摘要
为了提高洪水预报的精度,基于集合卡尔曼滤波,提出对流域中子流域中间状态量进行全状态量回溯修正方法。该方法根据每个子流域地貌特征和汇流时间不同,分别找出其相应的回溯时间,与新安江模型相结合对各个子流域特定时段前的中间状态量进行全状态量回溯修正,逐步降低误差的累积。采用理想模型验证,结果显示子流域中间状态量得到有效修正,洪量相对误差和洪峰相对误差减小,确定性系数提高。以大坡岭流域为例,采用该方法对流域12场历史洪水进行修正,修正结果表明此方法能有效提高洪水预报的精度,可在实际洪水预报中推广应用。
In order to improve the accuracy of flood forecasting, the paper proposes a retroactive correction method for the whole intermediate state variables of a sub-basin based on the ensemble Kalman filter. According to the different geomorphic feature and confluence time of each sub-basin, its corresponding retroactive time is found, and then, the Xinanjiang model is combined with to correct the state of each sub-basin before a certain time, gradually reducing the accumulation of errors. The results of the ideal model show that the intermediate state of sub-basin is effectively corrected, relative error of peak and volume decreases, and the deterministic coefficient increases. 12 historical floods of the Dapoling Basin, selected as an example, are effectively modified by the proposed method. As a result, the method can effectively improve the accuracy of flood forecasting and can be widely used in actual flood forecasting.
引文
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