Intelligent Water Management: Machine Learning, Remote Sensing, Data Analytics, Predictive Modeling, and the Path to Sustainability
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".
Deadline for manuscript submissions: 20 October 2025 | Viewed by 58
Special Issue Editors
Interests: water resources; hydrology; AI; climate change; sustainable development; time series; hydrological modelling; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: climate change; drought management; soil and water conservation; irrigation; hydrological modeling; surface hydrology; rainfall runoff modeling; hydraulics; numerical modeling; hydrology; hydrologic and water resource management; environment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Water is at the heart of humanity’s resilience in an era of climate uncertainty and resource scarcity. This Special Issue invites pioneering research that harnesses the power of artificial intelligence (AI) and advanced data technologies to revolutionize how we monitor, predict, and manage water systems. From real-time water quality monitoring and flood forecasting to drought prediction and water distribution optimization, we explore how machine learning, remote sensing, big data analytics, and predictive modeling can unlock smarter, more sustainable solutions. This collection aims to bridge the gap between traditional hydrological approaches and next-generation tools, fostering climate resilience, enhancing water resource management, and safeguarding ecosystems. Situated at the intersection of environmental science and cutting-edge technology, this Special Issue builds on the existing literature by spotlighting AI-driven forecasting, smart water systems, and data-driven decision-making as catalysts for transformative change. We welcome contributions that push boundaries—whether through theoretical breakthroughs or real-world applications—offering a dynamic platform for researchers, engineers, and policymakers to shape the future of water sustainability. Dive in and join us on the path to a water-secure world!
We look forward to receiving your contributions.
Dr. Hossein Bonakdari
Prof. Dr. Silvio José Gumiere
Guest Editors
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
- artificial intelligence (AI)
- water quality monitoring
- predictive modeling
- flood forecasting
- drought prediction
- water resource management
- big data analytics
- climate resilience
- sustainable water management
- environmental science
- hydrological modeling
- machine learning
- remote sensing
- data-driven decision-making
- smart water systems
- water distribution optimization
- AI-driven forecasting
- ecosystem management
- water conservation
- water infrastructure management
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