Saturated hydraulic conductivity model computed from bimodal water retention curves for a range of New Zealand soils

Pollacco, Joseph Alexander Paul; Webb, T. H.; McNeill, Stephen; Hu, Wei; Carrick, Sam; Hewitt, Allan E.; Lilburne, Linda

doi:10.5194/hess-21-2725-2017

Cited by 34 publications

(19 citation statements)

References 46 publications

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“…Assouline and Or (2013) review numerous expressions for the saturated hydraulic conductivity. Interestingly, approaches have emerged to estimate the saturated hydraulic conductivity from the retention curve parameters Pollacco et al, 2013Pollacco et al, , 2017.…”

Section: Introductionmentioning

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: Introductionmentioning

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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“…We note that the presented double prediction hyPTF does not alleviate problems mentioned in the literature relating to unconsidered effects of stone content on SHPs (Nasri et al, 2015;Tetegan et al, 2015), on organic (Wallor et al, 2018), forest (Puhlmann & von Wilpert, 2012), or multimodal soils (Pollacco et al, 2017). In addition, the effects of dynamic nonequilibrium Šimůnek & van Genuchten, 2008) and macropore flow are not captured, since in the sense of the BW-VGM model, only an application to matrix flow is possible.…”

Section: 1029/2019wr026820mentioning

confidence: 85%

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

Weber

Finkel

Gonçalves

et al. 2020

Water Resources Research

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Modeling 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/package¼spsh). Plain Language Summary Soil hydraulic property models are mathematical functions, which describe the relationship between the soil water pressure head and the state of soil water saturation, on the one hand, and the soil water pressure head and the unsaturated soil hydraulic conductivity, on the other. These types of mathematical functions are flexible by adjustable parameters. With one set of model equations, the hydraulic properties of soils which may have very different properties due to their vast natural variability can be described. The models treated in this work are (i) the van Genuchten-Mualem model, a model with well-known problems, but still frequently applied, and (ii) a relatively new physical comprehensive model, named the Brunswick model. First of all, in a data-based comparison of model performance, we demonstrate that the Brunswick model has systematic advantages. Second, knowledge about these above-mentioned parameters can be determined through other mathematical functions, so-called hydro-pedotransfer functions, which empirically relate these parameters to observed soil properties. The information about these soil properties can be measured in the laboratory and is also recorded in soil maps. We created a new pedotransfer function to facilitate the predictio...

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“…Previous work has shown that the S SA of soil is closely dependent upon the soil texture and could be estimated from the soil properties and PSD (Sepaskhah and Tafteh, 2013;Resurreccion et al, 2015). The method used to estimate the S SA in Sect.…”

Section: The Effects Of the Estimated S Samentioning

confidence: 99%

“…The soil water retention curve (SWRC), which represents the relationship between the water pressure and water content, is fundamental to researching water flow and chemical transport in unsaturated media (Pollacco et al, 2017). Direct measurements of the SWRC consume both time and money (Arya and Paris, 1981;Mohammadi and Vanclooster, 2011), while estimating the SWRC from the particle size distribution (PSD) is both rapid and economical.…”

Section: Introductionmentioning

confidence: 99%

Predicting the soil water retention curve from the particle size distribution based on a pore space geometry containing slit-shaped spaces

Chang

Cheng

2018

Hydrol. Earth Syst. Sci.

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Abstract. Traditional models employed to predict the soil water retention curve (SWRC) from the particle size distribution (PSD) always underestimate the water content in the dry range of the SWRC. Using the measured physical parameters of 48 soil samples from the UNSODA unsaturated soil hydraulic property database, these errors were proven to originate from an inaccurate estimation of the pore size distribution. A method was therefore proposed to improve the estimation of the water content at high suction heads using a pore model comprising a circle-shaped central pore connected to slit-shaped spaces. In this model, the pore volume fraction of the minimum pore diameter range and the corresponding water content were accordingly increased. The predicted SWRCs using the improved method reasonably approximated the measured SWRCs, which were more accurate than those obtained using the traditional method and the scaling approach in the dry range of the SWRC.

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Saturated hydraulic conductivity model computed from bimodal water retention curves for a range of New Zealand soils

Cited by 34 publications

References 46 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

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

Predicting the soil water retention curve from the particle size distribution based on a pore space geometry containing slit-shaped spaces

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