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E. United States

E. United States

Decision Support for Pond Aquaculture: Parameter Estimation Techniques

Work Plan 7, DAST Study 5

John P. Bolte and Shree S. Nath
Department of Bioresource Engineering
Oregon State University
Corvallis, Oregon, USA


Manual parameterization of the fish growth model in the decision support system POND© has proven to be time-consuming and complicated because of interactions among variables considered in the model and the large parameter space to be searched. This has limited the use of the software for examining production potential for different pond culture species. Traditional parameter estimation techniques typically require partial derivative evaluations; however, because this is a difficult task for simulation models that consider several variables, the use of an iterative, non-linear, adaptive search method (genetic algorithm or GA) for automatic parameterization of the fish growth model was explored. As with other parameter estimation techniques, the objective function to be optimized must be specified. The objective function chosen for GA testing is the minimization of the absolute error between observed and predicted fish growth. Adequate convergence to acceptable parameter values was obtained for the three species (channel catfish, tambaqui and pacu) chosen to evaluate GA's as an effective parameter estimation technique. This methodology has been incorporated directly into POND© to enable users to rapidly customize the software for alternate culture species and locations.

Aquaculture Pond Modeling for the Analysis of Integrated Aquaculture/Agriculture Systems

Interim Work Plan, DAST Study 2

Daniel Jamu and Raul H. Piedrahita
Department of Biological and
Agricultural Engineering
University of California
Davis, California, USA


Enhanced nutrient cycling through waste reuse and sustainable production are the major objectives for integrating aquaculture and agriculture. This report describes the initial steps in the development of a simulation model to analyze the effects of integrating aquaculture with agriculture on nutrient cycling, whole system productivity, and of the impacts of various management actions on the potential for enhancing pond sediment quality. The model consists of three modules: fishpond, crop, and terrestrial soil nitrogen. Inputs of nitrogen into the pond include feed/fertilizer and influent water and outputs from the pond include uptake by fish, effluent water, and removal of pond sediments. The three modules are linked through the use of sediment from ponds as crop fertilizer and/or the use of wastes from crops as feed/fertilizer to aquaculture ponds. Preliminary results demonstrate that feed quality and digestibility of feed need to be considered to improve overall estimation of organic matter and nitrogen production in the fish pond, and of fish growth.