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Presentation, evaluation and sensitivity of a discharge algorithm for remotely sensed river measurements : Test cases on Sacramento and Garonne Rivers

Yoon, Yeosang and Garambois, Pierre-André and Paiva, Rodrigo C.D. and Durand, Michael and Roux, Hélène and Beighley, Edward Presentation, evaluation and sensitivity of a discharge algorithm for remotely sensed river measurements : Test cases on Sacramento and Garonne Rivers. (2016) Water Resources Research, 52 (1). 278-294. ISSN 0043-1397

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Official URL: http://dx.doi.org/10.1002/2015WR017319

Abstract

We present an improvement to a previously presented algorithm that used a Bayesian Markov Chain Monte Carlo method for estimating river discharge from remotely sensed observations of river height, width, and slope. We also present an error budget for discharge calculations from the algorithm. The algorithm may be utilized by the upcoming Surface Water and Ocean Topography (SWOT) mission. We present a detailed evaluation of the method using synthetic SWOT-like observations (i.e., SWOT and AirSWOT, an airborne version of SWOT). The algorithm is evaluated using simulated AirSWOT observations over the Sacramento and Garonne Rivers that have differing hydraulic characteristics. The algorithm is also explored using SWOT observations over the Sacramento River. SWOT and AirSWOT height, width, and slope observations are simulated by corrupting the ‘‘true’’ hydraulic modeling results with instrument error. Algorithm discharge root mean square error (RMSE) was 9% for the Sacramento River and 15% for the Garonne River for the AirSWOT case using expected observation error. The discharge uncertainty calculated from Manning’s equation was 16.2% and 17.1%, respectively. For the SWOT scenario, the RMSE and uncertainty of the discharge estimate for the Sacramento River were 15% and 16.2%, respectively. A method based on the Kalman filter to correct errors of discharge estimates was shown to improve algorithm performance. From the error budget, the primary source of uncertainty was the a priori uncertainty of bathymetry and roughness parameters. Sensitivity to measurement errors was found to be a function of river characteristics. For example, Steeper Garonne River is less sensitive to slope errors than the flatter Sacramento River.

Item Type:Article
Additional Information:Thanks to American Geophysical Union (AGU) editor. The definitive version is available at http://onlinelibrary.wiley.com/ The original PDF of the article can be found at http://onlinelibrary.wiley.com/doi/10.1002/2015WR017319/abstract
HAL Id:hal-01717283
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Ecole Nationale du Génie de l'Eau et de l'Environnement de Strasbourg - ENGEES (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Other partners > Institut National des Sciences Appliquées de Strasbourg - INSA (FRANCE)
Other partners > Ohio State University (USA)
Other partners > Université de Strasbourg - UNISTRA (FRANCE)
Other partners > Universidade Federal do Rio Grande do Sul - UFRGS (BRAZIL)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Other partners > Northeastern University (USA)
Other partners > University of California – Merced (USA)
Laboratory name:
Funders:
NASA - CNES TOSCA
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Deposited By: Helene ROUX
Deposited On:26 Feb 2018 09:44

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