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RSS FeedsRemote Sensing, Vol. 15, Pages 767: Spatio-Temporal Changes in Water Use Efficiency and Its Driving Factors in Central Asia (2001–2021) (Remote Sensing)


29 january 2023 07:56:09

Remote Sensing, Vol. 15, Pages 767: Spatio-Temporal Changes in Water Use Efficiency and Its Driving Factors in Central Asia (2001–2021) (Remote Sensing)

Although understanding the carbon and water cycles of dryland ecosystems in terms of water use efficiency (WUE) is important, WUE and its driving mechanisms are less understood in Central Asia. This study calculated Central Asian WUE for 2001–2021 based on the Google Earth Engine (GEE) platform and analyzed its spatial and temporal variability using temporal information entropy. The importance of atmospheric factors, hydrological factors, and biological factors in driving WUE in Central Asia was also explored using a geographic detector. The results show the following: (1) the average WUE in Central Asia from 2001–2021 is 2.584–3.607 gCkg−1H2O, with weak inter-annual variability and significant intra-annual variability and spatial distribution changes; (2) atmospheric and hydrological factors are strong drivers, with land surface temperature (LST) being the strongest driver of WUE, explaining 54.8% of variation; (3) the interaction of the driving factors can enhance the driving effect by more than 60% for the interaction between most atmospheric factors and vegetation factors, of which the effect of the interaction of temperature (TEM) with vegetation cover (FVC) is the greatest, explaining 68.1% of the change in WUE. Furthermore, the interaction of driving factors with very low explanatory power (e.g., water pressure (VAP), aerosol optical depth over land (AOD), and groundwater (GWS)) has a significant enhancement effect. Vegetation is an important link in driving WUE, and it is important to understand the mechanisms of WUE change to guide ecological restoration projects.

80 viewsCategory: Geology, Physics
Remote Sensing, Vol. 15, Pages 766: Editorial for Special Issue “Remote Sensing for Coastal and Aquatic Ecosystems’ Monitoring and Biodiversity Management” (Remote Sensing)
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