Characterization of Background 

Water Quality

By M. Alisa Mast, Philip L. Verplanck, Winfield G. Wright, and Dana J. Bove

Chapter E7 of

Integrated Investigations of Environmental Effects of Historical 

Mining in the Animas River Watershed, San Juan County, Colorado

Edited by Stanley E. Church, Paul von Guerard, and Susan E. Finger

Professional Paper 1651

U.S. Department of the Interior

U.S. Geological Survey
Contents

Abstract .......................................................................................................................................................351

Introduction.................................................................................................................................................351

Purpose and Scope ..........................................................................................................................352

Study Methods ...........................................................................................................................................352

Geology, Alteration, and Mineralization .................................................................................................353

Water-Quality Characteristics .................................................................................................................355

Background Streams and Springs .................................................................................................356

Mine Drainage and Mining-Affected Surface Water .................................................................360

Relation Between Geology and Background Water Quality ..............................................................363

Inverse Geochemical Modeling of Selected Background Springs ..........................................367

Approaches for Describing Background Water Quality .....................................................................370

Statistical Descriptions ....................................................................................................................372

Mass-Balance Approach ................................................................................................................376

Isotopic Applications........................................................................................................................377

Strontium Isotopes ..................................................................................................................377

Sulfur and Oxygen Isotopes of Sulfate .................................................................................378

Rare-Earth Elements in Surface Water .........................................................................................381

Summary......................................................................................................................................................382

References Cited........................................................................................................................................383

Figures

 1. Map showing Animas River watershed study area, with distribution of major 

alteration assemblages ...........................................................................................................354

 2. Photographs showing areas of varied alteration, east side of Cement Creek, 

on peak 3,792 m, and in headwaters of Prospect Gulch ....................................................355

 3. Graphs showing dissolved sulfate, alkalinity, aluminum, and iron concentrations 

as a function of pH for background water-quality samples ..............................................357

 4. Maps showing pH and dissolved concentrations of sulfate, copper, and sodium 

in background water-quality samples ...................................................................................359

 5. Graph showing sum of dissolved base-metal concentrations as a function of pH 

for mine-drainage samples ......................................................................................................362

 6. Box plots showing comparison of dissolved constituent concentrations in 

background water-quality samples, streamflow-gauging stations, and minedrainage samples from upper Animas River, Cement Creek, and Mineral Creek 

basins ..........................................................................................................................................364

 7. Graphs showing dissolved zinc, copper, and sulfate concentrations as a function 

of pH for background water-quality samples draining different bedrock alteration 

assemblages ..............................................................................................................................365

 8. Photograph and sample-site map of Red tributary and peak 3,792 m area ....................367

 9. Graphs showing discharge and mass loading profiles for dissolved sulfate, 

calcium, aluminum, iron, and zinc along Red tributary ......................................................368
 10. Box plots showing comparison of dissolved constituent concentrations in minedischarge samples and in background water-quality samples draining different 

alteration assemblages ...........................................................................................................373

 11. Biplots of principal component scores for background streams and springs 

and mine drainage by primary alteration type, and groupings by cluster analysis ........375

 12–14. Graphs showing:

 12. Relation between 87Sr/86Sr and 1/strontium for whole-rock samples, and 

87Sr/86Sr and pH for water samples from Middle Fork Mineral Creek subbasin .......379

 13. Stable sulfur and oxygen isotopes of dissolved sulfate in background and 

 mining-affected water-quality samples, and range of isotopic values for 

 selected minerals ..............................................................................................................380

 14. Rare-earth element ratios of background water-quality and mine-discharge 

 samples from Prospect Gulch and Middle Fork Mineral Creek ..................................382

Tables

 1. Categories for ranking water-quality sampling sites and information used in their 

assignment .................................................................................................................................353

 2. Summary statistics for dissolved constituent concentrations in background waterquality samples (category I– II) in the Animas River watershed study area ....................356

 3. Spearman rank correlation coefficients (r values) showing the relation among 

dissolved constituent concentrations for background water-quality samples 

(category I–II) in the Animas River watershed study area ................................................358

 4. Comparison of selected dissolved constituents in surface water draining selected 

mineralized but unmined areas in Colorado and Alaska ......................................................360

 5. Summary statistics for dissolved constituent concentrations in mine-drainage 

samples from the Animas River watershed study area .....................................................361

 6. Results from Wilcoxon Signed-Ranks test comparing dissolved constituent 

concentrations in background water-quality samples (category I–II) with minedrainage samples and mining-affected surface water samples (category III–IV) 

in the Animas River watershed study area ..........................................................................363

 7. Dissolved constituent concentrations at stream transect sites along the Red 

tributary of Middle Fork Mineral Creek, October 2, 1999 ...................................................368

 8. Results of mass-balance modeling of background springs draining different 

alteration assemblages in the Animas River watershed study area ...............................369

 9. Median water-quality composition for groups defined by cluster analysis of 

principal component scores, and number of mines and background samples 

(by alteration assemblage) in each group, 1997–99 ............................................................376

 10. Concentrations and loads of dissolved constituents at the mouth of Middle Fork 

Mineral Creek and at major mines in the subbasin, and estimated contributions 

(percent) from background weathering ................................................................................377

Abstract

Water quality in historical mining districts is affected 

by metal-rich drainage from inactive mines and by weathering of mineralized bedrock in unmined areas. To characterize background water quality in the Animas River watershed 

study area, we sampled 146 streams and springs minimally 

affected by mining during low-flow conditions in 1997–99. 

Background springs and streams were dominantly calciumbicarbonate-sulfate type water but displayed a wide range of 

chemical compositions for both major and trace-metal constituents. For example, pH values of background samples ranged 

from 2.58 to 8.49 and specific conductance ranged from 12 to 

2,180 microsiemens per centimeter. Zinc was detected in more 

than one-half the background samples, and zinc concentrations 

exceeded acute aquatic-life standards in more than 30 percent 

of samples. The primary factor controlling the chemistry of 

background sites was the degree of bedrock alteration. Propylitically altered rock produced neutral surface water with low 

dissolved metal concentrations, whereas quartz-sericite-pyrite 

altered rock generated surface water with low pH and elevated 

dissolved metal concentrations. Drainage from 75 inactive 

mine sites and 95 mining-affected surface-water sites was 

sampled for comparison with background water quality. Minedrainage chemistry was highly variable: pH values ranged 

from 2.35 to 7.77, and specific conductance ranged from 180 

to 3,520 microsiemens per centimeter. Comparison of background samples with mine-drainage samples showed statistically significant differences in concentrations for all the major 

ions and many dissolved metals, including barium, copper, 

iron, manganese, strontium, and zinc. Higher concentrations 

of all metals except barium were at mine sites. Estimation of 

metal contributions from background sources on a watershed 

scale was complicated by a number of factors, including the 

large number of mining-related features, rugged topography, 

complex geology, and contributions of ground water from 

unknown sources. We explored several different approaches 

to estimate background water quality in the study area on different scales, including statistical descriptions, mass-balance 

calculations, isotopic applications, and rare-earth element geochemistry. The results demonstrate that metals released from 

weathering of altered rock from unmined areas are significant 

in some stream reaches and must be taken into account when 

water-quality standards and remediation goals are established 

for the Animas River watershed study area.

Introduction

One of the objectives of the Animas River watershed 

study is to characterize sources of metals to surface water that 

may have existed prior to mining activity. Although drainage 

from inactive mines can affect surface-water quality, background weathering of altered and mineralized bedrock is also 

an important source of metals and acidity in historical mining districts. Water-quality studies in highly mineralized yet 

unmined areas have demonstrated that background weathering 

processes can contribute substantial amounts of metals and 

acidity to streams (Bassett and others, 1992; Runnells and 

others, 1992; Miller and McHugh, 1994; Kirkham and others, 1995; Bove, 1996; Kelley and Taylor, 1997; Leybourne 

and others, 1998; Miller and others, 1999). For example, 

dozens of naturally occurring acidic springs are present in 

the headwaters of the Alamosa River in Colorado, which 

drains the Summitville acid-sulfate gold-silver-copper deposit 

(Kirkham and others, 1995). These springs had pH values 

as low as 1.4 and commonly had higher aluminum and iron 

concentrations than draining mines in the same area. In the 

Brooks Range of Alaska, streams draining undisturbed silverlead-zinc massive sulfide deposits were reported to be acidic 

and contained elevated levels of cadmium, lead, and zinc 

that in some streams exceeded drinking-water and aquaticlife standards (Kelley and Taylor, 1997). Geologic data also 

provide evidence of natural acidic rock drainage (Helgen and 

Moore, 1996; Logsdon and others, 1996; Furniss and others, 

1999; Church and others, 2000). In the New World mining 

district in Montana, radiocarbon dates revealed that ferricrete 

deposits were nearly 9,000 years old, suggesting that natural acidic rock drainage predated the earliest mining activity 

in the district (Furniss and others, 1999). The presence of 

Holocene ferricrete deposits and iron bogs directly associated 

with the distribution of hydrothermally altered rock (Bove and 

Chapter E7

Characterization of Background Water Quality

By M. Alisa Mast, Philip L. Verplanck, Winfield G. Wright, and Dana J. Bove
others, this volume, Chapter E3; Yager and Bove, this volume, 

Chapter E1 and pl. 2) in the San Juan Mountains provides 

strong evidence that acid rock drainage also was common in 

some parts of the Animas River watershed study area prior 

to mining (Logsdon and others, 1996; Nash, 1999; Verplanck 

and others, this volume, Chapter E15; Wirt and others, this 

volume, Chapter E17). This finding is further supported by 

geochemical studies in the Animas River which indicate that 

the weathering of exposed mineral deposits increased metal 

concentrations in streambed sediment prior to mining (Church 

and others, 2000; Church, Fey, and Unruh, this volume, 

Chapter E12).

Knowledge of background water quality in miningaffected areas can help establish cost-effective and technically 

feasible remediation goals for watersheds containing historical inactive mines. This concept is particularly important in 

areas where current water-quality standards may be lower 

than naturally occurring metal concentrations (Runnells and 

others, 1992). Several different approaches for estimating 

background metal contributions have recently been summarized by Alpers and Nordstrom (2000) and include statistical 

methods, examination of historical data, sediment sampling, 

geochemical modeling, comparison with analog areas, use of 

isotopic tracers, and mass-balance calculations. Because of 

the limitations and uncertainties associated with each of these 

approaches, Alpers and Nordstrom (2000) recommended that 

multiple approaches be used to help quantify premining conditions for a particular mining area. Determination of nonmining contributions of metals in historical mining areas can be a 

particularly challenging task because premining water-quality 

data from most mined areas are not available for comparison. 

In addition, most mineral deposits in relatively developed 

areas have been disturbed to some extent; thus, good analog sites for comparison with inactive mine sites are scarce 

(Maest, 1996).

Purpose and Scope

The purpose of this report is to identify and quantify 

dissolved constituent contributions from weathering of hydrothermally altered rock in unmined areas—herein referred to 

as background weathering—in the Animas River watershed 

study area. Water-quality samples were collected at more than 

300 stream, spring, and mine sites in the study area during 

summer low-flow conditions in 1995 and 1997–99 and were 

analyzed for major inorganic and selected trace-element constituents. Field measurements at each site included streamflow, 

specific conductance, pH, water temperature, and dissolved 

oxygen. These data were used to:

• Characterize the water quality of background springs 

and streams and compare to water quality of mine 

drainage and mining-affected surface water

• Determine the relation between background water 

quality and the degree of bedrock alteration

• Evaluate different qualitative and quantitative methods 

for estimating contributions of metals from background 

weathering to surface water.

The results of this study should improve our understanding 

of how background weathering processes control surface-water 

chemistry in a mineralized area. They also provide information 

that will contribute toward establishing water-quality standards 

and cost-effective, technically feasible remedia tion goals in the 

Animas River watershed study area. Further, the results will 

help guide future investi gations of background water quality 

in other geologically complex watersheds affected by historical 

mining activity.

Study Methods

Water-quality samples were collected at selected stream 

and spring sites throughout the watershed during summer low 

flow in 1995 and in 1997 through 1999. Because historical 

mining disturbance is so extensive throughout the study area 

(Church, Mast, and others, this volume, Chapter E5), determining whether a spring or stream has or has not been affected 

by mining is a challenge. Many of the water-quality sampling 

sites are obviously affected by historical mining activity, yet 

at other sites the extent to which mining activity has affected 

water quality is unclear. To address this issue, a ranking system 

was devised to evaluate the potential for the effects of mining 

on water quality (table 1). The ranking system consisted of four 

categories (I–IV), ranging from category I, having no evidence 

of mining activity, to category IV, having direct discharges 

from inactive mine sites. If a site appeared unaffected, but not 

unequivocally, the site was ranked category II. Conversely, 

sites that were not directly affected but had upgradient mining 

activity that likely affected the water quality were ranked as 

category III. Table 1 lists the many factors that were considered in the assignment of a category to each sampling site. 

An example of a category I site is a headwater stream or spring 

upgradient from any manmade disturbances. An example 

of a category II site is a spring along a valley side that has 

several dry prospect pits upgradient from it. An example of a 

category III site would be a stream or spring with an upgradient adit and mine-waste dump but no direct discharge or signs 

of direct discharge. Another example of a category III site is a 

spring in one subbasin that has a mine directly over the drainage divide that could influence the water quality of the spring. 

A category IV site would have obvious direct effects from mining upgradient or upstream from the site. The final assignment 

of category (whether I, II, III, or IV) was not a quantitative 

determination; however, the categories are considered to be the 

best assessment possible using the available information.

352 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 353

Of the 241 spring and stream sites sampled during the 

study, 108 sites were classified as category I, 38 sites as category II, 24 sites as category III, and 71 sites as category IV. 

Water-quality samples also were collected at 75 inactive mine 

sites for comparison with background water quality. Localities 

of streams, springs, and mine sites in the study area as well 

as the ranking information just discussed are in the study area 

database (Sole and others, this volume, Chapter G).

We collected samples for water-quality analyses by 

pumping water directly from the stream with polyvinyl tubing, through a 0.45-μm (micrometer) membrane filter, and 

into precleaned polyethylene bottles. A filtered aliquot for 

metal analyses was acidified to pH less than 2 using concentrated ultrapure nitric acid. A filtered, unpreserved aliquot 

was collected for sulfate analysis, and an unfiltered aliquot 

was collected for alkalinity. Field measurements at each site 

included discharge, specific conductance, pH, water temperature, and dissolved oxygen. Samples collected in 1995 were 

analyzed at the National Water Quality Laboratory according to methods in Fishman (1993), and results are published 

in the USGS National Water Information System (URL, 

http://waterdata.usgs.gov/nwis, accessed December 2002). For 

the 1997–99 samples, detailed descriptions of collection methods and analytical techniques and quality assurance data can be 

found in Mast, Evans, and others (2000). Major cation, silica, 

and dissolved metal concentrations were determined in the 

acidified samples by inductively coupled plasma–atomic emission spectrometry (ICP-AES). Alkalinity was determined by 

incremental titration within 5 hr of collection, and sulfate was 

determined by a turbidimetric method. Chemical results for all 

samples (including 1995) are in the relational database in Sole 

and others (this volume). Speciation calculations were made 

using the computer program PHREEQC (Parkhurst, 1995), 

and inverse geochemical models were solved with the NETPATH computer code (Plummer and others, 1994). Both computer programs were obtained from URL http://water.usgs.gov/

software/geochemical.html (accessed January 2002).

Geology, Alteration, and Mineralization

Because water quality is strongly controlled by geology, 

a brief discussion of bedrock geology, alteration, and mineralization of the Animas River watershed study area is presented 

in this section to provide the reader with a geologic framework for interpretation of background water quality. More 

detailed descriptions of geology and alteration and mineralization of the study area can be found in Yager and Bove (this 

volume) and Bove and others (this volume). The study area 

lies within the San Juan volcanic field of Tertiary age. The 

most prominent volcanic features of the area are the San Juan, 

Uncompahgre, and Silverton calderas, which formed about 

28 million years ago (Lipman and others, 1976; Bove and others, 2001). Thick volcanic sequences of lava flows, ash-flow 

tuffs, tuff breccias, conglomerates, and mudflow breccias 

make up most of the bedrock in the study area (Burbank and 

Luedke, 1969; Lipman and others, 1973; Ringrose, 1982). The 

unaltered lavas and tuffs generally are of intermediate composition and are composed of plagioclase, biotite, augite, quartz, 

and hornblende.

Subsequent to deposition and lithification, the volcanic 

bedrock in the study area was hydrothermally altered and 

mineralized to varying degrees (Burbank and Luedke, 1969) 

as shown by the distribution of major alteration assemblages 

in figure 1. The earliest hydrothermal event was related to 

resurgence of the San Juan and Silverton calderas and resulted 

Table 1. Categories for ranking water-quality sampling sites and information used in their assignment.

Categories in ranking system

I—No manmade disturbances upgradient or upstream from the water-quality sampling site

II—Some potential manmade disturbances upgradient or upstream from the water-quality sampling site

III—Some manmade disturbances upgradient or upstream from the water-quality sampling site

IV—Definite manmade disturbances upgradient or upstream from the water-quality sampling site

Information used in assignment of categories

Number of mines visibly draining water upgradient from sampling site

Number of mines (draining/not draining) upgradient from sampling site

Number of mine-waste dumps upgradient from sampling site

Number of prospects upgradient from sampling site

Number of shafts upgradient from sampling site

Inventory of exploration drill holes, abandoned mill sites, buildings and machinery, logging, grazing, roads upgradient from sampling site

References used for determination of categories:

• Direct observations

• Topographic maps

• Aerial photographs

• Published mine maps

• Written documentation

• Oral communication
in regional propylitic alteration of the bedrock (Burbank and 

Luedke, 1969). The propylitized bedrock underlies more than 

90 percent of the study area; in outcrop it is characteristically 

green to gray in color (fig. 2A). The alteration assemblage 

comprises primarily epidote, chlorite, albite, illite, and calcite 

and includes finely disseminated pyrite (Burbank and Luedke, 

1969).

The regional propylitic event was followed by three 

major episodes of magmatism, which were the source of most 

mineral deposition in the area (Casadevall and Ohmoto, 1977; 

Bove and others, this volume). Hydrothermal activity associated with these magmatic events superimposed more intense 

alteration assemblages (weak sericite-pyrite, quartz-sericitepyrite, and acid-sulfate) upon the earlier propylitic assemblage 

(fig. 1). The earliest of these magmatic events was caused by 

monzonite intrusive activity and resulted in a subeconomic 

porphyry copper-molybdenum deposit (Ringrose, 1982), 

which is situated between Middle and South Forks Mineral 

Creek (fig. 1). The most intensely altered area of this early 

phase is centered on peak 3,792 m, south of Middle Fork 

Mineral Creek, which owes its distinct red color to quartzsericite-pyrite altered bedrock at the center of the deposit 

(fig. 2B). The quartz-sericite-pyrite zone grades outward 

into a weak sericite-pyrite zone, which is characterized by 

metastable feldspars, sericite, pyrite, and occasional chlorite. 

Associated mineralized rock includes stockwork quartzmolybdenite-pyrite veinlets near the zone of most intense 

alteration, and polymetallic sulfide-bearing veins localized 

along fractures and faults on the periphery of the porphyry 

deposit (Ringrose, 1982). Minerals associated with the sulfidebearing veins include sphalerite, tetrahedrite-tennantite, 

galena, and pyrite.

Mineral Creek

3,792 m

Middle Fork

Cement Creek

Animas River

Red Mtn

Ohio Peak

Anvil Mountain

EXPLANATION

Streamflow-gauging station 

(site numbers from Chapter E11) 

Background (category I–II) water-quality sites 

(site numbers from table 8 and figure 12) 

A68

0

0

1

1

2

2

3

3

4 MILES

4 KILOMETERS 

Base from U.S. Geological Survey

1:100,000 Digital Line Graphs

Albers Equal-Area Conic projection

Standard parallels 37o30' and 40o30'

Central meridian 37o00

C48

A68

M34

107O 107 37'30" O45'

37O

52'

30"

Study area boundary

37O

45'

Red tributary

Prospect

Gulch

Houghton Mtn

Alteration assemblage

Acid-sulfate

Propylitic

Quartz-sericite-pyrite

Weak sericite-pyrite

MC71

MC30

CC86

CC36

CC29

CC53

CC50

UA40

Topeka 

Gulch

South Fork

MC70

CC133

CC132

MC82

MC81

MC76

MC73

MC86

Animas River

watershed 

study area

C O L O R A D O

Durango

Figure 1. Animas River watershed study area, with distribution of major alteration assemblages.

354 Environmental Effects of Historical Mining, Animas River Watershed, Colorado

'
Characterization of Background Water Quality 355

Later intrusions of dacite porphyry are related to a massive 

acid-sulfate hydrothermal system near Red Mountain and in the 

vicinity of Anvil Mountain and Ohio Peak (between Cement 

and Mineral Creeks). Much of the bedrock in this area is quartzsericite-pyrite altered and contains as much as 20 percent pyrite; 

it commonly weathers to bright-red and orange fields of talus 

(fig. 2C). Extensive acid-sulfate alteration zones, which contain 

quartz, alunite, pyrophyllite, dickite, and diaspore with as much 

as 30 percent pyrite, are superimposed on the quartz-sericitepyrite altered rock (Bove and others, 2000). Mineralization 

associated with the acid-sulfate alteration was localized along 

fault structures and hydrothermal breccia masses; dominant 

minerals are pyrite, sphalerite, galena, enargite, and tetrahedrite.

Later vein mineralization (post–20 Ma) was the cause 

of most economically important mineral deposits in the study 

area and appears to have been closely associated with intrusion 

of high-silica alkali rhyolite (Lipman and others, 1976). These 

veins are rich in pyrite and are mostly a polymetallic variety 

with variable proportions of chalcopyrite, galena, sphalerite, 

gold, and silver-bearing sulf-arsenide minerals (Nash, 1999). 

Manganese minerals including pyroxmangite and rhodochrosite are locally abundant in some veins. Adjacent to the vein, 

the wallrock is often altered to a quartz-sericite-pyrite assemblage. These envelopes of hydrothermally altered rock are 

narrow and typically are not more than twice the width of the 

vein (Bove and others, this volume).

Water-Quality Characteristics

We herein describe and compare water-quality characteristics of background and mining-affected surface water 

and drainage from selected mine sites in the Animas River 

watershed study area. For the purposes of this report, we 

combine the 108 category I and 38 category II sites into a 

group of 146 sites to represent background water quality in 

the study area. The rugged terrain of the watershed minimized 

mining-related features in the highest elevation areas; hence, 

many of the category I–II sites were located in headwater 

areas. Although some category III sites may be minimally 

affected by mining, category III and category IV sites were 

combined to represent mining-affected surface water in the 

watershed. In the assignment of category III and IV rankings, no consideration of distance from mine sites was made, 

despite the fact that metal concentrations can attenuate 

considerably downstream from mine contributions because 

of mixing and instream chemical reactions. Although more 

than 5,300 mining-related features have been mapped in the 

watershed (Church, Mast, and others, this volume), only about 

170 mines have surface drainage (Peter Butler, Robert Owen, 

and William Simon, Unpublished report to Colorado Water 

Quality Control Commission, Animas River Stakeholders 

Group, 2001), of which 75 were sampled for water-quality 

analyses as part of this study (see Church, Mast, and others, this volume). Of these 75 sites, 20 are among a group of 

32 mine sites that have been prioritized for remediation in the 

Figure 2. Areas of varied alteration. A, propylitized bedrock 

on east side of Cement Creek; B, subeconomic porphyry coppermolybdenum deposit centered on peak 3,792 m; C, acid-sulfate 

alteration in headwaters of Prospect Gulch.

A

C

B

3,792 m

Animas River watershed by the Animas River Stakeholders 

Group (Unpub. report to Colorado Water Quality Control 

Commission, ARSG, 2001). These 32 sites represent the largest point sources of metals in the study area and account for 

nearly 80 percent of the annual metal loading to surface water 

from mining-related sources (Unpub. report to Colorado Water 

Quality Control Commission, ARSG, 2001).
Background Streams and Springs

Statistical summaries of dissolved constituent concentrations for background streams and springs (category I and II 

sites) are in table 2, and site locations are shown in figure 1. 

Of the 146 sites sampled, 90 were streams and 56 were 

springs. The background sites had a wide variation in chemical composition; pH ranged from 2.58 to 8.49, and specific 

conductance ranged from 12 to 2,180 μS/cm. All the sampled 

streams were well oxygenated (dissolved oxygen 6–9 mg/L), 

but many of the springs had low (<5 mg/L) dissolved oxygen 

concentrations. The low dissolved oxygen concentrations 

may indicate that many springs are fed by oxygen-depleted 

ground water discharging at the surface along faults or 

fractures. Springs and streams were dominantly calciumsulfate type water. Sulfate concentrations ranged from 1 to 

1,300 mg/L, and calcium concentrations ranged from 0.8 to 

550 mg/L. Sites with high pH values (pH>6) typically had 

measurable concentrations of alkalinity (4–69 mg/L) and low 

aluminum and iron concentrations, whereas sites with low pH 

values (pH<6) had little measurable alkalinity and elevated 

concentrations of aluminum and iron (fig. 3). Other dissolved 

metals detected in most of the background samples include 

barium, copper, manganese, strontium, and zinc. Manganese 

was detected in 97 percent of samples, with concentrations 

ranging from less than 3 to 74,700 μg/L. Zinc and copper 

were detected in more than one-half the samples and reached 

concentrations as high as 14,400 μg/L and 372 μg/L, respectively. Other trace metals, including beryllium, chromium, 

cadmium, lead, lithium, nickel, and vanadium, were below 

detection in more than 90 percent of the background samples. 

Trace-metal concentrations showed patterns similar to those 

of aluminum and iron; the highest concentrations were at sites 

with lowest pH. For example, zinc was detected in more than 

80 percent of samples with pH less than 4.5 but in only 30 percent of samples with pH greater than 4.5. Similarly, copper 

was detected in 69 percent of samples with pH less than 4.5 

but in only 20 percent of samples with pH greater than 4.5. 

At the background sites, concentrations of several metals, 

including aluminum, copper, manganese, and zinc, were high 

enough to be potentially toxic to aquatic organisms (Colorado 

Water Quality Control Commission, 2001). Zinc and copper 

Table 2. Summary statistics for dissolved constituent concentrations in background water-quality samples (category I–II) in the 

Animas River watershed study area.

[<, less than; ft3/s, cubic feet per second; μS/cm, microsiemens per centimeter at 25°C; mg/L, milligrams per liter; μg/L, micrograms per liter; CaCO3, calcium 

carbonate; number of samples, 146]

Constituent Minimum 25th 

percentile Median 75th percentile Maximum

Discharge, ft3

/s 0.001 0.020 0.069 0.50 7.46

Specific conductance, μS/cm 12 131 270 573 2,180

pH in standard units 2.58 3.60 4.89 6.83 8.49

Dissolved oxygen, mg/L 0.0 6.2 7.3 8.2 16.3

Alkalinity, mg/L as CaCO3 <0.5 <0.5 <0.5 17.8 69.0

Sulfate, mg/L 1 41 90 230 1,300

Calcium, mg/L 0.8 14.1 27.6 47.3 550

Magnesium, mg/L 0.1 1.5 3.2 6.0 34.0

Sodium, mg/L <0.1 0.8 1.5 3.7 13.0

Potassium, mg/L 0.1 0.3 0.5 0.8 2.8

Silica, mg/L 0.8 2.4 5.8 15.6 53.0

Aluminum, μg/L <40 <40 359 4,130 71,400

Barium, μg/L <2 12 22 34 101

Beryllium, μg/L <1 <1 <1 <1 65

Cadmium, μg/L <2 <2 <2 <2 84

Chromium, μg/L <15 <15 <15 <15 50

Copper, μg/L <4 <4 <4 14 372

Iron, μg/L <30 <30 49 2,600 117,000

Lead, μg/L <30 <30 <30 <30 141

Lithium, μg/L <6 <6 <6 <6 43

Manganese, μg/L <3 4 191 958 74,700

Molybdenum, μg/L <10 <10 <10 <10 71

Nickel, μg/L <20 <20 <20 <20 44

Strontium, μg/L 6 89 236 472 5,700

Vanadium, μg/L <4 <4 <4 <4 11

Zinc, μg/L <20 <20 28 194 14,400

356 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 357

concentrations exceeded acute aquatic-life standards in 32 and 

23 percent of samples, respectively, and chronic aquatic-life 

standards in 34 and 27 percent of samples, respectively. Manganese exceeded chronic aquatic-life standards in less than 

10 percent of samples, whereas aluminum exceeded chronic 

aquatic-life standards in more than 50 percent of samples.

Statistical comparison of background stream and spring 

groupings using a Wilcoxon Signed-Ranks test indicated that 

spring samples were slightly more acidic and more concentrated than stream samples (p<0.01). The median pH of spring 

samples was 4.15, compared to a median pH of 6.11 for the 

stream samples. The median specific conductance of springs 

was 444 μS/cm compared to 230 μS/cm for the streams. Of 

the metals, only iron and manganese concentrations were 

statistically higher in the springs compared to the streams. The 

median concentrations of iron and manganese were 83 and 

179 μg/L in the springs compared with 34 and 74 μg/L in the 

streams, respectively. These slight differences in chemistry 

probably reflect greater water-rock interaction and differing 

redox conditions in the spring environment compared to the 

stream channel, as well as less dilution by surface inflows.

A Spearman (nonparametric) correlation matrix was 

constructed to analyze relations among dissolved constituent 

concentrations in background streams and springs (table 3). 

Inspection of the correlation matrix indicated a high degree 

of collinearity within two dominant clusters of variables. 

In one cluster, strong positive correlations (r>0.550) were 

found among major cations and sulfate, with the exception 

of the correlation between calcium and potassium (r=0.453). 

Silica also was positively correlated with sulfate and major 

cations, with the exception of calcium (r=0.322). This cluster 

of related variables represents the most important dissolution 

products of mineral weathering. Pyrite and calcium sulfate 

minerals such as anhydrite and gypsum are the primary 

sources of sulfate, whereas major cations and silica primarily 

are derived from dissolution of carbonate and silicate minerals 

in the volcanic rock. The strong correlation between calcium 

and strontium (r=0.818) and weak correlation between calcium and silica (r=0.322) indicate that most calcium is probably derived from weathering of calcite and possibly gypsum 

rather than silicate minerals. In the second cluster of variables, 

strong positive correlations were found among sulfate, aluminum, iron, manganese, and zinc. Associations of metals with 

sulfate reflect the oxidation of pyrite and associated mineral 

deposits. Several metals also had strong negative correlations 

with pH (or positive correlations with hydrogen ion) because 

their solubility and adsorption characteristics are strongly 

controlled by pH.

0

300

600

900

1,200

1,500

0

20

40

60

80

100

Sulfate

Alkalinity as CaCO3

SULFATE, IN MILLIGRAMS 

PER LITER

ALKALINITY, IN MILLIGRAMS

PER LITER

0.01

0.1

1

10

100

0.01

0.1

1

10

100

1,000

23456789

Aluminum

Iron

pH, IN STANDARD UNITS

ALUMINUM, IN MILLIGRAMS 

PER LITER

IRON, IN MILLIGRAMS 

PER LITER

Figure 3. Dissolved sulfate, alkalinity, aluminum, and iron concentrations 

as a function of pH for background water-quality samples from Animas River 

watershed study area, 1997–99.
Although sampling-site density was somewhat uneven 

across the watershed, some spatial patterns in water quality 

are apparent, as illustrated by the maps in figure 4. Among 

the three major basins (upper Animas River, Cement Creek, 

and Mineral Creek), streams and springs in the upper Animas 

River basin had distinctly higher pH values than those in the 

Cement and Mineral Creek basins. The median pH of background sites in the upper Animas River basin was 6.97, compared to the more acidic Cement and Mineral Creek basins, 

which had median pH values of 4.58 and 4.61, respectively. 

Although not shown in figure 4, the pattern for alkalinity was 

similar to that of pH. For example, the median alkalinity was 

32 mg/L in the upper Animas River basin compared to less 

than 0.1 mg/L in the more acidic basins. The neutral water 

samples in the Animas River are attributed to the presence 

of carbonate minerals in the propylitically altered lavas that 

underlie most of this basin. Dissolved metals as illustrated 

by the spatial pattern in copper concentrations were typically 

lowest in the upper Animas River basin (fig. 4). This may be 

related to the higher pH of the surface water in that basin, or 

it may reflect fewer metal-rich sources compared with the 

other two basins. The exception to this pattern in dissolved 

metal concentrations was zinc, which tends to act more conservatively at high pH than other dissolved metals. Some of 

the most acidic and metal-rich background water was in the 

western part of the study area, particularly including streams 

and springs draining the mountains situated between Cement 

and Mineral Creeks and the area surrounding peak 3,792 m 

between South and Middle Forks Mineral Creek (fig. 1). 

Bedrock in both areas is extensively silicified and altered 

(Bove and others, this volume) and contains large amounts of 

disseminated pyrite (as much as 20 volume percent). Streams 

and springs draining these areas were generally characterized 

by low pH, high sulfate concentrations, and elevated levels 

of metals, particularly copper (fig. 4), manganese, and zinc 

(data not shown in fig. 4). Sodium (and silica) concentrations 

also were elevated in the vicinity of peak 3,792 m relative to 

other parts of the study area, perhaps because of weathering 

of the secondary albite that has replaced plagioclase during 

subsequent alteration events (Bove and others, this volume). 

Because the albite tends to be fine grained and is present 

throughout the groundmass, it may be more susceptible to 

weathering than the primary plagioclase grains.

To compare with other mineralized settings, water-quality

data from background sites in the Animas River watershed 

study area are listed with water-quality data from mineralized 

but unmined areas in Colorado and Alaska (table 4). Water 

quality in the mineralized Summitville area in the eastern part 

of the San Juan Mountains was similar to the Animas River 

watershed study area for both major ion and dissolved metal 

concentrations. Both areas showed relatively high sulfate and 

calcium concentrations, and the dominant trace metals were 

manganese, zinc, and copper. This is not surprising, considering that the Summitville area is situated in the same volcanic 

field as the Animas River watershed study area and has undergone similar styles of alteration and mineralization (Miller and 

McHugh, 1994; Bove, 1996).

Geneva Basin in the Colorado Front Range is underlain 

by Precambrian gneiss and granite, which have been intruded 

by Tertiary dikes, sills, and stocks. Extensive pyritic alteration is associated with the Tertiary intrusions, and mineralization resulted mainly in small lead-zinc-silver veins (Bassett 

and others, 1992). Compared to the Animas River watershed 

study area, surface water in Geneva Basin had substantially 

lower calcium concentrations, yet higher concentrations of 

other major weathering products (not shown in table 4). This 

primarily reflects weathering of silicate minerals in the gneiss 

and granite that is accelerated by natural acidity produced by 

Table 3. Spearman rank correlation coefficients (r values) showing the relation among dissolved constituent concentrations for background 

water-quality samples (category I–II) in the Animas River watershed study area.

[SO4, sulfate; Ca, calcium; Mg, magnesium; Na, sodium; K, potassium; Si, silica; Al, aluminum; Ba, barium; Cu, copper; Fe, iron; Mn, manganese; Ni, nickel; 

Sr, strontium; Zn, zinc; r values greater than 0.550 shown in shaded cells]

pH SO4 Ca Mg Na K Si Al Ba Cu Fe Mn Ni Sr

SO4 –.505

Ca .014 .766

Mg –.446 .923 .743

Na –.184 .618 .565 .620

K –.506 .684 .453 .715 .657

Si –.731 .695 .322 .638 .667 .731

Al –.838 .560 .092 .540 .264 .620 .753

Ba .130 –.346 –.297 –.254 –.324 –.150 –.282 –.210

Cu –.588 .384 .093 .346 .062 .382 .401 .558 –.074

Fe –.726 .596 .195 .539 .282 .521 .667 .730 –.198 .447

Mn –.731 .715 .326 .689 .361 .623 .699 .857 –.264 .541 .703

Ni –.216 .159 –.049 .115 –.170 .206 .067 .412 –.078 .299 .343 .302

Sr .177 .560 .818 .594 .408 .228 .061 –.056 –.065 –.087 .205 .153 .061

Zn –.564 .580 .299 .602 .234 .580 .486 .690 –.244 .545 .438 .706 .413 .109

358 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 359 Figure 4. pH and dissolved concentrations of sulfate, copper, and sodium in background water-quality samples from Animas River watershed study area, 1997–99.

pH, in standard units Sulfate, in milligrams per literCopper, in micrograms per liter Sodium, in milligrams per liter

Less than 3.53.5-4.54.5-6.0Greater than 6.0

Less than 5050-100100-200Greater than 200

Less than 44-2020-50Greater than 50

Less than 11-22-4Greater than 4

Cement

Creek

Animas

River

Mineral

Creek
pyrite oxidation (Bassett and others, 1992). Dissolved metal 

concentrations were fairly similar between the Animas River 

watershed study area and Geneva Basin, perhaps reflecting 

similarities in the polymetallic vein deposits that occur in 

each area.

The Drenchwater and Lik deposits are shale-hosted 

silver-lead-zinc, massive sulfide deposits in the Brooks Range 

of northern Alaska. Despite different lithologies and deposit 

types than found in the Animas River watershed, this area 

was included in the comparison because it is one of only 

a few areas in the United States where water-quality studies were conducted prior to mining. Drenchwater deposit is 

acid producing and generates metal concentrations in surface water similar to those measured in the Animas River 

watershed study area (Kelley and Taylor, 1997). The only 

notable differences in water quality between the two areas 

were substantially lower concentrations of calcium and silica 

in the Drenchwater streams compared to the Animas River 

watershed study area. The Lik deposit yields nonacidic surface 

water with low dissolved metal concentrations, with the exception of zinc, compared to both the Drenchwater deposit area 

and the Animas River watershed study area. The water quality 

of the Lik deposit area is attributed to the presence of carbonate bedrock and abundant carbonate alteration minerals at Lik, 

which buffers the pH of the streams (Kelley and Taylor, 1997).

Lake chemistry in the Weminuche Wilderness in 

Colorado also was included in table 4 to provide comparable 

data for an unmineralized area with similar watershed characteristics to those of the study area, including topography, climate, and vegetation (Turk and others, 1993). The wilderness 

is located in the San Juan Mountains immediately south of the 

Animas River watershed study area but is outside the zone of 

extensive alteration/mineralization and drains metamorphic 

bedrock rather than volcanic bedrock. Surface water in the 

Weminuche Wilderness is dilute calcium-bicarbonate water 

containing very low concentrations of metals. Average sulfate 

concentrations in the study area were 300 times greater than 

in the adjacent wilderness, and average zinc concentrations, 

even in nonacidic surface water, were as much as 2,000 times 

greater in the study area than in the Weminuche Wilderness. 

These results illustrate striking differences in water quality 

between adjacent unmineralized and mineralized areas and 

clearly show that in mineralized areas, background metal 

concentrations in surface water can be substantially elevated 

because of background weathering of altered bedrock.

Mine Drainage and Mining-Affected 

Surface Water

Statistical summaries of dissolved constituent concentrations for drainage from 75 mines in the Animas River 

watershed study area that were sampled as part of this study 

are presented in table 5. As mentioned previously, although 

this group of mines represents less than one-half of the 

170 draining mine sites in the study area, it includes 20 of the 

32 draining adits with the largest metal loads (Unpub. report 

to Colorado Water Quality Control Commission, ARSG, 

2001). Similar to background streams and springs, water quality at the sampled mine sites was quite variable; pH ranged 

from 2.35 to 7.77 and specific conductance ranged from 180 

to 3,520 μS/cm. Mine drainage was dominantly calciumsulfate water, in which sulfate ranged from 45 to 2,720 mg/L 

and calcium from 2 to 460 mg/L. Many samples contained 

elevated concentrations of aluminum (as much as 71,400 μg/L) 

and iron (as much as 686,000 μg/L). Nearly one-half the mines 

had low levels of dissolved oxygen (0–5.5 mg/L), indicating 

that flow from these adits may be derived from deep fracture 

systems in the bedrock or that pyrite oxidation was depleting 

the dissolved oxygen. Copper was detected in about one-half 

of the mine-water samples, but only 10 percent of samples 

had concentrations exceeding 1,000 μg/L. Although zinc was 

Table 4. Comparison of selected dissolved constituents in surface water draining selected mineralized but unmined areas in Colorado and

Alaska.

[Spec. cond., specific conductance; μS/cm, microsiemens per centimeter at 25°C; mg/L, milligrams per liter; μg/L, micrograms per liter; <, less than; --, not 

reported]

Unmined, 

mineralized areas pH Spec. cond.(μS/cm)

Sulfate

(mg/L)

Calcium

(mg/L)

Copper

(μg/L)

Manganese

(μg/L)

Lead

(μg/L)

Zinc

(μg/L)

Upper Animas River Basin, Coloradoa 2.6–8.5 12–2,180 1–1,300 1–550 <4–372 <3–74,670 <30–141 <20–14,380

Summitville, Coloradob 2.5–8.5 50–2,400 6–1,250 6–170 <1–370 <10–15,000 <1–4 5–1,800

Geneva Basin, Coloradoc 3.1–7.3 46–830 5.7–370 2–18 2–440 10–5,500 -- 2–4,800

Drenchwater, Alaskad 2.8–7.0 38–2,150 12–1,180 5–23 <0.9–260 3–3,400 <0.3–10 4–2,600

Lik deposit, Alaskad 6.2–8.3 180–400 26–127 27–63 <10 <1–330 <10 <3–2,000

Weminuche Wilderness, unmineralized 

area, San Juan Mountains, Coloradoe

5.2–8.7 4–22 0.7–5.5 0.4–3.3 0.2–0.4 1.8–7.2 0.1–1.5 0.5–1.2

a

This study.

b

Miller and others, 1999.

c

McHugh and others, 1988.

d

Kelley and Taylor, 1997.

e

U.S. Geological Survey, unpublished data, 2000. 

360 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 361

detected in more than 90 percent of adits, only 40 percent 

reached concentrations in excess of 1,000 μg/L. Other trace 

metals, including beryllium, cadmium, chromium, lead, 

lithium, nickel, and vanadium, were below detection in more 

than 50 percent of the sampled mine-drainage samples. On 

the basis of the mine-water classification scheme of Ficklin 

and others (1992), 40 percent of the mine-drainage samples 

would be classified as “near neutral, low metal” water types, 

and 20 percent as “acid, low metal” water types (fig. 5). 

Despite low base-metal concentrations in the “acid, low metal” 

group, many of these samples had elevated concentrations of 

dissolved iron, aluminum, and manganese. Approximately 

15 percent of mine-drainage samples were classified as “near 

neutral, high metal” types. Many of these mines were associated with vein deposits located in areas where the surrounding 

bedrock had sufficient acid-neutralizing capacity to neutralize acidity produced by pyrite oxidation at the mine site. The 

elevated dissolved metal concentrations reflected the influence of other sulfide minerals such as sphalerite and chalcopyrite in the mineralized veins. The remaining 25 percent of 

mines were classified as “acid, high metal” and “high acid, 

high metal.” Many of the most acidic mine sites are in the 

intensely altered Red Mountain area, which is underlain by 

an extensive area of acid-sulfate hydrothermal alteration with 

associated polymetallic veins and breccia pipes (Bove and 

others, 2000). The high acidity of these mines reflects the low 

acid-neutralizing capacity of the acid-sulfate altered bedrock. 

Only one adit, the Koehler tunnel, fell in the range of the “high 

acid, extreme metal” water type. A more detailed discussion 

of mine-water chemistry and its relation to deposit type in the 

Animas River watershed study area can be found in Bove and 

others (this volume).

Although dissolved metal concentrations were elevated 

at some background sites in the study area, mine-drainage 

samples generally had higher dissolved metal concentrations 

than background sites. Results of a statistical comparison of 

background surface water (category I–II sites) with minedrainage samples using the nonparametric Wilcoxon SignedRanks test are shown in table 6. This test was used rather than 

the parametric t-test due to the non-normal distribution of the 

chemical data sets. Results for comparison of background 

samples (category I–II sites) with mine-drainage samples 

show statistically significant differences (α=0.01) in concentrations for all the major ions (except potassium) and the 

Table 5. Summary statistics for dissolved constituent concentrations in mine-drainage samples from the Animas River watershed study area.

[<, less than; ft3/s, cubic feet per second; μS/cm, microsiemens per centimeter at 25°C; mg/L, milligrams per liter; μg/L, micrograms per liter; CaCO3, calcium 

carbonate; number of samples, 75]

Constituent Minimum 25th 

percentile Median 75th percentile Maximum

Discharge, ft3

/s 0.001 0.010 0.036 0.091 1.03

Specific conductance, μS/cm 180 474 741 1,090 3,520

pH in standard units 2.35 3.44 5.74 6.71 7.77

Dissolved oxygen, mg/L 0.0 1.6 5.5 8.2 11.6

Alkalinity, mg/L as CaCO3 <0.5 <0.5 6.5 63.3 137

Sulfate, mg/L 45 169 309 509 2,720

Calcium, mg/L 2.0 36.8 79.6 164 460

Magnesium, mg/L 0.7 3.9 6.3 12.0 42.0

Sodium, mg/L 0.3 2.0 4.2 6.0 19.4

Potassium, mg/L 0.4 0.6 0.8 1.3 6.2

Silica, mg/L 2.0 5.5 10.0 16.0 30.0

Aluminum, μg/L <40 42 616 4,700 71,400

Barium, μg/L <2 6 10 15 62

Beryllium, μg/L <1 <1 <1 <1 6

Cadmium, μg/L <2 <2 <2 12 780

Chromium, μg/L <15 <15 <15 <15 400

Copper, μg/L <4 <4 6 89 98,600

Iron, μg/L <30 225 4,650 17,800 686,000

Lead, μg/L <30 <30 <30 <30 1,379

Lithium, μg/L <6 <6 <6 18 56

Manganese, μg/L <3 585 1,360 3,880 23,700

Molybdenum, μg/L <10 <10 <10 <10 42

Nickel, μg/L <20 <20 <20 <20 300

Strontium, μg/L 37 299 809 2,120 6,080

Vanadium, μg/L <4 <4 <4 <4 5

Zinc, μg/L <20 135 621 2,860 228,000
dissolved metals barium, copper, iron, manganese, strontium, 

and zinc. For constituents with statistically significant differences, concentrations in the mine-drainage samples were 

higher than in the background samples with the exception of 

barium. Higher concentrations in the mine-drainage samples 

were not unexpected considering that chemical-weathering 

processes commonly are accelerated at mine sites because of 

greater oxygen availability and greater contact with freshly 

exposed mineral surfaces (Nordstrom and Alpers, 1999). 

Lower barium concentrations in mine drainage may reflect 

solubility controls on barium resulting from high concentrations of sulfate in the mine samples (Davis and others, 2000). 

Aluminum was not significantly different between the background and mine-drainage sample groups, perhaps because pH 

also was not significantly different between the two groups.

A statistical comparison of background surface water 

(category I–II sites) with mining-affected surface water 

(category III-IV sites) using the nonparametric Wilcoxon 

Signed-Ranks test also is shown in table 6. Results show 

statistically significant differences (p>0.01) in concentrations 

for copper, manganese, and zinc (table 6), which were generally higher in mining-affected sites than at background sites. 

No statistically significant differences in concentration were 

found for the remaining constituents except silica. The lack 

of distinction between the background and mining-affected 

streams may be due in part to attenuation of pH-dependent 

metals as mine drainage is mixed with dilute and higher pH 

surface water. By contrast, the elevated zinc and manganese 

concentrations in mining-affected water may reflect the tendency of these metals not to sorb or coprecipitate on particles 

at near-neutral pH values.

Box plots were constructed to compare the water quality 

of background sites with that of mine-drainage sites in each of 

the three major basins (fig. 6). Background sites include the 

0.01

0.1

1

10

100

1,000

02 468

acid, high metal near neutral,

high metal

acid, low metal

high acid, 

extreme metal

near neutral, low metal

pH, IN STANDARD UNITS

SUM OF BASE METALS, 

IN MILLIGRAMS PER LITER

high acid, 

high metal

Figure 5. Sum of dissolved base-metal concentrations (zinc, copper, 

cadmium, lead, nickel) as a function of pH for mine-drainage samples from 

Animas River watershed study area, 1997–99.

146 category I and II sites; mine-drainage sites included the 

75 mine sites sampled as part of this study. Monthly samples 

collected at streamflow-gauging stations at the outlet of each 

basin (Animas River above Silverton, A68; Cement Creek, 

C48; and Mineral Creek, M34) were included for comparison 

(fig. 1, location of gauges). For more detailed information 

on sample-collection methods and analytical results at the 

streamflow-gauging stations, the reader is referred to Leib 

and others (this volume, Chapter E11). Results in figure 6 

show substantial differences in water quality among the three 

basins. As noted previously, background samples in the upper 

Animas River basin had higher pH and lower sulfate, silica, 

and dissolved metal concentrations, except for zinc, compared 

with background samples in the Cement Creek and Mineral 

Creek basins. This most likely reflects the larger areal extent 

of propylitically altered rocks in the upper Animas River basin 

(Yager and Bove, this volume), which have a lower sulfide 

content and greater capacity to neutralize acidity than the more 

intensely altered mineral assemblages in other parts of the 

study area. Comparison of mine-drainage samples revealed 

that mine drainage in the Cement Creek and Mineral Creek 

basins was similar, with the exception of sodium, which 

was slightly higher in Mineral Creek, and sulfate and iron, 

which were higher in Cement Creek. In contrast, mines in the 

Animas River had substantially higher pH values and lower 

sulfate, magnesium, silica, aluminum, iron, and copper concentrations compared to mine drainage in the other two basins. 

Zinc was the only metal that was similar in concentration 

among the three basins. The differences in aluminum and iron 

concentrations are clearly related to pH, whereas variations in 

base-metal concentrations, particularly copper and manganese, 

may reflect differences in the chemical composition and mineralogy of mineral deposits within each basin. More aggressive weathering conditions in the acidic mines are probably 

362 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 363

the cause of higher silica and aluminum concentrations in the 

Cement Creek and Mineral Creek mines compared to mines in 

the upper Animas River basin (Nordstrom and Alpers, 1999).

Because stream water at the outlet of each basin is influenced by both background and mining-related sources of metals, concentrations measured at the gauging stations might be 

expected to fall between the range of concentrations measured 

at the background and mine-drainage sampling sites. This pattern is generally observed for the Animas River and Cement 

Creek basins but not always for Mineral Creek. In the Animas 

River, the ranges of concentrations at the gauging station and 

the background sites were similar except for manganese and 

zinc. These metals were higher at the gauging station and were 

more similar to concentrations measured in mine-drainage 

samples than to concentrations in the background samples. 

In Cement Creek, the ranges of concentrations at the gauging 

station were bracketed by the ranges of concentrations at the 

background and mine sites. In contrast, the range of concentrations measured at the Mineral Creek gauging station was 

not bracketed by the other two groups for pH, sodium, silica, 

and sulfate. These differences may be partly an artifact of 

sampling locations in this basin, which had the highest density 

of sites in the intensely altered area around peak 3,792 m. In 

addition, water quality at the Mineral Creek gauging station is 

influenced by the contribution of large volumes of dilute, highpH water from South Fork Mineral Creek, which contributes 

more than 25 percent of the streamflow from this basin (Leib 

and others, 2003).

Relation Between Geology 

and Background Water Quality

To explore the relation between geology and water 

quality, background sites were grouped by the dominant 

alteration assemblage upstream from the sampling site on 

the basis of the major hydrothermal alteration assemblages 

mapped in the study area (fig. 1). Of the 146 samples, four 

water-quality sites were assigned to the acid-sulfate (AS) 

assemblage, 17 to weak sericite-pyrite (WSP), 33 to quartzsericite-pyrite (QSP), and 69 to propylitic (PROP). Thirty-six 

of the PROP sites were further subdivided into a propylitic 

with vein-related alteration assemblage (PROP-V) because of 

the presence of large mineralized structures upgradient from 

the sites. Twenty-three sites were not assigned to an alteration 

assemblage because they drain areas underlain by a mixture of assemblages. For this study, the QSP group includes 

samples draining either QSP alteration and vein-related QSP 

alteration assemblages as mapped by Bove and others (this 

volume). Background springs and streams in the study area 

had a wide range of compositions that were spatially related to 

the degree of bedrock alteration (fig. 7). Streams and springs 

draining propylitically (PROP) altered rock had higher pH 

values (5.74–8.49) and relatively low dissolved metal concentrations (zinc, <20–237 μg/L; copper, <4–73 μg/L). Although 

not shown in figure 7, these sites also were characterized by 

measurable alkalinity (1.4–68 mg/L) and lower dissolved iron 

(30–310 μg/L) and aluminum (40–140 μg/L) concentrations. 

Propylitically (PROP) altered rock, which occurs throughout the study area, contains as much as 30 percent calcite 

(Bove and others, this volume), which dissolves to produce 

the neutral surface-water composition characteristic of this 

alteration assemblage. Despite the relatively high pH of these 

samples, most also had relatively high sulfate concentrations 

(>20 mg/L) relative to atmospheric deposition (<0.5 mg/L; 

Mast and others, 2001). These elevated sulfate concentrations 

indicate that disseminated pyrite in the propylitic bedrock also 

is an important source of solutes to surface water, although in 

this alteration assemblage calcite is sufficient to neutralize any 

acidity produced by the oxidizing pyrite. Some sulfate also 

may be derived from calcium sulfate minerals such as gypsum 

and anhydrite, which are common in some parts of the study 

area (Casadevall and Ohmoto, 1977; Bove and others, this 

volume).

In contrast to the propylitic assemblage, the QSP 

alteration assemblage generated acidic surface water (pH 

2.70–6.16) with higher concentrations of iron (as much as 

77 mg/L), reflecting an abundance of pyrite and a lack of 

acid-neutralizing minerals, particularly calcite. This acidic 

water also reacts readily with aluminosilicate minerals in the 

bedrock and can contain high concentrations of aluminum 

(as much as 66 mg/L) and silica (as much as 28 mg/L). The 

QSP samples also were enriched in zinc, copper, and manganese relative to the PROP samples because of the base-metal 

sulfide minerals associated with this alteration assemblage. 

Comparison of QSP samples from the subeconomic porphyry 

Table 6. Results from Wilcoxon Signed-Ranks test comparing 

dissolved constituent concentrations in background water-quality 

samples (category I–II) with mine-drainage samples and miningaffected surface water samples (category III–IV) in the Animas 

River watershed study area.

[p-values in bold indicate a statistically significant difference in concentration 

between the background and mining-affected sample groups at the 0.01 confidence level; <, less than]

Constituent

p-value 

for comparison 

with mine drainage 

p-value 

for comparison 

with mining-affected 

surface water

pH 0.116 0.932

Specific conductance <.001 .660

Sulfate <.001 .706

Calcium <.001 .376

Magnesium <.001 .758

Sodium <.001 .030

Potassium .006 .907

Silica .068 <.001

Aluminum .954 .898

Barium <.001 .733

Copper .019 <.001

Iron <.001 .424

Manganese <.001 .007

Nickel .107 .389

Strontium <.001 .554

Zinc <.001 <.001
ANIMAS CEMENT MINERAL

0

500

1,000

1,500

3

5

7

0

200

400

600

800

1,000

0

100

200

300

400

0

5

10

15

20

25

0

2

4

6

8

10

0

10

20

30

40

0

5

10

15

0

20

40

60

80

0

0.05

0.10

0.15

0.20

0

1

2

3

4

0

2

4

6

8

A68

Cat I–II

Mines

C48

Mines

Cat I–II

M34

Mines

Cat I–II

Cat I–II

C48

Mines

M34

Cat I–II

Mines

Cat I–

A68

Mines

II

Cat I–II

C48

Mines

M34

Cat I–II

Mines

ANIMAS CEMENT MINERAL ANIMAS CEMENT MINERAL

EXPLANATION Median

25th percentile

75th percentile

5th percentile

95th percentile

A68

Cat I–II

Mines

COPPER, IN MILLIGRAMS PER LITER

MANGANESE, IN MILLIGRAMS 

PER LITER

ZINC, IN MILLIGRAMS 

PER LITER

IRON, IN MILLIGRAMS 

PER LITER

SODIUM, IN MILLIGRAMS 

PER LITER

SULFATE, IN MILLIGRAMS 

PER LITER

ALUMINUM, IN MILLIGRAMS 

PER LITER

MAGNESIUM, IN MILLIGRAMS 

PER LITER pH, IN STANDARD UNITS

SILICA, IN MILLIGRAMS PER LITER CALCIUM, IN MILLIGRAMS PER LITER

SPECIFIC CONDUCTANCE, IN

MICROSIEMENS PER CENTIMETER

Figure 6. Comparison of dissolved constituent concentrations in background water-quality samples (category I–II), streamflowgauging stations (A68, C48, M34), and mine-drainage samples (Mines) from the three major basins (upper Animas River, Cement 

Creek, Mineral Creek) of Animas River watershed study area, 1997–99.

364 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 365

copper-molybdenum deposit near peak 3,792 m with the 

acid-sulfate alteration near Red Mountain revealed no statistical differences in background water quality between 

these two deposit types. The AS assemblage was only represented by four samples; however, the AS samples showed 

a water-quality pattern distinctly different from that of the 

QSP alteration. Although the range of pH values was similar, 

sulfate concentrations were more than 10 times higher in the 

QSP samples than in the AS samples, and iron concentrations 

were more than 100 times higher. Median concentrations of 

copper and zinc were 31 and 201 μg/L, respectively, in the 

QSP samples, compared with detection-limit values in all but 

one AS sample. The AS sites may have lower concentrations 

because they may drain the surface of the acid-sulfate deposit, 

where post-mineralization oxidation has removed most of the 

sulfide minerals, leaving primarily silica (Plumlee and others, 

1999). In contrast to this small group of AS samples, Bove and 

Knepper (2000) reported very high concentrations of metals 

at background sites draining an acid-sulfate assemblage in the 

headwaters of the Uncompahgre River north of Red Mountain. 

One explanation for the higher concentrations of metals in 

these samples compared to the four samples from the study 

area is that surface water in the area north of Red Mountain 

contacts the sulfide-rich core of the acid-sulfate altered zone 

rather than just the oxidized surface.

Samples from streams that drain WSP-altered rock are 

from localities primarily near the margins of the peak 3,792 m 

porphyry deposit; they generally were intermediate in composition between the QSP and PROP samples, perhaps reflecting a greater abundance of reactive minerals such as chlorite, 

feldspar, and calcite than occurs in the QSP assemblage. 

Although base-metal concentrations were elevated in only a 

few WSP samples, most had sulfate concentrations similar to 

that of the QSP samples. Some of the highest pH samples in 

this alteration assemblage had sulfate concentrations above 

1,000 mg/L and relatively low zinc and copper concentrations. 

This water-quality signature may be a result of the dissolution of vein-filling gypsum or anhydrite (Bove and others, this 

volume), which could produce high concentrations of calcium 

and sulfate without the associated acidity and metals from 

sulfide oxidation. This explanation is supported by a sulfur 

isotope study (Wright and Nordstrom, 1999) in the vicinity 

of peak 3,792 m, which showed that many of the background 

sites with high sulfate and calcium concentrations had isotopic 

signatures more similar to that of gypsum than pyrite, indicating that dissolution of a calcium sulfate mineral was the dominant source of sulfate. The last alteration assemblage consists 

of samples that predominantly drain propylitically altered 

rock but are downstream from large mineralized structures 

or vein systems (PROP-V). Figure 7 shows that these samples 

have compositions ranging from PROP-like to QSP-like. 

The most acidic, metal-rich sites in this group were springs, 

many of which discharge along the middle reach of Cement 

Creek and may be related to large fault structures that run 

subparallel to the valley trend of Cement Creek (Luedke and 

Figure 7. Dissolved zinc, copper, and sulfate concentrations 

as a function of pH for background water-quality samples from 

streams draining different bedrock alteration assemblages. 

Alteration assemblages are propylitic (PROP), propylitic with 

vein mineralization (PROP-V), weak sericite-pyrite (WSP), quartzsericite-pyrite (QSP), and acid-sulfate (AS), 1997–99.

10

100

1,000

10,000

23456789

ZINC, IN MICROGRAMS PER LITER

PROP WSP AS

PROP-V QSP

1

10

100

1,000

COPPER, IN MICROGRAMS PER LITER

23456789

1

10

100

1,000

10,000

23456789

SULFATE, IN MILLIGRAMS PER LITER

pH

reporting limit

reporting limit

EXPLANATION
Burbank, 1996). An example of one of these springs is CC29 

(fig. 1) near the mouth of Prospect Gulch, which discharges 

in a pool surrounded by terraces of actively forming ferricrete. Although the alteration assemblage upgradient from the 

site is predominantly PROP, the sample pH of 3.13 and zinc 

concentration of 1,070 μg/L were among the highest of the 

background samples. Bove and others (2000) suggested that 

the spring discharged at the base of a large fracture system that 

acted as a conduit transporting acidic water from QSP altered 

areas high above the site to the discharge point of the spring. 

The high zinc concentration in this sample may be the result 

of interaction of ground water with mineralized vein material 

along the fracture conduit. In contrast to the acidic springs in 

the PROP-V group, more than one-half of the samples in this 

group had neutral pH values and sulfate concentrations similar 

to the PROP group. Despite the similarities, most of these sites 

had higher zinc concentrations than the PROP samples, presumably reflecting the influence of mineral occurrences along 

the mineralized vein systems.

Although the sites previously discussed represent drainage from single alteration assemblages, many streams in the 

watershed flow across several different alteration assemblages, 

which can result in significant changes in water quality over 

a stream reach. An excellent example of this type of drainage regime is provided by a small tributary stream of Middle 

Fork Mineral Creek, referred to as Red tributary in Mast, 

Verplanck, and others (2000), that drains the northwest side 

of peak 3,792 m and is unaffected by mining (fig. 8). The 

tributary originates in an alpine cirque that is underlain by 

propylitically altered lavas of the San Juan Formation, then 

flows through progressively more altered rock related to the 

subeconomic porphyry copper-molybdenum deposit centered 

on peak 3,792 m. Water-quality samples were collected along 

the 2.1-km reach of the Red tributary during summer low flow 

to investigate downstream changes in stream chemistry in 

this unique area (table 7). At the head of the drainage (MC27, 

MC21) in the PROP area, stream water was a dilute calciumsulfate-bicarbonate solution with a neutral pH and dissolved 

metal concentrations at or below analytical detection. Between 

MC21 and MC20, the alteration assemblage grades from 

PROP to WSP and the stream became acidic with substantial 

increases in dissolved aluminum, iron, manganese, and sulfate 

concentrations. The largest changes in solute concentrations 

occurred between MC19 and MC18, where the alteration 

transitions from WSP to QSP. This reach also is immediately 

downstream from a large debris fan that covers much of the 

northwest side of peak 3,792 m (fig. 8; Yager and Bove, this 

volume, pl. 1) and is composed of intensely altered rock from 

the center of the porphyry deposit (Yager and others, 2000). 

Concentrations of trace metals also had distinct patterns along 

the stream reach. Between the headwaters and mouth of Red 

tributary, manganese and zinc concentrations increased by 

nearly 1 to 3 orders of magnitude. By contrast, concentrations 

of most other trace metals, particularly copper and molybdenum, remained relatively low, even in the lower reach of the 

tributary where pH values were below 4.0. The relatively low 

concentrations of copper and molybdenum may indicate that 

most trace metals in this reach are derived from polymetallic 

veins along the margins rather than from deeper zones of copper and molybdenum enrichment in the core of the porphyry 

deposit.

Mass-loading profiles for the Red tributary were calculated to help determine sources and sinks of dissolved metals along the stream reach (Kimball, 1997). Discharge was 

multiplied by concentration to obtain the solute loads at each 

sampling point along the stream reach (fig. 8). Sites MC44 

and MC43 were the major contributors of surface-water inflow 

along the reach. These two sources, combined with a number 

of small springs, accounted for less than 20 percent of the 

measured flow at MC22. This indicates that ground-water 

discharge along the channel is the dominant source of flow 

to the stream during low flow. The loading profiles in figure 9 

show substantial increases in solute loadings along the reach, 

particularly between MC19 and MC17. For example, along 

this 384-m reach, sulfate loads increased by 4 times, aluminum by 43 times, iron by 184 times, and zinc by 12 times. 

Because the increase in discharge was only 20 percent, the 

results suggest that ground-water discharge along the tributary 

was rich in dissolved metals and sulfate. The average concentration of solutes in the ground water can in fact be estimated 

on the basis of the difference in loads between MC19, MC17, 

and MC43 (Kimball, 1997). The calculation yields concentrations of 3,880 mg/L for sulfate, 315,000 μg/L for aluminum, 530,000 μg/L for iron, and 18,000 μg/L for zinc. These 

concentrations were five times higher than those measured 

in any of the sampled springs in the Red tributary subbasin, 

indicating that a different source of ground water was contributing metals to the Red tributary. Yager and others (2000) 

suggested that the source of this metal-rich ground water 

is a large debris fan on the northwest side of peak 3,792 m 

composed predominantly of quartz-sericite-pyrite altered rock 

(fig. 8). Figure 9 also shows that iron loads decreased slightly 

downstream from MC17. This pattern probably is the result of 

precipitation of iron oxyhydroxide minerals, as evidenced by 

the thick, reddish-orange precipitates that coat the streambed 

downstream from MC18. Formation of iron oxyhydroxide also 

is consistent with speciation calculations using PHREEQC 

(Parkhurst, 1995), which indicated that stream water in the 

lower reach was in equilibrium with ferrihydrite. Although 

loss of other constituents was not apparent from the loading 

profiles, hydroxysulfate minerals such as jarosite (potassiumiron hydroxysulfate), schwertmannite (iron hydroxysulfate), 

or jurbanite (aluminum hydroxysulfate) (Nordstrom and 

Alpers, 1999) also might have been forming in the stream 

channel. Speciation calculations indicated that stream water 

was saturated with respect to jarosite and jurbanite at MC18, 

MC17, and MC22. Although the streambed precipitate was not 

analyzed, schwertmannite and jarosite were identified in soil 

samples collected at the toe of the large debris fan upgradient 

from the lower stream reach, indicating that hydroxysulfate 

minerals may be actively forming in this highly acidic weathering environment (Yager and others, 2000).

366 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 367

Inverse Geochemical Modeling of Selected 

Background Springs

To constrain the likely weathering reactions controlling 

background water quality in the Animas River watershed 

study area, inverse geochemical models were developed for 

background water draining different alteration assemblages in 

the watershed. Inverse modeling uses mass-balance calculations based on water-quality and mineralogic data to infer 

water-rock interactions along a known flow path (Alpers and 

Nordstrom, 1999). For this study, the calculations were made 

using the computer code NETPATH (Plummer and others, 

1994). To avoid the complications of mixing and instream 

chemical reactions, only spring-water samples were used 

in the modeling exercise. The chemistry of meteoric water 

was estimated from snowpack samples from Red Mountain 

Pass (Mast and others, 2001), and mineral assemblages and 

compositions were obtained from Bove and others (2000) 

and Yager and others (2000). Model results for nine samples 

are presented in table 8, which represent the different bedrock alteration assemblages in the watershed. Positive values 

in table 8 indicate mineral dissolution and negative values 

Figure 8. Red tributary and peak 3,792 m area. A, photograph of Red tributary and peak 

3,792 m looking toward the south; B, map showing the Red tributary drainage with stream 

transect sampling sites.

MC27

MC21

MC20

MC44

X

Red tributary

Mineral Creek

Mineral Creek

MC22

Middle Fork

MC17

MC19 MC43

3,792 m

MC27

MC17

MC19

3, 792 m

Debris fan

B

A

MC79

MS79

MS78

MS80

MS76

MS34

MS77

MC18

37°51'

107°46' 107°44'

EXPLANATION

Tributary streams

Transect sites 

0 1 KILOMETER

Mine sites 

Mouth of Middle Fork Mineral Creek
Table 7. Dissolved constituent concentrations at stream transect sites along the Red tributary of Middle Fork Mineral Creek, October 2, 1999.

[Site numbers in figure 8; Alter., bedrock alteration assemblage; QSP, quartz-sericite-pyrite; WSP, weak sericite-pyrite; PROP, propylitic; Dist., distance downstream from headwater site in meters; Q, discharge in cubic feet per second; SC, specific conductance in microsiemens per centimeter at 25°C; Alk, alkalinity in 

milligrams per liter as CaCO3

; concentrations of calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), sulfate (SO4), silica (Si), aluminum (Al), and iron 

(Fe) in units of milligrams per liter; concentrations of copper (Cu), manganese (Mn), and zinc (Zn) in micrograms per liter; <, less than]

Site Alter. Dist. Q SC pH Ca Mg Na K Alk SO4 Si Al Fe Cu Mn Zn

MC27 PROP 0 <0.01 58 6.50 8.8 0.6 0.4 0.2 13 17 0.77 0.040 0.012 <4 <3 <20

MC21 PROP 408 .201 109 6.95 14 1.2 1.7 0.3 11 34 4.4 .051 .001 <4 19 <20

MC20 WSP 1,188 .487 419 4.65 61 4.3 4.6 0.5 <0.5 185 11.8 1.17 .510 4 494 25

MC19 WSP 1,284 .708 586 4.64 86 5.2 4.9 0.6 <0.5 276 12.1 1.47 .555 28 625 34

MC18 QSP 1,596 (1

) 1,780 3.74 113 34 6.8 1.1 <0.5 1,090 16.2 71.4 130.4 20 2,150 353

MC17 QSP 1,668 .863 1,370 3.74 109 27 6.1 0.9 <0.5 846 15.6 51.5 83.8 22 1,770 325

MC22 QSP 2,136 1.01 1,410 3.32 112 28 7.0 1.0 <0.5 859 17.8 54.0 71.9 21 1,840 354

1

Not measured.

Figure 9. Discharge and mass loading profiles for dissolved sulfate, calcium, aluminum, 

iron, and zinc along the Red tributary of Middle Fork Mineral Creek, October 2, 1998. 

Sampling sites and numbers in figure 8.

Discharge

Sulfate

Calcium

Zinc

Iron

Aluminum

0

500

1,000

1,500

2,000

2,500

0

0.3

0.6

0.9

1.2

1.5

SULFATE LOAD, 

IN KILOGRAMS PER DAY

DISCHARGE, IN CUBIC

 FEET PER SECOND

0

50

100

150

200

250

0

0.2

0.4

0.6

0.8

1.0

0 500 1,000 1,500 2,000

DISTANCE DOWNSTREAM FROM HEADWATER, IN METERS

MC20

MC19

MC21

MC17

MC22

MC44 MC43

2,500

MC27

CALCIUM, IRON, ALUMINUM 

LOAD, IN KILOGRAMS PER DAY

ZINC LOAD, IN 

KILOGRAMS PER DAY

EXPLANATION

PROPYLITIC WEAK SERICITEPYRITEQUARTZ-SERICITE-PYRITE

TRIBUTARY DISCHARGE

368 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 369

indicate mineral precipitation. Although the results may not 

be the only reasonable models that account for the observed 

spring-water chemistry, they appear to be consistent with the 

mineralogy of the different alteration assemblages. Additional 

mineralogical data, particularly for soil minerals, would help 

to further constrain the weathering reactions.

The PROP spring (CC50 in fig. 1) is located in the headwaters of Cement Creek (fig. 1) and discharges from the base 

of a large talus slope composed of dense, dark-green, propylitically altered rock. The chemistry of CC50 was controlled 

primarily by dissolution of calcite and some pyrite; this result 

is consistent with the presence of calcite and disseminated 

pyrite associated with the propylitic alteration. Dissolution 

of small amounts of chlorite and albite was needed to account 

for other cations. The major secondary phases formed were 

ferrihydrite, which is required to remove the iron released by 

pyrite dissolution, and kaolinite, required to remove silica and 

aluminum. Precipitation of a small amount of silica also was 

required for CC50. Although the sample was close to saturation with respect to amorphous silica, the result might also be 

an artifact of the model due to differences in the composition 

of secondary minerals actually forming in the soil and the 

kaolinite used in the model.

The WSP spring (MC70) is located in the Red tributary 

subbasin and has a thick mound of ferricrete at its discharge 

point. The chemistry of MC70 also was dominated by calcite 

and pyrite dissolution; however, considerably more pyrite 

oxidation was needed at MC70 to account for the lower pH 

and higher sulfate concentration at this site, as compared with 

CC50. Another notable difference between these two springs 

was the increased importance of albite weathering in the WSP 

zone, which was necessary to account for the higher sodium 

and silica concentrations in this sample. This difference may 

reflect the additional acidity produced by pyrite oxidation, 

which might increase the dissolution rate of silicate minerals 

in the WSP alteration relative to the PROP alteration. Precipitation of ferrihydrite, kaolinite, and a small amount of aluminum 

hydroxide was necessary to remove iron, silica, and aluminum 

from solution. This result is consistent with speciation calculations that show the spring to be close to saturation with respect 

to ferrihydrite, kaolinite, and amorphous aluminum hydroxide.

Three springs (MC30, CC36, and UA40) were modeled 

to represent QSP or vein-related QSP alteration associated 

with different deposit types in the Animas River watershed 

study area. MC30 is on the east flank of peak 3,792 m and 

drains the center of the subeconomic porphyry coppermolybdenum deposit; CC36 is near Red Mountain within 

the acid-sulfate deposit; and UA40 discharges at the base of 

Houghton Mountain, which is an area hydrothermally altered 

by adjacent rhyolite intrusions. The model results for all 

three springs showed a predominance of pyrite weathering 

to account for the low pH values and high sulfate concentrations characteristic of these samples. Substantial amounts of 

calcite were necessary to account for the calcium, which was 

somewhat unexpected due to the paucity of calcium-bearing 

minerals in the QSP assemblage. One possibility is that calcium weathers from calcite contained in pods of less altered 

rock surrounded by QSP altered rock. Alternatively, calcium may be derived from vein-filling anhydrite or gypsum, 

which is present in some mineralized areas of the watershed 

(Casadevall and Ohmoto, 1977; McCusker, 1982). The highly 

acidic water in the QSP zone appears to promote the dissolution of an aluminosilicate mineral such as kaolinite in CC36 

and UA40, which is a common component of the QSP assemblage. This result is consistent with speciation calculations, 

Table 8. Results of mass-balance modeling of background springs draining different alteration assemblages in the Animas River 

watershed study area.

[Positive values indicate mineral dissolution, and negative values indicate mineral precipitation in units of millimoles of mineral per liter of water; site numbers 

(in parentheses) in figure 1; diss., dissolved; precip., precipitate; PROP, propylitic; WSP, weak sericite-pyrite; QSP, quartz-sericite-pyrite; AS, acid-sulfate; 

PROP-V, propylitic with vein mineralization; WSP-cal, modeled with calcite only; WSP-gyp, modeled with gypsum only; zinc from pyrite expressed as percentage of measured concentration; --, not included in model; <, less than; %, percent]

Mineral phase 

(diss. or precip.)

PROP

(CC50)

WSP

(MC70)

QSP

(MC30)

QSP

(CC36)

QSP

(UA40)

AS

(CC53)

PROP-V

(CC86)

PROP-V

(CC29)

WSP-cal

(MC82)

WSP-gyp

(MC82)

Pyrite 0.143 0.414 0.944 1.236 1.89 0.127 0.741 1.82 6.25 1.01

Calcite .312 .517 .537 .869 .555 .028 1.09 .793 10.49 --

Chlorite .005 .021 .037 .081 .032 .002 .067 .069 .163 .163

Sericite .020 .029 .020 .020 .056 .003 .020 .020 .029 .029

Albite .016 .280 .221 .011 .106 .001 .043 .046 .337 .337

Pyroxmangite <.001 .008 .014 .027 .117 <.001 .010 .014 .047 .047

Kaolinite –.036 –.132 -- .152 .586 -- –.158 .266 –.111 –.111

Ferrihydrite –.142 –.307 –.868 –1.142 –1.89 –.127 –.741 –.837 –6.09 –6.09

Gibbsite -- –.114 –.059 -- -- .016 -- -- –.444 –.444

Silica –.013 -- -- –.421 –1.63 .171 -- -- -- --

Gypsum -- -- -- -- -- -- -- -- -- 10.49

Sphalerite

(zinc from pyrite)

-- -- .0048 .0024 .220 -- .0027 .016 .0018 .0018

(15%) (41%) (<1%) (22%) (9%) (269%) (43%)
which indicate that the samples were undersaturated with 

respect to kaolinite. There also was substantially more albite 

dissolution in MC30 compared to CC36, perhaps because of 

differences in the mineralogy of the different deposit types. 

CC36 and UA40 also were close to saturation with respect to 

amorphous silica; however, the substantial amounts of silica 

precipitation required by the models may be an artifact of 

choosing kaolinite in the model rather than a more aluminumrich phase such as andalusite or gibbsite. Substantial amounts 

of ferrihydrite precipitation were required to remove iron 

released by pyrite oxidation. MC30 and CC36 also were close 

to saturation with respect to jarosite, indicating that some iron 

also could be removed by formation of iron-sulfate minerals. Although the pH was similar between the QSP and AS 

samples, the model results for the AS spring were quite different, reflecting the dilute character of this water sample.

Two additional samples (CC86 and CC29) were modeled as examples of springs draining the PROP-V alteration assemblage. Spring CC29 discharges near the mouth 

of Prospect Gulch (discussed in previous section) and was 

acidic, whereas spring CC86, which is in the headwaters of 

Georgia Gulch, had measurable alkalinity. The results for the 

two springs indicate that more pyrite dissolution was required 

for CC29, because of higher sulfate concentrations, and more 

calcite dissolution was required for CC86, because of higher 

calcium and alkalinity. In contrast, dissolution of chlorite, 

sericite, albite, and pyroxmangite was nearly identical between 

the two samples. The only other difference was that CC86 

required precipitation of kaolinite and CC29 required dissolution, which is consistent with the difference in pH of these 

two samples.

Spring MC82 (table 8) is in the Middle Fork Mineral 

Creek subbasin; it is categorized as WSP but has anomalously 

high concentrations of calcium, sulfate, and strontium. As 

discussed in the previous section, this water-quality signature 

may be a result of dissolution of some vein-filling gypsum 

or anhydrite, which could produce high concentrations of 

calcium and sulfate without the associated acidity and metals 

from pyrite oxidation. Results in table 8 are shown for two 

models (WSP-cal and WSP-gyp), one with calcite and one 

with gypsum. The first model requires 10.5 millimoles per 

liter (mmol/L) of calcite dissolution and 6 mmol/L of pyrite 

oxidation, which is considerably higher than pyrite oxidation 

amounts for even the most acidic QSP springs. In contrast, the 

model with gypsum resulted in 1 mmol/L of pyrite oxidation, 

with the remainder of sulfate coming from gypsum. This result 

appears to be more consistent with pyrite oxidation amounts 

modeled for the other springs and is consistent with speciation calculations, indicating that MC82 was close to saturation 

with respect to gypsum. Although the results for the gypsumonly model seem reasonable, it is not possible to distinguish 

between the two calcium sources (calcite versus gypsum) 

based on concentration data alone. The relative importance 

of gypsum dissolution can be better constrained using stable 

sulfur isotope data, which are discussed in detail by Nordstrom 

and others (this volume, Chapter E8).

Zinc concentrations in the background springs were 

modeled with the mineral sphalerite. Results are shown at 

the bottom of table 8 and indicate similar amounts of sphalerite dissolution for the QSP springs MC30 and CC36, the 

PROP-V spring CC86, and the WSP spring MC82. Substantially larger amounts of sphalerite were modeled at CC29 

and particularly UA40 because of the high zinc concentrations at these two sites. Model results for sphalerite are not 

presented for the PROP spring CC50, the WSP spring MC70, 

and the AS spring CC53 because dissolved zinc concentrations were below the detection limit of 20 μg/L. In addition 

to sphalerite, trace metals in pyrite could also be a source of 

zinc to surface water (Bove and others, 2000). To compare 

the relative importance of zinc from sphalerite and pyrite, 

the amount of zinc liberated by pyrite oxidation was calculated based on the number of moles of pyrite dissolved in 

each model and the zinc concentration of disseminated pyrite 

from the Animas River watershed study area, which averages 

435 parts per million (D.J. Bove, unpub. data, 2000). Results 

of these calculations for the modeled springs are presented at 

the bottom of table 8 in parentheses and are expressed as the 

percentage of the dissolved zinc derived from pyrite oxidation, 

with 100 percent indicating that all the dissolved zinc can be 

accounted for by pyrite oxidation. These values range from 

less than 1 percent in UA40 to just over 40 percent for CC36 

and MC82 (gypsum model only), indicating that most zinc in 

the background springs was derived from zinc-rich ore minerals rather than pyrite oxidation. The low percentage at UA40 

may indicate that flow in the spring is localized along a highly 

mineralized structure with significant zinc-bearing minerals. 

Zinc concentrations estimated from pyrite oxidation at CC50 

(8 μg/L), MC70 (22 μg/L), and CC53 (7 μg/L) were consistent with the analytical results for these samples (all were 

<20 μg/L), indicating that contributions of zinc from depositrelated minerals were minimal at these sites. For MC82, 

the zinc concentration estimated from oxidation of pyrite in 

the calcite-only model was nearly three times the measured 

concentration in the sample. By contrast, the estimated zinc 

concentration for the gypsum-only model was only 40 percent 

of the measured concentration, further supporting the hypothesis that dissolution of calcium sulfate minerals is an important 

control on the water quality of this spring site.

Approaches for Describing Background 

Water Quality

Describing background sources of metals to surface water 

is an important aspect of reclamation in watersheds affected by 

inactive, historical mining, which needs to be addressed in order 

to establish realistic remediation goals for mining-affected surface water (Runnells and others, 1992; Alpers and Nordstrom, 

2000). This need is particularly important in extensively mineralized areas such as the Animas River watershed study area, 

370 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 371

where naturally occurring dissolved metal concentrations in 

some springs and streams have been shown to exceed existing 

State and national water-quality standards (Wright and Janik, 

1995). Differentiating between nonmining and mining-affected 

dissolved constituents is often a challenging task, particularly 

in historical mining districts, because water-quality data that 

predate historical mining activities generally are not available 

(Alpers and Nordstrom, 2000). Determination of background in 

these areas also may be complicated by a lack of information on 

the extent of underground workings of inactive mines and their 

effect on ground-water hydrology and chemistry. Many methods for describing background water quality in mining-affected 

areas have been published in the literature and are summarized 

by Alpers and Nordstrom (2000). One of the most frequently 

used approaches is the use of remote and proximal analogs. 

For remote analogs, water-quality data from a mining-affected 

area can be compared with water-quality data from an unmined, 

mineralized area that is distant from the mine site (Runnells and 

others, 1992; Kelley and Taylor, 1997). For proximal analogs, 

water-quality data from a mining-affected area can be compared 

with water-quality data from a nearby area (Miller and others, 

1995; Will, 1998). Stable isotopes of water also have proved 

useful as tracers of mining-related contamination particularly in ground-water environments (Alpers and others, 1999). 

Geochemical modeling using both inverse and forward techniques is another approach that has been cited in the literature. 

Inverse modeling uses field data to interpret water-rock interactions, whereas forward modeling is used to predict or simulate 

geochemical reactions (Alpers and Nordstrom, 1999). Statistical 

methods also have been used to determine background metal 

concentrations—for example, the use of probability distribution diagrams as described by Runnells and others (1998). As 

pointed out by Alpers and Nordstrom (2000), each of these 

approaches has its limitations, and the success of a particular 

approach may differ from site to site depending on factors 

such as geology, hydrology, topography, climate, and mine-site 

geography. To overcome some of these limitations, it may be 

necessary to use several approaches to document uncertainties 

and establish a reasonable range of values for the mine site of 

interest (Alpers and Nordstrom, 2000).

Analysis of water-quality data collected in the Animas 

River watershed has shown that background weathering of 

hydrothermally altered bedrock is a significant source of 

metals and acidity to streams in some parts of the study area 

(Wright and Janik, 1995; Wright and Nordstrom, 1999; Bove 

and others, 2000; Mast, Verplanck, and others, 2000; Yager 

and others, 2000). However, quantification of background 

water quality, particularly on the watershed scale, has proved 

to be a difficult task, because of a number of complicating 

factors. One of the difficulties in describing background in 

the Animas River watershed is that of quantifying inputs 

of acidity and metals from mines and mine-related sites to 

streams. Church, Mast, and others (this volume) identified 

more than 5,300 mine-related sites scattered throughout the 

study area, of which 373 were determined to have the potential 

for significant environmental effect to streams. Although 

the water quality of most flowing adits in the study area has 

been characterized (Unpub. report to Colorado Water Quality 

Control Commission, ARSG, 2001), metal loads to streams 

can be difficult to quantify because of the mixing and chemical reactions that occur between the mine site and the stream 

(Plumlee and others, 1999). Mines also may affect groundwater chemistry, but because of the complexity of subsurface 

flow paths and geochemical reactions, it is very difficult to 

quantify the effect of ground-water contamination on streams. 

Metal loadings from nondraining mines and waste-rock piles 

also are poorly constrained in the study area. In addition to 

the inventoried sites, an estimated 8.6 million tons of tailings 

from milling operations were flushed into streams (Jones, this 

volume, chapter C), some of which were deposited as fluvial 

sediment (Church, Fey, and Unruh, this volume). This miningaffected sediment also may contribute metals to surface 

water; however, the magnitude of this contribution is difficult 

to quantify separately. Other human-related features and 

activities that may affect water quality include the extensive 

network of 4-wheel drive roads and the large numbers of sheep 

that are grazed at high elevations throughout the study area 

during summer.

Hydrologic factors also can complicate estimation of 

background water quality in the Animas River watershed 

study area. The accumulation of a deep seasonal snowpack 

causes large seasonal fluctuations to occur in streamflow, 

and the proportions of nonmining and mining-affected dissolved constituents may vary significantly through the annual 

hydrologic cycle (Leib and others, 2003; Leib and others, this 

volume, Chapter E11; Sullivan and Drever, 2001). Further, 

once metals enter the surface-water system, processes including precipitation, sorption, and sedimentation can change 

dissolved metal concentrations in streams, making it difficult 

to trace the metals from source to stream. Another complicating factor is the lack of knowledge of ground-water chemistry 

and flow paths in the study area. Few direct measurements 

of ground water in the basin have been made, but the highly 

fractured nature of the bedrock would suggest that subsurface 

flow would be an important component of the hydrologic 

system (Yager and Bove, this volume). The example of the 

Red tributary illustrated that ground water accounted for most 

of the discharge and metal load in stream water draining that 

highly altered area of the watershed. Results from tracerinjection studies on the lower reach of Cement Creek indicated 

that diffuse subsurface flow accounted for about 25 percent of 

the flow in the stream during low flow and a significant fraction of the instream chemical load (Kimball and others, 2002; 

Kimball and others, this volume, Chapter E9).

Perhaps the factor that most complicates the estimation 

of background water quality in the study area is the complex 

geology. Metal-source determination presents a challenge 

because of the temporal and spatial overlap of magmatism, 

mineralization, hydrothermal alteration, and fracturing within 

the San Juan and Silverton calderas, where historical mining 
activities were centered (Yager and Bove, this volume). 

Multiple episodes of mineralization created deposits with a 

range in metal concentrations that in some parts of the study 

area overlap each other (Burbank and Luedke, 1969; Bove and 

others, this volume; Nash and Fey, this volume, Chapter E6; 

Yager and Bove, this volume). As demonstrated here and by 

Bove and others (this volume), the type of mineral deposit 

and degree of hydrothermal alteration have a strong influence 

on water chemistry; therefore, a detailed understanding of 

geology is critical in defining background sources of metals 

to surface water.

In light of the complicating factors discussed herein, 

the use of a single method is unlikely to provide an adequate 

estimate of background water quality, in a large, complex 

watershed such as the Animas River watershed study area. In 

some situations, evaluation of background sources in smaller 

and more geologically similar subbasins of the study area 

may be more feasible. In the following sections, several different approaches are presented for describing or estimating 

background water quality on different scales within the study 

area, including (1) statistical descriptions of water quality, 

(2) mass balance calculations, (3) isotopic applications including use of strontium isotopes and stable isotopes of sulfate, 

and (4) rare-earth elements as tracers in surface water. None 

of these approaches has proven to be completely successful in 

the Animas River watershed because of the complexities and 

difficulties described previously. The approaches presented 

here are techniques that may be applied in other areas where 

complexities may be minimized, possibly through investigations on smaller scales.

Statistical Descriptions

Statistical methods to describe geochemical background 

in the literature range from simple approaches such as statistical summaries and probability distribution diagrams to complex techniques such as multivariate analysis and pattern recognition (Runnells and others, 1998). Because of the relatively 

large number of water-quality samples collected in the Animas 

River watershed study area, simple statistical summaries may 

provide useful information regarding ranges of dissolved metal 

concentrations in background surface water, which can then be 

compared to dissolved metal concentrations measured at mine 

sites. One means of presenting these statistical summaries is 

with box plots, which provide a concise graphical means of 

comparing the central values, spread, and symmetry of the 

data among different groups of samples (Helsel and Hirsch, 

1992). For the standard box plot, the lower and upper ends 

of the box define the 25th and 75th percentiles, respectively, 

and the center line is the median. The whiskers generally 

extend to the 5th and 95th percentiles. In the study area, water 

quality was found to be strongly controlled by the degree of 

bedrock alteration, so background water-quality samples were 

grouped by the major mapped alteration assemblages shown in 

figure 1—propylitic (PROP), weak sericite-pyrite (WSP), and 

quartz-sericite-pyrite (QSP)—for the box plots (fig. 10). The 

one exception was the AS group, which was combined with 

the QSP group because of the small number of samples (n=4). 

The concentration ranges in mine adit discharge from 75 sites 

also were included for comparison, although the mines were 

not subdivided by alteration or deposit type. For many of the 

background samples in the PROP group, most of the dissolved 

metal concentrations, particularly copper and zinc, were below 

the analytical reporting limits. Rather than substitution of a 

single value for the “less than” values, as is more commonly 

done, we estimated summary statistics using the maximum 

likelihood method described by Helsel and Hirsch (1992). 

The resulting box plots comparing background water and 

mine discharge are presented in figure 10 for pH and dissolved 

calcium, sulfate, copper, manganese, and zinc concentrations. 

Copper, manganese, and zinc were chosen because they are 

dissolved constituents that are potentially most toxic to aquatic 

organisms in the study area (Unpub. report to Colorado Water 

Quality Control Commission, ARSG, 2001). Sulfate concentrations and pH are indicators of the extent of pyrite oxidation, and calcium concentrations are a general indicator of 

weathering.

The box plots of pH show the expected trend with the 

highest values in the least altered (PROP) rock and the lowest 

values in the most intensely altered (QSP) rock (fig. 10). The 

mine-drainage samples fall within the range of values defined 

by all three background groups. Calcium shows a slightly 

different pattern with higher concentrations in the WSP group 

compared to both the PROP and QSP sample groups. The high 

calcium in the WSP group probably reflects the influence of 

gypsum dissolution, particularly for samples collected in the 

vicinity of the porphyry deposit at peak 3,792 m. The range 

of calcium concentrations in the mine samples is similar to the 

WSP group, indicating that gypsum may be a common accessory mineral in mineral deposits throughout the study area. 

Sulfate concentrations were elevated in the WSP and QSP 

groups relative to the PROP group, reflecting the influence 

of large amounts of pyrite associated with the more intensely 

altered rock and mineral deposits and to a lesser extent the 

presence of secondary sulfate minerals such as gypsum along 

veins and fractures. The patterns among metals (copper, zinc, 

and manganese) were similar and showed increasing concentrations with increasing alteration intensity; the highest 

concentrations were in the mine-drainage samples. In contrast 

to sulfate, which is derived from ubiquitous pyrite, these metals are derived from deposit-related sulfides and accessory 

minerals, which tend to be localized along mineralized veins 

and structures and are common at inactive mine sites and in 

waste dumps. A similar observation was made by Wirt and 

others (2001) in Prospect Gulch, where surface water draining inactive mine sites had elevated base-metal concentrations 

relative to naturally acidic surface water produced by regional 

weathering of the intensely altered bedrock.

Although figure 10 shows some pronounced differences between background and mining-affected water 

samples, the application of these statistical summaries to 

372 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 373

estimate background has several limitations. First, many of 

the category I–II sites are located in headwater areas of the 

watershed and may not accurately represent the chemistry of 

higher order streams because of mixing and instream chemical 

reactions, as well as differences in hydrologic residence times. 

Second, the chemistry of category I–II sites may not be representative of deeper ground water that is perhaps a more important component of flow in higher order streams and that may 

be the source of discharge at many mine sites. Finally, because 

the distribution of alteration assemblages is variable within the 

study area (fig. 1), mine sites need to be evaluated individually 

to determine which alteration assemblage and corresponding 

background water-quality type are most representative at the 

mine site of interest.

In addition to the simple box plot approach, background 

water quality in the study area also was evaluated using principal component analysis (PCA), a more complex statistical 

analysis tool useful for evaluating similarities and differences 

Figure 10. Comparison of dissolved constituent concentrations in mine-discharge samples and in background waterquality samples draining different alteration assemblages.

2

4

6

8

pH, IN STANDARD UNITS

PROP WSP QSP Mines PROP WSP QSP Mines CALCIUM, IN MILLIGRAMS PER LITER

0

400

800

1,200

PROP WSP QSP Mines

SULFATE, IN MILLIGRAMS PER LITER

COPPER, IN MICROGRAMS PER LITER

1

10

100

PROP WSP QSP Mines

1

10

100

1,000

10,000

PROP WSP QSP Mines

MANGANESE, IN MICROGRAMS PER LITER

1

10

100

1,000

10,000

PROP WSP QSP Mines

ZINC, IN MICROGRAMS PER LITER

100

300

500

0

EXPLANATION

Median

25th percentile

75th percentile

5th percentile

95th percentile

PROP

Weak sericite-pyrite N=17

Quartz-sericite-pyrite N=36

Mine-drainage samples N=75

Propylitic N=69

WSP

QSP

Mines 
between multivariable data. Kimball and others (this volume) 

provide a good description of the use of PCA in evaluating 

water-quality data. In summary, principal components represent a set of new, transformed reference axes that are linear 

combinations of the original variables. The first principal 

component (PC1) is oriented along the direction of the greatest variance in the data, and the second principal component 

(PC2) is orthogonal to PC1 and is oriented to show the next 

greatest amount of variance in the data. Depending on how 

strongly correlated the variables are, more principal components can be generated, and each is orthogonal to the previous. 

In general, three principal components will explain a large 

percentage of the variance for the type of data presented here. 

The data analysis presented herein includes water-quality 

results for all the category I–II spring and stream samples in 

addition to mine-drainage samples. All analytical results were 

converted to millimoles per liter and log transformed. The 

principal component score is the projection of each sample 

onto the principal component axis and is a useful tool in comparison of samples.

Figure 11A displays the principal component scores for 

the first two principal components (PC1 and PC2) with samples coded by alteration type for the category I–II samples and 

the mine-drainage samples. The inset plot displays the eigenvectors that represent the projection of the original variables 

in PC1 and PC2 space. Trace metals cadmium, copper, nickel, 

lead, and zinc, which are contained primarily in sulfide minerals, plot in the lower right quadrant of the inset plot along with 

hydrogen ion. The upper right quadrant contains constituents 

that are primarily derived from the weathering of rock-forming 

minerals, such as calcium, magnesium, sodium, and silica. 

Although aluminum is primarily derived from the weathering of rock-forming minerals, its aqueous chemical properties 

are strongly controlled by pH; thus, it plots in the lower right 

quadrant. In the inset plot, the sulfate eigenvector lies between 

calcium and iron because pyrite and calcium sulfate minerals 

such as gypsum and anhydrite are the two dominant sources 

of stream-water sulfate. The only constituent that plots in the 

upper left quadrant is alkalinity, which increases with decreasing acidity. The lower left quadrant of the inset plot does not 

contain any eigenvectors and represents a field for samples 

that have low concentrations of dissolved constituents. In the 

biplot of principal components (fig. 11A), samples from AS, 

PROP, and QSP alteration assemblages plot in separate fields, 

although samples from PROP-V and WSP alteration assemblages, and mine-drainage samples overlap these fields. As 

expected from the box plots (fig. 10) and geochemical modeling, most of the QSP and some of the mine-drainage samples 

plot in the lower right quadrant, but many of the mine samples 

plot in the upper portion of the plot as well. The PROP 

samples plot on the left side of the biplot in a field consisting 

of higher alkalinity and pH and lower solute concentrations. 

The spring and stream samples classified as PROP-V primarily plot within the field defined by PROP samples, but some 

of the PROP-V samples plot in the metal-rich field.

To further investigate patterns in the data set, the PCA 

scores were grouped using a clustering analysis routine to 

see if mine-drainage samples are statistically distinct from 

category I–II samples (fig. 11B). The clustering analysis utilizes all the principal component scores, not just PC1 and PC2; 

thus on the two-dimensional plot in figure 11B some groups 

overlap. Group 1 represents sites with dilute, circumneutral 

water chemistry and contains samples from all the alteration 

assemblages (table 9). Water collected at these sampling sites 

probably has short flow paths and minimal water-rock interaction. Group 2 primarily consists of PROP and mine-drainage 

samples that are within areas of extensive propylitic alteration. 

These samples have relatively high pH and high alkalinity, 

calcium, and strontium concentrations. The category I– II 

samples in this group are typically at lower elevations than 

the group 1 samples and probably have longer hydrologic residence times. Group 3 samples plot between groups 1 and 2, 

and the group primarily contains PROP and PROP-V samples 

with low metal concentrations. Eighteen of the twenty group 4 

samples are from locations in the Middle Fork Mineral Creek 

subbasin. Groups 5 and 6 samples are acidic; these two groups 

contain both category I–II samples and mine-drainage samples. Group 6 samples generally have higher solute concentrations than group 5 samples. Of the 33 samples in group 7, 

thirty-one are from mines that produced ore. Group 8 also 

consists almost entirely of mine-drainage samples, but differs 

from group 7 in that these samples are all acidic and have 

extremely high dissolved metal concentrations. The eight 

groupings provide some insights into controls on water quality 

in the study area. First, the classification of sampling sites by 

alteration assemblage appears to provide a reasonable predictor of water quality, although samples for a given alteration 

type can exhibit a wide range in water composition. This range 

in composition is likely a result of differences in hydrologic 

residence times as well as variations in mineralogy within each 

alteration assemblage. Overall, the groups that are primarily 

composed of category I and II samples have low trace-metal 

concentrations. Mine-drainage samples primarily fall in 

groups with elevated metal concentrations (groups 7 and 8); 

however, some samples cluster in groups that are dominantly 

composed of category I–II samples. Many of these low-metal 

mine-drainage samples were collected from prospects and 

small adits that never produced ore and hence produce minimal acid-mine drainage.

Overall, the PCA and the clustering analysis of this 

data set demonstrate that alteration assemblage is the dominant control on background water quality, and this results in 

a wide range in water quality across the study area. Similarly, 

mine-drainage samples also exhibit a wide range in water 

quality, which is largely controlled by the alteration type of the 

surrounding bedrock. Differences in mineral deposit type also 

control water quality at mines, particularly for trace-metal concentrations (Bove and others, this volume). In addition, many 

of the sites classified as mining related were prospects or small 

mines that do not produce significant acid-mine drainage.

374 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 375

Figure 11. Principal component scores for background streams and springs (category I–II) 

and mine drainage by primary alteration type (A) and groupings by cluster analysis (B). PROP, 

propylitic; PROP-V, propylitic with vein mineralization; WSP, weak sericite-pyrite; QSP, 

quartz-sericite-pyrite; AS, acid-sulfate mineralization. Inset in A displays principal component 

loadings for water-quality constituents.

-2 -1 0 1 2 3 4

-3

-2

-1

0

1

2

 Group 1

 Group 2

 Group 3

 Group 4

 Group 5

 Group 6

 Group 7

 Group 8

PC2 SCORES

PC1 SCORES

-2 -1 0 1 2 3 4

-3

-2

-1

0

1

2

 PROP

 PROP-V

 WSP

 QSP

 AS

 Mines

PC2 SCORES

PC1 SCORES

-1 0 1

-1

0

1

SCALED PC1 LOADINGS

Cd Ni

Pb Cu

H+

Zn

Al

Fe

Mn

Mg Na

Sr Ca

SO4

SiO2

HCO3

SCALED PC2 LOADINGS

A

B
Mass-Balance Approach

The mass-balance approach is simply a budget used 

to show the sources of the dissolved constituents in water 

(Drever, 1988). In this application, synoptic water-quality data 

and discharge measurements were used to estimate metal loads 

from weathering sources in unmined areas (background) of 

Middle Fork Mineral Creek, a 25-km2

 subbasin of the Animas 

River watershed study area (Mast, Verplanck, and others, 

2000). The total load from mining sources was calculated by 

multiplying the measured discharge at each mine site by the 

concentration and then summing the loads of all the mines. 

Assuming that the major mining-related sources are accounted 

for and that contributions of mining-affected ground water are 

minimal, contributions from background weathering can be 

estimated from the difference between the load of Middle Fork 

Mineral Creek and the total load from the mines. The concentrations and loads of selected dissolved constituents for the 

six major mines in the subbasin (MS34, MS76, MS77, MS78, 

MS79, and MS80; fig. 8) and at the mouth of Middle Fork 

Mineral Creek (MC79) are listed in table 10. All samples were 

collected in late September and thus represent an estimate of 

background weathering only for low-flow conditions.

The results of the calculations indicate that contributions 

from springs, streams, and ground water in unmined areas 

accounted for about 80 percent of the discharge of Middle 

Fork Mineral Creek as well as a substantial fraction of the 

solute and metal loads in the study basin. For the major cations 

and sulfate, between 65 and 75 percent of the stream load was 

derived from background weathering of altered rock. Contributions of dissolved metals from background weathering 

varied over a slightly wider range—56 percent for manganese, 

66 percent for iron, 76 percent for zinc, 81 percent for copper, 

and 90 percent for aluminum. The background contribution 

of zinc (76 percent), which should be fairly conservative 

in the stream channel (Kimball, 1997), was similar to the 

contribution of sulfate (72 percent), which also should be 

conservative. Nearly all aluminum from background weathering was derived from the Red tributary, which discharges 

acidic and aluminum-rich water into the lower reach of Middle 

Fork Mineral Creek (fig. 8). Red tributary, which drains the 

intensely altered area around peak 3,792 m, also contributed 

a substantial portion of the base-metal load in Middle Fork 

Mineral Creek, similar in magnitude to contributions from 

mining-related sources in the subbasin. For example, 20 percent of the zinc and 24 percent of the copper in Middle Fork 

Table 9. Median water-quality composition for groups defined by cluster analysis of principal component scores, and number of mines and

background samples (by alteration assemblage) in each group, 1997–99.

[Spec. cond., specific conductance; μS/cm, microsiemens per centimeter at 25°C; mg/L, milligrams per liter; --, below detec tion; N, number of samples; PROP, 

propylitic; PROP-V, propylitic with vein mineralization; WSP, weak sericite-pyrite; QSP, quartz-sericite-pyrite; AS, acid-sulfate]

Constituent Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group 8

Spec. cond. μS/cm 56 260 162 375 609 576 770 1,090

Field pH 4.26 7.04 6.96 5.42 3.78 3.49 6.34 2.63

Alkalinity, mg/L 0.1 50 19 6 0.1 0.1 20 0.1

Sulfate, mg/L 9.0 77 44 160 200 230 360 370

Calcium, mg/L 1.83 43.7 22.5 34.5 36.0 48.0 129 17.2

Magnesium, mg/L 0.37 3.19 1.64 3.85 6.83 5.90 7.72 1.87

Sodium, mg/L 0.35 3.16 0.80 3.30 1.09 4.86 4.63 0.67

Silica, mg/L 12.5 9.46 3.72 19.0 10.5 45.5 22.0 24.7

Aluminum, mg/L 0.359 -- -- 0.345 2.21 6.87 0.232 9.17

Barium, mg/L 0.046 0.023 0.023 0.019 0.017 0.016 0.011 0.010

Cadmium, mg/L -- -- -- -- -- -- 0.003 0.18

Copper, mg/L -- -- -- -- 0.018 0.024 -- 3.00

Iron, mg/L 0.036 -- -- 0.448 0.721 6.07 4.75 60.3

Manganese, mg/L 0.018 -- -- 0.329 1.18 0.970 2.27 3.80

Nickel, mg/L -- -- -- -- -- -- -- 0.032

Lead, mg/L -- -- -- -- -- -- -- 0.47

Strontium, mg/L 0.012 0.620 0.236 0.285 0.258 0.295 1.00 0.069

Zinc, mg/L -- -- -- 0.033 0.687 0.224 0.620 44.7

All samples (N) 10 25 35 20 30 35 33 9

PROP (N) 1 11 14 7 0 0 0 0

PROP-V(N) 2 2 16 3 9 4 0 0

WSP (N) 1 2 0 4 0 8 2 0

QSP (N) 2 0 3 2 9 16 0 0

AS (N) 4 0 0 0 0 0 0 0

Mine (N) 0 10 2 4 12 7 31 9

376 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 377

Mineral Creek were derived from the Red tributary, compared 

with 24 percent of the zinc and 19 percent of the copper from 

mining-related sources.

Although this example demonstrates that background 

weathering is a significant source of metals to Middle Fork 

Mineral Creek, the limitations and assumptions of this 

technique need to be considered in evaluation of results of 

mass-balance calculations. For example, because many metals 

such as iron and aluminum are not conservative in the stream 

channel (Kimball, 1997), these calculations might actually 

underestimate metal contributions from background sources, 

if metals from mine discharge are attenuated along the stream 

channel. Additionally, if some of the mine-adit discharge is 

fed by metal-rich springs that existed prior to mining (Nash, 

1999), contributions from background also would tend to be 

underestimated. Finally and most importantly, if the assumption that all mining-related sources are accounted for is not 

met, particularly concerning contributions of mining-affected 

ground water, background weathering could be significantly 

overestimated by this technique.

Isotopic Applications

A wide variety of stable isotopes has been used in hydrologic studies to trace sources of water and dissolved constituents in natural and contaminated environments (Clark and 

Fritz, 1997; Krouse and Grinenko, 1991). In mining-affected 

areas, the most common application has been the use of stable 

isotopes of water to delineate mining-affected ground-water 

plumes (Alpers and others, 1994; Finley and others, 1997; 

Davis and others, 2000). It also may be possible to distinguish 

background weathering from mining-related solute sources 

if mineral deposits have isotopically distinct signatures or if 

isotopic fractionation processes or geochemical reactions in 

the mine setting differ from those in the natural environment 

(Taylor and others, 1984; Wright and Nordstrom, 1999). In 

this study, strontium isotopes and stable isotopes of sulfate 

were evaluated as possible tracers to distinguish background 

from mining-related solute sources in the Animas River 

watershed study area. Strontium was not found to be a useful isotopic tracer because mineral deposits did not have an 

isotopic composition distinctly different from that of the 

host bedrock (Verplanck and others, 2001). Stable sulfur and 

oxygen isotopes of sulfate were found to be strongly controlled by geologic sources and in some situations were useful 

for separating mining from background at individual mine 

sites. In pyrite-dominated environments, the oxygen isotopes 

of sulfate in background water appeared to be different from 

those in mining-affected water; however, the usefulness of this 

technique as a tracer of background has not been clearly established. For a more detailed discussion of sulfur isotope studies 

in the study area, see Nordstrom and others (this volume, 

Chapter E8).

Strontium Isotopes

The usefulness of strontium isotopes to discriminate 

between background and mining-affected surface water was 

tested on a smaller scale by sampling a suite of water and 

rock samples from the Middle Fork Mineral Creek subbasin. 

Results include strontium isotopic compositions (87Sr/86Sr) 

of water and rock samples and isotopic and elemental data 

from leaching experiments. Leaching experiments with dilute 

sulfuric acid were undertaken to determine the composition 

of the easily extractable fraction. Verplanck and others (2001) 

described sampling sites and chemical results in detail. Six 

rock samples that span the range in lithology and alteration 

intensity were collected. During low flow in 1995, eight water 

samples were collected from background streams and springs 

and two were collected from mine discharge.

Table 10. Concentrations and loads of dissolved constituents at the mouth of Middle Fork Mineral Creek and at major mines in the 

subbasin, and estimated contributions (percent) from background weathering.

[MC79, mouth of Middle Fork Mineral Creek; MS34 and MS76–80, major mine sites in study area; sampling localities in figure 8; discharge in cubic feet per 

second; <, less than]

Constituent Concentrations, in milligrams per liter Loads in kilograms per day Percent

MC79 MS34 MS76 MS77 MS78 MS79 MS80 MC79 Mines Background

Discharge 7.95 0.009 1.03 0.60 0.025 0.030 0.040 7.95 1.73 78

Calcium 130 359 110 400 20 91 64 2,530 883 65

Magnesium 11 42 3.9 33 5.4 6.3 5.9 214 60 72

Sodium 4.6 8.0 3.6 7.8 4.4 6.0 6.8 89 22 75

Potassium 0.5 0.9 0.5 0.8 0.5 0.5 0.1 9.7 2.6 73

Sulfate 430 1,300 200 1,200 83 360 263 8,360 2,340 72

Silica 23 29 17 29 35 49 45 447 96 79

Aluminum 7.20 21.2 <0.001 8.60 0.16 7.39 4.14 140 14 90

Copper 0.011 <0.004 0.003 0.013 0.002 0.097 0.051 0.21 0.04 81

Iron 15.6 73.0 0.47 67.0 9.35 4.10 11.4 303 102 66

Manganese 1.10 5.92 0.53 5.10 1.80 2.95 1.09 21.4 9.3 56

Zinc 0.23 0.62 0.039 0.53 0.26 2.33 0.22 4.5 1.1 76
The concentration of strontium in ground water is 

generally 5–20 mg/L; at these low concentrations the isotopic 

composition can be easily affected by interaction with bedrock 

along the flow path (Wadleigh and others, 1985). The strontium isotopic composition of volcanic and plutonic bedrock, 

the primary units within the Middle Fork Mineral Creek 

subbasin, is a function of the initial isotopic composition and 

the amount of radioactive decay of 87Rb to 87Sr, which has a 

half-life of 48.8×109

 years. Because individual minerals within 

a rock can have very different rubidium:strontium ratios, the 

strontium isotopic ratios of water interacting with bedrock 

may not reflect the whole-rock 87Sr/86Sr but more likely would 

reflect the 87Sr/86Sr of the more easily weathered components 

(Kendall and others, 1995).

The measured whole-rock 87Sr/86Sr ratios of six rock 

samples range from 0.70638 to 0.71261 (Verplanck and others, 

2001). The two samples of the quartz monzonite porphyry had 

the lowest 87Sr/86Sr ratios, less than 0.70674, and samples of 

the San Juan Formation had distinctly higher 87Sr/86Sr ratios, 

0.70702 to 0.71261. For a given lithology, the propylitically altered samples had lower 87Sr/86Sr ratios than the more 

intensely altered samples (fig. 12A). The propylitically altered 

samples had consistently higher calcium and strontium concentrations, as well as lower potassium and rubidium concentrations, than the more intensely altered samples. Similar to 

the whole-rock samples, the leachates of quartz monzonite 

samples had lower 87Sr/86Sr ratios, less than 0.70704, than the 

leachates from the San Juan Formation samples, 0.70704 to 

0.70863 (Verplanck and others, 2001). For a given lithology, 

the leachates from the propylitically altered samples also had 

lower 87Sr/86Sr ratios and higher strontium concentrations than 

the more intensely altered rock types.

The water samples had strontium concentrations that 

ranged from 0.028 to 5.7 mg/L and 87Sr/86Sr ratios from 

0.70654 to 0.70899 (Verplanck and others, 2001). Variation 

in the 87Sr/86Sr ratios of the water samples was not correlated 

with strontium concentration but was correlated with pH 

(fig. 12B). Samples with lower 87Sr/86Sr ratios were the more 

acidic, and samples with higher 87Sr/86Sr ratios were generally less acidic. Water interacting with QSP altered rock leads 

to much different water quality than water interacting with 

propylitically altered units (Mast, Verplanck, and others, 

2000). Spatially, the samples with the lowest 87Sr/86Sr ratios 

(MC71, MC43, MS79) were taken along the flanks of peak 

3,792 m within or downgradient from the zone of altered 

quartz monzonite. The two samples with the lowest 87Sr/86Sr 

(MS79 and MC43) were from within or adjacent to the most 

intensely altered quartz monzonite porphyry. The 87Sr/86Sr of 

these samples (0.70654 and 0.70700) was similar to the weak, 

sericitically altered quartz monzonite sample (0.70674 wholerock and 0.70704 leachate). Sample MS79 was from a seep 

below the largest mine in the study area, and sample MC43 

was from a small stream upgradient of any mining activity. 

The pH values, strontium concentrations, and 87Sr/86Sr ratio 

were quite similar, demonstrating that in this environment 

the 87Sr/86Sr cannot be used as a tool for separating miningaffected water from naturally acidic drainage.

Water samples collected in more intensely altered 

San Juan Formation had distinctly higher 87Sr/86Sr (>0.7080) 

than samples from either propylitically altered San Juan 

Formation or all quartz monzonite regions. Sample MS77, 

from an adit within the weak sericite-pyrite zone, had a 

pH of 5.7 and 87Sr/86Sr ratio of 0.70853, which is within 

the range of nearby springs (pH of 5.7–6.8 and 87Sr/86Sr 

of 0.70816–0.70899). Similar to the other mine-water sample, this sample did not have a distinct strontium isotopic 

signature compared with background springs in the same 

lithology.

In the Middle Fork Mineral Creek subbasin, the strontium isotopic signature of spring, stream, and mine water was 

controlled by variations in the bedrock geology and intensity 

of hydrothermal alteration. Mine-water discharge did not 

have a unique 87Sr/86Sr ratio because the mineral deposits did 

not have an isotopic composition distinctly different from 

that of their host rock. The mining activity focused on basemetal-rich quartz veins, which did not appear to have unique 

87Sr/86Sr ratios.

Sulfur and Oxygen Isotopes of Sulfate

Stable isotopes of sulfur have been extensively used in 

environmental studies to fingerprint different sulfate sources, 

because sulfur is widely distributed in terrestrial materials and commonly has a large separation in isotopic values 

(Krouse and Grinenko, 1991). In the Animas River watershed 

study area, the major sources of sulfur in dissolved sulfate 

are pyrite, calcium sulfate minerals, including gypsum and 

anhydrite, and atmospheric deposition. Upon oxidation or 

dissolution of minerals, little or no fractionation of sulfur 

isotopes occurs, so the resulting isotopic signature of surface 

water should be representative of the geologic source. Once 

dissolved in surface water, the sulfur in sulfate can be fractionated by sulfate-reducing bacteria (Krouse and Grinenko, 

1991); however, the importance of this process in the study 

area is poorly understood. Stable sulfur isotopic ratios of 

minerals in the study area are presented by Bove and others 

(this volume). The sulfur isotopic composition of pyrite ranges 

from –6.9 to +2.5 per mil, with an average of –2.4 per mil. 

Calcium sulfate minerals are considerably heavier; values range from +14.6 to +18.0 per mil, with an average of 

+16.5 per mil. The sulfur isotopic composition of atmospheric 

deposition ranges from +4.0 to +4.4 per mil (Mast and others, 

2001); however, extremely low sulfate concentrations in precipitation render the isotopic infl uence of this source negligible. Because pyrite and gypsum are widespread throughout 

the watershed, sulfur isotopic data alone likely would not be 

useful for discriminating background from mining-related 

sources of sulfate except perhaps on smaller scales, where 

individual vein deposits might be isotopically distinct from 

the surrounding host rock.

Oxygen isotopes of dissolved sulfate have been utilized 

in a few studies to trace sulfur cycling in watershed studies (Mayer and others, 1995) and to examine mechanisms of 

378 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 379

pyrite oxidation in the laboratory (Taylor and others, 1984; 

Van Stempvoort and Krouse, 1994). During oxidation of 

pyrite, the sulfur in the resulting sulfate acquires the isotopic 

signature of pyrite; however, the oxygen can be derived from 

either water molecules (–50 to +10 per mil depending on 

distance from ocean, and on elevation, latitude, and temperature) or atmospheric oxygen (+23.5 per mil) dissolved in 

the water (Nordstrom and others, this volume). The relative 

amounts of oxygen from water and aqueous dissolved oxygen incorporated into the sulfate molecule may be affected 

by microbiota that play a role in sulfide oxidation and by the 

rate at which the sulfide minerals are oxidized (Wright and 

Nordstrom, 1999). Incorporation of dissolved oxygen (O2(aq)) 

in the sulfate anions is thought to result from sulfide oxidation reactions at neutral pH where the oxidant is atmospheric 

oxygen. Oxygen from the water molecule (H2

O) is thought to 

Figure 12. Relation between A, 87Sr/86Sr and 1/strontium for whole-rock samples, and 

B, 87Sr/86Sr and pH for water samples from Middle Fork Mineral Creek subbasin. QSP, 

quartz-sericite-pyrite; WSP, weak sericite-pyrite; PROP, propylitic. Surface-water sites 

in figure 1 and figure 8.

0.000 0.005 0.010 0.015 0.020 0.025 0.030

0.706

0.707

0.708

0.709

0.710

0.711

0.712

0.713

 San Juan Formation-QSP+WSP

 San Juan Formation-PROP

 Quartz monzonite-QSP

 Quartz monzonite-PROP

1/STRONTIUM, IN 1/MILLIGRAMS PER LITER 

A

B

0.7065

0.7070

0.7075

0.7080

0.7085

0.7090

MC71

MC76

MS79

MC70

MC81 MC82

MC86

MS77

MC73

MC43

pH, IN STANDARD UNITS

2345678

87Sr/86Sr 87Sr/86Sr
predominate in more acidic conditions where aqueous ferric 

iron is the primary oxidant (Taylor and others, 1984). Wright 

and Nordstrom (1999) proposed that the relative importance of 

these two oxidation pathways may reflect the weathering environment, which might be useful for distinguishing background 

from mining-affected sources of sulfate in pyrite-dominated 

systems. In some mineralized areas, including the Animas 

River watershed study area, primary calcium sulfate minerals 

such as gypsum and anhydrite are associated with the mineral 

deposits. Weathering of these minerals will produce sulfate 

with an oxygen isotopic composition of the dissolving mineral 

phases, which can greatly complicate the interpretation of 

oxygen isotopes in terms of mechanisms of pyrite oxidation 

(Nordstrom and others, this volume).

Sulfur and oxygen isotopes of dissolved sulfate were 

measured at a variety of stream, spring, and mine sites in 

the Animas River watershed study area to determine if sulfate 

isotopes were useful for separating background from mining 

sources of sulfate. For a complete discussion of this study, 

see Chapter E8 of this volume (Nordstrom and others). Sulfur 

and oxygen isotopes of dissolved sulfate are presented in 

figure 13 with the range of isotopic values for pyrite (sulfur 

only) and gypsum/anhydrite samples collected in the study 

area (Bove and others, this volume). The water samples 

show a strong linear correlation (r2

=0.64) between sulfur 

and oxygen isotopic values. This trend represents a mixing 

line between sulfate derived from anhydrite/gypsum dissolution (heavier isotopic values) and sulfate derived from pyrite 

oxidation (lighter isotopic values). Simple mixing calculations based on the average sulfur isotopic composition of the 

minerals indicate that dissolution of calcium sulfate minerals 

accounts for more than 20 percent of the dissolved sulfate 

in nearly half of the samples. Figure 13 also differentiates 

between background samples and mining-affected samples. 

Although the oxygen isotopic values appear to undergo a shift 

between these two sample groups, the importance of gypsum/

anhydrite dissolution greatly complicates the interpretation of 

this pattern. Nordstrom and others (this volume) determined 

that spatial variation in the sulfur isotopic composition of 

mineral phases probably accounts for much of the difference 

Figure 13. Stable sulfur and oxygen isotopes of dissolved sulfate in background 

and mining-affected water-quality samples, and range of isotopic values for 

selected minerals from the Animas River watershed study area.

-10

-5

0

5

10

15

-15 -10 -5 0 5

OXYGEN ISOTOPIC VALUES OF SULFATE (PER MIL)

SULFUR ISOTOPIC VALUES OF SULFATE (PER MIL)

RANGE OF 34S AND 18O FOR 

GYPSUM/ANHYDRITE

RANGE OF 34S 

FOR PYRITE 

Background samples

Mining-affected samples

EXPLANATION

380 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 381

and concluded that no recognizable differences could be noted 

in the stable isotopes of dissolved sulfate derived from background and from mining sources.

The results presented here and in Nordstrom and others 

(this volume) for the Animas River watershed study area suggest that stable isotopes of dissolved sulfate likely would not 

be useful for distinguishing mining from background sources 

of sulfate, at least on a watershed scale. At smaller scales, 

however, cases may exist in which discharge from a single 

mine has an isotopically distinct signature from background 

surface water because of local differences in mineralogy. In 

such situations, oxygen or sulfur isotopes of dissolved sulfate 

may be useful in mass-balance calculations to determine the 

proportion of stream-water sulfate derived from the mine. The 

following example describes the application of stable isotopes 

of dissolved sulfate to determine the proportion of sulfate from 

mine drainage in Topeka Gulch, a small tributary on the west 

side of Cement Creek where mine discharge is isotopically 

distinct from surface water draining the surrounding host rock 

(fi g. 1). To determine the percentage of the dissolved sulfate 

that comes from the mine, the isotope-dilution equation can be 

used where

 Percent sulfate from mining =

 (δ18Obackground – δ18Omining-affected) 

× 100

 (δ18Obackground – δ18Omine)

In this example, background surface water is represented 

by Topeka Gulch at CC132, which had an oxygen isotopic 

value of –6.8 per mil; and mining-affected surface water is 

represented by Topeka Gulch at CC133, which had a value 

of +0.3 per mil (fig. 1). The mine site, located downstream 

from CC132 but upstream from CC133, had an isotopic value 

of +0.83 per mil. Using these values, the isotope-dilution 

equation calculates that 93 percent of the dissolved sulfate 

in Topeka Gulch came from the draining mine adit. The same 

calculation can be made using stable sulfur isotopes, which 

yields a similar value with 96 percent of the sulfate coming from the mine adit discharge. Although mass balances 

also can be calculated using concentration data, for these 

calculations stream and mine discharges would be required. 

Discharge measurements in steep mountainous streams can 

be difficult to measure accurately, and large errors in the 

mass-balance accounting of dissolved constituents can result. 

When the isotope-dilution equation is used, discharges are not 

needed, eliminating that source of error. This method also is 

useful if mine water is discharging diffusely from fractures in 

bedrock and it is not possible to sample at the adit; the isotopic 

signature of the mine water likely still will be present in the 

stream downgradient from the mine site, assuming that the 

mine site was adequately bracketed. Therefore, the calculation 

of the percentage of mine water in the stream using the isotope 

dilution equation fully accounts for the effects of the entire 

mine site on the environment.

Rare-Earth Elements in Surface Water

Rare-earth element geochemistry is a powerful tool 

for constraining geochemical processes in many petrologic 

studies (Smedley, 1991) but is just beginning to be applied to 

aqueous systems. One limitation to using rare-earth elements 

as hydrologic tracers is their limited solubility in nonacidic 

water (Davis and others, 2000). The rare-earth elements are 

a suite of 14 metals from atomic number 57 (lanthanum) to 

71 (lutetium) that have similar chemical and physical properties because they generally form stable +

3 ions of similar 

size. Small differences arise in that with increasing atomic 

number there occurs a systematic decrease in ionic radius. The 

rare-earth elements are trivalent, with the exception of cerium 

(also +4) and europium (also +2). The behavior of cerium and 

europium relative to the other rare- earth elements potentially 

can be used as a probe of redox potential and pH of an environmental system (Loveland, 1989).

Two subbasins, Prospect Gulch and Middle Fork 

Mineral Creek, were used for investigation of techniques for 

identifying source-water signatures with rare-earth elements. 

These two subbasins were chosen for their differing geologic 

characteristics, particularly bedrock composition and types 

of alteration. Detailed discussions of the bedrock geology, 

alteration assemblages, and mining history for Prospect Gulch 

are found in Burbank and Luedke (1969), Fisher and Leedy 

(1973), and Bove and others (2001), and, for the Middle Fork 

Mineral Creek subbasin, Ringrose (1982) and Yager and others (2000).

In Prospect Gulch, five mine-drainage samples 

(pH 2.4–3.6) and four acidic springs (pH 3.3–5.7) were sampled during low flow in 1997. Rare-earth element concentrations for the spring and mine-discharge samples from Prospect 

Gulch, normalized to North American Shale Composite 

(NASC), display enrichment in the middle (Sm-Dy) rare-earth 

elements (fig. 14A). The spring and mine samples had similar 

overall patterns except that one spring exhibited a negative 

cerium anomaly.

During low flow in 1995, five mine-drainage samples 

(pH 3.1–5.7) and five background springs (pH 3.1–6.8) were 

sampled in the Middle Fork Mineral Creek subbasin. The 

rare-earth element patterns of these samples display a greater 

range in shape than the patterns in samples from Prospect 

Gulch. The mine-drainage samples have two types of patterns 

(fig. 14B): two samples display a more sinusoidal pattern and 

three display an enrichment of middle rare-earth elements. 

The two samples with the sinusoidal pattern are from the north 

side of the subbasin, which is underlain predominantly by 

propylitically altered volcanic rock. The three middle rareearth element-enriched mine-drainage samples are from the 

south side of the subbasin, within or near the quartz monzonite 

porphyries. The rare-earth element patterns of the background 

spring samples display enrichment of middle rare-earth elements; however, four of the five samples also have a negative 

cerium anomaly. The presence of the cerium anomaly reflects 
differing redox conditions in some of the spring environments 

as compared with the mine setting, but because this feature is 

not observed in all the springs, it is not a viable signature.

To discriminate between water derived from springs and 

mine drainage using rare-earth elements, a fundamental difference between the two settings, such as host-rock mineralogy, 

mineral composition, mineral grain size, redox conditions, or 

residence time, must occur. In these subbasins, the mine and 

background samples do not appear to have unique rare-earth 

element signatures.

Figure 14. Rare-earth element ratios (normalized to the North 

American Shale Composite) of background water-quality and 

mine-discharge samples from A, Prospect Gulch, and B, Middle 

Fork Mineral Creek.

Summary

This investigation was conducted as part of the 

Abandoned Mine Lands Initiative to characterize background 

water quality in the Animas River watershed study area. 

Although there remains little doubt that the water quality and 

aquatic resources of the Animas River watershed study area 

have been adversely affected by drainage from historical mine 

sites, background weathering of mineralized bedrock also may 

contribute substantial amounts of metals and acidity to surface 

water. The results of this study will improve understanding 

of the weathering processes controlling surface-water chemistry in a mineralized watershed, which should aid resource 

managers in establishing cost-effective and technically 

feasible remediation goals for the Animas River watershed 

study area.

During summer low flow in 1997–99, we sampled 

241 streams and springs in the watershed, more than onehalf of which were determined to be minimally affected by 

mining and thus representative of background water quality. The chemistry of background streams and springs varied 

over a considerable range; pH ranged from 2.58 to 8.49 and 

specific conductance from 12 to 2,180 μS/cm. Sites with 

neutral pH values were of the calcium-bicarbonate-sulfate 

water type, whereas low-pH samples were dominated by 

dissolved aluminum, iron, and sulfate. Other metals detected 

in background water were barium, copper, manganese, 

strontium, and zinc. Several trace metals, including zinc, 

copper, and manganese, were present at concentrations that 

exceeded aquatic-life standards at many of the background 

sites. Zinc, the metal most toxic to fish in the Animas River 

watershed study area, reached concentrations as high as 

14,400 μg/L and was detected in more than one-half of background samples.

Water quality was measured at 75 inactive mine sites 

that were observed to be discharging directly into surface 

water during low-flow conditions in late summer and fall. 

The chemical composition of mine drainage was highly variable; pH ranged from 2.35 to 7.77 and specific conductance 

from 180 to 3,520 μS/cm. Mine drainage chemistry was dominated by sulfate (45–2,720 mg/L) and calcium (2–460 mg/L) 

concentrations, and many samples contained elevated concentrations of aluminum (as much as 71 mg/L) and iron (as much 

as 686 mg/L). Comparison of background samples with minedrainage samples showed statistically significant differences 

in concentrations for all the major ions and many dissolved 

metals, including barium, copper, iron, manganese, strontium, 

and zinc, with higher concentrations at mine sites with the 

exception of barium.

The chemistry of springs and streams minimally affected 

by mining was strongly controlled by the degree of bedrock 

alteration. Chemical characteristics of surface water draining five major alteration assemblages differed as a function 

of bedrock mineralogy. Calcium-bicarbonate-sulfate water 

was characteristic of propylitically altered rock, whereas the 

QSP-altered rock generated acidic, metal-rich surface water. 

10-6

10-5

10-4

10-3

La Ce Pr Nd Sm Eu Gd Tb Dy Ho Er Tm Yb Lu

10-6

10-5

10-4

10-3

La Ce Pr Nd Sm Eu Gd Tb Dy Ho Er Tm Yb Lu

NORMALIZED RARE-EARTH ELEMENT RATIOS

A

B

Background

Mine discharge

EXPLANATION

382 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 383

Among the fi ve alteration assemblages, dissolved metal concentrations varied the most widely in samples categorized as 

propylitically altered with associated vein mineralization.

To further constrain the possible weathering reactions 

controlling background water quality in the Animas River 

watershed study area, inverse geochemical models based on 

water quality and mineralogic data were constructed. The 

composition of springs draining the alteration assemblages 

could be reproduced by modeling weathering of variable 

amounts of pyrite, calcite, and aluminosilicate minerals, with 

pyrite and aluminosilicate dissolution becoming more substantial in the intensely altered rock types. A few sites had anomalously high concentrations of calcium and sulfate associated 

with high pH and low metal concentrations. Inverse modeling 

results indicated that this water-quality signature was derived 

from dissolution of vein-filling gypsum or anhydrite. Modeling of base-metal sources revealed that zinc was derived 

primarily from weathering of sphalerite but that oxidation of 

disseminated pyrite also was an important zinc source in some 

areas. These results suggest that the chemistry of background 

surface water minimally affected by mining in the Animas 

River watershed study area should be somewhat predictable if 

information is available on patterns of bedrock alteration and 

the associated mineral assemblages.

Estimation of metal contributions from background 

sources on a watershed scale was complicated by several factors, including large number of mine sites in the 

study area, limited characterization of mining-related sites, 

complex geology, and unknown contributions of ground 

water. Several approaches for estimating background in the 

watershed were explored, including statistical descriptions, 

mass-balance calculations, isotopic applications, and rareearth element geochemistry. The two statistical techniques 

used to describe geochemical background in the study area 

ranged from simple statistical summaries using box plots 

to a more complex approach using principal component 

analysis (PCA) and cluster analysis. The box plots revealed 

that pH and major dissolved constituents at background and 

mine-discharge sites exhibited similar ranges in concentrations but that some metals, particularly zinc, were elevated in 

mine drainage relative to background. The PCA of this data 

set confirmed that background samples had a wide range in 

water quality, which is primarily controlled by the degree 

of bedrock alteration. The cluster analysis showed that most 

of the mine-discharge samples fell in water-quality groups 

with high dissolved metal concentrations; however, they did 

not cluster in one group consisting solely of mining-affected 

water. The mass-balance approach was applied in the Middle 

Fork Mineral Creek subbasin to determine the magnitude of 

metal loading to surface water from the highly altered bedrock 

of the subeconomic porphyry copper-molybdenum deposit at 

peak 3,792 m. The results showed that background sources 

accounted for 56–90 percent of the metal load, which was 

primarily derived from the highly altered rock types associated 

with the porphyry copper-molybdenum deposit. This approach 

can be problematic because of the nonconservative nature of 

many dissolved metals and the diffi culties with identifying and 

sampling all mining-affected water, particularly ground water; 

therefore, the results of this approach should be interpreted 

with care. The range of stable sulfur and oxygen isotopic 

values of dissolved sulfate was found to be controlled primarily by the relative importance of pyrite and gypsum/anhydrite 

dissolution. Although oxygen isotopes of sulfate were found to 

differ among the pyrite-dominated samples, the usefulness of 

this technique as a tool for distinguishing background weathering from mining sources is still under investigation. Stable 

isotopes of sulfur were successfully used at a smaller scale to 

determine the percent of stream-water sulfate in the Topeka 

Gulch subbasin that came from mining-related sources. To 

discriminate between water derived from springs and mine 

drainage using strontium isotopes and rare-earth elements, 

a fundamental difference between the two settings, such as 

host-rock mineralogy, mineral composition, mineral grain size, 

redox conditions, or residence time, must be recognized. In the 

Animas River watershed study area, the mine and background 

water samples do not appear to have unique strontium isotopic 

or rare-earth element signatures; thus, these tracers are not 

useful for discriminating metal sources to surface water.

References Cited

Alpers, C.N., Hamlin, S.N., and Hunerlach, M.P., 1999, 

Hydrogeology and geochemistry of acid mine drainage 

in ground water in the vicinity of Penn Mine and Camanche Reservoir, California—Summary report, 1993–95: 

U.S. Geological Survey Water-Resources Investigations 

Report 96–4287, p. 59.

Alpers, C.N., Hamlin, S.N., and Rye, R.O., 1994, Stable isotopes (O, H, S) distinguish sources of acid drainage at Penn 

Mine, California, in Lanphere, M.A., Dalrymple, G.B., 

and Turrin, B.D., eds., Abstracts of the eighth International 

Conference on Geochronology, Cosmochronology, and Isotope Geology (ICOG-8), Berkeley, California, June 5–11: 

U.S. Geological Survey Circular 1107, p. 4.

Alpers, C.N., and Nordstrom, D.K., 1999, Geochemical modeling of water-rock interactions in mining environments, in

Plumlee, G.S., and Logsdon, M.J., eds., The environmental 

geochemistry of mineral deposits: Society of Economic 

Geologists, p. 289–324.

Alpers, C.N., and Nordstrom, D.K., 2000, Estimation of premining conditions for trace metal mobility in mineralized 

areas—An overview, in ICARD 2000; Proceedings of the 

Fifth International Conference on Acid Rock Drainage, 

Volume 1: Society for Mining, Metallurgy, and Exploration, 

Inc., p. 463–472.

Bassett, R.L., Miller, W.R., McHugh, J.B., and Catts, J.G., 

1992, Simulation of natural acid sulfate weathering in 

an alpine watershed: Water Resources Research, v. 28, 

p. 2197–2209.
Bove, D.J., 1996, Geology, alteration, and rock and water 

chemistry of the Iron, Alum, and Bitter Creek areas, upper 

Alamosa River, southwestern Colorado: U.S. Geological 

Survey Open-File Report 96–39, 34 p.

Bove, D.J., Hon, Ken, Budding, K.E., Slack, J.F., Snee, L.W., 

and Yeoman, R.A., 2001, Geochronology and geology of 

late Oligocene through Miocene volcanism and mineralization in the western San Juan Mountains, Colorado: 

U.S. Geological Survey Professional Paper 1642, 30 p.

Bove, D.J., and Knepper, D.H., 2000, Surface-water data 

and geographic relation to Tertiary-age intrusions and 

hydrothermal alteration in the Grand Mesa, Uncompahgre, and Gunnison National Forests (GMUG) and 

intervening Bureau of Land Management (BLM) lands: 

U.S. Geological Survey Open-File Report 00–271. URL 

http://pubs.usgs.gov/of/2000/ofr-00-0271/.

Bove, D.J., Mast, M.A., Wright, W.G., Verplanck, P.L., 

Meeker, G.P., and Yager, D.B., 2000, Geologic control on 

acidic and metal-rich waters in the southeast Red Mountain 

area near Silverton, Colorado, in ICARD 2000; Proceedings of the Fifth International Conference on Acid Rock 

Drainage, Volume 1: Society for Mining, Metallurgy, and 

Exploration, Inc., p. 523–534.

Burbank, W.S., and Luedke, R.G., 1969, Geology and ore 

deposits of the Eureka and adjoining districts, San Juan 

Mountains, Colorado: U.S. Geological Survey Professional 

Paper 535, 73 p.

Casadevall, Thomas, and Ohmoto, Hiroshi, 1977, Sunnyside 

mine, Eureka mining district, San Juan County, Colorado—

Geochemistry of gold and base metal ore deposition 

in a volcanic environment: Economic Geology, v. 72, 

p. 1285–1320.

Church, S.E., Fey, D.L., and Blair, Robert, Jr., 2000, Premining bed sediment geochemical baseline in the Animas 

River watershed, southwestern Colorado, in ICARD 2000; 

Proceedings of the Fifth International Conference on Acid 

Rock Drainage, Volume 1: Society for Mining, Metallurgy, 

and Exploration, Inc., p. 449–512.

Clark, I.D., and Fritz, Peter, 1997, Environmental isotopes in 

hydrogeology: Boca Raton, Fla., CRC Press/Lewis Publishers, 311 p.

Colorado Water Quality Control Commission, 2001, 

Regulation 31–The basic standards and methodologies for 

surface water: Colorado Department of Public Health and 

Environment, 5CCR1002–31, 169 p.

Davis, Andy, Tisdayle, Amy, and Byrns, Cindi, 2000, Discriminating between background and mine-impacted waters, 

in ICARD 2000; Proceedings of the Fifth International 

Conference on Acid Rock Drainage, Volume 1: Society for 

Mining, Metallurgy, and Exploration, Inc., p. 473–484.

Drever, J.I., 1988, The geochemistry of natural waters: Englewood, N.J., Prentice-Hall, Inc., 437 p.

Ficklin, W.H., Plumlee, G.S., Smith, K.S., and McHugh, 

J.B., 1992, Geochemical classification of mine drainages 

and natural drainages in mineralized areas: Proceedings, 

7th International Water-Rock Interaction Conference, Park 

City, Utah, p. 381–384.

Finley, J.B., Runnells, D.D., and Callender, J.F., 1997, Isotope 

geochemistry of a low pH, metal-bearing ground water 

plume southwest Jordan Valley, Utah: Geological Society of 

America Abstracts with Programs, v. 29, p. 384.

Fisher, F.S., and Leedy, W.P., 1973, Geochemical characteristics of mineralized breccia pipes in the Red Mountain 

district, San Juan Mountains, Colorado: U.S. Geological 

Survey Bulletin 1381, 43 p.

Fishman, M.J., 1993, Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory—

Determination of inorganic and organic constituents in water 

and fluvial sediments: U.S. Geological Survey Open-File 

Report 93–125, 217 p.

Furniss, George, Hinman, N.W., Doyle, G.A., and Runnells, 

D.D., 1999, Radiocarbon-dated ferricrete provides a record 

of natural acid rock drainage and paleoclimatic changes: 

Environmental Geology, v. 37, p. 102–106.

Helgen, S.O., and Moore, J.N., 1996, Natural background 

determination and impact quantification in trace metalcontaminated river sediments: Environmental Science and 

Technology, v. 30, p. 129–135.

Helsel, D.R., and Hirsch, R.M., 1992, Statistical methods in 

water resources: New York, Elsevier Science Publishers, 

Studies in environmental science, v. 49, 522 p.

Kelley, K.D., and Taylor, C.D., 1997, Environmental geochemistry of shale-hosted Ag-Pb-An massive sulfide deposits in 

northwest Alaska—Natural background concentrations of 

metals in water from mineralized areas: Applied Geochemistry, v. 12, p. 397–409.

Kendall, Carol, Sklash, M.G., and Bullen, T.D., 1995, Isotope tracers of water and solute sources in catchments, in

Trudgill, S.T., ed., Solute modeling in catchment systems: 

New York, John Wiley, p. 261–303.

384 Environmental Effects of Historical Mining, Animas River Watershed, Colorado
Characterization of Background Water Quality 385

Kimball, B.A., Runkel, R.L., Walton-Day, Katherine, and 

Bencala, K.E., 2002, Assessment of metal loads in watersheds affected by acid mine drainage by using tracer 

injection and synoptic sampling—Cement Creek, Colorado, 

U.S.A.: Applied Geochemistry, v. 17, no. 9, p. 1183–1207.

Kimball, B.A., 1997, Use of tracer injections and synoptic 

sampling to measure metal loading from acid mine drainage: U.S. Geological Survey Fact Sheet 245–96, 4 p.

Kirkham, R.M., Lovekin, J.R., and Sares, M.A., 1995, Sources 

of acidity and heavy metals in the Alamosa River Basin 

outside of the Summitville mining area, Colorado, in Posey, 

H.H., Pendleton, J.A., and Van Zyl, D., eds., Proceedings—

Summitville Forum ‘95: Colorado Geological Survey 

Special Publication 38, p. 42–56.

Krouse, H.R., and Grinenko, V.A., 1991, Stable isotopes—

Natural and anthropogenic sulphur in the environment: 

New York, John Wiley, Scientific Committee on Problems 

of the Environment SCOPE 43, 440 p.

Leib, K.J., Mast, M.A., and Wright, W.G., 2003, Using waterquality profiles to characterize seasonal water quality and 

loading in the upper Animas River basin, southwestern 

Colorado: U.S. Geological Survey Water-Resources Investigations Report 02–4230, 43 p.

Leybourne, M.I., Goodfellow, W.D., and Boyle, D.R., 1998, 

Hydrogeochemical, isotopic, and rare earth element evidence for contrasting water-rock interactions at two undisturbed Zn-Pb massive sulphide deposits, Bathurst Mining 

Camp, N.B., Canada: Journal of Geochemical Exploration, 

v. 64, p. 237–261.

Lipman, P.W., Fisher, F.S., Mehnert, H.H., Naeser, C.W., 

Luedke, R.G., and Steven, T.A., 1976, Multiple ages of 

mid-Tertiary mineralization and alteration in the western 

San Juan Mountains, Colorado: Economic Geology, v. 71, 

p. 571–588.

Lipman, P.W., Steven, T.A., Luedke, R.G., and Burbank, 

W.S., 1973, Revised volcanic history of the San Juan, 

Uncompahgre, Silverton, and Lake City calderas in the 

western San Juan Mountains, Colorado: U.S. Geological 

Survey Journal of Research, v. 1, no. 6, p. 627–642.

Logsdon, M.J., Miller, Scott, Swanson, Eric, Goodhard, 

William, and Perino, Larry, 1996, Pre-mining water quality 

in historically mined area—Iron bogs and ferricretes in 

the San Juan Mountains, Colorado: Geological Society of 

America Abstracts with Programs, v. 28, no. 7, p. 518.

Loveland, Walter, 1989, Environmental sciences, in Bunzli, 

J.-C.G., and Choppin, G.R., eds., Lanthanide probes in 

life, chemical, and earth sciences: New York, Elsevier, 

p. 391–411.

Luedke, R.G., and Burbank, W.S., 1996, Preliminary geologic map of the Silverton 7.5-minute quadrangle, San Juan 

County, Colorado: U.S. Geological Survey Open-File 

Report 96–275, 10 p.

Maest, A.S., 1996, Divining the past—The limitations of 

current methods for determining baseline water quality at 

mine sites: Geological Society of America Abstracts with 

Programs, v. 28, no. 7, p. 22.

Mast, M.A., Evans, J.B., Leib, K.J., and Wright, W.G., 2000, 

Hydrologic and water-quality data at selected sites in the 

upper Animas River watershed, southwestern Colorado, 

1997–99: U.S. Geological Survey Open-File Report 00–53, 

20 p.

Mast, M.A., Turk, J.T., Ingersoll, G.P., Clow, D.W., and 

Kester, C.L., 2001, Use of stable sulfur isotopes to identify 

sources of sulfate in Rocky Mountain snowpacks: Atmospheric Environment, v. 35, p. 3303–3313.

Mast, M.A., Verplanck, P.L., Yager, D.B., Wright, W.G., and 

Bove, D.J., 2000, Natural sources of metals of surface 

waters in the Animas River watershed, Colorado, in ICARD 

2000; Proceedings of the Fifth International Conference on 

Acid Rock Drainage, Volume 1: Society for Mining, Metallurgy, and Exploration, Inc., p. 513–522.

Mayer, Bernard, Feger, K.H., Giesemann, A., and Jaeger, H.J., 

1995, Interpretation of sulfur cycling in two catchments in 

the Black Forest (Germany) using stable sulfur and oxygen 

isotope data: Biogeochemistry, v. 30, p. 31–58.

McCusker, R.T., 1982, Mount Moly progress report, 

1979–1980, Drill holes 1-6: Amax Exploration, Inc., 

24 p.

McHugh, J.B., Ficklin, W.H., and Miller, W.R., 1988, Analytical results for 32 water samples from a hydrochemical survey of the Geneva Creek area, central Colorado: 

U.S. Geological Survey Open-File Report 88–365, 8 p.

Miller, W.R., Bassett, R.L., McHugh, J.B., and Fickin, W.H., 

1999, The behavior of trace metals in water during natural 

acid sulfate weathering in an alpine watershed, in Filipek, 

L.H., and Plumlee, G.S., eds., The environmental geochemistry of mineral deposits—Part B, Case studies and research 

topics: Reviews in Economic Geology, v. 6B, p. 493–503.

Miller, W.R., and McHugh, J.B., 1994, Natural acid drainage 

from altered areas within and adjacent to the upper Alamosa 

River basin, Colorado: U.S. Geological Survey Open-File 

Report 94–144, 47 p.

Miller, W.R., McHugh, J.B., and Meier, A.L., 1995, Calculations of pre-mining geochemical baselines at three 

stream junctions in the vicinity of Summitville, Colorado: 

U.S. Geological Survey Open-File Report 95–71, 26 p.
Nash, J.T., 1999, Geochemical investigations and interim recommendations for priority abandoned mines sites on USDA 

Forest Service lands, Mineral Creek watershed, San Juan 

County, Colorado: U.S. Geological Survey Open-File 

Report 99–170, 39 p.

Nordstrom, D.K., and Alpers, C.N., 1999, Geochemistry of 

acid mine waters, in Plumlee, G.S., and Logsdon, M.J., 

eds., The environmental geochemistry of mineral deposits: 

Society of Economic Geologists, p. 133–160.

Parkhurst, D.L., 1995, User’s guide to PHREEQC, a computer 

program for speciation, reaction-path, advective-transport, 

and inverse geochemical calculations: U.S. Geological 

Survey Water-Resources Investigations Report 95–4227, 

143 p.

Plumlee, G.S., Smith, K.S., Montour, M.R., Ficklin, W.H., and 

Mosier, E.L., 1999, Geologic controls on the composition 

of natural waters and mine waters draining diverse mineraldeposit types, in Filipek, L.H., and Plumlee, G.S., eds., The 

environmental geochemistry of mineral deposits—Part B, 

Case studies and research topics: Reviews in Economic 

Geology, v. 6B, p. 373–432.

Plummer, L.N., Prestemon, E.C., and Parkhurst, D.L., 1994, 

An interactive code (NETPATH) for modeling NET 

geochemical reactions along a flow PATH, version 2.0: 

U.S. Geological Survey Water-Resources Investigations 

Report 94–4169, 130 p.

Ringrose, C.R., 1982, Geology, geochemistry, and stable isotope studies of a porphyry-style hydrothermal system west 

Silverton district, San Juan Mountains, Colorado: Aberdeen, 

Scotland, University of Aberdeen Ph. D. dissertation, 

256 p., 19 plates.

Runnells, D.D., Dupon, D.P., Jones, R.L., and Cline, D.J., 

1998, Determination of natural background concentrations 

of dissolved components in water at mining, milling, and 

smelting sites: Mining Engineering v. 50, p. 65–71.

Runnells, D.D., Shephard, T.A., and Angino, E.E., 1992, 

Metals in water—Determining natural background concentrations in mineralized areas: Environmental Science and 

Technology, v. 26, p. 2316–2323.

Smedley, P.L., 1991, The geochemistry of rare earth elements in ground water from the Carnmenellis area, southwest England: Geochimica et Cosmochimica Acta, v. 55, 

p. 2767–2779.

Sullivan, A.B., and Drever, J.I., 2001, Spatiotemporal variability in stream chemistry in a high-elevation catchment 

affected by mine drainage: Journal of Hydrology, v. 252, 

p. 237–250.

Taylor, B.E., Wheeler, M.C., and Nordstrom, D.K., 1984, 

Stable isotope geochemistry of acid mine drainage—

Experimental oxidation of pyrite: Geochimica et Cosmochimica Acta, v. 48, p. 2669–2678.

Turk, J.T., Campbell, D.H., and Spahr, N.E., 1993, Use of 

chemistry and stable sulfur isotopes to determine sources 

of trends in sulfate of Colorado lakes: Water, Air, and Soil 

Pollution, v. 67, p. 415–431.

Van Stempvoort, D.R., and Krouse, H.R., 1994, Controls of 

δ18O in sulfate—Review of experimental data and application to specific environments, in Alpers, C.N., and Blowers, 

D.W., eds., Environmental geochemistry of sulfide oxidation: American Chemical Society, Symposium Series 550, 

p. 446–480.

Verplanck, P.L., Unruh, D.M., and Fey, D.L., 2001, Evaluation of strontium isotopes as a geochemical tracer in the 

Middle Fork Mineral Creek Basin, southwestern Colorado: 

U.S. Geological Survey Water-Resources Investigations 

Report 00–4290, 20 p.

Wadleigh, M.A., Veizer, Jan, and Brooks, C., 1985, Strontium 

and its isotopes in Canadian rivers—Fluxes and global 

implications: Geochimica et Cosmochimica Acta, v. 49, 

p. 1727–1736.

Will, R., 1998, A mass balance study to determine Copper Creek metal sources, in Tailings and Mine Waste ‘98, 

Fort Collins, Colo., January 26–28, 1998: Brookfield, Vt., 

A.A. Balkema, p. 743–762.

Wirt, Laurie, Leib, K.J., Melick, Roger, and Bove, D.J., 2001, 

Metal loading assessment of a small mountainous subbasin 

characterized by acid drainage—Prospect Gulch, upper 

Animas River watershed, Colorado: U.S. Geological Survey 

Open File Report 01–0258, 36 p.

Wright, W.G., and Janik, C.J., 1995, Naturally occurring 

and mining-affected dissolved metals in two subbasins 

of the upper Animas River Basin, southwestern Colorado: 

U.S. Geological Survey Fact Sheet 243–95, 4 p.

Wright, W.G., and Nordstrom, D.K., 1999, Oxygen isotopes 

of dissolved sulfate as a tool to distinguish natural and 

mining-related dissolved constituents, in Tailings and Mine 

Waste ‘99: Brookfield, Vt., A.A. Balkema, p. 671–678.

Yager, D.B., Mast, M.A., Verplanck, P.L., Bove, D.J., Wright, 

W.G., and Hageman, P.L., 2000, Natural versus miningrelated water quality degradation to tributaries draining 

Mount Moly, Silverton, Colorado, in ICARD 2000; Proceedings of the Fifth International Conference on Acid 

Rock Drainage, Volume 1: Society for Mining, Metallurgy, 

and Exploration, Inc., p. 535–547.

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