Removing Sub-microGal Hydrologic Signals in Absolute Gravity Observations
Abstract
This project is titled “Removing Sub-microGal Hydrologic Signals in Absolute Gravity Observations “ and led by PIs Daniella Rempe and Clark Wilson from the Department of Geological Sciences at the University of Texas at Austin. Superconducting gravimeter (SG) observations indicate that changes in hydrological storage can lead to gravity variations below one microGal. These gravity variations are a source of noise to Absolute Gravimeter (AG) observations. This study seeks to develop an algorithm for removing hydrologic signals from AG observations at the microGal to sub-microGal level. We propose to incorporate hydrologic observations into gravity prediction and uniquely test these predictions against observations at two field sites in Texas that are situated in coastal and inland settings. At the mountainous, inland field site, the McDonald Geodetic Observatory, we will incorporate high resolution hydrological and ground surface deformation data into gravity prediction and directly test these predictions against SG observations. At the coastal site, near Corpus Christi, where a previous AG survey reported 17 microGal uncertainty, we will quantify the contribution of water level changes to the gravity signal by incorporating a variety of observations and novel water level prediction methods into our gravity calculations. Model-data integration at our field sites is expected to provide guidance on the data requirements for correction of hydrologic signals in AG observations. Further, the resulting algorithm, which incorporates hydrologic data into gravity prediction, is expected to provide a quantitative means of removing hydrologic noise from AG survey observations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 06, 2020
- Source ID
- HM04761912004
Entities
People
- Daniella Rempe
Organizations
- National Geospatial-Intelligence Agency
- University of Texas at Austin