**5. Conclusions**

SPPs have increasingly become an important data source for precipitation inputs in hydrological modeling and other related studies worldwide. For local regions with scarce precipitation observations or limited access to precipitation data, the latest GPM and TRMM products provide a valuable alternative for obtaining the much-needed rainfall inputs for various regional hydrological applications. However, the accuracy of their rainfall estimates should be systematically assessed before being utilized in real world applications. In this study, we have assessed and compared the accuracy of the latest five GPM IMERG V6 and TRMM 3B42 V7 precipitation products across the monthly, daily, and hourly scales in a middle-sized hilly river basin in eastern central China. For evaluation, a total of four continuous and three categorical metrics have been calculated based on SPP estimates and historical rainfall records at 13 stations over a period of 9 years from 2009 to 2017. The evaluation results have led to the following main conclusions:


In general, our nine-year systematic evaluation of the latest GPM IMERG V6 and TRMM 3B42 V7 precipitation products have shown that the SPPs, especially the post-time IMERG\_F product, could be considered as a reliable data source for providing monthly or daily rainfall data for regional hydrological applications. However, great caution needs to be exerted to utilize the hourly rainfall SPPs considering their overall weak correlations with ground rainfall observations, as well as the consistent tendency of underestimation by the IMERG products.

Hourly rainfall datasets have been increasingly found to be valuable inputs to a variety of hydrological applications. However, limited access to hourly rainfall datasets have restrained such applications in many regions. Owing to their wide spatial coverage and open access, SPPs have great potential to act as a useful alternative source for providing hourly rainfall data. Therefore, effective bias-correction algorithms incorporating ground rainfall observations are needed to improve the quality of hourly rainfall SPPs to safeguard the validity of their usage as ground measurement surrogates.

**Author Contributions:** Conceptualization, X.Y. and M.L.T.; Methodology, X.Y. and R.H.; Software, Y.L. and X.L.; Validation, X.Y. and G.W.; Formal analysis, X.Y. and Y.L.; Investigation, X.Y. and Y.L.; Resources, G.W. and R.H.; Data curation, Y.L. and X.L.; Writing—original draft preparation, X.Y. and Y.L.; Writing—review and editing, M.L.T., G.W., and R.H.; Visualization, Y.L. and X.L.; Supervision, X.Y. and R.H.; Project administration, X.Y. and R.H.; Funding acquisition, R.H. and X.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Belt and Road Special Foundation of the State Key Laboratory of Hydrology—Water Resources and Hydraulic Engineering at Nanjing Hydraulic Research Institute, China, grant number 2018nkzd01; National Natural Science Foundation of China, grant number 41830863 and 51679144; National Key Research and Development Program of China, grant number 2016YFA0601501; the Ministry of Education, Malaysia under the NEWTON-NERC grant (IMpacts of PRecipitation from Extreme StormS—Malaysia (IMPRESS-MALAYSIA), grant number 203.PHUMANITI.6780001; and Fundamental Research Grant Scheme, grant number 203.PHUMANITI.6711695. The APC was funded by the Belt and Road Special Foundation of the State Key Laboratory of Hydrology—Water Resources and Hydraulic Engineering at Nanjing Hydraulic Research Institute, China, grant number 2018nkzd01.

**Conflicts of Interest:** The authors declare no conflict of interest.
