Advances in Machine Learning for Flood Prediction and Water Risk Management
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: 25 April 2026 | Viewed by 23
Special Issue Editor
Interests: air quality modeling; machine learning in environmental science; climate and atmospheric science; flood prediction and hydrology; remote sensing and GIS applications; net-zero and low-carbon strategies; emission inventory development; environmental data science
Special Issue Information
Dear Colleagues,
Recent advances in data science, machine learning (ML), and remote sensing provide unique opportunities to address challenges in flood prediction and water-related risk management. Accurate and timely flood forecasting is critical for protecting communities, infrastructure, and ecosystems, particularly under the increasing pressures of climate change and urban expansion. This Special Issue aims to focus on innovative applications of machine learning methods—including deep learning, hybrid models, surrogate modeling, and data assimilation approaches—to improve flood forecasting, risk assessment, and early warning systems. Contributions may also explore the integration of socioeconomic and climatic drivers, novel sensor networks, uncertainty quantification, and explainable AI to enhance the transparency and usability of predictive models. By bringing together interdisciplinary research, this Special Issue aims to advance methodological innovations and provide actionable insights for policymakers, practitioners, and researchers in water sciences.
We welcome the submission of both methodological and applied studies, case studies from diverse regions, and reviews that highlight emerging directions in machine learning for hydrological and flood prediction research.
Dr. Masrur Ahmed
Guest Editor
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
- flood prediction
- machine learning and deep learning
- hydrological modeling
- climate change impacts on flood
- data assimilation
- remote sensing
- uncertainty analysis
- early warning systems
- flood prediction with global circulation model
- integration of AI and physics-based models
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