Download eBook for Free

FormatFile SizeNotes
PDF file 1.8 MB

Use Adobe Acrobat Reader version 10 or higher for the best experience.

Ensuring sufficient, high-quality water supplies for California over the next several decades will be a great challenge for water resource managers. Choosing an appropriate management response using standard methods will be extremely difficult and contentious because the scope and magnitude of these impacts are highly uncertain and stakeholders have diverse views about desirable outcomes. This dissertation first documents the development and use of a model to generate quantitative scenarios of future water demand in California. It next describes a new analytic method for decisionmaking under deep uncertainty called Robust Decision Making (RDM). To demonstrate how RDM can be a valuable analytic tool for California long-term water planning, the dissertation applies the methodology to a stylized representation of the water supply and demand management challenge facing Southern California.

Research conducted by

Financial support for this dissertation was provided by the Rothenberg Family and the National Science Foundation.

This report is part of the RAND Corporation dissertation series. Pardee RAND dissertations are produced by graduate fellows of the Pardee RAND Graduate School, the world's leading producer of Ph.D.'s in policy analysis. The dissertations are supervised, reviewed, and approved by a Pardee RAND faculty committee overseeing each dissertation.

Permission is given to duplicate this electronic document for personal use only, as long as it is unaltered and complete. Copies may not be duplicated for commercial purposes. Unauthorized posting of RAND PDFs to a non-RAND Web site is prohibited. RAND PDFs are protected under copyright law. For information on reprint and linking permissions, please visit the RAND Permissions page.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.