24-268 Monitoring of Coasts By Spatial Observations

il y a 2 semaines

MontSaintAignan, France CNES - Centre National d'Etudes Spatiales Temps plein

Doctorat, 36 mois
- Temps plein
- Aucune expérience exigée
- Maitrise, IEP, IUP, Bac+4
- Coastal, Littoral, Marine cryosphere

**Mission**:
Monitoring of COasts by Spatial observations and numerical MOdelling : COSMO

**Context and Motivation**

In the framework of the new mission SWOT, recently launched, the high-resolution measurements are keys to provide excellent coverages of nearshore and coastal evolution and give answers to various challenges, raised by the Science team SWOT, related to the accurate contribution of SWOT in these environments.

The main challenges addressed are:
1. To which extent SWOT products could improve the monitoring of hydrodynamic processes (waves, storm surges) in nearshore and coastal environments?

2. What is the contribution of SWOT’s data assimilation to improving numerical models/simulations of coastal hydrodynamics?

3. How can we optimize the use of SWOT products to investigate coastal flooding hazards?

Detailed Objectives

This project is structured in three parts:
1. Spatial observations of hydrodynamics (water level, waves) by the new mission SWOT and the conventional satellites (Sentinel 3, 6,..)

Regarding SWOT products, the HR products will be used to investigate the coastal processes. HR products are very different from LR products. For instance, they do not include correction from the Mean Sea Surface (MSS). It will thus be important to know to what extent they will help coastal processes modeling. In addition, LR products will be explored for nearshore hydrodynamics to define the extent of their use in this context. A particular focus will be made in the high frequency wave frequency in order to evaluate the finest 2D resolution of wave spectrum observed by SWOT. Accurate investigation to optimize the use of LR products in coastal areas will be made. Comparison between filtered/unfiltered data, grid size and corrections types such as tide or MSS corrections will be performed. In-situ data sets from the coastal SWOT Cal/Val field campaign performed in our previous project will be used to assess the validity of SWOT products close to the coastline. Data from other field campaign, for instance open data from the S-MODE campaign could be helpful, especially to compare results from airborne LiDAR measurements.

2. Numerical modeling and data assimilation (DA) for reducing uncertainties

2.1 Nearshore and coastal Modeling

The physically-based approaches allow for simulating coastal hydrodynamics and generating water level maps, including flooding over a user-defined model domain for a given compound event (Ye et al., 2021). Particularly, two-dimensional (2D) hydrodynamic models solve the continuity and momentum equations in 2D depth-average mode and require a detailed mesh resolution to ensure a correct representation of relevant topographic and bathymetric (topobathy) features and accurately simulate water level dynamics in DELFT3D-FM.

2.2 Data Assimilation and uncertainties

Indeed, the physically-based approaches are computationally intensive and also account for uncertainties derived from boundary conditions and/or validation data, model parameters, and model structure. Then, coupling numerical approaches with statistical techniques via the assimilation of data, provided by altimetry (Sentinel, SWOT) is relevant to alleviate the aforementioned limitations. Some recent studies implemented the data assimilation to estimate model parameters and correct the water levels at the coastal-ocean interface. The objective here is to integrate the hydrodynamic modelling DEFT3D-FM Ensemble Kalman filter estimators for correcting peak water surface elevation and wave spectrum in nearshore and coastal areas.

3. The benefits of SWOT products and Data Assimilation for assessing coastal flood hazards/compound flood hazards.

A special focus is given to the flood hazard assessment in coastal areas. The contribution of SWOT mission to capture the flooding events, when the track is crossing the English Channel. This information is useful to enhance the monitoring of flooding by:
(i) combining it with other airborne/spaceborne observations.

(ii) exploring the benefits of DA for hazardous scenarios or compound hazardous scenarios in coastal transition zones where fluvial, and coastal processes are all of paramount importance.

=================

**Profil**:
Master en géosciences ; Physical Oceanography - Civil Engineering - Remote Sensing ; connaissances solides en hydrodynamiques et côtières et/ou estuariennes et en télédétection Familiarisation avec la modélisation numérique Expérience en programmation : Python/Matlab/R et des logiciels SIG.

**Infos pratiques**:
M2C

**Mot du recruteur**:

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