AED2

General Information
Acronym of the model	AED
Full name of the model	Aquatic Ecodynamics Modelling Library
Model components	Chemistry and Biology
Supported platforms	Windows, Mac, Linux
Programming Language	Fortran 90
Still maintained	Yes, by: AED Research Group, University of Western Australia
Most recent version	2.4.0rc5
Model structure
Executables are available
0D
Model description
Model objective	Simulation of aquatic ecosystem dynamics. Provision of a flexible model structure
Specific application	- Analysis of oxygen depletion in an estuary (Bruce et al. 2014) - Selective withdrawal to manage oxygen concentration in a reservoir (Weber et al. 2017) - Analysis of hypolimnetic anoxia (Snortheim et al. 2017)
Background knowledge needed to run model	- Understanding of biological and chemical processes in the water body - some programing language to handle input/output files, e.g., R, Python or Matlab
Basic procedures	Note: the developer’s website provides extensive information on the model setup. The general procedure is: 1. Optional: Run one of the example simulations 2. Decide on a hydrodynamic model (e.g., GLM, Tuflow) and set-up that model 3. Prepare the input files for the model (e.g., inflow concentration of oxygen and nutrients; .csv file with inflow data) 4. Set the simulation settings (configuration which modules to include, set initial conditions, set module parameters specific to the study site); which files to include depends on the hydrodynamic driver and on the chosen modules (e.g. “aed_phyto_pars.nml” for the phytoplankton-specific parameters), you will always need to configure the “aed2.nml” text file 5. Prepare the validation data (e.g., measurements of oxygen, nutrient and chlorophyll concentrations in the water body) 6. Split input and monitoring data into two periods in time 7. Run the model (e.g., “glm.exe”) for the first period. 8. Compare model results and observations (start with oxygen, then the nutrients and then the biological variables) and calibrate model parameters (e.g., nutrient release from the sediment, mineralisation rates, oxygen demand, growth parameters, etc.). 9. Use the second period to validate the model, i.e. compare observations and model results without further calibrating the model and calculate the model fit. 10. Optional: Use your model set-up to run scenarios.
AED is an open source library of ecodynamics modules. This setup makes the model structure very flexible and allows for testing of different model formulations and algorithms. Some of the modules depend on each other and have to be run together. AED can be coupled to different hydrodynamic drivers. It has been coupled to GLM (1D), TUFLOW-FV (2D/3D finite volume) and Telemac (1/2/3D flexible mesh).
Link to website/manual	http://aed.see.uwa.edu.au/research/models/AED/overview.html http://aed.see.uwa.edu.au/research/models/AED/setup.html
Model characteristics
Input variables	Obligatory: External load and inflow: • DO (or assume saturation) • TP, knowledge of how to fractionate that, DOP • TN, full fractionation • Si • POC, DOC • If available and relevant: carbon of different phytoplankton groups In Lake/water body: • chlorophyll (+ if available: phytoplankton counts = or an idea of main groups/species and succesion), • phosphorus (TP, PO4, DOP) concentrations • nitrogen (TN, NO3, NH4, DON) concentrations • silicate (Si) concentration (only if limiting) • oxygen concentration Optional:
Input file format	ASCII, .csv
Output variables	dependent on the configuration: tracers, dissolved oxygen, carbon (dissolved inorganic carbon, methane), nitrogen (nitrate, ammonium, nitrous oxide), phosphorus (phosphate), silica, suspended solids, organic matter (dissolved and particulate carbon, nitrogen, phosphorus), phytoplankton, zooplankton
Output file format	.netfcdf, .csv
Biogeochemical model components	carbon (dissolved inorganic carbon, methane), nitrogen (nitrate, ammonium, nitrous oxide), phosphorus (phosphate), silica, suspended solids, organic matter (dissolved and particulate carbon, nitrogen, phosphorus), phytoplankton (up to seven groups), zooplankton (up to three groups)
Model structure/mathematical framework	ODE
Temporal resolution	depends on hydrodynamic driver
Minimal spatial resolution	NA
Variables needing calibration	typical: sediment and water column oxygen demand, nutrient release rates from the sediment, nutrient mineralization rates, growth parameters (maximum rate, nutrient uptake and storage, light-dependency, temperature-dependency)
Has successfully been used in
Climate Change Scenario	Snortheim et al. 2017
Management Support	Weber et al. 2017
Countries in which the model has been applied	Australia, Germany, USA
Which institutes have applied the model	University of Western Australia; Helmholtz Center for Environmental Research; Center for Limnology, University of Wisconsin; Virginia Tech
Has coding for	Sediment dynamics
Accessibility
Open-Source, Open-to-Use, Prompt-based, Test cases available
Available tools for pre- and post-processing
Support	Online Manual Community Forum
Can be coupled to the following models	GLM, TUFLOW-FV, Telemac, any other model via FABM
How can someone get access to this model	Executables on develop website Source Code on github
Miscellaneous
Useful tricks	Do not start off too complicated and only include those modules that are absolutely necessary. For example, rather simulate three phytoplankton groups than seven.
Links	http://aed.see.uwa.edu.au/research/models/AED/download.html https://groups.google.com/forum/#!forum/aquaticmodelling
Form was updated: 2018-10-23

Reference list:

Weber, M., Rinke, K., Hipsey, M.R. and Boehrer, B., 2017. Optimizing withdrawal from drinking water reservoirs to reduce downstream temperature pollution and reservoir hypoxia. Journal of Environmental Management, 197, pp.96-105.

Snortheim, C.A., Hanson, P.C., McMahon, K.D., Read, J.S., Carey, C.C. and Dugan, H.A., 2017. Meteorological drivers of hypolimnetic anoxia in a eutrophic, north temperate lake. Ecological Modelling, 343, pp.39-53.

Adiyanti, S., Eyre, B.D., Maher, D.T., Santos, I., Golsby-Smith, L., Mangion, P. and Hipsey, M.R., 2016. Stable isotopes reduce parameter uncertainty of an estuarine carbon cycling model. Environmental Modelling & Software, 79, pp.233-255.

Bruce, L.C., P.L.M. Cook and M.R. Hipsey (2015) A model of oxygen and nitrogen biogeochemical response to hydrodynamic regimes in the Yarra River estuary. In: Weber, T., McPhee, M.J. and Anderssen, R.S. (eds) MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2015, pp. 524–530. ISBN: 978-0-9872143-5-5

Paraska, D.W., L.C. Bruce, G. Shiell and M.R. Hipsey (2015) Predicting critical thresholds of aquaculture waste loading to coastal sediment. In: Weber, T., McPhee, M.J. and Anderssen, R.S. (eds) MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2015, pp. 536–542. ISBN: 978-0-9872143-5-5

Bruce, L.C., Cook, P.L.M., Teakle, I. and Hipsey, M.R., 2014. Hydrodynamic controls on oxygen dynamics in a riverine salt-wedge estuary, the Yarra River estuary, Australia. Hydrology & Earth System Sciences, 18: 1397 – 1411

Hipsey, M.R., Bruce, L.C. and Kilminster, K., 2013. A 3D hydrodynamic-biogeochemical model for assessing artificial oxygenation in a riverine salt-wedge estuary. MODSIM2013 – 20th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2013, Adelaide, Australia.

Li, Y. and Hipsey, M.R., 2013. The importance of model structural complexity when simulating aquatic food webs. MODSIM2013 – 20th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2013, Adelaide, Australia.

Bruce, L.C., Cook, P.L.M. and Hipsey, M.R., 2011. Using a 3D hydrodynamic-biogeochemical model to compare estuarine nitrogen assimilation efficiency under anoxic and oxic conditions. In: Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2011, pp. 3691-3697. ISBN: 978-0-9872143-1-7.