U.S. Department of the Interior

U.S. Geological Survey

Toxic Substances in Surface Waters and 

Sediments—A Study to Assess the Effects 

of Arsenic-Contaminated Alluvial Sediment 

in Whitewood Creek, South Dakota

Edited by James S. Kuwabara and Christopher C. Fuller

Section I

Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, 

South Dakota

By James S. Kuwabara, Cecily C.Y. Chang, and Sofie P. Pasilis

Section II

Evaluation of the Processes Controlling Dissolved Arsenic in 

Whitewood Creek, South Dakota

By Christopher C. Fuller and James A. Davis

Professional Paper 1681

U.S. Geological Survey Toxic Substances Hydrology Program
U.S. Department of the Interior

Gale A. Norton, Secretary

U.S. Geological Survey

Charles G. Groat, Director

U.S. Geological Survey, Reston, Virginia: 2003

For sale by U.S. Geological Survey, Information Services

Box 25286, Denver Federal Center

Denver, CO 80225

For more information about the USGS and its products:

Telephone: 1-888-ASK-USGS

World Wide Web: http://www.usgs.gov/

Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

Toxic substances in surface waters and sediments : a study to assess the effects of 

arsenic-contaminated alluvial sediment in Whitewood Creek, South Dakota : U.S. 

Geological Survey Toxic Substances Hydrology Program / by James S. Kuwabara

... [et al.].

p. cm. -- (Professional paper ; 1681)

Includes bibliographical references.

ISBN 0-607-93722-X (alk. paper)

1. Arsenic--Environmental aspects--South Dakota--Whitewood Creek. 2. 

Water--Pollution--South Dakota--Whitewood Creek. 3. Contaminated sediments--South

Dakota--Whitewood Creek. 4. U.S. Geological Survey Toxic Substances Hydrology 

Program. I. Kuwabara, James S. II. Geological Survey (U.S.) III. Geological Survey 

professional paper ; 1681.

TD427.A77T68 2003

363.738'4--dc22 2003049476

Library of Congress Cataloging-in-Publication Data
 iii

Contents

SECTION I. Effects of Benthic Flora on Arsenic Transport in 

Whitewood Creek, South Dakota, by James S. Kuwabara, 

Cecily C.Y. Chang, and Sofie P. Pasilis

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

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

Purpose and Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Study Site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Methods of Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Field Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Laboratory Studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Results and Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Field Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Laboratory Experiments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Effects of Benthic Flora on Physico-Chemical Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Figures

I–1. Map of the study area along Whitewood Creek, South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

I–2—I–5. Graphs showing:

I–2. Diel trends in pH and irradiance along Whitewood Creek at (A) the

Headwater site, (B) the Sewage-Treatment-Plant site, (C) the Above

Vale site, and (D) the Sheeler Seep site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

I–3. Diel trends in specific conductance and laboratory determinations 

for dissolved-arsenic species for (A) the Above Vale site and (B) the 

Sheeler Seep site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

I–4. Diel trends in pH and concentrations of arsenic species for (A) the 

Above Vale site and (B) the Sheeler Seep site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

I–5. Diel trends in concentrations of dissolved orthophosphate and arsenic 

species at (A) the Above Vale site and (B) the Sheeler Seep site . . . . . . . . . . . . . . . . . . . . . . . 20

Tables

I–1. Estimated biomass for four sampling sites along Whitewood Creek, 

August 4–9, 1986 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

I–2. Field data collected monthly during the summer of 1987 from four sites along 

Whitewood Creek. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

I–3. Physical and chemical characteristics in Whitewood Creek at the Headwater 

site, monitored between August 29 and 30, 1988, to examine diel fluctuations in

these characteristics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
iv 

I–4. Physical and chemical characteristics in Whitewood Creek at the SewageTreatment-Plant site, monitored between August 30 and 31, 1988, to examine

diel fluctuations in these characteristics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

I–5. Physical and chemical characteristics in Whitewood Creek at the Above Vale

site, monitored between August 31 and September 1, 1988, to examine diel

fluctuations in these characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

I–6. Physical and chemical characteristics in Whitewood Creek at the Sheeler

Seep site, monitored between September 1 and 2, 1988, to examine diel

fluctuations in these characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

I–7. Algal cell sorption of arsenate and orthophosphate at 24 and 48 hours by 

living and heat-killed cells using three Stichococcus isolates from three sites 

along Whitewood Creek. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

I–8. Total arsenic concentrations in dominant benthic plant species collected from

four sites along Whitewood Creek. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

I–9. Site comparison for parameters monitored along Whitewood Creek. . . . . . . . . . . . . . . . . . . . . . . . . . 20

I–10. Lag times, in hours, between selected water-quality variables monitored along

Whitewood Creek. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

I–11. Results from experiments examining arsenate sorption by heat-killed Achnanthes

minutissima cells isolated from the Headwater site and the Above Vale site. . . . . . . . . . . . . . . . . . . 21

I–12. Results from experiments examining orthophosphate sorption by cell surfaces of 

Achnanthes minutissima isolated from the Headwater site and the Above Vale site. . . . . . . . . . . 22

SECTION II. Evaluation of the Processes Controlling Dissolved 

Arsenic in Whitewood Creek, South Dakota, by Christopher C. Fuller 

and James A. Davis

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Purpose and Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Description of Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Methods of Sample Collection and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Diurnal Sampling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Statistical Analysis of Diurnal Surface-Water Chemistry Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Conservative-Tracer Injection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Sampling of Ground-Water Inflows. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Solid-Phase Characterization and Adsorption Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Results and Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Diurnal Fluctuations in Surface-Water Chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Ground-Water Chemistry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Variations in Stream Discharge. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Dissolved Arsenic in Synoptic Samples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Arsenate Adsorption and Isotopic Exchange on Iron Oxyhydroxides. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Processes that Contribute to the Diurnal Cycle of Dissolved Arsenic in Surface Water . . . . . . . . . . . . . . . . . . . . . . 39

Ground-Water Sources of Streamflows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Molecular Diffusive Flux from Bed Sediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Algal Uptake of Arsenate from Surface Water. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Potential for Desorption of Arsenic from Suspended Sediments and Bed Sediments. . . . . . . . . . . . . . . . . . 43

Additional Controlling Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

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

Figures

II–1. Map showing location of study area and location of sampling sites in Whitewood 

Creek. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

II–2—II–10. Graphs showing:

II–2. Incident-light intensity, dissolved-arsenate concentration, and pH compared

to time of day at site A, August 11–13, 1987 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

II–3. Dissolved-arsenate concentration and pH compared to time of day at site B,

August 12–13, 1987. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

II–4. Dissolved-arsenate concentration and pH compared to time of day at site C,

August 12–13, 1987. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

II–5. Total alkalinity concentration and pH compared to time of day at site A,

August 11–13, 1987. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

II–6. Sulfate and bromide concentrations compared to time of day at site A,

August 11–13, 1987. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

II–7. Bromide and sulfate concentrations compared to distance downstream

for lithium-bromide injection site, August 13, 1987, 9 a.m. to 1 p.m.. . . . . . . . . . . . . . . . . . . . 37

II–8. Synoptic dissolved-arsenate concentration related to distance from lithiumbromide injection site, August 13, 1987, 9 a.m. to 1 p.m.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

II–9. Uptake of arsenate at pH 8.0 from surface water by ferrihydrite formed from

ground-water seep, as a function of time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

II–10. Arsenic-isotope exchange as a function of time on ferrihydrite following 

96 hours of uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

II–11. Generalized diagram showing dissolved-arsenate cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Tables

II–1. Cross-correlation analysis of diurnal time-series data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

II–2. Ground-water chemistry data for Whitewood Creek near site A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

II–3. Estimated sources and sinks of dissolved arsenic (CAs) in Whitewood Creek,

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
vi 

Conversion Factors, Datum, and Abbreviated 

Water-Quality Units

Air temperatures are given in degrees Celsius (°C), which can be converted to degrees Fahrenheit (°F) by 

the following equation:

°F = 1.8(°C)+32

Vertical coordinate information is referenced to the National Geodetic Vertical Datum of 1929 (NGVD 29).

Horizontal coordinate information is referenced to the North American Datum of 1927 (NAD 27).

Chemical concentration and water temperature are given only in metric units. Chemical concentration in 

water is given in millimoles per liter (mmol/L) or micromoles per liter (μmol/L). Millimoles per liter is a unit 

expressing the solute per unit volume (liter) of water. One thousand micromoles per liter is equivalent 

to 1 millimole per liter. Molar concentrations can be converted to mass concentration by multiplying the 

molar concentration (moles per liter) by the molecular weight of the solute (grams per mole). For example, 

1 micromole per liter (μmol/L) dissolved arsenic is equivalent to 7.49×10–5 grams per liter or 74.92 μg/L. 

Total alkalinity is given in units of milliequivalents per liter (meq/L). Chemical cencentration of solid-phase 

samples is given in moles per gram (mol/g).

Multiply By To obtain

millimeter (mm) 0.03937 inch

centimeter (cm) 0.3937 inch

cubic centimeter (cm3) cubic inch

meter (m) 3.281 foot

kilometer (km) 0.6214 mile

square kilometer (km2) 0.3861 square mile

cubic meter per second (m3/s) 35.3107 cubic foot per second

cubic meter per second per meter (m3/s/m) cubic foot per second per foot

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

megagram (Mg) 106 grams 2,204.6 pounds

microgram (μg) 10–6 gram 2.2046×10–9 pound

gram (g) 0.0022046 pound

micrometer (μm) 10–6 meter 3.937×10–5 inch

nanometer (nm) 10–9 meter 3.937×10–8 inch

milligram (mg) 10–3 gram 2.2046×10–6 pound

liter (L) 0.3785 gallon

milliliter (m/L) 0.03785 gallon

cubic meter per second (m3/s) 35.3198 cubic feet per second

square meter (m2) 10.7650 square feet

square centimeter (cm2) 0.1550 square inch

gravitational constant (G)

parts per million (ppm)

micromoles per square meter per day 

(μmol/m2/d)

square centimeter per second (cm2/s)

micromoles per liter per day (μmol/L/d)

milligrams per liter (mg/L)

micromoles per gram (μmol/g)

milliequivalents per liter (meq/L) and 

(μmol/L) micromoles per liter

liter per day (L/d)

microeinsteins

microsiemens per centimeter at 25 degrees 

Celsius (μS/cm)
SECTION I. Effects of Benthic Flora on Arsenic Transport 

in Whitewood Creek, South Dakota

By James S. Kuwabara, Cecily C.Y. Chang, and Sofie P. Pasilis

Abstract

Field measurements and bioassay experiments were done 

to investigate the effects of arsenic and phosphorus interactions 

on sorption of these solutes by the benthic flora (periphyton and 

submerged macrophytes) in Whitewood Creek, a stream in 

western South Dakota. Short-term (24-hour) sorption experiments were used to determine arsenic transport characteristics 

for algae (first-order rate constants for solute sorption, biomass, 

and accumulation factors) collected in the creek along a transect 

beginning upstream from a mine discharge point and downgradient through a 57-kilometer reach. Temporal changes in 

biomass differed significantly between and within sampling 

sites. Arsenic concentrations in plant tissue increased with 

distance downstream, but temporal changes in concentrations 

in tissues differed considerably from site to site. Cultures of 

Achnanthes minutissima (Bacillariophyceae) and Stichococcus 

sp. (Chlorophyceae) were isolated from four sites along a longitudinal concentration gradient of dissolved arsenic within 

the study reach and were maintained at ambient solute concentrations. Arsenic accumulation factors and sorption-rate constants for these isolates were determined as a function of dissolved arsenate and orthophosphate. Cell surfaces of algal 

isolates exhibited preferential orthophosphate sorption over 

arsenate. Initial sorption of both arsenate and orthophosphate 

followed first-order mass transfer for each culturing condition. 

Although sorption-rate constants increased slightly with 

increased dissolved-arsenate concentration, algae, isolated from 

a site with elevated dissolved arsenic in the stream channel, had 

a significantly slower rate of arsenic sorption compared with the 

same species isolated from an uncontaminated site upstream.

In diel studies, amplitudes of the pH cycles increased 

with measured biomass except at a site immediately downstream from water-treatment-plant discharge. Inorganic pentavalent arsenic dominated arsenic speciation at all sites—not 

a surprising result for the well-oxygenated water column along 

this reach. Concentration fluctuations in dissolved-arsenic species lagged pH fluctuations by approximately 3 hours at the 

most downstream site, but no discernible lag was observed 

at an artificially pooled area with an order of magnitude higher 

biomass. Furthermore, the amplitudes of diel fluctuations in 

arsenic species were greater at the pooled area than at the most 

downstream site. Lack of correspondence between changes in 

dissolved-orthophosphate concentrations and arsenic species 

may have resulted from preferential sorption of orthophosphate 

over arsenate by the biomass. Based on carbon-fixation estimates, the phosphorus demand from photosynthetic activity 

required water-column concentrations to be supplemented 

by another source such as phosphate regeneration within the 

benthic community or desorption of particle-bound phosphate.

Introduction

Biological uptake and chemical transformations can 

affect transport of reactive solutes in streams and, consequently, 

the complexity of water-quality modeling and monitoring 

(Kuwabara and others, 1984; Cain and others, 1988; Kuwabara 

and others, 1988; Kuwabara and Helliker, 1988). For example, 

solute uptake by organisms may retard downstream transport, 

whereas metabolic reactions might change chemical speciation 

(Andreae, 1977; Sanders, 1985) and thereby effect changes in 

surface activity and transport characteristics. The effects of biological processes can be difficult to quantify because characteristics of the benthic and planktonic communities (for example, 

species composition and biomass) can change temporally and 

spatially. These changing characteristics can influence, and be 

affected by, interacting chemical and hydrologic processes.

Although biological processes have long been considered 

in water-quality and nutrient-cycling models for macronutrients, the importance of integrating biological models into tracecontaminant transport models has only recently been acknowledged (Zison and others, 1978; Jorgensen, 1983; Kuwabara and 

others, 1984). This can be due, in part, to the complexity of 

quantifying or even identifying the pertinent mechanisms that 

affect transport and distribution of a given solute. Biological 

processes that need to be considered in solute-transport models 

include solute uptake and release, toxicity and adaptation, 

metabolism and storage, community structure, and species 

interactions. In particular, attempts to model the influence of 

the benthic flora on arsenic transport within an aquatic environment have been hampered by a number of factors: (1) arsenate 
2 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

inhibits the growth of certain algal species at submicromolar 

concentrations, presumably because of interference with phosphate metabolism (Button and others, 1973; Sanders, 1979); 

(2) the effects of arsenic speciation on uptake rates and solute 

accumulation by periphyton are not well known; (3) possible 

changes in metabolic reaction rates as a consequence of prolonged exposure at elevated arsenic concentrations (and further 

uptake of arsenic) are poorly understood; and (4) data to quantify the effects of physical and chemical factors (for example, 

light intensity and surface reactions with inorganic particles) 

on arsenic uptake are sparse.

Purpose and Scope

The dependence of arsenic transport and speciation in 

Whitewood Creek on algal growth was investigated. This report 

presents results of a field and laboratory study of arsenic transport characteristics of periphyton and submerged macrophytes 

along a 57-km reach of Whitewood Creek in South Dakota, 

where both dissolved-arsenate and orthophosphate concentrations varied substantially. A first-order mass transfer equation 

was tested as a model to describe solute sorption on cell surfaces of the benthic flora. The variables in the equation (for 

example, algal biomass, sorption and release rates, and accumulation factors) may be used as a biological term in a comprehensive transport model consisting of hydrologic, chemical, and 

biological terms.

Results of a subsequent study done between August 30 

and September 2, 1988, also are presented that examine diel 

relationships among benthic flora and pH, specific conductance, water temperature, and photosynthetically active 

radiation. The effects of these relations on concentration 

trends for dissolved-orthophosphate and arsenic species are 

discussed.

Acknowledgments

The authors wish to thank Christopher Fuller for comments and discussions about this manuscript and for alkalinity 

measurements. Contributions to manuscript revisions by 

James Carter, James Davis, Ronald Harvey, and Harry 

Leland also are gratefully acknowledged. Thanks are extended 

to C.B. Hellquist, Biology Department, North Adams State 

College in North Adams, Massachusetts, and Raymond Wong 

of the Math/Science Nucleus in Fremont, California, for 

taxonomic analyses of submerged macrophytes and benthic 

algae. Logistical support from the staff of the U.S. Geological 

Survey South Dakota District office is very much appreciated. 

We also thank Cyndi Azevedo, Herbert Buxton, Keith Kirk, 

Gail Mallard, David Morganwalp, and Brent Topping 

for their critical administrative and editorial efforts. The 

USGS Toxic Substances Hydrology Program is gratefully 

acknowledged for long-term support of this interdisciplinary 

research.

Study Site

Whitewood Creek, a perennial, snow-fed stream in the 

Black Hills of South Dakota, has received effluents from gold 

mining since 1876 and from municipal activities such as sewage 

treatment and power-generator cooling. Four sites along the 

creek were selected for this study, beginning upstream from the 

mining activities and continuing approximately 1 km upstream 

from the confluence of Whitewood Creek and the Belle Fourche 

River (fig. I–1). Although direct discharge of mine tailings into 

the creek ended in 1977, residual mine tailings still form most 

of the bank and bed sediment over the 57-km study reach. These 

accumulated tailings contribute to a dissolved-arsenic concentration gradient that increases in the downstream direction from 

less than 0.1 micromolar (μmol/L) upstream from the mining 

activities to 1.5 μmol/L at the most downstream site (Goddard, 

1988). Conversely, inputs of phosphorus and other macronutrients from a municipal wastewater-treatment facility at 

Deadwood, downstream from major mining activities, provides 

a dissolved-orthophosphate gradient that decreases in the downstream direction from 20 μmol/L immediately downstream 

from the wastewater facility to less than 1 μmol/L at 57 km 

downstream (Goddard, 1988). A dense community of attached 

algae and submerged macrophytes quickly forms in Whitewood 

Creek after snowmelt and remains throughout the summer 

months. Dissolved arsenic (primarily as arsenate) in the 

streamwater also reaches maximal concentrations during the 

summer downstream from mining activities, possibly because 

of (1) elevated water-column pH during the summer that causes 

desorption of arsenic and (2) summer inputs of arsenic-laden 

ground water influenced by both percolation of irrigation 

water and lower summer surface-water flow after snowmelt 

(Goddard and others, 1988; Christopher C. Fuller, section II 

of this report). The study reach, therefore, represents ideal field 

conditions for the examination and quantification of potentially 

important contributions of the benthic flora to arsenic mobilization and attenuated transport.

Methods of Study

Arsenic transport characteristics were determined for 

algae and macrophytes collected at four sampling sites (fig. I–1): 

(1) 7 km upstream from the mining activities (1,700-m elevation); (2) 15 km downstream from the first site and within the 

town of Deadwood (0.25 km downstream from the municipal 

wastewater-treatment plant, 1,390-m elevation); (3) 39 km 

farther downstream at a U.S. Geological Survey gaging station 

(870-m elevation); and (4) approximately 1 km upstream from 

the confluence of Whitewood Creek and the Belle Fourche River 

(850-m elevation). These sites are hereinafter referred to as the 

Headwater (HW) site, the Sewage-Treatment-Plant (STP) site, the 

Above Vale (AV) site, and the Sheeler Seep (SS) site, respectively 

(Kuwabara and others, 1988). Abundant ground-water seepage 

occurs as springs along the banks of the creek at the farthest downstream site.
Methods of Study 3

SOUTH DAKOTA

Missouri Riv e

C

r

heyenne River

Study area

103 40' O

44 40' O

44 30' O

44 20' O

103 30' O

Belle Fourche River

Whitewood Creek

Above Vale

site

(elevation

870 meters)

Sheeler Seep site

(elevation 850 meters)

Sewage-treatmentplant site

(elevation 1,390 meters)

Headwater site

(elevation 1,700 meters)

Whitewood

Deadwood

Lead

Elevations based on

NGVD of 1929 0

0

10 KILOMETERS

10 MILES

Figure I–1. Map of the study area along Whitewood Creek, South Dakota.
4 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

Estimated transport characteristics included biomass (ρb) or 

the accessible biomass per unit streambed area, net sorption-rate 

constant (λb), and accumulation factor (that is, biological partitioning coefficient, Kb). The estimates were used to describe a biological component of a comprehensive transport model describing 

hydrologic, chemical, and biological processes. Assuming a firstorder process, the rate of change of dissolved arsenic resulting 

from plant tissue accumulation would take the form

where

( ρbj /Dj) = biomass factor that scales changes in solute 

concentrations in plant communities to changes 

in water-column solute concentration, in units 

of biotic mass per cubic length;

Rb = temporal change in Cb, in units of solute mass per 

biotic mass per unit time;

j = finite interval of the stream reach (dimensionless);

Cb = concentration associated with the benthic plant 

material, in units of solute mass per biotic mass;

D = mean interval channel depth, in units of length;

t = time;

and

C = solute concentration in the stream as a function of 

time, in units of solute mass per cubic length.

Field Studies

During an initial reconnaissance of Whitewood Creek, 

August 4–9, 1986, algal biomass (periphyton and macrophyte 

abundance in grams ash-free dry weight per square meter) was 

estimated from cobble scrapings (number of sample replicates, 

n=6) taken from the four sites illustrated in figure I–1 (table I–1). 

Acetone (99.5 percent) extractions of chlorophyll-a were analyzed fluorometrically (Franson, 1985). Ash-free dry weights 

from the scrapings also were taken in order to calculate an 

autotrophic index (mass ratio of plant biomass to chlorophyll-a) 

for each site as a potential indicator of environmental stress.

ρbj Dj ( ) ⁄ Rbj ρbj Dj –( ) ⁄ δCbj = ( ) ⁄ δt

λbj – ρbj Dj ( ) ⁄ Cbj KbjCj = ( ) –

Subsequent field studies during the summer of 1987 

examined temporal fluctuations in characteristics of the benthic 

flora. Benthic plant abundance (ρb) at each of the four sites was 

estimated monthly from late May to September 1987 by using 

ash-free dry weight and chlorophyll-a measurements (n=9) of 

streambed areas (Franson, 1985). Measurements of channel 

width (W, in meters, n=3), depth (D, in meters, n=9), and 

channel velocity (V, in meters per second, n=9) were made 

at all sites, as were temperature (TEMP, in degrees Celsius), 

specific conductance (COND, in microsiemens per centimeter 

at 25 degrees Celsius), dissolved oxygen, and pH (table I–2). 

Periphyton and submerged macrophytes were collected for 

arsenic analyses. Tissues were rinsed four times in streamwater and then four times in deionized water (18 megohms). 

Macrophyte root tissue was excluded from the samples in order 

to minimize arsenic contamination by attached inorganic particles that could not efficiently be removed by rinsing (that is, 

to improve precision in measurements of plant-tissue arsenic 

concentrations). The macrophyte sampling procedure did not 

exclude epiphytic algal cells. Lyophilized plant tissue was 

prepared and analyzed using a dry-ash procedure (Johns and 

Luoma, 1988). Reconstituted samples also were analyzed for 

total iron by flame atomic absorption spectroscopy to check 

for contamination by attached inorganic particles. Error bars 

presented in tables represent 95-percent confidence intervals 

for the specified replicate measurements.

Diel variations in biologically significant characteristics 

were examined using data loggers (Campbell, Model CR–10) 

at the four sampling sites. Data loggers were used with various 

probes to monitor the following variables: photosynthetically 

active radiation between 400 and 700 nm (LICOR probe, 

Model LI–192SA), water temperature (Campbell Scientific 

Probe, Model 107), air temperature (copper constantan thermocouple), specific conductance (4-lead probe fabricated by the 

Hydrologic Instrumentation Facility, U.S. Geological Survey), 

and pH (Innovative Sensors probe, Model M–12 with 9-volt 

preamplifier). Parameters monitored by data loggers and presented in tables I–3 to I–6 represent 15-minute averages of 

measurements taken at 10-second intervals. Data from the irradiance probe were verified against an irradiance meter (LICOR, 

Model LI185B) before the sampling study. Water and air temperature, and temperature corrected specific-conductance measurements (Cole Parmer, Model 1500–20) were taken manually every 

3 hours during the sampling period. Measurements from the pH 

probe, designed for long-term data-logging applications, also 

were calibrated every 3 hours against temperature-compensated 

pH determinations (Orion Research, Model SA250). Therefore, 

with the exception of the irradiance measurements, the plotted 

data-logger values are identical to the manually determined 

measurements taken at 3-hour intervals (fit to manually determined measurements is imposed). Analysis of time-series data 

was performed using a statistical computer program (Minitab; 

Ryan and others, 1985) to produce correllograms for a range 

of lag times.

During the diel study, periphyton and macrophytes were 

sampled at noon at each site (n=9) for ash-free dry mass and 

spectrophotometric determination of chlorophyll-a corrected

Table I–1. Estimated biomass for four sampling sites along 

Whitewood Creek, August 4–9, 1986.

[Headwater site, HW; Sewage-Treatment-Plant site, STP; Above Vale site, AV; 

and Sheeler Seep site, SS; Biomass, ρb, in grams per square meter; and temperature in degrees Celsius. The mass ratio of periphyton and macrophytes to 

chlorophyll-a, the autotrophic index, has been used as an indicator of environmental stress with increasing values indicating greater abundance of senescent 

algal cells or increased heterotrophic growth (Weber, 1973)]

Site Temperature Autotrophic

index Biomass

HW 13.2 120 21+14

STP 17.5 210 34±13

AV 19.0 140 77±27

SS 24.2 190 25±11
Methods of Study 5

for pheophytin-a (Franson 1985; Kuwabara and others, 1990). 

Streamwater sampled (n=5) at 3-hour intervals was filtered 

(Nuclepore, 0.2-μm polycarbonate membranes) for dissolvedarsenic and orthophosphate analyses. Water samples were 

simultaneously taken at 6-hour intervals for alkalinity determination by titration (Franson, 1985). Filtered orthophosphate 

samples (n=2 per sampling time) were preserved with mercuric 

chloride (1-mL mercury-saturated solution per 250-mL 

sample), and filtered arsenic samples were acidified to pH 2 

with 6 normal, quartz-distilled hydrochloric acid. All processed 

water samples were refrigerated (approximately 5°C) in 

darkness.

Arsenic speciation was determined in the laboratory by the 

following steps. The acidified sample was buffered to pH 5 by 

using an acetate buffer (Tallman and Shaikh, 1980) and analyzed directly for trivalent arsenic [As(III)] by hydride generation, atomic absorption spectrometry (AAS). The sample was 

then reduced with potassium iodide in 40-percent hydrochloric 

acid for 1.5 hours and analyzed again to determine the total of 

inorganic As(III) and pentavalent arsenic [As(V)] (Tallman 

and Shaikh, 1980; Glaubig and Goldberg, 1988). The reduced 

sample then was analyzed by graphite furnace AAS to provide 

a measure of total dissolved arsenic. Dissolved orthophosphate 

was determined colorimetrically by the molybdate method 

using an autoanalyzer (Technicon, Model II) with an extended 

cell-path length (50 mm) for greater sensitivity (Murphy and 

Riley, 1962; Merle Shockey, oral commun., September 6, 

1988).

Laboratory Studies

Algal species common to each of the four sampling sites 

were isolated for use in arsenate and orthophosphate sorption 

studies. Algal suspensions generated from periphyton scrapings 

were streaked on 1-percent agar plates containing an algal 

growth medium (Kuwabara and others, 1985) enriched with 

silica. Algal clusters that formed on the plates were transferred 

to liquid media for one week to increase algal density. This agar 

plate streaking and resuspension procedure was repeated until 

unialgal cultures were achieved. Stichococcus spp. and Scenedesmus spp. (Chlorophyceae), common to the four sampling 

sites, were initially isolated. It is not clear why common diatoms 

were not obtained from this isolation procedure because an 

abundance of diatoms was observed in the initial scrapings. 

One possibility is that chlorophyte growth was more rapid than 

diatoms on these agar plates. Another possibility is that the agar 

color obscured diatom clusters on the plates while chlorophyte 

clusters were readily visible. Stichococcus isolates were 

selected for use in subsequent sorption experiments over Scenedesmus because in agitated cultures, Stichococcus typically 

remained unicellular and therefore could be quickly and precisely enumerated with a particle counter. Algal isolates were 

maintained in a chemically defined growth medium with added 

solute concentrations similar to ambient levels at their respective collection sites (0.0 μmol/L for HW, 0.5 μmol/L for STP, 

and 1.0 μmol/L for AV and SS isolates).

Table I–2. Field data collected monthly during the summer of 1987 from four sites along Whitewood Creek.

[Headwater site, HW; Sewage-Treatment-Plant site, STP; Above Vale site, AV; and Sheeler Seep site, SS. Measured characteristics include: specific conductance, 

COND, in microsiemens per centimeter at 25 degrees Celsius; water temperature, TEMP, in degrees Celsius; pH; stream-channel width, W, in meters with 

95-percent confidence intervals (n=6); mean channel depth, D, in meters with 95-percent confidence intervals (n=9); mean velocity, V, in meters per second with 

95-percent confidence intervals (n=9); biomass, ρb, in grams per square meter with 95-percent confidence intervals (n=9); and autotrophic index, AI, in grams 

ash-free dry mass per gram chlorophyll-a. Sampling times are given in military format. The symbol “–” in the ρb or AI column indicates that the benthic-plant 

community at that time was not present in sufficient mass for analysis]

Date Time Site COND TEMP pH W D V ρb AI

05/27 0930 HW 420 8.2 8.3 2.6±0.1 0.12±0.05 0.82±0.02 37±15 120

05/27 1430 STP 545 15.2 8.1 7.7±0.5 0.38±0.09 0.94±0.12 34±17 110

05/28 1300 AV 890 18.4 8.2 21.6±1.6 0.35±0.12 0.30±0.11 – –

05/28 1550 SS 980 20.0 8.2 3.9±0.4 0.38±0.15 0.77±0.20 – –

07/07 1255 HW 450 16.0 8.3 2.4±0.3 0.10±0.02 0.58±0.10 52±19 110

07/08 1040 STP 760 17.0 8.4 7.3±0.5 0.24±0.04 0.74±0.11 71±51 120

07/09 1300 AV 1,180 21.5 8.6 17.9±0.7 0.05±0.02 0.39±0.14 469±65 90

07/10 1610 SS 1,310 28.0 8.6 3.4±0.5 0.24±0.11 0.86±0.16 28±5 80

08/19 0940 HW 429 9.0 8.7 2.5±0.3 0.15±0.03 0.51±0.16 51±27 140

08/19 1300 STP 899 17.6 8.3 7.1±0.3 0.23±0.06 0.65±0.19 54±19 100

08/26 1400 AV 1,108 17.0 8.0 18.0±0.5 0.21±0.18 0.13±0.03 280±30 180

08/26 1015 SS 1,245 14.5 8.1 3.6±0.3 0.27±0.04 0.72±0.20 29±14 160

09/16 1315 HW 563 11.1 8.3 1.7±0.2 0.10±0.02 0.25±0.05 60±34 170

09/16 1730 STP 930 16.8 7.9 6.5±0.7 0.19±0.04 0.53±0.07 82±60 120

09/28 1745 AV 1,167 18.3 8.1 17.8±0.8 0.33±0.06 0.07±0.01 237±25 310

09/28 1435 SS 1,222 19.5 8.3 3.7±0.4 0.24±0.05 0.46±0.09 7±4 20
6 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

Table I–3. Physical and chemical characteristics in Whitewood Creek at the Headwater site, monitored between August 29 and 30, 1988, 

to examine diel fluctuations in these characteristics.

[Elapsed time in minutes; water temperature in degrees Ce1sius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE

08/29/88 1645 0 16.9 8.77 216 160.5

1700 15 16.8 8.76 222 184.5

1715 30 16.8 8.75 228 160.7

1730 45 16.8 8.73 232 139.8

1745 60 16.7 8.73 236 151.9

1800 75 16.6 8.72 236 150.8

1815 90 16.6 8.71 242 123.6

1830 105 16.6 8.69 248 66.8

1845 120 16.3 8.66 252 42.1

1900 135 16.1 8.63 255 31.6

1915 150 15.8 8.60 252 22.4

1930 165 15.5 8.57 255 9.7

1945 180 15.4 8.53 248 3.4

2000 195 15.0 8.50 255 1.5

2015 210 14.7 8.47 255 1.5

2030 225 14.4 8.44 265 1.6

2045 240 14.2 8.41 261 1.7

2100 255 14.0 8.39 268 1.5

2115 270 13.6 8.37 268 1.6

2130 285 13.4 8.36 271 1.5

2145 300 13.2 8.34 268 1.6

2200 315 12.8 8.33 274 1.4

2215 330 12.6 8.33 271 1.4

2230 345 12.4 8.32 284 1.4

2245 360 12.2 8.31 278 1.4

2300 375 12.0 8.31 274 1.4

2315 390 11.7 8.31 281 1.4

2330 405 11.5 8.30 278 1.4

2345 420 11.3 8.31 281 1.4

08/30/88 0 435 11.1 8.31 281 1.4

 15 450 10.9 8.31 287 1.4

 30 465 10.8 8.31 287 1.4

 45 480 10.7 8.31 281 1.4

100 495 10.6 8.31 284 1.4

115 510 10.4 8.31 290 1.4

130 525 10.3 8.31 281 1.4

145 540 10.0 8.31 287 1.4

200 555 9.9 8.31 300 1.4

215 570 9.8 8.32 300 1.4

230 585 9.8 8.32 284 1.4

245 600 9.7 8.32 294 1.4

300 615 9.4 8.32 303 1.4

315 630 9.4 8.32 300 1.4

330 645 9.3 8.32 290 1.4
Methods of Study 7

08/30/88—Continued 345 660 9.2 8.32 294 1.4

400 675 9.0 8.32 310 1.4

415 690 9.0 8.33 307 1.4

430 705 9.1 8.33 294 1.4

445 720 9.0 8.33 313 1.4

500 735 8.9 8.33 297 1.4

515 750 8.9 8.33 300 1.4

530 765 8.8 8.33 307 1.4

545 780 8.7 8.33 316 1.4

600 795 8.7 8.33 316 1.4

615 810 8.6 8.33 313 1.7

630 825 8.5 8.34 303 3.3

645 840 8.5 8.34 303 6.5

700 855 8.5 8.34 307 9.7

715 870 8.3 8.35 310 14.1

730 885 8.3 8.36 313 19.4

745 900 8.3 8.36 317 25.4

800 915 8.3 8.37 318 34.5

815 930 8.4 8.39 320 55.3

830 945 8.5 8.41 307 76.5

845 960 8.5 8.44 317 107.9

900 975 8.8 8.47 307 111.3

915 990 9.0 8.49 314 112.6

930 1,005 9.1 8.52 317 136.8

945 1,020 9.4 8.55 317 146.4

1000 1,035 9.7 8.57 304 159.5

1015 1,050 10.0 8.60 310 173.9

1030 1,065 10.5 8.63 301 189.0

1045 1,080 10.9 8.65 310 210.2

1100 1,095 11.5 8.67 294 240.7

1115 1,110 12.0 8.69 290 318.0

1130 1,125 12.5 8.70 291 348.6

1145 1,140 13.1 8.71 278 465.3

1200 1,155 13.6 8.72 271 641.8

1215 1,170 14.2 8.73 261 421.8

1230 1,185 14.8 8.74 261 327.3

1245 1,200 15.4 8.74 252 594.7

1300 1,215 15.9 8.75 248 762.3

1315 1,230 16.4 8.75 236 831.7

1330 1,245 16.7 8.76 232 535.4

1345 1,260 17.1 8.77 232 626.4

1400 1,275 17.5 8.78 232 925.9

1415 1,290 17.8 8.77 229 1,026.6

1430 1,305 18.2 8.77 229 987.1

Table I–3. Physical and chemical characteristics in Whitewood Creek at the Headwater site, monitored between August 29 and 30, 1988, 

to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Ce1sius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
8 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

08/30/88—Continued 1445 1,320 18.4 8.78 226 402.5

1500 1,335 18.5 8.78 223 451.6

1515 1,350 18.6 8.78 223 212.4

1530 1,365 18.8 8.78 223 198.8

1545 1,380 18.8 8.78 226 91.7

1600 1,395 18.6 8.78 223 113.3

1615 1,410 18.5 8.78 232 138.9

1630 1,425 18.5 8.78 232 156.0

1645 1,440 18.3 8.77 226 166.3

1700 1,455 18.2 8.77 232 153.3

Table I–4. Physical and chemical characteristics in Whitewood Creek at the Sewage-Treatment-Plant site, monitored between August 30 

and 31, 1988, to examine diel fluctuations in these characteristics.

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second. Symbol “–” indicates the malfunction of 

the water-temperature probe]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE

08/30/88 845 0 12.4 8.26 820 152.5

900 15 12.6 8.26 817 172.3

915 30 12.6 8.27 817 195.9

930 45 12.7 8.28 814 210.6

945 60 12.9 8.29 812 241.0

1000 75 13.0 8.31 813 255.9

1015 90 13.3 8.32 807 338.3

1030 105 13.3 8.33 811 384.8

1045 120 13.6 8.34 806 412.9

1100 135 13.6 8.36 802 393.9

1115 150 13.8 8.38 794 443.8

1130 165 14.2 8.41 787 478.0

1145 180 14.4 8.42 777 454.0

1200 195 14.6 8.44 776 419.4

1215 210 14.9 8.45 771 393.9

1230 225 14.9 8.45 763 422.4

1245 240 15.3 8.46 758 429.4

1300 255 15.3 8.46 761 387.9

1315 270 15.5 8.47 761 301.4

1330 285 15.7 8.49 762 260.4

1345 300 16.0 8.50 757 258.1

1400 315 16.0 8.51 751 248.3

1415 330 16.2 8.52 745 243.3

1430 345 16.3 8.53 744 239.7

Table I–3. Physical and chemical characteristics in Whitewood Creek at the Headwater site, monitored between August 29 and 30, 1988, 

to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Ce1sius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
Methods of Study 9

08/30/88—Continued 1445 360 16.4 8.53 739 229.9

1500 375 16.6 8.54 733 229.0

1515 390 17.1 8.55 722 225.5

1530 405 17.1 8.56 723 224.9

1545 420 17.1 8.56 723 188.4

1600 435 17.1 8.55 726 209.0

1615 450 17.1 8.54 720 164.0

1630 465 17.0 8.54 724 146.3

1645 480 16.7 8.53 730 143.8

1700 495 16.7 8.53 732 128.3

1715 510 16.6 8.52 734 131.2

1730 525 16.5 8.51 733 95.0

1745 540 16.7 8.50 728 93.6

1800 555 16.4 8.49 734 103.3

1815 570 16.7 8.47 729 101.2

1830 585 16.5 8.46 735 60.4

1845 600 16.4 8.45 734 37.7

1900 615 16.3 8.43 730 21.8

1915 630 16.3 8.41 722 17.0

1930 645 16.1 8.40 724 7.4

1945 660 16.0 8.39 728 1.1

2000 675 16.0 8.38 734 0.1

2015 690 15.8 8.37 736 0.1

2030 705 15.6 8.36 740 0.1

2045 720 15.6 8.34 738 0.1

2100 735 15.3 8.33 745 0.1

2115 750 15.3 8.32 748 0.1

2130 765 15.2 8.32 752 0.1

2145 780 15.0 8.31 757 0.1

2200 795 14.9 8.31 762 0.1

2215 810 14.9 8.30 754 0.1

2230 825 14.6 8.29 755 0.1

2245 841 14.6 8.28 752 0.1

2300 856 14.6 8.28 753 0.1

2315 871 14.4 8.27 753 0.1

2330 886 14.2 8.26 756 0.1

2345 901 14.2 8.25 757 0.1

08/31/88 0 916 14.0 8.25 762 0.1

15 931 13.8 8.24 766 0.1

30 946 13.6 8.23 774 0.1

45 961 13.6 8.23 775 0.1

100 976 13.6 8.23 775 0.1

115 991 13.5 8.22 766 0.1

130 1,006 13.2 8.21 761 0.1

145 1,021 13.2 8.20 755 0.1

200 1,036 13.2 8.20 759 0.1

Table I–4. Physical and chemical characteristics in Whitewood Creek at the Sewage-Treatment-Plant site, monitored between August 30 

and 31, 1988, to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second. Symbol “–” indicates the malfunction of 

the water-temperature probe]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
10 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

08/31/88—Continued 215 1,051 13.0 8.19 762 0.1

230 1,066 12.9 8.19 771 0.1

245 1,081 12.8 8.18 775 0.0

300 1,096 12.6 8.18 783 0.1

315 1,111 12.6 8.17 784 0.0

330 1,126 12.6 8.17 784 0.0

345 1,141 12.4 8.16 783 0.2

400 1,156 12.3 8.15 793 0.2

415 1,171 12.3 8.14 792 0.3

430 1,186 12.3 8.14 789 0.4

445 1,201 12.1 8.15 783 0.3

500 1,216 12.0 8.15 786 0.3

515 1,231 12.0 8.15 786 0.5

530 1,246 12.0 8.15 789 0.5

545 1,261 12.0 8.16 789 0.6

600 1,276 12.0 8.16 791 0.6

615 1,291 12.0 8.16 791 1.3

630 1,306 12.0 8.17 795 1.7

645 1,321 12.0 8.17 796 4.4

700 1,336 12.0 8.18 805 7.9

715 1,351 – 8.19 804 10.8

730 1,366 – 8.19 799 15.7

745 1,381 – 8.20 794 20.7

800 1,396 – 8.21 791 24.7

815 1,411 – 8.22 787 35.1

830 1,426 – 8.23 791 55.4

845 1,441 – 8.23 789 80.9

900 1,456 – 8.25 792 75.9

915 1,471 – 8.26 795 116.2

930 1,486 – 8.27 802 144.2

945 1,501 – 8.28 817 153.6

1000 1,516 – 8.29 830 166.2

1015 1,531 – 8.31 830 308.9

1030 1,546 – 8.32 819 474.6

1045 1,561 – 8.33 814 517.8

1100 1,576 – 8.35 810 529.0

1115 1,591 – 8.37 812 552.3

1130 1,606 – 8.39 814 631.6

1145 1,621 – 8.41 821 686.0

1200 1,636 – 8.43 816 816.9

1215 1,651 – 8.45 808 941.1

1230 1,666 – 8.47 803 931.4

1245 1,681 – 8.50 804 808.8

1300 1,696 – 8.53 800 711.9

1315 1,711 – 8.55 780 388.2

Table I–4. Physical and chemical characteristics in Whitewood Creek at the Sewage-Treatment-Plant site, monitored between August 30 

and 31, 1988, to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second. Symbol “–” indicates the malfunction of 

the water-temperature probe]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
Methods of Study 11

08/31/88—Continued 1330 1,726 – 8.56 762 134.9

1345 1,741 – 8.56 748 90.8

1400 1,756 – 8.57 741 91.5

1415 1,771 – 8.57 737 102.2

1430 1,786 – 8.56 736 102.4

1445 1,801 – 8.54 730 91.4

1500 1,816 – 8.51 730 79.7

1515 1,831 – 8.49 727 92.0

1530 1,846 – 8.46 728 121.2

1545 1,861 – 8.43 729 130.2

1600 1,876 – 8.41 735 127.9

1615 1,891 – 8.39 731 123.8

1630 1,906 – 8.36 726 120.8

Table I–5. Physical and chemical characteristics in Whitewood Creek at the Above Vale site, monitored between August 31 and 

September 1, 1988, to examine diel fluctuations in these characteristics.

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE

08/31/88 700 0 15.1 8.37 1,177 9.7

715 15 15.1 8.38 1,177 19.8

730 30 15.1 8.40 1,177 32.3

745 45 15.1 8.41 1,178 43.4

800 60 14.9 8.43 1,179 53.5

815 75 14.8 8.44 1,180 69.7

830 90 14.9 8.47 1,180 75.9

845 105 14.8 8.49 1,180 92.2

900 120 14.9 8.52 1,179 129.8

915 135 15.0 8.55 1,179 175.3

930 150 15.1 8.58 1,178 286.2

945 165 15.1 8.62 1,177 376.3

1000 180 15.3 8.66 1,176 423.6

1015 195 15.4 8.70 1,174 486.0

1030 210 15.7 8.74 1,172 531.5 

1045 225 16.0 8.77 1,170 580.1

1100 240 16.2 8.80 1,168 599.6

1115 255 16.4 8.84 1,166 646.8

1130 230 16.7 8.88 1,163 675.1

1145 285 17.1 8.90 1,160 685.3

1200 300 17.3 8.92 1,158 698.3

Table I–4. Physical and chemical characteristics in Whitewood Creek at the Sewage-Treatment-Plant site, monitored between August 30 

and 31, 1988, to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second. Symbol “–” indicates the malfunction of 

the water-temperature probe]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
12 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

08/31/88—Continued 1215 315 17.6 8.93 1,155 723.2

1230 330 18.0 8.95 1,152 732.5

1300 360 18.7 9.00 1,147 831.51

1315 375 19.0 9.01 1,145 450.1

1330 390 19.4 9.03 1,141 354.4

1345 405 19.8 9.03 1,139 252.1

1400 420 20.1 9.03 1,136 281.9

1415 435 20.5 9.03 1,134 799.8

1430 450 20.9 9.04 1,131 813.5

1445 465 21.1 9.04 1,130 655.1

1500 480 21.4 9.05 1,128 429.7

1515 495 21.7 9.03 1,126 361.5

1530 510 22.1 9.02 1,124 348.9

1545 525 22.2 8.98 1,123 211.6

1600 540 22.5 8.94 1,122 172.8

1615 555 22.6 8.93 1,121 179.1

1630 570 22.8 8.92 1,120 182.4

1645 585 22.9 8.91 1,120 204.4

1700 600 23.0 8.89 1,120 254.8

1715 615 23.2 8.85 1,120 232.4

1730 630 23.1 8.80 1,120 157.7

1745 645 23.0 8.77 1,121 127.1

1800 660 22.9 8.76 1,122 117.6

1815 675 22.8 8.75 1,122 80.9

1830 690 22.6 8.74 1,123 45.8

1845 705 22.5 8.73 1,124 37.6

1900 720 22.3 8.72 1,125 27.9

1915 735 22.1 8.71 1,126 22.7

1930 750 22.1 8.71 1,126 11.2

1945 765 21.9 8.70 1,128 3.3

2000 780 21.5 8.69 1,130 1.4

2015 795 21.4 8.69 1,130 1.3

2030 810 21.1 8.67 1,132 1.4

2045 826 21.1 8.67 1,132 1.4

2100 841 20.8 8.66 1,134 1.6

2115 856 20.6 8.66 1,135 1.9

2130 871 20.4 8.65 1,136 1.6

2145 886 20.2 8.64 1,137 1.7

2200 901 10.0 8.63 1,138 2.0

2215 916 19.7 8.62 1,140 1.9

2230 931 19.7 8.60 1,140 1.8

2245 946 19.4 8.59 1,141 1.8

2300 961 19.4 8.57 1,142 1.7

2315 976 19.1 8.56 1,144 1.5

2330 991 18.8 8.54 1,145 1.7

2345 1,006 18.7 8.54 1,146 1.4

Table I–5. Physical and chemical characteristics in Whitewood Creek at the Above Vale site, monitored between August 31 and 

September 1, 1988, to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
Methods of Study 13

09/01/88 0 1,021 18.5 8.54 1,147 1.5

15 1,036 18.5 8.51 1,147 1.4

30 1,051 18.3 8.51 1,149 1.4

45 1,066 18.2 8.50 1,150 1.5

100 1,081 18.0 8.49 1,152 1.4

115 1,096 17.9 8.49 1,152 1.4

130 1,111 17.7 8.49 1,153 1.4

145 1,126 17.4 8.49 1,155 1.4

200 1,141 17.4 8.49 1,156 1.3

215 1,156 17.2 8.48 1,157 1.3

230 1,171 17.2 8.48 1,158 1.3

245 1,186 17.1 8.48 1,158 1.3

300 1,201 16.9 8.48 1,160 1.3

315 1,216 16.6 8.47 1,161 1.6

330 1,231 16.6 8.46 1,162 1.6

345 1,246 16.5 8.45 1,164 1.7

Table I–6. Physical and chemical characteristics in Whitewood Creek at the Sheeler Seep site, monitored between September 1 and 2, 

1988, to examine diel fluctuations in these characteristics.

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE

09/01/88 645 0 15.3 7.98 1,367 34.3

700 15 15.3 7.98 1,369 45.8

715 30 15.2 7.99 1,370 62.4

730 45 15.2 8.00 1,374 78.9 

745 60 15.2 8.00 1,377 97.5

800 75 15.2 8.01 1,378 135.2

815 90 15.2 8.03 1,380 186.9

830 105 15.2 8.04 1,383 133.3

845 120 15.3 8.05 1,383 366.0

900 135 15.3 8.07 1,386 485.9

915 150 15.5 8.08 1,385 549.7

930 165 15.6 8.09 1,390 624.8

945 180 15.9 8.10 1,388 696.7

1000 195 16.2 8.12 1,387 771.1

1015 210 16.5 8.14 1,385 850.5

1030 225 16.8 8.16 1,385 935.1

1045 240 17.3 8.17 1,383 980.9

1100 255 17.7 8.19 1,381 1,018.7

1115 270 18.1 8.20 1,378 1,091.0

1130 285 18.6 8.22 1,370 1,122.9

1145 300 19.3 8.23 1,370 1,146.0

Table I–5. Physical and chemical characteristics in Whitewood Creek at the Above Vale site, monitored between August 31 and 

September 1, 1988, to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
14 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

09/01/88—Continued 1200 315 19.8 8.24 1,368 1,177.4

1215 330 20.3 8.26 1,365 490.7

1230 345 21.0 8.27 1,364 663.8

1245 360 21.5 8.28 1,359 1,152.1

1300 375 22.1 8.29 1,355 1,218.8

1315 390 22.6 8.30 1,354 1,237.5

1330 405 23.0 8.31 1,349 1,256.4

1345 420 23.5 8.32 1,346 1,246.7

1400 435 24.0 8.32 1,344 1,214.4

1415 450 24.6 8.33 1,342 1,189.8

1430 465 24.9 8.34 1,341 1,167.1

1445 480 25.1 8.34 1,338 1,128.1

1500 495 25.4 8.34 1,338 1,071.4

1515 510 25.7 8.34 1,333 1,045.5

1530 525 25.8 8.34 1,325 986.5

1545 540 25.8 8.34 1,323 907.8

1600 555 26.1 8.33 1,325 838.3

1615 570 26.2 8.32 1,325 781.0

1630 585 26.2 8.32 1,325 717.5

1645 600 26.0 8.31 1,326 619.2

1700 615 25.8 8.31 1,325 545.4

1715 630 25.8 8.29 1,326 483.7

1730 645 25.5 8.28 1,326 279.4

1745 660 25.3 8.27 1,329 137.4

1800 675 25.0 8.25 1,326 82.6

1815 690 24.9 8.23 1,329 73.9

1830 705 24.6 8.21 1,331 60.5

1845 720 24.2 8.19 1,332 38.5

1900 735 23.9 8.18 1,334 33.9

1915 750 23.7 8.16 1,332 26.1

1930 765 23.5 8.15 1,334 10.8

1945 780 23.4 8.13 1,335 2.7

2000 795 23.0 8.11 1,336 1.7

2015 810 22.8 8.09 1,337 1.5

2030 825 22.5 8.08 1,337 1.4

2045 840 22.3 8.07 1,338 1.3

2100 855 22.0 8.05 1,339 1.3

2115 870 21.8 8.04 1,342 1.4

2130 885 21.4 8.03 1,344 1.3

2145 900 21.2 8.02 1,344 1.3

2200 915 20.9 8.01 1,344 1.3

2215 930 20.7 8.00 1,347 1.3

2230 945 20.3 8.00 1,351 1.3

2245 960 20.1 7.99 1,351 1.3

2300 975 19.8 7.99 1,349 1.3

2315 990 19.7 7.98 1,351 1.3

2330 1,005 19.4 7.97 1,349 1.3

2345 1,020 19.2 7.96 1,349 1.3

Table I–6. Physical and chemical characteristics in Whitewood Creek at the Sheeler Seep site, monitored between September 1 and 2, 

1988, to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
Methods of Study 15

In initial experiments, sorption of arsenate and phosphate was 

observed in living and heat-killed cells from three collection sites 

(HW, STP, and AV). The SS isolate was not initially used because 

of the similarity in media formulations for the AV and SS isolates. 

Algal suspensions (105 cells per milliliter) in 40-mL fluoroethylene polymer Oakridge tubes were spiked with arsenic-73 and 

phosphorus-32-labeled stock solutions yielding a 0.5-μmol/L concentration for both total dissolved arsenate and orthophosphate. 

Suspensions then were placed on a mechanical shaker and agitated. After 24 and 48 hours of exposure, suspensions were centrifuged at 10,000 revolutions per minute for 10 minutes to remove 

the algal cells from suspension. Five-milliliter volumes of the 

resulting supernatant, the algal suspension before centrifugation, 

and an internal arsenic-73 and phosphorus-32 standard were 

counted by liquid scintillation to determine the extent of arsenic 

and orthophosphate sorption by these cultures (table I–7).

In subsequent experiments, arsenic sorption by algal cells 

was studied in laboratory experiments as a function of dissolvedarsenate and orthophosphate concentrations in media formulations. Unialgal cultures of the diatom Achnanthes minutissima

(isolated by micropipetting from all four sampling sites) were used 

to determine sorption-rate constants. A. minutissima was selected 

for this series of experiments over the initially isolated chlorophytes (Stichococcus spp. and Scenedesmus spp.) because 

A. minutissima were present in greater abundance in periphyton 

samples and also were easily enumerated with a particle counter. 

Sorption-rate constants for arsenate and phosphate were determined from arsenic-73 and phosphorus-32-labeled experiments 

using heat-killed cells as described by Fisher and others (1984). 

Previous experiments (Kuwabara and others, 1988) indicated that 

use of heat-killed cells for short-term arsenate and orthophosphate 

sorption experiments yielded results comparable to living cell cultures and avoided the need for biomass corrections. A 32

 fullfactorial experimental design (n=3) was used to examine the 

interactive effects of arsenic and phosphorus on sorption rates 

and accumulation in A. minutissima. Isolates from the HW and 

AV sites were used because of contrasting ambient dissolvedarsenic concentrations. Arsenic-73 and phosphorus-32-labeled 

stock solutions were used to achieve 0.0-, 0.5-, and 1.0-μmol/L 

initial concentrations of dissolved arsenate and orthophosphate in 

the nine chemically defined formulations (representative of ambient concentration ranges observed at these two sites). An inoculum 

of heat-killed cells was then added (106

 cells per milliliter). After 

periods of 0.5, 1, 2, 4, 8, and 24 hours, supernatant from centrifuged cell suspensions were counted by liquid scintillation to 

determine solute removal from solution by the cells.

Table I–7. Algal cell sorption of arsenate and orthophosphate 

at 24 and 48 hours by living and heat-killed cells using three 

Stichococcus isolates from three sites along Whitewood Creek.

[Headwater site, HW; Sewage-Treatment-Plant site, STP; and the Above Vale 

site, AV. Calculated 95-percent confidence intervals are given for three replicate cultures. Culture media additions of dissolved arsenate and dissolved 

orthophosphate at 0.5 micromole per liter were used]

Sample

Elapsed

time

(hours)

Percent

arsenate

sorbed

Percent

orthophosphate

sorbed

Living Heatkilled Living Heatkilled

HW 24 25±12 29±11 93±2 94±2

48 23±8 20±6 96±2 95±2

STP 24 19±3 27±10 93±2 90±4

48 20±4 18±6 96±2 92±2

AV 24 24±6 21±10 88±2 84±2

48 16±5 19±3 94±2 84±2

09/01/88—Continued 0 1,035 19.0 7.96 1,354 1.3

15 1,050 18.7 7.96 1,351 1.3

30 1,065 18.5 7.95 1,354 1.3

45 1,080 18.2 7.95 1,357 1.3

100 1,095 18.2 7.95 1,357 1.3

115 1,110 18.0 7.95 1,360 1.3

130 1,125 17.7 7.94 1,359 1.3

145 1,140 17.6 7.94 1,360 1.3

200 1,155 17.4 7.94 1,360 1.3

215 1,170 17.4 7.94 1,360 1.3

230 1,185 17.2 7.93 1,362 1.2

245 1,200 17.1 7.93 1,355 1.3

300 1,215 16.9 7.93 1,360 1.3

315 1,230 16.7 7.93 1,354 1.3

Table I–6. Physical and chemical characteristics in Whitewood Creek at the Sheeler Seep site, monitored between September 1 and 2, 

1988, to examine diel fluctuations in these characteristics.—Continued

[Elapsed time in minutes; water temperature in degrees Celsius; COND, specific conductance in microsiemens per centimeter at 25 degrees Celsius; photosynthetically active radiation, IRRADIANCE, between 400 and 700 nanometers in microeinsteins per square meter per second]

Date Time Elapsed

time

Water

temperature pH COND IRRADIANCE
16 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

Results and Discussion

Field Experiments

Biomass in August 1986 increased downstream from 

the Headwater site (HW) to the Above Vale (AV) site and then 

decreased at the Sheeler Seep site (SS). Estimates for benthic 

plant biomass abundance (table I–1) represent the ash-free dry 

weights per unit area of scrapings multiplied by the percent coverage of algal growth at the sampling site. Autotrophic indices 

(AI) ranged from 120 at the HW site to 210 downstream from 

the municipal water-treatment plant (STP). This index has been 

used as an indicator of environmental stress, whereby increasing values indicate increasing abundance of senescent or 

stressed cells or an increasing proportion of heterotrophic 

growth (Leland and Carter, 1985; Weber, 1973). The HW and 

AV sites displayed AI values typical of unstressed communities 

(about 100±50), but elevated values at the STP and SS sites 

were observed.

Temporal changes in biomass observed in 1987 monthly 

samples differed among sites. Measured plant mass per unit 

streambed area was similar at the HW and STP sites, highest at 

the AV site once the mat was established, and lowest at the most 

downstream (SS) site (table I–2). At the HW site, which was 

dominated throughout the summer by a submerged macrophyte 

(Ranunculus longirostris), biomass increased from an average 

of 37 grams per square meter in late May to 60 grams per square 

meter in September. However, differences between monthly 

biomass measurements at the HW site were not significant at 

the 95-percent confidence level (table I–2). The large confidence intervals relative to average ρb values, even with nine 

replicates per site, is indicative of a patchy distribution of the 

benthic plant communities. At the STP site, a community dominated by Ranunculus during June and July changed during 

August and September to a dense growth of the pondweed 

Zannichellia galustris and the chlorophytes Cladophora spp.

and Ulothrix spp. Monthly biomass at the STP site did not differ 

significantly (table I–2). Because of streambed scouring, dense 

plant growth was not established at the AV site in June. However, by July, a thick (approximately 20 cm) mat of Ranunculus

and epiphytic diatoms blanketed more than half the stream 

channel. Similar to the STP site, August and September samples 

showed a shift toward Zannichellia and filamentous chlorophyte species at the AV site. Once a dense periphyton and 

macrophyte assemblage was established, biomass was most 

abundant at the AV site, where estimated biomass was an 

order of magnitude higher than at other sites. Elevated stream 

discharge in late May also inhibited the establishment of a 

dense assemblage at the SS site, but Zannichellia was observed 

in abundance by July under much lower flow conditions 

(table I–2). Epiphytic diatoms and filamentous chlorophytes 

dominated benthic plant communities in August and September 

samples. Biomass was consistently lower at the SS site than at 

the three upstream sites.

AI ranged from 80 at the SS site in July to 310 at the AV 

site in September (table I–2). All four sites in late May and 

July displayed AI values typical of unstressed or nonsenescent 

benthic plant communities, whereas elevated values were measured at the AV and SS sites in August and at the HW, AV, and 

SS sites in September. Dissolved oxygen was consistently at or 

above saturation in water-column samples.

Arsenic concentrations in algal tissues consistently 

increased between the late May and August sampling dates 

at the HW and STP sites and between July and August at 

the AV and SS sites except for the macroalgae at the SS site, 

which showed not significant concentration difference between 

July and August samples (table I–8). Concentrations measured 

in August and September samples were similar or showed a 

decrease in September. There also was a discernible increase 

in tissue arsenic concentration with distance downstream. 

However, the range of concentrations observed during the 

sampling period at the upstream (HW) site was greater than 

that observed at the downstream sites (table I–8). Arsenic 

in submerged macrophyte tissue was slightly higher than in 

macroalgae, although general concentration trends at each site 

were similar between plant groups. As noted in the “Methods 

of Study” section, arsenic concentrations for macrophyte tissue 

include contributions from epiphytic algal cells that are not 

excluded in the sampling procedure. Iron concentrations in 

digested samples indicate minimal effects on arsenic concentrations due to residual inorganic particles attached to plant tissues 

(table I–8).

Data from the diel study done between August 30 and 

September 2, 1988, at the four sampling sites are shown in 

tables I–3 to I–6 for the HW to SS sites, respectively, and in 

figures I–2 to I–5 plotted with dissolved-arsenic and orthophosphate concentrations. A comparison of measured parameters 

in this late summer sampling (data summarized in table I–9) 

shows trends in biomass and autotrophic indices (ratio of ashfree dry mass to chlorophyll-a) that were typical of the study 

sites for this period of the algal growth season (table I–2). Algal 

abundance increased from the HW to the AV site and decreased 

at the SS site. The highest estimated autotrophic index (210) 

at the AV site (the artificially pooled area) coincided with 

observed senescence of the benthic plant community at that 

site (for example, degraded macrophyte fronds and algal filaments, and visually observed organic detrital material within 

the mat).

The ranges for irradiance (table I–9) and the irradiance 

time course for the four sites (fig. I–2) were indicative of intermittent cloud cover, especially during the afternoons at the HW, 

STP, and AV sites, but indicated a consistently clear sampling 

day at the SS site. The water-temperature cycle typically lagged 

by 2 to 3 hours behind the irradiance (table I–10), and mean 

water temperature increased downgradient (that is, with 

decreased altitudes).

With the exception of the STP site, the amplitude of the pH 

cycle increased with increasing biomass, as one would expect of 

sites with metabolically active flora (the highest and lowest values for both pH amplitudes and biomass at the AV and SS sites, 
Results and Discussion 17

respectively). The pH cycle at each of the four sites lagged the 

irradiance cycle by 1 to 2 hours, which is similar to observed 

fluctuations in water temperature (table I–10).

An increase in total dissolved arsenic was observed 

between the HW and AV sites; a decrease occurred at the 

SS site (table I–9)—results are consistent with water years 1985 

and 1986 (Goddard, 1988). The predominant arsenic species at 

all four sites were inorganic. Our analytical protocol for arsenic

species indicated that inorganic trivalent arsenic represented 

less than 30 percent of the total dissolved arsenic at all sites, and 

significant dissolved organic arsenic was not detected as the difference between total dissolved arsenic and dissolved inorganic 

trivalent and pentavalent arsenic. There is a controversy as to 

whether the preservation technique prescribed by Glaubig and 

Goldberg (1988) does in fact prevent significant oxidation of 

trivalent arsenic to pentavalent arsenic. Therefore, the presence 

of reduced arsenic species may be even more significant than 

indicated by the analytical protocol used here. As expected, 

dissolved-orthophosphate concentrations were highest at the 

STP site and decreased downstream (table I–9). Concentration 

cycles in dissolved-arsenic species and dissolved orthophosphate lagged approximately 3 hours and 6 hours, respectively, 

behind pH cycles at the SS site, but no lag was resolved at the 

AV site for the major arsenic species (table I–10). Specific conductance at these sites cycled out of phase with fluctuations in 

arsenic species (fig. I–3). Diel cycles for dissolved arsenic and 

orthophosphate were not evident at the HW site upstream from 

mining activities because of low total dissolved-arsenic concentrations (less than 0.05 μmol/L) nor at the STP site downstream 

from water-treatment-plant discharge (table I–9).

Laboratory Experiments

In experiments using the chlorophyte Stichococcus, arsenate 

and orthophosphate sorption was similar for living and dead cells 

over the first 24 hours of exposure (table I–7). Concentrations 

accumulated (for both arsenic and phosphorus) were similar for 

algae collected from different sites and maintained at ambient solute concentrations. A preference of orthophosphate sorption over 

arsenate was observed for all species isolates.

Table I–8. Total arsenic concentrations in dominant benthic 

plant species collected from four sites along Whitewood Creek.

[Arsenic concentrations in plant tissues in micrograms solute per gram dry tissue with 95-percent confidence intervals (n=4 replicates). Iron concentrations 

in plant tissues in micrograms solute per gram dry tissue also were checked 

(n=1 replicate) for possible effects of residual inorganic particles (that is, particles remaining on plant tissue samples after the rinsing procedure) on reported 

arsenic concentrations. The Headwater and most upstream site, HW; SewageTreatment-Plant site, STP; Above Vale site, AV; and Sheeler Seep site (and 

most downstream sampling site for this study, SS). Symbol “–” indicates that 

the benthic plant community had not yet been established at that site and therefore tissues could not be sampled in adequate quantities for analysis]

Sampling site Arsenic Iron

Tissues sampled 05/27–28/87

HW Macroalgae1 1,465±38 2,180

Macrophyte2 1,552±16 2,070

STP Macroalgae 1,709±22 1,960

Macrophyte 1,757±14 1,850

AV Macroalgae – –

Macrophyte – –

SS Macroalgae – –

Macrophyte – –

Tissues sampled 07/07–10/87

HW Macroalgae 1,633±33 2,470

Macrophyte 1,866±9 2,140

STP Macroalgae 1,819±31 2,090

Macrophyte 1,971±8 1,690

AV Macroalgae 2,051±45 4,040

Macrophyte 2,390±8 5,170

SS Macroalgae 2,358±91 3,570

Macrophyte 2,480±16 3,150

Tissues sampled 08/19–26/87

HW Macroalgae 1,884±43 2,630

Macrophyte 2,180±52 2,860

STP Macroalgae 1,903±18 1,970

Macrophyte 2,030±49 2,210

AV Macroalgae 2,151±15 5,370

Macrophyte 2,479±39 4,830

SS Macroalgae 2,418±24 3,340

Macrophyte 2,572±42 3,020

Table I–8. Total arsenic concentrations in dominant benthic 

plant species collected from four sites along Whitewood Creek.

—Continued

Sampling site Arsenic Iron

Tissues sampled 09/16–28/87

HW Macroalgae 1,931±50 2,960

Macrophyte 1,991±83 2,340

STP Macroalgae 1,933±50 2,550

Macrophyte 2,099±112 2,070

AV Macroalgae 2,117±94 5,460

Macrophyte 2,184±95 5,160

SS Macroalgae 2,317±189 4,120

Macrophyte 2,352±23 4,760

1Samples dominated by filamentous chlorophytes and epiphytic diatoms. 

Specific changes in community structure are described in the text.

2Early summer samples typically dominated by the submerged macrophyte, Ranunculus longirostris and associated algal epiphytes, whereas later 

samples commonly dominated by the pondweed, Zannichellia palustris. 

Specific changes in dominant macrophyte species are discussed in the text.
18 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota pH pH

IRRADIANCE, IN

MICROEINSTEINS PER SQUARE METER PER SECOND

IRRADIANCE, IN

MICROEINSTEINS PER SQUARE METER PER SECOND

8.0

7.5

8.5

9.0

9.5

8.0

7.5

8.5

9.0

9.5

A

2400 2400 1200

0600 1800 2400 0600 1200 0600 1200 1800 2400 0600

1800 0600 0600 1800 1800 1800 1200 1200

08/29/88 08/30/88

0

500

1,000

1,500

0

500

1,000

1,500

B

08/30/88 08/31/88

TIME, IN HOURS

TIME, IN HOURS

C

08/31/88 09/01/88

D

09/01/88 09/02/88

pH

pH

pH

pH

Irradiance

Irradiance

Irradiance

Irradiance

Figure I–2. Diel trends in pH and irradiance along Whitewood Creek at (A) the Headwater site, (B) the Sewage-TreatmentPlant site, (C) the Above Vale site, and (D) the Sheeler Seep site.
Results and Discussion 19

TIME, IN HOURS

pH

pH

As(V)

As(III)

pH

As(V)

As(III)

0

0.5

1.0

1.5

B

8.0

8.5

7.5

9.0

9.5

A

1200 1200 1800 1800 2400 2400 0600 0600

08/31/88 09/01/88 09/01/88 09/02/88

DISSOLVED ARSENIC,

IN MICROMOLES PER LITER

AsT

AsT

Specific

SPECIFIC CONDUCTANCE,

conductance

IN MICROSIEMENS PER CENTIMETER

As(V)

As(III)

AsT

AsT

As(V)

As(III)

Specific

conductance

B

1,100

1,200

1,300

1,400

A

0

0.5

1.0

1.5

DISSOLVED ARSENIC,

IN MICROMOLES PER LITER

TIME, IN HOURS

1200 1200 1800 1800 2400 2400 0600 0600

08/31/88 09/01/88 09/01/88 09/02/88

Figure I–3. Diel trends in specific conductance and laboratory determinations for dissolved-arsenic species for (A) the 

Above Vale site and (B) the Sheeler Seep site.

Figure I–4. Diel trends in pH and concentrations of arsenic species for (A) the Above Vale site and (B) the Sheeler 

Seep site.
20 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

TIME, IN HOURS

Orthophosphate

As(V)

As(III)

AsT

AsT

As(V)

As(III)

Orthophosphate

0

0.5

1.0

1.5

B

0.6

0.4

0.2

0

A

1200 1200 1800 1800 2400 2400 0600 0600

08/31/88 09/01/88 09/01/88 09/02/88

DISSOLVED ORTHOPHOSPHATE,

IN MICROMOLES PER LITER

DISSOLVED ARSENIC,

IN MICROMOLES PER LITER

Figure I–5. Diel trends in concentrations of dissolved orthophosphate and arsenic species at (A) the Above Vale site 

and (B) the Sheeler Seep site.

Table I–9. Site comparison for parameters monitored along Whitewood Creek.

[Headwater site, HW; Sewage-Treatment-Plant site, STP; Above Vale site, AV; and Sheeler Seep site, SS. Mass concentrations of benthic flora, biomass, in grams 

per square meter are tabulated with 95-percent confidence intervals (n=9). Autotrophic indices reflect the ratio of mean ash-free dry mass to chlorophyll-a. Photosynthetically active radiation, irradiance, represents solar radiation between 400 and 700 nanometers in microeinsteins per square meter per second. Water and 

air temperatures are tabulated in degrees Celsius. Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius. Concentrations for total 

dissolved arsenic, pentavalent arsenic, As(V), trivalent arsenic, As(III), and orthophosphate are given in micromoles per liter. Alkalinity measurements are given 

in milliequivalents per liter. Values tabulated for data-logger parameters represent 15-minute averages of measurements taken at 10-second intervals. Brackets 

denote inclusive ranges for monitored parameters. Abbreviation “N.D.” indicates that parameter values were not determined]

Parameter

description HW STP AV SS

Biomass 48±19 57±26 316±53 32±17

Autotrophic index 120 110 210 190

Data-logger parameter ranges

Irradiance [0, 1030] [0, 940] [0, 830] [0, 1240]

Air temperature [3.1, 28.1] [7.7, 25.5] [10.1, 37.3] [6.3, 37.9]

Water temperature [8.5, 18.8] [12.0, 17.1] [14.8, 23.2] [15.2, 26.3]

pH [8.30, 8.78] [8.14, 8.57] [8.37, 9.02] [7.93, 8.34]

Specific conductance [220, 320] [720, 830] [1120, 1180] [1320, 1390]

Ranges for laboratory analysis1

Total dissolved arsenic <0.05 [0.23, 0.28] [0.91, 1.28] [0.45, 0.69]

Dissolved As(V) <0.05 [0.14, 0.18] [0.65, 1.12] [0.36, 0.59]

Dissolved As(III) <0.05 [0.06, 0.07] [0.11, 0.23] [0.08, 0.11]

Dissolved orthophosphate [0.04, 0.41] [13.1, 15.5] [0.19, 0.44] [0.06, 0.25]

Alkalinity N.D. N.D. [2.84, 3.24] [2.89, 3.40]

3Tabulated ranges indicate the minimum and maximum 15-minute average values for the site monitoring period (1 day for the Headwater, Above Vale, and 

Sheeler Seep sites; 2 days for the Sewage-Treatment-Plant site).

4Arsenic, orthophosphate, and alkalinity determinations by S.P. Pasilis, M.W. Shockey, and C.C. Fuller, respectively.
Results and Discussion 21

Short-term sorption-kinetics experiments using the 

diatom Achnanthes minutissima indicated that a first-order 

rate equation closely describes the observed algal sorption of 

arsenate. Fit of the kinetic data for HW and AV isolates at the 

nine treatment combinations to a first-order model (Dixon, 

1985) yielded consistently high coefficients of determination 

(r2

≥0.84, table I–11). Sorption-rate constants were significantly 

increased by elevating dissolved-arsenate concentrations. A 

comparison of rate constants for HW and AV isolates shows 

significantly lower constants for the apparently arsenic-tolerant 

AV isolate. The accumulation of arsenic by both isolates 

was inhibited by increasing orthophosphate concentrations. 

The AV isolate had slightly lower Kb values than did the 

HW isolate. Increasing dissolved-arsenate concentrations 

in the media did not result in a corresponding increase in 

biologically sorbed arsenic (note in table I–11 that the Kb

values significantly decreased at higher dissolved-arsenic 

concentrations).

As with arsenic sorption, orthophosphate sorption also 

was well described by first-order mass transfer (table I–12). 

Sorption-rate constants for orthophosphate were consistently 

lower than for arsenate, and unlike arsenate, sorption did not 

vary significantly between isolate or with variations in dissolved arsenate or orthophosphate (table I–12). Accumulation 

of phosphorus decreased with increase in dissolved arsenate. 

As observed in initial chlorophyte experiments, orthophosphate 

was preferentially accumulated over arsenate by A. minutissima, as clearly indicated by the orders of magnitude larger 

Kb scale for phosphorus relative to arsenic. Large Kb error 

bars for orthophosphate reflect low solution concentrations 

at equilibrium in these batch experiments.

Table I–10. Lag times, in hours, between selected water-quality 

variables monitored along Whitewood Creek.

[Total dissolved arsenic, AsT; dissolved pentavalent arsenic, As(V); and 

dissolved trivalent arsenic, As(III). Lag times in hours; cross correlation coefficient, r, is dimensionless, as is the number of time-corresponding measurements, n. Abbreviation “N.D.” indicates that values were not determined 

because diel fluctuations in dissolved-arsenic species and orthophosphate were 

not evident at the Headwater and Sewage-Treatment-Plant sites as described in 

the “Results” section]

Water-quality

characteristic

Lag

time

Maximal 

r value n

Headwater site

pH lags irradiance 1.5 0.75 98

Water temperature lags irradiance 2.0 0.77 98

AsT lags pH1 N.D.

As(V) lags pH N.D.

As(III) lags pH N.D.

Orthophosphate lags pH N.D.

Sewage-Treatment-Plant site

pH lags irradiance 2.0 0.80 126

Water temperature lags irradiance 2.0 0.77 98

AsT lags pH N.D.

As(V) lags pH N.D.

As(III) lags pH N.D.

Orthophosphate lags pH N.D.

Above Vale site

pH lags irradiance 1.0 0.82 82

Water temperature lags irradiance 3.0 0.71 82

AsT lags pH 0 0.80 8

As(V) lags pH 0 0.77 8

As(III) lags pH 6 0.55 8

Orthophosphate lags pH 6 0.55 4

Sheeler Seep site

pH lags irradiance 1.5 0.88 83

Water temperature lags irradiance 3.2 0.70 83

AsT lags pH 3 0.58 8

As(V) lags pH 3 0.69 8

As(III) lags pH 6 0.55 8

Orthophosphate lags pH 6 0.42 4

5

Lower significant figures in lag estimates involving arsenic and orthophosphate data reflect the lower sampling frequency for laboratory-analyzed 

concentrations relative to data-logged parameters.

Table I–11. Results from experiments examining arsenate 

sorption by heat-killed Achnanthes minutissima cells isolated 

from the Headwater site and the Above Vale site.

[Headwater (HW) site with low (less than 0.1 micromole per liter) dissolved 

arsenic; Above Vale (AV) site with elevated (approximately 1 micromole per 

liter) dissolved arsenic. Sorption-rate constants, λb, in reciprocal hours; accumulation factors, Kb, ratio of micromoles solute per gram algae to micromoles 

solute per gram media. Confidence intervals (95 percent) reflect the multivariate regression from a 32 full factorial design (n=3) sampled at elapsed times 

of 0.5, 1.0, 2.0, 4.0, 8.0, and 24.0 hours after inoculation. The coefficients of 

determination (r 2) are given for a fit of the kinetic data to a first-order model 

(Dixon, 1985). Details of the experimental design are provided in the text]

Treatments

(micromolar

solute added)

Arsenate transport

characteristics

Arsenate Orthophosphate λb Kb r 2

HW isolate

0.5 0.0 0.73±0.08 1,790±70 0.96

0.5 0.5 0.56±0.08 1,340±90 0.92

0.5 1.0 0.94±0.13 990±50 0.92

1.0 0.0 1.08±0.11 990±20 0.96

1.0 0.5 1.37±0.22 800±30 0.90

1.0 1.0 1.77±0.17 500±30 0.84

AV isolate

0.5 0.0 0.39±0.02 1,750±30 0.99

0.5 0.5 0.48±0.06 1,240±30 0.98

0.5 1.0 0.57±0.07 960±30 0.99

1.0 0.0 0.74±0.08 870±30 0.98

1.0 0.5 0.81±0.11 630±30 0.94

1.0 1.0 1.09±0.19 500±20 0.97
22 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

Effects of Benthic Flora on Physico-Chemical 

Processes

Our observation that arsenic accumulation (Kb values 

in table I–11) in A. minutissima decreased with increasing 

dissolved-orthophosphate concentrations is interesting but not 

surprising. Preferential sorption of orthophosphate over arsenate 

was observed in initial chlorophyte experiments (table I–7) and 

for marine diatoms (Morris and McCartney, 1984). Sanders 

(1985) suggested that the arsenic reactivity and toxicity to estuarine phytoplankton species could be altered by algal transformation of arsenic and subsequent release of methylated forms of 

arsenic. The mechanism of cell-surface preference for orthophosphate sorption in Whitewood Creek algal isolates has not been 

identified. However, the fact that preference was observed in 

experiments using cells from the HW site, not previously exposed 

to elevated dissolved-arsenate concentrations, suggests that the 

mechanism is not acquired by previous arsenic exposure.

Differences between algal isolates in arsenic sorption suggest that A. minutissima from the AV site exhibited arsenic tolerance in two ways. First, this isolate accumulated significantly less 

arsenic than did controls (the HW isolate) when initial dissolvedarsenate concentrations were high (1.0 μmol/L) and dissolvedorthophosphate concentrations were low (0.0 and 0.5 μmol/L) 

(table I–11). Second, the AV isolate consistently demonstrated 

slower arsenic sorption kinetics than did the HW isolate. Both 

observations represent distinctive advantages for cells exposed 

to elevated and fluctuating dissolved-arsenic concentrations. 

Conway (1978) observed that arsenic sorption by Asterionella 

formosa in continuous culture was linearly dependent on ambient 

dissolved-arsenate concentrations less than 1.8 μmol/L but 

reached a plateau at higher ambient concentrations. He hypothesized that this “leveling off” of cellular arsenic was due to saturation of arsenic sorption sites on cell surfaces. Our results using 

heat-killed cells support this hypothesis. However, Kb values for 

Whitewood Creek isolates suggest saturation above 0.5 μmol/L 

dissolved arsenate (table I–11). Arsenic saturation by A. minutissima at lower ambient concentrations relative to Asterionella 

formosa suggests a contributory factor toward the survival of 

A. minutissima over the arsenic concentration range of the four 

sampling sites (less than 0.1 to approximately 1 μmol/L). Algal 

accumulation factors measured here (table I–11) are within the 

range of values observed in other laboratory studies (Conway, 

1978; Giddings and Eddlemon, 1977).

Increasing algal abundance with distance downstream 

may be attributed to inputs of macronutrients from the watertreatment-plant effluent, ground-water inputs, and irrigation 

runoff from fertilized land. In addition, increased algal growth 

rates (Jorgensen, 1983) as a result of increasing water temperature in the downstream direction may contribute to the downstream increase in algal abundance (tables I–1 and I–2). At the 

SS site, decreased abundance may be caused by scarcity of firm 

substrate needed to establish a dense algal community. Visibly 

high turbidity also may have hindered photosynthetic activity 

at this site. Although periphyton and macrophyte growth was 

patchy, especially at the SS site, replicate ash-free, dry-weight 

measurements indicated similar biomass concentrations within 

the patches.

Elevated AI values, particularly at the AV and SS sites in 

August and September 1987, suggest a change in the condition 

of the submerged plant community. Senescence was visibly evident in these samples and probably represents typical growth progression and recession within these mats. It is interesting to note 

that the elevated AI observed in August 1986 at the STP site 

(Kuwabara and others, 1988) was not observed in 1987, probably 

because of a shift in community structure of benthic plants at the 

STP site in 1987 to include new growth of Z. palustris and various filamentous chlorophytes.

Without development of models describing physical and 

chemical transport of arsenic in this reach, it is difficult to directly 

apply the results of this modeling study to accurately determine 

the effects of the benthic flora on arsenic transport. However, episodic significance of the plant community can be demonstrated. 

In the spring, the most discernible change in plant abundance 

occurs with the establishment of the periphyton and macrophyte 

mat. Once the mat is formed, changes in the community structure 

principally observed at the STP and SS sites, and continued 

Table I–12. Results from experiments examining orthophosphate 

sorption by cell surfaces of Achnanthes minutissima isolated from 

the Headwater site and the Above Vale site.

[Headwater (HW) site with low (less than 0.1 micromole per liter) dissolved 

arsenic; Above Vale (AV) site with elevated (approximately 1 micromole per 

liter) dissolved arsenic. Sorption-rate constants, λb, in reciprocal hours; accumulation factors, Kb, ratio of micromoles solute per gram algae to micromoles 

solute per gram media. Confidence intervals (95 percent) reflect the multivariate regression from a 32

 full factorial design (n=3) sampled at elapsed times 

of 0.5, 1.0, 2.0, 4.0, 8.0, and 24.0 hours after inoculation. The coefficients of 

determination (r 2) are given for a fit of the kinetic data to a first-order model 

(Dixon, 1985). Details of the experimental design are provided in the text]

Treatments

(micromolar

solute added)

Orthophosphate transport

characteristics

Orthophosphate Arsenate λb Kb(×1,000) r 2

HW isolate

0.5 0.0 0.43±0.02 28±10 0.97

0.5 0.5 0.36±0.02 28±7 0.98

0.5 1.0 0.35±0.02 11±4 0.96

1.0 0.0 0.41±0.02 58±13 0.99

1.0 0.5 0.32±0.03 38±9 0.97

1.0 1.0 0.30±0.17 7.9±2.1 0.98

AV isolate

0.5 0.0 0.44±0.03 58±17 0.97

0.5 0.5 0.33±0.02 7.2±1.1 0.99

0.5 1.0 0.41±0.01 1.8±0.3 0.98

1.0 0.0 0.35±0.03 120±48 0.95

1.0 0.5 0.38±0.03 28±10 0.97

1.0 1.0 0.44±0.03 18±7 0.97
Results and Discussion 23

periphyton growth to maintain relatively constant ρb values as 

observed at the HW and STP sites, contribute to dynamics of the 

mat. In the fall, senescent tissues are scoured off and transported 

downstream or are decomposed and buried beneath settling sediment. These fluxes in the biomass parallel corresponding arsenic 

fluxes into and out of the mat as indicated by the temporal 

changes in biomass (ρb) and arsenic concentrations in the plant 

tissues (Cb) (tables I–2 and I–8). For example, at the SS site 

between May 28 and July 10, a 28 gram-per-square-meter change 

in ρb was observed. This corresponds to an average doubling time 

of 8.9 days. Using that 8.9-day doubling time and a 28 gramper-square-meter final biomass value in July, the greatest daily 

increase in biomass for this 43-day period would be 2.1 g/m2

/d. 

Given an average channel depth of 0.24 m (table I–2) and an algal 

tissue concentration of about 2,300 μg/g dry weight (table I–8), 

this daily mass flux during the establishment of the mat corresponds to a 0.3-μmol/L arsenic per day water-column flux. This 

is similar to the diurnal arsenic fluctuations observed by Fuller 

and others (1988) at the SS site. However, those measured fluctuations were made in August after the mat had been established. 

A similar calculation for the AV site results in a maximum daily 

mass flux and corresponding water-column arsenic flux of 

62.5 g/m2

/d and 7.8 μmol/L arsenic per day, respectively. This 

arsenic flux is an order of magnitude greater than the diurnal 

arsenic fluctuation observed at the AV site by Fuller and others 

(1988). The SS site was consistently dominated by epiphytic and 

filamentous algae that sorb solutes over the entire thallus (that is, 

water-column uptake). In contrast, at the AV site, 50 to 80 percent of the plant biomass is composed of submerged macrophytes 

that take up solutes from pore water through root systems in addition to water-column uptake. The effect on water-column solute 

concentrations for the AV site may therefore be overestimated by 

a factor of 2 to 5 but nevertheless is environmentally significant.

An inconsistency should be noted between the laboratory 

and field-measured values for arsenic accumulation by algal cells. 

Given the Kb values for the AV-site isolate (630 at 1 μmol/L 

dissolved arsenate and 0.5 μmol/L orthophosphate, table I–11), 

algal concentrations at that site should be approximately 400 μg 

arsenic per gram dry weight. Yet algal tissue concentrations 

of greater than 2,000 μg/g were measured. This discrepancy 

initially was believed to be due to arsenic associated with 

inorganic particles attached to plant tissues that remained 

after plants were washed. However, low iron concentrations 

in leachate used to measure algal arsenic concentrations do not 

support this hypothesis (table I–8). On the basis of arsenic-to-iron 

ratios reported for Whitewood Creek sediment (approximately 

1 to 70, Goddard and others, 1988), attached particles made up 

less than 10 percent of the total dry weight of the plant samples. 

Conway (1978) found that arsenic taken up by the diatom 

Asterionella formosa was concentrated in an organic layer surrounding the frustule. Enhanced accumulation by algae at the 

field sites could have been due to sorption and retention of particulate arsenic in this organic surface layer that was not effectively 

removed during washing. Results from laboratory algal cultures 

in the absence of particles would consequently underestimate 

measured algal accumulation.

Maintaining data-logger monitoring at the STP site for 

more than 24 hours allowed a comparison of pH trends during 

days when the site was exposed to different time courses in light 

intensity. Table I–4 indicates that the gradual irradiance fluctuations during the first day of monitoring relative to the second 

resulted in a corresponding gradual pH fluctuation on the first 

day relative to observed pH changes during the second. That is, 

pH lagged irradiance (table I–10) and showed similar trends in 

their time course over the two sampling days. 

The STP site, unlike the other three sites, exhibited a 

low pH amplitude relative to the biomass estimate (less than 

the HW site; 0.43 pH unit). This inconsistency may result at 

least in part from effects of the effluent from the municipal 

water-treatment plant on rates of photosynthesis or the buffering capacity at the STP site. This effluent represents a significant portion (approximately 10 percent) of the creek discharge 

at the STP site during the summer.

Diel fluctuations in specific conductance were examined 

as an indicator of ground-water effects on observed changes 

in solute concentrations. The observation that specific conductance was out of phase with irradiance is explained by the fact 

that the creek flows over a perched aquifer with high sulfate 

concentrations that contribute to high specific conductance of 

ground water (approximately 5,000 μS/cm with no diel fluctuations at the SS site, K.E. Goddard, oral commun.). Hem (1948) 

reported diel fluctuations in chloride concentration in the Gila 

River as a result of changes in the hydraulic gradient.

Diel variations in specific conductance have been reported 

(Kuwabara, 1992) as an indicator of trends in ground-water 

inflow. These trends are typical of streams where evapotranspiration in the riparian zone causes diel fluctuations in the hydraulic gradient (Rantz and Eakin, 1971; Wood, 1975; Winter and 

others, 1988). Changes in the hydraulic gradient also were 

evident in the increase in specific conductance with decrease 

in elevation between the HW and SS sites (table I–9). Maximal 

specific conductance, corresponding to maximal ground-water 

inflow into the creek, was not in phase with maximal dissolvedarsenic concentrations (figs. I–4 and I–5), thus supporting the 

hypothesis that the ground water was not the direct source driving observed fluctuations in dissolved arsenic, as observed by 

Fuller and others (1989), or dissolved orthophosphate. However, As(III), present at elevated concentrations in the ground 

water, oxidizes upon atmospheric or surface-water exposure 

(maximal channel inflow of ground water at night) then 

coprecipitates or adsorbs onto mineral surfaces. The ground 

water thereby may serve as an important source of particlebound arsenic that desorbs in response to photosynthetically 

driven increases in pH (Cherry and others, 1986; Goddard, 

1988; Fuller and Davis, 1989).

The observed lag in the arsenic species relative to 

the pH cycle observed at the SS site has been previously 

observed for total arsenic at the SS site and at another site 

7 km upstream from the AV site (Fuller and others, 1988). 

A discussion of the significance of these lags was previously 

presented and involves shifts in sorption equilibria in response 

to pH shifts (Fuller and Davis, 1989; Kuwabara, 1992). The 
24 Effects of Benthic Flora on Arsenic Transport in Whitewood Creek, South Dakota

lag of dissolved-arsenic species behind the observed pH cycle 

at the SS site was more pronounced than at the AV site, which 

had a greater biomass and a higher pH range than the SS site. In 

fact, the statistical analysis (table I–10) indicates that at a 3-hour 

sampling interval, a lag at the AV site cannot even be resolved 

for the dominant arsenic species. The amplitude of the cycles 

for dissolved-arsenic species at the AV site also were greater 

than at the SS site. In spite of lower cumulative irradiance at 

the AV site relative to the SS site on the respective sampling 

days for each site, the pH fluctuation was greater at the AV 

site, the artificially pooled area with higher biomass, than at 

the SS site.

Kuwabara (1992) discussed possible abiotic and biotic 

explanations for the lack of correspondence between temporal 

changes in dissolved orthophosphate and arsenic species 

observed at the AV and SS sites. Based on carbon-fixation estimates, Kuwabara (1992) determined that the demand for phosphorus by photosynthetic activity far exceeded the solution 

phase pool. Possible sources of supplementary phosphorus 

included solute regeneration within the mat or particle-bound 

phosphorus. Preferential sorption of orthophosphate over arsenate and the demand for orthophosphate imposed by photosynthetic activity provided a reasonable explanation for the dissolved orthophosphate lag behind changes in arsenic species. 

These observations for orthophosphate were contrasted by 

Fuller and Davis (1989) who concluded that periphyton uptake 

in Whitewood Creek was not a major process affecting arsenic 

diel cycles. These contrasting dissolved-orthophosphate and 

dissolved-arsenic observations might be expected based upon 

preferential phosphorus sorption by the benthic flora and consistently greater dissolved arsenic than dissolved orthophosphate at the AV and SS sites (table I–9), making the effects of 

the benthic flora on arsenic retention more difficult to resolve.

It is clear from these studies that algal isolates from 

Whitewood Creek have the ability to sorb orthophosphate over 

arsenate preferentially. Given the arsenic-transport characteristics reported here for A. minutissima, the rapid growth of biomass between late May and July at the AV and SS sites represents 

both a rapid and significant accumulation of arsenic (table I–8) 

within this single biological component. Furthermore, A. minutissima, which was exposed to elevated concentrations of dissolved arsenic, seems to be able to slow down the kinetics of 

cellular arsenic sorption. The results presented here suggest a 

number of extensions to this work that address complex questions related to the modeling of the effects of the benthic flora 

on stream transport of arsenic: What causes large annual variations in community structure of the type seen between 1986 and 

1987 samples? How do solute sorption processes differ between 

the algae and submerged macrophytes seen in abundance in 

1987? How does the state of the periphyton and macrophyte 

communities affect arsenic sorption and accumulation (that is, 

what other physical and chemical perturbations that account for 

changes in observed autotrophic indices, in addition to elevated 

orthophosphate concentrations, affect arsenic sorption)? How 

long does it take for plant species to adapt to ambient arsenic 

concentrations by way of changing sorption characteristics, and 

how does this vary among benthic plant species? Given the 

apparent importance of effects of cell sorption on solute transport, it is believed that a quantitative response to the above 

questions may be critical for incorporation into more sophisticated and ultimately predictive transport models for reactive 

solutes.

Summary and Conclusions

Effects of the benthic flora on arsenic transport in a 

mining-affected stream have been examined by estimating 

parameters for a kinetic sorption model. Using a first-order 

mass transfer equation, the effects of dissolved arsenate, 

orthophosphate, and previous solute exposure on transport 

parameters were determined for an algal species present at 

all four sampling sites along the 57-km study reach. Test algae 

took up orthophosphate preferentially over arsenate. Algae 

isolated from an area of elevated dissolved arsenate concentrated less arsenic than did the same species isolated upstream 

from mining activities when dissolved arsenate was high 

(1.0 μmol/L) and dissolved orthophosphate was low (0.0 and 

0.5 μmol/L). Lower arsenic sorption-rate constants also were 

determined for the apparently arsenic-tolerant isolate. These 

factors represent obvious advantages for species exposed to 

elevated and fluctuating dissolved-arsenic concentrations. Field 

and laboratory results reported here suggest that increases in 

plant biomass during mat development represent both a rapid 

and significant accumulation of arsenic within this single biological component and therefore may have significant effects 

on water-column concentrations.

In diel studies, characteristic shapes for diel pH fluctuations followed irradiance, while pH and water temperature 

lagged behind irradiance by 1 to 3 hours. Amplitudes of the pH 

cycles increased with biomass except at the STP site immediately downstream from water-treatment-plant discharge. Inorganic pentavalent arsenic dominated arsenic speciation at all 

sites. Concentration fluctuations in dissolved-arsenic species 

lagged pH fluctuations by approximately 3 hours at the Sheeler 

Seep site, but no discernible lag was observed at the Above 

Vale site, which has an order of magnitude higher biomass. 

Furthermore, the amplitudes of diel fluctuations in arsenic 

species were greater at the Above Vale site than at the Sheeler 

Seep site. The lack of phase correspondence between dissolvedorthophosphate concentrations and arsenic species may have 

resulted from preferential sorption of orthophosphate over 

arsenate by the biomass. The phosphorus demand from photosynthetic activity, based on carbon-fixation estimates, suggests 

a supplemental source, such as phosphate regeneration within 

the mat or desorption of particle-bound phosphate. The 

observed relationships provide further evidence for the need for 

a process-interactive approach to describe stream systems and 

for consideration of diel variations in water-quality monitoring 

programs.
References 25

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SECTION II. Evaluation of the Processes Controlling 

Dissolved Arsenic in Whitewood Creek, South Dakota

By Christopher C. Fuller and James A. Davis

Abstract

Coupled physical, chemical, and biological processes 

affect the concentration of dissolved arsenic in Whitewood 

Creek, South Dakota. In the lower reaches of the stream, 

dissolved-arsenic concentrations were controlled primarily 

by adsorption and coprecipitation with iron oxyhydroxides 

(ferrihydrite) as ground water enriched in arsenic entered the 

stream. Periphyton photosynthesis induced a diurnal pH fluctuation of 0.25 to 0.5 in surface water that had a pH of 8.1 to 8.7 and 

a concomitant diurnal cycle in arsenate (30- to 40-percent variation). The fluctuation in arsenate reflects the dynamic equilibrium 

of adsorption-desorption processes occurring in response to the 

pH cycle. Kinetics of the sorption processes are slow, which 

results in a cycle of dissolved arsenic that lags 2 to 4 hours behind 

the pH cycle. A mass balance for dissolved arsenate indicates that 

adsorption-desorption of arsenate on ferrihydrite surfaces in and 

on streambed sediments was the primary control of dissolved 

arsenic. Uptake of arsenate by algae and input from reducing 

sediments were of secondary importance to the dissolved-arsenic 

budget. The results demonstrate the importance of adsorptiondesorption processes in controlling trace-element concentrations 

in aquatic systems and the need to incorporate sorption kinetics 

into transport models. The effect of diurnal pH cycles on traceelement and nutrient cycling and availability may be of significance in other surface-water systems.

Introduction

Development of transport models to adequately describe 

and predict the fate of reactive solutes requires knowledge of 

the time dependence of chemical processes, such as adsorption, 

ion exchange, and precipitation, that control the partitioning 

between solution and solid phases (Rubin, 1983; Jaanasch and 

others, 1988). Incorporation of kinetic terms for such reactions 

is of particular importance in systems where the equilibrium 

that controls dissolved constituents fluctuates on time scales 

similar to or shorter than the partitioning process (reaction). 

For example, adsorption commonly is treated as an equilibrium 

process in partition-and-transport models, although kinetic 

studies of adsorption have shown a slow approach to equilibrium, particularly for the oxyanions (Hingston, 1981).

Adsorption processes commonly are invoked as a control on 

the concentrations of dissolved inorganic trace elements and contaminants in natural waters at concentrations below their solubilities (Morel, 1983; Drever, 1982). Recognition of the importance 

of this process of trace-element partitioning is the result of many 

laboratory studies on the uptake of metals and oxyanions by synthetic oxides (Davis and Leckie, 1980; Pierce and Moore, 1982; 

Anderson and others, 1976), natural solids (Lions and others, 

1982; Frost and Griffin, 1977), and from partial extractions of 

sediments from natural waters (Belzile and Tessier, 1990; Aggett 

and Roberts, 1986; Tessier and others, 1985).

Interest in the geochemical behavior of arsenic has developed because of growing concerns about contamination of surface water and ground water from agricultural and mining activities and as a consequence of power generation from fossilfuel combustion (Cullen and Reimer, 1989). The cycling of 

dissolved arsenic in surface-water systems is influenced by processes of absorption and desorption by chemical, physical, and 

biological constituents (Holm and others, 1980; Ferguson and 

Gavis, 1972; Aggett and O’Brien, 1985). Recent studies have 

suggested that iron is effective in the deposition, removal, and 

control of arsenic concentrations (Aggett and O’Brien, 1985; 

Belzile and Tessier, 1990; DeVitre and others, 1991). The 

arsenate anion is strongly sorbed by iron oxyhydroxides and, 

as in adsorption of other oxyanions by oxides, increases with 

decreasing values of pH (Leckie and others, 1980; Pierce and 

Moore, 1982; Goldberg, 1986; Fuller and others, 1993). 

pH is a determining factor in sorption equilibrium, and 

diurnal cycles of pH in surface water of upward of ±1 unit have 

been reported by Dunn (1967) and Turk (1988). Trace-element 

concentrations are controlled by sorption reactions. The effect 

of fluctuations of pH on trace-element cycles, however, has 

received little attention.

Purpose and Scope

The purpose of this report is to describe a mass balance for 

dissolved arsenic in order to evaluate the importance of sorption 

and other instream processes that control concentrations of 

dissolved arsenic. A field study was conducted to investigate 

the effect of adsorption processes on concentrations of dissolved arsenic in a small, perennial stream that was heavily contaminated by gold-mine tailings. A diurnal cycle in pH in surface water was observed that results from algal photosynthesis 
28 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

(Fuller and Davis, 1989). The concentration of dissolved 

arsenic also fluctuates diurnally in response to changes in the 

adsorption-desorption equilibrium with changing pH. A lag 

in the diurnal-arsenic cycle was attributed to the time dependence of the adsorption-desorption process. Kuwabara (1992) 

also observed diurnal cycles in pH, dissolved phosphate, and 

arsenic in this stream; the magnitude of the pH cycle was correlated to the standing crop of periphyton. 

Description of Study Area

Between 1876 and 1977, about 100 million Mg of finely 

ground mill tailings were discharged into Whitewood Creek in 

South Dakota. These tailings contain 0.25 to 0.75 percent arsenopyrite and other metallic-sulfide minerals (Goddard, 1987). 

This discharge has resulted in the deposition of contaminated 

flood-plain sediments that contain as much as 11,000 μg of 

arsenic per gram of sediment (Goddard, 1987). Field and 

mineralogic data indicate that a substantial fraction of the 

arsenic now is associated with iron oxyhydroxides and oxides. 

Transfer of arsenic from tailings to adjacent alluvial deposits 

has occurred when sulfide oxidation and flood-plain erosion 

and deposition were more active processes (Cherry and others, 

1986). As of 1987, most of the arsenic in fine-grained (<63 μm 

in diameter) suspended and bed sediments and in oxidized 

flood-plain deposits is associated with light mineral fractions in 

which density is less than 2.89 g/cm3

. In contrast, the arsenic in 

reduced flood-plain sediments is mainly in the heavy mineral 

fraction in which density is <2.89 g/cm3, perhaps as unoxidized 

arsenopyrite (McKallip and others, 1988). Oxidized flood-plain 

deposits mainly are coarse grained (>63 μm in diameter), and 

the bulk of the arsenic is in iron-oxide coatings on sand grains 

(Horowitz and others, 1988). Horowitz and others (1988) found 

arsenopyrite grains both in suspended- and bed-sediment samples that were not fractionated by density. However, attempts 

were not made to quantify the abundance of the unoxidized 

mineral. Iron-oxide rinds were on the surfaces of arsenopyrite 

and other sulfide mineral grains and may provide shielding 

from further oxidation (Horowitz and others, 1988).

Release of arsenic from the flood-plain deposits into 

ground water and surface water occurs by dissolution of, or 

desorption from, arsenic-rich ferrihydrite in alluvium (Cherry 

and others, 1986). Oxidation of arsenopyrite in tailings deposits 

is of minor importance because the abundance of carbonate 

minerals in flood-plain deposits (Marron, 1988) acts to buffer 

the acidity generated during oxidation of sulfides within the 

contaminated sediments. As a result, ground water in the 

flood-plain aquifers generally is of neutral pH (Cherry and 

others, 1986; Fuller and others, 1987). In the lower 35 km of 

the stream, input of arsenic to the stream results from seepage 

of arsenic-bearing and ferrous-iron-bearing ground water from 

the flood-plain aquifers after periods of high stream discharge 

(Cherry and others, 1986; Goddard, 1987). Dissolved arsenic 

in the ground water is present in the more reduced +3 oxidation 

state, arsenic(III); and in surface water, dissolved arsenic is 

essentially all in the +5 oxidation state, arsenic(V) (Fuller and 

others, 1987). Oxidation and precipitation of ferrous iron in the 

ground water occurs rapidly on contact with the atmosphere and 

the stream remove most of the dissolved arsenic through coprecipitation with iron or subsequent adsorption onto the ferrihydrite (Fuller and Davis, 1989). The buildup of arsenic-rich 

iron oxides in the streambed and a general downstream increase 

in dissolved arsenic result from the continuous discharge of 

contaminated ground water (Goddard, 1987). In addition, an 

increase in dissolved arsenic at a given site is observed at low 

stream stages during summer and fall because of the buildup of 

arsenic-bearing iron oxides in the streambed (Goddard and others, 1988). The abundance of iron oxides in the bed sediments 

and flood-plain sediments of this stream and the strong affinity 

of arsenate for iron oxyhydroxides (Pierce and Moore, 1982; 

Goldberg, 1986) suggest that control of dissolved arsenic is 

from reactions with the ferrihydrite surfaces. The small range 

in the molar ratio of arsenic to iron in iron precipitates, in 

coarse- and fine-grained bed sediments (average arsenic/iron: 

0.022±0.006), and in oxidized and unoxidized flood-plain 

deposits suggests that arsenic largely remains associated with 

iron throughout this system (Fuller and others, 1987). 

Acknowledgments

G.W. Zellweger contributed his expertise and efforts in 

conducting the conservative-tracer injection. J.S. Kuwabara 

provided suspended-sediment samples and data on concentrations of arsenic in algae.

Methods of Sample Collection and Analysis

Diurnal Sampling

In order to define the role of sorption processes in arsenic 

partitioning, hourly samples were collected in a 3-day period at 

the Sheeler Seep site (site A) in August 1987 (fig. II–1). This site 

is in the lower gradient reach of the stream about 2 km upstream 

from the confluence with the Belle Fourche River and 1 km 

upstream from the Sheeler site studied by Cherry and others 

(1986). Site A is 100 m downstream from a large, abandoned 

meander that contains unoxidized tailings and oxidized, coarser 

grained alluvium into which the stream was cutting as of 1987. 

Many seeps discharge ground water from this cutbank, and iron 

oxyhydroxide precipitates form as the ground water discharges 

into the stream. In this part of the stream, the flood plains are 

extensively contaminated with arsenic, and many visible groundwater seeps issue from the streambank during low flow.

At sites B and C (fig. II–1), hourly sampling also was conducted during the second and third days. Site B (Custer Camp) 

is 11.8 km upstream from site A in an area of extensive floodplain contamination and visible ground-water discharge. Site C 

(Whitewood Creek above Whitewood) is in the higher gradient
Methods of Sample Collection and Analysis 29

SOUTH DAKOTA

Missouri Riv e

C

r

heyenne River

Study area

Belle Fourche River

Whitewood Creek

Custer Camp

site B

Sheeler Seeps

site A

Whitewood Creek

above Whitewood

site C

Whitewood

Deadwood

Lead

103 40' O

44 40' O

44 30' O

44 20' O

103 30' O

0

0

10 KILOMETERS

10 MILES

Figure II–1. Map showing location of study area and location of sampling 

sites in Whitewood Creek.
30 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

part of the stream and had no apparent inflow of arsenic-bearing 

or iron-bearing ground water. At sites B and C, hourly water 

samples for determination of dissolved inorganic arsenic and 

other dissolved constituents were collected in a single container 

from the center of flow. At site A, samples were composited 

from four subsamples collected across the channel. Samples 

were filtered through 0.1-μm membrane filters and preserved 

by acidification with trace-metal grade hydrochloric acid to a 

pH of 1. A threefold greater iron concentration was measured in 

<0.45-μm filtrates than in <0.1- and <0.01-μm filtrates, which 

indicates a large component of colloidal iron (Fuller and others, 

1988a). The pH electrodes were calibrated at hourly intervals 

with buffers at surface-water temperature. Concurrent measurements of pH and water temperature also were made at onehalf-hour intervals. At site A, integrated incident-light intensity 

(400- to 700-nm wavelength) was measured at the water surface 

at one-half-hour intervals. Alkalinity samples were collected at 

3-hour intervals during the first 36 hours at site A. Total alkalinity was determined by Gran titration (Franson, 1985). Dissolved calcium was determined by flame atomic-absorption 

spectroscopy. Dissolved sulfate was determined by ion 

chromatography. Partial pressure of carbon dioxide of surface 

water was calculated with the chemical-equilibrium program 

MINEQL (Westall and others, 1976) from the measured pH 

and alkalinity during the first 24 hours at site A. Temperaturecorrected stability constants from Plummer and Busenberg 

(1982) were used.

Total dissolved inorganic arsenic was determined by 

hydride-generation atomic-absorption spectroscopy after 

reduction of arsenic(V) to arsenic(III) in strong acid by the addition of an excess of potassium iodide. The average uncertainty 

in analyses was ±0.03 μmol/L. Preliminary sampling indicated 

that dissolved arsenic in surface water is greater than 98 percent 

in the +5 oxidation state as the arsenate oxyanion (Fuller and 

others, 1987). Arsenic speciation was determined by graphitefurnace atomic-absorption spectroscopy after separation by 

anion exchange in the field immediately after filtration and 

acidification (Ficklin, 1983). The agreement between hydride 

generation and graphite-furnace analyses indicates that the 

concentrations of organic arsenic species are negligible. For 

the purpose of this report, dissolved-arsenic concentrations 

reported here are assumed to be entirely arsenic(V) as arsenate 

oxyanion species and will be referred to as CAs.

Statistical Analysis of Diurnal Surface-Water 

Chemistry Data

 A cross-correlation analysis was conducted on the diurnal 

time-series data to determine if observed variations in one constituent were in phase or lagging behind another constituent. 

The statistical computer program, Minitab (Ryan and others, 

1985), was used to generate correlograms of a range of lag times 

and their associated correlation coefficients (r). The correlation 

interval with the maximum r value was accepted as the lag 

time provided that the correlation was significant (P<0.05). The 

program required data sets with fixed time intervals. Missing 

intervals in time-series data were filled in by linear interpolation 

of adjacent time intervals. The resolution of the correlogram is 

equal to the sampling-time interval (±0.5 or ±1 hour). 

Conservative-Tracer Injection

In small streams, conservative-tracer injections are used 

to accurately determine stream discharge, fluctuations in discharge, and ground-water inflows (Bencala and others, 1987; 

Jackman and others, 1984/1985; Zellweger and others, 1989; 

Bencala and others, 1990). Traditional methods of stream gaging are inappropriate in streams that have a significant component of the total discharge flowing through streambed deposits 

(Zellweger and others, 1989). These subsurface zones have 

been described as transient-storage zones (Bencala and others, 

1990). The stream discharge determined by conservativetracer injection includes flow through the transient-storage 

zones, assuming that sufficient time is allowed for the tracer to 

equilibrate between the surface flow and the transient-storage 

zones. In this study, a conservative tracer was injected 2.8 km 

upstream from site A on the second and third days of diurnal 

sampling. Results from this conservative-tracer injection provided estimates of the magnitude of concentrations of dissolved 

arsenic in ground-water inflow to the stream along this reach.

A concentrated solution of bromide (4.02±0.14×105

 mg/L) 

was prepared by dissolving technical-grade lithium bromide into 

100 L of streamwater and injecting the solution into the stream 

for 28 hours at a flow rate of 69±1 mL/min from a constant-flowrate metering pump. At this concentration and flow rate, about 

1 mg/L of bromide in surface water was expected on dilution. 

This amount is above the background level for bromide concentration in surface water and ground water (<0.02 mg/L). During 

the first 3 hours of injection, samples were collected at 5- to 

10-minute intervals at four sites along the reach to determine the 

mean traveltime of the stream through the reach. Sampling times 

at these points were determined from a traveltime of about 

170 minutes for the reach on the basis of a dye test conducted 

before the injection. After the injected bromide had reached a plateau in concentration, stream discharge at any point downstream 

from the injection can be calculated from the bromide concentration at that point by the following relation (Zellweger and others, 

1989):

(1)

where

Qs = stream discharge below injection point in liters 

per second;

Qi = tracer-injection flow rate in liters per second;

Ca = bromide concentration in surface water, in milligrams per liter;

Ci = bromide concentration in injectate, in milligrams 

per liter; 

and

Cb = bromide concentration above injection point, in 

milligrams per liter.

Qs

Qi Ci Cb ( ) –

Ca Cb ( ) – = ----------------------------
Results and Discussion 31

Synoptic samples were collected 24 hours after the start of 

the injection at 20 points along this reach to determine the stream 

discharge as a function of distance. In addition, surface-water 

samples were collected at 10 of these sites for dissolved-arsenic 

analysis concurrent with the synoptic samples for bromide analysis. At the downstream end of the reach (the diurnal CAs sampling site), hourly samples for bromide analysis were collected 

throughout the duration of the injection to identify diurnal fluctuations in stream discharge. All surface-water samples for bromide analysis were filtered through 0.45-μm membrane filters. 

Concentrations of dissolved bromide, chloride, and sulfate were 

determined by ion chromatography. This method had a detection 

limit of 0.02 mg/L and a precision of ±0.01 mg/L.

Sampling of Ground-Water Inflows

Samples were collected at four seeps from the cutbank of 

the abandoned meander upstream from site A. A wide-mouth 

bottle was used to sample directly from the seep outflow, and 

the samples were filtered and acidified for determination of dissolved arsenic and iron. Separate samples were collected for 

anions and alkalinity. The other seeps along the 2.8-km reach 

were not suitable for sampling. In June 1987, at one of the four 

seeps, a 30-cm section of perforated 1.3-cm-diameter PVC tubing covered with 60-μm nylon screen was inserted horizontally 

into the streambank at the seep outlet, at the contact between the 

overlying flood-plain alluvium and the Pierre Shale. The outlet 

of the pipe was fitted with 0.64-mm (inside diameter) nylon tubing. Water was allowed to flow for 24 hours before sample collection. The seep was sampled in June and July 1987 as well as 

during the diurnal sampling. Ground water from this seep was 

filtered through a nitrogen-purged filtration tower and acidified 

before exposure to the atmosphere (Fuller and others, 1988a). 

Arsenic speciation after separation by anion exchange (Ficklin, 

1983) and iron speciation (Stookey, 1970) were determined for 

this sample. pH was measured in a flow-through cell that was 

fitted to the outlet of the horizontal well.

Solid-Phase Characterization and Adsorption 

Properties

To characterize the iron precipitate that forms as a result of 

oxygenation of ground water, a 20-L sample was collected in a 

glass carboy from the horizontal well seep. This sample was 

purged with air to oxidize and precipitate dissolved iron. The 

resulting precipitate was concentrated by settling and centrifugation. The iron oxyhydroxide precipitate was aged for 1 week at a 

pH of 8.0. An aliquot was dried and ground for X-ray diffraction 

characterization and for total arsenic and iron analyses following 

acid dissolution. The time dependence of arsenate adsorption 

onto this iron oxyhydroxide precipitate was studied by transferring 1.0-mL aliquots of the precipitate suspension into centrifuge 

tubes containing 30 mL of surface water collected at a pH of 

8.4 and filtered through a 0.1-μm filter. These tubes then were 

mixed on an end-over-end mixer at 12 revolutions per minute. 

At various time intervals through 120 hours, the solution 

phase from pairs of tubes was sampled for dissolved arsenic 

after pH measurement and centrifugation at 16,000 gravitational constant (G).

To determine the amount of arsenic associated with the solid 

that is available for desorption, arsenic isotopic exchange was 

measured on an additional set of tubes of the surface-water precipitate. The isotopic-exchange technique is based on the attainment 

of isotopic equilibrium between the solution phase (dissolved 

arsenic) and the fraction of adsorbate (arsenic) available for desorption (Davis and others, 1987). The radioisotope arsenic-73 in 

the +5 oxidation state was added to an aliquot of supernatant from 

one tube and mixed for 24 hours to ensure isotopic equilibrium in 

the solution phase. A 1.00-mL aliquot of the labeled solution then 

was added to each of 10 tubes that were equilibrated for 120 hours 

before the addition of the isotope. During the next 4 days, pairs 

of tubes were sampled, and the arsenic-73 activity that remained 

in solution was determined by gamma spectroscopy of the supernatant. The amount of exchangeable sorbed arsenic was calculated 

by mass balance from the amount of arsenic-73 removed from 

solution (Davis and others, 1987). This calculation assumes the 

total dissolved-arsenic concentration did not change significantly 

during isotopic exchange.

Results and Discussion

Diurnal Fluctuations in Surface-Water Chemistry

A diurnal fluctuation in the pH cycle of surface water varied 

as much as 0.5 unit at all three sites (figs. II–2, II–3, and II–4). 

The pH cycle results from algal photosynthesis that lowers the 

partial pressure of carbon dioxide during the day (Dunn, 1967; 

Turk, 1988). The diurnal cycle of pH is attributed to photosynthesis because of the correlation of pH maxima with light-intensity 

maxima at site A (fig. II–2A, table II–1) and because of the diurnal variations of dissolved oxygen (Fuller and Davis, 1989) and 

calculated partial pressure of carbon dioxide. At all three sites, the 

cycle of pH either preceded change in water temperature by as 

much as 2.5 hours or was in phase with the measured diurnal 

variation in water temperature (table II–1). The amplitude of the 

pH fluctuation generally was constant during the two or three 

cycles measured at each site, and the amplitude of the temperature cycle varied as much as 50 percent between cycles at each 

site. These differences between pH and water-temperature cycles 

suggest that increases in pH did not result from a decrease in 

carbon dioxide solubility as surface-water temperature increased. 

Partial pressure of carbon dioxide in surface water ranged from 

680 ppm at high pH to 1,200 ppm at low pH and always was 

supersaturated with respect to equilibrium with the atmosphere. 

Stream reaeration probably is insufficient for equilibrium with 

the atmosphere. This disequilibrium results in the fluctuations 

of pH in response to changes in partial pressure of carbon dioxide 

as the rate of photosynthesis varies diurnally. Diurnal pH fluctuations observed in other surface-water systems have been attributed to photosynthetic activity (Dunn, 1967; Turk, 1988).
32 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota INCIDENT-LIGHT INTENSITY, IN EINSTEINS PER SQUARE METER

 0

0.20

0.10

8.3

8.4

8.5

8.2

8.1

8.0

pH

0.05

0.15

 0.5

0.9

0.7

8.3

8.4

8.5

8.2

8.1

8.0

pH

0.6

0.8

TIME

AUGUST 11 AUGUST 12 AUGUST 13

LIGHT INTENSITY

pH

DISSOLVED ARSENATE

pH

DISSOLVED-ARSENATE CONCENTRATION,

IN MICROMOLES PER LITER

 0000 0600 1200 1800 0000 0600 1200 1800 0000 0600 1200 1800 0000

A

B

Figure II–2. Incident-light intensity, dissolved-arsenate concentration, and pH compared to time of day at site A, August 11–13, 1987.
Results and Discussion 33

9.0

8.2

pH

 0.7

1.1

0.9

0.8

1.0

TIME

AUGUST 11 AUGUST 12 AUGUST 13

DISSOLVED ARSENATE

pH

8.6

8.8

8.4

DISSOLVED-ARSENATE CONCENTRATION,

IN MICROMOLES PER LITER

 0000 0600 1200 1800 0000 0600 1200 1800 0000 0600 1200 1800 0000

Figure II–3. Dissolved-arsenate concentration and pH compared to time of day at site B, August 12–13, 1987.

Figure II–4. Dissolved-arsenate concentration and pH compared to time of day at site C, August 12–13, 1987.

9.2

8.0

pH

 0.7

1.1

0.9

0.8

1.0

AUGUST 11 AUGUST 12 AUGUST 13

DISSOLVED ARSENATE

pH

8.4

8.6

8.2

8.8

9.0

DISSOLVED-ARSENATE CONCENTRATION,

IN MICROMOLES PER LITER

TIME

 0000 0600 1800 1200 1800 0000 0600 1200 0000 0600 1200 1800 0000
34 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

A diurnal cycle in dissolved arsenate was observed at 

sites A and B (figs. II–2B and II–3). The fluctuation in CAs

of as much as 40 percent lagged behind the cycle of pH by 2 to 

4 hours (table II–1). Fluctuations in both pH and CAs were greater 

at site B than at site A. Additionally, a shorter lag time of CAs

behind pH also was observed at site B. The general trend of CAs

fluctuation with pH at these sites is consistent with the pH dependence of arsenate adsorption by iron oxyhydroxides (Pierce 

and Moore, 1982; Goldberg, 1986). The higher CAs at site B 

was because of higher pH range and a slightly higher arsenic to 

iron molar ratio in bed sediments in this reach. The shorter lag 

time of the CAs cycle for pH cycles of greater amplitude also was 

observed by Kuwabara (1992). Although a diurnal fluctuation in 

pH of 0.5 unit also was observed at site C, no significant variation 

in CAs was observed (fig. II–4). CAs, pH, and water-temperature 

data for the three sites are given in Fuller and others (1989).

Total alkalinity ranged from a minimum of 2.93 meq/L to 

a maximum of 3.42 meq/L and appeared to fluctuate in phase 

with pH (fig. II–5). A significant cross correlation of alkalinity 

with pH was not possible because of the small number of alkalinity samples. Sulfate fluctuated diurnally by 0.35 mmol/L 

but was out of phase with pH cycle by about 10 hours (fig. II–5 

and table II–1). Dissolved calcium also fluctuated diurnally and 

ranged from 3.05 to 3.38 mmol/L and was in phase with sulfate 

(data not shown). Dissolved ferrous and total iron both were 

below the detection limit of 0.1 μmol/L in all samples.

Table II–1. Cross-correlation analysis of diurnal time-series data.

Cross correlation of first component 

time series to second component time series

Time interval,

in hours

Lag of first component

time series behind

second component1

(hours)

Maximum correlation

coefficient used to

define lag time2

(r)

Number of pairs 

of data used in 

cross-correlation

analysis

I. Site A

Arsenic, dissolved to pH ................................ 1 4 0.62 55

pH to light ...................................................... 0.5 0.5 0.79 110

Water temperature to light.............................. 0.5 3.0 0.86 110

Water temperature to pH ................................ 0.5 1.5 0.66 110

Sulfate to pH................................................... 1 10 0.76 52

Bromide to sulfate .......................................... 1 –1 0.77 23

II. Site B

Arsenic, dissolved to pH ................................ 1 2 0.83 37

Water temperature to pH ................................ 0.5 2.5 0.83 73

III. Site C

Arsenic, dissolved to pH ................................ 2 (3) (4) 18

Water temperature to pH ................................ 0.5 0.5 0.80 71

IV. Intersite Comparison

1. Sites A and B

Arsenic, dissolved, site B to arsenic, 

dissolved, site A ..........................................

1 –2 0.67 33

pH, site B to pH, site A 0.5 –1.5 0.92 67

pH, site B to light, site A 0.5 –0.5 0.83 67

Temperature, site B to temperature, 

site A ..........................................................

0.5 0 0.93 67

2. Sites A and C

pH, site C to pH, site A .................................. 0.5 0 0.73 67

pH, site C to light, site A................................ 0.5 –1.0 0.79 67

Temperature, site C to temperature, 

site A ...........................................................

0.5 0 0.96 67

1

Negative lag indicates second component proceeds first.

2Resolution equals length of data-time intervals.

3

No correlation observed.

4Maximum r value insignificant (P<0.05).
Results and Discussion 35

Ground-Water Chemistry

The results of analyses of ground-water data collected 

from seeps in the abandoned meander upstream from site A 

(table II–2) are similar to results of analysis of ground-water 

data collected by piezometer in tailings and oxidized alluvium 

at several sites along Whitewood Creek (Cherry and others, 

1986; Fuller and others, 1988a). The concentration of 

dissolved arsenic was five to eight times higher in the groundwater seeps than in surface water and, in contrast to surface 

water, was predominantly in the +3 oxidation state. The predominance of +5 oxidation state in surface water suggests that 

oxidation of arsenic is rapid. Belzile and Tessier (1990) have 

argued that only arsenic in the +5 oxidation state should be 

associated with iron oxyhydroxides. Concentrations of dissolved iron—essentially all as ferrous iron—in ground water 

were more than three orders of magnitude greater than concentrations of dissolved iron in surface water. Sulfate and alkalinity 

also were elevated in ground water. Data for each constituent 

from the various sampling dates were averaged for use in modeling ground-water inflow to the stream (table II–2).

Variations in Stream Discharge

The increase in dissolved bromide from background level 

(<0.02 mg/L) to the plateau concentration (1.1 mg/L) at site A 

yielded a mean traveltime of 147 minutes through the 2.8-km 

injection reach (fig. II–6). Mean traveltime is defined as the time 

between the start of the bromide injection and the point at which 

bromide reaches 50 percent of plateau concentration. Triska and 

others (1989) have defined this as the nominal traveltime. An 

overall velocity of water in the reach of 0.32 m/s is calculated by 

dividing the length of the reach by the mean traveltime (Jackman 

and others, 1984/1985). Velocities within each subreach between 

adjacent sampling points were 0.34 m/s for the subreach 0 to 

1,518 m downstream from the injection point; 0.36 m/s for the 

subreach between 1,518 to 2,267 m, 0.22 m/s for the subreach 

between 2,267 to 2,543 m, and 0.32 m/s for the subreach between 

2,543 and 2,842 m. The lowest velocity was in a 276-m reach that 

included a ponded section of lower gradient stream reach that had 

thick, fine-grained bed sediments. The ponded section is not characteristic of the rest of the study reach. The overall traveltime and 

velocity for the 2.8-km reach are used in modeling ground-water 

inflows and rates of instream processes.

A linear decrease (r=0.91) in bromide concentration of 

7 percent through the 2.8-km injection reach (fig. II–7A) was 

measured in the synoptic samples. An increase in the stream discharge from 0.453 m3

/s at the injection point to 0.484 m3/s at the 

downstream end of the reach was calculated from equation II–1 

and the bromide concentrations from the linear regression for the 

upstream and downstream ends of the reach. The increase in 

stream discharge of 0.031 m3

/s is attributed to ground-water discharge from perched aquifers in the flood plain to the stream along 

the reach. This increase also is evident from a linear (r=0.98) 

downstream increase in dissolved sulfate (fig. II–7B) because 

ground water that discharges from flood-plain aquifers and the 

underlying shale is enriched in sulfate. The linear downstream 

decrease in bromide and the increase in sulfate indicate that

 0

4

2

1

3

AUGUST 11 AUGUST 12 AUGUST 13

TOTAL ALKALINITY

pH

8.3

8.4

8.5

8.2

8.1

8.0

pH

TOTAL ALKALINITY, IN MILLIEQUIVALENTS

PER LITER

TIME

 0000 0600 1200 1800 0000 0600 1200 1800 0000 0600 1200 1800 0000

Figure II–5. Total alkalinity concentration and pH compared to time of day at site A, August 11–13, 1987.
36 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

ground-water inflow to the stream is distributed evenly along the 

length of the reach. The fractional increase in stream discharge 

also can be calculated from the increase in sulfate throughout the 

reach by assuming a value of sulfate in ground water that is equal 

to the average concentration of sulfate determined in the seeps 

near site A (12.7 millimoles per liter [mmol/L], table II–2) as 

follows:

(II–2)

and

(II–3)

where

Qd = discharge at the diurnal sampling site A, in 

cubic meters per second;

Qgw = discharge from ground-water inflow, in cubic 

meters per second;

Qj = discharge at the injection point, in cubic meters 

per second;

SO4d = sulfate concentration at diurnal sampling site A, 

in millimoles per liter;

SO4gw = sulfate concentration in ground water, in 

millimoles per liter;

and

SO4j = sulfate concentration at injection point, in 

millimoles per liter.

If Qd is set to 1 and equation II–2 is substituted into 

equation II–3, solving for Qgw yields the fraction of discharge 

at site A because of ground-water inflow along the injection 

reach. This inflow results in a fractional increase in stream discharge of 0.11 in the 2.8-km reach that is significantly greater 

than discharge determined from the bromide data (0.07). Based 

on the range of sulfate—7 to 200 mmol/L— in ground water 

from piezometer measurements in the flood-plain aquifers of 

this stream (Cherry and others, 1986), the disparity probably 

results from ground water that contains higher sulfate concentrations than values of sulfate measured near site A. If values 

of stream discharge from bromide are used, an average value 

of sulfate in ground water of 18.7 mmol/L is required for the 

observed downstream increase in sulfate in surface water. 

Because of the uncertainty in concentration of sulfate in 

ground-water inflows, the fractional increase in stream discharge calculated from the injected bromide will be used for 

estimating the ground-water contribution to CAs.

Coincident diurnal fluctuations in bromide and sulfate 

were observed. Maximum concentrations for both constituents 

occurred at night, and minimal concentrations for sulfate 

occurred in early afternoon (fig. II–6). Cross-correlation analysis 

of diurnal bromide with sulfate time series yielded a 1-hour lag 

of sulfate behind bromide (table II–1). Because this diurnal fluctuation was observed both for the injected bromide and for sulfate, which is increased by ground-water inflow, the diurnal 

fluctuation in both constituents must be the result of an increase 

in stream discharge from sources upstream from the lithiumbromide injection site. The increase in stream discharge dilutes 

both constituents during the day. An increase in ground-water 

inflow only within the reach at night would result in the observed 

increase in sulfate but would cause a decrease in bromide from 

greater dilution. Concentrations of sulfate ranged from 5.93 to 

6.33 mmol/L, and concentrations of bromide ranged from 0.93 

to 1.18 mg/L. The greater relative fluctuation in bromide compared to sulfate may be attributed to a variation in sulfate in 

water entering the reach that dampens out the observed diurnal 

fluctuation in sulfate at the downstream end of the reach. On the 

basis of the concentrations of bromide in surface water, stream 

discharge at site A ranged from a minimum 0.391 m3/s at night 

to a maximum of 0.497 m3

/s at midday. The diurnal cycles of 

sulfate and bromide and, therefore, the stream-discharge minima, lag behind the pH cycle by 9 to 10 hours (table II–1). 

Qd = Qgw + Qj

SO4 [ ]d d Q SO4 [ ]gw gw Q SO4 = + [ ]j j Q

Table II–2. Ground-water chemistry data for Whitewood Creek near site A.

Date pH

Sulfate, 

in millimoles

per liter

Alkalinity, 

in millimoles

per liter

Arsenic, total,

in micromoles

per liter

Arsenic(III),

in micromoles

per liter

Arsenic(V),

in micromoles

per liter

Iron, total, 

in micromoles

per liter

Iron(II),

in micromoles

per liter

August 1986 6.6 12.0 (1) 3.63 3.39 0.24 151 125

June 1987 7.1 12.3 (1) 24.48±0.05 3.71±0.12 0.79±0.06 147 142

June 1987 7.1 12.9 5.3 4.06±0.07 (1) (1) 142 143

July 1987 7.0 12.7 (1) 3.57±0.13 3.50±0.05 0.26±0.11 191 190

July 1987 7.0 12.3 (1) 3.93±0.03 3.76±0.09 0.48±0.13 202 200

August 1987 (1) 13.7 (1) 2.42±0.11 (1) (1) (1) (1)

August 1987 (1) 12.8 (1) 4.11±0.11 (1) (1) (1) (1)

August 1987 (1) 12.1 (1) 4.22±0.24 (1) (1) (1) (1)

August 1987 (1) 12.9 (1) 3.73±0.18 (1) (1) (1) (1)

Average 

concentrations 7.0±0.1 12.7±0.8 5.3 3.8±0.6 3.6±0.2 0.4±0.3 167±28 160±33

5

Not analyzed.

6Plus minus sign represents standard error of mean of replicate analyses.
Results and Discussion 37

3

7

5

4

6

SLUFATE CONCENTRATION, IN MILLIMOLES PER LITER

AUGUST 11 AUGUST 12 AUGUST 13

2.0

0

BROMIDE CONCENTRATION, IN MILLIGRAMS PER LITER

1.0

1.5

0.5

SULFATE

BROMIDE

TIME

 0000 0600 1200 1800 0000 0600 1200 1800 0000 0600 1200 1800 0000

Figure II–6. Sulfate and bromide concentrations compared to time of day at site A, August 11–13, 1987.

Figure II–7. Bromide and sulfate concentrations compared to distance downstream for lithium-bromide injection site, 

August 13, 1987, 9 a.m. to 1 p.m.

4

8

6

5

7

DISTANCE DOWNSTREAM FROM INJECTION POINT, IN METERS

SLUFATE CONCENTRATION, IN MILLIMOLES PER LITER

0

BROMIDE CONCENTRATION, IN MILLIGRAMS PER LITER

0.50

0.75

0.25

SULFATE

BROMIDE

0 500 1,000 1,500 2,000 2,500 3,000 Diurnal arsenic sampling site

1.00

1.25
38 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

Diurnal fluctuations in stream discharge have previously been 

observed in tracer studies by Kennedy and others (1984/1985) 

and Bencala and others (1987), although no driving mechanism 

was proposed. Others have attributed these fluctuations to diurnal effects of evapotranspiration on ground-water discharge 

(Rantz and Eakin, 1972). Many large cottonwood trees growing 

in the flood plains of the stream may account for the observed 

fluctuation in ground-water inflow. 

Dissolved Arsenic in Synoptic Samples

Concentrations of dissolved arsenic in samples collected 

during synoptic sampling along the injection reach were variable 

but fell within the range of dissolved arsenic measured at site A 

(fig. II–8). If the synoptic sample CAs and the CAs measured at 

site A during the synoptic sampling period are plotted in relation 

to time instead of distance, the synoptic samples follow the trend 

of increasing CAs that was measured at site A. The measured variation then can be explained by the diurnal fluctuation in CAs. The 

results indicate that the processes that control the diurnal arsenic 

cycle occur throughout the reach and are present because of 

instream processes rather than variable point-source inflows and 

downstream transport. This hypothesis also is indicated by the 

concurrent cycles of CAs occurring at sites A and B (table II–1), 

which are 11.8 km apart. If the cycle was a result of transport 

from an upstream point source, the cycle of CAs at site A should 

lag behind the cycle at site B by 9.5 hours, assuming the traveltime per kilometer is the same as measured in the 2.8-km reach. 

Instead, the CAs cycle at site A lagged the CAs cycle at site B by 

1 hour (table II–1).

Arsenate Adsorption and Isotopic Exchange on Iron 

Oxyhydroxides

The reddish-orange iron oxyhydroxide precipitate that was 

formed and was isolated from ground water yielded an X-ray 

diffraction pattern characteristic of 2-line ferrihydrite (Carlson 

and Schwertmann, 1981). This least crystallized form of ferrihydrite results from the hydrolysis of ferric iron solutions at 

neutral pH and consists of primary crystallites of 0.8 to 1.5 nm 

in length (Waychunas and others, 1993). The ferrihydrite crystallites aggregate and coalesce rapidly under favorable conditions to form large, porous gelatinous floccules of 100 nm or 

greater length (Bottero and others, 1991). Ferrihydrite has a 

high reactive surface area for the adsorption of cations and 

anions (Dzombak and Morel, 1990). The field samples had 

a total iron concentration of 1.77×10–3 mol/g and total arsenic 

concentration of 2.36×10–5 mol/g that was determined by 

acid dissolution of the precipitate. Inductively coupled plasmaemission spectroscopic analysis of the acid leachate yielded, in 

addition to arsenic and iron, significant concentrations for manganese (4.9×10–5 mol/g) and cobalt (5.5×10–6 mol/g).

In laboratory studies of arsenate sorption by synthesized 

2-line ferrihydrite designed to simulate ground-water inflow to 

the stream, arsenic uptake during coprecipitation of arsenic with 

iron was rapid and was followed by constant CAs concentration 

during the next 24 hours (Fuller and Davis, 1989). The magnitude of uptake by coprecipitation decreased with increasing pH 

and resulted in a linear increase in CAs from a pH of 8.0 to a 

pH of 9.0. This pH dependence was similar to pH dependence 

in the sorption of oxyanions on oxides (Davis and Leckie, 1980;

0.5

0.8

0.7

0.6

DISTANCE DOWNSTREAM FROM INJECTION POINT, IN METERS

ARSENATE CONCENTRATION, IN MICROMOLES PER LITER

SYNOPTIC ARSENATE

DIURNAL ARSENATE

RANGE OF VALUES

0 500 1,000 1,500 2,000 2,500 3,000

RANGE OF VALUES OF DIURNAL CAS

DURING SYNOPTIC-SAMPLE COLLECTION

Figure II–8. Synoptic dissolved-arsenate concentration related to distance from lithium-bromide injection site, 

August 13, 1987, 9 a.m. to 1 p.m.
Processes that Contribute to the Diurnal Cycle of Dissolved Arsenic in Surface Water 39

Belzile and Tessier, 1990). In contrast, lower uptake and a slow 

approach to equilibrium were observed for the adsorption of 

arsenic when it was added subsequent to precipitation and aging 

of ferrihydrite (adsorption). Adsorption was characterized by 

a rapid (<5 minutes) uptake in arsenic that continued for 8 days 

as the arsenic diffused to adsorption sites on ferrihydrite surfaces within aggregates of colloidal particles (Fuller and others, 

1993). Desorption of arsenic from both adsorbed and coprecipitated systems with an increase in pH also exhibited this slow 

approach to equilibrium. Arsenate adsorbs to ferrihydrite primarily as an inner-sphere bidentate-surface complex in both 

coprecipitation and adsorption systems (Waychunas and others, 

1993). Adsorption is rapid in coprecipitation systems because 

arsenate adsorbs to ferrihydrite crystallite surfaces before 

aggregation. The rate of adsorption or desorption is limited 

by diffusion to or from sorption sites buried within ferrihydrite 

aggregates (Fuller and others, 1993). A slow approach to 

adsorption equilibrium often is observed for phosphate uptake 

onto ferrihydrite and soils (Barrow, 1983; Bolan and others, 

1985; Crosby and others, 1984). The rate-controlling process 

is attributed to the diffusion of phosphate into ferrihydrite 

aggregates (Willett and others, 1988).

A slow approach to equilibrium was measured for the 

uptake of arsenic at a pH of 8.0 from filtered surface water 

(<0.1-μm filter, collected at a pH of 8.4) onto the ferrihydrite 

precipitate formed from ground water (fig. II–9). This slow 

approach to equilibrium also was observed for arsenic adsorption and desorption by synthesized ferrihydrite (Fuller and 

others, 1993). After 5 days of uptake, the reversible fraction 

of sorbed arsenic was determined by arsenic-isotopic exchange. 

The exchange of arsenic-73 with particle-bound arsenic also 

exhibited a slow approach to equilibrium following an initial 

rapid exchange (fig. II–10). After 96 hours of arsenic-73 

uptake by the ferrihydrite, the calculated fraction of exchangeable arsenic was small (about 5 percent) compared with the total 

arsenic associated with the solid phase. The exchangeable fraction of sorbed arsenic would result in a solution concentration 

of 0.8 μmol/L if all the arsenic was desorbed. This amount 

is equivalent to about two times the uptake measured from 

pH 8.4 to pH 8.0. These experiments indicate that the arsenatesorption behavior of iron precipitates from the field is similar to 

arsenate-sorption behavior in laboratory-synthesized 2-line ferrihydrite (Fuller and others, 1993). Although the ferrihydrite 

precipitates and coatings on streambed sediments have high 

arsenic concentrations, the isotopic-exchange study indicates 

that, at most, only about 5 percent of the total arsenic is available for desorption.

Processes that Contribute to the Diurnal 

Cycle of Dissolved Arsenic in Surface Water

Diurnal cycles of CAs resulted from adsorption-desorption 

of arsenic from iron oxyhydroxides in the streambed (Fuller 

and Davis, 1989). A mass balance for dissolved arsenic at site A 

is presented to demonstrate the importance of adsorption processes in the streambed in controlling CAs in surface water. 

Processes contributing to the CAs cycle are estimated in units of 

micromoles per liter per day for comparison with the measured

TIME, IN HOURS

ARSENIC CONCENTRATION, IN MICROMOLES PER LITER

0 144

 0.2

0.7

24 48 72 96 120

0.6

0.5

0.4

0.3

Total iron = 1.4 x 10–4 mole per liter

Total arsenate = 15.7 micromoles per liter

 0.64 micromole per liter of dissolved

 arsenate added

pH = 8.0

Figure II–9. Uptake of arsenate at pH 8.0 from surface water by ferrihydrite formed from ground-water seep, as a 

function of time.
40 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

fluctuation in CAs of 0.21 μmol/L/d. A schematic representation 

of the dissolved-arsenic cycle illustrates the processes that may 

contribute to the diurnal cycle of CAs (fig. II–11). The fluctuation in concentrations of dissolved arsenate in surface water can 

be described by a one-dimensional advection-dispersion equation that includes the contribution to CAs from ground-water 

inflows. The equation was modified from Bencala (1983) to 

include other sources and sinks for CAs (fig. II–11) as follows:

(II–4)

where

CAs = concentrations of dissolved arsenate in surface 

water, in micromoles per liter; 

t = time, in seconds;

Q = volumetric streamflow, in cubic meters per 

second; 

x = distance, in meters;

A = cross sectional area of streamflow, in square 

meters; 

D = dispersion coefficient, in square meters per 

second; 

qgw = inflow of ground water per length of streamflow, 

in cubic meters per second per meter; 

Cgw = CAs of ground-water inflow, in micromoles per 

liter; 

fc = fraction of arsenic adsorbed during coprecipitation with iron from ground-water inflow;

Jsed = molecular diffusive flux of arsenic out of reducing 

fine-grained sediments, in micromoles per 

square meter per second; 

Ac = contact area of streamflow with streambed, in 

liters per square meter; 

Fc = net carbon fixation by algae, in moles of carbon 

per liter per second; 

and 

R = ratio of arsenic uptake by algae to carbon fixed, in 

micromoles of arsenic per moles of carbon.

The last two terms of equation II–4—Ps and Bs—describe 

the time-dependent adsorption and desorption of arsenate on ferrihydrite in suspended sediments and in bed sediments in contact 

with streamflow, respectively, as a function of pH and time as 

follows:

(II–5)

and

(II–6)

where

Ss = suspended-sediment concentrations, in grams per 

cubic meter;

λa = adsorption-desorption rate constant (s–1), in reciprocal seconds;

CAs ∂

∂t ----------- –QA

------- CAs ∂

∂x ----------- 1A

--- ∂

∂x

----- AD

CAs ∂

∂x ----------- ⎝ ⎠ ⎛ ⎞ = +

qgw

A

-------- Cgw 1 fc ∂[ ] ( ) –

∂pH ---------------------------------- ∂pH

∂t

+ ----------

J + ++ sedAc – FcR Ps Bs

Ps Ss

λa SAs KsCAs

1/n ∂ ( ) –

∂pH --------------------------------------------∂pH∂t = ----------

Bs AcZb( )ρ 1 – φ bBAs

λa BAs KsCAs

1/n ∂ ( ) –

∂pH -------------------------------------------- ∂pH∂t = ----------

TIME, IN HOURS

PERCENT ARSENIC-73 EXCHANGED

WITH ARSENIC ON SOLID

0 96 

 0

100

12 24 36 48 60 72 84

80

60

40

20

Figure II–10. Arsenic-isotope exchange as a function of time on ferrihydrite following 96 hours of uptake.
Processes that Contribute to the Diurnal Cycle of Dissolved Arsenic in Surface Water 41

SAs = concentration of arsenic in suspended sediments, 

in micromoles per gram;

n,Ks = Freundlich isotherm adsorption coefficients;

Zb = depth of bed sediment in contact with streamflow, 

in centimeters; 

φ = porosity of bed sediments;

ρb = dry sediment density, in grams per cubic 

centimeter; 

and

BAs = total arsenic concentration of bed sediment, in 

micromoles per gram.

Arsenate adsorption and desorption by ferrihydrite are 

described by a nonlinear Freundlich adsorption isotherm (Fuller 

and others, 1993). The rate of adsorption and desorption is limited by diffusion within aggregates of ferrihydrite (Fuller and 

others, 1993). For simplicity, a first-order rate constant is used 

to approximate the adsorption-desorption kinetics.

Instead of solving the complex transport equation (II–4), 

the individual input, reaction, and loss terms are evaluated over 

one diurnal cycle to illustrate the contribution of each process to 

the cycle in CAs. The source and loss terms are determined from 

the data collected in the 2.8-km study reach (2.4-hour traveltime) and are used to represent conditions along a reach with 

a 24-hour traveltime.

The various components contributing to the CAs cycle are 

estimated in units of micromoles per liter per day for comparison with the observed fluctuation in CAs of 0.21 μmol/L in 

1 day. The coincidence of pH and CAs cycles between sites 

(table II–1) indicates that the cycles are the result of processes 

that occur throughout the stream rather than the result of 

transport from upstream point sources. The measured variation 

in CAs with time in the 2.8-km reach also provides evidence that 

instream processes control the CAs cycle. Because the inflow 

of ground water is uniform throughout the 2.8-km reach as 

indicated by the linear decrease in bromide and increase in sulfate (fig. II–7), inflow of ground water per length of streamflow 

is assumed to be constant and equals ground-water discharge 

divided by reach length.

The following mass balance is limited to arsenic(V) 

species that comprises more than 98 percent of the total dissolved 

inorganic arsenic. In contrast, Kuwabara (1992) observed concentrations of arsenic(III) of 0.08 to 0.11 μmol/L at this site in the 

late summer of 1988; a slight fluctuation of arsenic(III) appears 

out of phase with arsenic(V). Possible reduction of arsenic(V) in 

acidified samples that occurs between sampling and analysis may 

account for the greater concentrations of arsenic(III) (Kuwabara, 

1992). In this study, arsenic(III) and arsenic(V) were separated 

immediately upon filtration by anion exchange (Ficklin, 1983) 

to eliminate reduction at low pH during sample storage.

Ground-Water Sources of Streamflows

Results of the bromide injection indicate that a 7-percent 

increase in stream discharge in the length of reach was attributed to ground-water inflow. The average concentration of 

dissolved arsenic in ground water at this site (3.8 μmol/L, 

Desorption

Sorption-desorption from flow

through coarse sediments

Reducing se

Organic degradation;

diments

iron oxide reduction

Streamflow

High arsenic [As] and iron [Fe+2]

ground-water discharge

Coprecipitation of

As with iron oxides

As

Sorption [As]

Sorption-desortion

onto sediments

Biological uptake by

algae and vascular plants

[As]

Molecular

diffusive flux

Iron

oxides

Streamflow

Oxidation

As(III) As(V)

Figure II–11. Generalized diagram showing dissolved-arsenate cycle.
42 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

table II–2) and the results of arsenic and iron coprecipitation 

experiments (Fuller and Davis, 1989) were used to estimate 

dissolved arsenic in ground-water inflow to the stream. By 

assuming that ground-water inflow to the surface water is uniform and constant in a distance equivalent to a 24-hour traveltime, the change in ground-water contribution to CAs is estimated by evaluating the third term in equation II–4 over one 

24-hour pH cycle as follows:

(II–7)

where

= change in CAs from ground-water inflow, in 

micromoles per liter per day;

∆t = change in time, in seconds; 

and 

fc = fraction of arsenic adsorbed with iron during 

coprecipitation from ground-water inflow.

Assuming that arsenic was not removed during precipitation of iron from ground water entering the stream (fc=0), a 

ground-water inflow of 2.37 μmol/L/d was calculated. Values 

of fc are determined from laboratory data for coprecipitation of 

arsenic under conditions simulating ground-water inflow to the 

stream as a function of pH (Fuller and Davis, 1989). Inputs of 

dissolved arsenic of 0.17 and 0.22 μmol/L/d are calculated 

when arsenic uptake is accounted for during coprecipitation 

with iron at a pH of 8.10 (fc=0.93) and 8.35 (fc=0.91), respectively. The difference in uptake of arsenic at a pH of 8.15 

and 8.35 results in a net change in CAs of 0.05 μmol/L/d 

( )because of input from ground water during a pH cycle. 

Because diurnal samples for arsenic and anion analyses were 

not collected at the upstream end of the injection reach, the 

effect of the measured diurnal fluctuations (fig. II–6) on 

ground-water inflows and on CAs cannot be determined. If 

inflow of ground water per length of streamflow increases by an 

amount equivalent to the observed day-to-night increase in sulfate of 7 percent, however, a of 0.04 μmol/L/d in a pH 

cycle is estimated by equation II–7.

Molecular Diffusive Flux from Bed Sediments

Release of arsenic to sediment interstitial water during the 

reductive dissolution of iron oxides and degradation of organic 

matter (Aggett and O’Brien, 1985; Peterson and Carpenter, 

1986; Cullen and Reimer, 1989) results in a diffusive flux to the 

overlying water column that contributes to CAs. A concentration 

of dissolved arsenic in pore water of 4.7 μmol/L was determined 

at a depth of 4 cm in a deposit of fine-grained reducing sediment (U.S. Geological Survey, unpub. data, 1987). Moleculardiffusive flux of arsenic from reducing fine-grained sediments 

(Jsed) was calculated from the gradient between CAs in pore water 

at 4 cm and the overlying surface water by using Fick’s first law 

(Berner, 1980) and evaluating the following equation over 4 cm:

(II–8)

where

D = self-diffusion coefficient, in square centimeters 

per second; 

θ = sediment tortuosity, unitless;

φ = porosity, unitless;

= concentrations of dissolved arsenic in pore water, 

in micromoles per liter; 

and

Z = depth in sediment, in centimeters. 

A Jsed of 1.65 μmol/m2/d is calculated using D for arsenate of 9.05×10–6 cm2/s at 25°C (Li and Gregory, 1974) and 

fine-grained sediment values for and θ of 0.8 and 2.0, respectively. This flux of arsenic is an upper limit because removal 

of arsenic by adsorption near the sediment/water interface is 

not accounted for (Aggett and O’Brien, 1985; Peterson and 

Carpenter, 1986).

Because the areal distribution of reducing sediments is 

unknown, quantifying the molecular-diffusive flux of arsenic 

in the length of the stream reach in the mass balance is difficult. 

An upper limit of the flux, however, can be calculated by 

converting the Jsed to micromoles per liter per day by multiplying by the effective contact area of surface water with the 

streambed, Ac. Ac is estimated from the overall mean-flow 

velocity for the 2.8-km reach of 0.32 m/s. First, a crosssectional area of flow (A) of 1.51 m2 is calculated by dividing 

the discharge (0.48 m3/s) by the velocity (Jackman and others, 

1984/1985). In 1 second, therefore, a volume of 0.48 m3 of 

water overlies 0.32 m of streambed. A vertically well-mixed 

stream that has a rectangular stream-channel geometry of 0.3 m 

in depth and 5.0 m in width for a cross-sectional area (A) of 

1.5 m2 is assumed. For these cross-sectional dimensions and a 

0.32-m length traversed in 1 second, a 0.48-cubic meter volume 

is in contact with 1.8 m2 of streambed for a contact area (Ac) of 

270 L/m2. Multiplying Jsed by Ac (equation II–4) results in a 

volumetric input of 0.006 μmol/L/d. This value is an upper limit 

because the assumption is made that the streambed along the 

reach is fine-grained reducing sediments. The streambed, however, typically consists of sand, gravel, cobbles, and limited 

areas of fine-grained (<63 μm) sediments that would reduce 

the magnitude of this input of CAs from the sediments by an 

unknown amount. The sediment-diffusive flux is assumed 

to be constant during the diurnal period and accounts for, at 

most, 3 percent of the measured diurnal fluctuation in CAs of 

0.21 μmol/L/d.

Algal Uptake of Arsenate from Surface Water

The similarity between the arsenate and phosphate molecules results in the uptake of arsenate by algae during photosynthesis (Apte and others, 1986; Andreae, 1978). Kuwabara 

and others (1990) observed preferential uptake of phosphate 

over arsenate by several orders of magnitude for algal cultures 

that were isolated from contaminated reaches of Whitewood 

Creek and that included site A. Despite this preferential uptake 

of phosphate, elevated arsenic content in algae at site A has been 

∆CAs

gw qgw∆t

A --------------Cgw 1 fc ( ) – pH8.15

pH8.35 =

∆CAs

gw

∆CAs

gw

∆CAs

gw

Jsed

θD

φ2 ------- Cpw

As ∂

∂Z = ----------------

Cpw

As

φ
Processes that Contribute to the Diurnal Cycle of Dissolved Arsenic in Surface Water 43

measured in the algal species, Cladophora and Ulothrix, that 

dominated the plant biomass. The rate of algal arsenic uptake 

from surface water (FcR in eq. II–4) is calculated by assuming 

that arsenic is incorporated during carbon fixation at the arsenicto-carbon molar ratio, R, observed in algae collected at this site 1 

week before the diurnal sampling (R=1.8×10–5; J.S. Kuwabara, 

hydrologist, U.S. Geological Survey, oral commun., 1987). 

Because nitrate uptake, which is light dependent (Triska and 

others, 1989), results in a concomitant increase in alkalinity 

(Stumm and Morgan, 1981), the observed diurnal fluctuation in 

alkalinity is attributed to algal productivity. The carbon-fixation 

rate, Fc, was estimated from the change in alkalinity (Stumm and 

Morgan, 1981) and the Redfield nitrogen-to-carbon-molar ratio. 

Multiplying the resulting Fc of 1.8×10–3 moles of carbon per 

liter per day by R yields an arsenic uptake rate by algae of 

0.033 μmol/L/d. This estimate may be low because alkalinity, 

like sulfate, is about two times greater in ground water than in 

surface water (table II–2). Because ground-water inflow may 

fluctuate diurnally, the surface-water alkalinity should increase 

at night and diminish the measured surface-water alkalinity fluctuation. An increase in alkalinity on the order of the 7-percent 

increase in sulfate measured from day to night, however, would 

not change the magnitude of algal arsenic uptake significantly. If 

the uptake of arsenic is directly correlated with phosphate uptake, 

which may be light enhanced (Wetzel, 1975; Stewart, 1974), the 

phase of algal arsenic uptake would diminish the measured diurnal fluctuation in CAs by 0.033 μmol/L/d.

Potential for Desorption of Arsenic from Suspended 

Sediments and Bed Sediments

The contribution to CAs by adsorption and desorption on 

suspended sediments in a cycle of pH could not be evaluated 

from equation II–5 because the pH dependence on nonlinearadsorption coefficients and the appropriate adsorption-rate constant are not well known. Instead, equation II–5 is simplified 

as follows to estimate the potential desorption of arsenate from 

suspended sediments by assuming that the fraction of SAs available to desorb is equivalent to the fraction of exchangeable 

arsenic associated with the seep precipitate as defined by isotopic exchange (5 percent). Desorption of arsenic is assumed to 

reach equilibrium rapidly.

(II–9)

where

= change in CAs due to desorption from suspended 

sediments, in micromoles per liter per day;

and

fd = fraction of adsorbed arsenic available for 

desorption.

Suspended sediments (Ss=22 mg/L) collected at this site 

in July 1987 had a concentration of arsenic of 5.2×10–6 mol/g 

(SAs) and a concentration of iron of 5.1×10–4 mol/g. These 

values were determined after digestion of suspended-sediment 

samples in concentrated nitric acid (U.S. Geological Survey, 

∆CAs

ss Ss fdS = As

∆CAs

ss

unpub. data, 1987). Assuming these values for Ss and SAs

were the same in August 1987 and that a maximum of 5 percent of the arsenic can desorb (fd=0.05), a maximum of 

0.006 μmol/L/d would result from desorption from suspended 

sediments, Ps, during a pH cycle. This estimate does not 

account for desorption of arsenic in or on streambed sediments.

The contribution to the diurnal fluctuation of CAs by 

adsorption and desorption from bed sediments in contact with 

streamflow, Bs, cannot be estimated independently because 

the depth of sediment, Zb, in equation II–6 is not known. 

The difference in the measured diurnal fluctuation in CAs of 

0.21 μmol/L/d and the sum of the other sources and sinks, 

however, indicate that by mass balance, Bs must account for 

85 percent of the diurnal CAs cycle (table II–3).

Sand-size and coarser grained bed sediments have visible 

iron-oxide coatings and contain high arsenic content (2.1 to 

20 μmol/g; Fuller and others, 1987). The arsenic-to-iron molar 

ratios both of fine- and coarse-grained sediments are similar to 

the arsenic-to-iron ratio of ferrihydrite precipitates collected at 

seep outflows. The continuous inflow of ground water to the 

stream results in a large reservoir of sorbed arsenic in the bed 

sediments because more than 90 percent of the dissolved-arsenic 

load is adsorbed to ferrihydrite that is formed during precipitation 

of iron in ground-water inflows. The ferrihydrite precipitates 

form coatings on the grains of the bed sediments. An additional 

source of adsorbed arsenic to the streambed occurs during high 

stream stages by the erosion of oxidized flood-plain deposits in 

which most of the arsenic is associated with iron-oxide coatings 

(Horowitz and others, 1988).

In order to estimate the contribution of the bed sediments 

to the diurnal cycle of CAs, the mass of sediment in contact with 

the streamflow must be determined. Bencala and others (1990) 

observed that a significant flow of streamflow moves through 

the streambeds of high-gradient gravel-bed and cobble-bed 

streams and that an exchange of water occurs between the surface flow and the flow within the streambed. The areas of flow 

through the streambed that exchange water with streamflow 

are transient-storage zones. The cross-sectional area of flow 

through the transient-storage zones can be estimated by modeling the increase of conservative-tracer concentration with time

∆CAs

ss

Table II–3. Estimated sources and sinks of dissolved arsenic 

(CAs) in Whitewood Creek, South Dakota.

Dissolved arsenic,

in micromoles per 

liter per day

Ground-water inflow, .............................. 0.05

Sediment diffusive flux, JsedAc .......................... 0.006

Algal uptake of As, FcR ..................................... –0.033

Desorption from suspended sediments, Ps ........ 0.006

Sum of inputs and loss....................................... 0.03

Observed diurnal fluctuation in CAs .................. 0.21

Desorption from bed sediment, Bs, 

by difference.................................................. 0.18

∆CAs

gw
44 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

after start of an injection and the decrease to background levels 

at the end of the injection period (Bencala and others, 1990). 

This flow includes a zone in which surface water exchanges 

rapidly with streambed flow.

Whitewood Creek is primarily a gravel-bed stream (Cherry 

and others, 1986), although significant amounts of sand and fines 

were measured within the streambed sediments. Quantifying the 

cross-sectional area of transient-storage zones was not possible 

with the present data set because bromide was not increased sufficiently above background levels to provide adequate resolution 

of the slow decrease to background levels following the rapid 

decrease in bromide after the injection ended. The absence of a 

resolvable slow decrease in the post-injection bromide and the 

rapid initial decrease in bromide (fig. II–6) suggest that the crosssectional area of the transient-storage zones is limited. Triska 

and others (1989) used the ratio of time for a conservative tracer 

to reach 50 percent of the plateau to the first arrival time of the 

tracer above background concentration as an indicator of the 

hydrologic retention of solutes in transient-storage zones within 

the streambed. A ratio of 1.06 for the 2.8-km injection reach indicates that these zones make up a small but significant fraction of 

the cross-sectional area of flow in Whitewood Creek.

Because the injection data do not allow determination of 

the cross-sectional area of the transient-storage zones or the 

mass of sediment in contact with this component of streamflow, 

desorption from a 1-cm-thick zone of bed sediment is calculated 

to illustrate the potential contribution of the bed sediments to 

the diurnal cycle in CAs. The assumption was made that a 1-cmthick zone is in chemical equilibrium with streamflow and that 

water in this zone exchanges rapidly with streamflow. The 

amount of arsenic that can desorb from a 1-cm-thick zone of 

streambed sediments during an increase in pH is calculated by 

simplifying equation II–6 to

(II–10)

where

= change in CAs due to desorption from bed sediments, in micromoles per liter per day; 

and

fd = fraction of BAs that desorbs because of increases 

in pH. 

For a pH increase from 8.15 to 8.35, fd is about 0.015 

based on the arsenic adsorption and isotopic-exchange 

experiments (figs. II–9 and II–10). The arsenic concentration 

(6.4±1.0 μmol/g) of fine sand (63 to 210 μm; U.S. Geological 

Survey, unpub. data, 1987) was used to represent arsenate sorbed 

onto ferrihydrite coatings of sediments, BAs. Using a value of 

0.5 for fine-sand bed-sediment porosity, φ, and a density, ρb, 

of 2.5 g/cm3

, a of 4 μmol/L was calculated from equation II–10. Although this estimate is much greater than the measured fluctuation in CAs of 0.21 μmol/L/d, the result suggests that 

the abundant sorbed arsenate in the bed sediments accounts for the 

cycle in CAs.

Additional Controlling Processes 

Other physical and chemical processes, such as variation 

in stream discharge and ground-water inflow, also may contribute to fluctuation of CAs. The coincident diurnal variations in 

sulfate and the injected bromide measured at site A suggest an 

increase in stream discharge from upstream sources that dilutes 

both constituents during the day rather than an increase in 

ground-water inflow along the reach at night. The magnitude 

of the fluctuation in discharge (7 to 25 percent on the basis of 

sulfate and bromide, respectively), however, is insufficient to 

result in the magnitude of the measured diurnal variation in 

CAs and is out of phase with the CAs cycle.

Reductive dissolution of ferrihydrite by photoreduction of 

iron (McKnight and others, 1988) would result in a release of 

adsorbed arsenic. The magnitude of this process was not evaluated because low ferrous-iron concentrations in surface water 

suggest that either photoreduced iron undergoes rapid reoxidation and precipitation (most arsenic sorbed during coprecipitation) or that iron photoreduction is negligible.

Solubility controls of CAs are unlikely because few 

arsenic compounds are stable in well-oxygenated water 

(Crecelius and others, 1986; Cullen and Reimer, 1989). For 

example at site A, the log degree of saturation with respect to 

calcium arsenate [Ca3(AsO4)2• 4H20] ranged from –8.8 to –9.4 

in the range of measured CAs, pH, and concentrations of dissolved calcium. These saturation indices were calculated using 

MINEQL (Westall and others, 1976) and a solubility product of 

1.26×10–19 (Naumov and others, 1974). Evaluation of aluminum 

arsenate (AlAsO4) was not possible because concentrations of 

dissolved aluminum were not determined. If the concentration 

of dissolved aluminum, however, is assumed to be in equilibrium 

with amorphous Al(OH)3 using the solubility and complexation 

constants of Lindsay and Walthall (1989), a log degree of saturation for AlAsO4 on the order of –9 is estimated. These calculated 

saturation indices, which are many orders of magnitude below 

saturation, agree with calculations by Belzile and Tessier (1990) 

and indicate a lack of solubility control on CAs. In contrast to 

Belzile and Tessier (1990), no solubility calculation for ferric 

arsenate was made because ferric arsenates are unstable with 

respect to ferrihydrite at a pH greater than 2 (Robins, 1987). 

Ferric arsenates do not form during coprecipitation at the pH 

of 8.0 to 8.5 in Whitewood Creek (Waychunas and others, 

1993).

The absence of other instream processes of sufficient magnitude to generate the measured fluctuation of CAs is evidence 

that the diurnal cycle in CAs at sites A and B are the result of 

arsenic adsorption and desorption processes on the surfaces of 

ferrihydrite on and in streambed sediments. The results of the 

laboratory experiments on the time and pH dependence of 

arsenate adsorption on synthetic 2-line ferrihydrite are consistent with the measured diurnal fluctuations of CAs.

∆CAs

bs fdBAs = ( )ρ 1 – φ bZbsAc

∆CAs

bs

∆CAs

bs
Summary 45

Summary

At the time of this study, dissolved arsenic (CAs) in the 

lower reaches of Whitewood Creek was controlled primarily 

by adsorption and coprecipitation with ferrihydrite as reducing 

ground water that contained dissolved arsenic contacted the 

atmosphere and surface water. Subsequent diurnal variations in 

CAs resulted from shifts in the adsorption and desorption equilibrium in response to a biologically induced diurnal pH cycle. 

The primary source and sink of dissolved CAs in the diurnal 

cycling was arsenic adsorption and desorption by the abundant 

ferrihydrite in bed sediments. The rate of adsorption and desorption process caused the CAs cycle to lag behind the pH cycle. 

Thus, the dynamic equilibrium of the chemical processes that 

control CAs are coupled to biological processes in the stream. 

This cycle of pH determines the importance of adsorption and 

desorption in controlling CAs. Development of an adequate 

model for arsenic transport in Whitewood Creek will require 

incorporation of adsorption kinetic terms into an advectiondispersion reaction model (for example, see eq. II–4). The 

adsorption control of CAs by ferrihydrite and the large “reservoir” of adsorbed arsenic in the streambed should act to support 

CAs even during high stream discharge.

Despite the cycle in pH at site C, the absence of a diurnal 

cycle and the lower levels of CAs are difficult to resolve with the 

present data set. In this higher gradient reach of the stream, contaminated flood-plain deposits and bed sediments with arsenic 

concentrations and molar ratios of arsenic to iron exist that are 

similar to the lower reaches. Ground-water seeps that supply 

dissolved arsenic and fresh ferrihydrite precipitates to the 

stream are not visible. Either the aging of the ferrihydrite or 

the adsorption of organics on ferrihydrite surfaces may diminish the role of sorption on ferrihydrite in the cycle of CAs by 

decreasing the availability of sorbed arsenate for desorption 

and decreasing the number of available sorption sites.

Evaluation of the diurnal pH cycles in other surface waters 

and their effect on the partitioning, cycling, and availability of 

trace elements and nutrients need to be made in order to adequately apply geochemical and biological models. For example, 

diurnal pH cycles generated by algal photosynthesis may 

increase availability of nutrients such as phosphate as well as 

toxic elements such as arsenate, selenium, and trace metals 

through the shifting of sorption equilibria. Diurnal cycles in 

orthophosphate concentration observed in Whitewood Creek 

appeared to lag the pH cycle by about 6 hours. The phase 

of the fluctuation of dissolved phosphate suggested the light 

dependence of phosphate uptake. In this study, a phosphate 

fluctuation of similar magnitude and phase also was measured; 

however, the data are not reported here because the measured 

concentrations of phosphate (0.05 to 0.15 μmol/L) had an 

uncertainty of 20 percent or greater. In both studies, the net 

change in phosphate was more than an order of magnitude 

lower than the phosphate-uptake rate predicted by the carbonfixation rate and Redfield ratios. This difference argues that 

an additional source of dissolved phosphate exists such as 

phosphate adsorbed on ferrihydrite. The competition of arsenate and phosphate for adsorption sites on ferrihydrite, greater 

uptake rates for phosphate by algae, and the factor of 4 or more 

higher CAs than phosphate all act to mask the cycle of phosphate 

that would result from pH fluctuations alone.

 Diurnal pH fluctuations should have a greater effect on 

the bioavailability of metals in more acidic systems in which 

metals are not as strongly adsorbed. The continual disturbance 

of the sorption equilibria may result in an increase in the residence time of metals in surface water and a decrease in the 

effective rate of the processes that remove reactive elements 

from a surface-water system.

Selected References

Aggett, John, and O’Brien, G.A., 1985, Detailed model for the 

mobility of arsenic in lacustrine sediments based on measurements in Lake Ohakuri: Environmental Science and Technology, v. 19, no. 3, p. 231–238.

Aggett, John, and Roberts, L.S., 1986, Insight into the mechanism of accumulation of arsenate and phosphate in hydrolake sediments by measuring the rate of dissolution with 

ethylenediaminetetracetic acid: Environmental Science and 

Technology, v. 20, no. 2, p. 183–186.

Anderson, M.A., Ferguson, J.F., and Gavis, J., 1976, Arsenate 

adsorption on amorphous aluminum hydroxide: Journal of 

Colloid and Interface Science, v. 54, no. 3, p. 391–399.

Andreae, M.O., 1978, Distribution and speciation of arsenic in 

natural waters and some marine algae: Deep-Sea Research, 

v. 25, no. 4, p. 391–402.

Apte, S.C., Howard, A.G., Morris, R.J., and McCartney, M.J., 

1986, Arsenic, antimony, and selenium speciation during 

a spring phytoplankton bloom in a closed experimental 

ecosystem: Marine Chemistry, v. 20, no. 2, p. 119–130. 

Barrow, N.J., 1983, A mechanistic model for describing the 

sorption and desorption of phosphate by soil: Journal of Soil 

Science, v. 34, no. 4, p. 733–750.

Belzile, Nelson, and Tessier, Andre, 1990, Interactions between 

arsenic and iron oxyhydroxides in lacustrine sediments: 

Geochimica et Cosmochimica Acta, v. 54, no. 1, p. 103–109.

Bencala, K.E., 1983, Simulation of solute transport in a mountain pool-and-riffle stream with a kinetic mass-transfer 

model for sorption: Water Resources Research, v. 19, no. 3, 

p. 732–738.

Bencala, K.E., McKnight, D.M., and Zellweger, G.W., 1987, 

Evaluation of natural tracers in an acidic and metal-rich 

stream: Water Resources Research, v. 23, no. 5, p. 827–836.

Bencala, K.E., McKnight, D.M., and Zellweger, G.W., 1990, 

Characterization of transport in an acidic and metal-rich 

mountain stream based on lithium tracer injection and simulations of transient storage: Water Resources Research, v. 26, 

no. 5, p. 989–1000.
46 Evaluation of the Processes Controlling Dissolved Arsenic in Whitewood Creek, South Dakota

Berner, R.A., 1980, Early diagenesis: Princeton, New Jersey, 

Princeton University Press, 241 p.

Bolan, N.S., Barrow, N.J., and Posner, A.M., 1985, Describing 

the effect of time on sorption of phosphate by iron and 

aluminum hydroxides: Journal of Soil Science, v. 36, no. 2, 

p. 187–197.

Bottero, J.-Y., Tchoubar, D., Arnaud, M., and Quienne, P., 

1991, Partial hydrolysis of ferric-nitrate salt—Structural 

investigation by dynamic light scattering and small angle 

x-ray scattering: Langmuir, v. 7., no. 7, p. 1365–1369.

Carlson, L., and Schwertmann, U., 1981, Natural ferrihydrite 

in surface deposits from Finland and their association with 

silica: Geochimica et Cosmochimica Acta, v. 45, no. 3, 

p. 421–429.

Cherry, J.A., Morel, F.M.M., Rouse, J.V., Schnoor, J.L., and 

Wolman, M.G., 1986, Hydrogeochemistry of sulfide and 

arsenic-rich tailings and alluvium along Whitewood Creek, 

South Dakota: Colorado School of Mines Mineral and 

Energy Resource Series, v. 29, no. 5, p. 1–15.

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