Sensitivity of Oregon's Cascade Lake s
to Acid Precipitatio n
by
Peter 0 . Nelso n
Gregory K . Delwich e
Water . Resources Research Institut e
Oregon State Universit y
Corvallis, Orego n
WRRI-8, 5
September 1983
SENSITIVITY OF OREGON'S CASCADE LAKE S
TO ACID PRECIPITATION
by
Peter O . Nelson and Gregory K . Delwich e
Civil Engineering Department, Oregon State Universit y
Final Technical Completion Repor t
for Project No . A-061-ORE
to
United States Department of the Interio r
Washington, D .C . 2024 0
Project Sponsored by :
Water Resources Research Institut e
Oregon State Universit y
Corvallis, Oregon 9733 1
The research upon which this report is based was financed in part by the U .S .
Department of the Interior, Washington, D .C . (Project No . A-061-ORE), a s
authorized by the Water Research and Development Act of 1978, P .L . 95-467 .
Contents of this publication do not necessarily reflect the views an d
policies of the U .S . Department of the Interior, nor does mention of trad e
names or commercial products constitute their endorsement or recommendatio n
for use by the United States Government .
WRRI-85
September 1983
ABSTRACT
A study of 63 Oregon Cascade lakes was conducted in 1982 to determin e
their susceptibility to acidification and to assess the extent o f
anthropogenic acidification that may have occurred to date . The study also
established baseline data for important chemical parameters against whic h
possible impacts could later be assessed and for comparison to dilut e
acidified lakes of similar geology as an aid in data interpretation . Th e
sampled lakes typically were located in forested watersheds at elevations o f
1000 to 2,000 meters . Geology of this study area is predominantly volcanic .
Of the 63 lakes sampled in this study, 55 lakes were grab-sampled on e
time each from shore or from a boat . The remaining 8 lakes were sampled 3
times each between July and October 1982 to gain an understanding of th e
temporal fluctuations in their water chemistry . Grab samples were taken fro m
shore on three of these lakes . The remaining five lakes were sampled from a
boat at various depths within their water columns . Temperature, pH ,
dissolved oxygen and light intensity profiles were also obtained for thes e
lakes .
All of the lake samples were analyzed for pH, conductivity, alkalinity ,
calcium, magnesium, sodium, potassium, dissolved silica, chloride an d
sulfate . Major ion balances were calculated . Analyses for total organi c
carbon, fluoride and aluminum were also performed on some samples .
Particular emphasis was place upon developing an understanding of th e
predominant buffer system in the lakes . The carbonate system, inorgani c
aluminum, and weak organic acids all have been reported to be significan t
buffer systems in other lakes of igneous geologic origin .
The investigated lakes studied can be characterized as having a n
extremely dilute ionic composition . The average conductivity was 17 . 0
umhos/cm . The average laboratory-equilibrated pH was 6 .96 ; the range wa s
5 .83 to 7 .91 . Alkalinities ranged from 1 to 527 ueq/l, with an average o f
137 .6 ueq/l . Twenty-five lakes had alkalinities of less than 50' ueq/l whil e
26 more had alkalinities less than 250 ueq/l and 11 of the remaining 12 lake s
had alkalinites less than 500 ueq/l . Nearly all of the lakes sampled in thi s
study are susceptible to acidification, according to recently propose d
criteria .
Calcium was the major cation (36%) and bicarbonate was the major anio n
(82%) present in the lakes studied .
Aluminum concentrations were extremel y
low (generally less than 20 uq/l) ; sulfate concentrations were also quite low
(generally less than 300 ug/l) . -Total' ion balances generally agreed withi n
10% (cation vs . an.ion) .
The dominant buffer system in the Oregon lakes was the carbonate system .
The extremely low aluminum and total organic carbon concentrations indicat e
the minor contribution of aluminum hydrolysis species and weak organic acid s
to the overall acid neutralizing capacity of these waters . The ratio o f
calcium to bicarbonate (equivalent basis) and the low dissolved aluminum an d
sulfate concentrations clearly indicate that anthropogenic acidification i s
undetectable to date in Oregon's Cascade lakes .
It was concluded that Oregon does not generally seem to have an aci d
precipitation problem at present . However, the lakes of the Oregon Cascade s
are extremely susceptible to acidification and could be rapidly impacted i f
acid precipitation were to occur . The lakes may serve as in chemica l
benchmark against which acidified lakes of similar geology can be compared .
FOREWORD
The Water Resources Research Institute, located on the Oregon State .
University campus, serves the State of Oregon . The Institute fosters ,
encourages and facilitates water resources research aed education inveLvi.n g
all aspects of the quality and quantity of water available for befi .cia l
use . The Institute administers and coordinates statewide aiid regi ;oaal,
programs of multidisciplinary research in water and related land re
r p ces. .
The Institute provides a necessary communications and coo .r~dination lin k
between the agencies of local, state and federal government, as wel .i as th e
private sector, and the broad research community at universities in the stat e
on matters of water-related research . The Institute also coordinates th e
inter-disciplinary program of graduate education in water resources at Oregon
State University .
It is Institute policy to make available the results of significan t
water-related research conducted in Oregon's universities and colleges . Th e
Institute neither endorses nor rejects the findings of the authors of suc h
research . It does recommend careful consideration of the accumulated fact s
by those concerned with the solution of water-related problems .
ACKNOWLEDGEMENT S
The authors wish to ackno w.;kedge the extensive help of Donald B . Miller ,
Research Associate, in condnoting the laboratory measurements . We also than k
Anne Chung, Jeff Dresser and Alan Ratcliff, graduate students i n
environmental engineering, for assistance with the Iaborlatory work . Davi d
Nichol, undergraduate civil engineering student, is thanked for his care i n
the final preparation of figures and tables and in making the regressio n
analyses . Laurie Delwiche, field aid, is thanked for her assistance i n
sample collection at most of the lakes .
ii
TABLE OF CONTENTS
P
List of Figures
. .y .
iv
.
.
.
iv
Introduction
.
. .
1
Research Procedures
.
.
.
3
.
.
. .
. .
3
4
. . .
9
. . .
. . .
9
9
List of Tables .
.
y
Sampling Methodology Analytical Techniques
Results of Analyses Overview of Results
Detailed Results
Discussion of Results
.
23
. . .
. . .
. . .
23
24
26
Conclusions
. . .
33
References
.
..
39
Appendices
. . .
39
Limnological Data for Studied Cascade Lakes . . . . .
Chemical Data for Studied Cascade Lakes . . . . . . .
Discussion of Experimentation in Laborator y
. . .
Techniques
41
45
Regional, Temporal, and Spatial Trend s
in Water Chemistry
General Acidification Sensitivity Criteria
Applicability of Acidification Sensitivity Models .
A.
B.
C.
. .
51
LIST OF FIGURE S
1 .
Study Area, Oregon Cascade Lakes .
2
2.
Bar Graph of Average Concentrations for Major Cations an d
Anions for the 63 Cascade Lakes .
11
3.
Alkalinity Frequency Distribution for the 63 Cascade Lakes .
12
4.
pH Frequency Distributions for the 63 Cascade Lakes .
.
13
5.
Relationship Between Alkalinity and Lab pH fo r
the 63 Cascade Lakes
.-
17
Titration Curves for Selected Cascade Lakes o f
Differing Alkalinity
.
25
Calcium-pH Diagrams for Oregon Cascade Lakes in Compariso n
with Washington Cascade Lakes .
30
6.
7.
. . .
LIST OF TABLES
Page
1.
Data Summary for Oregon Cascade Lakes 2.
Correlations of Major Cations and Anions wit h
Conductivity and pH, and Selected Cross-Correlations
3.
Alkalinity-Calcium Relations for Lakes fro m
Various Regions
iv
10
. , . . 14
29
INTRODUCTION
Acidification of lakes and streams has been identified as a serious wate r
quality problem in the northeastern United States (Driscoll, 1980) ,
southeastern Canada (Dillon et al ., 1980) and Scandinavia (Wright an d
Henricksen, 1978) . Acid precipitation has been recently reported in th e
central Washington Cascades, but concomitant lake acidification has apparentl y
not occurred to date (Logan et al .,1982) .
Based on Iimited data, acid precipitation does not appear to be a genera l
problem in the Oregon Cascades (Powers and Rambo, 1981
.U
;
.S . Geologica l
Survey, 1981) . There are no major sources of sulfur dioxide emissions i n
western Oregon ; however, automobiles in the heavily populated Willamett e
Valley and metropolitan Portland area represent a source of oxides o f
nitrogen . Such emissions have been indicated as the predominant causes o f
acid precipitation downwind of the Los Angeles area (Liljestrand and Morgan ,
1978) . Acid precipitation was recorded in Oregon immediately before an d
following the June 12, 1980 eruption of Mount St . Helens . Volcanic ash wa s
found in precipitation collectors following this eruption . Southerly wind s
which were blowing at the time of this eruption are, however, relatively rar e
in this area .
There were three primary objectives of this study : (1) . to determine th e
sensitivity of Oregon's Cascade lakes to acidification ; (2) to assess th e
extent of anthropogenic acidification that may have occurred to date ; and (3 )
to establish baseline data for important chemical parameters against whic h
possible impacts could later be assessed and for comparison to dilut e
acidified lakes of similar geology as an aid In data interpretation .
Sixty-three lakes in the Oregon Cascades, shown in Figure 1, were sample d
between July and October 1982 . The Oregon Cascade Range rams approximately 7 0
km east of the Willamette Valley and Portland, and downwind of prevailin g
westerly weather patterns . The lakes sampled in this study typically wer e
located in forested watersheds at elevations between 1,000 anal 2,000 meters .
The lakes and streams of the Oregon Cascades have geological, physical an d
chemical characteristics typical of waters sensitive to acidic imputs . Suc h
lakes are generally shallow, have small watershed/surface area ratios, low
productivity and short residence times . Watersheds are characterized b y
poorly developed seils, high .aamual precipitation and short soil/wate r
retention times . Bedrock is geaeraliy siliceous, of igneous origin, an d
highly resistant to chemical weathering . These charcteristics have bee n
proposed by others as typical of areas with acid-sensitive lakes (Schofield ,
1976 ; Wright and Gjessing, 1976 ; Driscoll, 1980 and Hendrey et al ., 1980) .
Although water chemistry data for Oregon's Cascade lakes is generally limited ,
60 of 80 lakes sampled in 1975 by Shulters (1975) had alkalinities less tha n
200 ueq/l, indicating the extreme sensitivity of these lakes to acidification .
STATE OF OREGO N
ENLARC'EU AREA OF
HIGH CASCADES
OLALLI E
MONOD
HORSESHOE
GIBSO N
BREITENBUS H
F I RST
HEAD
LOWE R
F I SH
SHEEP
WAL L
AVERILL
RED
BROOK
JUDE
RUSS
7
JORN
RED BUTT E
SANTIAM
DUFF Y
MOW I CH
BLUE, ROUN D
SCOU T
CLEA R
THREE CREEK S
LAVA CAMP, SCOTT
TODD
DEVILS
SPARK S
ELK
HOSMER
LAVA
L. LAVA
LUCKY
K I WA
WAHANNA
TORRE Y
WHI G
U. RI GDO N
L. RI GOON
BETT Y
GOLD
U. MARILYN
L. MARILYN
ODELL -J ~
SUMMIT .~~
CULTUS, L. CULTU S
CHARLETO N
DAVI S
CRESCEN T
Figure 1 . Study Area, Oregon Cascade Lakes .
.41
2
RESEARCH PROCEDURE S
Sampling Methodolog y
Water samples were collected and stored in one-liter linear polyethylene
sample bottles . These bottles were acid washed with nitric acid an d
copiously rinsed three times with distilled water and twice with double distilled deionized water . Samples were placed on ice after collection an d
were stored at 4 0 C upon returning to the laboratory . All samples wer e
filtered through 0 .45 um millipore filters immediately upon returning to th e
laboratory and prior to performing any analyses . Special care was taken i n
the laboratory to avoid contamination of water samples while performin g
analyses . Glassware and plasticware were acid washed and copiously rinse d
several times, first with distilled water and then with double-distille d
deionized water .
Of the 63 lakes sampled in this study, 53 lakes were grab-sampled on e
time each from shore . Eight of the remaining ten lakes were sampled thre e
times between July and October 1982 to investigate temporal fluctuations i n
their water chemistry . Grab samples were taken from shore on three of thes e
lakes :- Betty, Lucky and Summit (Mt . Hood National Forest) . The fiv e
remaining temporally sampled lakes, Waldo, Summit (Deschutes Nationa l
Forest), Bull Run, Lost andGjallie, were sampled by boat at various depth s
within their water columns 'to Study spatial variations in water chemistry .
Temperature, dissolved oxygen and light intensity profiles were also obtaine d
for these lakes . Finally, the remaining two lakes (Blue and Elk) wer e
sampled by boat one time during the summer at various locations within thei r
water columns .
Water samples from the 56 grab-sampled lakes were collected by holding a m
open sample bottle approximately 0 .3 m below the water surface adjacent t o
the shoreline . Sample bottles were rinsed with lake water approximately 4 t o
5 times before the final water sample was collected . Special care was taken
to avoid sampling lakes im littoral areas where physical characteristic s
differed from the general shoreline zone of the lake (i .e ., areas of inflow ,
swampy areas of an otherwise non-swampy lake, or areas of obvious huma n
impact) . Temperature and in-situ pH data were also collected at the time o f
sample collection .
For the five lakes sampled by boat at various depths, the water sample s
were collected with a 2-liter water sampler . Sample bottles were rinsed 3 t o
4 times with water from the sampler before the sample bottle was filled wit h
the final water sample . A small amount of the water from the sampler was .
placed in a rinsed 125 ml plastic bottle and the temperature and "in-situ "
pH were immediately taken and recorded .
3
It should be noted that the possibility of spatial differences in wate r
chemistry exists in lakes that were grab-sampled from shore . Ideally, th e
best possible situation would be to collect samples from the center of eac h
lake 1 to 2 meters below the water surface . Such a sampling procedure weul d
be both time-consuming and impractical for lakes without automobile amass .
Most of the lakes that were shore sampled, however, were small and/er too
shallow to be strongly stratified . Hence, it would be expected that thes e
lakes would have relatively homogeneous water chemistry, as they could b e
assumed to be completely mixed . in the larger lakes that were temperally an d
spatially sampled, there was little or no variation in the data from th e
various water'samples . Larson and Donaldson (1970) also reported a
remarkable lack of spatial variation in water chemistry for Waldo Lake ,
Oregon's second largest lake . This lack of spatial variation in wate r
chemistry was also reflected in the data collected In this study ; our dat a
and that by Larson, and Donaldson indicate that the water chemistry of shor e
samples is generally representative of the water chemistry of the entir e
lake .
Analytical Technique s
All water samples collected were analyzed for laboratory-equilibrated pH ,
conductivity, alkalinity, metals (calcium, magnesium, potassium, s ium .) ,
dissolved silica, chloride and sulfate . Analyses for alwminum ; tota l
dissolved organic carbon and fluoride were also performed on some samples.
In-situ pH data were collected at the sample site .
In-situ pH (Field pH) :
Field pH measurements were made with an Orion 211 digital pH mete r
equipped with an Orion 91-06 combination gel-filled electrode . This pH mete r
and electrode system is capable of being read to hundredths of a pH unit wit h
resolution of 0 .005 pH units (Orion, 1981) . The pH meter was standardized i n
the field at pH = 7 and the slope calibrated at pH = 4 in the lab . Specia l
care was taken to calibrate the meter to the exact pH of the buffer at th e
given buffer temperature, as buffer pH is a function of temperature . For
lakes that were shore-sampled, field pH (or in-situ pH) was taken by holdin g
the probe in the lake with the sensing bulb approximately 6 cm below th e
water surface in deep enough water such that the lake bottom was at least 5
cm below the bottom of the probe . For lakes that were sampled by boat, fiel d
pH data were collected by placing some of the sample in a rinsed 125 m l
narrow mouth plastic bottle immediately after collection and recording the p H
of the sample in the bottle, as described earlier . In both cases, field p H
values were recorded only after the pH meter was stable for at least on e
minute . Equilibration time was typically 3 to 10 minutes .
Laboratory-Equilibrated pH (Lab pH) :
Laboratory pH measurements were made with an Orion 601A digital pH mete r
equipped with a Ross 81-02 glass combination electrode . This pH meter i s
4
capable of being read to the nearest hundredth of a pH unit with a relativ e
accuracy of 0 .01 pH units (Orion, 1977A) . The pH meter was calibrated a t
pH = 7 and the slope calibrated at pH = 4 immediately prior to use . Spe€Ua t
care was taken to calibrate the meter to the exact pH of the buffer at th e
given buffer temperature . To measure lab pH, approximately 100 ml of th e
water sample was placed in a 150 ml beaker and stirred using a magneti c
stirrer . An insulating pad was placed between the beaker and stirrin g
mechanism to minimize heat transfer to the sample from the stirrer . Lab pH
values were recorded only after the pH was stable for at least 2 to 3
minutes . Equilibration time was typically 30 to 90 minutes . This lon g
equilibration time probably results from pH change induce d, by equilibratio n
of the water sample with atmospheric carbon dioxide in the laboratory .
Conductivity :
Conductivity measurements were performed using a Labline Lectro-mhe-mete r
Model MC-1 Mark IV cell-type conductivity meter . Conductivity measurement s
were performed within 24 hours after returning from the field .
Conductivities were temperature corrected so that the data reflec t
conductivity in umhos/cm at 25 0 C . Temperature corrections were made using an
averaged Linear correction based on conductivity analyses performed a t
various temperatures on two water samples--an extremely dilute sample ( 3
umho/cm) and a moderately dilute sample (15 umho/cm) .
Alkalinity (Acid Neutralizing Capacity) :
Alkalinity, or acid neutralizing capacity, was determine d
potentiometrically by titrating a 50 ml water sample with 0 .05 N HCI using a
10-100 ul adjustable micro-pipettor . Samples were stirred with a magneti c
stirrer apparatus during the titration . The Gran technique was used for
titration end point identification (Gran, 1952 ; Stumm and Morgan, 1981) .
Approximately 5 to 10 incremental points of volume-of-acid-added vs . pH wer e
linearly regressed using the Gran function . The regressed points all had p H
values of 4 to 5 . Analyses were performed in duplicate (or more) and nearl y
always agreed within 5% . Standards with alkalinities of 100 meq/l wer e
titrated frequently for quality assurance . These standards always agree d
within 5% and usually within 2% . Alkalinity analyses were performed within 1
to 5 days of sample collection .
Metals :
Analyses for sodium, potassium, magnesium and calcium were performe d
using a Perkin-Elmer Model 360 flame atomic absorption spectroph ..tometer .
Procedural techniques used were in accordance with Perkin Elmer, (1982) an d
Standard Methods (1980) . To eliminate inferences associated with th e
ionization of alkaline-earth metals, 2 .5 percent lanthanum in 50%
concentrated hydrochloric acid was added to the samples prior to analyses fo r
calcium and magnesium, in accordance with EPA (1974) . All samples had bee n
filtered immediately after returning from the field ; hence, the metals dat a
reflect dissolved concentrations . Detection limits for calcium, magnesium ,
sodium and potassium were all approximately 0 .03 mg/I . The accuracy of th e
calcium data was verified by EDTA tttrations on selected samples i n
accordance with Standard Methods (1980) .
5
Dissolved Silica :
Dissolved silica analyses were performed using the keterepoiy-blue metho d
(Standard Methods, 1980) . A Bausch and Lomb Spectronic 80 spectr®photernete r
was used for this colorimetric analysis . The detection limit of this meihed
was 0 .02 mg/I SI02 .
Chloride :
Chloride Ion concentrations were determined by titration with mercuri c
nitrate using diphenylcarbazone to indicate the titration endpoint and xylem e
cyanol FF as a pH Indicator (Standard Methods, 1980) . The 0 .0141 N mercuri c
nitrate was added with a 10-100 ul adjustable pipettor . The detection limi t
of this method was 0 .05 mg/I Cl .
Two other analytical methods for chloride were initially tried and foO .d
to be unsuitable . An Orion chloride electrode with a double junction
reference electrode was initially tried . This method of analysis was found t o
be unsuitable for several reasons . There was an extremely long response tim e
(>30 minutes) for each sample analyzed . Next, the lower limit of the linea r
or Nernstian range for the electrode was 1 .75 mg/I CI . This concentration wa s
significantly higher than the typical chloride concentrations eneoentered i n
this study . Although using sufficient standards enabled the electrode to be
used to measure concentrations below the Nernstian range, the procedwre wa s
very time-consuming, as large numbers of standards were required . I n
addition, when measuring chloride in a particular sample, there was a ver y
significant carryover of chloride from the previous sample . Thus, th e
chloride ion electrode was not used for the above reasons . A p..oten .tiometri c
titration for chloride using silver nitrate could have been used, but thi s
method was also very time-consuming and impractical for processing larg e
numbers of samples .
The other analytical method that was found to be unsuitabLe was th e
argentometric method (Standard Methods, 1980) . In this method, potassiu m
chromate Indicates the end point of a silver nitrate titration of the sample .
During the titration, silver chloride is preferentially precipitated befor e
the end point, which is indicated by the formation of red silver chromate .
This end point was, however, difficult to detect consistently, as the colo r
change was very gradual . Hence, this method was also found to be unsuitable .
Sulfate :
Sulfate analyses were performed using a modification of the turb i d imetr i c
method (Standard Methods, 1980) . A Hach 2100-A turbidimeter was used in thi s
analysis . The tu .r- b i d i.metr i c method involves adding barium chloride crystal s
to the sample, resulting in the precipitation of less-soluble barium sulfate .
A conditioning reagant containing glycerol, isopropyl alcoh®l, hydrochlori c
acid and sodium chloride is also added to assure formation of uniform-size d
barium sulfate crystals . This reagant, however, adds a background turbidit y
which is often much greater than the turbidity of the barium sulfat e
suspension, especially in a dilute water sample . Hence, at low
6
i
concentrations, the precision of the data collected using this method is poor .
In addition, the detection limit is also quite high, at 1 .0 mg/I SO4, becaus e
of the turbidity of the conditioning reagent .
Therefore, to increase the precision of this method and lower th e
detection limit, the con .dItioning reagant was not used . This change lowere d
the detection limit to <0 .1 mg/I S04 and greatly increased reproducibility .
Although the standard curve, after making this change, was more exponentia l
then linear, enough standards were used to bracket the range of sulfat e
concentrations measured . This non-linearity is probably due to the formatio n
of larger barium sulfate crystals at higher sulfate concentrations .
Aluminum :
Aluminum concentrations were determined colormetrically using a metho d
developed by Barnes (1975) . After filtration through a 0 .45 um milliper e
filter, 8-hydroxyquinoline was added to a 40 ml. aliquot of the water sample ,
forming a complex with the dissolved aluminum . This complex was immediatel y
extracted with methyl-iso-butyl-ketone . The reliable detection limit of thi s
method was 5 ug/l Al . Typical aluminum concentrations encountered in thi s
study ranged from <5 to 25 ug/l Al .
Total Organic Carbon :
Total dissolved .argaw.io carbon concentrations were determined by measurin g
the C02-infrared absorbance of the wet-oxidized dissolved organic carbon usin g
an Oceanography International Carbon Analyzer . Samples were prepared an d
organic carbon oxidized in accordance with the Oceanography Internationa l
Carbon Analyzer Instruction Manual (1974) within 1 to 3 days after sampl e
collection . Since samples were filtered through 0 .45 um mlliip .ore filte r
prior to oxidation of organic carbon, the total organic eeneen.trat .i .on s
reported are dissolved concentrations . The detection limit of this method wa s
0 .1 mg/l ; however, the reproducibility was about 75% of the mea n
concentration . Hence, total organic carbon concentrations reported her e
should be considered only as rough indicators of carbon concentrations .
Typical total organic carbon concentrations found in this study were ‹x•0 .1 to
1 mg/l TOC .
Fluoride :
Fluoride analyses were performed using an Orion 96-09 Fluoride'Oembinatie n
Electrode with an Orion 801A lonanalyzer . This meter is capable of being read
to tenths of a millivolt . The analytical procedure used was in accordance
with Orion (1977B) . The lower limit of the Nernstian or linear range for th+ e
electrode is 200 ug/l F . In this study,, the lower end of the linear range wa s
found to be 50 tog/I . The use of sufficient standards with concentration s
below the linear limit allowed fluoride concentrations a& low as 1 .0 ug/l to
be measured . At these low fluoride concentrations, equilibration time for th e
electrode was 10 to . 20 minutes . Typical fluoride concentrations encountere d
in this study were 1 to 10 ug/l F .
TS (P, ANALYSES
The detailed f i e l d and I aboredry data are presented I n
B . This chapter gives a general explanation of the data .
Append ices A
a'm.d
in addition to the analyses performed to achieve the primary objective s
of this study, additional laboratory experiments were performed t o
investigate (a) differences in analytical procedures used amon g
acid-precipitation researchers and (b) inconsistencies in comparin g
historical alkalinity data to recent data collected using Gran titration• t o
determine the alkalinity titration end point . The results of thes e
experiments are summarized in Appendix C .
Over■4ew o!Result s
The mean, median, standard deviation, and maximum and minimum values for
the water quality parameters monitored in this study are summarized in Tabl e
1 . The lakes sampled in this study can be characterized as poorly baf, feced
and having an extremely dilute ionic composition . The average cation/anio n
ratio (equivalent basis) was 0 .99, with s = 0 .15 . Calcium constituted 36% o f
the cations (equivalent basis), with sodium, maganesium and potassiu m
representing the remaining 31, 26 and 7 percent, respectively . Bicarbonate
constituted 82% of the anions, with chloride and sulfate representing th e
remaining 15 and 3 percent, respectively . Figure 2 is a bar graph showin g
the average concentration of major cations and anions for the 63 lake s
monitored in this study . Frequency distributions for alkalinity, in-sit u
(field) pH, and laboratory-equilibrated pH are shown in Figures 3 ant 4 . Th e
alkalinity frequency distribution (Figure 3) shows that the greatest numbe r
of lakes had alkalinities less than 25 ueq/I, with the few less-dilute Lake s
inflating the overall average alkalinity .
Cation concentrations and alkalinity were linearly correlated wit h
conductivity ; an exponential relationship was found to . exist between thes e
parameters and pH . Table 2 shows these correlations . The identifie d
equations are presented in following text discussion . The lack of treads
between chloride and sulfate as functions of conductivJty and pH may possibl y
indicate that these ions are not released in significant concentrations b y
mineral dissolution reactions (as are cations and alkalinity), but ar e
present as the result of deposition of anthropoge.mic emissions and/or se a
spray .
Detailed Results,
The mean, standard deviation, and maximum and minimum values (no t
sea-salt corrected) for the water chemistry parameters monitored in thi s
study are given in the following paragraphs .
Also presented are the sea-sal t
corrected correlations of each parameter with conductivity (COND) ,
alkalinity (ALK), and pH (based on concentrations in ueq/l) . A•shor t
discussion of observations with respect to each parameter is als o. presented .
9
1
Table 1 .
Data Summary for Oregon Cascade Lake s
Parameter
Lab pH
Field pH
COND, umhos/cm
Alkalinity, ueq/l
Ca, mg/I
Mg, mg/I
Na, mg/l
K, mg/l
S0 4 , mg/I
Cl, mg/I
-log, Pco 2 (field)
-log, Pco(lab)
2
F, ug/I
Al, ug/I
TOC, mg/I
SiO2, mg/l
AVG'Ecat ., ueq/l
AVG
ueq/I
Ecat ./EAn .
an.,
Number of
Lakes
Mean
63
63
63
63
63
63
63
63
59
60
63
63
20
8
6
62
61
59
59
6 .96
6 .93
Standard
Maxifnmm
61[njmmm
Deviation
0 .59
0 .80
13 .95
135 .80
17 .03
137 .60
1 .16
0 .51
1 .13
1 .02
0 .49
0 .94
0 .33
0 .28
0 .62
0 .48
0 .47
0 .28
0 .83
3 .35
3 .36
0 .15
18 .10
16 .00
---
11 .80
16 .00
< .10
7 .03
7 .27
168 .30
136 .40
172 .90
0 .99
142 .60
0 .15
10
7 .91
9 .51
57 .68
526 .70
3 .75
2 .00
3 .90
1 .27
2 ..1?
t.
2 .43
3 .03
82 .30
56 .00
2 .80
26 .56
539 .40
578 .80
1 .30
5 .83
5 .47
2 .58
1 .0 5
0 .0 9
0 .0 3
0 .1 2
0 .0 4
0 .0 3
0 .3 0
5 .3 3
3 .99
<1 .0 0
<1 .0 0
< .1 0
0 .0 5
12 .7 0
18 .0 0
0 .39
/E .
+
0
IV
)
U
SDV 1 JO e98WnN
n
r
11112MIMMEMEM
12MINEIMEMERIMBSOME
11IMIMERM
11MMEENIMMIM
so
m
N
U)
' -i
.a
sE>Iv -l
dO
U)
4-
m U1
N
a
o
JS8Wf1 N
•r
s-
4-)
N
m
0
G
>)
U
C
.-1
a)
a))
LI_
0l
0
0
W
H
IL
a)
Table 2 .
Correlations of Major Cations and Anions with Conductivit y
and pH, and Selected Cross-Correlation s
Equation a
Equation
No .
4
7
10
14
19
22
24
26
28
5
8
11
15
20
23
25
27
29
6
9
12
13
16
21
Correlation
Coefficient, r 2
ALK = -25 .65 + 9 .56 COND
Ca = -1 .26 + 3 .51 COND
Mg = -7 .65 + 2 .66 COND
Na = -9 .15 + 2 .38 COND
K=
4 .97 + 0 .41 COND
SCAT = -14 .41 + 9 .00 COND
S04 =
4 .50 + 0 .08 COND
CI =
1 .57 + 2 .12 COND
SI0 2 = -2 .69 + 6 .85 COND
ALK =
Ca =
Mg =
Na =
K=
ECAT =
S04 =
CI =
SiO2 =
COND =
ALK =
ALK =
ALK =
ALK =
ALK =
ALK =
0 .97
0 .88
0 .90
0 .7 6
0 .48
0 .96
0 .0 1
0 .3 4
0 .6 3
6 .96 (1077 ) exp (2 .63 pH)
1 .13 (10-4 )
1 .21 (1 07 )
4 .63 (10 6 )
6 .59 (10)
1 .11 (10)
5 .54 (1 0 1 )
3 .46 (1 0- ')
1 .06 (1 0 5 )
4 .95 (107 ')
-8 .66
-4 .33
7 .05
-5 .69
+
+
+
+
27 .19 +
0 .84 +
exp (1 .81
exp (2 .05
exp (2 .16
exp (1 .03
exp (1 .93
exp (0 .29
exp (4 .26
exp (2 .21
exp (1 .45
1 .05
pH)
pH)
pH)
pH)
pH)
pH)
pH)
pH)
pH)
SCAT
2 .42
3 .32
1 .49
Ca
Mg
(Ca + Mg)
3 .21
Na
11 .38 K
0 .9 4
0 .83
0 .7 1
0 .7 8
0 .44
0 .86
0 .0 1
0 .21
0 .72
0 .84
0 .99
0 .87
0 .9 2
0 .95
0 .8 2
0 .49
a Units for all parameters are ueq/l, except COND (umho/cm) .
All parameters are sea-salt corrected except Cl .
14
Conductivity :
The average conductivity in the 63 Lakes studied was 17 .03 umhos/cm, wit h
a high of 57 .7 umhos/cm, and a low of 2 .58 umhos/cm . The standard deviation
was 13 .95 umhos/cm . The large standard deviation reflects the variability i n
diluteness of the lakes sampled, while the extremely low mean conductivity i s
indicative of the generally dilute water chemistry of Oregon's Cascade lakes .
Strong linear correlations were found between conductivity and calcium ,
magnesium, sodium, potassium, silica and alkalinity (See following sections) .
Such correlations would be expected, as conductivity is a measure of th e
overall ionic composition of a water body . Conductivity increase d
exponentially with both in-situ pH and laboratory pH . In contrast, Driscol l
(1980) reported that conductivit[es of acidified Adirondock surface wate r
increased with decreasing pH, reflecting the increased conductance of th e
hydrogen ion at low pH values . When Driscoll's conductivities were correcte d
for hydrogen ion conductance, however, conductivity then increased wit h
increasing pH . Thus, the conductivity-pH relation for lakes of a give n
region could be used as an indicator of anthropogenic acidification .
The following linear regression between measured conductivity an d
calculated ionic strength was obtained :
I = 1 .28 (10 -5 ) COND
(n = 59, r 2 = 0 .99)
(1 )
Snoeyink and Jenkins (1980) report a somewhat similar expression :
I = 1 .6 (10 -5 ) COND . When activity coefficients are calculated using th e
average conductivity for the 63 lakes and the Debye-Huckel limiting law ,
coeffici•ekts of 0 .98 and 0 .93 were obtained for monovalent and divalent ions ,
respectively . Hence, the errors incurred by using concentrations i n
calculations, instead of activities, are probably insignificant and withi n
the analytical uncertainty of the data collected .
pH :
The average in-situ pH (field pH) of the 63 lakes was 6 .93, with a hig h
of 9 .51 and a low of 5 .47 . The standard deviation was 0 .80 . The averag e
laboratory-equilibrated pH was 6 .96, with a high of 7 .91 and a low of 5 .83 .
The standard deviation was 0 .59 .
The greater standard deviation in in-situ pH reflects the influences o f
biological activity, wave action and temperature fluctuations on dissolve d
carbon dioxide concentration . These influences were generally not present i n
the laboratory, as biological activity was minimized with filtering th e
sample and refrigerating it, and temperature fluctuations did . not exist .
When laboratory pH is regressed as a function of field pH, the followin g
expression is obtained :
Lab pH = 0 .646 + 0 .91(Field pH) (n = 63, r 2 = 0 .82)
15
(2 )
When this regression is forced through the origin, the following expressio n
is obtained :
Lab pH = 1 .003(Field pH)
(3 )
Thus, there was little deviation from a 1 :1 relationship between these
parameters .
Alkalinity :
The average alkalinity for the 63 lakes was 13 .7 .6 ueq/l, with a high o f
526 .7 ueq/l and a low of 1 . .1 ueq/l . The med i ai alkalinity was -83 .9 ueq/l .
The standard deviation was 135 .8 ueq/l . Figure 3 showed the distribution o f
alkalinities among the 63 lakes studied . There -was a,Iimntar relation betwee n
alkalinity and conductivity and an exponentl . al relation between alkalinit y
and pH . A strong linear correlation was found betileen alkalinity and tota l
cation concentration (equivalent basis) . These regressions are as follows :
ALK = -25 .65 + 9 .56 COND
(n =63, r 2 = 0 .97)
(4 )
ALK = 6 .96 (10 7) exp (2 .63 pH)
(n = 63, r 2 = .94)
(5 )
ALK = -8 .66 + 1 .05 SCAT
(n = 61, r 2 = 0 .99)
(6)
Figure 5 shows the relationship between alkalinity and lab pH . Th e
relationship between alkalinity and pH for a solution saturated with carbo n
dioxide is also shown . It is thus evident that the lakes sampled wer e
generally supersaturated with carbon dioxide when lab pH was determined o r
that additional weak acid buffering was present . This situation is discussed
in detail in a following section titled "Predominant Buffer Systems" (it i s
concluded in that section that the lakes were s .npers{turated and additiona l
weak acid buffering was negligible) .
Calcium :
The average calcium concentration in the 63 lakes sampled was 1 .16 mg/I ,
with a high of 3 .75 mg/I and a low of 0 .09 mg/I . The standard deviation wa s
1 .02 mg/I . As mentioned earlier, strong linear correlations were foun d
between calcium and both alkalinity and COND, while an exponentia l
correlation was found between calcium and pH . These expressions are a s
follows :
Ca = -1 .26 + 3 .51 COND
Ca =
(n = 63, r 2 = 0 .88)
1 .13 (10 -4 ) exp (1 .81 pH)
ALK = -4 .33 + 2 .42 Ca
(n = 63, r 2 = 0 .83)
(n = 63, r 2 = 0 .87)
16
(7 )
(8 )
(9 )
U,N
r
a
4)
u)
3
4-3
N
(7/Sn)
Al I N 11V>I 1 V
17
A comparison of calcium-alkalinity relationships for lakes in differen t
geographical areas is discussed in detail in a following section title d
"Applicability of Acidification Sensitivity Models" . The lakes sampled i n
this study had a significantly greater alkalinity-to-calcium ratio than mos t
other dilute, non-acidified lakes (see Table 3) . This high ratio is probabl y
due to large amounts of alkalinity associated with magnesium- , potassium- ,
and sodium-bearing minerals .
Magnesium :
The average magnesium concentration for the 63 lakes . was 0 .51 mg/I, wit h
a high of 2 .00 mg/I and a low of 0 .03 mg/I . The standard deviation was 0 .4 9
mg/l . As mentioned earlier, strong linear correlations between magnesium an d
both conductivity and alkalinity were found ; magnesium and pH wer e
exponentially related . These expressions are as follows :
Mg = -7 .65 + 2 .66 COND
(n =63, r 2 = 0 .90)
Mg = 1 .21 (10 5 ) exp (2 .05 pH) (n = 63, r 2 = 0 .71)
ALK = 7 .05 + 3 .32 Mg
(n = 63, r 2 =0 .92)
(10 )
(11 )
(12 )
The regression for the sum of magnesium and calcium versus alkalinity i s
as follows :
ALK = -5 .69 + 1 .49 (Ca + Mg)
(n = 63, r2 =0 .95)
(13 )
Thus, significant amounts of alkalinity must be associated with dissolutio n
of sodium- and potassium-bearing minerals, as the ratio of alkalinity t o
calcium-plus-magnesium is still significantly greater than unity .
Sodium :
The average sodium concentration for the 63 lakes was 1 .13 mg/i, with a
high of 3 .90 mg/I and a low of 0 .12 mg/l . The standard deviation was 0 .9 4
mg/I . Again, strong linear correlations. between sodium and both alkkal,init y
and conductivity were-found ; sodium and pH were exponentially related . Thes e
regressions are shown below '
Na = -9 .15 + 2 .38 COND
(n = 63,
r 2 =0 .7W,),
Na = 4 .63 (10 -6 ) exp (2 .16 pH) (n = 63, r 2 = 0 .78)
ALK = 27 .19 + 3 .21 Na
(n = 63, r 2 = 0 .82)
18
(14 )
(15 )
(16 )
The regression between sodium and chloride (equivalent basis) was a s
follows :
(n = 58, r 2 = 0 .26)
Na = 36 .9 + 0 .62 CI
(17 )
or, forced through the origin :
(18 )
Na = 1 .64 CI
Hence, if chloride is assumed to be entirely the re wIt e" sea spray
deposition, a varying but significant amount of sodium must be of watershe d
origin . It would also seem that there is a significant amount of alkalinit y
associated with this sodium of watershed origin .
Potassium :
The average potassium concentration was 0 .47 mg/I, with a high of 1 .27
A
mg/I and a low of 0 .04 mg/I . The standard deviation was 0 .33 mg/I .
somewhat weaker correlation was found between potassium and both alkalinit y
and conductivity ; potassium and pH were also more weakly related . Thes e
regressions are as follows :
(n = 63, r 2 =0 ..48) '
(19 )
K = 6 .59 ' (10 -3 ) exp (1 .03 pH) (n = 61, r 2 - = . 0 .44)•
(20 )
K=4 .97+0 .41'COND .
(n = 61, r 2 = 0 .49)
ALK = 0 .84 + 1 .1 ..38-K
(21 )
There was a greater variation in potassium concentrations compared to th e
other metals . There were also greater temporal and spatial potassiu m
variations in those lakes so sampled . The reason for this variability is no t
known .
Summary of Metal Results :
The regression between sea-spray-corrected total cation' concentration
and alkalinity was given in equation (6) as follows :
ALK = -8 .66 + 1 .05 SCAT
(6 )
This relationship indicates that the bicarbonate ion (approximately equal to
alkalinity) is the major anion associated with the major cations . Potassium ,
sodium, calcium and magnesium bearing minerals must be supplying equivalen t
amounts of alkalinity in dissolution reactions .
The regressions of total cations with conductivity and pH are as follows :
CAT = -14 .41 + 9 .00 COND
CAT =
(n =63, r 2 = 0 .96)
1 .11 (10 -4 ) exp (1 .93 pH) (n= 63, r 2 = 0 .86)
19
(22 )
(23 )
On an equivalent basis, the average calcium :sodium :magnesium :
potassium ratio was 36 :31 :26 :7 for the 63 lakes sampled . For three acidifie d
lakes in the Adirondack Mountains of New York State, Driscoll (1980) reporte d
an average Ca :Na :Mg :K ratio of 59 :16 :18 :7 . The average total cation
concentration for the 63 Oregon Cascade lakes sampled was 168 ueq/l . For th e
three acidified lakes studied by Driscoll, the average total catio n
concentration was 207 ueq/l . Hence, Oregon's Cascade lakes are somewhat mor e
dilute but ionic strengths are of the same order of magnitude .
Aluminum and hydrogen ion concentrations constitute approximately 18 an d
5%, respectively, of the total cations in the acidified Adirondack lake s
studied by Driscoll . These parameters have a negligible effect on the tota l
cation concentrations of the lakes sampled in this study .
Sulfate :
The average sulfate concentration for the 63 lakes was 0 .28 mg/I, with a
high of 2 .17 mg/I and a low of 0 .03 mg/I . The standard deviation was 0 .2 8
mg/i . The regressions between sulfate and conductivity and pH are a s
follows :
SO4 = 4 .50 + 0 .079 COND
(n = 59, r ? = 0 .01)
(24 )
SO 4 = 0 .55 exp (0 .29 pH)
(n = 59, r 2 = 0 .01)
(25 )
For the Oregon Cascade lakes sampled in this study, sulfate averaged 3 . 5
percent of the average total ions while bicarbonate averaged approximatel y
82% . Driscoll (1980) reported an average sulfate concentration of 6 .2 mg/ I
for three dilute acidified lakes in the Adirondack Mountains . In dilute
acidified lakes, sulfate replacep bicarbonate as the major anion . Wright an d
Gjessing (1976) report that aqueous sulfate generally comes fro m
anthropogenic sources and sea spray . The extremely low sulfate
concentrations in the 63 lakes studied by us indicates that anthropogeni c
sources of sulfate upwind of the Oregon Cascades are not present or are no t
influencing the lakes studied .
Chloride :
The average chloride concentration of the Oregon Cascade lakes sample d
was 0 .83 mg/I, with a high of 4 .10 mg/I and a low of 0 .30 mg/I . The standar d
deviation was 0 .62 mg/I . Both conductivity and pH are as follows (no t
sea-salt corrected) :
CI = 1 .57 + 2 .12 COND
(n = 63, r 2 = 0 .34)
(26 )
Cl = 3 .46 (10 -5 ) exp (4 .26 pH)
(n = 63, r2 = 0 .21)
(27)
These poor correlations may indicate that sources of chloride from withi n
the watershed are negligible, and chloride is generally the result o f
deposition of either sea spray or anthropogenic emissions . Sea spray was
reported as the dominant source of dissolved chloride by other investigator s
(Kramer and Tessier, 1982 ; Wright and Gjessing, 1976 ; and Henricksen, 1980) .
Chloride averaged 15% of the average total anions in the 63 lakes sampled .
20
Fluoride :
Total fluoride analyses were performed on samples from the eight lake s
that were temporally and spatially monitored and on an additional 12 lake s
that were grabbed sampled . Thus, average fluoride concentrations based upo n
this non-statistically selected subset may not be representative of th e
entire 63 lake sample size . With due caution, then, the average tota l
fluoride concentration was 11 .8 ug/l, with a high of 82 .3 ug/l and a low o f
<1 ug/l . The spatial and temporal variations in fluoride were very minima l
for the eight lakes from which multiple samples were collected .
Aluminum : Aluminum analyses were performed'on•samples from the 8 lakes that wer e
temporally and spatially monitored . The average aluminum concentration wa s
16 ug/l, the high was 56 ug/l and the low was less than 1 ug/l . The standar d
deviation was 16 ug/l . Nearly all of the samples analyzed had aluminu m
concentrations less than 25 ug/l . These concentrations are typical of thos e
reported by Wright and GJessing (1976) and other non-acidified dilute lakes .
Driscoll (1980) reported an average monomeric aluminum concentration of 33 2
ug/l for three acidified Adirondack lakes . The average pH of these lakes wa s
4 .96 . It is well known that aluminum concentrations become greatly elevate d
as lake pH decreases .
Total Organic Carbon :
Total organic carbon analyses were performed on samples from six lakes i n
this study . Total organic carbon was below the detection limit ( 0 .1 mg/I )
for four of these lakes .
Si I ica :
The average dissolved silica concentration for the 63 lakes sampled wa s
7 .03 mg/I as SiO2 , with a high of 26 .6 mg/I and a low of 0 .05 mg/l . Th e
standard deviation was 7 .27 mg/I . Good linear correlations were foun d
between silica and both conductivity and alkalinity ; an exponentia l
correlation between silica and pH was also found . These regressions are a s
follows :
SiO = -2 .69 + 6 .85 COND
(n = 62, r 2 = 0 .63)
Si O2 =
1 .06 (1 0 -5 ) exp (2 .21
Si 02 =
8 .63 + 0 .64 ALK
pH)
(n = 62, r 2 = 0 .72)
(n = 62, r 2 = 0 .95)
21
(28 )
(29 )
(30)
Driscoll (1980) reported significant seasonal fluctuations in silica fo r
three acidified lakes . He attributed low summer concentrations of silica t o
uptake by diatoms and high winter concentrations to decomposition of silic a
containing frustules of diatoms . He stated that although silica is generall y
used as an Indicator of the extemt of chemical weathering, it should not b e
used as such because of the biological interactions in silica cycling, Ther e
did not appear to be any temporal fluctuations in silica for the three-ment h
sampling period . It is possible that this sampling period . was too short to
reveal such trends .
Correlation of silica versus alkalinity was very similar to correlatio n
of basic cations versus alkalinity for the 63 lakes sampled . Hence, it i s
possible that weathering processes supplying silica to these lakes
concomitantly supply alkalinity and basic cations .
22
DISCUSSION-OF RESULTS
Regional . Temporal, and Spatial Trends in Water Chemistr y
r
There did not seem to be any overall trends between lake water, chemistr y
and lake location or elevation . Temporal and spatial trends in wate r
chemistry were remarkably minimal in the eight lakes monitored for suc h
variations . Significant fluctuations in some water chemistry parameters, such "
as alkalinity, existed in the three smallest lakes that were temporall y
monitored, but these fluctuations did not exhibit any overall trends . I n
acidified lakes with short residence times, springtime alkalinities ar e
generally depressed due to the slug input of acidified snowmelt ; alkalinitie s
then increase throughout the summer (Driscoll et al ., 1980) . Fluctuations i n
water chemistry with time were insignificant in the remaining five lakes tha t
were monitored temporally . These five lakes had water residence times muc h
greater than the three-month sampling period . A longer monitoring period ,
more commensurate with water residence times, might reveal such natura l
temporal trends, if they exist . it is doubtful that there . are' significan t
fluctuations in•seasonal water chemistry for Waldo Lake, which has an averag e
residence time of 30 years (Davis and Larson 1976) . Larson and Donaldso n
(1970) previously reported a lack of spatial variability in water chemistr y
for Waldo Lake . Lost Lake showed a decrease in alkalinity with depth, bu t
pH, cation and conductivity variations with depth were not significant .
Zimmerman and Harvey (1978-79) reported the importance of collecting a
composite water sample in contrast to a grab sample at the lake surface ;
alkalinities decreased substantially with depth in the Ontario lakes the y
studied . The large lakes investigated in this study had no alkalinit y
gradient (except Lost Lake, as discussed above) and the small lakes wer e
generally shallow enough to stratify only weakly, if at all . Thus, a
surface grab sample was generally representative of the lake water chemistr y
as a whole for the lakes sampled in this study .
Predominant Buffer Systems :
The carbonate system, organic aluminum, and weak organic acids all hav e
been reported as significant buffer systems in lakes of igneous geologi c
origin (Driscoll, 1980) . The carbonate system is the dominant buffer at p H
values above about 5 .5 . Aluminum hydrolysis species and weak organic acid s
become dominant buffer systems below this pH (Driscoll, 1980) .
For the 63 lakes sampled in this study, the mean in-situ and lab, p H
values were 6 .93 and 6 .96, respective)-y . These mean pH values, as. well as
the pH range of 5 .83 to 7 .91 for the 63 lakes, are well within the range o f
carbonate-dominated buffering . The average carbon dioxide partial pressure ,
as calculated from laboratory equilibrated pH and alkalinity (Stumm an d
Morgan, 1981), was 437x10 atmospheres . The global average atmospheri c
carbon dioxide partial pressure is 330x10 -6 atmospheres at sea level . Thus ,
the laboratory-equilibrated pH water samples were either supersaturated (b y
an average of 35 percent over equilibrium carbon dioxide) or additional wea k
23
acid buffering was present . The extremely low aluminum and total organi c
carbon concentrations indicate the very minor contribution of aluminu m
hydrolysis species and weak organic acids to the overall acid neutralizin g
capacity of these lakes . Logan et al ., (1982) also reported carbon dioxid e
partial pressures in excess of atmospheric carbon dioxide for 31 lakes of th e
central Washington Cascades . They attribute this supersaturation t o
temperature differences between the lake sampled and the laboratory, wher e
pH's were determined . In this study, pH was found to stabiliz e
asymptotically over long periods of time (generally 1 to 2 hours) . This ma y
indicate the existence of a kinetic limitation on the equilibration of th e
water sample with atmospheric carbon dioxide in the laboratory . Such a
limitation may explain the supersaturated carbon doxide partial pressure s
calculated from laboratory-equilibrated pH and alkalinity .
Figure 6 shows typical titration curves for several lakes with varyin g
alkalinities sampled in this study . A theoretical titration curve for a
system buffered only by carbonates (and water) with an alkalinity of 10 0
ueq/l and an initial pH of 7 .00 is also shown . The lakes with alkalinities
greater than approximately 40 ueq/I have titration curves similar to th e
theoretical curve . Specifically, there are smaller rates of pH change (fro m
acid addition) near both the pKa value for the carbonate system and at low p H
values, where buffering due to water dissociation becomes significant . Thus ,
the shape of these titration curves would seem to further indicate that th e
carbonate buffering system predominates in lakes with alkalinities greate r
than 40 ueq/l . The titration curves for lakes with alkalinites less than 4 0
ueq/l do not conclusively indicate the presence of any buffer systems (excep t
water) to significant concentrations . A logarithmic buffer intensity curv e
did, however, indicate that some buffering beyond that due to water wa s
present at higher pH's even in the most dilute lakes . Therefore, Cascad e
lakes with alkalinities greater than 40 ueq/l seemed to be predominantl y
buffered by carbonates . The pedominant buffer system in lakes wit h
alkalinities lower than 40 ueq/l was difficult to identify . However, th e
neutral pH of these lakes and the low concentrations of both aluminum an d
total organic carbon, collectively, seem to indicate that carbonates were th e
dominant buffer system at very low concentrations .
General Acidification Sens .itjvity Criteri a
Many approaches- have . been presented in the literature in assessing th e
sensitivity of water bodies to acidic inputs . When these models are applie d
to Oregon's Cascade lakes, they generally indicate that these lakes ar e
extremely sensitive to acidic inputs but have not been influenced by suc h
inputs .
The basic ionic strength and composition of a water body give a roug h
indication of Its sensitivity to acidic inputs (Driscoll, 1980) . For th e
lakes sampled in this study, alkalinity is significantly correlated wit h
total cation concentration, as seen in equation 20 of Table 2 .
24
250
n
1
# LAKE (ALKALINITY>
1 LUCKY (3. 0)
2 SUMMIT C12- 0 )
3 WALDO (17 . 1 )
4 BETTY C33 . 0>
5 BRE I TENBUSH (46 . 3 )
6 MOW I CH (69 . 9 >
7 LOST (83. 9)
8 BULL RUN (124 . 5>
9 T000(169 ..5 )
10 THEORETICAL (100) (CARBONATE SYSTEM )
20
150
0
H
U
s
100
1e
0
50
4 .5
5.5
6
6.5
7
PH
Figure
.' Titration Curves for 'TSelected .Cascade Lakes of Differing Alkalinity .
25
Most dilute, poorly buffered non-acidified lakes are dominated b y
bicarbonates and Ca, Mg, K and Na as the major cations (Wright and Gjessing ,
1976) . In acidified lakes, sulfate replaces bicarbonate as the dominan t
anion and aluminum becomes a significant percentage of the total cations .
The extremely low aluminium and sulfate concentrations in Oregon's Cascad e
lakes (see Table 1), as well as the overall ionic composition, indicate that
these lakes are typical of other dilute, poorly buffered, non-acidifie d
lakes .
According to Hendrey et al ., (1980), lakes with alkalinities less tha n
200 ueq/l are highly sensitive to acidification while only those lakes wit h
alkalinities greater than 500 ueq/I are considered to be non-sensitive .
Thus, 46 (73%) of the 63 Oregon lakes sampled would be considered as highl y
sensitive, and only one lake would be classified as non-sensitive .
The Ontario Ministry of the Environment (1981) proposes that lakes wit h
alkalinities less than 40 ueq/l possess extreme sensitivity and those wit h
alkalinities ranging from 40 to 200 ueq/l have moderate sensitivity .
Twenty-one (33%) of the lakes sampled in this study had alkalinities les s
than 40 ueq/l, 25 lakes (40%) had alkalinities of 40 to 200 ueq/l .
Finally, Zimmerman and Harvey (1978-79) propose that sensitive lakes hav e
pH values of 6 .3-6 .7, conductivities less than 30-40 umhos/cm an d
alkalinities less than 300 ueq/l . Twenty-one (33%) of the 63 Oregon lake s
had pH values less than 6 .7, 59 lakes (94%) had conductivities less than 4 0
umhos/cm and 55 lakes (87%) had alkalinities less than 300 ueq/l . Hence, b y
these proposed criteria, nearly all the lakes samples are sensitive to acidi c
inputs .
Applicability of Acidification Sensitivity Model s
Kramer and Tessier (1982) present a theoretically-derived relationshi p
between total major cation concentrations (sum of calcium, magnesium ,
potassium and sodium) and alkalinity, using charge_balance considerations .
This relationship, also proposed by Burns et al . (1981), as an indicator o f
anthropogenic acidification is as follows :
(31 )
ALK '= EMi - SO4
Where LMi = sum of major cation concentrations on an equivalent basis an d
adjusted for contribution of sea spray (as described by Wright and Gjessing ,
1976) .
In geographical areas where carbonic acid weathering predominates ,
alkalinity and cations are released on an equivalent basis in minera l
dissolution reactions ; hence, the slope of Equation 31 would be close t o
unity (Kramer and Tessier, 1982) .
26
If strong mineral acid weathering was occurring in a particular area, the .
slope of Equation 31 would be significantly less than unity ., indicating th e
release of cations, but without accompanying alkalinity. (Burns et al ., 1981) .
Burns showed that in areas affected by-acid precipitation,' t,i he alkalinity :
total cation ratios were much- less than unity (indicating m+i . sera I aci d
weathering) and ratios in unaffected areas were close to unity (indicatin g
carbonic acid weathering) . For this study, the following relationship wa s
obtained for regression of alkalinity as a function of total major cation s
(sea-spray corrected) :
ALK = 1 .05 Mi - 8 .7
r- = 0 .99
(32 )
See Also (6 )
The closeness of the slope to unity strongly indicates that carbonic aci d
weathering dominates in the Oregon Cascades and that anthropogeni c
acidification of the lakes has not occurred to date .
In the derivation of Equation 31, Kramer and Tessier assume that nitrat e
has a negligible influence on the overall aqueous charge balance . If nitrat e
was present in significant concentrations, the intercept of Equation 31 woul d
be more negative than if only sulfate was present . Hence, although assume d
nitrate to be negligible in their derivation, Equation 31 is still useful i n
areas that receive nitrogen-oxide-emission-induced acid precipitation . Thus ,
the sulfate concentration in Equation 31 can be substituted by the sum o f
sulfate and nitrate (on an equivalent basis and sea salt corrected) .
Although nitrate analyses were not performed in this study, the closenes s
of the intercept term (7 .4) of Equation 32 to the average sulfat e
concentration (5 .8 ueq/l) indicates that nitrate concentrations ar e
negligible . Hence, it is doubtful that significant nitrogen-oxide-derive d
acid precipitation is occurring in western Oregon .
Empirical Relationships :
Several investigators have used alkalinity-calcium relationships (and/o r
alkalinity-calcium plus magnesium relationships) to assess the extent o f
acidification in a particular area (Almer et al, 1978 ; Logan et al ., 1.982 ;
Dr.i.scoll, 1980 ; Henricksen, 1979) . These models are essentially simplifie d
and empirical approaches that can be derived from Kramer and Tessier' s
theoretical charge-balance model . Kramer and Tessier similarly simplifie d
their theoretical charge-balance model as follows :
ALK = b (Mg
ALK = b i
+2
+ Ca +2 ) - SO4
(33 )
Ca +2 - SO4(34
2
)
where b (of b ' ) must be greater than unity to account for the contribution o f
sodium and potassium to the overall charge balance . This model, as well a s
the similar models proposed by Almer, Logan, Driscoll and Henricksen, assume s
that a relatively constant and linear relationship exists between alkalinit y
and calcium (or calcium plus magnesium) for unacidifled lakes, and fo r
acidified lakes previous to acidification . Kramer and Tessier (1982) mentio n
the difficulty in using the simplified relations (Equations 33 and 34) due t o
the variability in b and b° because of varying contributions of sodium- an d
27
potasium-releasing mineral dissolution reactions, even in a particula r
region, to the overall charge balance .
For this study, from Table 2 (Equations 9 and 13), b = 1 .49 (r2 = 0 .95 )
and b ' = 2 .42 (r 2 = 0 .87) . The alkalinity/calcium relationships for severa l
other regions of the world with dilute, poorly-buffered, non-acidified lake s
and one region with acidified lakes are summarized in Table 3 . Th e
comparatively greater alkalinity/calcium slope for Oregon's Cascade lake s
seems to indicate that significant amounts of sodium- and potassium associated alkalinity are present in addition to that supplied by calcium an d
magnesium mineral dissolution reactions . Thus, Oregon lakes could incu r
significant acidic inputs and substantial loss of alkalinity before thei r
alkalinity/calcium ratio even approaches typical alkalinity/calcium ratio s
for dilute non-acidified lakes in other areas, as indicated in Table 3 .
Hence, the use of alkalinity/calcium ratios for inferring the extent o f
acidification in impacted areas could lead to misleading conclusions .
Kramer and Tessier (1982) mention (with caution) that the intercepts o f
Equations 33 and 34 can also be used to indicate sulfate concentration in a
way similar to the more rigorous Equation 31 . The charge balance-derive d
relation (Equation 31) can be more reliably used for this purpose, but al l
the parameters required to use it are not always available . If thi s
hypothesis is applied to the alkalinity/calcium relation shown in Table 3, i t
can be seen that su_Ifate concentrations are minimal in the lakes of thi s
study as well as those in northern Norway, Washington and Ontario . Th e
intercept of the alkalinity/calcium regression for the acidified lakes in Ne w
York's Adirondack Mountains is, however, much more negative, indicating bot h
the higher concentrations of sulfate in these lakes and probabl y
anthropogenic influences on their water chemistry .
Ca-pH Plots :
Henricksen (1979) suggests the use of calcium-pH plots to distinquis h
between non-acidified lakes and lakes that have lost some alkalinity (wit h
accompanying moderate depression in pH) but have not lost all carbonat e
buffering . Boundaries between acidified and non-acidified lake Ca-p H
relations were empirically drawn by Henricksen based on data for acidifie d
lakes in southern Norway and dilute non-acidified lakes of northern Norway .
Figure 7 presents Ca-pH plots for the 63 Cascades Lakes, with Henricksen' s
boundaries superimposed . It is evident that the data for the 63 Orego n
Cascade lakes are all in the non-acidified zone and that they appear to hav e
substantially higher pH values than the dilute, non-acidified lakes of bot h
the Washington Cascades and northern Norway . Hence, Oregon's lakes coul d
experience a moderate drop in pH (and some alkalinity loss), but still appea r
to be umirpacted with respect to Henricksen's plot . Thus, again there seem s
to be substantial contribution to alkalinity by weathering of sodium an d
potassium minerals, resulting in high pH values in lakes with calciu m
concentrations similar to those non-acidified lakes used by Henricksen in hi s
Ca-pH plot . Zimmerman (1982) also indicates that lakes high i n
magnesium-associated alkalinity may make Ca-pH plots inappropriate o r
28
Table 3 . Alkalinity-Calcium Relationships for Lakes From Various Region s
Region
Correlatio n
Coefficient, ,
r2
Equation ].
Sourc e
Oregon Cascades 2
ALK =
-3 .70 + 2 .40 Ca
0 .88
This Study
Central Washingto n
Cascades
ALK = - 5 .77 + 1 .07 Ca
0 .96
Logan et at ., 198 2
North Cascade s
(Washington)
ALK =
0 .98
Logan et al ., 198 2
Northern Norway
ALK = -29 .0
+ 1 .32 Ca
0 .85
Henrtckseny 197 9
Expt'al Lakes ,
Western Ontari o
area
ALK = -32 .0
+ 1 .42 Ca
0 .76
Henricksen, 197 9
ALK = -94 .9 :
4.
Adirondack Lakes ,
New York
.
2 .67 + .995 Ca
0 .94 Ca
Driscoll, 1980
'Units for ALK and Ca are ueq/ l
2 Regression of non-sea-spray corrected concentrations (for comparativ e
purposes) .
9
(1/ ban ) Wn 131V J
30
misleading as indicators of acid+fication . Hence, Ca-pH plots should b e
interpreted carefully, since alkalinity-supplying weathering reactions ma y
differ from one region to another .
Kramer and Tessier (1982) suggest that plots of total catio n
concentration vs . pH may be a better benchmark for comparing lakes o f
different regions . The use Of such plots as a compenative benchmark seems t o
have theoretical Justification, as alkalinity is related•to pH . However, th e
difficulty in comparing pH data among investigators still exists (Driscoll ,
1980) . Carbon dioxide partial pressures vary significantly due t o
photosynthesis-respiration activity, wave action and temperature changes, al l
resulting on pH fluctuations : These variations were minimized in this stud y
by determining pH under consistent, laboratory-equilibrated conditions . Th e
variability in pH data between different investigators has not, however, bee n
resolved . The total cation concentration-pH regression for the 63 lakes o f
this study is shown in Table 2, Equation 23 . Similar regressions for lake s
of other regions are not readily available .
Ca-pH plots, Ca-alkalinity plots, metals-alkalinity plots and metals-p H
plots, when used to predict extent of acidification, aLl implicitly assum e
that cation concentrations do not change as a water body is acidified ..
According to Kramer and Tessier (1982), some investigators found no change i n
calcium concentrations with acidification, while others found increases i n
calcium and other cations . Increased cation concentrations woul d
overestimate either pre-acidification alkalinity or loss of alkalinity fro m
acidification, depending on how these relationships were used . Henrickse n
(1979) hypothesizes that dissolution reactions which increase calcium an d
that other cations would probably also supply an equivalent amount o f
alkalinity . Typical mineral-acid dissolution reactions would not, however ,
release equivalent amounts of cations and alkalinity .
Henricksen (1980) has developed a nomograph which can be used to predic t
lake pH from lake calcium concentration and either precipitation pH or lak e
sulfate concentrations . This nomograph has limited applicability to Oregon' s
Cascade lakes, as lake sulfate concentrations were generally too low to us e
the nomograph . At best, the nomograph indicates that Oregon's Cascades lake s
have not received acidic inputs .
31
CONCLUSION S
Briefly, the following conclusions may be drawn from this study of 6 3
Oregon Cascade lakes :
1.
Oregon's Cascade lakes have an extremely dilute ionic compositio n
relative to typical freshwater lakes ;
2.
Most Oregon Cascade lakes are highly susceptible to aci d
precipitation and could be adversely impacted if aci d
precipitation were to increase ;
3.
Based on chemical composition, Oregon's Cascade lakes sho w
no signs that significant acidic inputs have occurred to date ; an d
4.
Comparison of the data from this study to data for dilut e
non-acidified lakes in other geographical areas indicate s
that natural differences in water chemistry are significant .
Conclusions regarding the extent of acidification based upo n
comparison of fake data from one region to another must b e
made carefully . Oregon lakes could incur significant acidi c
inputs but appear to be unimpacted if certain empiricial an d
comparative models in the literature are used .
33
REFERENCE S
Almer, B ., W . Dickson, E . Ekstrom, E . Hornstrom ; "Sulfur in th e
Environment, Part I I : Ecological Impacts" ; Nr i agu, J .O . Ed . ;
J .O . Wiley and Sons, Inc . ; New York ; 1978 ; p . 271 .
Barnes, R .B . ; "The Determ j.iitt i on of Specific Forms of A I um i raw i n
Natural Water, "Chemical Geology'• ;'V_ . 1 .5 ; 1975 ; p . 177-191 .
Burns, D .A ., J .N . Galloway and G .R . Heradrel ; Ac idifi.cation o f
Surface Waters In Two Areas of'the Eastern United States ,
"Water, Air and Soil . Pelkution" ; V . 16 ; 1981 ; p . 277-285 .
Davis, G .E . and G ..L . Larson ; "Sediment Characteristics and th e
Trophic Status of Four Oregon Lakes" ; Water Resources Researc h
Institute, Oregon State University, Corvallis, Oregon ; Repor t
WRRI-46 ; 1976 .
Dillon, D .T ., D .S . Jeffries, W .A . Schreider and N .D . Yam ; "Some Aspects
of Acidification in Southern Ontario" in Proc . Int . Conf . on Eeol .
Impact of Acid Precip . ; Drablos, D . and A . Tollan, Eds . ; Norway
(SNSF Project) ; 1980 ; p . 212-213 .
Driscoll, C .T . ; "Chemical Characterization of Some Dilute Acidifie d
Lakes and Streams in the Adirondack Region of New York State" ;
Ph .D . Thesis, Cornell University, Ithaca, N .Y .. ; 1980 .
Driscoll, C .T ., J .P . Balcer, J .J . Biscogni and C .L . Schofield ; "Effec t
of Aluminum Speciation on Fish in Dilute Acidified Waters" ; Nature ;
V . 284 ; 1980 ; p . 161 .
Gran, G . ; "Determination of the Equivalence Point in Potentiometri c
Titrations, Part II" . Analyst ; No . 77 ; 1952 ; p . 661-671 .
Haines T . ; Comments, Trans . of American Fisheries Society, Ill ;
1982 ; p . 779-786 .
Heradrey, G ., J .N . Galloway,. S .A . Norton, C .L . Schofield, D .W . Schaffer ,
and D .A . Burns ; "Geological and Hydrochemical Sensitivity o f
Eastern United States to Acid Precipitation'" ; EPA Ecologica l
Research Series, EPA 600/3-80-024 ; Corvallis Eavirommental ,
Research Laboratory, Corvallis ; Oregon ; 1980 .
Henricksen, A . ; "A Simple Approach for Identifying and Measurin g
Acidification of Freshwater" ; Nature ; V . 278 ; April ; 1979 ; p . 542-545 .
Henricksen, A . ; "Acidification of Freshwaters--A Large Scale Titration "
in Proc . Int . Conf . on Ecol. . Impact of Acid Precip . ; Drablos, D . an d
A . Tollan, Eds . ; Norway (SNSF Project) ; 1980 ; p . 68-74 .
35
Jeffries D . and A . Zimmerman ; "Comments on the Analysis and Sampling o f
Low Conductivity Natural Waters for Alkalinity" ; Can . J . Fisherie s
and Aquatic Sciences ; V . 37 ; 1980 ; p . 901-902 .
Kramer, J . and A . Tessier ; "Acidification of Aquatic Systems : A Critique
of Chemical Approaches" ; Environ . Sci . Technol . ; V . 16, No . 11 ; 1982 ;
p . 606A-615A .
Larson, D .W . and J .R . Donaldson ; "Waldo Lake, Oregon : An Ul.tra-Oligitrophi c
Environment and Some Implications Concerning Recreational Development" ;
Water Resources Research Institute, Oregon State University, Corvallis ,
Oregon ; Report WRRI-2 ; 1970 ; 21 p .
Liljestrand, H .M ., and J .J . Morgan ; "Chemical Composition of Aci d
Precipitation in Pasadena, California" ; Environ . Sci . Technol . ;
V . 12 ; 1978 ; pp . 1271-1273 .
Logan R .M ., J .D . Derby and L .C . Duncan ; ""Acid Precipitation and Lak e
Susceptibility in the, Central Washington Cascades" ; Environ . Sci .
Technol . ; V . 16 ; 1982 ; pp . 771-775 .
Oceanography International Carbon Analyzer Instruction Manual ; Oceanography
International Corp ., College Station, Texas ; 1974 .
Ontario Ministry of the Environment ; Acid Precipitation in Ontario Study ;
APi 002/81 ; Toronto, Canada ; 1981 .
Orion Moael 601 A Digital Ion Analyzer Instruction Manual ; Orion Researc h
Inc ., Cambridge, Massachusetts ; 1977A .
Orion Instruction Manual, Flouride Electrodes ; Orion Research, inc . ,
Cambridge, Massachusetts ; 1977B .
Orion Moael 211 Digital pH Meter Instruction Manual ; Orion Research, Inc . ,
Cambridge, Massachusetts ; 1981 .
Perkin-Elmer Analytical Methods for Atomic Absorption Spectropbtometry ;
Perkin-Elmer Corp ., Norwalk, Conn . ; 1973 .
Powers, C .F . and D .L . Rambo ; "The Occurrence of Ac,i,d Precipitatio n
on the West Coast of the United States" ; Environ . Monit . Assess . ;
V . 1 ; 1981 ; p . 93 .
Schofield, C .L . ; '!Effects on Fish" ; Ambio ; V . 5 ; 1976 ; p . 5 .
Shulters, M .V .,•• "Lakes of Oresgon . Vol . 3 : Hoed River, Multn,omah.,
Wash i .ngton, and Yamh i I I, Counties ; Vol : 4 : Clackamas County ; an d
Vol . 5 :' Marion County" ; U .S . Geological Survey, Open File Reports ;
1975 and 1976 .
Snoeyink V .L . and D . Jenkins ; "Water Chemistry" ; J .O . Wiley and Sons ,
New York ; 1980 .
36
Standard Methods ; 15th Edition ; Standard Methods for the Examinatio n
of Water and Wastewater ; American Public Health Association ,
Washington, D .C . ; 1980 .
Stumm W . and J .J . Morgan ; "Aquatic Chemistry" ; 2nd Edition ; 4 .0 . Wiley and
Sons, New York ; 1981 .
U .S . Environmental Protection Agency ; "Methods for Chemical Analysi s
of Water and Wastes ; National Environmental Research Center ,
Cincinnati, and Office of Technology Transfer, Washington, D .C . ;
1974 .
U .S . Geological Survey ; Water Resource Data for Oregon ; 1981 .
Wright R .F . and E .T . GJessing ; "Changes in the Chemical Compositio n
of Lakes" ; Ambio ; V . 5 ; 1976 ; p . 219-223 .
Wright R .F . and A . Henricksen ; "Chemistry of Small Norwegian Lakes ,
With Special Reference to Acid Precipitation" ; Limn®logy an d
Oceanography ; V . 23 ; No . 3 ; 1978 ; p . 487-498 .
Zimmerman, A .P . and H .H . Harvey ; "Final Report on Sensitivity t o
Acidification of Waters of Ontario and Neighboring States" ;
Ontario Hydro, Univ . of Toronto ; 1978-79 .
Zimmerman, A .P . ; "Sensitivity to Acidification . of Waters of Ontari o
and Neighboring States Ii : An Analysis of Data Set Variance an d
Prediction of Acid Sensitive Lake Areas" ; Ontario Hydro, Univ . o f
Toronto ; 1982 .
1
3T.
. APPENDICES'
•i
.
I
.
'
II
I
A.
LIMNOLOGICAL DATA FOR SEVEN CASCADE LAKES
B.
CHEMICAL DATA FOR 63 CASCADE LAKE S
C.
DISCUSSION OF EXPERIMENTATION IN LABORATORY TECHNIQUE S
39
-
Appendix A . Limnological Data for Seven Cascade Lakes .
a
DULL RUN LAKE
DEPTH
(feet)
0
10
20
25
30
35
40
44
45
50
60
70
80
90
100
TRANSM .
TEMP .
D .O .
(percent)
(C .)
{mg/L)
--------------------------- ND
19 . 0
7 .90
ND
19 . 0
7 .6 0
ND
16 . 0
8 .6 0
ND
ND
ND
ND
10 . 0
10 .0 0
ND
ND
ND
ND
5. 5
9 .7 0
ND
5. 2
9 .0 0
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
---------------------------(7/26182)-8 F .M .
`CALM, SUNSET
TRAMSM .
TEMP .
D .O .
(percent)
(C .)
(agIL )
---------------------------100
18 .7
7 .7 5
60
18 .7
7 .6 0
45
17 .5
7 .4 0
ND
15 .4
8 .8 0
38
14 .0
9 .9 0
ND
9 .8
10,2 0
29
8 .7
10 .4 0
ND
ND
ND
ND
ND
ND
28
6 .6
10 .40
ND
22
ND
22
ND
ND
19
ND
ND
16
ND
ND
12
ND
ND
--------------------------- (8/27/82)-4 P .M .
SUNN Y
r
TRANSM .
TEMP .
D .O .
(percent)
(C.)
(ag/L )
--------------------------- ND
11 .1
9 .1 0
ND
11 .1
8 .95
ND
11 .0
8 .85
ND
ND
ND
ND
11 .0
8 .85
ND
ND
ND
ND
10 .6
8 .90
ND
ND
ND
ND
9 .3
9 .0 0
ND
6 .5
10 .2 0
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
---------------------- i w
(104t82)P .M .
." CHDPRY
►- ~ ,
a
N
LOST LAKE
DEPTH
(feet)
0
10
20
22
25
28
30
35
40
45
50
60
70
80
90
100
TRANSM .
TEMP .
D .O .
(percent)
(C .)
*IL)
--------------------- 100
19 .5
7 .30
65
19 .1
7 .40
42
16 .3
7 .90
ND
ND
ND
ND
12 .2
9 .30
ND
ND
ND
31
9 .8
9.40
ND
NO
ND
24
7 .2
9 .80
ND
ND
ND
20
6 .0
9 .50
16
ND
ND
13
ND
ND
9
ND
ND
65
ND
ND
4
ND
ND
---------------------------(7127/82)-11 A .M .
SUNNY,CHOPPY
TRANSM .
TEMP .
0 .0 .
(percent)
(C .)
4g/L )
--------------------------- 100
19 .0
7 .3 0
65
18 .9
7 .35
43
18 .7
7 .3 0
ND
18 .0
7 .60
ND
16 .5
8 .3 0
ND
13 .9
9 .50
32
12 .2
9 .70
ND
10 .0
10 .00
25
7 .8
9 .80
ND
ND
ND
20
6 .3
9 .80
16
ND
ND
13
ND
ND
9
ND
ND
6
ND
ND
4
ND
ND
(8128/82)-12 A .M .
SUNNY
-TRANSM.
(percent)
TEMP .
(C .)
DA .
(ag/L )
--------------------------- -
100
11 .5
9 .1 0
60
10 .4
8 .9 0
45
10 .3
8 .9 0
ND
ND
ND
ND
ND
ND
ND
ND
ND
38
10 .2
8 .80
ND
ND
ND
32
10 .6
8 .60
ND
8 .0
9.90
26
6 .5
10 .00
19
ND
ND
14
ND
ND
9
ND
ND
5
ND
ND
2
ND
ND
---------------------------{10/15/82)-9 :30 A.M .
SUNNY, CALM
Appendix A . Continued .
WALDO LAKE (SOUTH END)
DEPT H
TRAM .
(feet)
(percent)
TEMP .
D .O.
(C .)
teg/L)
(percent)
TRANSM .
TEMP .
D .O .
TRANSM .
(C .)
(ag/L),
(percent)
TEMP .
(C .)
(ag/Li
D .O .
7 .90
0
100
15 .8
7 .70
100
16 .9
8 .10
100
13 .2
10
63
15 .1
7 .50
74
16 .8
7 .8'0
74
13.0
7 .85
20
55
12 .5
7 .90
64
16 .4
7 .90
69
12 .9
7 .50
25
ND
11 .7
14..2
ND
ND
ND
ND
ND
ND
ND
ND
ND
28
ND
13 .1
ND
ND
ND
ND
7 .6 5
30
48
9 .9
8 .65
56
11 .5
9 .45
61
12 .9
35
ND
7 .8
ND
ND
10 .1
ND
ND
ND
ND
40
ND
7 .0
8 .75
48
9 .4
9 .65
56
1'2 .8
7 .7 0
45
ND
ND
50
36
6 .1
60
70
33
80
ND
ND
8 .5
ND
ND
11 .4
5 .2 2
8 .80
44
8 .0
9 .80
53
10 .3
_8:85'
ND
38
ND
38
ND
48
44
ND
ND
ND
ND
ND
30
ND
ND
ND
ND
28
ND
38
ND
ND
41
ND
38
ND
ND
39
38
7 .5
ND
36
ND
ND
ND
ND
90
26
ND {
ND
ND
100
24
ND
ND
.
ND
------------- -
(7/12/82)-6 P .M .
(8/x/82)-11 A .M .
SUNNY,`CHOPPY
(97 =17/821-3 P .M .
SUNNY,CALM
. SUNNY,s.CAL M
WALDO LAKE (NORTH END )
DEPTH
(feet)
0
TRANSM .
TEMP .
D .O .
(percent)
(C.)
(ag/L)
--------------------------- -
TRANSM .
(percent)
TEMP .
D .O .
(C.)
(ag/L)
TRANSM .
•
TEMP .
(percent } . _ (C. l
,
0,0 .
Gli/L$
ND
16 .5
7 .90
100
18 .2
7 .85
100
10
ND
15 .8
7 .90
85
17 .2
7 .65
79
12 .5
12.5
20
ND
14 .8
8 .20
67
16 .6
7 .73
67
12 .3
22
.ND
ND
ND
ND
16 .2
7 .80
ND
ND
ND
25
ND
ND
ND
ND
14 .0
9 .20
ND
ND
ND
28
30
ND
ND
ND
ND
12 .1
9 .35
ND
ND
ND
ND
ND
ND
46
11 .5
9 .47
59
12 .3
7 .80
ND
55
ND
ND
12 .3
7 .3 0
ND
ND
ND
37
ND
ND
10 .0
9 .45
- .ND
ND
ND
ND
40
ND
ND
ND
ND
45
50
ND
'ND
ND
ND
ND
ND
ND
ND
ND
--------------------------- -
ND
ND
ND
--------------------------- -
(8/6/821-8 P .M .
SUNSET, CALM
8 .1 0
7 .90
7 .80
48
12 .5
6 .2 0
------------------------ -
(9/17/82)-1 P .N .
SUNNY, CHOPPY
,=
1.
Y•
Appendix A . Continued .
C- :
SUMMIT LAKE (WILL . PASS)
DEPTH
(feet)
0
10
15
20
25
30
40
50
TRANSM .
'TEMP .
D .O .
(percent)
(C .)
(egIL)
---------------------100
15 .0
8 .00
100
14 .8
8 .40
ND
3 .8
ND
98 •
13 .3
9 .00
ND
ND
X2 .5
B4
12 .4
9 .75
74 ti 12 .2
9•.80
61
11 .5
9 .95
----------------------- (7/13/82)-11 :3d A .M'.
OVERCAST 'CHOPPY
TRANSM .
(percent)
TEMP .
(C .)
D .Q .
(ogIL )
-TRANSM .
TEMP .
D.O .
(percent)
(C .)
(0g/L )
------------------------100
13 .5
7 .90
80
13 .5
•7 :6.0.
67
.ND
AN D
ND
7 :1 0 '
ND
ND
ND- r
61
13 .5 `
7 .65 - .
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1.3 .5
48
13 .5
6 .84
- 'F
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19 .0
7 .7 0
ND
18 .6
7 .6 0
ND
ND
'N D
NB'
18 .4
7 .4 0
ND
ND
, ND
ND
1B :2
. 7 .50
ND
18 .1 . - L.3 - `
ND
ND
'(D
-------------------------(8/7/82)-4 :30 P .M .
T-STORM,CALM
(9/18/82)-9 :30 A .M .
PART .SUFNVY,CAL M
OLALLIE LAK E
{
DEPT H
{feet)
TRANSM .
(percent)
TEMP .
IC .)
D .O .
(sg/L)
0
10
20
25
30
38
40
50
100
60
52
ND
43
ND
36
ND
18.8
18 .5
17 .9 .
16 .8
13 .6
12 .0
ND
'ND
7 .50
7 .25
7 .10
7 .40
8 .85
8 .50
ND
ND
TRANSM .
TEMP .
D.O .
(percent)
(C .)
(®g/L)
------- ------- ---------ND
18 .0
8,00
MD`
18 .0
7 .90
ND
18 .0
7 .95
ND
ND
ND
18 .0
7 .90
ND
ND
ND
ND
ND
18 .0
. 7 .80
ND
ND
ND
-
TRANSM .
(percent)
.
TEMP•-- -NO . (C .)
( .g/L )
ND .
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&/45 ' .
ND
8 .9
8.41 0
ND
8.9
7 .95
ND
ND
ND
119
8. 0
.NB
4D
ND
- ND
8 .8
7
Nb :,
ND
---------------------- -
(7/28/821 ;4 P .M .
SUNNY,'GHOPP Y
(8/29/82)-11 A .M .
OVERCAST ,CHOPPY
(10/15/82)-3 :30' .M•..
PART .OVEICAST,CHOPPY
1
Appendix A.}
Continued .
BLUE bME
- DEPTH
(feet)
0
2
4.'
6
8
10
15
20 .
30 '<, •
40
, ,
50'
60
70 80
.90
100
-
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(percent)
TEMP . (C . )
100
ND
ND -ND '
ND
62
ND
51
41
37'
33
30
29
25
23
21
14 .0
14 .0
14 .0
13 .8
10 .5
9 .0
7 .5
7 .0
6 .2
5 .8
5 .2
ND
ND
ND
ND
ND
,.
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9 .60
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12 .30
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12 .70
12 .50
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ND
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ND
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DEPTH
(feet )
TRiN I .
(percent)
TEMP .
0
100
25
41
35
31
ND
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1648 .
16 .8:
16 .4E
14 .5
10
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20
(C .)
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Appendix B-3 . Sea-Spray Corrected Concentrations for Major Cations and Anions . .
-------------------------------------------------- LAKE NAME
Ca
Mg
Na
K
2CAT
ALK
S04
Cl
ZAN EC/FA N
DAVIS
151 .5
103 .1
102 .7
21 .6
379 .0
379 .9
8 .6
0.0
388 .5
0 .976
CULTUS
80 .8
46.6
31 .9
9 .5
168 .8
172 .2
5 .2
0.0
177 .4
0 .95 1
L .CULTUS
99 .5
69 .1
49 .3
10 .6
228 .5 .-_
irl
8 .9
0.0
227 .9
1 .003
LAVA
84 .0
100.9
115.5
30 .0. .
330 .4
324 .0
5 .2
0.0
L .LAVA -
95 .0
102 .5
93 .7
26 .2
317 .3
367 .8
0 .1
0.0
367 .8
HOMER
49 .2
80 .1
145.3
21 .6
296 .2
295 .4
4 .9
0.0
300 .2
0.987
ELK(AV6)
91 .4
463
'44 .0
14 .3
196 .6
199 .3
4 .1
0.0
203 .4
0 .966
DEVILS
49 .4
64 .7
85 .8
22 .3
222 .1
249 .5
6 .9
0.0
256 .4
0 .866 1
SPARKS
48 .0
35 .6
46 .9
13 .9
144 .4
132 .9
5 .1
0 .0
138.0
1 .046
TODD
61 .9
18 .6
45 .3
21 .7
147 .6
169 .3
5 .6
0.0
174 .9
0 .844
3 .9
1 .2
0 .0
6 .1
11 .2
2 .9
1 .1
0.0
4 .0
t
191 .8
160 .8
112 .2
28 .2
492 .9
526 .3
2 .6
0 .0
528 . 9
SCOUT
68 .2
61 .9
24 .9
17 .3
172 .4
179 .5
4 .1
0. 0
183 . 6
ROUND
114 .5
92 .7
14 .7
8 .3
230 .2
205 .1
0 .0
0 .0
205 . 1
CLEAR
178 .2
156 .8
135 .8
-
24 .9
495 .7
496 .5
41 .2
0. 0
537 . 7
DUFFY
76 .9
38 .1
20 .3
'N
3 .9
139 .3
117 .6
3.0
0. 0
120 . 6
NONICH
26.6
23 .5
11 .1
=
4 .7
66 .0
69 .2
0 .6
0. 0
69 . 8
RED BUTTE
64 .E
54 .3
BOO'
18 .9
196 .9
187 .3'
3 .9
0. 0
191 . 2
JORN
38.0
28 .2
11 .7
2 .9
80 .8
78 .5
1 .1
0. 0
7 .
' 71 .7
86 .6
23 .1
8 .6
190 .0
195 .4
0 .9
0. 0
BULL RUN(AV6)
68 .9
35 .3
25 .9
7 .7
137 .9
124 .0
0 .3
0.0
LOST(AVG)
49 .8
26 .7
9 .2
8 .6
94 .3
83 .4
1 .5
0. 0
FRO6
43 .6
27 .6
29 .4
5 .7
106 .4
108 .9
1 .9
0 .0
110 .7
0 .'iti ~
CLEAR
74 .4
58 .1
23 .2
7 .7
163 .4
167 .7
0 .0
0.0
167 .7
t - i
N .SUMNIT(AV6l
10 .0
5 .7
2 .3
4 :9
22 .8
2 .B
11 .1
0 .0
13.9
1 .647
BAYS
3 .9
2 .1
0 .0
'0.7
6 .7
5 .2
ND
' . --
t
SCOUT
, 3 .5
0 .0
0 .0
0 .8
4 .3
7 .5
0 .0
0. 0
X7 .5
5
ROCK
36 .9
0
0•.0
0 .7
37 .7
2 .1
4 .8
0 .0
0 .7
ND
ND
17 .8
1 .420
335 .5
0 .97 7
LUCKY(AV6)
BLUE(AV6)
SANTIAM
*-
-
,
0 ..0 '
(POND}
'3 .4
0 .0
0 .0
4 .0
7 .4
WALDO
10 .8
3 .9
1 .5
9:1
25 .3
16 .9
1 .0
0.0
332 .2
3.3
0. 0
ODELL
142 .4 :
77 .8
117 .2
'20 :3
327 .8
CRESCENT
118 .6
71 .3
53 :9
31 .9
275 .7
'329
. ,1 .004
,
t Corrected ion balance not meaningful due to some negative values,'
49
ratio cOumn .
-
'
'
}
4 lt
` ~&I,9t'
14
t'
t
2 .2
0 :0
' 284 ..4
.01.969
282 .1
--------------------------------- --------- - ----------------------------------------------------------
1-Units for all tabulated parameters are (ueq/11 except for cation/ta i
_
,0•,,
"
Tr
;'
6-'P
. ii
i
.f_
I
7
~ ~~
r
L
Appendix B-3 . Continued .
LAKE NAME
Ca
Mg
Na
K
SCAT
ALK
S04
CI
ZAN
.C/FAN
-------------------------------------------------------------------------------------------------------------- SUMMIT(AV6)
6 .0
2 .0
3 .0
6 .7
17 .6
11 .9
1 .8
0 .0
13 .7
1 .286
BETTY(AY6)
14 .6
4 .1
10 .3
7 .7
36 .8
32 .8
3 .6
0 .0
36 .5
1 .008
CHARLETON
23 .6
12 .6
8 .5
53 .7
47 .6
3 .0
0 .0
50 .7
1 .060
TORREY
38 .4
24 .4
21 .0
9 .2
93 .0
82 .9
6 .3
0 .0
89 .2
1 .04 3
WHIG .
99 .2
49 .4
42 .9
18 .6
210 .1
182 .3
8 .3
0 .0
190 .6
1 .103
WAHANNA
20.0
16 .5
13 .6
-11 .0
61 .1
54 .2
6 .1
0 .0
60 .3
1 .01 5
S .RI6DON
4 .9
1 .6
0 .0
14 .8
21 .4
8 .1
3 .7
0 .0
11 . 8
N .RI6DON
26.9
11 .0
17 .9
• ND
43 .2
ND
ND
--
KIWA
32 .4
16 .0
20 .0
ND
50 .8
ND
ND
GOLD
176 .8
98.2
106 .9
30 .7
412 .5
421 .3
8 .2
0 .0
429 .5
0 .960
U .MARILYN
79 .3
31 :8
39 .7
•11 0 .0
160 .8_
190 .1
6 .3
0 .0
196.4
0 .81 9
L .MARILYN
84 .4
30 .7
29 .5
7 .5
152 .1
180 .8
6 .1
0 .0
187 .0
0 .81 3
OLALLIE(AVG)
10 .0
7 .3
1 .7
4 .4
23 .5
15 .8
1 .0
0 .0
16 .8
1 .398
MONOD
10 .8
6 .8
4 .0
10 .4
32 .0
26 .4
4 .0
0 .0
30 .4
1 .052
HORSESHOE
6 .5
2 .9
1 .4'
4 .6
15 .4
13 .3
0 .0
0 .0
13 .3
t
GIBSON
3 .0
1 .4
0 .0
3,4
7 .8
2 .9
0 .0
0 .0
2 .9
t
BREITENBUSH
21 .5
:8 .7
14 .0
51 k .
49 .3
46 .1
1 .5
0 .0
47 .5
1 .03 8
FIRST
11 .8
5 .2
0 .0
1 .2
18 .1
10 :4
0 .7
0 .0
11 .1
t
7 .7
, 4 .6
0 .0
: 1 .4
13 .7
7 .8
0 .0
9 .0
7 .8
t
LOWER
36 .7
10 .9
A .9
2 .5
55 .0
57 .5
0.0
• 0 .0
FISH
123 .3
38 .3
. -21 .4 .
,10.'
.493 .7
206 .4
3 .3
0 :0
209 :7
SHEEP
26 .8
0 .2
0 .0
14 .3
41 .3
8.'8
0.0
0 .0
.8 . 8
WALL
10 .1
0 .0
0 .0
21 .2
31 .4
9 .5
0 .0
010
4 7.9 .5
t
AVERILL
10 .9
0 .0
23 .8
34 .7
18.6
0.0.
0 .0
, .18 .6
t
RED
24 .8
0 .0
0.0
9 .0
33 .8
15 .6-
0 .0
0 .0
15 .6
1
BROOK
138 .0
59 .6
0 .0
9 .9
207 .5
270 .7
0 .0
0 .0
270 .7
JUDE
186.2
106 .9
78.3
16 .2
387 .6
375 .9
5 .7
0 .0
381 .6
1 .01 6
RUSS
,131 .2
55 .4
58 .1
11 .8
256 .4
267 .4
3 .4
-9 :0
270 ,
0 .94.7-
LAVA CAMP
10 .0
15 .3
# .0¢'
3 .1
29 .4
27 .2
2 .3
0 .0
- . : 29 .5
0 .995
SCOTT
13 .5
16 .1
8.t'
41 .7
41 43
0 .9
0 .0
42 .2
•10 .98q
THREE CREEKS
84 .2
56.0
`-r4 .1
•
13 .0
213 .5 "
0 .0
0 .0
213 .5
t
HEAD
9 .0 `
59 .9
213 .1
-t-,
1-Units for all tabulated parameters are (ueq/1) except for cation/anion ratio column .
t Corrected ion balance not meaningful due to some negative values .
g.51 .924
• 'Y -
t
ti
APPENDIX C
DISCUSSION ©F EXPERIMENTATION IN LABORATORY TECHNIQUE S
In addition to those analyses performed to achieve the primary objective s
of this study, additional laboratory experiments were performed to "shed mor e
light" on both the current differences in analytical . procedures used among
acid-precipitation researchers and the inconsistencies in comparin g
historical alkalinity data to recent data collected using Gran titration t o
determine the alkalinity titration endpoint . The results of thes e
experiments are summarized here .
The Gran titration procedure, or total inflection point (TIP) procedure ,
is described in detail by others (Gran, 1952 ; Stumm and Morgan, 1981 ;
Zimmerman and Harvey, 1978-79) . This procedure is generally accepted as th e
most rigorous and accurate method for determining alkalinity titratio n
endpoints and has been used by most investigators since 1970 (Kramer an d
Tessier, 1982) . Before 1970, alkaliniti .es were determined using fixe d
endpoint (FEP) acidimetric titrations . There seems to be considerabl e
difficulty and inconsistency when investigators compare present TI P
alkalinity data to historical FEP data in order to assess extent o f
acidification for a water body . In the past, FEP alkalinities wer e
determined using either colorimetric endpoint indicators or a fixed pH as a n
end point indicator (Kramer and Tessier, 1982) . The endpoint pH for a tota l
alkalinity titration is, however, an approximation of the f = 0 equivalenc e
point of the carbonate system . The equivalence point varies with inorgani c
carbon concentration ; a lake high in inorganic carbon and well-buffered ha s
an equivalence point of approximately pH = 4 .5 . A dilute lake, however, ha s
a higher equivalence point pH (>5 .0) . Hence, FEP alkalinity titration s
generally overestimate the alkalinity of dilute, poorly buffered lakes--thos e
which are sensitive to acidic inputs . Rigorously, the magnitude of thi s
overestimate is the amount of hydrogen ions titrated past the equivalenc e
point to reach the fixed endpoint .
Jeffries and Zimmerman (1980) report that mathematical correction of FE P
alkalinity data is not possible, as FEP data differ randomly from TIP data .
Other investigators report that accurate corrections of historical data ar e
possible . However, the magnitude of such corrections is inconsistent amon g
investigators . Kramer and Tessier (1982) report a methyl orange endpoint pH ,
as determined by three independent operators, of 4 .04± 0 .10 (n = 24) . Thus ,
he suggests that historical alkalinity data, for which methyl orange has bee n
used as the titration endpoint indicator, should be corrected by 81 ueq/I .
Kramer and Tessier describe this correction as the excess hydrogen io n
concentration resulting from the difference between their own methyl orang e
endpoint pH and an approximate equivalence point pH of 5 .0 for low-alkalinit y
solutions .
1
51
Most other investigators report fixed endpoint alkalinity titration dat a
corrections of 32 ueq/l . Burns et al ., (1981) report that a colorimetri c
indicator overestimates alkalinity by the hydrogen ion concentration at th e
titration endpoint . Thus, they report a correction of 32 ueq/l, which the y
describe as the hydrogen ion concentration at pH = 4 .50 . Rigorously, such a
correction exceeds the theoretical correction by the hydrogen io n
concentration at the titration endpoint . This concentration is, however ,
small ; the more dilute a system is the lower will be the endpoint hydroge n
ion concentration . Henricksen (1979) reported that if alkalinities ar e
determined by standard titration to pH = 4 .5, they are overestimated by 3 2
ueq/l--the hydrogen ion concentration at pH = 4 .5 . Haines (1982) mad e
extensive comparison of fixed endpoint and Gran titration alkalinties an d
reported that the two methods give linearly-correlated (r = 0 .998) result s
with a slope of 1 .0 and an intercept of 32 ueq/l (ALK Gran=ALI(FEp -32) .
It i s
not reported, however, whether the fixed endpoint alkalinities wer e
determined potentiometrically or colorimetrically . Finally, Hendrey et al . ,
(1980) reported that determination of alkalinities using fixed endpoint
titration to pH = 4 .5 requires 30 to 40 ueq/l excess titrant .
In this study, alkalinity titration endpoints were determined using th e
Gran technique . From the raw titration data, fixed endpoint alkalinitie s
based on endpoint pH values of 4 .5 and 4 .0 were also calculated . Linea r
regressions of these alkalinities versus the correspondin g
Gran-titration-alkalinities are shown as follows :
ALK
ALK
Gran = 0
Gra n = 0
.96 ALK 4 .5 -31 .20
(n = 63, r 2 = 1 .00)
(C-1 )
.93 ALK 4 .0 -91 .9 9
(n = 63, r 2 = 1 .00)
(C-2 )
These regressions indicate quite favorably that fixed endpoin t
alkalinities can be corrected easily and accurately if the endpoint pH fo r
the historical alkalinity data is known . In addition, these corrections
correspond closely to the corrections reported by others (and describe d
earlier) for the same titration endpoint pH values .
Generally, when fixed endpoint a l ka l i : n 1i. ty ti tra- i ons' were performed usin g
a specific endpoint pH, this'pH is readily available with, the historica l
data ; corrections are thus simple . Correction of data where FEP alkalinitie s
are determined using a colorimetric indicator is more difficult, however .
The pH at the methyl orange endpoint is not generally agreed upon and ma y
actually occur over a range of pH values, depending on the strength an d
amount of methyl orange added . Thus, historical alkalinities determine d
using methyl orange as an endpoint indicator cannot be as easily an d
accurately corrected . In this study, the methyl orange endpoint wa s
"investigated" and did not appear to be distinct ; the color change from
yellow to pink was gradual .
52
Equations C-1 and C-2 indicate that accurate corrections of fixe d
endpoint alkalinity data can be made . Differences among analysts, reagants ,
titrators and pH meters, however, might decrease the accuracy of suc h
corrections . To explore the effect of such differences, the alkalinities o f
16 lakes sampled in this study were compared to alkalinities of the same 1 6
lakes as determined In 1975 by Shulters (1975) . These past alkalinities wer e
determined using potentiometric fixed endpoint titration to pH = 4 .5 . Th e
linear regression of these data sets is shown as follows :
.7 ALK
ALK Gran = 0 .95 - 25
FEP
(n = 16,r = 0 .98)
(C-3 )
where the Gran alkalinity values are from this study and the FEP alkalinit y
values are those of Shulters .
The closeness of this regression to that of Equation C-1 for a fixe d
endpoint pH = 4 .5 is impressive . The historic fixed endpoint data wer e
determined using less sophisticated equipment and there was a seven-yea r
interval between sampling of the lakes . Natural fluctuations in alkalinitie s
due to different sampling dates, seasons, times of day and differen t
precipitation patterns could easily explain the slight difference i n
Equations C-i and C-3 . In this case, an accurate correction of historica l
fixed endpoint alkalinity was possible . Oregon Cascade lakes are weakl y
buffered by the carbonate system . The effect of the presence of other buffe r
systems on the proposed corrections is not known .
To study the extent of alkalinity deterioration with sample storage time ,
alkalinity analyses were performed weekly on water samples from two lakes .
The average alkalinities of these two lakes, as determined from 9 and 7
samples collected during the summer of 1982, were 125 ueq/I and 16 ueq/l ,
respectively . The water samples were collected in one liter linea r
polyethylene sample bottles, filtered through 0 .45 um Millipore filters, an d
refrigerated at 40 C between analyses . The results of this experiment ar e
shown in Figure C-1 . It is evident from Figure C-1 that alkalinity does not
change significantly with time and that linear polyethylene sample bottles d o
not influence alkalinity .
Finally, both in-situ and laboratory-equilibrated pH data were collecte d
in this study to investigate the effects of differences in conditions unde r
which pH data has been historically collected . The mean in-situ pH for th e
63 lakes was 6 .93, with s = 0 .80 . The mean lab pH was 6 .96, with s = 0 .59 .
Thus, there was more variability in in-situ pH, but the mean values wer e
nearly the same . Lab pH data were regressed as a function of field pH an d
the regression forced through the origin to obtain :
Lab pH = 1 .003(field pH)
(n =63, r 2 = 0 .82)
(C-4 )
Although there is greater variation in in-situ pH because of natura l
influences which are largely missing in the laboratory (primary production ,
53
r
0
CD
S0
4-3
N
s_
a)
4
)
a)
co
0 >,
1-0
0 0
•r
4-) 5
(C) r
s_ a)
0
r •r
S_ r
a)
4-3
a) • r
a)
~S4-3
•r
IS)
U)
U,
N
n
U,
U)
(1/ ban)
Al I N 11V>i1 V
54
U,
N
m
respiration, temperature effect and wind-driven . C0 2 supersaturation), It appear s
that pH data collected under both conditions can be compared without correction. .
The conclusions of these experiments are :
1. Excellent correlations were obtained between Gran-titration alkalinit y
data and fixed endpoint alk-alinities calculated from the raw titration, data .
The correlations obtained were.simi,lar to those reported- by many other
investigators .
2. Differences in Gran-titration alkalinities of 16 lakes sampled in thi s
study and fixed endpoint alkalinities for the same 16 lakes sampled in 1975 wer e
very similar to those differences predicted by the correlation betwee n
Gran-titration and fixed endpoint titration alkalinities . Any differences ar e
probably due to natural alkalinity fluctuations over the seven-year interva l
between sampling .
3. Alkalinity does not seem to change significantly with time (less than 5
weeks) for filtered water samples stored in polyethylene sample bottles at 4 ' C .
4. Differences between average in-situ pH and averag e
laboratory-equilibrated pH were not significant, although there was greate r
variability among in-situ pH values .
55
March 5, 1984
ERRATA SHEET
WRRI-85 : "Sensitivity of Oregon's Cascade Lakes to Acid Precipitation "
by Peter O . Nelson and Gregory K . Delwlch e
September 1983
USDI Project No . A-061-ORE ; NTIS Accession No . PB8 4 11178 0
Page1
Paragraph 5, line 3 reads . . . .less than 20 ueg/ l
should read . . . .less than 20 ug/ l
Paragraph 5, line 4 reads . . . .300 mg/ I
should read . . .300 ug/ l
Page 1 0
Table 1 . Under "Parameter" column, line 14 reads . . . .A1, ug/ l
should read . . . .Al, ug/ l
Paae 1 6
Under "Alkalinity" paragraph, line 1 0
reads . . . .ALK = -9 .10 + 1 .05 ECA T
should read . . . .ALK = -8 .66 + 1 .05 ECAT
Page 19
M .'
Under "Summary of Metal Results" paragraph
Line 3, reads . . . .ALK = -9 .10 + 1 .05 ECA T
should read . . . .ALK = -8 .66 + 1 .05 ECA T
Page 2 1
Paragraph 3, line 1 reads . . . .carbon analse s
should read . . . .carbon analyse s
Paragraph 4, line 4 reads . . . .an expotenta l
should read . . . .an expotentla l
Page 24
Paragraph 2, line 3 reads . . . .of 20 0
should read . . . .of 100
Page25
Figure 6 .
Key -- #10 reads . . . .Theoretical (200 )
should read . . . .Theoretical (100 )
rage28
Paragraph 3,
line 7 reads . . . .with Henricksens' s
should read . . . .wlth Henricksen' s
Page 29
Table 3 . Under "Source" colum n
Line 3 read . . . .Logan et al . ,
should read . . . .Logan et al ., 1982
Note : word processor put date in "Region" category
r