Lying roughly dead center in the lower half of Idaho, the Big Wood River Basin is more than 3,000 square miles, an area larger than Delaware. As with much of the U.S. West, the Big Wood is facing potential water scarcities as warming temperatures lead to less snowpack, changing the Big Wood’s hydrology and potentially affecting everyone from ski resort owners to farmers growing alfalfa and row crops.
To understand how climate change could impact life in the basin, my colleagues and I at CIRC, including Denise Lach, Co-Director of CIRC and Professor in Oregon State University’s School of Public Policy; John Bolte, CIRC researcher and Professor and Head of OSU’s Biological and Ecological Engineering Department; Allison Inouye, Bolte’s graduate student; and others tried out a somewhat new and largely untested methodology: for five years we engaged a stakeholder network in the co-production of science.
Climate change is often referred to as a ‘wicked problem.’ It is so complex and riddled with uncertainties that its solutions, especially in the realm of climate adaptation, cannot be fully implemented without involving those who will be most affected by the changes. Knowledge to action networks, or KTANs, attempt to resolve this problem by developing collaborative teams of researchers and stakeholders (people and organizations who hold a stake in what’s going on). Together these teams co-produce actionable science, science that is developed using the expertise of researchers and the knowledge of those who live and work in these geographic areas.
While this approach seems intuitive, it remains largely untested. CIRC and other projects in NOAA’s Regional Integrated Sciences and Assessments (RISA) program, build KTANs in an effort to meet stakeholder needs, but with varying degrees of success. (For a look at RISA efforts see “Connecting Scientists, Stakeholders, and Policymakers,” CIRCulator, May 2015.) KTANs are also time consuming to build.
We initially estimated CIRC’s Big Wood Project would take one to two years to complete. In the end, it took nearly five years and seemingly countless trips. In part, this reflects the complexity of the systems we were attempting to represent, but it also shows the challenges in forming and maintaining a collaborative network. Learning to understand a community’s language, culture, and geography takes time, but is nonetheless invaluable to achieve success.
As we would learned in the Big Wood, part of the challenge is simply developing a working relationship with a community. CIRC’s team was made up of outsiders who did not live in the basin or even in Idaho. We soon found that we needed to avoid a common trap scientists fall into: thinking we are experts who know best. For co-production to succeed, we needed to realize that we did not have a monopoly on knowledge.
Creating Actionable Science
Over several years of meetings, CIRC’s team presented to stakeholders findings that Bolte created in Envision. A powerful computer program designed by Bolte, Envision allowed us to model the interaction of hydrological and landscape processes across all 3,200 square miles of the Big Wood Basin, and gave us the ability to account for influences of different scenarios of climate and human processes.
In theory these scenarios (essentially computer-powered thought experiments) are simple: package a suite of assumptions about human systems or decisions and incorporate them into a model that explores their influence across a landscape. Doing this in the Big Wood allowed us to visualize what would happen if, for instance, a 7 degree Fahrenheit increase in temperature is accompanied by a population explosion.
But our tool was only as good as the information going into it, and we needed more than the latest climate and hydrologic science; we needed to know how projected changes in the environment were going to affect stakeholders. In the Big Wood, teams of stakeholders acted as sounding boards, commenting on the efficacy of our modeling approaches for answering important questions or identifying existing research and datasets that could save us time. You might even say this kept us grounded.
For example, farmers in the Big Wood Basin grow food that requires 20 to 30 inches per season of water, but only about half that amount falls as precipitation in the entire year. Consequently, farmers rely on irrigation from snow melt to meet their water needs. Our climate projections showed that rising temperatures (some 3° F to 12° F warmer by the end of this century across the basin) were going to limit snowpack, but understanding how that impacted crops or how farmers could respond required conversations with stakeholders.
What We Found
Over the course of the project, major landscape influences were distilled into four scenarios. The first two represented very different futures. One represented an economic base that became increasingly tourism dominated (Tourist Boom); the other, a future that was agriculturally dominated (Ag. Boom). Then, across each of these economic scenarios, we considered the influence of two diverging levels of management from today’s conditions: more managed and less managed.
For example, we considered what would happen in the Tourist Boom scenario if land use rules became more managed or less managed, and how these restrictions might influence the amount of land available for agriculture and overall water demand in the basin. In the Ag. Boom scenario, we considered changes in water management around reservoir storage, irrigation efficiency, and crop selections. Underlying these management assumptions were climate scenarios that considered a range of warming based on the extent to which humans would continue adding greenhouses to the atmosphere (the previously mentioned 3° F to 12° temperature shifts).
In the end, we found that the role of management turns out to be important. For example, by using existing tools for land use and water efficiency, the agriculture sector can maintain or even decrease the water scarcity it experiences, even as the climate changes. It’s also important to note that these scenarios were not intended to suggest what our Big Wood stakeholders should do in the future but what they could do. A full description of our scenarios and results can be found on the Data Explorer we created for the project: http://explorer.bee.oregonstate.edu/studyareas/bigwood/.
When my colleagues and I began this project, I found it difficult to know what to say to communities when they asked how climate change would impact them. Many of these communities, particularly in rural areas, were already facing challenges. Pointing out that climate change was only going to make things more difficult was not something people wanted to hear, especially if I couldn’t offer any solutions. Ultimately, our Big Wood project taught us that the role of human decision making is significant. And that without providing actionable solutions, the unpleasant implications of even the best climate science cannot lead to results.
Only time will tell if our efforts in the Big Wood aid adaptation there. I’m hopeful we will see progress, particularly since the community has begun more intensive planning to cope with the recent drought. As Bill Hazen, a retired extension agent and sheep rancher from the area noted: “The depth of understanding of the Big Wood drainage that you guys have achieved in this short time is astounding…[The] model[s] will influence many future decisions and especially the willingness to openly discuss problems and potentials.”