Application of Machine Learning in Hydrologic Sciences

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 161

Special Issue Editors

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Guest Editor
Department of Physical Chemistry, Faculty of Sciences, University of Vigo, 32004 Ourense, Spain
Interests: artificial intelligence (neural networks, fuzzy logic, expert systems, etc.); physical chemistry; water management; hydrology; food technology; bioinformatics; palynology
Special Issues, Collections and Topics in MDPI journals

Guest Editor
Environmental Physics Laboratory (EPhysLab), Centro de Investigación Mariña (CIM), Universidade de Vigo, Campus da Auga, 32004 Ourense, Spain
Interests: hydrodynamic numerical simulation; artificial intelligence; flood analysis; flood forecasting; flood early warning systems, climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last years, applications based on machine learning (ML) have been widely used to solve problems in different scientific areas. Within the current ML algorithms, support vector machines, Bayesian networks, and artificial neural networks, among others, can be mentioned.

Currently, there are many monitoring instruments/stations that allow a daily collection of hydrological data. Different ML-based models can be fed with these data to study/model the following: dam/water supply management, extreme events, natural/anthropogenic changes in lakes, transport of pollutants, drinking water quality, landslides induced by rain, etc.

The objective of this Special Issue on “Application of Machine Learning in Hydrologic Sciences” is to present current research on the aforementioned problems (but not limited exclusively to them) using machine learning.

We invite all researchers, working in hydrological sciences and ML, to submit research or review articles that demonstrate the significant potential of machine learning in this field.

Dr. Gonzalo Astray
Dr. Diego Fernández-Nóvoa
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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.


  • hydrology
  • water cycle
  • water–soil–atmosphere
  • machine learning
  • big data
  • monitoring/modelling/prediction/optimization/management
  • water flow/quality/supply/energy
  • risk/hazard assessment
  • multidisciplinary water research

Published Papers

This special issue is now open for submission.
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