## 6 Conclusions  
Few previous studies have focused on the statistical and hydrological evaluations of the latest GPM-era IMERG and GSMaP SPPs in both near- and post-real-time versions at sub-daily time scales. Therefore, this study proposed an assessment framework addressing this issue. With the aid of this framework, the 3-hourly daytime precipitation retrievals and 12-hourly nighttime retrievals from six GPM-era SPPs (IMERG-E, IMERG-L, IMERG-F, GSMaP-NVK, and GSMaP-GAUGE) and two TRMM-era SPPs (3B42 RT and 3B42V7) were statistically evaluated and compared in the sparsely gauged Chindwin River basin of Myanmar. Subsequently, the comparatively better near- and post-real-time SPPs were selected to drive the GXAJ hydrological model to investigate their hydrological utility in 3-hourly discharge simulations. The main findings of this study are summarized as follows:  
1. Statistical assessment at grid and basin scales demonstrates that 3B42 RT generally presents a higher quality, followed by IMERG-F and 3B42V7. IMERG-E, IMERG-L, GSMaP-NRT, GSMaP-MVK, and GSMaP-GAUGE obviously underestimate total precipitation, and the three GSMaP SPPs have the lowest accuracy. 2. Given that 3B42 RT demonstrates the best quality among the four near-real-time SPPs, 3B42 RT obtains satisfactory hydrological ability (NSE = 0.871) in 3-hourly streamflow simulations using the rain-gauge-benchmarked parameters, which is comparable with the rain-gauge-based precipitation data (NSE = 0.895). Although 3B42V7 and IMERG-F have comparatively better quality than the other two post-real-time SPPs, these two SPPs have mildly poorer hydrological performance (NSE = 0.690 and 0.664 for 3B42V7 and IMERG-F, respectively). 3. The input-specific model recalibration greatly improves the SPP-based streamflow simulations. 3B42 RT obtains good hydrological performance (NSE = 0.868). Following 3B42 RT, IMERG-F (NSE = 0.840) slightly outperforms 3B42V7 (NSE = 0.828). These aforementioned findings have implications for SPP development and can provide the local community with guidance to alternative choice of SPPs for hydrological applications. This study found that the post-real-time SPP, IMERG-F V05B, demonstrates comparable or even slightly better accuracy in statistical and hydrological evaluations in comparison with its predecessor, 3B42V7, indicating that the latest release of IMERG-F can be considered a suitable substitute for 3B42V7 in the Chindwin River basin in the evaluation period. However, in the case of near-real-time SPPs, the overall performance of IMERG-E and IMERG-L is still behind that of 3B42 RT, which even outperforms the post-real-time 3B42V7 and IMERG-F SPPs. The near-real-time IMERG products have fine spatiotemporal resolutions and short latencies, which add to their great potential for applications in real-time hydrological forecasting and flood monitoring. Therefore, the GPM scientific team should further refine the retrieving algorithms and improve the accuracy of IMERG-E and IMERG-L SPPs in the Chindwin River basin, where local precipitation is sparsely gauged and accurate and timely precipitation data are urgently needed for flood control and disaster mitigation. Several previous studies have likewise reported that the quality of GSMaP SPPs in China [72; 78; 79; 80], Brazil [29], and Bangladesh [74] is comparable with that of IMERG, or that GSMaP is slightly superior to IMERG. Nevertheless, this study shows that GSMaP SPPs in near- and post-real-time versions have relatively poorer performance in the study area, in comparison with TMPA and IMERG SPPs. Thus, there is a need for the GSMaP technical community to improve the quality of GSMaP SPPs in the Chindwin River basin. Furthermore, this work strengthens the necessity for the local authority to establish a denser rainfall-monitoring network. It not only helps avoid direct comparison of SPPs with a sparse gauge network and the subsequent gauge spatial representativeness problem, but also facilitates effective flood forecasting and prompt disaster mitigation.