## 5 Discussion
We selected five typical sites (Morecambe Bay, U.K. [12], Gomso Bay, Korea [10], Gulf of Tonkin, Vietnam [6], the Yangtze River mouth [14], and Dongsha Sandridges [15]) to compare with Tiaozini in our study in terms of vertical accuracy, horizontal accuracy and time span of DEM results. Details areelaborated in Table 3.  
DEM vertical accuracy: According to the previous studies, the accuracy of DEMs obtained by the waterline method is mostly within 0.5 m. For the more stable area, just like Gomso Bay, Korea, [PERSON] et al. (2008) succeeded in generating intertidal DEMs with an accuracy of 10.9 cm in the tidal flats [10]. In [6], the vertical accuracy reached 0.144 m in the northern coast of Vietnam, which is a stable ground. In Dongsha Sandbank of the Jiangsu coast (relatively unstable area), a DEM effectively contains the average height error within 47 cm [15]. In the author's previous study, the accuracy of the DEM obtained was within 0.2 m in Jiangsu's near shore [13]. Thus, the stability and complexity of tidal flats often determines the level of accuracy. [PERSON] et al. (2001) indicated that the vertical errors are different at different slopes. On 1:500 slope beaches 18-22 cm is achieved. This rises to 27 cm on 1:100 slope beaches, and 32 cm on 1:30 slope [34]. As shown in Table 3, in Tiaozini which is the extremely unstable area, the vertical accuracy can reach between 0.3 m and 0.4 m. It was credible and within reasonable superior range. DEM horizontal accuracy: Horizontal accuracy is less involved in previous studies Due to the different distribution density and sources of remote sensing images. The waterline method uses medium resolution remote sensing image data to extract the water edge line. Since the waterline itself has an accuracy of one pixel (e.g., 30 m), no matter how many waterlines are located at different tide levels, the DEM horizontal accuracy can only be infinitely close to, but less than one pixel (e.g., 30 m) [16]. As shown in Table 3, horizontal accuracy in previous studies was 30-60 m. Our study used each pixel of the remote sensing image to participate in the calculation, allowing the spatial resolution (e.g., 30 m) to be reached. From the perspective of horizontal accuracy, our method is better. However, the simulation results often require smooth fitting to remove noise from the DEM results. The timeliness of DEM acquisition: Because the waterline method requires a certain time span, it is suitable for relatively stable tidal flat areas, like areas with little or no change within a short time. At present, sufficiently high-quality remote sensing images are the core of the waterline method. In previous studies, the time span of images was one year, at least, up to as much as 3-4 years, as shown in Table 3. However, areas where the tidal flats change drastically, such as Tiaozini, the tide water from both north and south meet there every day [3]. Additionally, the topography of tidal flats is highly susceptible to affected changing tidal creeks, just like Xidagang, Dongdagang, Tiaoyugang feature intensive erosion and deposition [18]. Our model can invert the synchronous topography of the tidal flat at the synchronization time of remote sensing image, which greatly improves its timeliness to monthly levels. From the perspective of time accuracy, our method is better, especially in tidal \begin{table}
\begin{tabular}{c c c c c} \hline
**Parameter Combination** & **Average Error** & **Mean Absolute Error** & **Root Mean Square Error** & **Coefficient of Determination (R\({}^{2}\))** \\ \hline
4 Parameters & \(-\)0.03 m & 0.75 m & 0.73 m & 0.65 \\
6 Parameters & \(-\)0.02 m & 0.49 m & 0.52 m & 0.81 \\
7 Parameters & 0.01 m & 0.27 m & 0.32 m & 0.90 \\ \hline \end{tabular}
\end{table} 
Table 2: Comparison of simulation accuracy of three models.