## 1 Introduction  
With global warming, floods and urban water-logging caused by extreme weather have been more frequent in recent years, which dramatically affects the safety of human lives and properties. Thus, many flood detection and prediction methods have been developed to reduce the effect of flooding in recent years [1; 2]. Basically, these methods can be divided into three categories: hydrological model [3; 4; 5; 6], numerical model [7; 8], and SAR (Synthetic Aperture Radar) satellite technique [9; 10]. However, whether the GPS (Global Positioning System) can be used to retrieve or detect the flood has not been investigated, and this is a very interesting research topic.  
The multipath error is mainly caused by the signal from a satellite arriving at the receiver via different paths due to the reflection and scattering of the signal [11]. Thus, multipath error is relevant to the environment of the receiver antenna. Considering that the environment of the observation station will be changed during the flood, the multipath error under the environment of the flood is obviously different from the environment without the flood [12]. [PERSON] et al. [13] analyzed the effect of the surrounding environment on GPS and BDS (BeiDou System) satellites; the results show that pseudorange multipath error is largely increased in the environment with water compared with the open sky. In addition, [PERSON] [11] demonstrated that multipath error is relevant to the environment, especially the reflection coefficient of the surface of the object. Experimental results show that the multipath error induced by dry soil is much lower compared to the water. Thus, it can be inferred that multipath error is more serious in the environment of the flood compared to a normal environment without flooding.  
CNR observation is mainly used to reflect the quality of the GPS signal. Considering that the quality of the GPS signal is related to the multipath effect, the multipath effect can be further reflected in CNR observation. Based on this principle, [PERSON] et al. [14] developed a new method to detect the multipath error for GPS satellites by using the CNR observation. To mitigate the influence of random noise, [PERSON] and [PERSON] [15] proposed using a filter to extract the multipath error from CNR observation. By using the difference between different frequencies, [PERSON] and [PERSON] [16] presented a new method to mitigate the pseudorange multipath error of GPS satellites based on three frequencies. [PERSON] et al. [17] demonstrated an improved method to mitigate the influence of carrier phase multipath error based on CNR statistical strategies. In addition, [PERSON] et al. [18] indicated that the multipath error of carrier phase observation is strongly related to the CNR, and there is an inverse relation between them. [PERSON] et al. [19] investigated the influence of marine environments on BDS satellites, and experimental results show that the CNR of BDS satellites collected in a marine environment is lower than in a land environment. In addition, [PERSON] et al. [20] analyzed the influence of flood on GPS satellites, and results demonstrate that the CNR collected during the flood performs worse than in an environment without flooding. Moreover, by utilizing the technique of GNSS-IR (Global Navigation Satellite System Interferometric Reflectometry), the CNR can also be used to retrieve the soil water variation [21], snow depth [22], and sea level [23]. Thus, all of the above literature indicates that the multipath error is strongly relevant to CNR observation.  
Based on the above discussion, it can be inferred that the multipath error will increase in the environment of the flood, and the increased multipath error can further induce the CNR observation fluctuation in GPS satellites. Thus, taking advantage of the fluctuation in CNR observation, the whole flood process from occurrence to recession can be accurately retrieved. The concrete theory and proposed method are provided in the following sections.