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New Mexico State University (2010)

Remote sensing of energy balance for estimating land evapotranspiration in the semi-arid southwestern USA

Mariotto, Isabella

Titre : Remote sensing of energy balance for estimating land evapotranspiration in the semi-arid southwestern USA

Auteur : Mariotto, Isabella

Université de soutenance : New Mexico State University

Grade : Doctor of Philosophy (PhD) 2010

Résumé
Modeling spatial variation of evapotranspiration (ET) over heterogeneous landscapes is a difficult task for hydrologists, agronomists, and meteorologists. The application of energy balance algorithms to remotely sensed imagery often fails in properly discriminating ET over spectrally diverse land covers for the complexity of modeling the surface roughness. Furthermore, the assumption of a horizontally homogeneous Lambertian surface reflecting energy equally in all directions affects the albedo and vegetation index calculations. The objective of this study is to improve the accuracy of the Surface Energy Balance Algorithm for Land (SEBAL) for estimating ET from ASTER datasets by analyzing the spatial variation of anisotropic reflectance and surface roughness among different plant species-dominated grasslands, shrublands, and dunelands in Southern New Mexico. The degree to which land cover surfaces are anisotropic is assessed by applying a wavelength-dependent non-Lambertian topographic transformation with the Minnaert function. Surface roughness is modeled using a land cover map in conjunction with the fractional vegetation cover derived from vegetation indices. SEBAL modified for reflectance or for roughness showed stronger agreement with the Eddy-Covariance measurements than the non-modified SEBAL. Furthermore, the former showed higher, intermediate, and lower ET values among grasslands, schrublands, and dunelands respectively, while the latter resulted in more homogeneous ET values among land covers and in overestimation of ET over dunelands and underestimation over grasslands. Multiple pairwise land covers comparisons of ET means showed higher potential of the corrected model in discriminating ET. This study suggests that some assumptions in SEBAL tend to inadvertently homogenize ET on these diverse landscapes

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