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

机译:在两种不同天气情况下雪融入切博克萨雷水库的长期总体预报

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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.
机译:提出了一种长期的预报集成方法,该方法适用于切博克萨雷水库(俄罗斯)的水流入量。该方法基于半分布式水文模型ECOMAG(应用地球物理学的生态模型)的版本,该模型允许在前置时间段内使用两组不同的天气集合来计算流入水文图的整体。基于Ensemble Stream Flow Prediction方法论(基于ESP的预报)和由多站点天气生成器(基于WG的预报)模拟的综合天气数据构建而成。我们研究了以下内容:(1)与目前发布的切博克萨雷水库水流入量运行预测相比,已开发的整体预报是否有任何优势;(2)概率预报是否有显着改善与基于ESP的集成相比,使用WG模拟的集成时。我们发现,从1982年的水库注水开始的35年期间,连续和基于二元模型的总体预报(以确定性形式发布)均优于实际使用的4月至6月流入量的运行预报,并且此外,除了流入量外,还应提供其他水态特征的可接受预测。我们还证明了,基于工作组的概率预测(基于大量可能的天气情况)获得的模型性能指标(在验证期内)似乎比从ESP计算的相应指标在统计​​上更可靠基于观测到的天气情况的预报。

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