Special Issue "Recent Advances and New Directions in Flood Forecasting, Modeling, and Mapping"

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

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editor

Guest Editor
Prof. Venkatesh Merwade Website E-Mail
Lyles School of Civil Engineering, Purdue University, USA
Interests: surface water hydrology; GIS applications for water resources; flood modeling and mapping; cyberinfrastructure for water resources

Special Issue Information

Dear Colleagues,

With the increasing frequency of high magnitude floods around the globe, there is a greater need to provide accurate information on the potential impacts of such floods in the future. Flood modeling and mapping has evolved over the last few decades from simulating single river reaches, to millions of reaches at continental scales. Similarly, research on issues such as uncertainty quantification, data resolution, model structure, scale, and dimensionality, continues to advance the science of flood forecasting, modeling, and mapping. With advances in weather forecasting, the desire to have near-real-time flood maps at street level is also growing. Recently, the need for large-scale holistic flood risk management has driven the scientific community towards a systems-based approach to flood modeling, by incorporating feedbacks between the atmospheric, hydrologic, and societal processes. The primary goal of this Special Issue is to take stock of all these new developments for charting the next phase of flood modeling research, by using the newly available technology, data, and cyber–physical systems.

 

Topics that may be relevant to this Special Issue, but are not limited to, include:

  • Theories and strategies for hyper-resolution urban flood modeling and maping;
  • Issues related to the mapping of flood inundation from extreme events such as typhoons and hurricanes;
  • Application of artificial intelligence, big data, and cyberinfrastructure for flood modeling and research;
  • Data driven approaches for flood forecasting, modeling, and mapping;
  • Novel methods for incorporating crowdsourcing or citizen science for improving flood research;
  • Strategies for improving flood modeling and mapping for data sparse regions.

Prof. Venkatesh Merwade
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

  • Urban flood modeling
  • Hyper resolution flood modeling
  • Big data for floods
  • Citizen science and crowd sourcing
  • Cyberinfrastructure and artificial intelligence
  • Flood inundation mapping

Published Papers (1 paper)

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Research

Open AccessArticle
A Study on the Improvement of Flood Forecasting Techniques in Urban Areas by Considering Rainfall Intensity and Duration
Water 2019, 11(9), 1883; https://doi.org/10.3390/w11091883 - 10 Sep 2019
Abstract
Frequent localized torrential rains, excessive population density in urban areas, and increased impervious areas have led to massive flood damage that has been causing overloading of drainage systems (watersheds, reservoirs, drainage pump sites, etc.). Flood concerns are raised around the world in the [...] Read more.
Frequent localized torrential rains, excessive population density in urban areas, and increased impervious areas have led to massive flood damage that has been causing overloading of drainage systems (watersheds, reservoirs, drainage pump sites, etc.). Flood concerns are raised around the world in the events of rain. Flood forecasting, a typical nonstructural measure, was developed to help prevent repetitive flood damage. However, it is difficult to apply flood prediction techniques using training processes because training needs to be applied at every usage. Other techniques that use predicted rainfall data are also not appropriate for small watershed, such as single drainage area. Thus, in this paper, a flood prediction method is proposed by improving four criteria (50% water level, 70% water level, 100% water level, and first flooding of water pipes) in an attempt to reduce flooding in urban areas. The four criteria nodes are generated using a rainfall runoff simulation with synthetic rainfall at various durations. When applying real-time rainfall data, these nodes have the advantage of simple application. The improved flood nomograph made in this way is expected to help predict and prepare for rainstorms that can potentially cause flood damage. Full article
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