Monitoring river water level using multiple bounces of bridges in SAR images

Monitoring river water level is of great importance to understand hydrological and hydraulic processes and evaluate flood and landslide risk. This paper proposes a method for estimating river water levels under bridges using multi-temporal high-resolution synthetic aperture radar (SAR) intensity images. Due to the side-looking characteristics of SAR data acquisitions, bridges crossing over rivers usually exhibit multiple bounce echoes in SAR images caused by the multipath scattering. The range difference of the multiple returns is proportional to the clearance between the water surface and the bridge. In this study, the water level oscillation of Yangtze River under Badong Yangzte River Bridge (China) was calculated by estimating the range pixel distances of the multiple bounces in ALOS-2 PALSAR-2 images using cross correlation algorithm. Besides, a linear correlation between the range pixel distance of the multiple bounces and in situ water level measurements was found, with a coefficient of determination equal to 0.9985. This relationship allowed estimating the river water level in each SAR acquisition, with an average error equal to -0.39 m and root mean square error of 0.51 m, and the elevation of the bridge, with an error of about 0.5 m, which is smaller than the theoretical uncertainty of the method (1.24 m). The obtained results show the efficiency of the method in estimating river water levels. (C) 2021 COSPAR. Published by Elsevier B.V. All rights reserved.

Automated summary

This study proposes a method for estimating river water levels under bridges using high-resolution SAR images. The method accurately estimates the water level oscillation under the Badong Yangzte River Bridge on the Yangtze River and demonstrates efficiency in estimating river water levels.