High dimensional models typically require a large computational overhead for multiphysics applications, which hamper their use for broad-sweeping domain interrogation. Herein, we develop a modeling framework to capture the through-plane fluid dynamic response of electrodes and flow fields in a redox flow cell, generating a computationally inexpensive two-dimensional (2D) model. We leverage a depth averaging approach that also accounts for variations in out-of-plane fluid motion and departures from Darcy’s law that arise from averaging across three-dimensions (3D). Our Resulting depth-averaged 2D model successfully predict the fluid dynamic response of arbitrary in-plane flow field geometries, with discrepancies of < 5% for both maximum velocity and pressure drop. This corresponds to reduced computational expense, as compared to 3D representations (< 1% of duration and 10% of RAM usage), providing a platform to screen and optimize a diverse set of cell geometries.