scholarly journals Soil Water Retention Modeling Using Pedotransfer Functions

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
R. K. Jaiswal ◽  
T. Thomas ◽  
R. V. Galkate ◽  
Jaivir Tyagi
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Water Retention ◽  
Graphical Representation ◽  
Numerical Models ◽  
Pedotransfer Functions ◽  
Coefficient Of Determination ◽  
Soil Water Retention ◽  
Soil Moisture Retention

The unsaturated hydraulic functions are key input data in numerical models of vadose zone processes. The direct measurement of soil moisture at different suction heads requires detailed analysis of soil samples with sophisticated instruments which can be replaced with the help of pedotransfer functions (PTFs) which are empirical relationships between the soil hydraulic properties and the more easily obtainable basic soil properties. The CalcPTF software has been used to compute the parameters of the most commonly used models of Brooks and Corey (BC) and Van Genuchten (VG) from PTFs for determination of soil water retention curves on seventeen sites in the commands of Benisagar and Rangawan reservoirs in Chhatarpur district (MP), India. The parameters of sixteen PTFs have been estimated and results have been compared with observed data using root mean square error (RMSE), coefficient of determination (R2), Radj2, and graphical representation. The PTF of BC model suggested by Rawls and Brakensiek, 1985 (BC-RB), has been found to be the best-fit PTF for sites 1, 2, 5, 6, 10, 11, 14, 15, and 17, where BC model by Saxton et al., 1986 (BC-SEL), can be used for modeling the soil moisture for sites 3, 4, 9, 12, and 16. It may be concluded that the PTF suggested by Rawls and Brakensiek, 1985 (BC-RB), or Saxton et al., 1986 (BC-SEL), can be used for computation of soil moisture retention curves in the region.

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 Evaluation of compost influence on soil water retention

2011 ◽  
Vol 59 (3) ◽  
pp. 227-232 ◽  
Author(s):  
Pavel Zemánek
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Water Retention ◽  
Soil Conditions ◽  
Soil Water Retention ◽  
Soil Moisture Sensors ◽  
Water Property ◽  
Compost Application ◽  
Soil Moisture Retention ◽  
Positive Effect

The experiment was focused on evaluation of influence of compost application on soil water retention. Soil retention is a major soil water property that governs soil functioning as a ecosystem. Soil moisture forms a major buffer against flooding, and water capacity in subsoil is a major factor for plant growth. The effects of changes in soil water retention depend on the proportions of the textural components and the amount of organic carbon present in the soil. During seasons of 2009 and 2010, experiments at two sites of different soil conditions prepared by addition of compost doses of 50 and 100 t.ha−1 were carried out. Changes of humidity were continuously monitored and recorded by soil moisture sensors. Results showed that application of compost of above mentioned doses positively affected water retention of the soil. Organic matter, applied at the above mentioned amount has a positive effect on soil moisture retention, regardless of possible influence of soil type, grassing and amount of rainfalls. Outcomes of experiment become bases for recommended compost doses as well as for technical proposal of compost application processes.

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.

scholarly journals Assessment of pedotransfer functions for estimating soil water retention curves for the amazon region

2014 ◽  
Vol 38 (3) ◽  
pp. 730-743 ◽  
Author(s):  
João Carlos Medeiros ◽  
Miguel Cooper ◽  
Jaqueline Dalla Rosa ◽  
Michel Grimaldi ◽  
Yves Coquet
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Soil Layer ◽  
Direct Determination ◽  
Exchange Capacity ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Spatial And Temporal Variability ◽  
Soil Water Retention Curve ◽  
Soil Water Retention

Knowledge of the soil water retention curve (SWRC) is essential for understanding and modeling hydraulic processes in the soil. However, direct determination of the SWRC is time consuming and costly. In addition, it requires a large number of samples, due to the high spatial and temporal variability of soil hydraulic properties. An alternative is the use of models, called pedotransfer functions (PTFs), which estimate the SWRC from easy-to-measure properties. The aim of this paper was to test the accuracy of 16 point or parametric PTFs reported in the literature on different soils from the south and southeast of the State of Pará, Brazil. The PTFs tested were proposed by Pidgeon (1972), Lal (1979), Aina & Periaswamy (1985), Arruda et al. (1987), Dijkerman (1988), Vereecken et al. (1989), Batjes (1996), van den Berg et al. (1997), Tomasella et al. (2000), Hodnett & Tomasella (2002), Oliveira et al. (2002), and Barros (2010). We used a database that includes soil texture (sand, silt, and clay), bulk density, soil organic carbon, soil pH, cation exchange capacity, and the SWRC. Most of the PTFs tested did not show good performance in estimating the SWRC. The parametric PTFs, however, performed better than the point PTFs in assessing the SWRC in the tested region. Among the parametric PTFs, those proposed by Tomasella et al. (2000) achieved the best accuracy in estimating the empirical parameters of the van Genuchten (1980) model, especially when tested in the top soil layer.

Multiscale Pedotransfer Functions for Soil Water Retention

2007 ◽  
Vol 6 (4) ◽  
pp. 868-878 ◽  
Author(s):  
Raghavendra B. Jana ◽  
Binayak P. Mohanty ◽  
Everett P. Springer
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Soil Water Retention

The effects of biochar on the physical properties of bare soil

2012 ◽  
Vol 103 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Francesca Ventura ◽  
Fiorenzo Salvatorelli ◽  
Stefano Piana ◽  
Linda Pieri ◽  
Paola Rossi Pisa
Keyword(s):  
Soil Moisture ◽  
Bulk Density ◽  
Soil Water ◽  
Agricultural Soil ◽  
Water Retention ◽  
Bare Soil ◽  
Soil Water Retention ◽  
Experimental Scheme ◽  
Dark Colour ◽  
Key Factor

ABSTRACTThe pyrolysis conversion of vegetable residues into energy and biochar, and its incorporation in agricultural soil, reduces CO2emission and provides a longterm soil carbon sequestration. Moreover, biochar application in soil seems to increase nutrient stocks in the rooting layer, improving crop yield. Compared with the numerous studies assessing the positive effect of biochar on yield, however, little research has been published elucidating the mechanisms responsible for the reported benefits. Few studies cited soil moisture as the key factor, attributing the increased yield to the higher soil water availability.The aim of this study was to investigate the effect of biochar on the physical and hydraulic properties of a bare Padana Plain (Cadriano, Bologna) agricultural soil. A preliminary plot experiment in 2009 explored the influence of 10 and 30 kg ha–1of biochar on soil moisture, without effects from plants. Results of the first experiment suggested using higher biochar rates in a similar experimental scheme. During the second experiment, 30 and 60 t ha–1doses were investigated. Soil water content, bulk density, electrical conductivity and soil water retention were measured. The comparison between treated soils and the control indicates that the biochar rate is directly correlated to electrical conductibility and inversely correlated with bulk density. The effect on the density of soil can be very positive in case of heavy soils. The dark colour of the char increased the surface temperature with respect to the control, while no differences were detected at 7·5 cm depth. No influences were found on other soil characteristics, including soil pH, moisture and water retention.

Uncertainty analysis for large-scale prediction of the van Genuchten soil-water retention parameters with pedotransfer functions

Soil Research ◽  
2014 ◽  
Vol 52 (5) ◽  
pp. 431 ◽  
Author(s):  
K. Liao ◽  
S. Xu ◽  
J. Wu ◽  
Q. Zhu
Keyword(s):  
Soil Properties ◽  
Soil Water ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Soil Water Retention ◽  
Input Uncertainty ◽  
Spatial Estimation ◽  
Uncertainty Measurement ◽  
Error Bars ◽  
Retention Parameters

Hydrological, environmental and ecological modellers require van Genuchten soil-water retention parameters that are difficult to measure. Pedotransfer functions (PTFs) are thus routinely applied to predict hydraulic parameters (θs, ln(α) and n) from basic soil properties (e.g. bulk density, soil texture and organic matter content). This study investigated the spatial variations of van Genuchten parameters via geostatistical methods (e.g. kriging and co-kriging with remote-sensing data) and multiple-stepwise-regression-based PTFs with a limited number of samples (58) collected in Pingdu City, Shandong Province, China. The uncertainties in the spatial estimation of van Genuchten parameters were evaluated using bootstrap and Latin hypercube sampling methods. Results show that PTF-estimated parameters are less varied than observed parameters. The uncertainty in the parameter estimation is mainly due to the limited number of samples used for deriving PTFs (intrinsic uncertainty) and spatial interpolations of basic soil properties by (co)kriging (input uncertainty). When considering the intrinsic uncertainty, 36%, 29% and 47% of measurements are within the corresponding error bars (95% confidence intervals of the predictions) for the θs, ln(α) and n, respectively. When considering both intrinsic and input uncertainties, 86%, 66% and 88% of observations are within the corresponding error bars for the θs, ln(α) and n, respectively. Therefore, the input uncertainty is more important in the spatial estimation of van Genuchten parameters than the intrinsic uncertainty. Measurement of basic soil properties at high resolution and properly use of powerful spatial interpolation approach are both critical in the accurate spatial estimation of van Genuchten parameters.

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