Estimating Maximum Water Levels During Winter Flooding at Some Segments of the Lena River
- 10.2991/isees-19.2019.126How to use a DOI?
- spring floods; prediction; regression modeling; statistical approach; neural networks.
The Sakha Republic (Yakutia) has a large territory that covers various climatic zones and a network of water bodies and thus is exposed to a wide range of natural emergencies. The most typical of them is spring-summer floods that cause flooding of vast territories, facilities and infrastructure, thus causing enormous damage to the economy; it determines relevance of developing and perfecting flood prediction methods to reduce the hazard level and possible damage. This research presents application of multiparametric models and neuron networks for development of a predictive model that allows forecasting the spring flooding hazard from statistical data accumulated through 44 years of observation and regressive modeling. The proposed methods allow evaluating the spring flood water levels as a function of various factors (thickness of ice, temperature, etc.) with sufficient accuracy, as confirmed with the results of predicting maximum water levels for two segments of the Lena River. Selection of the river course segments was determined by nearby location of potentially hazardous facilities whose flooding may cause significant property loss. Factors influencing spring flood levels have been determined.
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - G.P. Struchkova AU - V.V. Timofeeva AU - T.A. Kapitonova AU - D.D. Nogovitsyn AU - K.I. Kusatov PY - 2019/08 DA - 2019/08 TI - Estimating Maximum Water Levels During Winter Flooding at Some Segments of the Lena River BT - Proceedings of the International Symposium "Engineering and Earth Sciences: Applied and Fundamental Research" dedicated to the 85th anniversary of H.I. Ibragimov (ISEES 2019) PB - Atlantis Press SP - 187 EP - 190 SN - 2590-3217 UR - https://doi.org/10.2991/isees-19.2019.126 DO - 10.2991/isees-19.2019.126 ID - Struchkova2019/08 ER -