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Cited by 53

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River levels from multi mission altimetry, a statistical approach

Nielsen, Karina, Zakharova, Elena, Tarpanelli, Angelica, Andersen, Ole B., Benveniste, Jérôme·2022·Remote Sensing of Environment
DOI 10.1016/j.rse.2021.112876
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Abstract

Satellite altimetry is a key technique to measure water level change in continental water bodies. Altimetry-based water level time series of rivers are typically constructed at locations where the satellite ground tracks intersect the rivers, the so-called virtual stations. The relatively low sampling frequency (10–27 days) of the repeat missions may result in an under-sampling of the hydrological regime in rivers with sub-monthly to weekly events. We are currently in a unique position with more than a handful satellite altimetry missions simultaneously mapping the surface elevation of the Earth. In combination, these missions contain an unexploited potential to obtain a more detailed picture of the hydrological regime of many of the Earth's rivers. The task of combining water levels measured at different locations and/or by satellites with different orbits is however, challenging due to e.g. topography, intermission biases, variation in river morphology, and other unidentified causes. In this work, we present a new method to combine multi-mission altimetry-based water levels from a river reach. This will also enable the use of geodetic missions like CryoSat-2 and SARAL/AltiKa (after June 2016) in water level time series. To combine the data we set up a state-space model where the process part is a first-order autoregressive process. The observations as a function of time and distance along the reach are described as a sum of the water level at a given time scaled by a distan…

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Metadata

Authors
Nielsen, K., Zakharova, E., Tarpanelli, A., Andersen, O. B., & Benveniste, J.
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2022-03
Volume
270
Pages
112876
ISSN
0034-4257
DOI
10.1016/j.rse.2021.112876
Cited by
53
References
1
Language
en
Licence
Funders
  • European Space Agency (20756/07/NL/CB, 4000125543/18/I-NB)
  • Lomonosov Moscow State University

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CoChat. (2026). Citation check: River levels from multi mission altimetry, a statistical approach. https://app.cochat.ai/papers/10.1016/j.rse.2021.112876
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Nielsen, K., Zakharova, E., Tarpanelli, A., Andersen, O. B., & Benveniste, J. (2022). River levels from multi mission altimetry, a statistical approach. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2021.112876

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