Diurnal Vegetation Moisture Dynamics and Water Stress: Insights from GNSS Reflectometry-Derived Vegetation Water Content

crossref(2024)

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摘要
The dynamics of Vegetation Water Content (VWC) throughout the day reflect how plants cope with water stress, trying to replenish lost water during daylight hours. Traditional radar sensors have shown sensitivity to diurnal vegetation moisture fluctuations but struggle due to their limited sampling rates, making it difficult to monitor daily patterns effectively. Innovations like Global Navigation Satellite Systems Reflectometry (GNSS-R) present a promising solution to overcome these limitations. In this study, we leverage GNSS-R measurements from the NASA Cyclone (CYGNSS) mission, launched in late 2016, to study diurnal VWC cycles in Amazon's evergreen forests. CYGNSS offers high sampling rates and increased sensitivity to VWC, penetrating vegetation layers effectively with longer L-band wavelengths. The eight satellites of CYGNSS provide frequent measurements in tropical regions across different times of the day. Our results uncover distinct differences between morning and evening VWCs over Amazon. We have observed a strong correlation (R = 0.75) between VWC and Vapor Pressure Deficit (VPD) throughout 2019, indicating VPD as a crucial factor influencing water stress. The diurnal VWC cycles in the Amazonian peatland demonstrate disruptions during arid periods and emphasize the significant role of VPD in governing vegetation diurnal moisture dynamics. Our findings bridge the information gap on water stress in vegetation, showing the potential of VWC derived from advanced remote sensing technologies. It complements in-situ data on water potential gradients, offering valuable insights into vegetation water status in these critical ecosystems.
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