An accurate description of the blood flow dynamic in local areas of interest is a key tool to explain emergence of certain abnormalities like stenosis. However, extraction of the entire vascular network is in general inaccessible and the truncated part is encoded via Windkessel models. These models rely on many parameters which are estimated by comparing the model with observations. This poster presents a systematic approach for this parameter estimation task using the Ensemble Kalman Method (EnKM) with a surrogate model based on Dynamic Mode Decomposition (DMD).