Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-13823
Authors: Schollmeier, Philipp
Title: Understanding the hydrological signature in gravity data
Issue Date: 2023
metadata.ubs.publikation.typ: Abschlussarbeit (Master)
metadata.ubs.publikation.seiten: 109
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-138429
http://elib.uni-stuttgart.de/handle/11682/13842
http://dx.doi.org/10.18419/opus-13823
Abstract: Over the past two decades, the subsequent advancements in Superconducting Gravimeters (SGs) have ushered in a level of precision that enables the measurement of the impact of ground water and soil water on gravity. Because of the challenging nature of monitoring the total water volume and the relatively subtle amplitude of the hydrological signal, a comprehensive understanding of the precise hydrological signature in continuous gravity data remains elusive. In this study, I use SG data in conjunction with hydrological measurements from a geoscientific observatory in Germany to find the signature of hydrological signals in gravity data. I scrutinize the various steps involved in extracting this signal, presenting new methodologies, including a technique to eliminate oscillations in gravity residuals that are likely attributed to remaining tidal signals due to an imperfect tidal model. A major contribution of this work involves constructing a data-driven model that incorporates precipitation and soil moisture measurements to elucidate gravity variations. I address critical questions such as the impact of utilizing soil moisture data on the model’s performance, determining the optimal model for achieving the closest fit with gravity measurements, and assessing the applicability of computed model parameters to new epochs. Furthermore, I provide recommendations for refining the model-building process in future investigations. Results show that a convolution of the different hydrological timeseries with one half of a Gaussian bell curve leads to a strong agreement with the gravity measurements. The use of soil moisture data significantly improves the fit, especially when the measurement stations are spatially well distributed. This fit becomes less strong when the computed parameters are applied to new events, but the approach showed promise for some of the events. Enhancing our comprehension of the hydrological influence on gravity measurements holds promising implications, potentially positioning SGs as instruments for monitoring soil and ground water in the future. Moreover, this improved understanding could elevate the pre cision of analyzing other subtle signals, such as the effects of Polar Motion.
Appears in Collections:06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

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