Eutrophication creates abundant growth in aquatic plants and algae blooms which lead to the depletion of oxygen in water ( Behbahani et al. Mitigating stormwater contamination that contributes to eutrophication in natural waters is critical ( Ding et al. Pollutants found in runoff, such as nutrients from fertilizers, can cause a harmful chain reaction in the aquatic ecosystem leading to contaminated source water and ecosystem damage, as observed in the western portion of Lake Erie in recent years ( Urry et al. Non-point source pollution, such as stormwater runoff resulting from local and global increases in impervious surfaces, threatens to erase much of the progress achieved by the Clean Water Act ( Dietz and Clausen 2007). 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. Sensitivity analyses of the estimated parameters were performed to assess the impacts of the model parameters on overall model output. Nash–Sutcliffe efficiency was used to assess the performance of the calibration procedure. The PCSWMM model calibration was accomplished by comparing water level data collected on site to the PCSWMM output data produced by the uncalibrated model. 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. A rainfall–runoff model was created using a proprietary version of the U.S. Irregularities within the measured water level datasets required data smoothing to prepare the observed data for calibration. In this study, water depth measurements were collected in storm water infrastructure during rain events using a pressure based water level sensor.