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Journal of Arid Land  2023, Vol. 15 Issue (10): 1174-1195    DOI: 10.1007/s40333-023-0066-8
Research article     
Wind regime features and their impacts on the middle reaches of the Yarlung Zangbo River on the Tibetan Plateau, China
ZHANG Yan1,2, ZHANG Zhengcai3,4,*(), MA Pengfei5, PAN Kaijia2,3, ZHA Duo6, CHEN Dingmei6, SHEN Caisheng7, LIANG Aimin4
1Institute of Atmosphere Physics, Chinese Academy of Sciences, Beijing 100029, China
2University of Chinese Academy of Sciences, Beijing 100083, China
3Key Laboratory of Desert and Desertification, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
4Shaanxi Normal University, Xi'an 710119, China
5Tibet Climate Center, Lhasa 850000, China
6Shannan Meteorological Bureau, Shannan 856000, China
7Policy Research Office of Party Committee of Tibet Autonomous Region, Lhasa 850000, China
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Abstract  

The wide valley of the Yarlung Zangbo River is one of the most intense areas in terms of aeolian activity on the Tibetan Plateau, China. In the past, the evaluation of the intensity of aeolian activity in the Quxu-Sangri section of the Yarlung Zangbo River Valley was mainly based on data from the old meteorological stations, especially in non-sandy areas. In 2020, six new meteorological stations, which are closest to the new meteorological stations, were built in the wind erosion source regions (i.e., sandy areas) in the Quxu-Sangri section. In this study, based on mathematical statistics and empirical orthogonal function (EOF) decomposition analysis, we compared the difference of the wind regime between new meteorological stations and old meteorological stations from December 2020 to November 2021, and discussed the reasons for the discrepancy. The results showed that sandy and non-sandy areas differed significantly regarding the mean velocity (8.3 (±0.3) versus 7.7 (±0.3) m/s, respectively), frequency (12.9% (±6.2%) versus 2.9% (±1.9%), respectively), and dominant direction (nearly east or west versus nearly north or south, respectively) of sand-driving winds, drift potential (168.1 (±77.3) versus 24.0 (±17.9) VU (where VU is the vector unit), respectively), resultant drift potential (92.3 (±78.5) versus 8.7 (±9.2) VU, respectively), and resultant drift direction (nearly westward or eastward versus nearly southward or northward, respectively). This indicated an obvious spatial variation in the wind regime between sandy and non-sandy areas and suggested that there exist problems when using wind velocity data from non-sandy areas to evaluate the wind regime in sandy areas. The wind regime between sandy and non-sandy areas differed due to the differences in topography, heat flows, and their coupling with underlying surface, thereby affecting the local atmospheric circulation. Affected by large-scale circulations (westerly jet and Indian monsoon systems), both sandy and non-sandy areas showed similar seasonal variations in their respective wind regime. These findings provide a credible reference for re-understanding the wind regime and scientific wind-sand control in the middle reaches of the Yarlung Zangbo River Valley.



Key wordswind regime      aeolian activity      sand-driving winds      drift potential      atmospheric circulation      Yarlung Zangbo River      Tibetan Plateau     
Received: 06 April 2023      Published: 31 October 2023
Corresponding Authors: *ZHANG Zhengcai (E-mail: zhangzhengcai@snnu.edu.cn)
Cite this article:

ZHANG Yan, ZHANG Zhengcai, MA Pengfei, PAN Kaijia, ZHA Duo, CHEN Dingmei, SHEN Caisheng, LIANG Aimin. Wind regime features and their impacts on the middle reaches of the Yarlung Zangbo River on the Tibetan Plateau, China. Journal of Arid Land, 2023, 15(10): 1174-1195.

URL:

http://jal.xjegi.com/10.1007/s40333-023-0066-8     OR     http://jal.xjegi.com/Y2023/V15/I10/1174

Site Station Ambient condition
SBR NMS Main-stream river valley; semi-fixed sandy land
OMS Tributary valley; grassland; 8.26 km from NMS
CG NMS Main-stream river valley; shifting sandy land
OMS Tributary valley; grassland; 10.90 km from NMS
AZ NMS Main-stream river valley; shifting sandy land
OMS Tributary valley; grassland and cultivated land; 6.21 km from NMS
SYS NMS Main-stream river valley; shifting sandy land
OMS Tributary valley; grassland and construction land for road; 6.32 km from NMS
DPZ NMS Main-stream river valley; shifting sandy land
OMS Tributary valley; grassland and building land; 6.32 km from NMS
SR NMS Main-stream river valley; shifting sandy land
OMS Tributary valley; grassland and woodland; 12.50 km from NMS
Table 1 Ambient conditions of all new meteorological stations and old meteorological stations at the six sites
Fig. 1 Overview of the Quxu-Sangri section of the Yarlung Zangbo River Valley and spatial distribution of new meteorological stations in sandy areas and old meteorological stations in non-sandy areas. SBR, CG, AZ, SYS, DPZ and SR represent the six sites, with each having a pair of new meteorological station and old meteorological station. The elevation data were downloaded from the website of https://search.asf.alaska.edu/, and land use type data were obtained from Ma et al. (2021b).
Spatial mode CVC (%) Eigenvalue
SBR CG AZ SYS DPZ SR
SA NSA SA NSA SA NSA SA NSA SA NSA SA NSA
Mode I 49 0.28 0.30 0.29 0.29 0.30 0.28 0.36 0.33 0.24 0.28 0.18 0.30
Mode II 21 0.12 0.17 0.29 -0.34 0.39 -0.32 0.19 -0.23 0.33 -0.34 0.29 -0.34
Mode III 11 -0.47 -0.27 -0.34 -0.12 -0.11 0.10 0.05 0.03 0.46 0.26 0.53 0.06
Table 2 Spatial modes and eigenvalues of their eigenvectors for regional wind velocity at the six sites in sandy and non-sandy areas
Fig. 2 Time coefficient anomaly of spatial Mode I (a), Mode II (b) and Mode III (c) for wind velocity in the Quxu-Sangri section of the Yarlung Zangbo River Valley from December 2020 to November 2021
Fig. 3 Comparison of the annual average velocity and frequency of sand-driving winds at the six sites in sandy and non-sandy areas
Site Winter Spring
$\overline{{{u}_{sdw}}}$(m/s) Fsdw (%) θsdw (°) $\overline{{{u}_{sdw}}}$(m/s) Fsdw (%) θsdw (°)
SA NSA SA NSA SA NSA SA NSA SA NSA SA NSA
SBR 7.8 7.6 1.3 1.2 269 258 7.9 8.0 2.8 2.7 284 180
CG 9.1 7.4 1.7 0.3 266 166 8.1 7.2 2.1 0.4 122 175
AZ 9.0 8.3 3.0 1.3 275 149 8.1 7.8 4.7 1.5 100 168
SYS 9.5 8.0 2.8 0.8 261 218 8.3 7.9 3.8 1.1 225 17
DPZ 8.3 7.7 5.7 0.6 110 150 7.7 7.4 7.1 1.0 104 150
SR 8.9 6.9 4.8 0.3 82 200 8.5 7.2 5.3 0.6 78 229
Site Summer Autumn
$\overline{{{u}_{sdw}}}$(m/s) Fsdw (%) θsdw (°) $\overline{{{u}_{sdw}}}$(m/s) Fsdw (%) θsdw (°)
SA NSA SA NSA SA NSA SA NSA SA NSA SA NSA
SBR 8.4 7.9 1.5 2.1 135 179 7.8 7.4 0.7 0.5 268 89
CG 7.9 8.3 1.2 0.1 120 - 8.6 7.9 0.8 0.0 265 -
AZ 7.8 7.9 3.1 0.9 104 352 8.0 7.8 2.1 0.7 277 158
SYS 8.0 7.8 2.3 0.4 100 18 8.6 8.2 1.6 0.4 257 222
DPZ 7.6 8.0 4.8 0.3 102 23 7.6 7.4 5.0 0.3 108 9
SR 8.5 7.2 4.8 0.1 75 225 8.7 6.7 4.1 0.0 73 -
Table 3 Comparison of seasonal average wind velocity ($\overline{{{u}_{sdw}}}$), wind frequency (Fsdw) and dominant wind direction (θsdw) of sand-driving winds at the six sites in sandy and non-sandy areas
Fig. 4 Seasonal and annual direction distributions of sand-driving winds at the six sites in sandy and non-sandy areas. The distance between the graphed data and the black circle indicates the probability density of wind direction. Values with red and blue fonts indicate the dominant wind direction at new meteorological stations and old meteorological stations, respectively. The red straight lines and the blue dashed lines indicate the position of the dominant wind direction corresponding to the maximum probability density of new meteorological stations and old meteorological stations, respectively.
Areas Site Winter Spring Summer Autumn
w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°)
Sandy areas SBR 0.76 269 23 0.40 284 30 0.45 135 27 0.58 268 38
CG 0.80 266 20 0.35 122 21 0.61 120 18 0.82 265 17
AZ 0.61 275 23 0.57 100 18 0.83 104 20 0.59 108 25
SYS 0.76 261 21 0.48 53 26 0.49 100 23 0.67 257 20
DPZ 0.79 110 25 0.70 104 30 0.78 102 22 0.45 108 35
SR 0.67 82 14 0.71 78 15 0.89 75 16 0.82 73 15
Non-sandy areas SBR 0.54 258 28 0.57 180 20 0.43 179 19 0.5 91 21
CG 0.53 166 27 0.56 33 21 0.85 36 19 0.95 30 18
AZ 0.70 149 31 0.56 168 23 0.51 352 25 0.55 3 24
SYS 0.40 221 22 0.40 16 20 0.54 17 17 0.41 222 20
DPZ 0.44 162 35 0.61 150 33 0.55 33 26 0.47 0 22
SR 0.65 218 27 0.65 231 24 0.63 231 20 0.51 222 30
Table 4 Dominant direction of sand-driving winds at the six sites in sandy and non-sandy areas
Fig. 5 Comparison of annual sand transport parameters between sandy and non-sandy areas at the six sites. DP, drift potential; RDP, resultant drift potential; RDD, resultant drift direction; RDP/DP, directional variability. Red and blue arrows represent RDD in sandy and non-sandy areas, respectively; red and blue solid circles represent new meteorological stations and old meteorological stations, respectively; the line segments without arrows on the circles represent DP in 16 directions.
Site Winter Spring
DP (VU) RDP (VU) RDD (°) DP (VU) RDP (VU) RDD (°)
SA NSA SA NSA SA NSA SA NSA SA NSA SA NSA
SBR 10.1 6.7 5.9 3.3 97 31 24.4 26.4 2.9 18.2 172 354
CG 43.5 1.4 39.9 0.9 83 225 22.5 1.1 12.5 0.7 33 228
AZ 63.5 16.4 24.7 2.8 88 266 49.6 12.7 11.2 4.2 287 169
SYS 88.5 8.2 73.5 2.1 86 40 48.1 10.7 8.9 7.5 63 198
DPZ 75.8 3.9 43.1 2.4 289 199 45.5 4.6 30.3 1.1 288 257
SR 101.9 0.4 77.9 0.2 255 28 78.5 2.1 57.1 0.3 260 148
Site Summer Autumn
DP (VU) RDP (VU) RDD (°) DP (VU) RDP (VU) RDD (°)
SA NSA SA NSA SA NSA SA NSA SA NSA SA NSA
SBR 21.0 17.8 7.7 10.1 237 318 5.2 2.4 2.3 1.4 124 294
CG 10.7 0.8 4.4 0.7 3 212 15.1 0.3 14.4 0.3 77 209
AZ 27.4 9.1 19.0 4.0 280 173 22.5 5.6 11.4 1.4 88 311
SYS 24.4 3.4 9.8 2.0 278 177 40.0 4.8 25.0 2.5 87 85
DPZ 28.9 3.0 19.7 1.2 277 162 28.8 1.5 18.2 0.7 293 112
SR 72.4 0.5 66.6 0.1 255 212 69.3 0.1 59.5 0.1 258 172
Table 5 Comparison of seasonal drift potential (DP), resultant drift potential (RDP) and resultant drift direction (RDD) between sandy and non-sandy areas at the six sites
Fig. 6 Diurnal variations of wind direction at the six sites in sandy areas in January. (a), SBR; (b), CG; (c), AZ; (d), SYS; (e), DPZ; (f), SR.
Fig. 7 Diurnal variation curves of wind velocity at the six sites in sandy areas (a) and non-sandy areas (b). Values are means for all months combined.
Site Annual Winter Spring Summer Autumn
w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°)
SBR 0.46 274 24 0.76 269 23 0.40 284 30 0.45 135 27 0.58 268 38
0.35 112 26 0.24 45 22 0.26 124 27 0.31 74 10 0.22 336 16
0.11 70 17 - - - 0.25 63 16 0.16 338 22 0.21 79 21
0.08 336 20 - - - 0.09 336 13 0.09 276 17 - - -
CG 0.51 265 25 0.80 266 20 0.35 122 21 0.61 120 18 0.82 265 17
0.30 121 26 0.11 116 21 0.33 196 23 0.21 266 19 0.13 120 18
0.19 197 24 0.09 201 24 0.31 264 19 0.18 193 18 - - -
AZ 0.60 102 20 0.61 275 23 0.57 100 18 0.83 104 20 0.59 108 25
0.41 271 18 0.39 102 21 0.43 271 32 0.17 269 16 0.41 277 19
SYS 0.55 265 25 0.76 261 21 0.48 53 18 0.49 100 23 0.67 257 20
0.24 56 27 0.24 58 22 0.44 225 30 0.29 52 40 0.18 107 17
0.21 101 28 - - - 0.09 91 26 0.23 258 31 0.15 53 24
DPZ 0.82 108 27 0.79 110 25 0.70 104 30 0.78 102 22 0.45 108 35
0.12 277 15 0.21 277 17 0.27 277 16 0.12 279 14 0.32 275 20
SR 0.76 79 15 0.67 82 14 0.71 78 15 0.89 75 16 0.82 73 15
0.22 255 22 0.33 255 21 0.29 193 30 - - - 0.18 253 24
Table S1 Dominant wind direction throughout the year and in different seasons in sandy areas
Site Annual Winter Spring Summer Autumn
w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°) w θ (°) σ (°)
SBR 0.45 181 20 0.54 258 28 0.57 180 20 0.43 179 19 0.50 89 21
0.31 89 28 0.29 188 27 0.25 86 25 0.34 89 20 0.28 179 18
0.24 255 27 0.18 91 24 0.18 269 23 - - - 0.22 273 27
CG 0.56 32 19 0.53 166 27 0.56 33 21 0.85 36 19 1.00 30 18
0.44 166 25 0.47 37 26 0.44 175 25 0.15 92 15 - - -
AZ 0.58 348 28 0.70 149 31 0.56 168 23 0.51 352 25 0.55 2 24
0.42 156 31 0.30 347 17 0.43 353 24 0.49 158 35 0.45 157 30
SYS 0.43 222 20 0.40 218 22 0.40 17 20 0.54 18 17 0.41 222 20
0.31 16 16 0.26 20 19 0.37 225 18 - - - 0.30 12 24
- - - - - - 0.23 61 20 - - - - - -
DPZ 0.51 151 28 0.44 151 35 0.61 150 33 0.55 23 26 0.47 0 22
0.43 15 31 0.43 12 26 0.34 15 19 0.27 147 27 0.37 165 28
SR 0.64 222 20 0.65 218 27 0.65 229 24 0.63 225 20 0.51 222 35
0.35 28 32 0.26 28 20 0.35 32 27 0.18 43 18 0.45 358 27
Table S2 Dominant wind direction throughout the year and in different seasons in non-sandy areas
Fig. S1 Diurnal variations of wind direction at the six sites in sandy areas in April (a1-a6), July (b1-b6) and October (c1-c6)
Fig. S2 Diurnal variations of wind direction at the six sites in non-sandy areas in January (a1-a6), April (b1-b6), July (c1-c6) and October (d1-d6)
Fig. S3 Diurnal variations of wind velocity in sandy areas and non-sandy areas in winter (a and b), spring (c and d), summer (e and f) and autumn (g and h)
[1]   Bagnold R A. 1941. The Physics of Blown Sand and Desert Dunes. London: Methuen, 267-277.
[2]   Baumbach G, Vogt U. 1999. Experimental determination of the effect of mountain-valley breeze circulation on air pollution in the vicinity of Freiburg. Atmosphere Environment, 33(24-25): 4019-4027.
doi: 10.1016/S1352-2310(99)00143-0
[3]   Bei N F, Zhao L N, Wu J R, et al. 2018. Impacts of sea-land and mountain-valley circulations on the air pollution in Beijing-Tianjin-Hebei (BTH): A case study. Environment Pollution, 234: 429-438.
doi: 10.1016/j.envpol.2017.11.066
[4]   Ben Y, Mei Y D, Chen Y M, et al. 2020. Inter- and intra-annual wind speed variabilities in wide valley regions of the middle reaches of the Yarlung Tsangpo River, China. Scientific Report, 10: 12657, doi: 10.1038/s41598-020-69392-2.
[5]   Benaglia T, Chauveau D, Hunter D R, et al. 2009. Mixtools: An R package for analyzing finite mixture models. Journal of Statistical Software, 32(6): 1-29.
[6]   Dong Z B, Zhang Z C, Qian G Q, et al. 2013. Geomorphology of star dunes in the southern Kumtagh Desert, China: control factors and formation. Environmental Earth Sciences, 69: 267-277.
doi: 10.1007/s12665-012-1954-y
[7]   Dong Z B, Hu G Y, Qian G Q, et al. 2017. High-altitude aeolian research on the Tibetan Plateau. Reviews of Geophysics, 55(4): 864-901.
doi: 10.1002/rog.v55.4
[8]   Fan W W, Ma W Q, Zheng Y, et al. 2018. Long-term variation of surface heating over the Qinghai-Tibetan Plateau linked to the westerly jet. Plateau Meteorology, 37(3): 591-601. (in Chinese)
doi: 10.7522/j.issn.1000-0534.2017.00062
[9]   Fryberger G S, Dean G. 1979. Dune forms and wind regime. In: McKee E D. A Study of Global Sand Seas. Washington: US Government Printing Office, 159-163.
[10]   Gao X M, Dong Z B, Duan Z H, et al. 2019. Wind regime for long-ridge yardangs in the Qaidam Basin, Northwest China. Journal of Arid Land, 11(5): 701-712.
doi: 10.1007/s40333-019-0108-4
[11]   Gevorgyan A. 2017. Summertime wind climate in Yerevan: valley wind systems. Climate Dynamic, 48: 1827-1840.
doi: 10.1007/s00382-016-3175-7
[12]   He P L, Zhang J, Herrmann H J, et al. 2022. Large-eddy simulation of wind-blown sand under unstable atmospheric boundary layer. Science Bulletin, 67(14): 1421-1424.
doi: 10.1016/j.scib.2022.05.011 pmid: 36546183
[13]   Hefflin B J, Jalaudin B, McClure E, et al. 1994. Surveillance for dust storms and respiratory diseases in Washington State, 1991. Archives of Environmental Health, 49(3): 170-174.
pmid: 8185387
[14]   Huang J P, Yu H P, Guan X D, et al. 2016. Accelerated dryland expansion under climate change. Nature Climate Change, 6: 166-174.
doi: 10.1038/NCLIMATE2837
[15]   Kok J F, Parteli E J R, Michaels T I, et al. 2012. The physics of wind-blown sand and dust. Reports on Progress in Physics, 75(10): 106901, doi: 10.1088/0034-4885/75/10/106901.
[16]   Li C J, Wang Y D, Lei J Q, et al. 2021a. Damage by wind-blown sand and its control measures along the Taklimakan Desert Highway in China. Journal of Arid land, 13(1): 98-106.
doi: 10.1007/s40333-020-0071-0
[17]   Li H D, Shen W S, Zou C X, et al. 2012. Soil nutrients content and grain size fraction of aeolian sandy land in the Shannan Wide Valley of the Yarlung Zangbo River, China. Acta Ecologica Sinica, 32(16): 4981-4992. (in Chinese)
doi: 10.5846/stxb
[18]   Li P J, Zuo D P, Xu Z X, et al. 2021b. Dynamic changes of land use/cover and landscape pattern in a typical alpine river basin of the Qinghai-Tibet Plateau, China. Land Degradation and Development, 32(15): 4327-4339.
doi: 10.1002/ldr.v32.15
[19]   Li S, Yang P, Dong Y X, et al. 2010. Sandy Desertification and Its Control in Tibet. Beijing: Science Press, 146-156. (in Chinese)
[20]   Ling Z Y, Jin J H, Wu D, et al. 2019. Aeolian sediments and their paleoenvironmental implication in the Yarlung Zangbo catchment (southern Tibet, China) since MIS3. Acta Geographica Sinica, 74(11): 2385-2400. (in Chinese)
doi: 10.11821/dlxb201911014
[21]   Ling Z Y, Li J S, Jin J H, et al. 2021. Geochemical characteristics and provenance of aeolian sediments in the Yarlung Tsangpo valley, Southern Tibetan Plateau. Environment Earth Sciences, 80: 623, doi: 10.1007/s12665-021-09928-5.
[22]   Liu Y, Wang Y S, Shen T. 2019a. Spatial distribution and formation mechanism of aeolian sand in the middle reaches of the Yarlung Zangbo River. Journal of Mountain Science, 16(9): 1987-2000.
doi: 10.1007/s11629-019-5509-5
[23]   Liu Z Y, Dong Z B, Zhang Z C, et al. 2019b. Spatial and temporal variation of the near-surface wind regimes in the Taklimakan Desert, Northwest China. Theoretical and Applied Climatology, 138: 433-447.
doi: 10.1007/s00704-019-02824-w
[24]   Lü P, Dong Z B. 2008. The dependency of sand transport rate by wind on the atmospheric stability: a numerical simulation. Geomorphology, 99(1-4): 296-301.
doi: 10.1016/j.geomorph.2007.11.007
[25]   Lü P, Narteau C, Dong Z B, et al. 2014. Emergence of oblique dunes in a landscape-scale experiment. Nature Geoscience, 7: 99-103.
doi: 10.1038/ngeo2047
[26]   Luo J, Xin L J, Liu F G, et al. 2022. Study of the intensity and driving factors of land use/cover change in the Yarlung Zangbo River, Nyang Qu River, and Lhasa River region, Qinghai-Tibet Plateau of China. Journal of Arid Land, 14(4): 411-425.
doi: 10.1007/s40333-022-0093-x
[27]   Ma P F, Gao J J, Zha D, et al. 2021a. Analysis of soil nutrients in the aeolian disaster region along middle reaches of Yarlung Zangbo River. Journal of Arid Land Resources and Environment, 35(6): 96-101. (in Chinese)
[28]   Ma P F, Lunzhu Q F, Zhang Y, et al. 2021b. Sand supplement characteristics indicated by the area of river inland, flood plain in the riverbed of the Yarlung Zangbo River. Journal of Desert Research, 41(3): 25-33. (in Chinese)
[29]   Ma P F, Zhang Z C, Lunzhu Q P, et al. 2021c. Analysis on the sand transport wind power conditions and suggestions on the sand disaster preventions in the middle reaches of Yarlung Zangbo River, China. Journal of Desert Research, 41(1): 10-18. (in Chinese)
[30]   Meng N, Wang N A, Zhao L Q, et al. 2022. Wind regimes and associated sand dune types in the hinterland of the Badain Jaran Desert, China. Journal of Arid Land, 14(5): 473-489.
doi: 10.1007/s40333-022-0063-3
[31]   Ngo T T, Letchford C W. 2009. Experimental study of topographic effects on gust wind speed. Journal of Wind Engineering and Industrial Aerodynamics, 97(9-10): 426-438.
doi: 10.1016/j.jweia.2009.06.013
[32]   Pye K, Tsoar H. 2009. Aeolian Sand and Sand Dunes. London: Unwin Hyman, 56-60.
[33]   Shan X, Zhou S W, Wang M R, et al. 2019. Influence of atmospheric heat anomaly over the Tibetan Plateau on the westerly jet. Journal of the Meteorological Sciences, 39(2): 206-213. (in Chinese)
[34]   Shao Y P. 2008. Physics and Modelling of Wind Erosion. New York: Springer Science & Business Media, 26-27.
[35]   Shen W S, Li H D, Sun M, et al. 2012. Dynamics of aeolian sandy land in the Yarlung Zangbo River basin of Tibet, China from 1975 to 2008. Global and Planetary Change, 86-87: 37-44.
doi: 10.1016/j.gloplacha.2012.01.012
[36]   Stout J E. 2015. Diurnal patterns of blowing dust on the Llano Estacado. Journal of Arid Environments, 122: 85-92.
doi: 10.1016/j.jaridenv.2015.06.013
[37]   Stull R B. 1988. An Introduction to Boundary Layer Meteorology. Dordrecht: Kluwer Academic Publisher, 26-27.
[38]   Walker A S, Olsen J W, Bagen. 1987. The Badain Jaran desert: remote sensing investigations. Geographical Journal, 153(2): 205-210.
[39]   Wang R X, Liu B, Li H R, et al. 2017. Variation of strong dust storm events in Northern China during 1978-2007. Atmosphere Research, 183: 166-172.
[40]   Wei F Y. 2007. Climatological Statistical Diagnosis and Prediction Technology. Beijing: Meteorological Press, 116-118. (in Chinese)
[41]   Yang J H, Xia D S, Wang S Y, et al. 2020. Near-surface wind environment in the Yarlung Zangbo River basin, southern Tibetan Plateau. Journal of Arid Land, 12(6): 917-936.
doi: 10.1007/s40333-020-0104-8
[42]   Yang X L, Li Y Y, Chen J, et al. 2022. Transmission of rare strong dust and its weather process continuous characteristics in Hexi Corridor. Arid Land Geography, 45(5): 1415-1425. (in Chinese)
[43]   Yao T D, Piao S L, Shen M G, et al. 2017. Chained impacts on modern environment of interaction between westerlies and Indian Monsoon on Tibetan Plateau. Bulletin of Chinese Academy of Sciences, 32(9): 976-984. (in Chinese)
[44]   Zhang G F, Azorin-Molia C, Shi P J, et al. 2019. Impact of near-surface wind speed variability on wind erosion in the eastern agro-pastoral transitional zone of Northern China, 1982-2016. Agricultural and Forest Meteorology, 271: 102-115.
doi: 10.1016/j.agrformet.2019.02.039
[45]   Zhang H Z, Zhou K S, Duojie S Z, et al. 2018. Analysis of spatiotemporal variation characteristic of wind-sand days in the Yarlung Zangbo River basin during 1981-2016. Journal of Arid Land Resources and Environment, 32(12): 131-136. (in Chinese)
[46]   Zhang Y, Ma P F, Zeng L, et al. 2021. Study on silt and clay provenance in the Yarlung Zangbo River middle reaches using sediment physicochemical characteristics. Journal of Desert Research, 41(3): 92-100. (in Chinese)
doi: 10.7522/j.issn.1000-694X.2021.00024
[47]   Zhang Z C, Dong Z B, Wen Q, et al. 2014. Wind regimes and aeolian geomorphology in the western and southwestern Tengger Desert, NW China. Geological Journal, 50(6): 707-719.
doi: 10.1002/gj.2586
[48]   Zhang Z C, Dong Z B, Li C X. 2015. Wind regime and sand transport in China's Badain Jaran Desert. Aeolian Research, 17: 1-13.
doi: 10.1016/j.aeolia.2015.01.004
[49]   Zhang Z C, Zhang Y, Ma P F, et al. 2022a. Aerodynamic parameters of typical underlying surfaces in an aeolian region in the middle reaches of the Yarlung Zangbo River. Arid Zone Research, 39(04): 997-1005. (in Chinese)
[50]   Zhang Z C, Zhang Y, Ma P F, et al. 2022b. Aeolian sediment transport rates in the middle reaches of the Yarlung Zangbo River, Tibet Plateau. Science of the Total Environment, 826: 154238, doi: 10.1016/j.scitotenv.2022.154238.
[51]   Zhao D, Chen S Y, Chen Y. 2022. Comparative analysis of two typical dust storm processes over East Asia. Journal of Lanzhou University (Natural Science), 58(3): 313-322. (in Chinese)
[52]   Zhou C, Yin J Q, Liu Y B. 2019. Effects of wind and rain on the motion of the high-voltage conductor in a simplified valley terrain. Electric Power Systems Research, 173: 153-163.
doi: 10.1016/j.epsr.2019.04.019
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