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Universidad de Chile (2014)

Estimación de la evapotranspiración real mediante teledetección satelital y su relación con la composición florística y estructura de la vegetación en una cuenca árida de la Región de Coquimbo

Ulloa Pino, Javiera Fernanda ;

Titre : Estimación de la evapotranspiración real mediante teledetección satelital y su relación con la composición florística y estructura de la vegetación en una cuenca árida de la Región de Coquimbo

Auteur : Ulloa Pino, Javiera Fernanda ;

Université de soutenance : Universidad de Chile

Grade : Ingeniera en Recursos Naturales Renovables 2014

Résumé
Knowing the relationship between the structure and functioning of natural system is key to fully understand and, therefore, establish effective strategies for management and conservation of nature. The development of new modeling techniques based on satellite remote sensing, has allowed to quantify functional ecosystem variables such as actual evapotranspiration (ETr). The ETr represents the availability of water and energy of the environment and is the largest water flow in arid and semi-arid zones. In this study, the objectives were to estimate ETr using satellite remote sensing techniques and to explore its relation with the floristic composition and vegetation structure in an arid watershed of the Coquimbo Region. To estimate the ETr the S-SEBI algorithm was calibrated, by the use of one ASTER scene and meteorological data. The floristic and structural attributes of vegetation were collected from 30 sampling sites that cover the entire range of variability of ETr and, in addition, topographical features were assessed, derived from a Digital Elevation Model (DEM). Statistical analyses were performed considering simple correlations (Pearson r ; Spearman rs) to explore the relationship between the ETr and the vegetation and topographical variables. Multivariate linear regression models were generated to predict ETr. The results show that the ETr varies between 0.01 and 5.05 [mm d-1], with mean ± SD 2.26 ± 0.90 [mm d-1], and is significantly correlated with several vegetation and topographical variables, among which are : the tree species richness (rs = 0.59 ; p < 0.001), average height of herbaceous plants (rs = 0.58 ; p < 0.001), altitude (r = 0.60 ; p < 0.001), northing aspect (rs = -0.49 ; p < 0.01) and easting aspect (rs = -0.42 ; p < 0.05). The predictive model generated with the variables previously mentioned explains 88% of the variability of ETr (RMSE = 0.33 [mm d-1]). We conclude that the ETr obtained by remote sensing techniques is a contribution to understand the functioning of native vegetation of arid and semi-arid environments.

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