## 3 Methods
### Processing Steps for \(T_{b}\) Data  
Before extracting the \(T_{b}\) data, pixels \(M\) and \(C\) needed to be selected according to the station location. The \"wet pixel\" (pixel \(M\) with the \(T_{b}\) value marked as \(M\)) that covers part or all of the river channel is located near the station in a non-bending river. The water level in this pixel will rise when flooding, so the floodplain on both sides of the river shows \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Basin**} & **YZR** & **YR** & **PR** & **SWR** & **HR** & **SER** & **Hai** & **SLR** & **IR** \\ \hline \multicolumn{2}{c}{**Tropical**} & & & & & & & & \\ \multicolumn{2}{c}{**Arid**} & & & 2 & & & 1 & 2 & 4 \\ \multicolumn{2}{c}{**Climate**} & **Temperature** & 21 & 7 & 4 & 4 & 5 & 3 & & \\ \multicolumn{2}{c}{**Cold**} & & & 2 & 2 & & 4 & 5 & \\ \multicolumn{2}{c}{**Polar**} & 4 & 2 & & 7 & & & & & \\ \hline \multicolumn{2}{c}{**Grassland**} & 4 & 5 & & 6 & & & & & \\ \multicolumn{2}{c}{**Forest + grassland**} & 4 & 1 & 2 & 2 & & 2 & 2 & \\ \multicolumn{2}{c}{**LULC**} & **Crops** & 5 & 2 & 2 & 2 & 5 & & 3 & & \\ \multicolumn{2}{c}{**Urban**} & 6 & 2 & 1 & 1 & & & & 1 \\ \multicolumn{2}{c}{**Forest land**} & 3 & & 3 & & 3 & 5 & & \\ \multicolumn{2}{c}{**Bare land**} & 3 & & 1 & & & & & 3 \\ \hline \multicolumn{2}{c}{**Mean**} & **\textless{}100** & 6 & 7 & 1 & 6 & 3 & & 5 & 7 & \\ \multicolumn{2}{c}{**discharge**} & **100–500** & 6 & 1 & 2 & 6 & 2 & 3 & & 4 \\ \multicolumn{2}{c}{**(m\({}^{3}\)/s)**} & \textgreater{}500 & 13 & 1 & 1 & 3 & 2 & & & \\ \hline \multicolumn{2}{c}{**Catchment**} & **\textless{}10** & 7 & 5 & 2 & 4 & 2 & 2 & 3 & 1 & \\ \multicolumn{2}{c}{**area**} & **10–50** & 5 & 3 & 2 & 7 & 2 & 1 & 2 & 6 & 4 \\ \multicolumn{2}{c}{**(\(\times 103\) km\({}^{2}\))**} & **\textgreater{}100** & 13 & 1 & & 4 & 3 & & & & \\ \hline \multicolumn{2}{c}{**Topography**} & **Fist terrace** & 4 & 6 & & 11 & & 3 & & & \\ \multicolumn{2}{c}{**Second terrace**} & 8 & 3 & 1 & 4 & & & 1 & 3 & 4 \\ \multicolumn{2}{c}{**Third terrace**} & 13 & & 3 & & 7 & & 4 & 4 & & \\ \hline \multicolumn{2}{c}{**Data Period**} & **1996–2005** & 4 & 3 & 1 & 4 & 6 & & 1 & 3 & \\ \multicolumn{2}{c}{**1999–2008**} & 21 & 6 & 3 & 11 & 1 & 3 & 4 & 4 & 4 \\ \hline \multicolumn{2}{c}{**Total**} & 25 & 9 & 4 & 15 & 7 & 3 & 5 & 7 & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Statistics of climate, land use/cover (LULC), topography and data period of 79 stations for the 9 basins, which are Yangtze River Basin (YZR), the Yellow River Basin (YR), the Pearl River Basin (PR), the Southwest River Basin (SWR), the Huai River Basin (HR), the Southeast River Basin (SER), the Hai River Basin (Hai), the Songliao River Basin (SLR) and the Inland River Basin (IR). periodic or seasonal changes in the \(T_{b}\) value. Correspondingly, the \"dry pixel\" (pixel \(C\) with the \(T_{b}\) value marked as \(C\)) covers only land areas near the \"wet pixel\". To make the selection process automatic, \(C\) is determined as the brightest (95 th percentile, avoiding selecting outliers) value of the pixels within a 9 \(\times\) 9 pixel array centered on the pixel \(M\). Ideally, the \(C\) is not influenced by water bodies and can also represent the \(T_{b}\) of the region if all other influencing factors can be excluded. According to the \(M/C\) signal method, by obtaining the ratio of \(T_{b}\) value of the dry and wet pixels, the influence of other environmental factors on the \"wet pixel\" can be excluded. Moreover, [PERSON]'s radiation law considers that the \(T_{b}\) value of the object is related to its physical temperature \(T\) and emissivity \(\varepsilon\).