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U.S. Salinity Laboratory, Riverside, CA
* Corresponding author (ilebron{at}ussl.ars.usda.gov)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSNOTESRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Abbreviations: A, area • DLVO, Derjaguin, Landau, Verwey and Overbeek • ESP, exchangeable Na percentage • GR, gypsum requirement • Ksat, saturated hydraulic conductivity • P, perimeter • Rh, hydraulic radius SAR, Na adsorption ratio • SEM, scanning electron microscopy
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSNOTESRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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While the chemical reactions involved in soil sodification and reclamation are relatively well known, there is no direct information, to our knowledge, about the physical mechanisms taking place in the soil while these processes are occurring. Changes in soil structure are quantified with reduction functions or simple correlations, but they typically do not explicitly account for the effect of solution chemistry on the arrangement of the soil particles and aggregates. Dispersion or flocculation of clays occurs because of the repulsion of similar charged clay platelets and the ability of the soil solution to mitigate this repulsion. Irreversible changes in soil structure may occur when clay particles become dislodged if, for example, the electrolyte level is decreased or the Na fraction increases.
There are several studies in which the decrease of Ksat has been related with increases in Na content (McNeal and Coleman, 1966; Frenkel et al., 1978; Shainberg and Letey, 1984; Suarez et al., 1984). However, there is no quantification, to our knowledge, of the repercussion that increases (or decreases) of Na have on the soil structure while water flow is occurring. Flocculation, slacking, and aggregate stability studies show that increases in ESP cause dispersion and a decrease in aggregate stability and aggregate size, but these tests are performed in fractions of the soil placed in sieves or test tubes. Despite all the information collected in the laboratory there are some doubts about our capability to predict the extent of aggregation and dislodging in real soils.
Explanation for the clay behavior has been typically based in the Derjaguin, Landau, Verwey and Overbeek (DLVO) model, this theory has been used successfully to explain a great number of laboratory experiments. Unfortunately, there is evidence that the electrical double-layer interactions between charged particles in confined geometries are different than in isolated environments (Larsen and Grier, 1997; Grier, 1998; Bowen and Sharif, 1998; Sader and Chan, 1999). Grier (1998) and Bowen and Sharif (1998) found that isolated pairs of like charged spheres behave as predicted by DLVO theory but spheres confined by a concentration of other spheres develop long-range attractions inconsistent with DLVO.
Dilute systems may not properly represent the soil scenario, as geometrical confinement has a dramatic effect in the pairwise double-layer interaction between two clay particles. Sader and Chan (1999) found that the interaction between two confined spheres with uniform constant surface charge is primarily affected by the electrical nature of confining plates. They also found that when the interaction is between two spheres with uniform constant surface potential, the interaction between the spheres is not only strongly affected by the potential and charge but is also affected by the electrical properties of the confining plates.
Considerations of previous findings summarized above, indicates that there is a need to reevaluate our knowledge of colloidal systems and perform measurements under conditions at which flow and transport phenomena occur. For that purpose, image analysis of soil micrographs has been proven to yield information impossible to collect otherwise.
There is a general agreement that the active pores conducting water are those at the micrometer scale (Ahuja et al., 1989). The size of the particles enclosing such pores are mostly aggregates, which are heterogeneous conglomerates in which submicron-clay particles are associated in domains. These domains are cemented with a variety of amorphous oxides, organic matter, and minerals. Scanning electron microscopy is suitable to measure features at the micrometer scale and together with image analysis provides the quantification required to follow changes in pore and aggregate size and shape with changing chemical and external factors (Lebron et al., 1999).
Gypsum has been used extensively in reclamation of sodic soils with infiltration problems. It is well known that application of gypsum to sodic soils improves the soil physical conditions by promoting flocculation, enhancing aggregate stability and increasing the infiltration rate. These observations have no scientific documentation or quantification regarding the actual assembling of the soil particles at the aggregate level.
Chemical and physical factors that affect soil structure should be considered in predictive and indirect models for the soil hydraulic properties. In the present study, we quantify the changes that the pores and aggregates undergo when a reclamation process with gypsum takes place in a sodic soil. We also relate the changes in size and shape of the aggregates with saturated hydraulic conductivity. This study is intended to establish the basis for a conceptual model to predict soil reclamation, salinization, and sodification processes in soils.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSNOTESRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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 | [1] |
b is the soil bulk density, CEC is the cation-exchange capacity, and ESPi and ESPf are the initial and final exchangeable Na percentage. Three saline-sodic soils were collected to measure the effect of gypsum on the soil structure and Ksat: Hanford (coarse-loamy, mixed, superactive, nonacid, thermic Typic Xerorthents) loamy sand (H) and Madera (fine, smectitic, thermic Abruptic Durixeralfs) sandy clay loam (M) from Madera County, CA, and Las Animas (coarse-loamy, mixed, superactive, calcareous, mesic Typic Fluvaquents) silty loam (LA) from Arkansas Valley, CO. A total of 24 soil columns were prepared as follows: from the Hanford soil, three different soil samples were collected, each one of the three samples was divided into four subsamples and treated with a GR of 0, 0.3, 0.5, and 1. Madera soils were divided into three subsamples and treated to achieve GR of 0, 0.3, and 0.5. Las Animas soils were divided into three subsamples and these were treated with 0.3, 0.5, and 1.0 of GR. The original ESP values of the samples were between 43 and 54.
Soils were mixed thoroughly with the gypsum and packed in columns of 5-cm diam. by 18 cm long to bulk densities between 1.6 to 1.3 g cm-3. Samples were saturated by first wetting by capillarity rise from below, then gradually raising the water level until water ponded on the surface. A constant head was used to measure Ksat. Leaching was achieved using Riverside municipal water. The chemical composition of the water was in the range of electrical conductivity (EC) = 0.51 to 0.56 dS m-1, Na adsorption ratio (SAR) = 0.3 to 1.7, and pH = 8.3 to 7.8. A minimum of 1 mo and a maximum of 3 mo was taken for each of the reclamation process, at least three pore volumes were allowed to pass through each column. Slow infiltration rates were used to realistically simulate field reclamation. Infiltration rates were measured and Ksat was calculated. At the end of the leaching process a 2-cm thick slide was cut from the top of the column; this slide was used to prepare a thin section. The slide was impregnated with an epoxy, after the preparation was hard, a thin section was cut and polished. Thin section preparation and SEM methodology is explained in detail in Lebron et al. (1999). Image analysis software was used to quantify the pore space and the aggregate dimensions (Princeton Gamma Tech.1, Princeton, NJ). The magnification used to collect the microscopic information was x50, that magnification provides pictures of 1024 by 804 pixels at 5.588 µm per pixel. Ten pictures from the same thin section were collected following a grid pattern and appended in one file. For each thin section a total of 46 mm2 was sampled.
The aggregates were quantified by directly measuring the number of pixels that conform to each feature in the binary image. Figure 1 shows the micrograph of a thin section with the gray scale produced by the electron reflection of the components of the soil. The electron reflection is proportional to the atomic weights of the chemical elements from the minerals of the soil. When Fig. 1 is transformed to binary colors with image analysis, the image is transformed to black and white. White areas represents the aggregates and black represents the pores, both of them were quantified by counting the pixels conforming each feature.
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A portion of the saturated paste was used to equilibrate and exchange the cations with NH4NO3 solution. The supernatant solution after equilibration was analyzed for alkalinity, SO2-4, Cl-, Ca2+, Mg2+, Na+, and K+. Three corrections were taken into account to express the final results: (i) the correction because of the carryover was calculated based on Cl data, (ii) the correction for calcite dissolution was made with alkalinity data, and (iii) the correction for gypsum dissolution with SO2-4 data (Amrhein and Suarez, 1990). Final composition for the exchangeable complex was calculated and expressed as CEC or ESP.
Aggregate stability was determined in four soils using the method of Kemper and Rosenau (1986). The soils samples were collected from the Columns 9, 10, 20, and 21 after the reclamation process was finished. In this method, only one fraction of the soil is tested (aggregates between 1 and 2 mm) and the sieves contained stainless steel 0.26-mm screens (24 mesh cm-1). Each sample was run in duplicate.
We used the Spearmen correlation (Press et al., 1988) to calculate the relationship among the different variables of our soils. We used this technique because of the fact that our data are not normally distributed, we chose two levels of significance, 0.05 and 0.01.
The clay fraction (<2 µm) was collected from the soils. X-ray diffraction (XRD) was performed on a randomly oriented powder preparation and in two glass slides, one with the clay sample saturated with K and the other with the clay saturated with Mg in 10% glycerol and at 10% humidity (Whittig and Allardice, 1986).
We also used energy dispersive X-ray analysis (EDXA) to analyze the elemental composition in the thin sections of different aggregates in selected samples. This analysis was intended to clarify the composition of the aggregates between 10 and 30 µm.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSNOTESRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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The soils after the reclamation process showed a linear relationship between EC and ESP (Table 3). In this particular case, the final EC is relatively low for all the samples, consequently we will consider the dispersion to be controlled by the SAR levels.
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b) (Table 3).
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Since our experiment was performed under saturated conditions, the presence of gypsum in our columns is supposed to act by inhibiting the breakdown of the already existing aggregates rather than promote the formation of larger ones. That inhibition occurs by increasing the Ca concentration in the bulk water and promoting the exchange of Na by Ca in the exchangeable complex of the clays. Only at the end of the experiment, in the drying process of the soil columns, can we expect new aggregate formation.
At the soil water content of saturation the disruption of the aggregates in the soil matrix is to a certain extent irreversible. Once the aggregate is broken, the individual particles will migrate if they are not physically constrained. The experiment lasted long enough to show some compaction when gypsum was not present and since the soil did not go through drying periods no significant amount of new aggregates should form during the leaching (Ghezzehei and Or, 2000). The beneficial effect of the gypsum is shown not only by the greater Ksat, but also by the lower bulk densities at the end of the experiment in comparison with their homologous soil with less or no gypsum. Las Animas soil shows some initial swelling because of the presence of small amounts of smectite clay but it shows a similar pattern; the greater the gypsum requirement the less the compaction during the leaching; the columns with the lower GR showed higher b.
The losts of soil structure, however, was not as much as we could have predicted from traditional aggregate stability tests. The results from Kemper and Roseanu method showed a percentage of the stable aggregates of 52.71 (±1.46), 57.54 (±2.60), 24.5 (±1.43), and 26.2 (±0.25) for Columns 9, 10, 20, and 21. We analyzed the weighted percentage of the aggregates in our thin sections. Table 4 shows that the aggregates between 0.3 and 2 mm were between 80 and 90% for Hanford and Madera soils. Since each micrograph has 46 mm2 and there were always more than two aggregates in each picture, we can safely assume that the maximum aggregate size analyzed with the SEM is similar to the one analyzed with the Kemper and Rossenau method (2 mm in diam.).
Aggregate stability test may not be reflecting the actual stability of the particles when they are constrained by the physical confinement of the soil matrix. The complexity of the electric field of the colloids overlapping and interacting in enclosed geometries has been shown to not follow the DLVO theory. Our soils show a more stable status than the one that would have been predicted according with experiments in dilute systems in which DLVO theory is applicable. The presence of long range attractive forces observed at length scales of several micrometers (Larsen and Grier, 1997; Squires and Brenner, 2000) and the fact that the aggregate stability tests are performed with loose soil after sieving and handling can be the reasons for the discrepancies shown between the traditional method and the in situ microscopic measurements.
Soil pores, as is the case with aggregates, do not have a specific geometry. Some authors utilize the hydraulic radius, what Hoffmann-Riem et al. (1999) defined as the ratio between the volumetric water content and the area of the water-solid interface. In our case, we used the hydraulic radius (Rh) defined as the area divided by the perimeter, Lebron et al. (1999) showed that Rh improved the capability to predict Ksat using the Kozeny-Carman equation when A and P were measured directly from a micrograph of a thin section.
The Rh was found to have a good correlation with all the chemical parameters and with Ksat (Table 3). These observations agreed with previous data in the literature (Lebron et al., 1999). The greater the ESP or the pH, the smaller the pores and consequently the lesser the Ksat. The Rh also had a good correlation with the b but it did not show any correlation with the total porosity (
) (Table 3).
We observed that (A/P)a had a linear relationship with Rh indicating that the size of the pores is determined by the size of the aggregates. This relationship seems intuitive and is one of the main conclusions of the present study. Unlike most of the previous modeling efforts we propose to concentrate on the aggregate size and distribution rather than on the texture to evaluate the pore space in soils. No relationship was found between pore size and texture. Lebron et al. (2001) also found a relationship between pore size and aggregate size for undisturbed soil cores. They proposed that the transformation of the texture data into aggregate size considering the chemistry and bulk density of the soils will improve the capability to predict hydraulic properties in soils.
Pore and aggregate size is critical but their shapes are also important (Philip, 1977; Reeves and Celia, 1996). A important feature of the pore structure in a real porous media is the angular corners of the pores. Ma et al. (1996) proposed a model of angular tubes as opposed to the commonly used cylindrical tube model to represent soil pore space. Triangles provide a versatile example for pore shapes; they have angular corners which can retain liquid, and irregular triangles give a wide range of shapes (Manson and Morrow, 1991). Manson and Morrow (1991) proposed a normalized shape factor for capillary action in triangular pores given the ratio between the cross-sectional area, A, to the square of the perimeter length, P. According to these authors, the amount of wetting phase that drains as the penetration curvature decreases as aspect ratio increases. The shape factor, A/P2, has been successfully used by Tuller et al. (1999), Lebron et al. (1999), and Or and Tuller (1999)(2000).
As shown in Table 3, A/P2 has a good correlation with ESP, SAR, and pH. This indicates that the chemical composition had an effect on the shape of the pores. Gypsum affected soil structure, not only the size of the aggregates but also in the self assembling of the particles, since the shapes of the pores were altered. The greater the pH or Na content the lesser the shape factor. These results are in agreement with Manson and Morrow (1991) and with our previous experiments (Suarez et al., 1984; Lebron et al., 1999) in which increases in ESP or pH causes a decrease in the water flow draining from a soil column.
From Table 3, we see also that Ksat had a good correlation with several physical and chemical parameters. Some of these interactions, such as the effect of exchangeable Na on the permeability (Fig. 4) of soils, have been known for a long time (Hilgard, 1890). However, incorporation of chemical parameters in the physical models to predict water transport has not been achieved. For example, Ksat was found to have a good correlation with the aggregate size (A/P)a (Fig. 5) , since aggregate size is affected by the chemical composition, one way to conceptually develop a model to predict Ksat would be to calculate the aggregate size based on the chemical composition. This process would require the accumulation of a large data base with microscopic, macroscopic, and chemical information to be able to develop the relationships linking the different variables. Variables such as clay mineralogy, organic matter, and Al and Fe oxides, all known to affect the stability of the soils should be included in the data base to obtain relationships applicable to a wide range of soils.
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSNOTESRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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NOTES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSNOTESRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Received for publication March 30, 2001.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSNOTESRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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