Informing the SWAT model with remote sensing detected vegetation phenology for improved modeling of ecohydrological processes
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Originalsprog | Engelsk |
---|---|
Artikelnummer | 128817 |
Tidsskrift | Journal of Hydrology |
Vol/bind | 616 |
Antal sider | 13 |
ISSN | 0022-1694 |
DOI | |
Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
This study was supported by the joint fund for regional innovation and development of NSFC (Grant No. U21A2039), the Distinguished Young Scholars (42025101), International Cooperation and Exchanges NSFC-STINT (42111530181) and the 111 Project (B18006). The authors gratefully acknowledge all members of the Hydrological Yearbook of the People’s Republic of China for providing the in situ runoff data. Dr. Xuesong Zhang is supported USDA-ARS. We thank Yishuo Cui and James Buxton from Liwen Bianji (Edanz) for editing the English text of this manuscript. We appreciate the associate editor and the reviewers’ constructive comments and helpful suggestions.
Funding Information:
This study was supported by the joint fund for regional innovation and development of NSFC (Grant No. U21A2039), the Distinguished Young Scholars (42025101), International Cooperation and Exchanges NSFC-STINT (42111530181) and the 111 Project (B18006). The authors gratefully acknowledge all members of the Hydrological Yearbook of the People's Republic of China for providing the in situ runoff data. Dr. Xuesong Zhang is supported USDA-ARS. We thank Yishuo Cui and James Buxton from Liwen Bianji (Edanz) for editing the English text of this manuscript. We appreciate the associate editor and the reviewers’ constructive comments and helpful suggestions.
Publisher Copyright:
© 2022 Elsevier B.V.
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