Automated Water Supply Model¶
Automated Water Supply Model (AWSM) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID. AWSM was designed to streamline the workflow used by the ARS to forecast the water supply of multiple water basins. AWSM standardizes the steps needed to distribute met. data with SMRF, run an energy and mass balance with iSnobal, and process the results, while maintaining the flexibility of each program.
The fastest way to get up and running with AWSM is to use the docker images that are prebuilt and can deployed cross platform.
To build AWSM natively from source checkout the install instructions here.
To mount a data volume, so that you can share data between the local filesystem and the docker, the -v option must be used. For a more in depth dicussion and tutorial, read about docker volumes. The container has a shared data volume at /data where the container can access the local filesystem.
When the image is run, it will go into the Python terminal within the image. Within this terminal, AWSM can be imported. The command /bin/bash can be appended to the end of docker run to enter into the docker terminal for full control. It will start in the /data location with AWSM code in /code/awsm.
docker run -v <path>:/data -it usdaarsnwrc/awsm [/bin/bash]
docker run -v /Users/<path>:/data -it usdaarsnwrc/awsm [/bin/bash]
docker run -v /c/Users/<path>:/data -it usdaarsnwrc/awsm [/bin/bash]
Running the test¶
docker run -it usdaarsnwrc/awsm /bin/bash cd /code/smrf gen_maxus --out_maxus test_data/topo/maxus.nc test_data/topo/dem.ipw cd /code/awsm awsm test_data/RME_run/config_pysnobal.ini
The output netCDF files will be placed in the /code/awsm/test_data/RME_run/output/rme/devel/wy1998/rme_test/runs/run1464_1670/output location.