gospl 0.1.1

A Python interface to perform Global Landscape Evolution Model

Global Scalable Paleo Landscape Evolution / gospl

What's in the box?

gospl (pronounced: /ˈɡospel/, [ˈɡo̞s̠pe̞l]) is a scalable parallelised Python-based numerical model built to simulate paleo-landscapes and basins reconstruction at global scale.

gospl is a parallel TIN-based landscape evolution model, built to simulate topography dynamic of the Earth over millions of years.

The model accounts for hillslope processes (soil creep using linear diffusion), fluvial incision (stream power law), spatially and temporally varying tectonics (horizontal and vertical displacements) and climatic forces (temporal and spatial precipitation changes and/or sea-level fluctuations).

Specs

The model is based on the following approaches:

• an adaptation of the implicit, parallelisable method for calculating drainage area for both single (D8) and multiple flow direction (Dinf) from [Richardson et al., 2014],
• the methods developed in badlands [Salles et al., 2018] for marine sediment distribution,
• a PETSc layer similar to the one in eSCAPE [Salles, 2019] for mash partitioning and solvers.

License

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with this program. If not, see http://www.gnu.org/licenses/lgpl-3.0.en.html.

Documentation & Installation

https://gospl.readthedocs.io/

Artemis HPC Sydney

module load gcc/4.9.3  python/3.6.5 petsc-gcc-mpich/3.11.1

export F77FLAGS=-fPIC
export FCFLAGS=-fPIC

python3 setup.py install --user

Performance tests

• Resolution distribution for 10 million points (min:7.6 km, max:10.3 km, mean: 9.1 km)

PTS	CPUS	WALLTIME	NODES
10612062	8	17:08:58	1
10612062	16	08:58:32	2
10612062	32	04:57:58	4
10612062	64	03:32:15	6
10612062	96	02:41:17	6
10612062	128	02:40:57	7

• Resolution distribution for 17 million points (min:4.8 km, max:7.6 km, mean: 6.0 km)

PTS	CPUS	WALLTIME	NODES
17004184	64	07:28:41	4
17004184	96	06:38:11	4
17004184	128	05:29:51	6
17004184	144	04:59:49	6
17004184	168	04:31:14	7
17004184	192	06:23:02	7