DOI: 10.5281/zenodo.17928116
title: Daily Water Surface Elevations on Rivers from Multi-Mission Satellite Altimetry

description: 1. Summary

This repository contains the daily Water Surface Elevation WSE time series derived from multi-mission satellite altimetry (SWOT, Sentinel-3A/B, Sentinel-6) using the Reach-Reg method, as detailed in Halicki et al., (2026). This methods uses WSE from the Dahiti webportal (Schwatke et al., (2015), dahiti.dgfi.tum.de/en), as well as river vectors from the SWORD database (Altenau et al., 2021). In the version v1, the dataset includes validated WSE estimates and associated accuracy metrics for 8 major global rivers, covering 95 Reference Stations (RS) across four continents. Future versions will include also other river data. The Python implementation of Reach-Reg is also freely available on GitHub (https://github.com/MichalHalicki4/Reach-Reg). When using WSE data from this repository, please cite Halicki et al. (2026).

1. Data formats

For each river there is a separate .rar file, containing (1) an accuracy metadata sheet, as well as (2) a separate .csv sheet for a daily WSE time series on each RS. 

 

3. Attribute description



Daily WSE time series:




Column Name
Description
Units




Index
Date of the observation (YYYY-MM-DD)
Date


wse
Daily Water Surface Elevation WSE
meters (m)


wse_u
WSE Uncertainty 
meters (m)


N
Number of individual altimetry measurements aggregated within the day
count





Accuracy metadata:




Column Name
Description
Units




id
Reference Station (RS) ID
integer


x, y
Coordinates of the RS (longitude, latitude)
decimal degrees


chain
Chainage of the RS (from the downstream boundary of the river section)
km


river
River name
text


g_chain
Chainage of the gauge (from the downstream boundary of the river section)
km


velocity
Estimated mean river flow velocity used for time synchronization
m/s


c
Estimated parameter 'c' from the at-a-station hydraulic geometry simplification
variable


v_uncrt_range
Uncertainty range of the estimated velocity
m/s


num_of_all_meas
Total number of all raw altimetry measurements used for RS densification during the study period
count


num_of_vs
Total number of Virtual Stations (VS) aggregated to densify WSE at RS
count


mean_bias
Mean error of all VS and RS WSE measurements
m


prct_in_unct
Percentage of in situ data falling within the WSE +/- uncertainty range
%


mean_rmsd_agg
Mean aggregated RMSD (from the chained regression)
m


wl_amp
Water Level Amplitude (based on the densified WSE time series at RS)
m


rmse_rr
Root Mean Squared Error of the Reach-Reg daily WSE time series (validated against in situ)
m


rmse_raw
RMSE of the raw RS time series (not densified, just interpolated)
m


rmsd_cval
RMSD derived from the cross-validation
m


nse_rr
Nash-Sutcliffe Efficiency of the  Reach-Reg daily WSE time series
-


nse_raw
NSE of the raw RS time series (not densified, just interpolated)
-


nse_cval
NSE derived from the cross-validation
-


nrmse_rr
Normalized Root Mean Squared Error of the  Reach-Reg daily WSE time series
%


nrmse_raw
NRMSE of theraw RS time series (not densified, just interpolated)
%


nrmse_cval
NRMSE derived from the cross-validation
%






4. References



Altenau, E. H., Pavelsky, T. M., Durand, M. T., Yang, X., Frasson, R. P. de M., & Bendezu, L. (2021). The surface water and ocean topography (SWOT) mission river database (SWORD): A global river network for satellite data products. Water Resources Research, 57(7). https://doi.org/10.1029/2021WR030054

Halicki, M., Niedzielski, T., Schwatke, C., Scherer, D., & Dettmering, D. (2026). Daily river water levels from multi-mission altimetry: A reach-based regression method using the unique SWOT data geometry. [In Review]

Schwatke, C., Dettmering, D., Bosch, W., & Seitz, F. (2015). Dahiti – an innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry, Hydrology and Earth System Sciences, 19, 4345–4364. https://doi.org/10.5194/hess-19-4345-2015