During this year's EGU General Assembly we will present initial results of porting the existing PyCatch catchment model from the PCRaster modelling framework to LUE. This allows the model to be used on much larger areas in greater temporal and spatial detail. We ran the model for Africa at 3 arc-second resolution. The run used 12 cluster nodes containing 1152 CPU cores in total.

Last week, our paper An environmental modelling framework based on asynchronous many-tasks: scalability and usability was published in the Environmental Modelling and Software journal. The full paper can be found online: 10.1016/j.envsoft.2021.104998.

We moved the LUE source code repository from the PCRaster organization to the Computational Geography organization. Both are Github organizations. If you have a local clone pointing to the LUE repository in the PCRaster organization, then we advise you to update it to point to the new repository URL:

# Use git instead of https if you have the required rights
git remote set-url origin https://github.com/computationalgeography/lue.git

Yesterday, we released the first version of the LUE Conda package. This makes installing LUE as easy as:

conda install -c conda-forge lue

You can find more information about installing LUE, including links to the Conda package manager, in the installation manual.