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

Ayzel, Georgy; Varentsova, Natalia; Erina, O.; Соколов, Д. И.; Kurochkina, L. Ya.; Moreydo, Vsevolod

doi:10.3390/w11081546

Cited by 14 publications

(21 citation statements)

References 46 publications

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“…In [29] NARR, ERA-Interim, CFSR, and MERRA reanalyses data were used for the calibration of the hydrological model and for the simulation of river flows over 370 watersheds in the continental part of the United States. In [30] operational runoff forecasting systems were developed for early warnings of floods and flashfloods for the European part of Russia using ERA-Interim reanalysis. In [31] five datasets and reanalyses were tested and used for the modelling of discharges in the Mekong river basin.…”

Section: Introductionmentioning

confidence: 99%

Modelling of Surface Runoff on the Yamal Peninsula, Russia, Using ERA5 Reanalysis

Matveeva

Sidorchuk

2020

Water

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The Yamal peninsula is a territory of active industrial development as it contains several rich fields of natural condensed gas and oil. The density of the gullies net on the Yamal peninsula is one of the highest in the Russian Arctic. The natural environment or constructions can be potentially damaged by gully erosion and the cost of such damage is high. The models of gully erosion require surface runoff estimates. The hydrological model was developed for surface runoff estimation during the spring snow thaw and summer rains. In the conditions of Arctic climate with deep permafrost, the losses in runoff are limited to evaporation, as soil permeability is negligible. The model was calibrated on the available measurements. The meteorological base for hydrological calculations was ERA5 reanalysis, the fifth generation of European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses, validated on the meteorological data. The deviations of reanalysis data from the measurements cause the errors in the results of surface runoff calculation. The daily surface runoff can vary in the range of 18–30% due to ERA5 errors in air temperature and snow cover depth. As the daily surface runoff is the main input to the models of gully erosion, these errors must be taken into account in the modelling of gully erosion on the Yamal peninsula.

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Section: Introductionmentioning

confidence: 99%

Modelling of Surface Runoff on the Yamal Peninsula, Russia, Using ERA5 Reanalysis

Matveeva

Sidorchuk

2020

Water

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“…The ranges of the GR4J parameters correspond to the 80% confidence intervals obtained by Perrin et al [56] calibrating the model over 429 catchments worldwide. The ranges of the CemaNeige model parameters are those suggested by Ayzel et al [91] for Kf and Ctg. For the accumulation threshold (X7-Tacc), the mean annual snowfall of the lower elevation layer was considered to be the maximum value of the range (minimum zero).…”

Section: Model Calibration and Validationmentioning

confidence: 76%

Nossana Spring (Northern Italy) under Climate Change: Projections of Future Discharge Rates and Water Availability

Citrini

Camera

Beretta

2020

Water

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Nossana represents an important pre-Alpine karst spring for drinking supply, sustaining a water distribution system serving 300,000 people. The goal of this study was to project Nossana discharges and evaluate potential supply limits for four future periods (2021–2040, 2041–2060, 2061–2080, 2081–2100). Bias-corrected Regional Climate Models (RCMs), part of the EURO-CORDEX experiment and forced by three emission scenarios (RCP2.6, RCP4.5, RCP8.5), were evaluated, statistically downscaled, and used as input in a calibrated rainfall-runoff model ensemble. For each emission scenario, the calibrated model ensemble considered three RCMs and ten rainfall-runoff parameterizations. Projected ensemble mean discharges are lower than observations (3%–23%) for all RCPs, though they do not show a clear trend between the four time periods. Days characterized by discharges lower than actual water demand are projected to decrease, except for the RCP8.5 emission scenarios and the period 2081–2100. Conversely, the same consecutive days are expected to increase after 2060 for all emission scenarios. These results reflect the projected precipitation trend, characterized by longer, drier summer periods and wetter autumns in comparison to today’s climate. Also, they indicate a possible need for alternative drinking water resources. The proposed methodology was demonstrated to deliver useful quantitative information for water management in the mid- long-term period.

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“…Russia has over 90 satellites that were initiated between 1972 and 2003 to form the early warning system's satellite constellation (Paleologue, 2005). It is signi cant to mention that there are different platforms, and one of them is the rst operational runoff forecasting system in Russia which is open forecast based only on open-source software and data-GR4J hydrological model, ERA-Interim meteorological reanalysis, and ICON deterministic short-range meteorological forecasts (Ayzel et al, 2019).…”

Section: Practice and Solutions In Warning Systemsmentioning

confidence: 99%

Innovative Solutions for Disaster Early Warning and Alert Systems: A Literary Review

Cvetković

2021

Preprint

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In different parts of the world, decision-makers and risk managers use specific and particularly complex disaster early warning and alert systems to protect people and their material goods from the harmful effects of various disasters in a timely, efficient and appropriate manner. However, concerning the level of scientific-technological and economic development of certain countries, such systems can differ in the many characteristics that make them more efficient in specific situations. Guided by this, the subject of the paper is reflected in the systematic identification, analysis, and classification of the best innovative solutions of early warning systems regarding their usability and efficiency. To find appropriate innovative solutions, it was performed a search of different electronic databases. The findings of this review showed that there is a huge potential for innovative solutions in the field of disaster early warning and alert systems.

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

Cited by 14 publications

References 46 publications

Modelling of Surface Runoff on the Yamal Peninsula, Russia, Using ERA5 Reanalysis

Modelling of Surface Runoff on the Yamal Peninsula, Russia, Using ERA5 Reanalysis

Nossana Spring (Northern Italy) under Climate Change: Projections of Future Discharge Rates and Water Availability

Innovative Solutions for Disaster Early Warning and Alert Systems: A Literary Review

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