Development of a world data set of soil water retention properties using pedotransfer rules

Geoderma ◽  
1996 ◽  
Vol 71 (1-2) ◽  
pp. 31-52 ◽  
Author(s):  
N.H. Batjes
2021 ◽  
pp. 51495
Author(s):  
Ruth M. Barajas‐Ledesma ◽  
Vanessa N. L. Wong ◽  
Karen Little ◽  
Antonio F. Patti ◽  
Gil Garnier

2013 ◽  
Vol 50 (4) ◽  
pp. 435-450 ◽  
Author(s):  
Christopher T.S. Beckett ◽  
Charles E. Augarde

Several models have been suggested to link a soil's pore-size distribution to its retention properties. This paper presents a method that builds on previous techniques by incorporating porosity and particles of different sizes, shapes, and separation distances to predict soil water retention properties. Mechanisms are suggested for the determination of both the main drying and wetting paths, which incorporate an adsorbed water phase and retention hysteresis. Predicted results are then compared with measured retention data to validate the model and to provide a foundation for discussing the validity and limitations of using pore-size distributions to predict retention properties.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 896 ◽  
Author(s):  
Amir Haghverdi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner

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.


2021 ◽  
Author(s):  
John R. Nimmo

<p>Most models of soil water retention represent the wettest range simplistically, reflecting a high priority on facilitating computation without recognition of the active physical processes. Commonly the wet range is misleadingly represented by a straight line of zero slope, or by default using the same formulation as for the middle range, even though the mechanisms of water retention are different for the wet and middle portions of the range. Though adequate for some purposes, such treatment causes problems for applications that are sensitive to wet-range processes. It prevents accurate prediction of critical but challenging wet-range phenomena such as domain exchange between preferential flow paths and soil matrix. It limits the choices available for quantifying flow problems, for example a blowing-up of derivatives on approach to saturation prohibits the use of diffusivity-based formulations.</p><p>A new model addresses these issues for the important case where the medium is soil matrix material exclusive of macropores, thus having a well-defined air-entry value, and the moisture dynamics are the typical wet and dry cycling that achieves maximum wetness at field saturation, with a presence of trapped air at zero matric potential. The range between the air-entry value and field saturation is dominated by trapped air expansion in response to pressure change, as well as a process that increases the sensitivity to changing matric pressure. This enhanced sensitivity may be related in part to a collapse of liquid bridges between air pockets as they expand. For this wet range, the new model incorporates the Boyles’ law inverse-proportionality of trapped air volume and pressure, amplified by an empirical factor to account for the additional processes. To cover the full range of possible moisture, this wet-range formula is supplemented by two others. The middle range of capillary advance/retreat and Haines jumps is represented by a new adaptation of the lognormal distribution function. The adsorption-dominated dry range is represented by a logarithmic relation used in earlier models. Joined together with a continuous first-derivative constraint, the overall formulation recognizes the dominant processes within three segments of the full range. Optimization of five parameters can fit the model to a full data set.</p><p>Tests have demonstrated excellent fits, using measured data that have many closely spaced points in the wet and middle ranges. With their basis in process, the model’s parameters have a strong physical interpretation, and potentially can be assigned values without fitting, from knowledge of fundamental relationships or individual measurements. This basis in process also may permit accommodation of hysteresis by a systematic adjustment of the relation between the wet and middle ranges, and with minimal additional data may serve to facilitate estimation of other properties such as hydraulic conductivity, diffusivity, and sorptivity.</p>


Pedosphere ◽  
2010 ◽  
Vol 20 (4) ◽  
pp. 456-465 ◽  
Author(s):  
B. GHANBARIAN-ALAVIJEH ◽  
A. LIAGHAT ◽  
Guan-Hua HUANG ◽  
M. Th. VAN GENUCHTEN

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