Co-Production with Water Managers to Improve Applicability and Adoption of an Emerging Decision Support Tool

Abstract:

In water management, changes in the frequency and intensity of extreme events (especially droughts and floods) are likely to require modifications of management strategies and, in some cases, new infrastructure. In light of these and other challenges, there is a serious need to improve the applicability of water resources research to real-world decision making. Multiobjective Evolutionary Algorithms (MOEAs) have shown promise in being able to generate and evaluate new planning alternatives under these conditions, but there has not yet been work that seeks to use a co-production framework to extensively test their efficacy. A group of engineering, social science, and climate researchers collaborated with practitioners from two municipal water providers to design this interdisciplinary study. The focus of the research is to co-produce and test a MOEA-based decision tool directly with a group of water managers from six water utilities from Colorado’s Front Range: Cities of Boulder, Aurora, and Fort Collins, Denver Water, Colorado Springs Utilities, and Northern Water. As part of the co-production of the MOEA testbed, managers provided critical insight on problem formulations, hydrology and demand scenarios, and a hypothetical water supply network using a workshop format. A problem formulation consists of objectives that measure performance, management options that decision makers can change, and constraints that represent acceptable limits for performance. The hypothetical network is based on feedback from our participating utilities and is representative of the water management context along the Front Range of Colorado. This presentation will focus on results from an initial workshop with water managers and provide insights on how our approach can help bridge the gap between decision support research and real-world water management. Our study seeks to inform a set of best practices for incorporating a MOEA-based decision tool in the decision making processes of utilities, to support water supply operations and systems that can adequately respond to a range of uncertain futures. Additionally, this project aims to demonstrate to water resources researchers and practitioners the efficacy of an interdisciplinary co-production framework for improving uptake of innovative decision support tools.