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OpenForecast

  • The development and deployment of new operational runoff forecasting systems are a strong focus of the scientific community due to the crucial importance of reliable and timely runoff predictions for early warnings of floods and flashfloods for local businesses and communities. OpenForecast, the first operational runoff forecasting system in Russia, open for public use, is presented in this study. We developed OpenForecast based only on open-source software and data-GR4J hydrological model, ERA-Interim meteorological reanalysis, and ICON deterministic short-range meteorological forecasts. Daily forecasts were generated for two basins in the European part of Russia. Simulation results showed a limited efficiency in reproducing the spring flood of 2019. Although the simulations managed to capture the timing of flood peaks, they failed in estimating flood volume. However, further implementation of the parsimonious data assimilation technique significantly alleviates simulation errors. The revealed limitations of the proposed operationalThe development and deployment of new operational runoff forecasting systems are a strong focus of the scientific community due to the crucial importance of reliable and timely runoff predictions for early warnings of floods and flashfloods for local businesses and communities. OpenForecast, the first operational runoff forecasting system in Russia, open for public use, is presented in this study. We developed OpenForecast based only on open-source software and data-GR4J hydrological model, ERA-Interim meteorological reanalysis, and ICON deterministic short-range meteorological forecasts. Daily forecasts were generated for two basins in the European part of Russia. Simulation results showed a limited efficiency in reproducing the spring flood of 2019. Although the simulations managed to capture the timing of flood peaks, they failed in estimating flood volume. However, further implementation of the parsimonious data assimilation technique significantly alleviates simulation errors. The revealed limitations of the proposed operational runoff forecasting system provided a foundation to outline its further development and improvement.zeige mehrzeige weniger

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Verfasserangaben:Georgy AyzelORCiD, Natalia VarentsovaORCiD, Oxana ErinaORCiD, Dmitriy SokolovORCiD, Liubov KurochkinaORCiD, Vsevolod MoreydoORCiD
URN:urn:nbn:de:kobv:517-opus4-473295
DOI:https://doi.org/10.25932/publishup-47329
ISSN:1866-8372
Titel des übergeordneten Werks (Englisch):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Untertitel (Englisch):The First Open-Source Operational Runoff Forecasting System in Russia
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (1338)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:26.07.2019
Erscheinungsjahr:2019
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:14.07.2023
Freies Schlagwort / Tag:OpenForecast; Russia; forecasting; open; operational service; runoff
Ausgabe:1338
Seitenanzahl:17
Quelle:Water 11 (2019) 8 DOI: 10.3390/w11081546
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Publikationsweg:Open Access / Green Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
Externe Anmerkung:Bibliographieeintrag der Originalveröffentlichung/Quelle
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