This incomplete model represents a building that is heated by conduction from the hot outside air, solar gain through the windows, and internal heat from the people and machines inside. To complete the model, define the flow that represents the heat removed by mechanical cooling.
This incomplete model represents a building that is heated by conduction from the hot outside air, solar gain through the windows, and internal heat from the people and machines inside. To complete the model, define the flow that represents the heat removed by mechanical cooling.
To calculate the emission from mobile sources (road traffic) in DKI Jakarta, Indonesia
To calculate the emission from mobile sources (road traffic) in DKI Jakarta, Indonesia
This model is a classic simulation of the production cycle in the ocean, including the effects of the thermocline in switching off advection of dissolved nutrients and detritus to the surface layer.  It illustrates a number of interesting features including the coupling of three state variables in a
This model is a classic simulation of the production cycle in the ocean, including the effects of the thermocline in switching off advection of dissolved nutrients and detritus to the surface layer.

It illustrates a number of interesting features including the coupling of three state variables in a closed cycle, the use of time to control the duration of advection, and the modulus function for cycling annual temperature data over multiple years.

The model state variables are expressed in nitrogen units (mg N m-3), and the calibration is based on:

Baliño, B.M. 1996. Eutrophication of the North Sea, 1980-1990: An evaluation of anthropogenic nutrient inputs using a 2D phytoplankton production model. Dr. scient. thesis, University of Bergen.
 
Fransz, H.G. & Verhagen, J.H.G. 1985. Modelling Research on the Production Cycle of Phytoplankton in the Southern Bight of the Northn Sea in Relation to Riverborne Nutrient Loads. Netherlands Journal of Sea Research 19 (3/4): 241-250.

This model was first implemented in PowerSim some years ago by one of my M.Sc. students, who then went on to become a Buddhist monk. Although this is a very Zen model, as far as I'm aware, the two facts are unrelated.
 for more information, contact Dr. Ann Stapleton at: stapletona@uncw.edu     Description:    A simple model for breeding plants from generation to generation, with one "yield" variable (e.g. height) and 4 combinations of plants from the parents. Simulation tracks the frequencies of each combination
for more information, contact Dr. Ann Stapleton at: stapletona@uncw.edu

Description:

A simple model for breeding plants from generation to generation, with one "yield" variable (e.g. height) and 4 combinations of plants from the parents. Simulation tracks the frequencies of each combination in each generation as well as the overall average height by generation.

Adjust all sliders before beginning simulation. Make sure the A1A2 parameters are equal to the A2A1 parameters.
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.
My AP Environmental Homework for the Cats Over Borneo Assignment
My AP Environmental Homework for the Cats Over Borneo Assignment
 Harvested fishery with endogenous investment. Ch 9 p340-345 John Morecroft (2007) Strategic Modelling and Business Dynamics

Harvested fishery with endogenous investment. Ch 9 p340-345 John Morecroft (2007) Strategic Modelling and Business Dynamics

This model describes the flow of energy from generation to consumption for neighborhoods in the metro Atlanta area. It also calculates the cost of energy production and the number of years it will take to recover that cost.
This model describes the flow of energy from generation to consumption for neighborhoods in the metro Atlanta area. It also calculates the cost of energy production and the number of years it will take to recover that cost.
 The purpose of this deer management model is to explore the capacity of wildlife management actions to help us adapt to the effects of climate change.

The purpose of this deer management model is to explore the capacity of wildlife management actions to help us adapt to the effects of climate change.

A system diagram for the Mojave Desert including example socio-economic factors for an assignment at OSU- RNG 341.
A system diagram for the Mojave Desert including example socio-economic factors for an assignment at OSU- RNG 341.
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 upper 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.

The lower slider allows you to simulate a variable river flow, and understand how dispersion compensates for changes in freshwater input.
 This story contains a conceptual model of phosphorus cycling in a dune-lake system in the Northland region of New Zealand. It is based on the concept of a stock and flow diagram. Each orange ellipse represents an input, while each blue box represents a stock. Each arrow represents a flow. A flow in

This story contains a conceptual model of phosphorus cycling in a dune-lake system in the Northland region of New Zealand. It is based on the concept of a stock and flow diagram. Each orange ellipse represents an input, while each blue box represents a stock. Each arrow represents a flow. A flow involves a loss from the stock at which it starts and an addition to the stock at which it ends.

Simple model to illustrate Michaelis-Menten equation for nutrient uptake by phytoplankton.  The equation is:  P = Ppot S / (Ks + S)  Where:  P: Nutrient-limited production (e.g. d-1, or mg C m-2 d-1) Ppot: Potential production (same units as P) S: Nutrient concentation (e.g. umol N L-1) Ks: Half sat
Simple model to illustrate Michaelis-Menten equation for nutrient uptake by phytoplankton.

The equation is:

P = Ppot S / (Ks + S)

Where:

P: Nutrient-limited production (e.g. d-1, or mg C m-2 d-1)
Ppot: Potential production (same units as P)
S: Nutrient concentation (e.g. umol N L-1)
Ks: Half saturation constant for nutrient (same units as S)

The model contains no state variables, just illustrates the rate of production, by making the value of S equal to the timestep (in days). Move the slider to the left for more pronounced hyperbolic response, to the right for linear response.
This is my basic simulation of the studley Park landfill in Tobago. I was trying to estimate the remaining life in the landfill. I also tied it into littering and pollution rates
This is my basic simulation of the studley Park landfill in Tobago. I was trying to estimate the remaining life in the landfill. I also tied it into littering and pollution rates
 This stock and flow diagram is a working draft of a conceptual model of a dune-lake system in the Northland region of New Zealand.

This stock and flow diagram is a working draft of a conceptual model of a dune-lake system in the Northland region of New Zealand.

This model depicts a very simplified series of interactions between water quality inspectors and cannabis cultivators in northern California.
This model depicts a very simplified series of interactions between water quality inspectors and cannabis cultivators in northern California.
 Clone of  IM-3993  WIP based on 2016 Land Use Science  article  on Causal Analysis by Patrick Meyfroidt

Clone of IM-3993 WIP based on 2016 Land Use Science article on Causal Analysis by Patrick Meyfroidt

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.
   THE 2018 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION.  WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER R

THE 2018 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION.
WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER RELOCATION IN WEATHER CHANGES IN FLOODS AND DROUGHTS AND EXTENDED TROPICAL AND HORSE LATTITUDE CYCLONE ACTIVITY AROUND HADLEY CELLS

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE  ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.
BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST. 
CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.

 This story presents a conceptual model of nitrogen cycling in a dune-lake system in the Northland region of New Zealand. It is based on the concept of a stock and flow diagram. Each orange ellipse represents an input, while each blue box represents a stock. Each arrow represents a flow. A flow invo

This story presents a conceptual model of nitrogen cycling in a dune-lake system in the Northland region of New Zealand. It is based on the concept of a stock and flow diagram. Each orange ellipse represents an input, while each blue box represents a stock. Each arrow represents a flow. A flow involves a loss from the stock at which it starts and an addition to the stock at which it ends.