Large water engineering projects have been a staple of modern engineering since the early nineteenth century. The development of water resources has been the pathway for developing modern economies — securing water for energy, food, cities, and security from floods and droughts. The most developed countries such as the United States have more than 75,000 dams, about 10 percent of the global total. Countries that are shifting from subsistence livelihoods to manufacturing and service economies are simultaneously changing how they manage their water resources — and often building or modifying new infrastructure. Developed economies often invest heavily in maintaining or modifying their extensive water infrastructure investments.

These pieces of infrastructure can last very long periods — very often decades, and sometimes centuries or even millennia in places such as China, India, Turkey, Peru, and Yemen. The longevity of most water infrastructure means that they are almost invariably exposed to changing environmental, demographic, and economic conditions. These are difficult for water managers, stakeholders, decision makers, and infrastructure designers and operators to predict and anticipate. Should we plan for a single future? Many futures? What factors are relevant? What may change over time?

In 2011, the International Joint Commission was in the middle of a five-year planning cycle for the International Upper Great Lakes Study (IUGLS), a team managing a large, diverse group of stakeholders sharing one of the world’s largest lakes divided between two countries. These stakeholders were confronted with an impasse: how do we plan for the future of Lake Superior given conflicting, divergent predictions of the future? How do we change uncertainty into confident decisions? In response, a new and untested methodology was proposed as a way to visualize risk. Climate information was considered critical to this process. In most cases, climate information is “downscaled” for decision makers. In this case, climate information was presented through a new methodology known as “decision scaling.”

To most aquatic ecologists, engineers seem deeply powerful. Their discipline communicates easily with decision makers and translates into the language of economics and finance, while their influence over water infrastructure design and operations is profound. Ecologists have often felt as if they were on the outside of an important conversation, their own voices lost.

Ecosystems have most often been represented in water management decisions by describing the water variables that are believed to be important for particular species or groups of species. Beginning in the 1990s, a more sophisticated approach looked at whole ecosystems by focusing on the “natural flow regime” — managing water infrastructure to mimic the seasonal variation in water volume and water quality in order to maintain a broad set of ecological variables through “environmental flows.”

However, the recent shift by engineers to include climate and non-stationary management goals — described in Part 1 — presented a new potential means of connecting ecology and engineering, since ecologists were also reconsidering how important shifts in climate may be altering their natural resource management goals. The rise of decision scaling as a new tool for holistically exploring risk could be the link — the bridge across the waters. The stakeholder-driven aspects of decision scaling seemed to be an effective means for balancing multiple concerns and risks, and if the “breaking points” of ecosystems could be defined, perhaps a shared vision of sustainable water management could be achieved as well.

Through the National Socio-Environmental Synthesis Center (SESYNC.org), LeRoy Poff and John Matthews, both aquatic ecologists, decided to explore how to bring together engineers and ecologists who were jointly concerned about reconciliation and open to using decision scaling as a mechanism to find a joint means for practical and sustainable water management. The largest obstacle seemed to be that ecological complexity was hard to place within the essentializing language of engineering. Overcoming that obstacle would be the goal for the first of four workshops: what would should we use as simple, climate-relevant ecological “performance markers” of resilience within a decision scaling framework?