Identification of Flood-Prone Areas Using Geo-informatics: A Case Study of Erbil City, Kurdistan Region, Iraq

Global flood events, intensified by an intricate interplay of natural dynamics and human activities, pose severe environmental and safety threats, driving the demand for advanced vulnerability assessments. This research innovates with a holistic geo-informatics methodology, pinpointing flood-prone regions in Erbil City, Kurdistan Region, Iraq. It harnesses the Analytic Hierarchy Process and Geographic Information System synergies, enriched with insights from multispectral satellite observations, to conduct an exhaustive analysis of key flood susceptibility indicators. These encompass geological, hydrological, meteorological, and anthropogenic parameters, integrated into a robust Geographic Information System analytical matrix. Through strategic factor analysis and prioritization, the study distills a detailed flood susceptibility cartogram, classifying regional vulnerabilities into distinct risk echelons: high (encompassing 25%), moderate (38.1%), low (28.4%), and very low (8.5%). The final flood map highlights an acute susceptibility epicenter in the northeast, contrasting with the minimal threat southwest. This demarcation reaffirms the Analytic Hierarchy Process-Geographic Information System fusion's precision in translating multifaceted data into strategic intelligence, proving instrumental for scholars, administrative frameworks, and developmental strategists. The insights garnered are pivotal in sculpting informed urban development and flood counteractive blueprints, instrumental in mitigating flood repercussions and preserving ecological and human integrities.

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Publication Details

Journal
Iraqi Geological Journal
Published
2024-09-30
DOI
https://doi.org/10.46717/igj.57.2c.19ms-2024-9-27
Citations
8
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
2.26
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article

Identification of Flood-Prone Areas Using Geo-informatics: A Case Study of Erbil City, Kurdistan Region, Iraq

Kaiwan K. Fatah, Rebar Tahseen Mzuri, Yaseen T. Mustafa
8 citations
Iraqi Geological Journal
Flood Risk Assessment and Management
2.26
article

Identification of Flood-Prone Areas Using Geo-informatics: A Case Study of Erbil City, Kurdistan Region, Iraq

Kaiwan K. Fatah, Rebar Tahseen Mzuri, Yaseen T. Mustafa
article en
8 citations

Abstract

Global flood events, intensified by an intricate interplay of natural dynamics and human activities, pose severe environmental and safety threats, driving the demand for advanced vulnerability assessments. This research innovates with a holistic geo-informatics methodology, pinpointing flood-prone regions in Erbil City, Kurdistan Region, Iraq. It harnesses the Analytic Hierarchy Process and Geographic Information System synergies, enriched with insights from multispectral satellite observations, to conduct an exhaustive analysis of key flood susceptibility indicators. These encompass geological, hydrological, meteorological, and anthropogenic parameters, integrated into a robust Geographic Information System analytical matrix. Through strategic factor analysis and prioritization, the study distills a detailed flood susceptibility cartogram, classifying regional vulnerabilities into distinct risk echelons: high (encompassing 25%), moderate (38.1%), low (28.4%), and very low (8.5%). The final flood map highlights an acute susceptibility epicenter in the northeast, contrasting with the minimal threat southwest. This demarcation reaffirms the Analytic Hierarchy Process-Geographic Information System fusion's precision in translating multifaceted data into strategic intelligence, proving instrumental for scholars, administrative frameworks, and developmental strategists. The insights garnered are pivotal in sculpting informed urban development and flood counteractive blueprints, instrumental in mitigating flood repercussions and preserving ecological and human integrities.

Iraqi Geological Journal
University of Zakho (IQ), Salahaddin University-Erbil (IQ)
Openalex Percentile: Top 12%
Flood Risk Assessment and Management
2.26
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