GNSS_Vel_95CI.py: A Python Module for Calculating the Uncertainty of GNSS-Derived Site Velocity

Cornelison, Brendan; Wang, Guoquan

doi:10.1061/(asce)su.1943-5428.0000410

Cited by 7 publications

(3 citation statements)

References 3 publications

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“… (a) Daily subsidence time series (PPP solutions) derived from GPS data at TXLM, UHC3, UHC2, UHC1, and UHC0, referenced to the GOM20 reference frame. Methods for calculating the average subsidence rate and its 95% confidence interval (95%CI) are detailed in Wang (2022b) and Cornelison and Wang (2023). (b) U.S. Drought Monitor map released on 14 September 2023 (map source: https://droughtmonitor.unl.edu).…”

Section: Resultsmentioning

confidence: 99%

Unveiling the Hidden Threat: Drought‐Induced Inelastic Subsidence in Expansive Soils

Welch,

Wang,

Bao

et al. 2024

Geophysical Research Letters

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Expansive soils pose a significant challenge in geotechnical engineering, especially in coastal areas. While research has mainly focused on their elastic properties, this study explores the overlooked aspect of inelastic subsidence during prolonged droughts, utilizing decade‐long GPS datasets from the University of Houston Coastal Center. Our findings reveal substantial subsidence, approximately one to two dm, during the summer droughts of 2018, 2020, 2022, and 2023, due to compaction within the upper 4 m of expansive soils. Inelastic subsidence constitutes roughly 10% of the total subsidence, resulting in step‐like permanent land elevation loss over time. Notably, drought‐induced subsidence is prominent in open‐field areas with expansive soils but is minor in built‐up areas or in non‐expansive soil regions. The occurrence of inelastic subsidence challenges traditional assessments of relative sea‐level rise and coastal flooding, emphasizing the need to consider it in coastal infrastructure planning for enhanced resilience against climate uncertainties.

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Section: Resultsmentioning

confidence: 99%

Unveiling the Hidden Threat: Drought‐Induced Inelastic Subsidence in Expansive Soils

Welch,

Wang,

Bao

et al. 2024

Geophysical Research Letters

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“…An open-source Python module for decomposing the daily GNSS time series is available to the public through the Package Installer for Python (PIP). 53…”

Section: Methodsmentioning

confidence: 99%

“…The details of these parameters are addressed in the reference. 53 (a) Displacements y ( i ) and the linear component L ( i ), (b) nonlinear component NL( i ), (c) seasonal component S ( i ), and (d) residuals r ( i ).…”

Section: Methodsmentioning

confidence: 99%

A methodology for long-term offshore structural health monitoring using stand-alone GNSS: case study in the Gulf of Mexico

Wang

2023

Structural Health Monitoring

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This article presents a robust methodology for long-term offshore structural health monitoring (SHM) using the Global Navigation Satellite Systems (GNSS). The methodology relies on recently developed regional reference frames and single-receiver phase-ambiguity-fixed Precise Point Positioning techniques. The stable Gulf of Mexico Reference Frame 2020 (GOM20) provides a robust and consistent reference system for long-term offshore SHM in the Gulf of Mexico (GOM). Continuous GNSS observations (DEV1, 2010–2020) on a fixed platform in the Eugene Island 330 oil field are used to illustrate the methodology. The platform was installed in 1982 in 82-m water about 130 km away from the Mississippi Delta coastline. The major monitoring items include horizontal movements, seafloor subsidence, structure submergence, and seasonal oscillations. The stand-alone GNSS monitoring achieves 3- to 4-mm root-mean-square accuracy in the horizontal direction and 7 mm in the vertical direction for daily positions in the GOM region. According to this study, the GNSS antenna (DEV1) has moved 6 cm toward the northeast with respect to GOM20 since 2010; the ongoing structure submergence rate in the Eugene Island 330 oil field area is approximately 15 mm/year, a combination of seafloor subsidence (12 mm/year) and sea-level rise (2.6 mm/year) with respect to GOM20. The submergence in the future 40 years (2021–2060) would be greater than 0.6 m, likely between 0.8 and 1.0 m, but is unlikely to exceed 1.3 m. The peak-to-trough amplitudes of the seasonal movements at the top of the platform are below 5 mm in all three directions, comparable with the seasonal movements recorded by onshore GNSS in the Louisiana coastal region. The methodology introduced in this article can be applied to SHM in other offshore regions where stable regional reference frames are available.

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Creep-induced subsidence along coastal Louisiana with GPS measurements and finite element modeling

Voyiadjis,

Zhou,

Abdalla

2024

Geoenergy Science and Engineering

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GNSS_Vel_95CI.py: A Python Module for Calculating the Uncertainty of GNSS-Derived Site Velocity

Cited by 7 publications

References 3 publications

Unveiling the Hidden Threat: Drought‐Induced Inelastic Subsidence in Expansive Soils

Unveiling the Hidden Threat: Drought‐Induced Inelastic Subsidence in Expansive Soils

A methodology for long-term offshore structural health monitoring using stand-alone GNSS: case study in the Gulf of Mexico

Creep-induced subsidence along coastal Louisiana with GPS measurements and finite element modeling

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