## 5 Discussion
### Comparison Analysis of Water Body Classifications  
The network architecture under discussion was applied to map diverse water bodies in the Yellow River Basin in 2021, using the WIF method. This mapping differentiated water bodies into non-water bodies, seasonal water bodies, and permanent water bodies, detailed in Figure 13. For an inclusive evaluation of these extensive mapping outcomes, products from ESA [43] and JRC [44] were brought into comparison. JRC product classifies observations into four types: invalid, non-water, seasonal water bodies, and permanent water bodies. In this analysis, the 'effective water bodies' term was coined to collectively describe both seasonal and permanent water bodies within the JRC framework. In contrast, ESA product presents 11 feature categories. This study narrows its scope to the water body category, aligning the comparison to concentrate solely on 'effective water bodies' for all referenced products.  
This research undertook a comparative analysis using 2021 water body data from the JRC and the 2021 land-cover classification from ESA, focusing on case areas in Urad Front Banner in Inner Mongolia Autonomous Region, Maqu County, Zhongning County, and Dongping County. The discrepancies in the water body areas within the Urad Front Banner, as depicted in JRC's versus this study's findings and ESA's datasets, are noticeable (Figure 14). One plausible explanation for this variance could be the coarser resolution of JRC dataset, potentially leading to the erroneous classification of barren land as water bodies. However, apart from these deviations, a substantial congruence is observed among  
Figure 13: Mapping of 2021 water body distribution within Yellow River Basin.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Model** & **FLOPs (G)** & **Params (M)** & **FPS** \\ \hline FCN & 55.26 & 23.85 & 35.63 \\ PSPNet & 62.83 & 48.90 & 28.72 \\ PVT & 82.35 & 63.75 & 29.83 \\ TransUnet & 105.30 & 103.23 & 16.64 \\ SegFormer-FAN & 67.63 & 58.92 & 19.48 \\ Ours & 92.85 & 83.26 & 8.65 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of computational efficiency of different model.  
the datasets. They all adeptly delineate the spatial distribution of water bodies in the Yellow River Basin, though this study indicates a higher number of water bodies compared to the figures in JRC and ESA datasets.  
In the four case areas of Urad Front Banner, Maqu County, Zhongning County, and Dongping County, this study demonstrates superior accuracy in detecting both extensive and smaller water bodies when compared to JRC and ESA datasets. This is particularly evident in Maqu County and Zhongning County, regions with a dense river network comprising Yellow River's main course and numerous smaller tributaries. JRC's data, with a spatial resolution of 30 m, fails to capture many smaller water bodies. Furthermore, in areas like Urad Front Banner and Dongping County, known  
Figure 14: Comparative analysis of different water body detections in various products.  
Dongping Lake respectively, ESA's datasets offer static results, unable to account for seasonal water bodies and thereby omitting them. This research stands out by considering the seasonal dynamics of water bodies and employing higher-resolution data, which contribute to the enhanced accuracy in water body identification.