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Allan Goddard Lindh

Publications and source records attributed to Allan Goddard Lindh.

7 recordsLinked to original sources
USGS2012

Seismic slip, segmentation, and the Loma Prieta Earthquake

We have plotted the cumulative seismic slip projected onto a vertical plane for earthquakes occurring during the last 20 years along 210 km of the San Andreas fault that includes the section that moved in the Loma Prieta earthquake. These plots illustrate the differences in depth and character of the seismicity between the locked and creeping portions of the fault or fault zone and define the segment upon which the Loma Prieta earthquake occurred. Working by analogy from the relation between pre-main shock microseismicity and presumed main shock slip regions at Parkfield and Loma Prieta, we identify a segment on the San Francisco Peninsula where we believe the M 7 1838 earthquake occurred, and which we believe may have accumulated sufficient strain that rupture should be expected in the coming decades.

California↗
USGS2012

Forecast model for moderate earthquakes near Parkfield, California

Earthquake instability models have possible application to earthquake forecasting because the models simulate both preseismic and coseismic changes of fault slip and ground deformation. In the forecast procedure proposed here, repeated measurements of preseismic fault slip and ground deformation constrain the values of model parameters. The early part of the model simulation corresponds to the available field data, and the subsequent part constitutes an estimate of future faulting and ground deformation. In particular, the time, location, and size of unstable faulting are estimates of the pending earthquake parameters. The forecast accuracy depends on the model realism and parameter resolution. The forecast procedure is applied to fault creep and trilateration data measured near Parkfield, California, where at least five magnitude 5.5 to 6 earthquakes have occurred regularly since 1881, the last in 1966. The quasi-static model consists of a flat vertical plane embedded in an elastic half space. Spacially variable fault slip of strike-slip sense is driven by an increasing regional shear stress but is impeded by a relatively strong patch of brittle, strain-softening fault. The field data are consistent with these approximate values of patch parameters: radius of 3 km, patch center 5 km deep and 8 km southeast of the 1966 epicenter, and maximum brittle strength of 26 bars. Fluctuations in the available field data prevent estimating the earthquake time with any more precision than use of the 21±8 year recurrence interval. However, the model may later give a more precise estimate of the earthquake time if the fault slip rate near the inferred patch increases before the earthquake, as predicted by the model.

Journal of Geophysical Research Solid Earth↗
USGS2003

The nature of earthquake prediction

Earthquake prediction is inherently statistical. Although some people continue to think of earthquake prediction as the specification of the time, place, and magnitude of a future earthquake, it has been clear for at least two decades that this is an unrealistic and unreasonable definition. The reality is that earthquake prediction starts from long-term forecasts of place and magnitude, with very approximate time constraints, and progresses, at least in principle, to a gradual narrowing of the time window as data and understanding permit. The analogy to catching a rabbit in an overgrown confined field may be appropriate. You do not just start out looking for the rabbit, you instead build a fence dividing the field in two and then decide which half the rabbit is in, thereby gaining one bit of information. You iterate this process until you have located the rabbit “close enough for practical purposes.” This is approximately how earthquake prediction proceeds in the real world, with time and position along a fault comprising the two dimensions of the search. (I assume here that we are considering for the moment only large earthquakes, that is those capable of inflicting serious damage on a regional scale; in California this means events of about M 6.7 and larger.) This more realistic perspective on the problem lays to rest the “red herring” that “earthquake predictions might do more harm than earthquakes.” These imaginary concerns are predicated on the fantasy of a prediction that precisely specifies time, place, and magnitude; in the real world a progression of probabilities that narrows the space-time window in small steps clearly carries no such threat.

Seismological Research Letters↗
USGS1999

Calibration formulae and values for velocity seismometers used in the 1998 Santa Clara Valley, California seismic experiment

Eaton (1975), Bakun and Dratler (1976), Eaton (1977), Healy and O’Neil (1977), Asten (1977), Stewart and O'Neill (1980), Liu and Peselnick (1986), Eaton (1991), Rodgers et al. (1995), and many others (see Asten (1977) for a list of earlier references) have presented formulae for calculating the damped generator constant (or motor constant), and the damping constant (or fractional damping ratio) for magnetically damped velocity seismometers. Unfortunately the notation varies between authors, and not all the formulae allow for some of the significant variables -- differences in input impedance of the recording system in particular. This has become particularly relevant because the USGS seismic networks in California have traditionally set up their velocity sensors for the 10K Ohm impedance of the standard USGS analog telemetry systems (Eaton, 1977), but modern digital recording systems are usually set up with high input impedances, often of a megaohm or greater. Thus the nominal calibration values valid for USGS velocity sensors in their “normal” configuration are incorrect when they are recorded on other systems. In this short note we have collected the relevant formulae needed, and computed the seismometer responses for the various velocity sensors used in the recent Santa Clara Valley Seismic Experiment (SCVSE, see Lindh et al., 1999).

California↗