Forward Modeling to Assess and Improve Gravity Network Geometry at Kilauea Volcano, Hawai`i

Abstract

Scientists have been using campaign gravity surveys to monitor volcanic activity at Kilauea's summit for decades, yet we have a poor understanding of the ability of the existing network to resolve sources of magma accumulation with different mass changes and depths. We also do not yet have a fully quantified measure of the relative importance of the stations in the network. This research tests the network using a simple forward modeling approach over a range of likely source volumes and depths. The analysis determines network sensitivity to three different likely source locations, calculates the relative importance of stations in the network, and examines the problem of signal distortion imposed by network geometry. This work finds that the current network is least sensitive to south caldera sources, and investigates the location and number of stations that will resolve this problem most effectively.

GRAV3D Validation using Generalized Cross-Validation (GCV) Algorithm by Lower Bounds Approach for 3D Gravity Data Inversion

“…The problem that arises is that there is no discussion about the validity of the GRAV3D program before it can be used for gravity data inversion modeling. Validation of the GRAV3D program must be done to obtain the validity and reliability of the recovered models obtained as a result of inversion [1], [2] There is a possibility of obtaining the validity of the UBC-GIF GRAV3D program through two approaches (i) a reference model ( ) and (ii) lower and upper bound models that define the minimum and maximum values, which will determine the cell value in the mesh until the recovered model is obtained smooth. [3].…”