ATS Demonstrations

This is a suite of demonstration problems which show the various capabilities and typical workflows of ATS simulations.

A wide range of capabilities are shown here -- this is really meant to be the first introduction to ATS and the primary introductory documentation for ATS. Start here!

Included in each demonstration folder is a collection of runs meant to map out usage of the described physical capability. These include everything needed to get started using ATS. Any given run contains some of, and maybe all of, the following components:

• An input file: an .xml file read by ATS via ats ../my_file.xml required

• A mesh file for non-trivial meshes: typically an .exo file. Most meshes have included a python script or ipython notebook used to generate that mesh, showing that workflow.

• Forcing data: typically an .h5 file, and often generated from DayMet or other products. Often a python script or ipython notebook is used to generate these files, and these are included to show that workflow as well.

• A jupyter notebook .ipynb which describes, documents, and plots the results from the given run. Note these can be viewed, including plots, without even running the simulation. This is where to understand what is being done in each run.

Running the demos

Running all of the demos can take some time, but individual demos are often fairly quick. To run a given demo, make sure ats is compiled and (preferably) in your path, or that you have a docker container ready to go, and then:

python run_demos.py path_to_suite.cfg

or

python run_demos.py path_to_suite.cfg -t test_name

or (with docker):

python run_demos.py path_to_suite.cfg -e metsi/ats:latest -t test_name

Note that some individual runs may depend upon results from previous runs in that suite, and so all demos in that suite should be run. This is particularly true for demos that show a full workflow, such as ecohydrology or arctic_hydrology.

Also, if you want to run the demos without using these python scripts, be sure to check out the FAQs on our Wiki <https://github.com/amanzi/ats/wiki>_

Visualizing the results

Inside each subdirectory is a jupyter notebook. Jupyter comes fairly standard with most comprehensive python installations. Anaconda python is the one most ATS developers use, and its default installation includes nearly all python packages used by ATS.

Demonstration Problems

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Richards Equation: Steady state

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ats_demos/01_richards_steadystate/richards_steadystate.ipynb

This shows examples of solving Richards equation to steadystate. Typically this is used to establish a water column that satisfies hydrostatic balance.

Richards Equation: Transient

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ats_demos/02_richards/richards.ipynb

Transient problems show a variety of variably saturated cases, and demonstrate seepage faces and other common boundary conditions for the flow of water in a porous media.

Surface Water

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ats_demos/03_surface_water/surface_water.ipynb

Overland flow is solved through a diffusion wave equation. This demonstrates that as a standalone capability, solving surface water problems to demonstrate common usages of boundary conditions and forcing.

Integrated Hydrology

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ats_demos/04_integrated_hydro/integrated_hydro.ipynb

Integrated hydrology brings the previous two examples together, solving both surface and subsurface flow of water.

Ecohydrology

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ats_demos/05_ecohydrology/ecohydrology.ipynb

Ecohydrogy brings in the effects of other ecological processes, here loosely used to include all surface processes like evaporation, transpiration, and canopy processes like interception and storage, and even simplified biogeochemistry processes for a full carbon cycle.

Arctic Hydrology

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ats_demos/06_arctic_hydrology/arctic_hydrology.ipynb

ATS was originally developed as an Arctic hydrology simulator. It includes state-of-the art constitutive models and numerical methods for solving coupled freeze-thaw processes in Arctic environments.

Reactive Transport

(Work in progress)

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ats_demos/07_reactive_transport/reactive_transport.ipynb

ATS's sister code Amanzi was designed for solving problems of reactive transport. Interoperability of ATS and Amanzi allows ATS to leverage this work to solve problems of nonreactive and reactive transport in both the surface and subsurface, and even in frozen environments. (See below for ATS reactive transport demos when used with integrated hydrology)

Integrated hydrology and Reactive Transport

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ats_demos/13_integrated_hydro_reactive_transport/integrated_hydro_reactive_transport.ipynb

ATS is unique in the its ability to simulate reactive transport in integrated hydrology problems. In other words, it is capable of simulating muticomponent reactive transport in both surface and subsurface compartments using a novel coupling approach, and levering powerful, external geochemical engines Molins et al (2022) WRR <https://doi.org/10.1029/2022WR032074>_