CREST模型家族的十年回顾:发展、应用和展望

IF 3.1 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Zhi Li , Xianwu Xue , Robert Clark , Humberto Vergara , Jonathan Gourley , Guoqiang Tang , Xinyi Shen , Guangyuan Kan , Ke Zhang , Jiahu Wang , Mengye Chen , Shang Gao , Jiaqi Zhang , Tiantian Yang , Yixin Wen , Pierre Kirstetter , Yang Hong
{"title":"CREST模型家族的十年回顾:发展、应用和展望","authors":"Zhi Li ,&nbsp;Xianwu Xue ,&nbsp;Robert Clark ,&nbsp;Humberto Vergara ,&nbsp;Jonathan Gourley ,&nbsp;Guoqiang Tang ,&nbsp;Xinyi Shen ,&nbsp;Guangyuan Kan ,&nbsp;Ke Zhang ,&nbsp;Jiahu Wang ,&nbsp;Mengye Chen ,&nbsp;Shang Gao ,&nbsp;Jiaqi Zhang ,&nbsp;Tiantian Yang ,&nbsp;Yixin Wen ,&nbsp;Pierre Kirstetter ,&nbsp;Yang Hong","doi":"10.1016/j.hydroa.2023.100159","DOIUrl":null,"url":null,"abstract":"<div><p>Hydrologic models are a powerful tool to predict water-related natural hazards. Of all hydrologic models, CREST (Coupled Routing and Excess STorage) was developed to facilitate hydrologic sciences and applications across various spatial and temporal scales. The CREST model was the earliest implementation of a quasi-global flood model integrating remote-sensing data and is the first operational deployment of a real-time model in the National Weather Service functioning at flash flood scales across a continent. Since being published in 2011, the CREST model has been evolving to empower flood predictions and to inform water resources management practices. Moreover, the CREST model is convenient to couple with other models/schemes (e.g., weather forecast model, snowmelt model, land surface model, hydrodynamic model, groundwater model, landslide model, vector-based routing) for border practices of investigating water-related natural hazards. To date its 10th anniversary, more than 80 peer-reviewed journal articles that have used the CREST model are curated and reviewed from the aspects of model development, worldwide applications, and outreach to emerging regions. Finally, the future directions for the CREST model family are outlined in the hope of stimulating new research endeavors. A digital collection of CREST model family is archived online at <span>https://crest-family.readthedocs.io/en/latest/</span><svg><path></path></svg>.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":"20 ","pages":"Article 100159"},"PeriodicalIF":3.1000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A decadal review of the CREST model family: Developments, applications, and outlook\",\"authors\":\"Zhi Li ,&nbsp;Xianwu Xue ,&nbsp;Robert Clark ,&nbsp;Humberto Vergara ,&nbsp;Jonathan Gourley ,&nbsp;Guoqiang Tang ,&nbsp;Xinyi Shen ,&nbsp;Guangyuan Kan ,&nbsp;Ke Zhang ,&nbsp;Jiahu Wang ,&nbsp;Mengye Chen ,&nbsp;Shang Gao ,&nbsp;Jiaqi Zhang ,&nbsp;Tiantian Yang ,&nbsp;Yixin Wen ,&nbsp;Pierre Kirstetter ,&nbsp;Yang Hong\",\"doi\":\"10.1016/j.hydroa.2023.100159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Hydrologic models are a powerful tool to predict water-related natural hazards. Of all hydrologic models, CREST (Coupled Routing and Excess STorage) was developed to facilitate hydrologic sciences and applications across various spatial and temporal scales. The CREST model was the earliest implementation of a quasi-global flood model integrating remote-sensing data and is the first operational deployment of a real-time model in the National Weather Service functioning at flash flood scales across a continent. Since being published in 2011, the CREST model has been evolving to empower flood predictions and to inform water resources management practices. Moreover, the CREST model is convenient to couple with other models/schemes (e.g., weather forecast model, snowmelt model, land surface model, hydrodynamic model, groundwater model, landslide model, vector-based routing) for border practices of investigating water-related natural hazards. To date its 10th anniversary, more than 80 peer-reviewed journal articles that have used the CREST model are curated and reviewed from the aspects of model development, worldwide applications, and outreach to emerging regions. Finally, the future directions for the CREST model family are outlined in the hope of stimulating new research endeavors. A digital collection of CREST model family is archived online at <span>https://crest-family.readthedocs.io/en/latest/</span><svg><path></path></svg>.</p></div>\",\"PeriodicalId\":36948,\"journal\":{\"name\":\"Journal of Hydrology X\",\"volume\":\"20 \",\"pages\":\"Article 100159\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydrology X\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2589915523000123\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology X","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589915523000123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

水文模型是预测与水有关的自然灾害的有力工具。在所有水文模型中,CREST(耦合路由和超额存储)的发展促进了水文科学和各种时空尺度的应用。CREST模型是整合遥感数据的准全球洪水模型的最早实现,也是美国国家气象局在整个大陆的山洪暴发规模上首次部署的实时模型。自2011年发布以来,CREST模型一直在不断发展,以增强洪水预测能力,并为水资源管理实践提供信息。此外,CREST模型便于与其他模型/方案(如天气预报模型、融雪模型、地表模型、水动力模型、地下水模型、滑坡模型、矢量路由)耦合,用于调查与水有关的自然灾害的边界实践。到目前为止,已有80多篇同行评议的期刊文章使用了CREST模型,从模型开发、全球应用和向新兴地区的推广等方面进行了整理和审查。最后,概述了CREST模型家族的未来发展方向,希望能激发新的研究努力。CREST模型家族的数字集合在线存档于https://crest-family.readthedocs.io/en/latest/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A decadal review of the CREST model family: Developments, applications, and outlook

Hydrologic models are a powerful tool to predict water-related natural hazards. Of all hydrologic models, CREST (Coupled Routing and Excess STorage) was developed to facilitate hydrologic sciences and applications across various spatial and temporal scales. The CREST model was the earliest implementation of a quasi-global flood model integrating remote-sensing data and is the first operational deployment of a real-time model in the National Weather Service functioning at flash flood scales across a continent. Since being published in 2011, the CREST model has been evolving to empower flood predictions and to inform water resources management practices. Moreover, the CREST model is convenient to couple with other models/schemes (e.g., weather forecast model, snowmelt model, land surface model, hydrodynamic model, groundwater model, landslide model, vector-based routing) for border practices of investigating water-related natural hazards. To date its 10th anniversary, more than 80 peer-reviewed journal articles that have used the CREST model are curated and reviewed from the aspects of model development, worldwide applications, and outreach to emerging regions. Finally, the future directions for the CREST model family are outlined in the hope of stimulating new research endeavors. A digital collection of CREST model family is archived online at https://crest-family.readthedocs.io/en/latest/.

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
Journal of Hydrology X
Journal of Hydrology X Environmental Science-Water Science and Technology
CiteScore
7.00
自引率
2.50%
发文量
20
审稿时长
25 weeks
×
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