DAHITI – an innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry

Satellite altimetry has been designed for sea level monitoring over open ocean areas. However, for some years, this technology has also been used to retrieve water levels from reservoirs, wetlands and in general any inland water body, although the radar altimetry technique has been especially applie...

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Bibliographic Details
Published in:Hydrology and earth system sciences 2015-10, Vol.19 (10), p.4345-4364
Main Authors: Schwatke, C, Dettmering, D, Bosch, W, Seitz, F
Format: Article
Language:English
Subjects:
Altimeters
Computation
Data
ERS-2
Hydrologic cycle
Hydrologic data
Hydrology
Inland waters
Investigations
Kalman filters
Lakes
Outliers (statistics)
Radar
Radar altimetry
Rivers
Satellite altimetry
Satellites
Sea level
Sea level monitoring
Time series
TOPEX
Water bodies
Water levels
Web services
Wetlands
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Summary:Satellite altimetry has been designed for sea level monitoring over open ocean areas. However, for some years, this technology has also been used to retrieve water levels from reservoirs, wetlands and in general any inland water body, although the radar altimetry technique has been especially applied to rivers and lakes. In this paper, a new approach for the estimation of inland water level time series is described. It is used for the computation of time series of rivers and lakes available through the web service "Database for Hydrological Time Series over Inland Waters" (DAHITI). The new method is based on an extended outlier rejection and a Kalman filter approach incorporating cross-calibrated multi-mission altimeter data from Envisat, ERS-2, Jason-1, Jason-2, TOPEX/Poseidon, and SARAL/AltiKa, including their uncertainties. The paper presents water level time series for a variety of lakes and rivers in North and South America featuring different characteristics such as shape, lake extent, river width, and data coverage. A comprehensive validation is performed by comparisons with in situ gauge data and results from external inland altimeter databases. The new approach yields rms differences with respect to in situ data between 4 and 36 cm for lakes and 8 and 114 cm for rivers. For most study cases, more accurate height information than from other available altimeter databases can be achieved.
ISSN:1607-7938
1027-5606
1607-7938
DOI:10.5194/hess-19-4345-2015