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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| Highlighted paper on group site | ||
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| Which groups | ||
| 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: |
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| Model(s) discussed: | CREST |
