Modeling water level using downstream river water level observations and machine learning methods

The article presents the results of the development of a model for calculating levels at one gauging station using the levels at another. To link the levels at two gauging stations, the data on levels, temperature and precipitation were used. The use of machine learning methods to solve the problem...

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Bibliographic Details
Published in:E3S web of conferences 2020-01, Vol.163, p.1009
Main Authors: Sarafanov, Mikhail, Kazakov, Eduard, Borisova, Yulia
Format: Article
Language:English
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Summary:The article presents the results of the development of a model for calculating levels at one gauging station using the levels at another. To link the levels at two gauging stations, the data on levels, temperature and precipitation were used. The use of machine learning methods to solve the problem of predicting water levels made it possible to achieve an accuracy of about 6 cm. At the same time, traditional statistical models (linear regression, polynomial regression) have 14-16 cm error.
ISSN:2267-1242
2267-1242
DOI:10.1051/e3sconf/202016301009