Zeekoe Catchment, Cape Town, to assess their feasibility as recharge basins for transferring detained stormwater runoff into the underlying aquifer. Field infiltration data were analysed to estimate hydraulic properties, while laboratory permeability tests and material classification on 36 soil samples provided inputs for numerical modelling using HYDRUS 2-D software. Simulations estimated recharge rates and indicated wetting front movement from pond surfaces to the water table (~5.5 m depth) ranged between 15 and 140 h. The results revealed field hydraulic conductivity values of 0.3 to 19.9 cm/h, with laboratory estimates up to 103% higher due to controlled conditions. Simulated infiltration rates were 67–182% higher than field measurements, attributed to idealised assumptions. Despite these variations, ponds in the central catchment exhibited the highest infiltration rates, indicating suitability for artificial recharge. Explicit recognition of pond-specific infiltration variability significantly contributes to informed urban water security planning, enabling targeted interventions to optimise groundwater recharge initiatives. Full article

Excessive nitrogen fertilizer in cotton cultivation boosts yields but causes groundwater pollution via nitrate-N (NO₃⁻-N) accumulation. This study combined field experiments and HYDRUS-1D modeling to analyze water and NO₃⁻-N dynamics in the vadose zone of cotton fields in Nanpi, Hebei Province, North China, under deep groundwater conditions. Monitoring during a 184-day growth period revealed that NO₃⁻-N accumulation increased from 11.4 to 21.2 g m⁻³ under conventional flood irrigation and pre-sowing fertilization. Soil texture critically influenced peak NO₃⁻-N accumulation depth, while rainfall, moisture, and crop uptake affected migration patterns. The HYDRUS-1D model was employed to numerically simulate the accumulation and migration of water and N in the cotton vadose zone. The HYDRUS-1D simulations closely matched the observed data, demonstrating effectiveness at modeling water–nitrogen transport patterns in the cotton vadose zone under deep groundwater conditions. Various factors, including rainfall, soil texture, soil moisture content, and crops, influenced the accumulation in the soil vadose zone. Notably, the location of the nitrate-N accumulation peak in the soil vadose zone was influenced by soil texture. This study highlights the environmental risks of current practices and provides insights for optimizing fertilizer management in arid agricultural zones. Full article

Mobile drip irrigation (MDI) systems integrate the technological advantages of center-pivot irrigation (CPI) systems and drip irrigation systems, boasting a high water-saving potential. To further enhance water use efficiency in alfalfa production in northern China, this preliminary study verified the accuracy of the HYDRUS-2D soil water movement numerical model through field experiments. Using the numerical model, four drip-line installation distances (60, 75, 90, and 105 cm), three deficit irrigation thresholds (45–50% FC, 55–60% FC, and 65–70% FC), and four irrigation depths (70% W, 85% W, 100% W, and 115% W) were set to simulate root water uptake, soil surface evaporation, total irrigation amount, and deep percolation during the entire growth cycle of alfalfa, respectively. Objective functions were constructed according to the simulation results, and the NSGA-II algorithm was used for multi-objective optimization of the deficit irrigation schedule. The preliminary results indicated that HYDRUS-2D can accurately simulate soil water movement under MDI systems, as the RMSE values of soil water content at all measured depths were less than 0.021 cm³/cm³, with the NRMSE values being below 23.3%, and the MAE values below 0.014 cm³/cm³. Increasing the deficit irrigation threshold from F1 to F3 enhanced root water uptake by 12.24–15.34% but simultaneously increased the total irrigation amount, soil surface evaporation (by up to 29.58%), and the risk of deep percolation; similar trends were observed with increasing irrigation depth. The drip-line installation distance had no significant impact on irrigation performance. The NSGA-II multi-objective optimization algorithm was used to obtain Pareto-optimal solutions that balance conflicting objectives. For this case study, a drip-line installation distance of 105 cm, a deficit irrigation threshold of 50–55% FC, and an irrigation depth of 112% W were recommended to achieve balance among the various optimization objectives. This study provides a preliminary framework for optimizing MDI systems and irrigation strategies. However, since a deeper root distribution (>80 cm) was not investigated in this study, future research incorporating deeper root zones is required for developing more comprehensive irrigation scheduling suitable for typical alfalfa cultivation scenarios. Full article

In order to study the leaching of exogenous nitrogen during green space management and maintenance, the parameters of the model were calibrated through field monitoring and grow box simulation experiments, and the Model for Studying Nitrogen Transport in Green Space Ecosystems was established by using HYDRUS-2D software. Results showed that the model is highly reliable for simulating nitrogen transport in microtopography, with R² values greater than 0.9 and RMSE values below 5. Slope gradient was positively correlated with horizontal nitrogen differences (ammonium and nitrate nitrogen) and negatively correlated with vertical differences (p < 0.05), while nitrogen application was positively correlated with both horizontal and vertical differences in nitrate nitrogen and negatively correlated with ammonium nitrogen (p < 0.05). The vertical differences of soil ammonium nitrogen exhibited a significant negative correlation with slope (−0.837 to −0.851), while the horizontal differences of nitrate nitrogen showed a significant positive correlation, with correlation coefficients of 0.965 and 0.967 for surface and subsurface soils, respectively. The increasing nitrogen application rate exacerbated these discrepancies, with the highest nitrogen treatment (0.312 g) exhibiting the most pronounced differential effects. Notably, the horizontal variation in nitrate nitrogen reached 6.9-fold that of ammonium nitrogen, while the vertical discrepancy demonstrated a 7.0-fold magnitude relative to ammonium nitrogen levels. Full article

HYDRUS-3D is a widely used software for modeling variably saturated water flow, but its performance under field conditions requires validation, particularly given the challenges of soil moisture detection. This study aimed to validate the accuracy of HYDRUS-3D in simulating soil water infiltration under drip irrigation using advanced horizontal mobile sensor systems (HMSSs). We designed a three-dimensional soil water infiltration experiment for drip-irrigated fields, employing two HMSSs which were orthogonally placed at 0.2 m and 0.4 m depths from the horizontal plane, and formed a trapezoidal configuration (height: 0.2 m, top edge width: 1 m) on the soil surface. These measurements provided three-dimensional data in the central area and two-dimensional data in the sloped sections. HYDRUS-3D simulations were compared to HMSS measurements, showing strong agreement in both the central area and sloped sections, with high R² values and low RMSE, indicating excellent model accuracy. These results confirm HYDRUS-3D’s reliability in simulating soil water movement under real-world conditions. In particular, the model effectively captured the horizontal fusion process of adjacent drip emitters, which advances its validation for field-scale applications and supports its use in precision agricultural water management. Full article

The increasing global reliance on water resources has necessitated improvements in turfgrass irrigation efficiency. This study aimed to compare measured field data with predicted data on irrigation water distribution in turfgrass rootzones to verify and enhance the accuracy of the HYDRUS-2D simulation model. Data were collected under controlled greenhouse conditions across unvegetated plots with two- and three-layered rootzone construction methods, each receiving 10 mm of water (intensity of 10 mm h⁻¹) via subsurface drip irrigation (SDI) or a sprinkler (SPR). The water content was monitored at various depths and time intervals. The hydraulic soil parameters required for the simulation model were determined through laboratory analysis. The HYDRUS-2D model was used for testing the sensitivity of various soil hydraulic parameters and subsequently for model calibration. Sensitivity analysis revealed that soil hydraulic property shape factor (n) was most sensitive, followed by factor θ_s^w (water content at saturation for the wetting water retention curve). The model calibration based on shape factors n and α_w either in Layer 1 for SPR variants or in both upper layers for SDI variants yielded the highest improvement in model efficiency values (NSEs). The calibrated models exhibited good overall performance, achieving NSEs up to 0.81 for the SDI variants and 0.75 for the SPR variants. The results of the irrigation management evaluation showed that, under SPR, dividing the irrigation amount of 10 mm into multiple smaller applications resulted in a higher soil storage of irrigation water (SOIL_S) and lower drainage flux (DFLU) compared to single large applications. Furthermore, the model data under the hybrid irrigation approach (HYBRID-IA) utilizing SPR and SDI indicated, after 48 h of observation, the following order in SOIL_S (mm of water storage in the topmost 50 cm of soil): HYBRID-IA3 (3.61 mm) > SDI-IA4 (2.53 mm) > SPR-IA3 (0.38 mm). HYDRUS-2D shows promise as an effective tool for optimizing irrigation management in turfgrass rootzones, although further refinement may be necessary for specific rootzone/irrigation combinations. This modeling approach has the potential to optimize irrigation management, improving water-use efficiency, sustainability, and ecosystem services in urban turfgrass management. Full article

This study provides a comprehensive assessment of the HYDRUS-1D model for predicting root-zone soil moisture (RZSM) and evapotranspiration (ET). It evaluates different soil hydrodynamic parameter (SHP) schemes—soil type-based, soil texture-based, and inverse solution—under varying cropping systems (Zea mays–Glycine max rotation and continuous Zea mays) and moisture conditions (irrigated and rainfed), aiming to understand water transport across different cultivation patterns. Using field measurements from 2002, the SHPs were optimized for each scheme and applied to predict RZSM and ET from 2003 to 2007. The inverse solution scheme produced nearly unbiased RZSM predictions with a root mean square error (RMSE) of 0.011 m³m⁻³, compared to RMSEs of 0.036 m³m⁻³ and 0.042 m³m⁻³ for the soil type-based and soil texture-based schemes, respectively. For ET predictions, comparable accuracy was achieved, with RMSEs of 66.4 Wm⁻², 69.5 Wm⁻², and 68.2 Wm⁻² across the three schemes. RZSM prediction accuracy declined over time in the continuous Zea mays field for all schemes, while systematic errors predominated in the Zea mays–Glycine max rotation field. ET accuracy trends mirrored RZSM in irrigated systems but diverged in rainfed croplands due to the decoupling of ET and RZSM under arid conditions. Full article

This study examines the impact of soil hydraulic parameterization on simulating soil water content in a drip-irrigated grapefruit orchard (Citrus paradisi Mac.) using precise laboratory measurements and the HYDRUS 2D/3D model. Undisturbed soil samples were analyzed for water retention and saturated hydraulic conductivity using high-precision instruments, and parameters were estimated with unimodal and bimodal Van Genuchten functions. Soil water dynamics under deficit (80% of crop evapotranspiration, ET_C) and full irrigation (100% ET_C) were simulated, accounting for circular drip emitters. Calibration relied on soil water content data collected at varying depths and distances from the emitters. Results from the fitting process with laboratory-measured data for water retention and hydraulic conductivity indicate that the bimodal function provided more accurate parameter estimates, yielding lower RMSE for soil water content (0.0026 cm³ cm⁻³) and hydraulic conductivity (0.1143 cm day⁻¹), compared to the unimodal (0.0047 cm³ cm⁻³ and 0.1586 cm day⁻¹). HYDRUS simulations also demonstrated superior calibration metrics for the bimodal function with RMSE, MAE, and NSE values of 0.024 cm³ cm⁻³, 0.016 cm³ cm⁻³, and 0.892 respectively, compared to 0.025 cm³ cm⁻³, 0.017 cm³ cm⁻³, and 0.883 for the unimodal function. Although differences between the functions were small, the bimodal model’s slight performance gain comes with added complexity and uncertainty in parameter estimation. These findings highlight the critical role of precise parameterization in refining irrigation strategies and ensuring sustainable water use in citrus orchards. Full article