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

Model code and software

Data, code, and results for the paper "Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea" Georgy Ayzel and Alexander Izhitskiy https://doi.org/10.5281/zenodo.1161906

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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.