Abstract

Quantifying actual evapotranspiration (ETa) over natural vegetation is crucial in evaluating the water status of ecosystems and the water-use patterns in local or regional hydrological basins. Remote sensing-based surface energy balance models have been used extensively for estimating ETa in agro-environments; however, the application of these models to natural ecosystems is still limited. The surface energy balance algorithm for land (SEBAL) physical-based surface energy balance model was applied to estimate the actual evapotranspiration over a heterogeneous coverage of Mediterranean maquis in a natural reserve in Sardinia, Italy. The model was applied on 19 Landsat 5 and 8 images from 2009 to 2014, and the results were compared to the data of a micrometeorological station with eddy covariance flux measurements. Comparing the SEBAL-based evaporative fraction (ΛS) to the corresponding tower-derived evaporative fractions (ΛT) showed good flux estimations in the Landsat overpass time (Coefficient of determination R2 = 0.77, root mean square error RMSE = 0.05 and mean absolute error MAE = 0.076). Three methods were evaluated for upscaling instantaneous latent heat flux (λE) to daily actual evapotranspiration (ETa,D). The upscaling methods use the evaporative fraction (Λ), the reference evapotranspiration fraction (EFr) and the ratio of daily to instantaneous incoming shortwave radiation (Rs24/Rsi) as upscaling factors under the hypothesis of diurnal self-preservation. A preliminary analysis performed using only in-situ measured data demonstrated that the three factors were relatively self-preserved during the daytime, and can yield good ETa,D estimations, particularly when obtained at near the Landsat scene acquisition time (≈10:00 UTC). The upscaling factors obtained from SEBAL retrieved instantaneous fluxes, and some ancillary measured meteorological data were used to upscale SEBAL-estimated instantaneous actual λ to daily ET. The Λ EFr and Rs24/Rsi methods on average overestimated the measured ETa,D by nearly 20, 61 and 18%, respectively. The performance of the Λ and Rs24/Rsi methods was considered satisfactory, bearing in mind the high variable ground cover and the inherent variability of the biome composition, which cannot be properly represented in the Landsat moderate spatial resolution. In this study, we tested the potential of the SEBAL model application in a complex natural ecosystem. This modeling approach will be used to represent the spatial dynamics of ET, which will be integrated into further environmental and hydrological applications.

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