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Estimating continental river basin discharges using multiple remote sensing data sets

Journal article
Authors A. W. Sichangi
L. Wang
K. Yang
Deliang Chen
Z. J. Wang
X. P. Li
J. Zhou
W. B. Liu
D. Kuria
Published in Remote Sensing of Environment
Volume 179
Pages 36-53
ISSN 0034-4257
Publication year 2016
Published at Department of Earth Sciences
Pages 36-53
Language en
Keywords Altimetry, Discharge, Remote sensing, stations hydraulic geometry, satellite radar altimetry, digital, elevation model, fresh-water discharge, rating curves, low-gradient, data-sparse, calibration, uncertainty, performance, Environmental Sciences & Ecology, Remote Sensing, Imaging Science &, Photographic Technology
Subject categories Earth and Related Environmental Sciences


Rivers act as a source of fresh water for terrestrial life, yet the discharges are poorly documented since the existing direct observations are inadequate and some observation stations have been interrupted or discontinued. Discharge estimates using remote sensing thus have a great potential to supplement ground observations. There are remote sensing methods established to estimate discharge based on single parameter derived relationships; however, they are limited to specific sections due to their empirical nature. In this study, we propose an innovative method to estimate daily discharges for continental rivers (with river channel widths >800 m (Birkett and Beckley, 2010)) using two satellite derived parameters. Multiple satellite altimetry data and Moderate Resolution Imaging Spectroradiometer (MODIS) data are used to provide a time series of river stages and effective river width. The derived MODIS and altimetry data are then used to optimize unknown parameters in a modified Manning's equation. In situ measurements are used to derive rating curves and to provide assessments of the estimated results. The Nash-Sutcliffe efficiency values for the estimates are between 0.60 and 0.97, indicating the power of the method and accuracy of the estimations. A comparison with a previously developed empirical multivariate equation for estimating river discharge shows that our method produces superior results, especially for large rivers. Furthermore, we found that discharge estimates using both effective river width and stage information consistently outperform those that only use stage data. (C) 2016 The Authors. Published by Elsevier Inc.

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