## 6 Conclusions  
The purpose of the current study was to assess the reliability of the IMERG products (IMERG_E, IMERG_L and IMERG_F) in hydro-meteorological applications in the KRB, Malaysia. First, a meteorological assessment was conducted using the continuous (CC, RMSE, RB, and MAD) and categorical (POD, FAR, CSI, ETS, and ACC) statistical metrics from 12 March 2014 to 31 December 2016. Second, SWAT model development, a parameters sensitivity analysis, calibration, and validation were conducted. Three statistical metrics (NSE, R\({}^{2}\) and RB) were used to validate the SWAT-simulated streamflow. Third, the IMERG products were incorporated into the calibrated SWAT to evaluate their capability in daily, monthly, and cumulative streamflow simulations. The final part involved the hydro-meteorological assessment of the IMERG products in the 2014-2015 flood period from 14 December 2014 to 3 January 2015. The main conclusions are summarized as follows:  
* The temporal variability of monthly precipitation was well captured by the IMERG products, with low precipitation amounts in February 2015 and March 2016, and high precipitation amounts in December 2014. The IMERG_F slightly outperformed the IMERG_E and IMERG_L in terms of systematic bias, with a RB value of 7.14%. * The SWAT model performed \"good\" in daily streamflow simulations, with NSE and R\({}^{2}\) values of 0.74 and 0.79, respectively. However, the model underestimated the daily streamflow by 16.4%, particularly during the peak flows. Because SWAT daily streamflow validation is relatively low in Malaysia, this study could act as a reference to those would like to study the daily scale of the Malaysian hydrological cycle. A modification of the oil palm module within the SWAT module is essential to improve the model's capability in tropical regions. * The IMERG products performed comparable with precipitation gauges in streamflow simulations, indicating a great potential in tropical hydrology applications. Overall, the IMERG_F (NSE = 0.71\(\sim\)0.86, R\({}^{2}\) = 0.73\(\sim\)0.9 and RB = \(-\)5.3%\(\sim\)\(-\)7.1%) performed the best in both daily and monthly streamflow simulations, followed by the IMERG_E (NSE = 0.7\(\sim\)0.81, R\({}^{2}\) = 0.75\(\sim\)0.91 and RB = \(-\)27.6%\(\sim\)\(-\)28.3%), and IMERG_L (NSE = 0.66\(\sim\)0.73 and R\({}^{2}\) = 0.75\(\sim\)0.91 and RB = \(-\)36.3%\(\sim\)\(-\)36.6%). The near real-time products underestimated the daily and monthly streamflow significantly, so a systematic bias correction is essential prior to applying them in any operational applications. * Similar to the findings reported by [PERSON] and [PERSON] (2014), the IMERG products have better meteorological performance in the 2014-2015 flood period than the entire period. In contrast to the meteorological assessment, all three products have a poorer hydrological performance in the 2014-2015 flood period compared to the entire period. Nevertheless, the performance of the IMERG_E and IMERG_F was still regarded as \"satisfactory\" in the flood streamflow simulations based on the NSE and R\({}^{2}\) values of 0.5\(\sim\)0.51 and 0.62\(\sim\)0.65, respectively. One thing to be considered is that the IMERG products underestimated the peak flow rate from 23 to 28 December 2014. Overall, the GPM IMERG products show a great potential for hydro-meteorological applications in the KRB. A further study on the development of a standardized GPM hydro-meteorological assessment framework (i.e., same hydrological model, statistical metrics, and same GPM IMERG products) is essential to make a fair comparison among studies from different climate and geographical conditions. Finally, the assessment of the IMERG products in other applications such as agricultural, ecological, and fish habitat monitoring is also required in the future. [PERSON] collected, processed, and analyzed the data, and drafted the manuscript. [PERSON], [PERSON] and R.R. reviewed and edited the manuscript. This research was funded by the Ministry of Higher Education Malaysia grant number [FRGS Grant No.