233 Understanding extreme hydroclimatological events in the Congo using SWOT

Job title:

233 Understanding extreme hydroclimatological events in the Congo using SWOT

Company:

Centre National d’Etudes Spatiales

Job description

25-233 Understanding extreme hydroclimatological events in the Congo using SWOTPostuler25-233 Understanding extreme hydroclimatological events in the Congo using SWOT

• Doctorat, 36 mois
• Temps plein
• Indifférent
• Maitrise, IEP, IUP, Bac+4
• Hydrology, Water cycle, Continental Cryosphere

PostulerMissionGoal:The aim is to better understand extreme hydroclimatological events, such as the 2024 flood in the Congo River Basin (CRB) and their link to climate variability, using remote sensing, including newly Surface Water Ocean Topography (SWOT) data.Context:As the second largest river basin on Earth, CRB is crucial to the world’s climate and water resources. The basin is now under risk due to climate change and anthropogenic pressure, compounded with large-scale climate variability such as ENSO event. Furthermore, its population, with millions affected by food insecurity and conflicts, is crucially dependent on water resource availability, making it vulnerable to changes in the water cycle and associated extreme events. The 2024 extreme flood that affected large parts of the basin and caused hundreds of deaths is only an example of such changes at regional scale. It thus calls for a better understanding of CRB hydrology across scales. Our knowledge of large-scale hydroclimatic-hydrodynamic variability of CRB is indeed still limited, mainly due to a scarce in-situ data. Recent developments in remote sensing techniques, along with state-of-the-art numerical hydrologic-hydrodynamic modeling, now provide new insights on the basin’s hydrology. It brings new opportunities to investigate the spatio-temporal dynamics of hydroclimatological extremes in an integrated approach and how they are linked with large-scale climate variability. Water level, a crucial variable to characterize flood dynamic, is now routinely monitored from space using nadir altimetry. The limitations of those techniques in terms of spatial and temporal coverage is now overcome with the Surface Water and Ocean Topography (SWOT) mission and its improved accuracy and coverage due its interferometric sensor. Therefore, it opens new major questions: What are the spatio-temporal variability of river and floodplain water levels, extent, slopes and discharges in CRB during extreme events? How do they jointly evolve during such events at different space-time scales? How is it related to large-scale climatic influences?These questions take new dimensions thanks to the availability of massive satellite-derived observations and their potential synergy with hydrologic-hydrodynamic modelling to reveal the processes of surface water dynamics during extreme flooding and their main drivers.Objectives:The objectives of this thesis are threefold: 1) Provide the first characterization of 2024 CRB flood dynamic at multi-scale by revealing exceptional high river and floodplain water elevation and resulting slopes and how it propagates using SWOT; 2) Improve our understanding of large scale flood processes using historical long term satellited observations (classic radar altimetry; flood extent) and hydrological models 3) Reveal SWOT potentials for studying extreme events, including links with large-scale climate teleconnections.

Methods:We will address the following topics: 1) Construction and validation of an expertized and multi-scale SWOT dataset in CRB along with the consolidation of long-term databases of space observations of the hydrological cycle (water levels, flooded areas) validated against available in situ data. A particular focus will be made on the large flooded areas where many key processes occur, including unobserved inundated forests; 2) Improvement of the existing hydrological-hydrodynamic model (namely the fine-tuned versions of the MGB model using data assimilation) in the CRB to properly investigate the several scales of processes from local to regional, at different temporal scales; 3) Identification of teleconnection patterns and the hydrological signatures of floods associated with large scale climatic processes and events (ENSO, Indian Ocean Dipole). Prospective includes the evaluation of regional flood (Chad, Central Africa) and teleconnections with the Amazon, which conversely experienced its greatest drought in 2023-2024.Expected Results:We will characterize CRB hydro-climatic patterns during extreme events and explore their links with respect to large-scale climate variability at different spatial/temporal resolution. This will enable us to investigate and answer questions regarding the processes governing the complex surface water dynamics and to explore the impacts of hydro-climate events on the water resources. This will also open new perspectives for long-term integrated water resources management in both basins, in assistance to ongoing efforts to mitigate climate change impacts on the most vulnerable riparian communities.International collaboration:This thesis has a clear international context with strong collaborations with institutes from France, DRC, Brazil and Germany. The PhD candidate will work with internationally recognized teams. The results of the thesis will have significant implications and will be replicate in other regions of the world, with similar biomes or similar climatic zones and patterns.For more Information about the topics and the co-financial partner (found by the lab !);contact Directeur de thèse –Then, prepare a resume, a recent transcript and a reference letter from your M2 supervisor/ engineering school director and you will be ready to apply online before March 14th, 2025 Midnight Paris time !ProfilMaster 2 in Earth Science, Hydrology, Climatology or applied mathematics. Skills in remote sensing are a plus. Skills in analyzing large datasets of satellite observations and model outputs would be an asset. A person with a good capacity of working in a large team and in a multicultural environment is expected. Level in English: fluent.

Expected salary

Location

Toulouse

Job date

Wed, 05 Feb 2025 03:12:43 GMT

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