With global warming, extreme weather such as floods and waterlogging occurs more frequently and seriously in recent years. During the flood, the surrounding environment of the GNSS (Global Navigation Satellite System) station will change as the volume of water increases. Considering the multipath error is directly relevant to the observation environment, thus, the influence of flood on the L4 combination observation (a geometry-free ionosphere-free linear combination of carrier phase) which is related to the multipath error of GPS (Global Positioning System) and GLONASS satellites is investigated in depth. In addition, the ground track repetition periods of GPS and GLONASS satellites are analyzed in the sky plot to illustrate the rationality of chosen reference day. Based on the results of the satellite sky plot, one and eight days are adopted to demonstrate the influence of flood on L4 combination observation for GPS and GLONASS satellites, respectively. Real data sets collected at the ZHNZ GNSS observation station during the flood from DOY (Day of Year) 193 to DOY 204, 2021 are used. Experimental results show that the flood has a significant impact on the L4 combination observation of GPS and GLONASS satellites, and the fluctuation of L4 under flood performs much larger than that of without flood. For GPS satellites, the maximum RMS (root mean square) increase rate of L4 under flood is approximately 186.67% on the G31 satellite. Even for the minimum RMS increase rate, it can reach approximately 23.52%, which is the G02 satellite. Moreover, the average RMS increase rate of GPS and GLONASS satellites can reach approximately 109.53% and 43.65%, respectively. In addition, the influence of rainfall and hardware device are also investigated, which can further demonstrate that the fluctuation of L4 is mainly caused by the flood but not by the rainfall and hardware device elements. Thus, based on the above results, the influence of flood on L4 observation should be taken into account during the applications of L4 used, such as the retrieval of soil moisture and vegetation water content based on GNSS L4 combination observations

The strength of a GPS carrier-to-noise ratio (CNR) signal is closely influenced by the multipath effect. This effect becomes more pronounced during flood events, as the reflection coefficient of water is significantly higher than that of dry soil. Consequently, the CNR measurements of GPS signals are impacted by floods. Based on this theory, the fluctuation of the CNR during a flood can be used to accurately monitor the process of a flood from occurrence to recession. Considering that the strength of the CNR largely depends on the satellite and frequency, and the characteristics of the influence of a flood on the CNR are different for each frequency, a new method based on the GPS dual-frequency direct signal CNR and the strength constraint threshold strategy was developed to increase the accuracy of the flood dynamics monitoring process. By using 64 MGEX (Multi-GNSS Experiment) stations distributed globally, an accurate direct-signal CNR threshold model of GPS dual-frequency was established. The threshold model demonstrated that the average difference of the direct-signal CNR, which is larger than 45 dB-Hz, between adjacent days at GPS L1 and L2 frequencies is 0.0659 dB-Hz and 0.0661 dB-Hz, respectively. Moreover, GPS real datasets in Zhengzhou city, China, from DOY (day of year) 199 to DOY 203, 2021, were collected to assess the proposed method. Based on the fluctuation of the direct-signal CNR threshold, the experimental results show that the flood appeared at about 16:04 PM on DOY 200, 2021, reached a peak at approximately 5:05 AM on DOY 202, and totally subsided at about 8:54 AM on DOY 202. Thus, the experiment results reveal that the proposed method accurately monitors the entire process of a flood from occurrence to recession, which provides valuable insights into operational flood dynamics, warning, and monitoring based on the GPS technique.