# Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin
## 5 Conclusions  
In this study, we analyzed four GPPs (TRMM 3B42, CMORPH, GSMaP, and CPC) and their hydrological application over the whole MRB for a nine-year period (1998-2006). We applied statistical indicators to evaluate the consistency between GPPs and the precipitation observations, and applied the SWAT model for analysis of the water balance components. The following major findings are concluded:  
1. Considering the statistical indicators and the average precipitation, TRMM 3B42 illustrated the best ability to capture precipitation at the annual, seasonal, and monthly scales. At the daily scale, GSMaP and CPC showed a better performance and should be considered for use, especially for the upstream region of the basin.
2. With each dataset calibrated individually by the SWAT model, satisfactory performances were achieved at the daily scale for all of the GPPs and the gauge-driven models. For the ungauged or sparsely gauged regions, better performance was seen from the GPPs than the gauge-driven models, especially for the CPC product. In the downstream regions, TRMM showed the best performance, except for the gauge-driven models. These results further confirm the appropriateness of the GPPs at the daily time scale, which suggests its promising potential to replace in situ observations in hydrologic applications and its potential in the performance of all water balance components.
3. This study attempted to use different GPPs for each individual sub-region to evaluate the water balance components, suggesting strong capabilities for utilizing the advantages of publicly available GPPs in hydrological applications.
4. The spatial variability of water balance components was analyzed in the sub-regions. The distribution of total runoff depth is consistent with the spatial patterns in rainfall, but the landscape, soil texture, and terrain are also major factors that shape the distribution of streamflow. Forests are the major water yield for vegetation types, contributing to the baseflow, while agriculture offers factor-driven high surface runoff.  
Generally, TRMM 3B42 is more robust than the other GPPs and is a reliable data source for hydrological applications in data-sparse area. The spatial variability of the water balance components should be analyzed based on the simulation with distinct suggested GPPs for each of the different sub-regions, which provides better references for the assessment and management of the basin water resources in data-scarce regions. Our findings are useful for selecting which GPP is suitable for advanced hydrological applications for each sub-region. Further studies should examine statistical distribution analysis and include extreme precipitation and the possible prediction of rainfall products over the river basin in order to add more inference and generalization to this study.  
This manuscript is a result of the research of K.D.D. under the supervision of T.N.A. and the advice of D.D.B., N.Y.N. and R.S. This paper was finished under the efforts of all authors. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Ministry of Science and Technology of Vietnam with the project code: NDT.58.RU/19, and Vingroup Innovation Foundation with the project code: VINIF.2019.DA17.  
We are grateful to the providers of operational satellite precipitation products and rain gauge measurements for making data available to us. We would also like to extend our acknowledgements to the editors and anonymous reviewers for their valuable comments and advice.  
The authors declare no conflicts of interest