Detection of flood vulnerable areas in urban basins using multi-criteria analysis and geospatial tools: a case study from eastern Mediterranean
The Eastern Mediterranean region is affected by devastating annual flood events that cause massive socio-economic losses, especially in Syria. The displacement of thousands of refugees to the western region of Syria has led to tremendous pressures on the landscape, increasing the flood vulnerability...
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description | The Eastern Mediterranean region is affected by devastating annual flood events that cause massive socio-economic losses, especially in Syria. The displacement of thousands of refugees to the western region of Syria has led to tremendous pressures on the landscape, increasing the flood vulnerability. Moreover, the absence of administrative control over the landscape increased the economic losses caused by flood events. Producing flood vulnerability maps is considered one of the most important spatial strategies that will provide the essential basis for flood hazard management. The present study sought to detect flood vulnerability areas in the Al-Fawar river basin, western Syria, utilising the combination of the Analytical Hierarchy Process (AHP) method and the Geographical Information System (GIS) environment. To accomplish this purpose, nine factors influencing flood vulnerability were appointed: rainfall, elevation, slope, Topographic Wetness Index (TWI), drainage density, distance from the river, soil resistance, Land Use/Land Cover (LULC) and lithology. Importantly, A total of 129 flood events were specified as a validation dataset for the accuracy inspection, which was conducted utilising the Area Under the Curve (AUC). The results demonstrate that more than 32% of the study basin is regarded high and very high flooding threat. These parts are found in the central and western parts of the study area along the river courses. The AUC value of 0.868 implies the flood vulnerability map's reliable and accurate predictive ability constructed utilising AHP. The current approach implemented denotes a productive tool for LULC planners and policymakers to develop managing plans for flood hazards in the environmental rehabilitation phase in Syria. |
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The displacement of thousands of refugees to the western region of Syria has led to tremendous pressures on the landscape, increasing the flood vulnerability. Moreover, the absence of administrative control over the landscape increased the economic losses caused by flood events. Producing flood vulnerability maps is considered one of the most important spatial strategies that will provide the essential basis for flood hazard management. The present study sought to detect flood vulnerability areas in the Al-Fawar river basin, western Syria, utilising the combination of the Analytical Hierarchy Process (AHP) method and the Geographical Information System (GIS) environment. To accomplish this purpose, nine factors influencing flood vulnerability were appointed: rainfall, elevation, slope, Topographic Wetness Index (TWI), drainage density, distance from the river, soil resistance, Land Use/Land Cover (LULC) and lithology. Importantly, A total of 129 flood events were specified as a validation dataset for the accuracy inspection, which was conducted utilising the Area Under the Curve (AUC). The results demonstrate that more than 32% of the study basin is regarded high and very high flooding threat. These parts are found in the central and western parts of the study area along the river courses. The AUC value of 0.868 implies the flood vulnerability map's reliable and accurate predictive ability constructed utilising AHP. 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The displacement of thousands of refugees to the western region of Syria has led to tremendous pressures on the landscape, increasing the flood vulnerability. Moreover, the absence of administrative control over the landscape increased the economic losses caused by flood events. Producing flood vulnerability maps is considered one of the most important spatial strategies that will provide the essential basis for flood hazard management. The present study sought to detect flood vulnerability areas in the Al-Fawar river basin, western Syria, utilising the combination of the Analytical Hierarchy Process (AHP) method and the Geographical Information System (GIS) environment. To accomplish this purpose, nine factors influencing flood vulnerability were appointed: rainfall, elevation, slope, Topographic Wetness Index (TWI), drainage density, distance from the river, soil resistance, Land Use/Land Cover (LULC) and lithology. Importantly, A total of 129 flood events were specified as a validation dataset for the accuracy inspection, which was conducted utilising the Area Under the Curve (AUC). The results demonstrate that more than 32% of the study basin is regarded high and very high flooding threat. These parts are found in the central and western parts of the study area along the river courses. The AUC value of 0.868 implies the flood vulnerability map's reliable and accurate predictive ability constructed utilising AHP. The current approach implemented denotes a productive tool for LULC planners and policymakers to develop managing plans for flood hazards in the environmental rehabilitation phase in Syria.</description><subject>Analytic hierarchy process</subject><subject>basins</subject><subject>Biogeosciences</subject><subject>case studies</subject><subject>data collection</subject><subject>drainage</subject><subject>Drainage density</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>ecological restoration</subject><subject>Economic impact</subject><subject>Economics</subject><subject>Environmental Science and Engineering</subject><subject>Flood hazards</subject><subject>Flood management</subject><subject>Flood predictions</subject><subject>Floods</subject><subject>Geochemistry</subject><subject>Geographic information systems</subject><subject>Geographical information systems</subject><subject>Geology</subject><subject>Hierarchies</subject><subject>Hydrology/Water Resources</subject><subject>Information processing</subject><subject>Information systems</subject><subject>Inspection</subject><subject>Land cover</subject><subject>Land use</subject><subject>landscapes</subject><subject>Lithology</subject><subject>Mediterranean region</subject><subject>Multiple criterion</subject><subject>Original Article</subject><subject>rain</subject><subject>Rainfall</subject><subject>Refugees</subject><subject>River basins</subject><subject>Rivers</subject><subject>Socioeconomic aspects</subject><subject>socioeconomics</subject><subject>soil</subject><subject>Soil resistance</subject><subject>Syria</subject><subject>Terrestrial Pollution</subject><subject>topography</subject><subject>watersheds</subject><subject>Wetness index</subject><issn>1866-6280</issn><issn>1866-6299</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kU9rFTEUxQexYGn7BboKuHEzNn9mMok7qX8qVNx0H-5k7jxS8pJnbkZ4n8KvbOoTBRfNIjmQ3zncy-m6a8HfCs6nGxJS67HncuiFMFz0_EV3LozWvZbWvvyrDX_VXRE98naUUJbr8-7nB6zoa8iJ5ZWtMeeF_dhiwgJzRAYFgVhIbCszJDYDhURsa_eO7bdYQ-9LqFgCMEgQjxSoiYXtMNMBaoDIas6R3jFgHggZ1W05srXkPWvJzZnYV1yeIgokhHTZna0QCa_-vBfdw6ePD7d3_f23z19u39_3XipVe2m0MnoRilsOWslxQmn86EGgV0Jj-5knYxczrSsfgOOiYZwHbrUctB3VRffmFHso-fuGVN0-kMcY2xB5I6fEqCYzGW4a-vo_9DFvpS3bKG6NHcU4qEbJE-VLJiq4ukMJeyhHJ7h7asmdWnKtJfe7JcebSZ1M1OC0w_Iv-hnXL29flhA</recordid><startdate>20240901</startdate><enddate>20240901</enddate><creator>Abdo, Hazem Ghassan</creator><creator>Darwish, Kamal Srogy</creator><creator>Bindajam, Ahmed Ali</creator><creator>Niknam, Arman</creator><creator>Youssef, Youssef M.</creator><creator>Ahmed, Mohamed Fatahalla Mohamed</creator><creator>Mallick, Javed</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0002-8927-7238</orcidid><orcidid>https://orcid.org/0000-0001-9283-3947</orcidid></search><sort><creationdate>20240901</creationdate><title>Detection of flood vulnerable areas in urban basins using multi-criteria analysis and geospatial tools: a case study from eastern Mediterranean</title><author>Abdo, Hazem Ghassan ; 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Importantly, A total of 129 flood events were specified as a validation dataset for the accuracy inspection, which was conducted utilising the Area Under the Curve (AUC). The results demonstrate that more than 32% of the study basin is regarded high and very high flooding threat. These parts are found in the central and western parts of the study area along the river courses. The AUC value of 0.868 implies the flood vulnerability map's reliable and accurate predictive ability constructed utilising AHP. The current approach implemented denotes a productive tool for LULC planners and policymakers to develop managing plans for flood hazards in the environmental rehabilitation phase in Syria.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s12665-024-11801-0</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-8927-7238</orcidid><orcidid>https://orcid.org/0000-0001-9283-3947</orcidid></addata></record> |
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subjects | Analytic hierarchy process basins Biogeosciences case studies data collection drainage Drainage density Earth and Environmental Science Earth Sciences ecological restoration Economic impact Economics Environmental Science and Engineering Flood hazards Flood management Flood predictions Floods Geochemistry Geographic information systems Geographical information systems Geology Hierarchies Hydrology/Water Resources Information processing Information systems Inspection Land cover Land use landscapes Lithology Mediterranean region Multiple criterion Original Article rain Rainfall Refugees River basins Rivers Socioeconomic aspects socioeconomics soil Soil resistance Syria Terrestrial Pollution topography watersheds Wetness index |
title | Detection of flood vulnerable areas in urban basins using multi-criteria analysis and geospatial tools: a case study from eastern Mediterranean |
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