Modelling Surface and Subsurface Flow on High-performance Computers

ParFlow is a numerical model that simulates the hydrologic cycle from the bedrock to the top of the plant canopy. It integrates three-dimensional groundwater flow with overland flow and plant processes using physically-based equations to rigorously simulate fluxes of water and energy in complex real-world systems. ParFlow is a computationally advanced model that can run on laptops and supercomputers and has been used in hundreds of studies evaluating hydrologic processes from the hillslope to the continental scale. ParFlow is open source (github.com/parflow) promoting community of active users and developers interested in advancing computational hydrology and improving hydrologic understanding.

Two courses are offered: Introduction and Advanced Applications with ParFlow (see course aims).

Course leader

Stefan Kollet (Forschungszentrum Jülich) Laura Condon (The University of Arizona) Nick Engdahl (Washington State University) Reed Maxwell (Colorado School of Mines)

Target group

Students, PhD students, postdocs, seniors.

Course aim

Introduction to ParFlow [July 20-21, 2020]

The trainee will learn about the basic theory of ParFlow, how to generate all necessary input information to construct basic ParFlow models, and perform simulations. In addition, post-processing and visualization of ParFlow results will be discussed.

Advanced applications with ParFlow [July 23-24, 2020]

The trainee is familiar with ParFlow and will learn about advanced input functionality that is required to construct large-scale, sophisticated models to simulate terrestrial systems from the subsurface to the land surface. Simulations will be performed and the results will be discussed and analyzed in the context of high-performance computing, parallel scaling and big data analytics.