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基于AREM 模式的贝叶斯洪水概率预报试验

Experiments of Bayesian probability flood forecasting based on the AREM model

  • 摘要: 为提高预见期内洪水预报精度,选取湖北省漳河水库2006 —2008 年汛期逐小时流域降水量、流量资料以及武汉暴雨研究所提供的相应时段AREM 模式预报的00 —60 h 逐小时降水预报产品作为研究资料,引入贝叶斯概率统计模型对AREM 模式的降水预报进行订正,并分别对订正前后的预报降水进行对比分析;其后,进一步将AREM 模式预报订正前后的降水预报值分别输入新安江水文模型进行洪水预报试验。结果表明,订正后的预报降水比订正前的精度有所提高,均方根误差减小幅度小于10 % ;检验期场次洪水的平均确定性系数提高10 .66 % ,平均洪峰相对误差减小3.05 % ,洪水预报精度在一定程度上有所提高。

     

    Abstract: To improve the accuracy of the flood prediction in forecast period, the Bayesian probabilistic model is introduced to correct the precipitation forecasted by AREM model using the hourly precipitation,flow data of the flood season of Zhanghe Reservoir in Hubei province from 2006 to 2008 and the corresponding 00-60 h hourly AREM forecasting precipitation provided by IHR(Institute of Heavy Rain in Wu-Han).The corrected and non corrected precipitation are analyzed comparatively, and then the both corrected and non corrected forecasting precipitation by AREM model are input into Xin'an-jiang hydrology flood forecast model.The results show that the corrected forecasting precipitation has the higher accuracy than that of non correcte done.The root mean square error was decreased by less than 10%. The average flood deterministic coefficient increases by 10.66%,the average relative error of peak reduces by 3.05% in the verification period.It improved the precision of flood forecast to some extent.

     

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