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ABSTRACT
We present a preliminary study on using the Surface Water and Ocean Topography (SWOT) mission to extend water surface elevation (WSE) measurements from a sparsely distributed in situ gauge network along a one-dimensional (1D) study reach within the Mahanadi River basin in India. We use the Centre National d’Etudes Spatiales (CNES) simulator to simulate 3 years of synthetic measurements of SWOT WSE, which are assimilated into a 1D stochastic model based on six independent configurations. For each configuration, the model is derived using historical measurements of in situ WSE to simulate daily WSE estimates every 200 m along the study reach. Assimilated outputs showed high Nash-Sutcliffe efficiency (0.697–0.811), high correlation (0.838–0.901) and low root mean square error (0.242–0.513 m) with respect to in situ validation data. Results indicate consistent performance of the SWOT-assimilated model framework and are relevant considering the declining availability of in situ monitoring stations.
Editor S. Archfield; Associate Editor T. Heckmann
Editor S. Archfield; Associate Editor T. Heckmann
Acknowledgements
The authors acknowledge the support from the DST CNRS project through IFC/4126/DST-CNRS/2018-19/1/1726, the BRICS project through CCAFRITPOA and the DST Center of Excellence in climate studies, IIT Bombay, under project DST/CCP/CoE/140/2018(G). The authors thank M. J. Tourian, University of Stuttgart, for the suggestions provided regarding the model set-up during the initial stages of the work. We extend our gratitude to Prof. Faisal H, University of Washington, for inviting IIT Bombay to be a part of the NASA SWOT Early Adopter projects, which gave us more insights into the SWOT mission and its capabilities. The authors acknowledge the support by the CEFIPRA project approved under CSRP scheme with Project no. 7000-W-1.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/02626667.2024.2368755