During the last decades, agriculture has drastically increased over the South American Andean Plateau (Altiplano), resulting in extensive changes in land cover from native vegetation to essentially Quinoa crop. Along with climatic variability, these land use changes appear as a catalyst in worsening the already existing drought events and water scarcity processes. Hence, understanding their relative contributions to the regional desertification process is crucial for sustainable water-use adaptation, but also is quite ambiguous because of water resource data scarcity over the Altiplano. Therefore, in the present study, an attempt to measure the impact of severe droughts and agricultural intensification on the water resources has been made using remote sensing datasets. The first step was dedicated to the validation of newly released CHIRPS v.2 precipitation and GLEAM v.3 potential evapotranspiration products by comparing their estimates with the results obtained from gauges data. Then, the Standardized Precipitation Index (SPI) was used to describe past hydro-meteorological drought events in terms of their spatial extent, duration, intensity and their impacts on the regional water resources. Finally, the dynamic trends in the spatial extent of the Quinoa crop and the meteorological conditions derived from CHIRPS v.2 and GLEAM v.3 were compared with the Vegetation Condition Index (VCI) and the Total Water Storage (TWS) derived from AVHRR and GRACE data respectively, to observe the respective influence of agriculture and climate variability on the regional hydrological system. A significant increase in Quinoa crop extent is observed from 2001 which corresponds to a significant decrease in regional VCI and TWS. Based on this trend, agriculture appears as a contributing factor in the water scarcity process over the Altiplano. The outcomes of this study will contribute to local decision making for a better water management and hydro-meteorological monitoring system.

Lake Titicaca is a crucial water resource in the central part of the Andean mountain range, and it is one of the lakes most affected by climate warming. Since surface evaporation explains most of the lake's water losses, reliable estimates are paramount to the prediction of global warming impacts on Lake Titicaca and to the region's water resource planning and adaptation to climate change. Evaporation estimates were done in the past at monthly time steps and using the four methods as follows: water balance, heat balance, and the mass transfer and Penman's equations. The obtained annual evaporation values showed significant dispersion. This study used new, daily frequency hydro-meteorological measurements. Evaporation losses were calculated following the mentioned methods using both daily records and their monthly averages to assess the impact of higher temporal resolution data in the evaporation estimates. Changes in the lake heat storage needed for the heat balance method were estimated based on the morning water surface temperature, because convection during nights results in a well-mixed top layer every morning over a constant temperature depth. We found that the most reliable method for determining the annual lake evaporation was the heat balance approach, although the Penman equation allows for an easier implementation based on generally available meteorological parameters. The mean annual lake evaporation was found to be 1700 mm year−1. This value is considered an upper limit of the annual evaporation, since the main study period was abnormally warm. The obtained upper limit lowers by 200 mm year−1, the highest evaporation estimation obtained previously, thus reducing the uncertainty in the actual value. Regarding the evaporation estimates using daily and monthly averages, these resulted in minor differences for all methodologies.

The mitigation of climate change by agro-sylvo-pastoral systems is complex to assess or model, owing to high spatial and temporal heterogeneities. We set a new long-term observatory up for the monitoring and modelling of microclimate, GHG and deep SOC in a semi-arid agro-sylvo-pastoral system (Niakhar, Senegal), dominated by the multipurpose Faidherbia albida tree. Crops were mainly millet and peanut, under annual rotation. Transhumant livestock contributed largely to manure, SOM and soil fertility. Early 2018, we installed 3 eddy-covariance towers above (i) the whole mosaic, (ii) millet and (iii) peanut and monitored energy, CO2 balance and evapotranspiration for one full year. The mosaic ecosystem displayed low but significant CO2 and H2O fluxes during the dry season, owing to Faidherbia in leaf (Fig. 1). When rains resumed, the soil bursted a large amount of CO2. Just after the raising of millet, CO2 uptake by photosynthesis increased dramatically, then stabilized before harvest. However, this was compensated by large ecosystem respiration. The annual ecosystem CO2 balance was close to nil. This observatory is currently installing soil chambers for GHG fluxes, studying the horizontal variability of SOC by Vis-NIR and of deep soil roots and C using wells. Microclimate (land surface temperature, energy balance and gas exchanges) and light-use-efficiency will be mapped through 3D modelling (Charbonnier et al., 2017; Vezy et al., 2018). This observatory is open for collaboration.

In 2015, an emergency state was declared in Bolivia when Poopó Lake dried up. Climate variability and the increasing need for water are potential factors responsible for this situation. Because field data are missing over the region, no statements are possible about the influence of mentioned factors. This study is a preliminary step toward the understanding of Poopó Lake drought using remote sensing data. First, atmospheric corrections for Landsat (FLAASH and L8SR), seven satellite derived indexes for extracting water bodies, MOD16 evapotranspiration, PERSIANN-CDR and MSWEP rainfall products potentiality were assessed. Then, the fluctuations of Poopó Lake extent over the last 26 years are presented for the first time jointly, with the mean regional annual rainfall. Three main droughts are highlighted between 1990 and 2015: two are associated with negative annual rainfall anomalies in 1994 and 1995 and one associated with positive annual rainfall anomaly in 2015. This suggests that other factors than rainfall influenced the recent disappearance of the lake. The regional evapotranspiration increased by 12.8% between 2000 and 2014. Evapotranspiration increase is not homogeneous over the watershed but limited over the main agriculture regions. Agriculture activity is one of the major factors contributing to the regional desertification and recent disappearance of Poopó Lake.

The new IMERG and GSMaP-v6 satellite rainfall estimation (SRE) products from the Global Precipitation Monitoring (GPM) mission have been available since January 2015. With a finer grid box of 0.1°, these products should provide more detailed information than their latest widely-adapted (relatively coarser spatial scale, 0.25°) counterpart. Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) assessment is done by comparing their rainfall estimations with 247 rainfall gauges from 2014 to 2016 in Bolivia. The comparisons were done on annual, monthly and daily temporal scales over the three main national watersheds (Amazon, La Plata and TDPS), for both wet and dry seasons to assess the seasonal variability and according to different slope classes to assess the topographic influence on SREs. To observe the potential enhancement in rainfall estimates brought by these two recently released products, the widely-used TRMM Multi-satellite Precipitation Analysis (TMPA) product is also considered in the analysis. The performances of all the products increase during the wet season. Slightly less accurate than TMPA, IMERG can almost achieve its main objective, which is to ensure TMPA rainfall measurements, while enhancing the discretization of rainy and non-rainy days. It also provides the most accurate estimates among all products over the Altiplano arid region. GSMaP-v6 is the least accurate product over the region and tends to underestimate rainfall over the Amazon and La Plata regions. Over the Amazon and La Plata region, SRE potentiality is related to topographic features with the highest bias observed over high slope regions. Over the TDPS watershed, the high rainfall spatial variability with marked wet and arid regions is the main factor influencing SREs.

The Madeira River is the second largest tributary of.the Amazon River. It contributes approximately 13% of the Amazon River flow and it may contribute up to 50% of its sediment discharge to the Atlantic Ocean. Until now, the suspended sediment load of the Madeira River was not well known and was estimated in a broad range from 240 to 715 Mt yr(-1). Since 2002, the HYBAM international network developed a new monitoring programme specially designed to provide more reliable data than in previous intents. It is based on the continuous monitoring of a set of 11 gauging stations in the Madeira River watershed from the Andes piedmont to the confluence with the Amazon River, and discrete sampling of the suspended sediment concentration every 7 or 10 days. This paper presents the results of the suspended sediment data obtained in the Madeira drainage basin during 2002-2011. The Madeira River suspended sediment load is estimated at 430 Mt yr-1 near its confluence with the Amazon River. The average production of the Madeira River Andean catchment is estimated at 640 Mt yr(-1) (+/- 30%), the corresponding sediment yield for the Andes is estimated at 3000 t km(-2) yr(-1) (+/- 30%), and the average denudation rate is estimated at 1.20 mm yr(-1) (+/- 30%). Contrary to previous results that had mentioned high sedimentation rates in the Beni River floodplain, we detected no measurable sedimentation process in this part of the basin. On the Mamore River basin, we observed heavy sediment deposition of approximately 210 Mt yr(-1) that seem to confirm previous studies. But while these studies mentioned heavy sedimentation in the floodplain, we showed that sediment deposition occurred mainly in the Andean piedmont and immediate foreland in rivers (Parapeti, Grande, Pirai, Yapacani, Chimore, Chapare, Secure, Maniqui) with discharges that are not sufficiently large to transport their sediment load downstream in the lowlands. (C)2017 Elsevier B.V. All rights reserved.

Previously available only over the Continental United States (CONUS), the 1 arc-second mesh size (spatial resolution) SRTM-GL1 (Shuttle Radar Topographic Mission – Global 1) product has been freely available worldwide since November 2014. With a relatively small mesh size, this digital elevation model (DEM) provides valuable topographic information over remote regions. SRTM-GL1 is assessed for the first time over the South American Andean Plateau in terms of both the absolute and relative vertical point-to-point accuracies at the regional scale and for different slope classes. For comparison, SRTM-v4 and GDEM-v2 Global DEM version 2 (GDEM-v2) generated by ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) are also considered. A total of approximately 160,000 ICESat/GLAS (Ice, Cloud and Land Elevation Satellite/Geoscience Laser Altimeter System) data are used as ground reference measurements. Relative error is often neglected in DEM assessments due to the lack of reference data. A new methodology is proposed to assess the relative accuracies of SRTM-GL1, SRTM-v4 and GDEM-v2 based on a comparison with ICESat/GLAS measurements. Slope values derived from DEMs and ICESat/GLAS measurements from approximately 265,000 ICESat/GLAS point pairs are compared using quantitative and categorical statistical analysis introducing a new index: the False Slope Ratio (FSR). Additionally, a reference hydrological network is derived from Google Earth and compared with river networks derived from the DEMs to assess each DEM’s potential for hydrological applications over the region. In terms of the absolute vertical accuracy on a global scale, GDEM-v2 is the most accurate DEM, while SRTM-GL1 is more accurate than SRTM-v4. However, a simple bias correction makes SRTM-GL1 the most accurate DEM over the region in terms of vertical accuracy. The relative accuracy results generally did not corroborate the absolute vertical accuracy. GDEM-v2 presents the lowest statistical results based on the relative accuracy, while SRTM-GL1 is the most accurate. Vertical accuracy and relative accuracy are two independent components that must be jointly considered when assessing a DEM’s potential. DEM accuracies increased with slope. In terms of hydrological potential, SRTM products are more accurate than GDEM-v2. However, the DEMs exhibit river extraction limitations over the region due to the low regional slope gradient.

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north–south gradient and a lighter east–west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (−42%) and moderately negative for GSMaP (−18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2mm day−1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a negative bias becomes positive for GSMaP. TMPA-3B42 Adjusted (Adj) version 7 demonstrates the best overall agreement with gauges in terms of correlation, rain rate distribution and bias. However, PERSIANN-Adj's bias in the southern part of the domain is very low.

Improving regional estimates of actual evapotranspiration (λΕ) in water-limited regions located at climatic transition zones is critical. This study assesses an λΕ model (PT-JPL model) based on downscaling potential evapotranspiration according to multiple stresses at daily time-scale in two of these regions using MSG–SEVIRI (surface temperature and albedo) and MODIS products (NDVI, LAI and fPAR). An open woody savanna in the Sahel (Mali) and a Mediterranean grassland (Spain) were selected as test sites with Eddy Covariance data used for evaluation. The PT-JPL model was modified to run at a daily time step and the outputs from eight algorithms differing in the input variables and also in the formulation of the biophysical constraints (stresses) were compared with the λΕ from the Eddy Covariance. Model outputs were also compared with other modeling studies at similar global dryland ecosystems. The novelty of this paper is the computation of a key model parameter, the soil moisture constraint, relying on the concept of apparent thermal inertia (fSM-ATI) computed with surface temperature and albedo observations. Our results showed that fSM-ATI from both in-situ and satellite data produced satisfactory results for λΕ at the Sahelian savanna, comparable to parameterizations using field-measured Soil Water Content (SWC) with r2 greater than 0.80. In the Mediterranean grasslands however, with much lower daily λE values, model results were not as good as in the Sahel (r2 = 0.57–0.31) but still better than reported values from more complex models applied at the site such as the Two Source Model (TSM) or the Penman–Monteith Leuning model (PML). PT-JPL-daily model with a soil moisture constraint based on apparent thermal inertia, fSM-ATI offers great potential for regionalization as no field-calibrations are required and water vapor deficit estimates, required in the original version, are not necessary, being air temperature and the available energy (Rn-G) the only input variables required, apart from routinely available satellite products.

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. (C) 2012 Elsevier B.V. All rights reserved.

Rainfall distribution and the soil moisture regime have been recognized to be the key drivers of the phenological rhythms in Sahelian woody plants, although different climate triggers have been assumed to be involved in determining the date of the onset of the phenophase. However, almost no comparisons have been made of the actual relative predictive power of these environmental factors. The aim of our study was to quantify the ability of several factors to predict phenophase occurrence in the dominant woody populations of northern Mali. Canopy leafing, flowering and fruiting were monitored from May 2005 to July 2007. Multiple logistic regressions were used to test the predictive power of cumulative rainfall, soil moisture, air temperature, air humidity and day length, with time lags of up to 2 months. Artificial variables derived from time lags observed in phenophases were included as predictors to account for possible auto-correlation and cross-correlation among phenophases. Surprisingly, a decrease in temperature associated with different time lags was most often found to be the strongest predictor of both leafing and reproductive phenophases. In Sahelian shrubs, morphological and physiological adaptations strongly contribute to the relative independence of their activity from water availability, leaf phenology being a way to adjust the plant water balance to current water availability and atmospheric water content. This study provides insight towards the development of a mechanistic understanding of phenological control in the Sahel, which is becoming increasingly important in the context of expected climate changes.

Making available regional estimates of daily evapotranspiration in water-scarce and climatic vulnerable regions is critical for improving agricultural and hydrological information as well as our understanding of land surface-atmosphere interactions. The aim of this study is to provide an operational algorithm for the Sahel relying on satellite products at 1-4 km spatial resolution without field calibration. An evapotranspiration model based on the Priestley-Taylor equation reduced according to multiple stresses based on Fisher ́s model was evaluated in a savanna site in the Sahel (Mali) introducing a new formulation for the soil moisture constraint. The model was successful to estimate daily evapotranspiration at the field level, with a better performance when using a soil moisture constraint based on a Thermal Inertia index (r=0.83; MAE=19.2 Wm) than on an atmospheric water deficit index. When up-scaling the model from field to satellite level, the decrease in accuracy was comparable to the results from a more complex SVAT model, with a better performance again of the Apparent Thermal Inertia index especially when calculated from MODIS rather than from SEVIRI data (r= 0.69; MAE=13.48 Wm). The global MODIS 8day evapotranspiration product (MOD16) was also evaluated at the site and failed to capture the dynamics of evapotranspiration in this Sahelian savanna.

This paper presents an analysis of the coupled cycling of energy and water by semi-arid Sahelian surfaces, based on two years of continuous vertical flux measurements from two homogeneous recording stations in the Wankama catchment, in the West Niger meso-site of the AMMA project. The two stations, sited in a millet field and in a semi-natural fallow savanna plot, sample the two dominant land cover types in this area typical of the cultivated Sahel. The 2-year study period enables an analysis of seasonal variations over two full wet-dry seasons cycles, characterized by two contrasted rain seasons that allow capturing a part of the interannual variability. All components of the surface energy budget (four-component radiation budget, soil heat flux and temperature, eddy fluxes) are measured independently, allowing for a quality check through analysis of the energy balance closure. Water cycle monitoring includes rainfall, evapotranspiration (from vapour eddy flux), and soil moisture at six depths.The main modes of observed variability are described, for the various energy and hydrological variables investigated. Results point to the dominant role of water in the energy cycle variability, be it seasonal, interannual, or between land cover types. Rainfall is responsible for nearly as much seasonal variations of most energy-related variables as solar forcing. Depending on water availability and plant requirements, evapotranspiration pre-empts the energy available from surface forcing radiation, over the other dependent processes (sensible and ground heat, outgoing long wave radiation). In the water budget, pre-emption by evapotranspiration leads to very large variability in soil moisture and in deep percolation, seasonally, interannually, and between vegetation types.The wetter 2006 season produced more evapotranspiration than 2005 from the fallow but not from the millet site, reflecting differences in plant development. Rain-season evapotranspiration is nearly always lower at the millet site. Higher soil moisture at this site suggests that this difference arises from lower vegetation requirements rather than from lower infiltration/higher runoff. This difference is partly compensated for during the next dry season. Effects of water and vegetation on the energy budget appear to occur more through latent heat than through albedo. A large part of albedo variability comes from soil wetting and drying. Prior to the onset of monsoon rain, the change in air mass temperature and wind produces, through modulation of sensible heat, a marked chilling effect on the components of the surface energy budget. (C) 2008 Elsevier B.V. All rights reserved.

The study quantifies the relationships at local scale between phenology and determinants of climate and soil water resources at two sites located along the latitudinal gradient of West Africa, one in the central Sahel (Mali), the other in the Sudanian bioclimatic zone (Benin). The aim is to improve our knowledge on possible vegetation response to possible climate change. Within the Sudanian site, average annual rainfall is 1200mm, extending from April to October, while, in the Sahelian site, it is 370mm, occurring from June to September. Physical data were collected from the African Monsoon Multidisciplinary Analysis research programme. The phenology of the dominant species was monitored in four types of vegetation cover at the wetter site, and in three types of vegetation cover at the drier site. For each sampled plant, leafing, flowering and fruiting were recorded as binary variables in terms of the presence/absence of phenophases. A small proportion of the variability of each phenophase occurrence is explained by the logit models. However, rainfall rise is significantly linked to leafing probability increase in the Sahelian site but not in the Sudanian site. Day length extension and temperature decrease are significantly correlated with an increase in leafing in the Sudanian site, but not in the Sahelian. On both sites, the increase in cumulative rainfall is not found to be linked to an increased probability of reproductive phenophases (negative or non-significant relationships). Air temperature is positively correlated with flowering rate in the Sudanian site, but, all other factors being constant, no climate factors are found to be highly significant of flowering occurrence in the Sahel. Fruiting probability is positively correlated mainly with temperature within the Sahelian site. Leafing occurrence is positively correlated with soil moisture in the 0–1m layer for the Sudanian site, but not for the Sahelian site. Significant relationships between fruiting occurrence and soil moisture may reflect a prior selection of plants on fruiting period that maximizes seed dispersion and germination differently at the two sites. While vegetative and reproduction schedules may be determined by specific genetic factors, the physical environment controls the possibility of their expression. Reduction of the rainfall amount and intensity may increase reproduction rates in wet areas. Although this factor should decrease leafing rate, it does not influence reproduction at dry sites, except through the decrease in air humidity. In wetter areas, increasing temperature may reduce leafing, but may increase reproduction rates. Cover reduction may have an impact on local physical factors and, consequently, probably also affects vegetation phenology.