30, 2019) — Understanding the earth’s water systems is a complicated endeavor.
Factors like climate, air and water quality, ecosystem, droughts, erosion,
sediments and the impact of human activity need to be taken into account when creating
a model that would accurately predict, for example, how the scale and frequency
of floods and droughts will be affected by climate change in the coming years.
Yet such a model would require tremendous amount of valuable
and diverse data that are not always readily available; specialized models from
across diverse disciplines; high-performance computing (HPC) resources to develop
integrated model simulations and store the massive outputs; and a sizable group
of researchers to orchestrate it.
Now, a national, cross-disciplinary team of researchers, led
by Xu Liang, professor of civil and environmental engineering at the University
of Pittsburgh Swanson School of Engineering, has received a combined $1.3
million from the National Science Foundation to create a new
cyberinfrastructure framework that can build such a model, with $437,232
designated for Pitt.
CyberWater, an open framework of cyberinfrastructure, will
enable easy integration of diverse data sets and models for investigating water
resources and climate-related environmental issues. It will allow users to
integrate many different models without the need for coding, and it will enable
reproducible computing and seamless, on-demand access to various HPC resources.
“Understanding environmental issues, like flooding, depends
on so many factors—topography, soil, changes in land cover and vegetation,
human activity, and more,” says Liang. “Critical questions like this one can
only be answered by looking at all these factors and how they interact, but
before CyberWater, they couldn’t easily be considered together without the
benefit of a large team of researchers from different disciplines, working
together over multiple years.”
The new cyberinfrastructure framework will allow scientists
to discover, access and use diverse sets of data, and link that data to
multiple models at once. The user can then assess and evaluate how the models
interact and, ultimately, test comprehensive hypotheses and alternate process
representations using the coupled models.
Liang will work with a team of experts to create this modeling
platform: computer scientists and cyber experts from Indiana University-Purdue
University Indianapolis, Indiana University, and Ball State University; climate
scientists from North Carolina State University; and hydrologists from Iowa
University and the Consortium of Universities for the Advancement of Hydrologic
Science, Inc. (CUAHSI).
The grant, titled “Collaborative
Research: CyberWater—An open and sustainable framework for diverse data and
model integration with provenance and access to HPC,” will continue through
Maggie Pavlick, 9/30/2019
Contact: Maggie Pavlick