Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

Gelfan, Alexander (Russian Academy of Sciences; Moscow State University)
Moreydo, Vsevolod (Russian Academy of Sciences)
Motovilov, Yury (Russian Academy of Sciences)
Solomatine, D.P. (TU Delft Water Resources; Russian Academy of Sciences; IHE Delft Institute for Water Education)

2018-04-04

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.

http://resolver.tudelft.nl/uuid:e8aad380-4a1b-405e-a4fe-752851aecf56

https://doi.org/10.5194/hess-22-2073-2018

1027-5606

Hydrology and Earth System Sciences, 22 (4), 2073-2089

Institutional Repository

journal article

© 2018 Alexander Gelfan, Vsevolod Moreydo, Yury Motovilov, D.P. Solomatine