复杂水情下H-ADCP流量在线监测推流方法  

Online H-ADCP discharge monitoring and flow derivation method under complex flow conditions

作　　者：刘墨阳 蒋四维 林云发 张生稳 晋涛 黄迎春[2] 兰蓓蓓 周晓英 蒋飞卿 童冰星 周文静 LIU Moyang;JIANG Siwei;LIN Yunfa;ZHANG Shengwen;JIN Tao;HUANG Yingchun;LAN Beibei;ZHOU Xiaoying;JIANG Feiqing;TONG Bingxing;ZHOU Wenjing(Hanjiang River Hydrology and Water Resources Survey Bureau,Hydrology Bureau of Changjiang Water Resources Commission,Xiangyang 441025,China;College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China)

机构地区：[1]长江水利委员会水文局汉江水文水资源勘测局,湖北襄阳441025 [2]河海大学水文水资源学院,江苏南京210098

出　　处：《水利水电科技进展》2022年第2期27-34,共8页Advances in Science and Technology of Water Resources

基　　金：国家重点研发计划(2018YFC1508102);国家自然科学基金(51909059);江苏省自然科学基金(BK20190492)。

摘　　要：为提高受水利工程影响测验断面推流精度及提升H-ADCP流量在线监测系统水平,综合考虑仪器入水深、落差等因素,建立多元线性回归模型推算断面平均流速,利用最小二乘法求解模型参数;同时针对小流量下推流精度低的问题,充分考虑相关性较强的单个流速网格单元,采用机器学习中的LASSO回归模型进行参数估计,充分挖掘每个网格流速与实测断面平均流速的关系,构建推流方案。汉江流域白河水文站的应用结果表明,该方法推流成果满足规范要求,可为白河水文站及类似受水利工程影响测站的H-ADCP推流方案构建提供参考。To improve the accuracy of flow discharge at monitoring sections influenced by hydraulic structures and the performance of HADCP-based discharge monitoring system, the apparatus depth, drop height and other relevant factors were comprehensively considered. A multilinear regression model solved by least-square method was built to calculate the cross-sectional mean velocity. In order to improve the low accuracy of flow discharge in low-flow conditions, the relationship of the measured mean velocity and the velocity cell of the H-ADCP which has a high correlation with the measured-mean velocity was considered using the LASSO regression model in machine learning for parameter estimation in low-flow conditions. The approach was applied in the Baihe Hydrological Station and the results meet the requirements of specification. The research results provide references for the H-ADCP velocity derivation scheme design in the Baihe Hydrological Station and other hydrological stations affected by hydraulic projects.

关 键 词：H-ADCP 多元线性回归模型 最小二乘回归模型 LASSO回归模型 白河水文站 

分 类 号：TV122[水利工程—水文学及水资源]