Effects of Clay Type and Content, Exchangeable Sodium Percentage, and Electrolyte Concentration on Clay Dispersion and Soil Hydraulic Conductivity

1978 ◽  
Vol 42 (1) ◽  
pp. 32-39 ◽  
Author(s):  
H. Frenkel ◽  
J. O. Goertzen ◽  
J. D. Rhoades
1969 ◽  
Vol 41 (1) ◽  
pp. 25-34
Author(s):  
Juan A. Bonnet ◽  
Eduardo J. Brenes

1. The area of soils surveyed in Lajas Valley was 24,656 acres. 2. The soils were classified into normal, saline, saline-alkali, and non- saline-alkali at depths of 0 to 8, 8 to 24, 24 to 48, and 48 to 72 inches, respectively. 3. A large percentage of normal soils was found in the upper soil layer and of saline-alkali soils in the lower layers. 4. Normal soils occupied about 86 percent of the surface area to a depth of 8 inches and about 63 percent at a depth of 8 to 24 inches. 5. Soils with a salinity problem increased from 9 percent at a depth of 8 inches to 28.3, 58.8 and 68.5 percent, respectively, at depths of 8 to 24, 24 to 48, and 48 to 72 inches. 6. The soils with a salinity problem were largely of the saline-alkali class. 7. In four soil-profile samples taken from Lajas Valley, the saturation percentage varied from 58 to 191, the electrical conductivity from 0.8 to 28.4 millimhos per centimeter, the exchangeable-sodium percentage from 2.2 to 46.0, the soil pH from 8.1 to 8.9, the content of gypsum from 0 to 21.9 tons per acre-foot, the gypsum requirement from 0 to 23.8 tons per acre-foot, and the hydraulic conductivity from less than 0.005 to 6.24 inches of water per hour. Higher gypsum contents were found in the deep subsoil layers of two soils (profiles 1 and 4). Amounts of gypsum varying from 9.9 to 20.3 tons per acre-foot of depth, are required for the reclamation of the surface layers of these two profiles. In general, the hydraulic- conductivity values show that the soil-surface layers are more permeable than the subsoil layers. 8. The procedure and methods used in this paper were found to be accurate, simple, rapid, and practical. They are recommended for the coordination of data related to the classification and reclamation of soils affected by salinity problems in the different countries of the world.


Geoderma ◽  
2021 ◽  
Vol 404 ◽  
pp. 115297
Author(s):  
Awedat Musbah Awedat ◽  
Yingcan Zhu ◽  
John McLean Bennett ◽  
Steven R. Raine

Revista CERES ◽  
2014 ◽  
Vol 61 (5) ◽  
pp. 715-722 ◽  
Author(s):  
Jefferson Luiz de Aguiar Paes ◽  
Hugo Alberto Ruiz ◽  
Raphael Bragança Alves Fernandes ◽  
Maria Betânia Galvão dos Santos Freire ◽  
Maria de Fatima Cavalcanti Barros ◽  
...  

Hydraulic conductivity is determined in laboratory assays to estimate the flow of water in saturated soils. However, the results of this analysis, when using distilled or deionized water, may not correspond to field conditions in soils with high concentrations of soluble salts. This study therefore set out to determine the hydraulic conductivity in laboratory conditions using solutions of different electrical conductivities in six soils representative of the State of Pernambuco, with the exchangeable sodium percentage adjusted in the range of 5-30%. The results showed an increase in hydraulic conductivity with both decreasing exchangeable sodium percentage and increasing electrical conductivity in the solution. The response to the treatments was more pronounced in soils with higher proportion of more active clays. Determination of hydraulic conductivity in laboratory is routinely performed with deionized or distilled water. However, in salt affected soils, these determinations should be carried out using solutions of electrical conductivity different from 0 dS m-1, with values close to those determined in the saturation extracts.


Soil Research ◽  
2011 ◽  
Vol 49 (1) ◽  
pp. 56 ◽  
Author(s):  
N. S. Jayawardane ◽  
E. W. Christen ◽  
M. Arienzo ◽  
W. C. Quayle

Effects of soil solution cation concentrations and ratios on hydraulic properties must be understood in order to model soil water flow in reactive soils or develop guidelines for sustainable land application of wastewater. We examined effects of different ratios and concentrations of the cations Ca2+, Mg2+, Na+, and K+, using hydraulic conductivity measurements in repacked soil cores, as an indicator of soil structural stability. We examined widely used indices—sodium, potassium, and monovalent cation absorption ratios (SAR, PAR, MCAR)—which assume that the flocculating effects of Ca2+ and Mg2+ are the same, and the dispersive effects of Na+ and K+ are the same. Our laboratory measurements indicate that at any given values of MCAR, the reductions in soil hydraulic conductivity with decrease in electrolyte concentration are not identical for different cation combinations in solution. The hydraulic conductivity curves showed a marked lateral shifting for both the surface and subsurface soils from a winery wastewater application site. This indicates that MCAR is inadequate as a soil stability parameter in soil solutions containing a mixture of Na+, K+, Ca2+, and Mg2+. We employed an unpublished equation that was proposed by P. Rengasamy as a modified index of soil stability for mixed cation combinations, using calculated relative flocculating powers of different cations (‘CROSS’, cation ratio of structural stability). Our observation of lateral shift in hydraulic conductivity measurements at any value of MCAR appears to relate to changes in CROSS values for all cation combinations tested, except for K–Mg solutions, for which a more generalised CROSS equation with modified parameters seems more suitable for calculating the CROSS value. Appropriate modified parameters for use in this generalised CROSS equation were determined empirically, using the experimental data. We derived a combination of threshold electrolyte concentration and CROSS values required to maintain high hydraulic conductivity for the soils at a winery wastewater application site. The potential use of this relationship in developing management practices for sustainable wastewater management at the site is discussed. Further research on the applicability of CROSS and generalised CROSS equations for other soils in the presence of different mixed cation combinations is needed.


Soil Research ◽  
2013 ◽  
Vol 51 (1) ◽  
pp. 23 ◽  
Author(s):  
Mohammad Reza Neyshabouri ◽  
Mehdi Rahmati ◽  
Claude Doussan ◽  
Boshra Behroozinezhad

Unsaturated soil hydraulic conductivity K is a fundamental transfer property of soil but its measurement is costly, difficult, and time-consuming due to its large variations with water content (θ) or matric potential (h). Recently, C. Doussan and S. Ruy proposed a method/model using measurements of the electrical conductivity of soil core samples to predict K(h). This method requires the measurement or the setting of a range of matric potentials h in the core samples—a possible lengthy process requiring specialised devices. To avoid h estimation, we propose to simplify that method by introducing the particle-size distribution (PSD) of the soil as a proxy for soil pore diameters and matric potentials, with the Arya and Paris (AP) model. Tests of this simplified model (SM) with laboratory data on a broad range of soils and using the AP model with available, previously defined parameters showed that the accuracy was lower for the SM than for the original model (DR) in predicting K (RMSE of logK = 1.10 for SM v. 0.30 for DR; K in m s–1). However, accuracy was increased for SM when considering coarse- and medium-textured soils only (RMSE of logK = 0.61 for SM v. 0.26 for DR). Further tests with 51 soils from the UNSODA database and our own measurements, with estimated electrical properties, confirmed good agreement of the SM for coarse–medium-textured soils (<35–40% clay). For these textures, the SM also performed well compared with the van Genuchten–Mualem model. Error analysis of SM results and fitting of the AP parameter showed that most of the error for fine-textured soils came from poorer adequacy of the AP model’s previously defined parameters for defining the water retention curve, whereas this was much less so for coarse-textured soils. The SM, using readily accessible soil data, could be a relatively straightforward way to estimate, in situ or in the laboratory, K(h) for coarse–medium-textured soils. This requires, however, a prior check of the predictive efficacy of the AP model for the specific soil investigated, in particular for fine-textured/structured soils and when using previously defined AP parameters.


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