# Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China
## 3 Results
### SMAP Monitoring Results  
Firstly, we use the brightness temperature (Tb) and soil moisture observed by SMAP microwave radiometer to monitor the flood. Since GNSS signals are circularly polarized, it is necessary to convert the linearly polarized Tb measured by SMAP into circularly polarized Tb [25; 36]. Then, the changes in brightness temperature and soil moisture were used to reflect the impact of flooding. As shown in Figures 9 and 10, we mapped the SMAP brightness temperature and soil moisture over a period of three days from 16 July to 27 July 2021 (close to the temporal resolution of SMAP data), and monitored the flood.  
Compared to Figure 9a, from19 July to 24 July 2021, the brightness temperature changes of the black box in Figure 9b and the red box in Figure 9c were more obvious. Compared to Figure 10a, from 19 July to 24 July 2021, the soil moisture of the black box in Figure 10b and the red box in Figure 10c also changed. It shows that the duration of the flood is from 19 July to 24 July 2021, and the area corresponding to the black box (Zhengzhou) and the area corresponding to the red box (Xinxiang) are also severely affected areas. Therefore, based on the changes of SMAP brightness temperature and soil moisture, the occurrence of floods and the affected areas can be monitored.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**City** & **Inundated Area (Square Kilometers)** \\ \hline Xinxiang & 6532 \\ Jiaozuo & 3270 \\ Zhengzhou & 2505 \\ Anyang & 1200 \\ Zhoukou & 1170 \\ Hebi & 998 \\ Kaifeng & 893 \\ Luohe & 495 \\ Pingdingshan & 420 \\ Xuchang & 330 \\ Puyang & 90 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The inundation area of the affected cities.  
Figure 9: (**a–d**) are the changes in the brightness temperature obtained from SMAP before and after the flood (from 16 July to 27 July 2021).  
In addition, SMAP time-series data on brightness temperature and soil moisture from 1 July to 15 August 2021, were collected for the study area to see the changes in both types of data before, during and after the flood. Surface brightness temperature and soil moisture values from the sampled pixel of the affected areas were plotted to see the response of the brightness temperature and soil moisture to the flood. Similar to [37], the median of all grids was selected as the threshold between the water and the land during the flood period (from 19 July to 24 July 2021). As shown in Figure 11, the threshold is 248 K for using brightness temperature data for time-series analysis. For using soil moisture data for the time-series analysis, the threshold is 0.38 cm\({}^{3}\)/cm\({}^{3}\) which is similar to that used in [37].  
Figures 12 and 13 are the inundated area maps drawn by SMAP brightness temperature and soil moisture, respectively (from 16 July to 27 July 2021). Based on the estimates from the SMAP observations, the approximate change in the flood and the inundated areas can be detected. Like [25], it also proved that SMAP can also monitor floods.  
Figure 11: (**a**) Surface brightness temperature of the grid from the 11 cities. (**b**) Surface soil moisture of the grid from the 11 cities.The red line indicates the median of the grid. The green dashed line represents the threshold (248 K and 0.38 cm\({}^{3}\)/cm\({}^{3}\)). The blue line represents the time series change of bright temperature (**a**) and soil moisture (**b**) of the grid. The black dashed line is from 19 July to 24 July 2021.  
Figure 10: (**a–d**) are the changes in soil moisture obtained from SMAP before and after the flood (from 16 July to 27 July 2021).