DOI: 10.5194/hess-22-2073-2018
Scopus记录号: 2-s2.0-85045017524
论文题名: Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios
作者: Gelfan A ; , Moreydo V ; , Motovilov Y ; , Solomatine D ; P
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2018
卷: 22, 期: 4 起始页码: 2073
结束页码: 2089
语种: 英语
Scopus关键词: Meteorology
; Reservoirs (water)
; Corresponding measures
; Ecological modeling
; Ensemble forecasts
; Long-term forecasting
; Operational forecasts
; Probabilistic forecasts
; Semi distributed hydrological models
; Streamflow prediction
; Weather forecasting
英文摘要: 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. © Author(s) 2018. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79341
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Water Problems Institute of Russian Academy of Sciences, Watershed Hydrology Lab., Moscow, Russian Federation; Moscow State University, Geographical Department, Moscow, Russian Federation; IHE Delft Institute for Water Education, Department of Hydroinformatics, Delft, Netherlands; Delft University of Technology, Water Resources Section, Delft, Netherlands
Recommended Citation:
Gelfan A,, Moreydo V,, Motovilov Y,et al. Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios[J]. Hydrology and Earth System Sciences,2018-01-01,22(4)