In this study, water depth measurements were collected in storm water infrastructure during rain events using a pressure based water level sensor. Irregularities within the measured water level datasets required data smoothing to prepare the observed data for calibration. A rainfall-runoff model was created using a proprietary version of the U.S. Environmental Protection Agency's Storm Water Management Model, PCSWMM, to predict the performance of recently implemented green stormwater infrastructure with respect to runoff at the site. The PCSWMM model calibration was accomplished by comparing water level data collected on site to the PCSWMM output data produced by the uncalibrated model. Nash-Sutcliffe efficiency was used to assess the performance of the calibration procedure. Sensitivity analyses of the estimated parameters were performed to assess the impacts of the model parameters on overall model output. The overarching objective of the study was to demonstrate the value of inexpensive and readily available real-time pressure based water level sensor data to calibrate a PCSWMM model.