PNNL

The Science

Planning and decision making around infrastructure needs, along a river basin for example, often happens at a regional scale. However, industrial sectors ranging from electricity production to water resources management typically do their own analyses, even when a holistic multi-sectoral approach would be better. To facilitate holistic cross-sectoral decision-making, a team of researchers led by scientists at the U.S. Department of Energy’s Pacific Northwest National Laboratory, have developed an open-source modeling platform, called Metis, that combines global human and Earth system dynamic tools with local datasets. This platform allows users to explore and evaluate impacts of different global and regional influences on the evolution of local resource interactions.

The Impact

The importance of holistic multi-sectoral modeling at multiple scales is well established in the literature, but implementation in practice remains a challenge. Metis provides an efficient modeling platform to easily analyze and evaluate the impacts of different global and regional influences across sectors at finer spatial scales than typically modeled in the Global Change Analysis Model (GCAM).

Summary

Metis is an open-source R package hosted on GitHub. To overcome the challenge of data scarcity that is typical of regional planning studies evaluating multi-sector dynamics, Metis provides users with default data sets describing energy, water, and land supplies and demands for the region of interest. These default data sets are built from GCAM outputs that are downscaled to a region of interest. Metis then aggregates the downscaled data and integrates multi-sectoral data across modeling tools at variable spatial scales. Metis functions collectively allow users to compare, manipulate, and harmonize multi-sector data at user-specified spatial scales. Users can also identify and quantify sectoral inter-linkages via Metis. Each Metis function can also be used independently to support an array of other research applications, such as spatial analysis and data visualization.

PNNL Contact

Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov

Funding

This research was supported by the U.S. Department of Energy, Office of Science, as part of research in the Multi-Sector Dynamics, Earth and Environmental System Modeling Program.