Analyzing dual porosity in soil hydraulic properties using soil databases for pedotransfer function development

Zhang, Yonggen; Weihermüller, Lutz; Szabó, Brigitta; Noman, Muhammad Zaeem; Vereecken, Harry

doi:10.1002/vzj2.20227

Cited by 15 publications

(11 citation statements)

References 82 publications

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“…The results are in line with Y. Zhang, Weihermüller, et al. (2022), who found that, by relying on an extended soil database, including UNSODA, Vereecken, and EU‐HYDI, the joint fitting of soil water retention and hydraulic conductivity data (with

{K}_{s}

fixed and

{K}_{s}

fitted cases) outperformed the fitting of only soil water retention in terms of estimating hydraulic conductivity data. For a comprehensive comparison of different models in characterizing all the observed hydraulic conductivity data, please see Section 3.3.…”

Section: Resultssupporting

confidence: 87%

A Family of Soil Water Retention Models Based on Sigmoid Functions

Zuo

Zhang

2023

Water Resources Research

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The soil water retention curve is the fundamental soil hydraulic property to characterize soil water movement and solute transport. Many efforts have been devoted in the past decades to developing models to describe soil water retention curves. However, most of them are empirical equations or assume that soil pore size distributions conform to a lognormal distribution. Yet, few effects have been undertaken to systematically propose and compare a series of possible alternative probability density functions to describe the sigmoid retention curves with parameters physically explainable. Here, we proposed a family of five soil water retention models based on sigmoid functions with parameters of clear physical implications coinciding with the statistical measures of soil pore size distribution. Compared with the widely used models (i.e., Brooks & Corey, 1964; Kosugi, 1996; van Genuchten, 1980), the proposed models have somewhat improved performances to characterize water retention data for a wide range of soil textures without introducing additional model parameters. Two of the proposed models are capable of characterizing the observed two local extrema in the moisture capacity curves. The associated unsaturated hydraulic conductivity models of the proposed soil water retention models are also derived, which show superior performance in characterizing the observed hydraulic conductivities compared with competing models, especially in macropore regimes. Additionally, we analyzed the parameter‐equivalent conversion between the proposed and the existing models, and a simple linear regression equation can be used to derive the parameters of the proposed models from the existing and other alternative different proposed models.

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{K}_{s}

fixed and

{K}_{s}

Section: Resultssupporting

confidence: 87%

A Family of Soil Water Retention Models Based on Sigmoid Functions

Zuo

Zhang

2023

Water Resources Research

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“…Also, authors have excluded the conductivity data > -6 cm pressure head, and estimated the VGM parameters, but then used the matching point conductivity (𝐾 0 [LT -1 ]; (Weynants et al, 2009;Zhang and Schaap, 2017a;Zhang and Schaap, 2017b) to describe datasets of WRC and HCC. This also indicates the presence of bimodality, something which has been corroborated by a systematic analyses of some data bases by Zhang et al (2022). Although these models are often needed to adequately describe tabulated data of WRC and HCC (Zhang et al, 2022;Volk et al, 2016), there are currently no PTFs for multimodal VGM.…”

Section: Non-uniform Pore Size Density Distributionsmentioning

confidence: 73%

“…This also indicates the presence of bimodality, something which has been corroborated by a systematic analyses of some data bases by Zhang et al (2022). Although these models are often needed to adequately describe tabulated data of WRC and HCC (Zhang et al, 2022;Volk et al, 2016), there are currently no PTFs for multimodal VGM.…”

Section: Non-uniform Pore Size Density Distributionsmentioning

confidence: 73%

“…Most SHP models applied spatially explicit modelling assume unimodal pore size distribution. This may be an oversimplification in LSM application, especially in forested areas where biopores created by tree roots or bioturbation commonly occur (Fatichi et al, 2020) bimodal or multimodal soils are currently not available (Zhang et al, 2022). Therefore, modulation of current PTFs is achieved to account for this by using vegetation indices to account for biologically-induced soil structure (Fatichi et al, 2020;Bonetti et al, 2021).…”

Section: Spatial Validity and Methods Of Modulationmentioning

confidence: 99%

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Hydro-pedotransfer functions: A roadmap for future development

Weber

2023

Preprint

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<p>Hydro-pedotransfer functions (hyPTF) are important methods to relate available knowledge about soil properties to soil hydraulic properties and model parameters to be applied in process models. At least more than four decades have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental issues related to the scope and adequacy of current hyPTFs, particularly when applied to parameterise models at the field scale and beyond. Much of the hyPTF development process has focussed on refining and advancing the methods, while fundamental questions remain largely unanswered, namely i) how should hyPTFs be built for maximum prediction confidence, ii) which processes/properties need to be predicted to move beyond the van Genuchten-Mualem based parameterisation of the Richards equation, iii) which new datasets and data coverage are needed, iv) how does the measurement process of soil hydraulic properties determine the construction of hyPTFs and at which scale, iv) how can we incorporate diverging scales (scale of derivation vs scale of application), and v) what scaling/modulation/constraining strategies are affective to make hyPTF predictions at field-to-regional scale appropriate and physically meaningful? These questions have been addressed in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim to systematise hyPTF research and provide a roadmap guiding scientists, reviewers, and make users aware of the shortcomings.</p>

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“…The presence of macropores is mainly related to soil structure rather than to the primary soil particles that identify the textural class of a soil (Shang and Li, 2019). The use of a bimodal or multimodal water retention function ensures a proper description of the pore-size distribution which is given by the aggregation of the primary particles into secondary and tertiary particles (Li et al, 2014;Haghverdi 2020;Hassan et al 2022;Zhang et al, 2022). The flexibility of PSD models based on a large number of parameters (Fredlund et al, 2000) enhance the prediction performance of the two physico-empirical PTFs analyzed in this study.…”

Section: Articlementioning

confidence: 99%

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

Lazzaro,

Mazzitelli,

Sica

et al. 2023

J Agric Eng

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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.

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Analyzing dual porosity in soil hydraulic properties using soil databases for pedotransfer function development

Cited by 15 publications

References 82 publications

A Family of Soil Water Retention Models Based on Sigmoid Functions

A Family of Soil Water Retention Models Based on Sigmoid Functions

Hydro-pedotransfer functions: A roadmap for future development

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

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