905R87103
Report on
Assessment of Minnesota
Pollution Control Agency's ~j\ f.
Ambient Water Quality Monitoring
Network
by
Ihsan Eler, P.E.
Arthur Lubin, Ph.D.
Environmental Monitoring Branch
Environmental Services Division
U.S. Environmental Protection Agency
Chicago, Illinois 60605
July, 1987
-------
905R87103
TABLE OF CONTENTS
Page
I. Executive Summary 1
II. Introduction 2
III. Description of Monitoring Stations 8
1. Station Locations, Types, Objectives
2. Classification of Monitoring Areas
3. Station Siting Purposes
4. Analyses of Parametric Coverage and Sampling Frequency
5. Monitoring Station Network Deficiencies
IV. Statistical Analysis 1R
1. Data and Setting
2. Statistical Procedures
V. Results 20
1. Eight Year Trend Analyses
2. Non-Point Source Pollution Trends
3. Point Source Pollution Trends
VI. Conclusions 35
Appendices
-------
I. Executive Summary
This report presents an assessment of water quality trends in Minnesota
as represented by fixed station ambient water monitoring data stored in
USEPA's STORE! data bases. The period of study is from January 1978 to
December 1985 and covers 75 fixed ambient monitoring stations. Approx-
imately 70,000 observations were analized to get the statistical trends
for this study. The overall objective of this is report to assess fixed
ambient monitoring network station, parametric coverage and to determine
current water quality trends of streams in Minnesota and types of pollu-
tion sources impacting the surface waters.
Water quality, as determined by the trend analyses for the past eight
year period, has shown some change in Minnesota. In fact, the following
types of pollution showed increasing trends as indicated by the analysis
of monitoring data:
0 Point source pollution increased at 8% and decreased at 7% of the
stations.
0 Non-point source pollution trends increased at 12% of the stations.
As a result of this study, the following changes to Minnesota's ambient
monitoring network are recommended:
0 Conduct biomonitoring and bioassays at monitoring stations where increased
pollution trends were observed.
0 Expand monitoring of sediments and water column for toxic variables at
the existing stations or establish new ones to detect toxicants.
0 Eliminate or relocate those stations based on trend indications and
professional judgement.
0 Avoid duplication by sharing monitoring information with the neigh-
boring states that have common waterbodies with Mi nesota.
-------
II. Introduction
The 1972 Water Pollution Control Act Amendments (PL-92-500) require the
states to monitor water quality and report their findings to Congress bi-
annual ly via 305(b) reports. In partial fulfillment of the requirements
of this Act, states and EPA operate and maintain fixed monitoring stations
as a part of their ambient monitoring efforts.
The Minnesota Pollution Control Agency (MPCA) operates and maintains 75
fixed ambient monitoring stations on a rotating basis to monitor the states'
water quality. The objectives of these ambient water quality monitoring
network of stations are to:
0 Assess long term trends in water qualilty;
0 Assess the effectiveness of pollution control efforts;
0 Determine effects of Point and Non-point sources on stream quality;
0 Determine the overall water quality at specific locations.
Thus, the overall objective of this report is to assesses Minnesota's
fixed ambient monitoring network stations locations, parametric cover-
age, to determine water quality trends of surface waters and pollution
impacts. To achieve this objective, the following aspects of ambient
monitoring stations were evaluated, analyzed and summarized:
1. Station location, type and objective;
2. Classification of the monitoring area;
3. Classifation of station siting purpose;
4. Parameter coverage and sampling frequency;
5. Uses of data collected;
6. Pollution trends.
This study analyzed fixed station monitoring data stored in STORET
for the period beginning in January 1978 and ending on December 1986.
In Table 1, the list of Minnesota's monitoring stations is given with
their respective map locations are shown on Figure 1.
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\ TMfc-WNj^/ ROS-%1 Jr-J
i I
RED
K-1.8 «IVER
LAKE OF
THE WOODS
BASIN
UlPPER
MISSISSIPPI
~ •
Minnesota
Water Quality
Monitoring
Network
Routine Sompling
Stotion
-------
Table 1. Minnesota Routine Monitoring Network stations
LAKE SUPERIOR BASIN
River
1. Beaver River*
2. St. Louis Bay*
3. St. Louis Bay
4. St. Louis River*
5. St. Louis River
6. Whlteface River***
7. Whiteface River***
8. Minnesota River
9. Minnesota River*
10. Minnesota River
11. Minnesota River
12. Minnesota River*
13. Minnesota River
14. Blue Earth River*
15. Elm Creek
16. Cedar Run Creek
17. Pomme de Terre R.
18. Redwood River
19. Cottonwood River
Station
SLB-1
SL-9
SL-38
SL-110
WF-22
WF-27
Location
li miles SW on CSAH-3 from junction
of CSAH-4, li miles north of Beaver
Bay
Below interstate 535 bridge, Duluth
Bridge on SH-23 at Fond du Lac
Bridge on USH-2 near Brookstone
Bridge on CSAH-7 near Forbes
Bridge on CR-29, 1 mile south and
2 miles west of Kelsey
Bridge on CSAH-7, i mile south of
Kelsey
MINNESOTA RIVER BASIN
MI-3.5 Fort SnelUng State Park-below
airport landing lights
MI-64 Bridge on SH-19 at Henderson
MI-88 Bridge on SH-22 at St. Peter
MI-133 Bridge on CSAH-24 at Courtland
MI-196 Bridge on SH-19 and USH-71 at
Mortan
MI-288 Bridge on SH-40, 3 miles U of Milan
BE-0 At confluence with Minnesota River
in Sibley Park above dam, Mankato
EMC-18 Bridge on CSAH-149, 5 miles SE of
Truman
CDR-12.8 Bridge on CSAH-9, 4 miles NW of
Trlmont
PT-10 Bridge on SH-7 at Appleton
RWR-1 Bridge on CSAH-101 at North Redwood
CO-0.5 Bridge E of SH-15 bridge at New Ulm
-------
Table 1. (cont'd)
MISSISSIPPI RIVER BASIN
River
20. Mississippi River*
21. Mississippi River
22. Mississippi River
23. Mississippi River
24. Mississippi River*
25. Mississippi River
26. Mississippi River
27. Mississippi River
28. Mississippi River
29. Mississippi River
30. Mississippi River
31. Mississippi River*
32. Mississippi River*
33. Mississippi River
34. Mississippi River*
35. Sauk River*
36. Crow River, N Fork
37. Rum River
38. Cannon River
Station
UM-698
UM-714
UM-738
UM-815
UM-826
UM-840
UM-859
UM-895
UM-914
UM-930
UM-982
UM-1172
DM-1186
UM-1292
UM-1365
SA-0
CRN-6
RUM-34
CA-13
Location
Bridge on USH-14 at LaCrosse,
Wisconsin
Lock and Dam #6, near LaMoille,
across via WI
Lock and Dam #5, SE of Minneiska
Lock and Dam #2 at Hastings
J.L.Shiely Company Larson Plant
Dock at Grey Cloud Island, Cottage
Grove
St. Paul Rowing Club dock below
Wabasha Street bridge, St. Paul
Minneapolis waterworks intake,
Fridley
Bridge on SH-25 at Monticello
Bridge on SH-24 at Clear-water
Bridge on SH-152 at Sauk Rapids
Bridge on SH-115 at Camp Ripley
Bridge on CR-441, 5 miles SE of
Grand Rapids near Blackberry
Bridge on SH-6, 6 miles SW of
Cohasset
Bridge on CSAH-8, E of Bemidji
Bridge on USH-200, i mile U of Lake
Itasca (town)
Bridge on CSAH-1, N of St. Cloucl
Bridge on CSAH-14, 4 miles W of
Rockford
Bridge on CSAH-5 at Isanti
Bridge on CR-1, 1 mile SE of
Clinton Falls
-------
Table 1. (cont'd)
River
39. Straight River
40. Long Prairie River
41. Zumbro River,
S.Fork
42. Whitewater River
43. Root River
44. Vermin ion River
45. Garvlri Brook
46. Swan River
47. Swan River
48. St. Croix River*
49. St. Croix River
50. Kettle River
51. Cedar River*
52. Cedar River
53. Shell Rock River
54. Red River*
55. Red River
Station
ST-18
LPR-3
ZRS-20
WWR-26
RT-3
VR-32.5
GB-4.5
SW-8.6
SW-4.1
ST. CROIX RIVFP
Location
n« °r f?'
Clinton Falls
m1le SE
Bridge on USH-10, S of Motley
CSAH'14' 3 m11es N of
Bridge on county road E i of
Section 2, T106, RIO, NW of Utica
Bridge on SH-26, 3 miles E of Hokah
Bridge on Blain Avenue, Farmington
Bridge on CSAH-23, 1.5 miles SW of
Minnesota River
' of
' of
SC-17
SC-111
KE-11
C 4 NW Railway bridge at Hudson,
Wisconsin
Bridge on SH-48, 2 miles W of
Danbury, Wisconsin
Bridge on SH-48, 4* miles E of
Hinckley
CEDAR RIVER BASIN
CD-10
CD-24
Bridge on CSAH-14, 3 miles S of
Austin
Bridge on CSAH-2. 0.5 miles E
of Lansing
SR-1.5 Bridge on CSAH-1 near Gordonsville
RED RIVER BASIN
RE-300
RE-403
At Grand Forks waterworks intake,
Alemont Ave. S., Grand Forks, N.D.
Bridge on CSAH-39, W of Perley
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Table 1. (cont'd)
River
56. Red River*
57. Red River
58. Rabbit River
59. Whiskey Creek
60. Otter Tail River
61. Otter Tall River
62. Red Lake River*
63. Red Lake River
64. Snake River
65. Two Rivers
(Middle Branch)
66. Roseau River
67. Rainy River*
68. Rainy River*
69. Rainy River
70. Kawishiwi River
71. Baudette River
72. Winter Road River
73. Rapid River
74. Big Fork River
75. Little Fork River
Station Location
RE-452 First Street Bridge, Moorhead
RE-536 Bridge on CSAH-18 at Brushvale
RBT-6 Bridge on US-75, 4 miles W. of
Campbel1
WSK-4.4 Bridge on US-75 at Kent
OT-1 Bridge on 4th Street N in
Breckenridge
OT-49 Bridge on CSAH-15, 2i miles W. of
Fergus Falls
RL-0.2 Bridge on SH-220 at East Grand
Forks
RL-23 Bridge on CSAH-15 at Fisher
SK-1.8 Bridge on SH-220, N of Big Woods
TMB-19 Bridge on USH-75, N of Hal lock
RCS-121 Bridge on CSAH-2 at Malung
RAINY RIVER BASIN
RA-12
RA-83
RA-86
KA-10
BAU-0.1
WR-1
RP-0.1
BF-0.5
LF-0.5
International bridge at Baudette
International toll bridge at
International Falls
Railroad Bridge at Rainer
Bridge on SH-1 at Birch Lake
Bridge on SH-11 at Baudette
Bridge on SH-11, W of Baudette
Bridge on SH-11 at Clemenson
Bridge on SH-11, 4 miles
E of Loman
Bridge on SH-11, W. of Pelland
* national fixed station network
** acid rain streams
*** peat monitoring stations
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III. Description of Monitoring Stations
1. Station Locations, Types and Objectives
STORE! contains comprehensive information for each station in Minne-
sota's fixed ambient monitoring network. Specifically, for each
station the following characteristics are included: waterbody, reach #,
purpose, waterbody type, parametric coverage,sampling frequency, data
entry into STORET, siting type, location and site description, and siting
purpose. Minnesota's network includes the following categories of
stations:
0 upstream and downstream of major metropolitan areas
0 large and small streams
0 streams influenced by Point and Non-Point sources
0 near the mouth of major tributaries to the Mississippi
and Minnesota rivers
0 on pollution free streams for background reference
Also in Table 2, each station's specific characteristics, location,
parameters, basins, and other pertinent information are shown.
Fifty-eight stations are located in rural areas, nine are in
urban areas and eight stations are in non-classifiable locations.
Twenty stations are National Network and fifty five are state network
stations. There are a total of 75 stations located in Minnesota as
shown in Figure 1. Eight are paired as upstream and downstream of
municipalities, major dischargers or other non-point source impact
sources. The remaining 67 stations are on: large and small streams,
point and non-point source impact free streams for background reference
purposes.
2. Classification of Monitoring Areas
In classifying stations by basins, 27 stations are in the Mississippi
River basin, seven are in the Lake Superior basin, 12 are in the Minne-
sota River basin, 3 are in the Cedar River basin, 12 are in the Red River
basin, and 9 are in the Rainy River basin. Furthermore, stations are
classified into four categories based on the types of pollution cate-
gories, such as urban, industrial, municipal and non-point as well as
areas which are relatively free from pollution so as to qualify as
pristine streams. These general groupings are given in Table 4.
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3. Station Siting Purpose(s)
All of the 75 stations are placed to measure basin status, water
quality standards attainment/maintenance and water quality conditions
for trends assessment purposes. Fifty-nine stations detect non-
point source impacts and twelve stations detect point source problems
due to municipal and industrial dischargers. Four stations detect
basin level water quality. However non of the ambient stations are
located on streams near major waste disposal or Superfund sites
where water quality maybe impaired by toxics form these locations.
4. Analysis of Parametric Coverage and Sampling Frequency
The MPCA generally follows the recommendations of the Water Monitoring
Program Guidance in selecting parameters and sampling frequency for
fixed station monitoring. However, sampling frequency has been redu-
ced to nine months per year due to budgetary constraints. The chemi-
cal measurements as shown in Table 2 consist of dissolved oxygen,
oxygen demanding substances, nutrients, solids and metals at all
stations. The biological measurements are limited to fish tissue
which has been sporadically conducted at the fixed stations during
the past eight years.However, the MPCA conducts an extensive annual
fish tissue monitoring program which covers a very limited number
of organic compounds and metals. The state's fish tissue residue
monitoring program is not conducted at fixed network stations on
a routine basis. A list of all the parameters for biological and
chemical analyses are given in Table 3.
5. Monitoring Stations Network Deficiencies
The following deficiencies were observed in monitoring capabilities
of the stations reviewed:
0 Lack of monitoring on streams near major hazardous and non-
hazardous waste disposal facilities and Superfund sites.
0 Biomonitoring for macro or micro invertebrates is not done.
0 Routine monitoring for fish tissue residue is too sporadic
at fixed monitoring stations.
0 Toxics monitoring is not conducted at ambient monitoring sites.
0 Bioassays are not conducted at any of the monitoring stations.
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10
Table 2- MINNESOTA FIXED STATION MONITORING ANALYSIS MATRIX
Station
Number
UM-698
UM-714
UM-738
UM-815
UM-826
UM-840
UM-859
UM-895
UM-914
UM-930
UM-982
UM-1172
UM-1186
UM-1292
UM-1365
SA-0
CRN-6
RUM-34
CA-13
BV-4
SLB-1
SL-9
Basin
Miss.R.
ii H
M H
ii M
H H
M H
ii H
M n
M n
n n
n n
n n
II H
II II
II II
II II
II II
II II
II II
Lk.SUP.
ii ii
H II
Location
Purpose Type
C,W,B,NP,*,U,BG,I,M
C.W.B.NP S,BG
C,W,B,NP S.BG
C.W.B.PS M,I
C.W.B.PS *,U,M,S,I
C.W.B *,U,I,M,S
C,W,B *,U,I,M,S
C,W,B,NP R,S,BG
C,W,B,NP S,R,BG
C,W,B,NP S,R,BG
C.W.B.NP S.R.BG
C,W,B,NP S.R.BG
C,B,NP *,R,BG,S
C,W,B,NP S.R.BG
C.W.B.NP *,R,BG,S
C,W,B,NP *,R,BG,S
C,W,B,NP S.R.BG
C,W,B,NP S.R.BG
C.W.B.NP S.R.BG
C,W,B,NP *,BG,R
C.W.PS.B *,M,S,U
C.W.B.PS BG.S
Biological
Type Freq.
FT P
FT P
FT P
FT P
FT P
FT P
FT P
FT P
FT P
FT P
FT P
FT P
Chemical
Type Freq.
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
n,0,N,S,M Mo
D,0,N,S,M Mo
0,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
O.O.N.S.M Mo
D,0,N,S,M Mo
0,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
0,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
0,0,N,S,M Mo
D,0,N,S,M Mo
Configutation
Single/Paired
Si
Si
Si-
Si
Si-
Si
Si-
Si
Si
Si-
Si
Si
Si
Si
Si
Si-
Si
Si
Si
Si-
Si
Si-
Flow
Meas. 1
Yes
Yes
1
1
1
No
No
* See page 14 for Legend for Table 2
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11
Table 2(cont'd) MINNESOTA FIXED STATION MONITORING ANALYSIS MATRIX
ion
ier
8
10
2
7
.5
>4
8
33
96
'88
18
12.8
0
1
.5
8
3
5.7
26
2.5
Basin
Lk.SUP.
H H
it M
H H
MINN Rv
H H
H it
n n
H n
n n
n n
n n
n n
M n
n n
n n
MISS Rv
n n
n H
n n
a n
n n
Location
Purpose Type
C.NP.W.B *,R,BG,S
C.W.B.NP S.R.BG
C.W.B.NP S.R.BG
C.W.B.NP S.R.BG
C.W.B.PS S.ll.I.BG
C.W.NP *,M,R,BS
C.W.B.NP S,R,BG
C.W.B.NP S.R.BG
C.NP.W *,R,BG
C,B,W,NP S.R.BG
C.NP.W.B *,R,BG
C.W.NP S.R.BG
C.W.NP S.R.BG
C.W.B.PS S.R.M
C.W.B.PS S,R,M
C,W,B,NP S.R.BG
C.W.B.PS S,R,M
C.W.B.NP S.R.BG
C.W.B.PS S.U.M.I
C,W,B,NP S.R.BG
C.W.B.NP S.R.BG
C.W.B.NP S.R.BG
Biological
Type Freq.
FT P
FT P
FT P
FT P
FT P
FT P
FT P
Chemical
Type Freq.
M.N.S.M Mo
n,0,N,S,M Mo
D.O.N.S.M Mo
D,0,N,S,M Mo
n,0,N,S,M Mo
n,0,N,S,M Mo
D,O,N,S,M MO
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D.O.N.S.M Mo
D.O.N.S.M Mo
n,0,N,S,M Mo
D,0,N,S,M Mo
D.O.N.S.M Mo
n,0,N,S,M Mo
n,0,N,S,M Mo
n,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,n,N,S,M Mo
I
Conf igutation
Single/Paired
Si
Si
Pa
Pa
Si-
Si
Si
Si
Si
Si
Si
Pa
Pa
Si
Si
Si-
Si
Si
Si
Si-
Si
Si
1
Flow
Meas.
i
Yes
Stream
Lake
S
s
S
S
S
<;
<;
s
s
s
s
S
s
S
S
s
s
S
s
S
S
S
-------
12
Table 2(cont'd) MINNESOTA FIXED STATION MONITORING ANALYSIS MATRIX
tation
umber
B-4.5
WAN-8.6
WAN-4.1
C-17
C-lll
E-ll
0-10
D-24
R-1.2
E-300
E-403
:E-452
BT-6
SK-4.4
T-l
)T-49
IL-0.2
11-23
5K-1.8
FMB-19
1CS-121
iA-12
Basin
MISS.Rv
H H
H n
SAINT
CROIX R
n
n
CEDAR R
n
H
RED Rv
n
n
n
n
n
n
n
n
n
n
u
RAINY R
Location
Purpose Type
C.W.B.NP S.R.BG
™»» 9 99
C.W.NP S.R.BG
C,W,NP S.R.BG
C.NP.W *,R,BG
C.B.W.NP S.R.BG
C,W,B,NP S.R.BG
C.W.B.PS *,R,M
C.W.B.NP S.R.BG
C.W.B.PS S,M,R
C.W.B.NP *,U,M,I
C.W.B.NP S,BG
C,W,NP,B S.R.BG
C.W.NP.B S.R.BG
C.W.B.NP S,R,BG
C,B,W,NP S.R.BG
C.B.W.NP S.R.BG
C,B,W,NP *,M,I,U
C.B.W.NP S.R.BG
C.W.B.NP S.R.BG
C,W,B,NP S.R.BG
C.W.B.NP S.R.BG
C.W.B.NP M.I.R
Biological
Type Freq.
FT P
FT P
FT P
FT P
FT P
FT P
FT P
FT P
Chemical
Type Freq.
n,0,N,S,M,P*H Mo
D.O.N.S.M Mo
D,0,N,S,M Mo
n,0,N,S,M Mo
D,n,N,S,M Mo
n,0,N,S,M Mo
n,n,N,s,M MO
n,0,N,S,M Mo
n,0,N,S,M Mo
n,n,N,s,M MO
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,n,N,S,M Mo
D,0,N,S,M Mo
P,0,N,S,M Mo
n,0,N,S,M Mo
D,0,N,S,M Mo
n,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
Conf iqutation
Single/Paired
Si
Pa
Pa
Si
Si
Si
Si
Si-
Si
Si
Si
Si
Si
Pa
Si
Si
Si
Si
Si
Si
Si
Si
Flow
Meas.
Yes
Str
Lak
s
S
S
s
S
S
s
s
s
s
s
s
s
s
s
1
1
s
s
s
s
1
s
s
s
-------
13
Table 2 (cont'd) MINNESOTA FIXED STATION MONITORING ANALYSIS MATRIX
tat ion
umber
A- 83
A- 86
\-10
UJ-0.1
M
>-0.1
•-0.5
:-0.5
Basin
RAINY R
n
n
n
n
n
M
n
Location
Purpose Type
C.W.B.NP *,U,BG
C,W,B,NP S.R.BG
C.W.B.NP S.R.BG
C,B S.BG
C,B S,BG
C,B S.BG
C,B S,BG
C,B S,BG
Biological
Type Freq.
FT P
Chemical
Type Freq.
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,S,M Mo
D,0,N,M,S Mo
Configutation
Single/Paired
Si
Si
Si
Si
Si
Si
Si
Si
Flow
Meas.
Stream
Lake
S
S
S
S
S
S
S
S
* Metals are not used as an indicator of long term water quality trends.
-------
14
Legend for Table 2 - Minnesota Fixed Station Monitoring Analysis Matrix
Location
Purpose
C -
W -
B -
PS -
NP -
Type
*
S -
R -
U -
I -
M -
BG -
Conditions and Trend Assessment
Water Quality Standards Attainment/Maintenance
Basin Status
Point Source
Non-point Source
National Core Network Station
State Network Station
Rural
Urban
Industrial Dischargers
Municipal Dischargers
Background
Variables
Biological
FT - Fish Tissue
Chemical
D - Dissolved Oxygen
0 - Oxygen Demanding
N - Nutrients
S - Solids
M - Metals
R - Radiochemical
Frequency
Mo - Monthly
Y - Yearly
P - Periodically
Configuration
Si - Single
Pa - Paired
-------
15
Table 3. Routine Water Quality Monitoring Parameters
Monthly Analysis at all Stations
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
STORE! Codes
00010
00300
00310
31613
31633
31639
00530
00400
00095
00630
00665
00625
00610
00605
Description
Temperature-C0 -field
Dissolved Oxygen-field
BOD5
Fecil Coliform
E. Coli
Enterococci
Suspended Solids
PH
Conductivity
Nitrite + Nitrate (N02+N0,)
Total Phosphorus
Total Kjeldahl Nitrogen
Ammonia Nitrogen (NH-)
Organic Nitrogen
B. Additional Monthly Analyses at Selected Stations
1.00940
2. 32730
3.
4.
5.
6.
7.
8.
01051
00910
00929
00945
00958
00076
9. 80082
10. 00335
11. 00680
12. 70507
13. 00615
14. 00500
15. 00505
16. 00535
Chloride at RE-300, RE-403, RE-452,
RE-536, OT-1, OT-49, RL-0.2, RL-23,
SK-1.8, TMB-19, WF-22, WF-27, BV-4,
SLB-b-1, GB-4.5, SW-8.6, SW-4.1, RBT-6,
WSK-4.4, EKC-18, CDR-12.8
Phenols at RA-12, RA-83, RA-86, ROS-121,
WR-1, RP-G.l, BF-0.5, LF-0.5, BAU-0.1,
WF-22, WF-27
Total Lead at BV-4, SLB-1
Calcium (as CAC03) at BV-4, SLB-1
Total Sodium at BV-4, SLB-1
Total Sulfate at BV-4, SLB-1, GB-4.5
Reactive Silicate at BV-4, SLB-1
Tubidity at GB-4.5, SW-8.6, SW-4.1, RBT-6,
WSK-4.4, EMC-18, CDR-12.8
BOD5-Carbonaceous at GB-4.5
COD at GB-4.5
TOC at GB-4.5
Ortho Phosphorus at GB-4.5
Nitrite at GB-4.5
Total Solids at GB-4.5
Total Vol. Solids at GB-4.5
Dissolved Vol. Solids at GB-4.5
-------
16
Table 3 (cont'd)
C. Quarterly (January. April, July and October} Analyses at Peat
Stations (WF-ZZ, WF-27)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
00410
00076
00080
00945
01002
01027
01034
01042
01900
01051
01067
01092
00910
00920
01105
01037
01045
01055
Total Alkalinity
Turbidity
Color
Total Sulfate
Total Arsenic
Total Cadmium
Total Chromium
Total Copper
Total Mercury
Total Lead
Total Nickel
Total Zinc
Total Calcium
Total Magnesium
Total Aluminum
Total Cobalt
Total Iron
Total Mangenese
-------
17
Table 4 Minnesota Network Stations Groupings Based on Pollution Sources
Group I - Non-Point Sources/Rural
UM-698
UM-714
UM-738
UM-895
UM-914
UM-930
UM-982
UM-1172
UM-1186
OT-49
BAU-0.1
CD-24
ME-403
RA-12
RA-86
Group II
UM-714
UM-738
UM-895
UM-914
UM-930
UM-982
UM-1172
UM-1292
CRN-6
RUM-34
RCS-121
RA-86
WR-1
BF-0.5
Group III
UM-815
RWR-1
SR-1.2
Group IV
WF-2.7
SWAN-8.6
EMC-18
RBT-6
UM-1292
UM-1365
SA-0
CRN-6
RUM-34
CA-13
BV-4
SL-110
WF-22
KA-10
KE-11
SK-1.8
RCS-121
WSK-4.4
- Homogenous -
General Water
CA-13
BV-4
SL-9
SL-38
SL-110
WF-22
WF-27
MI-3.5
MI-64
MI-88
RBT-6
OT-1
RL-23
TMB-19
- Point-Source
UM-826
ST-18
RE-300
WF-27
MI-64
MI-88
MI-133
MI-196
MI-288
BE-0
EMC-18
PT-10
SC-111
RL-23
RP-0.1
LF-0.5
RA-83
CO-0.5
LPR-3
WWR-2.6
RT-3
VR-32.5
GR-4.5
SWAN-8.6
SWAN-4.1
SC-17
RL-0.2
WR-1
RE-300
RBT-6
OT-1
Background, Recreation, Fishing and
Quality Conditions
MI-133
MI-196
MI-288
BE-0
EMC-18
CDR-12.8
PT-10
CO-0.5
LPR-3
WWR-26
RA-83
BAU-0.1
RP-0.1
LF-0.5
, Urban, Municipal
SL-9
ZSF-5.7
RL-0.2
RT-3
VR-32.5
GR-4.5
SWAN-8.fi
SWAN-4.1
SC-17
SC-111
KE-11
CD-24
RE-403
WSK-4.4
OT-49
SK-1.8
and Industrial
MI-3.5
.CD-10
RA-12
- Paired Stations', Upstream and Downstream
WF-22
SWAN-4.1
CDR-12.8
WSK-4.4
-------
-18-
IV. Statistical Analysis
The purpose of the statistical analysis is to determine if trends in the selected
water quality indicators have occurred from 1977 through 1986. A trend is defined
as a series of observations which exhibit a steady increase or decrease over time.
Thus, the selected procedures are used to differentiate random fluctuations from
those change patterns which have sufficient directional consistency to be trends.
This section describes the data and the statistical procedures used for the trend
analyses. An exemplary case is provided in the appendices.
The information employed are from the STORET data base. STORET, a information
management system of the U.S.E.P.A., contains water quality data from more than
200,000 water quality sampling stations in river basins. The data are from January
1977 through December 1986. There were 75 stations eligible for the analysis.
Several stations could not be used due to missing information. A potential trend
was only assessed if for the water quality indicator there was at least 75 per
cent data completeness. Because the data sufficiency criteria was applied separately
per variable, stations often have trends measured for fewer than all the indicators.
The indicators were chosen due to relatively complete information for the period as
well as being representative of water quality. The water quality indicators were:
STORET CODE Water Quality Indicator
00095 Conductivity at 25° Centigrade
00300 Dissolved Oxygen
00530 Total Suspended Solids
00625 Total Kjeldahl Nitrogen
00630 Total N02 * N03 (Nitrate and Nitrite)
00671 and 00665 Total Dissolved Phosphorous
00940 Total Chloride
31613 Fecal Coliform
00610 Ammonia
There were several statistical procedures used to measure environmental trends.
The initial consideration was whether the stations' data distributions reasonably
approximated the normal distribution. The skewness and kurtosis coefficients
indicated that the stations' data distributions were not normal. Non-parametric
rank order statistical procedures were used to demonstrate trends because the
kurtosis coefficients were not within +/- .25 and the skewness coefficients were
not within +/- .50. The two ranges are the generally accepted values within
which the coefficients must be within to consider a distribution to be normal.
Both Spearman's rho and Kendall's tau were used to support conclusions. A trend is
said to exist if both statistics have statistically significant results at the 90
per cent level. Both statistics have approximately 91 per cent power efficiency.
The two approaches are briefly discussed below:
Spearman's rho - Spearman's rho is one of the most widely used measures of association
for rank ordered data. The initial step is to rank the values of the selected
water quality indicator (from lowest to highest) and the time variable (year). The
computational formula is:
—-. di;
rs • " ' ^
-------
-19-
where: n = number of measurements in the sample and d^ = an individual difference
between ranks.
Kendall's tau - Kendall's tau, like Spearman's rho, requires ranked data for at least
two variables and measures the level of association between sets of rankings. The
range of possible values is plus or minus one. The computational formula is:
i = n i = n
tau = i = 1 i = 1
n (n + l)/2
= n
where
i = n
&
i ii
^ (K.J + ) = number of pairs ordered in the same way as the years; and
: i =1
i~) = number of pairs not ordered in the same way as the years.
The next step in the analytical process is to use ordinary least squares regression
to demonstrate trend strength for those trends suggested by the nonparametric corre-
lations. Trend strength for this discussion is the average level of change among
years. Admittedly, the data are not amenable to ordinary least squares linear
regression analysis according to statistical theory. However, for the mere purpose
of line fitting to determine average annual change the procedure is sufficient. The
computational formula is:
SSyy
r =
\j SSyySSxx
where: SS = sum of squares.
The results of the linear regression procedure are shown on the trend graphs in the
appendix. The availability of the graphics permitted a final trend verification
procedure. The graphs were individually examined and a trend was retained only if
the following somewhat subjectively applied criteria were satisfied:
1. The statistically significant annual trends did not visually appear to be minimal
within years; and 2. The trends were not mainly due to abrupt but discontinued change
rather than a persistent pattern. Several statistically significant trends were de-
leted due to the visual examination.
-------
20
V. Results
1. Seven Year Trend Analyses Summaries
The following parameters and corresponding stations which have shown
trends as indicated by the statistical analysis of the data in STORET
are listed in Table 5.
All of the stations monitor basically the same parameters listed below.
The following is a brief summary of these parameters and associated
trends.
Conductivity (umhos/cm) @ 25°C 100095
Conductivity is a measurement of the resistance of a solution to electrical
flow which is related to the content of ionized salts in water. This
parameter also indicates the degree to which dissolved solids contribute
to the overall water quality. An increasing trend for this parameter may he
due to potential problems associated with solids loading and non-
point source problems. Only two (2) stations exhibited conductivity
trends. Two stations showed decreasing trends.
Dissolve Oxygen (mg/1) 100300
Dissolved oxygen concentration is an important indicator of existing
water quality and the ability of a waterbody to support a well-balanced
aqquatic fauna. Water should contain sufficient dissolved oxygen to
maintain aerobic conditions in the water column to maintain a good fish
population. Due to seasonal and diurnal fluctuations, dissolved oxy-
gen values measured at monitoring stations provide at best an aprox-
imate value of actual dissolved oxygen concentration in existence.
Three (3) showed positive dissolved oxygen level trends. Only two stations
exhibited decreasing trends. The remaining stations did not indicate any
statistical trends.
Total Suspended Solids (mg/1) JE00530
Total suspended solids (TSS) is the amount of organic and inorganic
particulate matter in the water. An increase in TSS has been found to
adversely affect fish population, growth rate, fish food source, development
of fish eggs and larvae as well as the esthetics of the waterbody for
swimming. Seven stations showed an increase and none showed decreasing
trends for this parameter.
Total Kjeldahl Nttrbgen {mg/1) 100625
Total Kjeldahl Nitrogen which measures organic nitrogen and ammonia
concentrations is indicative of increased loadings from municipal and
industrial facilities. The trend for these parameters were positive
-------
21
for two stations (increasing). Eight stations showed decreasing
trends which indicated an improvement of water quality at at those
sites.
Nitrates and Nitrite (mg/1) #00631
The Nitrate and Nitrite ions are formed from the breakdown of ammo-
nia which may enter the waterbodies via municipal and industrial
discharges, septic tanks and feedlot discharges. These ions are also
indicative of the stage and degree of nitrification. There were
increasing trends at two stations.
Phosphorus-Dissolved Ortho #00671 & Total Phosphorus #00665 in (mg/1)
The total dissolved phosphorus concentrations are indicative of the
nutrient loadings received by the stream. It has been determined
that high phosphorus concentrations are associated with accelerated
eutrophication of waters, especially in lakes and reservoirs. Most of
the Minnesota network stations did not show substantial trends for
this parameter. One station showed an increasing trend.
Total Chloride (mg/1) #00940
Chloride in the form of chlorine ions is present in lakes and rivers.
The chloride concentrations in streams may show an increase due to in-
creased industrial and sewage treatment plant effluents and septic
tanks and other non-point source discharges, such as road salting and
natural occurrences. This parameter showed an increasing trend in one
station and a decreasing trend in one.
Fecal Coliform Bacteria (m-cagar/100 ml) #31613
Microbiological indicators are used to determine the safety of water
for drinking, swimming and shellfish population growth. The fecal
coliform is the primary indicator of fecal contamination in a water-
body. An increasing trend for this parameter is a result of poor chlo-
rination of municipal treatment plant discharges, feedlot effluents
and leakages from septic tank fields. For the period of this study
only one station indicated an increasing trend.
-------
22
Ammonia (mg/1) #00610
Un-ionized ammonia (NH3) which has been shown to a toxic form of
ammonia for aquatic life. Ammonia was reported to be acutely toxic
to freshwater organisms at concentrations ranging from 0.083 to 4.60
mg/1 NH3 for many fish species. This form of ammonia pollution is
usually due to municipal waste water treatment plant discharges and
other point sources of pollution. Six stations showed decreasing
ammonia levels.
-------
23
Table 5. Parameters Showing Increasing and Decreasing Trends
with corresponding Station Numbers
1. Conductivity #00095
Increasing Trend Statons:
None
Decreasing Trend Stations:
SLB-1, SL-9
2. Dissolved Oxygen #00300
Increasing Trend Stations:
PT-10, SR-1.2, ZSF-5.7 (ZRS-20)
Decreasing Trend Stations:
UM-1292, UM-982
3. Total Suspended Solids 100530
Increasing Trend Stations:
UM-859, MI-133, RL-0.2, RE-403, RE-452, SL-9, RE-300
Decreasing Trend Stations;
None
4. Total Kjeldahl Nitrogen #00625
Increasing Trend Stations:
KA-10, UM-895
Decreasing Trend Station:
ZSF-5.7, UM-1172
-------
24
Table 5 (Continued)
5. Nitrate and Nitrite #00630
Increasing Trend Stations:
SR-1.2, ZSF-5.7
Decreasing Trend Stations:
None
6. Total and Dissolved Phosphorus #00671 & 00565
Increasing Trend Stations:
None
Decreasing Trend Stations:
ZSF-5.7
7. Total Chloride #00940
Increasing Trend Stations:
OT-1
Decreasing Trend Stations:
RE-300
8. Fecal Coliform Bacteria 131613
Increasing Trend Stations:
MI-64
Decreasing Trend Stations:
None
-------
25
Table 5 (Cont'd)
9. Ammonia #00610
Increasing Trend Stations:
None
Decreasing Trend Stations:
RE-452, UM-738, UM-1292, SL-9, ZSF-5.7, UM-1186
-------
26
In general, the potential pollution sources generally impact environmental
parameters and cause these parameters to exhibit increasing or decreasing
trends over a given time period. Furthermore, there is a correlation between
environmental parameter levels and point and non-point sources of pollutants.
For the purpose of this study, point sources of pollution are considered to
originate from identifiable or known sources, such as industrial or municipal
treatment plant discharges. Unlike point sources of pollution, non-point
sources are more diffuse .difficult to identify and cover large areas of
origin. Non-point sources of pollution are generally recognized to be due to:
agriculture, mining, urban runoff, silviculture and construction. Non-point
source pollution will exhibit itself in waterbodies when the rate at which
matter/pollutants entering a waterbody exceeds natural levels. As shown in
Table 6, the point and non-point sources of pollution are generally associated
with respective environmental parameters and affect the trend as indicated in
the table.
Table 6 - Environmental Parameter & Associated Pollution Sources
Environmental Trend Pollution
Parameter Change Source
Dissolved Oxygen Decrease Point
Ammonia Increase Point
Fecal Coliform Increase Point
Kjeldahl Nitrogen Increase Point
Nitrate-Nitrite Increase Non-point
Total Suspended
Solids Increase Non-point
Phosphorus Increase Non-point
-------
27
As shown in the above Table, if the trend over a given period of time
for suspended solids showed an increase at a given station, then the
station and the county where the station is located were considered
to be an increasing non-point source pollution area. Likewise, an increa-
sing trend for ammonia was regarded as associated with increase in point
Source pollution for that station and surrounding county where the station
is located. For example, point source pollution was associated with a
decreasing trend in dissolved oxygen or an increasing trend in any one of the
following parameters: Ammonia, Fecal Coliform, Kjeldahl Nitrogen . Also, non-
point source pollution was associated with an increase in any one of the
following parameters: Nitrate-Nitrite, Total Suspended Solids and Phosphorus.
In summary, any increase or decrease in a trend for a given parameter is
related to either point or non-point sources of pollution.
Thus, based on the relationships among variables in Table 6,trends and corre-
sponding pollution sources maps were plotted as shown on Figures 3 through 7.
The maps were plotted in terms of two broad pollution sources which are:
0 Non-Point Sources
0 Point Sources
For each pollution source two types of trend maps were plotted. The
first trend map shows the counties where the monitoring stations are
located. The county map shows the pollution trend in a county as deter-
mined from the statistical analysis of STORET data. A county's trend
status is shown as decreasing or increasing. As previously specified,
a positive or negative trend is said to exist if the correlation coefficients
are statistically significant with 90 % significance level. Trend directions
(positive,negative,neutral) corresponds to the signs of the coefficients. A
neutral condition is present if either of the coefficients are not statisti-
cally significant. Data are considered insufficient if 75% completeness
criteria is not met. The second trend map shows the locations of monitoring
stations on streams as well as the specific pollution trend; e.g. non-point.
The stream trend maps show arrows next to the stations with an upward pointing
arrow indicating an increasing pollution trend and a downward pointing arrow
a decreasing trend. If an arrow is not shown adjacent to a station, then
trend was not observed at that station. The observed trends for point and
non-point sources are given on Figures 3 through 6 and in Tables 6 and 7
respectively.
-------
28
1. Non-Point Source Pollution Trends
As shown on Figures 3 and 5 , nine stations exhibited increasing trends
and the rest of the stations did not show any trends. In general, non-
point source pollution showed an increase of 12 percent for the period of
this study. The stations which showed trends and locations are given in
Table 6.
2. Point Source Pollution Trends
As shown on Figure 4 and 6, five stations showed an increasing trends,
six stations showed decreasing pollution trends and the rest were un-
changed. Based on the long term trends for the fixed network stations,
the point source pollution remained relatively unchanged. The stations
which exhibited trends are given in Table 7.
In summary, water quality conditions as determined by the trend analy-
ses for the eight year period (1978-1985) were as follows: of the 75
stations analyzed 15 percent had point source pollution trends and 12
per cent showed non-point source trends respectively. Thus,only 27 per-
cent of all the stations exhibited trends.
0 Non-Point Source Pollution trend increased 12% of the stations.
0 Point Source Pollution trend increased at 8% and decreased at 7%
of the stations.
-------
29
LI
-------
30
LL^. I_. £J
LAKE
THE WOODS
BASIN
MISSISSI
"~BASIN
. -00 16
CROIX >J
RIVER
BASIN
Fig. 3-Minnesota Network
Stations Point
Source Pollution
Trends 1978-86
:SO,TA
RIVER
Routine Sompling
^v1-,-—-
DESMOINES o
*
-------
MINNESOTA
Fig.4 -Minnesota Counties
Trend Status Based
on Ambient Stations
for NonrPoint Source
Pollution 1978-86
Increasing Trend
Decresing Trend
-------
32
MINNESOTA
Fig.5 -Minnesota Counties
Trend Status Based
on Ambient Stations
for Point Source
Pollution 1978-86
Increasing Trend
Decreasing Trend
-------
33
Table 6- Non-Point Source Pollution Trends at Stations by
County and Stream Locations
River and Location
Shell Rock Rv. near Gordonsville
Minnesota Rv. @ Courtland
Zumbro Rv. S.Fork @ Rochester
Mississippi Rv. 0 Minneapolis
Red Lake Rv. @ E. Grand Forks
Red Rv. @ Moorhead
Red Rv. West of Perley
St. Louis Bay, Fondu-Lac
Red River @ Grand Forks
STORET I
SR-1.5
MI-133
ZRS-20
UM-859
RL-0.2
RE-452
RE-403
SL-9
RE-300
Trend
UP
UP
UP
UP
UP
UP
UP
UP
UP
County
Freeborn
Nicolet
Olmsterl
Hennepin
Polk
Clay
Norman
St. Louis
Polk
-------
34
Table 7- Point Source Pollution Trends at Stations
by County and Stream Locations
River and Location
Mississippi River, E. of Bemidji
0 Camp Riley
@ Monticello
Minnesota " 9 Court!and
Kawishiwi " 9 Birch Lake
Zumbro Rv. S.Fork @ Rochester
Pomme de Terre Rv. @ Appleton
Mississippi Rv. SE of Minneiska
St. Louis Bay @ Fond du Lac
Red River @ Moorhead
Shell Rock Rv. @ Grand Forks
STORET #
UM-1292
UM-982
UM-895
MI-64
KA-10
ZRS-20
PT-10
UM-738
SL-9
RE-452
SR-1.5
Trend
UP
UP
UP
UP
UP
DOWN
DOWN
DOWN
DOWN
DOWN
DOWN
County
Beltrami
Morrison
Sherburne
Sibley
Lake
01 fisted
Swift
Winona
St. Louis
Clay
Freeborn
-------
35
VI. Conclusions and Recommendations
0 Because non-point source pollution has shown an increase at 12% of the
stations expanded programs for non-point source monitoring and pollution
controls are recommended.
0 Establish stations at locations on the same stream where water
quality is high and low to conduct bioassays to be used for reference
purposes.
0 Biological monitoring on a routine basis is non-existent. It
would be highly desirable to conduct biomonitoring on impacted
areas at least on an annual basis.
0 If a station appears not to be representative of water quality,
then investigate the possibilty of eliminating it or moving it to
a more representative location.
0 Establish stations or add variables to existing stations to
measure toxics' impact at such locations.
0 Chemical variable coverage is rather limited, expanded moni-
toring for other suspected toxic metals and organics would he
helpful.
0 The stations which did not exhibit trends and did not have high
pollution levels may be worth investigating for relocation or
elimination.
0 MPCA would benefit from shared monitoring of waterways with
neighboring states to reduce duplication of monitoring efforts
with the help of USEPA.
-------
Appendices
-------
Appendix A
Statistical Analysis - Exemplary Case
-------
The appendix contains an illustration of the manner in which the statistical
procedures in the statistical analysis section were performed. The calculations
are done with the SAS (Statistical Analysis System) STORET programs. The
example shows the results for station RL-0.2.
The first program and its accompanying output is designed to integrate SAS with
STORET. Line 20 allows the use of SAS. Lines 30 through 90 identify the
STORET stations, water qaulity variables, and the time frame. The variable
Y, defined on line 190, is the trend (time) variable.
The STORET output provides stream quality measurement information as well as
station number and location. The numbers of measurements per variable per year
also are shown. The most important SAS output for this report are the Spearman
and Kendall correlation matrices. In this case trends were found for ph (P3),
organic nitrogen (P7), total kjeldahl nitrogen (P9) and fecal coliform (P12).
Only the variables P9 and P12 were used as water quality indicators in the
report. The above listed variables were viewed as having definitive trends be-
cause the probabilities were .100 or lower for each of the variables correlation
coefficients with the variable Y (the probabilities are shown by the numbers
immediately below the coefficients). As previously indicated, because a station
may not have a sufficient number of measurements for every water quality variable,
it often was not possible to derive conclusions from the statistical analyses
for certain water quality characteristics used as indicators. (See Program 1
and Output 1).
-------
Progran 1
f RETRIEVAL DATE 86/12/08 ECHO OF ORIGINAL REBUEST
OOOOOCIO PGM*INVENT,PUPP=106/EPA,PRT«>«0,
OGOOOC20 MCSE-SAS,
0030CC3C H:AC=ST ATE.A»?IEM.NETWORK.MINN,
000001*3 HEAD.MIKN FISCAL YEAR 1986,
COPOOC50 A«21MINN,
00000060 5-RL-O.^,
OOOCOOTC P=95,P*300,P=530,P«60,P-9*0,P«310,P«605.P«610,P«625,
00000080 P«636,P=645,P«31615,
OOOOOC9C BD»789101,ED=9S1231,
OOOOflOO MOECHO,
OOOCOMO SASPARMS'BEGIN,
000001:0 »:
00300138 OPTIONS S*72 LS«131:
000001*0 DATA LU3IN;
00030153 *
C0000160 INCLUDE=
PREVIOUS KETUORO PEPLAC5D BY -
* MACRO (FCFREAD) - SAS - BEADS STORET MORE=3,4 t SAS FCF FORMATS
*
* WRITTEN BT LEE MANNING LAST MODIFIED BY LEE MANNING 4/25/54
*
* FUNCTION -
BREAKDOWN A STORET M?RE«4 CMCRE»3 OR MORE-SAS) FCF FILE
INTO ITS ELEMENTS FOR SUBSEQUENT PROCESSING BT ANY SAS
PR3CEDUPES :
OPTIONS NOSOURCE:
* R:F - THE STCRET ADVANCED RETRIEVAL MANUAL UNDER PROGRAM
«RET« FOR A DETAILED DESCRIPTION oe THE noRE«3,4 t SAS
RSCOKD FORMATS.
NOTE - THIS ROUTINE DECODES DOUBLE-CHARACTER REMARK COSES
STOȣ0 WITH USGS DATA, AS DESCRIBED WITHIN THE DATASET
•STORET.HEL'.USGS.REMARKS'
*:
FCSNAT DAT£ YYM"OD9.:
FORMiT TIM; MH^Mj.;
FORMAT DEPTH S6.:
FORMAT SMr *8.:
FOB«AT UMK *i KX-RSO:
INFILE FCF LENGTH«L:
FORMAT ("ORE $3.:
RETAIN MORE •3i5
IP _w_»i THEN Da: INPUT 924 MOR= si. a:
IF f»^S£»«9« THEM MORi-'SAS*;
POT « •:
PUT »»IOTE: FCF FORMAT is MORE«« MORE:
IF MORE-'3» TM£N 001
PUT • P.EMARR CCOES. DEPTH INFORMATION, »ND COMPOSITE1:
PUT • SAMPLE DESCRIPTORS WILL BE MISSING.*:
A-2
-------
Program 1 (continued)
PUT • «:
END: END:
INPUT 326 YYDLIM S2. 3 ;
IF L-305 I L-350 f L»7S I L»120:
* OMITS PARAMETER HEADERS AND STATION HEADERS :
IF YYOLTM-«»99': « 0»ITS DELIMITER RECORDS ;
INPUT 31 AGENCY $8. at STATION SIS. 326 DATE YTMMDD6.
3?2 KHR »2. KMN *2.
336 0 THEN REMOAT£»MOY(RMM,RDD,RTT);
SUP: If RHRtO>:
STATION«A>ENCT!I« MISTATION;
DC OVER P; IF p > o. t P < l.E-15 THEN P«. ; END;
IF AGENCT-«112«RO« THEN 00;
USGSRHKxNUMSER; * USCS •SAMPLE' RKK COOE :
NUMBER-* •;
END;
IF REMOAT5 •« . t
PUT(DAT£,YT*M006.>IIKHR!!KMN <- PUTCREMDATE.TYMMC06.)!IRMR!IRMN
THEN 00;
BEGDATE*OATE;8EGTIMr«TIME;ENOOATE«REMOATE;=NDTIME«RE»«TIME;
END:
IF REMDATE •« . t
PUT(D»T£.TTMMDD6.)IUHRHKMN > PUT(REMOATEf TTMMOC6.)! I »HR| |RMN
THEN DO:
BEGDATE«*EMOATE;S£GTI*E«REMTIME;ENDDATE-DATE;ENOTI*E»TI*E:
END;
CROP KHR KMN RTT RHM ROD RHR RMN REMDATE REKTINE TTDLIM I ;
OPTIONS SOURCE;
*
*
SOURCE LISTING SUPPRESSED
CFULL 59U«C£ - •STORET.HSLP.FCFREAO*)
*
*
DEFINITION OF VARIABLES CREATED BY MACRO CFCFREAO)
PORE - 3 CHAR COOE C*3*t*4*, OR *SA$*>
AGENCY - C CHAR STOREY AGENCY COOE
STATION - 24 CHARACTERS
• - STORET AGENCY COOE
i - BLANK
15 - STORET PRIMARY STATION IDENTIFIER
DATE - SAMPLE DATE CSAS DATE FORM)
tIKE - SAMPLE TIME CSAS TIME FORM)
DEPTH - 6 CHAR SAMPLE DEPTH • IEMARK
A-3
-------
Progran 1 (conti
KEDIA - 8 CHAR SAMPLE MEDIA CODE.
SMK - 8 CMA8 SAMPLE SMK CODE.
UMK - 8 CHAR SAMPLE UMK CODE.
P1-P50 - 50 FLOATING POINT NUMBERS.
VALUES Of SO PARAMETERS.
Rl-RSO - 50 1 CHAR STORET RMK COOES
USCSRMK - I CHAR USGS 'SAMPLE* RMK CODE
BEGDATE - COMPOSITE SAMPLE BEGINNING DATE
MGTIM? - COMPOSITE SAMPLE BEGINNING TIME
ENOOATE - COMPOSITE SAMPLE ENDING DATE
ENCTINE - COMPOSITE SAMPLE ENDING TIME
TTPE - CO-POSITE SAMPLE TYPs (STB)
CALC - COMPOSITE SAMPLE CALC CODE (AHLN)
- COMPOSITE SAMPLE NO. Of GRABS COR «C'>
EARNING
MACRO <*CFREAD> CONTAINS A "DROP" STATEMENT.
USERS MAT -NOT- USE THE "KEEP" STATEMENT.
MACRO (FCFR.EAD) - END-OF-XACRO
END OF REPLACE
00000160
00000170
OOC001SO
OOC00190
OOCC0290
0000021C
00000220
00000230
000002*0
OC000250
00000260
occcr;7o **ROUTE PRINT MOLD
00000280 »*JC8PARM LINE5*30
SAS DIAGNOSTICS (IF ANT) WILL BE PRINTED BELOW *
-OTR(OATE):
T«TEARCCATe>;
PPOC SORT; BT AGENcr STATION:
PPOC CORK S**EARM«N KENDALL DATA-LUBINC
VAR PI FZ P3 P4 PS P« P7 P8 f9 P10 Pll P12 TJ
*;
STOPSAS*
./LML JO!
-------
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-------
Output 1 (continued)
STORET RETRIEVAL DATE 86/12/08
1 TOTAL STATIONS PROCESSED
STATE.AMBIENT.NETWORK.*INN
MINN FISCAL TEAR 1986
PGM*IN¥ENT
CROSS
STA BE6 STA END • OF DBS f OF SAMPLE
<1967 0
1967 0
1968 0
1969 0
1970 0
1971 0
1972 0
1973 0
1974 0
1975 0
1976 0
1977 0
1978 1
1979 0
1980 0
1981 0
1992 0
1983 0
198* 0
1985 0
1*86 0
TOTAL 1
STA END-PERIOD OF RECO IN TRS
<3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
108
109
99
89
80
81
77
86
0
729
0
0
0
0
0
0
0
0
0
0
0
0
IZ
11
10
9
»
9
»
9
0
78
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
A-6
-------
Outpjt 1 (continued)
P2
P)
PS
P*
PT
PI
P10
P12
S*S 13:51 7UES04T, DECEMBER 9. 11
SPE1KIUN COtRU«TI2»t COEFFICIENTS / PtOB > |R| UWDJt NO:*HO>0 / NUMBER Cf C8SC* VATICMS
P2 P3 P4 P5 P6 P7 P« P9 P10 Pll P12
1.00000
0.0033
T7
0.01472
0.4157
76
o.ioia:
0.3712
TT
3.51121
0.0014
41
0. 52614
0.0001
T5
0.18636
0.1070
7*
0.233)1
0.0364
TT
0.01253
0.9139
TT
0.231T2
0.0*54
64
0.0*790
0.3961
TT
•0. 10533
0.3619
TT
0.14375
0.2422
41
0.12635
0.27)5
TT
-0.09472
0.415T
T4
1.00000
0.0006
TT
-0.5432S
0.0001
T6
0.07703
0.6322
41
-0.14191
0.227*
T4
-0.00*92
0.9*66
TS
-0.26617
0.0119
TT
0.21 8*3
0.0561
TT
-0.171T2
0.1749
44
0. 20 795
0.0694
TT
-0.49210
0.0001
TT
-0.10703
0.3*50
41
-O.OT011
0.5444
TT
-0.101(2
0.3712
TT
-0.5*325
0.0001
T*
1.00000
0.0000
TT
0.57)91
0.0001
41
0.06922
O.S551
75
0.41137
0.0002
T6
0.57416
0.0001
77
-0.21143
0.0649
TT
.,0.41274
0.0001
44
0.05129
0.4145
TT
0.71451
0.0001
TT
-0.04771
o.sm
41
0.23447
0.331*
77
-0.51129
0.0006
41
0.07703
0.6322
41
0.57991
0.0001
41
1.00000
0.0000
41
-0.55130
0.0002
40
0.16611
0.2972
41
-0.03352
0.1352
41
0.12851
0.4233
41
-0.10970
0.5781
21
0.11114
0.4419
41
0.2(341
0.0721
41
-0.01*79
0.9072
41
-0.312*2
0.0111
41
0.52614
0.0001
7$
-0.14191
0.227*
74
0.06922
0.5551
75
-0.55130
0.0002
40
1.00000
0.0000
75
0.09236
0.4331
74
0.27931
0.0152
75
-0.07221
0.5377
75
0.33617
0.0074
42
0.22147
0.0542
. TS
0.20223
0.0119
75
-0.06091
0.4267
44
0.01095
0.9257
75
-0.11636
0.1070
74
-0.00412
0.9666
75
0.41137
0.0002
74
0.16681
0.2972
41
0.09236
0.4)31
74
1.00000
0.0000
76
0.37936
0.0007
74
0.01921
0.1492
74
0.37438
0.0024
43
0.11715
0.3135
74
0.45497
0.0001
74
-0.32)44
0.0071
41
0.12585
0.2787
74
0.23831
0.0369
77
-0.2A69T
0.0119
77
0.57414
0.0001
77
-0.03352
0.1352
41
0.27931
0.0152
7S
0.37936
0.0007
74
1.03000
0.0000
70
0.02424
0.1)32
70
0.91527
0.0001
45
0.2591)
0.0220
71
0.49049
0.0001
70
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0.1607
41
O.J4082
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0.01251
0.9139
77
0.21143
0.0561
TT
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0.5377
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0.01921
0.1492
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0.02424
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70
1.00000
0.0000
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0. 31782
0.0010
45
0.44417
0.0001
70
0.03343
0.7714
70
0.12417
0.310)
41
-0.11575
0.10)5
71
0.23172
0.0654
64
-0.17172
0.1749
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0.4I2T4
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-0.10978
0.5781
21
0.33617
0.0074
42
0.37438
0.0024
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0.91527
0.0001
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0.39782
0.0010
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I. 00000
0.0000
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0.54084
0.0001
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0.5374S
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0.1545
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0.3)418
0.0065
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0.01790
0.3161
77
0.20795
0.0691
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0.05829
0.6145
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0.11814
0.4619
41
0.22147
0.0562
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0.11715
0.3135
74
0.25913
0.0220
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0.64417
0.0001
78
0.54016
0.0001
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1.00000
0.0000
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0.29147
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0.14428
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0.06418
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0.3619 0.2422
77 68
-0.49210 -0.10703
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77 68
0.71451 -0.06771
0.0001 0.5833
77 48
0.28369 -0.01879
0.0723 0.9072
41 41
0.20223 -0.04098
0.0819 0.4267
75 44
0.45497 -0.32344
0.0001 0.0071
74 48
0.49049 -0.17203
0.0001 0.1607
71 68
0.03343 0.12487
0.7714 0.3103
78 68
0.5)765 -0.19371
0.0001 0.1565
45 55
0.29197 0.14428
0.0095 0.2405
78 48
t. 00000 -0.11123
0.0000 0.3445
T8 48
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0.3665 0.0000
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0.13812 -0.34748
0.2278 0.00)7
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0.1263
0.273
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0.544
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0.2364
0.038
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0.92!
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0.271
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0.3401
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0.103
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0.33*
0.00
0.064
0.57
0.138
0.22
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A-7
-------
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Appendix B contains linear regression plots of water quality variables at
the monitoring stations which showed statistically as well as suhstantively
significant water quality trends. The plots were obtained by using the
Water Quality Analysis Branch's Browse interactive program. On each figure
the data are plotted in terms of the measured variable's value verse time.
The dotted line on graphs indicates the predicted bivariate linear regression
line for the period of measurement.
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