21 Feb 2023
 | 21 Feb 2023
Status: a revised version of this preprint is currently under review for the journal ESSD.

AltiMaP: Altimetry Mapping Procedure for Hydrography Data

Menaka Revel, Xudong Zhou, Prakat Modi, Dai Yamazaki, Stephane Calmant, and Jean-François Cretaux

Abstract. Satellite altimetry data are useful for monitoring water surface dynamics, evaluating and calibrating hydrodynamic models, and enhancing river-related variables through optimization or assimilation approaches. However, comparing simulated water surface elevations (WSEs) using satellite altimetry data is challenging due to the difficulty of correctly matching the representative locations of satellite altimetry virtual stations (VSs) to the discrete river grids used in hydrodynamic models. In this study, we introduce an automated altimetry mapping procedure (AltiMaP) that allocates VS locations listed in the HydroWeb database to the Multi-Error Removed Improved Terrain Hydrography (MERIT Hydro) river network. Each VS was flagged according to the land cover of the initial pixel allocation, with 10, 20, 30, and 40 representing river channel, land with the nearest single-channel river, land with the nearest multi-channel river, and ocean pixels, respectively. Then, each VS was assigned to the nearest MERIT Hydro river reach according to geometric distance. Among the approximately 12,000 allocated VSs, most were categorized as flag 10 (71.7 %). Flags 10 and 20 were mainly located in upstream and midstream reaches, whereas flags 30 and 40 were mainly located downstream. Approximately 0.8 % of VSs showed bias, with considerable elevation differences (≥|15|m) between the mean observed WSE and MERIT digital elevation model. These biased VSs were predominantly observed in narrow rivers at high altitudes. Following VS allocation using AltiMaP, the median root mean squared error of simulated WSEs compared to satellite altimetry was 7.86 m. The error rate was much lower (10.6 %) than that obtained using a traditional approach, partly due to bias reduction. Thus, allocating VSs to a river network using the proposed AltiMaP framework improved our comparison of WSEs simulated by the global hydrodynamic model to those obtained by satellite altimetry. The AltiMaP source code ( (Revel et al., 2023a) and data ( (Revel et al., 2022) are freely accessible online and we anticipate that they will be beneficial to the international hydrological community.

Menaka Revel et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-438', Anonymous Referee #1, 26 Apr 2023
    • AC1: 'Reply on RC1', Menaka Revel, 05 Aug 2023
  • RC2: 'Comment on essd-2022-438', Anonymous Referee #2, 03 Jul 2023
    • AC2: 'Reply on RC2', Menaka Revel, 05 Aug 2023
  • RC3: 'Comment on essd-2022-438', Anonymous Referee #3, 05 Jul 2023
    • AC3: 'Reply on RC3', Menaka Revel, 05 Aug 2023

Menaka Revel et al.

Data sets

AltiMaP v1.0 M. Revel, X. Zhou, P. Modi, D. Yamazaki, S. Calmant, and J. Cretaux

Model code and software

AltiMaP M. Revel, X. Zhou, P. Modi, D. Yamazaki, S. Calmant, and J. Cretaux

Menaka Revel et al.


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Short summary
As satellite technology advances, there is an incredible amount of remotely sensed data for observing terrestrial water. Satellite altimetry observations, which offer water heights can be utilized to calibrate and validate large-scale hydrodynamic models. However, because large-scale models are discontinuous, comparing satellite altimetry to predicted water surface elevation is difficult. We developed a satellite altimetry mapping procedure for high-resolution river network data.