EVASPA (EVapotranspiration Assessment from SPAce) Tool: An overview

AbstractEvapotranspiration (ET) is a fundamental variable of the hydrological cycle and its estimation is required for irrigation management, water resources planning and environmental studies. Remote sensing provides spatially distributed cost-effective information for ET maps production at regional scale. We have developed EVASPA too for mapping ET from remote sensing data at spatial and temporal scales relevant to hydrological or agronomica studies.EVASPA includes several algorithms for estimating evapotranspiration and various equations for estimating the required input information (net radiation, ground heat flux, evaporative fraction…), which provides a way to assess uncertainties in the derivation of ET. The tool integrates data from various remote sensing sensors and it can be easily adapted to new sensors. To test the tool, evapotranspiration maps have been produced for the Crau-Camargue pilot site (south-eastern France), where several energy balance stations deployed in contrasted areas provide ground measurements. An overall description of the tool and first results of performance asse sment (comparison to ground data) are presented here

Uncertainty assessment of surface net radiation derived from Landsat images

The net radiation flux available at the Earth's surface drives evapotranspiration, photosynthesis and other physical and biological processes. The only cost-effective way to capture its spatial and temporal variability at regional and global scales is remote sensing. However, the accuracy of net radiation derived from remote sensing data has been evaluated up to now over a limited number of in situ measurements and ecosystems. This study aims at evaluating estimates and uncertainties on net radiation derived from Landsat-7 images depending on reliability of the input surface variables albedo, emissivity and surface temperature. The later includes the reliability of remote sensing information (spectral reflectances and top of canopy brightness temperature) and shortwave and longwave incoming radiations. Primary information describing the surface is derived from remote sensing observations. Surface albedo is estimated from spectral reflectances using a narrow-to-broadband conversion method. Land surface temperature is retrieved from top of canopy brightness temperature by accounting for land surface emissivity and reflection of atmospheric radiation; and emissivity is estimated using a relationship with a vegetation index and a spectral database of soil and plant canopy properties in the study area. The net radiation uncertainty is assessed using comparison with ground measurements over the Crau–Camargue and lower Rhone valley regions in France. We found Root Mean Square Errors between retrievals and field measurements of 0.25–0.33 (14–19%) for albedo, ~ 1.7 K for surface temperature and ~ 20 W·m− 2 (5%) for net radiation. Results show a substantial underestimation of Landsat-7 albedo (up to 0.024), particularly for estimates retrieved using the middle infrared, which could be due to different sources: the calibration of field sensors, the correction of radiometric signals from Landsat-7 or the differences in spectral bands with the sensors for which the models where originally derived, or the atmospheric corrections. We report a global uncertainty in net radiation of 40–100 W·m− 2 equally distributed over the shortwave and longwave radiation, which varies spatially and temporally depending on the land use and the time of year. In situ measurements of incoming shortwave and longwave radiation contribute the most to uncertainty in net radiation (10–40 W·m− 2 and 20–30 W·m− 2, respectively), followed by uncertainties in albedo (< 25 W·m− 2) and surface temperature (~ 8 W·m− 2). For the latter, the main factors were the uncertainties in top of canopy reflectances (< 10 W·m− 2) and brightness temperature (5–7 W·m− 2). The generalization of these results to other sensors and study regions could be considered, except for the emissivity if prior knowledge on its characterization is not available

Modeling actual water use under different irrigation regimes at district scale: Application to the FAO-56 dual crop coefficient method

The modeling of irrigation in land surface models are generally based on two soil moisture parameters SMthreshold and SMtarget at which irrigation automatically starts and stops, respectively. Typically, both parameters are usually set to optimal values allowing to fill the soil water reservoir with just the estimated right amount and to avoid crop water excess at all times. The point is that agricultural practices greatly vary according to many factors (climatological, crop, soil, technical, human, etc.). To fill the gap, we propose a new calibration method of SMthreshold and SMtarget to represent the irrigation water use in any (optimal, deficit or even over) irrigation regime. The approach is tested using the dual-crop coefficient FAO-56 model implemented at the field scale over an 8100 ha irrigation district in northeastern Spain where the irrigation water use is precisely monitored at the district scale. Both irrigation parameters are first retrieved at monthly scale from the irrigation observations of year 2019. The irrigation simulated by the FAO-56 model is then evaluated against observations at district and weekly scale over 5 years (2017–2021) separately. The performance of the newly calibrated irrigation module is also assessed by comparing it against three other modules with varying configurations including default estimates for SMthreshold and SMtarget. The proposed irrigation module obtains systematically the best performance for each of the 5 years with an overall correlation coefficient of 0.95 ± 0.02 and root-mean square error of 0.27 ± 0.07 hm3/week (0.64 ± 0.17 mm/day). Unlike the three irrigation modules used as benchmark, the new irrigation module is able to reproduce the farmers’ practices throughout the year, and especially, to simulate the actual water use in the deficit and excess irrigation regimes occurring in the study area in spring and summer, respectively.This study was supported by the IDEWA project ( ANR-19-P026-003 ) of the Partnership for research and innovation in the Mediterranean area ( PRIMA ) program and by the Horizon 2020 ACCWA project (grant agreement # 823965 ) in the context of Marie Sklodowska-Curie Research and Innovation Staff Exchange (RISE) program. The authors wish to acknowledge the "Comunitat de Regants Canal Algerri Balaguer" and the Ebro Hydrographic Confederation (SAIH Ebro) for providing the observation irrigation data used in this study

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

Evapotranspiration is an important component of the water cycle, especially in semi-arid lands. A way to quantify the spatial distribution of evapotranspiration and water stress from remote-sensing data is to exploit the available surface temperature as a signature of the surface energy balance. Remotely sensed energy balance models enable one to estimate stress levels and, in turn, the water status of continental surfaces. Dual-source models are particularly useful since they allow derivation of a rough estimate of the water stress of the vegetation instead of that of a soil&#8211;vegetation composite. They either assume that the soil and the vegetation interact almost independently with the atmosphere (patch approach corresponding to a parallel resistance scheme) or are tightly coupled (layer approach corresponding to a series resistance scheme). The water status of both sources is solved simultaneously from a single surface temperature observation based on a realistic underlying assumption which states that, in most cases, the vegetation is unstressed, and that if the vegetation is stressed, evaporation is negligible. In the latter case, if the vegetation stress is not properly accounted for, the resulting evaporation will decrease to unrealistic levels (negative fluxes) in order to maintain the same total surface temperature. This work assesses the retrieval performances of total and component evapotranspiration as well as surface and plant water stress levels by (1) proposing a new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) in two versions (parallel and series resistance networks) based on the TSEB (Two-Source Energy Balance model, Norman et al., 1995) model rationale as well as state-of-the-art formulations of turbulent and radiative exchange, (2) challenging the limits of the underlying hypothesis for those two versions through a synthetic retrieval test and (3) testing the water stress retrievals (vegetation water stress and moisture-limited soil evaporation) against in situ data over contrasted test sites (irrigated and rainfed wheat). We demonstrated with those two data sets that the SPARSE series model is more robust to component stress retrieval for this cover type, that its performance increases by using bounding relationships based on potential conditions (root mean square error lowered by up to 11 W m&#8722;2 from values of the order of 50&#8211;80 W m&#8722;2), and that soil evaporation retrieval is generally consistent with an independent estimate from observed soil moisture evolution

Agrometerological study of semi-arid areas : an experiment for analysing the potential of time series of FORMOSAT-2 images (Tensift-Marrakech plain)

Earth Observing Systems designed to provide both high spatial resolution (10m) and high capacity of time revisit (a few days) offer strong opportunities for the management of agricultural water resources. The FORMOSAT-2 satellite is the first and only satellite with the ability to provide daily high-resolution images over a particular area with constant viewing angles. As part of the SudMed project, one of the first time series of FORMOSAT-2 images has been acquired over the semi-arid Tensift-Marrakech plain. Along with these acquisitions, an experimental data set has been collected to monitor land-cover/land-use, soil characteristics, vegetation dynamics and surface fluxes. This paper presents a first analysis of the potential of these data for agrometerological study of semi-arid areas

Référentiel de connaissances pour un numérique éco-responsable

L’objectif de ce document est de définir un référentiel/socle de connaissances commun pour les enseignements sur le numérique responsable (impacts du numérique et comment les limiter1), à destination de formations en informatique ou d’autres filières incluant des cours d’informatique.Nous cherchons à répondre à la question suivante :Quelles connaissances devrait apporter une formation en informatique à des étudiantes et étudiants pour leur permettre d’apporter des réponses aux enjeux environnementaux et sociétaux dans leur vie professionnelle et citoyenne ?Ce document est donc focalisé sur les impacts du numérique, mais certains aspects plus généraux(enjeux environnementaux, contexte économique...) sont néanmoins abordés car nécessaires à la compréhension des aspects informatiques.Ce référentiel vise à fournir des notions et références utiles, mais n’a pas vocation à remplacer un cours

Migratory Pathways and Connectivity in Asian Houbara Bustards: Evidence from 15 Years of Satellite Tracking

Information on migratory pathways and connectivity is essential to understanding population dynamics and structure of migrant species. Our manuscript uses a unique dataset, the fruit of 103 individual Asian houbara bustards captured on their breeding grounds in Central Asia over 15 years and equipped with satellite transmitters, to provide a better understanding of migratory pathways and connectivity; such information is critical to the implementation of biologically sound conservation measures in migrant species. At the scale of the distribution range we find substantial migratory connectivity, with a clear separation of migration pathways and wintering areas between western and eastern migrants. Within eastern migrants, we also describe a pattern of segregation on the wintering grounds. But at the local level connectivity is weak: birds breeding within the limits of our study areas were often found several hundreds of kilometres apart during winter. Although houbara wintering in Arabia are known to originate from Central Asia, out of all the birds captured and tracked here not one wintered on the Arabian Peninsula. This is very likely the result of decades of unregulated off-take and severe habitat degradation in this area. At a time when conservation measures are being implemented to safeguard the long-term future of this species, this study provides critical data on the spatial structuring of populations

ARIA 2016 : Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle

The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma and rhinitis and (3) to develop guidelines with all stakeholders that could be used globally for all countries and populations. ARIA-disseminated and implemented in over 70 countries globally-is now focusing on the implementation of emerging technologies for individualized and predictive medicine. MASK [MACVIA (Contre les Maladies Chroniques pour un Vieillissement Actif)-ARIA Sentinel NetworK] uses mobile technology to develop care pathways for the management of rhinitis and asthma by a multi-disciplinary group and by patients themselves. An app (Android and iOS) is available in 20 countries and 15 languages. It uses a visual analogue scale to assess symptom control and work productivity as well as a clinical decision support system. It is associated with an inter-operable tablet for physicians and other health care professionals. The scaling up strategy uses the recommendations of the European Innovation Partnership on Active and Healthy Ageing. The aim of the novel ARIA approach is to provide an active and healthy life to rhinitis sufferers, whatever their age, sex or socio-economic status, in order to reduce health and social inequalities incurred by the disease.Peer reviewe

ARIA 2016: Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle

The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma a