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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 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 (https://github.com/SMASHIproject/IWRM2018).

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Metadaten
Author details:Georgy AyzelORCiD, Alexander IzhitskiyORCiD
DOI:https://doi.org/10.5194/piahs-379-151-2018
ISSN:2199-899X
Title of parent work (English):Innovative Water Resources Management in a Changing Environment – Understanding and Balancing Interactions between Humankind and Nature
Publisher:Copernicus
Place of publishing:Göttingen
Editor(s):Z Peng Xu
Publication type:Other
Language:English
Date of first publication:2018/06/05
Publication year:2018
Release date:2022/02/28
Volume:379
Number of pages:8
First page:151
Last Page:158
Funding institution:Russian Foundation for Basic Research (RFBR)Russian Foundation for Basic Research (RFBR) [17-05-01175 A]; Russian Science FoundationRussian Science Foundation (RSF) [16-17-10039]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer review:Referiert
Publishing method:Open Access / Gold Open-Access
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License (German):License LogoCC-BY - Namensnennung 4.0 International
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