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Good IDEAS on Virtual Terrestrial Ecosystems

Sources: Dan Hawkes, Carl Steefel

Goodideas_3_blogIn a report published earlier this year (February 2015) by the DOE Office of Science, covering a workshop convened this past year, ESD’s Carl Steefel, Eoin Brodie, and Charlie Koven, among others, collectively sought ways of applying new scientific computing capabilities to studies of Earth’s subsurface.  One of the results of this workshop (and others) was Interoperable Design of Extreme-Scale Application Software (IDEAS), a recently initiated project co-funded by the Advanced Scientific Computing Research (ASCR) program and Office of Biological and Environmental Research (BER) within the Office of Science.

This project will proceed in concert with, and support, a number of flagship programs within BER, including ESD’s SFA 2.0 Genomes-to-Watershed, Next Generation Ecosystem Experiment (NGEE)-Arctic and NGEE-Tropics programs. These programs have the goal of developing a predictive understanding of the complex ecosystems under study in each of those programs. To achieve the desired level of predictive understanding, a new generation of multiscale, multiphysics models is needed for terrestrial systems—models that incorporate process couplings and feedbacks between various “pools” (i.e., vegetation, soils, subsurface aquifers, and surface waters) across wide ranges of spatial and temporal scales.

Fig6_goodideasThis is a formidable task. Terrestrial systems are inherently multiscale, involve more processes than traditional multiphysics applications, and have significant uncertainty in process representation and coupling at different scales. Moreover, the scientific software community is facing the confluence of disruptive changes in computing architectures and new opportunities for greatly improved simulation capabilities. New architectures, while demanding fundamental algorithm and software refactoring, are at the same time enabling new multiscale and multiphysics modeling, simulation, and analysis.

Both Genomes-to-Watershed and NGEE projects seek to take advantage of these new scientific software capabilities by incorporating IDEAS. IDEAS pursues the development and demonstration of new approaches for producing, using, and supporting scientific software. It will establish methodologies and tools that facilitate delivery of software as reusable, interoperable components. Software lifecycle models will be developed that are both flexible and rigorous.

Specifically for the Genomes-to-Watershed Project, Phase I of which is an intensive study of the Colorado River watershed near Rifle, Colorado, IDEAS will provide fundamental simulation of biogeochemical cycling within the East River Watershed. The objective of this work, over the next three years, will be a better understanding of aquifer redox status and climate impacts on watershed carbon and nitrogen cycling—through higher fidelity, multiscale models simulated at high spatial resolution.

Fig12_goodideasSpecifically for NGEE-Arctic, IDEAS will provide the foundation for multiscale, multiphysics simulations of warming tundra in the Barrow, Alaska, region. The objective of this work, over the next three years, will be to determine (through high-resolution simulation of domains extending over 10 km) how dynamic microtopography caused by thawing permafrost alters the hydrologic and carbon cycles of Arctic lowland tundra.

With IDEAS, BER envisions a software ecosystem of interoperable components to increase both software development and scientific productivity across its portfolio of projects that depend on modeling. 

To read more about IDEAS, view the pdf here

To access the report on the DOE workshop that spawned IDEAS, Building Virtual Ecosystems: Computational Challenges for Mechanistic Modeling of Terrestrial Environments, go here:


U.S. DOE (including C.I. Steefel, E.L. Brodie, and C.D. Koven) (2015), Building Virtual Ecosystems: Computational Challenges for Mechanistic Modeling of Terrestrial Environments: Workshop Report. DOE/SC-0171. U.S. Department of Energy Office of Science.