Generalized Model for Predicting Spawning Success of Fish in Reservoirs with Fluctuating Water Levels

A computer model (SUCCESS) was developed to predict spawning success of centrarchid fishes in a pumped storage reservoir. The model was quantified by conducting field and laboratory studies with bluegills (Lepomis macrochirus) from Leesville Lake, the lower impoundment of the Smith Mountain Pumped Storage Project near Roanoke, Virginia. Eight modifiable subprograms were used to increase the generality and utility of the model. Data necessary for use in the model are hourly water levels, water temperature regimens, and a distribution describing the depth of spawning activity in the reservoir. A sensitivity analysis of the model suggested that data on hatchability and rates of hatching and development from the fry to free-swimming stage had the greatest effect on the estimates of spawning success. SUCCESS should allow a reservoir fishery manager to predict the impact of water level fluctuations on spawning success of sport fishes or predict spawning success of undesirable species under various water level fluctuation regimens.