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Fault slip rates, constancy of seismic strain release, and landscape evolution in the eastern California shear zone
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Fault slip rates, constancy of seismic strain release, and landscape evolution in the eastern California shear zone
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FAULT SLIP RATES, CONSTANCY OF SEISMIC STRAIN RELEASE, AND LANDSCAPE EVOLUTION IN THE EASTERN CALIFORNIA SHEAR ZONE by Kurt Lang Frankel A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (GEOLOGICAL SCIENCES) August 2007 Copyright 2007 Kurt Lang Frankel ii ACKNOWLEDGEMENTS Four years ago I found myself at another university, disenchanted with science, and pondering my future. At the time, I was certain I would not continue in academia. Fortunately, a short e-mail and a follow-up phone conversation with James Dolan changed that. Only a year earlier I had turned down James’ offer to do my Ph.D. with him, yet there he was, willing to offer me a second chance. Few people would have gone out of their way to do something so kind; this is a testament to his integrity and genuine concern for others. Still not entirely sure that I wanted to pursue an academic career, I decided to accept his gracious offer, and I am certainly glad I did. Once I arrived at USC, James fostered my intellect, allowed me to grow into an independent scientist, helped me make numerous contacts, and became a friend and mentor in the process. I cannot thank James enough for giving me another chance and convincing me to stay in academia, even it does mean that I will have to continue to “laugh” at his “jokes.” In addition to James, a number other of people contributed to this dissertation and deserve to be recognized. They are listed below in no particular order. My qualifying exam committee of James Dolan, Greg Davis, Charlie Sammis, Ann Blythe, and Bill Weber challenged me and provided me with sound advice as to how best move forward with my research. My dissertation committee of James Dolan, Greg Davis, and Theio Hogen-Esch found this dissertation acceptable and were willing to sign off on it. Tom Jordan, Tom Henyey, James Dolan, and Barbara Grubb made my time as a teaching assistant a pleasure. Bob Finkel and iii Lewis Owen generously opened their laboratories to me, were enthusiastic collaborators, and answered many questions about geochronology. Dylan Rood, Jason Dortsch, Özgür Kozaci, Sara Hall, and Caitlin Lippincott provided assistance in the lab. Thought-provoking discussions with Patrick Belmont, Bob Finkel, Lewis Owen, Mike Oskin, Frank Pazzaglia, Allen Glazner, James Dolan, Michael Sartori, Josh Roering, Ramon Arrowsmith, Bill Carter, Jeff Knott, Ken Hudnut, Jeremy Zechar, Jeff Hoeft, Bill Bull, Ionut Iordache, Chris Crosby, Alex Densmore, John Oldow, Doug Walker, and many others, along with insightful manuscript reviews by Robert Anderson, Kyle Nichols, Alex Densmore, Phillip Allen, Gilles Peltzer, Isabelle Manighetti, and Lucilla Benedetti helped shape my thoughts on geochronology, active tectonics, and landscape evolution. The crew at the National Center for Airborne Laser Mapping facilitated the collection of the amazing LiDAR digital topographic data that were a key part of my research. Permission to collect samples and access field sites within Death Valley National Park was granted by the Death Valley National Park Natural Resources Office. Stephanie Briggs, Patrick Belmont, Jeff Hoeft, Jeremy Zechar, Özgür Kozaci, Lorraine Leon, Cecil and Clementine Patrick, Scott Hetzler, Hilary Strong, and Lewis Owen assisted with field work, often being subjected to extreme heat, bone-chilling cold, and hurricane-like winds while digging soil pits, carrying heavy samples, and surveying faults for what probably seemed like an eternity. My officemates, Lorraine Leon and Plamen Ganev, provided me with a great deal of amusement and support during the long hours spent in Zumberge Hall. Jack and Meg White produced lots of great tunes that iv helped keep me going in the office, the lab, and pretty much everywhere else I went. Shelly Werner and Dana Coyle provided excellent conversations during our Tuesday and Thursday lunches in addition to their assistance with reimbursements, travel arrangements, and proposal submissions. John Yu kept the computational infrastructure running smoothly, which is no small feat. Cynthia Waite was always available to answer questions, make sure the correct forms were signed, and made sure I was on track to graduate. John McRaney found ways to make sure I could move forward with my research before my project was funded. More importantly, he was always willing to lend advice about writing proposals, doing good science, and pursuing a career in academia. John is an invaluable resource and I will certainly miss him. James Dolan, Allen Glazner, Frank Pazzaglia, Tom Jordan, Greg Davis, and Lewis Owen each took the time to write numerous letters of recommendation, which in no small way contributed to me getting job offers. The faculty of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology offered me the job that I ultimately accepted. A number of people provided me with great friendships. Peter and Catherine Powers made sure I continually daydreamed about the next big powder day at Mammoth. Erik Frost and Frances Cooper kept me from getting completely out of shape by never failing to show up for our Sunday morning bike rides. Jeremy Zechar kicked my ass in racquetball on a regular basis. In addition, he patiently sat through hours of questions about math and statistics. Most importantly, he made sure that I got out and had some fun from time to time and I feel fortunate to have v been able to share an incredible number of laughs with him. Patrick Belmont continually challenged me intellectually, eagerly traveled the world with me, provided many laughs, and a great deal of support. Frank Pazzaglia continued to push me scientifically, in addition to always lending advice as a friend and mentor. Five people deserve special mention. On August 20 th , 1997 I wandered down to the basement of Mitchell Hall at the University of North Carolina for Allen Glazner’s Geology 11 course, eager to get my lab science requirement out of the way. Because of Allen, that pesky science requirement turned into a career and he has been an inspiration since the day I set foot in his classroom. My parents, Charles and Joanne Frankel, never once questioned what must have seemed like the completely crazy ideas that (1) I decided I wanted to be a geologist, and (2) that I was willing to stay in school for six more years to do so. Their love, support, encouragement, and friendship never wavered and without it I am certain I could not have made it to this point. Bruce Sherman taught me the meaning of hard work, dedication, and focus. The lessons he instilled in me are invaluable qualities that I will carry with me the rest of my life. And last, but most certainly not least, Stephanie Briggs provided me with undying love, friendship, laughter, encouragement, and support. Her companionship and willingness to put up with me over the past four years is nothing short of remarkable. She was always there when I needed her, always doing her best to make sure I didn’t get too stressed out or work too much, and of course, always ready to give me a “wet willy.” I cannot imagine a vi better partner and I look forward with excitement as we start the next chapter of our lives together! Of course, none of the work presented in this dissertation would have been possible without the generous support of the National Science Foundation, NASA, Lawrence Livermore National Laboratory, the Southern California Earthquake Center, the Geological Society of America, White Mountain Research Station, Sigma Xi, the Colorado Scientific Society, the National Center for Airborne Laser Mapping, and the University of Southern California Department of Earth Sciences. Finally, this dissertation includes parts of the following manuscripts: Frankel, K.L., and Dolan, J.F., 2007, Characterizing arid-region alluvial fan surface roughness with airborne laser swath mapping digital topographic data: Journal of Geophysical Research - Earth Surface, v. 112, doi:10.1029/2006JF000644. Frankel, K.L., Brantley, K.S, Dolan, J.F., Finkel, R.C., Klinger, R., Knott, J., Machette, M., Owen, L.A., Phillips, F.M., Slate, J.L, and Wernicke, B.P., 2007, Cosmogenic 10 Be and 36 Cl geochronology of offset alluvial fans along the northern Death Valley fault zone: Implications for transient strain in the eastern California shear zone: Journal of Geophysical Research - Solid Earth, v. 112, doi:10.1029/2006JB004350. Frankel, K.L., Dolan, J.F., Finkel, R.C., Owen, L.A., and Hoeft, J.S., in review, Spatial variations in slip rate along the Death Valley-Fish Lake Valley zone determined from LiDAR digital topography and cosmogenic 10 Be geochronology: Geophysical Research Letters, doi:10.1029/2007GL030549. The co-authors listed above shared data, assisted with field work, and helped to supervise the published research results. vii TABLE OF CONTENTS Acknowledgements ii List of Tables x List of Figures xi Abstract xiii Chapter 1: Introduction 1 1.1 Introduction 1 1.2 The Death Valley-Fish Lake Valley fault zone 3 1.3 Airborne Laser Swath Mapping 4 1.4 Terrestrial Cosmogenic Nuclide Geochronology 7 1.5 Research Implications 9 Chapter 2: Characterizing Arid-Region Alluvial Fan Surface Roughness 11 with Airborne Laser Swath Mapping Digital Topographic Data Abstract 11 2.1 Introduction 12 2.2 Geologic Setting 15 2.3 Alluvial Fan Stratigraphic and Surface Characteristics 18 2.4 Airborne Laser Swath Mapping 28 2.5 Surface Roughness 29 2.5.1 Standard Deviation of Slope 30 2.5.1.1 Surface Roughness Results 32 2.5.2 Statistical Analysis 36 2.5.2.1 Kolmogorov-Smirnov Test Results 37 2.6 Discussion 41 2.6.1 Changes in Surface Roughness 41 2.6.1.1 Surface Roughness Controlled by Bar 41 and Swale Topography 2.6.1.2 Surface Roughness at Multiple Length 43 Scales 2.6.1.3 Clast Size Patterns 44 2.6.2 Implications for Arid-Region Landscape 45 Evolution 2.7 Conclusions 48 viii Chapter 3: Cosmogenic 10 Be and 36 Cl geochronology of offset 50 alluvial fans along the northern Death Valley fault zone: Implications for transient strain in the eastern California shear zone Abstract 50 3.1 Introduction 51 3.2 Active Tectonics of the Eastern California Shear Zone 54 3.2.1 Death Valley Fault System 57 3.3 Study Area 59 3.4 Airborne Laser Swath Mapping 64 3.4.1 Airborne Laser Swath Mapping Data Collection 64 3.4.2 Red Wall Canyon Alluvial Fan Offset 66 3.5 Terrestrial Cosmogenic Nuclide Geochronology 68 3.5.1 Beryllium-10 Surface Samples 69 3.5.2 Chlorine-36 Depth Profile Samples 73 3.6 Discussion 81 3.6.1 Terrestrial Cosmogenic Nuclide Geochronology 81 3.6.1.1 Beryllium-10 81 3.6.1.2 Chlorine-36 84 3.6.2 Comparison of 10 Be and 36 Cl Geochronology 86 3.6.3 Fault Slip Rates 88 3.7 Implications for Eastern California Shear Zone Kinematics 93 3.8 Conclusions 95 Chapter 4: Spatial Variations in Fault Slip Rate Along the Death 97 Valley-Fish Lake Valley Fault System from LiDAR topographic data and cosmogenic 10 Be geochronology Abstract 97 4.1 Introduction 97 4.2 Eastern California Shear Zone Kinematics 100 4.3 LiDAR and Fault Displacement 101 4.3.1 Furnace Creek Offset 101 4.3.2 Indian Creek Offset 105 4.4 Alluvial Fan Geochronology 107 4.4.1 Furnace Creek Fan Age 109 4.4.2 Indian Creek Fan Age 113 4.5 Fault Slip Rates 113 4.6 Implications for ECSZ Strain Distribution 114 ix Chapter 5: Conclusions 117 5.1 Summary 117 5.2 Arid-Region Alluvial Landform Evolution 117 5.3 Constancy of Seismic Strain Release 118 5.4 Spatial Variations in Slip Rate 119 References 121 Appendices 136 Appendix A: Surface Roughness Distribution Functions 137 Appendix B: ECSZ Fault Descriptions 138 Appendix C: TCN Geochronology Methods 144 Appendix D: Red Wall Canyon and Big Dip Canyon 36 Cl Data 148 Appendix E: CHLOE Model Description 152 Appendix F: Fault Slip Rate Error Propagation 157 Appendix G: ArcGIS/Info Recipes 159 Appendix H: Beryllium-10 Geochronology Data 169 x LIST OF TABLES Table 2.1: Northern Death Valley Alluvial Fan Characteristics 25 Table 2.2: Kolmogorov-Smirnov Test Results 38 Table 3.1: Channel Offset Measurements for Red Wall Canyon Alluvial Fan 67 Table 3.2: Analytical Results of 10 Be Geochronology for the Red Wall 71 Canyon and Big Dip Canyon Alluvial Fans Table 3.3: Analytical Results of 36 Cl Geochronology for the Red Wall 75 Canyon and Big Dip Canyon Alluvial Fans Table 3.4: 36 Cl Best-Estimate Depositional Age, Depth-Profile Erosion 78 Rate, Reduced-Sum-of- χ 2 , Assumed Erosion/Aggradation Rate Bounds, Equivalent Inheritence Age, and Source-Area Catchment-Wide Erosion Rate Table 3.5: Eastern California Shear Zone Fault Slip Rates 91 Table 4.1: Analytical Results of Terrestrial Cosmogenic Nuclide 10 Be 111 Geochronology for the Furnace Creek Alluvial Fan Table 4.2: Analytical Results of Terrestrial Cosmogenic Nuclide 10 Be 112 Geochronology for the Indian Creek Alluvial Fan xi LIST OF FIGURES Figure 1.1: Location of the Death Valley-Fish Lake Valley Fault System 2 Figure 1.2: Airborne Laser Swath Mapping Comparison 6 Figure 2.1: Location of Death Valley and Surrounding Areas 16 Figure 2.2: Hillshaded ALSM Relief Maps 17 Figure 2.3: Geologic and Surface Roughness Maps of Alluvial Fan 1 20 Figure 2.4: Geologic and Surface Roughness Maps of Alluvial Fan 2 21 Figure 2.5: Field Photographs of Alluvial Fans 23 Figure 2.6: Clast Size Box and Whisker Plot 26 Figure 2.7: Schematic Slope Calculation Diagram 31 Figure 2.8: Surface Roughness Box and Whisker Plot 34 Figure 2.9: Mean Surface Roughness versus Window Size 35 Figure 2.10: Surface Roughness Cumulative Frequency Distributions 39 Figure 2.11: Kolmogorov-Smirnov Test Results 40 Figure 2.12: Schematic Alluvial Landform Evolution Diagram 46 Figure 3.1: Index Map of the Eastern California Shear Zone 53 Figure 3.2: Fault Map of the Northern Eastern California Shear Zone 56 Figure 3.3: Field Photograph of Red Wall Canyon Alluvial Fan 60 Figure 3.4: Field Photograph of Big Dip Canyon Depth Profile Location 62 Figure 3.5: ALSM Image of the Northern Death Valley Fault Zone 63 Figure 3.6: ALSM Image of Red Wall Canyon Fan 65 Figure 3.7: Probability Density Functions of 10 Be Ages 83 xii Figure 3.8: Chlorine-36 Depth Profile Plots 85 Figure 4.1: Northern Eastern California Shear Zone Fault Map 99 Figure 4.2: Furnace Creek and Indian Creek Hillshade Maps 102 Figure 4.3: Furnace Creek Geologic, Topographic, and Aspect Maps 103 Figure 4.4: Furnace Creek Topographic Profiles 104 Figure 4.5: Indian Creek Geologic, Topographic, and Aspect Maps 106 Figure 4.6: Furnace Creek Sample Location Photograph 108 Figure 4.7: Beryllium-10 Probability Density Functions 110 xiii ABSTRACT The constancy of strain accumulation and release in time and space is one of the most fundamental issues in tectonics. Models of geodetic data suggest the Death Valley-Fish Lake Valley fault zone (DV-FLVFZ) is storing most of the Pacific- North American plate boundary strain in the northern eastern California shear zone (ECSZ). However, the scarcity of geochronologically constrained slip rates on the DV-FLVFZ has made it difficult to determine whether strain storage and release are constant in this region. I used airborne laser swath mapping (ALSM) digital topographic data to restore offset alluvial fans to their pre-faulting positions, combined with cosmogenic 10 Be and 36 Cl geochronology to determine slip rates along the DV-FLVFZ. Offset measurements combined with cosmogenic nuclide geochronology yields a slip rate of ~4.5 mm/yr for the DV-FLVFZ in northern Death Valley. Summing this rate with known rates on the major faults at similar latitudes suggests a late-Pleistocene geologic slip budget across the northern ECSZ of 8.5 to 10 mm/yr. This rate agrees with the geodetic rate and implies the strain transient in the southern ECSZ does not extend away from the structurally complex zone near the Big Bend of the San Andreas fault. Combining offset measurements for two alluvial fans in Fish Lake Valley with 10 Be ages yields late Pleistocene rates of ~2.5 mm/yr and ~3 mm/yr for the northern DV-FLVFZ. These rates are slower than those determined for the system in Death Valley, indicating rates decrease northward. These data suggest that at xiv ~37.5°N latitude, significant deformation must be accommodated on structures east of Fish Lake Valley, or strain accumulation and release rates have not remained constant through time. Furthermore, comparison of surface roughness values derived from the ALSM data shows that eight mapped alluvial fans are statistically unique at the 99% confidence level. The roughness metric indicates that fans become smoother from the active channel to a surface dated at 70 ka. Beyond 70 ky, alluvial landforms become rougher with age, suggesting that fans in arid regions smooth out with time until a threshold is crossed where roughness increases with age due to headward tributary incision. 1 CHAPTER 1: Introduction 1.1 Introduction The degree to which fault loading and strain release rates are constant, or non-constant, in time and space is one of the most fundamental, unresolved issues in modern tectonics. In order to understand how strain is distributed across plate boundaries slip rate data must be compared over a wide range of time scales, from very short-term (decadal) geodetic rates to longer-term (millennial to million-year) geologic data. Such data are critical to better understand the complex behavior of plate boundary fault systems. Modern analysis of the kinematics and rates of plate boundary deformation requires a multidisciplinary approach that encompasses detailed landform analysis provided by high- resolution digital topographic data combined with geochronologic constraints on the rates of tectonic and surficial processes. This dissertation comprises research that uses such an integrated approach to analyze the manner in which an important section of the Pacific-North America plate boundary stores and releases seismic strain. My research focused on mapping, retro-deforming, and determining the ages of offset landforms along the Death Valley-Fish Lake Valley fault zone (DV-FLVFZ) by combining terrestrial cosmogenic nuclide (TCN) geochronology with high-resolution airborne laser swath mapping (ALSM; also known as LiDAR) data in order to fill in one of the last major missing pieces of the slip rate “puzzle” in the northern eastern California shear zone (ECSZ; Figure 1.1). 2 Figure 1.1 Location map of the Death Valley-Fish Lake Valley fault system and surrounding areas. FLV - Fish Lake Valley; FLVFZ = Fish Lake Valley fault zone; WMFZ = White Mountains fault zone; DSV = Deep Springs Valley; EV = Eureka Valley; OVFZ = Owens Valley fault zone; SV = Saline Valley; NDVFZ = northern Death Valley fault zone; GM = Grapevine Mountains; SV-HMFZ = Saline Valley-Hunter Mountain fault zone; YM = Yucca Mountain; FM = Funeral Mountains; BM = Black Mountains; PM = Panamint Mountains; PV = Panamint Valley; AHF = Ash Hill fault. Blue brackets indicate the extent of airborne laser swath mapping (ALSM) data collected for this dissertation. Red boxes show other areas in Death Valley where ALSM have been collected. 3 The study was proposed to provide a synoptic view of the cumulative slip rates of the major faults of the ECSZ north of the Garlock fault over geodetic to geologic time scales. I felt that a comparison of these longer-term rate data with short-term geodetic data would allow me to determine whether strain storage and release have been constant over the Holocene to late Pleistocene time scales of interest, or whether the strain transient proposed for the Mojave section of the ECSZ [Peltzer et al., 2001; Oskin and Iriondo, 2004] extends away from the zone of structural complexity associated with the Big Bend of the San Andreas fault. In other words, I proposed to test whether such strain transients are a fundamental feature of Pacific-North America plate boundary deformation, or whether they are limited to structural anomalies tied to specific regions. 1.2 The Death Valley-Fish Lake Valley Fault Zone The DV-FLVFZ is thought to accommodate most of the relative Pacific- North America plate motion east of the San Andreas fault. Specifically, a number of space-based geodetic surveys [Savage et al., 1990; Bennett et al., 1997; Dixon et al., 2000; McClusky et al., 2001; Dixon et al., 2003] have shown that over the past ~15 years the DV-FLVFZ has been accommodating up 3 to 9 mm/yr of the proposed 9 to 12 mm/yr of Pacific-North America plate motion in the ECSZ and Walker Lane [Humphreys and Weldon, 1994; Dixon et al., 2000]. Although numerous geodetic 4 campaigns have addressed this issue, only a few field studies had attempted to measure long-term geologic slip rates [Brogan et al., 1991; Reheis and Sawyer, 1997; Klinger, 2001]. The DV-FLVFZ offsets numerous alluvial fan surfaces of different relative age by varying amounts, thereby providing an ideal opportunity to study the constancy of fault slip rates in time and space. The caveat associated with earlier field studies is that ages of alluvial deposits and offset geomorphic surfaces used to estimate fault slip rate were generally determined on the basis of soil development and alluvial fan morphology. In contrast, my research examined intermediate- to long-term slip rates on the DV-FLVFZ using quantitative TCN geochronology coupled with analysis of high-resolution ALSM digital topographic data, resulting in much more precise age control and displacement measurements on offset landforms. In addition, I combined ALSM data with TCN geochronology to quantitatively characterize the evolution of alluvial landforms through time. 1.3 Airborne Laser Swath Mapping Any successful study of tectonics and topography must begin with a detailed analysis of the landscape. A key component my work was the acquisition of ALSM data along nearly the entire length of the DV-FLVFZ (Figure 1.1). The ALSM data were collected by the National Center for Airborne Laser Mapping (NCALM) at the University of Florida. A 33 kHz Optec laser source was flown over the field area in a light plane, recording the first return, last return, and intensity of laser pulses. An 5 almost complete absence of vegetation in the study area resulted in an ideal situation for acquisition of ALSM data because removal of data points related to returns from the top of plants does not reduce the point density of bare-earth shots, as it might in a heavily-canopied project area [Sartori, 2005]. The raw data were fitted with a smooth surface to produce a high-resolution digital elevation model (DEM) with 5 to10 cm vertical accuracy and sub-meter horizontal resolution [Shrestha et al., 1999; Carter et al., 2001; 2003; Sartori, 2005]. The digital topographic data facilitated the efficient identification, mapping, and analysis of deformed landforms in unprecedented detail. ALSM data have several great advantages over previously available forms of remotely-sensed and digital topographic data (Figure 1.2). In particular, surveying of deformed geomorphic features (offset channels and alluvial fans) and the construction of high- precision topographic maps [e.g., Frankel et al., 2007; in review], which would take days to weeks with traditional methods, can be accomplished in minutes with ALSM data. Moreover, the high-resolution topographic data can be digitally manipulated to enhance and reveal subtle topographic features, something not possible with aerial photographs, satellite imagery, or lower-resolution DEMs. For example, the landscape can be artificially illuminated from any angle to highlight previously unrecognized features of the landscape. Surface slope and slope aspect maps [e.g., Frankel et al., in review] can also be easily constructed to reveal and retrodeform extremely subtle topographic features. 6 Figure 1.2 Comparison of airborne laser swath mapping (ALSM; also known as light detection and ranging, or LiDAR) digital topographic data with aerial photography and other more commonly available digital topographic data. Images are map views of Badwater, the lowest point in the western hemisphere, in Death Valley, California. A. Thirty-meter horizontal resolution NASA shuttle radar topography mission (SRTM) digital topographic data. B. Ten- meter horizontal resolution USGS national elevation data (NED) digital topography. C. Black and white 1:12,000 scale aerial photograph. D. One-meter horizontal resolution LiDAR image. Badwater LiDAR data courtesy of Thad Wasklewicz. 7 Moreover, the ALSM data are of sufficiently high resolution that details of the landscape that could not previously be evaluated can now be quantitatively characterized. The Death Valley region provided an ideal setting to study arid- region landscape evolution. Alluvial landscapes have long been described qualitatively [Gilbert, 1877; Davis, 1905; Blackwelder, 1931; Denny, 1967; Bull, 1977], however, I was able to use ALSM data to quantify the evolution of alluvial landforms through time by developing various algorithms to measure surface roughness characteristics [Frankel and Dolan, 2007]. Combining detailed landform analyses with age control from TCN geochronology provided unprecedented insight into the rates and patterns of fault activity and landscape evolution. 1.4 Terrestrial Cosmogenic Nuclide Geochronology The accumulation of cosmogenic isotopes, produced by the interaction of cosmic rays with minerals at earth’s surface, allows stable geomorphic surfaces to be dated directly [Gosse and Phillips, 2001; see also references therein]. This is particularly useful in regions that either lack appropriate organic material, or where the age of such surfaces and deposits is beyond that accessible with radiocarbon. My research used the nuclides 10 Be and 36 Cl, which are produced by the interactions of cosmic rays with minerals at earth’s surface, to determine the age of alluvial deposits. Typically, quartz is used as the target mineral for 10 Be while 36 Cl can be determined in carbonates and basalts. The basic assumption of this technique is that the sample of interest has been exposed at, or near, the earth’s surface since the time 8 of deposition and that the sample has not had a prior exposure history. The concentration of cosmogenic nuclides measured in a sample is then a function of the time the sample has been exposed to cosmic radiation and of the production rate of the nuclide of interest. As such, the higher the concentration of cosmogenic nuclides in a sample, the longer it has been exposed at earth’s surface. The lack of vegetation, arid to hyper-arid arid climate, and long-term stability of alluvial surfaces in the Death Valley region makes the area ideally suited for the use of terrestrial cosmogenic nuclides to date geomorphic features [Bierman et al., 1995; Gosse and Phillips, 2001]. I collected numerous TCN samples from offset alluvial fans along the DV-FLVFZ and processed and analyzed the samples at the Lawrence Livermore National Laboratory Center for Accelerator Mass Spectrometry. When combined with fault offsets measured from ALSM data, the TCN ages allowed me to determine intermediate- and long-term geologic slip rates for the DV-FLVFZ. These data were used for comparison with previously generated geodetic strain measurements [e.g., Bennett et al., 2003] and geologic rate estimates [e.g., Reheis and Sawyer, 1997] to gain a better understanding of constancy of elastic strain accumulation and release in time and space. Furthermore, by incorporating ALSM data and TCN geochronology I was able to determine the rate at which alluvial fan surfaces in arid regions smooth out with time. 9 1.5 Research Implications The following three chapters present research results previously published in international, peer-reviewed journals [Frankel and Dolan, 2007; Frankel et al., 2007; Frankel et al., in review]. Chapter 1 discusses the use of ALSM data to understand the evolution of alluvial fan surface roughness through time as well as the use of ALSM data to objectively differentiate and map individual alluvial deposits. Chapter 2 reports on the first geochronologically determined fault slip rate for the northern Death Valley fault zone and discusses the implications of late Pleistocene geologic slip rates in the northern eastern California shear zone for transient strain accumulation along the Pacific-North America plate boundary. An analysis of spatial variations in fault slip rates along the northern Death Valley and Fish Lake Valley fault zones is presented in Chapter 3 and the implications of along-strike changes in fault slip rates for understanding strain distribution in the eastern California shear zone and Walker Lane are discussed. By taking the novel approach of integrating TCN geochronology with ALSM digital topographic data I was able to investigate fault slip rates and patterns of landscape evolution in the northern ECSZ. In doing so, I determined spatial and temporal patterns in fault slip rates and alluvial landform evolution. The results of my research have implications for understanding lithospheric dynamics and fault zone kinematics, not only within the eastern California shear 10 zone, but for the Pacific-North America plate boundary and other fault systems, as well as the surficial processes responsible for shaping arid landscapes throughout the world. 11 CHAPTER 2: Characterizing Arid-Region Alluvial Fan Surface Roughness with Airborne Laser Swath Mapping Digital Topographic Data Abstract Range-front alluvial fan deposition in arid environments is episodic and results in multiple fan surfaces and ages. These distinct landforms are often defined by descriptions of their surface morphology, desert varnish accumulation, clast rubification, desert pavement formation, soil development, and stratigraphy. Although quantifying surface roughness differences between alluvial fan units has proven to be difficult in the past, high-resolution airborne laser swath mapping (ALSM) digital topographic data are now providing researchers with an opportunity to study topography in unprecedented detail. Here, we use ALSM data to calculate surface roughness on two alluvial fans in northern Death Valley, California. We define surface roughness as the standard deviation of slope in a five-meter by five- meter moving window. Comparison of surface roughness values between mapped fan surfaces shows that each unit is statistically unique at the 99% confidence level. Furthermore, there is an obvious smoothing trend from the presently active channel to a deposit with cosmogenic 10 Be and 36 Cl surface exposure age of ~70 ka. Beyond 70 ky, alluvial landforms become progressively rougher with age. These data suggest that alluvial fans in arid regions smooth out with time until a threshold is crossed where roughness increases at greater wavelength with age as a result of surface runoff and headward tributary incision into the oldest surfaces. 12 2.1 Introduction Alluvial fans are common features along the piedmonts of steep mountain fronts where streams exit the narrow confines of their source canyons, resulting in a reduction in stream power and a consequent decrease in the ability of the streams to carry large sediment loads [Bull, 1977]. In arid environments, this range-front deposition tends to be episodic, can be punctuated by erosion, and is commonly expressed as multiple generations of alluvial fan surfaces [Bull, 1991]. Alluvial fans are important recorders of both climatic and tectonic signals; alluvium of varying age can contain vast amounts of information about climatic influences on deposition, or lack thereof, as well as rates and styles of tectonism and as such, have been studied extensively [Gilbert, 1877; Davis, 1905; Blackwelder, 1931; Denny, 1967; Bull, 1977; Wallace, 1977; Bull, 1984; Wells et al., 1987; Lubetkin and Clark, 1988; Bull, 1991; Whipple and Dunne, 1992; Ritter et al., 1993; Bierman et al, 1995; Matmon et al., 2005; Nichols et al., 2006; Bull, 2007]. Discrete alluvial units are often defined by descriptions of surface morphology, desert varnish accumulation, clast rubification, desert pavement formation, soil development, and stratigraphic relationships [Wells et al., 1987; Bull, 1991; Ritter et al., 1993]. In particular, studies of soil development on desert piedmonts have been especially useful in deciphering ages of alluvial landforms and rates of fan deposition [Birkeland, 1999]. Recent advances in Quaternary geochronology are allowing researchers to further quantify rates of arid-region 13 geomorphic processes [e.g., Nichols et al., 2002; Nichols et al., 2005; Nichols et al., 2006; Matmon et al., 2006]. In general, alluvial fan units are mapped on aerial photographs and topographic maps using the above criteria, in conjunction with elevation above active channels, in order to determine lithostratigraphic divisions. Quantifying the topographic characteristics and differences between multiple fan surfaces, however, has been difficult with previously available maps and remotely-sensed data because they generally lack the spatial resolution necessary to make a quantitative comparison between individual alluvial fan deposits [e.g., Farr and Chadwick, 1996]. Field techniques, such as clast-size counts or topographic surveying, while useful, are labor-intensive and usually limited in their spatial extent, therefore providing data on only a small segment of any single alluvial unit. Recently, however, the emergence of high-resolution airborne laser swath mapping (ALSM; also known as light detection and ranging or LiDAR) technology has renewed interest in the quantitative characterization of alluvial and colluvial landforms [McKean and Roering, 2004; Glenn et al., 2006; Staley et al., 2006]. ALSM digital topographic data are now providing researchers with the opportunity to study landforms in unprecedented detail [Carter et al., 2001; 2003]. The high resolution of ALSM digital topographic data, generally on the order of 0.5 to 3 m in the horizontal and 10 to 20 cm vertically, allows the construction of very accurate digital elevation models, from which a number of surface characteristics can be readily extracted [Krabill et al., 1995; Shrestha et al., 1999; Carter et al., 2003; 14 Haugerud et al., 2003]. Of particular interest to differentiating and quantifying alluvial landform development is surface roughness, which is often one of the most obvious features distinguishing fans of different age, yet has traditionally been one of the hardest metrics to quantify. Previous studies using ALSM digital elevation data to differentiate, characterize, and map landslide morphology have shown that surface roughness may be evaluated in a variety of ways [McKean and Roering, 2004; Glenn et al., 2006]. McKean and Roering [2004] analyzed ALSM data to objectively map the spatial and temporal characteristics of a landslide in New Zealand based on topographic roughness determined by eigenvector ratios. In a similar study, based on various measures of topographic roughness, Glenn et al. [2006] used surface roughness, slope, semivariance, and fractal dimension to characterize and differentiate landslide morphology and activity. In addition, Staley et al. [2006] used ALSM data to investigate depositional patterns on small debris flow fans in central Death Valley through the analysis of profile curvature and fan gradient. Here, we use the classic methods of topographic variability, degree of varnish accumulation, soil development, and clast size counts, combined with a quantitative measure of surface roughness calculated as the standard deviation of slope from ALSM data, to characterize and differentiate alluvial fan surfaces with different relative ages. Our calculation of surface roughness differs from previous studies in that it allows us to investigate topographic patterns at scales of individual bars and swales to entire alluvial fan systems. Specifically, this study is focused on two 15 alluvial fan complexes in northern Death Valley, along the western Grapevine Mountains piedmont (Figures 2.1 and 2.2). We show that fan units of different relative age can be successfully delimited through statistically unique surface roughness values extracted from high-resolution ALSM data and propose a model for the evolution of alluvial surfaces through time on the basis of the surface roughness calculations. Furthermore, our results suggest that ALSM data can be used to efficiently and objectively map alluvial landforms. 2.2 Geologic Setting Death Valley is located along the western edge of the Great Basin, at the transition between the extensional Basin and Range Province and the strike-slip faults comprising the eastern California shear zone. Death Valley is a pull-apart basin formed by a step-over between the right-lateral southern Death Valley and northern Death Valley fault zones. Displacement along a down-to-the-west normal fault forms the deep, central basin between the two strike-slip fault systems [Burchfiel and Stewart, 1966]. Opening of the basin as a result of continued tectonic activity since at least the Miocene has produced the accommodation space necessary for continuous deposition of alluvial deposits [Hamilton, 1988; Wernicke et al., 1988; Burchfiel et al., 1995]. Rates of tectonic activity range from 1 to 3 mm/yr along the normal fault in central Death Valley to ~4.5 mm/yr on the northern Death Valley fault zone [Brogan et al., 1991; Klinger, 2001; Knott et al., 2002; Frankel et al., 2007]. 16 Figure 2.1 Location map of the study sites and surrounding areas. Circled numbers represent the locations of the two alluvial fans in northern Death Valley used in this study. Location 1 refers to the fan in Figures 2.2A and 2.3. Location 2 refers to the fan in Figures 2.2B and 2.4. DSV = Deep Springs Valley, EV = Eureka Valley, LCR = Last Chance Range, GM = Grapevine Mountains, CM = Cottonwood Mountains, SV = Saline Valley, FM = Funeral Mountains, and BM = Black Mountains, YM = Yucca Mountain. 17 Figure 2.2 Hillshaded relief maps derived from airborne laser swath mapping data of the two alluvial fans in northern Death Valley analyzed in this study. Images were produced by gridding the airborne laser swath mapping data at 1 m and fitting a surface through a kriging routine. A. Alluvial fan at location 1 in Figure 2.1. B. Alluvial fan at location 2 in Figure 2.1. 18 Climate in the region during late-Pleistocene and Holocene time has been dominated by two wet, cold periods and two warm, dry intervals [Li et al., 1996; Lowenstein et al., 1999]. Perennial lakes existed in the central basin during the penultimate glacial advance from ~128 to 186 ka (oxygen isotope stage 6) and the last glacial maximum from ~12 to 35 ka (oxygen isotope stage 2) when the climate was cooler and wetter [Lowenstein et al., 1999]. From 60 to 120 ka, climate is thought to have been similar to the aridity characterizing the Holocene environment [Lowenstein et al., 1999]. The period from 35 to 60 ka was a time of unstable climate and hence, fluctuating lake levels. The present-day arid climate results from the large rain shadow produced by the Sierra Nevada, Inyo Mountains, and Panamint Mountains (Figure 2.1) [Poage and Chamberlin, 2002]. With elevations up to ~4400 m, these three ranges inhibit the eastward migration of moist air masses coming from the Pacific Ocean. As a result, modern-day precipitation in central Death Valley is a sparse ~6 cm/yr [Western Region Climate Center - http://www.wrcc.dri.edu]. 2.3 Alluvial Fan Stratigraphy and Surface Characteristics Alluvial fans are pervasive piedmont features at the base of the major mountain ranges bounding Death Valley to the east and west (Figures 2.1 and 2.2). Relatively small, steep alluvial fans deposited mainly in debris flow events are found at the base of the Black Mountains, where they are commonly offset by the range- bounding normal fault [Denny, 1965; Brogan et al., 1991; Burchfiel et al., 1995; Staley et al., 2006]. Throughout much of the rest of the Death Valley basin, such as 19 along the eastern Panamint and western Funeral and Grapevine Mountains piedmonts (Figures 2.1 and 2.2), alluvial fans are spatially more extensive, forming continuous bajada-like surfaces. Alluvial fans in these locations are generally thought to be deposited through a combination of sheet-wash and debris flow events [Denny, 1965; Hunt and Mabey, 1966; Bull, 1977; Blair, 2000]. Previous work, both in Death Valley and throughout southwestern North America, has defined a consistent alluvial fan stratigraphy for the region [Denny, 1965; Hunt and Mabey, 1966; Moring, 1986; Bull, 1991; Klinger, 2001]. The alluvial fans in our two study areas comprise eight distinct lithostratigraphic units - Q4b, Q4a, Q3c, Q3b, Q3a, Q2c, Q2b, and Q2a (Figures 2.3 and 2.4). Unit Q4b represents active alluvial channels and occupies the lowest topographic position in the landscape. Unit Q2a is the oldest alluvial landform in the study area and thus stands topographically higher than the other units (Figures 2.3 and 2.4). Each of these units is described briefly below. More detailed descriptions of the alluvial fan stratigraphy can be found in the works of Bull [1991] and Klinger [2001; 2002]. In addition, we measured clast sizes at one-meter increments for 50 meters on each surface in the mid-section of the fans to further characterize the units based on field observations. Table 2.1 provides a synopsis of the characteristics of each of the mapped surfaces in the study area. 20 Figure 2.3 Geologic and surface roughness maps of the alluvial fan at location 1 in Figure 2.1. A. Surficial geologic map of the alluvial fan. Arrows delineate the trace of the dextral-slip northern Death Valley fault zone [Frankel et al., 2007]. Faults left off map for clarity. See text and Table 2.1 for detailed descriptions of map units. Modified from Klinger [2001]. B. Surface roughness map of the alluvial fan in A. Roughness values were calculated as the standard deviation of slope over a 5 m 2 area. Note the similarity with the geologic map in A. Scale bar represents values of the standard deviation of slope, which is the metric used in this study to measure surface roughness. 21 Figure 2.4 Geologic and surface roughness maps of the alluvial fan at location 2 in Figure 2.1. A. Surficial geologic map of the alluvial fan. Arrows delineate the trace of the dextral northern Death Valley fault zone. Faults left off map for clarity. See text and Table 2.1 for detailed descriptions of map units. B. Surface roughness map of the alluvial fan in A. Note the similarity with the geologic map in A. Roughness values were calculated as the standard deviation of slope over a 5 m 2 area. Scale bar represent values of the standard deviation of slope, which is the metric used in this study to measure surface roughness. 22 Q4b – This is the youngest surface mapped in the study area (Figure 2.3A) and is defined as the active alluvial fan channels. The alluvium in this deposit is generally distributed bimodally, with bars of coarse cobbles and boulders, and swales (channels) consisting of finer-grained pebbles and sand (Figures 2.5A and 2.6). No desert varnish, soil, or desert pavement are developed on this surface. Relief on this surface ranges from 0.5 to 1.5 m. Q4a – The Q4a surface (Figure 2.3A) is characterized by prominent bar and swale topography similar to that of unit Q4b, with clasts ranging from pebble to boulder in size (Figures 2.5B and 2.6). Little to no varnish or rubification is developed on clasts. Locally, immature patches of pavement are observed in small, ~4 to 6 m 2 areas. The Q4a surface commonly has a thin (up to 5-cm-thick), Av soil horizon. This unit is the most recently abandoned surface found on the alluvial fans and is generally 0.5 to 1 m above the active channels. Q3c – A distinct bar-and-swale topography is still present on the Q3c surface with 0.5 to 1.0 m of relief (Figure 2.3A), however, an immature pavement, composed mainly of finer-grained clasts has started to form (Figure 2.5C). In addition, clasts, which range in size from pebbles to boulders (Figure 2.6), have a light coating of varnish and are slightly rubified. A weakly developed soil is present beneath the surface and is defined by a ≤5-cm-thick Av horizon, and a ~15-cm-thick B horizon with minor salt (Stage I), carbonate, and clay-film accumulations. 23 Figure 2.5 Photographs showing examples of the eight alluvial fan units mapped in northern Death Valley. A. Unit Q4b. B. Unit Q4a. C. Unit Q3c. D. Unit Q3b. E. Unit Q3a. F. Unit Q2c. G. Unit Q2b. H. Unit Q2a. Note the progression from the prominent bar and swale topography of the youngest units in A, B, and C to the planar intermediate-age surface in F and the more rounded surfaces in G and H. See Table 2.1 and text for more detailed descriptions of each unit. 24 Q3b – The Q3b surface (Figure 2.3A) is characterized by an intermediate desert pavement and a bar-and-swale morphology with moderate relief of 0.25 to 0.75 m (Figure 2.5D). Clasts, which range in size from pebbles to large cobbles/small boulders (Figure 2.6), are moderately varnished and rubified. Soils are characterized by a ≥10-cm-thick Av horizon, a ~30-cm-thick B horizon with small amounts of salt and carbonate accumulations (Stage I+) and moderate clay film development. In addition, weak soil development, ~10 cm thick, has altered the C horizon. Q3a – The bar-and-swale topography on the Q3a surface (Figure 2.3A) is subdued (0.1 to 0.5 m of relief), yet still observable, with clasts ranging from pebbles to cobbles in size (Figure 2.5E and 2.6). The surface is characterized by a well- packed pavement and clasts that are moderately to heavily varnished and rubified. A moderately well-developed soil is found beneath the surface and is distinguished by a 10- to 20-cm-thick Av horizon, a 40- to 50-cm-thick B horizon with Stage II salt and carbonate accumulations, and a weakly developed C horizon. Q2c – Clasts on the Q2c surface (Figure 2.3A) range from cobbles to small boulders in size (Figure 2.6). The clasts are tightly packed and form a mature desert pavement. The morphology of the Q2c unit is characterized by highly subdued to non-existent bar-and-swale morphology (Figure 2.5F). Tops of clasts are heavily varnished and clast undersides are highly rubified. Beneath the Q2c surface a 50+ cm-thick soil is developed. The soil is characterized by a 10- to 20-cm-thick Av 25 Table 2.1 Northern Death Valley Alluvial Fan Characteristics a Clast size distributions were determined from a count of 50 clasts at one clast/meter for a 50 meter segment of each surface in the mid- section of the alluvial fan. Bar and swale structure Clast size distribution a , cm Surface roughness, σ m Unit Desert pavement development morphology relief, m min. max. mean min. max. mean Number of roughness measurements extracted Q4b none prominent 0.5 to 1.5 2 85 16 0.41 15.28 3.55 14129 Q4a none/immature prominent 0.5 to 1.25 2 65 17 0.35 7.78 1.89 5525 Q3c immature/moderate well-defined 0.5 to 1.0 1 78 15 0.33 10.77 1.94 9813 Q3b moderate subdued 0.25 to 0.75 2 52 9 0.29 6.5 1.59 10054 Q3a mature subdued 0.1 to 0.5 2 12 5 0.12 3.51 1.02 6012 Q2c mature none 0 2 20 7 0.16 5.16 0.71 12747 Q2b moderate/mature none/subdued 0 to 0.25 2 13 7 0.20 3.15 0.97 7264 Q2a moderate/mature none/subdued 0 to 0.25 4 55 9 0.21 3.73 1.08 7350 26 Figure 2.6 Box and whisker plot of clast sizes from each alluvial fan unit in the study area. Clast counts were conducted by measuring the clast size at one-meter increments for 50 meters on each surface in the mid-section of the fan. A total of 50 clasts were measured on each surface. Horizontal bar in the center of the box represents the mean clast size. The limits of each box are the 25 th and 75 th percentiles. Whiskers (bars extending from the boxes) define the 10 th and 90 th percentiles and the black dots represent the 5 th and 95 th percentiles for clast sizes in each unit. 27 horizon with clay film accumulation in its lower half; a middle Bt horizon with carbonate and salt development; and lower Bk horizon with moderate carbonate accumulation (Stage III). The Q2c surface in our study area is ~70 ka, based on 10 Be and 36 Cl cosmogenic nuclide surface exposure geochronology [Frankel et al., 2007]. Q2b – The Q2b unit (Figure 2.4A) is characterized by smooth pavements that are moderately dissected, forming rounded hillslopes. The surface of the Q2b unit generally has a subdued bar-and-swale morphology with 0 to 0.25 m of local relief (Figure 2.5G). Clasts range in size from pebbles to small boulders and are packed together in a moderately- to well-developed pavement (Figure 2.6). Varnish development is generally moderate to high and clasts are highly rubified. A mature soil is developed beneath the Q2b surface and is characterized by a 10- to 20-cm thick Av horizon, a 20- to 60-cm-thick Bt horizon, and a 50- to 100-cm thick Bk horizon with Stage III carbonate development. Q2a – This unit is the oldest surface analyzed in our study (Figure 2.4A). The Q2a surface is generally composed of the incised remains of pavements forming convex hillslopes (Figure 2.5H). Clasts range in size from pebbles to boulders and are generally moderately varnished and moderately to heavily rubified (Figure 2.6). Soil formed beneath the surface is characterized by a 10- to 20-cm thick Av horizon, a Bt horizon up to 100 cm thick, and a 100- to 200-cm-thick Bk horizon with Stage IV carbonate development. Where bar and swale topography is present on this surface it is generally subdued, having relief on the order of 0 to 0.25 m. 28 Each of these units is identifiable and mappable from both field observations and high-resolution ALSM digital topographic data. In addition, individual units possess a distinct topographic signature, which can be readily extracted from ALSM data to quantify the dominant geomorphic characteristics of these deposits. 2.4 Airborne Laser Swath Mapping Airborne laser swath mapping (ALSM) digital topographic data have several advantages over more common forms of “static” remote sensing technology such as aerial photographs or satellite imagery. ALSM data can be manipulated in a geographic information system to extract features from the landscape such as elevation, slope, aspect, and curvature, among others. Moreover, detailed surveying of landforms, which takes days to weeks with traditional methods, can be accomplished in a matter of hours with ALSM data. The ALSM data used in this study were acquired by the National Center for Airborne Laser Mapping at the University of Florida [Carter et al., 2001] using a Cessna 337 twin-engine aircraft equipped with a Optech Model ALTM 1233 laser mapping system. The 33 kHz laser source was flown over the southern part of the study area (location 1 in Figure 2.1) at an elevation of 600 m above ground level and at an elevation of 820 m above ground level over the northern study site (location 2 in Figure 2.1) at an average speed of 60 m/s. The difference in elevation between the two study sites is a function of the amount of topographic relief along the range-front in each region and does not affect the final resolution of the data. First and last 29 returns, as well as the intensity of each laser pulse, were recorded. The sparse vegetation in the study area is ideal for ALSM data acquisition because the removal of data points related to laser returns from the tops of flora does not reduce the point density of bare-earth shots, as it might in a heavily-canopied region. Individual bare- earth data points were aligned in an equally-spaced grid at one meter intervals and fit with a smooth surface through a kriging algorithm using Surfer software. This produced a digital elevation model from the rasterized grid with one meter horizontal resolution and 5 to 10 cm vertical accuracy [e.g., Krabill et al., 1995; Burroughs and McDonnell, 1998; Shrestha et al., 1999; Carter et al., 2001, 2003; Sartori, 2005; Chaplot et al., 2006]. The grid was then imported into ArcInfo, which was used for all topographic analyses. 2.5 Surface Roughness Surface morphology is one of the most widely used criteria to distinguish alluvial fans of different ages [e.g., Wells et al., 1987; Bull, 1991; Ritter et al., 1993]. Previous studies suggest that the relative age of alluvial deposits is manifested by topographic variability, with fan surfaces tending to become smoother with increasing age [Bull, 1977; 1991; Matmon et al., 2006]. We exploit the high resolution of ALSM-derived digital elevation models to quantify changes in alluvial fan surface roughness through time. Although there are many ways in which to measure the texture of alluvial and colluvial material [e.g., McKean and Roering, 2004; Glenn et al., 2006], we define surface roughness as the standard deviation of 30 slope. We choose to calculate the roughness metric in this way because it allows us to average out surface features over a five-meter by five-meter area, thereby eliminating any anomalies related to individual boulders or the occasional large creosote bush. Furthermore, taking this approach to calculating surface roughness accounts more readily for the wavelengths (~5 to 10 m) of bar and swale morphology that are commonly observed in arid alluvial environments. 2.5.1 Standard Deviation of Slope The standard deviation of slope was calculated by first deriving a slope map from the one-meter-resolution, ALSM-derived digital elevation model. Slope, m, is defined for the central cell in a three-meter by three-meter (three cell by three cell; cell i, j in Figure 2.7) moving window as, 2 2 1 tan ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ∂ ∂ + ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ ∂ ∂ = − y z x z m (2.1), where, ( ) ( ) [ ] x z z z z z z x z j i j i j i j i j i j i ∂ + + − + + = ∂ ∂ − − − + − − + + + + 8 2 2 1 , 1 , 1 1 , 1 1 , 1 , 1 1 , 1 (2.2), and, ( ) ( ) [ ] y z z z z z z y z j i j i j i j i j i j i ∂ + + − + + = ∂ ∂ − − − − + + − + + + 8 2 2 1 , 1 1 , 1 , 1 1 , 1 1 , 1 , 1 (2.3). ∂z/ ∂y is the maximum slope in the north-south direction, ∂z/ ∂x is the maximum slope in the east-west direction, z is the elevation at a cell location specified by the subscripts relating to the schematic diagram in Figure 2.7, and ∂x and ∂y are the east- west and north-south cell dimension [Horn, 1981; Burroughs and McDonell, 1998]. 31 Figure 2.7 Schematic diagram of a three-meter by three-meter window in which slope and standard deviation of slope values are determined. Each cell is one-meter by one-meter in size. Slopes for the three-meter by three- meter window are calculated for the central cell (i, j) in the moving window. Slopes are calculated as the maximum difference between cells in the east-west and north-south directions. See text and Equations 2.1, 2.2, and 2.3 for details. The standard deviation of slopes ( σ m ) is taken as the standard deviation of all nine cells in the window and is reported in the center cell (i, j) of each window. See text and Equation 2.4 for details. 32 In our example, the north-south and east-west cell dimensions are everywhere one meter. The standard deviations of slope values are then calculated in a moving window over the slope map, where the standard deviation values are reported in the central cell (cell i, j in Figure 2.7). We define standard deviation as, () n m m n i i m ∑ = − = 1 2 σ (2.4), where σ m is the standard deviation of slope or surface roughness, n is the number of samples in the population, which in our analysis ranges from nine samples for a three cell by three cell area to 40,000 samples for a 200 cell by 200 cell region, m i is the value of one specific sample within the sampling area, and m is the population mean [Taylor, 1997]. Because slope values are determined across a three-meter by three- meter window and σ m values are computed from a subsequent filter of the slope map, surface roughness is averaged over areas ranging from a 5 m 2 area for a three cell by three cell moving window to a 202 m 2 area for a 200 cell by 200 cell window. 2.5.1.1 Surface Roughness Results Approximately 73,000 individual σ m values were extracted from the eight mapped fan units in the study area for each standard deviation window size (Table 2.1). Points were collected from the center of representative portions of each surface to avoid anomalously high surface roughness values associated with parts of the landscape such as the steep channel walls incised through the fans (Figures 2.3 and 2.4). These data illustrate the distinct character of each surface and reveal a trend of 33 decreasing roughness with increasing age when roughness is analyzed over a 5 m 2 area (Figure 2.8). On the oldest surfaces, this pattern is reversed, with surface roughness and age becoming positively correlated on the oldest fan deposits in the study area (Figure 2.8). In addition, younger surfaces exhibit a higher variance in surface roughness values, which progressively decreases with increasing age (Figure 2.8). When compared with previously mapped alluvial fan units in northern Death Valley (Figures 2.3A and 2.3B), maps of σ m values across the study area clearly illustrate the utility of this metric in characterizing and defining individual lithostratigraphic units (Figures 2.3B and 2.4B). Most prominent among these is the Q2c surface, which is the smoothest and most stable alluvial landform in the region (Figure 2.3B). Other alluvial units, although not as well defined, are still clearly distinguishable when compared with geologic observations (Figures 2.3 and 2.4). Calculation of surface roughness at multiple length scales (i.e., by determining σ m in moving windows of different size) also brings out a number of interesting patterns in the landscape (Figure 2.9). When mean surface roughness is plotted against the size of the moving window over which those values are determined, each surface is characterized by an initial increase in surface roughness with increased window size (Figure 2.9). Eventually each unit reaches a point where roughness no longer increases as a function of window size (e.g., “interface width” of Barabasi and Stanley [1995]) and roughness values eventually converge at the longest length scales (Figure 2.9A). In general, individual surfaces have distinct 34 Figure 2.8 Box and whisker plot of surface roughness averaged over a 5 m 2 for each alluvial fan unit in the study area. The horizontal bar inside each box is the mean. Box limits represent the 25 th and 75 th percentiles. Whiskers (bars extending from the top and bottom of each box) are the 10 th and 90 th percentiles and the black dots represent the 5 th and 95 th percentiles. Note the pattern of surfaces smoothing out with age and then starting to become rougher again as age increases further. The age of the Q2c surface is from 10 Be and 36 Cl cosmogenic nuclide surface exposure geochronology [Frankel et al., 2007]. 35 Figure 2.9 Plots showing mean surface roughness versus window size used to calculate the standard deviation of slope values. A. Mean surface roughness versus size of moving window for the Q4b, Q4a, Q3c, Q3b, Q3a, and Q2c surfaces. Window size ranges from five-meters by five-meters to 102-meters by 102-meters. B. Plots of mean surface roughness versus window size for the Q2a and Q2b surfaces. Window sizes range from five- meters by five-meters to 202-meters by 202-meters. Dominant surface roughness wavelengths are represented by the steepest parts of the curves. Roughness on the youngest surfaces is characterized at wavelengths of bar and swale topography (A). Older surfaces have topographic signatures that are defined by the longer wavelengths of convex hillslopes incised by tributary channels. See text for further discussion. 36 saturation lengths, with an increase in length scale corresponding to an increase in surface age (Figure 2.9). 2.5.2 Statistical Analysis Although the values of surface roughness on each of the eight alluvial fan units appear to be derived from unique populations (Figure 2.8), we quantitatively test this supposition using a Kolmogorov-Smirnov test. The Kolmogorov-Smirnov test was chosen because it does not make any assumptions regarding the distribution of sample populations, allows populations of different size to be directly compared to one another, and is most effective when applied to large (n ≥ 40) data sets [Borradaile, 2003]. The test relies on the maximum difference between the cumulative frequency distributions of two sample populations (Figure 2.10 and Appendix A), ( ) ) ( 2 ) ( 1 max x F x F D − = (2.5), where D is the Kolmogorov-Smirnov test statistic (D-statistic), and F1(x) and F2(x) are the cumulative frequency distributions of two sample populations [Davis, 2002]. D is compared against a critical value, D α , for a given level of significance defined as, N f D α α = (2.6), where, 2 1 2 1 n n n n N + = (2.7), 37 and f α is a coefficient specific to the confidence level for the critical value of D α . The f α coefficient is equal to 1.36 for the 95% confidence level and 1.63 for the 99% confidence level. n 1 and n 2 are simply the number of samples in the cumulative distribution functions, F1(x) and F2(x) [Chakravarti et al., 1967; Borradaile, 2003]. 2.5.2.1 Kolmogorov-Smirnov Test Results Kolmogorov-Smirnov analyses ultimately test for the existence of a null hypothesis. Here the null hypothesis is that surface-roughness values for each mapped alluvial fan unit (Figures 2.3 and 2.4) are derived from the same sample population. Each mapped alluvial fan surface was compared to the two surfaces adjacent to it in terms of relative age (Table 2.2). For example, unit Q3b was compared to both Q3c and Q3a, its younger and older neighbors, respectively. In addition, units that appeared to have similar σ m distributions, yet were not adjacent to one another in terms of relative age, such as units Q2b and Q3a, were also compared. Figures 2.10 and 2.11 show the relationship between fan units based on the Kolmogorov-Smirnov D-statistic and normalized for the size of each population (Table 2.1). Comparison of each mapped unit on the basis of the surface roughness calculations averaged over a 5 m 2 area clearly illustrates that the alluvial fan units defined in northern Death Valley are derived from populations that are statistically unique at the 99% confidence interval (Table 2.2; Figure 2.11). We can therefore 38 Table 2.2 Kolmogorov-Smirnov Test Results a Represents a confidence level of 99% (1 - α). b The P-value is the probability that the null hypothesis (i.e., the likelihood that the two samples came from the same population) is true. If the P-value is less than α, then the null hypothesis can be rejected. c The D-statistic is the maximum difference between the cumulative frequency plots of two populations. d Normalization coefficient for two population sizes, n 1 and n 2 . Alluvial fan unit comparison Significance level, α a P-value b D-statistic c N, n 1 +n 2 /n 1 n 2 d Q2a vs. Q2b 0.01 1.5 x 10 -49 0.1242 0.000274 Q2b vs. Q2c 0.01 0 0.304 0.000216 Q2c vs. Q3a 0.01 0 0.3704 0.000245 Q3a vs. Q3b 0.01 0 0.3604 0.000266 Q3b vs. Q3c 0.01 8.8 x 10 -82 0.1371 0.000201 Q3c vs. Q4a 0.01 5.4 x 10 -4 0.0340 0.000283 Q4a vs. Q4b 0.01 0 0.4941 0.000252 Q2a vs. Q3b 0.01 0 0.3083 0.000302 Q2b vs. Q3a 0.01 8.0 x 10 -14 0.0683 0.000216 39 Figure 2.10 Cumulative frequency distributions of surface roughness ( σ m ) determined in a five-meter by five-meter moving window for the comparison of eight alluvial fan units in northern Death Valley. The D-statistic in the Kolmogorov-Smirnov test is the maximum difference between the cumulative frequency distributions of two sample populations (Equation 2.5). A. Cumulative frequency distributions for units Q4b to Q2c. B. Cumulative frequency distributions for units Q2c to Q2a. See text and Table 2.1 for descriptions of each unit. 40 Figure 2.11 Results of the Kolmogorov-Smirnov tests for the comparison of surface roughness between alluvial fan units at a wavelength of five meters. Curves represent 95% ( α = 0.05) and 99% ( α = 0.01) confidence levels. The area above the curves is the region where the null hypothesis of the surface roughness for each unit being derived from the same population can be rejected (i.e. there is a statistically significant difference between the surface roughness of the units compared to one another). The region below the curves shaded in grey represents the region where null hypothesis cannot be rejected and the samples are derived from statistically similar populations. The D-statistic on the y-axis is the maximum difference between the cumulative frequency distributions in Figure 2.10. The value N on the x-axis is a normalization parameter for populations of different size where n 1 is the size of one population and n 2 is the size of the population to which n 1 is being compared. See Equations 2.5, 2.6, and 2.7 for further explanation. Parameters for the Kolmogorov-Smirnov test can be found in Table 2.2. Note that surface roughness distributions of units that are adjacent in age, as well as those with similar means but different ages, are all statistically different from each other at the 99% confidence level ( α = 0.01). 41 reject the null hypothesis that samples from individually mapped units are derived from the same populations. 2.6. Discussion 2.6.1 Changes in Surface Roughness 2.6.1.1 Surface Roughness Controlled by Bar and Swale Topography Quantifying surface roughness across a high-resolution digital elevation data set shows that individual fan units can be distinguished in a statistically significant manner (Figure 2.11). Surface roughness values, when plotted against relative fan- unit age (Figure 2.8), bring to light an interesting pattern, which previously has only been described through qualitative field observations [e.g., Bull, 1991]. The youngest alluvial fan surfaces, Q4b, Q4a, and Q3c, have the highest surface roughness values (Table 2.1; Figure 2.8). In addition, the youngest surfaces have the largest variance in the surface roughness metric (Table 2.1; Figure 2.8). This pattern results from freshly deposited clasts of different sizes being sequestered into bars and swales. In general, channel bars are composed of larger clasts and swales are filled with finer-grained material (Figure 2.5). Inasmuch as relatively coarse-grained alluvium defines bars, and swales comprise finer grains, surface roughness does not vary strictly as a function of clast size. The resolution of the digital elevation model, from which slope values were derived, is one meter. This window is larger than even the maximum clast size found on any individual fan surface in the study area (Table 2.1; Figure 2.6). 42 Therefore, our calculations of surface roughness take into account only the medium- wavelength (~5 to 10 m) bar-and-swale structures that dominate the surface morphology of alluvial fans. We note, however, that clast size may influence the formation and preservation of the bar-and-swale structures, as fans tend to be rougher (higher standard deviation of slope) where mean clast sizes are larger, which leads to a higher angle of repose, and where field observations suggest more prominent expression of bar-and-swale morphology (Figures 2.5, 2.6 and 2.8). As fan surfaces increase in age, surface roughness decreases from the youngest unit, Q4b, to the most stable, smoothest fan surface, Q2c (Figure 2.8). Previous work defined the age of the Q2c surface to be ~70 ka, on the basis of in-situ 10 Be and 36 Cl cosmogenic nuclide geochronology [Frankel et al., 2007]. Although fan surfaces younger than the Q2c surface have no absolute age control at present, soil formation and varnish accumulation on the Q4 and Q3 deposits suggest that fan smoothing occurs rapidly in the first few thousand years after deposition. From this point until ~70,000 years after deposition, smoothing of the fan surface proceeds ever more slowly with time. On surfaces older than ~ 70 ka, the steep walls of channels that have incised through the most stable alluvial surface, Q2c, begin to erode by headward tributary incision, and consume the once-planar surface. As this erosion proceeds, the older surfaces, Q2a and Q2b, become increasingly rougher with increasing age as the alluvial fans degrade with time (Figure 2.8). 43 2.6.1.2 Surface Roughness at Multiple Length Scales Changes in the pattern of surface roughness also occur as a function of the wavelength over which roughness values are calculated (Figure 2.9). Each mapped fan unit is characterized by an initial, rapid increase in surface roughness corresponding to an increase in the size of the moving window, over which the standard deviation of slope is determined (Figure 2.9A). The point at which surface roughness no longer changes rapidly as a function of the size of the averaging window gives an indication of the dominant topographic wavelengths for each surface. As the size of the window becomes larger, surface roughness values for each unit converge when the area over which roughness values are calculated begins to incorporate multiple surfaces (Figure 2.9A). Units Q4b, Q4a, Q3c, and Q3b are each characterized by a rapid increase in surface roughness values over wavelengths of five to 12 meters, representing the typical length scale of bar and swale topography (Figure 2.9A). At longer wavelengths, surface roughness values increase by only minor amounts, suggesting the topographic saturation length is ~12 m for the youngest surfaces [e.g., Barabasi and Stanley, 1995]. We note however, the youngest unit, Q4b, appears to have a saturation wavelength that is somewhat longer than units Q4a, Q3c, and Q3b (Figure 2.9A). This is likely due to the fact that the Q4b channels are often deeply incised through older alluvial fan surfaces (Figure 2.3A) and therefore, larger averaging windows incorporate steep channel walls, causing higher standard deviations in slope values. A similar pattern emerges for units Q3a and Q2c. 44 Units Q3a and Q2c show an initial rapid increase in surface roughness values over wavelengths of five to 12 meters (Figure 2.9A). However, both the Q3a and Q2c surface roughness values continue to increase steadily at longer wavelengths (Figure 2.9A). We feel this also occurs as result of active channels (Q4b) being deeply incised through older surfaces (Figure 2.3A), thus causing standard deviation of slope values to be higher at longer length scales away from the representative central portion of these deposits. A somewhat different pattern emerges when surface roughness values are analyzed as a function of window size for the two oldest surfaces in the study area, units Q2b and Q2a (Figure 2.9B). As with the younger units, surface roughness increases at first, although in this case it occurs over a length scale of 50 to 75 m (Figure 2.9B). The longer topographic saturation wavelength suggests that roughness values on the older surfaces are no longer controlled by the evolution of bar and swale topography. Rather, increased roughness values on these surfaces are the result of headward incision of tributary channels, transforming the once-planar surfaces into rounded hillslopes, leaving behind a signature of topographic roughness at longer wavelengths. Continued incision of tributary streams causes the oldest surface in the study area, Q2a, to have a longer topographic wavelength than the Q2b deposit. 2.6.1.3 Clast Size Patterns A pattern similar to that of surface roughness (Figure 2.8) is observed in the distribution of clast sizes on fan surfaces (Figure 2.6). A large range of clast sizes is 45 present on the fan surface immediately following deposition. With time, clasts begin to weather and become buried as fan surfaces smooth out [e.g., Bull, 2007]. Absolute clast size and clast-size variance decrease as the fans evolve toward a smooth, stable configuration. As fans continue to increase in age, larger clasts are exhumed from beneath the surface by erosion (Figure 2.6). Eventually, clast size increases and becomes more variable with age, in much the same way that fan surfaces become rougher. 2.6.2 Implications for Arid-Region Landscape Evolution Surface roughness, in addition to facilitating the characterization of individual fan units, lends insight to alluvial landform development. We propose an alluvial landform evolutionary scheme that begins with fan deposition within, and downstream from, the mouth of active channels. These areas exhibit prominent bar- and-swale morphology and large variations in clast size. Their surfaces are rougher than anywhere else in the alluvial fan complex (Figure 2.12A). Bar and swale topography is formed through a combination of sheet-flood and debris flow events in a braided channel network. The bars result from sediment-rich flows deposited at the end of distributary channels that criss-cross the active fan surface [Bull, 1977; Bull, 1991; Harvey and Wells, 2003]. With time, the locus of deposition changes and the active depositional surface is abandoned. This leaves the surface to evolve into a smooth, stable landform as the undulatory bar-and-swale morphology begins to diffuse away and pavements start to form (Figure 2.12B). As time progresses, the bar-and-swale structure continues to decay until a highly planar surface with little or 46 Figure 2.12 Schematic diagram showing the inferred landform evolution of alluvial fans in northern Death Valley based on surface roughness characteristics. A. The morphology of a young, active, or recently active, fan surface similar to units Q4b, Q4a, and Q3c with prominent bar-and-swale morphology. Stippled pattern represents active channels and white areas are channel bars with coarser material. B. Alluvial fan surface where the bar-and-swale morphology has started to smooth out and become subdued. Bars have eroded and filled in channels similar to units Q3b and Q3a. Stippled pattern represents abandoned channel with a concentration of fine-grained sediments. White areas are fan surfaces with moderate pavement development and a reduction in clast size. C. Smooth, planar alluvial fan surface similar to unit Q2c. White area is characterized by a well-packed, mature pavement and heavy varnish development. Stippled area is an active channel that has incised through the older, smoother surface. D. As fans continue to increase in age, steep channel walls are eroded by headward incision of tributaries and are transformed into convex (rounded) hillslopes, such as units Q2b and Q2a. In general, pavements are less well-developed on these surfaces because of the down-slope sediment transport. Stippled areas represent active, or recently active, channels and white areas are the alluvial fan surfaces that are diffusing into more mature landforms. 47 no relief is formed (Figure 2.12C). The smoothing of bar and swale topography results from the winnowing of fine-grained material from bars into swales and the weathering of larger clasts through rain splash, sheet-flow, wind, and expansion and contraction of the Av horizon from cycles of wetting and drying [Bull, 1991; Bull, 2007]. At the same time, pavements form by surface inflation from aeolian dust deposition and the transport of clasts from bars into swales [McFadden et al., 1987; Haff and Werner, 1996; Haff, 2001; Haff, 2005]. For the case of alluvial fans in the arid environment of northern Death Valley, this is accomplished over a period of ~70,000 years. Eventually, tributary channels form from erosion by surface runoff. Headward incision of these tributaries wears down the steep walls of channels that are incised through the stable, planar surface transforming the oldest alluvial landforms into convex hillslopes [e.g., Roering et al., 1999], leaving only small remnants of the planar surface intact (Figure 2.12D). Although the surface-roughness data illustrate the progression of fan development with time, at present we are not able to fully quantify the rates over which these processes operate, with the exception of the ≤ 70 ky it apparently takes to evolve from abandonment of the active depositional surface to a stable, planar landform. A recent study by Matmon et al. [2006], in which they investigated the morphologic development of alluvial landforms by measuring cosmogenic nuclide inventories in bars and swales of dated fans, suggests sediment residence times of at least 30,000 years. They suggested that >280,000 years are required for complete smoothing to take place on fans formed along the San Andreas fault in southern 48 California, a significantly longer time interval than we propose for fans in Death Valley. This result emphasizes that rates of alluvial landform evolution are likely to be location-dependent and therefore, calibration for different climatic and tectonic regimes is necessary. Future quantification of the rates of such processes, both through exploitation of high-resolution digital topographic data and by determining the age of individual fan units, will further improve our understanding of post- depositional alluvial landform development. 2.7 Conclusions We have exploited the high resolution of ALSM digital topographic data to quantify surface roughness on alluvial fans in northern Death Valley. By calculating surface roughness as the standard deviation of slope in a five-meter by five-meter moving window across a one-m-resolution digital elevation data set we have shown that individual lithostratigraphic units can be differentiated at the 99% confidence level on the basis of this topographic metric. Additionally, the surface roughness data demonstrate a characteristic, time-dependent evolution of fan morphology that has previously only been described through qualitative field observations. Specifically, the surfaces of alluvial fans decrease in roughness with time, eventually becoming smooth, planar landforms. In the arid climate of Death Valley, this smoothing process appears to occur over a period of ≤ 70,000 years. As the alluvial fan continues to evolve, stable landform configurations eventually erode into convex hillslopes. Once this threshold is crossed, surface roughness increases with age as 49 tributary channel incision dissects the formerly smooth surface. These results demonstrate that diagnostic morphologic features commonly observed on alluvial deposits can be quantified with high-resolution digital topographic data. With access to high-resolution digital topographic data sets becoming more and more common, this methodology will be a useful aid in the objective identification, mapping, and interpretation of alluvial landforms during future studies. 50 CHAPTER 3: Cosmogenic 10 Be and 36 Cl geochronology of offset alluvial fans along the northern Death Valley fault zone: Implications for transient strain in the eastern California shear zone Abstract The northern Death Valley fault zone (NDVFZ) has long been recognized as a major right-lateral strike-slip fault in the eastern California shear zone (ECSZ). However, its geologic slip rate has been difficult to determine. Using high- resolution digital topographic imagery and terrestrial cosmogenic nuclide dating we present the first geochronologically determined slip rate for the NDVFZ. Our study focuses on the Red Wall Canyon alluvial fan, which exposes clean dextral offsets of seven channels. Analysis of airborne laser swath mapping data indicates ~297 ± 9 m of right-lateral displacement on the fault system since the late Pleistocene. In situ terrestrial cosmogenic 10 Be and 36 Cl geochronology was used to date the Red Wall Canyon fan and a second, correlative fan also cut by the fault. Beryllium-10 dates from large cobbles and boulders provide a maximum age of 70 +22/-20 ka for the offset landforms. The minimum age of the alluvial fan deposits based on 36 Cl depth profiles is 63 ± 8 ka. Combining the offset measurement with the cosmogenic 10 Be date yields a geologic fault slip rate of 4.2 +1.9/-1.1 mm/yr, whereas the 36 Cl data indicate 4.7 +0.9/-0.6 mm/yr of slip. Summing these slip rates with known rates on the Owens Valley, Hunter Mountain, and Stateline faults at similar latitudes suggests a total geologic slip rate across the northern ECSZ of ~8.5 to 10 mm/yr. This rate is commensurate with the overall geodetic rate and implies that the apparent 51 discrepancy between geologic and geodetic data observed in the Mojave section of the ECSZ does not extend north of the Garlock fault. Although the overall geodetic rates are similar, the best estimates based on geology predict higher strain rates in the eastern part of the ECSZ than to the west, whereas the observed geodetic strain is relatively constant. 3.1 Introduction Whether strain storage and release rates are constant or non-uniform over geologic time is a fundamental, unresolved issue in modern geodynamics. Comparisons of short-term (<decadal) geodetic data with long-term (>thousand to million year) geologic data indicate that strain storage and release rates are comparable along most plate boundaries [Sella et al., 2002]. Along the Pacific- North American plate boundary, where plate motion is partitioned between the San Andreas fault and relatively low strain-rate, intraplate faults of the eastern California shear zone (ECSZ) and Basin and Range [e.g., Bennett et al., 2003], recent comparisons of geodetic and geologic strain rates reveal significant discrepancies. The Mojave section of the ECSZ south of the Garlock fault exhibits a pronounced strain transient [Peltzer et al., 2001; Oskin and Iriondo, 2004] wherein the geodetic rates appear to be as much as twice the longer-term geologic rates [Dixon et al., 2000; McClusky et al., 2001; Peltzer et al., 2001; Oskin and Iriondo, 2004; Oskin et al., 2006; Oskin et al., 2007]. Similarly, along the eastern margin of the ECSZ north of the Garlock fault, geodetic right-lateral shear of ~1.2 mm/yr across the Yucca 52 Mountain area is not accommodated by any comparable Quaternary structure [Wernicke et al., 2004; Friedrich et al., 2004]. These observations raise several fundamentally important questions about how strain accumulates and is released along major plate boundary fault systems. Most basically, how temporally constant is strain accumulation and release? Are geologic slip rates averaged over thousands to millions of years compatible with short-term geodetic rates, or do strain transients commonly occur? If transients do occur, over what time scales do they operate? Are strain transients localized features tied to regions of structural complexity or are they more fundamental features of plate boundary motion [e.g., Dixon et al., 2003; Friedrich et al., 2003; Bennett et al., 2004; Wernicke et al., 2005; Dolan et al., 2007]? In this paper, we address these questions as they pertain to the Pacific-North America plate boundary by determining a long-term geologic slip rate on the northern Death Valley fault zone (NDVFZ; Figure 3.1). Acquisition of high- resolution airborne laser swath mapping (ALSM; also known as LiDAR) digital topographic data allows us to restore deformed alluvial landforms in unprecedented detail along the trace of the fault. In the past it was difficult to quantitatively determine the precise age of Pleistocene deposits in arid environments due to the lack of datable materials. Over the past two decades, however, the advent of terrestrial cosmogenic nuclide geochronology has allowed researchers to resolve numerical ages for a variety of depositional landforms [Phillips et al., 1986; Lal, 1987; Elmore and Phillips, 1987; Finkel and Suter, 1993; Bierman et al., 1995; 53 Figure 3.1 Index map of the eastern California shear zone (ECSZ). The Death Valley and Fish Lake Valley fault zones are highlighted in white. Recent, major ECSZ surface ruptures are shown in dark gray. The white star indicates the location of the Red Wall Canyon and Big Dip Canyon alluvial fans. FLVF = Fish Lake Valley fault, WMF = White Mountains fault, NDVF = northern Death Valley fault zone, BMF = Black Mountains fault zone, HMF = Saline Valley-Hunter Mountain-Panamint Valley fault, OVF = Owens Valley fault, SDVF = Southern Death Valley fault, SLF = Stateline fault, SNF = Sierra Nevada frontal fault, AHF = Ash Hill fault, GF = Garlock fault, LF = Lockhart fault, HLF = Harper Lake fault, BF = Blackwater fault, GSF = Goldstone fault, HF = Helendale fault, LeF = Lendwood fault, CRF = Camp Rock fault, CF = Calico fault, PF = Pisgah fault, LuF = Ludlow fault, PMF = Pinto Mountain fault, SAF = San Andreas fault, NIF = Newport-Inglewood fault, EF = Elsinore fault, SJF = San Jacinto fault, LA = Los Angeles, and YM = Yucca Mountain. Geodetic (GPS) rates are from Savage et al. [1990], Dixon et al. [1995], Gan et al. [2000], and Bennett et al. [2003]. 54 Anderson et al., 1996; Hancock et al., 1999; Gosse and Phillips, 2001; Van der Woerd et al., 2002; Matmon et al., 2005; Matmon et al., 2006; Van der Woerd et al., 2006]. Dating offset landforms along the NDVFZ by in situ terrestrial cosmogenic 10 Be and 36 Cl, two independent, yet complementary techniques, yields a more precise geologic slip rate on the NDVFZ and provides the first direct comparison between the two geochronometers from the same deposit. The slip rates presented here fill in a major missing piece of the strain “puzzle” in the ECSZ. 3.2 Active Tectonics of the Eastern California Shear Zone The ECSZ and its northern equivalent, the Walker Lane belt of western Nevada, extend more than 800 km north from the eastern Transverse Ranges in southern California, through the Mojave Desert and along the westernmost portion of the Basin and Range province (Figure 3.1). The ECSZ is characterized by a system of predominantly right-lateral, strike-slip faults and normal faults that accommodate ~20-25% of the total relative motion between the Pacific and North America plates [Dokka and Travis, 1990; Humphreys and Weldon, 1994; Bennett et al., 1997; Reheis and Sawyer, 1997; McClusky et al., 2001; Bennett et al., 2003; Dixon et al., 2003]. In the Mojave Desert, south of the left-lateral Garlock fault, the southern ECSZ comprises a ~100-km-wide network of north-northwest-trending right-lateral faults. Geodetic data indicate that elastic strain is accumulating across this zone at 12 ± 2 mm/yr [Savage et al., 1990; Bennett et al., 1997; Gan et al., 2000; McClusky et 55 al., 2001; Miller et al., 2001; Peltzer et al., 2001]. Both seismological and paleoseismological data indicate that the southern ECSZ is releasing strain at a relatively rapid rate. Specifically, portions of several of the faults in this region ruptured during the 1992 M w 7.3 Landers and 1999 M w 7.1 Hector Mine earthquakes (Figure 3.1). Furthermore, paleoseismologic data indicate that these two earthquakes are part of an ongoing, ≥1,000-year-long seismic cluster [Rockwell et al., 2000]. However, such evidence for rapid strain accumulation and release during the recent past is at odds with geologic slip rate data. The long-term, cumulative slip rate across the Mojave segment of the ECSZ is much slower (by about half) than the current rate of strain accumulation [Oskin et al., 2006; Oskin et al., 2007]. These observations suggest the occurrence of a pronounced strain transient across the southern ECSZ. Displacement from the southern ECSZ continues north across the Garlock fault into the northern ECSZ, which consists of four major fault systems: the Owens Valley (OVFZ), Panamint Valley-Saline Valley-Hunter Mountain (HMFZ), northern Death Valley, and Stateline (SLFZ) fault zones (Figures 3.1 and 3.2). Farther north, most of the dextral motion between the Sierra Nevada block and North America is focused on the White Mountains and Fish Lake Valley fault zones bounding the east and west sides of the White Mountains, respectively (Figure 3.2). In addition to the major north-trending dextral faults, a number of northeast-trending faults transfer slip between faults of the Owens and Panamint Valley fault systems and the Death Valley fault system (Figure 3.2) [Dixon et al., 1995]. These predominantly down-to- 56 Figure 3.2 Detailed index map of the northern part of the eastern California shear zone showing the relationship between the Owens Valley, Hunter Mountain, northern Death Valley, and Stateline fault zones. The white box on the northern Death Valley fault zone indicates the location of Figure 3.5. White triangle shows the location of GPS site ROGE. Numbers in parentheses next to fault names indicate the preferred long-term slip rate of the fault and white circles represent locations where the slip rate was determined. Slip rates are from this study, Lee et al. [2001b], Oswald and Wesnousky [2002], and Schweickert and Lahren [1997]. See text for discussion. WMFZ = White Mountains fault zone, FLV = Fish Lake Valley, FLVFZ = Fish Lake Valley fault zone, DSV = Deep Springs Valley, EV = Eureka Valley, NDVF = northern Death Valley fault zone, SDVF = southern Death Valley fault zone, BMF = Black Mountains fault zone, SV = Saline Valley, SVF = Saline Valley fault zone, OVF = Owens Valley fault zone, HMF = Hunter Mountain fault zone, SLF = Stateline fault zone, PV = Panamint Valley, AHF = Ash Hill fault, PVF = Panamint Valley fault zone, GM = Grapevine Mountains, FM = Funeral Mountains, BM = Black Mountains, SNF = Sierra Nevada frontal fault, DSF = Deep Springs fault, TMF = Tin Mountain fault, and TPF = Towne Pass fault, and YM = Yucca Mountain. 57 the-northwest extensional faults include the Deep Springs, Towne Pass, and Tin Mountain faults [Dixon et al., 1995; Lee et al., 2001a; Klinger, 2001]. For detailed descriptions of individual faults in the northern ECSZ, please see Appendix B. 3.2.1 Death Valley Fault System The ~310-km-long Death Valley fault system, which includes the Fish Lake Valley fault zone [Reheis and Sawyer, 1997; Machette et al., 2001], is the largest and most continuous fault system in the ECSZ (Figure 3.1). The NDVFZ transitions into the Fish Lake Valley fault zone to the north (Figure 3.2) [Machette et al., 2001]. Both of these faults offset Quaternary deposits. In contrast, the southeastern extent of the NDVFZ, the Furnace Creek fault zone, does not offset Quaternary deposits in southernmost Amargosa Valley [Machette et al., 2001]. Net offset of pre-11.6 ± 0.3 Ma [Niemi et al., 2001] markers found in both the Cottonwood and Funeral Mountains is 68 ± 4 km [Snow and Wernicke, 1989]. This yields an average post- mid-Miocene slip rate of 5.9 ± 0.4 mm/yr for the combined traces of the northern Death Valley and Furnace Creek fault zones. Both geologic and geodetic observations suggest that the northern Death Valley and Fish Lake Valley fault zones accommodate the majority of slip in the ECSZ north of the Garlock fault. Estimates of the slip rate for the NDVFZ based on geodetic data range from ~3 to 8 mm/yr [Savage et al., 1990; Humphreys and Weldon, 1994; Bennett et al., 1997; Dixon et al., 2000; McClusky et al., 2001; Dixon et al., 2003; Bennett et al., 2003]. The total contemporary displacement rate between the central Panamint Range (GPS site ROGE, which is ~20 km WSW of the Death 58 Valley fault system and an equal distance ENE of the Panamint Valley fault system) and the relatively stable central Great Basin region is 3.6 ± 0.2 mm/yr [Wernicke et al., 2005]. Because a significant fraction of ROGE’s motion may be attributable to the Panamint Valley fault system as well as the SLFZ, this rate should be considered a firm upper bound on the contemporary geodetic displacement along the NDVFZ. The best estimate of total motion across the ECSZ/Walker Lane belt, including continuous GPS data, is 9.3 ± 0.2 mm/yr [Bennett et al., 2003]. This estimate is relatively low compared with previous, less robust estimates, but closer to a sum of estimated geologic slip rates on faults in the region. Studies estimating the 1,000 year to 1,000,000 year geologic slip rates on the NDVFZ are sparse [Brogan et al., 1991; Reheis and Sawyer, 1997; Klinger, 2001]. Klinger [2001] used tephrochronology and soil development to estimate Holocene to Pleistocene slip rates of 3 to 9 mm/yr on the NDVFZ. The broad range of slip rates highlights the difficulties associated with obtaining age control. Soil geomorphic ages are semi-quantitative and provide a reasonable correlative age, but they are not equivalent to geochronology. Tephrochronology is generally accurate and precise, but in Death Valley, the large number of nearby Long Valley caldera eruptions often makes correlations tentative [Klinger, 2001]. Although previous studies suggest slip rates that are broadly in agreement with geodetic estimates, improving upon them through direct dating of offset geomorphic features allows for a more robust comparison between geodetic and geologic rates. This study further refines the slip 59 rate on this important fault by dating and restoring the dextral offset on the Red Wall Canyon alluvial fan in northern Death Valley. 3.3 Study Area The alluvial fans at the mouth of Red Wall and Big Dip Canyons, which drain the western flank of the Grapevine Mountains are offset by the NDVFZ (Figures 3.1 and 3.2). Reynolds [1969] estimated the offset of Red Wall Canyon stream channels at 46 m. Klinger [2001] mapped six alluvial units ranging in age from late Pleistocene to the active channels, and documented 250 to 330 m of dextral offset. At Big Dip Canyon, Brogan et al. [1991] mapped a shutter ridge along the west side of the NDVFZ that effectively isolates older alluvial-fan deposits to the west. Alluvial-fan deposits in Death Valley are consistent with the ubiquitous desert piedmont deposits (Q1, Q2, Q3, and Q4) that can be correlated throughout southwestern North America by geomorphic expression and soil development [Bull, 1991]. Regionally, the Q2 surface is generally considered late Pleistocene in age and was deposited in a semi-arid environment during a slight warming in otherwise average glacial conditions during oxygen isotope stage four [Bull, 1991; Machette et al., in review]. Knott et al. [2002] showed that alluvial-fan deposits in southern Death Valley with the characteristic Q2 morphology are younger than the late Pleistocene Lake Manly deposits dated at 180 to 120 ka by Ku et al. [1998]. In northern Death Valley, Klinger [2002] mapped deposits with the characteristic Q2 60 Figure 3.3 A. View looking to the northeast across the Q2c surface of the Red Wall Canyon alluvial fan. Grapevine Mountains define the horizon. Notice the well developed pavement and heavily varnished clasts on the smooth Q2c surface with subdued bar and swale topography. Daypack for scale. B. Representative example of sample collected from the Q2c surface for 10 Be geochronology. Notebook for scale. C. Underside of the sample in B, showing the highly rubified nature of clasts on the Q2c surface and silty, vesicular A horizon commonly developed beneath clasts. 61 morphology that he subdivided into three units (Q2a, Q2b and Q2c) based on height above the active channel. At Red Wall and Big Dip Canyons, the Q2c unit is the only Q2 deposit preserved, and therefore our study is focused on the Q2c surface. Clasts on the Q2c fan surface range in size from cobble to small boulder and consist predominantly of carbonates and quartzites surrounded by tightly packed pebbles and small cobbles forming a mature desert pavement. The Q2c morphology is characterized by subdued to non-existent bar and swale topography and a well- developed desert pavement. The tops of clasts are heavily varnished whereas the undersides are highly rubified (Figure 3.3). At Red Wall and Big Dip Canyons the alluvial fans are composed of poorly sorted massive carbonate and quartzite breccias and conglomerates that are characteristic of debris flows [Bull, 1972]. A mature soil, as much as 50-cm-thick, is developed below the Q2c surface (Figure 3.4). The soil is characterized by a 10- to 20-cm-thick Av horizon with clay film accumulation in its lower half; a middle Bt horizon with carbonate and salt development; and a lower Bk horizon with moderate carbonate accumulation (Stage III) [Birkeland, 1999; Klinger, 2001]. Based on these characteristics, Klinger [2001] estimated that Q2c was deposited between 35 ka and 60 ka. Owing to its low relief, high degree of varnish, and well developed soil, the Q2c surface stands out in marked contrast to its surrounding deposits, making it a perfect candidate for fault displacement reconstructions [Frankel and Dolan, 2007]. The Q2c surface has been incised and isolated by younger alluvial channels. Thus, 62 Figure 3.4 A. Photograph looking north towards a channel-wall exposure of the Big Dip Canyon alluvial fan, ~5 km north of Red Wall Canyon. The vertical channel in the photograph is the sample location of 36 Cl depth profile NRWF. B. Photograph of a typical soil profile developed in Q2c surfaces in Death Valley. The tape measure provides a scale. Example shown is from the NRWF depth profile location. 63 Figure 3.5 A. Airborne laser swath mapping (ALSM) images of the study area. Location of strip map shown by white box in Figure 3.2. White arrows delineate the surface trace of the northern Death Valley fault zone. The Red Wall Canyon alluvial fan is located in the southeast half of the image and the detailed map in Figure 3.6 is outlined by the white box corners. B. Detailed image of sample locations on the Big Dip Canyon alluvial fan. Arrow points to location of the depth profile collected from this site. White box indicates the region where the six surface samples were collected. 64 restoring slip by realigning channels incised through the Q2c surface provides a minimum slip rate over a late Pleistocene time scale. While we cannot address the potential for spatial variations in slip rates in this region from this site alone, the Red Wall Canyon alluvial fan provides the single best location for a long-term slip rate study on the NDVFZ. The Red Wall Canyon fan preserves multiple well-defined piercing points, excellent fault zone exposure along a single trace, and is characterized by the most stable geomorphic surface in the region, making it the most amenable site for cosmogenic nuclide geochronology (Figure 3.5). Furthermore, the offsets at Red Wall Canyon are at similar latitude to slip rate locations on the Owens Valley, Hunter Mountain, and Stateline faults (Figure 3.2), which allows us to calculate a robust long-term slip rate budget across the region. 3.4 Airborne Laser Swath Mapping and Fault Offset 3.4.1 Airborne Laser Swath Mapping Data Collection An important component of our study is the acquisition of airborne laser swath mapping (ALSM; also known as LiDAR) digital topographic data along the NDVFZ (Figure 3.5). The data were collected from an Optech Inc. Model ALTM 1233 laser mapping system. The laser was flown over the field area at an elevation of 600 m above ground level at an average speed of 60 m/s using a Cessna 337 twin- engine aircraft. The aircraft was equipped with a dual-frequency geodetic quality GPS receiver and a real time display of the flight path and data coverage. 65 Figure 3.6 A. Color-coded airborne laser swath mapping (ALSM) image of the the Red Wall Canyon alluvial fan. The Q2c (oldest) surface is shown in red. Beryllium-10 surface sample locations are shown by black squares. Chlorine- 36 depth profile locations are shown by black triangles. Colored circles indicate channels that correlate to each other when offset is restored. B. ALSM image of Red Wall Canyon alluvial fan restored 297 ± 9 m to its original, pre-faulting configuration. Colored circles mark the correlation of channels shown in A. Q2c surface is shown in red. Geology based on mapping by Klinger [2001]. See Table 3.1 for individual channel offset measurements. 66 The laser source produced 33,000 laser pulses per second and recorded the first and last returns of each pulse, as well as the relative intensity of each return. Processing of these data using SURFER (Golden Software) Version 8.04 with a kriging algorithm allowed the construction of a highly precise digital elevation model with 5 to 10 cm vertical accuracy and one-meter horizontal resolution [Carter et al., 2001, 2003; Sartori, 2005]. 3.4.2 Red Wall Canyon Alluvial Fan Offset The ALSM data collected from our field area clearly show seven dextrally offset alluvial channels on the Red Wall Canyon alluvial fan (Figures 3.5 and 3.6A). The high-resolution digital elevation data allow us to precisely reconstruct the offset alluvial fan to its pre-faulting position (Figure 3.6). The ALSM data were processed in ArcInfo to produce hill-shaded relief maps and slope maps to aid in the identification, mapping, and reconstruction of offset landforms. Channel offsets were measured directly from the DEM in ArcInfo using the thalweg of each channel as a piercing point. Thalwegs were defined by constructing a channel network from the DEM where the deepest part of the channel is determined by routing the flow direction from each cell in the channel to its steepest downslope neighbor [e.g., Tarboton et al., 1991]. This allows for the objective delineation of thalwegs, and thus piercing points, from which we were able to restore slip on the fault. The total amount of along-strike offset for the channel thalwegs ranges from 286 to 307 m (Table 3.1). The mean offset of the channels incised into the Q2c surface at the Red Wall Canyon alluvial fan is 297 ± 9 m. We use the mean 67 Table 3.1 Channel Offset Measurement for Red Wall Canyon Alluvial Fan a Channel colors correspond to circles in Figure 3.6. b Channel offsets and errors are taken as the mean and standard deviation of each set of measurements. Channel a Thalweg offset, m NW riser offset, m SE riser offset, m Red 307 303 304 Dark blue 291 291 285 Light blue 304 308 304 Purple 286 290 289 Green 301 304 294 Orange 306 301 303 Yellow 287 275 284 68 and standard deviation of all measured offsets as the total post-Pleistocene fault displacement and error, respectively. This is a revision of the 250 to 330 m of displacement estimated by Klinger [2001] using low-sun-angle 1:12,000 scale aerial photographs. As a test of the offset measurements determined from the thalwegs, offsets were also measured based on the northwest and southeast channel walls. This was accomplished by deriving a slope map from the high-resolution DEM so that channel walls were more readily defined and easier to match with one another. Although somewhat more subjective than the thalweg method described above, the results are nearly identical. Restoration of the northwest channel walls produced an offset of 296 ± 11 m, while the southeast margins are offset 294 ± 9 m (Table 3.1). Because of the more objective nature of the thalweg offsets, we use that as our preferred late- Pleistocene displacement. No offset measurements were determined for the Big Dip Canyon alluvial fan. This fan does not have a correlative deposit preserved on the northeast side of the fault and therefore, slip cannot be restored to determine fault displacement at this location (Figure 3.5). 3.5 Terrestrial Cosmogenic Nuclide Geochronology The accumulation of terrestrial cosmogenic nuclides, produced by the interaction of cosmic rays with minerals at the Earth’s surface, allows the age and history of geomorphic surfaces and deposits to be quantified [Lal, 1991; Gosse and 69 Phillips, 2001]. Cosmogenic nuclides are particularly advantageous over techniques such as radiocarbon in regions that either lack datable organic matter, or where the anticipated age of such surfaces and deposits is greater than ~40 ka. For materials that contain no terrestrial cosmogenic nuclides at the time of formation (e.g., lava flows), the nuclide inventory is a function of only the time of exposure and erosion rate (please see Appendix C). In that case, the exposure age can generally be calculated based on a very limited number of samples. However, for samples from alluvial fans where inheritance is typically large, too many unknowns exist to uniquely solve the production equation. This problem can be overcome by collecting sub-surface samples in a depth profile [Anderson et al., 1996; Repka et al., 1997; Hancock et al., 1999]. Collecting samples at multiple depths allows the inherited component of the total cosmogenic-nuclide inventory to be separated from the in situ component [Anderson et al., 1996; Hancock et al., 1999; Gosse and Phillips, 2001]. 3.5.1 Beryllium-10 Surface Samples Beryllium-10 is produced through spallation and muon-induced reactions with Si and O. Typically, quartz is used as the target mineral for 10 Be because of its stoichiometric simplicity, quantitative retention of 10 Be, and resistance to chemical weathering [Gosse and Phillips, 2001]. Sixteen surface samples from quartzite boulders and large cobbles were collected for the analysis of in situ cosmogenic 10 Be (Figures 3.3, 3.5, and 3.6). Ten samples were collected from stable surfaces close to the fault across the mid-section of the Red Wall Canyon fan (Figure 3.6). Samples 70 from Big Dip Canyon were collected in close proximity to each other from the most stable and least incised part of the fan surface near the location of the 36 Cl depth profile (Figure 3.5). The samples were resting on a Av soil horizon, were coated with a dark desert varnish on the top, showed rubification on the underside, and lacked carbonate collars or varnish alteration above the soil/clast interface. All of these features are characteristic of clasts that have resided at the surface, relatively undisturbed, since deposition (Figure 3.3). The top 5 cm of each sample was cut away and only this portion of the clast was used for 10 Be extraction. The 5 cm-thick slabs were then crushed and sieved to separate the 250 to 500 μm grain size fraction. Pure quartz was then isolated by techniques outlined in Kohl and Nishiizumi [1992] and Be was extracted from the quartz by anion and cation exchange chromatography. Samples were then analyzed for 10 Be concentrations by accelerator mass spectrometry (AMS) at Lawrence Livermore National Laboratory. The sixteen surface samples range in age from 37 ± 6 ka. to 219 ± 4 ka.; 12 of the 16 samples cluster between ~50 and 90 ka (Table 3.2). Sample ages were calculated using production rates of 10 Be based on Stone [2000]. Carrier composition, counting statistics, and the blank are all potential sources of uncertainty in the measured 10 Be concentrations. A 3% error in the decay constant of 10 Be and 6% error in the production rates are propagated with the analytical uncertainties to produce errors on the 10 Be model age [Stone, 2000]. 71 Table 3.2 Analytical Results of 10 Be Geochronology Sample Location, latitude/longitude Altitude, m Quartz a , g Thickness, cm Be carrier b , g 10 Be/ 9 Be, 10 -12 Measured 10 Be c , 10 6 atoms/g SiO 2 10 Be age d , ka KF-031605-1 36°52.20/117°15.60 401 30.0400 5 0.7684 1.8440 ± 0.0292 1.379 ± 0.022 219.4 ± 3.5 KF-031605-2 36°52.58/117°15.75 393 30.0400 5 0.7556 0.6673 ± 0.0155 0.491 ± 0.011 76.9 ± 1.8 KF-031605-3 36°52.53/117°15.63 391 30.0000 5 0.7288 1.1220 ± 0.0221 0.797 ± 0.016 124.0 ± 2.4 KF-031605-4 36°52.57/117°15.59 398 30.0300 5 0.877 0.4678 ± 0.0178 0.399 ± 0.015 62.5 ± 2.4 KF-031605-5 36 52.55/117°15.51 399 30.0000 5 0.7602 0.6047 ± 0.0157 0.448 ± 0.012 70.0 ± 1.8 KF-031605-7 36°52.43/117°15.55 377 30.0100 5 0.7626 0.5615 ± 0.0231 0.417 ± 0.017 65.2 ± 2.7 KF-031605-8 36°52.37/117°15.50 372 30.0300 5 0.7605 0.6112 ± 0.0216 0.453 ± 0.016 70.8 ± 2.5 KF-031605-9 36°52.33/117°15.36 371 30.0500 5 0.7621 0.7415 ± 0.0209 0.550 ± 0.015 86.4 ± 2.4 KF-031605-10 36°52.27/117°15.34 361 30.0500 5 0.7586 0.6057 ± 0.0181 0.447 ± 0.013 69.9 ± 2.1 KF-RWC-03 36°52.20/117°15.20 355 30.0400 5 0.7615 0.5990 ± 0.0179 0.444 ± 0.013 69.4 ± 2.1 72 Table 3.2 Continued a A density of 2.7 g/cm 3 was used for the quartzite surface samples b Be carrier concentration = 437 μg/mL c Propagated uncertainties include error in the blank, carrier, and counting statistics. d Propagated error in the model ages include a 6% uncertainty in the production rate of 1 Be and 3% uncertainty in the 10 Be decay constant. Sample Location, latitude/longitude Altitude, m Quartz a , g Thickness, cm Be carrier b , g 10 Be/ 9 Be, 10-12 Measured 10 Be c , 10 6 atoms/g SiO 2 10 Be age d , ka Q2C-1 36°54.49/117°17.39 500 15.2900 5 0.9920 0.2837 ± 0.0921 0.538 ± 0.017 72.1 ± 2.3 Q2C-2 36°54.50/117°17.39 500 15.3855 5 0.9886 0.2224 ± 0.0817 0.418 ± 0.015 55.7 ± 2.0 Q2C-3 36°54.48/117°17.37 500 15.3095 5 0.9840 0.3235 ± 0.0101 0.608 ± 0.019 81.9 ± 2.5 Q2C-4 36°54.48/117°17.35 500 15.3363 5 0.9965 0.2549 ± 0.0984 0.484 ± 0.019 64.8 ± 2.5 Q2C-5 36°54.46/117°17.37 500 15.2311 5 0.9933 0.2439 ± 0.0827 0.465 ± 0.016 62.3 ± 2.1 Q2C-6 36°54.48/117°17.33 500 14.9566 5 0.9899 0.1416 ± 0.0219 0.274 ± 0.042 36.5 ± 5.6 73 3.5.2 Chlorine-36 Depth Profile Samples Previous cosmogenic depth profile geochronologic studies show that locally- sourced alluvial-fan deposits in Death Valley typically contain a large inherited component in measured cosmogenic nuclide inventories [Machette et al., 1999]. For this reason, three 36 Cl depth profiles were collected to (1) help determine the inherited signal in the Q2c surface and therefore, better define the age of deformed landforms along the NDVFZ, and (2) as a direct comparison of two independent cosmogenic nuclide geochronologic techniques. Cosmogenic 36 Cl is principally produced in carbonate rocks and calcic soils by four reactions: high-energy spallation of K and Ca, epithermal neutron absorption by Cl, and thermal neutron absorption by Cl [Gosse and Phillips, 2001]. Chlorine- 36 is also produced by muon-induced reactions, but the production rate in the top 2 m of alluvium is much less than for the reactions listed above [Gosse and Phillips, 2001]. The production rate at any depth below the surface by the first two reactions depends on the concentrations of the target elements and the high-energy cosmic-ray flux at that depth. The high-energy cosmic-ray flux decreases exponentially with the cumulative mass traversed by the cosmic rays. Thus, production by these reactions can be calculated based on measurement of the bulk densities in the soil column at each sample depth and the concentrations of K and Ca in the sample material (please see Appendix D). Production by low-energy neutron absorption depends on the low energy (thermal and epithermal) neutron fluxes and the Cl concentration (Table 3.3). 74 However, low-energy neutrons are produced by gradual deceleration of the high- energy flux and they can diffuse significant distances while in the epithermal-thermal energy range. The characteristics of the low-energy flux thus depend on bulk properties of the medium [Phillips et al., 2001]. A total of 16 carbonate-rich samples from three depth profiles were collected from natural exposures in alluvial channel walls incised into Q2c deposits at the Red Wall and Big Dip alluvial fans (Figure 3.4). Two depth profiles were collected from the Red Wall Canyon alluvial fan and one depth profile was collected from the correlative alluvial fan surface at Big Dip Canyon (Figures 3.5 and 3.6). The soil profile at Big Dip Canyon is consistent with the soils described on the Q2c surface at Red Wall Canyon by Klinger [2002]. We excavated into the channel walls at least one meter to reduce possible lateral cosmic-ray penetration (Figure 3.4). Approximately 150 clasts from the 5 to 15 mm grain size fraction were collected from the alluvium in 10- to 15-cm-thick sections distributed through the upper ~2 m of the alluvium, but below the Av horizon [Phillips et al., 2003]. Sampling intervals increased with depth below the surface; samples were more closely spaced in the upper one meter of the profile, where a higher concentration of the cosmogenic 36 Cl resides. The clasts were ground to find sand size and carefully mixed to ensure a homogeneous sample. 75 Table 3.3 Analytical Results of 36 Cl Geochronology Sample Location, latitude/longitude Elevation, m Topographic Shielding Factor Depth, m 36 Cl/Cl Cl, ppm Radiogenic 36 Cl, 10 18 atoms/g Cosmogenic 36 Cl, 10 5 atoms/g DV-14b 36°52.44/117°15.52 376 0.999 0.25 642 ± 12 77.79 1.32 8.5 ± 0.16 DV-14c - - 0.999 0.49 650 ± 12 93.80 1.59 10.0 ± 1.9 DV-14d - - 0.999 0.76 660 ± 13 79.77 1.35 8.9 ± 0.17 DV-14e - - 0.999 1.15 621 ± 21 95.67 1.62 9.8 ± 0.4 DV-14g - - 0.999 2.20 434 ± 15 67.14 1.14 5.0 ± 0.17 DV-15a 36°52.34/117°15.34 366 0.999 0.20 682 ± 20 104.00 1.77 12.0 ± 3.5 DV-15b - - 0.999 0.55 587 ± 22 86.46 1.47 8.4 ± 0.31 DV-15c - - 0.999 0.86 613 ± 23 57.95 0.98 5.9 ± 0.22 DV-15d - - 0.999 1.25 404 ± 13 78.96 1.34 5.3 ± 0.17 DV-15e - - 0.999 1.98 412 ± 12 102.24 1.74 7.0 ± 0.21 76 Table 3.3 Continued Sample Location, latitude/longitude Elevation, m Topographic Shielding Factor Depth, m 36 Cl/Cl Cl, ppm Radiogenic 36 Cl, 10 18 atoms/g Cosmogenic 36 Cl, 10 5 atoms/g NRWF-0 36°54.65/117°17.67 488 0.999 0.05 1740 ± 70 25.52 0.43 7.5 ± 0.30 NRWF-15 - - 0.999 0.15 1190 ± 29 49.19 0.84 9.9 ± 0.24 NRWF-35 - - 0.999 0.40 1110 ± 83 44.94 0.76 8.4 ± 0.63 NRWF-70 - - 0.999 0.75 896 ± 34 55.43 0.94 8.3 ± 0.32 NRWF- 120 - - 0.999 1.25 317 ± 150 31.47 0.53 1.6 ± 0.80 NRWF- 180 - - 0.999 1.85 883 ± 40 30.98 0.53 4.6 ± 0.21 77 Aliquots of the sample were sent to the New Mexico Bureau of Mines and Mineral Resources X-ray fluorescence laboratory for analysis of major elements and U and Th, and to the XRAL Laboratory in Ontario, Canada, for gamma-emission spectrometry analysis of B and Gd (please see Appendix D). Masses of the remaining sample material, ranging from 80 to 125 g, were dissolved to extract Cl using standard procedures [e.g., Zreda, 1994]. Samples were then sent to PRIME Lab at Purdue University for accelerator mass spectrometry analysis of the 36 Cl/Cl ratio and the 35 Cl/Cl ratio [Elmore et al., 1979]. The spreadsheet program CHLOE (CHLOrine-36 Exposure age) was used to calculate the 36 Cl/Cl ratio and Cl concentration of the samples based on the 36 Cl/Cl and 35 Cl/Cl analyses, sample mass, and mass of added 35 Cl carrier (Table 3.3; please see description of CHLOE in Appendix E) [Phillips and Plummer, 1996]. The soil age was determined by obtaining a best fit between a calculated 36 Cl inventory (as a function of depth) and the measured 36 Cl profile. The best-fit match was identified by minimization of the sum of the χ 2 values, computed from the differences between the calculated and measured values at each depth, for all of the samples in the profile. Uncertainties in the ages were also calculated from the χ 2 variation. The theoretical 36 Cl inventories with depth were calculated using CHLOE (please see Appendix E) [Phillips and Plummer, 1996]. Production parameters given in Phillips et al. [2001] and Stone et al. [1998] are used in the model. Use of 78 Table 3.4 36 Cl Best-Estimate Depositional Age, Depth-Profile Erosion Rate, Reduced-Sum-of- χ 2 , Assumed Erosion/Aggradation Rate Bounds, Equivalent Inheritance Age, and Source-Area Catchment-Wide Erosion Rate a Source area erosion rate not calculated for the Big Dip Canyon alluvial fan (sample NRWF). b Calculated assuming a bedrock density of 2.65 g/cm 3 . Erosion/aggradation limits Depth profile Deposition age, ka Profile erosion rate, g/cm 2 /ka χ υ 2 Lower limit, g/cm 2 /ka Upper limit, g/cm 2 /ka Inheritanc e age, ka Source area erosion rate, g/cm 2 /ka a Source area erosion rate, mm/ka b DV-14 65 +16/-10 -0.7 0.745 -0.7 0 59 ± 8 13 ± 2 46 ± 9 DV-15 55 +13/-16 0 0.12 -0.7 0 63 ± 8 23 ± 3 83 ± 10 NRWF 75 +18/-16 -0.35 3.97 -0.7 0 55 ± 20 79 alternative production parameters by Stone et al. [1996a; 1996b] would give ages that are younger by 18%. Using inferred soil histories based on soil descriptions [Klinger, 2002; Machette et al., in review] and the observed thickness of the A horizons, we estimated the amount of surface erosion or aggradation at each sampling site and used the cosmogenic 36 Cl concentrations in each depth profile to calculate maximum, minimum, and preferred surface erosion rates in mm/ka. The preferred erosion/aggradation rates range from 0 mm/ka (stable) to -0.7 mm/ka (7 cm of aggradation in 100 ka.; Table 3.4). In Table 3.4 we report the best-estimate depth profile ages with uncertainty bounds, best-estimate erosion rate associated with that age, the reduced sum of χ 2 (χ ν 2 ), the aggradation/erosion rate range employed in the analysis, the inheritance age (note that this reflects inheritance at the time of sampling, not deposition), and the calculated erosion rate in the source area. The two depth profiles from the Red Wall Canyon fan, DV-14 and DV-15, yielded ages of 65 +16/-10 ka. and 55 +13/-16 ka,, respectively. A single depth profile from the Big Dip Canyon fan produced an age of 75 +18/-16 ka. Two of the three profiles (DV-14 and DV-15) yield χ ν 2 values significantly less than one. These fits indicate that the CHLOE modeling approach is performing well in describing the cosmogenic nuclide accumulation processes and support the likelihood of a conservative bias in the uncertainty analysis. The third profile (NRWF) has a χ ν 2 of 3.97, largely due to the anomalous sample at 1.25 m depth. 80 In addition, we determined source-area erosion rates (i.e., the erosion rate in the mountain range from which the debris flows were derived) using the estimated inheritance of each profile. This assumes that the sediment in the profiles was derived directly from bedrock erosion in the source area catchment, without long- term storage in the drainage that could result in additional cosmogenic nuclide production during transit. The erosion rate was calculated using a weighted mean elevation/latitude scaling factor (S el ) derived by obtaining the hypsometry of the drainage basin upstream of the apex of the Red Wall Canyon alluvial fan from a 30- m-resolution DEM in ArcInfo and weighting the S el in each elevation class by its relative area. CHLOE was then used to calculate the steady-state erosion rate that would produce the observed inherited 36 Cl inventory for each profile. The calculated late Quaternary source-area catchment-wide erosion rates range from 46 ± 9 mm/ka to 83 ± 10 mm/ka and are somewhat slower than Holocene erosion rates estimated along the Black Mountains normal fault in central Death Valley (Table 3.4) [Frankel et al., 2004; Jayko, 2005]. 81 3.6 Discussion 3.6.1 Terrestrial Cosmogenic Nuclide Geochronology 3.6.1.1 Beryllium-10 Surface exposure dates for the Q2c surface obtained from 10 Be concentrations in quartzite clasts on two alluvial fans along the NDVFZ yield ages with a range of ~183 ka, from ~37 to 219 ka (Table 3.2). This relatively large variance is not surprising given that Machette et al. [1999; in review] report large inherited components of cosmogenic isotopes in other Death Valley alluvial fans. Nevertheless, this apparently disparate data set can be reconciled by plotting a probability density function of the distribution of ages (Figure 3.7). Based on visual inspection alone, one can pick out four peaks in the distribution shown by Figure 3.7C. The pronounced peak centered on ~70 ka is the most obvious and comprises 13 samples, 80% of those dated. Of the three outlying peaks, two are significantly older and one is somewhat younger. To the right of the main peak, two outliers exist, representing samples KF- 031605-1 and KF-031605-3. It is clear that these outlying samples have anomalously high concentrations of 10 Be. The elevated 10 Be concentrations likely result from an inherited cosmogenic signal possibly due to protracted exposure on hillslopes prior to being eroded or during transport. We feel these samples should therefore not be considered to reflect the age of this fan deposit. Similarly, to the left of the large peak an anomalously young sample is observed in Figure 3.7. We 82 hypothesize that there are several likely scenarios to explain the young age of this sample including the possibilities that the boulder may have been dislodged, broken, or rotated in such a way that different clast surface geometries were exposed to cosmic rays with the varnish, rubification and Av horizon subsequently re- established. Alternatively, the boulder may have been exhumed from beneath the surface by human or animal activity after the landform stabilized. Regardless, we feel this sample is not representative of the surface age, and therefore dismiss it. The highest peak in the probability density function in Figure 3.7 is used to represent the 10 Be age of the offset Q2c surface. The large cluster of ages centered on this peak suggests little or no inheritance in these samples. Based on 10 Be concentrations, the width of the distribution on either side of the highest probability not including the obvious outliers (i.e., ~50 ka and 92 ka), is considered to set a conservative bound on the uncertainty associated with the age of the surface (Figure 3.7). This corresponds to a 10 Be model age of 70 +22/-20 ka. This age is consistent with the 35 to 60 ka range estimated by Klinger [2001] on the basis of soil development and alluvial-fan morphology and the 180 to 120 ka ages of the stratigraphically older Lake Manly deposits [Ku et al., 1998]. 83 Figure 3.7 Probability density functions of the 10 Be ages from surface clasts, calculated using Isoplot [Ludwig, 2003]. A. Probability density function of the six ages determined for the correlative Q2c surface on the Big Dip Canyon alluvial fan. B. Probability density function of the ten ages for the Q2c surface on the Red Wall Canyon alluvial fan. C. Combined probability density function of all samples in A and B. The age of the Q2c surface based on the combined dates between 50 and 92 ka is 70 +22/-20 ka. 84 3.6.1.2 Chlorine-36 The 36 Cl age calculated from depth profiles beneath the offset Q2c surface are commensurate with the age determined by the cosmogenic 10 Be geochronology. The two depth profiles from the Red Wall Canyon alluvial fan (DV-14 and DV-15) yield ages of 65 +16/-10 ka and 55 +13/-16 ka (Figures 3.8A and 3.8B). Chlorine-36 inheritance of 59 ± 8 ka. and 63 ± 8 ka were removed from each profile, respectively in calculating the surface ages. The depth profile collected from Big Dip Canyon produced an age of 75 +18/-16 ka (Figure 3.8C). Approximately 55 ka of 36 Cl inheritance was removed from this depth profile. The 36 Cl model age for Q2c was determined by calculating a weighted mean of the three depth profiles. The uncertainty of the weighted mean age was taken to be the square-root of the geometric mean of the squared standard deviation uncertainties in each sample [Bevington and Robinson, 2003]. This allows us to account for a reduction in the uncertainty due to combining three sets of data. The resulting weighted mean 36 Cl model age of the three depth profiles on Q2c surface is 63 ± 8 ka. A weighted mean calculated using only the two Red Wall Canyon depth profiles (DV-14 and DV-15) produces a younger, but not significantly different, age of 60 ± 10 ka. 85 Figure 3.8 Normalized 36 Cl concentrations as a function of depth. A. Profile DV-14 from Red Wall Canyon alluvial fan. B. Profile DV-15 from Red Wall Canyon alluvial fan. C. Profile NRWF from Big Dip Canyon alluvial fan. The solid lines indicate the calculated best-fit profile and the dashed lines the calculated profiles for the 1 σ upper and lower bounding age estimates. t is the depositional age and ε the erosion/aggradation rate used to calculate the profiles. Positive values of ε represent erosion and negative values of ε represent aggradation. Note that although normalized concentration profiles are shown for purposes of illustration, the fitting was performed using actual measured concentrations and chemical compositions at each depth. See Appendix E for a detailed explanation of how ages were calculated from the depth profiles. Locations of the depth profiles are shown in Figures 3.5 and 3.6. 86 3.6.2 Comparison of 10 Be and 36 Cl Geochronology After the removal of inheritance from the 36 Cl depth profiles, the 63 ± 8 ka 36 Cl and 70 + 22/-20 ka 10 Be ages are in relatively good agreement. However, it is difficult to reconcile the large inherited component observed in the 36 Cl depth profile ages compared with the 10 Be surface ages, which have relatively minor inheritance. Although the processes governing the discrepancy in cosmogenic nuclide inventories between the 10 Be and 36 Cl samples are not well understood, we propose that a likely explanation for this disparity may reside in the greater than order of magnitude difference in sampled clast size [e.g., Brown et al., 1998; Matmon et al, 2003; Belmont et al., 2006]. For example, it is easy to imagine a scenario for the large cobbles and boulders where the time between hillslope exposure (if, in fact, the samples were exposed on the hillslope at all), erosion, transport, and deposition is short. In arid regions, like Death Valley, weathering-resistant lithologies produce steep slopes and large clasts in the source area [Harvey, 1997]. Both clasts that are exposed at the surface and those that have remained completely shielded would be transported from source to deposition in rapid, single events. In this case, clasts would be removed from hillslopes by advective (landsliding and non-linear creep) processes and transported by debris flows where the large clasts would remain intact and do not have time to undergo chemical or mechanical weathering before, or during, deposition. 87 Conversely, clasts collected from the sub-surface in the depth profiles are of considerably smaller grain size. These samples were likely exposed for long periods of time on hillslopes, as the relatively slow catchment-wide erosion rates suggest, where they would be exposed to increased chemical and mechanical weathering, resulting in grain by grain dissociation and slow, diffusive transport from hillslope to channel. Once in the channel network, these grains would be subject to the characteristic episodic precipitation of arid regions, which tends to generate steep rising-limb hydrographs with short lag times that result in high suspended load transport and reworking of sands and gravels from alluvial fan channels [Bull, 1991; Reid and Frostick, 1997]. The hypothesis that the fine-grained component of alluvial fan deposits contains large amounts of inherited cosmogenic nuclides is supported by 36 Cl measurements on modern alluvial-channel sands from four canyons on the west side of Death Valley by Machette et al. [in review]. These modern sand-fraction samples contained 36 Cl inheritance equivalent to 38 to 83 ka worth of exposure. Although Clapp et al. [2000; 2002] have previously suggested that no relationship exists between grain size and cosmogenic nuclide concentrations in arid environments, they did not take into account the wide range of grain sizes presented here. The significant differences in cosmogenic nuclide inventories between the two grain sizes analyzed in this study clearly reflect the underlying form and process of the arid-region alluvial fan erosion-deposition system. Additional work on this subject is obviously warranted and will, in all likelihood, improve our understanding 88 of denudation processes and interpretation of cosmogenic nuclide geochronologic data [e.g., Belmont et al., 2006]. 3.6.3 Fault Slip Rates The 10 Be and 36 Cl ages for the Q2c surface are, in effect, maximum ages for calculating slip rates because the channels used as piercing points must have developed after abandonment of the surface. Therefore, the ages provide a minimum slip rate estimate. The 10 Be ages are used as the maximum limiting age of the offset Q2c surface because these data are likely to have only a small amount of inheritance. The measured 297 ± 9 m offset of this surface over a 70 +22/-20 ka. time period yields a slip rate of 4.2 +1.9/-1.1 mm/yr. These data, therefore, provide a minimum slip rate for the NDVFZ. The age of the Q2c surface based on the weighted mean age of three 36 Cl depth profiles is taken to be a minimum bound on the age of the offset Q2c surface because we have been able to remove the inherited component from these samples. Using a minimum age of 63 ± 8 ka, the slip rate based on the cosmogenic 36 Cl geochronology is 4.7 +0.9/-0.6 mm/yr, which is in agreement with the slip rate derived from the 10 Be geochronology. The average of the two rates is 4.5 mm/yr. Using the bounding error limits for both rate calculations yields a 3.1 to 6.1 mm/yr (4.5 +1.6/-1.4 mm/yr) geologic slip rate for the NDVFZ at the Red Wall Canyon site. Because our slip rate is based on a single site along the NDVFZ we cannot address the potential for along-strike variations in slip rates in this region. However, we note that a number of previous studies indicate slip distributions are commonly 89 asymmetric, with the largest displacements often occurring near one end of the fault [e.g., Wesnousky, 1988; Ellis and Dunlap, 1988; Peacock and Sanderson, 1991; Cartwright and Mansfield, 1998; Maerten et al., 1999; Manighetti et al., 2001; Manighetti et al., 2005], and thus our study site is not necessarily located at the point of greatest cumulative displacement on the NDVFZ. Indeed, the long-term rate may increase to the north as slip is transferred from the Tin Mountain and Deep Springs faults onto the northern Death Valley and Fish Lake Valley fault zones (Figure 3.2) [e.g., Dixon et al., 1995]. Nevertheless, the slip rates derived from cosmogenic nuclide geochronology at Red Wall Canyon are consistent with the 3 to 9 mm/yr slip rate estimate of Klinger [2001] and with recent geodetic estimates of elastic strain accumulation on the Death Valley fault system [Bennett et al., 1997; Gan et al., 2000; Dixon et al., 2003; Wernicke et al., 2004]. We also note that the mid-range of our estimate of 4.5 mm/yr is <50% higher than the geodetic rate of 2.8 mm/yr suggested by McClusky et al. [2001] and Wernicke et al. [2004]. Our data, when combined with published rates on the other three major right-lateral faults (Owens Valley, Hunter Mountain, and Stateline) at the same latitude in this part of the ECSZ provides the first synoptic view of the cumulative slip rate across the ECSZ, north of the Garlock fault (Table 3.5; Figure 3.2). Oswald and Wesnousky [2002] report a right-lateral slip rate along the HMFZ of 3.3 to 4 mm/yr on the basis of 50 to 60 m of offset across a ~15 ka surface. Based on low-temperature thermochronologic data, Lee and Stockli [2006] suggest a similar 90 rate for the HMFZ since the Pliocene. We use 3.3 mm/yr for the HMFZ in this study because it provides us with a minimum slip rate for this fault. The OVFZ, site of the most recent major earthquake in the northern half of the Eastern California shear zone (M w ~7.6 in 1872), has a range of Holocene slip rates from 0.7 to 3.8 mm/yr [Lubetkin and Clark, 1988; Beanland and Clark, 1994; Lee et al., 2001b]. For this study, we use the 1.2 mm/yr slip rate for the OVFZ determined by Lee et al. [2001b] based on offset early Holocene channels dated by optically stimulated luminescence geochronology. This rate is close to the mean of the other rates reported for the OVFZ and is the only rate reported for the OVFZ where geochronologica age of the offset landform is known. We take the 1 mm/yr to be the best estimate for the geologic slip rate on the SLFZ [Schweickert and Lahren, 1997; Wernicke et al., 2004; Guest et al., 2005]. While Guest et al. [2005] report a post-mid-Miocene slip rate of ~2 mm/yr for the SLFZ, the subtle geomorphic expression of the fault in alluvial deposits suggests the late-Pleistocene to Holocene rate is somewhat lower. Summing the slip rates from the Owens Valley, Hunter Mountain, and Stateline fault zones with the slip rate determined for the NDVFZ in this study yields a total long-term geologic slip rate of 8.1 to 15.9 mm/yr across the northern ECSZ (Table 3.5; Figure 3.2). Using 1.2, 3.3, 4.5 and 1 mm/yr as the preferred slip rates for the OVFZ, HMFZ, NDVFZ, and SLFZ, respectively, the total geologic slip rate across the northern ECSZ at latitude ~37°N is 8.5 to 10 mm/yr (Table 3.5). Recent geodetic measurements suggest 9.3 ± 0.2 mm/yr of dextral shear across this region [Bennett et al., 2003], which is indistinguishable from our best-estimate of the 91 Table 3.5 Fault Slip Rates in the Northern Eastern California Shear Zone a This study; b Dixon et al., 1995; c Bennett et al., 1997; d Gan et al., 2000; e Miller et al., 2001; f McClusky et al., 2001; g Dixon et al., 2003; h Oswald and Wesnousky, 2002; i Lubetkin and Clark, 1988; j Beanland and Clark, 1994; k Lee et al., 2001; l Savage et al., 1990; m Savage and Lisowski, 1995; n Schweickert and Lahren, 1997; o Guest et al., 2005; p Wernicke et al., 2004; q Bennett et al., 2003. Fault Geologic Rate, mm/yr Time Period Method Used to Estimate Geologic Rate Geodetic Rate, mm/yr Northern Death Valley 3.1 - 6.1 a Late-Pleistocene Cosmogenic nuclides a 3 - 9.5 b-g Saline Valley-Hunter Mountain 3.3 - 4.0 h Late-Pleistocene Soil development h 1.7 - 4.9 b-g Owens Valley 0.7 - 3.8 i-k Late-Pleistocene to Holocene Optically stimulated luminescence k 1.8 - 8 b,c-g, l ,m Stateline 1 - 2 n, o Post-mid-Miocene Correlation of dated volcanic breccia o 0.9 - 1.4 p Northern ECSZ (range) 8.1 - 15.9 a Late-Pleistocene to present 7.4 - 23.8 b-g, l, m, p Northern ECSZ (best estimate) 8.5 - 10 a Late-Pleistocene to present 9.3 ± 0.2 q 92 geologic slip rate (Table 3.5). However, if we take our preferred geologic slip rate estimates for the OVFZ, HMFZ, and NDVFZ a strong skewing of the strain rate toward the east is predicted. This pattern is not observed in the geodetic data and may be the result of a secular slowing or transfer of strain from east to west across the region [e.g., Wernicke et al., 2005]. Alternatively, the effects of post-seismic processes, such as those resulting from the 1872 Owens Valley earthquake, could play a role in the observed pattern of elastic strain accumulation [Pollitz and Sacks, 1992; Dixon et al., 2003] The cosmogenic-nuclide geochronology and ALSM data presented here are fundamental for estimating a long-term geologic fault slip rate on the NDVFZ, an important piece to the slip rate “puzzle” in the northern ECSZ. A more quantitative estimate on the dextral motion of the HMFZ, in addition to the down-to-the- northwest extensional faults linking the strike-slip systems, would produce even tighter bounds on the long-term distribution of strain in this region. Even so, strain release in the northern ECSZ averaged over at least 50,000 to 100,000 years is consistent with the overall rate of strain accumulation as measured by short-term (5 to 10 years) geodetic data. However, the fact that the geologic estimates partition most of the strain (~85%) on to the HMFZ and NDVFZ does not agree with the relatively constant strain rate of 60 nstrain/yr measured across the entire ECSZ [Bennett et al., 2003], indicating that seismic cycle or other effects are at work. Although outside the scope of this study, questions still remain as to the spatial and 93 temporal constancy of strain accumulation and release along major strike-slip fault systems, such as the NDVFZ, and future work in the region should focus on this. 3.7 Implications for Eastern California Shear Zone Kinematics Strain accumulation and release appear to be relatively constant over a wide range of time scales on at least parts of the few major faults where sufficiently detailed geologic rate data are available, such as the central San Andreas fault [Sieh and Jahns, 1984; Argus and Gordon, 2001]. In contrast, rates of strain release during the past ~1500 years on other parts of the San Andreas system vary by a factor of four due to the accumulation of strain over multiple seismic cycles [Weldon et al., 2004]. Similarly, recent comparisons of geodetic and geologic rate data across the Mojave section of the ECSZ appear to indicate a pronounced strain transient. Specifically, the geodetic rates measured in the region (12 ± 2 mm/yr) are almost twice as fast as the longer-term geologic rates (on the order of ~5 to 7 mm/yr) [Dixon et al., 2000; Rockwell et al., 2000; McClusky et al., 2001; Peltzer et al., 2001; Oskin and Iriondo, 2004; Oskin et al., 2006; Oskin et al., 2007]. North of the Garlock fault, along the eastern margin of the ECSZ, continuous geodetic data from the Yucca Mountain area, Nevada, ~50 km NE of the NDVFZ, suggests that ~1 mm/yr of right-lateral shear across the area is not accommodated by any recognizable Quaternary structure [Wernicke et al., 2004]. In the north-central Basin and Range, some geodetic velocities across normal faults with late Holocene earthquakes indicate horizontal shortening, not extension [Wernicke et al., 2000; 94 Friedrich et al., 2004]. These studies serve to highlight the phenomenon of transient strain accumulation. The preferred sum of the geologic slip rates on the Owens Valley, Hunter Mountain, Stateline and northern Death Valley fault zones at latitude ~37° N is 8.5 to 10 mm/yr (Table 3.4). Geodetic data indicate a similar amount of dextral shear across this region of 9.3 ± 0.2 mm/yr over a ~5 year period (Table 3.5) [Bennett et al., 2003]. We note that our results indicate faster, long-term rates on the eastern faults in the study area. Previous geodetic studies report conflicting results when slip rates are modeled for individual faults in the northern ECSZ [Gan et al., 2000; Dixon et al., 2003]. Gan et al. [2000] suggest much faster rates on the western-most fault in the system, the Owens Valley fault zone, which appears to have a much slower long-term rate [Lee et al., 2001b]. Alternatively, Dixon et al. [2003] suggest the northern Death Valley fault zone accommodates the majority of slip in the region using a rate that is also much faster than the long-term geologic rate. The basic geodetic rate of 9.3 mm/yr across the entire ECSZ by Bennett et al. [2003] is robust; however, the details of individual faults are highly dependent on the model used to evaluate the geodetic data. Regardless, our results suggest that the transient strain accumulation proposed for the Mojave section of the ECSZ does not extend north of the Garlock fault. In the northern half of the eastern California shear zone, north of the Garlock fault and away from the zone of structural complexity in the Pacific-North America plate boundary, the far-field effect of the Big Bend of the San Andreas fault on strain 95 accumulation and release is dampened. As a result, strain is more simply accommodated by translation of the rigid Sierra Nevada block to the north with respect to the western Basin and Range province and stable North America [Argus and Gordon, 2001; Bennett et al., 2003]. Thus, the dextral component of plate boundary deformation in this region is partitioned among the Owens Valley, Hunter Mountain, northern Death Valley, and Stateline fault zones, which together accommodate ~20% of total Pacific-North America plate motion. 3.8 Conclusions Comparison of longer-term geologic rate data with short-term geodetic data illustrates that the average rate of strain storage and release over the past ~70 ka. is, within error, the same as the five-year rate of elastic strain accumulation in the northern half of the ECSZ. The agreement between the short- and long-term rates suggests that the transient strain accumulation observed in the Mojave Desert is not present north of the Garlock fault. Although our interpretation depends on the choice of individual geologic fault slip rates, given the limited data currently available this study provides the first synthesis of slip rates in the northern ECSZ. Clearly more long-term slip rate studies are needed to test our suppositions. Fault slip rates determined from 10 Be and 36 Cl cosmogenic geochronology on offset alluvial fans on the NDVFZ zone agree between the two independent cosmogenic geochronometers, yielding independent rates of 4.2 +1.9/-1.1 to 4.7 +0.9/-0.6 mm/yr, respectively. A summation of slip rates on the Owens Valley, 96 Hunter Mountain, northern Death Valley, and Stateline fault zones at latitude ~37° N implies that the long-term geologic slip rates across this region are similar to short- term geodetic rates over the northern ECSZ, both of which are ~9 mm/yr. However, the concentration of slip in the eastern portion of the shear zone on geological timescales is not consistent with the relatively constant strain rates measured from the eastern Sierra Nevada to Central Nevada. These data suggest that the current strain transient observed in the Mojave section of the ECSZ [Oskin and Iriondo, 2004] may be a localized feature, likely tied to the zone of structural complexity associated with the Big Bend of the San Andreas fault [e.g., Bartley et al., 1990; Nur et al., 1993; Du and Aydin, 1996; Li and Liu, 2006; Dolan et al., 2007], and may not be characteristic of the Pacific-North America plate boundary as a whole. 97 CHAPTER 4: Spatial variations in fault slip rate along the Death Valley-Fish Lake Valley fault zone determined from LiDAR topographic data and cosmogenic 10 Be geochronology Abstract The Death Valley-Fish Lake Valley fault zone (DV-FLVFZ) is a prominent dextral fault system in the eastern California shear zone (ECSZ). Combining offset measurements determined with LiDAR topographic data for two alluvial fans with terrestrial cosmogenic nuclide 10 Be ages from the fan surfaces yields late Pleistocene slip rates of ~2.5 mm/yr and ~3 mm/yr for the northern part of the DV-FLVFZ in Fish Lake Valley. These rates are slower than the late Pleistocene rate determined for the system in northern Death Valley, indicating that slip rates decrease northward along this major fault zone. When summed with the slip rate from the White Mountains fault, the other major fault in this part of the ECSZ our results suggest either that significant deformation is accommodated on structures east of Fish Lake Valley, or that rates of seismic strain accumulation and release have not remained constant over the late Pleistocene to Holocene. 4.1 Introduction The degree to which fault loading and strain release rates are constant in time and space is one of the most fundamental, unresolved issues in modern tectonics. In particular, data concerning the manner in which strain is distributed across plate boundaries in time and space are necessary to understand the complex behavior of 98 plate boundary fault systems and the lithospheric deformation that they accommodate. Such analyses require a comparison of slip rate data over a wide range of temporal and spatial scales. The Death Valley-Fish Lake Valley fault zone (DV-FLVFZ) is thought to accommodate most of the relative Pacific-North America plate motion east of the San Andreas fault (SAF; Figure 4.1). Although numerous geodetic campaigns have addressed issues of strain accumulation along this part of the plate boundary [e.g., Dixon et al., 1995; 2000; 2003; Bennett et al., 2003; references therein], only a few field-based studies have attempted to measure longer-term (1,000 to 100,000 year) geologic slip rates along this fault system [Brogan et al., 1991; Reheis and Sawyer, 1997; Frankel et al., 2007]. The relative scarcity of field-based studies utilizing quantitative geochronologic techniques to investigate deformational processes over millennial to million-year time scales has made it difficult to assess the behavior of the plate boundary in the region. Here, we use a multidisciplinary approach that encompasses analysis of high- resolution LiDAR digital topographic data combined with terrestrial cosmogenic nuclide (TCN) 10 Be geochronology to determine late Pleistocene slip rates along the northern part of the DV-FLVFZ in Fish Lake Valley. Our results reveal spatial variations in strain release rates along the DV-FLVFZ that have important implications for understanding the dynamics of Pacific-North America plate boundary deformation within the ECSZ. 99 Figure 4.1 Map of topography and Quaternary faults in the northern ECSZ. 1 = Red Wall Canyon alluvial fan. 2 = Furnace Creek alluvial fan (Figure 4.3). 3 = Indian Creek alluvial fan (Figure 4.5). GF = Garlock fault; BM = Black Mountains; DV = Death Valley; PM = Panamint Mountains; HMF = Panamint Valley-Hunter Mountain- Saline Valley fault zone; OVF = Owens Valley fault zone; DV-FLVF = Death Valley-Fish Lake Valley fault zone; IM = Inyo Mountains; GM = Grapevine Mountains; SLF = Stateline fault zone; EV = Eureka Valley; WMF = White Mountains fault zone; WM = White Mountains; EPF = Emigrant Peak fault zone; LV = Long Valley caldera; SR = Silver Peak Range; SPLM = Silver Peak-Lone Mountain extensional corridor. 100 4.2 Eastern California Shear Zone Kinematics The ECSZ and its northern continuation, the Walker Lane belt, extend for >800 km through the Mojave Desert and northward along the western edge of the Basin and Range. This system of predominantly right-lateral faults (Figure 4.1) is thought to accommodate 9.3 ± 0.2 mm/yr (~20%) of elastic strain accumulation along Pacific-North America plate boundary [Bennett et al., 2003]. Displacement from the Mojave segment of the ECSZ is funneled northward across the Garlock fault onto the Owens Valley, Panamint Valley-Hunter Mountain-Saline Valley, Death Valley-Fish Lake Valley, and Stateline fault zones (Figure 4.1). A number of northeast-trending faults transfer slip between the faults of Owens and Panamint Valleys and the Death Valley-Fish Lake Valley fault system (Figure 4.1) [Dixon et al., 1995; Reheis and Dixon, 1996; Lee et al., 2001a]. Farther north, dextral motion between the Sierra Nevada block and North America is focused on two faults bounding the White Mountains: the White Mountains fault zone (WMFZ) to the west and the DV-FLVFZ to the east. Modeling of GPS data suggests the DV-FLVZ is storing elastic strain at a rate of 4 to 10 mm/yr, while the WMFZ stores strain at 1 to 5 mm/yr [Dixon et al., 1995; 2000]. Thus, at latitude 37.5°N, geodetic data suggest that almost all plate-boundary deformation east of the SAF is accommodated on the WMFZ and northern part of the DV-FLVFZ. Due to the lack of numerical dates on offset alluvial landforms in most previous studies, long-term slip-rate estimates vary widely for the DV-FLVFZ in Fish Lake Valley. Estimates of late Pleistocene slip rates range from 1 to 9 mm/yr, 101 indicating that the DV-FLVFZ may accommodate almost none, to essentially all, of the deformation in the northern ECSZ over this time period [Reheis and Dixon, 1996; Reheis and Sawyer, 1997]. To the south, in northern Death Valley, TCN 10 Be and 36 Cl geochronology of the offset Red Wall Canyon alluvial fan yields a slip rate of ~4.5 mm/yr (Figure 4.1) [Frankel et al., 2007]. The right-lateral slip rate along the WMFZ, based on offset alluvial fans dated by TCN 36 Cl, is 0.3 to 0.4 mm/yr over late Pleistocene time scales [Kirby et al., 2006]. 4.3 LiDAR and Fault Displacement The use of high-resolution LiDAR digital topographic data to survey offset alluvial landforms along the DV-FLVFZ is a key part of this study. The LiDAR data were collected by the National Center for Airborne Laser Mapping. Individual data points were gridded at equally-spaced intervals to produce a digital elevation model (DEM) with 1 m horizontal resolution and 5 to 10 cm vertical accuracy [Shrestha et al., 1999]. The DEM was imported into ArcGIS where thalweg positions and hillshade, slope aspect, and topographic maps were derived from the LiDAR data. We used these data to precisely determine fault offsets at two sites along the northern part of the DV-FLVFZ (Figure 4.2). 4.3.1 Furnace Creek Offset The Furnace Creek alluvial fan in central Fish Lake Valley is offset right- laterally along two parallel strands of the DV-FLVFZ (Figures 4.1 and 4.3). 102 Figure 4.2 Hillshaded, bare-earth digital elevation models of the Furnace Creek and Indian Creek alluvial fans. A. Furnace Creek alluvial fan (location 2 in Figure 4.1). B. Indian Creek alluvial fan (location 3 in Figure 4.1). 103 Figure 4.3 Hillshaded geologic (A), slope aspect (C), and topographic (E) maps of the Furnace Creek alluvial fan from LiDAR data (location 2 in Figure 4.1). The Furnace Creek fan is retro- deformed 290 ± 20 m based on these data (B, D, and F). Hatched pattern indicates a fan surface of similar age, but set into the Qfio unit. Contour interval in E and F is 1 m. 104 Figure 4.4 Topographic profiles across the proximal, mid, and distal segments of the Furnace Creek alluvial fan. A. Location of topographic profiles. B. Topographic profiles showing dextral offset of channels and fan apex. Numbers indicate along-profile distance of prominent topographic features. C. Restored topographic profiles to their preferred pre-faulting configuration. Aligning the main channel in the fan complex yields 290 +/- 20 meters of offset since the late-Pleistocene. 105 Previous offset estimates for late Pleistocene alluvial fans along this segment of the fault range widely, from 111 m to >550 m [Brogan et al., 1991; Reheis et al., 1995 Reheis and Sawyer, 1997]. We used a prominent beheaded channel incised through the fan surface together with the morphology of the entire fan to reconstruct the offset Qfio deposit (Figure 4.3; unit Qfi of Reheis et al. [1995]). The hillshaded DEM image, topographic contour map, and channel thalwegs allowed us to accurately restore the offset channel (Figure 4.3). The slope aspect map aided in the reconstruction of the fan apex as well as the offset channel because it allowed us to highlight subtle topographic features by abrupt changes in slope direction (Figure 4.3). Based on these data, along with topographic profiles collected across the fan surfaces parallel to the fault (Figure 4.4), we determined the late Pleistocene strike-parallel displacement at Furnace Creek to be 290 ± 20 m. The uncertainty in this offset is based on the width of the offset channel. The LiDAR images in Figure 4.3, particularly the slope aspect map, show this is likely a unique solution to the displacement restoration at this site. 4.3.2 Indian Creek Offset Although the Indian Creek fan in northern Fish Lake Valley is deformed by multiple normal faults, the dextral component of offset is localized along a single strand (Figures 4.1 and 4.5). Late Pleistocene offset at this site was previously estimated at ~122 m, based on the offset of a single abandoned channel [Reheis et al., 1993; Reheis and Sawyer, 1997]. This published estimate appears to be an error. 106 Figure 4.5 Hillshaded geologic (A), slope aspect (C), and topographic (E) maps of the Indian Creek alluvial fan from LiDAR data (location 3 in Figure 4.1). The Indian Creek fan is retro- deformed 178 ± 20 m based on these data (B, D, and F). Contour interval in E and F is 1 m. 107 Retrodeformation of the Qfiy deposit (unit Qfi of Reheis et al. [1993]) on the Indian Creek fan based on the hillshade, slope aspect, and topographic maps, and channel thalwegs allowed us to restore at least four, and possibly six, offset channels incised through the fan surface, in addition to an abrupt change in fan slope direction (Figure 4.5). Using the average thalweg offsets of four prominent channels on the fan surface, including the channel used by Reheis et al. [1993] and Reheis and Sawyer [1997], we revise the late Pleistocene displacement at Indian Creek to 178 ± 20 m (Figure 4.5). While the standard deviation of the four offset measurements is only 7 m, we use a more conservative estimate of 20 m as the uncertainty in our offset measurement. 4.4 Alluvial Fan Geochronology We quantified the age of the Furnace Creek and Indian Creek alluvial fans by measuring the concentration of in-situ-produced TCN 10 Be in boulders on the fan surfaces [Lal, 1991; Gosse and Phillips, 2001]. Samples were collected from the top 2 to 5 cm of large boulders on stable parts of fan surfaces mapped as unit Qfi by Reheis et al. [1993; 1995] (Figure 4.6). The offset alluvial fans are characterized by subdued to moderately incised channels, well-developed desert pavement surrounding boulders, moderate to dark coatings of desert varnish on clasts, and a well-developed soil with a 5-to-10-cm-thick silty vesicular A horizon and an argillic B horizon with moderate clay film accumulation and stage II to III carbonate development [Reheis and Sawyer, 1997]. 108 Figure 4.6 Photograph looking west across the Furnace Creek alluvial fan. The White Mountains make up the distant sky-line ridge. Boulder in the foreground (sample KF-0418-5) is representative of locations from which samples were collected on the Furnace Creek and Indian Creek alluvial fans. Note the high degree of varnish development on the boulder surface. Boulders averaged ~115 x 90 x 85 cm in size at Furnace Creek and ~65 x 55 x 50 cm in size at Indian Creek. 109 We measured 10 Be/ 9 Be ratios for each sample by accelerator mass spectrometry at Lawrence Livermore National Laboratory. Sample ages were determined from 10 Be concentrations with the CRONUS-Earth on-line 10 Be- 26 Al exposure age calculator (version 1.1; http://hess.ess.washington.edu/math/), using 10 Be production rates based on Stone (Tables 4.1 and 4.2) [Stone, 2000]. 4.4.1 Furnace Creek Fan Age Nine TCN samples were collected from the offset Qfio surface on the Furnace Creek alluvial fan in central Fish Lake Valley (Figure 4.3). The nine samples range in age from 64 ± 5 ka to 112 ± 8 ka (Figure 4.7A; Table 4.1). Eight of the nine samples form a tight cluster of ages in the probability distribution in Figure 4.7A. The distribution of these eight samples is taken as evidence that the fan surface has remained relatively stable and that the samples have been exposed to cosmic radiation in their current configuration since deposition. The youngest sample is clearly an outlier (Figure 4.7A) and after reexamination of the sample location, we think this boulder was recently exhumed from the eroded southwestern edge of the alluvial fan. We therefore take the age of the fan to be the mean and standard deviation of the remaining eight samples, which yields an age of 94 ± 11 ka (Figure 4.7A). This age falls near the middle of the 50-130 ka age estimated by Reheis and Sawyer [1997] for the Furnace Creek fan on the basis of soil development and surface morphology. 110 Figure 4.7 Probability density functions of TCN 10 Be ages from the Furnace Creek and Indian Creek alluvial fans in Fish Lake Valley. A. Furnace Creek fan. Vertical grey bar represents the mean and standard deviation of the eight ages from the Qfio surface (Figure 4.3) that contribute to the main peak. B. Indian Creek fan. Vertical grey bar represents the mean and standard deviation of ages from the Qfiy surface (Figure 4.5). 111 Table 4.1 Analytical Results of Terrestrial Cosmogenic Nuclide 10 Be Geochronology for the Furnace Creek Alluvial Fan in Fish Lake Valley a A density of 2.7 g/cm 3 was used for the granitic surface samples. b Isotope ratios compared to ICN Pharmaceutical, Inc. 10 Be standards prepared by Nishiizumi et al. [2007] with a 10 Be half-life of 1.5x10 6 yrs. c Propagated uncertainties include error in the blank, carrier, and counting statistics. d Propagated error in the model ages include a 6% uncertainty in the 10Be production rate, 4% uncertainty in the 10Be decay constant, and 1% uncertainty in the carrier mass. e A mean 10Be blank concentration of 71,058 ± 45,650 atoms/g was used for samples FC-0805-1, FC-0805-3, FC-0805-4, FC-0805-7, and FC-0805-8; 147,668 ± 13,804 atoms/g was used for samples FC-0805-2, FC-0805-5, FC-0805-6, and KF-0418-5. f Beryllium-10 model ages were calculated with the CRONUS-Earth online 10Be-26Al exposure age calculator (version 1.1). g No geometric shielding correction for topography was necessary (horizon <20° in all directions). Sample number Location, latitude/longitude Altitude, m asl Quartz mass a , g Thickness, cm Mass of Be carrier, mg 10 Be/ 9 Be, 10 -13b Measured 10 Be c , 10 6 atoms/g SiO 2 10 Be model age d,e,f,g , ky FC-0805-1 37.5671°/-118.0110° 1648 10.0836 2 307.7 8.07 ± 0.33 1.64 ± 0.07 100.7 ± 8.3 FC-0805-2 37.5669°/-118.0108° 1650 10.0620 2 313.3 8.78 ± 0.21 1.81 ± 0.05 111.6 ± 8.4 FC-0805-3 37.5665°/-118.0109° 1653 10.0707 2 307.7 5.20 ± 0.10 1.05 ± 0.02 64.3 ± 4.7 FC-0805-4 37.5675°/-118.0089° 1626 10.1009 2 307.3 6.23 ± 0.43 1.26 ± 0.88 78.7 ± 7.8 FC-0805-5 37.5569°/-118.0081° 1624 10.0753 2 312.4 6.54 ± 0.15 1.34 ± 0.10 83.8 ± 8.4 FC-0805-6 37.5671°/-118.0083° 1626 10.0876 2 314.6 7.23 ± 0.20 1.49 ± 0.04 93.5 ± 7.1 FC-0805-7 37.5685°/-118.0080° 1617 9.9989 2 308.3 6.73 ± 0.17 1.38 ± 0.04 86.4 ± 6.5 FC-0805-8 37.5676°/-118.0071° 1620 9.9978 2 307.8 8.03 ± 0.16 1.65 ± 0.04 103.7 ± 7.6 KF-0418-5 37.5662°/-118.0014° 1593 10.0649 2 314.5 7.34 ± 0.18 1.52 ± 0.04 97.4 ± 7.3 112 Table 4.2 Analytical Results of Terrestrial Cosmogenic Nuclide 10 Be Geochronology for the Indian Creek Alluvial Fan in Fish Lake Valley a A density of 2.7 g/cm 3 was used for the granitic surface samples. b Isotope ratios compared to ICN Pharmaceutical, Inc. 10 Be standards prepared by Nishiizumi et al. [2007] with a 10 Be half-life of 1.5x10 6 yrs. c Propagated uncertainties include error in the blank, carrier, and counting statistics. d Propagated error in the model ages include a 6% uncertainty in the 10Be production rate, 4% uncertainty in the 10Be decay constant, and 1% uncertainty in the carrier mass. e A mean 10Be blank concentration of 71,058 ± 45,650 atoms/g was used for samples KF-1023-1, KF-1023-2, KF-1023-4, KF-1023-5; 147,668 ± 13,804 atoms/g was used for samples KF-0418-6, KF-0418-7, and KF-0418-8. f Beryllium-10 model ages were calculated with the CRONUS-Earth online 10Be-26Al exposure age calculator (version 1.1). g No geometric shielding correction for topography was necessary (horizon <20° in all directions). Sample number Location, latitude/longitude Altitude, m asl Quartz mass a , g Thickness, cm Mass of Be carrier, mg 10 Be/ 9 Be, 10 -13b Measured 10 Be c , 10 6 atoms/g SiO 2 10 Be model age d,e,f,g , ky KF-1023-1 37.7850°/-118.1800° 1835 10.0435 5 324.3 5.44 ± 0.14 1.17 ± 0.03 63.3 ± 4.7 KF-1023-2 37.7852°/-118.1799° 1834 10.0067 5 317.7 5.84 ± 0.15 1.23 ± 0.03 66.8 ± 5.0 KF-1023-3 37.7853°/-118.1806° 1797 10.0388 5 309.0 7.30 ± 0.18 1.37 ± 0.04 74.5 ± 5.6 KF-1023-4 37.7845°/-118.1769° 1797 10.1012 5 310.0 6.70 ± 0.19 1.49 ± 0.04 81.2 ± 6.1 KF-1023-5 37.7841°/-118.1763° 1794 10.0804 5 310.9 5.34 ± 0.14 1.09 ± 0.03 59.2 ± 4.4 KF-0418-6 37.7854°/-118.1830° 1854 10.0740 2 311.7 7.08 ± 0.18 1.45 ± 0.04 77.4 ± 5.8 KF-0418-7 37.7851°/-118.1819° 1847 10.0231 2 314.9 6.69 ± 0.17 1.39 ± 0.04 73.8 ± 5.5 KF-0418-8 37.7870°/-118.1823° 1848 10.0681 2 312.1 6.89 ± 0.25 1.41 ± 0.05 74.9 ± 6.0 113 4.4.2 Indian Creek Fan Age At the Indian Creek alluvial fan we collected eight TCN samples from the displaced Qfiy surface (Figure 4.5). The samples range in age from 59 ± 4 ka to 81 ± 6 ka (Figure 4.7B; Table 4.2). Although somewhat younger, the samples from Indian Creek exhibit a strong, single peak similar to the Furnace Creek data, as shown in the probability distribution in Figure 4.7B. As with the Furnace Creek samples, we take this to indicate that the boulders share a similar exposure history and have remained at the surface in their present geometry since deposition. The relatively tight cluster of ages yields a mean age and standard deviation of 71 ± 8 ka, which we take as the age of the Indian Creek alluvial fan (Figure 4.7B). This age agrees well with the previously reported age of 50-130 ka estimated on the basis of soil development and surface morphology [Reheis and Sawyer, 1997]. 4.5 Fault Slip Rates The TCN 10 Be exposure ages from the surfaces of the Furnace Creek and Indian Creek alluvial fans are interpreted to be maximum ages with regard to calculating slip rates because the incised, offset channels must have formed at some unconstrained time after deposition. In addition, our rates do not take into account deformation related to extensional faulting along the western White Mountains piedmont. As such, the slip rates reported here should be interpreted as minima, although we are confident that we have captured nearly all of the right-lateral displacement along the fault zone. 114 Combining the 290 ± 20 m of offset at Furnace Creek with the 94 ± 11 ka age of the offset Qfio surface yields a slip rate of 3.1 ± 0.4 mm/yr in central Fish Lake Valley. This rate is within the broad range of 1.5 to 9.3 mm/yr estimated by Reheis and Sawyer [1997] for this site. A slightly slower slip rate of 2.5 ± 0.4 mm/yr results from the 178 ± 20 m offset of a 71 ± 8 ka old surface at Indian Creek in northern Fish Lake Valley. Previous slip rate estimates at this site ranged from 1.1 to 3.3 mm/yr [Reheis and Sawyer, 1997]. 4.6 Implications for ECSZ Strain Distribution Previous work suggests that as strain is transferred from the Owens Valley and Panamint Valley-Hunter Mountain-Saline Valley faults, via down-to-the- northwest normal faults, into Fish Lake Valley, rates of deformation should increase on the NW-trending, northern DV-FLVFZ [Dixon et al., 1995; 2000; Reheis and Dixon, 1996; Lee et al., 2001a]. In contrast, our results show that slip rates on the DV-FLVFZ actually decrease northward. The geologic rate for the DV-FLVFZ from the dextrally offset Red Wall Canyon fan in northern Death Valley, measured over a similar time scale, is ~4.5 mm/yr [Frankel et al., 2007]. To the north, at the Furnace Creek fan in central Fish Lake Valley, this rate slows to ~3 mm/yr and decreases further yet, to ~2.5 mm/yr, at the Indian Creek site in northern Fish Lake Valley Moreover, taking into account the 0.3 to 0.4 mm/yr late Pleistocene right- lateral slip rate of the WMFZ [Kirby et al., 2006], the total long-term rate of 115 deformation accommodated by the two major faults at ~37.5°N is less than 4 mm/yr of the 9.3 ± 0.2 mm/yr region-wide rate of dextral shear determined from geodesy [Bennett et al., 2003]. This implies either that: (1) deformation is accommodated by structures other than the DV-FLVFZ and WMFZ if strain rates have remained constant since the late Pleistocene, as suggested for this part of the ECSZ [Frankel et al., 2007]; or (2) the region is currently experiencing a strain transient similar to that in the Mojave segment of the ECSZ [e.g., Oskin and Iriondo, 2004]. If strain rates have remained constant during the late Pleistocene and Holocene, then approximately half of the total strain budget in the northern ECSZ must be accommodated off of the two main faults, most likely east of Fish Lake Valley. Oldow et al. [1994] and Petronis et al. [2002] demonstrated that faults east of Fish Lake Valley (Figure 4.1) acted as extensional transfer zones and accommodated vertical axis block rotation between the nascent DV-FLVFZ and Walker Lane from the mid-Miocene through the Pliocene. Our results suggest these structures may still play an important role in accommodating strain transfer from the ECSZ to the active faults of the Walker Lane in western Nevada. In particular, the ~2.5 mm/yr rate from the Indian Creek fan implies that the Emigrant Peak fault accommodates ≥0.5 mm/yr of elastic strain, in agreement with the late Pleistocene rate of 0.4 to 1.3 mm/yr estimated for this fault [Reheis and Sawyer, 1997]. If true, the ECSZ-Walker Lane transition zone must begin south of the Mina deflection, from the Emigrant Peak fault zone through the Silver Peak-Lone Mountain extensional corridor [Oldow et al., 1994] in a broader, more diffuse zone 116 than previously recognized (Figure 4.1). As the ECSZ and Walker Lane become better organized parts of the Pacific-North America plate boundary, strain may localize on individual structures such as the DV-FLVFZ in Fish Lake Valley and the WMFZ in Owens Valley [e.g., Faulds et al., 2005; Wesnousky, 2005]. It appears, however, that since at least the late Pleistocene, and likely earlier, the northernmost part of the ECSZ may have accommodated deformation in a zone spanning a width of >100 km from Owens Valley in the west to the western margin of the Great Basin east of Fish Lake Valley. Our results document the first well-defined spatial slip rate variations along a major fault in the ECSZ and as such, have important implications for understanding along-strike changes on other faults, both within the ECSZ and elsewhere. 117 CHAPTER 5: Conclusions 5.1 Summary I have exploited the high resolution of airborne laser swath mapping (ALSM) digital topography together with terrestrial cosmogenic nuclide (TCN) geochronology to quantify the rates and processes of alluvial landform evolution and late Pleistocene tectonic activity along the Death Valley-Fish Lake Valley fault zone (DV-FLVFZ) in the northern eastern California shear zone (ECSZ). The results of my work have led to a better understanding of both arid-region geomorphic processes and temporal and spatial patterns of elastic strain accumulation and release along the Pacific-North America plate boundary. The following discussion summarizes the results of the three main chapters of this dissertation. 5.2 Arid-Region Alluvial Landform Evolution By calculating surface roughness from ALSM digital elevation data sets I was able to show that individual lithostratigraphic units in Death Valley can be differentiated at the 99% confidence level on the basis of this topographic metric. Moreover, the surface roughness measurements reveal a time-dependent evolution of fan morphology that has previously only been described through qualitative field observations. Specifically, the surfaces of alluvial fans decrease in roughness with time, eventually becoming smooth, planar landforms. This smoothing occurs over a period of ≤ 70,000 years in the arid environment of Death Valley. As the alluvial fans continue to evolve, the once stable landform configurations eventually erode 118 into convex hillslope systems. Once this happens, surface roughness increases with age as tributary channel incision dissects the formerly smooth surface. These results demonstrate that diagnostic morphologic features commonly observed on alluvial deposits can be quantified with high-resolution digital topographic data. This methodology will be a useful aid in the objective identification, mapping, and interpretation of alluvial landforms during future studies utilizing high-resolution digital topographic data sets. 5.3 Constancy of Seismic Strain Release Integrating ALSM digital topographic data with TCN dating also allowed my colleagues and me to determine the first geochronologically constrained fault slip rate for the northern Death Valley fault zone (NDVFZ). The ALSM data revealed 297 ± 9 m of late Pleistocene displacement on the fault system. Combining this offset measurement with ages determined by cosmogenic 10 Be and 36 Cl geochronology from the offset Red Wall Canyon and Big Dip canyon alluvial fans yields a late Pleistocene slip rate of ~4.5 mm/yr for the NDVFZ. Summing this rate with slip rates on the Owens Valley [Lee et al., 2001b], Hunter Mountain [Oswald and Wesnousky, 2002], and Stateline [Guest et al., 2005] fault zones at latitude ~37° N implies that the long-term geologic slip rates across this region are similar to short-term geodetic rates across the northern ECSZ, both of which are ~9 to 10 mm/yr. Although this interpretation depends on the choice of individual geologic fault slip rates, given the data currently available, this study 119 provides the first synthesis of slip rates over late Holocene to late Pleistocene time scales in the northern ECSZ. Furthermore, these data suggest that the current strain transient observed in the Mojave section of the ECSZ [Oskin and Iriondo, 2004] may be a localized feature. It is likely that the strain transient in the southern ECSZ is tied to the zone of structural complexity associated with the Big Bend of the San Andreas fault [e.g., Bartley et al., 1990; Nur et al., 1993; Du and Aydin, 1996; Li and Liu, 2006; Dolan et al., in review], and is not characteristic of the Pacific-North America plate boundary as a whole. 5.4 Spatial Variations in Slip Rate Additional displacement measurements from ALSM data and TCN 10 Be ages from offset alluvial fans in Fish Lake Valley suggest that slip rates on the DV- FLVFZ decrease northward. The late Pleistocene geologic rate for the DV-FLVFZ slows from ~4.5 mm/yr in northern Death Valley [Frankel et al., 2007] to ~3 mm/yr at the offset Furnace Creek fan in central Fish Lake Valley and decreases to ~2.5 mm/yr at the offset Indian Creek alluvial fan in northern Fish Lake Valley. Taking into account the 0.3 to 0.4 mm/yr late Pleistocene slip rate of the White Mountains fault zone (WMFZ) [Kirby et al., 2006], the deformation accommodated by the two major faults at ~37.5°N is less than 4 mm/yr of the 9.3 ± 0.2 mm/yr region-wide geodetic rate of dextral shear [Bennett et al., 2003]. If rates of elastic strain accumulation and release have remained constant, this implies either that deformation is accommodated by structures other than the Death Valley-Fish Lake 120 Valley and White Mountains fault zones or that a strain transient, similar to that in the Mojave segment of the ECSZ [e.g., Oskin and Iriondo, 2004], is present in the region. 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The D-statistic in the Kolmogorov-Smirnov test is the maximum difference between the cumulative frequency distributions of two sample populations (Equation 2.5). Plots A through G show comparisons of units adjacent to each other in age. Plots H and I show the relationship between units with similar mean surface roughness values but with significant differences in relative age (Figure 2.8). A. Q2a vs. Q2b. B. Q2b vs. Q2c. C. Q2c vs. Q3a. D. Q3a vs. Q3b. E. Q3b vs. Q3c. F. Q3c vs. Q4a. G. Q4a vs. Q4b. H. Q2a vs. Q3b. I. Q2b vs. Q3a. See Chapter 2 and Table 2.1 for descriptions of each unit. 138 APPENDIX B: Faults of the Northern Eastern California Shear Zone B1. Owens Valley Fault Zone In the west, the strike-slip component of motion through Owens Valley is accommodated by the Owens Valley fault zone (OVFZ), which last ruptured during the 1872 M w ~7.6 Owens Valley earthquake, and its northern continuation, the White Mountains fault system [Lubetkin and Clark, 1988; Beanland and Clark, 1994]. The last major seismic event along the White Mountains fault zone was a swarm in 1986 that included M w 5.7 and M w 6.3 earthquakes in Chalfant Valley [Smith and Priestly, 2000]. Geologic slip rate estimates of the OVFZ range from 0.7 to 3.8 mm/yr [Lubetkin and Clark, 1988; Beanland and Clark, 1994; Lee et al., 2001a]. Geologic rates on the White Mountains fault zone are similar to the OVFZ, ranging from 0.7 - 2.8 mm/yr [dePolo, 1989; Schroeder, 2003]. Geodetic rates for the OVFZ are higher, but vary dramatically. Studies using an elastic half-space model estimate rates of 4.1 - 8 mm/yr [Savage et al., 1990; Savage and Lisowski, 1995; Dixon et al., 1995; Dixon et al., 2000; Gan et al., 2000; Miller et al., 2001; McClusky et al., 2001]. In contrast, Dixon et al. [2003] used an elastic-viscoelastic half-space model to calculate a geodetic rate of 2.1 ± 0.3 mm/yr, which agrees better with the geologic data. B2. Panamint Valley, Ash Hill, and Hunter Mountain Fault Zones East of Owens Valley, the Ash Hill and Panamint Valley fault zones accommodate slip in Panamint Valley. These fault zones transfer slip northward to 139 the Hunter Mountain-Saline Valley fault zone (HMFZ). The Ash Hill fault zone, which extends for ~50 km along the west side of Panamint Valley, has a geologic slip rate of 0.3 - 0.5 mm/yr based on the offset of putative mid- to late-Pleistocene (~125 - 150 ka) pluvial lake shorelines and a ~4 Ma basalt flow [Densmore and Anderson, 1997]. The oblique dextral-normal Panamint Valley fault zone bounds the entire eastern piedmont of Panamint Valley. On the basis of measured Holocene alluvial fan offsets, Zhang et al. [1990] calculated a strike-slip rate of 2.4 ± 0.8 mm/yr. This rate, when combined with the dextral slip rate on the adjacent Ash Hill fault, is slightly slower than the 15 ka rate of 3.3 to 4.0 mm/yr estimated for the HMFZ to the north, which is responsible for transferring slip from Panamint Valley into Saline Valley [Oswald and Wesnousky, 2002]. Sternloff [1988] measured a 1.2 Ma rate of 3.2 - 3.4 mm/yr for the HMFZ, whereas Burchfiel et al. [1987] and Sternloff [1988] measured a slower, longer-term rate of 1.3 - 2.3 mm/yr on the basis of an offset 4.6 Ma basalt flow. B3. Stateline Fault Zone Still farther east, the Stateline fault system (SLFZ) along the Nevada- California border extends north through Mesquite and Pahrump Valleys to a complex transfer zone in the Amargosa Valley, finally trending to the north-northwest toward the Yucca Mountain area as a diffuse zone of faults (Figure 3.2) [Schweickert and Lahren, 1997; Guest et al., 2005]. The SLFZ forms a >90-km-long system of NW- trending fault scarps with associated pressure ridges and sag ponds [Guest et al., 140 2005]. On either side of the Quaternary scarps in Mesquite Valley, the fault offsets a 12.6 Ma volcanic breccia deposit 28 ± 3 km, yielding a post-mid-Miocene average slip rate of 2.2 ± 0.2 mm/yr [Guest et al., 2005]. Northwestward in the Amargosa Valley area, a simple through-going fault in Quaternary deposits is not observed, however diffuse faulting, aligned springs and other lines of evidence led Schweickert and Lahren [1997] to suggest an active fault with 1 to 2 mm/yr of slip may be present. Data from a dense, continuous GPS network across the Amargosa Valley/Yucca Mountain region indicate a zone of N20W right-lateral shear of 1.2 ± 0.2 mm/yr is present, with strain focused just east of Yucca Mountain [Wernicke et al., 2004]. Simple dislocation models of these data that include both the Stateline structure and the NDVFZ suggest geodetically determined slip rates of 0.9 mm/yr and 2.8 mm/yr, respectively [Wernicke et al., 2004], although other, more complex models involving seismic cycle effects are clearly possible [e.g., LaFemina et al., 2005; Schmalzle et al., 2005]. B4. Dip-Slip Transfer Faults In addition to the major north-trending dextral faults, a number of northeast- trending faults transfer slip between faults of the Owens and Panamint Valley fault systems and the Death Valley fault system (Figure 3.2) [Dixon et al., 1995]. These predominantly down-to-the-northwest extensional faults include the Deep Springs, Towne Pass, and Tin Mountain faults [Dixon et al., 1995; Lee et al., 2001b; Klinger, 2001]. Geologic slip rates are poorly defined for most of these structures, with the 141 exception of the Deep Springs fault, where Lee et al. [2001b] measured an extension rate of 0.2 - 0.7 mm/yr. Long-term slip rates of 3.2 - 3.4 mm/yr have been estimated for a complex system of normal faults cutting basalt flows along the northeast side of Saline Valley (Figure 3.2) [Sternloff, 1988]. References Beanland, S., and M.M. Clark (1994), The Owens Valley fault zone, eastern California, and surface faulting associated with the 1872 earthquake, U. S. Geological Survey Bulletin 1982, 29 pp. Burchfiel, B.C., K.V. Hodges, and L.H. Royden (1987), Geology of Panamint Valley - Saline Valley pull-apart system, California: Palinspastic evidence for low- angle geometry of a Neogene range-bounding fault, Journal of Geophysical Research, 92, 10,422-10,426. dePolo, C.M. (1989), Seismotectonics of the White Mountain fault system, eastern California and western Nevada, M.S. Thesis, 354 pp., University of Nevada, Reno. Densmore, A.L., and R.S. Anderson (1997), Tectonic geomorphology of the Ash Hill fault, Panamint Valley, California, Basin Research, 9, 53-63. Dixon, T.H., S. Robaudo, J. Lee, M.C. Reheis (1995), Constraints on present-day Basin and Range deformation from space geodesy, Tectonics, 14, 755-772. Dixon, T. H., M. Miller, F. Farina, H. Wang, and D. Johnson (2000), Present-day motion of the Sierra Nevada block and some tectonic implications for the basin and Range province, North American Cordillera, Tectonics, 19, 1-24. Dixon, T.H., E. Norabuena, and L. Hotaling (2003), Paleoseismology and global positioning system: Earthquake-cycle effects and geodetic versus geologic fault slip rates in the Eastern California shear zone, Geology, 31, 55-58. Gan, W., J.L. Svarc, J.C. Savage, and W.H. Prescott (2000), Strain accumulation across the eastern California shear zone at latitude 36°30’N, Journal of Geophysical Research, 105, 16,229-16,236. 142 Guest, B., N. Niemi, and B. Wernicke (2005), A measure of post-mid-Miocene offset on the Stateline fault, California and Nevada, Geological Society of America Annual Meeting Abstracts, 36, Abstract 122-13. Klinger, R.E. (2001), Stop A3: Evidence for large dextral offset near Red Wall Canyon, in Quaternary and late Pliocene geology of the Death Valley region: Recent observations on tectonic, stratigraphy, and lake cycles, edited by Machette, M.N., Johnson, M.L., and Slate, J.L., Open File Report 01-51 U.S. Geological Survey, A32-A37. LaFemina, P., G. Schmalzle, T. Dixon, and J. Oldow (2005), Strain partitioning across the eastern California shear zone, Geological Society of America Annual Meeting Abstracts, 36, Abstract 122-11. Lee, J., J.Q. Spencer, and L.A. Owen (2001a). Holocene slip rates along the Owens Valley fault, California: Implications for the recent evolution of the Eastern California Shear Zone, Geology, 29, 819–822. Lee, J., C.M. Rubin, and A. Calvert (2001b), Quaternary faulting history along the Deep Springs fault, California, Geological Society of America Bulletin, 113, 855-869. Lubetkin, L., and M.M. Clark (1988), Late Quaternary activity along the Lone Pine fault, eastern California, Geological Society of America Bulletin, 79, 509- 512. McClusky, S.C., S.C. Bjornstad, B.H. Hager, R.W. King, B.J. Meade, M.M. Miller, F.C. Monastero, and B.J. Souter (2001), Present day kinematics of the Eastern California Shear Zone from a geodetically constrained block model, Geophysical Research Letters, 28, 3369-3372. Miller, M.M., D.J. Johnson, T.H. Dixon, and R.K. Dokka (2001), Refined kinematics of the eastern California shear zone from GPS observations, 1993-1994, Journal of Geophysical Research, 106, 2245-2263. Oswald, J.A., and S.G. Wesnousky (2002), Neotectonics and Quaternary geology of the Hunter Mountain fault zone and Saline Valley region, southeastern California, Geomorphology, 42, 255-278. Savage, J.C., and M. Lisowski (1995), Strain accumulation in Owens Valley, California, Bulletin of the Seismological Society of America, 85, 151-158. Savage, J. C., M. Lisowski, and W.H. Prescott (1990), An apparent shear zone trending north-northwest across the Mojave Desert into Owens Valley, Geophysical Research Letters, 17, 2113-2116. 143 Schmalzle, G.M., P. La Femina, T. Dixon, R. Malservisi, R. Govers, and J. Oldow (2005), Strain patterns across the eastern California shear zone, EOS Transactions, American Geophysical Union Fall Meeting Supplement, 86, Abstract G21B-1281. Schroeder, J. (2003), Quaternary fault slip history of the White Mountains fault zone, California, M.S. Thesis, 62 pp., Central Washington University, Ellensburg. Schweickert, R.A., and M.M. Lahren (1997), Strike-slip fault system in Armagosa Valley and Yucca Mountain, Nevada, Tectonophysics, 272, 25-41. Smith, K.D., and K.F. Priestly (2000), Faulting in the 1986 Chalfant, California, sequence: Local tectonics and earthquake source parameters, Bulletin of the Seismological Society of America, 90, 813-831. Sternloff, K.R. (1988), Structural style and kinematic history of the active Panamint- Saline extensional system, Inyo County, California, M.S. Thesis, 30 pp., Massachusetts Institute of Technology, Cambridge. Wernicke, B., J.L. Davis, R.A. Bennett, J.E. Normandeau, A.M. Friederich, and N.A. Niemi (2004), Tectonic implications of a dense continuous GPS velocity field at Yucca Mountain, Nevada, Journal of Geophysical Research, 109, 10.1029/2003JB002832. Zhang, P., M. Ellis, D.B. Slemmons, and F. Mao (1990), Right-lateral displacements and the Holocene slip rate associated with prehistoric earthquakes along the southern Panamint Valley fault zone: Implications for southern Basin and Range tectonics and coastal California deformation, Journal of Geophysical Research, 95, 4857-4872. 144 APPENDIX C: Terrestrial Cosmogenic Nuclide Geochronology Methods C1. Terrestrial Cosmogenic Nuclide Geochronology The concentration of a cosmogenic nuclide in a sample exposed at or beneath an unstable geomorphic surface is given by: N m (Z,t,ε) = S el S T S s J q ε Λ () q + λ m exp − Z 0 −εt Λ () q ⎛ ⎝ ⎜ ⎜ ⎞ ⎠ ⎟ ⎟ − exp −λ m t − Z 0 Λ () q ⎛ ⎝ ⎜ ⎜ ⎞ ⎠ ⎟ ⎟ + N inh ⎡ ⎣ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ q ∑ (C1), where N(Z,t,ε) is the concentration of a cosmogenic nuclide at depth Z, time t, and erosion rate ε. S el , S T , and S s are the scaling factors for elevation/latitude, topographic obstruction of the cosmic-ray flux, and surface coverage (e.g., snow, sand), respectively. λ m is the decay constant of the nuclide of interest, ε is the erosion rate of the exposed surface, J q and ( Λ) q are the production terms and attenuation lengths for the four principal production reactions: fast neutron (spallation) reactions, epithermal neutron absorption, thermal neutron absorption, and muon-induced reactions. The production terms and corresponding attenuation lengths are specified by equations 3.83 to 3.90 in Gosse and Phillips [2001]. N inh is the inherited cosmogenic nuclide inventory, in other words, the cosmogenic nuclide concentration incorporated in the material at the time of deposition. In alluvial sediments, such as those investigated in this study, this inherited component usually arises from exposure to cosmic rays during weathering at the primary outcrop and transport to the site of deposition. 145 C2. Cosmogenic Nuclide Depth Profiles The distinction between the in situ and inherited components in a depth profile can be accomplished because the inherited signature should be relatively uniform through a depth profile in any single depositional unit that has experienced steady tectonic and climatic forcing over the duration of deposition. On the other hand, the in situ component should vary with a characteristic quasi-exponential decrease in concentration with depth. The rate at which nuclide production decreases is a function of the density of the material through which the cosmic rays are passing. In general, production rates decrease by 1/e for every ~160 g/cm 2 increase in depth. This absorption length is equivalent to about 80 cm in arid-zone fans. Therefore, by ~2 m depth, production of cosmogenic nuclides is negligible [Hancock et al., 1999; Gosse and Phillips, 2001]. By using the deep samples to estimate the inherited component, the exposure age and erosion rate can be determined by fitting the measured depth profile to the production equation. In this study, we use the cosmogenic nuclides 10 Be from surface samples and 36 Cl from depth profiles to determine the age of the Q2c surface at Red Wall and Big Dip Canyons. Amalgamating clasts with variable individual cosmic–ray-exposure histories allows the average exposure age of the deposit to be determined assuming the inherited component is the same at each depth interval. Previous studies have shown that ~150 clasts are necessary in order to average out irregularities in clast exposure histories and ensure repeatability of age determinations [Phillips et al., 2003]. 146 C3. Chlorine-36 The depth profile modeling treats the upper boundary (the soil surface) as a dynamic surface. This is because the air-soil interface is subject to erosion and/or aggradation especially during changes in climate [Bull, 1991]. The Red Wall and Big Dip Canyon fans are formed by a combination of debris flows and sheet-wash events where after deposition, pedogenesis becomes the dominant process, with clasts remaining at the surface resting on a cumulic soil [Denny, 1965; Wells et al., 1985; Wells et al., 1995; McFadden et al., 1998; Birkeland, 1999; Blair, 2000]. The presence of the A horizon indicates that the Q2c surfaces are not eroding [Dohrenwend et al., 1986]. Net surface aggradation or erosion can be estimated on the basis of soil property measurements and geological observations. Secondary accumulation products add to the original soil mass, thereby reducing the relative concentration of original sand and gravel. The Q2c surface in Death Valley is often characterized by aeolian silt and clay that has infiltrated to at least a meter depth [Machette et al., in review]. Addition of silt and clay leads to a net aggradation and results in volumetric expansion of the soil profile. However, in places, minor erosion of the Av horizon has occurred and the surface is distinguished by low amplitude undulations. In such cases, both aggradation and surface erosion may have occurred. Although erosion is an active process on the Q2c surface, among others, we selected depth profile sampling sites away from active arroyos and beneath flat, undisturbed surfaces. 147 References Blair, T.C. (2000), Sedimentology and progressive tectonic unconformities of the sheetflood-dominated Hell’s Gate alluvial fan, Death Valley, California, Sedimentary Geology, 132, 232-262. Birkeland, P.W. (1999), Soils and Geomorphology, 372 pp., Oxford University Press, New York. Bull, W.B. (1991), Geomorphic responses to climatic change, 326 pp., Oxford University Press, New York. Denny, C.S. (1965), Alluvial fans in the Death Valley region California and Nevada, Professional Paper 466, 62 pp., U.S. Geological Survey. Dohrenwend, J.C., S.G. Wells, and B.D. Turrin, (1986), Degradation of Quaternary cinder cones in the Cima volcanic field, Mojave Desert, California, Geological Society of America Bulletin, 97, 421-427. Gosse, J.C., and F.M. Phillips (2001), Terrestrial in situ cosmogenic nuclides: theory and application, Quaternary Science Reviews, 20, 1475-1560. Hancock, G.S., R.S. Anderson, O.A. Chadwick, and R.C. Finkel (1999), Dating fluvial terraces with 10 Be and 26 Al profiles: Application to the Wind River, Wyoming, Geomorphology, 27, 41-60. McFadden, L.D., E.V. McDonald, S.G. Wells, K. Anderson, J. Quade, and S.L. Forman (1998), The vesicular layer and carbonate collars of desert soils and pavements: Formation, age and relation to climate change, Geomorphology, 24, 101-145. Phillips, F.M., J.P. Ayarbe, B.J. Harrison, and D. Elmore (2003), Dating rupture events on alluvial fault scarps using cosmogenic nuclides and scarp morphology, Earth and Planetary Science Letters, 215, 203-218. Wells, S. G., J. C. Dohrenwend, L. D. McFadden, B. D. Turrin, K. D. Mahrer (1985), Late Cenozoic landscape evolution of lava flow surfaces of the Cima volcanic field, Mojave Desert, California, Geological Society of America Bulletin, 98, 1518-1529. Wells, S. G., L. D. McFadden, J. Poths, C. Olinger (1995), Cosmogenic 3 He surface- exposure dating of stone pavements: Implications for landscape evolution in deserts, Geology, 23, 613-616. 148 APPENDIX D: Red Wall Canyon and Big Dip Canyon 36 Cl Depth Profiles Chemical Data and Soil Properties The tables (Table D1 and Table D2) on the following pages correspond to the 36 Cl geochronology data presented in Chapter 3. Table D1 provides the chemical data necessary to calculate 36 Cl concentrations from depth profiles. Aliquots of the samples were sent to the New Mexico Bureau of Mines and Mineral Resources X- ray fluorescence laboratory for analysis of major elements and U and Th, and to the XRAL Laboratory in Ontario, Canada, for gamma-emission spectrometry analysis of B and Gd. Table D2 presents soil description and bulk density data for 36 Cl depth profiles. These data are also necessary for the calculation of 36 Cl concentrations from the depth profile samples. All information regarding sample locations can be found in Chapter 3. 149 Table D1. Chemical Data for 36 Cl Depth Profile Samples Sample C, wt% Na, wt% Mg, wt% Al, wt% Si, wt% P, wt% K, wt% Ca, wt% Ti, wt% Mn, wt% Fe, wt% B, ppm Sm, ppm Gd, ppm U, ppm Th, ppm DV-14b 1.20 0.87 0.68 5.58 87.67 0.02 1.92 0.29 0.37 0.00 2.03 18.00 3.00 3.00 1.00 6.00 DV-14c 3.49 1.38 1.72 7.04 79.43 0.03 2.79 1.98 0.46 0.01 1.83 19.00 3.00 3.00 2.00 9.00 DV-14d 1.55 1.16 0.81 7.53 83.36 0.03 3.15 0.52 0.53 0.02 1.71 20.00 3.00 3.00 2.00 9.00 DV-14e 4.98 1.25 2.48 6.75 77.23 0.04 2.57 3.15 0.38 0.02 1.66 18.00 3.00 3.00 2.00 10.00 DV-14g 3.33 0.75 1.71 7.35 80.51 0.04 2.81 1.65 0.44 0.01 2.13 0.00 3.00 0.00 2.00 8.00 DV-15a 4.93 0.95 2.24 5.40 80.31 0.03 2.46 3.01 0.32 0.01 1.14 9.10 3.00 3.00 2.00 5.00 DV-15b 3.45 0.95 1.60 6.80 81.33 0.03 2.62 1.59 0.37 0.01 1.89 21.70 2.20 2.20 2.00 9.00 DV-15c 1.34 0.95 1.60 6.80 81.33 0.03 2.62 1.59 0.37 0.01 1.89 21.70 2.20 2.20 2.00 9.00 DV-15d 1.38 0.88 0.70 6.85 85.58 0.03 2.68 0.35 0.44 0.01 1.91 30.90 0.90 0.90 2.00 7.00 DV-15e 6.15 1.02 2.78 6.37 76.12 0.03 2.54 3.77 0.29 2.78 1.54 22.90 3.10 3.10 2.00 8.00 150 Table D1 Continued Sample C, wt% Na, wt% Mg, wt% Al, wt% Si, wt% P, wt% K, wt% Ca, wt% Ti, wt% Mn, wt% Fe, wt% B, ppm Sm, ppm Gd, ppm U, ppm Th, ppm NRWF-0 1.15 2.62 0.44 11.63 76.89 0.01 5.05 0.25 0.18 0.02 1.86 20.00 3.00 3.00 1.00 6.00 NRWF-15 1.15 2.42 0.44 11.36 77.96 0.01 5.14 0.25 0.16 0.02 5.14 20.00 3.00 3.00 1.00 6.00 NRWF-35 0.85 2.52 0.23 11.49 77.79 0.01 5.25 0.16 0.15 0.03 1.48 20.00 3.00 3.00 1.00 6.00 NRWF-70 1.23 2.65 0.51 11.99 76.45 0.01 5.22 0.30 0.18 0.03 1.38 20.00 3.00 3.00 1.00 6.00 NRWF-120 0.93 2.61 0.48 12.37 75.76 0.02 5.31 0.35 0.24 0.04 2.23 20.00 3.00 3.00 1.00 6.00 NRWF-180 1.25 2.48 0.42 11.85 77.20 0.01 5.06 0.26 0.19 0.02 1.28 20.00 3.00 3.00 1.00 6.00 151 Table D2. Soil Description and Bulk Density Data for 36 Cl Depth Profiles Depth profile Depth, m Soil horizon Soil bulk density, g/cm 3 Soil water content, %volume DV-14 0 - 0.04 Avk 1.7 5.0 0.04 - 0.16 Btkz 1.8 5.0 0.16 - 0.28 2Bk1 2.2 5.0 0.28 - 0.50 2Bk2 2.2 5.0 0.50 - 0.85 2Bky 2.4 5.0 0.85 - 2.20 2C 2.4 5.0 DV-15 0 - 0.03 Av 1.7 5.0 0.03 - 0.20 2Btkz 1.8 5.0 0.20 - 0.45 2Bk1 2.2 5.0 0.45 - 2.05 2Bk2 2.4 5.0 NRWF 0 - 0.05 - 2.3 6.0 0.05 - 0.15 - 2.3 6.0 0.15 - 0.35 - 2.3 6.0 0.35 - 0.70 - 2.9 6.0 0.70 - 1.20 - 2.9 6.0 1.20 -1.80 - 2.9 6.0 152 APPENDIX E: Description of the CHLOE Depth Profile Age Model CHLOE is based on the cosmogenic nuclide production equations presented by Gosse and Phillips [2001]. The high-energy cosmic-ray flux is calculated based on standard exponential attenuation with mass depth and the spallation production rate is proportional to that flux. The model then uses this flux distribution as the source term for the calculation of the epithermal and thermal neutron fluxes by means of the diffusion equations derived by Phillips et al. [2001]. The spatial distributions of low-energy neutron fluxes are used to calculate the 36 Cl production by epithermal and thermal neutron absorption. Production parameters given in Phillips et al. [2001] and Stone et al. [1998] are used in the model. CHLOE uses the average bulk chemical composition of the soil profile to compute the depth distribution of the low-energy neutron fluxes. A fast neutron attenuation length of 170 g cm -2 was used to model all three profiles. The computed neutron fluxes and the Cl concentrations measured at each depth sampled are then used to calculate the 36 Cl production rate. In addition to production by the nucleonic component of the cosmic radiation, CHLOE also computes production rates due to primary and secondary effects of the cosmic-ray muon flux, using approaches analogous to those described above. The program also computes the concentration of nucleogenic 36 Cl (i.e., produced as a secondary result of radioactive decay reactions within the minerals) in the sample and subtracts it from the measured total 36 Cl to obtain the cosmogenic 36 Cl concentration. 153 CHLOE produces calculations of 36 Cl concentrations at the sampled depths, subject to variation of three adjustable parameters: the profile inheritance (t p ), the profile deposition age (t d ), and the rate of surface aggradation/erosion (ε). Given reasonable independent constraints on these variables, the model output was fairly sensitive to the first two, but relatively insensitive to the last one. The fitting of calculated 36 Cl concentrations to data was therefore restricted to aggradation/erosion rates limited between upper and lower bounds estimated for each site based on particle-size measurements and geological observations, as described above. However, the χ 2 variation shows a relatively high degree of sensitivity to the exposure age and a low sensitivity to the erosion rate. The result of this pattern of insensitivity was that the variation in ε played a significant role in estimation of the uncertainty of the best-fit deposition age, but only a small role in estimating its actual value. CHLOE simulates erosion using classical cosmogenic-nuclide formulations [e.g., Gosse and Phillips, 2001], which assume that erosion is from the surface. Analogous equations are not commonly used for the case of aggradation because there is no fixed relation between the cosmogenic nuclide concentration of sediment deposited on top of a geological unit and that of the material in the unit. However, for the material we are analyzing this is not an issue, because the aggradation resulted from atmospheric deposition and materials that were deposited (mainly silt and calcium carbonate) are separated from the parent material being analyzed by sieving and acid leaching. We therefore analyzed none of the material accumulated 154 due to atmospheric deposition and its cosmogenic nuclide content is thus not a factor in interpreting the data. However, some inconsistency remains because the classical equations, when used for aggradation, treat the process entirely as deposition on the surface. This is true for part of the actual atmospheric deposition (the Av horizon), but not for the pedogenic calcium carbonate that precipitates and silt that infiltrates the profile. This may to some extent affect the outcome of the curve-fitting analysis, but probably not to an extent that is large compared to other uncertainties. The profile age and uncertainty were calculated by means of χ 2 fitting [Bevington and Robinson, 2003] of the 36 Cl concentration data from the various depths to the 36 Cl distribution modeled by CHLOE. The sum of chi-squared function (χ 2 ) was calculated for each age-erosion pair as follows: χ 2 = O i − M i () 2 S i 2 i=1 n ∑ (E1), where O i is the observed, normalized, 36 Cl concentration at each depth interval, i, and M i is the modeled value at the same depth. The number of concentration measurements is n. S i is the standard deviation associated with the i th data point: S i = S i,36 + S inheri tan ce + S other (E2), where S i,36 is the standard deviation from the 36 Cl analytical measurement, S inheritance is the contribution to the standard deviation from variability in the inherited 36 Cl concentration, and S other is the contribution from other sources of variability, principally analytical uncertainties in the chemical analyses, bulk densities, and other parameters, combined with uncertainties in the 36 Cl production parameters. S i,36 was 155 taken directly from the AMS analyses. S inheritance was estimated based on a depth profile of 36 Cl concentration measured on a lacustrine beach deposit of known age (from radiocarbon chronology) formed by Lake Lahontan [Kurth, 2003]. χ 2 fitting of the profile fitting yields an age uncertainty that is 3% larger than theoretically calculated, assuming all other sources of variation were accounted for adequately. This enhancement of the χ 2 can presumably be attributed to unaccounted-for variability of the inherited component. S other was estimated based on an empirical comparison of 36 Cl ages with independently-constrained ages for 30 surface samples [Phillips et al., 2001] and was assigned a value of 6%. For each profile we also report the reduced sum of χ 2 (χ ν 2 ), which is the sum of χ 2 , as given above, divided by n, the number of samples in the profile. The magnitude of χ ν 2 is a measure of the goodness of fit of the data to the model. In general, for laboratory systems in which the model can be assured to provide a complete description, a χ ν 2 of less than one is considered a satisfactory fit [Bevington and Robinson, 2003]. When dealing with environmental measurements for which the model may be incomplete, somewhat larger χ ν 2 are often considered acceptable. The array of sum-of-χ 2 values was contoured. The best age estimate corresponds to the minimum value of the sum of χ 2 (in the t d versus t inh parameter space). One-standard-deviation uncertainty bounds were estimated from the maximum and minimum age limits of the χ min 2 + Δχ ν 2 contour in the age-erosion parameter space. χ min 2 is the minimum value of the calculated sum of χ 2 within the parameter space and Δχ ν 2 is the critical value of the change in sum of χ 2 for a 156 specified level of confidence and number of fitted parameters (ν) (Table 3.4) [e.g., Davis, 2002]. For our problem, the appropriate level of confidence is 68.3% (corresponding to one standard deviation uncertainty) and two fitted parameters (t d and t inh ), giving a Δχ ν 2 of 2.30. The approach to uncertainty estimation described above is comprehensive (it includes potential systematic as well as random sources of uncertainty) and it includes an explicit calculation of model accuracy, based on the fit of multiple samples within a single profile, as opposed to a single cosmogenic nuclide age determination for which model error can only be estimated. We believe that the overall uncertainty bounds calculated using this approach are conservative and are likely to overestimate, rather than underestimate, the actual uncertainties. References Bevington, P.R., and D.K. Robinson (2003), Data reduction and error analysis for the physical sciences, 320 pp., McGraw-Hill, Boston. Davis, J.C. (2002), Statistics and data analysis in geology, 638 pp., John Wiley and Sons, New York. Gosse, J.C., and F.M. Phillips (2001), Terrestrial in situ cosmogenic nuclides: theory and application, Quaternary Science Reviews, 20, 1475-1560. Kurth, G. (2003), Cosmogenic nuclide dating of old, high pluvial shorelines in the western Great Basin, M.S. thesis, XX pp., New Mexico Institute of Mining & Technology, Socorro. Phillips, F.M., W.D. Stone, and J.T. Fabryka-Martin (2001), An improved approach to calculating low-energy cosmic-ray neutron fluxes near the land/atmosphere interface, Chemical Geology, 175, 689-701. Stone J. O. H., J.M. Evans, L.K. Fifield, G.L. Allan, and R.G. Cresswell (1998) Cosmogenic chlorine-36 production in calcite by muons, Geochimica et Cosmochimica Acta, 62, 433-454. 157 APPENDIX F: Fault Slip Rate Error Propagation When dealing with fault slip rates there are two sources of uncertainty. The first is the error in the offset measurement, δs. The second is the error associated with the age of the offset unit, δa. Using standard error propagation methods [e.g., Taylor, 1997 - Chapter 3], we can determine the uncertainty is the slip rate, δr. We can determine the fault slip rate, r, by: a s r = (F1), where s is the total amount of slip, or displacement, and a is the age of the offset deposit. The uncertainty in fault slip rate is defined as: 2 2 ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ ∂ ∂ + ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ ∂ ∂ = a a r s s r r δ δ δ (F2), where a s r 1 = ∂ ∂ (F3), is the partial uncertainty (partial derivative) associated with the fault displacement and 2 a s a r − = ∂ ∂ (F4) is the partial uncertainty (partial derivative) associated with the age of the offset unit. 158 Substituting equation F3 and equation F4 into equation F2 yields: () () 2 2 2 1 ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ − + ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ = a a s s a r δ δ δ (F5). Equation F5 gives the total uncertainty in the fault slip rate as the quadratic sum of the partial uncertainties due to the errors associated with both the displacement and age. By propagating the errors associated with individual measurements in this way, the overall uncertainty is reduced. Reference Taylor, J.R. (1997), An introduction to error analysis: The study of uncertainties in physical measurements, 327 pp., Sausilito, University Science Books. 159 APPENDIX G: ArcGIS/Info Recipes G1. Introduction This appendix describes the various steps and commands necessary to extract data from digital elevation models (DEM). The instructions below were used in analyses of the airborne laser swath mapping digital topographic data in Chapter 2, Chapter 3, and Chapter 4 of this dissertation. The command-line instructions all refer to methods for ArcInfo. The directions for extracting parallel topographic profiles are split between ArcMap and ArcInfo. All of the raster data produced in ArcInfo can easily be displayed in ArcMap using the “Add Data” function and then selecting the maps from their respective ArcInfo workspace. There is no guarantee that these methods are the most efficient, or best, way to accomplish the tasks that are discussed. Nor is there any guarantee that these commands will actually work. The instructions assume that the user has a basic working knowledge of the ArcGIS and ArcInfo software packages and do not contain basic information regarding syntax, how to create a workspace, or how to import data into these programs. The “Help” menus in both ArcMap and ArcInfo, as well as the ESRI online user forums (http://support.esri.com/), are also excellent sources of information. In addition, the textbook by Burroughs and McDonnell [1998] is a great reference for a better of understanding geographic information systems. 160 G2. Slope Maps Slope maps allow for the determination of the maximum rate of change in elevation in the north-south and east-west direction (see Chapter 2). By default, ArcInfo calculates slope as the maximum rate of change over each cell in a DEM and its eight neighbors (i.e., slope is calculated in a 3 x 3 cell moving window). To calculate slope first load your DEM in Grid. Arc: grid Grid: mape name_grd Grid: image name_grd Next, run the slope command to calculate slope values across the DEM. Grid: name_slp = slope (name_grd) To view the slope map, simply load it in Grid. Grid: mape name_slp Grid: image name_slp G3. Slope Aspect Maps Calculating aspect values is straightforward. This command determines the compass direction (azimuth) of the maximum rate of change from one cell to the 161 next. First, you need to make a slope map by following the instruction in the previous section (Section G2). Once you have a slope map, run the commands below. Arc: grid Grid: name_asp = aspect (name_slp) To display the aspect map, load it in Grid. Grid: mape name_asp Grid: image name_asp G4. Standard Deviation ArcInfo allows the user to calculate the standard deviation of any Z value contained in the cells of a raster dataset. Standard deviation can be calculated over various shapes including rectangles, circles, wedges, etc. Here, I provide only the commands necessary to calculate the standard deviation in a rectangular area. This is the default setting in ArcInfo. The user can define the size of the area over which the standard deviation values are calculated and this is also described below. First, view the raster dataset in Grid. Arc: grid Grid: mape name_grd 162 Grid: image name_grd Now, run the standard deviation command on the grid. Grid: name_std = focalstd (name_grd) By default, ArcInfo will calculate the standard deviation of Z values over a 3 x 3 cell moving rectangle. To change the size of the area of the rectangle the user can define the size of the moving window as follows. Grid: name_stdX = focalstd (name_grd, width, height) In this case, replace the “X” in the new file name with a number referring to the size of the window being used. The width and height are numerical values (i.e., 10) for the dimensions of the moving window in the units of feet or meters, correspond to the units of your DEM. A note of caution, the larger the dimensions of the moving window, the longer it will take to run the calculations. G5. Extracting Points from a Grid A set of Z values can be extracted from a grid if you have a list of corresponding X and Y values, such as latitudes and longitudes or UTM eastings and northings. This is useful for obtaining different Z values (elevation, slope, curvature, standard deviation, etc.) from separate grids that cover the same region. To 163 accomplish this task, you must first have a tab- or comma-delimited ASCII file with X and Y values that are in the same coordinate system as the grid from which data are being extracted. Once these data are in the same workspace as the grid of interest, you can sample the Z values at each corresponding XY location by using the command below. Arc: grid Grid: name.dat = sample (coordinates.dat, name_grd, bilinear) “name.dat” is the file that will contain the Z values, “coordinates.dat” is the ASCII file with tab- or comma-delimited coordinates, and “name_grd” is the grid containing the Z values of interest. The “bilinear” term refers to the interpolation scheme used for the Z values. Bilinear interpolation weights the Z values from the four nearest cells. The user can also define cubic or nearest neighbor interpolations, however sensitivity tests suggest that bilinear interpolation is the most accurate. Once the Z values have been extracted from the grid you will need to export the data from ArcInfo to your computer. To do this, you must extract the data from Arc by using Info, as follows. Grid: q Arc: info ENTER USER NAME> arc 164 ENTER COMMAND> select NAME.DAT ENTER COMMAND> export c:/folder_name/name.dat sdf Do this for each set of Z values extracted from the grid. This will export the Z values as an ASCII file, which will contain X, Y, and Z data points as well as information about the spacing between each Z value. Data in the ASCII file can then be plotted in any common graphing software, such as Excel, SigmaPlot, Matlab, etc. Once all of the data are exported to your computer, issue the command below leave Info. ENTER COMMAND> q stop G6. Defining Drainage Networks to Determine Thalweg Positions Digital elevation models can easily be used to define drainage networks. This is a relatively easy and objective way to determine the position of thalwegs, which can be used as piercing points when measuring fault displacement. The following commands fill any artificial “holes” in the dataset, define the direction that water flows through the channel network, and determine which cells will accumulate water as channels, and which cells will have runoff as hillslopes. Arc: grid Grid: mape name_grd Grid: image name_grd 165 Grid: fill name_grd name_fill Grid: name_fd = flowdirection (name_fill) Grid: name_acc = flowaccumulation (name_fd) The drainage network is now defined. You should view the grid that displays the channels using the following command. Grid: image name_acc G7. Clipping a Grid There may be times when it is easier to work with a specific part of a DEM, rather than with an entire region. To clip out a small area of interest from a larger DEM, run the following commands in ArcInfo. Grid: mape name_grd Grid: image name_grd Grid: gridclip in_grd out_grd The syntax “in_grd” refers to the name of the original DEM and “out_grd” is the name given to the smaller, clipped portion of the DEM. Grid will allow you to interactively define a box around the region you want to clip in the graphics window. Once you define the box, that part of the DEM will be clipped out. Display the clipped DEM to ensure it is correct. 166 G8. Extracting Parallel Topographic Profiles Extracting parallel topographic profiles follows the same premise as a single profile, so I do not give single profiles them separate treatment here. To collect parallel topographic profiles, you will first start in ArcMap. Open the DEM of interest in ArcMap and draw a rectangle oriented in the along-strike direction of the profiles (Figure G1). Use the long sides of the rectangle to guide where the profiles will be drawn on the DEM (Figure G1). Using the “identify” tool, determine the endpoints of each parallel profile and record these values in map units (Figure G1). Once you have the coordinates (e.g., UTM easting and northing) for the end points of the profiles, open ArcInfo and then ArcPlot. You will load your DEM in ArcPlot to extract the topographic profiles following the steps below. Arc: &station 9999 Arc: arcplot Arcplot: mape name_grd Arcplot: image name_grd Arcplot: surface lattice name_grd Arcplot: surfaceprofile * ‘utm_easting,utm_northing utm_easting,utm_northing’ info_name sample_distance The “*” allows for an interactive selection of where the profile will be drawn in the graphics window. “utm_easting” and “utm_northing” are the coordinates at the two endpoints of the profile. The northing and easting values should be 167 Figure G1 Schematic diagram showing parallel topographic profile extraction in ArcMap. Red arrow points to rectangle tool. Blue arrow shows the identify tool used to determine coordinates at the corners of the rectangle. Coordinates determined with the identify tool will show up in a separate window shown by the green arrow. 168 separated with a comma and there should be a space between the two sets of coordinates. “info_name” is the name of the raw point data file that is exported to Info. “sample_dist” is the user-defined spacing between points on the profile. A value of “1” should be sufficient for the spacing (the default is 0.45). You will need to repeat the above command for each profile you wish to extract. After all of the profiles are extracted, use Info to export the profiles to your computer. Arcplot: q Arc: info ENTER USER NAME> arc ENTER COMMAND> select NAME_INFO ENTER COMMAND> export c:/folder_name/name.dat sdf You must do this for each profile extracted from the grid. This will export Z values as an ASCII file, which will contain X, Y, and Z values as well as information about the spacing between each Z value. The data in the ASCII file can be plotted using any graphing software (Excel, SigmaPlot, Matlab, etc.) Once all of the data are exported to your computer, issue the following command to leave Info. ENTER COMMAND> q stop Reference Burroughs, P.A., and R.A. McDonnell (1998), Principles of geographical information systems, 356 pp., Oxford University Press, New York. 169 APPENDIX H: Beryllium-10 Geochronology Data The tables on the following page are sets of cosmogenic nuclide 10 Be geochronology data from Death Valley, California; Fish Lake Valley, California and Nevada; and the Wasatch Mountains, Utah. Samples from Death Valley are from the following sites: Mormon Point, North of Furnace Creek Sea Level, North of Furnace Creek 30 m Offset, the Beatty Bar, and the North of Ubehebe Crater 390 m offset. Two samples collected from active channels at the Red Wall Canyon alluvial fan and the North of Furnace Creek 30 m offset are also reported. The samples from Fish Lake Valley are from the Qft surface on the Furnace Creek alluvial fan (please see Chapter 4). The samples from the Wasatch Mountains were collected to determine catchment-wide erosion rates along the Weber segment of the range front. The data reported here include analytical results from sample analysis by accelerator mass spectrometry at Lawrence Livermore National Laboratory. All of the relevant data necessary for calculation of ages are reported, including latitude and longitude, elevation, mass of quartz, mass of carrier, carrier concentration, sample thickness, sample density (approximate), lithology, 10 Be/ 9 Be ratios, and the background-corrected 10 Be/ 9 Be ratios associated with the blanks for each batch of samples that were processed and analyzed together. Topographic shielding is negligible for all samples (horizon <20° in all directions). Sample names containing “BL” are process blanks and those with “Be-BL” are carrier blanks. Samples were processed under the supervision of Dr. Robert Finkel at Lawrence Livermore National Laboratory and Dr. Lewis Owen at the University of Cincinnati. 170 Table H1. Beryllium-10 Analytical Data for the Qft surface at the Furnace Creek Alluvial Fan in Fish Lake Valley a All samples are granitic basement from the White Mountains. Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-0418-1 37.5643°/-118.0080° 1667 10.0115 2 2.7 0.3126 1000 16.36 ± 0.4022 KF-0418-2 37.5642°/-118.0079° 1667 10.0089 2 2.7 0.3084 1000 14.98 ± 0.3659 KF-0418-3 37.5641°/-118.0081° 1667 10.0482 2 2.7 0.3135 1000 10.43 ± 0.2566 KF-0418-4 37.5646°/-118.0091° 1667 10.1409 2 2.7 0.3106 1000 13.57 ± 0.3401 KF-BL-706-1 - - - - - 0.3090 1000 0.0681 ± 0.007853 KF-BL-706-2 - - - - - 0.3140 1000 0.07506 ± 0.0161 KF-Be-BL-706 - - - - - - 1000 0.00522 ± 0.002123 171 Table H2. Beryllium-10 Analytical Data for the Qa3 Surface at Mormon Point, Death Valley a All samples are granitic gneiss. Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-MP-101 36.0618°/-116.7564° -49 74.9976 5 2.7 0.3106 1000 7.409 ± 0.3183 KF-MP-103 36.0618°/-116.7564° -49 54.2447 5 2.7 0.3080 1000 1.733 ± 0.0628 KF-MP-105 36.0618°/-116.7564° -49 75.0042 5 2.7 0.3103 1000 0.6048 ± 0.06323 KF-MP-106 36.0618°/-116.7564° -49 73.7852 5 2.7 0.3090 1000 1.560 ± 0.07847 KF-MP-110 36.0618°/-116.7564° -49 74.9966 5 2.7 0.3088 1000 1.457 ± 0.07843 KF-MP-112 36.0618°/-116.7564° -49 75.0206 5 2.7 0.3081 1000 2.154 ± 0.09242 KF-BL-506-1 - - - - - 0.3087 1000 0.0466 ± 0.006665 KF-BL-506-2 - - - - - 0.3079 1000 0.05969 ± 0.005859 KF-BL-606-1 - - - - - 0.3123 1000 0.1596 ± 0.01369 KF-BL-606-2 - - - - - 0.3090 1000 0.06198 ± 0.01148 KF-BL-606-3 - - - - - 0.3155 1000 0.02485 ± 0.01022 KF-BL-606-4 - - - - - 0.3095 1000 0.01824 ± 0.005705 KF-Be-BL-1 - - - - - - 1000 0.005673 ± 0.001663 172 Table H3. Beryllium-10 Analytical Data for the Q2b Surface at the North of Ubehebe Crater 390 m Offset Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-0218-2 37.1005°/-117.4777° 844 8.5275 4 2.7 0.3180 1000 6.515 ± 0.1661 KF-0218-3 37.1007°/-117.4791° 827 10.0309 4 2.7 0.3290 1000 6.363 ± 0.2887 KF-0218-4 37.0958/-117.4731 860 10.0141 4 2.7 0.3158 1000 2.269 ± 0.08350 KF-0218-10 37.0987°/-117.4727° 855 10.0842 4 2.7 0.3222 1000 2.063 ± 0.07543 KF-0404-1 37.0958°/-117.4721° 872 10.0178 4 2.7 0.3093 1000 2.098 ± 0.1112 KF-0404-2 37.0959°/-117.4727° 869 10.0524 5 2.7 0.3081 1000 1.242 ± 0.06646 KF-0404-3 37.0966°/-117.4732° 864 10.0191 4 2.7 0.3108 1000 1.362 ± 0.06609 KF-0404-4 37.0979°/-117.4738° 855 10.0053 5 2.7 0.3075 1000 1.689 ± 0.08743 KF-0404-5 37.0989°/-117.4745° 856 10.0009 5 2.7 0.3095 1000 1.976 ± 0.07648 KF-0404-6 37.0989°/-117.4731° 863 10.0471 5 2.7 0.3107 1000 1.805 ± 0.06957 173 Table H3 Continued a All samples are quartzite. Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, mg Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-BL-506-1 - - - - - 0.3087 1000 0.0466 ± 0.006665 KF-BL-506-2 - - - - - 0.3079 1000 0.05969 ± 0.005859 KF-BL-606-1 - - - - - 0.3123 1000 0.1596 ± 0.01369 KF-BL-606-2 - - - - - 0.3090 1000 0.06198 ± 0.01148 KF-BL-606-3 - - - - - 0.3155 1000 0.02485 ± 0.01022 KF-BL-606-4 - - - - - 0.3095 1000 0.01824 ± 0.005705 KF-Be-BL-1 - - - - - - 1000 0.005673 ± 0.001663 174 Table H4. Beryllium-10 Analytical Data for the Q3 Surface at the North of Furnace Creek, Death Valley 30 m Offset Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-0406-1 36.6255°/-117.0032° 44 20.0663 4 2.7 0.3078 1000 2.870 ± 0.08752 KF-0406-2 36.6253°/-117.0032° 41 20.1898 4 2.7 0.3104 1000 3.489 ± 0.1001 KF-0406-3 36.6253°/-117.0033° 38 20.0977 4 2.7 0.3100 1000 3.128 ± 0.09019 KF-0406-4 36.6254°/-117.0036° 40 20.0109 2 2.7 0.3122 1000 1.736 ± 0.07446 KF-0406-5 36.6252°/-117.0034° 31 20.2957 4 2.7 0.3149 1000 3.354 ± 0.09454 KF-0406-6 36.6251°/-117.0029° 33 20.0509 4 2.7 0.3272 1000 2.439 ± 0.0758 KF-0406-7 36.6253°/-117.0032° 38 20.0029 3 2.7 0.3172 1000 4.326 ± 0.1752 KF-0406-8 36.6251°/-117.0031° 34 20.0375 4 2.7 0.3178 1000 2.551 ± 0.07951 KF-0406-9 36.6251°/-117.0033° 35 20.0492 4 2.7 0.3181 1000 3.386 ± 0.1061 KF-0406-10 36.6250°/-117.0037° 32 20.0155 4 2.7 0.3190 1000 5.151 ± 01314 175 Table H4 Continued a All samples are quartzite. Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-BL-506-1 - - - - - 0.3087 1000 0.0466 ± 0.006665 KF-BL-506-2 - - - - - 0.3079 1000 0.05969 ± 0.005859 KF-BL-606-1 - - - - - 0.3123 1000 0.1596 ± 0.01369 KF-BL-606-2 - - - - - 0.3090 1000 0.06198 ± 0.01148 KF-BL-606-3 - - - - - 0.3155 1000 0.02485 ± 0.01022 KF-BL-606-4 - - - - - 0.3095 1000 0.01824 ± 0.005705 KF-Be-BL-1 - - - - - - 1000 0.005673 ± 0.001663 176 Table H5. Beryllium-10 Analytical Data for the Q3 Surface near Sea Level North of Furnace Creek, Death Valley a All samples are quartzites. Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-0416-1 36.6196°/-116.9939° 18 30.0419 4 2.7 0.9679 500 1.385 ± 0.04567 KF-0416-2 36.6196°/-116.9939° 18 30.2397 4 2.7 0.9363 500 0.6474 ± 0.03887 KF-0416-3 36.6197°/-116.9939° 20 30.0195 5 2.7 0.9366 500 2.973 ± 0.08364 KF-0416-4 36.6192°/-116.9939° 20 30.0587 5 2.7 0.9773 500 0.9565 ± 0.03796 KF-0416-5 36.6199°/-116.9937° 18 30.1010 5 2.7 0.9861 500 5.602 ± 0.1381 KF-0416-6 36.6201°/-116.9935° 21 30.4084 5 2.7 0.9863 500 1.052 ± 0.03386 KF-BL-806-1 - - - - - 0.9337 500 0.3032 ± 0.01398 KF-BL-806-2 - - - - - 1.0354 500 0.2975 ± 0.01188 KF-BL-806-3 - - - - - 0.9631 500 0.3116 ± 0.01145 KF-Be-BL-806 - - - - - - 500 0.2795 ± 0.01037 177 Table H6. Beryllium-10 Analytical Data for the Surface of the Beatty Bar, Death Valley a All samples are quartizites. Sample number Location, latitude/longitude Altitude, m asl Quartz mass, g Thickness, cm Density a , g/cm 3 Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-0417-10 36.6196°/-116.9939° 35 20.0139 4 2.7 0.9853 500 3.294 ± .08419 KF-0417-11 36.6196°/-116.9939° 33 20.1133 4 2.7 0.9458 500 4.564 ± 0.1791 KF-0417-12 36.6197°/-116.9939° 33 20.1282 2 2.7 1.0074 500 9.717 ± 0.2908 KF-0417-13 36.6192°/-116.9939° 35 20.0566 3 2.7 0.9678 500 9.668 ± 0.2313 KF-0417-14 36.6199°-116.9937° 33 20.0913 4 2.7 1.0044 500 3.175 ± 0.08117 KF-0417-15 36.6201°/-116.9935° 33 20.0184 5 2.7 0.9704 500 3.909 ± 0.09651 KF-BL-806-1 - - - - - 0.9337 500 0.3032 ± 0.01398 KF-BL-806-2 - - - - - 1.0354 500 0.2975 ± 0.01188 KF-BL-806-3 - - - - - 0.9631 500 0.3116 ± 0.01145 KF-Be-BL-806 - - - - - - 500 0.2795 ± 0.01037 178 Table H7. Beryllium-10 Analytical Data for Death Valley Alluvial Fan Active Channel Sand (250 to 500 μm) Samples Sample number Location, latitude/longitude Channel location description Altitude, m Quartz mass, g Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 KF-0217-1 36.8932°/-117.2539° Red Wall Canyon fan 450 20.0415 0.3109 1000 1.737 ± 0.09236 KF-BL-506-1 - - - - 0.3087 1000 0.0466 ± 0.006665 KF-BL-506-2 - - - - 0.3079 1000 0.05969 ± 0.005859 KF-BL-606-1 - - - - 0.3123 1000 0.1596 ± 0.01369 KF-BL-606-2 - - - - 0.3090 1000 0.06198 ± 0.01148 KF-BL-606-3 - - - - 0.3155 1000 0.02485 ± 0.01022 KF-BL-606-4 - - - - 0.3095 1000 0.01824 ± 0.005705 KF-Be-BL-1 - - - - - 1000 0.005673 ± 0.001663 KF-0406-11 36.6258°/-117.2539° N. Furn. Cr. 30 m offset 42 30.0471 1.0162 500 0.5516 ± 0.02751 KF-BL-806-1 - - - - 0.9337 500 0.3032 ± 0.01398 KF-BL-806-2 - - - - 1.0354 500 0.2975 ± 0.01188 KF-BL-806-3 - - - - 0.9631 500 0.3116 ± 0.01145 KF-Be-BL-806 - - - - 500 0.2795 ± 0.01037 179 Table H8. Beryllium-10 Analytical Data for Wasatch Mountains (Weber Segment) Catchment-Wide Erosion Rate Samples a a All samples are sand from the mouth of the trunk channel in each catchment. Sample number Location, latitude/longitude Catchment name Altitude, m Quartz mass, g Mass of Be carrier, g Carrier concentration, μg/mL 10 Be/ 9 Be, 10 -13 WAS-1 41.1065°/-111.9034° N. Fork Kays Creek 1571 56.1026 0.3059 1000 6.658 ± 0.1574 WAS-4 41.0655°/-111.9026° N. Fork Holmes Cr. 1545 52.9941 0.3057 1000 7.168 ± 0.1691 WAS-5 41.0558°/-111.8996° Holmes Creek 1547 60.0123 0.3059 1000 5.835 ± 0.2092 WAS-7 41.0149°/-111.8918° Shepards Creek 1492 50.0133 0.3104 1000 3.191 ± 0.08910 WAS-9 40.9745°/-111.8701° Steed Creek 1475 70.5902 0.3071 1000 7.885 ± 0.1985 WAS-10 40.9391°/-111.8680° Ford Cyn./ Ricks Cr. 1471 70.0716 0.3058 1000 5.471 ± 0.1389 WAS-12 40.9164°/-111.8620° Centerville Creek 1407 70.0259 0.3078 1000 7.689 ± 0.2315 WAS-14 40.8810°/-111.8420° Holbrook Creek 1552 65.0217 0.3060 1000 5.579 ± 0.1106 WAS-BL-1 - - - - 0.3082 1000 0.1002 ± 0.007273 WAS-BL-2 - - - - 0.3068 1000 0.08046 ± 0.01235 KF-Be-BL-706 - - - - - 1000 0.00522 ± 0.002123
Abstract (if available)
Abstract
The constancy of strain accumulation and release in time and space is one of the most fundamental issues in tectonics. Models of geodetic data suggest the Death Valley-Fish Lake Valley fault zone (DV-FLVFZ) is storing most of the Pacific-North American plate boundary strain in the northern eastern California shear zone (ECSZ). However, the scarcity of geochronologically constrained slip rates on the DV-FLVFZ has made it difficult to determine whether strain storage and release are constant in this region. I used airborne laser swath mapping (ALSM) digital topographic data to restore offset alluvial fans to their pre-faulting positions, combined with cosmogenic Beryllium-10 and Chlorine-36 geochronology to determine slip rates along the DV-FLVFZ.
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University of Southern California Dissertations and Theses
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Creator
Frankel, Kurt Lang
(author)
Core Title
Fault slip rates, constancy of seismic strain release, and landscape evolution in the eastern California shear zone
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Geological Sciences
Publication Date
06/04/2007
Defense Date
04/25/2007
Publisher
University of Southern California
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University of Southern California. Libraries
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Tag
airborne laser swath mapping,cosmogenic nuclides,Death Valley,Fish Lake Valley,LiDAR,OAI-PMH Harvest
Place Name
California
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USA
(countries),
valleys: Death Valley
(geographic subject),
valleys: Fish Lake Valley
(geographic subject)
Language
English
Advisor
Dolan, James F. (
committee chair
), Davis, Gregory A. (
committee member
), Hogen-Esch, Thieo E. (
committee member
)
Creator Email
kfrankel@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-m503
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UC1418906
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etd-Frankel-20070604 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-496832 (legacy record id),usctheses-m503 (legacy record id)
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Frankel, Kurt Lang
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University of Southern California Dissertations and Theses
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Repository Location
Los Angeles, California
Repository Email
cisadmin@lib.usc.edu
Tags
airborne laser swath mapping
cosmogenic nuclides
Fish Lake Valley
LiDAR