Please wait a minute...
Journal of Arid Land  2021, Vol. 13 Issue (7): 653-673    DOI: 10.1007/s40333-021-0072-7     CSTR: 32276.14.s40333-021-0072-7
Research article     
Effect of stones on the sand saltation threshold during natural sand and dust storms in a stony desert in Tsogt-Ovoo in the Gobi Desert, Mongolia
Batjargal BUYANTOGTOKH1,2,*(), Yasunori KUROSAKI1, Atsushi TSUNEKAWA1, Mitsuru TSUBO1, Batdelger GANTSETSEG2, Amarsaikhan DAVAADORJ2, Masahide ISHIZUKA3, Tsuyoshi T SEKIYAMA4, Taichu Y TANAKA4, Takashi MAKI4
1Arid Land Research Center, Tottori University, Tottori 680-0001, Japan
2Information and Research Institute of Meteorology, Hydrology and Environment, Ulaanbaatar 15160, Mongolia
3Faculty of Engineering and Design, Kagawa University, Takamatsu 761-0396, Japan
4Meteorological Research Institute, Japan Meteorological Agency, Tsukuba 305-0052, Japan
Download: HTML     PDF(2716KB)
Export: BibTeX | EndNote (RIS)      

Abstract  

Non-erodible elements such as stones and vegetation are key to controlling wind erosion and dust emission in drylands. Stony deserts are widely distributed in the Gobi Desert, but the effect of stones on wind erosion and dust emission have not been well studied, except under artificial conditions. In this study, we evaluated the effect of stones on wind erosion and dust emission by measuring the sand saltation threshold in a stony desert in Tsogt-Ovoo in the Gobi Desert, Mongolia, under natural surface conditions during sand and dust storms. We quantified the amount of stones by measuring the roughness density, and determined the threshold friction velocity for sand saltation by measuring wind speed and sand saltation count. Our results showed that the threshold friction velocity increased with the roughness density of stones. In the northern part of the study area, where neither a surface crust nor vegetation was observed, the roughness density of stones was 0.000 in a topographic depression (TD), 0.050 on a northern slope (N.SL), and 0.160 on the northern mountain (N.MT). The mean threshold friction velocity values were 0.23, 0.41, and 0.57 m/s at the TD, N.SL, and N.MT sites, respectively. In the southern part of the study area, the roughness density values of stones were 0.000 and 0.070-0.320 at the TD and southern slope sites, respectively, and the mean threshold friction velocities were 0.23 and 0.45-0.71 m/s, respectively. We further compared the observed threshold friction velocities with simulated threshold friction velocities using Raupach's theoretical roughness correction and the measured roughness density values, and found that Raupach's roughness correction worked very well in the simulation of threshold friction velocity in the stony desert. This means that the results of our stone measurement can be applied to a numerical dust model.



Key wordsarid region      threshold friction velocity      roughness density      shear stress      sand saltation threshold      roughness correction      Gobi Desert     
Received: 21 December 2020      Published: 10 July 2021
Corresponding Authors:
About author: *Batjargal BUYANTOGTOKH (E-mail: buya_9@yahoo.com)
Cite this article:

Batjargal BUYANTOGTOKH, Yasunori KUROSAKI, Atsushi TSUNEKAWA, Mitsuru TSUBO, Batdelger GANTSETSEG, Amarsaikhan DAVAADORJ, Masahide ISHIZUKA, Tsuyoshi T SEKIYAMA, Taichu Y TANAKA, Takashi MAKI. Effect of stones on the sand saltation threshold during natural sand and dust storms in a stony desert in Tsogt-Ovoo in the Gobi Desert, Mongolia. Journal of Arid Land, 2021, 13(7): 653-673.

URL:

http://jal.xjegi.com/10.1007/s40333-021-0072-7     OR     http://jal.xjegi.com/Y2021/V13/I7/653

Fig. 1 Topographic map showing the locations of the observation sites around Tsogt-Ovoo. Stars indicate sites where observations were conducted year-round: The Main site (labeled 1; see Table 1) was established in March 2012, and sites Sub14A and Sub14B (labeled 2 and 3, respectively) were established in March 2014. Temporary observation sites are indicated by triangles. Observations were conducted during 1-5 May 2018 at sites Sub18A-Sub18D (labeled 4-7, respectively) and from 27 April to 8 May 2019 at sites Sub19A-Sub19D (labeled 8-11, respectively). Wind speed, wind direction, and sand saltation count were observed at all sites, whereas soil moisture was observed only at the year-round sites.
No. Site
name
Geographical coordinates Type of site Observation
period
Topographic position Surface
characteristic
1 Main 44°23′04′′N 105°16′59′′E Year-round 1-5 May 2018 N.SL Stone
27 April-8 May 2019 Stone and vegetation
2 Sub14A 44°23′37′′N 105°13′24′′E Year-round 1-5 May 2018 TD Hard crust
27 April-8 May 2019 Crust and vegetation
3 Sub14B 44°23′32′′N 105°13′12′′E Year-round 1-5 May 2018 S.SL Stone
27 April-8 May 2019 Stone and vegetation
4 Sub18A 44°22′23′′N 105°11′28′′E Temporary 1-5 May 2018 S.MT Stone
5 Sub18B 44°24′26′′N 105°14′01′′E Temporary 1-5 May 2018 N.SL Stone
6 Sub18C 44°27′32′′N 105°16′48′′E Temporary 1-5 May 2018 N.MT Stone
7 Sub18D 44°21′47′′N 105°14′51′′E Temporary 1-5 May 2018 TD Hard crust
8 Sub19A 44°21′52′′N 105°14′04′′E Temporary 27 April-8 May 2019 S.SL Stone
9 Sub19B 44°22′02′′N 105°14′27′′E Temporary 27 April-8 May 2019 S.SL Stone
10 Sub19C 44°22′29′′N 105°14′54′′E Temporary 27 April-8 May 2019 TD Sand and soft crust
11 Sub19D 44°22′39′′N 105°14′59′′E Temporary 27 April-8 May 2019 TD Sand
Table 1 Site locations and type, measurement periods, topographic positions, and surface characteristics
Fig. 2 Land surface conditions in front of the saltation count sensor at 14 observation sites. Each site name is shown at the bottom of each photo with the topographic position (MT, mountain; SL, slope; TD, topographic depression) and observation year in parentheses. The diameter of the mouth of the sand catcher was 3.1 cm, and the diameter of the sand saltation count sensor was 1.2 cm.
Fig. 3 Workflow showing the observation and model simulation of the threshold friction velocity in this study. λs is the roughness density of stones, and f(λs) is a correction functions for a roughness element.
Fig. 4 Layout of quadrats (gray rectangles) where land surface photographs were taken for stone measurement (a) and demonstration of anemometer and wind vane (b). The black dot in the left panel indicates the position of the UD-101 count sensor, which faced northwest. The UD-101 sensor was installed at the height of 0.1 m; the anemometer and wind vane were installed at the height of 1.7 m.
Fig. 5 Demonstration of image processing steps. (a), cropped image with scale; (b), the color threshold for soil that is manually set; (c), image after application of the threshold for stones and the ''Fill Holes'' and ''Watershed'' functions to separate particles; (d), final image after application of the ''Extended Particle Analyzer'' function, which removes coarse sand particles.
Fig. 6 Time series of friction velocity during 28-29 May 2019 at the site Sub19D. Blue line, no sand transport; black line, active sand transport; u*t inst, instantaneous threshold friction velocity at the start and end of sand transport; u*t mean, mean threshold friction velocity (dashed horizontal line). Friction velocities obtained when the wind direction was between 10° and 260° (green line) were not used in the determination of the threshold friction velocity. Friction velocity was calculated using Equation 3 with aerodynamic roughness length of the threshold friction velocity. Friction velocity was calculated using Equation 3 with aerodynamic roughness length of 0.0012 m/s. Wind speed and wind direction (WD) were measured at 1.7 m height. UTC is the Coordinated Universal Time.
Site name Soil texture Stone coverage (%) Ratio of breadth to height Height
(cm)
Roughness density Roughness
length
(cm)
Mean SD Mean SD Mean SD Mean SD
Main Loam 18.6 2.95 1.75 0.37 0.39 0.15 0.05 0.001 0.0152
Sub14A Loam 0.0 - - - - - 0.00 - 0.0012
Sub14B Loam 22.4 3.52 1.81 0.30 0.57 0.23 0.07 0.016 0.0318
Sub18A Loam 57.1 5.84 1.88 0.36 1.05 0.27 0.34 0.039 0.1569
Sub18B Loam 28.8 3.26 1.85 0.35 0.48 0.19 0.13 0.017 0.0519
Sub18C Sandy Loam 33.9 4.25 1.74 0.43 0.65 0.37 0.16 0.023 0.0878
Sub18D Silt Loam 2.9 1.01 1.93 0.41 0.47 0.16 0.01 0.004 0.0011
Sub19A Loam 47.2 4.13 1.89 0.37 1.01 0.35 0.32 0.031 0.1587
Sub19B Loam 39.7 4.73 1.84 0.39 0.89 0.30 0.24 0.036 0.1628
Sub19C Loam 0.0 - - - - - 0.00 - 0.0012
Sub19D Loam 0.0 - - - - - 0.00 - 0.0012
Table 2 Measurement results for coverage, mean height, roughness density, and roughness length of stones at each site
Fig. 7 Relationship between stone coverage and roughness density from this study (black dots) and the study of Marticorena et al. (2006) (open circles)
Fig. 8 Frequency distributions of the ratio of breadth to height of stones at the sites Sub18A (a), Sub19A (b), Sub19B (c), Sub18C (d), Sub18B (e), Sub14B (f), Main (g), and Sub18D (h)
Fig. 9 Friction velocity when the wind direction was between 260° and 370° (i.e., 10°) (blue lines) or between 10° and 260° (green lines), instantaneous threshold friction velocity (red circles), and mean threshold friction velocity (dashed lines) during 1-5 May 2018 at the sites Sub18C (a), Sub14B (b), and Main (c). u*t mean, mean threshold friction velocity; SD, standard deviation of the instantaneous thresholds around the mean.
Fig. 10 Friction velocity when the wind direction was between 260° and 370° (i.e., 10°) (blue lines) or between 10° and 260° (green lines), instantaneous threshold friction velocity (red circles), and mean threshold friction velocity (dashed lines) from 27 April to 8 May 2019 at the sites Sub19A (a), Sub19B (b), Sub14B (c), Main (d), Sub14A (e), Sub19C (f), and Sub19D (g).
Fig. 11 Relationship between roughness density and mean threshold friction velocity observed at the bare or stony (i.e., no vegetation and no crust) sites (black dots), stony and vegetated sites (open rectangles), vegetated site with crust (open triangle), and site with crust only (open rhombus) in spring 2018 and 2019. Symbols show the average roughness density and mean observed threshold friction velocity, and bars show their standard deviations. For sites Main, Sub14A, and Sub14B, where observations were carried out year-round, the four digits before the site name indicate the year of the observations.
Fig. 12 Scatter plot between the observed threshold friction velocity (during 1-5 May 2018 and during 27 April-8 May 2019) and simulated threshold friction velocity using the observed roughness density of stones at the bare or stony (i.e., no vegetation and no crust) sites (black dots), stony and vegetated sites (open rectangles), vegetated site with crust (open triangle), and site with crust only (open rhombus). The two horizontal thin dashed lines show the simulated threshold friction velocity using roughness densities of 0.002 and 0.020 for barren and sparsely vegetated land cover types, respectively.
Fig. 13 Crust conditions at the sites Sub14A (a) and Sub18D (b) in spring 2018, and at the sites Sub14A (c) and Sub19C (d) in spring 2019
[1]   Bagnold R A. 1941. The physics of blown sand and desert dunes. Progress in Physical Geography, 18(1):91-96.
[2]   Barchyn T E, Hugenholtz C H. 2011. Comparison of four methods to calculate aeolian sediment transport threshold from field data: Implications for transport prediction and discussion of method evolution. Geomorphology, 129(3-4):190-203.
doi: 10.1016/j.geomorph.2011.01.022
[3]   Belnap J, Gillette D A. 1998. Vulnerability of desert biological soil crusts to wind erosion: the influences of crust development, soil texture, and disturbance. Journal of Arid Environments, 39(2):133-142.
doi: 10.1006/jare.1998.0388
[4]   Boucher O, Randall D, Artaxo P, et al. 2013. Clouds and aerosols. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press, 571-657.
[5]   Callot Y, Marticorena B, Bergametti G. 2000. Geomorphologic approach for modelling the surface features of arid environments in a model of dust emissions: application to the Sahara Desert. Geodinamica Acta, 13(5):245-270.
doi: 10.1080/09853111.2000.11105373
[6]   Chen S, Huang J, Li J, et al. 2017. Comparison of dust emissions, transport, and deposition between the Taklimakan Desert and Gobi Desert from 2007 to 2011. Science China Earth Sciences, 60(7):1338-1355.
doi: 10.1007/s11430-016-9051-0
[7]   Cooke R U. 1970. Stone pavements in deserts. Annals of the Association of American Geographers, 60(3):560-577.
doi: 10.1111/j.1467-8306.1970.tb00741.x
[8]   Darmenova K, Sokolik I N, Shao Y, et al. 2009. Development of a physically based dust emission module within the Weather Research and Forecasting (WRF) model: Assessment of dust emission parameterizations and input parameters for source regions in Central and East Asia. Journal of Geophysical Research: Atmospheres, 114(D14), doi: 10.1029/2008JD011236.
[9]   Edwards B L, Namikas S L. 2015. Characterizing the sediment bed in terms of resistance to motion: Toward an improved model of saltation thresholds for aeolian transport. Aeolian Research, 19:123-128.
doi: 10.1016/j.aeolia.2015.10.004
[10]   Faé G S, Montes F, Bazilevskaya E, et al. 2019. Making soil particle size analysis by laser diffraction compatible with standard soil texture determination methods. Soil Science Society of America Journal, 83(4):1244-1252.
doi: 10.2136/sssaj2018.10.0385
[11]   Fécan F, Marticorena B, Bergametti G. 1998. Parametrization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semi-arid areas. Annales Geophysicae, 17:149-157.
doi: 10.1007/s00585-999-0149-7
[12]   Foroutan H, Young J, Napelenok S, et al. 2017. Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system. Journal of Advances in Modeling Earth Systems, 9(1):585-608.
doi: 10.1002/2016MS000823 pmid: 30245776
[13]   Gantsetseg B, Ishizuka M, Kurosaki Y, et al. 2017. Topographical and hydrological effects on meso-scale vegetation in desert steppe, Mongolia. Journal of Arid Land, 9(1):132-142.
doi: 10.1007/s40333-016-0090-z
[14]   Gillette D A. 1978. Tests with a portable wind tunnel for determining wind erosion threshold velocities. Atmospheric Environment, 12(12):2309-2313.
[15]   Gillette D A, Adams J, Endo A, et al. 1980. Threshold velocities for input of soil particles into the air by desert soils. Journal of Geophysical Research: Oceans, 85(C10):5621-5630.
[16]   Gillette D A, Adams J, Muhs D, et al. 1982. Threshold friction velocities and rupture moduli for crusted desert soils for the input of soil particles into the air. Journal of Geophysical Research: Oceans, 87(C11):9003-9015.
[17]   Gillette D A. 1988. Threshold friction velocities for dust production for agricultural soils. Journal of Geophysical Research: Atmospheres, 93(D10):12645-12662.
doi: 10.1029/JD093iD10p12645
[18]   Gillette D A, Herrick J E, Herbert G A. 2006. Wind characteristics of mesquite streets in the northern Chihuahuan Desert, New Mexico, USA. Environmental Fluid Mechanics, 6(3):241-275.
doi: 10.1007/s10652-005-6022-7
[19]   Gillies J A, Lancaster N, Nickling W G, et al. 2000. Field determination of drag forces and shear stress partitioning effects for a desert shrub (Sarcobatus vermiculatus, greasewood). Journal of Geophysical Research: Atmospheres, 105(D20):24871-24880.
doi: 10.1029/2000JD900431
[20]   Gillies J A, Nickling W G, King J. 2007. Shear stress partitioning in large patches of roughness in the atmospheric inertial sublayer. Boundary-Layer Meteorology, 122(2):367-396.
doi: 10.1007/s10546-006-9101-5
[21]   Greeley R, Iversen J D. 1985. Wind as a geological process on Earth, Mars, Venus and Titan. Cambridge: Cambridge University Press, 333.
[22]   Greeley R, Gaddis L, Lancaster N, et al. 1991. Assessment of aerodynamic roughness via airborne radar observations. In: Aeolian Grain Transport. Vienna: Springer, 77-88.
[23]   Hébrard E, Listowski C, Coll P, et al. 2012. An aerodynamic roughness length map derived from extended Martian rock abundance data. Journal of Geophysical Research: Planets, 117(E4), doi: 10.1029/2011JE003942.
[24]   Ishizuka M, Mikami M, Yamada Y, et al. 2009. Threshold friction velocities of saltation sand particles for different soil moisture conditions in the Taklimakan Desert. Sola, 5:184-187.
doi: 10.2151/sola.2009-047
[25]   Ishizuka M, Mikami M, Yamada Y, et al. 2012. Does ground surface soil aggregation affect transition of the wind speed threshold for saltation and dust emission? SOLA, 8:129-132.
doi: 10.2151/sola.2012-032
[26]   Iversen J D, Wang W P, Rasmussen K R, et al. 1990. The effect of a roughness element on local saltation transport. Journal of Wind Engineering and Industrial Aerodynamics, 36:845-854.
doi: 10.1016/0167-6105(90)90081-M
[27]   Kang J Y, Yoon S C, Shao Y, et al. 2011. Comparison of vertical dust flux by implementing three dust emission schemes in WRF/Chem. Journal of Geophysical Research: Atmospheres, 116(D9), doi: 10.1029/2010JD014649.
[28]   King J, Nickling W G, Gillies J A. 2005. Representation of vegetation and other nonerodible elements in aeolian shear stress partitioning models for predicting transport threshold. Journal of Geophysical Research: Earth Surface, 110(F4), doi: 10.1029/2004JF000281.
[29]   Kurosaki Y, Mikami M. 2007. Threshold wind speed for dust emission in East Asia and its seasonal variations. Journal of Geophysical Research: Atmospheres, 112(D17), doi: 10.1029/2006JD007988.
[30]   Kurosaki Y, Shinoda M, Mikami M. 2011a. What caused a recent increase in dust outbreaks over East Asia? Geophysical Research Letters, 38(11), doi: 10.1029/2011GL047494.
[31]   Kurosaki Y, Shinoda M, Mikami M, et al. 2011b. Effects of soil and land surface conditions in summer on dust outbreaks in the following Spring in a Mongolian Grassland. SOLA, 7:69-72.
doi: 10.2151/sola.2011-018
[32]   Lancaster N, Baas A. 1998. Influence of vegetation cover on sand transport by wind: field studies at Owens Lake, California. Earth Surface Processes and Landforms: The Journal of the British Geomorphological Group, 23(1):69-82.
[33]   Laurent B, Marticorena B, Bergametti G, et al. 2005. Simulation of the mineral dust emission frequencies from desert areas of China and Mongolia using an aerodynamic roughness length map derived from the POLDER/ADEOS 1 surface products. Journal of Geophysical Research: Atmospheres, 110(D18), doi: 10.1029/2004JD005013.
[34]   Lee H, Park S H. 2020. Stepwise assessment of different saltation theories in comparison with field observation data. Atmosphere, 11(1):10, doi: 10.3390/atmos11010010.
doi: 10.3390/atmos11010010
[35]   Li G, Zhang J, Herrmann H J, et al. 2020. Study of aerodynamic grain entrainment in aeolian transport. Geophysical Research Letters, 47(11): e2019GL086574.
[36]   Li Z, Wu S, Dale J, et al. 2008. Wind tunnel experiments of air flow patterns over nabkhas modeled after those from the Hotan River basin, Xinjiang, China (I): non-vegetated. Frontiers of Earth Science in China, 2(3):333-339.
doi: 10.1007/s11707-008-0019-8
[37]   Lopez M V, Sabre M, Gracia R, et al. 1998. Tillage effects on soil surface conditions and dust emission by wind erosion in semiarid Aragon (NE Spain). Soil and Tillage Research, 45(1-2):91-105.
doi: 10.1016/S0167-1987(97)00066-4
[38]   Marshall J K. 1971. Drag measurements in roughness arrays of varying density and distribution. Agricultural Meteorology, 8:269-292.
doi: 10.1016/0002-1571(71)90116-6
[39]   Marticorena B, Bergametti G. 1995. Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme. Journal of Geophysical Research: Atmospheres, 100(D8):16415-16430.
doi: 10.1029/95JD00690
[40]   Marticorena B, Bergametti G, Gillette D, et al. 1997a. Factors controlling threshold friction velocity in semiarid and arid areas of the United States. Journal of Geophysical Research: Atmospheres, 102(D19):23277-23287.
doi: 10.1029/97JD01303
[41]   Marticorena B, Bergametti G, Aumont B, et al. 1997b. Modeling the atmospheric dust cycle: 2. Simulation of Saharan dust sources. Journal of Geophysical Research: Atmospheres, 102(D4):4387-4404.
doi: 10.1029/96JD02964
[42]   Marticorena B, Chazette P, Bergametti G, et al. 2004. Mapping the aerodynamic roughness length of desert surfaces from the POLDER/ADEOS bi-directional reflectance product. International Journal of Remote Sensing, 25(3):603-626.
doi: 10.1080/0143116031000116976
[43]   Marticorena B, Kardous M, Bergametti G, et al. 2006. Surface and aerodynamic roughness in arid and semiarid areas and their relation to radar backscatter coefficient. Journal of Geophysical Research: Earth Surface, 111(F3), doi: 10.1029/2006JF000462.
[44]   Mazzoli A, Moriconi G. 2014. Particle size, size distribution and morphological evaluation of glass fiber reinforced plastic (GRP) industrial by-product. Micron, 67:169-178.
doi: S0968-4328(14)00151-6 pmid: 25195092
[45]   Mu H, Otani S, Shinoda M, et al. 2013. Long-term effects of livestock loss caused by dust storm on Mongolian inhabitants: a survey 1 year after the dust storm. Yonago Acta Medica, 56(1):39-42.
[46]   Natsagdorj L, Jugder D, Chung Y S. 2003. Analysis of dust storms observed in Mongolia during 1937-1999. Atmospheric Environment, 37(9-10):1401-1411.
doi: 10.1016/S1352-2310(02)01023-3
[47]   Onishi K, Otani S, Yoshida A, et al. 2015. Adverse health effects of Asian dust particles and heavy metals in Japan. Asia Pacific Journal of Public Health, 27(2): NP1719-NP1726.
[48]   Otsu N. 1979. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9(1):62-66.
doi: 10.1109/TSMC.1979.4310076
[49]   Raupach M R. 1992. Drag and drag partition on rough surfaces. Boundary-Layer Meteorology, 60(4):375-395.
doi: 10.1007/BF00155203
[50]   Raupach M R, Gillette D A, Leys J F. 1993. The effect of roughness elements on wind erosion threshold. Journal of Geophysical Research: Atmospheres, 98(D2):3023-3029.
doi: 10.1029/92JD01922
[51]   Schlichting H. 1936. Experimental investigation of the problem of surface roughness. In: National Advisory Committee for Aeronautics Collection. National Advisory Committee for Aeronautics, 1-34.
[52]   Shao Y, Raupach M R, Findlater P A. 1993. Effect of saltation bombardment on the entrainment of dust by wind. Journal of Geophysical Research: Atmospheres, 98(D7):12719-12726.
doi: 10.1029/93JD00396
[53]   Shao Y, Lu H. 2000. A simple expression for wind erosion threshold friction velocity. Journal of Geophysical Research: Atmospheres, 105(D17):22437-22443.
doi: 10.1029/2000JD900304
[54]   Shao Y. 2004. Simplification of a dust emission scheme and comparison with data. Journal of Geophysical Research: Atmospheres, 109(D10), doi: 10.1029/2003JD004372.
[55]   Shao Y. 2008. Physics and Modelling of Wind Erosion. Dordrecht: Springer, 18-20.
[56]   Shao Y, Ishizuka M, Mikami M, et al. 2011. Parameterization of size-resolved dust emission and validation with measurements. Journal of Geophysical Research: Atmospheres, 116(D8), doi: 10.1029/2010JD014527.
[57]   Shao Y, Nickling W, Bergametti G, et al. 2015. A tribute to Michael R. Raupach for contributions to aeolian fluid dynamics. Aeolian Research, 19:37-54.
doi: 10.1016/j.aeolia.2015.09.004
[58]   Tan L, Zhang W, Qu J, et al. 2013. Aeolian sand transport over gobi with different gravel coverages under limited sand supply: A mobile wind tunnel investigation. Aeolian Research, 11:67-74.
doi: 10.1016/j.aeolia.2013.10.003
[59]   Tan L, Zhang W, An Z, et al. 2019. The effect of roughness density of gobi beds on the entrainment of sediment by wind: A wind tunnel study. Journal of Wind Engineering and Industrial Aerodynamics, 190:183-189.
doi: 10.1016/j.jweia.2019.05.002
[60]   Udo K. 2009. Field measurement of seasonal wind-blown sand flux using high-frequency sampling instrumentation. Journal of Coastal Research, SI(56):148-152.
[61]   Wang X, Xia D, Wang T, et al. 2008. Dust sources in arid and semiarid China and southern Mongolia: Impacts of geomorphological setting and surface materials. Geomorphology, 97(3-4):583-600.
doi: 10.1016/j.geomorph.2007.09.006
[62]   Webb N P, Chappell A, LeGrand S L, et al. 2020. A note on the use of drag partition in aeolian transport models. Aeolian Research, 42:100560, doi: 10.1016/j.aeolia.2019.100560.
doi: 10.1016/j.aeolia.2019.100560
[63]   Wu C, Lin Z, Liu X. 2020. Global dust cycle and uncertainty in CMIP5 models. Atmospheric Chemistry and Physics Discussions, 2020: 1-52.
[64]   Wu J, Kurosaki Y, Shinoda M, et al. 2016. Regional characteristics of recent dust occurrence and its controlling factors in East Asia. SOLA, 12:187-191.
doi: 10.2151/sola.2016-038
[65]   Wu J, Kurosaki Y, Du C. 2020. Evaluation of climatic and anthropogenic impacts on dust erodibility: A case study in Xilingol Grassland, China. Sustainability, 12(2):629, doi: 10.3390/su12020629.
doi: 10.3390/su12020629
[66]   Xi X, Sokolik I N. 2015. Seasonal dynamics of threshold friction velocity and dust emission in Central Asia. Journal of Geophysical Research: Atmospheres, 120(4):1536-1564.
doi: 10.1002/jgrd.v120.4
[67]   Yan Y, Xu X, Xin X, et al. 2011. Effect of vegetation coverage on aeolian dust accumulation in a semiarid steppe of northern China. Catena, 87(3):351-356.
doi: 10.1016/j.catena.2011.07.002
[68]   Yang Y L, Victor S, Lu Q. 2002. Global Alarm: Dust and Sandstorms from the World's Drylands. New York: United Nations Pubns, 346.
[69]   Zhang J, Teng Z, Huang N, et al. 2016. Surface renewal as a significant mechanism for dust emission. Atmospheric Chemistry and Physics, 16(24):15517-15528.
doi: 10.5194/acp-16-15517-2016
[70]   Zhang K, Zhang W, Tan L, et al. 2015. Effects of gravel mulch on aeolian transport: a field wind tunnel simulation. Journal of Arid Land, 7(3):296-303.
doi: 10.1007/s40333-015-0121-1
[71]   Zhang W, Tan L, Zhang G, et al. 2014. Aeolian processes over gravel beds: Field wind tunnel simulation and its application atop the Mogao Grottoes, China. Aeolian Research, 15:335-344.
doi: 10.1016/j.aeolia.2014.07.001
[1] MENG Ruibing, MENG Zhongju, Brenton SHARRATT, ZHANG Jianguo, CAI Jiale, CHEN Xiaoyan. Threshold friction velocity influenced by soil particle size within the Columbia Plateau, northwestern United States[J]. Journal of Arid Land, 2024, 16(8): 1147-1162.
[2] YANG Zhiwei, CHEN Rensheng, LIU Zhangwen, ZHAO Yanni, LIU Yiwen, WU Wentong. Spatiotemporal variability of rain-on-snow events in the arid region of Northwest China[J]. Journal of Arid Land, 2024, 16(4): 483-499.
[3] Lobna MNIF FAKHFAKH, Mohamed CHAIEB. Effects of water stress on growth phenology photosynthesis and leaf water potential in Stipagrostis ciliata (Desf.) De Winter in North Africa[J]. Journal of Arid Land, 2023, 15(1): 77-90.
[4] WANG Kun, WANG Xiaoxia, FEI Hongyan, WAN Chuanyu, HAN Fengpeng. Changes in diversity, composition and assembly processes of soil microbial communities during Robinia pseudoacacia L. restoration on the Loess Plateau, China[J]. Journal of Arid Land, 2022, 14(5): 561-575.
[5] André L CARVALHO, Renato A ARAÚJO-NETO, Guilherme B LYRA, Carlos E P CERRI, Stoécio M F MAIA. Impact of rainfed and irrigated agriculture systems on soil carbon stock under different climate scenarios in the semi-arid region of Brazil[J]. Journal of Arid Land, 2022, 14(4): 359-373.
[6] Halimeh PIRI, Amir NASERIN, Ammar A ALBALASMEH. Interactive effects of deficit irrigation and vermicompost on yield, quality, and irrigation water use efficiency of greenhouse cucumber[J]. Journal of Arid Land, 2022, 14(11): 1274-1292.
[7] WU Jun, DENG Guoning, ZHOU Dongmei, ZHU Xiaoyan, MA Jing, CEN Guozhang, JIN Yinli, ZHANG Jun. Effects of climate change and land-use changes on spatiotemporal distributions of blue water and green water in Ningxia, Northwest China[J]. Journal of Arid Land, 2021, 13(7): 674-687.
[8] JIA Wuhui, YIN Lihe, ZHANG Maosheng, ZHANG Xinxin, ZHANG Jun, TANG Xiaoping, DONG Jiaqiu. Quantification of groundwater recharge and evapotranspiration along a semi-arid wetland transect using diurnal water table fluctuations[J]. Journal of Arid Land, 2021, 13(5): 455-469.
[9] LANG Man, LI Ping, WEI Wei. Gross nitrogen transformations and N2O emission sources in sandy loam and silt loam soils[J]. Journal of Arid Land, 2021, 13(5): 487-499.
[10] Mahsa MIRDASHTVAN, Mohsen MOHSENI SARAVI. Influence of non-stationarity and auto-correlation of climatic records on spatio-temporal trend and seasonality analysis in a region with prevailing arid and semi-arid climate, Iran[J]. Journal of Arid Land, 2020, 12(6): 964-983.
[11] FENG Jian, ZHAO Lingdi, ZHANG Yibo, SUN Lingxiao, YU Xiang, YU Yang. Can climate change influence agricultural GTFP in arid and semi-arid regions of Northwest China?[J]. Journal of Arid Land, 2020, 12(5): 837-853.
[12] CHEN Ditao, LIU Wenjiang, HUANG Farong, LI Qian, Friday UCHENNA-OCHEGE, LI Lanhai. Spatial-temporal characteristics and influencing factors of relative humidity in arid region of Northwest China during 1966-2017[J]. Journal of Arid Land, 2020, 12(3): 397-412.
[13] LYU Changhe, XU Zhiyuan. Crop production changes and the impact of Grain for Green program in the Loess Plateau of China[J]. Journal of Arid Land, 2020, 12(1): 18-28.
[14] HE Guohua, ZHAO Yong, WANG Jianhua, GAO Xuerui, HE Fan, LI Haihong, ZHAI Jiaqi, WANG Qingming, ZHU Yongnan. Attribution analysis based on Budyko hypothesis for land evapotranspiration change in the Loess Plateau, China[J]. Journal of Arid Land, 2019, 11(6): 939-953.
[15] Yaning CHEN, Baofu LI, Yuting FAN, Congjian SUN, Gonghuan FANG. Hydrological and water cycle processes of inland river basins in the arid region of Northwest China[J]. Journal of Arid Land, 2019, 11(2): 161-179.