41 research outputs found
Evaluation of Meteorological Data-Based Models for Potential and Actual Evapotranspiration Losses Using Flux Measurements
Evapotranspiration is a key process within the hydrological cycle, so
it requires an accurate assessment. This work aims at assessing monthly scale
performances of six meteorological data-based methods to predict evapotranspiration
by comparing model estimates with observations from six flux tower sites
differing for land cover and climate. Three of the proposed methodologies use
a potential evapotranspiration approach (Penman, Priestley-Taylor and Blaney-
Criddle models) while the additional three an actual evapotranspiration approach
(the Advection-Aridity, the Granger and Gray and the Antecedent Precipation
Index method). The results show that models efficiency varies from site to site,
even though land cover and climate features appear to have some influence. It is
difficult to comment on a general accuracy, but an overall moderate better performance
of the Advection-Aridity model can be reported within a context where
model calibration is not accounted for. If model calibration is further taken into
consideration, the Granger and Gray model appears the best performing method
but, at the same time, it is also the approach which is mostly affected by the calibration
process, and therefore less suited to evapotranspiration prediction tools
dealing with a data scarcity context