Simulation Modeling


Modeling natural systems are the current focus of the Argonne Simulation Project, led by John Christiansen (Argonne National Laboratory).The project uses ENKIMDU, a modeling framework with the capability to create a virtual world on which to run simulations based on environmental and social parameters.


ENKIMDU simulations replicate the interactions of natural and social processes as they operate in time and space. The time scales can be as short as minutes or decades or as long as centuries. The simulations include detailed demographic and social models that can show realistic social structures and dynamics over time.


ENKIMDU’s approach (holistic, agent-based, “bottom up” modeling) means the simulated historical trajectories of human-settlement landscapes appear as the cumulative outcomes of small-scale activities and interactions, for instance by individual persons, households, crop fields, and domesticated animals.


In CRANE’s environmental phase, ENKIMDU will work with variables such as soil, vegetation cover and weather. John is partnering with CRANE researchers to determine data appropriate for developing a desired, and accurate, model of the Orontes watershed for the late Bronze and early Iron age.


Lynn Welton (Durham University) is working to determine specifics. While some variables are straightforward, such as terrain, Lynn also will be investigating variables such as weather, river and stream courses, and what types of vegetation were present in the region in the past in enough detail to create small cells to be mapped onto the virtual world.


ENKIMDU will be linked with the OCHRE software platform, through which researchers will be able to change variables and run simulations. John is collaborating with the team in Chicago to ensure OCHRE can work with the rich data sets required by the simulation.



The first phase of the simulation project has focused on developing the natural environmental parameters of the Orontes Watershed that are required for the modeling program.  Currently, the project is compiling information on natural factors such as soils, hydrology, vegetation, weather and climate. The next stage of the project will begin to incorporate social processes such as agricultural decision making and resource sharing models.