Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/22440
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Morsy, Mona | - |
dc.contributor.author | Scholten, Thomas | - |
dc.contributor.author | Michaelides, Silas | - |
dc.contributor.author | Borg, Erik | - |
dc.contributor.author | Sherief, Youssef | - |
dc.contributor.author | Dietrich, Peter | - |
dc.date.accessioned | 2021-03-12T12:04:28Z | - |
dc.date.available | 2021-03-12T12:04:28Z | - |
dc.date.issued | 2021-02-02 | - |
dc.identifier.citation | Remote Sensing, 2021, vol. 13, no. 4, articl. no. 588 | en_US |
dc.identifier.issn | 2072-4292 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/22440 | - |
dc.description.abstract | The replenishment of aquifers depends mainly on precipitation rates, which is of vital importance for determining water budgets in arid and semi-arid regions. El-Qaa Plain in the Sinai Peninsula is a region that experiences constant population growth. This study compares the performance of two sets of satellite-based data of precipitation and in situ rainfall measurements. The dates selected refer to rainfall events between 2015 and 2018. For this purpose, 0.1° and 0.25° spatial resolution TMPA (Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis) and IMERG (Integrated Multi-satellite Retrievals for Global Precipitation Measurement) data were retrieved and analyzed, employing appropriate statistical metrics. The best-performing data set was determined as the data source capable to most accurately bridge gaps in the limited rain gauge records, embracing both frequent light-intensity rain events and more rare heavy-intensity events. With light-intensity events, the corresponding satellite-based data sets differ the least and correlate more, while the greatest differences and weakest correlations are noted for the heavy-intensity events. The satellite-based records best match those of the rain gauges during light-intensity events, when compared to the heaviest ones. IMERG data exhibit a superior performance than TMPA in all rainfall intensities. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.relation | ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment | en_US |
dc.relation.ispartof | Remote Sensing | en_US |
dc.rights | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Precipitation | en_US |
dc.subject | TRMM | en_US |
dc.subject | GPM | en_US |
dc.subject | Stressed aquifers | en_US |
dc.subject | Arid areas | en_US |
dc.subject | Sinai | en_US |
dc.title | Comparative Analysis of TMPA and IMERG Precipitation Datasets in the Arid Environment of El-Qaa Plain, Sinai | en_US |
dc.type | Article | en_US |
dc.collaboration | Suez Canal University | en_US |
dc.collaboration | Eberhard Karls University Tübingen | en_US |
dc.collaboration | Helmholtz Center for Environmental Research | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.collaboration | ERATOSTHENES Centre of Excellence | en_US |
dc.collaboration | German Remote Sensing Data Center | en_US |
dc.collaboration | Neubrandenburg University of Applied Sciences | en_US |
dc.collaboration | Sultan Qaboos University | en_US |
dc.collaboration | Zagazig University | en_US |
dc.subject.category | Civil Engineering | en_US |
dc.journals | Open Access | en_US |
dc.country | Egypt | en_US |
dc.country | Germany | en_US |
dc.country | Cyprus | en_US |
dc.country | Oman | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.3390/rs13040588 | en_US |
dc.relation.issue | 4 | en_US |
dc.relation.volume | 13 | en_US |
cut.common.academicyear | 2020-2021 | en_US |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | article | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
crisitem.journal.journalissn | 2072-4292 | - |
crisitem.journal.publisher | MDPI | - |
crisitem.author.dept | Department of Civil Engineering and Geomatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0002-3853-5065 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
crisitem.project.funder | EC | - |
crisitem.project.grantno | H2020-WIDESPREAD-2018-01 / WIDESPREAD-01-2018-2019 Teaming Phase 2 | - |
crisitem.project.fundingProgram | H2020 Spreading Excellence, Widening Participation, Science with and for Society | - |
crisitem.project.openAire | info:eu-repo/grantAgreeent/EC/H2020/857510 | - |
Appears in Collections: | Publications under the auspices of the EXCELSIOR H2020 Teaming Project/ERATOSTHENES Centre of Excellence |
Files in This Item:
File | Description | Size | Format | |
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remotesensing-13-00588.pdf | Fulltext | 2.37 MB | Adobe PDF | View/Open |
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