Estimating land surface evapotranspiration from remote sensing: a challenge for West Africa. In: 12th International Kovacs Colloquium : "Hydrological Inputs for Water-Related SDGs Implementation: Knowledge, Data, Indicators, Tools & Innovations"

International audienc

EVASPA, a tool for mapping evapotranspiration from space

International audienceContext and objectives: Evapotranspiration (ET) is a fundamental variable of the hydrological cycle. There is a strong need of methods to monitor ET in space and time, e.g. for evaluating crop water use, improving knowledge in surface processes in hydrological or climate modelling, as well as for weather forecast. We have developed the EVASPA tool to provide continuous mapping of daily ET from remote sensing (RS) data at spatial and temporal scales relevant to hydrological or agronomical studies (Gallego‐Elvira et al., 2013). Further, EVASPA has been designed for providing ET estimations together with estimation uncertainties. In this poster, we provide examples of EVASPA results over the Crau‐Camargue test site (Lower Rhône valley) from MODIS TERRA and AQUA (1km resolution) and LANDSAT‐7 ETM+ data (60 m resolution)

EVASPA, a tool for mapping evapotranspiration from space

International audienceContext and objectives: Evapotranspiration (ET) is a fundamental variable of the hydrological cycle. There is a strong need of methods to monitor ET in space and time, e.g. for evaluating crop water use, improving knowledge in surface processes in hydrological or climate modelling, as well as for weather forecast. We have developed the EVASPA tool to provide continuous mapping of daily ET from remote sensing (RS) data at spatial and temporal scales relevant to hydrological or agronomical studies (Gallego‐Elvira et al., 2013). Further, EVASPA has been designed for providing ET estimations together with estimation uncertainties. In this poster, we provide examples of EVASPA results over the Crau‐Camargue test site (Lower Rhône valley) from MODIS TERRA and AQUA (1km resolution) and LANDSAT‐7 ETM+ data (60 m resolution)

EVASPA : EVapotranspiration Assessment from SPAce

National audienc

The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat

International audienc

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).

International audienc

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Are

Monitoring evapotranspiration over the Crau Aquifer from remote sensing and flux tower data.

Monitoring evapotranspiration over the Crau Aquifer from remote sensing and flux tower data.. Conference internationale MISTRALS 2015 Environment in the mediterranean statements and prospects for research and societ

Evaluation and aggregation properties of thermal Infra-Red-based evapotranspiration algorithms from 100 m to the km scale over a semi-arid irrigated agricultural area

Evapotranspiration (ET) estimates are particularly needed for monitoring the available water of arid lands. Remote sensing data offer the ideal spatial and temporal coverage needed by irrigation water management institutions to deal with increasing pressure on available water. Low spatial resolution (LR) products present strong advantages. They cover larger zones and are acquired more frequently than high spatial resolution (HR) products. Current sensors such as Moderate-Resolution Imaging Spectroradiometer (MODIS) offer a long record history. However, validation of ET products at LR remains a difficult task. In this context, the objective of this study is to evaluate scaling properties of ET fluxes obtained at high and low resolution by two commonly used Energy Balance models, the Surface Energy Balance System (SEBS) and the Two-Source Energy Balance model (TSEB). Both are forced by local meteorological observations and remote sensing data in Visible, Near Infra-Red and Thermal Infra-Red spectral domains. Remotely sensed data stem from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and MODIS sensors, respectively, resampled at 100 m and 1000 m resolutions. The study zone is a square area of 4 by 4 km located in a semi-arid irrigated agricultural zone in the northwest of Mexico. Wheat is the dominant crop, followed by maize and vegetables. The HR ASTER dataset includes seven dates between the 30 December 2007 and 13 May 2008 and the LR MODIS products were retrieved for the same overpasses. ET retrievals from HR ASTER products provided reference ET maps at LR once linearly aggregated at the km scale. The quality of this retrieval was assessed using eddy covariance data at seven locations within the 4 by 4 km square. To investigate the impact of input aggregation, we first compared to the reference dataset all fluxes obtained by running TSEB and SEBS models using ASTER reflectances and radiances previously aggregated at the km scale. Second, we compared to the same reference dataset all fluxes obtained with SEBS and TSEB models using MODIS data. LR fluxes obtained by both models driven by aggregated ASTER input data compared well with the reference simulations and illustrated the relatively good accuracy achieved using aggregated inputs (relative bias of about 3.5% for SEBS and decreased to less than 1% for TSEB). Results also showed that MODIS ET estimates compared well with the reference simulation (relative bias was down to about 2% for SEBS and 3% for TSEB). Discrepancies were mainly related to fraction cover mapping for TSEB and to surface roughness length mapping for SEBS. This was consistent with the sensitivity analysis of those parameters previously published. To improve accuracy from LR estimates obtained using the 1 km surface temperature product provided by MODIS, we tested three statistical and one deterministic aggregation rules for the most sensible input parameter, the surface roughness length. The harmonic and geometric averages appeared to be the most accurate

Total and component evapotranspiration retrieval performances of a single-pixel energy balance models over agricultural crops.

International audienc