Elias C. Massoud, Forrest Hoffman, Zheng Shi, Jinyun Tang, Elie Alhajjar, Mallory Barnes, R. Braghiere, Zoe Cardon, Nathan Collier, Octavia Crompton, P. Dennedy‐Frank, S. Gautam, Miquel A Gonzalez-Meler, Julia K. Green, Charles Koven, Paul Levine, Natasha MacBean, J. Mao, Richard Tran Mills, U. Mishra, M. Mudunuru, Alexandre A. Renchon, Sarah Scott, E. Siirila‐Woodburn, Matthias Sprenger, C. Tague, Yaoping Wang, Chonggang Xu, C. Zarakas
{"title":"Perspectives on Artificial Intelligence for Predictions in Ecohydrology","authors":"Elias C. Massoud, Forrest Hoffman, Zheng Shi, Jinyun Tang, Elie Alhajjar, Mallory Barnes, R. Braghiere, Zoe Cardon, Nathan Collier, Octavia Crompton, P. Dennedy‐Frank, S. Gautam, Miquel A Gonzalez-Meler, Julia K. Green, Charles Koven, Paul Levine, Natasha MacBean, J. Mao, Richard Tran Mills, U. Mishra, M. Mudunuru, Alexandre A. Renchon, Sarah Scott, E. Siirila‐Woodburn, Matthias Sprenger, C. Tague, Yaoping Wang, Chonggang Xu, C. Zarakas","doi":"10.1175/aies-d-23-0005.1","DOIUrl":null,"url":null,"abstract":"\nIn November 2021, the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop was held, which involved hundreds of researchers from dozens of institutions (Hickmon et al., 2022). There were 17 sessions held at the workshop, including one on Ecohydrology. The Ecohydrology session included various break-out rooms that addressed specific topics, including: 1) Soils & Belowground, 2) Watersheds, 3) Hydrology, 4) Ecophysiology & Plant Hydraulics, 5) Ecology, 6) Extremes, Disturbance & Fire, and Land Use & Land Cover Change, and 7) Uncertainty Quantification Methods & Techniques. In this paper, we investigate and report on the potential application of Artificial Intelligence and Machine Learning (AI/ML) in Ecohydrology, highlight outcomes of the Ecohydrology session at the AI4ESP workshop, and provide visionary perspectives for future research in this area.","PeriodicalId":94369,"journal":{"name":"Artificial intelligence for the earth systems","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial intelligence for the earth systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/aies-d-23-0005.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In November 2021, the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop was held, which involved hundreds of researchers from dozens of institutions (Hickmon et al., 2022). There were 17 sessions held at the workshop, including one on Ecohydrology. The Ecohydrology session included various break-out rooms that addressed specific topics, including: 1) Soils & Belowground, 2) Watersheds, 3) Hydrology, 4) Ecophysiology & Plant Hydraulics, 5) Ecology, 6) Extremes, Disturbance & Fire, and Land Use & Land Cover Change, and 7) Uncertainty Quantification Methods & Techniques. In this paper, we investigate and report on the potential application of Artificial Intelligence and Machine Learning (AI/ML) in Ecohydrology, highlight outcomes of the Ecohydrology session at the AI4ESP workshop, and provide visionary perspectives for future research in this area.
2021年11月，举办了地球系统可预测性人工智能(AI4ESP)研讨会，来自数十个机构的数百名研究人员参加了该研讨会(Hickmon et al.， 2022)。研讨会共举行了17场会议，其中一场是关于生态水文学的。生态水文学会议包括不同的分组会议，讨论具体的主题，包括:1)土壤与地下，2)流域，3)水文学，4)生态生理学与植物水力学，5)生态学，6)极端，扰动与火灾，土地利用与土地覆盖变化，以及7)不确定性量化方法与技术。在本文中，我们调查和报告了人工智能和机器学习(AI/ML)在生态水文学中的潜在应用，重点介绍了AI4ESP研讨会上生态水文学会议的成果，并为该领域的未来研究提供了有远见的展望。
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