Repeat microgravity data from Tucson Basin and Avra Valley, Arizona, 2016-2019
Dates
Publication Date
2019-08-28
Start Date
2015-12-15
End Date
2019-04-26
Revision
2019-08-27
Citation
Kahler, L.M., and Landrum, M.T., 2019, Repeat microgravity data from Tucson Basin and Avra Valley, Arizona, 2016-2019 (ver. 2.0, August 2019): U.S. Geological Survey data release, https://doi.org/10.5066/P93513GH.
Summary
This dataset supercedes an earlier data release and includes all previous data in addition to data from 2019. These data represent the network-adjusted results of relative- and absolute-gravity surveys. Relative-gravity surveys were carried out using a Micro-g LaCoste D-series relative-gravity meter. The effect of solid Earth tides and ocean loading were removed from the data. Instrument drift was removed by evaluating gravity change during repeated measurements at one or more base stations. Absolute-gravity surveys were carried out using a Micro-g LaCoste, Inc. A-10 absolute-gravity meter. Vertical gradients between the different measuring heights of the absolute- and relative-gravity meters were measured using a relative-gravity [...]
Summary
This dataset supercedes an earlier data release and includes all previous data in addition to data from 2019. These data represent the network-adjusted results of relative- and absolute-gravity surveys. Relative-gravity surveys were carried out using a Micro-g LaCoste D-series relative-gravity meter. The effect of solid Earth tides and ocean loading were removed from the data. Instrument drift was removed by evaluating gravity change during repeated measurements at one or more base stations. Absolute-gravity surveys were carried out using a Micro-g LaCoste, Inc. A-10 absolute-gravity meter. Vertical gradients between the different measuring heights of the absolute- and relative-gravity meters were measured using a relative-gravity meter and fully-adjustable tripod, and used to correlate the measurements between the two instruments. Relative-gravity differences and absolute-gravity data were combined using a least-squares network adjustment, as implemented in the software Gravnet (Hwang, C., Wang, C., Lee, L., 2002. Adjustment of relative gravity measurements using weighted and datum-free constraints. Comput. Geosci. 28, 1005–1015). Additional information about the network adjustment is provided under Data Quality. Data pre- and post-processing were carried out using GSadjust (https://github.com/usgs/sgp-GSadjust).
First posted: August 12, 2018
Revised: August 27, 2019
TAMA_AdjustedGravity_2016-2019_vector.shp.xml Original FGDC Metadata
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TAMA_AdjustedGravity_2016-2019_vector.cpg
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TAMA_AdjustedGravity_2016-2019_vector.dbf
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TAMA_AdjustedGravity_2016-2019_vector.prj
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TAMA_AdjustedGravity_2016-2019_vector.sbn
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TAMA_AdjustedGravity_2016-2019_vector.sbx
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TAMA_AdjustedGravity_2016-2019_vector.shp
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TAMA_AdjustedGravity_2016-2019_vector.shx
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Purpose
Data were collected to evaluate aquifer-storage change. Using the horizontal infinite-slab approximation, gravity data (in units of acceleration, for example, m/s^2), are converted to a thickness of free-standing water, regardless of the depth to or porosity of the interval at which storage-change occurs. Data are not corrected for soil-moisture variation (that is, estimated storage changes include all storage change between the land surface and the aquifer).
