International audienceWetlands provide a vital resource to ecosystem services and associated rural livelihoods but their extent, geomorphological heterogeneity and flat topography make the representation of their hydrological functioning complex. A semi automated method exploiting 526 MODIS (Moderate Resolution Imaging Spectroradiometer) 8-day 500 m resolution images was developed to study the spatial and temporal dynamics of the annual flood across the Niger Inner Delta over the period 2000–2011. A composite band ratio index exploiting the Modified Normalised Difference Water Index (MNDWI) and Normalised Difference Moisture Index (NDMI) with fixed thresholds provided the most accurate detection of flooded areas out of six commonly used band ratio indices. K-means classified Landsat images were used to calibrate the thresholds. Estimated flooded surface areas were evaluated against additional classified Landsat images, previous studies and field stage data for a range of hydrological units: river stretches, lakes, floodplains and irrigated areas. This method illustrated how large amounts of MODIS images may be exploited to monitor flood dynamics with adequate spatial and temporal resolution and good accuracy, except during the flood rise due to cloud presence. Previous correlations between flow levels and flooded areas were refined to account for the hysteresis as the flood recedes and for the varying amplitude of the flood. Peak flooded areas varied between 10 300 km2 and 20 000 km2, resulting in evaporation losses ranging between 12 km3 and 21 km3. Direct precipitation assessed over flooded areas refined the wetland’s water balance and infiltration estimates. The knowledge gained on the timing, duration and extent of the flood across the wetland and in lakes, floodplains and irrigated plots may assist farmers in agricultural water management. Furthermore insights provided on the wetland’s flood dynamics may be used to develop and calibrate a hydraulic model of the flood in the Niger Inner Delta

, et al.. Soil moisture retrieval over irrigated grassland using X-band SAR data. Remote Sensing of Environment, Elsevier, 2016, 176, pp.202-218. hal-01336862 1 El Hajj M., Baghdadi N., Zribi M., Belaud G., Cheviron B., Courault D., and 1 Charron F., 2016. Soil moisture retrieval over irrigated grassland using X-2 band SAR data. Remote Sensing of Environment, vol. 176, doi

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This paper contributes to the understanding of the structure functions used implicitly in the four-dimensional variational assimilation (4D-Var) developed at the European Centre for Medium-Range Weather Forecasts in the last few years. The theoretical equivalence between 4D-Var and the Kalman filter allows us to interpret (after normalization by the error standard deviations) the analysis increments produced by one single observation as the structure functions used implicitly in 4D-Var. The shape of the analysis increments provides a three-dimensional picture of the covariances of the background errors, modified by the dynamics.We study a baroclinic situation and observations have been regularly distributed along a latitude circle crossing the baroclinic wave. Eight standard pressure levels have been considered to sample the vertical.The forecast error standard deviations and the structure functions implied in 4D-Var may differ considerably from those used in the 3D-Var analysis. Unlike 3D-Var, the structure functions are flow dependent: the effective background error standard deviation can be four times larger and the correlation length scale twice as short in the vicinity of a low. A meridional extension of the experimentation at the surface shows that the effective background error standard deviations at loo0 hPa are largest in the areas of strong pressure gradient.We quantify the link between the analysis increments produced by 4D-Var and the fastest growing perturbations over the same time interval. In the depression, the explained variance of the analysis increments by the first 13 singular vectors reaches 30%.The impact of the temporal dimension is assessed. A period of 24 hours seems a minimum for the increments to develop fully baroclinic structures.

Abstract:The objective of this study was to analyze the sensitivity of radar signals in the X-band in irrigated grassland conditions. The backscattered radar signals were analyzed according to soil moisture and vegetation parameters using linear regression models. A time series of radar (TerraSAR-X and COSMO-SkyMed) and optical (SPOT and LANDSAT) images was acquired at a high temporal frequency in 2013 over a small agricultural region in southeastern France. Ground measurements were conducted simultaneously with the satellite data acquisitions during several grassland growing cycles to monitor the evolution of the soil and vegetation characteristics. The comparison between the Normalized Difference Vegetation Index (NDVI) computed from optical images and the in situ Leaf Area Index (LAI) showed a logarithmic relationship with a greater scattering for the dates . Results showed that the radar signal depends on variations in soil moisture, with a higher sensitivity to soil moisture for biomass lower than 1 kg/m². HH and HV polarizations had approximately similar sensitivities to soil moisture. The penetration depth of the radar wave in the X-band was high, even for dense and high vegetation; flooded areas were visible in the images with higher detection potential in HH polarization than in HV polarization, even for vegetation heights reaching 1 m. Lower sensitivity was observed at the X-band between the radar signal and the vegetation parameters with very limited potential of the X-band to monitor grassland growth. These results showed that it is possible to track gravity irrigation and soil moisture variations from SAR X-band images acquired at high spatial resolution (an incidence angle near 30°).