This model implements the equations proposed by Ketchum in 1954. The rationale behind the concept is that only phytoplankton that grows above a certain rate will not be flushed out of an estuary.  For biological processes:  Pt  =  Po exp(kt)  Where Pt is the phytoplankton biomass at time t, Po is th
This model implements the equations proposed by Ketchum in 1954. The rationale behind the concept is that only phytoplankton that grows above a certain rate will not be flushed out of an estuary.

For biological processes:

Pt  =  Po exp(kt)

Where Pt is the phytoplankton biomass at time t, Po is the initial biomass, and k is the growth rate.

For physical processes:

Pm  =  Po (1-r)^m

Where Pm is the phytoplankton biomass after m tidal cycles, and r is the exchange ratio (proportion of estuary water which does not return each tidal cycle).

By substitution, and replacing t by m in the first equation, we get:

Pm = Poexp(km).(1-r)^m

For phytoplankton to exist in an estuary, Pm = Po (at least), i.e. 1 / (1-r)^m = exp(km)
ln(1) - m.ln(1-r) = km
-m.ln(1-r) = km
k = -ln(1-r)

Ketchum (1954) Relation between circulation and planktonic populations in estuaries. Ecology 35: 191-200.

In 2005, Ferreira and co-workers showed that this balance has direct implications on biodiversity of estuarine phytoplankton, and discussed how this could be relevant for water management, in particular for the EU Water Framework Directive 60/2000/EC (Ecological Modelling, 187(4) 513-523).
A model of water flow within the potable water supply chain
A model of water flow within the potable water supply chain
This model implements a very simple proxy for vertical dispersion of heat in a lake based on the equation:  dT/dt = 1/A d(EA)/dz (dT/dz)  where: T: temperature (oC); t: time (days); z: depth (m); A: cross-sectional area (m2); E: vertical dispersion coefficient (m2 d-1)  If we consider that E is cons
This model implements a very simple proxy for vertical dispersion of heat in a lake based on the equation:

dT/dt = 1/A d(EA)/dz (dT/dz)

where: T: temperature (oC); t: time (days); z: depth (m); A: cross-sectional area (m2); E: vertical dispersion coefficient (m2 d-1)

If we consider that E is constant (it is in this model), then the equation becomes dT/dt = (EA/A)(d^2T/dz^2) = E(d^2T/dz^2), the classic diffusion equation

The model is simplified by exchanging temperature as a state variable, rather than executing  the full heat balance. This would require a computation of fluxes of atmospheric longwave and shortwave radiation, water longwave radiation, water conduction and convection, and water evaporation and condensation.

The vertical dispersion coefficients are adjusted artificially so that mixing increases at lower temperatures, thus quickly homogenizing the water column in colder months of the year.
This stock and flow diagram provides a broad description of the key nutrient pathways (N and P) that exist in a dune-lake system subject to external loadings emanating from intensive agriculture.
This stock and flow diagram provides a broad description of the key nutrient pathways (N and P) that exist in a dune-lake system subject to external loadings emanating from intensive agriculture.
Primitives for Watershed modeling project. Click Clone Insight at the top right to make a copy that you can edit.  The converter in this file contains precipitation for Tucson only. Tucson watersheds are Arroyo Chico, Canada Agua, and Lower Canada del Oro.
Primitives for Watershed modeling project. Click Clone Insight at the top right to make a copy that you can edit.

The converter in this file contains precipitation for Tucson only. Tucson watersheds are Arroyo Chico, Canada Agua, and Lower Canada del Oro.
Two households with PV systems and Electric Vehicles, sharing a battery and connected to the grid. What are the advantages?
Two households with PV systems and Electric Vehicles, sharing a battery and connected to the grid. What are the advantages?


This model illustrates predator prey interactions using real-life data of bison and wolf populations at Yellowstone National Park.
This model illustrates predator prey interactions using real-life data of bison and wolf populations at Yellowstone National Park.


From Schluter et al 2017  article  A framework for mapping and comparing behavioural theories in models of social-ecological systems COMSeS2017  video .   See also Balke and Gilbert 2014 JASSS  article  How do agents make decisions? (recommended by Kurt Kreuger U of S)
From Schluter et al 2017 article A framework for mapping and comparing behavioural theories in models of social-ecological systems COMSeS2017 video. See also Balke and Gilbert 2014 JASSS article How do agents make decisions? (recommended by Kurt Kreuger U of S)
This model provides a dynamic simulation of the Sverdrup (1953) paper on the vernal blooming of phytoplankton.  The model simulates the dynamics of the mixed layer over the year, and illustrates how it's depth variation leads to conditions that trigger the spring bloom. In order for the bloom to occ
This model provides a dynamic simulation of the Sverdrup (1953) paper on the vernal blooming of phytoplankton.

The model simulates the dynamics of the mixed layer over the year, and illustrates how it's depth variation leads to conditions that trigger the spring bloom. In order for the bloom to occur, production of algae in the water column must exceed respiration.

This can only occur if vertical mixing cannot transport algae into deeper, darker water, for long periods, where they are unable to grow.

Sverdrup, H.U., 1953. On conditions for the vernal blooming of phytoplankton. J. Cons. Perm. Int. Exp. Mer, 18: 287-295
Simple energy balance model of a planet with albedo, ocean, and atmosphere.  This simulation models the stock and flow of energy between a
star, a planet’s surface (primarily its oceans, which are the largest reservoir
of heat), and space.The assumptions governing this model are:  1. The planet abso
Simple energy balance model of a planet with albedo, ocean, and atmosphere.

This simulation models the stock and flow of energy between a star, a planet’s surface (primarily its oceans, which are the largest reservoir of heat), and space.The assumptions governing this model are:

1. The planet absorbs a fraction of the shortwave radiation arriving from its star, with that fraction given by (1-A), where A is albedo. 

2. The planet radiates longwave infrared radiation into space, with the amount of radiation into space given by σΤe4, where σ is the Stefan-Boltzmann constant and Te is the temperature of the effective radiating level.

3. The atmospheric lapse rate is 6 K/km.

4. If there is an imbalance between shortwave radiation absorbed and longwave radiation emitted, the imbalance affects the temperature of the planet. However, it does not do so instantaneously – the imbalance must heat or cool the mixed layer of the ocean.

5. At the start of the simulation, the planet is extremely close to equilibrium given its default parameters. If any of these parameters are changed, the planet will be out of equilibrium, and will have to adjust.

 Students in ENVS 270 Online at the University of Arizona: please click Clone Insight at the top to make an editable copy of this model.    As initially proposed by Pr. William M White of Cornell University:    http://www.geo.cornell.edu/eas/education/course/descr/EAS302/302_06Lab11.pdf    http://ww
Students in ENVS 270 Online at the University of Arizona: please click Clone Insight at the top to make an editable copy of this model.

As initially proposed by Pr. William M White of Cornell University:
This diagram provides an accessible description of the key processes that guide the water quality within a lake.
This diagram provides an accessible description of the key processes that guide the water quality within a lake.