Date of Award

Spring 1-1-2018

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Joseph Kasprzyk

Second Advisor

Edith Zagona

Third Advisor

James Prairie

Abstract

The Colorado River spans seven US states and Mexico and is an important cultural, economic, and natural resource for 35 - 40 million people. Its complex operating policy is based on the “Law of the River,” which has evolved since the Colorado River Compact in 1922. Operational guidelines were negotiated in 2007 to address shortage reductions and coordinated operations of Lakes Powell and Mead. These interim guidelines – in effect until 2026 - were ultimately agreed on after manually exploring hundreds of alternatives. The Colorado River Basin’s projected water delivery reliability has continued to degrade since 2007, primarily due to a persistent drought causing a lower supply and secondarily from a growing demand. The magnitude of the future supply-demand imbalance is challenging to predict since the most likely realizations of future water demand and hydrology are unknown, nor are the uncertainties quantifiable. Hence, these future conditions can be described as deeply uncertain. Negotiations for the new 2026 guidelines will need to consider deep uncertainty when searching for and evaluating operational alternatives.

This research explores innovative planning approaches that are appropriate for conditions of deep uncertainty and then demonstrates an application of a method called Many Objective Robust Decision Making (MORDM). This MORDM application couples a multi-objective evolutionary algorithm (MOEA) with the Colorado River Simulation System (CRSS) model to generate and evaluate thousands of new operating policies for Lake Mead. The MOEA-generated policies are then re-simulated across multiple future water supply and water demand scenarios testing each policy’s performance across a wide range of plausible future uncertainty. This research identified multiple robust operating policies through applying a satisficing analysis to the set of MOEA-generated policies. The operational similarities between the identified robust policies may shed light on how Lake Mead's operation could be formulated to be more robust to a wide range of future hydrologic and water demand conditions. This research provides a realistic application of an MOEA to one of the largest most complex river basins that has been optimized using an MOEA to date.

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