Abstract
Estimating cropland latent heat flux (LE) from continental to global scales is vital to modeling crop production and managing water resources. Over the past several decades, numerous LE models were developed, such as the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing-based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL) and the modified satellite-based Priestley-Taylor LE algorithm (MS-PT). However, these LE models have not been directly compared over the global cropland ecosystem using various algorithms. In this study, we evaluated the performances of these four LE models using 34 eddy covariance (EC) sites. The results showed that mean annual LE for cropland varied from 33.49 to 58.97 W/m2 among the four models. The interannual LE slightly increased during 1982–2009 across the global cropland ecosystem. All models had acceptable performances with the coefficient of determination (R2) ranging from 0.4 to 0.7 and a root mean squared error (RMSE) of approximately 35 W/m2. MS-PT had good overall performance across the cropland ecosystem with the highest R2, lowest RMSE and a relatively low bias. The reduced performances of MOD16 and RRS, with R2 ranging from 0.4 to 0.6 and RMSEs from 30 to 39 W/m2, might be attributed to empirical parameters in the structure algorithms and calibrated coefficients.
Highlights
We evaluated four latent heat flux (LE) models, including moderate resolution imaging spectroradiometer (MODIS) Algorithm (MOD16), Revised Remote Sensing-Based Penman–Monteith LE Algorithm (RRS), Priestley–Taylor Algorithm (PT-JPL) and Modified Satellite-Based Priestley–Taylor Algorithm (MS-PT), using the LE measurements from thirty-four eddy covariance sites over cropland ecosystems, and results from temporal trend and spatial distribution of the estimated cropland LE by satellitebased observations
Four LE satellite-based LE algorithms, including MOD16, revised remote sensing-based Penman–Monteith LE algorithm (RRS), PT-JPL and modified satellite-based Priestley-Taylor LE algorithm (MS-PT), were evaluated over a cropland ecosystem based on 34 eddy covariance (EC) flux towers sites
The results showed that all the LE models produced acceptable results for cropland ecosystems
Summary
Latent heat flux (LE) plays a key role in the energy and water cycles in agricultural ecosystems [1, 2]. A large number of studies have shown that LE is a vital variable for developing precise irrigation scheduling and enhancing water use efficiency in agricultural production due to the close relationship between soil water depletion and the rate of evapotranspiration Latent heat fluxes estimation over the global cropland ecosystem using multiple satellite-based models. Science (312231103) and the High Resolution Earth Observation Systems of National Science and Technology Major Projects (Grant 05-Y30B029001-13/15-9). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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