Cover: Developing Key Indicators for Adaptive Water Planning

Developing Key Indicators for Adaptive Water Planning

Published in: Journal of Water Resources Planning and Management, Volume 141, Issue 7 (July 2015). doi: 10.1061/(ASCE)WR.1943-5452.0000471

Posted on rand.org Jul 11, 2023

by David G. Groves, Evan Bloom, Robert J. Lempert, Jordan R. Fischbach, Jennifer Nevills, Brandon Goshi

With hard-to-predict changes in future demand, climate, supply options, technological opportunities, and budgetary constraints, water agency plans should be flexible and robust, designed to meet agency goals over a wide range of plausible future conditions. But current state-of-the-art approaches to water planning make it difficult to craft flexible and robust plans to guide resource allocation and facilitate discussions with the agency's constituents and ratepayers. This paper describes an innovative effort by one agency, the Metropolitan Water District of Southern California (termed Metropolitan), to begin to address these challenges. Metropolitan's year 2010 integrated resources plan (IRP) update specifies resource allocations over 25 years and calls for an adaptive management approach to revisit these allocations over time. Using a quantitative decision support approach called robust decision-making (RDM), an enhanced version of Metropolitan's main planning model was run, over many thousands of cases representing different combinations of assumptions about future demand, conditions in the bay/delta, climate conditions, local resource yields, and implementation challenges. Statistical cluster analysis on the resulting database of model runs identifies scenarios that succinctly summarize the types of future conditions in which the IRP core resources strategy does and does not meet its goals. These scenarios inform early warning indicators that can guide the adaptive management component of the IRP. The robust decision methods presented in this paper should prove broadly useful for Metropolitan in addition to other water agencies seeking to develop robust and adaptive plans in the face of uncertain future conditions.

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