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ARS Home » Southeast Area » Oxford, Mississippi » National Sedimentation Laboratory » Watershed Physical Processes Research » Research » Publications at this Location » Publication #330304

Title: Self-adaptive method for high frequency multi-channel analysis of surface wave method

item LU, ZHIQU - University Of Mississippi

Submitted to: Journal of Applied Geophysics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/2/2015
Publication Date: 8/7/2015
Citation: Lu, Z. 2015. Self-adaptive method for high frequency multi-channel analysis of surface wave method. Journal of Applied Geophysics. 121:128-139.

Interpretive Summary: Non-invasive soil profile measurement and subsurface soil imaging are important for agriculture applications such as soil mechanical and hydraulic properties measurement, soil layering such as plowpan and fragipan detection, and soil surface erosion (surface crusting/sealing) evaluation. A high-frequency multi-channel analysis of surface wave (HF-MASW) method has been developed at National Center for Physical Acoustics, the University of Mississippi with the collaboration of researchers at USDA-ARS National Sedimentation Laboratory in Oxford. The technique can non-invasively measure one-dimensional soil profile and two-dimensional image of subsurface soil in the vadose zone in terms of the shear wave velocity that is related to soil strength, water content, and water potential. This paper described in detail the methodology of the HF-MASW method and proposed an innovative data acquisition configuration and signal processing algorithm, a so-called the self-adaptive MASW method. The new technique improve the accuracy and spatial resolution in the determination of soil profile.

Technical Abstract: When the high frequency multi-channel analysis of surface waves (MASW) method is conducted to explore soil properties in the vadose zone, existing rules for selecting the near offset and spread lengths cannot satisfy the requirements of planar dominant Rayleigh waves for all frequencies of interest and will inevitably introduce near and far field effects as well as spatial aliases at certain frequencies. To solve these problems, a self-adaptive method is developed to determine high frequency dispersion trends. In this method, an initial dispersion curve is obtained by a fixed-offset MASW method and used to estimate wavelengths at all frequencies of interest. At each frequency, the near offset and spread lengths are then set to be 0.2–0.6 and 2–4 wavelengths respectively. In other words, the near offset and spread lengths are self-adaptive to the corresponding wavelength. Furthermore, in order to avoid spatial aliases and minimize the number of sensors or sensor locations, a variable sensor spacing configuration is proposed, in which the spacing for the first 120 steps is set to be 0.5 cm and the next 40 steps start with 1 cm spacing followed by 1 cm incremental spacing for each subsequent step. In this study, an accelerometer was used as a sensor to detect surface vibrations generated by an electrodynamic shaker operating in chirp mode. Two field tests were conducted and the results from the fixed-offset, self-adaptive, and variable spacing MASW methods were compared. The study demonstrates the ability of the self-adaptive MASW method to preferentially identify the dispersion trends of either the fundamental mode or higher modes of Rayleigh waves. It is also found that the dispersion trends can be determined beyond the source frequency range due to nonlinear effects that generate high harmonics of surface waves. This nonlinear phenomenon deserves future investigation.