Assimilation of SWOT Altimetry and Sentinel-1 Flood Extent Observations for Flood Reanalysis – A Proof-of-Concept
arxiv(2024)
摘要
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.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要