Issue |
E3S Web Conf.
Volume 163, 2020
IV Vinogradov Conference “Hydrology: from Learning to Worldview” in Memory of Outstanding Russian Hydrologist Yury Vinogradov
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Article Number | 01006 | |
Number of page(s) | 6 | |
Section | Mathematical Modeling in Hydrology: Problems, Achievements, Practical Application | |
DOI | https://doi.org/10.1051/e3sconf/202016301006 | |
Published online | 17 April 2020 |
Runoff generation at the small permafrost river basin in Eastern Siberia: data analysis and hydrological modeling
1
Water Problems Institute RAS, Gubkina 3, 119333, Moscow, Russia
2
Melnikov Permafrost Institute SB RAS, Merzlotnaya 36, 677010, Yakutsk, Russia
* Corresponding author: kalugin-andrei@mail.ru
The study aims at the analysis of the long-term hydrometeorological data and hydrological modelling at the small permafrost Shestakovka river basin. The basin has postponed reaction to precipitation on different time scales from days to years. Annual, seasonal and monthly streamflow has higher correlation with precipitation sum for corresponding and antecedent time intervals than for the corresponding period only. It suggests importance of water storage and slow water release in the runoff generation that could be related to the suprapermafrost talik aquifers found in the river basin. A spatially distributed physically-based ECOMAG model was applied to the Shestakovka River basin. Evaluation of the simulated river runoff, soil moisture and snow water equivalent was carried out over a period 1990-2014. Obtained NSE 0.59 and BIAS 3% could be considered as satisfactory modelling results taking into account high inter annual and seasonal observed streamflow variability under much less variable meteorological conditions. Better understanding and modelling of the complex interactions between permafrost and hydrological processes is important for development of reliable flood forecasts and long-term future projections under changing climate and growing economical interests to cold regions.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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