## 6 Conclusions  
This study investigated the performance capability of the SWAT model in simulating runoff at the hourly scale, utilizing the coastal watershed as the subject of analysis. The research encompassed an assessment of the model's effectiveness in capturing baseflow, moderate flood peaks (0-200 m\({}^{3}\)/s), and high flood peaks (\(>\)200 m\({}^{3}\)/s). Furthermore, the study explored sensitivities within 14 hydrologically significant parameters, elucidating their impacts on hourly simulations and offering insights to enhance the efficiency of high-temporal-scale simulations. An analysis of intra-annual variability of hydrological elements within the basin was conducted using the model. Consequently, several key conclusions emerged from the high-temporal-scale simulations conducted on the basin:  
(a) The SWAT model's hourly simulations largely succeeded in capturing variations in baseflow and moderate flood peaks (0-200 m\({}^{3}\)/s) at the hourly scale. However, underestimation was observed in simulating high flood peaks (\(>\)200 m\({}^{3}\)/s).  
(b) In the parameter sensitivity analysis, specific parameters with significant impact on hourly flow simulations were identified, notably the influential role of the hourly simulation-specific parameter BIFO_LIST in regulating hourly scale baseflow.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Elements** & **T-Statistic** & \(p\)**-Value** \\ \hline Surface runoff & 3.25 & \(<\)0.05 \\ Lateral flow contribution to & 3.03 & \(<\)0.05 \\ streamflow & & \\ Groundwater contribution to & 2.55 & \(<\)0.05 \\ streamflow & 2.91 & \(<\)0.05 \\ Evapotranspiration & 4.95 & \(<\)0.05 \\ Air temperature & 6.19 & \(<\)0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The T-statistic and \(p\)-value for each hydrological element.  
(c) Through basin-wide hydrological element analysis, it was deduced that precipitation's effects follow a descending order of magnitude on major hydrological constituents: surface runoff, lateral flow, groundwater, and evapotranspiration. Notably, the influence of precipitation on surface runoff surpasses its impact on baseflow.  
Y.C.: conceptualization, methodology, software, validation, formal analysis, writing--original draft preparation; C.F.: conceptualization, methodology, writing--review and editing; M.Y.: software, resources. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key Research and Development Program of China, grant number 2019 YFA0607100, and the Pioneer Hundred Talent Program, Chinese Academy of Sciences, grant number Y7 BR021001.  
Not applicable.  
The DEM data used in the model for dividing watersheds and sub-basins are available at [[https://earthexplorer.usgs.gov](https://earthexplorer.usgs.gov)]([https://earthexplorer.usgs.gov](https://earthexplorer.usgs.gov)) (19 July 2019). Both soil data and land use are sourced from [[https://nlftp.mlit.go.jp](https://nlftp.mlit.go.jp)]([https://nlftp.mlit.go.jp](https://nlftp.mlit.go.jp)) (29 July 2019). Meteorological data and hourly observed runoff data are obtained from [[http://www.data.jma.go.jp](http://www.data.jma.go.jp)]([http://www.data.jma.go.jp](http://www.data.jma.go.jp)) (30 July 2019) and [[http://www.river.go.jp](http://www.river.go.jp)]([http://www.river.go.jp](http://www.river.go.jp)) (5 August 2019), respectively. Other data in this study are available upon reasonable request to the corresponding author (C.F., [EMAIL_ADDRESS]).  
The authors declare no conflict of interest.