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Water-level monitoring is essential for analyzing hydrological extremes, environmental flows, sustainable development and management of water resources. Satellite altimeters have operationally been used to estimate river water levels (e.g., SARAL-Altika, Jason-2/3) with poor revisit times (10–35 days). In this current study, we propose a method to estimate river water levels using scatterometer data with 2-day temporal resolution. Sensitivity analysis of radar frequency (Ku- and C-bands) for river water-level estimation was carried out. The concept of change in radar backscatter with an increase in soil wetness is used to develop a model function between basin water index (BWI) and observed river stage. High-resolution OceanSat Scatterometer (OSCAT) (Ku-band) and advanced scatterometer (ASCAT) (C-band) scatterometer image reconstruction (SIR), digital elevation model, and observed water stage datasets have been used in this study. We observed that C-band scatterometer shows better results than Ku-band in terms of Pearson correlation coefficient ( <tex-math notation="LaTeX">R </tex-math>), Nash–Sutcliffe Efficiency (NSE), and root mean square error (RMSE), which can be attributed to higher soil wetness sensitivity of the C-band compared with Ku-band scatterometers. <tex-math notation="LaTeX">R </tex-math> ranged between 0.93 and 0.97 for the C-band and between 0.89 and 0.95 for the Ku-band data. Similarly, NSE ranged from 0.84 to 0.95 for the C-band and between 0.56 and 0.95 for the Ku-band data over selected study sites in the Brahmaputra river basin. Model accuracy was found to be adequate for monitoring of river stage from a remote sensing platform. This study shows that scatterometer observations can be used for operational water-level estimations, which can be useful for water resource management.
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Kushwaha et al. (2022) studied this question.
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