Institutional Boundaries and Common-Pool Resource Management: A Comparative Analysis of Water Management Agencies in California

Abstract

"This article examines one way that institutions governing water resources can affect the management of scarce water supplies. Specifically, it analyzes the relationship between the scale of water management institutions and the use of a promising water management method, known as conjunctive water management. The scale of institutional boundaries, or jurisdictions, has been considered particularly important in shaping water resource management. For instance, recent calls for 'watershed level management' have argued that small or fragmented institutions governing water resources lack both the ability for comprehensive resource planning and the ability to address problems that cross state and local boundaries (Gottlieb and FitzSimmons 1991; Dzurik 1990; Kenney 1997). While such studies acknowledge the importance of institutional boundaries for managing water resources, the relative effectiveness of different types of institutional boundaries in facilitating improved watershed use remains open to empirical analysis. This article begins by describing conjunctive water management, as an example of a water management method that offers improved resource efficiency and sustainability. The first section also discusses why the state of California provides an appropriate study setting for analyzing the relationship between institutions and water management decisions. This article then examines two streams of literature that offer propositions about the effects of institutional boundaries on water management decisions; they are common-pool resource management theory and the literature on public service industries. It considers the implications from these two bodies of literature for understanding how institutional boundaries affect water management decisions. The final section of this article empirically tests the assumptions derived from the literature review using data from water management agencies in California. The data are evaluated using both a logit regression model and a Boolean analysis, also known as Qualitative Comparative Analysis (QCA)."