摘要
多支流河流径流预报误差具有复杂性、多重不确定性,研究多源径流预报误差可为流域制定水资源管理方案提供更加可靠的来水依据。基于具有稳定鲁棒性的t Location-Scale分布,构建反映径流预报误差多重不确定性、缓解分布假设不正确问题的多源径流预报误差混合分布模型,应用于长江上游屏山站、朱沱站等干支流7座代表性水文站,分汛期、非汛期研究径流预报误差特性。结果表明:各水文站汛期、非汛期径流预报误差最佳边缘分布基本适宜采用t Lo⁃cation-Scale分布;朱沱站、寸滩站及清溪场站汛期多源径流预报误差混合分布模型拟合效果较好,非汛期拟合效果仅次于最佳边缘分布;模型产生的径流预报误差模拟值与实际值均值、变差系数的相对误差不超过11%,偏态系数变化规律相似,能进一步修正径流预报,为流域水资源开发利用及优化配置提供依据。
The forecast error of runoff in multi-tributary rivers has complexity and multiple uncertainties.The research on the forecast error of runoff from multi-source rivers can provide a more reliable inflow basis for the formulation of water resources management scheme in the basin.Based on the t location-scale distribution with stability and robustness,a mixed distribution model of runoff forecast error with multiple sources was constructed to reflect the multiple uncertainties of runoff forecast error and alleviate the problem of incorrect distribution hypothesis.It is applied to 7 representative hydrological stations in the upper reaches of the Yangtze River,such as Pingshan Station and Zhutuo Station to study the error characteristics of runoff forecast in the flood season and the non-flood season.The results show that:t location-scale distribution is basically suitable for the optimal marginal distribution of daily runoff forecast error series of hydrological stations in the flood season and non-flood season.The mixed distribution model of multi-source runoff forecast error at Zhutuo Station,Cuntan Station and Qingxiichang Station in the flood season has a good fitting effect,and it is second only to the optimal marginal distribution model in the nonflood season.The relative error of mean value and the coefficient of variation between the simulated value and the actual value is less than 11%,and the variation law of the skewness coefficient is similar,which can be used to modify the runoff forecast sequence and to provide a more accurate foundation for the development and utilization of water resources and optimal allocation in the basin.
作者
李继清
孙凤玲
王爽
田雨
LI Ji-qing;SUN Feng-ling;WANG Shuang;TIAN Yu(School of Water Resources and Hydropower Engineering,North China Electric Power University,Beijing 102206,China;Water Conservation Promotion Center of the Ministry of Water Resources,Beijing 100038,China;China Institute of Water Resources and Hydropower Research,Beijing 100038,China)
出处
《中国农村水利水电》
北大核心
2022年第5期125-132,共8页
China Rural Water and Hydropower
基金
国家重点研发计划(2016YFC0402208)
国家自然科学基金(51879273,52179014)。
