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Dmitriy Sokolov
Lomonosov Moscow State University, Faculty of Geography, GSP-1, 1 Leninskiye Gory, 119991, Moscow, Russia

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Conference paper
Published: 17 April 2020 in E3S Web of Conferences
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In 2019, we conducted an integrated study on the Moskva River and its tributaries during the low summer season with a focus on organic matter content (OM) assessment in river waters. The maximum OM content was measured at the river headwaters and related to natural sources. The Mozhaysk Reservoir regulation in the summer had the effect of increased organic load below the dam due to a rise in the allochthonous labile OM. Upstream from the Moscow City, the OM content was relatively low, despite wastewater inflow from several densely populated areas and polluted river inflow. Within the city, organic matter concentration increased by a factor of 1.5 due to an inflow from the Volga River via the Moskva-Volga Canal, whereas the release of treated sewage from the Moscow City wastewater treatment facilities did not have a significant effect. Below the city, the OM content increased again by a factor of 1.5 due to the inflow of urban and industrial wastewater and polluted tributaries. The observations in the lower reaches of the Moskva River indicate a high degree of anthropogenic euthrophication.

ACS Style

Dmitriy Sokolov; Oxana Erina; Maria Tereshina; Sergey Chalov. Human impact on organic matter distribution in the Moskva River. E3S Web of Conferences 2020, 163, 05013 .

AMA Style

Dmitriy Sokolov, Oxana Erina, Maria Tereshina, Sergey Chalov. Human impact on organic matter distribution in the Moskva River. E3S Web of Conferences. 2020; 163 ():05013.

Chicago/Turabian Style

Dmitriy Sokolov; Oxana Erina; Maria Tereshina; Sergey Chalov. 2020. "Human impact on organic matter distribution in the Moskva River." E3S Web of Conferences 163, no. : 05013.

Journal article
Published: 26 July 2019 in Water
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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.

ACS Style

Georgy Ayzel; Natalia Varentsova; Oxana Erina; Dmitriy Sokolov; Liubov Kurochkina; Vsevolod Moreydo. OpenForecast: The First Open-Source Operational Runoff Forecasting System in Russia. Water 2019, 11, 1546 .

AMA Style

Georgy Ayzel, Natalia Varentsova, Oxana Erina, Dmitriy Sokolov, Liubov Kurochkina, Vsevolod Moreydo. OpenForecast: The First Open-Source Operational Runoff Forecasting System in Russia. Water. 2019; 11 (8):1546.

Chicago/Turabian Style

Georgy Ayzel; Natalia Varentsova; Oxana Erina; Dmitriy Sokolov; Liubov Kurochkina; Vsevolod Moreydo. 2019. "OpenForecast: The First Open-Source Operational Runoff Forecasting System in Russia." Water 11, no. 8: 1546.