Chapter 11 Aquaponics Systems Modelling
11.8 Discussion and Conclusions
Aquaponics are complex technical and biological systems. For example, possible explanations for fish not growing properly can be small food rations, adverse water quality, technical problems causing stress, etc. Due to the inherently slow biology, scientific investigations of the validity of these explanations would be tedious and require several experimental trials to get all important factors and their interactions, demanding a lot of facilities, expertise, research time and financial assets. Therefore, the issue of modelling aquaponic systems was addressed in this chapter.
· Aquaponics Food Production Systems11.7 Modelling Tools
In aquaponics, flow charts or stock and flow diagrams (SFD) and causal loop diagrams (CLDs) are commonly used to illustrate the functionality of the aquaponic system. In the following, flow chart and CLDs will be described. 11.7.1 Flow Charts To get a systemic understanding of the aquaponics, flow charts with the most important components of the aquaponics are a good tool to show how material flows in the system. This can help, for example, in finding missing components and unbalanced flows and mainly influencing determinants of the subprocesses.
· Aquaponics Food Production Systems11.6 Multi-loop Aquaponic Modelling
Traditional aquaponic designs comprise of aquaculture and hydroponic units involving recirculating water between both subsystems (Körner et al. 2017; Graber and Junge 2009). In such one-loop aquaponic systems, it is necessary to make trade-offs between the conditions of both subsystems in terms of pH, temperature and nutrient concentrations, as fish and plants share one ecosystem (Goddek et al. 2015). By contrast, decoupled double-loop aquaponic systems separate the RAS and hydroponic units from one another, creating detached ecosystems with inherent advantages for both plants and fish.
· Aquaponics Food Production Systems11.5 HP Greenhouse Modelling
The crop water use and nutrient uptake is a central subsystem of aquaponics. The HP part is complex, as pure uptake of water and dissolved nutrients do not simply follow a rather simple linear relationship as, e.g. fish growth. To create a full-functional model, a complete greenhouse simulator is needed. This involves sub-model systems of greenhouse physics including climate controllers and crop biology covering interactive processes with biological and physical stressors.
· Aquaponics Food Production Systems11.4 Modelling Anaerobic Digestion
Fig. 11.10 Simulation of TAN (XsubNHx-N,1/sub) in [mg/l] over 2 days = 2880 min with Q = 300 l/min (blue) and Q = 200 l/min (orange) Fig. 11.11 Simulation of nitrate-N (XsubNO3-N,1/sub) in [mg/l] over 50 days = 72,000 min with QsubExc/sub = 300 l/day (yellow), QsubExc/sub = 480 l/day (orange) and QsubExc/sub = 600 l/day (blue) Anaerobic digestion (AD) of organic material is a process that involves the sequential steps of hydrolysis, acidogenesis, acetogenesis and methanogenesis (Batstone et al.
· Aquaponics Food Production Systems11.3 RAS Modelling
Global fish aquaculture reached 50 million tons in 2014 (FAO 2016). Given the growing human population, there is a growing demand for fish proteins. Sustainable growth of aquaculture requires novel (bio)technologies such as recirculating aquaculture systems (RAS). RAS have a low water consumption (Orellana 2014) and allow for a recycling of excretory products (Waller et al. 2015). RAS provide suitable living conditions for fish, as a result of a multistep water treatment, such as particle separation, nitrification (biofiltration), gas exchange and temperature control.
· Aquaponics Food Production Systems11.2 Background
Many definitions of a system are available, ranging from loose descriptions to strict mathematical formulations. In what follows, a system is considered to be an object in which different variables interact at all kinds of time and space scales and that produces observable signals. These types of systems are also called open systems. A graphical representation of a general open system (S) with vector-valued input and output signals is represented in Fig.
· Aquaponics Food Production Systems11.1 Introduction
In general, mathematical models can take very different forms depending on the system under study, which may range from social, economic and environmental to mechanical and electrical systems. Typically, the internal mechanisms of social, economic or environmental systems are not very well known or understood and often only small data sets are available, while the prior knowledge of mechanical and electrical systems is at a high level, and experiments can easily be done.
· Aquaponics Food Production Systems