Bidirectional dependency between vegetation and terrestrial water storage in China

归一化差异植被指数 增强植被指数 植被(病理学) 环境科学 干旱 背景(考古学) 陆地生态系统 滞后 生态系统 自然地理学 气候学 气候变化 地质学 植被指数 生态学 地理 海洋学 计算机科学 生物 病理 医学 古生物学 计算机网络
作者
Jianyong Xiao,Binggeng Xie,Kaichun Zhou,Chao Liang,Junhan Li,Jing Xie,Xuemao Zhang
出处
期刊:Journal of Hydrology [Elsevier]
卷期号:626: 130313-130313 被引量:8
标识
DOI:10.1016/j.jhydrol.2023.130313
摘要

Alterations in water availability strongly impact vegetation growth, and vegetation could affect terrestrial water storage (TWS) by altering surface hydrological processes. Understanding the relationships between vegetation change and terrestrial water conditions in ecosystems is crucial. In the research, the partial correlation was implemented to identify time-lag effects and revealed a non-linear interaction between TWS and the normalized difference vegetation index (NDVI) using the Granger causality approach. The results showed that most vegetation in China underwent significant greening from January 2003 to December 2020, and TWS showed a spatial distribution pattern of increasing in the south and decreasing in the north. TWS and NDVI both had significant mutual lag responses. The proportion of the area with a significant correlation between TWS and NDVI increased from 42 % to 63 % after considering the time-lag effect. NDVI was generally influenced by TWS, with 55 % of TWS in the vegetation cover of China having a causal effect on NDVI; conversely, two different vegetation greening methods regulated TWS in vegetated areas in China, and > 59 % of TWS changes were dependent on NDVI. The effect of vegetation dynamics on surface hydrological processes may increase with increasing aridity. Determining the existence of Granger causality between NDVI and TWS has significant implications in terms of comprehending the relationships between terrestrial vegetation and water within the context of a changing climate and for the sustainable use of carbon–water cycle ecosystem services.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI2S应助妮妮采纳,获得10
刚刚
刚刚
1秒前
1秒前
1秒前
今后应助九宫格采纳,获得10
2秒前
裴瑞志发布了新的文献求助10
2秒前
2秒前
要减肥的宝贝完成签到,获得积分10
4秒前
homeless发布了新的文献求助10
5秒前
6秒前
英吉利25发布了新的文献求助10
6秒前
CWNU_HAN发布了新的文献求助20
7秒前
CodeCraft应助ming采纳,获得10
7秒前
7秒前
Lee发布了新的文献求助10
7秒前
慕青应助yun采纳,获得10
7秒前
7秒前
慕青应助Ren采纳,获得10
8秒前
8秒前
妮妮完成签到,获得积分10
9秒前
9秒前
鹤轩发布了新的文献求助10
10秒前
无花果应助krislan采纳,获得10
10秒前
10秒前
12秒前
暮寻屿苗完成签到,获得积分10
12秒前
远志发布了新的文献求助10
12秒前
哈哈发布了新的文献求助10
13秒前
gladuhere完成签到 ,获得积分10
13秒前
杨羽完成签到,获得积分10
14秒前
小波发布了新的文献求助10
15秒前
15秒前
妮妮发布了新的文献求助10
15秒前
暮寻屿苗发布了新的文献求助30
16秒前
16秒前
17秒前
17秒前
叛逆黑洞完成签到 ,获得积分10
17秒前
lurenxin完成签到,获得积分10
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Kinesiophobia : a new view of chronic pain behavior 5000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6019772
求助须知:如何正确求助?哪些是违规求助? 7614944
关于积分的说明 16163093
捐赠科研通 5167540
什么是DOI,文献DOI怎么找? 2765662
邀请新用户注册赠送积分活动 1747539
关于科研通互助平台的介绍 1635688