Development of an integrated model for sustainable aquaculture and optimization of fish production in raceway systems

Sustainable aquaculture needs effective fish farm management to balance high yield production with low farm effluent, as well as consider changes in available water resources. The aim of this research is to develop a model to simulate fish growth, total farm production, and effluent load estimation for single and multiple stocking events. Modeling is in a spreadsheet format for the most common system of cold-water fish farming in Iran, that is, the raceway system. Model equations were based on the literature and currently available aquaculture models. In addition, new equations, based on mass-balance considerations, and modification of temperature for conditions of fish growth in above optimum temperatures conditions are proposed. Five main modules, that is, Environment, Individual Fish Weight, Water Quality Effluent, Farm, and Analysis, were developed to cover the main processes and parameters in a fish farm. Multiple-model inference was adopted for estimating fish growth. Water quality parameters included dissolved oxygen, total ammonia nitrogen and phosphorous. Effluent load was estimated based on dissolved oxygen depletion, feed requirement, phosphate and total ammonia nitrogen. Single and multi-stocking events as well as use of multiple species is possible in the model. The model was validated to primary and secondary data. Primary data of water temperature and fish weight was used to validate the fish growth in the Individual Fish Weight module. Secondary data from published data sets and results from other current aquaculture models were used to compare with the simulation results of the model developed. The data were for trout, salmon and Seabream fish. The results for fish growth showed very good correlation (R2>0.98) with the measured data of a fish farm at Haraz River, Iran, with mean absolute percentage error (MAPE) of less than 10 percent. Comparison of the model simulation results with other existing models, such as AquaOptima and AquaFarm, also showed very good correlations (R2>0.98) except for estimation of feed requirements with the AquaFarm model results (R2=0.87 and MAPE=24%). In conclusion, the model developed produced several important results which contribute to improved knowledge for aquaculture modeling. These are the ability to use of a simple tool for complex situations, improved fish growth modeling, proposal for a parameterization of fish growth in temperature conditions which are beyond optimum growth temperature, the possibility to simulate for variable temperature patterns, together with the possibility for fish farm effluent estimation, under single and multiple stocking conditions. The model can be used for planning aquaculture development due to the capability for simulation of multiple scenarios in single integrated aquaculture model. In this way the model will be useful for a wide range of stakeholders as a tool for sustainable management of an aquaculture farm.

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