ERC特刊征稿|AI for Model and Data Integration in Hydrology

23 10月 2023 gabriels



  • 史海匀,南方科技大学
  • 郑一,南方科技大学
  • Chaopeng Shen,美国宾夕法尼亚大学
  • 王大刚,中山大学
  • 姜丽光,南方科技大学
  • 刘苏宁,南方科技大学



The potential of Artificial Intelligence (AI) in analysing, modelling, and forecasting complex hydrological processes has been clearly demonstrated in recent years, as the number of applications grow substantially each year. Moreover, there is an increasing number of large datasets, especially EO data and crowdsourced data, for researchers to address existing issues either at improved accuracy or enlarged spatial coverage, or new problems that were inaccessible before. However, such study introduces its own challenges. There arises a critical need to bridge the gap between AI researchers and hydrologists.
This focus issue aims to collect the latest advancements in methodologies and applications of AI in the field of for hydrology, especially for the integration of model and data. Potential topics include, but are not limited to, the following:

  • Recent AI advances contributed to the field of hydrology
  • Promising use cases of AI in hydrological modelling and data integration
  • The next generation of applications in hydrology

The Guest Editors particularly welcome contributions that may address the supplementary and complementary role of process-based models and machine learning with respect to the others and also their integration.

The Guest Editors also welcome open call proposals from the community. If you believe you have a suitable research article or topical review in preparation you can send your pre-submission query either to the journal publishing team ( or to one of the Guest Editors listed above.





作者可登入期刊主页进行在线投稿,选择“文章类型”(Letter/Paper/Topical Review),并在“选择特刊”的下拉框中选择“Focus on Artificial Intelligence for Model and Data Integration in Hydrology”。



Environmental Research Communications

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