6 results on '"Pôle d'Etudes et Recherches AFB-Irstea Hydroécologie des Plans d'eau (France)"'
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2. Contribution of 3D coupled hydrodynamic-ecological modeling to assess the representativeness of a sampling protocol for lake water quality assessment
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Vincent Chanudet, Bastiaan Willem Ibelings, Yann Guénand, Dominique Trevisan, Pierre-Alain Danis, Orlane Anneville, Tristan Harmel, Damien Bouffard, Etienne Dambrine, Frédéric Soulignac, R. E. Uittenbogaard, Centre Alpin de Recherche sur les Réseaux Trophiques et Ecosystèmes Limniques (CARRTEL), Institut National de la Recherche Agronomique (INRA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Ecole Polytechnique Fédérale de Lausanne (EPFL), Swiss Federal Insitute of Aquatic Science and Technology [Dübendorf] (EAWAG), Centre d'Ingénierie Hydraulique [Savoie Technolac] (CIH-EDF), EDF (EDF), Géosciences Environnement Toulouse (GET), Institut national des sciences de l'Univers (INSU - CNRS)-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-Université Fédérale Toulouse Midi-Pyrénées-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), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Department F.-A. Forel for Environmental and Aquatic Sciences, University of Geneva, Deltares [The Netherlands], Agence Française pour la Biodiversité (AFB), French Agency for Biodiversity (AFB) 15000239European Space Agency (ESA) Scientific Exploitation of Operational Missions element (SEOM) A0/1-8216/15/I-SBoFrench Alpine Lakes Observatory International Commission for the Protection of Lake Geneva (CIPEL) AnaEE-France Department of environment, transport and agriculture (DETA) of the Geneva water ecology service, laboratoire Eau Environnement et Systèmes Urbains (LEESU), AgroParisTech-École des Ponts ParisTech (ENPC)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National de la Recherche Agronomique (INRA), EDF-CIH, Savoie Technolac, Pôle d'Etudes et Recherches AFB-Irstea Hydroécologie des Plans d'eau (France), Agence Française pour la Biodiversité - AFB (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)-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)
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0106 biological sciences ,010501 environmental sciences ,Management, Monitoring, Policy and Law ,Aquatic Science ,Structural basin ,water quality ,01 natural sciences ,Representativeness heuristic ,lcsh:Aquaculture. Fisheries. Angling ,3D modeling ,Ecosystem model ,lakes ,water framework directive ,ddc:550 ,Lake Geneva ,phytoplankton abundance ,lac de genève ,0105 earth and related environmental sciences ,Nature and Landscape Conservation ,Water Science and Technology ,ddc:333.7-333.9 ,lcsh:SH1-691 ,[SDV.EE]Life Sciences [q-bio]/Ecology, environment ,Hydrology ,Ecology ,010604 marine biology & hydrobiology ,modèle 3d ,qualité de l'eau ,Sampling (statistics) ,6. Clean water ,Spatial heterogeneity ,Lakes ,Water quality ,Water Framework Directive ,13. Climate action ,Water framework directive ,Environmental science ,Spatial variability ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology - Abstract
This study deals with the impact of spatio-temporal heterogeneities on the assessment of lake ecological status according to the European water framework directive (WFD). A method, based on three-dimensional coupled hydrodynamic and ecological modeling, is presented to assess the variability of lake ecological status, and to locate the most representative sampling station of Lake Geneva (France/Switzerland). Five variables used in the lake ecological status evaluation were simulated by using the free software Delft3D. The numerical simulation results showed that the simulated ecological status based on chlorophyll a and total phosphorus concentrations measured at the regulatory monitoring station depend on the choice of the sampling date. Results also indicated a strong spatial heterogeneity in ecological status that varies from “poor” to “good” along an East-West gradient. Finally, the numerical simulation results showed that the most representative point of a mean theoretical ecological quality for Lake Geneva would be located in the center of the upper basin, close to the historical sampling station.
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- 2019
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3. Sunglint correction of the Multi-Spectral Instrument (MSI)-SENTINEL-2 imagery over inland and sea waters from SWIR bands
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Pierre-Alain Danis, Tristan Harmel, Malik Chami, Thierry Tormos, Nathalie Reynaud, SORBONNE UNIVERSITÉS UPMC UNIV PARIS 06 INSU-CNRS LABORATOIRE D'OCÉANOGRAPHIE DE VILLEFRANCHE FRA, 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), Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), INSTITUT UNIVERSITAIRE DE FRANCE PARIS FRA, Agence Française pour la Biodiversité (AFB), Pôle Écla - écosystèmes lacustres (ECLA), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Office français de la biodiversité (OFB), Pôle d'Etudes et Recherches AFB-Irstea Hydroécologie des Plans d'eau (France), Agence Française pour la Biodiversité - AFB (FRANCE), Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), and Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)
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010504 meteorology & atmospheric sciences ,Meteorology ,AERONET-OC ,Soil Science ,Sunglint ,01 natural sciences ,010309 optics ,CAMS DATA ,0103 physical sciences ,WATER COLOR ,14. Life underwater ,ATMOSPHERIC CORRECTION ,Computers in Earth Sciences ,0105 earth and related environmental sciences ,Remote sensing ,[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] ,Atmospheric correction ,Geology ,Spectral bands ,SUNGLINT ,OCEAN COLOR ,AERONET ,SENTINEL-2 ,13. Climate action ,Ocean color ,[SDE]Environmental Sciences ,Radiance ,Environmental science ,Satellite ,Bidirectional reflectance distribution function ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
International audience; Remote sensing of inland and sea waters depends on the quality of the retrieval of the water-leaving radiance from the top-of-atmosphere measurements. The water-leaving radiance can be difficult to observe due to the reflection of direct sunlight on the air-water interface (sunglint) in the direction of the satellite field of view. The viewing geometry of Sentinel-2 satellite (European Space Agency) makes it vulnerable to sunglint contamination. In this paper, an original method is proposed to correct Sentinel-2-like imagery for sunglint contamination. The sunglint contribution is first estimated from the shortwave-infrared (SWIR) part of the spectrum and then extrapolated toward the near-infrared and visible bands. The spectral variation of the sunglint signal is thus revisited for a wide spectral range (from 350 to 2500 nm). The bidirectional reflectance distribution function related to the sunglint is shown to vary by > 28% from the SWIR to the blue bands of Sentinel-2. The application of the proposed algorithm on actual Sentinel-2 data demonstrates that sunglint patterns are satisfactorily removed over the entire images whatever the altitude of the observed target. Comparison with in situ data of water-leaving radiances (AERONET-OC) showed that our proposed algorithm significantly improves the correlation between satellite and in situ data by 55% (i.e., from R2 = 0.56 to R2 = 0.87). In addition, the discrepancies between satellite and in situ measurements are reduced by 60%. It is also shown that the aerosol data provided by the Copernicus Atmosphere Monitoring Service (CAMS) can be safely used within the proposed algorithm to correct the Sentinel-2-like satellite data for both sunglint and atmospheric radiances. Improvements of the proposed method potentially rely on simultaneous retrievals of the aerosol optical properties. The proposed method is applicable to any satellite sensor which is able to measure in SWIR spectral bands over aquatic environments.
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- 2018
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4. Detection of flavescence dorée grapevine disease using unmanned aerial vehicle (UAV) multispectral imagery
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Michel Goulard, Gérard Dedieu, Hervé Poilvé, Johanna Albetis, Jean-Baptiste Féret, Fabio Güttler, Sylvie Duthoit, Anne Jacquin, Dynamiques Forestières dans l'Espace Rural (DYNAFOR), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, UMR 1201 Dynamiques et écologie des paysages agriforestiers, Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), TerraNIS, Airbus Defence and Space, Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS), 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), Centre National d'Études Spatiales [Toulouse] (CNES), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD [France-Ouest]), Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Institut National de la Recherche Agronomique - INRA (FRANCE), Institut national de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture - IRSTEA (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Institut national des sciences de l'Univers - INSU (FRANCE), Pôle d'Etudes et Recherches AFB-Irstea Hydroécologie des Plans d'eau (France), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), 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 National Polytechnique de Toulouse - Toulouse INP (FRANCE), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), 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 Toulouse (UT), and albetis de la cruz, Johanna
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Multivariate statistics ,010504 meteorology & atmospheric sciences ,Biodiversité et Ecologie ,Multispectral image ,precision viticulture ,disease detection ,unmanned aerial vehicle (UAV) ,flavescence dorée grapevine disease ,vegetation indices ,biophysical parameters ,0211 other engineering and technologies ,Context (language use) ,02 engineering and technology ,01 natural sciences ,Biodiversity and Ecology ,Vegetation indices ,Biophysical parameters ,Flavescence dorée grapevine disease ,021101 geological & geomatics engineering ,0105 earth and related environmental sciences ,Remote sensing ,Precision viticulture ,Ground truth ,Spectral signature ,Univariate ,15. Life on land ,Disease detection ,Geography ,Unmanned aerial vehicle (UAV) ,General Earth and Planetary Sciences ,Flavescence dorée ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology - Abstract
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS; Flavescence dorée is a grapevine disease affecting European vineyards which has severe economic consequences and containing its spread is therefore considered as a major challenge for viticulture. Flavescence dorée is subject to mandatory pest control including removal of the infected vines and, in this context, automatic detection of Flavescence dorée symptomatic vines by unmanned aerial vehicle (UAV) remote sensing could constitute a key diagnosis instrument for growers. The objective of this paper is to evaluate the feasibility of discriminating the Flavescence dorée symptoms in red and white cultivars from healthy vine vegetation using UAV multispectral imagery. Exhaustive ground truth data and UAV multispectral imagery (visible and near-infrared domain) have been acquired in September 2015 over four selected vineyards in Southwest France. Spectral signatures of healthy and symptomatic plants were studied with a set of 20 variables computed from the UAV images (spectral bands, vegetation indices and biophysical parameters) using univariate and multivariate classification approaches. Best results were achieved with red cultivars (both using univariate and multivariate approaches). For white cultivars, results were not satisfactory either for the univariate or the multivariate. Nevertheless, external accuracy assessment show that despite problems of Flavescence dorée and healthy pixel misclassification, an operational Flavescence dorée mapping technique using UAV-based imagery can still be proposed.
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- 2017
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5. Scale dependency in the hydromorphological control of a stream ecosystem functioning
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Jean-Marc Baudoin, Karl Kreutzenberger, Vincent Tamisier, Didier Lambrigot, Laurent Valette, Fanny Colas, Eric Chauvet, Frédéric Gob, Laboratoire Ecologie Fonctionnelle et Environnement (ECOLAB), Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-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)-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)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Pôle d'Etudes et Recherches AFB-Irstea Hydroécologie des Plans d'eau (France), Agence Française pour la Biodiversité - AFB (FRANCE), Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Milieux aquatiques, écologie et pollutions (UR MALY), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Office national de l'eau et des milieux aquatiques (ONEMA), Ministère de l'écologie, du développement durable et de l'énergie, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Institut national de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture - IRSTEA (FRANCE), Université Paris 1 Panthéon-Sorbonne (FRANCE), Université Paris Est Créteil Val de Marne - UPEC (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Office national de l'eau et des milieux aquatiques - ONEMA (FRANCE), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-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)-Centre National de la Recherche Scientifique (CNRS), 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)-Institut National Polytechnique (Toulouse) (Toulouse INP), Institut National Polytechnique de Toulouse - INPT (FRANCE), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), Laboratoire Ecologie Fonctionnelle et Environnement (LEFE), Université de Toulouse (UT)-Université de Toulouse (UT)-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 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)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT), and Agence Française pour la Biodiversité (AFB)
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0106 biological sciences ,Environmental Engineering ,River ecosystem ,[SDE.MCG]Environmental Sciences/Global Changes ,Drainage basin ,Context (language use) ,[SDV.BID]Life Sciences [q-bio]/Biodiversity ,Scaling effect ,010603 evolutionary biology ,01 natural sciences ,[SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems ,Rivers ,Water Quality ,Environmental monitoring ,Leaf breakdown ,Ecosystem ,[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology ,Milieux et Changements globaux ,Multiple stressors ,Waste Management and Disposal ,Hydrologie ,Water Science and Technology ,Civil and Structural Engineering ,Hydrology ,geography ,geography.geographical_feature_category ,Ecology ,010604 marine biology & hydrobiology ,Ecological Modeling ,Hydromorphology ,fungi ,food and beverages ,15. Life on land ,Pollution ,6. Clean water ,Habitat destruction ,Habitat ,Ecosystèmes ,13. Climate action ,Ecosystem functioning ,Environmental science ,Water quality ,Biodiversité ,Environmental Monitoring - Abstract
[Departement_IRSTEA]Eaux [TR1_IRSTEA]QUASARE; International audience; Physical habitat degradation is prevalent in river ecosystems. Although still little is known about the ecological consequences of altered hydromorphology, understanding the factors at play can contribute to sustainable environmental management. In this study we aimed to identify the hydromorphological features controlling a key ecosystem function and the spatial scales where such linkages operate. As hydromorphological and chemical pressures often occur in parallel, we examined the relative importance of hydromorphological and chemical factors as determinants of leaf breakdown. Leaf breakdown assays were investigated at 82 sites of rivers throughout the French territory. Leaf breakdown data were then crossed with data on water quality and with a multi-scale hydro- morphological assessment (i.e. upstream catchment, river segment, reach and habitat) when quantitative data were available. Microbial and total leaf breakdown rates exhibited differential responses to both hydromorphological and chemical alterations. Relationships between the chemical quality of the water and leaf breakdown were weak, while hydromorphological integrity explained independently up to 84.2% of leaf breakdown. Hydrological and morphological parameters were the main predictors of microbial leaf breakdown, whereas hydrological parameters had a major effect on total leaf breakdown, particularly at large scales, while morphological parameters were important at smaller scales. Microbial leaf breakdown were best predicted by hydromorphological features defined at the upstream catchment level whereas total leaf breakdown were best predicted by reach and habitat level geomorphic variables. This study demonstrates the use of leaf breakdown in a biomonitoring context and the importance of hydromorphological integrity for the functioning of running water. It provides new insights for envi- ronmental decision-makers to identify the management and restoration actions that have to be un- dertaken including the hydromorphogical features that should be kept in minimal maintenance to support leaf breakdown.
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- 2017
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6. Seasonal and event-based concentration-discharge relationships to identify catchment controls on nutrient export regimes
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Pierre-Alain Danis, Vincent Roubeix, Chantal Gascuel-Odoux, Rémi Dupas, Florentina Moatar, Camille Minaudo, Physics of Aquatic Systems Laboratory [Lausanne], Ecole Polytechnique Fédérale de Lausanne (EPFL), GéoHydrosystèmes COntinentaux (GéHCO EA6293), Université de Tours, Sol Agro et hydrosystème Spatialisation (SAS), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Pôle d'Etudes et Recherches AFB-Irstea Hydroécologie des Plans d'eau (France), Agence Française pour la Biodiversité - AFB (FRANCE), RiverLy (UR Riverly), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université de Tours (UT), Agence Française pour la Biodiversité (AFB), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Aix Marseille Université (AMU)
- Subjects
Biogeochemical cycle ,010504 meteorology & atmospheric sciences ,Nutrient export regime ,Nitrogen ,river ,[SDE.MCG]Environmental Sciences/Global Changes ,0207 environmental engineering ,Concentration-discharge relationships ,02 engineering and technology ,STREAMS ,Atmospheric sciences ,Spatial variability ,Catchment ,01 natural sciences ,water-quality ,nitrate export ,patterns ,Predictability ,020701 environmental engineering ,Temporal scales ,0105 earth and related environmental sciences ,Water Science and Technology ,Baseflow ,stream ,River network ,Phosphorus ,Storm ,Eutrophication ,15. Life on land ,6. Clean water ,high-frequency ,phosphorus release ,sediment ,13. Climate action ,flow ,Environmental science ,solute - Abstract
[Departement_IRSTEA]Eaux [ADD1_IRSTEA]Hydrosystèmes et risques naturels [ADD2_IRSTEA]Dynamique et fonctionnement des écosystèmes [ADD2_IRSTEA]Systèmes aquatiques soumis à des pressions multiples; International audience; The analysis of concentration-discharge (C-Q) relationships provides useful information on the processes controlling the mobilization and delivery of chemical elements into streams as well as biogeochemical transformations in river networks. Previous metrics developed to characterize export regimes seldom considered the possibility for the C response to Q dynamics to differ between short-term Q variations during storm events and seasonal Q variations during baseflow periods. Here, we present the “C-Qquick-slow” model, which considers the possibility for C-Q relationships to vary across temporal scales. This model was applied in 219 French catchments with various sizes (11–2500 km2), land use and hydrological contexts. We evidenced contrasting export regimes for nitrate (NO3 −), total phosphorus (TP) and soluble reactive phosphorus (SRP), and surprisingly consistent C-Q patterns at the seasonal scale for each parameter. For instance, NO3 −-Q relationships were positive at the seasonal scale in 75% cases and relationships during storms showed either a dilution pattern (24% cases), a non-significant pattern (50%), or a mobilization pattern (12%). TP and SRP relationships with Q at the seasonal scale were almostsystematically negative (95%), and patterns during storm events were in most cases mobilization for TP (77%) or non-significant for SRP (69%). We linked the different C-Q relationships with catchment descriptors and found that indicators of diffuse source loading determined NO3 − seasonal amplitudes, and hydrological drivers could explain the behavior during storms. By contrast, point sources determined P seasonal amplitudes, and diffuse sources controlled P dynamics during storms. The C-Qquick-slow model has the potential to improve nutrient loadestimations because of the good predictability of appropriate C-Q archetypes and the possibility to interpolate low frequency concentration data to a daily frequency
- Published
- 2019
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