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Remote sensing vegetation indices enhance understanding of the coupling of terrestrial ecosystem evapotranspiration and photosynthesis on a global scale
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  • Yun Bai,
  • Sha Zhang,
  • Jiahua Zhang,
  • Shanshan yang,
  • Jingwen Wang,
  • Enzo Magliulo,
  • Luca Vitale,
  • Yanchuang Zhao
Yun Bai
Qingdao University

Corresponding Author:[email protected]

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Sha Zhang
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences; University of Chinese Academy of Sciences
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Jiahua Zhang
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
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Shanshan yang
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences; University of Chinese Academy of Sciences
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Jingwen Wang
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences; University of Chinese Academy of Sciences
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Enzo Magliulo
CNR ISAFoM
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Luca Vitale
CNR Institute for Mediterranean Agricultural and Forest Systems
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Yanchuang Zhao
College of Information Science and Engineering, Henan University of Technology, 450001 Zhengzhou, PR China; Instituto Multidisciplinar para el Estudio del Medio "Ramón Margalef," Universidad de Alicante, 03690 San Vicente del Raspeig, Alicante, Spain.
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Abstract

The current approaches have known limitations to understanding the coupling of terrestrial ecosystem evapotranspiration (ET) and photosynthesis (referred to as gross primary productivity, GPP). To better characterize the relationship between ET and GPP, we developed a novel remote sensing (RS)-driven approach (RCEEP) based on the underlying water use efficiency (uWUE). RCEEP partitions transpiration (T) from ET using a RS vegetation index (VI)-derived ratio of T to ET (VI-fT) and then links T and GPP via RS VI-derived Gc (VI-Gc) rather than leaf-to-air vapor pressure difference. RCEEP and other two uWUE versions (VI-T or VI-G), which only incorporate VI-fT or VI-Gc , were evaluated and compared with the original uWUE model in terms of their performances (Nash-Sutcliffe efficiency, NSE) in estimating GPP from ET over 180 flux sites covering 11 biome types over the globe. Results revealed better performances of VI-T and VI-G compared to the original uWUE, implying remarkable contributions of VI-fT and VI-Gc to a more meaningful relationship between ET and GPP. RCEEP yielded the best performances with a reasonable mean NSE value of 0.70 (0.76) on a daily (monthly) scale and across all biome types. Further comparisons of RCEEP and approaches modified from recent studies revealed consistently better performances of RCEEP and thus, positive implications of introducing VI-fT and VI-Gc in bridging ecosystem ET and GPP. These results are promising in view of improving or developing algorithms on coupled estimates of ecosystem ET and GPP and understanding the GPP dynamics concerning ET on a global scale.