Accurate Retrieval of the Whole Flood Process from Occurrence to Recession Based on GPS Original CNR, Fitted CNR, and Seamless CNR Series

Abstract

The CNR (Carrier-to-Noise Ratio) of GPS (Global Positioning System) satellites is highly relevant to the multipath error. The multipath error is more serious in the flood environment since the reflection and diffraction coefficients of water are much higher compared to dry soil. Thus, the amplitude of CNR will decrease in the flood environment. In this study, the relationship between multipath error, flooding, and CNR is introduced in theory. Then, by using the characteristic of the orbital repetition period, the stability of CNR between 2 adjacent days in a static observation environment is demonstrated by 32 MGEX (Multi-GNSS Experiment) stations in different latitude and longitude regions of the world. The results show that the average RMS of different CNRs between two adjacent days is only about 0.62 dB-Hz. In addition, the correlation coefficient of CNRs between two adjacent days is analyzed. The correlation coefficient of the original signal CNR is 0.997. Moreover, after mitigating the influence of random noise and lower CNR, the correlation coefficients of the fitted CNRs larger than 40 dB-Hz can reach 0.999. Thus, based on the fluctuation in original CNR, fitted CNR, and seamless series characteristics of CNR, the whole flood process from occurrence to recession can be retrieved. A flood that occurred in Zhengzhou City, China, from DOY 200 to DOY 202, 2021 is used to demonstrate the process of retrieval. The experimental results indicate that the flood appeared at about 15:30 pm on DOY 200, reached a peak at approximately 8:30 am on DOY 202, and totally subsided at about 10:00 am on DOY 202. In conclusion, the CNR can be effectively used to retrieve the whole process of the flood, which lays a foundation for researching flood detection and warning based on GPS satellites.