关键词: 蒸散发, 遥感反演, 地表能量平衡, 过程模型, 数据同化

Abstract:

Remote sensing is the effective technology for estimation evapotranspiration (ET). In recent years, many remote sensing ET methods have been developed, and great progress has been made in ET estimation research. While accurate estimation of the satellite-based global terrestrial ET at high spatial and temporal scales remains a major challenge. A review of the commonly applied ET models using remotely sensed data, including the simplified empirical regression method, empirical statistical model for global ET, Penmen-Monteith-based remote sensing model, complementary relationship model, Priestley-Taylor model, triangle or trapezoidal feature space method, residual method of surface energy balance with one-source and two-source framework, three temperature method, nonparametric approach, semiempirical Penman algorithm, and Bayesian model averaging method were presented in this article. Beside the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, these models varied greatly in inputs, main assumptions and accuracy of results, etc. Most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, relied to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. The main inputs, assumptions, theories, advantages and drawbacks of each model were discussed. Moreover, the advantages and disadvantages of remote sensing, conventional calculation formula and process model simulation were analyzed. The data assimilation approaches based on the remotely sensed data to the extrapolation of instantaneous ET to the continuous values are also presented. The data assimilation approaches were divided into surface energy balance-based method and complex process model-based method. The principles, cases and common assimilation algorithms of the two types of methods were reviewed. In the final part, the problems currently and possible solutions such as efficiency, uncertainty, validation and scale in the estimation of regional ET based on remotely sensed data and ground-based measurements were discussed.

Key words: evapotranspiration, remote sensing inversion, surface energy balance, complex process model, data assimilation