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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
DOI:https://doi.org/10.3390/w11081546
ISSN:2073-4441
Titel des übergeordneten Werks (Englisch):Water : Molecular Diversity Preservation International
Untertitel (Englisch):The First Open-Source Operational Runoff Forecasting System in Russia
Verlag:MDPI
Verlagsort:Basel
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:26.07.2019
Erscheinungsjahr:2019
Datum der Freischaltung:14.12.2020
Freies Schlagwort / Tag:OpenForecast; Russia; forecasting; open; operational service; runoff
Band:11
Ausgabe:8
Seitenanzahl:17
Fördernde Institution:Russian Foundation for Basic Research (RFBR)Russian Foundation for Basic Research (RFBR) [19-05-00087 A]; Russian Science FoundationRussian Science Foundation (RSF) [16-17-10039]; Geo. X, the Research Network for Geosciences in Berlin and Potsdam
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Publikationsweg:Open Access / Gold Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
Externe Anmerkung:Zweitveröffentlichung in der Schriftenreihe Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 1338
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