The Colorado River is a vital source of water in the Western United States, providing drinking water for homes and irrigation for farms in seven states, but the basin is under increasing pressure from climate change and drought. A new computational tool developed by a research team, led by Penn State scientists, may help the region adapt to a complex and uncertain future.
Their tool, the Framework for Narrative Storylines and Impact Classification (FRNSIC), can help decision-makers explore many plausible futures and identify consequential scenario storylines -- or descriptions of what critical futures might look like -- to help planners better address the uncertainties and impacts presented by climate change. They reported their findings Sept. 19 in the journal Earth's Future.
"One of the ways states like Colorado are preparing for the future is by making plans for how things might evolve based on the available science and inputs from various stakeholders," said Antonia Hadjimichael, assistant professor in the Department of Geosciences at Penn State and lead author of the study. "This scenario planning process recognizes that planning for the future comes with many uncertainties about climate and water needs. So, planners have to consider different possibilities, such as a high-warming or a low-warming scenario."
Hadjimichael said that both the scientific community and decision makers around the world often turn to scenarios to describe what conditions may look like in the future, but this approach may regard only a few possibilities and discount other alternatives.
These scenario planning approaches often feature a relatively small number of scenarios -- for example what drought conditions might look like under different levels of warming -- and may fail to capture the complexity of all the factors involved.
Alternatively, scientists use a technique called exploratory modeling, where models simulate thousands to millions of possible futures to discover which are consequential. But this approach is often not practical for use by decision makers, the scientists said.
"We wanted to provide something in the middle," Hadjimichael said. "We wanted to create something that bridges the two -- that considers the complexities but also boils it down to something that's a little more actionable and a little less daunting."
Their tool, FRNSIC, uses exploratory modeling first to investigate a large number of hypothesized plausible future conditions. It then uses that data to classify and identify relevant and locally meaningful storylines, the scientists said.
"Our approach essentially explores plausible future impacts and then says, 'for this stakeholder, this is the storyline that would matter the most -- and then for this other stakeholder, there is a different storyline they should be worried about," Hadjimichael said. "It's adding a little bit more pluralism and a little bit more nuance into how planning scenarios are established."
In the Colorado River basin, decision makers face a complex set of factors, including how to supply enough water for growing populations and farmers while ensuring their state is not using more than their allowed share of the river's flow, Hadjimichael said.
"The problem is there is not a single criterion that captures everybody and what they care about," she said. "Maybe you have a very large farm, and maybe I have a very small farm. And maybe we grow different things. It's hard to use a single factor to find out scenarios that would make us all happy, or make us all unhappy."
The storylines produced by FRNSIC can be used in future work in the Colorado River basin -- for example, how drought events are impacted when populations adapt and make changes.
"This allows policymakers to explore different states the world and helps review how different interventions might affect the basin under each storyline," Hadjimichael said. "These drought scenarios can be used to illuminate potential consequences, and therefore be used in negotiations or when asking stakeholders for their input."
Also contributing were Patrick Reed, professor at Cornell University; Julianne Quinn, assistant professor at the University of Virginia; and Chris Vernon, geospatial scientist, and Travis Thurber, software engineer, at Pacific Northwest National Laboratory
The U.S. Department of Energy, Office of Science, as part of research in MultiSector Dynamics, in the Earth and Environmental System Modeling Program supported this research.