Estimation of evapotranspiration from remote sensing in West Africa : toward a better knowledge of this key variable for the region

Abstract

West Africa is particularly vulnerable to climate and human-induced changes, exerting increasing pressure on water and plant resources. Sound management of the latter requires substantial scientific progress. In particular, it is essential to better understand energy and matter exchanges through the surface-atmosphere continuum, which are a major driver of the hydrological cycle and of vegetation development. In this respect, evapotranspiration is a key variable, as most of precipitation returns to the atmosphere by evapotranspiration and as it couples the water and energy cycles. In West Africa, current knowledge of this process is still limited because it is mainly based on field measurements that are representative of small spatial scales, or on land surface models that would require considerably more data than available in this region. In this context, this thesis work aims at improving our knowledge of the spatiotemporal variability of evapotranspiration, by analyzing the potential of remote sensing to estimate evapotranspiration in West Africa. The proposed approach is based on an inter-comparison of available remote sensing evapotranspiration products and on the proposal of a new method to generate new estimation products. The study was carried out over three mesoscale sites (~ 104 km2) providing a sample of the eco-climatic conditions encountered in West Africa, namely from North to South: the North-Sahel (in East-Central Mali), the South-Sahel (in South-West Niger) and the Sudanian zone (in North Benin). An improved remote sensing method for estimating daily evapotranspiration and its epistemic uncertainty named EVASPA S-SEBI Sahel (E3S) was developed. E3S was applied to the three study sites using data from the MODIS sensors onboard TERRA and AQUA satellites. Daily evapotranspiration estimates were evaluated against pluriannual observations acquired by the AMMA-CATCH Observatory. This study highlights the potential of E3S for estimating daily