TITRE: ARARAS (Algorithm for Radar Altimetry Retracking on speculAr waveformS), application over the Mana river for long-term multimission Time Series

In the context of climate change, it is imperative to have a global understanding of water resources and their use. Long-term water level time series play an essential role in analyzing long-term trends, detecting inter-annual variations, understanding seasonal cycles and estimating long-term hydrological changes. Unfortunately, long time series from in situ stations are seldom available at the global scale, and particularly in remote areas such as tropical forests. Altimetry is emerging as an effective alternative.

We have developed an innovative processing method to optimize the use of historical altimetry missions in low-resolution mode (LRM) and generate extended time series. This retracker uses a physical model to search for sinc-squared patterns in echoes. Adapted to the specific features of each altimeter, it enables the processing of clipped waveforms, a common phenomenon for narrow rivers. This is particularly relevant for Poseidon altimeters, where conventional retracking methods, such as Offset Center of Gravity (OCOG), struggle to produce accurate results with such clipped echoes.

Applying this retracker, we generated time series of water levels along the Mana River in French Guiana, using data from the Jason family missions. These results illustrate the influence exerted on the water cycle by the construction of a run-of-river hydroelectric power plant near Saut Maman Valentin.

 

Keywords – Altimetry, Jason, Topex/Poseidon, Low Resolution Mode Altimetry, Inland Water Altimetry, River