I model the evolution of the Earth's surface, and use computer simulations to read what the landscapes around us can tell us about past environments. I''m a lead developer on Landlab, a Python-based, open source community modelling tool for doing this kind of research.
I'm a lead developer on Landlab, a Python-based, open source community modelling tool for simulating how water, rock, and sediment move around at the surface of the Earth, how these movements interact with each other, and ultimately how they shape the surface of the Earth. These processes respond to climate (e.g., weathering rates, amounts and timings of rainfall, the role of plants) and to tectonics (e.g., surface uplift, deformation of mountain belts, seismic shaking). This means that we can use models like Landlab to explore what information about past climate and tectonics is encoded into the landscapes around us, and to use this understanding to make predictions about the future.
Landlab is a very unusual Earth surface process model, in that it attempts to follow modern best practices for open source software, as endorsed by the Institute. This means it is well documented, well tested, and offers interfaces to permit interoperability with other models. It also exists as a precompiled Python package, allowing users with entry-level Python skills to quickly get up to speed with its use; we also offer tutorials and other online resources to try to aid this process. However, as noted, these kinds of approaches to software in the Earth surface and indeed wider geoscientific modelling communities remain very much the exception rather than the rule. As part of my fellowship, I hope to learn more about cutting-edge best practice in open source software development, then go out into my scientific community to evangelise about its benefits!
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