Repository logo
 
Publication

Improving a DSM Obtained by Unmanned Aerial Vehicles for Flood Modelling

2017-12Journal article Open access
Simple item page
dc.contributor.authorMourato, Sandra
dc.contributor.authorFernandez, Paulo
dc.contributor.authorPereira, Luísa
dc.contributor.authorMoreira, Madalena
dc.date.accessioned2025-05-26T10:45:31Z
dc.date.available2025-05-26T10:45:31Z
dc.date.issued2017-12
dc.description.abstractAccording to the EU flood risks directive, flood hazard map must be used to assess the flood risk. These maps can be developed with hydraulic modelling tools using a Digital Surface Runoff Model (DSRM). During the last decade, important evolutions of the spatial data processing has been developed which will certainly improve the hydraulic models results. Currently, images acquired with Red/Green/Blue (RGB) camera transported by Unmanned Aerial Vehicles (UAV) are seen as a good alternative data sources to represent the terrain surface with a high level of resolution and precision. The question is if the digital surface model obtain with this data is adequate enough for a good representation of the hydraulics flood characteristics. For this purpose, the hydraulic model HEC-RAS was run with 4 different DSRM for an 8.5 km reach of the Lis River in Portugal. The computational performance of the 4 modelling implementations is evaluated. Two hydrometric stations water level records were used as boundary conditions of the hydraulic model. The records from a third hydrometric station were used to validate the optimal DSRM. The HEC-RAS results had the best performance during the validation step were the ones where the DSRM with integration of the two altimetry data sources.eng
dc.description.sponsorshipThe data of this work is funded by POCTEP - European Regional Development Fund under the project Territorial and Environmental Observatory of the Cross-border Region composed by Alentejo and Centro Regions of Portugal and Extremadura Region of Spain (OTALEX-C). This work is funded by National Fund through FCT – Foundation for Science and Technology under the Project UID/AGR/00115/2013.
dc.identifier.citationSandra Mourato et al 2017 IOP Conf. Ser.: Earth Environ. Sci. 95 022014, 10.1088/1755-1315/95/2/022014
dc.identifier.doi10.1088/1755-1315/95/2/022014
dc.identifier.issn1755-1307
dc.identifier.issn1755-1315
dc.identifier.urihttp://hdl.handle.net/10400.8/12978
dc.language.isoeng
dc.peerreviewedn/a
dc.publisherIOP Publishing
dc.relationUID/AGR/00115/2013
dc.relation.ispartofIOP Conference Series: Earth and Environmental Science
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleImproving a DSM Obtained by Unmanned Aerial Vehicles for Flood Modellingeng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.volume95
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameMourato
person.givenNameSandra
person.identifier.ciencia-idC81B-16CD-EDFE
person.identifier.orcid0000-0001-9545-2584
person.identifier.scopus-author-id56387285400
relation.isAuthorOfPublication66af47bd-4c47-48ec-8f3a-f6ce092514db
relation.isAuthorOfPublication.latestForDiscovery66af47bd-4c47-48ec-8f3a-f6ce092514db

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Mourato_2017_IOP_Conf._Ser.__Earth_Environ._Sci._95_022014.pdf
Size:
3.14 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.32 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ESTG - Artigos em revistas internacionais