Improved estimation of clay content from water content for soils rich in smectite and kaolinite
Introduction
Numerous soil microbial, physical and chemical processes (e.g., soil respiration, water and nutrient retention and dynamics and soil erosion) are strongly affected by the abundance of clay, silt and organic matter. Consequently, accurate estimates of these soil properties are of essence for studying soil processes across scales. Because standard measurement methods for the particle size distribution (e.g., the pipette and hydrometer methods), particularly the clay fraction (<2 μm), are laborious and difficult to repeat, various alternative methods including the Kettler rapid method (Kettler et al., 2001; Moosavi et al., 2014), laser diffraction (Zobeck, 2004), the Sedigraph method (Müller et al., 2009), and proximal sensing methods such as gamma-ray spectrometry (Heggemann et al., 2017) and infrared spectroscopy (e.g., Hermansen et al., 2017) have been proposed. The rapid and proximal sensing methods can still be expensive and location-specific, respectively. Applying previously developed models from proximal sensing approaches to new geographical locations often requires extensive calibration with local samples.
Utilization of soil water content to estimate clay content presents a much cheaper option with little or no instrumentation because clay estimation models that utilize water contents require only a relative humidity meter and a standard laboratory oven. As soil dries, the clay fraction is intimately linked to water content, and several pedotransfer functions have been developed to estimate properties like permanent wilting point from the clay fraction (Adhikary et al., 2008). Similarly, models have been developed to estimate the clay fraction from sorbed or hygroscopic water content (Wäldchen et al., 2012; Wuddivira et al., 2012). These models estimate the clay fraction from water content at relative humidity (RH) ~20–22% (Wäldchen et al., 2012), 50% RH (Wuddivira et al., 2012), at an arbitrary RH (Chen et al., 2014) or at permanent wilting point, RH = 98.9% (Farrick et al., 2019). The models estimate clay contents reasonably well but are limited by water sorption hysteresis, presence of large contents of organic matter, and silt (Arthur et al., 2015), calcium carbonate content (Arthur et al., 2017), and the prevailing clay mineralogy (Wuddivira et al., 2012). Subsequent improvements to such models accounted for hysteresis and samples with large contents of organic matter (Arthur et al., 2015). One of the outstanding limitations of such models is consideration of the dominant clay mineralogy of the sample (Chen et al., 2014). A majority of the water sorption-based models were developed from samples that have a mixture of clay minerals or large amounts of illitic minerals (Arthur et al., 2015; Chen et al., 2014; Wuddivira et al., 2012). Consequently, the models give inaccurate estimations of clay content for samples comprising primarily of kaolinite or smectite minerals, due to the large variation in water sorption for these types of samples. At any given RH, the water sorbed for a kaolinitic sample will be significantly smaller, due to its much smaller specific surface area, than for a smectitic sample that has identical clay content. Globally, kaolinite is the dominant clay mineral in highly weathered soils of the southeastern United States, and tropical regions of Africa, Asia and South America (Ito and Wagai, 2017). Further, smectitic soils occur in large quantities in areas such the northwestern Mississippi River watershed (Sionneau et al., 2008), large swathes of Russia, Australia and sub-Sahara Africa. Consequently, it is of interest to consider modifying existing water sorption-based models to account for these two groups of soils. The objective was to propose correction factors to existing water sorption-based clay estimation models for soils rich in 1:1 non-swelling clay (kaolinite) and 2:1 swelling clay (smectite) minerals to improve estimation accuracy.
Section snippets
Investigated samples
One hundred and six (106) soil samples from 20 countries across five continents (Europe [20], North America [41], Africa and Asia [30], and South America [15]) were considered for this study. Based on the clay mineralogy, the ratio of cation exchange capacity (CEC) to clay content, and the shape of the water vapor sorption isotherms (see Fig. 1), the samples were divided into three groups: 20 illite-rich [IL], 54 smectite-rich [SM], and 32 kaolinitic [KA]-rich samples. The IL, SM, and KA-rich
Results and discussion
Typical sorption isotherms for three types of samples, smectitic, illitic and kaolinitic, are presented in Fig. 1. The samples differed in the shape of their isotherms, the amount of water sorbed, and the magnitude of hysteresis. The SM sample isotherms can be classified as Type IV, while the IL and KA samples exhibited Type II and III isotherm shapes, respectively (Brunauer et al., 1940). The SM sample isotherm is hysteretic across the full RH range; the IL exhibits increasing hysteresis with
Conclusions
We evaluated an existing model to estimate clay contents from hygroscopic water content for three soil sample groups: samples rich in smectite (SM), illite (IL), and kaolinite (KA). The model estimated clay content accurately for the IL samples, but poorly estimated clay content for the SM and KA samples. Correction factors based on the deviation of the estimated clay content from the measured clay content were used to improve the existing model. The improved model reduced average estimation
Acknowledgments
This research was financed by VILLUM FONDEN research grant 13162 and Danish Council for Independent Research via the project: Water Vapor Sorption Isotherms as Proxy for Soil Surface Properties DFF -4184-00171). We especially thank Dr. Cristine Morgan, formerly of Texas A&M University, The International Soil Reference and Information Centre (ISRIC) and Professor Dr. Eric Van Ranst of Ghent University for providing soil samples for this research.
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