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The use of water quality models to support watershed management decisions has been under great scrutiny in Total Maximum Daily Load (TMDL) development. Some stakeholders feel that there is not enough information to support the accuracy of model predictions, thereby making the models unsuitable for making policy decisions. Recently, researchers have been making an effort to quantify modeling uncertainties in order to provide greater understanding and awareness of the validity and/or reliability of model outputs. This understanding would then foster greater stakeholder acceptance of policy decisions that are made based on the results of water quality models. This paper is a review of numerous approaches to quantify uncertainty in model predictions that result from residual variability and uncertainty in input parameters. It is hoped that this review will serve as a quick reference report on the present approaches.