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ASTM Selected Technical Papers
Water Quality Parameters
By
S Barabas
S Barabas
1
Head
, Analytical Methods Research Section,
Canada Centre for Inland Waters
,
Burlington, Ontario,
Canada
, general chairman
Search for other works by this author on:
ISBN-10:
0-8031-5526-3
ISBN:
978-0-8031-5526-8
No. of Pages:
590
Publisher:
ASTM International
Publication date:
1975

A large data system is one which is hard to turn off. This inertia is directly proportional to the amount of money invested in hardware and facilities, to the number of careers involved, and to the length of record.

Large data systems are concerned with the collection of time series. What eventually will become a data management problem in a large data system using manual techniques quickly becomes a crisis with automatic equipment. It is accordingly essential in the design of continuous monitoring networks that the utilization of the data be adequately considered and optimized.

The arguments for optimization of time-series collection, analysis, and utilization apply equally to space fields. In either case, the problem is to match the resolution of the data collection system to that of the response system. For example, the digitizing or averaging period used for pollution detection should be consistent with the time constant for pollution control or abatement measures.

The institutional value of monitoring programs may be equally important, but is more difficult to predict. In any event, the analysis and interpretation of the data must correspond to the real world use to which it will be put.

1.
Gunnerson
,
C. G.
,
Journal, Sanitary Engineering Division, Proceedings of the American Society of Civil Engineers
, Vol.
92
No.
SA2
,
1966
, pp. 103–125.
2.
Gunnerson
,
C. G.
,
Water Pollution Research
, Vol.
3
, No.
2
,
1967
, pp. 491–504.
3.
Gunnerson
,
C. G.
in
Proceedings
, IBM Scientific Computing Symposium on Water and Air Resources Management, 23–25 Oct. 1967,
IBM Data Processing Division
,
White Plains, N.Y.
1967
, pp. 115–140.
4.
Continuous Water Pollution Surveillance Monitoring, Potomac River at Washington, D.C., July 19, 1963–December 31, 1964
,”
Water Quality Activities, Division of Pollution Surveillance, F.W.P.C.A.
,
Cincinnati
,
1965
.
5.
Gumbel
,
E. J.
, “
Statistical Theory of Extreme Values and Some Practical Applications
,” No. 33, Applied Mathematics Series,
National Bureau of Standards
,
Washington, D.C.
,
1954
.
6.
Water Pollution Surveillance System Annual Compilation of Data, October 1, 1961–September 30, 1962
,” Publication No. 663,
U.S. Public Health Service
,
Washington, D.C.
,
1962
.
7.
U.S. Public Health Service Water Pollution Surveillance System Annual Compilation of Data, October 1, 1962–September 30, 1963
,” Publication No. 663, Vols.
7
and
8
,
U.S. Public Health Service
,
Washington, D.C.
,
1963
.
8.
Quality of Surface Waters of the United States, 1958-Parts 1–4: North Atlantic Slope Basins to St. Lawrence River Basin
,” Water Supply Paper 1571,
Geological Survey, U.S. Department of the Interior
,
Washington, D.C.
,
1958
.
9.
Carter
,
R. W.
,
Anderson
,
W. L.
,
Isherwood
,
W. L.
,
Rolfe
,
K. W.
,
Showen
,
C. R.
, and
Smith
,
W.
, “
Automation of Stream Flow Records
,” Circular 474,
Geological Survey, U.S. Department of the Interior
,
Washington, D.C.
,
1958
.
10.
BMD-Biomedical Computer Programs
,”
Dixon
W. J.
, Ed., Health Sciences Computing Facility,
Department of Preventive Medicine and Public Health School of Medicine, University of California
,
Los Angeles
,
01
1964
.
11.
Gunnerson
,
C. G.
,
Journal, Sanitary Engineering Division, Proceedings of the American Society of Civil Engineers
, Vol.
93
, No.
6
,
1967
, pp. 1–16.
12.
Hydrologic Data, 1963, Vol II, Northeastern California
,”
State of California
,
Department of Water Resources
, Sacramento,
1965
.
13.
Pritchard
,
D. W.
in
Proceedings
, Symposium on Environmental Measurements,
07
1964
,
U.S. Public Health Service
, Publication No. 999-WP-15,
1964
, p. 235.
14.
Gill
,
G. C.
and
Bierly
,
E. W.
,
Journal of Applied Meteorology
 0894-8763, Vol.
2
, No.
4
,
1963
, pp. 431–439.
15.
Tukey
,
J. W.
in
Proceedings
, IBM Scientific Computing Symposium on Statistics, 21–23 Oct. 1963,
IBM Data Processing Division
,
White Plains, N.Y.
,
1965
, pp. 141–152.
16.
Kneese
,
A. V.
,
The Economics of Regional Water Quality Management
,
The John Hopkins Press
,
Baltimore, Md.
,
1964
.
17.
Wastler
,
T. A.
, “
Application of Spectral Analysis to Stream and Estuary Field Surveys—I. Individual Power Spectra
,” Publication No. 999-WP-7,
U.S. Public Health Service
,
Washington, D.C.
,
1963
. This reference has been superseded by “
Spectral Analysis Applications in Water Pollution Control
,”
U.S. Federal Water Pollution Control Administration
,
1969
.
18.
Tukey
,
J. W.
in
Symposium on Application of Autocorrelation Analysis to Physical Problems
,
Woods Hole, Mass.
,
Office of Naval Research
,
1947
, pp. 47–67.
19.
Munk
,
W. H.
in
The Sea
,
Hill
M. N.
, Ed.,
Interscience Publishers, Inc.
,
New York
,
1962
, pp. 647–663.
20.
Gunnerson
,
C. G.
, and
Ozturgut
,
E.
, “
The Bosporus
,”
The Black Sea
,
Ross
D. A.
, Ed.,
American Association of Petroleum Geologists
,
Tulsa, Okla.
,
1973
.
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