Assessing the responses of vegetation to meteorological drought and its influencing factors with partial wavelet coherence analysis

Zhaoqiang Zhou; Suning Liu; Yibo Ding; Qiang Fu; Yao Wang; Hejiang Cai; Haiyun Shi

doi:10.1016/j.jenvman.2022.114879

Assessing the responses of vegetation to meteorological drought and its influencing factors with partial wavelet coherence analysis

J Environ Manage. 2022 Mar 15:311:114879. doi: 10.1016/j.jenvman.2022.114879. Online ahead of print.

Authors

Zhaoqiang Zhou¹, Suning Liu², Yibo Ding³, Qiang Fu⁴, Yao Wang¹, Hejiang Cai⁵, Haiyun Shi⁶

Affiliations

¹ State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
² State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Center for Climate Physics, Institute for Basic Science, Busan, Republic of Korea.
³ Yellow River Engineering Consulting Co. Ltd., Zhengzhou, 450003, China.
⁴ School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, China.
⁵ State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Department of Civil and Environmental Engineering, National University of Singapore, Singapore.
⁶ State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China. Electronic address: shihy@sustech.edu.cn.

PMID: 35303597
DOI: 10.1016/j.jenvman.2022.114879

Abstract

The increase in drought frequency in recent years is considered as an important factor affecting vegetation diversity. Understanding the responses of vegetation dynamics to drought is helpful to reveal the behavioral mechanisms of terrestrial ecosystems and propose effective drought control measures. In this study, long time series of Normalized Difference Vegetation Index (NDVI) and Solar-induced chlorophyll fluorescence (SIF) were used to analyze the vegetation dynamics in the Pearl River Basin (PRB). The relationship between vegetation and meteorological drought was evaluated, and the corresponding differences among different vegetation types were revealed. Based on an improved partial wavelet coherence (PWC) analysis, the influences of teleconnection factors (i.e., large-scale climate patterns and solar activity) on the response relationship between meteorological drought and vegetation were quantitatively analyzed to determine the roles of factors. The results indicate that (a) vegetation in the PRB showed an increasing trend from 2001 to 2019, and the SIF increased more than that of NDVI; (b) the vegetation response time (VRT) based on NDVI (VRT_N) was typically 4-6 months, while the VRT based on SIF (VRT_S) was typically 2-4 months. The VRT was shortest in the woody savannas and longest in the evergreen broadleaf forests. (c) The relationship between the SIF and meteorological drought was more significant than that between the NDVI and meteorological drought. (d) There was a significant positive correlation between meteorological drought and vegetation in the period of 8-20 years. The El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and sunspots were important driving factors affecting the response relationship between drought and vegetation. Specifically, the PDO had the greatest impacts among these factors.

Keywords: Meteorological drought; Normalized difference vegetation index; Partial wavelet coherence analysis; Solar-induced chlorophyll fluorescence; Vegetation dynamics.