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Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather...
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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: closed (1 April 2020) | Viewed by 25660

Special Issue Editors

Dr. Dimitris Myronidis

E-Mail Website
Guest Editor
School of Forestry and Natural Environment, Aristotle University of Thessaloniki, University Campus 54124, Po Box 268, Thessaloniki, Greece
Interests: hydrology; check-dam modelling; erosion assessment and control; discharge regulation; flood, drought, erosion, and landslide hazard analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Lampros Vasiliades

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Thessaly, 38334 Volos, Greece
Interests: geographic information systems; hydrology; management of extreme hydrological phenomena; hydrologic modelling and forecasting; spatial analysis techniques and remote sensing applications in civil engineering
Special Issues, Collections and Topics in MDPI journals

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 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. Water is an international peer-reviewed open access semimonthly 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 2600 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 (7 papers)

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Research

17 pages, 2982 KiB  
Article
An Index-Flood Statistical Model for Hydrological Drought Assessment
by Filip Strnad, Vojtěch Moravec, Yannis Markonis, Petr Máca, Jan Masner, Michal Stočes and Martin Hanel
Water 2020, 12(4), 1213; https://doi.org/10.3390/w12041213 - 24 Apr 2020
Cited by 6 | Viewed by 3409
Abstract
Modelling of hydrological extremes and drought modelling in particular has received much attention over recent decades. The main aim of this study is to apply a statistical model for drought estimation (in this case deficit volume) using extreme value theory and the index-flood [...] Read more.
Modelling of hydrological extremes and drought modelling in particular has received much attention over recent decades. The main aim of this study is to apply a statistical model for drought estimation (in this case deficit volume) using extreme value theory and the index-flood method and to reduce the uncertainties in estimation of drought event return levels. Deficit volumes for 133 catchments in the Czech Republic (1901–2015) were simulated by hydrological model BILAN. The validation of severity, intensity and length of simulated drought events revealed good match with the available observed data. To estimate return levels of the deficit volumes, it is assumed (in accord with the index-flood method), that the deficit volumes within a homogeneous region are identically distributed after scaling with a site-specific factor. The parameters of the scaled regional distribution are estimated using L-moments. The goodness-of-fit of the statistical model is assessed by Anderson–Darling test. For the estimation of critical values, sampling methods allowing for handling of years without drought were used. It is shown, that the index-flood model with a Generalized Pareto distribution performs well and substantially reduces the uncertainty related to the estimation of the shape parameter and of the large deficit volume quantiles. Full article
(This article belongs to the Special Issue Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events)
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15 pages, 3065 KiB  
Article
Changes in Precipitation Extremes over the Source Region of the Yellow River and Its Relationship with Teleconnection Patterns
by Feifei Yuan, Jiahong Liu, Ronny Berndtsson, Zhenchun Hao, Qing Cao, Huimin Wang, Yiheng Du and Dong An
Water 2020, 12(4), 978; https://doi.org/10.3390/w12040978 - 30 Mar 2020
Cited by 11 | Viewed by 2423
Abstract
Precipitation extremes and their underlying causes are important processes to understand to plan appropriate adaptation measures. This paper presents an analysis of the spatiotemporal variability and trend of precipitation extremes in the important source region of the Yellow River and explores the connection [...] Read more.
Precipitation extremes and their underlying causes are important processes to understand to plan appropriate adaptation measures. This paper presents an analysis of the spatiotemporal variability and trend of precipitation extremes in the important source region of the Yellow River and explores the connection to global teleconnection patterns and the 850-mb vector wind. Six indices for precipitation extremes were computed and analyzed for assessment of a changing regional climate. Results showed that these indices have a strong gradient from the northwest to the southeast part for the period 1961–2015, due to the great influence from the south-easterly summer monsoon flow. However, no statistically significant trends were found for the defined indices at the majority of stations, and their spatial distribution are noticed by irregularly mixed positive and negative changes except for the maximum number of consecutive wet days (CWD). Singular value decomposition analysis revealed that the precipitation extreme indices—including annual total precipitation when daily precipitation >95th percentile (R95p), annual count of days with daily precipitation ≥10 mm (R10mm), annual maximum consecutive 5-day precipitation (R5d), total precipitation divided by the number of wet days (SDII), and CWD—are negatively related to the El Nino-Southern Oscillation (NINO 3.4) in the first mode, and the maximum number of consecutive dry days (CDD) is positively related to the Scandinavian pattern in the second mode at 0.05 significance level. The 850-mb vector wind analysis showed that the southwestern monsoon originating from the Indian Ocean brings sufficient moisture to this region. Furthermore, the anti-cyclone in the western part of the North Pacific plays a significant role in the transport of moisture to the source region of the Yellow River. The links between precipitation extremes and teleconnection patterns explored in this study are important for better prediction and preparedness of climatic extremes. Full article
(This article belongs to the Special Issue Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events)
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18 pages, 9624 KiB  
Article
Indexing of Heatwaves in Ukraine
by Olga Shevchenko, Rostyslav Oliinyk, Sergiy Snizhko, Hanna Svintsitska and Ivan Kostyrko
Water 2020, 12(4), 962; https://doi.org/10.3390/w12040962 - 28 Mar 2020
Cited by 9 | Viewed by 6029
Abstract
During the last decades, the number of heatwaves (HWs) has increased worldwide, as well as in Ukraine. It is very important to determine the duration, intensity, and other HW parameters, in particular under climate change condition. For this purpose, various heatwave indices and [...] Read more.
During the last decades, the number of heatwaves (HWs) has increased worldwide, as well as in Ukraine. It is very important to determine the duration, intensity, and other HW parameters, in particular under climate change condition. For this purpose, various heatwave indices and characteristics are used. The aims of this study were (1) to investigate heatwave indices and their characteristics over the territory of Ukraine for the reference period 1981–2010, as well as to examine the extreme heatwave event of 2010 and (2) to make a comparison and establish a statistical relationship between the HW indices and their characteristics and to assess their suitability and sensitivity to changes in the modern climate of Ukraine. On the basis of 49 selected stations, daily values of maximum air temperature (Tmax) in the summer months June to August of 1981–2010 were used to determine two heatwave indices (HWMI (heatwave magnitude index) and HWMId (heatwave magnitude index daily)) and five heatwave characteristics (HWM (heatwave mean), HWA (heatwave amplitude), HWN (heatwave number), HWD (heatwave duration), HWF (heatwave day frequency)). The calculated indices of heatwaves appeared to be sufficiently sensitive to minor changes in the daily maximum air temperature. HWMId was found to be more sensitive to temperature changes than HWMI. The heatwave characteristics of the HWN, HWF, HWM, and the HWMId climate index proved to be the most informative in the study of heatwaves in Ukraine. Full article
(This article belongs to the Special Issue Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events)
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17 pages, 941 KiB  
Article
Generating Regional Models for Estimating the Peak Flows and Environmental Flows Magnitude for the Bulgarian-Greek Rhodope Mountain Range Torrential Watersheds
by Dimitrios Myronidis and Ekaterina Ivanova
Water 2020, 12(3), 784; https://doi.org/10.3390/w12030784 - 12 Mar 2020
Cited by 15 | Viewed by 2732
Abstract
The flood magnitudes with 25, 50, and 100 years return periods and the environmental flows (Qenv) are of outmost importance in the context of hydraulic and hydrologic design. In this study, 25 watershed characteristics were linked with the aforementioned recurrence [...] Read more.
The flood magnitudes with 25, 50, and 100 years return periods and the environmental flows (Qenv) are of outmost importance in the context of hydraulic and hydrologic design. In this study, 25 watershed characteristics were linked with the aforementioned recurrence intervals, peak discharge values, as well as Qenv for 15 pristine torrential watersheds with more than 10 years of streamflow records in the Rhodopi mountain range with a view to generating regional relationships for the assessment of discharge annual peaks and environmental flows regarding the ungauged torrential watersheds in the region. The Log-Pearson Type III probability distribution was fitted in the discharge annual peaks time series, so as to predict Q25, Q50, and Q100, whereas the Tennant method was utilised so as to estimate the environmental flows magnitude. Similarly, the Kolmogorov–Smirnov and the Anderson–Darling tests were performed to verify the distribution fitting. The Principal Components Analysis method reduced the explanatory variables number to 14, whilst the stepwise multiple regression analysis indicated that the exponential model is suitable for predicting the Q25, the power model best forecasted the Q50 and Q100, whereas the linear model is appropriate for Qenv prognosis. In addition, the reliability of the obtained regression models was evaluated by employing the R2, the Nash–Sutcliffe efficiency, and the Index of Agreement Statistical Criteria, which were found to range from 0.91–0.96, 0.88–0.95 and 0.97–0.99, respectively, thereby denoting very strong and accurate forecasts by the generated equations. Thus, the developed equations could successfully predict the peak discharge values and environmental flows within the region’s ungauged watersheds with the drainage size not exceeding 330 km2. Full article
(This article belongs to the Special Issue Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events)
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20 pages, 3495 KiB  
Article
Development of Combined Heavy Rain Damage Prediction Models with Machine Learning
by Changhyun Choi, Jeonghwan Kim, Jungwook Kim and Hung Soo Kim
Water 2019, 11(12), 2516; https://doi.org/10.3390/w11122516 - 28 Nov 2019
Cited by 9 | Viewed by 3944
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
(This article belongs to the Special Issue Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events)
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16 pages, 2670 KiB  
Article
Combination of Structural Measures for Flood Prevention in Anyangcheon River Basin, South Korea
by Kyunghun Kim, Daegun Han, Deokhwan Kim, Wonjoon Wang, Jaewon Jung, Jungwook Kim and Hung Soo Kim
Water 2019, 11(11), 2268; https://doi.org/10.3390/w11112268 - 29 Oct 2019
Cited by 8 | Viewed by 3727
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
(This article belongs to the Special Issue Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events)
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13 pages, 2860 KiB  
Article
Inter-Seasonal Precipitation Variability over Southern China Associated with Commingling Effect of Indian Ocean Dipole and El Niño
by Chaizi Heng, Sun-Kwon Yoon, Jong-Suk Kim and Lihua Xiong
Water 2019, 11(10), 2023; https://doi.org/10.3390/w11102023 - 28 Sep 2019
Cited by 5 | Viewed by 2632
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
(This article belongs to the Special Issue Understanding, Modelling and Mitigating Flood, Drought and other Extreme Weather Events)
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