Drought evolution characteristics and vegetation response in the midwestern region of northwest China from 1963 to 2022

doi:10.11755/j.issn.1006-7639-2025-02-0163

Journal of Arid Meteorology ›› 2025, Vol. 43 ›› Issue (2): 163-175.DOI: 10.11755/j.issn.1006-7639-2025-02-0163

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Drought evolution characteristics and vegetation response in the midwestern region of northwest China from 1963 to 2022

SU Tianxin¹(), MENG Xianhong²^,³, YANG Xianyu¹(), AN Yingying²^,³, ZHAO Cailing⁴

1. College of Atmospheric Sciences， Chengdu University of Information Technology/ Sichuan Key Laboratory of Plateau Atmosphere and Environment， Chengdu 610225， China
2. Northwest Institute of Eco-Environment and Resources， Chinese Academy of Sciences / Key Laboratory of Cryosphere Science and Frozen Soil Engineering， Lanzhou 730000， China
3. Field Scientific Observatory for Climate and Environment in the Yellow River Source Region， Lanzhou 730000， China
4. Key Laboratory for Arid Climate Change and Disaster Reduction of Gansu Province， Lanzhou Institute of Arid Meteorology/ Key Laboratory for Arid Climate Change and Disaster Reduction of the China Meteorological Administration， Lanzhou 730020， China

Received:2024-11-28 Revised:2025-01-16 Online:2025-04-30 Published:2025-05-13

1963—2022年西北地区中西部干旱演变特征及植被响应研究

苏天鑫¹(), 孟宪红²^,³, 杨显玉¹(), 安颖颖²^,³, 赵采玲⁴

1.成都信息工程大学大气科学学院/高原大气与环境四川省重点实验室，四川成都 610225
2.中国科学院西北生态环境资源研究院/冰冻圈科学与冻土工程重点实验室，甘肃兰州 730000
3.甘肃省黄河源区气候与环境野外科学观测研究站，甘肃兰州 730000
4.中国气象局兰州干旱气象研究所甘肃省干旱气候变化与减灾重点实验室/中国气象局干旱气候变化与减灾重点实验室，甘肃兰州 730020

通讯作者: 杨显玉（1982—），男，内蒙古赤峰人，副教授，主要从事陆面过程与气候变化研究。E-mail：xyang@cuit.edu.cn。
作者简介:苏天鑫（2001—），男，湖北襄阳人，硕士研究生，主要从事区域气候变化及其影响研究。E-mail：sutianxin2001@163.com。
基金资助:
中国科学院B类先导专项(XDB0720200);甘肃省科技领军人才项目(24RCKB009);中国科学院“西部之光-西部交叉团队”项目(xbzg-zdsys-202215);甘肃省科技计划项目(23JRRA654);干旱气象科学研究基金项目(IAM201803)

Abstract

Abstract:

Systematically investigating drought evolution characteristics and vegetation responses to drought is crucial for drought prevention, disaster mitigation, water resource management, and policy formulation. Our study focuses on Xinjiang, Qinghai, and Gansu provinces in mid-western Northwest China. Using the CN05.1 dataset from 1963 to 2022 to calculate the standardized precipitation evapotranspiration index (SPEI), combined with the normalized difference vegetation index (NDVI) from 2003 to 2022, we applied run theory, Theil-Sen slope estimator, Mann-Kendall trend test, and regression analysis to analyze drought evolution across multiple temporal scales and explore drought impacts on vegetation. The results indicate that over the past 60 years, the study area exhibited a drying trend on decadal and interannual scales, with 1998 identified as a significant drought mutation year. Pronounced drying trends were observed in eastern and southern Xinjiang, the Qaidam Basin, and the Hexi Corridor, where light and moderate droughts were predominant. The Hexi Corridor experienced a significantly higher frequency of moderate droughts (greater than 15.00%) than other regions. Drought variability exhibited periodic characteristics of 12-year, 30-year, and 46-year cycles, with notable seasonal differences. In spring, summer, and autumn, the mid-western Northwest China showed significant drying trends, with the most rapid decline in autumn (SPEI rate: -0.034 yr?1). The Hexi Corridor exhibited SPEI decline rates below -0.030 yr?1 across all three seasons, indicating high risks of consecutive droughts, alongside prolonged duration, higher peak intensity, and mean drought intensity. The Tarim Basin also faced severe drought conditions in spring and autumn. Drought exerted measurable impacts on vegetation dynamics. Compared to 2003-2012, NDVI degradation areas increased by approximately 3.52% during 2013-2022. Over the past two decades, vegetation degradation was concentrated in western Xinjiang, eastern and southern Qinghai, where NDVI and SPEI were positively correlated.

Key words: Mid-western Northwest, drought, standardized precipitation evapotranspiration index, NDVI

摘要： 系统研究干旱演变特征及植被对干旱的响应，对防旱减灾、水资源管理和策略制定具有重要意义。本研究以新疆、青海和甘肃三省为研究区域，基于1963—2022年CN05.1数据计算标准化降水蒸散指数（Standardized Precipitation Evapotranspiration Index，SPEI），结合2003—2022年植被归一化指数NDVI，应用游程理论、Theil-Sen趋势检验、Mann-Kendall显著性检验、回归分析等方法，分析西北地区中西部不同时间尺度的干旱演变特征，并探讨干旱对植被的影响。结果表明，近60 a来，研究区在年代际和年际尺度上呈现干旱化趋势，1998年为干旱突变年；新疆东部和南部、柴达木盆地及河西走廊的干旱化趋势更为明显，干旱程度以轻旱和中旱为主，河西走廊中旱发生频率（大于15.00%）明显高于其他地区。干旱变化具有12 a、30 a和46 a的周期特征并具有明显的季节差异。春、夏、秋季西北地区中西部具有明显干旱化趋势，其中秋季SPEI减小速率为-0.034 a^-1，干旱化趋势最突出；尤其是河西走廊，春、夏、秋季SPEI减小速率均小于-0.030 a^-1，表明该地区连旱可能性较高，同时干旱历时、烈度峰值和平均干旱烈度均较高。塔里木盆地春秋季的干旱程度亦较为突出。干旱对植被变化具有一定的影响。与2003—2012年相比，2013—2022年NDVI退化面积增加约3.52%。近20 a来植被退化区域主要分布在新疆西部、青海东部和南部，NDVI与SPEI呈正相关。

关键词: 西北地区中西部, 干旱, 标准化降水蒸散指数, NDVI

CLC Number:

P426.616

SU Tianxin, MENG Xianhong, YANG Xianyu, AN Yingying, ZHAO Cailing. Drought evolution characteristics and vegetation response in the midwestern region of northwest China from 1963 to 2022[J]. Journal of Arid Meteorology, 2025, 43(2): 163-175.

苏天鑫, 孟宪红, 杨显玉, 安颖颖, 赵采玲. 1963—2022年西北地区中西部干旱演变特征及植被响应研究[J]. 干旱气象, 2025, 43(2): 163-175.

Figures/Tables 18

Fig.1 Schematic diagram of the study area

Tab.1 Drought classification criteria based on SPEI

等级	干旱类型	SPEI值
1	无旱	-0.5<SPEI
2	轻旱	-1.0<SPEI≤-0.5
3	中旱	-1.5<SPEI≤-1.0
4	重旱	-2.0<SPEI≤-1.5
5	特旱	SPEI≤-2.0

Tab.2 Drought event SPEI applicability rating criteria

监测结果	监测效果	评分
空检测或漏监测	差	0
程度和范围均有偏差	较差	1
程度和范围有1项符合	一般	2
程度和范围均符合	较好	3

Tab.3 Drought events in study area、monitoring effectiveness rating and accuracy

干旱类型	年份	主要旱区	评分	准确率/%
春旱	1974	新疆大部、甘肃河东	2	62.50
	1977	新疆局部、青海大部	2
	1978	新疆大部、甘肃河东	2
	1981	甘肃大部	1
	1986	新疆大部、甘肃河西	1
	2000	新疆大部、甘肃大部、青海海东	3
	2004	新疆大部、甘肃河东	2
	2015	新疆大部、甘肃大部	2
夏旱	1972	甘肃河东、青海海东	2	79.17
	1978	新疆大部、甘肃河西	2
	1990	新疆大部、甘肃河东	2
	1991	西北大部	3
	1995	甘肃河东、青海大部	3
	1997	甘肃大部	2
	2006	西北大部	3
	2017	甘肃大部、青海东部	2
秋旱	1986	新疆大部	2	83.33
	1991	新疆北部、甘肃河东	3
	1998	甘肃河东	3
	1999	甘肃中东部	2
春夏秋连旱	1978	新疆大部	2	75.00
	1997	甘肃大部	2
	2008	新疆大部	3
	2022	甘肃大部	2
整体			53	73.61

Fig.2 Spatial distribution of SPEI for four drought events in the midwestern region of northwest China

Fig.3 Spatial distribution of SPEI in different decades in the midwestern region of northwest China from 1963 to 2022

Fig.4 Interannual variation of SPEI and M-K test in the midwestern region of northwest China from 1963 to 2022

Fig.5 Spatial distribution of the SPEI change rate in the midwestern region of northwest China from 1963 to 2022 （The dotted areas indicate significance at the 95% confidence level）

Fig.6 Wavelet analysis of drought cycles based on SPEI （a） and corresponding wavelet coefficient variance （b） in the midwestern region of northwest China from 1963 to 2022

Fig.7 Spatial distribution of drought occurrence frequency （Unit： %） at different severity levels in the midwestern region of northwest China from 1963 to 2022

Fig.8 Spatial distribution of seasonal SPEI trends in the midwestern region of northwest China from 1963 to 2022 (Unit: a-1) (The dotted areas indicate significance at the 95% confidence level)

Fig.9 Spatial distribution of seasonal drought frequency， mean duration， peak intensity， and mean intensity in the midwestern region of northwest China from 1963 to 2022

Fig.10 Seasonal variation of SPEI and M-K test in the midwestern region of northwest China from 1963 to 2022

Fig.11 Spatial distribution of annual mean NDVI and its trend changes in different periods in the midwestern region of northwest China from 2003 to 2022

Tab.4 Annual average statistics of NDVI in the midwestern region of northwest China from 2003 to 2022

NDVI均值	像元个数	百分比/%
<0.1	18 928 780	41.06
~0.1<0.2	9 231 039	20.02
~0.2<0.3	3 847 051	8.35
~0.3<0.4	2 606 813	5.65
~0.4<0.95	11 484 042	24.92

Tab.5 Statistics on the trend of NDVI in the midwestern region of northwest China from 2003 to 2022

$S N D V I$ /a^-1	$Z$	NDVI趋势	像元个数	百分比/%
<-0.000 5	≤1.96	轻微退化	2 926 009	6.48
<-0.000 5	>1.96	显著退化	716 410	1.59
-0.000 5~0.000 5		稳定不变	15 602 273	34.57
>0.000 5	>1.96	明显改善	14 966 410	33.17
>0.000 5	≤1.96	轻微改善	10 915 416	24.19

Tab.5 Statistics on the trend of NDVI in the midwestern region of northwest China from 2003 to 2022

$S N D V I$ /a^-1	$Z$	NDVI趋势	像元个数	百分比/%
<-0.000 5	≤1.96	轻微退化	2 926 009	6.48
<-0.000 5	>1.96	显著退化	716 410	1.59
-0.000 5~0.000 5		稳定不变	15 602 273	34.57
>0.000 5	>1.96	明显改善	14 966 410	33.17
>0.000 5	≤1.96	轻微改善	10 915 416	24.19

Tab.6 Statistics of NDVI trends in the midwestern region of northwest China from 2003 to 2012 and from 2013 to 2022

2003—2012年			2013—2022年
NDVI趋势	像元个数	百分比/%	NDVI趋势	像元个数	百分比/%
轻微退化	8 013 340	17.72	轻微退化	9 291 888	20.54
明显退化	782 646	1.73	明显退化	1 099 378	2.43
稳定不变	11 958 309	26.45	稳定不变	11 165 730	24.68
明显改善	6 001 385	13.27	明显改善	5 199 594	11.49
轻微改善	18 455 916	40.83	轻微改善	18 487 780	40.86

Fig.12 Spatial distribution of the correlation coefficient between NDVI and SPEI in the midwestern region of northwest China from 2003 to 2022 （The black areas indicate significance at the 95% confidence level）

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Drought evolution characteristics and vegetation response in the midwestern region of northwest China from 1963 to 2022

1963—2022年西北地区中西部干旱演变特征及植被响应研究

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