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11 results on '"Centre d'études spatiales de la biosphère (CESBIO)"'

1. Snowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered area

Author

Esteban Alonso-González, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, Simon Gascoin, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Technology, 010504 meteorology & atmospheric sciences, 0207 environmental engineering, 02 engineering and technology, Environmental technology. Sanitary engineering, 01 natural sciences, Environmental sciences, 13. Climate action, Geography. Anthropology. Recreation, GE1-350, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 020701 environmental engineering, TD1-1066, 0105 earth and related environmental sciences
Abstract

The snowpack over the Mediterranean mountains constitutes a key water resource for the downstream populations. However, its dynamics have not been studied in detail yet in many areas, mostly because of the scarcity of snowpack observations. In this work, we present a characterization of the snowpack over the two mountain ranges of Lebanon. To obtain the necessary snowpack information, we have developed a 1 km regional-scale snow reanalysis (ICAR_assim) covering the period 2010–2017. ICAR_assim was developed by means of an ensemble-based data assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) fractional snow-covered area (fSCA) through an energy and mass snow balance model, the Flexible Snow Model (FSM2), using the particle batch smoother (PBS). The meteorological forcing data were obtained by a regional atmospheric simulation from the Intermediate Complexity Atmospheric Research model (ICAR) nested inside a coarser regional simulation from the Weather Research and Forecasting model (WRF). The boundary and initial conditions of WRF were provided by the ERA5 atmospheric reanalysis. ICAR_assim showed very good agreement with MODIS gap-filled snow products, with a spatial correlation of R=0.98 in the snow probability (P(snow)) and a temporal correlation of R=0.88 on the day of peak snow water equivalent (SWE). Similarly, ICAR_assim has shown a correlation with the seasonal mean SWE of R=0.75 compared with in situ observations from automatic weather stations (AWSs). The results highlight the high temporal variability in the snowpack in the Lebanese mountain ranges, with the differences between Mount Lebanon and the Anti-Lebanon Mountains that cannot only be explained by hypsography as the Anti-Lebanon Mountains are in the rain shadow of Mount Lebanon. The maximum fresh water stored in the snowpack is in the middle elevations, approximately between 2200 and 2500 m a.s.l. (above sea level). Thus, the resilience to further warming is low for the snow water resources of Lebanon due to the proximity of the snowpack to the zero isotherm.

Published
2021

2. Assessment of actual evapotranspiration over a semiarid heterogeneous land surface by means of coupled low-resolution remote sensing data with an energy balance model: comparison to extra-large aperture scintillometer measurements

Author

Saadi, Sameh, Boulet, Gilles, Bahir, Malik, Brut, Aurore, Delogu, Emilie, Fanise, Pascal, Mougenot, Bernard, Simonneaux, Vincent, Lili Chabaâne, Zohra, Chabaane, Zohra, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Carthage - University of Carthage, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie]), Laboratoire de Phytopathologie (Tunis, Tunisie), Institut National Agronomique de Tunisie, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)

Subjects
lcsh:GE1-350, lcsh:G, lcsh:T, [SDE.MCG]Environmental Sciences/Global Changes, lcsh:Geography. Anthropology. Recreation, lcsh:Environmental technology. Sanitary engineering, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, lcsh:Technology, lcsh:TD1-1066, lcsh:Environmental sciences
Abstract

In semiarid areas, agricultural production is restricted by water availability; hence, efficient agricultural water management is a major issue. The design of tools providing regional estimates of evapotranspiration (ET), one of the most relevant water balance fluxes, may help the sustainable management of water resources. Remote sensing provides periodic data about actual vegetation temporal dynamics (through the normalized difference vegetation index, NDVI) and water availability under water stress (through the surface temperature Tsurf), which are crucial factors controlling ET. In this study, spatially distributed estimates of ET (or its energy equivalent, the latent heat flux LE) in the Kairouan plain (central Tunisia) were computed by applying the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) model fed by low-resolution remote sensing data (Terra and Aqua MODIS). The work's goal was to assess the operational use of the SPARSE model and the accuracy of the modeled (i) sensible heat flux (H) and (ii) daily ET over a heterogeneous semiarid landscape with complex land cover (i.e., trees, winter cereals, summer vegetables). SPARSE was run to compute instantaneous estimates of H and LE fluxes at the satellite overpass times. The good correspondence (R2 = 0.60 and 0.63 and RMSE = 57.89 and 53.85 W m−2 for Terra and Aqua, respectively) between instantaneous H estimates and large aperture scintillometer (XLAS) H measurements along a path length of 4 km over the study area showed that the SPARSE model presents satisfactory accuracy. Results showed that, despite the fairly large scatter, the instantaneous LE can be suitably estimated at large scales (RMSE = 47.20 and 43.20 W m−2 for Terra and Aqua, respectively, and R2 = 0.55 for both satellites). Additionally, water stress was investigated by comparing modeled (SPARSE) and observed (XLAS) water stress values; we found that most points were located within a 0.2 confidence interval, thus the general tendencies are well reproduced. Even though extrapolation of instantaneous latent heat flux values to daily totals was less obvious, daily ET estimates are deemed acceptable.

Published
2018

3. Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France)

Author

Etchanchu, J., Rivalland, Vincent, Gascoin, Simon, Cros, J., Tallec, Tiphaine, Brut, Aurore, Boulet, Gérard, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'aérologie (LAERO), Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)

Subjects
lcsh:GE1-350, lcsh:G, lcsh:T, lcsh:Geography. Anthropology. Recreation, lcsh:Environmental technology. Sanitary engineering, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Technology, ComputingMilieux_MISCELLANEOUS, lcsh:TD1-1066, lcsh:Environmental sciences
Abstract

Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model included in the EXternalized SURface (SURFEX) modeling platform. The study focuses on the effect of the leaf area index (LAI) spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m). The study area is an agricultural zone in southwestern France covering 576 km2 (24 km × 24 km). An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE). Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE) in the simulated evapotranspiration. This finding is attributable to a better description of LAI evolution processes with Formosat-2 data, which further modify soil water content and drainage of soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels with simulations using Formosat-2 data in comparison to the reference simulation values. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

Published
2017

4. SMOS near-real-time soil moisture product: processor overview and first validation results

Author

Patricia de Rosnay, Yann Kerr, Matthias Drusch, Clément Albergel, J. M. Sabater, P. Richaume, Susanne Mecklenburg, Nemesio Rodriguez-Fernandez, Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Agence Spatiale Européenne = European Space Agency (ESA)

Subjects
010504 meteorology & atmospheric sciences, Meteorology, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, lcsh:Technology, Standard deviation, lcsh:TD1-1066, Soil temperature, Range (statistics), lcsh:Environmental technology. Sanitary engineering, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Water content, Retrieval algorithm, lcsh:Environmental sciences, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, General Environmental Science, Remote sensing, lcsh:GE1-350, lcsh:T, lcsh:Geography. Anthropology. Recreation, Numerical weather prediction, lcsh:G, [SDU]Sciences of the Universe [physics], 13. Climate action, Product (mathematics), General Earth and Planetary Sciences, Environmental science, Satellite
Abstract

Measurements of the surface soil moisture (SM) content are important for a wide range of applications. Among them, operational hydrology and numerical weather prediction, for instance, need SM information in near-real-time (NRT), typically not later than 3 h after sensing. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite is the first mission specifically designed to measure SM from space. The ESA Level 2 SM retrieval algorithm is based on a detailed geophysical modelling and cannot provide SM in NRT. This paper presents the new ESA SMOS NRT SM product. It uses a neural network (NN) to provide SM in NRT. The NN inputs are SMOS brightness temperatures for horizontal and vertical polarizations and incidence angles from 30 to 45°. In addition, the NN uses surface soil temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS). The NN was trained on SMOS Level 2 (L2) SM. The swath of the NRT SM retrieval is somewhat narrower (∼ 915 km) than that of the L2 SM dataset (∼ 1150 km), which implies a slightly lower revisit time. The new SMOS NRT SM product was compared to the SMOS Level 2 SM product. The NRT SM data show a standard deviation of the difference with respect to the L2 data of 3 m−3 in most of the Earth and a Pearson correlation coefficient higher than 0.7 in large regions of the globe. The NRT SM dataset does not show a global bias with respect to the L2 dataset but can show local biases of up to 0.05 m3 m−3 in absolute value. The two SMOS SM products were evaluated against in situ measurements of SM from more than 120 sites of the SCAN (Soil Climate Analysis Network) and the USCRN (US Climate Reference Network) networks in North America. The NRT dataset obtains similar but slightly better results than the L2 data. In summary, the NN SMOS NRT SM product exhibits performances similar to those of the Level 2 SM product but it has the advantage of being available in less than 3.5 h after sensing, complying with NRT requirements. The new product is processed at ECMWF and it is distributed by ESA and via the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) multicast service (EUMETCast).

Published
2017

5. A snow cover climatology for the Pyrenees from MODIS snow products

Author

Mireille Huc, R Sánchez, Renaud Marti, Camille Szczypta, Simon Gascoin, Olivier Hagolle, Jean-François Dejoux, Lionel Jarlan, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Géographie de l'environnement (GEODE), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Confederación hidrográfica del Ebro - CHE (SPAIN), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), and Université Toulouse - Jean Jaurès (UT2J)-Centre National de la Recherche Scientifique (CNRS)

Subjects
010504 meteorology & atmospheric sciences, 0207 environmental engineering, 02 engineering and technology, Land cover, lcsh:Technology, 01 natural sciences, lcsh:TD1-1066, Hydrology (agriculture), medicine, Satellite imagery, lcsh:Environmental technology. Sanitary engineering, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, 020701 environmental engineering, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, lcsh:T, lcsh:Geography. Anthropology. Recreation, Elevation, Vegetation, 15. Life on land, Snowpack, Seasonality, medicine.disease, Snow, lcsh:G, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, 13. Climate action, Climatology, Environmental science
Abstract

The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively, for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snowpack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50% of the time above 1600 m between December and April. We finally analyze the snow patterns for the atypical winter 2011–2012. Snow cover duration anomalies reveal a deficient snowpack on the Spanish side of the Pyrenees, which seems to have caused a drop in the national hydropower production.

Published
2015

6. Combining high-resolution satellite images and altimetry to estimate the volume of small lakes

Author

J. M. Maubant, Frédéric Baup, Frédéric Frappart, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)

Subjects
lcsh:GE1-350, 010504 meteorology & atmospheric sciences, lcsh:T, 0211 other engineering and technologies, lcsh:Geography. Anthropology. Recreation, High resolution, 02 engineering and technology, 01 natural sciences, lcsh:Technology, lcsh:TD1-1066, 6. Clean water, lcsh:G, [SDU]Sciences of the Universe [physics], 13. Climate action, Satellite, Altimeter, lcsh:Environmental technology. Sanitary engineering, lcsh:Environmental sciences, Geology, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, Volume (compression)
Abstract

This study presents an approach to determining the volume of water in small lakes (R2ABV = 0.98, RMSEABV = 5%, R2HRBV = 0.90, and RMSEABV = 7.4%), assuming a time-varying triangular shape for the shore slope of the lake (this form is well adapted since it implies a difference inferior to 2% between the theoretical volume of the lake and the one estimated from bathymetry). The third method (AHRBVC) combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2AHRBVC = 0.98) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.

Published
2014

7. An original interpretation of the wet edge of the surface temperature–albedo space to estimate crop evapotranspiration (SEB-1S), and its validation over an irrigated area in northwestern Mexico

Author

Olivier Merlin, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Surface (mathematics), 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, 0211 other engineering and technologies, evapotranspiration, 02 engineering and technology, Edge (geometry), Space (mathematics), Atmospheric sciences, 01 natural sciences, lcsh:Technology, irrigation, lcsh:TD1-1066, Evapotranspiration, Point (geometry), [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, lcsh:Environmental technology. Sanitary engineering, lcsh:Environmental sciences, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, lcsh:GE1-350, lcsh:T, evaporative fraction, lcsh:Geography. Anthropology. Recreation, temperature, Albedo, lcsh:G, 13. Climate action, Available energy, Line (geometry), Geology, albedo
Abstract

The space defined by the pair surface temperature (T) and surface albedo (α), and the space defined by the pair T and fractional green vegetation cover (fvg) have been extensively used to estimate evaporative fraction (EF) from solar/thermal remote sensing data. In both space-based approaches, evapotranspiration (ET) is estimated as remotely sensed EF times the available energy. For a given data point in the T-α space or in the T-fvg space, EF is derived as the ratio of the distance separating the point from the line identified as the dry edge to the distance separating the dry edge and the line identified as the wet edge. The dry and wet edges are classically defined as the upper and lower limit of the spaces, respectively. When investigating side by side the T-α and the T-fvg spaces, one observes that the range covered by T values on the (classically determined) wet edge is different for both spaces. In addition, when extending the wet and dry lines of the T-α space, both lines cross at α ≈ 0.4 although the wet and dry edges of the T-fvg space never cross for 0 &leq; fvg < 1. In this paper, a new ET (EF) model (SEB-1S) is derived by revisiting the classical physical interpretation of the T-α space to make its wet edge consistent with that of the T-fvg space. SEB-1S is tested over a 16 km by 10 km irrigated area in northwestern Mexico during the 2007–2008 agricultural season. The classical T-α space-based model is implemented as benchmark to evaluate the performance of SEB-1S. 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-1S and the classical T-α space-based model are compared on seven ASTER overpass dates with the in situ measurements collected at six locations within the study domain. The ET simulated by SEB-1S is significantly more accurate and robust than that predicted by the classical T-α space-based model. The correlation coefficient and slope of the linear regression between simulated and observed ET is improved from 0.82 to 0.93, and from 0.63 to 0.90, respectively. Moreover, constraining the wet edge using air temperature data improves the slope of the linear regression between simulated and observed ET.

Published
2013

8. Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation

Author

A. Chahbi, Mehrez Zribi, Abdelghani Chehbouni, Rim Amri, Nicolas Baghdadi, Zohra Lili-Chabaane, Benoît Duchemin, Marouen Shabou, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Météo France-Centre National de la Recherche Scientifique (CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Météo France, INAT, Université de Carthage - University of Carthage, Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), UNIVERSITE CADI AYYAD MARRAKECH MAR, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), INAT Laboratoire Recherche-Développement Sciences et Technologie de l'Eau (INAT-LRSTE), Université de Carthage - University of Carthage-INAT, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), The publication of this article is financed by CNRS-INSU., Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Irrigation, 010504 meteorology & atmospheric sciences, 0211 other engineering and technologies, Soil science, 02 engineering and technology, lcsh:Technology, 01 natural sciences, lcsh:TD1-1066, law.invention, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, law, lcsh:Environmental technology. Sanitary engineering, Radar, Water content, lcsh:Environmental sciences, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, lcsh:GE1-350, 2. Zero hunger, Moisture, lcsh:T, lcsh:Geography. Anthropology. Recreation, Vegetation, 15. Life on land, Arid, lcsh:G, [SDE]Environmental Sciences, Potential evaporation, Environmental science, Satellite
Abstract

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE; The present paper proposes a method for the evaluation of soil evaporation, using soil moisture estimations based on radar satellite measurements. We present firstly an approach for the estimation and monitoring of soil moisture in a semi-arid region in North Africa, using ENVISAT ASAR images, over two types of vegetation covers. The first mapping process is dedicated solely to the monitoring of moisture variability related to rainfall events, over areas in the "non-irrigated olive tree" class of land use. The developed approach is based on a simple linear relationship between soil moisture and the backscattered radar signal normalised at a reference incidence angle. The second process is proposed over wheat fields, using an analysis of moisture variability due to both rainfall and irrigation. A semi-empirical model, based on the water-cloud model for vegetation correction, is used to retrieve soil moisture from the radar signal. Moisture mapping is carried out over wheat fields, showing high variability between irrigated and non-irrigated wheat covers. This analysis is based on a large database, including both ENVISAT ASAR and simultaneously acquired ground-truth measurements (moisture, vegetation, roughness), during the 2008-2009 vegetation cycle. Finally, a semi-empirical approach is proposed in order to relate surface moisture to the difference between soil evaporation and the climate demand, as defined by the potential evaporation. Mapping of the soil evaporation is proposed.

Published
2011

9. Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region

Author

Françoise Ruget, B. Duchemin, Olivier Hagolle, Albert Olioso, Dominique Courault, Rachid Hadria, G. Dedieu, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), DAR 2006 TOSCA, Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)

Subjects
GRASSLAND, 010504 meteorology & atmospheric sciences, télédétection, évapotranspiration, lcsh:Technology, 01 natural sciences, CROP MODEL, Sciences de la Terre, irrigation, Grassland, zone méditerranéenne, Water balance, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Evapotranspiration, gestion de l'eau, lcsh:Environmental technology. Sanitary engineering, bilan hydrique, Drainage, lcsh:Environmental sciences, lcsh:GE1-350, 2. Zero hunger, geography.geographical_feature_category, lcsh:Geography. Anthropology. Recreation, 04 agricultural and veterinary sciences, WATER BUDGET, INDICE FOLIAIRE, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, drainage, Irrigation, WATER MANAGEMENT, AGRICULTURAL PRACTICE, REMOTE SENSING, LEAF AREA INDEX, MEDITERANEAN REGION, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, lcsh:TD1-1066, prévision de rendement, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Leaf area index, pratique culturale, modélisation, 0105 earth and related environmental sciences, Hydrology, geography, lcsh:T, Crop yield, prairie permanente, 15. Life on land, lcsh:G, Earth Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Spatial variability
Abstract

The aim of this study is to propose methods to improve crop and water management in Mediterranean regions. At landscape scale, there is a very large spatial variability of agricultural practices, particularly for grasslands irrigated by flooding. These grasslands are harvested three times per year and produce high quality hay, but their productions decreased significantly these last few years because of the water scarcity. It is therefore important to assess the real water requirement for crops in order to predict productions in the case of agricultural practice modifications. Until now, the spatial variability of agricultural practices was obtained through surveys from farmers, but this method was tedious to describe an entire region. Thus, the specific aim of the study is to propose a new approach based on: 1) the feasibility of using optical remote sensing data acquired at high spatio-temporal resolutions for agricultural practice monitoring and, 2) the evaluation of a crop model, forced with this data, for estimating water balance and crop yield. We developed a methodology based on the combined use of FORMOSAT-2 images and STICS crop model to estimate production, evapotranspiration and drainage of irrigated grasslands in "the Crau" region in the South Eastern France. Numerous surveys and ground measurements were performed during an experiment conducted in 2006. Simple algorithms were developed to retrieve the dynamic of Leaf Area Index (LAI) for each plot and the main agricultural practices such as mowing and irrigation dates. This information was then used to parameterize STICS, applied at region scale to estimate the spatial variability of water budget associated with the biomass productions. Results are displayed at the farm scale. Satisfactory results were obtained when compared to ground measurements. The method for extrapolation to other regions or crops is discussed as regard to data available.

Published
2010

10. Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

Author

Dan Braithwaite, S. Juglea, Kuolin Hsu, Arnaud Mialon, Yann Kerr, Ernesto Lopez-Baeza, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Facultat de Fisica [València] (UV), Universitat de València (UV), Center for Hydrometeorology and Remote Sensing (CHRS), University of California [Irvine] (UCI), University of California-University of California, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of California [Irvine] (UC Irvine), and University of California (UC)-University of California (UC)

Subjects
010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, satellite, 0207 environmental engineering, Context (language use), 02 engineering and technology, system, computer.software_genre, rainfall estimation, 01 natural sciences, lcsh:Technology, lcsh:TD1-1066, Precipitation, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, lcsh:Environmental technology. Sanitary engineering, 020701 environmental engineering, Water content, precipitation estimation, retrieval, lcsh:Environmental sciences, 0105 earth and related environmental sciences, Remote sensing, lcsh:GE1-350, Database, Rain gauge, Moisture, lcsh:T, lcsh:Geography. Anthropology. Recreation, Life Sciences, neural-network, 15. Life on land, parameterization, okavango river, products, africa, lcsh:G, 13. Climate action, Soil water, PERSIANN, Environmental science, Spatial variability, computer
Abstract

In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS1database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km2). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe. A faithful representation of the soil moisture distribution at SMOS pixel scale (50×50 km2) requires an accurate estimation of the amount and temporal/spatial distribution of precipitation. To quantify the gain of using the comprehensive PERSIANN database instead of sparsely distributed rain gauge measurements, comparisons between in situ observations and satellite rainfall data are done both at point and areal scale. An overestimation of the satellite rainfall amounts is observed in most of the cases (about 66%) but the precipitation occurrences are in general retrieved (about 67%). To simulate the high variability in space and time of surface soil moisture, a Soil Vegetation Atmosphere Transfer (SVAT) model – ISBA (Interactions between Soil Biosphere Atmosphere) is used. The interest of using satellite rainfall estimates as well as the influence that the precipitation events can induce on the modelling of the water content in the soil is depicted by a comparison between different soil moisture data. Point-like and spatialized simulated data using rain gauge observations or PERSIANN – CCS database as well as ground measurements are used. It is shown that a good adequacy is reached in most part of the year, the precipitation differences having less impact upon the simulated soil moisture. The behaviour of simulated surface soil moisture at SMOS scale is verified by the use of remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E). We show that the PERSIANN database provides useful information at temporal and spatial scales in the context of soil moisture retrieval. 1Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System – http://chrs.web.uci.edu/persiann

Published
2010

11. Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin

Author

S. M. Vicente-Serrano, Juan I. López-Moreno, Instituto Pirenaico de Ecologia (IPE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Unit for Landscape Modelling, University of Cambridge [UK] (CAM), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Instituto Pirenaico de Ecologìa = Pyrenean Institute of Ecology [Zaragoza] (IPE - CSIC)

Subjects
010504 meteorology & atmospheric sciences, 0207 environmental engineering, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Economic shortage, 02 engineering and technology, Structural basin, lcsh:Technology, 01 natural sciences, Mediterranean Basin, lcsh:TD1-1066, Precipitation, lcsh:Environmental technology. Sanitary engineering, Water cycle, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 020701 environmental engineering, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, lcsh:T, lcsh:Geography. Anthropology. Recreation, 15. Life on land, 6. Clean water, Water demand, lcsh:G, 13. Climate action, Climatology, Environmental science, Precipitation index, Spatial extent
Abstract

11 páginas, 7 figuras, 1 tabla.-- This work is licensed under a Creative Commons License., At present, the Standardized Precipitation Index (SPI) is the most widely used drought index to provide good estimations about the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI in comparison with other indices is the fact that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. It is widely accepted that SPI time scales affect different sub-systems in the hydrological cycle due to the fact that the response of the different water usable sources to precipitation shortages can be very different. The long time scales of SPI are related to hydrological droughts (river flows and reservoir storages). Nevertheless, few analyses empirically verify these statements or the usefulness of the SPI time scales to monitor drought. In this paper, the SPI at different time scales is compared with surface hydrological variables in a big closed basin located in the central Spanish Pyrenees. We provide evidence about the way in which the longer (>12 months) SPI time scales may not be useful for drought quantification in this area. In general, the surface flows respond to short SPI time scales whereas the reservoir storages respond to longer time scales (7–10 months). Nevertheless, important seasonal differences can be identified in the SPI-usable water sources relationships. This suggests that it is necessary to test the drought indices and time scales in relation to their usefulness for monitoring different drought types under different environmental conditions and water demand situations., The authors want to acknowledge financial support from the following projects: BSO2002-02743, REN2003-07453, CGL2005-04508/BOS, PIRIHEROS (REN2003- 08678/HID) and CANOA (CGL 2004-04919-c02-01), funded by Ministerio de Ciencia y Tecnología (Spain) and UE-FEDER, and “Programa de grupos de investigación consolidados” (BOA 48 of 20-04-2005), funded by Aragon Government. Research of the first author was supported by postdoctoral fellowship by the Ministerio de Educación y Ciencia (Spain).

Published
2005

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