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The Time Lag Effects and Interaction among Climate, Soil Moisture, and Vegetation from In Situ Monitoring Measurements across China

Authors :
Jie Wang
Zhenxin Bao
Guoqing Wang
Cuishan Liu
Mingming Xie
Bin Wang
Jianyun Zhang
Source :
Remote Sensing, Vol 16, Iss 12, p 2063 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The interaction between soil moisture (SM) and vegetation dynamics has been proven in previous studies. In situ measurements have provided reliable data to investigate and validate the time effect in different zones, which is important in the hydrology and agriculture fields. There were 845 SM in situ monitoring measurements utilized with the correlation between SM and vegetation across various soil depths and climate zones in China. The impact of climate and teleconnection factors on SM and the leaf area index (LAI) are also discussed. The results indicate that SM increases from northwest to southeast in China. The time lag responses of SM to temperature, precipitation, relative humidity, and sunshine duration are 0–3 days, 3–7 days, 1–3 days, and 3–15 days, respectively. The LAI is most strongly correlated with the climate of the current month. When the LAI leads SM, a negative correlation is observed, whereas a positive correlation is observed when SM leads the LAI. This proves that vegetation growth restricts the increase in SM, and soil drying further restricts the growth of vegetation. There was a response time of 2–4 months between the LAI and SM. The effect of vegetation and deeper SM was significant in the arid zone, while they were coupled with shallow SM in the humid zone. Additionally, the El Niño–Southern Oscillation (ENSO) showed a significant positive correlation with SM in 2015–2016 with signals of 9–14 months. The results provide support for balancing the contradiction between future vegetation restoration and water resource scarcity.

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.79d25944912649df8e528eb9542e3c67
Document Type :
article
Full Text :
https://doi.org/10.3390/rs16122063