基于三维识别的中国干旱事件演变特征分析

doi:10.13866/j.azr.2023.06.01

摘要/Abstract

摘要：

中国是世界上受干旱影响最严重的国家之一，干旱频发给我国经济社会发展和生态环境造成严重影响。为分析近40 a干旱事件的时空特征，本文结合三维聚类算法，从干旱事件时空联动的本质出发，识别中国1981—2020年间干旱事件并定量分析干旱事件的时空动态演变过程。主要结论如下：三维聚类算法能有效识别干旱事件及其动态变化过程。中国1981—2020年间发生持续2个月及以上的干旱事件102场，空间上，干旱事件空间轨迹倾向于自东向西发展；时间上，干旱事件时间重叠度较高，长历时干旱多具有多峰特点。此外，覆盖范围广且严重度高的干旱事件集中发生于2005—2010年。本文结论有助于发现中国干旱事件的时空演化规律，为我国干旱监测和干旱风险管理提供科学参考。

关键词: 三维聚类算法, 干旱事件, 三维演变特征, 动态演变, SPEI, 中国

Abstract:

Globally, China is one of the country’s most frequently and severely affected by drought. These frequent drought events have subsequently caused serious economic, social development, and ecological environment losses. Drought simultaneously leads to alterations in both space and time, and this paper aims to identify drought events and quantify their spatial and temporal dynamic evolution using a three-dimensional clustering algorithm for mainland China, from 1981-2020. The three-dimensional clustering algorithm can be used to effectively identify drought events and describe their dynamic processes. From 1981-2020 there were 102 drought events lasting 2 months or more in mainland China. Spatially, the trajectory of drought events was found to show a tendency to develop from east to west. Temporally, there are high time overlaps between different drought events. In addition, drought events with wide coverage and high severity were concentrated in the period from 2005-2010. The findings of this paper will help to elucidate the spatial and temporal evolution patterns of drought events and provide scientific references for drought monitoring and drought risk management in mainland China.

Key words: three-dimensional clustering algorithm, drought event, three-dimensional evolutionary features, dynamic evolution, SPEI, China

吕潇雨, 郭浩, 孟翔晨, 包安明, 田芸菲, 朱丽. 基于三维识别的中国干旱事件演变特征分析[J]. 干旱区研究, 2023, 40(6): 849-962.

LYU Xiaoyu, GUO Hao, MENG Xiangchen, BAO Anming, TIAN Yunfei, ZHU Li. Characterization of the evolution of drought events in China based on 3D identification[J]. Arid Zone Research, 2023, 40(6): 849-962.

图/表 11

图1

表1

SPEI计算步骤"

步骤	公式	备注
1	$D j = P j - P E T j$	j表示月份； $D j$ 表示第j月的降水（ $P j$ ）与该月潜在蒸散发（PET_j）的差值
2	$X i, j k = ∑ l = 13 - k + j 12 D i - 1, l + ∑ l = 1 j D i, ? l, ? j < k X i, j k = ∑ l = j - k + j j D i - 1, l, ? ? j ≥ k$	$X i, j k$ 表示降水（ $P j$ ）与潜在蒸散发（PET_j）在k个月时间尺度上第i年j月的累加值
3	$F (X) = 1 + α X - γ β - 1$	$F (X)$ 是根据log-logistic分布得出的 $D j$ 序列的概率分布函数，其中α、β和γ分别代表尺度系数、形状系数和 origin 参数
4	$β = 2 w 1 - w 0 6 w 1 - w 0 - 6 w 2 α = w 0 - 2 w 1 β τ 1 + 1 β τ 1 - 1 β γ = w 0 - α τ 1 + 1 β τ 1 - 1 β$	$w 0$ 、 $w 1$ 、 $w 2$ 表示log-logistic分布的3个矩比参数，采用线性矩方法（L-moment）拟合获得； $τ$ 是Gamma分布函数
5	$p = 1 - F (x)$ $w = - 2 l n (p) - 2 l n (1 - p), ? ? p ≤ 0.5, ? ? p > 0.5$ $S P E I = w - c 0 + c 1 w + c 2 w 2 1 + d 1 w + d 2 w 2 + d 3 w 3$	p是标准化的分布函数值；w是一个参数； $c 0$ =2.515517， $c 1$ =0.802853， $c 2$ =0.010328， $d 1$ =1.432788， $d 2$ =0.189269和 $d 3$ =0.001308，相关参数来自于Vicente-Serrano等^[32]

表1

图2

表2

图3

图4

图5

图6

图7

图8

图9

参考文献 45

[1]	Barros V, Stocker T F. Managing the risks of extreme events and disasters to advance climate change adaptation: Special report of the intergovernmental panel on climate change[J]. Journal of Clinical Endocrinology & Metabolism, 2012, 18(6): 586-599. doi: 10.1210/jcem-18-6-586
[2]	Zhang X, Chen N, Sheng H, et al. Urban drought challenge to 2030 sustainable development goals[J]. Science of the Total Environment, 2019, 693: 133536-133547. doi: 10.1016/j.scitotenv.2019.07.342
[3]	Su B, Huang J, Fischer T, et al. Drought losses in China might double between the 1.5 degrees C and 2.0 degrees C warming[J]. Proceedings of the National Academy of Sciences of The United States of America, 2018, 115(42): 10600-10605.
[4]	张强, 姚玉璧, 李耀辉, 等. 中国干旱事件成因和变化规律的研究进展与展望[J]. 气象学报, 2020, 78(3): 500-521.
	[Zhang Qiang, Yao Yubi, Li Yaohui, et al. Progress and prospect on the study of causes and variation regularity of droughts in China[J]. Acta Meteorologica Sinica, 2020, 78(3): 500-521.]
[5]	Guo H, Bao A, Ndayisaba F, et al. Space-time characterization of drought events and their impacts on vegetation in Central Asia[J]. Journal of Hydrology, 2018, 564: 1165-1178. doi: 10.1016/j.jhydrol.2018.07.081
[6]	任朝霞, 杨达源. 近40 a西北干旱区极端气候变化趋势研究[J]. 干旱区资源与环境, 2007, 21(4): 10-13.
	[Ren Zhaoxia, Yang Dayuan. Study on trends of extreme climate change in the arid region of Northwest China in resent 40 years[J]. Journal of Arid Land Resources and Environment, 2007, 21(4): 10-13.]
[7]	李天水, 王顺, 庄文化, 等. 游程理论和Copula函数在二维干旱变量联合分布中的应用[J]. 干旱区资源与环境, 2016, 30(6): 77-82.
	[Li Tianshui, Wang Shun, Zhuang Wenhua, et al. Application of the theory of run and Copula function to the joint distribution of two-dimension drought variables[J]. Journal of Arid Land Resources and Environment, 2016, 30(6): 77-82.]
[8]	Huang S, Li P, Huang Q, et al. The propagation from meteorological to hydrological drought and its potential influence factors[J]. Journal of Hydrology, 2017, 547: 184-195. doi: 10.1016/j.jhydrol.2017.01.041
[9]	Tatli H, Türkeş M. Empirical orthogonal function analysis of the palmer drought indices[J]. Agricultural and Forest Meteorology, 2011, 151(7): 981-991. doi: 10.1016/j.agrformet.2011.03.004
[10]	朱亚芬. 530年来中国东部旱涝分区及北方旱涝演变[J]. 地理学报, 2003, 58(S1): 100-107.
	[Zhu Yafen. The regional division of dryness/wetness over Eastern China and variations of dryness/wetness in northern China during the last 530 years[J]. Acta Geographica Sinica, 2003, 58(S1): 100-107.]
[11]	Andreadis K M, Clark E A, Wood A W, et al. Twentieth-century drought in the conterminous United States[J]. Journal of Hydrometeorology, 2005, 6(6): 985-1001. doi: 10.1175/JHM450.1
[12]	Lloyd-Hughes B. A spatio-temporal structure-based approach to drought characterisation[J]. International Journal of Climatology, 2012, 32(3): 406-418. doi: 10.1002/joc.2280
[13]	Liu Y, Zhu Y, Ren L, et al. Understanding the spatiotemporal links between meteorological and hydrological droughts from a Three-Dimensional Perspective[J]. Journal of Geophysical Research: Atmospheres, 2019, 124(6): 3090-3109. doi: 10.1029/2018JD028947
[14]	Wen X, Tu Y, Tan Q, et al. Construction of 3D drought structures of meteorological drought events and their spatio-temporal evolution characteristics[J]. Journal of Hydrology, 2020, 590(6): 125539-125550. doi: 10.1016/j.jhydrol.2020.125539
[15]	Xu K, Yang D, Yang H, et al. Spatio-temporal variation of drought in China during 1961-2012: A climatic perspective[J]. Journal of Hydrology, 2015, 526: 253-264. doi: 10.1016/j.jhydrol.2014.09.047
[16]	冯凯, 粟晓玲. 基于三维视角的农业干旱对气象干旱的时空响应关系[J]. 农业工程学报, 2020, 36(8): 103-113.
	[Feng Kai, Su Xiaoling. Spatiotemporal response characteristics of agricultural drought to meteorological drought from a three-dimensional perspective[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(8): 103-113.]
[17]	邓翠玲, 佘敦先, 张利平, 等. 基于图像三维连通性识别方法的长江流域干旱事件特征[J]. 农业工程学报, 2021, 37(11): 131-139.
	[Deng Cuiling, She Dunxian, Zhang Liping, et al. Multi-model projections of meteorological drought characteristics under different scenarios in the middle and lower reaches of Yangtze River Basin[J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 37(11): 131-139.]
[18]	Du X, Jin X, Yang X, et al. Spatial-temporal pattern changes of main agriculture natural disasters in China during 1990-2011[J]. Journal of Geographical Sciences, 2015, 25(4): 387-398. doi: 10.1007/s11442-015-1175-x
[19]	吴鹏, 谷星月, 王朋岭. 中国气候变化蓝皮书(2022)发布[N]. 2022-08-04, 2022: 001.
	[Wu Peng, Gu Xingyue, Wang Pengling. Blue Book on Climate Change of China 2022 Rolled Out[N]. 2022-08-04, 2022: 001.]
[20]	Zhai J, Su B, Krysanova V, et al. Spatial variation and trends in PDSI and SPI indices and their relation to streamflow in 10 large regions of China[J]. Journal of Climate, 2010, 23(3): 649-663. doi: 10.1175/2009JCLI2968.1
[21]	郝立生, 马宁, 何丽烨. 2022年长江中下游夏季异常干旱高温事件之环流异常特征[J]. 干旱气象, 2022, 40(5): 721-732. doi: 10.11755/j.issn.1006-7639(2022)-05-0721
	[Hao Lisheng, Ma Ning, He Liye. Circulation anomalies characteritics of the abnormal drought and high temperature event in the middle and lower reaches of the Yangtze River in summer of 2022[J]. Journal of Arid Meteorology, 2022, 40(5): 721-732.] doi: 10.11755/j.issn.1006-7639(2022)-05-0721
[22]	李忆平, 张金玉, 岳平, 等. 2022年夏季长江流域重大干旱特征及其成因研究[J]. 干旱气象, 2022, 40(5): 733-747. doi: 10.11755/j.issn.1006-7639(2022)-05-0733
	[Li Yiping, Zhang Jinyu, Yue Ping, et al. Study on characteristics of severe drought event over Yangtze River Basin in summer of 2022 and its causes[J]. Journal of Arid Meteorology, 2022, 40(5): 733-747.] doi: 10.11755/j.issn.1006-7639(2022)-05-0733
[23]	张强. 科学解读“2022年长江流域重大干旱”[J]. 干旱气象, 2022, 40(4): 545-548. doi: 10.11755/j.issn.1006-7639（2022）-04-0545
	[Zhang Qiang. Scientific interpretation of severe drought in the Yangtze River Basin[J]. Journal of Arid Meteorology, 2022, 40(4): 545-548.] doi: 10.11755/j.issn.1006-7639（2022）-04-0545
[24]	Shen Y, Feng M, Zhang H, et al. Interpolation methods of China daily precipitation data[J]. Journal of Applied Meteorological Science, 2010, 21(3): 279-286.
[25]	Shen Y, Xiong A. Validation and comparison of a new gauge-based precipitation analysis over mainland China[J]. International Journal of Climatology, 2016, 36(1): 252-265. doi: 10.1002/joc.4341
[26]	Muñoz-Sabater J, Dutra E, Agustí-Panareda A, et al. ERA5-Land: A state-of-the-art global reanalysis dataset for land applications[J]. Earth System Science Data, 2021, 13(9): 4349-4383. doi: 10.5194/essd-13-4349-2021
[27]	Zandler H, Senftl T, Vanselow K A. Reanalysis datasets outperform other gridded climate products in vegetation change analysis in peripheral conservation areas of Central Asia[J]. Scientific Reports, 2020, 10(1): 22446. doi: 10.1038/s41598-020-79480-y pmid: 33384431
[28]	Xue C, Wu H, Jiang X. Temporal and spatial change monitoring of drought grade based on ERA5 analysis data and BFAST method in the Belt and Road area during 1989-2017[J]. Advances in Meteorology, 2019, 2019: 4053718-4053729.
[29]	Chen H, Sun J. Changes in drought characteristics over China using the standardized precipitation evapotranspiration index[J]. Journal of Climate, 2015, 28(13): 5430-5447. doi: 10.1175/JCLI-D-14-00707.1
[30]	周扬, 李宁, 吉中会, 等. 基于SPI指数的1981—2010年内蒙古地区干旱时空分布特征[J]. 自然资源学报, 2013, 28(10): 1694-1706. doi: 10.11849/zrzyxb.2013.10.005
	[Zhou Yang, Li Ning, Ji Zhonghui, et al. Temporal and spatial patterns of droughts based on Standard Precipitation Index(SPI) in Inner Mongolia during 1981-2010[J]. Journal of Natural Resources, 2013, 28(10): 1694-1706.] doi: 10.11849/zrzyxb.2013.10.005
[31]	王荣江, 李谢辉, 周任君, 等. 三种气象干旱指数在四川省的适用性分析[J]. 长江流域资源与环境, 2021, 30(3): 734-744.
	[Wang Rongjiang, Li Xiehui, Zhou Renjun, et al. Applicability analysis of three meteorological drought indices in Sichuan Province[J]. Resources and Environment in the Yangtze Basin, 2021, 30(3): 734-744.]
[32]	Vicente-Serrano S M, Beguería S, López-Moreno J I. A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index[J]. Journal of Climate, 2010, 23(7): 1696-1718. doi: 10.1175/2009JCLI2909.1
[33]	Wang A, Lettenmaier D P, Sheffield J. Soil moisture drought in China, 1950-2006[J]. Journal of Climate, 2011, 24(13): 3257-3271. doi: 10.1175/2011JCLI3733.1
[34]	王姣妍. 基于MSWEP降水产品的新疆干旱时空特征分析[J]. 干旱区研究, 2022, 39(5): 1398-1409.
	[Wang Jiaoyan. Study on spatiotemporal characteristics of drought in Xinjiang based on Multi-Source Weighted-Ensemble Precipitation multi-source merged precipitation product[J]. Arid Zone Research, 2022, 39(5): 1398-1409.]
[35]	Guo H, Bao A, Liu T, et al. Meteorological drought analysis in the lower Mekong Basin using satellite-based long-term CHIRPS product[J]. Sustainability, 2017, 9(6): 1-21. doi: 10.3390/su9010001
[36]	Ma B, Zhang B, Jia L, et al. Conditional distribution selection for SPEI-daily and its revealed meteorological drought characteristics in China from 1961 to 2017[J]. Atmospheric Research, 2020, 246: 105108-105119. doi: 10.1016/j.atmosres.2020.105108
[37]	Guo H, Bao A, Liu T, et al. Spatial and temporal characteristics of droughts in Central Asia during 1966-2015[J]. Science of the Total Environment, 2018, 624: 1523-1538. doi: 10.1016/j.scitotenv.2017.12.120
[38]	Diaz V, Corzo Perez G A, Van Lanen H A J, et al. Characterisation of the dynamics of past droughts[J]. Science of the Total Environment, 2020, 718: 134588-134600. doi: 10.1016/j.scitotenv.2019.134588
[39]	Colwell R K, Lees D C. The mid-domain effect: Geometric constraints on the geography of species richness[J]. Trends in Ecology & Evolution, 2000, 15(2): 70-76. doi: 10.1016/S0169-5347(99)01767-X
[40]	冯琳. 2009年全国旱灾及抗旱行动情况[J]. 中国防汛抗旱, 2010, 20(1): 76-79.
	[Feng Lin. National drought and drought action in 2009[J]. China Flood & Drought Management, 2010, 20(1): 76-79.]
[41]	王红军, 白爱娟. 2008/2009年冬季大气环流异常对我国东部严重干旱的影响[J]. 干旱区资源与环境, 2010, 24(11): 104-109.
	[Wang Hongjun, Bai Aijuan. The severe drought in eastern China by the anomalies atmospheric circulation in winter 2008[J]. Journal of Arid Land Resources and Environment, 2010, 24(11): 104-109.]
[42]	江东, 付晶莹, 庄大方, 等. 2008—2009年中国北方干旱遥感动态监测[J]. 自然灾害学报, 2012, 21(3): 92-101.
	[Jiang Dong, Fu Jingying, Zhuang Dafang, et al. Dynamic drought-remote sensing monitoring in North China from 2008 to 2009[J]. Journal of Natural Disasters, 2012, 21(3): 92-101.]
[43]	中国水旱灾害防御公报编写组. 《中国水旱灾害防御公报2020》概要[J]. 中国防汛抗旱, 2021, 31(11): 7.
	[Compilation group of China Flood and Drought Disaster Prevention Bulletin. Summary of China Flood and Drought Disaster Prevention Bulletin 2020[J]. China Flood & Drought Management, 2021, 31(11): 7.]
[44]	中国气象局. 中国气象干旱图集[M]. 北京: 气象出版社, 2010.
	[China Meteorological Administration. Atlas of China’s Meteorological Drought[M]. Beijing: Meteorological Press, 2010.]
[45]	冯凯, 李彦彬, 王飞, 等. 基于改进三维识别方法的西北地区干旱事件分析[J]. 水资源保护, 2023, 39(1): 63-72.
	[Feng Kai, Li Yanbin, Wang Fei, et al. Analysis of drought events in Northwest China based on an improved three-dimensional identification method[J]. Water Resources Protection, 2023, 39(1): 63-72.]

序号	起始时间/年-月	干旱历时 /个月	干旱烈度	干旱严重度 /10⁷ km²	干旱面积 /10⁶ km²	干旱质心			干旱质心路径/km	备注
序号	起始时间/年-月	干旱历时 /个月	干旱烈度	干旱严重度 /10⁷ km²	干旱面积 /10⁶ km²	纬度（N）	经度（E）	时间/年-月	干旱质心路径/km	备注
1	2008-08—2009-09	14	0.44	4.91	8.00	38.13	103.13	2009-04	5553.09	干旱事件d
2	2010-11—2011-11	13	0.51	3.67	5.52	32.13	109.88	2011-04	4377.83
3	2018-10—2020-07	22	0.40	3.32	3.78	41.88	120.63	2019-07	8027.61	干旱事件f
4	1998-10—1999-06	9	0.61	3.30	6.01	33.38	105.13	1999-02	3278.50	干旱事件b
5	2001-02—2002-04	15	0.36	2.89	5.40	40.63	112.88	2001-09	6381.09
6	2004-02—2004-11	10	0.40	2.66	6.70	39.38	106.38	2004-06	7401.21
7	2009-09—2010-07	11	0.44	2.58	5.37	31.63	101.63	2010-01	4907.81
8	2017-03—2018-06	16	0.31	2.37	4.82	41.38	108.63	2017-12	7257.69
9	2013-07—2014-09	15	0.28	2.30	5.57	36.38	103.63	2013-12	7550.17
10	2015-07—2016-06	12	0.40	2.19	4.53	34.88	91.63	2015-12	3549.72
11	1996-10—1997-12	15	0.28	2.07	4.94	35.13	111.13	1997-08	4298.00
12	2012-12—2013-05	6	0.68	2.05	5.04	35.38	100.63	2013-03	2246.02	干旱事件e
13	1984-03—1985-05	15	0.51	2.01	2.64	34.88	89.13	1984-10	3309.17
14	1986-08—1987-09	14	0.32	1.74	3.89	32.63	98.38	1987-03	4501.10	干旱事件a
15	2007-06—2008-05	12	0.90	1.74	1.61	46.88	123.13	2007-11	1444.02	干旱事件c
16	2006-03—2006-10	8	0.48	1.70	4.39	34.38	106.63	2006-07	2247.29
17	2014-07—2015-05	11	0.27	1.44	4.93	38.88	110.38	2015-01	6247.83
18	1991-04—1991-12	9	0.37	1.35	4.02	33.38	108.13	1991-09	3548.70
19	2019-09—2020-08	12	0.33	1.34	3.37	40.63	94.63	2020-03	6040.55
20	2017-11—2018-07	9	0.38	1.34	3.93	31.13	98.63	2018-02	3783.17