Articles | Volume 379
Proc. IAHS, 379, 151–158, 2018
https://doi.org/10.5194/piahs-379-151-2018
Proc. IAHS, 379, 151–158, 2018
https://doi.org/10.5194/piahs-379-151-2018
Pre-conference publication
05 Jun 2018
Pre-conference publication | 05 Jun 2018

Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea

Georgy Ayzel and Alexander Izhitskiy

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Latest update: 20 May 2022
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Short summary
Presented paper is our first step in developing a geoscientific stack of models for an assessment of the Small Aral Sea basin current hydrological conditions within the interdisciplinary SMASHI project (smashiproject.github.io). Based on coupling state-of-the-art physically-based hydrological and machine learning models we have developed the skillful model for the Syr Darya river runoff prediction. This result is the key to understanding water balance trends in vulnerable Aral Sea region.