A mixed integer chance constrained optimization model was developed to determine design and rehabilitation management strategies for storm-water drainage systems conditioned on the likelihood of exceed ing the system's conveyance capacity. The model is multiobjective in nature and capable of considering multiple d~sign or rehabilita~i~n alternatives. Model objectives include the minimization of cost and probability of system flUlure. The probabllity that storm-water flows exceed the conveyance capacity of any network segment within the system is expressed as a chance constraint. The model combines kinematic wave routing methods and second ~o~ent. analysis to formulate the chance constraint. In this manner, only the mean, variance, and form of the dls~butlOn of the storm-water flows are needed to formulate the deterministic equivalent optimization model. To lllustrate the model, an example is presented using an existing storm-water drainage network at Duke Uni versity, Durham, North Carolina. Results of this example specify the most cost-effective storm-water network design at varying system reliabilities. These results define trade-off relationships between total system cost and the probability of system failure.