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Special Issue "Flash Floods in Urban Areas"

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

Deadline for manuscript submissions: 31 July 2019

Special Issue Editor

Guest Editor
Dr. Stefanos Stefanidis

Laboratory of Mountainous Water Management and Control, Faculty of Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloníki, Greece
Website | E-Mail
Interests: soil erosion and mountainous catchment degrafation; landslide management and control; cause and mechanism of debris and mud flow phenomena; torrent control works; check dams design and dimmensioning; sediment sources areas; flash floods phenomena; forest hydrology

Special Issue Information

Dear Colleagues,

Flash floods have been considered to be the most common natural disaster worldwide over the last decades. Their consequences are not only environmental but also economic, since they may cause damage to urban areas and may even result in the loss of life. Rapid population growth and urbanization have led to encroachments within stream beds and land use changes to catchments in upper urban centers. It is worth mentioning that many times flood phenomena could have been avoided if no anthropogenic interventions existed within stream beds. Moreover, due to climate change, flash floods will continually grow.

Topics of interest include, but are not limited to:

  • Post flash flood investigations
  • Causes and mechanisms of flash flood phenomena
  • Identification of flood prone areas
  • Urban flooding and climate change
  • Flood forecasting in urban areas
  • Anthropogenic flood hazards
  • Flood risk assessments in urban areas
  • Mitigation measures against flooding in urban environments
  • Relationship between rainfall and runoff

Dr. Stefanos Stefanidis
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 1600 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

  • flood modeling
  • flash floods
  • flood risk analysis

Published Papers (4 papers)

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Research

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Open AccessArticle
Retrospective Dynamic Inundation Mapping of Hurricane Harvey Flooding in the Houston Metropolitan Area Using High-Resolution Modeling and High-Performance Computing
Water 2019, 11(3), 597; https://doi.org/10.3390/w11030597
Received: 24 December 2018 / Revised: 15 March 2019 / Accepted: 16 March 2019 / Published: 22 March 2019
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Abstract
Hurricane Harvey was one of the most extreme weather events to occur in Texas, USA; there was a huge amount of urban flooding in the city of Houston and the adjoining coastal areas. In this study, we reanalyze the spatiotemporal evolution of inundation [...] Read more.
Hurricane Harvey was one of the most extreme weather events to occur in Texas, USA; there was a huge amount of urban flooding in the city of Houston and the adjoining coastal areas. In this study, we reanalyze the spatiotemporal evolution of inundation during Hurricane Harvey using high-resolution two-dimensional urban flood modeling. This study’s domain includes the bayou basins in and around the Houston metropolitan area. The flood model uses the dynamic wave method and terrain data of 10-m resolution. It is forced by radar-based quantitative precipitation estimates. To evaluate the simulated inundation, on-site photos and water level observations were used. The inundation extent and severity are estimated by combining the retrieved water depths, images collected from the impacted area, and high-resolution terrain data. The simulated maximum inundation extent, which is frequently found outside of the designated flood zones, points out the importance of capturing multi-scale hydrodynamics in the built environment under extreme rainfall for effective flood risk and emergency management. Full article
(This article belongs to the Special Issue Flash Floods in Urban Areas)
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Open AccessArticle
Application of Fuzzy TOPSIS to Flood Hazard Mapping for Levee Failure
Water 2019, 11(3), 592; https://doi.org/10.3390/w11030592
Received: 31 January 2019 / Revised: 18 March 2019 / Accepted: 18 March 2019 / Published: 21 March 2019
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Abstract
This paper proposes a new approach to consider the uncertainties for constructing flood hazard maps for levee failure. The flood depth, velocity, and arrival time were estimated by the 2-Dimensional model and were considered as flood indices for flood hazard mapping. Each flood [...] Read more.
This paper proposes a new approach to consider the uncertainties for constructing flood hazard maps for levee failure. The flood depth, velocity, and arrival time were estimated by the 2-Dimensional model and were considered as flood indices for flood hazard mapping. Each flood index predicted from the 2-D flood analysis based on several scenarios was fuzzified to reflect the uncertainties of the indices. The fuzzified flood indices were integrated using the Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), resulting in a single graded flood hazard map. This methodology was applied to the Gam river in South Korea and confirmed that the Fuzzy MCDM (Multiple Criteria Decision Making) technique can be used to produce flood hazard maps. The flood hazard map produced in this study compared with the current flood hazard map of MOLIT (Ministry of Land, Infrastructure and Transports). This study found that the proposed methodology was more advantageous than the current methods with regard to the accuracy and grading of the flood areas, as well as in regard to an integrated single map. This report is expected to be expand upon other floods, including dam failure and urban flooding. Full article
(This article belongs to the Special Issue Flash Floods in Urban Areas)
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Review

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Open AccessReview
Recommendations for Improving Integration in National End-to-End Flood Forecasting Systems: An Overview of the FFIR (Flooding From Intense Rainfall) Programme
Water 2019, 11(4), 725; https://doi.org/10.3390/w11040725
Received: 13 March 2019 / Revised: 29 March 2019 / Accepted: 2 April 2019 / Published: 8 April 2019
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Abstract
Recent surface-water and flash floods have caused millions of pounds worth of damage in the UK. These events form rapidly and are difficult to predict due to their short-lived and localised nature. The interdisciplinary Flooding From Intense Rainfall (FFIR) programme investigated the feasibility [...] Read more.
Recent surface-water and flash floods have caused millions of pounds worth of damage in the UK. These events form rapidly and are difficult to predict due to their short-lived and localised nature. The interdisciplinary Flooding From Intense Rainfall (FFIR) programme investigated the feasibility of enhancing the integration of an end-to-end forecasting system for flash and surface-water floods to help increase the lead time for warnings for these events. Here we propose developments to the integration of an operational end-to-end forecasting system based on the findings of the FFIR programme. The suggested developments include methods to improve radar-derived rainfall rates and understanding of the uncertainty in the position of intense rainfall in weather forecasts; the addition of hydraulic modelling components; and novel education techniques to help lead to effective dissemination of flood warnings. We make recommendations for future advances such as research into the propagation of uncertainty throughout the forecast chain. We further propose the creation of closer bonds to the end users to allow for an improved, integrated, end-to-end forecasting system that is easily accessible for users and end users alike, and will ultimately help mitigate the impacts of flooding from intense rainfall by informed and timely action. Full article
(This article belongs to the Special Issue Flash Floods in Urban Areas)
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Other

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Open AccessTechnical Note
Extraction of Urban Waterlogging Depth from Video Images Using Transfer Learning
Water 2018, 10(10), 1485; https://doi.org/10.3390/w10101485
Received: 25 September 2018 / Revised: 18 October 2018 / Accepted: 19 October 2018 / Published: 21 October 2018
Cited by 1 | PDF Full-text (2277 KB) | HTML Full-text | XML Full-text
Abstract
Urban flood control requires real-time and spatially detailed information regarding the waterlogging depth over large areas, but such information cannot be effectively obtained by the existing methods. Video supervision equipment, which is readily available in most cities, can record urban waterlogging processes in [...] Read more.
Urban flood control requires real-time and spatially detailed information regarding the waterlogging depth over large areas, but such information cannot be effectively obtained by the existing methods. Video supervision equipment, which is readily available in most cities, can record urban waterlogging processes in video form. These video data could be a valuable data source for waterlogging depth extraction. The present paper is aimed at demonstrating a new approach to extract urban waterlogging depths from video images based on transfer learning and lasso regression. First, a transfer learning model is used to extract feature vectors from a video image set of urban waterlogging. Second, a lasso regression model is trained with these feature vectors and employed to calculate the waterlogging depth. Two case studies in China were used to evaluate the proposed method, and the experimental results illustrate the effectiveness of the method. This method can be applied to video images from widespread cameras in cities, so that a powerful urban waterlogging monitoring network can be formed. Full article
(This article belongs to the Special Issue Flash Floods in Urban Areas)
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