Copyright 2020 - copyright UMR ESPACE-DEV - 2017

Le projet WASACA, lauréat de l'appel à projets « Climate change, biodiversity, food systems : Agriculture-Based Solutions » d'Agropolis Fondation

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Le projet WASACA, porté par Frédéric SATGE, chercheur à l'UMR Espace-Dev, a été sélectioné dans le cadre de l'appel à projets « Climate change, biodiversity, food systems : Agriculture-Based Solutions » d'Agropolis Fondation. 
 

Nos dernières publications - Avril 2020

icone documentation publication

  • Pinel S., Bonnet Marie-Paule, Da Silva J. S., Sampaio T. C., Garnier J., Catry Thibault, Calmant Stéphane, Fragoso C. R., Moreira D., Marques D. M., Seyler Frédérique. Flooding dynamics within an Amazonian floodplain : water circulation patterns and inundation duration. Water Resources Research, 2020, 56 (1), p. e2019WR026081 [22 p.].

https://doi.org/10.1029/2019wr026081

Flooding dynamics across a medium-size (Janauaca Lake, 786 km(2)) floodplain system along the Amazon/Solimoes River over a 9-year period (2006-2015) is studied through integration of remote sensing and limited in situ data in hydrologic-hydrodynamic modelling based on Telemac-2D model. Model accuracy varies through the hydrological year. We focus on seasonal and interannual spatial variability of water circulation and inundation duration. We highlight strong heterogeneities in water velocity magnitude between the different morphological domains of the floodplain, the highest velocities being encountered in the river-floodplain channel. In addition to topography, we emphasize the importance of the main channel and the local runoff in controlling the water circulation, at least during part of the hydrological year. From low water to early rising period, local runoff constrains the river incursion across the floodplain, while the rates of main channel rising/receding controls the flood duration. The comparison of several hydrological years highlights the interannual changes of these hydraulic controls and also the influence exerted by prior inundation conditions. While we observed few changes in water velocity distribution among hydrological years, the inundation duration is highly variable. Usually defined by maximum water level, extreme flood events may paradoxically induce positive (up to 40 days) but also negative (up to -20 days) anomalies of inundation duration.

Affiliation IRD : UMR 228 (ESPACE-DEV) ; UMR 065 (LEGOS)
Descr. géo. : BRESIL; AMAZONE, SOLIMOES COURS D'EAU; JANAUACA LAC
Lien permanent : https://www.documentation.ird.fr/hor/fdi:010078886

 

  • Tavares M. H., Cunha A. H. F., Motta-Marques D., Ruhoff A. L., Fragoso C. R., Munar A. M., Bonnet Marie-Paule. Derivation of consistent, continuous daily river temperature data series by combining remote sensing and water temperature models. Remote Sensing of Environment, 2020, 241, p. art. 111721 [18 p.].

https://doi.org/10.1016/j.rse.2020.111721

Scarcity of water temperature data in rivers may limit a diversity of studies considering this property, which regulates many physical, chemical, and biological processes. We present a robust method to generate a consistent, continuous daily river water temperature (RWT) data series for medium and large rivers using the combined techniques of remote sensing and water temperature modelling. In order to validate our approach, we divided this study into two parts: (i) we evaluated methods to derive RWT from Landsat 7 ETM+ and Landsat 8 TIRS imagery; and (ii) we evaluated the calibration and validation of river temperature models, using these data, to generate the continuous RWT data series. A 1.2 km section of the White River located near Hazleton, IN, USA, was selected to assess this method mainly due to river width and data availability. We tested three methods to retrieve RWT from Landsat 7 and four from Landsat 8, and we also applied a simple thermal sharpening technique. For Landsat 7, the methods showed bias and RMSE of 0.01-0.46 degrees C and 1.32-1.84 degrees C, while for Landsat 8, the methods showed bias and RMSE of 0.08-1.27 degrees C and 1.74-2.17 degrees C, and in both cases, the best results were found applying the radiative transfer equation with NASA's Atmospheric Correction Parameter Calculator. For the second part of the validation process, we compared a stochastic model and a hybrid model, air2stream, using as input two datasets: the RWT data derived from Landsat 7 only, and a combined dataset of both Landsat 7 and 8 derived RWT. The air2stream model outperformed the stochastic model when calibrated with Landsat 7 data only, with RMSE of 1.83 degrees C, but both models showed similar results when calibrated with the combined Landsat data, when air2stream showed RMSE of 1.58 degrees C. Due to its physical basis, better calibration procedure, and higher consistency, air2stream was considered the best model for deriving the continuous RWT data series. When compared to the measured daily mean RWT data, there was no observed tendency in under or overestimating the RWT in low or high temperature conditions by the modelled series. While further tests are needed in order to evaluate if our approach can be applied to analyse past behaviour and present trends, and the impacts of climate change on the temperature of rivers, the consistent results indicate that this approach has the potential to be applied in rivers with no measured temperature data, for example, in the spatial modelling of longitudinal profiles of rivers and the modelling of tributary river temperatures.

Water surface temperature ; Temperature modelling ; Landsat ; Thermal infrared ; Atmospheric correction ; Temperature-based validation ; Thermal response

Affiliation IRD : UMR 228 (ESPACE-DEV)
Descr. géo. : ETATS UNIS
Lien permanent : https://www.documentation.ird.fr/hor/fdi:010078944

Nos dernières publications - Mars 2020

icone documentation publicationAlexandre Cyprien, Johary R., Catry ThibaultMouquet Pascal, Revillion C., Rakotondraompiana S., Pennober G. A Sentinel-1 based processing chain for detection of cyclonic flood impacts. Remote Sensing, 2020, 12 (2), p. art. 252 [18 p.] .

https://doi.org/10.3390/rs12020252

In the future, climate change will induce even more severe hurricanes. Not only should these be better understood, but there is also a necessity to improve the assessment of their impacts. Flooding is one of the most common powerful impacts of these storms. Analyzing the impacts of floods is essential in order to delineate damaged areas and study the economic cost of hurricane-related floods. This paper presents an automated processing chain for Sentinel-1 synthetic aperture radar (SAR) data. This processing chain is based on the S1-Tiling algorithm and the normalized difference ratio (NDR). It is able to download and clip S1 images on Sentinel-2 tiles footprints, perform multi-temporal filtering, and threshold NDR images to produce a mask of flooded areas. Applied to two different study zones, subject to hurricanes and cyclones, this chain is reliable and simple to implement. With the rapid mapping product of EMS Copernicus (Emergency Management Service) as reference, the method confers up to 95% accuracy and a Kappa value of 0.75.

hurricane ; cyclone ; flood ; Sentinel 1 time series ; change detection ; NDR ; SAR

Affiliation IRD : UMR 228 (ESPACE-DEV)

Lien permanent : https://www.documentation.ird.fr/hor/fdi:010077971

 

Satge FrédéricDefrance DimitriSultan BenjaminBonnet Marie-PauleSeyler FrédériqueRouché Nathalie, Pierron F., Paturel Jean-Emmanuel. Evaluation of 23 gridded precipitation datasets across West Africa. Journal of Hydrology, 2020, 581, p. art. 124412 [19 p.].

https://doi.org/10.1016/j.jhydrol.2019.124412

This study aims reporting on 23 gridded precipitation datasets (P-datasets) reliability across West Africa through direct comparisons with rain gauges measurement at the daily and monthly time scales over a 4 years period (2000-2003). All P-datasets reliability vary in space and time. The most efficient P-dataset in term of Kling-Gupta Efficiency (KGE) changes at the local scale and the P-dataset performance is sensitive to seasonal effects. Satellite-based P-datasets performed better during the wet than the dry season whereas the opposite is observed for reanalysis P-datasets. The best overall performance was obtained for MSWEP v.2.2 and CHIRPS v.2 for daily and monthly time-step, respectively. Part of the differences in P-dataset performance at daily and monthly time step comes from the time step used to proceed the gauges adjustment (Le day or month) and from a mismatch between gauge and satellite reporting times. In comparison to the others P-datasets, TMPA-Adj v.7 reliability is stable and reach the second highest KGE value at both daily and monthly time step. Reanalysis P-datasets (WFDEI, MERRA-2, JRA-55, ERA-Interim) present among the lowest statistical scores at the daily time step, which drastically increased at the monthly time step for WFDEI and MERRA-2. The non-adjusted P-datasets were the less efficient, but, their near-real time availability should be helpful for risk forecast studies (i.e. GSMaP-RT v.6). The results of this study give important elements to select the most adapted P-dataset for specific application across West Africa.

Precipitation datasets ; Reliability ; West Africa

Affiliation IRD : UMR 228 (ESPACE-DEV) ; UMR 050 (HSM)

Descr. géo. : AFRIQUE DE L'OUEST

Lien permanent : https://www.documentation.ird.fr/hor/fdi:010077958

 

Proposition de contrat doctoral - Avignon Université

Titre : Emergence et développement du tourisme domestique au Népal : acteurs,espaces, pratiques et imaginaires diplome obtenu

Le projet s’inscrit dans le prolongement du programme ANR AQAPA (« À qui appartiennent les paysages en Asie ? La mise en tourisme des hautes terres en Asie méridionale : dynamiques sociales et patrimonialisation des paysages dans les campagnes à minorités
ethniques »), coord. E. Gauché – UMR 7324 CITERES.

Les dossiers de candidature sont à envoyer le plus rapidement possible, et au plus tard le 12 mai 2020.

Télécharger la proposition

 

Prolongation des appels à communication - International MangSES symposium

MANGSES

La date limite de soumission des résumés est prolongée jusqu'au 11 mai 2020 !
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Plus d'informations sur : https://mangses.sciencesconf.org/

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L'UMR Espace-Dev (Mayotte) co-organise une conférence internationale sur les mangroves. Cette conférence sur les systèmes socio-écologiques des mangroves (MangSES) mettra l'accent sur des présentations et des discussions interdisciplinaires. Une journée sur le terrain permettra de découvrir les enjeux et problématiques de certaines mangroves de Mayotte.

Date limite de l'appel à communications : 17 mai 2020

👉 Plus d'informations sur : https://mangses.sciencesconf.org/

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