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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.
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This content will become publicly available on August 1, 2026
Understanding the Impact of Institutions on Climate‐Adaptive Policy Designs: A Study of Collective Action Inference in Urban Water Systems
Feedback is ubiquitous in complex systems and critical to the process of designing public policies to solve problems such as climate adaptation. However, well‐known cognitive and institutional constraints can impact information feedback processes, limiting a system's ability to incorporate feedback into policy designs. This study analyzes the role that institutions play in regulating feedback in coupled infrastructure systems (CIS) to support the development of climate‐adaptive policies. Focusing on urban water systems, we ask:how do multilevel institutions governing information processing influence urban water systems' climate‐adaptive policy responses?Using the CIS framework, we develop a theoretical argument for policy design based on the cognitive model of active inference. Drawing on hydrological, administrative, media, interview, and institutional data, we trace two urban water systems' policy design processes over a decade. We find that successive waves of state‐level changes to water planning rules prompted more “exploratory” information processing during the study period. Moreover, an urban water utility's ownership type (public vs. investor‐owned) influenced how expected climate impacts were incorporated into policy designs. These findings provide insight into how institutional arrangements shape policy designs and suggest ways such arrangements may be altered to enable adaptive responses in the face of environmental uncertainty.
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- Award ID(s):
- 1923880
- PAR ID:
- 10642914
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Policy Studies Journal
- Volume:
- 53
- Issue:
- 3
- ISSN:
- 0190-292X
- Page Range / eLocation ID:
- 637 to 653
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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