Hydrological-Hydrodynamic Simulation Based on Artificial Intelligence
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydraulics and Hydrodynamics".
Deadline for manuscript submissions: 25 September 2024 | Viewed by 230
Special Issue Editors
Interests: hydrology; hydraulics; hydrodynamic; digital water; flood hazard; climate change
Interests: hydroinformatics; hydraulics; urban water systems; flood hazards mitigation and disaster prevention; water uses; NBS; climate change
Interests: smart water grid; water distribution systems; water balance and drought assessment; numerical analysis in river hydraulics and water quality assessment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Numerical modelling and simulation are essential ways of supporting the engineers, managers and decision makers in assessing the characteristics of the water cycle and the human impacts in the past, the present and the future. However, the growing complexity of the competition among water uses and the emerging understanding of the synergy effects within catchments and rivers have underlined the need for more detailed information to comprehend these systems. Nevertheless, dataset sources, even though they are becoming diverse and predominant in our digitalised society, remain largely unexploited within the community. Traditional physical-based hydrological–hydrodynamic modelling approaches have difficulties in transitioning toward an efficient integration in the big data era Therefore, this Special Issue aims to curate a comprehensive and interdisciplinary collection of innovations integrating big data and deep learning in hydrological and hydrodynamic processes’ simulation, introducing novel models, algorithms and frameworks that harness advanced artificial intelligence to refine the accuracy, efficiency and reliability of real-time assessment, representation and prediction.
We welcome submissions from researchers involved in experimental, theoretical, and computational aspects of high-performance hydrological–hydrodynamic modelling with artificial intelligence techniques in the field of real-time simulation, scenario analysis, parameter optimization, parallel computation, system integration, etc.
Dr. Qiang Ma
Guest Editor
Dr. Morgan Abily
Dr. Dongwoo Jang
Guest Editor Assistants
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- hydrological-hydrodynamic modelling
- artificial intelligence
- machine learning
- optimization algorithm
- high performance computation
- real-time simulation
- climate change
- digital water
