Publication Date:
2023-08-09
Description:
The widespread use of relative gravimeters has enabled scientists, surveyors, and engineers to collect large amounts of surface gravity data in a rapid and relatively inexpensive way. Nevertheless, to obtain absolute values of acceleration due to gravity, the relative measurements need to be tied to absolute gravity stations through a network adjustment, and the sources of error present in the data must be accounted for. Gravity observations are affected by (1) systematic errors, such as the gravimeter drift, atmospheric pressure variations, groundwater changes, and Earth tides, (2) random errors (ground vibrations, environmental and transportation conditions, accumulation of random-walk-type errors, etc.) that can allow long wavelength biases to develop in the adjusted solution, especially towards the edges of the network, and (3) blunders (e.g., operator reading and transcribing errors). Therefore, obtaining high accuracy gravity values for thousands of stations that spread over vast distances, largely depends on rigorous data-collection protocols and appropriate adjustment techniques. In this work we present a field protocol that is based on massively redundant observation patterns and a robust two-step least squares adjustment. This methodology, implemented as a Matlab package, guarantees reliable adjusted gravity values with well-constrained standard error estimates. We demonstrate the capabilities of our technique for the case of the Bolivian gravity network (~2400 stations), where the acceleration of gravity was determined with a typical level of uncertainty of 0.1 to 0.15 mGals.
Language:
English
Type:
info:eu-repo/semantics/conferenceObject
Permalink
