## 3 Results and Discussion
### Streamflow Simulation Scenarios and Results
#### 3.3.1 Scenario I: Hydrological Model Calibrated by Gauge Observations
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Period** & **Precipitation Input** & **NSCE** & **BIAS (\%)** & **CC** & **RMSE (m\({}^{3}\)/s)** \\ \hline Calibration & CGDPA & 0.87 & \(-\)2.99 & 0.93 & 305.77 \\ \cline{2-5}  & CGDPA & 0.62 & \(-\)9.76 & 0.81 & 379.28 \\  & 3B42V7 & 0.65 & \(-\)8.46 & 0.83 & 366.67 \\  & 3B42 RT & 0.52 & 12.49 & 0.81 & 427.78 \\  & IMERG-cal & 0.69 & \(-\)5.53 & 0.86 & 340.65 \\  & IMERG-uncal & 0.59 & \(-\)19.45 & 0.81 & 392.91 \\ Validation & ERA5 & 0.52 & \(-\)29.33 & 0.80 & 427.95 \\  & ERA-Interim & 0.09 & \(-\)47.81 & 0.64 & 588.57 \\  & GSMAP & 0.60 & \(-\)30.31 & 0.85 & 393.08 \\  & GSMAP-RNL & 0.38 & \(-\)40.29 & 0.78 & 483.95 \\  & PERSIANN-CCS & \(-\)0.66 & \(-\)82.09 & 0.59 & 793.82 \\  & Average Rain 1 & 0.69 & \(-\)18.46 & 0.86 & 342.38 \\  & Average Rain 2 & 0.68 & \(-\)18.76 & 0.86 & 347.07 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Statistics of daily simulated streamflow during the calibration (1 April 2006–31 December 2010) and validation (1 January 2011–31 December 2018) periods under Scenario I for the Dongjiang River Basin. Figure 10: Q–Q plots for (**a**) modeled streamflow driven by CGDPA-calibrated parameters under Scenario I; (**b–j**) CREST-simulated streamflow with satellite, reanalysis, and two merged precipitation-recalibrated parameters under Scenario II; and (**k,l**) two merged streamflow series under Scenario III from 2006 to 2018 in the Beijing River Basin. Figure 9: Comparison of (**a**) modeled streamflow driven by CGDPA-calibrated parameters under Scenario I; (**b–j**) modeled streamflow with satellite, reanalysis, and two merged precipitation-recalibrated parameters under Scenario II; and (**k,l**) two merged streamflow series under Scenario III from 2006 to 2018 in the Beijing River Basin. Figure 11: Comparison of (**a**) modeled streamflow driven by CGDPA-calibrated parameters under Scenario I; (**b–j**) modeled streamflow with satellite, reanalysis, and two merged precipitation-recalibrated parameters under Scenario II; and (**k,l**) two merged streamflow series under Scenario III from 2006 to 2018 in the Dongjiang River Basin. Figure 12: Q–Q plots for (**a**) modeled streamflow driven by CGDPA-calibrated parameters under Scenario I; (**b–j**) CREST-simulated streamflow with satellite, reanalysis, and two merged precipitation-recalibrated parameters under Scenario II; and (**k,l**) two merged streamflow series under Scenario III from 2006 to 2018 in the Dongjiang River Basin. Streamflow simulations forced by multi-source precipitation  
After that, using the same model parameters calibrated via CGDPA, we applied eleven precipitation datasets to force the CREST model during the validation period from January 2011 to December 2018, respectively. As shown in Table 4, GSMaP performed best for hydrological modeling (i.e., the values of NSCE, BIAS, CC, and RMSE were 0.78, \(-\)13.23%, 0.89, and 724.98 m\({}^{3}\)/s, respectively), followed by Average Rain 1 and IMERG-cal in the Beijing River Basin. In contrast, PERSIANN-CCS showed the worst performance, followed by GSMaP-RNL and ERA-Interim (e.g., NSCE and RMSE values were less than 0.45 and more than 1154.42 m\({}^{3}\)/s, respectively). As shown in Table 5, IMERG-cal performed best in hydrological modeling (i.e., the values of NSCE, BIAS, CC, and RMSE were 0.69, \(-\)5.53%, 0.86, and 340.65 m\({}^{3}\)/s, respectively), followed by Average Rain 1 and Average Rain 2 in the Dongjiang River Basin. PERSIANN-CCS also showed the worst performance, followed by ERA-Interim and GSMaP-RNL (e.g., the values of NSCE, BIAS, and RMSE were less than 0.38, \(-\)40.20%, and more than 483.95 m\({}^{3}\)/s, respectively). Overall, all the corrected precipitation datasets performed much better than their corresponding uncorrected datasets for hydrologic modeling. The reason for this is that the corrected precipitation products have lower uncertainties compared with their uncorrected ones, whose information was incorporated into the hydrological model.