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Open AccessArticle

OpenForecast: The First Open-Source Operational Runoff Forecasting System in Russia

1
Institute for Environmental Sciences and Geography, University of Potsdam, Potsdam 14476, Germany
2
Water Problems Institute of Russian Academy of Sciences, Moscow 119333, Russia
3
Central Administration for Hydrometeorology and Ecology Monitoring (FSBI CAHEM), Moscow 123995, Russia
4
Department of Hydrology, Lomonosov Moscow State University, Moscow 119991, Russia
5
State Hydrological Institute, Saint Petersburg 199004, Russia
*
Author to whom correspondence should be addressed.
Water 2019, 11(8), 1546; https://doi.org/10.3390/w11081546
Received: 3 June 2019 / Revised: 22 July 2019 / Accepted: 24 July 2019 / Published: 26 July 2019
(This article belongs to the Special Issue Hydrologic Modelling for Water Resources and River Basin Management)
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 operational runoff forecasting system provided a foundation to outline its further development and improvement. View Full-Text
Keywords: OpenForecast; open; operational service; runoff; forecasting; Russia OpenForecast; open; operational service; runoff; forecasting; Russia
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MDPI and ACS Style

Ayzel, G.; Varentsova, N.; Erina, O.; Sokolov, D.; Kurochkina, L.; Moreydo, V. OpenForecast: The First Open-Source Operational Runoff Forecasting System in Russia. Water 2019, 11, 1546.

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