Author(s): Jaehyuk Lee; Kwangtae Choi; Hokun Chung; Sejong Kim; Hoetae Jeong

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Keywords: Extended Kalman Filter; H-ADCP; Low-velocity flow; Time-series filtering

Abstract: Reliable velocity measurement under low-flow conditions remains a major challenge in automatic discharge monitoring using Horizontal Acoustic Doppler Current Profilers (H-ADCPs). This study proposes a post-processing framework that combines Interquartile Range (IQR)-based outlier removal with a selective application of the Extended Kalman Filter (EKF) to enhance the quality of H-ADCP time-series data. Field measurements were conducted at three bridges on the Han and Nakdong Rivers (Gwangjin, Yeoju, and Hoguk) in October 2024. The EKF was selectively applied to segments where the Coefficient of Variation (CV) exceeded 0.1, indicating unstable velocity fluctuations. Results show that in the low-velocity regime (< 0.10 m/s), the CV decreased by an average of 22.8% and a maximum of 33.7%, while higher-velocity segments (≥ 0.10 m/s) improved by up to 16.7%. Comparison with official reference velocities confirmed a reduction in Root Mean Square Error (RMSE) and an increase in Coefficient of Determination (R²) at most sites. The proposed hybrid filter effectively suppresses short-term noise without distorting long-term flow patterns. This approach provides a practical solution for improving H-ADCP measurement reliability in real-time river monitoring systems.

DOI:

Year: 2026