摘要数值气象预报与水文模型相结合能有效延长洪水预报的预见期,对中小流域山洪预警具有重要意义。为了研究高分辨率数值气象预报模式在中小流域洪水预报中的应用潜力,以福建省桃溪流域为研究对象,评估了数值气象预报模式GRAPES-RAFS (RapidAnalysis and Forecast System)在不同起报时刻的短期降雨预报能力,采用两种偏差校正方法(线性放缩法(LS)和分位数匹配法(QM))对降雨预报数据进行偏差校正处理,并分别用校正前和校正后的数据驱动新安江模型,评估预报降水在场次洪水预报中的适用性。评估结果表明,GRAPES-RAFS中小流域降雨过程具有较好的预报能力,但高估了降雨量,所有评价指标具有较好的一致性;采用两种偏差校正方法均能显著降低降雨预报的偏差,12场降雨的平均相对偏差从60.33%分别降低至18.00%(LS方法)和21.33%(QM方法);未经校正的GRAPES-RAFS预报降雨直接用于洪水预报的效果表现不佳,洪峰被明显高估,但降雨偏差校正能显著提升洪水预报的精度。总体而言,偏差校正后表现较好的降雨场次对应表现较好的洪水场次,且两种偏差校正方法表现相近。
Abstract:The leading-time of flood forecasts can be effectively extended by combining numerical meteorological forecasts with hydrological models, which is of great significance in warning of flash floods over small and medium sized river basins. In order to investigate the potential of using high-resolution numerical meteorological forecasting models in the simulation of flash flood processes, the Taoxi River Basin in Fujian Province was taken as the research object to evaluate the ability of a high spatial and temporal resolution numerical weather prediction model (GRAPES-RAFS) (Rapid Analysis and Forecast System) in short-term rainfall forecasting at different reporting times. Two bias correction methods (LS and QM methods) are further used to correct the systematic bias of GRAPES-RAFS simulated rainfall. The corrected rainfall forecasts are also used to drive the Xin’ anjiang hydrological model with pre corrected and post corrected data to evaluate their applicability in flood forecasts. The evaluation results show that GRAPES-RAFS performs well in simulating rainfall process, but significantly overestimate rainfall amounts. All the evaluation indicators have a good consistency. Both bias correction methods can significantly improve the accuracy of rainfall forecasts, reducing the average relative bias from 60.30% to 18.00% (LS method) and 21.33% QM method), respectively across 12 rainfall events. The performance of uncorrected GRAPES-RAFS in predicting rainfall directly for flood forecasting is poor, and flood peaks are significantly overestimated. However, rainfall bias correction can significantly improve the accuracy of flood. Overall, the rainfall events that perform better after bias correction correspond to the flood events that perform better, and the two bias correction methods perform similarly forecasting.
曲丽英. 高分辨率数值降雨预报在中小流域洪水预报中的适用性评价[J]. 中国防汛抗旱, 2023, 33(6): 55-61,87.
QU Liying. Applicability of high-resolution numerical rainfall forecasts in flood forecasting over small and medium sized river basin. journal1, 2023, 33(6): 55-61,87.
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