Academic Journal
An Open‐Source Python Library for Varying Model Parameters and Automating Concurrent Simulations of the National Water Model.
| Τίτλος: | An Open‐Source Python Library for Varying Model Parameters and Automating Concurrent Simulations of the National Water Model. |
|---|---|
| Συγγραφείς: | Raney, Austin, Maghami, Iman, Feng, Yenchia, Mandli, Kyle, Cohen, Sagy, Goodall, Jonathan |
| Πηγή: | Journal of the American Water Resources Association; Feb2022, Vol. 58 Issue 1, p75-85, 11p |
| Θεματικοί όροι: | Python programming language, Meteorological research, Hydrologic models, Hydrological forecasting, Weather forecasting |
| Περίληψη: | The National Water Model (NWM), a configuration of the Weather Research and Forecasting Hydrological model, operates as the United States' hydrological model. The NWM predicts streamflow at more than 2.7 million river reaches; and is a subject of growing attention in the hydrological modeling community. Large‐scale computationally distributed models such as the NWM, often require technical knowledge of, and access to, cluster‐based computing environments for model compilation and simulation. User‐friendly tools capable of setting up and running such models to adjust and explore their parameter space generally do not exist. Here we present the Dockerized Job Scheduler (DJS) a Python library that takes a service approach to modeling. The library is capable of (1) generating varied parameter sets and (2) orchestrating concurrent NWM simulations via Docker. DJS is designed to automate the deployment of varied parameter simulations and lower the model usage entrance barrier. In this paper, we use a case study to demonstrate its installation and usage. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of the American Water Resources Association is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Biomedical Index |
| FullText | Links: – Type: other Text: Availability: 0 |
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| Header | DbId: edm DbLabel: Biomedical Index An: 155397434 RelevancyScore: 916 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 915.914001464844 |
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| Items | – Name: Title Label: Title Group: Ti Data: An Open‐Source Python Library for Varying Model Parameters and Automating Concurrent Simulations of the National Water Model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Raney%2C+Austin%22">Raney, Austin</searchLink><br /><searchLink fieldCode="AR" term="%22Maghami%2C+Iman%22">Maghami, Iman</searchLink><br /><searchLink fieldCode="AR" term="%22Feng%2C+Yenchia%22">Feng, Yenchia</searchLink><br /><searchLink fieldCode="AR" term="%22Mandli%2C+Kyle%22">Mandli, Kyle</searchLink><br /><searchLink fieldCode="AR" term="%22Cohen%2C+Sagy%22">Cohen, Sagy</searchLink><br /><searchLink fieldCode="AR" term="%22Goodall%2C+Jonathan%22">Goodall, Jonathan</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of the American Water Resources Association; Feb2022, Vol. 58 Issue 1, p75-85, 11p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink><br /><searchLink fieldCode="DE" term="%22Meteorological+research%22">Meteorological research</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrologic+models%22">Hydrologic models</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrological+forecasting%22">Hydrological forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Weather+forecasting%22">Weather forecasting</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The National Water Model (NWM), a configuration of the Weather Research and Forecasting Hydrological model, operates as the United States' hydrological model. The NWM predicts streamflow at more than 2.7 million river reaches; and is a subject of growing attention in the hydrological modeling community. Large‐scale computationally distributed models such as the NWM, often require technical knowledge of, and access to, cluster‐based computing environments for model compilation and simulation. User‐friendly tools capable of setting up and running such models to adjust and explore their parameter space generally do not exist. Here we present the Dockerized Job Scheduler (DJS) a Python library that takes a service approach to modeling. The library is capable of (1) generating varied parameter sets and (2) orchestrating concurrent NWM simulations via Docker. DJS is designed to automate the deployment of varied parameter simulations and lower the model usage entrance barrier. In this paper, we use a case study to demonstrate its installation and usage. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of the American Water Resources Association is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/1752-1688.12973 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 75 Subjects: – SubjectFull: Python programming language Type: general – SubjectFull: Meteorological research Type: general – SubjectFull: Hydrologic models Type: general – SubjectFull: Hydrological forecasting Type: general – SubjectFull: Weather forecasting Type: general Titles: – TitleFull: An Open‐Source Python Library for Varying Model Parameters and Automating Concurrent Simulations of the National Water Model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Raney, Austin – PersonEntity: Name: NameFull: Maghami, Iman – PersonEntity: Name: NameFull: Feng, Yenchia – PersonEntity: Name: NameFull: Mandli, Kyle – PersonEntity: Name: NameFull: Cohen, Sagy – PersonEntity: Name: NameFull: Goodall, Jonathan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 1093474X Numbering: – Type: volume Value: 58 – Type: issue Value: 1 Titles: – TitleFull: Journal of the American Water Resources Association Type: main |
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