Keywords
Deep Uncertainty, Robust Decision Making, Multi-Objective Optimization, Water Resources, Water Resources Planning and Management
Start Date
15-9-2020 4:20 PM
End Date
15-9-2020 4:40 PM
Abstract
The Colorado River spans the United 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. 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 planning in multi-reservoir systems. A Multi-Objective Evolutionary Algorithm (MOEA) is coupled with the Colorado River Simulation System (CRSS) model, built in RiverWare, to generate thousands of new operating policies for Lake Mead. The MOEA-generated policies are then re-simulated across many future water supply and water demand scenarios to test each policy’s performance across a wide range of plausible future conditions. Multiple robust operating policies were identified 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 operating policy could be formulated to be more robust to a wide range of future hydrologic and water demand conditions. The presentation will use the Colorado River Basin test case to demonstrate the powerful coupling of MOEAs and RiverWare, appropriate for planning in many worldwide complex river basins. Ongoing work includes incorporating Lake Powell into the framework.
Using Multiobjective Evolutionary Algorithms and RiverWare for Generating Robust Lake Mead Operating Policies
The Colorado River spans the United 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. 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 planning in multi-reservoir systems. A Multi-Objective Evolutionary Algorithm (MOEA) is coupled with the Colorado River Simulation System (CRSS) model, built in RiverWare, to generate thousands of new operating policies for Lake Mead. The MOEA-generated policies are then re-simulated across many future water supply and water demand scenarios to test each policy’s performance across a wide range of plausible future conditions. Multiple robust operating policies were identified 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 operating policy could be formulated to be more robust to a wide range of future hydrologic and water demand conditions. The presentation will use the Colorado River Basin test case to demonstrate the powerful coupling of MOEAs and RiverWare, appropriate for planning in many worldwide complex river basins. Ongoing work includes incorporating Lake Powell into the framework.
Stream and Session
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