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Effectiveness of artificial zeolite amendment in improving the physicochemical properties of saline-sodic soils characterised by different clay mineralogies.

Introduction

The FAO/UNESCO soil map of the world shows that a total land area of 12.8 billion ha has been affected by salinity and sodicity (FAO 2000). The percentage of saline and sodic soils in arable land amounts to 49.2% and 45.8%, respectively, in total in each degraded area. These degraded soils are distributed in dry and semi-dry lands such as those in Australia and South America and in poorly drained lowlands such as those found around the Aral Sea (Cai et al. 2003). Soil is defined as sodic when the ratio of exchangeable sodium percentage (ESP) to cation exchange capacity (CEC) is >15%. This is the threshold, based on hydraulic conductivity measurements, above which soil structure is adversely affected (US Salinity Laboratory Staff 1954; Sumner 1993). Sodic soils contain sodium carbonate, which is easily soluble in water. The presence of sodium carbonate can lead to an increase in soil pH to >8.5. Sodic soil can damage plant growth because of sodium toxicity and also because of decreased soil infiltration of water as a result of decreased aggregate stability, which in turn contributes to salt accumulation in soil (Lauchli and Epstein 1990).

The breakdown of aggregates promotes soil erosion by water by the following processes: (1) detachment of soil material by rainfall impact and/or runoff shear, and (2) transport of the resulting sediment by raindrop splash and/or flowing runoff. Although the kinetic energy for splash by raindrop is more than that required for runoff shear, sediment transport is mainly by runoff water (Mamedov et al. 2002). This runoff water is closely associated with seal formation, which in turn reduces the infiltration rate (Tang et al. 2006). Seal formation is caused by the following mechanisms: (1) physical disintegration of surface soil aggregates by rain wetting and impact of drops, and (2) a physicochemical dispersion of soil clays, which migrate and clog the pores immediately beneath the soil surface (Agassi et al. 1981). Thus, the breakdown of aggregates involves all processes related to generation of soil erosion. Conversely, if the connections that bind the micro/macro-aggregates are resistant to forces that disperse the aggregate, soil erosion can be suppressed to a minimum.

When dried soil is subjected to fast wetting, the aggregates are easily broken down by slaking exploded by entrapped air (Panabokke and Quirk 1957; Chan and Mullins 1994) and differential swelling (Kemper and Rosenau 1984). The other mechanisms for aggregate breakdown are rainfall impact (McIntyre 1958) and physicochemical dispersion as a result of the osmotic stress that occurs on wetting with low electrolyte water (Emerson 1967; Levy and Mamedov 2002). This physicochemical clay dispersion is enhanced with an increase in exchangeable [Na.sup.+] in the soil solution and also at exchange sites contributing repulsive charges that disperse clay particles (Bronick and Lal 2005). However, the influence of higher ESP on aggregate dispersion generally depends on the clay mineralogy (Stem et al. 1991; Sumner 1993). For instance smectite soil, compared to kaolinite soil, tends to easily degrade as a result of swelling and dispersion of clay, leading to reduced infiltration and increased soil loss (Oster et al. 1980; Mamedov et al. 2002; Arai et al. 2003), whereas allophane soil derived from volcanic ash is dispersed under high pH conditions (Wada 1985; Horikawa et al. 2004).

Soil amendments such as gypsum or lime, which contribute to the suppression of a diffuse electrical double layer, have been applied to sodic soils to decrease the ESP and improve soil aggregate stability (Shainberg et al. 1989; Agassi 1996). Polymers such as polysaccharide and polyacrylamide have been applied to reduce aggregate dispersion and as an adhesive for aggregation bonding (Ben-Hur and Letey 1989; Zhang and Miller 1996; Yamamoto et al. 2008). Another soil amendment that has received increasing attention with regard to the improvement of the physicochemical properties of soil is coal fly-ash and its industrially modified form, artificial zeolite (AZ) (Yamada et al. 2002).

The disposal of coal fly ash generated by thermal power plants poses a serious environmental problem (Kumar and Singh 2003). Artificial zeolite has been used to improve plant growth and soil aggregate stability as well as to control soil erosion (Al-Busaide et al. 2007; Andry et al. 2007a, 2008; Yamada et al. 2007). The calcium type of AZ, Ca-AZ, is produced by adding a solution containing Ca cations to the original Na-AZ. This type of AZ possesses high porosity and high CEC, which is useful for the clarification of water quality and for deodorising unpleasant smells, such as ammonia (McCrory and Hobbs 2001). Moreover, it has been reported that AZ also leads to improvement in water retention, decrease in aluminum toxicity, and control of acid soil erosion (Andry et al. 2007b, 2008). Thus, the use of AZ as a soil amendment can help in alleviating the environmental problems associated with its disposal. However, literature is scarce pertaining to the effects of AZ on sodic soils characterised by different clay mineralogies.

Research that can be carried out on natural soils is limited by the inherent variability of soil properties in a field. Controlling and measuring various physicochemical parameters during field study, under variable conditions of sodic soils, can lead to complex and variable measured values (Commandeur 1992). As a result, it is difficult to determine the most important factors responsible for soil erosion and to predict where and when soil erosion events might occur (Adiku et al. 1997). These problems have led to the need for controlled simulation, including simulated rainfall as well as simulated sodic soil. Rainfall simulation has been used for decades to study basic erosion processes (e.g. surface sealing, soil aggregate stability, and raindrop detachment) that are difficult to study in detail in the field. The use of artificial sodic soil characterised by different clay mineralogies is a method that would permit study of sodic soils.

The objective of this study was to investigate the effectiveness of AZ as a soil amendment in improving the physicochemical properties of sodic soils characterised by different clay mineralogies.

Materials and methods

Preparation of sodic soils

Each of the 3 original soils used in this study had a dominant clay mineral associated with it. The dominant minerals were smectite (SS), kaolinite (KS), and allophane (AS) in the soils, which were taken, respectively, from the Japanese cities of Isahaya city (32[degrees]50'N, 130[degrees]9'E) in Nagasaki prefecture, and Hukube-cho (35[degrees]3UN, 134[degrees]17'E) and Kotoura-cho (35[degrees]25'N, 133[degrees]39'E) in Tottori prefecture. The clay mineralogies of these soils were identified from a composition map of clay minerals of Japan (Kurahayashi 1972; Ueda et al. 1983; Kanno et al. 1985; Takada et al. 1985; Nakashima and Egashira 1998). The physicochemical properties of the 3 types of soil are listed in Table 1. The CEC of the SS soil was higher than that of the other soils because of its high smectite clay content (62.1%). The lowest pH of 5.3 was in AS soil, which can be attributed to allophane, which includes Al.

The absorption of cations by soil differs depending on the electrical conductivity (EC) and the type of cation in the solution used (Shainberg and Kemper 1966; Lai et al. 1978; Bond 1997). Moreover, the situation becomes more complex because the characteristic of chemical absorption varies with clay contents and mineralogies (Kubota 1975; Sumner 1993). Therefore, the sodicity of soils was achieved through a trial-and-error process. Original soils were treated by an air-drying process after the addition of Ca[Cl.sub.2] and MgS[O.sub.4] solutions for KS and SS, and Mg[(OH).sub.2] and Ca[(OH).sub.2] solutions for AS. Adjustment of pH with [Na.sub.2]C[O.sub.3] was used in both processes. The value of ESP was calculated using Richards' Eqn (Richards 1954), which can be expressed as follows:

ESP = 100 x (-0.0126 + 0.01475SAR)/1 + (-0.0126 + 0.01475SAR) (1)

and SAR was calculated using the following equation:

SAR = BNa/[square root of ((Mg + Ca)/2) (2)

where Na, Mg, and Ca are the concentrations in [mmol.sub.c]/L of each cation, measured by the saturated paste method.

The ESP was adjusted by changing the concentration of each solution. ESP of SS was set at 37, 45, and 53, where the samples were called SS37, SS45, and SS53, respectively. ESP of AS was set at 12, 25, and 30, where the samples were called AS12, AS25, and AS30, respectively. ESP of KS was increased up to 77 (KS77) to obtain a high sodicity compared to that of the SS treatment, in order to understand its soil aggregate stability against sodicity. Consequently, only I treatment ofsodicity was prepared with this soil. The sodic soils were analysed after passing them through a sieve of 4.75mm aperture. The physicochemical properties of these soils are listed in Table 2.

The original soils and sodic soils were mixed with AZ, with weight ratios of 5% and 10%. In the case of treatment of SS, a 25% application ratio was also used.

Physical and chemical characterisation of soil

The soil samples were prepared for the determination of EC with ratio of 1:5 and soil pH with ratio of 1:2.5. Exchangeable cations and CEC were determined in the leaching solution with 1M C[H.sub.3]COON[H.sub.4] and 1M C[H.sub.3]COONa solutions and C[H.sub.3]COON[H.sub.4], after washing with ethanol as per the method described by Schollenberger and Simon (1945).

Saturated hydraulic conductivity (KS) was measured in saturated soil packed in 100-[cm.sup.3] soil columns. KS was determined in the laboratory using the Klute and Dirksen (1986) falling-head method using distilled water. Modified fast-wetting in water, as proposed by Le Bissonnais (1996), was used to measure the aggregate stability of 2-mm air-dried aggregates (35g). Vertical movement of 4cm amplitude was applied for 5 min to a nest of sieves (>2000, 1000-2000, 500-1000, 250-500, 250-106, <106 [micro]m) immersed in a container of tap water (101 [micro]S/cm). The material that remained after wet-shaking in each sieve was carefully removed, and the mean weight diameter (MWD) of the aggregate size was calculated using Eqn 3:

MWD = [n.summation over (i=1)][x.sub.i][w.sub.i] (3)

where n is the number of sieves, and x and w are diameter and weight, respectively.

Rainfall experiment

A water erosion experiment was performed under a rainfall simulator at the Arid Land Research Center. Rain was delivered from a 12-m-high tower (Fig. 1). The rainfall distribution uniformity, calculated from the equation of uniformity coefficient developed by Christiansen, was set at 80%, and ~85% of the drops had a diameter <2 mm (Andry et al. 2007b). The effects of clay mineralogy and zeolite on soil erosion from smectite and kaolinite soil were analysed. Rainfall intensity of 40 mm/h was applied on SS soils (treated as well as control soils), while an intensity of 60 mm/h was applied on KS soils (treated as well as control soils). The soils were subjected to different rainfall intensities based on 2 facts: (1) that it has been proven that smectite soil can erode more easily than kaolinite soil, and most importantly (2) that smectite soils are generally developed in regions with lower rainfall than are kaolinite soils (Richter and Babbar 1991).

The air-dried soil of <4.75 mm was packed in 2 types of plot trays, with 30 cm width, 50 cm slope length, and 5 cm depth for the KS, and 50cm width, 100cm slope length, and 15cm depth for the SS and AS. The trays were set at a slope of 10[degrees] and subjected to simulated rainfall composed of ion-exchange water (EC 10.1 [micro]S/cm), which had been passed through an ion-exchange filtration system (WL 100, Yamato Scientific Co. Ltd). The runoff sample was collected at intervals of 5 min and the volume was measured and the EC recorded. Infiltration was not observed in all soils, even the control soils. The sediment in the runoff subsamples was determined gravimetrically after oven-drying at 105[degrees]C for 48h.

Two rainfall intensities were compared and evaluated for soil loss and sediment concentration at the equivalent of a total rainfall amount of 40 mm, although the kinetic energies of the simulated rainfall for 60 and 40 mm/h, which were computed using the formula proposed by van Dijk et al. (2002), were 27.1 and 25.6 J/[m.sup.2], respectively. The amount of soil loss (SL) from the different sizes of soil boxes used for KS and SS was normalised by dividing by the surface area of the soil box used. Thus, all experiments were performed under conditions that simulated higher rainfall intensity and ESP for the KS treatments than for the SS treatments.

[FIGURE 1 OMITTED]

Statistical analyses

The rainfall experiment for the KS treatment was replicated 3 times, while there was usually no replication for the SS treatment. The triplicate data were subjected to mean separation analysis using the 1-way ANOVA test at significance of P = 0.05. Multiple regressions were performed to evaluate the cause-effect relationships between a combination of physicochemical properties and corresponding sediment concentrations (Tamene et al. 2006). Principal component analysis (PCA) was used to condense the variations in soil series by loading in 2 orthogonal axes that summarised the main underlying gradients (Tamene et al. 2006; Moreno-de las Heras 2009). PCA results in data reduction that aims to explain most of the variance in the data while reducing the number of variables to a few uncorrelated principle components (PC) (Boruvka et al. 2007). Before applying PCA, the data for all soils for each parameter were standardised with mean and standard deviation of 0 and 1, respectively, in order to eliminate the influence of different units of measurement and render the data dimensionless (Singh et al. 2005; Salvati and Zitti 2009). In order to analyse the direct impact of the parameters of soil physicochemical properties, soil loss, sediment concentration, and EC of runoff on soil series, regression method between loadings of each PC in all soil series and corresponding above each parameter were calculated (Naruoka et al. 1995; Singh et al. 2005). The coefficient in the regression equation indicates the factor scores, and the larger scores show the larger influence of parameters on soils (Kadono et al. 2008). Thus, the factor scores reveal the relative contribution of parameters to loadings of PCA. All these statistical analyses were performed with the SPSS software (10.0).

Results and discussion

Physicochemical properties of zeolite

The AZ used was made of coal ash from a generating power plant, whose composition of Si[O.sub.2] and Al2[O.sub.3] was similar to that of volcanic materials (Querol et al. 2002). AZ was synthesised with NaOH solution in a heat treatment process in which the temperature ranged from ~80 to 200[degrees]C (Moriyama et al. 2005).

The Ca type of AZ was used, whose pH and EC were 10.5 and 1.72dS/m, respectively. AZ had a high CEC value of 320 [cmol.sub.c]/kg soil, which was 2-3 times higher than that for natural zeolite, which was effective for the removal of heavy metals (Forstner et al. 2001). The texture of AZ was 9.6, 84.0, and 6.4% sand, silt, and clay, respectively, predominantly in silt particles. The dry bulk density of AZ was low at 0.50 [cm.sup.3]/[cm.sup.3] due to its high porosity, although the specific gravity of particles was 2.69, a value similar to that in general mineralogy. The greater porosity of 81.9% is expected to contribute to the improvement in soil water retention and infiltration.

Preparation of sodic soil

The process of sodicity of soil with the clay mineral KS is discussed here. The AS soil showed similar trends when 3.0 and 1.0 cmol/kg of Ca[(OH).sub.2] and Mg[(OH).sub.2], respectively, were used. ESP and EC of KS increased with natural logarithmic values ([R.sup.2] = 0.99) that tended to a nearly linear function in the ranges 28.5-77.0% and 0.54-1.2dS/m, respectively, with [Na.sub.2]C[O.sub.3] solution input from 5 to 15 cmol/kg and Ca[Cl.sub.2] and MgS[O.sub.4] at concentrations of 1 cmol/kg. The increase in ESP was due to the replacement of [Na.sup.+] from [Na.sub.2]C[O.sub.3] at cation exchange sites of clay (Sumner 1993). In the case of AS, EC and ESP increased proportionally in the ranges 0.60-1.72 dS/m and 29.9-80.3%, with an increase in the [Na.sub.2]C[O.sub.3] solution input from 3 to 12 cmol/kg. The different pattern of variation of ESP and EC between KS and AS might be the result of differences in the contents and mineralogy of clay, and concentration of soil solution (Shainberg and Kemper 1966; Kubota 1975; Lai et al. 1978; Sumner 1993), and because of the different types of solution added. However, the relationships between pH and the [Na.sub.2]C[O.sub.3] solution input for KS can be expressed by the equation pH-l.16ln(x) + 6.50 ([R.sup.2] = 0.94). This equation has a trend similar to that for AS, whose equation was pH = 1.12ln(x) + 6.51 ([R.sup.2] = 0.94).

Physicochemical properties of sodic soil

Figure 2 shows the water-stable soil aggregate distributions for KS77, SS45, AS30, and each original soil. The aggregate fraction >500 [micro]m of all soils broke down into smaller size fractions. The reduction in the fractions >2000 [micro]m for SS45, KS77, and AS30 was 88.6, 42.5, and 79.5%, respectively, whereas the aggregates >500 [micro]m broke down at 70.0, 53.2, and 66.5%, respectively. The fractions <106 [micro]m increased by 3.7 ([+ or -] 0.2) times on an average in all sodic soils, compared to the original soils. The soil aggregate breakdown of the large aggregate sizes could be attributed to slaking caused by compression of entrapped air during fast wetting (Panabokke and Quirk 1957), whereas clay dispersion due to osmotic stress upon the wetting process with low electrolyte water was considered a reason for the large increase in the size of aggregates <106 [micro]m after sodification (Fig. 2) (Emerson 1967; Levy et al. 2003). The aggregates of KS and AS were more stable under the condition of sodicity than those of SS. This could be the result of additional swelling induced by the high sodium content in the smectite soil, which leads to further aggregate dispersion (Kopittke et al. 2006).

Saturated hydraulic conductivity of SS, KS, and AS decreased considerably, by 188, 25.8, and 9.2 times respectively, after the sodification process (Table 2). The decrease in soil saturated hydraulic conductivity could be the result of clogging of soil pores by fine materials, as can be observed in the aggregate size distribution shown in Fig. 2. The increase in the amount of the fine material (<106 [micro]m), which easily moved downward and was trapped in the soil pores, was in line with the decrease in soil saturated hydraulic conductivity.

Erodibility of sodic soil

Figure 3 shows the effect of soil sodicity on soil erosion from KS and SS soils. The sediment concentration increased with increasing soil sodicity, and the increase was significant for the SS soil. The sediment concentration of the original soil for KS was 7.4 kg/[m.sup.3], a value larger than that for SS of 5.3 kg/[m.sup.3]. As the ESP increased, the SS treatment eroded more than the KS treatment, exhibiting different characteristic trends of soil erosion. A linear relation was observed between ESP and sediment concentration for the KS soil ([R.sup.2] =0.95), whereas exponential power was the appropriate fit for the SS soil ([R.sup.2] = 0.93). Lado and Ben-Hur (2004) suggested that soil dominated by smectite is more erodible than kaolinitic soil because of the greater seal formation which is generated due to the dispersion of aggregates. However, the sediment concentration in the KS control soil was 1.4 times higher than that for the SS control soil. The soil organic carbon in SS was found to be less than that in KS; however, the clay content of 62.1% and MWD of 1.85mm in the SS control were higher than those in KS, which were 56.0 and 1.53, respectively (Tables 1, 2). These higher clay contents and MWD might contribute to a higher tolerance to erosion for the SS control compared to the KS control soil (Bronick and Lal 2005). As the ESP of the soil increased, the sediment concentration of SS soil increased significantly compared to that of KS soil. This result might be explained by the fact that sodic SS is more susceptible to clay dispersion with increasing soil ESP and the effect of low soil solution caused by rainfall. The additional effect of aggregate slaking by fast wetting, which was susceptible to detachment by the impact of drops and flow shear, could contribute to the increase in sediment concentration in the SS treatment (Levy et al. 2003; Tang et al. 2006).

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

Effect of zeolite on physicochemical properties of sodic soil

Table 2 lists the physicochemical properties of sodic soils after the soils were amended with AZ. The pH and EC increased with the mixing ratio of AZ. The CEC of SS, KS, and AS treated with 10% AZ increased by 1.9, 3.8, and 3.9 times that of the original soil, respectively. The CEC of KS and AS increased more than that of SS, since the CEC of these soils had a lower value of 11 [cmol.sub.c]/kg compared to that of SS, which enhanced the effect of AZ. The ESP decreased according to the mixing ratio of AZ owing to the increase in CEC.

The MWD of SS, KS, and AS decreased up to 79.1,49.5, and 55.5%, respectively, owing to soil sodicity. This could be explained by the clay dispersion process caused by the high ESP and low EC of tap water (Emerson 1967; Levy et al. 2003). In the case of KS, the degree of dispersion was the least and the most stable under a high degree of sodicity. The addition of 10% AZ to sodic soil increased the MWD by up to 22.4% and 59.4% in the case of SS45 and KS77, respectively. The saturated hydraulic conductivity of SS45 and KS77 soils treated with 10% AZ increased by up to 2.5 and 2.0 times, respectively, after the ESP decreased, resulting in a decrease in soil aggregate dispersion (Hamid and Mustafa 1975). The reason for the decreasing ESP might be that it is enhanced by the same mechanisms as for lime and gypsum applications, in which [Na.sup.+] from cation exchange sites of clay is replaced with [Ca.sup.2+] from these amendments (Shainberg et al. 1989; Tang et al. 2006). AZ has high CEC, which may give more opportunity for [Na.sup.+] entry of clay into the cation exchange sites of AZ and for [Ca.sup.2+] to release from these sites into clay exchange sites. This chemical retention of cations in AZ may enable the prevention of the leaching of pollutants such as heavy metals (Erdem et al. 2004; Pitcher et al. 2004), although the high pH such as that caused by lime and gypsum can also work as an immobiliser by decreasing the metal solubility (Castaldi et al. 2005). Determination of the extent of the chemical role of AZ in suppressing the clay dispersion, for instance the exchange rates of [Na.sup.+] and [Ca.sup.2+] between clay and zeolite, seems to be complicated. However, the increase in MWD of sodic soil by AZ suggests that clay dispersion is suppressed since [Ca.sup.2+] is absorbed into clay instead of the release of [Na.sup.+].

Improvement in erodibility of sodic soil by zeolite amendment

The aggregate stability of the sodic soils was consistent with the amount of soil loss. A linear relationship was observed between ESP and soil loss for KS ([R.sup.2] = 0.86), and an exponential power relationship for SS ([R.sup.2] = 0.87) soil. Figures pertaining to this relationship are not provided in this document since aggregate stability exhibited the same pattern as that exhibited by sediment concentration, shown in Fig. 3. A significant increase in soil loss was observed in the SS soil with an increase in the ESP. The cumulative soil loss (CSL) of SS increased by 8.2, 12.1, and 17.9 times for ESP values of 37, 45, and 57, respectively, compared to the CSL values of SS control, and the CSL of sodic soil decreased with the mixing rate of AZ amendment (Fig. 4). The CSL of SS45 and KS77 treated with 10% AZ decreased significantly (P<0.05) by 31.5 and 37.4%, respectively, as compared to that of the unamended soils. This result suggests that the application of AZ improved the erodibility of sodic soil, a finding which is consistent with the increase in MWD of the soil shown in Table 2.

The cumulative surface runoff (CR) increased with soil sodicity. The CR of SS45 and KS77 increased by 1.4 ([+ or -] 0.1) times compared to the average value of CR of 26.2 ([+ or -] 0.7) mm of the control soils. This could be attributed to the decrease in soil infiltration as a result of seal formation due to the dispersion of aggregates. The effect of AZ on the reduction in surface runoff was observed in all soils. The CR of SS37, SS45, and SS53 treated with the addition of 10% AZ decreased by 9.2 [+ or -] 3.1% on average, while that of KS77 decreased by 16.3%.

Figure 5 shows the change in sediment concentration (SC) of SS45 and KS77 amended by up to 10% of AZ. The SC of both soils decreased significantly (P < 0.05) as AZ was applied up to 10%, although the average value of SC with 10% of AZ in SS45 was 2.3 times that of KS77. The average value of SC in SS increased with ESP rate of 37, 45, and 53, and the corresponding values were 29.7, 47.1, and 66.3kg/[m.sup.3]. These SC values decreased by 6.7 ([+ or -] 2.0) and 21.1 [+ or -] 6.8% after 5 and 10% of AZ amendment, respectively, while SC of KS77 decreased significantly (P<0.05) by 15.0 and 23.2% after 5 and 10% of AZ amendment, respectively.

[FIGURE 4 OMITTED]

Figure 6 shows the variation of runoff EC in SS45 and KS77 treatments with respect to the total rainfall amounts. The peak of EC was observed for all treatments in the rainfall range 5-13 mm, and it showed a steady value after decreasing from the peak. This steady value in KS77 of 0.42 dS/m was lower than the steady value for SS45 of 0.70 dS/m. This could be explained by the large soil loss from the SS45 treatment, which was 2.3 times greater than that from the KS77 treatment. Another possible explanation is that the average EC of the SS45 treatment was 15.8% higher than that of KS77 (Table 2). Runoff EC in SS45 and KS77 decreased by 12.9 and 16.7%, respectively, after 5% AZ amendment and 24.3 and 40.5%, respectively, after 10% AZ amendment with a significance of P < 0.05.

[FIGURE 5 OMITTED]

[FIGURE 6 OMITTED]

Figure 7 shows the amount of sodium content in runoff water, when the rainfall amount was 40 mm, from the SS and SS45 soils treated with 0, 5, 10, and 25% AZ. The sodium content of runoff water from SS increased with AZ treatment. This result could be explained by the dispersion resulting from the dissolved salts of AZ, which affected the osmotic stress upon wetting with the low electrolyte of rainfall water (Levy et al. 2003). However, the amounts of sodium content in SS45 treated with AZ decreased by 17.0, 23.6, and 43.1% compared with that of SS45 of 558 kg/ha when a mixture ratio of 5, 10, and 25% of AZ was used, respectively. This could be the result of decreasing ESP caused by the AZ amendment, which effectively suppressed the soil dispersion and detachment, which in turn led to a decrease in the soil salt content in the runoff.

[FIGURE 7 OMITTED]

[FIGURE 8 OMITTED]

Multivariate analysis

PCA was carried out on the standardised data matrix to extract the latent patterns and reduce data complexity. PCA resulted in 2 significant PCs of PC1 and PC2 with eigenvalues >1, which explained ~73% of the total variance in the dataset. Figure 8a, b show the loadings and factor scores from the results of the PCA, respectively. The 3 groups can be divided as follows: (1) original soil, (2) kaolinitic soil, and (3) smectitic sodic soil with zeolite amendment. The positive directions of the x- and v-axes can explain the degree of soil erodibility and amendment with zeolite, respectively, since the gathering scatter of AZ contents and CEC, and SL and SC were distributed on the positive x- and y-axes, respectively (Fig. 8b). In fact, sodic SS without AZ amendment was significantly characterised by a positive x-axis, and after amendment with zeolite, the point was shifted from the positive y-axis to the negative x-axis, which was explained by the effect of zeolite on the reduction of the erodibility of saline-sodic soil. The factors pH and EC of soil were distributed between the positive x- and y-axes, which was a characteristic of the saline-sodic soil, while the Ks and MWD were distributed in the opposite direction (negative axis), which was a characteristic of the normal soil. In fact, the original soil was distributed in the negative position of x- and y-axes, which was also characterised by lower erodibility. Thus, this method is useful because the characteristics of soil that are affected by complicated factors, can be subjected to simple analyses.

In order to assess the role of factors affecting the variation of SC of sodic soil in KS and SS treatments together, a stepwise regression was run using the 7 variables shown in Table 2. The results indicate that the combination of 3 parameters, EC, MWD, and AZ contents, significantly affects SC ([R.sup.2] =0.97, P < 0.001, n - 13) (Table 3). The higher MWD and AZ contents control the SC significantly (P < 0.01), although EC of soil increased the erodibility significantly (p < 0.001).

Conclusions

The effectiveness of artificial zeolite as a soil amendment in improving the physicochemical properties of sodic soils characterised with different clay mineralogies was investigated in this study. The soil aggregate breakdown process of sodic soil showed different tendencies, depending on the clay mineralogy of smectite (SS), kaolinite (KS), and allophane (AS). The mean weight diameter (MWD) of KS was most stable against sodicity followed by that of SS. The reduction rates of size fractions >2000 [micro]m of SS45, KS77, and AS30 were 88.6, 42.5, and 79.5%, respectively, whereas the aggregates >500 [micro]m broke down at 70.0, 53.2, and 66.5%, respectively. This is because the dispersion of aggregate of sodic SS was easily affected by slaking during fast wetting and swelling induced by the high sodium content. As the ESP increased, both soils exhibited different characteristic trends of soil erosion. A linear relation was found between the ESP and the sediment concentration for the KS soil, whereas a power function was the appropriate fit for the SS soil.

The incorporation of artificial zeolite amendments improved wet aggregate stability. For instance, the application of 10% AZ to sodic soil increased the MWD to 22.4% and 59.4% in the case of SS45 and KS77, respectively, as the soil ESP decreased. This result leads to improvement in saturated hydraulic conductivity of SS45 and KS77 treated with 10% AZ by up to 2.5 and 2.0 times, respectively. This amendment also resulted in a considerable decrease in soil loss and sediment concentration. The cumulative runoff (CR) of SS37, SS45, and SS53 treated with the addition of 10% AZ decreased up to 9.2 [+ or -] 3.1% on an average, while that of KS77 decreased up to 16.3%. SC of the sodic SS also decreased by 21.1 [+ or -] 6.8% after 10% AZ amendment, while SC of KS77 decreased by 23.2% after 10% AZ amendment. The effect of AZ amendment extended to the quality of the runoffwater. The EC of the runoff increased owing to the dissolved ions generated from soil aggregate dispersion; however, the application of AZ considerably decreased the EC of the runoff and the amount of Na.

PCA was also performed to group all the studied soils into fewer groups characterised by significant factors. The soils were grouped as follows: 3 original soils, and sodic KS and SS treatments, which were characterised by physicochemical properties of soil and erodibility. Stepwise regression was carried out to assess the indicator of erodibility. The increased effect of MWD and AZ contents on SC was observed, while negative influence of EC on SC was observed. These findings are also backed up by the effect of AZ in controlling soil erosion. However, further studies are needed to clarify the physicochemical mechanisms of AZ such as the contribution of the chemical exchange between clay and AZ and the binding of soil dispersed particles.

10.1071/SR09158

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Manuscript received 1 September 2009, accepted 23 February 2010

S. Moritani (A,D), T. Yamamoto (A), H. Andry (A), M. Inoue (A), A. Yuya (B), and T. Kaneuchi (C)

(A) Arid Land Research Center, Tottori University, Tottori, Japan.

(B) Forestry and Forest Products Research Institute, Hiroshima, Japan.

(C) Tokyu Construction Co. Ltd, Tokyo, Japan.

(D) Corresponding author. Email: hatshige01@alrc.tottori_u.ac.jp
Table 1. Physicochemical properties of 3 types of soils

SS, Smectitic; KS, kaolinitic; AS, allophonic soil, n.d.,
Not determined

Soil              Fraction (%)
                                        Soil organic        Bulk
         Sand        Silt       Clay       carbon         density
       2.0-0.02   0.02-0.002   >0.002      (g/kg)      (g/[cm.sup.3])

SS       12.1        25.8       62.1        17.0             n.d.
KS       25.0        19.0       56.0        27.0             1.09
AS       22.3        29.1       46.8         5.0             1.11

Table 2. Physicochemical properties of artificial zeolite
(AZ), kaolinitic soil (KS), smectitic soil (SS) allophonic
soil (AS), each sodic soil, and soils amended by AZ

EC, Electronical conductivity at I : 5 water: soil extract;
CEC, cation exchange capacity; ESP, exchangeable sodium
percentage; MWD, mean weight diameter; KS, saturated
hydraulic conductivity. Numerical values with soil indicate
ESP. n.d., Not determined

                   [MATHEMATICAL EXPRESSION
Soil     AZ       NOT REPRODUCIBLE IN ASCII]    E[C.sub.1:5]
       content             (1:2.5)                 (dS/m)
         (%)

AZ       100                10.5                   1.72
SS         0                 6.9                   0.12
KS         0                 6.7                    0.7
AS         0                 5.3                   0.05
SS45       0                  10                   1.46
           5                10.2                   1.47
          10                10.2                   1.49
KS77       0                 8.8                    1.2
           5                 9.2                   1.24
          10                 9.2                   1.28
AS30       0                 9.6                   0.91
           5                 9.8                   0.95
          10                 9.8                   0.99

Soil     AZ             CEC           ESP    MWD           KS
       content   ([cmol.sub.c]/kg)    (%)   (mm)    ([10.sub.-6]cm/S)
         (%)

AZ       100             320         20.9   0.047          n.d.
SS         0            31.9          1.2   1.85            320
KS         0            11.4          6.4   1.53             67
AS         0            10.7         0.94   0.95           1200
SS45       0            31.9           45   0.39            1.7
           5            46.3         36.7   0.41            1.8
          10            60.7         32.3   0.47            4.3
KS77       0            11.4           77   0.77            2.6
           5            27.4         38.8   0.99            4.6
          10            43.5         29.4   1.05            5.3
AS30       0            10.7           30   0.42            130
           5            26.2         24.5   n.d.            n.d.
          10            41.6           23   n.d.            n.d.

Table 3. Regression coefficients, standard error, and significance
level of the stepwise regression between sediment concentration of
kaolinitic and smectitic sodic soil with artificial zeolite (AZ)
amendment and 4 main soil properties

Model          Unstandardised   Standardised     T     Significance
                coefficients    coefficients              level
                                    Beta                   (P)
                  B     s.e.

Constant        -24.9   8.67                   -2.87       0.018
EC               51.1   4.63        0.79       11.03      <0.001
MWD             -20.2   5.17       -0.28        3.91       0.004
AZ contents     -0.55   0.15       -0.22       -3.75       0.005
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Author:Moritani, S.; Yamamoto, T.; Andry, H.; Inoue, M.; Yuya, A.; Kaneuchi, T.
Publication:Australian Journal of Soil Research
Article Type:Report
Geographic Code:9JAPA
Date:Aug 1, 2010
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