New Technologies for Hydrological Forecasting and Modeling
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".
Deadline for manuscript submissions: 25 May 2026 | Viewed by 9
Special Issue Editors
Interests: hydrological extremes; floods; droughts; extreme precipitation; statistical and stochastic modeling; flood frequency analysis; risk and uncertainty analysis; hydrological forecasts; anthropogenic impacts on the hydrological regime; climate change
Special Issues, Collections and Topics in MDPI journals
Interests: hydrological time series; nonstationarity detection; statistical methods; hydro-climatic extreme events; temporal and spatial variability; climatic changes impact on hydrological characteristics; anthropogenic impacts on extreme events; drought indices
Special Issues, Collections and Topics in MDPI journals
Interests: applied statistics; hydrological time series; droughts; environmental modeling; statistical methods in hydrology; temporal and spatial variability; river hydrology; geospatial analysis; survey data analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the face of increasing climate variability, intensified hydrological extremes, and rapid environmental changes, the demand for advanced hydrological forecasting and modeling has never been more urgent. Traditional hydrological models, while valuable, often struggle to accommodate the complexity and dynamics of contemporary hydrological systems. Emerging technologies—such as remote sensing, real-time data assimilation, high-performance computing, and artificial intelligence (AI)—can improve our ability to predict, simulate, and manage water-related processes and hazards.
These technological innovations enable more accurate forecasting of floods, droughts, and water availability; enhance early warning systems; and support evidence-based decision-making for sustainable water resource management. As such, integrating new tools and methods into hydrological practice represents a key scientific and societal priority.
In this Special Issue of Water, we are particularly interested in studies related to recent advancements, applications, and evaluations of modern technologies in hydrological forecasting and modeling. We invite authors to present their research on the following topics (not limited to the list below):
- Real-time hydrological data assimilation and forecasting.
- Remote sensing for hydrological model input and validation.
- Integration of hydrological and hydraulic models.
- Uncertainty quantification and model evaluation techniques.
- Early warning systems for floods and droughts.
- Coupled models for land–atmosphere–water interactions.
- Climate change impact assessment on future hydrological conditions.
- Machine learning and AI applications in hydrology.
We look forward to your contributions.
Dr. Iwona Kuptel-Markiewicz
Dr. Agnieszka Rutkowska
Guest Editors
Dr. Katarzyna Baran-Gurgul
Guest Editor Assistant
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 modeling and foorecasting
- machine learning in hydrology
- real-time forecasting
- remote sensing applications
- uncertainty analysis
- hydrological extreme events
- artificial intelligence in hydrology
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