## 3 Methodology  
The SWAT model's computational framework has been continuously enhanced and refined since 1995, progressively expanding its applicability due to the model's powerful computational capabilities and robust physical mechanisms. Consequently, it has become a pivotal foundation for developing strategies and policies in managing water resources [23; 24]. According to a 2015 statistical study on hydrological modeling [25], the SWAT model was employed in about 46% of such studies, indicating its position as one of the most widely used hydrological models. In the model's temporal scope, the recent inclusion of the SWAT model's hourly simulation module introduces greater complexity. However, it necessitates heightened precision in meteorological input data, real measurements, and a higher level of intricacy compared to daily scale simulations [26]. DEM input data are used to delineate watershed boundaries, define sub-basins, establish the river network, and generate flow directions in the watershed. Once the watershed information is extracted, land use and soil property data are incorporated into the model. Topography, land use, and soil property data are reclassified, and unique combinations of land use type, soil type, and slope type are categorized as Hydrologic Response Units (HRUs) in the SWAT model. It assumes that HRUs within the same class exhibit similar hydrological behaviors, and hydrological processes are computed separately for each class of HRUs in sub-basins. Meteorological information for each HRU is generated based on the data from the nearest meteorological station. This study utilized ArcSWAT version 2012 to build the model and performed parameterization using SWAT-CUP 2012. The watershed extraction function within ArcSWAT 2012 was utilized to delineate sub-basins and establish river networks. ArcSWAT 2012 automatically extracts sub-basins and establishes river networks based on the elevation data, and it determines the number of sub-basins and the density of river networks by setting the minimum area threshold of sub-basins. The principle is that it should be detailed enough to capture significant topographic changes within the watershed. In this study, we divided a basin of 759.5 km\({}^{2}\) into 47 sub-basins, which is a relatively detailed division, although the sub-basin division levels basically do not clearly affect the simulation results [27]. In addition, we used Google Earth to verify the river network path automatically extracted by the model to prevent path deviation. A threshold of 981 ha was adopted for watershed extraction, leading to the classification of 369 hydrological response units. Precipitation data with a 1 h interval were input into the model, formatted as \"year month day, 60\" with \"60\" signifying 60 min (equivalent to 1 h). The calibration and validation of the SWAT model were executed using the SUFI-2 algorithm within the SWAT-CUP software. Throughout this process, hourly runoff measurements were incorporated in the format \"FLOW_OUT_Year_Month_Day_Hourly Runoff Value\". In contrast to daily, monthly, and annual scale simulations, the inclusion of an hourly simulation plug-in was essential for executing hourly simulations. Since the original SWAT-CUP software only works on daily, monthly, and yearly scales, a plug-in for hourly simulation was designed for calibration and