U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2018-5081

Prepared in cooperation with the Bureau of Land Management and the Idaho Department of 

Environmental Quality

Spatial and Temporal Trends in Selenium in the Upper 

Blackfoot River Watershed, Southeastern Idaho, 2001–16
Cover: Upper Blackfoot River, looking east across mouth of Dry Valley and 

toward the Maybe Canyon Mines, southeastern Idaho. Photograph by 

Chris Mebane, U.S. Geological Survey, June 21, 2016, during sampling for the 

seepage study.
Spatial and Temporal Trends in Selenium 

in the Upper Blackfoot River Watershed, 

Southeastern Idaho, 2001–16

By Lauren M. Zinsser, Christopher A. Mebane, Greg C. Mladenka, 

Lynn R. Van Every, and Marshall L. Williams

Prepared in cooperation with the Bureau of Land Management and 

the Idaho Department of Environmental Quality

Scientific Investigations Report 2018-5081

U.S. Department of the Interior

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

RYAN K. ZINKE, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2018

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

natural hazards, and the environment—visit https://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, visit https://store.usgs.gov.

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

Government.

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

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

Suggested citation:

Zinsser, L.M., Mebane, C.A., Mladenka, G.C., Van Every, L.R., and Williams, M.L., 2018, Spatial and temporal trends 

in selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001–16: U.S. Geological Survey Scientific 

Investigations Report 2018-5081, 37 p., https://doi.org/10.3133/sir20185081.

ISSN 2328-0328 (online)
iii

Contents

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

Introduction.....................................................................................................................................................2

Description of Study Area ...................................................................................................................2

Selenium in the Environment ..............................................................................................................5

Methods of Investigation..............................................................................................................................5

Sampling Methods at USGS Station 13063000.................................................................................5

Watershed-Wide Sampling Methods................................................................................................6

Dry Valley Reach Seepage Study Sampling Methods....................................................................7

Site Evaluation..............................................................................................................................7

Streamflow and Sampling Methods .........................................................................................7

Estimates of Uncertainty ............................................................................................................8

Other Data..............................................................................................................................................8

Statistical Interpretations....................................................................................................................9

Concentrations Versus Loads....................................................................................................9

Statistical Methods .....................................................................................................................9

Selenium in the Upper Blackfoot River Watershed .................................................................................9

Data Quality............................................................................................................................................9

Temporal Patterns and Trends in Selenium Concentrations .......................................................10

Spatial Patterns and Trends in Selenium Concentrations and Loads........................................13

Dry Valley Reach Seepage Study.....................................................................................................18

Discussion.....................................................................................................................................................24

Selenium During Runoff.....................................................................................................................24

Selenium During Baseflow................................................................................................................25

Selenium in the Blackfoot River Near Dry Valley ..........................................................................25

Future Monitoring Considerations ...................................................................................................26

Summary........................................................................................................................................................28

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

References Cited..........................................................................................................................................29

Appendix 1. Data Quality Evaluations ...................................................................................................33
iv

Figures

1. Map showing phosphate mines and monitoring stations in the upper Blackfoot

River watershed study area, southeastern, Idaho, 2001–16 .................................................3

2. Schematic diagram showing hierarchy of tributaries and phosphate mines in

relation to the Idaho Department of Environmental Quality (IDEQ) sampling 

stations on the mainstem upper Blackfoot River (open circles) and tributaries, 

southeastern Idaho ......................................................................................................................4

3. Graph showing selenium concentration (total and dissolved) and streamflow in 

the Blackfoot River above reservoir near Henry, Idaho (13063000), 2001–16...................11

4. Graphs showing annual patterns of selenium concentrations (total and dissolved)

and streamflow in the Blackfoot River above reservoir near Henry, Idaho

(13063000), calendar year 2009–16...........................................................................................12

5. Boxplots of selenium concentrations (total and dissolved) during (April and May

(runoff streamflow) and August, September, and October (baseflow) in the

Blackfoot River above reservoir near Henry, Idaho (13063000)..........................................14

6. Time series graphs showing selenium concentrations (total and dissolved) during

April and May (runoff streamflow) and August, September, and October (baseflow)

in the Blackfoot River above reservoir near Henry, Idaho (13063000)...............................15

7. Graph showing total water year precipitation in the upper Blackfoot River

watershed, southeastern, Idaho, water years 2001–16 .......................................................16

8. Graphs and boxplot showing selenium concentrations in Blackfoot River 

mainstem and tributaries from Idaho Department of Environmental Quality 

annual spring runoff sampling (2001–16)................................................................................17

9. Graphs showing cumulative streamflow and selenium load accumulation in 

the Blackfoot River and tributaries, southeastern Idaho. Measured by the 

Idaho Department of Environmental Quality during spring runoff in 2007, 2009, 

and 2011–16 .................................................................................................................................20

10. Graphs showing seepage study streamflow and selenium load accumulation in 

the Blackfoot River and tributaries, upper Blackfoot River watershed, 

southeastern, Idaho ...................................................................................................................22

Tables

1. Annual summaries of selenium concentrations (total and dissolved data included)

collected by autosampler at U.S. Geological Survey streamgage, Blackfoot River

above Reservoir near Henry, Idaho (13063000), 2013–16 .....................................................11

2. Spearman correlations between selenium concentration and streamflow at sites 

in the upper Blackfoot River watershed, southeastern, Idaho, 2001–16...........................16

3. Selenium concentrations and loads from synoptic surveys of East Mill Creek, 

Spring Creek, and the Blackfoot River, 2013–16 ...................................................................19

4. Streamflow and selenium concentrations (dissolved) and loads from the Dry Valley

reach seepage study, upper Blackfoot River watershed, southeastern, Idaho ..............23

5. Site-specific aquatic life criterion values for the upper Blackfoot River 

watershed, southeastern Idaho ..............................................................................................26

6. Summary of selenium concentrations in fish tissue reported from collections

that overlapped in time with water sampling by U.S. Geological Survey or Idaho

Department of Environmental Quality, mainstem upper Blackfoot River,

southeastern Idaho ....................................................................................................................27
v

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2) 2.590 square kilometer (km2)

Volume

cubic foot (ft3) 0.02832 cubic meter (m3)

Flow rate

foot per second (ft/s) 0.3048 meter per second (m/s)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

gallon per day (gal/d) 0.003785 cubic meter per day (m3/d)

International System of Units to U.S. customary units

Multiply By To obtain

Volume

liter (L) 33.81402 ounce, fluid (fl. oz)

liter (L) 1.057 quart (qt)

liter (L) 0.2642 gallon (gal)

Mass

kilogram (kg) 2.205 pound avoirdupois (lb)

Datums

Vertical coordinate information is referenced to the North American Vertical Datum of 1929 

(NAVD 29).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

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

Supplemental Information

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

or micrograms per liter (μg/L). Concentrations of chemical constituents in rock are given in 

milligrams per kilogram (mg/kg) and in fish tissue are given in milligrams per kilogram dry weight 

(mg/kg dry weight).

Abbreviations

BAF bioaccumulation factor

dw dry weight

EWI equal width increment

GPS Global Positioning System

IDEQ Idaho Department of Environmental Quality

MPV most probable values

NWQL National Water Quality Laboratory

RSD relative sample deviation

Se selenium

USGS U.S. Geological Survey
Spatial and Temporal Trends in Selenium in the Upper 

Blackfoot River Watershed, Southeastern Idaho, 2001–16

By Lauren M. Zinsser,1 Christopher A. Mebane,1 Greg C. Mladenka,2 Lynn R. Van Every,2 and 

Marshall L. Williams1

1U.S. Geological Survey.

2Idaho Department of Environmental Quality.

Abstract

Phosphate mining in southeastern Idaho has been 

an important economic driver for the region and State 

for over 100 years, but weathering of mining waste rock 

has also released selenium into the Blackfoot River. This 

report analyzes and presents data from three separate but 

complementary studies monitoring selenium in streams in the 

region. The U.S. Geological Survey (USGS), in cooperation 

with the Bureau of Land Management, has been collecting 

streamflow and water-quality samples year-round on the 

Blackfoot River above reservoir near Henry, Idaho, (USGS 

streamgage 13063000) since 2001. Over the same period, 

the Idaho Department of Environmental Quality (IDEQ) has 

collected streamflow and water-quality samples from the 

Blackfoot River and tributaries during spring runoff. Data 

collected from 2001 to 2012 during these two studies were 

analyzed previously. This report extends the analysis using 

new data collected through 2016. This report also presents the 

results of a joint USGS and IDEQ seepage study conducted in 

June 2016 in the Blackfoot River near Dry Valley. Although 

limited in scope, this study explored the hypothesis that 

unaccounted selenium loading (loading in excess of tributary 

inputs) in this reach could be caused by groundwater inflow.

USGS dissolved selenium concentration data from 

streamgage 13063000 on the Blackfoot River and IDEQ 

data from the mainstem and mining-affected tributaries are 

highest shortly after peak runoff and correlate with streamflow 

magnitude. Although earlier analyses indicated increasing 

selenium concentrations from 2001 to 2012, this study shows 

that runoff and baseflow dissolved selenium concentrations 

increased and then decreased during 2001–16. High median 

runoff concentrations from 2005 through 2011 are associated 

with high snowpack and streamflow. This result suggests 

that more snowmelt moving through selenium-bearing waste 

rock leads to increased instream concentrations. The time lag 

between peak runoff and then peak selenium concentrations 

suggests that selenium mobilization may occur as snowmelt 

percolates through waste rock rather than by faster surface 

runoff. However, variability in local snow accumulation and 

snowmelt conditions likely affects interannual variability in 

selenium concentrations in the mainstem Blackfoot River and 

tributaries.

In contrast to runoff selenium concentrations, 

median baseflow (August to October) dissolved selenium 

concentrations were highest from 2009 to 2013. Aquatic plant 

senescence and release of selenium is an unlikely explanation 

for this trend because plants are still growing during this time 

of year. In addition, this trend is observed during and shortly 

after the observed period of high snowpack. Thus, increased 

baseflow selenium concentrations suggest that increased 

selenium loading to alluvial groundwater may occur during 

periods of high snowmelt and manifest in later years as higher 

instream concentrations during baseflows when the majority of 

streamflow is attributable to groundwater gains.

Runoff-period streamflow and selenium loads were 

calculated for the tributaries and mainstem Blackfoot River. 

Selenium loads vary from year to year with mainstem loads 

greater than the total tributary contributions in some years 

and less than tributary contributions in other years. In general, 

East Mill Creek usually accounted for the largest proportion of 

the total Blackfoot River load, and unaccounted loads (loads 

in excess of tributary inputs) often occurred in the vicinity 

of Spring Creek and Dry Valley. The latter observation led 

the USGS and IDEQ to conduct a seepage study to further 

investigate groundwater and selenium loading to the Blackfoot 

River near Dry Valley.
2 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

The seepage study results show consistent albeit small 

unaccounted increases in streamflow and dissolved selenium 

load in the Blackfoot River near Dry Valley. Field observation 

of a spring to the north of the river and independent 

groundwater monitoring data from Dry Valley to the south of 

the river suggest that alluvial groundwater may discharge to 

the river from both sides. However, the small unaccounted 

selenium load measured in the June 2016 study relative 

to loads measured during runoff suggest that groundwater 

loading in this reach may occur primarily during runoff. 

An improved understanding of alluvial groundwater extent, 

gradient, hydraulic conductivity, and quality would aid in 

interpreting unaccounted gains and losses in selenium loads in 

the Blackfoot River.

Finally, State of Idaho selenium water-quality criteria 

have recently shifted to a hierarchical fish tissue and water 

concentration scheme. This report summarizes existing fish 

tissue and water-quality data in the mainstem and offers 

considerations for future selenium monitoring in the Blackfoot 

River.

Introduction

Phosphate mining and processing in southeastern Idaho 

has been an important economic activity since the early 1900s. 

Mining targets the Permian Phosphoria Formation that hosts 

rocks rich in phosphorus ore and selenium. In the mid-1990s, 

selenium contamination was identified as an environmental 

concern in the area following a series of livestock deaths. 

Since that time, numerous studies have been conducted 

to understand the extent, magnitude, and mechanisms 

of selenium contamination and transport throughout the 

watershed (for example, Hein, 2004).

Mebane and others (2015) compiled water-quality data 

collected by the U.S. Geological Survey (USGS) and the 

Idaho Department of Environmental Quality (IDEQ) from 

2001 through 2012 and described spatial and temporal patterns 

in selenium concentrations and loading in the Blackfoot River 

and tributaries. This analysis showed that the highest selenium 

concentrations occur during high spring runoff flows, and 

that in most years the majority of selenium loading could be 

attributed to a single tributary, East Mill Creek. However, 

Mebane and others (2015) also noted that selenium load 

increased with distance downstream in some years and that 

the increase in selenium load near Dry Valley could not be 

explained by measured tributary loads. This finding suggested 

that groundwater inflow was a potential source of selenium 

loading, which led to the Dry Valley reach seepage study.

This report presents the results of the Dry Valley reach 

seepage study and updates Mebane and others (2015) work by 

extending and analyzing the compiled water-quality data from 

2001 through 2016.

Description of Study Area

The study area comprises the upper Blackfoot River 

watershed, defined here as the part of the watershed upstream 

of the Blackfoot Reservoir (fig. 1). The Blackfoot River is 

a tributary of the Snake River. The upper Blackfoot River 

watershed spans approximately 345 mi2 and ranges in 

elevation from 6,100 to 8,790 ft with a mean elevation of 

about 7,000 ft. In this watershed, the USGS operates one 

streamgage and water-quality monitoring station at Blackfoot 

River above reservoir near Henry, Idaho (13063000). This 

station is about 4.9 mi upstream of the reservoir and captures 

about 97 percent of the upper Blackfoot River watershed by 

area. This area includes the major tributaries to the Blackfoot 

River and 13 mines; however, drainage from 1 operating 

mine, Blackfoot Bridge, occurs mostly downstream of this 

station (fig. 2). The Dry Valley reach seepage study area 

(fig. 1) is about 28 river miles upstream of the streamgage. 

This small reach is about 2 mi long and the downstream-most 

measurement site represents a watershed of about 185 mi2 

or about 54 percent of the upper Blackfoot River watershed. 

Tributaries in the watershed often originate on the ridges and 

disappear into the alluvium upon reaching the valleys without 

surficially connecting to the valley bottom streams (fig. 1).

Sedimentary rock, primarily of marine origin, underlies 

the upper Blackfoot River watershed. Major formations in the 

area include the Wells, Phosphoria and Dinwoody. Topography 

in the upper Blackfoot River watershed largely follows 

geology, with northwest-southeast trending ridges formed 

roughly along fold axes. Mining tends to occur on ridges and 

flanks because alluvium of variable depth covers ore in the 

valleys. The upper Blackfoot watershed contains 13 mines, 

of which 3 are currently active (Bureau of Land Management 

and U.S. Forest Service, 2016). Mining activity extracts ore 

from the Meade Peak member of the Phosphoria Formation. 

The Meade Peak member hosts two phosphate ore zones 

separated and stratigraphically overlain by black “waste” shale 

zones. Elevated selenium concentrations occur in both the 

waste shales and the ore zones and averages 65 milligrams 

per kilogram (mg/kg) overall, compared to the average crustal 

abundance of about 0.05 mg/kg (Herring and Grauch, 2004). 

This selenium readily weathers from the rock when exposed 

to air and water through mining activities (Herring, 2004). 
Introduction 3

tac18-1229_fig01

Lanes Creek

Spring Creek

Diamond

Creek

East M ill Creek

T1

T2

10 DV DV historic

T3

(same as

IDEQ #8)

T 2.5

State Lands Creek

Goodheart Creek

Blackfoot 

Reservoir

Slug Cre ek

Diamond Creek

Blackfoot River

Lanes Creek

Sheep Creek

Trail Creek

Dry Valley Creek

Johnson

Creek

Angus Creek

Wooley Valley Creek

Blackfoot River

Dry Valley Creek

Crow Creek

13025500

13063000

8 7

5

4

3

2

1

21

20

19

18 17

16

14 15

13

12

10

9

6

20

19

18

17

16

17a

11

k

l

c

a

e

j

f

b

g

d

h

i

e

0 5 10 MILES

0 5 10 KILOMETERS

0 1 MILE

0 0.3 MILE

111°30' 111°15' 111°00'

43°

00'

42°

45'

Base map modified from U.S. Geological Survey digital data. Stream features from the Idaho

Department of Water Resources Stream Order data, 1:100,000. 

Transverse Mercator, North American Datum of 1983.

Locations of phosphate mines areas of 2001 from Moyle and 

Kayser (2006), except for the newer Blackfoot Bridge Mine (l) 

drawn from Bureau of Land Management (2011).

Blackfoot River

watershed 

IDAHO

EXPLANATION

Phosphate mines

Upper Blackfoot River watershed boundary

USGS streamgage and water quality monitoring station (13063000)

Other USGS streamgage and water quality monitoring stations

IDEQ monitoring station 

Seepage study site

12

13025500

2

T2

k

Figure 1. Phosphate mines and monitoring stations in the upper Blackfoot River watershed study area, southeastern, Idaho, 2001–16. Phosphate 

mines in the watershed upstream of the U.S. Geological Survey (USGS) streamgage and water quality monitoring station, Blackfoot River above 

reservoir near Henry (13063000), include Ballard (a), Wooley Valley (b), Enoch Valley (c), Rasmussen Ridge (d), Lanes Creek (e), Maybe Canyon North 

(f), Maybe Canyon South (g), Champ (h), Mountain Fuel (i), Dry Valley (j), and Conda (k). Part of the Blackfoot Bridge Mine (l) reports to the Blackfoot 

River downstream of USGS station 13063000. (IDEQ, Idaho Department of Environmental Quality).
4 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

tac18-1229_fig02

2. Blackfoot River at USGS streamgage 13063000

1. Blackfoot River at China Hat

3. State Land Creek

4. Blackfoot River at Trail Creek Road

8. Blackfoot River at Slug Creek Road

12. Blackfoot River above Narrows

16. Blackfoot River at upper bridge

19.Diamond Creek above

confluence Lanes Creek

20. Lanes Creek above confluence Diamond Creek

21. Sheep Creek

5. Trail Creek

6. Slug Creek

9. Johnson Creek

11. Goodheart Creek 

Blackfoot River

7. Wooley Valley Creek 

10. Dry Valley Creek

13. Angus Creek 

(headwaters)

14. Rasmussen Creek

15. No Name

Creek

17. Spring Creek

18. East Mill Creek

Blackfoot Reservoir

(d. Rasmussen Ridge Mine)

(f. Maybe Canyon Mine North)

(c. Enoch Valley, d. Rasmussen Ridge )

(g. Maybe Canyon Mine South,

j. Dry Valley Mine)

(b. Wooley Valley) 

(a. Ballard, b. Wooley Valley) 

(h. Champ Mine,

i. Mountain Fuel Mine)

(k. CondaMine, l. Blackfoot Bridge Mine)

(e. Lanes Creek Mine)

17a. North spring near Spring Creek

Seepage study area (Dry Valley reach) 

Figure 2. Hierarchy of tributaries and phosphate mines in relation to the Idaho Department of Environmental Quality (IDEQ) sampling 

stations on the mainstem upper Blackfoot River (open circles) and tributaries, southeastern Idaho. Phosphate mines within the 

watersheds of different tributaries are shown in parentheses with letters; mine and site locations are shown in figure 1.
Methods of Investigation 5

Exposures of the Phosphoria Formation extend beyond the 

upper Blackfoot River watershed and, in some areas, are also 

associated with elevated selenium concentrations in stream 

drainages. For example, Crow Creek in southeastern Idaho and 

southwestern Wyoming receives drainage from mined areas 

just east of the upper Blackfoot River watershed. From 2012 

to 2017, selenium concentrations in water samples from lower 

Crow Creek near Fairview, Wyoming (station 13025500) 

averaged 16 micrograms per liter [μg/L, range 4.9–21.2 μg/L, 

n = 21; U.S. Geological Survey (2017b)].

The Wells Formation, which stratigraphically underlies 

the Phosphoria Formation, comprises limestone, dolomite, 

and sandstone, and hosts a regional aquifer whose flow paths 

are determined by stratigraphy and structure (Ralston and 

Williams, 1979). Alluvial and surficial deposits in the valleys 

form local, shallow aquifers. The low permeability Meade 

Peak member largely functions as an aquitard. The Meade 

Peak member is stratigraphically overlain by the Rex Chert 

and Cherty Shale members of the Phosphoria Formation and 

by the Dinwoody Formation. The Dinwoody shale and Rex 

Chert form sub-watershed scale aquifers within the upper 

Blackfoot River watershed (Ralston and Williams, 1979).

Selenium in the Environment

Previous works have shown that elevated selenium 

concentrations occur through aquatic food webs in miningaffected streams in the upper Blackfoot River watershed 

(Hamilton, 2004; Conley, 2012). Waste rock piles release 

selenium into aquatic ecosystems through drainage systems 

and subsequent periphyton uptake, and into terrestrial 

ecosystems through plant uptake (Hamilton and others, 2004). 

At low concentrations selenium is an essential micronutrient 

for animals but at marginally higher concentrations it can 

be toxic. A nonmetal, selenium behaves similarly to sulfur; 

toxicity of selenium occurs when biochemical pathways 

substitute selenium for sulfur during protein synthesis, thus 

altering their structure and function (Presser and Luoma, 

2010).

Selenium exists in four oxidation states in the 

environment: elemental selenium (Se0), selenide (Se-2), 

selenite (SeO3) and selenate (SeO4). Selenide is insoluble in 

water and elemental selenium tends to be stable in reducing 

environments. In oxygenated waters, selenium occurs 

primarily as selenate, less frequently as selenite, and least 

frequently as organic selenium (McNeal and Balistrieri, 

1989; Maher and others, 2010). Previous work on selenium 

speciation in the Blackfoot River showed that selenate 

represented a median of 80 percent of the total selenium with 

selenite making up the remainder. Selenate was most abundant 

during spring runoff conditions, whereas selenite was more 

abundant during late summer low flows (Mebane and others, 

2015). Both of these species occur in dissolved form and 

dissolved selenium generally represents more than 90 percent 

of the total selenium in the Blackfoot River system (Presser 

and others, 2004a).

Prior to 2018, selenium concentrations in the study area 

were compared to the Idaho chronic aquatic life criterion 

for selenium, which was 5 μg/L (Idaho Department of 

Environmental Quality, variously dated). In 2018, site-specific 

aquatic life criteria were established for the upper Blackfoot 

River watershed. The new criteria framework is more complex 

and is primarily defined in terms of fish tissue concentrations 

(Idaho Department of Environmental Quality, 2017). Thus, 

selenium concentrations in water in this report are described 

in the context of trends and summary statistics, but are not 

compared to any specific concentration benchmark, for there is 

none. The site-specific criteria are described in more detail in 

section, “Future Monitoring Considerations.”

Methods of Investigation

For this study, water-quality sample data and streamflow 

measurements were combined from three separate but related 

studies: (1) data collected by the USGS at Blackfoot River 

near Henry, Idaho (13063000), from 2001 to 2016; (2) data 

collected by the IDEQ in the Blackfoot River and tributaries 

from 2001 to 2016; and (3) data collected jointly by the USGS 

and IDEQ in a reach of the Blackfoot River during a June 

2016 seepage study.

Sampling Methods at USGS Station 13063000

The USGS measured streamflow and concentrations of 

selenium and other constituents at USGS station 13063000 

from 2001 through 2016. During freezing conditions 

(approximately October through mid-March), but when water 

velocity was greater than or equal to 1.5 foot per second 

(ft/s), water-quality samples were collected by equal width 

increment (EWI) methods. When water velocity was less than 

1.5 ft/s, grab samples were collected at the point of greatest 

streamflow velocity using a DH-81 sampler and Teflon®

bottle without a nozzle (U.S. Geological Survey, variously 

dated). During non-freezing conditions (approximately 
6 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

late March through September), an ISCO model 3700 

autosampler (ISCO) was used to collect samples based on 

the volume of water flowing past the streamgage. Generally, 

the ISCO collected one sample for every streamflow pulse 

(when 50 million ft3 of water has passed the streamgage); 

however, during high streamflow (spring runoff) conditions, 

the ISCO was generally programmed to collect one sample 

every other streamflow pulse. The ISCO was programmed to 

collect samples according to streamflow pulses so that more 

samples would be collected during spring runoff and fewer 

samples during summer low streamflow conditions, and the 

optimal pulse volume was determined iteratively. Autosamples 

were retrieved from the ISCO every 2–3 weeks. Samples 

were filtered using a 0.45 micrometer pore-size disposable 

capsule filter, preserved with nitric acid, and sent to the USGS 

National Water Quality Laboratory for analysis of major 

ions, selenium, and other selected trace elements. Equipment 

components that contacted samples were cleaned with 

Liquinox® detergent, soaked in a 5 percent hydrochloric acid 

solution, and rinsed with deionized water prior to use.

From 2001 to 2005, selenium concentrations 

were measured by inductively coupled plasma-mass 

spectrometry, which has a method detection limit of about 

0.1 μg/L (Garbarino, 1999). From 2006 to 2016, selenium 

concentrations were measured by collision/reaction cell 

inductively coupled plasma-mass spectrometry, which has 

a method detection limit of about 0.03 μg/L (Garbarino and 

others, 2006). Previous work has indicated that most selenium 

in the Blackfoot River is dissolved (Presser and others, 2004a; 

Mebane and others, 2015); therefore, for this study, dissolved 

selenium samples were primarily measured. However, a 

limited number of total selenium analyses were completed 

from 2012 to 2014 and these data (n = 22) were combined 

with the dissolved selenium results (n = 481) for the analyses 

presented in this report. Where both dissolved and total sample 

selenium analyses were available for a single date (n = 3), 

dissolved analyses were preferentially selected for analysis. 

Finally, where replicate samples were available for a single 

date (n = 219 total on 85 individual dates), only the parent 

sample was selected for statistical analysis.

Data quality of the water-quality analyses for this 

study was evaluated using several types of quality control 

samples (Mueller and others, 2015). First, the USGS National 

Water Quality Laboratory performance was examined 

through regular testing of inorganic blind samples and 

through semiannual interlaboratory testing of standard 

reference samples. Second, ambient blanks were used to 

evaluate atmospheric cross-contamination of samples in the 

autosampler housing. Third, equipment blanks were used to 

assess the effectiveness of equipment cleaning procedures. 

Fourth, grab samples collected concurrently with autosamples 

(concurrent replicates) were used to determine if autosample 

composition was affected by the autosampler pump intake 

mechanism. Fifth, grab sample replicates were collected 

to determine variability of grab sampling. Lastly, EWI 

samples collected concurrently with autosamples (concurrent 

replicates) were used to evaluate how well autosamples 

represented the entire river cross section. The quality control 

samples were collected according to the protocols detailed by 

the U.S. Geological Survey (variously dated).

Watershed-Wide Sampling Methods

In contrast to the USGS, whose sampling efforts focused 

on a single, watershed-integrating site sampled year-round, 

the IDEQ sampled 21 sites on the Blackfoot River mainstem 

and tributaries (fig. 2) annually during spring runoff conditions 

from 2001 to 2016. Field crews followed USGS sampling 

and processing methods (U.S. Geological Survey, variously 

dated). Water-quality samples were collected using width- and 

depth-integrated sampling methods; these included using 

depth-integrating samplers from bridgeboards or long rods 

from bridges when streams were not wadable and using 

handheld depth-integrating samplers in wadable conditions. 

Samples were subsequently stored in polyethylene containers 

and preserved with nitric acid. The IDEQ targeted 4-day 

sampling periods, during which time three samples from each 

site were collected and composited. This strategy allowed 

direct comparison to the pre-2018 State of Idaho chronic 

selenium standard which was expressed as a 4-day average 

concentration. Equipment that contacted water-quality samples 

was washed with Alconox® detergent and triple-rinsed with 

deionized water and then rinsed with sample water between 

successive samples. The IDEQ samples were processed by 

ACZ Laboratories (Steamboat Springs, Colorado) from 2001 

to 2008, and by SVL Analytical (Kellogg, Idaho) from 2009 

to 2016. Both laboratories analyzed total selenium either 

by Standard Method 3114B, hydride generation and atomic 

absorption (Eaton and others, 2005) or U.S. Environmental 

Protection Agency method 6020A (U.S. Environmental 

Protection Agency, 1998). Both laboratories reported detection 

limits averaging 2 μg/L but ranging from 1 to 5 μg/L.
Methods of Investigation 7

In addition to regular samples, quality control samples 

including split replicates, ambient blanks, and equipment 

blanks were collected concurrently with field samples to assess 

data quality. Split replicate samples were collected as a single 

composite sample collected in the field and subsequently split 

into two subsamples for separate analysis. Ambient blanks 

were collected by pouring deionized water directly into sample 

bottles in the field. Equipment blanks were collected by 

processing deionized water through the sampling equipment 

after cleaning.

In smaller streams, IDEQ measured instantaneous 

streamflow using a Marsh-McBirney model 2000 portable 

electromagnetic streamflow meter and a top-setting wading 

rod. In larger streams, an acoustic Doppler current profiler was 

used to measure streamflow. Streamflow was measured on day 

one and day four of the sampling period; mean streamflow for 

this period was calculated by averaging the two measurements. 

Low streamflows were estimated visually at the threshold of 

less than 0.25 cubic feet per second (ft3/s); streamflow was 

measured at sites with flows higher than this threshold.

Dry Valley Reach Seepage Study Sampling 

Methods

Site Evaluation

In June 2016, USGS and IDEQ jointly conducted a 

seepage study in a targeted reach of the Blackfoot River 

between the Narrows and the confluence with Dry Valley 

Creek (fig. 1). Seepage study refers to a methodology in which 

streamflow is measured at multiple locations in a stream, and 

streamflow gains or losses between locations are inferred to 

indicate groundwater exchange (Riggs, 1972). A longitudinal 

profile of water-quality parameters along the reach was 

collected as a preliminary site evaluation on June 20, 2016, 

to determine the placement of streamflow and water-quality 

sampling sites. A global position system (GPS) unit and a 

water-quality sonde measuring specific conductance, pH, 

and dissolved oxygen, were mounted on a kayak to identify 

locations along the stream reach where changing water-quality 

conditions might indicate potential groundwater inflow.

Based on this preliminary evaluation, three transects 

were established. T1 was at the upstream end of the reach, just 

downstream of the Narrows; T2 was about two-thirds of the 

way downstream in the reach, where the Blackfoot River is 

near Blackfoot River Road; and T3 was at the downstream end 

of the reach, below the confluence of Dry Valley Creek and 

the Slug Creek Road bridge (fig. 1). Streamflow measurements 

and water-quality samples were collected at these sites on 

June 21, 22, and 23. Additionally, a fourth site, T2.5, was 

approximately halfway between sites T2 and T3 and upstream 

of the railroad bridge; streamflow and water-quality samples 

were collected at T2.5 site on June 22 and 23. Samples and 

streamflow measurements were also collected at the mouth of 

Dry Valley Creek (site DV, fig. 1) on all three days, and at the 

mouth of the historical Dry Valley Creek channel on June 21. 

The current Dry Valley Creek channel is not the original 

channel configuration; Dry Valley Creek was straightened 

along the north margin of the railroad spur in the mid-1960s. 

The historical Dry Valley Creek channel is on the southern 

margin of the railroad spur and is no longer surficially 

connected to the Dry Valley Creek drainage.

Streamflow and Sampling Methods

Samples were collected, processed and analyzed for 

selenium at each site in accordance with the EWI methods 

previously described for USGS station 13063000 and the 

methods described in U.S. Geological Survey (variously 

dated). Split replicates were collected and sent to USGS 

National Water Quality Laboratory and SVL Analytical to 

compare analytical performance between laboratories used 

by USGS and IDEQ, respectively (Mueller and others, 

2015). Streamflow measurements were taken in accordance 

with USGS Office of Surface Water protocols, policies, and 

published guidance (Oberg and others, 2005; Sauer and 

Turnipseed, 2010).

The YSI SonTek® FlowTracker handheld acoustic 

Doppler velocimeters and top-setting wading rods were used 

to make streamflow measurements. Geographic coordinates 

provided for the measurement sites were based on a handheld 

GPS, using the horizontal coordinate information of the North 

American Datum of 1983. Streamflow measurements were 

completed at each site on each day, excepting the historical 

channel of Dry Valley Creek. The streamflow at this site was 

low (0.045 ft3/s on June 21) and stable, and therefore was 

estimated at the same streamflow (0.045 ft3/s) on subsequent 

days. Temporary stage gages were installed at the upstream 

and downstream ends of the reach. Pressure transducers 

were suspended in PVC housing and secured to a fixed point 

and collocated with staff gages. These data were collected 

to provide a relative sense of streamflow stability during 

the study duration but were not used to measure absolute 

streamflow rates.
8 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

During the seepage study, streamflow measurements 

were made at sites along the mainstem of the river and at 

each significant inflow; no outflows were seen or measured 

along the study reach. The increase or decrease in the 

streamflow between mainstem measurement sites that 

could not be attributed to inflows or outflows (and ignoring 

evapotranspiration losses, which were expected to be small) 

represented an estimate of the net flow interchange between 

surface water and groundwater. The mass balance equation 

used for determining this estimate is as follows (Simonds and 

Sinclair, 2002):

Net flow gain or loss = Q T d − − Q D u + , (1)

where 

Qd is the streamflow measured at the downstream 

end of the reach, in cubic feet per second;

Qu is the streamflow measured at the upstream end 

of the reach, in cubic feet per second;

T is the sum of tributary inflows, in cubic feet per 

second, and

D is the sum of the diversion outflows, in cubic 

feet per second.

Thus, the equation estimated the net change, in cubic feet 

per second, in the streamflow through a reach, where positive 

values indicated a gaining reach and negative values indicated 

a losing reach.

Estimates of Uncertainty

The FlowTracker acoustic Doppler velocimeter internally 

calculates an uncertainty value through a statistical technique 

developed by the USGS (U.S. Geological Survey, 2017a). 

Because net gain or loss is calculated from two or more 

measurements, the uncertainty from each measurement must 

be propagated to determine the uncertainty inherent in the 

net gain or loss. The propagated uncertainty was calculated 

according to the following formula (Wheeler and Eddy-Miller, 

2005):

( ) ( ) ( ) 22 2 sa b n = ± + ± ...+ ± , (2)

where 

s is the error propagated from all estimated 

individual errors, and

a, b, ..., n are the estimated errors for the streamflow 

measurement at each site.

Other Data

In addition to data collected by the USGS and IDEQ, 

some data collected by other entities are used in this report. 

Precipitation data, including water year total precipitation and 

snow water equivalent, was obtained from the Somsen Ranch 

and Slug Creek Divide SNOTEL stations which are operated 

by the U.S. Department of Agriculture, Natural Resources 

Conservation Service (Natural Resources Conservation 

Service, 2017a; 2017b). The Somsen Ranch station is near 

the upper northeastern bound of the upper Blackfoot River 

watershed at an elevation of about 6,800 ft. The Slug Creek 

Divide station is about midway along the southern margin 

of the watershed at an elevation of about 7,225 ft. In the 

Blackfoot River watershed, which averages 7,000 ft, elevation 

strongly influences precipitation and snow accumulation. 

Therefore, precipitation data from both stations were averaged 

for analysis to better represent the overall conditions of the 

watershed.

Precipitation indices were calculated at each station 

then averaged together. Total precipitation was defined as the 

cumulative precipitation total for each water year. Total snow 

water equivalent was defined as the maximum cumulative 

snow water equivalent value for each water year. Runoff 

precipitation was the sum of precipitation occurring during 

April and May. Therefore, if the maximum cumulative snow 

water equivalent occurred in April or May, it is possible that 

some precipitation may be double counted for a given year as 

both snow water equivalent and runoff precipitation. However, 

this amount of precipitation is expected to be small because 

maximum cumulative snow water equivalent occurs during 

March in most years.

The IDEQ tributary data for Dry Valley Creek were 

supplemented with data from Whetstone Associates (2017). 

Whetstone Associates collected more samples from Dry Valley 

Creek from 2001 to 2016 than IDEQ, and including these data 

allowed a greater range of concentrations and conditions to be 

included in the analysis. These data were collected consistent 

with the methods used by IDEQ as previously described 

(Whetstone Associates, 2017).
Selenium in the Upper Blackfoot River Watershed 9

Statistical Interpretations

Concentrations Versus Loads

In this report, selenium is reported as concentrations and 

loads; both are useful for analyzing data in different ways. 

Concentrations (mass per unit volume) are directly measured 

and are useful for assessing water-quality based standard and 

criteria. Loads (mass per unit time) are useful for assessing 

sources and sinks of selenium on a watershed-wide basis 

as well as for evaluating the mass transport of selenium to 

downstream waters. Selenium loads were calculated using 

point-in-time concentrations and streamflows. Daily selenium 

loads, in kilograms per day (kg/d), were estimated according 

to the following formula:

Load kg

d Q C 



 



 = × × 2. , 447 (3)

where 

Q is streamflow, in ft3/s,

C is concentration, in mg/L, and 2.447 is a unit 

conversion constant for calculating daily 

load.

For daily load calculations made at the USGS 

station 13063000, loads were calculated using point-intime concentrations and daily average streamflow. For 

watershed wide and seepage load calculations, point-in-time 

concentrations and measured instantaneous streamflows 

were used to calculate instantaneous loads. Instantaneous 

loads were then extrapolated to a daily load by assuming the 

streamflow and chemistry remained constant through the day.

Statistical Methods

Statistical methods used to analyze the water-quality 

data are primarily descriptive. Methods used included 

data graphing, descriptions of centrality and variance, and 

analytical approaches to dampen seasonal influences and 

outlier data including locally weighted scatterplot smoothing 

(LOESS; Cleveland and others, 1992). Spearman’s rho 

was used to describe correlations between streamflow and 

concentration; because it is nonparametric, Spearman’s rho 

is useful for detecting monotonic correlations between two 

variables without requiring them to be linear or transformed. 

Non-linear techniques are imperative for evaluating 

streamflow and datasets of selenium concentration, which 

can have small sample sizes (for some tributaries), be rightskewed, and often exhibit a log normal data distribution.

Because USGS station 13063000 was operated only 

seasonally since 2006, MOVE.1 methods (Hirsch, 1982; 

Granato, 2009) were used to create an estimated, or synthetic, 

daily streamflow record for times when the streamgage was 

not operating. MOVE.1 is a maintenance of variance method 

that uses a nearby streamgage with a complete streamflow 

record (in this case, USGS station 13027500, Salt River above 

reservoir near Etna, Wyoming) to estimate a complete record 

at a station of interest (in this case, USGS station 13063000). 

Although a complete streamflow record was useful for some 

analyses, daily average measurement values were used 

whenever they were available and estimated streamflow data 

were used only in the absence of daily values.

Selenium in the Upper Blackfoot River 

Watershed

The results presented in this report focus on selenium 

although multiple other water-quality constituents also have 

been measured and are available through the National Water 

Information System website, https://waterdata.usgs.gov/nwis, 

(U.S. Geological Survey, 2017b). Note that water-quality 

concentrations are reported herein with the significant figures 

provided by the laboratory. Thus, concentrations are consistent 

with reported analytical precision (which varied by laboratory 

and over time) but significant figures are not necessarily the 

same for all results.

Data Quality

The data quality evaluations are discussed here in 

brief; appendix 1 contains a more detailed discussion of 

these results. Evaluations of USGS data quality showed no 

evidence of field or laboratory contamination of samples, with 

no selenium detections in any of 15 ambient and equipment 

blanks collected between 2013 and 2016. Analysis of the 

concurrent replicate samples collected from 2013 to 2016 

by autosampler, EWI, and grab methods showed similar 

concentrations indicating that the autosampler adequately 

represented the river cross section concentrations. The median 

relative sample deviation (RSD) was 2.8 percent, ranging 

from 0 to only 6.9 percent in the 13 concurrent replicate pairs 

(appendix 1).

Equipment and ambient blanks collected by IDEQ 

similarly showed no evidence of field contamination of 

samples, with no selenium detections in any of the 19 

equipment and ambient blanks collected between 2001 and 

2016. Split replicate sample results were generally in good 

agreement with RSD less than 20 percent for selenium in 21 of 

23 split replicate pairs collected from 2001 to 2016. One split 

replicate pair from upper Angus Creek and one pair from the 

Blackfoot River above Narrows exceeded 50 percent RSD in 

2004 and 2005 respectively.
10 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

The inherent accuracy and bias of the laboratory analyses 

was evaluated through examining internal inorganic blind 

sample results and interlaboratory standard reference sample 

evaluations conducted by the USGS Bureau of Quality 

Systems and by Environment Canada. The evaluation showed 

a persistent low bias for selenium concentrations less than 

about 0.5 μg/L, and a slight high bias in concentrations 

greater than about 30 μg/L. Within the range of selenium 

concentrations most relevant to this study (about 1–10 μg/L), 

the results of performance testing were linear and within 

acceptable bounds. A more detailed analysis of these results is 

presented in appendix 1.

Specific to this project, six pairs of split replicate 

samples were collected during the seepage study and analyzed 

separately for selenium by the USGS National Water Quality 

Laboratory and by the laboratory used to analyze the IDEQ 

samples (SVL Analytical). The agreement between the 

National Water Quality Laboratory and SVL Analytical results 

was good, with a median RSD of 4.1 percent and a range of 

1.3–12.3 percent for the split samples (appendix 1). Overall, 

the data quality results indicate that the data collected for 

this study accurately characterize selenium concentrations 

in the study area and are thus suitable for evaluations in the 

following sections.

Temporal Patterns and Trends in Selenium 

Concentrations

Selenium was detected in each of the 635 water 

samples collected by the USGS at station 13063000 

between 2001 and 2016 and concentrations ranged from a 

minimum of 0.5 μg/L to a maximum of 13.8 μg/L with a 

median concentration of 2.7 μg/L (U.S. Geological Survey, 

2017b). In general, selenium concentration correlated with 

streamflow (Spearman’s rho = 0.605, p = 0, n = 500). More 

specifically, selenium concentrations tended to be highest 

during and shortly following peak streamflow, decreased 

during the hydrograph recession, and remained relatively 

stable and low during late summer and early autumn baseflow 

conditions (fig. 3). During runoff conditions (defined herein 

as streamflows in April and May), selenium concentrations 

ranged from 1 to 13.8 μg/L and had a median concentration 

of 4.1 μg/L (n = 308). During baseflow conditions (defined 

herein as streamflows in August, September and October), 

selenium concentrations ranged from 0.5 μg/L to 3 μg/L, with 

a median concentration of 1.5 μg/L (n = 66). In comparison, 

IDEQ reported a median total selenium concentration of 

0.14 μg/L in 34 samples collected as part of a statewide survey 

of large rivers (Essig, 2010).

Mebane and others (2015) compared 2001 to 2012 

water-quality data to established State of Idaho and federal 

water-quality criteria at that time. For the years added to the 

record (2013–16) and included in this report, various summary 

statistics were calculated, including arithmetic averages, 

minimums, maximums, time-weighted averages (calculated 

for March 1 through September 30, approximately when the 

autosampler operated), and maximum 4- and 30-day moving 

average selenium concentrations (table 1). Each year, the 

single measured maximum selenium concentration was equal 

to or higher than the 4-day moving average and the 4-day 

moving average was higher than the 30-day moving average. 

This outcome is expected, given that selenium concentrations 

tend to peak and decline relatively quickly in concert with 

peak streamflow in the Blackfoot River, and longer averaging 

periods will include more samples collected outside of the 

peak streamflow times (fig. 3).

As reported in Mebane and others (2015), the relationship 

between selenium concentration and streamflow is complex 

(fig. 4). The highest selenium concentrations generally lagged 

peak streamflow by as little as 2 days to as long as 36 days, 

with a median lag in the peak selenium concentration of 

15 days after peak streamflow. However, there were some 

exceptions to this generality. For example, in 2015, the peak 

selenium concentration of 5.6 μg/L occurred 25 days after 

an early April secondary peak in streamflow of 300 ft3/s, but 

before the annual peak streamflow of 418 ft3/s in late May.

In general, the relative magnitude of the annual peak 

selenium concentration correlated to the relative magnitude 

of the annual peak streamflow. For instance, high runoff 

streamflows (peak around 1,200 ft3/s) corresponded with 

high selenium concentrations (12 μg/L) in 2009, and low 

runoff streamflows (peak around 500 ft3/s) corresponded 

with low selenium concentrations (4 μg/L) in 2012 (fig. 4). 

However, there were exceptions to this general relationship. 

For example, a relatively high peak streamflow in 2011 

(about 1,600 ft3/s) occurred with a relatively low peak 

selenium concentration (about 9 μg/L). Conversely, a 

relatively low peak streamflow of about 400 ft3/s in 2013 

occurred with a peak selenium concentration of 13.8 μg/L, 

the highest concentration measured at USGS streamgage 

13063000 (fig. 4).
Selenium in the Upper Blackfoot River Watershed 11

tac18-1229_fig03

Water year

Streamflow, in cubic feet per second

0

200

400

600

800

1,000

1,200

1,400

1,600

2000 2002 2004 2006 2008 2010 2012 2014 2001 2003 2005 2007 2009 2011 2013 2015 2016 2017

0

2

4

6

8

10

12

14

Selenium concentration, in micrograms per liter

Measured streamflow

Estimated streamflow

Dissolved selenium

Total selenium

EXPLANATION

Figure 3. Selenium concentration (total and dissolved) and streamflow in the Blackfoot River above reservoir 

near Henry, Idaho (13063000), 2001–16. Water year labels are centered on May 1.

Table 1. Annual summaries of selenium concentrations (total and dissolved data included) collected by autosampler at U.S. Geological 

Survey streamgage, Blackfoot River above Reservoir near Henry, Idaho (13063000), 2013–16.

[Original data are available from U.S. Geological Survey (2017b). Abbreviations: Se, selenium; μg/L, microgram per liter]

Water Year

2013 2014 2015 2016

Minimum Se (μg/L) 1.6 1.2 0.84 1.1

Mean Se (μg/L) 4.2 2.4 2.2 2.7

Maximum Se (μg/L) 13.8 6.3 5.6 6.5

Maximum 4-day moving average Se (μg/L) 12.9 6.3 5.3 6.5

Maximum 30-day moving average Se (μg/L) 7.3 4.6 3.7 4.9

March 1–September 30 time-weighted average selenium (μg/L) 2.9 2.1 1.8 2.1

Number of samples per year 37 33 38 41
12 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

tac18-1229_fig04

2014

2015

2016

2013

2012

2011

2010

Jan. Feb. Mar.Apr. MayJuneJuly Aug. Sept.Oct. Nov.Dec.

Mar. Apr. May June July Aug. Sept. Oct. Nov.

Mar. Apr. May June July Aug. Sept. Oct. Nov.

Mar. Apr. May June July Aug. Sept. Oct. Nov.

0

200

400

600

800

1,000

1,200

1,400

1,600

0

200

400

600

800

1,000

1,200

1,400

1,600

0

200

400

600

800

1,000

1,200

1,400

1,600

0

200

400

600

800

1,000

1,200

1,400

1,600

2009

0

2

4

6

8

10

12

14

Jan. Feb. Mar.Apr. MayJuneJuly Aug. Sept.Oct. Nov.Dec.

0

200

400

600

800

1,000

1,200

1,400

1,600

0

2

4

6

8

10

12

14

Jan. Feb. Mar.Apr. MayJuneJuly Aug. Sept.Oct. Nov.Dec.

0

200

400

600

800

1,000

1,200

1,400

1,600

0

2

4

6

8

10

12

14

Jan. Feb. Mar.Apr. MayJuneJuly Aug. Sept.Oct. Nov.Dec.

0

200

400

600

800

1,000

1,200

1,400

1,600

0

2

4

6

8

10

12

14

Jan. Feb. Mar.Apr. MayJuneJuly Aug. Sept.Oct. Nov.Dec.

0

200

400

600

800

1,000

1,200

1,400

1,600

0

2

4

6

8

10

12

14

Selenium concentration, in micrograms per liter

Daily mean streamflow, in cubic feet per second

EXPLANATION

Streamflow

Total selenium

Dissolved selenium

Figure 4. Annual patterns of selenium concentrations (total and dissolved) and streamflow in the Blackfoot River above 

reservoir near Henry, Idaho (13063000), calendar year 2009–16.
Selenium in the Upper Blackfoot River Watershed 13

From 2005 to 2011 median runoff selenium 

concentrations were higher than the long-term runoff median 

(4.1 μg/L) in every year except 2007 (fig. 5). The LOESS 

regression on the runoff selenium concentrations over this 

period similarly indicated increasing concentrations from 2001 

to 2008 and decreasing concentrations from 2009 to 2016 

(fig. 6). The period of high concentrations in the middle of the 

study generally coincided with high snowpack years (that is, 

higher than the 30-year median total snow water equivalent 

calculated for 1981–2010, fig. 7). The 2006, 2008, 2009, and 

2011 water years all had higher than median total snow water 

equivalent (fig. 7) and corresponded with higher than median 

selenium concentrations (fig. 5). However, the association of 

higher selenium with higher snow water equivalent and runoff 

does not hold for all years. For example, 2007 and 2010 water 

years had below median snow water equivalent, but relatively 

high maximum selenium concentrations. This may indicate 

that both the current year snowpack and the snowpack of 

the previous year may be important for the mobilization of 

selenium within the Blackfoot River watershed. Similarly, 

2014 had higher than median snowpack but relatively low 

selenium concentrations, possibly due to low snowpack in the 

preceding years. In contrast, 2012 and 2013 had relatively low 

snowpack but the 2013 selenium concentrations included the 

highest measured during this study at USGS station 13063000 

(fig. 1).

Although runoff selenium concentrations were elevated 

from 2005 to 2011, median baseflow selenium concentrations 

were higher than the long-term baseflow median (1.5 μg/L) 

from 2009 to 2013 (fig. 5). The LOESS regression on baseflow 

selenium concentrations indicated increasing concentrations 

from 2001 to 2012 and decreasing concentrations from 2013 

to 2016 (fig. 6). This contrasts with runoff flows where the 

LOESS trend inflection point was 2008 (fig. 6). Notably, 

both the baseflow and runoff LOESS regressions indicate 

that the apparent monotonic increasing trend in selenium 

concentrations from 2001 to 2012, as noted by Mebane and 

others (2015), changed direction in the extended analysis 

period (2001–16).

Spatial Patterns and Trends in Selenium 

Concentrations and Loads

The USGS sampling at station 13063000 provides 

temporal data for selenium concentrations in the Blackfoot 

River, whereas the IDEQ annual runoff sampling (2001–16), 

provides spatial data for selenium concentrations throughout 

the mainstem and tributaries in the Blackfoot River watershed. 

Starting near the upstream part of the watershed at Sheep 

Creek (figs. 1 and 2), selenium concentrations in the IDEQ 

dataset ranged from non-detected at <1.0 to 9 μg/L and were 

consistently about 1 μg/L in Lanes Creek and Diamond Creek 

(fig. 7; Mladenka and others, 2018). Selenium concentrations 

in East Mill Creek were consistently high, ranging from 212 

to 870 μg/L, and in Spring Creek (which receives streamflow 

from East Mill Creek) selenium concentrations ranged from 

12.3 to 69 μg/L. Downstream of the Spring Creek confluence, 

the Blackfoot River had selenium concentrations ranging from 

3 to 8.7 μg/L; selenium in the Blackfoot River remained at 

about this concentration in the remainder of the downstream 

sites despite the addition of streamflow from several tributaries 

(fig. 8).

The downstream tributaries Rasmussen Creek, Angus 

Creek, Goodheart Creek, Dry Valley Creek, Wooley Creek 

and Slug Creek, each showed high variability in selenium 

concentrations. Rasmussen Creek ranged from less than 1.0 

to 14.2 μg/L, and Angus Creek ranged from 0.46 to 39 μg/L. 

Dry Valley Creek and Goodheart Creek tended to have high, 

although still variable, selenium concentrations ranging from 

4 to 119 μg/L and 2 to 91.6 μg/L, respectively. Selenium 

concentrations in Wooley Valley Creek and Slug Creek were 

low, ranging from less than 1.0 to 12.77 μg/L and less than 1.0 

to 7.95 μg/L, respectively (fig. 8).

Many of the highest concentrations of selenium in both 

the mainstem and tributary sites were measured in years with 

high streamflows and high snowpack, particularly 2009 and 

2011 (figs. 3, 7, and 9). However, the mainstem sites and 

Spring Creek also had high concentrations of selenium in 

2013, which was a relatively low streamflow year and had 

neither a high snow pack nor high precipitation. Like USGS 

station 13063000, many of the IDEQ tributary and mainstem 

sites have statistically significant (Spearman’s rho, p-value 

< 0.10) correlations between streamflow and selenium 

concentration (table 2). These include sites on Rasmussen 

Creek, Dry Valley Creek, Goodheart Creek, Sheep Creek, 

East Mill Creek, State Land Creek, Wooley Valley Creek and 

Lanes Creek. Each of these creeks have upstream mining 

disturbance. The strength and shape of these relationships 

varies between tributaries (table 2), suggesting that factors 

such as the type and location of mine waste piles, amount of 

snow accumulation, and nature of water movement through a 

site likely influence how and to what extent runoff mobilizes 

selenium.
14 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

tac18-1229_fig05

0

2

4

6

8

10

12

14

Selenium concentration, in micrograms per liter

2001 2004 2006 2008 2010 2012 2014 2016

0

1

2

3

4

Selenium concentration, in micrograms per liter

Water year

Water year

A. Runoff streamflow

B. Baseflow

2001 2003 2005 2007 2009 2011 2013 2015

2003 2005 2007 2013

2014 2016

2009 2011 2015

2002 2004 2006 2008 2010 2012

EXPLANATION 

75

Maximum

Minimum

th percentile

50th percentile

(median)

25th percentile

Interquartile

range 

Figure 5. Selenium concentrations (total and dissolved) during (A) April and May (runoff streamflow) and (B) August, September, 

and October (baseflow) in the Blackfoot River above reservoir near Henry, Idaho (13063000). Box extent represents the interquartile 

range with the median shown and whiskers representing the range of measured values. Dashed line represents the 2001–16 

seasonal median (4.1 micrograms per liter [μg/L] in A, 1.5 μg/L in B). Water year 2002 missing from (B) baseflow data because no 

data are available.
Selenium in the Upper Blackfoot River Watershed 15

tac18-1229_fig06

0

2

4

6

8

10

12

14

Selenium concentration, in micrograms per liter

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Selenium concentration, in micrograms per liter

Water year

A. Runoff streamflow

B. Baseflow

0

2

4

6

8

10

12

14

Selenium concentration

LOESS trend

EXPLANATION

Figure 6. Selenium concentrations (total and dissolved) during (A) April and May (runoff streamflow) and (B) August, 

September, and October (baseflow) in the Blackfoot River above reservoir near Henry, Idaho (13063000). The LOESS trends are 

also shown. Water year labels are centered on May 1.
16 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

tac18-1229_fig07

2001 2003 2005 2007 2009 2011 2013 2015 2002 2004 2006 2008 2010 2012 2014 2016

Water year

Total precipitation, in inches

0

10

20

30

40

50

EXPLANATION

Snow-water equivalent

April−May precipitation

Remainder of water year precipitation

1981−2010 median total precipation

1981−2010 median snow-water 

equivalent

Figure 7. Total water year precipitation in the upper Blackfoot River watershed, southeastern, Idaho, water years 2001–16. 

Data are averaged from the Slug Creek Divide and Somsen Ranch SNOTEL stations. The height of each water year bar 

represents the total precipitation (in inches) for the year.

Table 2. Spearman correlations between selenium concentration and streamflow at sites in the upper Blackfoot River watershed, 

southeastern, Idaho, 2001–16.

[Bold and italic indicate statistical significance at p-value < 0.1. Abbreviation: n, count of samples used for correlation]

Site No. Site name Spearman’s rho p-value n

1 Blackfoot River at China Hat 0.50 0.27 7

2 Blackfoot River at USGS Streamgage 0.44 0.09 16

3 State Land Creek 0.99 0.00 6

4 Blackfoot River at Trail Creek Road 0.68 0.01 13

5 Trail Creek 0.05 0.88 12

6 Slug Creek 0.27 0.40 12

7 Wooley Valley Creek 0.79 0.00 12

8 Blackfoot River at Slug Creek Road 0.38 0.14 16

9 Johnson Creek 0.43 0.35 7

10 Dry Valley Creek 0.59 0.03 14

11 Goodheart Creek 0.85 0.00 13

12 Blackfoot River above Narrows 0.37 0.16 16

13 Angus Creek -0.31 0.26 15

14 Rasmussen Creek 0.71 0.00 14

15 No Name Creek -0.20 0.78 5

16 Blackfoot River at upper bridge 0.36 0.17 16

17 Spring Creek 0.04 0.88 16

18 East Mill Creek 0.69 0.01 15

19 Diamond Creek above confluence with Lanes Creek 0.35 0.50 6

20 Lanes Creek above confluence with Diamond Creek 0.53 0.06 13

21 Sheep Creek 0.75 0.01 12

13063000 USGS station 13063000 0.61 0.00 500
Selenium in the Upper Blackfoot River Watershed 17

tac18-1229_fig08

18. East Mill Creek

20. Lanes Creek 2. Blackfoot Riverat USGS gage

11. Goodheart Creek 6. Slug Creek

8. Blackfoot River

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

2000 2005 2010 2015 0.1

1

10

100

1,000

10. Dry Valley Creek

0.1

1

10

100

1,000

12. Blackfoot River

17. Spring Creek

Selenium concentration, in micrograms per liter

Selenium concentration,

in micrograms per liter

Selenium concentration,

in micrograms per liter

21. Sheep Creek20. Lanes Creek19. Diamond Creek18. East Mill Creek17. Spring Creek16. Blackfoot River at upper bridge14. Rasmussen Creek13. Angus Creek12. Blackfoot River above Narrows11. Goodheart Creek10. Dry Valley Creek8. Blackfoot River at Slug Creek Road7. Wooley Valley Creek6. Slug Creek4. Blackfoot River at Trail Creek Road2. Blackfoot River at USGS site 130630001. Blackfoot River at China Hat

75

Maximum

Mean

50th percentile

(median)

Selenium concentration

Minimum

th percentile

25th percentile

Interquartile

range 

EXPLANATION 

Figure 8. Selenium concentrations in Blackfoot River mainstem (grey-shaded boxes and black line graphs) and tributaries (blue boxes and blue 

line graphs) from Idaho Department of Environmental Quality annual spring runoff sampling (2001–16). Box extent represents the interquartile 

range with the median shown and whiskers representing the range of measured values; individual sample concentrations are shown as red dots. 

Censored data are displayed at the non-detect value. Arrows depict tributary streamflow into other tributaries or into the mainstem Blackfoot River. 

Mainstem and tributary site numbers (as shown in table 2 and figures 1 and 2) are labeled. 
18 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

However, several sites on creeks with upstream mining 

disturbance do not show a significant correlation between 

selenium concentration and streamflow; these include sites on 

Spring Creek, Angus Creek and Slug Creek (table 2). Each 

of these creeks is affected by conditions that may confound 

simple correlation between selenium concentration and 

streamflow. For example, Spring Creek is largely sourced 

from by alluvial groundwater; mining-impacted Goodheart 

Creek only connects to Slug Creek in some years; and the 

sampling location on Angus Creek shifted from an upstream to 

a downstream location after 2010. Nonetheless, the correlation 

between selenium concentration and streamflow in most of 

the mining-affected tributaries in the upper Blackfoot River 

watershed suggests that the amount of water moving through 

the mining-affected landscape strongly affects the annual 

variation in instream selenium concentrations.

The anomalously high selenium concentrations in both 

the USGS and IDEQ samples collected during May 2013 

were consistent with independent data collected by AECOM 

Technical Services, Inc. (2015a, 2015b) and Arcadis U.S., Inc. 

(2016) from synoptic sampling of the East Mill Creek- Spring 

Creek-Blackfoot River area (table 3), which receives drainage 

from the Maybe Canyon Mine North (fig. 2). Selenium 

concentrations measured near the headwaters of East Mill 

Creek were not markedly different in 2013 as compared to 

2014 through 2016, with concentrations of about 2,200 to 

2,600 μg/L. Similarly, selenium loads in the headwaters of 

East Mill Creek in 2013 were not unusually high (table 3). 

However, 2013 selenium concentrations in lower Spring Creek 

and the Blackfoot River were among the highest measured 

at those sites: 120 and 15 μg/L, respectively (table 3). These 

independent results support the conclusion that the East Mill 

Creek drainage was the source of the high 2013 concentrations 

and loads in the Blackfoot River, although the specific 

hydrologic connection is unclear.

Evaluating the accumulation of streamflow and 

selenium load in the Blackfoot River and tributaries provided 

another means to understand this system. The Blackfoot 

River generally accrued groundwater discharge (gaining 

stream) between the headwaters and the downstream site 

at USGS station 13063000 (site 2; fig. 9). In most years, 

tributary inflows cannot account for the gains in streamflow 

in the Blackfoot River, indicating that groundwater inflows 

contributed to total streamflow. In most years, substantive nontributary (inferred groundwater) flows were gained between 

sites 16 and 12 (Blackfoot River at upper bridge and Blackfoot 

River above Narrows), and between sites 12 and 8 (Blackfoot 

River above Narrows and Blackfoot River at Slug Creek 

Road; fig. 2). However, in 2013 the Blackfoot River gained 

less streamflow between sites 16 and 12 than it gained from 

Angus Creek (site 13), indicating a streamflow loss in this 

reach (fig. 9).

The selenium load accumulations in the Blackfoot River 

varied from year to year (fig. 9). In some years, the selenium 

load in the mainstem was less than the cumulative tributary 

load (for example, 2013). In other years, the selenium load 

in the mainstem was higher than the cumulative tributary 

load (for example, 2012, 2015 and 2016) or the load in the 

mainstem showed unaccounted gains larger than the tributary 

loads in some reaches, and unaccounted losses in other 

reaches (for example, 2007, 2009, 2011, and 2014; fig. 9). 

Nonetheless, several general consistencies are apparent. First, 

East Mill Creek (site 17) generally accounted for the largest 

proportion of the total Blackfoot River selenium load (Mebane 

and others, 2015). Second, unaccounted (non-tributary) 

selenium loads frequently, but not always, occurred between 

the headwater sites (Diamond and Lanes Creeks, sites 19 and 

20) and Blackfoot River at the upper bridge (site 16), and 

between Blackfoot River at Narrows (site 12) and Blackfoot 

River at Slug Creek Road (site 8; fig. 9). Mebane and others 

(2015) noted the unaccounted load increase between sites 16 

and 8; this observation, paired with the wide range of selenium 

concentrations measured in Dry Valley Creek, led to the Dry 

Valley reach seepage study.

Dry Valley Reach Seepage Study

During the Dry Valley reach seepage study in June 

2016, streamflow decreased slightly over the 3 days of study, 

but remained relatively stable during each set of synoptic 

measurements. On each day, streamflow increased from the 

upstream-most site (T1) to the downstream-most site (T3) 

by between 7.4 and 9.0 ft3/s (fig. 10; table 4) and the sum of 

the tributary inflows (Dry Valley Creek and historical Dry 

Valley Creek) ranged from 1.3 to 1.4 ft3/s. Therefore, the 

average net unaccounted streamflow increase (that is, the 

inferred groundwater) in the Blackfoot River from T1 to T3 

ranged from 6.0±3.0 to 7.7±3.1 ft3/s, where the plus or minus 

streamflow represents the propagated measurement uncertainty 

through the entire reach.

Based on the streamflow measurements at the mainstem 

sites, most of the streamflow was gained between T2 and T2.5. 

The reach between T2.5 and T3 showed a slight streamflow 

loss (about 2 ft3/s) but this amount of loss is within the 

propagated measurement uncertainty (about ±3 ft3/s) and 

therefore is considered neither a net gain nor loss (table 4).

Selenium concentrations in the Blackfoot River also 

increased consistently from T1 to T3 on each of the three 

days, with an average of 1.52 μg/L at T1 to 1.89 μg/L at T3 

(table 4). The selenium concentration in Dry Valley Creek 

averaged 1.43 μg/L, and the single sample collected from 

historical Dry Valley Creek was 0.28 μg/L. Although the 

upstream to downstream increase in selenium concentration 
Selenium in the Upper Blackfoot River Watershed 19

Table 3. Selenium concentrations and loads from synoptic surveys of East Mill Creek, Spring Creek, and the Blackfoot River, 2013–16.

[Data sources: AECOM Technical Services, Inc. (2015a, 2015b) and Arcadis (2016). East Mill Creek (middle reach): Similar location to Idaho Department 

of Environmental Quality (IDEQ) site 18 (East Mill Creek). Spring Creek, near the mouth: Similar location to IDEQ site 17 (Spring Creek). Abbreviations:

μg/L, microgram per liter; kg/d, kilogram per day; <, less than]

Selenium concentrations (μg/L)

Synoptic 

survey date

East Mill Creek 

(headwaters)

East Mill Creek 

(middle reach)

Spring Creek, 

near the mouth

Blackfoot River 

downstream of 

Spring Creek

Blackfoot River 

upstream of Spring 

Creek

High streamflow samplings

05-10-16 2,600 402 18 11.1 0.40

04-28-15 2,500 390 23 157.0 0.55

05-09-14 2,500 370 31 4.3 0.63

05-14-13 2,200 760 120 15.0 0.51

Low streamflow samplings

09-22-16 2,200 32 4.0 1.3 <0.2

09-28-15 2,400 42 3.7 115.5 <0.2

09-24-14 1,900 33 2.6 18.6 <0.25

09-29-13 1,800 36 5.1 1.8 <0.12

Selenium loads (kg/d)

Synoptic 

survey date

East Mill Creek 

(headwaters)

East Mill Creek 

(middle reach)

Spring Creek, 

near the mouth

Blackfoot River 

downstream of 

Spring Creek

Blackfoot River 

upstream of Spring 

Creek

Blackfoot River, 

increase upstream 

to downstream of 

Spring Creek

05-10-16 6.35 3.54 1.69 6.1 0.39 5.71

04-28-15 3.67 2.96 1.11 119.4 0.23 19.15

05-09-14 6.06 4.89 2.12 2.3 0.30 2.02

05-14-13 4.20 8.37 5.87 4.4 0.29 4.07

09-22-16 0.01 0.09 0.13 0.18 0.03 0.15

09-28-15 0.05 0.16 0.15 12.20 0.05 2.15

09-24-14 0.02 0.11 0.06 10.93 0.02 0.90

09-29-13 0.10 0.11 0.10 0.15 0.02 0.14

1Selenium concentrations are considered high biased because samples were collected immediately downstream of a contaminated tributary confluence 

(IDEQ site 17a), which has selenium concentrations ranging from at least 19 to 307 μg/L; the samples are therefore not directly comparable with the fully 

mixed, width and depth integrated samples collected by IDEQ at site 16.

between T1 and T3 was relatively small, it was consistent on 

all three days. Paired with the reach increase in streamflow, 

the selenium load increased from an average of 0.372 kg/d at 

T1 to 0.501 kg/d at T3 (table 4 and fig. 10). No measurable 

selenium load was contributed by historical Dry Valley 

Creek and only 0.005 kg/d, on average, was contributed from 

Dry Valley Creek. Thus, on average, about 0.125 kg/d of 

unaccounted selenium accumulated in the Blackfoot River 

between T1 and T3.

Assuming that all the unaccounted streamflow and 

selenium load between T1 and T3 is derived from groundwater 

(eqn. 3, in section, “Statistical Interpretations”) can be used to 

estimate the average groundwater concentration of selenium. 

Assuming an average unaccounted groundwater inflow of 

6.8 ft3/s (table 4), the average selenium concentration in 

groundwater contributed to the Blackfoot River between 

T1 and T3 would be 7.50 μg/L. However, this calculation 

is sensitive to streamflow measurement uncertainty; if the 

measurement uncertainty is used to bound upper and lower 

rates of groundwater entering the Blackfoot River at 10.0 

and 3.6 ft3/s, respectively, the average groundwater selenium 

concentration could range from 5.12 μg/L to 14.0 μg/L. This 

also assumes that all of the unaccounted streamflow and 

selenium load is derived from groundwater; alternate sources 

are discussed in later sections of this report.
20 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

tac18-1229_fig09a

2

4

12 8

1

6

7 5 17a 13 10 6

17

2

8 4

12

16

5

7 6

10

13

17a

17

2

4

8

12

16

5

10 6 7

13

17a

17

2012 2012

2 4

8

12

16

5

7 6

10

13

17a

17

2

8 4

16 12

7 5 6

10

13 17 17a

2 4

8

12

16

5

6 7

10 13

17

17a

2011 2011

2 4

8

12

16

7 5

6

10

17a 13

17

-5 0 5 10 15 20 25 30 35 -5 0 5 10 15 20 25 30 35

-5 0 5 10 15 20 25 30 35 -5 0 5 10 15 20 25 30 35

-5 0 5 10 15 20 25 30 35

0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35

0 5 10 15 20 25 30 35

60

70

80

90

100

110

120

130

140

150

0.0

0.5

1.0

1.5

2.0

2.5

5

6

7

8

9

0

1

2

3

4

10

8

10

12

14

16

0

2

4

6

18

0.0

0.5

1.0

1.5

2.0

300

280

320

340

360

380

400

420

440

460

480

450

500

550

600

650

700

750

800

100

120

140

160

180

200

2

4 8 12

16

5 6 7

13 10

17

17a

2009 2009

2007 2007

Streamflow, in cubic feet per second

Selenium load, in kilograms per day

Cumulative streamflow accumulations Cumulative selenium load accumulations

River miles downstream of confluence, approximate

Mainstem site and site No.

Tributary site and site No.

EXPLANATION 2

5

A

Figure 9. Cumulative streamflow and selenium load accumulation in the Blackfoot River and tributaries, southeastern Idaho. 

Measured by the Idaho Department of Environmental Quality during spring runoff in 2007, 2009, and 2011–16. Mainstem and 

tributary site numbers (as shown in table 2 and figures 1 and 2) are labeled. Note the vertical axis varies between plots. Distance 0 

represents the confluence of Diamond and Lanes Creek, which marks the start of the Blackfoot River.
Selenium in the Upper Blackfoot River Watershed 21

tac18-1229_fig09b

4 2

8

12 16

10 6 7 5

17a 13

17

2

4 8

12 16 10 6 7 5

13 17a

17

2

4

8

12

16

5

10 6 7 17a 13

17

2

4

8

12

16

5

6 7 10

13 17a

17

2

4

8

12

16

6 7 5

13 10 17a

17

2

4 8

12

16 5

6 7 10 13

17a

17

2

4 8

12

16

5

6 7 10

13

17a

17

2016 2016

2015 2015

2

4

8

12

16

6 7 5

10 13

17a

17

2014 2014

2013 2013

-5 0 5 10 15 20 25 30 35 -5 0 5 10 15 20 25 30 35

-5 0 5 10 15 20 25 30 35

-5 0 5 10 15 20 25 30 35

-5 0 5 10 15 20 25 30 35

140

160

180

200

220

240

260

160

180

200

200

140

160

180

280

280

320

360

200

240

300

340

380

220

260

400

0.0

1.5

2.5

3.5

4.5

1.0

0.5

2.0

3.0

4.0

5.0

5.5

0.0

1.5

2.5

3.5

4.5

1.0

0.5

2.0

3.0

4.0

5.0

0.5

1.5

2.5

0.0

1.0

2.0

3.0

3.5

0.5

1.5

0.0

1.0

2.0

2.5

-5 0 5 10 15 20 25 30 35

-5 0 5 10 15 20 25 30 35

0 5 10 15 20 25 30 35

Streamflow, in cubic feet per second

Selenium load, in kilograms per day

Cumulative streamflow accumulations Cumulative selenium load accumulations

River miles downstream of confluence, approximate

B

Figure 9.—Continued
22 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

tac18-1229_fig10

0

20

40

60

80

100

120

Streamflow, in cubic feet per second

A

B

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

Distance downstream, in miles

Selenium load, in kilograms per day

Day 1 main stem

Day 2 main stem

Day 3 main stem

Day 1 tributaries

Day 2 tributaries

Day 3 tributaries

Streamflow measurement 

uncertainty

EXPLANATION

Figure 10. Seepage study streamflow (A) and selenium load (B) accumulation in the Blackfoot River and tributaries, upper 

Blackfoot River watershed, southeastern, Idaho. Where Day 1 and Day 2 tributary symbols are not visible, values were equal to, and 

obscured by, Day 3 values. Sample sites are shown in figure 1. Error bars in A represent streamflow measurement uncertainty.
Selenium in the Upper Blackfoot River Watershed 23

Table 4. Streamflow and selenium concentrations (dissolved) and loads from the Dry Valley reach seepage study, upper Blackfoot 

River watershed, southeastern, Idaho.

[Abbreviations: mi, mile; ft3/s, cubic foot per second; kg/d, kilogram per day; μg/L, microgram per liter; –, no data]

Station ID Site No. and 

name

Distance 

(mi)

Mainstem 

streamflow 

(ft3/s)

Tributary 

streamflow 

(ft3/s)

Net 

unaccounted 

gain or loss 

(ft3/s)

Measurement 

uncertainty 

(ft3/s)

Dissolved 

selenium 

(μg/L)

Dissolved 

selenium 

load 

(kg/d)

Day 1—06-21-16

4247361112214 T1 - Upper site 0 103 – – 2.3 1.55 0.391

4247171112308 T2 - Middle site 1.44 103 – – 2.2 1.95 0.491

4247101112310 T2.5 - Middle site 1.66 – – – – – –

4247071112310 Dry Valley Creek 1.74 – 1.32 – 0.10 1.38 0.004

424703111231000 Dry Valley Creek, 

historical

1.80 – 0.05 – 0.01 0.28 0.000

13062857 T3 - Lower site 1.89 111 – – 2.4 1.92 0.522

Net Reach Change – – 8.0 1.4 6.6 3.3 – 0.126

Day 2—06-22-16

4247361112214 T1 - Upper site 0 98.0 – – 2.1 1.54 0.369

4247171112308 T2 - Middle site 1.44 98.6 – – 2.2 1.85 0.446

4247101112310 T2.5 - Middle site 1.66 109 – – 2.6 1.87 0.499

4247071112310 Dry Valley Creek 1.74 – 1.23 – 0.09 1.42 0.004

424703111231000 Dry Valley Creek, 

historical

1.80 – – – – – –

13062857 T3 - Lower site 1.89 107 – – 2.4 1.86 0.487

Net Reach Change – – 9.0 1.3 7.7 3.1 – 0.113

Day 3—06-23-16

4247361112214 T1 - Upper site 0 99.6 – – 2.1 1.46 0.356

4247171112308 T2 - Middle site 1.44 102 – – 2.1 1.90 0.474

4247101112310 T2.5 - Middle site 1.66 109 – – 2.6 1.88 0.501

4247071112310 Dry Valley Creek 1.74 – 1.34 – 0.06 1.48 0.005

424703111231000 Dry Valley Creek, 

historical

1.80 – – – – – –

13062857 T3 - Lower site 1.89 107 – – 2.1 1.89 0.495

Net Reach Change – – 7.4 1.4 6.0 3.0 – 0.134

Average

4247361112214 T1 - Upper site 0 100 – – – 1.52 0.372

4247171112308 T2 - Middle site 1.44 101 – – – 1.90 0.471

4247101112310 T2.5 - Middle site 1.66 – – – – – –

4247071112310 Dry Valley Creek 1.74 – 1.30 – – 1.43 0.005

424703111231000 Dry Valley Creek, 

historical

1.80 – – – – – –

13062857 T3 - Lower site 1.89 108 – – – 1.89 0.501

Net Reach Change – – 8.1 1.3 6.8 3.2 – 0.125
24 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

Discussion

Selenium During Runoff

The relations between streamflow, snowpack, and 

selenium concentration in the mainstem Blackfoot River and 

mining-affected tributaries leads to a conceptual understanding 

of selenium transport in the watershed. The magnitude 

of selenium concentration during runoff is related to the 

streamflow magnitude (fig. 3), and in this mountainous region 

the size and shape of the streamflow hydrograph is driven by 

the depth of snowpack and the timing of runoff. A series of 

high snowpack years occurred in 2006, 2008, 2009, and 2011 

(fig. 7). These years align with a period of higher than median 

selenium concentrations during runoff flows (fig. 5), and 

the lower snowpack years prior to 2006 and following 2011 

coincide with the lower than median selenium concentrations 

in runoff flows (fig. 5). Conceptually, this suggests that the 

amount of snowmelt moving through the landscape in a given 

year influences the concentration of selenium in the Blackfoot 

River and tributaries.

Contrary to fluvial systems in which sediment-bound 

contaminants are primarily transported during sediment 

mobilization near peak snowmelt runoff, selenium transport 

in the Blackfoot River is dominated by dissolved rather than 

particulate selenium (Presser and others, 2004b) and peak 

concentrations lag behind peak streamflow (fig. 4). As posited 

by Mebane and others (2015), this lag could arise as snowmelt 

percolates through cross-valley fill mine dumps, effectively 

taking a more tortuous path to streams as compared to runoff 

directly into streams, but still passing through the dumps 

relatively efficiently (Sidle and others, 1994; Amacher and 

others, 1995; Mars and Crowley, 2003). Alternately, if East 

Mill Creek largely drives selenium concentrations in the 

Blackfoot River (fig. 8), then annual snowmelt timing on the 

higher elevation and north-facing Maybe Canyon Mine North 

dump (which largely sources East Mill Creek) may be an 

important contributor to the observed selenium lag.

The hypothesis that snowmelt percolation through 

waste rock controls selenium transport is also geochemically 

plausible. High selenium concentrations measured during 

runoff conditions are similar to the “first flush” effect seen in 

other mining affected areas where the first high streamflow 

following a dry period causes the dissolution of soluble metal 

salts and subsequent high metal concentrations in streams 

(Nordstrom, 2009). Selenium in the Meade Peak member 

occurs primarily in association with sulfide minerals (such 

as, pyrite and sphalerite) and in elemental form (Grauch and 

others, 2004; Perkins and Foster, 2004; Stillings and Amacher, 

2010) but readily oxidizes to more mobile forms when 

exposed to air and water (Herring, 2004; Knudsen and Gunter, 

2004; Stillings and Amacher, 2010). Although selenium 

salts have not been directly identified, zinc sulfate salts have 

been measured and observed to occur with selenium (of 

indeterminate form) on newly mined rock faces (Grauch and 

others, 2004), and Perkins and Foster (2004) detected selenate 

associated with acid-soluble oxyhydroxides in weathered 

Meade Peak rocks.

With respect to selenium mobilization, field data from 

a Wooley Valley waste rock dump paired with laboratory 

data showed that selenium concentrations following initial 

wetting were highest and subsequently decreased to a lower, 

steady-state concentration. These kinetics data indicate that 

water passing through waste rock dissolves and mobilizes 

readily available forms of selenium (selenate), and then slowly 

oxidizes less soluble selenium (elemental or sulfide mineral 

bound selenium) over time (Stillings and Amacher, 2010). In 

the absence of enough water to move the slowly oxidizing 

selenium, this oxidized selenium may build up over dry 

periods and then be mobilized in high concentrations with the 

next rain or snowmelt event. Thus, the high concentrations 

of selenium measured in the Blackfoot River and tributaries 

following peak streamflows is geochemically consistent with 

the mobilization of soluble selenium via snowmelt moving 

through waste rock.

High snowpack years could increase selenium transport 

to the hydrologic system in several ways. Larger amounts 

of snowmelt passing through cross-valley fill dumps allows 

for more water-mineral contact, subsequently mobilizing 

more available selenium during spring runoff. Additionally, 

increased and prolonged snowmelt runoff percolating through 

the dumps could release more of the less soluble selenium 

in the rocks over time (Stillings and Amacher, 2010). This 

oxidized selenium may be released later in the season, 

resulting in higher selenium concentrations during baseflow in 

the Blackfoot River and tributaries; it may move into shallow 

alluvial groundwater (Hay and others, 2016); or it may be 

“primed” to be released during the following spring when 

the next year’s snowmelt percolates through the cross-valley 

fill dumps (Nordstrom, 2009). Such a priming mechanism is 

congruent with the relatively high selenium concentrations 

seen in unremarkable snowmelt years that followed high 

snowmelt years (for example, 2007 and 2010).

As an aside, the kinetics work completed by Stillings and 

Amacher (2010), and previously described here, used field 

data collected in 2002, 2006, and 2008, which were the only 

years during 2002-08 that the seep at the base of the Wooley 

Valley waste rock dump flowed enough to collect samples 

and measure streamflow. Thus, there is evidence that this 

mechanism of selenium release and transport in the upper 

Blackfoot River watershed may primarily occur under certain 

snowpack and precipitation conditions, which may account for 

some of the variability in year-to-year selenium concentrations 

in the Blackfoot River and tributaries.

Some of the annual variability of instream selenium 

concentrations likely results from local variability in 

snowpack accumulation and snowmelt conditions. Total snow 

water equivalent is being used here as a coarse indicator of 

the amount of water moving through the landscape during the 

runoff period. Although there is a strong correlation between 
Discussion 25

snow water equivalent and streamflow, the manner in which 

runoff occurs and therefore the amount of water moving 

through the landscape, is likely to be dependent on multiple 

factors. These factors may include the timing and rate of 

snowmelt, the spatial distribution of snow on the landscape, 

the occurrence of rainfall during snowmelt, variations in air 

temperature, the antecedent soil conditions (including water 

content and temperature), and the water table of the shallow 

alluvial groundwater. All of these factors can affect local water 

movement and likely contribute to some of the variability in 

the selenium concentrations in both the mainstem Blackfoot 

River and tributaries.

Selenium During Baseflow

Whereas median selenium runoff concentrations seemed 

to peak during 2008 and 2009 and then decrease, the LOESS 

trend for higher concentrations during baseflow lagged with a 

peak in 2013 before decreasing (fig. 6). Because baseflows in 

the Blackfoot River are primarily sustained by groundwater 

inflow, the increase in baseflow selenium concentrations until 

2013 could indicate increasing concentrations of selenium 

in groundwater. When selenium is weathered in waste rock 

dumps, it can be mobilized and percolate into groundwater 

where it may remain in solution at elevated concentrations 

under high oxygen conditions or be attenuated through 

microbially mediated reductive precipitation under low 

oxygen conditions (Hay and others, 2016). Under oxygenated 

conditions, shallow alluvial groundwater with elevated 

selenium concentrations may discharge to tributaries of the 

Blackfoot River or into the mainstem itself. Unfortunately, 

there is limited information available on the shape of the 

alluvial water table and thus the direction of groundwater 

movement on a watershed-wide scale.

However, selenium moves through the environment in 

a variety of complex ways that could also affect instream 

baseflow concentrations. For example, selenium is readily 

taken up by phytoplankton and bacteria, which in turn may 

pass selenium up the food chain or release selenium through 

senescence of aquatic plants (Chapman and others, 2009). 

Senescence might be a reasonable explanation for small 

increases measured during late autumn and early winter 

(November–December) but seems less plausible during 

August, September, and October when plant growth is likely 

still occurring. For instance, in a low-gradient, groundwaterfed eastern Idaho River, aquatic plant beds reach their annual 

biomass maxima in September, and their annual biomass 

minima in February (Angradi, 1991).

Similarly, stream sediments and exchange of water 

through the hyporheic zone can also serve as either sources 

or sinks of selenium. Oram and others (2010) showed that 

anoxic conditions deeper within the hyporheic zone promoted 

reprecipitation and sequestration of selenium from surface 

water in East Mill Creek. Alternately, Oram and others (2008) 

proposed that the oxygenated, approximately neutral pH 

Blackfoot River may dissolve selenium-substituted pyrite in 

sediments near the water-sediment interface. Such sediments 

could be a long-term source of dissolved selenium when 

river concentrations of selenium remain less than 1.6 μg/L 

(Oram and others, 2010). It is possible that increased 

hyporheic exchange of water and selenium associated with 

high baseflows in the middle of the study period promoted 

increased dissolution of selenium. However, the increased 

baseflow selenium concentrations measured from 2009 to 

2013 averaged about 2 μg/L (fig. 5B) which suggests selenium 

loading beyond pyrite dissolution occurred during this time. 

Thus, baseflow selenium concentrations may be controlled by 

alluvial groundwater selenium concentrations and discharge to 

the Blackfoot River, but a more comprehensive understanding 

of the connectivity and selenium concentrations in the alluvial 

aquifer would aid interpretation.

Selenium in the Blackfoot River Near Dry Valley

Loading analysis of the mainstem Blackfoot River and 

tributaries from 2001 to 2016 showed multiple years with 

unaccounted mainstem loading of selenium (in excess of the 

tributary contributions) in the vicinity of Spring Creek and 

Dry Valley. This unaccounted loading motivated the limited 

scope evaluation of seepage in the Dry Valley. During the 

June 2016 study, small but consistent unaccounted increases 

in streamflow and selenium load were measured in the Dry 

Valley reach of the Blackfoot River (fig. 10).

These unaccounted flows and load may be derived 

from discharge of alluvial groundwater from the northern 

or southern sides of the river. Selenium loading to alluvial 

groundwater is known to occur within Dry Valley (Hay and 

others, 2016; Whetstone Associates, 2017), located south 

of the river. Additionally, a small seep on the northern side 

of the river near T2 was identified during the study. The 

selenium concentration in the seep (2.44 μg/L) was somewhat 

higher than the concentrations in Dry Valley Creek or the 

Blackfoot River, although the estimated discharge from the 

seep was only about 0.03 ft3/s. Therefore, although the seep 

itself does not contribute appreciably to the selenium load 

in the Blackfoot River, it may be indicative of selenium 

concentrations in alluvial groundwater north of the river.

Alternately, the variations in selenium concentration 

in the Blackfoot River through the Dry Valley reach may be 

unrelated to variations in streamflow. As previously discussed, 

selenium can be taken up and released by phytoplankton and 

bacteria and can be released or sequestered by sediment in 

the hyporheic zone. However, increases in streamflow and 

selenium loading have been measured during multiple runoff 

events (fig. 9). Increases in streamflow and selenium loading 

(0.125 kg/d) to the Dry Valley reach during the inferred 

groundwater study were lower than the increases observed 

during the 2016 runoff streamflow and load study (0.35 kg/d), 

and substantially lower than the average runoff selenium 

loading (2.17 kg/d) to the reach estimated from multiple years 
26 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

of IDEQ sampling. This suggests that most of the selenium 

loading to the Dry Valley reach of the Blackfoot River 

probably occurs during or near runoff.

From a mechanistic perspective, the water table in the 

shallow alluvial aquifer increases in concert with spring 

snowmelt (Whetstone Associates, 2017), which may result in 

an increase in the gradient between the shallow groundwater 

and Blackfoot River. With an increased gradient, water 

percolating through waste rock in the valleys north and 

south of the river may be transported more quickly and in 

greater quantity towards the Blackfoot River. This transport 

mechanism seems to be a plausible means for loading 

in the Dry Valley reach during runoff. Nonetheless, an 

improved understanding of the alluvial aquifer, including 

extent, hydraulic conductivity, and selenium concentration, 

in the vicinity of the Dry Valley reach would help in the 

interpretation of selenium loading to the Blackfoot River.

Future Monitoring Considerations

Environmental planning, monitoring, modeling, and 

assessment of phosphate mining in Idaho has long relied 

upon the former aquatic life criterion of 5 μg/L in water as 

a performance benchmark. As of March 28, 2018, the Idaho 

Department of Environmental Quality (2017) set the sitespecific selenium criterion for the upper Blackfoot River 

watershed to a scheme based upon fish tissue concentrations 

and water column values (section 287.01; reproduced in 

table 5). This recent adoption of revised State of Idaho 

selenium criteria replaced a fixed water concentration-based 

criterion with a comparatively complex framework of fish 

tissue and water selenium criteria and introduces additional 

monitoring considerations.

The criterion is defined in a four-part priority scheme 

where, if sufficient data are available, the egg-ovary 

concentrations supersede all other measures, and the wholebody or muscle fish tissue supersede the water column values. 

Whole-body and muscle tissue values have equal priority. For 

comparison with criterion, tissue samples from at least five 

fish of the same species are either blended into a composite 

sample before analysis or averaged from individual analyses. 

In the absence of steady-state condition fish tissue values, 

water column values are intended to be the applicable criterion 

element (Idaho Department of Environmental Quality, 2017, 

section 287.01). More generally, the Idaho rules specify in 

section 287 that site-specific water column values are based 

on dissolved total selenium using either the mechanistic 

modeling method or the bioaccumulation factor (BAF) method 

described in the national selenium criteria document (U.S. 

Environmental Protection Agency, 2016).

To give context to this new criterion, existing resident 

fish tissue samples for the mainstem upper Blackfoot River 

that were collected during the period in which the USGS 

and IDEQ conducted selenium water sampling are compiled 

in table 6 (Idaho Department of Fish and Game, 2018). The 

data, which are mostly whole-body tissue samples, show that 

selenium residues in fish tissue were close to the criterion 

values for the upper Blackfoot River for most samples and 

times. Average concentrations in sculpin were slightly higher 

than in trout or dace, which might indicate the restricted 

motility of sculpin. However, differences between the averages 

were not large and the variabilities among samples from the 

same species were greater than differences between species 

averages. Across all samplings, cutthroat trout (Oncorhynchus 

clarkii bouvieri) averaged 11.5 (± standard deviation of 2.8), 

dace 13.0 (± 1.8), and sculpin 15.9 (± 5.0), mg/kg dry weight, 

respectively (from table 6).

Table 5. Site-specific aquatic life criterion values for the upper Blackfoot River watershed, southeastern Idaho.

[From Idaho Department of Environmental Quality (variously dated). Abbreviations: mg, milligram; kg, kilogram; dw, dry weight; μg, microgram; L, liter]

Chronic Short-term, ST

Egg-ovary (mg/kg dw) Fish Tissue (mg/kg dw) Water column Water column

Whole body Muscle (filet) Dissolved Se, μg/L Dissolved Se, μg/L

24.5 12.5 12.8 WQC=Tissuecriterion/BAF ST=(WQC-Cbkgrnd(1-fint))/fint

Where: WQC are site-specific lotic water quality criterion element values (30-day averages), Tissuecriterion is either the egg/ovary, whole-body, or muscle 

fish tissue criteria elements, BAF is the bioaccumulation factor derived by dividing the site-specific field collected samples of fish tissue (whole-body) by sitespecific field collected samples of water, Cbkgrnd is the average background dissolved selenium concentration, and fint is the fraction of any 30-day period during 

which elevated selenium concentrations occur, constrained to be ≥ 0.033 (one day)
Discussion 27

Table 6. Summary of selenium concentrations in fish tissue reported from collections that overlapped in time with water sampling by U.S. Geological Survey or Idaho Department of Environmental Quality, mainstem upper Blackfoot River, southeastern Idaho.[All fish samples were reported as being taken from whole-body fish, except those from Essig (2010) which were from muscle. Data from May 2009 sampling targeting upstream migrating adfluvial fish that had only recently entered the Blackfoot River from the Blackfoot Reservoir were not included in the table. Average Se concentrations in water for 30 days closest to sampling were calculated from USGS data collected at site 2, except for the 8/12/2008 samples for which both the fish and water values were from Essig (2010). Fish collection location sites: Idaho Department of Environmental Quality site numbers as shown in figure 1. Data source: 1, Hamilton and Buhl (2005); 2, Idaho Department of Fish and Game (2018); 3, Essig (2010). Abbreviations: mg, milligram; kg, kilogram; dw, dry weight; BAF, bioaccumulation factor; μg, microgram; L, liter; Se, selenium; –, not applicable]

Sampling 

date Species

Average 

Se in fish 

tissue 

(mg/kg dry 

weight)

Standard

deviation

Number 

of 

samples 

(tissue)

30-day 

average Se 

in water near 

the time of 

fish sampling 

(μg/L)

Number 

of 

samples 

(water)

March 1–

September 30 

time-weighted 

average Se in 

water 

(μg/L)

Bioaccumulation 

factor 

(BAF)

Fish 

collection 

location 

sites

Applicable fishtissue water quality criterion 

concentration 

(mg/kg, dry 

weight)

Data 

source

05-2001 Cutthroat trout (Oncorhynchus 

clarkii bouvieri)

12.2 – 1 4.2 13 2.5 2.9 2 12.5 1

05-2001 Sculpin (Cottus spp.) 12.3 – 1 4.2 13 2.5 2.9 2 12.5 105-2001 Longnose dace (Rhinichthys 

cataractae)

10.9 – 1 4.2 13 2.5 2.6 2 12.5 1

05-2001 Redside shiner (Richardsonius 

balteatus)

13.6 – 1 4.2 13 2.5 3.3 2 12.5 1

07-25-06 Rainbow trout (O. mykiss) 9.7 2.1 4 1.3 1 2.2 7.4 1 12.5 210-25-07 Sculpin 22.9 3.8 10 0.87 1 2.1 26.3 16 12.5 210-11-07 Cutthroat trout 16.2 1.9 10 0.87 1 2.1 18.6 16 12.5 208-12-08 Cutthroat trout 14.7 Composite 2 1.6 1 2.0 9.4 2 12.8 308-12-08 1Utah sucker (Catostomus 

ardens)

12.3 Composite 5 1.6 1 2.0 7.8 2 12.8 3

08-12-08 1Utah sucker (split duplicate 

sample)

10.5 Composite 5 1.6 1 2.0 6.7 2 12.8 3

10-13-09 Speckled dace (Rhinichthys 

osculus)

14.0 0.6 5 2.2 1 2.8 6.4 16 12.5 2

10-13-09 Paiute sculpin (Cottus beldingi) 12.2 0.8 5 2.2 1 2.8 5.5 16 12.5 210-13-09 Cutthroat trout 10.5 1.0 10 2.2 1 2.8 4.8 16 12.5 210-13-09 Speckled dace 14.0 2.2 5 2.2 1 2.8 6.4 16 12.5 210-13-09 Paiute sculpin 16.2 2.3 5 2.2 1 2.8 7.4 16 12.5 207-21-10 Cutthroat trout 10.6 1.6 10 2.4 7 2.5 4.3 16 12.5 207-19-11 Cutthroat trout 13.0 2.6 10 2.2 4 3.0 5.9 16 12.5 207-19-11 Cutthroat trout 11.1 3.0 9 2.2 4 3.0 5.1 16 12.5 208-29-12 Cutthroat trout 7.0 2.2 9 2.0 3 2.5 3.6 16 12.5 2

1The 08-12-08 values for Utah sucker were listed as Bridgelip sucker in the source, but are considered most likely to have been Utah sucker based on the known distributions of sucker species in Idaho 

(Wallace and Zaroban, 2013).
28 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

Except for the 2001 samples collected during May, all 

other fish samples listed in table 6 were collected during 

August to October baseflow conditions. Corresponding 

selenium concentrations in water during those times were 

relatively low, ranging from 0.9 to 2.4 μg/L. Selenium samples 

in cutthroat trout, the species with the most data, ranged from 

7 to 16 mg/kg dry weight, with no obvious relations between 

the selenium concentrations in fish compared to water. The 

highest concentrations of selenium in fish occurred at the 

same time as the lowest concentrations of selenium in water 

(October 2007), and the selenium content in fish collected in 

May 2001 was unremarkable even though this time had the 

highest water selenium concentrations of any sample groups. 

As a result of this disparity, BAFs varied by 10 times, from 2.6 

to 26 (table 6).

The specifics of future monitoring strategies guided by 

the updated selenium criterion scheme will likely evolve, as 

some of the terms are undefined by the rule (Idaho Department 

of Environmental Quality, 2017) or in the national selenium 

criteria document (U.S. Environmental Protection Agency, 

2016), where most terms originated. For instance, “elevated 

selenium concentrations” (U.S. Environmental Protection 

Agency, 2016, p. 737-780) is not further defined and does 

not distinguish whether “elevated” is intended to be relative 

to background concentrations or relative to criteria values. 

No definition is given for what is considered steady-state in 

“steady-state condition fish tissue data” (U.S. Environmental 

Protection Agency, 2016, p. 737-780). For example, selenium 

in water varies on seasonal, interannual, and possibly decadal 

time frames (figs. 3, 4, and 6), and presumably selenium 

concentrations in water influence selenium concentrations 

in fish tissue. The cutthroat trout data (table 6) varied by 

over two times between samplings, yet the 2001 and 2011 

concentrations were nearly identical. The lowest cutthroat 

trout value was from 2012, which was one of the years with 

the lowest maximum 30-day average concentrations (3.9 μg/L) 

but also with the highest low-flow selenium concentrations 

and a middling time-weighted average concentration of 2.5 

μg/L from March 1 through September 30 (fig. 5, table 1).

These data suggest that for evaluating trends and the 

effectiveness of mitigation measures, systematic sampling of 

selenium in water should continue. Coordinated, systematic 

fish collections targeting the same species year to year, with 

samples collected near the water sampling site(s), would seem 

to be the best case for detecting potential trends and evaluating 

criterion compliance. Only fish tissue samples collected in 

2001 and 2008 were collected from the same location as the 

water sampling. Although the available water data indicates 

selenium concentrations are similar among sample locations 

on the mainstem Blackfoot River (fig. 8), colocating fish and 

water sampling is one way to potentially reduce variability and 

strengthen the correlation between selenium in water and fish.

Summary

Increased baseflow concentrations of selenium from 2009 

to 2013 and unaccounted streamflow and selenium loads in the 

Blackfoot River near Dry Valley indicate that alluvial groundwater 

may be a source of selenium loading to the Blackfoot River 

during runoff and baseflow conditions. However, an improved 

understanding of shallow alluvial aquifers throughout the upper 

Blackfoot River watershed would be useful for understanding 

the extent of selenium transport through this mechanism. The 

increasing trends in selenium observed from 2001 to 2012 during 

runoff and baseflow conditions (Mebane and others, 2015) were 

short-lived in the context of the longer water-quality record 

of 2001 to 2016. However, increased median runoff selenium 

concentrations from about 2005 through 2011 may illustrate an 

important aspect of selenium transport in the watershed. Namely, 

high snowmelt years provide a physical mechanism for transporting 

selenium through cross-valley dumps, and a geochemical 

mechanism for increased weathering of available selenium in 

these dumps. Additional weathering may thus manifest as higher 

selenium loads transported to streams during runoff and baseflow in 

following years. This finding suggests that thoughtful management 

of stormwater and snowmelt runoff on mining affected lands 

throughout the watershed may be important for limiting waste 

rock weathering and subsequent selenium release and transport 

throughout the watershed.

Acknowledgments

Primary funding for the U.S. Geological Survey (USGS) 

streamgaging and water-quality data collection at USGS station 

13063000 was from the U.S. Department of Interior, Bureau of 

Land Management. The authors thank the Fish Sampling Protocol 

Technical Team for compiling and furnishing the data in table 6; 

data are available by contacting the Idaho Department of Fish 

and Game, Southeast Regional Office, Pocatello, Idaho. The 

authors would like to thank the USGS staff who have supported 

the streamflow measurements and water-quality data collection 

over the years, including Jay Bateman, Donald Coles, Robert 

Erickson, Mark Hardy, Nathan “Jake” Jacobson, James Johnson, 

Stan Landon, Robert Reaves, and Brad Vande Kamp. Funding for 

the seepage study and this analysis was from the Idaho Department 

of Environmental Quality (IDEQ) and USGS. The authors would 

like to thank the many people who have assisted in the IDEQ 

data collection, including Michelle Byrd, Kelsey Flandro, David 

Goings, Andrew Ray, Joshua Schultz, Melissa Thompson, Michael 

Rowe, Christine Waite (IDEQ); Victoria Burkhardt, Will Frymire, 

and Darrel Vanderweg (U.S. Forest Service); Sandi Fisher (U.S. 

Fish and Wildlife Service); Dean Fox (U.S. Bureau of Land 

Management); and Justin Skinner (Agrium, Inc.). Reviews of 

earlier versions of this report by Christian Schmidt (USGS Idaho 

Water Science Center, Boise, Idaho), Gregory Clark (USGS 

emeritus), and Alexandra Etheridge (USGS California Water 

Science Center) were greatly appreciated.
References Cited 29

References Cited

AECOM Technical Services, Inc., 2015a, North Maybe Mine 

East Mill Operable Unit, baseline monitoring samples—

Caribou National Forest, Idaho: Sacramento, California, 

AECOM Technical Services, Inc., 2013 Data Summary 

Report, prepared for Nu-West Industries, Inc., Soda Springs, 

Idaho, 6815 p.

AECOM Technical Services, Inc., 2015b, North Maybe Mine 

East Mill Operable Unit, baseline monitoring samples—

Caribou National Forest, Idaho: Sacramento, California, 

AECOM Technical Services, Inc., 2014 Data Summary 

Report, prepared for Nu-Qest Industries, Inc., Soda Springs, 

Idaho, 473 p.

Amacher, M.C., Brown, R.W., Sidle, R.C., and 

Kotuby‐Amacher, J., 1995, Effect of mine waste on 

element speciation in headwater streams, in Allen, H.E., 

Huang, C.-P., Bailey, G.W., and Bowers, A.R., eds., Metal 

speciation and contamination of soil: Ann Arbor, Michigan, 

Lewis Publishers, p. 275–309.

Angradi, T.R., 1991, Transport of coarse particulate organic 

matter in an Idaho river, USA: Hydrobiologia, v. 211, no. 3, 

p. 171–183, 10.1007/BF00008533.

Arcadis U.S., Inc., 2016, Final 2015 data summary report, 

North Maybe Mine, Creeks Sub-Operable Unit, Caribou 

County, Idaho: Highlands Ranch, Colorado, Arcadis U.S., 

Inc., prepared for Nu-West Industries, Inc./Nu-West Mining, 

Inc., 19477 p.

Bureau of Land Management, 2011, Final environmental 

impact statement—Blackfoot Bridge Mine: Pocatello Field 

Office, Bureau of Land Management, 874 p., accessed 

March 22, 2013 at http://www.monsanto.com/soda-springs/

Pages/blackfoot-bridge.aspx.

Bureau of Land Management and U.S. Forest Service, 

2016, Final environmental impact statement—Volume 1, 

Rasmussen Valley Mine, Caribou County, Idaho: Pocatello 

Field Office, Caribou-Targhee National Forest, U.S. 

Department of the Interior, U.S. Department of Agriculture. 

1183 p, accessed April 6, 2017, at https://eplanning.blm.

gov/epl-front-office/eplanning/docset_view.do?projectId=48

240¤tPageId=62914&documentId=80012.

Chapman, P.M., Adams, W.J., Brooks, M.L., Delos, C.G., 

Luoma, S.N., Maher, W.A., Ohlendorf, H.M., Presser, T.S., 

and Shaw, D.P., 2009, Ecological assessment of selenium 

in the aquatic environment: Summary of a SETAC Pellston 

Workshop, p. 339

Cleveland, W.S., Grosse, E., and Shyu, W.M., 1992, Local 

regression models, in Chambers, J.M., and Hastie, T., 

eds., Statistical models in S: Pacific Grove, California, 

Wadsworth & Brooks/Cole Advanced Books & Software, 

p. 309–376.

Cleveland, W.S., and Devlin, S.J., 1988, Locally weighted 

regression: an approach to regression analysis by local 

fitting: Journal of the American Statistical Association, 

v. 83, no. 403, p. 596–610, also available at http://dx.doi.org

/10.1080/01621459.1988.10478639.

Conley, J.M., 2012, Evaluation of selenium in biotic and 

abiotic ecosystem components of the upper Blackfoot River 

Watershed: Raleigh, N.C., prepared for Greater Yellowstone 

Coalition, North Carolina State University, Department of 

Environmental and Molecular Toxicology, p. 36.

Eaton, A.D., Clesceri, L.S., Rice, E.W., and Greenberg, A.E., 

eds., 2005, Standard methods for the examination of water 

and wastewater: Washington D.C., American Public Health 

Association, American Water Works Association, and Water 

Environment Federation, variously paged.

Essig, D.A., 2010, Arsenic, mercury, and selenium in fish 

tissue and water from Idaho’s major rivers: a statewide 

assessment, 118 p., accessed May 22, 2018, at https://www.

deq.idaho.gov/media/639752-arsenic_mercury_fish_tissue_

report_0310.pdf.

Garbarino, J.R., 1999, Methods of analysis by the U.S. 

Geological Survey National Water Quality Laboratory—

Determination of dissolved arsenic, boron, lithium, 

selenium, strontium, thallium, and vanadium using 

inductively coupled plasma-mass spectrometry: U.S. 

Geological Survey Open-File Report 99–093, 31 p., https://

pubs.er.usgs.gov/publication/ofr9993.

Garbarino, J.R., Kanagy, L.K., and Cree, M.E., 2006, 

Determination of elements in natural-water, biota, sediment, 

and soil samples using collision/reaction cell inductively 

coupled plasma-mass spectrometry: U.S. Geological Survey 

Techniques and Methods, book 5, chap. B1, 88 p., https://

pubs.er.usgs.gov/publication/tm5B1.

Granato, G.E., 2009, Computer programs for obtaining 

and analyzing daily mean streamflow data from the U.S. 

Geological Survey National Water Information System Web 

Site: U.S. Geological Survey Open-File Report 2008–1362, 

123 p. on CD-ROM, 5 appendixes, http://pubs.er.usgs.gov/

publication/ofr20081362.
30 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

Grauch, R.I., Desborough, G.A., Meeker, G.P., Foster, A.L., 

Tysdal, R.G., Herring, J.R., Lowers, H.A., Ball, B.A., 

Zielinski, R.A., and Johnson, E.A., 2004, Petrogenesis and 

mineralogic residence of selected elements in the meade 

peak phosphatic shale member of the permian phosphoria 

formation, Southeast Idaho, chap. 8 of Hein, J.R., ed., 

Handbook of exploration and environmental geochemistry: 

Elsevier Science B.V., v. 8, p. 189–226, also available 

at http://www.sciencedirect.com/science/article/pii/

S187427340480010X.

Hamilton, S.J., 2004, Review of selenium toxicity in the 

aquatic food chain: The Science of the Total Environment, 

v. 326, no. 1–3, p. 1–31, also available at http://dx.doi.

org/10.1016/j.scitotenv.2004.01.019.

Hamilton, S.J., and Buhl, K.J., 2005, Selenium in the 

Blackfoot, Salt, and Bear River Watersheds: Environmental 

Monitoring and Assessment, v. 104, no. 1, p. 309–339, 

10.1007/s10661-005-1618-4.

Hamilton, S.J., Buhl, K.J., and Lamothe, P.J., 2004, Selenium 

and other trace elements in water, sediment, aquatic 

plants, aquatic invertebrates, and fish from streams in SE 

Idaho near phosphate mining, chap. 18 of Hein, J.R., ed., 

Handbook of exploration and environmental geochemistry: 

Elsevier Science B.V., v. 8, p. 483–525, also available 

at http://www.sciencedirect.com/science/article/pii/

S1874273404800202.

Hay, M.B., Leone, G., Partey, F., and Wilking, B., 2016, 

Selenium attenuation via reductive precipitation in 

unsaturated waste rock as a control on groundwater impacts 

in the Idaho phosphate patch: Applied Geochemistry, v. 74, 

p. 176–193, also available at http://dx.doi.org/10.1016/j.

apgeochem.2016.09.008.

Hein, J.R., ed., 2004, Life cycle of the phosphoria formation—

From deposition to the post-mining environment, in

Handbook of exploration and environmental geochemistry: 

Elsevier Science B.V., v. 8, 635 p.

Herring, J.R., 2004, Rock leachate geochemistry of the meade 

peak phosphatic shale member of the phosphoria formation, 

Southeast Idaho, chap. 13 of Hein, J.R., ed., Handbook 

of exploration and environmental geochemistry: Elsevier 

Science B.V., v. 8, p. 367–397, also available at http://www.

sciencedirect.com/science/article/pii/S1874273404800159.

Herring, J.R., and Grauch, R.I., 2004, Lithogeochemistry of 

the meade peak phosphatic shale member of the phosphoria 

formation, Southeast Idaho, chap. 12 of Hein, J.R., ed., 

Handbook of exploration and environmental geochemistry: 

Elsevier Science B.V., p. 321–366, also available 

at http://www.sciencedirect.com/science/article/pii/

S1874273404800147.

Hirsch, R.M., 1982, A comparison of four streamflow 

record extension techniques: Water Resources Research, 

v. 18, no. 4, p. 1081-1088, also available at http://dx.doi.

org/10.1029/WR018i004p01081.

Idaho Department of Environmental Quality, variously dated, 

IDAPA 58.01.02—Water quality standards, title 1, chapter 

2: Pocatello, Idaho, Idaho Department of Environmental 

Quality, 180 p., accessed May 22, 2018, at https://

adminrules.idaho.gov/rules/current/58/0102.pdf.

Idaho Department of Environmental Quality, 2017, IDAPA 

58.01.02—Water quality standards, title 1, chapter 2, 

docket no. 58-0102-1701, Notice of rulemaking—Proposed 

rulemaking: Pocatello, Idaho, Idaho Department of 

Environmental, 21 p., accessed May 22, 2018, at http://

www.deq.idaho.gov/media/60180627/58-0102-1701-

proposed-rule-notice-0817.pdf.

Idaho Department of Fish and Game, 2018, Master database of 

fish tissue selenium concentrations collected in waterbodies 

in southeast Idaho: Pocatello, Idaho Department of Fish and 

Game database, Southeast Regional Office.

Knudsen, A.C., and Gunter, M.E., 2004, The effects of 

weathering on the mineralogy of the phosphoria formation, 

Southeast Idaho, chap. 7 of Hein, J.R., ed., Handbook of 

exploration and environmental geochemistry: Elsevier 

Science B.V., v. 8, p. 169–187, also available at http://www.

sciencedirect.com/science/article/pii/S1874273404800093.

Maher, W.A., Roach, A., Doblin, M.A., Fan, T.W.-M., Foster, 

S., Garrett, R., Moller, G., Oram, L.L., and Wallschlager, D., 

2010, Environmental sources, speciation, and partitioning 

of selenium, in Chapman, P.M., Adams, W.J., Brooks, M.L., 

Delos, C.G., Luoma, S.N., Maher, W.A., Ohlendorf, H.M., 

Presser, T.S., and Shaw, D.P., eds., Ecological assessment 

of selenium in the aquatic environment: Pensacola, Florida, 

SETAC Press, p. 47–92.

Mars, J.C., and Crowley, J.K., 2003, Mapping mine wastes 

and analyzing areas affected by selenium-rich water 

runoff in southeast Idaho using AVIRIS imagery and 

digital elevation data: Remote Sensing of Environment, 

v. 84, no. 3, p. 422–436, also available at http://dx.doi.

org/10.1016/S0034-4257(02)00132-3.

McNeal, J.M., and Balistrieri, L.S., 1989, Geochemistry and 

occurrence of selenium—An overview, in Jacobs, L.W., ed., 

Selenium in agriculture and the environment—SSSA special 

publication: Madison, WI, Soil Science Society of America 

and American Society of Agronomy, p. 1–13., 10.2136/

sssaspecpub23.c1.
References Cited 31

Mebane, C.A., Mladenka, G., Van Every, L., Williams, M.L., 

Hardy, M.A., and Garbarino, J.R., 2015, Selenium in the 

upper Blackfoot River watershed, southeastern Idaho, 

2001–12: U.S. Geological Survey Scientific Investigations 

Report 2014-5203 (ver. 1.1), 34 p, plus appendixes, http://

dx.doi.org/10.3133/sir20145203.

Mladenka, G., Van Every, L., Zinsser, L.M., and 

Mebane, C.A., 2018, Selenium in the upper Blackfoot River 

watershed, Idaho, 2001–2016: Digital datasets, http://dx.doi.

org/10.6084/m9.figshare.5405662.

Moyle, P.R., and Kayser, H.Z., 2006, Spatial database of 

mining-related features in 2001 at selected phosphate mines, 

Bannock, Bear Lake, Bingham, and Caribou Counties, 

Idaho: U.S. Geological Survey Data Series 223, 58 p., 1 pl., 

also available at http://pubs.er.usgs.gov/publication/ds223.

Mueller, D.K., Schertz, T.L., Martin, J.D., and 

Sandstrom, M.W., 2015, Design, analysis, and interpretation 

of field quality-control data for water-sampling projects: 

U.S. Geological Survey Techniques and Methods, book 4, 

chap. C4, 54 p., https://dx.doi.org/10.3133/tm4C4.

Natural Resources Conservation Service, 2017a, Slug Creek 

Divide Snotel (761): U.S. Department of Agriculture 

database, accessed June 2017 at https://wcc.sc.egov.usda.

gov/nwcc/site?sitenum=761.

Natural Resources Conservation Service, 2017b, Somsen 

Ranch Snotel (770): U.S Department of Agriculture, 

accessed January 12, 2017, at https://wcc.sc.egov.usda.gov/

nwcc/site?sitenum=770.

Nordstrom, D.K., 2009, Acid rock drainage and climate 

change: Journal of Geochemical Exploration, v. 100, no. 

2, p. 97–104, also available at https://doi.org/10.1016/j.

gexplo.2008.08.002.

Oberg, K.A., Morlock, S.E., and Caldwell, W.S., 2005, 

Quality-assurance plan for discharge measurements using 

acoustic Doppler current profilers: U.S. Geological Survey 

Scientific Investigations Report 2005-5183, 41 p, also 

available at http://pubs.er.usgs.gov/publication/sir20055183.

Oram, L.L., Strawn, D.G., Marcus, M.A., Fakra, S.C., and 

Möller, G., 2008, Macro- and microscale investigation of 

selenium speciation in Blackfoot River, Idaho sediments: 

Environmental Science & Technology, v. 42, no. 18, p., 

6830–6836, 10.1021/es7032229.

Oram, L.L., Strawn, D.G., Morra, M.J., and Möller, G., 

2010, Selenium biogeochemical cycling and fluxes 

in the hyporheic zone of a mining-impacted stream: 

Environmental Science & Technology, v. 44, no. 11, 

p. 4176–4183, 10.1021/es100149u.

Paul, A.P., Garbarino, J.R., Olsen, L.D., Rosen, M.R., 

Mebane, C.A., and Struzeski, T.M., 2016, Potential sources 

of analytical bias and error in selected trace element dataquality analyses: Reston, Virginia, 2016-5135, 68 p, also 

available at http://pubs.er.usgs.gov/publication/sir20165135.

Perkins, R.B., and Foster, A.L., 2004, Mineral affinities 

and distribution of selenium and other trace elements in 

black shale and phosphorite of the phosphoria formation, 

chap. 10 of Hein, J.R., ed., Handbook of exploration 

and environmental geochemistry: Elsevier Science B.V., 

p. 251–295, also available at http://www.sciencedirect.com/

science/article/pii/S1874273404800123.

Presser, T.S., Hardy, M., Huebner, M.A., and Lamothe, P.J., 

2004a, Selenium loading through the Blackfoot River 

watershed—Linking sources to ecosystems, chap. 16 of

Hein, J.R., ed., Handbook of exploration and environmental 

geochemistry: Elsevier Science B.V., p. 437–466, also 

available at http://www.sciencedirect.com/science/article/

pii/S1874273404800184.

Presser, T.S., and Luoma, S.N., 2010, A methodology 

for ecosystem-scale modeling of selenium: Integrated 

Environmental Assessment and Management, v. 6, no. 4, 

p. 685–710, 10.1002/ieam.101.

Presser, T.S., Piper, D.Z., Bird, K.J., Skorupa, J.P., 

Hamilton, S.J., Detwiler, S.J., and Huebner, M.A., 2004b, 

The phosphoria formation—A model for forecasting global 

selenium sources to the environment, chap. 11 of Hein, 

J.R., ed., Handbook of exploration and environmental 

geochemistry: Elsevier Science B.V., p. 299–319, also 

available at http://www.sciencedirect.com/science/article/

pii/S1874273404800135.

Ralston, D.R., and Williams, R.E., 1979, Groundwater flow 

systems in the western phosphate field in Idaho: Journal of 

Hydrology (Amsterdam), v. 43, no. 1, p. 239– 264, 

also available at http://dx.doi.org/10.1016/0022-

1694(79)90175-6.

Riggs, H.C., 1972, Low-flow investigations: U.S. Geological 

Survey Techniques of Water-Resources Investigations, book 

4, chap. B1, 18 p., also available at http://pubs.er.usgs.gov/

publication/twri04B1.

Sauer, V.B., and Turnipseed, D.P., 2010, Stage measurement 

at gaging stations: U.S. Geological Survey Techniques and. 

Methods book 3, chap. A7, 45 p., also available at https://

pubs.er.usgs.gov/publication/tm3A7.

Sidle, R.C., Farmer, E.E., and Williams, B.D., 1994, 

Subsidence and rock creep in a cross-valley fill: 

Environmental Geology, v. 24, no. 3, p. 159–165, also 

available at http://dx.doi.org/10.1007/bf00766885.
32 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

Simonds, F.W., and Sinclair, K.A., 2002, Surface water-ground 

water interactions along the lower Dungeness River and 

vertical hydraulic conductivity of streambed sediments, 

Clallam County, Washington, September 1999–July 2001: 

U.S. Geological Survey Water-Resources Investigations 

Report 02-4161, 60 p., also available at http://pubs.er.usgs.

gov/publication/wri024161.

Stillings, L.L., and Amacher, M.C., 2010, Kinetics of 

selenium release in mine waste from the Meade Peak 

Phosphatic Shale, Phosphoria Formation, Wooley 

Valley, Idaho: Chemical Geology, v. 269, no. 1–2, 

p. 113–123, also available at http://dx.doi.org/10.1016/j.

chemgeo.2009.10.011.

U.S. Environmental Protection Agency, 1998, Method 

6020A Inductively couple plasma—Mass spectrometry: 

Washington, D.C., U.S. Environmental Protection 

Agency, 23 p., also available at https://www.epa.gov/sites/

production/files/2015-07/documents/epa-6020a.pdf. 

U.S. Environmental Protection Agency, 2016, Appendix K–

Translation of a selenium fish tissue criterion element to a 

site-specific water column value: Washington, D.C., U.S. 

Environmental Protection Agency, p. 737–780 (K1–K44), 

also available at https://www.epa.gov/wqc/aquatic-lifecriterion-selenium.

U.S. Geological Survey, 2017a, Methods for quantifying 

streamflow measurement uncertainty for measurements 

stored in the National Water Information System: Reston, 

Virginia, U.S. Geological Survey, Office of Surface Water 

Technical Memo 2017.12, 3 p., also available at https://

water.usgs.gov/admin/memo/SW/sw17.12.pdf.

U.S. Geological Survey, 2017b, National Water Information 

System (NWIS): U.S. Geological Survey National Water 

Information System, accessed May 22, 2018, at https://nwis.

waterdata.usgs.gov/nwis.

U.S. Geological Survey, variously dated, National field manual 

for the collection of water-quality data, U.S. Geological 

Survey Techniques of Water-Resources Investigations, 

book 9, chaps. A1–A10, accessed May 22, 2018, at http://

pubs.water.usgs.gov/twri9A.

Wallace, R.L., and Zaroban, D.W., 2013, Native fishes of 

Idaho: Bethesda, Maryland, American Fisheries Society, 

216 p.

Wheeler, J.D., and Eddy-Miller, C.A., 2005, Seepage 

investigation on selected reaches of Fish Creek, Teton 

County, Wyoming, 2004: U.S. Geological Survey Scientific 

Investigations Report 2005-5133, 22 p., accessed May 22, 

2018, at http://pubs.er.usgs.gov/publication/sir20055133.

Whetstone Associates, 2017, North Dry Valley Mine surface 

water and groundwater monitoring results, year 2016: 

Gunnison, Colorado, Whetstone Associates, 87 p.
Appendix 1 33

Appendix 1. Data Quality Evaluations

No selenium was detected in any of the 15 ambient or 

equipment blank samples analyzed during 2013–16, with 

laboratory reporting limits of 0.03 to 0.05 micrograms per liter 

(μg/L).

Variability in concurrent replicate samples collected 

by the autosampler, grab samples from a single point in the 

stream channel, or equal-width increment (EWI) samples was 

evaluated by comparing the relative sample deviation (RSD), 

also known as the coefficient of variability, and is defined 

as the standard deviation of all replicates values, divided 

by the average, expressed as a percentage. With selenium, 

12 matched sets of automatically collected, grab, and EWI 

samples were evaluated (table 1.1). Of these, the median RSD 

was 2.8 percent, ranging from 0 to 6.9 percent.

For the majority of the selenium samples, the similar 

results between grab samples and automatically collected 

samples indicate that the sampler pumping system did not 

significantly affect samples. Likewise, the similarity between 

samples shows that the autosampler represented well the 

dissolved selenium in the stream cross section. By implication, 

in this well-mixed location distant from any seeps or selenium 

sources, EWI samples add little information over grab or 

automatic samples, other than providing reassurance of the 

representativeness of the grab and autosamples.

Comparisons of Laboratory Results With 

External Quality Control Samples

The preceding examination of quality control blank 

samples and the combined variability from environmental 

variability, different sampling methods, and inherent 

variability of laboratory analyses showed the absence of 

measurable cross contamination of samples from field or 

laboratory processing and analyses, and showed high precision 

in the reported selenium concentrations. However, precision 

and accuracy are two different concepts and neither the 

absence of contamination nor high precision demonstrate the 

accuracy of the laboratory analyses. Underlying the variability 

in the comparisons among the field sampling methods is the 

intrinsic measurement uncertainty of the laboratory analyses. 

A previous evaluation of selenium trends in the upper 

Blackfoot River watershed suggested a slight but persistent 

and increasing low bias to the laboratory results (Mebane 

and others, 2015). Other external evaluations showed that 

although the U.S. Geological Survey (USGS) National Water 

Quality Laboratory (NWQL) selenium analyses generally met 

established data quality objectives (generally ±20 percent of 

quality control sample values, in addition to internal control 

limits), selenium analyses had a slight but systematic low 

bias (Paul and others, 2016). Although the NWQL maintains 

a strict regimen of internal controls and external validation 

in keeping with industry good laboratory practices (http://

wwwnwql.cr.usgs.gov/USGS_Quality.shtml), in this study we 

are seeking to detect subtle trends over time, which depends 

upon accurate and precise laboratory performance. Thus, 

we examined the potential for analytical bias to affect our 

interpretations, and we also evaluated external quality testing 

of the NWQL in some detail.

First, we considered the measurement uncertainty of 

the laboratory analyses by evaluating the accuracy and bias 

of selenium results obtained for blind, standard reference 

samples. During the period of our study, 2013–16, the USGS 

NWQL analyzed 359 blind standard reference samples 

(filtered river water samples that had been spiked with 

selenium and other inorganics) through the USGS Bureau 

of Quality Services Inorganic Blind Sample Program. 

These results were matched with the most probable values 

(MPVs) obtained from round robin sampling (fig. 1.1). The 

round robin MPVs are assumed here to represent “true” 

concentrations, although MPVs have their own variability and 

uncertainties. The agreement between MPVs and measured 

values can be examined quantitatively by calculating the 

percent recovery of the laboratory samples which reflects 

the inherent measurement uncertainty and any tendencies 

toward a positive or negative bias in the data (fig. 1.2). The 

percent recoveries were evaluated for bias trends over time 

through locally weighted (LOESS) regression Cleveland 

and Devlin, 1988). The absence of bias would be indicated 

by even distribution of percent recovery values above and 

below the 100 percent recovery line. Visually, the percent 

recoveries show a distinct negative bias that seemed to 

strengthen from 2014 to 2016 (fig. 1.1). A closer inspection 

of absolute values behind the relative percent recoveries 

suggests a concentration dependence to the bias, and that the 

great majority of the standard reference samples analyzed 

by the NWQL through the Inorganic Blind Sample Program 

were low, with 80 percent of the MPVs less than 0.8 μg/L 

and with a median MPV of 0.58 μg/L (fig. 1.1 and underlying 

data). These concentrations are lower than the vast majority 

of concentrations measured in the upper Blackfoot River 

watershed study, for which 90 percent of the samples were 

greater than 1.2 μg/L. The grand average from 2010 to 2016 

was 3.5 μg/L, ranging from 0.5 to 13.8 μg/L, n = 619.
34 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

Two additional lines of evidence are relevant to the 

question of whether the low bias apparent from the Inorganic 

Blind Sample Program samples at low concentrations (figs. 1.1

and 1.2) held at the higher concentrations that were more 

representative of concentrations encountered in the upper 

Blackfoot River watershed study area. First, split samples 

from the Blackfoot River and tributaries were analyzed by the 

NWQL and SVL Analytical (SVL; Kellogg, Idaho). SVL has 

provided chemical analyses for Blackfoot River monitoring 

by IDEQ since 2008 (Mladenka and others, 2018). As this 

report relied on data from the IDEQ and USGS sampling, SVL 

provided blind standard reference samples for analysis, and six 

pairs of split samples were analyzed by the NWQL and SVL. 

The results (table 1.2) show close agreement between the SVL 

results and the USGS standard reference samples, and close 

agreement between the NWQL and SVL sample pairs.

In the second approach to evaluate the NWQL results for 

bias in the concentration range of most concern in the present 

study (about 1 to 10 μg/L), selenium interlaboratory quality 

comparison testing comparisons were evaluated. The NWQL 

participates in the semiannual standard reference sample round 

robin tests with one concentration per cycle (https://bqs.usgs.

gov/srs/), and in annual performance testing by Environment 

Canada (which provides accredited proficiency tests for 

laboratories) with 10 concentrations per cycle (https://nwql.

usgs.gov/Public/perf_eval.shtml). The results obtained with 

these reference samples during 2013–16 are plotted against the 

expected most probable values for the samples, with arbitrarily 

selected performance bounds of ±20 percent (fig. 1.3). Only 

for the lowest concentration in the dataset was the NWQL 

measurement well outside of the ±20 percent performance 

bounds. A high bias is discernable at about greater than 30 

μg/L selenium. However, figure 1.3 shows at least that at 

selenium concentrations greater than about 0.5 μg/L, selenium 

results provided by the NWQL were highly repeatable and 

acceptably precise and accurate. Together, the various data 

quality evaluations indicate that the combined field and 

laboratory processes give highly repeatable results, and for 

the conditions encountered in the upper Blackfoot River 

watershed study, reported concentrations were sufficiently 

precise and sufficiently accurate. During 2013–16, NWQL 

reported selenium concentrations of about less than or equal to 

0.5 μg/L were likely low biased; however, few concentrations 

nearly this low were reported among the upper Blackfoot 

River watershed dataset during this period.
Appendix 1 35

Table 1.1. Matched quality control sample results collected from replicate automated pump 

sampler, grab samples, and equal width increment samples.

[Abbreviations: auto, automated pump sampler; EWI, equal width increment; RSD, relative sample deviation; 

μg/L, micrograms per liter]

Date Sample 

type

Dissolved selenium 

(μg/L)

Relative sample deviation 

(percent)

May 2, 2013 Auto 3.4 1.7

May 2, 2013 Grab 3.5

May 2, 2013 EWI 3.4

June 25, 2013 Auto 2.4 0.0

June 25, 2013 Grab 2.4

June 25, 2013 EWI 2.4

September 16, 2013 Auto 1.7 2.8

September 16, 2013 Grab 1.8

September 16, 2013 Grab 1.8

September 16, 2013 EWI 1.8

May 13, 2014 EWI 5.5 6.3

May 13, 2014 Grab 4.9

May 13, 2014 Auto 5

July 10, 2014 Auto 1.4 0.0

July 10, 2014 Grab 1.4

September 16, 2014 Auto 1.5 3.7

September 16, 2014 EWI 1.6

September 16, 2014 Grab 1.6

May 6, 2015 Auto 4.6 3.1

May 6, 2015 EWI 4.4

July 13, 2015 Auto 1.1 0.0

July 13, 2015 Auto 1.1

July 13, 2015 Grab 1.1

September 24, 2015 Auto 0.97 6.9

September 24, 2015 Grab 0.99

September 24, 2015 EWI 1.1

April 21, 2016 Auto 3.8 3.6

April 21, 2016 Grab 4

July 13, 2016 Grab 1.5 0.0

July 13, 2016 Auto 1.5

September 21, 2016 Grab 1.6 3.7

September 21, 2016 EWI 1.6

September 21, 2016 Auto 1.5

Maximum RSD 6.9

90 percentile RSD 5.7

Median RSD 2.8

n comparisons 12
36 Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Idaho, 2001–16

Table 1.2. Interlaboratory comparison of selenium samples, Blackfoot River, Idaho, June 2016.

[RPD: Relative percent difference. Abbreviations: NWQL, National Water Quality Laboratory; Se, selenium; SRS, standard reference sample; 

SVL, SVL Analytical; USGS, U.S. Geological Survey; μg/L, microgram per liter]

Date Site No. Site name

Field 

ID 

name

SRS sample 

No.

USGS standard 

Reference sample 

[Se] (μg/L)

± F-pseudo 

sigma 

(deviation) 

(μg/L)

SVL 

result 

[Se]

(μg/L)

06-21-16 13062857 Blackfoot River nr Conda, ID Site 3 T225 5.33 0.571 4.8

06-21-16 13062857 Blackfoot River nr Conda, ID Site 3 T223 11.2 0.89 10.9

06-21-16 13062857 Blackfoot River nr Conda, ID Site 3 T217 3.8 0.434 3.4

NWQL, selenium, 

water, unfiltered, 

(μg/L) 

SVL, selenium, 

water, unfiltered, 

(μg/L) 

RPD

06-21-16 13062857 Blackfoot River nr Conda, ID Site 3 2.2 1.9 12.3

06-22-16 13062857 Blackfoot River nr Conda, ID Site 3 2.0 1.8 8.5

06-23-16 13062857 Blackfoot River nr Conda, ID Site 3 2.0 1.9 2.6

06-21-16 4247361112214 Blackfoot River site 1 near Conda ID Site 1 1.7 1.6 5.5

06-22-16 4247361112214 Blackfoot River site 1 near Conda ID Site 1 1.5 1.5 1.3

06-23-16 4247361112214 Blackfoot River site 1 near Conda ID Site 1 1.5 1.5 2.0

2012 2013 2014 2015 2016

0

2

4

6

8

Selenium, in micrograms per liter

Year

Laboratory value

Most probable value

EXPLANATION

Figure 1.1. Quality control results of filtered selenium values measured by the U.S. Geological Survey 

National Water Quality Laboratory compared with the most probable values from round-robin testing of 

spiked filtered river water samples.
Appendix 1 37

tac18-1229_appendix_fig1-2

2001 2003 2005 2007 2009 2011 2013 2015 2017

0

20

40

60

80

100

120

140

160

180

200

Recovery (percent of most probable value)

Year

EXPLANATION

Locally weighted regression

Recovery (percent of most 

probable value)

Figure 1.2. Accuracy and bias of selenium measurements made by the U.S. Geological Survey National Water Quality Laboratory 

with blind standard reference samples (spiked river water samples), as percentages of most probable values.

0.1 1 10 100

0.1

1

10

100

NWQL selenium concentration, in micrograms per liter

Expected selenium concentration, in micrograms per liter

EXPLANATION

1 to 1

+20 percent

-20 percent

Environment Canada

USGS SRS

Figure 1.3. Selenium concentrations measured by the National Water Quality Laboratory compared to expected concentrations in 

round robin interlaboratory performance testing evaluations by Environment Canada or the U.S. Geological Survey Bureau of Quality 

Systems Standard Reference Sample programs. Except for the lowest selenium concentration that was clearly out of bounds, most 

samples were within ±20 percent bounds of the expected values. (Se, selenium; SRS, standard reference sample; μg/L, microgram per 

liter). 

Publishing support provided by the U.S. Geological Survey 

Science Publishing Network, Tacoma Publishing Service Center

For more information concerning the research in this report, contact the 

Director, Idaho Water Science Center

U.S. Geological Survey 

230 Collins Road

Boise, Idaho 83702

https://www.usgs.gov/centers/id-water
Zinsser and others—Spatial and Temporal Trends in Selenium in the Upper Blackfoot River Watershed, Southeastern Idaho, 2001–16—Scientific Investigations Report 2018-5081

ISSN 2331-1258 (online)

https://doi.org/10.3133/sir20185081