The PAVICS-Hydro platform: A virtual laboratory for hydroclimatic modelling and forecasting over North America

This paper presents the PAVICS-Hydro platform, the result of long-term strategic considerations and compromises between functionality and ease-of-use, which is developed to provide users with direct access to a comprehensive hydroclimatic modeling and analysis framework over North America. This incl...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2023-10, Vol.168, p.105808, Article 105808
Hauptverfasser: Arsenault, Richard, Huard, David, Martel, Jean-Luc, Troin, Magali, Mai, Juliane, Brissette, François, Jauvin, Christian, Vu, Long, Craig, James R., Smith, Trevor J., Logan, Travis, Tolson, Bryan A., Han, Ming, Gravel, Francis, Langlois, Sébastien
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Sprache:eng
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Zusammenfassung:This paper presents the PAVICS-Hydro platform, the result of long-term strategic considerations and compromises between functionality and ease-of-use, which is developed to provide users with direct access to a comprehensive hydroclimatic modeling and analysis framework over North America. This includes a Python hydrological modelling package, efficient access to meteorological data, a large array of post-processed hydroclimatic data, numerical weather forecasts and bias-corrected CMIP6 climate projections at the scale of 5797 catchments, thus providing the basic components necessary for hydrological modeling and forecasting, as well as climate change impact studies. This paper presents the principles on which the PAVICS-Hydro platform was developed while explaining the choices behind its key features, with a specific focus on lessons learned for creators of the next generations’ scientific research platforms. A case study using PAVICS-Hydro is given to illustrate how this platform can be used to support different needs in the field of water resources. •We present the PAVICS-Hydro platform for hydrological modelling and research.•The platform can be used for simulation, forecasting and climate change studies.•It helps automate repetitive tasks such as model building and data processing.•Access to multiple large-scale hydrometeorological and climate datasets is provided.•The platform is built on open-source software and free to use.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2023.105808