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Abstract Uncertainty arising from climate change poses a central challenge to the long‐term performance of many engineered water systems. Water supply infrastructure projects can leverage different types of flexibility, in planning, design, or operations, to adapt infrastructure systems in response to climate change over time. Both flexible planning and design enable future capacity expansion if‐and‐when needed, with flexible design proactively incorporating physical design changes that enable retrofits. All three forms of flexibility have not previously been analyzed together to explicitly assess their relative value in mitigating cost and water supply reliability risk. In this paper, we propose a new framework to evaluate combinations of flexible planning, design, and operations. We develop a nested stochastic dynamic optimization approach that jointly optimizes dam development and operating policies under dynamic climate uncertainty. We demonstrate this approach on a reservoir project near Mombasa, Kenya. Our results find that flexible operations have the greatest potential to reduce costs. Flexible design and flexible planning can amplify the value of flexible operations under higher discounting scenarios and when initial infrastructure capacities are undersized. This approach provides insight on the climate change and techno‐economic conditions under which flexible planning, design, and operations can be best leveraged individually or in combination to reduce climate change uncertainty risks in water supply infrastructure projects.
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Quantifying the Value of Learning for Flexible Water Infrastructure Planning
Uncertainty in future climate change challenges water infrastructure development decisions. Flexible infrastructure development, in which infrastructure is proactively designed to be changed in the future, can reduce the risk of overbuilding unnecessary infrastructure while maintaining reliable water supply. Flexible strategies assume that water planners will learn over time, updating future climate projections and using that new information to change plans. Previous work has developed methods to incorporate learning using climate observations into flexible planning but has not quantified the impact of different amounts of learning on the effectiveness of flexible planning. In this work, we develop a framework to assess how differences in the amount of learning about climate uncertainty affect the value of flexible water infrastructure planning. In the first part of our framework, we design climate scenarios with different amounts of learning using an exploratory Bayesian modeling approach. Then, we quantify the impacts of learning on flexibility using simulated costs and infrastructure decisions. We demonstrate this framework on a stylized case study of the Mwache Dam near Mombasa, Kenya. Flexible planning is more effective in avoiding over‐ or underbuilding under high‐learning scenarios, especially in avoiding overbuilding in wet climates. This framework provides insight on the climate conditions and learning scenarios that make flexible infrastructure most valuable.
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- Award ID(s):
- 2207036
- PAR ID:
- 10501226
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 59
- Issue:
- 6
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2022WR034412
