Evaluation of modeled actual evapotranspiration estimates from a land surface, empirical and satellite-based models using in situ observations from a South African semi-arid savanna ecosystem

dc.contributor.authorKhosa, Floyd V.
dc.contributor.authorFeig, Gregor Timothy
dc.contributor.authorVan der Merwe, Martina R.
dc.contributor.authorMateyisi, Mohau Jacob
dc.contributor.authorMudau, Azwitamisi E.
dc.contributor.authorSavage, Michael J.
dc.date.accessioned2019-09-20T10:45:00Z
dc.date.available2019-09-20T10:45:00Z
dc.date.issued2019-12
dc.description.abstractEvapotranspiration (ET) plays a crucial role in the land-atmosphere interaction and climate variability, especially in arid and semi-arid areas. Accurate estimates of ET are important in hydrological and climate modeling. This study evaluates eight ET data products from different models used for ET estimation. The data products are classified into three main categories depending on the type of modeling approaches: namely process-based land surface model, empirical models, and satellite data derived estimates. The different model estimates are evaluated against in situ measurements from the Skukuza flux tower which is situated in a semi-arid savanna in South Africa. The correlation score and cantered root mean square error computed on monthly ET averages indicate that the satellite-derived model and land surface model estimates are closer to the observed ET signal for the Skukuza site, both in-phase and magnitude. The empirical models' outputs tend to reflect a relatively pronounced departure from observations in magnitude. The normalised mean bias computed for different seasons reveals that the estimates from all modeling approaches are close to the observed signal during the transition period (March–May) to the austral summer. In general, all models overestimate ET during summer and underestimate it in winter. A qualitative analysis of the year-to-year variation for different seasons reveals that all model estimates are qualitatively consistent with the observed seasonal pattern of the signal. Satellite and process-based land surface models (LSMs) also show a response to extremes events such as drought years. The study identifies satellite-derived model outputs as a candidate for understanding spatio-temporal variability of ET across different landscapes within the study region, and process-based models to potentially be used for climate change impact studies on ET.en_ZA
dc.description.departmentGeography, Geoinformatics and Meteorologyen_ZA
dc.description.librarianhj2019en_ZA
dc.description.sponsorshipThe Council for Scientific and Industrial Research [project number EEGC030].en_ZA
dc.description.urihttps://www.elsevier.com/locate/agrformeten_ZA
dc.identifier.citationKhosa, F.V., Feig, G.T., Van der Merwe, M.R. et al. 2019, 'Evaluation of modeled actual evapotranspiration estimates from a land surface, empirical and satellite-based models using in situ observations from a South African semi-arid savanna ecosystem', Agricultural and Forest Meteorology, vol. 279, art. 107706, pp. 1-20.en_ZA
dc.identifier.issn0168-1923 (print)
dc.identifier.issn1873-2240 (online)
dc.identifier.other10.1016/j.agrformet.2019.107706
dc.identifier.urihttp://hdl.handle.net/2263/71431
dc.language.isoenen_ZA
dc.publisherElsevieren_ZA
dc.rights© 2019 The Authors. Published by Elsevier B.V. Open access article publish under a Creative Commons license.en_ZA
dc.subjectEvapotranspiration (ET)en_ZA
dc.subjectLand surface model (LSM)en_ZA
dc.subjectBrutsaert–Strickleren_ZA
dc.subjectCommmunity atmosphere biosphere land exchange (CABLE)en_ZA
dc.subjectGlobal land evaporation Amsterdam model (GLEAM)en_ZA
dc.subjectGranger–Grayen_ZA
dc.subjectSzilagyi–Jozsaen_ZA
dc.subjectComplementary relationshipen_ZA
dc.subjectActual evapotranspiration (AET)en_ZA
dc.subjectSouth Africa (SA)en_ZA
dc.subjectSemi-arid savanna ecosystemen_ZA
dc.titleEvaluation of modeled actual evapotranspiration estimates from a land surface, empirical and satellite-based models using in situ observations from a South African semi-arid savanna ecosystemen_ZA
dc.typeArticleen_ZA

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