Vegetation's Dynamic Changes, Spatial Trends, and Responses to Drought in the Yellow River Basin, China

被引:1
作者
Wang, Fei [1 ]
Men, Ruyi [1 ]
Yan, Shaofeng [2 ]
Lai, Hexin [1 ]
Wang, Zipeng [1 ]
Feng, Kai [1 ]
Gao, Shikai [1 ]
Li, Yanbin [1 ]
Guo, Wenxian [1 ]
Qu, Yanping [3 ]
机构
[1] North China Univ Water Resources & Elect Power, Sch Water Conservancy, Zhengzhou 450046, Peoples R China
[2] Hubei Inst Water Resources Survey & Design Co Ltd, Wuhan 430070, Peoples R China
[3] China Inst Water Resources & Hydropower Res, Res Ctr Flood & Drought Disaster Reduct, Beijing 100038, Peoples R China
来源
AGRONOMY-BASEL | 2024年 / 14卷 / 08期
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
vegetation dynamics; drought response; driving effect; remote-sensing technology; Yellow River Basin (YRB); AGRICULTURAL DROUGHT; LOESS PLATEAU; CLIMATE; PRECIPITATION; EVAPOTRANSPIRATION; INDEX; TEMPERATURE; GROWTH; SHIFTS;
D O I
10.3390/agronomy14081724
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Drought is a complex and recurrent natural disaster that can have devastating impacts on economies, societies, and ecosystems around the world. In light of climate change, the frequency, duration, and severity of drought events worldwide have increased, and extreme drought events have caused more severe and irreversible damage to terrestrial ecosystems. Therefore, estimating the resilience of different vegetation to drought events and vegetation's response to damage is crucial to ensuring ecological security and guiding ecological restoration. Based on meteorological and remote-sensing datasets from 1982 to 2022, the spatial distribution characteristics and temporal variability of vegetation were identified in the Yellow River Basin (YRB), the dynamic changes and recurrence periods of typical drought events were clarified, and the driving effects of different drought types on vegetation were revealed. The results indicated that (1) during the research period, the standardized vegetation water-deficit index (SVWI) showed a downward trend in the YRB, with a 99.52% probability of abrupt seasonal changes in the SVWI occurring in January 2003; (2) the characteristic values of the grid trend Zs were -1.46 and 0.20 in winter and summer, respectively, indicating a significant downward trend in the winter SVWI; (3) the drought with the highest severity (6.48) occurred from September 1998 to February 1999, with a recurrence period of 8.54 years; and (4) the growth of vegetation was closely related to drought, and as the duration of drought increased, the sensitivity of vegetation to drought events gradually weakened. The research results provide a new perspective for identifying vegetation's dynamic changes and responses to drought, which is of great significance in revealing the adaptability and potential influencing factors of vegetation in relation to climate.
引用
收藏
页数:21
相关论文
共 67 条
[1]   Modeling the influence of daily temperature and precipitation extreme indices on vegetation dynamics in Katsina State using statistical downscaling model (SDM) [J].
Ahmad, Mohammad Hadi ;
Abubakar, Ahmed ;
Ishak, Mohd Yusoff ;
Danhassan, Samir Shehu ;
Jiahua, Zhang ;
Alatalo, Juha M. .
ECOLOGICAL INDICATORS, 2023, 155
[2]   Assessment of drought conditions over Iraqi transboundary rivers using FLDAS and satellite datasets [J].
Albarakat, Reyadh ;
Le, Manh-Hung ;
Lakshmi, Venkataraman .
JOURNAL OF HYDROLOGY-REGIONAL STUDIES, 2022, 41
[3]   The Evaporative Stress Index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts [J].
Anderson, Martha C. ;
Zolin, Cornelio A. ;
Sentelhas, Paulo C. ;
Hain, Christopher R. ;
Semmens, Kathryn ;
Yilmaz, M. Tugrul ;
Gao, Feng ;
Otkin, Jason A. ;
Tetrault, Robert .
REMOTE SENSING OF ENVIRONMENT, 2016, 174 :82-99
[4]   Robust ecological drought projections for drylands in the 21st century [J].
Bradford, John B. ;
Schlaepfer, Daniel R. ;
Lauenroth, William K. ;
Palmquist, Kyle A. .
GLOBAL CHANGE BIOLOGY, 2020, 26 (07) :3906-3919
[5]   Monitoring the Vegetation Dynamics in the Dongting Lake Wetland from 2000 to 2019 Using the BEAST Algorithm Based on Dense Landsat Time Series [J].
Cai, Yaotong ;
Liu, Shutong ;
Lin, Hui .
APPLIED SCIENCES-BASEL, 2020, 10 (12)
[6]   Ecosystems threatened by intensified drought with divergent vulnerability [J].
Chen, Qi ;
Timmermans, Joris ;
Wen, Wen ;
van Bodegom, Peter M. .
REMOTE SENSING OF ENVIRONMENT, 2023, 289
[7]   Estimation of the ecological water requirement for natural vegetation in the Ergune River basin in Northeastern China from 2001 to 2014 [J].
Chi, Dengkai ;
Wang, Hong ;
Li, Xiaobing ;
Liu, Honghai ;
Li, Xiaohui .
ECOLOGICAL INDICATORS, 2018, 92 :141-150
[8]   NDVI-based vegetation dynamics and its response to climate changes at Amur-Heilongjiang River Basin from 1982 to 2015 [J].
Chu, Hongshuai ;
Venevsky, Sergey ;
Wu, Chao ;
Wang, Menghui .
SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 650 :2051-2062
[9]   Spatiotemporal evolution of agricultural drought and its attribution under different climate zones and vegetation types in the Yellow River Basin of China [J].
Ding, Yujie ;
Zhang, Lifeng ;
He, Yi ;
Cao, Shengpeng ;
Wei, Xiao ;
Guo, Yan ;
Ran, Ling ;
Filonchyk, Mikalai .
SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 914
[10]   Interacting effects of temperature and precipitation on climatic sensitivity of spring vegetation green-up in arid mountains of China [J].
Du, Jun ;
He, Zhibin ;
Piatek, Kathryn B. ;
Chen, Longfei ;
Lin, Peifei ;
Zhu, Xi .
AGRICULTURAL AND FOREST METEOROLOGY, 2019, 269 :71-77