## 4 Results and Discussion  
### Evaluation of SPPs  
#### 4.1.1 General Evaluation  
GSMaP-NRT and IMERG-Early (hereafter referred to GSMaP and IMERG, respectively) data and the rain gauge data were compared at the watershed scale at hourly, daily, 10-daily, and monthly temporal scales. To be consistent with the period of the flood simulation, the hourly data were calculated within the case period. In contrast, others employed the data from 2002 to 2011 for a comprehensive evaluation with enough samples. Figure 3 shows the scatterplots and regression curve of NRT SPPs and gauge rainfall. Based on the regression curve, SPPs underestimated the rainfall at all temporal scales except monthly GSMaP, which performed best with a CC of 0.84 among all temporal scales. Generally, the correlation improved as the temporal scale increased [22]. Moreover, it is evident that there are more dots on the upper left side than the lower right side when hourly rainfall > 5 mm, daily rainfall > 25 mm, 10-day rainfall > 50 mm, and monthly rainfall > 100 mm. It can be concluded that GSMaP and IMERG generally underestimate the extreme precipitation. Table 1 shows the evaluation results for both original and bias-corrected SPPs more comprehensively. All evaluation metrics were calculated for two bias correction techniques (SMC, RBC) with two bias factors (monthly and 10-day) at all temporal scales. Overall, the SPPs corrected by the 10-day bias factor improved significantly. RBC with a 10-day bias factor was the best correction method among others as all metrics had been significantly improved. In particular, _BIAS_ and _CC_ almost reached the optimal value 0 and 1 after correction. From the aspect of _MAE_ and _RMSE_, there is little difference on the time scale of hourly and daily no matter which correction method and factor we chose. In addition, on the temporal scale of 10-day and month, both SMBC and RBC performed well only with the corresponding bias factor. Figure 3: Scatterplots and regression lines from the original Satellite Precipitation Products (SPPs) and gauges with different temporal scales. (**a**) hourly, (**b**) daily, (**c**) 10-day, (**d**) monthly. Blue lines and dots denote Integrated Multi-satellite Retrievals (IMERG) Early data, while red lines and dots represent Global Satellite Mapping of Precipitation-Near Real Time (GSMaP-NRT) data, and the black line is the equal line. In summary, we selected precipitation data, which were corrected by RBC \(-\)10 day as the input data of the BTOP model, refer to them as GSMaP-RBC and IMERG-RBC, respectively. Furthermore, Figure 4 shows the cumulative rainfall for each data source in selected cases. The monthly precipitation of GSMaP-RBC and IMERG-RBC is consistent with the measured precipitation. Furthermore, precipitation is heterogeneous in temporal and spatial scales. The specific effect of the statistical correction method cannot be identified. Moreover, a significant discrepancy still exists from the aspect of a single rainfall event. However, we obtained satisfactory correction results with statistic bias correction methods based on the watershed scale. This shows that from an average point of view, the statistical correction method has considerable effectiveness.