Very simple model demonstrating growth of phytoplankton using Steele's equation for potential production and Michaelis-Menten equation for nutrient limitation.  Both light and nutrients (e.g. nitrogen) are modelled as forcing functions, and the model is "over-calibrated" for stability.  The phytopla
Very simple model demonstrating growth of phytoplankton using Steele's equation for potential production and Michaelis-Menten equation for nutrient limitation.

Both light and nutrients (e.g. nitrogen) are modelled as forcing functions, and the model is "over-calibrated" for stability.

The phytoplankton model approximately reproduces the spring-summer diatom bloom and the (smaller) late summer dinoflagellate bloom.
 
Oyster growth is modelled only as a throughput from algae. Further developments would include filtration as a function of oyster biomass, oyster mortality, and other adjustments.
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.  We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

My AP Environmental Homework for the Cats Over Borneo Assignment
My AP Environmental Homework for the Cats Over Borneo Assignment
The beginning of a systems dynamics model for teaching NRM 320.
The beginning of a systems dynamics model for teaching NRM 320.
  The effect of phosphorus on an ecosystem
 The effect of phosphorus on an ecosystem
M.Sc. in Environmental Engineering SIMA 2018 New University of Lisbon, Portugal   Model to represent oyster individual growth by simulating feeding and metabolism. Model (i) partitions metabolic costs into feeding and fasting catabolism; (ii) adds allometry to clearance rate; (iii) adds temperature
M.Sc. in Environmental Engineering SIMA 2018
New University of Lisbon, Portugal

 Model to represent oyster individual growth by simulating feeding and metabolism. Model (i) partitions metabolic costs into feeding and fasting catabolism; (ii) adds allometry to clearance rate; (iii) adds temperature dependence to clearance rate; (iv) illustrates how clearance rate per gram is used if we multiply by the oyster biomass
This model implements the one-dimensional version of the advection-dispersion equation for an estuary. The equation is:  dS/dt = (1/A)d(QS)/dx - (1/A)d(EA)/dx(dS/dx) (Eq. 1)  Where S: salinity (or any other constituent such as chlorophyll or dissolved oxygen), (e.g. kg m-3); t: time (s); A: cross-se
This model implements the one-dimensional version of the advection-dispersion equation for an estuary. The equation is:

dS/dt = (1/A)d(QS)/dx - (1/A)d(EA)/dx(dS/dx) (Eq. 1)

Where S: salinity (or any other constituent such as chlorophyll or dissolved oxygen), (e.g. kg m-3); t: time (s); A: cross-sectional area (m2); Q: river flow (m3 s-1); x: length of box (m); E: dispersion coefficient (m2 s-1).

For a given length delta x, Adx = V, the box volume. For a set value of Q, the equation becomes:

VdS/dt = QdS - (d(EA)/dx) dS (Eq. 2)

EA/x, i.e. (m2 X m2) / (m s) = E(b), the bulk dispersion coefficient, units in m3 s-1, i.e. a flow, equivalent to Q

At steady state, dS/dt = 0, therefore we can rewrite Eq. 2 for one estuarine box as:

Q(Sr-Se)=E(b)r,e(Sr-Se)-E(b)e,s(Se-Ss) (Eq. 3)

Where Sr: river salinity (=0), Se: mean estuary salinity; Ss: mean ocean salinity

E(b)r,e: dispersion coefficient between river and estuary, and E(b)e,s: dispersion coefficient between the estuary and ocean.

By definition the value of E(b)r,e is zero, otherwise we are not at the head (upstream limit of salt intrusion) of the estuary. Likewise Sr is zero, otherwise we're not in the river. Therefore:

QSe=E(b)e,s(Se-Ss) (Eq. 4)

At steady state

E(b)e,s = QSe/(Se-Ss) (Eq 5)

The longitudinal dispersion simulates the turbulent mixiing of water in the estuary during flood and ebb, which supplies salt water to the estuary on the flood tide, and make the sea a little more brackish on the ebb.

You can use the slider to turn off dispersion (set to zero), and see that if the tidal wave did not mix with the estuary water due to turbulence, the estuary would quickly become a freshwater system.
Very simple model demonstrating growth of phytoplankton using Steele's equation for potential production and Michaelis-Menten equation for nutrient limitation.  Both light and nutrients (e.g. nitrogen) are modelled as forcing functions, and the model is "over-calibrated" for stability.  The phytopla
Very simple model demonstrating growth of phytoplankton using Steele's equation for potential production and Michaelis-Menten equation for nutrient limitation.

Both light and nutrients (e.g. nitrogen) are modelled as forcing functions, and the model is "over-calibrated" for stability.

The phytoplankton model approximately reproduces the spring-summer diatom bloom and the (smaller) late summer dinoflagellate bloom.
 
Oyster growth is modelled only as a throughput from algae. Further developments would include filtration as a function of oyster biomass, oyster mortality, and other adjustments.
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.  We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

First level of slowly building up a generic cost-benefit model primarily to show T313 students but useful elsewhere
First level of slowly building up a generic cost-benefit model primarily to show T313 students but useful elsewhere
In Chile,  60% of its population are exposed to levels of Particulate Matter (PM) above international standards . Air Pollution is causing  4,000 premature deaths per year , including health costs over US$8 billion.    The System Dynamics Causal Loop Diagram developed herein shows an initial study o
In Chile, 60% of its population are exposed to levels of Particulate Matter (PM) above international standards. Air Pollution is causing 4,000 premature deaths per year, including health costs over US$8 billion.

The System Dynamics Causal Loop Diagram developed herein shows an initial study of the dynamics among the variables that influences the accumulation of PM in the air, in particular the case of Temuco, in the South of Chile. In Temuco, 97% of the PM inventories comes from the combustion of low quality firewood, which in turns is being burned due to its low price and cultural habits/tradition.
European Masters in System Dynamics 2016 New University of Lisbon, Portugal  Simple model to represent oyster individual growth by simulating feeding and metabolism.
European Masters in System Dynamics 2016
New University of Lisbon, Portugal

Simple model to represent oyster individual growth by simulating feeding and metabolism.
Simple mass balance model for lakes, based on the Vollenweider equation:  dMw/dt = Min - sMw - Mout  The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs, for eutrophication assessment.
Simple mass balance model for lakes, based on the Vollenweider equation:

dMw/dt = Min - sMw - Mout

The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs, for eutrophication assessment.
The following insight shows the level of crime in the town of Bourke in comparison to the levels of Police and Community Engagement
The following insight shows the level of crime in the town of Bourke in comparison to the levels of Police and Community Engagement
In Chile,  60% of its population are exposed to levels of Particulate Matter (PM) above international standards . Air Pollution is causing  4,000 premature deaths per year , including health costs over US$8 billion.    The System Dynamics Causal Loop Diagram developed herein shows an initial study o
In Chile, 60% of its population are exposed to levels of Particulate Matter (PM) above international standards. Air Pollution is causing 4,000 premature deaths per year, including health costs over US$8 billion.

The System Dynamics Causal Loop Diagram developed herein shows an initial study of the dynamics among the variables that influences the accumulation of PM in the air, in particular the case of Temuco, in the South of Chile. In Temuco, 97% of the PM inventories comes from the combustion of low quality firewood, which in turns is being burned due to its low price and cultural habits/tradition.
 This model describes nitrogen cycling in a dune-lake system in the Northland region of New Zealand. It is based on stock and flow diagrams where each orange oval represents an input, while each blue box represents a stock. Each arrow represents a flow. Flows reduce the stock at which they start and

This model describes nitrogen cycling in a dune-lake system in the Northland region of New Zealand. It is based on stock and flow diagrams where each orange oval represents an input, while each blue box represents a stock. Each arrow represents a flow. Flows reduce the stock at which they start and add to the stock at which they end.

Teilmodell für die Umweltbelastung mit den Parametern Schadstoffeintrag, Erholungsrate und Schadschwelle.
Teilmodell für die Umweltbelastung mit den Parametern Schadstoffeintrag, Erholungsrate und Schadschwelle.
In Chile,  60% of its population are exposed to levels of Particulate Matter (PM) above international standards . Air Pollution is causing  4,000 premature deaths per year , including health costs over US$8 billion.    The System Dynamics Causal Loop Diagram developed herein shows an initial study o
In Chile, 60% of its population are exposed to levels of Particulate Matter (PM) above international standards. Air Pollution is causing 4,000 premature deaths per year, including health costs over US$8 billion.

The System Dynamics Causal Loop Diagram developed herein shows an initial study of the dynamics among the variables that influences the accumulation of PM in the air, in particular the case of Temuco, in the South of Chile. In Temuco, 97% of the PM inventories comes from the combustion of low quality firewood, which in turns is being burned due to its low price and cultural habits/tradition.