MATHEMATICAL MODELING OF RIVER FLOW HYDROGRAPH

Authors

DOI:

https://doi.org/10.36773/1818-1112-2026-140-2-115-120

Keywords:

hydrograph, flood start date, flood end date, forecast lead time, modeling, flood, forecast, river runoff, extrapolation

Abstract

The article addresses current issues of mathematical modeling of river flow hydrographs and development of automated methods for predicting floods in the Republic of Belarus. The research is driven by the need to improve the accuracy of hydrological forecasts under changing climate conditions and anthropogenic impact on river basins. An adaptive methodology has been developed to determine the start and end dates of floods, based on the analysis of daily water discharges. The techniques were tested using data from 16 hydrological stations over a 40-year period (1971–2010). Verification results demonstrated high accuracy in determining the start of floods (average absolute error of 2–3 days in 90 % of cases) and satisfactory accuracy for the end dates (5–6 days in 90 % of cases). An extrapolation algorithm for the hydrograph has been proposed to forecast river flow with a lead time of 1 to 10 days. The developed software module automates the forecasting process and incorporates a self-learning mechanism to account for climate changes. The practical significance of the work lies in creating tools for effective water resource management, protecting the population from emergencies, and rational use of water bodies. The proposed techniques are applicable to both single-peak and multi-peak hydrographs, expanding their usability under various hydrological conditions.

Author Biographies

Alexander Alexandrovich Volchak, Brest State Technical University

Doctor of Geographical Sciences of the Russian Federation and the Republic of Belarus, Professor, Professor of the Department of Environmental Management, Brest State Technical University, Brest, Belarus.

Svetlana Vasilievna Sidak, Brest State Technical University

Candidate of Geographical Sciences, Senior Lecturer, Department of Mathematics and Computer Science, Educational Institution "Brest State Technical University", Brest, Belarus.

Sergey Ivanovich Parfomuk, Brest State Technical University

Candidate of Technical Sciences, Associate Professor, Head of the Department of Mathematics and Computer Science, Educational Institution "Brest State Technical University", Brest, Belarus.

Oleg Pavlovich Meshik, Brest State Technical University

Candidate of Technical Sciences, Associate Professor, Dean of the Faculty of Engineering Systems and Ecology, Brest State Technical University, Brest, Belarus.

Yulia Petrovna Kaliada, Brest State Technical University

Master of Science, Senior Lecturer, Department of Environmental Engineering, Brest State Technical University, Brest, Belarus.

Marina Viktorovna Borushko, Brest State Technical University

Master of Science (Engineering), Senior Lecturer, Department of Linguistic Disciplines and Intercultural Communication, Brest State Technical University, Brest, Belarus.

Anastasia Sergeevna Protasevich, Brest State Technical University

Master's degree student, Deputy Dean for Ideological and Educational Work, Faculty of Engineering Systems and Ecology, Brest State Technical University, Brest, Belarus.

References

State of the Global Climate 2025 // World Meteorological Organization. – URL: https://wmo.int/publication-series/state-of-global-climate/state-of-global-climate-2025 (date of access: 01.06.2026).

Волчек, А. А. Многолетняя изменчивость стока рек Беларуси в условиях изменения климата и антропогенных воздействий / А. А. Волчек, С. В. Сидак, С. И. Парфомук // Актуальные научно-технические и экологические проблемы сохранения среды обитания : сб. тр. IV Междунар. науч.-практ. конф., посвящ. 55-летию Брест. гос. техн. ун-та и 50-летию ф-та инженерных систем и экологии, Брест, 7–8 окт. 2021 г. / Брест. гос. техн. ун-т ; редкол.: А. А. Волчек [и др.]. – Брест, 2021. – С. 101–113.

Волчек, А. А. Оценка современных изменений максимального стока рек Беларуси / А. А. Волчек, Ан. А. Волчек, С. В. Сидак // Геаграфiя. – 2020. – Т. 4. – С. 26–32.

Volchak, A. Intra-annual runoff distribution in the Pripyat River basin / A. Volchak, S. Parfomuk, S. Sidak // ICBTE 2020, E3S Web of Conferences. – 2020. – Т. 212. – P. 01016. – DOI: 10.1051/e3sconf/202021201016.

Волчек, А. А. Динамика изменения водных ресурсов Беларуси в современных условиях / А. А. Волчек, С. В. Сидак, С. И. Парфомук // Инновации: от теории к практике : сб. науч. ст. VIII Междунар. науч.-практ. конф., Брест, 21–22 окт. 2021 г. / Брест. гос. техн. ун-т; редкол.: В. В. Зазерская [и др.]. – Брест, 2021. – С. 81–89.

Investigating Impacts of Climate Change on Runoff from the Qinhuai River by Using the SWAT Model and CMIP6 Scenarios / J. Sun, H. Yan, Z. Bao, G. Wang // Water. – 2022. – Vol. 14, № 11. – P. 1778. – DOI: 10.3390/w14111778.

Алгоритм автоматизированного расчленения гидрографа по методу БИ Куделина GrWat: проблемы и перспективы / Е. П. Рец, М. Б. Киреева, Т. Е. Самсонов [и др.] // Водные ресурсы. – 2022. – Т. 49, № 1. – С. 27–42. – DOI: 10.31857/S032105962201014X.

Куделин, Б. И. Принципы региональной оценки естественных ресурсов подземных вод / Б. И. Куделин. – М. : МГУ, 1960. – 343 с.

Чижова, Ю. Н. Двухкомпонентное расчленение гидрографа р. Протвы / Ю. Н. Чижова, Е. П. Рец, Н. А. Тебенькова [и др.] // Вестн. МГУ. Сер. География. – 2021. – № 6. – С. 48–56.

Оптимизация параметров методов расчленения гидрографа для повышения их эффективности на примере бассейна реки Белой / И. А. Хасанов, А. Н. Елизарьев, Д. А. Тараканов, Дм. А. Тараканов // Гидросфера. Опасные процессы и явления. – 2025. – Т. 6, №. 2. – С. 125–137. – DOI: 10.34753/HS.2024.6.1.125.

Eckhardt, K. A comparison of baseflow indices, which were calculated with seven different baseflow separation methods / K. Eckhardt // Journal of Hydrology. – 2008. – Vol. 352 (1–2). – Р. 168–173.

Lyne, V. Stochastic time-variable rainfall-runoff modelling / V. Lyne, M. Hollick // Institute of engineers Australia national conference. Barton, Australia: Institute of Engineers Australia. – 1979. – Т. 79, Vol. 10. – P. 89–93.

Kirchner, J. W. Quantifying new water fractions and transit time distributions using ensemble hydrograph separation: theory and benchmark tests / J. W. Kirchner // Hydrology and Earth System Sciences. – 2019. – Vol. 23, № 1. – P. 303–349.

Ensemble machine learning for global hydrological prediction / C. Liu, D. Liu, L. Mu, J. Zhang // Water Resources Research. – 2022. – Vol. 58, № 12. – Art. e2021WR030993.

Berhail, S. The use of the recession index as indicator for components of flow / S. Berhail, L. Ouerdachi, H. Boutaghane // Energy Procedia. – 2012. – № 18. – P. 741–750.

Framework for ensemble hydrograph prediction using machine learning and hydrological models / G. I. Brunner, N. Addor, M. Zappa, F. Comola // Hydrology and Earth System Sciences. – 2021. – Vol. 25, No. 3. – P. 1423–1441.

Охрана окружающей среды и природопользование. Гидрометеорологическая деятельность. Государственный водный кадастр. Правила составления справочника «Многолетние данные о режиме и ресурсах поверхностных вод» : ТКП 17-10.25-2010 (02120). – Введ. 01.03.11. − Минск : Минприроды, 2011. – 59 с.

Шевнина, Е. В. Методика расчета характеристик весеннего половодья по данным ежедневных расходов воды / Е. В. Шевнина // Проблемы Арктики и Антарктики. − 2013. − № 1 (95). − С. 44–50.

Экстраполяция гидрографов как метод краткосрочного прогнозирования речного стока / С. В. Борщ, Ю. А. Симонов, А. В. Христофоров [и др.] // Гидрологические исследования и прогнозы. − 2018. − № 3 (369). − С. 74–86.

Прогнозирование стока рек России методом экстраполяции гидрографа / С. В. Борщ, В. М. Колий, Н. К. Семенова [и др.] // Вестник МГУ. Сер. География. – 2021. – № 2 (380). – С. 77–94. – DOI: 10.37162/2618-9631-2021-2-77-94.

Published

2026-07-20

How to Cite

(1)
Volchak, A. A.; Sidak, S. V.; Parfomuk, S. I.; Meshik, O. P.; Kaliada, Y. P.; Borushko, M. V.; Protasevich, A. S. MATHEMATICAL MODELING OF RIVER FLOW HYDROGRAPH. Вестник БрГТУ 2026, 115-120.