Quantitative Precipitation Estimation (QPE) is extremely challenging in regions of complex terrain due to a combination of issues related to sampling. In particular, radar beams are often blocked or scan above the liquid precipitation zone while rain gauge density is often too low to properly characterize the spatial distribution of precipitation. Due to poor radar coverage, rain gauge networks are used by the National Weather Service (NWS) River Forecast Centers as the principal source for QPE across the western U.S. However, there has been little evaluation to determine the relative performance of gauge-only, radar, and blended radar-gauge QPE products in the western U.S. The National Water Center (NWC) is intended to develop and provide new-generation and interoperable water information and services in support of the NWS, and other NOAA and federal agencies. To support the NWC mission, the best possible QPE is needed to serve as input forcing for hydrologic models to produce accurate and timely stream flow forecasts. Therefore, QPE evaluations are needed to determine the relative merits of different algorithms and sensors as well as to develop uncertainty estimates for QPE products. In this study, an evaluation of radar-only, merged radar-gauge, and gauge-only QPE products is performed on precipitation events occurring in a portion of northern California (including the Russian and American River basins) using an independent set of rain gauge data from the Hydrometeorology Testbed (HMT). The evaluation is performed with the Multisensor Precipitation Estimator (MPE) and National Mosaic and Multi-sensor QPE (NMQ) Q2 algorithms, using retrospective versions of the NMQ Q2 and MPE algorithms installed at the NOAA Earth System Research Laboratory. The retrospective versions of these algorithms allow for sensitivity tests using different gauge and radar data input.