Abstract An important goal of the Surface Water and Ocean Topography (SWOT) mission is to provide river width, height, slope to estimate global river discharges. To appraise the feasibility of SWOT data over India, the present study utilizes the SWOT simulator from Centre National D’Etudes Spatiales (CNES) to generate a long time-series (three years) of SWOT observations over the Mahanadi River basin in India. Two independent sources of river geometry are used in this study, namely satellite-based and hydrodynamic model-based estimates. Satellite-based river geometry is derived using a web-based User Interface (UI) developed in-house to generate time series of accurate river width shapefiles from Sentinel-1 satellite imagery. To compare these results, a 1D unsteady flow analysis is carried out over the Mahanadi River to simulate channel water depth and inundation extent using the Hydrologic Engineering Center's River Analysis System (HEC-RAS) model. The simulated observations are used in this study to assess the potential error in SWOT channel water depth measurements. Results indicate a good spatial correlation between the water surface area derived from Sentinel and HEC-RAS models with a correlation of 0.74. The simulated data shows a bias of 20 cm compared to gauge observations. This study is conducted as a proof of concept in demonstrating the ability of simulated SWOT data in capturing river water surface elevation with respect to the conventional HEC-RAS model. It also implements a new tool in google earth engine (GEE) to generate input to SWOT simulator.
Evaluating SWOT water level information using a large scale hydrology simulator: A case study over India
Advances in Space Research ; 70 , 5 ; 1362-1374
2022-05-01
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Transforming Surface Water Hydrology Through SWOT Altimetry
British Library Conference Proceedings | 2013
|PO.DAAC SWOT Hydrology Data Access
NTRS | 2019
|SWOT Oceanography and Hydrology Data Product Simulators
NTRS | 2013
|SWOT over the ice-covered ocean
NTRS | 2017
|