Home >

news Help

Publication Information


Title
Japanese: 
English:Estimating River Discharge by Assimilating SWOT Observations using a Physically Based Empirical Localization Method 
Author
Japanese: RevelNilanka Menaka Tisho Kumar, 池嶋大樹, 山崎大, 鼎信次郎.  
English: Menaka Revel, Daiki Ikeshima, Dai Yamazaki, Shinjiro Kanae.  
Language English 
Journal/Book name
Japanese: 
English: 
Volume, Number, Page        
Published date Dec. 2020 
Publisher
Japanese: 
English:AGU 
Conference name
Japanese: 
English:AGU Fall Meeting 2020 
Conference site
Japanese:USA 
English: 
Official URL https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/688267
 
Abstract Estimating river discharge is important in understanding spatial and temporal variations in terrestrial waters. The future Surface Water and Ocean Topography (SWOT) satellite mission will observe the water surface elevation and slope and can be used to estimate river discharge. Even though methods for incorporating SWOT measurements into river hydrodynamic models have been developed to generate spatially and temporally continuous discharge estimates. However, application of those methods in global scale is still difficult due the computational capabilities of assimilation schemes. We developed a physically based empirical localization technique to overcome global-scale hydrological data assimilation incapacities. With the help of developed hydrological data assimilation method, a framework for estimating river discharge on a global-scale was derived by incorporating SWOT observations into the CaMa-Flood hydrodynamic model. Several experiments were performed with and without model error assumption using multi-model runoff forcing. The inaccurate model parameters were assumed to be represented in Manning’s coefficient. Assimilation of virtual SWOT observations considerably improved river discharge estimates for continental-scale rivers at high latitudes (>50°) and also downstream river reaches at low latitudes. High assimilation efficiency in downstream river reaches was due to both local state correction and the propagation of corrected hydrodynamic states from upstream river reaches. More accurate global river discharge estimates were obtained in river reaches with large accumulated SWOT overpasses from upstream reaches per SWOT cycle when no model error was assumed. Even though introducing model errors decreased the assimilation efficacy, the accuracy of estimated river discharge remain high. Therefore, estimating correct hydrodynamic model parameters (i.e. Manning’s’ coefficient) are essential for maximizing SWOT information. We also found that basin-wide assimilation, rather than reach-specific assimilation, was required for estimating discharge in river reaches with a large drainage area. These synthetic experiments showed where discharge estimates can be improved using SWOT observations. Further advances are needed for data assimilation on global-scale.

©2007 Tokyo Institute of Technology All rights reserved.