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Exploring Fine-Scale Satellite-Derived Coastal Bathymetry for Ocean Modeling: A Case Study from West Africa

Domaine:

geospatialenvironment and energy

Type de record:

paperdataset
Créateur:
MarThoDieAlmar, Rafael
Éditeur:
LabLabCenThu
Éditeur:
CCSDSpringer-Verlag
Hôte:avatar
International audience Coastal risk assessment requires accurate coastal bathymetry, which is largely lacking in many regions of the world’s coastal oceans. This is particularly true in Guinea-Bissau, where the tidal range is the highest of any country in West Africa, affecting several socio-economic sectors such as agriculture and urban development. Here, we present a selection of coastal bathymetry datasets available for generally poorly sampled coastal regions. These include the General Bathymetric Chart of the Oceans (GEBCO), digital nautical charts (CMAP), and depth retrieval from satellite wave detection (S2Shores). While GEBCO provides the right regional envelope of bathymetry, the coastal zone is plagued with random bumpiness at scales below 10 km (“orange peel” texture). S2Shores can be used to correct these errors and instead reveal the presence of small-scale channels, reminiscent of very high-resolution satellite color images. These structures are also confirmed by nautical charts, which show the channels to be well correlated but deeper than that indicated by the satellite retrieval (with a 40% higher variance, and 40 m instead of 20 m for Orango, the main and deepest channel). Simulations with a coastal ocean hydro-sedimentary model (CROCO) further show that submerged rivers can help drive a smooth flow of tidal energy into the main estuary of Guinea-Bissau. Tidal energy flux is better channeled in the CMAP and S2shores cases, while GEBCO produces an order of magnitude greater form drag, resulting in a stronger response from the sediment bed. Tides therefore have the effect of smoothing bathymetry along fine-scale channels, minimizing friction on the way to equilibrium. This result highlights the potential of combining different approaches to estimate updated coastal bathymetry and its effect on coastal dynamics in the most challenging areas.

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ut3-toulouseinp.hal.science

Languages

Bidyogo

Tags

Tidal modelingRemote sensingWave inversionCoastal bathymetryGuinea-Bissau[SDU]Sciences of the Universe [physics]

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