Local Hydrological Information in Gravity Time Series: Application and Reduction
Hydrological variations of up to some 10 nm/s2 are significant and broadband signals in temporal gravity observations. On the one hand they need to be eliminated from the data as they interfere with geodynamic signals. On the other hand they can be used to improve the understanding of hydrological process dynamics and to evaluate distributed hydrological models. Compared to satellite observations which are affected by global and regional hydrological variations continuous recordings from superconducting gravimeters (SGs) additionally may contain extractable information on local changes. To compare terrestrial data to satellite observations and to regional/global hydrological models, a local hydrological impact on the observations must be quantified and appropriately reduced first.
To investigate the local hydrological impact on gravity of the hilly and geologically heterogeneous surroundings of the SG at the Geodynamic Observatory Moxa, Germany, interdisciplinary research has been carried out. For an area of about 1.5 × 1.5 km2 a hydrological catchment model was combined with a gravimetric 3D model, including heterogeneities of the subsoil and topography in detail. A reduction of the local hydrological signal in the SG recordings was developed. About 30% of the local hydrological effect in the SG data originate from an area within a radius of 90 m around the observatory. The contribution of areas above the SG level is about 85% of the total local effect. After the local hydrological signal is separated, the SG data become suitable to be interpreted with regard to changes in continental water storage as found in GRACE satellite observations and in global hydrological models. The evaluation of the local hydrological model basing on the gravimetric modelling and the SG data highlights approaches for further enhancement of the internal hydrological process representations.
KeywordsHydrological Model Gravity Data Superconducting Gravimeter High Soil Water Content Snow Storage
The authors are indebted to Manfred Fink, Norbert Kasch, Wernfrid Kühnel, Matthias Meininger, Martin Rasmussen and Stefanie Zeumann from Friedrich-Schiller-University-Jena for their help in the extensive field work. We gratefully acknowledge Hans-Jürgen Götze and Sabine Schmidt from Chrisitan-Albrechts-University Kiel for fruitful discussions and for providing the software IGMAS. The authors thank the German Research Foundation (DFG) for their funding of this research.
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