Balancing and making trade-offs amongst multiple-objectives is complicated.
Conventional approaches often fall short by emphasizing a handful of objectives which tends to promote a world of “winners and losers.” Even with creative identification of alternative actions, complex and large-scale decision problems can rarely be boiled down to a handful of choices capable of enduring over a range of exogenous conditions. Nowhere is this more evident than in the Sacramento River and Sacramento–San Joaquin Delta (SRD). The rivers flowing into and out of the SRD are among the most intensively managed in the world, and include multiple dams, reservoirs, canals, levees, large scale pumping plants and other water diversion systems. Together they are intended to provide reliable water supplies to human communities and agricultural enterprises and mitigate flood risk and drought all while supporting natural ecosystems and helping protect and recover threatened and endangered species.
ESSA’s scientists, in partnership with The Nature Conservancy, recently published a paper that proposes an innovative new solution to the perennial challenge of managing water for conflicting needs. The approach – coined “Turn Taking Optimization” (TTO) – draws inspiration from the song made famous by the Rolling Stones: “You can’t always get what you want.” This approach for managing water is based on the principle of taking turns using multiple objective optimization through time and requires managers to embrace flexibility and learning. An underlying tenet is that natural selection and evolution confer on many species the ability to survive and persist during poor habitat conditions – as long as there are enough good years. Although these adaptive capabilities have limits (e.g., continuous poor habitat conditions year after year can lead to extirpation), species resiliency affords practical opportunities for flexibility. Accepting this premise, our approach allows past ecological benefits to be “remembered” in the optimization, so that, for example, if a species’ ecological indicator (however defined) has been achieved in water year t -1 or earlier, its priority can be downgraded for an ecologically appropriate period, allowing other ecological indicators to have a higher priority. Put simply, as species “get what they need” their priority is temporarily reduced, letting other species and habitats have their turn. The idea is not that complicated, but the tough question is: “how do we actually manage flows to meet all these needs?”
To do this, our team studied ways to link the suite of hydrosystem simulation tools commonly used by state water planners with the Ecological Flows Tool (EFT) to evaluate how the Sacramento River flow regime could better balance favourable habitat conditions for 15 representative species and 31 indicators. Since intensive computations were required, the team employed a cloud-based optimization system that searches for alternative solutions using an approach called “particle swarm optimization.” Comparing TTO results to current management practices, 12 EFT indicators were improved, 14 showed no change, and 5 showed a reduction in suitability. When grouped into nine species and life-history groups, performance improved in four (late-fall-run Chinook, winter-run Chinook, spring-run Chinook, and Fremont cottonwood), did not change in four (fall-run Chinook Salmon, Delta Smelt, Splittail, and Longfin Smelt), and was worse in one group (steelhead). A net positive result yet one still tethered to the inescapable reality of ‘Jagger’s Law.’
Our study demonstrates that adopting a water allocation approach that incorporates shifting priorities and optimization of indicators across years can lead to overall multi-objective and species benefits.
Although a water-management paradigm that embraces TTO will not solve every trade-off, if it were tried, managers just might find that more values and objectives get what they need.
For a deeper look at study methods and results please see our article in the San Francisco Estuary & Watershed Science.