Full particle size distribution characteristics of land surface sediment and their effect on wind erosion resistance in arid and semiarid regions of Northwest China
Introduction
The characteristics of the land surface are varied rather than homogeneous. Arid and semiarid areas are characterized by different landscape surfaces such as desert, Gobi, salt lakes, oases, desertified grassland, and savanna. The particle size distribution (PSD) of sediment on the surface of such landscapes differs markedly. Even at the very small scale (e.g., 1 m), the PSD of sediment on the surface of various landscapes is rarely uniform. In arid and semiarid areas, surface heterogeneity affects the effective transmission of momentum between the atmosphere and the surface, which can influence the entire process of wind erosion from entrainment through transportation to deposition (Bagnold, 1941; Shao, 2008; Kok et al., 2012). Moreover, the combination of vegetation cover and the sediment PSD markedly influences the resistance of the land surface to wind erosion (Gillette, 1978; Tsoar, 1986; Alfaro, 2008; Goossens and Buck, 2010; Nicholas and Strong, 2011), the intensity and frequency of surface windblown-sand activity (Laurent et al., 2006, Laurent et al., 2008; Li et al., 2008; Wang et al., 2015), and eolian geomorphic evolution and the development of sandy desertification processes (Anderson and Bunas, 1993; David and Thomas, 2011; Nield and Wiggs, 2011).
The traditional parameters of the mean value, sorting coefficient, skewness, and kurtosis of the PSD of sediment are used commonly to identify differences in sediment particle characteristics (Folk and Ward, 1957; Wang et al., 2003; Farrell et al., 2012; Alessio et al., 2016). However, the spatial distribution of the components of sediment is difficult to realize based on these parameters of the full PSD, that is, they cannot characterize the spatial heterogeneity of the full PSD of surface sediment. Various mathematical models have been proposed for describing the PSD of sediment, such as the Beerkan Estimation of Soil Transfer model (Lassabatere et al., 2006), Logarithm model (Zhuang et al., 2001), Hyperbolic model (Vipulanandan and Ozgurel, 2009), Weibull two-parameter model (Wohletz et al., 1989; Zobeck et al., 1999), and fractal models (Bittelli et al., 1999; Millan et al., 2003). Bayat et al. (2015) compared the characteristics and fitting capability of these different PSD models. The model parameters were found to fit well with the PSD curves of sand, silt, clay, and other particles, and such models have been applied successfully in research on soil physics and soil mechanics owing to their simplicity and accuracy. However, many full PSD model parameters are determined by the structural characteristics of sediment, which are derived without consideration of the relationship with traditional PSD parameters, composition content, and resistance of the surface to wind erosion. Consequently, in relation to arid and semiarid areas, the surface eolian sand processes related to environmental evolution and geomorphic evolution have seldom been studied.
The Li model P(Di) = CDi−μexp(−Di/Dc) is applicable to the PSD of all types of soil (Li et al., 2017). The power function and the exponential function of this expression correspond to the self-similar and random processes, respectively, of particle fragmentation and accumulation in the process of soil evolution. Parameters μ and Dc satisfy a certain probability distribution (e.g., the Weibull distribution), and this relationship can be used to express quantitatively the spatial heterogeneity of soil (Li et al., 2017). Soil is a loose aggregation of mineral particles and organic matter with developed pores that largely contain water and air. It is popularly understood as a comprehensive product formed from a parent material under the action of biology. However, the surface materials in arid and semiarid areas are generally Quaternary sediments or weathered deposits owing to the periods of drought and low rainfall that limit the formation of soil particles, and the intense and frequent periods of wind erosion that can easily remove soil particles during windblown-sand activities. Sediments can serve as the parent material of soil; however, not all sediments become soil, especially those sediments distributed in arid and semiarid climates. Obviously, soil and sediment are related but they are not identical. Thus, further verification is required to determine whether the Li model is suitable for application to eolian sediments in arid regions, and to establish the general characteristics and application value of the full PSD parameters.
The arid and semiarid region of Northwest China, which is a mid-latitude continental arid climate zone, represents a globally notable area of desert and desertified land that is an important source of dust release (Zhang et al., 1997; Shao, 2008; Guan et al., 2017, Guan et al., 2019). Based on the Li model, this study investigated the spatial differentiation characteristics and parameters of the full PSD of the surface sediment of various types of landscape in the arid and semiarid region of Northwest China. The significance of the characterization has important consequences regarding understanding of the environment, geomorphic evolution, and related surface windblown-sediment processes in arid regions; specifically, surface resistance to wind erosion.
Section snippets
Regional setting
This study focused on the arid and semiarid region of Northwest China (34°–44°N, 75°–125°E). In arid parts of this region, such as the Tarim Basin (I), Qaidam Basin (II), and Hexi–Alxa region (III), annual rainfall is <200 mm, whereas in semiarid areas, such as the Ordos Plateau (IV) and eastern parts of the Inner Mongolia Plateau (V), annual rainfall is 200–400 mm (Fig. 1). Gobi refers to a desert area in which the ground surface is mostly covered with coarse sand and gravel and where plants
Wind erosion monitoring and sampling
During March 2009 and April 2011, Ir data were collected in four overlapping intervals: Period 1 (8/3/2009–15/7/2009), Period 2 (10/6/2009–29/5/2010), Period 3 (29/3/2010–19/5/2010), and Period 4 (7/5/2010–29/3/2011). For each monitoring period, the first date represents the day on which the first monitoring station was set and the last date represents the last day of monitoring. Overall, nearly 1000 trap sand collectors with volume of 5 L and mouth diameters of 90 mm were implemented. Full
Distribution, composition, and mean particle size parameters
The mean contents of different particle sizes and the standard deviation distribution of the surface sediment in the different landscapes investigated in this study are shown in Fig. 4. Table 2 also presents the mean particle size parameters of the different landscapes. The results reveal significant differences in the distribution, composition, and mean particle size parameters among the sandy gravel, sandy, and silty sand surfaces in the five regions (Fig. 4 and Table 2).
It can be seen that
Applicability of the Li model to land surface sediment from arid regions
From a probability and statistical perspective, the Weibull distribution is a continuous probability distribution, the density function of which can be expressed as follows:where x is a random variable, λ > 0 is a scale parameter, and κ > 0 is a shape parameter. As κ = 1 indicates an exponential distribution, its cumulative distribution function is an extended exponential distribution function.
In the field of geosciences, the Weibull distribution has been used to describe
Conclusions
The Li model of the full PSD can be used to accurately and flexibly calculate the variation trend of sediment particle size accumulation; however, the representativeness of the parameters is influenced by both the sampling particle size division (i.e., ΔDi and N) and the range (Dmin, Dmax) of the particle size data to be fitted. The full PSD parameters μ and Dc not only reveal the distribution of the total particle sizes of the surface sediment of various landscapes, but they also reflect the
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (No. 41861001), the Talent program of the Inner Mongolia Agricultural University (NDVB2017-3), and the opening Fund of the Key Laboratory of Desert and Desertification, Chinese Academy of Sciences (KLDD-2020-011). We thank James Buxton MSc from Liwen Bianji, Edanz Group China (www.liwenbianji.cn/ac), for editing the English text of this manuscript.
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