Geoff Blewitt

Land Subsidence in Las Vegas, Nevada, 1935–2000: New Geodetic Data Show Evolution, Revised Spatial Patterns, and Reduced Rates

Subsidence in Las Vegas Valley has been geodetically monitored since 1935, and several generations of maps have depicted more than 1.5 m of total subsidence. This study presents new geodetic data that reveal insights into the spatial distribution and magnitude of subsidence through the year 2000. In particular, synthetic aperture radar interferometry (InSAR) and global positioning system (GPS) studies demonstrate that subsidence is localized within four bowls, each bounded by Quaternary faults. Conventional level line surveys across the faults further indicate that these spatial patterns have been present since at least 1978, and based on the new geodetic data a revised map showing subsidence between 1963 and 2000 has been developed. A comparison of the location of the subsidence bowls with the distribution of pumping in the valley indicates that subsidence is offset from the principal zones of pumping. Although the reasons for this offset are not well understood, it is likely the result of heavy pumping up-gradient from compressible deposits in the subsidence zones. A compilation of subsidence rates based on conventional, InSAR, and GPS data indicates that rates have significantly declined since 1991 because of an artificial recharge program. The rates in the northwest part of the valley have declined from more than 5–6 cm/year to about 2.5–3 cm/year, a reduction of 50 percent; in the central and southern parts of the valley, rates have declined from about 2.5 cm/year to only a few millimeters per year, a reduction of more than 80 percent.

Rapid GPS-based determination of earthquake displacement field and magnitude for tsunami propagation modeling and warning

Reliable tsunami early warning requires a rapid assessment of the tsunamigenic potential of an earthquake as well as a prediction of the likely propagation pattern of the tsunami. Low-latency availability of the coseismic Earths surface displacements can support the assessment of the tsunamigenic potential of an earthquake and improve predictions of the propagation pattern of the tsunami. We have developed a fingerprint methodology for the rapid determination of the surface displacement field from GNSS-determined displacements. The fingerprint methodology depends on a priori knowledge of the faults potentially involved in a rupture. The known faults are parametrized with standard elements and for each element so-called fingerprint functions are computed for unit strike and dip slips. After an event, the model space of all reasonable fault-element combinations is searched for the element-slip combination best fitting the observed displacements. This combination provides the best estimate of the displacement field and earthquake magnitude consistent with observations. Here we describe the fingerprint methodology and the main architectural elements of a prototype for the rapid determination of magnitude and displacement field.

Rapid determination of earthquake magnitude and displacement field from GPS-observed coseismic offsets for tsunami warning

Rapid assessment of the tsunamigenic potential of an earthquake as well as a prediction of the likely propagation pattern of the tsunami support reliable tsunami early warning. Availability of the coseismic surface displacements with low latency can support the assessment of the tsunamigenic potential of an earthquake and improve predictions of the propagation pattern of the tsunami. We use a fingerprint methodology for the rapid determination of the static co-seismic displacement field and an unbiased magnitude estimate from GNSS displacements. The fingerprint methodology requires a priori knowledge of the faults potentially involved in a rupture. The known faults are parametrized with standard elements and for each element so-called fingerprint functions are computed for unit strike and dip slips. After an event, the model space of all reasonable fault-element combinations is searched for the element-slip combination best fitting the observed displacements, which provides the best estimate of the earthquake displacement field and magnitude. Here we describe the fingerprint methodology and discuss the limitations of the current system.