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dc.contributor.authorTomás-Burguera, Miqueles_ES
dc.contributor.authorVicente Serrano, Sergio M.es_ES
dc.contributor.authorGrimalt, Miqueles_ES
dc.contributor.authorBeguería, Santiagoes_ES
dc.date.accessioned2017-01-18T09:36:02Z-
dc.date.available2017-01-18T09:36:02Z-
dc.date.issued2017-03-
dc.identifier.citationTomás-Burguera M, Vicente-Serrano SM, Grimalt M, Beguería S. Accuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsula. Agricultural Water Management 182 (1): 103–116 (2017)es_ES
dc.identifier.issn0378-3774-
dc.identifier.urihttp://hdl.handle.net/10261/142660-
dc.description14 Pags.- 6 Tabls.- 9 Figs.- Appendix (supplementary data).es_ES
dc.description.abstractThe standard approach for computing reference crop evapotranspiration (ETo) is the FAO-56 Penman-Monteith (FAO-PM) method, which requires data on air temperature, radiation, air humidity and wind speed. Unlike air temperature the other variables are less frequently available, hindering the application of FAO-PM. A lot of efforts exist to find the best method to estimate FAO-PM ETo when some variables are not available. The FAO-56 manual recommends to estimate the missing variables based on those currently observed (PM-R), or use the less demanding Hargreaves and Samani method (HS). Additionally, if the missing variables are measured at nearby stations, spatial interpolation can be used to estimate the missing data previous to applying FAO-PM (PM-IC). This paper focuses on the comparison, at the monthly time scale, of the performance of these methods to in the Iberian Peninsula. By using 53 weather stations with all data to calculate FAO-PM, data scarcity scenarios are simulated and the mentioned methods are tested (PM-R, HS, PM-IC)PM-IC yielded consistently the best results according to a number of tests. It yielded the lowest mean absolute error (MAE) at 7.56 mm/month, while PM-R yielded values of 10.15 mm/month and HS 9.36 mm/month and biased results. PM-IC was also best at reproducing the long-term variability and trends in ETo. A good and unbiased estimation of monthly ETo time series are required for irrigation planning and crop design.es_ES
dc.description.sponsorshipThis work was supported by the research projects CGL2011-24185, CGL2011-29263-C02-02, CGL2014-52135-C3-1-R and CGL2014-517221-REDT financed by the Spanish Commission of Science and Technology and FEDER and “LIFE12 ENV/ES/000536-Demonstration and validation of innovative methodology for regional climate change adaptation in the Mediterranean area (LIFE MEDACC)” financed by the EU LIFE program. The first author was supported by the predoctoral FPU program 2013 (Ministerio de Educación, Cultura y Deporte).es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationMINECO/ICTI2013-2016/CGL2014-52135-C3-1-R-
dc.relationMINECO/ICTI2013-2016/CGL2014-517221-REDT-
dc.rightsclosedAccesses_ES
dc.subjectReference evapotranspirationes_ES
dc.subjectUnmeasured dataes_ES
dc.subjectStationary relationshipses_ES
dc.subjectInterpolationes_ES
dc.subjectPositive trendes_ES
dc.titleAccuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsulaes_ES
dc.typeartículoes_ES
dc.identifier.doi10.1016/j.agwat.2016.12.013-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.agwat.2016.12.013es_ES
dc.contributor.funderComisión Interministerial de Ciencia y Tecnología, CICYT (España)es_ES
dc.contributor.funderMinisterio de Educación, Cultura y Deporte (España)es_ES
dc.contributor.funderEuropean Commission-
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.identifier.funderhttp://dx.doi.org/10.13039/501100007273es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100003176es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
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