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Regression models for soil water storage estimation using the ESA CCI satellite soil moisture product: a case study in Northeast Portugal

2021Journal article Open access
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dc.contributor.authorFigueiredo, Tomás de
dc.contributor.authorRoyer, Ana Caroline
dc.contributor.authorFonseca, Felícia
dc.contributor.authorSchütz, Fabiana Costa Araújo
dc.contributor.authorHernández, Zulimar
dc.date.accessioned2021-09-16T10:28:51Z
dc.date.available2021-09-16T10:28:51Z
dc.date.issued2021
dc.description.abstractThe European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.pt_PT
dc.description.sponsorshipThis research was partially funded by the Foundation for Science and Technology (FCT, Lisbon, Portugal), grant number UIDB/00690/2020. Furthermore, A.C.R.’s contribution to the research was financially supported, first, by the Instituto Politécnico de Bragança through the Double Diploma MSc programme in Environmental Technology with the Technological Federal University of Paraná, Brazil, and second, by the EU FEDER Fund, through the POCTEP programme funding the TERRAMATER research project (grant 0701_TERRAMATER_1_E).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFigueiredo, Tomás de; Royer, Ana Carolina; Fonseca, Felícia; Schütz, Fabiana Costa de Araújo; Hernandez Hernandez, Zulimar (2021). Regression models for soil water storage estimation using the ESA CCI satellite soil moisture product: a case study in Northeast Portugal. Water. ISSN 2073-4441. 13:1, p. 1-26pt_PT
dc.identifier.doi10.3390/w13010037pt_PT
dc.identifier.issn2073-4441
dc.identifier.urihttp://hdl.handle.net/10198/23915
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectRemote sensingpt_PT
dc.subjectRadar satellite datapt_PT
dc.subjectActive and passive microwave sensorspt_PT
dc.subjectESA CCI SM productpt_PT
dc.subjectSoil water balancept_PT
dc.subjectSoil water storagept_PT
dc.subjectRegression modelspt_PT
dc.subjectHysteresispt_PT
dc.titleRegression models for soil water storage estimation using the ESA CCI satellite soil moisture product: a case study in Northeast Portugalpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue1pt_PT
oaire.citation.startPage37pt_PT
oaire.citation.titleWaterpt_PT
oaire.citation.volume13pt_PT
person.familyNameFreitas Rosa de Figueiredo
person.familyNameRoyer
person.familyNameFonseca
person.givenNameTomás d' Aquino
person.givenNameAna Caroline
person.givenNameFelícia
person.identifier1297327
person.identifier.ciencia-id961D-607D-51CC
person.identifier.ciencia-id721A-9374-4C35
person.identifier.orcid0000-0001-7690-8996
person.identifier.orcid0000-0002-0746-185X
person.identifier.orcid0000-0001-7727-071X
person.identifier.scopus-author-id54790554500
person.identifier.scopus-author-id36970960500
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscovery4f6f8be1-73c1-45bb-b159-ce3f8ff96c84

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