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dc.contributor.authorFaridani, F
dc.contributor.authorBakhtiari, S
dc.contributor.authorFaridhosseini, A
dc.contributor.authorGibson, MJ
dc.contributor.authorFarmani, R
dc.contributor.authorLasaponara, R
dc.date.accessioned2020-09-09T12:06:01Z
dc.date.issued2020-09-08
dc.description.abstractThere is not enough data and computational power for conventional flood mapping methods in many parts of the world, thus fast and low-data-demanding methods are very useful in facing the disaster. This paper presents an innovative procedure for estimating flood extent and depth using only DEM SRTM 30 m and the Geomorphic Flood Index (GFI). The Geomorphologic Flood Assessment (GFA) tool which is the corresponding application of the GFI in QGIS is implemented to achieved the results in three basins in Iran. Moreover, the novel concept of Intensity-Duration-Frequency-Area (IDFA) curves is introduced to modify the GFI model by imposing a constraint on the maximum hydrologically contributing area of a basin. The GFA model implements the linear binary classification algorithm to classify a watershed into flooded and non-flooded areas using an optimized GFI threshold that minimizes the errors with a standard flood map of a small region in the study area. The standard hydraulic model envisaged for this study is the Cellular Automata Dual-DraInagE Simulation (CADDIES) 2D model which employs simple transition rules and a weight-based system rather than complex shallow water equations allowing fast flood modelling for large-scale problems. The results revealed that the floodplains generated by the GFI has a good agreement with the standard maps, especially in the fluvial rivers. However, the performance of the GFI decreases in the less steep and alluvial rivers. With some overestimation, the GFI model is also able to capture the general trend of water depth variations in comparison with the CADDIES-2D flood depth map. The modifications made in the GFI model, to confine the maximum precipitable area through implementing the IDFAs, improved the classification of flooded area and estimation of water depth in all study areas. Finally, the calibrated GFI thresholds were used to achieve the complete 100-year floodplain maps of the study areas.en_GB
dc.description.sponsorshipUniversity of Basilicataen_GB
dc.description.sponsorshipCNR-IMAAen_GB
dc.description.sponsorshipOpenet Technologiesen_GB
dc.description.sponsorshipRoyal Academy of Engineering (RAE)en_GB
dc.identifier.citationVol. 12 (18), article 7371en_GB
dc.identifier.doi10.3390/su12187371
dc.identifier.grantnumberIF\192057en_GB
dc.identifier.urihttp://hdl.handle.net/10871/122798
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectCADDIES-2Den_GB
dc.subjectDEM SRTM 30 men_GB
dc.subjectfloodplain delineationen_GB
dc.subjectgeomorphic flood indexen_GB
dc.subjectIDFA curvesen_GB
dc.subjectlinear binary classificationen_GB
dc.titleEstimating flood characteristics using geomorphologic flood index with regards to rainfall intensity-duration-frequency-area curves and CADDIES-2D model in three Iranian basinsen_GB
dc.typeArticleen_GB
dc.date.available2020-09-09T12:06:01Z
dc.identifier.issn1937-0695
dc.descriptionThis is the final version. Available on open access from MDPI via the DOI in this recorden_GB
dc.identifier.journalSustainabilityen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-08-31
exeter.funder::Royal Academy of Engineering (RAE)en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-08-31
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-09-09T11:38:38Z
refterms.versionFCDAM
refterms.dateFOA2020-09-09T12:06:06Z
refterms.panelBen_GB


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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).