Articles | Volume 22, issue 4
https://doi.org/10.5194/hess-22-2225-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-22-2225-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Statistical forecast of seasonal discharge in Central Asia using observational records: development of a generic linear modelling tool for operational water resource management
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Zharkinay Abdykerimova
Hydro-Meteorological Service of Kyrgyzstan, Bishkek, Kyrgyzstan
Marina Agalhanova
Hydro-Meteorological Service of Turkmenistan, Ashgabat, Turkmenistan
Azamat Baimaganbetov
Hydro-Meteorological Service of Kazakhstan, Almaty, Kazakhstan
Nadejda Gavrilenko
Hydro-Meteorological Service of Uzbekistan, Tashkent, Uzbekistan
Lars Gerlitz
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Olga Kalashnikova
CAIAG Central Asian Institute for Applied Geoscience, Bishkek, Kyrgyzstan
Katy Unger-Shayesteh
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Sergiy Vorogushyn
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Abror Gafurov
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
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Latest update: 23 Nov 2024
Short summary
Central Asia crucially depends on water resources supplied by snow melt in the mountains during summer. To support water resources management we propose a generic tool for statistical forecasts of seasonal discharge based on multiple linear regressions. The predictors are observed precipitation and temperature, snow coverage, and discharge. The automatically derived models for 13 different catchments provided very skilful forecasts in April, and acceptable forecasts in January.
Central Asia crucially depends on water resources supplied by snow melt in the mountains during...
Special issue