30 April 2024 Examining the impact of hydro-geomorphological features in satellite river width-based discharge estimations
M. S. Adarsh, C. T. Dhanya, Shard Chander
Author Affiliations +
Abstract

We investigate the reliability of satellite river width (SRW) measurements to estimate the river discharge and its sensitivity to various hydro-geomorphological features. The study encompasses SRW extents at 141 in-situ hydrological observation stations, across seven tropical basins in India, with a mean annual discharge ranging from 2351 m3/s to less than 1 m3/s. Integrating optical (Sentinel-2, Landsat) and synthetic-aperture radar (SAR; Sentinel-1) data in the Google Earth Engine (GEE), 63,885 images are processed in the GEE to generate a dense time series of the SRW. Results demonstrate a good correlation (>0.50) between the SRW and in-situ discharge at 61 stations, primarily in the Godavari and Mahanadi basins. Furthermore, SRW-based rating curves exhibit reliable predictive capabilities at 44 stations, highlighting the potential to develop SRW rating curves in sparsely gauged basins. Investigations on the possible impact of different hydro-geomorphological features on the performance of the SRW to estimate the river discharge revealed optimal conditions in river reaches at lower elevations with substantial temporal variations in the discharge and associated variation in the river width along with a history of maximum water spread. Consequently, the Surface Water and Ocean Topography satellite’s river networks in the region are classified based on these findings, with 3567 out of 6132 river reaches identified as suitable for reliable SRW-based discharge estimation.

© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE)
M. S. Adarsh, C. T. Dhanya, and Shard Chander "Examining the impact of hydro-geomorphological features in satellite river width-based discharge estimations," Journal of Applied Remote Sensing 18(2), 024503 (30 April 2024). https://doi.org/10.1117/1.JRS.18.024503
Received: 30 October 2023; Accepted: 10 April 2024; Published: 30 April 2024
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KEYWORDS
Satellites

Synthetic aperture radar

Landsat

Earth observing sensors

Rain

Satellite imaging

Clouds

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