An approach to developing and using Bayesian networks to model watershed management decisions is presented with a case study application to phosphorus management in the East Canyon watershed in Northern Utah, USA. The Bayesian network analysis includes a graphical model of the key variables in the system and conditional and marginal probability distributions derived from a variety of data and information sources. The resulting model is used to 1) estimate the probability of meeting legal water quality requirements for phosphorus in East Canyon Creek under several management scenarios and 2) estimate the probability of increased recreational use of East Canyon Reservoir and subsequent revenue under these scenarios.