Estimation of River Ice Thickness in the Shisifenzi Reach of the Yellow River With Remote Sensing and Air Temperature Data

Abstract

River ice is an important part of the cryosphere, and effective monitoring of ice thickness information is essential for river ice research. The task of preventing and controlling winter ice damage in the Yellow River is severe, and it is significant to explore the applicability of different ice thickness estimation methods in this region. There is a lack of inversion studies on the thickness of the Yellow River ice. In this study, a typical reach of the Yellow River was selected as the research area. Based on the measured ice thickness data for many years, the applications of river ice thickness estimation models based on remote sensing and air temperature were explored respectively in this area. The results show that the VV polarized backscatter coefficient of Sentinel-1 SAR data has the highest correlation with the measured ice thickness, with a Pearson correlation coefficient of 0.702. SAR ice thickness inversion results are helpful to identify ice jam location. The simulation accuracy of the air temperature model for ice thickness is better than that of the SAR model. Long-term air temperature-based ice thickness estimates show the maximum ice thickness in the study area is thinning at a rate of –0.7 cm a decade.

Keywords

• Air temperature
• remote sensing
• river ice thickness
• Sentinel-1
• the Yellow River