Comparison Between Particle Size Distribution as a Predictor of Pedotransfer Functions using Laser Diffraction and Sedimentation Methods

Mady, Ahmed Yehia; Шеин, Е. В.

doi:10.3923/ijss.2017.65.71

Cited by 10 publications

(6 citation statements)

References 15 publications

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“…This result was in agreement with the HYDRUS-1D program [17], which was used for estimating thermal conductivity and thermal regime using the model of Chung and Horton [16] and the parameters of the model were estimated using only soil texture [17]. Also, Mady and Shein [26] found that the soils which have the same texture, have same soil physical characteristics. Moreover, Ghader [20], studied the effect of the bulk density on increasing the thermal properties of clay-loam soil which was more than that of moisture content.…”

Section: The Efficiency Of Ptf For Predicating Soil Thermal Diffusivitysupporting

confidence: 82%

Estimating Soil Thermal Diffusivity Using Pedotransfer Functions with Nonlinear Regression

Mady¹,

Шеин²

2018

TOASJ

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Background and Objective:Pedotransfer Functions (PTFs) are widely used for estimating soil thermal diffusivity. Some attempts have been made to indirectly predict soil thermal diffusivity from the easy available fundamental soil physics properties. The aim of the work was to validate usage PTFs with Nonlinear Regression (NLR) for estimating soil thermal diffusivity (KD), moreover was to select the best predictor variables used for determination of PTFs.Materials and Methods:Soil thermal diffusivity was measured at different values of water content using Kondratieff method. The parameters of the quadratic equation, which described the relation between thermal diffusivity and water content, were determined by the fitting curve and using PTFs (exponential equations) based on soil physical properties. The Combination of different soil physical properties used as PTF model’s independent variables was tested. Three classes of PTFs were proposed using NLR to estimate KDwere: KDPTF-1 (Sand+ Silt+ Clay), KDPTF-2 (Sand+ Silt+ Clay + Bulk density), and KDPTF-3 (Sand+ Silt+ Clay+ Bulk density + Organic matter).Results:The best class of PTF could be used for calculating the parameters of the quadratic equation and soil thermal diffusivity, was KDPTF-1 which taking into account the percentage of sand, silt and clay, RMSE=2.94×10-8m2/s, and GMER =1.05.Conclusion:The quadratic and exponential equations were representing the nonlinear regression equations, which could be used for estimating soil thermal diffusivity at different values of water content from easily available data on soil texture, bulk density, and organic matter content.

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Section: The Efficiency Of Ptf For Predicating Soil Thermal Diffusivitysupporting

confidence: 82%

Estimating Soil Thermal Diffusivity Using Pedotransfer Functions with Nonlinear Regression

Mady¹,

Шеин²

2018

TOASJ

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“…PSD represents the most significant soil physical and even some soil chemical properties (Centeri et al 2015). It is the most vital characteristic affecting pore geometry, porosity, pore size distribution, solid surface area, hydrophysical, and thermo-physical characteristics (Cartacuzencu et al 2014;Mady and Shein 2017).…”

Section: Discussionmentioning

confidence: 99%

Mineralogical and petrographical studies of agricultural soil, Assiut Governorate, Egypt

et al. 2019

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Background: The lack of information about the Egyptian soil needs more attention, especially mineralogical, petrographical studies, and quality data. Thus, the aim of this study was to evaluate the physicochemical parameters of north Assiut agricultural soil; pH, moisture%, CaCO 3 %, organic matter (OM%), and mineralogical contents of the studied soil. Results: The studied soil is characterized by alkaline nature, low organic matter, and high CaCO 3 %. Mineralogically, the studied agricultural soil samples consist mainly of quartz, plagioclase, and minor calcite (as non-clay minerals), as well as montmorillonite, vermiculite, and illite in decreasing abundance order as clay minerals. The plagioclase consists of two minerals; calcined albite and anorthite. Conclusion:The clay minerals in the studied soils may be derived from the old alluvial plain (Plio-Pleistocene sediments) by successive Nile floods and reworking. The recorded clay minerals in the studied soils are montmorillonite, vermiculite, and illite in decreasing order of abundance. They have the ability to retain the irrigation water and adsorb more exchangeable cations in aqueous media which can feed the plants.

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“…The parameters of van Genuchten (θr and α) calculated based on PSD-LDT were usually smaller than the calculated by PSD-PM. The reason of that is related to the percentage of clay measured by LDT was smaller than its measurement by PM as Figure 3c (Di Stefano et al, 2010;Mady and Shein, 2017). While the calculated parameters (θs and n) based on PSD-LDT were larger than those calculated by PSD-PM.…”

Section: Soil Hydraulic Propertiesmentioning

confidence: 84%

“…Moreover, there is no agreement between PSD-PM and PSD-LDT as Figure 3. So, utilizing PSD-LDT in the predictive programs tend to large estimation error especially, if this difference leads to a change in soil texture (Mady and Shein, 2017).…”

Section: Evaluation Of Psd Measured By Ldt and Pmmentioning

confidence: 99%

“…Although LDT is a simple and fast method for PSD estimation, however it has estimated a smaller content of clay and larger content of silt compared to sedimentation method measurements (Di Stefano et al, 2010;Polakowski et al, 2014;Mady and Shein, 2017). The efficiency of LDT is based mainly on a dispersing agent (Ryżak and Bieganowski, 2011;Makó et al, 2014;Mady and Shein, 2017). Moreover, the shape of sand particles influences the PSD estimation using LDT (Polakowski et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Optimizing particle size distribution measured by laser diffraction technique for estimating soil hydraulic properties

Mady¹,

Шеин²

2019

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Particle size distribution (PSD) is the fundamental characteristic that gives information about soil physical properties. It is the essential predictor used in most predictive programs for predicting water flux, solute, and heat transport in soil. Predictive programs such as Rosetta, RETC, and HYDRUS-1D are usually used PSD measured by the pipette method (PM), whereas the usage of PSD measured by laser diffraction technique (LDT) yields a large estimation error in heavy soil. The aim of the work was to optimize PSD measured by LDT for approaching to PSD measured by PM by suggesting Pedotransfer functions (PTFs). Furthermore, it is to evaluate the efficiency of PSD calculated by the proposed PTFs for estimating soil hydraulic properties using Rosetta program. Particle size distribution was measured by two methods: LDT and PM using the same dispersion factor (sodium pyrophosphate solution 4%). Proposed PTFs were derived for calculation of particle size distribution using a linear regression between PSD measured by LDT as an independent variable and PSD measured by PM as a dependent variable. PSD calculated using proposed PTFs leads to optimize values of PSD measured by LDT for approaching to values of PSD measured by PM. Optimizing PSD by proposed PTFs was suitable for calculating soil hydraulic parameters using Rosetta program with a little estimation error, for agro-soddy podzolic with soil texture as silty loam and silty clay loam.

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Comparison Between Particle Size Distribution as a Predictor of Pedotransfer Functions using Laser Diffraction and Sedimentation Methods

Cited by 10 publications

References 15 publications

Estimating Soil Thermal Diffusivity Using Pedotransfer Functions with Nonlinear Regression

Estimating Soil Thermal Diffusivity Using Pedotransfer Functions with Nonlinear Regression

Mineralogical and petrographical studies of agricultural soil, Assiut Governorate, Egypt

Optimizing particle size distribution measured by laser diffraction technique for estimating soil hydraulic properties

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