河流断面特征因子对表面流速系数的影响规律研究
Study on the Influence of River Cross-Sectional Characteristics on Surface Flow Velocity Coefficient

为明确河流断面特征因子对河流表面流速系数的影响机制，提升视觉测流方法精度和水文监测智能化水平，本研究基于福建省多个水文站的实测数据，提出一种系统的断面特征因子提取与概化方法。研究采用多尺度因子分析方法，构建流速剖面对数律分布理论模型，分析水力半径、河宽、断面面积、边坡系数、二次流、河道宽深比、河床粗糙度及水生植被密度等断面特征因子与表面流速系数的响应关系，并利用主成分分析法(PCA)进行降维处理。结果表明：① 表面流速系数与水力半径、河宽等因子分别存在不同的显著响应关系；② 通过主成分分析提取出三个核心公共因子：水力特性因子、河道形态因子和河床糙度因子；③ 理论模型定性揭示了不同断面形态与水文条件下表面流速系数的变化规律。研究成果为非接触式智能水文监测提供理论依据与技术支撑。
To clarify the influence mechanisms of river cross-section characteristic factors on the surface velocity coefficient and enhance the accuracy of visual flow measurement methods along with the intelligence level of hydrological monitoring, this study proposes a systematic method for extracting and generalizing cross-section characteristic factors based on field data from multiple hydrological stations in Fujian Province of China. A theoretical model of logarithmic velocity distribution was developed using multi-scale factor analysis to investigate the response relationships between surface velocity coefficient and cross-section characteristic factors—including hydraulic radius, channel width, cross-sectional area, bank slope coefficient, secondary flow, aspect ratio (B/H), bed roughness, and aquatic vegetation density. Dimensionality reduction was performed via principal component analysis (PCA). The results indicate that: 1) Distinct significant response relationships exist between the surface velocity coefficient and factors such as hydraulic radius and channel width; 2) Three core common factors were extracted through PCA: hydraulic characteristic factor, channel morphological factor, and bed roughness factor; 3) The theoretical model revealed variation patterns of surface velocity coefficient under different cross-section morphologies and hydrological conditions. This research provides theoretical foundations and technical tools for improving visual flow measurement accuracy and advancing intelligent hydrological monitoring.