Core Ideas AMMA‐CATCH is a long‐term critical zone observatory in West Africa. Four sites sample the sharp ecoclimatic gradient characteristic of this region. Combined measurements of meteorology, water, and vegetation dynamics began in 1990. Intensification of rainfall and hydrological cycles is observed. The strong overall re‐greening may hide contrasted changes. West Africa is a region in fast transition from climate, demography, and land use perspectives. In this context, the African Monsoon Multidisciplinary Analysis (AMMA)–Couplage de l'Atmosphère Tropicale et du Cycle eco‐Hydrologique (CATCH) long‐term regional observatory was developed to monitor the impacts of global change on the critical zone of West Africa and to better understand its current and future dynamics. The observatory is organized into three thematic axes, which drive the observation and instrumentation strategy: (i) analyze the long‐term evolution of eco‐hydrosystems from a regional perspective; (ii) better understand critical zone processes and their variability; and (iii) meet socioeconomic and development needs. To achieve these goals, the observatory has gathered data since 1990 from four densely instrumented mesoscale sites (∼104 km2 each), located at different latitudes (Benin, Niger, Mali, and Senegal) so as to sample the sharp eco‐climatic gradient that is characteristic of the region. Simultaneous monitoring of the vegetation cover and of various components of the water balance at these four sites has provided new insights into the seemingly paradoxical eco‐hydrological changes observed in the Sahel during the last decades: groundwater recharge and/or runoff intensification despite rainfall deficit and subsequent re‐greening with still increasing runoff. Hydrological processes and the role of certain key landscape features are highlighted, as well as the importance of an appropriate description of soil and subsoil characteristics. Applications of these scientific results for sustainable development issues are proposed. Finally, detecting and attributing eco‐hydrological changes and identifying possible regime shifts in the hydrologic cycle are the next challenges that need to be faced.

In many tropical areas, evapotranspiration is the most important but least known component of the water cycle. An innovative method, named E3S (for EVASPA S-SEBI Sahel), was developed to provide spatially-distributed estimates of daily actual evapotranspiration (ETd) from remote sensing data in the Sahel. This new method combines the strengths of a contextual approach that is used to estimate the evaporative fraction (EF) from surface temperature vs. albedo scatterograms and of an ensemble approach that derives ETd estimates from a weighted average of evapotranspiration estimated from several EF methods. In this work, the two combined approaches were derived from the simplified surface energy balance index (S-SEBI) model and the EVapotranspiration Assessment from SPAce (EVASPA) tool. Main innovative aspects concern (i) ensemble predictions of ETd through the implementation of a dynamic weighting scheme of several evapotranspiration estimations, (ii) epistemic uncertainty of the estimation of ETd from the analysis of the variability of evapotranspiration estimates, and (iii) a new cloud filtering method that significantly improves the detection of cloud edges that negatively affect EF determination. E3S was applied to MODIS/TERRA and AQUA datasets acquired during the 2005–2008 period over the mesoscale AMMA-CATCH (Analyse Multidisciplinaire de la Mousson Africaine—Couplage de l’Atmosphère Tropicale et du Cycle Hydrologique) observatory in South-West Niger. E3S estimates of instantaneous and daily available energy, evaporative fraction, and evapotranspiration were evaluated at a local scale based on two field-monitored plots representing the two main ecosystem types in the area—a millet crop and a fallow savannah bush. In addition to these ground-based observations, the local scale evaluation was performed against continuous simulations by a locally-calibrated soil-vegetation-atmosphere transfer model for the two plots. The RMSE (root mean square error) from this comparison for E3S’s ETd estimates from combined AQUA/TERRA sources was 0.5 mm·day−1, and the determination coefficient was 0.90. E3S significantly improved representation of the evapotranspiration seasonality, compared with a classical implementation of S-SEBI or with the original EVASPA’s non-weighted ensemble scheme. At the mesoscale, ETd estimates were obtained with an average epistemic uncertainty of 0.4 mm·day−1. Comparisons with the reference 0.25°-resolution GLEAM (global land evaporation Amsterdam model) product showed good agreement. These results suggested that E3S could be used to produce reliable continuous regional estimations at a kilometric resolution, consistent with land and water management requirements in the Sahel. Moreover, all these innovations could be easily transposed to other contextual approaches.