High-resolution in situ field measurements capturing seasonal 3D mixing dynamics at river confluences are scarce, yet this understanding is essential for effective water-quality management and pollutant-transport prediction in river–lake systems. To address this gap, this study investigates the confluence of the North and South Han Rivers in the Paldang Reservoir. We introduce and apply a novel mixing proximity index (MPI) to quantify the degree of mixing and water-mass origin based on 3D electrical conductivity and temperature data. Seasonal field campaigns, conducted with an acoustic Doppler current profiler and multi-parameter sensors, revealed distinct hydrodynamic behaviors: strong summer stratification suppressed vertical mixing; winter momentum asymmetry induced persistent flow separation despite minimal temperature differences; and spring conditions fostered rapid mixing, barring some residual unmixed deep layers. The MPI effectively delineated shear layers and identified unmixed water zones, providing an enhanced understanding of mixing dynamics beyond the capabilities of traditional tracer- or statistics-based metrics. These findings highlight the combined influence of density differences, tributary momentum, and dam operations on confluence mixing, offering practical insights for water-resource management and improving 3D hydrodynamic model validation.