Reference:Reference-014667
From CSDMS
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
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Feature reference | No |
PublicationClusterID | 0 |
MS_PublicationClusterID | 3161929512 |
Semantic_ID | 0b1b1bfe7129ad9a906217ffe273ebc8cf2b7efe |
Nr of citations | 16 |
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: |
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Model(s) discussed: | CREST |