塔里木盆地风沙灾害强度和频次的时空分布特征

doi:10.12118/j.issn.1000–6060.2021.06.08

干旱区地理 ›› 2021, Vol. 44 ›› Issue (6): 1590-1600.doi: 10.12118/j.issn.1000–6060.2021.06.08

塔里木盆地风沙灾害强度和频次的时空分布特征

王旭¹(),王昀²,陈宝欣³,王秀琴⁴,李斌¹()

1. 新疆维吾尔自治区人工影响天气办公室,新疆乌鲁木齐 830002
2. 兰州大学大气科学学院,甘肃干旱气候变化与减灾重点实验室,甘肃兰州 730000
3. 澳门理工学院人文及社会科学高等学校,澳门 999078
4. 新疆维吾尔自治区气象信息中心,新疆乌鲁木齐 830002

收稿日期:2021-01-04 修回日期:2021-08-04 出版日期:2021-11-25 发布日期:2021-12-03
通讯作者: 李斌
作者简介:王旭（1964-）,男,研究员,主要从事灾害性天气形成机理及人工影响天气研究. E-mail: wangxu2323@vip.163.com
基金资助:
新疆人工影响天气基金课题(RYB202001)

Spatial and temporal distribution characteristics of intensity and frequency of wind-sand disasters in Tarim Basin

WANG Xu¹(),WANG Yun²,CHEN Baoxin³,WANG Xiuqin⁴,LI Bin¹()

1. Weather Modification Office of Xinjiang Uygur Autonomous Region, Urumqi 830002, Xinjiang, China
2. Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, College of Atmospheric Science of Lanzhou University, Lanzhou 730000, Gansu, China
3. School of Humanities and Social Sciences, Macao Polytechnic Institute, Macao 999078, China
4. Meteorological Information Center of Xinjiang Uygur Autonomous Region, Urumqi 830002, Xinjiang, China

Received:2021-01-04 Revised:2021-08-04 Online:2021-11-25 Published:2021-12-03
Contact: Bin LI

摘要/Abstract

摘要：

风沙灾害是造成塔里木盆地农牧业生产严重损害的一种气象灾害。利用1990—2019年塔里木盆地42个县（市）出现的1028次风沙灾害事件,以死亡人数、倒塌房屋数、倒塌棚圈数、损坏大棚数、牲畜死亡数量、农作物受灾面积作为6大灾情要素,采用比值权重和无量纲化线性组合方法,构建能综合表达灾害事件强度的灾损指数,进而利用百分位数法将灾害事件的强度定量划分为一般（1级）、较重（2级）、严重（3级）和特重（4级）4个等级,基于灾害出现次数和灾损指数,分析盆地风沙灾害的时空分布特征。结果表明：盆地风沙灾害春季出现最多、强度最重,且集中在4—5月,盆地北部1~4级出现次数和强度明显大于盆地其他区域,盆地北部是风沙灾害的多发区和重灾区。1990—2019年盆地风沙灾害年出现次数呈显著的线性增加趋势,但年灾害强度围绕气候平均值上下震荡。1级年出现次数和年灾害强度均呈显著的线性增加趋势,而2~4级年出现次数和年灾害强度围绕气候平均值上下震荡。通过创建楼兰指数可从动力气候学角度解释盆地风沙灾害年出现次数长期变化的动力机制。随着盆地东部与西部气压差（楼兰指数）的不断加大,引发盆地4月和5月逐小时10 min平均风速≥6.0 m·s^-1出现次数逐年增多,加之盆地绿洲规模的逐渐扩大,导致盆地风沙灾害年出现次数不断增加。研究结果可为塔里木盆地风沙灾害预报预警和防范提供科学依据。

关键词: 风沙灾害, 灾损指数, 强度和频次, 时空分布, 楼兰指数, 塔里木盆地

Abstract:

Sandstorm is a common meteorological disaster that causes serious damage to agricultural production and animal husbandry in the Tarim Basin, Xinjiang, China. Based on the disaster data acquired from the 1028 wind-sand disasters that occurred in 42 counties (cities) in the Tarim Basin from 1990 to 2019, six factors were selected as major disaster elements, namely, death toll, number of collapsed houses, collapsed shed circles, damaged sheds, livestock deaths, and affected areas. The disaster damage index could be integrated to express the intensity of disaster events using the method of ratio scale weighting and the dimensionless approach of linear combination. The intensity of disaster events was quantitatively divided into four levels using the percentile method: general (level 1), heavy (level 2), large (level 3), and extremely large (level 4). The temporal and spatial distribution characteristics of wind-sand disasters in the basin were analyzed in terms of the frequency of occurrence and the disaster damage index. Results showed that the wind-sand disaster hit the basin with the highest frequency and intensity in spring, especially in April and May. The frequency and intensity in the north Tarim Basin were obviously higher than those in other areas in the basin, making it the most frequently and hardest hit area of wind-sand disasters. During 1990—2019, the annual frequency of occurrence of wind-sand disasters in the basin conside-rably increased linearly, but the intensity fluctuated around the climatic average. The annual occurrence and intensity of wind-sand disaster in level 1 also showed a considerable linear increase, whereas level 2-4 varied around the climatic average. The established Loulan index, which is defined as the pressure difference between the east and west parts of the basin, could explain the dynamic mechanism of long-term changes in the frequency of occurrence of wind-sand disasters in the basin based on dynamic climatology. As this index increased during 1990—2019, the occurrence of an average wind speed of more than 6.0 m·s^-1 per hour in the basin from April to May increased per year. The scale of the basin oasis gradually expanded, resulting in the yearly increasing occurrence of wind-sand disaster in the basin. Thus, this study could provide a scientific basis for the prevention of wind-sand disasters in the Tarim Basin.

Key words: wind-sand disaster, disaster index, intensity and frequency, temporal and spatial distribution, Loulan index, Tarim Basin

王旭,王昀,陈宝欣,王秀琴,李斌. 塔里木盆地风沙灾害强度和频次的时空分布特征[J]. 干旱区地理, 2021, 44(6): 1590-1600.

WANG Xu,WANG Yun,CHEN Baoxin,WANG Xiuqin,LI Bin. Spatial and temporal distribution characteristics of intensity and frequency of wind-sand disasters in Tarim Basin[J]. Arid Land Geography, 2021, 44(6): 1590-1600.

图/表 13

图1

表1

表2

表3

图2

表4

表5

图3

图4

图5

图6

图7

图8

参考文献 37

[1]	IPCC. Climate change 2013: The physical science basis[M]. Cambridge: Cambridge University Press, 2013.
[2]	Dobson A P, Bradshaw A D, Baker A J M. Hopes for the future: Restoration ecology and conservation biology[J]. Science, 1997, 277(5325):515-522. doi: 10.1126/science.277.5325.515
[3]	魏秀菊, 王应宽, 王柳, 等. 跟踪学科前沿, 引导学科发展——《农业工程学报》的发展探索[J]. 农业工程学报, 2006, 22(3):171-175.
	[ Wei Xiuju, Wang Yingkuan, Wang Liu, et al. Following the frontier and leading the development of agricultural engineering discipline: Exploring the development of the Transactions of the CSAE[J]. Transactions of the Chinese Society of Agricultural Engineering, 2006, 22(3):171-175. ]
[4]	Cao S X. Why large-scale afforestation efforts in China have failed to solve the desertification problem[J]. Environmental Science & Technology, 2008, 42:1826-1831. doi: 10.1021/es0870597
[5]	魏秀菊, 胡振琪, 何蔓. 土地整理可能引发的生态环境问题及宏观管理对策[J]. 农业工程学报, 2005, 21(增刊1):127-130.
	[ Wei Xiuju, Hu Zhenqi, He Man. Potential problems of ecological environment resulted from land rehabilitation and their macroscopic management countermeasures[J]. Transactions of the Chinese Society of Agricultural Engineering, 2005, 21(Suppl. 1):127-130. ]
[6]	张鹏, 李宁. 我国自然灾害风险分级方法的标准化[J]. 灾害学, 2014, 29(2):60-64.
	[ Zhang Peng, Li Ning. The standardization of natural disasters risk grading methods in China[J]. Journal of Catastrophology, 2014, 29(2):60-64. ]
[7]	王涛, 陈广庭. 西部地标·中国的沙漠戈壁[M]. 上海: 上海科学技术文献出版社, 2008: 28-31.
	[ Wang Tao, Chen Guangting. Western landmark: The desert and gobi of China[M]. Shanghai: Shanghai Science and Technology Literature Publishing House, 2008: 28-31. ]
[8]	秦越, 徐翔宇, 许凯, 等. 农业干旱灾害风险模糊评价体系及其应用[J]. 农业工程学报, 2013, 29(10):83-91.
	[ Qin Yue, Xu Xiangyu, Xu Kai, et al. Fuzzy evaluation system of agriculture drought disaster risk and its application[J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(10):83-91. ]
[9]	范一大, 史培军, 周俊华, 等. 近50年来中国沙尘暴变化趋势分析[J]. 自然灾害学报, 2005, 14(3):22-26.
	[ Fan Yida, Shi Peijun, Zhou Junhua, et al. Research on change of dust storm in China in recent 50 years[J]. Journal of Natural Disasters, 2005, 14(3):22-26. ]
[10]	周自江, 王锡稳, 牛若芸. 近47年中国沙尘暴气候特征研究[J]. 应用气象学报, 2002, 13(2):193-200.
	[ Zhou Zijiang, Wang Xiwen, Niu Ruoyun. Climate characteristics of sandstorm in China in recent 47 years[J]. Journal of Applied Meteorological Science, 2002, 13(2):193-200. ]
[11]	Han Z W, Wang T, Sun Q W, et al. Sand harm in Taklimakan Desert highway and sand control[J]. Journal of Geographical Sciences, 2003, 13(1):45-53. doi: 10.1007/BF02873146
[12]	王静爱, 徐伟, 史培军, 等. 2000年中国风沙灾害的时空格局与危险性评价[J]. 自然灾害学报, 2001, 10(4):1-6.
	[ Wang Jing’ai, Xu Wei, Shi Peijun, et al. Spatio-temporal pattern and risk assessment of wind sand disaster in China in 2000[J]. Journal of Natural Disasters, 2001, 10(4):1-6. ]
[13]	徐海量, 陈亚宁. 塔里木盆地风沙灾害危险性评价[J]. 自然灾害学报, 2003, 12(2):35-39.
	[ Xu Hailiang, Chen Yaning. Hazard assessment of wind sand disaster in Tarim Basin[J]. Journal of Natural Disasters, 2003, 12(2):35-39. ]
[14]	Okada N, Tatano H, Hagihara Y, et al. Integrated research on methodological development of urban diagnosis for disaster risk and its applications[J]. Annual Report of Institute of Disaster Prevention, Kyoto University, 2004: 1-8.
[15]	史培军. 三论灾害研究的理论与实践[J]. 自然灾害学报, 2002, 11(3):1-9.
	[ Shi Peijun. Theory on disaster science and disaster dynamics[J]. Journal of Natural Disasters, 2002, 11(3):1-9. ]
[16]	王玉竹, 闫浩文, 王小平. 新疆风沙灾害风险评估[J]. 中国沙漠, 2020, 40(6):13-21.
	[ Wang Yuzhu, Yan Haowen, Wang Xiaoping. Risk assessment of wind-sand disaster in Xinjiang, China[J]. Journal of Desert Research, 2020, 40(6):13-21. ]
[17]	管梦鸾, 张正偲, 董治宝. 风沙灾害风险评估研究进展[J]. 中国沙漠, 2018, 38(5):978-988.
	[ Guan Mengluan, Zhang Zhengcai, Dong Zhibao. Progresses on the research of aeolian disaster risk assessment[J]. Journal of Desert Research, 2018, 38(5):978-988. ]
[18]	刘海涛, 刘海红, 韩春光, 等. 南疆大风气候特征分析[J]. 干旱区资源与环境, 2014, 28(3):148-154.
	[ Liu Haitao, Liu Haihong, Han Chunguang, et al. Analysis on the climatic characteristics of gales in south Xinjiang[J]. Journal of Arid Land Resources and Environment, 2014, 28(3):148-154. ]
[19]	潘伯荣, 李崇舜, 刘文江. 新疆沙漠与风沙灾害治理研究[J]. 中国生态农业学报, 2001, 9(3):19-21.
	[ Pan Borong, Li Chongshun, Liu Wenjiang. Desert and controlling of aeolian disaster in Xinjiang[J]. Chinese Journal of Eco-Agriculture, 2001, 9(3):19-21. ]
[20]	蒋富强, 李荧, 李凯崇, 等. 兰新铁路百里风区风沙流结构特性研究[J]. 铁道学报, 2010, 32(3):105-110.
	[ Jiang fuqiang, Li Ying, Li Kaichong, et al. Study on structural characteristics of gobi wind sand flow in 100 km wind area along Lan-Xin railway[J]. Journal of the China Railway Society, 2010, 32(3):105-110. ]
[21]	Jiapaer G, Chen X, Bao A M. A comparison of methods for estimating fractional vegetation cover in arid regions[J]. Agricultural & Forest Meteorology, 2011, 151(12):1698-1710.
[22]	Zhang K C, Qu J J, Liao K T, et al. Damage by windblown sand and its control along Qinghai-Tibet railway in China[J]. Aeolian Research, 2010, 2:143-146. doi: 10.1016/j.aeolia.2010.04.004
[23]	张志伟, 杨发相, 吴吉龙, 等. 新疆沙漠空间分布格局与类型结构[J]. 干旱区研究, 2014, 31(4):763-770.
	[ Zhang Zhiwei, Yang Faxiang, Wu Jilong, et al. Spatial distribution patterns and type structure of the deserts in Xinjiang[J]. Arid Zone Research, 2014, 31(4):763-770. ]
[24]	李锋. 沙尘暴灾害风险评估指标体系初探[J]. 灾害学, 2011, 26(4):8-13, 23.
	[ Li Feng. A preliminary discussion on risk assessment index system of sandstorm disasters[J]. Journal of Catastrophology, 2011, 26(4):8-13, 23. ]
[25]	吴美华, 王怀军, 孙桂丽, 等. 新疆农业气象灾害成因及其风险分析[J]. 干旱区地理, 2016, 39(6):1212-1220.
	[ Wu Meihua, Wang Huaijun, Sun Guili, et al. Formation and risk analysis of meteorological disasters in Xinjiang[J]. Arid Land Geography, 2016, 39(6):1212-1220. ]
[26]	温克刚. 中国气象灾害大典·新疆卷[M]. 北京: 气象出版社, 2006: 233-273.
	[ Wen Kegang. China meteorological disasters: Xinjiang volume[M]. Beijing: Meteorological Press, 2006: 233-273. ]
[27]	任晓, 穆桂金, 徐立帅, 等. 塔里木盆地南缘2000—2013年人工绿洲扩张特点[J]. 干旱区地理, 2015, 38(5):1022-1030.
	[ Ren Xiao, Mu Guijin, Xu Lishuai, et al. Characteristics of artificial oasis expansion in south Tarim Basin from 2000 to 2013[J]. Arid Land Geography, 2015, 38(5):1022-1030. ]
[28]	中国气象局. 地面气象观测规范[M]. 北京: 气象出版社, 2003: 21.
	[China Meteorological Administration. Ground meteorological observation specifications[M]. Beijing: Meteorological Press, 2003: 21. ]
[29]	陈洪武, 王旭, 马禹. 大风对新疆沙尘暴的影响[J]. 北京大学学报(自然科学版), 2003, 39(2):187-193.
	[ Chen Hongwu, Wang Xu, Ma Yu. Effects of strong winds on sandstorms in Xinjiang[J]. Universitatis Pekinensis (Acta Scientiarum Naturalium), 2003, 39(2):187-193. ]
[30]	王昀, 王旭, 马禹, 等. 新疆农作物生长期雹灾的时空分布及危害性评估[J]. 农业工程学报, 2019, 35(6):149-157.
	[ Wang Yun, Wang Xu, Ma Yu, et al. Spatial and temporal distribution and hazard assessment of hailstorm in Xinjiang during crop growing period[J]. Transactions of the Chinese Society of Agricultural Engineering, 2019, 36(6):149-157. ]
[31]	陈颖, 马禹. 新疆不同等级暴雨洪涝灾害的时空变化特征[J/OL]. [2021-08-21]. https://kns.cnki.net/kcms/detail/65.1103.X.20210820.1117.002.html .
	[ Chen Ying, Ma Yu. Spatial and temporal characteristics of flood and rainstorm disaster in Xinjiang[J/OL]. [2021-08-21]. https://kns.cnki.net/kcms/detail/65.1103.X.20210820.1117.002.html . ]
[32]	张太西, 王慧, 余行杰. 新疆风灾时空分布特征分析[J]. 干旱区地理, 2021, 44(5):1281-1289.
	[ Zhang Taixi, Wang Hui, Yu Xingjie. Spatial-temporal distribution of wind disasters in Xinjiang[J]. Arid Land Geography, 2021, 44(5):1281-1289. ]
[33]	赵清波, 李莉. 利用原始资料计算百分位数的方法[J]. 中国卫生统计, 1999, 3(16):185.
	[ Zhao Qingbo, Li Li. Method of calculating percentiles using original data[J]. China Health Statistics, 1999, 3(16):185. ]
[34]	李乃强, 徐贵阳. 基于自然间断点分级法的土地利用数据网格化分析[J]. 测绘通报, 2020(4):106-110.
	[ Li Naiqiang, Xu Guiyang. Grid analysis of land use based on natural breaks (jenks) classification[J]. Bulletin of Surveying and Mapping, 2020(4):106-110. ]
[35]	李冬梅, 陈春艳. 新疆沙尘天气知多少[EB/OL]. [2014-04-25]. http://www.cma.gov.cn/kppd/kppdrt/201404/t20140425_244387.html .
	[ Li Dongmei, Chen Chunyan. How much about sand-dust weather in Xinjiang[EB/OL].[2014-04-25]. http://www.cma.gov.cn/kppd/kppdrt/201404/t20140425_244387.html .]
[36]	王玉竹, 闫浩文, 王小平, 等. 新疆大风集中程度时空特征分析[J]. 干旱区地理, 2020, 43(3):623-632.
	[ Wang Yuzhu, Yan Haowen, Wang Xiaoping, et al. Spatio-temporal analysis of gale concentration in Xinjiang[J]. Arid Land Geography, 2020, 43(3):623-632. ]
[37]	何毅, 杨太保, 陈杰, 等. 1960—2013年南北疆风速变化特征分析[J]. 干旱区地理, 2015, 38(2):249-259.
	[ He Yi, Yang Taibao, Chen Jie, et al. Wind speed change in north and south Xinjiang from 1960 to 2013[J]. Arid Land Geography, 2015, 38(2):249-259. ]

序号	站号	站名	序号	站号	站名	序号	站号	站名	序号	站号	站名
1	51559	和静^*	11	51628	阿克苏^*	21	51709	喀什^*	31	51705	乌恰
2	51567	焉耆^*	12	51629	温宿	22	51716	巴楚^*	32	51708	阿克陶^*
3	51568	和硕^*	13	51633	拜城	23	51717	岳普湖	33	51711	阿合奇^*
4	51642	轮台	14	51636	新和	24	51802	英吉沙	34	51818	皮山
5	51655	尉犁	15	51639	沙雅	25	51804	塔什库尔干	35	51826	策勒
6	51656	库尔勒^*	16	51644	库车^*	26	51810	麦盖提	36	51827	墨玉
7	51765	铁干里克	17	51720	柯坪	27	51811	莎车	37	51828	和田^*
8	51777	若羌	18	51722	阿瓦提	28	51814	叶城	38	51829	洛普
9	51855	且末	19	51730	阿拉尔	29	51815	泽普	39	51839	民丰^*
10	51627	乌什	20	51707	伽师	30	51704	阿图什	40	51931	于田^*

统计量灾情要素	死亡人数/人	倒塌房屋数/间	倒塌棚圈数/座	损坏大棚数/座	牲畜死亡数量/头	农作物受灾面积/hm²
权重	0.07	0.07	0.06	0.24	0.09	0.47
平均值	0.02	9.44	8.53	80.98	233.09	2980.50
最大值	3.00	1414.00	1582.00	3442.00	25580.00	65419.40

百分位数S/%	灾损指数（Z）	风沙灾害强度等级
S≤50	Z≤0.35	一般（1级）
50<S≤75	0.35<Z≤0.94	较重（2级）
75<S≤90	0.94<Z≤2.31	严重（3级）
90<S	2.31<Z	特重（4级）

区域平均	1级/次	2级/次	3级/次	4级/次	合计/次	百分率/%
东部	0.39	0.17	0.12	0.07	0.75	22.46
北部	0.56	0.25	0.17	0.14	1.12	33.53
西部	0.31	0.21	0.12	0.07	0.71	21.26
南部	0.45	0.18	0.07	0.06	0.76	22.75

区域平均	1级	2级	3级	4级	合计	百分率/%
东部	0.05	0.10	0.19	0.26	0.60	18.02
北部	0.06	0.15	0.22	1.01	1.44	43.24
西部	0.04	0.12	0.19	0.33	0.68	20.42
南部	0.04	0.11	0.10	0.36	0.61	18.32

塔里木盆地风沙灾害强度和频次的时空分布特征

Spatial and temporal distribution characteristics of intensity and frequency of wind-sand disasters in Tarim Basin

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 13

参考文献 37

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	李乐乐, 钞锦龙, 赵德一, 李浩杰, 吴林栋, 李佳骏. 1957—2019年山西省暴雨时空分布特征与暴雨灾害风险评估[J]. 干旱区地理, 2023, 46(5): 689-699.
[2]	曲良璐, 姚俊强, 赵勇, 周雪雁. 塔里木盆地北缘一次局地极端暴雪天气异常机制及成因[J]. 干旱区地理, 2023, 46(5): 719-729.
[3]	吴志祥, 张志斌, 赵学伟, 陈龙, 马晓敏, 柴姣. 中国西北地区A级旅游景区时空分布格局及影响因素[J]. 干旱区地理, 2023, 46(12): 2061-2073.
[4]	魏娟娟, 万瑜, 张俊兰, 赵凤环, 李桉孛. 近20 a塔城地区暖区暴雪环流分型及成因分析[J]. 干旱区地理, 2022, 45(6): 1718-1728.
[5]	孙爱军, 赵晖, 刘冰, 汪克奇, 晁倩, 史志林, 陈发虎. 末次冰盛期以来塔里木盆地绿洲演化研究进展与问题[J]. 干旱区地理, 2022, 45(6): 1761-1772.
[6]	陈佳毅,赵勇. 伊朗高原和北非感热异常对夏季塔里木盆地降水的影响[J]. 干旱区地理, 2022, 45(5): 1357-1369.
[7]	刘兆旭,刘晶,范子昂. 2005—2020年新疆雷电灾害特征分析[J]. 干旱区地理, 2022, 45(5): 1402-1414.
[8]	买合木提江·维吉旦,玉素甫江·如素力,仇忠丽. 2000—2019年新疆积雪终日时空变化特征[J]. 干旱区地理, 2022, 45(4): 1061-1070.
[9]	杜军,高佳佳,王挺,平措桑旦. 2007—2020年西藏草面温度时空分布特征[J]. 干旱区地理, 2022, 45(4): 1103-1113.
[10]	杨涛,杨莲梅,周鸿奎,余行杰,李元鹏. 新疆北部小时降雪特征及大暴雪天气影响系统研究[J]. 干旱区地理, 2022, 45(3): 725-733.
[11]	陶泽涪,王世清,孙丕苓,李凯迪,田文,韩潇潇. 中国北方农牧交错带耕地时空分异及驱动因素[J]. 干旱区地理, 2022, 45(1): 153-163.
[12]	陈颖,马禹. 新疆不同等级暴雨洪涝灾害的时空变化特征[J]. 干旱区地理, 2021, 44(6): 1515-1524.
[13]	顾玮,古丽·加帕尔,尹瀚民,姜亮亮,藏晓芳. 新疆南疆地区太阳能资源时空分布特征及区划研究[J]. 干旱区地理, 2021, 44(6): 1665-1675.
[14]	刘圣锋,高柏,张海阳,樊骅,蒋文波. 塔里木盆地西部地下水水质评价及氟化物富集特征--以阿克陶县为例[J]. 干旱区地理, 2021, 44(5): 1261-1271.
[15]	张太西,王慧,余行杰. 新疆风灾时空分布特征分析[J]. 干旱区地理, 2021, 44(5): 1281-1289.