Abstract
Terrestrial vegetation dynamics are closely influenced by both hydrological process and climate change. This study investigated the relationships between vegetation pattern and hydro-meteorological elements. The joint entropy method was employed to evaluate the dependence between the normalized difference vegetation index (NDVI) and coupled variables in the middle reaches of the Hei River basin. Based on the spatial distribution of mutual information, the whole study area was divided into five sub-regions. In each sub-region, nested statistical models were applied to model the NDVI on the grid and regional scales, respectively. Results showed that the annual average NDVI increased at a rate of 0.005/a over the past 11 years. In the desert regions, the NDVI increased significantly with an increase in precipitation and temperature, and a high accuracy of retrieving NDVI model was obtained by coupling precipitation and temperature, especially in sub-region I. In the oasis regions, groundwater was also an important factor driving vegetation growth, and the rise of the groundwater level contributed to the growth of vegetation. However, the relationship was weaker in artificial oasis regions (sub-region III and sub-region V) due to the influence of human activities such as irrigation. The overall correlation coefficient between the observed NDVI and modeled NDVI was observed to be 0.97. The outcomes of this study are suitable for ecosystem monitoring, especially in the realm of climate change. Further studies are necessary and should consider more factors, such as runoff and irrigation.
Highlights
Terrestrial vegetation plays a key role in energy, water, and biogeochemical cycles, while variation in vegetation can significantly influence atmospheric and hydrological processes
Considering the nonlinear relationship between hydro-meteorological variables, the entropy theory was employed to calculate the mutual information between the normalized difference vegetation index (NDVI) time series and coupled hydro meteorological variables
Based on the spatial distribution of mutual information, the whole region was further divided into 5 sub-regions, and nested statistical models were employed to simulate NDVI in each sub-region
Summary
Terrestrial vegetation plays a key role in energy, water, and biogeochemical cycles, while variation in vegetation can significantly influence atmospheric and hydrological processes. Vegetation is a sensitive indicator of global change and can be a natural link between the atmosphere, land surface, soil, and water [1,2]. Changes in vegetation cover are influenced by climate change, human activities, and the atmospheric CO2 fertilization effect [3,4,5]. It is necessary to explore the response mechanism of vegetation dynamics to hydrological processes and climate change. Vegetation emergence and senescence are closely related to characteristics of the lower atmosphere, including the annual cycle of weather pattern shifts, temperature and precipitation [6]. The amount and duration of precipitation and temperature play a significant role in controlling vegetation
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