Soil Water Retention Function Research Articles

A generalized van Genuchten model for unsaturated soil hydraulic conductivity

AbstractThe hydrodynamics of variably saturated soils or porous media in general are described via nonlinear functions of water retention and hydraulic conductivity, which facilitate the simulation of various mass and energy transport processes (e.g., water, heat, contaminants, colloids) within the porous medium. We set out to derive improved functions for more accurate estimations of soil hydraulic functions to advance the simulation of porous medium hydrodynamics. A new model is proposed for estimating the unsaturated hydraulic conductivity (UHC) from a soil water retention (SWR) function that is parameterized via nonlinear regression of measured data. The function can be viewed as a generalized van Genuchten (1980) model (GVG). We tested the new SWR and UHC expressions for numerous data sets from literature that cover a wide range of soil textures. Our comparisons reveal more accurate estimations using the GVG model by comparison with the original van Genuchten model.

Coupled hydro‐mechanical pore‐scale modeling of biopore‐coated clods for upscaling soil shrinkage and hydraulic properties

AbstractEarthworms and plant roots are vital for macropore formation and stabilization. The organo‐mineral coating of biopore surfaces also regulates macropore‐matrix mass exchange during preferential flow. The influence of finer‐textured burrow coatings on macroscopic soil properties during shrinkage could potentially be assessed by upscaling pore‐scale hydraulic and mechanical simulations. The aim was to investigate the influence of micro parameters (particle size, stiffness, and bond strength) on macro parameters (i.e., shrinkage curve and soil hydraulic properties). Drainage experiments and simulations were carried out using biopore‐coated clod‐size samples compared to those without coating. Simulations were performed using a two‐phase pore‐scale finite volume coupled with discrete element model (DEM‐2PFV). The structural dynamics was characterized by analyzing the pore volume and soil shrinkage curve obtained from numerically determined data. The soil hydraulic parameters were described using uni‐ and bimodal van Genuchten (vG) functions. The drainage simulations revealed hydro‐mechanical dynamics characterized by Braudeau‐shrinkage curve subdomains: The matrix‐only samples, with lower particle bond strength, exhibited relatively higher shrinkage. The coated samples, with higher particle stiffness and bond strength, displayed greater hydro‐mechanical stability. The numerically determined initial value of the saturated hydraulic conductivity (Ks) was about 70 times larger for matrix‐only samples than for coated samples. As expected, for the nonrigid soil structures, constant Ks, α, and n values for bimodal vG model resulted in prediction errors. Upscaling DEM‐2PFV pore‐scale model outcomes quantifies micro‐coating effects on macro hydro‐mechanics. This yields void ratio‐based soil water retention and hydraulic conductivity functions, advancing macroscopic soil hydraulic models and enhancing structured soil flow and transport descriptions.

Precipitation and plant community-weighted mean traits determine total transpirable soil water in a desert grassland

The desert grassland has low precipitation, high evaporation and a limited soil water supply. Thus the tension between water shortage and sustainable vegetation restoration is increasingly evident. Change in total transpirable soil water (TTSW) reflects the water utilization and extraction capacity of plant communities, which are the basis for maintaining productivity and stability in communities, as well as the key ecological processes alleviating the above tension. Change in TTSW is influenced by precipitation, vegetation and soil. Quantifying the relative contribution of these factors to change in TTSW is key to the sustainable restoration of desert grassland. However, the current understanding of such effects remains limited. This study examined four typical plant communities in the Ningxia desert grassland, monitoring soil water content and evaluating plant community characteristics and diversity over three consecutive years. Using redundancy analysis and hierarchical partitioning methods, the influence of annual precipitation, vegetation (functional and species diversity, community characteristics) and soil physical properties on TTSW variation were investigated. Findings revealed: (1) The factors contributing to TTSW variation were annual precipitation (41 %-68 %,), vegetation (29 %-45 %), and soil physical properties (0 %-6.7 %). Specifically, community-weighted mean traits (CWM) and functional diversity (FD) explained TTSW variation by 24–37 % and 0.25–11 % respectively. In Gramineae communities, the influence of annual precipitation and vegetation on TTSW variation was consistent across soil depths. However, in degraded Sophora alopecuroides + Artemisia scoparia (SA) communities, the influence of vegetation (CWM, FD, community composition and community function) on TTSW variation was more pronounced in shallow soils (45 %) than in deeper soils (33 %), while annual precipitation effects were more substantial in the deep soil layers (66 %) than in the shallow soil layers (42 %). (2) Annual precipitation and CWM were the main biological and abiotic factors affecting TTSW. Interestingly, increased annual precipitation was negatively correlated with TTSW. Similarly, the primary controlling factor, CWM, also showed a significant negative relationship with TTSW. This relationship varied across community types and could be linear or quadratic, highlighting the need to understand the selection effects mediated by CWM in ensuring sustainable vegetation restoration. This research offers insights into the relationship between plant functional diversity and soil water retention function.

An effective stress-based approach to modeling the hydro-mechanical behavior of unsaturated soils

A constitutive model of unsaturated soils is developed by incorporating the concept of intergranular stress into the framework of the modified Cam–Clay model. Within this context, the degree of saturation is viewed as an internal state variable, so that the soil–water retention function appears naturally as an evolution equation for the volume fraction of water. The new model not only has a neat structure but also includes fewer material parameters compared to the other models. A new volumetric-hardening law is proposed by taking into account the effect of wetting-induced pore collapse. It is shown that the collapsing void ratio (the current void ratio minus the void ratio at full saturation under the same effective stress) is dominated by the degree of pore air saturation (one minus the degree of water saturation) and practically independent of intergranular pulling forces, highlighting the important effect of soil fabric on the wetting-induced pore collapse. The proposed model is applied to simulate different types of experiments on unsaturated soils subjected to various combined hydraulic and mechanical loadings, showing its capability and diversity in modeling the hydraulic and mechanical behavior of unsaturated soils.

Adhesion theory and model for air humidity impact on dust emission

It has been suggested that air humidity influences dust emission under very dry conditions and adhesion might be the responsible process which changes the binding between soil particles. The process of adhesion is so far poorly understood and difficult to quantify. Here, a critical examination of the relevant studies is provided, and an adhesion model is proposed. Both isothermal-kinematic and diffusion processes can limit the soil liquid–water and water–vapor exchange in soil, but for the particle size range concerned in aeolian studies, diffusion appears to be the limiting process. The model shows that soil moisture in the topsoil layers is positively correlated with air humidity, but with delays of several hours. The model performance is influenced by several parameters but is particularly sensitive to the equilibrium soil water–vapor content. This implies that soil microscopic properties can strongly influence adhesion. A new formulation of soil water retention function covering the entire soil moisture range is also proposed, which links soil water retention function and pore size distribution. Using a relationship between soil particle-size and pore-size distributions, an adhesion-affected grain size can be estimated, which defines the upper size limit of soil particles influenced by soil moisture. This study explains how air humidity influences soil moisture through adhesion and dust emission and why low air humidity promotes the emission of finer dust particles.

On evaluating the hypothesis of shape similarity between soil particle-size distribution and water retention function

Two pedotransfer functions (PTFs) are available in the literature enabling the soil water retention function (WRF) to be estimated from knowledge of the soil particle-size distribution (PSD), oven-dry soil bulk density (b), and saturated soil water content (s): i) the Arya and Heitman model (PTF-AH) and ii) the Mohammadi and Vanclooster model (PTF-MV). These physico-empirical PTFs rely on the hypothesis of shape similarity between PSD and WRF, and do not require the calibration of the input parameters. In the first stage, twenty-seven PSD models were evaluated using 4,128 soil samples collected in Campania (southern Italy). These models were ranked according to the root mean square residuals (RMSR), corrected Akaike Information Criterion (AICc), and adjusted coefficient of determination (R2adj). In the second stage, three subsets of PSD and WRF data (DS-1, DS-2, and DS-3), comprising 282 soil samples, were used to evaluate the two PTFs using the best three PSD models selected in the first stage. The hypothesis of shape similarity was assumed as acceptable only when the RMSR value was lower than the field standard deviation of the WRFs (*), which is viewed as a tolerance threshold and computed from the physically-based scaling approach proposed by Kosugi and Hopmans (1998). In the first study area (DS-1), characterized by a fairly uniform, loamy textured volcanic soil, the PTF-AH outperformed the PTF-MV and both PTFs provided reasonable performance within the acceptance threshold (i.e., RMSR < *). In the other two heterogeneous field sites (DS-2 and DS-3, characterized by soil textural classes that span from clay and clay-loam to loam and even sandy-loam soils), the PTF-MV (with 3% to 6% RMSR surpassing *) outperformed the PTF-AH (with 8% to 30% RMSR surpassing *) and the majority of RMSR values were larger than those obtained in the original studies. The mean relative error (MRE) revealed that the PTF-MV systematically underestimates the measured WRFs, whereas the PTF-AH provided negative MRE values indicating an overall overestimation. The outcomes of our study provide a critical evaluation when using calibration-free PTFs to predict WRFs over large areas.

Improved calculation of soil hydraulic conductivity with the simplified evaporation method

AbstractNumerical modeling of soil water dynamics and storage is generally based on the Richards equation. Its solution requires knowledge of the soil hydraulic properties (SHP): the soil water retention function and the hydraulic conductivity function. To determine SHP, laboratory evaporation experiments are particularly popular because they provide data for both SHP functions. The evaluation by the simplified evaporation method (SEM) method, originally proposed by Schindler and subsequently improved by several authors, relies on linearization assumptions that allow for a relatively simple calculation scheme but result in biased conductivity data for some soils. The objective of this study is to propose and test an improved computational scheme for the hydraulic conductivity function. We present the new theory and show that it leads generally to higher accuracy of the conductivity function. The improvement is most pronounced for sandy soils and soil water pressure heads below −100 cm, where the original method provided data with bias.

Assessment of the interactions between soil–biosphere–atmosphere (ISBA) land surface model soil hydrology, using four closed-form soil water relationships and several lysimeters

Abstract. Soil water drainage is the main source of groundwater recharge and river flow. It is therefore a key process for water resource management. In this study, we evaluate the soil hydrology and the soil water drainage, simulated by the interactions between soil–biosphere–atmosphere (ISBA) land surface model currently used for hydrological applications from the watershed scale to the global scale, where parameters are generally not calibrated. This evaluation is done using seven lysimeters from two long-term model approach sites measuring hourly water dynamics between 2009 and 2019 in northeastern France. These 2 m depth lysimeters are filled with different soil types and are either maintained as bare soil or covered with vegetation. Four closed-form equations describing soil water retention and hydraulic conductivity functions are tested, namely the commonly used equations from Brooks and Corey (1966) and van Genuchten (1980), a combination of the van Genuchten (1980) soil water retention function with the Brooks and Corey (1966) unsaturated hydraulic conductivity function, and, for the very first time in a land surface model (LSM), a modified version of the van Genuchten (1980) equations, with a new hydraulic conductivity curve proposed by Iden et al. (2015). The results indicate good performance by ISBA with the different closure equations in terms of soil volumetric water content and water mass. The drained flow at the bottom of the lysimeter is well simulated, using Brooks and Corey (1966), while some weaknesses appear with van Genuchten (1980) due to the abrupt shape near the saturation of its hydraulic conductivity function. The mixed form or the new van Genuchten (1980) hydraulic conductivity function from Iden et al. (2015) allows the solving of this problem and even improves the simulation of the drainage dynamic, especially for intense drainage events. The study also highlights the importance of the vertical heterogeneity of the soil hydrodynamic parameters to correctly simulate the drainage dynamic, in addition to the primary influence of the parameters characterizing the shape of the soil water retention function.

Upgraded closed‐form soil hydraulic functions from oven dryness to saturation

AbstractIn the past decades, remarkable progresses have been made in developing soil water retention (SWR) functions and relative hydraulic conductivity (kr) models for the full range of matric suction. However, such an existing SWR function and the corresponding kr model were found not to have a consistent prediction performance, that is, for a given soil, the SWR function could perform very well but the kr model might perform poorly or even fail. Given that both water retention and hydraulic conductivity need to be accurately predicted to simulate land‐atmosphere interactions, vadose‐zone soil–water dynamics, and shallow groundwater recharges, this paper proposed an upgraded SWR function and derived a new closed‐form kr model by combining the function with the well‐known Mualem model. The upgradation was done by introducing an exponential function for the pendular (i.e., dry and very dry) range of matric suction. The SWR function and kr model keep the conventional simplicity, reflect the capillary versus adsorptive soil–water mechanisms, eliminate fictitious parameters, and are continuously differentiable with closed forms. The assessment using the experimental data for 35 soils with nine different textures indicated that the upgraded SWR function and new kr model reproduced the data more accurately than the existing functions and models, as measured by visualization plots and four statistics, namely coefficient of determination, sum squared error, root mean squared error, and Nash–Sutcliffe efficiency. The contribution of this paper is to overcome the inconsistent‐performance issue mentioned above.

Mixed formulation for an easy and robust numerical computation of sorptivity

Abstract. Sorptivity is one of the most important parameters for the quantification of water infiltration into soils. Parlange (1975) proposed a specific formulation to derive sorptivity as a function of the soil water retention and hydraulic conductivity functions, as well as initial and final soil water contents. However, this formulation requires the integration of a function involving hydraulic diffusivity, which may be undefined or present numerical difficulties that cause numerical misestimations. In this study, we propose a mixed formulation that scales sorptivity and splits the integrals into two parts: the first term involves the scaled degree of saturation, while the second involves the scaled water pressure head. The new mixed formulation is shown to be robust and well-suited to any type of hydraulic function – even with infinite hydraulic diffusivity or positive air-entry water pressure heads – and any boundary condition, including infinite initial water pressure head, h→-∞. Lastly, we show the benefits of using the proposed formulation for modeling water into soil with analytical models that use sorptivity.

Assessment of the Effects of the 2021 Caldor Megafire on Soil Physical Properties, Eastern Sierra Nevada, USA

The Caldor fire burned ~222,000 acres of the Eastern Sierra Nevada during summer–fall 2021. We evaluated the effects of this “megafire” on the physical properties of a sandy soil developed from glacial tills to document fire-induced soil modifications in this region. We measured soil water retention and hydraulic conductivity functions as well as the thermal properties of five core samples from control (unburned) areas and eight core samples from burned soil of the same soil unit. Soil water repellency was measured in terms of water drop penetration time (WDPT) in the field and apparent contact angle in the laboratory on control and burned soil as well as ash samples. Soil organic matter (SOM) and particle and aggregate size distributions were determined on control and burned soil samples. Additionally, scanning electron microscopy (SEM) was used to image microaggregates of control and burned soil samples. We found a significant difference in SOM content and sand and silt aggregate size distribution between control and burned samples, which we associated with the disintegration of microaggregates due to the fire. We found no significant difference between soil water retention and hydraulic conductivity functions of control and burned soil but observed greater variation in saturated hydraulic conductivity and systematic shifts in thermal conductivity functions of burned compared to control samples. WDPT and apparent contact angle values were significantly higher for burned soils, indicating the occurrence of fire-induced soil hydrophobicity (FISH). Interestingly, the average apparent contact angle of the control soil was >90°, indicating that even the unburned soil was hydrophobic. However, the ash on top of the burned soil was found to be hydrophilic, having apparent contact angles <10°. Our results indicate that SOM and microaggregates were readily affected by the Caldor fire, even for sandy soil with a weakly developed structure. The fire seemed to have moderated thermal properties, significantly and soil wettability but had only minimal effects on water retention and hydraulic conductivity functions. Our findings demonstrate the complex nature of fire-soil interactions in a natural environment and highlight the need for additional investigation into the causes and processes associated with FISH and structure alterations due to fire to improve our ability to rapidly determine potential problem areas in terms of hazards commonly associated with fire-affected soils.

Self organizing hydrological processes in a runoff source area

Understanding the hydrology of runoff source areas is crucial for predicting floods and evaluating chemical transport. Numerically modeling water fluxes in the source areas is quite complex. However, the self-organization of complex hydrological systems makes it possible to simplify watershed models by considering the landscape functions. The limitation is that input values are not known a priori. This study seeks to find the soil physical parameters governing the hydrology of runoff source areas in humid climates and use them in a surrogate simulation model to predict the runoff and the perched water table height. The site chosen was a 5.4-ha, periodically saturated runoff source area with a shallow perched water table and a humid temperate climate. The only inflow was from precipitation. Perched water table depths at five locations and the outflow were measured continuously. Measurements showed that the outflow was negligible 24 h after a rain event. It indicated that a quasi-static equilibrium had been established, in which the capillary pressure decreased linearly with depth to zero at the shallow groundwater. The soil–water retention function determined the soil water distribution and the drainable porosity. Runoff was generated by saturation excess and equaled the rainfall minus the empty pore volume. Based on these observations, a simple spreadsheet-based surrogate model was developed to calculate the air-filled pore volume by accounting for daily precipitation and evaporation. The surrogate model accurately predicted daily discharge and water table height using climatic data and a literature-based water retention function. In our case, the quasi-static equilibrium was restored within a day. Thus, the small-scale nonlinear physics that determines the soil’s water flow rate before equilibrium is reached were irrelevant when the time step is one day. Studies in similar runoff source areas could utilize this approach and create their specific surrogate models.

Anthropogenic Disturbances Shape Soil Capillary and Saturated Water Retention Indirectly via Plant Functional Traits and Soil Organic Carbon in Temperate Forests

Soil’s water-physical properties support essential soil water retention functions for driving water distribution and availability, which is vital for plant growth and biogeochemical cycling. However, the question concerning how tree compositions and their interactions with other abiotic factors modulate soil’s water-physical properties in disturbed forests remains poorly understood. Based on observational data from nine permanent forest sites (18,747 trees and 210 plots) in the northeast of China, where forests once undergone three different levels of anthropogenic logging disturbance, we evaluated how multiple biotic (i.e., tree diversity and functional trait composition) and abiotic (soil texture and soil organic carbon) factors influence water-physical properties (i.e., in terms of soil capillary water retention (WC) and soil saturated water retention (WS)) in temperate forests. We found that the impacts of logging disturbance on soil water-physical properties were associated with improved tree diversity, acquisitive functional traits, and SOC. These associated attributes were also positively related to WC and WS, while there was no significant effect from soil texture. Moreover, disturbance indirectly affected soil water-physical properties mainly by functional traits and SOC, as acquisitive functional traits significantly mediate the effect from disturbance on WC and SOC mediates the influence from disturbance on WS. Finally, our results emphasize the potential relationships of tree composition with SOC and soil water retention as compared with soil texture and hence suggest that plants can actively modulate their abiotic contexts after disturbance, which is meaningful for understanding forest health and resistance.

Assimilation of Cosmogenic Neutron Counts for Improved Soil Moisture Prediction in a Distributed Land Surface Model

Cosmic-Ray Neutron Sensing (CRNS) offers a non-invasive method for estimating soil moisture at the field scale, in our case a few tens of hectares. The current study uses the Ensemble Adjustment Kalman Filter (EAKF) to assimilate neutron counts observed at four locations within a 655 km2 pre-alpine river catchment into the Noah-MP land surface model (LSM) to improve soil moisture simulations and to optimize model parameters. The model runs with 100 m spatial resolution and uses the EU-SoilHydroGrids soil map along with the Mualem–van Genuchten soil water retention functions. Using the state estimation (ST) and joint state–parameter estimation (STP) technique, soil moisture states and model parameters controlling infiltration and evaporation rates were optimized, respectively. The added value of assimilation was evaluated for local and regional impacts using independent root zone soil moisture observations. The results show that during the assimilation period both ST and STP significantly improved the simulated soil moisture around the neutron sensors locations with improvements of the root mean square errors between 60 and 62% for ST and 55–66% for STP. STP could further enhance the model performance for the validation period at assimilation locations, mainly by reducing the Bias. Nevertheless, due to a lack of convergence of calculated parameters and a shorter evaluation period, performance during the validation phase degraded at a site further away from the assimilation locations. The comparison of modeled soil moisture with field-scale spatial patterns of a dense network of CRNS observations showed that STP helped to improve the average wetness conditions (reduction of spatial Bias from –0.038 cm3 cm−3 to –0.012 cm3 cm−3) for the validation period. However, the assimilation of neutron counts from only four stations showed limited success in enhancing the field-scale soil moisture patterns.

Evaluation of pedotransfer functions for predicting soil hydraulic properties: A voyage from regional to field scales across Europe

Study regionEurope. A total of 660, 522, and 4940 soil samples belonging to GRIZZLY, HYPRES, and EU-HYDI databases, respectively, were used for parametric evaluation. Study focusThe soil water retention and hydraulic conductivity functions are crucial input information for land surface models. Determining these functions by using direct methods is hampered by excessive time and unaffordable costs required for field activities and laboratory analyses. Pedotransfer functions (PTFs) are widely-used indirect techniques enabling soil hydraulic properties to be predicted by using easily-retrievable soil information. In a parametric evaluation, the predictive capability of PTFs is examined by comparing measured and estimated soil water retention parameters and saturated hydraulic conductivity. Yet information about the performance of PTFs for specific modeling applications is mandatory to evaluate PTF effectiveness in greater depth. This approach is commonly defined as functional evaluation. New hydrological insights for the regionThe best performing four PTFs selected in the parametric evaluations are tested under two functional evaluations. The first encompasses a spatial interpolation with a geostatistical technique, whereas the second employs Hydrus-1D to simulate the water balance components along an experimental transect. Our results reinforce and integrate the insights of previous studies about the use of a PTF, and highlight the ability, or inability, of this technique to adequately reproduce the observed spatial variability of soil hydraulic properties and simulated water fluxes.

PySWR- A Python code for fitting soil water retention functions

Soil water retention (SWR) function is an important model that provides an empirical relationship between soil moisture and capillary pressure. We present a simple Python tool for fitting different types of SWR functions to laboratory-measured soil moisture data. Three different optimization methods including the Levenberg-Marquardt (LM) method, Trust Region Reflective (TR) method, and Dog Box (DB) method are considered. We used all three methods to fit the van Genuchten (VG) and Brooks and Corey (BC) models to ten soil moisture datasets. Our results show that the TR method, which allows the user to search for optimal parameter values within a constrained region, is the best approach for fitting these models. We developed a new graphical procedure for evaluating the guesstimates and bounds for different SWR model parameters. Overall, the TR method available in Python, together with the proposed graphical procedure, is an excellent approach for fitting both VG and BC models to soil moisture data.

Unsaturated Soil Hydraulic Properties according to Double-Ring Infiltration of Saline Water

Inverse modeling is a relatively complex procedure that allows quick estimation of soil hydraulic properties, yielding parameters for both soil water retention and unsaturated hydraulic conductivity function from a single experiment. The purpose of this research was to evaluate saline water effect on unsaturated hydraulic properties of clay loamy nonsaline-sodic soil layers and estimate these properties inversely from infiltration data using a double-ring infiltrometer.Three levels of water salinity (EC) 1.1, 2.2 and 5.8 dS/m were used for each treatment (T1, T2, and T3, respectively). Soil samples at three depths (0–20, 20–40 and 40–60 cm) were taken to measure Mualem–van Genuchten (MVG) hydraulic parameters (θr, residual water content, θs, saturated water content, α and n, shape parameters, and Ks, lab saturated hydraulic conductivity). Soil hydraulic parameters were estimated with an inverse solution using HYDRUS-1D model and infiltration data. Besides, the most sensitive MVG parameters to infiltration data (n, θs, and Ks) were inversely estimated due to difficulty in estimating several parameters simultaneously. Results showed that salinity had no significant effect on soil water infiltration and soil hydraulic conductivity changes in the specified salinity range according to the variance analyses (ANOVA).The Nash–Sutcliffe coefficient of efficiency (Ce) between simulated (HYDRUS) and measured values of cumulative infiltration data was about 0.998, indicating an excellent match. Soil water retention, as well as unsaturated soil hydraulic conductivity, were optimized with reasonable accuracy when the soil profile was assumed to be homogenous. In addition, simulated soil-water contents were quite similar to the measured values in which the values of Nash–Sutcliffe efficiency (Ce) for T1, T2, and T3 were 0.83, 0.85, and 0.85, respectively. In conclusion, the soil hydraulic parameters can be inversely estimated using the measured infiltration data through the double ring method if the soil is homogeneous.

Modeling near‐surface water redistribution in a desert soil

AbstractDespite the vast extent of desert soils on the earth's surface, our understanding of the moisture dynamics of near‐surface desert soils (i.e., the top centimeters to few meters of the soil profile) remain limited. The goal of this study was to explore the use of the Peters–Durner–Iden (or PDI) instead of bimodal van Genuchten (or BVG) hydraulic functions to improve water redistribution simulations using HYDRUS‐1D for drier soils in desert environments. The PDI hydraulic functions take capillary and film flow into account, whereas BVG hydraulic functions are limited to capillary flow. By comparing measured with simulated water content data, we found that moisture redistribution simulations were improved by using PDI instead of BVG soil water retention and hydraulic conductivity functions. Compared with the BVG simulations, the PDI simulations particularly improved for drier soil conditions (i.e., volumetric water contents ranging from 6 to 10%; suction heads between pF 2 and pF 3.8, and saturation degrees between 19 and 32%, respectively) for the studied sandy soil of Scaling Environmental Processes in Heterogeneous Arid Soils (SEPHAS) Lysimeter 1. For pF >3, the PDI functions predicted higher hydraulic conductivity than the BVG functions, which confirmed the hypothesis that a hydraulic conductivity function, which can capture film flow, may improve moisture distribution simulations for dry soils. For pF between 2 and 3, however, simulation results improved due to the difference in the water retention rather than the hydraulic conductivity function.

Simulation of drip irrigation on slope lands

One of the main tasks of drip irrigation is to predict the geometric parameters of the moisture contours by estimating the impact of the water rate and the irrigation water on the moisture distribution in the soil. In this paper the soil water retention curve and function of moisture conductivity are used to simulate the process of moisture movement taking into account both the state and the type of soil. A software tool has been developed to automate calculations and visualize them. One of the main advantages of this software tool is that it allows using three-dimensional arrays of porosity values, specific surface area and initial soil moisture for each elementary volume of soil. The results of simulating various initial conditions make it possible to form contours and maintain optimum soil moisture right in the area of the plant root zone development. The correspondence of the simulation results to real data was verified by a series of laboratory and field experiments having light-gray forest soil. The calculated coefficients of determination have average values, that are quite high for such tasks, namely 0.68 (horizontal surfaces) and 0.72 (inclined surfaces).

The role of soil water retention functions of near-surface fissures with different vegetation types in a rocky desertification area

Aims Soil water deficits have presented challenges to vegetation restoration in rocky desertification areas. In the field, small volumes of soil resources are present only in near-surface crevices, fissures, and other similar features. Water stored in the soil in near-surface fissures can help plants grow in such areas. The goals of this study are to discuss the soil water retention functions of near-surface fissures in terms of soil structure, water infiltration and water storage capacity and to define the role of fissure water in the growth of plants in rocky desertification areas.