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Atmosphere
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Mapping and Modelling Hydroclimate Extremes Using Remote Sensing and Advanced...
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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 2873

Special Issue Editors

Dr. Ben Jarihani

E-Mail Website
Guest Editor
1. Earth and Environmental Science Department, College of Science and Engineering, James Cook University, Douglas, QLD, Australia
2. School of Science, Technology and Engineering, University of the Sunshine Coast, Sippy Downs, QLD, Australia
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
Dr. Beata Calka

E-Mail Website
Guest Editor
Department of Geospatial Information Systems, Institute of Geospatial Engineering and Geodesy, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, Poland
Interests: GIS; spatial analysis and modeling; advanced geospatial techniques; climate change analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Khalil Valizadeh Kamran

E-Mail Website
Guest Editor
Head of Remote Sensing & GIS Department, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran
Interests: spatial modelling; remote sensing and GIS; environmental monitoring and mapping

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 250 words) can be sent to the Editorial Office for assessment.

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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Published Papers (1 paper)

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Research

24 pages, 19475 KB  
Article
Spatio-Temporal Evaluation of MSWEP, CHIRPS and ERA5-Land Reveals Regional-Specific Responses Across Complex Topography in Bolivia
by Álvaro Salazar, Daniel M. Larrea-Alcázar, Angéline Bertin, Nicolas Gouin, Alejandro Pareja, Luis Morales, Oswaldo Maillard, Diego Ocampo-Melgar and Francisco A. Squeo
Atmosphere 2025, 16(11), 1281; https://doi.org/10.3390/atmos16111281 - 11 Nov 2025
Cited by 1 | Viewed by 2070
Abstract
Reliable precipitation estimates are critical for climate analysis and ecosystem management in regions with complex topography and limited ground-based observations. Bolivia, where the Andes, inter-Andean valleys, and Amazonian lowlands converge, presents sharp climatic heterogeneity that challenges both satellite retrievals and reanalysis products. This [...] Read more.
Reliable precipitation estimates are critical for climate analysis and ecosystem management in regions with complex topography and limited ground-based observations. Bolivia, where the Andes, inter-Andean valleys, and Amazonian lowlands converge, presents sharp climatic heterogeneity that challenges both satellite retrievals and reanalysis products. This study evaluated three widely used datasets, MSWEP V2.2, CHIRPS V2, and ERA5-Land, against monthly station records from 1980 to 2022 to identify the most reliable precipitation estimations for hydrological and climate applications in five distinct regions. We applied a robust validation framework that integrates continuous and categorical performance metrics into a Combined Accuracy Index (CAI), providing a balanced measure of magnitude and event detection skill. Additionally, we implemented a conservative trend analysis with explicit correction for serial autocorrelation to ensure reliable identification of long-term changes. The results showed that MSWEP V2.2 consistently outperforms CHIRPS V2 and ERA5-Land across most regions, achieving the highest combined skill. In the Altiplano, MSWEP reached a CAI of 0.91, compared to CHIRPS (0.80) AND ERA5-Land (0.68). In the Valles region, MSWEP also led with 0.85, outperforming CHIRPS (0.79) and ERA5-Land (0.51). By contrast, CHIRPS V2 performed better in the Llanos (0.85) relative to MSWEP (0.82) and ERA5-Land (0.79). In the Chaco, MSWEP and CHIRPS performed similarly (0.80 and 0.81, respectively), while ERA5-Land scored 0.70. In the Amazonian lowlands, all three products performed well, with MSWEP ranking first (0.93), followed by ERA5-Land (0.88) and CHIRPS (0.86). ERA5-Land systematically overestimated precipitation across Bolivia, with annual biases above 36 mm month−1. Trend analysis revealed significant precipitation declines, particularly in the Llanos (MSWEP: −0.88 mm year−1; CHIRPS: −1.19 mm year−1; ERA5-Land: −0.90 mm year−1), while changes in the Altiplano, Valles and Amazonia were weaker or nonsignificant. These findings highlight MSWEP V2.2 as the most reliable dataset for Bolivia. The methodological framework proposed here offers a transferable approach to validate gridded products in other data-scarce and environmentally diverse regions. Full article
(This article belongs to the Special Issue Mapping and Modelling Hydroclimate Extremes Using Remote Sensing and Advanced Geospatial Techniques)
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