## 3 Results and Discussion
### Evaluation of Streamflow Simulation Capacity of Different Precipitation Products  
Figure 5 presents the simulated hydrographs for different precipitation scenarios. Figure 5 illustrates the hydrograph obtained from the hydrologic model simulated under the observed rainfall. However, there are some mismatches between observed and simulated streamflow with mixed results (over-estimations and under-estimations). These differences can clearly be seen for flood peaks during the rainy seasons. However, it is noteworthy, the flood peak in 2010 simulated by the SWAT model from RGs was comparable with observed discharge. Through eyeball analysis, it is evident that baseflow during the dry seasons in most of the years was simulated fairly well through the SWAT model. Figure 5b-d present the hydrographs obtained under the SbPPs. Fairly acceptable matches in discharges are found in Figure 5b for 3B42 precipitation product; however, underestimations in simulated discharges can be clearly seen in Figure 5c,d for 3B42-RT and CMORPH precipitation products. These two SbPPs have underestimated the precipitation too (refer to Figure 4). Figure 5e,f present the simulated hydrographs under the GbGPPs (APHRODITE_V1901 and GPCC, respectively). Over-estimations can be clearly seen in APHRODITE_V1901 and GPCC precipitation products. All other simulated hydrographs are presented in Figure 1a-g in the Appendix A of this paper. However, among all precipitation products, the RG simulated SWAT model outperformed all other precipitation products. This observation can be seen from by [PERSON] et al. [36] for the Chi River Basin in the north-eastern part of Thailand. Conclusions drafted from Figure 5 are based on the visual observations. Therefore, the hydrologic performance of different precipitation products was examined by statistical indices, including the NSE and the R\({}^{2}\), which were recommended by [PERSON] et al. [59]. Table 3 provides the NSE and R\({}^{2}\) obtained for hydrologic simulations under different precipitation products. Figure 5: _Cont_. Figure 5: Simulated hydrographs under SbPPS and GbGPPs. **(a)** For observed rainfall; **(b)** For 3B42; **(c)** For 3B42-RT; **(d)** For CMORPH; **(e)** For APHRODITE V1901; **(f)** For GPCC. Among the tested precipitation products, only observed rainfall, 3B42, and APHRODITE_V1901 show NSE and R2 values higher than 0.50 in both calibration and validation processes. Therefore, it can be argued that only these precipitation products are acceptable for hydrologic modeling of the HBS. Thus, it can be stated that 3B42 precipitation product outperformed the other SbPPs in terms of the SWAT model performance for simulating streamflow. This was observed in the obtained hydrographs (refer to Figure 4b). Similarly, APHRODITE_V1901 outperformed other GbGPPs with NSE greater than 0.50 for both calibration and validation time periods in terms of the tested GbGPPs. Although CHIRPS and MSWEP have performed fairly well during the calibration time periods (provided with NSE values greater than 0.50), the performance of hydrologic modeling significantly decreased during the validation time period. The over-estimations compared to RGs produced from SbPPs can be the reasons for this observation. However, in contrast, PERSIANN showcased a better performance during the validation period. In addition, the CMORPH products showed the worst performance (NSE \(<\) 0) during both calibration and validation time periods. This can be directly attributed to the lower detection accuracy of rainfall events observed, which was also observed by [PERSON] et al. [63]. Furthermore, CCS significantly under-estimates the streamflow from the SWAT model developed for the HBS. Similar results were demonstrated by [PERSON] et al. [2] for the Upper Nan River Basin in Northern Thailand using the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) hydrologic model. The significant underestimations of streamflow simulated by 3B42-RT, PERSIANN, and CCS were also previously demonstrated by [PERSON] et al. [2].