<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/99BCFD49-0463-404A-9292-A74760F2D72E"><efrbr-work:titleOfTheWork>Spatiotemporal geostatistical analysis of precipitation combining ground and satellite observations</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/99BCFD49-0463-404A-9292-A74760F2D72E"><efrbr-expression:titleOfTheExpression>Spatiotemporal geostatistical analysis of precipitation combining ground and satellite observations</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Peer-Reviewed Journal Publication
            Δημοσίευση σε Περιοδικό με Κριτές
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2022-11-14</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2021</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>Precipitation data are useful for the management of water resources as well as flood and drought events. However, precipitation monitoring is sparse and often unreliable in regions with complicated geomorphology. Subsequently, the spatial variability of the precipitation distribution is frequently represented incorrectly. Satellite precipitation data provide an attractive supplement to ground observations. However, satellite data involve errors due to the complexity of the retrieval algorithms and/or the presence of obstacles that affect the infrared observation capability. This work presents a methodology that combines satellite and ground observations leading to improved spatiotemporal mapping and analysis of precipitation. The applied methodology is based on space–time regression kriging. The case study refers to the island of Crete, Greece, for the time period of 2010–2018. Precipitation data from 53 stations are used in combination with satellite images for the reference period. This work introduces an improved spatiotemporal approach for precipitation mapping.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="journal name">Hydrology Research</efrbr-expression:note><efrbr-expression:note type="journal volume">52</efrbr-expression:note><efrbr-expression:note type="journal number">3</efrbr-expression:note><efrbr-expression:note type="page range">804–820</efrbr-expression:note></efrbr-expression:expression><efrbr-manifestation:manifestation identifier="https://dias.library.tuc.gr/view/93975"><efrbr-manifestation:titleOfTheManifestation>Varouchakis_et_al_Hydrol. Res._52(3)_2021.pdf</efrbr-manifestation:titleOfTheManifestation><efrbr-manifestation:publicationDistribution><efrbr-manifestation:placeOfPublicationDistribution type="distribution">Chania [Greece]</efrbr-manifestation:placeOfPublicationDistribution><efrbr-manifestation:publisherDistributor type="distributor">Library of TUC</efrbr-manifestation:publisherDistributor><efrbr-manifestation:dateOfPublicationDistribution>2022-11-14</efrbr-manifestation:dateOfPublicationDistribution></efrbr-manifestation:publicationDistribution><efrbr-manifestation:formOfCarrier>application/pdf</efrbr-manifestation:formOfCarrier><efrbr-manifestation:extentOfTheCarrier>731.7 kB</efrbr-manifestation:extentOfTheCarrier><efrbr-manifestation:accessRestrictionsOnTheManifestation>free</efrbr-manifestation:accessRestrictionsOnTheManifestation></efrbr-manifestation:manifestation><efrbr-person:person identifier="http://users.isc.tuc.gr/~evarouchakis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Varouchakis Emmanouil
            Βαρουχακης Εμμανουηλ
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            Christopoulos Dionysios
            Χριστοπουλος Διονυσιος
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            Karatzas Georgios
            Καρατζας Γεωργιος
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            Corzo Perez Gerald A.
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            Diaz Vitali
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            IWA Publishing
         </efrbr-corporateBody:nameOfTheCorporateBody></efrbr-corporateBody:corporateBody><efrbr-concept:concept identifier="97810A2E-78B1-47D3-8A1E-B4CEDF0C88CA"><efrbr-concept:termForTheConcept>
            Crete
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="184DCC2E-336F-456D-ACB8-B1B8F23EA17A"><efrbr-concept:termForTheConcept>
            Precipitation
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            Satellite data
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            Space–time kriging
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            Spartan variogram
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            Sum-metric variogram
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