FINAL REPORT
Submitted
to
Maryland Department of Natural Resources
Chesapeake Bay Research and Monitoring Division
Contract: CB93-005-002
"Transmission of
Atmospherically Deposited Trace Elements
Through an Undeveloped, Forested Maryland Watershed"
Project Scientists:
Thomas M. Church, Joseph R. Scudlark and Kathryn M. Conko
College of Marine Studies
University of Delaware
Newark, DE 19716
Owen P. Bricker and Karen C. Rice
Water Resources Division
U. S. Geological Survey, M.S 432
Reston, VA 22092
TABLE OF CONTENTS
Title
Page
FORWARD .................................................................................................................................. vi
EXECUTIVE SUMMARY ........................................................................................................ vii
GLOSSARY OF TERMS AND ABBREVIATIONS.............................................................. viii
I.
INTRODUCTION..................................................................................................1
II.
STUDY OBJECTIVES AND BACKGROUND ..................................................2
III.
THE STUDY ..........................................................................................................4
A. Sampling Strategy ............................................................................................4
B. Sampling Site ....................................................................................................5
IV.
DESCRIPTION OF METHODS ..........................................................................7
A. Sampling Techniques .......................................................................................7
B. Analyses ...........................................................................................................11
V.
QUALITY ASSURANCE AND CONTROL.....................................................15
VI.
RESULTS AND DISCUSSION ..........................................................................20
A.
B.
C.
D.
E.
VII.
Atmospheric Inputs........................................................................................20
Stream Export ................................................................................................41
Dissolved Trace Element Mass Balance .......................................................70
NETPATH Modeling .....................................................................................75
Comparison of NETPATH and Mass Balance ............................................78
SUMMARY AND CONCLUSIONS ..................................................................80
ACKNOWLEDGMENTS ...........................................................................................................81
REFERENCES .............................................................................................................................82
LIST OF TABLES:
Table 1.
Table 2.
Table 3.
Table 4.
Table 5.
Table 6.
Table 7.
Table 8.
Table 9.
Table 10.
Table 11.
Table 12.
Table 13.
Table 14.
Table 15.
Table 16.
Table 17.
Table 18.
Table 19.
Table 20.
Table 21.
Table 22.
PAGE
Analytical techniques and detection limits for the trace
elements analyzed for this study ............................................................................14
Major ion concentrations (µeq/L) in wet only precipitation ..................................21
Major ion concentrations (µeq/L) in bulk throughfall under a
deciduous canopy ...................................................................................................23
Major ion concentrations (µeq/L) in bulk throughfall under a
coniferous canopy ..................................................................................................24
Volume-weighted average (µeq/L) composition of precipitation,
Catoctin Mountain, Maryland ................................................................................25
Long-term annual average of major chemical constitutents in
throughfall at Bear Branch Catoctin Mountain, Maryland ....................................25
Average wet deposition loadings (moles/ha/yr) Catoctin Mountain,
Maryland ................................................................................................................26
Trace element concentration (µg/L) in wet only weekly precipitation
samples collected on an open tower and integrated using an automated
collector..................................................................................................................27
Trace element concentrations (µg/L) in bulk deposition collected
on an open tower using a continuously open collector ..........................................29
Trace element concentrations (µg/L) in bulk throughfall samples
collected beneath coniferious canopy ....................................................................30
Trace element concentrations (µg/L) in bulk throughfall samples
collected beneath a deciduous canopy ...................................................................31
Metalloid concentrations (µg/L) (As, Se) in integrated precipitation
event samples .........................................................................................................32
Major ion dissolved concentrations (µeq/L) in routine stream grabs ....................43
Annual export of major chemical constituents at Bear Branch, Catoctin
Mountain, Maryland...............................................................................................44
Trace element dissolved concentrations (µg/L) in routine stream grabs ...............45
Major ion disolved concentrations (µeq/L) collected during three stream
intensives................................................................................................................53
Trace element dissolved concentrations (µg/L) collected in the stream
during three stream intensives................................................................................54
Trace element particulate concentrations (µg/g) collected in the stream
during three storm intensives .................................................................................55
Estimated suspended particulate stream loading based on measured
average loadings during the summer intensives....................................................67
Annual measured dissolved and estimated particulate loading of trace
elements in the Bear Branch stream .......................................................................67
Comparative loadings (g/yr) of Mn, Cr and Ni to Bear Branch
watershed ...............................................................................................................77
Comparative loadings (g/yr) of trace elements to the Bear Branch
watershed from weathering 6% phillite in the bedrock .........................................78
LIST OF FIGURES
Fig. 1
PAGE
Bear Branch watershed study area near Thurmont, Maryland
and location within the Potomac River watershed ...................................................6
Fig. 2
Analytical, lab, and field blank concentrations (μg/L) for
trace elements in precipitation compared to mean volumeweighted concentrations in precipitation at Bear Branch .....................................18
Fig. 3
Process, filter, and ISCo sampler field blank concentrations
for dissolved trace elements compared to average stream samples .......................19
Fig. 4a Comparison of seasonal dissolved atmospheric inputs (mg/m2/yr)
of Al, Fe, Mn, Zn to the Bear Branch watershed ...................................................33
Fig. 4b Comparison of seasonal dissolved atmospheric inputs (μg/m2/yr)
of Cd, Cr, Cu and Ni to the Bear Branch watershed ..............................................34
Fig. 4c Comparison of seasonal dissolved atmospheric inputs (μg/m2/yr)
of Pb, As, Se and cm precipitation to the Bear Branch watershed.........................35
Fig. 4d Annual dissolved Al, Fe, Mn, Cu, Pb, and Zn atmospheric
inputs (mg/m2/yr) to the Bear Branch watershed ...................................................36
Fig. 4e Annual dissolved Ni, Cr, Cd, As, and Se atmospheric inputs
(mg/m2/yr), and amount of precipitation (cm/ppt) to the Bear
Branch watershed ...................................................................................................37
Fig. 4f Comparison of wet only atmospheric input of trace elements
(μg/m2/yr) at Bear Branch watershed with the other midAtlantic locations ...................................................................................................38
Fig. 5
Mean stream discharge in cubic feet per second (cfs) in the
Bear Branch watershed recorded at the USGS gauging station
on a semi-log plot and daily basis ..........................................................................42
Fig. 6a Instantaneous dissolved stream concentrations (μg/L) for Al, Fe,
and Mn together with precipitation (cm) and discharge (cfs) ................................46
Fig. 6b Instantaneous dissolved stream concentrations (μg/L) for Ni, Pb,
and Zn together with precipitation (cm) and discharge (cfs) .................................47
Fig. 6c Instantaneous dissolved stream concentrations (μg/L) for Cd, Cr,
and Cu together with precipitation (cm) and discharge (cfs) .................................48
Fig. 6d Instantaneous dissolved stream concentrations (µg/L) for As
and Se together with precipitation (cm) and discharge (cfs).................................49
Fig. 7
Comparative trace element dissolved concentrations (μg/L)
in the Potomac River and other regional stream systems ......................................51
Fig. 8a Stream sampling for precipitation depth (cm), suspended
load (µg/L), protons (μequ/L), and discharge (cfs) during
the May storm intensive .........................................................................................56
Fig. 8b Stream sampling for total Al, Fe, and Mn concentration (µg/L)
during the May storm intensive .............................................................................57
Fig. 8c Stream sampling for total Cu, Ni, and Zn concentration (µg/L)
during the May storm intensive .............................................................................58
Fig. 8d Stream sampling for total Cd, Cr, and Pb concentration (µg/L)
during the May storm intensive .............................................................................59
PAGE
Fig. 8e Stream sampling for total As and Se concentration (µg/L)
during the May storm intensive .............................................................................60
Fig. 9a Stream sampling for precipitation depth (cm), suspended
load (µg/L), protons (μequ/L), and discharge (cfs)
during the August storm intensive .........................................................................61
Fig. 9b Stream sampling for total Al, Fe, and Mn concentration
(µg/L) during the August storm intensive ..............................................................62
Fig. 9c Stream sampling for total Cu, Ni, and Zn concentration
(µg/L) during the August storm intensive ..............................................................63
Fig. 9d Stream sampling for total Cd, Cr, and Pb concentration
(µg/L) during the August storm intensive ..............................................................64
Fig. 9e Stream sampling for total As and Se concentration (µg/L)
during the August storm intensive .........................................................................65
Fig. 10 The percent dissolved-particulate trace element distributions
measured in stream samples during the May storm intensive................................66
Fig. 11 The percent dissolved-particulate trace element distributions
measured in stream samples during the August storm intensive ...........................68
Fig. 12 Annually estimated dissolved-particulate trace element
distribution in the stream .......................................................................................69
Fig. 13 Seasonal watershed loadings, compared for bulk atmospheric
deposition and dissolved stream export .................................................................71
Fig. 14 Annual watershed loadings comparing bulk atmospheric
mport and dissolved stream export ........................................................................72
Fig. 15 Watershed retention factor, expressed as the ratio of three
forms of atmospheric input (bulk, wet, canopy) to dissolved
stream export ..........................................................................................................73
Fig. 16 Watershed transmission factor expressed as the ratio of
dissolved stream export to three forms of atmospheric input
(bulk, wet and canopy) ...........................................................................................74
FORWARD
This report describes the work conducted under the auspices of the Maryland
Department of Natural Resources. Funds for the project were provided by the Power Plant
Research Program under the direction of Paul Miller. It is designated contract CB93-005002 with a University of Delaware (UDE) subcontract to the U.S. Geological Survey (USGS).
EXECUTIVE SUMMARY
Increasing evidence supports the hypothesis that atmospheric deposition provides a
quantitatively important pathway for the input of contaminants to coastal waters. While recent
programs (e.g., CBADS, AEOLOS) have produced estimates of the direct aeolian input to
surface waters (Baker et al., 1997), there exists considerable uncertainty in estimating the
indirect input as transmitted through the contiguous watershed (Scudlark and Church, 1997).
Thus, the net export of trace elements that cross any fall line and received by a coastal water
body will depend on their weighted transmission through the various watersheds.
Such
transmission factors will ultimately depend on the regional atmospheric sources, as well as the
lithology and land use within the various watersheds above the fall line.
This forms the
rationale for the current study.
Retention and transmission of atmospherically-derived major (H+, Na+, K+, Ca2+, Mg2+,
HCO3-, NO3-, SO42-, Cl-, SiO2 ) and trace (Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Se, and Zn)
species were evaluated in an undeveloped forested watershed underlain by a rather inert
quartzite lithology (Bear Branch, Catoctin State Forest, Thurmont, Maryland).
These
comparisons were based on atmospheric input to stream export over a period of 16 months.
Both wet (precipitation) and total (bulk, including vegetative throughfall) atmospheric loading to
the catchment were determined. Stream export was gauged based on systematic sampling of
the stream under varied flow regimes. Additionally, watershed export of both dissolved and
particulate trace element phases was examined during three high run-off intensives associated
with summer storms.
Results in the Bear Branch watershed indicate that like many watersheds undergoing
atmospheric acidification in the eastern U.S., the major ions are dominated by magnesium,
sulfate, and nitrate. The atmospheric trace element inputs for elements such as Al, Zn, Ni,
Mn, and Cd are mostly transmitted through the watershed, while others such as Cu, Cr, Se,
As, Fe, and Pb are mostly retained within the drainage basin in the respective order noted.
Remobilization occurs primarily in the dissolved phase both seasonally and episodically in
conjunction with storage of acids and trace elements in the watershed during previous periods
of snow pack accumulation, forest growth, and drier seasons. For a few elements (Al, Fe,
Pb, Cr and As), particle loading during large precipitation/runoff events appears to contribute
to watershed export, but only to a minor proportion. Results suggest that the precipitation and
subsequent soil pH is the primary factor which determines the remobilization of sequestered
trace elements from the weathered phases.
To further resolve primary atmospheric and secondary weathering components in the
Bear Branch watershed, existing geochemical models (e.g., NETPATH) were applied. The
results show that minerals dissolved include chlorite, plagioclase feldspar, epidote and
potassium feldspar with those formed being kaolinite, pyrite, and silica phases. The model
suggests this weathering process contributed negligible amounts of trace elements in the
stream. Most of the trace element loading comes as a result of atmospheric scavenging of air
emissions from the regional airshed and their corresponding deposition to the local watershed.
GLOSSARY OF TERMS AND ABBREVIATIONS
ANC
acid neutralizing capacity.
Atmospheric Deposition
the flux of material from the air to the earth's surface.
Base Flow
the steady-state input of groundwater to a stream or river.
DCP-OES
Direct Current Plasma-Optical Emission Spectroscopy.
DI-H2O
high purity deionized water, having a resistivity of at least 10
megohms/cm.
Dry Deposition
the flux of particulate or gaseous constituents from the
atmosphere to an underlying surface, accomplished by
various mechanisms (e.g., gravitational settling, impaction,
surface adsorption etc.).
Fall Line
The fall line marks the boundary between the ancient,
resistant crystalline rocks of the Piedmont Plateau and the
younger, softer sediments of the Atlantic Coastal Plain in
the eastern U.S. It also marks the limit of navigability of
the rivers
Flux
the rate of transport of a material across an interface.
GFAAS
Graphite Furnace Atomic Absorption Spectroscopy
ICP-OES
Inductively
Coupled
Plasma-Optical
Emission
Spectroscopy.
Ion Balance
Σ (cation charges) - Σ (anion charges). If all ions are
accurately accounted for, the ion balance should equal 0.
Loading
The total net amount of a material entering an
environmental reservoir. In the context of a watershed,
this is meant to be the whole system flux.
ppb
parts per billion, also expressed as μg/kg or μg/L.
ppm
parts per million, also expressed as mg/kg or mg/L.
Qz-HCl
high purity hydrochloric acid that has been prepared by
double-redistillation in an all-quartz sub-boiling still.
Throughfall
net total (wet + dry) deposition below a forest canopy,
which reflects interaction with the foliage.
Unsaturated Zone
the layer above the water table (also referred to as the
zone of aeration).
Watershed
the hydrological drainage basin from which a body of
water receives its freshwater input.
Weathering
the dissolution of rocks and derived soils, brought about
by chemical, physical and biological processes.
Wet Deposition
the flux of constituents from the atmosphere to the earth's
surface as effected by rain, snow, fog, sleet, etc.
List of Trace Elements:
Cr
Chromium
Cu
Copper
Fe
Iron
Mn
Manganese
N
Nitrogen
Ni
Nickel
Pb
Lead
S
Sulfur
Al
Aluminum
Se
Selenium
As
Arsenic
Zn
Zinc
Cd
Cadmium
List of Major Ions:
Ca2+
calcium
Cl-
chloride
H+
protons
HCO3- bicarbonate
K+
potassium
Mg2+
magnesium
Na+
sodium
NH4+ ammonium ion
NO3-
nitrate
SiO2
silicata
SO42- sulfate
I.
INTRODUCTION
The weathering of rocks by water is a fundamental process of the earth's surface,
having direct implications to both the geochemistry of surface waters and climate. Weathering
of silicate minerals is central to soil formation and nutrition, chemical transport from the land to
the coastal ocean, and ultimately the composition of estuaries and the open ocean.
Weathering rates between different minerals vary naturally by several orders of magnitude
(e.g., Lasaga, 1984). Some minerals dissolve completely while others undergo mineralogical
transformations during weathering which results in the release of some cations and the
retention of others in a new mineral phase (e.g., Nesbitt et al., 1980). In regions downwind
from large industrial/urban emission sources, the basic chemical composition of precipitation is
being altered by the addition of acid and trace element reactants, which may fundamentally
accelerate the natural geochemical processes of weathering and thus, the characteristics of
watersheds.
Atmospheric deposition contributes to the weathering process, both in terms of amount
and chemistry of the associated precipitation. However, because precipitation in the eastern
U.S. contains added chemical components in the form of base cations, trace elements and
acid precursors emitted from upwind emission sources, it is likely that environmental
degradation of the atmosphere is fundamentally altering the weathering process for trace
elements and consequently the geochemistry and quality of receiving surface waters.
One of the primary examples of environmental degradation is the alteration of
atmospheric chemistry by human influences. Although atmospheric deposition consists of both
wet and dry components, it is the wet component which provides the primary weathering
agent.
Naturally, precipitation is slightly acidic from carbonic acid; but, downwind from
urban/industrial regions (such as the eastern U.S.), it is on average more than 10 times as
acidic due to the addition of sulfuric (S) and nitric (N) acid precursors derived from fossil fuel
combustion. To the acid components in precipitation is added an enriched suite of trace
elements from similar atmospheric emission sources. Thus, the trace element geochemistry in
even the most primitive watersheds of the eastern U.S. will, at the time of precipitation, be
heavily influenced by industrialized emissions affecting regional atmospheric processes. Most
of the natural acidity for weathering comes from soil generated carbon dioxide (CO2) which
may be an order of magnitude greater than that in the atmosphere. This can be overwhelmed
by the strong acids in atmospherically contaminated.
Watersheds are the primary receptacles for atmospheric deposition and the initial loci
for the processes of rock weathering. The major and trace element geochemistry of the
resulting runoff reflects not only the chemistry of the primary precipitation, but also the lithology
of the indigenous sediments and rocks as well. Soil formation and the formation of additional
or altered secondary minerals and sediments is occurring through weathering processes during
modern times. Watershed models are thus constrained to reflect some basic balance between
the precipitation inputs, stream chemistry and resulting secondary mineral or soil formation.
II.
STUDY OBJECTIVES AND BACKGROUND
The overall objective of this study was to determine the transmission of both major (H+,
Na+, K+, Ca2+, Mg2+, HCO3-, NO3-, SO42-, Cl-, SiO2) ions and trace (Al, As, Cd, Cr, Cu, Fe,
Mn, Ni, Pb, Se and Zn) elements through an undeveloped, forested watershed on Catoctin
Mountain near Thurmont, Maryland from August 1993 - December 1994. Specifically, these
goals were to:
(1) measure the direct atmospheric wet deposition of major ions and trace
elements,
(2) estimate the indirect atmospheric deposition from dry fallout, based on
measurements of forest canopy throughfall,
(3) compare the atmospheric input with the fluvial output fluxes from the
watershed, and
(4) estimate the transmission of atmospherically derived trace elements
through the watershed relative to weathered components.
Precipitation is the ultimate source of recharge to groundwater in small headwater
watersheds on Catoctin Mountain. Thus, the quantity and chemical quality of the precipitation
entering the watershed, therefore, have significant effects on the hydrologic and geochemical
response of the stream. The results of this study are particularly relevant to State of Maryland
issues that concern atmospheric sources of pollutants to surface and groundwaters.
Particularly relevant is the flux of atmospheric pollutants derived from power-plant emissions
falling into Maryland watersheds which transmit to the Chesapeake Bay and contribute to the
degradation of its water quality.
We would emphasize that the goals of the study do not include resolving the
components of atmospheric interaction with the forest canopy or ecosystem. Rather, our
objectives are to quantify the retention of atmospherically deposited trace elements in the
watershed and understand how this relates to known principles of congruent (complete
dissolution) and incongruent (dissolution with newly formed phases) weathering reactions.
Such a study should give some prediction of the nature of the abiotic metal retention as it
relates to short episodic and seasonal, or long-term releases to the coastal waters
downstream.
These objectives succeed many other previous major ion watershed studies in the
Chesapeake region.
A study of major ion balance between precipitation inputs and
streamwater outputs have been measured nearby in the Catoctin (Katz et al., 1985) and
Shenandoah (Ryan et al., 1989; Cosby et al., 1991) watersheds of the Potomac, as well as
the Rhode River watershed of the Chesapeake (Correll et al., 1984; Jordan et al., 1995).
Similar small watershed studies which address streamflow generation, hydrology during high
runoff, changes in major ion chemistry of streamwater as a function of season and flow, and
the influence of bedrock geology on watershed chemistry include: Bricker and Rice, 1989;
Christopherson et al., 1990; DeWalle et al., 1988; Lynch and Dise, 1985; Lynch and Corbett,
1989; O'Brien et al., 1993; and Rice and Bricker, 1995.
Most major ion and trace element models of weathering relate reactant precipitation and
source rock geochemistry, with secondary mineral products in soils and the chemistry of
resulting stream and groundwater. Because trace elements like Al, Fe, and Mn are abundant
in source rocks, natural weathering is their primary source. For this reason, such elements
remain at relatively constant levels in most natural streamwaters and serve as a natural
weathering indicator (Erel et al., 1991), although acidity may affect this level. Other elements
like Pb and Cd are naturally present in only trace quantities in the rock, although in modern
times they are being introduced to the atmosphere and waters in unprecedented amounts from
human industrial practices (e.g., Patterson, 1965; Salomons and Forstner, 1984; Patterson
and Settle, 1987; Nriagu, 1989).
Consequently, streams and groundwater now contain
significant sources of trace metals from sources other than weathering, such as precipitation
scavenging of industrial emissions into the watershed (e.g., Erel et al., 1990, 1991). Thus,
measuring the atmospheric deposition of trace elements into and modeling associated rock
weathering within a watershed should provide the means to resolve their primary atmospheric
and secondary rock-weathering sources.
Similar studies of trace metal fluxes and throughput in watersheds include those of
Lindberg and associates at the Oak Ridge National Laboratory (Lindberg and Turner, 1988;
Lindberg, 1989; and Petty and Lindberg, 1990). These studies have taken place for over a
decade in various southeastern watersheds, including the well studied Walker Branch research
site. Here it has been found that forest canopies can either accumulate or translocate trace
elements from the soil to leaf surfaces or intercept them by dry deposition which are either
retained or leached by washout during wet deposition.
A study of trace metal (Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb) fluxes and storage
was conducted in beech and spruce forests (Heinrichs and Mayer, 1980). The annual input
from atmospheric deposition was small (less than 30%) for the metals Cr, Mn, and Ni when
compared to the amounts stored in the annual increment of biomass.
However, the
percentage is higher for Fe (40-60%), which must be made up for by weathering of soil
minerals.
Biomass accumulation of Cd, Co, Cu, Pb and Zn in both cycled (leaves and
needles) and noncycled (wood) components can be accounted for or exceeds atmospheric
deposition. Such biomass accounted for up to 27% of total Cd in the ecosystem, but less
than 10% for the other metals.
The accumulation of Pb, Fe and Co in the forest floor
exceeds up to 180 fold the amount supplied by litterfall, suggesting direct accumulation of
atmospheric deposition in the organic litter. However, the amount of Mn accumulation is only
several fold, indicating fast release of the metal by decomposition of organic matter.
One comprehensive study of lead accumulation in the floor of Hubbard Brook
experimental forest (Smith and Siccama, 1981) showed that most of the lead was
accumulated from atmospheric deposition onto lichens and mosses. The amount of lead
exported from the forest ecosystem was only about 1-2% of the atmospheric deposition. This
was independent of forest elevation suggesting a constant inventory. The biogeochemical
retention was unaffected by disturbances such as harvest cutting, other than increased
particulate runoff due to associated erosion.
III.
THE STUDY
A.
Sampling Strategy
The stated objectives were met by:
(1)
directly measuring the trace elements in wet deposition, using automated
sampling techniques;
(2)
estimating the total (wet + dry) atmospheric input of trace elements,
employing bulk samplers in the open as well as beneath vegetative
canopies;
(3)
gauging the fluvial trace element flux from the watershed from
systematic stream sampling under varied flow regimes, using clean
sampling and analytical techniques;
(4)
conducting intensive sampling to capture high flow periods, utilizing an
automatic stream sampler poised to capture such major precipitation and
flushing events; and
(5)
estimating the weathered trace element component by use of the USGS
geochemical model NETPATH from an assumed bedrock composition
based on known mineralogy.
The quality of the riverine water that crosses the fall line and enters an estuary reflects
an aggregate of the outputs from a myriad of small watersheds, such as the one investigated
here. It is, therefore, necessary to begin with the outputs from such small watersheds in order
to understand the larger more complex systems. Both the Chesapeake Bay and Potomac
River basins are approximately 60% forested, therefore, the watershed proposed for this study
was chosen to be representative of the significant land use of the basins. Thus, it was
deemed reasonable to start with what is probably the least complex system, the undisturbed
(except for the influence of acid rain) forested watershed, underlain by relatively inert bedrock.
The atmospheric input to the watershed includes both a wet and a dry component.
While the wet deposition can be directly measured with a reasonable degree of accuracy,
there do not exist any universally-recognized techniques to directly quantify dry deposition.
Perhaps the most commonly-employed approach involves the determination of ambient aerosol
concentrations and application of deposition models to estimate dry flux.
However, with
respect to the objectives of this study, such approaches fail to take into account foliar
interactions in mediating actual fluxes to the forest floor.
One technique that has found
increased application within the past decade involves the measurement of vegetative
throughfall. Throughfall represents the total (wet + dry), net deposition to the watershed,
accounting for canopy interactions. This technique has been successfully applied to major ions
(Lovett and Lindberg, 1984; Lindberg et al., 1986; Hanson and Lindberg, 1991; Hansen et al.,
1994; Draaijers et al., 1996), and more recently, trace elements (Lindberg, 1989; Rea et al.,
1996).
B.
Sampling Site
This study took place in the Bear Branch watershed (area: 98.4 ha or .39 mi2 ) on
Catoctin Mountain in Cunningham Falls State Park west of Thurmont, Maryland (Fig. 1). This
primitive watershed has been well characterized hydrologically over the past years by scientists
from the USGS Water Resources Division. The USGS has been monitoring precipitation at
one site and streamwater major inorganic ions in four watersheds including Bear Branch during
the past 10 years. The periods of records for streamwater chemistry are: Hauver Branch
(1982-present), Hunting Creek (1982-1994), Fishing Creek Tributary (1987-1995), and Bear
Branch (1990-1995). This background of data was used to diagnose the basic chemistry of
the watershed which resolves the weathering of both major and trace element minerals. This
record was also used to predict the best periods for sampling and plan the sampling strategy
according to the historical hydrographs.
Previous research performed by the USGS resulted in the conclusion that Bear Branch
is highly susceptible to episodic acidification because: 1) weathering of the underlying quartzite
bedrock produces little acid neutralization; and 2) the high natural gradient of the watershed is
conducive to the shallow flowpaths that cause episodic acidification during storms (Rice and
Bricker, 1996). During base flow, pH of Bear Branch streamwater is about 5.5, but during
high runoff, the pH can decrease to below 4.0. During base flow, the dominant cations, in
order of highest to lowest concentration, are Mg2+, Ca2+, Na+, and K+, and the anions are
SO42-, Cl-, NO3-, and HCO3-.
Such a dominance of nitrate anion over bicarbonate is a
relatively common modern observation in eastern watersheds influenced by the impact of acid
deposition. Increased nitrate in streams draining some eastern watersheds has been attributed
to impacts from defoliation of trees by gypsy moths (Webb et al., 1985). Although there has
been some gypsy moth infestation in the Catoctin Mountain, we have seen no significant
increase in the nitrate concentration of the streams in those areas over the past decade.
The Bear Branch watershed is located on 98 hectares of State designated wild lands
within Cunningham Falls State Park, and thus, is relatively undisturbed by recent development
after its primary clearing approximately a century ago.
It is drained by a small, eastward
flowing, perennial headwater stream, and is completely forested with deciduous (oak, maple,
beech, wild cherry, poplar) and coniferous (hemlock) trees, in an area ratio of approximately
9:1 (Rice and Bricker, 1996). The site is utilized as park land where only day hiking and
hunting are allowed. The topography is steep and rocky, and the average stream gradient is
203 m/km (20%). The watershed is underlain entirely by the lower unit of the Weverton
Formation (Fauth, 1977). The soils consist of Ultisols and Inceptisols and are mapped as the
Edgemont-Chandler series complex, which is characterized as very stony loams with 20%60% slopes (Matthews, 1960). A USGS streamflow-gauging station (USGS identification
number 01640980) was constructed near the outlet of the watershed during May, 1990 and
was in continuous operation from June 1990 through September, 1995. The watershed was
previously instrumented with a permanent stream-gauging station, automatic samplers for
major ions in stream and precipitation waters, a transect of shallow piezometers, and a tipping
bucket rain gauge. For this study, the current sampling array was augmented with a trace
element clean automatic stream sampler of similar design.
IV.
DESCRIPTION OF METHODS
A.
Sampling Techniques
Sampling for all parameters was conducted from 18 August 1993 through 13 December
1994 (16 months). Although originally proposed for only 12 months, the additional sampling
was carried out to assure the generation of a comprehensive and congruous set of data for all
parameters, encompassing a complete growing season (16 months).
Major Ions. The USGS Catoctin Mountain precipitation-collection station, located in
Cunningham Falls State Park, was situated on top of a 7.6 m high water-storage tank, free of
surrounding tree canopy, and thus met the National Acid Deposition Program angle criteria
(Robertson and Wilson, 1985).
The collection equipment included an Aerochem Metrics
Model 301 wet/dry atmospheric deposition collector for major inorganic ions, a Belfort (5-780
Series) weighing-bucket precipitation gauge, and a Sierra Misco Model ES-160 tipping-bucket
precipitation gauge. The collection equipment was anchored on top of a wooden platform 2 m
above the water tank. This elevation served to minimize contamination of the samples by
"splash up" from the top of the water tank and to discourage vandalism. Although the Belfort
gauge measures snow, not as effectively as rain, this is not a significant problem since only a
small amount of the annual precipitation at the site falls as snow.
It is recognized that one precipitation collection site may not provide representative
information on the variation of precipitation across the entire watershed. Although financial
and personnel constraints limited the site to one location, the original atmosphere collection
project started in 1982 when two sites were established in the watershed. The existing study
site is at an elevation of 530 m and another site about 3 km to the south was at an elevation
of 287 m where samples were collected simultaneously (Katz et al., 1985). A comparison of
paired data collected at the two sites for 1982 and 1983 showed no statistically significant
differences in the chemistry or volume of precipitation, and thus, the lower, less secure site
was discontinued.
Precipitation samples were collected weekly from the Aerochem Metrics collector. The
wet deposition collection bucket, which contained the precipitation sample, was replaced with
an empty bucket that had been previously rinsed three times with distilled water. When there
was no precipitation sample, the bucket was still replaced with a clean one. The samples
were submitted to the USGS laboratory in Reston, Virginia for chemical analysis.
Throughfall collectors for major ions consisted of 203 mm diameter polyethylene
funnels that were connected to 1 L brown, polyethylene collection bottle by Tygon® tubing.
The tubing was looped to prevent evaporation of the sample. A Tru-chek® plastic rain gauge
attached to each throughfall collector gave an approximate measure of the amount of
throughfall collected at each site. The funnels were located approximately 1.2 m above the
forest floor to help minimize "splash up."
Only one collector was located beneath a
deciduous canopy and one collector under a coniferous canopy as funds and personnel were
limited. Again, we recognize that the amount and variability of throughfall across the entire
watershed is probably not well represented by only one collector under each canopy type.
However, this study does show general characteristics of throughfall beneath coniferous and
deciduous canopies, and the importance of canopy interactions for trace element loading to the
watershed.
Throughfall samples were collected on a weekly basis. Depending on the number of
rainstorms during the week, the throughfall sample represented either a single storm or was a
composite of more than one storm. At the time of sample collection, the amount of rainfall
collected in each rain gauge was recorded. The funnels, throughfall collection bottles, and
Tygon® tubing were thoroughly rinsed with distilled water after the samples were collected in
preparation for the next rainstorm. If there was no precipitation/throughfall during the week,
the collectors were still rinsed and cleaned with DI-H2O. Periodically, the bottles, funnels, and
tubing were replaced. One deciduous and one coniferous throughfall sample was collected
and the samples were submitted to the USGS laboratory for chemical analysis.
The staff gauge, in conjunction with an analog-to-digital recorder, was used to
determine and record stream stage near the outlet of the watershed. An existing natural
control in the stream provided a pool where the staff gauge could be located. The stream
stage was recorded on paper tape at 15-minute intervals by the Fisher Porter analog-to-digital
recorder. Every six weeks the paper tape was removed, and a discharge measurement of the
stream was made according to methods described in Buchanan and Somers (1968, 1969).
The stream-gauge data and the periodic discharge measurements were used to develop loglog rating curves, with coefficient of determination (r2) values ranging from 0.967 to 0.989
from which instantaneous stream discharges were calculated according to methods described
in Kennedy (1983, 1984). Mean daily stream discharges for the period of data collection can
be found in the annual Water Resources Data reports published by the USGS (U.S.
Geological Survey, 1993-95). These values were used to calculate fluxes.
Streamwater samples were collected weekly for most of the study period. The samples
were collected as grab samples from a point of maximum flow in the stream at the upstream
corner of the deck that supported the streamflow-gauging station. Streamwater samples were
submitted to the USGS laboratory for chemical analysis.
Precipitation, throughfall, and streamwater major ion samples were filtered in the field
immediately after collection through 0.l μm (micron) pore-size, cellulose-nitrate filters by using
positive pressure created by a peristaltic pump. Each sample was split into two aliquots: a
filtered acidified (FA) sample and a filtered chilled (FC) sample.
The FA sample was
prepared by filtering approximately 125 mL of sample into a 250 mL white, polyethylene bottle
that had been rinsed with nitric acid; then 200 μL of Baker's InstrAnalyzed nitric acid were
pipetted into the sample bottle. The addition of nitric acid acidified the sample to a pH of less
than 2.0 and served to preserve the sample. The FA sample was delivered to the laboratory
where it was analyzed for cation and silica concentrations. The FC sample was prepared by
filtering approximately 120 mL of sample into a 125 mL brown, polyethylene bottle that had
been rinsed three times with filtered sample water. When the sample volume retrieved from a
collector was insufficient to obtain full filtered samples, the FC sample bottle was rinsed three
times with distilled water and then with the first few drops of filtered sample water. The
sample was then collected from the available water, as previously described. The FC sample
was transported from the field on ice and stored at 4C in the laboratory. The brown bottle,
the filtration, and the chilled storage served to decrease the activity of organisms that can
cause the chemistry of the sample to change. The FC sample was analyzed in the laboratory
for alkalinity and anion concentrations, and pH.
Storm-flow samples for major ions were obtained using an automated Isco® sequential
sampler (Isco® Inc., Lincoln, Nebraska). The streamwater was pumped from the stream
through a polyethylene strainer that was attached to 9.5 mm diameter braided Tygon® tubing
by means of a peristaltic pump. The braided Tygon® tubing was connected in turn to silicon
peristaltic tubing.
The tubing ran through the distributor arm inside the Isco® automatic
sampler and delivered sample water sequentially to a series of 1,000 mL capacity
polypropylene bottles. Stormflow samples were retrieved from the field on a weekly basis, and
sometimes on a storm basis within one day of the storm. At that time, the bottles containing
the stormflow samples were replaced with a set of clean Isco® bottles. The Isco® sample
bottles were transported on ice to the USGS laboratory in Towson, Maryland where they were
processed either that day or the following day. The stormflow samples were submitted to the
USGS laboratory for chemical analysis.
The Isco® automatic sampler was controlled by a program on a CR10 data logger.
The program for the CR10 was modified from a program originally developed by N.E. Peters
(USGS, written communication, 1990). The site-specific program allowed the user to enter
the positive change in stage that would initiate the sampling program and the positive or
negative change in stage required for additional streamwater samples to be collected. Once
the storm-sampling routine had been initiated by the CR10 program, data on the date, time,
stage of the next rising or falling limb of the hydrograph, and sample number were stored on
the data-storage module. Observation of the stage/discharge relation at the site allowed the
user to enter appropriate numbers into the program that would cause the Isco® to collect
representative samples throughout the duration of stormflow. Because the Isco® has the
capacity to collect a maximum of 24 samples at a time, the numbers entered in the program
provided an optimal sample set for only a specific range of storm sizes. The numbers in the
program were periodically changed in order to obtain a data set over a wide range in
stormflow conditions. Changes to the CR10 program were made in the office through a
computer and the revised program was downloaded to a data-storage module. Upon arrival at
the field site, the new program version was downloaded from the data-storage module to the
CR10 data logger. Of the 61 events collected, 5 intensive storms were sampled that satisfied
the above criteria and three were of sufficient number to be presented in this report. As these
were in the late spring or summer, none represented particularly wet periods.
Trace Elements. During the entire project, wet-only precipitation was sampled for trace
elements on a weekly-integrated basis (Tuesday-Tuesday) in parallel with major ions. During
the initial phases of the study (17 August 1993 to 24 May 1994), bulk (wet + dry) deposition
as well as stream samples were sampled bi-weekly. Subsequently from May 1994 until 13
December 1994, the sampling frequency of both bulk and stream sampling was increased to
weekly (concurrent with the wet-only sampling) to achieve better temporal resolution and
assure congruity with the wet-only sampling. The bulk deposition samples consisted of a
tower sample (BT), situated next to the wet-only collector, and two canopy throughfall
samples, one deployed under a deciduous canopy and one under a coniferous canopy.
Wet-only precipitation was sampled using a commercially available, automated, wet-only
collector which was specially modified for trace element sampling (Aerochem Metrics, Inc.,
Bushnell, FL
33143).
Details of sample collection and processing were adapted from
Tramontano et al. (1987) and Scudlark et al. (1992) and are described in Section IV-B. The
sample buckets with lids were sealed in plastic bags and transported to the USGS laboratory
at Towson, Maryland for processing.
Bulk deposition and canopy throughfall were sampled using funnel/bottle collectors that
were continuously exposed to the atmosphere. The LDPE funnels employed had a surface
area of 860 cm2, and possessed 8 cm extended, vertical sides intended to minimize
resuspension of particles and snowfall. The funnel was attached to a 4 L LDPE sample bottle
by means of a watertight, screw-fitted LDPE coupling having an effective opening of 1 cm (to
minimize evaporation). At the time of retrieval, the funnels were rinsed with 50 mL of 0.04%
Qz-HCl in order to facilitate the transfer of material adhering to the funnel into the sample
bottle. The collection bottle was then detached, capped, doubly-sealed in clean plastic bags,
and returned to the laboratory for processing.
At the USGS laboratory, under a Class 1000 clean bench, the samples were acidified
with high-purity Qz-HCl to 0.4% (v/v).
Once acidified, the samples were allowed to
equilibrate for at least 24 hours, transferred to trace metal cleaned LDPE storage bottles, and
stored frozen in a trace metals-dedicated freezer at the laboratory pending retrieval by
University of Delaware personnel.
Thus, the atmospheric input we measured represents the
dissolved component plus the total acid-extractable (at pH1.5) fraction.
Studies in the
University of Delaware laboratory (Scudlark et al., 1992) and elsewhere have shown that
except for the crustal elements in the more refractory mineral phases (Al and Fe), most trace
elements in precipitation are highly soluble under these conditions.
Streamwater was initially sampled bi-weekly in conjunction with the throughfall sampling
from 07 September 1993 to 24 May 1994.
Instantaneous stream grab samples were
collected by filling a 1 L LDPE bottle directly from the stream, after three rinses. The sample
was filtered on-site (in the USGS clean van) through a 0.45 μm Gelman Groundwater
sampling capsule filter (Gelman Sciences, Ann Arbor, Michigan) into an LDPE bottle, acidified
to 0.4% (v/v) with Qz-HCl, and frozen.
Storm-flow sampling for trace metals was carried out in parallel with major ion
sampling, using a separate Isco® sampler (Model 3700), "slaved" to a common data logger.
The Isco® sampler was specially modified for trace element sampling as follows: Samples
were pumped directly from the stream through a polyethylene strainer (to exclude large leaf
litter and other debris) that was attached to 9.5 mm Teflon® tubing. The Teflon® tubing was
connected to silicon tubing at the inlet of the peristaltic pump, which was connected in turn to
another length of Teflon® tubing which ran through the distributor arm of the Isco® sampler.
Samples were pumped sequentially into 1000 mL polypropylene bottles. Sample sequencing
was controlled by the data logger, based on a change in stream height, as previously
described for major ions. All tubing and bottles used for trace metal sampling were precleaned using acid-washing procedures (Scudlark et al., 1992).
To minimize contamination, and to facilitate the collection of the particulates, the stream
intensive samples were frozen upon collection and transported to the University of Delaware
laboratory for processing. Upon receipt at the University of Delaware, the samples were
thawed and immediately filtered through pre-cleaned, tared, 0.45 μm polycarbonate filters
(Nuclepore® Corp., Sunnyvale, California) that were retained for particulate analysis.
Particulate samples were transferred to Teflon® bombs for a total digestion. The procedures
consisted of successive heatings with increasing amounts of concentrated acids. The final
digestate of HNO3:HCl:HF (approximate ratio 10:5:2) was brought to volume with saturated
boric acid solution.
B.
Analyses
Major Ions. Aliquots of precipitation, throughfall and streamwater were analyzed in the
field for specific conductance and pH. Specific conductance was measured for samples with a
YSI model 34 conductance-resistance meter, a model 3417 conductivity cell, and a
temperature compensator. The performance of the conductivity cell was checked on the day
of the sampling in standard specific conductance solutions. A Beckman Phi 31 pH meter, an
Orion Ross glass combination electrode, and a Beckman temperature compensator were used
to measure pH. The pH electrode was calibrated at the beginning of the sampling day with
standard buffer solutions of pH 7.0 and 4.0. The buffers were diluted approximately 50% by
the addition of distilled water to "sensitize" the electrode to the low-ionic-strength water it was
to measure. The calibration of the electrode then was checked in 10-4 normal H2SO4 (sulfuric
acid) (pH = 4.0). The electrode was calibrated two or more times during long sampling days.
Stormflow samples were filtered and prepared as previously described, except that the
sample processing was generally performed later in the day or the following day in the
laboratory.
The samples were allowed to equilibrate to room temperature before
measurements of specific conductance and pH were made. Each sample was then filtered
into discrete sample bottles; that is, no composite samples were collected. The filter was
changed after every third or fourth sample, and the filter and tubing to the pump were
thoroughly flushed with distilled water after each sample was filtered.
Water samples collected for the determination of major inorganic ion concentrations
were sent to the USGS laboratory in Reston, Virginia for analysis. Precipitation samples were
analyzed in the laboratory for dissolved calcium (Ca2+), magnesium (Mg2+), sodium (Na+),
potassium (K+), ammonium (NH4+), chloride (Cl-), nitrite (NO2-), nitrate (NO3-), sulfate (SO42), and for pH (for quality-assurance purposes). Streamwater samples were analyzed for Ca2+,
Mg2+, Na+, K+, Cl-, NO2-, NO3-, SO42-, bicarbonate (HCO3-), silicon (reported as SiO2), and
for pH (for quality-assurance purposes).
Filtered acidified (FA) samples were analyzed for dissolved concentrations of Ca2+,
Mg2+, Na+, K+, and SiO2 while filtered chilled (FC) samples were analyzed for dissolved
concentrations of NH4+, Cl-, NO2-, NO3-, SO42-, and HCO3-. Laboratory pH of these samples
was determined for quality-assurance purposes only.
Dissolved concentrations of Cl-, NO2-, NO3-, and SO42- were determined using a
Dionex 2110i ion chromatograph. The Waters Maxima 820 Chromatography Workstation was
used to collect, calculate, and report the ion-chromatographic data. The detection limits, in
microequivalents per liter (μeq/L) were as follows: Cl-, 1.8; NO2-, 0.8; NO3-, 0.45; and SO42, 0.8. A Dionex 100DX ion chromatograph with Waters Maxima 820 computer program was
used to determine NH4+ concentrations with a detection limit of 2.4 μeq/L.
Base cation concentrations were analyzed simultaneously by DCP-OES using an ARL
Spectra Span V DCP-A.
Silica concentration was determined separately by DCP-OES
because of possible interferences. During this period, detection limits (defined here as the
minimum concentration that can be measured with a 95% confidence limit), in μeq/L, were as
follows: Ca2+, 0.45; Mg2+, 0.05; Na+, 0.13; K+, 0.2; and in μm/L, SiO2, 0.43. The detection
limit was determined for every sample analyzed by statistical calculation, using computer
software incorporated in the DCP-OES instrument. A measured concentration reported in the
tables can be lower than the instrument detection limit because the unique combination of the
signal and the noise for an individual sample makes it possible for a concentration lower than
the normal detection limit to be measured.
Acid-neutralizing capacity (ANC) can be operationally defined as the equivalent sum of
all the base that can be titrated with a strong acid to a determined equivalence point. It
measures the net deficiency of protons, which can include non-carbonate contributions such as
ammonia, borate, hydroxide, organic ligands, phosphate, silicate, and sulfide (Stumm and
Morgan, 1981). In freshwater streams with a pH range of the samples in this study, it can be
assumed that bicarbonate alkalinity and positive ANC are equivalent.
Radiometer's Low Ionic Strength Titration System (LIST) was used to determine ANC.
This system employs a modified Gran Titration. The calculation procedure determines the
ANC by utilizing the acid-titration data. A modified Gran Titration calculation can result in a
negative value; therefore, the method has no detection limit.
Trace Elements. Atmospheric deposition and stream samples were analyzed for Al,
Cd, Cu, Cr, Fe, Mn, Ni, Pb, and Zn using a Perkin Elmer 3300 Atomic Absorption
Spectrophotometer, equipped with a 600 HGA graphite furnace (GFAAS) as published
(Tramontano et al. (1987); Scudlark et al., [1992]). This instrument was also equipped with
deuterium background correction, and a L'vov platform was utilized to maximize temperature
stability. For Al analysis, due to acidification with HCl, the char/ash step is limited to 170C
to prevent volatilization of AlCl3 (b.p. 185C). Citric acid was used as a matrix modifier for Al
and Fe to increase analytical sensitivity. The standard analyte injection was 60 μL for all
elements except for Zn (10 μL). Multiple injections were used for Cr, Ni and Pb, increasing
the volume of analyte to 120-180 μL and thus, augmenting the sensitivity 2-3 times.
The trace elements As and Se were present in precipitation at concentrations
significantly lower than the detection limits achievable using commercially available hydride/AA
systems. Accurate quantification of these elements require the application of nontraditional
analytical methods (Cutter, 1986; Cutter et al., 1991). Methods for both As and Se involved
hydride generation, preconcentration by cryogenic trapping and subsequent volatilization. The
As hydride (arsine) was determined using gas chromatography-photoionization detection, while
the Se hydride was determined with an air/hydrogen quartz burner fitted to an atomic
absorption spectrometer. Larger analytical volume requirements limit metalloid analysis to
precipitation samples greater than 200 mL (ca. 0.3 cm precipitation). Thus, these elements
were analyzed in volume weighted monthly integrated samples so that all events could be
included.
Employing the above methodologies, the analytical detection limits for all of the
elements determined were conservatively estimated (D.L.= 3X std. dev. of analytical blank).
The analytical techniques and detection limits for all metals are summarized in Table 1.
Error Analysis. Due to study restrictions, field replicates of atmospheric deposition and
stream sampling were not performed. This restricts the ability to determine the overall spatial
variability within the watershed.
However, care was taken during the site selection to
determine very representative areas for each collection type.
Additionally, any sample
exhibiting noticeable field contamination (leaf debris, insects, etc.) were noted and taken into
consideration during data analysis.
In spite of field collection limitations, great care was taken to ensure that during
subsequent steps of sampling, analysis and data reduction all errors in the form of standard
deviations were examined and recorded. These errors were held at <10% as documented as
follows in the Quality Control section.
Table 1. Analytical techniques and detection limits for the trace elements analyzed for this study. Detection limits for
particulate analyses are calculated assuming 0.1 mg dry weight of particulate and dilution to 25 mLs; however,
actual detection limits vary with the mass of particulate (sediment) collected onto the fiber. The dissolved
fraction is reported as micrograms per liter and the particulate fraction as micrograms per gram.
Constituent
Al (Aluminum) particulate
GFAAS
As, (Arsenic), particulate
As, dissolved
Cd (Cadmium), particulate
Cd, dissolved
Technique
ICPAES
Detection Limit
3.0 µg/g
Al,dissolved
0.4 µg/L
Hydride, AAS
Hydride, AAS
0.18 µg/g
0.005 µg/L
GFAAS
0.10 µg/g
0.006 µg/L
GFAAS
Cr (Chromium), particulate
Cr, dissolved
ICPAES
GFAAS
3.0 µg/g
Cu (Copper), particulate
Cu, dissolved
ICPAES
GFAAS
3.0 µg/g
Fe (Iron), particulate
Fe, dissolved
ICPAES
GFAAS
2.0 µg/g
Pb (Lead), particulate
Pb, dissolved
GFAAS
GFAAS
Mn (Manganese), particulate
Mn, dissolved
ICPAES
GFAAS
3.0 µg/g
Ni (Nickel), particulate
Ni, dissolved
ICPAES
GFAAS
3.0 µg/g
Se (Selenium), particulate
Se, dissolved
Hydride, AAS
Hydride, AAS
Zn (Zinc), particulate
Zn, dissolved
ICPAES
GFAAS
0.03 µg/L
0.03 µg/L
0.05 µg/L
3.0 µg/g
0.03 µg/L
0.1 µg/L
0.1 µg/L
0.22 µg/g
0.005 µg/L
3.0 µg/g
GFAAS = Graphite Furnace, Atomic Absorption Spectroscopy
ICPAES = Inductively Coupled Plasma, Atomic Emission Spectroscopy
0.1 µg/L
V.
QUALITY ASSURANCE AND CONTROL
Major Ions.
Quality assurance (QA) of the major ion field data collection and
laboratory analyses was accomplished through a series of approved methods, which included
the analysis of field and laboratory standards, duplicates, blanks, analyses of the DI-H2O and
reagents used in the field and laboratory, and comparison of calculated specific conductivity to
measured specific conductivity of selected samples. In addition, inter-laboratory comparisons
of analytical results of standard reference water samples were performed biannually. As a
further verification of the major ion data quality, ion balances were calculated for each sample.
For the ion chromatography analyses (anions and NH4+), each set (20-40) of samples
was preceded by four multi-element standards. For the instrumental calibration curves to be
acceptable, a minimum correlation coefficient (r2) of 0.999 was required. In instances when
the concentration of any ion of interest in the sample exhibited a concentration larger than the
highest standard, a quantitative dilution of the sample was made and it was reanalyzed.
During the chemical analysis of a set of samples, known standard solutions were analyzed
after every fifth sample. In addition, certified reference solutions, obtained from the National
Institute of Standards and Technology (NIST) (for precipitation samples, Simulated Rain Water
NIST Standard 2964A; for stream samples USGS standard water sample for trace constituents
designated as Central Lab Standard USGS WRD BDTQS Central Lab Quality Assurance
Group Round Robin, Golden, CO 80401), were analyzed at the beginning and end of each
analytical session in order to assess the precision of the instrument.
Cation standard solutions were prepared from commercially available stock solutions by
dilution with a 0.5% nitric-acid matrix. This acid concentration approximates the acidity of the
FA samples analyzed. A blank solution was prepared using just the 0.5% nitric-acid solution.
This procedure ensured that the generated calibration curve was of the same ionic strength
as the analyzed FA samples. During the set of analyses, the high standard solution was
analyzed and calibrated after every 5 samples and the low standard solution (the blank) was
analyzed and calibrated after every 10 samples. The same rigorous QC methods were used
for the determination of SiO2 concentration.
Samples that had an ion-balance error of more than ±10% were repeated if there was
no direct evidence of a contributing organic acid or NH4+ concentration. For samples with an
anion deficit of more than 10% (most commonly throughfall), the presence of organic acids
was determined by analysis of dissolved organic carbon using a Shimadzu TOC-5000 carbon
analyzer. Because NH4+ in throughfall samples is unstable (M. M. Kennedy, USGS, personal
communication) qualitative determinations for NH4+ were performed by ion chromatography to
confirm the presence of NH4+ for QA purposes, but not to report or quantify it in throughfall.
Trace Metals.
Due to their typically low concentrations and high potential for
contamination, the accurate measurement of trace elements in precipitation and surface waters
requires strict adherence to a rigorous Quality Assurance program. The QA program for trace
metals encompassed all components of this study, from the initial site selection to final data
validation. Essential elements of this QA program were:
a)
conducting and evaluating procedural blanks on a regular basis,
b)
use of externally certified analytical reference solutions, and
c)
conducting
replicate
analysis,
using
redundant
analytical
techniques when possible.
To ensure cleanliness and uniformity, all precleaned plasticware (funnels, sample
bottles, collection buckets, pipette tips), reagents (DI-H2O, Qz-HCl) were provided by the
University of Delaware laboratory. To remove trace element contamination introduced via
manufacture and/or prior use, all plasticware (collection buckets and sample bottles) were
rigorously cleaned. This cleaning involved successive leaching in acids of varying composition
and strength. Ultra-pure ASTM Type I (18 megohm/cm) rinse water (Millipore Milli-Q) was
used for all sample processing and cleaning (subsequently referred to as DI-H2O). Ultra-pure,
double quartz-redistilled HCl (Qz-HCl) was used for sample acidification, analysis and
processing, which included a final "polishing" leach in the cleaning procedure. Analytical
standards were prepared gravimetrically from certified standards, which were prepared in turn
from pure metal dissolution (SPEX Industries, Inc.). All other reagents were of at least ACS
quality. Every sample was carefully processed under a clean bench in a dedicated clean
room.
Blanks. Most contamination associated with accurately quantifying the trace elements
in precipitation is associated with field deployment and sampling.
Thus, conducting and
evaluating operational blanks on a regular basis is the most critical component in our QA
Program.
Three types of additive, diagnostic operative blanks were routinely conducted in
conjunction with precipitation and throughfall sampling: a Field Blank, Laboratory Blank, and
Process Blank.
Data from these blanks were interpreted both to accurately quantify the
background trace element contribution from materials and methods, and to identify and remedy
any source of severe contamination.
Additionally, all sampling equipment was tested to
determine the potential trace metal contamination of each step along the sampling chain.
The Process Blank consisted of DI-H2O in a sample storage bottle, to which was
added Qz-HCl in a ratio identical with normal samples (0.4% v/v). The Process Blank is
thus a measure of the trace element contribution from the water, acid, leaching from the
storage bottle and analytical procedures. The Laboratory Blank was DI-H2O poured into a
clean bucket or funnel under a clean bench, acidified, and otherwise handled as with a bona
fide sample. The Laboratory Blank gauges trace element input from all sources including the
Process Blank, as well as metal leached from the collector bucket/funnel or contributed from
airborne dust during the additional handling steps. The Field Blank was conducted identically
to the Laboratory Blank, except employing a bucket or funnel which was previously deployed
in the collector for a representative (weekly) interval without rain. In addition to the sources
incorporated in the Laboratory Blank, the Field Blank reflects all metal input from the passive
capture of fugitive dust during sampler transport, deployment, and recovery. The Field Blank
thus provided the most comprehensive representation of contamination during actual sample
collection and processing.
A total of 64 various types of blanks were collected and analyzed as part of the QA
program.
These results (Fig. 2) indicate that the samples exceeded the field blanks by
factors of at least 3 to as much as 20 fold.
Field blanks were similarly conducted for stream grab and storm sampling. For the
stream grab samples, an aliquot of acidified (0.4%) DI-H2O was filtered and processed in
parallel with the normal samples. For the storm sampling, DI-H2O was pumped through the
Isco® sampler, filtered and processed along with the stream samples. Again, these results
(Fig. 3) indicate that the samples exceeded the field blanks by factors of at least 3 to as
much as 20 fold.
Standard GFAAS calibration curves included an analytical blank and at least three
standards. Additionally, the standard additions method was used on one sample every 15
samples to verify the calibration curve. Externally certified reference samples were regularly
included in analytical sessions to verify the accuracy of the calibration curve.
Replicate
samples were run on separate days to verify true analytical reproducibility (which included but
was not limited to instrument reproducibility). Reproducibility of less than 10% variation was
deemed acceptable.
Standard curves for the metalloid determinations included a blank and at least four
standards. Large volume events (about 30% of all analyses) were analyzed by the method of
standard additions. Samples were run at least in triplicate and 5-10% of the samples were
replicated on a second day to establish reproducibility. The calibration was verified utilizing
certified reference solutions.
VI.
RESULTS AND DISCUSSION
A.
Atmospheric Inputs
Precipitation. The 16 months of sample collection at Bear Branch yielded 43 wet only
precipitation samples and 37 of each type of bulk deposition (tower, deciduous and
coniferous). From 1982-93, the average annual amount of precipitation on Catoctin Mountain
was 114 cm. This 12-year average compares favorably with the long-term average (1931-80)
of 112 cm for north-central Maryland (NOAA, 1981). For the 12-year period of record, the
variability in the annual amount of precipitation ranged from 93.7 cm in 1982 to 148.5 cm in
1984. Compared with the long term annual average observed at Bear Branch (114 cm/yr),
the average precipitation amount during the 16-month study period (127 cm/yr) was
somewhat larger than normal but well within the range observed over the past 12 years. This
is somewhat misleading in that the last four months of 1993 were wetter than average, with
62 cm of precipitation falling during that period, while the entire calendar year 1994 was
slightly below the average, receiving 108 cm of precipitation. This is reflected in the stream
discharge, with calendar year 1993 having an annual discharge of 8771 L/s and 1994 a
discharge of 6912 L/s. Taking together the last four months of 1993 and all of 1994, the
study period was wetter than average overall. For the sake of comparison, 168.8 cm of
precipitation fell during the 16 months of the study period. For computational purposes, we
have calculated the annual average precipitation during the 16 month study period based on
the monthly average. Calculated in this manner, the precipitation for the average study year
was 127 cm, which is slightly above the 12-year (1982-93) average of 114 cm.
Major Ions. The major ions present in atmospheric deposition come from a number of
sources, including sea salt, terrestrial materials entrained by wind, and anthropogenic
materials, particularly emissions of SO2 and NOx that ultimately oxidize to SO42- and NO3-.
Because of compounds from anthropogenic emissions, precipitation falling on Catoctin
Mountain is some of the most acidic in the United States (Rice and Bricker, 1992). When
wet deposition falls on the forest canopy, additional materials that have collected on leaves
from atmospheric sources or have been exuded onto the surfaces of leaves by the trees’
internal processes, are washed off in throughfall. The composition of throughfall is therefore
more concentrated than wet precipitation.
Data for major ions in atmospheric deposition are presented in Table 2 for wet-only
precipitation, Table 3 for bulk throughfall under the deciduous canopy, and Table 4 for bulk
throughfall under the coniferous canopy. A comparison of major ion chemistry between this
study and the long term (1982-91) volume-weighted average concentration at the same site is
summarized for wet precipitation in Table 5 and the average of the previous three years
(1991-93) of canopy throughfall in Table 6.
Major ion concentrations for this site have
already been published and discussed extensively elsewhere (Rice et al., 1993 and Rice and
Bricker, 1996). The primary purpose for acquiring major ion data during the current study was
the NETPATH modeling of chemical weathering. The wet precipitation major ions during the
study period, in general, closely resemble the long-term averages reported for the previous
decade, but the study period precipitation was slightly more dilute than the long-term average
in all concentrations except H+ which was slightly more concentrated.
Table 2. Major ion concentrations (µeq/L) in wet only precipitation.
DATE
NO2-
08/24/93
09/07/93
09/14/93
09/21/93
09/28/93
10/05/93
10/12/93
10/19/93
10/26/93
11/02/93
11/09/93
11/16/93
11/23/93
11/30/93
12/07/93
12/14/93
12/22/93
12/30/93
01/05/94
01/25/94
02/08/94
02/15/94
02/22/94
03/01/94
03/07/94
03/15/94
03/22/94
03/30/94
04/12/94
04/19/94
05/10/94
05/17/94
05/24/94
05/31/94
06/07/94
06/21/94
06/28/94
07/06/94
07/12/94
07/20/94
07/26/94
08/02/94
08/09/94
08/16/94
08/23/94
08/30/94
COND
pH
pH
us/cm
lab
field
45
12
32
30
34
57
28
15
18
26
12
27
18
12
15
34
30
48
11
97
69
17
25
17
14
41
58
30
26
15
28
19
110
34
53
90
21
34
45
47
32
51
23
44
12
41
4.11
4.81
4.31
4.32
4.23
4.07
n.a
4.72
5.07
4.45
4.81
4.43
4.58
4.75
4.80
4.21
4.22
n.a.
4.85
3.84
3.95
4.69
4.43
4.61
4.65
4.18
4.06
4.36
4.52
4.67
4.38
4.44
n.a.
4.24
4.10
3.75
4.45
4.20
4.04
4.05
4.20
4.00
4.29
4.40
4.94
4.43
3.86
4.55
4.05
3.69
3.67
3.65
3.99
3.93
4.00
3.39
4.40
4.23
4.44
4.67
4.44
3.87
4.03
3.82
4.47
3.59
3.86
4.29
4.30
4.49
4.74
4.10
3.96
4.24
4.38
4.62
4.42
4.31
3.66
4.24
3.97
3.68
4.39
4.12
3.95
4.00
4.18
3.92
4.24
4.02
4.74
3.90
H+
138
28.2
89.1
204
214
224
102
118
100
407
39.8
58.9
36.3
21.4
36.3
135
93.3
151
33.9
257
138
51.3
50.1
32.4
18.2
79.4
110
57.5
41.7
24.0
38.0
49.0
219
57.5
107
209
40.7
75.9
112
100
66.1
120
57.5
95.5
18.2
126
Ca2+
Mg2+
Na+
K+
NH4+
µeq/L µeq/L µeq/L µeq/L
µeq/L µeq/L
11.5 1.56
0.7
0.6
6.0 1.48
1.6
0.6
10.5 2.47
0.5
1.0
5.0 1.23
1.9
0.5
<0.5 0.56
1.5
0.5
10.0 2.47
2.8
0.8
n.a. n.a.
n.a.
n.a.
<0.5
0.41
0.3 <0.2
22.5 2.47
1.1
27
4.0 1.73
4.4 <0.2
<0.5
0.50
0.6
0.6
5.5 1.40
2.3
0.6
5.0 1.74
3.4
0.6
<0.5 3.37
14
<0.2
2.5 1.23
1.8 <0.2
10.5 2.05
4.1
0.6
6.5 1.10
2.5
0.4
n.a.
n.a
n.a.
n.a
6.0
2.20
10
0.6
40.9 6.10
29
2.1
15.5 2.90
6.5
0.6
9.0
3.20
2.7
0.4
4.5
1.90
6.0
18
<0.5 0.40
0.3
<0.2
4.5
1.40
1.2
0.3
6.0
1.90
3.7
0.2
16.5 3.00
2.4
8.4
5.5
0.80
0.7
0.4
3.5
1.90
6.8
0.7
3.5
1.50
4.2
0.5
3.5 0.84 <0.1 <0.2
15.2 2.88
0.4
1.9
n.a. n.a.
n.a.
n.a.
12.0 2.05 <0.1
0.4
19.0 4.11
44
2.2
12.9 3.21
2.9
0.8
8.6 1.65
2.9 <0.2
12.0 1.98
0.6
3.0
8.2
1.07
0.4
0.5
4.7 0.66 <0.1
0.5
12.7 1.89
2.2
1.4
7.7 1.48 <0.1
3.2
6.4
0.74
0.6
0.5
7.3 1.98
1.8
1.1
6.4 1.73
3.3
1.2
14.0 1.32
<0.1
2.3
(Table con’t. on next page)
34.8
18.0
28.4
22.1
14.2
18.6
n.a.
8.7
10.4
12.3
2.8
1.8
<2.4
<2.4
12.6
4.2
<2.4
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
18.3
13.4
39.4
<1.8
<1.8
3.7
4.0
4.3
6.1
n.a.
2.6
7.1
6.8
1.4
4.6
4.3
17.2
4.9
5.0
4.3
n.a.
10.7
28.8
11.9
14.3
26.0
4.1
5.3
8.3
14.1
2.6
7.0
6.0
3.0
3.9
n.a.
4.2
6.2
10.4
6.9
7.0
4.7
4.2
6.1
8.7
5.7
4.9
6.0
4.3
Cl-
NO3-
SO42-
µeq/L µeq/L µeq/L
30.5
12.7
20.5
19.9
25.6
48.3
n.a.
10.9
14.8
24.7
10.6
19.0
15.7
7.7
11.9
23.9
46.8
n.a.
18.7
119
81.6
22.0
18.9
18.5
16.0
32.0
54.9
18.0
20.0
16.6
16.5
23.6
n.a.
29.1
36.2
73.6
22.4
26.2
25.6
30.6
28.0
42.4
26.0
22.2
8.8
28.7
97.4
24.2
68.7
55.7
65.9
88.6
n.a.
23.0
38.8
34.4
19.4
29.5
24.8
18.8
23.3
55.1
33.8
n.a.
19.6
135
110
36.1
35.2
23.4
17.6
57.0
88.5
40.8
40.9
26.2
40.3
59.5
n.a.
90.3
99.3
197
45.6
78.0
106
96.4
69.5
95.0
50.3
73.0
24.9
8 5.8
<0.8
0.8
<0.8
0.5
0.3
0.4
n.a.
<0.8
<0.8
0.4
1.1
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
n.a.
<0.8
0.8
1.0
<0.8
<0.8
<0.8
<0.8
<0.8
0.2
<0.8
<0.8
0.8
<0.8
<0.8
n.a.
<0.8
<0.8
0.3
<0.8
0.2
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
1.4
Table 2. Major ion concentrations (µeq/L) in wet only precipitation.
(Con’t.)
DATE
NO2-
COND
pH
pH
us/cm
lab
field
45
11
39
19
25
10
12
24
23
10
11
21
31
4.08
4.71
4.25
4.87
4.45
4.42
4.66
4.29
4.31
4.65
4.64
4.47
4.16
3.99
4.69
4.08
4.48
4.21
4.65
4.65
4.16
4.24
4.62
4.56
4.22
3.95
09/20/94
09/27/94
10/04/94
10/11/94
10/25/94
11/01/94
11/08/94
11/15/94
11/22/94
11/29/94
12/06/94
12/13/94
12/20/94
n.a. =
not available
H+
102
20.4
83.2
33.1
61.7
22.4
22.4
69.2
57.5
24.0
27.5
60.3
112
Ca2+
Mg2+
Na+
K+
NH4+
µeq/L µeq/L µeq/L µeq/L
µeq/L µeq/L
9.4
4.6
21.1
5.5
<0.5
<0.5
1.0
3.5
<0.5
<0.5
<0.5
n.a.
6.3
55.2
14.1
27.7
32.1
11.9
6.5
9.3
30.1
11.8
8.5
5.4
n.a.
2.4
2.14
2.30
3.21
2.28
0.21
0.16
0.31
1.54
1.71
0.39
0.51
n.a.
6.58
<0.1
0.6
0.7
1.9
<0.1
1.9
2.8
3.1
0.2 <0.2
0.2 <0.2
0.4 <0.2
1.6
14
7.5 <0.2
1.6 <0.2
2.4
3.1
n.a.
n.a.
30.5
6.2
3.9
3.4
3.4
7.8
5.2
5.1
5.0
16.6
10.1
6.6
6.9
3.2
44.1
Cl-
NO3-
SO42-
µeq/L µeq/L µeq/L
28.6
13.1
34.4
15.5
20.3
10.9
10.9
31.3
16.6
11.5
9.3
9.3
34.7
106
26.9
77.2
31.6
36.0
19.5
25.5
46.1
28.5
22.9
21.4
24.9
62.7
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
<0.8
Table 3. Major ion concentrations (µeq/L) in bulk throughfall under a deciduous canopy.
DATE
08/24/93
09/07/93
09/14/93
09/21/93
09/28/93
10/05/93
10/12/93
10/19/93
10/26/93
11/02/93
11/09/93
11/16/93
11/23/93
11/30/93
12/07/93
12/14/93
12/21/93
01/25/94
02/08/94
03/07/94
03/22/94
03/30/94
04/12/94
04/19/94
05/10/94
05/24/94
05/31/94
06/21/94
06/28/94
07/06/94
07/12/94
07/20/94
08/02/94
08/09/94
08/16/94
08/23/94
08/30/94
09/20/94
09/27/94
10/04/94
10/25/94
11/01/94
11/08/94
11/15/94
11/22/94
11/29/94
12/06/94
12/13/94
COND
us/cm
52
22
25
23
39
42
35
22
66
92
23
56
41
24
23
28
48
46
66
28
53
31
22
26
53
23
59
71
24
25
48
3.6
51
24
37
44
40
52
17
33
53
110
24
57
26
13
11
25
pH
lab
4.38
4.78
4.84
5.12
4.42
4.85
5.52
6.41
6.50
6.27
5.95
6.90
6.14
5.50
4.51
4.47
4.20
4.33
4.03
4.44
4.15
4.37
5.34
4.48
6.85
6.06
3.87
6.16
5.43
4.77
4.13
4.33
4.09
4.63
4.90
5.22
4.94
4.46
5.94
4.43
6.16
6.02
7.04
6.59
5.99
5.11
4.93
4.39
n.a. = not analyzed
pH
field
4.09
4.67
4.55
3.76
3.98
4.51
5.66
6.45
6.64
6.18
5.90
7.00
6.72
5.23
4.29
4.26
3.92
4.06
3.93
4.39
4.06
4.28
5.28
4.50
6.35
6.62
3.77
5.94
5.36
5.50
4.09
4.33
4.08
4.86
4.61
5.07
4.43
4.43
5.53
6.23
6.08
5.68
6.65
6.60
5.79
4.76
4.73
4.41
H+ Ca2+ Mg2+
µeq/L µeq/L
81.3 91.8
27.4
21.4 50.9
13.8
28.2 52.4
16.3
174 66.4
20.0
105 56.4
17.6
30.9 103
33.4
2.19 61.9
23.0
0.35 44.9
18.1
0.23 205
88.9
0.66 272
140
1.26 39.9
19.5
0.10 85.3
53.3
0.19 45.9
29.0
5.89 21.5
15.9
51.3 8.50
6.90
55.0 28.4
12.0
120 42.4
17.6
87.1 27.0
13.0
117 24.5
11.3
40.7 17.5
5.40
87.1 40.9
12.8
52.5 18.5
5.40
5.25 37.9
11.2
31.6 24.0
9.30
0.45 74.4
45.9
0.24 129
120
170 43.5
28.4
1.15 n.a.
n.a.
4.37 56.4
30.9
3.16 67.2
33.2
81.3 44.0
20.8
46.8 41.2
14.3
83.2 40.9
16.1
13.8 50.3
15.8
24.5 n.a.
n.a.
8.51 24.8
9.22
37.2 85.1
29.1
37.2 139
44.4
2.95 44.7
17.3
0.589 107
53.8
0.832 138
46.3
2.09 449
174
0.224 30.9
25.2
0.251 87.3
65.5
1.62 14.5
19.9
17.4 6.0
6.67
18.6 2.4
3.89
38.9 12.4
6.58
Na+
K+
µeq/L µeq/L
2.9
95.9
3.1
41.7
1.3
39.7
2.7
48.1
2.6
53.0
8.7
87.7
13.5
123
4.1
78.3
11.8
264
21.7
389
1.9
101
9.1
251
6.3
227
44.0
57.8
3.8
29.7
2.0
29.7
4.1
33.3
44.4
24.3
35.8
13.0
5.7
7.0
11.7
10.3
2.0
7.30
10.4
13.0
13.4
11.5
5.4
126
59.2
10.6
0.5
88.3
n.a.
n.a.
6.6
65.2
8.7
81.7
2.7
69.2
1.9
26.9
0.2
18.8
0.7
65.7
n.a.
n.a.
4.9
16.8
1.2
52.1
1.7
74.1
2.1
52.7
0.7
117
9.3
253
5.5
437
1.2
202
4.1
399
29.3
123
5.7
21.0
3.5
10.9
1.2
31.5
nd = not detected
Cl +
µeq/L
13.3
3.4
5.5
7.8
7.9
16.9
26.5
11.4
27.6
50.5
9.1
32.6
15.5
56.3
7.1
5.9
11.3
52.9
44.7
9.3
18.5
4.8
17.4
18.6
16.0
19.5
7.8
27.6
17.4
5.7
6.9
6.8
6.4
9.9
9.5
8.7
7.2
14.7
6.4
28.9
25.9
29.2
20.9
47.0
15.0
7.0
11.4
6.4
NO3µeq/L
3.1
1.4
4.8
7.3
31.8
60.2
30.3
11.0
26.2
26.3
0.8
36.0
nd
20.4
25.4
22.6
72.4
55.9
70.8
38.4
71.3
29.9
48.2
39.4
6.9
3.4
1.3
9.6
76.1
33.8
41.4
42.4
48.5
58.1
47.5
14.0
44.9
80.2
19.3
32.0
44.1
3.0
2.9
3.2
5.7
8.8
21.8
16.1
SO4- NO2SIO2
µeq/L µeq/L µm/L
1.8
nd
1.8
47.8
nd
nd
97.2
nd
nd
98.1
nd
2.5
122
0.4
1.1
126
nd
3.6
63.3
0.4
1.1
51.5
0.7
2.5
161
nd
10
132
1.0
4.8
71.1
nd
0.7
113
1.2
1.7
72.6
nd
1. 3
45.8
nd
nd
47.4
nd
nd
67.6
nd
nd
88.4
nd
nd
71.5
nd
nd
120
0.9
nd
34.4
nd
nd
82.0
nd
nd
50.9
nd
nd
60.3
nd
nd
54.0
nd
nd
97.4
1.3
nd
144
nd
nd
134
nd
nd
21 5
5.3
nd
98.8
nd
5.0
9 3.7
0.3
nd
142
nd
nd
94.6
nd
nd
122
nd
nd
152
nd
nd
11 5
nd
nd
40.9
nd
nd
114
nd
nd
257
nd
nd
45.3
1.1
nd
111
nd
nd
87.3
nd
nd
73.8
nd
7.6
39.3
nd
nd
81.0
nd
nd
39.2
nd
nd
24.8
nd
nd
14.4
nd
nd
58.8
0.8
nd
Table 4. Major ion concentrations (µeq/L) in bulk throughfall under a coniferous canopy.
DATE
COND
pH
pH
H+ Ca2+ Mg2+ Na+
K+
Cl +
NO3us/cm
lab
field
µeq/L µeq/L µeq/L µeq/L µeq/L µeq/L
08/24/93
63
4.19
4.05 89.1 104
27.3
3.2
85.4
19.6
42.5
09/07/93
32
4.52
4.31 49.0 39.9 11.2
2.1
29.7
7.7
25.1
09/14/93
39
4.27
4.04 91.2 40.4 11.6
1.0
25.1
8.2
28.4
09/21/93
35
4.36
3.28 525 43.9 12.1
2.6
24.1
9.9
26.4
09/28/93
54
4.13
3.70 200 47.9 15.4
2.3
44.3
9.9
39.4
10/05/93
71
4.11
3.66 219 97.3 29.1
8.4
51.9
24.4
79.1
10/12/93
30
4.82
4.47 33.9 36.9 12.0
8.8
50.1
22.0
4.1
10/19/93
10
5.35
4.85 14.1 16.0 5.00
2.0
17.1
5.9
5.3
10/26/93
66
5.44
4.92 12.0 190
65.3 13.0
155
52.5
60.9
11/02/93
65
5.81
5.57
2.7 157
80.6 27.3
271
69.9
61.1
11/09/93
40
4.56
3.97 107 65.4 25.6
2.9
49.4
15.0
36.8
11/16/93
100
4.26
4.11 77.6 198
78.2 10.9
143
61.5
241
11/23/93
66
4.14
4.0
85.1 88.8 33.4
9.1
66.0
27.5
80.8
11/30/93
37
4.41
4.41 38.9 33.9 14.5 45.7
16.1
65.9
37.0
12/07/93
41
4.31
3.81 155 27.9 11.5
7.4
15.1
11.4
47.3
12/14/93
64
4.06
3.87 135 61.4 22.5
4.0
21.0
12.5
57.0
12/21/93
74
3.96
3.64 229 67.9 22.4
5.9
20.7
16.8
89.0
01/25/94
110
4.03
3.73 186 127
40.8 108
26.4
95.5
133
02/08/94
180
3.64
3.58 263 154
49.3 112
50.1
141
213
02/22/94
100
3.93
3.83 148 83.3 23.5 52.6
21.5
66.5
147
03/07/94
49
4.17
4.11 77.6 26.5 8.50 11.4
14.2
16.0
55.5
03/22/94
110
3.83
3.72 191 93.3 27.4 27.4
22.8
44.2
170
03/30/94
53
4.08
4.02 95.5 24.5 7.40
5.3
15.9
10.0
51.1
04/12/94
83
4.00
3.92 120 81.3 23.3 17.9
27.4
32.3
133
04/19/94
48
4.17
4.19 64.6 41.9 13.6 17.0
19.2
30.6
62.4
05/10/94
150
7.02
6.23
0.6 104
96.1 18.3
439
47.8
9.2
05/24/94
76
5.71
6.48 0.331 n.a
n.a.
n.a.
n.a.
31.4
22.6
05/31/94
44
5.41
4.40 39.8 52.3 28.2
1.6
73.2
12.8
17.8
06/21/94
130
4.34
4.35 44.7 n.a.
n.a.
n.a.
n.a.
53.5
211
06/28/94
51
4.53
4.46 34.7 61.7 27.7
3.0
50.7
18.9
83.7
07/06/94
41
4.27
4.27 53.7 49.3 22.4
1.7
44.5
10.1
47.6
07/12/94
59
4.11
4.06 87.1 46.4 18.4
2.5
47.4
15.0
72.9
07/20/94
54
4.16
4.19 64.6 62.9 26.3
1.7
48.2
1 3.7
81.4
07/26/94
34
4.42
4.46 34.7 38.7 14.5
3.5
37.9
10.6
36.7
08/02/94
54
4.14
4.14 72.4 50.6 21.6
1.1
35.8
9.7
57.4
08/09/94
60
4.24
4.14 72.4 104
54.2
2.5
86.4
15.3
65.9
08/16/94
68
4.26
4.28 52.5 n.a.
n.a.
n.a.
n.a.
27.0
105
08/23/94
96
4.69
4.53 29.5 33.8 14.5
4.1
29.9
12.7
32.1
08/30/94
58
4.45
4.07 85.1 86.9 37.0
3.3
74.1
15.9
60.1
09/20/94
95
4.06
3.98 105 142
58.3
4.8
124
57.5
97.9
09/27/94
28
4.56
4.54 28.8 31.5 16.7
2.6
70.8
14.4
30.2
10/04/94
53
4.43
4.28 52.5 76.0 35.2
2.3
105
19.7
34.7
10/25/94
56
4.57
4.74 18.2 114
61.1
8.5
177
73.4
127
11/01/94
45
4.53
4.53 29.5 66.9 33.7
4.6
105
35.7
69.9
11/08/94
13
5.46
5.28 5.25 18.5 10.4
1.0
48.6
9.2
3.1
11/15/94
92
4.15
3.99 102 204
64.4
8.3
84.4
33.2
214
11/22/94
39
4.23
4.27 53.7 39.9 21.2 27.4
25.3
43.6
58.0
11/29/94
27
4.56
4.53 29.5 20.5 23.3 10.0
15.9
18.7
38.0
12/06/94
19
4.51
4.48 33.1 12.5 6.67
5.9
6.4
11.8
20.5
12/13/94
52
4.09
4.10 79.4 55.9 25.5
4.9
93.6
15.4
35.4
n.a. = not analyzed
nd = not detected
SO4µeq/L
122
54.1
110
95.2
147
179
65.1
27.0
249
177
123
211
134
58.9
77.5
129
147
220
365
154
70.1
155
76.3
104
84.4
194
142
140
268
111
114
179
122
83.4
149
149
191
73.7
155
331
72.7
110
173
90.6
39.1
257
90.0
50.1
4 2.5
145
NO2SIO2
µeq/L µm/L
0.80
2.0
1.60
nd
0.70
nd
nd
nd
nd
nd
nd
1.4
nd
nd
nd
nd
nd
7.2
nd
4.1
nd
nd
nd
2.7
nd
1.6
nd
nd
nd
nd
nd
0.7
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
0.6
nd
nd
nd
nd
nd
nd
56
nd
7.8
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
nd
1.4
nd
1.9
nd
nd
nd
1.4
nd
nd
nd
nd
nd
nd
nd
nd
Table 5. Volume-weighted average (µeq/L) composition of precipitation, Catoctin Mountain, Maryland.
<-----------------------Cations------------------------>
H+
Ca2+
Mg2+
Na+
K+
NH4+
(field)
<--------Anions--------->
ClNO3- SO42-
Total
Total
Cations Anions
Long-termAverage*
(1982-1993)
69
std (±)
(14)
9
(3)
3
(1)
7
(3)
2
(1)
14
(1)
12
(3)
24
(3)
51
(7)
104
87
This Study Average
(1993-1994)
73
6
2
4
1
8
7
22
45
94
74
*Rice and Bricker (1996)
Table 6. Long-term annual average of major chemical constitutents in throughfall at Bear Branch Catoctin Mountain,
Maryland. Constituents in moles/hct/yr. (Rice and Bricker, 1993).
<------------------Cations------------------->
H+
Ca2+
Mg2+
Na+
K+
(field)
<-------------Anions-------------->
ClNO3- SO42- SiO2
Coniferous
std (+/-)
721
(365)
257
(91)
99
(35)
123
(10)
442
(96)
252
(112)
584
(236)
514
(116)
5.4
(1.1)
Deciduous
std (+/-)
460
(138)
239
(83)
106
(38)
90
(63)
612
(207)
178
(70)
296
(112)
412
(69)
8.9
(1.7)
The major cation in both wet precipitation and throughfall for the period of study was
H+ and the major anion was SO42-, followed by NO3-. No seasonal variability was observed
over the period of record in base-cation concentrations; however, H+ ion, SO42- and NO3- show
a seasonal pattern with the higher concentrations during the summer months. This is typical
of precipitation in regions strongly impacted by acid deposition. Because of the low pH,
precipitation and throughfall do not exhibit measurable carbonate alkalinity.
Table 7 shows the average wet precipitation loadings of major ions to the watershed
during the period of study compared to the long-term loadings over the previous decade. The
largest difference is in higher loadings of H+, NO3- and SO42- due to the increased volume of
precipitation during the study year. In the period 1982-93, the largest loading of H+ was 1022
mol/ha in 1983 and the smallest was 480 in 1985. The H+ loading of 1243 mol/ha during
the study year was slightly larger than in any previous year.
Table 7. Average wet deposition loadings (moles/ha/yr) Catoctin Mountain, Maryland.
<------------------------Cations------------------------->
H+
Ca2+
Mg2+
Na+
K+
NH4+
(field)
<---------Anions---------->
ClNO3SO42-
Long-term Average*
(1982-1993)
766
std (±)
(180)
56
(25)
21
(18)
72
(44)
20
(11)
170†
(9)
120
(50)
259
(43)
333
(106)
This Study Average
(1993-1994)
1243
55
15
66
19
144
124
384
389
*Rice and Bricker (1996)
†
1992-1993
Trace Elements. The trace element concentration data are presented for wet-only
precipitation (Table 8), bulk deposition on the open tower (Table 9), and bulk throughfall
under coniferous (Table 10) and deciduous (Table 11) canopies.
Table 12 contains the
integrated data for the metalloids. As discussed, due to volume limitations, the metalloids
were assayed as volume-weighted composites integrated over monthly periods rather than as
single events.
Based on these measured concentrations at the single collection sites, atmospheric
fluxes were computed for each deposition type and presented as an annual summary in Figs.
4 (a-e). The average annual trace element wet fluxes (μg/m2/yr) during the study period
were: Al (14,600), As (100), Cd (52), Cr (268), Cu (465), Fe (12,500), Mn (2,340), Ni
(408), Pb (520), Se (253) and Zn (1,870). For all elements except Cd, Ni, and Zn, the
wet fluxes observed at Bear Branch are equal to or greater than those measured at other
regional sites (such as around the Chesapeake Bay farther east) using identical methods
during a comparable time period (Fig. 4f) (Baker et al., 1997).
This trend is perhaps
indicative of a closer "down wind" proximity of the Bear Branch site to mid-western U.S.
sources, in particular, coal-fired power plants. For example, the metalloids As and Se, which
have dominant sources from coal combustion and have been shown to exhibit strong
correlations with acid species in mid-Atlantic (Lewes, Delaware) precipitation (Cutter and
Church, 1986; Scudlark and Church, 1988), are about a factor of two greater at Bear Branch.
On an annual basis, the fluxes generally follow the predicted sequence: throughfall
(deciduous + coniferous) > total bulk > wet-only. This order reflects the capture of dry
deposition in the bulk collectors, and the enhanced scavenging of dry components by the
forest canopy. Notable exceptions to this behavior are Mn and Cr. For Mn, it has been
shown (Lindberg, 1989) that the vegetative canopy provides an active source of Mn due to
foliar translocation of Mn in plant tissues, evapotranspiration or subsequent leaching of dry
deposition. This appears to be especially true for coniferous foliage (Fig. 4d). Thus, it is
likely that the atmospheric flux of Mn is over-estimated using throughfall techniques.
In the
case of Cr, the
Table 8. Trace element concentration (µg/L) in wet only weekly precipitation samples collected on an open tower and
integrated using an automated collector.
Date
930824
930907
930914
930921
930928
931005
931012
931019
931026
931102
931109
<-----in
0.79
3.73
1.30
2.47
1.86
0.37
0.97
0.35
0.56
1.14
0.61
Precip
cm
--------> Al
ml
ug/L
Cd
ug/L
Cr
ug/L
Cu
ug/L
Fe
ug/L
Mn
ug/L
Ni
ug/L
Pb
ug/L
Zn
ug/L
2.01
9.47
3.30
6.27
4.72
0.94
2.46
0.89
1.42
2.90
1.55
1800
6807
2357
4257
3037
628
1818
528
741
1747
1067
0.021
0.032
0.026
0.032
0.060
0.059
0.015
0.039
0.043
0.064
0.010
<0.03
<0.03
0.04
0.06
<0.03
0.08
0.05
0.04
<0.03
0.05
<0.03
0.26
0.30
0.19
0.40
0.17
0.46
0.04
0.07
0.45
0.12
0.12
7.56
11.4
9.36
5.65
2.85
20.4
0.36
2.79
4.34
3.37
1.63
0.6
2.3
0.7
1.2
0.8
3.0
0.1
0.2
72.2
1.0
1.1
<0.1
0.4
0.2
0.2
0.3
0.5
0.3
0.4
0.3
0.2
<0.1
0.31
0.23
0.59
0.45
0.64
1.06
0.12
0.30
0.12
0.71
0.21
1.1
0.7
1.0
1.0
1.4
2.5
0.3
0.5
3.1
1.4
0.7
6.7
7.7
4.4
4.1
2.4
15.1
0.4
2.6
3.5
4.2
3.6
931116
931123
931202
931207
931214
931222
940111
940125
940208
940215
940222
940301
940307
940315
940322
940330
940412
940419
940426
940503
940510
940517
940524
940531
940607
940614
940621
940628
940706
940712
940720
940726
940802
0.21
0.45
5.08
3.15
0.30
0.40
0.52
1.80
1.98
1.79
0.31
2.19
2.03
1.39
0.58
2.81
1.49
1.35
0.45
0.63
1.85
0.69
0.11
1.64
0.14
0.05
0.37
1.35
0.50
0.55
1.35
1.07
0.47
0.53
1.14
12.90
8.00
0.76
1.02
1.32
4.57
5.03
4.55
0.79
5.56
5.16
3.53
1.47
7.14
3.78
3.43
1.14
1.60
4.70
1.75
0.28
4.17
0.36
0.13
0.94
3.43
1.27
1.40
3.43
2.72
1.19
245
1092
7201
6085
840
1421
387
3080
2598
1408
656
2414
1081
2385
1024
4299
2399
2966
982
1095
415
1152
287
2839
316
1081
840
2499
1024
1124
2158
1818
868
6.2
2.9
0.1
1.0
7.9
7.5
7.2
42.0
7.4
3.0
3.6
10.0
1.2
15.0
29.0
16.0
3.2
2.0
9.2
43.0
14.0
9.2
178
6.2
33.1
1.7
35.1
38.3
14.8
11.4
2.5
14.6
5.1
0.030
0.04 0.12
5.44
0.046 <0.03 0.21
4.44
0.031 <0.03 0.05
0.40
0.059 <0.03 0.13
0.63
0.073
0.04 0.35
9.37
0.087
0.04 0.36
11.3
0.252
0.18 0.69
12.6
0.026 <0.03 0.13
15.8
0.062
0.05 0.27
8.52
0.068
0.04 0.17
5.53
0.029 <0.03 0.26
4.48
0.057
0.05 1.25
13.7
0.025 <0.03 0.10
2.02
0.026
0.04 0.29
10.3
0.105
0.12 0.66
30.2
0.024
0.10 0.21
5.41
0.006
0.03 0.61
3.62
0.017
0.10 0.45
5.19
0.019 <0.03 0.13
10.5
0.050
0.07 0.81
36.0
0.016 <0.03 0.44
8.55
0.026
0.08 0.63
11.7
0.221
0.41 2.61
198
0.020 <0.03 0.11
8.95
0.043
0.08 1.41
58.0
0.073
0.05 0.12
4.23
0.128
0.21 1.25
30.2
0.023 <0.03 0.40
19.9
0.084
0.03 0.42
12.2
0.032 <0.03 0.48
9.63
0.020
0.08 0.16
6.71
0.013
0.05 0.50
18.9
0.066 <0.03 0.21
16.1
(Table con’t. on next page)
3.4
2.1
0.1
0.2
2.6
0.7
0.5
0.5
0.6
0.4
0.4
0.9
0.2
0.6
3.1
0.6
0.5
0.5
1.1
26.7
2.4
3.5
33.9
2.4
12.2
0.1
3.0
3.0
2.5
1.6
0.9
1.4
0.2
0.1
0.3
0.4
0.2
0.4
0.6
0.4
0.4
0.6
0.2
<0.1
0.4
0.2
0.1
0.4
<0.1
0.2
<0.1
0.5
0.4
<0.1
0.2
0.6
<0.1
0.3
0.8
0.5
<0.1
<0.1
0.2
0.3
<0.1
0.2
0.24
0.17
0.12
0.31
0.65
0.74
0.30
0.56
0.81
0.61
0.28
0.73
0.27
0.70
1.10
0.08
0.24
0.03
0.07
0.90
0.63
0.38
4.96
0.23
0.79
<0.03
1.30
0.08
0.73
0.43
<0.03
0.07
0.21
0.5
0.5
0.3
0.2
1.7
2.2
3.0
2.4
1.7
1.1
0.8
2.5
0.5
1.3
3.8
0.8
0.5
1.2
0.6
5.7
1.8
3.5
15.0
0.6
4.6
0.7
10.7
1.1
7.0
1.1
0.8
1.7
4.0
Table 8. Trace element concentration (µg/L) in wet only weekly precipitation samples collected on an open tower and
(Con’t.) integrated using an automated collector.
Date
940809
940816
940823
940830
940915
940920
940927
941004
941011
941025
941101
<-----in
Precip
cm
--------> Al
ml
ug/L
Cd
ug/L
Cr
ug/L
Cu
ug/L
Fe
ug/L
Mn
ug/L
Ni
ug/L
Pb
ug/L
0.58
0.93
4.80
0.71
0.01
1.05
1.80
0.62
0.27
0.50
0.50
1.47
2.36
12.19
1.80
0.03
2.67
4.57
1.57
0.69
1.27
1.27
1166
1818
10294
1336
301
2059
3420
1223
571
1010
1109
0.005
0.042
0.006
0.014
0.094
0.047
0.032
0.108
0.032
0.013
0.016
<0.03
0.14
2.08
0.25
0.26
0.15
<0.03
0.05
0.14
0.11
0.02
0.52
0.31
0.24
0.35
2.03
1.52
0.17
0.40
0.33
0.39
0.86
2.83
14.4
24.4
10.9
46.0
20.1
2.70
23.7
11.7
3.95
2.41
0.3
1.4
1.6
1.9
6.9
1.8
0.4
5.2
1.1
0.5
0.7
<0.1
0.4
1.2
0.1
0.2
<0.1
<0.1
<0.1
0.4
<0.1
0.4
<0.03
0.41
0.30
0.63
1.01
0.62
0.16
0.59
0.31
0.34
0.25
3.9
14.3
38.1
15.2
37.1
16.8
6.1
30.8
8.1
2.3
4.1
Zn
ug/L
0.3
3.8
0.7
2.8
9.8
3.2
2.2
2.6
1.6
0.9
1.1
941108
941115
941122
941129
941206
941213
0.90
0.44
2.20
2.42
1.42
0.69
2.29
1.12
5.59
6.15
3.61
1.75
1832
755
3803
2201
2442
1761
1.4
13.6
1.1
2.7
1.8
8.2
0.023
0.099
0.044
0.032
0.035
0.006
0.12
<0.03
0.06
<0.03
0.11
0.08
0.73
0.42
0.30
0.48
0.19
0.30
2.33
11.2
2.76
3.22
2.30
5.88
1.1
2.0
0.3
0.3
0.1
0.5
0.3
0.7
0.2
0.2
<0.1
<0.1
0.28
0.73
0.33
0.46
0.23
0.56
0.6
2.2
0.9
1.0
0.8
1.5
Table 9. Trace element concentrations (µg/L) in bulk deposition collected on an open tower using a continuously open
collector.
Date
930831
930907
930914
930921
931012
931102
931116
931202
931207
931222
940111
940125
940208
940222
940307
940322
940330
940412
940419
940510
940524
940531
940607
940621
940628
940706
940712
940720
940726
940802
940809
940816
940823
940830
940915
940920
940927
941004
941011
941025
941101
941108
941115
941122
941129
941206
941213
<----in
0.83
3.73
1.30
2.47
1.34
2.05
0.82
5.53
3.15
0.70
0.52
0.66
0.30
0.20
0.71
0.71
2.81
1.55
1.35
1.85
0.80
1.64
0.14
0.42
1.47
0.50
0.62
1.40
1.20
0.63
0.45
1.03
5.85
0.78
0.23
1.12
2.10
0.50
0.29
0.54
0.63
1.10
0.41
2.16
1.18
1.38
0.81
Precip
cm
------>
ml
Al
µg/L
Cd
µg/L
Cr
µg/L
Cu
µg/L
Fe
µg/L
Mn
µg/L
Ni
µg/L
Pb
µg/L
Zn
µg/L
2.11
9.47
3.30
6.27
3.40
5.21
2.08
14.05
8.00
1.78
1.32
1.68
0.76
0.51
1.80
1.80
7.14
3.94
3.43
4.70
2.03
4.17
0.36
1.07
3.73
1.27
1.57
3.56
3.05
1.60
1.14
2.62
14.86
1.98
0.59
2.84
5.33
1.27
0.74
1.37
1.60
2.79
1.04
5.49
3.00
3.51
2.06
1744
6196
2906
5032
3034
4196
1900
3732
4139
2608
2112
3119
3530
3799
3587
4097
3998
3303
3601
4125
1871
3416
326
1163
3204
1120
1319
2934
2523
1389
1489
2031
4097
1645
511
2382
3941
1432
766
1148
1347
1234
837
4068
2580
2949
2141
16.7
12.0
9.2
5.0
16.7
8.1
14.0
4.4
2.0
15.9
16.5
7.5
12.6
10.0
11.2
22.1
69.7
49.2
25.8
47.4
84.1
31.4
172
60.4
54.8
47.5
36.4
15.7
75.6
25.9
24.4
22.8
87.8
28.4
182
27.7
7.6
60.5
59.9
19.0
32.6
16.3
43.0
11.1
10.9
8.2
44.6
0.041
0.022
0.011
0.050
0.173
0.049
0.063
0.035
0.041
0.034
0.057
0.039
0.070
0.047
0.045
0.061
0.028
0.052
0.024
0.040
0.061
0.040
0.053
0.080
0.063
0.069
0.019
0.035
0.031
0.034
0.046
0.026
0.027
0.053
0.062
0.049
0.030
0.042
0.024
0.016
0.019
0.059
0.050
0.039
0.031
0.031
0.037
0.09
0.03
<0.03
0.12
0.07
0.05
0.05
0.04
0.03
0.05
0.06
0.09
0.07
0.07
0.10
0.10
0.20
0.24
0.16
0.16
0.18
0.08
0.26
0.16
0.11
0.09
0.09
0.07
0.08
0.12
0.14
0.07
0.12
0.15
0.58
0.10
0.09
0.25
0.17
0.17
0.13
0.13
0.08
<0.03
<0.03
0.16
<0.03
0.25
0.11
0.20
0.26
0.54
0.31
0.29
0.11
0.57
0.44
0.26
0.08
0.26
0.26
0.23
0.31
0.36
0.46
<0.03
0.49
1.79
0.54
1.50
0.97
0.19
0.56
0.42
0.39
0.23
0.53
0.42
0.51
0.55
0.94
3.04
0.41
0.55
0.43
1.26
0.92
0.50
0.64
0.28
0.40
0.25
0.28
0.26
21.6
15.5
12.0
8.12
20.7
11.9
18.8
7.50
3.26
18.9
17.2
7.13
18.2
15.4
20.1
23.3
55.4
49.3
27.5
64.1
102
37.9
184
76.2
35.6
41.6
36.5
24.0
40.4
26.8
25.5
27.8
67.8
35.7
173
37.7
10.6
60.4
70.5
25.7
28.7
23.0
49.3
10.5
11.2
4.35
8.47
2.3
4.3
2.6
1.2
7.6
9.5
2.8
0.8
0.4
1.7
1.1
0.5
1.0
1.0
1.2
2.3
1.8
3.4
1.3
10.1
50.0
22.9
36.1
7.6
3.3
4.8
4.2
1.9
2.0
3.0
1.7
2.8
2.9
3.3
23.4
2.2
4.0
7.4
9.7
3.5
2.8
4.8
4.0
0.7
1.4
0.4
1.0
0.4
<0.1
<0.1
0.3
0.3
0.3
0.3
0.5
0.4
0.3
0.2
0.2
0.4
0.5
0.4
0.4
0.3
<0.1
0.3
<0.1
0.5
0.2
0.6
0.9
0.2
0.3
0.1
0.3
0.3
0.5
0.2
<0.1
0.2
0.1
0.3
0.3
0.7
0.2
0.1
0.2
0.5
0.6
0.3
0.3
0.2
0.3
0.2
0.41
0.19
0.43
0.44
0.41
0.52
0.40
0.30
0.42
0.59
0.51
0.43
0.82
0.68
1.04
0.92
0.65
0.50
0.39
0.61
1.19
0.71
0.99
1.63
0.45
0.87
0.43
0.72
0.47
0.67
0.55
0.14
0.36
0.65
1.34
0.48
0.45
0.60
0.50
0.40
0.40
0.28
0.45
0.44
0.50
0.32
0.55
1.3
0.8
1.6
0.8
2.7
2.8
1.7
1.3
0.9
3.1
2.9
1.4
2.0
2.0
2.7
2.7
1.6
3.1
1.7
4.1
7.1
2.5
8.5
3.2
1.1
2.5
1.1
2.4
2.0
3.6
1.9
1.7
1.9
6.0
26.5
1.0
2.0
2.4
5.5
5.2
3.0
2.2
2.2
1.4
1.3
0.9
1.7
Table 10. Trace element concentrations (µg/L) in bulk throughfall samples collected beneath coniferious canopy.
Date
930831
930907
930914
930921
931012
931102
931116
931202
931207
931221
940111
940125
940208
940222
940307
940322
940330
940412
940419
940510
940524
940531
940607
940621
940628
940706
940712
940720
940726
940802
940809
940816
940823
940830
940915
940920
940927
941004
941011
941025
941101
941108
941115
941122
941129
941206
941213
<-------- Precip
in
cm
0.43
2.50
1.10
1.00
0.89
1.28
0.51
3.70
2.25
0.97
0.52
1.68
1.35
1.63
2.50
1.50
2.98
0.80
0.88
1.60
0.30
1.35
0.06
0.23
0.58
0.40
0.80
0.85
0.94
0.94
0.30
0.33
3.60
0.42
0.13
0.26
1.25
0.29
0.10
0.30
0.50
0.40
0.29
0.41
0.43
0.83
0.54
1.09
6.35
2.79
2.54
2.26
3.25
1.30
9.40
5.72
2.46
1.32
4.27
3.43
4.14
6.35
3.81
7.57
2.03
2.24
4.06
0.76
3.43
0.15
0.58
1.47
1.02
2.03
2.16
2.39
2.39
0.76
0.84
9.14
1.07
0.33
0.66
3.18
0.74
0.25
0.76
1.27
1.02
0.74
1.04
1.09
2.11
1.37
------>
ml
1049
5613
3714
3417
2495
3770
1460
3831
4153
2552
1985
2608
3560
4139
4111
3983
4083
2155
2580
3827
1134
3289
341
922
1942
1163
1942
2297
2864
3572
940
982
4154
1148
567
794
2977
936
454
1063
1460
1176
638
890
2031
2892
1630
Al
µg/L
205
90.4
34.8
31.8
76.2
58.4
271
19.9
6.73
29.6
42.0
44.5
81.2
51.0
30.5
75.1
161
242
108
114
143
65.0
330
290
332
141
152
116
46.1
77.0
173
328
182
478
242
103
147
194
342
189
179
118
113
58.4
41.6
18.9
66.4
Cd
µg/L
Cr
µg/L
Cu
µg/L
0.063
0.056
0.058
0.050
0.160
0.038
0.067
0.015
0.018
0.061
0.049
0.081
0.074
0.030
0.046
0.064
0.048
0.160
0.039
0.034
0.360
0.072
0.270
0.260
0.059
0.120
0.100
0.130
0.083
0.110
0.270
0.430
0.056
0.290
0.450
0.120
0.100
0.460
0.140
0.140
0.140
0.140
0.180
0.085
0.180
0.031
0.110
0.07
0.05
0.05
0.11
0.08
0.08
0.12
0.03
0.04
0.07
0.10
0.11
0.13
0.14
0.11
0.25
0.21
0.25
0.09
0.10
0.22
0.12
0.55
0.43
0.23
0.18
0.15
0.12
0.27
0.07
0.16
0.54
0.96
0.23
0.19
0.48
0.09
0.23
0.15
0.09
0.14
0.23
0.35
0.15
0.14
0.08
0.32
1.29
0.77
0.47
0.66
0.72
1.09
2.39
0.45
0.12
0.44
0.57
0.56
0.80
0.67
0.53
0.56
0.57
1.52
1.20
3.52
8.03
1.81
9.35
5.01
2.03
3.71
1.50
1.94
1.40
0.82
1.91
2.99
0.79
2.01
3.09
2.26
0.87
3.46
2.83
1.94
1.41
2.03
1.45
0.93
0.80
0.29
1.73
Fe
µg/L
57.9
50.9
21.6
18.0
32.3
14.4
65.3
11.7
4.66
21.8
34.2
27.7
37.0
35.5
33.9
57.9
50.7
112
83.1
87.6
130
64.8
327
283
150
126
93.0
70.5
74.9
40.8
87.3
151
98.7
204
156
148
30.0
81.6
173
63.6
56.2
63.1
84.0
37.1
38.5
17.1
54.0
Mn
µg/L
Ni
µg/L
Pb
µg/L
Zn
µg/L
478
266
173
176
456
260
590
97.1
41.2
219
83.0
143
245
133
62.3
279
59.4
421
223
347
301
216
664
557
20.3
649
186
510
115
337
696
618
342
690
734
189
329
28.0
558
176
458
48.2
83.0
168
160
40.8
311
0.6
0.5
0.3
0.4
0.8
0.8
1.0
0.3
0.4
0.5
0.5
0.6
0.9
0.7
0.5
1.0
1.1
0.5
0.7
1.2
2.9
0.4
3.1
1.6
0.5
0.6
0.5
0.7
0.5
0.7
1.0
1.7
0.8
1.2
1.1
1.4
0.6
1.1
1.2
1.8
0.7
0.7
1.0
0.7
0.5
0.1
0.5
1.36
0.97
0.77
0.64
0.80
0.69
3.37
0.34
0.39
0.73
1.30
0.90
1.34
1.30
1.58
1.50
0.76
1.45
1.29
0.68
2.72
1.65
4.84
5.12
1.17
2.58
1.36
1.56
0.90
1.13
1.23
1.43
0.43
1.90
2.39
1.54
0.41
1.06
1.21
0.95
0.52
1.06
1.33
0.42
0.92
0.32
0.62
10.1
5.0
3.8
3.6
10.6
1.1
14.5
3.6
0.9
6.8
4.5
7.0
11.3
7.3
4.7
11.9
1.9
10.3
6.2
13.7
21.3
6.6
15.7
14.5
1.4
7.1
6.4
10.3
9.2
7.0
17.3
72.5
4.5
25.2
32.0
13.6
2.5
5.5
15.3
33.6
13.1
2.4
4.9
6.6
16.0
1.8
9.5
Table 11. Trace element concentrations (µg/L) in bulk throughfall samples collected beneath a deciduous canopy.
Date
930831
930907
930914
930921
931012
931102
931116
931202
931207
931221
940111
940125
940208
940222
940307
940322
940330
940412
940419
940510
940524
940531
940607
940621
940628
940706
940712
940720
940726
940802
940809
940816
940823
940830
940915
940920
940927
941004
941011
941025
941101
941108
941115
941122
941129
941206
941213
<------- Precip
in
cm
0.42
2.70
1.50
1.60
1.41
1.73
0.62
4.32
2.50
1.23
0.52
1.25
1.30
1.88
2.40
1.95
2.20
1.03
1.08
1.65
0.40
1.55
0.14
0.32
1.00
0.30
0.60
0.66
0.94
0.94
0.26
0.40
4.05
0.33
0.30
0.45
1.48
0.34
0.17
0.52
0.28
0.33
0.21
1.66
1.05
1.18
0.73
1.07
6.86
3.81
4.06
3.58
4.39
1.57
10.97
6.35
3.12
1.32
3.18
3.30
4.78
6.10
4.95
5.59
2.62
2.74
4.19
1.02
3.94
0.36
0.81
2.54
0.76
1.52
1.66
2.39
2.39
0.66
1.02
10.29
0.84
0.76
1.14
3.75
0.86
0.43
1.32
0.71
0.84
0.53
4.22
2.67
2.98
1.85
--------> Al
ml
µg/L
Cd
µg/L
Cr
µg/L
Cu
µg/L
Fe
µg/L
Mn
µg/L
Ni
µg/L
Pb
µg/L
Zn
µg/L
1318
5501
3728
3912
2269
4111
1616
3845
4040
2353
3062
2580
2084
4083
4040
4026
4125
1432
2821
4068
1134
3303
383
1120
2027
1276
2056
2509
3020
3359
1007
997
4182
1347
539
851
3501
964
440
993
1560
1234
851
3998
2566
2949
1828
0.045
0.026
0.013
0.031
0.037
0.062
0.039
0.020
0.014
0.021
0.060
0.044
0.051
0.019
0.022
0.048
0.026
0.064
0.037
0.066
0.060
0.037
0.039
0.025
0.047
0.063
0.047
0.036
0.025
0.036
0.294
0.067
0.037
0.037
0.282
0.049
0.043
0.024
0.048
0.035
0.033
0.045
0.038
0.043
0.031
0.026
0.037
0.13
0.06
0.08
<0.03
0.05
0.07
0.04
<0.03
0.03
0.05
0.13
0.05
0.15
0.04
0.04
0.12
0.13
0.15
0.22
0.20
0.28
0.10
0.38
0.26
0.04
0.09
0.16
0.21
0.13
0.20
0.08
0.26
1.53
0.18
0.62
0.26
0.16
0.21
0.23
0.14
0.13
0.18
0.26
0.24
0.08
<0.03
0.04
2.30
0.56
0.56
0.27
1.05
1.98
1.18
1.74
0.46
0.70
0.60
0.31
1.06
0.49
0.55
0.80
0.34
1.46
2.32
6.80
4.01
7.43
40.5
6.22
2.59
3.73
2.13
1.22
0.79
1.02
1.35
2.01
0.72
2.13
3.45
2.67
0.52
0.94
2.19
4.16
2.34
1.34
2.06
1.33
0.54
0.69
0.69
59.0
28.7
20.0
10.5
32.4
14.3
16.2
13.2
4.67
19.9
22.5
13.3
34.2
17.6
20.7
40.0
40.8
86.3
61.3
108
253
58.9
232
120
87.4
56.0
69.3
39.7
61.8
38.8
45.7
114
70.6
64.5
274
115
17.6
38.1
172
63.0
36.1
25.2
37.3
23.2
9.53
9.54
15.7
49.6
15.5
42.9
32.0
49.6
224
105
39.2
11.2
33.2
7.6
17.9
49.2
20.1
24.7
37.5
12.4
42.5
39.2
219
205
70.2
14.4
8.5
53.5
65.4
75.8
40.2
22.0
30.0
33.3
55.7
19.6
98.0
293
57.7
19.0
24.7
61.6
373
361
114
105
36.8
18.8
7.5
20.9
0.3
0.3
0.4
0.4
0.6
1.2
0.6
0.6
0.3
0.4
0.7
0.3
0.8
0.3
0.6
0.6
0.2
0.8
0.4
0.6
0.8
0.8
4.1
2.0
1.3
0.5
0.5
0.5
0.9
0.4
0.2
0.2
1.6
0.6
1.0
1.3
0.4
0.5
0.6
1.9
2.1
0.8
1.3
0.7
0.6
0.3
0.2
1.25
0.20
0.46
0.23
0.68
0.78
0.46
0.87
0.72
0.72
0.61
0.74
1.85
0.94
1.01
1.57
0.31
1.15
0.62
1.47
1.53
0.85
2.08
1.54
0.85
0.92
1.26
0.90
0.55
0.96
0.67
0.70
0.27
0.76
1.77
0.73
0.36
0.41
1.16
0.90
0.58
0.47
0.67
0.70
0.66
0.48
0.45
9.3
1.4
2.3
0.9
7.3
9.3
4.2
3.7
1.5
4.0
2.3
2.2
6.7
2.4
4.3
7.1
1.8
5.9
2.2
6.9
8.2
6.6
9.2
18.8
7.0
5.9
14.3
5.6
2.5
4.2
5.1
9.0
2.1
9.1
54.5
10.5
1.0
3.0
12.9
21.9
7.1
4.6
6.7
3.1
2.0
2.0
2.9
113
36.9
33.2
20.4
64.3
154
55.5
29.1
11.1
31.8
22.8
36.9
44.7
20.8
18.3
43.4
54.3
88.3
62.6
116
421
72.2
439
266
89.6
78.8
80.4
93.6
62.3
45.2
62.7
173
84.7
93.5
444
198
25.4
45.2
225
198
345
97.6
62.2
29.1
14.4
10.8
22.3
Table 12. Metalloid concentrations (µg/L) (As, Se) in integrated precipitation event samples.
As
Date Type µg/L
Se
As
Se
As
µg/L Type µg/L µg/L Type µg/L
930824
930831
930907
930914
930921
930928
931005
931012
931019
931026
931102
931109
931116
931123
931202
931207
931214
931222
931229
PT 0.070 0.304
N/S
N/S
*no rain for week BT 0.096 0.447
PT 0.032 0.166 BT 0.043 0.160
PT 0.068 0.309 BT 0.056 0.189
PT 0.126 0.165 BT 0.048 0.241
PT 0.079 0.244
N/S
N/S
PT 0.169 ISA
N/S
N/S
PT 0.033 0.176 BT 0.059 0.116
PT 0.060 0.064
N/S
N/S
PT 0.117 0.062
N/S
N/S
PT 0.146 0.228 BT 0.146 0.206
PT 0.060 0.140
N/S
N/S
PT ISA ISA
BT 0.089 0.117
PT 0.044 0.235
N/S
N/S
PT 0.018 0.093 BT 0.029 0.164
PT 0.030 0.177 BT 0.091 0.284
PT 0.224 0.217
N/S
N/S
PT 0.154 0.303 BT 0.196 0.208
N/S
N/S
N/S
N/S
1994
*Samples composited Monthly
Jan
Feb
March
April
May
June
July
Aug
Sept
Oct
Nov
Dec
PT
PT
PT
PT
PT
PT
PT
PT
PT
PT
PT
PT
0.173
0.121
0.056
0.025
0.077
0.050
0.092
0.051
0.107
0.116
0.049
0.030
0.336
0.097
0.162
0.109
0.248
0.202
0.235
0.210
0.247
0.276
0.115
0.106
BT
BT
BT
BT
BT
BT
BT
BT
BT
BT
BT
BT
0.145
0.127
0.154
0.111
0.174
0.144
0.106
0.066
0.072
0.131
0.081
0.042
0.198
0.240
0.291
0.160
0.237
0.268
0.310
0.175
0.174
0.107
0.470
0.178
Se
As
µg/L Type µg/L
Se
As
µg/L Type µg/L
Se
µg/L
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
N/S
0.101
0.050
0.061
0.045
N/S
N/S
0.050
N/S
N/S
0.173
N/S
0.129
N/S
0.032
0.075
N/S
0.12
N/S
N/S
0.203
0.090
0.242
0.210
N/S
N/S
0.143
N/S
N/S
0.256
N/S
0.215
N/S
0.208
0.282
N/S
0.327
N/S
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
N/S
0.142
0.043
0.056
0.048
N/S
N/S
0.059
N/S
N/S
0.146
N/S
0.071
N/S
0.096
0.091
N/S
0.269
N/S
N/S
0.044
0.094
0.260
ISA
N/S
N/S
0.054
N/S
N/S
0.065
N/S
0.098
N/S
0.420
0.356
N/S
0.418
N/S
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
N/S
N/S
0.012
N/S
0.024
N/S
0.017
N/S
0.011
N/S
0.013
N/S
N/S
N/S
N/S
N/S
0.010
N/S
0.010
N/S
N/ S
0.130
N/S
0.085
N/S
0.064
N/S
0.092
N/S
0.044
N/S
N/S
N/S
N/S
N/S
0.134
N/S
0.119
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
BC
ISA
0.136
0.157
0.146
0.112
0.160
0.125
ISA
0.106
0.131
0.101
0.044
ISA
BD
0.246 BD
0.288 BD
0.235 BD
0.202 BD
0.147 BD
0.210 BD
ISA
BD
0.214 BD
0.129 BD
0.147 BD
0.094 BD
0.189
0.069
0.157
0.122
0.124
0.173
0.106
0.092
0.129
0.127
0.098
0.067
0.382
0.184
0.266
0.270
0.150
0.404
0.317
0.237
0.213
0.263
0.027
0.178
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
0.010
0.012
0.010
0.008
0.010
0.010
0.012
0.015
0.015
0.011
0.008
0.009
0.027
0.035
0.053
0.048
0.024
0.020
0.033
0.022
0.051
0.038
0.036
0.038
Type
PT = Wet only precipitation, at tower
BT = Total (wet+dry) deposition, at tower
BC = Total (wet+dry) deposition, coniferous
BD = Total (wet=dry) deposition, deciduous
SG = Weekly stream grab
N/S = No sample collected
ISA= Insufficient volume for analysis
observed bulk (wet + dry) and throughfall fluxes are slightly less than wet only.
This
suggests than net preferential release by the canopy through foliar exudation, the efficient
capture of the dry component using bulk techniques, and/or a negative artifact in the wet-only
collector. In fact, an examination of the seasonal Cr flux data (Fig. 4b) supports the latter
explanation. However, although such circumstantial evidence suggests contamination of Cr,
there was no compelling basis to omit the questionable values.
Although the primary focus of this study is on net flux to the forest floor, our sampling
strategy was designed to provide some insights into the mechanisms of depositional
processes. If it is assumed the total bulk data are representative of the total (wet + dry) flux,
then the difference between the total bulk and measured wet-only flux is representative of the
relative dry deposition flux. Based on the annual average fluxes, the wet-only and total bulk
fluxes can be thus compared. However, given the uncertainty in the capture of dry fallout by
bulk collectors, this comparison should be viewed only in a semi-quantitative sense.
For elements which have major crustal sources (Al, Fe, Mn, and Cr), the wet flux
appears to comprise about half of the total bulk atmospheric deposition. In contrast, for
elements which originate primarily from anthropogenic activities, the relative wet deposition
rates are larger, ranging from about 60% (Zn) to 85% (Cd and Cu) of the total atmospheric
input.
It has been suggested (Church and Scudlark, 1992) that this trend reflects the
propensity of crustal elements to be enriched on large particles, which readily dry deposit due
to gravitational settling. Conversely, high-temperature combustion condensates, characteristic
of most anthropogenic emissions, typically exhibit enrichment on sub-micron aerosols, which
have longer atmospheric residence times and are more efficiently removed by wet-scavenging
mechanisms. This behavior may be exacerbated by the reported tendency of bulk collectors
to over-estimate the flux of large soil particles (due to resuspension) while underestimating the
flux of small particles (due to aerodynamic effects) (Hicks, 1986).
Overall, the general trend observed at Bear Branch is consistent with observations
based on a similar experimental approach at the Walker Branch watershed (Lindberg and
Turner, 1988), although the wet fluxes at Bear Branch represent a larger proportion of the
overall atmospheric flux. The dry deposition rates at Bear Branch are, however, in accord
with estimates reported for Lewes, Delaware (Church and Scudlark, 1992), which were
calculated from measured aerosol concentrations and assumed dry deposition velocities.
On an annual basis, the ratio of throughfall flux to that of incident precipitation varies
from 2-5 for non-crustally derived elements; for the crustal elements Al and Fe, throughfall
fluxes reflect a even greater enhancement (6-8X). The significant enrichment of throughfall
fluxes over total/bulk (wet + dry) fluxes is indicative of the enhanced capture efficiency
provided by vegetative surfaces (Bondietti et al., 1984; Lindberg and Lovett, 1985). The
relative enhancement of throughfall fluxes we observed at Bear Branch are consistent with
those previously reported for a deciduous forest in the southeastern U.S. (Lindberg, 1989).
Overall, the observed metal fluxes are somewhat (<2X) greater during spring and
summer. This behavior parallels and is on par with trends which have been noted for acid
species in the eastern U.S. (Lindberg et al., 1982; Scudlark and Church, 1997). However, in
contrast to the acid components, whose seasonal abundance primarily reflects their
photochemical production, factors which influence this behavior for metals are primarily
meteorological, for example: (a) greater transport from the mid-western source region during
summer; (b) more effective horizontal and vertical atmospheric scavenging associated with
summer convective storm systems and stagnating air masses; c) slightly greater emissions
during the summer (e.g., because of increased output from coal-fired power plants, peak
summer utility use, increased automobile traffic, etc.). Notable exceptions are As and Se,
which display rather uniform seasonal deposition trends which is unusual as these are some of
the primary elements associated with coal burning. For these elements, the close proximity of
the sampling site to dominant mid-western U.S. emission sources may obscure other seasonal
effects.
Seasonally, compared with incident precipitation, the throughfall fluxes display the
greatest enrichment during spring and summer.
Furthermore, if we compare the annual
throughfall fluxes under the two canopy types, the coniferous flux is equal to or greater than
the deciduous flux for all elements except Cu, Cr, and Ni. The logical explanation for these
observations is that there is less vegetative scavenging under the leafless deciduous canopy
during the dormant period (roughly mid-October through mid-April). Interestingly, the seasonal
patterns for deciduous vs. coniferous flux do not support this theory; in fact, differences
between vegetation types are less pronounced during fall and winter. Alternatively, a plausible
explanation is that the degree of canopy uptake on deciduous foliage is greater than
coniferous. Thus, naturally, the greatest differences observed between canopy types would be
during the growing season. Other seasonally variable factors which would influence throughfall
fluxes include the duration of the antecedent dry period as well as the precipitation amount,
intensity, type and duration.
To gauge the total (wet + dry), net trace element deposition to the forest floor, the
throughfall fluxes were weighted 90:10 (deciduous:coniferous), to reflect the average areal
forest composition in the Bear Branch watershed. Although throughfall measurements are
often combined with stemflow techniques to derive total flux to the forest floor, previous
studies have shown that the stemflow contribution is typically less than 10% of the total
vegetative flux to the forest floor (Draaijers et al., 1996).
Thus, our assessment of
atmospheric loading may be slightly underestimated. However, given the magnitude of the
uncertainties inherent with throughfall measurement considering only single collection sites, this
error would not be significant.
An overview of the technical requirements of throughfall, stemflow and precipitation
measurements used for monitoring the atmospheric deposition of forests has been made
(Draaijers et al., 1996). From this, an assessment of the uncertainties involved in such
measurements based on major ions can be inferred. For homogeneous forest stands with a
closed canopy, the overall uncertainty in annual mean soil loads for base cations can be as
low as 10-15%. This assumes state-of-the-art measurement and analytical techniques are
used in combination with a sufficiently large number of replicate samplers (e.g., 20). The
former conditions apply here, but the singularity of collectors necessitated by resources of this
pilot project, mean that the actual uncertainties based on the study cited are probably not
better than 35-50%, or about triple the measurement and analytical uncertainty. Subsequent
studies are necessary to ascertain those components that may make up the majority of this
uncertainty. They include factors such as canopy exchange and dry deposition to the forest
floor and understory vegetation usually not addressed in throughfall studies.
B.
Stream Export
The export of dissolved chemical constituents in streamwater will reflect contributions
from atmospheric deposition and watershed processes such as chemical weathering, ion
exchange, sorption, and biotic uptake and release. The remaining flux, after subtracting the
atmospheric contribution from the total stream load, is the amount contributed by processes
active within the watershed. These data can be used to decipher the watershed processes
important in determining the chemical composition of the streamwater and are necessary to
distinguish the materials introduced through atmospheric pathways from those produced within
the watershed.
The 16 months of sampling at Bear Branch yielded 38 stream grabs and 29 stream
intensive samples (for both dissolved and particulate phases). The hydrological drainage
basin of Bear Branch is small, with shallow flow paths, as determined by stable isotopic
measurements (Rice and Bricker, 1996). As a result, the runoff is flashy, and streamflow
dissipates significantly during the summer (Fig. 5). Bear Branch was sampled in 1992 for
radon (222Rn), tritium (3H), and chlorofluorocarbons (CFCs) to determine approximate
residence time of the water contributing base flow to the stream. Although all three agedating techniques have error, the three techniques indicated that Bear Branch water is very
young, recharged perhaps within the previous six months to one year. The mean annual flow
for the period was 8771 L/s for 1993 and 6912 L/s for 1994. The mean annual flow during
the period of study was somewhat higher than both 1992 (7380 L/s) and 1991 (4632 L/s).
Major Ions. The dissolved major ion concentrations in the individual stream grabs are
presented in Table 13. Annual export of the dissolved constituents was calculated on the
basis of the period-weighted method of summing discharge (Rice and Bricker, 1996). For
example, when samples were collected weekly, the mean daily discharges for the three days
prior to the sample date, the three days after the sample date, and the discharge on the
sample date were summed to give a total discharge that was then multiplied by the
concentrations of each constituent on the sample date. The products of the discharges and
concentrations were then summed and multiplied by a conversion factor to determine the
annual export of each constituent.
The annual export of major chemical constituents
calculated as the product of concentration in the stream grabs times the daily average
discharge during the sample interval. This is summarized in Table 14 and compared to the
previous two years. The export loadings between the two periods are quite comparable, in
spite of the increased precipitation. Somewhat higher loadings during the previous two years
may be related to annual differences in canopy composition and snowfall that could increase
scavenging of both acid and road salt constituents.
The major ion chemical export from the streamwater data have been published and
discussed elsewhere (Rice et al., 1995 and Rice and Bricker, 1996). Thus, in the context of
this report, the data are utilized primarily as critical constituents in the NETPATH weathering
model for the other trace elements.
Table 13. Major ion dissolved concentrations (µeq/L) in routine stream grabs.
DATE TIME
SIO2
COND
Q
pH
pH
H+
us/cm cfs lab field
08/24/93
08/31/93
09/07/93
09/14/93
09/15/93
09/21/93
09/28/93
10/05/93
10/12/93
10/19/93
10/26/93
1330
1130
1030
1040
1317
1140
1107
957
1050
1000
1340
16
17
17
16
17
16
18
16
20
15
15
0.06
0.05
0.07
0.08
0.08
0.08
0.08
0.08
0.10
0.08
0.08
5.34
n.a.
5.41
n.a.
n.a.
5.44
n.a.
5.36
n.a.
5.41
n.a.
5.12
5.43
5.30
4.75
4.53
3.87
4.47
4.72
4.84
4.55
4.82
7.59
3.72
5.01
17.8
29.5
135
33.9
19.1
14.5
28.2
15.1
Ca2+
Mg2+
Na+
K+
CL-
NO3-
SO42-
HCO3-
µeq/L µeq/L µeq/L µeq/L µeq/L µeq/L µeq/L
µeq/L
µm/L
24.0
n.a.
27.0
n.a.
n.a.
26.0
n.a.
25.5
n.a.
23.0
n.a
1 .0
n.a.
4.4
n.a.
n.a.
6.8
n.a.
6. 7
n.a.
5.4
n.a.
110
n.a.
110
n.a.
n.a.
100
n.a.
100
n.a.
100
n.a.
30.4
n.a.
30.9
n.a.
n.a.
30.5
n.a.
32.9
n.a.
30.2
n.a.
30.1 8.95
n.a.
n.a.
29.8 10.3
n.a.
n.a.
n.a.
n.a
30.2 10.7
n.a.
n.a.
31.1
9.2
n.a.
n.a.
31.2
8.4
n.a.
n.a.
32.9
n.a.
31.5
n.a.
n.a.
31.7
n.a.
31.8
n.a.
31.7
n.a.
5.7
n.a.
1.7
n.a.
n.a.
3.5
n.a.
6.1
n.a.
2.0
n.a.
62.8
n.a.
66.1
n.a.
n.a.
65.7
n.a.
65.3
n.a.
63.6
n.a.
11/02/93
11/09/93
11/16/93
11/23/93
11/30/93
12/07/93
12/14/93
12/21/93
12/29/93
01/11/94
01/25/94
02/08/94
02/22/94
03/07/94
03/22/94
04/05/94
04/19/94
05/03/94
05/17/94
05/31/94
06/14/94
06/28/94
07/12/94
07/26/94
08/09/94
08/23/94
09/07/94
09/20/94
10/04/94
10/18/94
11/01/94
11/15/94
11/29/94
12/13/94
1730
1322
1200
1147
1300
1302
1155
1426
1415
1430
1510
1410
1335
1020
1050
1050
1110
1230
1045
1300
1100
950
1330
1245
1300
1500
945
1000
1100
1100
1330
1415
930
1445
16
17
17
17
29
30
27
25
25
24
24
25
33
27
28
24
24
22
22
21
19
19
17
18
17
18
17
17
16
16
23
16
21
25
0.10
0.10
0.08
0.10
1.60
2.10
0.89
0.65
0.55
0.35
0.31
0.60
3.00
1.10
1.80
1.80
1.50
0.50
0.60
0.29
0.24
0.20
0.12
0.12
0.10
0.14
0.11
0.10
0.11
0.10
0.35
0.11
0.29
0.89
n.a. = not analyzed
5.38
n.a.
5.75
n.a.
5.08
n.a.
5.14
n.a.
5.18
5.35
5.50
5.43
5.22
5.39
5.27
5.34
5.35
5.52
5.30
5.41
5.43
5.23
5.25
5.32
5.33
5.31
5.52
5.35
5.25
5.43
5.88
5.99
5.83
5.66
5.13
5.05
5.45
5.75
5.07
4.98
4.49
4.64
5.34
5.34
5.28
5.71
5.16
5.38
5.34
5.64
5.54
5.97
5.35
5.53
5.54
5.26
5.20
5.17
5.29
5.31
5.32
5.26
5.32
5.51
5.80
5.63
5.88
5.61
7.41
8.91
3.55
1.78
8.51
10.5
32.4
22.9
4.57
4.57
5.25
1.95
6.92
4.17
4.57
2.29
2.88
1.07
4.47
2.95
2.88
5.50
6.31
6.76
5.13
4.90
4.79
5.50
4.79
3.09
1.58
2.34
1.32
2.45
25.4
n.a.
25.0
n.a.
60.9
n.a.
52.4
n.a.
44.9
41.9
43.4
47.4
62.9
48.9
52.9
46.4
44.4
44.1
43.0
40.1
35.7
34.3
30.0
29.8
40.7
32.6
26.1
26.9
25.7
29.9
38.4
22.0
37.4
50.0
36.2
n.a.
35.3
n.a.
67.3
n.a.
63.1
n.a.
58.2
55.6
54.3
62.9
76.5
63.1
67.3
57.7
57.1
55.0
55.8
50.3
46.3
43.0
37.1
36.0
45.7
41.6
35.4
33.7
34.2
33.7
44.7
33.7
46.2
61.7
nd = not detected
30.1
n.a.
30.5
n.a.
28.1
n.a.
27.5
n.a.
29.5
31.2
33.5
29.1
29.7
28.5
26.6
26.5
28.1
27.0
28.2
27.8
30.3
29.1
30.5
29.9
30.1
31.4
31.8
29.6
30.1
27.3
28.5
30.5
30.1
26.4
17.7
n.a.
18.7
n.a.
25.8
n.a.
23.5
n.a.
22.3
22.8
24.3
24.0
28.1
25.3
26.4
24.8
26.4
20.9
19.5
17.3
14.2
12.9
9.5
11.9
10.5
12.2
8.7
10.3
9.0
29.2
49.9
18.9
27.6
21.0
35.5
n.a.
32.8
n.a.
33.1
n.a.
35.6
n.a.
32.9
33.7
31.2
33.8
31.6
32.5
30.6
30.4
32.6
32.0
34.5
32.1
32.4
28.7
34.2
33.0
33.7
26.1
32.2
31.7
31.2
41.0
34.0
38.4
36.4
29.4
0.6
n.a.
n.a.
n.a.
23.0
n.a.
19.0
n.a.
18.0
17.0
18.0
19.0
30.0
18.0
19.0
14.0
15.0
10.0
12.0
4.9
4.8
8.0
6.5
3.6
9.3
5.6
5.0
5.0
5.5
5.6
2.9
nd
nd
12.0
78.0
n.a.
0.3
n.a.
132
n.a.
128
n.a.
111
104
96.0
130
143
120
132
118
121
107
110
98.9
88.6
75.2
74.2
72.8
73.2
66.1
66.3
66.7
64.5
77.6
77.5
77.6
102
112
7.3
n.a.
14
n.a.
nd
n.a.
nd
n.a.
nd
nd
3.1
nd
nd
nd
nd
nd
1.8
6.0
5.0
7.6
10
6.0
nd
4.0
6.1
20.0
nd
nd
nd
8.7
27.0
nd
nd
nd
99
n.a.
99
n.a.
83
n.a.
81
n.a.
83
83
76
79
73
75
73
71
72
73
78
79
86
90
100
98
98
100
110
97
96
95
76
93
86
78
Table 14. Annual export of major chemical constituents at Bear Branch, Catoctin Mountain, Maryland. Constituents
in moles/ha/yr.
<-------------------------Cations------------------------->
H+
SIO2
Ca2+
Mg2+
Na+
K+
(field)
Long-term Average*
(1982-1993)
37.6
std (±)
420
(137)
166
(49)
196
(62)
183
(47)
151
(47)
This Study Average 34.0
444
212
265
160
137
<--------------Anions-------------->
HCO3ClNO3SO42-
9
221
(52)
184
(22)
346
(134)
183
94
515
*Rice and Bricker, 1996
Dissolved Trace Elements. Grab samples of Bear Branch streamwater were made on
a bi-weekly basis for the first part of the program (through 1993), and on a weekly basis
thereafter (through 1994). The dissolved concentrations (μg/L) are presented in Table 15,
and plotted as instantaneous dissolved concentration in Figs. 6 (a-d), along with precipitation
amount and stream discharge. The annual export of trace element constituents was calculated
as the product of concentration in the stream grabs times the daily average discharge during
the sample interval.
An additional error is associated with the interpolation of weekly collection of the stream
to seasonal and yearly loads. Loads are calculated as the product of the flow of a stream
and the concentration of the chemical constituent in question, after a conversion factor is used
to accommodate units.
The method used here to calculate the loads (the Integration
Interpolation method), is discussed thoroughly in Godfrey et al., 1995. Briefly, this method
uses the daily mean flow collected at the stream gauging station and a daily concentration
interpolated from the weekly grab sample.
Monthly, seasonal and annual loads were
calculated using this method which assumes a uniform rise and fall of stream chemistry, and
would dampen out any short-term changes in the concentrations. This would happen during
stormflow periods when we were not sampling intensively and metal concentrations have been
shown to increase. By not sampling during all storm periods, our load calculation method
underestimates the amount of metals.
Previous studies by Lindberg and associates (e.g., Lindberg and Turner, 1988) have
identified four primary factors which influence trace metal export from a watershed: stream pH,
the organic carbon content of the soils, the bedrock geology and the hydrological
characteristics of the site. This is in accord with the following discussion.
Both the crustal (Al, Fe, and Mn) and more anthropogenic (Cu, Ni, Zn) elements show
the greatest daily loading during the spring freshet when the stream pH is lower.
This
presumably reflects the dissolution of freshly weathered material evolved during the winter
freeze/thaw cycles
Table 15. Trace element dissolved concentrations (µg/L) in routine stream grabs.
DATE
type
pH
H+
Al
µg/L
Cd
µg/L
Cr
µg/L
Cu
µg/L
930907
930921
931005
931019
931102
931214
931229
940111
940125
940208
940307
940322
940405
940419
940503
940517
940531
940607
940614
940621
940628
940706
940712
940720
940726
940802
940809
940816
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
5.30
3.87
4.72
4.55
5.13
4.49
5.34
5.34
5.28
5.71
5.38
5.34
5.64
5.54
5.97
5.35
5.53
6.00
5.54
5.58
5.26
5.18
5.20
5.22
5.17
5.31
5.29
5.29
5.01
135
19.1
28.2
7.41
32.4
4.57
4.57
5.25
1.95
4.17
4.57
2.29
2.88
1.07
4.47
2.95
1.00
2.88
2.63
5.50
6.61
6.31
6.03
6.76
4.90
5.13
5.13
37.7
79.4
81.2
60.4
56.7
53.3
44.5
33.9
28.9
51.5
45.2
67.1
41.8
29.0
44.9
61.1
20.9
17.2
17.5
17.7
48.8
27.3
48.2
41.4
58.2
69.2
36.8
69.2
0.055
0.220
0.056
0.062
0.089
0.615
0.499
0.592
0.085
0.093
0.125
0.184
0.117
0.060
0.124
0.086
0.060
0.027
0.049
0.050
0.156
0.065
0.107
0.134
0.044
0.148
0.062
0.131
0.04 0.08
0.05 0.27
<0.03 0.10
0.04 0.07
0.07 0.23
0.05 1.62
<0.03 2.96
0.06 0.90
<0.03 0.50
<0.03 0.34
<0.03 0.21
<0.03 0.25
0.15 0.39
0.09 0.24
<0.03 1.62
0.04 1.39
<0.03 0.30
0.09 <0.03
0.14 0.23
<0.03 1.37
<0.03 0.93
<0.03 0.51
0.03 0.68
0.08 1.93
0.10 2.30
0.19 0.85
0.06 0.36
0.61 0.22
Fe
µg/L
Mn
µg/L
Ni
µg/L
Pb
µg/L
Zn
µg/L
12.68
25.55
18.96
12.59
10.22
1.40
1.82
1.30
2.53
3.20
1.45
1.00
0.82
1.05
2.78
4.73
1.79
1.13
0.53
1.07
4.21
4.92
5.70
6.55
8.82
17.13
4.50
14.32
15.0
32.7
22.7
21.1
17.0
27.0
14.0
9.9
4.8
9.7
9.6
19.5
11.4
9.2
12.1
9.8
7.0
4.5
5.9
9.9
22.8
29.3
32.0
39.9
43.6
40.5
17.1
37.6
0.6
1.2
0.8
0.9
0.6
1.1
1.2
0.7
0.5
0.7
0.7
1.0
0.6
1.0
0.7
0.7
0.8
0.4
0.3
0.8
1.0
1.0
1.3
0.9
1.5
0.9
0.7
1.3
0.09
0.11
0.04
<0.03
<0.03
<0.03
<0.03
<0.03
<0.03
0.37
<0.03
<0.03
<0.03
0.04
0.14
0.04
0.07
0.11
<0.03
0.08
0.11
0.03
0.09
<0.03
0.05
0.26
0.14
<0.03
0.8
3.6
3.0
3.4
2.0
4.1
3.5
2.6
1.8
3.4
2.4
5.2
2.6
2.2
3.3
13.3
1.8
1.0
11
1.9
9.7
1.9
2.9
5.0
5.4
11.1
1.6
3.7
940823
940830
940907
940915
940920
940927
941004
941011
941018
941025
941101
941108
941115
941122
941129
941206
941213
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
5.31
5.29
5.32
5.25
5.26
NA
5.32
5.96
5.51
5.54
5.80
5.83
5.63
5.98
5.88
NA
NA
4.90
5.13
4.79
5.62
5.50
4.79
1.10
3.09
2.88
1.58
1.48
2.34
1.05
1.32
-
51.8
47.6
49.2
71.7
49.0
65.7
69.6
68.1
32.4
45.1
47.1
53.5
37.4
49.9
36.7
43.0
62.3
0.091
0.065
0.075
0.106
0.089
0.100
0.131
0.110
0.044
0.060
0.055
0.035
0.015
0.017
0.017
0.026
0.062
C
0.21
0.11 0.22
0.05 0.42
0.06 0.27
0.16 0.33
0.12 0.35
0.06 0.16
0.11 <0.03
0.04 0.04
0.07 0.25
0.06 0.25
<0.03 <0.03
0.08 0.29
0.07 0.13
0.27 0.11
0.08 0.04
<0.03 0.17
37.61
8.81
8.11
9.37
6.14
8.42
6.67
8.16
5.71
6.42
4.29
7.71
7.71
6.68
3.87
2.44
1.99
24.4
22.4
25.9
32.5
19.8
29.2
18.3
21.2
10.3
15.6
13.4
15.7
8.4
7.7
5.8
6.1
10.1
6.2
0.7
0.6
0.8
0.8
0.7
0.8
0.8
0.3
0.6
0.4
0.5
0.4
0.6
0.3
0.4
0.6
0.04
<0.03
<0.03
0.17
0.13
0.10
0.09
<0.03
<0.03
<0.03
0.16
0.19
0.14
0.14
<0.03
<0.03
<0.03
3.0
2.5
3.4
9.4
1.9
2.0
13.3
13.1
3.9
1.5
0.8
1.4
0.7
0.9
1.4
1.7
3.5
C = contaminated
for the crustal elements, and the accumulation of both acidic and trace element charged
loadings in the snow pack for the more non-crustal (anthropogenic) elements. However, all
also show export in early or late Fall of 1993. This is assumed due to diagenetic effects in
the watershed, such as dissolution/stabilization by humic chelation, or in the case of Fe and
Mn potential reduction to more soluble/complexed forms. In the case of Mn which is known
to be exuded from tree leaves (Lindberg and Turner, 1988), a similar effect may be occurring
during canopy washoff.
It has also been proposed (Lindberg and Turner, 1988) that
conditions during summer (increased water temperature and microbial activity coupled with
decreased streamflow) favor the formation of stagnant pools in the streambed, which in turn
would result in the increased solubility of Mn under more reducing conditions. Here, litterfall
from the previous fall may be trapped, solubilized during organic oxidation, and remobilized to
the streambed.
The crustal elements (Al and Mn) show distinct seasonal export, increasing almost as
much as an order magnitude into the spring and decreasing during the later spring and
summer. This may reflect seasonal solubility effects in the stream related to melt off,
discharge, and acidity. It is also possible that in addition to solubility, the spring is when
organic ligands from growing vegetation in the watershed are being released to the stream.
Under the increased sunlight, photoreduction may render Mn and possibly Cr into more soluble
and stabilized, reduced forms as has been reported for Fe (McKnight and Bencala, 1990).
Other non-crustal bioactive elements such as Cr, Ni, Se, and Zn show a similar seasonal
pattern. Zinc, which shows this effect the most, is an element which is readily stabilized by
strong organic ligands (Stumm and Morgan, 1981).
Other anthropogenically mobilized elements (As, Cd, Cr, Pb, and Se) show export
which is quite uniform over the year, with some slight suggestion of maximum periods during
the early spring freshet. This suggests that the watershed is well buffered in its retention and
equilibrium poise of such elements, and that secondary effects associated with deciduous
canopy cycles of leaf growth and drop do not have a large effect.
On the other hand, a more general explanation may be in order. The loadings will be
higher during the wetter periods of the year simply because of the greater transport of
dissolved constituents by the larger volume of water.
This occurs even though the
concentrations of some of the constituents may be lower at this time. The increased volume
over compensates for the decreased concentration. An additional factor is the lower pH in the
spring and during the high flow of storm events. The decrease in pH tends to mobilize many
of the trace elements. The dissolved organic concentrations are also generally higher during
the spring and in high-flow events which could augment the transport of trace elements by
organic complexing. Probably all of these factors play a role.
Regional Stream Comparisons. Concentrations of dissolved trace elements in Bear
Branch are compared with others in the same watershed, including the Potomac at its fall line
near Washington, D.C., the Anacostia River in urban D.C. sampled in 1995 and 1996, and
another watershed on Herrington Creek near Frostburg, Maryland (sampled in 1996 and 1997)
(Fig. 7). Generally, the trace element concentration at Bear Branch is more comparable to
the Potomac at its fall line than to the other two streams, which might be expected considering
that forested watersheds such as this comprise more than half the total drainage area. The
Anacostia concentrations are elevated for most elements because of its polluted nature.
Somewhat surprising are the elevated concentrations for Herrington Creek which are most
elevated for Fe, Mn, Ni, and Zn. This may reflect the compositions of the more metamorphic
lithologies or enhanced atmospheric deposition from coal fired power plants to the west in
nearby Maryland or the Ohio Valley.
Intensive Trace Element Loadings. Intensive sampling of the stream occurred on
three occasions, with the major ion data presented as Table 16 and both the dissolved and
particulate trace element data presented in Tables 17 and 18, respectively. The dissolved
instantaneous loads during the intensives are presented as Figs. 8 (a-e) and 9 (a-e) for the
May and August intensives respectively (the July intensive only yielded four samples with no
discharge or precipitation information). As will be shown later, the relative particulate load is
not important for most trace elements. These figures are presented as a time line, showing
both the precipitation amount, discharge, suspended sediment, and frequency of sampling.
During the first intensive (25 May 1994), 1.45 inches of rain fell and 9 samples were
collected (Fig. 8a).
The stream discharge rose suddenly during the first half hour during
which 4 samples were taken, and then fell gradually over the next several hours and even into
the afternoon of the next day. The dissolved metal loadings for the crustal Al, Fe, and Mn
(Fig. 8b) increased similar to discharge and suspended sediments and perhaps were
mobilized by the initial acidity. This pattern also typifies the dissolved loadings for Zn, Ni and
Cu in that order (Fig. 8c) and perhaps reflects the stabilization by strong organic ligands
which follow this same order predicted by ligand chelation stability constants (Irving Williams
Order; Stumm and Morgan, 1981). Dissolved Cd loading appears to decrease quickly after
the first few samples, and the order Cd, Cr, and Pb first increases and then decreases over
the following few hours. The dissolved loading for the metalloid As rises sharply with acidity
in the first few samples while Se shows a broader delayed pattern like Cd, Cr, and Pb. As
shown in Fig. 10, expressed as percent distribution, the particulate trace element loading is of
only minor significance for the crustal trace elements Al, Fe, (and to some extent Cr) plus the
anthropogenic elements As and Se throughout the storm, in spite of the initial rise in
precipitation and particle resuspension.
This may be a result of trace element enriched
particles stored during the winter gradually percolating out of the watershed during the spring
season. Lead particulate loading appears to dominate at times, but this is an artifact of
analyzing very small concentrations of lead near its detection limit with large relative
uncertainty. The second intensive yielded only four data points which is considered too few
for presentation and interpretation.
During the third and largest intensive (17 August 1994) when 3.6 inches of rain fell
into the watershed, 16 samples were collected over a 21-hour period. The discharge and
suspended sediment rose initially after the initial peak of precipitation along with acidity, but
then more gradually, with another peak 12 hours into the event.
This second peak
corresponds to the peak dissolved loading of the crustal elements Al, Fe, Mn along with Zn,
and to a lesser extent Se. All the other elements show less dramatic dissolved loading, with
Ni and Cd and Se peaking as much in the beginning as in the final period. Elements which
show little dissolved loading trend include Cu and Pb and Cr.
Table 16. Major ion disolved concentrations (µeq/L) collected during three stream intensives.
DATE TIME
COND Q pH pH H+ Ca2+ Mg2+ Na+
K+ CL- NO3 SO42- HCO3- SIO2
us/cm cfs lab field
µeq/L µeq/L µeq/L µeq/L µeq/L µeq/L µeq/L µeq/L µm/L
05/25/94
05/25/94
05/25/94
05/25/94
05/25/94
05/25/94
05/25/94
05/25/94
05/26/94
1417
1421
1425
1429
1434
1549
1649
1949
1507
26
27
28
27
27
29
27
25
21
0.55 6.13 5.49 0.74
0.76 5.57 5.31 2.69
1.0 5.62 5.41 2.40
1.3 5.62 5.46 2.40
1.7 6.15 5.41 0.71
1.2 5.54 5.45 2.88
0.89 5.55 5.46 2.82
0.65 5.35 5.53 4.47
0.65 5.61 5.55 2.45
49.9 52.3
52.0 52.2
53.3 56.0
53.7 56.8
53.6 57.9
57.5 67.2
55.0 66.0
48.4 60.0
43.1 54.3
07/06/94
07/06/94
07/06/94
07/07/94
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
2044
2048
2059
348
754
807
813
823
1212
1239
1543
1833
1903
1925
25
25
27
22
20
20
20
22
23
26
27
25
25
26
n.a.
n.a.
n.a.
n.a.
0.14
0.18
0.25
0.35
0.46
0.60
0.42
0.55
0.70
0.89
45.0
50.2
50.6
41.9
39.5
40.8
42.5
40.9
48.7
51.6
54.6
50.4
53.9
55.6
5.77
5.11
5.07
5.60
5.79
5.54
5.66
5.63
5.59
5.41
5.25
5.17
5.18
5.25
5.48
4.99
5.01
5.62
5.41
5.20
5.16
5.14
5.21
5.35
5.22
5.24
5.15
5.20
1.70
7.76
8.51
2.51
1.62
2.88
2.19
2.34
2.57
3.89
5.62
6.76
6.61
5.62
43.5
47.4
51.4
50.6
40.7
39.9
42.3
44.4
54.5
57.3
62.1
55.1
58.9
59.2
28.0
24.9
25.2
23.3
23.2
26.3
27.1
27.9
25.4
26.8
27.8
27.8
30.8
29.5
27.2
27.0
28.4
27.8
27.5
28.3
26.2
27.0
25.9
37.4
37.7
40.8
43.8
39.1
33.5
28.3
26.1
25.3
22.6
23.2
23.8
15.1
17.2
17.8
18.4
20.5
20.5
22.5
20.8
21.2
22.9
24.4
30.7
28.0
28.0
24.8
25.7
27.9
28.8
29.7
27.5
29.0
30.6
23.4
31.5
28.1
26.2
27.3
24.1
23.0
21.1
22.6
22.2
24.6
23.5
<0.5
1.00
<0.5
<0.5
<0.5
3.0
3.0
20.1
3.4
23.1
24.8
26.4
21.4
17.3
18.4
20.5
22.1
30.0
25.3
26.8
21.6
23.1
21 .6
104
108
115
107
115
120
119
112
95.8
30
26
32
32
27
3 .0
2. 1
1.0
10
66
59
57
53
50
59
62
69
68
90.1
109
118
89.3
66.9
66.1
69.4
70.0
75.9
82.7
82.5
80.4
89.2
88.5
7.1
<1.0
<1.0
2.9
<1.0
<1.0
2.5
<1.0
<1.0
<1.0
<1.0
<1.0
<1.0
<1.0
73
75
73
84
90
81
81
77
77
74
82
73
71
67
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
08/17/94
1957
2010
2034
2135
2215
2316
26
25
27
29
29
28
1.1
1.4
1.8
1.3
0.96
0.70
n.a. = not available
5.24
5.28
5.20
5.04
5.08
5.04
5.12
5.10
5.11
5.09
5.08
5.11
5.75
5.25
6.31
9.12
8.32
9.12
60.7
58.7
62.5
65.0
62.8
60.8
63.3
60.7
63.9
68.1
67.7
66.3
25.5
23.8
23.9
24.7
24.6
26.2
25.9
28.8
29.2
27.8
26.0
24.3
24.6
23.1
24.6
23.9
23.8
24.2
25.0
21.7
23.7
20.3
20.0
17.2
99.4
88.8
105
116
114
111
<1.0
<1.0
<1.0
<1.0
<1.0
<1.0
67
61
59
65
67
72
Table 17. Trace element dissolved concentrations (µg/L) collected in the stream during three stream intensives.
DATE
ID
Dischg Time
(cfs) (EST)
Precip
(mls)
pH
940525
940525
940525
940525
940525
940525
940525
940525
940526
I-1
I-2
I-3
I-4
I-5
I-6
I-7
I-8
I-9
0.550
0.760
1.036
1.289
1.698
1.200
0.890
0.649
0.649
940706
940706
940706
940706
I-1
I-2
I-3
I-4
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
I1
I2
I3
I4
I5
I6
I7
I8
I9
I10
I11
I12
I13
I14
I15
I16
14:17
14:21
14:25
14:29
14:34
15:49
16:49
19:49
15:07
0.70
0.05
0.00
0.00
0.01
0.04
0.00
0.00
0.65
5.49
5.31
5.41
5.46
5.41
5.45
5.46
5.53
5.55
24.3
30.6
46.9
39.5
63.2
37.5
20.2
11.5
22.3
0.666
0.161
0.065
0.064
0.080
0.137
0.195
0.105
0.109
0.08
0.06
0.07
0.07
0.07
0.08
0.07
0.05
0.06
0.26
0.39
0.40
0.31
0.50
0.47
0.33
0.62
0.67
3.20
3.96
3.97
18.6
3.86
2.87
3.14
2.03
1.95
18.7
12.3
17.2
454
162
41.7
34.8
24.4
22.3
1.1
1.6
1.2
1.0
1.3
2.3
1.6
2.4
1.2
nd
nd
nd
0.10
nd
0.06
nd
0.05
0.12
3.1
3.1
2.1
3.3
3.7
5.2
3.5
4.1
3.8
0.019
0.017
0.022
0.059
0.021
0.017
0.018
0.013
0.016
0.005
0.016
0.011
0.025
0.007
0.092
0.079
0.054
0.047
0.000
0.000
0.000
0.000
20:44
20:48
20:59
03:48
0.00
0.00
0.00
0.00
5.48
4.99
5.01
5.62
75.0
90.9
88.7
18.5
0.158
0.170
0.592
0.321
0.02
0.07
0.10
0.04
0.64
0.41
0.69
0.49
4.69
4.64
4.29
2.47
177
146
182
58.6
1.9
1.9
3.5
2.8
0.19
0.15
0.11
0.08
4.3 0.024
6.2 0.023
11.5 0.024
7.4 0.015
0.085
0.076
0.114
0.048
0.138
0.183
0.252
0.346
0.460
0.598
0.419
0.550
0.703
0.890
1.115
1.383
1.185
1.289
0.961
0.703
07:54
08:07
08:13
08:23
12:12
12:39
15:43
18:33
19:03
19:25
19:57
20:10
20:34
21:35
22:15
23:16
0.70
0.20
0.04
0.11
0.55
0.20
0.50
0.25
0.37
0.10
0.10
0.08
0.20
0.20
0.00
0.00
5.41 89.4 0.121 0.08
5.20 89.8 0.534 0.03
5.16 98.6 0.429 0.07
5.14 99.3 0.210 0.22
5.21 104 1.010 0.15
5.35 115
0.336 nd
5.22 85.4 0.298 0.21
5.24 104 0.523 0.20
5.15 114 0.703 0.21
5.20 139 0.307 0.07
5.12 157 0.293 0.08
5.10 139 0.333 0.16
5.11 156 0.192 0.14
5.09 144 0.192 0.13
5.08 118 0.170 0.16
5.11 101 0.205 0.19
0.44
0.42
0.37
0.47
0.49
0.52
0.37
0.47
1.10
0.79
0.85
0.36
0.40
0.60
0.44
0.52
20.1
8.19
10.9
12.6
12.1
70.3
12.0
25.7
12.2
13.9
14.0
17.1
17.9
16.6
13.0
12.4
76.4
89.1
92.6
86.0
80.6
92.2
77.6
84.5
79.1
92.1
104
101
111
105
100
90.4
1.9
1.8
1.2
1.3
1.9
nd
2.4
2.3
2.3
1.9
2.9
1.8
2.3
2.0
2.6
2.6
0.15
0.22
0.10
0.04
0.05
nd
0.10
0.17
0.07
0.15
0.13
0.17
0.16
0.22
0.07
0.08
4.8 0.025
5.0 0.021
5.0 0.021
5.9 0.021
6.4 0.015
6.2 0.024
8.2 0.019
14.4 0.027
10.4 0.017
10.1 0.019
6.7 0.022
7.1 0.022
7.7 0.021
8.4 0.024
8.5 0.021
8.6 0.017
0.061
0.076
0.083
0.061
0.141
0.080
0.068
0.080
0.111
0.102
0.108
0.112
0.104
0.117
0.105
0.107
nd = not detecteed
Al
Cd
Cr Cu Fe Mn Ni Pb Zn As Se
µg/L µg/L µg/L µg/L µg/L µg/L µg/L µg/L µg/L µg/L µg/L
Table 18. Trace element particulate concentrations (µg/g) collected in the stream during three storm intensives.
Sample
ID
Al
µg/g
Cd
µg/g
940706
940706
940706
940706
Cr
µg/g
Cu
µg/g
Fe
µg/g
Ni
µg/g
Pb
µg/g
Zn
µg/g
As
µg/g
Se
µg/g
1*4
2*4
3*4
4*4
61800
80200
612000
4540
0.9
0.8
1.1
0.6
41
49
423
6
13
18
142
4
20800 1840
22700 2450
216000 19500
1630
56
21
23
237
14
30
36
29
7
67
74
646
18
2.5
2.8
2.5
0.9
0.7
0.5
0.7
0.6
940525
940525
940525
940525
940525
940525
940525
940525
940525
1*9
2*9
3*9
4*9
5*9
6*9
7*9
8*9
9*9
6270
98000
62500
93400
77000
91600
328000
272000
57100
7.1
12.0
1.1
1.4
0.7
1.5
16.9
28.7
1.2
7
202
56
69
53
211
1540
1120
58
2
37
14
21
17
69
173
363
18
2680
37400
23000
26000
14500
35000
117000
73800
23000
363
7
5200
77
3400
28
1060
24
2210
20
2180 135
4850 616
4940 1152
2040
44
6
51
27
35
24
49
168
361
39
16
146
74
93
73
80
827
675
89
1.9
10.3
3.3
3.9
2.2
7.2
57.0
87.0
3.8
0.2
2.8
0.6
0.6
0.9
0.7
6.0
11.7
0.8
940817
940817
940817
940817
940817
940817
940817
940817
940817
940817
1*16
41800
2*16 198000
3*16
73600
4*16
63400
5*16
31300
6*16
48900
7*16
23300
8*16
30900
9*16
39300
10*16
1.2
39.1
3.2
0.9
17.4
1.7
5.4
5.1
1.9
40
128
24
29
24
27
61
39
15
8
14700 1350
8
105
76400 7240
80
9
11500 1780
11
36
14400 1570
9
106
14700 1200 145
9
13500 1220
2
6
8640
516
23
11
10900
743
16
5
1420
148
3
***** SAMPLE LOST *****
32
156
31
31
54
33
38
27
11
62
169
49
53
175
46
65
55
28
2.9
7.7
3.1
2.7
4.1
2.5
4.5
4.3
1.0
0.5
5.2
0.4
0.5
3.7
ISA
9.2
2.8
2.7
940817
940817
940817
940817
940817
940817
11*16 45900
12*16 111000
13*16 126000
14*16 27700
15*16 25600
16*16
3130
28.1
16.5
3.9
0.9
1.2
0.1
53
37
43
48
48
<3
16
22
23
5
8
1
1890
4880
5730
10100
9700
260
184
437
509
657
644
67
8
20
12
31
26
1
97
14
309
49
6
1
171
264
227
59
51
15
10.0
8.5
13.6
2.0
2.3
0.1
ISA
ISA
4.9
ISA
0.9
ISA
Stream Sediment
Site #1
45300
Site #2
49200
Site #3
45400
Site #4
24000
1.2
0.4
0.3
0.1
23
28
26
14
16
14
10
5
15900 2150
20900 2940
20000 2970
13000 919
14
16
13
5
68
30
21
11
20
51
52
19
ISA
ISA
ISA
ISA
ISA
ISA
ISA
ISA
ISA = Insufficient Amount of Sample for analysis
Mn
µg/g
The suspended particulates plotted in Fig. 9a show that the storm began and ended
with a pulse of both precipitation and associated particles. The suspended particulate load
rose to a very sharp primary peak, then fell and then peaked secondarily with the discharge
some 12 hours later.
During this intensive, the particulate metal loading expressed as
percentage distribution (Fig. 11) is again of only minor importance for the crustal elements Al,
Fe, Cr and anthropogenic elements Pb and As near the beginning of the intensive, even
though discharge and resuspension rose throughout the event. This may reflect the initial
washout of organic fines accumulated in the watershed during the drier summer period.
Annual
Particulate
Loading.
Particle trace element loading was only
evaluated on an intensive basis as just
described, but the data can be used to
estimate its importance on an annual basis.
On the regular weekly or bi-weekly grab
samples, neither were the suspended
particulate loading collected
nor
Table 19. Estimated suspended particulate
stream loading based on measured
average loadings during the summer
intensives.
________________________________
Average Particulate
Flow Ranges (cfs) Loading (mg/L)
________________________________
0.00 - 0.1
0.01
0.2 - 0.74
0.05
0.75 plus
0.14
________________________________
their
analyses performed under this project.
However,
one
can
estimate
the
particulate
stream burden in the following way. The annual discharge hydrograph curve was partitioned
into three averages based on the particulate loadings calculated for the intensives (Table 19).
Next, streambed material collected in late August 1994 was analyzed in total, and separated
into a low (organic) and high (inorganic) specific gravity fractions.
This separation was
accomplished using dilute magnesium sulfate (dominant cation and anion) solution of mean
concentration to that measured in the stream adjusted to its mean pH.
The trace element analysis of the
fraction was assumed to be dominantly
lighter fraction was applied to the two lower
resuspended.
The total trace element
ranges of discharge where the organic
analysis
applied
was
to
the highest
discharge range where total resuspension
(Potomac) or coastal waters (Chesapeake
of both the organic and inorganic fractions
Bay).
was assumed to take place. The results
are listed in Table 20 and expressed again
as percent dissolved/particulate distribution
in Fig. 12. Calculated accordingly, all trace
element particulate loadings are of minor
significance for Fe, Mn, Al and Cr ranging
only 5% (Cr) to 40% (Fe) in importance.
Even at these levels, the particulate load is
not expected to be carried very far
downstream or contribute significantly to
loading of receiving rivers
Table 20. Annual measured dissolved and estimated
particulate loading of trace elements in the
Bear
Branch stream.*
_________________________________________
Dissolved
Particulate
Total
g/year
g/year
g/year
_________________________________________
Al
28000
1840
29800
As
6
130
136
Cd
100
0.025
100
Cr
50
1.2
51
Cu
310
1
313
Fe
1650
1210
2860
Mn
8370
1400
9770
Ni
450
*not estimated
450
Pb
20
180
200
Se
30
*not estimated
30
Zn
2000
80
2280
________________________________________
* Since Se and Ni were not analyzed in the sediment
samples, and they cannot be estimated here. Based
on intensive data, the particulate fraction for these
elements comprises less than 2% of the load.
C.
Dissolved Trace Element Mass Balance
The degree of retention of a given element in the watershed will largely depend on the
degree to which it is effectively complexed by the soil organic matter. A number of studies
have reported that Pb is immobile in forest soils and exhibits a long soil residence time in the
forest floor (Friedland et al., 1992, and references therein).
The bulk atmospheric loading to the watershed was evaluated on the basis of weighted
canopy throughfall and is compared to the dissolved stream export on seasonal and annual
bases in Figs. 13 and 14 respectively and the following observations are made.
For the crustal-type elements, Cr is retained during all seasons, while Fe is
predominantly retained during the spring and summer. However, Al and Mn are exported
primarily in winter and secondarily in spring, somewhat opposite than expected for any
vegetative effects. This may be related to pH; in winter and spring the stream pH is generally
lower than at other times of the year. The low pH of atmospheric deposition (~4.2) in this
region strongly affects the weathering solutions and the export of major elements and trace
elements from the watershed. The mobilization and transport of Al and Mn are pH dependent,
their solubilities increasing with decreasing pH. In summer, the pH of the stream is near the
solubility minimum for aluminum oxyhydroxide phases and for kaolinite (~pH=5.8), thus Al
should be strongly retained in the watershed during the summer period. The solubilities of
these phases increases rapidly below this pH value (Drever, 1988) leading to greater export
of Al in winter and spring when stream pH is lower. In general, the solubilities of silicate
minerals such as chlorite and epidote increase with decreasing pH (Sverdrup, 1990), although
the solubility of feldspar minerals is rather insensitive to pH over the range pH 4-pH 9
(Wollast and Chou, 1985).
For bioactive elements (Cu, Se, and Zn), retention is greatest during the summer and
fall, although both metalloids As and Se are strongly retained during all seasons. For Cd, Cu,
Ni, and Zn stream export exceeds atmospheric import during the winter and spring, as might
be expected if recharge during these months acts to flush the aquifer loadings of metals
complexed from the previous seasons of forest growth and decay.
On a yearly basis, atmospheric bulk deposition exceeds stream export during all
seasons for many elements such as As, Mn, Cr, Pb, Se and Fe. These are elements which
apparently are retained in the watershed during all seasons. For Al and Cu, net dissolved
export occurs only during the winter, while for Cd, Ni and Zn it occurs during the spring as
well.
The retention of dissolved constituents in the Bear Branch watershed was evaluated by
using the ratio of the three types of atmospheric fluxes. This ratio was calculated separately
for wet only, total (bulk) fluxes in the open, and the total throughfall under the canopy,
weighted for coniferous and deciduous types divided by the dissolved stream export (retention
factor). On an annual basis, this is plotted in Fig. 15 for all three of the atmospheric collector
types. The inverse ratio (transmission factor) is also calculated for atmospheric throughfall
and shown as Fig. 16.
Trace elements for which the watershed retention was nearly zero compared to
atmospheric deposition into the open bulk collector (RF of 1 ± - 0.5) included Al, Cd, Mn, Ni,
and Zn, with the yield under the canopy in slight deficit for Al, Ni, and Zn. The greatest
relative canopy enrichment was for Mn, Fe and Pb which perhaps represents active tree
pumping from the unsaturated zone followed by leaf exudation, as reported for Mn (Lindberg,
1989).
An inspection of the transmission factor shows that the export for Al, Mn and Cd
exceeds wet only input, and for Ni, Mn and Cd, bulk input as well. This might suggest that
there is a weathering source for these elements in excess of atmospheric deposition, in spite
of the NETPATH calculations discussed in the next section.
Alternatively, this might be
important evidence for the non-steady state release of trace elements from earlier periods of
higher atmospheric deposition stored within the watershed.
All other trace elements were mostly retained within the watershed in the order (RF
value) Cu (5), Cr (5), Se (8), As (18), Fe (20), and Pb (30). The large retention value for
Fe reflects a factor two greater of component dry deposition being retained by the canopy.
Like Mn, for As, Fe, and Pb, the canopy had a noticeable effect on increasing the fraction
retained. In all these cases, the transmission factor is less than one, more so based on the
canopy throughfall than the wet or bulk input for Se, Cr, and Cu. This may reflect particle
reactive uptake primarily on vegetation and for Cu by particles in the bulk deposition as well.
The elemental factors involved in retention are probably complex, involving both abiotic
weathering and biotic forest effects. Those elements which are retained tend to have particle
reactive (Type A) chemistries. Some similarities include the retention of the metalloids As and
Se which form reactive oxy-anions in their oxidized states. Some anomalies include the
crustal elements, most of which would be expected to be retained as Type A elements
involved in reverse weathering reactions. The efficient export of Al and Mn (canopy effects
excepted), may be due to their tendency to form organic chelates with fresh organic material,
and even become stabilized in the case of partially oxidized Mn. Another anomaly is Cd (the
most efficiently exported) vs. Pb (the most efficiently retained) which are normally very similar
elements and as Type A expected to be retained. However, Cd can have a unique biotic
behavior by substituting in Zn enzymes under nutrient limitation or during bacterial cell wall
synthesis which may contribute to its export efficiency. This striking difference has also been
observed in the Delaware watershed (Church and Scudlark, 1998).
D.
NETPATH Modeling
In order to determine the amount of atmospherically deposited trace elements that are
transmitted through the watershed as dissolved species, it is necessary to know the quantity of
each of the elements that are deposited from the atmosphere and the quantity released from
watershed sources by weathering processes. The trace elements deposited by atmospheric
deposition and the quantity released from watershed sources by weathering processes should
tend toward some steady- state balance.
The trace elements deposited by atmospheric
deposition were measured directly and the computer code NETPATH (Plummer et al., 1994)
was used to assess the potential magnitude of the contribution of trace elements derived from
within the watershed. NETPATH uses the compositions of initial water, a final water, and the
compositions of all of the mineral phases in the system to calculate how much of each phase
must either be dissolved or precipitated to change the composition of the initial water to that of
the final water. We assume that only those minerals that undergo chemical weathering in the
watershed are potential contributors of trace elements to the system. If the amount of each of
the minerals weathered, and their trace element content is known, then the amount of trace
elements that could potentially be contributed from watershed sources can be calculated.
The Weverton Formation, the bedrock formation underlying the Bear Branch watershed,
is an orthoquarzite which consists almost entirely of the mineral quartz, but contains small
amounts of plagioclase feldspar, orthoclase, chlorite, and illite with trace amounts of epidote,
ilmenite, rutile, tourmaline, and zircon. Quartz is one of the most inert minerals known in the
weathering environment, and quartz is also very pure, generally containing elemental
substitution at the less than 0.000X% level (primarily Al and Ge). The inertness of quartz in
the weathering environment combined with this high degree of purity make it very unlikely that
significant amounts of trace elements would be contributed by weathering of quartz. For
example, if all of the dissolved silica measured in Bear Branch (typically <100 μm/L) was
contributed by weathering of quartz, trace element release would be in the 10 μm/L range,
i.e., below detectability for most trace elements. Illmenite, rutile, tourmaline, epidote and
zircon are found in the heavy mineral suite of Bear Branch stream sediments indicating that
they do not weather readily. As will be shown below, the streamwater chemistry is consistent
with weathering small amounts of plagioclase feldspar, orthoclase, chlorite and epidote. Any
watershed contribution to the trace element load of the stream must come predominantly from
these minerals.
The potential watershed trace element contribution from mineral dissolution was
determined based on the trace element content of each of the minerals, multiplied by the
amount of the mineral reacted.
There is little direct information on the trace element
composition of specific minerals in the Bear Branch watershed. Preliminary qualitative EDAX
scans of orthoclase revealed a trace of Ba, scans of epidote revealed trace lanthanides and
small amounts of manganese. There was no indication of other trace elements in these
phases.
Additional information from the literature provides a range of trace element
compositions within which the Catoctin minerals are likely to fall.
By using the largest
concentrations within the range, a maximum watershed contribution can be calculated. This
procedure should overestimate the actual watershed contribution.
Thus, if the calculated
contributions are insignificant, it should be safe to assume that atmospheric deposition is the
major source of trace elements to the system.
The computer code NETPATH was run using rain as the input solution, streamwater as
the output solution, dissolved ions in the waters as constraints, and the primary and secondary
minerals and CO2 as reactive phases to calculate mass transfers in the system (i.e., the
amounts of each of the minerals dissolved or precipitated to give the output water
composition).
A geochemically reasonable model that resulted from the NETPATH runs
indicated that 0.012 mmol chlorite, 0.026 mmol plagioclase feldspar, 0.125 mmol orthoclase
feldspar and 0.052 mmol of epidote dissolve per kilogram of water per year, while 0.168
mmol kaolinite, 0.080 mmol pyrite and 0.213 mmol of silica are formed per kilogram of water
per year. These reactions account for the streamwater composition and the residual kaolinite
in the watershed.
The only trace elements of interest to this project that the minerals NETPATH identified
as reactants (dissolved to produce observed water compositions) are likely to contain Al, Fe,
and Mn (Deer et al.,1965). Chlorite, a Mg-Al-Fe silicate mineral, commonly contains a small
amount of Mn, Cr, and Ni (Lapham, 1958). Some unusual chlorite minerals contain as much
as 0.160 atoms of Cr and 0.034 atoms of Ni per mol, but these occur in association with ore
deposits in ultramafic rocks of New Zealand, not in the type of rocks that form Catoctin
Mountain.
Feldspars (alkali and plagioclase) may contain trace amounts of Mn and Fe,
generally less than 0.002 and 0.07 atoms/mol, respectively. Epidote, a Ca-Fe-Al silicate
mineral, commonly contains 0.02 atoms/mol Mn and trace amounts of the lanthanide
elements.
From the NETPATH estimates of
specific quantities of minerals dissolved and
formed in the Weverton Formation and
compositional information on these minerals
from other localities, one can estimate the
relative contribution of at least Mn, Cr, and
Ni loadings from mineral dissolution and
formation relative to the canopy throughfall
and stream loading (Table 21).
and Al are excluded since
already
The Fe
they are
Table 21. Comparative loadings (g/yr) of Mn, Cr and
Ni to Bear Branch watershed.
___________________________________________
Mineral
Atmospheric Stream
Dissolved Formation Throughfall Loading
____________________________________________
Mn
126
77,720
8370
Cr
146
162
51
Ni
35
142
634
450
___________________________________________
considered major components included in the NETPATH modeling. The results show that the
amounts of these three metals involved in new mineral formation contributed by mineral
weathering are indeed small. In fact, the amount of Ni taken up by mineral formation (pyrite)
exceeds several fold the amount dissolved from source minerals. The exception is Cr which
may have an equivalent contribution from atmospheric deposition and mineral (chlorite)
weathering. However, considering that the calculation used the highest reported Cr content for
Cr-clinochlore (a Cr talc chlorite), the Cr contribution from mineral dissolution may have been
overestimated.
Another approach to estimating the amount of trace elements contributed by rock weathering
is to estimate that from the dissolution of phyllite, the major trace element micaceous type in the
bedrock. Phyllite, which is estimated to make up 6% of the bedrock, was analyzed for trace elements
(Table 22). A maximum calculation would be if all the silica dissolved in the streamload came from
the dissolution of the other 94% silica in the bedrock. The NETPATH model predicts the formation
of several other new minerals which can consume significant quantities of Si, Al, and probably Fe.
In fact, the calculation reflects this in that 70 and 445% of the Al and Fe in the stream could come
from phyllite weathering. Only Cr and Pb could derive 10-20% from such a process, which is still
minor. However, for all the other trace elements considered, complete weathering of phyllite is an
insignificant proportion of the dissolved load in the stream. These calculations only reinforce the
concept that the majority of the trace elements not incorporated as major constituents in rocks (Al,
Fe) are being exported from the Bear Branch watershed from the transmission of atmospheric
throughfall.
Table 22. Comparative loadings (g/yr) of trace elements to the Bear Branch watershed from weathering 6% phillite in
the bedrock.
Element
Al
Fe
Mn
Zn
Cr
Ni
Cu
Pb
As
Phillite
Phillite
Dissolved
Composition
Weathering
Streamload
(µg/g)
(g/yr)
(g/yr)
125,000
46,800
340
109
51
26
17
15
0.38
19,700
7,360
53
17
8
4
3
2
0.06
27,000
1,650
8,370
2,000
51
450
312
18
6
% Phillite
Weathering
70
445
0.6
0.9
16
0.9
1.0
11
1.0
E.
Comparison of NETPATH and Mass Balance
It is apparent, from examination of Figs. 14 and 15 and, considering the NETPATH
results, that the transmission of trace elements through the watershed is strongly affected by
biogeochemical processes within the watershed. Figure 14 shows that there is more Fe and
Al being contributed to the system by atmospheric deposition than is being exported by the
stream. These two elements are also produced by weathering reactions in the watershed, so
it is expected that there would be considerably greater export than input, however the reverse
is observed. The solubility of aluminum oxyhydroxide minerals and kaolinite is a function of
pH, and the minimum in solubility occurs near pH=6. Al in the streamwater under base-flow
conditions corresponds closely to that which would be expected in equilibrium with a poorly
crystallized gibbsite. It is believed that the export of Al is controlled by the solubility of this
phase, consequently, Al is strongly retained in the watershed.
In similar fashion, Fe is
contributed by both atmospheric deposition and weathering in the watershed, therefore, one
would expect to observe greater export than input from atmospheric deposition. Again, the
opposite is observed; Fe is strongly retained in the watershed.
The solubility of iron
oxyhydroxide minerals under the redox conditions of the oxygenated streamwater is very low.
Under these conditions, Fe will be oxidized and retained in mineral phases in the watershed.
In the scattered small wetland areas adjacent to the stream where organic matter is being
decomposed, Fe is immobilized as iron sulfide (pyrite), another highly insoluble compound.
Thus, Fe is largely retained in the watershed.
Magnesium exhibits a slight excess of export over input. This reflects both the internal
source of Mg in the watershed and the significantly greater solubility of Mg minerals over Fe
minerals under the pH and redox conditions in the system. There is no apparent watershed
source for any of the other trace elements investigated, however, their transmission through
the system may be influenced by watershed processes. Iron oxide is an efficient scavenger of
many trace elements. Pb, the most strongly retained trace element in the system, is known to
sorb strongly onto ferric oxyhydroxide and organic matter. Arsenic, Cr and Se also have an
affinity for ferric oxyhydroxide surfaces and may be scavenged and retained in the watershed
by that mechanism. Careful examination of the secondary mineral phases and the organic
detritus in the system would be necessary to establish the extent of sorption and coprecipitation processes. The transmission of trace elements through a forested watershed,
even one with relatively simple and resistant bedrock, is not straightforward.
For some
elements, export in the dissolved form approximately balances inputs from atmospheric
deposition, while for other elements there is strong retention in the solid phases.
The
elements that behave in the latter manner will be transmitted through the watershed in
association with the particulate matter during episodic events of sufficient magnitude to
mobilize and transport sediment.
VII.
SUMMARY AND CONCLUSIONS
A major focus of this study was to improve our estimation of the indirect transmission
of atmospherically-deposited metals through watersheds into recipient coastal waters, such as
Chesapeake Bay. Based on a very limited amount of data from one forested watershed at
Walker Branch, Tennessee (Lindberg and Turner, 1988), the assumption has been made that
the net transmission is relatively low. Our previous estimation (Scudlark and Church, 1997),
employed an annual, watershed integrated average transmission factor of 10% for all metals.
Even utilizing such modest estimates, for most metals the indirect atmospheric loading terms
were comparable to the direct input to the Bay surface water. This is a reflection of the large
drainage basin to open water ratio for the Chesapeake (16:1), which is typical of coastal plain
estuaries (Scudlark and Church, 1997).
Although our results for Bear Branch can only be applied with a limited degree of
certainty to catchments possessing similar land use and lithology, they provide some qualitative
insight into processes affecting metal retention vs. export. In particular, they furnish first-order
estimates of the behavior of metals in forested systems, which represent about 60% of the
land use in both the Potomac and parent Chesapeake watersheds.
The results of the study indicate that some elements (notably Fe and Pb) are very
effectively captured in forest soils. In the case of Pb, this appears to be related to efficient
complexation by organic ligands. In fact, it is interesting to note that the Retention Factor
order reflected in Fig. 15 (Pb>Cu>Zn, Ni>Cd) is nearly identical to the reported stability of
organo-metallic complexes averaged for U.S. forest soils (Pb>Cu>Ni>Cd>Zn) (KabataPendias and Pendias, 1984). One might predict, therefore, that in more highly developed
soils, the degree of retention for these elements would be even greater. Thus, for such
elements, we may have over estimated their indirect atmospheric loading in our previous
assessment (Scudlark and Church, 1997). It is also tempting to speculate that if an organic
complexation mechanism is valid, it may be that eastern watersheds which are accumulating
metals, may some day exceed their finite "carrying capacity" and begin "leaking" stored
reservoirs during long term diagenesis and decomposition of organic matter in the forest soil.
Conversely, forest soils appear to be more unreactive than previously believed towards
other elements. For example, within the uncertainty imposed by our experimental design, it
appears that virtually all of the atmospherically deposited Cd and Ni are transmitted through
the Bear Branch watershed.
In some respects, this contrasting behavior is somewhat
surprising, since Cd and Pb possess similar chemistries and generally exhibit parallel behavior
in other natural aquatic systems. Indeed, Lindberg and Turner (1988) report that Cd was
strongly retained (79-91%) in the Walker Branch watershed. Thus, for such elements, the
watershed transmission of atmospherically-deposited metals may vary regionally depending on
the particular watershed characteristics. If Bear Branch is typical of forested watersheds in the
Potomac, then atmospheric throughput of trace elements may be considerably larger than
originally estimated.
It is also interesting to note that studies have shown that the rate of organic
decomposition in forest soils decreases in response to the accumulation of toxic metals
(Ruhling and Tyler, 1973; Johnson and Lindberg, 1992 and references therein). Thus, it is
interesting to speculate that from an ecological perspective, the atmospheric input of nutrients
and metals may be providing a feedback mechanism whereby the complexation capacity
(organic content) of forest soils is being increased and accommodating an increased metal
burden.
This theory, if valid, would also have serious implications with respect to basic
nutrient recycling in forested ecosystems.
Clearly, there exists a critical need to extend studies such as this to other forested
watersheds (having differing lithologies) and other representative land use types.
The
challenge will be to deconvolute weathering reactions under more complex land use regimes
that include urban and agricultural watersheds.
ACKNOWLEDGMENTS
We wish to specially recognize the invaluable assistance provided by Judy Leonard
(UDE) who contributed substantially to construction of the final report. We also wish to thank
Marie Freeman (UDE) for providing laboratory assistance, and George Zynjuk and Jeff Kevch
(USGS) for constructing the gauge house and installing equipment at Bear Branch. In
particular, we wish to commend the efforts of our site operator, Ms. Chris Carter of the USGS,
without whose conscientious dedication and perseverance this project would not have been
possible. We gratefully acknowledge the cooperation and assistance afforded in hosting this
study by Mr. William Miller (Manager) and Mr. Chuck Boller (Assistant Manager) at
Cunningham Falls State Park. We wish to especially thank Dr. Paul Miller at the Maryland
Department of Natural Resources, for his patience and scientific interest displayed in
overseeing and supporting this project.
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