Cargando…

Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study

Climate extreme events such as floods and droughts in any area have a significant impact on human life, infrastructure, agriculture, and the economy. In the last two years, flash floods caused by heavy rainstorms have become frequent and destructive in many catchments in Northern Iraq. The present s...

Descripción completa

Detalles Bibliográficos
Autores principales: Ahmed, Alaa, Al Maliki, Ali, Hashim, Bassim, Alshamsi, Dalal, Arman, Hasan, Gad, Ahmed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366121/
https://www.ncbi.nlm.nih.gov/pubmed/37488264
http://dx.doi.org/10.1038/s41598-023-39290-4
_version_ 1785077101820379136
author Ahmed, Alaa
Al Maliki, Ali
Hashim, Bassim
Alshamsi, Dalal
Arman, Hasan
Gad, Ahmed
author_facet Ahmed, Alaa
Al Maliki, Ali
Hashim, Bassim
Alshamsi, Dalal
Arman, Hasan
Gad, Ahmed
author_sort Ahmed, Alaa
collection PubMed
description Climate extreme events such as floods and droughts in any area have a significant impact on human life, infrastructure, agriculture, and the economy. In the last two years, flash floods caused by heavy rainstorms have become frequent and destructive in many catchments in Northern Iraq. The present study aims to examine flash floods in the Erbil region, Northern Iraq using Remote sensing (RS), Geographic Information System (GIS), and Principal Component Analysis (PCA) for geomorphic data. PCA results revealed that 12 geomorphic parameters exhibited a significant correlation with two different statistical components. To facilitate practical application, ranks are assigned based on the calculated parameters for flood susceptibility mapping. Out of the 24 basins in the current study, three basins (16, 3, and 14) have the highest geomorphometric values (36–39), indicating the zone most susceptible to flash floods and making up a maximum area of 38.58% of the studied region. Six basins (4, 8, 9, 10, 12, and 15), which have geomorphometric values between 30 and 35 and cover a land area of 27.86%, are the most moderately vulnerable to floods. The remaining basins, which make up 33.47% of the research, are occasionally subject to floods and have geomorphometric scores below 30. The precision of the flood susceptibility mapping was validated using the bifurcation ratio and drainage density relationship as well as past flood damages, such as economic losses and human casualties. Most of the recorded injuries and fatalities took place in areas that were particularly prone to severe past flooding. Additionally, the investigation revealed that 44.56% of all populated areas are located in extremely vulnerable basins. The findings demonstrate a notable correlation between the identified flood-susceptible areas and the occurrence of past flood damage.
format Online
Article
Text
id pubmed-10366121
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-103661212023-07-26 Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study Ahmed, Alaa Al Maliki, Ali Hashim, Bassim Alshamsi, Dalal Arman, Hasan Gad, Ahmed Sci Rep Article Climate extreme events such as floods and droughts in any area have a significant impact on human life, infrastructure, agriculture, and the economy. In the last two years, flash floods caused by heavy rainstorms have become frequent and destructive in many catchments in Northern Iraq. The present study aims to examine flash floods in the Erbil region, Northern Iraq using Remote sensing (RS), Geographic Information System (GIS), and Principal Component Analysis (PCA) for geomorphic data. PCA results revealed that 12 geomorphic parameters exhibited a significant correlation with two different statistical components. To facilitate practical application, ranks are assigned based on the calculated parameters for flood susceptibility mapping. Out of the 24 basins in the current study, three basins (16, 3, and 14) have the highest geomorphometric values (36–39), indicating the zone most susceptible to flash floods and making up a maximum area of 38.58% of the studied region. Six basins (4, 8, 9, 10, 12, and 15), which have geomorphometric values between 30 and 35 and cover a land area of 27.86%, are the most moderately vulnerable to floods. The remaining basins, which make up 33.47% of the research, are occasionally subject to floods and have geomorphometric scores below 30. The precision of the flood susceptibility mapping was validated using the bifurcation ratio and drainage density relationship as well as past flood damages, such as economic losses and human casualties. Most of the recorded injuries and fatalities took place in areas that were particularly prone to severe past flooding. Additionally, the investigation revealed that 44.56% of all populated areas are located in extremely vulnerable basins. The findings demonstrate a notable correlation between the identified flood-susceptible areas and the occurrence of past flood damage. Nature Publishing Group UK 2023-07-24 /pmc/articles/PMC10366121/ /pubmed/37488264 http://dx.doi.org/10.1038/s41598-023-39290-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ahmed, Alaa
Al Maliki, Ali
Hashim, Bassim
Alshamsi, Dalal
Arman, Hasan
Gad, Ahmed
Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study
title Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study
title_full Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study
title_fullStr Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study
title_full_unstemmed Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study
title_short Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study
title_sort flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, erbil area in northern iraq as a case study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366121/
https://www.ncbi.nlm.nih.gov/pubmed/37488264
http://dx.doi.org/10.1038/s41598-023-39290-4
work_keys_str_mv AT ahmedalaa floodsusceptibilitymappingutilizingtheintegrationofgeospatialandmultivariatestatisticalanalysiserbilareainnortherniraqasacasestudy
AT almalikiali floodsusceptibilitymappingutilizingtheintegrationofgeospatialandmultivariatestatisticalanalysiserbilareainnortherniraqasacasestudy
AT hashimbassim floodsusceptibilitymappingutilizingtheintegrationofgeospatialandmultivariatestatisticalanalysiserbilareainnortherniraqasacasestudy
AT alshamsidalal floodsusceptibilitymappingutilizingtheintegrationofgeospatialandmultivariatestatisticalanalysiserbilareainnortherniraqasacasestudy
AT armanhasan floodsusceptibilitymappingutilizingtheintegrationofgeospatialandmultivariatestatisticalanalysiserbilareainnortherniraqasacasestudy
AT gadahmed floodsusceptibilitymappingutilizingtheintegrationofgeospatialandmultivariatestatisticalanalysiserbilareainnortherniraqasacasestudy