Search

Your search keyword '"Mougin, Eric"' showing total 255 results
Start Over Author "Mougin, Eric"
255 results on '"Mougin, Eric"'

5. Modelling CO2 and N2O emissions from soils in silvopastoral systems of the West-African Sahelian band

Author

Agbohessou, Yélognissè frédi, Delon, Claire, Grippa, Manuela, Mougin, Eric, Ngom, Daouda, Gaglo, Koudjo Espoir, Ndiaye, Ousmane, Salgado, Paulo, Roupsard, Olivier, Agbohessou, Yélognissè frédi, Delon, Claire, Grippa, Manuela, Mougin, Eric, Ngom, Daouda, Gaglo, Koudjo Espoir, Ndiaye, Ousmane, Salgado, Paulo, and Roupsard, Olivier

Abstract

Silvopastoral systems (SPSs) have been shown to improve ecosystem resilience and provide sustainable land management solutions in the Sahel. However, accurately estimating the contribution of Sahelian ecosystems to the overall greenhouse gas (GHG) balance is a challenge, in particular regarding the magnitude of carbon dioxide (CO2) and nitrous oxide (N2O) emissions from soils. In this work, we spatialized and applied the process-based model Sahelian Transpiration Evaporation and Productivity – GENeral model of litter DEComposition – N2O (STEP–GENDEC-N2O) to investigate the magnitude and spatial and temporal patterns of herbaceous mass, as well as CO2 and N2O emissions from soil (not net emissions) in Sahelian SPSs. Our results show that over the last decade (2012–2022), there was a heterogeneous spatial distribution of herbaceous mass production and of soil CO2 and N2O emissions in Sahelian SPSs. Spatial variations in soil CO2 emissions are primarily controlled by soil carbon content, temperature, herbaceous mass, and animal load, while soil nitrogen content, soil water content, and animal load are the main factors driving the spatial variations in N2O emissions from soil. The estimated CO2 and N2O emissions from soil in Sahelian SPSs over the 2012–2022 period were equal to 58.79 ± 4.83 Tg CO2-C yr−1 (1 Tg = 1012 g) and 21.59 ± 3.91 Gg N2O-N yr−1 (1 Gg = 109 g), respectively. These values are generally lower than estimates reported in the literature for tropical areas and croplands. Furthermore, our simulations indicated a significant annual rising trend of soil CO2 and N2O emissions between 2012 and 2020 as herbaceous mass increased, making more C and N available for the nitrification, denitrification, and decomposition processes. By mapping soil CO2 and N2O emissions, we provide crucial insights into the localization of emission hotspots in Sahelian SPSs, thereby offering valuable information that can be used to devise and implement effective strategies aimed at f

Published
2024

6. Modelling CO2 and N2O emissions from soils in silvopastoral systems of the West African Sahelian band.

Author

Agbohessou, Yélognissè, Delon, Claire, Grippa, Manuela, Mougin, Eric, Ngom, Daouda, Gaglo, Espoir Koudjo, Ndiaye, Ousmane, Salgado, Paulo, and Roupsard, Olivier

Subjects
SILVOPASTORAL systems, CARBON emissions, NITROGEN in soils, CARBON in soils, SOIL moisture
Abstract

Silvopastoral systems (SPSs) have been shown to improve ecosystem resilience and provide sustainable land management solutions in the Sahel. However, accurately estimating the contribution of Sahelian ecosystems to the overall greenhouse gas (GHG) balance is a challenge, in particular regarding the magnitude of carbon dioxide (CO 2) and nitrous oxide (N 2 O) emissions from soils. In this work, we spatialized and applied the process-based model Sahelian Transpiration Evaporation and Productivity – GENeral model of litter DEComposition – N 2 O (STEP–GENDEC-N 2 O) to investigate the magnitude and spatial and temporal patterns of herbaceous mass, as well as CO 2 and N 2 O emissions from soil (not net emissions) in Sahelian SPSs. Our results show that over the last decade (2012–2022), there was a heterogeneous spatial distribution of herbaceous mass production and of soil CO 2 and N 2 O emissions in Sahelian SPSs. Spatial variations in soil CO 2 emissions are primarily controlled by soil carbon content, temperature, herbaceous mass, and animal load, while soil nitrogen content, soil water content, and animal load are the main factors driving the spatial variations in N 2 O emissions from soil. The estimated CO 2 and N 2 O emissions from soil in Sahelian SPSs over the 2012–2022 period were equal to 58.79 ± 4.83 Tg CO 2 -C yr -1 (1 Tg = 10 12 g) and 21.59 ± 3.91 Gg N 2 O-N yr -1 (1 Gg = 10 9 g), respectively. These values are generally lower than estimates reported in the literature for tropical areas and croplands. Furthermore, our simulations indicated a significant annual rising trend of soil CO 2 and N 2 O emissions between 2012 and 2020 as herbaceous mass increased, making more C and N available for the nitrification, denitrification, and decomposition processes. By mapping soil CO 2 and N 2 O emissions, we provide crucial insights into the localization of emission hotspots in Sahelian SPSs, thereby offering valuable information that can be used to devise and implement effective strategies aimed at fostering carbon sequestration in the Sahel. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

7. Quantification of surface water extent and volume in the Inner Niger Delta (IND) over 2000-2022 using multispectral imagery and radar altimetry.

Author

Normandin, Cassandra, Frappart, Frédéric, Bourrel, Luc, Diepkilé, Adama Telly, Mougin, Eric, Zwarts, Leo, Blarel, Fabien, Egon, Flavien, and Wigneron, Jean-Pierre

Subjects
RADAR altimetry, REMOTE sensing, WATER storage, WATER levels, FLOODS
Abstract

Spatio-temporal dynamics of surface water reservoirs at regional and global scales remain poorly understood. Using satellite remote sensing provides a unique opportunity to address this problem. This study aims to (1) quantify the extent and volume of surface water and (2) compare our approach with other datasets. We utilized MODIS-based spectral indices to monitor temporal variations in inundation extent. By interpolating water levels across the surface water extent, we generated water level maps and quantified surface water volume from 2000 to 2022. Evaluation against ICESat-2 data involved 64 comparisons, with approximately 58% showing an R2 value greater than or equal to 0.5, and 38% were higher than or equal to 0.7. Compared to the flooding model, our method aligns more closely with ICESat-2 data, contrary to the flooding model which tends to overestimate water levels and, consequently, water storage. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

13. Allometric equations to estimate the dry mass of Sahel woody plants mapped with very-high resolution satellite imagery

Author

Hiernaux, Pierre, Issoufou, Hassane Bil Assanou, Igel, Christian, Kariryaa, Ankit, Kourouma, Moussa, Chave, Jérôme, Mougin, Eric, Savadogo, Patrice, Hiernaux, Pierre, Issoufou, Hassane Bil Assanou, Igel, Christian, Kariryaa, Ankit, Kourouma, Moussa, Chave, Jérôme, Mougin, Eric, and Savadogo, Patrice

Abstract

Very high-resolution satellite images and deep learning are achieving the mapping of individual trees and shrubs over large areas in Africa. Each woody plant is precisely georeferenced and defined by its crown area and, sometimes, its height. The challenge is to build allometric equations for foliage, wood and root dry masses based either on crown area alone, or the product crown area × tree height as independent variables regardless of species. This was met by reanalyzing existing Sahel woody plant data from destructive sampling. Overall, the foliage (seasonal maximum), wood and root dry masses were measured on 900, 698 and 26 trees or shrubs from 27, 26 and 5 species respectively. The regression models tested for foliage, wood or root masses were linear or power functions using a range of different approaches: Ordinary least square (OLS) regression after log–log transform with or without Baskerville correction (1972), and non-linear regressions (NLR). All the models outputs were intercompared for fit indicators and prediction uncertainty, as well as the resulting trends in root to wood ratio, and foliage to wood ratio over the range of crown areas. This process selected a set of OLS log–log equations with crown area as independent variable. When the Baskerville correction is applied the approximation errors are 0.4 kg Dry Matter (DM) for foliage, 12.2 for wood and 6.3 for roots, aggregating at 13.8 kg DM per tree. These allometry equations were compared to published equations for tropical trees, most from the more humid tropics that were generally based on stem diameter, tree height and wood density. This paper's allometry predictions were within the range of these other allometry equations, reinforcing the confidence in their use even beyond the Sahel domain towards sub-humid savannas.

Published
2023

14. GNSS-R monitoring of soil moisture dynamics in areas of severe drought:example of Dahra in the Sahelian climatic zone (Senegal)

Author

Ha, Minh-Cuong, Darrozes, José, Llubes, Muriel, Grippa, Manuela, Ramillien, Guillaume, Frappart, Frédéric, Baup, Frédéric, Tagesson, Håkan Torbern, Mougin, Eric, Guiro, Idrissa, Kergoat, Laurent, Nguyen, Huu Duy, Seoane, Lucia, Dufrechou, Gregory, Vu, Phuong-Lan, Ha, Minh-Cuong, Darrozes, José, Llubes, Muriel, Grippa, Manuela, Ramillien, Guillaume, Frappart, Frédéric, Baup, Frédéric, Tagesson, Håkan Torbern, Mougin, Eric, Guiro, Idrissa, Kergoat, Laurent, Nguyen, Huu Duy, Seoane, Lucia, Dufrechou, Gregory, and Vu, Phuong-Lan

Abstract

With population growth, water will increase in the following decades tremendously. The optimization of water allocation for agriculture requires accurate soil moisture (SM) monitoring. Recent Global Navigation Satellite System Reflectometry (GNSS-R) studies take advantage of continuously emitted navigation signals by the Global Navigation Satellite System (GNSS) constellations to retrieve spatiotemporal soil moisture changes for soil with high clay content. It presents the advantage of sensing a whole surface around a reference GNSS antenna. This article focuses on sandy SM monitoring in the driest condition observed in the study field of Dahra, (Senegal). The area consists of 95% sand and in situ volumetric soil moisture (VSM) range from similar to 3% to similar to 5% durinf the dry to the rainy season. Unfortunately, the GNSS signals' waves penetrated deep into the soil during the dry period and strongly reduced the accuracy of GNSS reflectometry (GNSS-R) surface moisture measurements. However, we obtain VSM estimate at low/medium penetration depth. The correlation reaches 0.9 with VSM error lower than 0.16% for the 5-10-cm-depth probes and achieves excellent temporal monitoring to benefit from the antenna heights directly correlated to spatial resolution. The SM measurement models in our research are potentially valuable tools that contribute to the planning of sustainable agriculture, especially in countries often affected by drought.

Published
2023

15. GNSS-R monitoring of soil moisture dynamics in areas of severe drought: example of Dahra in the Sahelian climatic zone (Senegal).

Author

Ha, Minh-Cuong, Darrozes, José, Llubes, Muriel, Grippa, Manuela, Ramillien, Guillaume, Frappart, Frédéric, Baup, Frédéric, Tagesson, Håkan Torbern, Mougin, Eric, Guiro, Idrissa, Kergoat, Laurent, Nguyen, Huu Duy, Seoane, Lucia, Dufrechou, Gregory, and Vu, Phuong-Lan

Subjects
DROUGHT management, SOIL moisture, GLOBAL Positioning System, SOIL dynamics, DROUGHTS, CLIMATIC zones, ANTENNAS (Electronics), MOISTURE measurement
Abstract

With population growth, water will increase in the following decades tremendously. The optimization of water allocation for agriculture requires accurate soil moisture (SM) monitoring. Recent Global Navigation Satellite System Reflectometry (GNSS-R) studies take advantage of continuously emitted navigation signals by the Global Navigation Satellite System (GNSS) constellations to retrieve spatiotemporal soil moisture changes for soil with high clay content. It presents the advantage of sensing a whole surface around a reference GNSS antenna. This article focuses on sandy SM monitoring in the driest condition observed in the study field of Dahra, (Senegal). The area consists of 95% sand and in situ volumetric soil moisture (VSM) range from ~3% to ~5% durinf the dry to the rainy season. Unfortunately, the GNSS signals' waves penetrated deep into the soil during the dry period and strongly reduced the accuracy of GNSS reflectometry (GNSS-R) surface moisture measurements. However, we obtain VSM estimate at low/medium penetration depth. The correlation reaches 0.9 with VSM error lower than 0.16% for the 5–10-cm-depth probes and achieves excellent temporal monitoring to benefit from the antenna heights directly correlated to spatial resolution. The SM measurement models in our research are potentially valuable tools that contribute to the planning of sustainable agriculture, especially in countries often affected by drought. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

17. Dry and Wet Atmospheric Nitrogen Deposition in West Central Africa

Author

Galy-Lacaux, Corinne, Delon, Claire, Solmon, Fabien, Adon, Marcellin, Yoboué, Véronique, Mphepya, Jonas, Pienaar, Jacobus J., Diop, Babakar, Sigha, Luc, Dungall, Laouali, Akpo, Aristide, Mougin, Eric, Gardrat, Eric, Castera, Pierre, Sutton, Mark A., editor, Mason, Kate E., editor, Sheppard, Lucy J., editor, Sverdrup, Harald, editor, Haeuber, Richard, editor, and Hicks, W. Kevin, editor

Published
2014
Full Text
View/download PDF

22. 17O-excess of tropical forest and savanna phytoliths record diurnal atmospheric relative humidity of the growing season: implications for paleoclimate reconstructions and model-data comparisons

Author

Alexandre, Anne, primary, Outrequin, Clément, additional, Peugeot, Christophe, additional, Aleman, Julie, additional, Vallet-Coulomb, Christine, additional, Voigt, Claudia, additional, Au Yang, David, additional, Landais, Amaelle, additional, Mazur, Jean-Charles, additional, Sonzogni, Corinne, additional, Wubda, Maxime, additional, Ouani, Theodore, additional, Afouda, Simon, additional, Grippa, Manuela, additional, Soumaguel, Nogmana, additional, Tagesson, Torbern, additional, Fensholt, Rasmus, additional, Ndiaye, Ousmane, additional, and Mougin, Eric, additional

Published
2023
Full Text
View/download PDF

23. Is the Impact of Livestock on Greenhouse Gas Emissions Offset by the Presence of Trees in a Sahelian Silvopastoral System?

Author

Agbohessou, Yélognissè F., primary, Delon, Claire, additional, Mougin, Eric, additional, Grippa, Manuela, additional, Tagesson, Torbern, additional, Diedhiou, Moussa, additional, Ba, Seydina, additional, Ngom, Daouda, additional, Vezy, Rémi, additional, Ndiaye, Ousmane, additional, Assouma, Mohamed H., additional, and Roupsard, Olivier, additional

Published
2023
Full Text
View/download PDF

24. GNSS-R monitoring of soil moisture dynamics in areas of severe drought: example of Dahra in the Sahelian climatic zone (Senegal)

Author

Ha, Minh-Cuong, primary, Darrozes, José, additional, Llubes, Muriel, additional, Grippa, Manuela, additional, Ramillien, Guillaume, additional, Frappart, Frédéric, additional, Baup, Frédéric, additional, Tagesson, Håkan Torbern, additional, Mougin, Eric, additional, Guiro, Idrissa, additional, Kergoat, Laurent, additional, Nguyen, Huu Duy, additional, Seoane, Lucia, additional, Dufrechou, Gregory, additional, and Vu, Phuong-Lan, additional

Published
2022
Full Text
View/download PDF

26. Modelling CO2 and N2O emissions from soils in silvopastoral systems of the West-African Sahelian band.

Author

Agbohessou, Yélognissè, Delon, Claire, Grippa, Manuela, Mougin, Eric, Ngom, Daouda, Gaglo, Espoir Koudjo, Ndiaye, Ousmane, Salgado, Paulo, and Roupsard, Olivier

Subjects
SILVOPASTORAL systems, NITROGEN in soils, CARBON in soils, SOIL moisture, GREENHOUSE gases
Abstract

Silvopastoral systems (SPSs) have been shown to improve ecosystem resilience and provide sustainable land management solutions in the Sahel. However, accurately estimating the contribution of Sahelian ecosystems to the overall greenhouse gas (GHG) balance is a challenge, in particular the magnitude of carbon dioxide (CO2) and nitrous oxide (N2O) emissions from soils. In this work, we spatialized and applied the process-based model STEP-GENDEC-N2O to investigate the magnitude, spatial, and temporal patterns of herbaceous mass, as well as CO2 and N2O emissions from soil in Sahelian SPSs. Our results show that over the last decade (2012-2022), there was a heterogeneous spatial distribution of herbaceous mass production, as well as of soil CO2 and N2O emissions in Sahelian SPSs. Spatial variations in soil CO2 emissions are primarily controlled by soil carbon content, temperature, herbaceous mass, and animal load, while soil nitrogen content, soil water content, and animal load are the main factors driving the spatial variations in N2O emissions from soil. The estimated CO2 and N2O emissions from soil in Sahelian SPSs over the 2012-2022 period were equal to 58.79 ± 4.83 Tg CO2-C yr-1 (1 Tg = 1012 g) and 21.59 ± 3.91 Gg N2O-N yr-1 (1 Gg = 109 g), respectively. These values are generally lower than estimates reported in the literature for tropical areas and croplands. Furthermore, our simulations indicated a significant annual rising trend of soil CO2 and N2O emissions between 2012-2020 as herbaceous mass increases, making more C and N available for nitrification, denitrification and decomposition processes. By mapping soil CO2 and N2O emissions, we provide crucial insights into the localization of emission hotspots in Sahelian SPSs, thereby offering valuable information that can be used to devise and implement effective strategies aimed at fostering carbon sequestration in the Sahel. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

30. Tipping points in hydrology: observed regional regime shift and System Dynamics modeling

Author

Wendling, Valentin, Peugeot, Christophe, Grippa, Manuela, Kergoat, Laurent, Mougin, Eric, Hiernaux, Pierre, Rouché, Nathalie, Panthou, Geremy, Rajot, Jean-Louis, Pierre, Caroline, Mora, Olivier, Garcia-Mayor, Angeles, Ba, Abdramane, Lawin, Emmanuel, Bouzou-Moussa, Ibrahim, Demarty, Jerôme, Etchanchu, Jordi, Hector, Basile, Galle, Sylvie, Lebel, Thierry, Project, Tiphyc, Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Géosciences Environnement Toulouse (GET), 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)-Observatoire Midi-Pyrénées (OMP), 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 des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris ), Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Délégation à l'Expertise scientifique collective, à la Prospective et aux Etudes (UAR), Institut National de la Recherche Agronomique (INRA), Utrecht University [Utrecht], Institut National de L’Eau, Cotonou, Université Abdou Moumouni [Niamey], Université des Sciences, des Techniques et des Technologies de Bamako (USTTB), ANR : Exploring tipping points in the West African hydrological cycle – TipHyc, and ANR-20-CE01-0014,TipHyc,Exploration des points de bascule dans le cycle hydrologique ouest-africain(2020)

Subjects
[SDE.MCG]Environmental Sciences/Global Changes, [NLIN]Nonlinear Sciences [physics], [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract

River runoff and climate data existing from 1950 to present time in West Africa are analyzed over a climatic gradient from the Sahel (semi-arid) to the Gulf of Guinea (humid). The region experienced a severe drought in the 70s-90s, with strong impact on the vegetation, soils and populations. We show that the hydrological regime in the Sahel has shifted: the runoff increased significantly between pre- and post-drought periods and is still increasing. In the Guinean region, instead, no shift is observed. This suggests that a tipping point could have been passed, triggered by climate and/or land use change. In order to explore this hypothesis, we developed a System Dynamics model representing feedbacks between soil, vegetation and flow connectivity of hillslopes, channels and aquifers. Model runs were initialized in 1950 with maps of land use/land cover, and fed with observed rainfall (climate external forcing). The modeling results accurately represent the observed evolution of the hydrological regime on the watersheds monitored since the 50s (ranging from 1 to 50000 km²). The model revealed that alternative stable states can exist for the climatic conditions of the study period. From the model runs, we showed that the drought triggered the crossing of a tipping point (rainfall threshold), which explains the regime shift. We identified domains within the watersheds where tipping occurred at small scale, leading to larger scale shifts. This result supports that tipping points exist in semi-arid systems where ecohydrology plays a major role. This approach seems well suited to identify areas of high risk of irreversible hydrological regime shifts under different climate and land-use scenarios.

Published
2022
Full Text
View/download PDF

31. THE AMMA LAND SURFACE MODEL INTERCOMPARISON PROJECT (ALMIP)

Author

Boone, Aaron, de Rosnay, Patricia, Balsamo, Gianpaolo, Beljaars, Anton, Chopin, Franck, Decharme, Bertrand, Delire, Christine, Ducharne, Agnes, Gascoin, Simon, Grippa, Manuela, Guichard, Françoise, Gusev, Yeugeniy, Harris, Phil, Jarlan, Lionel, Kergoat, Laurent, Mougin, Eric, Nasonova, Olga, Norgaard, Anette, Orgeval, Tristan, Ottlé, Catherine, Poccard-Leclercq, Isabelle, Polcher, Jan, Sandholt, Inge, Saux-Picart, Stephane, Taylor, Christopher, and Xue, Yongkang

Published
2009

32. The AMMA-CATCH observatory : a platform to address scientific and societal issues in West-Africa

Author

Cohard, Jean-Martial, primary, Grippa, Manuela, additional, Lawin, Emmanuel, additional, Peugeot, Christophe, additional, Assanou, Bil, additional, Boucher, Marie, additional, Chaffard, Véronique, additional, Diawara, Mamadou, additional, Etchanchu, Jordi, additional, Faye, Gayane, additional, Galle, Sylvie, additional, Mainassara, Ibrahim, additional, Malam-Abdou, Moussa, additional, Mamadou, Ossenatou, additional, Mariscal, Armand, additional, Mougin, Eric, additional, Moumouni, Soumaïla, additional, Panthou, Geremy, additional, and Lebel, Thierry, additional

Published
2022
Full Text
View/download PDF

34. Scientific Committee

Author

Fouad, Youssef, primary, Carrere, Véronique, additional, Chabrillat, Sabine, additional, Demarez, Valérie, additional, Roujean, Jean Louis, additional, Lacaze, Roselyne, additional, Pattey, Elizabeth, additional, Kayitakire, Francois, additional, Ceschia, Eric, additional, Brunet, Yves, additional, Sheeren, David, additional, Vaudour, Emmanuelle, additional, Alleaume, Samuel, additional, Bappel, Eric, additional, Corgne, Samuel, additional, Arvor, Damien, additional, Catry, Thibault, additional, Rudant, Jean-Paul, additional, Gaetano, Raffaele, additional, Mougin, Eric, additional, Weiss, Marie, additional, Michez, Adrien, additional, Bauwens, Sébastien, additional, Bonnet, Stéphanie, additional, Lejeune, Philippe, additional, Belouard, Thierry, additional, Barbier, Nicolas, additional, Rejou, Maxime, additional, Vincent, Grégoire, additional, Baghdadi, Nicolas, additional, and Zribi, Mehrez, additional

Published
2016
Full Text
View/download PDF

37. List of Authors

Author

Baghdadi, Nicolas, primary, Barbu, Alina L., additional, Bernier, Monique, additional, Boniface, Karen, additional, Boulet, Gilles, additional, Boussetta, Souhail, additional, Calmant, Stéphane, additional, Calvet, Jean-Christophe, additional, Cretaux, Jean-François, additional, Dedieu, Jean-Pierre, additional, De Rosnay, Patricia, additional, Duguay, Yannick, additional, Dumont, Marie, additional, Egido, Alejandro, additional, Frappart, Frédéric, additional, Frison, Pierre-Louis, additional, Gascoin, Simon, additional, Jarlan, Lionel, additional, Kerr, Yann, additional, Lagouarde, Jean-Pierre, additional, Leroux, Delphine, additional, Magagi, Ramata, additional, Motte, Erwan, additional, Mougin, Eric, additional, Pellarin, Thierry, additional, Ramillien, Guillaume, additional, Remy, Frédérique, additional, Roussel, Nicolas, additional, Seoane, Lucía, additional, Wigneron, Jean-Pierre, additional, and Zribi, Mehrez, additional

Published
2016
Full Text
View/download PDF

50. Drought-induced regime shift and resilience of a Sahelian ecohydrosystem

Author

Wendling, Valentin, Peugeot, Christophe, Mayor, Ángeles Garcia, Hiernaux, Pierre, Mougin, Eric, Grippa, Manuela, Kergoat, Laurent, Walcker, Romain, Galle, Sylvie, Lebel, Thierry, Spatial Ecology and Global Change, Environmental Sciences, Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Copernicus Institute for Sustainable Development, Utrecht University [Utrecht], Géosciences Environnement Toulouse (GET), 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), Laboratoire Ecologie Fonctionnelle et Environnement (ECOLAB), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), 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), 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 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), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-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 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), Laboratoire Ecologie Fonctionnelle et Environnement (LEFE), 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 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), Spatial Ecology and Global Change, and Environmental Sciences

Subjects
010504 meteorology & atmospheric sciences, rainfall, Climate change, alternative stable states, 010501 environmental sciences, 01 natural sciences, Alternative stable state, Soil retrogression and degradation, Sahel, Clearing, Ecosystem, Regime shift, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, regime shifts, rainfall variability, Renewable Energy, Sustainability and the Environment, variability, Public Health, Environmental and Occupational Health, Vegetation, 15. Life on land, 13. Climate action, Climatology, [SDE]Environmental Sciences, eco-hydrology, Environmental science, Surface runoff
Abstract

International audience; The Sahel (a semi-arid fringe south of the Sahara) experienced a long and prolonged drought from the1970s to the mid-1990s, with a few extremely severe episodes that strongly affected ecosystems andsocieties. Long-term observations showed that surface runoff increased during this period, despite therainfall deficit. This paradox stems from the soil degradation that was induced by various factors,either directly linked to the drought (impact on vegetation cover), or, in places, to human practices (land clearing and cropping). Surface runoff is still increasing throughout the region, suggesting that Sahelian ecohydrosystems may have shifted to a new hydrological regime. In order to explore this issue, we have developed a simple system dynamics model incorporating vegetation–hydrology interactions and representing in a lumped way the first order processes occurring at the hillslope scale and the annual timestep. Long term observations on a pilot site in northern Mali were used to constrain the model and define an ensemble of plausible simulations. The model successfully reproduced the vegetation collapse and the runoff increase observed over the last 60 years. Our results confirmed that the system presents two alternative states and that during the drought it shifted from a high-vegetation/low-runoff regime to the alternative low-vegetation/high-runoff one, where it has remained trapped until now. We showed that the mean annual rainfall deficit was sufficient to explain the shift. According to the model, vegetation recovery and runoff reduction are possible in this system, but the conditions in which they could occur remain uncertain as the model was only constrained by observations over the collapse trajectory. The study shows that the system is also sensitive to the interannual and decadal variability of rainfall, and that larger variability leads to higher runoff. Both mean rainfall and rainfall variability may increase in central Sahel under climate change, leading to antagonist effects on the system, which makes its resilience uncertain.

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results