Improving the relevance and impact of decision support research: A co-production framework and water management case study

In light of the unpredictable effects of climate change and population shifts, responsible resource management will require new types of information and strategies going forward. For water utilities, this means that water supply infrastructure systems must be expanded and/or managed for changes in overall supply and increased extremes. Utilities have begun seeking innovative tools and methods to support planning and decision making, but there are limited channels through which they can gain exposure to emerging tools from the research world, and for researchers to uptake important real-world planning and decision context. A transdisciplinary team of engineers, social and climate scientists, and water managers designed this study to develop and apply a co-production framework which explores the potential of an emerging decision support tool to enhance flexibility and adaptability in water utility planning. It also demonstrates how to improve the link between research and practice in the water sector. In this study we apply the co-production framework to the use of Multiobjective Evolutionary Algorithms (MOEAs). MOEAs have shown promise in being able to generate and evaluate new planning alternatives but they have had little testing or application in water utilities. Anchored by two workshops, this study (1) elicited input from water managers from six water suppliers on the Front Range of Colorado, USA, to create a testbed MOEA application, and (2) evaluated the managers' responses to multiobjective optimization results. The testbed consists of a Front Range-relevant hypothetical water supply model, the Borg MOEA, hydrology and demand scenarios, and a set of planning decisions and performance objectives that drive the link between the algorithm and the model. In this presentation we describe researcher-manager interactions at the initial workshop that served to establish relationships and provide in-depth information to researchers about regional water management context. We also describe the development of, and experiences from, the second workshop which included activities for water managers to interact directly with MOEA testbed results. Finally, we evaluate the co-production framework itself and the potential for the feedback from managers to shape future development of decision support tools.