Influence of Subseasonal-to-Annual Water Supply Forecasts on Many-Objective Water System Robustness under Long-Term Change
Publication: Journal of Water Resources Planning and Management
Volume 150, Issue 5
Abstract
The sensitivity of forecast-informed reservoir operating policies to forecast attributes (lead-time and skill) in many-objective water systems has been well-established. However, the viability of forecast-informed operations as a climate change adaptation strategy remains underexplored, especially in many-objective systems with complex trade-offs across interests. Little is known about the relationships between forecast attribute and policy robustness under deep uncertainty in future conditions and the relationships between forecast-informed performance and future hydrologic state. This study explores the sensitivity of forecast-informed policy robustness to forecast lead-time and skill in the outflow management plan of the Lake Ontario basin. We create water supply forecasts at four different subseasonal-to-annual lead-times and two levels of skill and further employ a many-objective evolutionary algorithm to discover policies tailored for each forecast case, historical supply conditions, and six objectives. We also leverage a partnership with decision-makers to identify a subset of candidate policies, which are reevaluated under a large set of plausible hydrologic conditions that reflect stationary and nonstationary climates. Scenario discovery techniques are used to map attributes of future hydrology to forecast-informed policy performance. Results show policy robustness is directly related to forecast lead-time, where policies conditioned on 12-month forecasts were more robust under future hydrology. Policies tailored for noisier long-lead forecasts were more robust under a wide range of plausible futures compared with policies trained to perfect forecasts, which highlights the potential to overfit control policies to historical information, even for a forecast-informed policy with perfect foresight. The relationship between performance and the hydrologic regime is dependent on the complexity of the interactions between control decisions and objectives. A threshold of objective performance as a function of supply conditions can support adaptive management of the system. However, more complex interactions make it difficult to identify simple hydrologic indicators that can serve as triggers for dynamic management.
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Data Availability Statement
All models and code generated or used during the study are available in an online repository at github.com/ksemmendinger/Plan-2014-Python.
Acknowledgments
We acknowledge the Great Lakes–St. Lawrence River Adaptive Management Committee for providing feedback on this work to align study outcomes with decision-making needs. This work was supported by the U.S. Geological Survey Northeast Climate Adaptation Science Center, which is managed by the USGS National Climate Adaptation Science Center, under Grant/Cooperative Agreement No. G21AC10601-00, and also by the National Science Foundation under Grant No. CBET-2144332 and through the NSF Graduate Research Fellowship under Grant No. DGE-1650441. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the Northeast Climate Adaptation Science Center or the USGS.
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Journal of Water Resources Planning and Management
Volume 150 • Issue 5 • May 2024
Copyright
© 2024 American Society of Civil Engineers.
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Received: Mar 31, 2023
Accepted: Dec 3, 2023
Published online: Feb 23, 2024
Published in print: May 1, 2024
Discussion open until: Jul 23, 2024
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