We are adaptively managing water levels in the Great Lakes, and projects being pursued by an IJC Great Lakes-St. Lawrence River Adaptive Management Committee will help improve climate monitoring in the basin. Adaptive management, as defined in a 2009 US Department of the Interior guide, “is a systematic approach for improving resource management by learning from management outcomes.”
The International Lake Ontario-St. Lawrence River Study Board recommended adaptive management in 2006 to refine its recommendations, which had been based on computer simulations that showed how water levels would impact several management objectives, including wetland health and shore protection costs. The process recommended by that Board, to model, decide, monitor, revise the model, and revisit the decision, is the essence of adaptive management.
Collaboration is not an aspiration for GLAM, it is a necessity. The IJC has created the space for adaptive management, but it is a meeting room, not a command center. The work described in GLAM’s Semi-Annual Report to the IJC (covering March-August 2016) is work done by its members, agencies and individuals in many categories including improved fisheries (see “Helping Fish in St. Marys Rapids with the Push of a Button”), improved climate monitoring, and model validation.
Improved climate monitoring
Climate researchers watch for trends in precipitation, runoff and temperature data that could signal a shift in climate and lake levels. But the estimates of how much water enters and leaves the lakes each day are imprecise. Two different approaches are used in the Great Lakes to measure these flows, and the differences between the estimates can be significant, leaving researchers to wonder whether trends are errors, or whether errors are hiding trends. GLAM helped organize and supported IJC funding that leveraged three efforts to improve these estimates.
Andrew Gronewold at the Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan, is applying a novel statistical model that uses the differences between the two estimates as clues for finding errors in one or the other. An initial experiment using a small dataset essentially eliminated the difference. Now the Lab will attempt to apply the method to a much longer dataset.
Another effort, headed by Vincent Fortin of Environment and Climate Change Canada, is working to improve historical estimates of on-lake precipitation. The records we have are extrapolations from land-based stations, and those estimates are suspect. High-resolution, short-term precipitation forecasts can provide more consistently accurate estimates of rainfall on the lakes. When the drivers used in these forecasts are available as historical datasets, the models can use them to produce “hindcasts” – predictions of things that have already happened.
A five-year hindcast run during the Upper Great Lakes Study provided convincing evidence that this would produce a better historical precipitation record, but required substantial computing power. Using a typical desktop computer, it would take about 900 years to produce the desired 30-year record. Environment and Climate Change Canada will use a new supercomputer to accomplish this in less than a year.
Finally, GLAM has been supporting IJC funding for projects to measure and report evaporation from lakes using eddy-covariance techniques. Prior to the Upper Great Lakes study, there were no sustained measurements of Great Lakes evaporation, a flow of water much larger than the flow over Niagara Falls.
Model validation GLAM has been managing efforts to validate the wetland plant and shore protection models that were so important in developing the IJC’s proposed Plan 2014 for regulating Lake Ontario levels. Working with the GLAM committee, Environment Canada, The Nature Conservancy and the state of New York have been monitoring wetland plant types by location and elevation since 2009, and these results are now being compared to modeled predictions from the wetland model. New York and the Army Corps have conducted surveys of individual shore protection structures to refine damage estimates produced during the study.
The US Department of Interior guide mentioned previously reports that “Adaptive management as described here is infrequently implemented, even though many resource planning documents call for it and numerous resource managers refer to it.” It is not easy to forge a collaborative focus across borders and agency missions on the lakes. It takes conscious planning to gather the evidence needed for science based management. This was not easy, but it has begun in the Great Lakes.
The Climate Change Framework Working Group IJC boards are working together to get ready for climate change. Representatives from boards across the boundary have formed a Climate Change Framework Working Group to expand on the basic ideas they had agreed to at an International Watersheds Initiative Workshop in Washington, D.C., on April 20, 2016.
The framework is still under development but it is built on three core ideas: that each board would use planning methods that were consistent across the boundary but flexible enough to accommodate the differences among board missions, that IJC and the boards would support and share a clearinghouse of information and lessons learned, and that there would be institutional support for adaptive management. The initial concept is described in a draft white paper and was presented to the St. Croix River Watershed Board on Nov. 29, 2016. The plan is to present the framework to commissioners in January 2017 to get their input.