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GEE can prominently reduce uncertainties from input data and parameters of the remote sensing-driven distributed

Zihao Pan1, Shengtian Yang1, Xiaoyu Ren2

  • 1College of Water Science, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Urban Water Cycle and Sponge City Technology, Beijing 100875, China.

The Science of the Total Environment
|January 29, 2023
PubMed

Keywords:
Distributed hydrological modelEfficiency and uncertaintyGoogle Earth EngineRemote sensingRemote sensing hydrological station technology

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