Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa

Abstract

Globally, water is an important resource required for the survival of human beings. Water is a scarce resource in the semi-arid environments, including South Africa. In South Africa, several studies have quantified evapotranspiration (ET) in different ecosystems at a local scale. Accurate spatially explicit information on ET is rare in the country mainly due to lack of appropriate tools. In recent years, a remote sensing ET product from the MODerate Resolution Imaging Spectrometer (MOD16) has been developed. However, its accuracy is not known in South African ecosystems. The objective of this study was to validate the MOD16 ET product using data from two eddy covariance flux towers, namely; Skukuza and Malopeni installed in a savanna and woodland ecosystem within the Kruger National Park, South Africa. Eight day cumulative ET data from the flux towers was calculated to coincide with the eight day MOD16 products over a period of 10 years from 2000 to 2010. The Skukuza flux tower results showed inconsistent comparisons with MOD16 ET. The Malopeni site achieved a poorer comparison with MOD16 ET compared to the Skukuza, and due to a shorter measurement period, data validation was performed for 2009 only. The inconsistent comparison of MOD16 and flux tower-based ET can be attributed to, among other things, the parameterization of the Penman-Monteith model, flux tower measurement errors, and flux tower footprint vs. OPEN ACCESS Remote Sens. 2014, 6 7407 MODIS pixel. MOD16 is important for global inference of ET, but for use in South Africa’s integrated water management, a locally parameterized and improved product should be developed.

DOI: 10.3390/rs6087406

Extracted Key Phrases

10 Figures and Tables

Cite this paper

@article{Ramoelo2014ValidationOG, title={Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa}, author={Abel Ramoelo and Nobuhle Majozi and Renaud Mathieu and Nebo Jovanovic and Alecia Nickless and Sebinasi Dzikiti}, journal={Remote Sensing}, year={2014}, volume={6}, pages={7406-7423} }