High-Frequency Centimeter-Accuracy Water Level Estimation in the Yangtze River Using Multi-GNSS Interferometric Reflectometry

Water level measurement is essential for managing and conserving water resources. The Yangtze River has a significant impact on agriculture, transportation, and local ecosystems, while traditional water level measurement still has some limitations, e.g. high cost and low coverage. Recently, Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) has become a new means for water level monitoring. This paper integrates the reflected signals from GPS, GLONASS, Galileo and BDS constellations for real time high-frequency water level estimation at Yangtze River stations (BADO and DATO). By integrating a sliding window with Variational Mode Decomposition (VMD), Iteratively Reweighted Least Squares (IRLS), and Savitzky-Golay (S-G) filtering, water level measurements at a 5-minute temporal resolution are obtained and evaluated. Our individual and combined results show that the VMD method efficiently provides more accurate and stable inversion results using signal-to-noise ratio (SNR) data in each window. The combined and filtered results increased the accuracy by over 45.88% when compared to single-system measurements. The root mean square error (RMSE) was 4.86 cm at BADO and 2.28 cm at DATO with coefficient of determination (R2) 0.99 at both stations. Our results demonstrated that the combined method enabled precise and continuous water level monitoring, which provides new pathways for hydrological monitoring and real-time water resource management.