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Assessing the impact of LAI data assimilation on simulations of the soil water balance and maize development using MOHID-Land

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dc.contributor.authorRamos, Tiago B.
dc.contributor.authorSimionesei, Lucian
dc.contributor.authorOliveira, Ana R.
dc.contributor.authorDarouich, Hanaa
dc.contributor.authorNeves, Ramiro
dc.date.accessioned2018-11-07T14:26:28Z
dc.date.available2018-11-07T14:26:28Z
dc.date.issued2018
dc.description.abstractHydrological modeling at the catchment scale requires the upscaling of many input parameters for better characterizing landscape heterogeneity, including soil, land use and climate variability. In this sense, remote sensing is often considered as a practical solution. This study aimed to access the impact of assimilation of leaf area index (LAI) data derived from Landsat 8 imagery on MOHID-Land’s simulations of the soil water balance and maize state variables (LAI, canopy height, aboveground dry biomass and yield). Data assimilation impacts on final model results were first assessed by comparing distinct modeling approaches to measured data. Then, the uncertainty related to assimilated LAI values was quantified on final model results using a Monte Carlo method. While LAI assimilation improved MOHID-Land’s estimates of the soil water balance and simulations of crop state variables during early stages, it was never sufficient to overcome the absence of a local calibrated crop dataset. Final model estimates further showed great uncertainty for LAI assimilated values during earlier crop stages, decreasing then with season reaching its end. Thus, while model simulations can be improved using LAI data assimilation, additional data sources should be considered for complementing crop parameterizationpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationWater 2018, 10, 1367pt_PT
dc.identifier.doi10.3390/w10101367pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/16310
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationWATER4EVER (Optimizing water use efficiency in agriculture to preserve soil and water resourcespt_PT
dc.relationVariabilidade espacial e upscaling das propriedades básicas e hidráulicas do solo na modelação hidrológica
dc.relation.publisherversionwww.mdpi.com/journal/waterpt_PT
dc.subjectbiomasspt_PT
dc.subjectcrop transpirationpt_PT
dc.subjectdirect forcingpt_PT
dc.subjectleaf area indexpt_PT
dc.subjectsoil evaporationpt_PT
dc.titleAssessing the impact of LAI data assimilation on simulations of the soil water balance and maize development using MOHID-Landpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberWaterJPI/0010/2016
oaire.awardNumberUID/EEA/50009/2013
oaire.awardNumberSFRH/BPD/110655/2015
oaire.awardTitleVariabilidade espacial e upscaling das propriedades básicas e hidráulicas do solo na modelação hidrológica
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/WaterJPI%2F0010%2F2016/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F50009%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBPD%2F110655%2F2015/PT
oaire.citation.titleWaterpt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStream5876
person.familyNameDarouich
person.givenNameHanaa
person.identifier.ciencia-id5D13-DECD-D29D
person.identifier.orcid0000-0001-8811-1175
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication2f3da168-54c0-4b69-8d21-0db117ba3530
relation.isAuthorOfPublication.latestForDiscovery2f3da168-54c0-4b69-8d21-0db117ba3530
relation.isProjectOfPublicationdc2d6cd7-8121-4ae3-9ada-48a2670cdcba
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