Gridded precipitation products are becoming good alternative data sources for regions with limited weather gauging stations. In this study, four climate gridded precipitation products were utilized, namely Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim/land, the Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), and Multi-Source Weighted-Ensemble Precipitation (MSWEP). The key novelty of this study is to fill the gap in one of important areas of the transcontinental region of Eurasia, namely Rize province in the Black Sea region being selected as a study area since it has complex topography and climatology in addition to a limited number of gauging stations. A set of precipitation products were assessed for performance with the observed precipitation data before using a hydrological model (SWAT) to evaluate the basin response for the climate products. Three methods were considered in this study: (i) spatial comparison and (ii) hydrological and (iii) statistical evaluations. Along with precipitation forcing, the SWAT model simulations were analyzed in conjunction with streamflow observations. In an overall evaluation, the percentage bias of ERA-Interim/land, CFSR, APHRODITE, and MSWEP mean monthly precipitation is 19.9%, 33.4%, 41.4%, and 85.0% respectively. For the flow simulations, the CFSR and MSWEP have resulted in exaggerated peak flows in the high flow season due to overestimated precipitation forcing (Nash Sutcliffe efficiency [NS] equal to 0.22 and -0.73, respectively). On the contrary, the APHRODITE underestimated the peak flows due to lower precipitation estimates (NS = 0.38). The ERA-Interim land showed good agreement with the observed flows (NS = 0.53). From these readings, we stated that the ERA-Interim land exhibited improved performance with the observed precipitation whereas the CFSR showed the worst performance. The study suggests that gridded precipitation products could supplement observed precipitation data for observational data scarcity in mountainous regions.