• search hit 39 of 558
Back to Result List

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).

Download full text files

  • pmnr703.pdfeng

    SHA-1: 9c1711d453304e09941c5310101d0555c270b163

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Author:Georgy AyzelORCiD, Alexander Izhitskiy
Parent Title (English):Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
Series (Serial Number):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (703)
Document Type:Postprint
Date of first Publication:2019/04/26
Year of Completion:2018
Publishing Institution:Universität Potsdam
Release Date:2019/04/26
Tag:Asia; catchments; climate-change; river-basin; runoff
First Page:151
Last Page:158
Source:Proceedings of the International Association of Hydrological Sciences (PIAHS) 379 (2018), pp. 151–158 DOI: 10.5194/piahs-379-151-2018
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Publication Way:Open Access
Licence (German):License LogoCreative Commons - Namensnennung, 4.0 International