Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea
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 amo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-06-01
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| Series: | Proceedings of the International Association of Hydrological Sciences |
| Online Access: | https://www.proc-iahs.net/379/151/2018/piahs-379-151-2018.pdf |
| Summary: | 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>). |
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| ISSN: | 2199-8981 2199-899X |