ECOSTRESS: NASA's next generation mission to measure evapotranspiration from the International Space Station

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station ECOSTRESS) was launched to the International Space Station on June 29, 2018. The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as level‐3 (L3) latent heat flux (LE) data products. These data are generated from the level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are over‐represented. The 70 m high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1 km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data

La petite irrigation par les eaux souterraines, une solution durable contre la pauvreté et les crises alimentaires au Niger ?

Dans les pays du Sahel, le développement de l’agriculture irriguée est une des solutions pour améliorer la sécurité alimentaire. À travers l’exemple du sud-ouest du Niger, cette étude montre que le développement d’une irrigation à faible coût est possible par pompage de l’eau des nappes phréatiques, ressource renouvelable et mieux répartie dans l’espace que les eaux de surface. Les ressources en eau et en terres irrigables de la zone ont été localisées, quantifiées et leur potentiel à long terme réévalué à partir de données actualisées. Les résultats montrent que 50 000 à 160 000 ha (3 à 9 % de la surface totale cultivée) pourraient être mis en valeur par la petite irrigation à partir des eaux souterraines les plus accessibles (jusqu’à 20 m de profondeur). Cette estimation est du même ordre de grandeur que celle déjà avancée pour les seules eaux de surface, doublant ainsi le potentiel irrigable de la zone

Climate Change impacts on hydrological and plant resources in the agro-pastoral Sahel

International audienceThe Sahel is a semi-arid region where the majority of the population depends on subsistence farming. This region is considered as a hotspot for climate change with an expected warming of 3 to 4°C by 2100. Indeed, climate projections show that dry periods are likely to be longer and extreme rainfall will be more frequent. These changes could have a major impact on hydrological and vegetal resources. This study aims to assess these impacts on a typical Sahelian agro-pastoral ecosystem dominated by millet crops and shrubby savannah in South-Western Niger. Climate scenarios are constructed from a local set of observed climate data combined with CMIP6 and other climate scenarios dedicated to Sahelian region. These scenarios are used to constrain SiSPAT SVAT (soil-vegetation-atmosphere transfer) model in order to simulate the surface water and energy fluxes. Results show that both energy and water balances are deeply influenced by temperature and air humidity changes. Temperature increase mainly affects the sensible heat flux (H), e.g., H decreases by 38% for a 3°C of temperature increase. Moreover, results show that the impact of temperature and humidity changes on evapotranspiration, partly compensate each other; higher temperature in the rainy season, leads to higher evapotranspiration values, contrarily to the impact of humidity increase. The surface water balance is mostly influenced by the rainfall regime modification, e.g., intensification of extreme rainfall leads to 59% increase in drainage. It also generates more runoff (+ 500 %), that would increase the risk of flooding but could cause a rise in groundwater levels, which is called the Sahelian paradox. Finally, it also increases the soil water storage, which could lead to a longer vegetation cycle. For this aim, coupling with crop and/or hydrological modelling would be useful to quantify the impacts of climate evolution on vegetal and water resources dynamics. It would allow to find efficiently adapted strategies for crop and water management

Estimating evapotranspiration from remote sensing: the case of Sahelian Africa.

Allies A., J. Demarty, A. Olioso, H. B.-A. Issoufou, I. Maïnassara, J.-P. Chazarin, M. Oï, C. Velluet, M. Bahir, B. Cappelaere, 2017. Estimating evapotranspiration from remote sensing: the case of Sahelian Africa. Abstract IAHS2017-164. IAHS 2017 Scientific Assembly, 10 – 14 July 2017, Port Elizabeth, South Africa. [Présentation orale par A. Allies]http://meetingorganizer.copernicus.org/IAHS2017/IAHS2017-164.pdfEstimating evapotranspiration from remote sensing: the case of Sahelian Africa. . IAHS 2017 Scientific Assembl

Evapotranspiration Estimation in the Sahel Using a New Ensemble-Contextual Method

International audienceIn 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 (ET d) 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 ET d 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 ET d through the implementation of a dynamic weighting scheme of several evapotranspiration estimations, (ii) epistemic uncertainty of the estimation of ET d 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 SouthWest 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 ET d 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, ET d 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 Remote Sens. 2020, 12, 380 2 of 34 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

Modeling Land Surface Fluxes from Uncertain Rainfall: A Case Study in the Sahel with Field-Driven Stochastic Rainfields

International audienceIn distributed land surface modeling (LSM) studies, uncertainty in the rainfields that are used to force models is a major source of error in predicted land surface response variables. This is particularly true for applications in the African Sahel region, where weak knowledge of highly time/space-variable convective rainfall in a poorly monitored region is a considerable obstacle to such developments. In this study, we used a field-based stochastic rainfield generator to analyze the propagation of the rainfall uncertainty through a distributed land surface model simulating water and energy fluxes in Sahelian ecosystems. Ensemble time/space rainfields were generated from field observations of the local AMMA-CATCH-Niger recording raingauge network. The rainfields were then used to force the SEtHyS-Savannah LSM, yielding an ensemble of time/space simulated fluxes. Through informative graphical representations and innovative diagnosis metrics, these outputs were analyzed to separate the different components of flux variability, among which was the uncertainty represented by ensemble-wise variability. Scale dependence was analyzed for each flux type in the water and energy budgets, producing a comprehensive picture of uncertainty propagation for the various flux types, with its relationship to intrinsic space/time flux variability. The study was performed over a 2530 km 2 domain over six months, covering an entire monsoon season and the subsequent dry-down, using a kilometer/daily base resolution of analysis. The newly introduced dimensionless uncertainty measure, called the uncertainty coefficient, proved to be more effective in describing uncertainty patterns and relationships than a more classical measure based on variance fractions. Results show a clear scaling relationship in uncertainty coefficients between rainfall and the dependent fluxes, specific to each flux type. These results suggest a higher sensitivity to rainfall uncertainty for hydrological than for agro-ecological or meteorological applications, even though eddy fluxes do receive a substantial part of that source uncertainty