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首页> 外文期刊>Journal of hydrometeorology >A Dynamical Climate Model-Driven Hydrologic Prediction System for the Fraser River, Canada
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A Dynamical Climate Model-Driven Hydrologic Prediction System for the Fraser River, Canada

机译：加拿大弗雷泽河的动态气候模型驱动的水文预报系统

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Recent improvements in forecast skill of the climate system by dynamical climate models could lead to improvements in seasonal streamflow predictions. This study evaluates the hydrologic prediction skill of a dynamical climate model-driven hydrologic prediction system (CM-HPS), based on an ensemble of statistically downscaled outputs from the Canadian Seasonal to Interannual Prediction System (CanSIPS). For comparison, historical and future climate traces-driven ensemble streamflow prediction (ESP) was employed. The Variable Infiltration Capacity model (VIC) hydrologic model setup for the Fraser River basin, British Columbia, Canada, was used as a test bed for the two systems. In both cases, results revealed limited precipitation prediction skill. For streamflow prediction, the ESP approach has very limited or no correlation skill beyond the months influenced by initial hydrologic conditions, while the CM-HPS has moderately better correlation skill, attributable to the enhanced temperature prediction skill that results from CanSIPS's ability to predict El Nino-Southern Oscillation (ENSO) and its teleconnections. The root-mean-square error, bias, and categorical skills for the two methods are mostly similar. Hydrologic modeling uncertainty also affects the prediction skill, and in some cases prediction skill is constrained by hydrologic model skill. Overall, the CM-HPS shows potential for seasonal streamflow prediction, and further enhancements in climate models could potentially to lead to more skillful hydrologic predictions.
机译：动态气候模型对气候系统预报技能的最新改进可能会导致季节性水流预报的改进。这项研究基于从加拿大季节预报系统到年际预报系统（CanSIPS）的统计缩减规模的输出，评估了动态气候模型驱动的水文预报系统（CM-HPS）的水文预报技能。为了进行比较，采用了历史和未来气候跟踪驱动的集成流预测（ESP）。为加拿大不列颠哥伦比亚省的弗雷泽河流域建立的可变渗透能力模型（VIC）水文模型被用作这两个系统的试验台。在这两种情况下，结果都表明降水预测技术有限。对于流量预测，ESP方法在受初始水文条件影响的月份以外的几个月中，具有非常有限的相关技能或没有相关技能，而CM-HPS具有中等更好的相关技能，这归因于CanSIPS预测厄尔尼诺现象的能力增强了温度预测技能-南方涛动（ENSO）及其遥相关。这两种方法的均方根误差，偏倚和分类技巧基本相似。水文建模的不确定性也会影响预测技能，在某些情况下，预测技能会受到水文模型技能的限制。总体而言，CM-HPS显示出季节性流量预测的潜力，而气候模型的进一步增强可能导致更熟练的水文预测。

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