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The sensitivity of the radar signal to the seasonal dynamics in the Sahel region is a considerable asset for monitoring surface parameters including soil moisture. Given the sensitivity of the radar signal to vegetation mass production, roughness and soil moisture, the main problem has been to estimate the contribution of these three parameters to the signal. This study aims to circumvent this problem by combining radar with optical data. The DMP (Dry Mater Product) extracted from SPOT data allowed to estimate vegetation mass production. Surface roughness was estimated from radar data during the dry season. Because during the dry season, radar signal is only conditioned by soil roughness in this region a Radiative Transfer Model (RTM) was used: it consists in a microwave scattering model of layered vegetation based on the first-order solution of the radiative transfer equation and it accounts for multiple scattering within the canopy, surface roughness of the soil, and the interaction between canopy surface and soil.This model was designed to account for the branch size distribution, leaf orientation distribution, and branch orientation distribution for each size. In this study, the RTM has been calibrated with ESCAT (European Radar Satellite Scatterometer) data, and has been used in order to estimate soil moisture.The results obtained have allowed to track the spatial and temporal dynamics of soil moisture on the one hand, and on the other hand the influence of geology and morphopedology on the spatial dynamics of the soil moisture variability. These results are promising despite the fact that the inversed RTM often faces difficulties to interpret the signal for saturated soils, giving an aberrant value of soil moisture more often than not. Keywords: Soil moisture, Radar remote sensing, ASAR, ERS, SPOT-VEGETATION, Ferlo

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.

A large part of the Sahel consists of endorheic hydrological systems, where reservoirs and lakes capture surface runoff during the rainy season, making water available during the dry season. Monitoring and understanding the dynamics of these lakes and their relationships to the ecohydrological evolution of the region is important to assess past, present and future changes of water resources in the Sahel. Yet, most of Sahelian watersheds are still ungauged or poorly gauged, which hinders the assessment of the water flows feeding the lakes and the overall runoff over their watershed. In this paper, a methodology is developed to estimate water inflow to lakes for ungauged watersheds. It is tested for the Agoufou lake in the Gourma region in Mali, for which in situ water height measurements and surface areas estimations by remote sensing are simultaneously available. A Height-Volume-Area (HVA) model is developed to relate water volume to water height and lake surface area. This model is combined to daily evaporation and precipitation to estimate water inflow to the lake, which approximates runoff over the whole watershed. The ratio between annual water inflow and precipitation increases over the last sixty years as a result of a significant increase in runoff coefficient over the Agoufou watershed. The method is then extended to derive water inflow to three other Sahelian lakes in Mauritania and Niger. No in situ measurements are available and lake surface areas estimation by remote sensing is the only source of information. Dry season surface area changes and estimated evaporation are used to select a suited VA relationship for each case. It is found that the ratio between annual water inflow and precipitation has also increased in the last 60 years over these watersheds, although trends at the Mauritanian site are not statistically significant. The remote sensing approach developed in this study can be easily applied to recent sensors such as Sentinel-2 or Landsat-8, to quantify the evolution of hydrological systems in ungauged Sahelian regions.

In semi-arid areas like the Sahel, vegetation is particularly sensitive to climate variability and can play an important role in surface-atmosphere coupling. After a wet period extending from 1950 to 1970, the Sahel experienced a severe drought in the 1970s and 1980s, followed by a partial recovery of rainfall and a “re-greening” of vegetation beginning in the 1990s. This study explores how the multidecadal variability of Sahelian rainfall and particularly the drought period have affected vegetation phenology and growth since 1960. The STEP model, which is specifically designed to simulate the Sahelian annual vegetation, including the dry season processes, is run over an area extending from 13°N to 18°N and from 20°W to 20°E. Mean values, interannual variability and phenological characteristics of the Sahelian annual grasslands simulated by STEP are in good agreement with MODIS derived production and phenology over the 2001–2014 period, which demonstrates the skill of the model and allows the analysis of vegetation changes and variability over the last 50 years. It was found that droughts in the 1970s and 1980s shortened the mean vegetation cycle and reduced its amplitude and that, despite the rainfall recovery since the 1990s, the current conditions for green and dry vegetation are still below pre-drought conditions. While the decrease in vegetation production has been largely homogeneous during droughts, vegetation recovery has been heterogeneous over the Sahel since 1990, with specific changes near the western coast and at the eastern edge of the West African monsoon area. Since 1970, the Sahel also experienced an increased interannual variability in vegetation mass and phenology. In terms of phenology, region-averaged End and Length of Season are the most variable, while maximum date and Start of Season are the least variable, although the latter displays a high variability locally.

International audience; Quantifying wind erosion and dust emissions in the semi-arid Sahel remains challenging because of the large seasonal and interannual dynamics of surface properties. The increasing conversion of rangelands into croplands raises issues for quantifying wind erosion over these two contrasted surfaces. Whereas wind erosion models have been so far applied to these two surface types separately, this study proposes a common modeling approach to represent the horizontal flux from Sahelian rangelands and croplands. Pair simulations of both typical Sahelian land surface types investigate the horizontal flux due to wind erosion over a 3-year period for two instrumented sites in Mali and Niger. Two different vegetation models simulate the specific phenology and growth of a rangeland grass and a millet crop. These models also account for the local cropping and pastoral practices. Compared to field measurements, the vegetation cover is satisfyingly simulated by the models, especially the strong seasonal dynamics. Specific parameterizations of the aerodynamic surface roughness length (Z(0)) as a function of vegetation variables are established using measurements from the two sites. The simulated horizontal flux turns out to be higher for a cropland than for a rangeland by approximately a factor 1.5, implying that increasing Sahelian cropped areas would increase dust emissions from the Sahel. This difference is mainly due to the time shift between grass and millet growth: the latter starts growing about 2-3 weeks later than annual grass. The amount of dry vegetation remaining during late dry season is also important for Sahelian wind erosion.

This study presents a comprehensive comparison of radar signatures acquired over West Africa (between latitudes 0°–25°N and longitudes 5°W–25°E) at both C- and Ku-bands using nadir-looking altimeters (35-day orbital period ENVISAT RA-2 over 2003–2010 and 10-day orbital period Jason-2 over mid-2008–2011) and side-looking scatterometers (QuikSCAT over 2003–2009 and ASCAT over mid-2008–2011) that covers the major bioclimatic zones, soil and vegetation types encountered in this region. The backscattering coefficient's time series measured by both radar instruments are generated over regional transects and local sites. Meridian transects from the wet tropics to the arid regions of the Sahara desert demonstrate the spatial and temporal changes of the radar response over the West African bioclimatic gradient in terms of surface roughness, land cover and soil wetness. Nadir-looking altimetry appears more sensitive to variations of surface soil moisture than side-looking scatterometry at both C- and Ku-bands. In contrast, the impact of vegetation on the backscattered signals is found to be lower for nadir-looking instruments compared to side-looking ones.

Leaf area index, LAI , fraction of absorbed photosynthetic active radiation, fAPAR , and vegetation cover fraction, fCover , drive the main vegetation canopy processes and are key variables in ecosystem, climate, hydrology and biogeochemistry models. The present study aims to evaluate the joint use of hemispherical photographs and the CAN-EYE image processing software for deriving reliable estimates of these 3 variables in a semi-arid environment. First, LAI and fAPAR estimates are evaluated at a fine scale (about 1 m 2 ) for which independent observations (destructive measurements for LAI , direct transmitted PAR radiation for fAPAR ) are also accurately acquired. Second, a sampling methodology is defined to provide reliable estimations of these variables at the 1 km scale taking into account the spatial heterogeneity of the vegetation cover. Estimated accuracy for the 3 variables is about ±17.3% when 100 photographs are acquired along a 1 km transect. In addition, spatial and temporal variations of the clumping index of the herbaceous canopy are characterized. For pastoral sites of northern Sahel, measurements performed along one or two perpendicular 1 km transects provide reliable LAI / fAPAR / fCover estimates at that scale that should allow comparison with satellite products derived from medium resolution satellites such as the moderate resolution imaging spectroradiometer, MODIS.

Monitoring the mass of herbaceous vegetation during the dry season in semi-arid areas is important for a number of domains in ecology, agronomy, or economy and remote sensing offers relevant spatial coverage and frequency to that end. Existing remote sensing studies dedicated to dry herbaceous vegetation detection are mainly motivated by the assessment of soil tillage intensity and soil residue management, risk of soil erosion, and risk of wildfire linked to the mass of dead fuel. Few studies so far have dealt with monitoring of straw and litter degradation during the dry season over large areas while they are important fodder for livestock sustainability. MODIS band combinations (NBAR collection 5) were tested against a set of field measurements carried out over 20 rangeland sites from 2004 to 2011 in the Sahel. The best empirical linear models were obtained for indices using MODIS bands in the shortwave infrared domain (Band 6 centered at 1.6 μm, Band 7 centered at 2.1 μm), in particular with the Soil Tillage Index (STI). STI explained 66% of the variance of dry masses (Mass = 3158(STI − 1.05), r2 = 0.66, RMSE = 280 kg DM/ha, n = 232) for dry and intermediate season data. A regression is also proposed for year-round data (Mass = 3371(STI − 1.06), r2 = 0.67, RMSE = 352 kg DM/ha, n = 536). The strong inter-site and inter-annual variabilitieswere well captured and the decay ratewas found consistent with grazing intensity and fire occurrence. The results imply that the STI can be applied to monitor the mass of dry tissues in the Sahel and potentially in many semi-arid areas.

Desertification of the Sahel region has been debated for decades, while the concept of a "re-greening" Sahel appeared with satellite remote sensing data that allowed vegetation monitoring across wide regions and over increasingly long series of years (nowadays 30 years with the GIMMS-3g dataset). However, the scarcity of long-term field observations of vegetation in the Sahel prevents ground validation and deeper analysis of such trends. After assessing the consistency of the new GIMMS-3g NDVI product by comparison to three other AVHRR-NDVI datasets and MODIS NDVI, regional GIMMS-3g NDVI trends over 1981-2011 are analyzed. Trends are found positive and statistically significant almost everywhere in Sahel over the 1981-2011 period. Long-term field observations of the aboveground herbaceous layer mass have been collected within the Gourma region in Mali (1984-2011) and within the Fakara region in western Niger (1994-2011). These observations sample ecosystem and soil diversity, thus enabling estimation of averaged values representative of the Gourma and Fakara. NDVI measurements are found in good agreement with field observations, both over the Gourma and Fakara regions where re-greening and negative trends are observed respectively. A linear regression analysis performed between spatially averaged seasonal NDVI and a weighted average of field measurements explains 59% of the variability for the Gourma region over 1984-2011, and 38% for the Fakara region over 1994-2011. In the Gourma, which is a pastoral region, the re-greening trend is mainly observed over sandy soils, and attests for the ecosystem's resilience to the 1980s' drought, able to react to the more favorable rainfall of the 1990s and 2000s. However, contrasted changes in the landscape's functioning have occurred locally. An increase in erosion and run-off processes in association with decreasing or stable vegetation cover was observed over shallow soils, which occupy 30% of the area. In the agro-pastoral Fakara, the decreasing trends observed both from satellite NDVI and field assessments of herbaceous mass are hardly explained by rainfall. These results give confidence in the dominant positive trends in Sahelian greenness, but indicate that degradation trends can also be observed, both in situ and from satellite time series.

International audience; This paper analyses the potential of the radar altimeter onboard ENVISAT for estimating surface soil moisture in the semi-arid Gourma region in Northern Mali. To this end, the relationships between observed backscattering coefficients derived from 4 retracking algorithms, namely Ocean, Ice-1, Ice-2 and Sea-Ice, and ground data, including soil type, topography, vegetation and soil moisture are investigated. The considered period is 2002-2010. Results show a strong linear relationship between the backscattering coefficients and surface soil moisture measured at six different stations along the satellite track. The best results are obtained with the Ice-1 and Ice-2 algorithms. In these cases, correlation coefficients are higher than 0.8 with RMSE smaller than 2%. Vegetation effects are found to be small due both to the nadir-looking configuration of the radar altimeter and to the low vegetation cover. Finally, the relationship between soil moisture and normalized backscattering coefficient is used to retrieve soil moisture from the altimeter data. These estimates are then compared to soil moisture estimations obtained from the METeorological Operational (METOP) Advanced SCATterometer (ASCAT). These results highlight the high capabilities of Ku-band altimeters to provide an accurate estimation of surface soil moisture in semiarid regions.

Summary A series of numerical experiments has been designed to investigate how effective satellite estimates of radiometric surface temperatures and soil surface moisture are for calibrating a Soil–Vegetation–Atmosphere Transfer (SVAT) model. Multi–objective calibration based on error minimization of temperature and soil moisture model outputs is performed in a semi–arid environment. Model accuracy when calibrated using in situ versus satellite objectives is explored in detail. Observational meteorological datasets from the African Monsoon Multidisciplinary Analysis (AMMA) were used to force a column model during a growing season in Mali. Fourier Amplitude Sensitivity Test (FAST) revealed the most sensitive parameters to model outputs. Parameters found sensitive were subsequently optimized in a series of model calibrations to reveal trade-offs between model objectives. Our main findings are (1) the SVAT model performs well in the semi–arid environment, but underestimates peak growing season evapotranspiration and overestimates soil moisture, (2) most of the parameters important for flux estimates can be constrained using surface temperature and soil surface moisture with the three exceptions: root depth, the extinction coefficient and unstressed stomatal resistance, (3) flux simulations are improved when the model is calibrated using in situ surface temperature and soil surface moisture versus satellite estimates.

The patterns of the changes in woody plant population densities, size and species composition is documented and discussed for 24 rangeland sites monitored from 1984 to 2006 in Gourma (Mali). The sites are sampled along the North-South bioclimatic gradient on each of the main soils and levels of grazing intensity. Site woody plant populations range from extremely sparse on shallow soils, to scattered on sandy soils, to open forest in temporarily flooded clayed soils, and to narrow thickets on hard pans. Three different methods contributed to assess and monitor woody plant density and canopy cover. In the short term woody populations were struck by the 1983-84 droughts irrespective 1 of their edaphic situation and location along the bioclimatic gradient. Drought induced mortality was not more severe under drier climate within the Sahel gradient but occurred sooner after drought in shallow soils, and with a lag of a year or two on flooded clay soils. No evidences were found of higher mortality rates in stands with history of intense grazing. Although rainfall remained below average for a decade after the drought, active recruitment of woody plants occurred in all sites starting as soon as 1985. Recruitment proceeded by successive cohorts, often with short-living perennial undershrubs and pioneer shrubs settling first. Acacia species were among the first to settle or re-establish, especially on the sites most intensively grazed. The release of competition due to drought induced mortality and to the reduction of herbaceous cover contributed to the success of the recruitment. The species composition change that resulted could first be interpreted as a shift toward a more arid tolerant flora, then some diversification occurred since the mid 90's that could indicate a possible return to previous composition in the long term, confirming the resilience Sahel vegetation.

The West African Sahel rainfall regime is known for its spatio-temporal variability at different scales which has a strong impact on vegetation development. This study presents results of the combined use of a simple water balance model, a radiative transfer model and ERS scatterometer data to produce map of vegetation biomass and thus vegetation cover at a spatial resolution of 25 km. The backscattering coefficient measured by spaceborne wind scatterometers over Sahel shows a marked seasonality linked to the drastic changes of both soil and vegetation dielectric properties associated to the alternating dry and wet seasons. For lack of a direct observation, METEOSAT rainfall estimates are used to calculate temporal series of soil moisture with the help of a water balance model. This a priori information is used as input of the radiative transfer model that simulates the interaction between the radar wave and the surface components (soil and vegetation). Then, an inversion algorithm is applied to retrieve vegetation aerial mass from the ERS scatterometer data. Because of the nonlinear feature of the inverse problem to be solved, the inversion is performed using a global stochastic nonlinear inversion method. A good agreement is obtained between the inverse solutions and independent field measurements with mean and standard deviation of −54 and 130 kg of dry matter by hectare (kg DM/ha), respectively. The algorithm is then applied to a 350,000 km 2 area including the Malian Gourma and Seno region and a Sahelian part of Burkina Faso during two contrasted seasons (1999 and 2000). At the considered resolution, the obtained herbaceous mass maps show a global qualitative consistency ( r 2 =0.71) with NDVI images acquired by the VEGETATION instrument.

ERS wind scatterometer (WSC) time series are analyzed over different ecoclimatic regions of the African Sahel during the period 1991–1995. At 45° incidence angle, the strong seasonality of σ o time series can be directly linked to the successive wet and dry seasons. Moreover, the annual σ o dynamic range was found to be strongly correlated to total rainfall. The interpretation of the σ o temporal plots is carried out by combining a backscattering model to a grassland growth model. Results highlight the decreasing contribution of the herbaceous component with latitude. However, its contribution is far from negligible and can reach 60% in the Soudano-Sahelian subzone at peak herbaceous mass. Additionally, the tree layer has a negligible effect on the radar signal at the scale of a resolution cell. Finally, a simple parametric backscattering model is calibrated and used in an inversion process. The resolution of the inverse problem is based on a ‘brute-force’ method that consists of exploring all the combinations of parameters of interest. Despite a poor estimation of the temporal variation of the herbaceous mass B t , the retrieved maximum mass compares well with ground estimates.

Polarimetric AIRSAR data acquired over a variety of mangrove forests are analyzed with the assistance of a three-layer radiative transfer model. The necessary input parameters to the model come from detailed ground measurements performed in 12 mangrove stands that are representative of the different successional stages of the mangrove forest dynamics. On the whole, P-band provides the most pronounced polarimetric signatures. Among the polarimetric parameters, the polarization ratio is found to be useful for analyzing scattering mechanisms and for discriminating between various forest stages. Comparison between AIRSAR data and simulations shows that the model is able to describe the overall radar signature of mangrove forests at P-, L- and C-band. However, this study also points out the limitation of such models.

This article presents an analysis of ERS-1 wind-scatterometer (WSC) data acquired over a region located in the northern Sahel. The considered period extends from January 1992 to December 1995, that is, covering four vegetation cycles. Experimental observations show that WSC responses at 45° of incidence angle display a marked seasonality associated with the development and senescence of annual grasses during the successive rainy seasons. The interpretation of the σ° temporal plots is performed with the assistance of a semiempirical backscattering model combined with an ecosystem grassland model. Contributions of the various components of the Sahelian landscape to the total backscattering are identified. Overall, the soil contribution is always large but the σ°(45) temporal plots reflect well the vegetation development. The analysis of the different contributions leads to a simplification of the backscattering model. Finally, this latter is parameterized as a function of two surface parameters, namely, the soil volumetric water content and the vegetation biomass. This simplified model allows the vegetation biomass to be estimated with a 33% error.

A microwave polarimetric scattering model for a forest canopy is developed based on the iterative solution of the vector radiative transfer equations up to the second order. The forest canopy constituents (branches, leaves, stems, and trunks) are embedded in a multi-layered medium over a rough interface. The branches, stems, and trunks are modeled as finite randomly oriented cylinders. Deciduous leaves are modeled as randomly oriented discs and coniferous leaves are modeled as randomly oriented needles. The vector radiative transfer equations contain non-diagonal extinction matrices that account for the difference in propagation constants and the attenuation rates between the vertical and horizontal polarizations. For a plane wave exciting the canopy, the average Mueller matrix is formulated, and then used to determine the linearly polarized backscattering coefficients including both the copolarized and cross-polarized power returns. Comparisons of the model with measurements from Les Landes Forest of France showed good agreements over a wide frequency band and gave a quantitative understanding of the relation between the backscattering coefficients and the age of the trees in the forest and forest biomass.

An approach for combining remote sensing spectral measurements with an ecosystem model was presented in an accompanying article (Mougin et al., 1995). The sahelian grassland ecosystem STEP model developed for that purpose was also described and validated. In order to fulfill a prerequisite for using coarse resolution optical satellite data with the STEP model, the present paper presents i) a modeling of the reflectance which is adapted to the sahelian landscape and ii) a study based on the coupled ecosystem-reflectance modeling to assess the potential of vegetation indices for inferring vegetation parameters. The modeling of the landscape reflectance is based on existing soil and canopy reflectance models, and considers area-weighted contributions from green and dry vegetation, and bare soil components. The ecosystem model provides the landscape reflectance models with inputs like vegetation cover fraction ( f v ) and leaf area index (LAI) to characterize the vegetation present. Atmospheric effects are also accounted for using an existing simplified radiative transfer model. Simulated top of the atmosphere reflectances confronted to real satellite data during a growing season indicate that the modeling is adequate to reproduce temporal profiles of vegetation indices when atmospheric conditions are not prohibitive. Simulated vegetation indices (NDVI, SAVI, GEMI, SR) compared to vegetation characteristics show that a good tracking of the evolution of LAI and v during the growing season is possible before maturation. A sensitivity study of the four VIs to green biomass, soil brightness, and atmospheric water vapor is carried out for the specific case of the Sahel. The SAW and NDVI are both found to be adequate if atmospheric effects are minimized. NDVI integrated over the growing season is compared to net primary productivity (NPP) for different sites, regions, and growing seasons. A near-linear relationship is found, but the same relationship may not be applicable to different regions or growing seasons. On the whole, the results suggest that vegetation indices contain information which are useful for the ecosystem model, despite the fact that perturbating factors make the retrieval of these informations difficult. The possibility of using satellite data to drive the STEP model, or control its simulations, will be assessed in a forthcoming article.

An approach to combining remote sensing spectral measurements with an ecosystem process model is presented. In this approach, the ecosystem model is not bound by the sole use of satellite data, but integrates the latter in an explicit formulation of the main processes of vegetation functioning. A close analysis of the relationships between processes described by the model and spectral measurements can therefore be carried out, and the capability of the model to be driven by remote sensing can also be investigated. This first article presents a regional ecosystem process model for Sahelian regions. The model describes a herbaceous layer composed of only annual species. The processes of the soil-plant-atmosphere system, such as water fluxes in the soil, evaporation, transpiration, photosynthesis, respiration, senescence, litter production, and litter decomposition at the soil surface, are modeled. Moreover, structural parameters such as vegetation cover fraction, LAI, and canopy height, which are essential parameters for coupling with physical models of reflectivity, are also simulated. Comparison with aboveground biomass measured between 1976 and 1992 at a regional scale in two different regions of the Sahel, namely, Ferlo in Senegal and Gourma in Mali, shows that the model is able to simulate the temporal evolution of the aboveground biomass components.