Evaluation of Soil Water Retention Models Based on Basic Soil Physical Properties

1995 ◽  
Vol 59 (4) ◽  
pp. 1134-1141 ◽  
Author(s):  
Jeffrey S. Kern
Keyword(s):  
Physical Properties ◽  
Soil Water ◽  
Water Retention ◽  
Soil Physical Properties ◽  
Soil Water Retention ◽  
Retention Models

Soil Physical Properties of Tied Ridges in the Sudan Savannah of Burkina Faso

1988 ◽  
Vol 24 (3) ◽  
pp. 375-384 ◽  
Author(s):  
N. R. Hulugalle ◽  
M. S. Rodriguez
Keyword(s):  
Physical Properties ◽  
Soil Temperature ◽  
Bulk Density ◽  
Soil Water ◽  
Water Retention ◽  
Clay Content ◽  
Soil Physical Properties ◽  
Water Infiltration ◽  
Soil Water Retention ◽  
Maize Varieties

SUMMARYThe soil physical properties of tied ridges were measured in a trial, established in 1983, comparing three treatments: handhoe cultivation and planting on the flat; planting directly without any cultivation on tied ridges constructed the previous year; and handhoe cultivation and remoulding of tied ridges constructed the previous year. Two maize varieties and two management levels were used. The soil properties monitored were particle size distribution, penetro-meter resistance in the surface 20 mm, bulk density, water infiltration, soil water retention and soil temperature.Soil physical properties were affected mainly by the type of seedbed. Clay content in the surface 0.05 m was greater with tied ridging, with that in the furrows being higher than that in the ridge slopes. Daily maximum soil temperature was greatest in the flat planted plots and in the ridge slopes of the tied ridged plots. Penetrometer resistance at a soil water content of 0.05 kg kg−1 was greater in the tied ridged plots. Cumulative infiltration after 2 h was greatest with flat planting. The bulk density of ridge slopes in tied ridged plots was less than that in the furrows and in the flat planted plots. Soil water retention was greatest in the furrows of the tied ridged plots. Clay content was the major factor determining all the soil physical properties measured.

scholarly journals Topography and spatial variability of soil physical properties

2009 ◽  
Vol 66 (3) ◽  
pp. 338-352 ◽  
Author(s):  
Marcos Bacis Ceddia ◽  
Sidney Rosa Vieira ◽  
André Luis Oliveira Villela ◽  
Lenilson dos Santos Mota ◽  
Lúcia Helena Cunha dos Anjos ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Physical Properties ◽  
Bulk Density ◽  
Soil Water ◽  
Water Retention ◽  
Particle Density ◽  
Soil Physical Properties ◽  
Soil Water Retention ◽  
Soil Attributes ◽  
Physical Attributes

Among the soil formation factors, relief is one of the most used in soil mapping, because of its strong correlation with the spatial variability of soil attributes over a landscape. In this study the relationship between topography and the spatial variability of some soil physical properties was evaluated. The study site, a pasture with 2.84 ha, is located near Seropédica, Rio de Janeiro State, Brazil, where a regular square grid with 20 m spacing was laid out and georreferenced. In each sampling point, altitude was measured and undisturbed soil samples were collected, at 0.0-0.1, 0.1-0.2, and 0.2-0.3 m depths. Organic carbon content, soil texture, bulk density, particle density, and soil water retention at 10 (Field Capacity), 80 (limit of tensiometer reading) and 1500 kPa (Permanent Wilting Point) were determined. Descriptive statistics was used to evaluate central tendency and dispersion parameters of the data. Semivariograms and cross semivariograms were calculated to evaluate the spatial variability of elevation and soil physical attributes, as well as, the relation between elevation and soil physical attributes. Except for silt fraction content (at the three depths), bulk density (at 0.2-0.3 m) and particle density (at 0.0-0.1 m depth), all soil attributes showed a strong spatial dependence. Areas with higher elevation presented higher values of clay content, as well as soil water retention at 10, 80 and 1500 kPa. The correlation between altitude and soil physical attributes decreased as soil depth increased. The cross semivariograms demonstrated the viability in using altitude as an auxiliary variable to improve the interpolation of sand and clay contents at the depth of 0.0-0.3 m, and of water retention at 10, 80 and 1500 kPa at the depth of 0.0-0.2 m.

scholarly journals A new approach in comparison and evaluation of the overall accuracy of six soil-water retention models using statistical benchmarks and fuzzy method

2021 ◽  
Author(s):  
Mohammad Nakhaei ◽  
Amin Mohebbi Tafreshi ◽  
Ghazaleh Mohebbi Tafreshi
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Water Retention Curve ◽  
Suitable Model ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve ◽  
Fuzzy Method ◽  
Retention Models ◽  
Multi Criteria Evaluation

Abstract In this research, six samples of valid and widely soil-water retention curve (SWRC) estimation models, including van Genuchten, Brooks and Corey, Fredlund and Xing, Durner, Kosugi, and Seki were studied. To realize this approach, in the first step, the accuracy of each model was calculated using ten statistical benchmarks, and then the numbers obtained from the fitting accuracy were standardized based on each benchmark by the standard fuzzy method so that all of them had a similar scale. Finally, with the sum of the fuzzy standardized values, an index for each model was obtained as a new index called the Best-Fit Model (BFM) index, which was the basis for comparing and evaluating the overall accuracy of the models in each soil texture. Accordingly, if the BMF index is more extensive and closer to 10, the model is more fitted and gets a higher rating. The superiority of this method to other similar studies is that here, as in the multi-criteria evaluation methods, it can simultaneously assess in terms of different statistical benchmarks and ranking the models according to the diversity in the reaction of each to various benchmarks provided. The results showed that Brooks and Corey model with the lowest and the Durner model with the highest BMF and rank among other models in most soil textures are considered as the weakest and as the most suitable model from the overall accuracy viewpoint of fitting based on the approach used throughout this study, respectively.

scholarly journals 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

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 900 ◽  
Author(s):  
Amir Haghverdi ◽  
Mohsen Najarchi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner
Keyword(s):  
High Resolution ◽  
Soil Water ◽  
Water Retention ◽  
The United States ◽  
Retention Data ◽  
Soil Water Retention ◽  
Retention Models ◽  
Direct Model ◽  
Free Parameters ◽  
Measured Water

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.

Scaling analysis of soil water retention parameters and physical properties of a Chinese agricultural soil

Soil Research ◽  
2009 ◽  
Vol 47 (8) ◽  
pp. 821 ◽  
Author(s):  
Zhenying Wang ◽  
Qiaosheng Shu ◽  
Zuoxin Liu ◽  
Bingcheng Si
Keyword(s):  
Physical Properties ◽  
Water Content ◽  
Soil Water ◽  
Agricultural Soil ◽  
Water Retention ◽  
Residual Water ◽  
Soil Water Retention ◽  
Fractal Scaling ◽  
Scaling Property ◽  
Retention Parameters

Measurement scale of soil water retention parameters is often different from the application scale. Knowledge of scaling property of soil hydraulic parameters is important because scaling allows information to be transferred from one scale to another. The objective of this study is to examine whether these parameters have fractal scaling properties in a cultivated agricultural soil in China. Undisturbed soil samples (128) were collected from a 640-m transect at Fuxin, China. Soil water retention curve and soil physical properties were measured from each sample, and residual water content (θr), saturated soil water content (θs), and parameters αvG and n of the van Genuchten water retention function were determined by curve-fitting. In addition, multiple scale variability was evaluated through multifractal analyses. Mass probability distribution of all properties was related to the support scale in a power law manner. Some properties such as sand content, silt content, θs, and n had mono-fractal scaling behaviour, indicating that, whether for high or low data values, they can be upscaled from small-scale measurements to large-scale applications using the measured data. The spatial distribution of organic carbon content had typically multifractal scaling property, and other properties – clay content, θr, and αvG – showed a weakly multifractal distribution. The upscaling or downscaling of multifractal distribution was more complex than that of monofractal distribution. It also suggested that distinguishing mono-fractals and multifractals is important for understanding the underlying processes, for simulation and for spatial interpolation of soil water retention characteristics and physical properties.

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