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Atmosphere
Special Issues
Hydrometeorological Extremes: Current Status and Emerging Challenges
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Hydrometeorological Extremes: Current Status and Emerging Challenges

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 806

Special Issue Editors

Dr. Cristian Anghel

E-Mail Website
Guest Editor
Faculty of Hydrotechnics, Technical University of Civil Engineering Bucharest, Lacul Tei, Nr. 122-124, 020396 Bucharest, Romania
Interests: extreme and rare events; floods; droughts; frequency analyses; trend analyses; climate changes; uncertainties; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Xiong Zhou

E-Mail Website
Guest Editor
1. China-Canada Center for Energy, Environment and Ecology Research, UofR-BNU, Beijing Normal University, Beijing 100875, China
2. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK S4S 0A2, Canada
Interests: regional climate modeling; hydrological simulation; water resources management; climate-change impact assessment; environmental systems modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Severe hydrometeorological events are serious issues that have an impact on global society, having a big impact on agriculture, infrastructure, human safety, and water resources. For management and mitigation efforts to be effective, it is imperative to comprehend the current state, as well as upcoming difficulties related to these extremes.

We invite original research materials that explore various facets of hydrometeorological extremes, such as floods, excessive precipitation, and droughts, for this Special Issue. We are particularly interested in research that examines how these catastrophic events impact local and regional climate scales.

We invite submissions that employ multidisciplinary approaches, integrating modern technologies like remote sensing and satellite data to enhance the monitoring and forecasting of extreme events. Topics of interest include the following: floods, frequency analyses, trend analyses, hydrological and hydrometeorological drought analyses, etc. This Special Issue aims to explore the current status and emerging challenges, providing a deeper understanding of these extreme events, which is essential for effective management and mitigation strategies.

Dr. Cristian Anghel
Dr. Xiong Zhou
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 and rare events
  • floods
  • droughts
  • frequency analyses
  • remote sensing
  • trend analyses
  • climate changes
  • uncertainties
  • machine learning

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Published Papers (1 paper)

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Research

21 pages, 6689 KiB  
Article
Assessing the Impact of Climate Change on Intensity-Duration-Frequency (IDF) Curves for the Qassim Region, Saudi Arabia
by Mohammed ALRakathi and Abdullah Alodah
Atmosphere 2025, 16(1), 59; https://doi.org/10.3390/atmos16010059 - 8 Jan 2025
Viewed by 391
Abstract
Climate change has the potential to significantly impact various aspects of Earth’s climate systems, including precipitation patterns, necessitating region-specific action plans. This study examines the Wadi Al Rummah region in Qassim province, Saudi Arabia, by analyzing Intensity-Duration-Frequency (IDF) curves across six locations, utilizing [...] Read more.
Climate change has the potential to significantly impact various aspects of Earth’s climate systems, including precipitation patterns, necessitating region-specific action plans. This study examines the Wadi Al Rummah region in Qassim province, Saudi Arabia, by analyzing Intensity-Duration-Frequency (IDF) curves across six locations, utilizing observed daily precipitation data from 1986 to 2014. The nonparametric quantile mapping method was employed to adjust the outputs of eight Regional Climate Models (RCMs) within the CMIP6 ensemble. These models were evaluated under four Shared Socioeconomic Pathways (SSPs), ranging from a stringent mitigation scenario to one with very high greenhouse gas emissions. Also, two statistical tests, namely the Kolmogorov-Smirnov and Chi-Square tests, were used to assess the best-fitting distribution to estimate the maximum rainfall values. Temporal disaggregation of daily precipitation data was performed using the K-nearest neighbors (KNN) method. The IDF curves were generated for both historical and three projected future periods using Gumbel distribution, which proved to be the best-fitting statistical model, using six return periods: 2, 5, 10, 25, 50, and 100 years. Results indicate that high-emission scenarios and longer timeframes exhibit greater uncertainty in IDF projections. Additionally, rainfall intensity is expected to increase over shorter durations, with significant increases observed in Buriydah and Nabhaniyah under SSP 8.5. In contrast, Al Rass, Badayea, and Al Mithnab show mixed trends, while Unaizah shows little to no significant change. These findings emphasize the need for sustainable development and adaptive strategies to mitigate risks in Qassim province, as climate impacts are projected to intensify, particularly in the short to long term. Full article
(This article belongs to the Special Issue Hydrometeorological Extremes: Current Status and Emerging Challenges)
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Graphical abstract
Full article ">Figure 1
<p>Location of the study area and the meteorological stations (colors indicate the elevation in meters above sea level).</p> Full article ">Figure 2
<p>An illustrative flowchart delineating the methodologies for updating the IDF curves.</p> Full article ">Figure 3
<p>The K-nearest neighbor disaggregation process.</p> Full article ">Figure 4
<p>The IDF curves of Buridah station employing the Gumbel distribution.</p> Full article ">Figure 5
<p>The IDF curves developed for all eight RCMs across four SSPs (boxplots) and the observed IDF curves (red lines) for (<b>a</b>) short-term, (<b>b</b>) mid-term, and (<b>c</b>) long-term future periods of Buraidah station.</p> Full article ">Figure 5 Cont.
<p>The IDF curves developed for all eight RCMs across four SSPs (boxplots) and the observed IDF curves (red lines) for (<b>a</b>) short-term, (<b>b</b>) mid-term, and (<b>c</b>) long-term future periods of Buraidah station.</p> Full article ">Figure 6
<p>Violin plots of the projected annual maximum precipitation intensity for all stations for comparison, covering different models and SSPs for three future periods. Tthe dotted lines represent the 25th percentile (Q1), the 50th percentile (median), and the 75th percentile (Q3) of the data distribution.</p> Full article ">Figure 6 Cont.
<p>Violin plots of the projected annual maximum precipitation intensity for all stations for comparison, covering different models and SSPs for three future periods. Tthe dotted lines represent the 25th percentile (Q1), the 50th percentile (median), and the 75th percentile (Q3) of the data distribution.</p> Full article ">
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