Many reservoirs around the world are being operated based on rule curves developed without considering the evacuation of deposited sediment. Current reservoir simulation and optimization models fall short of incorporating the concept of sustainability because the reservoir storage losses due to sedimentation are not considered. This study develops a new model called Reservoir Optimization-Simulation with Sediment Evacuation (ROSSE) model. The model utilizes genetic algorithm based optimization capabilities and embeds the sediment evacuation module into the simulation module. The sediment evacuation module is implemented using the Tsinghua university flushing equation. The ROSSE model is applied to optimize the rule curves of Tarbela Reservoir, the largest reservoir in Pakistan with chronic sedimentation problems. In the present study, rule curves are optimized for maximization of net economic benefits from water released. The water released can be used for irrigation, power production, sediment evacuation, and for flood control purposes. Relative weights are used to combine the benefits from these conflicting water uses. Nine sets of rule curves are compared, namely existing rule curves and proposed rule curves for eight scenarios developed for various policy options. These optimized rule curves show an increase of net individual economic benefits ranging from 9 to 248% over the existing rule curves. The shortage of irrigation supply during the simulation period is reduced by 38% and reservoir sustainability is enhanced by 28% through increased sediment evacuation. The study concludes that by modifying the operating policy and rule curves, it is possible to enhance the reservoir's sustainability and maximize the net economic benefits. The developed methodology and the model can be used for optimization of rule curves of other reservoirs with sedimentation problems. Copyright © 2008 John Wiley & Sons, Ltd.