采用分位点回归模型分析洪水预报的不确定性, 提供洪水预报倾向值( 预报概率分布的中位数) 和 90% 置信度的预报区间成果, 实现了洪水概率预报。基于/ 精度2可靠性0 联合评价指标对分位点回归模型计算的预报倾向值 和预报区间成果进行了评估。在信江流域梅港站的应用结果表明: 基于分位点回归模型提供的倾向值定值预报结 果可进一步提升洪水预报的精度; 同时该模型提供的 90% 预报区间结果具有较高的覆盖率( 约 90% ) 且离散度较小 ( 小于 01 20) , 表明预报区间以较窄的宽度包含了绝大多数的实测值, 预报可靠性较强。

The quantile regression model is used to analyze the uncertainty of flood forecasting. The results of preferred value ( median of predicted probability distribution function) and 90% confidence interval of flood forecasting are provided to realize the forecast of flood probability . The performance of probabilistic forecasting obtained by the quantile regression model is evaluated using "accuracy reliability " joint evaluation index . The application results of Meigang Station in the Xinjiang River Basin show that in term o f prediction preferred value, the quantile regression model can further improve the accuracy of the flood forecasting. Simultaneously , the prediction interval results with 90% confidence level provided by the model have higher coverage ( about 90% ) and less dispersion ( less than 0. 20) , which means that the narrow prediction interval contains most of the observation, and the reliability of the forecast interval is strong.

国家重点研发计划( 2016YFC0402709; 2016YFC0402707) ; 国家自然科学基金( 41730750; 51709073)