Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios
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Published:2018-04-04
Issue:4
Volume:22
Page:2073-2089
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ISSN:1607-7938
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Container-title:Hydrology and Earth System Sciences
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language:en
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Short-container-title:Hydrol. Earth Syst. Sci.
Author:
Gelfan AlexanderORCID, Moreydo Vsevolod, Motovilov Yury, Solomatine Dimitri P.ORCID
Abstract
Abstract. A long-term forecasting ensemble methodology, applied to water inflows into
the Cheboksary Reservoir (Russia), is presented. The methodology is based on
a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for
the calculation of an ensemble of inflow hydrographs using two different sets of
weather ensembles for the lead time period: observed weather data,
constructed on the basis of the Ensemble Streamflow Prediction methodology
(ESP-based forecast), and synthetic weather data, simulated by a
multi-site weather generator (WG-based forecast). We have studied the following:
(1) whether there is any advantage of the developed ensemble forecasts in
comparison with the currently issued operational forecasts of water inflow
into the Cheboksary Reservoir, and (2) whether there is any noticeable
improvement in probabilistic forecasts when using the WG-simulated ensemble
compared to the ESP-based ensemble. We have found that for a 35-year period
beginning from the reservoir filling in 1982, both continuous and binary
model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April–June inflow volume
actually used and, additionally, provide acceptable forecasts of additional water regime
characteristics besides the inflow volume. We have also demonstrated that
the model performance measures (in the verification period) obtained from the
WG-based probabilistic forecasts, which are based on a large number of
possible weather scenarios, appeared to be more statistically reliable than
the corresponding measures calculated from the ESP-based forecasts based on
the observed weather scenarios.
Funder
Russian Science Foundation Russian Foundation for Basic Research
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
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