Abstract

Water quality and maintenance are perhaps the most crucial features for optimal fish productivity and health in Recirculating Aquaculture Systems (RAS). This study develops an SD model designed to optimize the water quality parameters RAS operates on, including ammonia, nitrites, nitrates, dissolved oxygen, and pH values. The model integrates biological and chemical operational components, featuring feedback loops that represent fish metabolism, dependency on feed, biofilter dynamics, and water exchange. Several operational scenarios were tested, varying stocking density, feed intensity, and aeration, to assess the system's response. Results from predictions were shown to validate the model's capacity to evaluate decision bioreactor control changes, thus enabling timely intervention in critical zones where parameter values are destined to change. The SD method notably demonstrates how these interactions can evolve, particularly highlighting the need for strong biological filtration and oxygenation to cleanse the system of toxic substances before they reach dangerous concentrations. Sensitivity analysis yielded that the most stable scenario of significant water quality improvement was achieved through changes to biofilter control and adjustments to feeding rates. The model demonstrates how planning control can be implemented within aquaculture systems, with a focus on enhancing system sustainability, reducing volumetric water resource consumption, and providing optimal conditions for aquaculture growth. This work emphasizes the role of dynamic modeling in developing environmental and economic sustainability for RAS efficiency.