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Free keywords:
Hydrogravimetry, iGrav, terrestrial gravimetry, electrical resistivity tomography, sub surface processes, soil moisture, inverse modelling
Abstract:
A sprinkling experiment was conducted at the geodetic observatory Wettzell (Bavaria, Germany) with the intention to combine classical hydrological field observations of soil moisture with gravity data and electrical resistivity tomography (ERT). The setup consisted of 8 sprinkling units installed around a gravimeter in field enclosure. Artificial rainfall was applied for 6 hours. The sprinkling area of 15 x 15 m was equipped with 3 vertical soil moisture sensor profiles, 1 horizontal soil moisture transect, near-surface soil moisture sensors and 3 ERT profiles. The non-invasive gravity data and the ancillary monitoring data were used to infer water transport processes in the subsurface during the sprinkling experiment. To this end, the gravity data were used to identify the structure and the parameters of a subsurface flow model in an inverse modelling approach by optimizing the simulated gravity response with respect to the observations. The ancillary soil moisture and ERT data were used to evaluate the model outputs in terms of adequacy and dominant subsurface flow processes. Model data cover the following subtopics:
• virtual experiments to show the theoretical relationships between subsurface water re-distribution processes and their corresponding gravity responses
• an uncertainty analysis of the sprinkling experiment, e.g., with respect to water volumes and their spatial distribution, and the impact on the expected gravity response
• inverse modelling to identify dominant subsurface water re-distribution processes
• a synthetical model setup based on the ancillary datasets of soil moisture and ERT
Monitoring and model output data used for this investigation is provided within this data repository. A detailed description and discussion can be found in Reich et al. (2021). The inverse modelling was carried out using the R-package gravityInf (Reich, 2021).
