WET

General Information
Acronym of the model	WET
Full name of the model	Water Ecosystems Tool
Model components	Chemistry, Biology
Supported platforms	Windows, Mac
Programming Language	FORTRAN95
Still maintained	Yes, by: Aarhus University
Most recent version	beta version
Model structure
Executables are available
1D, 2D (horizontal), 2D (vertical), 3D
Other: Flexible grid, Fixed grid, Mass balance included
Model description
Model objective	Water Ecosystem Tool is an aquatic ecosystem model describing the most important processes and mass balances for freshwater ecosystems.
Specific application	Impact assessment of - Eutrophication and (re-)oligotrophication - Climate change - Biomanipulations
Background knowledge needed to run model	Basic limnological understanding to interpret model simulation results
Basic procedures	For a comprehensive series of video tutorials to set up WET coupled to GOTM, see the resources here
WET simulate the most important dynamics and interactions between multiple trophic levels, including piscivorous, zooplanktivorous and bentivorous fish, zooplankton, zoobenthos, phytoplankton and rooted macrophytes and organic and inorganic nutrients. The model tracks dry weight, nitrogen and phosphorous,as well as accounts for oxygen dynamics.
Link to website/manual	Website
Model characteristics
Input variables	Obligatory: Weatehr data (time series for forcing) - Lake hypsography (for coupling to 1D models) - Amount of water layers Optional: - In- and outflow of nutrients and water (can also be specified as constant over time)
Input file format	.nml
Output variables	All state-variables in WET can be formatted to be output. The most common state-variables are: Water column Total phosphorus (TP), PO4, organic P-POM and P-DOM Total nitrogen (TN), NO3, NH4, organic N-POM and N-DOM Dissolved oxygen and silicate Phytoplankton dry-weight (DW) biomass, N- and P-Phyto and chlorophyll a concentrations Zooplankton DW biomass and fish DW biomass Sediment P-adsorbed to inorganic matter, TP, PO4, P-POM, P-DOM, TN, NO3, NH4, N-POM and N-DOM Zoobenthos DW biomass Macrophyte DW biomass and coverage A new feature in WET is the option to also output all or selected rates.
Output file format	.netcdf
Biogeochemical model components	Nutrients (NO3, NH4, NDOM, NPOM, PO4, PDOM, PPOM) Phytoplankton (user specified groups), Zooplankton (user specified groups), Zoobenthos (user specified groups), Fish (user specified groups), Rooted macrophytes (user specified groups)
Model structure/mathematical framework	ODE and empirical relartions
Temporal resolution	Seconds to days
Minimal spatial resolution	The minimal spatial resolution of WET has not been tested.
Variables needing calibration	Please see this website for a standard set of parameters that has previously been calibrated for four Danish lakes.
Has successfully been used in
Climate Change Scenario	Chen et al. (2019)
Mesotrophic water	Chen et al. (2019)
Management Support	Andersen et al. (2020)
Re-oligotrophication	Andersen et al. (2020)
Countries in which the model has been applied	Denmark
Which institutes have applied the model	Institute of Bioscience, Aarhus University
Accessibility
Open-Source, Prompt based, GUI
Available tools for pre- and post-processing	QWET is a GUI that facilitates model set-up, coupling to a SWAT catchment model, auto-calibration through ParSAC, model simulation visualization and a diverse array of scenario simulations
Support	Community forum on Gitlab page on model compiling, set-up, calibration and post-processes available as well as contact information on main webpage
Can be coupled to the following models	Coupled to FABM which allows a suite of hydrodynamic models to be coupled to
How can someone get access to this model	Gitlab
Miscellaneous
Comments	The entry form for WET is filled out with coupling to the 1D hydrodynamic model GOTM-AU.
Useful tricks and hints	Check webpage
Links	Gitlab Website
Form was updated: 2020-10-27

Reference list:
Andersen, T.K., Nielsen, A., Jeppesen, E., Hu, F., Bolding, K., Liu, Z.,Søndergaard, M., Johansson, L.S., Trolle, D., 2020. Predicting ecosystem state changes in shallow lakes using an aquatic ecosystem model: Lake Hinge, Denmark, an example. Ecol. Appl. 30. https://doi.org/10.1002/eap.2160Chen, W., Nielsen, A., Andersen, T.K., Hu, F., Chou, Q., Søndergaard, M., Jeppesen, E., Trolle, D., 2019. Modeling the Ecological Response of a Temporarily Summer-Stratified Lake to Extreme Heatwaves. Water 12, 94. https://doi.org/10.3390/w12010094