DRAFT conceptual model of climate change connections in Yamuna river project.
Yamuna River Restoration and Climate Change With MSW
This stock and flow diagram is an updated working draft of a conceptual model of a dune-lake system in the Northland region of New Zealand.
Clone of Stock and flow diagram of phosphorus in a lake
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
Clone of Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Clone of EA sustainability take 2
The model starts in 1900. In the year 2000 you get the chance to set a new emission target and nominal time to reach it. Your aim is to have atmospheric CO2 stabilise at about 400 ppmv in 2100. From Sterman, John D. (2008) Risk Communication on Climate: Mental Models and Mass Balance. Science 322 (24 October): 532-533. Clone of IM-694 to run 1900 to 2100.
Clone of Climate Stabilization Task
This diagram provides a stylised description of important feedbacks within a shallow-lake system.
Clone of Clone of Key feedbacks in a shallow lake relating to Koura
This model is used in a world studies extended essay research. The research question is: In what ways would the water desalination method used in Singapore benefit water-stressed and economically less developed countries, using Palestine as a case study.
This model retrieved data on Palestine water resources from Authority, Palestinian Water. "Annual status report on water resources, water supply, and wastewater in the occupied State of Palestine 2011." Palestinian Water Authority, Ramallah 13 (2012)
Data for Singapore desalination process is taken from PUB, Singapore Water Agency, "Singapore Water Story." PUB, Singapore's National Water Agency. N.p., n.d. Web. 25 Feb. 2017.
Data for Palestine population growth was taken from World Bank. World Bank. "West Bank and Gaza Home." The World Bank. N.p., n.d. Web. 25 Feb. 2017.
This model assumes that Palestine population will grow at 2.92% (World Bank, 2015) and average domestic consumption is 90 litres per capita per day(Palestine Water Authority, 2012). This model does not take into account growing demands for industrial and agricultural sector. It also does not show the impact of climate change on Palestine natural water resources.
Clone of Model of Palestine water demand and supply in 40 years without input from desalination process
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.
Clone of Vollenweider model
Harvested fishery with endogenous investment and ship deployment policy. Ch 9 p345-360 John Morecroft (2007) Strategic Modelling and Business Dynamics. See simpler models at IM-2990 and IM-2991
Fishery Dynamics with Ship Deployment Policy
The beginning of a systems dynamics model for teaching NRM 320.
Clone of Insight Starting Guide for NRM 320
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.
Clone of Simple phytoplankton and oyster model
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.
Clone of Clone of Clone of Vollenweider model
•Dry
Period Case
–
25 years of historical dry period on record (1947-1973)-including drought of
record (1947-1956)
–Represents
the dry period case
–Future
dry cycle includes dry cycle of AMO and overlay of IPCC climate change
predictions
Clone of Clone of EA dry conditions 1947-1973
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.
Clone of Clone of Clone of Estuarine salinity 1 box model (J. Gomes Ferreira)
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.
Clone of NPD model (Nutrients, Phytoplankton, Detritus)
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.
Clone of Clone of NPD model (Nutrients, Phytoplankton, Detritus)
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
Clone of Midterm - Power Model
Two households with PV systems and Electric Vehicles, sharing a battery and connected to the grid. What are the advantages?
Clone of Vehicle to Grid Simulation
This model simulates the growth of carp in an aquaculture pond, both with respect to production and environmental effects.
Both the anabolism and fasting catabolism functions contain elements of allometry, through the m and n exponents that reduce the ration per unit body weight as the animal grows bigger.
The 'S' term provides a growth adjustment with respect to the number of fish, so implicitly adds competition (for food, oxygen, space, etc).
Carp are mainly cultivated in Asia and Europe, and contribute to the world food supply.
Aquaculture currently produces sixty million tonnes of fish and shellfish every year. In 2011, aquaculture production overtook wild fisheries for human consumption.
This paradigm shift last occurred in the Neolithic period, ten thousand years ago, when agriculture displaced hunter-gatherers as a source of human food.
Aquaculture is here to stay, and wild fish capture (fishing) will never again exceed cultivation.
Recreational fishing will remain a human activity, just as hunting still is, after ten thousand years - but it won't be a major source of food from the seas.
The best way to preserve wild fish is not to fish them.
Clone of CARP - Carp AquacultuRe in Ponds
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://www.eas.cornell.edu/
Clone of Clone of Global Carbon Cycle - For ENVS 270 Online
Simulate an impact of an asteroid of any Diameter at any given Speed!
Clone of Asteroid impact simulator
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.
Clone of Estuarine salinity 1 box model (J. Gomes Ferreira)
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.
Clone of Vollenweider model
Clone 26/07/16 of Plastic Pollution Solution Revolution