scholarly journals Pedotransfer functions for point and parametric estimations of soil water retention curve

2011 ◽  
Vol 52 (No, 7) ◽  
pp. 321-327 ◽  
Author(s):  
H. Merdun
Keyword(s):  
Soil Properties ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Coefficient Of Determination ◽  
Retention Data ◽  
Parametric Methods ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve

A water retention curve is required for the simulation studies of water and solute transport in unsaturated or vadose zone. Unlike the direct measurement of water retention data, pedotransfer functions (PTFs) have attracted the attention of researchers for determining water retention curves from basic soil properties. The objective of this study was to develop and validate point and parametric PTFs for the estimation of water retention curve from basic soil properties such as particle-size distribution, bulk density, and porosity using multiple-linear regression technique and comparing the performances of point and two parametric methods using some evaluation criteria. 140 soil samples were collected from three different databases and divided as 100 and 40 for the derivation and validation of the PTFs. All three methods predicted water contents at selected water potentials and combined water retention curves pretty well, but van Genuchten&rsquo;s model performed the best in prediction. However, the differences among the methods in point and water retention curve predictions were not statistically significant (p &gt; 0.05). Prediction accuracies were evaluated by the coefficient of determination (R<sup>2</sup>) and the root mean square error (RMSE) between the measured and predicted values. The R<sup>2</sup> and RMSE were 0.962 and 0.036, 0.994 and 0.067, and 0.946 and 0.082 for point and parametric (van Genuchten, and Brooks and Corey) methods, respectively, in predicting combined water retention curve. The three methods can be alternatively used in the estimation of water retention curves, but parametric methods are preferred for yielding continuous water retention functions used in flow and transport modeling.

scholarly journals Pedotransfer functions of soil water properties to estimate the S-index

2018 ◽  
Vol 22 (7) ◽  
pp. 465-470
Author(s):  
João H. Caviglione
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Field Conditions ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Coefficient Of Determination ◽  
Native Forest ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Soil Physical Quality

ABSTRACT One big challenge for soil science is to translate existing data into data that is needed. Pedotransfer functions have been proposed for this purpose and they can be point or parametric when estimating the water retention characteristics. Many indicators of soil physical quality have been proposed, including the S-Index proposed by Dexter. The objective of this study was to assess the use of pedotransfer functions for soil water retention to estimate the S-index under field conditions in the diversity of soils of the Paraná state. Soil samples were collected from 36 sites with textures ranging from sandy to heavy clay in the layers of 0-0.10 and 0.10-0.20 m and under two conditions (native forest and cultivated soil). Water content at six matric potentials, bulk density and contents of clay, sand and silt were determined. Soil-water retention curve was fitted by the van Genuchten-Mualem model and the S-index was calculated. S-index was estimated from water retention curves obtained by the pedotransfer function of Tomasella (point and parametric). Although the coefficient of determination varied from 0.759 to 0.895, modeling efficiency was negative and the regression coefficient between observed and predicted data was different from 1 in all comparisons. Under field conditions in the soil diversity of the Paraná state, restrictions were found in S-index estimation using the evaluated pedotransfer functions.

scholarly journals Modelling of soil-water retention curve considering the effects of existing salt solution in the pore fluid

2021 ◽  
Vol 337 ◽  
pp. 02001
Author(s):  
Hamed Sadeghi ◽  
Ali Golaghaei Darzi
Keyword(s):  
Soil Water ◽  
Osmotic Potential ◽  
Water Retention ◽  
Pore Fluid ◽  
Water Retention Curve ◽  
Model Parameters ◽  
Retention Data ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve

Soil-water retention curve (SWRC) has a wide application in geoenvironmental engineering from the predication of unsaturated shear strength to transient two-phase flow and stability analyses. Although various SWRC models have been proposed to take into account some influencing factors, less attention has been given to consider the effects of pore fluid osmotic potential. Therefore, the key objective of this study is to extend van Genchten’s model so that osmotic potential is considered as an independent factor governing the SWRC behavior. The new model comprises only six variables, which can be calibrated through minimal experimental measurements. More importantly, most of the model parameters have physical meaning by correlating macroscopic volumetric behavior and general trends of SWRC to osmotic potential. The results of validation tests revealed that the new osmotic-dependent SWRC model can predict the retention data in terms of both total and matric suction for two different soils and various molar concentrations very good. The proposed modeling approach does not require any advanced mercury intrusion porosimetry (MIP) tests, yet it can deliver excellent predictions by calibrating only six parameters which are far less than those incorporated into similar models for saline water permeating through the pore structure.

Evaluation of soil texture data for estimating soil water retention curve

2009 ◽  
Vol 89 (4) ◽  
pp. 461-471 ◽  
Author(s):  
B Ghanbarian-Alavijeh ◽  
A M Liaghat
Keyword(s):  
Soil Water ◽  
Soil Texture ◽  
Water Retention ◽  
Geometric Mean ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Statistical Parameters ◽  
Retention Curve

The soil water retention curve (SWRC) is one of the basic characteristics used in determining soil hydraulic properties, including unsaturated hydraulic conductivity. As its measurement is time consuming and difficult, much effort has been expended to develop indirect methods, such as pedotransfer functions and empirical relationships, to estimate SWRC. In this study, three methods were evaluated based on estimation of retention models parameters and, consequently, the soil water retention curve. For this purpose, soil data collected from three data bases, totaling 72 soil samples with 11 different textures, were used in this study. The statistical parameters such as: MR (mean of residual), RE (relative error), RMSE (root mean square error), AIC (Akaike’s information criterion) and GMER (geometric mean error ratio) showed that the Saxton et al. (1986) method estimates the soil water retention curve better than the other methods.Key words: Pedotransfer function, soil texture, soil water retention curve

scholarly journals Developing Pseudo Continuous Pedotransfer Functions for International Soils Measured with the Evaporation Method and the HYPROP System: I. The Soil Water Retention Curve

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3425
Author(s):  
Amninder Singh ◽  
Amir Haghverdi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Soil Samples ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Data Set ◽  
Retention Curve ◽  
Evaporation Method

Direct measurements of soil hydraulic properties are time-consuming, challenging, and often expensive. Therefore, their indirect estimation via pedotransfer functions (PTFs) based on easily collected properties like soil texture, bulk density, and organic matter content is desirable. This study was carried out to assess the accuracy of the pseudo continuous neural network PTF (PCNN-PTF) approach for estimating the soil water retention curve of 153 international soils (a total of 12,654 measured water retention pairs) measured via the evaporation method. In addition, an independent data set from Turkey (79 soil samples with 7729 measured data pairs) was used to evaluate the reliability of the PCNN-PTF. The best PCNN-PTF showed high accuracy (root mean square error (RMSE) = 0.043 cm3 cm−3) and reliability (RMSE = 0.061 cm3 cm−3). When Turkish soil samples were incorporated into the training data set, the performance of the PCNN-PTF was enhanced by 33%. Therefore, to further improve the performance of the PCNN-PTF for new regions, we recommend the incorporation of local soils, when available, into the international data sets and developing new sets of PCNN-PTFs.

scholarly journals Comparison Of Selected Pedotransfer Functions For The Determination Of Soil Water Retention Curves

2015 ◽  
Vol 23 (3) ◽  
pp. 33-36 ◽  
Author(s):  
Michal Kupec ◽  
Peter Stradiot ◽  
Štefan Rehák
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Undisturbed Soil ◽  
Retention Curve ◽  
Van Genuchten Model

Abstract Soil water retention curves were measured using a sandbox and the pressure plate extractor method on undisturbed soil samples from the Borská Lowland. The basic soil properties (e.g. soil texture, dry bulk density) of the samples were determined. The soil water retention curve was described using the van Genuchten model (Van Genuchten, 1980). The parameters of the model were obtained using the RETC program (Van Genuchten et al., 1991). For the determination of the soil water retention curve parameters, two pedotransfer functions (PTF) were also used that were derived for this area by Skalová (2003) and the Rosetta computer program (Schaap et al., 2001). The performance of the PTFs was characterized using the mean difference and root mean square error.

Retrieving Soil Physical Properties via Assimilating SMAP Brightness Temperature Observations in the Community Land Model

2021 ◽  
Author(s):  
Hong Zhao ◽  
Yijian Zeng ◽  
Xujun Han ◽  
Bob Su
Keyword(s):  
Soil Moisture ◽  
Physical Properties ◽  
Soil Properties ◽  
Water Retention ◽  
Soil Physical Properties ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve ◽  
Community Land Model

&lt;p&gt;Basic soil physical properties (i.e., soil texture and organic matter) and associated soil hydraulic properties (i.e., soil water retention curve and hydraulic conductivity) play an essential role in land surface models (LSMs) for estimating soil moisture. With the physical link between soil properties, LSMs and Radiative Transfer Models (RTMs), the soil physical properties can be retrieved, using a LSM coupled with a microwave L-band emission observation model in a data assimilation framework. To this purpose, this paper couples an enhanced physically-based discrete scattering-emission model with the Community Land Model 4.5 (CLM), to retreive soil physical properties using the Local Ensemble Transform Kalman Filter (LETKF) algorithm, assimilating Soil Moisture Active and Passive (SMAP) Level-1C (L1C) brightness temperature at H and V polarization ( and ) separately, assisted with in situ measurements at the Maqu site on the eastern Tibetan Plateau. Results show the improved estimate of soil properties at the topmost layer via assimilating SMAP ( H, V), as well as at profile using the retrieved top-layer soil properties and a prior depth ratio. The use of &amp;#160;and &amp;#160;shows varied sensitivities to retrievals of different soil compositions (i.e., sand, clay, silt) and soil moisture estimates. However, analyses show that the retrieved soil properties with fine accuracy are not sensitive factors affecting soil moisture estimates. Instead, uncertainties of CLM model structures shall be considered, such as the fixed PTFs (pedotransfer functions), the hydraulic function describing soil water retention curve and the water stress function determining root water update.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document