Mapping and Modelling Hydroclimate Extremes Using Remote Sensing and Advanced Geospatial Techniques
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".
Deadline for manuscript submissions: 1 June 2026 | Viewed by 22
Special Issue Editors
2. School of Science, Technology and Engineering, University of the Sunshine Coast, Sippy Downs, QLD, Australia
3. Department of Hydrometeorology and Environmental Monitoring, Faculty of Hydrometeorology, National University of Uzbekistan, Tashkent, Uzbekistan
Interests: remote sensing applications in water resource management; hydrological and hydrodynamic modeling; geospatial analysis of hydroclimate extremes; climate change impacts on hydrological systems; nature-based solutions and wetland restoration
Special Issues, Collections and Topics in MDPI journals
Interests: GIS; spatial analysis and modeling; advanced geospatial techniques; climate change analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Hydroclimate extremes, particularly extreme floods, are increasing in frequency and intensity due to climate change and landscape alterations. These events pose major threats to lives, infrastructure, and ecosystems and call for robust methods to understand, monitor, and predict their impacts. This Special Issue invites original research and reviews focusing on mapping, modeling, and assessing extreme flood events, emphasizing integrating remote sensing, advanced geospatial analysis, and hydrological and hydrodynamic modeling techniques.
We seek contributions that leverage satellite data (e.g., Sentinel, SWOT, MODIS), UAV-based observations, LiDAR, and SAR to detect, map, and quantify flood extents, water levels, and landscape responses. Studies employing data assimilation, AI/ML-based modeling, and coupling remote sensing with hydrodynamic simulations to enhance flood prediction and decision-making are highly encouraged.
The Special Issue will foster cross-disciplinary research addressing challenges in flood risk mapping, early warning systems, and nature-based solutions. We welcome submissions covering a range of scales—from catchment to continental—and geographic contexts, particularly in data-scarce or climate-sensitive regions.
Dr. Ben Jarihani
Dr. Beata Calka
Dr. Khalil Valizadeh Kamran
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. Atmosphere is an international peer-reviewed open access monthly 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 2400 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
- extreme flood events
- remote sensing
- hydrodynamic modeling
- geospatial analysis
- climate change impacts
- data assimilation
- machine learning in hydrology
- early warning systems
- satellite altimetry
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