A new model for the soil‐water retention curve that solves the problem of residual water contents

Groenevelt, P. H.; Grant, C. D.

doi:10.1111/j.1365-2389.2004.00617.x

Cited by 144 publications

(148 citation statements)

References 14 publications

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“…VGN and VGA have a sigmoid shape and therefore are able to fit curves that have an inflection point. As Groenevelt and Grant (2004) pointed out, θ r serves as the third required shape parameter for curves with an inflection point, frequently resulting in improbable values for this parameter. Table 1 shows the fitting parameters and their physically permitted range.…”

Section: Parameter Fitting 321 Selected Parameterizationsmentioning

confidence: 99%

Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

Madi

Rooij

Mielenz

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Few parametric expressions for the soil water retention curve are suitable for dry conditions. Furthermore, expressions for the soil hydraulic conductivity curves associated with parametric retention functions can behave unrealistically near saturation. We developed a general criterion for water retention parameterizations that ensures physically plausible conductivity curves. Only 3 of the 18 tested parameterizations met this criterion without restrictions on the parameters of a popular conductivity curve parameterization. A fourth required one parameter to be fixed.We estimated parameters by shuffled complex evolution (SCE) with the objective function tailored to various observation methods used to obtain retention curve data. We fitted the four parameterizations with physically plausible conductivities as well as the most widely used parameterization. The performance of the resulting 12 combinations of retention and conductivity curves was assessed in a numerical study with 751 days of semiarid atmospheric forcing applied to unvegetated, uniform, 1 m freely draining columns for four textures.Choosing different parameterizations had a minor effect on evaporation, but cumulative bottom fluxes varied by up to an order of magnitude between them. This highlights the need for a careful selection of the soil hydraulic parameterization that ideally does not only rely on goodness of fit to static soil water retention data but also on hydraulic conductivity measurements.Parameter fits for 21 soils showed that extrapolations into the dry range of the retention curve often became physically more realistic when the parameterization had a logarithmic dry branch, particularly in fine-textured soils where high residual water contents would otherwise be fitted.

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Section: Parameter Fitting 321 Selected Parameterizationsmentioning

confidence: 99%

Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

Madi

Rooij

Mielenz

et al. 2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

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“…These WRCs, which will not be shown here, are taken from Groenevelt and Grant (2004) and Fredlund and Xing (1994).…”

Section: Water Retention Curvementioning

confidence: 99%

“…The two other WRCs tested for model performance were Groenevelt and Grant (2004) (GG04) and Fredlund and Xing (1994) (FX94). But prior to implementing them in the model they were both calibrated to be numerically similar near the dry end (θ ≤ 0.…”

Section: Water Retention Curves and Hydraulic Conductivity Functionsmentioning

confidence: 99%

A non-equilibrium model for soil heating and moisture transport during extreme surface heating: the soil (heat–moisture–vapor) HMV-Model Version 1

Massman

2015

Geosci. Model Dev.

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Abstract. Increased use of prescribed fire by land managers and the increasing likelihood of wildfires due to climate change require an improved modeling capability of extreme heating of soils during fires. This issue is addressed here by developing and testing the soil (heat-moisture-vapor) HMVmodel, a 1-D (one-dimensional) non-equilibrium (liquidvapor phase change) model of soil evaporation that simulates the coupled simultaneous transport of heat, soil moisture, and water vapor. This model is intended for use with surface forcing ranging from daily solar cycles to extreme conditions encountered during fires. It employs a linearized Crank-Nicolson scheme for the conservation equations of energy and mass and its performance is evaluated against dynamic soil temperature and moisture observations, which were obtained during laboratory experiments on soil samples exposed to surface heat fluxes ranging between 10 000 and 50 000 W m −2 . The Hertz-Knudsen equation is the basis for constructing the model's non-equilibrium evaporative source term. Some unusual aspects of the model that were found to be extremely important to the model's performance include (1) a dynamic (temperature and moisture potential dependent) condensation coefficient associated with the evaporative source term, (2) an infrared radiation component to the soil's thermal conductivity, and (3) a dynamic residual soil moisture. This last term, which is parameterized as a function of temperature and soil water potential, is incorporated into the water retention curve and hydraulic conductivity functions in order to improve the model's ability to capture the evaporative dynamics of the strongly bound soil moisture, which requires temperatures well beyond 150 • C to fully evaporate. The model also includes film flow, although this phenomenon did not contribute much to the model's overall performance. In general, the model simulates the laboratoryobserved temperature dynamics quite well, but is less precise (but still good) at capturing the moisture dynamics. The model emulates the observed increase in soil moisture ahead of the drying front and the hiatus in the soil temperature rise during the strongly evaporative stage of drying. It also captures the observed rapid evaporation of soil moisture that occurs at relatively low temperatures (50-90 • C), and can provide quite accurate predictions of the total amount of soil moisture evaporated during the laboratory experiments. The model's solution for water vapor density (and vapor pressure), which can exceed 1 standard atmosphere, cannot be experimentally verified, but they are supported by results from (earlier and very different) models developed for somewhat different purposes and for different porous media. Overall, this non-equilibrium model provides a much more physically realistic simulation over a previous equilibrium model developed for the same purpose. Current model performance strongly suggests that it is now ready for testing under field conditions.

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“…The higher the frequency of these additions, the closer plants are to steady state. Soil water status can then be transformed into soil water potential via a water release curve (Groenevelt and Grant 2004).…”

Section: F Soil Watermentioning

confidence: 99%

The art of growing plants for experimental purposes: a practical guide for the plant biologist

Poorter

Fiorani

Stitt

et al. 2012

Functional Plant Biol.

211

157

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Abstract. Every year thousands of experiments are conducted using plants grown under more-or-less controlled environmental conditions. The aim of many such experiments is to compare the phenotype of different species or genotypes in a specific environment, or to study plant performance under a range of suboptimal conditions. Our paper aims to bring together the minimum knowledge necessary for a plant biologist to set up such experiments and apply the environmental conditions that are appropriate to answer the questions of interest. We first focus on the basic choices that have to be made with regard to the experimental setup (e.g. where are the plants grown; what rooting medium; what pot size). Second, we present practical considerations concerning the number of plants that have to be analysed considering the variability in plant material and the required precision. Third, we discuss eight of the most important environmental factors for plant growth (light quantity, light quality, CO 2 , nutrients, air humidity, water, temperature and salinity); what critical issues should be taken into account to ensure proper growth conditions in controlled environments and which specific aspects need attention if plants are challenged with a certain a-biotic stress factor. Finally, we propose a simple checklist that could be used for tracking and reporting experimental conditions.

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A new model for the soil‐water retention curve that solves the problem of residual water contents

Cited by 144 publications

References 14 publications

Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

A non-equilibrium model for soil heating and moisture transport during extreme surface heating: the soil (heat–moisture–vapor) HMV-Model Version 1

The art of growing plants for experimental purposes: a practical guide for the plant biologist

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