Special Issue "Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 14 February 2020.

Special Issue Editors

Dr. Dimitrios Myronidis
E-Mail Website
Guest Editor
School of Forestry and Natural Environment, Aristotle University of Thessaloniki , University Campus 54124, Po Box 268, Thessaloniki, Greece
Dr. Lampros Vasiliades
E-Mail Website
Guest Editor
Department of Civil Engineering, University of Thessaly, Pedion Areos, 38334 Volos, Greece
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Special Issue Information

Dear Colleagues,

The rise in global temperature is already negatively influencing water resources, while in the upcoming years it is anticipated that this pressure on water bodies will intensify to an unprecedented level. The frequency, intensity, timing, patterns and magnitude of floods, droughts, heatwaves and heavy storm events are expected to change dramatically, and to have a detrimental effect on humans and infrastructure, while causing severe damage to the environment as well. Additionally, human interventions such as urbanization, land use change and the inappropriate design and failure of works can trigger or aggravate the aforementioned phenomena.

This Special Issue aims to provide a forum for scientists from different domains to unveil, through original and innovating papers, the key processes, mechanisms and consequences of the latter phenomena, so that this new knowledge can be used to mitigate the impact of such events for the benefit of society. The related coverage of these topics, which foresees a major breakthrough in current knowledge, will involve the detection, analysis, monitoring, interpretation, modelling, forecasting, preparedness, prevention adaptation, mitigation and public awareness of such events, on multiple spatial and temporal scales.

Dr. Dimitrios Myronidis
Guest Editor

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 papers will be 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 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

  • Floods
  • Droughts
  • Heatwaves
  • Heavy storm events

Published Papers (3 papers)

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Research

Open AccessArticle
Development of Combined Heavy Rain Damage Prediction Models with Machine Learning
Water 2019, 11(12), 2516; https://doi.org/10.3390/w11122516 - 28 Nov 2019
Cited by 1
Abstract
Adequate forecasting and preparation for heavy rain can minimize life and property damage. Some studies have been conducted on the heavy rain damage prediction model (HDPM), however, most of their models are limited to the linear regression model that simply explains the linear [...] Read more.
Adequate forecasting and preparation for heavy rain can minimize life and property damage. Some studies have been conducted on the heavy rain damage prediction model (HDPM), however, most of their models are limited to the linear regression model that simply explains the linear relation between rainfall data and damage. This study develops the combined heavy rain damage prediction model (CHDPM) where the residual prediction model (RPM) is added to the HDPM. The predictive performance of the CHDPM is analyzed to be 4–14% higher than that of HDPM. Through this, we confirmed that the predictive performance of the model is improved by combining the RPM of the machine learning models to complement the linearity of the HDPM. The results of this study can be used as basic data beneficial for natural disaster management. Full article
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Open AccessArticle
Combination of Structural Measures for Flood Prevention in Anyangcheon River Basin, South Korea
Water 2019, 11(11), 2268; https://doi.org/10.3390/w11112268 - 29 Oct 2019
Abstract
Climate change and fast urbanization increased rainfall intensity and runoff discharge. These changes lead to the growing possibility of flood damages. In South Korea, a government established the “Comprehensive Flood Prevention Plan (CFPP)” for each of river basin against flood. The plan is [...] Read more.
Climate change and fast urbanization increased rainfall intensity and runoff discharge. These changes lead to the growing possibility of flood damages. In South Korea, a government established the “Comprehensive Flood Prevention Plan (CFPP)” for each of river basin against flood. The plan is based on the combination of structural measures selected by experienced hydrologists. However, it lacks clear criteria. To solving this problem, this study classifies the structural measures and suggests a combination method, which use relationships between measures, to ensure the objectivity of the process in identifying proper measures. For Anyangcheon river basin, two plans are provided; the first is developed by the study, and the other is by the CFPP. Comparing the two plans, the results show that the combination, selected by proposed method in this study, is economically more feasible compared to CFPP. Therefore, this study expected be useful when selecting and combining structural measures for formulating river basin flood prevention plans. Full article
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Open AccessArticle
Inter-Seasonal Precipitation Variability over Southern China Associated with Commingling Effect of Indian Ocean Dipole and El Niño
Water 2019, 11(10), 2023; https://doi.org/10.3390/w11102023 - 28 Sep 2019
Abstract
This study analyzed temporal and regional responses of precipitation to the Indian Ocean Dipole (IOD) over southern China and the differences between IOD-only and El Niño–southern oscillation–IOD cases. The Mann–Kendall test and intentionally biased bootstrapping were used. The results revealed three main phases [...] Read more.
This study analyzed temporal and regional responses of precipitation to the Indian Ocean Dipole (IOD) over southern China and the differences between IOD-only and El Niño–southern oscillation–IOD cases. The Mann–Kendall test and intentionally biased bootstrapping were used. The results revealed three main phases (development and peak, decay, and aftermath) of percentage changes in seasonal total rainfall and showed the most positive sensitivity to positive IOD events in southern China. Moreover, El Niño played an essential role in intensifying the positive response to positive IOD events in the first and second phases while contributing little to the third. In terms of precipitation variability (frequency, intensity, and magnitude), seasonal maximum 1-day precipitation and maximum number of consecutive dry days were more sensitive to positive IOD events than the maximum number of consecutive wet days and simple daily precipitation intensity index. This study enhances knowledge of the temporal and spatial sensitivity of precipitation features to positive IOD events over southern China. Full article
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