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Remote Sens. 2019, 11(8), 892;

Uncertainties in Evapotranspiration Estimates over West Africa

Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Science Systems and Applications, Inc., Lanham, MD 20706, USA
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
Science Applications International Corporation, McLean, VA 22102, USA
Author to whom correspondence should be addressed.
Received: 18 March 2019 / Revised: 8 April 2019 / Accepted: 10 April 2019 / Published: 12 April 2019
(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET))
PDF [4757 KB, uploaded 12 April 2019]


An evapotranspiration (ET) ensemble composed of 36 land surface model (LSM) experiments and four diagnostic datasets (GLEAM, ALEXI, MOD16, and FLUXNET) is used to investigate uncertainties in ET estimate over five climate regions in West Africa. Diagnostic ET datasets show lower uncertainty estimates and smaller seasonal variations than the LSM-based ET values, particularly in the humid climate regions. Overall, the impact of the choice of LSMs and meteorological forcing datasets on the modeled ET rates increases from north to south. The LSM formulations and parameters have the largest impact on ET in humid regions, contributing to 90% of the ET uncertainty estimates. Precipitation contributes to the ET uncertainty primarily in arid regions. The LSM-based ET estimates are sensitive to the uncertainty of net radiation in arid region and precipitation in humid region. This study serves as support for better determining water availability for agriculture and livelihoods in Africa with earth observations and land surface models. View Full-Text
Keywords: evapotranspiration; uncertainty; land surface model; West Africa evapotranspiration; uncertainty; land surface model; West Africa

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Jung, H.C.; Getirana, A.; Arsenault, K.R.; Holmes, T.R.; McNally, A. Uncertainties in Evapotranspiration Estimates over West Africa. Remote Sens. 2019, 11, 892.

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