高级检索

      长江上游干支流洪水预报精度分析

      Analysis of flood forecasting accuracy for mainstream and tributaries of upper Changjiang River

      • 摘要: 洪水预报信息的有效应用是提升水库调控效益的关键, 预报精度分析与误差分布规律是其应用的核心前提。基于长江流域上游干支流7个重要水文控制断面近10 a的数据(寸滩、三峡断面采用2011~2023年数据, 其余5个断面采用2017~2023年的数据), 数据的预见期为1~10 d, 针对连续径流过程、分级流量过程、场次洪水过程, 系统评估了长江上游干支流洪水预报精度及误差分布规律。结果表明: 预报精度评价方面, 干流预报精度整体优于支流, 其中三峡断面1~5 d预见期合格率达85%以上, 预报表现最优;分级流量预报中, 除三峡断面外, 其余断面大量级洪水预报精度优于中小量级洪水;三峡断面场次洪水预报的洪峰、洪量相对误差在5 d预见期内均不超过20%。此外, 在误差分布分析方面, 连续径流过程误差不服从常规分布, 但特定量级符合正态分布, 因此常规分布无法全面表示洪水预报概率误差, 而依据极大熵原理可描述洪水预报误差分布, 研究成果可为水库风险调度提供决策依据。

         

        Abstract: The effective application of flood forecasting information is pivotal for enhancing reservoir regulation efficiency, with the analysis of forecast accuracy and error distribution patterns serving as the core prerequisite for its practical implementation. This study systematically evaluated forecast accuracy and error distribution characteristics with 1 to 10 days forecast period based on a decade of data from seven critical hydrological control sections in the upper mainstream and tributaries of Changjiang River Basin (data for the Cuntan and Three Gorges Sections covered the period from 2011 to 2023, while the data for other five sections were from 2017 to 2023), focusing on continuous runoff processes, graded discharge magnitudes, and flood event processes. The results demonstrated that the mainstream forecasting accuracy was generally superior to that of the tributaries, with the Three Gorges Section achieving a qualified rate exceeding 85% for lead times of 1 to 5 days, representing the optimal forecasting performance. In graded discharge forecasting, large-magnitude flow predictions at other sections outperformed medium-small magnitudes, except for the Three Gorges Section. For flood events at the Three Gorges, both peak flow and flood volume forecast errors remained within 20% across a 5-day lead time. Furthermore, hypothesis testing indicates that errors in continuous runoff processes do not follow conventional distributions, although errors for specific discharge levels conform to a normal distribution. Therefore, conventional distributions cannot fully represent probabilistic forecast errors, while modeling error distributions based on the maximum entropy principle can provide a decision-making basis for risk-informed reservoir operation.

         

      /

      返回文章
      返回