Journal of Geodesy

, Volume 91, Issue 5, pp 519–534 | Cite as

Combination of multi-mission altimetry data along the Mekong River with spatio-temporal kriging

  • Eva BoergensEmail author
  • Sven BuhlEmail author
  • Denise Dettmering
  • Claudia Klüppelberg
  • Florian Seitz
Original Article


River water-level time series at fixed geographical locations, so-called virtual stations, have been computed from single altimeter crossings for many years. Their temporal resolution is limited by the repeat cycle of the individual altimetry missions. The combination of all altimetry measurements along a river enables computing a water-level time series with improved temporal and spatial resolutions. This study uses the geostatistical method of spatio-temporal ordinary kriging to link multi-mission altimetry data along the Mekong River. The required covariance models reflecting the water flow are estimated based on empirical covariance values between altimetry observations at various locations. In this study, two covariance models are developed and tested in the case of the Mekong River: a stationary and a non-stationary covariance model. The proposed approach predicts water-level time series at different locations along the Mekong River with a temporal resolution of 5 days. Validation is performed against in situ data from four gauging stations, yielding RMS differences between 0.82 and 1.29 m and squared correlation coefficients between 0.89 and 0.94. Both models produce comparable results when used for combining data from Envisat, Jason-1, and SARAL for the time period between 2002 and 2015. The quality of the predicted time series turns out to be robust against a possibly decreasing availability of altimetry mission data. This demonstrates that our method is able to close the data gap between the end of the Envisat and the launch of the SARAL mission with interpolated time series.


Multi-mission altimetry Spatio-temporal ordinary kriging Inland altimetry Mekong River Stochastic space–time processes Covariance models along river Non-stationary covariance models 



The altimeter observations and geophysical corrections are taken from OpenADB ( The altimeter missions are operated and maintained by ESA (Envisat), ISRO/CNES (SARAL), and NASA, CNES, EUMETSAT and NOAA (Jason-2). The original data sets are disseminated by AVISO, ESA, and PODAAC. We thank Christian Schwatke for the help by the processing of the altimeter time series in DAHITI. SB thanks Anthony Davison and his group, especially Sebastian Engelke and Peiman Asadi, for interesting discussions and advice during his research stay at EPFL Lausanne. This work was supported by the German Research Foundation (DFG) through fund SE 1916/4-1 and by the TUM International Graduate School of Science and Engineering (IGSSE).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Deutsches Geodätisches ForschungsinstitutTechnische Universität MünchenMunichGermany
  2. 2.Center for Mathematical SciencesTechnische Universität MünchenGarchingGermany

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