receiver functions at station BMN and compressional-wave (P-wave) velocity .... also be small in generating significant transverse-component ...... Hearn et al.
Bulletin of the SeismologicalSociety of America, Vol. 87, No. 1, pp. 183-199, February 1997
Shear-Wave Velocity Structure in the Northern Basin and Range Province from the Combined Analysis of Receiver Functions and Surface Waves by Serdar Ozalaybey,* Martha K. Savage, Anne F. Sheehan, John N. Louie, and James N. Brune
Abstract
A new method based on the joint inversion of receiver functions and surface-wave phase velocities results in well-determined shear-velocity structures that are consistent with the compressional-wave structure, gravity, heat flow, and elevation data in the northern Basin and Range. This new inversion method takes advantage of average-velocity information present in the surface-wave method and differential velocity information contained in the receiver function method, thus minimizing the nonuniqueness problem that results from the velocity-depth trade-off. An unusually thick (38 kin) and relatively faster crust and upper mantle are found in central and eastern Nevada compared to the thin (28 to 34 km) and slower crust and upper mantle of the western Basin and Range. We interpret the regions of thicker and faster crust and upper mantle as zones that have undergone less Cenozoic extension relative to the surrounding regions to the west and north. The thick crust and consequently greater depth to the dense mantle material is consistent with the gravity low pattern in central and eastern Nevada. Simple gravity modeling shows both local and regional isostatic compensation occur within 40 km of the surface, indicating a near-classical Airy type of compensation in the province. We analyze in detail the shear-wave (S-wave) velocity model derived from the receiver functions at station BMN and compressional-wave (P-wave) velocity models derived from the 1986 PASSCAL experiment in northwestern Nevada. The most interesting feature of these models is the presence of negative-velocity gradients in the S-wave model with no corresponding velocity decrease in the P-wave models between depths of 10 and 24 km. This combined velocity model may be explained by high pore fluid pressures at these depths. This model favors a layered fluid porosity model proposed in the literature to explain extensive middle- to lower-crust continental seismic reflections and high electrical conductivity. An upper-mantle, gradational low-velocity zone is present between 32 and 38 km in the S-wave model. This upper-mantle, shear-wave, low-velocity zone is consistent with partial melt, which may be the source material for magmatic underplating in this region.
Introduction average differential arrival time as a fast, thick layer. Given a series of initial-velocity models, the velocity-depth tradeoff allows a group of final-velocity models with differing average velocities to be found that fit the observed receiver function equally well (Ammon et al., 1990). Based on this analysis, Ammon et aL (1990) urged that all future receiverfunction studies perform nonuniqueness analysis to exclude velocity models that do not fit the other a priori geophysical constraints obtained from refraction, reflection, earthquake travel-time, and surface-wave data where available. We address the nonuniqueness problem by combining receiver-function inversion with surface-wave phase velocity data. Surface-wave (fundamental-mode) phase velocities
Receiver-function modeling is a valuable means of obtaining local shear velocities in the crust and upper mantle beneath three-component, broadband, digital stations (e.g., Langston, 1979; Owens and Zandt, 1985; Ammon and Zandt, 1993; Kind et aL, 1995; Cassidy, 1995). Receiver-function inversions for shear-wave velocity structure are nonunique since there is very little absolute-velocity information contained in the receiver functions. This lack of information causes the nonuniqueness problem known as the velocitydepth trade-off; a slow, thin layer will produce the same *Present address: Department of Geology, NHB 245, University of Illinois, Urbana, Illinois 61801. E-mail:serdar@mercury'ge°l°gy'uiuc'edu
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are sensitive to the average shear-velocity structure of the material within the depth ranges to which they penetrate. The phase velocities provide information on the long-wavelength vertical averages of the shear structure between any given station pair. This information is essentially absent in the receiver functions, which are sensitive to velocity contrasts between materials. Thus, at depths sampled by both methods, a joint inversion of surface-wave phase velocities and receiver functions will result in a better-determined shearwave structure than inversion from either method alone. Compressional-structure studies also use a similar combination of two data sets to obtain well-determined velocity models of the crust. These data sets are from wide-angle refraction/reflection and near-vertical incidence reflection profiles (e.g., Holbrook et al., 1991; Catchings and Mooney, 1991). While seismic refraction data constrain absolute velocities, reflection data constrain a high-resolution structural image. Only the gross shear-wave structure of the crust and upper mantle of the northern Basin and Range province (NBRP) has been determined from the regional surface-wave phase velocity data inversions (e.g., Priestley and Brune, 1978, 1982; Priestley et al., 1980; Taylor and Patton, 1986) and from the attenuation of teleseismic and surface waves (e.g., Taylor et al., 1986; Patton and Taylor, 1984). Yet, there is a large volume of work that has produced detailed compressional-wave structure of the crust from modern reflection and refraction profiles (e.g., Klemperer et al., 1986; Allmendinger et al., 1987; Potter et al., 1987; Potter et al., 1987; Holbrook, 1990; Catchings and Mooney, 1991). One-dimensional shear-wave structures obtained from the inversion of receiver functions have the potential to offer vertical and horizontal resolution comparable to the compressional-wave structures obtained from refraction studies (Zandt and Owens, 1986). At a given frequency, shear waves travel at shorter wavelengths than compressional waves and thus maintain higher resolution; a shear waveform with a dominant frequency of 1 Hz is expected to be influenced by layers as thin as 1 km (Owens, 1987). Shear waveforms also display stronger anomalies than the compressional waveforms for the presence of seismic anisotropy, fluids and fractures in crustal rocks, and partial melt in the upper mantle. With high-quality receiver functions, all these potential effects can be studied in detail. In the following sections, we show that the joint inversion of receiver functions and surface-wave phase velocity data is a robust and valuable method for obtaining wellconstrained shear-wave velocity models. We show a sample synthetic test of this method and then present the results of using this method on real data to obtain one-dimensional crustal shear-wave structures beneath nine stations located in the NBRP. We summarize our shear-wave structures with three parameters that represent local averages, namely, crustal thickness, mean crustal, and upper-mantle shearwave velocities for each station. These parameters are then interpreted together with compressional-wave structure,
gravity, heat flow, and elevation data to detect regional variations in the structure. Data We model shear-wave velocity structure beneath five stations (DNY, BMN, WHR, KVN, and MNA) from the permanent broadband digital network of the University of Nevada, Reno (UNIt) and four portable stations (MLC, RTS, WCP, and GAll) from a recently conducted field experiment (Sheehan et al., 1995) (Fig. 1). The five UNR stations are equipped with broadband three-component Geotech sensors (models 7505Z, 8700H, SL-210Z, and SL-220H, 15-sec natural period) (Peppin and Nicks, 1992). The portable stations were deployed with CMG3-ESP broadband sensors for a period of 10 months. These stations are capable of recording seismic signals with a flat velocity response in the frequency range 0.03 to 20 Hz. We have analyzed the calibration pulses to make sure that the vertical- and horizontal-component sensors at each station have nearly the same amplitude and phase response within this frequency range. In addition to these stations, UNR broadband station WCN, and short-period stations RYN and MIL (1-sec natural period, vertical component) are used to increase path coverage for the surface-wave phase velocity measurements. Receiver Functions Receiver functions are extracted from the three-component broadband recordings of teleseismic P waveforms at epicentral distances ranging from 30° to 85 °. For this range, P waves are steeply incident and are recorded dominantly on the vertical component, while P-to-S converted shear waves are recorded dominantly on the horizontal-component seismogram. The extraction procedure is described by Langston (1979) and consists of a simple deconvolution of vertical-component seismograms from the radial and transverse components. The receiver functions obtained this way are assumed to be free of source, mantle-path, and instrumentresponse effects. The deconvolution is performed in the frequency domain (Owens et al., 1984) using a Gaussian filter and spectral trough filler. We have used a Gaussian filter width of 2.5 and trough filler value of 0.01, which produced stable deconvolutions. True amplitudes of receiver functions are preserved in the deconvolution process. The use of true amplitudes preserves information about the shallow velocity structure (Ammon, 1991) and helps avoid inaccuracies due to the presence of dipping layers (Cassidy, 1992). The receiver functions have been extracted from many events clustered in distance and backazimuth ranges. These receiver functions are stacked to decrease noise. Figure 2 shows the stacked receiver functions for the UNR permanent stations from three backazimuth ranges grouped as southeast (SE), northwest (NW), and southwest (SW). Northeast receiver functions are not shown because of lack of events in this quadrant. In general, the SW receiver
Shear-Wave Velocity Structure in the Northern Basin and Range Province from the Combined Analysis of Receiver Functions
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Figure 1. Bouguer gravity anomaly map of the northern Basin and Range province plotted with crustal thickness (km), mean crustal shear velocity (km/sec), and uppermantle shear velocity (km/sec), respectively, shown under each station symbol. The UNR permanent stations are indicated with underlined station names. Crossing solid white lines indicate the location of the 1986 PASSCALexperiment profiles. Dashed white line shows the location of Isr = 0.708 line from Farmer and De Paolo (1983). Thick, solid white line is the refraction profile of Hill and Pakiser (1967). Black line shows the outline of butterfly gravity low anomaly pattern.
functions are noisier and associated with the highest transverse-component arrivals. The transverse-component arrivals may be due to scattering, anisotropy, or dipping layers. The transverse-component energy is, therefore, a measure of the deviation from isotropic and planar structure (Ammon and Zandt, 1993). The SW receiver functions are extracted from a distance range 65 ° to 85 ° and therefore are associated with steep angle of incidences at the base of the crust and low signal strength, generating weaker P-to-S conversions than closer events. Because of the low quality of the SW receiver functions, we do not use them in the inversions. The SE and NW receiver functions have strong P-to-S (Ps) converted arrivals (Moho Ps phase following the direct P-wave arrival) (Fig. 2). We model the radial component receiver functions from the NW and SE backazimuths assuming isotropic and planelayered crustal structure. The transverse-component receiver functions can be modeled for the effects of anisotropy and/ or dipping structure when a high number of events are used in stacking and/or data are available from an array of stations. McNamara and Owens (1993) analyze more than 100 Moho Ps conversions from a large aperture station array in
west-central Nevada (near stations BMN and WHR) (Fig. 1). They find a fast azimuth of anisotropy oriented NW-SE with average delay times of 0.2 sec (due to shear-wave splitting in the Moho Ps phases), consistent with both our own and their observations of minimal transverse-component energy excitation associated with energetic radial Moho Ps arrivals from the NW and SE backazimuth events. According to the seismic reflection data (e.g., Klempeter et al., 1986), the effects of dipping and laterally heterogeneous structure from the middle and lower crust must also be small in generating significant transverse-component energy. Thus, the transverse-component receiver-function arrivals we observe are probably the result of complex nearsurface scattering in the upper crust, which may not be modeled in any simple way. We form receiver-function stacks from the SE backazimuth at three distance ranges for stations BMN, WHR, and MNA. We group these receiver functions from distances of 28 ° to 45 ° as range 1, 50 ° to 60 ° as range 2, and greater than 65 ° as range 3. The variations of amplitude and phase among different ranges, corresponding to different sampling of ray parameters, are important in constraining the velocity struc-
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ture. The moveout of the multiples that travel as both P and S waves in the crust can provide average-velocity information on both compressional- and shear-wave velocities. We take advantage of this by jointly inverting receiver functions from different distance ranges. Figure 3 shows the stacked receiver functions only from the SE and NW backazimuth quadrants for the portable stations WCP, GAR, RTS, and MLC. The quality of the receiver functions from these stations is lower than that of the permanent stations because the short-period deployment resuited in fewer stackable events. However, we have at least one well-determined backazimuth quadrant suitable for the inversion at each station•
Surface-Wave Data We have measured Rayleigh-wave phase velocities for three paths using a regional event from Oregon and a teleseismic event from the Tonga Islands (Fig. 4). While the Oregon event provided data for the measurement of shortperiod (10 sec) Rayleigh-wave fundamental-mode phase velocities near station MNA (path 3), the Tonga event provided data for longer-period (20 to 25 sec) Rayleigh-wave fundamental-mode phase velocity measurements along paths 1 and 2 (Fig. 4). Both events have a high signal-to-noise ratio. The reason for observing these periods only is due to the energy produced by an event of a given size at a given dis-
Shear-Wave Velocity Structure in the Northern Basin and Range Provincefrom the Combined Analysis of Receiver Functions
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tance and the instrument response. Interstation Rayleighwave phase velocities were measured using the peak and trough method (Brune et al., 1960) after correcting for instrument phase response differences between stations. The peak and trough method is based on the time domain phase correlation of surface-wave peaks and troughs of nearly the same periods recorded at a station pair lying on the same great circle path. Measured phase velocities are shown in Figure 4. The accuracy of these phase velocities is estimated to be within + 0.1 km/sec, which is nearly equal to the scatter in the measured phase velocities between different station pairs. These phase velocities also deviate by only + 0.1 km/sec from the Great Basin model dispersion curve of Priestley and Brune (1978).
where D is a matrix containing partial derivatives of receiver function with respect to unknown velocity model m, m0 is the initial velocity model, F is a matrix of constraints made up from partial derivatives of surface-wave phase velocities with respect to m, A is the smoothness constraint matrix forming the second difference of the model m, o- is the adjustable parameter controlling the trade-off between fitting the waveform and smoothness of the model (Ammon et al., 1990), and rr and r Care vectors containing receiver-function waveform and phase velocity residuals, respectively• The partial derivatives in the constraint matrix F contain localized averaging functions of the model parameters associated with different periods of phase velocities. We show this behavior of F in the next section on a synthetic example. This additional averaging information helps to resolve the nonuniqueness problem caused by the velocity-depth trade-off. We use a small amount of smoothness during inversions (smoothness parameter o- = 0.1 to 0.3). The inversions quickly converge within five iterations.
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Synthetic Test In this section, we present a sample synthetic test to validate the constrained inversion method formulated above. We take the shear-wave velocity model of Mangino et al. (1993) and generate a synthetic radial-component receiver function representing our observed true-model receiverfunction data. We contaminate this receiver function by adding a real transverse-component receiver function representing noise. The maximum amplitude of the noise equals 10% amplitude of the radial receiver function. Rayleigh-wave phase velocities at 10- and 20-sec periods are used as the surface-wave phase velocity data. We choose the Great Basin shear-wave structure of Priestley and Brune (1978) as our initial model. Three velocity models are inverted using the receiver function and three pairs of phase velocity data. These pairs are obtained by adding and subtracting 0.2 km/ sec from the true-model phase velocity pair, respectively. Figure 5 shows these velocity models together with the theoretical dispersion curves for each model, a plot of Rayleigh-wave partial derivative-depth curves for the phase velocities, and receiver-function waveforms computed for
these models. The Rayleigh-wave partial derivatives of phase velocities with respect to model parameters and theoretical dispersion curves for a given velocity model are computed using the method of Rayleigh's variation principle and stress-motion propagator matrices, respectively (Aki and Richards, 1980). All surface-wave computations in this article are made with a computer program package written by Zeng (1995, personal comm.). These models differ the most in their average velocities for a depth range between 10 and 35 kin; the dotted model represents a high-velocity crust; the dashed model, a lowvelocity crust; and the solid model, a crust with velocities between the other two models (Fig. 5a). The solid model is found by the constrained inversion of the receiver function and the true-model phase velocity pair (3.06 km/sec at 10 sec and 3.51 km/sec at 20 sec) (Fig. 5c) and is nearly identical to the true-model velocity structure. The high-velocity and low-velocity crust models are found by using the highest- and lowest-phase velocity pairs, respectively. All three models fit the true-model receiver function with a waveform correlation coefficient of 0.993 or higher (Fig. 5d).
Shear-Wave Velocity Structure in the Northern Basin and Range Province from the Combined Analysis of Receiver Functions
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The Rayleigh-wave partial derivative-depth curves shown in Figure 5b make up the constraint matrix F in the matrix equation (1). Clearly, the 10-sec partial derivative curve is a localized averaging function for a depth range between 8 and 20 km, and a 20-sec partial derivative curve is a localized averaging function for depths of 15 km and deeper. It is this localized averaging behavior of the partial derivatives that leads to a unique velocity model as shown in this test. Thus, a pair of phase velocity data sampling different regions of the model space (corresponding to different periods of phase velocity measurements) is sufficient to provide the information needed to remove the nonuniqueness in the solutions. This is why we refer to the F matrix as the matrix of constraints, because we do not need a full joint inversion of phase velocity data with the receiver functions, but only a pair of well-determined phase velocity points. This avoids measurement of a full dispersion curve. In this way, we let the long-wavelength features of the velocity model, i.e., its average velocity, be resolved with the phase velocity data and the short-wavelength details be resolved by the receiver-function data. Another way of looking at these partial derivatives is that they construct long-wavelength smoothness constraints. No weighting, i.e., unit weighting, between the receiver function and phase velocity data was needed in solving the matrix equation (1) for a good fit of both data sets. Further, although this study includes only fundamental-
Figure 5. (a) Velocity models from the inversion constrained by the three pairs of phase velocity (shown as observed) joined with curves of the corresponding line type shown in (c). (b) Rayleigh-wave partial derivative curves computed for the initial model. (c) Dispersion curves corresponding to each velocity model. (d) Computed synthetic waveforms for each model shown above. mode Rayleigh-wave phase velocity derivatives, in principal, the F matrix can include different types of phase velocity derivative functions, which may be computed for travel times of earthquake S phases and for fundamental- and/or higher-mode surface waves of Rayleigh and/or Love type. The constrained-inversion method we describe here is a valuable method for obtaining well-constrained velocity models.
Inversion Results Initial Velocity Models Two initial models have been chosen to invert receiver functions. For the northwestern Basin and Range, we have taken the compressional-wave reflection velocity model of Benz et al. (1990) (N-S profile from SP8) and converted to shear-wave velocity structure (assuming a Poisson's ratio of 0.25). This model is used as the initial model for stations DNY, BMN, WHR, RTS, WCP, and GAR. For stations MNA, KVN, and MLC, we use the final shear-wave velocity model of Mangino et al. (1993) obtained from the receiver-function inversion at station MNV, located within 350 m of our station MNA. We generate 45 different initial models from each initial model by perturbing them with a cubic perturbation of 1.0 km/sec and 20% random component (Ammon et al., 1990).
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S. 13zalaybey, M. K. Savage, A. F. Sheehan, J. N. Louie, and J. N. Brune
We repeat inversions for each perturbed initial model to find joint models that fit both the receiver-function and phase velocity data. The inversion of many initial models is needed because inversions starting with models that do not predict phase velocity data well do not converge. The following sections present the results of receiverfunction inversions. This section will be presented in the following format: stations are grouped by their geographical locations as central (MNA, KVN, and MLC), eastern (RTS, WCP, and GAR), and northern (DNY, BMN, and WHR). The surface-wave phase velocity measurements shown in Figure 4 are used to constrain each inversion as follows; the longperiod measurements from the Tonga event from path 2 for the central and eastern and from path 1 for the northern stations, and the short-period measurements from the Oregon event from path 3 for the central stations (MNA and KVN only). We present inversion summary plots showing the final shear-wave velocity structure, the phase velocity data, and the receiver-function waveform fit for stations MNA, MLC, BMN, RTS, and GAR (Figs. 6, 8, 9, 10, and 11, respectively) (for other stations, see Ozalaybey, 1996). We identify the Moho with a thick black arrow in these plots. Our Moho picks are based on the nature of crust-mantle transition, i.e., the first increase in velocity either sharply or with a gradient at the expected velocities for the Moho (~4.3 km/sec). Where we have gradational boundaries, we pick the Moho at depths where shear-wave velocities first exceed approximately 4.3 km/sec. Figure 7 shows the final shear-wave velocity models for the other remaining stations. Central Stations MNA receiver functions from the NW show more scattering than the SE backazimuth counterpart (Fig. 2). We focus on the SE backazimuth receiver functions because they are simpler and display the same arrivals from all three ranges on the radial receiver functions. The arrivals for the first 6 sec seem to be coherent from all three ranges on both the radial and transverse receiver functions. These receiver functions are nearly identical to the receiver functions of Mangino et al. (1993) for station MNV. All three receiver functions in Figure 6 were inverted simultaneously. The final velocity model (Fig. 6a) fits both the receiver function and observed phase velocity data well (Fig. 6b and 6c). The main features of the velocity model are a sharp velocity increase in the upper 5 km (1.8 to 3.5 km/sec), a nearly constant velocity crust (3.5 km/sec), and a crust-mantle transition between depths of 32 and 34 kin. Station KVN has poor quality receiver functions from all backazimuth quadrants. The NW quadrant receiver function seems to be the simplest for inversion. We avoid fitting the details of this receiver function by using a high value of smoothness parameter (o- = 0.3). The high value of smoothness constraint for this inversion caused a poor fit to the receiver function but a good fit to dispersion data. This model indicates a crustal thickness of 32 km (Fig. 7). For station MLC, we invert the NW receiver function
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Figure 6. Inversion of MNA receiver functions from ranges 1, 2, and 3 and Rayleigh-wave phase velocities. (a) Final shear-wave velocity model (solid). Mangino et al. (1993) velocity model (dashed) is shown for comparison. The shaded regions indicate confidence bounds obtained from the sensitivity analysis (see Sensitivity Analysis for explanations). The bold arrow indicates the Moho. (b) Rayleigh-wave dispersion fit; observed phase velocities are from path 3 (10-sec period) and path 2 of MNA-MLCstation pair. Theoretical dispersion curve for the velocity model shown on the left fits this data well. (c) Receiverfunction waveform fit; the shaded region represents one standard deviation bounds for the stacked receiver functions. The solid lines indicate modeled receiver functions computed for the final velocity model.
because it displays much smaller transverse component and better-defined radial-component arrivals with tighter standard deviation bounds than the SE receiver function (Fig. 3). The broad Moho Ps phase clearly seen arriving near 5 sec implies a thick crust at this station. The most important feature of the velocity model is the gradational crust-mantle transition (Fig. 8). The upper-mantle shear velocities are reached at about 38 km, confirming a very thick crust beneath this station. Upper and lower crustal low-velocity zones (LVZ) are present in this model but are not constrained well by our data (see Sensitivity Analysis). Northern Stations At station BMN, we inverted only the SE receiver functions because other backazimuth quadrants are not characterized yet. The receiver functions from this station are of
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high quality and show a clear Moho Ps phase (at 3.8 sec) and its multiple PpPms near 12 sec from ranges 1 and 2 (Fig. 9). The amplitude of the transverse-component receiver functions is less than half the size of the radial components for these arrivals. We inverted the receiver functions from these two ranges simultaneously to obtain a joint shear-wave velocity model. The resulting final velocity model is smooth and shows a sharp crust-mantle boundary at 28 km (Fig. 9). An LVZ is present between depths of 32 and 38 km. We will analyze this model further in the following sections. The WHR receiver function from the SE backazimuth displays smaller transverse-component arrivals for the first 7 sec (Fig. 2). Note that there is a strong, coherent transverse arrival near 7 sec indicating deviations from laterally homogeneous, isotropic structure. The NW receiver function is also well determined and displays similar arrivals. We inverted these receiver functions. The final velocity model shows a gradational crust-mantle transition starting from 28 km and reaching upper-mantle shear-wave velocities at 34 to 36 kin. The large, negative trough seen near 1.7 sec in the NW receiver function requires a sharp velocity increase beneath the surface layer (Fig. 7). The receiver functions from station DNY are the lowest quality in our data set. Both the SE and NW receiver functions have large standard deviations and transverse-component arrivals. Large, secondary arrivals after the Moho Ps
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192
S. Ozalaybey, M. K. Savage, A. F. Sheehan, J. N. Louie, and J. N. Brune
arrival near 4.1 sec dominate both receiver functions and are probably associated with a large amount of scattering (Fig. 2). We have only inverted the NW receiver function because it is somewhat better than the SE one. The inversion of this receiver function was problematic because the arrivals around the Moho Ps phase and other late secondary arrivals required a model with alternating high- and low-velocity layers. We repeated the inversions with a high value of smoothness parameter (a = 0.3) until a satisfactory fit with a smooth model is obtained. A sharp increase in velocity from 28 to 30 km marks the crust-mantle boundary. An immediate LVZ is present beneath this boundary, which may be the result of scattered energy (Fig. 7).
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Eastern Stations At stations RTS, the Moho Ps phase arrives near 3.9 sec in the NW receiver function (Fig. 3) but about 0.5 sec later in the SE receiver function. This may indicate thicker crust to the SE. The NW receiver function has more events in the stack and smaller transverse-component arrivals. Therefore, we inverted the NW receiver function using a high value of smoothness parameter (a = 0.3). This caused a relatively low fit to the negative-polarity arrivals around the Moho Ps phase, which may be indicative of LVZs beneath and above the Moho and/or complex crustal scattering (Fig. 10). The Moho Ps phase and phase velocity data were fit well, but more data are needed to model the details of the receiver function. A sharp crust-mantle boundary is evident at a depth of 32 km for the NW direction at this station (Fig. 10). The GAR receiver functions from both backazimuth quadrants-display common arrivals for the first 6 sec (Fig. 3) and have been inverted jointly. The Moho Ps phase arrives late (near 5 sec), indicating a thick crust. The transversecomponent arrivals are extremely small, especially for the NW backazimuth. Both the phase velocity data (from path 2 RTS-WCP pair) and receiver functions were fit well (Fig. 11). A gradational crust-mantle transition with a crustal thickness around 38 kin is present in the velocity model (Fig. 11). The WCP receiver function from the SE backazimuth is dominated by large, transverse-component arrivals. The NW receiver function shows a strong and well-determined Moho Ps phase (Fig. 3). We inverted this receiver function grouped into two distance ranges. The velocity model from this inversion indicates a sharp velocity gradient at the top of the crust-mantle transition with a 32-kin-thick crust (Fig. 7).
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Sensitivity Analysis The joint inversion method eliminates many solutions that would otherwise be obtained from the inversion of receiver functions alone (Ammon et al., 1990). This is because the velocity-depth trade-off problem inherent in receiverfunction inversions is largely minimized by the additional surface-wave phase velocity constraints imposed during the inversions. The sensitivity analysis is aimed to show the possible range of velocities for a specific velocity feature in a
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Shear-Wave Velocity Structure in the Northern Basin and Range Province from the Combined Analysis of Receiver Functions given final velocity model due to the uncertainties in our data. We consider a maximum + 0.1 km/sec phase velocity measurement error and one standard deviation bounds of the receiver functions as allowable errors in our data fits. As mentioned earlier, the receiver functions resolve velocity discontinuities, and the surface waves resolve average velocities. Thus, we have a good control on average velocities and velocity contrasts. Our sensitivity analysis is performed in two steps; in the first step, we add positive- and negativevelocity perturbations (6fl) to the given velocity feature in question and keep the rest of the model the same. In the second step, we compute predicted phase velocity and receiver functions for these models and compare these predicted data with the real data. We repeat this process until the velocity perturbations are so large that we cannot accept the misfit between the predicted and observed data. This provides us with confidence bounds for each velocity feature. The details of the sensitivity analysis can be found in the work by Ozalaybey (1996). The confidence bounds are shown as shaded regions for each final velocity model in Figures 6 through 11. In these figures, a single, labeled region identified by regions of 1, 2, 3, or 4 between thin arrows can be positively or negatively perturbed within the confidence bounds without affecting the data fits. Based on the confidence bounds, the low-velocity layers less than 6 km thick can have maximum velocity perturbations of 6fl = _+0.2 km/sec. Stations KVN, MNA, MLC, and GAR show upper-crustal low-velocity layers. The middlecrustal and upper-mantle velocities can have perturbations up to cSfl = + 0.1 km/sec. We compute average crustal velocity (tic) and upper mantle (tim) using our Moho picks. From the confidence bounds, we obtain uncertainties in tic and tim as + 0.05 sec and + 0.1 km/sec, respectively. We perform a more detailed sensitivity analysis for the BMN velocity model because it has two distinct features that are of interest in our discussion. These features are the negative-velocity gradients between 10 and 24 km and 32 and 38 km (Fig. 9). The removal of these negative gradients (seen in regions 2, 3, and 4 in Fig. 9) by applying positivevelocity perturbations one at a time and keeping the rest of the model the same as before resulted in synthetic receiver functions that had considerable misfits to both observed bounding receiver functions and the surface-wave phase velocity data. In particular, the removal of each negative-velocity gradient caused a timing and amplitude mismatch to direct Ps arrivals from the l 8-kin discontinuity arriving near 2.5 sec and from the Moho near 3.8 sec, and the Moho multiple PpPms near 12 sec (Fig. 9). These mismatches were 0.05 to 0.1 sec early in timing and 20 to 40% in amplitude. The timing of the Moho multiple was early by nearly twice that of the direct Ps arrivals because this multiple traveled twice the distance through the model. The removal of the deeper low-velocity layer resulted in overprediction of the Moho Ps amplitude by --40% with almost no effect on the Moho multiple. The overprediction of amplitude occurs be-
193
cause the negative-velocity gradient layer in the mantle generates a negative polarity Ps arrival, which reduces the positive polarity arrival from the Moho. This also resulted in phase velocity values that exceeded our accepted error bounds. The estimated velocity uncertainty is ___0.1 km/sec for this feature. Discussion Our sensitivity analysis indicates that average velocities and crustal thicknesses are the best resolved parameters. Therefore, we choose to interpret these parameters together with compressional-wave structure, gravity, and heat flow data, to detect regional variations in the crustal structure. Figure 1 shows these parameters plotted on the Bouguer gravity anomaly map of the NBRP. Regional crustal thickness variations derived from the receiver function and surface-wave phase velocity data correlate well with the heat flow, gravity, and elevation data. The thinnest crust is found beneath stations BMN and DNY (28 to 30 kin) in the northwestern Basin and Range. This region is characterized by the highest heat flow (_->2.5 hfu, Battle Mountain high anomaly) (Lachenbruch and Sass, 1978), higher Bouguer gravity ( - - 170 mgal), lower elevations ( - 1 . 5 kin), and younger volcanism (< 17 Ma) than other regions. The thickest crust is found beneath stations MLC and GAR (38 kin) in the central and eastern part of the province. These stations lie within the central Nevada highland with elevations reaching --2.5 kin, a broad region of the lowest gravity values ( - - 220 mgal), and relatively older volcanism (17 to 34 Ma) (Blackwell, 1978). Station MLC is within the Eureka heat flow low (=>1.5 hfu) anomaly of Lachenbruch and Sass (1978). Other stations have a crustal thickness of 32 to 34 km and are located within transitional regions of elevations, heat flow, and gravity anomalies (Fig. 1). Velocities In general, average crustal and mantle velocities increase from west to east; stations located in the western part of the province (DNY, BMN, WHR, KVN, and MNA) with average tic = 3.49 km/sec and tim = 4.42 km/sec in contrast to the stations located in the central and eastern part of the province (MLC, GAR, RTS, and WCP) with average tic = 3.55 km/sec and tim = 4.58 km/sec. Our average shear velocities are in good agreement with the Great Basin model of Priestly and Brune (1978), which has an average crustal velocity of 3.54 kndsec and mantle lid shear velocity of 4.5 km/sec. They also agree with other shear velocity estimates that range from 4.44 and 4.62 km/sec (for a Poisson's ratio of 0.25) predicted from previously reported province-wide upper-mantle Pn velocities (7.7 to 8.0 km/sec) (e.g., Prodehl, 1979; Pakiser, 1989) and the average crustal shear velocities of 3.4 to 3.5 km/sec reported by Hawman et al. (1990) for northwestern Nevada. The northwestern Basin and Range reflection/refraction
194
S. C)zalaybey, M. K. Savage, A. F. Sheehan, J. N. Louie, and J. N. Brune
1986 Program for Array Seismic Studies of the Continental Lithosphere (PASSCAL) experiment (profiles shown as solid, white, straight lines in Fig. 1) provides crustal thickness estimates we can compare with our crustal thickness estimates in northwestern and central Nevada. The PASSCAL experiment determined that the crustal thickness varies laterally from 28 to 36 km in this region (e.g., Benz et aL, 1990; Holbrook, 1990; Catchings and Mooney, 1991). The crustal thickness between SP1 (i.e., shot point 1) and SP4 (Fig. 1) varies by + 2 km from the average thickness of 32 km (Catchings and Mooney, 1991; Holbrook, 1990). The crustal thickness of 34 km found beneath WHR and 30 km beneath DNY is in good agreement with the PASSCAL experiment result. Between SP4 and SP8 (Fig. 1), the PASSCAL experiment indicates a Moho with crust-mantle transition occurring at depths of 28 and 33 km (e.g., Benz et al., 1990; Holbrook, 1990; Catchings and Mooney, 1991). Hearn et al. (1991) estimated a depth of 29 km to the Moho from the station static of their tomographic study at BMN. Our velocity model at BMN, which is --40 km east of SP9, displays features that warrant a detailed comparison with the PASSCAL experiment velocity models. For this comparison, we converted the two-dimensional compressional velocity models of Holbrook (1990) and Catchings and Mooney (1991) from near SP9 into one-dimensional P-wave models. Figure 12 shows these models together with our S-wave model. The structural complexity found in the upper crust with compressional-wave velocities ranging from 2.5 to 6.0 km/sec (Catchings, 1992) between basins and ranges can account for the small differences present at shallow depths ( < 8 km) between the models. Between 8 and 28 km, the velocity discontinuities in the P-wave model of Catchings and Moohey (1991) shows nearly one-to-one correspondence to the velocity discontinuities in the S-wave model. Holbrook's (1990) model, which tried to produce the simplest possible velocity variations to fit the data, shows a lesser degree of correlation with our model in this range. We note that in the S-wave model, each sudden increase in velocity with depth is followed by a smooth, negative-velocity gradient (e.g., discontinuities at 8, 18, and 28 km). These gradients are not present in the P-wave models (Fig. 12). Below 28 kin, at the crust-mantle transition, both P-wave models have an uppermantle velocity of 7.9 to 8.0 km/sec with a sharp jump at 30 or 32 km, whereas the S-wave model displays a gradational LVZ between 32 and 38 kin. The S-wave velocity within the LVZ is 4.0 km/sec, while just above and below it is 4.3 km/ sec. Interestingly, the velocity model of Holbrook (1990) displays a P-wave LVZ between 38 and 42 km with a Pwave velocity of 7.5 _+ 0.2 km/sec (Fig. 12). This LVZ extends from SP4 to about 30 km north of SP9 (Fig. 1). Holbrook's (1990) LVZ (Fig. 12), although located deeper, was also modeled as a gradational boundary due to lack of upper-mantle reflections on vertical-incidence reflection data in this region (e.g., Holbrook, 1990; Klemperer et al., 1986). Holbrook (1990), however, considered the details
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of his LVZ as tentative because of the uncertainties in modeling LVZ's with the surface refraction method and the evidence for the LVZ from only SP8 records. Conversely, the LVZ in the S-wave model is a required feature with only a + 0.1 km/sec velocity uncertainty based on our sensitivity analysis. Thus, our S-wave model combined with Holbrook's (1990) interpretation provide evidence for the presence of an LVZ at these depths in this region. The LVZ that is present in the uppermost mantle in the S-wave model is partially coincident with the magmatically underplated layer of Catchings and Mooney (1991) and the LVZ of Holbrook (1990). Thus, our LVZ may represent evidence for the presence of a partial melt that could be considered the source material for magmatic underplating. Humphreys and Dueker (1994) also interpreted relatively low P-wave velocity upper mantle as hot and partially molten (1 to 3% partial melt) in this region. Jarchow (1991) identified a magma body referred to as the "Buena Vista Magma Body" at the base of the crust beneath Buena Vista Valley near SP9 (Fig. 1) from P-to-S converted reflections. According to his model, the Buena Vista Magma Body is small in areal extent ( < 1.8 km) and in thickness (
