Jiajia Huang , Wenyan Wu , Holger R. Maier , Justin Hughes , Quan J. Wang , Yuan Cao
{"title":"深度不确定性下油藏长期管理的综合框架","authors":"Jiajia Huang , Wenyan Wu , Holger R. Maier , Justin Hughes , Quan J. Wang , Yuan Cao","doi":"10.1016/j.envsoft.2025.106740","DOIUrl":null,"url":null,"abstract":"<div><div>Reservoir systems play a crucial role in providing essential services such as water supply, flood protection, and energy generation. However, reservoir management is highly complex due to (i) multiple conflicting management goals, (ii) long-term changes in water availability and demand over the long life span of these systems, and (iii) deep uncertainty. While some of these challenges have been addressed in previous studies, there is a lack of a comprehensive framework that can maximize the co-benefits of addressing these challenges in an integrated manner. Such an optimization framework has been developed in this study. By incorporating deep uncertainty, the causal relationships between decisions, system performance, and robustness can be explored. By adapting both operation policy and infrastructure upgrade decisions to long-term changes, infrastructure investments can be reduced without compromising system performance. By explicitly accounting for multiple conflicting objectives, the framework also provides a platform for negotiation during the decision-making process.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"195 ","pages":"Article 106740"},"PeriodicalIF":4.6000,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive framework for long-term reservoir management under deep uncertainty\",\"authors\":\"Jiajia Huang , Wenyan Wu , Holger R. Maier , Justin Hughes , Quan J. Wang , Yuan Cao\",\"doi\":\"10.1016/j.envsoft.2025.106740\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Reservoir systems play a crucial role in providing essential services such as water supply, flood protection, and energy generation. However, reservoir management is highly complex due to (i) multiple conflicting management goals, (ii) long-term changes in water availability and demand over the long life span of these systems, and (iii) deep uncertainty. While some of these challenges have been addressed in previous studies, there is a lack of a comprehensive framework that can maximize the co-benefits of addressing these challenges in an integrated manner. Such an optimization framework has been developed in this study. By incorporating deep uncertainty, the causal relationships between decisions, system performance, and robustness can be explored. By adapting both operation policy and infrastructure upgrade decisions to long-term changes, infrastructure investments can be reduced without compromising system performance. By explicitly accounting for multiple conflicting objectives, the framework also provides a platform for negotiation during the decision-making process.</div></div>\",\"PeriodicalId\":310,\"journal\":{\"name\":\"Environmental Modelling & Software\",\"volume\":\"195 \",\"pages\":\"Article 106740\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Modelling & Software\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1364815225004244\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modelling & Software","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364815225004244","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Comprehensive framework for long-term reservoir management under deep uncertainty
Reservoir systems play a crucial role in providing essential services such as water supply, flood protection, and energy generation. However, reservoir management is highly complex due to (i) multiple conflicting management goals, (ii) long-term changes in water availability and demand over the long life span of these systems, and (iii) deep uncertainty. While some of these challenges have been addressed in previous studies, there is a lack of a comprehensive framework that can maximize the co-benefits of addressing these challenges in an integrated manner. Such an optimization framework has been developed in this study. By incorporating deep uncertainty, the causal relationships between decisions, system performance, and robustness can be explored. By adapting both operation policy and infrastructure upgrade decisions to long-term changes, infrastructure investments can be reduced without compromising system performance. By explicitly accounting for multiple conflicting objectives, the framework also provides a platform for negotiation during the decision-making process.
期刊介绍:
Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.