气候变化领域集成服务门户(CCPortal): Learning and flexibility for water supply infrastructure planning under groundwater resource uncertainty

CCPortal

DOI	10.1088/1748-9326/ab4664
	Learning and flexibility for water supply infrastructure planning under groundwater resource uncertainty
	Fletcher S.; Strzepek K.; Alsaati A.; De Weck O.
发表日期	2019
ISSN	17489318
卷号	14 期号:11
英文摘要	Water supply infrastructure planning in groundwater-dependent regions is often challenged by uncertainty in future groundwater resource availability. Many major aquifer systems face long-term water table decline due to unsustainable withdrawals. However, many regions, especially those in the developing world, have a scarcity of groundwater data. This creates large uncertainties in groundwater resource predictions and decisions about whether to develop alternative supply sources. Developing infrastructure too soon can lead to unnecessary and expensive irreversible investments, but waiting too long can threaten water supply reliability. This study develops an adaptive infrastructure planning framework that applies Bayesian learning on groundwater observations to assess opportunities to learn about groundwater availability in the future and adapt infrastructure plans. This approach allows planners in data scarce regions to assess under what conditions a flexible infrastructure planning approach, in which initial plans are made but infrastructure development is deferred, can mitigate the risk of overbuilding infrastructure while maintaining water supply reliability in the face of uncertainty. This framework connects engineering options analysis from infrastructure planning to groundwater resources modeling. We demonstrate a proof-of-concept on a desalination planning case for the city of Riyadh, Saudi Arabia, where poor characterization of a fossil aquifer creates uncertainty in how long current groundwater resources can reliably supply demand. We find that a flexible planning approach reduces the risk of over-building infrastructure compared to a traditional static planning approach by 40% with minimal reliability risk (<1%). This striking result may be explained by the slow-evolving nature of groundwater decline, which provides time for planners to react, in contrast to more sudden risks such as flooding where tradeoffs between cost and reliability risk are heightened. This Bayesian approach shows promise for many civil infrastructure domains by providing a method to quantify learning in environmental modeling and assess the effectiveness of adaptive planning. © 2019 The Author(s). Published by IOP Publishing Ltd.
英文关键词	adaptive planning, infrastructure; decision support; groundwater; uncertainty
语种	英语
scopus关键词	Aquifers; Bayesian networks; Decision support systems; Desalination; Developing countries; Groundwater; Investments; Planning; Reliability; Risk assessment; Uncertainty analysis; Water supply; Adaptive infrastructures; Adaptive planning; Decision supports; Infrastructure development; Infrastructure planning; Irreversible investments; uncertainty; Water supply infrastructures; Groundwater resources; adaptive management; decision support system; environmental modeling; flooding; groundwater abstraction; groundwater resource; infrastructure planning; learning; uncertainty analysis; water management; water supply; water table; Riyadh [Saudi Arabia]; Saudi Arabia
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154760
作者单位	Civil and Environmental Engineering, Massachusetts Institute of Technology, United States; Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, United States; Hydrology Water Resources and Environmental Fluid Mechanics, University of Colorado Boulder, United States; Center for Complex Engineering Systems, King Abdulaziz City for Science and Technology, Saudi Arabia; Institute for Data Systems and Society, Massachusetts Institute of Technology, United States
推荐引用方式 GB/T 7714	Fletcher S.,Strzepek K.,Alsaati A.,et al. Learning and flexibility for water supply infrastructure planning under groundwater resource uncertainty[J],2019,14(11).
APA	Fletcher S.,Strzepek K.,Alsaati A.,&De Weck O..(2019).Learning and flexibility for water supply infrastructure planning under groundwater resource uncertainty.Environmental Research Letters,14(11).
MLA	Fletcher S.,et al."Learning and flexibility for water supply infrastructure planning under groundwater resource uncertainty".Environmental Research Letters 14.11(2019).