U.S. Department of the Interior

U.S. Geological Survey

Circular 1413

Developing Integrated Methods to 

Address Complex Resource and 

Environmental Issues

Geophysics

Remote Sensing

Geochemistry
Front cover. Top photograph, Jonathan Caine drilling a stilling well for a streamgage in upper Handcart Gulch, 

Colo. (USGS photograph) Middle photograph, Ships and relief drill rigs working to intersect and seal the Macondo 

well during the Deepwater Horizon oil spill, July 9, 2010. (Photograph by Gregg Swayze, USGS) Bottom photograph, 

Benjamin Drenth measuring strength of the Earth’s gravity field at Great Dunes National Park, June 2011. 

(Photograph by David V. Fitterman)

Back cover. Seth Haines doing field work near Isabella Dam, above Bakersfield, Calif., February 2007. 

(Photograph by Bethany Burton)
Developing Integrated Methods to 

Address Complex Resource and 

Environmental Issues

Edited by Kathleen S. Smith, Jeffrey D. Phillips, Anne E. McCafferty, and 

Roger N. Clark

Circular 1413

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Director

U.S. Geological Survey, Reston, Virginia: 2016

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

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visit http://www.usgs.gov/pubprod/.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Smith, K.S., Phillips, J.D., McCafferty, A.E., and Clark, R.N., eds., 2016, Developing integrated methods to address 

complex resource and environmental issues: U.S. Geological Survey Circular 1413, 160 p., 

http://dx.doi.org/10.3133/cir1413.

Library of Congress Cataloging-in-Publication Data

Developing integrated methods to address complex resource and environmental issues / edited by Kathleen S. Smith, 

Jeffrey D. Phillips, Anne E. McCafferty, and Roger N. Clark.

pages cm. -- (Circular ; 1413)

 Includes bibliographical references.

ISBN 978-1-4113-3969-9 (pbk.)

1. Geophysics. 2. Geodynamics. 3. Earth sciences. 4. Environmental risk assessment. I. Smith, Kathleen S. 

(Geologist) II. Phillips, Jeffrey D. III. McCafferty, Anne. IV. Clark, Roger N. (Roger Nelson)

 QE501.D485 2015

 550--dc23

 2015035017

ISSN 1067-084X (print)

ISSN 2330-5703 (online)

ISBN 978-1-4113-3969-9
iii

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd) 

Area

square meter (m2

) 0.0002471 acre 

square kilometer (km2

) 247.1 acre

square centimeter (cm2

) 0.001076 square foot (ft2)

square meter (m2

) 10.76 square foot (ft2) 

square centimeter (cm2

) 0.1550 square inch (ft2) 

square kilometer (km2

) 0.3861 square mile (mi2)

Volume

liter (L) 33.82 ounce, fluid (fl. oz)

liter (L) 0.2642 gallon (gal)

cubic meter (m3

) 264.2 gallon (gal) 

cubic decimeter (dm3

) 0.2642 gallon (gal) 

cubic meter (m3

) 0.0002642 million gallons (Mgal) 

cubic centimeter (cm3

) 0.06102 cubic inch (in3) 

cubic decimeter (dm3

) 61.02 cubic inch (in3) 

liter (L) 61.02 cubic inch (in3

) 

cubic decimeter (dm3

) 0.03531 cubic foot (ft3) 

cubic meter (m3

) 35.31 cubic foot (ft3)

cubic meter (m3

) 1.308 cubic yard (yd3) 

cubic kilometer (km3

) 0.2399 cubic mile (mi3) 

Flow rate

meter per second (m/s) 3.281 foot per second (ft/s) 

meter per minute (m/min) 3.281 foot per minute (ft/min) 

meter per hour (m/hr) 3.281 foot per hour (ft/hr)

meter per day (m/d) 3.281 foot per day (ft/d)

meter per year (m/yr) 3.281 foot per year ft/yr) 

cubic meter per second (m3

/s) 35.31 cubic foot per second (ft3/s)

cubic meter per second per 

square kilometer [(m3

/s)/km2]

91.49 cubic foot per second per square mile [(ft3

/s)/mi2]

cubic meter per day (m3

/d) 35.31 cubic foot per day (ft3/d) 

liter per second (L/s) 15.85 gallon per minute (gal/min) 

cubic meter per day (m3

/d) 264.2 gallon per day (gal/d) 

cubic meter per second (m3

/s) 22.83 million gallons per day (Mgal/d) 

kilometer per hour (km/h) 0.6214 mile per hour (mi/h)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

megagram (Mg) 1.102 ton, short (2,000 lb)

megagram (Mg) 0.9842 ton, long (2,240 lb)

metric ton per day 1.102 ton per day (ton/d) 
iv

Magnetic susceptibility

magnetic susceptibility (SI) 1/(4π)=0.079577 magnetic susceptibility (cgs or electromagnetic 

unit per cubic centimeter [emu/cm3

])

Density

kilogram per cubic meter (kg/m3

) 0.001 grams per cubic centimeter (g/cm3) 

Hydraulic conductivity

meter per day (m/d) 3.281 foot per day (ft/d) 

Hydraulic gradient

meter per kilometer (m/km) 5.27983 foot per mile (ft/mi) 

Transmissivity*

meter squared per day (m2

/d) 10.76 foot squared per day (ft2/d) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the insert datum name (and abbreviation) here, 

for instance, “North American Vertical Datum of 1988 (NAVD 88)”

Horizontal coordinate information is referenced to the insert datum name (and abbreviation) 

here, for instance, “North American Datum of 1983 (NAD 83)”

Altitude, as used in this report, refers to distance above the vertical datum.

*Transmissivity: The standard unit for transmissivity is cubic foot per day per square foot times 

foot of aquifer thickness [(ft3/d)/ft2]ft. In this report, the mathematically reduced form, foot 

squared per day (ft2/d), is used for convenience.

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm at 

25 °C).

Electrical conductivity is given in microsiemens per centimeters (μS/cm).

Resistivity is given in ohm-meters.

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).

Conversion Factors—Continued

SI to Inch/Pound

Multiply By To obtain
v

Contents

Introduction............................................................................................................................................1

Laboratory Facilities and Capabilities 4

Spectroscopy Laboratory ..................................................................................................4

References Cited...................................................................................................................................5

Geophysical Instrumentation Laboratory.......................................................................6

Denver Microbeam Laboratory for Microanalysis.......................................................7

Selection of Published Research Supported by the Denver Microbeam Laboratory...............7

Minerals and Health Laboratory ......................................................................................8

Projects...................................................................................................................................................8

Primary Products ..................................................................................................................................8

References Cited...................................................................................................................................9

Petrophysics Laboratory....................................................................................................9

References Cited...................................................................................................................................9

Biocatalysis Laboratory...................................................................................................10

References Cited.................................................................................................................................10

Gene-Based Techniques in Support of U.S. Geological Survey Environmental 

Health and Ecology Studies ................................................................................11

References Cited.................................................................................................................................12

Identification of Trace-Metal Species and Their Distribution in Rocks, 

Sediments, and Biota Using Synchrotron Techniques ..................................13

References Cited.................................................................................................................................13

Method and Software Development 15

U.S. Geological Survey Digital Spectral Library ........................................................15

Issue and Scope..................................................................................................................................15

Objectives.............................................................................................................................................15

Background..........................................................................................................................................15

Results and Conclusions ...................................................................................................................16

Additional Information .......................................................................................................................16

References Cited.................................................................................................................................16

Remote Identification, Mapping, and Quantification of Materials.........................17

Issue and Scope..................................................................................................................................17

Objectives.............................................................................................................................................17

Background..........................................................................................................................................17

Results and Conclusions ...................................................................................................................19

Primary Products ................................................................................................................................19

References Cited.................................................................................................................................19
vi

Multifaceted Approach to Microanalysis....................................................................20

Issue and Scope..................................................................................................................................20

Objectives.............................................................................................................................................20

Background..........................................................................................................................................20

Results and Conclusions ...................................................................................................................20

Collaborators .......................................................................................................................................23

References Cited.................................................................................................................................23

Three-Dimensional Magnetotelluric Inversion for Improved Structural

Imaging....................................................................................................................23

Issue and Scope..................................................................................................................................23

Objectives.............................................................................................................................................24

Background..........................................................................................................................................24

Results and Conclusions ...................................................................................................................24

References Cited.................................................................................................................................26

Improving Radar and Acoustic Imaging.......................................................................29

Issue and Scope..................................................................................................................................29

Objectives.............................................................................................................................................29

Background..........................................................................................................................................29

Results and Conclusions ...................................................................................................................29

Collaborators .......................................................................................................................................30

Selected References..........................................................................................................................30

U.S. Geological Survey Open-Source Ground Penetrating Radar Software ........31

Issue and Scope..................................................................................................................................31

Objectives.............................................................................................................................................31

Background..........................................................................................................................................32

Results and Conclusions ...................................................................................................................32

Collaborators .......................................................................................................................................32

References Cited.................................................................................................................................32

Potential-Field Software .................................................................................................35

Issue and Scope..................................................................................................................................35

Objectives.............................................................................................................................................35

Background..........................................................................................................................................35

Results and Conclusions ...................................................................................................................35

Collaborators .......................................................................................................................................36

References Cited.................................................................................................................................36

Improving Geophysical Model Assessment with Bayesian Markov Chain 

Monte Carlo Methods...........................................................................................37

Issue and Scope..................................................................................................................................37

Objectives.............................................................................................................................................37

Background..........................................................................................................................................38

Results and Conclusions ...................................................................................................................38

Selected References..........................................................................................................................41
vii

Instrument Development 42

Development and Implementation of Passive Electrical Monitoring Arrays.......42

Issue and Scope..................................................................................................................................42

Objectives.............................................................................................................................................42

Background..........................................................................................................................................43

Results and Conclusions ...................................................................................................................43

Collaborators .......................................................................................................................................44

Selected References..........................................................................................................................44

Development of a Waterborne Electromagnetic Survey System............................44

Issue and Scope..................................................................................................................................44

Objectives.............................................................................................................................................44

Background..........................................................................................................................................44

Results and Conclusions ...................................................................................................................45

Collaborators .......................................................................................................................................45

Selected References..........................................................................................................................45

Minerals, Energy, and Climate 48

Integrated Structural Geologic and Potential-Field Geophysical Studies to 

Understand the Spatial Localization of Magmatic-Hydrothermal 

Mineral Deposits ...................................................................................................48

Issue and Scope..................................................................................................................................48

Objectives.............................................................................................................................................48

Background..........................................................................................................................................48

Results ..................................................................................................................................................48

Conclusions..........................................................................................................................................50

Acknowledgments..............................................................................................................................50

Related Project References..............................................................................................................50

References Cited.................................................................................................................................50

Geophysical Support for Global Mineral Resource Assessments .........................52

Issue and Scope..................................................................................................................................52

Objectives.............................................................................................................................................52

Background..........................................................................................................................................52

Results and Conclusions ...................................................................................................................52

Collaborators .......................................................................................................................................52
viii

References Cited.................................................................................................................................52

U.S. Geological Survey Cooperative Research on Carbon Dioxide 

Sequestration Using Ultramafic and Carbonate Rocks.................................54

Issue and Scope..................................................................................................................................54

Objectives.............................................................................................................................................54

Background..........................................................................................................................................54

Accelerated Weathering of Limestone..................................................................................54

Mineral Carbonation Using Ultramafic Rocks ......................................................................54

Results and Conclusions ...................................................................................................................54

Collaborators .......................................................................................................................................56

For Additional Information.................................................................................................................56

References Cited.................................................................................................................................56

Three-Dimensional Magnetic Property Model Characterizing the Mesozoic 

Section of the Cook Inlet Basin, South-Central Alaska.................................57

Issue and Scope..................................................................................................................................57

Objectives.............................................................................................................................................57

Background..........................................................................................................................................57

Results and Conclusions ...................................................................................................................57

Collaborators .......................................................................................................................................59

Selected References..........................................................................................................................59

Integrated Research on Hydrogeological and Geochemical Processes in a 

Mineralized Alpine Watershed—Handcart Gulch, Colorado ......................59

Issue and Scope..................................................................................................................................59

Objectives.............................................................................................................................................59

Background..........................................................................................................................................60

Results, Conclusions, and Ongoing Work.......................................................................................61

Collaborators .......................................................................................................................................61

References Cited.................................................................................................................................61

Overview of Carbon Reservoirs and Sequestration in Sulfide 

Mine Wastes...........................................................................................................66

Issue and Scope..................................................................................................................................66

Objectives.............................................................................................................................................66

Background..........................................................................................................................................66

Results and Conclusions ...................................................................................................................67

References Cited.................................................................................................................................68

Metals Sequestration by Biochar in Sulfide-Bearing Mine-Waste Leachate 

Experiments—Implications for Mine-Waste Reclamation and Carbon 

Sequestration .........................................................................................................68

Issue and Scope..................................................................................................................................68

Objectives.............................................................................................................................................68

Background..........................................................................................................................................68

Results and Conclusions ...................................................................................................................69

Collaborators .......................................................................................................................................70

Selected References..........................................................................................................................70
ix

Element Cycling, Toxicity, and Health 72

Salt and Selenium Cycling in Shale-Derived Soils, Southwestern 

United States ..........................................................................................................72

Issue and Scope..................................................................................................................................72

Objectives.............................................................................................................................................72

Background..........................................................................................................................................72

Results and Conclusions ...................................................................................................................73

Collaborators .......................................................................................................................................75

References Cited.................................................................................................................................75

Microbial Communities Involved in Arsenic and Iron Cycling at the Lava Cap 

Mine Superfund Site, California.........................................................................76

Issue and Scope..................................................................................................................................76

Objectives.............................................................................................................................................76

Background..........................................................................................................................................76

Results and Conclusions ...................................................................................................................76

Collaborators .......................................................................................................................................80

References Cited.................................................................................................................................80

Geochemical Signatures as Natural Fingerprints .....................................................80

Issue and Scope..................................................................................................................................80

Objectives.............................................................................................................................................80

Background..........................................................................................................................................80

Results and Conclusions ...................................................................................................................81

Collaborators .......................................................................................................................................81

References Cited.................................................................................................................................83

Trace Metal Partitioning Between Sediments and Groundwater in the 

Basin-Fill Aquifer Surrounding Fallon, Nevada..............................................84

Issue and Scope..................................................................................................................................84

Objectives.............................................................................................................................................84

Background..........................................................................................................................................84

Results and Conclusions ...................................................................................................................84

Acknowledgments..............................................................................................................................86

Collaborators .......................................................................................................................................86

References Cited.................................................................................................................................86

Bioaccessibility of Potentially Toxic Metals and Metalloids in 

Earth Materials ......................................................................................................87

Issue and Scope..................................................................................................................................87

Objectives.............................................................................................................................................87

Background..........................................................................................................................................87

Results and Conclusions ...................................................................................................................88

Collaborators .......................................................................................................................................89

Publications Funded in Part by This Project ..................................................................................89
x

Diffusive Gradients in Thin Films and Biotic Ligand Models—Tools for 

Evaluating the Health of the Environment........................................................90

Issue and Scope..................................................................................................................................90

Objectives.............................................................................................................................................90

Background..........................................................................................................................................90

Results and Conclusions ...................................................................................................................91

Collaborators .......................................................................................................................................92

Selected References..........................................................................................................................92

Influence of Organic Matter on Copper Toxicity in Streams Impacted 

by Mining.................................................................................................................93

Issue and Scope..................................................................................................................................93

Objectives.............................................................................................................................................93

Background..........................................................................................................................................93

Results and Conclusions ...................................................................................................................93

Collaborators .......................................................................................................................................94

Selected References .........................................................................................................................95

Detection of Potentially Asbestos-Bearing Rocks Using Imaging 

Spectroscopy..........................................................................................................95

Issue and Scope..................................................................................................................................95

Objectives.............................................................................................................................................95

Background..........................................................................................................................................96

Results and Conclusions ...................................................................................................................96

Collaborators .......................................................................................................................................98

Publications Funded in Part by This Project ..................................................................................98

References Cited.................................................................................................................................98

Hydrology and Water Quality 101

MiniSipper—New, Long-Duration, Automated, In Situ Sampler for 

High-Resolution Water-Quality Monitoring...................................................101

Issue and Scope................................................................................................................................101

Objectives...........................................................................................................................................101

Background........................................................................................................................................101

Results and Conclusions .................................................................................................................102

Collaborators .....................................................................................................................................103

Selected References........................................................................................................................103

Mapping the Environment—Pollution, Organics, and Bacteria ...........................103

Issue and Scope................................................................................................................................103

Objectives...........................................................................................................................................103

Background........................................................................................................................................103

Results and Conclusions .................................................................................................................106

Primary Products ..............................................................................................................................106

References Cited...............................................................................................................................106
xi

Aeromagnetic Methods for Mapping Covered Faults in Sediments ....................108

Issue and Scope................................................................................................................................108

Objectives...........................................................................................................................................108

Background........................................................................................................................................108

Results and Conclusions .................................................................................................................108

Related U.S. Geological Survey Project........................................................................................110

References Cited...............................................................................................................................110

Constraints on Rio Grande Rift Structure and Stratigraphy from 3-D 

Magnetotelluric Modelling, Española Basin, New Mexico ......................110

Issue and Scope................................................................................................................................110

Objectives...........................................................................................................................................110

Background........................................................................................................................................110

Results and Conclusions .................................................................................................................112

Collaborators .....................................................................................................................................112

Selected References........................................................................................................................112

Providing a Subsurface Framework for Regional Groundwater Models of 

Alluvial Basins—Example from the Southern Española Basin, 

North-Central New Mexico...............................................................................113

Issue and Scope................................................................................................................................113

Objectives...........................................................................................................................................113

Background........................................................................................................................................115

Results and Conclusions .................................................................................................................115

Related U.S. Geological Survey Project........................................................................................115

References Cited...............................................................................................................................115

Hazards and Disaster Assessment 116

Geophysics of Volcanic Landslide Hazards—Inside Story....................................116

Issue and Scope................................................................................................................................116

Objectives...........................................................................................................................................116

Background........................................................................................................................................116

Results and Conclusions .................................................................................................................116

Collaborators .....................................................................................................................................118

References Cited...............................................................................................................................118

Helicopter Electromagnetic Surveys Over Volcanoes—Resolution and 

Limitations for Mapping Ice Thickness ..........................................................119

Issue and Scope................................................................................................................................119

Objectives...........................................................................................................................................119

Background........................................................................................................................................119

Results and Conclusions .................................................................................................................120

Collaborators .....................................................................................................................................123

Selected References........................................................................................................................123
xii

Geophysical Investigations for Dam and Levee Safety Engineers .......................124

Issue and Scope................................................................................................................................124

Objectives...........................................................................................................................................124

Background........................................................................................................................................124

Results and Conclusions .................................................................................................................125

Collaborators .....................................................................................................................................127

Bibliography.......................................................................................................................................128

Ground-Based Magnetic Survey for a Basalt Aquifer in Frenchman Flat, 

Nevada National Security Site and Nevada Test and Training Range, 

Nevada...................................................................................................................129

Issue and Scope................................................................................................................................129

Objectives...........................................................................................................................................129

Background........................................................................................................................................129

Results and Conclusions .................................................................................................................129

Collaborators .....................................................................................................................................129

Selected References........................................................................................................................129

Estimating Bedrock Depth Using Constrained Gravity Inversion, 

Tooele Army Depot, Utah....................................................................................131

Issue and Scope................................................................................................................................131

Objectives...........................................................................................................................................131

Background........................................................................................................................................131

Results and Conclusions .................................................................................................................132

Collaborators .....................................................................................................................................132

Reference Cited.................................................................................................................................132

Development of the ALLTEM, an Electromagnetic System for Detection and 

Discrimination of Munitions and Explosives of Concern............................134

Issue and Scope................................................................................................................................134

Objectives...........................................................................................................................................134

Background........................................................................................................................................134

Results and Conclusions .................................................................................................................137

Collaborators .....................................................................................................................................137

References Cited...............................................................................................................................137

Development of a Ground-Based Tensor Magnetic Gradiometer System ..........138

Issue and Scope................................................................................................................................138

Objectives...........................................................................................................................................138

Background........................................................................................................................................138

Results and Conclusions .................................................................................................................138

Collaborators .....................................................................................................................................140
xiii

U.S. Geological Survey Environmental Studies of the World Trade Center 

Area, New York City, after September 11, 2001 .............................................141

Issue and Scope................................................................................................................................141

Objectives...........................................................................................................................................141

Background........................................................................................................................................141

Results and Conclusions .................................................................................................................141

Collaborators .....................................................................................................................................141

Primary Products ..............................................................................................................................141

References Cited...............................................................................................................................141

Spectral Studies of the Deepwater Horizon Oil Spill..............................................144

Issue and Scope................................................................................................................................144

Objectives...........................................................................................................................................144

Background........................................................................................................................................144

Results and Conclusions .................................................................................................................144

Collaborators .....................................................................................................................................146

Primary Products ..............................................................................................................................146

References Cited...............................................................................................................................148

Databases and Framework Studies 149

Unlocking Secrets of East Antarctica with Geophysics.........................................149

Issue and Scope................................................................................................................................149

Objectives...........................................................................................................................................149

Background........................................................................................................................................149

Results and Conclusions .................................................................................................................149

Collaborators .....................................................................................................................................150

References Cited...............................................................................................................................150

Linking Petrophysical Properties to Environmental and Geological Factors ....152

Issue and Scope................................................................................................................................152

Objectives...........................................................................................................................................153

Background........................................................................................................................................153

Results and Conclusions .................................................................................................................154

Collaborators .....................................................................................................................................155

References Cited...............................................................................................................................156

Restoring a National Treasure—Recovery and Reprocessing of Legacy 

Airborne Data from the Tape Archives of the State Company of 

Geological Survey and Mining (GEOSURV-IRAQ) ........................................157

Issue and Scope................................................................................................................................157

Objectives...........................................................................................................................................157

Background........................................................................................................................................157

Results and Conclusions .................................................................................................................157

Collaborators .....................................................................................................................................157

Bibliography.......................................................................................................................................158
xiv

Figures

1. Diagram showing Integrated Methods Development Project (2008–2012) was an 

interdisciplinary project to develop tools and conduct innovative research requiring 

integration of geologic, geophysical, geochemical, and remote-sensing expertise........1

2. Photograph showing an analytical instrument has a specially designed environment 

chamber for spectral measurement of materials over a wide range of temperatures 

and pressures at wavelengths from the ultraviolet to the far infrared................................4

3. Photographs showing geophysical Instrumentation Laboratory projects and 

facilities ..........................................................................................................................................6

4. Photograph showing sediment sample prepared for a four-electrode, low-frequency 

(0.001 to 1,000 hertz) electrical resistivity measurement .......................................................9

5. Photograph showing reaction vessel for studying mine waste geochemistry................10

6. Graph showing comparison of spectra for alunite from four sensors with different 

spectral resolutions....................................................................................................................15

7. Graph showing spectra of the pyrite weathering sequence from the U.S. Geological 

Survey spectral library...............................................................................................................16

8. Map and graph showing use of Tetracorder mapping system at Leadville, Colorado, 

mining district..............................................................................................................................19

9. Graph showing spectrum of Saturn’s moon lapetus.............................................................19

10. Grayscale image shows the cathodoluminescence intensity of quartz ...........................21

11. Backscattered electron (BSE) image (top) and X-ray intensity maps of lead (Pb),

phosphorus (P), and tungsten (W) from a Nigerian soil sample.........................................22

12. Map, 3-D inversion model, and cross sections showing copper-gold-molybdenum 

porphyry deposit, southwest Alaska .......................................................................................25

13. Graph, cross section, and inverse model showing magnetotelluric profile data 

distorted by coast effect, southwest Oregon.........................................................................27

14. Map showing resistivity depth slices through the Pacific Northwest United States at 

depths of A, 1 kilometer and B, 20 kilometer..........................................................................28

15. Model estimated from the crosswell radar data...................................................................30

16. Example GprViewer+ screens ..................................................................................................33

17. Screen example use of hyperbola fitting (to rebar reflections) for velocity analysis 

of concrete...................................................................................................................................34

18. PDEPTH (a graphical magnetic- and gravity-profile-analysis program) is one

example of a U.S. Geological Survey potential-field software program

incorporating a graphical user interface................................................................................36

High-Altitude Magnetic Survey of the Conterminous United States, Alaska, 

and Offshore Regions..........................................................................................159

Issue and Scope................................................................................................................................159

Objectives...........................................................................................................................................159

Background........................................................................................................................................160

Results and Conclusions .................................................................................................................160

Collaborators .....................................................................................................................................160

References Cited...............................................................................................................................160
xv

19. Airborne frequency-domain electromagnetic profile in western Nebraska....................39

20. Graphs showing Markov chain Monte Carlo (MCMC)-sampled probability 

distribution from figure 19E compared with deterministic inversion result (green 

curve), borehole resistivity logs (yellow curves), and lithologic data (right panel).........40

21. Photographs showing electrical monitoring array ...............................................................42

22. Photographs showing deployment of electrodes .................................................................43

23. Photographs showing waterborne electromagnetic system consisting of 

watercraft for towing and data acquisition (left) and the electromagnetic bird 

mounted on a pontoon raft (right)............................................................................................45

24. Graph and map showing apparent resistivity data...............................................................46

25. Graphs showing comparison of airborne helicopter electromagnetic data and 

waterborne electromagnetic data...........................................................................................47

26. Contour map of calculated depths to the base of Butte Quartz Monzonite using a

3-D gravity inversion model ......................................................................................................49

27. Map showing the complex networks of linked, fanning, or horsetailing faults color 

coded to show how groups of faults may have grown as a set .........................................51

28. Map showing polymetallic quartz veins and faults in the Butte mining district ..............51

29. Generalized tectonic map of the Spasski fold belt in Central Asia, plotted on 

top of a color shaded-relief, reduced-to-pole aeromagnetic map.....................................53

30. National-scale maps of A, carbonate rocks and B, magnesium-rich ultramafic

rocks thought suitable for carbon dioxide sequestration in the

conterminous United States .....................................................................................................55

31. Examples of enhancements applied to magnetic survey data ...........................................56

32. Three-dimensional magnetization model for the Cook Inlet, Alaska, colored to

emphasize lithostratigraphic boundaries ...............................................................................58

33. Maps and aerial photography showing handcart Gulch in central Colorado..................60

34. Photographs, model results, and graphs showing watershed approach used to 

understand the processes controlling water availability and water quality ....................62

35. Photograph showing formation of iron oxide on acid neutralizing capacity (ANC) 

rock surfaces in reaction vessel; mine waste material is the upper light-tan layer.......67

36. Photographic showing acid neutralizing capacity (ANC) rock aiding vegetation 

and soil recovery of mine waste ..............................................................................................69

37. Scanning electron microscope, secondary electron image of pine wood biochar

produced by Biochar Engineering Corporation, Niwot, Colorado, using a two-stage,

low-temperature pyrolysis unit ................................................................................................69

38. Scanning electron microscope, backscatter image of pine-wood biochar exposed

to mine-waste leachate in vessel test ....................................................................................70

39. Graph showing depth profile of Mancos Shale trench showing tau (τ) values for 

total salt (gypsum equivalent, [GE]) and selenium (Se) in soil, transition soil, and 

shale..............................................................................................................................................73

40. Graph showing salt and selenium extract (ex) concentrations (dry weight basis) in 

sequential saturation paste extracts. mg/kg, milligrams per kilogram..............................74

41. Map showing regional to site-level overview of the Lava Cap Mine Superfund Site, 

Nevada County, California.........................................................................................................77

42. Boxplots showing basic statistics of arsenic (top), iron, and manganese dry weight

concentrations measured over the study period at several locations at the Lava

Cap Mine Superfund Site ..........................................................................................................78
xvi

43. Graph showing percent attenuation of dissolved arsenic (As), iron (Fe), and

manganese (Mn) through a naturally developed passive bioreactor system that

was measured several times during the study period as the difference between

the dissolved concentrations of these elements measured at site LL1 (where low

oxygen [O2], Fe-, Mn-, and As-rich water seeps out below the dam) and site LL10

(just upstream of the site where seep water meets highly oxygenated lake water

from the dam spillway)...............................................................................................................79

44. Dual-transmitted-light and epifluorescent-light image (400×) of cells of a

sheath-forming, iron-oxidizing bacterium (L. ochracea) that composes the bulk of

the biogenic ferric (hydr)oxide produced at the Lava Cap Mine Superfund Site............79

45. Photographs showing collection and sample preparation of Tanner crabs from 

Glacier Bay National Park.........................................................................................................81

46. Map showing sampling locations relative to generalized bedrock geology, and the 

locations of known mineral occurrences within Glacier Bay National Park ...................82

47. Boxplots of A, in Ca (logarithm calcium) concentration and B, in Mo (molybdenum)

concentration in carapaces based on the bay of origin and C, plots of delta N

(nitrogen) compared to delta C (carbon) for the muscle and shell ....................................83

48. Graph showing partitioning of trace elements among seven sediment fractions ..........85

49. Schematic diagram illustrating exposure pathways and variability in body fluid

types and compositions that can be encountered by earth materials ..............................88

50. Graph showing total fluoride, simulated gastric fluid (SGF) leach, and water-leach 

fluoride concentrations for volcanic ash samples................................................................89

51. Photograph showing deployment of diffusive gradients in thin films (DGT) 

samplers in the Coeur d’Alene River in northern Idaho.......................................................91

52. Photograph showing preparing to deploy diffusive gradients in thin films (DGT) 

samplers in the upper Columbia River in northeastern Washington in-line with 

flow from seepage meters ........................................................................................................92

53. Photograph showing measuring radon in the upper Columbia River in northeastern 

Washington. Precipitation of iron oxide during exchange between metal-enriched 

groundwater and river water likely accounts for the red staining on the rocks .............92

54. Photograph showing sampling locations for natural organic matter (NOM) in the 

mixing zone below the confluence of the Snake River with Deer Creek near 

Montezuma, Summit County, Colorado...................................................................................94

55. Graph showing toxicity test results for copper acute toxicity using water fleas in 

water amended with natural organic matter (NOM) isolated from water (blue) and 

suspended sediment (red) collected from the Snake River, Colorado ..............................94

56. Maps showing ultamafic rocks in California..........................................................................96

57. Reflectance spectra of serpentine minerals and color-coded AVIRIS maps of

asbestos-related mineralogy and vegetation ........................................................................97

58. Map, graph, and photograph showing determination of the effects of variable 

grass cover on spectral identification of underlying serpentine in the Garden 

Valley study area.........................................................................................................................99

59. Photograph showing difficulties with water sampling at abandoned mine site in 

late spring ..................................................................................................................................101

60. Photograph showing MiniSipper with electronics housing, sample coil, and gas 

(nitrogen, N2) bag .....................................................................................................................101

61. Photograph showing year-long record of aluminum (Al), zinc (Zn), flow, and 

conductivity at the Standard Mine ........................................................................................102

62. Spectral map of phytoplankton-rich water shows a plume originating from the

shore of Turquoise Lake in Colorado.....................................................................................104
xvii

63. Screen image of the Hyperion imaging spectrometer on the EO-1 satellite mapping

results for the Fort Cobb reservoir, southwestern Oklahoma, in 2006 .............................105

64. Graph showing spectra of samples containing bacteria...................................................106

65. Tetracorder (Clark and others, 2003) materials maps for Norris Geyser Basin in

Yellowstone National Park using data from the NASA Airborne Visible and Infrared

Imaging Spectrometer (AVIRIS).............................................................................................107

66. Examples of aeromagnetic expressions of intrasedimentary normal faults and

associated derivative maps in the central Rio Grande rift (inset). Images are

displayed as color-shaded relief, illuminated from the west ............................................109

67. Simplified geologic map and cross section location of Santa Fe region, New Mexico,

showing regional boreholes (solid red circles), magnetotelluric (MT) stations

(green circles), and the MT profile cross section (solid black line).................................111

68. Profile A–A′ is a resistivity section extracted from the 3-D resistivity model with

gross lithologic interpretation ................................................................................................112

69. Perspective view of the modeled elevation of the base of the alluvial aquifer in the

southern Española Basin in relation to topography, looking east. Topographic

surface is raised above the base...........................................................................................114

70. Three-dimensional view of the distribution of water and alteration based on

geologic mapping, resistivity (upper 300 meters), and magnetic (>300-meter

thickness) models and measured rock properties..............................................................117

71. Graph showing uncertainties in ice thickness estimates as a function of ice 

thickness and basement resistivity .......................................................................................120

72. Example of cross section from Mount Adams two-layer laterally continuous

inversions...................................................................................................................................120

73. Maps showing ice thicknesses for Mounts Baker and Adams........................................122

74. Photograph showing Success Dam above Portersville, California, has over 250 

boreholes drilled into the foundation materials to characterize soft sediments 

with a potential for liquefaction .............................................................................................125

75. Photograph showing view of the downstream toe of the west abutment of Isabella 

Auxiliary Dam showing seismic equipment deployed across a fault zone between 

the top and bottom of the hill ..................................................................................................126

76. Photograph showing student interns help acquire seismic data on the reservoir 

side of Martis Creek Dam using a trailer-mounted seismic source.................................127

77. Raw magnetic-profile data after removal of the diurnal field plotted as colored dots

on a hydrostratigraphic-unit base map (Bechtel Nevada, 2005) with alluvial units

above the basalt removed.......................................................................................................130

78. Map showing bedrock elevation for the Tooele Army Depot, Tooele, Utah, as 

estimated using constrained gravity inversion. The solution is colored within 

1,500 feet of outcrops, boreholes, and gravity stations. Note the nonlinear color 

scale. Reliability is expected to be poor in the uncolored areas......................................133

79. Graph showing ALLTEM (ALL-the-Time-ElectroMagnetic) transmitter triangular 

waveform and measured responses from steel (ferrous) and brass (nonferrous) 

balls.............................................................................................................................................134

80. Phototgraphs showing ALLTEM (ALL-the-Time-ElectroMagnetic) system ....................135

81. Map showing processed ALLTEM (ALL-the-Time-ElectroMagnetic) target 

response from the1 meter gradiometer receiver with the horizontal coil (hertz) 

energized....................................................................................................................................136

82. Graph showing classified ALLTEM (ALL-the-Time-ElectroMagnetic) data from 

Yuma Proving Ground, Arizona...............................................................................................137
xviii

83. Photograph showing tensor magnetic gradiometer system undergoing tests at 

Yuma Proving Ground, Arizona...............................................................................................139

84. Photograph showing multiaxis magnetometer array is mounted in a towed 

platform, along with thermometers, inclinometers, and accelerometers.......................139

85. Photograph showing calibration coefficients were derived from measurements 

made as the magnetometer array was spun on a turntable apparatus in a nearly 

uniform magnetic field on site ................................................................................................139

86. Map showing high-quality data acquired by the prototype tensor magnetic 

gradiometer system..................................................................................................................140

87. False-color images showing the core affected area around the World

Trade Center (WTC) extending from 5 to 12 days after the collapse ...............................143

88. Graph showing laboratory spectra of oil:water emulsion from the Deepwater 

Horizon oil spill. Sample (DWH10-3) collected May 7, 2010 ..............................................145

89. Photograph of oil emulsion from the Deepwater Horizon oil spill in the Gulf of 

Mexico off the Louisiana coast..............................................................................................146

90. Mapping results for oil-to-water ratio for a portion of AVIRIS (airborne

visible and infra-red imaging spectrometer) flight line (May 17, 2010)............................146

91. Three-dimensional perspective of the Gamburtsev Subglacial Mountains, 

including a view of the deep root imaged beneath the range and of the thinner 

crust of the East Antarctic rift system that surrounds the mountains.............................150

92. Geologic map of the study area with locations of samples ..............................................152

93. Magnetic anomaly map over the volcanic rocks of the Tertiary Burns Member of

the Silverton Volcanics, southwestern Colorado................................................................154

94. Boxplot showing magnetic susceptibility ranges for geologic units sampled...............155

95. Map showing final recovered aeromagnetic data, gridded and merged .......................158

96. Diagram showing a lack of available signal strength (amplitude) in a spectral gap

that needs to be filled by data from a high-altitude magnetic survey (Hildenbrand

and others 1996)........................................................................................................................159

Tables

1. Available free ground penetrating radar analysis software ...............................................31

2. Statistics of sampled magnetizations (A/m) at well locations ............................................57

3. Total and extractable selenium and salt (gypsum equivalent) inventories for

Mancos Shale soil (0–45 centimeters) in the Uncompahgre River watershed.

Values are totals for the landscape (in metric tonnes [t]) and per square meter

(m–2) of landscape. Undisturbed landscapes are those above the flood plain (FP).......74

4. Fluxes calculated from precipitation rates, rainfall simulation data, and

saturation-paste-extract data are compared to loads measured in tributaries 

and the Uncompahgre River (UR) ............................................................................................74

5. Grain-size analysis .....................................................................................................................85

6. Results of modified Cordell-Henderson gravity inversion .................................................132

7. Geologic unit, age, and lithologic description of rocks sampled for this study ............153

8. Average and relative ranking of major lithologic units based on the average

physical or environmental property of each unit ................................................................156
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Developing Integrated Methods to Address Complex 

Resource and Environmental Issues

Edited by Kathleen S. Smith, Jeffrey D. Phillips, Anne E. McCafferty, and Roger N. Clark

Introduction

This circular provides an overview of selected activities that were conducted within the U.S. Geological Survey 

(USGS) Integrated Methods Development Project (fig. 1), 

an interdisciplinary project designed to develop new tools 

and conduct innovative research requiring integration of 

geologic, geophysical, geochemical, and remote-sensing 

expertise. The project was supported by the USGS Mineral 

Resources Program, and its products and acquired capabilities have broad applications to missions throughout the 

USGS and beyond.

The goals of the project were to anticipate new technologies and research directions that will be needed in the future 

and to support the following:

• Maintenance and expansion of existing laboratories, 

equipment, and capabilities;

• Development and evaluation of new methods and 

applications; and

• Innovative fundamental and applied research activities.

In addressing challenges associated with understanding 

the location, quantity, and quality of mineral resources, and 

in investigating the potential environmental consequences 

of resource development, a number of field and laboratory 

capabilities and interpretative methodologies evolved from the 

project that have applications to traditional resource studies as 

well as to studies related to ecosystem health, human health, 

disaster and hazard assessment, and planetary science. New 

or improved tools and research findings developed within 

the project have been applied to other projects and activities. 

Specifically, geophysical equipment and techniques have been 

applied to a variety of traditional and nontraditional mineraland energy-resource studies, military applications, environmental investigations, and applied research activities that 

involve climate change, mapping techniques, and monitoring 

capabilities. Diverse applied geochemistry activities provide a 

process-level understanding of the mobility, chemical speciation, and bioavailability of elements, particularly metals and 

metalloids, in a variety of environmental settings. Imaging 

spectroscopy capabilities maintained and developed within 

the project have been applied to traditional resource studies as 

well as to studies related to ecosystem health, human health, 

disaster assessment, and planetary science. Brief descriptions 

of capabilities and laboratory facilities and summaries of some 

applications of project products and research findings are 

included in this circular. The work helped support the USGS 

mission to “provide reliable scientific information to describe 

and understand the Earth; minimize loss of life and property 

from natural disasters; manage water, biological, energy, and 

mineral resources; and enhance and protect our quality of 

life.” Activities within the project include the following:

• Spanned scales from microscopic to planetary;

• Demonstrated broad applications across disciplines;

• Included life-cycle studies of mineral resources;

• Incorporated specialized areas of expertise in applied 

geochemistry including mineralogy, hydrogeology, 

analytical chemistry, aqueous geochemistry, 

Figure 1. Integrated Methods Development Project (2008–2012) 

was an interdisciplinary project to develop tools and conduct 

innovative research requiring integration of geologic, geophysical, 

geochemical, and remote-sensing expertise. Products and research 

conducted within the Integrated Methods Development Project 

have broad applications.
2 Developing Integrated Methods to Address Complex Resource and Environmental Issues

biogeochemistry, microbiology, aquatic toxicology, and 

public health; and

• Incorporated specialized areas of expertise in geophysics including magnetics, gravity, radiometrics, electromagnetics, seismic, ground-penetrating radar, borehole 

radar, and imaging spectroscopy.

Participating laboratory facilities and capabilities for 

the project include the Spectroscopy Laboratory, Geophysical Instrumentation Laboratory, Petrophysics Laboratory, 

Microbeam Laboratory, Minerals and Health Laboratory, and 

Biocatalysis Laboratory, all in Denver, Colorado, as well as 

Microbial Ecology Techniques and Synchrotron Techniques, 

both in Menlo Park, California.

Geophysical research within the project evaluated and 

improved existing geophysical methods, software, and instrumentation, and anticipated and developed new geophysical 

techniques and software applications that the USGS will need 

in the future. Method development occurred through formulation of new concepts and extension of existing theory, which 

were then implemented and tested in software that was applied 

to the processing and interpretation of geophysical data. In 

addition, funding from the project was used to maintain existing geophysical instrumentation and to develop new instrumentation and techniques that lead to improved data resolution 

or provide new information about geological, hydrological, or 

cultural sources of geophysical anomalies.

Applied geochemistry research within the project 

included a wide variety of applied geochemistry studies that 

have broad applications and frequently were conducted in collaboration with other USGS projects. These process-oriented 

research studies spanned scales (microscopic to regional) and 

environments (earth materials to human health) relevant to 

mineral and energy resources, water quality, climate change, 

ecosystem health, and human health. Emerging technologies; integrated laboratory, field, and modeling studies; and 

new state-of-the-art analytical methods were combined to 

advance our knowledge of processes that determine metal 

mobility, chemical speciation, and bioavailability in a variety 

of environmental settings. This process-level understanding 

provides the foundation for evaluating how the quality of 

water, sediment, and health of aquatic and terrestrial organisms is affected by natural and anthropogenic changes in the 

environment, and for assisting other Federal, State, and local 

agencies who make decisions about the management and use 

of our Nation’s natural resources. These studies frequently 

required specialized equipment and facilities, and numerous 

small laboratories supported this work.

Imaging spectroscopy research within the project developed and enhanced fundamental methodologies and databases 

that enable spectral identification and mapping strategies for 

minerals, vegetation, man-made materials, and other constituents that may be encountered in remote-sensing data. The 

USGS Spectral Library was managed and enhanced under 

this project. The library is the premier spectral database of 

earth materials, is used worldwide, and forms the knowledge 

base for all imaging spectroscopy studies where materials 

identification and mineral mapping is a goal. The library has 

been used by multiple projects under the Mineral Resources 

Program, the USGS response in Afghanistan, and USGS rapid 

responses (for example, Deepwater Horizon oil spill, World 

Trade Center disaster zones, and others). In addition, funding 

from the project was used to maintain the Spectroscopy Laboratory and spectrometers, which are critical to remote-sensing 

studies for a variety of applications.

A number of research activities were conducted within 

the project that required integration of geologic, geochemical, 

and geophysical information for traditional and nontraditional 

mineral-resource and mineral-environmental applications. 

These activities included the following topics:

• Coupled thermal, chemical, and mechanical processes 

in magmatic-hydrothermal systems that explain the 

localization and environments of moderate to hightemperature mineral deposits;

• Geophysical data from Greenland and Antarctica to 

help monitor ice sheet mass balance that is critical to 

understanding sea level rise;

• Processes that control tungsten concentrations in 

groundwater, which is related to possible environmental causes of a childhood leukemia cluster in Fallon, 

Nevada;

• Petrophysical properties related to mineral appraisals, 

environmental rock properties, volcanic hazards, and 

national security applications; and

• Mineral carbonation as a means to mitigate negative 

effects of global climate change.

This circular consists of eight sections that contain summaries of various activities under the project. The eight sections are listed below:

• Laboratory Facilities and Capabilities, which includes 

brief descriptions of the various types of laboratories 

and capabilities used for the project;

• Method and Software Development, which includes 

summaries of remote-sensing, geophysical, and mineralogical methods developed or enhanced by the project;

• Instrument Development, which includes descriptions of 

geophysical instruments developed under the project;

• Minerals, Energy, and Climate, which includes summaries of research that applies to mineral or energy 

resources, environmental processes and monitoring, 

and carbon sequestration by earth materials;

• Element Cycling, Toxicity, and Health, which includes 

summaries of several process-oriented geochemical and biogeochemical studies and health-related 

research activities;
Introduction 

3

• Hydrogeology and Water Quality, which includes 

descriptions of innovative geophysical, remotesensing, and geochemical research pertaining to hydro

-

geology and water-quality applications;

• Hazards and Disaster Assessment, which includes sum-

maries of research and method development that were 

applied to natural hazards, human-caused hazards, and 

disaster assessments; and

• Databases and Framework Studies, which includes 

descriptions of fundamental applications of geophysi-

cal studies and of the importance of archived data.
Spectroscopy Laboratory

By Gregg A. Swayze

The U.S. Geological Survey (USGS) Denver, Colorado, 

Spectroscopy Laboratory houses analytical instruments for 

the spectral measurement of samples under a full range of 

pressure and temperature conditions necessary to mimic all 

extremes on the Earth’s surface and the moons of the outer 

planets (fig. 2). Capabilities include reflectance and transmission measurements from the ultraviolet out into the far 

infrared (0.1 to 150 micrometers) at temperatures ranging 

from 77 to 500 kelvin (K) (–320 to 440 degrees Fahrenheit 

[°F]) and pressures ranging from a total vacuum up to several 

atmospheres. Data collected on these spectrometers have been 

used to map water on the Moon (Clark and others, 2009), 

identify opal on Mars (Milliken and others, 2008), and create 

an online spectral library used worldwide (Clark and others, 

2007). It is likely that the Denver Spectroscopy Laboratory 

is the only lab capable of making spectral measurements that 

span such a wide range of environmental conditions. We can 

bring our visible/near-infrared spectrometers to the field to 

make in situ measurements of samples and calibrate broadband or hyperspectral remote-sensing data. In the past, these 

portable instruments have played a critical role in mapping 

Figure 2. This analytical instrument has a specially designed environment chamber for spectral measurement of 

materials over a wide range of temperatures and pressures at wavelengths from the ultraviolet to the far infrared. This 

equipment allows simulation of conditions at the outer planets and extremes on the Earth’s surface. Multiple observation 

ports allow measurement by several spectrometers without disturbing the samples. (USGS photograph)

Laboratory Facilities and Capabilities
Laboratory Facilities and Capabilities 5

acid-mine drainage at abandoned mines (Swayze and others, 

2000), measuring asbestos in the World Trade Center dust 

(Clark and others, 2001) and potentially asbestos-bearing 

rocks in communities in the Sierra Nevada Foothills (Swayze 

and others, 2009), characterizing vegetation biochemistry to 

monitor global change (Kokaly and Clark, 1999), examining 

highly alkaline ash from wildfires (Kokaly and others, 2008), 

providing calibration for hyperspectral mineral images of 

Afghanistan (Kokaly and others, 2011), and estimating the 

volume of oil floating on the ocean surface during the Deepwater Horizon oil spill (Clark and others, 2010). 

To support these endeavors, the lab houses several 

mineral collections with thousands of samples used to compile our online spectral library used throughout the world by 

scientists conducting laboratory and remote-sensing studies. 

One of the collections contains man-made building materials so their spectra can be used to accurately map urban areas 

in case of natural or man-made disasters. We continually add 

new mineral entries to the library collections to support new 

remote-sensing applications. One thing that sets our spectral 

library apart from others is that we analyze sample purity with 

multiple analytical techniques and include this “metadata” 

with the spectra in our online library.

A key part of the Spectroscopy Laboratory is its computing facilities, which are some of the largest in the USGS. 

Spectroscopic analysis and hyperspectral mapping and identification require tremendous computing power. The USGS 

Spectroscopy Laboratory has multiple Linux and UNIX computer servers. The main machine is a 24-cpu (central processing unit) system with 296 gigabytes of random access memory 

(RAM) and more than 140 terabytes of disk space, containing 

spectroscopy and hyperspectral data for the Earth, Mars, the 

Moon, and other objects throughout the Solar System. The 

compute power allows up to 60 million spectral features per 

second to be compared enabling large imaging spectroscopy 

datasets to be analyzed rapidly. 

References Cited

Clark, R.N., 2009, Detection of absorbed water and hydroxyl 

on the Moon: Science, v. 226, no. 5952, p. 562–564.

Clark, R.N., Green, R.O., Swayze, G.A., Meeker, Greg, 

Sutley, Steve., Hoefen, T.M., Livo, K.E., Plumlee, Geoff, 

Pavri, Betina, Sarture, Chuck, Wilson, Steve, Hageman, 

Phil, Lamothe, Paul, Vance, J.S., Boardman, Joe, Brownfield, Isabelle, Gent, Carol, Morath, L.C., Taggart, Joseph, 

Theodorakos, P.M., and Adams, Monique, 2001, Environmental studies of the World Trade Center area after the September 11, 2001 attack: U.S. Geological Survey Open-File 

Report 01–0429, 260 p.

Clark, R.N., Swayze, G.A., Leifer, Ira, Livo, K.E., Kokaly, 

Raymond, Hoefen, Todd, Lundeen, Sarah, Eastwood, 

Michael, Green, R.O., Pearson, Neil, Sarture, Charles, 

McCubbin, Ian, Roberts, Dar, Bradley, Eliza, Steele, Denis, 

Ryan, Thomas, Dominguez, Roseanne, and the Airborne 

Visible/Infrared Imaging Spectrometer (AVIRIS) Team, 

2010, A method for quantitative mapping of thick oil spills 

using imaging spectroscopy: U.S. Geological Survey OpenFile Report 2010–1167, 51 p.

Clark, R.N., Swayze, G.A., Wise, R.A., Livo, K.E., Hoefen, 

T.M., Kokaly, R.F., and Sutley, S.J., 2007, USGS digital 

spectral library splib06a: U.S. Geological Survey Digital 

Data Series DS–231, [about 6,100] p.

Kokaly, R.F., and Clark, R.N., 1999, Spectroscopic determination of leaf biochemistry using band-depth analysis of 

absorption features and stepwise multiple linear regression: 

Remote Sensing of Environment, v. 67, p. 267–287.

Kokaly, R.F., King, T.V.V., Hoefen, T.M., Dudek, K.B., and 

Livo, K.E., 2011, Surface materials map of Afghanistan—

Carbonates, phyllosilicates, sulfates, altered minerals, and 

other materials: U.S. Geological Survey Scientific Investigations Map 3152–A, one sheet, scale 1:1,100,000, http://

pubs.usgs.gov/sim/3152/A/.

Kokaly, R.F., Rockwell, B.W., Haire, S.L., and King, T.V.V., 

2007, Characterization of post-fire surface cover, soils, and 

burn severity at the Cerro Grande Fire, New Mexico, using 

hyperspectral and multispectral remote sensing: Remote 

Sensing of Environment, v. 106, p. 305–325.

Milliken, R.E., Swayze, G.A., Arvidson, R.E., Bishop, J.L., 

Clark, R.N., Ehlmann, B.L., Green, R.O., Grotzinger, J.P., 

Morris, R.V., Murchie, S.L., Mustard, J.F., Weitz, C., and 

the CRISM Science Team, 2008, Opaline silica in young 

deposits on Mars: Geology, v. 36, no. 11, p. 847–850.

Swayze, G.A., Kokaly, R.F., Higgins, C.T., Clinkenbeard, J.P., 

Clark, R.N., Lowers, H.A., and Sutley, S.J., 2009, mapping 

potentially asbestos-bearing rocks using imaging spectroscopy: Geology, v. 37, no. 8, p. 763–766.

Swayze, G.A., Smith, K.S., Clark, R.N., Sutley, S.J., Pearson, 

R.N., Rust, G.S., Vance, J.S., Hageman, P.L., Briggs, P.H., 

Meier, A.L., Singleton, M.J., and Roth, Shelly, 2000, Using 

imaging spectroscopy to map acidic mine waste: Environmental Science and Technology, v. 34, no. 1, p. 47–54.
6 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Geophysical Instrumentation Laboratory

By Craig W. Moulton

The primary objective of the Geophysical Instrumentation Laboratory is the development of new geophysical instrumentation that will lead to improved data resolution or provide 

other new information about geological, hydrological, or cultural sources of geophysical anomalies. A secondary objective 

is the maintenance of existing geophysical instrumentation.

The laboratory has a full machine shop containing two 

large engine lathes, two large mills and all associated tooling, large-throat band saws, a wide metal shear and brake, 

full welding capability (inert gases/arc/brazing/plasma cutter/

oxyacetylene), bead blasting, grinders, and band sanders. Also 

available is a full woodshop containing saws (radial/table/

compound miter/scroll/band), a joiner, drill press, and router 

table. The electronic laboratory equipment consists of oscilloscopes, function generators, network analyzers, laboratory 

power supplies, data acquisition systems, and a large assortment of board-level electronic components. The laboratory has 

printed circuit board layout capability. Software is developed 

for controlling data acquisition systems using the LabVIEW 

(from National Instruments) programming language.

Leveraging funding from the U.S. Department of Defense 

Strategic Environmental Research and Development Program 

and the Environmental Technology Demonstration and Validation Program, the laboratory has developed a tractor-towed 

unexploded ordnance (UXO) detection system called the 

ALLTEM (on ALL the Time Electro-Magnetic) (fig. 3). The 

laboratory contributed its expertise in the development and 

fabrication of the ALLTEM mechanical systems (fiberglass cart 

and detection cube) and the electronic control and data acquisition systems. Software was developed to use global positioning 

system information to aid in UXO survey planning and tractor steering accuracy. The ALLTEM system is currently being 

used at a UXO cleanup project in Texas. Other projects recently 

developed include a seismic hammer-strike sensor with wireless 

transmission to a data acquisition system, an automated antenna 

positioning system to perform cross-well radar tomography 

experiments in a large sand tank, fabrication of flux-gate magnetometer instruments used for in situ long-term monitoring, 

and a modernization (new software and hardware) of the U.S. 

Geological Survey Petrophysics Instrumentation Laboratory’s 

nonlinear complex-resistivity measurement system.

Figure 3. Geophysical Instrumentation Laboratory projects and 

facilities. A, ALLTEM (on ALL the Time Electro-Magnetic) system 

performing an unexploded ordnance survey; B, ALLTEM cube; 

C, Machine shop; D, Magnetometer; and E, Wireless hammer. 

(USGS photographs)

A B

C D E
Laboratory Facilities and Capabilities 7

Denver Microbeam Laboratory for 

Microanalysis

By Heather A. Lowers

The Denver Microbeam Laboratory is an analytical 

facility that specializes in microanalysis—both chemical and 

morphological—of rocks, minerals, dust and particulates, 

and other materials from a wide variety of applications using 

electron-beam-based techniques. The laboratory supports 

programs within the Energy and Minerals and Environmental 

Health Mission Areas as well as other mission areas within 

the U.S. Geological Survey (USGS). In addition to collaborating with, and providing microanalytical services to USGS 

researchers, the Denver Microbeam Laboratory caters to a 

number of Federal, State, and international agencies, and academic researchers by agreement.

The Denver Microbeam Laboratory operates low-vacuum, 

low-voltage scanning electron microscopes (SEM). They are 

equipped with energy dispersive (EDS) X-ray analysis systems that are capable of elemental detection from beryllium 

to uranium. The EDS system provides the capability to image 

and chemically analyze a variety of samples including biological and geological materials, ceramics, polymers, composites, and metals. Both instruments are capable of imaging, at 

nanometer resolution, the surface features of materials (secondary electron imaging), subtle density variations within a 

sample (backscattered electron imaging), as well as defects 

related to trace-element impurities and structural defects 

(cathodoluminescence). One SEM is also equipped with an 

electron backscatter diffraction system that provides crystal 

structural information of the material. In addition there is a fully 

automated electron microprobe (electron probe micro-analyzer, 

EPMA) designed to produce in situ, quantitative elemental 

analysis from sample volumes as small as 2 micrometer in 

diameter at better than two percent accuracy and precision. The 

detection limit for most elements is between 300–800 parts per 

million, but using advanced methods, detection limits can be at 

single-digit parts per million levels. The electron microprobe 

also offers wavelength-dispersive X-ray intensity mapping, 

which provides better energy resolution than EDS mapping.

The Denver Microbeam Laboratory also maintains stereo 

and petrographic transmitted- and reflected-light microscopes 

with digital imaging capability and a variety of image processing and desktop publishing software. The laboratory has 

a clean room and facilities for manipulating small particles 

in preparation for analysis. Sample preparation equipment 

includes a vacuum impregnator, mechanical polishing apparatus, and an ion mill.

Selection of Published Research Supported by 

the Denver Microbeam Laboratory

Aleinikoff, J.N., Creaser, R.A., Lowers, H.A., Magee, C.W., 

Jr., and Grauch, R.I., 2012, Multiple age components 

in individual molybdenite grains: Chemical Geology, 

v. 300–301, p. 55–60.

Diehl, S.F., Goldhaber, M.B., Lowers, H.A., Koenig, A.E., 

and Ruppert, L.F., 2012, Distribution of arsenic, selenium, 

and other trace elements in high pyrite Appalachian coals—

Evidence for multiple episodes of pyrite formation: International Journal of Coal Geology Special Issue, Minerals and 

Trace Elements in Coal, v. 94, p. 238–249.

Fishman, N.S., Hackley, P.C., Lowers, H.A., Hill, R.J., Egenhoff, S.O., Eberl, D.D., and Blum, A.E., 2012, The nature 

of porosity in organic-rich mudstones of the Upper Jurassic 

Kimmeridge Clay Formation, North Sea, offshore United 

Kingdom: International Journal of Coal Geology, v. 103, 

p. 32–50.

Henley, R.W., and Berger, B.R., 2012, Pyrite-sulfosalt reactions and semimetal fractionation in the Chinkuashih, 

Taiwan, copper-gold deposit—A 1 Ma paleo-fumarole: 

Geofluids, v. 12, p. 245–260.

Lowers, H.A., Breit, G.N., Foster, A.L., Whitney, John, Yount, 

James, Uddin, Md. Nehal, and Muneem, Ad. Atual, 2007, 

Arsenic incorporation into authigenic pyrite, Bengal Basin 

sediment, Bangladesh: Geochimica et Cosmochimica Acta, 

v. 71, p. 2699–2717.

Lowers, H.A., Meeker, G.P., Lioy, P.J., and Lippmann, Morton, 2009, Summary of the development of a signature for 

detection of residual dust from collapse of the World Trade 

Center buildings: Journal of Exposure Science and Environmental Epidemiology, v. 19, p. 325–335. 

Rusk, B.G., Lowers, H.A., and Reed, M.H., 2008, Trace 

elements in hydrothermal quartz—Relationships to cathodoluminescent textures and insights into vein formation: 

Geology, v. 36, no. 7, p. 547–550. 

Wilson, S.A., Koenig, A.E., and Lowers, H.A, 2012, A new 

basaltic glass microanalytical reference material for multiple techniques: Microscopy Today, v. 20, p. 12–16.
8 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Minerals and Health Laboratory

By Suzette A. Morman

Earth scientists have a growing role in understanding 

and anticipating potential health issues associated with toxic 

metal(loid)s in often poorly understood earth materials such as 

dust, volcanic ash, wildfire ash, and mine wastes. By elucidating the mineralogical and geochemical characteristics of 

these materials, earth scientists can aid in identifying primary 

exposure pathways of concern, how materials may be taken 

up by the body, and the chemical behavior and toxicological 

properties of the materials once in the body. Through the use 

of laboratory methods such as physiologically based extraction 

tests, our Minerals and Health Laboratory provides valuable 

information on the solubility or bioaccessibility of elements 

present in earth materials.

Bioaccessibility, generally defined as the amount of a 

metal(loid) that is soluble in a simulated gastric solution, 

provides an estimate of what is available to the body for 

uptake (Ruby and others, 1999). Although it does not measure 

bioavailability (what is actually taken up by target organs such 

as the kidneys or liver), bioaccessibility provides a quick and 

inexpensive alternative to animal testing studies that directly 

measure uptake of toxicants from earth materials. This testing 

methodology is frequently used in Europe as well as in the 

United States (Oomen and others, 2002). The Minerals and 

Health Laboratory has used and modified physiologically 

based extraction tests (PBET), also called in vitro bioaccessibility (IVBA) tests, to examine the bioaccessibility of metal/

metalloid toxicants in a variety of earth materials and samplemedium types. Our gastric bioaccessibility method is based 

on a U.S. Environmental Protection Agency (EPA) method to 

evaluate the bioaccessibility of lead (EPA, 2008). We also test 

potential bioaccessibility of inhaled or respired earth materials using simulated lung fluids (Morman and others, 2013), 

serum-based fluids, and fluids simulating those found in cells 

that engulf and digest foreign particles in the lungs and upper 

respiratory tract.

Projects

The following U.S. Geological Survey projects and 

groups have utilized the capabilities of the Minerals and 

Health Laboratory: 

• Effects of Climatic Variability and Land Use on American Drylands, 

• Geoanalytical Research Chemistry Group, and 

• U.S. Geological Survey Reference Materials and Minerals and Health.

Primary Products

The following reports, from latest to earliest, utilized 

results from the Minerals and Health Laboratory:

Goldstein, H.L., Reynolds, R.L., Morman, S.A., Moskowitz, 

Bruce, Kokaly, R.F., Goossens, Dirk, Buck, B.J., Flagg, 

Cody, Till, Jessica, Yauk, Kimberly, and Berquó, T.S., 2013, 

Iron mineralogy and bioaccessibility of dust generated 

from soils as determined by reflectance spectroscopy and 

magnetic and chemical properties—Nellis Dunes recreational area, Nevada: U.S. Geological Survey Scientific 

Investigations Report 2013–5054, 15 p. http://pubs.usgs.

gov/sir/2013/5054/.

Plumlee, G.S., Durant, J.T., Morman, S.A., Neri, Antonio, 

Wolf, R.E., Dooyema, C.A., Hageman, P.L., Lowers, H.A., 

Fernette, G.L., Meeker, G.P., Benzel, W.M., Driscoll, R.L., 

Berry, C.J., Crock, J.G., Goldstein, H.L., Adams, Monique, 

Bartrem, C.L., Tirima, Simba, Behbod, BBehrooz, von 

Lindern, IIan, and Brown, M.J., 2013, Linking geological 

and health sciences to assess childhood lead poisoning from 

artisanal gold mining in Nigeria: Environmental Health 

Perspectives, v. 121, no.6, p. 744–750.

Morman, Suzette, 2012, In vitro bioavailability extractions, 

Appendix E, in Driscoll, Rhonda, Hageman, P.L., Benzel, 

W.M., Diehl, S.F., Adams, D.T., Morman, Suzette, and Choate, L.M., Assessment of the Geoavailability of Trace Elements from Minerals in Mine Wastes: Analytical Techniques 

and Assessment of Selected Copper Minerals: U.S. Geological Survey Scientific Investigations Report 2011–5211, 

p. 34–43. http://pubs.usgs.gov/sir/2011/5211/.

Wolf, R.E., Morman, S.A., Hageman, P.L, Hoefen, T.M., and 

Plumlee, G.S., 2011, Simultaneous speciation of arsenic, 

selenium, and chromium: species stability, sample preservation, and analysis of ash and soil leachates: Analytical and 

Bioanalytical Chemistry, v. 401, no. 9, p. 2733–2745. doi: 

10.1007/s00216-011-5275-x.

Gray, J.E., Plumlee, G.S., Morman S.A., Higueras, P.L., 

Crock, J.G., Lowers, H.A., and Witten, M.L., 2010, In vitro 

studies evaluating leaching of mercury from mine waste 

calcine using simulated human body fluids: Environmental 

Science and Technology, v. 44, no. 12, p. 4782–4788. doi: 

10.1021/es1001133.

Garrison, Virginia, Lamothe, Paul, Morman, Suzette, and 

Plumlee, Geoffrey, 2010, Trace-metal concentrations in 

African dust: Effects of long-distance transport and implications for human health: 19th World Congress of Soil Science, August1–6, 2010, Brisbane, Australia. 

Morman, S.A., 2010, Arsenic: A detective story in dusts: Earth 

Magazine, v. 55, no. 6, p. 40–47.
Laboratory Facilities and Capabilities 9

References Cited

Morman, S.A., Garrison, V.H., and Plumlee, G.S., 2013, Trace 

metals in Saharan dust: The use of in vitro bioaccessibility extractions to assess potential health risks in a dustier 

world: American Chemical Society Symposium Series 

1149, p. 41–58.

Oomen, A.G., Hack, Alfons, Minekus, Mans, Zeijdner, 

Evelijn, Cornelis, Christa, Schoeters, Greet, Verstraete, 

Willy, Van de Wiele, Tom, Wragg, Joanna, Rompelberg, 

C.J.M., Sips, A.J.A.M., and Van Wijnen, J.H., 2002, Comparison of five in vitro digestion models to study the bioaccessibility of soil contaminants: Environmental Science & 

Technology, v. 36, p. 3326–3334.

Ruby, M.V., Schoof, R., Brattin, W., Goldade, M., Post, G., 

Harnois, M., Mosby, D.E., Casteel, S.W., Berti, W., Carpenter, M., Edwards, D., Cragin, D., and Chappell, W., 1999, 

Advances in evaluating the oral bioavailability of inorganics 

in soil for use in human health risk assessment: Environmental Science & Technology, v. 33, p. 3697–3705.

U.S. Environmental Protection Agency (EPA), 2008, Standard 

operating procedure for an in vitro bioaccessibility assay for 

lead in soil: U.S. Environmental Protection Agency, EPA 

9200.2-86, 9 p., http://nepis.epa.gov/.

Petrophysics Laboratory

By Robert J. Horton

The Petrophysics Laboratory (PetLab) has the ability 

to measure the physical properties of earth materials (fig. 4). 

Knowledge of physical properties is essential in the interpretation of geophysical data, for survey design, numerical modeling, and geophysical sensor development. PetLab measurements can determine the density and magnetic, electrical, and 

radioactive properties of solid rocks, unconsolidated sediments, and liquids. Laboratory measurements show the range 

of physical properties to be expected for a given geologic unit 

or site and can show how those properties change as conditions vary. For example, the electrical properties of the ground 

vary as a function of water content, which can be manipulated 

in the laboratory to represent different conditions. By combining physical property measurements with geochemical and 

mineralogical data, an integrated interpretation can be made 

showing the effect of the composition of a sample on its geophysical signature (that is, McCafferty and others, 2011).

References Cited

McCafferty, A.E., Horton, R.J., Stanton, M.R., McDougal, 

R.R., and Fey, D.L., 2011, Geophysical geochemical, 

mineralogical, and environmental data for rock samples collected in a mineralized volcanic environment, upper Animas 

River watershed, Colorado: U.S. Geological Survey Data 

Series 595, 13 p.

Figure 4. Sediment sample prepared for a four-electrode, lowfrequency (0.001 to 1,000 hertz) electrical resistivity measurement. 

(USGS photograph)
10 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Biocatalysis Laboratory

By Mark R. Stanton

The Biocatalysis Laboratory possesses several resources 

for studying the physical, chemical, biological, and electrical properties of specific geochemical systems (fig. 5). The 

lab was originally designed to study microbially mediated 

geochemical reactions but has since been expanded to cover 

broader topic areas. For example, the lab has been used to 

determine the mineralogical and microbiological composition of sediments in an area impacted by acid-mine drainage 

(Stanton and others, 2007). Currently, the geochemical system 

in which we are most interested is sulfide mine waste. Studies 

of these mine wastes present unique challenges in that they 

are metal-rich, strongly acidic, and can produce high aqueous 

concentrations of metals.

Long-term studies of these systems often are hindered 

by lack of year-round access because of remote location and 

harsh, variable weather conditions. The lab is set up to examine mine wastes under controlled conditions to better define 

the geochemistry of these systems. Work done in the lab has 

been essential in identifying the mineral properties of acidgenerating and acid-neutralizing volcanic rocks near Silverton, 

Colorado (Yager and others, 2008), and in determining the 

rates at which the sulfide mineral sphalerite (ZnS) dissolves 

under acid drainage conditions (Stanton and others, 2008).

Complex reaction vessels have been designed, built, and 

instrumented with devices for measuring parameters such as 

resistivity, conductance, carbon content, acid-neutralizing 

capacity, net acid production, microbial types and abundances, 

and rates of sulfide dissolution reactions.

References Cited

Stanton, M.R., Fey, D.L., Church, S.E., and Holmes, C.W., 

2007, Processes affecting the geochemical composition of 

wetland sediment, chap. E25 of Church, S.E., von Guerard, 

Paul, and Finger, S.E., eds., Integrated investigations of 

environmental effects of historical mining in the Animas 

River watershed, San Juan County, Colorado: U.S. Geological Survey Professional Paper 1651, p. 1029–1064.

Stanton, M.R., Gemery-Hill, P.A., Shanks, W.C., III, and Taylor, C.D., 2008, Rates of zinc and trace metal release from 

dissolving sphalerite at pH 2.0–4.0: Applied Geochemistry, 

v. 23, p. 136–147.

Yager, D.B., Choate, L.D., and Stanton, M.R., 2008, Net 

acid production, acid neutralizing capacity, and associated mineralogical and geochemical characteristics of 

Animas River watershed igneous rocks near Silverton, 

Colorado: U.S. Geological Survey Scientific Investigations 

Report 2008–5063, 63 p., 1 plate.

Figure 5. Reaction vessel for studying mine waste geochemistry. 

Instruments on bench top are wired to platinum-coil arrays within 

the mine waste to measure changes in resistivity and conductivity. 

(USGS photograph)
Laboratory Facilities and Capabilities 11

Gene-Based Techniques in Support of 

U.S. Geological Survey Environmental 

Health and Ecology Studies

By Andrea L. Foster

During the past ≈30 years, scientific interest in the role 

microorganisms play in controlling the major forms (for 

example, valence-state) of elements (their speciation) on Earth 

has increased dramatically to become a major subdiscipline, 

often called “geomicrobiology.” In the area of geochemistry, 

many water-mineral reactions critical to the cycling of trace 

elements are recognized to be microbially driven, including 

the oxidative dissolution and reductive formation of pyrite and 

the reductive dissolution/oxidative precipitation of iron and 

manganese oxides (for example, Tebo, 1997). Microbes that 

use toxic trace elements in their metabolic cycle (for example, 

arsenic-reducing bacteria) clearly also play important roles in 

the mobility of those elements, especially with regard to water 

quality in potable groundwater supplies (Sutton and others, 

2009). The role of microbes in the cycling of carbon (fixing 

in carbonate minerals and mobilizing via respiration) and 

nitrogen is also a subject of great interest (Harms and Grimm, 

2008). The isolation of individual microbes from the environment and characterization of their physiology, as well as 

measurement of in situ turnover rates by unidentified microbial communities (that is, sulfur reduction), has allowed geochemists to develop quantitative values for the rates at which 

microbes perform geochemical reactions. These rates are then 

added to geochemical models used to describe and (or) predict 

the behavior of elements such as carbon (after below-ground 

sequestration or in warming, Alaskan peat deposits), arsenic, 

chromium, mercury, and uranium (in naturally or anthropogenically contaminated aquifer sediment) (Bethke, 2008). 

Although these approaches continue to be valuable to 

geomicrobiologists, it is also well-recognized that isolation 

approaches only provide the equivalent of a fleeting glimpse 

into the microbial world and its great diversity. It has been 

estimated that less than 1 percent of the microbes in the 

environment can be cultivated. Gene-based studies provide a 

wider window into the microbial world of the natural environment because their starting material (nucleic acid) is extracted 

directly from microbes. Two main goals of gene-based studies 

have been the identification and quantification of microbial 

groups. Studies tracking these variables across environmental 

gradients (salinity, temperature, water, oxygen concentration, 

and contamination) and time have been conducted in support 

of projects within the Energy, Minerals, and Environmental 

Health Mission Area. With these data, ecological principles 

can be applied to improve process-based understanding and 

descriptive/predictive modeling of microbial population 

dynamics at sites where that information is of substantial 

value to the Nation. 

Below is a brief summary of gene-based techniques 

for which method development was supported by the 

Integrated Methods Development Project, with examples 

of how these developments have supported various USGS 

projects. It is important to note that this summary is quite 

limited in scope and is not an attempt to describe all the 

available gene-based techniques.

A major research thrust has been toward the development of high-throughput methods that allow capture of 

significantly larger amounts of gene-based data from the 

environment. Automation and miniaturization of processes 

have been important in this regard, as has been substituting gel-based procedures for liquid-based ones. The primary 

activity supported under the project was the development of 

high-throughput chromatographic procedures for the size- and 

sequence-dependent separation of DNA (deoxyribonucleic 

acid) fragments to replace gel-based methods, which are more 

tedious and have larger errors related to the extracted data. 

Polymerase chain reaction (PCR) is a standard technique for the amplification of specific DNA fragments. DNA 

extracted from an environmental sample such as pond mud, 

groundwater, soil, or biological secretion is a mix of prokaryotic and eukaryotic DNA, as well as protein and other undesirable contaminants. PCR employs primers (short pieces of 

single-stranded DNA) to ensure that only specific regions of 

the genome are amplified. Primers are chosen from the literature (or developed by the user) and can be very general or very 

specific (down to strains of E. coli, for example). The amplification is conducted under a series of precisely controlled 

thermal cycles producing an exponential copy rate. PCR is 

used for detection of low-abundance species of concern (that 

is, specific pathogens) but is also the workhorse genetic technique producing the amplified DNA required for downstream 

techniques such as gel electrophoresis, DNA chromatography, 

and DNA sequencing.

Under the Integrated Methods Development, PCR methods were optimized for use of the reaction products in DNA 

chromatography (see below). Numerous common additives 

in PCR reactions cannot be put through the chromatographic 

column, so the use of alternative thermal-cycle methods to 

produce high-yield and specific PCR reactions were investigated and best methods developed.

Quantitative PCR (qPCR) is a related technique that 

offers additional benefits; primary among these benefits is 

that the amount of amplified DNA at each cycle of the PCR 

can be quantified and used to determine the amount of the 

specific gene fragment that was present prior to the amplification. QPCR has been used to track the relative abundances of 

microbial populations at the kingdom (for example, Eubacteria, Archea, and Eukaryotes), group (for example, sulfate 

reducers), and subspecies (for example, E. coli strains) levels. 

Under the project, published qPCR methods were tested and 

run on samples relevant to projects concerning the extent of 

microbial methylation of mercury, microbial sequestration and 

transformation of arsenic in a former gold mine, and microbial 

populations in intertidal sediments impacted by mining of volcanic massive sulfide deposits. These data are being compiled 

for future reports.
12 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Polyacrylamide gel electrophoresis (PAGE) and denaturing gradient gel electrophoresis (DGGE) are vertical, thin 

(1–2 millimeter thick), acrylamide gel techniques used to 

analyze PCR products based on size (PAGE) or sequence 

(DGGE). Both techniques use an applied electric field to 

propel DNA fragments through the small holes in the gel—in 

PAGE, the gel is pure acrylamide, but for DGGE, the gel also 

contains a denaturing agent that forces the double-stranded 

DNA to separate and migrate at a rate that is effectively 

sequence-dependent. Gels can be imaged and converted to 

digital data, which can be analyzed by multivariate statistical 

techniques, but gels are inherently difficult to reproduce and 

have large quantification error. Individual bands can also be 

cut out of gels, and the sequence within that band determined 

and used to help identify the organism. Under the project, 

PAGE and DGGE gels of PCR-amplified DNA fragments 

were run primarily as a comparison with DNA chromatographic techniques that were the main focus of the project.

DNA chromatography is analogous to PAGE/DGGE but 

uses reversed-phase ion-paring chromatography to separate 

PCR-amplified DNA fragments on the basis of sequence or 

size. DNA chromatography is more sensitive to PCR reaction chemistry than PAGE/DGGE but is more quantifiable, 

reproducible, and automated. Furthermore, the separated 

DNA fragments can be recovered by automated fraction 

collection for downstream cloning, sequencing, or other purposes. Automation of sample injection and fraction collection 

increases the throughput and decreases the time necessary 

to obtain information about the diversity and composition 

of microbial communities. Data obtained in chromatogram 

format are, in principle, easier to analyze automatically and 

by standard multivariate statistical techniques than are gelbased data.

Under the project, published chromatographic methods 

for the analysis of microbial communities by DNA chromatography (Barlaan and others, 2005; Goldenberg and others, 2007) were applied to the projects listed above. Also, 

published methods for DGGE analysis of specific microbial 

groups, such as sulfate-reducing bacteria, were adapted for 

DNA chromatography and tested on samples related to the 

aforementioned projects. A large dataset was acquired for 

one project—a study of arsenic attenuation by iron-oxidizing 

microbes at a historic gold mine site (Foster and others, 

2009)—and will be included in a later report. Findings to date 

indicate that the population is dominated by members of the 

genus Leptothrix, which are peculiar in their ability to precipitate large amounts of carbon-based “sheaths” that become 

coated with iron- and manganese-oxide precipitates, which 

act as a sponge for arsenic (Foster and others, 2010). These 

communities may be effective in the removal of toxic arsenic 

from water as well as iron and manganese, which are problems 

in many rural water systems. In addition, carbon fixation is an 

added benefit that can be used in the total cost accounting of a 

bioremediation project.

References Cited

Barlaan, E.A., Sugimori, Miho, Furukawa, Seiji, and Takeuchi, Kazuhisa, 2005, Profiling and monitoring of microbial 

populations by denaturing high-performance liquid chromatography: Journal of Microbiological Methods, v. 61, no. 3, 

p. 399–412.

Bethke, C.M., 2008, Geochemical and biogeochemical reaction modeling (2nd ed.): Cambridge University Press, 

543 p.

Foster, A.L., Ashley, R.P., Ona-Nguema, Georges, Rytuba, J.J., 

and Brown, G.E., Jr., 2010, Microbially-mediated arsenic 

cycling at the Lava Cap Mine Superfund Site, Nevada 

County, CA [abs.]: Geological Society of America Abstracts 

with Program, v. 42, p. 500.

Foster, A.L., Ona-Nguema, Georges, Tufano, Kate, and White, 

Richard, III , 2009, Temporal chemical data for sediment, 

water, and biological samples from the Lava Cap Mine 

Superfund Site, Nevada County, California—2006–2008: 

U.S. Geological Survey Open-File Report 2009–1268, 46 p. 

http://pubs.usgs.gov/of/2009/1268/.

Goldenberg, Oliver, Herrmann, Stefanie, Marjoram, Gina, 

Noyer-Weidner, Mario, Hong, George, Bereswill, Stefan, 

and Gobel, U.B., 2007, Molecular monitoring of the intestinal flora by denaturing high performance liquid chromatography: Journal of Microbiological Methods, v. 68, no. 1, 

p. 94–105.

Harms, T.K., and Grimm, N.B., 2008, Hot spots and hot 

moments of carbon and nitrogen dynamics in a semiarid 

riparian zone: Journal of Geophysical Research G: Biogeosciences, v. 113, no. 1, p. 1–14.

Sutton, N.B., van der Kraan, G.M., van Loosdrecht, M.C.M., 

Muyzer, Gerard, Bruining, Johannes, and Schotting, R.J., 

2009, Characterization of geochemical constituents and bacterial populations associated with As mobilization in deep 

and shallow tube wells in Bangladesh: Water Research, 

v. 43, no. 6, p. 1720–1730.

Tebo, B.M., 1997, Bacterially-mediated mineral formation—Insights into manganese(II) oxidation from molecular 

genetic and biochemical studies, in Banfield, J.F., and Nealson, K.H., eds., Geomicrobiology—Interactions between 

microbes and minerals: Washington, D.C., Mineralogical 

Society of America, p. 225–260.
Laboratory Facilities and Capabilities 13

Identification of Trace-Metal 

Species and Their Distribution in 

Rocks, Sediments, and Biota Using 

Synchrotron Techniques

By Andrea L. Foster

Identification of the form in which an element occurs 

in the environment is as important as understanding the 

total amount that is present because an element’s form (also 

known as species) is an important determinant of its mobility 

in the environment and its toxicity. The X-ray-based techniques available at synchrotron light sources are being used 

to identify elemental species in rocks, sediments, and biota in 

situ, that is, with little or no preparation (Manceau and others, 

2002). Most other techniques with the sensitivity required to 

measure trace elements in solids are ex situ, requiring manipulation of the sample by digestion, dissolution, drying, or other 

procedures in order to perform the analysis. These procedures 

often alter the original species distribution, confounding the 

analysis. In addition, significant quantities of sample (usually 

grams) are required for species measurement, but in some 

important cases, the important species are not easily sampled. 

The miniaturization of synchrotron X-ray beams (currently, 

most can be focused down to between 2 to 30 micrometers) 

has made the analysis of trace-element species in environmental matrices at the micron scale possible.

Synchrotron-based X-ray fluorescence (XRF) mapping, 

X-ray diffraction (XRD), and X-ray absorption spectroscopy 

(XAS) are being employed more than ever before to understand trace-metal species in rocks, sediments, and biota in support of USGS projects. The techniques involve illuminating a 

sample by a beam of ultrahigh-intensity X-rays (several orders 

of magnitude greater than that in a dentist’s office). XRF and 

XRD are two common instruments used in the conventional 

laboratory to extract chemical and mineralogical information (respectively) from bulk, powdered samples. Using the 

much higher flux of focused and tunable X-rays available at 

synchrotrons, element (and species) distribution maps with 

sensitivity on the parts per million (ppm) level can be produced at micrometer scales under ambient conditions in moist 

or wet samples—something that would be impossible using 

conventional techniques. Similarly, benefits of conducting 

XRD analysis at the synchrotron include order-of-magnitude 

lower detection limits for trace crystalline phases and collection of XRD patterns at the micrometer scale. 

XAS analysis of elements at trace levels is a technique 

that is simply not feasible using laboratory X-ray sources. 

Analysis of XAS spectra provides information on an element’s 

valence state and molecular-scale coordination (number and 

distance of neighboring atoms) that is used to infer its speciation. In this experiment, high-energy X-rays (typically in the 

range of 7,000–30,000 electron volts for trace elements) are 

used to eject core-level electrons from a specific element of 

interest in the sample. The scattering of these ejected electrons 

off of neighboring atoms produces modulations in the absorbance spectrum that can be modeled quantitatively. The technique has an operational detection limit of about 1–100 ppm, 

depending on the specific conditions of the experiment. As 

with XRF and XRD, XAS can be performed at the micrometer 

scale using focused synchrotron X-ray beams. 

Through the project, several improvements in methods 

of synchrotron X-ray data collection and analysis were made. 

Investigations into alternative methods of cooling samples 

to improve the quality and quantity of data collection were 

performed. The performance of multivariate statistical 

analyses (particularly principal component analysis (PCA) 

on bulk XAS and micro-scale XRF/XAS datasets was tested 

on model datasets (Brown and others, 2010) and applied to 

USGS studies. Improvements in methods of collecting and 

analyzing synchrotron data have enhanced the quality of 

work produced by several USGS projects focused on aspects 

of (1) trace-element geochemistry (Foster and others, 2000; 

Foster and Ashley, 2002; Breit and others, 2004; Perkins and 

Foster, 2004; Lowers and others, 2007; Zielinski and others, 

2007; Foster and others, 2010; Foster and others, 2011; Alpers and others, 2012), (2) the health of threatened ecosystems 

and characteristic megafauna (Foster and others, 2009), and 

(3) mineral resource studies of elements deemed critical to 

our Nation’s economy (A.L. Foster and others, oral commun., 2011; Hayes and others, 2011). 

References Cited

Alpers, C.N., Burlak, T.L., Foster, A.L., Basta, N.T., and 

Mitchell, V.L., 2012, Arsenic and old gold mines—

Mineralogy, speciation, and bioaccessibility [abs.]: V.M. 

Goldschmidt Conference, 22nd, Montreal, June 2012, p. 

1418.

Breit, G.N., Foster, A.L., Perkins, R.B., Yount, J.C., King, 

Trude., Welch, A.H., Whitney, J.W., Uddin, M.N., 

Muneemn, A.A., and Alam, M.M., 2004, As-rich ferric oxyhydroxide enrichments in the shallow subsurface of Bangladesh, in Wanty, R.B., and Seal, R.R., eds., Proceedings 

of the Eleventh International Symposium on Water-Rock 

Interaction: New York, A.A. Balkema, p. 1457–1461.

Brown, A.L., Foster, A.L., Alpers, C.N., Hansel, Colleen, Lentini, Chris, and Kim, C.S., 2010, Factors affecting principal 

component analysis (PCA) of X-ray absorption fine structure spectral datasets of arsenic and iron compounds [abs.]: 

Geological Society of America Abstracts with Program, 

v. 42, p. 615.

Foster, A.L., and Ashley, R.P., 2002, Characterization of arsenic species in microbial mat communities in the vicinity of 

the Lava Cap gold mine, Nevada City, CA—Geochemistry: 

Exploration, Environment, and Analysis, v. 2, p. 253–261.
14 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Foster, A.L., Ashley, R.P., Ona-Nguema, Georges, Rytuba, J.J., 

and Brown, G.E., Jr., 2010, Microbially-mediated arsenic 

cycling at the Lava Cap Mine Superfund Site, Nevada 

County, CA [abs.]: Geological Society of America Abstracts 

with Program, v. 42, p. 500.

Foster, A.L., Ashley, R.P., and Rytuba, J.J., 2011, Arsenic species in weathering mine tailings and biogenic solids at the 

Lava Cap Mine Superfund Site, Nevada City, CA: Geochemical Transactions, v. 12, no. 1, p. 1.

Foster, A.L., Berry, K., Jacobson, E.R., and Rytuba, J.J., 2009, 

Arsenic species in scute (shell plate) and lung tissue of 

desert tortoises: EOS Transactions American Geophysical 

Union Fall Meeting Supplement, v. 90, no. 52, p. B32B–04.

Foster, A.L., Breit, G.N., Welch, A.H., Whitney, J.W., Yount, 

J.C., Islam, M.S., Alam, M.M., Islam, M.K., and Islam, 

M.N., 2000, In-situ identification of arsenic species in soil 

and aquifer sediment from Ramrail, Brahmanbaria, Bangladesh [abs.]: American Geophysical Union Fall Meeting 

Supplement, p. H21D–01.

Hayes, S., Foster, A.L., and Balistrieri, L.S., 2011, Examining tellurium geochemistry using laboratory-based sorption 

studies and spectroscopic investigation of natural samples 

[abs.]: American Geophysical Union Fall 2010 Meeting, 

Abstracts with Program, V13B–2598.

Lowers, H.A., Breit, G.N., Foster, A.L., Whitney, John, Yount, 

James, Uddin, M.N., and Muneem, A.A., 2007, Arsenic 

incorporation into authigenic pyrite, Bengal Basin sediment, 

Bangladesh: Geochimica et Cosmochimica Acta, v. 71, 

no. 11, p. 2699–2717.

Manceau, Alain, Marcus, M.A., and Tamura, Nobumichi, 

2002, Quantitative speciation of heavy metals in soils and 

sediments by synchrotron X-ray techniques, in Fenter, 

P.A., Rivers, M.L., Sturchio, N.C., and Sutton, S.R., eds., 

Applications of synchrotron radiation in low-temperature 

geochemistry and environmental science: Washington, D.C., 

Mineralogical Society of America, p. 341–428.

Perkins, R.B., and Foster, A.L., 2004, Mineral affinities and 

distribution of selenium and other trace elements in black 

shale and phosphorite of the Phosphoria Formation, in Hein, 

J.R., ed., Life cycle of the Phosphoria Formation: New 

York, Elsevier, p. 251–298.

Zielinski, R.A., Foster, A.L., Meeker, G.P., and Brownfield, 

I.K., 2007, Mode of occurrence of arsenic in feed coal and 

its derivative fly ash, Black Warrior Basin, Alabama: Fuel, 

v. 86, p. 560–572.
Method and Software Development

U.S. Geological Survey Digital Spectral 

Library

By Roger N. Clark and Gregg A. Swayze

Issue and Scope

All analytical methods require standards and a knowledge 

base on which to verify results. Though traditional remote 

sensing can use simple ratios to show differences, imaging 

spectroscopy can detect, differentiate, and map subtle chemical differences in minerals and other compounds. But to correctly identify materials, their “spectral fingerprint” must be 

known. Without accurate knowledge of the spectral response 

of materials, accurate identification and mapping with spectroscopic remote sensing would be impossible.

Spectroscopy is a tool that detects the absorption or 

emission of light. Our eyes are crude spectrometers: we see 

different colors in materials and can infer composition. For 

example, the green of chlorophyll absorbs blue and red light, 

leaving green, or the red in a rock is due to iron oxide that 

absorbs green and blue light. A digital camera is also a crude 

spectrometer, sensing three colors. Broad-band remote sensing 

instruments like Landsat Thematic Mapper have seven bands 

(colors) from the blue to infrared. But spectrometers contain 

more than 100 bands and can measure the detailed positions 

and shapes of absorption (or emission) bands in compounds 

(fig. 6). The absorptions observed in spectra of rocks, minerals, and other compounds are due to chemical bonds, thus, 

“sense” the chemistry of the material, making it a very powerful method that with current technology can be done from 

great distances. (Not to be confused with atomic emission 

spectroscopy, like the emission from a neon sign that “senses” 

atomic transitions.)

Objectives

The objective of the U.S. Geological Survey (USGS) 

spectral library is to provide reference spectra of minerals and 

other materials that could be encountered in nature and need 

to be distinguished in remote-sensing data. Materials include 

minerals, amorphous compounds, plants and other organic 

materials, man-made materials, environmental materials, and 

liquids that may be found in imaging spectroscopy datasets. 

The National Aeronautics and Space Administration (NASA) 

also funds spectroscopy of materials of planetary interest, and 

those spectra are also included in the spectral library.

Background

In order to interpret the vast array of absorptions seen 

in spectra of materials, we must know and understand those 

absorptions and how they change with subtle changes in 

chemistry. For example, a small substitution of an element 

in a mineral will change the length of chemical bonds in 

that mineral causing a shift in the absorption band position. 

Understanding that shift then enables one to remotely detect 

that substitution and map small changes in chemistry (see 

Clark and others, 1990; Clark, 1999; and Clark and others, 

2003, 2007 for more details). The pyrite weathering sequence 

of spectra from the library shown in figure 7 illustrates the 

importance of spectral signatures. This sequence is key to 

identification and mapping of acidic rock drainage and led to a 

faster and lower cost cleanup of the Leadville, Colorado, mining district (Swayze and others, 2000).

Landsat TM

MODIS

AVIRIS

Laboratory

EXPLANATION

Low transmittance through Earth’s atmosphere

Wavelength, in micrometers

Reflectance + offset

1

2

3

4

5

1.5

1.0

0.5

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Figure 6. Comparison of spectra for alunite from four sensors with 

different spectral resolutions. Landsat Thematic Mapper (TM) with 

six bands in the visible to near-infrared spectrum cannot resolve any 

absorptions typical in minerals. The MODerate resolution imaging 

spectrometer (MODIS) has enough spectral channels to barely 

resolve some spectral features in the visible portion of the spectrum 

but not in the important near-infrared. The National Aeronautics 

and Space Administration airborne visible and infrared imaging 

spectrometer (AVIRIS), however, has sufficient spectral range and 

resolution to resolve many common absorption bands found in a 

wide variety of minerals and other compounds.
16 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Hematite

Goethite

Jarosite

Schwertmannite

Ferrihydrite

Pyrite

Scaled reflectance

Wavelength, in micrometers

1.5

1.0

0.5

0.5 1.0 1.5 2.0 2.5

Figure 7. Spectra of the pyrite weathering sequence from the 

U.S. Geological Survey spectral library. From Swayze and others 

(2000).

Results and Conclusions

The USGS spectral library is used in numerous studies, far 

too many to list here. The spectral library is included as a key 

reference library in commercial spectral image processing software packages (for example, ENVI) and is used by spacecraft 

teams mapping the Solar System. For example, the library is 

used by the Mars rover team to identify water-bearing minerals 

on the Martian surface (Rice and others, 2010) and was critical 

to producing the mineral maps of Afghanistan (King and others, 2011) and in rapid responses like the World Trade Center 

Disaster (Clark and others, 2001, 2006) and the Deepwater 

Horizon oil spill.

The wide use of the USGS spectral library is recognition 

of its importance in the terrestrial and planetary spectroscopy and imaging spectroscopy communities. The library is 

probably the most widely used set of standards for remote 

sensing in use today. The library continues to grow in content, 

enabling new science as well as improved current science in 

many areas from mineralogy, ecology, the environment, and 

disaster response to remote planetary applications.

Additional Information

The USGS digital spectral library is available online at 

http://speclab.cr.usgs.gov/spectral-lib.html.

References Cited

Clark, R.N., 1999, Spectroscopy of rocks and minerals and 

principles of spectroscopy, chap. 1 of Rencz, A.N., ed., 

Manual of remote sensing: New York, Wiley, p. 3–58.

Clark, R.N., Green, R.O., Swayze, G.A., Meeker, G.P., Sutley, 

S.J., Hoefen, T.M., Livo, K.E., Plumlee, G.S., Pavri, Betina, 

Sarture, Chuck, Wilson, Steve, Hageman, Phil, Lamothe, 

Paul, Vance, J.S., Boardman Joe, Brownfield, Isabelle, 

Gent, Carol, Morath, L.C., Taggart, Joseph, Theodorakos, 

P.M., and Adams, Monique, 2001, Environmental studies of 

the World Trade Center area after the September 11, 2001 

attack: U.S. Geological Survey Open File Report 01–0429, 

[about 260] p.), available online at http://pubs.usgs.gov/

of/2001/ofr-01-0429/.

Clark, R.N., King, T.V.V., Klejwa, Matthew, Swayze, G.A., 

and Vergo, Norma, 1990, High spectral resolution reflectance spectroscopy of minerals: Journal of Geophysical 

Research, v. 95, p. 12653–12680. 

Clark, R.N., Swayze, G.A., Hoefen, T.M., Green, R.O., Livo, 

K.E., Meeker, G.P., Sutley, S.J., Plumlee, G.S., Pavri, 

Betina, Sarture, Chuck, Boardman, Joe, Brownfield, I.K., 

and Morath, L.C., 2006, Environmental mapping of the 

World Trade Center area with imaging spectroscopy after 

the September 11, 2001 attack, chap. 4 of Gaffney, J.S., 

and Marley, N.A., eds., Urban aerosols and their impacts—

Lessons learned from the World Trade Center tragedy: 

Oxford University Press, American Chemical Society, 

Symposium Series 919, p. 66–83, plates 4.1–4.6.

Clark, R.N., Swayze, G.A., Livo, K.E., Kokaly, R.F., Sutley, S.J., Dalton, J.B., McDougal, R.R., and Gent, C.A., 

2003, Imaging spectroscopy—Earth and planetary remote 

sensing with the USGS Tetracorder and Expert Systems: 

Journal of Geophysical Research, v. 108, no. E12, 5131, 

doi:10.1029/2002JE001847, 44 p.

King, T.V.V., Johnson, M.R., Hubbard, B.E., and Drenth, 

B.J., eds., 2011, Identification of mineral resources in 

Afghanistan—Detecting and mapping resource anomalies 

in prioritized areas using geophysical and remote sensing 

(ASTER and HyMap) data: U.S. Geological Survey OpenFile Report 2011–1229, 327 p.

Rice, M.S., Bell, J.F., III, Cloutis, E.A., Wang, A., Ruff, S.W., 

Craig, M.A., Bailey, D.T., Johnson, J.R., de Souza, P.A., 

and Farrand, W.H., 2010, Silica-rich deposits and hydrated 

minerals at Gusev Crater, Mars—Vis-NIR spectral characterization and regional mapping: Icarus, v. 205, p. 375–395.

Swayze, G.A., Smith, K.S., Clark, R.N., Sutley, S.J., Pearson, 

R.N., Rust, G.S., Vance, J.S., Hageman, P.L., Briggs, P.H., 

Meier, A.L., Singleton, M.J., and Roth, Shelly, 2000, Using 

imaging spectroscopy to map acidic mine waste: Environmental Science and Technology, v. 34, p. 47–54. 
Method and Software Development 17

Remote Identification, Mapping, and 

Quantification of Materials

By Roger N. Clark and Gregg A. Swayze

Issue and Scope

Remote identification and mapping of materials and other 

compounds was very limited in the last century due to the 

available sensor technology. In the early 1990s, imaging spectrometers were developed with very good spectral resolution 

and spectral range. Solids, liquids, and gases preferentially 

absorb light at different wavelengths enabling us to remotely 

fingerprint virtually any material using spectroscopy (with 

limitations imposed by the Earth’s atmosphere for remote 

sensing). The combination of imaging and spectroscopy 

(imaging spectroscopy) enables those materials to be mapped 

over broad areas on the surface of the Earth and throughout 

the Solar System. Given sufficient spectral range, spectral 

resolution, and sensor sensitivity, quantitative abundances of 

surface materials can be derived remotely from airborne and 

orbital sensors. Deriving abundance from spectra of solid 

materials is a formidable radiative transfer problem, which 

requires the use of modern high-performance computers for 

data analysis.

Objectives

Imaging spectroscopy is a universal tool that can be 

applied to many problems from mineral to environmental 

mapping, including finding sources of acid-rock drainage 

that potentially release pollution into rivers. The absorption 

bands observed in the spectrum of a material (for example, 

its spectral fingerprints) are a function of that material’s 

abundance, its grain size, the abundances and grain sizes of 

materials mixed with it, and elemental substitutions in its crystal structure. For example, one may be interested in a certain 

mineral in a soil, but deriving its abundance remotely using 

spectroscopy requires determining the grain-size distribution 

of all soil components and their abundances. The problem is 

highly nonlinear. Further, we now understand that nano-size 

particles (particles less than 200 nanometers in diameter) play 

significant roles in spectra of soils on Earth as well as on surfaces throughout the Solar System. Imaging spectroscopy and 

radiative transfer modeling seek to provide more detail about 

our world and other surfaces in the Solar System.

Background

The USGS Imaging Spectroscopy group has developed 

sophisticated tools for identification and mapping of minerals 

and other materials (Clark and others, 2003). Many studies 

have used these tools to map minerals in outcrops, on the 

scale of entire countries, to planetary scales (see references 

throughout this circular). In some cases, it is desirable to do 

more than simply identify the location of a material; sometimes quantifying its abundance is necessary to solve a problem. This can be done in two ways: (1) derivation of abundances based on observed empirical trends and (2) derivation 

of abundances based on first principles using radiative transfer 

modeling. We have demonstrated both methods independently 

and also a hybrid of both.

Figure 8 shows the detection of minerals with the 

potential to generate acidic runoff in the Leadville, Colorado, 

mining district. Our mapping system, called Tetracorder (Clark 

and others, 2003) searches for minerals and materials that may 

impact the environment. The presence on the surface of pyrite, 

jarosite, goethite, and hematite can be used as a proxy for the 

pH of water draining from the site (Swayze and others, 2000). 

This study enabled the U.S. Environmental Protection Agency 

(EPA) to accelerate mine waste cleanup by 2 years, saving 

$2 million in cleanup costs.

In a hybrid combination of radiative transfer modeling and 

laboratory analyses of oil emulsions, Clark and others (2010) 

were able to derive for the first time the amount and location of 

thick oil floating on the ocean’s surface, providing a physicsbased estimate for the volume of oil released by the Deepwater 

Horizon oil spill (see Swayze and Clark, this circular). Future 

refinements of radiative transfer models of oil thickness and 

emulsion state will enable a faster, more efficient response to 

future oil spills whether natural or man-made.

Calculating the abundances of materials in a rock or soil 

requires sophisticated radiative transfer modeling and the 

optical constants of those materials in the rock or soil. Recent 

research (Clark and others, 2012) has shown that nano-size 

particles have major optical effects on spectral properties 

that was previously unrecognized. Previous radiative transfer 

models were not able to correctly model the spectral response 

from subwavelength particles in surfaces, and we now know 

that some of the effects of small particles are widely observed 

on the Earth and in the Solar System. Nano-size particles can 

affect such things as radiative heat balance in snow packs, 

with implications for climate change. Small particles create 

Rayleigh scattering and Rayleigh absorption in soils, rocks, 

and in snow containing dust or soot.

Clark and others (2012) developed the first radiative 

transfer model that incorporates both Rayleigh scattering 

and Rayleigh absorption from nano-size particles (fig. 9). 

Results from this model have shown that what was formerly 

thought to be dark organic compounds on one of Saturn’s 

moons is in fact nano-size metallic iron, nano-size iron 

oxide, trapped carbon dioxide, adsorbed water, and ice. This 

new model can now be applied to spectra of rocks, soils, 

snow, and other surface materials on the Earth and throughout the Solar System.
18 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Traverse distance, in meters

Leachate pH

7

6

5

4

3

2

0 50 100 150 200 250

A

B

EXPLANATION

Open pit Venir waste

rock pile

Sampling

Traverse

Spectral

Traverse

Jarosite Jarosite +

Goethite

Goethite Hematite

106°14'19" 106°14'10"

39°

14'

20"

39°

14'

15"

0 10 20 30 40 50 METERS

0 50 100 150 FEET
Method and Software Development 19

Figure 9. Spectrum of Saturn’s moon lapetus adapted from Clark 

and others (2012). The spectrum shows an unusually dark and red 

(increasing reflectance toward longer wavelengths) spectrum, 

from more limited Earth-based data, that was previously thought 

to be caused by dark organic compounds. In the visible spectrum 

(from about 0.4 to 0.7 microns), Iapetus appears as dark as soot. 

The Cassini spacecraft orbiting Saturn obtained this spectrum, 

and the expected organic absorption features were not seen in 

the infrared. The model (red line) is a combination of submicron 

and nano-size particles of metallic iron and iron oxide. The large 

absorption at 3 microns is due to water molecules adsorbed onto 

the iron-oxide grains. The 4.25-micron absorption is due to trapped 

carbon dioxide molecules. Model abundances and grain size are 

given in Clark and others (2012). H2

0, water; CO2, carbon dioxide.

Lapetus dark material

Model:

nano-iron + 

nano-hematite +

H2

O + CO2

H2O

CO2

EXPLANATION

Wavelength, in micrometers

Reflectance

0.05

0.04

0.03

0.02

0.01

0.00 1 2 3 4 5

Results and Conclusions

Applications of imaging spectroscopy, from remote 

material identification to calculating quantitative abundances 

at levels never before considered possible, are maturing, and 

future applications are virtually unlimited. Remote spectroscopic mapping is an astounding tool but still cannot match the 

detail and precision that can be obtained in laboratory analyses. 

Field sampling, laboratory analyses of those samples, and the 

synoptic view provided by high-spectral and spatial imaging 

spectroscopy is an extremely powerful combination of analytical tools for finding materials and monitoring our environment.

Primary Products

Materials maps of minerals, organics, and other compounds, their abundances and grain sizes.

References Cited

Clark, R.N., Cruikshank, D.P., Jaumann, Ralf, Brown, R.H., 

Curchin, J.M., Hoefen, T.M., Stephan, Katrin, Dalle Ore, 

C.M., Buratti, B.J., Filacchione, Gianrico, Baines, K.H., 

and Nicholson, P.D., 2012, The composition of Iapetus—

Mapping results from Cassini VIMS: Icarus, v. 218, 

p. 831–860, doi:10.1016/j.icarus.2012.01.008.

Clark, R.N., Swayze, G.A., Livo, K.E., Kokaly, R.F., Sutley, S.J., Dalton, J.B., McDougal, R.R., and Gent, C.A., 

2003, Imaging spectroscopy—Earth and planetary remote 

sensing with the USGS Tetracorder and Expert Systems: 

Journal of Geophysical Research, v. 108, no. E12, 5131, 

doi:10.1029/2002JE001847, 44 p., http://speclab.cr.usgs.

gov/PAPERS/tetracorder/.

Swayze, G.A., Smith, K.S., Clark, R.N., Sutley, S.J., Pearson, 

R.N., Rust, G.S., Vance, J.S., Hageman, P.L., Briggs, P.H., 

Meier, A.L., Singleton, M.J., and Roth, Shelly, 2000, Using 

imaging spectroscopy to map acidic mine waste: Environmental Science and Technology, v. 34, p. 47–54, http://

speclab.cr.usgs.gov/PAPERS/leadville99/ldv99.html.

Figure 8. (facing page) Use of Tetracorder mapping system 

at Leadville, Colorado, mining district. A, Spectral traverse and 

AVIRIS (airborne visible and infrared imaging spectrometer) 

mineral maps overlaid on a high-spatial-resolution aerial 

photograph of the Venir mine waste pile in Leadville, Colorado. 

Mineral maps show the spectrally dominant iron-bearing 

secondary minerals. B, pH compared to distance along the Venir 

mine waste pile traverse. Each spectral mineral zone is denoted 

by a different symbol color-coded to the key in A. Spectral 

secondary mineral zones can be used as a proxy for leachate pH, 

suggesting that runoff from areas with jarosite will have a low pH 

that could potentially impact downstream riparian zones. Both A

and B are modified from Swayze and others (2000).
20 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Multifaceted Approach to 

Microanalysis

By Heather A. Lowers and Alan E. Koenig

Issue and Scope

The Denver Microbeam Laboratory (DML), in collaboration with the Laser Ablation-Inductively Coupled Plasma–Mass 

Spectrometry (LA-ICP–MS) Laboratory, assists scientists who 

require microanalytical work to assess ore deposits, generate ore deposit models, and study the adverse effects of mine 

wastes. Often the variation and abundances of trace elements 

in ore and gangue materials, and secondary mineralization of 

the primary phases, reveals insights into the formation history 

of the deposit and commodity of interest. Although the size of 

the deposit may be quite large and yield plentiful sample, the 

limiting factor for in situ chemical analysis is often the grain 

size of the material of interest. These two laboratories develop 

new methods and refine existing methods to better meet the 

growing need for lowering the detection limits of elements at 

smaller spatial resolutions and more efficient data acquisition 

by combining the various techniques offered in each lab. 

In addition to its core mission, the U.S. Geological Survey 

(USGS) has responded to natural and environmental disasters such as the World Trade Center collapse, 2007 Southern 

California wildfires, Deepwater Horizon oil spill, and in collaboration with other Federal agencies, the contamination from 

mining practices in foreign countries such as Hungary, Zambia, 

and Nigeria (that is, Gray and others, 2010; Lowers and others, 

2009; Plumlee and others, 2007). The goals of these studies were 

to determine what elements and phases of concern, both from 

an environmental and human health perspective, are present and 

what the potential of these materials is to cause harm. Whereas 

these catastrophes may produce plentiful sample, not all situations will yield ample material to run unlimited analytical tests.

The USGS uses a combination of X-ray diffraction, 

X-ray fluorescence, ICP–MS, and leach tests for complete 

bulk-sample characterization. Electron microscopy and LAICP–MS are able to assimilate data gained by bulk techniques 

to link particle size, morphology, and chemistry to phase identification. Data gathered using this approach are better able 

to predict potential adverse effects to human health and the 

environment with minimal sample supply and analysis time. 

Whether the sample supply is large or very limited, an informative approach to analysis order can minimize the amount 

of material needed and provide guidance on which samples 

require further investigation.

Objectives

We describe here a study that was conducted to explore 

methods to lower the detection limits for select trace elements 

in a range of materials using electron probe microanalysis 

(EPMA) and to correlate the abundance of these elements with 

elemental concentrations determined by LA-ICP–MS. A second study was conducted to develop a routine to link particle 

size and morphology to phases that may contain bioaccessible 

elements that may cause harm to human health or the environment. An overall objective of our work, which links these two 

studies, was to develop a work flow for all samples, regardless 

of origin or type, that may be submitted for microanalysis so 

they are fully characterized before the sample is consumed and 

not available for further investigation. 

Background

The solid-phase residence of trace elements in geologic 

materials is not always apparent. Often the element of interest 

is mobile and found associated with secondary mineralization. The element of interest may occur in significant abundance in a phase that occurs at levels not detectable by X-ray 

diffraction (XRD) (usually less than 1 percent by weight) or 

the element may occur in trace quantities (less than 1 percent 

elemental) in several phases. Elemental abundances in various 

phases may provide information such as temperature, pressure, fluid composition, and age of the material or the potential 

toxicity to human health and the environment.

Results and Conclusions

The methods developed in the first study have resulted 

in a work flow that preserves the sample until characterization is completed and the ability to achieve single-digit parts 

per million levels of titanium and aluminum in quartz at the 

5-micrometer spatial resolution. The first step is to acquire 

cathodoluminescence (CL) images followed by backscattered and secondary electron images with qualitative chemical analyses. Depending on the end product, the analysis can 

continue to EPMA and (or) LA-ICP–MS. Using this work 

flow, we have determined lithium and aluminum are correlated 

with one another and with higher intensity CL zones in quartz 

from low temperature Mississippi Valley type ore deposits. 

This result was made possible by analyzing some of the same 

elements by EPMA and LA-ICP–MS (fig. 10).

A work flow path for environmental samples, applicable 

to all sample types, has been developed. The sample material 

can consist of a split dedicated to microanalytical work or a 

portion from the XRD material (before or after XRD analysis) dispersed on an SEM (scanning electron microscope) 

sample mount or embedded in epoxy and polished to a flat 

surface. Spectrum images and a backscattered electron image 

are acquired of a large area. The sum spectrum from the field 

of view is analyzed to determine all elements detected in that 

field. An example of a sum spectrum of Nigerian soil is shown 

in figure 11. In this example, elements of concern detected 

include lead and tungsten. Observations of the tungsten map 

and spectrum of grain 3 (shown as G3, fig. 11) reveals a lead 

tungstate mineral, which is less than 25 micrometers in the 

longest dimension. The data reveal many lead-containing 

particles that are of ingestible and respirable size.
Method and Software Development 21

Figure 10. Grayscale image shows the 

cathodoluminescence intensity of quartz. 

The red box outlines the area of an aluminum 

X-ray intensity map collected with the electron 

microprobe. The black box outlines the area 

of aluminum (Al)-, lithium (Li)-, and gallium 

(Ga)-concentration maps collected with laserablation inductively coupled plasma–mass 

spectroscopy. ppm, parts per million; mm, 

millimeter; SEM, scanning electron microscope; 

CL, cathodoluminescence.

0 200 400 600 800 1,000 1,200 1,400 1,600 0

200

400

600

50 ppm

150 ppm

250 ppm

350 ppm

450 ppm

550 ppm

650 ppm

750 ppm

850 ppm

Li

0 200 400 600 800 1,000 1,200 1,400 1,600

0

200

400

600

0 ppm

100 ppm

200 ppm

300 ppm

400 ppm

500 ppm

600 ppm

700 ppm

800 ppm

900 ppm

1,000 ppm

Al

0 200 400 600 800 1,000 1,200 1,400 1,600

0

200

400

600

10 ppm

20 ppm

30 ppm

40 ppm

50 ppm

60 ppm

70 ppm

80 ppm

Ga

Distance, in micrometers

Distance, in micrometers

Quartz

1 mm

Aluminum

Epoxy

SEM-CL image
22 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 11. Backscattered electron (BSE) image (top) and X-ray intensity maps of lead (Pb), phosphorus (P), and tungsten (W) from a 

Nigerian soil sample. The upper spectrum represents a maximum pixel spectrum and reveals all elements detected in the field of the 

view. The horizontal field width is 1.5 millimeters.

Sum Spectrum

G1=cerrusite(?)

G2=pyromorphite

G3=lead tungstate

C

C O

C O

C

O

W

Pb

Pb

Pb Pb

Pb Pb

Pb

Pb

W Pb

P

O

Na

MgAl

Si

W

P

Pb

K

Ca

V

Mn Fe

Fe Cu Pb Pb

Ti

Relative counts per second Relative counts per second Relative counts per second Relative counts per second

Kiloelectron volt

0 3 6 9 12
Method and Software Development 23

Collaborators

Brian Rusk, University of Western Washington

John Donovan, University of Oregon 

U.S. Geological Survey Geoenvironmental Assessment Group

References Cited

Diehl, S.F., Goldhaber, M.B., Koenig, A.E., Lowers, H.A., 

and Ruppert, L.F., 2012, Distribution of arsenic, selenium, 

and other trace elements in high pyrite Appalachian coals: 

Evidence for multiple episodes of pyrite formation: International Journal of Coal Geology, v. 94, p. 238–249.

Donovan, J.J., Lowers, H.A., and Rusk, B.G., 2011, Improved 

electron probe microanalysis of trace elements in quartz: 

American Mineralogist, v. 96, no. 2–3, p. 274–282.

Gray, J.E., Plumlee, G.S., Morman, S.A., Higueras, P.L., 

Crock, J.G., Lowers, H.A., and Witten, M.L., 2010, In vitro 

studies evaluating leaching of mercury from mine waste 

calcine using simulated human body fluids: Environmental 

Science and Technology, v. 44, p. 4782–4788.

Hageman, P.L., Plumlee, G.S., Martin, D.A., Hoefen, T.M., 

Meeker, G.P., Adams, Monique, Lamothe, P.J., and 

Anthony, M.W., 2008, Leachate geochemical results for ash 

and burned soil samples from the October 2007 Southern 

California wildfires: U.S. Geological Survey Open-File 

Report 2008–1139, 14 p.

Hoefen, T.M., Kokaly, R.F., Martin, D.A., Rochester, Carlton, 

Plumlee, G.S., Mendez, Greg, Reichard, E.G., and Fisher, 

R.N., 2009, Sample collection of ash and burned soils from 

the October 2007 Southern California wildfires: U.S. Geological Survey Open-File Report 2009–1038, 64 p.

Lowers, H.A., Meeker, G.P., Lioy, P.J., and Lippmann, Morton, 2009, Summary of the development of a signature for 

detection of residual dust from collapse of the World Trade 

Center buildings: Journal of Exposure Science and Environmental Epidemiology, v. 19, p. 325–335.

Plumlee, G.S., Martin, D.A., Hoefen, Todd, Kokaly, Raymond, 

Hageman, Philip, Eckberg, Alison, Meeker, G.P., Adams, 

Monique, Anthony, Michael, and Lamothe, P.J., 2007, Preliminary analytical results for ash and burned soils from the 

October 2007 Southern California wildfires: U.S. Geological Survey Open-File Report 2007–1407, 13 p.

Rusk, Brian, Koenig, Alan, and Lowers, Heather, 2011, 

Visualizing trace element distribution in quartz using cathodoluminescence, electron microprobe, and laser ablationinductively coupled plasma-mass spectrometry: American 

Mineralogist, v. 96, no. 5–6, p. 703–708.

Rusk, B.G., Lowers, H.A., and Reed, M.H., 2008, Trace 

elements in hydrothermal quartz—Relationships to cathodoluminescent textures and insights into vein formation: 

Geology, v. 36, no. 7, p. 547–550. 

Three-Dimensional Magnetotelluric 

Inversion for Improved Structural 

Imaging

By Paul A. Bedrosian

Issue and Scope

Magnetotellurics (MT) is a passive electromagnetic (EM) 

method unique in its ability to image Earth’s electrical resistivity structure on depth scales ranging from 100s of meters to 

100s of kilometers. MT is commonly employed in a range of 

applications including groundwater resources, mineral exploration, geothermal resource evaluation, and framework tectonics.

Both an advantage and a limitation of the MT method is 

its sensitivity to complex Earth structure. Other electrical and 

EM techniques have a focused footprint, which better justifies a one- or two-dimensional (1-D or 2-D) analysis. MT 

data, in contrast, reflect the full complexity of the subsurface 

and are sensitive to electrically conductive structures at great 

depth and at great distance (10s to 100s of kilometers) from 

the survey area. The traditional MT approach is to collect data 

along a profile perpendicular to geologic strike (as defined, for 

example, by faults or lineaments), to show or assume that the 

data are consistent with a 2-D resistivity structure, and to invert 

the data using a 2-D inversion, which explicitly assumes that 

resistivity does not vary along the geologic strike direction.

This approach works well in many cases but is approximate at best and fails spectacularly in a number of situations. 

Three-dimensional (3-D) environments, in which no clear 

strike direction exists, are commonly encountered in geothermal and mineral resource exploration. Even in quasi-2-D environments, the geologic strike may be unknown prior to data 

collection and can result in profile data collected subparallel to 

geologic strike and unacceptable for 2-D inversion (Siripunvaraporn and others, 2005b). Additionally, MT data collected 

within several hundred kilometers of a coastline are disturbed 

by the “coast effect” and can only be effectively inverted in 

2-D if the coastline is subparallel to the geologic strike. 

Three-dimensional magnetotelluric inversion presents an 

opportunity to recover complex Earth resistivity models without 

the limitations associated with 2-D inversion. Three-dimensional MT inversion, however, is computationally intensive, 

and noncommercial 3-D MT inversion codes have only recently 

become practical on high-power desktop computers and distributed memory clusters. Three-dimensional MT inversion is also 

challenging to implement in cases of nonuniform and limited 

site distributions where different parts of the model space are 

more or less constrained by measured data. Finally, static-shift 

distortion, in which small-scale, near-surface, conductivity 

structures distort the measured data, remains a problem in 3-D. 

This report summarizes research into the application of 3-D 

magnetotelluric inversion at a range of scales relevant to mineral resource assessment and tectonic investigations.
24 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Objectives

The objective of U.S. Geological Survey (USGS) 

research into 3-D magnetotelluric inversion lies not in the 

development of 3-D inversion algorithms but in the development of 3-D MT inversion strategies, the comparison of 

different inversion algorithms, and the application of 3-D MT 

inversion to a range of datasets in differing environments, at 

varying spatial scales, and with varying site distributions. This 

work is aimed at improving USGS capabilities in resolving 

complex geologic structure and at making 3-D MT inversion 

more accessible to non-experts. 

Background

The goal of magnetotelluric inversion is to estimate 

the Earth’s resistivity structure from surface electric (E) and 

magnetic (H) field measurements. The measured fields are 

typically transformed into the frequency domain and then used 

to estimate transfer functions:

E

E

Z Z

Z Z

H

H

x

y

xx xy

yx yy

x

y





 



 = 



 









 





(1)

Here, the elements Zij form the impedance tensor, a 

complex, frequency-dependent tensor describing the amplitude 

and phase relations between E and H. The form of the impedance tensor, Z, is related to the complexity of the subsurface 

resistivity distribution. For the case of 2-D Earth structure, 

where resistivity varies with depth and in one lateral direction, 

the impedance tensor takes the antidiagonal form

Z

Z

Z D

xy

yx

2

0

0

   = 



 





(2)

when rotated into a coordinate system in which one axis is 

parallel to geologic strike. This reduced form of the impedance tensor is the basis for 2-D MT inversion. In the case of 

3-D Earth structure, or the quasi-2-D cases discussed earlier, 

the impedance tensor is fully occupied, and neglecting the 

diagonal components, as is done in 2-D inversion, will lead 

to artifacts in the resulting inverse models. Furthermore, the 

diagonal tensor elements contain valuable information about 

the complexity of the subsurface that is not, and cannot, be 

used within a 2-D MT inversion.

The primary 3-D MT inversion algorithm investigated 

is WSINV3DMT, a data-space variant of the Occam inversion approach developed by Siripunvaraporn and others 

(2005a). This work utilizes the serial version of WSINV3DMT, which can be run on a desktop computer but 

requires significant amounts of memory to handle large 

inversion problems. A newer parallelized version of WSINV3DMT is less memory intensive and is capable of inverting vertical magnetic-field transfer functions in addition to 

the MT impedance transfer functions.

As a comparison, the 3-D inversion RLM3DI was investigated for one dataset. RLM3DI uses a nonlinear conjugate 

gradients approach to minimizing the objective function. 

RLM3DI is based upon the work of Rodi and Mackie (2001) 

and solves a series of linearized inverse problems without 

explicit calculation of the Jacobian (sensitivity) matrix. 

RLM3DI is not publically available—the inversion results 

shown here were produced by GSY-USA, Inc., and are reproduced with permission from the Pebble Limited Partnership.

Six datasets have been examined to date using 3-D 

magnetotelluric inversion. The datasets span a range of spatial 

scales from a deposit-scale mineral investigation in southwest 

Alaska to the inversion of regional EarthScope MT data covering the entire Pacific Northwest, United States. Specialized 

investigations include the 3-D inversion of MT profile data in 

a predominantly 2-D environment (Siripunvaraporn and others, 2005b), MT profile data leveraged by off-profile sites, and 

a dense profile oriented oblique to a coastline. What follows is 

a brief discussion of some specific findings related to 3-D MT 

inversion as illustrated through three studies.

Results and Conclusions

A high-resolution MT dataset over the Pebble coppergold-molybdenum porphyry deposit served as a test-bed for 

comparing RL2DI and WSINV3DMT (Bedrosian, 2008). 

This dataset is ideal for application of 3-D MT inversion as 

the sites are closely spaced (120 sites, 200-m site spacing) 

and distributed evenly throughout the model area (fig. 12A). 

Furthermore, the site is in remote southwest Alaska where 

the data are virtually undisturbed by cultural noise. Finally, 

this is a highly 3-D environment containing structures that 

cannot be successfully imaged using 2-D inversion. These 

include multiple intrusive-rock suites that have been offset 

along faults and covered by volcanic and glacial material 

since emplacement (Shah and others, 2013). Resistivity 

depth slices (figs. 12B and 12C) and cross sections 

(figs. 12D and 12E) through the deposit area are consistent 

between the different inversion algorithms. Model features 

C1-C3 and R1-R2 were identified from the RLM2DI model 

and are overlain on the WSINV3DMT models; all features 

show good correspondence between the two models. Differences occur primarily, but not exclusively, far from the 

measurement sites or within the deeper part of the model 

domain and reflect the role of regularization in guiding the 

inversion where data sensitivity is low. Differences within 

the central model domain likely stem from the inclusion of 

vertical magnetic-field transfer functions in the RLM2DI 

inversion, which in concert with MT impedance data tend 

to better localize discrete structures (for example, ellipses 

in figs. 12B and 12C).

A 3-D inversion example of MT profile data distorted by 

the coast effect comes from southwest Oregon (Wannamaker and 

others, 2014; Bedrosian and Box, 2007). A northwest-oriented 

MT profile crosses perpendicular to the boundary between the 

Siletz and the Klamath terranes but is oblique to the Oregon 
Method and Software Development 25

R1 R2

C1

C2

C3

R1 R2

C1

C2

C3

R1

R2

C1

C2

C3

R2

C1

C2

C3

R1 R2

C1

C2

C3

R1 R2

C1

C2

C3

R1

R2

C1

C2

C3

R1

R2

C1

C2

C3

0

1

2

3

4

–1

–2

–3

–4

–4 –2–3 –1 0 1 2 3 4

0

1

2

3

4

–1

–2

–3

–4

–4 –2–3 –1 0 1 2 3 4

Depth, in kilometers

Depth, in kilometers

–4 –2–3 –1 0 1 2 3 4

0

–1

–2

–3

–4

–5

–4 –2–3 –1 0 1 2 3 4

0

–1

–2

–3

–4

–5

Distance, in kilometers Distance, in kilometers

A A' A A'

South to north distance, in kilometers

South to north distance, in kilometers

West to east distance, in kilometers West to east distance, in kilometers

A

A'

A

A' A'

B

D E

C

Resistivity, 

 in ohm-meters

10

100

1,000

10,000

! Magnetotelluric site

Cu deposit boundary

Faults

EXPLANATION

Interpreted features

!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!( !( !( !( !( !( !( !( !( !( !( !( !( !(

!( !( !(

!( !( !( !( !( !( !( !( !(

!( !(

!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(

!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(

!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(

!( !( !( !( !( !( !( !( !( !( !(

!( !( !( !( !(

!( !( !( !( !( !( !(

!(

!( !( !( !( !( !( !( !(

!(

!(

!( !( !( !( !( !(

!( !( !(

!( !(

!( !(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!( !(

!( !(

!( !(

!( !(

!( !(

!( !(

155°18' 155°16' 155°14' 155°12'

59°54'

59°52'

0 1 2 MILES

0 1 2 KILOMETERS

A

Base from digital orthophotography

Universal Transverse Mercator projection, zone 5 north

North American Datum of 1983 

A

A'

SOUTH NORTH

SOUTH NORTH

Figure 12. Copper-gold-molybdenum porphyry deposit, southwest Alaska. A, Location of magnetotelluric sites near 

deposit. Red line denotes the deposit outline defined by the 0.3-percent copper-equivalent cutoff. Faults were mapped 

primarily through subsurface drilling. B, and C, Depth slices at 100 meters through 3-D inverse models of the same 

dataset using RLM2DI and WSINV3DMT, respectively. D, and E, Cross sections along profile A–A′ through the same 

inverse models using RLM2DI and WSINV3DMT, respectively. Interpreted features (dashed lines) are discussed in the 

text. Cu, copper.
26 Developing Integrated Methods to Address Complex Resource and Environmental Issues

coastline. In this scenario, 2-D inversion results in artifacts at 

depth beneath sites near the ocean (red box in fig. 13C) where 

we expect a homogeneous resistive body associated with the 

subducting Juan de Fuca plate. The alternating conductive 

and resistive regions highlight the violation of the 2-D modeling assumptions, and represent erroneous anisotropic model 

structure required to account for both north–south electric current flow along the coastline and northeast–southwest current 

flow along the geologic strike. A depth slice and cross section 

(figs. 13A and 13B) through a 3-D inversion model using the 

same data confirm this interpretation and recover a more realistic 

resistivity model. The depth slice further illustrates an important 

aspect of inverting profile data in 3-D. The measured data are 

only sensitive to structure a limited distance from the profile. The 

uniform resistivity structure that can be seen away from the profile (fig. 13A) reflects the lack of data constraint in these regions 

and is the result of an inversion process designed to highlight 

only areas where structure is resolved. In this approach, the data 

are inverted beginning from a starting model with the conductive 

ocean explicitly included in a homogenous, less conductive halfspace (red region in fig. 2A). This model also serves as a prior 

during the inversion, penalizing differences from this model. 

This combination of starting and prior models serves to steer 

the inversion where needed to fit the data and to replace model 

structure with a uniform half-space where data sensitivity is low. 

This approach has been tested on numerous datasets and has 

been found to be crucial to recovering meaningful results when 

dealing with nonuniform site distributions.

A final example is the 3-D inversion of EarthScope MT 

data covering the Pacific Northwest, United States (Bedrosian 

and Feucht, 2014). This ever-growing dataset is unprecedented 

in its aperture and upon completion will provide the first continental-scale 3-D resistivity model of the North American lithosphere. Since the inception of EarthScope, a concern has been 

the coarse MT station layout (70-km site spacing) and how the 

effects of static shifts associated with local (outcrop-scale) heterogeneity will propagate into the resulting inverse models. Two 

depth slices through a 3-D inverse model of the EarthScope MT 

data are shown in figure 14. The effect of spatial aliasing is evident in the 1-km-depth slice (fig. 14A) with localized structure 

confined to the region surrounding a single site. An important 

observation from this study is that in 3-D, the distorting effects 

of static shifts are to some extent “soaked up” within the nearsurface model layers where the MT data have little sensitivity. 

Thus, a 3-D inversion with a sufficiently fine mesh can, to some 

degree, handle the effects of static shifts, even when station 

spacing is quite large. At 20-km depth (fig. 14B), structures 

reflecting the tectonic evolution of North America are imaged, 

including a first-order transition in central Oregon reflecting 

the northern extent of the Basin and Range (A), the rigid Siletz 

terrane and the intrusive roots of the Western Cascades (B), 

the mineralized Belt Basin (C), and the southwest Washington 

crustal conductor (D), the origin of which is subject to debate.

The above examples illustrate the capabilities of 3-D 

magnetotelluric inversion and highlight a few practical aspects 

of its application at a range of scales and with varying data 

distribution. 3-D MT inversion is refining the traditional 

approach to data collection from profile-based to grid-based 

surveys. It is also proving to be a valuable tool with which to 

revisit legacy datasets that were interpreted prior to the advent 

of 3-D MT inversion.

References Cited

Bedrosian, P.A. and Feucht, D.W., 2014, Structure and tectonics of the northwestern United States from EarthScope 

USArray Magnetotelluric Data: Earth and Planetary Science 

Letters, v. 402, p. 275–289. 

Bedrosian, P.A., 2008, A tale of two inversions—A comparison of 3-D magnetotelluric inversion in a mineralized 

region [abs.]: 19th Workshop on Electromagnetic Induction 

in the Earth, Beijing, China, Abstracts, v. 1, p. 112.

Bedrosian, P.A., and Box, S.E., 2007, Subsurface geometry of 

the Siletz-Klamath suture in southwest Oregon from magnetotelluric imaging [abs.]: Geological Society of America 

Abstracts with Programs, v. 39, no. 6, p. 47.

McCrory, P.A., Blair, J.L., Oppenheimer, D.H, and Walter, 

S.R., 2006, Depth to the Juan de Fuca slab beneath the Cascadia subduction margin—A 3-D model for sorting earthquakes: U.S. Geological Survey Data Series 91, 13 p. http://

pubs.usgs.gov/ds/91/.

Rodi, William, and Mackie, R.L., 2001, Nonlinear conjugate 

gradients algorithm for 2-D magnetotelluric inversion: Geophysics, v. 86, p. 174–187. 

Shah, A.K., Bedrosian, P.A., Anderson, E.D., Kelley, K.D., 

and Lang, James, 2013, Integrated geophysical imaging of 

a concealed mineral deposit: A case study of the world-class 

Pebble porphyry deposit in southwestern Alaska: Geophysics, v. 75, p. B317–B328.

Siripunvaraporn, Weerachai, Egbert, Gary, Lenbury, Yongwimon, and Uyeshima, Makoto, 2005a, Three-dimensional 

magnetotelluric inversion—Data-space method: Physics of 

the Earth and Planetary Interiors, v. 150, p. 3–14.

Siripunvaraporn Weerachai, Egbert, Gary, and Uyeshima, 

Makoto, 2005b, Interpretation of 2-D magnetotelluric 

profile data with 3-D inversion—Synthetic examples: Geophysical Journal International, v. 160, p. 804–814. 

Wannamaker, P.E., Evans, R.L., Bedrosian, P.A., Unsworth, 

M.J., Maris, Virginie, and McGary, R.S., 2014, Segmentation of plate coupling, fate of subduction fluids, and modes 

of arc magmatism in Cascadia, inferred from magnetotelluric resistivity: Geochemistry, Geophysics, Geosystems, 

v. 15 (11), p. 4230–4253, doi: 10.1002/2014GC005509.
Method and Software Development 27

Figure 13. Magnetotelluric profile data distorted by coast effect, southwest Oregon. A, Resistivity depth slice at 100 meters through 

a 3-D (three-dimensional) inverse model. Conductive ocean (red) is included as a priori structure in the inversion. B, Resistivity cross 

section through the 3-D inverse model taken along the site profile A–A′. Red dots denote the top of the Juan de Fuca subducting plate 

(from McCrory and others, 2006). C, Two-dimensional inverse model along the site profile in which model artifacts are evident (red box) 

due to distortion from coastline-parallel electric currents that are oblique to the geologic strike. mm/yr, millimeters per year.

Distance from mesh origin, in kilometers 

Juan de Fuca

 convergence 

~30 mm/yr

Coast

Mantle wedge

Accretionary

wedge

A

A

A'

B

B'

0

50

100

150

200

250

300

0 50 100 150 200 250 300

Distance from mesh origin, in kilometers 

0

−10

−20

−30

−40

−50

Depth, in kilometers 

0 50 100 150 200 250 300

Distance, in kilometers 

Juan de Fuca plate

NORTHWEST SOUTHEAST

B

A A′

C

NORTHWEST SOUTHEAST

0

−10

−20

−30

−40

−50

Depth, in kilometers 

50 100 150 200 250

Distance, in kilometers 

Inverse model

artifacts

B B'

Resistivity (A, B), 

 in ohm-meters

! Magnetotelluric site

EXPLANATION

1

10

1,000

Resistivity (C), 

 in ohm-meters

10

100

1,000

100

!(

!(

!( !(

!(

!(

!( !(

!(

!(

!( !(

!(

!(

!(

!(

!(

!( !(

!(

!( !(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!(

!( !(

!(

!( !(

!(

!(

!( !(

!(

!(

N
28 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 14. Resistivity depth slices through 

the Pacific Northwest United States at 

depths of A, 1 kilometer and B, 20 kilometer. 

The dashed line indicates a prominent lower 

crustal transition interpreted as the northern 

boundary of the Basin and Range Province. 

Labels A through D in B denote features 

described in the text.

D

C

B A

 125° 120° 115° 110°

40°

45°

50°

 125° 120° 115° 110°

40°

45°

50°

Resistivity (A, B), 

 in ohm-meters

!( Magnetotelluric site

EXPLANATION

1

10

1,000

100

Volcano

Lower crustal 

transition

B

A

0 100 200 KILOMETERS

0 100 200 MILES
Method and Software Development 29

Improving Radar and Acoustic Imaging

By Karl J. Ellefsen

Issue and Scope

The U.S. Environmental Protection Agency delineates 

contaminants in the ground, and the U.S. Army Corp of 

Engineers delineates various types of heterogeneity in the 

ground. So, both agencies helped fund the development of a 

new method to process radar and acoustic data. Of course, this 

processing method also can be applied to radar and acoustic 

data collected for other purposes.

Although many methods have been developed to process 

radar and acoustic data, most require significant approximations of the physics of wave propagation because such 

approximations simplify numerical simulation on a computer. 

Recently, the need for such approximations has diminished 

because inexpensive but powerful computers are readily 

available. For this project, the processing method requires few 

approximations. Thus, an image from this new method should 

better represent actual heterogeneity than an image from an 

older method.

Objectives

The objective of this work was to develop a method to 

estimate the properties of the ground using either radar traces 

or acoustic traces. The method was constrained to use only 

those computer resources that are typically available in a modern personal computer. For example, the method could require 

multiple processor cores but not a cluster of computers.

Background

In the model used for the processing, locations are 

specified by a rectangular Cartesian coordinate system. The 

x–z plane of the model is divided into a grid of square cells. 

To each cell are assigned the model properties. Thus, model 

properties may vary in the x and z directions, but not in the y

direction. The model properties are based on complex slowness because it is closely related to wave propagation. The 

model properties are the natural logarithm of the real part of 

the complex slowness log SR and the natural logarithm of the 

imaginary part of the complex slowness log SI.

The inversion is based on this objective function: 

 O(m)=(dc

(m)−do)

TCd

–1 (dc

(m)−do)

*

+(m−mp)

T Cm

–1 (m−mp

) (3)

where superscript T represents the transpose operation and 

the superscript * represents the complex conjugate operation. 

Vector m comprises log SR and log SI for every model cell. 

Vector mp is equivalent to vector m, except that it pertains to 

the reference model and is constant throughout the inversion. 

Matrix Cm is the model covariance matrix. Vector do comprises the observed data. These data are the recorded traces 

that are transformed from the time domain to the frequency 

domain. (Alternatively, these data can be just the amplitudes 

and traveltimes [phases] of the first arriving waves.) Vector 

dc(m) is similar to do, except that it comprises the calculated 

data for the current model. These data are computed from the 

numerical solution of the vector Helmholtz equation, which 

accounts for propagation in the y direction as well as the x and 

z directions, making the model two-and-one-half dimensional 

(2.5-D). Matrix Cd is the data covariance matrix.

The objective function O(m) is minimized using conjugate direction and line search methods. The conjugate 

direction is used to change the model parameters causing the 

objective function to decrease. Because the objective function 

is nonlinear, this procedure must be applied repeatedly. 

Results and Conclusions

The new method was evaluated, in part, by processing 

crosswell radar data that were collected in a laboratory tank. 

The tank was filled with dry, well-sorted sand to a depth of 

1.61 meter (m). Embedded within the sand was an air-filled, 

plastic box for which the height and width were 0.178 and 

0.121 m, respectively. Two vertical, air-filled wells, which 

were 0.78 m apart, penetrated almost all of the sand. These 

two wells were used to collect the radar data. The radar traces 

were recorded with a sample interval of 40 picoseconds, and 

the trace duration was 20 nanoseconds. The frequencies with 

high amplitudes ranged approximately from 0.4 to 1.5 Gigahertz (GHz). 

The crosswell radar data were used to estimate the model 

shown in figure 15. For this figure, the estimated log SR and 

log SI were converted to relative dielectric permittivity εr with 

the equation:

ε

μ r

R I s s = −2 2

(4)

where μ is the magnetic permeability. The prominent, lowvalued anomaly corresponds to the air-filled box. Within this 

anomaly, the smallest εr (1.58 [no units]) is larger than the 

corresponding εr for air (1 [no units]) because of the limited 

spatial resolution. Throughout the sand, there are numerous 

small anomalies, which are interpreted as changes in compaction, moisture content, and mineral composition. For example, 

in the lower right corner of figure 15, εr is relatively low 

compared to the rest of the sand, and this region is interpreted 

as poorly compacted sand. At depths less than 0.5 m, εr ranges 

from approximately 2.24 to 3.42 (no units), which is consistent with a laboratory-measured value of 2.71 (no units) at 

0.95 GHz.

Some practical applications of this method include 

processing crosswell radar data and crosswell acoustic data. 

The processing could use either the complete traces or just the 

traveltimes and the amplitudes of the first arriving wave. Other 

practical applications include processing data collected with 
30 Developing Integrated Methods to Address Complex Resource and Environmental Issues

an uncommon geometry (for example, surface to well) or an 

uncommon antenna orientation for radar data. The method has 

been used to estimate S-wave velocities using the traveltimes 

from an S-wave refraction survey (Ellefsen, 2009); of course, 

the method also could be used to estimate P-wave velocities 

using the traveltimes from a P-wave refraction survey.

Collaborators

U.S. Environmental Protection Agency, Office of Research 

 and Development

Mineral Resource Program of the U.S. Geological Survey

Toxics Substances Hydrology Program of the U.S. 

 Geological Survey

U.S. Army Engineer Research & Development Center of the 

 U.S. Army Corp of Engineers 

Selected References

Burton, B.L., and Ellefsen, K.J., 2011, Phase inversion of 

refraction traveltimes: Environmental and Engineering Geophysical Society, Proceedings of the Annual Symposium on 

the Application of Geophysics to Engineering and Environmental Problems, Charleston, South Carolina, p. 179–182 

(CD-ROM).

Ellefsen, K.J., Croizé, Delphine, Mazzella, A.T., and McKenna, J.R., 2009, Frequency-domain Green’s functions for 

radar waves in heterogeneous 2.5D media: Geophysics, 

v. 74, no. 3, p. J13–J22. 

Ellefsen, K.J., 2009, A comparison of phase inversion and 

traveltime tomography for processing near-surface refraction 

traveltimes: Geophysics, v. 74, no. 6, p. WCB11–WCB24. 

Ellefsen, K.J., Mazzella, A.T., Horton, R.J., and McKenna, 

J.R., 2010, Frequency domain, waveform inversion of 

laboratory crosswell radar data: Society of Exploration 

Geophysicists Expanded Abstracts, v. 29, p. 4019–4023, 

doi:10.1190/1.3513697. 

Ellefsen, K.J., 2011, Computer programs for forward and 

inverse modeling of acoustic and electromagnetic data: U.S. 

Geological Survey Open-File Report 2011–1124, 11 p., 

http://pubs.usgs.gov/of/2011/1124/.

Ellefsen, K.J., Mazzella, A.T., Horton, R.J., and McKenna, 

J.R., 2011, Phase and amplitude inversion of crosswell radar data: Geophysics, v. 76, no. 3, p. G1–G12, 

doi:10.1190/1.3554412. 

Peters, Bas, Moulton, C.W., Ellefsen, K.J., Horton, R.J., and 

McKenna, J.R., 2010, High-frequency, crosswell radar 

data collected in a laboratory tank: U.S. Geological Survey 

Digital Data Series 486, 19 p., plus digital data, http://pubs.

usgs.gov/ds/486/.

Figure 15. Model estimated from the crosswell 

radar data. The model edges correspond to the 

boundary of the region probed by the radar waves. 

The black rectangle is the outline of the air-filled box. Well C Well B

0.0 1.0

1.5

1.0

0.5

0.5

0.0

Horizontal distance, in meters

Depth below sand-air interface, in meters

Relative dielectric

permittivity, unitless

1.74

3.25

1.91

2.07

2.24

2.41

2.58

2.75

2.92

3.08

3.42

1.57

EXPLANATION
Method and Software Development 31

U.S. Geological Survey Open-Source 

Ground Penetrating Radar Software

By Jeffrey E. Lucius and Lawrence B. Conyers

Issue and Scope

Ground penetrating radar (GPR) is a powerful tool for 

exploring the shallow subsurface of the Earth and certain 

structures, such as buildings and roads. In 1977 the U.S. 

Geological Survey (USGS) was one of the first organizations 

to acquire a commercial GPR system. At that time there was 

no commercially available GPR analysis software. Consequently, the USGS developed its own processing packages. 

Today, over three decades later, there is robust and highquality software available from GPR equipment manufacturers (for example, Geophysical Survey Systems, Inc., MALÅ 

Geoscience, and Sensors and Software, Inc.) and various 

other commercial entities (such as Geophysical Archaeometry 

Laboratory, Inc., Geoscanners AB, Ingegneria dei Sistemi 

S.p.A., and Sandmeier Scientific Software). In addition, there 

are many free software packages that visualize, process, and 

model GPR data (table 1). However, only a few of these packages include source code. Other than Seismic Unix, which is 

focused on seismic data analysis but can be used with GPR 

data (http://www.cwp.mines.edu/cwpcodes/), the USGS has 

been the only provider of general GPR analysis software, for 

the DOS and Microsoft Windows operating systems, with 

source code (written in the C and C++ programming languages; table 1). Here we describe the latest version of USGS 

GPR software, GprViewer+, which processes and displays 

GPR data in reflection profiles for two-dimensional analysis.

Objectives

The goal of GprViewer+ is to provide GPR users with 

easy to use software, with source code, which is both free 

and comprehensive in its features. Having access to source 

code is important for several reasons: (1) processing methods 

Table 1. Available free ground penetrating radar analysis software.

[OS (Operating System): D = DOS, Indep = OS independent, M = Macintosh, U = Unix/Linux, W = Windows; Type: Sim = 

numerical simulator/modeler, Multi = viewing, processing, maybe modeling, Viewer = basically just views data, Slicing = 

volume generator and slicer; USGS OFR, U.S. Geological Survey Open-File Report]

Source Software OS Type Source Code

Antonis Giannopoulos GprMAX2D, GprMAX3D M, U, W Sim –

Andr Tzanis matGPR M, U, W Multi MATLAB scripts

Carsten Aubert radarFTDT Indep Sim C

CWP CSM1 Seismic Unix U, W4 Multi C

GSSI2 Radview W Viewer –

Gary Olhoeft3 Groradar D Multi –

Geoscanners GPRsoft_lite W Multi –

Giles Grandjean Radar Unix U Multi Unix scripts, C

IEP5 PG Software U Multi –

Interpex IXGPR W Viewer –

Jeff Daniels6 Gphyz W Multi IDL scripts

Larry Conyers7 GPR_Process W Slicing –

SourceForge openGPR U Multi Python scripts

USGS OFR 95–588 GPRMODV2 D Sim C

USGS OFR 02–1669 GPR programs D Multi, slicing C

USGS OFR 2006–136510 GP Workbench W Multi C, C++

1

Center for Wave Phenomenon at Colorado School of Mines.

2

Geophysical Survey Systems, Inc.

3

U.S. Geological Survey and Colorado School of Mines.

4

Windows graphical user interface available.

5

Institute for Environmental Physics.

6

Ohio State University.

7

University of Denver.

8

Michael Powers and Gary Olhoeft.

9

Jeffrey Lucius and Michael Powers.

10Charles Oden and Craig Moulton.
32 Developing Integrated Methods to Address Complex Resource and Environmental Issues

can be checked for accuracy; (2) object-oriented code can be 

reused; (3) using the original source code, the software can be 

modified and recompiled for execution; and (4) the algorithms 

and techniques can be instructional. This first version of the 

software has all the basic features needed by most users: reading and writing the standard data storage formats, conversion 

between storage formats, robust visualization (2-D only at 

this time), basic data processing operations, velocity analysis, 

publication-quality image exporting, and Windows printing. 

This software is designed for users who want to visualize and 

perform basic processing on multiple GPR data files in 2-D, 

without having to organize them into a project.

Background

In the 1980s the USGS (Gary Olhoeft and Jeffrey Lucius) 

developed GPR software written in HP Basic for HP 9845 and 

HP 9000 workstations. Around 1990 we started writing software in the C programming language for use on personal computers running DOS and early versions of Windows. Michael 

Powers wrote a 1-D, full-waveform, GPR modeling program, 

which was published with source code in 1995 (Powers and 

Olhoeft, 1995). In 2002, we published all our C-code GPR 

programs, which ran in DOS or in a command-prompt window 

in Windows (Lucius and Powers, 2002). As part of his development of GPR antennas at the USGS, Charles Oden wrapped 

some of our early C-code software and his new C++ code with 

a Windows graphical user interface (GUI) and published GP 

Workbench (Oden and Moulton, 2006).

From 2003 to 2005, the USGS and University of Denver 

(DU) developed GprViewr in the Java programming language. 

This first version of our GUI-based GPR analysis software 

could be run on any operating system that could utilize the 

Java Runtime Environment (JRE). Though not published, it 

has been used extensively at DU and by other users around the 

world. In 2010 we started development of the latest version 

of our software, now called GprViewer+. It is object-oriented 

software written in C# and will run in 32-bit or 64-bit Windows when .NET 4 (or later version) is installed. The first version of GprViewer+ should be ready for publication in 2015.

Results and Conclusions

GprViewer+ has the familiar Windows design and functionality, including standard menus and tool bars, status bar, and 

panels, which can be hidden or shown. It has “drag and drop” 

functionality for importing GPR data files. The most common 

GPR storage formats can be read, as well as the SEG-Y format. 

Files can be converted from one format to the other when saved. 

The Message Panel can display file headers, trace headers, the 

internal “GprInfo” object, which records all information available about the GPR file and data, and messages. 

Each GPR reflection profile appears in its own window. 

Switching between GPR windows can be accomplished in several different ways. There are a variety of window arrangements 

available including cascading, tile by columns, and tile by rows. 

GPR data are initially displayed as depth or time on the 

vertical scale and distance or trace number on the horizontal 

scale. Nine preset color palettes are available. Zoom options 

include fixed multiplier, drawn-rectangle zoom, fit the window, 

fit the window width, fit the window height, or a 1-to-1 display 

(one sample for each screen pixel). If topographic information 

is supplied, the data can be topographically corrected for elevation with optional vertical exaggeration enforced.

For the cursor position in the active GPR window, the 

status bar displays sample number, trace number, sample 

amplitude, sample time, and, if available, sample depth and 

trace distance. A wiggle-trace panel, showing the trace under the 

cursor, can be made visible or hidden within each GPR window.

At the present stage of development, GprViewer+ includes 

basic data processing, mostly available through the Processing 

Panel and tool bar: (1) trim data to user-selected first and last 

traces, (2) set time zero and nominal relative dielectric permittivity, (3) remove a background trace, (4) stack traces, (5) mix 

traces (using a sliding moving-average window), (6) apply 

amplitude gain with real-time image updates, and (7) use 

hyperbola fitting to determine radar wave velocity. The original 

data are stored internally and never manipulated. There are two 

copies of the data that are used for processing, one for temporary display and one for saved changes. The original data can 

be restored at any time.

Future versions of GprViewer+ will include much more 

advanced data processing, drawing functions, numerical 

modeling, and 3-D voxel generation with slicing. Figures 16 

and 17 show some of the features available at this time in 

GprViewer+.

Collaborators

GprViewer+ and earlier software were developed in cooperation with the University of Denver and funded by the USGS 

Integrated Methods Development Project, the USGS Toxic 

Substances Hydrology Program, and the U.S. Army Engineer 

Research & Development Center.

References Cited

Lucius, J.E., and Powers, M.H., 2002, GPR data processing 

computer software for the PC: U.S. Geological Survey 

Open-File Report 02–166, 101 p., also available at http://

pubs.usgs.gov/of/2002/ofr-02-0166/.

Oden, C.P., and Moulton, C.W., 2006, GP Workbench manual—Technical manual, user’s guide, and software guide: 

U.S. Geological Survey Open-File Report 2006–1365, 81 

p., also available at http://pubs.usgs.gov/of/2006/1365/.

Powers, M.H., and Olhoeft, G.R., 1995, GPRMODV2—Onedimensional full waveform forward modeling of dispersive 

ground penetrating radar data, version 2.0: U.S. Geological 

Survey Open-File Report 95–58, 41 p., also available at 

http://pubs.usgs.gov/of/1995/0058/report.pdf.
Method and Software Development 33

Figure 16. Example GprViewer+ screens. A, Main window with all panels and bars displayed. The same data file is shown 

in each window. The window on the left is how the file is initially displayed when opened, with the (optional) wiggle trace 

panel visible. The two windows on the right have been formatted using the Format Image dialog, and a background trace 

has been removed from the data. B, Examples of the Format Image dialog.

A

B
Figure 17. Example use of hyperbola fitting (to rebar reflections) for velocity analysis of concrete.
Method and Software Development 35

Potential-Field Software

By Jeffrey D. Phillips

Issue and Scope

For more than 60 years, the U.S. Geological Survey 

(USGS) has been developing software to process and display 

potential-field (gravity and magnetic) and other geophysical 

data. This software includes basic tools for editing, projecting, and gridding scattered and flight-line data; tools for 

spatial and Fourier filtering of gridded and profile data; 

rudimentary tools for display of the data; and tools for the 

interpretation of the data using forward modeling, source 

parameter estimation, and inversion. In 1971, standard USGS 

data formats were adopted for grids and point data. This 

allowed computer programs written by different authors 

to work together as a coherent package, which became a 

research tool for prototyping new algorithms and extending 

the potential-field method. 

At first programs were developed on IBM mainframe 

computers, then on VAX and Unix-based minicomputers, 

and, starting in 1989, on personal computers running the DOS 

operating system (Godson and Mall, 1989; Cordell and others, 

1992; Phillips and others, 1993; Grauch and others, 1993). 

The last update of the DOS-based software package (Phillips, 1997) contained 246 executable programs and 36 batch 

scripts. Today the 16-bit DOS operating system has been 

replaced by 32-bit and 64-bit Windows operating systems 

requiring the use of new compilers and new strategies for 

maintaining this valuable software resource and applying it to 

USGS needs in the 21st century.

Objectives

The primary goal of this effort is an update of the USGS 

potential-field software package capable of running on 32-bit 

and 64-bit Windows-based computers. To make this package 

useful, both for current data processing needs and for future 

development of the potential-field method by USGS geophysicists, it must be based on open-source compilers and graphics 

toolkits, and it must use the standard USGS data formats for 

grids and point data. 

A secondary goal is to distribute USGS potential-field 

software to the geophysical community at large, both as 

a stand-alone package and as plug-in modules to popular 

commercial geophysical software packages such as Geosoft 

Oasis-montaj (Geosoft, 1998). Although not as polished as 

commercial software, free geophysical software is valuable 

to students, professors, and individual researchers. Opensource software is an important resource for validation of 

results and for stimulating development of new methods 

and capabilities.

Background

Until the late 1990s, in-house development of potentialfield geophysical software was the only option available to the 

USGS. This software was used for the processing of geophysical data and the production of geophysical maps for publication. By 1998, commercial geophysical software packages 

were offering data handling and map production capabilities 

far superior to those of the USGS software. In that year, the 

USGS entered into a long-term contract with Geosoft for multiple licenses of Oasis-montaj. As part of the contract, USGS 

binary data formats for grids and point-data files were permanently incorporated into Oasis-montaj.

Although Oasis-montaj currently addresses the routine data 

processing and map production needs of the USGS, it has two 

disadvantages over in-house software: (1) the processing algorithms are hidden as “black-boxes,” so they cannot be examined 

in detail and (2) the package is not suitable for the rapid development of new algorithms for data processing or interpretation. 

To partially address the “black box” issue, Phillips and others 

(2003) and Phillips (2007) released 52 USGS potential-field 

algorithms as plug-in modules for Oasis-montaj, complete with 

source code. These Geosoft eXecutables or GXs provide an 

alternative to the Geosoft algorithms for basic grid utilities, spatial and Fourier filtering of grids, and grid interpretation. They 

also extend the capabilities of Oasis-montaj to include matched 

filtering of grids and new source-location algorithms.

Although GXs provide a way of incorporating USGS 

algorithms into Oasis-montaj, they are only useful for mature 

algorithms that are fully debugged. To develop new USGS 

algorithms and to preserve the old DOS algorithms, a Windows version of the USGS development environment has been 

assembled replacing 16-bit Microsoft Fortran and C compilers 

with a combination of open-source, 32-bit compilers (g77, 

gfortran, and gcc) and the Tcl/Tk graphical user interface 

(Welch and others, 2003; von Hagen, 2006). Several subroutine libraries of Webring (1998) have been used directly or 

modified to provide a new uniform command-line interface 

and access to binary files. PDEPTH (fig. 18), a graphical magnetic- and gravity-profile-analysis program, is one example 

of a USGS program updated using this new environment. 

Release of a complete package of USGS Windows-based software is planned for the near future. 

Results and Conclusions

USGS contributions to potential-field geophysics are 

documented in publications and in software (Bankey and 

Anderson, 1995). Most of the publications are readily available, but much of the software has become out-of-date as 

personal computers have evolved. Converting outdated USGS 

software to GX plug-in modules, or to stand-alone programs 

that will run on modern computers, is the best way to maintain 

this legacy code. The development environments used for this 

preservation effort also permit the future development of the 

potential-field method at the USGS.
36 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Collaborators

Misac Nabighian and Yaoguo Li, Colorado School of Mines

Mark Pilkington, Geological Survey of Canada

Richard Hansen (deceased) and Mike Hall, Edcon-PRJ

Jim Roy, Northwest Geophysical Associates, Inc.

Gerry Connard, Geosoft

Des Fitzgerald, Intrepid Geoscience

Mike Webring and Bob Simpson, USGS emeriti

V.J.S. (Tien) Grauch and Richard J. Blakely, USGS

Figure 18. PDEPTH (a graphical magnetic- and gravity-profile-analysis program) is one example of a U.S. Geological Survey potential-field 

software program incorporating a graphical user interface. The ground-based magnetic profile (orange symbols in upper “profile” window) was 

collected on a surface (orange symbols in lower “section” window) just above the ground surface (upper gray line in section window, largely 

obscured by the orange observation surface symbols). Other gray lines in the section window represent geologic horizons and a fault extracted 

from a three-dimensional model. Vertical gray lines represent features such as bends in the line and intersections with other lines. Also scaled 

to fit within the profile window are the reduced-to-pole magnetic profile (red line, largely obscured by the orange observed magnetic profile 

symbols ), pseudogravity profile (purple line), and upward-continued pseudogravity profile (green line). The continuation surface (green line just 

above the section window) is 200 feet above the observation surface. Magnetic source locations estimated from upward-continued profiles are 

shown as green symbols (“C” for contact solutions and “S” for sheet solutions) in the section window. Dips of some sources are assumed to be 

vertical or horizontal; dips of other sources are estimated. Mouse-driven control buttons are on the right-hand side.

References Cited

Bankey, Viki, and Anderson, W.L., 1995, A bibliography of 

some geophysical computer programs, databases, and maps 

from the U.S. Geological Survey, 1971–1994: U.S. Geological Survey Open-File Report 95–77, unpaginated.

Cordell, Lindrith, Phillips, J.D., and Godson, R.H., 1992, U.S. 

Geological Survey potential-field geophysical software version 2.0: U.S. Geological Survey Open-File Report 93–18, 

18 p., 6 diskettes. 
Method and Software Development 37

Geosoft, 1998, OASIS Montaj Data Processing and Analysis 

(DPA) System for earth science applications, version 4.2, 

user guide: Geosoft, 268 p.

Godson, R.H., and Mall, M.R., 1989, Potential-field geophysical programs for IBM compatible microcomputers, version 

1.0: U.S. Geological Survey Open-File Report 89–197, 

23 p., 5 diskettes.

Grauch, V.J.S., Phillips, J.D., Hoover, D.B., Pitkin, J.A., Livo, 

K.E., and McCafferty, Anne, 1993, Materials provided at 

the workshop “Geophysical Map Interpretation on the PC,” 

convened April 21–22, 1993: U.S. Geological Survey OpenFile Report 93–560, 150 p., 14 diskettes (includes potentialfield software update 2.11).

Phillips, J.D., 1997, Potential-field geophysical software for 

the PC, version 2.2: U.S. Geological Survey Open-File 

Report 97–725, 34 p., http://pubs.usgs.gov/of/1997/ofr-97-

0725/pfofr.htm.

Phillips, J.D., 2007, Geosoft eXecutables (GX’s) developed by 

the U.S. Geological Survey, version 2.0, with notes on GX 

development from Fortran code: U.S. Geological Survey 

Open-File Report 2007–1355, 111 p., http://pubs.usgs.gov/

of/2007/1355/.

Phillips, J.D., Duval, J.S., and Ambrosiak, R.A., 1993, 

National geophysical data grids—Gamma-ray, gravity, 

magnetic, and topographic data for the conterminous United 

States: U.S. Geological Survey Digital Data Series DDS–9, 

1 CD-ROM, includes potential-field software version 2.1.

Phillips, J.D., Duval, J.S., and Saltus, R.W., 2003, Geosoft 

eXecutables (GX’s) developed by the U.S. Geological Survey, version 1.0, with a viewgraph tutorial on GX development: U.S. Geological Survey Open-File Report 03–010, 

23 p., http://pubs.usgs.gov/of/2003/ofr-03-010/.

von Hagen, William, 2006, The definitive guide to GCC: New 

York, NY, Apress, 584 p.

Webring, M.W., 1998, ODDF—A file I/O subroutine package 

implementing NASA PDS data description and USGS map 

projections, version 1.6: U.S. Geological Survey Open-File 

Report 98–765, 132 p., http://pubs.usgs.gov/of/1998/0765/

report.pdf.

Welch, B.B., Jones, Ken, and Hobbs, Jeffrey, 2003, Practical 

programming in Tcl and Tk: Upper Saddle River, NJ, Prentice Hall PTR, 960 p.

Improving Geophysical Model 

Assessment with Bayesian Markov 

Chain Monte Carlo Methods

By Burke J. Minsley

Issue and Scope

Geophysical models are inherently uncertain due to the 

underlying measurement physics, data errors, acquisition 

geometry, and method of interpretation. But information about 

model uncertainty is rarely provided to nongeophysicist endusers be they hydrologists, geologists, or policy makers. Instead, 

geophysical results are often presented as a single “best” 

model. Although this simple product is often what the end-user 

wants, it can lead to misleading or incorrect interpretations. 

For example, if a geophysical model is displayed to a depth of 

150 meters (m), it may be interpreted to that depth—even if the 

actual depth to which the data are sensitive is much shallower. 

When geophysical models disagree with co-located borehole 

data, it is often assumed that the geophysics is wrong, when in 

fact both models may be consistent with the measured data but 

are different because of equivalence and resolution issues. For 

these and many other reasons, the development of robust model 

assessment tools that can better inform nongeophysicists is critical to advancing the value of geophysical data.

The focus of this work is to convey the characteristics of 

geophysical models that are consistent with measured data, 

rather than focus on the properties of any single model. This 

approach was popularized within the geophysical community by Albert Tarantola, who wrote “Practitioners usually 

seek the ‘best solution’ implied by the data, but observations 

should only be used to falsify possible solutions, not to deduce 

any particular solution” (Tarantola, 2006). Here, a Bayesian 

Markov chain Monte Carlo (MCMC) algorithm was developed to assess the information contained in frequency-domain 

electromagnetic (FDEM) data, which are commonly acquired 

from both airborne and ground-based platforms by the U.S. 

Geological Survey (USGS). Whereas FDEM data are the focus 

here, the algorithm is readily adaptable to other geophysical 

methods, which will be the focus of future efforts.

Objectives

The objective of this work was to adapt and extend existing Bayesian MCMC methods developed originally for directcurrent resistivity surveys (Malinverno, 2002) for application 

to FDEM data. Because the algorithm can be readily modified 

for use with other types of geophysical data, this project is the 

base upon which future MCMC development will be founded. 

Initial applications for this work include model assessment and 

uncertainty analysis for airborne electromagnetic data acquired 

in western Nebraska (presented in the Results and Conclusions 
38 Developing Integrated Methods to Address Complex Resource and Environmental Issues

section) and Alaska, as well as ground-based FDEM data from 

the Powder River Basin in Wyoming. 

In addition to its use as a model assessment tool, the 

MCMC algorithm has also been modified to investigate instrument calibration errors (Minsley and others, 2011a,b). By 

gaging systematic instrument errors, correction factors can be 

derived that yield more accurate data which, in turn, lead to 

more accurate interpretations. Understanding data errors, both 

random and systematic, is absolutely critical for producing 

reliable results that can be interpreted with confidence. Information about reliability and model uncertainty is extremely 

relevant for USGS products that are available for use by decision makers and the public.

Background

Stochastic parameter estimation techniques, as opposed to 

traditional deterministic inversion methods, have been utilized 

for some time to quantify uncertainty in geophysical inverse 

problems (Sambridge and Mosegaard, 2002). Advances in 

computational resources have made random search methods 

increasingly tractable for a growing class of parameter estimation problems. The primary benefit to stochastic methods is 

their ability to assess many viable models, rather than to focus 

on a single “best” model. In addition, many of the drawbacks of 

deterministic methods (such as the necessary linearization of the 

inverse problem and risk of finding solutions that are local, rather 

than global, minima) can be avoided using a stochastic approach. 

The work of Malinverno (2002) and Sambridge and 

others (2006) has been adapted to perform model assessment FDEM geophysical datasets using a trans-dimensional 

Bayesian MCMC algorithm, the details of which can be found 

in Minsley (2011). This is a one-dimensional algorithm that 

produces an ensemble of many (tens to hundreds of thousands) 

layered-earth models of electrical resistivity as a function of 

depth that are consistent with the measured data. The main 

features of the algorithm are summarized below:

• Parameterization: Unknown parameters include layer 

interface depths and resistivity values within each 

layer. A unique feature of this algorithm is the fact that 

it is trans-dimensional, which means that the number of 

unknowns (that is, the number of layers) is one of the 

unknowns. That is, the number of layers is allowed to 

vary and the data, rather than a priori assumptions, are 

used to estimate the appropriate number of layers. This 

trans-dimensional aspect of the algorithm provides a 

substantial benefit in that solutions are not biased by a 

predetermined choice about the correct number of layers. In addition, models with fewer layers are implicitly 

favored, which provides a natural measure of simplicity in the parameter assessment problem. In addition to 

the number of layers, interface depths, and resistivity 

values, the user can choose to estimate several optional 

parameters, including the level of random noise in the 

data, systematic instrument errors, and errors in the 

reported elevation of the FDEM system.

• Bayesian approach: According to Bayes theorem, 

each model is assigned a probability based on its fit to 

the data and how well it agrees with a priori assumptions. In this work, the only prior information is that 

resistivity values should not oscillate wildly, which is 

based on the assumption that geologic properties do 

not vary significantly over short distances. This prior 

information is incorporated through a normal distribution that penalizes models with thin layers that have 

large resistivity contrasts. The data fit is also described 

by a normal distribution that measures the difference between observed and predicted data for a given 

model. The product of these two distributions is used 

to calculate the posterior probability for each sampled 

model. Although normal distributions are used here, it 

is straightforward to use any other probability density 

function that is appropriate.

• MCMC sampling: MCMC sampling is an effective 

tool for solving Bayesian problems where the posterior 

distribution cannot be evaluated analytically. MCMC 

sampling rules provide a guideline for proposing 

and accepting or rejecting models that, after a short 

“burn-in” period, are samples of the target posterior 

distribution. Each proposed model in the Markov 

chain depends only on the previous model in the chain. 

Making proposals that efficiently explore the space 

of plausible models is extremely important and is discussed in detail by Minsley (2011). The algorithm runs 

for a prespecified number of samples are drawn or until 

some convergence criterion is met.

• Computational details: The FDEM trans-dimensional 

Bayesian MCMC algorithm is coded in Matlab. The 

computational bottleneck is in calculating the forward 

response to each proposed model; therefore, an efficient 

FDEM forward solver was written for Matlab, which 

utilizes multithreaded CPUs. The time for a single 

MCMC step is approximately 20 milliseconds (though 

it depends on the number of layers in the proposed 

model); therefore, a typical model assessment that samples 100,000 models takes approximately 30 minutes.

Results and Conclusions

Compared with deterministic inversion algorithms, the 

MCMC method is significantly more computationally expensive but also contains much more information that can be used 

for model assessment and uncertainty analysis. For this reason, 

we utilize both methods together—the fast deterministic inversion algorithm is first run to provide an estimate of parameter 

values over an entire survey. Next, the MCMC algorithm is 

run at a few characteristic locations within the survey where 

information about uncertainty is needed.

An example of this approach from an airborne FDEM 

survey in western Nebraska (Smith and others, 2010) is presented here. The primary goal of this survey was to map the 
Method and Software Development 39

geometry of alluvial aquifer material that overlies a siltstone 

aquitard. The aquifer geometry is incorporated in hydrologic 

models to produce more reliable estimates of groundwater 

flow and aquifer saturated thickness. Deterministic inversion 

results along a single ≈25-kilometer-long survey profile clearly 

map the geometry of the resistive (red, fig. 19A) alluvial aquifer overlying the more conductive (blue, fig. 19A) aquitard to 

depths of ≈75 m (fig. 19A). These results are consistent with 

sparse borehole information but do not convey information 

about model uncertainty. For this purpose, the MCMC algorithm was run at four characteristic locations of interest along 

the profile, marked I–IV in figure 19A. 

Figures 19B–19E show the distribution of plausible 

resistivity models as a function of depth for each of the 

MCMC depth of investigation estimate—Normalized

 95 percent confidence interval width

MCMC model distribution EM1DFM model

MCMC 95 percent limit

B D

F G

C E

H I

I II III IV METERS

1,050

1,100

1,150

1,200

1,250

1,300

1,350

10 

20 

40 

80 

160

320

100° 43’

3

0 4321 5

0 21

KILOMETERS

MILES

SOUTH NORTH

A

Resistivity, in ohm-meters

0

50

100

150

Depth, in meters

0

50

100

150

0

50

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150

0

50

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0.01

0.1

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1,000

100

10

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100,000

0

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150

0 0.01 0.02 0.03

0

50

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150

0 0.02 0.04 0.06

0

50

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0 0.01 0.02 0.03

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0 0.01 0.02

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10

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100,000

Resistivity, in ohm-meters Resistivity, in ohm-meters Resistivity, in ohm-meters Resistivity, in ohm-meters

Depth, in meters

Frequency Frequency Frequency Frequency

EXPLANATION

MCMC most probable model

Figure 19. Airborne frequency-domain electromagnetic profile in western Nebraska. A, Deterministic 

inversion results (from Smith and others, 2010). B–E, Markov chain Monte Carlo (MCMC)-sampled probability 

distributions of resistivity models at the four locations along the survey profile in A compared with the 

deterministic models at the same locations. F–I, Distribution of interface depths for each of the four MCMC 

locations indicate likely interface depths as well as the ability to resolve different interfaces. Pink curves 

indicate the width of the 95-percent credible region of models (dashed lines in B–E), normalized to the width at 

the bottom of the model.
40 Developing Integrated Methods to Address Complex Resource and Environmental Issues

150

100

50

0

Resistivity, in ohm-meters

0 100 200

−150

−100

−50

0

Formation factor 

 MCMC model distribution

MCMC most probable model

EM1DFM model

MCMC 95 percent limit

Short normal resistivity log

Long normal resistivity log

Gravel/gravelly soils

Sand/sandy soils

Formation factor Silts and clays

Depth, in meters

1 10 100 1,000 10,000 100,000

EXPLANATION

Figure 20. Markov chain Monte Carlo (MCMC)-sampled probability distribution 

from figure 19E compared with deterministic inversion result (green curve), borehole 

resistivity logs (yellow curves), and lithologic data (right panel). Although the “bestfit” inversion model appears to not agree with the borehole data, the MCMC analysis 

indicates that the frequency-domain electromagnetic data is also consistent with the 

borehole data, even though it is not the most probable model. EM1DFM is a software 

program (Farquharson and others [2003]).

four locations. These distributions are illustrated as shaded 

hit maps, where regions of the model with darker shading 

indicate a higher probability of a given resistivity value at 

the corresponding depth. Superimposed on each panel is the 

deterministic inversion result at that location (green curve) 

as well as the bounds that contain 95 percent of the MCMC 

sampled models (dashed magenta curves). These images convey information about the plausible range of resistivity values 

at depth and indicate the variable uncertainty associated with 

different sounding locations. Figures 19F–19I show histograms of the interface depths for all of the sampled MCMC 

models. In these panels, the peaks in the histogram indicate 

likely interface depths, and the width of the peak conveys 

details about how well resolved the interface is. For example, 

the base of the resistive aquifer at location II is much less 

well-defined than at location III due to the fact that it is much 

deeper. The magenta curves in figures 19F–19I show the 

width of the 95-percent credible region bounds from figures 

19B–19E and provide a quantitative metric for the depth of 

investigation, where there is a rapid increase in uncertainty 

beneath ≈50-m depth.

The resistivity distribution from figure 19E is reproduced 

in figure 20 along with downhole resistivity logs (yellow 

curves) and lithology information (right panel) from a borehole at the same location as the FDEM data. This location 

offers an example where the deterministic inversion result 

(green curve) appears to be inconsistent with the downhole 

data because it does not capture the increase in resistivity 

from ≈40–75 m depth. However, the MCMC results show 

that elevated resistivity values in this depth range are in fact 

consistent with the measured data. This illustrates the danger 

in interpreting the results of a single “best-fit” model.
Method and Software Development 41

Robust methods for quantifying the uncertainty associated with geophysical models provide critical information for 

the end-users of geophysical datasets. The Bayesian MCMC 

approach implemented here has broad applicability for datasets acquired by the USGS, and will also be adapted for other 

types of data. 

Selected References

Farquharson, C.G., Oldenburg, D.W.,and Routh, P.S., 2003, 

Simultaneous 1D inversion of loop–loop electromagnetic 

data for magnetic susceptibility and electrical conductivity: 

Geophysics, 68(6), 1857–1869, doi:10.1190/1.1635038.

Malinverno, Alberto, 2002, Parsimonious Bayesian Markov 

chain Monte Carlo inversion in a nonlinear geophysical 

problem: Geophysical Journal International, v. 151, no. 3, 

p. 675–688.

Minsley, B.J., 2011, A trans-dimensional Bayesian Markov 

chain Monte Carlo algorithm for model assessment using 

frequency-domain electromagnetic data: Geophysical Journal International, v. 187, no. 1, p. 21.

Minsley, B.J., Hodges, Greg, Smith, B.D., and Abraham, J.D., 

2011a, Multi-elevation calibration of frequency domain 

electromagnetic data: 17th European Meeting of Environmental and Engineering Geophysics of the EAGE, Leicester, England [invited paper].

Minsley, B.J., Hodges, Greg, Smith, B.D., and Abraham, J.D., 

2011b, Multi-elevation calibration of frequency domain 

electromagnetic data: 24th Symposium on the Application 

of Geophysics to Engineering and Environmental Problems, 

Charleston, South Carolina. 

Minsley, B.J., 2010, Improved geophysical model assessment using Bayesian Markov chain Monte Carlo Sampling 

[abs.]: American Geophysical Union 2010 Fall Meeting, 

San Francisco, Calif., December 13–17, 2010, Abstract 

NS13A-1163.

Minsley, Burke, 2010, Electrical resistivity parameter estimation and model appraisal using Bayesian inference, in S.R. 

Brady (ed.), Proceedings of the Third USGS Modeling 

Conference, June 7–11, 2010, Broomfield, Colorado—

Understanding and Predicting for a Changing World: U.S. 

Geological Survey Scientific Investigations Report 2011–

5147, p. 49. 

Minsley, B., 2009, Assessing electrical resistivity model uncertainty using Bayesian inference [abs.]: EOS Transactions, 

American Geophysical Union, v. 90, no. 22, Joint Assembly 

Supplement, Toronto, Canada, Abstract NS13A-03. 

Sambridge, Malcolm, and Mosegaard, Klaus, 2002, Monte 

Carlo methods in geophysical inverse problems: Reviews of 

Geophysics, v. 40, no. 3, p. 3–1.

Sambridge, Malcolm, Gallagher, Kerry, Jackson, Andrew, and 

Rickwood, Peter, 2006, Trans-dimensional inverse problems, model comparison and the evidence: Geophysical 

Journal International, v. 167, no. 2, p. 528–542.

Smith, B.D., Abraham, J.D., Cannia, J.C., Minsley, Burke, 

Deszcz-Pan, Maria, and Ball, Lyndsay, 2010, Helicopter 

electromagnetic and magnetic geophysical survey data, portions of the North Platte and South Platte Natural Resources 

Districts, Western Nebraska, May 2009: U.S. Geological 

Survey Open-File Report 2010–1259, 33 p. http://pubs.usgs.

gov/of/2010/1259/

Tarantola, Albert, 2006, Popper, Bayes and the inverse problem: Nature Physics, v. 2, no. 8, p. 492–494.
Instrument Development

Development and Implementation of 

Passive Electrical Monitoring Arrays

By Burke J. Minsley and Paul A. Bedrosian

Issue and Scope

Passive electrical and electromagnetic measurements are 

widely used for the geophysical characterization of subsurface 

properties and processes (Bedrosian, 2007; Bedrosian and 

others, 2007; Linde and others, 2011). Monitoring applications, however, require additional consideration as measuring 

systems must be deployed for long periods of time (weeks 

to months) and in harsh environments. Passive electrical 

monitoring arrays comprise two main components: measuring 

electrodes that are placed in direct contact with the Earth and 

the necessary cabling and data-logging equipment that is connected to the electrodes. Both components of the system must 

be robust to diverse environmental conditions while providing 

reliable and stable measurements.

We summarize the development of a multichannel 

passive monitoring array that was deployed for 1 month at 

Kilauea Volcano, Hawaii, and later for 1.5 months underwater 

in the Great Salt Lake, Utah. In the Kilauea project, the system 

was utilized to monitor hydrothermal and magmatic processes 

at the volcano summit, whereas the Great Salt Lake study 

investigated submarine groundwater discharge. Both projects 

presented challenging environmental conditions that required 

the design of a multichannel monitoring system, which is not 

available commercially.

In addition, we have constructed a laboratory 

tank for monitoring and comparing the long-term stability of different electrode designs. This controlled 

setting provides a platform for investigating the 

stability and noise characteristics of various types of 

electrodes and is used to select and match electrodes 

prior to taking them into the field. From a practical 

perspective, the tank is also ideal for maintaining 

electrodes, which tend to degrade if allowed to dry.

Objectives

Our primary objective was to design a versatile passive electrical monitoring array that could be 

deployed in harsh environmental conditions for a 

variety of monitoring applications and over a range of 

spatial scales and for durations of months or longer. 

Because of the requirements of the Great Salt Lake 

project, the system was designed not only to be 

weatherproof, but also to be capable of underwater 

installation. Other system requirements included integrated data storage to minimize manual data retrieval, 

ability to operate remotely with a solar-charged 

battery power supply, and need for a modular cable 

design to allow for flexibility in electrode geometry 

A B

C D

E

A B

Figure 21. Electrical monitoring array. A, Multiconductor 

electrode cables, each with eight waterproof electrode 

takeouts at 20-meter intervals. B, Adapters for connecting 

bare-wire electrodes to the waterproof takeouts. 

C, Lead-lead chloride electrodes encased in bentonite 

and porous cloth bags to reduce contact resistance with 

the earth. D, Weatherproof box housing the data-logging 

system. Solar panel (not visible) is affixed to the box lid. 

E, Electrode test tank with datalogger. (USGS photographs)
Instrument Development 43

and spacing. In addition to the monitoring array, a laboratory 

test tank was needed to test and maintain the large number of 

nonpolarizable electrodes utilized within the array and for other 

geophysical measurements (self-potential, magnetotelluric, 

induced-polarization).

Background

The initial array design consisted of eight 160-m multichannel cables (fig. 21A), each of which has eight electrode 

takeouts, for a total capacity of 64 electrodes. After the first 

two system deployments, an additional eight cables were purchased, increasing the capacity to 128 electrodes. Each cable 

can be deployed independently, or two cables can be mated to 

extend the array length and capacity to 320 m (16 electrodes). 

Electrode takeouts are spaced at 20-m intervals along the cable 

allowing for a relatively large electrode spacing that can be 

reduced as needed by bunching together the cable between 

electrodes. Takeouts are terminated with the female end of 

an underwater connector. For the Great Salt Lake project, 

64 silver-silver chloride electrodes were custom manufactured with the male end of the underwater connectors. Male 

underwater connectors to bare-wire adapters were also made 

for deployments that do not require the special underwater 

electrodes and facilitate the use of the array with any conceivable electrode design (fig. 21B). In resistive environments, 

such as at Kilauea, electrodes were encased in bentonite and 

surrounded by porous cloth bags in order to lower contact 

resistance with the Earth (fig. 21C).

Cables are connected to one or more Campbell Scientific 

multiplexers and dataloggers that can be programmed for custom data-sampling schedules. The multiplexers and dataloggers 

are housed in a weatherproof box, which also houses a rechargeable battery connected to a solar panel and voltage regulator 

(fig. 21D). Data can be retrieved at any time by connecting a 

laptop to the datalogger via serial cable. The length of unattended data acquisition depends upon sample rate and array size 

but is typically on the order of 1–2 weeks for typical layouts. 

Longer remote deployments can be achieved with additional 

system memory or a variety of telemetry options. Additional 

environmental variables such as soil and water temperature and 

oxidation-reduction potential (ORP) can also be recorded with 

separate sensors purchased with the Campbell system.

An electrode test tank was constructed to hold 64 geophysical electrodes in a temperature and salinity controlled 

environment (fig. 21E). Electrodes are suspended in a saturated 

and circulating salt solution. The potential of each electrode is 

sampled every 30 seconds relative to a common reference electrode using a recording setup identical to that of the monitoring 

array. Air and water temperature are additionally monitored to 

assess the degree of environmental forcing on the system. The 

electrodes are periodically examined to estimate thermal coefficient (in millivolts per degrees Celsius [mV/°C]), potential 

(mV), and long-term stability. The long-term averaged potential measurements are further used to match pairs of electrodes 

with similar potential and, hence, reduce errors in geophysical measurements. A second test tank is under construction to 

house electrodes of a different chemical composition.

Results and Conclusions

At Kilauea volcano, a deployment of 64 

electrodes with 20-m spacing was installed along 

a 1.2-km profile radiating outward from the 

Halema`uma`u vent, an active vent with connection to the shallow magmatic system. Electrodes 

were installed in weathered volcanic sand (fig. 22A), 

where possible, and pressed into crevices of recent 

volcanic flows where necessary. Electrode voltages were sampled every 20 seconds, in addition to 

temperature probes that recorded ground temperature 

at two locations along the array and gas temperature 

within an active fumarole. Data loggers and multiplexers were housed in weatherproof enclosures and 

Figure 22. Deployment of electrodes. A, Single electrode 

takeout and connector leading to buried electrode within 

volcanic sand at Kilauea volcano. B, Downloading data at 

Kilauea volcano. Datalogger is within weather enclosure 

and black plastic bagging. Halema`uma`u vent is visible 

in the background. C, Electrode installation in the Great 

Salt Lake. D, Downloading data at Great Salt Lake. 

(USGS photographs)

A B

C D
44 Developing Integrated Methods to Address Complex Resource and Environmental Issues

further wrapped in plastic bags to limit exposure to corrosive 

volcanic gases (fig. 22B). Batteries were changed and data 

recovered approximately every 10 days. The data are being 

analyzed in relation to volcanogenic processes, including 

pronounced deflation/inflation cycles of the summit area and 

magma drain/fill cycles within the Halema`uma`u vent (Bedrosian and Kauahikaua, 2010).

In the Great Salt Lake, 64 electrodes were installed in loose 

sand beneath 20–40 cm of water (fig. 22C). The data recording 

equipment were housed in a Pelican case mounted on a platform 

built over the water (fig. 22D) and powered by a small solar 

panel. Electrodes were deployed along shore-parallel profiles 

extending 160 m in both directions from the datalogger, with 

5–10 m electrode spacing. All 64 electrodes, plus one measurement of temperature and ORP in the water near the datalogger, 

were sampled every two minutes from June 17–August 4, 2010, 

resulting in nearly two million data points. Analysis of these 

data, combined with fiber optic distributed temperature measurements collected along a longer, subparallel profile, are ongoing. 

Collaborators

Utah Water Science Center

USGS Office of Groundwater, Branch of Geophysics

 Hawaiian Volcano Observatory

USGS Geology Venture Capital Fund

Selected References

Bedrosian, P.A., 2007, MT+, integrating magnetotellurics to 

determine Earth structure, composition, and processes: Surveys in Geophysics, doi:10.1007/s10712-007-9019-6.

Bedrosian, P.A., and Kauahikaua, James, 2010, Monitoring 

volcanic processes at Kilauea volcano with electrical and 

electromagnetic methods: Proceedings, 20th Workshop 

on Electromagnetic Induction in the Earth, Cairo, Egypt, 

2010, 4 p.

Bedrosian, P.A., Unsworth, M.J., and Johnston, M.J.S., 2007, 

Hydrothermal circulation at Mount St. Helens determined 

by self-potential measurements: Journal of Volcanology and 

Geothermal Research, v. 160, no. 1–2, p. 137–146.

Linde, Niklas., Doetsch, Joseph, Jougnot, Damien, Genoni, 

O., Dürst, Yolanda, Minsley, B.J., Vogt, Tobais, Pasquale, 

N., and Luster, Jörg, 2011, Self-potential investigations of a 

gravel bar in a restored river corridor: Hydrology and Earth 

System Sciences, v. 15, no. 3, p. 729–742.

Development of a Waterborne 

Electromagnetic Survey System

By David V. Smith, Maria Deszcz-Pan, 

Daniel S. Scheirer, and Charles D. Blome

Issue and Scope

Airborne geophysical methods provide a cost-effective 

means of rapidly mapping electrical and magnetic properties 

over large areas of the Earth. Because these physical properties are often diagnostic of rock types, such surveys can be 

a valuable tool for geologic mapping. Unless equipped with 

pontoons, commercial helicopter surveys undertaken in the 

United States are restricted from flying over open water by 

Federal Aviation Administration rules. In many places, complex geological structural features, such as faults, are under 

cover of water, inaccessible to field geologists.

Objectives

In areas of complex geology, it is often desirable to map 

structures that are under water to resolve, for example, fault 

traces, which are otherwise inferred. The objective of this 

work is to supplement airborne electromagnetic (EM) data 

with comparable data acquired on a freshwater lake using an 

EM bird mounted on a raft that is towed by a motorboat.

Background

The Lake of the Arbuckles in Chickasaw National 

Recreation Area was selected for waterborne electromagnetic 

(WEM) testing and evaluation because data from the lake 

would dovetail with data from a helicopter EM (HEM) survey 

flown in 2007 over an area bordering the lake to the east 

(Smith and others, 2011). An HEM bird originally developed 

for measuring sea ice thickness was mounted on a pontoon raft 

for operation on water. The EM bird was suspended inside a 

rectangular housing for ease of handling and protection from 

water. The raft also carried a magnetometer and a Q-coil for 

automatic calibration during the survey. The raft was towed 

by a motorboat, which carried the data acquisition systems for 

the EM bird and sonar bathymetry (fig. 23). In addition to EM 

data, accurate water depths were continuously measured along 

survey lines using a multibeam echo-sounder. Water-quality 

soundings were obtained at multiple locations to determine 

electrical conductivities of the water column, which will be 

used in subsequent data processing.

A theoretical model evaluated the sensitivity of the 

system to the geoelectrical parameters encountered in the lake 

environment. The model consisted of a 29 ohm-meter (Ω-m) 

water layer of varying thickness over a 20 Ω-m basement. 

Basement resistivity was estimated from the adjacent HEM 

survey measurements. The model showed that the expected 
Instrument Development 45

system response significantly diminished for water depth 

greater than 5–10 m. Field data confirmed this result, showing 

flat responses over water deeper than about 7–10 m.

Results and Conclusions

The resolution of basement resistivity below the water 

layer depends on water depth, basement resistivity, and system 

parameters. Modeling showed that for a realistic system assuming 

5 percent noise, detection of the 20 Ω-m basement is not possible below 10-m water depth. Detection depth would increase 

for a more conductive basement (up to about 15 m for 10 Ω-m 

basement), a less conductive water column, or lower system 

noise. Lower HEM frequencies penetrate deeper than the higher 

frequencies and have lower signal levels. The lowest frequency 

collected with the WEM system was 15 kHz (kilohertz), and 

data analysis showed it was less affected by the problems with 

signal saturation than higher frequencies. The grids of apparent resistivity, at 15 kHz collected on the lake, suggest a general 

trend of higher resistivity in the northern arm of the lake, and 

lower resistivity along the northern shore of the eastern arm 

of the lake (fig. 24, bottom panel). These trends are consistent 

with the apparent resistivity grid based on 25 kHz HEM data 

(fig. 24, grid below flight lines, shown in blue) collected previously with a different system. The inverted resistivity sections 

from both systems are also consistent with each other. This can 

be observed by comparing the two panels in figure 25, where the 

upper panel shows the inverted section of waterborne data, and 

the lower panel shows the inverted section based on HEM data. 

The dashed vertical lines show the extent of the overlapping segments. The location of the section is indicated in figure 24B as the 

short white-line segment. The WEM inverted resistivity values 

are consistent with in situ measured water resistivity of 29 Ω-m. 

The inverted section of HEM data (fig. 25, lower panel) also 

gives resistivity values in the range 22–30 Ω-m. An example of 

inverted waterborne data for a longer line is given in figure 24A.

The black line on the section traces the measured water depth.

Because the depth of investigation with the WEM is limited to about 15 m in fresh water, valid measurements of the 

underlying geology whose resistivity is above 20 Ω-m can be 

acquired only in nearshore shallow areas. With this in mind, 

WEM surveys need to be run with closely spaced parallel lines 

conforming to the shoreline. Although deep water, such as the 

central areas of the Lake of the Arbuckles, precludes adequate 

signal, data collected over deep water, though not indicative of 

underlying geology, are crucial to system calibration. Central 

areas of the lake were too deep for adequate signal with the 

existing WEM bird. A bird with an operating frequency lower 

than 15 kHz would penetrate greater water depths. Accurate bathymetry is important to limiting the uncertainties in 

resolving basement resistivity using layered-earth inversions. 

Knowledge of water resistivity is essential for the success of 

this method.

Collaborators

Chickasaw National Recreation Area, a unit of the National

 Park Service

Oklahoma Water Resources Board

Selected References

Deszcz-Pan, Maria, Smith, D.V., and Smith, B.D., 2011, 

Application of an airborne HEM system on a freshwater 

lake: Environmental and Engineering Geophysical Society 

(EEGS) Symposium on the Application of Geophysics to 

Engineering and Environmental Problems (SAGEEP) 2011 

Annual Meeting, Charleston, S.C., April 10–14, poster.

Smith, B.D., Smith, D.V., Deszcz-Pan, Maria, Blome, C.D., 

and Hill, Patricia, 2011, Helicopter electromagnetic and 

magnetic geophysical survey data, Hunton anticline, southcentral Oklahoma: U.S. Geological Survey Open-File 

Report 2011–1240, 15 p.

Figure 23. Waterborne electromagnetic system consisting of watercraft for towing and data acquisition (left) and the electromagnetic 

bird mounted on a pontoon raft (right). (USGS photograph)
46 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 24. Apparent resistivity 

data. A, Inverted waterborne data 

along the selected waterborne 

transect where measured 

water depth is traced by a thin 

black line. B, Map of apparent 

resistivity for both surveys at the 

lowest waterborne frequency of 

15 kHz (kilohertz) (over the lake 

area) and the closest 25 kHz 

frequency for airborne data (over 

land). The lines of helicopter 

electromagnetic data are shown 

in blue, waterborne lines are 

shown in green, with the selected 

waterborne transect shown in 

heavy black. The short white-line 

segment shows the waterborne 

transect overlapping the airborne 

line depicted in figure 25.

682,000 683,000

Easting, in meters

−2,000

−1,000

0

1,000

2,000

Distance from section, in meters

240

250

260

270

Elevation, in meters

A

B

10,000

10

15

17

22

29

50

150

Resistivity, in 

 ohm-meters

20

30

35

75

100

0.1

EXPLANATION

681,000 684,000

0 1,000 METERS

0 2,000 FEET
Instrument Development 47

280

240

250

260

270

Elevation, in meters

3,812,500 3,813,000

Northing, in meters

240

280

250

260

270

Elevation, in meters

Resistivity, in 

 ohm-meters

10,000

0.1

35

50

75

100

150

22

29

30

10

15

17

20

A EXPLANATION

B

0 500 METERS

0 1,000 FEET

Figure 25. Comparison of airborne helicopter electromagnetic data and waterborne electromagnetic 

data. The two panels show inverted sections from A, waterborne and B, airborne data with black 

dashed lines demarcating the extent of the overlapping line segment.
Minerals, Energy, and Climate

ore-forming solutions flow—of most hydrothermal mineral 

deposits. A fracture must be stressed, tectonically or hydraulically, to near its point of failure in order for it to conduct the 

volumes of fluids necessary to form a hydrothermal mineral 

deposit. Therefore, by geophysically mapping fault and fracture systems in the subsurface using gravity and magnetic data 

and identifying the nature of these systems by anchoring the 

geophysical data to structural geologic data derived from field 

studies in the same area as well as developing models derived 

from experimental and analytical studies, we can reconstruct 

the paleo-orientation of tectonic stresses and the systematics of 

faulting, and then obtain a predictive model of the most likely 

locations within the mapped fault systems for focused fluid 

flow to have occurred and, in some circumstances, provide a 

framework for understanding mineral zoning in a district.

Results

The Boulder batholith, Montana, hosts one of the world’s 

historically important copper resources in the Butte mining district and provides an opportunity to study the tectonic 

context of a batholith, the structural evolution of its component parts, and the relation of mineralization-controlling 

faults to this tectonic/structural story. Detailed geologic maps 

of the batholith allow its internal structural evolution to be 

interpreted, and the analysis of magnetic and gravity data 

allow the structural evolution of the batholith to be put into 

a tectonic context (see Berger and others, 2011). Figure 26 

shows the topography on the basal surface of Butte Quartz 

Monzonite intrusion, the largest single pluton and core of the 

batholith. The solid white line shows the geophysical outer 

margin of the whole batholith; the inner dashed white line is 

the outer boundary of Butte Quartz Monzonite. Butte Quartz 

Monzonite has a generally hour-glass shape and flat bottom at 

6–8 kilometer (km) depth. Two zones with calculated depths 

of 13–15 km are suggestive that Butte Quartz Monzonite was 

intruded through two separate zones at the base and forms 

two funnel-shaped masses that coalesced to give an apparent single intrusion in map view. This geometry is consistent 

with a model that Butte Quartz Monzonite was intruded into a 

structural pull-apart (for example, Schmidt and others, 1990) 

formed behind the advancing Montana Disturbed Belt thrust 

front. The axis of symmetry of this pull-apart is coincident 

with a zone of faulting trending northeast from Butte to the 

northeast margin of the batholith that has been interpreted 

(Schmidt and others, 1990) to be a deep-seated, Precambrian 

fault zone. The Butte mining district is localized within this 

axially symmetric fault zone and associated with the southern 

part of the inferred Butte Quartz Monzonite feeder zones.

The mineralized veins in the Butte district form overlapping sets of fanning or horsetailing faults (fig. 27) that step 

from northwest to southeast across the fault zone that makes 

up the axis of symmetry of the pull-apart structure within 

Integrated Structural Geologic and 

Potential-Field Geophysical Studies 

to Understand the Spatial Localization 

of Magmatic-Hydrothermal Mineral 

Deposits

By Byron R. Berger, Thomas G. Hildenbrand, and 

J. Michael O’Neill

Issue and Scope

Most of the mineral deposits that crop out on Earth’s 

surface have been explored, and the greatest potential for 

undiscovered deposits is in favorable rocks buried beneath 

cover materials. Predicting the locations of undiscovered, buried mineral deposits is a major source of uncertainty to geologists engaged in mineral-resource assessments and minerals 

exploration. To reduce the uncertainty and accurately predict 

covered deposit locations, it is necessary to better understand 

the phenomena important in the localization of mineralizing 

systems and the mechanisms that facilitate the formation of 

ore bodies within mineralizing systems. 

Objectives

To form an economic hydrothermal mineral deposit, 

it takes a large volume of hot fluid flowing at high rates 

that must be sustained for a significant length of time. This 

necessitates that connected fault and fracture permeability 

plays a dominating role in mineral deposit formation, and, 

consequently, there is a need to understand the permeability structure of mineral-deposit-forming environments and 

how they evolve in a dynamic setting. Our research has two 

primary objectives. Through the study of known mining 

districts and deposits, a first objective is to understand the 

permeability structure of connected fault and fracture systems 

at the mineral-district and ore-body scales. A second objective 

is to understand how the permeability structure changes in 

response to active seismicity and concurrent hydraulic stress. 

To achieve these objectives, we integrate structural geologic 

and magnetic and gravity geophysical data to construct 

models of known mineralized systems to use as analogs in the 

analysis of covered terrains.

Background

Interconnected networks of faults and fractures dominate 

the permeability structure—the channelways along which 
Minerals, Energy, and Climate 49

Figure 26. Calculated depths to the base of Butte Quartz Monzonite using a 3-D gravity inversion model. 

The model shows that Butte Quartz Monzonite forms an hour-glass shaped, flat slab that was likely derived 

principally from two feeder zones. The arrows indicate where the base of the batholith appears to pinch inward 

coincident with higher density batholithic rocks as indicated by magnetic data. The anomaly associated with 

the Deer Lodge Valley is a modeling edge effect. From Berger and others (2011).

−2.4

−1.2

 0.0

 1.2

 2.4

 3.6

 4.8

 6.0

 7.2

 8.4

 9.6

10.8

12.0

13.2

14.4

Feeder?

Denser granodiorite

at depth?

Feeder?

Butte

Deer Lodge Valley

Depth, in kilometers

112°40' 112°00'

46°00'

46°40'

EXPLANATION

N

0 10 20 KILOMETERS

0 10 20 MILES
50 Developing Integrated Methods to Address Complex Resource and Environmental Issues

which Butte Quartz Monzonite intruded. All of the faults are 

parallel to local, pre-existing joint trends in the Butte Quartz 

Monzonite and were likely guided by these joint weaknesses. 

The faults are interpreted to be sets of segmented, northeaststriking right-lateral “master” faults along which small splay 

or wing faults developed at the fault tips, again following antecedent fracture trends, on one or both sides of northeast fault 

segments and then propagated away from the tips to ultimately 

form the observed networks of northeast, east–west, and 

northwest striking faults. In figure 27, each interpreted fault 

set is color coded to aid differentiation. In figure 28, the faults 

are color coded to differentiate those veins that were silverrich versus copper-rich. From figure 28 it can be inferred that 

the first two fanning fault sets to the northwest (purple and 

blue in fig. 27) formed a linked-fluid upflow compartment that 

was physically separate and chemically different from the sets 

to the southeast. Intermingling of the two fluids from the two 

upflow zones occurred only in the northwest part of the district 

where silver- and copper-rich veins are known to mutually 

crosscut the other.

Conclusions

Integrating structural geologic data interpretations and 

state-of-the-art interpretative techniques of potential-field geophysical data provides insights as to how (1) pre-mineralization 

structures affect subsequent fault and fracture deformation 

events, (2) different processes couple to localize igneous intrusions, and (3) ore-localizing fault and fracture permeability 

develops, and the mechanisms through which deformation can 

lead to focused fluid flow. Studies in the Butte mining district 

show how integrated studies in batholithic terranes can reduce 

uncertainties in mineral-resource assessments and reduce risk 

in exploration activities in analogous terranes. Reduced risk 

comes from a better understanding of why mineral deposits are 

localized where they are in batholithic terranes, which, in turn, 

reduces the area of search.

Acknowledgments

Byron (Barney) Berger passed away on December 10, 

2013, after a long battle with cancer. During his 36 years at 

the U.S. Geological Survey, Barney became an internationally prominent economic geologist specializing in quantitative 

mineral resource assessments and ore genesis research. He 

authored or co-authored nearly 50 papers on the geology and 

geochemistry of ore deposits. He also served in a USGS leadership role as branch chief of the Exploration Geochemistry 

Branch and later of the Geochemistry Branch.

Related Project References

Berger, B.R., 2007, The 3D fault and vein architecture of 

strike-slip releasing and restraining bends–Evidence from 

volcanic-centre-related mineral deposits, in Cunningham, 

W.D., and Mann, P., eds., Tectonics of strike-slip restraining 

and releasing bends: Geological Society of London Special 

Publication 290, p. 447–471.

Berger, B.R., Anderson, R.E., Phillips, J.D., and Tingley, 

J.V., 2005, Plate-boundary transverse deformation zones 

and their structural roles in localizing mineralization in the 

Virginia City, Goldfield, and Silver Star mining districts, 

Nevada, in Rhoden, H.N., Steininger, R.C., and Vikre, P.G., 

eds., Geological Society of Nevada Symposium 2005—

Window to the world: Geological Society of Nevada, Reno, 

p. 269–281.

Berger, B.R., Tingley, J.V., and Drew, L.J., 2003, Structural 

localization and origin of compartmentalized fluid flow, 

Comstock Lode, Virginia City, Nevada: Economic Geology, 

v. 98, p. 387–408.

Blakely, R.J., John, D.A., Box, S.E., Berger, B.R., Fleck, R.J., 

Ashley, R.P., Newport, G.R., and Heinemeyer, G.R., 2007, 

Crustal controls on magmatic-hydrothermal systems—A 

geophysical comparison of White River, Washington, with 

Goldfield, Nevada: Geosphere, v. 3, p. 91–107.

Hildenbrand, T.G., Berger, B.R., Jachens, R.C., and Ludington, S.D., 2000, Regional crustal structures and their 

relation to the distribution of ore deposits in Western United 

States based on magnetic and gravity data: Economic Geology, v. 95, p. 1583–1603.

Hildenbrand, T.G., Berger, Byron, Jachens, R.C., and Ludington, Stephen, 2001, Utility of magnetic and gravity data in 

evaluating regional controls on mineralization—Examples 

from the Western United States: Society of Economic 

Geologists Reviews in Economic Geology, v. 14, p. 75–109.

References Cited

Berger, B.R., Hildenbrand, T.G., and O’Neill, J.M., 2011, 

Control of Precambrian basement deformation zones on 

emplacement of the Laramide Boulder batholith and Butte 

mining district, Montana, United States: U.S. Geological 

Survey Scientific Investigations Report 2011–5016, 29 p.

Schmidt, C.J., Smedes, H.W., and O’Neill, J.M., 1990, Syncompressional emplacement of the Boulder and Tobacco 

Root batholiths (Montana-USA) by pull-apart along old 

fault zones: Geological Journal, v. 25, p. 305–318.
Minerals, Energy, and Climate 51

Figure 27. Complex networks of linked, fanning, or horsetailing 

faults color coded to show how groups of faults may have 

grown as a set. The sets developed in a manner that eventually 

kinematically linked the northwesternmost northeast “master” 

(controlling) fault to the southeasternmost “master” fault. After 

Berger and others (2011).

Figure 28. Map of polymetallic quartz veins and faults in the Butte mining district. Those veins and associated faults that were 

predominantly mined for silver are color coded differently from those veins and faults predominantly mined for copper. From Berger and 

others (2011).

EXPLANATION

Arrows indicate sense of displacement on northeast-striking

 strike-slip faults.

N

MC

L2 K

A

S

Lx

Continental 

deposit

Berkeley

deposit

CONTINENTAL FAULT

0 500 METERS

0 2,000 FEET

L2

EXPLANATION

Copper-rich zone

Silver-rich zone

Northeast-striking veins and faults Fault, undivided

Mine shaft

Mine shaft name

General outline of porphyry-style deposit

East- to west–striking veins and faults

Northwest-striking veins and faults

Northeast-striking veins and faults

Northwest-striking veins and faults

Extensional stepover faults between the Berkeley

 and Continental porphyry-style deposits

MONTANA
52 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Geophysical Support for Global 

Mineral Resource Assessments

By Jeffrey D. Phillips and Byron R. Berger

Issue and Scope

Mineral resource assessments conducted by the U.S. 

Geological Survey (USGS) of areas within foreign countries 

often must rely on interpretative products such as published 

geologic maps and cross sections that may not conform to our 

current understanding of global tectonics. Geophysical data, 

such as regional or global aeromagnetic compilations, offer 

a synoptic view of the upper crust and provide an unbiased 

framework for comparative understanding of the regional 

tectonics, identification of tectonic boundaries, and subdivision of terranes into different domains based on geophysical attributes. One of the early steps in any mineral resource 

assessment involves identifying the boundaries of geologically 

permissive areas or “tracts” where a specific mineral deposit 

type might occur. Geophysically determined tectonic boundaries can help guide the establishment of tract boundaries 

where the basement geology is uncertain or is concealed under 

sedimentary, volcanic, or structural cover.

Objectives

The goal of this effort was to incorporate regional geophysical data, primarily crustal magnetic anomaly data, into 

global mineral resource assessments. The magnetic anomaly 

data were used to supplement available geologic maps and 

aid in the interpretation of major tectonic features such as 

magmatic arcs of various ages, the occurrence of favorable 

geologic units such as intrusive rocks, and the boundaries of 

intrusive complexes that constitute permissive terranes for 

specific types of mineral deposits.

Background

Due to contractual agreements and copyright restrictions, 

high-quality aeromagnetic data are rarely available at an affordable price for most foreign countries. Canada and Australia 

are two exceptions. Compiled aeromagnetic grids are available for some countries such as Mexico and the former Soviet 

Union (U.S.S.R.). A global magnetic anomaly grid at a 2-arc 

minute (3.7 kilometer [km] or better) resolution compiled from 

aeromagnetic, shipborne magnetic, and satellite magnetic data 

is available from the National Oceanographic and Atmospheric 

Administration (NOAA) (Maus and others, 2009).

During a recent USGS global assessment of porphyry 

copper resources, magnetic anomaly data from the global grid 

and from the former U.S.S.R. grid were used to support tectonic interpretations in several areas including Europe, eastern 

Europe, Mongolia, eastern Russia, Iran, the southern Urals, 

and Central Asia. Here we illustrate the use of these geophysical data through an example from the western Central Asia 

assessment (Berger and others, 2014).

Results and Conclusions

An aeromagnetic dataset for the former U.S.S.R is available 

in digital form on CD-ROM from the NOAA National Geophysical Data Center (NGDC, 1997). At the highest resolution, these 

data were sampled in a 2,500-meter grid in order to be useful for 

examining the longer wavelength components of the aeromagnetic field. These data were used to produce a grid of long-wavelength aeromagnetic anomalies for the Central Asia study area.

The aeromagnetic grid was reduced to the pole using 

proprietary software. Reduction-to-the pole (RTP) is a filtering 

process that removes the effect of geomagnetic latitude and 

repositions magnetic anomalies directly over their sources 

(Blakely, 1995). As a first step toward interpretation, the horizontal gradient magnitude of the RTP aeromagnetic grid was 

calculated, and the lines of maximum horizontal gradient were 

extracted. These lines define potential locations of vertical 

(steeply dipping) magnetic contacts within the crust (Cordell 

and Grauch, 1985; Blakely and Simpson, 1986; Grauch and 

Cordell, 1987). The lines were superimposed on the RTP 

aeromagnetic map to aid in geologic interpretation and the 

selection of tract boundaries (fig. 29).

These geophysical boundaries were used for defining 

tract boundaries in areas where no clear boundaries could be 

determined from the mapped geology (see heavy white and 

dashed black lines in fig. 29). The ability to draw these boundaries in covered or poorly mapped areas reduced the overall 

level of uncertainty in the assessment.

Collaborators

Jane M. Hammarstrom and Michael L. Zientek, Project Chiefs,

 USGS Global Mineral Resource Assessment Project

References Cited

Berger, B.R., Mars, J.C., Denning, P.D., Phillips, J.D., Hammarstrom, J.M., Zientek, M.L, Dicken, C.L., and Drew, 

L.J., with contributions from Alexeiev, Dmitriy, Seltmann, 

Reimar, and Herrington, R.J., 2014, Porphyry copper assessment of western Central Asia: U.S. Geological Survey Scientific Investigations Report 2010–5090–N, 219 p., 8 plates, 

and spatial data, http://dx.doi.org/10.3133/sir20105090N.

Blakely, R.J., 1995, Potential theory in gravity and magnetic 

applications: Cambridge, United Kingdom, Cambridge 

University Press, 441 p.

Blakely, R.J., and Simpson, R.W., 1986, Approximating edges 

of source bodies from magnetic or gravity anomalies: Geophysics, v. 51, no. 7, p. 1494–1498.
Minerals, Energy, and Climate 53

Figure 29. Generalized tectonic 

map (after Chitalin, 1996) of 

the Spasski fold belt in Central 

Asia, plotted on top of a color 

shaded-relief, reduced-to-pole 

aeromagnetic map. Red colors 

indicate magnetic highs; blue 

colors indicate magnetic lows. 

Thin white lines give locations 

of the maximum horizontal 

gradients of the reduced-topole magnetic field; these may 

correspond to steeply dipping 

magnetic contacts representing 

crustal boundaries. The fold 

belt separates the ZharmanSarysu (ZS) accreted terrane of 

Windley and others (2007) from 

the northern part of the Devonian 

magmatic arc (D) that overlaps 

the Zharman-Sarysu terrane 

on its east and west margins. 

Also shown is the Carboniferous 

Balkhash-Ili magmatic arc (BI). 

Faults, shown in light-gray lines, 

are from Seltmann and others 

(2009). The map area is north 

and northwest of Lake Balkhash, 

north-central Kazakhstan. The 

latitude, longitude, and location 

of the city of Karaganda were 

approximated using Google Earth. 

Chitalin, A.F., 1996, Variscan structural evolution of central 

Kazakhstan, in Shatov, V., Seltmann, R. Kremenetsky, A., 

Lehmann, B., Popov, V., and Ermolov, P., eds., Graniterelated ore deposits of central Kazakhstan and adjacent areas: 

St. Petersburg, GLAGOL Publishing House, p. 93–102.

Cordell, Lindrith, and Grauch, V.J.S., 1985, Mapping basement magnetization zones from aeromagnetic data in the 

San Juan Basin, New Mexico, in Hinze, W.J., ed., The utility of regional gravity and magnetic anomaly maps: Society 

of Exploration Geophysicists, p. 181–197.

Grauch, V.J.S., and Cordell, Lindrith, 1987, Limitations on 

determining density or magnetic boundaries from the horizontal gradient of gravity or pseudogravity data: Geophysics, v. 52, no. 1, p. 118–121.

Maus, S, Barckhausen, U., Berkenbosch, H., Bournas, N., 

Brozena, J., Childers, V., Dostaler, F., Fairhead, J.D., Finn, 

C., von Frese, R.R.B., Gaina, C., Golynsky, S., Kucks, R., 

Lühr, H., Milligan, P., Mogren, S., Müller, R.D., Olesen, O., 

 Pilkington, M., Saltus, R., Schreckenberger, B., Thébault, 

E., and Caratori Tontini, F., 2009, EMAG2—A 2-arc min 

resolution Earth magnetic anomaly grid compiled from 

satellite, airborne, and marine magnetic measurements: 

Geochemistry, Geophysics, Geosystems, v. 10, Q08005, 

doi:10.1029/2009GC002471, 12 p.

National Geophysical Data Center (NGDC), 1997, Magnetic 

anomaly data of the former Soviet Union: National Oceanographic and Atmospheric Administration, National Geophysical Data Center CD-ROM, unpaginated.

Seltmann, R., Shatov, V., and Yakubchuk, A., 2009, Mineral deposits database and thematic maps of Central Asia, 

explanatory notes: London, Natural History Museum, Center for Russian and Central Asian Mineral Studies, 174 p.

Windley, B.F., Alexeiev, Dmitriy, Xiao, Wenjiao, Kröner, 

Alfred, and Badarch, Gombosuren, 2007, Tectonic models 

for accretion of the Central Asian orogenic belt: Journal of 

the Geological Society of London, v. 164, p. 31–47.

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Karaganda

50°

48°

71° 73° 75° 77°

D

D

BI

ZS

ZS

EXPLANATION

Outer boundary of Carboniferous

 magmatic-arc rocks 

Outer boundary of

 Devonian magmatic-arc rocks 

High-angle faults,

 undifferentiated

Previously mapped faults

 (Seltmann and others, 2009)

Low

High

Magnetic field

Maximum

 horizontal

 gradient

0 50 100 KILOMETERS

Middle Carboniferous 0 25 50 MILES

 thrust faults 

Late Carboniferous to

 Permian thrust faults 
54 Developing Integrated Methods to Address Complex Resource and Environmental Issues

U.S. Geological Survey Cooperative 

Research on Carbon Dioxide 

Sequestration Using Ultramafic and 

Carbonate Rocks

By Anne E. McCafferty, William H. Langer, and 

Bradley S. Van Gosen

Issue and Scope

Over geologic time, the natural weathering of carbonate 

and ultramafic rocks at and near the Earth’s surface captures 

and sequesters atmospheric carbon dioxide (CO2). Reducing 

CO2 in the atmosphere that is emitted from fossil-fuel-fired 

power plants will require a range of carbon management and 

sequestration options. Two emerging carbon storage methods 

that attempt to speed up the natural weathering processes are 

mineral CO2

 sequestration (also known as mineral carbonation) 

and accelerated weathering of limestone (AWL). One responsibility of the U.S. Geological Survey (USGS) is to provide 

critical geologic information at a national scale to underpin the 

chemical and industrial research and development of mineral 

resources. In the case of ultramafic rocks, the USGS also 

provides information on how geophysical data can be used to 

extend and refine the geologic mapping of ultramafic rocks. 

Objectives

One of the first tasks to address the viability of both 

these approaches is to estimate the available mineral 

resources. For this initial estimation, the USGS produced 

national-scale geologic maps that show calcium-rich limestone and magnesium-rich ultramafic rocks (fig. 30). These 

maps were produced in cooperation with researchers from 

the Earth Institute at Columbia University (http://www.

energy.columbia.edu/), the University of California, Santa 

Cruz (http://ims.ucsc.edu/facres/index.html), and the Carnegie Institution for Science (http://dge.stanford.edu/labs/

caldeiralab). These national-scale maps detail the geographical distribution and extent of rocks suitable for use in accelerated weathering of limestone (fig. 30A) and mineral CO2

sequestration with ultramafic rocks (fig. 30B), respectively.

Background

Accelerated Weathering of Limestone

Accelerated weathering of limestone is proposed as a 

low-tech method to capture and sequester CO2 that is expelled 

from fossil-fuel-fired power plants and other point-sources, 

such as cement manufacturing plants. AWL combines captured 

CO2 with water and calcium carbonate to produce water that 

is rich in bicarbonate ions. This slurry can be released in the 

ocean with little or no apparent negative environmental impact 

(Caldeira and Rau, 2000). Rocks rich in calcium carbonate, 

particularly limestone, are ideally suited for this process. The 

large amounts of pulverized limestone (“fines”) produced during the processing of crushed limestone may be useful in this 

method of CO2

 sequestration, providing finely ground calcium 

carbonate for use in the slurry mixture. 

Mineral Carbonation Using Ultramafic Rocks

Mineral storage of CO2 occurs in nature through chemical 

reactions during the weathering of ultramafic rocks. When it 

rains, the rainwater mixes with CO2 in the atmosphere to form 

a weak carbonic acid. The carbonic acid reacts with magnesium-silicate minerals—which are abundant in ultramafic 

rocks—to form a solid magnesium-carbonate rock called 

magnesite (MgCO3). In this manner, CO2 gas is permanently 

“locked up” in the magnesite as a solid. 

Rates of natural mineral carbon sequestration vary with 

geologic conditions but typically occur too slowly to make 

it an effective immediate means to sequester carbon dioxide 

from industrial sources. Hence, research organizations are 

exploring ways to chemically, thermally, or mechanically 

accelerate and enhance the natural process through an industrial process that is timely and economically viable (Matter 

and Kelemen, 2009; Zevenhoven, 2010). Advantages to this 

type of sequestration is that magnesite is a stable mineral at 

the Earth’s surface, it has no legacy issues (such as acid drainage), and would require no monitoring after disposal, because 

magnesite remains environmentally benign over geologic time 

scales. Additionally, large amounts of waste rock generated 

from the past mining of asbestos in ultramafic rocks could be 

considered as source material for the mineral carbonation process. Asbestos minerals are very reactive and as such are some 

of the first minerals to dissolve in the mineral carbonation 

process, thereby providing a means to simultaneously mitigate 

both a climate and human health hazard.

Results and Conclusions

A feasibility study conducted by the USGS for carbon 

sequestration through an accelerated weathering of limestone 

operation requires access to an inexpensive source of limestone and to seawater; these parameters limit AWL facilities to 

within about 10 kilometers (km) of the coastline (fig. 30A). The 

majority of U.S. power-generating facilities in coastal areas are 

within economical transport distance of limestone resources 

(Langer and others, 2009). AWL presents opportunities for collaborative efforts between the crushed stone industry, electrical 

utilities, cement manufactures, and research scientists.

The USGS, in cooperation with the Earth Institute at 

Columbia University, released a national-scale map of magnesium-rich ultramafic rocks for mineral CO2

 sequestration in 

both report and digital map form (Krevor and others, 2009). The 

report identifies the largest known sources of ultramafic bedrocks 
Minerals, Energy, and Climate 55

Figure 30. National-scale maps of A, carbonate rocks and B, magnesium-rich ultramafic 

rocks (in red) thought suitable for carbon dioxide sequestration in the conterminous United 

States. Circles on A show locations of power plants along coastal areas; colors indicate 

distance from power plants to carbonate rock. Modified from Krevor and others (2009). km, 

kilometers; Mg, magnesium.

in the continental United States (fig. 30B). In total, the map 

shows 16,263 km2 of ultramafic rocks, an area roughly equivalent 

to the State of Hawaii including all its islands. Scientists from 

Columbia University estimate this is enough material to sequester 500 years of carbon dioxide at 2009 levels of emissions.

In addition, the USGS extended the geologic mapping of 

the ultramafic rocks to include geophysical methods to map the 

volume, area, and depth of ultramafic rock masses (McCafferty 

and others, 2009). Ultramafic rocks contain magnetic minerals that make them ideal targets for aeromagnetic surveying. 

Mathematical enhancements can be applied to magnetic survey 

data to enhance anomalies that occur over ultramafic rocks 

(fig. 31). These enhancements allow for detailed examination 

of ultramafic rocks that may be completely or shallowly buried, 

which allows for a more robust assessment and characterization 

of rock material available for mineral carbonation.

AA BB

B

1 km

2 to 10 km

11 to 50 km

51 to 100 km

101 to 200 km

201 to 300 km

301 to 400 km

Distance from power

plants to limestone

EXPLANATION

Limestone

Mg-rich ultramafic rock

EXPLANATION
56 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Collaborators

Sam Krevor, Stanford University Global Climate & Energy 

 Project, Stanford University, California 

Gregory Rau, Research Marine Scientist, Institute of Marine 

 Sciences, University of California, Santa Cruz 

Ken Caldeira, Senior Scientist, Department of Global Ecology,

 Stanford University

For Additional Information

U.S. Geological Survey data and studies related to this 

topic can be found at http://crustal.usgs.gov/projects/CO2_

sequestration/index.html.

References Cited

Caldeira, Ken, and Rau, G.H., 2000, Accelerating carbonate 

dissolution to sequester carbon dioxide in the ocean, geochemical implications: Geophysical Research Letters, v. 27, 

p. 225–228.

Krevor, S.C., Graves, C.R., Van Gosen, B.S., and McCafferty, 

A.E., 2009, Mapping the mineral resource base for mineral 

carbon-dioxide sequestration in the conterminous United 

States: U.S. Geological Survey Digital Data Series 414, 

14 p., 1 plate, http://pubs.usgs.gov/ds/414.

Langer, W.H., San Juan, C.A., Rau, G.H., and Caleira, Ken, 

2009, Accelerated weathering of limestone for CO2

 mitigation—Opportunities for the stone and cement industries: 

Mining Engineering Magazine, February 2009, p. 27–32, 

http://crustal.usgs.gov/projects/CO2_sequestration/AWL_

Feb09_ME_508.pdf [article provided courtesy of Society 

for Mining, Metallurgy & Exploration].

Matter, J.M., and Kelemen, P.B., 2009, Permanent storage of 

carbon dioxide in geological reservoirs by mineral carbonation: Nature Geoscience, v. 2, p. 837–841.

McCafferty, A.E., Van Gosen, B.S., Krevor, S.C., and Graves, 

C.R., 2009, Geophysical delineation of Mg-rich ultramafic 

rocks for mineral carbon sequestration: U.S. Geological 

Survey Open-File Report 2009–1127, 24 p., http://pubs.

usgs.gov/of/2009/1127/.

Zevenhoven, Ron, 2010, Proceedings from the Third International Conference on Accelerated Carbonation for 

Environmental and Materials Engineering, ACEME10: 

Turku, Finland, ACEME, November 29–December 1, 2010, 

348 p., available at http://web.abo.fi/fak/tkf/vt/aceme10/

conferencematerial.html.

Figure 31. Examples of enhancements applied to magnetic survey data. A, Airborne magnetic anomaly caused by exposed and buried 

ultramafic rock. B, Interpretive “terrace” filter applied to magnetic data to enhance the edges of the buried rock. C, Estimation of 

geometry and area of exposed and buried ultramafic rock available for mineral carbon dioxide sequestration.

2

km

A B C

0 1 KILOMETERS

0 1 MILES

0 1 KILOMETERS

0 1 MILES

0 1 KILOMETERS

0 1 MILES

exposed

ultramafic

rock
Minerals, Energy, and Climate 57

Three-Dimensional Magnetic Property 

Model Characterizing the Mesozoic 

Section of the Cook Inlet Basin,

South-Central Alaska

By Jeffrey D. Phillips and Richard G. Stanley

Issue and Scope

The Cook Inlet Basin of south-central Alaska is the 

principal source of natural gas used for heating and electric 

power generation in the Anchorage metropolitan area. Oil is 

also produced in the basin. In preparation for a new oil and 

gas resource assessment of the Cook Inlet Basin (Stanley and 

others, 2011), the U.S. Geological Survey (USGS) reanalyzed 

commercially available, medium- to high-resolution aeromagnetic data over the basin using separation filtering and 

experimental inversion software.

Although the Tertiary sedimentary section of the basin, 

which contains the principal hydrocarbon reservoirs, is well 

understood from drilling and seismic reflection profiles, 

relatively little is known about the deeper Mesozoic sedimentary section, which contains both potential hydrocarbon 

reservoir rocks and the principal oil source rocks. In particular, the thickness of the Mesozoic sedimentary rocks is poorly 

known; only five wells penetrate both the top and bottom of 

this section.

Objectives

This study was designed to use the aeromagnetic data to 

estimate the thickness and magnetic properties of the Mesozoic sedimentary section in the Cook Inlet Basin. In addition 

to the merged aeromagnetic data grid, which was assembled 

from two commercial surveys and the USGS Anchorage 

survey, the available data included a surface at the base of 

the Tertiary section provided by the State of Alaska (Schellenbaum and others, 2010) and the well database for the 

Cook Inlet.

Background

The aeromagnetic data clearly show strong magnetic 

anomalies related to structures within the Tertiary sedimentary section of the basin and strong anomalies produced by 

basement rocks outside of the basin (Saltus and others, 2001). 

The first step involved using separation filtering to remove the 

magnetic anomalies produced within the Tertiary sedimentary 

section from the gridded aeromagnetic data. This was accomplished by constructing an equivalent-source model using 

vertical rectangular prisms having tops at the base-Tertiary 

surface and flat bottom at 30-kilometer depth. Iterative 

inversion was used to find the magnetization of the prisms 

that produced the best fit to the aeromagnetic data. Magnetic 

anomalies that could not be fit by the equivalent prism sources 

were considered to be due to sources within the Tertiary sedimentary section; these were discarded.

The second step involved using two-dimensional 

(2-D) physical-property inversion (Pilkington, 1997, 2009) 

along rows and columns of the filtered aeromagnetic grid to 

estimate the magnetization of the pre-Tertiary sedimentary 

and basement rocks. The 2-D inversions were combined into 

a 3-D model of the row solutions and a 3-D model of the 

column solutions. By choosing the magnetization in each 

cell that had the largest magnitude, the two 3-D models were 

combined into a single 3-D magnetization model. This final 

3-D model was sampled at the locations of wells within the 

basin to establish a statistical relation between magnetization 

values and lithostratigraphy (table 2). This relation was used 

to construct a color scale emphasizing lithologic boundaries 

within the magnetization model (fig. 32).

Results and Conclusions

Magnetic inversion proved to be an effective way of 

estimating the thickness of the Mesozoic sedimentary section 

within the Cook Inlet Basin and thus the potential distribution of 

oil source rocks. The magnetic properties of this section and the 

underlying basement were also estimated. Viewing the magnetic 

properties at the top of the Mesozoic section helps reveal the 

structures that immediately underlie the Tertiary section and 

control the oil migration into the Tertiary structural traps.

Table 2. Statistics of sampled magnetizations (A/m) at well locations. 

[Magnetizations are in amperes per meter (A/m). Jmin is the minimum value sampled; Jmax is the maximum value sampled; Jmean is the mean value; Jsd is 

the standard deviation; Jlower (Jmean minus Jsd) is the chosen magnetization for the lower color boundary of the unit; Jupper (Jmean plus Jsd) is the chosen 

magnetization for the upper color boundary of the unit]

Geology Number of 

samples Jmin Jmax Jmean Jsd Jlower Jupper

Tertiary sedimentary rocks 2,393 –0.92 0.42 –0.02 0.08 –0.10 0.06

Mesozoic sedimentary rocks 158 –0.99 0.32 –0.01 0.17 –0.18 0.16

Basement rocks 28 –0.97 0.62 0.02 0.30 –0.28 0.32
−0.28−0.18−0.10

0.060.160.32

Magnetization, in 

ampere per meter

Basement rocksMesozoic sedimentary rocksTertiary (not shown) and Mesozoic sedimentary rocksMesozoic sedimentary rocksBasement rocks

EXPLANATION

Interpretive description

N

Figure 32. Three-dimensional magnetization model for the Cook Inlet, Alaska, colored to emphasize lithostratigraphic boundaries. The view is to the nunits have been stripped off to reveal the units at the top of the Mesozoic section. Blue lines indicate the coastline and lakes.
Minerals, Energy, and Climate 59

Without the results of this study, the oil and gas resource 

assessment of the Cook Inlet Basin would have been conducted without any knowledge of the volume of material 

contained in the critically important Mesozoic sedimentary 

section. This would have greatly increased the level of uncertainty in the assessment results.

Collaborators

Mark Pilkington, Geological Survey of Canada

Diane Schellenbaum, Alaska Division of Oil and Gas

Selected References

Phillips, J.D., 2011, 3D magnetic property models from 2D 

inversions [abs.]: XXV International Union of Geodesy 

and Geophysics General Assembly, Melbourne, Australia, 

July 5, 2011.

Phillips, J.D., and Stanley, R.G., 2011, A 3D magnetic property model of the Cook Inlet Basin, south-central Alaska—

Imaging Tertiary structural traps and Mesozoic sedimentary 

thickness [abs.]: American Association of Petroleum Geologists Pacific Section, Anchorage, Alaska, May 9, 2011.

Pilkington, Mark, 1997, 3-D magnetic imaging using conjugate gradients: Geophysics, v. 62, p. 1132–1142.

Pilkington, Mark, 2009, 3D magnetic data-space inversion 

with sparseness constraints: Geophysics, v. 74, p. L7–L15.

Saltus, R.W., Haeussler, P.J., Bracken, R.E., Doucette, J.P., and 

Jachens, R.C., 2001, Anchorage urban region aeromagnetics (AURA) project—Preliminary geophysical results: U.S. 

Geological Survey Open-File Report 01–0085. http://pubs.

usgs.gov/of/2001/ofr-01-0085/.

Shellenbaum, D.P., Gregersen, L.S., and Delaney, P.R., 2010, 

Top Mesozoic unconformity depth map of the Cook Inlet 

Basin, Alaska: Alaska Division of Geological & Geophysical Surveys Report of Investigation 2010-2, 1 sheet, 

scale 1:500,000.

Stanley, R.G., Charpentier, R.R., Cook, T.A., Houseknecht, 

D.W., Klett, T.R., Lewis, K.A., Lillis, P.G., Nelson, P.H., 

Phillips, J.D., Pollastro, R.M., Potter, C.J., Rouse, W.A., 

Saltus, R.W., Schenk, C.J., Shah, A.K., and Valin, Z.C., 

2011, Assessment of undiscovered oil and gas resources 

of the Cook Inlet region, south-central Alaska, 2011: U.S. 

Geological Survey Fact Sheet 2011–3068, 2 p.

Integrated Research on 

Hydrogeological and Geochemical 

Processes in a Mineralized Alpine 

Watershed—Handcart Gulch, Colorado

By Jonathan Saul Caine, Andrew H. Manning, 

Philip L. Verplanck, and Dana J. Bove

Issue and Scope

Precipitation increases dramatically with elevation in 

arid and semiarid regions, such that mountain headwaters 

are primary sources of water for downstream ecosystem and 

human use. Yet, fundamental controls on the amount and 

quality of mountain-sourced water are poorly understood, 

primarily because few monitoring sites are located in the 

mountains and fewer have dedicated groundwater monitoring 

wells (for example, Lins and others, 2010). Handcart Gulch 

(fig. 33) is an alpine watershed in the Rocky Mountains of 

central Colorado representative of many headwater regions. 

Importantly, the watershed contains (1) an unmined zone of 

metallic minerals that naturally produces water more acidic 

than vinegar and with elevated concentrations of heavy metals 

(natural acid-rock drainage) and (2) an instrumented network 

of groundwater monitoring wells. Handcart Gulch provides a 

unique opportunity to evaluate the hydrogeochemical processes controlling water quality and quantity in a hydrothermally mineralized, headwater region.

Objectives

The overall objective of this work is to understand both 

hydrogeological processes controlling water availability in 

mountainous regions and geochemical processes controlling 

water quality in mineralized areas. To meet this objective, 

a watershed approach has been adopted (fig. 34). Data are 

collected to understand and quantify the major processes 

controlling the movement of water and chemical constituents 

dissolved within it (dissolved mass) into, through, and out 

of the entire watershed. A “budget” for water and dissolved 

mass is developed that accounts for the primary controlling 

factors and processes such that total input minus total output 

equals zero. Ultimately, all knowledge of the watershed 

system is integrated into comprehensive conceptual and 

mathematical (computer) models that can be used to address 

challenging yet fundamental questions related to water 

resources and ecosystem management. For example, over 

the last 30 years, large increases in sulfate and zinc have 

been measured in a watershed adjacent to Handcart Gulch 

and attributed to climate change (Todd and others, 2012). 

Hydrologic and geochemical models from Handcart Gulch 

indicate that a likely cause of the observed degradation in 
60 Developing Integrated Methods to Address Complex Resource and Environmental Issues

water quality is a climate-driven decrease in recharge and 

subsequent lowering of the water table in the crystalline 

bedrock aquifer (Manning and Caine, 2007; Manning and 

others, 2012). Knowledge of mechanisms linking climate 

and surface-water quality gained through research at Handcart Gulch thus may be used to guide potential revisions to 

water-quality standards and remediation efforts at active and 

abandoned mine sites in mountainous regions.

Handcart Gulch serves as a rare analog of premining conditions in watersheds where mining of metallic minerals has 

enhanced natural acid-rock drainage and substantially deteriorated water quality. An improved understanding of the causes 

of natural acid-rock drainage at Handcart Gulch should allow 

for better separation of pre-mining background versus miningrelated contributions to poor water quality at similar mine sites 

common in the Western United States.

Background

Four deep mineral exploration boreholes were drilled to a 

maximum depth of 3,500 feet in 2001 (one at the Continental 

Divide at 12,100 feet above sea level) and were subsequently 

donated to the U.S. Geological Survey (USGS) for research 

purposes. The USGS drilled nine additional shallow holes, 10 

to 170 feet deep, and all the holes were converted to monitoring 

wells. Extensive geologic and geophysical site characterization was performed from 2002 to 2004, instrumented recording 

began in 2005, and regular sampling of surface and groundwater geochemistry has been ongoing. Currently, the monitoring 

network includes two meteorological stations, four wells with 

sensors that continuously monitor groundwater levels and 

water temperature, a streamgage to monitor surface-water flow, 

and an automatic water sampler to periodically collect stream 

Figure 33. Handcart Gulch in central Colorado. A, Location of Handcart Gulch with major physiographic province boundaries and 

the location of the study area within the Colorado Mineral Belt (modified from Tweto and Sims, 1963). B, Aerial photograph draped on 

a 10-meter (33-foot) digital elevation model and tilted showing the study area watershed topography with no vertical exaggeration 

(modified from Google Earth). The image shows the extreme topographic relief (over 2,600 feet with a gradient of ≈0.1) and the redorange weathering of the unmined pyrite-rich geologic units at the head of the watershed. C, Geologic map showing major geological 

structures and hydrothermal alteration zones and thus potential sources of heavy metal contaminants.

A

C

Webster Pass

12,100 feet

B

Webster Pass

12,100 feet

Handcart Gulch

N

0 0.5 1 KILOMETERS

0 0.5 1 MILES

Shallow borehole

Deep borehole

Study area boundary

EXPLANATION

Digital elevation model

Quartz, sericite, pyrite alteration

Chlorite, epidote, calcite alteration

Fault

Metallic vein

Dike

109° COLORADO

41°

COLORADO

MINERAL

BELT

Vail Denver

Mountains

Southern

Rocky

Great Plains

Colorado

Plateau

Location of Handcart

Gulch Research

Watershed (A and C)
Minerals, Energy, and Climate 61

water for chemical analysis. Results have been previously published in Caine and others (2006), Manning and Caine (2007), 

Kahn and others (2008), Verplanck (2008), Verplanck and others (2008, 2009), and Bove and others (2012).

Results, Conclusions, and Ongoing Work

We have characterized the geology of Handcart Gulch 

through innovative mapping, collection of rock geochemical 

and mineralogical data from surface outcrops and drill cores, 

and direct geophysical imaging of the borehole walls. These 

data help to characterize the three-dimensional distribution of 

different types of rocks and minerals in the subsurface, including minerals that potentially serve as sources of acid-rock 

drainage, and information on fractures and faults that control 

groundwater flow. Water-table elevations and their seasonal 

variations, aquifer test results, subsurface thermal data, and 

aqueous geochemical and isotopic data (including dissolved 

gas measurements and groundwater ages) have provided an 

understanding of aquifer characteristics and hydrological 

dynamics in the watershed (Manning and Caine, 2007). This 

understanding of the groundwater system was combined with 

meteorological data and streamflow measurements to develop 

a preliminary water budget for the watershed that includes 

estimates of total precipitation, potential evapotranspiration, 

streamflow, and groundwater outflow below the stream (Kahn 

and others, 2008). Two different computer models simulate 

groundwater flow and thermal processes in the watershed and 

serve to integrate our current knowledge of the system (Manning and others, 2004; Kahn and others, 2008).

Ongoing work at Handcart Gulch includes refinement of 

our conceptual model of acid-rock drainage and its causes as 

well as development of new computer models that simulate 

geochemical processes. Preliminary geochemical modeling has 

led us to hypothesize that the flow of oxygen from the atmosphere into the subsurface is of primary importance in controlling acid-rock drainage. Recently developed high-technology 

sensors have been deployed for a variety of novel measurements of dissolved oxygen in subsurface air and groundwater 

to test this hypothesis. Ongoing work also includes continued 

monitoring of meteorological, hydrological, and geochemical 

conditions to build a continuous, long-term record. This record 

is being used to identify changes in water quantity and quality through time and understand processes that control these 

changes in alpine watersheds. In particular, this record will 

allow us to evaluate climate variability and potential relations 

among climate, water quantity, and quality.

Collaborators

This research is funded by the U.S. Geological Survey 

Mineral Resources and Mendenhall Postdoctoral Fellowship 

Programs. The work is done in cooperation with the U.S. Forest Service, the Colorado Geological Survey, and the University of Colorado, Boulder.

References Cited

Bove, D.J., Caine, J.S., and Lowers, H.A., 2012, Geologic and 

mineralogic controls on acid and metal-rich rock drainage in an 

alpine watershed, Handcart Gulch, Colorado: U.S. Geological 

Survey Scientific Investigations Report 2012–5067, 121 p.

Caine, J.S., Manning, A.H., Verplanck, P.L, Bove, D.J., Kahn, 

K.G., and Ge, Shemin, 2006, Well construction information, 

lithologic logs, water level data, and overview of research in 

Handcart Gulch, Colorado—An alpine watershed affected 

by metalliferous hydrothermal alteration: U.S. Geological 

Survey Open-File Report 2006–1189, 14 p., http://pubs.

usgs.gov/of/2006/1189/.

Kahn, K.G., Ge, Shemin, Caine, J.S., and Manning, A.H., 

2008, Characterization of the shallow groundwater system 

in an alpine watershed—Handcart Gulch, Colorado, USA: 

Hydrogeology Journal, v. 16, p. 103–121.

Lins, H.F., Hirsch, R.M., and Kiang, Julie, 2010, Water—The 

Nation’s fundamental climate issue—A white paper on the 

U.S. Geological Survey role and capabilities: U.S. Geological Survey Circular 1347, 9 p., http://pubs.usgs.gov/

circ/1347.

Manning, A.H., and Caine, J.S., 2007, Groundwater noble 

gas, age, and temperature signatures in an alpine watershed—Valuable tools in conceptual model development: Water Resources Research, v. 43, W04404, DOI: 

10.1029/2006WR005349, 16 p.

Manning, A.H., Caine, J.S., Verplanck, P.L., Bove, D.J., and 

Landis, G.P., 2004, Insights into groundwater flow in an 

alpine watershed provided by a coupled heat, mass, and 

fluid transport model, Handcart Gulch, Colorado [abs.]: 

Geological Society of America Abstracts with Programs, 

v. 36, p. 539.

Manning, A.H., Todd, A.S., Verplanck, P.L., and Caine, J.S., 

2012, Possible links between climate change and deteriorating water quality in a mineralized watershed [abs.]: Geological Society of America Abstracts with Programs, v. 44, 

no. 7, p. 340.

Todd, A.S., Manning, A.H., Verplanck, P.L., Crouch, Caitlin, 

McKnight, D.M., and Dunham, Ryan, 2012, Climatechange-driven deterioration of water quality in a mineralized watershed: Environmental Science and Technology, 

v. 46, no. 17, p. 9324–9332.

Tweto, Ogden, and Sims, P.K., 1963, Precambrian ancestry of 

the Colorado Mineral Belt: Geological Society of America 

Bulletin, v. 74, p. 991–1014.

Verplanck, P.L., ed., 2008, Understanding contaminants 

associated with mineral deposits: U.S. Geological Survey 

Circular 1328, 96 p.
62 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Precipitation Evapotranspiration

WATERSHED

DIVIDE

Recharge

Shallow 

flow

Baseflow

Regional

flow

BEDROCK

AQUIFER

Total

stream

flow

Water

table

Aquifer

permeability (k)

k1

 > k2

k2

k1

C D

A B

Figure 34. Watershed approach is used to understand the processes controlling water availability and water quality. A, Using a watershed 

approach (mass input – mass output = 0), water, and potential contaminants in it, can be tracked and accounted for as it moves from 

headwater to lowland regions, where ultimately it is used for domestic and industrial purposes. The fundamental source of water is 

precipitation, in mountainous regions usually in the form of snow. B, Meteorological stations provide measurements of annual precipitation 

and other data used to monitor longer term climate variability. Wind speed and duration, humidity, solar insolation, and ground temperatures 

are also measured and provide data used to estimate evapotranspiration—a critical and difficult parameter to measure. C and D, A network 

of deep and shallow wells is instrumented with water-level and temperature sensors providing hourly hydraulic-head data and its response 

to variations in recharge. E and F, Geological mapping and characterization of faults and fractures at the surface and in the subsurface using, 

G and H, borehole geophysical logging are critical to understanding the physical vessel in which groundwater flows. I, The composition of 

different rock types and how they are altered by hydrothermal fluids imparting potential contaminants such as heavy metals is determined 
Minerals, Energy, and Climate 63

E F

G

H

by mineralogical and elemental chemical analyses of drill core samples. J, Hydraulic aquifer tests are used to determine the permeability and 

storage capacity of bedrock aquifers, which tends to decrease with depth. K, Age and chemistry of groundwater are measured annually in the 

monitoring well network. L, Stream flow, also known as discharge, is a critical variable for understanding the amount of water that leaves a 

watershed and is measured at a streamgage. M, Stream-water quality is measured by its chemistry and temperature. M and N, Water quality 

is measured at benchmark sites annually and at numerous downstream sites during studies where a nonreactive tracer is injected into the 

stream. O, All data cited above are integrated using sophisticated computer models that allow the quantification of the mass balance and 

contaminant transport from the watershed. These data and model results also provide opportunities for other research scientists and students 

to better understand hydrogeological processes, climate, and the unseen subsurface. (USGS photographs)
64 Developing Integrated Methods to Address Complex Resource and Environmental Issues

K

L

I J
Minerals, Energy, and Climate 65

Figure 34. Watershed approach is used to understand the processes controlling water availability and water quality. A, Using a watershed 

approach (mass input – mass output = 0), water, and potential contaminants in it, can be tracked and accounted for as it moves from 

headwater to lowland regions, where ultimately it is used for domestic and industrial purposes. The fundamental source of water is 

precipitation, in mountainous regions usually in the form of snow. B, Meteorological stations provide measurements of annual precipitation 

and other data used to monitor longer term climate variability. Wind speed and duration, humidity, solar insolation, and ground temperatures 

are also measured and provide data used to estimate evapotranspiration—a critical and difficult parameter to measure. C and D, A network 

of deep and shallow wells is instrumented with water-level and temperature sensors providing hourly hydraulic-head data and its response 

to variations in recharge. E and F, Geological mapping and characterization of faults and fractures at the surface and in the subsurface using, 

G and H, borehole geophysical logging are critical to understanding the physical vessel in which groundwater flows. I, The composition of 

different rock types and how they are altered by hydrothermal fluids imparting potential contaminants such as heavy metals is determined by 

mineralogical and elemental chemical analyses of drill core samples. J, Hydraulic aquifer tests are used to determine the permeability and 

storage capacity of bedrock aquifers, which tends to decrease with depth. K, Age and chemistry of groundwater are measured annually in the 

monitoring well network. L, Stream flow, also known as discharge, is a critical variable for understanding the amount of water that leaves a 

watershed and is measured at a streamgage. M, Stream-water quality is measured by its chemistry and temperature. M and N, Water quality 

is measured at benchmark sites annually and at numerous downstream sites during studies where a nonreactive tracer is injected into the 

stream. O, All data cited above are integrated using sophisticated computer models that allow the quantification of the mass balance and 

contaminant transport from the watershed. These data and model results also provide opportunities for other research scientists and students 

to better understand hydrogeological processes, climate, and the unseen subsurface. (USGS photographs)—Continued

O

M N

EXPLANATION

Stream

Inflows

Bedrock wells

4.5

4.0

3.5

3.0

2.5

0 500 1,000

Distance downstream, in meters

BW1 BW2 BW3 BW4 BW5

1,500 2,000

pH
66 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Verplanck, P.L., Manning, A.H., Kimball, B.A., McCleskey, 

R.B., Runkel, R.L., Caine, J.S., Adams, Monique, 

Gemery-Hill, P.A., and Fey, D.L., 2008, Ground- and 

surface-water chemistry of Handcart Gulch, Park County, 

Colorado, 2003–2006: U.S. Geological Survey Open-File 

Report 2007–1020, 31 p.

Verplanck, P.L., Nordstrom, D.K., Bove, D.J., Plumlee, G.S., 

and Runkel, R.L., 2009, Naturally acidic surface and ground 

waters draining porphyry-related mineralized areas of the 

Southern Rocky Mountains, Colorado and New Mexico: 

Applied Geochemistry, v. 24, p. 255–267.

Background

The two major forms of carbon (carbon reservoirs) in 

mine waste are mineral carbon and organic carbon. Mineral 

carbon includes primary (originally present in the ore/host 

rock) and secondary (formed after ore rock was left as mine 

waste) carbonate minerals such as calcite (CaCO3) or magnesite (MgCO3

). Where limestone is the ore host rock, primary 

carbonate minerals are abundant. In the waste rock, physical 

separation of ore from the host rock during mining resulted 

in enrichment of sulfide mineral waste relative to carbonate 

host rock. Over time, buffering of acid (produced via sulfide 

mineral weathering) by the carbonate minerals results in the 

destruction of the carbonates. In most other mine wastes (not 

hosted by carbonates), secondarily formed carbonate minerals 

are generally lacking.

Organic carbon in mine wastes results from decaying or 

live vegetation that has been preserved within the pile since 

emplacement (Stanton, 1999). Photosynthetic plants and other 

macroorganisms that grow on waste piles are varied but may 

include fungi, mosses, and vascular plants and grasses. However, the number of any of these organisms on a single waste 

pile is usually limited, and because mine wastes tend to be 

highly oxidizing environments, little organic matter is preserved over time. As surficial plant life is usually sparse, often 

the decaying or live plant material is removed by mechanical 

means, such as wind and water erosion.

Microbial carbon, a subset of the organic carbon reservoir, is difficult to measure and depends upon physical location of the mine waste, pile composition, types of microbiota 

(algae versus bacteria), and even the method used to estimate 

this parameter (Lehmann and others, 2011). Blue-green bacteria can develop a thick microbial mat on mine waste during 

wet periods of the year and impart high organic content to the 

mine waste, but these samples are not always representative of 

the entire pile. In general, waste piles in low-altitude temperate settings tend to have higher microbial masses and numbers because of readily available water and nutrients. Wastes 

located above timberline or in deserts are lower in microbial 

numbers because of harsher environmental conditions (temperature and lack of liquid water most months). Other bacteria 

are present in waste piles, for example thiobacilli (Stanton and 

others, 2007), which oxidize iron and sulfur and “fix” carbon 

for cell growth from carbon dioxide in the environment. Numbers and cell mass of some bacteria can be estimated with different tests, but many bacteria are considered “unculturable” 

because exact growth conditions are unknown and cannot be 

replicated outside the waste-pile environment. Again, measurement of microbial carbon is difficult to obtain on a routine 

basis because of the variability of populations.

Anthropogenic carbon (for example, support ties and 

mine timbers) is often present in waste piles. This extraneous 

carbon still may play a role in sorbing metals or contributing 

to improved conditions for microbial or plant growth. Numerous fungi, mosses, and lichens have been observed growing 

on timbers in many waste piles. These simpler organisms are 

Overview of Carbon Reservoirs and 

Sequestration in Sulfide Mine Wastes

By Mark R. Stanton and Douglas B. Yager

Issue and Scope

Sulfide mine wastes can be continuous sources of metal 

contaminants and acidity in local environments. Compared to 

most soils, sulfide mine wastes are barren with respect to different forms of carbon (carbon reservoirs). The acidic character and high metals content of mine waste-derived water and 

soil inhibits plant growth and soil development and subsequent 

carbon sequestration (retention). Changing the geochemical 

character of these mine wastes may lead to reduced generation of acidity and metals and improved carbon sequestration. 

In turn, if carbon retention is improved, an organic soil might 

be able to develop within the mine waste and ultimately result 

in desirable reductions in metal and acid release and physical 

stabilization of a waste pile. We are examining methods to 

alter the geochemistry of mine waste that might make it more 

chemically inert to weathering and more amenable to carbon 

sequestration and soil formation.

Objectives

The objectives of this task are to characterize the carbon 

content of sulfide mine wastes and to see if induced changes 

in geochemistry (especially pH) can influence carbon sequestration properties and the quality of water produced by the 

mine waste. One goal is to see if improvements in the carbon 

sequestration of mine wastes might lead to enhanced soil 

formation and thus, potentially reduce acid drainage generation. What is ultimately sought is a chemically and physically 

stable environment that is less toxic to vegetation and other 

soil-inhabiting species (for example, fungi).
Minerals, Energy, and Climate 67

“pioneers” that break down complex organic matter to provide 

more-usable forms of carbon and growth factors to allow 

growth of various organisms.

Results and Conclusions

We ran some experiments designed to determine if any 

processes or conditions might lead to sequestration of different 

forms of carbon and thus increase the total carbon reservoir in 

mine wastes. The first type of experiment examined addition 

of biochar (pyrolyzed biomass produced in controlled temperature and oxygen conditions) to mine wastes. Recent work 

with biochar has shown promise in enhancing soil fertility, 

improving soil drainage, reducing metal toxicity, and maintaining pH at levels best suited for plant growth (Lehmann and 

others, 2011). The most immediate effect of biochar addition 

to wastes is the adsorptive removal of metals from solution. 

High metal concentrations that normally would be present in 

the absence of char are lowered to more acceptable (nontoxic) 

levels. Future experiments are aimed at longer term results, 

for example, determining if biochar provides any increased 

buffering capacity or increase in soil fertility.

Another type of experiment examined the addition of acid 

neutralizing capacity (ANC) rocks containing CaCO3 to mine 

waste. A control run where pure fine-grained limestone was 

mixed into mine waste on a 1:1 mass basis resulted in the pH 

being buffered to values above 8.0 (from an initial pH value 

of 3.4 for mine waste alone). This higher pH not only resulted 

in lower aqueous metals concentrations but also resulted in 

the formation of abundant iron oxides, which can adsorb or 

coprecipitate metals from solution.

Similarly, volcanic rocks that contained minor 

(<18 weight percent) amounts of CaCO3, plus numerous 

silicates, were added to mine-waste rocks then reacted in aqueous solution. The added volcanic rocks (propylitically altered 

pyroxene andesite; Yager and others, 2008) did produce an 

increase in pH from 3.4 up to 5.8., Though not as effective 

as pure limestone, these volcanic rocks do have the ability to 

neutralize some of the acid drainage that would normally form 

by reaction of mine waste with water.

As noted, one consequence of raising pH above approximately 5.0 was the formation of abundant iron oxide in the 

reaction vessel (fig. 35). The iron precipitates preferentially 

formed in the calcite-bearing rock that had relatively higher 

pH (up to 6.0) than the overlying mine waste (pH=3.4). 

When iron oxides precipitate from solution, they tend to 

coprecipitate other metals and even organic matter and continue to adsorb metals and organics after formation. Thus, the 

process of iron-oxide formation and maintenance of higher 

pH should be useful in reducing the mobility of toxic metals 

in the waste pile and in localizing more organic matter within 

non-sulfide rocks.

Some experiments were carried out where thiobacilli

were added to mine waste to see if these might enhance carbon 

sequestration. Initially, higher numbers of cells were observed 

but not maintained, and eventually, cell numbers returned to the 

original low values. Thus, it was uncertain if the bacteria were 

able to grow and add mass to the organic carbon reservoir at 

slightly elevated pH (≤5.8). Any future studies would involve 

adding heterotrophic bacteria that utilize organic matter and 

grow more quickly than iron oxidizers to see if they would 

enhance retention of organic (bacterial) carbon in the waste pile.

We also examined the formation of secondary carbonate minerals as a means of raising pH, but these solids appear 

to be limited in most sulfide mine wastes. That is, results 

from field work and lab experiments indicate that secondary carbonate minerals that form in waste piles are unstable 

(short-lived). If pH is not maintained at higher values (>5.5), 

the minerals can be redissolved by acid drainage. In addition, 

the dominant evaporite minerals in most sulfide wastes are 

sulfate salts of widely varying compositions. These minerals 

readily redissolve and release stored acidity back to the mine 

waste, further inhibiting formation of stable carbonate phases. 

Addition of carbonate (limestone) from outside sources may 

improve geochemistry of mine wastes, but formation of carbonate minerals within the waste-pile solids or solutions does 

not appear to be great enough to have any significant effect on 

pH or carbon forms.

Figure 35. Formation of iron oxide on acid neutralizing capacity 

(ANC) rock surfaces in reaction vessel; mine waste material is the 

upper light-tan layer. The pH of the mine waste solution is 3.4, and 

the pH of the ANC solution is 5.8. (USGS photograph)
68 Developing Integrated Methods to Address Complex Resource and Environmental Issues

References Cited

Lehmann, Johannes., Rillig, M.C., Thies, Janice, Masiello, 

C.A., Hockaday, W.C., and Crowley, David, 2011, Biochar 

effects on soil biota—A review: Soil Biology and Biochemistry, v. 43, p. 1812–1836.

Stanton, M.R., 1999, The role of weathering in the redistribution of trace metals in the Mayday Mine dump near 

Silverton, Colorado: 4th International Conference on 

Acid Rock Drainage (ICARD), May 2000, Denver, Colo., 

p. 1501–1509.

Stanton, M.R., Yager, D.B., Fey, D.L., and Wright, W.G., 

2007, Formation and geochemical significance of iron bog 

deposits, chap. E14 of Church, S.E., von Guerard, Paul, and 

Finger, S.E., eds., Integrated investigations of environmental effects of historical mining in the Animas River watershed, San Juan County, Colorado: U.S. Geological Survey 

Professional Paper 1651, p. 689–720.

Yager, D.B, Choate, L.D., and Stanton, M.R., 2008, Net 

acid production, acid neutralizing capacity, and associated 

mineralogical and geochemical characteristics of Animas 

River watershed igneous rocks near Silverton, Colorado: 

U.S. Geological Survey Scientific Investigations Report 

2008–5063, 63 p.

Metals Sequestration by Biochar in 

Sulfide-Bearing Mine-Waste Leachate 

Experiments—Implications for MineWaste Reclamation and Carbon 

Sequestration

By Douglas B. Yager and Mark R. Stanton

Issue and Scope

Sequestration of metals by biochar (pyrolyzed biomass 

produced in controlled temperature and oxygen conditions) is 

not well understood but is a potentially important process that 

could aid in mine-waste reclamation (Fellet and others, 2011). 

Sulfide-bearing mine waste is a challenging reclamation environment and can remain devoid of vegetation for decades; the 

acidic conditions produced by weathering of sulfide minerals 

prevent re-colonization. Acidity and leaching of metals from 

barren mine waste can adversely impact local groundwater and 

surface-water quality and can be a long-term source of contaminants. Controlled laboratory studies are needed to address 

the acid neutralizing and metals sequestration potential of 

biochar. When biochar is applied in the field at mine sites and 

reclamation areas, there will likely be numerous geoenvironmental variables that may complicate interpretation of field 

experiments. Controlled laboratory vessel tests completed as 

part of this study will help to quantify the metals sequestration 

potential of biochar and aid in identifying key processes that 

may influence the effectiveness of biochar applied in field trials that cover large areas and involve complex systems.

Objectives

The objective of this study was to determine the acid neutralizing capacity and metals sequestration potential (species 

and quantity) of biochar. In order to simulate natural weathering processes in the field, laboratory reaction vessels were 

constructed that involved leaching (with deionized water) 

mine waste containing polymetallic veins and host rocks with 

base metal sulfides (copper-lead-zinc-cadmium, aluminum, 

and iron), amended with layered or mixed biochar. A goal was 

to determine the metals sorption capacity, pH, specific conductance, and electrical properties of biochar during laboratory 

vessel-test reactions.

Background

Hard rock metal mining produces large volumes of mine 

waste that lack vegetation, organic carbon, and soil nutrients 

(Yager and others, 2010). Measured soil enzyme activities 

have also been determined to be very low (Yager and others 
Minerals, Energy, and Climate 69

2007, 2010; Yager, Burchell, and others, 2008) indicating 

poor soil quality. Enhanced recovery of mine waste using 

soil amendments including biochar and locally sourced rocks 

having acid neutralizing capacity (ANC) could be a useful 

reclamation approach in improving soil quality.

Previous leachate and laboratory vessel tests by Stanton and Yager (this volume), Yager and others (2009) and 

Yager, Choate, and Stanton (2008) have addressed the ANC 

of propylitically altered bedrocks that are commonly associated with mineralized polymetallic vein and porphyry systems. The ANC of these materials was calculated to be high 

(>20 kilograms CaCO3 [calcium carbonate]/ton equivalent) 

and metals contribution due to leaching was determined to be 

low compared with metals contributed from leaching of sulfide-bearing mine waste (Yager, Choate, and Stanton, 2008). 

The use of locally sourced ANC rock that could be amended to 

mine waste during all phases of a project may initially reduce 

acidity of mine waste upon initiation of mining, reduce reclamation efforts once mining ceases, aid soil recovery (fig. 36), 

and lower the carbon footprint of a project due to the reduced 

need to transport limestone (the traditional remediation material) to the mine site from long distances.

The use of biochar in mine waste reclamation is in its 

pioneering stages with field trials only having been recently 

initiated (Peltz and others, 2010). Degraded mine-waste lands 

could benefit from application of biochar (Lehmann and others, 2003). This is due to physical and chemical properties of 

biochar that make it useful as a soil conditioner to improve 

soil quality and to sorb inorganic contaminants. In previous 

studies, biochar was shown to enhance plant growth by supplying and retaining nutrients, increase pH and soil moisture 

retention, improve soil structure, increase nutrient retention, 

decrease N2

O (nitrous oxide) and CH4 (methane) emissions, 

sorb metals, and reduce leaching (Lehmann, and others, 2006; 

Cao and others, 2009; Spokas and others, 2009; Sohi, 2010; 

Fellet and others, 2011). Biochar is a porous and permeable 

medium that has a high cation exchange capacity and, once 

amended to soils and stored in soil aggregates, is recalcitrant 

to weathering for millennia (Deluca and Aplet, 2008) (fig. 37). 

It is thus proposed as a potentially effective agent to offset 

atmospheric CO2 (carbon dioxide) emissions (Yager, Burchell, 

and others, 2008; Woolf and others, 2010). The laboratory 

vessel tests completed as part of this project will augment 

long-duration field trials where biochar is used to reclaim mine 

waste and other degraded soils.

Results and Conclusions

Laboratory vessel tests were designed to evaluate the 

physical and chemical reactions of mine-waste leachate with 

(a) biochar only and (b) a mixture of biochar and minewaste material. The experiment (a) that isolated biochar 

only involved saturating 12 centimeters of biochar with pure 

deionized water. Biochar feedstock was from pine wood, 

pyrolyzed at 450 °C (degrees Celsius). Nonreacted biochar 

metal concentrations were analyzed by inductively coupled 

plasma–mass spectroscopy (Lamothe and others, 2002) for 

comparison with post-reaction analytical results. Biochar was 

applied at a 10-percent rate to the vessel involving a biochar 

mine-waste mixture. Multiple regenerated cellulose membrane bags containing biochar were seeded in each vessel for 

extraction during various phases of reaction. Each vessel was 

Figure 36. Acid neutralizing capacity (ANC) rock aiding vegetation 

and soil recovery of mine waste. Red line is interface between 

altered andesite lava containing calcite that helps neutralize acidity 

generated from sulfide-bearing mine waste. Location is near 

Engineer Pass, at Hough Mine site, San Juan Mountains, Colorado. 

(Photograph from Alison Burchell, NTS Group).

Mine waste ANC rock

Vegetation

Figure 37. Scanning electron microscope, secondary electron 

image of pine wood biochar produced by Biochar Engineering 

Corporation, Niwot, Colorado, using a two-stage, low-temperature 

pyrolysis unit. Image shows the porous texture and high-surface 

area of the material. (Image from Sharon Diehl and U.S. Geological 

Survey microbeam facility in Denver, Colorado. White scale bar 

[lower right] represents 250 microns.)
70 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 38. Scanning electron microscope, backscatter image of pine-wood biochar exposed to mine-waste 

leachate in vessel test. Bright areas along cell walls and adjacent to circular areas (plant stoma) adsorbed 

iron, aluminum, and zinc during reaction in the vessel. Example spectra for bright areas (lower left). Instrument 

operating conditions were 20 kiloelectron volts (keV); image size is approximately 2 microns across. (Image from 

Sharon Diehl and U.S. Geological Survey microbeam facility in Denver, Colorado.)

Zn

Zn

Fe

Mn Fe

Ca

S

S Al

C

keV

counts

O

instrumented to measure pH, specific conductance, resistivity, 

and self-potential. Biochar was analyzed for metals throughout 

the experiment duration. Preliminary results of vessel tests 

suggest that base metal cations are sorbed to biochar particles 

having high surface areas and high cation exchange capacity. Scanning electron microscope analyses of biochar reacted 

with mine-waste leachate shows sorption of iron, aluminum, 

copper, and zinc by biochar (fig. 38). Longer duration (several 

months) vessel tests are needed to determine the quantity and 

species of metals sequestered and whether acidity and specific 

conductance are reduced over the long term. Future vessel 

tests will evaluate whether the combined use of ANC rocks 

and biochar as amendments to mine waste is more effective in 

sequestering metals and reducing acidity. 

Collaborators

Alison Burchell, NTS Group, P.O. Box 3671, Boulder, CO,

 80307

Carleton Bern, U.S. Geological Survey, PO Box 25046,

 MS 964D, Denver Federal Center, Denver, CO, 80225.

Ted Dodge, Jefferson Watershed Council, P.O. Box, 585, Pony,

 MT, 59747

Selected References

Burchell, Alison, Yager, D.B., Johnson, R.H., Aiken, J.R., 

and Butler, Kenna, 2010, High total organic soil carbon 

(TOSC), low dissolved organic carbon (DOC), and black 

carbon (BC) horizons, San Juan Mountains, Colorado—

Implications for enhanced natural terrestrial carbon 

sequestration (NTS) land use management and reclamation 

protocols [abs.]: Geological Society of America Abstracts 

with Programs, vol. 42, no. 5, p. 160.
Minerals, Energy, and Climate 71

Cao, Xinde, Ma, Lena Qiying, Gao, Bin, and Harris, Willie, 

2009, Dairy-manure derived biochar effectively sorbs lead 

and atrazine: Environmental Science and Technology, v. 43, 

p. 3285–3291.

DeLuca, T.H., and Aplet, G.H., 2008, Charcoal and carbon 

storage in forest soils in the Rocky Mountain West: Frontiers in Ecology, v. 6, no. 1, p. 18–24. 

Fellet, G., Marchiol, L., Vedove, G.D., and Peressotti, A., 

2011, Application of biochar on mine tailings—Effects and 

perspectives for land reclamation: Chemosphere, v. 83, 

issue 9, p. 1262–1267.

Lamothe, P.L., Meier, A.M., and Wilson, S.A., 2002, The 

determination of forty-four elements in aqueous samples by 

inductively coupled plasma–mass spectrometry, in Taggart, 

J.E., Jr., ed., Analytical methods for chemical analysis of 

geologic and other materials: U.S. Geological Survey OpenFile Report 02–0223–H, p. H1–H11.

Lehmann, Johannes, da Silva, J.P., Jr., Steiner, Christoph, 

Nehls, Thomas, Zech, Wolfgang, and Glaser, Bruno, 2003, 

Nutrient availability and leaching in an archeological 

Anthrosol and a Ferralsol of the Central Amazon basin: 

fertilizer, manure and charcoal amendments: Plant and Soil, 

v. 249, p. 343–357. 

Lehmann, Johannes, Gaunt, John, and Rondon, Marco, 2006, 

Bio-char sequestration in terrestrial ecosystems—A review: 

Mitigation and Adaptation Strategies for Global Change, 

v. 11, p. 403–427.

Peltz, Christopher, Nydick, Koren, Fitzgerald, Gretchen, 

and Zillich, Cathleen, 2010, Biochar for soil remediation 

on abandoned mine lands [abs.]: Geological Society of 

America Abstracts with Programs, v. 42, no. 5, p. 85.

Sohi, S.P., Krull, E., Lopez-Chapel, E., and Bol, R., 2010, A 

review of biochar and its use and function in soil: Advances 

in Agronomy, v. 105, p. 47–82.

Spokas, K.A., Koskinen, W.C., Baker, J.M., and Reicosky, D.C., 

2009, Impacts of woodchip biochar additions on greenhouse 

gas production and sorption/degradation of two herbicides in 

Minnesota soil: Chemosphere, v. 77, p. 574–581.

Yager, D.B., 2008, Environmental rock properties at abandoned mine lands that generate or neutralize acid drainage, 

Silverton, Colorado, chap. K of Verplanck, P.L., ed., Understanding contaminants associated with mineral deposits: 

U.S. Geological Survey Circular 1328, p. 64–69. 

Yager, D.B., Burchell, Alison, and Johnson, R.H, 2010, A 

geologic and anthropogenic journey from the Precambrian 

to the new energy economy through the San Juan volcanic 

field, in Morgan, L.A., and Quane, S.L., eds., Through the 

generations—Geologic and anthropogenic field excursions 

in the Rocky Mountains from modern to ancient: Geological Society of America Field Guide 18, p. 193–237.

Yager, D.B., Burchell, Alison, and Johnson, R.H., 2008, The 

Natural terrestrial carbon sequestration potential of Rocky 

Mountain soils derived from volcanic bedrock [abs.]: Eos, 

Transactions of the American Geophysical Union, Fall 

Meeting, Supplement, Abstract GC21A–0172.

Yager, D.B., Burchell, Alison, Robinson, Rob, Odell, Stephanie, Dick, R.P., Johnson, C.A., Hidinger, Jack, and Rathke, 

David, 2007, Natural terrestrial sequestration potential of 

high plains prairie to subalpine forest and mined-lands soils 

derived from weathering of Tertiary volcanics [abs.]: EOS, 

Transactions of the American Geophysical Union, Fall 

Meeting, Supplement, Abstract B23D–1,588.

Yager, D.B., Choate, LaDonna, and Stanton, M.R., 2008, 

Net acid production, acid neutralizing capacity, and associated mineralogical and geochemical characteristics of 

Animas River watershed igneous rocks near Silverton, 

Colorado: U.S. Geological Survey Scientific Investigations 

Report 2008–5063, 63 p.

Yager, D.B., Stanton, M.R., Choate, L.M., and Burchell, Alison, 2009, Acid neutralizing capacity and leachate results 

for igneous rocks with associated carbon contents of derived 

soils, Animas River AML site, Silverton, Colorado, in Barnhisel, R.I., ed.: American Society for Reclamation Mining 

and Safety, Lexington, Ky., p. 1662–1697.

Woolf, Dominic, Amonette, J.E., Street-Perrott, F.A., Lehmann, Johannes, and Joseph, Stephen, 2010, Sustainable 

biochar to mitigate global climate change: Nature Communications, 1:56 doi: 10.1038/ncomms1053, 9 p.
Element Cycling, Toxicity, and Health

methods that produce derivative data necessary to quantify 

contaminant reservoirs on Mancos Shale in the Uncompahgre 

River watershed (a tributary to the upper Colorado River), 

to calculate the flux among reservoirs, and to scale results to 

include all Mancos Shale landscapes in the UCRB.

Objectives

The objectives of our study were three-fold. The first 

objective was to construct a critical zone model that tracks contaminants as Mancos weathers to soil (pedogenesis). Different 

methods in the literature have been used to track contaminant 

gain, loss, and redistribution within weathering profiles. Bulk 

density data (Lisa Stillings, U.S. Geological Survey, written 

commun., 2007) and chemistry (Tuttle and others, 2007) for 

Mancos samples were used to evaluate the different methods.

The second objective was to develop a method to quantitatively inventory contaminants in different reservoirs across 

different Mancos land-use landscapes (for example, natural, 

irrigated, and urbanized). Identifying and quantifying contaminants in each reservoir can be difficult and costly, so the use of 

operationally defined reservoirs (readily soluble and insoluble 

reservoirs) was investigated. The techniques were evaluated 

comparing chemical results from different rock:water ratio 

extracts of Mancos soil to stream loads (Tuttle and Grauch, 

2009) and chemical data from Mancos rainfall simulation 

experiments (Elliott and others, 2007; Tuttle, unpub. data). 

Laboratory leaching experiments were designed to measure 

the potential for the insoluble soil reservoir to continually 

supply contaminants to the readily soluble soil reservoir as 

contaminants are removed with drainage.

The third objective was to develop a protocol from constructing contaminant budgets at the watershed scale. Budgets 

include contaminant inventories, contaminants solubilized but 

returned to the soil by infiltration, contaminants transported 

by runoff, and contaminants in eroded soil and alluvium. The 

utility of these budgets for scaling data from small studied 

watersheds to larger regional landscapes was tested using 

results from the literature and the two studies discussed in the 

Background section.

Background

The U.S. Geological Survey (USGS) partnered with 

Federal and State agencies to collect and help understand data 

on these nonpoint contaminant sources. In 2003, the USGS 

initiated a large multidisciplinary study on undisturbed Mancos 

Shale in the Uncompahgre River watershed above the flood 

plain focusing on weathering of black shale and the impact 

of recreational land use. Geochemical data were collected on 

samples from trenches, core, and regional soil surveys. The 

Salt and Selenium Cycling in ShaleDerived Soils, Southwestern United 

States

By Michele L.W. Tuttle, Juli Fahy, and Jean Morrison

Issue and Scope

The Colorado River in the southwestern portion of the 

United States is considered one of the most stressed in the 

world because of increasing salinization and selenium (Se) 

contamination (Engberg, 1999; Serageldin, 2000). Nearly 

36 million people and 4.5 million acres of United States and 

Mexico farmland depend on the Colorado River (U.S. Department of Interior, 2005) and salinization damages in the United 

States alone are estimated at $306 million (U.S. Department 

of Interior, 2005). Rocks weathering in the Upper Colorado 

River Basin (UCRB) supply a significant portion of the contaminants. Tuttle and Grauch (2009) estimate that 33 percent 

of the 2005 solute load in the river near the Colorado-Utah 

border was derived from chemical weathering of Cretaceous 

Mancos Shale. The dominant anion in the load was sulfate, 

and the amount attributed to the Mancos is equivalent to 

1,400,800 tonnes per year of gypsum dissolution. Nearly all 

the Se contamination in the UCRB is from natural weathering 

and irrigation of the Mancos (Clark, 1995; Engberg, 1999). 

Tuttle and Grauch (2009) estimated that 60 t a−1 of Se were 

derived from Mancos Shale landscapes in Colorado, representing nearly the entire 2005 Se load in the river near the 

Colorado-Utah border. The Se load is of concern because concentrations in the river exceed the U.S. Environmental Protection Agency’s (EPA) National Recommended Water Quality 

Criteria (5 micrograms per liter [μg L−1] for freshwater) in 

some reaches inhabited by threatened and endangered species 

of fish (Hamilton, 1998), and Se impacts the habitat of other 

wildlife along the river such as waterfowl (Presser and others, 

1994; Butler and others, 1996). 

Previous studies have described salt and Se in the UCRB; 

however, none include a comprehensive understanding of 

the processes that occur during both chemical and mechanical weathering of rock and derived soil, nor do they produce 

geochemical models that describe the flux of salt and contaminants among rock, soil and alluvium, and aqueous phases. 

Conceptually and quantitatively understanding contaminant 

cycling under natural and irrigated conditions is critical for 

developing strategies to preserve the health of soils developed 

on shale landscapes across the arid southwest and to remediate 

salinization and contaminants in waterways that flow through 

them. The focus of this study was to develop and test different 
Element Cycling, Toxicity, and Health 73

Figure 39. Depth profile of Mancos Shale trench showing tau (τ) values for total salt (gypsum 

equivalent, [GE]) and selenium (Se) in soil, transition soil, and shale. mg/kg, milligrams per kilogram.

results of this study show that weathering processes redistribute and concentrate contaminants in secondary reservoirs. On 

undisturbed landscapes, most redistributed contaminants are 

stored in the soil and, even during severe storm events, are only 

transported short distances. In a parallel study by the Bureau 

of Reclamation and Natural Resources Conservation Service, 

similar Mancos data were collected from irrigated fields and 

adjacent vacant land on the Uncompahgre River flood plain. 

The results of this study showed that irrigation from farming 

and other anthropogenic activities mobilized large concentrations of stored salt and Se into streams and groundwater.

Although the data from both studies were collected 

and analyzed with similar methods, no attempt was made to 

integrate them into an understanding of how Mancos Shale 

weathers under different land-use practices. To achieve this, 

contaminants in different reservoirs need to be quantified and 

the flux of contaminants among reservoirs determined. This 

study developed the methods to integrate the data, provides 

documentation on how to construct contaminant cycles in this 

and similar watersheds, and provides tools for land managers 

to assess the impact of contaminants from weathering landscapes under different land-use scenarios.

Results and Conclusions

Tracking contaminant mobility.—Index elements (generally titanium [Ti], neodymium [Nd], zirconium [Zr], and 

silicon dioxide [SiO2

]) are commonly used to track the gain or 

loss of contaminants during pedogenesis. Using bulk density 

measurements, Ti was chosen as the least mobile index element and was used to calculate a Tao (τ) value for each sample 

in our trench profiles. Tao converts concentration into a fraction lost or gained relative to that in the starting material, corrects for mass changes of other components during weathering 

(White, 2003), and is calculated as follows (Brimhall, 1991):

 τj,w = {(Cj,w/Cj,o)/Ci,w/Ci,o)} – 1. (5)

The Cj,w and Cj,o are concentrations of contaminant j (salt 

or Se) in weathered and starting material, respectively, and 

Ci,w/Ci,o are the concentrations of the immobile, index phase 

i (Ti) in weathered and starting material. Tao depth profiles 

for salt and Se (fig. 39) show an 18-fold increase in salt in the 

soil zone and a small net loss of Se over the profile. The salt 

accumulation zone forms because nearly 90 percent of the 

rainfall and all of the snowmelt infiltrates into the soil where 

the moisture is subsequently lost through evapotranspiration 

leaving behind the salt. Selenium increases slightly in this salt 

accumulation zone.

Availability of contaminants.—Multiple rock:water extract 

data showed that extract salinity is controlled by gypsum solubility and that smaller ratios (higher water amounts) extracted 

more salt and Se. Our goal was to use an extract ratio that best 

mimicked natural conditions, so the extract data were compared 

to data from rain simulation experimental (RSE) data collected 

in the field. The concentration of Se in the saturation paste 

–1 –1 –0.5 0 0.5 1

–500

–400

–300

–200

–100

0

Depth in centimeters

5 10 15 20

Transition

Soil

Shale

EXPLANATION

τSalt(GE) τSe(total)
74 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 40. Salt and selenium extract (ex) concentrations (dry 

weight basis) in sequential saturation paste extracts. mg/kg, 

milligrams per kilogram.

Table 3. Total and extractable selenium and salt (gypsum equivalent) inventories for Mancos Shale soil (0–45 centimeters) in the 

Uncompahgre River watershed. Values are totals for the landscape (in metric tonnes [t]) and per square meter (m–2) of landscape. 

Undisturbed landscapes are those above the flood plain (FP).

[g, gram; km2, square kilometers; Se, selenium; nonirr., nonirrigated; --, no data]

Landscape Undisturbed 470 km2 FP Irrigated 119 km2 FP nonirr. 101 km2 FP wetland 18 km2

Total Extractable Total Extractable Total Extractable Total Extractable

Se (g m–2) 0.8 0.05 1.5 0.01 2.5 0.09 7.2 0.7

Se (t) 380 26 180 1.2 250 9.3 130 12

Salt (g m–2) 2.2 x 104 870 -- 630 -- 2.1 x 103 -- 3.2 x 103

Salt (t) 1.0 x 107 4.1 x 105 -- 7.5 x 104 -- 2.1 x 105 -- 5.7 x 104

Table 4. Fluxes calculated from precipitation rates, rainfall simulation data, and saturation-paste-extract data are compared to 

loads measured in tributaries and the Uncompahgre River (UR). Calculated budget for tributaries include the undisturbed Mancos 

Shale above the flood plain (FP).

[-, no data; %, percent; g acre–1, grams per acre]

Salt (g acre–1) Selenium (g acre–1)

Sources Water loads % UR

load

Calculated 

budget

% UR

load

Water 

budget

% UR

load

Calculated 

budget

% UR

load

Precipitation 2.1 x 108 <1 -- 5.7 x 104 <1 -- --

River above study 9.3 x 1010 31 -- 0 0 -- --

Diversion (irrigation) 8.5 x 1010 28 -- 0 0 -- --

Tributaries in study 2.1 x 1010 7 2.0 x 1010 7 1.8 x 105 5 1.4 x 105 4

Mancos soils (FP) 7.2 x 1010 24 8.3 x 1010 24 3.2 x 106 95 3.5 x 106 96

Irrigated -- -- 7.3 x 1010 21 -- -- 3.0 x 106 82

Nonirrigated -- -- 1.0 x 1010 3 -- -- 4.9 x 105 14

Other soils (FP) 2.7 x 1010 10 -- -- 0 0 -- --

Uncompahgre River 3.0 x 1011 100 -- -- 3.4 x 106 100 3.6 x 106 --

0

0.005

0.01

0.015

0.02

0.025

0.03

1 2 3 4 5 6 7 8 9 10

Sequential extract number

Se(ex) mg/kg soil

500

1,000

1,500

2,000

Salt(ex) mg/kg soil
Element Cycling, Toxicity, and Health 75

extract (SPE) was 5.0 μg L–1 compared to 5.6 μg L–1 in the RSE 

runoff. The SPE overestimates the salt content; however, this 

was not an issue on a watershed scale. These results indicate 

that soil SPE concentrations are a good estimation of readily soluble reservoirs and provide reliable data for calculating 

fluxes between reservoirs. Results from our leaching experiments (fig. 40) show a continual supply of contaminants to the 

soluble reservoir controlled by adsorption and solubility.

Contaminant inventories and fluxes.—Salt and Se 

inventories (table 3) were constructed using regional soil 

data collected in the two studies mentioned above. Mancos 

Shale landscapes on the Uncompahgre River flood plain 

contain more Setotal per square meter than undisturbed Mancos 

landscapes above the flood plain. Irrigated fields contain the 

least amount of extractable Se and salt due to leaching over 

time but are still serious nonpoint contaminant sources as 

determined from the leaching experiments. Fluxes from different reservoirs are calculated from SPE and inventory data. 

Comparison of the calculated fluxes with measured stream 

loads is given in table 4.

The authors are applying these methods to a study in a second upper Colorado River tributary (Pariette Draw, Utah) where 

Tertiary shale (Green River and Uinta Formations) weathers under 

the same conditions as in the Mancos Shale study. The Tertiary 

shale contributes salt and Se (plus boron) to the stream in concentrations that exceed EPA Total Maximum Daily Load standards.

Collaborators

Collaborators in the Mancos Shale study are Bureau 

of Land Management, Montrose Colorado; USGS Colorado 

Water Science Center; and Bureau of Reclamation. Collaborators in the ongoing Pariette Draw study are Bureau of Land 

Management, Vernal and Salt Lake City, Utah; Colorado 

River Salinity Control Program (Bureau of Reclamation); 

Bureau of Land Management Salinity Program; Utah Division of Water Quality; Utah State University; and Kansas 

State University.

References Cited

Brimhall, G.H., Lewis, C.J., Ford, Chris, Bratt, James, Taylor, 

Gordon, and Warin, Oliver, 1991, Quantitative geochemical 

approach to pedogenesis—Importance of parent material 

reduction, volumetric expansion, and eolian influx in lateritization: Geoderma, v. 51, p. 51–91. 

Butler, D.L., Wright, W.G., Steward, K.G., Campbell Osmundson, 

Barbara, Krueger, R.P., and Crabtree, D.W., 1996, Detailed 

study of selenium and other constituents in water, bottom sediment, soil, alfalfa, and biota associated with irrigation drainage 

in the Uncompahgre Project Area and in the Grand Valley, westcentral Colorado, 1991–93: U.S. Geological Survey WaterResources Investigation Report 96–4138, 136 p.

Clark, S.L., 1995, The distribution of selenium in the upper 

Colorado River: Tempe, Arizona State University, Ph.D. dissertation, UMI 9526987, Ann Arbor, UMI Company, 150 p.

Elliott, J.E., Herring, J.R., Ingersoll, G.P., Kosovick, J.J., 

and Fahy, Juli, 2007, Rainfall-runoff and erosion data 

from the Mancos Shale Formation in the Gunnison 

Gorge National Conservation Area, southwestern Colorado, 2003–2006: U.S. Geological Survey Open-File 

Report 2007–1002–G, 67 p., at https://pubs.er.usgs.gov/

publication/ofr20071002G/.

Engberg, R.A., 1999, Selenium budgets for Lake Powell and 

the upper Colorado River: Journal of the American Water 

Resources Association, v. 35, p. 771–786.

Hamilton, S.J., 1998, Selenium effects on endangered fish in 

the Colorado River Basin, in Frankenberger, W.T., Jr., and 

Engleberg, R.A., eds., Environmental chemistry of selenium: New York, Marcel Dekker, Inc., p. 297–313.

Presser, T.S., Sylvester, M.A., and Low, W.H., 1994, Bioaccumulation of selenium from natural geologic sources in 

Western States and its potential consequences: Environmental Management v. 18, p. 423–436.

Serageldin, Ismail, 2000, World’s rivers in crisis—Some are 

dying; others could die: World Commission on Water for 

the 21st Century, at http://www.worldwatercouncil.org/Visio

n/6902B03438178538C125683A004BE974.htm.

Tuttle, M.L., and Grauch, R.I., 2009, Salinization of the upper 

Colorado River—Fingerprinting geologic salt sources: U.S. 

Geological Survey Scientific Investigations Report 2009–

5072, 62 p., at http://pubs.usgs.gov/sir/2009/5072/.

Tuttle, M.L.W., Fahy, Juli, Grauch, R.I., Ball, B.A., Chong, 

G.W., Elliott, J.G., Kosovich, J.J., Livo, K.E., and Stillings, 

L.L., 2007, Results of chemical analyses of soil, shale, and 

soil/shale extract from the Mancos Shale Formation in the 

Gunnison Gorge National Conservation Area, Southwestern 

Colorado, and at Hanksville, Utah: U.S. Geological OpenFile Report 2007–1002–D, 24 p., at http://pubs.usgs.gov/

of/2007/1002/D/.

U.S. Department of Interior, 2005, Quality of water, Colorado 

River Basin progress report no. 22: Denver, Colo., Bureau 

of Reclamation, 69 p., at http://www.usbr.gov/uc/progact/

salinity/index.html.

White, A.F., 2003, Natural weathering rates of silicate minerals, in Holland, H.D., and Turekian, K.K., eds., Treatise on 

geochemistry, vol. 5: New York, Elsevier, p. 133–168. 
76 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Microbial Communities Involved in 

Arsenic and Iron Cycling at the Lava 

Cap Mine Superfund Site, California

By Andrea L. Foster

Issue and Scope

Understanding the spatial and temporal relations among 

microbial groups in field and laboratory settings is required 

for (1) process-based understanding of the role and impact of 

microorganisms on toxic trace metal mobility and bioavailability, (2) the development of microbially enhanced remediation technologies, and (3) development of microbially based 

processes to extract economically important elements from 

mineral deposits. The U.S. Environmental Protection Agency 

(EPA) Superfund Program, which is in charge of hazardous 

waste sites at which human health has been determined to be 

particularly at risk, has a specific directive to pursue “green” 

and “renewable” technologies developed from materials at or 

near the site. Native microorganisms that are found to perform 

a useful function could, in theory, be used to help clean up 

hazardous waste sites.

Objectives

Our objective was to evaluate the feasibility for native, 

iron-oxidizing microbes to be used in passive bioreactors to 

help remove arsenic (As) from water at the Lava Cap Mine 

Superfund Site (LCMS), California (fig. 41). Over a 2-year 

period, we conducted geochemical and microbiological 

monitoring studies at several locations on the site where the 

iron-oxidizing microbial communities were observed to form 

visible colonies. Our specific actions were (1) to quantify the 

seasonal and spatial variation in the magnitude of As uptake 

by biogenic ferric (hydr)oxide, (2) to determine the composition of the microbial community producing the ferric (hydr)

oxide, (3) to track seasonal and spatial variation in the composition of that community, (4) to monitor the performance of a 

naturally occurring passive bioreactor developed fortuitously 

at the base of an intact tailings dam, and (5) to determine 

the mechanism of As sequestration on the biogenic ferric 

hydr(oxide) and its reversibility.

Background

The Lava Cap Mine exploited a gold-bearing quartzcarbonate-vein system typical of the Sierran (“Lode”) Gold 

Belt. Peak production at the Lava Cap occurred between 

1934 and 1943 when about 90,000 tons of ore per year were 

processed (Clark, 1970). To facilitate removal of the gold and 

accessory sulfide minerals, the ore was crushed to a very fine 

sand or silt grain size for processing. The Lava Cap Mine and 

surrounding area were placed on the EPA National Priority 

(that is, Superfund) List of priority sites for cleanup due to 

several factors that coalesced in December 31, 1996, when 

a log-tailings retention dam failed at the mine site sending 

an estimated 8,000–10,000 cubic meters of tailings down a 

stream and into a second, intact tailings dam that was being 

used as a small private lake by local residents. Between 1996 

and 2000, members of the U.S. Geological Survey (USGS) 

Mineral Resources Program worked with the California 

Department of Toxic Substances Control to characterize the 

degree to which the catastrophic log-dam failure and minetailings release affected downstream waterways (specifically 

Little Clipper Creek and Lost Lake) in terms of (1) metals 

loading to sediments and waters and (2) the extent of As 

transformation from forms in sulfide minerals originally in 

the tailings to labile and oxidized forms (Foster and others, 

2011). During the course of this research, the investigators 

discovered that aquatic flocculent ferric (hydr)oxide deposits 

were biogenic in nature, and that these deposits scavenged As 

from water (Foster and Ashley, 2002). The EPA took interest in this work and, beginning in 2006, funded the USGS to 

study these communities in greater detail.

Results and Conclusions

Major conclusions from the study (which employed 

genetic, culturing, chemical, and spectroscopic techniques) are 

as follows:

1. The site-wide average As concentration in dried biogenic 

ferric (hydr)oxide (BFH) was >10,000 milligrams per 

kilogram (mg/kg; ppm [parts per million]) but ranged 

from 3,000 to 39,000 mg/kg (fig. 42). Typical As concentrations in LCMS tailings range from 500–1000 mg/kg, 

demonstrating the efficacy of this biosorbent in accumulating arsenic.

2. BFH contains far more iron (Fe) and manganese (Mn) 

than As (average of 29 percent and 10 percent, respectively; fig. 42), and therefore is useful for lowering the 

concentration of these “nuisance” elements from water. 

This is particularly advantageous because after removal 

of As, in a pilot cleanup plant, discharge from the site 

was still above water-quality standards for Fe and Mn.

3. A naturally occurring passive bioreactor developed at 

the site removed an average of 44, 55, and 29 percent of 

As, Fe, and Mn, respectively, from water over the 2-year 

sampling period (fig. 43). Variability in performance was 

related to water-flow rate rather than changes in influent 

As concentration, with lower flow resulting in greater 

As, Fe, and Mn removal.

4. Both arsenate and arsenite are accumulated by BFH, 

and As is both adsorbed and co-precipitated on BFH. 

Analysis of synchrotron-based X-ray absorption spectra 

allowed these conclusions to be made. Purely adsorbed 
Element Cycling, Toxicity, and Health 77

Figure 41. Regional to site-level overview of the Lava Cap Mine Superfund Site, Nevada County, California. An 

estimated 10,000 cubic meters (m3) of tailings were released into Little Clipper Creek due to failure of a tailings dam 

(labeled) located near the mine. Most of this material settled in the downstream deposition area and in Lost Lake—a 

second tailings retention structure that already contained an estimated 382,277 m3

 of tailings deposited during the 

active mining period. Interaction of water with tailings produces conditions conducive to the growth of iron-oxidizing 

microbial communities; these are most extensively developed in water seeping out below the Lost Lake dam.

IDAHO-MARYLAND ROAD

GREENHORN MOUNTAIN ROAD

LAVA CAP MINE

(CENTRAL SHAFT)

BANNER MINE

Lost

Lake

Drainage tunnel

TAILINGS

DAM

TAILINGS

DAM

Clipper Creek

Little

Clipper

Creek

Greenhorn

Little

Creek

Wolf Creek

Little Deer Creek

20 21 22

17 16 15

27

28 29

32 33 34

5 4 3 2

T.

16

N. 

T.

15

N.

R. 9 E.

2800

2800

2800

2800

2800

3000

2800

3000

3200

2800 3000

2800

3200

3200

2800

3000

3200

3600

3800

3400

2600

2800

3000

3200

2600

2600

2600

2600

2400

2400

39°15'

38°12'30"

121°00' 120°57'30"

0 0.5 KILOMETERS

0 0.5 MILES

Little

Greenhorn

Creek

Nevada

City

Grass

Valley

SR49

SR49

SR20

SR174

Deer

Creek

ROLLINS

RESERVOIR

Clipper

Creek

MAP AREA

Base map USGS Chicago Park quadrangle, scale 1:24,000.

Modified from Foster and Ashley (2002).
78 Developing Integrated Methods to Address Complex Resource and Environmental Issues

species are associated only with the surfaces of minerals, 

whereas co-precipitated species are also located within 

the bulk mineral. Adsorbed species can be released from 

minerals by small changes in solution composition such 

as pH or ionic strength changes.

5. The microbial consortia producing BFH are of low 

diversity. They appear to be dominated by species of 

the Leptothrix genus of Eubacteria. Analysis of DNA 

extracted from fresh BFH flocs across the LCMS 

show a remarkable similarity and low diversity of the 

microbial community. Under the microscope (light and 

electron), BFH is seen to be composed primarily of 

microbial sheaths, which are coated with ferric (hydr)

oxide (fig. 44). Few sheath-forming bacteria exist in 

nature, and fewer still prefer environments low in carbon 

(so called “oligotrophic” environments). These unique 

characteristics allowed the identification of members of 

the genus Leptothrix as the predominant members of the 

BFH-forming microbial community.

6. Native populations of suboxic to anoxic bacteria are 

present in BFH from the LCMS; these bacteria can 

dissolve ferric (hydr)oxide and release to solution some 

or all of the As, Fe, or Mn associated with it. The BFH 

produced by Leptothrix and other community members has the potential to be “food” for another group of 

microorganisms—the iron-reducing bacteria (FeRB). 

These bacteria have several different strategies for 

coupling the reduction of ferric iron to energy-generating 

processes, and they have been the focus of many studies. No gene for iron reduction has yet been discovered 

that would allow an estimation of the abundance of the 

FeRB community by gene-based techniques. Therefore, 

most probable number (MPN), a serial-dilution, culturebased technique, was employed to assess the abundance 

of FeRB in the BFH. Substantial populations of FeRB 

were enumerated suggesting that if a passive bioreactor 

were constructed, careful maintenance of the geochemical environment in the reactor would be required to 

ensure that As was not being re-released under changing 

seasonal conditions.

Our study found that naturally occurring, Leptothrixdominated microbial communities could remove As to below 

water-quality criteria in a natural system analogous to a passive bioreactor, but removal is highly dependent on flow rate 

and therefore would need to be carefully managed. Both major 

species of arsenic bind to iron hydroxide precipitated on the 

sheaths of Leptothrix in what appears to be predominantly 

adsorbed complexes that may be easily removed by changes in 

pH or concentration of competing anions such as phosphate or 

silica. Although the communities are dominated by Leptothrix

and appear to change little with season, a latent population of 

iron-reducing bacteria is also present and poses a threat to the 

long-term stability of the solid-phase arsenic. Simple changes 

in geochemical conditions could mobilize a significant fraction 

of arsenic bound to Leptothrix sheaths. However, this problem 

Figure 42. Basic statistics of arsenic (top), iron, and manganese 

dry weight concentrations measured over the study period at 

several locations at the Lava Cap Mine Superfund Site.

5,000

0

10,000

15,000

30,000

Arsenic, milligrams per kilogram 20,000

25,000

0

20

40

Iron, in percent 

10,000

0

20,000

30,000

40,000

50,000

60,000

70,000

Manganese, milligrams per kilogram

Biogenic ferric (hydr)oxide samples Algae
Element Cycling, Toxicity, and Health 79

Figure 43. Percent attenuation of dissolved arsenic (As), iron (Fe), and manganese (Mn) through 

a naturally developed passive bioreactor system that was measured several times during the study 

period as the difference between the dissolved concentrations of these elements measured at site 

LL1 (where low oxygen [O2

], Fe-, Mn-, and As-rich water seeps out below the dam) and site LL10 (just 

upstream of the site where seep water meets highly oxygenated lake water from the dam spillway). 

Most of the variability in removal of the constituents can be traced to differences in water-flow 

conditions, where higher flow rate equals less removal of the three constituents.

Figure 44. Dual-transmitted-light and epifluorescent-light image (400×) of cells of a sheath-forming, 

iron-oxidizing bacterium (L. ochracea) that composes the bulk of the biogenic ferric (hydr)oxide 

produced at the Lava Cap Mine Superfund Site. Members of the genus Leptothrix prefer low-carbon 

environments, are aerobic, and have the ability to form sheaths, which is relatively rare among the 

bacteria. Members of the genus are known to harbor proteins on their sheaths and capsular material 

that enzymatically oxidize iron and manganese. The cells have been stained with propidium iodide 

for visibility under ultraviolet light demonstrating their filamentous nature and the fact that very few 

sheaths are populated—another well-known characteristic of L. ochracea (Foster and Ashley, 2002).

10

20

30

40

50

60

70

80

90

100

June October November

Percent

February

2006 2007 2008

Date

March August October March

EXPLANATION

As

Fe

Mn

LL1 

LL10

Lost

Lake
80 Developing Integrated Methods to Address Complex Resource and Environmental Issues

is analogous to the current problem of disposal of large volumes of chemically prepared As adsorbed on iron hydroxides 

produced in active remediation systems. In those remediation 

systems, the potentially labile adsorbed As is currently managed by maintaining this material under oxidizing, subaqueous 

conditions in lined holding ponds (Paktunc and others, 2003).

Collaborators

U.S. Environmental Protection Agency Region 9, Superfund

 Section through interagency agreement DW14-95571901-0.

Stanford University Environmental Molecular Sciences 

 Institute (National Science Foundation grant)

References Cited

Clark, W.B., 1970, Gold districts of California: California 

Division of Mines and Geology Bulletin 193, 186 p.

Foster, A.L., and Ashley, R.P., 2002, Characterization of arsenic species in microbial mat communities in the vicinity of 

the Lava Cap gold mine, Nevada City, CA: Geochemistry: 

Exploration, Environment, and Analysis, v. 2, p. 253–261.

Foster, A.L., Ashley, R.P., and Rytuba, J.J., 2011, Arsenic species in weathering tailings and biogenic solids at the Lava 

Cap Mine Superfund Site, Nevada County, CA: Geochemical 

Transactions, v. 12, p. 1-21, doi:10.1186/1467-4866-12-1.

Paktunc, Dogan, Foster, Andrea, and Laflamme, Gilles, 2003, 

Speciation and characterization of arsenic in Ketza River 

mine tailings using X-ray absorption spectroscopy: Environmental Science & Technology, v. 37, p. 2067–2074.

Geochemical Signatures as Natural 

Fingerprints

By Bronwen Wang and Robert Seal

Issue and Scope

The migration of Tanner crabs (Chionoecetes bairdi) 

throughout their life cycle is poorly understood but could have 

important implications for fisheries management. Relatively 

dense populations of juvenile Tanner crabs have been found 

in several areas within Glacier Bay, Alaska; these could be 

nursery areas from which maturing crabs disperse.

Objectives

Our objectives were to evaluate if geochemical signatures are imparted to the carapace during molt or to the 

muscle tissue during growth and, if so, to determine if they 

could serve as a natural fingerprint that identifies the area 

where molting or growth occurred. Geochemical signatures 

may reflect subtle elemental or isotopic compositional differences that arise from hydrologic, geologic, or nutritional 

variations in Glacier Bay (fig. 45).

Background

Elemental and isotopic variations in biota arise from differences in local environmental conditions. In some instances, 

these “geochemical fingerprints” are sufficiently unique to 

serve as life-history markers. Geochemical fingerprints have 

been used to distinguish stock and migration patterns for a 

variety of fish and marine invertebrates (Edmond and others, 

1989; DiBacco and Levin, 2000). Stable isotopic studies have 

been carried out on a variety of topics related to aquatic and 

terrestrial ecosystems (Fry and Sherr, 1984; Carmichael and 

others, 2004). Environmental conditions that may result in 

unique geochemical signatures include food source, carbon 

source (for example, shelf or oceanic), salinity and temperature differences, and differences in the local geology. 

The success of geochemical fingerprinting tools in other 

studies (that is, DiBacco and Levin, 2000) led us to consider 

the possibility that such signatures in Tanner crabs may aid 

in understanding their migration within Glacier Bay. Tanner 

crab life-history characteristics make them well suited for a 

geochemical fingerprinting approach. Female Tanner crabs do 

not molt again after they molt to sexual maturity. Therefore, 

if a female Tanner crab leaves the area where she molted to 

maturity (for example, a nursery area), the geochemical signature in her carapace could be used as a marker for the area 

in which she molted. In addition, isotopic variations in the 

muscle tissue could serve as an indicator of crab movement 

and thus could complement the geochemical information 
Element Cycling, Toxicity, and Health 81

from the carapace. For example, if crabs leave the nursery 

area after molting, the carapace should reflect the signature 

of the nursery area, whereas the muscle may reflect both the 

terminal molt and a more recent environment. Based on the 

geological and hydrological heterogeneity present in Glacier 

Bay (fig. 46) and the life history of the Tanner crab, there is 

a reasonable chance geochemical variations imparted to the 

crab body tissue can be used to determine the area where the 

terminal molt occurred.

Results and Conclusions

Elemental and isotopic differences were found in crabs 

collected from the five locations within Glacier Bay, and it 

appears promising that a geochemical fingerprint of location 

of molt may be identified (fig. 47; Wang and others, 2007). 

To fully evaluate the potential of geochemical fingerprinting as a tool in understanding crab movement within 

Glacier Bay, more work is necessary to examine the stability 

of the elemental and isotopic signature with time, changes 

of the isotopic signature with diet, isotopic signature of 

different prey types, the possibility of sex as a confounding factor, and the role of biogenic calcite on the elemental 

signature and isotopic signatures through separation of the 

calcite and chitin. 

Such work would have management application in 

area-based fisheries management (for example, marine 

protected areas and essential fish habitat designation) that 

requires an increased understanding of spatial processes, 

such as rearing areas and movement during the course 

of an organisms development. Long-term movements of 

juvenile Tanner crabs are very difficult to quantify because 

tags that can be reliably retained through the molt have not 

been developed. Movement of females and sublegal males 

cannot be detected in traditional tagging studies that use 

fisheries to recapture tagged animals based on sex and size 

regulations of the fishery. Multi-year sonic tagging studies

are expensive and relatively few animals can be tracked. 

If geochemical fingerprinting can eventually be used to 

determine movement with ontogeny, it will be an elegant, 

robust, relatively cost-effective tool that can achieve results 

in a short period of time (that is, one survey as opposed to 

several years of sonic tracking). 

Collaborators

Spencer Taggart and Jennifer Mondragon, U.S. Geological 

 Survey, Juneau, AK

Figure 45. Collection and sample preparation of Tanner crabs from Glacier Bay National Park. A, Tanner crab collection, B, carapace, 

and C, meat during sample preparation. (USGS photographs)

 A B

C
Wachusett Inlet Scidmore Bay Charpentier Inlet

BartlettCove

HughMiller

ALASKA

137°30' 137°00' 136°30' 136°00' 

58°30'

59°00'

Mineral occurrence within study area

Au

Fe, Ni?

Ag, Au

Cu

Cu, NiCu, Mo

Pb, Zn

Zn

Ag, Au, Cu

Mo

Ag

Fe

Mo, W

Ag, Cu, Pb

Cu, Fe, Ti

Ag, Pb, Zn

Pb, Zn

Sampling locations within bays

Snow and ice

Sedimentary rocks

Magmatic rocksMetamorphic rocks

EXPLANATION

0 1 KILOMETERS0 1 MILES

Base map from Geiselman and others (1997).

Figure 46. Sampling locations relative to generalized bedrock geology, and the locations of known mineral occurrences within Glacier Bay 
Element Cycling, Toxicity, and Health 83

Figure 47. Boxplots of A, ln Ca (logarithm 

calcium) concentration and B, ln Mo (logarithm 

molybdenum) concentration in carapaces 

based on the bay of origin and C, plots of delta 

N (nitrogen) compared to delta C (carbon) for 

the muscle and shell.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

–25.0 –20.0 –15.0 –10.0 –5.0

δ13C, in permil

δ15N, in permil

Charpentier Inlet

Hugh Miller Inlet

Bartlett Cove

Scidmore Bay

Wachusetts Inlet

Lower East Arm

Analytical uncertainty

Shell muscle

Shell

Intrasample

variability

Muscle

Intrasample

variability

One trophic

level

EXPLANATION

0.3

0.2

0.1

0.0

–0.1

–0.2

–0.3

Bartlett Cove

Charpentier

Hugh Miller

Scidmore

Wachusetts Inlet

 Size adjusted ln Ca

A

2

1

0

–1

–2

–3

Bartlett Cove

Charpentier

Hugh Miller

Scidmore

Wachusetts Inlet

Size adjusted ln Mo 

B

C

References Cited

Carmichael, R.H., Rutecki, Deborah, Annett, Brendan, Gaines, 

Emily, and Valiela, Ivan, 2004, Position of horseshoe crabs 

in estuarine food webs: N and C stable isotopic study of foraging ranges and diet composition: Journal of Experimental 

Marine Biology and Ecology, v. 299, p. 231–253.

DiBacco, Claudio, and Levin, L.A., 2000, Development and 

application of elemental fingerprinting to track the dispersal 

of marine invertebrate larvae: Limnology and Oceanography, v. 45, no. 4, p. 871–880.

Edmond, J.S., Moran, M.J., Caputi, N., and Morita M., 1989, 

Trace element analysis of fish sagittae as an aid to stock 

identification: Canadian Journal of Fisheries and Aquatic 

Science, v. 46, p. 50–54.

Fry, B., and Sherr, E.B., 1984, d13C measurements as indicators of carbon flow in marine and freshwater ecosystems: 

Contributions in Marine Science, v. 27, p. 13–47.

Geiselman, J., Dunlap J., Hooge, P., and Albert, D., eds., 1997, 

Glacier Bay ecosystem GIS CD-ROM set: Anchorage 

and Juneau, Alaska, U.S. Geological Survey and Interrain 

Pacific, 2 CD-ROM volumes.

Wang, Bronwen, Seal, R.R., Taggart, S.J., Mondragon, 

Jennifer, Andrews, Alex, Nielsen, Julie, Crock, J.G., and 

Wandless, G.A., 2007, Geochemical signatures as natural 

fingerprints to aid in determining Tanner crab movement in 

Glacier Bay National Park, Alaska, in Piatt, J.F., and Gende, 

S.M., eds., Proceedings of the Fourth Glacier Bay Science 

Symposium: U.S. Geological Survey Scientific Investigations Report 2007–5047, p. 97–101, at http://pubs.usgs.gov/

sir/2007/5047/pdf/sir20075047.pdf.
84 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Trace Metal Partitioning Between 

Sediments and Groundwater in the 

Basin-Fill Aquifer Surrounding Fallon, 

Nevada

By Lisa L. Stillings, Nicole K. Cutler, John K. McCormack, 

and Ralph L. Seiler

Issue and Scope

There has been relatively little research into the geochemical cycle of tungsten (W) in the environment. This became 

apparent during investigations into possible environmental 

causes of a childhood leukemia cluster in Fallon, Nevada. 

These studies found high concentrations of W in airborne dust, 

lichens, and in groundwater of the local basin-fill aquifers. An 

understanding of the processes that govern the occurrence of W 

in the environment requires knowledge of the speciation of W 

within solid phase minerals. The purpose of this research was 

to identify the spatial variation, concentration, and mineralogical phase association(s) of W and other trace metals commonly 

found in the basin-fill aquifer surrounding Fallon, Nevada.

Objectives

A thorough description of hydrogeochemical conditions 

in the basin-fill aquifer is key to understanding W and trace 

metal geochemical cycles in the study area. Water and sediment 

samples were collected from the same depth in the aquifer in 

order to evaluate the geochemical controls on solid and aqueous phase composition. The overall focus of the entire study 

is to address the hypotheses that redox levels in the aquifer 

will control the solid-solution partitioning and mineral phase 

association of W and other trace metals. Seiler and others 

(2005) proposed that Eh-pH conditions in groundwater of the 

basin-fill aquifers would promote reductive dissolution of iron 

and manganese oxyhydroxides thereby releasing adsorbed W 

into solution. The first objective of the study is to document 

the geochemistry and mineralogy of sediments in the basin-fill 

aquifer and to describe the solid phase partitioning of W and 

trace metals between the sediment fractions. Trace elements of 

interest include those that form oxyanions (W, molybdenum 

[Mo], chromium [Cr], arsenic [As], and uranium [U]) and 

cobalt (Co). 

Background

The current debate over the sources and sinks of W 

in the Carson Desert of Nevada began with investigations 

by the Centers for Disease Control and Prevention (CDC) 

into possible ties between a childhood leukemia cluster and 

environmental causes in Lahontan Valley, an agricultural area 

surrounding the city of Fallon, Nevada. In 2002, the CDC 

National Center for Environmental Health nominated W for 

toxicological and (or) fate and transport studies in order to 

investigate W sources and mobilization mechanisms. Environmental factors were eventually ruled out as the cause of 

the leukemia cluster in Fallon after extensive testing of water, 

soil, air and dust, and jet fuel (Koutsospyros and others, 

2006). However, the observations of increased W in tree-core 

samples, lichens, human blood and urine (CDC, 2003), and 

groundwater samples (Seiler and others, 2005) have prompted 

researchers to learn more about the geochemical cycle of W in 

the environment. 

The study area was located in Lahontan Valley where 

samples of aquifer sediment were collected from five drilling 

sites near domestic wells that exhibit a wide range of aqueous 

W concentration. Boreholes were drilled to access waterbearing sediment layers in the shallow (<13 meters (m) depth) 

and intermediate (≈13–50 m) aquifers. Aquifer sediments 

were collected with depth, at approximately 6-m intervals or 

at water-bearing layers, down to a maximum 37-m depth. One 

sediment sample was collected at the well-screen depth in the 

shallow aquifer, and four samples were collected at wellscreen depth in the intermediate aquifer.

Results and Conclusions

The analytical techniques of scanning electron microscopy–energy dispersive spectroscopy (SEM–EDS; Goldstein, 

2003) and X-ray diffraction (XRD; Bish and Post, 1989) were 

used to identify sediment mineralogy. Analyses showed that 

the samples contained quartz, plagioclase feldspar, potassium 

feldspar, augite, biotite (with titanium substitution), amphibole 

(hornblende, actinolite, and tremolite), ilmenite, hematite, and 

calcite. Amorphous iron coatings were identified on many of 

the grains and were interpreted to be ferric oxyhydroxides. 

Manganese coatings were only observed in two samples. 

Pyrite was observed in euhedral, anhedral, framboidal, and 

crystalline habits and was often observed in samples that 

contained iron oxides. Less abundant minerals include apatite, 

barite, calcite, olivine, rhodonite, siderite, sphalerite, and 

zircon. Diatoms of ≈10–100 micrometer (μm) size, including 

Surirella sp., and other calcareous microfossils were observed. 

Tungstate minerals were not detected, nor was W observed 

with the SEM–EDS while using the backscatter mode.

Solid phase bulk W concentrations range from 1.3 to 

7.9 milligrams per kilogram (mg/kg), with an analytical 

error of 5 percent based on duplicate sample analyses. Other 

transition metals with chemistries similar to W (Group 6B of 

the periodic table), Mo and Cr, had bulk chemistry concentrations ranging from 0.7 to 33.5 mg/kg and from 8 to 40 mg/kg, 

respectively. Bulk concentrations of As ranged from 6 to 

25 mg/kg, U from 1.4 to 4.5 mg/kg, and Co from 4.6 to 

16.1 mg/kg. Bulk W concentrations are positively correlated 

with bulk Cr, As, U, and Co values in the sediment. Bulk Mo 

concentrations were variable and did not correlate with bulk 

W concentrations.
Element Cycling, Toxicity, and Health 85

Table 5. Grain-size analysis.

[%, percent; <, less than; μm, micrometer; mm, millimeter]

Grain size

Sample % clay

(<2 μm)

% silt

(2–53 μm)

% sand

(53 μm–2 mm) Classification1

CDP39-12.2 19 3 78 sand

CDP39-29 3 78 19 sand

FCL43-12 7 25 68 sandy silt

FCL43-19.8 6 62 32 silty sand

FCL43-19.9 6 80 14 sand

FCL46-6.1 3 91 6 sand

FCL46-24.4 5 91 4 sand

FCL54-12.2 2 77 21 sand

FCL54-12.3 19 18 62 sandy silt

FCL54-13.7 1 74 25 sand

FCL54-24.4 1 84 15 sand

FCL54-30.5 2 76 22 sand

FPo01-6.1 42 4 54 clayey silt

FPo01-18.3 17 6 78 silt

FPo01-36.6 15 28 56 sandy silt

FPo01-36.7 18 31 51 sandy silt

1

Size classification from Shepard (1954).

Figure 48. Partitioning of trace elements among seven sediment fractions. Averages are 

calculated from 16 samples. Exch ions, exchangeable ions; MnOx, manganese oxides; 

c-FeOx, crystalline iron oxides nc-FeOx, noncrystalline iron oxides; OM, organic matter.

Sediment phases

Extraction percentage

0

20

Exch ions

Carbonates

MnOx

nc-FeOx

c-FeOx

OM

Sulfides

40

60 EXPLANATION

W

Mo

Cr

As

U

Co
86 Developing Integrated Methods to Address Complex Resource and Environmental Issues

The partitioning of W and trace metals within aquifer 

sediments was measured with a selective extraction procedure (SEP) designed to target the following seven sediment 

fractions (Amacher, 2003): exchangeable ions, carbonates, 

manganese oxides (MnO), noncrystalline iron oxides (ncFeO), 

crystalline Fe oxides (cFeO), organic matter (OM), and sulfides. Figure 48 compares the percent of each element found 

within each sediment fraction, where percent is calculated as 

percent

c

c

i z

i z

z

=

=

∑

,

,

1

7

(5)

where ci = average concentration of element i and z = SEP 

extraction step. Results indicate that (1) Mo was the only 

element with a significant percentage of its mass bound in the 

exchangeable ion fraction; (2) all elements except W associated with carbonates; (3) Mo and As were the only elements 

to significantly bind with MnO; (4) all elements were present 

in the ncFeO and cFeO fractions, but W exhibited the highest 

percentage in each; (5) W was the predominate trace metal 

to associate with OM; and (6) all elements except W were 

predominately associated with the sulfide fraction. 

Grain size classification (table 5; Shepard, 1954) shows two 

distinct groups of grain sizes in the sample set: sands and silts. 

Bulk concentrations of W, Cr, As, U, and Co are significantly 

higher in the silt samples than in the sand samples. The variability in bulk Mo concentrations was too great to show statistical 

difference between the grain sizes. Bulk median concentration of 

W in silt-size sediments, 5.3 mg/kg, was significantly different 

from the median concentration in sands, 1.9 mg/kg, as determined by a t-test at P value = 0.009. This observed partitioning 

of trace elements into the silt-size sediments is due to the chemical composition of the finer grained sediments. From the SEP it 

was determined that the main sediment phases to host trace elements contained inorganic and organic carbon, Fe, and S. All of 

these components are present in higher concentrations in the siltsize sediments. Mineralogic composition also varied with grain 

size. Ferrihydrite, pyrite, and calcite (secondary, precipitated in 

situ) were only identified primarily in finer grained samples.

In conclusion, no primary tungsten minerals (for example, 

scheelite) were found in the aquifer sediments. Instead, W, with 

bulk sediment concentrations of 1.3–7.9 mg/kg, partitioned into 

three sediment phases: noncrystalline and crystalline iron oxides 

(together referred to as FeO), and organic matter (OM). The 

variation in W concentration with grain size is due to increased 

concentrations of FeO and OM in the smaller size fraction.

Other trace elements (Mo, Cr, As, U, and Co) are found 

in the aquifer sediments in concentrations ranging from 0.7 to 

40 mg/kg. The concentrations of all of these elements, with 

the exception of Mo, correlate strongly with W concentration. 

The chemistry of W, however, is unique because, although the 

other trace metals are found predominately associated with the 

sulfides in aquifer sediments, W was found primarily in the 

FeO and OM sediment phases (Cutler and others, 2009).

Acknowledgments

The authors thank the homeowners in Lahontan Valley for permission to collect samples on their properties. We 

thank Paul Lamothe and Monique Adams of the USGS-MRP 

Analytical Laboratory for analysis of the leachate samples, 

and Robert Oscarson, USGS, for assistance with SEM. NKC 

acknowledges funding from a student research grant from the 

Geological Society of America, and from a USGS Cooperative 

Agreement, Number G09AC00075, awarded to the University 

of Nevada, Reno. 

Collaborators

Program of Hydrological Sciences and Department of 

 Geological Sciences and Engineering, University of 

 Nevada Reno

References Cited

Amacher, M.C., 2003, Manual of Methods: Open-File Report 

2003, USDA Forest Service, Intermountain Research Station, Forestry Sciences Laboratory, Logan, UT, 62 p.

Bish, D.L., and Post, J.E., eds., 1989, Modern powder diffraction: Mineralogical Society of America Reviews in Mineralogy, v. 20, 369 p.

Centers for Disease Control and Prevention (CDC), 2003, 

Cross-sectional exposure assessment of environmental contaminants in Churchill County, Nevada: Centers for Disease 

Control and Prevention, accessed May 20, 2008, at http://

www.cdc.gov/nceh/clusters/Fallon/study.htm.

Cutler, N.K., Stillings, L.L., and McCormack, J.K., 2009, 

Sediment phase associations of tungsten in the alluvial aquifers, Fallon, Nevada [abs.]: Geological Society of America, 

Abstracts with Programs, Vol. 41, No. 7, p. 328.

Goldstein, Joseph, 2003, Scanning electron microscopy and 

X-ray microanalysis: Kluwer Academic/Plenum Publishers, 

689 p.

Koutsospyros, A., Braida, W., Christodoulatos, C., Dermatas, D., and Strigul, N., 2006, A review of tungsten: From 

environmental obscurity to scrutiny. Journal of Hazardous 

Materials v. 136, p. 1–19.

Seiler, R.L., Stollenwerk, K.G., Garbarino, J.R., 2005, Factors 

controlling tungsten concentrations in ground water, Carson 

Desert, Nevada: Applied Geochemistry v. 20, p. 423–441.

Shepard, F.P., 1954, Nomenclature based on sand-silt-clay 

ratios: Journal of Sedimentary Petrology, v. 24, p.151–158.
Element Cycling, Toxicity, and Health 87

Bioaccessibility of Potentially Toxic 

Metals and Metalloids in Earth 

Materials

By Suzette A. Morman and Geoffrey S. Plumlee

Issue and Scope

Throughout our lifetime, we are exposed to a variety of 

soils, mineral dusts, and other earth materials that contain a 

variety of mineral or metal toxicants. Although we commonly 

think of contaminants as the result of only anthropogenic 

processes, natural processes can also concentrate potentially 

toxic elements with known human health risks such as arsenic, 

cadmium, and lead in rocks and soils. Both natural (weathering and winds) and anthropogenic processes (mining, smelting, and construction) may expose and promote distribution of 

these naturally occurring contaminants into the environment.

For example, the air we breathe, depending upon the season, where we are, and other factors, can contain a complex mix 

of airborne particulate matter (PM) derived from many different 

natural and anthropogenic sources. Although research has substantiated associations between PM exposure and cardiovascular 

and respiratory disease, it was focused on PM generated from 

anthropogenic sources. Few studies considered contributions 

from geogenic PM (produced from the Earth by natural processes, for example, volcanic ash, windborne ash from wildfires, 

and mineral dusts) or geoanthropogenic PM (produced from 

natural sources by processes that are modified or enhanced by 

human activities, for example, dusts produced from areas that 

have undergone desertification as a result of human practices).

In addition to inhalation of PM, ingestion can also be 

a primary pathway for exposure to earth materials such as 

soils, settled dust deposits, and flood sediments. Although 

geophagia, the purposeful consumption of soils, is still 

practiced in some cultures, most ingestion of earth materials 

is inadvertent. Inadvertent ingestion occurs through hand to 

mouth transfer, consumption of soil particles on improperly 

washed produce, or by swallowing of inhaled particles that 

have been trapped in mucus lining the respiratory tract and 

cleared into the throat.

Earth materials that are taken up by the body interact 

chemically with the body’s fluids encountered along the different exposure routes (fig. 49). These interactions strongly 

influence potential toxicity effects. For example some earth 

materials can contain bioaccessible toxicants that are readily 

released into the body’s fluids and are available for uptake by 

the body. Other earth materials can be toxic because they are 

biodurable (are insoluble in the body’s fluids), can persist in 

the body for years, and cause long-term toxicity effects.

Under the auspices of the U.S. Geological Survey Minerals and Health Project, the Development of Mineral Environmental Assessment Methodologies Project, and this project, 

we have collaborated with numerous colleagues in the earth 

and public health sciences to measure and interpret toxicologically relevant mineralogical, physical, geochemical, and bioaccessibility characteristics of many different earth materials. 

By elucidating these characteristics, we can help toxicologists 

and other public health specialists identify primary exposure 

routes of concern, how these materials may be taken up by the 

body, and their chemical behavior and toxicological properties 

once in the body.

Objectives

This project has helped fund the development of physiologically based extraction tests (PBETs), also called in vitro 

bioaccessibility assessments (IVBAs), which model the solubility behavior of diverse earth materials in fluids encountered 

along inhalation and ingestion exposure routes.

We have modified and adapted several commonly used 

PBETs covering a variety of simulated body fluid types and 

have explored their use in estimating exposures to potentially 

toxic metals in a wide array of naturally occurring earth materials and earth materials transformed for use by society. The 

results allow us to estimate what portion of a sample is soluble 

or bioaccessible and thus available to the body. The results also 

allow us to understand how mineralogy and processes such as 

weathering and transport may alter biosolubility. Through the 

use of these tests, our Minerals and Health Research Laboratory 

(see Laboratory Facilities and Capabilities section, this volume) 

provides valuable information on the solubility or bioaccessibility of elements present in a wide array of earth materials.

Background

Physiologically based extraction tests provide a quick 

and inexpensive alternative to animal or cell-line testing. Bioaccessibility testing was pioneered in the 1970s to 

explore the solubility of radionuclides in mine wastes and 

dusts. Since the 1970s, much of the focus has been on the 

development of PBETs to model the gastric and intestinal 

bioaccessibility of lead in mine wastes and contaminated 

soils, and PBETs to model the biosolubility of asbestos and 

man-made vitreous fibers in fluids lining the respiratory 

tract. These tests use fluids that are similar in composition 

and pH to those in the human body to evaluate what percentage of a metal or other element is soluble and thus available 

for uptake by the target organs such as the kidneys or liver. 

Although these tests do not measure the amount the body 

absorbs (bioavailability), the results are important for understanding how matrix, mineral, particle size, process, and 

speciation impact the solubility or bioaccessibility of often 

poorly understood earth materials.
88 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Results and Conclusions

Controls on metal mobility in soils, such as soil pH, 

organic carbon content, and absorption by clay minerals, are 

generally site specific, vary by metal, and may affect bioaccessibility as well. This is illustrated by our work comparing arsenic (As) concentrations in simulated gastric fluid extractions 

of dusts from a playa in the Mojave Desert to those in background soils. The bioaccessibility of As in the dusts, present 

with evaporative salts, was two to three times higher than we 

have measured in background soils. This increase is attributed 

to desorption and concentration of As from ferric oxides that 

coat silt and clays, whereas the As in soils remains bound. 

However, though matrix properties are important, the mineral 

form of the metal and the pH of the leaching solution also play 

an important role. For example, fluorosis (a disease marked by 

severe dental and bone problems) has been noted in livestock 

and wildlife following some volcanic eruptions and has been 

attributed to high levels of water-soluble fluoride in volcanic 

ash; the fluoride is either leached from the ash into water 

supplies that are then consumed by the animals or is directly 

taken up by animals that eat ash-coated forage. Water extraction tests are traditionally used to test fluoride release from 

volcanic ash but have been shown not to adequately predict 

the development of fluorosis in animals following some types 

of eruptions. Using a low pH (pH 1.5) simulated gastric PBET 

Figure 49. Schematic diagram illustrating exposure pathways and variability in body fluid types and compositions that can be 

encountered by earth materials (from Plumlee and Ziegler, 2006).

Stomach

(pH 1.5, electrolytes,

enzymes)

Large intestine

(near-neutral pH, reducing)

Small intestine

(near-neutral pH, reducing)

Primary bronchi

Nasal cavity

Oral cavity

Pharynx

Larynx

Trachea

Secondary bronchi

Terminal bronchioles

Alveolar duct, sac,

and alveoli

Cilia

Aqueous fluid

(near neutral pH, high PO2)

Alveolar macrophage

(acidic lysosomal fluids)

Capillary–plasma

(pH 7.4, moderately high

PO2, high proteins)

Lung fluid

(pH 7.4, high PO2,

mucoproteins, phospholipids)

Mucus

(mucoproteins, water)

Interstitial fluids

(pH 7.4; high Na,

low K; low proteins)

Intracellular fluids

(pH 7.4; high K, Mg, P)

Interstial fluids, plasma

(exposed at breaks in skin:

pH 7.4; plasma has high proteins)

Sweat

(acidic pH, high urea,

lactic acid, etc.)
Element Cycling, Toxicity, and Health 89

on ash samples from several volcanoes, we demonstrated that 

the higher pH (pH >5) water extractions may grossly underestimate the amount of bioaccessible fluoride in some types of 

volcanic ash (fig. 50).

To elucidate the processes that may alter metal solubility in long traveled dusts such as those from the Sahel region 

of Africa, we developed a new PBET method to analyze 

toxicant bioaccessibility in dusts from air filters collected at a 

source site in Africa as well from downwind locations in the 

Caribbean. In general, concentrations of elemental toxicants 

such as As exceeded the U.S. mean background concentration, and bioaccessibility increased downwind along the 

transect away from the origin in both the simulated gastric 

and lung fluid extractions.

We have also applied PBETs to examine roadside vegetation exposed to fugitive dusts generated from mining transport 

vehicles. These tests indicated that the bioaccessibility of lead 

and other metal toxicants varied by sample and by vegetation type. Bioaccessibility was greatest in vegetation samples 

for cadmium and zinc, and rinsing produced only moderate 

decreases that varied by plant type. Lead concentration and 

bioaccessibility were highest in the dust, likely related to 

weathering and oxidation, and lowest in the mine concentrate, 

a sulfide-bearing ore, with low bioaccessibility. This indicates 

that multiple processes, both biological and physical, may be 

involved at every site.

Earth scientists have a growing role in helping health 

scientists anticipate potential health issues associated with 

toxic metals and metalloids in diverse natural and anthropogenic earth materials and understanding the processes that 

enhance bioaccessibility, such as weathering and transport. In 

vitro bioaccessibility tests, or PBETs, are a useful assessment 

tool that can be easily applied to many different types of earth 

materials. They provide needed insights into how earth materials behave chemically in the body and how readily metal or 

metalloid toxicants may be released from the earth materials 

and become available for uptake by the body.

Collaborators

U.S. Geological Survey Minerals and Health Project, 

 Richard L. Reynolds, William Brumbaugh, and 

 Virginia Garrison.

Publications Funded in Part by This Project

Brumbaugh, W.G., Morman, S.A., and May, T.W., 2011, Concentrations and bioaccessibility of metals in vegetation and 

dust near a mining haul road, Cape Krusenstern National 

Monument, Alaska: Environmental Monitoring and Assessment, v. 182 (1–4), p. 325–340.

Morman, S.A., Garrison, V.H., Plumlee, G.S., Lowers, H.A., 

and Bunnell, J.E., 2009, Assessing concentration and 

bioaccessibility of potentially toxic elements in African 

dust [abs.]: Geological Society of America Abstracts with 

Programs, v. 41, no. 7, p. 554.

Morman, S.A., and Plumlee, G.S., 2010, In vitro physiologically based extraction tests of volcanic ash from diverse 

volcanoes [abs]: Cities on Volcanoes 6, Tenerife, Canary 

Islands, May–June 2010, http://www.ivhhn.org/meetings/

pastmeetings.html.

Morman, S.A., Reynolds, R.L., Reheis, Marith, Goldstein, 

Harland, Plumlee, Geoffrey, and Wolf, R.E., 2008, Bioaccessibility of toxic elements in dusts from dry saline lakes 

in the Mojave Desert [abs.]: Geological Society of America 

Meeting Abstracts with Program, v. 40, no. 6, p. 78.

Figure 50. Total fluoride, simulated gastric fluid (SGF) leach, and 

water-leach fluoride concentrations for volcanic ash samples.

100,000

10,000

1,000

100

10

1

0.1

Milligrams per kilogram

Oldoinyo Lengai,

Tanzania (2007)

Ilamatepec,

El Salvador (2005)

Mount St. Helens,

Washington (1980)

Halema’uma’u,

Hawaii (2008)

EXPLANATION

SGF

Water

Fluoride, total
90 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Diffusive Gradients in Thin Films 

and Biotic Ligand Models—Tools 

for Evaluating the Health of the 

Environment

By Laurie S. Balistrieri

Issue and Scope

Historical mining activities have left a legacy of metalenriched water and sediment in many watersheds in the 

United States. A major concern of regulators, land managers, 

and the public is the potential adverse impact of the metals on environmental health or, alternately, on the quality 

of air, water, and sediment and the health of humans, fish, 

wildlife, and other organisms living in these watersheds. The 

challenge for U.S. Geological Survey (USGS) scientists is 

to provide detailed information that links the distribution, 

behavior, and geochemical characteristics of metals to their 

availability and toxicity to living organisms. Understanding 

how geochemical pathways expose biota to metal toxicity is 

the foundation for other Federal and State agencies to (1) set 

standards for the quality of air, water, and sediment in the 

environment; (2) evaluate the best options for cleaning up 

contaminated sites; or (3) minimize risks of metal toxicity to 

the health of humans and other organisms.

Objectives

The project goals were to define the geochemical factors 

and processes that influence the toxicity of metals to aquatic 

organisms in watersheds affected by historical mining. A combination of sampling and modeling tools were used. Concentrations and chemical forms (or speciation) of dissolved metals 

were determined using traditional filtering methods, diffusive gradients in thin films (DGT), and computer modeling, 

whereas the health of aquatic organisms was evaluated using 

concentrations of dissolved metals, water-quality criteria, and 

biotic ligand models (BLMs). In addition, processes such as 

transport by water that redistributes metals throughout the 

environment and geochemical reactions that transform metals 

among their dissolved and particulate phases were examined. 

Each of the study sites had unique geochemical characteristics and together they provided information on dissolved 

metal behavior and toxicity to aquatic organisms for a wide 

range of environmental conditions. The study sites were as 

follows:

1. Copperas Brook and the Ompompanoosuc River that 

drain the Elizabeth Copper Mine Superfund Site in 

Vermont. Copperas Brook was very acidic (pH <3) 

and enriched in dissolved metals during the study and 

flowed into the slightly basic, pristine Ompompanoosuc 

River (pH ≈8). The study examined environmental conditions and health of aquatic organisms in the mixing 

and reaction zone just downstream of the confluence of 

the two rivers. 

2. South Fork of the Coeur d’Alene River and its tributaries, which flow through the Coeur d’Alene mining 

district in northern Idaho. Populations of fish are nonexistent or limited in these watersheds and appear to be 

affected by high concentrations of dissolved metal.

3. Silver Bow and High Ore Creeks, which, respectively, 

drain the Butte mining district and the abandoned Comet 

Mine in Montana. Diel (24 hour) changes in dissolved 

metal concentrations occur in these creeks, and an 

approach for evaluating toxicity to fish was developed 

for these dynamic systems. 

4. Upper Columbia River in northeastern Washington that 

is downstream of several smelter facilities. The effect 

of exchange between metal-enriched groundwater and 

upper Columbia River water on dissolved metal concentrations was assessed.

Background

Dissolved metal ions exist as free ions, complexes with 

inorganic anions or ligands (for example, carbonate, chloride, or sulfate), or as complexes with organic ligands, such 

as fulvic and humic acids. The relative concentrations of 

these various chemical forms of dissolved metals depend on 

the composition of the solution. Of importance to studies of 

environmental health is that chemical speciation of dissolved 

metals influences their toxicity to aquatic organisms. Generally, free metal ions are considered to be more toxic to aquatic 

organisms than metal-ligand complexes. 

DGT and BLMs are two tools used in our studies to 

define links among the compositions of natural waters, 

speciation of dissolved metals, and environmental health. 

DGT is a sampling method that involves transport by diffusion of dissolved metal ions through hydrogel to a resin 

that binds the free-metal ion. Concentrations of dissolved 

labile metal, which includes free ions and complexes with 

inorganic anions as well as some complexes with organic 

anions, depending on their size and ability to dissociate, are 

determined. Metals associated with colloidal and particulate 

phases do not enter the hydrogel because of their size. DGT 

also provides information about dissolved chemical speciation because the diffusion of metal-organic ligand complexes 

through the hydrogel is slower than diffusion of free ions 

and metal-inorganic ligand complexes. Therefore, a solution containing dissolved free-metal ions and complexes of 

metal with inorganic and organic ligands would contain less 

dissolved labile metal than if the solution had no organic 

ligands. In addition, DGT samplers continuously accumulate 

metal during deployment in water. This characteristic provides two advantages. First, low concentrations of dissolved 
Element Cycling, Toxicity, and Health 91

metals can be determined because the amount of metal 

accumulated on the resin depends on the time of deployment. 

The longer the deployment, the greater the amount of metal 

accumulated. Second, DGT provides time-integrated dissolved labile-metal concentrations, which are important in 

dynamic systems, such as mixing zones or during diel metal 

cycling, where dissolved metal concentrations can widely 

vary in time.

BLMs link chemical speciation to toxicity of dissolved 

metals. BLMs involve equilibrium speciation calculations 

that consider the interactions of free-metal ions with inorganic, organic, and biotic (biological receptors) ligands. The 

amount of metal that binds to the biotic ligand is related 

to toxicity and depends on the site-specific composition of 

water. Whether a specific metal is toxic or lethal depends on 

the sensitivity of the aquatic organism, such as fish or water 

fleas, to the amount of metal loading on the biotic ligands at 

each study site.

Results and Conclusions

Project scientists used multiple sampling and modeling tools to provide fundamental information on the pathways of metal exposure to aquatic organisms. These studies 

(1) evaluated critical processes that affect the distribution, 

concentration, and chemical forms of dissolved metals in the 

environment; (2) illustrated important links between chemical speciation of dissolved metals and their availability and 

toxicity to aquatic biota; and (3) identified those metals that 

most influence the quality of water and habitat for aquatic 

organisms at a given location. This information assists other 

Federal and State agencies in managing our Nation’s natural 

resources and minimizing risks of metal toxicity to the health 

of aquatic ecosystems. The main conclusions for each study 

site are as follows:

1. Dilution, precipitation of aluminum and iron-oxide minerals, and adsorption attenuate acid and dissolved metal 

concentrations downstream of the confluence of Copperas 

Brook and the Ompompanoosuc River in Vermont. DGT 

data suggest that almost all chemical forms of cadmium, 

copper, nickel, and zinc are inorganic near the confluence. 

Sites closest to the confluence have poor water quality and 

habitat primarily due to copper. For these sites, dissolved 

concentrations of copper exceed water-quality standards 

and BLM calculations for copper indicate toxic conditions 

for fathead minnows and water fleas. 

2. Chemical speciation calculations using the Windermere Humic Aqueous Model VI (WHAM VI) indicate 

that dissolved cadmium and zinc primarily exist as 

free-metal ions and metal-inorganic ligand complexes, 

whereas the main chemical forms of dissolved copper 

and lead are as metal-organic ligand complexes in the 

South Fork of the Coeur d’Alene River (fig. 51) and its 

tributaries in northern Idaho. Dissolved concentrations 

of copper and lead are below water-quality standards at 

all sites. In contrast, dissolved cadmium and zinc concentrations exceed water-quality standards, and calculations using BLMs indicate that zinc and, in some cases, 

cadmium ions are toxic to fish within and downstream 

of the mining district. 

3. The magnitude of diel changes in dissolved cadmium 

and zinc concentrations ranged from 64 to 77 percent 

and from 157 to 988 percent, respectively, in Silver 

Bow and High Ore Creeks in Montana during August 

2010. These variations are due to daily changes in 

temperature and biologically driven changes in pH 

that, in turn, affect adsorption and desorption reactions 

among dissolved metals and particulate phases. DGT 

determined time-integrated dissolved concentrations 

of metals in the creeks, which were used to estimate 

metal loading of biotic ligands using a multiple metal, 

competitive BLM. That loading was incorporated into 

a toxicity function that was related to survivability of 

fish. Fish mortality was predicted to be low in Silver 

Bow Creek and high in High Ore Creek.

4. Radon data indicated interaction between metalenriched groundwater and upper Columbia River 

(fig. 52 and fig. 53) water during daily changes in 

water levels by upstream dams. This interaction was 

not reflected in time-integrated dissolved concentrations of aluminum, cadmium, copper, manganese, lead, 

uranium, and zinc in the river as determined by DGT, 

presumably due to large dilution of inflowing groundwater by river water. 

Figure 51. Deployment of diffusive gradients in thin films 

(DGT) samplers in the Coeur d’Alene River in northern Idaho. 

(USGS photograph)
92 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Collaborators

Richard Blank, R.G. Blank Enterprises, LLC

Stephen Cox, U.S. Geological Survey

Christopher Mebane, U.S. Geological Survey

David Nimick, U.S. Geological Survey

Barbara Paul, University of Washington

Nadine Piatak, U.S. Geological Survey

Robert Seal, U.S. Geological Survey

Peter Swarzenski, U.S. Geological Survey

Selected References

Balistrieri, L.S., 2009, Dissolved and DGT labile metal concentrations—Comparisons among thermodynamic speciation models and implications for biotic ligand models [abs.]: 

Conference on DGT and the Environment, Sardinia, Italy, 

October 7–9, 2009.

Balistrieri, L.S., and Blank, R.G., 2008, Concentrations of 

dissolved and labile Cd, Cu, Pb, and Zn in the South Fork 

Coeur d’Alene River, Idaho—Comparisons among chemical equilibrium models and implications for biotic ligand 

models: Applied Geochemistry, v. 23, no. 12, p. 3355–3371.

Balistrieri, L.S., and Blank, R.G., 2009, Dissolved and labile 

concentrations of Cd, Cu, Pb, and Zn in the South Fork 

Coeur D’Alene River, Idaho—Comparisons among equilibrium models and implications for biotic ligand models 

[abs.]: American Chemical Society Annual Meeting, Salt 

Lake City, UT, March 22–26, 2009.

Balistrieri, L.S., Cox, S.E., and Swarzenski, P.W., 2011, Using 

diffusive gradients in thin films (DGT) to monitor dissolved labile concentrations of trace elements in the upper 

Columbia River, WA, USA [abs.]: 2011 Association for the 

Sciences of Limnology and Oceanography (ASLO) Aquatic 

Sciences Meeting, San Juan, Puerto Rico, http://aslo.org/

meetings/sanjuan2011/.

Balistrieri, L.S., Nimick, D.A., and Mebane, C.A., 2012, 

Assessing time-integrated dissolved concentrations and 

predicting toxicity of metals during diel cycling in streams: 

Science of the Total Environment, v. 425, p. 155–168.

Balistrieri, L.S., Seal, Robert, II, and Piatak, Nadine, 2005, 

Processes affecting dissolved, labile, and toxic metal 

concentrations during mixing of acid-mine drainage and 

ambient surface water downstream of the Elizabeth Copper 

Mine Superfund Site, Vermont [abs.]: Geological Society of 

America, Abstracts with Programs, v. 37, no. 7, p. 179.

Balistrieri, L.S., Seal, R.R., II, Piatak, N.M., and Paul, Barbara, 2007, Assessing the concentration, speciation, and 

toxicity of dissolved metals during mixing of acid-mine 

drainage and ambient river water downstream of the Elizabeth Copper Mine, Vermont, USA: Applied Geochemistry, 

v. 22, no. 5, p. 930–952.

Figure 52. Preparing to deploy diffusive gradients in thin films (DGT) 

samplers in the upper Columbia River in northeastern Washington 

in-line with flow from seepage meters. (USGS photograph)

Figure 53. Measuring radon in the upper Columbia River in 

northeastern Washington. Precipitation of iron oxide during 

exchange between metal-enriched groundwater and river water 

likely accounts for the red staining on the rocks. (USGS photograph)
Element Cycling, Toxicity, and Health 93

Influence of Organic Matter on Copper 

Toxicity in Streams Impacted by Mining

By Kathleen S. Smith and James F. Ranville

Issue and Scope

The concentration of dissolved metals in stream water 

commonly is elevated in mined and mineralized areas. The 

chemical speciation of these dissolved metals influences their 

potential toxicity to aquatic biota. Therefore, it is important to 

understand processes that influence the chemical speciation of 

metals so that their potential impact on the environment can be 

predicted and modeled.

Objectives

The primary objective of this study was to determine 

whether the chemical fractionation of natural organic matter (NOM) in mined and mineralized areas can affect copper 

toxicity to aquatic biota in streams.

Background

Mined and mineralized areas are fairly specialized 

geochemical systems. The chemical composition of water 

originating from mined and mineralized areas can be quite 

different from that of water originating from nonmineralized 

areas. Mined and mineralized areas commonly generate acidic 

water with elevated dissolved metal concentrations. Iron and 

aluminum can precipitate and coat the bottom of streams, 

especially downstream of confluences between impacted and 

relatively pristine streams. It is important to understand the 

processes that take place in these specialized systems so that 

potential environmental impacts can be anticipated and abated.

The chemical speciation of metals influences their potential toxicity to aquatic biota. The presence of NOM tends to 

decrease metal toxicity to aquatic biota because the NOM ties 

up some of the metals that otherwise would be bioavailable to 

the organisms. NOM consists of a mixture of biomolecules that 

have a broad spectrum of metal-binding sites and metal-binding affinities. McKnight and others (1992) demonstrated that 

NOM in stream water chemically fractionates in the presence 

of precipitating iron- and aluminum-oxide minerals. In this 

chemical fractionation, some of the dissolved NOM is removed 

from the water with precipitating iron- and aluminum-oxide 

minerals, and the remainder of the NOM stays dissolved in the 

stream water. The NOM that is removed with the precipitating iron and aluminum minerals is associated with the solid 

phase and consists of molecules that have strong metal-binding 

affinities, whereas the NOM that remains in the stream water is 

relatively depleted in strong metal-binding molecules. Therefore, chemical fractionation of NOM in stream water results in 

stream sediment that has NOM with substantial metal-binding 

capacity (although it may be tied up by complexation with the 

metal-oxide minerals) and stream water with NOM that has 

reduced metal-binding capacity.

The biotic ligand model (BLM) is a computer model that 

mathematically estimates the effects of water chemistry on the 

speciation of metals and their acute toxicity to aquatic biota 

(Di Toro and others, 2001; Smith and others, 2015). The BLM 

has been incorporated into the aquatic life ambient freshwaterquality criteria for copper (U.S. Environmental Protection 

Agency [EPA], 2007) and is being used to determine regulatory site-specific water-quality criteria for copper. Mined 

and mineralized sites present some challenges for the BLM 

because of their unusual geochemical conditions.

Results and Conclusions

We conducted copper toxicity studies in water amended 

with NOM samples collected and isolated by McKnight and 

others (1992) from below the confluence of a relatively pristine 

stream (Deer Creek, Colorado) and an acidic-metal-enriched 

stream (Snake River). Figure 54 shows the confluence and locations of the NOM sample collection. The NOM samples included 

(1) NOM from stream water that was collected below the confluence (Snake River dissolved, fig. 54)), and (2) NOM extracted 

from suspended sediment that was collected below the confluence 

(Snake River sediment, fig. 54). Our copper toxicity experiments 

were designed to test if the chemical fractionation of the NOM is 

significant enough to influence copper toxicity to aquatic biota.

We used standard EPA toxicity testing methods with water 

fleas (Ceriodaphnia dubia; photograph in fig. 55), a sensitive 

fresh water invertebrate commonly used in toxicity testing 

of contaminants. The measure of aquatic toxicity is the LC50, 

which is the metal concentration that is lethal to 50 percent of a 

group of test organisms within a given time frame (in this case, 

48 hours). Results of our toxicity tests are shown in figure 55. 

There is approximately four times greater toxicity in the test 

solutions amended with dissolved NOM (6 milligrams per liter 

[mg/L]) as compared with those amended with the sedimentderived NOM. The test solutions that contain the sedimentderived NOM have more copper bound to the NOM, which 

reduces the amount of copper available to the organisms thus 

reducing the copper toxicity. These results confirm that chemical fractionation of NOM in streams where iron and aluminum 

minerals precipitate can be an important factor in determining 

copper toxicity to stream-water biota. Detailed results from this 

work are reported in Smith and others (2014).

Our results highlight the importance of considering the 

potential effects of iron and aluminum when attempting to anticipate potential toxic effects of metals in mined and mineralized 

areas. Stream ecosystems downstream of iron- and aluminumrich streams may be more vulnerable to adverse effects from 

metal toxicity. Currently, the BLM does not take iron and aluminum concentrations or NOM fractionation into consideration. 

It is likely that a modified version of the BLM will need to be 

used to compute site-specific water-quality criteria and potential 

metal toxicity in many mined and mineralized areas.
94 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Collaborators

Department of Chemistry and Geochemistry, Colorado School 

 of Mines

Diane M. McKnight (INSTAAR, University of Colorado, 

 Boulder, Colorado)

Daniel J. Diedrich (NOAA Office of Response & Restoration, 

 Seattle, Washington)

Ruth M. Sofield (Western Washington University, Department

 of Environmental Sciences, Bellingham, Washington)

Figure 55. Toxicity test results for 

copper acute toxicity using water fleas 

in water amended with natural organic 

matter (NOM) isolated from water (blue) 

and suspended sediment (red) collected 

from the Snake River, Colorado. Note 

that there is more than four times greater 

toxicity measured in the test solution 

containing the stream-water NOM (LC50

= 13 micrograms per liter [μg/L] copper 

[Cu]) compared with the test solution 

containing the sediment NOM (LC50 = 60 

μg/L Cu). LC50, metal concentration lethal 

to 50 percent of a group of test organisms 

within a given time frame; mm, millimeter. EXPLANATION

Shift shows the effect of NOM

fractionation on copper toxicity

Snake River sediment

Snake River dissolved

LC50

1 mm

Less toxic

Water flea

Copper concentration, in micrograms per liter

Mortality, in percent

0

0

20

40

60

80

100

20 40 60 80 100 120 140 160

Figure 54. Sampling locations for natural organic matter (NOM) in 

the mixing zone below the confluence of the Snake River with Deer 

Creek near Montezuma, Summit County, Colorado. (Photograph 

by Philip Hageman, USGS) The “Snake River dissolved” NOM 

sample was collected from the stream water and the “Snake River 

sediment” NOM sample was extracted from iron- and aluminumrich suspended sediment.

Snake River Dissolved

(dissolved NOM)

Snake River Sediment

(NOM in suspended iron and

aluminum oxides)

Higher pH

water (pH >7)

(Deer Creek) Acidic

water (pH <5)

(Snake River)
Element Cycling, Toxicity, and Health 95

Selected References

Di Toro, D.M., Allen, H.E., Bergman, H.L., Meyer, J.S., 

Paquin, P.R., and Santore, R.C., 2001, Biotic ligand model 

of the acute toxicity of metals 1. Technical basis: Environmental Toxicology Chemistry, v. 20, p. 2383–2396.

McKnight, D.M., Bencala, K.E., Zellweger, G.W., Aiken, 

G.R., Feder, G.L., and Thorn, K.A., 1992, Sorption of 

dissolved organic carbon by hydrous aluminum and iron 

oxides occurring at the confluence of Deer Creek with the 

Snake River, Summit County, Colorado: Environmental 

Science & Technology, v. 26, p. 1388–1396.

Ranville, James, Blumenstein, Eric, Adams, Marty, Choate, 

LaDonna, Smith, Kathleen, and Wildeman, Thomas, 2006, 

Integrating bioavailability approaches into waste rock 

evaluations: Proceedings of the Seventh International Conference on Acid Rock Drainage (ICARD 7), St. Louis, Mo., 

March 26–30, 2006, p. 1642–1653.

Smith, K.S., Balistrieri, L.S., and Todd, A.S., 2015, Using 

biotic ligand models to predict metal toxicity in mineralized systems (Review Paper): Applied Geochemistry, 

v. 57, p. 55–72, http://dx.doi.org/10.1016/j.apgeochem.2014.07.005.

Smith, K.S., Ranville, J.F., Adams, M.K., Choate, L.M., 

Church, S.E., Fey, D.L., Wanty, R.B., and Crock, J.G., 

2006, Predicting toxic effects of copper on aquatic biota in 

mineralized areas by using the biotic ligand model: Proceedings of the Seventh International Conference on Acid 

Rock Drainage (ICARD 7), St. Louis, Mo., March 26–30, 

2006, p. 2055–2077.

Smith, K.S., Ranville, J.F., Diedrich, D.J., McKnight, D.M., 

and Sofield, R.M., 2009, Consideration of iron-organic matter interactions when predicting aquatic toxicity of copper in 

mineralized areas: Proceedings of Securing the Future and 

Eighth International Conference on Acid Rock Drainage 

(ICARD8), Skellefteå, Sweden, June 22–26, 2009, 9 p.

Smith, K.S., Ranville, J.F., Lesher, E.K., Diedrich, D.J., 

McKnight, D.M., and Sofield, R.M., 2014, Fractionation of 

fulvic acid by iron and aluminum oxides—Influence on copper toxicity to Ceriodaphnia dubia: Environmental Science 

and Technology, v. 48 (20), p. 11934–11943, http://dx.doi.

org/10.1021/es502243m.

U.S. Environmental Protection Agency, 2007, Aquatic 

life ambient freshwater quality criteria—Copper: 2007 

revision: U.S. Environmental Protection Agency, EPA–

822–R–07–001.

Detection of Potentially AsbestosBearing Rocks Using Imaging 

Spectroscopy

By Gregg A. Swayze and Raymond F. Kokaly

Issue and Scope

Naturally occurring asbestiform fibers are potential hazards to human health because of their link to mesothelioma, 

lung cancer, and asbestosis (see for example, Van Oss and 

others, 1999). Among the minerals of concern are chrysotile 

(a member of the serpentine group), several fibrous forms 

of amphiboles (that is, actinolite, anthophyllite, crocidolite, 

cummingtonite, grunerite [otherwise known as amosite], 

tremolite, richterite, and winchite) and a fibrous zeolite called 

erionite. These minerals occur in many places, primarily in 

States along the east and west coasts of the United States 

(Van Gosen, 2007). Issues with naturally occurring asbestos (NOA) have made news headlines in the Eldorado Hills 

community in the foothills of the Sierra Nevada in California 

(Bowman, 2004). In central and northern California, chrysotile and fibrous amphiboles like tremolite and actinolite are 

dominantly, but not exclusively, associated with serpentinite and ultramafic rocks, which are common in the Sierra 

Nevada, Coast Ranges, and Klamath Mountains (fig. 56A). 

Many suburban communities are expanding into areas underlain by these rocks. Pan and others (2005) have identified 

an increased risk of mesothelioma among people living near 

sources of NOA in California. Consequently, it is important 

that these rock types be identified to help reduce the public’s 

exposure to potentially NOA-bearing dust generated during 

building and outdoor activities.

Objectives

Imaging spectroscopy, a new type of remote sensing, can be used to help identify serpentine- and tremolite/

actinolite-bearing rocks, which potentially contain NOA, in 

areas where current geologic mapping is limited. The U.S. 

Geological Survey (USGS) and the California Geological 

Survey conducted a joint study to test the effectiveness of 

data collected by the airborne visible/infrared imaging spectrometer (AVIRIS) for mapping the distribution of potentially 

asbestos-bearing serpentinite and ultramafic rocks (Swayze 

and others, 2009). Spectral identification of minerals exposed 

in rock outcrops is a direct way of detecting potentially 

asbestos-bearing minerals; spectrally mapping vegetation 

cover that prefers to grow on these rocks is an indirect way 

of detecting potentially asbestos-bearing minerals. The main 

study area is located in western El Dorado County in the 

Sierra Nevada (fig. 56B).
96 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Background

AVIRIS measures light reflected from the surface in 224 

spectral channels from the ultraviolet into the near-infrared 

(0.38 to 2.5 microns). Data were collected on August 25, 2001, 

from an aircraft that was flown at 5,300 meters (m) altitude, 

producing 4-m pixels on the ground and images with swaths of 

about 2.5 to 3.0 kilometers (km), depending on surface elevation. Data were calibrated to apparent reflectance and analyzed 

to map mineralogy and vegetation using the USGS Tetracorder System (Clark and others, 2003). Color-coded maps of 

asbestos-related mineralogy and vegetation were produced for 

five AVIRIS flight lines, two of which will be discussed here.

Although reflectance spectra of the serpentine minerals lizardite, chrysotile, and antigorite are distinct from those 

of nonserpentine group minerals, they have similarly shaped 

spectral absorptions in the 2.3-micron region (fig. 57A). 

Because of their spectral similarity and because chrysotile 

was a minor component of the serpentinite at sites that were 

visited, chrysotile was grouped with the more abundant nonfibrous varieties of serpentine (that is, lizardite and antigorite) 

on the mineral maps. The spectral distinction between tremolite and magnesium (Mg)-rich actinolite can be subtle at 

AVIRIS spectral resolution, and both are spectrally similar to 

talc but can be easily distinguished from the main 2.33-micron 

absorption of serpentine minerals (fig. 57A). Because actinolite and tremolite spectrally resemble talc and because these 

minerals can occur together, they were combined into a single 

spectral category called talc/tremolite-actinolite (T/TA) to 

simplify spectral mapping.

Results and Conclusions

The spectral map of the westernmost AVIRIS flight 

line, collected over the densely vegetated Flagstaff Hill area 

(fig. 57B), shows mineral exposures consist of serpentine + 

minor dry vegetation (red) and T/TA (yellow) along unpaved 

roads and in quarries. At the southern end of the flight line, 

these units are well exposed along the Folsom Lake shoreline 

during low-water conditions (fig. 57C). Exposures on both 

shores were field checked and verified to be chrysotile-bearing 

Figure 56. Ultamafic rocks in California. A, Ultramafic rocks (black) are more likely to contain naturally occurring 

asbestos. B, Areas more likely to contain asbestos (dark gray) and associated fault zones for western El Dorado 

County, California. Rectangles show areas imaged by airborne visible/infrared imaging spectrometer (AVIRIS). 

WBMF = West Bear Mountains fault; EBMF = East Bear Mountains fault; MFZ = Melones fault zone. Figure 

modified from Churchill and Hill (2000), Churchill and others (2000), and Swayze and others (2009).

San

Francisco

EL DORADO COUNTY

(WESTERN PORTION)

Garden

Valley

Flagstaff Hill

El Dorado

Hills

Placerville

WBMF

Iron Mtn.

Sacramento Foothills Sierra Nevada

Coast Ranges

Klamath

Mountains

Los Angeles

A B

MFZ

MFZ

121° 121°40’

39°

38°30’

0 10 KILOMETERS

0 6 MILES

0 200 KILOMETERS

0 200 MILES

N
Element Cycling, Toxicity, and Health 97

Figure 57. Reflectance spectra of serpentine minerals and color-coded AVIRIS maps of asbestos-related mineralogy and vegetation. 

A, Vibrational absorption features in spectra of reference minerals associated with serpentine deposits in El Dorado County, California. 

Spectra are offset for clarity; vertical lines mark positions of diagnostic tremolite and serpentine (for example, chrysotile) absorptions. 

B, Map of potentially asbestos-bearing minerals, serpentine/vegetation mixtures, and chaparral vegetative cover for a portion of the 

Flagstaff Hill airborne visible/infrared imaging spectrometer (AVIRIS) flight line. Vegetation category (green) refers to areas where the 

spectral signatures of minerals are obscured by vegetation other than chaparral. C, Details of Iron Mountain area marked in B. Sites 

marked ED03-7A and ED03-3A are collection locations for samples shown in E and F; sites marked S1 and S2 correspond to collection 

locations of samples with spectra shown in D. E and F, Secondary electron images of chrysotile asbestos and fibrous to asbestiform 

tremolite from locations shown in C. E, Laboratory spectra of samples from, and AVIRIS spectra of, areas S1 and S2 along the shoreline 

shown in C. Figure modified from Swayze and others (2009).

IRON

MOUNTAIN

E

20 μm 

Chrysotile ED03-7A

S2

S1

ED03-7A

ED03-3A

B C

IRON

MOUNTAIN

F

Tremolite ED03-3A

Chrysotile

Tremolite

Talc

Lizardite

Antigorite

 0.0

 0.5

 1.0

 1.5

 2.0 2.1 2.2 2.3 2.4 2.5

Magnesiohornblende/

actinolite

Wavelength, in micrometers

Scaled reflectance

A

 2.0 2.1 2.2 2.3 2.4 2.5

 0.10

 0.15

 0.20

 0.25

Talc (S1)

Talc/tremoliteactinolite

Field

AVIRIS (S1)

Field

AVIRIS (S2)

Chrysotile (S2)

Serpentine

Scaled reflectance

Wavelength, in micrometers

D

121°05’ 121°5’

38°48’

38°45’

38°46’

50 μm 

Folsom Lake

Folsom Lake

EXPLANATION

Chaparral

Serpentine + major dry vegetation

Serpentine + minor dry vegetation

Serpentine

Vegetation

Other material

Encloses areas more likely to contain

 natural occurrences of asbestos

 (Churchill and others, 2000)

Talc/tremolite-actinolite

Flagstaff Hill

0 0.5 KILOMETERS 0 0.2 KILOMETERS
98 Developing Integrated Methods to Address Complex Resource and Environmental Issues

serpentinite (fig. 57D) and tremolite-talc schist. Chrystotile 

tremolite, as determined by electron probe microanalysis, 

ranged from prismatic to fibrous over a distance of a few 

meters (fig. 57E and 57H). Because talc is more abundant than 

tremolite in the schist, AVIRIS spectra from these areas match 

reference spectra of talc instead of tremolite-actinolite. 

Areas more likely to contain NOA, identified by 

Churchill and others (2000) using traditional field investigation methods, are shown by white-line polygons in figure 57. 

These polygons enclose previously mapped ultramafic rocks, 

serpentinite, and their associated soils. Results of this spectral 

mapping test show that nearly all of the high-density clusters 

of pixels that mapped as serpentine, serpentine + minor dry 

vegetation, and T/TA either fall inside or within a few hundred 

meters of these boundaries except where transported by human 

activities or exposed by low-water condition of Folsom Lake. 

The spectral signatures of chaparral species were studied 

to determine if they could be used to indirectly identify areas 

of serpentine. Although not strictly confined to serpentine, 

these species have a local affinity for serpentine (Kruckeberg, 

1984). In the Flagstaff Hill image (fig. 57B), 96 percent of 

the detected chaparral falls within the polygon areas based on 

spatial analysis. 

We investigated the effects of variable grass cover on 

the spectral identification of underlying serpentine using the 

AVIRIS flight line over the Garden Valley area (fig. 58A). 

The 2.3-micrometer (μm) absorption feature of dry grass 

coincides very closely with the position of the serpentine 

2.33-μm absorption (fig. 58B) making spectral identification difficult. We used the method described in Karnieli and 

others (2001) for identifying multiple spectral components 

in a pixel, which involved adding a spectrum of serpentine 

to that of grass in 10 percent increments. The serpentine and 

grass spectra used for the mixtures were measured in the 

field with a portable spectrometer and convolved to AVIRIS 

spectral resolution (figs. 58B and 58C) for use as reference 

spectra. Grass and serpentine mixtures with a grass fraction 

greater than 20 percent were detected over large portions of 

the Garden Valley study area; on the spectral map, orange 

color-coded pixels indicate areas with approximately 30 

to 80 percent dry grass cover on serpentinite (fig. 58A). In 

grassy areas where serpentine composes approximately 

10 percent or less of the exposed surface, the serpentine 

spectral features are too weak to allow detection with this 

spectral mixture method.

The vegetation categories are an important component 

of the Flagstaff Hill and Garden Valley spectral maps because 

chaparral and serpentine/grass mixtures cover at least half of 

the area within the polygons, considerably more area than is 

covered by rock exposures. Spectral maps that integrate information from substrate-dependent vegetative classification and 

lithologically independent mineral identification can be used 

as a tool for delineating areas more likely to contain NOA. 

These maps can also be used to identify roads surfaced with 

serpentine aggregate, locate areas in need of dust control, and 

help fill gaps in geologic mapping where access is limited. 

Collaborators

California Geological Survey (provided matching funds for

 AVIRIS data collection)

National Aeronautics and Space Administration 

California Institute of Technology/Jet Propulsion Laboratory 

Publications Funded in Part by This Project

Swayze, G.A., Higgins, C.T., Clinkenbeard, J.P., Kokaly, 

R.F., Clark, R.N., Meeker, G.P., and Sutley, S.J., 2004, 

Preliminary report on using imaging spectroscopy to map 

ultramafic rocks, serpentinites, and tremolite-actinolitebearing rocks in California: U.S. Geological Survey 

Open-File Report 2004–1304, 20 p., at http://pubs.usgs.gov/

of/2004/1304/.

Swayze, G.A., Higgins, C.T., Clinkenbeard, J.P, Kokaly, 

R.F., Clark, R.N., Meeker, G.P., and Sutley, S.J., 2004, 

Preliminary report on using imaging spectroscopy to map 

ultramafic rocks, serpentinites, and tremolite-actinolitebearing rocks in California: California Geological Survey Geologic Hazards Investigation 2004–01, 20 p., 

http://www.conservation.ca.gov/cgs/geologic_hazards/

hazardous_minerals/Pages/aviris.aspx.

Swayze, G.A., Kokaly, R.F., Higgins, C.T., Clinkenbeard, J.P., 

Clark, R.N., Lowers, H.A., and Sutley, S.J., 2009, Mapping 

potentially asbestos-bearing rocks using imaging spectroscopy: Geology, v. 37, no. 8, p. 763–766, http://geology.

gsapubs.org/content/37/8/763.full.

References Cited

Bowman, Chris, 2004, EPA to test kid’s asbestos exposure: 

The Sacramento Bee, August 15, 2004.

Churchill, R.K., Higgins, C.T., and Hill, Bob, 2000, Areas 

more likely to contain natural occurrences of asbestos in 

western El Dorado County, California: California Department of Conservation, Division of Mines and Geology, 

Open-File Report 2000–002, 66 p.

Churchill, R.K., and Hill, R.L., 2000, A general location guide 

for ultramafic rocks in California—Areas more likely to 

contain naturally occurring asbestos: California Department 

of Conservation, Division of Mines and Geology, Open-File 

Report 2000–19, 7 p.

Clark, R.N., Swayze, G.A., Livo, K.E., Kokaly, R.F., Sutley, 

S.J., Dalton, J.B., McDougal, R.R., and Gent, C.A., 2003, 

Imaging spectroscopy—Earth and planetary remote sensing 

with the USGS Tetracorder and Expert Systems: Journal of Geophysical Research, v. 108, no. E12, 5131, doi: 

0129/2002JE001847.
Element Cycling, Toxicity, and Health 99

Figure 58. Determination of the effects of variable grass cover on spectral identification of underlying 

serpentine in the Garden Valley study area. A, Map of potentially asbestos-bearing minerals, serpentine/

vegetation mixtures, and chaparral vegetation cover for a portion of the Garden Valley quarry airborne visible/

infrared imaging spectrometer (AVIRIS) flight line. B, Field spectra of serpentine/grass areas marked in C, and 

an AVIRIS spectrum for an area of chaparral covered by the Flagstaff Hill AVIRIS flight line. Spectra are offset 

for clarity. Reflectance at 1.00 micrometer is given. Channels in wavelength regions of strong atmospheric 

absorptions were deleted from the spectra (dashed lines). C, Photograph of the serpentine/grass field site 

along road right-of-way labeled in A, Arrows on the photograph indicate where field spectra were measured. 

Inset photographs were taken looking straight-down; all have the same scale. Figure modified from Swayze 

and others (2009).

0.25

0.22

0.23

0.18

0.1

0.5 1.0 1.5 2.0 2.5

B

AVIRIS

Field

Field

Field

A C Reflectance

Serpentine/grass mix

Grass

Flagstaff Hill

chaparral

Serpentine

Chlorophyll

absorption

2.1

and

2.3

bands

Wavelength, in micrometers

120°53’

38°49’ 38°50’

EXPLANATION

Chaparral

Serpentine + major dry vegetation

Serpentine + minor dry vegetation

Serpentine

Vegetation

Other material

Edge of AVIRIS flight line

Talc/tremolite-actinolite

Encloses areas more likely to contain

 natural occurrences of asbestos

Garden

Valley

quarry

Serpentineaggregate

covered road

Serpentine/grass

field site

0 0.5 KILOMETERS

Serpentine/grass

field site

Serpentine/

grass mix

Grass

Serpentine

0 5 CENTIMETERS
100 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Karnieli, A., Kokaly, R.F., West, N.E., and Clark, R.N., 2001, 

Remote sensing of biological soil crusts, in Belnap J., and 

Lange, O.L., eds., Biological soil crusts: Structure, function 

and management: Berlin, Springer-Verlag, Ecological Studies, v. 150, p. 431–456.

Kruckeberg, A.R., 1984, California serpentines—Flora, 

vegetation, geology, soils, and management problems: Los 

Angeles, University of California Press, 180 p.

Pan, X.L., Day, H.W., Wang, Wei, Beckett, L.A., and Schenker, M.B., 2005, Residential proximity to naturally occurring asbestos and mesothelioma risk in California: American Journal of Respiratory and Critical Care Medicine, v. 

172, p. 1019–1025.

Swayze, G.A., Kokaly, R.F., Higgins, C.T., Clinkenbeard, J.P., 

Clark, R.N., Lowers, H.A., and Sutley, S.J., 2009, Mapping 

potentially asbestos-bearing rocks using imaging spectroscopy: Geology, v. 37, no. 8, p. 763–766, http://geology.

gsapubs.org/content/37/8/763.full.

Van Gosen, B.S., 2007, The geology of asbestos in the United 

States and its practical applications: Environmental & Engineering Geoscience, v. 13, no. 1, p. 55–68.

van Oss, C.J., Naim, J.O., Costanzo, P.M., Giese, R.F., Jr., Wu, 

W., and Sorling, A.F., 1999, Impact of different asbestos 

species and other mineral particles on pulmonary pathogenesis: Clays and Clay Minerals, v. 47, no. 6, p. 697–707.
Figure 59. Difficulties with water sampling at abandoned mine 

site in late spring. (USGS photograph)

Figure 60. MiniSipper with electronics housing, sample coil, and 

gas (nitrogen, N2) bag. (USGS photograph)

Objectives

The goal of this research is to develop and apply a new 

water sampling technology (MiniSipper) that overcomes the 

limitations of currently available automated samplers. The 

MiniSipper is a small, light, low-cost, high-capacity, longduration, in-stream water sampler developed by the U.S. 

Geological Survey (USGS). MiniSippers are currently used 

to study the effects of acid-mine drainage, evaluate the effectiveness of abandoned mine cleanup efforts, and to monitor 

postwildfire watersheds.

Background

The MiniSipper is a submersible instrument designed 

to collect small sample volumes at programmed intervals 

(fig. 60). The MiniSipper injects 5-milliliters (mL) water 

samples into a long Teflon sample coil. Samples are filtered 

and preserved with nitric acid, and adjacent samples are 

separated by a nitrogen gas bubble. More than 250 of the 

5-mL water samples can be loaded into the sample coil. After 

recovery, samples are pumped out of the sample coil and are 

analyzed by high sensitivity multi-element methods. The 

MiniSipper can operate unattended for more than 12 months 

and can be deployed under surface ice for over-winter and 

snowmelt-runoff sampling. The long deployment duration and 

large number of samples collected greatly reduces fieldwork 

costs making the MiniSipper ideal for remote-site monitoring 

(Chapin and Todd, 2012). 

MiniSippers have been deployed in support of an U.S. 

Environmental Protection Agency (EPA) project evaluating 

Hydrology and Water Quality

MiniSipper—New, Long-Duration, 

Automated, In Situ Sampler for HighResolution Water-Quality Monitoring

By Thomas P. Chapin and Andrew S. Todd

Issue and Scope

Water-quality monitoring is critical to our understanding 

of the fate and transport of elements in watersheds. Monitoring 

provides researchers, resource managers, and policy makers 

with the data needed to understand the processes that affect 

water quality, monitor the health of our waters, and evaluate 

the effectiveness of land-use practices. Water-quality monitoring programs typically collect a sample per month in accessible areas whereas remote areas are sampled a few times per 

year during accessible periods (for example, summer). These 

samples are typically collected by hand, which is very labor 

and cost intensive. Watersheds, however, can experience large 

changes in water flow during snowmelt runoff or rainstorms 

and these transient events are rarely captured by traditional 

sampling strategies, especially in remote inaccessible areas. 

Automated water samplers are available, but these instruments 

are typically large, heavy, collect 24 samples, and are not well 

suited to sampling in freezing conditions or areas that are difficult to access (fig. 59).
102 Developing Integrated Methods to Address Complex Resource and Environmental Issues

toxic metal inputs from the Standard Mine, located at an 

elevation of 11,000 feet near Crested Butte, Colorado. The 

abandoned mine site is accessible by four-wheel-drive vehicle 

during the summer months but is very difficult to access in 

winter (November–June). The mine watershed drains into a 

creek that is a municipal drinking-water supply, so toxic metal 

inputs from the mine require close monitoring. The Standard 

Mine is a Superfund site, and the EPA is interested in costeffective, high-resolution sampling that can characterize the 

major processes that affect the flux of toxic metals from the 

mine and guide EPA remediation efforts.

Results and Conclusions

Metal concentrations at the Standard Mine show distinct 

seasonal variations. During fall and winter, water issuing 

from the Standard Mine has high conductivity and zinc (Zn) 

levels, low aluminum (Al) levels, and a flow rate of <20 liters/

minute (fig. 61). In mid-April 2010, a transient snowmelt 

pulse increased the water flow, Al and Zn concentrations, and 

decreased conductivity. An early May snowstorm dropped temperatures and reduced snowmelt runoff resulting in decreased 

Al, Zn, water flow, and conductivity. The major snowmeltrunoff event started in late May with a transient spike in Al 

concentrations and then a dilution of mine waters resulting in 

decreasing Al, Zn, and conductivity values during peak runoff 

in mid-June. After peak runoff, Al concentrations continued to 

decrease while Zn concentrations and conductivity increased. 

Conditions in late fall show low Al concentrations and water 

flow with high Zn and conductivity values. Summer rainstorms 

did not significantly affect metal concentrations at the Standard Mine, but we have observed significant storm responses 

at other mines. The EPA is using the MiniSipper metal data to 

help design water-treatment options for the Standard Mine.

The MiniSipper deployed at the Standard Mine was able 

to capture details of the changes in metal concentrations that are 

almost impossible to monitor with standard sampling methods. 

The high-sample capacity and long deployment duration of the 

MiniSipper greatly increased sample collection (≈200 samples) 

while decreasing field-visit costs over this year-long period. 

0

100

200

300

400

500

600

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

Nov. 1 Dec. 11 Jan. 21 Mar. 2 Apr. 12 May 22 July 2 Aug. 11 Sept. 21 Oct. 31

Al (x10)−Zn, in micrograms per liter

Conductivity, in microsiemens per centemeter−Flow, in liters per minute

Date

2009 2010

Al x10

Zn

Cond

Flow

EXPLANATION

Figure 61. Year-long record of aluminum (Al×10), zinc (Zn), flow, and conductivity at the Standard 

Mine. More than 200 MiniSipper samples were analyzed.
Hydrology and Water Quality 103

MiniSippers have also been deployed deep underground in 

abandoned mines and in watersheds impacted by wildfires. A 

new instrument, the Borehole MiniSipper, has been deployed 

in 2-inch monitoring wells. Current development efforts are 

focused on incorporating event-response sampling where sudden changes in depth or conductivity, such as those associated 

with large rainstorms, will trigger changes in the sampling 

rate. With event-trigger capability, the MiniSipper will be an 

extremely versatile instrument that provides monitoring program with high-resolution, long-duration water sampling.

Collaborators

U.S. Environmental Protection Agency

Great Sand Dunes National Park

Selected References

Chapin, T.P., and Todd, A.S., 2010, MiniSipper—A new highcapacity, long-duration, automated in-situ water sampler for 

acid mine drainage monitoring [abs.]: Geological Society of 

America Abstracts with Programs, v. 42, no. 5, p. 203.

Chapin, T.P., and Todd, A.S., 2010, MiniSipper—A new highcapacity, long-duration, automated in-situ water sampler 

[abs.]: 2010 National Water Quality Monitoring Council 

Conference, Denver, CO, April, 2010.

Chapin, T.P., and Todd, A.S., 2011, MiniSipper—A new highcapacity, long-duration, automated in-situ water sampler for 

fire science monitoring [abs.]: American Chemical Society 

National Fall Meeting, Denver, CO, August 2011.

Chapin, T.P., and Todd, A.S., 2012, MiniSipper: A new in situ 

water sampler for high-resolution, long-duration acid mine 

drainage monitoring: Science of the Total Environment, 

v. 439, p. 343–353, doi:10.1016/j.scitotenv.2012.07.083.

Chapin, T.P., Todd, A.S., and Crock, J.G., 2009, MiniSipper—

A new high-capacity, long-duration, automated in-situ water 

sampler [abs.]: 2009 Geoanalysis Conference, KwazuluNatal, South Africa, September, 2009.

Mapping the Environment—Pollution, 

Organics, and Bacteria

By Roger N. Clark

Issue and Scope

Many materials can be found in our environment, and 

some of them are not desirable, for example, pollution. Most 

compounds have chemical bonds that may be detected with 

spectroscopy through absorption or emission of light at certain 

wavelengths. If the positions of the absorptions/emissions 

in the spectrum occur at wavelengths that may be observed 

through the Earth’s atmosphere, the compounds may be 

detected and mapped remotely (typically from high-altitude 

aircraft or satellites). Here we give some examples of detecting and mapping chlorophyll pollution in lakes and the detection and mapping of bacteria.

Objectives

The imaging spectroscopy research we conduct strives 

to better understand our environment, what it is made of—

from the mineral composition of rocks and soils to ecosystem 

health—and threats to the environment. Spectroscopy is a 

universal tool that can be applied to many problems from mineral mapping, environmental mapping, pollution, detection of 

threats such as bacteria, or pollution in lakes and their sources.

Background

Chlorophyll absorbs blue and red wavelengths leaving a 

green peak in reflected light that we see with our eyes, making 

plants appear green. Spectrometers resolve the fine spectral 

details allowing vegetation species to be detected and mapped 

(see for example, Clark and others, 2003; Kokaly and others 

2003). For example, the shapes of the chlorophyll absorptions 

are slightly different from a blue spruce tree compared to that 

from a Ponderosa pine tree. Bacteria also have absorption 

bands that can be detected with available imaging spectroscopy 

technology, and as we learn more about the spectral properties 

of bacteria and other organic compounds, more applications 

will become possible for understanding our environment.

Figure 62 shows the detection of a chlorophyll plume 

in a lake that was found while mapping acidic-rock drainage 

in the region of the Leadville, Colorado, mining district. Our 

mapping system, called Tetracorder (Clark and others, 2003), 

searches for minerals and different spectral types of vegetation 

and materials that may impact the environment. Included in 

the search was chlorophyll in water.

The synoptic view of imaging spectroscopy remote 

sensing enabled the mapping of selected compounds in the 

Fort Cobb Reservoir watershed to provide information about 
104 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 62. Spectral map of phytoplankton-rich water shows a plume originating from the shore of Turquoise Lake in Colorado. The plume 

probably originates from a low-volume sewage leak near a campground. The Tetracorder result shows detection of phytoplankton-rich 

water only over the lake and no response from nonwater targets. The Tetracorder spectral matching-decision process enables robust 

identifications in this situation. From Clark and others (2003). AVIRIS, airborne visible and infra-red imaging spectrometer.

EXPLANATION

High

Low

Medium

Chlorophyll content

0 1 2 3 KILOMETERS

0 1 2 MILES

sources of compounds that may be affecting water quality in 

the watershed (Clark and Wise, 2011). An advantage of imaging spectroscopic remote sensing is that it provides continuous 

synoptic sampling over large areas with tens-of-thousands of 

samples (pixels in an image). Limited field sampling efforts 

do not collect as many samples for analyses as remote sensing 

can; thus, field sampling may miss major potential sources of 

sediments and nutrients (fig. 63).

In areas where small creeks drained directly from 

cultivated fields, plumes of relatively large chlorophyll 

concentrations in the reservoir were observed (fig. 63). These 

plumes may be related to ecosystem buffering of fertilizer 

runoff from the cultivated fields near the larger creeks. If 

natural ecosystems reduce runoff, then increased areas of 

natural ecosystems to create a buffer zone between cultivated 

fields and streams, lakes, and reservoirs may improve water 

quality of the Fort Cobb and other reservoirs and lakes in the 

region (Clark and Wise, 2011).

Bacteria also have diagnostic absorption bands that shift 

wavelength and shape depending on the type of bacteria. 

Spectra of bacteria are illustrated in figure 64, which shows a 

variety of absorption-band positions. If you have ever seen the 

colorful bacteria of moldy bread, those colors are indicative of 

different absorptions in different molds.

We mapped minerals and bacteria in and around hot 

springs in Yellowstone National Park (fig. 65) where the different absorptions of bacteria and minerals were separated 

through the use of imaging spectroscopy. Applications for 

mapping bacteria go far beyond the environment and could be 

applied to health and safety of people and animals.
Hydrology and Water Quality 105

Figure 63. Screen image of the Hyperion imaging spectrometer on the EO-1 satellite mapping results for the Fort Cobb reservoir, 

southwestern Oklahoma, in 2006 (Clark and Wise, 2011). Reservoir sampling and laboratory-derived chlorophyll and photocyanin 

concentrations are shown as circles in panels C and D. Larger point sizes in panels C (green circles in the reservoir) and D (blue circles 

in the reservoir) indicate greater abundances derived from field sampling.

A B

C D

Reflectance

red = 1.65 microns

green = 0.85 mincron

blue = 0.53 micron

:

Chlorophyll:

red = 0.85-micron reflectance

green = chlorophyll spectral abundance (Brighter green in 

 the reservoir indicates larger chlorophyll concentration)

blue = 0.55 micron reflectance

Fort Cobb

Reservoir

Fort Cobb

Reservoir

Chlorophyll map plus chlorophyll points Chlorophyll map plus cyanin points
106 Developing Integrated Methods to Address Complex Resource and Environmental Issues Reflectance/continuum + offset

Wavelength, in micrometers

1.2

1.0

0.8

0.6

0.4 0.6 0.8 1.0 1.2

Bacteria

Yeast (baker’s) GDS561

ID: spd0513 r 46-106

Sulfollobus bacteria

Katrina sediment Chalmette 1_E9

Katrina sediment Chalmette 1_E7

H2O H2

O

H2

O

H2

O

H2O

H2O

Yellowstone, Octopus Spring, orange bacteria

Dipel dust, B. Thuringiensis

GDS565

Yellowstone, Octopus

 Spring red-orange bacteria

Figure 64. Spectra of samples containing bacteria. Different bacteria 

have absorptions at different locations allowing different types of bacteria 

to be distinguished. The Dipel dust contains 6 parts per million Bacillus 

thuringiensis. The spectra are offset for clarity.

Results and Conclusions

Application of the science and technology of imaging 

spectroscopy of organic compounds are virtually unlimited. 

Possible studies range from monitoring of ecosystem health 

to mapping pollution and pollution sources. Field sampling 

with laboratory analyses coupled with the synoptic view of 

remote full-spatial coverage is an extremely powerful combination of tools to understand and map our environment. Field 

sampling and laboratory analyses provide detailed analysis 

with limited coverage. Imaging spectroscopy compositional 

mapping provides detailed spatial sampling that no field sampling campaign can accomplish but with more limited detectability. However, imaging spectroscopy detectability of many 

compounds is much greater and more robust than traditional 

broad-band remote sensing. Applications also include environmental assessments after natural or man-made disasters.

Primary Products

Materials maps of minerals, organics, and other 

compounds.

References Cited

Clark, R.N., Swayze, G.A., Livo, K.E., Kokaly, R.F., Sutley, S.J., Dalton, J.B., McDougal, R.R., and Gent, C.A., 

2003, Imaging spectroscopy—Earth and planetary remote 

sensing with the USGS Tetracorder and Expert Systems: 

Journal of Geophysical Research, v. 108, no. E12, 5131, 

doi:10.1029/2002JE001847, 44 p., http://speclab.cr.usgs.

gov/PAPERS/tetracorder/.

Clark, R.N., and Wise, R.A., 2011, Mapping with imaging 

spectroscopy, Fort Cobb Reservoir watershed, southwestern 

Oklahoma, chap. 6 of Becker, C.J., ed., Assessment of conservation practices in the Fort Cobb Reservoir watershed, 

southwestern Oklahoma: U.S. Geological Survey Scientific 

Investigations Report 2010–5257, 23 p.

Kokaly, R.F., Despain, D.G., Clark, R.N., and Livo, K.E., 

2003, Mapping the biology of Yellowstone National Park 

using imaging spectroscopy: Remote Sensing of Environment, v. 84, p. 437–456.
Hydrology and Water Quality 107

Figure 65. Tetracorder (Clark and others, 2003) materials maps 

for Norris Geyser Basin in Yellowstone National Park using 

data from the NASA Airborne Visible and Infrared Imaging 

Spectrometer (AVIRIS). Minerals and bacteria are detected and 

mapped with the same data set. RGB, red, green and blue light 

added together.

Mineral map

RGB composite

Hot Springs biota

Hot Springs bacteria−Synochoccus

Mudflat

Algae−Cyanidium

Hot Springs bacteria

Hot Springs bacteria

Chalcedony

Halloysite

Alunite (50%) + Kaolinite (50%)

Montmorillonite−Calcium

Kaolinite−Well crystalline

Kaolinite−Poorly crystalline

EXPLANATION

EXPLANATION
108 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Aeromagnetic Methods for Mapping 

Covered Faults in Sediments

By V.J.S. Grauch

Issue and Scope

The Rio Grande rift in New Mexico and Colorado is a 

series of linked sedimentary basins that formed during the past 

25–30 million years through faulting and earthquake activity 

as the crust pulled apart. Sediments that filled the deepening 

basins now represent important aquifers supplying most of the 

drinking water for the cities of Albuquerque, Santa Fe, and 

Taos, New Mexico, as well as irrigation water for agricultural 

use in the San Luis Valley, Colorado. Normal faults bound the 

edges of the basins and are also numerous throughout the sedimentary section within the basins where many are concealed 

just below the ground. Although many of the faults are currently inactive, their presence has an influence on groundwater 

flow through the aquifers, upward migration of hot water 

associated with geothermal energy resources, and transmission 

of seismic energy throughout the basin if an earthquake were 

to occur. Moreover, normal faults with large displacements 

can potentially form major boundaries between aquifers of 

very different hydraulic properties. Thus, accurately mapping 

faults within the basins and estimating fault displacements is 

important for improving models related to groundwater flow, 

geothermal resource potential, and seismic hazards.

During a previous study of the sedimentary basin surrounding the city of Albuquerque by the U.S. Geological 

Survey (USGS), unconventional application of aeromagnetic 

methods successfully detected signals from many intrabasin faults (Grauch, 2001). At a regional scale, the magnetic 

expressions of the faults, called anomalies, were easy-tofollow linear features in aeromagnetic data images. At more 

local scales, however, the aeromagnetic expression was quite 

varied, both between faults and along the strike of individual 

faults. Some of the anomaly shapes appeared inconsistent 

with anomalies expected from simple normal faults. Standard 

methods to locate faults from aeromagnetic data proved to be 

inaccurate for these types of anomalies, so a better approach 

was required. 

Objectives

This study involved the development of methods for 

mapping covered faults from aeromagnetic data acquired 

for sedimentary basins, with a focus on the anomalies with 

unexpected shapes. The objectives were to locate concealed 

fault traces as accurately as possible from gridded aeromagnetic data and to provide some insight on the amount of fault 

displacement from analysis of individual anomalies.

Background

The approach focused on modeling the range of sources 

of the fault anomalies using known faults as guides. As part 

of a related project, detailed geophysical and rock-property 

studies of exposed faults provided evidence that the aeromagnetic anomalies are produced by the juxtaposition of 

magnetically differing strata as opposed to chemical processes acting at the fault zone (Grauch and Hudson, 2007; 

Hudson and others, 2008). From these results, hypothetical 

models of juxtaposed strata were developed to represent the 

whole range of possible types of fault anomalies. The hypothetical models were then used to test methods of mapping 

fault traces and strategies for approximating fault throw from 

known or estimated geophysical parameters. 

Results and Conclusions

The wide variety of anomaly shapes possible from 

juxtaposed strata can be characterized by four simple endmember hypothetical geophysical models, two of which fit 

traditional fault models and two of which do not (Grauch 

and Hudson, 2011). In map view, computing derivatives of 

gridded data (such as the horizontal gradient magnitude of 

the reduced-to-pole data) can help interpreters distinguish 

nontraditional fault-related anomalies from other geologic 

interpretations. Faults that are represented by the two nontraditional models produce parallel, double-track ridges in 

the horizontal derivative map, as demonstrated in figure 66. 

One of the parallel ridges is characteristically narrower than 

the other, which identifies the source as juxtaposed strata as 

opposed to other types of linear geologic sources, such as 

paleochannels or fault-zone alteration. Based on the model 

analysis, the trace of the fault is located most accurately by 

following the narrower of the two ridges. Thus, interpreters 

are able to map fault traces from the aeromagnetic data even 

where the anomaly shapes are unusual.

An examination of the relations between the geophysical parameters for the simplest of the four end-member 

models of juxtaposed strata allows us to estimate the criteria 

required to produce detectable aeromagnetic anomalies for 

a given survey design. The relations between fault throw, 

magnetic properties, and depth of the fault are presented in 

graphical form for ease of use (Grauch and Hudson, 2007, 

2011), which allows an interpreter to estimate fault throw 

from observed aeromagnetic data. In addition, the graphs are 

useful for planning new aeromagnetic surveys over sedimentary basins, assessing the amount of fault throw required to 

produce an aeromagnetic anomaly in a particular area, and 

estimating the depths to which these faults will be detected. 

These methods can also be applied to areas of layered geology outside the sedimentary environment, such as fields of 

layered volcanic flows.
Hydrology and Water Quality 109

Figure 66. Examples of aeromagnetic expressions of intrasedimentary normal faults and associated derivative maps in the central 

Rio Grande rift (inset). Images are displayed as color-shaded relief, illuminated from the west. The top panel shows reduced-topole aeromagnetic expressions A, without and B, with interpreted fault locations. The bottom panel shows the horizontal gradient 

magnitude of the reduced-to-pole (HGM-RTP) aeromagnetic data C, without and D, with interpreted fault locations. Note the many 

double-track ridges with fairly consistent separation over long distances. The interpreted fault is located at the narrower ridge of 

the double track, as demonstrated in E, for upper and lower profiles. Modified from Grauch and Hudson (2011). km, kilometers.

pipeline

pipeline

arroyo

pipeline

arroyo

A

A'

B B'

A

A'

B B'

0 100 200

HGM-RTP, in nanoTeslas per kilometer (C, D)

D

B B'

–340

–335

RTP magnetic field,

in nanoTeslas

25

50

0

HGM-RTP, in

nanoTeslas per km

Distance, in meters

500 1,000

1,750

Elevation,

in meters 1,730

0

Vertical exaggeration=10x

interpreted fault

location

C

E

1,000

1,730

1,750

1,770

0 500

interpreted fault

location

Distance, in meters

Elevation,

in meters

A A'

–372

–370

–368

25

50

0

HGM-RTP, in

nanoTeslas per km

RTP magnetic field,

in nanoTeslas

–500 0 500

RTP, in nanoTeslas (A, B)

EXPLANATION

pipeline

pipeline

arroyo

pipeline

pipeline

arroyo

pipeline

pipeline

arroyo

pipeline

pipeline

arroyo

pipeline

pipeline

arroyo

pipeline

pipeline

arroyo

pipeline

pipeline

arroyo

pipeline

pipeline

arroyo

106°45' 106°45'

35°15'

0 1 2 3 4 5 KILOMETERS

0 1 2 3 MILES

A

A'

B B'

A

A'

B B'

NM

MAP

AREA RIO

GRANDE RIFT

COLORADO

NEW

MEXICO

A B

Normal fault interpreted from

 aeromagnetic data
110 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Related U.S. Geological Survey Project

Geologic Framework of Rio Grande Basins Project, 

funded by National Cooperative Geologic Mapping and Mineral Resources Programs. 

References Cited

Grauch, V.J.S., 2001, High-resolution aeromagnetic data, a 

new tool for mapping intrabasinal faults—Example from 

the Albuquerque Basin, New Mexico: Geology, v. 29, no. 4, 

p. 367–370.

Grauch, V.J.S., and Hudson, M.R., 2007, Guides to understanding the aeromagnetic expression of faults in sedimentary basins—Lessons learned from the central Rio Grande 

rift, New Mexico: Geosphere, v. 3, no. 6, p. 596–623, DOI: 

10.1130/GES00128.1.

Grauch, V.J.S., and Hudson, M.R., 2011, Aeromagnetic 

anomalies over faulted strata: The Leading Edge, v. 30, 

no. 11, p. 1242–1252.

Hudson, M.R., Grauch, V.J.S., and Minor, S.A., 2008, Rock 

magnetic characterization of faulted sediments with associated magnetic anomalies in the Albuquerque Basin, Rio 

Grande rift, New Mexico: Geological Society of America 

Bulletin, v. 120, no. 5/6, p. 641–658.

Constraints on Rio Grande Rift 

Structure and Stratigraphy from 3-D 

Magnetotelluric Modelling, Española 

Basin, New Mexico

By Brian D. Rodriguez and David A. Sawyer

Issue and Scope

The population of the Santa Fe region in northern New 

Mexico is growing. Water shortfalls in this low rainfall region 

could have serious consequences. Decisions for future growth 

and land management in the region depend on an accurate assessment and protection of the region’s groundwater 

resources. An important aspect of managing the groundwater 

resources is a better understanding of the hydrogeology of the 

Santa Fe Group and the nature of the sedimentary deposits that 

fill the Rio Grande rift, which contain the principal groundwater aquifers. The Santa Fe Group aquifer in the Española 

Basin is the main source of municipal water for the region.

Objectives

In collaboration with Black Oil, Inc., Los Alamos National 

Laboratories, New Mexico Bureau of Geology and Mineral 

Resources, and the U.S. Geological Survey (USGS) National 

Cooperative Geologic Mapping Program, project scientists 

used deep electrical geophysical measurements to provide constraints for mapping subsurface stratigraphy and structure on 

the Rio Grande rift in the Española Basin. An improved understanding of the geologic framework of the Española Basin in 

New Mexico (fig. 67) will provide more accurate hydrogeologic parameters for a newer generation of hydrologic models. 

This will ultimately better quantify estimates of future water 

supplies for northern New Mexico’s growing urban centers, 

which largely subsist on aquifers, primarily in the upper Santa 

Fe Group sediments, in basins of the Rio Grande rift.

Background

Electrical geophysical methods, and in particular the 

magnetotelluric (MT) method, have been used previously in 

mapping the subsurface structure within the Rio Grande rift 

and the deep crust. The MT method is capable of distinguishing rocks that are strong electrical conductors (such as thick 

clay-rich Mesozoic shales) from rocks that are moderately (for 

example, sandstones) or highly (for example, Cenozoic volcanic 

rocks or Precambrian crystalline rocks) electrically resistive. 

MT can also map electrically conductive rocks from shallow 

(about 100 meters) to very great (to greater than 10 kilometers) 

depths, provided they are thick enough and have a large enough 

electrical resistivity contrast with nearby rocks. 
Hydrology and Water Quality 111

Figure 67. Simplified geologic map and cross section location of Santa Fe region, New 

Mexico, showing regional boreholes (solid red circles), magnetotelluric (MT) stations 

(green circles), and the MT profile cross section (solid black line). Colored polygons 

(modified from Green and Jones, 1997) represent major exposed geologic targets that 

are mapped in the subsurface using MT sounding.

27

1 3

35

A'

Cerros del Rio

volcanic field

Santa Fe

Los Alamos

Española

VALLES CALDERA

36°00'

106°30' 106°00'

A

Santo Domingo

basin

I-25

CERRILLOS UPLIFT

Española

basin

I-25

U.S. 285

U.S. 285

35°30'

0 10 20 KILOMETERS

0 5 10 MILES

Magnetotelluric station

Well

Precambrian crystalline rocks

Paleozoic sedimentary rocks

Mesozoic sedimentary rocks

Cenozoic Sante Fe Group

Cenozoic volcanic rocks

EXPLANATION

Geologic map units

NEW MEXICO

Map

area

2

34

14

28

15

33

32

12

31

30

36

17

11 5

25

10

23 22

9

29

4

20

8

21
112 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Borehole data from 45 exploratory wells that penetrate 

the Rio Grande rift or the related sedimentary rocks drilled 

on the flanks of the rift are used to calibrate our models of the 

electrical properties of lithologic units known or predicted to 

underlie the rift. This is particularly important where there 

is a thick electrically conductive unit (for example, Mesozoic shales) that underlay more resistive volcanic rocks (for 

example, Cenozoic basalts).

Results and Conclusions

Based on borehole resistivity data, Santa Fe Group sediments are conductive to moderately resistive (4–44 ohm-m) on 

average, whereas Cenozoic igneous rocks are resistive (greater 

than about 200 ohm-m). Resistivity data for the Mesozoic 

shales indicate that they are strong electrical conductors (about 

4–8 ohm meters [ohm-m]). Where the shales occur in the 

upper kilometer of crust, they may function as local hydrogeologic basement (separating older saline basinal waters from 

younger fresher groundwater). Paleozoic rocks generally have 

both moderately conductive and moderately resistive signatures (about 11–33 ohm-m). Precambrian crystalline rocks are 

resistive (greater than 600 ohm-m on average).

MT measurements provide additional constraints on 

the relative positions of basement rocks and the thicknesses 

of Paleozoic, Mesozoic, and Cenozoic sedimentary rocks in 

the Española Basin. The northern extent of a basement high 

(Cerrillos uplift, fig. 68) beneath the Cerros del Rio volcanic 

field (fig. 67) is delineated. The resistivity model also helps 

constrain models of the thickness of the upper Santa Fe Group 

(the coarser grained facies of Santa Fe Group sediments and 

primary aquifer in the region).

By correlating our resistivity model with surface geology 

and the deeper stratigraphic horizons using the deep well log 

data, we are able to interpret with more confidence which of the 

resistivity variations in the upper 2 kilometers belong to the upper 

Santa Fe Group sediments. The MT data primarily constrain the 

composite thickness of the conductive Cenozoic, Mesozoic, and 

upper Paleozoic sedimentary rocks that overlie more resistive 

lower Paleozoic sedimentary rocks and Precambrian basement.

Collaborators

Black Oil, Inc. 

Los Alamos National Laboratories 

New Mexico Bureau of Geology and Mineral Resources 

USGS National Cooperative Geologic Mapping Program

Selected References

Grauch, V.J.S., Phillips, J.D., Koning, D.J., Johnson, P.S., 

and Bankey, Viki, 2009, Geophysical interpretations of the 

southern Española Basin, New Mexico, that contribute to 

understanding its hydrogeologic framework: U.S. Geological Survey Professional Paper 1761, 88 p.

Green, G.N., and Jones, G.E., 1997, The digital geologic map 

of New Mexico in ARC/INFO format: U.S. Geological 

Survey Open-File Report 97–0052, 9 p., at https://pubs.

er.usgs.gov/publication/ofr9752.

Figure 68. Profile A–A′ is a resistivity section extracted from the 3-D resistivity model with gross lithologic 

interpretation. Numbered labels at the top of the model are MT station numbers. Numbers in parentheses within 

the section are modeled resistivity in ohm-meters. The thick dashed line is the basin-floor model from Grauch 

and others (2009). The thin dashed line is the interpreted top of Precambrian (poorly constrained by MT data).

|

04

|

20 |

08

|

21 |

11

|

05 |

25

|

10 |

23

|

22 |

09

|

27

0

Volcanic rocks of the Cerros del Rio Volcanic Field

(24-1000 ohm-meters)

A A'

SOUTH NORTH

DEPTH, IN

METERS

3,000

2,000

5,000

upper Santa Fe Group

lower Santa Fe Group(?)

Mesozoic(?)

Paleozoic(?)

Precambrian(?)

CERRILLOS UPLIFT

(6 ohm-meters)

(6–24 ohm-meters)

(33–44 ohm-meters)

(100–1,000 ohm-meters)

4,000

1,000

NO VERTICAL EXAGGERATION 0 2,000 4,000 METERS

0 4,000 8,000 FEET
Hydrology and Water Quality 113

Hudson, M.R., Grauch, V.J.S., Pantea, M.P., Koning, D.J., 

Johnson, P.S., Rodriguez, B.D., Minor, S.A., Caine, J.S., 

and Sawyer, D.S., 2009, Updated 3D model of the geological and geophysical framework of the southern Espanola 

Basin near Santa Fe, New Mexico, in Simmons, A., ed., 

Geology and hydrology of the Española Basin: Proceedings 

of the 7th Annual Española Basin Workshop, Santa Fe, New 

Mexico, March 6, 2008, New Mexico Bureau of Geology 

and Mineral Resources Open-File Report 513, p. 10.

Koning, D.J., Grauch, V.J.S., and Rodriguez, B.D., 2010, 

Cross-sections and geologic map for the eastern Española 

Basin, Rio Grande rift, north-central New Mexico, in Simmons, A., ed., The link between science and water policy: 

Proceedings of the 8th Annual Española Basin Workshop, 

Santa Fe, New Mexico, March 3, 2009, New Mexico 

Bureau of Geology and Mineral Resources Open-File 

Report 525, p. 11.

Rodriguez, B.D., and Sawyer, D.A, 2007, Correlation of 

magnetotelluric resistivity soundings and regional borehole 

geophysical rock properties to stratigraphy of the northern 

Rio Grande rift, New Mexico [abs.]: Geological Society of 

America Abstracts with Programs, v. 39, no. 6, p. 494.

Rodriguez, B.D., and Sawyer, D.A., 2008, Magnetotelluric 

soundings and deep borehole geophysical data constrain 

interpretations of subsurface geology of the southern Española Basin, New Mexico, in Borchert, C.I., ed., Geologic 

and hydrogeologic framework of the Española Basin: Proceedings of the 6th Annual Española Basin Workshop, Santa 

Fe, New Mexico, March 6, 2007, New Mexico Bureau of 

Geology and Mineral Resources Open-File Report 508, p. 7.

Rodriguez, B.D., and Sawyer, D.A., 2009, Geophysical constraints of Rio Grande rift structure and stratigraphy based 

on magnetotelluric resistivity soundings and regional borehole geophysical rock properties, Northern New Mexico, in

Simmons, A., ed., Geology and hydrology of the Española 

Basin: Proceedings of the 7th Annual Española Basin Workshop, Santa Fe, New Mexico, March 6, 2008, New Mexico 

Bureau of Geology and Mineral Resources, Open-File 

Report 513, p. 18

Rodriguez, B.D., and Sawyer, D.A., 2013, Geophysical 

constraints on Rio Grande rift structure and stratigraphy 

from magnetotelluric models and borehole resistivity logs, 

northern New Mexico, in Hudson, M.R., and Grauch, V.J.S., 

eds., New Perspectives on Rio Grande Rift Basins: From 

Tectonics to Groundwater: Geological Society of America 

Special Paper 494, p. 323–344, doi:10.1130/2013.2494(13).

Providing a Subsurface Framework 

for Regional Groundwater Models 

of Alluvial Basins—Example from 

the Southern Española Basin, NorthCentral New Mexico

By V.J.S. Grauch and Jeffrey D. Phillips

Issue and Scope

Alluvial basins that follow the Rio Grande in northcentral and northern New Mexico contain sediments that are 

important aquifers for communities such as Albuquerque, 

Santa Fe, Española, Taos, eight Pueblo nations, and surrounding suburban areas. Regional groundwater-flow models are 

commonly constructed to help manage and regulate these 

groundwater resources. Thus, accurate models are important 

but are hindered by lack of information in between scattered 

water wells. In particular, estimating the thickness of the 

basin-fill sediments is important for estimating the maximum 

storage capacity of the aquifer. 

Traditionally, aeromagnetic methods have been underutilized for determining the thickness of basin-fill sediments, 

yet the geology in many areas of the alluvial basins along the 

Rio Grande is favorable for this approach. A good example 

is in the southern Española Basin, south of the city of Santa 

Fe, New Mexico. In this area, weakly magnetic sediments, 

which make up the alluvial aquifer, are locally underlain by 

older, moderately to strongly magnetic igneous and volcaniclastic rocks. Because aeromagnetic data (measurements 

of the magnetic field from aircraft) are most sensitive to the 

underlying moderately to strongly magnetic rocks, estimating 

the depths to the tops of the igneous and volcaniclastic rocks 

also indicates the thickness of overlying sediments. Thus, 

the maximum thickness of the aquifer can be estimated from 

quantitative analysis of high-resolution aeromagnetic data 

acquired over the region.

Objectives

Many methods for estimating depth to magnetic sources 

from aeromagnetic data have been developed previously. The 

methods generally provide the depth to the shallowest, most 

magnetic source. Because no one method is the best for all 

situations and amount of noise in the data (Phillips, 2000), the 

best approach to using magnetic depth estimation is to investigate the results of multiple methods.

Although the situation for the southern Española Basin 

appeared ideal for using magnetic depth-estimation methods 

to map the base of the aquifer, preliminary results (Phillips 

and Grauch, 2004) revealed some important difficulties. The 

difficulties arose because the shallowest, most magnetic source 
–1,000

0

1,000

2,000

Elevation, in meters

3,990,000 3,980,000 3,970,000 3,960,000 3,950,000 3,940,000 3,930,000 

Northing, in meters 

–1,500

–1,000

–500

0

500

1,000

1,500

2,000

2,500

Elevation, 

in meters

Santa

Fe

Santa

Fe

 

SANTA FE MOUNTAINS

 

SANTA FE MOUNTAINS

Española

Española

25

84

68

285

NEW

MEXICO

COLORADO

TEXAS

R

I

O

G

RANDE

RIFT

 Rio

Grande

Santa Fe

Albuquerque

Taos

Alamosa

Socorro

MEXICO

EXPLANATION

N

Figure 69. Perspective view of the modeled elevation of the base of the alluvial aquifer in the southern Española Basin in relation to topography, loosurface is raised above the base. From Grauch and others (2009).
Hydrology and Water Quality 115

was generally, but not always, located along the top of the igneous and volcaniclastic unit. In some cases, the sediments were 

magnetic enough that they represented the shallowest, magnetic 

source. In other cases, variability in layers of the underlying 

igneous and volcanic unit produced magnetic layers internal to 

the unit that were more magnetic than its top. Thus, the objectives of this study were to (1) apply a variety of depth-estimation 

methods developed under the auspices of the Integrated Methods 

Development Project to the southern Española Basin, and (2) 

combine the depth-estimate results with information from other 

geologic and geophysical data in a 3-D environment to obtain a 

consistent surface representing the base of the aquifer.

Background

Magnetic depth-estimation methods examined or developed under the auspices of the Integrated Methods Development 

Project were applied to aeromagnetic data from the southern 

Española Basin in profile and gridded form separately. Profiles 

were analyzed by using the computer program PDEPTH (Phillips, 1997), which incorporates a variety of methods so that 

results can be examined together. Gridded data were analyzed 

using adaptations of the local wave-number method (Thurston 

and Smith, 1997; Smith and others, 1998; Phillips and others, 

2007) and two-step extended Euler method (Reid and others, 

1990; Nabighian and Hansen, 2001; Phillips, 2002; Phillips 

and Grauch, 2004). The results of depth estimation were then 

incorporated into a 3-D model developed by Grauch and others 

(2009) using the software package GeoModeller.TM

Results and Conclusions

The depth-estimate solutions from profile versus gridded data were brought into the 3-D model in different ways. 

Depth-estimate solutions for profile data were used to develop 

2-D geophysical models along the same profiles. The 2-D 

models were then incorporated directly into the 3-D model, 

rather than the depth-estimate solutions themselves. In contrast, the 3-D locations of more than 100,000 depth-estimate 

solutions from the grid-based methods were input directly into 

the 3-D model. This direct input allowed us to project the solution locations onto any desired 2-D section for inspection in 

relation to other geologic and geophysical information. 

Comparison of gridded depth-estimate solutions in the 

3-D modeling environment with other geophysical information and well data proved invaluable for resolving difficulties 

presented by variable magnetic sources. Using this approach, 

depth estimates locating the top of the igneous and volcaniclastic unit could easily be distinguished from those locating 

other magnetic interfaces internal to this unit or within the 

sediments above it. Finally, combining the improved understanding of the magnetic depth-estimate solutions with other 

geophysical information and well data allowed us to develop a 

3-D model of the base of the aquifer for the southern Española 

Basin (fig. 69; Grauch and others, 2009).

Related U.S. Geological Survey Project

Geologic Framework of Rio Grande Basins Project, 

 funded by National Cooperative Geologic Mapping and 

 Mineral Resources Programs

References Cited

Grauch, V.J.S., Phillips, J.D., Koning, D.J., Johnson, P.S., 

and Bankey, Viki, 2009, Geophysical interpretations of the 

southern Española Basin, New Mexico, that contribute to 

understanding its hydrogeologic framework: U.S. Geological Survey Professional Paper 1761, 88 p., at http://pubs.

usgs.gov/pp/1761/.

Nabighian, M.N., and Hansen, R.O., 2001, Unification of 

Euler and Werner deconvolution in three dimensions via 

the generalized Hilbert transform: Geophysics, v. 66, 

p. 1805–1810.

Phillips, J.D., 1997, Potential-field geophysical software for 

the PC, version 2.2: U.S. Geological Survey Open-File 

Report 97–725; unpaged, at http://pubs.usgs.gov/of/1997/

ofr-97-0725/.

Phillips, J.D, 2000, Locating magnetic contacts—A comparison of the horizontal gradient, analytic signal, and local 

wavenumber methods [abs.]: Annual International Meeting 

of Society of Exploration Geophysicists, 70th, Expanded 

Abstracts, v. 19, p. 402–405, at http://seg.org/publications/

archive/exAbsHist/abs_pdf/2000/ea200004020405.pdf.

Phillips, J.D., 2002, Two-step processing for 3D magnetic 

source locations and structural indices using extended 

Euler or analytic signal methods [abs.]: Society of Exploration Geophysicists, 2002 Technical Program Expanded 

Abstracts, 4 p.

Phillips, J.D., and Grauch, V.J.S., 2004, Thickness of Santa Fe 

Group sediments in the Española Basin south of Santa Fe, 

New Mexico, as estimated from aeromagnetic data: U.S. 

Geological Survey Open-File Report 2004–1354, 24 p., at 

http://pubs.usgs.gov/of/2004/1354/.

Phillips, J.D., Hansen, R.O., and Blakely, R.J., 2007, The use 

of curvature in potential-field interpretation: Exploration 

Geophysics, v. 38, p. 111–119.

Reid, A.B., Allsop, J.M., Granser, H., Millett, A.J., and Somerton, I.W., 1990, Magnetic interpretation in three dimensions 

using Euler deconvolution: Geophysics, v. 55, p. 80–91.

Smith, R.S., Thurston, J.B., Dai, Ting-Fan, and MacLeod, I.N., 

1998, iSPITM—The improved source parameter imaging 

method: Geophysical Prospecting, v. 46, p. 141–151.

Thurston, J.B., and Smith, R.S., 1997, Automatic conversion 

of magnetic data to depth, dip, and susceptibility contrast 

using the SPITM method: Geophysics, v. 62, p. 807–813.
Hazards and Disaster Assessment

significantly reducing the magnetization of volcanic rocks. 

These changes in rock properties produce clear distinctions 

between altered and unaltered rock in geophysical survey 

measurements. The presence of water helps form clay minerals that weaken the edifice but also reduce pore pressures, 

increasing the potential for slope failure. In addition, water 

and entrained melting ice acts as a lubricant to transform 

debris avalanches into lahars.

The objectives of this study are to determine the 3-D 

distribution of alteration and water on Mount Rainier, Mount 

Baker, and Mount Adams with HEM data to aid in hazards, 

water-resource, and mineral studies. The rugged, magnetic, 

and resistive volcanoes pose difficulties in data collection and 

analysis. We applied a variety of data reduction and modeling approaches to obtain 3-D models of the composition of 

the volcanoes. In order to tie the results of the modeling to the 

geology, we measured electrical and magnetic properties of 

representative samples from each volcano.

Background

Analysis and modeling of the magnetic and HEM data 

required application of techniques developed at the U.S. Geological Survey (USGS) including filtering, depth estimates, 

equivalent source determination, and magnetic (Phillips, 1992, 

1997, 2000, 2001, 2007) and HEM modeling. The results from 

application of these techniques helped constrain modeling of 

the magnetic and electromagnetic data. In addition, electrical 

resistivity, susceptibility, and density of rock samples were 

measured in the USGS Petrophysics laboratory to help constrain the 3-D geophysical models. Samples ranged from fresh, 

massive andesite and dacite to completely altered powders 

composed of opal, alunite, kaolinite, and montmorillonite. 

Results and Conclusions

Combined HEM and magnetic models (fig. 70) show that 

appreciable thickness (>500 meters [m]) of low to moderate 

resistivity (0.1–100 ohm-meters), nonmagnetic, water-saturated hydrothermally altered material lies under ice west of 

the modern summit of Mount Rainier in the Sunset Amphitheater region (Finn and others, 2001) and in the central core 

of Mount Adams north of the summit (Finn, Deszcz-Pan, and 

others, 2007) (dark blue zones in fig. 70). Alteration at Mount 

Baker is restricted to thinner (<300 m) zones beneath Sherman 

Crater and the Dorr Fumarole Field (Finn and Deszcz-Pan, 

2009). These altered water-saturated rocks lie at shallow 

depths (1–90 m) beneath the ice. The magnetic model tends to 

show minimum thickness and cannot unequivocally determine 

the base of alteration, because of uncertainties and variability 

of magnetization contrasts.

Geophysics of Volcanic Landslide 

Hazards—Inside Story

By Carol A. Finn and Maria Deszcz-Pan

Issue and Scope

Hydrothermally altered rocks, particularly if water 

saturated, can weaken stratovolcanoes, thereby increasing 

the potential for catastrophic sector collapses that can lead to 

far-traveled, destructive debris flows or volcanic landslides. 

Evaluating the hazards associated with such alteration is difficult because alteration has been mapped on few active volcanoes, and the distribution and severity of subsurface alteration 

is largely unknown on any active volcano. Large landslides 

from Mounts Adams, Baker, and Rainier are their primary 

hazards, not eruptions. Collapses of water-saturated hydrothermally altered edifice flanks from these volcanoes have generated numerous extensive landslides, and future collapses could 

threaten areas that are now densely populated.

Traditional methods for evaluation of landslide hazards 

have been largely restricted to surficial mapping of volcanoes 

and landslide deposits. However, the applications of technologies, rock property measurements, and analysis tools from 

the minerals industry can help delineate water-saturated and 

hydrothermally altered rock, thereby aiding in volcanic landslide hazards assessments.

Objectives

Critical to quantifying the hazard from volcanic landslides is knowledge of the three-dimensional (3-D) distribution of pervasively altered rock and shallow groundwater that 

plays an important role in transforming debris avalanches 

to far-traveled lahars, which are the debris that flows down 

the slopes of a volcano (Vallance and Scott, 1997; Vallance, 

1999), both of which can be detected by helicopter electromagnetic (HEM) and magnetic data (Deszcz-Pan and others, 

1998; Finn and others, 2001; Finn, Descsz-Pan, and others, 

2007; Finn, Deszcz-Pan, Anderson, and John, 2007; Finn and 

Deszcz-Pan, 2009; Finn and Descsz-Pan, 2011). Hydrothermally altered volcanic rocks possess low electrical resistivities because of their water and clay contents, whereas high 

resistivities characterize fresh, dry, massive volcanic rocks. 

Low to moderate resistivities characterize groundwater of 

various salinities (Keller, 1987; Finizola and others, 2006). 

Magnetic data reflect variations in the distribution and type 

of magnetic minerals, primarily magnetite, in the Earth’s 

crust. Hydrothermal alteration generally destroys magnetite, 
Hazards and Disaster Assessment 117

Figure 70. Three-dimensional view of the distribution of water and alteration based on geologic mapping, 

resistivity (upper 300 meters), and magnetic (>300-meter thickness) models and measured rock properties.

Dry, fresh rock or ice Saturated, intensely altered rock

Saturated, fresh or weakly altered rock

Moist intensely altered rock

Intensely altered rock (saturation

 level unknown)

EXPLANATION

A Mount Adams

Resistivity

model

Magnetic

model

White

Salmon

Glacier

Summit

0

1,500

4,500

3,000

0

1,500

3,000 

1,000

2,000

3,000

Elevation, in meters

3,200

1,200

2,000

2,800

2,400

1,600

Elevation, in meters

0

2,000

4,000 4,000

2,000

0

4,000

1,000

2,000

3,000

Elevation, in meters

Sunset

Aphitheater

Summit

Summit

Sherman

crater

B Mount Baker

C Mount Rainier

Distance, in meters

Distance, in meters

N
118 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Resistivities of 100–850 ohm-m characterize watersaturated fresh volcanic rocks (green in fig. 70). Given 

observed stratigraphy, the water is contained in permeable 

breccia bounded by impermeable lava flows. It is likely that 

water-rich rock lies below the 100–200 m detection depth of 

the HEM data. The magnetic data identify low susceptibilities 

that likely represent intensely altered rock to depths of at least 

1,000 m below the surface; water could occupy pore space 

in these rocks as they do near the surface. Several geologic 

observations support the geophysical identification of waterrich layers: alteration is strongly controlled by permeability 

and the presence of water; the presence of opal and other silica 

phases near the summit that form at and below the water table; 

and reconnaissance stable isotope data of hydrothermal minerals that indicate formation predominantly from groundwater 

(John and others, 2008). These permeable units most likely 

represent local perched water units. The HEM data identified 

water-saturated rocks from the surface to the detection limit 

(100–200 m) in discreet zones at Mount Rainier (Finn and 

others, 2001) and Mount Adams (Finn, Deszcz-Pan, Anderson, 

and John, 2007) and over the entire summit region at Mount 

Baker (Finn and Deszcz-Pan, 2009).

Ice thickness measurements critical for flood and 

landslide hazards studies are very sparse on Cascade Range 

volcanoes. The HEM data were used to determine ice thickness over portions of Mount Baker and Mount Adams volcanoes. A variety of HEM modeling techniques were applied 

to the data. Resistivity sections provide good estimates of 

ice thickness where the basement is altered and conductive. 

In general, ice thicknesses less than 100 m over low- to 

moderate-resistivity basement are well-resolved. Estimates 

greater than ≈100 m are not resolved nor were those over 

very high resistivity (>1,000 ohm-m) basement. The ice 

thicknesses derived from HEM are consistent with the 

previous drill-hole data from Mount Adams and radar data 

from both volcanoes with mean thickness of 31 m for Mount 

Adams and 43 m for Mount Baker. The resulting ice thickness maps show that the thickest ice on Mount Baker is on 

the gentle lower slopes and the thickest ice at Mount Adams 

is at the summit (Finn and others, 2012). 

The application of helicopter magnetic and HEM methods, traditional tools of the mining industry, to geotechnical 

studies of volcanoes is challenging due to high elevation and 

rugged, magnetic, and resistive terrain. Difficult flight conditions can result in uneven flight lines at less than optimum 

heights above the ground for modeling. Due to highly magnetic 

volcanic rocks, small changes in elevations over the sources, 

especially over deep valleys, make modeling difficult resulting 

in unrealistic geometries in some cases in the upper 100–200 m 

of the models. The high resistivities make differentiating 

between thick ice and rock and identifying water in fresh volcanic rocks difficult. However, combining magnetic and HEM 

data with geology and rock property measurements and innovative modeling approaches allows identification of alteration and 

water and ice thickness critical to evaluating volcanic landslide 

hazards and water and ice availability to the landslides.

Collaborators

Thomas Sission, Mark Reid, David John, George Breit, and 

 Robert Horton, all U.S. Geological Survey.

References Cited

Deszcz-Pan, Maria, Fitterman, D.V., and Labson, V.F., 1998, 

Reduction of inversion errors in helicopter EM data using 

auxiliary information: Exploration Geophysics, v. 29, 

p. 142–146.

Finizola, A., Revil, A., Rizzo, E., Piscitelli, S., Ricci, T., 

Morin, J., Angeletti, B., Mocochain, L., and Sortino, F., 

2006, Hydrogeologic insights at Stromboli volcano (Italy) 

from geoelectrical, temperature, and CO2 soil degassing 

investigations: Geophysical Research Letters, v. 33, 4 p., 

doi:10.1029/2006GL026842.

Finn, C.A., and Deszcz-Pan, Maria, 2009, The 3-D distribution 

of alteration, ice and water from helicopter magnetic and 

electromagnetic surveys at Mts. Adams, Baker and Rainier, 

Washington—Implications for debris flows hazards [abs.]: 

Geological Society of America Abstracts with Programs, 

v. 41, p. 717.

Finn, C.A., and Descsz-Pan, Maria, 2011, Helicopter magnetic 

and electromagnetic surveys at Mounts Adams, Baker and 

Rainier, Washington—Implications for debris flow hazards 

and volcano hydrology [abs.]: International Workshop on 

Gravity, Electrical & Magnetic Methods and Their Applications, Beijing, China, October 10–13, 2011: p. 24, http://

dx.doi.org/10.1190/1.3659065.

Finn, C.A., Deszcz-Pan, Maryla, Anderson, E.D., and John, 

D.A., 2007, Three-dimensional geophysical mapping of 

rock alteration and water content at Mount Adams, Washington—Implications for lahar hazards: Journal of Geophysical Research, v. 112, 21 p.

Finn, C.A., Descsz-Pan, Maria, and Bedrosian, P.A., 2012, 

Helicopter electromagnetic data map ice thickness at Mount 

Adams and Mount Baker, Washington, USA: Journal of 

Glaciology, v. 58, no. 212, p. 1133–1143.

Finn, C.A., Deszcz-Pan, M., Horton, R., Breit, G., and John, 

D., 2007, Airborne magnetic and electromagnetic data map 

rock alteration and water content at Mount Adams, Mount 

Baker and Mount Rainier, Washington—Implications for 

lahar hazards and hydrothermal systems: Eos Transactions 

American Geophysical Union, v. 88, (Fall Meeting Supplement), Abstract NS34A-05.

Finn, C.A., Sisson, T.W., and Descsz-Pan, Maryla, 2001, 

Aerogeophysical measurements of collapse-prone hydrothermally altered zones at Mount Rainier Volcano, Washington: Nature, v. 409, p. 600–603.
Hazards and Disaster Assessment 119

John, D.A., Sisson, T.W., Breit, G.N., Rye, R.O., and Vallance, 

J.W., 2008, Characteristics, extent and origin of hydrothermal alteration at Mount Rainier Volcano, Cascades arc, 

USA—Implications for debris-flow hazards and mineral 

deposits: Journal of Volcanology and Geothermal Research, 

v. 175, p. 289–314.

Keller, G.V., 1987, Rock and mineral properties: Investigations in Geophysics, v. 3, p. 13–51.

Phillips, J.D., 1992, TERRACE: A terracing procedure for 

gridded data, with FORTRAN programs and VAX command procedures, UNIX C-shell and DOS implimentations: 

U.S. Geological Survey Open-File Report 92–5, unpaged, at 

http://pubs.usgs.gov/of/1997/ofr-97-0725/.

Phillips, J.D., 1997, Potential-field geophysical software for 

the PC, version 2.2: U.S. Geological Survey Open-File 

Report 97–725, 34 p.

Phillips, J.D., 2000, Locating magnetic contacts—A comparison of the horizontal gradient, analytic signal, and 

local wavenumber methods [abs.]: Society of Exploration 

Geophysicists Technical Program Expanded Abstracts, 

p. 402–405.

Phillips, J.D, 2001, Designing matched bandpass and azimuthal filters for the separation of potential-field anomalies 

by source region and source type [abs]: Australian Society 

of Exploration Geophysicists, 15th Geophysical Conference 

and Exhibition, Expanded Abstracts, CD-ROM, p. 4.

Phillips, J.D., 2007, Geosoft eXecutables (GX’s) developed by 

the U.S. Geological Survey, version 2.0, with notes on GX 

development from Fortran code: U.S. Geological Survey 

Open-File Report 2007–1355, 111 p.

Vallance, J.W., 1999, Postglacial lahars and potential hazards 

in the White Salmon River system on the southwest flank of 

Mount Adams, Washington: U.S. Geological Survey Bulletin 2161, 49 p.

Vallance, J.W., and Scott, K.M., 1997, The Osceola mudflow 

from Mount Rainier—Sedimentology and hazard implications of a huge clay-rich debris flow: Geological Society of 

America Bulletin, v. 109, p. 143–163.

Helicopter Electromagnetic Surveys 

Over Volcanoes—Resolution and 

Limitations for Mapping Ice Thickness

By Maria Deszcz-Pan, Carol A. Finn, and 

Paul Bedrosian

Issue and Scope

The occurrence of floods and mudflows during the eruption of Mount St. Helens and documented large water-saturated 

mudflows from Mount Rainier and Mount Adams indicate the 

need for ice thickness measurements to help predict the waterhazard of Cascade volcanoes (Driedger and Kennard, 1986). 

The biggest hazards from Mount Baker and Mount Adams are 

not eruptions but debris avalanches and lahars partially lubricated by ice, snow, and melt water (Gardner, 1995; Scott and 

others, 1995; Vallance, 1999). Other hazards include removal 

of ice and snow during eruptions, which leads to flooding and 

melting of ice and snow that contributes to phreatic and hydrothermal eruptions (Mastin, 1995). However, few ice thickness 

measurements have been directly made on these and other 

Cascade volcanoes (Driedger and Kennard, 1986). 

Objectives

We report the pioneering use of helicopter electromagnetic 

(HEM) data, originally collected to detect hydrothermal alteration (Finn and others, 2001; Finn and others, 2007a,b; to estimate 

ice thickness for parts of Mount Baker and Mount Adams. We 

focus on the innovative approach of using resistivity inversions 

to obtain ice thickness and to quantify the limits and uncertainties in ice depth estimates. Comparisons of the HEM results 

with ice-penetrating radar measurements and drill-hole data help 

determine their reliability.

Background

To evaluate the reliability of determining ice thickness 

from the HEM data, we used a freeware program called EMMA 

(Auken and others, 2002) to provide expected ranges of ice 

thickness values for a specific HEM system and survey parameters and for a resistivity model that approximates local geologic conditions. The resistivity model contains variably thick 

(0–125 meters [m]) resistive ice layer (10,000 ohm-m) over basement with variable resistivities. Figure 71 presents the results.

If the resistivity of the basement is low (for example, 

<100 ohm-m), the calculated ice thickness closely approximates the true layer thickness for depths less than 60 m, is 

within about 10 m for ice thickness between 60 and ≈90 m, and 

errors may exceed 25 m for ice thickness >100 m (fig. 71). For 

300 ohm-m basement resistivity, the uncertainty in ice thickness 
120 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 72 (facing page). Example of cross section from Mount 

Adams two-layer laterally continuous inversions (Auken and 

others, 2005). A, Measured in-phase (I) component at five 

frequencies. B, Measured quadrature (Q) component at five 

frequencies. C, Inverted resistivity section with sensor elevation 

shown above topography. Sensor elevations are shown in red 

where they exceed 100 meters. Ice thickness, where reliable, 

is defined by the bottom of orange-brown ice layer. Gray lines 

indicate the upper and lower bounds on the ice thickness. Black 

line shows the depth of investigation. Vertical thin lines near 

summit indicate ice depths from the radar profile. D, Upper and 

lower bounds on the layer thickness. Lines are red where the 

solution is unreliable. E, Location of flight path from the top of 

Mount Adams volcano on aerial photograph. Borehole symbols 

are color-coded and show ice thickness from 1930s drill holes 

(Fowler, 1935); circles are also color-coded and show radar 

soundings over the summit ice cap (Tulaczyk, University of 

California, Santa Cruz, written commun., 2006).

Figure 71. Uncertainties in ice thickness estimates as a function 

of ice thickness and basement resistivity. The x-axis represents 

the true layer thickness and the y-axis represents the maximum 

and minimum thickness of ice estimated from the inversion of data 

at six frequencies, assuming a given noise (Auken and others, 

2002) and 50-meter system elevation. Color-coded lines represent 

the expected range of thickness estimates depending on the 

basement resistivity compared to the true ice thickness shown in 

red. The curves are truncated where ice thickness resolution is 

low, chosen to be twice the true ice thickness value.

True ice thickness, in meters

0 25 50 75 100 125

EXPLANATION

True layer thickness

10 ohm-meter basement

100 ohm-meter basement 850 ohm-meter basement

600 ohm-meter basement

300 ohm-meter basement

0

25

50

75

100

125 Estimated ice thickness range, in meters 

estimate exceeds 25 m for 75-m-thick ice and is about 5 m for 

ice <≈50 m thick (fig. 71). For basement resistivities between 

300 and ≈850 ohm-m, ice thickness <≈35 m can be determined reliably. For thin ice (<≈10 m) and resistive basement 

(300–850 ohm-m), the ice thickness is not resolved, because 

there is not enough difference in response between them.

We invert the data for the ice thickness using onedimensional (1-D) laterally constrained inversion (LCI) algorithm (Auken and others, 2005; Siemon, 2009). Because we 

are only interested in ice thickness, two layers are sufficient 

for the modeling, with the understanding that the uncertainties associated with the inverted top layer thickness provide 

a measure of uncertainties in ice thickness estimates. An 

example of one inverted line from the top of Mount Adams is 

given in figure 72C.

For LCI inversion we subdivided the profiles into blocks 

of ≈500 m with ≈50 soundings in each block, within which all 

1-D datasets and models are inverted as one system, producing 

layered sections with laterally smooth transitions within each 

block. Because the inversion consists only of two layers, a 

limited number of parameters need to be determined. For 

parameterized inversions, such as the two-layer inversion 

applied here, estimates of the standard deviation values for a 

given parameter (for example, layer thickness) were calculated 

directly from the model covariance matrix. The upper and 

lower limits of the inverted thickness of the top layer are plotted in figure 72D, where gray lines show well-resolved depths 

and red lines show unresolved or below the depth of investigation (described in next paragraph) values.

An estimate of the maximum depth of reliable HEM 

inversion results, called the depth-of-investigation (DOI), is 

calculated by finely discretizing the final two-layer inverse 

model and calculating the sensitivity matrix for the rediscretized model, resulting in a cumulative sum of column-wise 

averages of the sensitivity matrix (Christiansen and Auken, 

2010). The DOI metric is subsequently defined as the depth 

at which data sensitivity drops below a threshold of 0.8. 

The black line on the cross section in figure 72C shows this 

boundary. This metric, one measure of DOI, is influenced 

by the regularization and starting model and is best used to 

assess relative lateral variations in the DOI rather than an 

absolute measure of DOI. Other gray lines on the cross section 

in figure 72C show the same upper and lower limits on layer 

thickness estimate as in figure 72D.

Results and Conclusions

The reliability of the ice thickness values depended on 

several factors. Figure 72 demonstrates that the signal levels 

(shown in figs. 72A and 72B for in-phase and quadrature components, respectively) are higher when the basement is conductive (blue colors in fig. 72C), shallow, and when the measurement bird is closer to the Earth’s surface (compare line above 
Hazards and Disaster Assessment 121

 0

 

 10

 

 20

 

 40

 

 60

 

 80

 

 100

 

 30

 50

 70

90

110

 200

Ice thickness,

in meters

1 

5

45

80

140

215

300

370

450

520

600

675

750

850

950

1,000

5,500

10,000

20,000

615,000 616,000 617,000 618,000

Easting, in meters

−500

0

500

Distance, in meters

2,500

3,000

3,500

Elevation, in meters

50

100

150

200

Thickness, in meters

 

 

 

 

 

 

 

 

 

 

 

 

 

  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

500

1,000

1,500

2,000

I, in parts per million

0

500

1,000

1,500

2,000

Q, in parts per million

614,000 619,000

100,000

 25,000

 6,200

 3,300

 1,500

 400

E

D

C

B

A

Universal Transverse Mercator projection, zone 10 north

North American Datum of 1927

Lower bound

on ice thickness

Upper bound

on ice thickness

Sensor

elevation

Depth of

investigation

EXPLANATION

EXPLANATION

0 1,000 METERS

0 4,000 FEET

 Resistivity,

in ohm-meters

EXPLANATION

Signal frequency,

in hertz
122 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Seattle

MOUNT BAKER

MOUNT ADAMS

MOUNT SAINT HELENS

MOUNT RAINIER

WASHINGTON

Map location

EXPLANATION

200 ohm-meter basement

 resistivity contour

Airborne electromagnetic

 flight path

−121°51' −121°49' −121°47'

drill hole and radar

measurements

−121°31' −121°30' −121°29' −121°28'

Error, in meters

50

45

40

35

30

25

20

15

10

5

B

A

Universal Transverse Mercator projection, zone 10 north

North American Datum of 1927

46°11'

46°12'

46°13'

48°46'

48°47'

Ice thickness, in meters

>110

100 to 110

90 to 100

80 to 90

70 to 80

60 to 70

50 to 60

40 to 50

30 to 40

20 to 30

10 to 20

<10

CARMELO

CRATER

SHERMAN

CRATER

EASTON

GLACIER

WHITE

SALMON

KLICKITAT

LYMAN

WILSON ADAMS

Figure 73. Ice thicknesses for Mounts 

Baker and Adams. A, Mount Baker ice 

thickness spot and gridded results overlain 

on aerial photographs based on helicopter 

electromagnetic (HEM) and radar data (squares) 

(Harper, 1993; Tucker and others, 2009; Park, 

2011). Depths indicated by colors. Size is 

proportional to the absolute uncertainty in depth 

estimate expressed as a difference between 

gray lines in figure 72D. Black lines represent 

200 ohm-meters basement resistivity contour. 

B, Mount Adams ice thickness spot and gridded 

results overlain on aerial photographs based on 

HEM, radar (Tulaczyk, University of California, 

Santa Cruz, written commun., 2006), and drill-hole 

(Fowler, 1935) data. Black lines represent 200 

ohm-meters basement resistivity contour. Depths 

indicated by colors. Size is proportional to the 

absolute uncertainty in depth estimate expressed 

as a difference between gray lines in figure 72D.
Hazards and Disaster Assessment 123

inverted section in fig. 72C [showing the sensor elevation above 

the topography] with signal levels). The line is black when the 

elevation is less than 100 m and red for the sensor higher than 

100 m. On Mount Adams, higher bird elevations and more 

resistive basement outside of the summit area produced lower 

signal levels (fig. 73B) yielding fewer ice thickness estimates 

than for Mount Baker (fig. 73A). The most reliable ice thickness 

values are located where the ice is <≈100 m thick over <200 

ohm-m basement (figs. 73A and 73B). Over resistive basement 

(>≈200 ohm-m; contours figs. 73A and 73B), thicknesses are 

acceptable if the ice is <30–50 m thick but become increasingly 

unreliable with increasing resistivity and ice thickness (fig. 71) 

because of low signal levels and the limitations of the HEM 

method to differentiate between the resistive ice and rock layers 

(figs. 71, 72, and 73).

At Mount Baker, basement resistivities are generally 

<850 ohm-m, with large regions less than 200 ohm-m (contours, 

fig. 73A) (Finn and others, 2012) making ice thickness estimates 

possible over much of the survey area (fig. 73). Although ice 

thickness reaches about 75–80 m in Carmelo crater (fig. 73A), 

ice is generally thinner than ≈50 m, including Sherman Crater, at 

high elevations (fig. 73A). Ice thickness increases on the gentler 

slopes at the edge of the volcano to >100 m (fig. 73A). Radar 

measurements on Easton Glacier show that the ice maintains 

its >80-m thickness for nearly 2 kilometers south of the HEM 

survey region (Harper, 1993) suggesting that all glaciers could 

contain thick ice outside of the survey region (fig. 73A). 

At Mount Adams, ice is thickest over the central and western part of the summit ice cap, exceeding 120 m (fig. 73B). The 

upper reaches of the White Salmon, Adams, Lyman, and Klickitat Glaciers (fig. 73B) contain ice ranging in thickness from 

≈25–60 m. The glaciers lower down on the volcano are less than 

≈30 m thick. Inspection of the aerial photographs shows outcrop 

in many parts of the lower portions of the glaciers revealing thin 

ice (<10 m), especially in the south (fig. 73B). In general, thin 

ice mantles the steep slopes around Mount Adams where ice 

thickness increases with increasing elevation (fig. 73B).

The 1980 eruption of Mount St. Helens, the most active 

volcano in the Cascades, removed ≈130 x106

 m3 of ice and 

snow, resulting in lahars and floods (Driedger and Kennard, 

1986). Mount Baker is the second most-active volcano in 

the Cascades, with vigorous fumaroles in Sherman Crater, 

the site of thermal unrest in 1975 (Crider and others, 2011), 

where ice volumes are ≈1.3–2.1 x106

 m3 (Park, 2011). An 

eruption could result in significant melting of ice and snow 

into the water reservoir east of the volcano (Gardner, 1995). 

The significant thickness of ice on Mount Adams at high 

elevations could pose a similar hazard, but Mount Adams has 

not been active from the summit region for more than 3,500 

years and seems to be quiescent with the exception of traces 

of hydrogen sulfur gas, suggesting only mild hydrothermal 

activity beneath the ice (Hildreth and Fierstein, 1997). The 

presence of the thickest ice in the headwalls of the Adams 

and White Salmon Glaciers (fig. 73B) suggests that if melt 

water were to originate at the summit, most of it would flow 

down the west side.

Collaborators

Thomas Sisson, Mark Reid, David John, George Breit,

 Robert Horton, Eric Anderson, Burke Minsley, all 

 U.S. Geological Survey.

Selected References

Auken, Esben., Christiansen, A.V., Jacobsen, B.H., Foged, 

Nikolaj., and Sørensen, K.I., 2005, Piecewise 1D laterally 

constrained inversion of resistivity data: Geophysical Prospecting, v. 53, p. 497–506.

Auken, Esben, Nebel, L., Sorensen, K.I., Breiner, M., Pellerin, 

Louis., and Christensen, N.B., 2002, EMMA—A geophysical training and education tool for electromagnetic modeling and analysis: Journal of Environmental and Engineering 

Geophysics, v. 7, p. 57–68.

Christiansen, A.V., and Auken, Esben, 2010, A global measure 

for depth of investigation in EM and DC modeling [abs.]: 

Australian Society of Exploration Geophysicists 21st Conference, Sydney, Australia, extended abstract, v. 2010, 4 p.

Crider, J.G., Frank, David, Malone, S.D., Poland, M.P., 

Werner, Cynthia, and Caplan-Auerbach, Jacqueline, 2011, 

Magma at depth—A retrospective analysis of the 1975 

unrest at Mount Baker, Washington, USA: Bulletin of Volcanology, v. 73, p. 175–189.

Driedger, C.L., and Kennard, P.M., 1986, Ice volumes on 

Cascade volcanoes—Mount Rainier, Mount Hood, Three 

Sisters, and Mount Shasta: U. S. Geological Survey Professional Paper 1365, 28 p.

Finn, C.A., and Deszcz-Pan, M., 2009, The 3-D distribution 

of alteration, ice and water from helicopter magnetic and 

electromagnetic surveys at Mts. Adams, Baker and Rainier, 

Washington—Implications for debris flows hazards [abs.]: 

Geological Society of America Abstracts with Programs, 

v. 41(7), p. 717.

Finn, C.A., Deszcz-Pan, Maria, Anderson, E.D., and John, 

D.A., 2007a, Three-dimensional geophysical mapping of 

rock alteration and water content at Mount Adams, Washington—Implications for lahar hazards: Journal of Geophysical Research, v. 112 (B10204).

Finn, C.A., Deszcz-Pan, Maria, and Bedrosian, P.D., 2012, 

Helicopter electromagnetic data map ice thickness at Mount 

Adams and Mount Baker, Washington: Journal of Glaciology, v. 58, p. 1133–1143.

Finn, C.A., Deszcz-Pan, M., Horton, R., Breit, G., and John, 

D., 2007b, Airborne magnetic and electromagnetic data map 

rock alteration and water content at Mount Adams, Mount 

Baker and Mount Rainier, Washington—Implications for 

lahar hazards and hydrothermal systems: Eos, Transactions 

American Geophysical Union, v. 88(52), Fall Meeting 

Supplement, Abstract NS34A-05.
124 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Finn, C.A., Sisson, T.W., and Deszcz-Pan, Maryla, 2001, 

Aerogeophysical measurements of collapse-prone hydrothermally altered zones at Mount Rainier Volcano, Washington: Nature, v. 409, p. 600–603.

Fowler, C.S.,1935, The origin of the sulphur deposits of 

Mount Adams: State College of Washington, Pullman, M.S. 

thesis, 22 p.

Gardner, C.A., Scott, K.M., Miller, C.D., Myers, B., Hildreth, 

W., and Pringle, P.T., 1995, Potential volcanic hazards from 

future activity of Mount Baker, Washington: U.S. Geological Survey Open-File Report 95–498, 16 p, 1 plate.

Harper, J.T., 1993, Glacier terminus fluctuations on Mount 

Baker, Washington, USA, 1940–1990, and climatic variations: Arctic and Alpine Research, v. 25 no. 4, p. 332–340.

Hildreth, Wes, and Fierstein, Judy, 1997, Recent eruptions 

of Mount Adams, Washington Cascades, USA: Bulletin of 

Volcanology, v. 58, p. 472–490.

Mastin, L.G., 1995, Thermodynamics of gas and steam-blast 

eruptions: Bulletin of Volcanology, v. 57, p. 85–98.

Park, Melissa, 2011, Glacial and geothermal dynamics in 

Sherman Crater, Mount Baker, Washington: Western Washington University, Bellingham, M.S. thesis, 90 p.

Scott, W.E., Iverson, R.M., Vallance, J.W., and Hildreth, 

Wes, 1995, Volcano hazards in the Mount Adams 

region, Washington: U.S. Geological Survey Open-File 

Report 95–492, 11 p.

Siemon, Bernhard, Auken, Esben, and Christiansen, A.V., 

2009, Laterally constrained inversion of helicopter-borne 

frequency-domain electromagnetic data: Journal of Applied 

Geophysics, v. 67, no. 3, p. 259–268.

Tucker, D.S., Driedger, C.L., Nereson, Nadine, Conway, Howard, and Scurlock, John, 2009, Morphology of Mount Baker’s Carmelo (Summit) Crater revealed by ice-penetrating 

radar: Geological Society of America, v. 41, no. 7, p. 191.

Vallance, J.W., 1999, Postglacial lahars and potential hazards 

in the White Salmon River system on the southwest flank of 

Mount Adams, Washington: U. S. Geological Survey Bulletin 2161, 49 p.

Geophysical Investigations for Dam 

and Levee Safety Engineers

By Michael H. Powers and Bethany L. Burton

Issue and Scope

Civil engineers involved in large, Federally funded 

geotechnical projects can benefit from geophysical subsurface 

imaging methods originally developed for mineral and energy 

exploration and production. Decisions for repair or replacement of hundreds of large, aging, earthen dams and thousands 

of miles of earthen levees can involve billions of dollars and 

the safety of millions of people. Geophysical surveys can help 

lower the risks to property and lives when used effectively. 

The application of geophysics to shallow engineering projects in need of high-resolution images of subsurface property 

variations such as compressive strength, shear modulus, 

relative hydraulic conductivity, and relative erosion potential is underutilized. A continuing relationship between U.S. 

Geological Survey (USGS) geophysicists who specialize in 

shallow, high-resolution methods and USACE (U.S. Army 

Corps of Engineers) district engineers involved with dam and 

levee safety projects are working to determine efficiencies in 

the costs of dam and levee risk management. 

Objectives

Increased effective use of geophysical surveys in concert with established methods during the investigation phase 

of large earthen dams and levee systems identified as high 

risk has potential for great cost efficiency in risk-mitigation 

projects. Lowered costs are achieved through greater understanding of critical subsurface features than is possible through 

standard drilling, trenching, and surface mapping alone. The 

use of geophysical results can lead to fewer, more effectively 

placed boreholes and trenches. Examples of geophysical 

investigations used effectively will lead to greater understanding and industrywide acceptance of effective geophysical 

surveys during project investigations.

Background

In 2005, the USACE established a nationwide ranking 

system for estimating high-risk dams based on the probability and consequences of dam failure. Dam safety funding for 

risk mitigation was prioritized starting with the highest risk 

dams. The Sacramento District, California, of the USACE 

contracted industry-standard geophysical investigations at 

several high-risk dams and was interested in augmenting this 

work with more detailed and extensive geophysical investigations performed by USGS research scientists. From 2006 

through 2009, the USACE funded USGS geophysical surveys 
Hazards and Disaster Assessment 125

at Success Dam (fig. 74), Isabella Dam (fig. 75), Hidden 

Dam, and Martis Creek Dam (fig. 76). In 2007, the USACE 

funded USGS geophysical surveys along the American River 

levee system through the city of Sacramento, and in 2011, in 

response to a major flood event along the Missouri River, the 

USGS demonstrated geophysical technology along a levee 

surrounding a power plant in danger of being flooded. All of 

these surveys were initiated as proof-of-concept studies to 

determine if and how increased investment in modern geophysical investigations would be cost effective in large dam 

and levee risk mitigation projects. As the geophysical surveys 

have proven to be cost effective and to provide useful information to the engineers during the investigation phases of 

these projects, the size and scope of subsequent surveys have 

increased with positive results.

Results and Conclusions

Success Dam, above Porterville, California, has seepage and potential liquefaction concerns related to soft sand 

layers or lenses in the original foundation geology. Over 

250 boreholes have been drilled to delineate soft sediments 

and determine depth of competent bedrock. A stratigraphic 

cross section of the dam foundation materials had been created from the borehole information, but depth to competent 

bedrock and lateral and vertical extents of soft layers were 

still unknown. For about the cost of six boreholes, the USGS 

acquired densely spaced resistivity and seismic data that 

matched the existing borehole-derived stratigraphy, identified the extents of soft layers vertically and horizontally, 

and determined depths to weathered and competent bedrock 

across the valley. 

Figure 74. Success Dam above Portersville, California, has over 250 boreholes drilled into the foundation materials to characterize 

soft sediments with a potential for liquefaction. Geophysical surveys across the downstream toe matched the borehole stratigraphy, 

extended the characterization of soft sediments laterally and vertically, and determined depth to weathered and competent bedrock. 

(USGS photograph)
126 Developing Integrated Methods to Address Complex Resource and Environmental Issues

At Isabella Dam, above Bakersfield, California, USGS 

geophysical surveys clearly characterized a fault zone in the 

foundation with detailed offset of bedrock and alluvial layers, 

located depths to water table and bedrock, and indicated shallow alluvial layers with variable amounts of gravels, sands, 

silts, and clays. The information helped determine if dam 

repairs or replacement would most cost-effectively mitigate 

the multiple risks associated with this dam. Replacement is 

very expensive, and a plan for much less costly modifications 

is now underway.

Martis Creek Dam, near Truckee, California, was 

completed in 1972. Heavy seepage stopped the first reservoir 

fill test, followed by modifications. Over the next 20 years, 

successive fill tests were stopped early, and more modifications were performed until in 1995 the dam was deemed 

unsafe to hold more than a minimal reservoir pool confined 

to the banks of the original Martis Creek channel. The fill 

tests had shown that when the pool was raised only 6 meters 

(m) above the minimal level and still confined to the original 

drainage channel, heavy seepage appeared on the downstream side of the left abutment more than 300 m from the 

pool edge. The USGS designed and completed a large survey 

over 18 months that included a grid of resistivity profiles 

in the dry reservoir bottom between the low pool edge and 

the seepage areas. The surveys revealed two large channels 

incised into a paleosurface that had been covered with highly 

permeable glacial outwash. The location, orientation, and 

depth of the buried channels correspond with the seepage 

patterns observed in the fill tests and could provide a more 

focused mitigation plan for this dam.

In 2007, a 10-kilometer (km) section of the American 

River levee system through Sacramento was surveyed by the 

USGS using electrical and electromagnetic surveys to identify 

sand deposits that may be more prone to preferential scour 

during a high-water event that could potentially undermine 

the levees. These surveys were successful in identifying such 

deposits and have resulted in additional electrical and seismic 

surveys to be completed to complement the drilling program 

Figure 75. View of the downstream toe of the west abutment of Isabella Auxiliary Dam showing seismic equipment deployed across a 

fault zone between the top and bottom of the hill. (USGS photograph)
Hazards and Disaster Assessment 127

Figure 76. Student interns help acquire seismic data on the reservoir side of Martis Creek Dam using a trailer-mounted seismic 

source. This reservoir has remained at a level much lower than its designed level due to heavy seepage concerns. The geophysical 

surveys revealed buried paleochannels that corresponded well with the previously unexplained seepage patterns. (USGS photograph)

in mapping the subsurface stratigraphy below the levees and 

the river bottom. More extensive geophysical investigations 

continued in 2011 and 2012 to help determine effective flood 

hazard mitigation along the lower American River.

In June 2011, the USGS responded during a major flood 

event along the Missouri River near Nebraska City, Nebraska, 

to demonstrate an electromagnetic technique to the USACE 

that can be used to differentiate alluvial deposits surrounding 

the levee and possibly provide information about the structural 

integrity and variations in the levee embankment materials 

themselves. Seven kilometers of data were acquired and preliminary results were presented in one day. The objective was 

to identify coarser grained sediment deposits (such as sand and 

gravel), typically associated with paleochannels, which have 

a greater potential to undermine the levees due to their higher 

transmissivity properties than finer grained deposits (such as 

silt and clay).

To realize more effective use of geophysical results, 

improvements are needed in communication between engineers 

and geophysicists at all stages of investigation but especially 

during planning and presentation. Simple, visual correlation 

between standard engineering measurements (such as borehole 

lithology logs or cone penetrometer tests) and geophysical 

results are essential. With ambitious design and execution, 

shallow, applied exploration geophysical surveys can provide 

great cost savings for large geotechnical projects, especially 

when completed in conjunction with a focused drilling program 

that can be partially guided by preliminary geophysical results.

Collaborators

U.S. Army Corps of Engineers, Sacramento District, 

 Omaha District, Chicago District
128 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Bibliography

Asch, Theodore, Burton, B.L., Powers, M.H., Rodriguez, B.D., 

and Bedrosian, P.A., 2007, Electrical characterization of Success Dam in Porterville, CA: Proceedings of the 20th Annual 

Symposium on the Application of Geophysics to Engineering 

and Environmental Problems (SAGEEP), p. 41–60.

Asch, T.H., Deszcz-Pan, Maria, Burton, B.L., and Ball, L.B., 

2008, Geophysical characterization of American River 

levees, Sacramento, California, using electromagnetics, 

capacitively coupled resistivity, and dc resistivity: U.S. 

Geological Survey Open-File Report 2008–1109, 12 p.

Bedrosian, P.A, Burton, B.L., Powers, M.H., Minsley, Burke, 

Phillips, Jeffrey, Hunter, L.E., 2012, Geophysical investigations of geology and structure at the Martis Creek Dam, 

Truckee, CA: Journal of Applied Geophysics, v. 77, p. 7–20.

Burton, B.L., and Cannia, J.C., 2011, Capacitively coupled 

resistivity survey of the levee surrounding the Omaha Public Power District Nebraska City Power Plant, June 2011: 

U.S. Geological Survey Open-File Report 2011–1211, 10 p.

Hunter, L.E., and Powers, M.H., 2008, Geophysical investigations of earthen dams—An overview: Proceedings of the 

21st Annual Symposium on the Application of Geophysics 

to Engineering and Environmental Problems (SAGEEP), 

p. 1083–1096.

Hunter, L.E., Powers, M.H., and Burton, B.L., 2010, Identification of the Polaris fault using lidar and shallow geophysical methods: Proceedings of the 23rd Annual Symposium 

on the Application of Geophysics to Engineering and 

Environmental Problems (SAGEEP), p. 391–399.

Hunter, L.E., Powers, M.H., and Rose, R.S., 2010, The 

foundation of Martis Creek Dam—Revealed by geophysical imaging: Proceedings of the Association of State Dam 

Safety Officials (ASDSO) Conference, Seattle, Wash., 24 p.

Hunter, L.E., Serafini, D.C., Powers, M.H., Haines, S.A., 

Asch, Theodore, and Burton, B.L., 2006, Geophysical 

evaluation of the Success Dam foundation, Porterville, CA: 

Proceedings of the Association of State Dam Safety Officials (ASDSO) Conference, Boston, Mass., p. 27–45.

Minsley, B.J., Burton, B.L., Ikard, Scott, and Powers, M.H., 

2010, Geophysical investigations at Hidden Dam, Raymond, 

California—Summary of fieldwork and data analysis: U.S. 

Geological Survey Open-File Report 2010–1013, 25 p.

Minsley, B.J, Burton, B.L, Ikard, Scott, and Powers, M.H., 

2011, Hydrogeophysical investigations at Hidden Dam, 

Raymond, California: Journal of Environmental & Engineering Geophysics (JEEG), v.16, no. 4, p. 145–164. 

Powers, M.H., and Burton, B.L., 2008, Seismic refraction 

tomography in an urban environment using a vibrator 

source: Proceedings of the 21st Symposium on the Application of Geophysics to Engineering and Environmental 

Problems (SAGEEP), p. 595–605.

Powers, M.H., Haines, S.A., and Burton, B.L., 2007, Compressional and shear wave seismic refraction tomography at Success Dam, Porterville, CA: Proceedings of the 20th Annual 

Symposium on the Application of Geophysics to Engineering and Environmental Problems (SAGEEP), p. 31–40.
Hazards and Disaster Assessment 129

Ground-Based Magnetic Survey for 

a Basalt Aquifer in Frenchman Flat, 

Nevada National Security Site and 

Nevada Test and Training Range, 

Nevada

By Jeffrey D. Phillips and Bethany L. Burton

Issue and Scope

In late September 2010, the United States Geological 

Survey (USGS) conducted a ground-based magnetic survey 

of the northeast portion of Frenchman Flat within the Nevada 

National Security Site (NNSS, formerly the Nevada Test 

Site) and within the adjacent Nevada Test and Training Range 

(NTTR). The survey was designed to address two questions 

of importance to the siting of new model evaluation wells 

downgradient of and within potential groundwater contaminant plumes resulting from the Milk Shake and Pin Stripe 

underground nuclear tests.

Objectives

The first objective was to estimate the horizontal extent 

of a thin, discontinuous basalt flow informally called the basalt 

lava flow aquifer (BLFA) encountered in three wells within 

the alluvial section at depths ranging from 880 to 950 feet 

(ft) (268 to 290 meters [m]) with a thickness ranging from 30 

to 70 ft (9 to 21 m). The edge of the buried basalt flow was 

partially mapped by a previous ground-based magnetic and 

seismic survey conducted by the USGS in the 1960s (Carr and 

others, 1975). The second objective was to estimate the southward extent, beneath alluvium, of basin-and-range normal 

faulting observed in the hills north of Frenchman Flat.

Background

The ground magnetic-profile data were divided into 

23 long lines, designated as lines A through W, and several 

shorter lines (fig. 77). Analysis of each long line was done 

using an updated version of program PDEPTH, a magneticprofile modeling program with built-in source-depth analysis 

options (Phillips, 1997). Because the thin basalt flow was an 

important target of the investigation, each line was analyzed 

for possible locations of magnetic sheet sources as estimated 

using several different analysis methods. Due to the high noise 

levels of the observed magnetic profiles, this analysis was 

done on profiles that had been analytically continued upward 

by 200 feet using Fourier filtering. The 200-foot continuation distance provided adequate low-pass filtering to image 

deeper sources. The resulting magnetic source locations were 

compared to the predicted location of the basalt horizon in the 

three-dimensional geologic model of Frenchman Flat. Solutions within 250 feet of the predicted horizon were assumed 

to represent the basalt. This approach proved to be a very 

effective way to relate the distribution of magnetic sources to 

the subsurface geologic units and to indicate the presence or 

absence of the buried basalt flow. 

To address the question of faults and fault locations, 

contact solutions were estimated, again using magnetic-profile 

data that had been upward continued by 200 feet. Solutions 

with large magnetization contrasts were considered to be more 

reliable indicators of faults or contacts. The recovered sources 

were almost always near the top of the section, within the 

younger alluvium. 

Results and Conclusions

The analysis suggests that the buried basalt flow has 

an outer boundary that extends much farther to the east and 

southeast than previously modeled. Due to the limited ground 

coverage, it is unclear whether an area of missing basalt in 

the interior of the flow is closed off or if it extends across the 

entire flow, potentially separating the flow into two disconnected lobes. Newly interpreted faults include east–west faults 

through the existing well field and several north-trending 

basin-and-range faults on the eastern margin of the hills to the 

north of Frenchman Flat. In general, objectives of the survey 

were met, but the shallow fault solutions leave open the question of additional deeper faulting.

Collaborators

Bonnie Thompson, U.S. Geological Survey Nevada National

 Security Site Program Manager

Sig Drellack, National Security Technologies, LLC

Selected References

Bechtel Nevada, 2005, A hydrostratigraphic framework model 

and alternatives for the groundwater flow and contaminant 

transport model of Corrective Action Unit 98—Frenchman 

Flat, Clark, Lincoln and Nye Counties, Nevada: Bechtel 

Nevada, Department of Energy contract DOE/NV/11718–

1064, Las Vegas, Nev., http://www.osti.gov/bridge/purl.

cover.jsp?purl=/859292-Y8IoHG/859292.pdf.

Carr, W.J., Bath, G.D., Healey, D.L., and Hazlewood, R.M., 

1975, Geology of northern Frenchman Flat, Nevada Test 

Site: U.S. Geological Survey Report USGS-474-216 [NTS188, 1967], 23 p.
130 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 77. Raw magnetic-profile data after removal of the diurnal field plotted as colored dots on a hydrostratigraphic-unit base 

map (Bechtel Nevada, 2005) with alluvial units above the basalt removed. The long lines are labeled by their letter designations. Of 

interest are the red and orange values along lines L, M, F, G, and H, which are known to be due to a discontinuous buried basalt flow 

encountered in nearby wells (as predicted by the dark-gray areas on the map). The red and orange values along lines I, J, K, C, P, 

and Q suggest that the basalt is also present over a large area of the basin to the southeast of the well control (as predicted by the 

light-gray areas on the geologic map).

Total magnetic field anomaly, in nanoTesla

36°50'

36°51'

36°52'

36°53'

36°54'

−115°58' −115°57' −115°56' −115°55' −115°54' −115°53'

Line R

Line S

Line U

Line V

Line I

Line K

Line A

Line N

Line B

Line O

Line J

Line H

Line E

Line Q

Line P Line W

Line D

Line M Line F

Line C

Line L

Line G

Line T

Line R

Line S

Line U

Line V

Line I

Line K

Line A

Line N

Line B

Line O

Line J

Line H

Line E

Line Q

Line P Line W

Line D

Line M Line F

Line C

Line L

Line G

Line T

175 −60 −40 −20 0 20 40 60 260

EXPLANATION

0 1 KILOMETERS

0 1 MILES
Hazards and Disaster Assessment 131

Phillips, J.D., 1997, Potential-field geophysical software 

for the PC, version 2.2: U.S. Geological Survey OpenFile Report 97–725, 34 p., http://pubs.usgs.gov/of/1997/

ofr-97-0725/pfofr.htm.

Phillips, J.D., Burton, B.L., Curry-Elrod, Erika, and Drellack, 

Sigmund, 2011, A ground-based magnetic survey of Frenchman Flat, Nevada National Security Site and Nevada Test 

and Training Range, Nevada—Preliminary results: Underground Test Area (UGTA) Technical Information Exchange 

Meeting, Las Vegas, Nevada, April 27, 2011, 1 p.

Phillips, J.D., Burton, B.L., Curry-Elrod, Erika, and Drellack, Sigmund, 2014, A ground-based magnetic survey of 

Frenchman Flat, Nevada National Security Site and Nevada 

Test and Training Range, Nevada—Data release and preliminary interpretation: U.S. Geological Survey Open-File 

Report 2014–1187, 144 p., 1 pl., http://dx.doi.org/10.3133/

ofr20141187, http://pubs.usgs.gov/of/2014/1187/.

Estimating Bedrock Depth Using 

Constrained Gravity Inversion, Tooele 

Army Depot, Utah

By Jeffrey D. Phillips and Theodore Asch

Issue and Scope

The configuration of the bedrock under the Tooele Army 

Depot (TEAD), Tooele, Utah, helps to contain one or more 

contaminant plumes of saline groundwater. These plumes are 

considered to be environmental hazards by the U.S. Environmental Protection Agency. Knowledge of the bedrock surface 

comes from boreholes and gravity inversion. The U.S. Geological Survey (USGS) was asked to modify a contractor’s report 

on the configuration of the bedrock surface following the 

drilling of additional boreholes and the collection of additional 

gravity stations at TEAD. Although the contractor’s final grid 

of the bedrock surface was provided to the USGS, the methodology used by the contractor was not well documented.

Objectives

The objective of the study was to estimate the thickness 

of the overburden and the elevation of the bedrock surface 

using gravity inversion, while at the same time, forcing the 

result to agree with the available borehole data. The boreholes 

are concentrated over a bedrock high in the center of the study 

area, but there are scattered boreholes throughout the study 

area, many of which do not reach the bedrock surface. The 

bedrock also outcrops along the southern boundary of the 

study area.

Background

A critical early step in the inversion involved the removal 

of the regional gravity field from the complete Bouguer 

anomaly (CBA) data. In the absence of other information, we 

assumed that the regional field was represented by a planar 

surface over the area of interest. To determine the parameters 

of this regional field, we used the only information available, 

the known depth to bedrock in 49 boreholes and at 4 outcrop 

locations. A density of 2.20 grams per cubic centimeter (g/cm3) 

was assumed for the overburden and a density of 2.67 g/cm3

was assumed for the bedrock. The known depth to bedrock was 

translated into an estimated overburden gravity anomaly at the 

53 locations using the Bouguer slab approximation

g h

h

z =

= −

0 01278

0 006007

.

.

∆ρ

(6)

where h is the depth to bedrock in feet and Δρ is the density 

contrast of –0.47 g/cm3. The estimated overburden gravity 
132 Developing Integrated Methods to Address Complex Resource and Environmental Issues

was subtracted from the observed CBA to give estimates of 

the regional gravity field at the 53 locations. A planar surface was then fit to these 53 estimates of regional gravity 

using a linear least-squares approach. This planar surface 

was assumed to represent the regional gravity field, and it 

was subtracted from the gridded CBA data to produce the 

observed residual gravity anomaly grid.

The gravity inversion was done using a modified 

Cordell-Henderson approach (Cordell and Henderson, 1968). 

In this approach an initial overburden thickness model, based 

on the Bouguer slab approximation, is modified in an iterative way to improve the agreement between the calculated 

gravity field of the model and the observed residual gravity field. The initial thickness estimate and a fixed negative density contrast are used to calculate the gravity field 

of the model on a flat surface representing the top of the 

overburden. The calculated gravity field should be negative, 

except in areas where the overburden has zero thickness. If 

the calculated field is not negative, a minimum constant is 

subtracted so as to make it negative. At each iteration, the 

overburden thickness is updated as

new thickness observed gravity

calculated gravity _ old _

_ = 



 



× _ thickness

(7)

Usually only a few iterations are needed to bring the thickness 

and observed gravity into agreement.

In the modified Cordell-Henderson approach, the initial 

Bouguer slab thickness estimate for iteration zero and the 

thickness estimates for subsequent iterations calculated 

using equation 7 are modified to agree with the borehole 

data before each new gravity field is calculated. This is done 

using a correction surface constructed as follows from data 

at the borehole locations. First, the preliminary overburden 

thickness grid produced by equation 7 is sampled at the 

locations of the boreholes and outcrops. Differences between 

the true bedrock depths (where known) or minimum bedrock depths (as represented by the total depths of boreholes 

that did not intersect bedrock) and the sampled values are 

computed. For boreholes (or outcrops) that intersect the 

bedrock surface, the difference is retained regardless of 

sign. For boreholes that do not intersect the bedrock surface, 

the difference is retained if it is negative (the preliminary 

surface is above the bottom of the borehole) and set to zero 

if it is positive (the preliminary surface is below the bottom 

of the borehole). The edited difference is then gridded using 

minimum curvature to produce the correction surface. This 

correction surface is added to the preliminary overburden 

thickness grid to produce the revised overburden thickness 

grid at each iteration.

Following iteration one, additional iterations did not 

produce any real improvement to the result (table 6), so the 

overburden thickness estimate from iteration one was added to 

the topographic surface grid generated from the 2 arc-second 

digital elevation model to produce the final estimated bedrock 

surface elevation (fig. 78).

Results and Conclusions

The final thickness estimate included undulations north 

of the mountain front in the southeast corner of the area. 

These undulations are largely unconstrained by any gravity 

or borehole data. The gravity field calculated from the final 

thickness estimate was in good agreement with the observed 

residual gravity, having a root-mean-squared (RMS) misfit 

of 0.59 milligal (mGal) (table 6). This surface is likely to be 

unreliable in the southwest and northwest corners and elsewhere where borehole data is absent and the gravity stations 

are sparse. Based on these results, the U.S. Army Corp of 

Engineers made significant modifications to their groundwater 

model and later performed verification drilling.

Collaborators

Karl Cole, U.S. Army Corp of Engineers

Reference Cited

Cordell, Lindrith, and Henderson, R.G., 1968, Iterative threedimensional solution of gravity anomaly data using a digital 

computer: Geophysics, v. 33, p. 596–601.

Table 6. Results of modified Cordell-Henderson gravity 

inversion.

[RMS, root-mean-squared; mGal, milligal]

Iteration

Misfit in overburden thickness at 

bedrock boreholes and outcrops Gravity RMS

misfit 

(mGal) Mean

(feet)

Standard deviation

(feet)

0 –5.4 12.6 0.84

1 –6.6 15.3 0.59

2 –5.1 13.9 0.61

3 –5.0 15.3 0.60

4 –5.4 16.1 0.60
Hazards and Disaster Assessment 133

Borehole above bedrock

Borehole to bedrock

Bedrock outcrop

3,556 3,760 3,841 3,898 3,941 3,985 4,050 4,124 4,192 4,263 4,382 4,511 4,740

EXPLANATION

Estimated bedrock elevation, in feet

40°31'

40°32'

40°33'

40°34'

40°35'

−112°25' −112°24' −112°23' −112°22' −112°21' −112°20' −112°19'

3300

3400

3500

3600

3700

3800

North American Datum of 1983

Utah state plane projection, central zone

Bedrock elevation, contour interval = 50 feet

4200

4300

4400

4000

3800

4300

4700

4700

5200

4600

4500

4100

4100

3900

4000

4200

4300

4600

4400

3700

3800

3900

4000

3900

3900

3800

3700

4100

0 1 KILOMETERS

0 1 MILES

Figure 78. Bedrock elevation for the Tooele Army Depot, Tooele, Utah, as estimated using constrained 

gravity inversion. The solution is colored within 1,500 feet of outcrops, boreholes, and gravity stations. 

Note the nonlinear color scale. Reliability is expected to be poor in the uncolored areas.
134 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Development of the ALLTEM, an 

Electromagnetic System for Detection 

and Discrimination of Munitions and 

Explosives of Concern

By Craig W. Moulton, Theodore H. Asch, 

David L. Wright, David V. Smith, Paul H. Wigton, 

and Ronnie D. Coffee

Issue and Scope

There are hundreds of thousands of acres of Federal 

land that are contaminated by munitions and explosives of 

concern (MEC) including unexploded ordnance (UXO) and 

ordnance debris. Congress has mandated that formerly used 

target and bombing ranges be cleaned up and given back to 

civilian use, if possible. One mission of the U.S. Geological Survey (USGS) is to support other Federal agencies in 

managing national resources and protecting environmental 

health. The Department of Defense (DoD) Strategic Environmental Research and Development Program (SERDP) 

and Environmental Security and Technology Certification 

Program (ESTCP) have funded a project to conduct novel 

research whose goal is reducing remediation costs and 

increasing the confidence level of UXO clearance operations. MEC includes items of widely varying size, from 

20 millimeter (mm) projectiles to large bombs that are buried 

at varying depths, from the surface to many feet deep, with 

unknown orientations in the earth and with varying electromagnetic and magnetic properties. Although existing electromagnetic induction (EMI) and magnetometer sensors have 

demonstrated high detection rates under many conditions, the 

ability to discriminate between harmless buried metal objects 

and UXO is extremely limited.

Objectives

The U.S. Geological Survey (USGS) designed, built, 

and tested the ALLTEM (ALL-the-Time-ElectroMagnetic), 

a novel EMI system for UXO detection and discrimination. 

Two main design features distinguish the ALLTEM from 

most other EMI systems. The first is that the ALLTEM drives 

its transmitter loops with a continuous triangular-shaped current waveform, as opposed to a narrow time-repetitive pulse. 

The second is that the ALLTEM can perform UXO surveys 

while continuously moving as opposed to a “cued” mode of 

operation, requiring the system to be immobile at each data 

measurement point.

Figure 79. ALLTEM (ALL-the-Time-ElectroMagnetic) 

transmitter triangular waveform and measured responses 

from steel (ferrous) and brass (nonferrous) balls.

−15

−10

−5

0

5

10

15

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.01 0.011

Response, in volts

Time, in seconds

Excitation current, in amps

4-inch steel ball

(ferrous)

4-inch brass ball

(nonferrous)

Excitation

current

Background

The ALLTEM system transmitter loops are driven by a 

continuous triangle current waveform (fig. 79). The resulting electromagnetically induced target-response voltages in 

the Rx-(receiver) induction loops are measured in the time 

domain. The use of a triangular wave drive in EMI systems 

was originally pioneered to detect large underground ore 

bodies (West and others, 1984) and was adapted for use 

in the ALLTEM (Wright and others, 2006). The use of a 

triangle wave has advantages over systems that use a pulse 

drive. One advantage is that the dynamic-range demands on 

the receiver electronics are smaller. Another is that ferrous 

and nonferrous targets show distinctly different waveforms 

(fig. 79).

Beyond detection of metal objects, the ability to discriminate between UXO and non-UXO targets (typically metallic 

clutter) is a highly prized goal because in many cases more 

than 70 percent of range clearance costs are attributed to digging up harmless scrap metal that could have been left in the 

ground. The ALLTEM has 19 unique combinations of drive 

and receiver coil measurements of the target’s response that 

help considerably in the data analysis process to discriminate 

between UXO and clutter.

The ALLTEM employs a 1-meter (m) cube containing 

the 3-axis drive coils, 8 pairs of small gradiometer receiver 

coils, and a larger, top-to-bottom, gradiometer receiver coil 

pair (fig. 80A). The cube and cart used to transport the cube 

during surveys are constructed from lightweight plastic 

honeycomb with fiberglass faces. The cart, with nonmetallic 

wheels and bearings, is connected by a 3-m fiberglass tow bar 

to a small tractor. The coil drive amplifier and data acquisition system are housed in an electronics chassis on the back 

of the tractor (fig. 80B). Alternating current (AC) power for 
Hazards and Disaster Assessment 135

Figure 80. ALLTEM (ALL-the-Time-ElectroMagnetic) system. A, Parts and components of the cube and cart. B, Performing 

a survey at Camp Stanley, Texas. (USGS photographs)

GPS guidance

monitor

2-kilowatt

generator Transport tractor

ALLTEM cart and cube

Electronics chassis Data aquisition monitor

GPS guidance

monitor

2-kilowatt

generator Transport tractor

ALLTEM cart and cube

Electronics chassis Data aquisition monitor

B

A

Z calibration ball holder

Small sensor coil (1 of 16)

X drive coil (on back)

Y calibration ball holder

ALLTEM cart Y drive coil ALLTEM cube Z drive coil

Fiberglass tow bar

Attitude sensor GPS antenna

1-meter sensor coil (under lid)

Z calibration ball holder

Small sensor coil (1 of 16)

X drive coil (on back)

Y calibration ball holder

ALLTEM cart Y drive coil ALLTEM cube Z drive coil

Fiberglass tow bar

Attitude sensor GPS antenna

1-meter sensor coil (under lid)
136 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 81. Processed ALLTEM (ALL-the-Time-ElectroMagnetic) target response from the 1-meter gradiometer receiver with the 

horizontal coil (hertz) energized. The response from each target detected is represented by the pink or yellow anomaly in the figure. 

The targets are inert unexploded ordnance (UXO) items and scrap metal (clutter) seeded in the calibration grid at the Yuma Proving 

Grounds in Arizona. Targets around the perimeter of the area are 8 lb cannon balls. Some of the smaller anomalies in the upper right 

corner are from clutter items. The rest of the responses are from various UXO items buried at different depths and orientations.

–0.0144 –0.0049 –0.0005 0.0031 0.0065 0.0098 0.0139 0.0201

EXPLANATION

Response, in volts

N

0 5 10 METERS

0 10 20 30 FEET

the electronics and cube coil drive is provided by a 2 kilowatt (kW) generator on the front of the tractor. Real-time 

kinematic (RTK) global positioning system (GPS) is used to 

record the cart’s location during surveys. The cube’s attitude 

information (roll, pitch, yaw, and heading) is recorded from a 

sensor mounted on the front of the cart. A second RTK GPS 

system provides the tractor’s location, which the operator 

uses to help steer during surveys.

The gradiometer configuration of the receiver-loop pairs 

allow for the common mode signals (direct coupled signal 

from the drive coil and cultural noise) to be cancelled by 

electronic subtraction of the pair’s outputs. This allows for 

measurement of the differential-mode induced response from 

any metal target in the ground, which is then amplified and 

filtered before being recorded by the digitizers. Cultural noise 

at 60 hertz (Hz) is greatly attenuated by the choice of 90 Hz as 

the triangle waveform frequency. By recording and averaging 

three 90-Hz receiver waveforms into one, any 60-Hz components in that period sum up to zero.

The three drive coils are sequentially energized with the 

11-amp peak-triangle wave. The ALLTEM system surveys 

are typically driven at 1 m/second, with 0.5 m between lines. 

This speed and line spacing has been found to be adequate for 

insuring that the smallest targets of interest (20-mm projectiles, approximately 20 mm × 85 mm) are detected.

The ALLTEM system has completed a number of controlled tests at Department of Defense standardized test sites 

at the Yuma (YPG), Arizona, and Aberdeen (APG), Maryland, 
Hazards and Disaster Assessment 137

Proving Grounds. These sites consist of areas with known 

targets at known locations, depths, and orientations and areas 

with an unknown number of targets. Figure 81 shows one of 

the 19 target maps produced at the YPG.

The ultimate goal of this technology, as mentioned above, 

was to be able to discriminate between dangerous unexploded ordnance and harmless clutter. To meet this goal, once 

ALLTEM data are acquired, processed, and inverted using 

dipole models to represent the axial-symmetric targets of interest, the data are “classified” into groups of clutter and types of 

UXO. This is achieved by statistically comparing the properties and inverted results of unknown targets to known targets. 

The data presented in figure 82 are an illustration of the ability 

of the ALLTEM data analysis to distinguish between clutter 

and different types of ordnance.

Results and Conclusions

The ALLTEM system has been successful in collecting 

high-quality target data and determining the location, depth, 

size, length, width, and orientation of the targets. The modeled target characteristics were compared to those of known 

UXO items to make the determination as to whether the 

item was UXO or not. These results have been scored by the 

Department of Defense (SERDP and ESTCP) and ALLTEM 

achieved high scores for target detection, classification 

(UXO or non-UXO), and correct identification of UXO 

items. The ALLTEM has moved on to investigating active 

sites, including the Camp Stanley Storage Activity north of 

San Antonio, Texas, where MEC remediation efforts are currently in progress. 

Collaborators

Department of Defense Strategic Environmental Research and

 Development Program

Department of Defense Environmental Security Technology

 Certification Program

Colorado School of Mines, Golden, Colorado

References Cited

West, G.F., Macnae, J.C., and Lamontagne, Y., 1984, A timedomain electromagnetic system measuring the step response 

of the ground: Geophysics, v. 49, p. 1010–1026.

Wright, D.L., Moulton, C.W., Asch, T.H., Brown, P.J., Hutton, 

S.R., Nabighian, M.N., and Li, Y., 2006, ALLTEM for UXO 

applications—First field tests: Proceedings of the Symposium on the Application of Geophysics to Engineering and 

Environmental Problems, April 2–6, 2006, p. 1761–1775.

Figure 82. Classified ALLTEM (ALL-the-Time-ElectroMagnetic) data from Yuma Proving Ground, 

Arizona. Symbols represent the groupings of different munitions detected and analyzed. mm, millimeters.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2

Radius, in meters

Length, in meters

25 mm

37 mm

105M60

81mm

60 mm

20 mm

Clutter

8lb Shot

105HEAT

EXPLANATION
138 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Development of a Ground-Based 

Tensor Magnetic Gradiometer System

By David V. Smith, Robert E. Bracken, S. Ray Hutton, 

and Jeffrey D. Phillips

Issue and Scope

Hundreds of thousands of acres of Federal land are 

contaminated with ordnance debris and unexploded ordnance 

(UXO). Congress has mandated that formerly used target and 

bombing ranges be cleaned up and returned to civilian use, 

if at all possible. One mission of the U.S. Geological Survey 

(USGS) is to support other Federal agencies in managing 

national resources and protecting environmental health. The 

Strategic Environmental Research and Development Program 

(SERDP) funded a project to conduct novel research whose 

goal is reducing remediation costs and increasing the confidence level of clearance operations. This project draws on 

years of USGS expertise in research and development of prototype geophysical instrumentation that pushes performance 

envelopes and expands capabilities of potential field methods.

Objectives

The USGS designed, fabricated, tested, and evaluated a 

tensor magnetic gradiometer system (TMGS) for application 

to detection, location, and discrimination of UXO, shown in 

figure 83. Tensor magnetic gradiometry offers many advantages over scalar potential field methods. By directly measuring 

the gradients of the vector components of the magnetic field at 

a single measurement point, it is possible to determine the distance and direction to a magnetic dipole source. Isolated scraps 

of metal and intact UXO closely approximate a dipole source; 

therefore, a functional TMGS potentially offers advantages 

over conventional magnetic surveys.

Background

Conventional magnetic sensors measure either the total 

magnetic field or a single magnetic vector. For these types of 

sensors to be successful, numerous measurements must be 

acquired at closely spaced locations over the survey area. As 

part of research into volcanic hazards, the USGS developed a 

portable volcano-magnetic observatory to measure subtle magnetic field variations caused by transitions of magma through 

the curie-temperature. The triaxial fluxgate magnetometers 

from this volcano-magnetic observatory were adapted for use 

on a towed platform. Four observatory-grade magnetometer 

heads were affixed to a telescope mirror blank for dimensional 

stability to create the array. The array was mounted on a towed 

platform along with thermometers, inclinometers, and accelerometers to measure platform temperature, attitude, and shock 

and vibration (fig. 84). The data acquisition system, guidance 

system, and power supplies were mounted on a tractor that 

towed the sensor array (fig. 83). A single magnetometer head 

contains three orthogonally mounted fluxgate magnetometer 

cores. Because of manufacturing tolerances, the cores in each 

head are not exactly aligned. Small, but non-negligible inorthogonalities remain. Furthermore, offsets and misalignments 

exist among the four heads in the array. In order to remove the 

intrinsic errors caused by these misalignments, it was necessary to measure them through a rigorous calibration procedure 

using an apparatus that spun the array through a uniform 

magnetic field (fig. 85). Deviations from ideal responses were 

analyzed to yield calibration coefficients that could be used to 

correct the systematic errors.

Controlled tests were conducted at the Standardized Test Site at Yuma Proving Ground, Arizona. This test 

site consists of a calibration grid, a blind test grid, and an 

open field area. The calibration grid—a rectangular grid of 

2 meters (m) by 2 m cells—contains known targets at known 

locations, depths, and orientations for the purpose of defining system responses to UXO and non-UXO items. A similar 

area, the blind test grid, is seeded with targets whose locations, depths, and types are unknown to experimentalists. 

Measurements were collected from all sensors at a rate of 

1,000 hertz (Hz) as the system moved along closely spaced 

parallel survey lines. Accurate positions were obtained at a 

rate of 20 Hz using a Leica 1200 global positioning system. 

To account for system drift, a spin-calibration was performed at the beginning and end of each completed survey. 

Due in part to the great quantity of data obtained and subtle 

interactive effects of the systematic errors, extensive processing was required to extract the 81 necessary calibration 

coefficients and to apply these to the magnetic vector measurements. The final compensated data were used to create 

maps of tensor gradients and tensor magnitude.

Results and Conclusions

The prototype TMGS successfully acquired high-quality 

data in controlled tests, as shown in the tensor gradient data 

(fig. 86A) and tensor magnitude data (fig. 86B). The rainbow 

color scale registers high magnetic gradient values as red 

and low values as blue. This research showed that, though a 

TMGS can outperform competing magnetometer systems, 

a practical system would have to have greater signal-tonoise figures and be more stable electronically. Following 

the demonstration of the TMGS, research was conducted 

into the possibility of modifying the TMGS to incorporate a 

large primary coil to generate an oscillating magnetic field 

that would induce a controlled magnetic response in ferrous 

targets underlying the array. This research showed that such a 

system would have the ability to discriminate between intact, 

axially symmetric UXO and irregularly shaped pieces of 

scrap metal. However, such a system was deemed to be not 

feasible, because the engineering requirements cannot be met 

with existing magnetometers and materials.
Hazards and Disaster Assessment 139

Figure 85. Calibration coefficients were derived from measurements 

made as the magnetometer array was spun on a turntable apparatus 

in a nearly uniform magnetic field on site. (USGS photograph)

Figure 84. Multiaxis magnetometer array is mounted in a 

towed platform, along with thermometers, inclinometers, and 

accelerometers. (USGS photograph)

Figure 83. Tensor magnetic gradiometer system undergoing tests at Yuma Proving Ground, Arizona. (USGS photograph)
140 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 86. High-quality data acquired by the prototype tensor 

magnetic gradiometer system. A, Tensor magnetic gradient data and 

B, tensor magnitude data over a test site seeded with inert unexploded 

ordnance targets and clutter items. nT/m, nano-tesla per meter; TMGS, 

tensor magnetic gradiometer system.

−114.2467

32.8530

32.8529

32.8528

32.8527

32.8526

−114.2466 −114.2465 −114.2464 −114.2463 A

B −114.2467

32.8530

32.8529

32.8528

32.8527

32.8526

−114.2466 −114.2465 −114.2464 −114.2463

EXPLANATION

EXPLANATION

−348.9

−152.9

−61.3

−32.8

−19.3

−12.0

−7.6

−4.7

−2.7

−1.1

0.3

1.8

3.5

5.7

8.5

12.9

20.2

35.1

77.2

308.5

Gxx, (n T /m )

5.3

6.6

8.6

10.6

12.6

14.9

17.5

20.6

24.3

28.9

34.9

42.7

53.5

68.4

89.6

121.3

173.6

285.6

566.6

1872.2

I1, (n T /m )

Collaborators

Strategic Environmental Research and Development 

 Program (SERDP)
Hazards and Disaster Assessment 141

U.S. Geological Survey Environmental 

Studies of the World Trade Center Area, 

New York City, after September 11, 2001

By Roger N. Clark and Gregg A. Swayze

Issue and Scope

The U.S. Geological Survey (USGS) response to the 

World Trade Center disaster illustrates the integrated capabilities of imaging spectroscopy, field work, and laboratory 

analyses. Two days after the September 11, 2001, attack on 

World Trade Center (WTC), the USGS was asked by the U.S. 

Environmental Protection Agency (EPA) and the U.S. Public 

Health Service to conduct a remote-sensing and mineralogical characterization study of lower Manhattan around the 

WTC. This study, conducted in cooperation with the National 

Aeronautics and Space Administration (NASA) and the Jet 

Propulsion Laboratory (JPL), was requested to rapidly provide 

emergency response teams with information on the concentrations and distribution of asbestos and other materials in the 

dusts deposited around lower Manhattan after the September 

11 WTC building collapse in New York City.

Objectives

The airborne visible/infrared imaging spectrometer 

(AVIRIS), an aircraft-based remote-sensing instrument, was 

flown by JPL/NASA over the WTC area on September 16, 

18, 22, and 23, 2001. From September 16 through 19, 2001, 

a two-person USGS field crew visited lower Manhattan to 

field calibrate the AVIRIS remote sensing and collect samples 

of dust and airfall debris from 33 outdoor locations within a 

1-kilometer radius of the WTC. The objectives were to characterize the extent and hazards created by the disaster.

Background

AVIRIS remote sensing measures the amount of light 

reflected from the ground surface in the visible through 

near-infrared spectrum. Individual minerals or other dust 

components have characteristic light reflection features across 

the visible and infrared spectrum, which can be used to map 

spatial variations in the materials making up the dusts deposited around the WTC. 

Samples of the dusts were analyzed using several different methods. All of the results indicate that the dust deposits 

formed from the WTC collapse are heterogeneous and are 

composed largely of particles of glass fibers, gypsum wallboard, concrete, paper, window glass, and other miscellaneous 

materials commonly used in building construction or found in 

office buildings.

Results and Conclusions

AVIRIS was used to detect high-temperature fires burning within the debris through smoke because first responders 

could not see the fires deep within the debris pile (fig. 87). The 

AVIRIS data were used to find location, temperature, and size 

of the hot spots on September 16, 18, 22, and 23, 2001 (see 

Clark, Green, Swayze, Hoefen, and others, 2001; Clark, Green, 

Swayze, Meeker, and others, 2001; Clark and others, 2006).

The USGS detected chrysotile asbestos in more than 

two thirds of the dust samples studied, at levels less than 1 

weight percent. Analyses of the material coating a steel beam 

in the WTC debris detected the presence of chrysotile asbestos at levels as high as 20 percent (by volume) of the coating 

material. See Clark, Green, Swayze, Meeker, and others, 2001 

(2001), Meeker and others (2006), Plumlee and others (2006), 

and Swayze and others (2006) for more details.

Collaborators

National Aeronautics and Space Administration (NASA)

Environmental Protection Agency (EPA)

Primary Products

Materials maps of minerals, organics, and other compounds. Maps of thermal hot spots and their global positioning 

system (GPS) locations as shown here in this report.

References Cited

Clark, R.N., Green, R.O., Swayze, G.A., Hoefen, T.M., Livo, 

K.E., Pavri, Betina, Sarcher, Chuck., Boardman, Joe, and 

Vance, J.S., 2001a, Images of the World Trade Center site 

show thermal hot spots on September 16 and 23, 2001: U.S. 

Geological Survey Open-File Report 01–0405, unpaged, 

http://pubs.usgs.gov/of/2001/ofr-01-0405/.

Clark, R.N., Green, R.O., Swayze, G.A., Meeker, Greg, 

Sutley, Steve, Hoefen, T.M., Livo, K.E., Plumlee, Geoff, 

Pavri, Betina, Sarture, Chuck, Wilson, Steve, Hageman, 

Phil, Lamothe, Paul, Vance, J.S., Boardman, Joe, Brownfield, Isabelle, Gent, Carol, Morath, L.C., Taggart, Joseph, 

Theodorakos, P.M., and Adams, Monique, 2001b, Environmental studies of the World Trade Center area after the 

September 11, 2001, attack: U. S. Geological Survey Open 

File Report 01–0429, [about 260 printed] p., http://pubs.

usgs.gov/of/2001/ofr-01-0429/.
142 Developing Integrated Methods to Address Complex Resource and Environmental Issues

WTC

site

EXPLANATION

Color infrared composite:

 Blue = 0.56 microns

 Green = 1.59 microns

 Red = 2.47 microns

0 200 METERS

0 200 FEET

N

0 100 METERS

0 100 FEET
Hazards and Disaster Assessment 143

Clark, R.N., Swayze, G.A., Hoefen, T.M., Green, R.O., Livo, 

K.E., Meeker, G.P., Sutley, S.J., Plumlee, G.S., Pavri, 

Betina, Sarture, Chuck, Boardman, Joe, Brownfield, I.K., 

and Morath, L.C., 2006, Environmental mapping of the 

World Trade Center area with imaging spectroscopy after 

the September 11, 2001 attack, chap. 4, Gaffney, J.S., and 

Marley, N.A. (eds.), Urban aerosols and their impacts—

Lessons learned from the World Trade Center tragedy: 

Oxford University Press, American Chemical Society, 

Symposium Series 919, p. 66–83, plates 4.1–4.6.

Meeker, G.P., Sutley, S.J., Brownfield, I.K., Lowers, H.A., 

Bern, A.M., Swayze, G.A., Hoefen, T.M., Plumlee, G.S., 

Clark, R.N., and Gent, C.A., 2006, Materials characterization of dusts generated by the collapse of the World Trade 

Center, chap. 5, Gaffney, J.S. and Marley, N.A. (eds.), Urban 

aerosols and their impacts—Lessons learned from the World 

Trade Center tragedy: Oxford University Press, American 

Chemical Society, Symposium Series 919, p. 84–102.

Figure 87 (facing page). False-color images showing the core 

affected area around the World Trade Center (WTC) extending 

from 5 to 12 days after the collapse. Hot spots appear orange and 

yellow. Dozens of hot spots are seen September 16 and 18, 2001, 

but most had cooled or the fires had been put out by September 

23. The September 18 image is dark because of clouds that 

blocked sunlight but not light emitted by the fires. The explanation 

shows hot-spot locations (A–J) in table I of Clark and others 

(2006). Analysis of the data indicates temperatures greater than 

700 °C. More than three dozen hot spots are identified in the core 

zone. By September 23, only four, or possibly five, hot spots are 

apparent in the image, with temperatures cooler than those on 

September 16. Vegetated areas are green, water is blue, and the 

smoke from the fires appears as a light-blue haze. White and 

lighter blue areas are rooftops, roads, and concrete as well as 

dust and debris from the collapsed buildings. Dust, probably more 

than a few millimeters thick (the optical depth), appears in shades 

of brown around the core WTC area on September 16. 

Plumlee, G.S., Hageman, P.L., Lamothe, P.J., Ziegler, T.L., 

Meeker, G.P., Theodorakos, P.M., Brownfield, I.K., Adams, 

M.G., Swayze G.A., Hoefen, T.M., Taggart, J.E., Clark, 

R.N., Wilson, S.E., and Sutley, S.J., 2006, Inorganic chemical composition and chemical reactivity of settled dusts 

generated by the World Trade Center building collapse, 

chap. 12, Gaffney, J.S. and Marley, N.A. (eds.), Urban aerosols and their impacts—Lessons learned from the World 

Trade Center tragedy: Oxford University Press, American 

Chemical Society, Symposium Series 919, p. 238–276, 

plates 12.1–12.2.

Swayze, G.A., Clark, R.N., Sutley, S.J., Hoefen, T.M., 

Plumlee, G.S., Meeker, G.P., Brownfield, I.K., Livo, K.E., 

and Morath, L.C., 2006, Spectroscopic and X-ray diffraction analyses of asbestos in the World Trade Center dust, 

chap. 3, Gaffney, J.S. and Marley, N.A. (eds.), Urban aerosols and their impacts—Lessons learned from the World 

Trade Center tragedy: Oxford University Press, American 

Chemical Society, Symposium Series 919, p. 40–65.
144 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Spectral Studies of the Deepwater 

Horizon Oil Spill

By Gregg A. Swayze and Roger N. Clark

Issue and Scope

Remote sensing of surface oil has the potential to provide 

emergency responders and scientists with a tool to monitor 

an oil spill, remotely measure variations in its chemistry, and 

examine how the oil interacts with its surroundings on a large 

scale. Such a tool can help scientists develop insights into 

the fate of petroleum in the environment and whether it leaks 

from natural or anthropogenic sources. A rapid, quantitative, 

remote-sensing method is needed to map the extent of oil 

spills, assess their chemistry, and calculate their volume so 

adequate resources can be devoted to cleanup efforts.

Though satellite color-broadband imagery can show the 

location of surface oil, it is difficult to assess its thickness and 

volume with these data because it has a relatively low signalto-noise ratio and does not contain enough information to 

robustly correct for interfering atmospheric aerosols and atmospheric gas absorptions. Alternatively, imaging spectroscopy, 

a relatively new type of ultraviolet to near-infrared remote 

sensing that measures reflected light in hundreds of contiguous 

spectral channels can overcome these difficulties to provide 

quantitative estimates of oil spill thickness and volume. 

Objectives

In response to a request by National Oceanic and Atmospheric Administration for an estimate of the volume of oil 

floating on the ocean surface from the Deepwater Horizon 

oil spill in the Gulf of Mexico, a method of near-infrared 

(NIR) imaging spectroscopic analysis was developed to map 

the locations of thick oil floating on water (Clark and others, 

2010). The method uses the shape of NIR absorption features 

and spectral continuum slopes due to organic compounds 

found in oil to identify different oil chemistries, including its 

weathering state and thickness. These diagnostic vibrational 

absorptions are too weak for detection in thin oil sheens (a few 

microns), but thicker (a few millimeters) water-in-oil emulsion 

slicks have strong detectable absorptions and are bright in the 

NIR compared to surrounding water (fig. 88). 

Our experience in analyzing imaging spectrometer data 

acquired over Hurricane Katrina damaged areas of the Gulf 

Coast and open ocean suggested that thick crude oil emulsions 

could be differentiated from seaweed and algal life floating on 

the surface of the ocean (Swayze and others, 2007). With this 

experience in mind, remote-sensing data for this analysis were 

collected by the UV-NIR 224 spectral channel National Aeronautics and Space Administration (NASA) airborne visible/

infrared imaging spectrometer (AVIRIS) instrument, which 

was flown over the oil spill on May 17, 2010. 

Background

Because of the large extent of the Deepwater Horizon oil 

spill, AVIRIS flight lines could cover only a portion of the spill 

on a relatively calm, nearly cloud-free day. Flight lines were 

oriented and timed to avoid sun glint, which complicates data 

analysis. The U.S. Geological Survey (USGS) Tetracorder 

“shape-matching” spectral identification system (Clark and 

others, 2003) was used to turn AVIRIS images into colorcoded oil:water ratio, areal fraction, thickness, and volume 

maps for thick oil floating on the ocean surface within the 

limits of light penetration into the oil.

An emulsion sample collected on a May 7, 2010 boat 

traverse to the incident site (fig. 89) was used to create a series 

of emulsions that spanned the entire oil:water range by addition of seawater or evaporation of contained water. In all, 22 

reference spectra of these lab-constructed emulsions measured 

at thicknesses ranging from 0.025 to 28 millimeters (mm) 

were used for spectral mapping. The proportion of emulsion to water covering a given pixel can be calculated based 

on the reflectance value (that can vary between 0 and 1) at 

1.3 microns and the assumption that the spectral contribution 

of water at that wavelength is essentially zero.

Depending on the relative depths of oil and water-related 

NIR absorptions, the oil-to-water ratios of thick emulsion 

slicks were estimated for pixels in the AVIRIS data (fig. 90). 

The volume of oil in a pixel is a function of the area of the 

pixel, areal fraction of oil in that pixel, thickness of emulsion 

in that pixel, and the average oil:water ratio of the emulsion 

in that pixel. Values for each of these parameters were derived 

from the instrument flight altitude and the spectrally matching 

emulsion selected by Tetracorder for a given pixel. On this 

same day a NASA MODIS (Moderate Resolution Imaging 

Spectroradiometer; Terra) satellite-broadband image of the 

spill with a strong sun glint component was acquired from 

orbit. In this case sun glint helps define the boundaries and 

internal structure of the spill, and when compared to overlapping higher spatial resolution (8.5 × 8.5 meters [m] per pixel) 

AVIRIS data, indicates that the brownish-gray core of the spill 

was composed of emulsion slicks (2 percent) and broad intervening sheens, whereas its gray outer regions were composed 

entirely of sheens at the relatively coarse spatial resolution of 

the MODIS image (250 × 250 m/pixel). 

Results and Conclusions

Tetracorder-derived lower limits for oil volumes within 

the top few millimeters of the ocean surface directly probed 

with the NIR light in the AVIRIS scenes were 19,000 (conservative) to 34,000 (aggressive) barrels of oil. Based on 

laboratory measurements, NIR photons penetrate only a few 

millimeters into oil-water emulsions. As such, the oil volumes derived with this method are lower limits. Spectra of 

emulsions begin to resemble one another beyond a certain 

thickness threshold because light can only penetrate a certain 

depth before it is either absorbed or scattered back out of an 
Hazards and Disaster Assessment 145

Figure 88. Laboratory spectra of oil:water emulsion from the Deepwater Horizon oil spill. Sample (DWH10-3) 

collected May 7, 2010. At visible wavelengths, the oil is very absorbing and does not change color significantly 

with thickness. At infrared wavelengths, both reflectance levels and absorptions due to organic compounds 

vary in strength with thickness. This sample contains approximately 40 percent water as determined by heat 

separation. Black line is for illustrative purposes to better visualize continuum endpoints used for mapping 

individual absorptions. From Clark and others (2010). μm, micrometers; mm, millimeters.

Visible

spectrum

4 mm

thickness

0.1 mm

thickness

1.2-μm

C-H feature

1.73-μm

C-H feature

2.3-μm

C-H feature

0.6

0.5

0.4

0.3

0.2

0.1

0.0

0.5 1.0 1.5 2.0 2.5

Reflectance

Wavelength, in micrometers

emulsion’s surface. The conservative and aggressive volume 

estimates are based on choosing either 2 millimeters (mm) 

(conservative) or 4 mm (aggressive) for AVIRIS spectra of 

sea-surface emulsions that spectrally resemble similar-looking 

reference emulsions with those thicknesses.

On May 17, 2010 AVIRIS covered about 30 percent of the 

core spill area. Areas of oil sheen lacking oil emulsion slicks 

outside of the core spill were not evaluated for oil volume in 

this study. If the core spill areas not covered by flight lines 

contained similar amounts of oil and water-in-oil emulsions, 

then extrapolation to the entire core spill area defined by the 

MODIS image indicates a minimum of 66,000 to 120,000 barrels of oil were floating on the surface. Further, the detection is 

only of thick surface oil and does not include oil in sheens, oil 

under the surface, oil washed onto land, or oil burned, evaporated, or biodegraded as of May 17. These minimum surface 

volumes form the basis of the Mass Balance Team’s flowrate estimates (Labson and others, 2010). Because NIR light 

penetration within emulsions is limited, and having made field 

observations that oil emulsions sometimes exceeded 20 mm 

in thickness, we estimate that the volume of oil, including oil 

thicker than can be probed in the AVIRIS imagery, is possibly 

as much as 150,000 barrels in the AVIRIS scenes. When this 

value is projected to the entire spill, it gives a volume of about 

500,000 barrels of thick oil remaining on the ocean surface as 

of May 17. This method can be applied to future spills for estimating emulsion oil:water ratios and their volume to help direct 

recovery efforts to areas where they are most effective.
146 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 90 (facing page). Mapping results for oil-to-water ratio 

for a portion of AVIRIS (airborne visible and infra-red imaging 

spectrometer) flight line (May 17, 2010). The width of the scene is 

about 5.5 kilometers and north is at about the 4 o’clock position. 

Black areas on the right panel are where no thick oil was 

detected. The center of this image is about 12 kilometers westsouthwest of the Macondo well site. From Clark and others (2010).

Figure 89. Oil emulsion from the Deepwater Horizon oil spill in the Gulf of Mexico off the Louisiana coast. Photograph taken on May 7, 

2010, by Sonia Gallegos and Gregg Swayze.

Collaborators

National Aeronautics and Space Administration 

California Institute of Technology/Jet Propulsion Laboratory 

National Oceanic and Atmospheric Administration 

U.S. Geological Survey, Minerals and Health Project 

Funding provided by U.S. Coast Guard

Primary Products

We provided the first independent Federal Government 

estimate for the volume of oil floating on the ocean surface as of 

May 17, 2010. This information was used to estimate a minimum range flow rate for the Macondo well at between 12,500 to 

21,500 barrels of oil per day for 27 days from April 20 to May 

17, 2010. This flow rate implied that the Deepwater Horizon oil 

spill was larger than that of the Exxon Valdez as of this date.
Hazards and Disaster Assessment 147

EXPLANATION

Oil:Water >90:<10

 80:20

 60:40

 40:60

 23:77

 6:94

 1:99

~60:40

>90:<10

 80:20

 60:40

 40:60

 23:77

 6:94

 1:99

~60:40

A B

0 1 KILOMETERS

0 1 MILES
148 Developing Integrated Methods to Address Complex Resource and Environmental Issues

References Cited

Clark, R.N., Swayze, G.A., Leifer, Ira, Livo, K.E., Kokaly, 

Raymond., Hoefen, Todd, Lundeen, Sarah, Eastwood, 

Michael, Green, R.O., Pearson, Neil, Sarture, Charles, 

McCubbin, Ian, Roberts, Dar, Bradley, Eliza, Steele, 

Denis, Ryan, Thomas, Dominguez, Roseanne, and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) 

Team, 2010, A method for quantitative mapping of thick oil 

spills using imaging spectroscopy: U.S. Geological Survey 

Open-File Report 2010–1167, 51 p., http://pubs.usgs.gov/

of/2010/1167/.

Clark, R.N., Swayze, G.A., Livo, K.E., Kokaly, R.F., Sutley, S.J., Dalton, J.B., McDougal, R.R., and Gent, C.A., 

2003, Imaging spectroscopy—Earth and planetary remote 

sensing with the USGS Tetracorder and Expert Systems: 

Journal of Geophysical Research, v. 108, no. E12, 5131, 

doi:10.1029/2002JE001847, 44 p., http://speclab.cr.usgs.

gov/PAPERS/tetracorder/.

Labson, V.F., Clark, R.N., Swayze, G.A., Hoefen, T.M., 

Kokaly, Raymond, Livo, K.E., Powers, M.H., Plumlee, 

G.S., and Meeker, G.P., 2010, Estimated lower bound for 

leak rates from the Deepwater Horizon spill—Interim report 

to the Flow Rate Technical Group from the Mass Balance 

Team: U.S. Geological Survey Open-File Report 2010–

1132, 4 p., http://pubs.usgs.gov/of/2010/1132/.

Swayze, G.A., Furlong, E.T., and Livo, K.E., 2007, Mapping 

pollution plumes in areas impacted by Hurricane Katrina 

with imaging spectroscopy [abs.]: American Geophysical Union, v. 88, no. 52, Fall Meeting, Abstract H31L-07, 

http://www.agu.org/meetings/fm07/fm07-sessions/fm07_

H31L.html.
Unlocking Secrets of East Antarctica 

with Geophysics

By Carol A. Finn

Issue and Scope

Exploration, whether for resources or knowledge of Earth 

and beyond, is a fundamental imperative for man. One of the 

least explored parts of the planet is East Antarctica whose 

geology and past is shrouded by the East Antarctic Ice Sheet. 

During the International Polar Year (IPY, 2007–2009), a team 

of seven nations launched an expedition to the Gamburtsev 

Subglacial Mountains, a hidden range the size of the European 

Alps. This multinational, multidisciplinary effort included aerogeophysics, traverse programs, and passive seismic instrumentation complimented by ice core and bedrock drilling. A central 

component of the Gamburtsev Mountains expedition was a 

major aerogeophysical survey targeted at understanding the 

tectonic origin of these enigmatic mountains, providing crucial 

new inputs into ice sheet models, identifying potential drilling 

sites for the international ice core community, and providing 

key site survey support for the Chinese ice and bedrock drilling 

efforts. In addition, understanding the evolution of the greater 

East Antarctic Precambrian shield will help constrain understanding of the Precambrian plate reconstructions (Finn and 

Pisarevesky, 2007) and Cenozoic ice sheet development (Behrendt and others, 2007) critical to climate and resource studies.

A major new airborne dataset including gravity, magnetics, ice thickness, SAR (Synthetic Aperture Radar) images of 

the ice-bed interface, near-surface and deep internal layers, 

and ice-surface elevation was acquired during the IPY. The 

U.S. Geological Survey (USGS) is continuing its long tradition—starting with the first magnetic survey ever conducted in 

Antarctica in 1946—of collecting, processing, and archiving 

the aeromagnetic data. Interpretation required innovative 

methods and approaches (for example, see Phillips, 1997; 

Phillips, 2007).

Objectives

The Gamburtsev Subglacial Mountains are important 

because they are thought to be the location where the ice 

sheet we know today initiated its march across Antarctica. 

Unravelling the history of the Gamburtsev Mountains provides climate studies with a better understanding, not just of 

past changes on Earth, but possible future scenarios as well. 

One hundred and twenty thousand kilometers (km) of new 

aerogeophysical data were collected and merged with satellite 

and previous airborne geophysical data resulting in data over 

an area of 2,000 × 1,500 km and providing the most comprehensive geophysical perspective of crustal architecture and 

mountain-building processes in interior East Antarctica. The 

objectives of this study are to map and model geophysical 

data from East Antarctica and to determine models for the 

origin of the Gamburtsev Mountains.

Background

The Gamburtsev Subglacial Mountains are the least 

understood tectonic feature on Earth because they are completely hidden beneath the East Antarctic Ice Sheet. Their high 

elevation and jagged topography are intriguing. How could 

such a topography, which is characteristic of recently formed 

and uplifted tectonic features, have formed in the interior of 

an ancient, geologically dead continent (Veevers, 2011)? The 

preservation of Alpine topography in the Gamburtsevs may 

reflect extremely low long-term erosion rates beneath the ice 

sheet but do not explain the uplift of the mountains. Analysis 

and modeling of the geophysical data were the first steps in 

unlocking the secrets of the tectonic history of these enigmatic 

mountains. This required application of techniques developed 

at the USGS including filtering, depth estimates (Finn and 

Ravat, 2004), equivalent source determination, and modeling 

(Phillips, 1992, 1997, 2000, 2001, 2007). The results from 

application of these techniques helped constrain modeling of 

the magnetic, gravity, radar, and seismic data.

Results and Conclusions

The new radar data reveal highly dissected Alpine 

topography reaching maximum elevations of 3,000 meters 

(m) and a median elevation of about 1,400 m in the north- to 

south-trending Gamburtsevs (fig. 91). The magnetic data 

distinguish several basement provinces indicating that interior 

East Antarctica is probably composed of a mosaic of different Precambrian cratons and orogens as in other parts of East 

Antarctica (Finn and others, 2006; Finn and others, 2011; 

Goodge and Finn, 2010). The linear, northeast-trending magnetic anomalies that characterize much of the Gamburtsevs are 

similar to anomalies associated with Precambrian sources to 

the north. Regional northeast-trending Bouguer gravity lows 

and seismic data (Hansen and others, 2010) define a thickened 

Precambrian crust under the Gamburtsev province (fig. 91) 

(Ferraccioli and others, 2011).

Gravity models, constrained by seismic data (Hansen and 

others, 2010) and magnetic depth estimates (Phillips, 2002; 

Finn and Ravat, 2004), indicate an anomalously high density 

lower crustal root beneath the northern and central Gamburstevs. These high densities are comparable to those modelled 

Databases and Framework Studies
150 Developing Integrated Methods to Address Complex Resource and Environmental Issues

beneath old collisional orogens whose dense lower crustal 

roots lost buoyancy owing to temperature decreases and metamorphism (Leech, 2001; Fischer, 2002). Precambrian ages of 

the Gamburtsev and Vostok provinces suggest that collisional 

events associated with Rodinia or earlier supercontinental 

assembly formed the crustal root (Ferraccioli and others, 2011) 

(fig. 91).

More recent tectonic events must have rejuvenated the 

crustal root and triggered uplift of the modern Gamburtsevs 

(Ferraccioli and others, 2011). Extension around 250 million years (m.y.) ago and oblique rifting ≈100 m.y. ago led to 

the formation of an extensive rift-valley system with uplifted 

flanks (Lambert rift, fig. 91). The new data reveal that the Lambert rift branches at the northwestern edge of the Gamburtsevs 

into narrow basins that surround the Gamburtsev province 

(fig. 91). Collectively, the rifts form part of a newly identified 

East Antarctic rift system, with similar geometry and length 

to the modern East African rift system (fig. 91). Today, these 

rift basins host the largest of all subglacial lakes in Antarctica 

(for example, Lake Vostok, fig. 91), which resemble in size rift 

lakes in East Africa (Ferraccioli and others, 2011; Finn, 2011). 

Mechanical unloading of the lithosphere during extension 

and consequent isostatic rebound produces high topography 

along rift flanks. The rifting enhanced the buoyancy of the 

crustal root by heating and possible introduction of water. The 

uplift of the Gamburtsevs was driven by a combination of the 

buoyancy of the root and the isostatic response—the readjustment of the level of the crustal root in the underlying mantle—

to mechanical and erosional unloading of overlying rock along 

the rift flank and in the glacial valleys (Veevers, 2011). The 

uplifted regions were incised, first by rivers and then (from 

34–14 m.y. ago) by glaciers, to create the steep peaks and valleys of the Gamburtsevs. The youthful topography of the Gamburtsevs was then literally frozen by the East Antarctic Ice Sheet 

≈14 Ma (Mega-annum). The models show that the combination 

of rift-flank uplift, root buoyancy, and the isostatic response to 

fluvial and glacial erosion explain the high elevation and relief 

of the Gamburtsevs. The evolution of the Gamburtsevs demonstrates that rifting and preserved orogenic roots can produce 

broad regions of high topography in continental interiors 

without significantly modifying the underlying Precambrian 

lithosphere. In addition, mountain building is often attributed 

to a single tectonic event in contrast to the multiple events over 

a billion years that formed the Gamburtsevs. Any pre-existing 

conditions for mountain building are often unknown. Therefore, 

the Gamburtsevs may inform studies of other mountain ranges 

where a youthful look may mask a hidden past.

Collaborators

Robin Bell (Lamont-Doherty Earth Observatory)

Fausto Ferraccioli (British Antarctic Survey)

Detelef Damaske (German Geological Survey)

John Goodge (University of Minnesota-Duluth)

Tom Jordan (British Antarctic Survey)

Lester Anderson (British Antarctic Survey)

Mark Fahnstock (University of New Hampshire)

David Braaten (University of Kansas)

Adrian Smith (Lamont-Doherty Earth Observatory)

Jared Abraham (U.S. Geological Survey)

Eric Anderson (U.S.Geological Survey)

References Cited

Behrendt, J.C., Finn, C.A., and Blankenship, D.D., 2007, 

Question of ages of Cenozoic volcanic centers inferred 

beneath the West Antarctic Ice Sheet (WAIS) in the West 

Antarctic rift system (WR) from coincident aeromagnetic 

and radar ice sounding surveys: Eos, Transactions American Geophysical Union, v. 88, Fall Meeting Supplement, 

Abstract C51A-0068.

Figure 91. Three-dimensional perspective of the Gamburtsev 

Subglacial Mountains, including a view of the deep root imaged 

beneath the range and of the thinner crust of the East Antarctic 

rift system that surrounds the mountains (modified from 

Ferraccioli and others, 2011).

- - -

Gamburtsev

Mountains
Databases and Framework Studies 151

Ferraccioli, Fausto., Finn, C.A., Jordan, T.A., Bell, R.E., 

Anderson, L.M., and Damaske, Detlef., 2011, East Antarctic 

rifting triggers uplift of the Gamburtsev Mountains: Nature, 

v. 479, p. 388–394.

Finn, C.A., and Pisarevesky, S., 2007, New airborne magnetic 

data evaluate SWEAT reconstruction, in Antarctica., in

Cooper, A.K., Raymond, C.R., and 10th ISAES Editorial 

Team, eds., Antarctica—A keystone in a changing world—

Online proceedings of the 10th International Symposium 

on Antarctic Earth Sciences [abs]: U.S. Geological Survey 

Open-File Report 2007–1047, Extended Abstract 170, 4 p.

Finn, C.A., and Ravat, D., 2004, Magnetic depth estimates and 

their potential for constraining crustal composition and heat 

flow in Antarctica: Eos, Transactions American Geophysical 

Union, Fall Meeting Supplement, v. 85, Abstract T11A1236.

Finn, C., Ferraccioli, F., and Golynsky, A., 2011, Geology of 

East Antarctica from a geophysical perspective—Some of 

the latest news [abs.]: 11th International Symposium on 

Antarctic Earth Sciences, July 10–15, 2011, Edinburgh, 

Scotland, p. 219.

Finn, C., Ferraccioli, Fausto, Jordan, Tom, Block, Adrienne, 

and Bell, R.E., 2011, Rift controls on the location of some 

large subglacial lakes in East Antarctica [abs.]: 11th International Symposium on Antarctic Earth Sciences, July 10–15, 

2011, Edinburgh, Scotland, p. 140.

Finn, C.A., Goodge, J.W., Damaske, DDetlef, and Fanning, C.M., 2006, Scouting craton’s edge in Paleo-Pacific 

Gondwana, in Fütterer, D., Damaske, D., Kleinschmidt, 

G., Miller, H., and Tessensohn, F., eds., Antarctica—

Contributions to global earth sciences: 9th International 

Symposium on Antararctic Earth Sciences, Potsdam, 

Germany, Alfred Wegener Institute, p. 165–174.

Fischer, K.M., 2002, Waning buoyancy in the crustal roots of 

old mountains: Nature, v. 417, p. 933–936.

Goodge, J.W., and Finn, C.A., 2010, Glimpses of East Antarctica—Aeromagnetic and satellite magnetic view from the 

central Transantarctic Mountains of East Antarctica: Journal 

of Geophysical Research, v. 115, p. 22.

Hansen, S.E., Nyblade, A.A., Heeszel, D.S., Wiens, D.A., 

Shore, Patrick, and Kanao, Masaki, 2010, Crustal structure 

of the Gamburtsev Mountains, East Antarctica, from S-wave 

receiver functions and Rayleigh wave phase velocities: Earth 

and Planetary Science Letters, v. 300, p. 395–401.

Leech, M.L., 2001, Arrested orogenic development—

Eclogitization, delamination and tectonic collapse: Earth 

and Planetary Science Letters, v. 185, p. 149–159.

Phillips, J.D., 1992, TERRACE–A terracing procedure for 

gridded data, with FORTRAN programs and VAX command procedures, UNIX C-shell and DOS implimentations: 

U.S. Geological Survey Open-File Report 92–5–A–B, 20 p., 

1 diskette.

Phillips, J.D., 1997, Potential-field geophysical software for 

the PC, version 2.2: U.S. Geological Survey Open-File 

Report 97–725, not paged.

Phillips, J.D., 2000, Locating magnetic contacts—A comparison of the horizontal gradient, analytic signal, and 

local wavenumber methods [abs.]: Society of Exploration 

Geophysicists Technical Program Expanded Abstracts, 

p. 402–405.

Phillips, J.D., 2001, Designing matched bandpass and azimuthal filters for the separation of potential-field anomalies 

by source region and source type [abs.]: Australian Society 

of Exploration Geophysicists, 15th Geophysical Conference 

and Exhibition, Expanded Abstracts CD-ROM, p. 4.

Phillips, J.D., 2002, Two-step processing for 3D magnetic 

source locations and structural indices using extended 

Euler or analytic signal methods [abs.]: Society of Exploration Geophysicists, 2002 Technical Program Expanded 

Abstracts, v. 21, p. 727–730.

Phillips, J.D., 2007, Geosoft eXecutables (GX’s) developed by 

the U.S. Geological Survey, version 2.0, with notes on GX 

development from Fortran code: U.S. Geological Survey 

Open-File Report 2007–1355, 111 p.

Veevers, J.J., 2011, Earth’s longest fossil rift-valley system: 

Nature, v. 479, p. 304–306.
152 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Linking Petrophysical Properties to 

Environmental and Geological Factors

By Robert J. Horton and Anne E. McCafferty

Issue and Scope

The U.S. Geological Survey (USGS), in cooperation 

with other Federal agencies, has been investigating the negative effects of acid-mine drainage in the upper Animas River 

watershed. Natural weathering of mineral assemblages formed 

from extensive hydrothermal alteration of volcanic and plutonic 

rocks is a significant contributor to the quality of surface and 

groundwater in the watershed. Characterization of in situ rock 

properties related to this weathering is important to establish the 

background influences these rocks may have on water quality. 

Land managers can then use this information to develop realistic 

water-quality targets for cleanup efforts of mined areas. 

As part of the investigation, a suite of samples were collected from volcanic and plutonic rocks that form the majority 

of exposed bedrock in the watershed (fig. 92). The samples 

were analyzed with a wide range of geochemical, mineralogical, and geophysical laboratory methods (McCafferty and others, 2011). Laboratory measurements relate physical property 

values to measurements of acid neutralization capacity (ANC) 

and net acid production (NAP). Results have helped to develop 

an understanding of how chemical and physical characteristics 

change with alteration type for numerous rock types.

Figure 92. Geologic map of the study area with locations of samples. Descriptions of geologic units are given in table 7.

!

!

Silverton

37°55'

Tpa

Tpa

Tpa

Tpa

Tpa

Tpa

Tpa

Tpa

Tig

Tig

Tig

Tig

Tig

Tig

Tb

Tb

Tb

Tb

Tb

Tb

Tb

Tb

Tb

Tdi

Tse

Tse

Tse

Tse

Tsj

Tsj

Tsj

Tsj

107°45' 107°40' 107°35'

37°50'

pg pg

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

Mineral Creek

Cement Creek

Upper Animas River

EXPLANATION

Sample locations

Airborne magnetic and resistivity survey

Streams

Watershed boundary

Silverton caldera margin—dashed where inferred
Databases and Framework Studies 153

Objectives

The objectives of this laboratory study are threefold: 

(1) determine the range of physical properties of different 

geologic units within the watersheds, (2) correlate these properties with their ANC and NAP measurements, and (3) use the 

physical property data as ground truth to interpret airborne 

geophysical survey data in terms of ANC or NAP.

Background

Ninety rock samples were collected from 12 different 

lithologic units (table 7) within the watershed. These units 

include Tertiary dacite intrusion (Tdi), Tertiary granodiorite 

to monzonite (Tig), Tertiary volcaniclastic sedimentary rocks 

(Th), Tertiary pyroxene andesite lava (Tpa), Tertiary rhyolitic 

ash-flow tuff (Tb), Tertiary rhyolitic to dacitic ash-flow tuff 

(Tse), Tertiary megabreccia (Tsemb), Tertiary volcaniclastic 

breccia and lava (Tsj), unknown pre-caldera sedimentary rocks 

(Unk), Precambrian gneiss (pCCg), Precambrian hornblende 

gneiss (pCi), and vein deposits (table 7). The samples were 

analyzed for geochemical and mineralogical composition, 

physical properties, and the environmental properties of ANC 

and NAP. Physical property measurements included density, 

porosity, magnetic susceptibility, electrical resistivity and 

pore-fluid conductivity, and pH. The results of these analyses 

are given in McCafferty and others (2011).

Past studies demonstrated that certain lithologies provided significant ANC and, in addition, have characteristic 

magnetic signatures (McCafferty and others, 2006). The 

addition of other physical property measurements, particularly 

electrical resistivity measurements, provide an important 

additional parameter to further define the airborne geophysical 

signatures related to the ANC and NAP of a rock. The airborne geophysical survey consists of electrical resistivity and 

magnetic anomaly data (Smith and others, 2007). 

The geophysical maps are complicated over the watershed. Figure 93 shows the complex magnetic anomaly signature over the volcanic rocks of Tertiary Burns Member of the 

Silverton Volcanics in southwest Colorado. This unit consists 

of andesite to rhyolite ash-flow tuffs, flows, and flow breccias, 

all of which host the majority of mineralization in the study 

area. It is the most voluminous lithology in the study area, 

both in thickness and aerial extent and exhibits a wide range 

of alteration types (Bove and others, 2007). Because of these 

factors, the Burns volcanic rocks have the greatest impact on 

water quality of any lithologic unit in the study area. Samples 

collected and analyzed within this unit provide important 

ground-truth to accurately interpret the geophysical anomalies.

The magnetic susceptibility of rocks is primarily due 

to the amount of magnetite present, whereas the electrical 

resistivity is dependent on a number of factors including 

mineral composition, porosity, hydration state, and pore-fluid 

chemistry. The amount and quality of water present are usually 

the dominant factors affecting the observed resistivity. All 

other factors being equal, dry rocks are more resistive than wet 

rocks, and rocks saturated with clean water are more resistive 

than rocks saturated with water with high total dissolved solids 

(TDS). Rocks containing alteration minerals and clays are 

typically less resistive than their unaltered counterpart. 

To evaluate the effect of water content on the electrical 

properties of the rock suite, samples were measured when dry, 

Table 7. Geologic unit, age, and lithologic description of rocks sampled for this study. Lithologic descriptions after Yager and Bove (2002).

Geologic unit Lithology Number of 

samples

Vein Quartz-rich vein 1

Tdi Tertiary dacite intrusion 1

Tig Tertiary granodiorite to monzonite 8

Th Tertiary volcaniclastic sedimentary rocks of the Silverton Volcanics 2

Tpa Tertiary pyroxene andesite lava member of the Silverton Volcanics 28

Tb Tertiary rhyolitic ash-flow tuff Burns Member of the Silverton Volcanics 21

Tse Tertiary rhyolitic to dacitic ash-flow tuff Eureka Member of Sapinero Mesa Tuff 9

Tsemb Tertiary megabreccia consisting of andesitic to dacitic blocks encased in ash-flow tuff Eureka 

Member of the Sapinero Mesa Tuff

2

Tsj Tertiary volcaniclastic breccia and lava San Juan Tuff 15

Unk Unknown pre-caldera sedimentary rocks 1

pCCg Precambrian gneiss 1

p_i Precambrian hornblende gneiss; Irving Formation tailings 1
154 Developing Integrated Methods to Address Complex Resource and Environmental Issues

hydrated at 100 percent relative humidity, and 100 percent 

saturated. Water content was determined by weight. Measurements made at different water contents are representative of 

conditions above and below the water table and demonstrate 

the range of resistivities to be expected for a given rock unit 

under different environmental conditions. 

Results and Conclusions

The results of the laboratory measurements show that 

for a given lithologic unit there is a wide range in physical 

properties, particularly magnetic susceptibility and electrical 

resistivity. Figure 94 shows that magnetic susceptibility can 

vary more than four orders of magnitude for a given unit and 

demonstrates that there is significant overlap in the susceptibilities of different units. 

Electrical property measurements indicate the resistivity of 

saturated units typically ranges two to three orders of magnitude 

for a given unit, with significant overlap between different units. 

Collectively, these observations indicate there is not a single 

property value that can be used to characterize a given lithology. 

Multiple samples and multiple analyses are necessary to characterize the variability of the physical properties of a unit. 

Of the 12 lithologic units sampled, 5 units are represented 

by multiple samples, whereas the other 7 units were only 

sampled one or two times (table 7). The “major” lithologic 

Figure 93. Magnetic anomaly map over the volcanic rocks of the Tertiary Burns Member of the Silverton Volcanics, 

southwestern Colorado (Smith and others, 2007).

!

!

!

!

!

!

!

!

!

!

Magnetic

anomaly

nanoteslas

(nT)

Silverton

37°55'

107°45' 107°40' 107°35'

37°50'

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

EXPLANATION

Sample locations

Airborne magnetic and resistivity survey

Streams

Watershed boundary

Mineral Creek

Cement Creek

Upper Animas River

−137.1

−91.2

−69.6

−50.1

−31.3

−11.7

10.5

88.5

218.7

40.4
Databases and Framework Studies 155

Figure 94. Magnetic susceptibility ranges for geologic units sampled. 

Geologic-unit symbols are explained in table 7. n, number of samples; emu/cm3, 

electromagnetic units per cubic centimeter.

Vein Tdi Tig Th Tpa Tb Tse Tsemb Tsj UNK pi pg

Geologic unit

5E-8

5E-7

5E-6

5E-5

0.0005

0.0050

0.0500

0.5000

5.0000

n = 1

n = 1

n = 8

n = 2

n = 28n = 21

n = 9

n = 2

n = 15

n = 1

n = 1

n = 1

Volume susceptibility

emu/cm3

 Median 

25-75 percent 

 Minimum-maximum

EXPLANATION

units, those represented by seven or more samples, include 

units Tb, Tig, Tpa, Tse and Tsj. Table 8 gives the range and 

average of physical properties of the major lithologic units 

and shows the relative ranking of the major units based on the 

average physical or environmental properties of each unit. The 

average properties of these major units provide insight on the 

relative contribution each unit may have on water quality and 

airborne geophysical signature.

As was observed in earlier studies (McCafferty and others, 2006), there appears to be an inverse correlation between 

magnetic susceptibility and NAP. For example, unit Tsj has 

the highest NAP but the lowest average magnetic susceptibility (table 8). Unit Tpa has the highest magnetic susceptibility 

and a relatively low NAP. There may be an inverse correlation between NAP and resistivity because unit Tsj also has a 

relatively low average saturated resistivity. There also appears 

to be an inverse correlation between ANC and resistivity. Unit 

Tig has higher than average resistivities but the lowest average 

ANC. Unit Tb has the highest average ANC and a relatively 

low average hydrated resistivity. 

A number of the observed physical property correlations 

are expected. For example density typically varies inversely with 

porosity and resistivity. Unit Tpa was observed to have the highest average density at 2.70 grams per cubic centimeter (g/cm3

) 

and the lowest average porosity, 1.44 percent, whereas unit 

Tse has a relatively high average porosity and the lowest average resistivity. As postulated by Poisson’s Relation, density and 

magnetic susceptibility are directly proportional, demonstrated 

by unit Tpa, which has both the highest average density and 

susceptibility, and by unit Tse with the lowest average density and 

a relatively low average susceptibility. Another expected observation is the inverse correlation between resistivity and pore-fluid 

conductivity, demonstrated by unit Tig, which has higher than 

average resistivities and the lowest average pore-fluid conductivity. Unit Tig also has the lowest average clay mineral composition, which is consistent with its high bulk resistivity.

Conversely, a number of unexpected correlations were 

observed. Unit Tpa is interesting in that it has the lowest average resistivities and the lowest average porosity. Generally, 

low resistivities are associated with higher water content due 

to high porosity. Unit Tpa also has a relatively low pore-fluid 

conductivity. The combined properties of low resistivity, low 

porosity, and low pore-fluid conductivity indicate unit Tpa 

must have a relatively conductive mineral composition. Mineralogical analysis shows that unit Tpa has the highest average 

total clay content (muscovite + illite + pyrophyllite + kaolinite 

+ montmorillonite) of the major lithologic units.

This study has shown the range of physical properties 

of different geologic units within the watershed. Laboratory 

measurements have helped correlate physical properties with 

ANC and NAP of the rocks and provide the basis for interpretation of airborne geophysical anomalies that delineate 

altered rock that may be acid neutralizing or acid producing. 

Collaborators

U.S. Bureau of Land Management

U.S. Forest Service 
156 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Table 8. Average and relative ranking of major lithologic units based on the average physical or environmental property of each unit.

[Table 8 defines geologic-unit symbols; n, number of samples analyzed; g/cm3, grams per cubic centimeter; emu/cm3, electromagnetic units per cubic centimeter; %, percent; ohm-m, ohm-meters; μS/cm, microsiemens per centimeter; kg/ton, kilograms per ton]

Property Unit n Average Geologic unit

Low Intermediate High

Density (dry) g/cm3 103 2.67

Tse

2.62

Tig

2.65

Tsj

2.66

Tb

2.67

Tpa

2.70

Magnetic susceptibility1 emu/cm3 88 9.00e–4 Tsj

1.03e-4

Tse

1.83e–4

Tb

2.72e–4

Tig

2.55e–3

Tpa

3.64e–3

Porosity2 % 90 2.18 Tpa

1.44

Tb

1.96

Tig

2.22

Tse

2.30

Tsj

2.89

Hydrated resistivity3 ohm-m 69 1.80e4 Tpa

9.00e3

Tb

1.59e4

Tse

1.94e4

Tsj

2.03e4

Tig

2.21e4

Saturated resistivity3 ohm-m 77 3.08e3 Tpa

1.84e3

Tsj

1.90e3

Tse

2.05e3

Tig

3.45e3

Tb

4.41e3

Pore-fluid conductivity uS/cm 72 42.7 Tig

37.2

Tpa

37.3

Tb

37.6

Tse

43.5

Tsj

59.3

Pore-fluid pH pH 72 8.22

Tb

7.86

Tsj

7.91

Tig

8.14

Tpa

8.25

Tse

8.43

ANC4 kg/ton 73 20.83 Tig

3.59

Tpa

14.87

Tse

18.50

Tsj

30.63

Tb

33.96

NAP4 kg/ton 83 41.25

Tb

24.63

Tpa

32.31

Tse

44.19

Tig

60.10

Tsj

65.94

Total clay minerals5 % 33 14.4 Tig

9

Tb

11

Tse 

15

Tsj

16

Tpa

20.5

1

Volume susceptibility in scientific notation.

2

Water-available porosity.

3

Resistivity at 100 hertz, scientific notation.

4

Acid neutralization capacity in kilograms calcium carbonate (CaCO3) per ton.

5

Muscovite + illite + pyrophyllite + kaolinite + montmorillonite from X-ray diffraction analysis.

References Cited

Bove, D.J., Mast, M.A., Dalton, J.B., Wright, W.G., and 

Yager, D.B., 2007, Major styles of mineralization and 

hydrothermal alteration and related solid- and aqueousphase geochemical signatures, in Church, S.E., von 

Guerard, Paul, and Finger, S.E., eds., Integrated investigations of environmental effects of historical mining in the 

Animas River watershed, San Juan County, Colorado: U.S. 

Geological Survey Professional Paper 1651, p. 230–254, 

http://pubs.usgs.gov/pp/1651/.

McCafferty, A.E., Horton, R.J., Stanton, M.R., McDougal, 

R.R., and Fey, D.L., 2011, Geophysical, geochemical, 

mineralogical, and environmental data for rock samples 

collected in a mineralized volcanic environment, upper 

Animas River watershed, Colorado: U.S. Geological Survey Data Series 595, 13 p.

McCafferty, A.E., Yager, D.B., Horton, R.J., and Diehl, S.F., 

2006, Magnetic properties, acid neutralization capacity, and 

net acid production of rocks in the Animas River watershed, 

Silverton, Colorado, in Symposium on the Application of 

Geophysics to Engineering and Environmental Problems, 

19, Seattle, Wash., April 2–6, 2006, Proceedings: Environmental and Engineering Geophysical Society, 10 p.

Smith, B.D., McDougal, R.M., Deszca-Pan, Maryla, and Yager, 

D.B., 2007, Helicopter electromagnetic and magnetic surveys, in Church, S.E., von Guerard, Paul, and Finger, S.E., 

eds., Integrated investigations of environmental effects of 

historical mining in the Animas River watershed, San Juan 

County, Colorado: U.S. Geological Survey Professional 

Paper 1651, p. 230–254, http://pubs.usgs.gov/pp/1651/.

Yager, D.B., and Bove, D.J., 2002, Generalized geologic map 

of part of the upper Animas River watershed and vicinity, 

Silverton, Colorado: U.S. Geological Survey Miscellaneous 

Field Studies Map MF–2377, scale 1:48,000, http://pubs.

usgs.gov/mf/2002/mf-2377/.
Databases and Framework Studies 157

Restoring a National Treasure—

Recovery and Reprocessing of Legacy 

Airborne Data from the Tape Archives 

of the State Company of Geological 

Survey and Mining (GEOSURV-IRAQ)

By David V. Smith, Benjamin J. Drenth, Jared D. 

Abraham, Michael D. Wussow, and Janan K. Saffo

Issue and Scope

Comprehensive geophysical databases constitute an 

enormously valuable asset for a country’s economic development. As part of a program to redevelop the economy of Iraq, 

the Task Force for Business Stability Operations (TFBSO) of 

the U.S. Department of Defense funded projects to modernize 

the scientific capabilities of the State Company of Geological 

Survey and Mining (GEOSURV-IRAQ). The TFBSO turned to 

the U.S. Geological Survey (USGS), Crustal Geophysics and 

Geochemistry Science Center (CGGSC) for its long expertise 

in data acquisition, data processing, and database management 

gained under the USGS Mineral Resources Program.

Objectives

GEOSURV-IRAQ has original printed large-scale maps 

of the reduced and processed aeromagnetic survey, which 

was flown in 1974 by Compagnie General de Geophysique 

of France. Although these paper maps can be digitized 

for further, limited analysis, only the high-quality digital 

flight-line data can be fully analyzed using modern methods. 

Therefore, the goal was to transfer as much data as possible 

from very old nine-track magnetic tapes to modern storage 

media in a universally accessible format. In instances where 

data were corrupted or missing, every effort was made to 

reconstitute the data. In anticipation of at least partial success, USGS scientists involved in the data recovery effort 

trained GEOSURV-IRAQ geophysicists in data reduction, 

analysis, and interpretation methods using state-of-the-art 

software tools. Training workshops were held in Erbil, Iraq, 

and in Istanbul, Turkey.

Background

Following stringent protocols, 29 irreplaceable tapes 

were shipped from the GEOSURV-IRAQ archives in Baghdad, Iraq, to the CGGSC in Lakewood, Colorado. Working 

closely with USGS scientists, Frontier Processing Company 

used 1970s vintage computer hardware to process and read 

the tapes. Magnetic tapes naturally deteriorate with time 

even when stored under ideal conditions. The 35-year-old 

tapes were found to be in extremely poor condition requiring special heat treatments for sticky-tape syndrome before 

attempts could be made to read the tapes without damaging 

the data recorded in tracks on the thin magnetic-oxide layer. 

As each tape was played back, signal levels were monitored 

on an oscilloscope. Adjustments were made to tape speed 

and amplifier gains as necessary to maximize signal amplitude. Extremely corrupted tapes were played back multiple 

times in an effort to capture the faintest signals. Despite 

these compensations, the recovered raw data files were rife 

with data errors caused by marginal pickup of magnetic 

signals. Numerals in the data records were encoded as 8-bit 

bytes in Expanded Binary Coded Decimal Interchange Code 

(EBCDIC) format. Data errors manifested as a numeral converting to a different numeral or to a character because one or 

more of the bits in a byte flipped from “0” to “1” or viceversa. Where long spans of tape suffered from these errors, 

entire blocks of data records were partially or totally lost. 

Sporadic and isolated bit-flips could reliably be detected and 

corrected using custom software routines developed in-house. 

In serious cases of clustered or sequential errors, the numeric 

values were either reconstructed using character-matching 

and pattern-recognition algorithms or replaced with a dummy 

value. In subsequent examinations, dummy values were either 

precisely estimated by interpolation or ultimately deleted. 

The quality of the final recovered data was evaluated using 

statistical methods. Data from each tape were cast into tabulated text files (ASCII format) and into Geosoft Oasis montaj 

databases for further analysis and interpretation. 

Results and Conclusions

Over 99.9 percent of the raw flight-line data on the tapes 

were recovered and saved as universally readable computer 

files. The final outcome (fig. 95) delivered to GEOSURVIRAQ is vastly superior to the original paper map. The 

two large rectangular swaths in the southeastern part of the 

country are due to lack of data, perhaps still on a single tape 

missing from the archive. The high-quality digital databases 

are suitable for modeling and interpretation and for joint 

inversion with existing countrywide gravity data. Because 

these data have been recovered, it will not be necessary to 

fly another aeromagnetic survey, saving Iraq considerable 

time and money. The money that would have been spent 

to fly another full-scale aeromagnetic survey—estimated 

at millions of dollars—can be directed to other economic 

development needs.

Collaborators

The Task Force for Business and Stability Operations of the 

 U.S. Department of Defense

The State Company of Geological Survey and Mining 

 (GEOSURV-IRAQ)

Frontier Processing Company, Centennial, Colorado
158 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Figure 95. Final recovered aeromagnetic data, gridded and merged.

Low Magnetic field anomaly High

EXPLANATION

40°

36°

34°

32°

30°

42° 44° 46° 48°

0

0 60 120 180 KILOMETERS

60 120 180 MILES

Bibliography

Smith, D.V., Drenth, B.R., Fairhead, J.D., Lei, Kaxia, Dark, 

J.A., and Al-Bassam, Khaldoun, 2011, Recovery and 

reprocessing of legacy geophysical data from the archives 

of the State Company of Geology and Mining (GEOSURV) of Iraq and Iraq Petroleum Company (IPC) [abs.]: 

Society of Exploration Geophysicists Expanded Abstracts, 

p. 856–860, DOI:10.1190/1.3628209.
Databases and Framework Studies 159

High-Altitude Magnetic Survey of the 

Conterminous United States, Alaska, 

and Offshore Regions

By Robert E. Bracken and Vicki Childers

Issue and Scope

The Earth’s crust contains numerous geologic structures 

with complicated boundaries in three dimensions where differing rock units adjoin. A number of geophysical methods 

can be used to map these boundaries, each having various 

advantages and limitations. The magnetic method measures 

how the magnetic field is modified by heterogeneities of 

magnetic materials in the Earth’s crust and thereby promotes 

the mapping and modeling of many crustal structures. Generally, any departure from a model of the Earth’s core magnetic 

field constitutes a crustal anomaly, and the characteristics of 

the anomaly can then be used to estimate locations, slopes, 

and extents of a variety of boundaries, thereby delineating the 

associated buried structures. 

Magnetic measurement systems are relatively compact 

and lightweight, and magnetic anomalies of geologic origin tend to have large signals that can be detected from an 

aircraft. Consequently, airborne magnetics platforms can be 

used to map large areas quickly and efficiently. However, 

the observation altitude has a huge effect on what the survey 

actually maps: a low-altitude survey will be dominated by 

shallow structures, and a high-altitude survey will attenuate 

the details of shallow structures allowing the deeper structures to be discerned. 

The issue at hand is that we have a great deal of data collected at very low altitude, and from satellites, we have essentially worldwide coverage at great altitude. Consequently, 

there is a conspicuous gap in our spectral data coverage, which 

can only be filled by data acquisition from aircraft at high 

altitude. Figure 96 provides a conceptual feel for the character 

and magnitude of the data gap. This gap signifies a glaring 

lack of data—worldwide—suitable for modeling mid-to lower 

crustal structures and boundaries. 

Objectives

The objective of a high-altitude magnetic survey is to fill 

the magnetics data gap; an inexpensive means is to add magnetic measurement systems to surveys that are already funded 

and flying. One such survey, the Gravity for the Redefinition 

of the American Vertical Datum (GRAV-D) project, is being 

conducted over the conterminous United States, Alaska, and 

adjacent offshore regions by the National Geodetic Survey 

(NGS) of the National Oceanic and Atmospheric Administration (NOAA). GRAV-D acquires high-altitude airborne gravity 

datasets and combines them with satellite and surface measurements to help generate a gravimetric geoid that defines a new 

vertical datum for the United States (see http://www.ngs.noaa.

gov/GRAV-D/).The survey presents an excellent opportunity for 

gathering high-altitude magnetic data. Toward this end, we have 

already begun piggybacking magnetic surveys onto GRAV-D.

Figure 96. Diagram showing a lack of available signal strength (amplitude) in a spectral gap that needs to be filled by data from 

a high-altitude magnetic survey (Hildenbrand and others 1996). Magsat, magnetic data from the Magsat satellite.

Normalized amplitude

Aeromagnetic data

(Altitude = 1 kilometer)

Magsat

(Altitude = 450 kilometers)

Spectral gap

Wave number, radians per kiometer

0.0

0.0

0.5

1.0

0.2 0.4 0.6 0.8 1.0
160 Developing Integrated Methods to Address Complex Resource and Environmental Issues

Background

Over the years, beginning in the early 1990s, we have 

developed a solid background and understanding of the 

rationale, issues, and procedures associated with flying highaltitude surveys. This expertise is described in Hildenbrand 

and others (1996) when we were working with the ER-2 highaltitude aircraft, and again in Hildenbrand and others (2002) 

when we were working with a Canberra high-altitude aircraft. 

Our most recent endeavor, spring of 2011, was a survey piggybacked onto a NOAA P-3 aircraft flying in northern Alaska 

under the GRAV-D project. 

Results and Conclusions

The recent P-3 aircraft work has resulted in not only a 

good high-altitude magnetic dataset in northern Alaska but 

also a new method for removing aircraft interference from 

magnetic data collected at high altitude. This work has not yet 

been published.

In the bigger picture, however, understanding the 

structure of the mid- to lower crust is essential for developing hazards prediction and mitigation methods, for predicting 

resource locations and extents, and for generally adding to 

our knowledge of Earth processes and enhancement of future 

geosciences research. 

Filling the spectral data gap shown in figure 96 by flying 

a high-altitude magnetic survey of the conterminous United 

States and Alaska would directly provide much-needed data 

for improving the North American magnetic anomaly map 

(NAMAM) to include the accurate intermediate wavelengths 

required for deep crustal interpretation. The NAMAM (North 

American Magnetic Anomaly Group, 2002) distills magnetic 

information gathered by all surveys into what is perhaps the 

most important single reference used for interpreting continental-scale crustal magnetic signatures of North America. The 

Australians have produced a similar map, which is now in its 

fifth generation (http://explorationgeophysics.info/?p=1131), 

and incorporates a great deal of information from high-altitude 

data acquisition.

However, the magnetics data gap remains worldwide: 

few countries, except Australia, have endeavored to conduct 

systematic magnetic surveys at high altitude.

Collaborators

National Oceanic and Atmospheric Administration, National

 Geodetic Survey GRAV-D project. Project Manager:

 Vicki Childers

References Cited

Hildenbrand, T.G., Acuna, Mario, Bracken, R.E., Hardwick, 

Doug, Hinze, W.J., Keller, G.R., Phillips, J.D., and Roest, 

W.R., 2002, Rationale and operational plan for a U.S. highaltitude magnetic survey: U.S. Geological Survey Open-File 

Report 02–366, 22 p., http://pubs.usgs.gov/of/2002/0366/.

Hildenbrand, T.G., Blakely, R.J., Bracken, R.E., Edwards, 

Lynn, Hardwick, Doug, Hinze, W.J., Labson, Vic, Malliot, 

Hal, Nabighian, Misac, Nilsson, Bruno, Phillips, Jeff, 

Quinn, J.M., and Roest, Walter, 1996, Rationale and preliminary operational plan for a high-altitude magnetic survey 

over the United States: U.S. Geological Survey Open-File 

Report 96–276, 55 p. 

North American Magnetic Anomaly Group, 2002, Magnetic 

Anomaly Map of North America: U.S. Geological Survey 

Special Map, scale 1:5,000,000, http://pubs.usgs.gov/sm/

mag_map/.
Publishing support provided by: 

Denver Publishing Service Center

For more information concerning this publication, contact:

Center Director, USGS Crustal Geophysics and Geochemistry Science Center

Box 25046, Mail Stop 964

Denver, CO 80225

(303) 236-1312

Or visit the Crustal Geophysics and Geochemistry Science Center Web site at:

http://crustal.usgs.gov/

Or visit the Central Energy Resources Science Center Web site at:

http://energy.usgs.gov/
Smith and others, eds.—Developing Integrated Methods to Address Complex Resource and Environmental Issues—Circular 1413

ISSN 1067-084X (print)

ISSN 2330-5703 (online)

http://dx.doi.org/10.3133/cir1413