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

• Main Authors: G. Ayzel, A. Izhitskiy
• Format: Article
• Language: English
• Published: Copernicus Publications 2018-06-01
• Series: Proceedings of the International Association of Hydrological Sciences
• Online Access: https://www.proc-iahs.net/379/151/2018/piahs-379-151-2018.pdf

The Aral Sea desiccation and related changes in hydroclimatic conditions on a regional level is a hot topic for past decades. The key problem of scientific research projects devoted to an investigation of modern Aral Sea basin hydrological regime is its discontinuous nature – the only limited amount of papers takes into account the complex runoff formation system entirely. Addressing this challenge we have developed a continuous prediction system for assessing freshwater inflow into the Small Aral Sea based on coupling stack of hydrological and data-driven models. Results show a good prediction skill and approve the possibility to develop a valuable water assessment tool which utilizes the power of classical physically based and modern machine learning models both for territories with complex water management system and strong water-related data scarcity. The source code and data of the proposed system is available on a Github page (<a href="https://github.com/SMASHIproject/IWRM2018" target="_blank">https://github.com/SMASHIproject/IWRM2018</a>).