An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S)

A remote sensing-based surface energy balance model is developed to explicitly represent the energy fluxes of four surface components of agricultural fields including bare soil, unstressed green vegetation, non-transpiring green vegetation, and standing senescent vegetation. Such a four-source representation (SEB-4S) is achieved by a consistent physical interpretation of the edges and vertices of the polygon (named T-f(vg) polygon) obtained by plotting surface temperature (T) as a function of fractional green vegetation (f(vg)) and the polygon (named T - alpha polygon) obtained by plotting T as a function of surface albedo (alpha). To test the performance of SEB-4S, a T-alpha image-based model and a T-f(vg) image-based model are implemented as benchmarks. The three models are tested over a 16 km by 10 km irrigated area in northwestern Mexico during the 2007-2008 agricultural season. Input data are composed of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) thermal infrared, Formosat-2 shortwave, and station-based meteorological data. The fluxes simulated by SEB-4S, the T- alpha image-based model, and the T-f(vg) image-based model are compared on seven ASTER overpass dates with the in situ measurements collected at six locations within the study domain. The evapotranspiration simulated by SEB-4S is significantly more accurate and robust than that predicted by the models based on a single (either T-f(vg) or T- alpha) polygon. The improvement provided with SEB-4S reaches about 100W m(-2) at low values and about 100W m(-2) at the seasonal peak of evapotranspiration as compared with both the T- alpha and T-f(vg) image-based models. SEB-4S can be operationally applied to irrigated agricultural areas using high-resolution solar/thermal remote sensing data, and has potential to further integrate microwave-derived soil moisture as additional constraint on surface soil energy and water fluxes

An empirical expression to relate aerodynamic and surface temperatures for use within single-source energy balance models

International audienceSingle-source energy balance models are simple and particularly suited to assimilate mixed pixel remote sensing data. Mixed pixels are made of a combination of two main elements, the soil and the vegetation. The use of single-source models implies that the source of convective fluxes, especially the aerodynamic temperature, is linked to the available remotely sensed surface temperature. There are many empirical relationships between both temperatures in the literature, but few that try to find objective constraints on this link. They usually modify the roughness length for thermal turbulent transport by an expression known as “radiometric kB-1”, which depends mostly on Leaf Area Index (LAI). Acknowledging that the two temperatures should be similar for bare soil and high LAI conditions, we propose an empirical relationship between LAI and the ratio of the difference between the aerodynamic and the air temperatures and the difference between the surface and the air temperatures, also known as “beta function”. Seven datasets over agricultural areas (3 in south western France nearby Toulouse, 3 in south eastern France near Avignon, one in Morocco nearby Marrakech) are used to evaluate this new relationship. They all span the entire cropping season, and LAI values range from 0 to about 5. The new mathematical function is then compared to the beta function retrieved from measured sensible heat flux and in-situ radiometric measurements as well as a two-source SVAT model (ICARE) whose parameters have been calibrated on the same datasets. Its performance in estimating the sensible heat compared to other empirical functions, either based on a “beta function” or a “radiometric kB-1”, is also investigated. This work is carried out in the context of the preparation of the MISTIGRI satellite mission

Ability of a soil-vegetation-atmosphere transfer model and a two-source energy balance model to predict evapotranspiration for several crops and climate conditions

International audienceThe heterogeneity of Agroecosystems, in terms of hydric conditions, crop types and states, and meteorological forcing, is difficult to characterize precisely at the field scale over an agricultural landscape. This study aims to perform a sensitivity study with respect to the uncertain model inputs of two classical approaches used to map the evapotranspiration of agroecosystems: (1) a surface energy balance (SEB) model, the Two-Source Energy Balance (TSEB) model, forced with thermal infrared (TIR) data as a proxy for the crop hydric conditions, and (2) a soil- vegetation-atmosphere transfer (SVAT) model, the SEtHyS model, where hydric conditions are computed from a soil water budget. To this end, the models' skill was compared using a large and unique in situ database covering different crops and climate conditions, which was acquired over three experimental sites in southern France and Morocco. On average, the models provide 30 min estimations of latent heat flux (LE) with a RMSE of around 55 W m(-2) for TSEB and 47 W m(-2) for SEtHyS, and estimations of sensible heat flux (H) with a RMSE of around 29 W m(-2) for TSEB and 38 W m(-2) for SEtHyS. A sensitivity analysis based on realistic errors aimed to estimate the potential decrease in performance induced by the spatialization process. For the SVAT model, the multi-objective calibration iterative procedure (MCIP) is used to determine and test different sets of parameters. TSEB is run with only one set of parameters and provides acceptable performance for all crop stages apart from the early growing season (LAI 0.8 m(2)m(-2)) and unstressed conditions, using sets of parameters that only differentiate crop types is a valuable trade-off for SEtHyS. This study provides some scientific elements regarding the joint use of both approaches and TIR imagery, via the development of new data assimilation and calibration strategies

An empirical expression to relate aerodynamic and surface temperatures for use within single-source energy balance models

International audienceSingle-source energy balance models are simple and particularly suited to assimilate mixed pixel remote sensing data. Mixed pixels are made up of a combination of two main elements, the soil and the vegetation. The use of single-source models implies that the reference temperature for the estimation of convective fluxes, the aerodynamic temperature, is linked to the available remotely sensed surface temperature. There are many relationships relating both temperatures in the literature, but few that try to find objective constraints on this link. These relationships account for the difference between both temperatures by dividing the roughness length for thermal turbulent transport by an expression known as "radiometric kB-1", which depends mostly on Leaf Area Index (LAI). Acknowledging that the two temperatures should be similar for bare soil and high LAI conditions, we propose an empirical relationship between LAI and the ratio of the difference between the aerodynamic and the air temperatures and the difference between the surface and the air temperatures, also known as "beta function". Nine datasets obtained in agricultural areas (four in south western France near Toulouse, four in south eastern France near Avignon, one in Morocco near Marrakech) are used to evaluate this new relationship. They all span the entire cropping season, and LAI values range from 0 to about 5. This new expression of the function is then compared to the beta function retrieved from measured sensible heat flux and in-situ radiometric measurements as well as the beta function simulated by a two-source SVAT model (ICARE). Its performance in estimating the sensible heat compares well to other empirical or semi-empirical functions, either based on a beta function or a radiometric kB-1

Suivi du bilan hydrique des surfaces à l’aide des données IRT: Impact de la revisite et de la précision de la mission MISTIGRI.

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Seasonal evaporation using instantaneous satellite measurements in the thermal infrared domain (Evolution de l’évaporation saisonnière à partir de mesures instantanées dans l’infra-rouge thermique).

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Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass

International audienceEvapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first type estimates a potential evapotranspiration rate from vegetation indices, and adjusts this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods relies on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provides an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets

Validation of evapotranspiration maps from 100-m to the 1-km scale over a semi-arid irrigated agricultural area

International audienceEvapotranspiration (ET) estimates are particularly needed for monitoring available water over arid lands. Remote sensing data offer the ideal spatial and temporal coverage needed by irrigation water management institutions to deal with evolving regional water table issues. Low spatial resolution products present strong advantages as they cover larger zones and are acquired more frequently than high spatial resolution images. Further, they usually offer a long record history, such as the Moderate Resolution Imaging Spectroradiometer (MODIS). However, validation of ET products at low spatial resolution still remains a difficult task. The objective of this study is to evaluate instantaneous fluxes obtained through local meteorological observations and remote sensing data (in visible, near infrared and thermal infrared domains) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER; resampled to 100-m spatial resolution) and MODIS (resampled to 1-km spatial resolution). It was considered the Surface Energy Balance System (SEBS; Su, 2002) and the Two-Source Energy Balance (TSEB; Norman et al., 1995) models. The study zone is a 4 km×4 km semi-arid irrigated agricultural area located in the North-West of Mexico (Yaqui, Sonora; 27°12’N, 109°57’W). Wheat is the dominant crop, followed by maize and vegetables. The ASTER dataset includes 7 dates from December 30, 2007 to May 13, 2008. Daily available MODIS products were considered for the same dates. ET retrievals from ASTER data using both models showed good performances when compared to eddy covariance measurements from 7 locations within the 4 km×4 km square. Next, they were linearly aggregated to the 1-km scale (and considered as the reference ET) and compared to the ET maps obtained using MODIS data considering the SEBS and TSEB models. Further, in order to analyze the effect of the spatial resolution of the inputs, fluxes were also derived by first considering the inputs of the TSEB and SEBS models estimated from ASTER radiances and reflectances previously aggregated to 1-km and then considering all the parameters of both models derived from high spatial resolution ASTER radiances and reflectances before being aggregated to 1-km. MODIS ET estimates compare well with the reference ET (relative bias is about 5% for SEBS and 10% for TSEB). Discrepancies are mainly related to fraction cover mapping for TSEB and vegetation height mapping for SEBS. This is consistent with the sensitivity of each model to these parameters. Low spatial resolution fluxes obtained using both models and ASTER aggregated input data compare well with the reference fluxes, illustrating the relatively good accuracy of using aggregated inputs (relative bias is about 6% for SEBS and 2% for TSEB)

Remote Sensing of Water Resources in Semi-Arid Mediterranean Areas : the joint international laboratory TREMA

Monitoring of water resources and a better understanding of the eco-hydrological processes governing their dynamics are necessary to anticipate and develop measures to adapt to climate and water-use changes. Focusing on this aim, a research project carried out within the framework of French-Moroccan cooperation demonstrated how remote sensing can help improve the monitoring and modelling of water resources in semi-arid Mediterranean regions. The study area is the Tensift Basin located near Marrakech (Morocco) - a typical Southern Mediterranean catchment with water production in the mountains and downstream consumption mainly driven by agriculture. Following a description of the institutional context and the experimental network, the main recent research results are presented: (1) methodological development for the retrieval of key components of the water cycle in a snow-covered area from remote-sensing imagery (disaggregated soil moisture from soil moisture and ocean salinity) at the kilometre scale, based on the Moderate Resolution Imaging Spectroradiometer (MODIS); (2) the use of remote-sensing products together with land-surface modelling for the monitoring of evapotranspiration; and (3) phenomenological modelling based only on time series of remote-sensing data with application to forecasting of cereal yields. Finally, the issue of transfer of research results is also addressed through two remote sensing-based tools developed together with the project partners involved in water management and irrigation planning

A highly virulent variant of HIV-1 circulating in the Netherlands

We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log10 increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence