Special Issue "Flash-Flood Susceptibility, Forecast and Warning"

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

Deadline for manuscript submissions: 30 September 2021.

Special Issue Editor

Dr. Romulus Costache
E-Mail Website
Guest Editor
Flash-Flood Forecast Department, National Institute of Hydrology and Water Management, București-Ploiești Road, 97E, 1st District, 013686, Bucharest, Romania
Interests: flash-flood susceptibility mapping; flash-flood forecast and warning; artificial intelligence; hydrology; surface runoff modelling
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Special Issue Information

Dear Colleagues,

Flash-floods, due to their unexpected nature, can cause severe economic damages and loss of human life. They may be caused either by extreme precipitation, by the failure of human-made structures, such as dams, or by complex water–snow interactions. Flash-flood early warning systems represent the most effective non-structural measure, which should be taken in order to mitigate the negative effects of these hydrological hazards. An efficient and operational flash-flood early warning system should be based on the following two major components: a map representing a very accuracte detection of flash-flood susceptible areas and a performant meteorological radar network, which are able detect the cloud systems that are likely to generate heavy rainfalls over the susceptible areas, and also to accurately estimate the rainfall amount and their accumulation.

In the light of the above-mentioned aspects, the main scope of this Special Issue is to collect the state of the art findings related to the application of newest techniques and software in order to estimate flash-flood susceptibity and the likelihood of heavy rainfall occurrence, and also the studies related to the development of new flash-flood early warning system. High-quality original research papers that present theoretical frameworks, methodologies, and applications of case studies from a single- or cross-country perspectives are welcome, as well as review articles.

Dr. Romulus Costache
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 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

  • flash-flood forecast systems
  • flash-flood susceptiblity
  • flash-flood warnings encoding
  • machine learning
  • geographic information systems
  • remote sesning
  • heavy rainfall
  • meteorological radar

Published Papers (2 papers)

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Research

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Article
Flood Susceptibility Assessment Using Novel Ensemble of Hyperpipes and Support Vector Regression Algorithms
Water 2021, 13(2), 241; https://doi.org/10.3390/w13020241 - 19 Jan 2021
Cited by 6 | Viewed by 1052
Abstract
Recurrent floods are one of the major global threats among people, particularly in developing countries like India, as this nation has a tropical monsoon type of climate. Therefore, flood susceptibility (FS) mapping is indeed necessary to overcome this type of natural hazard phenomena. [...] Read more.
Recurrent floods are one of the major global threats among people, particularly in developing countries like India, as this nation has a tropical monsoon type of climate. Therefore, flood susceptibility (FS) mapping is indeed necessary to overcome this type of natural hazard phenomena. With this in mind, we evaluated the prediction performance of FS mapping in the Koiya River basin, Eastern India. The present research work was done through preparation of a sophisticated flood inventory map; eight flood conditioning variables were selected based on the topography and hydro-climatological condition, and by applying the novel ensemble approach of hyperpipes (HP) and support vector regression (SVR) machine learning (ML) algorithms. The ensemble approach of HP-SVR was also compared with the stand-alone ML algorithms of HP and SVR. In relative importance of variables, distance to river was the most dominant factor for flood occurrences followed by rainfall, land use land cover (LULC), and normalized difference vegetation index (NDVI). The validation and accuracy assessment of FS maps was done through five popular statistical methods. The result of accuracy evaluation showed that the ensemble approach is the most optimal model (AUC = 0.915, sensitivity = 0.932, specificity = 0.902, accuracy = 0.928 and Kappa = 0.835) in FS assessment, followed by HP (AUC = 0.885) and SVR (AUC = 0.871). Full article
(This article belongs to the Special Issue Flash-Flood Susceptibility, Forecast and Warning)
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Review

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Review
An Overview of Flood Risk Analysis Methods
Water 2021, 13(4), 474; https://doi.org/10.3390/w13040474 - 11 Feb 2021
Viewed by 784
Abstract
Scientific papers present a wide range of methods of flood analysis and forecasting. Floods are a phenomenon with significant socio-economic implications, for which many researchers try to identify the most appropriate methodologies to analyze their temporal and spatial development. This research aims to [...] Read more.
Scientific papers present a wide range of methods of flood analysis and forecasting. Floods are a phenomenon with significant socio-economic implications, for which many researchers try to identify the most appropriate methodologies to analyze their temporal and spatial development. This research aims to create an overview of flood analysis and forecasting methods. The study is based on the need to select and group papers into well-defined methodological categories. The article provides an overview of recent developments in the analysis of flood methodologies and shows current research directions based on this overview. The study was performed taking into account the information included in the Web of Science Core Collection, which brought together 1326 articles. The research concludes with a discussion on the relevance, ease of application, and usefulness of the methodologies. Full article
(This article belongs to the Special Issue Flash-Flood Susceptibility, Forecast and Warning)
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