## 4 Results
### Assessment of Discharge Simulations Using Multiple SPPs
#### 4.2.3 Effects of Product-Specific Model Recalibration on Flood Simulations  
The basin-averaged model parameter values calibrated using 3B42 RT, 3B42V7, and IMERG-F were compared with the rain-gauge-benchmarked parameter set (Table S1) to evaluate the effects of satellite-product-specific model recalibration on flood simulations. As stated in Section 3.2, the GXAJ model parameter K (coefficient of PE) predominantly controls the simulated total runoff [67]. A large K value inclines to produce high actual ET and hence generates a low total runoff. The 3B42 RT-based simulation run using the gauge-based parameters overestimates the total runoff by 9.1% in the calibration period (Figure 9a) because of the considerable overestimation of basin-averaged precipitation in 3B42 RT (Table 1). The 3B42 RT-based model recalibration increases K from 1.104 to 1.184 (Table S1) and effectively cuts down the systematic error to \(-1.0\%\) in the calibration period (Figure 9d). In contrast to 3B42 RT, 3B42V7 and IMERG-F systematically underestimate basin-averaged precipitation (Table 1). As a result, the GXAJ model that uses the gauge-based parameters considerably or even largely underestimates the total runoff in the studied basin, when forced by 3B42V7 and IMERG-F SPPs (Figure 9a). Model recalibration using 3B42V7 and IMERG-F considerably decreases K from 1.104 to 0.921 and 0.954, respectively (Table S1). Thus, the magnitude of total runoff underestimation is remarkably dampened (Figure 9d).  
The areal mean free water storage capacity (SM) predominately regulates the high flow magnitude [67]. Reducing SM tends to partition a lower proportion of surface runoff from the total runoff and hence produce high flood peaks. Under Scenario I, the GXAJ model driven by 3B42V7 and IMERG-F underestimates most high flows (Figure 8b,c), as a result of the remarkable systematic underestimation of heavy rain events in these SPPs (Figures 5 and 7). The model recalibration alleviates the magnitudes of high-flow underestimation (Figure 8e,f) via decreasing SM from 134.575 mm to 101.161 mm for 3B42V7 and 117.526 mm for IMERG-F, respectively (Table S1). The 3B42 RT-based recalibration increases SM to 142.720 mm (Table S1) because the 3B42 RT-driven simulation presents a slight high-flow overestimation in the calibration period under Scenario I (Figure 8a), and thus moderately decreases flood peaks in the entire simulation period under Scenario II (Figure 8d).  
Moreover, reducing the recession constants of surface, interflow and groundwater runoffs (CS, CI, and CG) may lead to a faster recession rate for each runoff component and consequently augment high flows to a certain extent. Table S1 shows that the IMERG-F-based recalibration optimizes these three runoff recession coefficients to be consistently lower than the rain-gauge-benchmarked parameter values, thereby partially compensating for the high-flow underestimation.  
Table S1 also shows that the optimized parameters using 3B42 RT exhibit less deviation from the gauge-based parameter set than those calibrated using 3B42V7 and IMERG-F. This finding indicates that 3B42 RT has less compensation effect of model recalibration than other SPPs. This result is likely due to the situation where 3B42 RT, in general, has the best quality among all SPPs in the Chindwin River basin (Figure 6). In the Wangchu basin of Bhutan, [PERSON] et al. [19] found that 3B42V7 was generally improved than its predecessor, 3B42V6. As a result, 3B42V7 has less obvious recalibration effect relative to 3B42V6.