Public hatchery facilities increasingly respond to recreational fishing demands for larger catchable salmonids and to production programs that require a variety of species. The result of this tendency is to require more complexity in hatchery design and operations involving the simultaneous rearing of several species that results in overlapping production schedules for crops of fish that carryover from 1 year to the next. This paper presents a highly accessible spreadsheet based computer simulation model for use by culturists, designers, and program planners in designing hatchery facilities with these expanded program demands. It addresses trade offs between budget constraints, stocking objectives, available water resources, and production technologies. The model is structured so that all the assumptions for any facility program simulation can be entered on a single spreadsheet. The essential fish growth, density, flow, and feeding relationships used within the model are those based on widely used paradigms developed by Piper et al. (1982) and others. The program information assumptions include all of the essential information to simulate production runs for each group of fish within the facility, each with specific characteristics such as growth rate, feed conversion, calendar day stocking and harvest dates, and duration of the crop. Those program assumptions are linked to a series of other spreadsheets within the spreadsheet workbook that calculate weekly model simulation results for rearing space, first-pass and rearing flows, feed consumption, and phosphorus discharge for each group of fish and then for the combined results of the entire facility. The facility simulation results are automatically plotted in a graphic format for comparative evaluation of any series of production program assumptions that the operators consider in the design process. The graphic results for simulated rearing space, flow, and feeding are presented in an annual format in weekly increments. The graphic results readily present the utilization of facility space and water resources and clearly indicate opportunities to improve facility efficiency in a new simulation providing a rapid means of iterating design changes until the exercise generates the most favorable facility. Several case studies provide examples of this process for the user. Published by Elsevier B.V.
