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Titel Annual evapotranspiration retrieved from satellite vegetation indices for the eastern Mediterranean at 250 m spatial resolution
VerfasserIn D. Helman, A. Givati, I. M. Lensky
Medientyp Artikel
Sprache Englisch
ISSN 1680-7316
Digitales Dokument URL
Erschienen In: Atmospheric Chemistry and Physics ; 15, no. 21 ; Nr. 15, no. 21 (2015-11-11), S.12567-12579
Datensatznummer 250120156
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/acp-15-12567-2015.pdf
 
Zusammenfassung
We present a model to retrieve actual evapotranspiration (ET) from satellites' vegetation indices (Parameterization of Vegetation Indices for ET estimation model, or PaVI-E) for the eastern Mediterranean (EM) at a spatial resolution of 250 m. The model is based on the empirical relationship between satellites' vegetation indices (normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from MODIS) and total annual ET (ETAnnual) estimated at 16 FLUXNET sites, representing a wide range of plant functional types and ETAnnual. Empirical relationships were first examined separately for (a) annual vegetation systems (i.e. croplands and grasslands) and (b) systems with combined annual and perennial vegetation (i.e. woodlands, forests, savannah and shrublands). Vegetation indices explained most of the variance in ETAnnual in those systems (71 % for annuals, and 88 % for combined annual and perennial systems), while adding land surface temperature data in a multiple-variable regression and a modified version of the Temperature and Greenness model did not result in better correlations (p > 0.1). After establishing empirical relationships, PaVI-E was used to retrieve ETAnnual for the EM from 2000 to 2014. Models' estimates were highly correlated (R = 0.92, p < 0.01) with ETAnnual calculated from water catchment balances along rainfall gradient of the EM. They were also comparable to the coarser-resolution ET products of the Land Surface Analysis Satellite Applications Facility (LSA-SAF MSG ETa, 3.1 km) and MODIS (MOD16, 1 km) at 148 EM basins with R of 0.75 and 0.77 and relative biases of 5.2 and −5.2 %, respectively (p < 0.001 for both). In the absence of high-resolution (< 1 km) ET models for the EM the proposed model is expected to contribute to the hydrological study of this region, assisting in water resource management, which is one of the most valuable resources of this region.
 
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