## 4 Conclusions  
The present study conducted a comparative analysis of flood simulations by utilizing rain gauge, ground- and space-borne radar precipitation products. The primary objective was to assess the efficacy of incorporating two radar-based gridded data sources, namely RAR and GPM IMERG, in a dam watershed where gauge observations are relatively abundant. Additionally, this study aims to seek the feasibility of utilizing the half-hourly IMERG product in regions characterized by ungauged or limited availability of observed data. To achieve these objectives, data processing programs and two types of HEC-HMS models were developed for areal-averaged and spatially distributed gridded data based on flood simulations, focusing on the selected eight rainfall storm events. The key findings are as follows:  
1. Overall, the Korea Meteorological Administration's ground-borne weather radar data (RAR) exhibited a slight underestimation of precipitation values compared to gauge point observations, with a difference of 28.2% across all eight flood events (R\({}^{2}\) 0.86). Consequently, adjustments to related model parameter values were necessary for flood analysis using the RAR data. However, due to the spatial distribution advantages of radar rainfall, aspects related to rainfall-runoff transformation and river channel routing, such as travel time, could be simulated to generate hydrographs that closely resembled the observed discharge without the need to adjust the related parameter values;
2. For space-borne (i.e., satellite-based) IMERG precipitation data, the total observed amount was underestimated by 15.1% across the eight flood events. However, the correlation coefficient (R\({}^{2}\)) was 0.46, indicating significant differences from the gauged data. Even with adjustments to parameter values, flood simulations using the IMERG product demonstrated relatively lower correlation and model efficiency compared to the observations. This indicates a significant limitation in using the half-hourly IMERG data for flood modeling in ungauged watersheds. Despite this constraint, it is still inferred that in locations where some discharge data are available, the utilization of the model through verification and calibration is feasible;
3. When comparing the flood simulation results using the conventional method based on rain gauge observations with those using weather radar and satellite-based precipitation data, the models utilizing both radar data sources exhibited an average Nash-Sutcliffe efficiency (E\({}_{\text{NS}}\)) of 0.863 and 0.776, an R\({}^{2}\) of 0.873 and 0.787, and a percent bias (PBIAS) of 7.49% and 7.15%, respectively. The model using the areal-averaged values showed an E\({}_{\text{NS}}\) of 0.895, an R\({}^{2}\) of 0.906, and a PBIAS of 7.42%. Although there were some differences, simulations using the RAR data demonstrated relatively satisfactory performance without adjusting parameter values, confirming their utility and efficiency;
4. Despite varying ratios ranging from 26.0% to 82.2% depending on antecedent rainfall conditions, the analysis of the eight selected flood events revealed the characteristic of watershed flood discharge with an average runoff ratio of 52.5%. Finally, the aforementioned research results could be compared due to the availability of reliable discharge data obtained through extensive measurements in the upstream reaches of the watershed. Most of all, the presence of observational data is crucial in assessing the effectiveness of any hydrological model. Consequently, the utilization of hourly discharge data from multiple gauge observation points in this simulation of flood discharge can be considered as a noteworthy case study in the modeling of watershed flood management. In addition, although the GPM IMERG half-hourly product has not yet been established as a reliable dataset for hydrological modeling through this research, it is essential to apply it in diverse regions to evaluate its performance with additional case studies.