从多种未来到一种未来:针对资源节约型深度气候不确定性分析的气候知情规划情景分析

IF 4.8 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Baptiste François, Alexis Dufour, Thi Nhu Khanh Nguyen, Alexa Bruce, Dong Kwan Park, Casey Brown
{"title":"从多种未来到一种未来:针对资源节约型深度气候不确定性分析的气候知情规划情景分析","authors":"Baptiste François, Alexis Dufour, Thi Nhu Khanh Nguyen, Alexa Bruce, Dong Kwan Park, Casey Brown","doi":"10.1007/s10584-024-03772-9","DOIUrl":null,"url":null,"abstract":"<p>Water resources managers face decisions related to building new infrastructure to increase water system resilience to climate and demand changes. To inform this adaptation planning process, current decision-making methods commonly use scenario approaches to estimate the benefit of adaptation options. While effective, these new analyses require communication of complicated findings to often nontechnical audiences. This paper introduces a pragmatic approach that uses the results from a bottom-up assessment of vulnerability of the water system with future climate projection-based probabilities of climate change to select a single planning scenario that encapsulates the decision-makers’ chosen level of robustness for their system. Contrary to typical implementation of option analysis under deep climate uncertainty, the proposed pragmatic approach does not require the analyst to evaluate each portfolio of adaptation options against all possible states of the world, significantly reducing the required computational costs and communication challenges. It also aligns with the planning scenario approach used in practice by water utilities. The modeling framework is illustrated for the regional water system operated by the San Francisco Public Utilities Commission (California, United States) for which changes in average temperature, precipitation and urban demand are considered.</p>","PeriodicalId":10372,"journal":{"name":"Climatic Change","volume":"13 1","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"From many futures to one: climate-informed planning scenario analysis for resource-efficient deep climate uncertainty analysis\",\"authors\":\"Baptiste François, Alexis Dufour, Thi Nhu Khanh Nguyen, Alexa Bruce, Dong Kwan Park, Casey Brown\",\"doi\":\"10.1007/s10584-024-03772-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Water resources managers face decisions related to building new infrastructure to increase water system resilience to climate and demand changes. To inform this adaptation planning process, current decision-making methods commonly use scenario approaches to estimate the benefit of adaptation options. While effective, these new analyses require communication of complicated findings to often nontechnical audiences. This paper introduces a pragmatic approach that uses the results from a bottom-up assessment of vulnerability of the water system with future climate projection-based probabilities of climate change to select a single planning scenario that encapsulates the decision-makers’ chosen level of robustness for their system. Contrary to typical implementation of option analysis under deep climate uncertainty, the proposed pragmatic approach does not require the analyst to evaluate each portfolio of adaptation options against all possible states of the world, significantly reducing the required computational costs and communication challenges. It also aligns with the planning scenario approach used in practice by water utilities. The modeling framework is illustrated for the regional water system operated by the San Francisco Public Utilities Commission (California, United States) for which changes in average temperature, precipitation and urban demand are considered.</p>\",\"PeriodicalId\":10372,\"journal\":{\"name\":\"Climatic Change\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Climatic Change\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1007/s10584-024-03772-9\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Climatic Change","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s10584-024-03772-9","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

水资源管理者面临着与建设新基础设施有关的决策,以提高水系统对气候和需求变化的适应能力。为了给这一适应规划过程提供信息,当前的决策方法通常采用情景模拟法来估算适应方案的效益。这些新的分析方法虽然有效,但需要将复杂的分析结果传达给非技术受众。本文介绍了一种务实的方法,即利用自下而上的水系统脆弱性评估结果和基于未来气候预测的气候变化概率,选择一个单一的规划情景,其中包含决策者为其系统选择的稳健性水平。与典型的深度气候不确定性下的选项分析不同,所提出的务实方法不要求分析师针对世界上所有可能的状态来评估每个适应选项组合,从而大大降低了所需的计算成本和沟通挑战。该方法还与水务公司在实践中使用的规划情景方法相一致。建模框架以旧金山公用事业委员会(美国加利福尼亚州)运营的区域供水系统为例进行说明,其中考虑了平均气温、降水量和城市需求的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

From many futures to one: climate-informed planning scenario analysis for resource-efficient deep climate uncertainty analysis

From many futures to one: climate-informed planning scenario analysis for resource-efficient deep climate uncertainty analysis

Water resources managers face decisions related to building new infrastructure to increase water system resilience to climate and demand changes. To inform this adaptation planning process, current decision-making methods commonly use scenario approaches to estimate the benefit of adaptation options. While effective, these new analyses require communication of complicated findings to often nontechnical audiences. This paper introduces a pragmatic approach that uses the results from a bottom-up assessment of vulnerability of the water system with future climate projection-based probabilities of climate change to select a single planning scenario that encapsulates the decision-makers’ chosen level of robustness for their system. Contrary to typical implementation of option analysis under deep climate uncertainty, the proposed pragmatic approach does not require the analyst to evaluate each portfolio of adaptation options against all possible states of the world, significantly reducing the required computational costs and communication challenges. It also aligns with the planning scenario approach used in practice by water utilities. The modeling framework is illustrated for the regional water system operated by the San Francisco Public Utilities Commission (California, United States) for which changes in average temperature, precipitation and urban demand are considered.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Climatic Change
Climatic Change 环境科学-环境科学
CiteScore
10.20
自引率
4.20%
发文量
180
审稿时长
7.5 months
期刊介绍: Climatic Change is dedicated to the totality of the problem of climatic variability and change - its descriptions, causes, implications and interactions among these. The purpose of the journal is to provide a means of exchange among those working in different disciplines on problems related to climatic variations. This means that authors have an opportunity to communicate the essence of their studies to people in other climate-related disciplines and to interested non-disciplinarians, as well as to report on research in which the originality is in the combinations of (not necessarily original) work from several disciplines. The journal also includes vigorous editorial and book review sections.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信