TY  - GEN
A1  - Ayzel, Georgy
A1  - Izhitskiy, Alexander
A2  - Xu, Z Peng
T1  - Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea
T2  - Innovative Water Resources Management in a Changing Environment – Understanding and Balancing Interactions between Humankind and Nature
N2  - 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).
Y1  - 2018
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/54090
SN  - 2199-899X
VL  - 379
SP  - 151
EP  - 158
PB  - Copernicus
CY  - Göttingen
ER  -