Reference:Reference-014667: Difference between revisions

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|PublicationClusterID=0
|PublicationClusterID=0
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|MS_PublicationClusterID=3161929512
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|Semantic_ID=0b1b1bfe7129ad9a906217ffe273ebc8cf2b7efe |CorpusID=236313868
|CorpusID=236313868
|PublicationWhatKindOf=a module application description
|PublicationWhatKindOf=a module application description
|PublicationNrofModels=a single module
|PublicationNrofModels=a single module

Latest revision as of 11:29, 8 October 2024



Author(s) Kim, Taereem; Yang, Tiantian; Gao, Shang; Zhang, Lujun; Ding, Ziyu; Wen, Xin; Gourley, Jonathan J.; Hong, Yang;
BibType journalArticle
Title Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS
Editors
Year 2021-07
Journal Journal of Hydrology
Booktitle
Volume 598
Pages 126423
URL https://linkinghub.elsevier.com/retrieve/pii/S0022169421004704
DOI 10.1016/j.jhydrol.2021.126423
ISBN
Note Auto downloaded ref at: 2021-07-03


 
Feature reference No
PublicationClusterID 0
MS_PublicationClusterID 3161929512
Semantic_ID 0b1b1bfe7129ad9a906217ffe273ebc8cf2b7efe
Nr of citations 70
Sort of publication a module application description
Sort of model publication a single module
Is the CSDMS HPC used No
If HPC is used, for what project was it?:
Associated simulation movie if any:


Model(s) discussed: CREST