Time-Lag Effect of Vegetation Response to Volumetric Soil Water Content: A Case Study of Guangdong Province, Southern China

Abstract

The content of soil water affects the physiological activities of vegetation, and the type of vegetation also affects the soil water balance. It is of great significance to study the response of vegetation to soil moisture change, which is helpful for understanding the vulnerability of vegetation for regional and environmental protections. The response of vegetation to soil moisture in Guangdong Province from mid-October 2015 to the end of March 2017 was studied by using cloudy region drought index (CRDI) as the drought index and volumetric soil water content (VSWC) as the soil moisture index to measure the level of water stress on vegetation. Taking the peak and valley positions of CRDI and VSWC as characteristic points, the lag time of vegetation to volumetric soil water content was obtained by judging the difference between the peak and valley positions of the two indexes. The results indicate that the response of vegetation to volumetric soil water content in Guangdong lagged 3.33 periods (9–35 days) on average. When VSWC is sufficient, there is no obvious difference in time-lag between different types of vegetation. However, when VSWC is relatively insufficient, grass shows the fastest response to the change of volumetric soil water content. Both longitude and soil moisture affect the lag time of vegetation. Under the same conditions, the higher the soil humidity is, the longer the lag time is, and the longer the delay time is with the greater longitude. CRDI can reflect the time-lag effect between vegetation and VSWC in Guangdong, indicating it is a sensitive and applicable index for characterizing the time-lag phenomena of vegetation to soil moisture.

Sensitivity of the land surface temperature and NDWI index to soil moisture on wheat and barley

“…Under controlled irrigation, Liu et al (2018) found that SIF and indices calculated at wavelengths between 680 nm and 750 nm are related to soil moisture at different depths and exhibit different response times on wheat. Therefore, it should be noted that the responses of spectral indices to soil water profile and response times depend on the climatic regimes of the study area, the type of vegetation and its phenological stage, the depth and distribution of the roots, the soil physical characteristics and the spatial scale of the observation (Celik et al 2022;Li et al 2022;Liu et al 2018;Pablos et al 2014).…”

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

“…The time lag effect is a key characteristic in the interaction between SM and vegetation. This means local SM (vegetation) may have a closer connection with temporarily lagging vegetation (SM) [7,13]. Li et al [14] concluded that moist soil can promote sequential vegetation growth.…”

Estimation of Soil Moisture Using Multi-Source Remote Sensing and Machine Learning Algorithms in Farming Land of Northern China

“…The soil moisture content within the root zone (0-15 cm) exerts a profound influence on crop physiological states. Theoretically, it can be indirectly assessed through the analysis of crop canopy reflectance or vegetation indices [14,15]. The relationship between soil moisture content and vegetation spectra is intricate, posing challenges for classical regression methods in achieving unbiased and effective parameter estimation [16,17].…”