Drift potential characteristics of Mu Us Sandy Land calculated with different data sources

doi:10.7522/j.issn.1000-694X.2022.00014

Journal of Desert Research ›› 2022, Vol. 42 ›› Issue (5): 54-62.DOI: 10.7522/j.issn.1000-694X.2022.00014

Previous Articles Next Articles

Drift potential characteristics of Mu Us Sandy Land calculated with different data sources

Lixia Gu(), Ping Lv(), Fang Ma, Guoxiang Chen, Zhun Liang, Mingjing Xu, Ying Yang

School of Geography and Tourism，Shaanxi Normal University，Xi'an 710119，China

Received:2021-12-12 Revised:2022-02-27 Online:2022-09-20 Published:2022-09-22
Contact: Ping Lv

Abstract

Abstract:

Wind is the dynamic basis for the development of wind erosion and aeolian geomorphology in arid and semi-arid areas. We usually use wind speed data to discuss the regional wind regime， but there are differences in the results when different wind speed data are selected to study the same regional wind regime. Taking the Mu Us Sandy Land as an example， the daily maximum wind speed and wind direction data from the China Meteorological Data Service Center （CMDC） and the daily observation wind speed and wind direction data from the US National Climatic Data Center （NCDC） were selected to analyze the sand-driving wind. The results show that：（1） The difference of average sand-driving wind speed is small， but the frequency of sand-driving wind is obviously higher in CMDC data source. （2） The annual sand-driving wind direction in the sandy land is mainly WNW， W and NW， but the composition of annual sand-driving wind direction， summer and autumn sand-driving wind direction in different regions is more complex in CMDC data source， and the frequency of primary and secondary sand-driving wind direction is higher in CMDC data source. （3） The sandy land as a whole belongs to low wind energy environment， medium wind direction variability， sharp double peak or wide single peak wind conditions， but the annual sand drift potential calculated by maximum wind speed is about 3.3 times that calculated by timing observation wind speed. Based on the above two sets of data sources， quantitative comparative analysis of wind regime and sand drift potential in Mu Us Sandy Land is made， which is a new attempt to study regional wind regime， in order to improve our understanding of wind speed differences provided by different data sources， and provide certain reference for the analysis of sand-driving wind in different regions in the future.

Key words: CMDC, NCDC, wind regime, drift potential, Mu Us Sandy Land

CLC Number:

P931.3

Lixia Gu, Ping Lv, Fang Ma, Guoxiang Chen, Zhun Liang, Mingjing Xu, Ying Yang. Drift potential characteristics of Mu Us Sandy Land calculated with different data sources[J]. Journal of Desert Research, 2022, 42(5): 54-62.

Figures/Tables 8

Fig.1 Geographical location of the Mu Us Sandy Land （modified from［7］）

Table 1 Comparison of annual wind conditions at each station in Mu Us Sandy Land

站名	年平均风速/（m·s^-1）		年平均起沙风速/（m·s^-1）		年起沙风频率/%
站名	CMDC	NCDC	CMDC	NCDC	CMDC	NCDC
鄂托克旗	2.5	2.6	8.1	7.0	46.5	9.1
盐池	2.1	2.2	7.6	6.8	31.1	5.0
榆林	2.7	2.9	7.9	6.9	40.8	6.4

Fig.2 Comparison of monthly variation of mean wind speed and mean sand-driving wind speed in Mu Us Sandy Land

Fig.3 Comparison of annual sand-driving wind roses at each station in Mu Us Sandy Land based on CMDC （A） and NCDC （B） data

Fig.4 Comparison of seasonal sand-driving wind roses at Etuoke Station based on CMDC （A） and NCDC（B） data

Fig.5 Comparison of seasonal sand-driving wind roses at Yanchi Station based on CMDC （A） and NCDC （B） data

Fig.6 Comparison of seasonal sand-driving wind roses at Yulin Station based on CMDC （A） and NCDC（B） data

Fig.7 Comparison of annual drift potential roses in Mu Us Sandy Land based on CMDC （A） and NCDC（B） data

References 45

1	董治宝，吕萍.70年来中国风沙地貌学的发展［J］.地理学报，2020，75（3）：509-527.
2	Azorin-Molina C， Vicente-Serrano S M， McVicar T R，et al.Homogenization and assessment of observed near-surface wind speed trends over Spain and Portugal，1961-2011［J］.Journal of Climate，2014，27（10）：3692-3712.
3	Wan H， Wang X L， Swail V R.Homogenization and trend analysis of Canadian near-surface wind speeds［J］.Journal of Climate，2010，23（5）：1209-1225.
4	吕萍，董治宝，张正偲，等.腾格里沙漠近地面层风、气温、湿度特征［J］.中国沙漠，2009，29（5）：977-981.
5	吴正.风沙地貌与治沙工程［M］.北京：科学出版社，2010：36-37.
6	庞营军，吴波，贾晓红，等.毛乌素沙地风况及输沙势特征［J］.中国沙漠，2019，39（1）：62-67.
7	Cui X J， Sun H， Dong Z B，et al.Temporal variation of the wind environment and its possible causes in the Mu Us Dunefield of Northern China，1960-2014［J］.Theoretical and Applied Climatology，2019，135：1017-1029.
8	Joseph A M， James B S， Lu H Y，et al.Limited change in dune mobility in response to a large decrease in wind power in semi-arid northern China since the 1970s［J］.Geomorphology，2008，102（3）：351-363.
9	刘彦随， Gao Jay.陕北长城沿线地区土地退化态势分析［J］.地理学报，2002，57（4）：443-450.
10	吴正.中国沙漠及其治理［M］.北京：科学出版社，2009：68-69.
11	王立新，刘华民，杨劼，等.毛乌素沙地气候变化及其对植被覆盖的影响［J］.自然资源学报，2010，25（12）：2030-2039.
12	白壮壮，崔建新.近2 000 a毛乌素沙地沙漠化及成因［J］.中国沙漠，2019，39（2）：177-185.
13	刘荔昀，鲁瑞洁，刘小槺.风成沉积物色度记录的毛乌素沙漠全新世以来气候变化［J］.中国沙漠，2019，39（6）：83-89.
14	王晓伟.毛乌素沙地东南缘晚第四纪风成沉积及其环境意义［D］.兰州：兰州大学，2020.
15	刘倩倩，杨小平.毛乌素沙地和库布齐沙漠风成沙粒度参数的空间变化及其成因［J］.中国沙漠，2020，40（5）：158-168.
16	哈斯，庄燕美，王蕾，等.毛乌素沙地南缘横向沙丘粒度分布及其对风向变化的响应［J］.地理科学进展，2006（6）：42-51.
17	陈国祥，董治宝，崔徐甲，等.毛乌素沙地中部风成沙的组成与微形态特征［J］.中国沙漠，2018，38（3）：473-483.
18	舒培仙，牛东风，李保生，等.毛乌素沙地现代沙丘沙的粒度特征及其意义［J］.中国沙漠，2016，36（1）：158-166.
19	韩雪莹，杨光，秦富仓，等.毛乌素沙地近30年沙漠化土地时空动态演变格局［J］.水土保持研究，2019，26（5）：144-150.
20	沈关东.毛乌素沙地东南缘沙漠化演变趋势及其与气候因子的相关性分析［D］.西安：西北大学，2017.
21	王静璞，王光镇，韩柳，等.毛乌素沙地不同固沙措施下沙丘的移动特征［J］.甘肃农业大学学报，2017，52（2）：54-60.
22	王静璞，刘连友，沈玲玲.基于Google Earth的毛乌素沙地新月形沙丘移动规律研究［J］.遥感技术与应用，2013，28（6）：1094-1100.
23	Zhang D， Liang P， Yang X，et al.The control of wind strength on the barchan to parabolic dune transition［J］.Earth Surface Processes And Landforms，2020，45（10）：2300-2313.
24	吴徽.近50年来毛乌素沙地的沙漠化过程研究［J］.中国沙漠，2001，21（2）：164-169.
25	王涛.中国沙漠与沙漠化［M］.石家庄：河北科学技术出版社，2003.
26	许明静，吕萍，肖南，等.毛乌素沙地西北部植被覆盖对沙丘移动的影响［J］.中国沙漠，2020，40（4）：71-80.
27	王训明，李晋昌，郎丽丽.中国干旱半干旱区灌丛沙丘的形成演化及其对环境变化的影响［M］.北京：科学出版社，2017：36-37.
28	刘海霞，李晋昌，苏志珠，等.毛乌素沙地西南缘灌丛沙丘沉积物的粒度和元素特征［J］.中国沙漠，2015，35（1）：24-31.
29	高国雄，吴卿，杨春霞.毛乌素沙地东南缘人工植被结构与生态功能研究［M］.郑州：黄河水利出版社，2010：48-49.
30	徐志伟，鹿化煜.毛乌素沙地风沙环境变化研究的理论和新认识［J］.地理学报，2021，76（9）：2203-2223.
31	朱震达，吴正，刘恕，等.中国沙漠概论［M］.北京：科学出版社，1974.
32	陈宗颜，董治宝，汪青春.青海共和盆地风况及风沙地貌［J］.中国沙漠，2018，38（3）：492-499.
33	马芳，吕萍.新月形沙丘与线性沙丘共存区域风况特征［J］.中国沙漠，2019，39（3）：98-106.
34	Fryberger S G.Dune forms and wind regime［M］//Mckee E D.A Study of Global Sand Seas.Washington，USA：US Government Printing Office，1979.
35	鲍锋，董治宝，张正偲.柴达木盆地风沙地貌区风况特征［J］.中国沙漠，2015，35（3）：549-554.
36	胡光印，董治宝，张正偲，等.若尔盖盆地起沙风风况与输沙势特征［J］.中国沙漠，2020，40（5）：20-24.
37	张正偲，董治宝，赵爱国.输沙势计算中的“时距”问题［J］.干旱区地理，2010，33（2）：177-182.
38	张正偲，董治宝，赵爱国，等.库姆塔格沙漠昼夜风向变化特征［J］.干旱区资源与环境，2010，24（8）：126-130.
39	田敏，钱广强，杨转玲，等.柴达木盆地东北部哈勒腾河流域风况特征及其对风沙地貌发育的影响［J］.中国沙漠，2021，41（1）：1-9.
40	王兆云，牛改红，柳本立.风沙活动强度3种估算指标对比及适用性分析［J］.中国沙漠，2021，41（3）：118-126.
41	俎瑞平，张克存，屈建军，等.塔克拉玛干沙漠地面风场特征及周边地区沙丘排列关系分析［J］.应用气象学报，2005，16（4）：468-475.
42	李红军，何清，杨青.近40 a新疆输沙势的分析［J］.中国沙漠，2004，24（6）：46-50.
43	李振山，陈广庭.塔克拉玛干沙漠起沙风况［J］.中国沙漠，1999，19（1）：44-46.
44	陈渭南，董治宝，杨佐涛，等.塔克拉玛干沙漠的起沙风速［J］.地理学报，1995（4）：360-367.
45	Yizhaq H Z， Xu Z W， Ashkenazy Y.The effect of wind speed averaging time on the calculation of sand drift potential New scaling laws［J］.Earth and Planetary Science Letters，2020，544：1-10.

[1]	Guangyu Hong, Xiaojiang Wang, Tieshan Liu, Hailong, Zhenting Wu, Huercha, Xiaowei Gao, Haifeng Yang, Zhuofan Li, Zihao Li, Siqin, Lejun Wang. Applicability of Hydrus-*1D Model in simulating the soil moisture in Hedysarum leave* in Mu Us Sandy Land， China** [J]. Journal of Desert Research, 2022, 42(6): 233-242.
[2]	Aibaidoula Gulayisaimu, Feng Zhang, Feng Wu, Shixin Wu, Jianghua Zheng, Tao Sun. Grain size characteristics of dune sands and spatial variation in the Tengger Desert [J]. Journal of Desert Research, 2022, 42(5): 133-145.
[3]	Xinying Liu, Ming Jin, Fan Yang, Yapeng Ma, Hui Liu, Xiaoyun Sun, Dunsheng Xia. A preliminary study of environmental changes since middle Holocene and its impacts on the evolution of civilization in the eastern Mu Us Sandy Land [J]. Journal of Desert Research, 2022, 42(5): 92-100.
[4]	Jingxue Feng, Zhanliang Ding, Li You, Guang Han. Wind regimes and drift potentials in the corridor of transverse dunefield in western Korqin Sandy Land [J]. Journal of Desert Research, 2022, 42(4): 110-119.
[5]	Wubin Jiang, Deguo Zhang, Xiaoping Yang. Response of dune morphology and grain-size characteristics to the change of wind regimes and vegetation cover [J]. Journal of Desert Research, 2022, 42(4): 120-129.
[6]	Yuyan Ren, Yufeng Zheng, Yandong Zhang, Haibing Wang, Shiqiang Wang, Jinjun He. Evaluation on development sustainability of kulun eco-economic circle in the Mu Us Sandy Land [J]. Journal of Desert Research, 2022, 42(4): 264-272.
[7]	Honglin Lian, Xueying Han, Yali Liu, Yuqing Han, Wenbin Yang, Wei Xiong. Study on spatiotemporal characteristics of atmospheric drought from 1981 to 2020 in the Mu Us Sandy Land of China based on SPEI index [J]. Journal of Desert Research, 2022, 42(4): 71-80.
[8]	Shuo Qiao, Haibing Wang, Hejun Zuo, Xiya Liu, Yueru Wu. Evolution of ecological service value and network pattern of Mu Us Sandy Land [J]. Journal of Desert Research, 2022, 42(3): 118-126.
[9]	Ming Yan, Yinghua Zhang, Li He, Weiming Cheng, Suiji Wang, Jiongxin Xu. Blocking effect of upper reaches of Wuding River on desertification [J]. Journal of Desert Research, 2022, 42(2): 62-68.
[10]	Hairong Liang, Tao Wang, Yu Yang, Wei Feng, Honglin Lian, Xuefeng Liu, Jiatao Li, Jia Liu. Comparison of deep soil recharge characteristics between Mu Us Sandy Land and Hunshandake Sandy Land [J]. Journal of Desert Research, 2022, 42(2): 69-76.
[11]	Xiaoqin Yuan, Shengquan Liu, Feng Ai, Zheng Zhang, Qiang Li, Jinyu Jiang, Changchun Shi. Wind erosion resistance of litter of Salix psammophila community in the southeast edge of Mu Us Sandy Land， China [J]. Journal of Desert Research, 2022, 42(1): 134-138.
[12]	Zhizhong Li, Jianhui Jin, Rui Liu, Xihao Xie, Xiaojun Zou, Yunqiang Ma, Dianjia Tan. Review and prospect of aeolian geomorphology research in Gurbantunggut Desert， China [J]. Journal of Desert Research, 2022, 42(1): 41-47.
[13]	Jiyan Li, Xuemin Gao, Zhibao Dong. The dataset of wind regime for yardang landforms in the Qaidam Basin [J]. Journal of Desert Research, 2021, 41(6): 265-268.
[14]	Lin Shi, Yuxing Zhao, Eerdun Hasi, Ping Zhang, Yingjun Xu, Zhuoran Wang. Changes of vegetation and soil nutrient on windward slope of dune under sand barrier environment in Mu Us Sandy Land [J]. Journal of Desert Research, 2021, 41(5): 140-146.
[15]	Boyu Gao, Bo Yang, Deguo Zhang. Extracting the sand dune crest lines from satellite images using U-Net deep convolutional neural network [J]. Journal of Desert Research, 2021, 41(5): 21-32.

Drift potential characteristics of Mu Us Sandy Land calculated with different data sources

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 45

Related Articles 15

Recommended Articles

Metrics

Comments