Effect of Soil Aggregate Size Distribution on Water Retention

Guber, Andrey; Rawls, W. J.; Шеин, Е. В.; Pachepsky, Y. A.

doi:10.1097/01.ss.0000064887.94869.d3

Cited by 30 publications

(19 citation statements)

References 17 publications

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“…These results are in agreement with those from other studies (Arya et al, 1983;Tallon and Si, 2004;Pachepsky et al, 2005;Guber et al, 2008;Penna et al, 2009;Hu et al, 2009). The effects of climatic conditions (Hu et al, 2010), root activity (Cassel et al, 2000), and soil structure (Guber et al, 2003) on the SWS spatial patterns gradually decrease with depth. Other studies investigating the temporal stability of SWS spatial patterns using Spearman's rank correlations have reported similar results (Biswas and Si, 2011a;Gao and Shao, 2012b;Jia and Shao, 2013;Zhang and Shao, 2013).…”

Section: Discussionsupporting

confidence: 83%

Depth persistence of the spatial pattern of soil–water storage along a small transect in the Loess Plateau of China

Shao

Jia

et al. 2015

Journal of Hydrology

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Keywords:Depth persistence Soil-water storage Spatial pattern Wavelet coherency The Loess Plateau s u m m a r y Knowledge of the spatial patterns of soil-water storage (SWS) in soil profiles is important for understanding the dynamics of soil water between surface and subsurface soil layers in semiarid area. We investigated the depth persistence of the overall and scale-specific spatial patterns of SWS for different soil layers during different seasons. Soil-water contents were measured using a neutron probe on 22 occasions in 2012 and 2013 along a 1340-m transect over several sub-watersheds in the Liudaogou catchment on the Loess Plateau of China. Similarities in the spatial patterns of SWS were analyzed by Spearman's rank correlations and wavelet coherency. A spatiotemporal analysis indicated that the temporal evolution of the SWS profiles differed between the growing and non-growing seasons and that landscape position and soil texture determined the amount of SWS at each sampling location. Spearman's rank correlations were significant between any two layers within different seasons, and the correlation coefficients decreased as the distance between layers increased. Clay content controlled the spatial pattern of SWS between layers at large scales. The SWS spatial pattern had a higher depth persistence during the non-growing season than during the growing season, and the soil layer had a larger effect than season on the similarity in SWS spatial patterns. These results can improve our understanding of the hydrological processes in soil profiles and can be of considerable value in the application of hydrological models and in water management.

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Section: Discussionsupporting

confidence: 83%

Depth persistence of the spatial pattern of soil–water storage along a small transect in the Loess Plateau of China

Shao

Jia

et al. 2015

Journal of Hydrology

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“…Therefore, the study of scaling properties in soil water content at the surface few centimeters (such as remote sensing measurement) is more complicated and is highly variable in nature (Biswas and Si, 2011a, b). On contrary, deep soil layers are less responsive to the changes in meteorological conditions (Hu et al, 2010), have less root activity (Cassel et al, 2000) and less disturbed soil structure (Guber et al, 2003;Pachepsky et al, 2005), which increase the buffering capacity of soil water changes in the deep layers and create an hydrological inertia (Martínez-Fernández and Ceballos, 2003) in soil water dynamics. Moreover, the rapid changes of soil water at the surface do not represent the actual changes in the vadosezone soil water storage.…”

Section: A Biswas Et Al: Multifractal Detrended Fluctuation Analysismentioning

confidence: 99%

Multifractal detrended fluctuation analysis in examining scaling properties of the spatial patterns of soil water storage

Biswas

Zeleke²,

Cheng

2012

Nonlin. Processes Geophys.

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Abstract. Knowledge about the scaling properties of soil water storage is crucial in transferring locally measured fluctuations to larger scales and vice-versa. Studies based on remotely sensed data have shown that the variability in surface soil water has clear scaling properties (i.e., statistically self similar) over a wider range of spatial scales. However, the scaling property of soil water storage to a certain depth at a field scale is not well understood. The major challenges in scaling analysis for soil water are the presence of localized trends and nonstationarities in the spatial series. The objective of this study was to characterize scaling properties of soil water storage variability through multifractal detrended fluctuation analysis (MFDFA). A field experiment was conducted in a sub-humid climate at Alvena, Saskatchewan, Canada. A north-south transect of 624-m long was established on a rolling landscape. Soil water storage was monitored weekly between 2002 and 2005 at 104 locations along the transect. The spatial scaling property of the surface 0 to 40 cm depth was characterized using the MFDFA technique for six of the soil water content series (all gravimetrically determined) representing soil water storage after snowmelt, rainfall, and evapotranspiration. For the studied transect, scaling properties of soil water storage are different between drier periods and wet periods. It also appears that local controls such as site topography and texture (that dominantly control the pattern during wet states) results in multiscaling property. The nonlocal controls such as evapotranspiration results in the reduction of the degree of multiscaling and improvement in the simple scaling. Therefore, the scaling property of soil water storage is a function of both soil moisture status and the spatial extent considered.

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“…Particle size distribution is a fundamental soil property that is commonly used to estimate other soil properties and processes, such as water retention characteristics (Guber et al, 2003;Henderson et al, 2005;Wösten et al, 2001), erosion capacity (Cheng et al, 2007;Guo et al, 2007;Wischmeier and Mannering, 1969), and transmission and distribution of nutrients and pollutants (Li and Pang, 2014;Six et al, 2002;Wang and Keller, 2008;Wang et al, 2006). Numerous studies have demonstrated that soil surface properties profoundly influence these soil properties and processes (Bower and Gschwend, 1952;Ding et al, 2010;Fruhstorfer et al, 1993;Jenny and Reitemeier, 1934;Jiang et al, 2011;Li et al, 2010a;Petersen et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

Unraveling the size distributions of surface properties for purple soil and yellow soil

Tang

Liu

et al. 2015

Journal of Environmental Sciences

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Soils contain diverse colloidal particles whose properties are pertinent to ecological and human health, whereas few investigations systematically analyze the surface properties of these particles. The objective of this study was to elucidate the surface properties of particles within targeted size ranges (i.e. > 10, 1-10, 0.5-1, 0.2-0.5 and <0.2 μm) for a purple soil (Entisol) and a yellow soil (Ultisol) using the combined determination method. The mineralogy of corresponding particle-size fractions was determined by X-ray diffraction.We found that up to 80% of the specific surface area and 85% of the surface charge of the entire soil came from colloidal-sized particles (< 1 μm), and almost half of the specific surface area and surface charge came from the smallest particles (< 0.2 μm). Vermiculite, illite, montmorillonite and mica dominated in the colloidal-sized particles, of which the smallest particles had the highest proportion of vermiculite and montmorillonite. For a given size fraction, the purple soil had a larger specific surface area, stronger electrostatic field, and higher surface charge than the yellow soil due to differences in mineralogy.Likewise, the differences in surface properties among the various particle-size fractions can also be ascribed to mineralogy. Our results indicated that soil surface properties were essentially determined by the colloidal-sized particles, and the < 0.2 μm nanoparticles made the largest contribution to soil properties. The composition of clay minerals within the diverse particle-size fractions could fully explain the size distributions of surface properties.

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Effect of Soil Aggregate Size Distribution on Water Retention

Cited by 30 publications

References 17 publications

Depth persistence of the spatial pattern of soil–water storage along a small transect in the Loess Plateau of China

Depth persistence of the spatial pattern of soil–water storage along a small transect in the Loess Plateau of China

Multifractal detrended fluctuation analysis in examining scaling properties of the spatial patterns of soil water storage

Unraveling the size distributions of surface properties for purple soil and yellow soil

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