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|
Possibilities of application of logistic regression in hydrological forecasts (on the example of the mountain river Samur)
1 Russian State Hydrometeorological University, 79, Voronezhskaya Str., St. Petersburg, 192007, Russian Federation
2 Yerevan State University, 1, Alek Manukyan, Yerevan Str., 375025, Armenia
* Corresponding author: firstname.lastname@example.org
The possibilities of constructing regression equations for predicting the runoff of mountain and semi-mountain rivers are considered. A predictive equation for the Samur river catchment has been obtained, which connects water discharge and predictors by casual relationships: water levels, air temperature, air humidity, atmospheric pressure, precipitation, dew point temperature, wind direction, and cloudiness. Logistic regressions are obtained, which allow using categorical variables as independent variables. The result of a logistic regression forecast is the probability of the occurrence or non-occurrence of the event of the predicted value. The positive and negative aspects of this approach for mountain rivers are revealed, which consist of the interpretation of the predicted probability of the event. Actions are proposed that allow for obtaining more reliable forecasts.
© The Authors, published by EDP Sciences, 2023
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.
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.