Modelling Flood Hazards and Management for Environmental Sustainability

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

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 3905

Special Issue Editors


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Guest Editor
Department of Geography, The University of Burdwan, West Bengal, India
Interests: remote sensing; hazard modeling; water resource management; climate change; land use change; geomorphology; soil water dynamics; extreme events (flood, landslide, drought); forest health and modeling

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Guest Editor
K. Banerjee Center of Atmospheric & Ocean Studies, IIDS, Nehru Science Center, University of Allahabad, UP, Allahabad, India
Interests: agriculture; climate change; land use/land cover change dynamics; remote sensing; soil moisture; water quality; hydrological modeling; water resource management
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Special Issue Information

Dear Colleagues,

Floods are extreme and frequent types of natural hazards that cost human life and result in major economic losses. Flooding occurs when water cannot be stored or adjusted in a normal system of drainage. Floods are a threat to people, infrastructure, and settlements. The higher the risk of flooding is, the greater the amount of damage caused. Flooding can seriously damage a wide variety of aspects, including the economy, human life, transport, environment, and infrastructure. Over the last decade, floods have tended to occur on a very regular basis as environmental destruction, such as population growth, deforestation, and urbanization, has increased. Susceptibility to floods is a critical challenge to disaster preparedness and flood control approaches. The objective of this Special Issue of Water is to collect articles (original research articles, review articles, and case studies) to provide insight into the applications of remote sensing and remote sensing–GIS-based techniques for addressing critical flood hazard issues and their management, including assessment and modelling on a wide range of spatial and temporal scales.

This open-access Special Issue invites high-quality and innovative scientific articles, including innovative and cutting-edge research on the use of remote sensing techniques and data from any platform (ground sensing, satellite, aircraft, drones, etc.) to study critical water-related issues. Potential topics include but are not limited to the following:

  • Water resource management;
  • Sustainable water resource management;
  • Deep learning application in water resources;
  • Big data analytics in flood forecasting;
  • Machine learning approaches for flood modeling;
  • Impact of climate change on urban flood;
  • Data driven approaches for flood mapping and modeling;
  • Novel methods for improving flood research.

Dr. Subodh Ch Pal
Dr. Sudhir K. Singh
Guest Editors

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Keywords

  • flood modeling
  • urban flood
  • flash flood forecasting
  • quantitative precipitation estimation
  • climate change
  • data fusion
  • data mining
  • sensor networks
  • hydrologic model
  • hydraulic model
  • machine learning
  • GIS

Published Papers (1 paper)

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Research

22 pages, 16615 KiB  
Article
Impact Assessment of Flood Damage in Urban Areas Using RCP 8.5 Climate Change Scenarios and Building Inventory
by Dong-Ho Kang, Dong-Ho Nam, Se-Jin Jeung and Byung-Sik Kim
Water 2021, 13(6), 756; https://doi.org/10.3390/w13060756 - 10 Mar 2021
Cited by 4 | Viewed by 3257
Abstract
Korea has frequent flood damage due to localized torrential rain and typhoons as a result of climate change, which causes many casualties and property damage. In particular, much damage occurs due to urban inundation caused by stream flooding as a result of climate [...] Read more.
Korea has frequent flood damage due to localized torrential rain and typhoons as a result of climate change, which causes many casualties and property damage. In particular, much damage occurs due to urban inundation caused by stream flooding as a result of climate change. Thus, this study aims to analyze the effect of climate change on flood damage targeting the Wonjucheon basin, which is an urban stream flowing the city. For future rainfall data, RCP (Representative Concentration Pathways) 8.5 climate change scenario data was used, statistical detailed using SDQDM (Spatial Disaggregation with Quantile Delta Mapping) techniques, and daily data was downscaled using Copula model. In general, the flood damage rate is calculated by using the area ratio according to the land use in the administrative district, but in this study, the flood damage rate is calculated using the flood damage rate proposed in the multi-dimensional flood damage analysis using Building Inventory. Using the created future rainfall data and current data, the runoff in the Wonjucheon basin, Wonju-si, South Korea, by rainfall frequency was calculated through the Spatial Runoff Assessment Tool (S-RAT) model, which was a distributed rainfall-runoff model. The runoff was calculated using 100-year and 200-year frequency rainfalls for a four-hour duration and the flood damage area was calculated by applying the calculated runoff to the Flo-2D model, was developed by Federal Emergency Management Agency (FEMA) in United State of America, which was a flood inundation model. As a result of calculating the amount of discharge, it was analyzed that the average amount of discharge increased by 16% over the 100-year, 200-year frequency. The calculated result of the flood damage area was analyzed and the analysis results showed that the future flood damage area increased by around 30% at the 100-year frequency and around 15% at the 200-year frequency. The estimated flood damage by rainfall frequency was calculated using the flood damage area by frequency and multi-dimensional analysis, and the analysis result exhibited that the damage increased by around 23% at the 100-year frequency and around 45% at the 200-year frequency. Full article
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