Water Retention Data Research Articles

Impacts of soil type and crop species on permanent wilting of plants

The lack of a continuous network of water-filled pores necessary for the flow of water in the soil has been related to the wilting of plants as well as to the limitations of soil sample equilibrium in pressure plates. The objectives of this study were: (i) to quantify deviations of the soil water content measured in pressure plates and dew point measurements at a matric potential of −15,000 hPa (commonly defined as the permanent wilting point), (ii) to determine the soil matric potential at which the physiological wilting of different plant species occurs in soil with contrasting texture, and (iii) to evaluate if the wilting of plants occurs at the hydraulic cut-off in soil. An experiment was conducted to determine the soil matric potential at which wilting of sunflower (Helianthus annuus L.), maize (Zea mays L.) and soybean (Glycine max L.) occurs in four soils with clay contents ranging from 7 to 57%. Soil water retention characteristics were determined by the pressure chamber and the dew point technique. Soil water retention data were fitted to empirical models for estimates of soil matric potential and water content at the hydraulic cut-off. The water contents at −15,000 hPa in samples equilibrated in pressure plates was similar to those obtained from the dew point method in our soils. Our results show that physiological wilting of plants is both plant species and soil dependent. In soils with low clay contents, different plant species wilted at similar water contents. However, in the clayey soils, the different crops showed different abilities in the uptake of water from the soil, where soybean wilted at significantly lower water contents than the other two species. The values of matric potential at the permanent wilting point found in our study were considerably lower than −15,000 hPa, suggesting that the commonly used definition of permanent wilting point as water content at −15,000 hPa is incorrect.

A modification to the van Genuchten model for improved prediction of relative hydraulic conductivity of unsaturated soils

AbstractModelling of flow and transport in unsaturated soils requires information on two fundamental hydraulic properties: the soil water retention curve and relative hydraulic conductivity. A soil's relative hydraulic conductivity is frequently predicted from the soil water retention curve. The most widely used combination is the van Genuchten model for the soil water retention curve and the Mualem model for relative hydraulic conductivity (VGM). Previous studies show that the VGM model underestimates measured relative hydraulic conductivity for soils with fine textures; a sharp drop in relative hydraulic conductivity can be seen near saturation. A new modification of the van Genuchten soil water retention model is proposed with the aim of improving the agreement between predicted and measured relative hydraulic conductivity. The Brooks and Corey‐Burdine model is used to predict relative hydraulic conductivity from the modified van Genuchten soil water retention curve (MVG‐BCB). The modified model assumes independent m and n in the van Genuchten model but with constraints n > 2 and 0 < m < 1. The MVG‐BCB model is evaluated by comparing calculated and measured data for 59 soils that have widely varying soil textures, ranging from sandstone to clay. The MVG‐BCB model improves the agreement between calculated and measured data for both the soil water retention curve and relative hydraulic conductivity. The MVG‐BCB model is closer to measured relative hydraulic conductivity data for most of the selected soils and the sharp drop near saturation is eliminated. Both the modified soil water retention curve and relative hydraulic conductivity functions are smooth curves and can easily be incorporated into vadose zone flow and transport modellings.Highlights A new modification to the van Genuchten soil water retention model. The model improves the fit to measured soil water retention data. The chosen model improves the prediction of relative hydraulic conductivity.

Use of water retention data and soil physical quality index S to quantify hard-setting and degree of soil compactness indices of gypsiferous soils

Hard-setting gypsiferous soils become hard and compact during drying without the impact of soil compaction caused by agricultural field traffic. Thus, these soils are difficult or impossible to cultivate unless they are re-wetted. Moreover, it has previously been shown that Dexter soil physical quality index (S-index) negatively affected by compaction. This study was done to quantify the hard-setting as well as the soil compactness (expressed in terms of the degree of compactness, DC, which is relative density expressed as the ratio of bulk density to a reference density) using water retention data and soil physical quality index of fifteen soils with a wide range of gypsum content (30−301 g kg−1). Repacked soil cores were prepared with less disturbance of soil aggregates ≤ 4 mm). Water retention curves of the soils were measured in the matric suction range 10−15000 hPa. A single-porosity van Genuchten-Mualem model was fitted to water retention data. S-index and Dexter hard-setting (HDexter) were calculated using the van Genuchten-Mualem parameters. The relationships between S-index and both DC and HDexter were investigated for the 15 gypsiferous soils. A strong positive polynomial and power correlation were found between DC and HDexter and S (i.e. 1/S) respectively, and that are valid across different soil gypsum content. Significant negative relationships between HDexter and soil gypsum content were observed. Positive polynomial relations were derived between S and bulk density and polynomial relation was obtained between HDexter and bulk density. Positive relationships were observed between HDexter, DC, and relative bulk density. These findings confirmed that the new proposed HDexter index enables the prediction of soil hard-setting behavior to quantify the gypsiferous soil physical quality using only water retention data with no need to measure soil mechanical strength.

Estimating soil water retention for wide ranges of pressure head and bulk density based on a fractional bulk density concept

Soil water retention determines plant water availability and contaminant transport processes in the subsurface environment. However, it is usually difficult to measure soil water retention characteristics. In this study, an analytical model based on a fractional bulk density (FBD) concept was presented for estimating soil water retention curves. The concept allows partitioning of soil pore space according to the relative contribution of certain size fractions of particles to the change in total pore space. The input parameters of the model are particle size distribution (PSD), bulk density, and residual water content at water pressure head of 15,000 cm. The model was tested on 30 sets of water retention data obtained from various types of soils that cover wide ranges of soil texture from clay to sand and soil bulk density from 0.33 g/cm3 to 1.65 g/cm3. Results showed that the FBD model was effective for all soil textures and bulk densities. The estimation was more sensitive to the changes in soil bulk density and residual water content than PSD parameters. The proposed model provides an easy way to evaluate the impacts of soil bulk density on water conservation in soils that are manipulated by mechanical operation.

Pedotransfer Function for the Brunswick Soil Hydraulic Property Model and Comparison to the van Genuchten‐Mualem Model

AbstractModeling soil hydraulic properties requires an effective representation of capillary and noncapillary storage and conductivity. This is made possible by using physically comprehensive yet flexible soil hydraulic property models. Such a model (Brunswick [BW] model) was introduced by Weber et al. (2019, https://doi.org/10.1029/2018WR024584), and it overcomes some core deficiencies present in the widely used van Genuchten‐Mualem (VGM) model. We first compared the performance of the BW model to that of the VGM model in its ability to describe water retention and hydraulic conductivity data on a set of measurements of 402 soil samples with textures covering the entire range of classes. Second, we developed a simple transfer function to predict BW parameters based on VGM parameters. Combined with our new function, any existing pedotransfer function for the prediction of the VGM parameters can be extended to predict BW model parameters. Based on information criteria, the smaller variance of the residuals, and a 40% reduction in mean absolute error in the hydraulic conductivity over all samples, the BW model clearly outperforms VGM. This is possible as the BW model explicitly accounts for hydraulic properties of dry soils. With the new pedotransfer function developed in this study, better descriptions of water retention and hydraulic conductivities are possible. We are convinced that this will strengthen the utility of the new model and enable improved field‐scale simulations, climate change impact assessments on water, energy and nutrient fluxes, as well as crop productivity in agroecosystems by soil‐crop and land‐surface modeling. The models and the pedotransfer function are included in an R package spsh (https://cran.r‐project.org/package=spsh).

Development of Hierarchical Ensemble Model and Estimates of Soil Water Retention With Global Coverage

AbstractCorrect quantification of mass and energy exchange processes between land surface and atmosphere requires an accurate description of unsaturated soil hydraulic properties. Soil pedotransfer functions (PTFs) have been widely used to predict soil hydraulic parameters. Here, 13 PTFs were grouped according to input data requirements and evaluated against a well‐documented database (National Cooperative Soil Survey Characterization [NCSS]) covering the continental United States (87.7% of data) and other regions of the globe (12.3% of data). Weighted ensembles were shown to have improved performance over individual PTFs in terms of evaluation criteria. Validation of moisture content estimated from the ensemble models against observations showed promising results. Global maps of soil water retention data from the ensemble models as well as their uncertainty were provided. Our full 13‐member ensemble model provides more accurate estimates than PTFs that are currently being used in Earth system models, which may, therefore, provide improved water fluxes and reduce uncertainty of the estimations.

Predicting water retention of biochar-amended soil from independent measurements of biochar and soil properties

Biochar is black carbon produced from pyrolysis of biomass and may be added to soil to sequester carbon and improve soil water retention. To date models to predict changes in soil water retention with biochar amendment are still missing and therefore direct measurements are required for every biochar/soil combination, which can be time-consuming. Here, a predictive model for biochar's effect on soil water retention was developed and tested that includes water retained in biochar intrapores and biochar's impact on interpores between particles. The independently measured parameters needed for the model are the particle size distributions (PSDs) and particle densities for biochar and soil, water retention data for biochar-free soil, biochar intrapore volume distribution from mercury porosimetry, amount of biochar added, bulk density of the biochar/soil mixture, and dew point potentiometer measurements of biochar. The model was tested using poultry litter and wood biochars amended to two soils (sand and sandy loam) at 2 and 7% mass fraction. The model predicted changes in the soil water characteristic well for the biochar amendment, with RMSE decreasing by ~50% when the full model was used. Model predictions of the change in available water capacity with biochar amendment for eight biochar/soil combinations had an average absolute error of 0.017 ± 0.006 and an average relative error of 10¯0 ± 40%. The model correctly predicted the increase in available water content when sandy loam was amended with wood biochar, and the decrease if amended with poultry litter biochar. The model provides an improved understanding of the mechanisms by which biochar alters water retention, and a means to estimate the initial change in available water capacity for a particular biochar/soil combination if necessary biochar and soil properties are measured.

Physical Constraints for Improved Soil Hydraulic Parameter Estimation by Pedotransfer Functions

AbstractGlobal land surface models use spatially distributed soil information for the parameterization of soil hydraulic properties (SHP). Parameters of measured SHP are correlated with easy‐to‐measure soil properties to construct general pedotransfer functions (PTFs) used to predict SHP from spatial soil information. Global PTFs are based on a limited number of samples yielding highly variable and poorly constrained SHP. The study implements a physical constraint, soil‐specific capillary length, to reduce unphysical combinations of SHP. The procedure fits concurrently soil water retention and capillary length using the same parameters. Results suggest that meeting the capillary length constraint has minor effects on the goodness of fit to soil water retention data. Constrained SHP were applied to represent 4 years of lysimeter fluxes yielding evapotranspiration values in close agreement with measurements relative to slight overestimation by unconstrained SHP. The procedure was applied for testing constraint SHP at a regional scale in New Zealand using the surface evaporation capacitance model and Noah‐MP for detailed simulations of land surface processes. The use of constrained SHP in both models yields higher surface runoff in agreement with observations (unconstrained SHP severely underestimated runoff generation). The concept of constrained SHP could be extended to include other physical constraints to improve PTFs, for example, by consideration of vegetation cover and soil structure effects on infiltration.

Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: I. Direct Model Fit Using the Extended Evaporation and Dewpoint Methods

This study focuses on the reliable parametrization of the full Soil Water Retention Curve (SWRC) from saturation to oven-dryness using high resolution but limited range measured water retention data by the Hydraulic Property Analyzer (HYPROP) system. We studied the performance of five unimodal water retention models including the Brooks and Corey model (BC model), the Fredlund and Xing model (FX model), the Kosugi model (K model), the van Genuchten constrained model with four free parameters (VG model), and the van Genuchten unconstrained model with five free parameters (VGm model). In addition, eleven alternative expressions including Peters–Durner–Iden (PDI), bimodal, and bimodal-PDI variants of the original models were evaluated. We used a data set consisting of 94 soil samples from Turkey and the United States with high-resolution measured data (a total of 9264 measured water retention data pairs) mainly via the HYPROP system and supplemented for some samples with measured dry-end data using the WP4C instrument. Among unimodal expressions, the FX and the K models with the Mean Absolute Error (MAE) values equal to 0.005 cm3 cm−3 and 0.015 cm3 cm−3 have the highest and the lowest accuracy, respectively. Overall, the alternative variants provided a better fit than the unimodal expressions. The unimodal models, except for the FX model, fail to provide reliable dry-end estimations using HYPROP data (average MAE: 0.041 cm3 cm−3, average r: 0.52). Our results suggested that only models that account for the zero water content at the oven dryness and properly shift from the middle range to dry-end (i.e., the FX model and PDI variants) can adequately represent the full SWRC using typical data obtained via the HYPROP system.

Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: II. Evaluation of Parametric Pedotransfer Functions Against Direct Fits

A high-resolution soil water retention data set (81 repacked soil samples with 7729 observations) measured by the HYPROP system was used to develop and evaluate the performance of regression parametric pedotransfer functions (PTFs). A total of sixteen soil hydraulic models were evaluated including five unimodal water retention expressions of Brooks and Corey (BC model), Fredlund and Xing (FX model), Kosugi (K model), van Genuchten with four free parameters (VG model) and van Genuchten with five free parameters (VGm model). In addition, eleven bimodal, Peters–Durner–Iden (PDI) and bimodal-PDI variants of the original expressions were studied. Six modeling scenarios (S1 to S6) were examined with different combinations of the following input predictors: soil texture (percentages of sand, silt and clay), soil bulk density, organic matter content, percent of stable aggregates and saturated water content (θs). Although a majority of the model parameters showed low correlations with basic soil properties, most of the parametric PTFs provided reasonable water content estimations. The VGm parametric PTF with an RMSE of 0.034 cm3 cm−3 was the best PTF when all input predictors were considered. When averaged across modeling scenarios, the PDI variant of the K model with an RMSE of 0.045 cm3 cm−3 showed the highest performance. The best performance of all models occurred at S6 when θs was considered as an additional input predictor. The second-best performance for 11 out of the 16 models belonged to S1 with soil textural components as the only inputs. Our results do not recommend the development of parametric PTFs using bimodal variants because of their poor performance, which is attributed to their high number of free parameters.

A novel segmental model to describe the complete soil water retention curve from saturation to oven dryness

Traditional water retention models that use the residual water content parameter fail to accurately describe the dry end of the soil water retention curve (SWRC). We developed two- and three-segment smooth, continuous SWRC models, acknowledging the existence of three saturation states, for water contents ranging from saturation to oven-dryness. The equations near the oven dryness end in both models were obtained based on the assumption of proportionality between the soil water content and the logarithm of suction. The equations in the wet range for both models were modified from the van Genuchten model and/or Brook-Corey model(s) by removing the residual water content parameter. The continuity and smoothness conditions at the junction points reduced the fitting parameters of the three- and two- segment models from 9 to 4 and from 6 to 3, respectively. Both models were tested with water retention data from the Washington soil database and the Unsaturated Soil Hydraulic Database (UNSODA) over nearly the entire range. Both models were also compared with seven existing SWRC models and were evaluated on the basis of the adjusted coefficient of determination (adj R2), the root mean square error (RMSE) and the Kashyap information criteria (KIC). The testing results showed that the three-segment model performed better than the two-segment model at fitting the SWRC at the dry end. For the three-segment model, the adj R2 value was greater than 0.90, the RMSE was less than 0.02, and the mean KIC value was −67.0, and these values were superior to those of the other models. In addition, the three-segment model was robust and stable for extrapolation of values in the dry range when data near the dry end were unavailable.

Splintex 2.0: A physically-based model to estimate water retention and hydraulic conductivity parameters from soil physical data

Soil water retention curve (SWRC) and hydraulic conductivity curve (SHCC) are functions that contribute to the understanding and modeling of hydraulic processes in the vadose zone of the soil. However, their measurement is often difficult and expensive becoming impractical the large-scale monitoring. Pedotransfer functions (PTFs) are, therefore, an alternative to estimate SWRC and SHCC data. Most PTFs are usually calibrated with data from local soils and may be uncertain when applied to soils with different morphological properties. On the other hand, PTFs with a physico-empirical basis have as advantage their wide application. Splintex 1.0 is a physico-empirical model developed in BASIC language that is based on the particle size distribution and other basic soil information. This model estimates the parameters of the van Genuchten-Mualem equation that compose the SWRC without requiring prior calibration and the saturated hydraulic conductivity (Ks) using a texture-PTF. A second version with a user-friendly computational interface is presented to improve the estimates of the SWRC parameters and to introduce the estimation of the SHCC parameters with different PTFs, which are based on two physically-based models that can be applied universally. Computational procedures and equations of Splintex 2.0 were written in C++ language and the performance of both model versions was tested for different soil texture classes. The performance analysis was carried out using the Pearson correlation coefficient and the mean absolute and root mean square errors. Splintex 2.0 yielded good performance in the quantification of water retention data, showing its application to any soil class. As an advantage, the conductivity data can be estimated without the need of Ks and SWRC parameters.

Comparison of the performance of 22 models describing soil water retention curves from saturation to oven dryness

AbstractSoil water retention curve (SWRC) is key hydraulic property for vadose zone hydrology. Selected 22 SWRC models with different structures were divided into four types: traditional, single‐segment, two‐segment, and three‐segment models. According to the accuracy and model selection criterion, these models were compared and evaluated using water retention data from saturation to oven dryness of 94 soil samples covering almost all soil types. Among the models, the EG model (exponential model combined with the Groenevelt–Grant model) shows the best performance, but the BC (Brooks–Corey) and VG (van Genuchten) models performed the worst. The relationship between model performance and complexity showed that traditional models with residual water content performed worse than segmental models from saturation to oven dryness, and the segmental models performed worse with an increase in the segment number. In general, models with more parameters perform better, but when the parameter number is greater than five, the model performance gradually worsens due to the equifinality of different parameters. The correlation analysis between soil properties on model performance showed that soil texture has a more significant effect on model performance than bulk density and organic matter content, because the models are primarily affected by their mathematical forms rather than the physical significance of the parameters. Each model picks its limitations and may apply to only one or particular group(s) of soil(s). Therefore, the complementarities of different models may be a great choice to improve SWRC fitting and simulation in arid soil.

Short-term effect of tillage methods, residue levels, and forward speeds on soil-water characteristic curve (SWCC): A case study on the eastern soils of Karun River, Khuzestan province, Iran.

The current study was conducted to investigate the effect of tillage methods, residue rates, and forward speeds on the soil-water characteristic curve (SWCC) of Haploustepts soil over the course of one crop year (2014-2015). The treatments consisted of conventional mechanized tillage (CT: moldboard plough+disc) and reduced tillage (RT1: chisel peker+plough and RT2: combined tillage), different surface residues, including three levels of no residue, 40% residue, and 80% residue, and forward speeds at three levels: low (4 km/h), normal (7 km/h), and high (10 km/h). The experimental water retention data were fitted to uni-modal van Genuchten (termed uni-modal vG) and bi-modal Dexter (termed bi-modal Dex) models. No significant impact was observed on different physical parameters, except for parameter n. In the slope at the inflection point of SWCC, 11.8% and 8.9% reductions were observed in CT and RT1 treatments, respectively, compared to RT2. Based on the results, measured under CT tended to be higher than that of other tillage treatments. Residual covers and higher forward speeds tended to increase both and . Changes in PSD were more pronounced in larger (macro) and medium (meso) pore diameter classes. The highest value of structural void ratio as transmission pores was observed in RT2. This finding indicates that with respect to , , , and values, the soil PSD descriptive system is a bi-peak distribution such as H-L; therefore, due to the hierarchical nature of soil structure, van Genuchten equation cannot appropriately describe multi-modal soils inherently.

New pedotransfer function (“CRC”) for the prediction of unsaturated soil hydraulic conductivity using soil water retention data

New pedotransfer function (“CRC”) for the prediction of unsaturated soil hydraulic conductivity using soil water retention data

Measured and modelled above‐ and below‐canopy turbulent fluxes for a snow‐dominated mountain forest using GEOtop

AbstractThe prediction of snowmelt in mountainous forests strongly depends on the accurate description of sensible and latent heat turbulent fluxes. Uncertainty about the within‐canopy wind conditions especially poses a challenge, with relatively few studies examining both above‐ and below‐canopy turbulent fluxes. In this study, turbulent flux predictions from a state‐of‐the‐art watershed model GEOtop were verified against eddy covariance data from one above‐canopy tower and two below‐canopy towers in a snow‐dominated coniferous forest in south‐eastern Wyoming. The model was applied in one‐dimensional vertical mode using field‐observed vegetation parameters and laboratory‐measured soil water retention data. The model was calibrated by identifying optimum values for the canopy fraction and the within‐canopy eddy decay coefficient using the brute‐force method. Above‐canopy sensible heat flux at the Glacier Lakes Ecosystem Experiments Site was predicted reasonably well (r2 = .851). The prediction of above‐canopy latent heat flux was weaker (r2 = .426). For latent heat flux, errors in 30‐min values offset each other when fluxes were aggregated over time, resulting in realistic mean diurnal trends. Below‐canopy turbulent flux at two sites in the Libby Creek Experimental Watershed were predicted with variable success with r2 = .031–.146 for sensible heat flux and r2 = .445–.581 for latent heat flux. Modelled below‐canopy sensible heat flux was too low due to the underestimation of daytime ground surface temperature, because of not enough solar radiation reaching the soil surface. This study suggests that future work on GEOtop and related models should include better parameterizations of the ground surface energy balance to more reliably predict snowmelt and streamflow from mountainous forests.

Impact of pulp drying modes for water-retention values measured by headspace gas chromatographic method

The water-retaining capabilities of bleached chemical pulps treated by the oven-, air-, vacuum-, and freeze-drying modes were determined with use of a reliable the headspace gas chromatographic method (HS-GC) developed recently. The results showed that reliable water retention data could be determined by the HS-GC method only in the case of air-dried pulp. This result was supplemented by observations of the surface morphology of the fibers from these drying processes. The present HS-GC method can be used for checking the differences of wettability (at a given equilibration time) of pulp specimens from different drying modes.

Whether the Rock Fragment Content Should Be Considered When Investigating Nitrogen Cycle in Stony Soils?

AbstractThis study was conducted on a stony‐soil hillslope that severely eroded due to land use change from bamboo to tea. First, three approaches were used to extract soil hydraulic properties and then inputted into the Denitrification–Decomposition model for simulations. The Denitrification–Decomposition model defaults and ROSETTA pedotransfer function were traditional approaches without considering the rock fragment impacts on soil hydraulic properties, while the dual‐porosity function considered rock fragment impacts since it was calibrated with observed soil water retention data. Results showed that dual‐porosity functions gave the most accurate or physically sound results in simulating the nitrous oxide (N2O) emissions and leachate nitrate nitrogen (NO3−‐N) concentrations, with the root‐mean‐square errors as 0.0043–0.0107 kg N/ha and 4.39–9.09 mg/L, respectively. This suggested that rock fragments could impact the soil N cycle by affecting soil hydraulic properties. Second, the model simulations in the first step were further corrected by the volumetric rock fragment contents. This correction significantly reduced the N2O emissions and NO3−‐N leaching by 25–43% and improved the simulations. This suggested that high rock fragment contents could reduce the N emission and leaching by decreasing the volume of soils participated in N cycle. Last, under the climate change, the NO3−‐N leaching were overestimated without considering the rock fragments, while simulation using regular sets of Denitrification–Decomposition was coincide to the real N2O emissions without physical meanings. Our findings suggested that rock fragments should be considered in soil N cycling studies in the stony‐soil areas.

THE USE OF SOIL HYDRAULIC PROPERTIES AS INDICATORS FOR ASSESSING THE IMPACT OF MANAGEMENT PRACTICES UNDER SEMI-ARID CLIMATES

Water retention capacity and hydraulic conductivity are major soil hydraulic properties that influence soil quality and the environment. The objective of this work was to assess major soil hydraulic characteristics in response to the effect of soil management and tillage practices. Eight soil treatments were considered: conventional tillage, reduced tillage, no-tillage, fallow no-tillage, abandoned soil, compacted soil, plough on compacted soil, and application of super absorbent polymers. The experiments were conducted at Koohin station, Iran. The equality of field saturated hydraulic conductivity (Kfs) and estimated Kfs was studied. Moreover, the contribution of the porosity to soil water flux was investigated and quantified. At the -1500 kPa potential, water content was influenced by the compacted treatment at soil depth of 0 to 25 cm. In this study, van Genuchten water retention curve parameters n, a, and .r values were not significantly different among treatments. The fit of the van Genuchten equation to the soil water retention data resulted in low sum of squared errors. No distinct trend was observed for estimated sorptivity in the studied area. The sorptivity values were not significantly different among soil management practices. Moreover, estimated Kfs values by DISC software were lower than measured Kfs. Soil treatments did not influence the soil water-conducting medium and macropores. Unsaturated hydraulic conductivity may partly be affected by soil texture and soil structure which were uniform under all treatments. Soil water retention and transmission may be manipulated with changes in pore size distribution under different tillage and management practices in long-term.

Performance of the Groenevelt and Grant Model for Fitting Soil Water Retention Data from Brazilian Soils

ABSTRACT The soil water retention curve (SWRC) is essential for vadose zone hydrological modeling and related applications. In 2004, Groenevelt and Grant (GRT) presented a mathematical model for describing the SWRC and reported its mathematical versatility and good fit to soils from a Dutch database. In order to evaluate the application of GRT to SWRCs of Brazilian soils, we aimed to analyze the performance of GRT for 72 soils from Brazil. Besides that, the obtained results with GRT for these [...]