Modeling reservoir outflow and storage is challenging due to limited publicly available data and human decision-making. For 100 reservoirs in the US, we examined how calibrating reservoir algorithms against outflow and storage-related variables affects performance. We found that calibration notably improves storage simulations, while outflow simulations are more influenced by the quality of inflow data. We recommend using remotely sensed storage anomalies to calibrate reservoir algorithms.