Predicting Nature to improve environmental management: How close are we and how do we get there?
When: Monday, October 21st, 11am MT / 1 pm ET
Presented by: Melissa Kenney—University of Minnesota
Dr. Melissa A. Kenney is an environmental decision scientist with expertise in multidisciplinary, team-based science approaches to solving sustainability challenges. Her research program broadly addresses how to integrate both scientific knowledge and societal values into policy decision-making under uncertainty. Dr. Kenney is also the Associate Director of Knowledge Initiatives at the University of Minnesota’s Institute on the Environment where she directs efforts to build synergy across IonE’s broad scientific research portfolio. She earned a Ph.D. from Duke University, focused on integrating water quality and decision models.
Near-term iterative ecological forecasting an emerging win-win for accelerating ecological research while making our science more directly relevant to society. However, ecological forecasting efforts span a wide range of subdisciplines that are often unaware of each other. In 2018 we launched the Ecological Forecasting Initiative (EFI), an international grassroots consortium aimed at developing an iterative forecasting community of practice. Our mission is to solve the challenge of predicting nature. In this talk, I briefly discuss EFI’s six cross-cutting themes (theory and synthesis, education, cyberinfrastructure, methods, knowledge transfer, and decision science) and how we are working to bring the community together. Particular examples from a decision science perspective will be highlighted.
Powell Center Working Group: Operationalizing Ecological Forecasts
When: Monday, November 18th, 11am MT / 1 pm ET
Presented by: Ward Sanford—USGS
Dr. Ward Sanford has been researching regional-scale groundwater flow and transport for 30+ years at the USGS. A former member of the National Research Program, he is now in the Integrated Modeling and Prediction Division where he has been overseeing the development of a CONUS-extent shallow groundwater model of the United States. He has also been recognized for his research on the use of environmental age tracers to help calibrate groundwater models, and on the availability of groundwater in the Middle Rio Grande Basin, the Chesapeake Bay Impact Crater, and the Southern High Plains of Texas.
NASA’s GRACE satellite has been measuring spatial and temporal changes in the earth’s gravitation field for more than 15 years. Much of the effort that has gone into interpreting the GRACE data has focused on estimating multi-year storage declines resulting from, e.g., regional groundwater extraction or the melting of glaciers. NASA in the meantime has provided downscaled (100-km resolution) global maps of change in water storage. These maps have tempted researchers to use the data to interpret local water storage changes. An explanation of the way the data is collected can demonstrate the appropriate spatial scale for its application. On the other hand, few studies have examined the implications of the seasonal water storage signal detected by GRACE. As one aspect of the USGS Powell Center working group on the integration of GRACE data interpretation with ground-based monitoring and modeling, we are examining seasonal GRACE signals and correlating them to seasonal gravity signals that have been quantified for the conterminous United States (CONUS). Independent estimates have been made of seasonal changes in snowpack, soil water, surface water, and groundwater storage as well as man-made impacts such as irrigation pumping from regional aquifers. The decomposition of the GRACE seasonal signal into its hydrologic components is providing important constraints on aquifer storage properties as part of our ongoing work to calibrate a national-scale groundwater model of the CONUS.
Powell Center Working Group: Integrating GRACE Satellite and Ground-based Estimates of Groundwater Storage Changes
Optimizing satellite resources for the global assessment and mitigation of volcanic hazards
When: Tuesday, December 3rd, 11am MT / 1 pm ET
Presented by: Kevin Reath—Cornell University
Dr. Kevin Reath is a Powel Center fellow and postdoctoral associate at Cornell University. His expertise is in remote sensing and volcanology. His research focuses on combining multi-parameter remote sensing data to identify volcanic processes and characterize volcanic activity.A significant number of the world’s active volcanoes are unmonitored by ground-based sensors, yet constitute an important hazard to nearby residents and infrastructure, as well as air travel and global commerce. Less than 35% of the volcanoes that have erupted since 1500 AD have continuous ground monitoring. Data from an international constellation of more than 50 current satellite instruments provide a cost-effective means of tracking activity at such volcanoes around the world and potentially forecasting hazards. These data span the electromagnetic spectrum -- ultraviolet, optical, infrared, and microwave (synthetic aperture radar--SAR) -- and can measure volcanic gas and thermal emissions, ground displacements, as well as surface and topographic change. Satellites offer the unique potential to globally monitor all ~1414 subaerial volcanoes with a common set of instruments that can address one of the grand challenges in volcanology -- to overcome our current biased understanding of the relation between volcanic unrest and eruption based on only a few well-studied volcanoes.
Powell Center Working Group: Optimizing satellite resources for the global assessment and mitigation of volcanic hazards