Current Ground Motions Along the Long-Point Fault Derived from Continuous GPS Observations (2012-2014)

dc.contributor.advisorWang, Guoquan
dc.contributor.committeeMemberSaylor, Joel E.
dc.contributor.committeeMemberShrestha, Ramesh L.
dc.creatorSerna, John, Jr.
dc.date.accessioned2017-06-22T14:01:20Z
dc.date.available2017-06-22T14:01:20Z
dc.date.createdMay 2015
dc.date.issued2015-05
dc.date.submittedMay 2015
dc.date.updated2017-06-22T14:01:20Z
dc.description.abstractThe Texas Gulf Coast region possesses numerous complex fault structures. This case study focused on the Long-Point Fault, an active fault located in west Houston; with 16 kilometers of length, it is the longest fault within the region. This fault causes recurring damage to roadways, buried pipes, and buildings along the fault trace, resulting in a financial burden for taxpayers. This study employed a high-resolution LiDAR map depicting precise locations of principal fault systems within the greater Houston metropolitan area. Georeferencing was combined with a high-accuracy kinematic GPS technique in order to establish the precise fault trace of the Long-Point Fault. Field investigations verified that the fault scarp mapped by the 2001 airborne LiDAR mapping of Houston coincides with the surface trace of the Long-Point Fault. To establish surface fault motion, eleven permanent GPS stations were installed for continuous GPS monitoring in 2012. To enhance spatial resolution, twenty-six benchmarks were installed along the Long-Point fault trace and were reoccupied in monthly surveys. Daily GPS observations from 2012–2014 were processed using both relative (double differencing) and absolute (precise point) positioning methods. Two years of GPS observations indicate that the Long-Point Fault area is experiencing subsidence. All GPS stations along the Long-Point Fault observed subsidence rated ranging from 1–7 mm/year as well as strong vertical seasonal variation, 4 cm peak to peak. Minor horizontal movements at 1–4 mm/yr, referenced to the stable Houston reference frame (SHRF), were observed at several GPS stations; however, no coherent fault motion was observed along the length of the fault surface trace. Groundwater data from water wells near the Long-Point Fault area were obtained and examined for possible correlation with subsidence. At the end of 2014, the groundwater levels in the Chicot and Evangeline aquifers in the Long-Point Fault area are 50–53 m and 69–106 m below the ground surface, respectively. Daily depth to groundwater level for the Chicot and Evangeline aquifer system show correlation between aquifer recharge, and withdrawal, and vertical seasonal variation exhibited by all installed GPS stations along the Long-Point Fault. The Chicot and Evangeline ground water levels have been increasing in this area since 2000, but are still below the regional preconsolidation of ~30 m below the ground surface, contributing to the subsidence observed. While correlation between seasonal vertical movement and groundwater level change exists, a longer period of continuous GPS observations will be able to provide more information about the activity of the fault.
dc.description.departmentEarth and Atmospheric Sciences, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/1799
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectGPS
dc.subjectLong Point Fault
dc.titleCurrent Ground Motions Along the Long-Point Fault Derived from Continuous GPS Observations (2012-2014)
dc.type.dcmitext
dc.type.genreThesis
thesis.degree.collegeCollege of Natural Sciences and Mathematics
thesis.degree.departmentEarth and Atmospheric Sciences, Department of
thesis.degree.disciplineGeophysics
thesis.degree.grantorUniversity of Houston
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

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