Abstract
Currently, thermal remote sensing-based evapotranspiration (ET) models can only calculate instantaneous ET at the time of satellite overpass. Five temporal upscaling methods, namely, constant evaporative fraction (ConEF), corrected ConEF (CorEF), diurnal evaporative fraction (DiEF), constant solar radiation ratio (SolRad), and constant reference evaporative fraction (ConETrF), were selected to upscale the instantaneous ET to daily values. Moreover, five temporal reconstruction approaches, namely, data assimilation (ET_EnKF and ET_SCE_UA), surface resistance (ET_SR), reference evapotranspiration (ET_ETrF), and harmonic analysis of time series (ET_HANTS), were used to produce continuous daily ET with discrete clear-sky daily ET values. For clear-sky daily ET generation, SolRad and ConETrF produced the best estimates. In contrast, ConEF usually underestimated the daily ET. The optimum method, however, was found by combining SolRad and ConETrF, which produced the lowest root-mean-square error (RMSE) values. For continuous daily ET production, ET_ETrF and ET_SCE_UA performed the best, whereas the ET_SR and ET_HANTS methods had large errors. The annual ET distributions over the Beijing area were calculated with these methods. The spatial ET distributions from ET_ETrF and ET_SCE_UA had the same trend as ETWatch products, and had a smaller RMSE when compared with ET observations derived from the water balance method.
Highlights
Evapotranspiration (ET) is one of the most important components of surface energy budgets and hydrologic cycles
Flux observation networks (e.g., FluxNet) and enhanced experiments (e.g., HiWATER) have been set up to monitor long-term surface heat fluxes over different kinds of land cover [1,2,3]
The mean relative error (MRE) values indicated that the constant evaporative fraction (ConEF) method significantly underestimated the daily ET by 19.1% and 14.1% at the Guantao and Arou sites, respectively
Summary
Evapotranspiration (ET) is one of the most important components of surface energy budgets and hydrologic cycles. Flux observation networks (e.g., FluxNet) and enhanced experiments (e.g., HiWATER) have been set up to monitor long-term surface heat fluxes over different kinds of land cover [1,2,3]. Models have been developed to map ET over continental scales based on remotely sensed information [4,5,6,7,8,9,10,11]. The snapshot of the ET map cannot satisfy practical applications, such as, irrigation judgment, and water resource planning and management. To satisfy such applications, the instantaneous ET needs to be upscaled to daily values for clear-sky days
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