Insight diagram
Here is the Covid 19 Statistics model based on the Philippines.
Ph_Covid19SDM_Jaspher Balcueba (FINAL)
Insight diagram
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)
Insight diagram
A system diagram for the Mojave Desert including example socio-economic factors for an assignment at OSU- RNG 341.
Mojave Desert System Diagram with SES
Insight diagram
Combining electromobility and renewable energies since 2014.

http://www.amsterdamvehicle2grid.nl/

SEEV4-City Prototype model
Insight diagram
Koala Prediction
Insight diagram
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 Vollenweider model
Insight diagram
For Sustainability & Eco Innovation class
Clone of The Olympics Stock & Flow + Stakeholders
Insight diagram

A simulation illustrating simple predator prey dynamics. You have two populations.

Clone of Predator Prey
Insight diagram
This model illustrates the key processes that influence the water level within Lake Okeechobee.


References:

Southwest Florida Water Management District. (2020). Lake Okeechobee. Retrieved from https://apps.sfwmd.gov/sitestatus/

United States Geological Survey. (2020). USGS Water-Year Summary for Site USGS 02276400. Retrieved from https://nwis.waterdata.usgs.gov/nwis/wys_rpt?dv_ts_ids=210619&wys_water_yr=2019&site_no=02276400&agency_cd=USGS&adr_water_years=2006%2C2007%2C2008%2C2009%2C2010%2C2011%2C2012%2C2013%2C2014%2C2015%2C2016%2C2017%2C2018%2C2019&referred_module=

Winchester, J. (2020, October 10). Water releases from Lake Okeechobee to begin next week. Retrieved from https://www.winknews.com/2020/10/09/water-releases-from-lake-okeechobee-to-begin-next-week/


Created By:

Roger Al-Bahou
Carlos Alvarez
Christina Burgess
Devin Hanley
Daniel Harper
Water Level in Lake Okeechobee
Insight diagram
Clone of ENV 221 Assignment 2 - Watershed Stock&Flow
Insight diagram
The following insight shows the level of crime in the town of Bourke in comparison to the levels of Police and Community Engagement
Clone of Crime vs. Engagement
Insight diagram
The time-variable solution to a step-function change in inflow concentration for an ideal, completely mixed lake.
Clone of Clone of Clone of ENVE 431 - HW5 - PROBLEM 7
Insight diagram
Combining electromobility and renewable energies since 2014.

http://www.amsterdamvehicle2grid.nl/

Clone of Amsterdam V2G simulation 2.0
Insight diagram
Collapse of the economy, not just recession, is now very likely. To give just one possible cause, in the U.S. the fracking industry is in deep trouble. It is not only that most fracking companies have never achieved a free cash flow (made a profit) since the fracking boom started in 2008, but that  an already very weak  and unprofitable oil industry cannot cope with extremely low oil prices. The result will be the imminent collapse of the industry. However, when the fracking industry collapses in the US, so will the American economy – and by extension, probably, the rest of the world economy. To grasp a second and far more serious threat it is vital to understand the phenomenon of ‘Global Dimming’. Industrial activity not only produces greenhouse gases, but emits also sulphur dioxide which converts to reflective sulphate aerosols in the atmosphere. Sulphate aerosols act like little mirrors that reflect sunlight back into space, cooling the atmosphere. But when economic activity stops, these aerosols (unlike carbon dioxide) drop out of the atmosphere, adding perhaps as much as 1° C to global average temperatures. This can happen in a very short period time, and when it does mankind will be bereft of any means to mitigate the furious onslaught of an out-of-control and merciless climate. The data and the unrelenting dynamic of the viral pandemic paint bleak picture.  As events unfold in the next few months,  we may discover that it is too late to act,  that our reign on this planet has, indeed,  come to an abrupt end?  
Covid 19 - irreversible and catastrophic consequences
Insight diagram
Westley, F. R., O. Tjornbo, L. Schultz, P. Olsson, C. Folke, B. Crona and Ö. Bodin. 2013. A theory of transformative agency in linked social-ecological systems. Ecology and Society 18(3): 27. link

Clone of Transformative Agency in Social-Ecological System
Insight diagram
Simple model to illustrate oyster growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where: 

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)
I: Light energy at depth of interest (uE m-2 s-1)
Iopt: Light energy at which Pmax occurs (uE m-2 s-1)
S: Nutrient concentration (umol N L-1)
Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:
- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.
- Light limited by the concentration of phytoplankton.
- Temperature effect on phytoplankton and Oyster growth.


Clone of Clone of Oyster Growth based on Phytoplankton Biomass
Insight diagram
Plastic Pollution Solution Revolution
Insight diagram
Modeling forest succession in a northeast deciduous forest.
Lab1 Forestry Succession Model
Insight diagram
Clone of Plastic Pollution Solution Revolution
Insight diagram

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
Insight diagram
B
Predator-Prey Interactions (Wolves & Moose) QB
Insight diagram
Simple model to illustrate oyster growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where: 

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)
I: Light energy at depth of interest (uE m-2 s-1)
Iopt: Light energy at which Pmax occurs (uE m-2 s-1)
S: Nutrient concentration (umol N L-1)
Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:
- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.
- Light limited by the concentration of phytoplankton.
- Temperature effect on phytoplankton and Oyster growth.


Clone of Clone of Clone of micro algae , biogas , bioelectrcidades
Insight diagram
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)