• Energy Research

Remote sensing estimation of evapotranspiration (ET) was done by combining remote sensing data and the ISBA soil‐vegetation‐atmosphere transfer model over the Alpilles test site. We tested the possible use of low resolution data (∼1km) to derive leaf area index (LAI) at the field scale using a disaggregation method. Disaggregated LAI were then used as inputs of ISBA for monitoring ET for 9 months. Estimation of LAI and ET were first performed at high resolution for being used as reference for evaluating the use of low resolution data. Estimations of LAI at high spatial resolution using an artificial neural network (ANN) algorithm were in very good agreement with ground measurements. At low resolution, we found that it was possible to estimate accurately LAI for the most frequent types of vegetation cover, wheat and sunflower, but not for the other types. However, the estimation of ET from disaggregated low resolution data was found to be quite accurate for any type of vegetation cover (the comparison to h...

Evapotranspiration (ET) can be mapped using thermal infrared and spectral reflectance data. Various ET models have been developed but there was no competitive evaluation of them over a large range of situations. Ensemble model averaging is a tool that can be used for deriving ET from multi-model simulations. In this study, we used bayesian model averaging, which consists in weighting each model according to their performances when deriving the ensemble average. It was applied to the monitoring of ET over a saltmarsh scrub area in South France from MODIS data. ET monitoring was improved ( $\mathrm{RMSE}=0.57 \mathrm{mm}\ \mathrm{d}^{-1}$ ) when using a weighted averaging procedure as compared to the performances of a simple average or to the performances of each individual model.

Estimating evapotranspiration (ET) beyond the local or point scale is essential for many water-related studies. By exploiting the relationship between surface biophysical parameters and thermal emission, continuous ET at such larger spatial scales can be obtained. In this study, we applied the EVASPA tool, which provides an ensemble of ET estimates, over southern France. This was done using MODIS data, including Land Surface Temperature, NDVI, and albedo, resulting in 243 ET estimates. Initial evaluations using in-situ flux data yielded reasonable results even when a simple average was used, with a broad absolute and performance range between the member estimates being observed. Additionally, our uncertainty analyses indicated that ensemble-based contextual modelling can provide sufficient spread for enhanced flux simulations. As EVASPA is intended for operational use, this work aims to guide the establishment of an optimal weighting criteria for the members to improve ET estimates.

Abstract. West African Sahelian and Sudanian ecosystems provide essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing, and uncertainty remains with respect to how these changes will affect the potential of these regions to provide food and fodder resources or how they will affect the biosphere–atmosphere exchange of CO2. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. In order to improve the simulation of phenology, we introduced soil-water availability as a common driver of foliage development and productivity for all of these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations as well as leaf area index data from satellite images (MODIS, MODerate resolution Imaging Spectroradiometer). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed good performance regarding biomass of crops, grass, or trees, yielding correlation coefficients of 0.82, 0.94, and 0.77 and root-mean-square errors of 0.15, 0.22, and 0.12 kg m−2, respectively. The simulations indicate aboveground carbon stocks of up to 0.17, 0.33, and 0.54 kg C ha−1 m−2 for agricultural, savanna grasslands, and savanna mixed tree–grassland sites, respectively. Carbon stocks and exchange rates were particularly correlated with the abundance of trees, and grass biomass and crop yields were higher under more humid climatic conditions. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semiarid West Africa under a wide range of conditions; thus, the model could be used to assess the impact of land-use and climate change on the regional biomass productivity.

Semi-arid regions play an increasingly important role as a sink within the global carbon (C) cycle and is the main biome driving inter-annual variability in carbon dioxide (CO2) uptake by terrestrial ecosystems. This indicates the need for detailed studies of spatiotemporal variability in C cycling for semi-arid ecosystems. We have synthesized data on the land-atmosphere exchange of CO2 measured with the eddy covariance technique from the six existing sites across the Sahel, one of the largest semi-arid regions in the world. The overall aim of the study is to analyse and quantify the spatiotemporal variability in these fluxes and to analyse to which degree spatiotemporal variation can be explained by hydrological, climatic, edaphic and vegetation variables. All ecosystems were C sinks (average ± total error -162 ± 48 g C m-2 y-1), but were smaller when strongly impacted by anthropogenic influences. Spatial and inter-annual variability in the C flux processes indicated a strong resilience to dry conditions, and were correlated with phenological metrics. Gross primary productivity (GPP) was the most important flux process affecting the sink strength, and diurnal variability in GPP was regulated by incoming radiation, whereas seasonal dynamics was closely coupled with phenology, and soil water content. Diurnal variability in ecosystem respiration was regulated by GPP, whereas seasonal variability was strongly coupled to phenology and GPP. A budget for the entire Sahel indicated a strong C sink mitigating the global anthropogenic C emissions. Global circulation models project an increase in temperature, whereas rainfall is projected to decrease for western Sahel and increase for the eastern part, indicating that the C sink will possibly decrease and increase for the western and eastern Sahel, respectively.