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Urban water systems across the United States are facing a variety of challenges to existing supply and demand dynamics. Responding to these challenges and working toward sustainability in these complex socio-environmental systems (SES) requires integrating various types of information – ranging from hydrologic data to political considerations and beyond – into policy and management decisions. However, the design of institutions, i.e. the formal rules in which urban water utilities are embedded, impact the flow of various types of information, especially across diverse actor groups critical to developing and implementing policy. Drawing on a neuroscience-informed Bayesian application of the Robustness of Coupled Infrastructure Systems (CIS) Framework, this study examines the institutional designs of two urban U.S. water systems. It aims to advance our understanding of these systems by: A) theoretically linking cognitive science and its action-oriented predictive processing approach to the institutional configurations that shape collective-action; and B) identifying potential institutional dependencies and voids that may limit the use of formalized climate-related guidance in systems facing increased risks. We utilize process-tracing along with an institutional analysis approach called the Institutional Grammar Tool (IGT) to parse the institutions into their semantic and syntactic components, identifying institutional dependencies, voids, or conflicts which may influence long-range performance of the systems. Our findings have important implications for the (re)design of institutions that better facilitate the flow of information among key policy actors and support policy changes that promote sustainable long-term urban water supply.