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Climate
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Hydro-Meteorological Hazards: Causes, Impacts, and Mitigation Strategies
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Hydro-Meteorological Hazards: Causes, Impacts, and Mitigation Strategies

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: 30 April 2025 | Viewed by 1307

Special Issue Editors

Dr. Marco Luppichini

E-Mail Website
Guest Editor
Department of Earth Sciences, University of Pisa, Via Santa Maria 53, 56126 Pisa, Italy
Interests: climate change; fluvial geomorphology; coastal geomorphology; extreme events; AI; statistical analysis of climate time series
Special Issues, Collections and Topics in MDPI journals
Dr. Monica Bini

E-Mail Website
Guest Editor
Earth Sciences Department, University of Pisa, Via S. Maria 53, 56126 Pisa, Italy
Interests: geoarchaeology; coastal geomorphology; climate change; human impact; Anthropocene
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Hydro-meteorological hazards, including extreme events like floods, hurricanes, and droughts, are increasingly frequent and intense due to climate change and rapid land-use changes. These events, driven by complex atmospheric and hydrological processes, are further intensified by human activities such as deforestation, urbanization, and greenhouse gas emissions. Such hazards pose significant threats to ecosystems, water resources, infrastructure, and human life. Research on these events is crucial to better understand their underlying mechanisms and interactions and to inform more effective strategies for risk mitigation and climate adaptation.

This Special Issue seeks to advance our understanding of hydro-meteorological hazards by bringing together studies that explore their causes, impacts, and mitigation strategies. By addressing topics such as predictive modeling, risk assessment, and the influence of anthropogenic factors on extreme weather events, this Issue aligns closely with the scope of Climate, emphasizing climate variability, environmental risks, and resilience-building measures. The research will offer both theoretical and applied insights, supporting policymakers, urban planners, and environmental scientists in developing adaptive strategies that respond to the evolving risks posed by climate-driven extreme weather.

This Special Issue invites original research, reviews, and case studies addressing themes such as the following:  (1) the physical and climatological drivers of hydro-meteorological hazards; (2) advanced modeling techniques for forecasting extreme events, (3) impacts on ecosystems and socio-economic systems, (4) sustainable land and water management practices, and (5) early warning and risk mitigation technologies. Submissions may also cover policy-oriented approaches and cross-disciplinary studies that connect environmental science with public health, socioeconomics, and urban planning.

Dr. Marco Luppichini
Dr. Monica Bini
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. Climate 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 1800 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

  • climate change impacts
  • extreme weather events
  • flooding and drought risk
  • risk assessment
  • hazard mitigation strategies
  • resilience and adaptation
  • early warning systems
  • Anthropogenic influences
  • climate-driven disasters
  • early warning systems

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

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17 pages, 3364 KiB  
Article
Development of Prediction Model for Damage Costs of Heavy Rainfall Disasters Using Machine Learning in the Republic of Korea
by Youngseok Song, Yang Ho Song, Moojong Park and Sang Yeob Kim
Climate 2025, 13(4), 72; https://doi.org/10.3390/cli13040072 - 1 Apr 2025
Viewed by 233
Abstract
In this study, a prediction model was developed that considers the rainfall characteristics and damage characteristics of heavy rainfall disasters in Korea using machine learning models. Considering the damage characteristics of heavy rainfall disasters that occurred from 1999 to 2019 in 228 administrative [...] Read more.
In this study, a prediction model was developed that considers the rainfall characteristics and damage characteristics of heavy rainfall disasters in Korea using machine learning models. Considering the damage characteristics of heavy rainfall disasters that occurred from 1999 to 2019 in 228 administrative districts in Korea, four types of total rainfall and five types of damage costs were selected to predict the total damage cost. The machine learning models selected for this study were Random Forest, K-Nearest Neighbors, Decision Tree, and eXtreme Gradient Boosting, and their accuracy was evaluated using R2, EVS, and MAPE. The training period spanned from 1999 to 2015, while the evaluation period extended from 2016 to 2019. The Random Forest model emerged as the most effective model for predicting the total damage costs associated with heavy rainfall disasters, exhibiting an accuracy of 0.95 for R2, 0.95 for EVS, and 0.05 for MAPE. It was observed that when the total damage costs are minimal, all models demonstrate high prediction capability. However, as the damage costs escalate, the prediction power experiences a decline due to the presence of errors. The machine learning prediction model for heavy rainfall disasters developed in this study has the potential to contribute to national efforts aimed at preventing and preparing for heavy rainfall disasters. Full article
(This article belongs to the Special Issue Hydro-Meteorological Hazards: Causes, Impacts, and Mitigation Strategies)
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Review

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17 pages, 1253 KiB  
Review
Adaptation to Glacial Lake Outburst Floods (GLOFs) in the Hindukush-Himalaya: A Review
by Sobia Shah and Asif Ishtiaque
Climate 2025, 13(3), 60; https://doi.org/10.3390/cli13030060 - 17 Mar 2025
Cited by 1 | Viewed by 668
Abstract
This study examines adaptation strategies to mitigate the risks posed by Glacial Lake Outburst Floods (GLOFs) in the Hindu Kush Himalayan (HKH) region, encompassing Pakistan, India, Nepal, Bhutan, and Afghanistan. GLOFs occur when water is suddenly released from glacial lakes and they present [...] Read more.
This study examines adaptation strategies to mitigate the risks posed by Glacial Lake Outburst Floods (GLOFs) in the Hindu Kush Himalayan (HKH) region, encompassing Pakistan, India, Nepal, Bhutan, and Afghanistan. GLOFs occur when water is suddenly released from glacial lakes and they present significant threats to communities, infrastructure, and ecosystems in high-altitude regions, particularly as climate change intensifies their frequencies and severity. While there are many studies on the changes in glacial lakes, studies on adaptation to GLOF risks are scant. Also, these studies tend to focus on case-specific scenarios, leaving a gap in comprehensive, region-wide analyses. This review article aims to fill that gap by synthesizing the adaptation strategies adopted across the HKH region. We conducted a literature review following several inclusion and exclusion criteria and reviewed 23 scholarly sources on GLOF adaptation. We qualitatively synthesized the data and categorized the adaptation strategies into two main types: structural and non-structural. Structural measures include engineering solutions such as lake-level control, channel modifications, and flood defense infrastructure, designed to reduce the physical damage caused by GLOFs. Non-structural measures include community-based practices, economic diversification, awareness programs, and improvements in institutional governance, addressing social and economic vulnerabilities. We found that Afghanistan remains underrepresented in GLOF-related studies, with only one article that specifically focuses on GLOFs, while Nepal and Pakistan receive greater attention in research. The findings underscore the need for a holistic, context-specific approach that integrates both structural and non-structural measures to enhance resilience across the HKH region. Policy-makers should prioritize the development of sustainable mechanisms to support long-term adaptation efforts, foster cross-border collaborations for data sharing and coordinated risk management, and ensure that adaptation strategies are inclusive of vulnerable communities. Practitioners should focus on strengthening early warning systems, expanding community-based adaptation initiatives, and integrating traditional knowledge with modern scientific approaches to enhance local resilience. By adopting a collaborative and regionally coordinated approach, stakeholders can improve GLOF risk preparedness, mitigate socioeconomic impacts, and build long-term resilience in South Asia’s high-altitude regions. Full article
(This article belongs to the Special Issue Hydro-Meteorological Hazards: Causes, Impacts, and Mitigation Strategies)
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