区域尺度蒸散发遥感估算——反演与数据同化研究进展

遥感技术近年来在估算区域尺度蒸散发中应用广泛。不同方法在驱动数据、模型机理和适用范围往往存在很大差别。鉴于此,阐述了基于传统方法空间尺度扩展的遥感模型,经验统计公式,特征空间法,单源、双源垂向能量平衡余项法等几类的遥感蒸散发反演方法,简要介绍了三温模型、非参数化模型、半经验模型、集成模型等常用模型。同时,分析了遥感数据同化实现连续估算区域蒸散发的主要思路,综述了基于能量平衡和基于复杂过程模型的数据同化的原理、方法演进及常用同化算法等。最后,探讨了各类区域蒸散发遥感方法的优劣、展望了模型机理完善、不确定性研究、结果验证等与蒸散发直接反演和数据同化相关的研究方向。

Review of Current Methodologies for Regional Evapotranspiration Estimation:Inversion and Data Assimilation

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.