## 5 Discussion  
One unanticipated finding was that the gauge-adjusted IMERG_F did not show significant improvement compared to the near real-time products in hydro-meteorological assessment. These results agree with the findings reported in the Beijing River Basin [12] and Malaysia [7]. In the current study, the IMERG_F only shows improvement in term of the bias systematic error for the entire period, while its reliability during the 2014-2015 flood period is similar to those near real-time products. This situation can be explained in part by the usage of the monthly precipitation gauges in the IMERG_F bias correction cannot capture the rapidly-changing daily precipitation. Moreover,  
Figure 8: Box plots of **(a)** CC; **(b)** RMSE; **(c)** RB and **(d)** MAD statistical metrics of the GPM IMERG products against gauge during the 2014–2015 flood period. Figure 9: Daily SWAT streamflow simulations during the 2014–2015 flood by gauge and three GPM IMERG products at the Jambatan Guillermard. only 24-37 precipitation gauges (different every year) distributed over Malaysia were supplied for the GPCC product development [7], and these gauges are insufficient to improve the IMERG_F effectively for a basin-scale application. To increase the reliability of the IMERG_F in hydro-meteorological applications, a comprehensive bias correction scheme with more daily observed precipitation data is needed. As shown in the hydrological assessment section, the IMERG products could be used to study the hydrological cycle in the KRB. The reason for this is the IMERG products show comparable SWAT daily and monthly simulations with the precipitation gauges. However, improvement of the SWAT modelling in tropical regions is needed as it was initially constructed based on the climate and environmental conditions in the United States. For example, in recent years, some studies have been conducted to improve the paddy module within the SWAT model [39; 40]. As oil palm plantation is a major crop in tropical countries including Malaysia, Indonesia, and some African countries, so modification of the oil palm module might be able to increase the reliability of the SWAT model in the tropical regions. Another suggestion for improving the IMERG products hydro-meteorological assessment is the development of a unification GPM hydro-meteorological reliability assessment framework. For instance, through the application of the same hydrological model and statistical metrics in the assessment. To date, numerous hydrological models were applied in the GPM hydrological assessment, including Xiannjiang model [10], Variable Infiltration Capacity (VIC) model [12], Coupled Routing and Excess Storage (CREST) model [13; 14], and SWAT model (this study). Each hydrological model has its own characteristics and computational mechanisms, causing a hydrological model uncertainty. Therefore, it is quite difficult to make a fair comparison among GPM hydro-meteorological assessment studies. A major issue of SPPs assessment studies is the mismatch between the spatial between gauge (point) and the SPPs (pixel) [3]. Also, satellite measures precipitation from the sky, but gauge collects precipitation on the ground. It is interesting to contemplate whether the comparison approach would influence to the results of SPPs assessment. We compared the point-to-pixel and pixel-to-pixel approaches in the IMERG products validation over KRB. The latter approach was conducted by averaging the precipitation data of two or more gauges within a pixel first before the comparison. Figure 10 shows that the selection of comparison approach did not have much influence on the conclusions of the study. Overall, statistical metric values among the three IMERG products as calculated by the point-to-pixel and pixel-to-pixel approaches are quite similar. Such a comparison should be conducted in other regions as well to identify the uncertainty of the point-to-pixel and pixel-to-pixel approaches in the SPPs validation studies.