摘要
为了提高淮河流域上游的洪水预报精度,引入计量经济学中的协整理论与误差修正模型用于洪水预报实时校正;同时为了解决自回归算法无法针对非平稳序列建模以及序贯相关性问题,构建了基于误差修正概念的自回归误差修正模型。以淮河鲁台子站以上流域为研究区域,基于分布式垂向混合产流模型模拟结果,分别构建一阶至三阶自回归模型、误差修正模型和基于误差修正的自回归模型对模拟结果进行校正,采用修正效果评价系数、确定性系数、洪峰相对误差、径流深相对误差和峰现时差5个评价指标,分析对比各校正模型对流域2003—2014年10场洪水的校正效果。结果表明:3种实时校正方法均对淮河流域上游洪水有一定的校正效果,其中,自回归模型校正效果最差,排除误差序列非平稳的两次洪水后,其平均修正效果评价系数为0.20;误差修正模型能够有效校正预报洪水,其平均修正效果评价系数为0.76;基于误差修正的自回归模型校正效果较好,与传统自回归模型相比,对洪峰流量的校正效果显著提高,其平均修正效果评价系数达到0.98,可用于淮河流域上游洪水预报的实时校正。
In order to improve the accuracy of flood forecasting in the upper Huaihe River Basin,the cointegration theory and error correction model(ECM)in econometrics were introduced for real-time correction of flood forecasting.Meanwhile,for solving the problem that the autoregressive(AR)model is not able to simulate the non-stationary sequence and the problem of sequential correlation,the autoregressive error correction model(ARECM)was constructed based on the concept of error correction.With the Huaihe River Basin above the Lutaizi station used as the study area,1-to 3-order AR model,ECM and ARECM were constructed respectively to correct the simulation results of the distributed vertical mixed runoff generation model.The correction results of different correction models regarding 10 floods forecasting from 2003 to 2014 in the upper Huaihe River Basin were analyzed and compared using five evaluation indexes,including the correction effect evaluation coefficient,deterministic coefficient,relative error of flood peak,relative error of runoff depth,and error of time to flood peak.The results show that the forecasted flood in the upper Huaihe River Basin is effectively corrected by the three real-time correction models.The correction performance of the AR model is relatively worse,and after two floods that have non-stationary error sequences are excluded,the average correction effect evaluation coefficient is 0.20;ECM can effectively correct forecasted floods,and the average correction effect evaluation coefficient is 0.76;the correction performance of ARECM is better as compared to the traditional AR model,and the correction effect of flood peak is significantly improved,with the average correction effect evaluation coefficient being 0.98,demonstrating that ARECM can be well applied to real-time correction of flood forecasting in the upper Huaihe River Basin.
作者
张旭旻
瞿思敏
李倩
石朋
嵇海祥
宋兰兰
王麒栋
ZHANG Xumin;QU Simin;LI Qian;SHI Peng;JI Haixiang;SONG Lanlan;WANG Qidong(College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China;Wanghui(Suzhou)Water Resources Consulting Co.,Ltd.,Suzhou 215128,China;Nanjing Automation Institute of Water Conservancy and Hydrology,Ministry of Water Resources,Nanjing 210008,China;Zhoushan Ecological Environment Bureau,Zhoushan 316021,China)
出处
《水资源保护》
EI
CAS
CSCD
北大核心
2022年第6期88-95,145,共9页
Water Resources Protection
基金
国家自然科学基金(52179011)
国家重点研发计划(2019YFC0409000)。
关键词
协整理论
误差修正模型
自回归模型
实时校正
淮河流域上游
cointegration theory
error correction model
autoregressive model
real-time correction
the upper Huaihe River Basin
