Abstract. In spite of the fundamental role of the landscape water balance for the Earth's water and energy cycles, monitoring the water balance and its components beyond the point scale is notoriously difficult due to the multitude of flow and storage processes and their spatial heterogeneity. Here, we present the first field deployment of an iGrav superconducting gravimeter (SG) in a minimized enclosure for long-term integrative monitoring of water storage changes. Results of the field SG on a grassland site under wet–temperate climate conditions were compared to data provided by a nearby SG located in the controlled environment of an observatory building. The field system proves to provide gravity time series that are similarly precise as those of the observatory SG. At the same time, the field SG is more sensitive to hydrological variations than the observatory SG. We demonstrate that the gravity variations observed by the field setup are almost independent of the depth below the terrain surface where water storage changes occur (contrary to SGs in buildings), and thus the field SG system directly observes the total water storage change, i.e., the water balance, in its surroundings in an integrative way. We provide a framework to single out the water balance components actual evapotranspiration and lateral subsurface discharge from the gravity time series on annual to daily timescales. With about 99 and 85 % of the gravity signal due to local water storage changes originating within a radius of 4000 and 200 m around the instrument, respectively, this setup paves the road towards gravimetry as a continuous hydrological field-monitoring technique at the landscape scale.

We present a Matlab/Octave-based software tool mGlobe to compute the effect 1 of atmospheric, continental water storage, and non-tidal ocean mass variations on 2 surface gravity. These effects must be considered or reduced prior to any analy-3 sis of geophysical phenomena using observations of superconducting gravimeters. effect, we introduce a site-specific correction factor based on differences between 13 the real topography and model's orography. 14

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Ground-based gravimetry is increasingly used to study mass distributions and mass transport below the earth surface. The gravity effect of local water storage variations can be large and should be accounted for in the interpretation of these data. However, the effect of hydrologic mass changes in the immediate vicinity of the gravimeter is not considered in standard routines for separating unwanted signal components. This applies in particular to the effect of the buildings in which gravimeters are installed. The building shields the underlying soil from precipitation and evapotranspiration and thus directly affects the water storage dynamics in the near-field of the gravimeter. A combined approach of in situ soil moisture observations and hydrologic modeling was used to quantify the altered water storage variations below observatory buildings. Subsequently, the errors caused by different estimation approaches for this umbrella effect in hydrogravitational computations were assessed. Depending on the site characteristics, the errors range from 4.1 to [Formula: see text] for the intra-annual amplitude when natural soil moisture data are considered for modeling the umbrella effect, and they range from 4.1 to [Formula: see text] when assuming no gravity change within 5 m below the building. These results were condensed to general recommendations, leading to a new simple and broadly applicable method to reduce observed gravity data for building effects, given basic information about the gravimeter location, building dimensions, climatic regime, and soil type of the observation site. This new reduction approach indicates errors of the intra-annual amplitude from 1.9 to [Formula: see text].

Terrestrial gravimetry is increasingly used to monitor mass transport processes in geophysics boosted by the ongoing technological development of instruments. Resolving a particular phenomenon of interest, however, requires a set of gravity corrections of which the uncertainties have not been addressed up to now. In this study, we quantify the time domain uncertainty of tide, global atmospheric, large‐scale hydrological, and nontidal ocean loading corrections. The uncertainty is assessed by comparing the majority of available global models for a suite of sites worldwide. The average uncertainty expressed as root‐mean‐square error equals 5.1 nm/s2, discounting local hydrology or air pressure. The correction‐induced uncertainty of gravity changes over various time periods of interest ranges from 0.6 nm/s2 for hours up to a maximum of 6.7 nm/s2 for 6 months. The corrections are shown to be significant and should be applied for most geophysical applications of terrestrial gravimetry. From a statistical point of view, however, resolving subtle gravity effects in the order of few nanometers per square second is challenged by the uncertainty of the corrections.

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Abstract. In spite of the fundamental role of the landscape water balance for the Earth’s water and energy cycles, monitoring the water balance and its components beyond the point scale is notoriously difficult due to the multitude of flow and storage processes and their spatial heterogeneity. Here, we present the first field deployment of an iGrav superconducting gravimeter (SG) in a minimized enclosure for long-term integrative monitoring of water storage changes. Results of the field SG on a grassland site under wet-temperate climate conditions were compared to data provided by a nearby SG located in the controlled environment of an observatory building. The field system proves to provide gravity time series that are similarly precise as those of the observatory SG. At the same time, the field SG is more sensitive to hydrological variations than the observatory SG. We demonstrate that the gravity variations observed by the field setup are almost independent of the depth below the terrain surface where water storage changes occur (contrary to SGs in buildings), and thus the field SG system directly observes the total water storage change, i.e., the water balance, in its surroundings in an integrative way. We provide a framework to single out the water balance components actual evapotranspiration and lateral subsurface discharge from the gravity time series on annual to daily time scales. With about 99 % and 85 % of the gravity signal due to local water storage changes originating within a radius of 4000 and 200 meter around the instrument, respectively, this setup paves the road towards gravimetry as a continuous hydrological field monitoring technique at the landscape scale.

The Argentine-German Geodetic Observatory (AGGO) is one of the very few sites in the Southern Hemisphere equipped with comprehensive cutting-edge geodetic instrumentation. The employed observation techniques are used for a wide range of geophysical applications. The data set provides gravity time series and selected gravity models together with the hydrometeorological monitoring data of the observatory. These parameters are of great interest to the scientific community, e.g. for achieving accurate realization of terrestrial and celestial reference frames. Moreover, the availability of the hydrometeorological products is beneficial to inhabitants of the region as they allow for monitoring of environmental changes and natural hazards including extreme events. The hydrological data set is composed of time series of groundwater level, modelled and observed soil moisture content, soil temperature, and physical soil properties and aquifer properties. The meteorological time series include air temperature, humidity, pressure, wind speed, solar radiation, precipitation, and derived reference evapotranspiration. These data products are extended by gravity models of hydrological, oceanic, La Plata estuary, and atmospheric effects. The quality of the provided meteorological time series is tested via comparison to the two closest WMO (World Meteorological Organization) sites where data are available only in an inferior temporal resolution. The hydrological series are validated by comparing the respective forward-modelled gravity effects to independent gravity observations reduced up to a signal corresponding to local water storage variation. Most of the time series cover the time span between April 2016 and November 2018 with either no or only few missing data points. The data set is available at https://doi.