SHS Web of Conf.
Volume 164, 202311th International Scientific and Practical Conference “Current Issues of Linguistics and Didactics: The Interdisciplinary Approach in Humanities and Social Sciences” (CILDIAH-2022)
|Number of page(s)||4|
|Published online||11 May 2023|
- Z.F. Khakimova, N.R. Sobirova, Issues of long-term forecasts of mountain river runoff for the growing season. In: Use of water resources in the context of climate change (Ufa, Bashkir State Agrar. Univ., 2022) [Google Scholar]
- E.A. Semenchin, N.G. Titov, M.M. Kuzyakina, K.A. Lebedev, Comparative analysis of methods of mathematical modeling of the water level in the river mountain type (for example, the river Mzymta). Kuban State Univ. 12-5, 952–957 (2014) [Google Scholar]
- N.G. Titov, M.V. Kuzyakina, K.A. Lebedev, Applying the Markov equation to predicting the water level in a river with a steep dip. Sci. almanac 9(11), 1126–1129 (2015). DOI: 10.17117/na.2015.09.1126 [Google Scholar]
- Zh.Zh. Karamoldoev, O.Yu. Kalashnikova, Forecast of water inflow into the Toktogul reservoir for the growing season. Bishkek: Bull. of BSU 3(23), 146–150 (2012) [Google Scholar]
- V.P. Galakhov, O.V. Lovtskaya, S.Yu. Samoilova, E.V. Mardasova, Comparative analysis of methods for forecasting maximum levels and volumes of flood runoff of a mountain river. Bull. of the Tomsk Polyt. Univ. Georesource engin. 2, 193–203 (2022). DOI: 10.18799/24131830/2022/2/3438 [Google Scholar]
- V.M. Mukhin, Methodological bases of physical and statistical types of short-term forecasts of mountain river runoff. Proc. of the Hydrometeorol. Res. Center of the Rus. Fed. 349, 5–46 (2013) [Google Scholar]
- R.G. Verdiev, Computation and prediction of the flood runoff of the eastern Caucasus rivers. Rus. Meteor. and Hydrol. 34, 46–50 (2009) [Google Scholar]
- Automated information system for state monitoring of water bodies. Retrieved from: https://gmvo.skniivh.ru/ Accessed: 20-April-2022 [Google Scholar]
- All-Russian Research Institute of Hydrometeorological Information, World Data Center. Retrieved from: http://meteo.ru/ Accessed: 21-April-2022 [Google Scholar]
- E.V. Gaidukova, V.G. Margaryan, I.O. Vinokurov, A.Yu. Romashchenko, Short-term forecasting of water consumption on the river. Samur. Int. Res. J. 6-3(108), 17–23 (2021). DOI: 10.23670/IRJ.2021.108.6.064 [Google Scholar]
- O.V. Tereshchenko, N.V. Kurilovich, E.I. Knyazeva, Multivariate statistical data analysis in social sciences (Minsk, BGU, 2012) [Google Scholar]
- M.A. Kharchenko, Correlation analysis (Voronezh, VSU Publishing House, 2010) [Google Scholar]
- E.V. Gaidukova, A.E. Kachalova, K.A. Litvinova, Accounting for the periodicity of water content in forecasting river runoff on the example of the rivers of the North-West region. N. word in scien.: dev. pros. 4-1(10), 72–77 (2016) [Google Scholar]
- A.E. Sumachev, N.V. Myakisheva, V.G. Margaryan, A.E. Misakyan, Long-term forecasting of water levels in Lake Ilmen using probabilistic approaches. Nat. and tech. scien. 6(157), 96–102 (2021) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.