## 4 Conclusions  
In this study, the performances of nine uncorrected versus corrected satellite and reanalysis precipitation products, including TMPA-3B42V7, TMPA-3B42 RT, IMERG-cal, IMERG-uncal, ERA5, ERA-Interim, GSMaP, GSMaP-RNL, and PERSIANN-CCS, were comprehensively evaluated at the daily scale from 2006 to 2018 over the Beijing and Dongjiang River Basins. Further, we compared two merging methods to improve hydrological simulation: merging multi-source precipitation inputs and directly merging their corresponding streamflow outputs. The major findings are drawn as below:  
In general, compared with the best performance of the GSMaP precipitation dataset, two merged precipitation products were more consistent with gauge observations than their original members, while the worst performance was found for PERSIANN-CCS and GSMaP-RNL. All the corrected precipitation products showed an increased ability to capture spatial precipitation patterns and trends compared to their uncorrected counterparts, particularly in the Beijing River, which has a larger drainage area. In addition, TMPA-3B42 RT and ERA5 showed similar performances across the study basins during the whole period. For Scenarios I and II, the performance of streamflow simulations derived from the merged uncorrected precipitation data (Average Rain 2) were better than their original  
Figure 14: Statistical metrics of (**a**) CC, (**b**) BIAS, (**c**) MAE, and (**d**) KGE’ of the daily CREST-simulated and two merged streamflow series versus the observations for five flood categories during 2006–2018 in the Dongjiang River Basin. members, but the merged corrected ones (Average Rain 1) failed to improve streamflow simulations. This indicates that merging IMERG-cal and GSMaP precipitation makes little difference to hydrological modeling. For Scenario III, all the BIAS values of different merged streamflow simulations were slightly reduced compared to those of their merged precipitation products over the study basins, which indicates that streamflow simulations under Scenario III achieve better results than those of Scenarios II and I. According to different flood categories, for each river basin, the performances of almost all streamflow series deteriorated from Flood Level I to V. The rankings of two merged precipitation products were similar to those of their corresponding merged streamflow simulation. In conclusion, the results suggest that merging multi-source modeled streamflow outputs was more efficient than merging multi-source precipitation inputs. The findings presented in this study will provide valuable information for improving the hydrological simulation of global precipitation products. However, it is essential to note that the quality of merged gridded precipitation datasets is greatly affected by merging approaches and various errors propagated from each individual component. Furthermore, it is also necessary to clarify the potential effects of hydrological model structure and associated model parameters and basin characteristics in future work. Finally, due to the limitations of the available discharge data, further efforts should be made to use different approaches to expand applicability in more regions, to facilitate comparison. Conceptualization, [PERSON], [PERSON] and W.J. ; methodology, [PERSON] and G.T. ; analysis, [PERSON]; writing--original draft preparation, [PERSON]; writing--review and editing, [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and J.S. ; funding acquisition, [PERSON] and W.J. All authors have read and agreed to the published version of the manuscript. This research was jointly funded by the National Key R&D Program of China (2022 YFF0711602), the National Natural Science Foundation of China (42271479), the Science and Technology Program of Guangzhou (2023A04J1993), the GDAS' Project of Science and Technology Development (2024 GDASZH-2024010101, 2022 GDASZH-2022010202, 2022 GDASZH-2022020402-01), and the Science and Technology Program of Guangdong (2021B1212100006).