# Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China
## 1 Introduction  
Floods are one of the most common and destructive natural disasters in the world. The occurrence of floods has a severe impact on human life and the environment. And it causes severe economic losses to society [1; 2; 3]. Climate factors and geographical environment are essential reasons behind flooding. After heavy rains, when water overflows lakes and dams, floods occur in low-lying areas. In case of high-intensity, large-scale rainstroms, the affected area is prone to flooding and serious disasters that may even emulate the cities [4; 5]. Recently, Zhengzhou, Henan Province and other cities have encountered extreme weather, which has caused serious floods. Timely and detailed mapping of the inundated area and also the disaster-affected area is essential for post-disaster rescue and restoration. Additionally, it can help relevant departments better understand the temporal and spatial evolution of this type of disaster, and provide references for the areas that may be affected again [6; 7]. At present, flood monitoring on a large scale can be achieved using spaceborne remote sensing data. Optical remote sensing systems (for example, MODIS, Sentinel-2) can providedata with good spatial resolution [8; 9]. However, they cannot penetrate clouds and Earth's surface is usually obscured by clouds during floods. Therefore, they are often unable to monitor the progress of floods. Microwave remote sensing, in contrast, is not affected by these limitations. However, current active radar satellites cannot provide observations with high spatial and temporal resolution at the same time. For example, Synthetic Aperture Radar (SAR) can provide observations with high spatial resolution, but the revisit period is long (6-11 days, e.g., TerraSAR-X, and Sentinel-1 SAR) [10]. Due to the high dynamics of floods, SAR images cannot be used to monitor floods. GNSS-R (Global Navigation Satellite System -Reflectometry) technology is a remote sensing technology that extracts geophysical parameters by receiving and processing GNSS signals reflected on the Earth's surface [11]. This technology is an effective microwave remote sensing method, and it has numerous GNSS signals (e.g. GPS, Galileo, GLONASS, and BDS) as a source of opportunity [12]. A constellation of GNSS-R small satellites can provide a much shorter revisit time, and NASA launched a CYGNSS (Cyclone Global Navigation Satellite System) satellite constellation in December 2016, which provides sufficient data to facilitate the use of GNSS-R technology. The overall median revisit time is 2.8 h, and the mean revisit time is 7 h [13]. Theoretically, the reflected footprint of CYGNSS is nearly 0.5 km \(\times\) 0.5 km. For oceans with very rough surfaces, the spatial resolution is approximately 25 km \(\times\) 25 km [14]. CYGNSS uses a passive sensor with L-band frequency waves and can work irrespective of time or weather conditions [15]. Thus, compared with other remote sensing technologies (such as optical and active remote sensing varieties), CYGNSS observations for flood monitoring can meet the requirements of high dynamics. At present, spaceborne GNSS-R data are being used to conduct research on sea ice and sea altimetry [16; 17; 18], soil moisture [19; 20; 21], sea surface wind speed [22; 23], flood monitoring [24; 25], surface vegetation water content [26] etc. The papers [15; 21] indicate that the reflectivity obtained from TDS-1 and CYGNSS data can be used to perceive surface water bodies, such as lakes and rivers. The reflectivity of water bodies is higher and that of arid areas is lower. This mechanism can help detect soil moisture, flooding areas and inland waters. This paper uses CYGNSS high temporal and spatial resolution data for flood monitoring. The main content is to quantify the occurrence and duration of flood caused by extreme weather in Henan, and to map the distribution of the inundated area and those most affected by the flood.