{"title":"Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability","authors":"Dan Lu, Tiantian Yang, Xiaofeng Liu","doi":"10.3389/frwa.2023.1215966","DOIUrl":null,"url":null,"abstract":"COPYRIGHT © 2023 Lu, Yang and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Water","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frwa.2023.1215966","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
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社论:数据驱动的机器学习提高水文和水力可预测性
版权所有©2023鲁、杨和刘。这是一篇根据知识共享署名许可（CC BY）条款发布的开放获取文章。根据公认的学术惯例，允许在其他论坛上使用、分发或复制，前提是原作者和版权所有人得到认可，并引用本期刊上的原始出版物。不允许使用、分发或复制不符合这些条款的内容。社论：数据驱动的机器学习用于提高水文和水力可预测性
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