Assimilation of SWOT Altimetry and Sentinel-1 Flood Extent Observations for Flood Reanalysis -- A Proof-of-Concept

التفاصيل البيبلوغرافية
العنوان: Assimilation of SWOT Altimetry and Sentinel-1 Flood Extent Observations for Flood Reanalysis -- A Proof-of-Concept
المؤلفون: Nguyen, Thanh Huy, Ricci, Sophie, Piacentini, Andrea, Emery, Charlotte, Suquet, Raquel Rodriguez, Luque, Santiago Peña
سنة النشر: 2024
مصطلحات موضوعية: Electrical Engineering and Systems Science - Image and Video Processing
الوصف: In spite of astonishing advances and developments in remote sensing technologies, meeting the spatio-temporal requirements for flood hydrodynamic modeling remains a great challenge for Earth Observation. The assimilation of multi-source remote sensing data in 2D hydrodynamic models participates to overcome such a challenge. The recently launched Surface Water and Ocean Topography (SWOT) wide-swath altimetry satellite provides a global coverage of water surface elevation at a high resolution. SWOT provides complementary observation to radar and optical images, increasing the opportunity to observe and monitor flood events. This research work focuses on the assimilation of 2D flood extent maps derived from Sentinel-1 C-SAR imagery data, and water surface elevation from SWOT as well as in-situ water level measurements. An Ensemble Kalman Filter (EnKF) with a joint state-parameter analysis is implemented on top of a 2D hydrodynamic TELEMAC-2D model to account for errors in roughness, input forcing and water depth in floodplain subdomains. The proposed strategy is carried out in an Observing System Simulation Experiment based on the 2021 flood event over the Garonne Marmandaise catchment. This work makes the most of the large volume of heterogeneous data from space for flood prediction in hindcast mode paves the way for nowcasting.
Comment: Accepted for publication in IEEE 2024 International Geoscience & Remote Sensing Symposium (IGARSS 2024)
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2403.14394
رقم الأكسشن: edsarx.2403.14394
قاعدة البيانات: arXiv