Global Change Intersectoral Modeling System (GCIMS)

Many emergent societal challenges arise from the close interaction of human and environmental systems that occur at different spatial and temporal scales. The GCIMS project is a DOE-funded, multi-institution collaboration aimed at improving our understanding of the complex interaction of energy, water, and land systems at the regional-to-global scale over the course of the next century, with an emphasis on computationally efficient, open-source modeling frameworks. The Lamontagne Lab’s efforts on GCIMS aim to improve representations of uncertainty and scenario discovery tools to derive robust insight from large-ensemble analyses.

Nexus Exploration of Opportunities in Uruguay and Argentina (NEXO-UA)

This NSF-funded project develops a new analytical approach to improved regional food-energy-water integrated systems planning in river basins in Argentina and Uruguay taking into account regional, national, and global socioeconomic and climate dynamics. The Lamontagne Lab focuses on characterizing model uncertainties and aiding stakeholders in identifying and visualizing robust planning strategies. This project is a collaboration between Tufts University, the Wild Lab at the University of Maryland, and the White Lab at Arizona State University.

MA Hydroclimate Risk

Policy makers and planners are concerned with hydrologic and climate extremes and how climate change may impact their intensity and frequency. Standard hydrologic models are ill-suited to capturing these extremes at the local scale that is most relevant to basin-scale decision making. This Massachusetts EEOA funded project aims to adapt standard hydrologic models to better capture extremes by developing stochastic streamflow and weather generators as well as new risk and reliability metrics, in collaboration with the Steinschneider Lab at Cornell University and the USGS.