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Management of the flood Disaster and Assessment their damaged areas using Remote Sensing and GIS Techniques: A Case Study of Tigris River – Maysan Governorate, Iraq

EasyChair Preprint 5155

12 pagesDate: March 16, 2021

Abstract

Flood is the most widespread hazard across the world. Its management is a source of concern for all decision makers. During Spring 2019, this phenomenon occurred in Iraq, especially in the Governorate of Maysan, where the amount of water flowing into Tigris River increased. This led to rise the river level as a result of heavy and close periods of rain, in Maysan Governorate, the drainage quantities of water have been increased from Kut Dam. Remote Sensing techniques and the Geographic Information System (GIS) environment are used for the purpose of assessing the damage areas that resulting from flood and torrent in Maysan Governorate, which based on Sentinel-2 multispectral imagery data, by extracting the NDVI and NDWI values. Also, for the purpose of managing and reducing the volume of torrent and potential flood in the future, SRTM satellite is utilized to great hydrologic model based on the Arc Hydro tool in GIS environment to suggest a flood escape location. A couple hydraulic model (One Dimension (1D) and Two Dimension (2D)) is performed using HEC-Ras software for Maysan Governorate at the site of the proposed escape to determine the size of flood in the flood shelter. Accordingly, a flood map is produced for Maysan Governorate using the outputs from the analysis process and depending on the GIS environment.

Keyphrases: DEM, Flood hazard, GIS, NDVI, NDWI

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:5155,
  author    = {Khalid Wadeea and Hussein Sabah Jaber and Zainab Fakhri Merzah},
  title     = {Management of the flood Disaster and Assessment their damaged areas using Remote Sensing and GIS Techniques: A Case Study of Tigris River – Maysan Governorate, Iraq},
  howpublished = {EasyChair Preprint 5155},
  year      = {EasyChair, 2021}}
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