Water Levels of Inland Water Bodies

The determination of water levels of inland waters offers numerous challenges. Observations are usually limited to large rivers or main streams (river widths of many hundreds of meters to kilometers), since radar signals in the case of small water bodies can be heavily distorted by surrounding topography and off-nadir backscatter signals. Furthermore, the spatial and temporal resolution of the observation data depends on the satellite orbits.  

In order to improve the data coverage and produce the most accurate time series possible, DGFI-TUM is working on the development of improved analysis methods for radar echoes perturbed by the influence of land and the combination of different missions with different sensors and orbital characteristics (e.g. missions on repeat-tracks and on drifting orbit configurations). This comprises the classification and retracking of altimeter waveforms, the treatment of inter-mission and retracker biases, the elimination or appropriate use of off-nadir observations (so-called hooking effect) and outliers, and the optimal combination of observations. To provide a comprehensive spatio-temporal description of a river system, statistically robust interpolation methods are developed that take into account the changing flow velocity of the river as well as particular catchment conditions.

Using the developed methods, time series of water levels for lakes, reservoirs and rivers are calculated and thoroughly validated by comparison with in situ gauge data. Depending on the size of the water body and the topography, accuracies of up to one centimeter are achieved.

Data are made available through the web service DAHITI (Database for Hydrological Time Series of Inland Waters).
 

Related projects

Selected Publications

Boergens E., Schmidt M., Seitz F.: The use of B-splines to represent the topography of river networks. GEM - International Journal on Geomathematics, 12(1), 10.1007/s13137-021-00188-w, 2021 (Open Access)
Boergens E., Dettmering D., Seitz F.: Observing water level extremes in the Mekong River Basin: The benefit of long-repeat orbit missions in a multi-mission satellite altimetry approach. Journal of Hydrology, 570, 463-472, 10.1016/j.jhydrol.2018.12.041, 2019
Passaro M., Rose S.K., Andersen O.B., Boergens E., Calafat F.M., Dettmering D., Benveniste J.: ALES+: Adapting a homogenous ocean retracker for satellite altimetry to sea ice leads, coastal and inland waters. Remote Sensing of Environment, 211, 456-471, 10.1016/j.rse.2018.02.074, 2018
Boergens E., Nielsen K., Andersen O., Dettmering D., Seitz F.: River Levels Derived with CryoSat-2 SAR Data Classification-A Case Study in the Mekong River Basin. Remote Sensing, 9(9), 1238, 10.3390/rs9121238, 2017 (Open Access)
Boergens E., Buhl S., Dettmering D., Klüppelberg C., Seitz F.: Combination of multi-mission altimetry data along the Mekong River with spatio-temporal kriging. Journal of Geodesy, 91(5), 519-534, 10.1007/s00190-016-0980-z, 2017
Göttl F., Dettmering D., Müller F.L., Schwatke C.: Lake level estimation based on CryoSat-2 SAR altimetry and multi-looked waveform classification. Remote Sensing, 8(11), 885, 10.3390/rs8110885, 2016 (Open Access)
Dettmering D., Schwatke C., Boergens E., Seitz F.: Potential of ENVISAT radar altimetry for water level monitoring in the Pantanal wetland. Remote Sensing, 8(7), 596, 10.3390/rs8070596, 2016 (Open Access)
Boergens E., Dettmering D., Schwatke C., Seitz F.: Treating the hooking effect in satellite altimetry data: a case study along the Mekong River and its tributaries. Remote Sensing, 8(2), 91, 10.3390/rs8020091, 2016 (Open Access)
Schwatke C., Dettmering D., Bosch W., Seitz F.: DAHITI – an innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry. Hydrology and Earth System Sciences 19(10): 4345-4364, 10.5194/hess-19-4345-2015, 2015 (Open Access)

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