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USGS · 70035546

Hydrogeologic structure underlying a recharge pond delineated with shear-wave seismic reflection and cone penetrometer data

Abstract

With the goal of improving the understanding of the subsurface structure beneath the Harkins Slough recharge pond in Pajaro Valley, California, USA, we have undertaken a multimodal approach to develop a robust velocity model to yield an accurate seismic reflection section. Our shear-wave reflection section helps us identify and map an important and previously unknown flow barrier at depth; it also helps us map other relevant structure within the surficial aquifer. Development of an accurate velocity model is essential for depth conversion and interpretation of the reflection section. We incorporate information provided by shear-wave seismic methods along with cone penetrometer testing and seismic cone penetrometer testing measurements. One velocity model is based on reflected and refracted arrivals and provides reliable velocity estimates for the full depth range of interest when anchored on interface depths determined from cone data and borehole drillers' logs. A second velocity model is based on seismic cone penetrometer testing data that provide higher-resolution ID velocity columns with error estimates within the depth range of the cone penetrometer testing. Comparison of the reflection/refraction model with the seismic cone penetrometer testing model also suggests that the mass of the cone truck can influence velocity with the equivalent effect of approximately one metre of extra overburden stress. Together, these velocity models and the depth-converted reflection section result in a better constrained hydrologic model of the subsurface and illustrate the pivotal role that cone data can provide in the reflection processing workflow. ?? 2009 European Association of Geoscientists & Engineers.

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S.S. Haines, Adam Pidlisecky, R. Knight. 2009. Hydrogeologic structure underlying a recharge pond delineated with shear-wave seismic reflection and cone penetrometer data. https://pubs.usgs.gov/publication/70035546

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