EPA-600/S-74-004
January Socioeconomic Environmental Studies Series
Design of Cost-Effective
Water Quality
Surveillance Systems
Office of Research and Development
U.S. Environmental Protection Agency
Washinaton. DC 20460
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and
Monitoring, Environmental Protection Agency, have
been grouped into five series. These five broad
categories were established to facilitate further
development and application of environmental
technology. Elimination of traditional grouping
was consciously planned to foster technology
transfer and a maximum interface in related
fields. The five series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
t. Environmental Monitoring
5. Socioeconomic Environmental Studies
This report has been assigned to the SOCIOECONOMIC
ENVIRONMENTAL STUDIES series. This series
describes research on the socioeconomic impact of
environmental problems. This covers recycling and
other recovery operations with emphasis on
monetary incentives. The non-scientific realms of
legal systems, cultural values, and business
systems are also involved. Because of their
interdisciplinary scope, system evaluations and
environmental management reports are included in
this series.
EPA REVIEW NOTICE
This report has been reviewed by the Office of Research and
Development, EPA, and approved for publication. Approval
does not signify that the contents necessarily reflect the
views and policies of the Environmental Protection Agency,
nor does mention of trade names or commercial products
constitute endorsement or recommendation for use.
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January 1974
DESIGN OF COST-EFFECTIVE WATER
QUALITY SURVEILLANCE SYSTEMS
By
Charles V. Beckers
Stanley G. Chamberlain
Contract No 68-01-0703
Program Element 1BA030
Project Officer
Dr. Roger D. Shull
Implementation Research Division
Environmental Protection Agency
Washington, DC 20460
Prepared for
OFFICE OF RESEARCH AND DEVELOPMENT
US ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, DC 20460
For sale by the Superintendent of Documents, U.S. Government Printing Office
Washington, D.C. 20402 - Price $4.OS
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ABSTRACT
This report presents the development and successful demonstration of quantita-
tive methods for the design of river basin water quality surveillance systems
for pollution abatement. The methods provide a systematic approach to
the consideration of expected stream conditions, system characteristics, equip-
ment performance, and cost in the selection of a preferred system design from
among a number of candidates.
The methods are based on a systems approach in which the total system is
evaluated for cost and effectiveness. They make extensive use of mathematics
previously developed to describe the effectiveness of sampling in the context of
abatement. The analysis of candidate system performance draws heavily on
reliability and maintainability engineering technology. Data availability remains
a constraint to the general application of the methods, but acquisition of the
necessary data is wholly within the prerogatives of governmental agencies
operating monitoring systems.
The methods are computerized and the computer programs are detailed in this
report. They make use of the information available from the computerized
river basin models now under general development.
The computerized design methods are demonstrated to function satisfactorily on
the Beaver River Basin when artificial data is used to supplement the data base.
It is concluded that the methods are acceptable for use by governmental water
quality agencies under the existing constraints.
in
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This report is submitted in fulfillment of Contract Number 68-01-0703, by the
Raytheon Company, Oceanographic and Environmental Services Department,
Portsmouth, RI, under the sponsorship of the Environmental Protection Agency.
iv
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CONTENTS
Page
Preface ii
List of Figures v(
List of Tables xi
Acknowledgements xiii
Sections
I Conclusions 1
II Recommendations 3
III Introduction 5
IV Review of Previous Development 9
V Study Objective and Approach 31
VI Development of Cost-Effectiveness Methods 35
VII Design of Water Quality Surveillance Systems 87
VIII Demonstration of Design Methods 127
K Discussion 185
X References 189
XI Glossary 193
XII Appendices 195
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FIGURES
No. Page
1 General Systems Analysis Framework 12
2 Schematic Representation of Filtering (from [6]) 16
3 Handbook Task Flow Diagram (from [3]) 18
4 Conversion of Parameter Process into Violation Process
(after [3]) 22
5 Temporal Effectiveness Rating as a Function of T , T
and A (from [3]) 22
6 RIBAM Top-Level Flow Chart (from [7]) 27
7 RIBAM Program Element Relationships (from [?]) 28
8 C-E Trade-off for Fixed Effectiveness 39
9 C-E Trade-off for Fixed Cost 39
10 Unacceptable Result of Fixed Effectiveness Trade-off 39
11 C-E Ratio Approach to Candidate Selection 39
12 System Design Flow Diagram 40
13 Typical Organizational Framework 44
14 Typical Station Functional Structure 47
15 Typical Functional Frameworks for Station Illustrated in
Figure 14 47
16 Illustration of Multi-level Sub-paths 48
17 Format of Utilization Table 50
18 Illustration of Multi-Sub-path Element Path 51
19 Example Progression of Independent Violations in a Basin 61
20 Illustration of Type I and Type II Errors for Gaussian Error
Distribution with Mean (?) and Standard Deviation (
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FIGURES (Cont.)
No. Page
22 niustration of Effect of Decision Threshold, CD, on Error
Probabilities of Worst Case Condition (C(t) =CT) 65
23 niustration of Violation Types 68
24 Failure States for Typical Three-Means Element 74
25 Sample Survivability Transition Matrix 76
26 Sample Availability Transition Matrix 90
27 Design Task Flow Diagram 90
28 Program Organization 99
29 Top Level Program Flowchart 100
30 Typical Preliminary Design Output 108
31 Typical Reach-by-Reach Analysis Print-out 109
32 Typical Final Summary Page 109
33 Typical Echo Print of USGS Data Input 110
34 Typical Echo Print of System Characteristics Input 111
35 Typical Echo Print of System Reliability Input 112
36 Typical Echo Print of Availability Input Data 112
37 Typical Echo Print of Survivability Input Data 112
38 Preliminary Design Data Deck 115
39 CONTROL Card Format 116
40 USGS Card Format 117
41 CHAR Card Format 119
42 Final Design Data Deck 121
43 MTTF Card Format 122
44 AVAIL and SURV Card Format 123
45 COST Card Format 125
46 Beaver River Basin 129
vii
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FIGURES (Cont.)
No. Page
47 Stretches of River Included in Basin Subset 133
48 Basin Segmentation 138
49 Basin Stick Diagram (Mahoning River Section) 139
50 Basin Stick Diagram (Shenango-Beaver Section) 140
51 USGS Gaging Stations in the Beaver River Basin 142
52 Preliminary Design Data for Dissolved Solids 143
53 Preliminary Design Data for Cyanides 143
54 Preliminary Design Data for Phenols 144
55 Preliminary Design Data for Dissolved Oxygen 144
56 Overall System Organizational Framework Assumed for All
Candidates 148
57 Ohio System Organizational Framework Assumed for
Candidate 1.0 148
58 Pennsylvania System Organizational Framework Assumed
for Candidate 1.0 149
59 Functional Framework for Candidate 1.0 150
60 Ohio System Organizational Framework Assumed for
Candidate 2. 0 159
61 Pennsylvania System Organizational Framework for
Candidate 2.0 159
62 Functional Framework for Candidate 2.0 160
63 Additional Ohio Organizational Framework Assumed
for Candidate 2.3 179
64 Additional Pennsylvania Organizational Framework
Assumed for Candidate 2.3 179
viii
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FIGURES (Cont.)
No.
65 Additional Functional Framework for Candidate 2.3 180
66 Effect of Routine Maintenance on Periodic Sampling 225
67 Concentration vs Flow Curve Fitting 231
68 "Double Star" Violation of a Non-Coupled Parameter 233
69 "Double Star" Violation of a Coupled Parameter 233
70 Typical "Single Star" Violation Conditions 235
71 Assignment of Binary State Number 238
72 Recursive Pattern in Transition Matrix 240
73 Flowchart of Search Algorithm 243
74 Example of Survivability Computation 244
75 Flowchart for MAIN Program 249
76 Flowchart for Subroutine RPC 251
77 Flowchart for Subroutine RCHAR 262
78 Flowchart for Subroutine QTCAL 266
79 Flowchart for Subroutine EXPDUR 284
80 Flowchart for Subroutine COMPT 289
81 Flowchart for Subroutine PPDES 291
82 Flowchart of Subroutine CAPBLE 293
83 Flowchart of Function ANORM 295
84 Flowchart of Subroutine RMTTF 296
85 Flowchart of Subroutine LMNTEFF 298
86 Flowchart of Subroutine LDEFF 302
87 Flowchart of Subroutine SETUP 306
IX
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FIGURES (Cont.)
No. Page
88 Flowchart of Subroutine LPLACE 308
89 Flowchart of Subroutine SOLVE 309
90 Flowchart of Subroutine SYSEFF 312
91 Flowchart of Subroutine CALCST 314
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TABLES
No. Page
1 Relationship Between Function and Objectives of State
Programs (after [4]) 10
2 Limitations on RIBAM (from [7]) 29
3 Utilization Table 51
4 Summary of System Characteristics 92
5 Preferred Sampling Location by Parameter Category 94
6 Required Preliminary Design Input Data 114
7 Required Final Design Input Data 120
8 Major Tributaries to Basin Subset 134
9 Threshold Concentrations Assumed for Purposes of
Demonstration (mg/1) 137
10 Candidate 1.0 Sampling Program (sampling interval
in days, locations in river miles) 147
11 System Means for Candidate 1.0 151
12 Utilization Table for Candidate 1.0 152
13 Assumed Sampling Errors for Candidate 1.0 153
14 Assumed Failure and Repair Rates for Candidate 1,0
(years ) 154
15 Assumed Component Costs for Candidate 1.0 ($) 155
16 Candidate 2.0 Sampling Program (sampling interval in
days, locations in river miles) 157
17 System Means for Candidate 2.0 158
18 Assumed Sampling Errors for Candidate 2.0 161
19 Assumed Failure and Repair Rates for Candidate 2.0
(years ) 162
20 Assumed Component Costs for Candidate 2.0 163
xi
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TABLES (Cont.)
No. Page
21 Summary Cost-Effectiveness Results for Candidate 1.0 164
22 Summary Cost-Effectiveness Results for Candidate 2.0 165
23 Candidate 1.1 Sampling Program (sampling interval in
days, locations in river miles) 168
24 Assumed Component Costs for Candidate 1.1 169
25 Summary Cost-Effectiveness Results for Candidate 1.1 170
26 Summary Cost-Effectiveness Results for Candidate 2.1 171
27 Effect of Flow Record Length on E (Candidate 1.0) 173
sys
28 Summary Cost-Effectiveness Results for Candidate 1.2 175
29 Summary Cost-Effectiveness Results for Candidate 2.2 176
30 Candidate 2.3 Sampling Program (sampling interval in
days, locations in river miles) 178
31 Additional System Means for Candidate 2.3 181
32 Summary of Cost-Effectiveness Results for Candidate 2.3 182
33 Water Quality Parameters Modeled and Code Number
Assignments 198
34 Limitations on Reaction Rates of Coupled Parameters
xii
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ACKNOWLEDGMENTS
The authors wish to acknowledge the contributions of a number of individuals
and organizations to the development of the quantitative methods for design of
water quality surveillance systems. In particular, recognition must be given
to the continuing support and guidance of their Project Officer, Dr. Roger D.
Shull of the Implementation Research Division (IRD), Environmental Protection
Agency (EPA). Mr. Donald H. Lewis of EPA-IRD provided review and
comments on the draft report that led to significant improvements in the final
version. The professional staff of Raytheon Oceanographic and Environmental
Services (OES) is thanked for supplying answers to many questions beyond the
training and experience of the authors. The computer programming is primarily
the product of Mr. Richard N. Marshall of Raytheon OES.
International Mathematical and Statistical Libraries, Inc., Houston, Texas
77036, is thanked for permission to incorporate a limited number of subroutines
from their mathematical subroutine library in the computer programs prepared
for government use.
Xlll
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SECTION I
CONCLUSIONS
The quantitative methods for design of river basin water quality surveillance
systems developed in this report constitute a start-to-finish approach to the
design of monitoring systems meeting the requirements of pollution abatement.
They incorporate all the major factors influencing the system designer in his
choice of design options and provide reasonable guidelines for the assessment
of those factors.
The computer programs implementing those methods achieve their goal of
reducing the computational labor involved in design analysis and of making the
methodology tractable. They successfully make use of the information available
from computerized river basin models.
The methods and the computer programs are successfully demonstrated for
artificial data on the Beaver River Basin of Ohio and Pennsylvania.
Their utility remains limited by the availability of data on the performance
of system components, but acquisition of these data is entirely within the pre-
rogatives of the governmental agencies operating such systems.
The methods and computer programs are not immutable; they are expected
to be modified by the user and to benefit from the experience gained in their
application to real design problems. They provide a core methodology for use
by the system designer.
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SECTION II
RECOMMENDATIONS
The limitations placed on the application of the design methods by data avail-
ability should be removed. A research project directed at the acquisition and
analysis of data on the reliability and maintainability of surveillance system
components would provide valuable information both for use in monitoring sys-
tem planning and for the improvement of the technology.
The methods should be actively applied to the analysis of existing and new
surveillance systems. Such application can be expected to lead to cost-effective
allocation of resources and to evolutionary improvement of the methods them-
selves.
Further research and development should be undertaken to provide a similar
body of design methods for the direct monitoring of effluent sources. The
effluent monitoring design methods should be complementary to the existing in-
stream methods. Together, they should provide a total capability for the
optimization of resource allocation between and within the two classes of water
quality monitoring.
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SECTION in
INTRODUCTION
The Federal Water Pollution Control Act, as amended, calls for the Administra-
tor of the Environmental Protection Agency, in cooperation with a number of
federal and state agencies, to "establish, equip, and maintain a water quality
surveillance system for the purpose of monitoring the quality of the navigable
waters and ground waters and the contiguous zone and the oceans . . . . "[l] The
act is the latest successor to a series of legislative responses to the increasing
public awareness and concern for the quality of the environment. The water
quality surveillance system called for constitutes only one element of a broad-
ranging, federal-state program to "restore and maintain the chemical, physical,
and biological integrity of the Nation's waters, "[l]
Water quality surveillance is essential to the success of this initiative toward
environmental quality. William T. Sayers has pointed out that monitoring of
"... the rivers, lakes, and coastal waters receiving wastes [is required] to
assure attainment and maintenance of desired water quality levels consistent
with criteria contained in state-federal water quality standards. " [2] He further
states the aims of water quality surveillance are "... to assess existing water
quality conditions, to determine long-term trends in water quality and to evalu-
ate compliance with state-federal water quality standards. "
In order to promote the development of cost-effective surveillance systems, the
Environmental Protection Agency is supporting a program aimed at provid-
ing system designers with methods for planning such surveillance systems.
This report is one of several recent studies undertaken with EPA support
to examine the question of design of water quality data acquisition systems.
It is the second of two studies undertaken by Raytheon Oceanographic and
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Environmental Services to provide the design methods. The first Raytheon
report [3] and two other related reports [4, 5] are reviewed in Section IV to pro-
vide the necessary background for the present study.
Such water quality surveillance systems may be directed at either of two general
objectives: prevention or abatement [4]. Prevention refers to those actions
aimed at maintaining the existing (presumable good) water quality. Abatement,
on the other hand, refers to those actions directed at reducing or moderating
existing pollution conditions.
This report is directed at the design of abatement-type water quality surveillance
systems for river basins. It is intended to extend the quantitative methods of the
previous Raytheon study [3] to include cost and effectiveness, and to computer-
ize those methods. The implications of these objectives are discussed in detail
in Section V, along with the approach taken in achieving the objectives.
Section VI, supported by Appendices B, C and D, presents the development of the
quantitative cost-effectiveness methods, as applied to water quality surveillance
systems. These included the consideration of such aspects as system accuracy,
reliability, maintenance, survival, cost, and resource diversions.
The cost-effectiveness methods are merged with the previously developed pre-
liminary design methods and presented as a unified design method in Section VII.
To accommodate the merger, some modifications of the earlier preliminary
design methods are required. They are detailed in Section VII.
Also presented in Section VII is a summary of the computer programs developed
to implement the design methods. Instructions are provided for the preparation
of input data and the use of the programs. Program development details may be
found in Appendix E, which provides the reader with the criteria and considera-
tions necessary to the preparation of the programs contained in Appendix F.
6
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Included in Appendix E are special algorithms used in the implementation of the
quantitative design methods.
The design of a cost-effective surveillance system using the quantitative methods
is demonstrated in Section VIII. The demonstration is conducted on the Beaver
River Basin of Ohio and Pennsylvania. A final discussion of the results of the
study and its predecessors is contained in Section DC.
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SECTION IV
REVIEW OF PREVIOUS DEVELOPMENT
In order to provide the reader with a background for the development presented
in this report, several related reports are reviewed in this section. The pre-
sent study is a direct outgrowth and expansion of a previous study by Raytheon
Oceanographic and Environmental Services, reported in [3]. It is related to two
other EPA studies [4, 5] and must be viewed in the context of general research
on the design of water quality monitoring systems, such as [6]. In addition, it
makes use of a computerized river basin model (RIBAM) developed by Raytheon
Oceanographic and Environmental Services for the EPA and described in [7].
Each of these related studies is reviewed in this section.
The review is organized in a logical manner, rather than by publication date.
This allows the use of a somewhat tutorial presentation, aimed at the establish-
ment of a baseline for the development of later sections.
The overall objective of four of the five reports reviewed in this section [3, 4,
5, 6], as well as this report, is the development of concepts and methods to
guide systems designers in the preparation of plans for water quality monitoring
of river basins. The specific approaches and the desired results are conditioned
on the objectives of the monitoring system, which are in turn dependent upon the
objectives of the operating agency.
Ward [4] has categorized the state water pollution control programs according
to two broad objectives: 1) prevention and 2) abatement. Within each of these
broad program objectives, he identifies several, more specific functions of
state programs. Table 1 summarizes the relationships among the functions and objec-
tives. As indicated hi the table, thedataacquisitionfunctionis associated with both
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Table 1. RELATIONSHIP BETWEEN FUNCTIONS AND OBJECTIVES
OF STATE PROGRAMS (after [4])
Function
Planning
Research
Aid programs
Technical assistance
Regulation
Legal enforcement
Data collection, processing,
dissemination
Objective
Prevention
X
X
X
X
Abatement
X
X
X
X
objectives. Specific data collection activities must be tailored to the broader of
the two objectives to be satisfied by those activities.
The water quality monitoring systems considered in [3, 4, 5, 6] emphasize in-
stream observation of water quality for pollution abatement. This emphasis is
in contrast to use a direct effluent sampling as a means of pollution abatement.
It is a result of the limitations of all but the most recent Fe ~3ral water quality
legislation. Prior to the enactment of the Federal Water Pollution Control Act
Amendments of 1972 [8], the Federal Water Pollution Control Act [9] authorized
only the establishment and enforcement of stream water quality standards.
Thus, the concern has been for design of surveillance systems providing in-
stream observations. With the passage of the Amendments of 1972 [8], the
abatement of pollution through the establishment and enforcement of effluent
standards (in conjunction with stream standards) gained legal recognition.
Further efforts are required to develop comparable design methods for augment-
ing in-stream surveillance with effluent surveillance.
10
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In addition to abatement, the observation of stream conditions is essential to the
performance of prevention-type functions. In general, surveillance systems
aimed at an abatement objective also satisfy the requirements of prevention for
those regions of the river basin under surveillance [3, 4].
Thus, the study of general application of systems analysis techniques to design of
water quality surveillance systems reported in [5] focuses on in-stream surveill-
ance. It addresses thequestionof setting up in-stream water quality surveillance
systems throughout the country, in accordance with the earlier version of the Federal
Water Pollution Control Act [9]. To insure compatibility of individual systems
developed by various federal, state and regional agencies, systems analysis
techniques are adapted to the design of the surveillance systems.
The resulting systems analysis framework is summarized in Figure 1 (Figure 7
from [5]). The figure presents an integrated analysis of all the pertinent con-
siderations inherent to the establishment of an in-stream water quality surveil-
lance system. The analysis is compatible with any specific geographic area of
interest.
The logic represented in Figure 1 can be divided into two stages of system design
development. The first stage comprises those activities that analyze the rela-
tionship between the surveillance system and the natural system to be
monitored. This preliminary design stage (shown in Figure 1 within the broken
line) deals only with the establishment of water quality sampling on the basis of
scientific and social considerations. The second, or final, design stage is com-
posed of those activities that are aimed at the selection of the "best" realization
of the preliminary design. The practical considerations of engineering, legal
constraints, cost, reliability, and existing surveillance are used during the final
design stage, to select a preferred implementation of the surveillance system.
11
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12
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tfST-EFFECTIVENESi
ANALYSIS
Figure 1. General Systems Analysis Framework (Sheet 2 of 2)
13
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A qualitative approach to the application of the general system design method is
demonstrated in [5]. As a result, a number of recommendations are advanced
to further development of the systems analysis methods. Among them is one
suggesting that "... the tasks, functions, and interrelationships as identified
in the systems analytical framework should be described in specific quantitative
relationships ..." and that "... a user handbook . . . should be developed
to describe these techniques and extend their utility. "
Several approaches to providing such quantitative relationships have been devel-
oped [3, 4, 6]. Each is based on a different theoretical foundation, but the
results are, in many respects, comparable. The development presented in this
report is a direct extension of one of these approaches [3] and, in conjunction
with that work, provides a complete quantitative method for the design of in-
stream water quality surveillance systems for abatement purposes according to
the framework of Figure 1. Ward's approach [4] is somewhat less quantitative,
but still provides a complete method for evaluating system designs within the
framework presented in Figure 1. Moore's method [6], like the earlier Ray-
theon report [3], is confined to the preliminary design phase of system design.
Each of these is discussed in the following paragraphs.
Ward's approach [4] discusses both prevention and abatement-type surveillance.
The description here is confined to abatement since the present study is so con-
fined. The approach calls for the location of surveillance stations at the critical
quality point below each major area of pollution sources. The critical point is
defined by comparison of a quantitative characterization of stream quality with
the stream quality standards. No attempt is made to associate a numerical priority
with each recommended location and no recognition is given to the possibility that the
critical point will vary according to specific pollutant. An optimization theoretic
14
-------
approach developed by Vanderholm [10] is used in the selection of sampling fre-
quency. A computerized simulation provides a number of random, artificial
pollution events that are matched against candidate sampling schemes to select
the best candidate on the basis of percentage detection. The distribution of event
initiation is uniform in space and time, with deterministic event durations. Thus,
while recognition is given to the existence of major point sources in selection of
the spatial sampling scheme, the higher probability of violation events associated
with these sources is ignored in determination of the temporal sampling scheme.
In addition, the use of a uniform random distribution in the computation ignores
the real physical processes that influence the temporal initiation and termination
of a pollution event. Finally, it is noted that the selection of sampling is done on
a reach by reach basis, without consideration of the possible influence of up-
stream reaches.
Another quantitative preliminary design method, based on estimation theory, has
been studied by Moore [6]. His method makes use of the Kalman filter technique
to provide estimates of the water quality, based on a current set of field obser-
vations and an a priori description of the natural system being monitored (a
dynamic model). Figure 2 is a schematic representation of the filter method.
A feature of the method is the indirect way in which the actual field data are used
to produce the current estimate of the water quality. Roughly speaking, the cur-
rent estimate is based on our projection of the current value from the previous
estimate using the dynamic model, with a weighted correction for the difference
between the projection and the current observed value. A decision on the existence
of a violation is based on a comparison of the current estimate, not the observed
value, with the water quality standards threshold. Since the estimated variance
of the water quality estimate is also computed, it is possible to calculate the
confidence in the decision. That is, it is possible to compute the probability that
15
-------
r
i_
Dynamic model
Muiel
uncertainty
Field measurements
Comparison
of each mode
of estimation
\
f
Weighting
algorithm
l
Best estimate
of system state
"1
Sampling
uncertainty
J
1
Prediction of variance in
estimate of system state
Figure 2. Schematic Representation of Filtering (from [6] )
the decision is a correct one. Since Moore's method does not permit the compu-
tation of the probability of a violation existing at the time of observation, no esti-
mate of the percent of violations detected can be obtained. For a given (arbitrary)
candidate spatial distribution of monitoring, the temporal frequency can be opti-
mized by selecting the minimum rate (i.e., minimum economic cost) that per-
mits the achievement of a preselected confidence level. Thus, with Moore's
method, it is possible to select a sampling scheme that is exceptionally good at
detecting those events that exist when a sample is taken, but that may miss a
very large number of violations. It should also be noted that the method does
not immediately direct the user to locate stations at the points of highest proba-
bility of violation, although trial and error use should tend to produce a prefer-
ence for these station locations. From a practical viewpoint, Moore's method
is severely limited by the size of the covariance matrices and the associated
computational costs necessary to analyze even simple river basins [6].
16
-------
The method for preliminary system design developed by Raytheon [3] employs a
decision theory approach that focuses attention on the event of interest, the
water quality violation. Like Ward's approach, the optimization criterion is the
maximization of the expected percent detection and it directs the designer to
sample at the critical point. It is an improvement over Ward's method, in that
it specifies a priority for each sampling station, based on the projected likeli-
hood of violation. The temporal sampling frequency is determined analytically,
rather than through use of a simulation approach. Selection of temporal sam-
pling incorporates data on the expected behavior of the physical pollution pro-
cesses by associating violations with the point sources and employing a Poisson
distribution to describe the temporal variability. The method bases the violation
detections directly on the observed data, an approach that is likely to be pre-
ferred in legal proceedings.
The essential features of Raytheon's quantitative preliminary design method [3]
are detailed in the following paragraphs, since it forms the foundation for the
present study.
Application of the Raytheon approach, as summarized in the User Handbook of
[3], calls for sequential performance of six basic tasks. The general task flow
is summarized in Figure 3 (Figure G-l from [3]). Each of these tasks corre-
sponds to one or more of the functional blocks in the general systems analysis
framework (Figure 1). In Task 1, the user is concerned with gathering neces-
sary data, organizing information and determining certain guidelines for his
particular application. Task 2 is devoted to the development of specific items
of information that characterize the river basin. This is accomplished by mani-
pulation of the data collected in Task 1. In Task 3, the user begins the actual
preliminary design by establishing stream segments, stretches of the stream
17
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TASK1
GATHER DATA
SET GUIDELINES
\
TASK 2
DEVELOP
INPUT DATA
\
TASK 3
SEGMENT
STREAM
\
TASK 4
CHARACTERIZE
SEGMENTS
PREFERRED
SAMPLING
LOCATIONS
TASKS
COMPUTE
PRIORITY
\
TASK 6
SAMPLING
FREQUENCIES
( RATING
OF
V MERIT
Figure 3. Handbook Task Flow Diagram (from[3] )
18
-------
that may be dealt with as uniform units. Using the Task 3 segmentation, a sim-
ple mathematical model is employed in Task 4 to project the behavior of the
stream. The preferred sampling locations may then be identified with the criti-
cal points predicted by the model. Using other data from the model, the priority
of observing each parameter of interest at the preferred location in each segment
is computed in Task 5. Finally, Task 6 is concerned with the computation of a
rating curve for the evaluation of sampling frequencies. It should be noted that
a unique preferred frequency of sampling cannot be derived from this method
until other factors, such as cost, are considered (as is the case in the present
study).
One recommendation reported in [3] proposes that the mathematical models used
in Task 4 for stream characterization be computerized. The computerization
would benefit the user in two ways. First, the procedures for computation of
stream quality described in [3] are laborious. Although every attempt is made
to minimize tedious hand computation, the procedures still require detailed
manual calculation. Thus, computerization would increase their utility. Second,
by computerizing, the user may take advantage of existing computerized river
basin models, such as the RIBAM model [7]. Use of these models will provide
even better estimates of stream conditions than can be achieved by the manual
computations of [3]. The characterization of stream quality using the compu-
terized model is described later in this section.
Turning to establishment of segment priority in Task 5, the mathematical basis
for priority is the probability of
"Not to Exceed "-type standard):
for priority is the probability of violation. Probability of violation (TT ) is (for a
co
(c(x)>CT) =f P(C;x)dC (1)
19
-------
where x = location
C = concentration
C = water quality standards threshold value
Pr = probability
p = probability density function
It is argued in [3] that the maximum expected TT is a, defined by:
C - C
a =
(2)
where C = the mean concentration at the critical point
o- = the standard deviation of the concentration at the critical point
° and the critical point is the point of maximum or minimum (worst
case) concentration.
The initial segment priority is defined to be a.
As the system designer selects segments for the implementation of monitoring,
it may be anticipated that priority of the remaining segments will be changed.
Due to the existence of a strong point source, several neighboring segments may
initially have high priority. Establishment of a station in any one of them may
be expected to detect violations in all of the highly correlated segments, so that
the remaining, unmonitored segments take on a relatively lower priority.
The Raytheon quantitative preliminary design method incorporates a means for
-evaluating segment priority as stations are selected for implementation. The
'-called ultimate segment priority is computed by considering the inter-segment
correlation in the evaluation of priority.
The measure of sampling frequency effectiveness used in Task 6 for evaluation
of sampling frequency is defined as:
re
so
20
-------
M =
Expected Number of Violations Detected at a Point
Expected Number of Violations at that Point
(3)
An analytical expression for the evaluation of M is developed in [3], using an
assumed Poisson distribution in a Markov process to describe the violation pro-
cess. That is, a two-state violation process is defined by the water quality
standards and the expected temporal variation of concentration, as shown in
Figure 4. The two-state process is used because most in-stream water quality
standards are of the simple threshold type [3], The severity of the violation
is, therefore, not of interest in system design. Statistically, such a process
may be described by the average duration of each state, T and T , where the
subscript 0 indicates "no violation" and the subscript 1 indicates "violation".
It is shown in [3] that the expected number of violations, n , can be expressed
as:
= l/(T
o
(4)
It is also indicated in [3] that a good approximation for the number of violations
detected, n , is:
d
n
Vi
0
exp - — -
(5)
in which A is the sampling interval. Combination of equation (4) with equation
(5) yields the approximate form of M:
M(A' V V * T
exp (- A/T ) - exp
(TO/TI) - i
(6)
Estimates of T and T are obtained in Task 6, using information supplied by
the mathematical model and a knowledge of the variability of water quality. The
21
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Figure 4. Conversion of Parameter Process into Violation Process (after [3])
result is an effectiveness rating curve, such as that shown in Figure 5. The sys-
tem designer can use the rating curve in the selection of appropriate sampling
frequencies, in conjunction with other factors, such as cost.
i.o
T0 - AVERAGE NON-VIOLATION DURATION
T,-AVERAGE VIOLATION DURATION _
.1 1.0 10.
NORMALIZED SAMPLING PERIOD ( A /T,)
Figure 5. Temporal Effectiveness Rating as a Function of T , T and A (from
* °
22
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Implicit in the development of the quantitative methods reported in [3] is the con-
cept of system duration. System duration is defined as that time over which the
water quality surveillance system will maintain a fixed configuration of spatial
and temporal sampling. All system design factors are average factors over the
system duration. The need to monitor a segment of the river (IT ) is essentially
the average need to monitor for the planned system duration. Similarly, the
measure of time sampling effectiveness (M) is essentially the average effective-
ness for the total span of the planned period of system operation.
For computational purposes, the system designer selects the system duration
on the basis of constraints imposed by the objectives of the operating agency.
If the surveillance system is intended solely to identify water quality violations
during the low-flow period, then the system duration corresponds to that period.
Typically, the system duration may be expected to range from about 3 months
to about 5 years. The upper limit is defined by the time required to implement
abatement actions of a magnitude sufficient to change the conditions for which
the system is designed.
In fact, the design method, of necessity, assumes that conditions in the basin
remain statistically constant throughout the system duration. As suggested
above, implementation of abatement actions violates this assumption. Another
violation of the assumption occurs when a polluter adjusts his operational
schedule to avoid detection by the system. The surveillance system design
method presented in this report and in [3] is not intended for conditions in which
the polluters and the enforcers engage in "game playing". That is, there can
be no feedback to the possible violator regarding the organization or operation
of the surveillance system if the analysis is to hold.
23
-------
Another concept essential to the quantitative design methods is the so called
"macroscopic" concept. Under the "macroscopic" concept the spatial and tem-
poral scales employed in the design methodology are restricted. The stream is
treated as a one-dimensional flow, with depth and width entering only as they
influence the values of coefficients and other natural characteristics, such as
velocity. Point sources located in "close" proximity to each other are grouped
and treated as a single source, based on a quantitative measure of closeness.
Commensurate with the space scale, the time scale is restricted to very slow
variations, those taking place over days. Computation of spatial factors is
based on time-averaged inputs.
Therefore, a constraint on the quantitative methods of [3], as with several of
the other methods reviewed in this section, is that it is restricted to the stream
portions of the river basin. That is, the mathematical models used to charac-
terize the water quality are one-dimensional models and are restricted to cases
in which the concentration profiles along the depth and width can be considered
uniform. Deep impoundments, such as reservoirs, estuaries and open coastal
waters can not, in general, be included in the analysis, since they can rarely be
described as one-dimensional. The quantitative methods are, however, entirely
satisfactory for the greatest portion of the nation's river basins, that which can
be considered one-dimensional to reasonable approximation.
In Section VII of this report, the relationship of each of the six tasks to the
methods developed during this study is discussed in detail. The essential con-
cepts of [3] have been preserved in the present development. In some cases,
the details have been modified to accommodate the present needs.
As mentioned previously in this section, the manual computation of stream
characterization is replaced in this report by a computerized mathematical
24
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model known as RIBAM (River BAsin Model). RIBAM was developed by Ray-
theon as part of the Beaver River Basin Modeling Project for the EPA and is
documented in [7]. It is a modification and extension of the earlier DOSAG
water quality model, prepared by the Texas Water Development Board to model
two stream quality parameters, biochemical oxygen demand (BOD) and dissolved
oxygen (DO) [ll]. In developing RIBAM, the basic DOSAG model has been
expanded to model as many as seventeen water quality parameters, plus four
stream parameters. RIBAM is a steady-state, one-dimensional model, capable
of adaptation to any river basin through the preparation of input data decks.
Thus, it constitutes an equivalent replacement for the mathematical models used
in [3].
The analytical approach used in RIBAM calls for representation of the river
basin as a network consisting of four basic components:
1. Junctions—the confluence between two streams within the basin being
modeled
2. Stretches—the length of river between junctions
3. Headwater stretches—the length of river from the headwater to the first
junction with another stretch
4. Reaches—the subunits that comprise a stretch (either headwater or nor-
mal.
Reach boundaries are defined by any unique combination of the physical charac-
teristics of the river basin, such as effluent sources, reaction rates or flow
regimes. Thus, RIBAM reaches correspond to the stream segments defined in
[3] and both terms are used interchangeably in this report.
The mathematical approach used in computation of the water quality parameters
in the basin is a "piecewise continuous" approach, in which the parameter is
25
-------
assumed to behave according to a continuous differential equation throughout a
reach. This approach may be used because the definition of a reach assumes
that the important physical characteristics of the stream remain constant for the
length of the reach.
The water quality parameters modeled in RIBAM are grouped into three cate-
gories:
1. conservative
2. non-conservative, non-coupled
3. non-conservative, coupled.
(See the Glossary, Appendix A, or [3] for discussions of these three terms.)
Each parameter within a given category is assumed to obey a general equation
characteristic of that category. With the exception of the non-conservative,
coupled category, the equations used in RIBAM are identical with those used in
[3]. The non-conservative, coupled equations used in RIBAM are more sophis-
ticated than those used in [3], since they consider coupling between more than
two parameters at a time. Appendix A summarizes the mathematical details of
RIBAM.
The top-level organization of the RIBAM computer programs, as they are used
for river basin planning, is shown in Figure 6 (Figure 1 from [7]). The pro-
grams are written in FORTRAN IV and consist of a main program and twelve
subroutines that perform the computations (see Figure 7).
The major restriction on RIBAM, as on the quantitative methods of [3], is in the
consideration of deep impoundments. The mathematical models are so-called
one-dimensional models and are restricted to cases in which the concentration
profiles along the depth and width dimensions can be neglected. Clearly, deep
26
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START
READ
PROGCONT
DECK
NEXT
PARAM
SELECTED
READ
STANDARD
DATA DECK
t
FIRST
PARAM
SELECTED
/PERFORM
-W SIMULATION
\COMPUTATIONJ
\
WRITE
FINAL
SUMMARY
YES ^ MORE
SIMULATIONS'"
Figure 6. RIBAM Top-Level Flow Chart (from [7] )
27
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impoundments such as deep reservoirs violate these conditions, because of the
vertical stratification typical of such reservoirs.
Other restrictions are related primarily to computer storage limitations. They
are summarized in Table 2. Another restriction is that the reaction rates of
coupled parameters may not be equal, since that violates the mathematical
assumptions of the model. (Intermediate forms are decaying as rapidly as they
are created, if two or more coupled reaction rates are taken as equal.)
As used in the present study, the RIBAM model has been slightly modified.
These modifications are discussed in detail in Section VII and Appendix E. In
summary, the plotting subroutine CPLOT has been deleted and all written output
has been eliminated. The main RIBAM program has been truncated and merged
with a subroutine of the design methods programming. It is assumed that the
systems designer will use the full RIBAM model for calibration purposes, prior
to use of the Standard Data Decks for system design purposes.
REINI
TRIBO
Figure 7. RIBAM Program Element Relationship (from[?] )
28
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Table 2. LIMITATIONS ON RIBAM (from [7])
Quantity
Maximum
number
Headwater stretches
Junctions
Reaches
Stretches (including headwater
stretches)
Reaches per stretch
Sequential simulations of each
parameter using sensitivity
analysis options
10
10
40
20
20
5
29
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SECTION V
STUDY OBJECTIVE AND APPROACH
As a direct continuation of the studies discussed in Section IV, the objectives of
this report and the approach taken are strongly related to those of its prede-
cessors. In this section, the objectives of the present study are presented and
related to the previous studies. A description of the basic approach taken in
achieving the study objectives is then given and discussed in the perspective of
the related studies.
STUDY OBJECTIVES
The objectives of the study are: 1) the augmentation of the existing quantitative
procedure for preliminary design of water quality surveillance systems [3] with
a means for including cost and effectiveness in the design process, and 2) the
development of methods for utilizing computerized river basin models [7] to reduce
the labor involved in system design. Implicit in the second objective is the
general application of computerization to handle the detailed evaluation of can-
didate system designs.
Thus, the scope of the study is expanded from that of [3] to include both the
preliminary design stage and nearly all of the final design stage (see Figure 1).
Consideration of cost, reliability, maintenance and other aspects of real sys-
tems had been specifically excluded from [3], In expanding the scope to include
such factors, attention is focused on the collection and analysis subsystems
diagrammed in Figure 1. Attention is focused on these two subsystems,
because they appear most in need of treatment at this time. The other two sub-
systems, data transmission and data dissemination, are less dependent on a
31
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knowledge of the problems of water quality monitoring and more amenable to
previously available engineering approaches.
Addition of a quantitative cost-effectiveness methodology to the existing pro-
cedures provides a "start-to-finish" numerical design capability for river basin
surveillance system design. The use of such a design procedure assures
uniformity in the results of monitoring system designs for the wide variety of
river basins requiring surveillance. It standardizes approaches taken by the
numerous responsible agencies and, thereby, promotes the correlation of
information. It will support the application of legal action by assuring the
defensibility of the monitoring approach. Finally, it allows management of sys-
tem implementation based on quantitative judgments, rather than qualitative
ones, in cases where constraints do not permit establishment of stations in
every reach of the basin.
With the experience of demonstrating the preliminary design procedures on the
Wabash River Basin, it became apparent that a computerized approach would
simplify the application of the methods and greatly reduce the chance for care-
less errors. In addition, it was recognized that the analysis of system effec-
tiveness would require extensive, detailed computations of system survivability,
availability and capability, in which the effect of each individual component of
the system would have to be considered.
With the development of a number of computerized river basin water quality
models, for example [7], it became possible to consider using the existing basin
models to automatically provide information obtained previously through tedious
manual computation in [3], By carefully merging these models with other com-
puter programs designed to provide the system designer with an evaluation of
the candidate system, the major portion of the design process could be automated.
32
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This would leave the designer free to consider more important aspects of the
design process than how to perform the massive computations.
STUDY APPROACH
Because the study is so closely tied to the previous work [3], the number of
technical approaches considered was constrained to those compatible with the
existing preliminary design methods. The basic assumptions made in the
development of the preliminary design methods were carried over into the
present study intact. These included the concept of system duration and the so-
called "macroscopic" concept, in addition to the assumption that the need to
monitor is related to the relative probability of violation. As before, attention
is confined by the "macroscopic" concept to the "one-dimensional" portions of
the river basin and the surveillance system is assumed to have the abatement
objective.
However, it was recognized that automation of the preliminary design computa-
tions might require that some conceptual modifications be made. Provision
was made to reconsider those aspects and to amend the design methods as
appropriate. The results of the amendment process are described in Section VII.
The study approach called, first, for the theoretical development of the cost-
effectiveness model. From the outset, it was recognized that the data available
to the system designer for evaluation of cost-effectiveness would be minimal.
The approach was to deal with the problem at a level where the suppliers of
equipment and instrumentation might reasonably be required to produce the
necessary data.
The cost-effectiveness model could then be merged with the preliminary design
methodology to produce a consistent "start-to-finish" design method. A major
33
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R1343
aspect of the merger was the selection of optimum interaction points between
the designer and what was to become an automated process. Another aspect of
the merger was the optimization of basin model usage to minimize the necessity
for repeated simulations of the river.
The design methodology could then be flow-charted and computerized. By care-
ful development of the design logic, it was the intent that the system design
programs be capable of being run on the same machines capable of handling the
river basin models. For maximum compatibility, program coding was done
consistent with the existing basin models in FORTRAN IV. Throughout the
program development process, modular testing using artificial data was per-
formed to verify the program coding.
In conjunction with the EPA, the Beaver River Basin was selected for demon-
stration of the design methodology. An important aspect of the demonstration
activity was the feedback provided to update the methods.
In the next section, the theoretical development of the cost-effectiveness
methods is presented.
34
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SECTION VI
DEVELOPMENT OF COST-EFFECTIVENESS METHODS
The objective of this section is the development of methods for examining the
cost-effectiveness of alternative approaches to water quality surveillance in a
river basin. The discussion is, in general, confined to those portions of the
methodology that are unique to the water quality surveillance system design pro-
cess. No attempt is made to provide a text in engineering economics, cost
accountancy, or reliability and maintainability. When necessary, individual
topics from these disciplines, and others, are included for completeness. For
detailed examinations of these fields of engineering, the reader is directed to
their literature. In particular, [12], [13], [14], [15] and [16] have proven use-
ful during the development of the cost-effectiveness methods described in this
section.
SUMMARY OF COST-EFFECTIVENESS METHODS
Analysis of surveillance system cost-effectiveness requires the separate esti-
mation of the system cost for the planned system duration and the expected effec-
tiveness of the system over that time period. Effectiveness of water quality
surveillance systems is defined as the expected percentage of the violations
which occur throughout the basin during the system duration that are detected
by the system. Cost analysis is conducted on the basis of an organizational
framework incorporating both the system means that perform the in-line sur-
veillance functions and the facilities that support those means. Costs are esti-
mated for each system component in four areas:
• acquisition
• operation
35
-------
• maintenance
• value on completion of system use.
Effectiveness is a function of:
• location
• sampling rate
• maintenance pattern
• availability
• survivability
• capability
of the individual system elements that perform the monitoring function.
These, in turn, are functions of the configuration and characteristics of the
means incorporated in each system element. The estimation of system effec-
tiveness is conducted within the framework of a functional analysis that specifies
the role of each means in monitoring a specific site for a specific parameter.
INITIAL CONCEPTS OF COST EFFECTIVENESS
The objective of cost-effectiveness analysis is the selection of the "best" water
quality surveillance system for a given river basin. The concept of the "best"
system is explored here, along with the overall approach taken in selecting the
"best" system.
A given configuration of means for accomplishing river basin surveillance may
be evaluated on the basis of its ability to perform, relative to some ideal (the
effectiveness of the configuration), and its total economic cost.
The word "means" is used throughout this report to indicate a way of perform-
ing a function necessary to the production of water quality data. A "means" may
36
-------
be a completely automated device, an entirely manual technique, or some com-
bination of manual and automated equipments. The context should be sufficient
to resolve any confusion between this usage of the word "means" and the plural
form of the arithmetic average (the mean value).
One way to compare alternative system configurations is to consider only those
alternatives that are specifically designed to achieve a single, unique level of
effectiveness. Under these circumstances, the selected level of effectiveness
will clearly meet minimum acceptance requirements, since it would be useless
to design a system that did not. The choice of "best" configuration then resolves
itself to identifying the minimum cost configuration (see Figure 8).
Another approach is to consider only those alternatives specifically designed to
a single, unique expected cost. Once again, because the cost is selected a priori,
it is certain to fall below any maximum acceptance level. The "best" configura-
tion in this case is the one with the greatest effectiveness (see Figure 9).
Neither of these two approaches assures that both minimum effectiveness and
maximum cost constraints will be met by the alternative selected. For example,
all those alternatives considered that satisfy the fixed effectiveness criterion
may be too costly (see Figure 10). For a fixed effectiveness, it may be very
difficult to bring cost within acceptable limits.
A further difficulty with these two approaches lies in the design of systems to
meet specific fixed criteria, either effectiveness or cost. It is felt that exces-
sive effort may easily be expended in attempting to formulate alternate configu-
rations of water quality surveillance systems that meet one or the other of these
requirements. The difficulty may become particularly apparent when external
constraints, such as maximum use of existing facilities, are imposed on the
selection process.
37
-------
Thus, the method used in evaluating alternative system configurations must be
capable of comparing candidates for both cost and effectiveness, simultaneously.
In addition, it must be capable of eliminating those candidates that either fail to
achieve minimum effectiveness criteria or exceed maximum cost limits.
The use of the cost-effectiveness ratio as the measure of the proposed candidates
satisfies the foregoing requirements on the method of evaluation. Since neither
cost nor effectiveness is fixed initially, maximum flexibility is permitted in
satisfying externally imposed constraints on system design. Candidates may be
eliminated prior to computation of the cost-effectiveness ratio, should either
cost or effectiveness be individually unacceptable. Of those alternatives that
meet minimum acceptance standards, the "best" system is the candidate with
minimum cost per unit effectiveness, in the acceptable region (see Figure 11).
Thus, the measure of goodness applied to an alternative configuration is the
cost-effectiveness ratio (r):
Cost-Effectiveness = P
Total System Cost
Total System Effectiveness
K
sys
= E <7>
sys
It should be apparent from the foregoing that the approach taken in determining
the "best" configuration is a suboptimization approach. No attempt is made to
determine the universally optimum configuration. The emphasis is placed on
identifying the "best" of those alternatives considered, which may constitute a
small sub-set of all possible alternatives. The cost-effectiveness method does
not automatically result in synthesis of the "best" system. The system designer
38
-------
t
MIN. ACCEPTABLE
EFFECTIVENESS
MAX. ACCEPTABLE
COST
CO
o
o
^
o -A»
0 "B"
V)
o
J"C" "
"D"
"BEST" SYSTEM
1 ^
EFFECTIVENESS
A
"A" "B" Mc" "D"
- © GO 0
"BEST" SYSTEM
^^_
EFFECTIVENESS
Figure 8. C-E Trade-off for Fixed Figure 9. C-E Trade-off for Fixed
Effectiveness Cost
e/9
o
0
1
® "A"
® "B"
® a em
t
. (g) J1RL
\ MAX. ACCEPTABLE
COST &
o
u
MIN. ACCEPTABLE
-^"EFFECTIVENESS
1
ACCEPTABLE »«..
REGION
\
| ^ "F'0
1 G"E"
"B" ] G'c" 0'D"
® 1
EFFECTIVENESS
EFFECTIVENESS
Figure 10. Unacceptable Result of Figure 11. C-E Ratio Approach to
Fixed Effectiveness Trade- Candidate Selection
off
= Acceptable
= Unacceptable
39
-------
must first synthesize each candidate, then compare its cost-effectiveness with
those of other candidates that he has synthesized.
The flow diagram in Figure 12 shows the steps required to synthesize and com-
pare alternative system configurations. The system design process begins with
selection of a preliminary set of water quality parameters of interest to the
designer. Typically, the selection is made on the basis of the applicable stream
quality standards and expected sub-standard conditions. Using the techniques
previously developed [3], the river basin is then modeled for these parameters
to establish a measure of the parameter-segment priorities, preferred locations
for sampling and the shape of the temporal sampling effectiveness curve. Based
on the parameter-segment priorities, the designer may select a preferred set of
system elements to be implemented. Using this set, he then selects one or
more candidate configurations for implementation of the system. The candidates
may then be evaluated for cost, effectiveness and the cost-effectiveness ratio.
Figure 12. System Design Flow Diagram
40
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The total design process shown in Figure 12 is described in detail in Section
VII—Design of Water Quality Surveillance Systems. In that section, the cost-
effectiveness methods are merged with the preliminary design methods developed
in [3] to form a unified, computerized design method.
In synthesizing the system configuration, the system designer should adopt a
planning philosophy that includes contingency planning.
Such contingency planning may lead to the selection of back-up mechanisms that
materially change the cost, performance or implementation pattern for the sys-
tem. An example of this is the activation of a low sampling-rate, manual set of
means to replace a high rate, automated system destroyed by a flood. It can be
anticipated that material differences in both cost and performance between the
manual and automatic means will exist. Another example is the need to tem-
porarily divert manpower or equipment from a manned surveillance system to a
higher priority activity not related to surveillance. In the second example, an
entirely different set of system elements may be implemented for the duration
of the resource diversion.
When contingency planning leads to selection of such materially different alter-
native system operating plans, the total system cost-effectiveness is computed
on the basis of weighted average of the cost-effectiveness of the operating plans
considered independently. The weighting function is the probability of activation
of the operating plan, either normal or contingency. Thus, the total system
cost-effectiveness of the n. alternative system candidate is:
L
41
-------
where I is the particular system operating plan under consideration for the can-
didate and L is the number of contingency plans associated with the n can-
n
didate. For example, a candidate system may call for sampling from a boat
during normal conditions. As a contingency plan during high river stages when
launching a boat might be dangerous, the intention may be to sample from
bridges. The overall cost-effectivenss of the candidate would be the weighted
siun of the separate cost-effectiveness of the two operating plans taken independently.
The weighting would be the probabilities of normal and high-water stages.
ANALYSIS OF CANDIDATE SYSTEMS
Prior to a detailed development of the cost-effectiveness concepts, it is necessary to
develop an analytical framework with which to describe each system candidate.
By choosing to deal with the design problem at a system level, recognition has
been given to the need to consider the interrelationships that tie the system
together, that make it a recognizable entity. One of the primary attributes of
systems is their complexity. In particular, systems may be characterized by
the multi-purpose utilization of individual system components (the means) [16].
Water quality surveillance systems may be described with either of two analyti-
cal frameworks. One is a functional framework related to the processes, equip-
ments and personnel necessary to perform observations for a specific system
element. The other is an organizational framework describing the operational
relationships among the system means. For example, an atomic absorption
spectrometer, (AA) may be used in a given surveillance system to detect heavy
mr' Is. If the heavy metals parameters are measured at a number of points in
th sin, the single AA unit is functionally a component means in a number of
system elements. Organizationally, the single AA unit is assigned to a single
42
-------
laboratory, along with other means, such as BOD incubators, that are associ-
ated with other system elements.
Each type of analytical framework has a unique use in the design methods. The
organizational framework is most useful in the analysis and allocation of costs.
The functional framework is used for analysis of system effectiveness, in which
the technical or scientific worth of the system is assessed.
Organizational Analysis
The development of the system organizational framework is done in a straight-
forward way, using methods that should be familiar to anyone who works in a
departmentalized organization.
For purposes of surveillance system design, two framework components are
used: the means and the group. A means is the technique, apparatus, equip-
ment and/or person by which a necessary function in the flow of information is
performed. It is identical with the component of the same name used in func-
tional analysis. A group is the operational unit, department, or laboratory to
which several means or other lower-level groups are assigned. Thus, there
may be several levels of groups, constituting a heirarchy. The highest level
group is identical with the total surveillance system.
To illustrate the organizational analysis, take the example of the AA unit men-
tioned above (see Figure 13). The AA unit is a means in the acquisition and
analysis of data for one or more system elements. It is located in a laboratory
and supported by the facilities in the lab, including glassware, chemicals, water,
electricity, and personnel. Thus, the AA is a component of the group called the
43
-------
GROtif
(LEVEL 1)
GROUP
(LEVEL 2]
GROUP
' (LEVELS)
MEANS
Figure 13. Typical Organizational Framework
laboratory. In turn, the laboratory may be one of several such facilities sup-
ported and administered by another higher-level group. Finally, all such
administrative groups are parts of the total surveillance system, the highest-
level group.
The identification of component groups in the organizational structure is a mat-
ter of judgment on the part of the system designer. Because the organizational
framework is used only in the cost analysis, the designer will generally prefer
to use convenient cost units as the organizational group.
For purposes of the computerized analysis described in Section VII, it is neces-
sary to assign identification numbers to the individual groups and means incor-
porated in the organizational framework. The highest level (i.e., system level)
group is always assigned the identification number "1". All other groups may
44
-------
be numbered arbitrarily. The means are also numbered arbitrarily in a separ-
ate sequence; no special significance is attached to number "1" in the means
sequence. The means numbers assigned in the organizational analysis must be
identical with those described below for the functional analysis.
Functional Analysis
Development of the surveillance system functional framework is done on the
basis of individual system elements. One of the basic assumptions of the sur-
veillance system design method is that observations of a given parameter at a
particular point in the stream are considered independently from all other
observations. Thus, it is not necessary to prepare a single, system-wide func-
tional analysis. The analyses are prepared separately for each parameter-
segment pair to be monitored by the candidate system (a system element).
The objective of the functional analysis is the identification of all the alternative
routes for each system element by which information on the presence or absence
of a water quality violation travels from the sampling point in the stream to the
recording point in the system.
At the highest level, there is only one path associated with each system element
(the element path). That is, information enters the system element at only one
point, the point of sample acquisition, and it leaves the system element at only
one point, the point at which the data becomes available to users. The element
path may include one or more serially connected means and two or more sub-
paths.
In turn, sub-paths may include one or more serially connected means and two or
more lower-level sub-paths. A sub-path always begins and terminates at a node,
45
-------
a branching point in an element, where information may take any of two or more
parallel sub-paths. Sub-paths may be either normally active or normally stand-
by. In the latter case, the standby sub-path is activated upon failure of the
parallel sub-path that it backs-up.
It should be noted that, in the functional analysis, it is not necessary to explicitly
identify the support facilities associated with a means, as is the case for organi-
zational analysis. In functional analysis, only the means that participate directly
in the flow of information are included in the analysis framework.
To illustrate and clarify the significance of each of these terms, consider the
example in Figure 14. Each rectangle indicates an individual means. The solid
lines connecting the means indicate the routes along which information flows in
the system. Two system elements are shown in Figure 14; they correspond to
monitoring of two different parameters in the same segment. They share
several means, including the telemetry unit, the office telemetry/recorder, and
the maintenance man who periodically collects the data from the back-up field
recorders. The first system element (Element 1-1) has one element path con-
sisting of one serial means and two sub-paths. The two sub-paths back up each-
other and are both normally operating. Each sub-path has two serial means and
no lower-level sub-paths. The second system element also has one element
path consisting of one serial means and two sub-paths. In this case, one of the
sub-paths is a stand-by sub-path, activated only on failure of the prime path.
The element paths, sub-paths and means are diagrammed in Figure 15. The
letters correspond to those in the upper right-hand corners of the means sym-
bols in Figure 14.
46
-------
/
SEGMENT t
(
V
(
SYSTEM ELEMENT 11
\~
H^
I*.
PAR AMI
ANALYZER
IB
PA RAM 2 ' —
ANALYZER
l-^
• ^
SYSTEM ELEMENT 1-2
FIELD 1 —
RECORDER
(NORMALLY OP.)
SHARED LL
TELEMETRY
UNIT
FIELD IE
RECORDER '
(ACTIVATES ON
FAILURE OF T/M)
1
1 1
». T«nEUIVLn MAINTENANCE^-
8 RECORDER MAN
J i
H
1
Figure 14. Typical Station Functional Structure
-PATH-
- SUB-PATH-
-LU
H-J
^ NODES ^-
SYSTEM ELEMENT 1-1
X
-SUB PATH •
-SUB-PATH-
I
B
X
(
D
E
IIODES
F
G
^^
}
\
{
SYSTEM ELEMENT 1-2
- STANDBY SUB-PATH-
. PATH
Figure 15. Typical Functional Frameworks for Station Illustrated in Figure 14
47
-------
As can be seen in Figure 16, a given system element may have several levels of
paths and sub-paths. The main path in this example consists of two serial
means H and M, and two first-level sub-paths. One of these first-level sub-
paths consist of two serial means, P and N. The other consists of two serial
means, 1 and J, and two second-level subpaths, each consisting of only one
serial means (K and L, respectively).
The inherent complexity of a multi-segment, multi-parameter, multi-means,
multi-path surveillance system can readily be understood from the simple illus-
trations just given. The definitions provide a framework by which to analyse the
surveillance system into a manageable body of data that fully describe the sys-
tem functioning.
SUB-PATH, LEVEL 1-
PATH
Figure 16. Illustration of Multi-level Sub-paths
48
-------
One reason for performing such an analysis is to permit the evaluation of multi-
ple utilization of single means to fulfill functions in several independent system
elements. Examples of such multiple utilization may be found in both fully auto-
matic and fully manual systems. In the former, one automatic station (a means)
may perform the sample acquisition, analysis and recording function for a num-
ber of different water quality parameters (system elements). In the latter, a
single piece of laboratory equipment may be used to perform all the analyses for
a single parameter in all the segments of the basin.
The functional analysis is performed by first generating an information flow dia-
gram such as those in Figure 15 for every system element and then creating a
table of descriptive data such as that shown in Figure 17. The table is called
the "Utilization Table. " For each system element (segment—parameter pair),
each path and sub-path is identified with a number. The single path associated
with the entire system element must be numbered "1"; all other sub-paths are
numbered arbitrarily. It is conceivable that path "1" may consist of a number
of sub-paths and no serial means, as in Figure 18. Path "1" never has any
paths parallel to it. For each path or sub-path in the system element, the fol-
lowing information is entered in the utilization table:
1. The normal status of the path or sub-path:
1 — normally operating (always the status of the element path)
the sequence of activation if normally stand-by (not valid for the
element path)
49
-------
SEGMENT
NUMBER
PARAMETER
NUMBER
PATH
NUMBER
NORMAL
PATH
STATUS
PARALLEL
SUB-PATHS
SERIES
MEANS
IN PATH
SUB-PATHS
IN PATH
Figure 17. Format of Utilization Table
2. If a sub-path, the identification number of all parallel sub-paths (all
sub-paths between the same two nodes)
3. The identification numbers of all means in series in the path or sub-path
4. The identification numbers of all the next lower-level sub-paths that
form a part of the path or sub-path.
The means identification numbers may be assigned arbitrarily, one number to
each identifiable unit in the entire surveillance system for which data on cost,
accuracy, reliability, maintainability, survivability, etc., are available. It is
not necessary to explicitly identify the level of each sub-path, since this infor-
mation is implicit in the tabulated data. The computer programs described in
Section VII automatically analyze these data for path level when needed.
Table 3 illustrates the results of the analysis for the system element shown in
Figure 18. Thus, it is possible to develop a Utilization Table, such as Table 3,
that relates the system means to their assignments in each system element.
Such a table clearly shows the multiple utilization characteristic, as the means
identification number will show up in the "Serial Means" column each time it is
50
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Table 3. UTILIZATION TABLE
Seg
No.
i
i
i
i
i
Par am
No.
j
j
j
j
j
Path
No.
1
2
3
4
5
Normal
Path
Status
1
1
1
1
2
Parallel
Sub-Paths
—
4
5
2
3
Series
Means
in
Path
—
6, 7
1, 8
4, 5
2, 3
Sub-Paths
in
Path
3, 5
—
2, 4
—
—
4
/
L
>
/
I
i
^
>
A
7
r
•HIM 1
>ATU "
n I n *
)ATU •
M 1 H i
PATU
9ATU 1
J
f
J
r
\
^
-
J
1
Figure 18. Hlustration of Multi-Sub-path Element Path
-------
assigned to a different system element. The table does not show the organiza-
tional structure within which the means operate, and it does not indicate the
feasibility of actually achieving such a utilization pattern for the planned sam-
pling scheme. Prior to preparing the Utilization Table, the system designer
must have considered in detail such questions as the inherent capacity of thf
means and scheduling conflicts.
ANALYSIS OF SYSTEM COSTS
In order to compute the cost-effectiveness of the n candidate system (r ), it
n
is necessary to arrive at an estimate of the total system cost (K ). The
development of those techniques of system cost estimation that are specific to
the design of water quality surveillance systems are presented below. The
objective of the development is a set of methods that assure that all applicable
costs are included, while promoting convenient manipulation of costs as various
candidates are examined.
Total System Cost
The total system cost of the candidate (K ) is defined in terms of the organi-
sys
zational framework described earlier in this section. Each system component,
means or group, is assigned a cost in accordance with the basic concepts des-
cribed below. For convenience, the cost assignment can be done once for all
the system components that may be considered for inclusion in any candidate
system. It is then possible to arrive at a total system cost for a particular can-
didate by summing the costs for only those means and groups incorporated in that
candidate.
52
-------
Thus, the total system cost is defined as:
K -
sys m *— g
where K = the costs of the means included in the candidate system
m J
K = the costs of the support groups necessary to the means included
in the candidate system.
Both the organizational and functional analysis of the candidate must have been
completed prior to computation of total system cost. The Utilization Table
associated with the functional analysis is used to identify those means included
in the candidate system. With that information the first term in equation (9) can
be evaluated. The second term is evaluated using the organizational framework.
The cost of a group is added to the total, if one or more lower-level groups or
means associated with it are required by the candidate.
To clarify the cost summation, consider the following illustrations based on the
organizational framework shown in Figure 13. If the Utilization Table for sys-
tem candidate number one calls for incorporation of the boat and crew, but not
the AA, GC, or BOD incubator, the total system cost for candidate 1 would
include the following terms:
K (1) = K + K + K
sys boat crew field off.
+ K,. _, , +K + . . . (10)
field ops adm. sys adm.
In contrast, a second candidate system that required two boats and crews from
the same field office would have a total system cost including:
53
-------
K (2) = K +K + K + K
sys boat 1 boat 2 crew 1 crew 2
field off. field ops adm. sys adm. + . . .
Finally, a third candidate might require, in addition to a boat and crew, an AA.
The resulting system cost would include:
K (3) = K + K + K + K
sys boat crew field off field ops adm.
+ KAA+KIK + KIK^ +K A +... (12)
AA lab lab adm. sys adm.
Notice that the cost of the laboratory group is summed in the total system cost
only when a laboratory means is required by the candidate under consideration.
Notice also that the cost of the field office is included only once, no matter how
many means associated with it are required by the system.
Cost of System Components
The costs used in estimating the total system cost are life-cycle costs, the total
expected economic cost of the component over the expected lifetime of the sys-
tem. For the purposes of water quality surveillance system design, the system
lifetime is defined to be the system duration [3], the period over which the sys-
tem is expected to maintain a fixed configuration.
In estimating the life-cycle costs of the means used to implement the water
quality surveillance system, a number of factors must be considered. The
actual estimating methods used by an individual system designer will be a func-
tion of personal preference and the fiscal structure of the organization that is to
operate the system. The aim here is to highlight the major factors that must be
incorporated in the estimates, no matter what detailed approach is employed.
54
-------
It should be clear from the preceeding illustrations that the system designer
must carefully separate those invariant costs associated with a group (no matter
how many lower-level groups or means are active) from those costs that vary as
a function of the sub-groups and means required. For example, candidate 2
above requires two boats and crews at the same field office. The costs associ-
ated with the field office are those costs that are due to the existence of the field
office, no matter how many boats and crews use it. The costs associated with
boats and crews are allocated directly to those means, so that a requirement
for two boats and crews results in a doubling of those costs over a requirement
for one of each.
Four basic costs must be considered in the estimation of cost for a means or
group:
1. the cost to acquire the means or group
2. the cost to operate the means or group
3. the cost to maintain the means or group and
4. the residual value of the means or group at the end of the system dura-
tion.
Because of the parallelism in the estimation of cost for means or group, atten-
tion is confined to the means in the following. The discussion is perfectly appli-
cable to groups as well.
In equation form, the cost of a means is:
K=K +K +K -K (13)
m acq, m op, m maint, m res, m
Each of these terms requires discussion to fully define the economic costs
included.
55
-------
The cost to acquire the means (K ) includes both direct hardware costs and
acq
the cost of all engineering, planning, purchasing and installation actions associ-
ated with the initial establishment of an operational water quality monitoring sys-
tem and specific to the means. (Under this definition, the overall costs of per-
forming the total system design activities described in this report and in [3] are
charged directly to the system level group, group 1.) Other economic costs
include the cost to finance the acquisition cost, for example interest on bond
issues, and the so called inheritance costs. The inheritance cost is the economic
cost of employing an available resource on the system under design, thereby
foregoing its use in any other activity. The inheritance cost is used to account
for the idea that apparently free resources, such as surplus equipment, may, in
fact, have a real cost which ought to be charged to the system.
The cost to operate the means (K ) is the direct and indirect charges attribut-
op
able to the performance of the system function. These charges include adminis-
trative and facilities overhead allocations (variable group costs), direct opera-
tional labor charges, and the cost of expendables and consummables, such as
chemicals and electric power.
Similarly, the cost to maintain the means (K . J is the direct and indirect
mamt
charges attributable to routine maintenance and non-routine repair of failures.
In addition to direct labor, spares costs and allocated overhead expenses, there
is also the cost associated with replacement of entire units. Such replacement
is a matter of system administrative policy. Selection of means that are
expected to require replacement within the system duration may result in an
acceptable system effectiveness, if a mechanism is provided for their replace-
ment. Fiscal mechanisms for planned replacement include direct purchase from
capital budgets and sinking funds. These same mechanisms, plus insurance,
56
-------
may be used if system policy is to replace means that fail to survive due to
catastrophic occurances, such as floods and ice jams. The costs of these fiscal
mechanisms are maintenance costs and are included in K
maint
Since many of the system means may survive the system duration, the means
may be expected to have a residual value associated with them at that time.
This residual value is of the same kind as the inheritance costs charged to the
system acquisition cost for use of surplus means from previous systems. By
subtracting the residual value from the cost of the means, only that portion of
the useful life of the means actually employed in the system is charged to the
system.
The reader is directed to [12], [15], and [16], if more extensive discussion of
these costs is sought.
ANALYSIS OF SYSTEM EFFECTIVENESS
The other element of the cost-effectiveness ratio is the total system effective-
ness (E ). The purpose of computing a system effectiveness is to provide a
sy s
quantitative measure of the success of the system at achieving its objective.
Thus, the computation of a system effectiveness depends on a definition of the
system objective and a method of predicting the success of candidate systems
relative to that objective. The following paragraphs present, first, the defini-
tion of total system effectiveness adopted for water quality surveillance systems.
Then they examine in detail the factors that contribute to system effectiveness.
Once again, the objective of the development is a set of methods to assure that
all applicable effectiveness factors are included, while promoting convenient
manipulation of these factors as various candidates are examined.
57
-------
Total System Effectiveness
For the design of water quality surveillance systems, the total system effective-
ness (E ) is defined as the ratio of the expected number of (true) detections of
sys
violations to the expected number of violations. More precisely, E is defined
sys
as:
Expected number of independent violations to be detected
_ by the system over the system duration
fj .III — —.- -I— I— —-,-•! !.—.,•. 1. •-. •»•.. I. .. |. ^ /1_4^
sys Expected number of independent violations in the
basin over the system duration
This definition of total system effectiveness is based on the assumed system
objective, the concept of independent violations, and the concept of detection.
It is similar to the definition of temporal sampling effectiveness (M, equation
(3)) developed in [3]. The difference between equation (3) and the definition of
total system effectiveness is in the spatial dimension. The temporal sampling
effectiveness is concerned only with detection of violations that occur at a single
monitoring site. The total system effectiveness deals with the detection of vio-
lations throughout a river basin by the entire monitoring system.
System Objective -
As in the previous study [3], it is assumed that the water quality surveillance
system has the abatement objective. That is, the objective of the system is to
detect every violation of the stream water quality standards. Thus, a reason-
able measure of the success of the system is the percentage of violations actually
detected, or, in the case of system design, the expected percentage detected.
58
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Violation Concept -
An independent violation is said to come into existence whenever an upstream
boundary to a region of the stream in the violation state is formed. The inde-
pendent violation continues to persist as long as the associated upstream bound-
ary persists. It ceases to exist whenever a definite upstream boundary ceases
to exist.
The concept of independent violations is crucial to the definition of total system
effectiveness. In a stream, violations typically extend over both space and time.
It is conceivable that a given violation may be observed by the system at more
than one point in space or more than once at any given point. Thus, care must
be taken in the definition of an independent violation, so that multiple detections
of the same violation may be discounted.
To permit such regions to be correctly identified and counted, a unique property
of the region must be identified as characteristic of the region. The region can
be described as a set of adjacent points on the stream where a water quality vio-
lation exists, that is, where a parameter concentration exceeds the established
water quality threshold. The concept of a unique water quality threshold is
selected in [3] on the basis of a detailed review of water quality standards. In
general, severity of the violation is not considered in the standards. Thus, the
violation is characterized as a concentration in excess of a simple threshold.
Since all points within the region share this common description uniformly, the
region can also be characterized by the location of its boundaries.
Of the two boundaries, the upstream boundary is selected arbitrarily as charac-
teristic of the region. The downstream boundary would serve equally well.
The existence and location of the region boundaries is a function of time. Fol-
lowing its initial formation, such a region may subsequently divide into two or
59
-------
more separate regions when points within the region return to the non-violation
state. Such a division is characterized by the formation of one or more new
upstream boundaries. Similarly, two or more such regions may merge when
intervening points change to the violation state. Such a merger is characterized
by disappearance of the upstream boundaries of the downstream regions.
Figure 19 presents an example progression of independent violations in a simple
river basin to illustrate the concept. Initially, there are no violations. Due to
an increase in waste discharge at the upstream point source, violation "A" is
formed and characterized by an upstream boundary to the region in violation of
the standard. Similarly, violation "B"is initiated by the downstream source.
As discharge at the upstream source continues to increase, the length of "A"
increases until it eventually overlaps "B". Since an upstream boundary for "B"
no longer exists, "B" ceases to exist as an independent violation. Later, the
discharge from the upstream source decreases, causing "A" to contract. The
violation due to the downstream source is now the sole cause of a violation at
that point in the stream and a new violation ("C") is characterized by the
reappearance of an upstream boundary at that source. Finally, the upstream
discharge ceases and violation "A"ceases to exist, while "C" continues as the
sole independent violation.
Thus, an independent violation is said to come into existence with the formation
of an upstream boundary. The mode of formation can be either directly by
transition from the non-violation state or by separation from a previously exist-
ing independent violation. Similarly, an independent violation is said to cease
to exist when the upstream boundary disappears, either directly by transition
to the non-violation state or by merger with another independent violation.
60
-------
TIME
ADV
i
ANCES
V(X) 1 -
0
V(X) 1 -
0
V/Xl 1 -
V\l\l 1
0
V(X) 1 -
0
\iiy\ i _
V\A) 1 ~
0
\IIY\ 1 -
VIA) I
0
\//v\ I .
VIA/ I
n
(NO VIOLATIONS IN BASIN)
A A ^
POINTSOURCE POINTSOURCE
VIOLATION "A"
V
r~
A A -
VIOLATION "A" VIOLATION "B"
1 1
A A
"A"
' 1 1
A A
"A" ("B" CEASES TO
A
"A"
|
A
("A" CEASES TO EXIST)
"B"
EXIST)
"C"
i „
A ^
"C"
1 .
Figure 19. Example Progression of Independent Violations in a Basin
61
-------
Detection Concept -
For purposes of the design method, an independent violation is said to have been
detected when one or more observations taken within the region of the violation
have values in excess of the threshold value set by the water quality standards.
The choice of the standards threshold as the criterion against which observations
are compared is founded in statistical decision theory. The objective of statis-
tical decision theory is to establish a basis for decision that tends to minimize
the loss due to error in the presence of uncertainty. It considers four alterna-
tive conditions, in the present context:
Pr(D IV)
Pr(D IV) Type I error
Pr(D IV)
Pr(D |V) Type II error
where D implies detection, V implies violation and the bar over the symbol indi-
cates "not". The second and fourth conditions are traditionally called "Errors
of the First and Second Kind", respectively [17] (Figure 20). They are the
probability of false dismissal and the probability of false detection. In general,
system effectiveness should be penalized for errors and the formulation of sys-
tem effectiveness should reflect consideration of both these errors.
For water quality surveillance systems, the source of the uncertainty is random
error in the observed values of water quality. The goal is to select a decision
criterion for detection in the presence of the random observational errors that
tends to minimize both Pr(D IV) and Pr(D I V). If the errors are assumed to
have a symmetrical distribution (for example, gaussian), then it can readily be
seen that the worst case for each type of error occurs when the true value of the
water quality parameter is near the standards thresholds (Figure 21). In that
62
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P(C +U
Figure 20. Illustration of Type I and Type II Errors for Gaussian Error
Distribution with Mean (I ) and Standard Deviation (
-------
WORST
CASE
WORST
CASE
Figure 21. Illustration of Worst Case Error Probabilities for Gaussian Error
Distribution (T=0)
64
-------
MINIMIZED
CT, C(t)
MAXIMIZED
EQUAL
EQUAL
> c(t)
MAXIMIZED
CT, C(t)
MINIMIZED
•u
Figure 22. Illustration of Effect of Decision Threshold, C^, on Error
Probabilities for Worst Case Condition
65
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Thus, an independent violation is said to be detected when one or more observa-
tions of that violation have values in excess of the standards threshold. In count-
ing detections, multiple observations of the violation state are ignored; the vio-
lation is considered to have been detected once, no matter how many observations
indicating the violation state are taken.
Approximate Mathematical Formulation
In the development of the cost-effectiveness methods, an approximate mathema-
tical form of the total system effectiveness is used. The approximate form is
written as:
K J
E E vv«
_ k = 1 j = 1
E
sys I J
E Z V* <'• »
(15)
where n ** (i, j) = the expected number of independent violations that occur for
parameter j in segment i
n * (i , j) = the expected number of independent violations of parameter
j detected in monitored segment i
K
I = the total number of segments in the basin
J = the total number of parameters included in the system
design
K = the total number of monitored segments
i = the index number of the k monitored segment.
The approximate formulation is based on the assumption that the surveillance
system is a relatively sparse network of monitoring stations. Under the assumed
66
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sparse conditions, violations that commence upstream of or in a monitored seg-
ment have a low likelihood of continuing downstream to the next monitored seg-
ment. This effectively eliminates the need to consider events in which an up-
stream station fails to sense a violation when a downstream station does. The
same result would be achieved if the effectiveness of each individual system ele-
ment, E(i , j), were high, that is, if n * (i, , j) were nearly equal to the number
K Q *^
of violations occuring in the monitored segment.
The superscript asterisks are used to define the two different types of violations
ennumerated by n * and n **. Three types of violations can be defined with
d v
respect to a segment i. They are:
1. Type 1 Violation—a violation in segment i, that begins anywhere down-
stream of segment H and ends anywhere (downstream of i).
2. Type 2 Violation—a violation in segment i, that begins in segment i and
ends anywhere.
3. Type 3 Violation—a violation in segment i, that begins anywhere and
ends anywhere.
The second type of violation is the kind associated with the superscript **, while
the first type is associated with the superscript *, if i = i and i = i _ (k-1
indicating the next upstream monitored segment ) (Figure 23). The third type of
violation is not used in the present methods. It was used in [3] for computation
of initial segment priority and is presented here for comparison with types 1
and 2.
Since only those violations that have an upstream boundary in segment i contri-
bute to n ** (i, j), the summation in the denominate:
the total expected number of violations in the basin.
bute to n ** (i, j), the summation in the denominator of equation (15) is clearly
67
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'VIOLATIONS
X
>
MONITOR K-1
MONITOR K
1 --
1 1 1
**VIOLATION
i -
1 ' 1 l 1 ' -
MONITOR K-1
MONITOR K
Figure 23. Illustration of Violation Types
The numerator of equation (15) is a conservative estimate of the expected num-
ber of detections, since it ignores the (presummably) small expected number of
violations that are not detected in segment i and are detected in segment i .
k-1 k
Included in n * are those violations that begin anywhere in the interval between
d
and including segments i and i , and that extend to segment i . Those vio-
K "~ -I- K K
lations that both begin and end in the interval are not counted since there is no
chance that they would be detected by the system.
A complete discussion of the development of equation (15) may be found in Appen-
dix B. It should be clear from this expression that the measure of system per-
formance used here constitutes a shift in emphasis from the concept of segment
priority developed in [3]. (See Section VII for a discussion of this point.)
68
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Effectiveness of System Elements
The effectiveness of the individual system element is represented in the numera-
tor of equation (15) by n * (i , j). In a given segment for a given parameter, the
d k
expected number of detections can be related to the expected number of violations
by:
n * - Pr (D V) n * (16)
where n * is the expected number of type I violations.
The factors contributing to the effectiveness of a system element may be deter-
mined by considering those events that must take place to achieve the detection.
Given a violation in a segment in which a station is located, the following must
be jointly true:
1. one or more samples must be scheduled during the period of the viola-
tion
2. the method of observation and analysis must be sensitive enough to detect
the violation
3. the system element must not have failed either:
a) in a repairable mode, or
b) in an irrecoverable mode.
The first two of these events relate to whether or not the system element is
capable (c) of detecting the violation when operating normally. They are depen-
dent on the complex interaction between the known characteristics of the system
element and the expected characteristics of the violation process. The third
event is entirely independent of the violation process, being solely dependent on
69
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the characteristics of the system element and events external to the system,
such as vandalism and weather. The two types of failure included in the third
item may be treated separately, because they have different properties. The
system element has survived (s) if it has sustained no failure that cannot be
repaired. Given that it survives, the system must also be available (a); it must
not have failed and be under repair.
The effectiveness of the system element may be written as:
n * = Pr(D I V) n * = Pr(c, a, s I V) n * (17)
d v v
That is, the effectiveness of a system element is equal to the joint probability
that the element is capable of detecting the violation and available to detect it
and has survived long enough to detect it, given that a violation occurs. Because
availability and survivability (these two terms are defined more precisely below)
are both independent of the violation process, equation (17) may be written as:
n *= Pr(D IV) n *= Pr(c IV, a, s) Pr(a|s) Pr(s) n * (18)
Each of the probability terms in equation (18) has been given a name for clarity
in discussion. They are:
(Pr (c | V, a, s) n *) = Capability = C
^— — — v
Pr (aj s) = Availability - A
Pr (s) = Survivability - S (19)
Thus, the effectiveness of the system element is:
n * - C • A • S (20)
d
As will be seen below, capability has been carefully defined to include n *. This
permits use of mathematics developed for [3] in the present context.
70
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ESTIMATION OF SYSTEM EFFECTIVENESS
The estimation of system effectiveness requires the estimation of two quantities:
n * (i , j) and n ** (i, j). The app
titles is described in the following.
n * (i , j) and n ** (i, j). The approach used in computing each of these quan-
Estimation of Number of Violations
Computation of the denominator for equation (15) requires estimates of the
n ** (i, j). By extension from [3] :
*
where T ** is the expected duration of a type 2 violation and T ** is the expected
interval between type 2 violations. Estimation of the necessary values for T **
and T ** is discussed later in this section.
Estimation of Element Effectiveness
Estimation of the effectiveness of each system element, n * (i , j), requires
d k
the estimation of each of the components of effectiveness: capability, availability
and survivability. These, in turn, depend on the properties of the means assigned
to the system element and on the organization of those means.
For purposes of this study, it has been assumed that the necessary information
on individual means will be available to the system designer. It is not the intent
of this report to provide instruction in the performance of the test programs
necessary to obtain these data for hardware equipments. Neither is it intended
to develop methods for estimating these properties for human components of the
system. The reader is referred to the literature, e.g., [12], [13] , and [14],
71
-------
for these techniques. It is wholly within the prerogatives of the governmental
agencies operating water quality surveillance systems to expect and require
these data from the hardware manufacturers.
Given the appropriate data on the system means, the estimation method must
combine these data to reflect the influence of system configuration on system
effectiveness. The approach used differs for each of the three components of
element effectiveness. These will be discussed individually below, survivability
first, followed by availability and capability.
Estimation of Survivability -
Survivability is, literally, the probability that the system element has experi-
enced no unacceptable, irrecoverable failure since it was "turned on".
By "irrecoverable failure" is meant a failure for which no provision has or can
be made to repair or replace the failed means. As discussed under Analysis of
System Costs, the incorporation of such a provision to back up catastrophic fail-
ures is a matter of system administrative policy that must be decided during the
system design. If the back-up is, for example, a replacement unit kept at a pro-
tected site, the unit is incorporated in the system flow diagram as a stand-by
path. If the back-up requires activation of a materially different surveillance
system, then it is not included in the flow diagram. It is analyzed as if it were
a separate candidate system and handled according to equation (8).
An "unacceptable failure" is any failure or combination of failures of the means
associated with the system element that results in an interruption of the flow of
information in the element path. Such an interruption occurs whenever a means
fails and no back-up exists to take its place, either because there is no back-up
or because the back-up has also failed.
72
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For example, consider the simple system element diagrammed in Figure 24.
The normal condition of the system element is State 0. States 1 and 6 constitute
unacceptable failure states for the element, since all possible information flow
routes are blocked in each case. While failures have occurred in States 2 and 4,
they are acceptable, since the element continues to function normally. It should
be noted that the possibility for off-line failure of the stand-by means is included.
If the unacceptable failures illustrated in Figure 24 are irrecoverable failures,
then the system element has failed to survive. That is, since there is no way to
return a failed means to service, there is no way to return the system element
to an acceptable state and the system element will be out of service from the
time of failure forward.
Thus, the estimation of survivability requires the estimation of the probability
that the system element remains in an acceptable state for the system duration.
The survivability of the system element is a function of the survivability of the
associated means and the configuration of those means in the element.
For purposes of this development, it is assumed that the survivability of a
means may be described by a Poisson process. That is, the following assump-
tions about the failure process are made:
1. the probability of a failure in the interval (t, t + dt) is Xdt
2. the probability of more than one failure in the interval (t, t + dt) is of
order O(dt) - 0.
The failure rate, X , of the means is assumed to be a constant with respect to
time. It may, however, take on different values depending on whether or not the
means is in operating or stand-by status.
73
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'ERATI
A
NG
r-
1-
c
OPERATING
STAND-BY
VFAILED,
X-
OPERATING
OPERATING
STATE 0
OPERATING
STATE 1
STAND-BY
FAILED
STATE 2
OPERATING
OPERATING
STATE 4
FAILED
ERATI
A
NG
/
\
X
X
FAILED
^
s
FAILED
STATE 6
STATE 7
Figure 24. Failure States for Typical Three-Means Element
74
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The assumption of a Poisson process is made primarily for purposes of tracta-
bility. It is an assumption that is almost traditional in reliability and maintain-
ability theory (see for example [13] and [14] ). In making it, all temporal vari-
ability in the failure process is ignored. In the present case, such variations
as the higher likelihood of ice floes in early spring and of floods in late spring
are not considered for their impact on survivability. While these variations
may, in fact, be important in detail, the objective of the project is to provide a
system design method based on reasonable engineering assumptions. It is
believed that the results of any comparison between alternative surveillance sys
tems will be comparatively insensitive to this engineering assumption.
The number of different failure states that a system element may assume is:
Ng (ik, j) = 2 (22)
where M is the number of means associated with the element. This is simply
the number of different combinations of the M means associated with the element.
Transitions from one failure state to another may occur through the failure of an
additional means. For example, in Figure 24 the transition from State 2 to State 6
corresponds to failure of means "C". The probability of such a transition in the
interval (t, t + dt) is:
\^ dt
Co
where ^ is the failure rate of means C, while it is operating (i.e. , not in
standby).
2
Information on the N possible transitions can readily be organized into an N
s s
by N square matrix, called the transition matrix. Figure 25 illustrates the
S
matrix for the three-means system element shown in Figure 24. There are
75
-------
TO-STATE
234
o4
cc
5
6
Figure 25. Sample Survivability Transition Matrix
3
2 =8 possible failure states. The matrix is organized so that the rows represent
the state at time t (from-state) and the columns represent the state at time t +dt
(to-state). Since there is no possibility for repair of a failed means, all X's
below the diagonal are zero. The upper triangle is composed of the X's for
each possible transition due to failure of a single means. Transitions corre-
sponding to failure of two or more means are assumed to have probability zero.
The dt's are not written in the matrix, but are assumed present. The diagonal
elements correspond to the probability of remaining in the initial state for the
interval (t, t + dt); they are equal to 1 - (sum of the transition probabilities).
It is shown in [13] that the probability, P (t), of the system element being in
n
State n at time t can be derived directly from the transition matrix. The state
probability vector, P(t), is defined as:
76
-------
P(t)= [PQ(t), P^t), . . . , PN (t)] (23)
s
The vector of Laplace transforms of the state probabilities, P(s), is defined as:
P(s)=[P0(s), P^s), . . . , PN (s)] (24)
s
then, from [13] :
P(s)= P(0) (si- B)' (25)
where I = the identity matrix
B- S - I
S = the survivability transition matrix
and the negative exponent implies matrix inversion. Finally, the desired proba-
bility is obtained from the inverse Laplace transform:-
-1
Pn(t) - £ (Pn(s)) (26)
Using equation (26), the survivability is computed as:
P (T) (27)
k \
where the n refers to the k acceptable failure state and T is the system dura-
rC
tion.
Thus, estimation of survivability consists of the following steps:
1. preparation of the transition matrix, S
2. determination of the acceptable failure states
77
-------
3. computation of the ~Pn,(^) from the transition matrix
4. computation of S from the P (T).
Estimation of Availability -
Availability is the probability that the system element is not in an unacceptable
state of temporary failure at any time, t, after initial "turn on", given that it
has survived.
A "state of temporary failure" means a condition of failure for which repair is
possible, but has not been completed. The emphasis here is on repair of a fail-
ure, not on routine maintenance downtime. Thus, the process is a random one,
rather than periodic.
As in survivability, an unacceptable failure is any failure or combination of fail-
ures of the means associated with the system element that results in an inter-
ruption of the flow of information in the element path.
In analyzing the system element for availability, the method of describing the
element is essentially the same as that used for survivability. An information
flow diagram such as those shown in Figure 24, may be prepared for the system
element. The availability flow diagram for a given element may be expected to
differ from the survivability flow diagram in many cases. One major point of
difference is the exclusion of some back-up paths from the availability diagram.
The excluded back-up paths are those that would not be activated for short term
system failures. For example, total loss of an entire automated station (failure
to survive) might be cause to mobilize a complete replacement unit. Temporary,
repairable failure of an associated telemetry unit might activate a stand-by
recorder, but would not be likely to require complete replacement of the unit.
78
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Another major point of difference is the identification of the means associated
with the system element. While survivability is concerned with total loss of
facilities physically near enough to be destroyed as a group, availability is fre-
quently concerned with the sub-units of such grouping.
In estimating availability, it is assumed that both the failure process and the
repair process are Poisson processes. As in survivability, the assumption is
made primarily for tractability. The approximations involved in making the
assumption are discussed in [13]. The Poisson process ignores such considera-
tions as the wearing out of mechanical parts, that would increase the failure
rate over time. It also assumes that the equipment is designed so that high like-
lihood failures are more easily repaired than low likelihood failures. For the
purposes of system-level design of water quality surveillance systems, it is felt
that ignoring such factors is a reasonable engineering approximation.
A transition matrix can be prepared for availability in the same was as the matrix
for survivability, except that transitions from failed to non-failed states must be
M
considered. The number of possible system states is, as before, N = 2 . The
s
lower triangle is composed of transitions from failed to repaired status; the
upper triangle is, as before, composed of failure transitions. Again the diagonal
elements of the matrix are the probabilities of remaining in the state for the
interval (t, t + dt).
Figure 26 illustrates the availability transition matrix for the system element
shown in Figure 24. The failure rate of each means is shown as a \ and the
repair rate as a |i.
It is shown in [13] that a system having the properties described above tends
toward an equilibrium availability state as time increases. That is, the avail-
ability at any time, t, is independent of the time. Such a condition results in a
79
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Figure 26. Sample Availability Transition Matrix (where the ( ) indicate
the sum of all the row transition probabilities)
set of linear algebraic equations based on the availability transition matrix, of
the form:
N
(28)
plus the identity:
N
i = 1
(29)
where the A are the elements of the availability transition matrix, A, and P
U i
is the probability of being in state i.
80
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The system of linear equations can be solved directly for the P.'s. Then the
availability, A, can be computed as:
A = Pn (30)
k k
tVi
where n refers to the k acceptable failure state.
Thus, estimation of availability consists of the following steps:
1. preparation of the availability information flow diagram
2. preparation of the transition matrix, A
3. determination of the acceptable failure states
4. solution of equations (28) and (29) for the P.
5. computation of A from the P .
\
Estimation of Capability -
The concept of element capability is an extension of the concept of sampling
effectiveness developed in [3] (see Section IV). In that development, considera-
tion is given to the effect of discrete sampling of the river on the probability of
detection of a violation, given that a violation occurred. It is assumed in [3]
that the violation is detected if a sample is taken during the violation. It is also
assumed that the sampling process continues without breaks for the duration of
the system and that all samples are taken at the preferred station location in
each segment.
The above restrictions are removed in estimating element capability. In addi-
tion to the effect of periodic sampling, capability incorporates the following fac-
tors:
81
-------
1. the effect of routine maintenance downtime
2. the effect of designing the system so that samples are taken at a point
other than the preferred station location
3. the effect of random errors in the analytical process.
Other factors may be expected to affect the capability of the system element,
but they have been assumed to be negligible. Such factors as the random error
in locating the station and the random error in timing the sample are considered
small, in comparison to the factors included in capability.
Capability (C) is defined above as (equation (19)):
C = Pr [c IV, a, s] n * (31)
Implicit in the definition is knowledge of the preferred station location, x , the
m
designed station location, x, the effective sampling interval, A , the mean error
c
of the analytical process (the calibration accuracy), ?, and the standard devi-
ation of the analytical process (the precision),
-------
In its place, a less elegant, more pragmatic approach has been used. That
approach also draws on the results of the previous study, in combination with
a straightforward consideration of sampling error. The result is clearly an
approximation and is shown to be conservative, i. e., to underestimate capability.
The expected number of independent violations that will be sampled at least once
at a given observation point can be computed directly from the equation for
expected number developed in [3]. The only adjustments necessary are in the
location considered, the actual sampling location instead of the preferred sam-
pling location, and in the sampling interval used. Thus, the expected number of
violations sampled (n *) is;
s
n * =
T * T *
0 1
exp
(-A \ / -A \
e\ / e\
vrexp(v)
(33)
where the T * and T * are estimated for type 1 violations at the actual sampling
location and the A is the sampling interval adjusted for routine maintenance.
"
The approach used in estimating T * and T * is discussed later in this section.
The effect of routine maintenance is to modulate the sampling process, periodi-
cally turning it off. The result is an average, or effective, sampling period,
A , that is slightly greater than the sampling interval of the sampling process,
e
A. The difference between A and A depends on the maintenance policy, as
developed in Appendix D. If the next sample following return to service is taken
in phase with the previous schedule:
N +N +1
A =-J H A (34)
e N +1
u
83
-------
where N , = Integer (T ,/A)
d d
N = Integer (T /A)
u u
T & T = the scheduled downtime and maintenance interval (uptime)
d u ,. .
respectively.
If the next sample is taken immediately following return to service and the sam-
pling schedule adjusted to the new phase, then:
N A+ T
d u
Ae = -N-TT- <35>
u
The probability of a given violation that is sampled at least once being detected
is a function of the sampling error and the number of times that the violation is
sampled.
A conservative estimate of number of independent observations of the average
independent violation (n ) is:
(36)
where T * is the average duration of a type 1 violation at the station location.
This estimate is conservative, since T * is less than the average duration of
violations that are sampled at least once. That is, the shortest violations tend
not to get sampled at all and are not counted in n *. Thus, they should also be
s
left out of the n computation. They are not, so the estimate is conservative.
o
The probability of falsely dismissing a violation, on the basis of a single obser-
vation, Pr [D I V], is a function of the mean error, ? , the standard deviation of
the error,
-------
known, a conservative estimate of Pr [D IV] is the maximum probability of
error, P , that is obtained when C = C . If the observational errors are
m T
assumed gaussian:
P >N(C +?,T),?/^N(0,1)
-CO -00
Thus, a conservative estimate of the probability of falsely dismissing the aver-
age violation that is sampled is:
Pr [DIV] = (P )n° (38)
m
and the probability of making the correct decision is
Pr [DIV] = 1 - Pr [DIV] = 1 - (P )° (39)
Combining the two factors, the capability of the system element is conservatively
estimated as:
C —
n
1 - (P ) I n * (40)
m ' ~
Estimation of T and T
The foregoing methods for evaluating system effectiveness depend on the avail-
ability of estimates for T *, T *, T ** and T ** in equations (21) and (33).
The estimation approach used in the analysis of cost-effectiveness is essentially
identical with that developed in [3] for estimation of T and T , the expected
values characteristic of a type 3 violation. The threshold concentration in the
85
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stream quality standards is replaced by the threshold flow that results in stream
quality reaching the standards threshold. The USGS stream gaging station
records are then searched for periods in which stream flow fell below the thres-
hold value in the reach under consideration. The associated durations are
recorded and the expected durations estimated by the average values of the vio-
lations found in the historical records. That is:
T^L y t
0 N •£-' on
n - 1
(41)
T -1 f .
1 N 2-* In
n = 1
where the t and t are the interval preceeding and the duration of the n vio-
on In
lation, respectively.
Estimation of T *, T *, T **, and T ** requires the counting of only those
violations that fit the appropriate type descriptions. In searching the historical
flow data, comparisons must be made to determine the spatial extent of each
violation found in the i segment. For the n violation, t * and t ** are
on on
considered to be the interval preceeding the n violation of the corresponding
type, even though a violation of a different type may exist in the i segment
during that period.
86
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SECTION VII
DESIGN OF WATER QUALITY SURVEILLANCE SYSTEMS
With the development of the cost-effectiveness design methods presented in Sec-
tion VI, a complete quantitative design method encompassing all the factors in
Figure 1 can be assembled and computer programs can be prepared. The quan-
titative design method is a result of merging the preliminary design methods of
[3] with the methods for analysis of system cost-effectiveness described in this
report. This section provides a summary of the design methods and the compu-
ter programs used to implement those methods. Following the summary are
instructions on the preparation of input data and use of the programs. Details of
the computer program development may be found in Appendix E.»
OVERVIEW OF DESIGN METHODS
The overall process of designing a river basin surveillance system is dia-
grammed in Figure 12. That process can be thought of as composed of two
design phases, described in the following paragraphs.
The first, or preliminary design, phase is directed at developing a sufficient
description of the river system to allow the designer to rationally allocate his
surveillance resources. The description consists of: 1) a set of preferred
locations for the observation of the water quality parameters under considera-
tion, 2) a measure of the importance of making observations at each of those
preferred locations, and 3) data that permit a preliminary evaluation of the
efficiency of various sampling rates at detecting water quality violations. Using
this description of the river basin as it relates to surveillance, the system
designer may then select one or more candidate surveillance systems for further
evaluation.
87
-------
During the second, or final, design phase, the system designer selects a pre-
ferred surveillance system configuration on the basis of his evaluation of the
candidates. The evaluation considers three aspects of the system design:
1) the expected interaction between the surveillance system (working according
to its design specifications) and the natural system, 2) the likelihood that the
system is not meeting its specifications, and 3) the anticipated cost of the system
candidate. Using the information obtained from his evaluation, the system
designer may either select one of the candidates for implementation or evaluate
additional candidates designed on the basis of the knowledge gained during the
first evaluations.
The computer programs discussed in this section are designed to support the
system designer in both the preliminary and the final design phases of the sys-
tem design process. They are intended to provide for use of the computer in
the most tedious and complex aspects of the design selection and evaluation
process. No attempt is made to automate all the activities required by system
design. For example, it is still up to the designer to assure himself that the
sampling schedule specified for a candidate is achievable with the organization
and resources allocated to the candidate.
Based on the experience of [3] and the early engineering of the current project,
several areas can be identified as being appropriate for computerization. These
areas are: 1) the description (model) of the river basin, 2) the estimation of
the expected durations T and T from USGS flow records, and 3) the computa-
tion of availability and survivability. The labor involved in manually computing
the results of a river basin mathematical model is documented in [3]. Inclusion
of a computerized basin model needs no further justification. The computation
of T * 'T * T **, and T ** requires the search of long USGS flow records
88
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(many years) for threshold crossings. Detailed consideration must be given to
the spatial persistence of the violation. In a typical basin described by 40
reaches, design of a system to detect violations of 5 water quality parameters,
using a 5 - year (1825 days) record of daily flows at 8 separate gaging stations
would require a spectacularly large number of individual comparisons with
threshold values. It is best computerized. Similarly, one candidate system
for the above basin might have 5 stations monitoring 3 water quality parameters
each, with typically six means assigned to each system element (parameter-
station pair). The computation of availability and survivability would thus
require the generation and solution of 30 transition matrices consisting of 64
elements each. Thus, as a minimum, the computer programs must be capable
of computing the preliminary and final aspects of the interaction between the
basin and the surveillance system, and of computing the reliability engineering
aspects.
Tn addition, a relatively complete analytical program can be achieved by includ-
ing coding to evaluate total cost and perform the final division of total cost by
system effectiveness to yield the cost-effectiveness of the candidate.
The computer programs described in this section reflect these considerations.
DESCRIPTION OF DESIGN METHODS
The design methods can be thought of in terms of six basic task activities that
encompass the processes and decisions suggested by Figure 12. Figure 27
shows the task flow of system design. As indicated, the modeling of the river
basin can be done essentially off-line with respect to the system design. The
task flow can be entered at either of two points. The first entry point is used
when the designer's objective is to evaluate either an entirely new surveillance
89
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c
ENTRY 2
ENTRY 1
)
TASK 1 -
DATA
ASSEMBLY
I
TASK 3 -
PRELIMINARY
DESIGN
TASK 4 -
CANDIDATE
DESIGN
1
TASK 5 -
CANDIDATE
EVALUATION
TASK 2 -
BASIN
MODELING
ITERATE
SYSTEM
DESIGN
Figure 27. Design Task Flow Diagram
90
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system or an existing one developed with another design approach. The second
entry point is appropriate when the designer wishes to evaluate the effects of
incremental improvements in an existing or candidate system, one for which the
earlier task results are still valid. A third design objective might be the evalu-
ation of an existing surveillance system on the basis of new information about
the river basin. In this third case, the river basin model must be revised and
the first entry point is used.
Task 1 - Data Assembly
The first step is the gathering of basic data descriptive of the river basin, of
the water quality standards and of the surveillance methods. A full description
of the necessary stream quality, stream characteristics, and effluent data
required may be found in [3]. Assuming that the designer intends to use the
computerized design methods detailed later in this section, [l] and [18] are useful
in determining the data needs of the computerized basin model. The required
information on surveillance methods is that necessary to fully characterize the
candidates to be evaluated. The system characteristics are summarized in
Table 4. Data on the indicated characteristics should be collected early in the
design project during Task 1.
In addition, two essential determinations should be made during Task 1. Since
the planned system duration (see Section IV) is always an externally imposed
constraint on system design, an early determination of system duration
should be made. At the same time, the designer must choose the water quality
parameters to be considered in the design analysis. The decision is crucial,
since it affects the evaluation of cost-effectiveness. A parameter included in
the analysis, but never sampled, may cause a reduction in system effectiveness.
91
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Table 4. SUMMARY OF SYSTEM CHARACTERISTICS
System Characteristic
• Cost
Acquisition
Maintenance
Operating
Residual (Value)
Organization
• Availability
• Unit Reliability (\)
• Unit Maintainability (H-)
• Configuration
• Survivability
• Unit Survivability (X.)
• Configuration
• Capability
Location
Sampling Rate
Scheduled Maintenance
Calibration Accuracy
Precision
• Nominal Characteristics
• Parameters Considered
• Segments Monitored
• Parameters Monitored
• System Duration
Task 1
Input
Data
X
X
X
X
X
X
X
X
X
X
Input
Decision
X
X
Task 4
Design
Variable
X
X
X
X
X
X
X
92
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Thus, a system designer must weigh the goals of his system in selecting the set
of parameters to be analyzed. In general, the water quality standards to be
enforced with the system will provide a guideline, listing specific parameters
for enforcement.
Task 2 - Basin Modeling
Task 2 calls for the calibration of a mathematical model descriptive of the river
basin under consideration. It is assumed in this report that the designer will
employ RIBAM (see Section IV and Appendix A), a computerized basin model.
Detailed information on the calibration of RIBAM using the Task 1 data inputs
may be found in [7]. Additional useful guidance may be found in the User Hand-
book of [3].
In summary, Task 2 activities include: 1) identification of major point sources
or groups of sources (impact nuclei), 2) selection of the basin segmentation
scheme, and 3) preparation of the Standard Data Deck for the design conditions.
The procedure is accomplished using the stand-alone version of RIBAM.
Should the designer choose to use some other basin model, either computerized
or manual, the activities required to calibrate the model can be expected to be
similar to those of RIBAM. Thus, the RIBAM calibration process serves as a
useful guide to Task 2.
Task 2 can, of course, be done externally to the design process. RIBAM was
developed for river basin planning purposes, not surveillance system design.
It may be anticipated that many of the activities required in Task 1 and 2 will
already have been accomplished when the monitoring system design project
begins. One of the objectives in making use of a computerized model is the
realization of such "spin-off" benefits.
93
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Task 3 - Preliminary Design
The objective of Task 3 is the development of information to allow rational
selection of candidate surveillance systems. That information includes: 1) the
set of preferred sampling locations, 2). a measure of the preference for sam-
pling at each of those locations, and 3) data on the temporal variability of water
quality at those locations.
The preferred sampling location is the point in each reach of the basin where
there is the greatest likelihood of a violation for each parameter. That point is
shown in [3] to correspond approximately to the location of the expected worst
conditions in each segment as determined by the river basin model. Table 5
indicates the assumed location for each category of water quality parameter.
Table 5. PREFERRED SAMPLING LOCATION BY PARAMETER CATEGORY
Category
Preferred Sampling Location
Conservative
Non-Conservative, non-coupled
Non-Conservative, coupled
("Not to exceed" threshold)
Non-Conservative, coupled
("Not less than" threshold)
Any point in segment
Head of segment
Point of maximum value in segment
Point of minimum value in segment
The relative preferrence for monitoring at each preferred location is the
expected number of violations having upstream boundaries in the segment
during the planned system duration, n **. The expected number is computed
from estimates of TQ** andT^* using equation (21).
Use of n ** as a measure of preferrence for monitoring a segment constitutes
v
a shift from the approach developed in [3]. The previous approach was to com-
pute a measure (a) of the probability of violation (TT) in the segment and select
94
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those segments with high a (highir ) for surveillance. The probability of violation
v
in a segment is not of direct use in attempting to maximize E (equation (15)),
sys
since segments that are nearly always in a violation state will have a high proba-
bility of violation, but a small n **. Similarly, those segments with low proba-
bility of violation would also have a small n **, since they would tend to always
be in a non-violation state. Thus, a better strategy for the selection of segments
to monitor is to choose those segments with large n **, no matter what the
probability of violation.
It is interesting to note that this result, derived in the context of statistical
decision theory, is similar to a central concept of information theory. That
concept can be stated generally as: "the more likely an event is, the less
information is conveyed us by the knowledge of its actual occurence." [19]
Thus, there is little information to be gained from monitoring segments in which
there is a high probability of being in one of the states. The segments from
which the most information may be gained from monitoring are those in which
the greatest variability, i.e. the largest n **, exists.
Replacement of a with n ** has an additional advantage; it eliminates the need to
assume a gaussian distribution of the water quality parameter. The assumption
of a distribution was necessary to the estimation of the probability of violation [3],
While the use of the gaussian assumption appears to be reasonably sound in this
case, the elimination of any assumption is welcome in an engineering
method.
Selection, in Task 4, of the sampling rates for monitoring is done with the
guidance of Figure 5, developed in [3]. The necessary inputs to use of the
sampling effectiveness rating curves are T and T . For the present case, it
is sufficient to approximate these with the T ** and T ** used in estimation of
n **.
v
95
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Task 4 - Candidate Design
The fourth task is the focus of the design process. Based on the preliminary
design data supplied by the computer in Task 3, the system designer must
design one or more candidate systems. Using the information on n ** com-
puted in Task 3, the first step is the choice of segments and parameters to be
monitored. For each parameter to be monitored in each reach of the basin, the
system designer must then specify:
Sampling Location
Sampling Rate
Sampling (calibration) Accuracy
Sampling Precision
Configuration of Means Used in Sampling
Maintenance Schedule
Selection of each of these requires a careful balancing of such factors as the
resources available to the designer, the characteristics of those resources, the
external constraints of access to the river and legal requirements, and the
practical limitations of manpower and equipment scheduling. It is assumed that
the system designer is capable of performing all the necessary design functions
to assure that the nominal system characteristics specified can be achieved with
the equipments and schedules specified.
Specification of sampling location requires analysis of both the preferred location
computed in Task 3 and the ability to actually sample at that location. Another
factor to consider is the grouping of monitoring of several parameters at the
same site, perhaps different from the preferred location for each.
Sampling rate is based on the effectiveness indicated for a given rate using the
T ** and T ** with Figure 5. Also affecting sampling rate are the sampling
96
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capacity of the equipment proposed and the scheduling of equipment and person-
nel.
The accuracy and precision to be achieved by each system element (parameter-
segment pair monitored) is estimated as the overall error expected for the set
of means in the element configuration, when working as intended. (Any other
condition is considered a failed state.)
Task 5 - Candidate Evaluation
During Task 5, the methods developed in Section VI are applied to the candidate
designs prepared in Task 4. Each candidate is evaluated for total cost, total
effectiveness and the cost-effectiveness ratio. Intermediate results, such as
availability, survivability and capability, may be retained for guidance in itera-
tive ly improving candidates.
Task 6 - Design Selection
Selection of the final system design is performed in Task 6 by comparison of
the Task 5 evaluation results with predefined selection criteria in three areas:
cost, effectiveness, and cost-effectiveness ratio. If none of the candidates
satisfy the selection criteria or if it is desired to improve on particular candi-
dates, the designer may choose to return to Task 4. In doing so, the evaluation
data may be used to guide the development of new or improved candidates. For
example, low values of capability may indicate a need for improvement in the
nominal system characteristics, such as sampling frequency or reaches sampled.
Poor survivability or availability may call for improvement of the means
employed or incorporation of redundancies in the system. It should be pointed
out here that the most cost-effective system is that system with the least cost
per unit effectiveness, even though that value may be several times the true
cost of the system. Q7
-------
OVERVIEW OF COMPUTER PROGRAMS
The monitoring system design analysis computer program consists of a main
program and 33 subprograms. The relationships among the subprograms are
diagrammed in Figure 28. As indicated in the figure, the coding that constitutes
the analysis program comes from three different sources. The majority of the
programming has been prepared by Raytheon OES specifically for the design
analysis project. Other sections are taken, essentially intact, from RIBAM,
the river basin model developed by Raytheon OES for the EPA. (See Section IV
and [7].) International Mathematical and Statistical Libraries, Inc. (IMSL) has
provided specific subprograms that perform general mathematical operations,
such as curve fitting and solution of systems of linear equations. (See Acknowl-
edgements.)
The program coding adopted from RIBAM is computationally identical with that
found in the stand-alone version of RIBAM. The major change has been the
elimination of the printed output from those subprograms. It is assumed that
the Standard Data Deck used for system design analysis will have been calibrated
using the stand-alone version of RIBAM. Thus, there is no need for printed
output from the model portion of the design analysis program.
The organization of the main program reflects the basic computational sequence
necessary in the evaluation of a monitoring system design. Figure 29 is a flow-
chart of the overall design analysis program. The initial step is a description
of the natural (river) system to be monitored. This information includes the
water quality parameters under consideration (not necessarily those monitored),
the physical description of the river basin (tributaries, junctions, reaches,
flows, etc.), the point-source loads (location, quantity, parameters, etc.), the
reaction and decay rates, the relationships among the flows in individual reaches
98
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CO
CO
I I PROGRAM CODING SPCCIFIC TO COST EFFECTIVENESS ANALYSIS
rI PROGRAM COOING FROM RIB AM (MAY BE SLIGHTLY MODIFIED; SEE TEXT)
I V PROGRAM COOING PROVIDED BY INTERNATIONAL MATHEMATICAL AND STATISTICAL
I 1 LIBRARIES. INC. (SEE ACKNOWLEDGEMENTS)
Figure 28. Program Organization
-------
Figure 29. Top Level Program Flowchart
100
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and those recorded by USGS gaging stations, and the range of flows to be consid-
ered for design purposes. The majority of the information is provided by the
previously calibrated RIBAM Standard Data Deck. Using this information, a
sequence of computations must be performed for each water quality parameter
under consideration. The objective of the computations is either the evaluation
of the capability of each system element, as defined in Section VI or the develop-
ment of the preliminary design data. For each parameter, the nominal charac-
teristics and the factors directly affecting capability must be supplied to the
design analysis program. Using the approach developed in [3], threshold flows
are computed, corresponding to the threshold concentrations specified in the
stream standards. The threshold flow values are then compared with a long
record of actual USGS gaging station observations to derive expected durations
of violation and non-violation. The expected number of violations (n **) and of
detected violations (n *) may then be computed, the latter using information on
sampling interval and observational errors. For preliminary design, the program
terminates at this point. Having completed the computation of system capability
for each water quality parameter under consideration, attention is turned to the
engineering aspects of the design analysis, if final design analysis is required.
The engineering characteristics of the individual system means (mean survival
times, mean failure times, mean repair times) are described. Using these data,
the survivability and availability of each system element may be computed from
information on the organization of the means in the element. Combining sur-
vivability and availability with the previously computed capability yields the
element effectiveness. System effectiveness is then computed from element
effectiveness and the expected number of violations. System cost is computed
next, from information on the component costs. Finally, cost and effectiveness
are combined to yield the cost-effectiveness index.
101
-------
The reader is referred to Appendix E for details of the program development.
In the following paragraphs, the overall function of the main program and each
subprogram is summarized.
MAIN - The main program provides overall sequencing of data input and
computation. With one exception, no computations are performed by MAIN
directly. The single exception is the computation of the total system cost-
effectiveness (equation (7)).
RPC - Subroutine RFC reads data on the water quality parameters to be
included, planned system duration, range of river flows, and the relation-
ship of the river reaches to the USGS gaging stations.
RSDD - Subroutine RSDD consists of the coding from the RIBAM main pro-
gram that reads the RIBAM Standard Data Deck. The echo-printing of the
input data has been deleted, as have alt other functions of the RIBAM main
program. RSDD calls the RIBAM Subroutines RCOND, RDATA, RDRATE [3] .
RCOND - Subroutine RCOND reads the headwater concentration data from
the Standard Data Deck for all parameters being simulated. It is identical
to the RIBAM version, except for deletion of echo-printing [3].
RDATA - Subroutine RDATA reads the point-source concentration data from
the Standard Data Deck. It is identical to the RIBAM version, except for
deletion of echo-printing
RDRATE - Subroutine RDRATE reads the reaction rate data for non-conser-
vative parameters being simulated from the Standard Data Deck. It is
identical to the RIBAM version, except for deletion of echo-printing [3] .
102
-------
RCHAR - Each time Subroutine RCHAR is called it reads in a set of data
describing the characteristics of the system related to system capability
for the parameter under consideration (see Appendix F).
QTCAL - Subroutine QTCAL uses the R1BAM subroutines REINI, TRIED,
COUPLES, DECAY, K2CAL, RMATC and BLEND, and the IMSL subroutine
ICSSMU to compute the threshold flows in each reach for the parameter
under consideration (see Appendix E).
REINI - Subroutine REINI initializes the concentration for the parameter
being computed in all headwater stretches and initializes flows in all head-
water stretches. It calls TRIED for each headwater stretch and repeats
until all headwater stretches have been considered. It stores the concen-
trations at the end of the headwater stretch for the parameter being com-
puted. It then calls RMATC for each junction and repeats until all junctions
have been considered. All printed output and calls to output subroutines
have been deleted from the RIBAM version [3].
TRIED - Subroutine TRIED computes physical parameters for each reach.
It computes the concentration at the head of each reach for the parameter
being computed. After all effluent source inputs have been added at the
head of each reach, TRIED computes the concentration at that point for the
parameter in concern. It calls DECAY, if the parameter is non-conserva-
tive, non-coupled. If the parameter is non-conservative, coupled, it calls
COUPLES. It is identical to the RIBAM version, except for deletion of
printed output [3].
DECAY - Subroutine DECAY computes the decay of non-conservative, non-
coupled parameters from the head of each reach to the end of the reach. It
is identical to the RIBAM version [3],
103
-------
COUPLES - Subroutine COUPLES divides each reach into ten subreaches
of equal length and computes the concentration of the non-conservative,
coupled parameters at the end of each subreach. It then finds the maximum
and minimum subreach concentrations and the river mile of the end of the
subreach where they occur. It is identical to the RIBAM version [ 3],
RMATC - Subroutine RMATC determines which headwater stretches enter
a junction and which stretch is formed as a result of a junction. It then
calls BLEND and TRIED sequentially. It is identical to the RIBAM version [3].
BLEND - Subroutine BLEND computes the flow at the beginning of a down-
stream stretch formed by the junction of upstream stretches and computes
the concentration of parameters at the beginning of the downstream stretch.
It is identical to the RIBAM version [3].
K2CAL - Subroutine K2CAL obtains a value for average depth at each reach
from one of two options. It then computes the reaeration coefficient for
each reach from one of three options and adjusts values of reaeration coef-
ficient for temperature dependency. It is identical to the RIBAM version [3].
ICSSMU - Subroutine ICSSMU performs a cubic spline curve fit on the five
concentration versus flow curves computed using the RIBAM subroutines
for each reach. QTCAL then uses the output of ICSSMU to compute the
threshold flow for each reach. It is an IMSL library subroutine [20].
EXPDUR - Subroutine EXPDUR computes the expected durations: T *, T *,
T **, and T **, using the threshold flows computed in QTCAL and actual
historical stream flow data supplied by Subroutine GSTAPE. The subroutine
contains very detailed logic to identify the spatial range of violations and to
deal with stream junctions (see Appendix E).
104
-------
GSTAPE - Subroutine GST APE is intended to provide the USGS gaging station
data to EXPDUR in the proper form. In general, the USGS data are avail-
able from the federal government on magnetic tape. Because the interaction
of a mag tape written by the USGS computer with the user's computer
facility is determined by facility type, no general purpose subprogram can
be prepared. Information is provided in Appendix F to guide the user in the
preparation of a subroutine satisfying the functional requirements of
GSTAPE.
COMPT - Subroutine COMPT performs two functions. First, it computes
n ** from T ** and T ** (equation (21)). Then, it scans the T*'s for zero
values and sets a flag accordingly. The flag is used in Subroutine CAPBLE
to select the computational procedure used to evaluate n *.
PPDES - Subroutine PPDES performs the simple task of formating and
printing the information required for preliminary design.
CAPBLE - Subroutine CAPBLE computes n * from the values of T * and
d 0
T * supplied by EXPDUR and from the adjusted value for A (equation (40)).
-L c
The computation is performed according to the approximate formulation
presented in Section VI. Subroutine CAPBLE calls the function subprogram
ANORM to supply values for the cumulative normal distribution (equation
(37)).
ANORM - Function ANORM provides the calling program with the approxi-
mate value for the cummulative normal distribution with zero mean and
unity standard deviation. The value is obtained by linear interpolation
between tabular values for the cummulative distribution.
105
-------
RMTTF - Subroutine RMTTF reads the data describing the engineering
reliability, maintainability, and survivability characteristics of the indi-
vidual means that may be included in the monitoring system.
LMNTEFF - Subroutine LMNTEFF computes the element effectiveness as
the product of capability, availability and survivability (equation (20)).
Capability is provided by Subroutine CAPBLE. Availability and survivability
are computed by a call to Subroutine LDEFF.
LDEFF - For each system element, Subroutine LDEFF reads data describ-
ing the organization of the means used to perform the sampling of the ele-
ment. It then uses Subroutines SETUP, LPLACE and SOLVE to setup the
transition matrix and compute the survivability (LPLACE) or availability
(SOLVE). The process is iterated until all system elements have been
evaluated.
SETUP- Subroutine SETUP is used to generate the transition matrix using
the element configuration (from LDEFF) and the means engineering data
(from RMTTF). SETUP is used to generate either the survivability or the
availability transition matrices (equations (25) and (28); also see Appendix E).
LPLACE - Subroutine LPLACE performs the computations necessary to
effectively evaluate the Laplace transforms necessary in the survivability
calculation (see Appendix E, equations (101), (102) and (103)).
SOLVE - Subroutine SOLVE prepares the availability transition matrix for
solution using gaussian elimination. It calls the LEQTIFto perform the
gaussian elimination (see Appendix E).
LEQT1F - Subroutine LEQT1F is an IMSL library routine that solves a set
of linear equations using gaussian elimination with equilibration and partial
pivoting. [20] The subroutine calls LUDATF, LUELMF and UERTST.
106
-------
LUDATF - Subroutine LUDATF is an IMSL library routine that performs
matrix decomposition. The NXN matrix is decomposed into a lower trian-
gular and an upper triangular matrix. LUDATF calls UERTST. [20]
LUELMF- Subroutine LUELMF performs the elimination portion of the
solution procedure. It is an IMSL library subroutine. [20]
UERTST - Subroutine UERTST is an IMSL library subroutine that is used to
generate error messages. [20]
SYSEFF- The subroutine SYSEFF is used to sum all the individual element
effectivenesses and the expected number of violations, and to compute the
total system effectiveness, E (equation (15)).
sys
CALCST - Using cost data supplied to it, Subroutine CALCST calculates the
total system cost (equation (9)) by matching the costs of the individual means
with the list of means included in the system.
PROGRAM OUTPUT
The printed output resulting from use of the surveillance system design program
is dependent on the choice of option, either preliminary design or final design.
Selection of the preliminary design option will produce output of the form shown
in Figure 30. For each parameter under design consideration, the computer
will produce a reach-by-reach listing of the expected number of violations
originating in the reach (n **) during the system duration, the expected duration
of the violations (T **), the expected duration of non-violation states (T **),
and the preferred monitoring location (x ). In the example shown in Figure 30,
m
the preliminary design output is for parameter 11. It can be seen that, in reach
number 29, 114 violations can be expected over the system duration, with an
107
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PARAMETER
REACH NO.
11
EXP. NO. OF
VIOLATIONS
EXP. DLWATrON OF
A VIOLATION
EXP. DURATION OF
A NON-VIOLA I ION
PREF. SAMPLING
LOCATION.R.M.
j
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3
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12
13
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16
17
18
19
20
21
22
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24
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26
27
28
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30
31
32
33
34
35
36
37
38
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Figure 30. Typical Preliminary Design Output
average duration of 1 day and an average interval between violations of 15 days.
The preferred sampling location in reach 29 is at river mile 15.5.
Choice of the final design option produces output typified by Figures 31 and 32.
For each parameter under consideration, a reach-by-reach listing of capability,
survivability, availability and element effectiveness is produced (Figure 31).
For each parameter (parameter 17 in the example shown), the results of the
effectiveness analysis are listed for each reach selected for monitoring in the
candidate under consideration. Capability is computed according to equation
(40), while survivability and availability are computed according to equations
(27) and (30), respectively. The element effectiveness is the product of those
three factors, as in equation (20). A final summary page follows (Figure 32),
108
-------
PARAMETER NUMBER = 17
REACH NO. = 2 CAP = 2.57711E-0
REACH NO. * 18 CAP * 1.71128E-02 SURV = 9.35785E-01 AVAIL * 9.99801E.-01 ELEMENT EFF. r 1.60107E-02
REACH NO. = 21 CAP * 2.663S4E-02 SURV * 9.35785E-01 AVAIL * 9.99801E-01 ELEMENT EFF. « 2.49200E-02
REACH NO. * 36 CAP * 1.7
-------
DESIGN TYPE = F SYSTEM DUR. * 1.00 NO. OF MONTHS > 60 FLOW SCALING FACTORS • 1.0 5.0
STA. NO. STA. 1.0. SEG. NO. SEG. ASSOCIATION
1
2
3
4
5
6
7
8
3091500
3094000
3098000
3099500
3103SOO
310B500
3107500
3095500
5
7
25
29
13
33
36
11
678 910-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0*0-0-0-0-0
2728293031-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
32333*-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
Figure 33. Typical Echo-Print of USGS Data Input
Figure 34 shows the result of echo-printing data from the CHAR cards described
later in this section. The example shown in Figure 34 is for parameter 17. The
candidate system under consideration will sample parameter 17 at four locations,
reaches 2, 18, 21 and 36, as indicated by "T" under the "IMPL. " heading. The
station at reach 21 will be maintained according to the policy described by equa-
tion (34) (heading "MN. PLCY. "= "T"), with no down time ("TUP" - 365. and
"TDOWN" = 0.0). The water quality standards threshold ("CT") is 5 mg/1 in
the reach. Sampling will be done every 3. 5 days ("DELTA") at river mile 30. 6
("IMPL. LOC. "). The means used to sample the river has an accuracy ("EPSI")
of 0. 02 and a precision ("SEPSI") of 0.1.
The data input on the MTTF cards are echo-printed in the form shown in Figure
35, with the following correspondences:
MTTFS = X. for survivability
MTTFA = X for availability
MTTRA = LL for availability.
Data on the detailed configurations of the system means input on the AVAIL and
SURV cards are echo-printed in the formats shown in Figures 36 and 37. These
110
-------
PARAMETER NUMBER = 17
REACH NO. IMPL. MM. PLCV. CT
DELTA IMPU. LOC, EPSI
SEPSI
TUP
TOOWN
1
2
3
4
5
6
7
8
<>
10
11
a
13
14
15
16
17
IB
19
30
21
22
23
2
-------
MEANS NO..
STATE 1 - OPERATING. STATE 2 « STAND-BY
MTTFS-1 MTTFS-2 MTTFA-1 MTTFA-2 MTTRA-1
MTTRA-2
1
a
3
4
5
6
7
a
9
10
11
12
13
It
IS
16
17
ia
.20
.01
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.01
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.20
.01
.20
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.02
.20
.01
.20
.20
.20
.01
.01
.01
.01
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.01
.01
.01
.01
.01
.01
.01
.01
.u^
.01
.01
.01
.01
.10
2.00
2.00
2.00
ft.00
4.00
2.00
2.00
2.00
ft.00
2.00
2.00
ft.00
ft.00
4.00
2.00
2.00
ft.00
ft.00
ft.00
1.00
.01
.01
7.00
.10
1.00
.01
.01
2.00
1.00
.01
2.00
2.00
.10
1.00
.01
2.00
2.00
1.00
365.00
365.00
365.00
365.00
52.00
365.00
365,00
365.00
365.00
165.00
365.00
365.00
365.00
52.00
365.00
365,00
365.00
365.00
122.00
365.00
365,00
365.00
365.00
52.00
36S.OO
365,00
365,00
365.00
365.00
365.00
365.00
365.00
S2.00
36S.OO
365,00
365.00
365.00
122.00
Figure 35. Typical Echo-Print of System Reliability Input
PARAMETER NUMBER - n ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
H
2
2
Ifl
1H
18
ei
v\
36
•36
36
S 25 3M19
M IM ftP 3
M 6M 9P 2
S 25 3 -0
M10M12P 3
M15M17P 2
M IM ftp 3
M 6M
-------
outputs essentially duplicate the card formats; the reader is referred to follow-
ing portions of this section for a detailed explanation of those formats.
USE OF PROGRAMS
As described earlier in this section, the design analysis programs constitute an
integral part of design Tasks 3 and 5. They provide the preliminary design data
necessary to design of system candidates in Task 4 and they perform the cost-
effectiveness analysis required for candidate selection in Task 6. In the follow-
ing paragraphs, use of the design analysis programs is described first for pre-
liminary design analysis and then for final design analysis.
Preliminary Design
Preliminary design analysis requires that the computer programs be supplied
with the data listed in Table 6. As indicated in the table, each data item is
associated with a data input card, with the entire set of cards constituting the
preliminary design data deck (Figure 38). These cards are identical with those
found in the "front-end" of the final design data deck described below.
As shown in Figure 38, the first card in the data deck is the CONTROL card.
The format of the CONTROL card is shown in Figure 39. For preliminary
design, a "T" (= .TRUE.) is placed in column 9. In columns 11-27, the water
quality parameters to be modeled and those to be included in the effectiveness
analysis are selected. Each column in the field corresponds to a parameter in
the RIBAM model, with column 11 corresponding to parameter 1 and column 27
corresponding to parameter 17. Since the correspondence between parameter
number and the actual water quality parameter may vary with RIBAM application,
the relationship can not be detailed further (see Appendix A). Because many of
the parameters modeled by RIBAM are non-conservative coupled parameters, it
113
-------
Table 6, REQUIRED PRELIMINARY DESIGN INPUT DATA
Data Type
Data Card(s)
Units
Parameters to be modeled
Parameters included in effectiveness
analysis
System duration
Length of USGS gaging station record
Flow scaling factors
USGS station ID numbers
Location of USGS stations
Stream segments associated with
USGS stations
Basin, description
Water quality standard threshold
concentration
CONTROL
CONTROL
CONTROL
CONTROL
CONTROL
USGS (1 ea. sta.)
USGS (1 ea. sta.)
USGS (1 ea. sta.)
RIBAM Standard
Data Deck
CHAR (1 ea. para-
meter and segment)
N/A
N/A
years
months
N/A
N/A
N/A
N/A
N/A
mg/1
(except
coliforms)
is frequently necessary to model more parameters than those to be included in
the analysis. When a parameter is to be included in the analysis, a "2" is
punched in the corresponding column. If a parameter must be modeled to satisfy
RIBAM coupling requirements, but is not to be included in the analysis, a "1" is
punched in the corresponding column. As shown in Figure 39, the system dura-
tion (years), the length of the USGS gaging station record (months) and the flow
scaling factors selected by the system designer are also entered onthe CONTROL
card. Finally, the user indicates his preference for echo-printing by entering
a "T" in column 70.
114
-------
CHAR(ACTERISTICS) CARDS
1st PARAM
ANALYZED
/ END
/ 2nd PARA ANALY
CHAR
END
oov r- A one
ZED
.
/RIBAM STANDARD DATA DECK
L
/ END CARD
USGS CARDS
PROL CARD
Figure 38. Preliminary Design Data Deck
The next set of cards in the data deck is the file of USGS cards. There is one
card for each USGS flow gaging station in the basin used in the analysis. The
format of the USGS card is shown in Figure 40. An arbitrary sequence or index
number is entered in columns 9-10. The last eight digits of the ID number
assigned by USGS to the station is entered in columns 13-20. Columns 22-23
contain the number of the stream reach in which the gaging station is located.
Following in columns 25-80 are the two-digit reach numbers of each stream seg-
ment associated with the gaging station for computation of stream flow. The seg-
ment listed in columns 22-23 must be repeated in columns 25-80. The file of
USGS cards is followed by a card with "END" punched in columns 1-3.
Following the USGS card file is the RIBAM Standard Data Deck. Details of the
RIBAM Standard Data Deck may be found in [7], along with instructions for pre-
paration.
The preliminary design data deck is terminated by one or more characteristics
(CHAR) card files. One file is prepared for each parameter to be analyzed
115
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(2's in columns 11-27 of the CONTROL card). Each file contains one card for
each reach in the basin. The CHAR card format is shown in Figure 41. The
parameter number (numbers 1-17) is entered in columns 5-6 and the segment
number in columns 7-8. Columns 11-20 contain the water quality standards
threshold for the parameter in the segment. For purposes of preliminary design,
the remainder of the CHAR card may be left blank, since those fields are
descriptive of the candidate monitoring system element. Each file of CHAR
cards for one parameter is terminated by an END card.
Final Design Analysis
In addition to the data required by preliminary design (Table 6), the final design
requires the data listed in Table 7. The final design data deck for each candi-
date is prepared by adding information to the CHAR card file(s) and by appending
additional card files. The composition of the final design data deck is illustrated
in Figure 42.
The information added to the CHAR cards is entered in columns 9-10 and 21-80
(see Figure 41). If the candidate system includes monitoring of the parameter
and segment indicated in columns 5-8 of the CHAR card, a"T" is punched in
column 9 and the remainder of the card filled-in. If no monitoring is to be done,
column 9 may be left blank or punched with an "F" and the remainder of the card
is left as it was in preliminary design.
The MTTF card file contains one card for each means incorporated in the sys-
tem. For convenience in analysis of a number of candidates sharing the same
means, cards for means not incorporated in a given candidate may also be left
in the file. Thus, only one MTTF file need be prepared for all the candidates.
The format of the MTTF card is shown in Figure 43. The means number's is
entered in columns 8-10. Following that, in 6 fields of 10 columns each, are:
118
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Table 7. REQUIRED FINAL DESIGN INPUT DATA
Data Type
Element sampling interval
Element sampling location
Element accuracy
Element precision
Element maintenance policy
Maintenance schedule
Survivability
Reliability
Maintainability
Element design (survivability)
Element design (availability)
Cost data-group
Cost data-means
Data Card(s)
CHAR
CHAR
CHAR
CHAR
CHAR
CHAR
MTTF
MTTF
MTTF
SURV
AVAIL
COSTG
COSTM
Units
days
RM
mg/1
nig/1
N/A
days
-1
years
-1
years
-1
years
N/A
N/A
$/sys. dur.
$/sys. dur.
V for survivability in operation
\for survivability in stand-by
^for availability in operation
Xfor availability in stand-by
Kfor availability in operation
H-for availability in stand-by
It should be noted that these are the rates, not the mean times. Thus, a means
that tends to fail in a repairable mode twice a year has a value of 2.0 entered in
columns 31-40 and a means that tends to survive for ten years has a value of
0.1 entered in columns 11-20.
120
-------
r
SURV CARDS (PARAM N)
•
(^ END CARD
COST CARDS
DCARO
1M Ml
PRELIMINARY DESIGN
DATA DECK
Figure 42. Final Design Data Deck
Following the MTTF file are paired files of AVAIL and SURV cards. There is
one pair of files for each parameter included in the effectiveness analysis ("2"
in columns 11-27 of the CONTROL card). Within each file are cards describing
the functional configuration of system element for the associated category, either
availability (AVAIL) or survivability (SURV). One card is prepared for each path
in each system element (see Section VI). The segment number is entered in
columns 8-9 (Figure 44) the parameter number is entered in columns 13-14, and
the path number in columns 18-19. The normal operating status of the path is
entered in columns 23-24. As described in Section VI, each element path or
sub-path may be composed of means and other sub-paths. In addition, each sub-
path may have one or more parallel sub-paths. This information is punched in
121
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122
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The next two columns of each field contain the two digit identifying number of the
means, sub-path or parallel path associated with the path specified in columns
18-19. The 3-column fields must be filled in from left to right, since the first
blank leading column terminates processing of the card. The cards are grouped
together by parameter, as shown in Figure 42, with all paths of the same system
element in sequence. Each file is terminated with an END card. See the dem-
onstration case in Section VIII for several examples of these cards.
The last card file in the final design data deck is the COST file. The format of
the COST card is shown in Figure 45. The type of cost analysis component is
specified by entry of either G = group or M = means in column 5. The means or
group number is entered in columns 6-10, as appropriate. Following, in fields
of 10, from column 11 to column 50 are:
Cost to acquire - cols. 11-20
Cost to operate - cols. 21-30
Cost to maintain - cols. 31-40
Residual value - cols. 41-50
The number of the next higher level group is entered in columns 56-60. For
group 1, the system level, columns 56-60 are left blank. If they are blank on
any other card of the file, an error is sensed and processing terminated. As
with the MTTF file, extraneous means and groups may be included in the file
for convenience in analyzing a large number of candidates. Only those means
specified in the AVAIL and SURV files are included in the cost estimate by the
analysis programs. The file is terminated by an END card.
124
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-------
Adaptation to Computer Facility
The computer programs for design analysis have been prepared and tested on a
CDC 6700 computer. Some care has been taken to maintain generality in the
program, but that has not always been feasible. As discussed in Appendix E,
use is made of the 60-bit word length available on the CDC 6700. Minor pro-
gram modifications are necessary to adapt the programs to a smaller word-
length machine. Another adaptation required is in the handling of the USGS flow
data tape. A special purpose subroutine (Subroutine GSTAPE) must be prepared
to handle the gaging station data tape with the hardware available at the user
facility. Appendix F provides guidance in the preparation of the subroutine. As
usual in a new program application, attention must be paid to all the input/output
specifications when implementing on a new computer. Finally, for any given
application, some adjustments of the storage allocated to data arrays may be
necessary. The array sizes specified in the program listings (Appendix F) are
relatively arbitrary and based on the requirements of the demonstration case.
126
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SECTION VIII
DEMONSTRATION OF DESIGN METHODS
In order to illustrate the major features of the surveillance system design
methods, the methods are demonstrated for the Beaver River Basin of Ohio and
Pennsylvania. Various alternative systems are analyzed to highlight relation-
ships among the several factors incorporated in the analysis.
The section begins with introductory remarks concerning the significance the
demonstration results and the choice of the Beaver River Basin as the demon-
stration basin. A brief description of the Basin follows. Then, the primary
demonstration case is described on a task-by-task level. The results of the
primary demonstration are discussed and used as a point of departure for
various permutations of the primary case. The section is concluded with a
summary of the demonstration.
CAVEAT
The objective of the demonstration is to illustrate features of the design methoo.
The selection and use of the Beaver River Basin to achieve this objective is
based on the practical considerations discussed below and does not constitute a
statement of opinion concerning the water quality of the Basin. The results of
the demonstration are based on a careful application of the design method to the
data used. In many cases that data is intentionally artificial, in order to avoid
appearing to recommend a particular surveillance method or device. Specifi-
cally, the cost data and the reliability data are to be considered artificial,
although the range of values has been guided by [4, 10, and 28]. Therefore,
the results of the demonstration do not constitute a fully realistic recommenda-
tion for water quality surveillance in the Beaver River Basin and must be viewed
in the light of these limitations.
127
-------
SELECTION OF BEAVER RIVER BASIN
Choice of the Beaver River Basin for use as the demonstration case was based
almost entirely on a pragmatic consideration: three calibrated Standard Data
Decks already existed for the basin [7]. Thus, in a project directed primarily
at development of design methods, the effort expended in preparing for demon-
stration of those methods could be minimized.
In addition, the Beaver River Basin can be considered qualitatively typical of
many river basins in the country. It has a broad range of uses, including public
water supply, industrial water supply, municipal sanitation and runoff removal,
recreation and wildlife support. It includes both major dams for reservoirs
and minor, run-of-the-stream dams for industrial supply. Problems in the
basin include mine drainage, municipal waste treatment and industrial dis-
charges, primarily from the steel industry.
Another factor influencing the choice is the political division of the Basin
between two states, Ohio and Pennsylvania. This factor permits the demon-
stration of features of the method for dealing with changes in authority.
Description of Beaver River Basin
The geographical location and extent of the Beaver River Basin is mapped in
Figure 46. The basin is drained primarily by the Mahoning and Shenango
Rivers, which join in western Pennsylvania to form the Beaver River. The
Beaver is ultimately tributary to the Ohio River. The northern half of the basin
is relatively flat, while the southern half includes western parts of the Allegheny
Mountains. Particularly in its lower reaches, the Beaver River lies in a
narrow, rugged valley cut through a plateau [29]. Included in the basin is the
highly industrialized area in the vicinity of Youngstown, Ohio.
128
-------
0 R D
S T
Figure 46. Beaver River Basin
129
-------
The Mahoning River drains an area of approximately 1,130 square miles, most
of which is in eastern Ohio, and its length is approximately 110 miles. Its
principal tributaries are the West Branch of the Mahoning, Eagle Creek,
Mosquito Creek and Meander Creek. Five multipurpose reservoirs are located
in the Mahoning sub-basin, for flood control, low-flow augmentation, public
water supply and recreation. In addition, between Levittsburg and Lowellville
on the Mahoning, there is a series of low dams that pond water for industrial
intakes. Earthfills for railroads and mills also constrict the flow along the
natural stream channel in this area.
The Shenango River drains a total area of approximately 1,080 square miles,
with about 285 square miles in Ohio and the remaining 795 square miles in
Pennsylvania. Its length to the confluence with the Mahoning is approximately
52 miles. Two multipurpose reservoirs are located on the upper Shenango.
The Beaver River, from its head near New Castle, Pennsylvania, to its mouth
at Rochester, Pennsylvania, is about 21.4 miles in length. Its total drainage
area, including the areas drained by the Maliening and the Shenango, is about
3,145 square miles [30].
Water Quality Problems
The major water quality problems in the Beaver River Basin are due to dis-
charge of domestic and industrial waste. Agriculture, dairying and food pro-
cessing are also of some importance.
Several large industrial centers are located within the basin, contributing
massive manufacturing waste discharges to the rivers. The greatest industrial
concentration is in and around Youngstown, Ohio, the largest city in the Basin.
Other areas of intense industrial activity, principally iron and steel industry,
130
-------
are found at Warren, Niles, Girard and McDonald on the Mahoning River, and at
Sharpsvillc, Sharon, Parrel and New Castle on the Shenango. Industrial activity
along the Beaver River is present at Koppel, West Mayfield, Beaver Falls and
Fallston.
In addition to the dominant iron and steel industry, basin industrial activity
includes chemicals, lumber, glass, textiles, quarrying of high quality lime-
stone, and the manufacturing of cement.
Population concentrations in the basin correspond to industrial centers. The
total population of the Beaver River Basin today is in excess of 800,000 people
[29], but domestic waste from more than half of this population is discharged
along the 25 mile stretch of the Mahoning from Warren to Lowellville. Prior to
I960 nearly 50% of that effluent was left untreated, particularly in the Youngs-
town area [29]. Since then, measures have been taken to bring at least primary
treatment to all sewered populations in the portion of the basin considered. As
of 1960, as many as 59 communities discharged significant amounts of treated
and untreated municipal wastes to the streams of the basin [29].
Effects of Pollution
The effects of poor water quality in the Beaver River Basin can be seen in both
the natural biological sphere and the human economic sphere.
Aquatic life in the rivers of the basin has been drastically influenced by poor
water quality. The Mahoning River in the vicinity of Younstown, Ohio, may
serve as an example. Downstream of Youngstown to the state boundary, the
river is completely devoid of bottom fauna, in contrast to the diverse and
abundant benthic life found in its headwaters [31].
131
-------
The economic effect can be illustrated by the impact of water quality on the
public water supply at Beaver Falls, Pennsylvania. The Mahoning River,
degraded by the considerable impact of Youngstown, Ohio, is an important
contributor of pollution to the Beaver River. Consequently, the use of the
Beaver River for public water supply is affected by excessively high bacterio-
logical counts, by high variability in hardness, iron and other physical/chemical
properties, and by tastes and odors resulting from domestic and industrial
wastes. Thus, Beaver Falls must absorb the expense of the very difficult and
extensive water supply treatment required [29],
The Basin Subset
The portion of the Beaver River Basin included in the surveillance system design/
model, the so-called "basin subset", is of limited geographical extent. The
stretches of river to be included are (Figure 47):
1. The Mahoning River from Alliance, Ohio, to the confluence with the
Shenango River
2. The Mosquito Creek from the Mosquito Creek Dam to the confluence
with the Mahoning River.
3. The Shenango River from Sharpsville, Pennsylvania, to the confluence
with the Mahoning River
4. The Beaver River from the confluence of the Mahoning and Shenango
Rivers to its mouth at the Ohio River.
This "basin subset" includes two of the multipurpose reservoirs discussed
above, the Berlin and the Milton reservoirs. A list of the major tributaries to
he basin subset, with their respective drainage areas, is found in Table 8.
132
-------
, , -. 10 2S SO STATUTE hMi-E.fi
Figure 47. Stretches of River Included in Basin Street
133
-------
Table 8. MAJOR TRIBUTARIES TO BASIN SUBSET
Tributary
Draining Area (sq. mi.)
Beech Creek
Deer Creek
Willow Creek
Mill Creek (to Berlin Reservoir)
Kale Creek
West Branch Mahoning,1 River
Eagle Creek
Chocolate Run
Duck Creek
Infirmary Run
Red Run
Mud Creek
Mosquito Creek
Meander Creek
Squaw Creek
Fourmile Run
Mill Creek (near Youngstown)
Crab Creek
Dry Run
Yellow Creek
Coffee Run
Hickory Run
Neshannock Creek
Big Run
Connoquenessing Creek
33.42
35.71
19.90
31.76
24.24
109.36
109.53
4.50
36.71
10.51
7.20
11.23
139.33
83.56
17.32
4.69
79.10
20.28
10.11
32.43
10.26
24.24
244.00
33.90
829.00
134
-------
PRIMARY DEMONSTRATION CASE
Application of the design method to the Beaver River Basin calls for the perfor-
mance of the six tasks detailed in Section VII. The actions and results of each
task are described in the following paragraphs for a case in which a totally
manual system of surveillance is compared with a totally automatic system.
When constraints have been applied solely for purposes of the demonstration,
they are clearly labeled.
Task 1 - Data Assembly
Because the demonstration draws on the results of the Beaver River Basin
Modeling Project, most of the data acquisition process may be considered to
have been completed. The reader is referred to [7] and [18] for a complete
discussion of the data on the Beaver River Basin. The major action of Task 1
is, thus, the very important choice of the water quality parameters to be
included in the design analysis.
Four water quality parameters are considered for incorporation in the monitor-
ing system:
1. Dissolved Oxygen
2. Cyanides (Ohio portion of Basin)
3. Phenols (Pennsylvania portion of Basin)
4. Dissolved Solids.
The criteria for selection are a combination of the general requirements for
inclusion in design analysis and of the specific requirements of the demonstra-
tion.
135
-------
The general requirements reflect the water quality standards in force in the
Basin. The Ohio standards for the Mahoning River include absolute limits on
dissolved oxygen, cyanides and dissolved solids, along with a number of other
parameters. Ohio standards for phenols in the Mahoning River are referenced
to ambient. Similarly, the Pennsylvania standards for the Mahoning, Shenango
and Beaver Rivers include absolute limits for dissolved oxygen, phenols and
dissolved solids. In Pennsylvania, cyanides fall under the more general pro-
vision calling for freedom from toxic substances in the Beaver Basin. Thus,
these four water quality parameters would ordinarily be among those selected
for inclusion in a monitoring network.
The specific requirements for demonstration call for one parameter from each
of the three classes of water quality parameters:
1. Conservative
2. Non-conservative, non-coupled
3. Non-conservative, coupled.
For reasons of economy, use of only one parameter from each class is preferred
for the demonstration. The requirements of the demonstration also call for
selection of parameters for which both manual and automatic surveillance meth-
ods are available, so comparisons can be made between the two types of
approaches.
Thus, the four parameters have been selected for demonstration, because they
satisfy the requirements of the demonstration. Dissolved oxygen is modeled
as a non-conservative, coupled parameter, with established thresholds through-
out the Basin. Cyanides is modeled as a non-conservative, non-coupled para-
meter, with established thresholds in the Ohio portion of the Basin and an
136
-------
implied zero threshold in the Pennsylvania portion. Phenols is modeled as a
non-conservative, non-coupled parameter, with established, absolute thresholds
in the Pennsylvania portion of the Basin. For the Ohio portion of the Basin, an
artificial, high threshold for phenols is arbitrarily used in lieu of an established
state standard. Dissolved solids is modeled as a conservative parameter, with
established thresholds throughout the Basin.
The threshold concentrations used in the demonstration are listed in Table 9 by
region of application.
Task 2 - Basin Modeling
Once again, the activities associated with Task 2 can be considered to have been
completed within the Beaver River Basin Modeling Project. During that project,
three calibrated Standard Data Decks were prepared:
1. September 1970
2. March 1971
3. August 1971.
For purposes of the present demonstration, the September 1970 baseline period
is used as the design condition. It is selected for two reasons: 1) it corresponds
Table 9. THRESHOLD CONCENTRATIONS ASSUMED FOR PURPOSES OF
DEMONSTRATION (mg/1)
Parameter
Dissolved Solids
Cyanides
Phenols
Dissolved Oxygen
Parameter
Number
5
10
11
17
Ohio
1500.0
0.005
0.100
5.000
Pennsylvania
500.0
0.000
0.005
5.000
137
-------
to low-flow conditions near the end of the water year and 2) the other low-flow
period (August 1971) includes data taken during a major shutdown of the steel
mills in the Basin.
A complete description of the calibration of RIBAM for the Beaver River Basin
can be found in [7].
In summary, the Basin is segmented into 38 reaches, as shown in Figures 48,
49 and 50. The head of each reach corresponds to a major point-source, impact
2.1
13
Figure 48. Basin Segmentation
30
19
**
138
-------
«AO«9UITO CH JUNCTION |Zl| BM3I.O
SYMBOL.
D
DEFINITION
MBAO Of K.CJkCH
NUV.BSR
T TRIBUTARY
• W MUNICIPAL &OURCE
I INPUSTKIAV. »OU«CC
CORKE&BONDJNOt TO
HUMftCII (OKC. T*.»Lt_)
X USO,* <«AU4m4 STATION
I.J.i
1*1 KM MO
^TO >l <. .«A T
Figure 49* Basin Stick Diagram (Mahonlng River Section)
139
-------
•YMftOL. DEFINITION
,__, HEAD OF KBACH
D
IU*CH NUMBER
M MUNICIPAL SOURCE
I INDUSTRIAL, •OURCC
X
A
DfcVt
Izil *MO.O nU
KM 21 ft
KMlC.B
|3M RM 7 a
r RM IB
RM 0.0
* RMSI.2
i« CM a* .a
-il
RM z* a i
->4,»«,li,\7,l»
.•$9
-4 I
-10.11
. IZ
O I Z S 4 s 4
I 1 1 1 1 I !
Figure 50. Basin Stick Diagram (Shenango-Beaver Section)
140
-------
nucleus (group of sources), tributary junction or change of physical character-
istics, as diagrammed. The USGS gaging stations used to develop stream flow
data are shown in Figure 51. Of the 16 stations shown, only the eight indicated
have data records sufficient to the design method. Thus, only those eight
stations are used in the preliminary and final design runs.
Task 3 - Preliminary Design
The major results of Task 3 are contained in the computer print-outs shown in
Figures 52, 53, 54, and55. They are the product of the design analysis pro-
grams described in Section VII, used in the preliminary design mode. The
September 1970 Standard Data Deck and 60 months of USGS flow data beginning
with January 1957 constitute the major input data, along with the threshold
concentrations from Table 9. A complete listing of the input data deck may be
found in Appendix G.
As indicated in Figure 52, violations of the dissolved solids standards begin in
only one segment, reach 30. The value in the column labelled "EXP. NO. OF
VIOLATIONS" indicates that slightly less than 3 violations of dissolved solids
may be expected each year in reach 30. The values for the other reaches are a
nominally low value, indicating that no violations were found over the 5 year
(1826 day) flow record searched. The violations in reach 30 are associated
directly with the change in dissolved solids threshold from 1500 mg/1 on the
Ohio side of the line (reach 29) to 500 mg/1 on the Pennsylvania side (reach 30).
As indicated, these violations may be expected to last about 6 days, with about
124 days between violations. The preferred sampling location is, of course,
irrelevant for a conservative parameter such as dissolved solids.
Turning to cyanides (Figure 53), it can be seen that a number of reaches may be
expected to be continuously in violation, while only one reach (reach 21) has any
141
-------
SHENANGO AT
SHARPSVILLE
BEAVER AT
BE-fiveR. FALLS
Figure 51. USGS Gaging Stations in the Beaver River Basin
142
-------
PARAMETER
REACH NO. EXP. NO. OF
VIOLATIONS
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
.99890E-01
.99890E-01
.99890E-01
.99890E-01
.99B90E-OI
.99890E-01
.99890E-01
.99890E-01
.99890E-01
.99B90E-01
.99890E-01
.99890E-01
.99890E-01
.99B90E-01
.99B90E-01
.99890E-01
.99890E-01
.99890E-01
.99890E-01
.99890E-01
.99890E-01
.99890E-01
.99890E-01
.99B90E-01
.99890E-01
.99B90E-01
.99890E-01
.99890E-01
.99890E-01
.7
-------
PARAMETER « 11
REACH NO.
EXP. NO. OF
VIOLATIONS
EXP. DURATION OF
A VIOLATION
EXP. DURATION OF
A NON-VIOLATION
PREF. SAMPLING
LOCATION.R.M.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
IB
19
20
21
22
23
24
as
26
27
28
29
30
31
32
33
34
35
36
37
38
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.32896E«01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
3.79376E«00
1.99890E-01
1.99890E-01
1.55915E*01
1.99B90E-01
1.99890E-01
1.59787E»00
1.67908E-01
2.05675E»01
1.27404E*01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99S90E-01
1.99890E-01
1.99890E-01
1.99890E-01
0.
0.
0.
0.
0.
0.
0.
0.
1.32985E«01
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
2.00000E*00
0.
0.
4.35897E»00
0.
0.
1.428S7E»00
1.29643E»dl
1.88235E»00
7.53968E»00
0.
0.
0.
0.
0.
0.
0.
0.
l.B2600E»03
1.82600E»03
1.82600E»03
1.82600E*03
1.82600E.03
1.82600E*03
l.S2600E*03
1.82600E*03
1.41667E»01
1.82600E-03
82600E«03
82600E»03
82600E*03
82600E.03
82600E«03
82600E*03
82600E»03
82600E»03
82600£»03
82600E»03
9.42105E.01
1.82600E.03
1.82600E»03
1.90S13E.01
1.82600E-03
1.82600E.03
2.27000E«02
8.7738lE«00
1.58641E*01
2.11094E*01
1.82600E-03
1.82600E*03
1.82600E*03
1.62600E-03
1.82600E«03
1.82600E-03
1.82600E*03
1.82600E»03
88.0
87.0
72.0
70.0
62.0
55.0
47.0
42.0
37.0
35.0
12.0
6.5
54.4
51.2
48.8
47.4
44.8
42.4
36.8
24.8
31.0
28.0
25.0
23.5
21.5
19.5
18.5
16.5
15.5
12.5
4.5
21.6
19.8
12.6
10.8
7.8
3.8
1.8
Figure 54. Preliminary Design Data for Phenols
PARAMETER
REACH NO.
17
EXP. NO. OF
VIOLATIONS
EXP. DURATION OF
A VIOLATION
EXP. DURATION OF
A NON-VIOLATION
PREF. SAMPLING
LOCATION.R.M.
1
2
3
4
5
6
7
a
9
10
11
12
13
14
15
16
17
16
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
3*
35
36
37
38
1.99890E-01
3.38044E«00
1.Q9890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
7.91614E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
7.94198E-01
7.55992E*00
1.70620E»Ol
9.98905E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.99890E-01
1.91895E»01
1.29839E»01
1.99890E-01
1.99890E-01
0.
9.84118E«01
0.
a.
0.
0.
0.
0.
0.
1.83333E»Ol
0.
0.
0.
0.
0.
1.23333E»01
8.6756BE*00
7.62791E«00
1.00000E«00
0.
1.8?600E*03
0.
0.
0,
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
5.15625E*00
1.26563E-00
0.
0.
1.82600E-03
9.56250E«00
l.B2600E»03
1.82600E-03
1.82600E»03
1.82600E'C3
1.82600E*03
1.82600E»03
l.B2600E*03
4.42750E»02
1.82600E»03
1.82600E«03
1.82600E»03
l.B2600E«03
1.82600E«03
4.47250E»02
3.96053E»01
3.64400E»02
1.82600E«03
0.
l.S2600E*03
1.82600E.03
1.82600E«03
1.82600E«03
1.82600E«03
1.82600E«03
1.82600Et03
1.82600E«03
1.82600E«03
1.82600E«03
1.82600E»03
1.82600E-03
1.82600E»03
1.38646E«01
2.68462E«01
1.82600E.03
1.82600E»03
87.0
82.5
70.0
65.2
57. 1
53.4
43.0
39.5
35.0
31.0
11.4
3.3
51.2
48.8
47.4
44.8
42.4
36.8
35.6
24.5
28.0
25.0
23.5
21.5
19.5
18.5
16.S
15.5
12.5
4.5
4.0
21.4
19.1
12.4
7.8
4.6
3.6
1.6
Figure 55.
Preliminary Design Data for Dissolved Oxygen
144
-------
variability. The reaches continuously in violation have the same low likelihood
of a new violation as those continuously free of violation. In reach 21, we
expect about 24 new violations per year, each of about 4 days duration, with
about 11 days between. The preferred sampling location, 31. 0 river miles
above the confluence with the Shenango, corresponds to the head of reach 21,
since cyanides are modeled as a non-conservative, non-coupled parameter.
The preliminary design data for phenols (Figure 54) indicate a greater variabil-
ity than for the previous two parameters. A number of new violations can be
expected to begin in reaches 9, 21, 24, 27, 28, 29, and 30. Of these, only
reach 30 is in Pennsylvania, where a threshold for phenols is established. The
violations in reaches 9, 21, 24, 27, 28, and 29 are violations of a concentration
threshold set 20 times higher than the Pennsylvania standard, to simulate the
assumed lack of a phenols standard in Ohio.
Finally, the dissolved oxygen standard may be expected to be violated in reaches
2, 10, 16, 17, 18, 19, 21, 35, and 36 (Figure 55). Of those, reach 21 is
continuously in violation. The preferred sampling locations correspond to the
oxygen sag point or the lower end of the reach, whichever is further upstream.
For example, the preferred sampling location in reach 35 is 7. 8 river miles,
corresponding to the head of reach 36. This indicates that the sag point for the
source at the head of reach 35 lies somewhere in or downstream of reach 36.
Task 4 - Candidate Design
Using the data in Figures 52, 53, 54 and 55, two candidate systems are designed
for comparison using the final design mode of the analysis programs. The two
candidates are intended to monitor the same reaches of the Basin. Beyond that,
they have been designed to make normal use of the means to be incorporated.
145
-------
Candidate 1.0 is a totally manual monitoring system, while Candidate 2.0 is a
fully automatic system.
Candidate 1.0 —
The initial decision in the design of the totally manual system concerns the
selection of the nominal system characteristics: parameters monitored, seg-
ments monitored, and system duration (Table 4). For purposes of the demon-
stration, the system duration is initially chosen to be 1 year. Since the pre-
liminary design data indicate violations of each of the parameters, the system
will monitor dissolved solids, cyanides, phenols and dissolved oxygen.
The choice of segments, locations and sampling frequencies is based on an
analysis of the preliminary design data in Figures 52, 53, 54 and 55. The
results are summarized in Table 10. Choice of reach 30 for monitoring of
dissolved solids is a foregone conclusion. The location is keyed to coincide
with the location used to monitor phenols in reach 30, the Churchill Road Bridge
at river mile 11.0. A weekly rate is selected (using Figure 5), since both
phenols and dissolved solids have expected durations on the order of 7 days, and
since weekly sampling is a very common sampling frequency [3]. Similarly,
cyanides are monitored only in reach 21 at the Erie Railroad Bridge (river mile
30. 6) just downstream of the preferred location. Once again the location coin-
cides with monitoring of other parameters in reach 21 and the frequency is the
commonly used weekly rate. The locations selected for monitoring of phenols
are relatively arbitrary, given the number of segments indicating violations.
Reach 30 is selected as the only reach in Pennsylvania with an expectation of phenols
violations. Although Ohio's standard for phenols is assumed high for demon-
stration purposes, a number of segments appear to have problems with phenols
so monitoring is instituted in reaches 9 and 21, as a minimum system. The
146
-------
Table 10. CANDIDATE 1.0 SAMPLING PROGRAM
(sampling interval in days, locations in river miles)
Reach
2
9
18
21
30
36
Dissolved
Solids
7
Cyanides
7
Phenols
14
7
7
DO
45
7
7
7
Location
82.5
37.0
36.8
1
30.6
2
11.0
3
4.0
Notes:
1. Erie Railroad Bridge
2. Churchill Road Bridge
3. 10 Street Bridge
frequency at reach 9 is set at 14 days, due to the expected violation duration and
interval in that reach. Finally, monitoring for dissolved oxygen is to take place
in reaches 2, 18, 21 and 36. Reach 2 is a reservoir, so it is assumed that
monitoring of DO in reach 2 will take place from a boat at the preferred sampl-
ing location, RM 82. 5. A low sampling rate is assumed, due to the long expect-
ed violation duration. Reach 21 is monitored in preference to reach 10, since
other parameters are to be monitored there and since the preferred location in
reach 10 is RM 31. 0, the head of reach 21. The availability of the 10th Street
Bridge in Reach 36 makes monitoring for DO there preferrable to monitoring in
Reach 35.
For purposes of the demonstration, it is assumed that each state will monitor
those segments of the Basin within its borders. Thus, the basic organizational
framework shown in Figures 56, 57 and 58 is envisioned for the system means
147
-------
TOTAL SYSTEM
GROUP 1
OHIO
SYSTEM
GROUP 2
PENNSYLVANIA
SYSTEM
GROUP 5
(Candidate 1)
OR
GROUP 8
(Candidate 2)
Figure 56. Overall System Organizational Framework Assumed for All Candi-
dates
GROUP 4
SAMPLE ACQ. TEAM "A"
SAMPLE ACQ. TEAM "B"
CYANIDES FIELD KIT "A"
CYANIDES FIELD KIT "B"
PHENOLS FIELD KIT "A"
PHENOLS FIELD KIT "B"
DO PROBE "A"
DO PROBE"B"
BOAT
GROUP 2
GROUP 3
ure 57. Ohio System Organizational Framework Assumed for Candidate 1.0
148
-------
listed in Table 11. Nineteen means are identified, including back-up equip-
ment. Sample acquisition is to be performed by field teams traveling from
site to site. Dissolved oxygen is to be monitored with a portable electrochem-
ical monitor and dissolved solids estimated from conductivity measured with a
portable monitoring instrument. Cyanides and phenols are to be determined
using laboratory photometric techniques on samples prepared in the field for
transportation. The functional framework of the system is shown in Figure 59
and summarized in the Utilization Table (Table 12).
The remainder of the required design data is summarized in Tables 13, 14 and
15. They are based on estimates by Raytheon personnel from their experience
and are to be considered arbitrary. They are made solely for the purposes of
the demonstration.
GROUPS
GROUP 6
Figure 58. Pennsylvania System Organizational Framework Assumed for
Candidate 1.0
149
-------
SEGMENT PARAMETER
Z 17 119|
17
21 10
21
11
21
17
30
30
OB
36
17
- OPERATING MEANS
- STANDBY MEANS
Figure 59. Functional Framework for Candidate 1.0
150
-------
Table 11. SYSTEM MEANS FOR CANDIDATE 1.0
Means
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
State
OH
OH
OH
OH
OH
OH
OH
OH
OH
PA
PA
PA
PA
PA
PA
PA
PA
PA
OH
Description
Sample acquisition team "A" (incl. transp. )
Cyanides Field Kit "A"
Phenols Field Kit "A"
DO Probe
Spectrophoto meter
Sample acquisition team "B" (incl. transp. )
Cyanides Field Kit "B"
Phenols Field Kit "B"
DO Probe "B"
Sample acquisition team "A" (incl. transp. )
Phenols Field Kit "A"
DO Probe "A"
Conductivity Probe "A"
Spectrophotometer
Sample acquisition team "B" (incl. transp.)
Phenols Field Kit "B"
DO Probe "B"
Conductivity Probe "B"
Small Boat and Dockage
151
-------
Table 12. UTILIZATION TABLE FOR CANDIDATE 1.0
Segment
Number
2
9
18
21
21
21
30
30
36
Parameter
Number
17
11
17
10
11
17
5
11
17
Path
Number
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
Normal
Path
States
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
Parallel
Sub- Paths
—
3
2
—
3
2
_
3
2
—
3
2
—
3
2
—
3
2
—
3
2
—
3
2
—
3
2
Series
Means
in Path
19
1, 4
6, 9
5
1, 3
6, 8
—
10, 12
15, 17
—
1, 2
6, 7
5
1, 3
6, 8
—
1, 4
6, 9
—
10, 13
15, 18
14
10, 11
15, 16
—
10, 12
15, 7
Sub- Paths
in Path
2, 3
—
2, 3
—
2, 3
_
—
2, 3
—
2, 3
—
2, 3
—
2, 3
—
—
2, 3
—
—
2, 3
—
—
152
-------
Table 13. ASSUMED SAMPLING ERRORS FOR CANDIDATE 1. 0
Parameter
Dissolved Solids
Cyanides
Phenols
Dissolved Oxygen
Parameter
Number
5
10
11
17
Accuracy
(«)
15.
0.05
0.001
0.02
Precision
K)
15.
0.10
0.002
0.10
153
-------
Table 14. ASSUMED FAILURE AND REPAIR RATES FOR CANDIDATE l.Q
(years~l)
Means
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Survival
Rate
(Operating)
0.2
0.01
0.01
0.2
0.02
0.2
0.01
0.01
0.2
0.2
0.01
0.2
0.2
0.02
0.2
0.01
0.2
0.2
0.2
Survival
Rate
(Standby)
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.1
Failure
Rate
(Operating)
2.0
2.0
2.0
4.0
4.0
2.0
2.0
2.0
4.0
2.0
2.0
4.0
4.0
4.0
2.0
2.0
4.0
4.0
4.0
Failure
Rate
(Standby)
1.0
0.01
0.01
2.0
0.1
1.0
0.01
0.01
2.0
1.0
0.01
2.0
2.0
0.1
1.0
0.01
2.0
2.0
1.0
Repair
Rate
(Operating)
365.
365.
365.
365.
52.
365.
365.
365.
365.
365.
365.
365.
365.
52.
365.
365.
365.
365.
122.
Repair
Rate
(Standby)
365.
365.
365.
365.
52.
365.
365.
365.
365.
365.
365.
365.
365.
52.
365.
365.
365.
365.
122.
154
-------
Table 15. ASSUMED COMPONENT COSTS FOR CANDIDATE 1.0 ($)
Means
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Groups
1
2
3
4
5
6
7
8
Acquisition
3000.
400.
400.
600.
1500.
3000.
400.
400.
600.
3000.
400.
600.
300.
1500.
3000.
400.
600.
300.
1500.
40000.
10000.
20000.
5000.
10000.
20000.
5000.
5000.
Operation
5000.
500.
500.
10.
50.
1000.
50.
50.
10.
5000.
500.
10.
10.
50.
1000.
50.
10.
10.
100.
0.
5000.
4500.
2500.
5000.
4500.
1500.
1500.
Maintenance
400.
0.
0.
100.
0.
400.
0.
0.
100.
400.
0.
100.
50.
0.
400.
0.
100.
50.
100.
0.
0.
1000.
500.
0.
1000.
250.
250.
Residual
2000.
0.
0.
300.
1500.
2000.
0.
0.
300.
2000.
0.
300.
150.
1500.
2000.
0.
300.
150.
1000.
0.
0.
20000.
4500.
0.
20000.
4500.
4500.
155
-------
Also for purposes of the demonstration, it is assumed that all maintenance on
the system can be scheduled during the intervals between sampling. That is,
there is no routine maintenance downtime for Candidate 1.0.
Appendix G contains a complete listing of the design analysis program data
deck for Candidate 1.0.
Candidate 2.0 —
In order to provide for direct comparison between Candidate 1.0 and Candidate
2.0, the same choice of monitored parameters and segments is used in both
candidates. Table 16 summarizes the nominal characteristics of the Candidate
2.0 system. The very high sampling rate corresponds to an assumed hourly
sampling interval for automated equipment. It is also assumed that the auto-
matic equipment can be positioned at or very near the preferred sampling
locations, with appropriate compromises being made when DO is sampled along
with other parameters. Maintenance on the Candidate 2.0 equipment is per-
formed weekly and takes six hours (T = 6. 75 days, T , = 0. 25 days).
up down '
The organizational and functional frameworks for the means listed in Table 17
are shown in Figures 56, 60, 61 and 62. Each state is to operate its own
telemetered remote monitoring system that transmits data to a central process-
ing system for display. In addition, each monitoring station records the obser-
vations on an analog stripchart recorder for weekly collection by the mainte-
nance personnel.
The assumed sampling errors, failure and repair rates, and system costs for
Candidate 2.0 are presented in Tables 18, 19, and 20.
A complete listing of the design analysis data deck for Candidate 2.0 may be
found in Appendix G.
156
-------
Table 16. CANDIDATE 2. 0 SAMPLING PROGRAM
(sampling interval in days, locations in river miles)
Reach
2
9
18
21
30
36
Dissolved
Solids
0.0417
Cyanides
0.0417
Phenols
0.0417
0.0417
0.0417
DO
0.0417
0.0417
0.0417
0.0417
Location
82.5
37.0
36.8
31.0
12.5
7.8
157
-------
Table 17. SYSTEM MEANS FOR CANDIDATE 2. 0
Means No.
21
22
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
41
42
43
44
50
51
52
53
State
PA
PA
PA
PA
PA
PA
PA
PA
PA
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
PA
PA
PA
PA
Description
DO Monitor "1"
Conductivity Monitor
Phenols Monitor
DO Monitor "2"
Recorder "1"
Service Team "1"
Radio Telemetry Unit "1"
Central Telemetry Unit
Recorder "2"
Cyanide Monitor
Phenol Monitor "1"
Phenol Monitor "2"
DO Monitor "1"
DO Monitor "2"
Recorder "1"
Paper Tape Punch
Service Team
Recorder "2"
Telephone Telemetry Unit "1"
Telephone System
Central Telemetry Unit
Recorder "3"
Telephone Telemetry Unit "2"
Radio Telemetry Unit "2"
Recorder "3"
Radio Telemetry Unit "3"
Service Team "2"
158
-------
GROUP 2
OHIO
SYSTEM
1 GROUP 3
DATA
ACQUISITION
1 GROUP 4
FIELD
MAINTENANCE
TELEPHONE NETWORK©
1
GROUPS 1 GROUPS | GROUP 7
STATION
SEGMENT 2
SERVICE TEAM (0)
CENTRAL T/M UNIT @
STATION STATION
SEGMENT 9 SEGMENT 21
DO MONITOR "1" ®
RECORDER "1" ®
TAPE PUNCH NO. ®
PHENOL MONITOR"!"©
RECORDER "2" ®
T/M UNIT "V ®
CYANIDE MONITOR©
PHENOL MONITOR "Z"
DO MONITOR "2" ®
RECORDER "3" ®
T/M UNIT "2" (§
Figure 60. Ohio System Organizational Framework Assumed for Candidate 2.0
GROUPB
[GROUP
CENTRAL
FACILITY
t
[GROUP 10
FIELD
OFFICE
CENTRAL T/M UNIT ®
_____ • , 1 , , —
(GROUP 11 | GROUP 12
STATION
SEGMENT 18
SERVICE TEAM "V®
SERVICE TEAM "2" ©
STATION
SEGMENT 30
00 MONITOR "1" ©
RECORDER "1" ©
T/M UNIT "1" @
(GROUP 13
STATION
SEGMENT 36
CONDUCTIVITY MONITOR
PHENOLS MONITOR®
RECORDER "2" ®
00 MONITOR "2" v
RECORDER "3" ©
T/M UNIT "3" ®
T/M UNIT "2" @
Figure 61. Pennsylvania System Organizational Framework for Candidate 2.0
159
-------
SEGMENT PARAMETER
2 17
18
21
I I
17
I
LEGEND
OPERATING MEANS
SEGMENT PARAMETER
$
4!
36
37
F
h
r 53 -,
oft oc
{2O —•— 26
^rn
27 — 28
h-S
44
H
42
30
30
36
17
05
I !
17
- 53 n
28J-
28 J
r 51 -1-26
L 52 — 28
^J PRIMARY STANDBY MEANS [~^ SECONDARY STANDBY MEANS
Figure 62. Functional Framework for Candidate 2.0
-------
Table 18. ASSUMED SAMPLING EREORS FOR CANDIDATE 2. 0
Parameter
Dissolved Solids
Cyanides
Phenols
Dissolved Oxygen
Parameter
Number
5
10
11
17
Accuracy
(€)
15.
0.02
0.001
0.05
Precision
<
60.
0. 15
0.005
0.15
161
-------
Table 19. ASSUMED FAILURE AND REPAIR RATES FOR CANDIDATE 2.0
(years~l)
Means
No.
21
22
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
41
42
43
44
50
51
52
53
Survival
Rate
(Operating)
0.2
0.2
0.2
0.2
0.2
0.01
0.2
0.01
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.01
0.2
0.2
0.01
0.01
0.2
0.2
0.2
0.2
0.2
0.01
Survival
Rate
(Standby)
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Failure
Rate
(Operating)
5.0
5.0
6.0
5.0
3.0
2.0
5.0
3.0
3.0
6.0
6.0
6.0
5.0
5.0
3.0
3.0
2.0
3.0
5.0
52.0
3.0
3.0
5.0
5.0
3.0
5.0
2.0
Failure
Rate
(Standby)
365.
365.
365.
365.
0.3
0.5
1.
3.
0.3
365.
365.
365.
365.
365.
0.3
0.3
0.5
0.3
1.0
52.0
3.0
0.3
1.0
1.0
0.3
1.0
0.5
Repair
Rate
(Operating)
100.
100.
100.
100.
100.
365.
137.
365.
100.
100.
100.
100.
100.
100.
100.
100.
365.
100.
137.
9999.
365.
100.
137.
137.
100.
137.
365.
Repair
Rate
(Standby)
365.
365.
365.
365.
45.
365.
137.
365.
45.
365.
365.
365.
365.
365.
45.
45.
365.
45.
137.
9999.
365.
45.
137.
137.
45.
137.
365.
162
-------
Table 20. ASSUMED COMPONENT COSTS FOR CANDIDATE 2.0
Means A
21
22
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
41
42
43
44
50
51
52
53
Groups
1
2
3
4
5
6
7
8
9
10
11
12
13
cquisition
1200.
800.
3500.
1200.
1200.
3000.
7000.
45000.
1200.
3500.
3500.
3500.
1200.
1200.
1200.
1800.
3000.
1200.
4500.
0.
40000.
1200.
4500.
7000.
1200.
7000.
3000.
40000.
10000.
20000.
5000.
1000.
1000.
1000.
10000.
20000.
5000.
1000.
1000.
1000.
Operation
200.
100.
300.
200.
20.
5000.
400.
500.
20.
300.
300.
300.
200.
200.
20.
20.
5000.
20.
400.
12000.
400.
20.
400.
400.
20.
400.
5000.
0.
5000.
1000.
2500.
150.
150.
150.
5000.
1000.
2500.
150.
150.
150.
Maintenance
200.
50.
350.
200.
50.
400.
1000.
1000.
50.
350.
350.
350.
200.
200.
50.
50.
400.
50.
900.
0.
1000.
50.
900.
1000.
50.
1000.
400.
0.
0.
0.
500.
350.
350.
350.
0.
0.
500.
350.
350.
350.
Residual
900.
600.
1800.
900.
900.
2000.
5500.
35000.
900.
1800.
1800.
1800.
900.
900.
900.
1000.
2000.
900.
3800.
0.
35000.
900.
3800.
5500.
900.
5500.
2000.
0.
0.
20000.
4500.
150.
150.
150.
0.
20000.
4500.
150.
150.
150.
163
-------
Task 5 - Candidate Evaluation
The evaluation of Candidates 1. 0 and 2. 0 is performed using the design analysis
programs in the final design mode. As previously mentioned, the input data.
decks are listed in Appendix G. The resulting computer print-outs may also be
found in Appendix G.
Tables 21 and 22 summarize the results of the cost-effectiveness computer runs
for Candidate 1.0 and 2.0, respectively. The data in each table are rounded to
3 decimal places.
Table 21. SUMMARY COST-EFFECTIVENESS RESULTS FOR CANDIDATE 1.0
Parameter
5
10
11
11
11
17
17
17
17
Segment
30
21
9
21
30
2
18
21
36
Capability
0.004
0.017
0.009
0.001
0.006
0.001
0.017
0.017
0.017
Survivability
0.936
0.979
0.960
0.960
0.960
0.766
0.936
0.936
0.936
Availability
1.000
1.000
0.929
0.929
0.929
0.968
1.000
1.000
1.000
V
0.003
0.017
0.008
0,001
0.005
0.001
0.016
0.016
0.016
E =0.151
sys
K = $1.535 • 10l
sys
T = 10.162 • 10
1.0
164
-------
Table 22. SUMMARY COST-EFFECTIVENESS RESULTS FOR CANDIDATE 2.0
Parameter
5
10
11
11
11
17
17
17
17
Segment
30
21
9
21
30
2
18
21
36
Capability
0.008
0.034
0.036
0.010
0.009
0.009
0.031
0.000
0.030
Survivability
0.981
0.980
0.980
0.980
0.981
0.796
0.981
0.980
0.981
Availability
0.999
0.978
0.978
0.978
0.999
0.947
0.999
0.978
0.999
V
0.007
0.032
0.035
0.010
0.009
0.007
0.031
0.000
0.030
E -0.292
sys
K = $2.005 • 10
sys
Task 6 - Design Selection
In an actual design analysis, the next step is the selection of one of the candi-
dates, or alternatively the design of new candidates, on the basis of the analysis
results.
If the objective is to select one of the two candidates, the separate acceptability
of E and K must first be considered. Then the comparison for cost-effec-
sys sys
tiveness made.
The effectiveness of both candidates is relatively low, while the costs for the
one-year system duration seem within reason. The high frequency sampling of
165
-------
the Candidate 2.0 system does have a clear advantage over the low frequency
Candidate 1.0 system, yielding almost twice the effectiveness. Yet the Candi-
date 1.0 system stands up reasonably well, when one considers that the sampl-
ing rate of Candidate 2.0 is about 200 times greater.
If it is assumed that both effectiveness ratings are acceptable, then the choice
goes to Candidate 2. 0 on the basis of a lower cost/effectiveness ratio (r). It
should be noted that Candidate 2.0 is the more costly of the two. It is the
higher system effectiveness of Candidate 2.0 that makes it the "better" system
This seems an appropriate point to remind the reader of the caveat at the begin-
ning of the Section. These results are entirely a function of the assumptions of
the demonstration. They should not be interpreted as a recommendation of
Candidate 2.0 for use in the Beaver River Basin.
ADDITIONAL CANDIDATES
A more likely course of action for the system designer during Task 6 would be
rejection of both candidates on the basis of the low effectiveness ratings. The
next step would be to return to Task 4 and design additional candidates with the
intention of improving the performance. The following paragraphs explore some
possible candidates that might result from such a decision.
Candidate 1.1
In attempting to improve the effectiveness of Candidate 1.0, the system designer
examines the analysis results for points of poor performance. Capability is the
prime cause of the low effectiveness associated with Candidate 1.0 (Table 21). in
mostcases the sampling interval used in Candidate 1.0 is near the expected duration
of the violations. It might be expected that an improvement would result from
increased sampling in some reaches, especially in the light of the analysis
166
-------
results for Candidate 2.0. Other stations might be eliminated altogether, due
to low effectiveness.
Candidate 1.1 is designed using Candidate 1.0 as a basis. The sampling inter-
vals are changed to the values indicated in Table 23, while the costs are adjust-
ed upwards or downwards to match the increased or decreased sampling (Table
24). Appendix G presents a complete listing of the data deck for Candidate 1.1.
The analysis results for Candidate 1.1 are shown in Table 25.
It can be seen that Candidate 1.1 represents a real improvement over Candidate
1.0, although it is still not as good as Candidate 2.0. Despite the elimination
of sampling for phenols at reach 21 and the doubling of the DO sampling inter-
val at reach 2, the new effectiveness is only 0. 051 greater than the Candidate
1. 0 effectiveness (E ). Since cost is only slightly increased, due to cost
sy s
reductions at those two system elements, the cost-effectiveness ratio is signifi-
cantly improved.
Candidate 2.1
In the examination of Candidate 2.0 analysis results, the system designer might
particularly note the very low capability associated with the DO monitor in reach
21. The designer might conclude that the station is misplaced, since the high
sampling rate of Candidate 2.0 should assure that it would detect any violation
occurring at the monitoring point.
The conclusion is correct. The intent was to monitor the DO at the downstream
end of reach 10 by placing the station at the head of reach 21. However,
Mosquito Creek joins the Mahoning at reach 21, contributing relatively high
DO waters. Computationally, the math model incorporates the addition by pro-
167
-------
Table 23. CANDIDATE 1. 1 SAMPLING PROGRAM
(sampling interval in days, locations in river miles)
Reach
2
9
18
21
30
36
Dissolved
Solids
3.5
Cyanides
3.5
Phenols
7
3.5
DO
90
7
3.5
7
Location
82.5
37.0
36.8
30.6
11.0
4.0
168
-------
Table 24. ASSUMED COMPONENT COSTS FOR CANDIDATE 1.1
Means
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Group
1
2
3
4
5
6
7
8
Acquisition
3000.
400.
400.
600.
1500.
3000.
400.
400.
600.
3000.
400.
600.
300.
1500.
3000.
400.
600.
300.
1500.
40000.
10000.
20000.
5000.
10000.
20000.
5000.
5000.
Operation
10000.
1000.
500.
20.
50.
1000.
50.
50.
10.
7000.
1000.
10.
20.
50.
1000.
50.
10.
10.
200.
0.
5000.
4500.
2500.
5000.
4500.
1500.
1500.
Maintenance
600.
0.
0.
200.
0.
400.
0.
0.
100.
400.
0.
100.
100.
0.
400.
0.
100.
50.
100.
0.
0.
1000.
500.
0.
1000.
250.
250.
Residual
2000.
0.
0.
300.
1500.
2000.
0.
0.
300.
2000.
0.
300.
150.
1500.
2000.
0.
300.
150.
1000.
0.
0.
20000.
4500.
0.
20000.
4500.
4500.
169
-------
ducing two different DO values for RM 7. 8, one at the downstream end of reach
10 and the other at the upstream end of reach 21.
Table 25. SUMMARY COST-EFFECTIVENESS RESULTS FOR CANDIDATE 1.1
Parameter
5
10
11
11
17
17
17
17
Segment
30
21
9
30
2
18
21
36
Capability
0.006
0.025
0.020
0.007
0.000
0.017
0.027
0.017
Survivability
0.936
0.979
0.960
0.960
0.766
0.936
0.936
0.936
Availability
1.000
1.000
0.929
0.929
0.968
1.000
1.000
1.000
V
0.005
0.025
0.017
0.006
0.000
0.016
0.025
0.016
E =0.202
sys
K = $1.619 • 105
sys
r = 8.013 • 105
J-« -L
Thus, both computationally and in actuality the stream monitor should be placed
upstream of the stream junction to detect DO violations in reach 10. '
Table 26 presents the analysis results for Candidate 2.1. The new candidate is
identical with Candidate 2.0, except that the DO monitor is moved to reach 10
RM 7.8. (See Appendix G for a data deck listing.) The result is a slight
improvement in system effectiveness with the associated improvement in coat-
effectiveness. Since costs have not been revised to reflect the need for addi-
tional equipment to support the relocated monitor, the actual cost-effectiveness
would be somewhat poorer than that shown in Table 26.
170
-------
Table 26. SUMMARY COST-EFFECTIVENESS RESULTS FOR CANDIDATE 2.1
II
Parameter
5
10
11
11
11
17
17
17
17
Segment
30
21
9
21
30
2
10
18
36
Capability
0.007
0.034
0.036
0.010
0.009
0.009
0.002
0.031
0.030
Survivability
0.981
0.980
0.980
0.980
0.981
0.796
0.980
0.981
0.981
Availability
0.999
0.978
0.978
0.978
0.999
0.947
0.978
0.999
0.999
V
0.007
0.032
0.035
0.010
0.009
0.007
0.002
0.031
0.030
E -0.296
sys
K = $2.005 • 10
sys
T = 6,777- 10
2.1
Design Selection
With the additional analyses the system designer is in a better position to evalu-
ate his candidates and select one. It appears on the basis of the results contained
in Tables 21, 22, 25 and 26 that, of those examined, Candidate 2.0 remains the
preferred design for a one-year system duration under the demonstration
assumptions. While Candidate 1.1 is an improvement over Candidate 1,0, it is
still inferior to Candidates 2.0 and 2.1,
The system designer may wish to perform one more iteration before settling on
Candidate 2.0, however. Since there is little improvement when the DO monitor
171
-------
is moved from reach 21 to reach 10, it might be of interest to examine a candi-
date similar to candidate 2.0, but without DO monitoring in either reach 10 or
21. It is left to the interested reader to pursue this line of reasoning. Sufficient
information may be found in the tables and Appendix G to permit a manual com-
putation of the change in E and K
sys sys
FURTHER ILLUSTRATION
In addition to the points demonstrated in the preceeding, there are several other
factors worthy of illustration. One of these is the effect of choice of flow record
length. Another is the effect of increased system duration. The third is the
potential for improved system effectiveness through additional monitoring. Each
of these factors is discussed in the following paragraphs.
Length of Flow Record
The estimation of effectiveness depends on estimates for the T 's and T fs, that
are, in turn, derived from USGS gaging station flow data. The length of the
record used in the analysis affects the results in two ways. For those reaches
in which the river is either constantly in violation state or constantly in non-
violation state, the value of n ** is a function of the record length. For those
cases either T ** or T ** is equal to the record length, the other is zero, and
equation (21) reduces to either:
<42>
n"<''j)= (43>
172
-------
The other effect of the record length is in the estimation T Ts and T »s for
reaches with low variability. Since these expected durations are computed as
averages (equation (41)), the quality of the estimate improves as the number
of events increases. The number of events included in the averages is, in turn,
a function of the flow record length.
Thus, the system designer might wish to question the stability of the analysis
results as a function of USGS gaging station record length.
To answer the question for Candidate 1.0 and to illustrate the general case,
three analysis of Candidate 1.0 are run. The three analyses are for record
lengths of 4, 5 and 6 years, respectively. The resulting system effectiveness
for each case is listed in Table 27. Some trend toward increased E with
sys
increased record length can be seen, due primarily to the reduction in n **.
The results are relatively stable, however, despite the 20% changes in record
length.
Table 27. EFFECT OF FLOW RECORD LENGTH ON E
sys
(Candidate 1.0)
Record Length
(years)
4
5
6
E
sys
0.141
0.151
0.159
Thus, comparison of candidate systems analyzed using the same flow record is
unaffected by the absolute length of the flow record, as long as it is sufficiently
long to include several violation events. This is due to the use of the same
values for n ** in each calculation of E
v sys
173
-------
In addition, the absolute value of cost-effectiveness is relatively stable for
large changes in the flow record length. Table 27 would suggest a variation
of about 5% for record length changes on the order of 20%.
Increased System Duration
Unlike the flow record length, the choice of system duration may be expected to
have a major effect on the analysis results. As system duration increases,
candidates with large ratio of fixed costs to variable costs will have an increased
advantage over candidates with low ratios. That is, systems that operate with
the largest proportion of their costs in the operation and maintenance categories
will tend to increase total cost faster than those with a predominance of the
acquisition cost.
Since such clear-cut distinctions are difficult to make in the demonstration
candidates used previously in this section, the system designer cannot, a. priori.
decide which will be the better system for a longer system duration. Use of
the analysis programs does provide the answer.
Candidates 1.2 and 2.2 are created from Candidates 1.1 and 2.1, respectively,
to test the effect of increased system duration. The major change in the data
decks (see listings in Appendix G) is the adjustment of the cost data. The
operating and maintenance budgets are increased by a factor of 5 to correspond
to a 5-year system duration. In addition, appropriate changes are made when-
ever replacement of equipment is anticipated. For example, allowance is made
to supply field crews with new vehicles during the system duration.
The analysis results for Candidates 1.2 and 2.2 are summarized in Tables 28
and 29.
174
-------
Table 28. SUMMARY COST-EFFECTIVENESS RESULTS FOR CANDIDATE 1.2
Parameter
5
10
11
11
17
17
17
17
Segment
30
21
9
30
2
18
21
36
Capability
0.006
0.025
0.020
0.007
0.000
0.017
0.027
0.017
Survivability
0.393
0.700
0.633
0.633
0.145
0.393
0.393
0.393
Availability
1.000
1.000
0.929
0.929
0.968
1.000
1.000
1.000
"a*
0.002
0.018
0.011
0.004
0.000
0.007
0.010
0.007
E =0.108
sys
K =$4.367 • 10
sys
-L •
=40.302 • 10
= 8.060 • 105
annual
The results are as expected. The total system costs are increased and the
system effectiveness is decreased due to the possibility of irrecoverable failure.
In the case of Candidate 1.2, the effectiveness is about 1/2 that of Candidate
1. 1. For Candidate 2. 2, E is about 2/3 of the value for Candidate 2. 1. The
sys
value of the cost-effectiveness ratio gives Candidate 2.2 the clear advantage
over Candidate 1.2, despite a $100,000 difference in total cost.
The reader is reminded once again that these results are a function of the
arbitrary data used in this demonstration. Unwarranted conclusions about real
systems should not be drawn.
175
-------
In order to compare these candidates with the previous candidates designed for
one-year system duration, a factored cost-effectiveness can be computed. By
divising the r's for Candidates 1.2 and 2.2 by a factor of 5, an average annual
r can be computed, as shown in Tables 28 and 29. As expected, the automatic
system
E =0.212
sys
K = $5.564 . 105
sys
T =26.190 • 105
T , = 5.238 • 105
annual
(Candidate 2.2), with its higher initial investment and lower operating and
maintenance costs, comes out ahead, when compared with Candidates 1.1, 1.2
and 2.1 on an annual basis.
Table 29. SUMMARY COST-EFFECTIVENESS RESULTS FOR CANDIDATE 2.2
Parameter
5
10
11
11
11
17
17
1 -•;
17
Segment
30
21
9
21
30
2
10
18
36
Capability
0.008
0.034
0.036
0.010
0.009
0.009
0.002
0.031
0.030
Survivability
0.726
0.717
0.717
0.717
0.726
0.254
0.717
0.726
0.726
Availability
1.000
0.978
0.978
0.978
0.999
0.947
0.978
0.999
0.999
•«•'
0.006
0.024
0.025
0.007
0.006
0.002
0.002
0.023
0.022
•~"^— ^••^^i
176
-------
Additional Monitoring
Finally, the system designer might wish to explore the effects of increased
monitoring of the basin. General results of implementing monitoring in addi-
tional segments cannot be predicted. The result for the Beaver River Basin can
be used as an illustration of a specific case, however.
Candidate 2.3 is developed from Candidate 2.2 by implementing additional
monitoring for phenols and dissolved oxygen. The additional sampling is
detailed in Table 30. The additional organizational and functional frameworks
are specified in Figures 63, 64 and 65 for the additional means listed in Table
31. A complete listing of the data deck for Candidate 2.3 can be found in
Appendix G.
The analysis results for Candidate 2.3 are summarized in Table 32.
A tremendous improvement in the system effectiveness and cost-effectiveness
ratio is achieved by this additional monitoring. The E jumps from about
sys
20% for Candidate 2.2 to nearly 60% for Candidate 2.3. Costs are, of course,
greater, but the improved effectiveness reduces r from about 26 • 10 to about
12 • 10 . On an annual basis, this is equivalent to a cost-effectiveness ratio of
5
about 2.4 • 10 , the best r achieved by any of the candidates examined.
5
Thus, it would appear that, if a budget of $7.23 • 10 over five years is accept-
able, Candidate 2.3 is the choice of the system designer (within the limits of
the demonstration).
FINAL COMMENTS
The demonstration cases examined in this section suggest the utility of the
design analysis programs from a performance viewpoint.
177
-------
R1343
Table 30. CANDIDATE 2. 3 SAMPLING PROGRAM
(sampling interval in days, locations in river miles)
Reach
2
9
10
16
17
18
19
21
24
27
28
29
30
35
36
Dissolved
Solids
0.0417
Cyanides
0.0417
Phenols
0.0417
0.0417
0.0417
0.0417
0.0417
0.0417
0.0417
0.0417
DO
0.0417
0.0417
0.0417
0.0417
0.0417
0.0417
0.0417
Location
82.5
37.0
31.0
44.8
42.4
36.8
35.6
31.0
23.5
18.5
16.5
15.5
12.5
7.8
4.6
Weighted against their utility is the cost of using the computer programs. The
time occupied in the preparation of the candidate system designs and data decks
is of course, a function of the system designer and the facilities available to
him. The computer run times are a function of the machine used and the pro-
gramming.
178
-------
°H'°
I SYSTEM |
GROUP 2
G»OUPZ
FIGURE, ...
68 '
STAT
SECM
ON
ENT24
GROUP U
STAT
SEGNI
PHENOLS MONITOR "3"
RECORDER "4"
11
T/M UNIT'
3"
ON
ENT27
GROUP. 5
STATI
SEGM
PHENOLS MONITOR "4"
RECORDER
"5"
T/M UNIT "4"
OH
ENT28
GROUP 16
S°NMT29 'RDUP17
PHENOLS MONITOR "5" ^
RECORDER "6"
TO
T/M UNIT
'5" '»
PHENOLS MONITOR "6"
RECORDER"?"
T/M UNIT "6"
81
82
Figure 63. Additional Ohio Organizational Framework Assumed for Candidate
2.3
I 1
I PENNSYLVANIA !
I SYSTEM I
L , 1
i
I
FIGURE r
69 '
1
STATION
SEGMENT 16
GROUP IB
STATION
SEGMENT 17
DO MONITOR "3"
RECORDER "4" M
T/M UNIT
'*" D5
GROUP 19
STATION
SEGMENT 19
DO MONITOR "4"
RECORDER "6" 0,
T/M UNIT
•5" Dfi
GROUP 20
STATION
SEGMENT 35
00 MONITOR "5" „
RECORDER "6" „„
T/M UNIT
•6" .,,
GROUP 21
00 MONITOR "6"
RECORDER"?"
T/M UNIT
T
94
Figure 64. Additional Pennsylvania Organizational Framework Assumed for
Candidate 2.3
179
-------
SEGMENT PARAMETER
24 11
27
29
16
17
19
35
11
11
17
17
17
17
f~~] -OPERATING MEANS
-PRIMARY STANDBY MEANS
-SECONDARY STANDBY MEANS
Figure 65. Additional Functional Framework for Candidate 2.3
180
-------
Table 31. ADDITIONAL SYSTEM MEANS FOR CANDIDATE 2. 3
Means
No.
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
State
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
PA
PA
PA
PA
PA
PA
PA
PA
PA
PA
PA
PA
Same Type of Equipment
as Means No. *
32
36
40
32
36
40
32
36
40
32
36
40
34
36
27
34
36
27
34
36
27
34
36
27
*Implies the use of the same cost and reliability/
maintainability data.
181
-------
Table 32. SUMMARY OF COST-EFFECTIVENESS RESULTS
CANDIDATE 2.3
FOR
Parameter
5
10
11
11
11
11
11
11
11
17
17
17
17
17
17
17
17
Segment
30
21
9
21
24
27
28
29
30
2
10
16
17
18
19
35
36
Capability
0.008
0.034
0.036
0.010
0.042
0.004
0.046
0.056
0.035
0.009
0.002
0.002
0.021
0.031
0.047
0.030
0.050
Survivability
0.726
0.717
0.717
0.717
0.717
0.717
0.717
0.717
0.726
0.254
0.717
0.726
0.726
0.726
0.726
0.726
0.726
Availability
0.999
0.978
0.978
0.978
0.978
0.978
0.978
0.978
0.999
0.947
0.978
0.999
0.999
0.999
0.999
0.999
0.999
*
nd
0.006
0.02^
0.025
0.007
0.030
0.003
0.032
0.039
0.025
0.002
0.002
0.002
0.015
0.023
0.034
0.022
0.036
E
K
r
sys
T
''sys
»
2.3
- 0.593
= $7.238-10£
= 12.196-10£
5
T , =2.439-10
annual
182
-------
Typical computation times on the CDC 6700 ranged from about 3 min CPU time
for the preliminary design run to 5 min CPU time for the final design analysis
of Candidate 2.3. In practice, the authors found that, given the basic data deck,
a candidate could be revised, the data deck modified and the analysis results
computed in the span of two hours (during the evening shift on Raytheon1 s CDC
6700). Preparation of the basic data deck, of course, required a substantially
longer time, due primarily to the keypunching requirement. Excluded from
consideration here is the labor involved in calibrating the RIBAM model. See
[7] for an understanding of that process.
The computation times mentioned above are quite long and constitute a sub-
stantial dollar cost. When compared with the potential cost of performing the
design analysis manually, they are quite acceptable, if used with discretion.
The system designer may wish to take due precautions to assure that the data
*
deck, especially the last files (e.g., COSTM and COSTG), are correct before
submission for a run. Errors in the data deck frequently cause termination of
the run before the final results are printed, causing loss of information from
analysis of the correct portions of the data deck. Such loss can be expensive,
if it occurs near the end of a 5 min run.
183
-------
SECTION IX
DISCUSSION
The water quality surveillance system design methods developed in [3] and in
this report constitute a fundamental approach to the engineering of La-stream
monitoring systems. They incorporate all the major factors influencing the
system designer in his selection of design options and provide reasonable guide-
lines for the assessment of those factors for a given river basin.
The procedures have been successfully demonstrated on the Wabash River Basin
[3] and on the Beaver River Basin. The results of the demonstration analyses
seem consistent with our understanding of river processes and systems per-
formance. The definition of system effectiveness presented in equation (14)
appears to have significance in the present context of in-stream monitoring.
As illustrated in the demonstration, it is sensitive to changes in the basic sys-
tem characteristics and provides the system designer with useful information
to guide the iterative development of his design. The demonstration also
suggests that the computerization of the design methods substantially satisfies
the goals of drawing on the existing basin modeling capabilities and reducing the
labor involved in evaluation of candidate systems. The costs of computer usage
are very reasonable when considered in the light of the alternatives.
However, the methods developed in this report do not constitute a complete
analysis of the design problem. As indicated in Section VI and [3], a number of
lesser design factors have been neglected in the effort to develop a beginning-to-
end approach incorporating the more important considerations. Furthermore, a
number of simplifying assumptions and pragmatic substitutions have been used,
when required, to by-pass particularly knotty problems. While the approach as
185
-------
a whole performs well in the demonstration, each of these artifices should be
subject to further confirmation.
In the development of these methods, emphasis has been placed on the theoret-
ical and functional aspects. It is not claimed that the computer programs are
fully optimized. In the context of a development project, the authors are
satisfied that they correctly perform the necessary computations without requir-
ing either excessive storage or CPU time.
In addition, real application of the method in the near future may be expected to
suffer from limitations on cost and reliability data. Experience and the litera-
ture (e.g., the extensive review in [28]) suggest that the techniques and instru-
ments employed for water quality surveillance have a history of questionable per-
formance in these areas. Detailed analyses of their performance are not avail able,
in general. Consider ing the extent of surveillance required to implement the current
legislation [1], development of a data base to support cost-effectiveness analysis
appears entirely in order. It seems entirely within the prerogatives of the govern-
mental agencies engaged in water quality surveillance to develop such a capability.
The water quality surveillance called for in[l] is, of course, not confined to in-
stream monitoring. The emphasis is shared with direct monitor ing of point-source
effluents. Similar development of systems analysis methods should be aimed at the
effluent monitor ing sector of the surveillance system. Since effluent monitor ing and
in-stream monitoring constitute complementary parts of a total surveillance
capability, future development of system design methods should optimize total
system performance through compatible use of both monitoring strategies.
In conclusion, the worth of these methods will be proven in the application. The
authors fully expect that each user will have his own contribution to make to the
design methods. The computer programs are not immutable; they should be
186
-------
used as a tool and modified as appropriate to the situation. Likewise, the
methods will benefit from the experience gained through application in a variety
of river basins.
187
-------
SECTION X
REFERENCES
[l] Public Law 92-500, Federal Water Pollution Control Act, Sections 101 (a)
and 104 (a) (5) (1972).
[2] Sayers, W. T. Water Quality Surveillance. Environmental Science and
Technology. 5 (2), February 1971.
[3] Beckers, C.V., S. G. Chamberlain, and G. P. Grimsrud. Quantitative
Methods for Preliminary Design of Water Quality Surveillance Systems.
Environmental Protection Agency, Washington, DC. Report No. EPA-R5-
72-001. November 1972. 226 p.
[4] Ward, R.C. Data Acquisition Systems in Water Quality Management,
Environmental Protection Agency, Washington, DC. Report No. EPA-R5-
73-014. May 1973. 259 p.
[5] NUS Corporation. Design of Water Quality Surveillance Systems. US Dept
of the Interior, Federal Water Quality Administration, Washington, DC.
Report No. 16090 DBJ 08/70. August 1970. 302 p.
[6] Moore, S. F. Estimation Theory Applications to Design of Water Quality
Monitoring Systems. Jour. Hydr. Div., Proc. ASCE. 99_ (HY5): 815-831,
May 1973.
[7] Raytheon Company. Documentation Report, Beaver River Basin Model
Project. Environmental Protection Agency, Washington, DC. Draft Report,
Contract No. 68-01-0746. March 1973. Vols. I and n, 531 p.
[8] Public Law 92-500, Federal Water Pollution Control Act Amendments of
1972, 86 STAT 816 et. seq., October 18, 1973.
[9] Committee on Public Works, US House of Representatives. Laws of the
United States Relating to Water Pollution Control and Environmental Quality.
US Government Printing Office, Washington, DC. July 1970. 265 p.
[10] Vanderholm, D.H. Planning Water Quality Surveillance. Dept. of Agri-
cultural Engineering, Colorado State University. Ph. D. Dissertation.
1972. 148 p.
[11] Texas Water Development Board. DOSAG-1, Simulation of Water Quality
in Streams and Canals, Program Documentation and User's Manual.
Report No. PB 202 974. September 1970.
189
-------
[12] Seller, K. Introduction to Systems Cost Effectiveness. New York, Wiley-
Interscience, 1969. 108 p.
[13] Sandier, G.H. System Reliability Engineering. Englewood Cliffs, Prentice-
Hall, 1963. 221 p.
[14] Goldman, A. S., and T. B. Slattery. Maintainability: A Major Element of
System Effectiveness. New York, John Wiley & Sons, Inc., 1964, 282 p.
[15] Grant, E. L., and W. G. Ireson. Principles of Engineering Economy, 4th
ed. New York, The Ronald Press Co., 1960. 574 p.
[16] English, J.M., ed. Cost Effectiveness—the Economic Evaluation of Engineered
Systems. New York, John Wiley & Sons, Inc., 1968. 301 p.
[17] Helstrom, C.W. Statistical Theory of Signal Detection. New York, Pergamon
Press, 1960. 364 p.
[18] Raytheon Company. Data Report, Beaver River Basin Model Project.
Environmental Protection Agency, Washington, DC. Draft Report, Contract
No. 68-01-0746. November 1972.
[19] Feinstein, A. Foundations of Information Theory. New York, McGraw-Hill,
1958. 137 p.
[20] International Mathematical and Statistical Libraries, Inc. IMSL Library 3
Reference Manual, 2nd ed. Houston. December 1972.
[21] Texas Water Development Board. QUAL-1, Simulation of Water Quality
in Streams and Canals, Program Documentation and Users Manual.
September, 1970.
[22] Texas Water Development Board. Simulation of Water Quality in Streams
and Canals. Theory and Description of the QUAL-1 Mathematical Modeling
System. May 1971.
[23] Environmental Protection Agency, Water Quality Office. Storm Water
Management Model. Washington, DC. September 1971. Vol. I, II, HI & rv.
[24] Water Resources Engineers, Inc. Mathematical Models for the Prediction
of Thermal Energy Changes in Impoundments. Environmental Protection
Agency, Washington, DC. December 1969.
[25] Water Resources Engineers, Inc. Mathematical Models for the Prediction
of Thermal Energy Changes in Impoundments, Computer Application Supple-
ment. Federal Water Pollution Control Administration, Columbia River
Thermal Effects Project.
190
-------
[26] Environmental Protection Agency, Region X, Pacific Northwest Laboratory.
User's Guide and Documentation for Outfall PLUME Model. Working Paper
No. 80. May 1971.
[27] Feigner, K.D., andH.S. Harris. Documentation Report, FWQA Dynamic
Estuary Model. US Dept of the Interior, Federal Water Pollution Control
Administration. July 1970.
[28] Sylvester, M. Application of Automatic Monitors for State Water Quality
Surveillance. Dept. of Agricultural Engineering, Colprado State University,
M.S. Thesis. August 1972. 143 p.
[29] Pennsylvania Department of Health, Region III. Report on the Beaver River.
Harrisburg. 1963.
[30] US Dept. of Health, Education and Welfare. Report on Quality of Interstate
Waters of the Mahoning River. Chicago. 1965.
[31] US Dept. of the Interior, Federal Water Pollution Control Administration,
Ohio Basin Region. Benthic Biology of the Beaver River Basin—Ohio,
Pennsylvania. Washington, DC. 1968.
191
-------
SECTION XI
GLOSSARY
Abatement Objective - The system design goal in which the objective is to detect
the occurence of water quality standards violations.
Basin Subset - The portion of a river basin that is under consideration in system
design.
BOD - Biochemical Oxygen Demand.
Conservative Parameter - A water quality parameter that does not decay as a
function of time, for example, dissolved solids. (See Appendix A.)
Critical Point - The point in a stream segment at which a water quality param-
eter reaches its worst value.
DO_- Dissolved Oxygen.
Final Design - The stage of surveillance system design that deals with the total
performance of the surveillance system in achieving its design goals.
Impact Nucleus - Same as Source Group.
^Macroscopic Concept" - The overview approach to system design that limits the
spatial and temporal scales.
Means - A way of performing a function necessary to the production of water
quality; an equipment, technology, device, person, or a combination of these.
NL_T - Not less than.
Non-Conservative, Coupled Parameter - A water quality parameter for which
the concentration in the stream is a function both of time and of the concentra-
tion of other parameters. An example is DO, which is coupled to BOD. (See
Appendix A.)
193
-------
Non-Conservative, Non-Coupled Parameter - A water quality parameter for
which the concentration in the stream is a function of time. BOD is an example.
(See Appendix A.)
NTE - Not to exceed.
Preliminary Design - The stage of surveillance system design that deals solely
with the relationship of the surveillance system to the natural system.
Reach - Same as Segment.
Segment - A length of stream in which the physical characteristics affecting
water quality are assumed constant.
Source Group - A group of effluent outfalls considered as a single source for
design purposes.
System Characteristics - The basic system attributes that must be described to
permit analysis of cost-effectiveness.
System Duration - The time over which the water quality surveillance system
will maintain a fixed configuration.
USGS - United States Geological Survey.
194
-------
SECTION XII
APPENDICES
CONTENTS
Appendices Page
A. Summary of RIBAM Mathematical Formulation 195
B. Development of Total System Effectiveness 197
C. Development of Full Form for Estimation of Capability 217
D. Effective Sampling Interval 223
E. Development of Computerized System Design Methods 227
F, Design Analysis Computer Programs 247
G. Computer Listings for Demonstration Candidates 315
195
-------
APPENDIX A
SUMMARY OF RIBAM MATHEMATICAL FORMULATION
The version of RIBAM used in the development and demonstration of the system
design methods is the original version developed for the Beaver River Basin
Modeling Project [7]. One aspect of the application of RIBAM to a river basin
is the assignment parameter code numbers to the water quality parameters
selected for modeling. The assignment is specific to the application and may
vary from basin to basin. The parameter code assignments for the Beaver
River Basin and used in the demonstration case are listed in Table 33. The
table also constitutes a list of the seventeen parameters modeled by RIBAM for
the Beaver River Basin.
In addition to the seventeen water quality constituents, RIBAM models the
following physical parameters:
1. Stream Flow in CFS
2. Stream Velocity in ft/sec
3. Time of Travel in days
4. Stream Depth in feet (computed only if dissolved oxygen is also com-
puted).
The analytical approach used in RIBAM remains as defined in the DOSAG
model [11]. The river basin is represented as a network consisting of four basic
components. These four components are:
1. junctions—the confluence between two streams within the river basin
being modeled
2. stretches—the length of river between junctions
197
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Table 33. WATER QUALITY PARAMETERS MODELED AND
CODE NUMBER ASSIGNMENTS
Parameter
Code Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Parameter
Name
Sulfates
Manganese
Iron
Total Nitrogen
Dissolved Solids
Lead
Chlorides
Phosphorous
Ammonia
Cyanides
Phenols
BOD
Coliforms
Nitrites
Nitrates
Chlorophyll A
Dissolved Oxygen
3. headwater stretches—the length of river from its headwater to its first
junction with another stream
4. reaches—the subunits that comprise a stretch (either headwater or
normal).
198
-------
Reach boundaries are defined by any unique combination of the physical char-
acteristics of the river basin, such as effluent sources, reaction rates or flow
regimes. As a result of this definition, effluent sources are considered to enter
the stream only at the upstream end, or head, of a reach.
To restrict the number of reaches, individual effluent sources are frequently
grouped together. This grouping of individual sources is done only when the
sources are in close proximity to each other. A more detailed discussion of
the grouping procedure is presented in [3], Sources are grouped together
according to the type of the source. Three source types have been identified:
1. tributary streams
2. municipal wastewater sources
3. industrial process water sources.
These types are based on the functional characteristics of the sources. Tribu-
tary streams and municipal wastewater sources are considered to add to the net
flow of the stream. Industrial sources are assumed to have no effect on the net
flow of the stream, since industrial process water is most frequently withdrawn
from the stream, then discharged back into the stream after use. Municipal
wastewater sources have been separated from tributary streams to facilitate
use of RIBAM in planning.
A fourth type of source has also been included in RIBAM, the unaccountable load.
In the initial stages of model testing it is frequently found that large discrep-
ancies exist between predicted and observed stream quality, possibly due to
weaknesses in the data on source concentrations. To provide the capability to
test agreement without adjusting any of the other three types of source data,
the 'Unaccountable" load is introduced. It is so called, because the pollution
199
-------
loads associated with this source-type cannot be accounted for in the initially
available data on known effluent sources. The unaccountable loads may be either
positive or negative. They are treated as no-flow mass additions or with-
drawals, not as concentrations. The necessity for inclusion of large unaccount-
able loads in any reach may be interpreted as an indication of very poor data for
that reach.
The mathematical approach used in computation of the water quality param-
eters in the basin is a "piecewise continuous" approach, in which the parameter
is assumed to behave according to a continuous differential equation throughout
a reach. This approach may be used because the definition of a reach assumes
that the important physical characteristics of the stream remain constant for the
length of the reach. The model, thus, requires that the relevant physical char-
acteristics of each reach of the stream be supplied as input data.
The mathematical models of stream quality are one-dimensional; they compute
the concentration profile along the length of the stream. The concentrations
are assumed to be uniform in depth and width.
The seventeen water quality parameters are grouped into three categories: 1)
conservative, 2) non-conservative, non-coupled and 3) non-conservative,
coupled. Each parameter within a given category obeys a general equation which
is characteristic of that category.
In the conservative parameter equation, the concentration, C, of a water quality
parameter is defined by:
f - ° <«)
the solution of which is:
C(t) = C° (46)
200
-------
where C° is the concentration of the parameter at the head of the reach (i.e. ,
at time equal to zero) and t is time.
The concentration at the head of the reach, C°, is determined by a mass balance
equation. The mass balance equation describes the ratio of the total mass of
the constituent entering the reach, both from the upstream reach and from all
sources at the head of the reach, to the total flow in the reach. The mass bal-
ance equation is :
where Q = stream flow entering from the upstream reach
s
Q = flow added by tributary streams
Q = flow added by municipal wastewater sources
^
Q * = flow passing through industrial sources
o
C = concentration of parameter entering from the upstream reach
8
C = concentration of parameter in tributary streams
C = concentration of parameter in municipal wastewater sources
£t
jfc
C = net change in concentration of parameter between intake and dis-
charge of industrial process water.
The asterisk is used to differentiate between the municipal/tributary-type
sources, which add to total stream flow, and the industrial -type sources, which
do not add to the total stream flow. The definitions above are carefully worded
to reflect this difference.
The conservative parameters, or those parameters whose concentrations are
assumed to be defined by the conservative parameter equation are:
201
-------
Sulfates
Manganese
Iron
Total Nitrogen
Dissolved Solids
Lead Chlorides
In the non-conservative, non-coupled parameter equation, the concentration of
a constituent is defined by:
dC
dt
= -KG (48)
where K is the reaction rate of the constituent. The solution to the equation is:
-Kt
C(t) = C°e (49)
In RIBAM, the following constituents are modeled by the non-conservative equa-
tion:
Phosphorous
Ammonia
Cyanides
Phenols
BOD
Coliforms
The non-conservative, coupled parameter equation has the characteristic of
coupling the constituent in concern with one or more other constituents. The
concentration of each of the following constituents is defined by a non-conserva-
tive, coupled equation:
202
-------
Nitrites
Nitrates
Chlorophyll A
Dissolved Oxygen
While a general equation can be written for non-conservative, coupled param-
eters, because they are coupled to different constituents, each parameter has
its own unique equation.
To simplify the presentation of these equations, a numerical subscript is
assigned to each water quality parameter. The subscript assignments corre-
spond to the code numbers used to represent each parameter in the computer
programming.
The symbols used in the equations below are:
C. = the concentration of parameter number i
K. = the reaction rate of parameter number i
K. . = the coupling coefficient between parameter number i and param-
1$ 3 eter number j
where i and j refer to the numbers in Table 33.
The nitrite parameter is assumed to be coupled to ammonia and is defined by
the following equation:
dC14
-dT=-K14C14+K9,UC9 (50)
The solution to the previous equation for nitrites is:
"V "V
C14(t)=(CU tA9,14)e -\14e
203
-------
where :
K9,14C9°
The nitrate parameter is assumed to be coupled to nitrites and is defined by
the following equation:
f«- K C .K C
dt 15 15 14,15 14 (52>
The solution to the previous equation for nitrates is:
W*U *S I*** *>>'-*! ! *~V-A e~V
15 15 9,15 14,15 14,15 9,15
where:
_"K14,15A9,14
Vl»(C14
~
Chlorphyll A is assumed to be coupled to phosphorous and nitrates. Its con-
centration is defined by the equation: ,
dC16
— =-K16C16+K8,16C8+K15,16C15 <54>
204
-------
The solution to the previous equation is:
C16
~
A A"0*
ft 1 C V V
7, Ib K - IS.
The dissolved oxygen deficit, D-,7> is assumed to be coupled to iron, ammonia,
BOD, nitrites, chlorophyll A and benthic oxygen demand. Its equation is:
= -K!7 °17 + A3 K3, 17 °3 ^\ll°9+ K14, 17 C14
205
-------
where D - change in benthic oxygen
B
K = reaeration coefficient
A ~ percent of total iron that is oxidizable
O
The solution to equation (12) is:
-K t -K t -K
-K t -K t -K t
15 12 16
-K t
where
A K C°
3 3,17 3
3,17
A _K12,17C12
_K16.17 (°16 +A15.16H'A14,16
-
. = "K16,17A15,16
1c: 17 K V
15,17 K - K
(57)
206
-------
K14, 17 (C14 + A9, 14> ' K16, 17 AU. 16
AU,17= K-K
K9.17C9 " A9.14K14,17'A9.16K9.16K16.17
VK!7
_"K16.17 A8.
8,17= K-K
b ' DB/K17
Dissolved oxygen concentration is determined by taking the difference between
saturated dissolved oxygen (C . ) and the dissolved oxygen deficit.
o A 1
The saturation dissolved oxygen is estimated with the following equation t
2
C = (14.62 - (0.3898*T) + (0.006060*T )
SAT
- <0.00005897*T3))* (59)
((1. - (0.00000697*E))5'67)
where T = reach temperature (°C)
E = mean basin elevation (feet above sea level)
The reaeration coefficient, K , may either be assumed to remain constant for
all flow regimes, or it may be computed by one of two methods.
207
-------
T.ie first method assumes:
B
A*V
K17 = -C- <60>
where V = the stream velocity
D = the stream depth
and A, B, and C are constants that must be obtained for each reach by statistical
methods from observational data. The stream velocity may, in turn, be esti-
mated using the equation
V - a*Qb (61)
where Q = the stream flow
a,b = constants estimated by statistical methods from observational data
for each reach
The depth, D, may either be provided by the user from hydrographic data or it
may be estimated by the equation:
D=c*Q (62)
where Q = the stream flow
c,d = constants estimated by statistical methods from observational data
for each reach
The second method for estimation of the reaeration coefficient assumes that:
K1?= **QP (63)
ws.ere Q = stream flow
and the two constants, a and p, are estimated statistically for each reach of the
basin.
208
-------
The value of the reaeration coefficient, no matter which method is used, is
determined for a temperature of 20° C. The value is adjusted for temperature
dependency according to the equation:
rr -
K (T) = K (20°C)*1.0159V (64)
where T = the reach temperature (°C).
Another physical process that affects the dissolved oxygen deficit is the turbulent
mixing as the water flows over a dam. The change in the dissolved oxygen
deficit, D, as the stream flows over a dam is computed according to the follow-
ing equation:
D
u
°D = 1.0 +0.11*(1.0 + 0.046T)h (65)
where D - dissolved oxygen deficit below dam
D = dissolved oxygen deficit above dam
T = temperature of reach where dam is located (°C)
h = height of dam (feet)
The value of each parameter is computed for any point in a reach by evaluating
the appropriate equation for the time of travel from the head of the reach to the
point. Time of travel is computed by the usual time-rate-distance equation:
t = i (66)
where x = the distance downstream from the head of the reach.
The major restriction of the mathematical models is in the consideration of
deep impoundments. The mathematical models are so-called one -dimensional
209
-------
models and are restricted to cases in which the concentration profiles along the
depth and width dimensions can be considered uniform. Clearly, deep impound-
ments such as deep reservoirs violate these conditions because of the vertical
stratification in such reservoirs. RIBAM may not be used to simulate water
quality in a deep impoundment. It may, however, be used to simulate a basin
containing impoundments of sufficiently shallow depth that they are essentially
one-dimensional. In the latter case, the effect of dam spillways on reaeration
is included in the model.
Non-conservative, coupled parameters can be simulated only under the restric-
tion that the reaction rates of coupled parameters are not equal. The restriction
are due to the nature of the solutions of the particular equations describing each
non-conservative, coupled parameter. A list of the restrictions is presented
in Table 34.
Table 34. LIMITATIONS ON REACTION RATES OF COUPLED PARAMETERS
Non-conservative, Coupled
Parameter
Nitrites
Nitrates
Chlorophyll A
Dissolved Oxygen
Reaction Rates that
Cannot be Equal
K9 ' K14
K9 ' K15,
K9 ' K16,
K8 ' K16
K3 * K17. K16
K12 ' K!7, K15
K
17, !4
K17. K9
K
K
!7,
17
210
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APPENDIX B
DEVELOPMENT OF TOTAL SYSTEM EFFECTIVENESS
For the design of river basin water quality surveillance systems, the total sys-
tem effectiveness is defined as the ratio of the expected number of detections of
violations to the expected number of violations. More precisely, E is
sys
defined as:
Expected number of independent violations to be
_ detected by the system over the system duration
sys Expected number of independent violations
in the basin over the system duration
The conceptual bases for the definition are discussed in Section VI.
Implicit in the definition are two assumptions. First, all violations are equally
weighted, regardless of which water quality parameter is causing the violation.
Second, all violations are equally weighted, regardless of the location of the
violation. These assumptions are justified by the analysis of stream water
quality standards presented in [3]. The stream standards are considered to be
society's judgment of the importance of each parameter in each reach of the
basin. The quantitative value of the standard for each parameter in each reach
constitutes sufficient weighting of the design analysis to reflect this judgment.
In order to develop a mathematical formulation for the definition of total system
effectiveness, consider a simple river basin. It consists of one river with no
tributaries. To aid in the mathematical formulation, the segments are numbered
in sequence beginning with the headwaters. Similarly, each monitoring station
is numbered in another sequence beginning with the most upstream station. For
each parameter, there is only one monitoring station per reach.
211
-------
The denominator of equation (67) can readily be expressed by counting the
expected number of independent violations that come into existence in each seg-
ment. The resulting mathematical formulation is adequately described in Sec-
tion VI. It is
nv (i' j) (68)
where i = the segment index number
j = the parameter index number
I = the maximum i
J = the maximum j
**
n (i, j) = the expected number of type 2 violations of parameter j in
segment i.
An expression for the numerator of equation (67) is much more complex. For
each violation of parameter j that occurs in the k monitored segment, L , the
numerator must include:
1. the possibility that the violation may or may not be detected in segment
2. the spatial extent of the violation, and
3. the possibility that the violation may or may not be detected at any other
monitored segment in which it exists.
By ennumerating these conditions from the headwaters to the month, it is
possible to limit consideration of each of these factors to the portion of the
basin upstream of each segment. The resulting expression is
212
-------
J
s
H
K
D PDIV(V
k=l
£=1
V-
k-1
(69)
where j - the parameter index number
k - the monitoring station index number
f~V\
i = the segment containing the k monitoring station
£, m = dummy indices identical to k
P (L , j) = the probability of detecting each violation of parameter
j that occurs in segment i
1C
N(i , j; i. , L) = the expected number of violations of parameter j that
occur in segment i^ and that begin upstream of or in
segment i., but downstream of segment L .
The term "begin" above refers to the upstream boundary of the violation, as
described in Section VI.
To understand expression (69) fully, a term-by-term examination of the expression
is necessary. If only one parameter is considered, the equation can be rewritten
in simplified form:
K
k-1
The term:
N(ik;
k-1
m-
(70)
N(ik; iM, V
(71)
213
-------
is the total expected number of violations that occur in monitored segment L .
Because of the segment numbering scheme, they must begin in the interval
[l < i < i ]. If there is an upstream monitoring station (L ), those violations
K K"" J.
that begin upstream of L may be detected at L . Similarly, if there are two
monitoring stations upstream of L (L and L ), violations that begin upstream
of L may be caught at either i or L . Since the objective is to count as
detections in i only those violations not detected elsewhere, the expected num-
K
ber of undetected violations in L that begin in the interval (L , i ) is:
Nvw w
(72)
Similarly, the expected number of undetected violations in i that begin upstream
it
°f 1S:
N(ik; W W
(73)
Thus:
g N V '„• V
k-1
n
(74)
is the expected number of previously undetected violations that occur in segment
L . Of those, the expected number that are detected in L is:
k
2=1
k-1
n
(75)
Finally, the total number of independent violations of the parameter under con-
sideration throughout the basin is the sum over k given by expression (70).
214
-------
Implicit in this development is the assumption that pn|V is independent of the
violation, that is, PD]V is the average probability of detection. This probability
could be defined as the effectiveness of the system element E(L , j).
The estimation of expression (69) in the context of system design is a difficult task
and simplification is desirable. The desired simplification can be achieved if
either of two conditions apply:
1. N, j; i§ i small for £
This form (expression (77)) can be compared with equation (16) where:
(78)
Thus, the approximate form of the total system effectiveness is (equation (15)):
K J
a. J)
1=1 =i
215
-------
The approximation holds for sparse monitoring networks in which condition (1)
is most likely to apply. It is clear that assumption of such conditions for the
demonstration case described in Section VIII is valid and it is anticipated that the
assumption is generally valid. However, the system designer must be aware of
the assumption in the evaluation of his design analysis.
216
-------
APPENDIX C
DEVELOPMENT OF FULL FORM FOR ESTIMATION OF CAPABILITY
i
As indicated in Section VI, a more elegant mathematical approach to the estima-
tion of capability than that used by the design method is available. It is based on
a direct application of the equation for expected number of detections developed
in [3], rather than the indirect approach described in Section VI. Unfortunately,
the estimation of some of the independent variables from the available data pre-
sents difficulties. The more elegant approach is presented here for complete-
ness and for guidance, should a system designer prefer to implement a less
approximate method for computing capability.
As developed in [3], the expected number of violations sampled, n , can be com
s
puted with the equation:
(80)
where A = the sampling interval
T = the expected duration of a violation
T = the expected interval between violations.
0
All of the factors affecting system capability can be directly incorporated in
equation (80) by suitably defining the independent variables: A, T and T . The
effect of routine maintenance can be included in the same manner as in Section
VI, through use of an effective sampling interval, A . The effects of sampling
location and random analysis errors can be incorporated through computation of
T 's and T 's corresponding to the violation process as viewed by the surveil-
lance system. These new variables are characteristic of the violations liable to
be detected and are designated: T and T .
217
n — ~
s
L
T T
0 1
/ 2 T 2\
-------
Thus, given that the system has survived and is available, the expected number
of detections can be estimated as:
n *{x, A , e, a | a, s)
d e « ~
-A
e
(81)
The development of an estimate for A is described in Appendix D. The remain-
der of this appendix is directed at the problematical T and T estimates.
In order to develop the approach to estimating T and T , consider the process
under surveillance, as viewed by whatever device or person makes the no-viola-
tion-violation decision. It consists of the true value of concentration at the loca-
tion of sampling, C(x), and a random observational error, t. Thus, the observed
value, C'(x), is:
C'(x) = C(x) + i (82)
As developed in Section VI, a violation is considered to have occurred whenever
the observed value exceeds the threshold value, C . That is:
T
C(x) > C - £ —*- violation (83)
d d
Inequality (83) implies that T, and T are found in the same way as T and T
10 1 0
in [3], except that the location is x, rather than x (the preferred location) and
m
the effective threshold is (C - « ), rather than C .
It is clear that (C - (_) is a random variable, since the random error e_ is never
known precisely. An assumption of this method, however, is that the mean, ? ,
and standard duration, o- , are known reasonably well. If p(« |? , o-^ ) is the
218
-------
probability density function of ±, given T and (87)
219
-------
where the functional form, f(-), is derived from the relationship between C and
Q.
Thus, the integral in equation (84) can be replaced by:
T. = T.(x, 6 , o-6)=
-00
where C^L is the random threshold flow. The relationship between T. and Q' at
locations x can be developed empirically from the USGS data by examining the
flow record for a number of Q 's and fitting an appropriate curve. It is then
necessary to perform a numerical integration to evaluate equation (88). An
alternative is to assume an integrable form for T. (x, CLJ, such as an exponen-
tial, and evaluate the equation analytically. If, for example, it is assumed that:
T. (x, Q^) = a. exp [b. Q^ (89)
then
- d
T. = a. exp
(90)
where Q is the flow threshold corresponding to C .
Neither of these two approaches is particularly satisfactory in the present con-
text. Numerical integration of general equations presents difficulties that far
outway its usefulness for system design. Yet, it is difficult to find an integrable
form for T. (x, Q ) that is sufficiently descriptive of the actual data over the
broad range of possible values. For example, the exponential cited above is a
very poor approximation for low flow conditions.
220
-------
It is for these reasons that the more pragmatic formulation described in Section
VI is preferred over the formulation presented in this appendix.
221
-------
APPENDIX D
EFFECTIVE SAMPLING INTERVAL
In the development of the water quality surveillance system design methodology,
it is assumed that the system is a sampled system. That assumption appears
valid for a large number of expected cases, ranging from the fully-manned sur-
veillance system taking monthly or weekly samples, to the fully automated sys-
tem transmitting samples to a central station on an hourly schedule.
As is done in [3], sampled data systems taking essentially instantaneous observa-
tions can be characterized by the interval between samples, A. It is assumed
in [3] that the sampling scheme is a periodic function, with any random error
in the timing of the sample considered negligibly small in comparison with the
period. That assumption seems to characterize the majority of routine sampling
schedules that may be expected.
The measure of sampling effectiveness developed in [3] is based on an assumed
regular sampling scheme, with sampling interval A .
However, it can be seen from an examination of the development of the measure
that it holds, at least approximately, for a random sampling process with an
effective sampling interval equal to the mean sampling interval,A = A. It is
e
only approximately true, since the artifice by which multiple detections are
eliminated no longer holds exactly. If a random sample replaces a periodic sam-
ple, some violations that would otherwise be detected once are detected more
than once and others not at all. On the average the total number of detections is
the same, although they are no longer all independent detections. The approxima-
tion improves as the variance of the sampling interval approaches 0.
223
-------
In the present development, the effect of routine maintenance must be incorpor-
ated in the computation of system effectiveness.
As shown in Figure 66, the routine maintenance process modulates the periodic
sampling process. There are two cases possible. In the first, the next sample
following the maintenance downtime is taken as if the sampling sequence had
never been interrupted. In the second, the next sample immediately follows the
return to service and the sampling sequence is reset to that time. Clearly, the
two cases merge when T + T = nA, any integer multiple of A.
The resulting sampling process can be thought of as an approximately random
sample, for system design purposes. It has a mean sample interval and a well
defined variance, when a long enough time period is considered. For typical
routine maintenance in which T^> >Td, the variance is small and the measure
of sampling effectiveness developed in [3] is approximately true.
The computation of that measure then depends on an estimate of the effective
sampling interval under routine maintenance conditons. Examination of Figure
66 leads to the following formula for estimating A in each case.
6
The expected number of samples that are taken during the operating period (N )
u
is the truncated (integer) value of the quotient:
/T
N = mt I -
u y A
Similarly, the expected number of samples that would have been taken during
the maintenance period (N,) is:
d
02)
224
-------
ROUTINE
MAINTENANCE
PROCESS
ON
OFF
1
SAMPLE
SAMPLING PROCESS
WITHOUT MAI NT.
SAMPLING PROCESS SAMPLE
WITH MAI NT.
(CASE 1)
TIME
TIME
TIME
SAMPLING PROCESS
WITH MAINT.
(CASE 2)
SAMPLE
TIME
Figure 66. Effect of Routine Maintenance on Periodic Sampling
225
-------
The new sampling interval during the maintenance period (A ,) is, for case 1:
Ad = (Nd + 1)A (93>
The sample interval during the operating period is still A, the effective, or
average, sampling interval (A ) for case 1 is:
c
Ae = N-TT (*d + V> <94>
u
N + 1
u
For case 2 theA is computed according to the equation:
' d
AJ = N A + ( T - N A ) (95)
d d u u '
giving the effective sampling interval of
Ae = rrr ^d + NuA > w
u
N, A 4- (T - N A) +N A
d a u u
N + 1
u
N A+ T
_d _ u_
N + 1
u
It is assumed that the system designer will ordinarily plan maintenance to fall
between sample times when T,
-------
APPENDIX E
DEVELOPMENT OF COMPUTERIZED SYSTEM DESIGN METHODS
The development of the computational procedures for the design of water qual-
ity surveillance systems is based on the theoretical developments of Section VI
and [3], and on the total design method outlined in Section VII. For the most
part» it requires straight forward computer programming of the mathematical
formulation. In some cases, it requires the use of approximations, the adapta-
tion of existing programming and the development of special mechanisms for
handling aspects of the problem.
The objective of this appendix is to provide an understanding of the nature and
content of the design programs presented in detail in Appendix F. Toward this
end, specific highlights are described in detail. These highlights are selected
for discussion because they do not necessarily derive directly from the theore-
tical base of the design method.
SELECTION OF BASIN MODEL
As anticipated in Section IV, the necessary description of the natural system used
in the evaluation of surveillance system design is provided by a computerized
mathematical river basin planning model. The model used is the River BAsin
Model (RIBAM) developed by Raytheon OES for the Environmental Protection
Agency [7]. Selection of RIBAM for use in this project is based on more than
the coincidence of authorship, although that is a factor in the choice.
The essential criteria in the choice of a river basin model for use in surveillance
system design are:
1. The computerized model must be of the same type as the manual model
used in the initial development of the design methods (i.e., steady-state,
227
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one-dimensional, capable of handling conservative, non-conservative
non-coupled, and non-conservative coupled parameters.
2. That it be available for general application through the EPA when the
design methods were published.
3. That it be available to the design methods project at the required point
in time.
At the time the present project was begun a number of EPA water quality models
existed. They included the DOSAG [11], QUAL-I [21,22], RECEIV portion of the
Storm Water Management Model [23], RESERVOIR [24,25], PLUME [26], and
DEM [27] models.
In addition, each of the foregoing models has been undergoing adaptation and
expansion for use in the various basins being modeled under EPA's River Basin
Planning Models Program, of which the Beaver River Basin Model Project
is only one segment [7]. These changes include, in general, expansion to
include additional parameters and modification to incorporate more complex
coupling of non-conservative parameters. As discussed in Section IV, the RIBAM
model resulted from such modification and adaptation of the DOSAG model, for
use by Raytheon OES in the Beaver River Project. Other such improved ver-
sions have not been available to the design methods project, since the work has
been in process by other EPA contractors.
Choice of RIBAM is based on an elimination process. PLUME was not directly
relevant to the processes to be modeled, since it models only the near-field of
an outfall. RESERVOIR and DEM are two-dimensional models, not one-dimen-
sional. RECEIV and QUAL-I are dynamic models, not steady state. RIBAM is
selected over DOSAG, (also a one-dimensional, steady-state model) because it
is more general in the parameter coverage and the mathematical treatment.
228
-------
As it is used in the design methods programs, RIBAM is computationally identi-
cal to the stand-alone version used for basin planning. The main program por-
tion of RIBAM has been converted to subroutine form and adapted to the design
procedure. All printed output from the RIBAM computations has been elimi-
nated, since it is assumed that the user will have calibrated the model using the
stand-alone version, as described in the Beaver River Project Documentation
Report [7]. The stand-alone version requires the preparation of two sets of
input data cards, the Program Control Deck and the Standard Data Deck. As
used in the design methods program, the Standard Data Deck is retained intact.
The necessary information from the Program Control Deck has been combined
with other information on the "CONTROL" card in the design methods data deck.
PROGRAM DETAILS
With the overall understanding of the programs provided by Section VII, it is
possible to highlight the more important details of the programming. The objec-
tive of the following paragraphs is to describe the implementation of the concepts
developed in Section VIIand [3].
Estimation of n * and n **
S V
As detailed in Section VI, the computation of n * and n ** depend on the estima-
s v
tion of the expected durations T * T * T ** and T **.
The estimation approach used in the development of the design analysis programs
is the same as that used in [3].
It is assumed that, at the macroscopic scales under consideration, the statis-
tical variability of the water quality is due primarily to variability of the stream
flow. The estimation approach, thus, calls for translation of the water quality
threshold specified by the stream standards into thresholds on stream flow. It
229
-------
is also assumed that the stream flow in the basin is statistically stationary over
the period of the USGS gaging records for the basin. Comparison of the flow
thresholds with the USGS data then allows the accumulation of statistics on T
and T 's.
Thus, the computation of n * and n ** for each system element may be sepa-
S V
rated into three steps: 1) the computation of a threshold flow, Q , for each
system element, 2) the analysis of the USGS data for the T 's and T 's, and
3) use of the T 's and T 's to compute the n * and n ** values.
0 1 s v
Estimation of Threshold Flows —
The approach used to compute the threshold flows in Subroutine QTCAL is an
indirect, estimation approach. In general, it is not possible to solve explicitly
the equations relating concentration of a water quality parameter to physical
factors in the stream such as stream flow. Thus, one cannot straightforwardly
solve for the threshold flow Q , by substitution of the water quality standards
threshold, C , into the concentration equations.
Instead, the concentration of the water quality parameter is computed for five
values of stream flow. The five values are computed by QTCAL by applying
scaling factors to the standard flow values specified in the RIBAM Standard Data
Deck. The selection of the scaling factors is done once for the entire basin and
provided as input data to Subroutine RFC. In selecting the scaling factor, the
designer will attempt to assure that the range of flows is sufficient to cause the
computed concentrations to bracket the C 's for most parameters. The designer
must also be careful not to specify a scaling factor that will "dry up" the river
that is, not provide sufficient flow to maintain the expected river uses specified
in the RIBAM Standard Data Deck.
230
-------
Using the five computed points, a C versus Q curve is fit by the ICSSMU subroutine.
That subroutine performs a cubic spline curve fit. That is, it computes the
coefficients of five cubic equations for curves joining the points, such that the
weighted average difference in slopes at the points is a minimum (see Figure 67).
Mathematically, this is approximately equivalent to the curve fit that would be
achieved by a draftsman using a supple wooden or metal strip - a spline - to
draw a curve through the points. The cubic spline approach was selected
because it forces the resulting curves to go through the points being fitted. This
is in contrast to other types of curve fitting, such as least squares, in which the
resulting curve may or may not pass through the points.
A value for Q may then be computed by interpolation, using the cubic equation
appropriate to the range of values containing C . Clearly, this process must be
70
34 5676
STREAM FLOW lt02CFS>
10 II
Figure 67. Concentration vs Flow Curve Fitting (Boxed Numbers
Indicate Data Points and Circled Numbers Indicated Associated Curves)
231
-------
repeated for each reach of the basin for each parameter included in the system
design.
Estimation of the Expected Durations—
Using the Q 's, the USGS gaging station records for the basin may then be
examined for periods falling above and below the threshold. While this is a
relatively straightforward process, two factors have been carefully included
in Subroutine EXPDUR.
The first is the relationship between the basin reaches and the network of USGS
gaging stations. Typically, there are many fewer stations than there are
reaches. In the preparation of the RIBAM Standard Data Deck, the system
designer will have selected the gaging station most representative of each reach
and determined the relationship between the flow at the station and the flow at
the reach. The reach-station relationship is applied to the Q _'s, which are
then compared directly with the gaging station data.
The second is the identification of violations that fit into the "single-star" or
"double-star" categories, as defined in Section VI.
For the case of the "double-star" violation, the key property is the continuity
of the violation into the next upstream reach of the stream. For non-coupled
parameters, a reach is said to contain a "double-star" violation if the head of
the reach is in violation state but the end of the upstream reach is not in viola-
tion (see Figure 68). For the case of coupled parameters, the condition is
satisfied if: 1) a violation exists at the worst point in the reach, 2) a violation
exists at the best point in the reach upstream of the worst point, and 3) if a
violation does not exist at the best point in the next upstream reach that is
downstream of the worst point in the upstream reach (see Figure 69). if the
reach is a headwater reach, existence of a violation qualifies as a "double-star"
232
-------
VIOLATION
CONCENTRATION
NTE THRESHOLD
DOWNSTREAM
Figure 68. "Double Star" Violation of a Non-coupled Parameter
BEST POINT UPSTREAM
CONCENTRATION
VIOLATION
NTETHRESHOLD
BEST POINT DOWNSTREAM
REACH 1
REACH 2
DOWNSTREAM
DISTANCE
Figure 69. "Double Star" Violation of a Coupled Parameter
violation. If the reach is below a junction, the conditions must hold in both up-
stream segments to satisfy the definitions of a "double-star" violation.
233
-------
For the case of a "single-star" violation, the key property is the continuity of
the violation from the reach containing the proposed station to the next upstream
reach containing a proposed station. In this case, any violation that is continu-
ous from the reach under consideration to any upstream reach containing a
station fails to satisfy the conditions on a "single-star" violation. In the case
of stations above and below one or more junctions, detection of the violation
on any one of the upstream branches constitutes a failure to satisfy the condi-
tions. For coupled parameters, the existence of a violation must be tested at
best and worst points of each upstream reach to establish continuity of the vio-
lation (see Figure 70).
Clearly, the computation of the T * and T * requires continual searching of
upstream segments. Because the reach numbering scheme is entirely arbitrary
when the RIBAM Standard Data Deck is prepared, the search would require
continual referencing of the arrays describing the basin topology. In preference
to such time-consuming referencing, Subroutine EXPDUR performs the topology
mapping only once. It sets up an array of masks that indicate the upstream
reaches that must be checked for the identification of "single-star" violation.
The subroutine first checks each reach in the basin for its violation state and
then overlays the masks to determine those reaches with "single-star" viola-
tions. It should be noted that use of this masking technique limits the number
of stream reaches that may be modelled to the number of bits per word of
memory in the computer used. The user may remove this limitation for any
specific machine by implementing a multi-word masking approach. The original
programming was performed on the 60-bit/word CDC 6700, so no hinderance
was encountered. A smaller machine, such as an IBM 360 (32 bits/word)
would be so limited.
234
-------
STATION
REACH 6 x\ 7^ REACH 4
REACH 5 -V- REACH 3
REACH 2
STATION ® REACH 1
STREAM STICK DIAGRAM
C
CT-
CASE 1 :
"SINGLE-STAR
VIOLATION
NTE CT
CASE 2:
"SINGLE-STAR"
VIOLATION
H—r—*•
Figure 70. Typical "Single Star" Violation Conditions
235
-------
Computation of n ** and n *—
_ v _ s_
The final computation of n ** (Subroutine COMPT) and n * (Subroutine CAPBLE)
is performed in a straightforward way using the equations presented in Section
VI, equations (21) and (33). The computation of the adjusted sampling interval,
A , is done according to equation (34) or (35), as appropriate.
e
Estimation of Survivability
As is concluded in Section VI, the basic steps in the estimation of survivability
of a system element are:
1. preparation of the transition matrix, S
2. determination of the acceptable failure states
3. computation of the P (t) from the transition matrix
\
4. computation of survivability, S, from the P (t).
K
A feature of the estimation process is the use of the Laplace transform to
obtain the desired probabilities:
P(s) = P(o) (si- B)"1 (97)
Pn(t) = (Pn(s)) (98)
Implementation of the survivability estimation process for automatic computa-
tion presents an immediate problem. In general, a Laplace transform is log-
ical or mathematical in nature, rather than arithmetical. Automatic digital
computers could be programmed to perform the necessary logical manipulations
required for a general Laplace transform, but the program necessary to do so
236
-------
would be excessively large and complex. It is preferable to confine use of the
computer to arithmetic processes, whenever possible.
Thus, it is of interest to develop a general algorithm for the computation of
p (t) that does not require actual manipulation of the Laplace transform. The
n
requirement for such an algorithm is that P (s) always have the same general
mathematical form. That, in turn, requires that the survivability matrix be
formed in a consistent manner each time it is prepared.
The following paragraphs present the development of the general algorithm used
in the computation of survivability. The objective of the development is a
procedure that meets the limitations imposed by the computer, as discussed
above.
Transition Matrix—
The first step in the procedure is the preparation of the transition matrix, §,
so that it has a consistent form, no matter how many means are included in the
system element, nor what their configuration is.
Such a transition matrix can be generated, if the state numbers are assigned
according to a binary scheme. Each means in the system element is identified
with a binary place tn a binary number that represents the system state number.
Failure of the means is associated with a "1" in the corresponding binary place;
operating status is associated with a "0". Figure 71 illustrates the assignment
of state number for a three means system element. The identification of each
means with a binary place is entirely arbitrary, but remains fixed, once done,
for each system element. In the case illustrated, means B corresponds to
0 1 2
2 =1, means A to 2 =2, and means C to 2 =
have both failed, the assigned state number is:
0 1 2
2 =1, means A to 2 =2, and means C to 2 =4. Thus, when means A and B
237
-------
s. y1
Nr
/V
' >
^
1
- A
V
/
V
f
/
s
^
/
^
s
^
X
^
r
\
/
\
/
s
>
/
s
D
V/
A,
c
v
A
B
V
/
\
/
-
s
s
\
J
3
-
-- '-"""
c
22=4
n
o
o
o
1
1
A
* =2
o
o
1
1
0
1
1
B
2°=1
o
I
o
I
I
I
= 0
= I
= 2
= 3
- A
= 5
- fi
__
= 7
Figure 71. Assignment of Binary State Number
238
-------
210
(0x2 ) + (lx2 ) + (1 x 2 ) = 3 (99)
Use of such a state number assignment scheme assures that the transition
matrix will have the form illustrated in Figure 72 for the case of up to four
means in the system element. The numbers shown as the matrix elements
indicate the binary place corresponding to the failed means that causes a
transition from the row state to the column state. The diagonal elements are
not shown, for simplicity (see Figure 25). Thus, for example, in the three
means case shown in Figure 71 the transition from system state 3 to state 7
2
corresponds to failure of the means assigned to 2 , or means C. In generating
the transition matrix for the example system, the failure rate x would be
c
inserted in the matrix element S . The example given in Section VI (Figures
3,7
24 and 25) illustrates such a three means case. In that example, the correspon-
dence is:
2 = means A
2 = means B
2
2 = means C
and the transition from state 3 to state 7 is related again to \ .
c
As can be seen in Figure 72, a regular and predictable pattern is developed in
the transition matrix when the binary scheme is used in assignment of state
numbers to system states. The reader can readily convince himself that the
pattern recurs for any number of means.
239
-------
4 MEANS
3 MEANS
JL
2 MEANS
0
I
2_
3
4
5
6
7
e~
9
10
1 2
1 0 | 1 |
3
1
0
4
2
5
2
°
6
2
'
7 I
1
1
2
1
0
9 10 II 12 13 14 15
0 I
i
0
12
13
14
IS
j
Figure 72. Recursive Pattern in Transition Matrix
240
-------
State Probabilities—
Skipping over the determination of acceptable states, for the moment, the next
step is computation of values for P (t), when t equals the system duration. The
direct solution of equation (97) requires the logical manipulation of the Laplace
transform and is to be avoided in the computer programming. An alternative
approach may be developed from a method presented in [13]. It is shown ther
that the vector of time derivatives of probability (P1 (t)) can be formed by:
P'(t) = P(t) (S-J) (100)
where I is the identity matrix and P(t) is as defined in Section VI. Equation (100)
represents a set of linear differential equations for which a general solution can
be found using Laplace transforms. Since the solution itself is general and can
be evaluated arithmetically without resort to the Laplace transform, the desired
result is achieved. The general solution is:
P (t) = e + C e (101)
-
-S t
where: T, refers to the coefficient of the e term for the P (t)
km k
equation, the summations are only performed for (n - 1) >0, and C is a
nn
complicated expression not readily stated in general mathematical form. For
the case of three means, it would be:
(102)
C-
nn
n- 1 S
V~"> an
2~t S -S
a = 0 aa nn
a - 1
E
Sba
bb nn
241
-------
For the case of four means, it becomes:
n - 1
C =
nn
an
a - 1
S -S
aa nn
cb
S -S
cc nn
ba
S -S
bb nn
dc
S —S
dd nn
(103)
And so on for each additional means. It should be noted that this general result
is dependent on the organizational form of the survivability matrix as described
above.
Computer evaluation of the general solution for probability of survival, P (t), is
n
achieved through use of a search algorithm, rather than through a direct arithmetic
approach. The search approach permits development of a computer subroutine that
is capable of handling any number of means in a system element. A direct arithmetic
approach would limit the program to a selected number of means or range of num-
bers, due to the form of the coefficient C .
nn
The search algorithm flowchart is shown in Figure 73. The operation of the
algorithm can be illustrated for C in the case of 3 elemental means as shown
in Figure 74. For that case, C is:
67
46
04
r =
77 S -S S -S S -S
66 77 44 77 00 77
67
26
02
s -s
60 77
S57
SQ
~"O
55 77
S -S
22 00
S45
S44 "S77
s -s
00 77
S04
S00 ~S77
(Cont.)
242
-------
ADD INTERMeO. PRODUCT
FOR CURRENT UVEl
TO LAST COEFFICIENT
FOBCUSREfirsrUTE
IC_-EQUATION (Mil
Figure 73. Flowchart of Search Algorithm
243
-------
X
TERM1
TERM 2
TERM 3
TERM 4
TERM 5
TERM 6
Figure 74. Example of Survivability Computation
244
-------
s
57
B *™o
55 77
S37
s -s
33 77
S37
S15
Sll -S79
S23
S -S
22 77
S13
soi
S -S
00 77
S02
s -s
00 77
soi
S33"S77 Sll"S77 S00"S77
The expression for C can be formed by generating the products and quotients
from the matrix elements as suggested by Figure 74. The remaining terms in
the expression for P (t) are generated from the previous coefficients as sug-
gested by equation (101).
Computation of Survivability—
The survivability (S) is computed by summing the P provided by equation (101)
for all the acceptable states. Acceptability of a state is determined by a direct
check for continuity of information flow under the state of failure specified by
the binary state number. For convenience, the acceptability check is performed
in Subroutine SETUP at the time that the state numbering is established.
Estimation of Availability
The similarity between computation of survivability and availability should be
clear from the discussion in Section VI. Due to that similarity, the same
approach may be used in setting up both transition matrices. The system means
are identified with the binary places composing the state number, and matrix
elements are equated with mean times to fail or repair as appropriate. The
solution of the linear algebraic equations (equation (28) and (29)) may be per-
245
-------
formed numerically using a procedure such as gaussian elimination. In order
to accomodate gaussian elimination, the availability matrix must be in trans-
posed form. That is, the "to-states" must be the rows and the "from-states"
must be the columns. Since no other application of the availability transition
matrix is made, the computer programming (Subroutine SETUP) automatically
generates A in the transposed format. The identity, equation (29), replaces the
last row of the matrix, prior to application of the gaussian technique.
246
-------
APPENDIX F
DESIGN ANALYSIS COMPUTER PROGRAMS
The program flowcharts and program listings for the design analysis computer
programs are presented in this appendix. Only those programs and sub-programs
specific to the design analysis are flowcharted. The appendix does contain the
complete program listing, including the RIBAM subroutines. Detailed informa-
tion on the RIBAM subroutines may be found in [7]. Section VII and Appendix E
of this report contains a discussion of the development and underlying principles
of these programs.
The programs listed in this appendix are written in FORTRAN IV, for use on the
CDC 6700. They have been compiled under the CDC RUN 76 compiler and run
under the KRONOS 2. 0 operating system (version 12), as supported by the Ray-
theon Scientific Computer Center, Bedford, Massachusetts. The original card
decks are punched in BCDIC.
With the exception of the GST APE subroutine, the reader is referred to Section
VII and Appendix E for textual material on these programs.
247
-------
PROGRAM MAIN
PROGRAM MAIN ( INPUT, OUTPUT, TAPE5=lNPUT ,T Ap£6=OUTPUT tTAPE2>
COMMON CAP<40»20)»VIOLSS(40.20)f NVAP(?0), IMPL<40), IREAD<20)»
» MTTFAI300.2) • MTTFS1300.2) , MTTRA ( 300 , 2) , LISTI4), COST<4),
» MEMBERU00.2) . CSTINC1100.2) » SUATA(IO). NOATA(IO), MSYS(10»23),
» NSAC<64), MINC<5), MPATHI5), MEMb(lo). NsTATE(5)» PFAILUO).
» PCHK(IO). NTRANS<5), LEVEL(lO), Tt«ANM64,64) , AVAIL<40>
COMMON COEF(6^f»6A)» SRV(4&)t PHOO(65)t PROB(65)f NSTI64),
» NSFR(64), EFF ( 40 ) t DUMMY (3425)
COMMON/BLOCK!/ NR« FINLt IA» II» IOPT» JA, JJ, JO. JU» JXt JY.
» JZt NJ» NPAR» IRON* NUM. QUP. NZt NT» NSrAS, TA. AACUP»BBCUP»
»CCUPl.CCUP2»CCUP3«CCUP4,CCUP5.CCUP6,CCtlP7, CCRON* A3t ORENTH.
* ELEVf CSATf VALMIS. MON. NYEAR* CACT. KK. NI, NINIT. NOX» M2»
* MY* MZY» NJUNC. NTTRIB. N»EA» NACC. DEMOM, ESYS, TOTCST. CHECK
COMMON/BLK/MASK(40)
DATA (MASK(I) .1 = 1 .40 )/OOOOOOlH» 000000?^. OOOOOOtB. 00000 1 OB » 000 0020
*B»00000408»0000100H,0000?OOH»U00040(MiOOOlOOlH ,0002000fl »
*0400000H» 100000 OB, ?000000^.4000000B, 1 OOOoOOOH. ?000000 OR.
»*OOOOOOOB.100000000R.-?OOOOOOOOH,"*OOOOOOOOR. 1 000000 OOOH, 2000000000
»8. 40000000 OOHilOOOOOOOOOOH, 20 UOOOOOOOOR.tOOOOOOOOOOrt. 100000000 OOOB
». 2000000 00 OOO^i. ^00000 OOOOOO^i* lOOUOOOOOOOOOrt. 20 000000000004,
*4000000000 000 ^.10000000 0000 00-1/
COMMON/riLOCK5?/TIMe»NMH.OTYPf.,POPT
LOGICAL MASK.OTYPE
K»I=5
N)=6 30
CALL RPC
CALL «SDD
DENOM=0.0
00 300 JU = l.NPAR
MUM = MVAR(JU)
IF (IREAD(NUM) .EQ.l) GO TO 200
CALL RCHAR
200 CALL QTCAL
IF (IREAD(NUM).EO.l) GO TO 300
CALL EXPDUR
CALL COMPT
IF (.NOT.OTYPE) GO TO 500
CALL PPDES
GO TO 300
500 CALL CAPBLE
300 CONTINUE
IF (DTYPE) GO TO 600
CALL RMTTF
DO 2 I = l.NREA
EFF(I) * 0.0
2 CONTINUE
00 400 JU=1»NPAR
NUM = NVAR(JU)
IF (IREAD(NUM).EQ.l) GO TO 400
CALL LMNTEFF
400 CONTINUE
CALL SYSEFF
CALL CALC5T
CSTEFF = TOTCST / ESYS
PRINT 3000. TOTCST, CSTEFF
3000 FORMAT (X/10X, 13HTOTAL COST = ,El3.5,///» 10X» 12HCOST/EFF. = ,Ei3.5
*)
600 STOP
END
248
-------
c
/ READ PROGRAM VKV
< CONTROL»RIVl* V)
\ FLOW INFORMATION Y
READ RIIAM
STANDARD DATA
DECK
;UAD CHARACTERISTICS
}F MONITORING
IVSTEMFORPARAMETiR
Figure 75. Flowchar t for MAIN Program
249
-------
SUBROUTINE RFC
SUBROUTINE RPC
COMMON CAP(40.20),VIOLSS(40.20), NVAR<20), IMPLI40).
IREAD(20), CONDE(20»2>. CONDI ( 20 , 18) f DATA<40»94)» FINIS<40.9)»
0(40*20*5), HWFLOWUO»12>. INITdO), IORO(20*20>» MONTH(12),
JUNC(10»3)» TITLE(20)» QSCAL<5)* TEMPR(40)* CMAXM(40»5),
CMINUX(40»5) » TLMAXM<40»5)» XL (40), CT<40)
COMMON EPSH40), SEPSK40)* XACT<40*5)» CMINUM (40. 5) . TMINUM<40).
CMINDM<40»5), NDOPTUO), K20PT<40>, NSOC<20, 28) , NSTAT(20),
XORD(5) tYORO(5>* QT<40,9), MSK(40,5)» NJcUO), ICPY(IO),
FIRST(40)» STATE<40>, NDAYS<40>» STATEK40), FIRSTK40)
COMMON KONTS(40»2)» NTOTSUO»2)t NOAYS1(40)» KOUNT(40t?)» PREV(4Q>
t NTOT(40i2>» PREV1(40)< 0(31,20), TS(40,2), TSSI40.2), TUP(40)»
TDOWN(40), OELTA(40), HTH(40>, CMINQX (40,5) , TMlNUX(40),
TMINOX(40) ,TMINOM(40) ,X1 (40»5,2) ,Y1 (40.5> tDEFC(40) »TCOMP(40»2>
COMMON CINT(10*4), TLEN(10)» NSEG(20)» MNPLCY (40 ) »TL(40)
COMMON/BLOCK I/ NR, FINL, lAt II* IOPT, JA« JJ, JO, JU» JX, JY,
» JZt NJ» NPAR» IRUN, NUM, QUP* Hit NT» NSFASt TA» AACUP»BBCUP*
*CCUPltCCUP2,CCUP3,CCUP4,CCUP5tCCUP6fCCUP7, CCP.ON, A3* DBENTH,
* ELEV. CSAT, VALMIS, MON, NYEAR* CACT, KK, NI, NINIT» NOX. MZ*
* MY* MZY, NJUNC* NTRI8, NREA* NACC, DENOM. ESYS, TOTCST* CHECK
COMMON/BLK/MASK (40)
COMMON/BLOCK2/TIME»NMR,OTYPE»POPT
LOGICAL MASK, CHECK, DTYPE.POPT
DATA ENO/4HENO /
DO 50 K = 1,20
50 NSTAT(K) = 0
READ PRORAM CONTROL CARD
READ (NI»100) DUM1»DUM2»DTYPE»(IREAD(I) » I si » 20 ) »TIME*NMR» (QSCAL( I )
«.I«1.5)*POPT
100 FORMAT <2A4,LI,1X,20I1»F5.0»I5,5F5.0,4X,L1)
IF (POPT) WRITE (NJ,150) DTYPE»TIME,NMR. (OSCAL ( I ) » I»l »5)
150 FORMAT (1H1,//10X»»DESIGN TYPE = »»L1*» SYSTEM OUR. = *«F7.2t» NO,
« OF MONTHS » *»I5*« FLOW SCALING FACTORS = »,5F5.1)
COMPUTE THE NUMBER OF PARAMETERS TO BE SlMULftTED
NPAR = 0
DO 200 I a 1,20
IF UREAD(I) .GT.O) NPAR = NPAR * 1
200 CONTINUE
DO 300 I = 1.5
IF (OSCAL(I).EQ.O.) QSCALU) = 1-
300 CONTINUE
IF (POPT) WRITE (NJ.250)
250 FORMAT » (NSOC (NGS, I > . I»l ,28)
4QO FORMAT 2,3
3 IF (POPT) WRITE (NJ,350) NGS.NSTAT (NGS) .NSEG (NGS) , (NSOC (NGS, I ) » I»l
350 FORMAT
500 CONTINUE
600 CONTINUE
RETURN
END
250
-------
( ENTER J
JE
READ PROGRAM
CONTROL CARD
i
COMPUTE THE
NO. OF PARAMETERS
SPECIFIED
READ USGS
STATION
INFORMATION
ECHO PRINT
USGS
STATION
INFORMATION
SET UP CHECK
FOR SEGMENT
USGS STATION
ASSOCIATION
i
(RETURN TO \
CALLER MAIN J
Figure 76. Flowchart for Subroutine RFC
251
-------
SUBROUTINE RSDD
SUlROUTINE RSOO
COMMON CAP(40.20)»VIOL5S<40,20)» NVA«(20), IMPL<40)»
IREAD(20). CONDE» CONDI ( 20 » 18) » DATA<40»94)» FINIS<40»9)»
G(40t20t5)t HWFLOW<10.12)» INIT<10). IORn<20«20>» MONTH(12).
JUNC<10»3)t TITLE(20)» OSCAL(5)» TEMPR<40)» CMAXM(40»5>t
CMINUX(40t5)« TLMAXM(40t5)t XLC+0), CT(40>
COMMON EPSI<40)t SEPSK40)* XACT<40,5)» CMINUM(40»5)» TMINUM(40)»
CMINOM(40»5)» NOOPT<40)» K20PTC*0)» NSOC(20»28)» NSTAT(20)»
XORD(5).YORO(5)» QT<40»9>» MSK<<»0,5). NJCUO). ICPY(10)i
FIRST(40>t STATE140). NDAYSUOI* STATEK40)* FIRSTK40)
COMMON KONTS(40»2)» MTOTS(40«2)» NOAYSK40)* KOUNT(40»2>t PREV(40)
» NTOT(40»2)» PREV1(40>» Q(31»20)» TS(40f2)» TSS(40»2)i TUP(40)t
TDOWN(40>t DELTAI40)? HTH(40). CMINDX (40f5) . TMlNUX(<*0)t
TMINDX(40)tTMINOM(40)»X1<40»5»2>•Y1(4Q»5),OEFC(40> tTCOMP<4o»2>
COMMON CINT<10«4), TLEN(10)» NS£G<20)» MNPLCY<40)»TL(40)
COMMON/BLOCK I/ NR» FINL» IA» II» lOPTt JA, JJ» JO. JU. JXt JYt
« JZt NJ» NPAR* IRUN» NUMf QUP» N2» NT» NSEAS» TA»AACUP.88CUP*
*CCUPlfCCUP3.CCUP3fCCUP4»CCUP5»CCiJP6.CCUP7, CCRONt A3t OBENTH.
* ELEV. CSAT, VALMIS, MON, NYEA*, CACT. KK, NJ, NINIT* NOX, MZt
* MY» MZY, NJUNC» NTRI8. NREA» NACCt DENOM, ESYS, TOTCST. CHECK
DATA ENOF/4HENOF/ 170
LOGICAL IMPL
DO 40 I = 1»40
40 IMPL(I) = .FALSE.
DO 3333 I = 1»20
DO 3333 J= ltl«
3333 CONDI (I»J)=0.
DO 788 I = 1.10
00 788 J=l,l?
788 HWFLOW(I.J) = 0.0
NR=5
C 300
C °EAO FILE A THRU FILF F-3
C 340
C FILE A - BASIN TITLE
41 READ (MI.U OUM1»11.IM?« 190
1 fORMAT (20A4) 210
READ (NI»i) DUMlfOUM? 240
IF (DUM1.NE.ENOF) GO TO 777 2bo
C FILE 8 - BASIN COMPONENTS
READ (NI*2A) DUMltDUM?tNINIT.NJiJNC,N«EA»NT«IH.ELEV
?6 FORMAT (2A4«5X»12.5Xt3(4X»I2»4X)»r10.0)
C
READ (Nltl) DOMltOUM?
IF (DUM1.NE.ENOF) GO TO 777
C
C RILE C - REACH ORDER
C
DO 10 K = 1.NTRH 50Q
READ (NI«3) DUMl»OllM2»I.UOrtU(I»J> »J=lt20) 510
3 FORMAT <2A4»3X.I2«7X,2U<1X,I2)) 52
10 CONTINUE 550
READ (NI»1) DUM1»OUM?
IF (DUM1.NE.ENOF) GO TO 777
IF (NJUNC.EQ.O) GO TO 887
C
C .FILE D - JUNCTIONS
C
252
-------
00 11 K=1»NJUNC 680
READ DUMl,DUM2tI.(JUNC(I•J),J=lt3) 690
33 FORMAT (2A4,13X.I2.2X»3(4X.I2,4X» 700
11 CONTINUE 960
READ (NI«1) DUM1.DUM2 730
IF (DUMUNE.ENOF) GO TO 777 750
C
C
C FILE E - HEADWATER CONCENTRATIONS
C
887 DO 373 MZY * 1.6
CALL RCONO
READ > 850
105 FORMAT <2A4.8X.I2t2X»6(2X,F8.0n 860
100 CONTINUE 1340
READ (NI»U DUM1»DUM2 890
IF (DUMUNE.ENDF) GO TO 777 910
C FILE F-2 - DATA(If7)tK20PT(I),DATA THRU DATA OUMltOUM2.I»OATA(It7)»K20PT(I)•(DATA!I»J)iJ*8i13>
608 FORMAT (2A DUM1«OUM2
IF (DUM1.NE.ENDF) GO TO 777
C
C FILE F-3 - NDOPT(I)» DATA<1»14) - r>ATA(Itl6). RIOENTd«J»
C - DEPTH OPTIONt DEPTH INFORMATION! REACH IDENTIFICATION
DO 160 K»1»NREA
READ (NltSlU DUMUDUM2»ItNDOPT(D»
160 CONTINUE
READ CNIfl) DUM1.DUM2
IF (DUM1.NE.ENDF) GO TO 777
C
C READ FILE F-4 THRU F-9» DATA(I»17) - DATA(I«84)
C - REACH-8Y-REACH CONCENTRATIONS OF ftLL EFFLUENT SOURCE TYPES
C - FOR ALL 17 CONSTITUENTS
C
DO 780 MZ = 1»6
CALL RDATA
READ (Nltl) DUM1*DUM2
IF (DUM1.NE.ENOF) GO TO 777
7RO CONTINUE
C
C
C READ FILE G« ^OMTH INDICATE
C
READ
-------
c
C READ FILE H, *1F;AN MONTHLY HEAuwATE^ FLOW<;
C
DO 250 K = 1,NINIT lijttO
READ INI,260) OUM1 ,r>tJM2» I » (HWFLO* ( I» J) • J=l , 12) 1290
260 FORMAT <2A4»3X»12,7X,1?F5.0> 130Q
250 CONTINUE 23
-------
SUBROUTINE RCOND
SUBROUTINE RCONO
COMMON CAP(40»20)»V10LSS<40.20)» NVAR(20). IMPLIED).
» IREAD<20), CONDE(20,2), CONDI (.20 118) « DATA (40 » 94) . FINIS<40»9).
« G(40»20»5>» HWFLOW(10»12>» iNlTdO), IORn(ao»20>» MONTHI12),
* JUNC<10,3)» TITLE(20), QSCAL<5>» TEMPRI40), CMAXMUO»5)»
« CMINUX(40,5)» TLMAXM(40»5>» XLC+0), CT(40>
COMMON EPSK4Q), 5EPSK40), XACT<40»5)» CMINUM (40,5) • TMINUMI40),
* CMIND'M(40.,5>» NDOPTI40), K20PTC+0), N90C(20»2S)» NSTAT(20>,
» XORO<5)tYORO(5)t QT(40»9), MSK(Hj,5), NJC(10)« ICPY(10»»
* FIRSK40). STATE(40). MDAYS<40)» ST6TFl(40)t FIRSTK40)
COMMON KONTS<40*2)« NTOTS(40»2)» NOAYSl(tr>)» KOUNT(40«2)« PR£V<40)
» « NTOT(40»?)» PREV1(40)» 0(31.70), TS(40,?), TSS(40.?)» TUP(40)»
* TOOWN(40)» OELTA(40)» HTH(40)» CMINDX (40,5) , rMlNUX(*»n),
» TMINOXUO) ,TMINOM {40 ),X 1(40,5,2) ,yiC»n,5) ,OEFC (40) ,TCOMH (40,2)
COMMON CINT(1D,4), TLEN(IO), NSE&(20), MNPLCY(40),TL(40)
COMMON/BLOCK I/ NR, FINL, IA, II, 10PT, JA, JJ, JO, JU, JX» JY»
« JZ, NJ, NPAR» IRUN, MUM, QXIP, N^» NT, NSFAS, TA,AACUP.BBCUP,
*CCUPl»CCUP2»CCUP3.CCUP4»CCUP5,CC^Pfa»CCU°7, CCRON', A3, OHtNTH,
» ELEV, CSAT, VALMIS, MOM, NYE4W, C*CT« KK, MI, NINIT, NOA, MZ,
# MY, HZY, NJUNC, NTRIB, NHEA, NACC, OENOM, ESYS, TOTCST. CHECK
C
C READS CONCENTRATIONS OF SIMULATtO P4RAMFTFP-S IN ILL HEAO*ATt.r OUM1,DUM2,I»CONDI(I«LINIT)
INIT(K) * I
41 CONTINUE
GO TO 9
3 DO 42 K=l,NINIT
READ (NI,103) DUM1,DUM2»1»CONOI(I»LINIT*1)
INIT(K) = I
255
-------
42 CONTINUE
GO TO 9
4 00 43 K-ltNINIT
READ (NI.104) OUM1»DUM2»I,CONOI(I»LINIT) »CONOI (I »LINIT«-1)
INIT DUMl»DUM2»I,CONDI DUM1,OUM2»I,CONDI DUM1,DUM2,I,.L=LINIT.NFIN)
INIT(K) = I
47 CONTINUE
101 FORMAT
104 FORMAT (2A4»HX,I2,4X,F8.0»12XfFH.J)
105 FORMAT (2A4.8X,I2,44X«F8.0)
106 FORMAT <2A4»RX»I2t4X»F8.0.3?XtF8.U)
107 FORMAT <2A4»8X«I?t?4X»Ffl.0.l2X«Fd.O)
108 FORMAT <2A4,8x»i2»<*x.F«.<,)»?(i2x»fro.o))
Q RETURN
EMD
256
-------
SUBROUTINE RDATA
SUBROUTINE ROATA
COMMON CAP(40t20)»VIOLSS<40,20), .NVArfC'O). IMPL(40)»
« IREAO<20), CO^DE(20,2)» COMDI ( 2<> , 1H) , OATA(40«^4), FINIS (40 »<#) *
r,(40t20»5)» HWFLOWUO, 1?) , INIT(IO), lO^T(20»20)» WIONTHI12),
JUNC»3), TITLE<2ri), OSC*L(5)» TEMPR(4o)» CMAXM(40,5),
CMINUX(40,5>, TLMAXM(40,5) , XL(**0), CT(4o)
COMMON EPSI(40), SEPSI(40)» XACT <<+0,5) . CMlNUH (40 ,b) , TMINUMUO),
CMINOM(40,5), NOOPT(40), K20PTC*0), MSOC(20,29), NSTftT<20)»
XORO(5),YORO(5)» QT(40,9), MSK<40,5)» NJC<10)» ICPY(IO),
FIRST(40), STATE<40), *OAYS<40)» ST&TF1UO), FIRSTH40)
COMMON KONTS(40»2), NTOTS (40,2) , NOAYSK41), KOUNT(40,2), PRE7(40)
» , NTOT(40,2)» PRF.VK40), 0(31,20), TSC40,?), TSS(40,2), TUP(40)»
» TnOWN(40), OELTAI40), HTH(40), CMINOX (40,5) , TMlNUXUO),
« TMINDXI40)»TMINDM(40),X1(40»5,2)»Yl(40,5) ,OEFC(40) , TCOMP(40,2)
COMMON CINTUO»4), TLEN(IO), NS£G<20), MNPLCY (40) ,TL (40)
COMMON/BLOCK!/ NR, FINIL, lAt II, lOPT, JA, JJ, JO, JU, JX, JY,
» JZ, NJ, NPAR* IRUN, MUM* QUP, NZ, NT, NSF&S, TA»AACUP,BBCUP,
•CCUP1,CCUP2,CCUP3,CCUP4,CCUP5,CCUP6,CCUP7, CCRON* A3, 08ENTH»
• ELEV, CSAT, VALMIS, MON, NYEAR, CACT, KK, NI, NINIT, NOX» MZ,
» MY, MZY, NJUNC, NTRIB, NREA, NACC, DENOM, ESYS, TOTCST, CHECK
C
C READS CONCENTR4TIONS OF EFFLUENT SOURCES FOR SIMULATED PARAMETERS
C - AND ALL REACHES
C
KPP » 0
IF (MZ.EQ.6) KPP=?
NSUM = 1
LINIT s 6MMZ-1) » 1
LMID » LINIT * 1
NFIN » 6*(MZ-1) + 3
C DETERMINES WHICH OF THE EIGHT POSSIBLE COMBINATIONS
c - MUST SE READ IN FOR EACH SLOCK OF THREE PARAMETERS
C
00 750 IBAR - It3
IRY - ,3*
-------
C READS CONCENTRATIONS FOR ONLY THOSE PARAMETERS TO BE SIMULATED
C
GO TO (11.12. 13, 14, 15. 16. 17, 18), NSUM
C
11 DO 21 K » liNREA
READ (NI.101) BLANK 1
READ (NIilOl) BLANK 1
21 CONTINUE
GO TO 9
C
12 DO 23 K = 1,N«£A
READ INI, 102) DUM1,DUM2.I»DATA(I»KS)»OATA
23 CONTINUE
GO TO 9
C
13 DO 24 K=1.NREA
READ {NItl03> DUM1,DUM2.I,OATA(I»KS*2> .DATA ( I tKS*3)
READ (NI.103) OUMl,DUM2,I.DATA(I»LS+2) ,OATA(I,LS*3>
24 CONTINUE
GO TO 9
C
14 DO 25 K=liNREA
READ (NIil04) OUM1.0UM2.I. (DATA < 1 » J) . J=KS,KR)
READ (NI,104) DUM1,DUM2,I, (DATA ( I , J) , J=L<;,LW>
25 CONTINUE
GO TO 9
C
15 DO 26 K=1,NREA
READ (NI.105* OUM1,DJM2,I» DATA(I.KT)t OATA(I.KP)
READ (NItlOS) DOMl,OUM2tI»OATA(I«LT)»OATA DUM1,DUM2.I»DATA(I»KS)» DATA
-------
SUBROUTINE RDRATE
SUBROUTINE RDRATE
COMMON CAP<40.20).VIOLSS(40,20)» NVAR» CONDI<20*13), DATA(40.94), FINIS<40»9>»
G<40»20»5). HWFLOW<10*12)» INITUO), IORrM20,20)» MONTHU2).
JUNC(10t3)« TITLE<20), Q5CAL<5)« TEMPR<4fn» CMAXM«»0.5).
CMINUX<40»5>» TLMAXM(40»5), XL(<»0), CT<40>
COMMON EPSK40). SEPSK40). XACTUQ.5). CMINUM (40 .5) * TMINUM(40)»
CMINDM<40»5)* NOOPT(40), K20PTC»0), NSOC<20,28)« NSTAT<20),
XORO<5)»YORD<5)* OT(40»9)» MSKC+Ot5)» NJC(10)» ICPY(10)»
FIRST<^0)t STATE(40)» NDAYSUO)» STATFl(40)t FIRSTK40)
COMMON KONTS(40»2)« NTOTSUO»2). NOAV tYl(40*5)tOEFC(40)tTCOMP(40»2)
COMMON CINTO0.4), TLEN<10)» NSE
23 CONTINUE
GO TO 500
13 oo 24 KSUNREA
READ (NI.in3) DUMl,OUM2.I,OATA
259
-------
24 CONTINUE
GO TO 500
14 00 25 K=1»NREA
READ (NI»10<»> DUMl,r>UM2tI.OATA(K»KS) .OATA(KiKO)
25 CONTINUE
GO TO 500
15 DO 26 K=1»NREA
READ (NItlOS) r>UMl,OUM2.I»DATA OUM1,UUM2»I»DATA(K»KO),nATA(K,KT)
?8 CONTINUE
GO TO 500
18 DO 29 K=1,NREA
READ (1411108) DUMliDUM2,I» (DATA(K»L) tL=KS,KT)
29 CONTINUE
101 FORMAT (Al)
102 FORMAT (2A4,flX,I2, 4X.F8.0)
103 FORMAT (2A4»8X»I2»24X. F8.0)
104 FORMAT <2A4,8X,I2,<»Xt F8.0» li2X, F8.0 )
105 FORMAT (2A4»8X»12»44X, F8.0)
106 FORMAT <2A4,flx«i2«4x» F^.O ,J2x, r8.o>
107 FORMAT <2A<»,8X,I2«24XtF8.0«12X»Fa.O )
108 FORMAT (2A4»flX» I2»
-------
SUBROUTINE RCHAR
SUHKOUTINE RCHAR
COMMON CAP(40»?0),VIOLSS(40,20), NVA*»
» IREAD(20), CONDE(20»2)» CONDI ( 2Ut 18) , OATA(40»14) * FINIS(40»9>«
» G(40»?0»5)» HKFLOWUOU2) » INITdO), I0«rv(20»20) « MONTHU2),
» JUNC(10»3), TITLE(20), QSC« NDAYS(40)t STATE1<40)» FI«ST1(«»0)
COMMON KONTS<40»2>» NTOTS(40,?), NDAYSK^O)^ KOUNT(4C»2)»
» , NTOT(40,?>. PR?V1(40), 0(31,20), TS<40,?>, TSS(40»2).
» TDOrtN(*0), DELTA<40)» HTH(aO), CMINOX (40.5) , TMlNUJC C.O) ,
» TMJNDX(40) ,TMINOM<40) , X 1 (40 » S»2) » Y1 U1 ,bl »OEFC(40) » TCOMP<<*0 , 2)
COMMON CINT.(10»<*)t TLEN(lO)» NS£0(20)» MNPLCY (4Q) i TH40>
COMMON/HLOCK1/ MR, FINLi IA» II, IOPT, JA, JJ, JQ, JU, JX, JY.
» JZ, NJ, NPARt TRDN, MUM, QIJP, N^» NT, NS^AS, T A, AACOP,BSCUP,
ttCcuPHCCUPStCCUpa^cup^MCCUPStCCUPfe.ccijp?, CCRON« A3« OHENTH,
« FLEV, CSAT, VALMIS, WON, NYEAW* CACT, KK, NI, NINITt NOX, MZ,
» MY, MZY, NJUNC, NTRIH, N*
-------
c
START
I
CONSIDER
FIRST
REACH
READ
CHARACTERISTIC
CARD
PRINT
CHARACTERISTIC
INFORMATION
•IS REACH ^^
IMPLEMENTED 7X5"*"
SET CHECK
FOR IMPLEMENTATION
CONSIDER
NEXT
REACH
PRINT
ERROR
MESSAGE
C
RETURN TO
CALLER MAIN
STOP
Figure 77. Flowchart for Subroutine RCHAR
262
-------
SUBROUTINE QTCAL
SUBROUTINE QTCAL
COMMON CAP(40»20) »VIOLSS(40,20) , NVAR. HWFLOW(10»12)« INITUO), IORD<20»20)t MONTH(12)t
• JUNC(10»3>» TITLE<20>» OSCAL(5)t T£MPR(4o)« CMAXM(40»5)»
• CMINUXU0.5) » rLMAXM(40»5>» XL<<»0), CT(4Q)
COMMON EPS 1(40) . SEPSK40). XACT(40,5>, CMlNUM(40t5)» TMINUM<40),
« CMINDM<40»5>, NOOPT<40>» K20PTC*<», NSOC(20»28)» NSTATt20)»
• XORD(5)»YORD(5>» 07(40.9) , MSK<40,5), NJC(IO). ICPY(10)t
• FIRST(40)t STATE(40)» NDAYS(40)» STATEK40). FIRSTK40)
COMMON KONTS(40»2). NTOTS(40»2)t NOAYSK40). KOUNT(40,2). PREVUO)
* « NTOK40.2). PREVK40). 0(31.20), TS(40.2). TSS(40«2)« TUP(40)«
* TOOWN(40). DELTA(40)» HTH(40)t CMINOX<40t5)« TMINUX(40)»
* TMINDX(40)»TMINDM<40)»X1<40.5.2>»Y1{40.5).OEFC(40).TCOMP<40.2)
COMMON CINT(10»4), TLEN(IO). NSEG(20)» MNPLCY (40) »TL ('vO)
COMMON/BLOCK I/ NR. FINL. I A. II, IOPT. JA, JJ. JQ, JU. JX. JY»
• JZ« NJ» NPAR» IRUN, NUM, QUP. NZ. NT. NSFAS. TA«AACUP.BBCUP.
•CCUP1.CCUP2»CCUP3.CCUP4,CCUP5.CCUP6»CCUP7, CCHON. A3. OBENTH,
• ELEV. CSAT. VALMIS, WON, NYEAR, CACT. KK, NIi NINIT. NOX. MZ.
* MY. MZY» NJUNC. NTRIB. NREA. NACC, OENOM, ESYS. TOTCST, CHECK
COMMON/BLK/MASK(40)
COMMON/BLK4/ X(5),Y(5) »DY<5) ,A(6)»B(6),C(6).0(6),«<(50>
LOGICAL CACT.IMPL,MASK.CHECK
DATA END/5HEND /
C 20
C »0
DO 585 I = l.NREA
IF (CHECK.AND.MASK(I)) 585,595
585 CONTINUE
C
44 DO 13 IRUN=1»NH
DO 24 L = 1* 10
CONDI=HWFLOW(L.NSEAS)
C
C IF FLOW SENSITIVITY ANALYSIS IS SPECIFIED, MULTIPLY HEAOWATEK
c - FLOWS 8Y THE FLOW SCALING FACTOK
CONDI(L.18) = QSCAL(IRUN) * CONDI(L»)8)
24 CONTINUE 26SO
C I730
CALL REINI
IF (NUM.GE.14) GO TO 13
C 2860
C REPEAT FOR ALL SIMULATIONS
DO 8740 IS*1»NREA
XKIStlRUN.l) = G(IS»NUM,IRUN)
Xl(IStIRUN,2) = FINIS(IS,9I
Yl(IS.IRUN) = FINISI1S.4)
8740 CONTINUE
13 CONTINUE
IF (IREAD(NUM).EQ.l) GO TO 597
c REPEAT FOR ALL PARAMETERS
IF (NUM.NE.17) GO TO 9202
DO 9203 IS » l.NREA
CSAT = (14.62 -(.3898»TEMPR(IS)) * (.006969«TEMPR(IS)»«2) - ( .000
«05897 » TEMPR(IS)«*3» » ((1.0 - (O.OOOOOs97«ELEV)) *« 5.167)
9203 CT(IS) = CSAT - CTdS)
9202 DO 8900 IM a 1,9
DO 8741 IR*1*NREA
DO 8800 IRON = l.NR
Y(IRUN) = YKIR.IRUN)
IT » IM - ^
263
-------
C INSERT APPROPRIATE VALUES IN X ARRAY
IF (NUM.GE.14) GO TO 8301
IF (IM.GT.3) GO TO 8900
GO TO (911,912,913),IM
911 X(IRUN) = XKIRiIRUM.l)
GO TO 8800
913 X(IRUN) = XI UH»IRLNt2)
GO TO 8800
913 IF (IMPL(IR).ANO.MASK(NUM)) 94li«J741
941 X(IRUN) * XACTdR.IRUN)
GO TO 8800
8801 IF (IM.LE.3) GO TO 8900
GO TO (961»962.963»964t965»966).IT
961 X(IRUN) = CMAXM(IR»IRUN)
GO TO 8800
962 X(IRUN) = CMINUMdR»I»UN>
GO TO 8800
963 X(IRUN) = CMINOMdR.IRUN)
GO TO 8800
964 IF
GO TO 8800
965 IF (IMPL(IR).AND.MASK(MUM)) 985*8741
985 X(IRUN) = CMINUX(IR.IRUN)
GO TO 8800
966 IF (JMPL(IR).AND.MASK .GT.XORD(MG)) GO TO 9QO
XORO(NG) - X(I)
YORD(NG)=Y{I>
NZ = I
900 CONTINUE
NR = NG * 1
IF (NX.ME.NZ> Y(NZ) = Y(NX)
IF (NX.NE.NZ) X(NZ) = X = TLMAXMdR.l)
00 8751 IX=2.NR ,
CNT? = CMAXM(IR.IX)-CTdR)
IF (CNT2.GT.CNT1) GO TO 8751
CNT1 = CNT2
TLUR) = TLMAXM(IR»IX)
8751 CONTINUE
GO TO 8741
264
-------
™E TH"E<5HOLO CONCENTRATION LIES IN
IF (X(IRUN) .LT.CNIJM) GO TO 8730
IF (IM.EQ.4) TL(IR) = TLMAXM ( IR,
MZ = IRUN
XX = XURUN-1)
GO TO 872?
8720 CONTINUE
GO TO 8721
mCT °F THRt"SHOLD FLOW IN THIS INTERVAL USING CUBIC
C SPLINE METHOD
C
8722 S=0.
N=NR
00 3010 IK=1,5
DY(IK)=1.
3010 CONTINUE
IF (X(l).EQ.O.) GO TO 410
GO TO 420
410 DO 430 IX*2»NR
JX=IX
IF GO TO 8750
CNT1 » CNT2
TL(IR) = TLMAXM(IR.IX)
8750 CONTINUE
8741 CONTINUE
8900 CONTINUE
GO TO 597
595 WRITE (NJ.596)
596/^fIoN1X'6°HEACH SEGMENT HAS N°T HEEN ^SOCIATEO WITH A GAUGING
STOP 441
C
597 RETURN
END
-------
to
Oi
Oi
Figure 79. Flowchart for Subroutine EXPDUR (Sheet 1 of 2)
-------
CO
Oi
-q
Figure 79. Flowchart for Subroutine EXPDUR (Sheet 2 of 2)
-------
SUBROUTINE REINI
SUBROUTINE REINI
COMMON CAP(40»?0> »VIOLSS<40»20) » iWAH(?0>, 1MHL<40>»
» IREADI20), CONOE» CONDI(2D,Ifl), OATA<40«94), FINIS(40»9),
* 0(40,20,5), HWFLOWdO, 12) » iNITdO), I0rtn(?0,20)» MONTH(12)»
» JUNC(10»3)» TITLE(20). OSCAL(5)t TEMPR(4n), CM4XM<40,5),
» CMINUX(40,5)» TLMAXM(40»5i * XL(40>, CT(4f»)
COMMON EPSI (40)» SEPSI(40>, XftCT(40»5)? CMINUM(40»5)t TMINUM(40)»
« CMINDM(40»5) » MDOPT(40)t KPOPK-+0), MSOC (80«2«) » NSTAT(20)»
* XORD(5) »YORD(5) » QT(40.9)» MSKC*o,5), NJCdO)» ICPYdOl*
* FI«ST(40)» STATE(40), NOAYS(40)» STATEK40), FIRSTK^tO)
COMMON KONTS(40»2), NTOTS(40»?)» NQAYSl(4i)), KOUNT(40»2)t PREV(40)
» , NTOT(40,2). PREVK40), Q<31»20). TSI40.2), TSS(40.?), TUP(40),
» TDOWN(40), DELTA(40). HTH(40). CMINDX(40,5)« TMlNUX(lO)»
* TMINOXC40)»TMINOM(40)»X1(40»5»2)»Yl(40.5).OEFC(40)«TCOMP(4Q«2)
COMMON CINT<10.4), TLEN(10>. NSEG(20), MNPLCY(4Q).TL(40)
COMMON/BLOCK I/ NR» FINL. IA. II. IOPT. JA. JJ» JQ. JU. JX» JYt
* JZ« NJ» NPAR» IRUN, MUM, QUP, N/» NT, NSEAS, TA»AACUP,B8CUP»
»CCUP1,CCUP2,CCUP3,CCUP4,CCUP5,CCUP6,CCUP7, CCRON, A3, DflENTH,
» ELEV, CSAT, VALMIS, MON, NYEAR, CACT, KK, NI, NINIT, NOX, MZ.
« MY, MZY, NJUNC, NTRI8, NREA» NACC, DENOM, ESYS. TOTCST, CHECK
C
00 1 1=1,NINIT
JA=INIT
-------
SUBROUTINE TRIED
SUBROUTINE TRIHD 6220
COMMON CAP(40t20) »VIOL.SS (40 120) « NVA*(?0), TMPL(40)»
» IREAD<20)t COMDE(?0»?)t CONDI < 2o »1 *) • DATA (<.OtQH) » FlNlS(40t^)»
» G(40t20»5)t HWFLOWt INlT(iO)t IORO(2u«20)t MONTH(12)t
• JUNC<10»3)» TITLE(2i>V» OSCAL<5)» TEwPR(4n)* CMAXM<<«C»5) »
* CMINUX(40t5)i TLMAXM(40»5)* XL<40)» CT<40>
COMMON EPSI(40)• SEPSI(40)» XACT(40»5). CMINUM(40.S)t
* CMINDM(40t5)t NDOPT(40)« K20PT(4j), NSOC(20»?*)i
» XORD(5) tYOROIS) t QT(40t9)t M5K(4ot5)t NJCdOlt ICPYUOlt
COMMON KONTS<40»2)t NTOTS«40»2)t NOAYSU«»T>t KOilNT (40.2) . PHEV(4o>
» TDOWN(40)» OCLTA(40)« HTH(40>t CMINOX(40t5)» T^INUX(40>t
* TMINDX(40)tTMINDM(40)»X1(40t5,2)tYl(40»S>tDEFC(40).TCOMP(40»2)
COMMON CINT<10,4), TLEN(10)t NSEG(20)t MNPLCY(40)»TL(40)
COMMON/BLOCKI/ NRt FINLt lAt lit IOPT« JA. JJ. JOt JU» JXt JY.
» JZt NJt NPARt IRUNt NUMt QUPt NZ« NT* NSFAS, TAtAACUPtBBCUPt
»CCUPl»CCUP2tCCUP3tCCUP4tCCUPS»CCUP6»CCUP7t CCSONt A3t 08ENTn»
« ELEVt CSATt VALMISt MONt NYEAPt CACTt KKt Nit NINITt NOXt MZ.
» MYt MZYt NJUNCt NTRISt NREAi NACC, DENOM, ESYSt TOTCSTt CHECK
COMMON/BLK/MASK(^0)
LOGICAL CACT tIMPLtMA«iK
C 632°
C 637°
KP = 0
C COMPUTE SUBSCRIPTS OF EFFLUtNT CONCFNTRATIONS
C
KPP * 0
IF (NUM.GE.16) KPP=2
KP » (NUM-D/3
JY = 15 * 2»NUM * 6»KP
JX a 8 » NUM
JO = JY * 1
JB = 21 * 2*NUM * 6»KP - KPP
JO =J8 + 1
£ 6400
2 IF UORO(JAtl)) I»lt3
C 644°
3 IAsIO«0(JA,I)
C
CACT = .FALSE.
c 6460
C
C «** COMPOTE PHYSICAL PARAMETERS FOR EACH REACH *«»
C MULTIPLY TRIBUTARY AND MUNICIPAL FLO*S BY FLO* SCALING FACTOR
C
DATA(IAt7> = OSCALdRUN) • DATA(IA,7)
OATA(IA.5> = QSCALURUN) * DATA(IA,5)
C
C STREAM FLOX IS AUGMENTED 8Y TRIBUTARY AND MUNICIPAL FLOW
FINIS(IA»41 s QUP * OATA(IAtS) * UATA(IAt7)
FINIS(IAfl) * IA
FINIS
-------
C VELOCITY IS COMPUTED AS A FUNCTION OF FLOW
FINIS(IA»7> = OATA(IA,3) « *» DATA(IAt4))
FINIS(IA,6) = OATAdAfU/ (FINIS < I A»7> « 16. 36)
FINIS(IA,8) = DATA(IA,14)
FINIS(IA»5) = 0.
C 6510
C
COMP = FINL
IF (NUM.ME.17) GO TO 3374
C
C IF DO IS THE PARAMETER* OETt-RMINE THE rfEAERATION COEFFICIENT
CALL K?CAL
C
C CONCENTRATION OF INDUSTRIAL SOURCES EQUALS THE AMBIENT STREAM
C CONCENTRATION PLUS TrIF. NET CHANGE ODE TO INDUSTKY
3374 DCONC = COMP + DATA(IA»JQ>
UNACC = 0.
C
C COMPUTE THE MASS ADDED AT Th£ HEAD OF THE REACH
DELTAM = DCONC * OATAdA,6) + OAU(IAt.JY) * DATA(IAiS) + UATA(IA»J
*B) * DATA(IA.7) + UNACC
DELTAO = DATA(IAtS) + DATAUA.7)
QTNT = DATA(IA»6)
C
C COMPUTE THE CONCENTRATION Ot- THE PAPAMETEW AT THE HEAD OF A
C REACH AFTER THE MASS FROM THE SOURCFS HAS BEEN ADDED
114 GlIAiNOMf IRUN) = (COMPMQUP-QINT) + DELTAM) / (OUP + DELTAO)
IF (IMPL(IA) .ANO.MASK.CNUM)) CACT = ,TW1)E.
C
C IF PARAMETER IS CONSE^V (\T IVL, -itfilNNlNG CONC = FINAL CONC.
C WITHIN THE REACH
C
IF (NVAFM JU) .LF.7) FINIS(IA»9) = b(I A,NUMfIRUN)
IF (NVAW(JU).LE.7) GO TO 333
NZ = 77 + NUM
C
IF (NVAR(JU) .LF..13) GO TO 34
C
C IF PARAMETER IS NON-CONSERVATIVE COuPLEDt COMPUTE THE CONCENTRATION
C - OF EACH PARAMETER ACCORDING TO ITS OWN UNIQUE EQUATION
C
15 CALL COUPLES
GO TO 33
C
C IF THE PARAMETER IS NON-CONSERVATIVE NOM-COUPLED, COMPUTE
C THE DECAY WITHIN THE HEflCH
34 CALL DECAY
GO TO 33
333 IF (CACT) XACTUA.IRIJN) = G ( I A.NU>v|, IHUN)
C
C
C SET FINAL CONCENTRATION OF PARAMETER IN REACH, EQUAL TO
C - NON-SUBSCRIPTFD VARIABLE
C
33 FINL = FINISdA,1*)
C
OUP = FINIS (IA,4)
C
1 = 1 + 1
DATA(IA«5) = DATA(IA.o) / QSCAL(IKUN)
OATA(IA«7) = OATAIIA.7) / QSCAL(IRUN)
GO TO ?
1 RETURN
END 6810
270
-------
SUBROUTINE COUPLES
SUBROUTINE COUPLES
COMMON CAP(40. 20), VIOI.SSC40, 20), .MVAP(?0>, IMPL(40>,
* IREADI20), CONOEI20,?), CONDI C2«, 1R) . DATA<40,94>, FINIS(4.),9>,
* G<40,?0,5>, HWFLO* (I-"., 12), iNITUo), T0*n , 2o, 20 ) , "ONTH C 12) I
• JUNC(1U,3), TITLE(2D, OSCALI5), TE.'PR<40>, CMflXM(40,S>,
» CM!NUX<40,5>, TLMAXM(4Q,5), XL<-^>, C7(40>
COMMON EPSK40), SFPSM40), "UCTUfl.S), CMI NUM l<,(i,b) , TMINUMUO).
• CMINUM<40,5>, MOOPTC40), K20PTC+0), «M«OC»20.2H> . NSTAT<20>,
« XORO(5),YORO(<5), QT C*r.,) - DATA ( I A, 92) )
* «<5nA,14) * A14) / )/(UATA(IA,92)-DATA(IA,93»
22 AC = 0.
23 CONTINUE
AD = CUP6 • r,(IA,8,IRUiM) / (DAT A ( I A. HS) - OATA(IA,93))
C
C
4 CUP1 =CCIH»1
ClJPl =CUP1 *1.07»»(TEMPR(IA)-2u.)
CIRON =CCRON
CIRON =CIRON *1.07««(TtiMPR(IA)-?0.)
CUP2 =CCUP?
CIJP2 =CUP2 *1,047»»(TEMPR(1A)-?0.)
CIJP3 =CCUP3
CUP3 =CUP3 «
CUP4 =CCUP4
CUP4 =CUP4 «1.30«»(TEMPR(IA)-20.)
CUP7 =CCUP7
CUP7 =CUP7 *1.07«»(TEMP9(IA)-20.)
CSAT = (14.6? - (.3898* TEMPR(IA)) * ( ,
DEFC(IA) = CSAT - G ( I A, 1
IF (HTH(IA).EO.O.) GO TO 300
DEFC(IA) = DEFC(IA) / (1. M.U . (1. . . Q4MTEMPR ( U) » «HTH(IA>
^
271
-------
300 CONTINUE
A3 = A3/100.
A17 = A3»CUP1»M IA»3,IRUN) / (CIROiM-DATA ( I A»94) )
Alfl s CUP2* G< IA» 1?» IRUN) / (DATA < I Ai ^9) -OAT A ( I A»94 ) )
A19 = CUP7» +AC*AH*AA) / (DATA ( I A. 93) -DATA ( I A. Q4)
A
777 CONTINUE
C
C
C DIVIDE *E4CH IMTO TEN SUBRtACHfc.S OF EQUAL DISTANCE
C - AND TIME OF T^ftVEL
C COMPUTE SUHREACH CONCENTRATION OF PARAMETER IN CONCERN
C - ACCORDING TO ITS OWN UNIQUE SOLUTION
C
DO 30 N= 1,10
TT = N
TLEN(N)= FINISdA,?)- ) / 10.
C
GO T0<5,6,7,3> ,NOX
GO TO 30
6 CINTINt?) ~ (G(IAtlt5»IRIJM)+AlS+All»«E') *T
«B) - AD*EXP(-DATA(IA»85)»TB)
GO TO 30
8 CINT(N»4)=(DEFC(IA)+A17*A22*A21»A20*A19+A1H*A23-BENTH)»EXP<-DATA(
*IA.94)*TB) - A17 * EXP(-CIRON«TB) - A?? * EXP (-DATA ( I A. 80) »TB) -
«A21 * EXP(-OATA(IA<91)»T8) -A 18«Exp (-DATA ( I A. 89) «TB) - A19 *ExP(-
*DATA(IA»93)«TB) - A20*EXP (-DATA ( I A, 92) «TB) -A23»EXP (-DATA ( I A» 85) »T
*B) * BENTH
IF (N.EQ.10) FINIS(Ift,9) ~ CSAT - ClNT(10,4)
30 CONTINUE
C
CINIT = G(IA.NUM.IRUN)
IF (NUM.EQ.17) CINIT=DEFC(IA)
C
C FIND MAXIMUM CONCENTRATION AND ITS LOCATION
MCSEG » 1
CMAX = CINT(1»NOX)
TLMAX = TLENID
DO 11 M = 2.10
IF (CMAX-CINT(MtNOX)) 14,14,11
14 CMAX = CINT(M.NOX)
TLMAX = TLEN(M)
MCSEG=M
11 CONTINUE
CMAXMdA , IRUN)= CMAX
TLMAXM(IA.IRUN) = TLMAX
C FIND MINIMUM CONCENTRATION UPSTREAM OF MAXIMUM CONCENTRATION
CMINUM(IA»IRUN) = CMAXM (I A, IRUN)
TMINUMdA) = TLMAXM(IA,IPUN)
IF (MCSEG. LE.l) GO TO 402
MCT = MCSEG - 1
DO 15 I = 1»MCT
IF (CINT(I»NOX)- CMINUM(IA,IRUN)> 16, 16, IS
16 CMINUMdA.IRUN) = CINT(I,NOX)
TMINUMdA) * TLEN(I)
15 CONTINUE
402 IF (CMINUMdA, IRUN). GE. CINIT) 401,400
401 CMINUMdA, IRUN) = CINIT
TMINUMdA) = FINIS(IA,2)
272
-------
C FIND MINIMUM CONCENTRATION DOWNSTREAM OF MAXIMUM CONCENTRATION
400 CMlNOM(IAtlRUN) = CMAXM(lAtIRUN)
TMlNDMdA) * TLMAXMdA.IRUN)
IF (MCSEG.EQ.10) GO TO 19
MCT * MCSEG*!
oo 17 I « MCT .10
IF (CINTd.NOX) - CMINDM(IA.IRUN)) 18.18*17
18 CMINDMdA.IRUN) = CINT*A15*A16)»EXP(-DATAdA»92>»TB)-Al6»
«EXP<-OATAdA.91)*TB) -A15«EXP »TB>
GO TO 130
107 XACT(IA»IRUN)=(G(IA,16»IRUN)*AD*AC*AB»AA)»EXP(-OATA(IA,93)*TB>
* -AC • EXP(OATAdA»93)*TB) - AB » £XP< DATAdA»92) *TB) -AB*EXP(-D
«ATA( IA»92)*T8) -AB * EXP(-DATA -A1»«C.AP<-OATA(IA,?9)»TB) - A19 »EXP(-
«OATA(IA«93)«TB) - A2')#EXP (-DATA (Irt .9?) «TB) -A23«EXP (-OATA (I A. 85) »T
•B) + BENTH
130 CONTINUE
C FIND SU8INTERVAL *HICH C(X) IS LOCATED
DO 39 M=1.10
IF (XL(IA).GT.TLEN(M)) GO TO 39
MXSEG = M
GO TO 31
39 CONTINUE
MXSEG = o
CMINUX(IAtlRUN) = CINIT
TMINUX(IA) = FINISdA,?)
GO TO 34
C FIND MINIMUM CONCENTRATION UPSTREAM OF X
31 CMINUX(IAiIRUN) = (j( I A»NUM» IRUN)
TMINUX(IA) * FINISdA.?)
MCT = MXSEG
00 32 I = l.MCT
IF (CINT(ItNOX)-CMlNUX(IA.IRUN)) 33,33,32
33 CMINUXdA.IRUN) a CINT(I.NOX)
TMINUX(IA) = TLENd)
32 CONTINUE
37 IF (CMINUX(IA,IRUN>.GE,CINIT) 38i34
38 CMINUX(UtlRUN) = CINIT
TMINUXdA) = FINIS(IA»2>
C FIN MINIMUM CONCENTRATION OOWNSTKEAM OF X
34 CMINDX(IAtlRUN) = CINTdO.NOX)
TMINOX(IA) = TLEN(IO)
IF (MXSEG.EQ.10) GO TO 40
MXSEG * MXSEG »1
DO 35 I =MXSEG,10
IF (CINTd.NOX)-CMINDX(IA.IRUN)) 36t36«35
36 CMINDX(IA.IRUN) * CINTd.NOX)
TMINDX(IA) = TLENd)
35 CONTINUE
'40 OATA(IA«NZ) = OATAdA.NZ) / FACT
-------
SUBROUTINE K2CAL
c
c
c
c
c
c
c
c
c
c
c
c
SUBROUTINE K?CAL
COMMON CAP(40»?0> , VIOL SS U0» 20) , NVA«»
» GUOt20»5)» HWFLOWUO, 1?) , INIT(IO), IQrtT (20 ,20 ) » MONTH(12>»
* JUNC(li'J,3)» TITLE(2f>), OSCAL(5>» TEMPR(40>» CMAXM (40 ,5) t
« CMINUXU0.5) » TLMAXM<40,5> » Xl_<40), CT(4f)>
COMMON EPSK40), SEPSI'40), XACT<40,5>» CMlNUM Ufi.S) » TMINUM
» CMINOM(40,«5) , NDOPT<40)» K?OPT(-*'J), M^OC(?0»?M)» NSTAT<20)»
« XORDI5) »YORr><5> » QT<40.4)« M«;K («*u ,5) , NJr(10)» ICPY(10)«
* FIRST(40)» STATE(^0)« NOAYS(40)t 5TATFK40). FIR^TK^O)
COMMON KONTS(^»0»2)» MTOTS(40»2)» ^DAYSl(4o>« KOUNT(^0«2)»
* « NTOT(40,2), PReVK^O), 0(31,20), TSI40,?), TSS«*0,?>, TUPUO),
* TDOWN(40)» DELTA(40), HTHI40), CMINDX (40,5) , TMlNUXUO),
« TMINDX(40) ,TMINDM(40) «Xl(40,b»2)»Yl(4(l,5) ,DEFC(40) »TCOMP(40,2)
COMMON CINT(10,4), TLENtlO), NSE^(20), MNDLCY (10) »TL (40)
COMMON/BLOCK!/ NR, FINL, IA, II. IfJPT, JA, JJ, JQ, JU, JX, JY,
« JZt NJ. NPAR, IRON, NUM, OUP, N2» NT, NSFAS, T A, AACUP,BBCUP,
«CClJPl»CCUP2»CCUP3»CCUP4,CCtJP5.CCUH6,CCUP7, CCROM, A3, DRENTH,
* ECEV, CSAT, VALMI<;, MON, NYEAS, CACT, KK, NI, NINIT, NOX, MZ,
« MY, MZY, NJUNC, NTRIR, NREA, NACC, DENOM, ESYS, TOTCST, CHECK
10770
A VALUE OF DEPTH IS OBTAINED FROM ONE OF TWO OPTIONS
NOPT =
NDPT *
1,
2,
i -
5
70
SIGNIFIES OPTION
SIGNIFIES OPTION ?
REGRESSION EQUATION
NDPT = NDOPT(IA)
IF (NDPT.EQ.?) GO TO 5
DEPTH = DATA , IOPT
1 DATA (1A.9A) = DATA = DATA(IA,9)» (FINIS (I A, 7) »«DAT A (I A, 10)) /(DEPTH**
»OATA(IA*1D) * 2.31
GO TO 100
3 DATA (IA.94) - DATA(IA,12)« (FINIS(IA»4) «» DATA(lAtl3)) «2.31
100 CONTINUE
COMPUTE KIT WITH TEMPERATURE DEPENDENCE
DATA (IA,94) = DATA(IA,94) « 1.0l39«» (TEMPR(I A)-?0.)
IF SENSITIVITY ANALYSIS F0« REACTION RATES* MULTIPLY REAERATION
RATE SY ITS SCALING FACTOR
FINIS(IA»8) = OEPTH
RETURN
END
10980
11020
11050
11060
11100
11110
274
-------
SUBROUTINE DECAY
SUBROUTINE DECAY
COMMON CAP(40»20>»VIOLSS<40»20> » NVAR(20>, IMPL(40>»
» IREAD<20>» CONDE(20»2)» CONDI (80, 18> , DATA<40»94), FINIS<40,9),
» G(40t20,5), HWFLOW(10»12) » INIT(lO), IORO(20.20>» MONTHU2),
« JUNC<10»3), TITLEJ20), QSCAL(5)t TEMPR<40)» CMAXM(40,5>»
• CMINUX<40»5> » TLMAXM<40»5) * XL(40)» CT(4Q)
COMMON EPSH40), SEPSK40), XACT<40»5)« CMINUMUO»5)» TMINUMUO),
» CMINDM<40»5) » NDOPT(40)» K20PTC»0)t NSOC(20»28), NSTAT(20)«
» XO«D(5),YORD(5)« QT<40»9), MSKC*0,5), NJC(10>» ICPY(10)»
* FIRSK40), ,STATE(40)» NDAYS(AO)» STATE1UO), FIRSTK40)
COMMON KONTS«40»2)» NTOTS<40»2)» Nt)AYSl<40>» KOUNT(^0»2)» PREV(^O)
» * NTOT(40,2)» PREV1«>0)» 0(31.20)t TS(40.2)i TSS(<>0»2). TUP(^0)t
» TDOWN(^O), DELTAI40), HTH140), CH1NDX 1 40 .5) * TMINUXUO)»
» TMINOX<40) »TMINDM(^0) »X1<40 ,5»2> » Yl (40 »5) tDEFC(40> ,TCOMP(40,2)
COMMON CINT<10»4), TLEN<10>» MSE, MNPLCY (40) ,TL«40)
COMMON/BLOCK I/ NR, FINL» IA, II, IOPT, JA» JJ, JQ, JU, JX, JY,
« JZ» NJ, NPAR, IRUN, NUM, QUP, NZ« NT, NSFAS* T A» AACUP.BBCUP,
»CCUP1,CCUP2»CCUP3,CCJP4,CCUP5,CCUP6»CCUP7, CCRON» A3, D8ENTH,
» ELEV, CSAT, VALMIS, MON, NYEAR, CACT , KK, NI, NINITf NOX, Mi,
» MY, MZY, NJUNC, NTRIB, NREA, NACC, OENOM, ESYS, TOTCST, CHECK
LOGICAL CACT
COMMON/REACT/FACT ( 20 )
DATA )
DD = EXP(B)
XACT(IAtlRUN) = OD»G(lA,NUM,laiJN>
C RETURNS TO CALLFR TRI8D
40 OATA(IA,NZ) = DATA(IA,NZ) / FACT (NUM) »»(TPMP« ( I fl) -20. )
RETURN
END
275
-------
SUBROUTINE RMATC
SUBROUTINE RMATC 5170
COMMON CAP(40,?0).VIOl SS<40.?0)» NVA^(?0), IMPL(4<))«
* IREAD(20)« CONDE<20»?>. CONDI(?v»16)» OATA<40»94). FINIS(40.9)t
* G(40»?0»5)t HWFLOWdm 12) » INITdO)* IOKO(20»2(t)» MONTHU2).
* JUNC(10»3>t TITLE<20), QSCAL<5)» TEMPR(4(>)t CMftXM(40»^>»
» CMINUX<40»5>» TLMAXM<40»5>• Xl.f+0), CT(40)
COMMON EPSK40). SEPSK40), X ACT <<•*(> .5) , C^INUM UO.5) » TMINUM(40).
» CMINOMI40.5)» NOOPT(40)* K?OPTC+U)< NSOC(20t26)» NSTAT(20),
» XORD(S)»YORO(5)» OT(40«9)i MSKC*U»5), NJC(10)» ICPY(10)»
» FIRST(40)« STATE(40), NDAYS(40)» STATF1(40)» FIRSTK40)
COMMON KONTS<40»2)» MTOTS(40»2)» NOAY?lC»n)» KOUNT<40»P)» Prt£V(40>
» , NTOT(40»2)» PREVK^O)* 0(31.20), TSI40.2), TSS(40»?)» TUPI40),
» TDOWN(40)» DELTA(40>« HTH(<*0), CMINUX (40,5) , TMINUX(40),
» TMINOX(40> «TMINOM(40)»X1(40»5»2)»Y1(40»5)tOEFC(40)»TCQMP(40»2>
COMMON CINT(10»4), TLFM(10)» NSEt)<20). MNPLCY(40)«TL(40)
COMMON/BLOCK I/ NR» FINL» IA. II. lOPTi JA« JJ. JOi JUt JX« JY»
» JZ» NJ» NPARt IRiJN, NU^» OUP» N^» NT» MSFAS, TAtAACUP.BBCUP,
»CCUP1.CCUP2,CCUP3,CCUP4,CCUPS,CCUP6,CCUP7, CCPO'sl. A3. QBENTH,
« ELEV» CSAT. VALMIS. WON, NYEAk, CACT* KK, NJ» NlNIT. NOA» MZ»
» MY. MZY. NJUNC. NTRIR. NREA. NACC, DENOM, ESYS. TOTCST. CHECK
C 5270
C DETERMINE WHICH STRETCHES £NTEw & JUNCTION
C 5310
IINIT=NINIT 2020
16 DO 4 1=1.NJUNC 2070
DO 5 J=1.IINIT 2080
IF(JUNC(Itl)-INIT(J))5.ft.5
5 CONTINUE 5460
GO TO 4 5470
6 00 7 J=1»IINIT 2100
IF(JUNC(I»2)-INIT(J)>7,a,7
7 CONTINUE 5500
GO TO 4 5510
8 II=JUNC(I.l) 2120
JJ=JUNC(I»2) 2130
C
C
KK=JUNC(I.3) 2140
JA=KK 2150
C 5570
C CALL 8 L E N D 5590
C 5600
CALL BLEND 56io
C
C
FINL = CONDI (JA»NUM)
QUP = CONDI(JA»18)
C
C CALL T R I 8 0 58SO
C 5860
CALL TRIBO 5870
C 5880
C SET FINAL CONDITIONS EQUAL 59S0
C TO CALCULATED CONDITIONS 5960
C
CONDE(JA»1) = FINL
CONOEUA.2) = OUP
C 6020
C REPEAT UNTIL ALL JUNCTIONS HAVE BEEN CONSIDERED
C 6070
IINIT=IINIT+1 2290
INIT(IINIT) = KK
4 CONTINUE 2310
C 276 6l6°
15 RETURN 6200
END 6210
-------
SUBROUTINE BLEND
SUBROUTINE BLEND
COMMON CAP(M>»20)»VIOLSS<^0»20) » NVAR(?t», IMPL<»
IREAO(2Q)» CONOE<20»2)» CONDI(20,18). DAT A (40 »<)<»)» F1NISU0.9).
G<<.0,20,5), HWFLOW(10,12), INIT<10)» IORn<20»20)» MONTH(12),
JUNC(10»3)» TITL£(20>, QSCAL(5>» TEMPR(*0)» CMAXMC40,5)»
CMINUXUO*5) » TLMAXM(<»0»5) » XLC+0), CT(<»0)
COMMON EPSI(40)» SEPSK40), KfcCT<<»0,5>» CMlNUM (40,5) • TMlNUM(, NOOPT(^0)» K20PT, NSOC(20»28)t NSTAT(20).
XPRO(5) ,YORO(5) t QT<<*0»9)» MSKC^U.S), NJC(10)» ICPY(10)»
FIRST(AO)* STATE(40)» NOAYS(40)» STATEl(i»0), FIRSTK40)
COMMON KONTS<40»2>» NTOTS (<*0» 2) » NOAYSK^O), KOUNT f»0 , 2) , PREVUO)
* NTOT(^0«2)» PREV1(40)» 0(31.20), TS<<»0,2)» TSS(*»0»2),
TDOWN(^O). OELTA(40)» HTH(<»0)» CMINOX (A0,5) , TMINUXC.O),
TMINOX(40) ,TMINOM(^0),Xl( ,Y1(<»0»5) ,OEFC(
-------
SUBROUTINE ICSSMU
The listing for Subroutine ICSSMU is not presented in this report to limit distri-
bution of the EMSL proprietary subroutine. An interpreted FORTRAN source
deck for ICSSMU is supplied to EPA with the total program source deck.
278
-------
SUBROUTINE EXPDUR
SUBROUTINE EXPOUR
COMMON CAP(40»20)»VIOLSS(40»20), NVAR(20), IMPL<40>»
IR£AD(20>» CONOE<20»2), CONDI(20,18)t DATA(40,94) » FlNIS(40»9),
G<40»20»5)» HWFLOW(10»12), INITUO), IORr><20»20>» MONTH<12>,
JUNC(10f3>* TITLE(20>» QSCAL(5>» TEMPR(4o>» CMAXM(40»5)»
CMINUX(40»5)» TLMAXM(40»5), XLC*0)» CT<40)
COMMON EPSI<40>» SEPSK40), XACT<40»5)» CMlNUM (40 ,5) » TMINUM(40),
CMINOM<40»5)» NDOPTJ40), K?OPT(40), NSOC<20,28)» NSTAT(20).
XORD(5)»YORO(5)» QT<40»9), MSKC»0»5>» NJC<10)» ICPY(IO)*
FIRST140), STATE(40>» NDAYS<40>» STATEK^O)t FIRSTK40)
COMMON KONTS(40»2)t NTOTS(40t?)» NOAYS1(40)» KOUNT(40.2)t PREV(40)
, NTOT(40t2). PREVK40). Q(31»2Cl)t TS(40,2)* TSS(<»0«2)» TUP(40),
TOOWN(40)» DELTA(40). HTH(40), CMINOX(40,5), TMlNUX(40)t
TMINOX(40)»TMINDM(40)»X1(40t5»2> »Yl<40f5),OEFC(40> tTCOMP(40»2>
COMMON CINT(10.4), TLENt(lO). NSEG(20>» MNPLCY(40)»TL(40)
COMMON/BLOCK I/ NR. FINL. IA» II» IOPT. JA* JJ. JQ, JU. JX. JY.
* JZt NJt NPARt IRUN, NUM, QUPv NZ» NT* NSFASt TAiAACUPtBBCUPt
»CCUPlfCCUP2»CCUP3.CCUP4,CCUP5,CCUP6fCCUP7, CCRONt A3f OBENTH,
* ELEV* CSAT. VALMISt WON. NYEARt CACT. KK, NI« NINITt NOXt MZt
• MYt MZY» NJUNC* NTRIB» NREA» NACCt OENOM, ESYS, TQTCST. CHECK
COMMON/BLK/MASK(40)
COMMON/BLOCK2/TIME.NMR.DTYPE.POPT
LOGICAL FIRST,STATE» INOTt PREV, 08LSTR,EOF,IMPL,
»NCALL» MASK, FIRST1, STATE1, INlTl, PREV1
LOGICAL MSK.ASTATEtCHEC .TEST,VUPStVDNS,ICPY»VXN,VXC»
» VMAX, VMINUM.VMINDM, VMINUX,VMINOX
MAX = NREA » 1
NSTATE = 0
J = NUM
C DETERMINE IMPLEMENTATION SCHEME FOR tACH PARAMETER
DO 1 I - 1»NREA
NRJ = 1
NPATH = 1
DO 49 MTZ = 1*5
49 MSK(ItMTZ) * .FALSE.
C TEST FOR IMPLEMENTED SEGMENTS
IF (IMPL(I).AND.MASK(J)) 2,1
C DETERMINE STRETCH OF IMPLEMENTED ELEMENT
2 00 3 IX a 1,NTRI8
DO 3 JP = 1,20
NSX = IX
NRX = JP
IF (I.EQ.IORO(NSX,NRX)) 80*3
3 CONTINUE
C DETERMINE IF SEGMENT IS AT THE HEAD OF A STRETCH
80 NCR = I
74 IF
-------
C THERE IS ANOTHER UPSTREAM JUNCTION
C COPY MASK
85 ICPY(NRJ) = MSK(I«MPATH)
C SET SEQUENTIAL JUNCTION LIST
NJC(NRJ) = NJX
NRJ = NRJ + 1
NSX = JUNC(NJX.l)
DO 86 JP = It 20
IF = .FALSE.
NDAYS(I) = 0
NDAYSKI) * 0
FIRSTHI) » .TRUE.
STATEKI) 3 .FALSE.
PREVKI) « .FALSE.
DO 400 KK»lt2
KONTS(ItKK) s Q
NTtiTSUtKK) - 0
KOUNT(ItKK) = 0
NTOT(I.KK) s 0
400 CONTINUE
C READ USGS TAPE FOR ALL MONTHS
C REPEAT FOR EACH PARAMETER
NMN = 0
6 CALL GSTAPE (NMN)
IF (NMN.EO.NMR) NSTATF = 1
C DETERMINE THE NUMBER OF DAYS IN THE CURRENT MONTH
GO TO <7t9t7»8«7»8»7,7»8»7.8»7)»MON
7 MAXDAY=31
GO TO 10
8 MAXDAY=30
GO TO 10
<) YEAR=NYEAR
FRACT=YEAR/4.0
lNTEG=NYEAR/4
FRACT*FRACT-INTEG
MAXOAY»29 280
IF(FRACT.NE.O.) MAXDAY=2H
-------
C LOOP FOR DAYS
10 DO 24 IDAY=1»MAXOAY
C SET UP WORDS INDICATING WHETHER A VIOLATION OCCURS OR NOT AT EACH
C SEGMENT FOR THE DAY IN CONCERN
VUPS » .FALSE.
VDNS a .FALSE.
VMAX * .FALSE.
VMINUM * .FALSE.
VMINOM = .FALSE.
VMINUX a .FALSE.
VMINDX = .FALSE.
VXC * .FALSE.
VXN = .FALSE.
DO 500 IMtNREA
DO 66 KX = 1,20
IF •NSTAT(KX).EO.O) GO TO 66
DO 666 IT a 1,28
IF .EO.O) GO TO 66
666 CONTINUE
66 CONTINUE
445 IF (J.GE.14) GO TO 82
IF 671*669
C IF UPSTREAM END OF SEGMENT IS IN VIOLATION, TURN ON CORRESPOND ING BIT
669 IF (Q(IOAY.NGS).LE.QT(I.l)) VUPS = VUPS.OR.MASK(I)
C IF DOWNSTREAM END OF SEGMENT IS IN VIOLATION, TURN ON CORRESPONDING BIT
IF (Q(IDAY»NGS).LE.QT(It?» VDNS=VDNS.OR.MASK(I)
IF (IMPL(I).ANO.MASK(J)) 81,500
8l IF (Q(IDAY,NGS).LE.OT(I,3» VXN = VXN.OR.MASK(I)
GO TO 500
671 IF .LE.QTU»5>> VMINUM = VMINUM.OR.MASK (I)
IF VMINUM = VMINOM.OR.MASK(I)
IF (IMPL(I).AND.MASK(J)) 83,500
83 IF (0(IDAY,NGS).LE.QT(I,7)) VXC * VXC.OR.MASK(I)
IF (Q(IDAY*NGS).LE.OT(I,8)> VMINUX = VMINUX.OR.MASK(I)
IF ) 675*676
675 VMAX a VMAX.OR.MASK(I)
VMINUM » VMINUM.OR.MASK(I)
VMINDM » VMINOM .OR.MASK(I)
676 IF (IMPLm.AND.MASK(J) ) 677,500
677 IF (PREVl(I).ANO.MASK(J)) 678*500
678 VXC a VXC.OR.MASK(J)
VMINUX * VMINUX.OR.MASK(I)
VMINDX s VMINDX.OR.MASK(I)
500 CONTINUE
C INITIALIZE INDEX FOR SEGMENTS
I a 1
C TEST FOR VIOLATION
46 IF (J.LE»13) CHEC * VUPS.AND.MASK(1)
IF
-------
13
=STATE(I).OR.MASK(J)
STATE(I):
GO TO 15
14 STATE(I)=STATE(I).ANO..NOT.MASK(J)
15 IF .AND.MASK(J)> GO TO 160
GO TO 16
160 FIRST(I)=FIRST(I).AND..NOT.MASK(J)
PREV(I)=STATE(I)
GO TO 17
C IF NOT FIRST DAY* TEST FOR A CHANCit IN STATt
16 IF(STATEU) .EQ.PRfiV(I) ) 17.99
17 NOAYS(I) = NDAYSU> » 1
GO TO 220
C IF CHANGE IN STATE. INCREMENT TOTAL TIME AND NO. OF VIOLATIONS
99 KK=1
IF(PREVU) .AND.MASK!J) ) KK = ?
KOUNT(I.KK) = KOUNT(I.KK) + 1
NTOT(I.KK) a NTOT(I,KK) »NOAYS
-------
00 501 IR=1«NREA
TEST = MSK * 1
GO TO 271
250 KK = 1
IF (PREVKI) .ANO.MASK(J)) KK=2
KONTS
-------
to
oo
Figure 78. Flowchart for Subroutine QTCAL (Sheet 1 of 2)
-------
to
CD
CJI
Figure 78. Flowchart for Subroutine QTCAL (Sheet 2 of 2)
-------
SUBROUTINE GST APE
As noted in Section VII, Subroutine GST APE must be prepared specifically for
the computer system being used for design analysis. The objective of GSTAPE
is to provide Subroutine EXPDUR with USGS gaging station stream flow data,
available to the user from USGS on magnetic tape. GSTAPE is provided with
the number of the month required by EXPDUR. GSTAPE must locate and store
the flow data from each station required by the design analysis programs for
the corresponding month. The necessary stations are those specified in the
USGS file of the data deck. The data is stored in the array Q(31, 20) and
returned to EXPDUR via COMMON. The first index is the day of the month
and the second index corresponds to the USGS station sequence number (not the
station ID) specified for each necessary station in the USGS file of the data deck.
GSTAPE must also return the month of the year (MON) and the year (NYEAR) to
EXPDUR, both via COMMON.
The user should contact the US Geological Survey, Water Resources Division,
Automatic Data Section, Washington, D.C. for detailed information on the avail-
ability and format of machine processable data for the basin under consideration.
For the Beaver River Basin demonstration case, the data from the 16 gaging
stations in the Basin were provided by the USGS on 7-track magnetic tape, pre-
pared on an IBM 360. Data were stored on the tape by station, with all data for
each station following in sequence by month. The original tape was processed
on Raytheon's UNIVAC 1108 to eliminate extraneous data, reformat to card
image, and produce a tape readable by the Raytheon CDC 6700. Using a FOR-
TRAN IV utility program, a limited amount of data was read from the secondary
tape and stored on a mass storage medium (disk file) in the sequence necessary
for program use: by month, by station. It is the data on mass storage that is
286
-------
accessed by the Subroutine GSTAPE listed below. This listing is provided to
guide the user in preparing a subroutine for use on his equipment. It may not
be necessary for a specific user to go through all the preparatory steps neces-
sary on the Raytheon facilities.
SUBROUTINE GSTAPE
COMMON CAP<40»?0)«VIOLS5(40.20)» NVAR, IMPL<40>.
* IREAD(20>, CONDE<20.2> « CONDI ( 2u» 1«) » OATAI40.94), F INIS (40.3) »
« 0(40.20*5). HWFLOHM10.1?) . INITdO). I0*n(20»20)i MONTHU2J.
» JUNC<10»3). TITLE(20)t OSCAL(5)» TEMPR(4(l). CMAXM(40»5)»
* CMINUX<40»5) « TLMAXWM40.5) » XLC»U), CTI40)
COMMON EPSI<40>« SEPSK40)t XACT<4Q«S)» CMINUM(40i5) « TMINUM(40)»
« CMINOM(40»5) . NDOPT(40)« K20PTC*0>, .MSOC ( 20»?>J) t NSTAT(20)»
XORD(5) «YORnC5) < QT(40»«»)« MSKC*0»5)t NJC(10)t ICPY(10)«
FIRST(40)» STftTE(40)» MOAYS(40)» STflTFl(40)t FTRSTK40)
COMMON KONTSUO«2)t MTOTS(40«?)» nOAYSl (40) < KOUNT<40»2>» P«EV(<»0)
, NTOT(40«2)t PRFVK^O). » TUP(<»0)i
TDOWN(40)t OELTA(40), HTH(40)» CwiNOX (40 ,5) . TMlNUX(^0>»
TMINDX140) .TMTNOM(40)»Xll40»'5»2)tYl(40t5)»DEFC(40).TCOMP(40t2)
COMMON CINT<10»4). TLEN(IO), NSEl><20)» MNPLCY (40 ) « TL (40)
COMMON/BLOCK I/ NR» FINL« IA« II» lOPTi JA. JJ» J0» JU» JX« JYi
» JZ» NJ» NPAR» IRUNt NUM» Ql)P» Nif NT » NSF.AS* TA« AACUP»BBCUPt
*CCUPltCCUP2iCCUP3.CCUP4,CCUP5tCCUP6»CCUP7, CCRON. A3. OBENTH,
• ELEVf CSAT. VALMISt MON. NYEAR. CACT» KK, Nit NINIT* NOX, MZt
» MY« MZY* NJUNC* NTRIBt NREA» NACC» OENOM, ESYS, TOTCSTt CHECK
DIMENSION INDEX ( 1537) ,N (52)
VALMIS=999999.
NMN = NMN » 1
IF (NMN.NE.l) GO TO 20
CALL OPENMS (2. INDEX » 1537.0)
20 00 4 NSTA*ltl6
IJ * NMN » (NSTA-1) « 96
CALL REAOMS(2»N»52,IJ)
00 33 K=l,20
IF (NSTAT(K).EO.N(2)) 30.33
30 NGS » K
NYEAR » N(3)
MON * N(4)
00 34 I * 1.31
NN * I » 5»(1 *
34 CONTINUE
33 CONTINUE
4 CONTINUE
RETURN
END
287
-------
SUBROUTINE COMPT
SUBROUTINE COMPT
COMMON CAP(40»20)*VIOLSS(40*20)t NVAW(20>. IMPL<40)»
* IREAD<20)» CONDEI20.2). CONDI(20. 18)» DATA<40»94)t FINIS(40t9>»
•G<40»20»5)» HWFLOW(10tl2). INITdO), IORn(20t20>» MONTHO2),
• JUNC(10»3)t TITLE(20)» QSCAL<5)» TEMPRC40)* CMAXM<40»5)»
• CMINUX(40*5)* TLMAXM<40»5>t XL<40). CT(4Q>
COMMON EPSK40)* SEPSK40). XACT(40t5)» CMINUM (40.5) . TMINUMUO),
* CMINDM<40»5)» NOOPT(40)» K30PTC»0), NSOC(20»28), NSTAT(20)»
• XORD<5>»YORD<5>. QT(40t9)t MSK(40t5)t NJC(10)t ICPYdO).
» FIRST(40). STATE(40)t NOAYS(40)» STATE1(40>» FIRSTK40)
COMMON KONTS(40.2)» NTOTS(40»2)» NOAYS1(40>« KOUNT(40t2)t PREV(40)
» * NTOT(40t2). PREVK40). Q(31t20)f TS(40,2)t TSS(40»2)t TUP(40)t
* TOOWN(40)t DELTA(40)» HTH(40>f CMJNDX(40,5)t TMINUX(40)f
• TMINOXC40)tTMINOM(40)tXl(40«5.2)tYl(40»5)tOEFC(40),TCOMP(40t2)
COMMON CINT(10»4>, TLEN(IO)* NSEG(20), MNPLCY(40)»TL(40)
COMMON/BLOCK I/ NRt FINLf IA» II* IOPT» JA, JJ« JQt JU» JX* JY»
* JZ* NJ» NPAR* IRON, NUMt QUP* N/» NTt NSEAS. TA»AACUP.BBCUP.
*CCUPl*CCUP2»CCUP3,CCUP4tCCUP5.CCUP6tCCUP7, CCRON* A3» OBENTH,
* ELEV. CSATt VALMIS, MOI^. NYEARt CACTt KK, NI, NINITt NOX, MZt
• MY* MZY* NJUNC* NTRIB* NREA* NACC, OENOMt ESYS* TOTCST* CHECK
COMMON/BUK/MASK(40)
LOGICAL IMPLtMASK,TCOMP
00 3 IR -1»NREA
IF
-------
( ENTER J
CONSIDER
FIRST
REACH
CONSIDER
NEXT
REACH
NO
YES
(RETURN TO "\
CALLER )
MAIN J
COMPUTE EXPECTED
NO. OF VIOLATIONS/
DAY FOR REACH
i
INCREMENT TOTAL
EXPECTED NO. OF
VIOLATIONS/DAY
IS
REACH
IMPLEMENTED
7
YES
SET CHECK
IFTfl*=0
i
SET CHECK IF
Figure 80. Flowchart for Subroutine COMPT
289
-------
SUBROUTINE PPDES
SUBROUTINE PPOES
COMMON CAP<40»20) .VIOLSS (40,20 ) » NVAw(?0), IMPL(40>»
« IREAD<20), CONDE(20,?>» CONDI < 2*J » 1*> » DATA<40»94), FINIS(40,9>,
« 0(40.20.5), HWFLOH<1"»12>, INITdO), IORn(20,20) . MONTHU2),
* JUNCU0.3), TITLEI20), QSCALIS). TEMP9(40)» CM4XM(40,5)»
« CMINUX(40»5) » TLMAXM<40»5) , XLC+0), CT(40)
COMMON EPSK40)* SEPSK40), XACTf+o,5), CMINUM (40.5) , TMINUM(^O),
« CMINOM140.5) » MDOPT<<*0)» K?OPT(4o)» NSOC(20.28)» NSTATI20).
« XORO(5) »YORO(5) » 07(40.9). MSKC+0»5)» NJf(lO). ICPY(IO),
* FIRST (40)* STATE(tO). NDAYS(^O). STATFK40). FIRSTK40)
COMMON KONTS(40t2)t NTOT5 <40 . 2) » NOAYSK40), KOUNT(40.2). PREV(40)
« * NTOT(40.?), PREVK40), Q(31,20>. TSI40.2). TSSC40.2). TUP(40),
« TOOWN(40), OEUTA(40). HTH(40), CMINOX (40,5) « TwlNUX(40),
« TMINOX(40).TMINDM(40)»X1<40»5»2> *Y1 (40,5) .DEFC (40) ,TCOMP(40»2)
COMMON CINT(10,4)» TLEN(IO). NSE(i(20)» MNPLCY (40) »TL (40)
COMMON/BLOCK I/ NR» FINL, IA» II. lOPT, JA, JJ, JQ, JU, JX» JY,
« JZ, NJ» NPAR, IRUN, NUM. QUP, NZ» NT, NSPAS, TAt AACUP.BBCUP.
•CCUPltCCUP2tCCUP3»CCUP4»CCUP5,CCUP6,CCUP7, CCRON, A3, DBENTH,
• ELEV, CSAT, VALMIS, MON, NYEAR, CACT, KK, NI, NINIT. NOX, MZ,
« MY. MZYf NJUNC. NTRIB. NREA. NACC, DENOM, ESYS, TOTCST, CHECK
COMMON/BLOCK2/TIME.NMR.DTYPE.POPT
PRINT 10.NUM
10 FORMAT (IHI.//IOX. 'PARAMETER =».l3,//,iox,»REACH NO. EXP. NO. o
•F EXP. DURATION OF EXP. DURATION OF PREF. SAMPLING»./,23X
•f»VIOLATIONS A VIOLATION A NON-VIOLATION LOCATION.
00 20 I=1.NREA
IF (NOM.LE.13) PSL=DATA(I,2)
IF(NUM.GE.14) PSL=TL(I>
ENV * 365.»TIME*VIOLSS(I»NUM)
PRINT 30.I.ENV »TSS ( I ,2) «TSS ( I . 1 ) »PSL
30 FORMAT ( 10X, I7.6X,E13.5,5X,E13.5.7X,E1 3.5,4X,F8. 1 )
20 CONTINUE
RETURN
END
290
-------
c
ENTER
CONSIDER FIRST
REACH
IS
PARAMETER
COUPLED ?
PREFERRED SAMPLING
LOCATION IS AS
DEFINED IN QTCAL
PREFERRED SAMPLING
LOCATION IS AT THE
HEAD OF THE REACH
CONVERT EXPECTED
NO. OF VIOLATIONS/DAY
TO EXPECTED NO. OF
VIOLATIONS OVER
SYSTEM DURATION
I
PRINT PRELIMINARY
DESIGN INFORMATION
CONSIDER
NEXT
REACH
RETURN TO
CALLER MAIN
Figure 81. Flowchart for Subroutine PPDES
291
-------
SUBROUTINE CAPBLE
SU8ROUTINE
COMMON CAP(40,20) ,VIOLSS(40i20) » NVAH(?0)« IMPLI40),
IREAD<20)» CONDEI20.2). CONDI < 20, 18) , DATA<40.94>, FINIS<40.9>»
G<40.20,5)» HWFLOWdOtl?) » INIT<10), IORD (20,20) « MONTH(12).
JUNC(10»3)» TITLE(20)» QSCAL(5)t TEMPR(4f))« CMAXMU0.5). •
CMrNUX<40»5>. TLMAXM(40.5>, XLC*i»» CTI40)
COMMON EPSK40), SEPSK40), XACT<<+0»5>, CMINUM (40 »5> » TMINUMUO),
CMINDMI40.5) . NDOPT<40)» K?OPT(40), NSOC(20»28), NSTAT(20),
XORD<5) »YORD<5) . OT(40.9), MSK(40,5), NJC(IO). ICPY(IO),
FI»ST(40)» STATE(4Q), NDArS(40)« STATF1(40)» FIRST1UO)
COMMON KONTS<40«2)t NTOTS (40 » 2) * NOAYS1(40>» KOUNT (40 .2) » PREVI40)
• » NTOT(40t2>« PREVK40). Q(31*?0)t TS(40»2)t TSS(40»?)» TUP<40)»
* TDOWN(«*0)» DELTA(40)« HTH(40)» CilINDX (40,5) i TMlNU
* TMINDXI40) »TMINDM(40) iXl(40t5.2)»Yl(40t5) «DEFC(40)
COMMON CINT(10»4), TLfN(lO>t NSE6(20). MNoLCY (40 ) »TL (40 )
COMMON/BLOCK]/ N», FlNLt lAt lit iQPT< JA, JJt JO. JUt JX» JY»
# JZ» NJ» NPARf IRUN. NUM» QUP« N/» NT« NSFAS* T A« AACUP»8BCUP»
»CCUPltCCUP2.CCUP3,CCJP4,CCUP5,CCUP6.CCUP7, CCROM. A3. OBEiMTH*
* F.LEV. CSAT. VALMIS» WON, NYEAK. CACT» KK, NI. NINIT* NOX. MZ.
* MY. MZY. NJUNC. NTRIH* NWEA» NACC. DENOM, ESYS. TOTCST* CHECK
COMMON/BLK/ MASK ( 40 )
COMMON/BLOCK?/TIME.NMH,OTYPE.POPT
LOGICAL IMPL» MASK. MNPLCY.TCOMP
DO 4 1=1.40
IF (IMPL(I).ANO.MASK(NUM) ) 6.4
6 NnOWN=TDOWN(I) /DELTAU)
NUP=TUP(I) /DELTA (I)
IF (MNPLCY(I) ) GO TO )
DELSTR=(NDOWN*OELTA( I) +TUPU)) /(NUP+1)
GO TO ?
1 DELSTR=«»2)
IF (OENM .EO.O.) OENM = 1.
CAP(I»NUM) s TS(I,1) • TS(I»2) * (EO-ED/DENM
GO TO 7
12 CAP(I.NUM) = 1.
GO TO 7
13 CAP(I,NUM) s 0.
7 R«TS(I,2)
DTIMa 36S.»TIME
IF (R.GT.DTIM) R=DTIM
08SN = R / DELSTR
ARG * -EPSKI) /SEPSI(I)
PMISS = ANORM(ARG)
IF
-------
Figure 82. Flowchart for Subroutine CAPBLE (Sheet 1 of 2)
293
-------
COMPUTE EXPECTED
NO. OF SAMPLE
OF A VIOLATION
COMPUTE ARGUMENT
FORANORM
CALL FUNCTION
ANORM
COMPUTE PROBABILITY
OF MISSING A VIOLATION
ON A GIVEN SAMPLE
PROBABILITY = 0
AND
NO. OF SAMPLES
CAPABILITY
= 0
REVISE CAPABILITY
BY THE PROBABILITY
OF MISSING A
VIOLATION
Figure 82. Flowchart for Subroutine CAPBLE (Sheet 2 of 2)
294
-------
FUNCTION ANORM
FUNCTION ANORM(ARG)
DIMENSION 8NORMI 66)
DATA (BNORM(I).1=1.46 )/ .5000,.5199,.5398,.5596*.5793,.5987,
.6179..6368..6554..6736,.6915,.7u88,.7257,.742?,.7580 ,.7734,
.7881, .8023,.8159,.K289..8413..8531..8643,.8749,.8849,.8944,
.9032, .9115,.9192,.9265..933?,.9394,.9452,.9505,.9554,.9599,
.9641, .9678,.9713».9744».9772,.9798,.98?!,.9842,.9861..98787
DATA (BNORM(I).1=47,66 )/ .9893,.9906,.9918,.9929,.9938,.9946.
. 9953. . 9960 » . 9965, . 9970 . . 9974« . 9978. . 9981. . 99B<»» . 9987. .9989 .
.9990..9992*.9993,.9994 /
FIND CUMULATIVE NORMAL DISTRIBUTION OF ARGUMENT
IF 1,2,2
2 I =ARG/.05+1
IF (I.GE.66) GO TO 3
2 = 1-1
ANORM = BNORM(I) +(A*r, - Z «.05>/.05 * <6NORM(I + D- BNORMUM
GO TO 10
3 ANORM = 1.0
GO TO 10
11= -ARG/.05*1
IF (I.GE.66) GO TO 4
Z = 1-1
ANORM = .5000 -(BNORMtI>-.5000> *<-ARG-Z».05>X.05»(BNORM(1*1) •
• BNORM(D)
GO TO 10
4 ANORM = 0.0
10 RETURN
END
PROBABILITY OF
MISSING A
VIOLATION = 0.5
COMPUTE PROBABILITY
OF MISSING A
VIOLATION ACCORDING
TO THE AREA TO THE
LEFT OF THE
ARGUMENT ON THE
NORMAL CURVE
t
/" RETURN TO A
' " ^\ LAKBLt 1
Figure 83. Flowchart of Function ANORM
295
-------
SUBROUTINE RMTTF
SUBROUTINE RMTTF
COMMON CAP(40,20),VIOLSS<40. 20). NVAR(?0), IMPL(40>, IREAO(20)»
• MTTFAO00.2) » MTTFS (300,2) , MTTHA<300» 2) , LIST<4). COST(4),
» MEMBER (lOOf 2) f CSTINC < 100,2) . SUATA(IO), NOATA(IO), MSYS(10.23).
« NSACC64), MINC(5), MPATH(5). MEMB(lo), NsTATE<5>, PFAILUO),
* PCHK(IO), NTRANS(5), LEVEL UO), TRANS (64,64) , AVAIK40)
COMMON COEF<64,64), SRV(40), PROO(65). PROB(65), NST(64)t
• NSFR(64>, EFF<40)
COMMON/BLK/MASK(40)
COMMON/8LOCK2/T I ME »NMR , DT YPE • POPT
LOGICAL LIST. MASK, POPT
REAL MTTFA»MTTRA,MTTFS
DATA END/5HEND /
00 30 K=l»10
00 30 L=1.23
30 MSYS(K,L) =0
00 44 I ~ 1,4
44 LIST.(I) « .FALSE.
IF (POPT) WRITE (6 ,200)
200 FORMAT ( 1H1///,30X,« STATE 1 = OPERATING, STATE 2 = STAND-BY',//,
*10X,«MEANS NO.. MTTFS-1 MTTFS-2 MTTFA-1 MTTFA-2
»MTTRA-1 MTTRA-2*,//)
READ MEAN TIME CARDS FOR ALL MEANS
READ (5,100) OUM1,M,MTTFS(M,1>,MTTFS(M,2),MTTFA(M»1),MTTFA(M»2)»
MTTRA(M,1) *MTTRA(M,2>
FORMAT
IF (DUM1.EO.ENO) 3,2
INTEG = 1 * (M-l) /32
IHIT » M - (INTEG-1)»32
LIST(INTEG) = LIST(INTEG).OR.MASK(I8IT)
IF (POPT) WRITE (6 .300) M.MTTFS (M, 1 ) ,MTTFS (M,2) ,MTTFA (M» 1) ,MTTFA (
1
100
MTTRA(M,1), MTTRA(M,2)
300 FORMAT ( 13X, I3,5X,6(F8.2,4X) )
GO TO 1
3 RETURN
END
Figure 84. Flowchart of Subroutine RMTTF
296
-------
SUBROUTINE LMNTEFF
SUBROUTINE LMNTEFF
COMMON CAP<40.20>.VIOLSSC40»20>* NVAR<20>, IMPL(40), I«EAD(20).
« MTTFAO00.2) » MTTFS(300.2)» MTT«A(300.2), LIST(4)» COSTU),
« MEMBER(100*2)« CSTINC<100.2). SUATA(10)» NOATAUO), MSYS(10.23),
» NSAC<64), M1NC<5)» MPATH(5>, MEMb(lO), NsTATECS), PFAIL<10)»
« PCHK(IO). NTRANSC5). LEVEL(lU). TRANS(64.64), AVAIL(40)
COMMON COEF(64.64), SRV(40), PROU(65)» PR08(65), NST(fe4).
• NSFR(64). EFF<40)
COMMON/BLOCK I/ NR» FINL» lAi lit IOPT. JA, JJ» J0» JU» JX. JY.
« JZi NJ» NPARt IRUN. NUMt QUP» Hit NT« NSFAS» TAtAACUP»8BCUPt
•CCUPltCCUP2tCCUP3»CCUP4,CCUP5,CCOP6.CCUP7, CCRON. A3i DBENTH.
« ELEV» CSAT» VALMIS» MON» NYEAR* CACT» KK, NI, NINIT* NOX» »2t
# MY. MZY. NJUNC. NTRIB. NREA, NACC* OENOM, ESYS, TOTCST, CHECK
COMMON/BLK/ MASK(40)
LOGICAL MNPLCY. MASK. IMPL
DO 40 ITYPE =1.2
CALL LDEFF (ITYPE)
40 CONTINUE
WRITE (NJ.60) MUM
60 FORMAT (1H1,///10X.«PARAMETER NUMBER = *,I3,//X)
00 50 I = l.NREA.
IF (IMPL(I).AND.MASK(NUM)) 45,50
45 TEMP a CAP(I.NUM) » SRV1I) » AVAlC(I)
WRITE (NJ.70) I»CAP(I»NUM).SRV(I).AVAIL(I),TEMP
70 FORMAT(/10X,"REACH NO. = *»I3,* CAP a *,E\3.S.» SURV * ».E13.5,» A
•VAIL * »,E13.5,» ELEMENT EFF. * «»£13.S)
EFF(I) = EFF
-------
( ENTER J
/CALLLDEFF \
( FOR )
\ SURVIVABILITY/
/ CALL LOEFF
( FOR
\ AVAILABILITY
V
i
CONSIDER
FIRST
REACH
IS
REACH
^IMPLEMENTED.
NO
YES
COMPUTE
ELEMENT
EFFECTIVENESS
CONSIDER
NEXT
REACH
±
PRINT
ELEMENT
EFFECTIVENESS
INFORMATION,
INCREMENT TOTAL
EFFECTIVENESS OF
REACH BY
ELEM EFFECTIVENESS
YES
(RETURN TO A
CALLER MAINI/
Figure 85. Flowchart of Subroutine LMNTFF
298
-------
SUBROUTINE LDEFF
SUBROUTINE LDEFF (ITYPE)
COMMON CAP(40»20> . VIOLSS (40 t 20) t NVAR(20), IMPL<40>» IREAO(20)t
• MTTFA(300»2) t MTTFS < 300»2> « MTTHA <30G»?) « LIST(4)i COST<4)»
* MEMBER(100»2>» CSTINC( 100.2) » SOATA(IO). NDATAUO). MSYS(10»23)f
• NSAC(64>. MINC(5)» ^PATH(5)» M£MB(l(i), NsTATE(S). PFAILUO),
« PCHK(10)» NTRANS(S), LEVELIK))* TRANS t64, 64) . AVAIL(40)
COMMON COEF(64*64) « SRV(40)» PROD(65)» PHOHM65), NST(64).
* NSFRI64). EFF(40)
COMMON/BLOCK I/ NR» FINLt IA. lit IOPT» JA, JJ« JQ. JU» JX. JY»
* JZt NJt NPAR» IRUNt NUM« QUP* N^t NT» NSFAS. TAt ACUP« bCUPt
« CUPlt CUP2» CUP3» CUP^t CUP5» CUP6i CUP7, CIRONt A3» OflENTHt
» ELEVt CSAT, VALMlSi MON« NYEAR. CACTt KK, NI, NlNITt N0*i MZ,
* MY» MZY» NJUNC» NTRIBt NHEA» NACC, OENOM, ESYS, TOTCST. CHECK
COMMON/BLK/ MASK (40)
COMMON/BLOCK?/! IME . NMR t DT YPE »POPT
REAL MTTFA.MTTRA«MTTFS
LOGICAL MASK »MI^IP(40)» IMPL 1 1 TPtHOPT
DATA END/5HEND /,S/1HS/«P/1HP/ »OM/lhM/, BLANK/ 1H /
IX = 0
NMAX = 1
DO 70 J = 1.40
70 MIMP(J) = .FALSE.
C ITYPE * I IMPLIES SURVIWAHILITY
C ITYPE = 2 IMPLIES AVAILABILITY
C
C READ ELEMENT DESIGN CARDS
C
IF (.NOT.POPT) GO TO 3
IF (ITYPE. EQ.l) IrfRITE (6 »400) NUrt
IF (ITYPE. EQ. 2) WRITE <6 »410) M^M
400 FORMAT (lHlt///IOX. "PARAMETER NUMBER =»»I3,» ELEMENT RESIGN FOK SU
•RVIVA8ILITY»«/)
410 FORMAT ( 1HU///10X. "PARAMETER NUMBER = «tI3t« ELEMENT DESIGN FOR A
•VAILABILITY*»/)
WRITE (6 *420)
420 FORMAT (10Xt*REACH NO. PATH NO. NORMAL STATUS ELEMENT DESlGN*t
3 READ (5.101) DUMltI,J,IJP(NORM,(SL>ATA(L>»NOATA(L> tL=1.10>
C CHECK IDS
IF (OUM1.EQ.ENO) GO TO 55
IF (POPT) WRITE (6 »430> I i IJP.NOHM. (SDATA (L> »NOATA(L) »L=1» 10)
430 FORMAT (10X»I6.6X,l4,9X,I4»8Xf 10«A1,I3))
C SET CURRENT ELEMENT
4 NCURR = 100»I * J
IF (IX.EQ.O) GO TO 14
C
C CHECK FOR OLD OR NEW ELEMENT
IF (NCURR. NE.NTEST) GO TO 30
C
C TEST FOR IMPLEMENTATION
C
230 IF (IMPL (I). AND. MASK(J)) GO TO 14
MN * I
NN » J
NTEST * NCURR
GO TO 3
30 IX * IX * 1
IF ( IMPL (MN) .AND. MASMNN) ) GO TO 220
GO TO 360
55 IF ( IMPL (MN). AND. MASK(NN)) GO TO 220
GO TO 5
C CHECK FOR PREVIOUS COMPUTATION
220 IF(MIMPIMN) .AND. MASK(NN)) GO TO -*98
299
-------
c
C
C
C
C
C
C
C
C
C
C
SET CHECK
MIMP(MN) = MIMP SUM = SUM + PROd(M)
AVAIL (MM) = SUM
RESET STORAGE
360 DO 35 L=1»NMAX
DO 35 N=l,23
35 MSYS(L«N) = 0
IF (OUM1.EQ.END) GO TO 5
NMAX = 1
GO TO 230
PROCESS AN0 STORE
STORE NORMAL STATUS
\U MSYS(IJP.l) = NORM
IX = IX + 1
CHECK FOR FIRST PATH
IF (IJP.EQ.l) MSYSIIJP.23) = 1
NTEST = NCURR
MN = 1
NN = J
FIRST DATA ELEMENT
M = 1
ELEMENT TYPE
NS = 15
NP = 2
NM = 7
10 IF (SDATA(M)
IF (SOATA(M)
IF (SDATA(M)
GO TO 999
STORE IN 7-14
6 IF (NM.GE.15) GO TO 996
MSYS(IJP»NM) = NDATA(M)
NM s NM * 1
GO TO 9
7 IFINP.GE.7) GO TO 996
MSYS(IJP»NP) =NDATA(M)
NP a NP + 1
NT = NDATA(M)
IF (NT. GT. NMAX) NMAX = NT
GO TO 9
.EQ.OM) GO TO 6
.EO.P) GO TO 7
.EQ.S> GO TO 8
300
-------
8 IF (NS.GE.23) GO TO 996
MSYS(IJP.NS) = NOATA(M)
NS » NS + 1
SET LEVEL OF PATH
NT * NOATA(M)
MSYSCNT.23) * MSYS
STOP
998 PRINT 104
104 FORMAT
-------
CO
o
to
SET IDENTIFIER
FOR CURRENT
ELEMENT
H0 HAVE \ YES
Jill IMPLEMENT!
—^ELEMENTS BEEN
EVALUATED
Figure 86. Flowchart of Subroutine LDEFF
-------
SUBROUTINE SETUP
SUBROUTINE SETUP , IMPLI40). IREAD<20)»
« MTTFAO00.2). MTTFSO00.2) . MTTMA (300.2) , IIST(4), COSTU),
• MEMBERU00.2). CSTINC<100»2)» SUATAUO). NDATAUO). MSYS110.23),
« NSAC<64), MINC<5), MPATH<5>, MEMd(lO), NKTATEC5). PFAlLdO).
« PCHKUO). NTRANS(5). LEVEL(IO), TRANS(64,64) , AVAILUO)
COMMON COEF<64,64). SRV<40), PROO<65), PRo8(b5). NST<64),
« NSFR<64), EFF<40)
COMMON/BLOCKI/ NRt FINL« IA. II» IOPT» JA, JJ» JQ. JU. JX. JY»
« JZ» NJ. NPARt IRUN» NUM, QUP« N2f NT» NSFASt TAtAACUP.BBCUPt
•CCUPltCCUP2tCCUP3tCCUP4.CCUP5tCCUP6.CCUP7, CCRON. A3. 08ENTH.
* ELEV. CSATt VAUMISt MON« NYEARt CACT* KK, NI. NINITt NOXt MZ«
« MY» MZY» NJUNCt NTRIB» NREA. NACC, OENOM, ESYS, TOTCST, CHECK
REAL MTTFA.MTTRA»MTTFS
LOGICAL PFAIL ,PCHK .IMPL.UP
C THIS SUBROUTINE SETS-UP THE TRANSITION MATRIX FOR A SYSTEM
c ELEMENT. BASED ON THE MASTER SYSTEM MATRIX AND THE MTTF
C MATRIX. AS PRESENTLY WRITTEN. IT IS LIMITED TO SIX MEANS
C PER ELEMENT.
C
C INITIALIZE ARRAYS
C
00 2 NSFROM=1»6*
00 I NSTO»1,64
1 TRANS(NSFROM.NSTO)*0.0
2 CONTINUE
DO 3 IJP«1»IJPMAX
3 MEMB *0
C
C DETERMINE NO. OF MEANS ASSOCIATED rtlTH SYSTEM ELEMENT AND
C ESTABLISH MAPS OF MEANS. PATHS. AND LEVELS
C
MMAX<=C
DO 6 IJPM.IJPMAX
LEVEL ( UP )»MSYS (UP.33)
DO 4 IJPM*7,14
IFtMSYS (UPtIJPM).EQ.O> GO TO 4
MMAX«MMAX*1
MINC(MMAX)»MSYS (IJP.IJPM)
MPATH(MMAX)*IJP
4 CONTINUE
DO 5 IJPSM5*22
IJP1»MSYS
-------
NSTAT£s. FALSE.
MAXLEV=0
DO 9 NB!N=1»MMAX
IF(NSTATE(NBIN) .EO.O) GO TO 9
IJP=MPATH(NBIN)
PFAIL(IJP>=.TRUE.
IF(LEVELdJP) .GT.MAXLEV) MAXLEV=LtVEL < UP)
9 CONTINUE
IF(MAXLEV.EO.O) GO TO 13
00 12 LEV=1»MAXLEV
INVLEV=MAXLEV-LEV+1
DO 11 IJP=1»IJPMAX
IF(.NOT.PFAIL«IJP)> r,0 TO 11
IF(LEVELdJP) .NE.INVLEV) GO TO H
IF(PCHK(IJP» GO TO 11
PCHK(IJP)=.TRl)E.
NPP=0
NPPF=0
DO 10 IJPP=3»6
IJP1=MSYS (IJP»IJPP>
IF(IJPl.EQ.O) GO TO 10
PCHM UP 1)=. TRUE.
NPP«NPP*1
IF(.NOT.PFAIL(IJPD) GO TO 10
10 CONTINUE
IF
-------
DETERMINE IF MEANS IS STAND-BY OK OPERATING AND INSERT MTTF
IJP=MPATH(N8IN)
MFAIL*MINC(NBIN)
NORM=MSYS (IJP.l)
IF (NORM.NE.I) GO TO 230
IF (ITP) 211»20
230 NHIP=0
NHIPF=0
DO 19 IJPPs2»6
IJP1*MSYS (IJP»IJPP)
IF(IJPl.EQ.O) GO TO 19
NORPAR=MSYS (IJP1.1)
IF(NORPAR.GT.NORM) GO TO 19
NHIP=NHIP*1
IF(.NOT.PFAIHIJPD) GO TO 19
NHIPF=NHIPF+1
19 CONTINUE
IF (ITP) GO TO 210
IF(NMIPF.GE.NHIP) GO TO 20
TRANS(NSFROM.NSTO) =MTTFS(MFAIL»^>
GO TO 21
20 TRANS (NSFROM»NSTO) = MTTFS TRANS(NSTO.NSFROM) = MTTRA(MFAIL.2)
GO TO 21
211 IF(NTRANS(N8IN).E0.1) TRANS(NSTO»NSFROM) = MTTFA(MFAlL.1)
IF(NTRANS(NBIN).EQ.O) TRANS(NSTO»NSFROM) = MTTRA(MFAlLi1)
21 CONTINUE
IF (ITP) GO TO 220
NSTART=NSFROM+1
TMPSUM=0.0
IF(NSTART.GT.NSMAX) GO TO 23
DO 22 NSTO=NSTART»NSMAX
22 TMPSUM=TMPSUM*TRANS(NSFROM.NSTO)
23 TRANS(NSFROM,NSFROM)=TMPSUM
GO TO ?4
2?0 TMPSUM=0.0
DO 221 NSTO=1»NSMAX
2?1 TMPSUM = TMPSUM » TRANS(NSTOtNSFKOM)
T9ANS(NSFROMtNSFROM)= -TMPSUM
?A CONTINUE
RETURN
END
305
-------
Figure 87. Flowchart of Subroutine SETUP
306
-------
SUBROUTINE LPLACE
SUBROUTINE LPLACE (NSMAX)
COMMON CAP(40.20),VIOLSS(40.20). NVAR(20>, IMPL(40). IREAU<20)»
« MTTFA(300,2)» MTTF5 ( 300.2) . MTTRA < 300 ,2) , LIST(4), COSTC4),
• MEMBER<100,2>, CSTINC( 100, 2> , SDATA(IO). NDATA(10)t MSYS(10,23).
« NSAC<64), MINC<5), MPATH<5), MEMB(10), NsTATE(5>. PFAILUO),
* PCHK(IO), NTRANS(S), LEVELUO). TRANS (64,64) , AVAILUO)
COMMON COEF(64,64), SRVC40), PROD(65) , PR0B(65), NST(64).
* NSFR(64), EFFC40)
COMMON/BLOCK I/ NR, FINL. lAt II. IOPT. JA, JJ, JQ, JU» JX. JY.
• JZ» NJ» NPAR, IRUN. NUM. GUP, NZ. NT, NSF.AS. TA.AACUP.BBCUP,
«CCUP1.CCUP2,CCUP3,CCUP4.CCUP5,CCUP6,CCUP7, CCRON, A3* OBENTH,
« ELEV, CSAT, VALMIS, MON, NYEAR, CACT. KK, NB, NIINIT. NOX. MZ,
* MY, MZY, NJUNC, NTRIB, NREA, NACC, OENOM, ESYS, TOTCST, CHECK
COMMON/BLOCK2/T IME , NMR, OT YPE . POPT
LOGICAL IMPL
REAL MTTFA, MTTRA, MTTFS
C THIS SUBROUTINE IS INTENDED TO PRODUCE THE STATE PROBABILITIES
C THROUGH THE SOLUTION OF THE LAPLACE TRANSFORM EQUATIONS DESCRIBING
C THE TRANSITION MATRIX. AS PRESENTLY WRITTEN, IT WILL HANDLE THE
c MATRICES RESULTING FROM AN EIGHT-UNIT SYSTEM (256 STATES),
DO 8 NS»1,NSMAX
DO 1 INDEX»1,NSMAX
1 COEF(NS, INDEX) *0*0
LEVEL*!
NST <1)»NS
PROO(1)=1.0
2 IF(NST (LEVEL), LE.l) GO TO 4
NSFR (LEVEL) =NST (LEVEL)
3 NSFR (LEVEL) *NSFR (LEVEL) -1
IFCNSFR (LEVEL). EQ.O) GO TO 5
NXsNSFR (LEVEL)
NY»NST (LEVEL)
IF(TRANS(NX,NY)*EQ.O.) GO TO 3
PROD (LEVEL* I )=PROD (LEVEL) *TRANS (NX, NY) /(TOANS (NX, NX) -TRANS (NS.NSI)
LEVEL=LEVEL*1 i««naiNa,nan
NST (LEVEL )=NSFR (LEVEL- 1)
GO TO 2
4 COEF(NS,NS)=COEF(NS,NS)*PROD(LEVE.L)
5 LEVEL=LEVEL-1
IF (LEVEL. GT.O) GO TO 3
PROfl(NS)=COEF(NS,NS)/F:XP (TRANS (NS,NS)»TIMF)
MAXDEX=NS-1
IF(MAXDEX.EQ.O) GO TO 3
DO 7 INOEX=1,MAXOEX
DO 6 JDEX=1,MAXDEX
IF(TRANS(JDEX,NS).E(5,0) GO TO 6
IF(COEFUDEX.IMDEX).EQ.O) GO TO 6
)-TRANS(INOEX, INDEX) )
6 CONTINUE
TTMn
CONTINUE
RETURN
EMD
307
-------
Figure 88. Flowchart of Subroutine LPLACE
308
-------
SUBROUTINE SOLVE
SUBROUTINE SOLVE(NSMAX)
COMMON CAP(«»0.20)tVIOLSSUO»20)» NVAR<20>. IMPL(40)» IREAO(20>»
* MTTFA<300»2). MTTFS(300.2)« MTT«A(300.2)t LIST(4)» COST(4)«
* MEMBER(100.2). CSTINC(100.2), SUATA(IO). NDATA(IO). MSYS(10»23)
• NSAC<64). MINC<5)» MPATK(5>» MEMBOO) , NsTATE<5)» PFA1L(10)»
* PCHK(IO), NTRANS<5), LEVEL(lO). TRANS (64,6*) , AVAILUO)
COMMON COEF<64t64)» SRV(40>* PROO(65)» PRo8(65)» NST(64)t
* NSFR(64)t EFF(40)
COMMON/BLOCK I/ NR* FINLt lAt II* lOPTt JA< JJt JO* JUt JX. JY.
» JZ» NJ. NPAR. IRUN. NUM. QUP. N/t NT. NSEAS. TA.AACUP.BBCUP,
»CCUP1.CCUP2.CCUP3,CCUP4,CCUP5,CCUP6.CCUP7, CCRON. A3. OBENTH,
« ELEV. CSAT. VALMIS, MON, NVEAR. CACT. KK, NI, NINIT, NOX. MZ.
« MY. MZY» NJUNC* NTRIB. N«EA» NACC. DENOM. ESYS. TOTCST. CHECK
DIMENSION MKAREA<256)
REAL MTTFA.MTTRA»MTTFS
LOGICAL IMPL
DO 1 I=1.NSMAX
1 PROB(I) « 0.0
PROB(NSMAX) * 1.
DO 2 I»1.NSMAX
2 TRANS(NSMAX.I) a 1.
CALL LEOTlF(TRANS,l.NSMAX.6A,PROct.2.WKAREA.IER)
RETURN
END
T ENTER J
INITIALIZE
PROBABILITY MATRIX
TO ZERO
SET FINAL PROBABILITY
ELEMENT AND FINAL ROW
OF TRANSITION MATRIX
EQUAL TO 1
CALL LEOT1F-
6AUSSIAN ELIMINATION
ROUTINE WHICH
COMPUTES PROBABILITY OF
BEING IN EACH STATE
(
RETURN TO
CALLERLDEFF
Figure 89. Flowchart of Subroutine SOLVE
309
-------
SUBBOUTINES LEQT1F, LVDATF, LVELMF, and VERTST
The listings for Subroutines LEQT1F, LVDATF, LVELMF and VERTST are not
presented in this report to limit distribution of the IMSL proprietary subroutines.
Interpreted FORTRAN IV source decks for the subroutines are supplied to the
EPA with the total program source deck.
310
-------
SUBROUTINE SYSEFF
SUBROUTINE SYSEFF
COMMON CAP<40«20)»VIOLSS(40»20>» NVAR(?0), IMPL<40>» IREAD(20>»
» MTTFA(300»2) « MTTFS<300.2)» MTTRA<300.2>, LIST(4). COST(4.)»
» MEMBERU00.2). CSTIMC (10012> . SUATAIIO). NOATA(IO). MSYS<10,23>,
* NSAC<64>, MINC(5>» MPATH<5). MEMB(IO). N«;TATE(5>. PFAIL<10),
» PCHK(IO). NTRANS<5)» LEVELUO)* TRANS(64,64), AVAIL(40)
COMMON COEF(t>4.6<»>» SRVI40), PROU165), PROB(65)« NST(64)t
* NSFR<64>* EFF(40>
COMMON/BLOCK I/ NR* FINLt IA* II* IOPT* JA, JJt JO* JUt JX* JY,
« JZt NJ, NPARt IRUN, NUM* OUP* N^t NT* NSFA5» TA»AACUP,B8CUP,
»CCUP1»CCUP2»CCUP3,CCUP4,CCUP5,CCUP6,CCUP7, CCRON* A3» 08ENTH,
* ELEV» CSAT, VALMIS* MON. MYEAR. CACT* KK, NI, NINIT* NOX* MZt
» MY» MZY. NJUNC» NTRTB, NREA* NACC, OENOM, ESYS, TOTCSTt CHECK
COMMON/BLK/ MASK(20)
C
C THIS SUBROUTINE COMPUTES THE TOTAL SYSTEM EFFECTIVENESS FOR THE
C RIVER BASIN MONITORING SYSTEM. REQUIRED INPUT DATA ARE THE
C ELEMENT PRIORITIES* THE VIOLATION DURATIONS. THE ELEMENT
C EFFECTIVENESSES AND THE SYSTEM IMPLEMENTATION SCHEME. AS
C PROGRAMMED? IT WILL HANDLE A MAXIMUM OF 40 SEGMENTS AND 20
C PARAMETERS.
C
LOGICAL IMPLf MASK
ESYS « 0.0
00 10 I'ltNREA
ESYS « ESYS » EFF(I)
10 CONTINUE
ESYS-ESYS/OENOM
PRINT 20.ESYS
ZO FORMAT UH1»//10X,« SYSTEM EFFECTIVENESS = «»E13.5)
RETURN
END
311
-------
c
ENTER
SYSTEM
EFFECTIVENESS
= 0
CONSIDER
FIRST
REACH
CONSIDER
NEXT
REACH
INCREMENT SYSTEM
EFFECTIVENESS BY
TOTAL EFFECTIVENESS
OF REACH
YES
NO
DIVIDE SYSTEM
EFFECTIVENESS BY
TOTAL EXPECTED NO.
OF VIOLATIONS/DAY
I
PRINT
SYSTEM
EFFECTIVENESS
C
RETURN TO
CALLER MAIN
Figure 90. Flowchart of Subroutine SYSEFF
312
-------
SUBROUTINE CALCST
SUBROUTINE CALCST
COMMON CAP(40.20),VIOLSS(40.20). NVAR(?0), IMPL«»0). IREAO<20).
• MTTFA(300,2>. MTTFS(300.2)t MTTHA(300.2), LIST<4>, COSTI4),
» MEMBER(100.2>. CSTINC(100,2), StMTA(lO). NOATA(IO). MSYSU0.23),
• NSAC<64>. MINC<5), MPATH<5). MEMb(lo). N<;TATE(5>. PFAILUO).
* PCHK(IO), NTRANS(S), LEVEL(lO). TRANS (64,64) . AVAILED)
COMMON COEF(64.64), S*V(40), PROO<65), P«oB<65), NST(64).
* NSFR<64), EFFC40)
COMMON/BLOCK I/ NR, FINL. IA, II, 1OPT, JA, JJ, JQ, ju, JX. JY.
• JZ» NJ. NPAR. IRUN» NUM, QUP» N^» NT. NSEAS. TA.AACUP.BBCUP,
•CCUP1«CCUP2»CCUP3,CCUP4,CCUP5,CCUP6,CCUP7, CCRON. A3. DBENTH,
• ELEV. CSAT, VALMIS, MON, NYEAR, CACT. KK, NI, NINIT. NOX, MZ,
» MY. MZY, NJUNC, NTRIB, NREA. NACC, OENOM, ESYS, TOTCST, CHECK
COMMON/BLK/MASK(40)
INTEGER CARD
DATA NEND/5HEND X.NGrtP/bHCOSTG/.NCST/SHCOSTM/
LOGICAL LIST.MASK.TEST
33 TOTCST = 0.0
1 READ (5 ,20U CARD. ION, (COST (N) .*=•!,<.) , IfiROUP
201 FORMAT fA5.I5.4F10.0.15)
IF (CARD.EQ.NENO) GO TO 6
IF (CARD.EO.NGRP) GO TO 3
IF (CARO.EQ.NCST) GO TO 2
GO TO 11
2 IF (IGROUP.LE.O) GO TO 11
MEMBER)ION.1) » IGROUP
CSTINC(IDN.l) » COST(l) »COST(2> • COST(3) -COSTUI
109 FORMAT (EU.2)
GO TO 1
3 IF (IGROUP) 11.4.5
4 If (ION.NE.1) GO TO 11
S MEMBER(ION.2> * IGROUP
CSTINC(IDN»2) a COST(1) » COST(2> «COST(3) -COST(4)
GO TO 1
6 IF (MEMBER(1,2).NE.O) GO TO 11
DO 10 M*l»100
INTEG * I * JM-D/32
IBIT « M - (INTEG-1)«32
TEST » LIST(INTEG).ANO.MASK(IBIT)
IF (TEST) 20.10
20 INDEX » MEMBER(M.I)
IF (INDEX.LE.O) GO TO 11
TOTCST = TOTCST * CSTINC(M.l)
7 IF (MEMBER(INDEX,2)) 10.8,
-------
o
CO
Figure 91. Flowchart of Subroutine CALCST
-------
APPENDIX G
COMPUTER LISTINGS FOR DEMONSTRATION CANDIDATES
Presented in this appendix are the listings of the input data decks and the result-
ing printed output for analysis of the various demonstration candidates. The
listing of the input data deck for each candidate is presented first, followed
immediately by the associated output from the design analysis program. The
exception to this approach is the Preliminary Design case. The output of the
computer analysis for preliminary design is presented in Section Vin. The
entire RIBAM Standard Data Deck is printed only once, since it is the same for
each candidate. The listing of the RIBAM Standard Data Deck is presented first.
315
-------
RIBAM STANDARD DATA DECK
FILE A
ENDFILE A
FILE B
ENOFILE 8
FILE C
FILE C
FILE C
FILE C
FILE C
ENDFILE C
FILE 0
FILE 0
ENOFILE 0
FILE E-l
FILE E-l
FILE 6-1
ENOFILE E
FILE E-2
FILE E-2
FILE E-2
ENOFILE E
FILE E-3
FILE E-3
FILE E-3
ENOFILE E
FILE E-4
FILE E-4
FILE E-4
ENOFILE E
FILE E-5
FILE E-5
FILE E-5
ENDFILE E
FILE E-6
FILE E-f>
FILE E-6
ENDFILE E
FILE F-
FILF. F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-
FILE F-l
01
02
03
04
05
BEAVER RIVER BASIN ANALYSIS - SEPTEMBER 1970
03 02 38 05 1182.
01 02 03 04 05 06 07 08 09 10
11 12
13 14 15 16 17 18 19 20
21 22 23 24 25 26 27 28 29 30 31
32 33 34 35 36 37 38
-1
-2
-3
-4
-5
-6
01
02
01
04
02
03
04
05
01
02
03
01
02
03
01
02
03
01
02
03
01
02
03
01
02
03
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
120.
40.
30.
4.5
1.1
1.1
26.
18.
13.
1.0
15.0
2.0
8.0
7.0
8.0
5.0
5.0
2.0
4.0
5.5
6.5
3.2
2.4
1.4
2.6
2.4
5.6
12.0
3.2
3.0
3.0
1.5
2.0
2.0
1.0
2.0
88.0
87.0
72.0
70.0
62.0
55.0
47.0
42.0
37.0
35.0
12.0
6.5
54.4
51.2
48.8
47.4
44.8
42.4
36.8
24.8
31.0
28.0
25.0
23.5
21.5
19.5
18.5
420.
155.
150.
.7
.15
.04
.004
.2
.1
.1
7.0
7.0
8.5
.119526
.119526
.119526
.119526
.119526
.13443
.13443
.13443
.112
.138
.12412
.12412
.06925
.06925
.069?5
.06925
.06925
.06925
.06925
.06925
.067
.071
.056
.078
.045
.096
.212
.51326
.51326
.51326
.51326
.51326
.41952
.41952
.41952
.406
.303
.38799
.38799
.48418
.48418
.46418
.48418
.46418
.48418
.48418
.48418
.315
.330
.343
.364
.463
.318
.217
0.5
.3
3.0
1.5
.5
1.5
1.5
2.0
1.3
.5
.5
11.0
23.2
123.2
0.0
16.9
88.8
18.45
1.8
1.2
4.2
31.0
19.87
2.0
21.1
126.6
18.9
4.1
16.1
18.2
3.7
.192
0.647
.0508
75.1
124.57
.3
141.2
3.42
.23
2.77
252.0
84.7
.34
208.67
1.09
0.18
316
-------
FILE F-l
FILE F-l
FILE F-l
FILE F-l
CILE F-l
rILE F-l
FILE F-l
FILE F-l
FILE F-l
FILE F-l
FILE F-l
ENDFILE F-l
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
FILE F-2
ENDFILE F-2
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
28
29
30
31
32
33
34
35
36
37
38
01
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
02
01
03
04
05
06
07
08
09
10
11
12
13
14
15
1.0
3.0
8.0
4.5
1.8
7.2
1.8
3.0
4.0
2.0
1.8
4.3
.12
.77
.051
15.7
.4
.9
3.8
2.7
1.23
0.2
3.7
.46
3.1
43.9
2.9
!?6
7.7
0.2
0.23
3.1
1.8
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
16.5
15.5
12.5
4.5
21.6
19.8
12.6
10.8
7.8
3.8
1.8
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
A O
02
02
02
02
02
02
02
02
02
02
2.2
2.3
2.1
1 .9
A . ~
1.7
2.0
C . V
2.3
2.3
4.5
5.0
2.3
2.3
2.7
2.7
2.7
.084
.075
.136
.02959
.05046
.05046
.05046
.00801
.00801
.00801
.00801
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
5.026
.393
.336 4.14
.60960
.54204 9.5
.54204 2.5
.54204 133.8
.67583
.67583
.67583 4.9
.67583
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.969
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
.673
DEER.BEI
All f AU/*I
*LL1 ANC
BELOW Bl
LAKE Mil
MILTON <
WEST BR
pAfll f r\i
t AuLciO
C"WELO
REPUBLI
WARREN
BELOW M
HOWLAND
BELOW S
cuAOnc* ..
5HARPSV
cuAOrvti
362.7
12.3
0.18
5.15
.28
.09
STP
317
-------
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
rILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
FILE F-3
ENOFILE F-3
FILE F-4
FILE F-4
FILF F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILF F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILF F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
rT'.E F-4
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
01
01
0?
2
03
3
04
4
05
5
06
6
07
7
08
8
09
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
100.
180.
100.
90.
120.
120.
60.
100.
100.
100.
60.
150.
150.
150.
100.
50.
50.
150.
100.
60.
100.
60.
100.
60.
60.
200.
100.
2.7
2.7
2.7
2.7
2.7
7.0
5.5
6.0
3.5
4.8
5.0
3.0
2.5
4.5
4.5
2.0
2.1
2.2
2.2
2.5
2.8
3.1
3.1
9.8
-66767,
11926.
7.66
10.8
53.6
2.61
59.3
YANKEE RUN*SHARON ST
HOGBACK RUN
WEST MIDDLESEX STP
DEER CREEK
NESHANNOCK CREEK
MILES ELEC.,STP,MEA
MCDONALD STP»STEEL
GIRARD STP
YOUNGS. SHEET»STEEL
MILL CREEK
YOUNGS. STP,CRAB CR.
DRY RUN
REPUBLIC STEEL
YOUNGS. SHEET*TUBE
LOWELLVILLE STP
NEWCASTLE STP
PENN POWER CO.
WAMPOM STP
.CONNOOUENNESSING CR.
KOPPEL STP
BABCOCK * WILCOX
BEAVER FALLS STP
NEW BRIGHTON STP
0.0007
.27
0.23
0.198
.2
.2
.1
.2
7.2
35.
1136.
.42
32.05
1.25
182.
0.22
17.95
69.44
-319A9.
9.92
73226.
.067
•24683,
318
-------
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILF F-4
FILE F-4
FILE F-4
FILE F-4
FILE F-«
FILE F-4
FILE F-4
FILE F-4
FILE F-4
FILF F-4
FILE F-4
FILF F-4
FILE F-4
FILE F-4
FILf7 F-4
FILE E-4
FILE F-4
FILE F-4
FILE F-4
FILF F-4
FILE F-4
FILE E-4
FILE F-4
FILE F-4
FILF F-4
ENDFILE F-4
FILF F-5
FILE F-5
FILF F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILF F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-S
FILE F-S
FILE F-S
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
22
22
23
23
24
24
25
25
26
2ft
27
?7
?8
28
?9
29
30
30
31
31
32
3?
33
33
34
34
35
35
16
36
37
37
3ft
38
1
01
2
02
3
03
04
4
05
5
06
ft
07
7
08
09
9
10
10
11
11
12
12
13
13
14
14
15
15
16
120.
100.
100.
180.
120.
120.
150.
80.
8P.
150.
150.
150.
150.
150.
to.
100.
190.
150.
ISO.
150.
120.
2.6
4.5
1.4
2.1
1 .4
4 • **
2.1
1.4
22.
1.4
•3-3
cc .
1A
«H
1.4
1.6
1.4
14.
22.
.1
22.
33.
Q
• T
7.45
7.45
2967.
37.7?
!
5?0.
<»20.
3
-------
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
FILE F-5
ENDFILE F-5
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
?6
27
27
28
28
29
29
30
30
31
31
32
32
33
33
34
34
35
35
36
36
37
37
38
38
01
1
02
2
03
3
04
4
05
5
06
6
07
7
08
8
09
9
10
10
?2
.9
?2.
.9
22.
.9
.9
1.0
22.
1.5
22.
22.
1.5
1.5
6.
1.5
22.
22.
1.4
22.
11.
1.4
1.0
41.
1.8
22.
1.4
32.
32.
26.
30.
30.
30.
21.
30.
30.
60.
25.
30.
30.
30.
30.
90.
1.96
-2878.
2539.
4.14
1.23
-3280.
.4
2.28
-94.
-4178.
10428.
-715.
.48
9.78
500.
320.
500.
320.
500.
3?0.
320.
400.
500.
3?0.
500.
500.
4?0.
320.
580.
320.
660.
650.
320.
500.
470.
320.
315.
740.
320.
400.
320.
320.
320.
1.2
6.9
.2
.2
.06
6.9
.1
6.9
.6
6.9
.5
.2
.2
4.0
139.
640.
-30095.
25.4
?5.3
2000.
286339.
17.1
88.5
5.0
26.4
55.2
156942.
57551.
36.9
48.0
67493.
.13
88.
5.0
-183.
2.83
.01
3.0
21.4
1.5
1.5
1.5
21.4
1.5
21.4
1.5
21.4
1.5
1.5
1.5
13.0
0.002
.22
.003
.05
105.
-104.
1.95
320
-------
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILF F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-h
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
FILE F-6
ENOFILE F-6
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30
31
31
32
3?
33
33
34
34
35
35
36
36
37
37
38
38
01
1
02
2
03
3
04
4
05
30.
84.
180.
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30.
30.
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30.
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6.9
.2
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.2
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6.9
.2
6.9
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.8
6.9
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27195.
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. la
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.5
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.5
.5
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.41
1.91
-4145.
-67.
.66
.66
4.08
1.28
-361.
17.3
321
-------
TILE: F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
FILE F-7
5
06
6
07
7
08
8
09
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
?5
25
26
26
27
27
28
28
29
29
30
30
31
31
32
3?
33
33
34
34
35
35
36
36
37
37
38
.071
0.01
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,112
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16665.
5.36
41.0
322
-------
FILE F-7
ENDFILE F-7
FILE F-*,
FILE F-8
FILF F-8
FILE F-8
FILE F-8
FILF F-8
FILF F-8
FILE F-P
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE. F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-«
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILF F-8
FILE F-8
FILF F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILF F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
38
1
1
2
?
3
3
04
04
5
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
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31
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383
-------
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
FILE F-8
ENDFILE F-fl
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
33
33
34
34
35
35
36
36
37
37
38
3B
01
01
02
?
03
3
04
4
05
5
06
6
07
7
08
8
09
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
.03
.?
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7.
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6.
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7.0
7.0
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7.0
7.0
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19.
-5135.
-5840.
-628.
324
-------
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
FILE F-9
ENOFILE F-9
FILE G
ENDFILE
FILE H 1
FILE H ?
FILE H 3
ENDFILE H
FILE
FILE
FILE
FILE
FILE
FILE
FILE
FILE
FILE
FILE
FILE
FILE
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FILE
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FILE
FILE
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FILE
FILE
FILE
FILE
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FILE
FILE
FILE
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FILE
FILE
27
28
28
?9
29
30
30
31
31
32
32
33
33
34
34
35
35
36
36
37
37
38
38
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
22.
22.
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-1656.
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1
29.3
48.3
338.0
325
-------
FILE I
FILE I
ENOFILE I
FILE J
ENOFILE J
FILE K-
FILE K-
FILE K-
FILE K-
FILE K-
FILE K-
FILF K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILF. K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
FILE K-l
ENOFILE K-l
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
37
36
.15 4.0
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
IB
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23.
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.15
.15
.15
.15
.15
.15
.15
.15
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.15
.15
.15
.15
.15
.15
.15
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.15
.15
.15
.15
.15
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.15
.15
.15
.15
.15
.15
.15
.15
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
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,30 6.6 .27
10
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.25
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.25
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.25
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.25
.25
.25
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.3
.3
.3
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.3
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.3
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3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
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1.
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1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
326
-------
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-?
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
FILE K-2
ENOFILE K-2
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
FILE K-3
ENDFILE K-3
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2,0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
.3
.3
.3
.3
.3
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1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
327
-------
PRELIMINARY DESIGN DATA DECK
CONTROL
USGS
USGS
USGS
USGS
USGS
USGS
USGS
USGS
END
T 001030011221011180
1.
60 1,
2.
.5 .25
01 03091500 05 0103030405
02 03094000 07 0607030910
03 03098000 25 212223242526
04 03099500 29 2728293031
05 03103500 13 1314151617181920
06 03105500 33 323334
07 03107500 36 35363738
06 03095500 11 1112
"RIBAM SDD"
CHAR050 I
CHAR0502
CHAR0503
CHAR0504
CHAR0505
CHAR0506
CHAR0507
CHAROS08
CHAR0509
CHAR0510
CHAR0511
CHAR0512
CHAR0513
CHAR0514
CHAR0515
CHAR0516
CHAR0517
CHAR0518
CHAR0519
CHAR0520
CHAR0521
CHAR0522
CHAR0523
CHAR0524
CHAR0525
CHAR0526
CHAR0527
CHAR0528
CHAR0529
CHAR0530
CHAR0531
CHAR0532
CHAR0533
CHAR0534
CHAR0535
CHAR0536
CHAR0537
CHAR0538
END
CHAR1001
CHAR 1002
CHAR 1003
CHAR 1004
CHAR 1005
CHAR 1006
CHAR1007
CHAR1008
CHAR1009
CHAR 1010
CHAR 1011
CHAR1012
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
500.
500.
500.
500.
500.
500.
500.
500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
500.
500.
500.
500.
500.
500.
500.
500.
500.
.005
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.005
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.005
.005
.005
.005
.005
.005
328
-------
CHAR1013
CHAR 10 14
CHAR1015
CHAR1016
CHAR 10 17
CHAR1018
CHAR 10 19
CHAR 1020
CHAR1021
CHAR1022
CHAR1023
CHAR 102*
CHAR1025
CHAR1026
CHAR1027
CHAR 10 28
CHAR 1029
CHAR1030
CHAR 1031
CHAR1032
CHAR 1033
CHAR1034
CHAR1035
CHAR 1036
CHAR1037
CHAR1038
END
CHAR 1101
CHAR1102
CHAR1103
CHAR 1104
CHAR1105
CHAR 11 06
CHAR 1107
CHAR 1108
CHAR1109
CHAR1110
CHAR1111
CHAR1112
CHAR1113
CHAR 111 4
CHAR 11 IS
CHAR 1116
CHAR1117
CHAR1118
CHAR1119
CHAR 11 20
CHAR1121
CHAR 11 22
CHAR 11 23
CHAR 11 24
CHAR 11 25
CHAR 11 26
CHAR 11 27
CHAR 11 28
CHAR 11 29
CHAR 11 30
CHAR1131
CHAR1132
CHAR 11 33
CHAR 11 34
CHAR 11 35
CHAR 11 36
CHAR 11 37
CHAR 11 38
END
.0
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.005
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.005
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0.00
0.0
0.0
0.00
0.0
0.0
0.0
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.1
0.005
0.005
0.005
0.005
0.005
0.005
0.005
O.OOS
0.
0.
0.
0.
0.
0.
0.
0.
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0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.005
329
-------
CHAR1701
CHAR1702
CHAR1703
CHAR 1704
CHAR1705
CHAR 1706
CHAR1707
CHAR1708
CHAR 1709
CHAR1710
CHAR1711
CHAR1712
CHAR1713
CHAR1714
CHAR1715
CHAR1716
CHAR1717
CHAR1718
CHAR1719
CHAR1720
CHAR 1721
CHAR1722
CHAR 1723
CHAR 1724
CHAR 1725
CHAR 1726
CHAR 1727
CHAR 1728
CHAR1729
CHAR 1730
CHAR1731
CHAR1732
CHAR1733
CHAR 1734
CHAR1735
CHAR1736
CHAR1737
CHAR1738
END
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
CANDIDATE 1. 0 DATA DECK
CONTROL F 00102001122101
USGS
USGS
USGS
USGS
USGS
USGS
USGS
USGS
END
01
02
03
04
05
06
07
08
03091500
03094000
03098000
03099500
03103500
03105500
03107500
03095500
05
07
25
29
13
33
36
11
"RIBAM SDD"
CHAR0501
CHAR0502
CHAR0503
CHAR0504
CHAR0505
CHAR0506
CHAR0507
CHAR0508
CHAR0509
CHAR0510
CHAR0511
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
11?0 1. 60
010^030405
0607080910
212223242526
2728293031
13l4l516171819
-------
CHAR0512
CHAR0513
CHAR0514
CHAR0515
CHAR0516
CHAR0517
CHAR051B
CHAR0519
CHAR0520
CHAR0521
CHAR0522
CHAR0523
CHAR0524
CMAR0525
CHAR0526
CHAR0527
CHAR0528
CHAR0529
CHAR0530TT
CHAR0531
CHAR053?
CMAR0533
CHAR0534
CHAR0535
CHAROS36
CHAR0537
CHAR0538
END
CHAR1001
CHAR1002
CHAR1003
CHAR1004
CHAR1005
CHAR1006
CHAR1007
CHAR1008
CHAR1009
CHAR1010
CHA91011
CHAR1012
CHAR1013
CHAR1014
CHAR1015
CHAP1016
CHAR1017
CHAR101B
CHARIOT
CHAR1020
CHAR1021TT
CHAR1022
CHAR1023
CHAR 1024
CHAR1025
CHAR1026
CHAR 1027
CHAR1028
CHAR1029
CHAR 10 30
CHAR1031
CHAR 10 32
CHAR1033
CHAR 10 34
CHAR1035
CHAR1036
CHAR1037
CHAR1038
END
1500.
500.
500.
500.
500.
500.
500.
500.
500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
1500.
500.
500.
500.
500.
500.
500.
500.
500.
500.
.005
.005
.005
.005
.005
.005
.005
.005
.005
.005
.005
.005
.0
.0
.0
.0
.0
.0
.0
.0
.005
.005
.005
.005
.005
.005
.005
.005
.005
.0
.0
0.00
0.0
0.0
0.00
o.o
o.o
0.0
7.0
11.0
15.0
15.0
365.
7.0
30.6
0.05
0.10
365.
0.
331
-------
CHAR1101
CHAR1102
CHAR1103
CHAR1104
CHAR1105
CHAR1106
CHAR1107
CHARHOfl
CHAR1109TT
CHAR1110
CHAR1111
CHAR1112
CHAR1113
CHAR1114
CHAR1115
CHAR1116
CHAR1117
CHAR1U8
CHAR1119
CHAR1120
CHAR1121TT
CHAR 11 22
CHAR 11 23
CHAR 11 24
CHAR 11 25
CHAR112*
CHAR 11 27
CHAR 1128
CHAR 11 29
CHAR1130TT
CHAR1131
CHAR 11 32
CHAR1133
CHAR 11 34
CHAR1135
CHAR 11 36
CHAR1137
CHAR 11 38
END
CHAR1701
CHAR1702TT
CHAR1703
CHAR1706
CHAR1705
CHAR1706
CHAR1707
CHAR1708
CHAR170«J
CHAR1710
CHAR1711
CHAR171?
CHAR1713
CHAR171<»
CHAR1715
CHAR1716
CHAR1717
CHAR1718TT
CHAR1719
CHAR1720
CHAR1721TT
CHAR1722
CHAR1723
CHAR1724
CHAR1725
CHAR1726
CHAR1727
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.005
0.005
0.005
0.075
0.005
0.005
0.005
0.005
0.005
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
7.
37.0
.001 .002
365.
o.
30.6 0.001 0.002 365.
0.
11.0 0.001 0.002 365.
82.5
0.02 0.10
365. 0.
36.8
30.6
0.02 0.10 365.
0.0?
0.10 365.
0.
332
-------
CHAR1728
CHAR1729
CHAR1730
CHAR1731
CHAR1732
CHAR1733
CHAR1734
CHAR1735
CHAR1736TT
CHAR1737
CHAR1738
END
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
END
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
01
02
03
04
05
06
07
OH
09
10
11
12
13
14
15
16
17
18
19
30
30
30
30
30
30
21
21
21
21
21
21
09
09
09
21
21
21
30
30
30
09
09
09
21
21
21
30
30
05
05
05
05
05
05
10
10
10
10
10
10
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
0.2
0.01
0.01
0.2
0.02
0.2
0.01
0.01
0.2
0.2
0.01
0.2
0.2
0.0?
0.2
0.01
0.2
0.2
0.2
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
7.0 4.
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.1
1S02S03
1M10M13P03
2M15M16P02
1S02S03
1M10M13P03
2M15M1BP02
1S02S03
1M01M02P03
?MO*M07P02
1S02S03
1M01M02P03
2M06M07P02
1MQSS02S03
1M01M03P03
2M06M08P02
1S02S03M05
1M01M03P03
2M06M08P02
1M14S02S03
1M10M11P03
2M15M16P02
1MOSS02S03
1M01M03P03
2M06M08P02
1S02S03M05
1M01M03P03
2M06MQ8P02
1M14S02S03
1M10M11P03
0
2.0
2.0
2.0
4.0
4.0
2.0
2.0
2.0
4.0
2.0
2.0
4.0
4.0
4.0
2.0
2.0
4.0
4.0
4.0
0.02
1.0
0.01
0.01
o!i
1.0
0.01
0.01
i!o
0.01
0.1
1.0
.01
1.0
0.10
365.
365.
365.
365.
52.
365.
365.
365.
365.
365,
365.
365.
365.
52.
365.
365.
365.
365.
122.
365.
365.
365.
36S.
365.
52.
365.
365.
365.
365.
36b.
365.
365.
365.
52.
365.
365.
365.
365.
122.
333
-------
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
END
*
30
02
02
02
18
18
18
21
21
21
36
36
36
02
02
02
18
18
18
?1
21
21
36
36
36
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
11 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
40000.
10000.
?0000.
5000.
10000.
20000.
5000.
5000.
3000.
400.
400.
600.
1500.
3000.
400.
400.
600.
3000.
400.
600.
300.
1500.
3000.
400.
600.
300.
1500.
?M15M16P02
1SOPS03M19
1M01M04P03
2M06MQ9P02
1S02S03
1M10M12P03
2M15M17P02
1S02S03
1MQ1M04P03
2M06M09P02
1S02SQ3
1M10M12P03
2M1SM17P02
1S02S03M19
1M01M04P03
2MOSM09P02
1S02S03
1M10M12P03
2M15M17P02
1S02S03
1M01M04P03
2M06M09P02
1S02S03
1M1GM12P03
2M1SM17P02
0.
sooo.
4500.
2500.
5000.
4500.
1500.
1500.
5000.
500.
500.
10.
50.
1000.
50.
50.
10.
5000.
500.
10.
10.
SO.
1000.
50.
10.
10.
100.
a.
0.
(000.
500.
0.
1000.
250.
250.
400.
0.
0.
100.
0.
400.
u.
0.
100.
400.
0.
100.
50.
0.
400.
0.
100.
50.
100.
0.
0.
?oooo.
4500.
0.
20000.
4500.
4500.
2000.
0.
0.
300.
IbOO.
?000i
0.
0.
300.
2000.
0.
300.
ISO.
1500.
2000.
0.
300.
150.
1000.
0
1
2
2
1
5
5
5
4
4
4
4
3
4
4
4
4
7
7
7
7
6
8
8
8
8
4
334
-------
CANDIDATE 1. 0 RESULTS
DESIGN TYPE * F SYSTEM OUR. « 1.00 NO. OF MONTHS « 60 FLO* SCALING FACTORS « 1.0 5.0 2.0 .5 .3
STA. NO. STA. I.D.
SEG. NO. SEC. ASSOCIATION
1
5
3091500
"IflQiftA A
JU T*»V v v
3098QOQ *~ j
5
3G
3103500
•» 1 ACCAA
y 11 nTCAA
8
PARAMETER
REACH NO.
1
2
3
4
5
6
7
8
9
10
11
12
13
10
15
16
17
18
19
20
21
22
23
24
25
26
27
3095500
NUMBER
IMPL.
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
r
F
F
F
F
F
3 S
MN. PLCY
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
f
r
r
r
f
r
F
F
F
F
F
K T
13
33
36
11
CT
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
500.000
500.000
500.000
500.000
500.000
500.000
500.000
500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1
1314151617181920-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
1 1 12-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
DFLTA
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
IMPL. LOC.
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
EPS I
-o.ooo
-0.000
-0.000
-o.ooo
-0.000
-o.ooo
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
TUP
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TDOWN
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
335
-------
26 f f 1500.000
?« F F 1500.000
30 T T 500.000
31 F F 500.000
3? F F 500.000
33 F F 500.000
3* F F 500.000
35 F F 500.000
36 F F 500.000
37 F F 500.000
38 F F 500.000
PARAMETER NUHBER « 10
»E»CM MO. im>L. MN. PLCr. CT
1 F F ,oos
IF f .OOS
3 F F .005
* F F .OOS
S F F .flOS
» F F .OOS
' F F .OOS
• F F .OOS
« F F .OOS
10 F F .OOS
II F F .OOS
1? F F .005
13 F F 0.000
I* f F 0.000
IS F F 0.000
16 F F 0.000
17 F F 0.000
11 F F 4.000
i1* f f o.ooo
20 F F 0.000
?l r T .005
?? F F .005
?3 F F .005
;»» F f .005
?S F F .005
?6 F F .005
?7 F F .005
^» F F .005
'» F F .005
30 F F 0.000
-0.00
-0.00
T.OO
-0.00
-0.00
-o.oo
-o.oo
-o.oo
-o.oo
-0.00
-0.00
OCLT*
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
T.OO
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
11.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
INPL. LOC.
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
30.60
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.000
-0.000
15.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
EPS I
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
.050
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
15.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
.100
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.00
-0.00
365.00
-0.00
-0.00
-o.oo
-o.oo
-o.oo
-0.00
-0.00
-0.00
TOP
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
3*5.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TOOMN
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
336
-------
31
32
33
3*
35
36
37
38
PARAMETER
REACH NO.
1
2
3
-------
3ft F
37 F
38 F
PARAMETER NUMBER
REACH NO. IMPL.
1 F
2 T
3 F
4 F
5 F
6 F
7 F
8 F
9 F
10 F
11 F
12 F
13 F
1* F
15 F
16 F
17 F
18 T
19 F
20 F
21 T
22 F
?3 F
2* F
25 F
26 F
27 F
28 F
29 F
30 F
31 F
32 F
33 F
34 F
35 F
36 T
37 F
38 F
F .005
F .005
F .005
= 17
MN. PLCY. CT
F 5.000
T 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F 3.000
F 5.000
F b.OOO
F 5,000
F 5.000
T b.OOO
F 3.000
F 5.000
T 5.000
F 5.000
F 5.000
F 5.000
F 5.000
F S.OOO
F 5.000
F 3.000
F 5.000
F 5.000
F 5. QOO
F 5.000
F 5.000
F 5.000
F 5.000
T 5.000
F 5.000
F 5.000
-0.00
-0.00
-0.00
DELTA
-0.00
45.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-o.oo
-0.00
-o.oo
-o.oo
-0.00
-o.oo
-o.oo
-o.oo
-o.oo
-0.00
7.00
-0.00
-0.00
7.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.oo
-o.oo
-o.oo
-0.00
-0.00
7.00
-0.00
-0.00
-0.00
-0.00
-0.00
IMPL. LOC.
-0.00
82.50
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
36.80
-0.00
-0.00
30.60
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.i/o
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
4.00
-0.00
-0.00
-0.000
-0.000
-0.000
EPSI
-0.000
.020
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.020
-0.000
-0.000
.020
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.020
-o.ooo
-0.000
-0.000
-0.000
-0.000
SEPSI
-o.ooo
.100
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
.100
-0.000
-0.000
.100
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
.100
-0.000
-0.000
-0.00
-0.00
-0.00
TUP
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
365.00
-0.00
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
TOOWN
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
•0.00
-0.00
338
-------
MEANS NO.
1
2
3
4
5
6
7
B
9
10
11
12
13
1*
15
16
17
U
19
STATE 1 " OPERATING. STATE 8 « STAND-BY
MTTFS-1 MTTFS-2 MTTFA-1 MTTFA-2 MTTRA-1
.20
.01
.01
.20
.02
.20
.01
.01
.20
.ZO
.01
.20
.20
.02
.20
.01
.20
.20
.20
.01
.01
.01
.01
.02
.01
.01
.01
.01
.01
.01
.01
.01
.02
.01
.01
.01
.01
.10
2.00
2.00
2.00
4.00
4.00
2.00
2.00
2.00
4.00
2.00
2.00
4.00
4.00
4.00
2.00
2.00
4.00
4.00
4.00
1.00
.01
.01
2.00
.10
1.00
.01
.01
2.00
1.00
.01
2.00
2.00
.10
1.00
.01
2.00
2.00
1.00
365.00
365.00
365.00
365.00
52.00
365.00
365.00
365.00
365.00
365.00
365.00
365.00
365.00
S2.00
365.00
365.00
365.00
365.00
122.00
MTTRA-2
365.00
365.00
365.00
365.00
52.00
365.00
365.00
365.00
365.00
365.00
365.00
365.00
365.00
52.00
365.00
365.00
365.00
365.00
122.00
PARAMETER NUMBER * 5 ELEMENT DESIGN FOR SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
30
30
30
1 S 2S 3 -0 -0 -0 -0 -0 -0 -0 -0
1 M10M13P 3 -0 -0 -0 -0 -0 -0 -0
2 MJSM18P 2 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER * S ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
***
*•*
30 1 1
30 2 1
30 3 2
M S LCUERTSTI *•* WARNING
M S L(UERTST) ••• WARNING
S 2S 3 -0 -0 -0 -0 -0 -0 -0 -0
M10M13P 3 -0 -0 -0 -0 -0 -0 -0
M15M18P 2 -0 -0 -0 -0 -0 -0 -0
LUDATF 2
LEQT1F 2
PARAMETER NUMBER = 5
REACH NO. » 30 CAP = 3.581i2E-o3 SURV = 9.35765E-01 AVAIL • 9.99801E-01 ELEMENT EFT.
3.35068E-03
PARAMETER NUMBER • 10 ELEMENT DESIGN FOR SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
21
21
1 S 2S 3 -0 -0 -0 -0 -0 -0 -0 -0
1 M 1M 2P 3 -0 -0 -0 -0 -0 -0 -0
2 M 6M 7P 2 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER » 10 ELEMCNT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
•*•
21
21
21
M S L(UERTST)
M S L(UERTST)
WARNING
WARNING
1 S 2S 3 -0 -0 -0 -0 -0 -0 -0 -0
1 M 1M 2P 3 -0 -0 -0 -0 -0 -0 -0
2 M 6M 7P 2 -0 -0 -0 -0 -0 -0 -0
LUDATF 2
LEQT1F 2
PARAMETER NUMBER = \n
REACH NO. * 21 CAP * 1.73213E-02 SURV * 9.79116E-01 AVAIL * 9.99925E-01 ELEMENT EFF.
1.69583E-02
339
-------
PARAMETER NUMBER = 11 ELEMENT DESIGN FOR SURVIVABILITY
CEACH NO. PATH NO. NOrtMAL STATUS ELEMENT DESIGN
**«
**«
• «*
*««
»••
»•*
9
9
9
ai
21
21
30
30
30
PARAMETER
REACH NO.
9
9
9
21
I M S LIUERTST)
I M S LIUERTST)
21
21
10
I M S LIUERTST)
I M S LIUERTST)
30
30
I M S LIUERTST)
I M S LIUERTST)
1
2
3
1
2
3
1
2
3
NUMBER = 1 1
1
1
2
1
1
2
1
1
2
M SS 2S 3 -0 -0 -0 -0 -0 -0 -0
M 1M 3P 3 -0 -0 -0 -0 -0 -0 -0
M 6M 8P 2 -0 -0 -0 -0 -0 -0 -0
S 2S 3M 5 -0 -0 -0 -0 -0 -0 -0
M IM 3P 3 -o -0 -0 -0 -0 -0 -0
M 6M 8P 2 -0 -0 -0 -0 -0 -0 -0
Ml*5 25 3 -0 -0 -0 -0 -0 -0 -0
M10M11P 3 -0 -0 -0 -0 -0 -0 -0
M15M16P 2 -0 -0 -0 -0 -0 -0 -0
ELEMENT DESIGN F03 AVAILABILITY
PATH NO. NORMAL STATUS
1
?.
3
1
•«• WARNING
«•• WARNING
2
3
1
••• WARNING
••* DOWNING
2
3
•«• WARNING
••• WARNING
1
1
2
1
1
2
1
1
7
ELEMENT DESIGN
M SS 2S 3 -0 -0 -0 -0 -0 -0 -0
M IM 3P 3 -0 -0 -0 -0 -0 -0 -0
M 6M «P 2 -0 -0 -0 -0 -0 -0 -0
S 2S 3M S -0 -0 -0 -0 -0 -0 -0
LUDATF ?
LEOT1F 2
M IM 3P 3 -0 -0 -0 -0 -0 -0 -0
M 6M 8P 2 -0 -0 -0 -0 -0 -0 -0
M14S ?S 3 -0 -0 -0 -0 -0 -0 -0
LUOATF 2
LEQUF 2
M10M11P 3 -0 -0 -0 -0 -0 -0 -0
M15M16P 2 -0 -0 -0 -0 -0 -0 -0
LUDATF 2
LEOT1F 2
PARAMETER NUMBER * 11
REACH NO. - 9 CAP * 8.83016E-03 SURV »
REACH NO. « SI CAP = 7.*233«tE-0 5.0410SE-03
PARAMETER NUMBER * 17 ELEMENT DESIGN FOR SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
z
2
2
18
16
18
21
21
21
36
36
36
S 2S 3M19 -0 -0 -0
M IM «P 3 -0 -0 -0
M 6M 9P 2 -0 -0 -0
S 25 3 -0 -0 -0 -0
M10M12P 3 -0 -0 -0
M15M17P 2 -0 -0 -0
S 25 3 -0 -0 -0 -0
M IM 4P 3 -0 -0 -0
M 6M 9P 2 -0 -0 -0
S 25 3 -0 -0 -0 -0
M10M12P 3 -0 -0 -0
M15M17P 2 -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
PARAMETER NUMBER » 17 ELEMENT DESIGN FOrt AVAILABILITY
REACH NO, PATH NO. NORMAL STATUS ELEMENT DESIGN
2
2
2
18
'••IMS LIUERTST)
'••IMS LIUERTST)
18
18
21
••IMS LIUERTST)
••IMS LIUERTSTI
21
21
36
1
2
3
1
••• WARNING
••• WARNING
2
3
1
••• WARNING
••• WARNING
2
3
1
1
1
2
1
1
2
1
1
2
1
s as 3Mi9 -o -o -o
M IM 4P 3 -0 -0 -0
M 6M 9P 2 -0 -0 -0
S 2S 3 -0 -0 -0 -0
LUOATF 2
LEOT1F 2
M10MI2P 3 -0 -0 -0
M15M17P 2 -0 -0 -0
S 2S 3 -0 -0 -0 -0 -
LUOATF ?
LEOT1F 2
M IM 4P 3 -0 -0 -0
M 6M
-------
••• I M S L(UERTST) *•• EARNING
•*• I M S UUEBTST) *•• WARNING
36 2
36 3
••• IMS L(UERTST) *•• WARNING
••• I M S L
-------
CHAR0527
CHAR0528
CHAR0529
CHAR0530TT
CHAR0531
CHAR053?
CHAR0533
CHAR0534
CHAR0535
CHAR0536
CHAR0537
CHAR0538
END
CHAR1001
CHAR1002
CHAR1003
CHAR1004
CHAR1005
CHAR1006
CHAR1007
CHAR1008
CHAR100Q
CHAR1010
CHAR1011
CHAR1012
CHAR1013
CHAR1014
CHAR101S
CHAR1016
CHAR1017
CHAR1018
CHAR1019
CHAR1020
CHAR1021TT
CHAR1022
CHAR1023
CHAR1024
CHAR1025
CHAR1026
CHAR1027
CHAR102H
CHAR1029
CHAR1030
CHAR1031
CHAR1032
CHAR1033
CHAR 10 34
CHAP1035
CHARlOJh
CHAR1037
CHAR1038
END
CHAR1101
CHAR1102
CHAR1103
CHAR1104
CHAR1105
CHAR1106
CHAR1107
CHARllOfl
CHAR1109TT
CHAR1110
CHAR1111
CHAR1112
CHAR1113
CHAR11U
1500.
1500.
1500.
500.
500.
500.
500.
500.
500.
500.
500.
500.
.005
.005
.005
.005
.005
.005
.005
.005
.005
.005
.005
.005
.0
.0
.0
.0
.0
.0
.0
.0
.005
.005
.005
.005
.005
.005
.005
.005
.005
.0
.0
0.00
0.0
0.0
0.00
0.0
0.0
0.0
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.005
0.005
0.0417
12.5
15.0
60.0
6.75
0.25
0.0417
31.0
0.02
0.15
6.75
0.25
0.0417
37.00
.001
.005
6.75
0.25
342
-------
CHAR1115
CHAR1116
CHAR 111 7
CHAR1118
CHAR 11 19
CHAR 11 20
CHAR1121TT
CHAR1122
CHAR1123
CHAR 1124
CHAR 11 25
CHAR1126
CHAR1127
CHAR 11 28
CHAR 11 29
CHAR1130TT
CHAR1131
CHAR 11 32
CHAR 11 33
CHAR1134
CHAR1135
CHAR 11 36
CHAR 11 37
CHAR1138
END
CHAR1701
CHAR1702TT
CHAR1703
CHAR170*
CHAR1705
CHAR1706
CHAR1707
CHAR1708
CHAR1709
CHAR1710
CHAR1711
CHAR1712
CHAR1713
CHAR1714
CHAR1715
CHAR1716
CHAR1717
CHAR1718TT
CHAR1719
CHAR1720
CHAR1721TT
CHAR1722
CHAR1723
CHAR172«*
CHAR1725
CHAR1726
CHAR1727
CHAR1728
CHAR 1729
CHAR1730
CHAR1731
CHAR 1732
CHAR1733
CHAR1734
CHAR173S
CHAR1736TT
CHAR1737
CHAR 1738
END
MTTF 21
MTTF 22
0.005
0.005
0.005
0.005
0.005
0.005
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.005
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
.2
.2
0,0417
0.0417
0.0417
0.0417
0.0417
0.0417
.01
.01
31*0
,001
.005
6.75
0.25
12. 5
,001
.005
6.75 0.25
82.b
0.05
0.15
6.75 0.25
36.8 0.05 0.15 6.75 0.25
31.0 O.OS 0.15 6.75 0.25
7.B
0.05
0.1S
6.75
0.25
5.
5.
3b5.
365.
100.
100.
365.
365.
343
-------
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
END
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
EMD
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
41
42
43
44
50
51
53
30
30
30
30
30
30
30
30
30
30
21
21
21
21
21
?1
09
09
09
21
21
21
30
30
30
30
30
09
09
09
?\
21
21
30
30
.2
.2
.2
.01
.2
.01
.2
.2
.2
.2
.2
.2
.2
.2
.01
.2
.2
.01
.01
.2
.2
.2
.2
,2
.01
05
05
05
05
05
05
OS
05
05
05
10
10
10
10
10
10
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
1
2
3
4
5
1
2
3
4
5
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
4
5
1
2
3
1
2
3
1
2
.01 6.
.')! 5.
.01 3.
.01 2.
.01 5.
.01 3.
.01 3.
.01 6.
.01 6.
.01 6.
.01 5.
.01 5.
.01 3.
.01 3.
.01 2.
.01 3.
.01 5.
.01 52.
.01 3.
.01 3.
.01 5.
.01 5.
.01 3.
.01 5.
.01 2.
1M22S02S03
!M<50M2ftP03
?M?9P02S04S05
2M26P05
3M53P04
iM2?S02S03
1M50M28P03
2M29P02S04S05
2M26P05
3M53P04
1M31S02S03
1M44M41M42P03
2M43M3HP02
1M31S02S03
1M44M41M42PU3
2M43M3SP02
1$0?S03M32
1P03M40M41M42
2P?>?M39M3rt
1M31S02S03
1M44M41M<*2^<)3
2M43M38PO?
1M23S02S03
1MSOM2«P03
2M?^PQ2S04Su5
?w?6P05
3M53P04
1S02S03M32
1P03M40M41M<»2
2Po?M39M39
1M33SO'S03
1M44M41M42P03
2M43M3HP02
1M23S02S03
1M50M2HP03
365.
365.
.3
.5
1.
3.
.3
365.
365.
365.
365.
365.
.3
.3
.5
.3
1.
52.
3,
.3
1.
1.
.3
1.
.5
100.
100.
100.
365.
137.
365.
100.
100.
100.
100.
100.
100.
100.
100.
365.
100.
137.
9999.
365.
100.
137.
137.
100.
137.
365.
365.
365.
45.
365.
137.
365.
45.
365.
365.
365.
365.
365.
45.
45.
365.
45.
137.
9999
365.
45.
137.
137.
45.
137.
365.
344
-------
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
COSTG
COSTS
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
30
30
30
02
02
02
18
18
IB
18
18
21
21
21
36
36
36
36
36
02
02
02
18
18
18
18
18
21
21
21
36
36
36
36
36
1
2
3
4
5
6
7
a
9
10
11
12
13
21
22
23
2*
25
26
27
28
29
31
32
33
34
35
36
11
11
11
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
40000.
10000.
20000.
5000.
1000.
1000.
1000.
10000.
20000.
5000.
1000.
1000.
1000.
1200.
800.
3500.
1200.
1200.
3500.
7000.
45000.
1200.
3500.
3500.
3500.
1200.
1200.
1200.
3
4 '
5
1
2
3
1
2
3
4
5
1
2
3
1
2
3
4
5
1
2
3
1
2
3
4
5
1
2
3
1
2
3
4
5
2M29P02S04S05
2MP6P05
3M53P04
1S02S03M34M38
1P03M37
2P02M36
1M21S02S03
1M?7M28P03
2MP5S04S05P02
2M26P05
3M53P04
1M3SS02S03
1M44M41M42P03
2M43M38P02
1M24S02S03
1M52M28P03
2M51P02S04S05
2M26P05
3M53P04
1S02S03M34M38
1P03M37
2P02M36
1M21S02S03
1M27M28P03
2M25S04S05P02
2M26P05
3M53P04
1M35S02S03
1M44M41M42P03
2M43M38P02
1M24S02S03
1M52M28P03
2M51P02S04S05
2M26P05
3M53P04
0.0 0.0
5000. 0.0
1000. 0.0
2500. 500.
150. 350.
150. 350.
150. 350.
5000. 0.0
1000. 0.0
2500. 500.
150. 350.
150. 350.
150." 350.
200. 200.
100. 50.
300. 350.
200. 200.
20. 50.
300. 350.
400. 1000.
500. 1000.
20. 50.
300. 350.
300. 350*
300. 350.
200. 200.
200. 200.
20. 50.
o.u
0.0
20000.
4SOO.
ISO.
150.
ISO.
0.0
20000.
4500.
150.
ISO.
150.
900.
600.
1300.
900.
900.
1800.
5500.
35UOO.
900.
1600.
1800.
moo.
900.
900.
900.
0
1
2
2
2
2
2
1
8
8
8
8
8
11
12
12
13
11
10
11
9
12
7
6
7
5
7
5
345
-------
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
END
#
37
38
39
40
41
4?
4.1
44
50
51
5?
53
1800.
3000.
1200.
4500.
0.
40000.
1200.
4500.
7000.
1200.
7000.
3000.
20.
5000.
20.
400.
12000.
400.
20.
400.
400.
20.
400.
5000.
f>0.
400.
50.
900.
0.
1000.
50.
900.
1000.
50.
1000.
400.
1000.
?UOO.
300.
3800.
0.
3SOOO.
900.
3800.
5500.
9UO.
5SOO.
?(JOO.
5
4
6
6
3
3
7
7
12
13
13
13
CANDIDATE 2.0 RESULTS
DESIGN TYPE » F SYSTEM DUR.
1.00 NO, OF MONTHS
60 FLO* SCALINS FACTORS * 1.0 5.0 2.0
.3
STA. NO.
STA. I.D.
SEr,. NO.
SEG. ASSOCIATION
1
2
3
4
5
6
7
a
3041500
309*000
3098000
3099500
3103500
31 05500
3107500
3095500
5
7
25
39
1 3
33
36
11
1 2 3
-------
is r
19 F
20 F
21 F
22 F
23 F
24 F
25 F
26 F
27 F
28 F
Z9 F
30 T
31 F
32 F
33 F
3* F
35 F
36 F
37 F
3« F
PARAMETER NUMBER
tfEACH NO. HPL.
1 F
2 F
3 F
4 F
5 F
6 F
7 F
8 F
1 F
10 F
11 F
12 F
13 F
14 F
15 F
16 F
17 F
18 F
19 F
20 F
F 500.000
F 500.000
F 500.000
F 1500.000
F 1500.000
F 1500.QOO
F 1500.000
F 1500.700
F 1500.000
F 1500.000
F 1500.000
F 1500.000
T SCO. 000
F 500.000
F 500.000
F 500.000
F 500.000
F 500.000
F 500.000
F 500.000
F 500.000
= 10
MN. PLCY. CT
F .OOs
F .DOS
F .005
F .DOS
F .005
F .001
F .00^
F .OO''
F .00*3
F .DOS
F .COS
F .DOS
F U.OOO
F 0.000
F 0.000
F U.OOO
F 0.000
F 0.000
F 0.000
F 0.000
-0.00
-0.00
-0<00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
DELTA
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-o.oo
-0,00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
12.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
IHPL. LOC.
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.000
-0.000
-0.000
.0.000
-0.000
-0.000
-0*000
-o.ooo
-0.000
-o.ooo
-0.000
-0.000
15.000
-o.ooo
-o.ooo
-0.000
-0.000
-0.000
-o.ooo
-o.ooo
-0.000
EPS I
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
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-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
60.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
6.75
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-o.oo
-0.00
-0.00
-0.00
-0,00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TDOMN
-0.00
-0.00
-o.oo
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
347
-------
21 T T
33 F F
73 f F
2* F F
25 F F
36 F F
27 F F
28 F F
?9 F F
30 F F
31 F F
3? F F
33 F F
3* F F
35 F F
36 F F
37 F F
38 F F
PARAMETER NUMBER » 11
REACH NO. IMPL. MN. PLCY.
1 F F
2 F F
3 F F
ft F F
5 F F
t> F F
7 F F
8 F F
9 T T
JO F F
11 F F
12 F F
13 F F
1ft F F
15 F F
16 F F
17 F F
18 F F
19 F F
20 F F
21 T T
22 F F
23 F F
2» F F
.005
.005
.005
.005
.006
.005
' .005
.005
.005
0.000
0.000
0.000
0.000
0.000
0.000
0.000
o.ooo
0.000
CT
.100
.100
.100
.100
.100
.100
.100
• 100
.100
.100
.100
.100
.005
.005
.005
.005
.005
.005
.005
.005
.100
.100
.100
.too
.Oft
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-o.oo
-o.oo
-0.00
-0.00
-0.00
-0.00
-o.oo
•0.00
-0.00
-0.00
DELTA
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.Oft
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-o.oo
-0.00
.Oft
-0.00
-0.00
-0.00
31.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
IMPL. LOG.
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
37.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
31.00
-0.00
-0.00
-0.00
348
.020
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
EPSI
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
•0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.005
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
.005
-0.000
-0.000
-0.000
6. 75
-0.00
-o.oa
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-o.oo
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-0.00
-o.oo
.25
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TOOWN
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0,00
-0.00
.25
-0.00
-0.00
-0.00
-------
25
26
27
28
29
30
31
32
33
34
35
36
37
38
PARAMETER
REACH NO.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
18
19
20
21
22
23
24
25
26
27
28
F
F
F
F
F
T
F
F
F
F
F
F
F
F
NUMBER
IMPL.
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
T
F
• F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
» 17
MN. PLCV.
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
T
F
F
F
F
F
F
F
• 100
.100
.100
.100
.100
.005
.005
.005
.005
.005
.005
.005
.005
.005
CT
5.000
5.000
5.000
5.000
5.000
5.000
5.000
S.OOO
5.000
5.000
5.000
5.000
5.000
S.OOO
S.OOO
5.000
S.OOO
5.000
S.OOO
S.OOO
5.000
5.000
5.000
S.OOO
S.OOO
5.000
5.000
S.OOO
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
DELTA
-0.00
.04
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-0.00
-0.00
.04
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
12.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
IMPL. LOC.
-0.00
62.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
36.80
-0.00
-0.00
31.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.000
-0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
EPSI
-0.000
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.050
-0.000
-0.000
.050
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.005
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.150
-0.000
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6. 75
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
TDOWN
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
349
-------
29
30
31
32
33
34
35
36
37
38
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
T
F
F
5.000
5.000
5.000
5.000
5.000
5.000
5.000
S.OOO
5.000
5.000
•0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
7.60
-0.00
-0.00
-0.000 -0.000 -0.00 -0.00
-0.000 -0.000 -0.00 -0.00
-0*000 -0.000 -0.00 -0.00
-0.000
-0.000
-0.000
-0.000
-o.ooo
.050 .150
-0.000 -0.000
-0.000 -0.00 -0.00
-0.000 -0.00 -0.00
-0.000 -0.00 -0.00
-0.00 -0.00
6.75 .25
-0.00 -0.00
-0.000 -0.000 -0.00 -O.OC
MEANS NO.
21
22
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
41
42
43
44
50
SI
52
53
STATE I » OPERATING! STATE 2 « STAND-BY
MTTFS-1 MTTFS-? MTTFA-1 MTTFA-2 MTTRA-1
.20
.20
.20
.20
.20
.01
.20
.01
.20
.20
.20
.20
.20
.20
.20
.20
.0)
.20
.20
.01
.01
.20
.20
.20
.20
.20
.01
MTTRA-2
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
.OJ
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
.01
5.00
5.00
6.00
5.00
3.00
3.00
5.00
3.00
3.00
6.00
6.00
6.00
5.00
5.00
3.00
3.00
2.00
3.00
5.00
S2.00
3.00
3.00
5.00
5.00
3.00
5.00
2.00
365.00
36S.OO
365.00
365.00
.30
.50
1.00
3.00
.30
365.00
365.00
365.00
365.00
365.00
.30
.30
.50
.30
1.00
52.00
3.00
.30
1.00
1.00
.30
1.00
.50
100.00
100.00
100.00
100.00
100.00
365.00
137.00
365.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
365.00
100.00
137.00
9999.00
365.00
100.00
137.00
137.00
100.00
137.00
365.00
365.00
365.00
365.00
365.00
45.00
365.00
137.00
365.00
45.00
365.00
365.00
365.00
365.00
365.00
45.00
45.00
365.00
45.00
137.00
9999.00
365.00
45.00
137.00
137.00
45.00
137.00
365.00
PARAMETER NUMBER = s ELEMENT OESIGN FOR SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT OESIGN
30
30
30
30
30
PARAMETER NUMBER •
REACH NO. PATH NO.
30 1
30 2
30 3
30 4
30 5
I M S L(UEHTST) •*• *
I M 5 L(UERTST) **• W
1 M22S 2S 3 -0 -0 -0
1 MSOM28P 3 -0 -0 -0
2 M29P 2S 4S 5 -0 -0
2 MJ6P 5 -0 -0 -0 -0
3 M53P 4 -0 -0 -0 -0
5 ELEMENT DESIGN FOR AVAILABILITY
I 1 I I I
0 0 O O 0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
NORMAL STATUS ELEMENT OESIGN
1
1
2
2
3
NG
HG
M22S 2S 3
MSOMZ8P 3
M29P 25 45
M26P 5 -0
M53P 4 -0
LUOATF
LEOTIF
-0
-0
5
-0
-0
-0
-0
-0
-0
-0
2
2
-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
PARAMETER NUMBER • 5
REACH NO. * 30 CAP • 7.639lbE-03 SURV ii 9.80935E-01 AVAIL « 9.99296E-01 ELEMENT EfT.
7.46834E-03
350
-------
PARAMETER NUMBER ' 10 ELEMENT DESIGN FOR SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
81
1 M31S 2S 3 -0 -0 -0 -0 -0 -0 -0
1 M44M41M42P 3 -0 -0 -0 -0 -0 -0
2 M43M38P 2 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER '« 10 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21 1 1
Zl 2 I
21 3 Z
••• I M S L(UERTST) ••• WARNING
•••IMS L(UERTST) ••• WARNING
M31S 2S 3 -0 -0 -0 -0 -0 -0 -0
M44M41M42P 3 -0 -0 -0 -0 -0 -0
M43M38P 2 -0 -0 -0 -0 -0 -0 -0
UUDATF 2
LEOT1F 2
PARAMETER NUMBER = 10
PEACH NO. » 21 CAP = 3.3682<»E-02 SUBV = 9.80095E-01 AVAIL = 9.7844SE-OI ELEMENT EFF.
3.230C4E-02
PARAMETER NUMBER * 11 ELEMENT DESIGN FOR SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
9
9
9
21
21
21
30
30
30
30
30
1
Z
1
1
2
3
1
2
3
4
5
2
2
3
S 2S 3M32 -0 -0 -0 -0 -0 -0 -0
P 3M40M41M42 -0 -0 -0 -0 -0 -0
P 2M39M3B -0 -0 -0 -0 -0 -0 -0
M33S 2S 3 -0 -0 -0 -0 -0 -0 -0
M44M41M42P 3 -0 -0 -0 -0 -0 -0
M43M38P 2 -0 -0 -0 -0 -0 -0 -0
M?3S 2S 3 -0 -0 -0 -0 -0 -0 -0
M50M28P 3 -0 -0 -0 -0 -0 -0 -0
M39P 25 4S 5 -0 -0 -0 -0 -0 -0
M26P 5 -0 -0 -0 -0 -0 -0 -0 -0
M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER » 11 ELEMENT DESIGN FOR AVAILABILITY
REACH NO.
9
9
9
21
•» I M S L(UERTST)
••IMS L•• I M S U(UERTST)
PATH NO. NORMAL
1
2
3
1
••• WARNING
••• WARNING
2
3
1
••• WARNING
••• WARNING
2
3
4
S
••• WARNING
••• WARNING
STATUS
1
1
S
1
1
2
1
1
2
2
3
ELEMENT DESIGN
S 2S 3M32 -0 -0 -0 -0 -0 -0 -0
P 3M40M41M42 -0 -0 -0 -0 -0 -0
P 2M39M38 -0 -0 -0 -0 -0 -0 -0
M33S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUDATF ?
LEOT1F 2
M44M41M42P 3 -0 -0 -0 -0 -0 -0
M43M38P 2 -0 -0 -0 -0 -0 -0 -0
M?3S 2S 3 -0 -0 -0 -0 -0 -0-0
LUDATF 2
LEOT1F 2
MSOMZBP 3 -o -o -o -o -o -o -o
M?9P 2S 4S 5 -0 -0 -0 -0 -0 -0
M26P S -0 -0 -0 -0 -0 -0 -0 -0
M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
LUDATF 2
LEOT1F 2
PARAMETER NUMBER * 11
REACH NO. * 9 CAP - 3.629SBE-02 SURV «
REACH NO. > 21 CAP ' 1.02833E-02 SURV »
REACH NO. » 30 CAP » 8.73741E-03 SURV *
9.80095E-01 AVAIL *
9.S009SE-01 AVAIL *
9.80935E-01 AVAIL '
9.7844SE-01 ELEMENT EFF.
9.7844SE-01 ELEMENT EFF.
9.99296E-01 ELEMENT EFF.
3.4B066E-02
9.86135E-03
8.56480E-03
351
-------
PARAMETER NUMBER = 17 ELEMENT DESIGN FQR SURVIVABILITY
kEACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
2
1
2
IB
16
18
18
16
31
21
21
36
36
36
36
36
S 25 3M34M38 -0 -0
P 3M37 -0 -0 -0 -0
P 2M36 -0 -0 -0 -0
M21S 2S 3 -0 -0 -0
M27M28P 3 -0 -0 -0
M?SS 45 SP 2 -0 -0
M26P 5 -0 -0 -0 -0
M53P 4 -0 -0 -0 -0
M35S 2S 3 -0 -0 -0
M44M41M42P 3 -0 -0
M43M38P Z -0 -0 -0
M24S 25 3 -0 -0 -0
MS2M28P 3 -0 -0 -0
MSIP 25 45 5 -0 -0
M?6P S -0 -0 -0 -0
M53P 4 -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
PARAMETER NUMdE» * IT ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
*«4
• ••
• **
• **
***
#••
• *•
**»
I
I
I
I
I
I
I
I
M
M
M
M
M
H
M
M
S
S
s
s
s
s
s
s
2
2
2
is
L(UEMTST)
L(UERTST)
18
18
18
18
21
LdJERTSTI
LlUERTST)
21
21
36
LCUERTST)
LCUERTST)
36
36
36
36
L(UERTST)
L(UERTST)
1
2
3
1
•*• WARNING
*•• WARNING
2
3
it
5
1
»«• WARNING
••• WARNING
2
3
1
»** WARNING
•«• WARNING
2
3
4
5
••• WARNING
»*• WARNING
S 25 3M34M38 -0
P 3M37 -0 -0 -0
P 2M36 -0 -0 -0
M21S 25 3 -0 -0
LUDATF 2
LEQUF 2
M=>7M28P 3 -0 -0
MP5S 45 5P 2 -0
M?6P 5 -0 -0 -0
M-53P 4 -0 -0 -0
M35S 25 3 -0 -0
LUOATF 2
LEOT1F 2
M44M41M42P 3 -0
M43M3BP 2 -0 -0
M24S 2S 3 -0 -0
LUOATF 1
LEOTlF 2
M52H2BP 3 -0 -0
M51P 2S 4S S -0
M?6P S -0 -0 -0
M53P 4 -0 -0 -0
LUDATF 2
LEOTlF 2
-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
-o -o -o -o -o
•0 -0 -0 -0 -0
-0 -0 -0 -0 -0
-o -o -o -o -o
•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
PARAMETER NUMBER « 17
REACH NO. » 2 CAP » 9.23774E-03 SURV
REACH NO. « 18 CAP • 3.14209E-02 SURV
REACH NO. • 21 CAP » 0. SURV
REACH NO. > 36 CAP • 3.03844£-02 SURV
7.95719E-01 AVAIL •
9.80935E-01 AVAIL •
9.80095E-01 AVAIL «
9.80935E-01 AVAIL '
9.46683E-01 ELEMENT EFF.
9.99296E-01 ELEMENT EFF.
9.7S261E-01 ELEMENT EFF.
9.99296E-01 ELEMENT EFF.
6.9S873E-03
3.oaooie-os
0.
2.97842E-OZ
SYSTEM EFFECTIVENESS • 2.9Z079E-01
TOTAL COST • 2.00490E«05
COST/EFF. • 6.»6423E»05
352
-------
CANDIDATE 1.1 DATA DECK
CONTROL F 001020011221011120 1. 60
USGS
USGS
USGS
US6S
USGS
USGS
USGS
USGS
END
01
02
03
04
05
06
07
08
03091500
03094000
0309ROOO
03099500
03103500
03105500
03107500
03095500
05
07
25
29
13
33
36
11
0102030405
0^07080910
21??2324252fe
27PH293031
1314151617181920
323334
35363738
111?
2.
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"RIBAM SDD"
CHAR0501
CHAROS02
CHAR0503
CHAR0504
CHAR0505
CHAR0506
CHAR0507
CHAR0508
CHAR0509
CHAR0510
CHAR0511
CHAR0512
CHAR0513
CHAR0514
CHAR0515
CHAR0516
CHAR0517
CHAR0518
CHAR0519
CHAR0520
CHAR0521
CHAR0522
CHAR0523
CHAR0524
CHAR0525
CHAR0526
CHAR0527
CHAR0528
CHAR0529
CHAR0530TT
CHAR0531
CHAR0532
CHAR0533
CHAR0534
CHAR0535
CHAR0536
CHAR0537
CHAR0538
END
.CHAR 1001
CHAR1002
CHAR 1003
CHAR 10 04
CHAR 1005
CHAR 1006
CHAR1007
CHAR100R
CHAR1009
CHAR1010
CHAR1011
CHAR1012
1500.
1500.
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11.0
15.0
15.0
365.
0.
353
-------
CHAR 10 13
CHAR 10 14
CHAR 10 15
CHAR1016
CHAR1017
CHAR 10 18
CHAR1019
CHAR1020
CHAR1021TT
CHAR1022
CHAR1023
CHAR1024
CHAR102*
CHAR1026
CHAR1027
CHAR102*
CHAR1029
CHAR1030
CHAR1031
CHAR1032
CHAR1033
CHAR1034
CHAR1035
CHAR1036
CHAR1037
CHAR1038
END
CHAR1101
CHARHO?
CHAR1103
CHAR1104
CHAR 1105
CHARllOft
CHAR1107
CHAR1108
CHAR1109TT
CHAR1110
CHARllll
CHAR1112
CHAR1113
CHAR1114
CHAR1115
CHAR1116
CHARJ117
CHAR111M
CHAR 11 19
CHAR1120
CHAR1121
CHAR 11 22
CHAR1123
CHAR1124
CHARU25
CHAR 11 26
CHAR 11 27
CHAR 11 2ft
CHAR 11 29
CHAR1130TT
CHAR1131
CHAR 11 32
CHAR 11 33
CHAR 11 34
CHAR 11 35
CHAR1136
CHAR1137
CHAR 11 38
END
.0
.0
.0
.0
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.0
.0
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.005
.005
.005
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0.0
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0.0
0.0
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0.
0.
0.
0.
0.
0.
0.1
0.1
0.1
0.1
0.1
0.005
0.005
0.005
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0.005
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0.005
0.005
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
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0.005
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3.5
30.
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365.
0.
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3.5
11.0
0.001
0.002
3651
354
-------
CHAR1701
CHAR1702TT
CHAR1703
CHAR1704
CHAR1705
CHAR1706
CHAR1707
CHAR1708
CHAR1709
CHAR1710
CHAR1711
CHAR1712
CHAR1713
CHAR171**
CHAR171S
CHAR1716
CHAR1717
CHAR1718TT
CHAR1719
CHAR1720
CHAR1721TT
CHAR1722
CHAR1723
CHAR1724
CHAR172S
CHAR1726
CHAR1727
CHAP1728
CHAR1729
CHAR1730
CHAR1731
CHAR1732
CHAR1733
CHAR1734
CHAR1735
CHAR1736TT
CHAR1737
CHAR1738
END
MTTF 01
MTTF 02
MTTF 03
MTTF 04
MTTF 05
MTTF 06
MTTF 07
MTTF 08
MTTF 09
MTTF 10
MTTF 11
MTTF 12
MTTF 13
MTTF 14
MTTF 15
MTTF 16
MTTF 17
MTTF 18
MTTF 19
END
SURV 30
SURV 30
SURV 30
END
AVAIL 30
AVAIL 30
AVAIL 30
END
5.0
5.0
5.0
5.0
5.0
b.O
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
0.2
0.01
0.01
0.2
0.02
0.2
0.01
0.01
0.2
0.2
0.01
0.2
0.2
0.02
0.2
0.01
0.2
0.2
0.2
05 1
05 2
05 3
05 1
05 2
05 3
so.
7.
3.5
7.0
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.1
1S02S03
1M10M13P03
2M15M18P02
1SOPS03
1M10M13P03
2M15M1HP02
82.5 0.02
36.8 0.02
3o.6 0.0?
4.0 0.0?
2.U i.o
2.U o.Ol
2.U 0.01
4.0 2.o
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365.
365.
365.
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365.
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365.
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122.
0.
0.
0.
355
-------
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTM
COSTM
COSTM
COSTM
COSTM
21
21
21
21
21
21
09
09
09
21
21
21
30
30
30
09
09
09
21
21
21
30
30
30
02
02
02
18
18
18
21
21
21
36
36
36
02
02
02
18
18
18
21
21
21
36
36
36
1
2
3
4
5
6
7
8
1
2
3
4
5
10 1
10 2
10 3
10 1
10 2
10 3
11 1
11 2
11 3
11 1
11 2
11 3
11 1
11 2
11 3
11 1
11 ?
11 3
11 1
11 2
11 3
11 1
11 2
11 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
40000.
10000.'
20000.
5000.
10000.
20000.
5000.
5000.
3000.
400.
400.
600.
1500.
1S02S03
1M01M02P03
2M06M07P02
1S02S03
1M01M02P03
2M06M07P02
1MOBS02S03
1M01M03P03
2M06M08P02
1S02S03M05
1M01M03P03
2M06M08P02
1M14S02S03
1M10M11P03
2M15M16P02
1MOSS02S03
1M01M03P03
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1M01M03P03
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1M10M11P03
2M1SM16P02
1S02S03M14
1M01M04P03
2M06M09P02
1SOPS03
1M10M12P03
2M15M17P02
1SOPS03
1M01M04P03
2M06M09P02
1S02S03
1M10M12P03
2M15M17P02
1S02S03M19
1M01MO*P03
2M06M09P02
1S02S03
1M10M12P03
2M15M17P02
1S02S03
1M01M04P03
2M06M09P02
1S02S03
1M10M12P03
2M15M17P02
0. 0. 0.
5000. 0. 0.
4500. 1000. 20000.
2500. 500. 4500.
5000. 0. 0.
4500. 1000. 20000.
1500. 250. 4500.
1500. 250. 4500.
10000. 600. 2000.
1000. 0. 0.
500. 0. 0.
20. 200. 300.
50. 0* 1500.
0
1
2
2
1
5
5
5
4
4
4
4
3
356
-------
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
END
*
6
7
8
9
10
11
12
13
14
15
16
17
18
1
-------
16
17
IB
19
20
21
U
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
if.
PARAMETER
REACH NO.
,
2
3
A
5
6
7
8
t
10
11
12
13
14
15
16
17
18
19
F
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
NUMBER
IMPL.
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
, F
F
F
F
F
F
- JO
MM.
F
F
F
F
F
F
F
F
F
F
F
F
f
f
T
r
F
f
r
500
500
500
500
500
1500
1500
1500
1500
1500
1500
1500
1500
1500
500
500
500
500
500
500
SOU
500
500
PLCr.
0
0
ft
I)
0
0
0
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.090
.000
.000
.000
.000
.000
.000
.000
.000
CT
.oos
.005
.005
.005
.005
.005
.005
.005
.005
• cos
.DOS
.005
.000
.000
.000
.000
.000
.000
.000
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-o.oo
-0.00
-o.oo
-0.00
-0.00
-0.00
3.50
-0.00
-o.oo
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
DCLTA
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
•0.00
-0.00
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
•0.
-0.
11.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
IMPL.
-0.
-0.
•0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
, LOC.
00
,00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
15.000
-o.ooo
-o.ooo
-o.ooo
-0.000
-0.000
-0,000
-o.ooo
-0.000
EPS I
-0.000
-o.ooo
-o.ooo
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-O.ODO
15.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
sepsi
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.oo
-o.oo
-0.00
-0.00
-0.00
-o.oo
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
TUP
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TDOWN
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
358
-------
20
21
?2
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
PARAMETER
REACH NO.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
16
19
20
21
22
23
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
NUMBER
IMPL.
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
r
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
= 11
UN. PLcr.
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
0.000
• DOS
• 005
.00%
.oos
• 005
.005
.OOS
.005
.005
0.000
0.000
u.ooo
o.ooo
0.000
0.000
0.000
0.000
OtOOO
CT
.100
.100
.100
.100
.100
.100
.100
.100
• 100
.100
.100
.100
.oos
• DOS
.00%
.oos
.005
.005
.005
.oos
.100
.100
.100
-0.00
3.50
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-o.oo
-0.00
-0.00
-0.00
-o.oo
-0.00
-o.oo
-0.00
-0.00
-o.oo
-0.00
DELTA
-0.00
-0.00
-0.00
-0.00
-o.oo
-o.oo
-0,00
-o.oo
7.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
7.00
-0.00
-0.00
-0.
30.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
00
60
00
00
00
00
00
00
00
00
00
oo
00
00
-0.00
-0.
-0.
-0.
-0.
IMPL
-0
-0
-0
-0
-0
-0
-0
-0
37
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
30
-0
-0
.00
.00
,00
,00
. LOG.
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.60
.00
.00
-0.000
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
EPS I
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
.001
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
-0.000
.100
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
SEPSI
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.002
-Q.OOO
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.002
-0.000
-0.000
-0.
365.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
-0.
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
-0.00
TUP
-0
-0
-0
-0
-0
-0
-0
-0
365
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
365
-0
-0
.00
.00
.00
.00
,00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0,00
-0.00
fO.OO
-0.00
-0.00
-0.00
-0.00
-0.00
TOOWN
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
359
-------
24 F
25 F
2o F
27 F
28 F
29 F
30 T
31 F
32 F
33 F
34 F
35 F
36 F
37 F
38 F
PARAMETER NUMBER
REACH NO. IHPL.
1 F
2 T
3 F
4 F
5 F
6 F
7 F
ft F
9 F
JO F
11 F
12 F
13 F
14 F
15 F
16 F
17 F
18 T
19 F
20 F
21 T
?? F
23 F
24 F
25 F
26 F
27 F
F .100
F .100
F .100
F .100
F .100
F .100
T .005
F .005
F .005
F .DOS
F .005
F .005
F .005
F .005
F .005
= 17
MM. PLCY. CT
F b.OOU
T b.OOO
F 3.000
F 5.000
F 5.000
F 3.000
F 5.1)00
F 3.00U
F 5.000
F b.OOO
F b.OOO
F 5.000
F 5.000
F 3.000
F b.OOO
F 5.000
F 5.000
T 3.000
F 5.000
F 5.000
T 5.000
F 5.000
F 5.000
F S.OOO
F 5.000
F 5.000
F 3.000
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
3. SO
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
DELTA
-0.00
40.00
-0.00
-0.00
-0.00
-0.00
-o.uo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
7.00
-0.00
-0.00
1.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
11.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
IMPL. LOC.
-0.00
82. SO
-0.00
-0.00
-0.00
-n.oo
-o.co
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
36.80
-0.00
-0.00
30.60
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
EPSI
-0.000
.020
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-o.ooo
-0.000
.020
-0.000
-0.000
.020
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.002
-0,000
-0.000
-0.000
-0.000
-0.000
-0,000
-0.000
-0.000
SEPSI
-0.000
.100
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-o.ooo
-o.ooo
.100
-0.000
-0.000
.100
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-0.00
36S.OO
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
365.00
-0.00
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TDOWN
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
360
-------
28
?<»
30
31
32
33
34
35
36
37
36
F F b.OOO
F F 5.000
F F 5.000
F F a. 000
F f 5.000
F F 5.000
F F 5.000
F F 5.000
T T 5.000
F F 5.000
F F 5.000
-0.00 -0.00 -0.000 -0.000
-0.00 -0.00 -0.000 -0.000
-0.00 -0.00 -0.000 -0.000
-0.00 -0.00 -0*000 -0.000
-0.00 -0.00 -0.000 -0.000
-0.00 -0.00 -0.000 -0.000
-0.00 -0.00 -0.000 -0.000
-0.00 -0.00 -0.000 -0.000
7.00 4.00 .020 .100
-0.00 -0.00 -0.000 -0.000
-0.00 -0.00 -0.000 -0.000
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-o.oo
STATE 1 » OPFWATlNGi STATE 2 = STAND-BY
MEANS NO.
1
2
3
^
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
. MTTFS-I «TTFb-2
.20 .01
.01 .01
.01 .01
.20 .01
.02 .02
.?0 .01
.01 .01
.01 .01
.20 .01
.20 .»!
.01 .01
.20 .01
.2n .01
.02 ,a^
.2u .01
.01 .01
.20 ."I
.2n .01
,
-------
PARAMETER NUMBER « 10 ELEMENT DESIGN TOR SURVJVARILITT
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
21
21
S 25 3 -0 -0 -0 -0 -0 -0 -0 -0
M 1« 2P 3 -0 -0 -0 -0 -0 -0 -0
M *>M 7P ? -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER = 10 ELEMENT DESIGN F0« AVAILABILITY
MEACH NO. PATH NO. NOHMAL STATUS ELEMENT DESIGN
21 1 1 S 25 3 -0 -0 -0 -0 -0 -0 -0 -0
21 2 1 M 1M 2P 3 -o -0 -0 -0 -0 -0 -0
21 3 2 M 6M 7P 2 -0 -0 -0 -0 -0 -0 -0
M S L(UERTST) ••• WARNING LUDATF ?
M S L(OERTST) **« WARNING LEOTlF 2
PARAMETER NUMBF.R » 10
REACH NO. * 21 CAP = 2.531V1E-0? SURV = 9.79116E-01 AVAIL » 9.99925E-01 ELEMENT EFF.
2.47685E-02
PARAMETER NUMBER * 11 ELEMENT DESIGN Fo» SUHVIVABILm
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
9
9
9
21
21
?]
30
30
30
PARAMETER NUMBER
M 5S 2S
M 1M 3P
M 6M 8P
S 2S 3M
M 1M 3P
M 6M CP
M1*S 2S
M10M11P
3 -0
3 -0
2 -0
5 -0
3 -0
-0
-o -o -o
-0 -0 -0
-0 -0 -0
-0 -0 -0
-0 -0 -0
-0 -0 -0
-0 -0 -0 -0
3 -0 -0 -0 -0
M1SM16P Z -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
11 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NOHMAL STATUS ELEMENT DESIGN
••• I
••• 1
••• I
«•• I
M S
M S
M S
M S
9
9
9
21
L 3 -0 -0 -0
M 6M 8P 2 -0 -0 -0
S 2S 3M 5 -0 -0 -0
LUDATF ?
LEQT1F 2
M 1M 3P 3 -0 -0 -0
M 6M 8P 2 -0 -0 -0
MlbS 2S 3 -0 -0 -0
MtOMHP 3 -0 -0 -0
M1SM16P 2 -0 -0 -0
LUOATF 2
LEQT1F 2
9.59728E-01 AVAIL «
9.S9728E-01 AVAIL «
•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
9.28502E-01 ELEMENT EFF. • 1.7393OE-02
9.28502E-01 ELEMENT EFF. « 6.23303E-03
362
-------
PARAMETER NUMBER » 17 ELEMENT DESIGN FOR SURVIVABIL1TY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
e 1
2 2
2 3
16 1
18 2
18 3
21 1
91 9
£ I £•
21 3 2
36 1 1
36 2 1
36 3 2
M 6M 9P 2 -0 -« -0 -0 -0 -0 -0
S 2S 3 -0 -0 -0 -« -0 -0 -0 -0
M10M12P 3 -0 -0 -0 -0 -0 -0 -0
M1SM17P 2 -0 -0 -0 -0 -0 -0 -0
S ZS 3 -0 -0 -0 -0 -0 -0 -0 -0
M 6M 9P 2 -0 -0 -0 -0 -0 -0 -0
S 2S 3 -0 -0 -0 -0 -0 -0 -0 -0
M10M12P 3 -0 -0 -0 -0 -0 -0 -0
M15M17P 2 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER < IT ELEMENT DESIGN FOR AVAILABILITY
••• I
••* i
... i
••• i
••« i
••• i
... i
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REACH NO. PATH NO. NORMAL STATUS
21 1
2 2 1
23 2
18 1 1
M S L(UERTST) ••* WARNING
M S LIUERTST) ••* WARNING
18 2 1
18 3 2
?1 1 1
M S L(OERTST) ••• WARNING
M S L(UERTST) ••• WARNING
21 i 1
21 3 2
36 1 1
M S L
-------
60
CANDIDATE 2.1 DATA DECK
CONTROL F 001020011221011120 1.
USGS 01 03091500 05 0102030405
USGS 02 03094000 07 0607060910
USGS 03 03098000 25 212223242526
USGS 04 03099500 29 2728293031
USGS 05 03103500 13 1314151617181920
USGS 06 03105500 33 323334
USGS 07 03107500 36 35363738
USGS .08 03095500 11 1112
END
2.
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"RIBAM SDD"
CHAR0501
CHAR0502
CHAR0503
CHAR0504
CHAR0505
CHAR0506
CHAR0507
CHAR0508
CHAR0509
CHAR0510
CHAR0511
CHAR0512
CHAR0513
CHAR0514
CHAR0515
CHAR0516
CHAR0517
CHAR0518
CHAR0519
CHAR0520
CHAR0521
CHAR0522
CHAR0523
CHAR0524
CHAR0525
CHAR0526
CHAR0527
CHAR0528
CHAR0529
CHAR0530TT
CHAR0531
CHAR0532
CHAR0533
CHAR0534
CHAR0535
CHAR0536
CHAR0537
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CHAR1001
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CHAR1003
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CHAR 1101
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CHAR1110
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CHAR 11 25
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365
-------
CHAR1701
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CHAR1709
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CHAR1718TT
CHAR1719
CHAR1720
CHAR 1721
CHAR1722
CHAR 1723
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CHAR1725
CHAR1726
CHAR1727
CHAR1728
CHAR1729
CHAR1730
CHAR1731
CHAR1732
CHAR1733
CHAR 1734
CHAR1735
CHAR173(STT
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CHAR 1738
END
MTTF 21
MTTF 22
MTTF 23
MTTF 24
MTTF 25
MTTF 26
MTTF 27
MTTF 28
MTTF 29
MTTF 31
MTTF 32
MTTF 33
MTTF 34
MTTF 35
MTTF 36
MTTF 37
MTTF 38
MTTF 39
MTTF 40
MTTF 41
MTTF 42
MTTF 43
MTTF 44
MTTF 50
MTTF 51
MTTF 52
MTTF 53
5.0
5.0
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366
-------
END
SURV
SURV
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AVAIL
AVAIL
AVAIL
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SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
30
30
30
30
30
30
30
30
30
30
21
21
21
21
21
21
21
21
21
09
09
09
21
21
21
30
30
30
30
30
09
09
09
21
21
21
30
30
30
30
30
02
02
02
10
10
10
18
IS
18
18
18
36
36
36
36
36
05
05
05
05
05
05
05
05
05
05
10
10
10
10
10
10
10
10
10
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
1
2
3
4
5
1
2
3
4
5
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
4
5
1
2
3
1
2
3
1
2
3
4
5
1
2
3
1
2
3
1
2
3
it
5
1
2
3
4
5
1M22S02S03
1M50M28P03
2M29P02S04S05
2M26P05
3M53P04
1M22S02S03
1M50M28P03
2M29P02S04S05
2M26P05
3M53P04
1M31S02S03
1M44M41M42P03
2M43M38P02
1M31S02S03
1M44M41M42P03
2M43M38P02
1M31S02S03
1M44M41M42P03
2M43M38P02
1S02S03M32
1P03M40M41M42
2P02M39M38
1M33S02S03
1M44M41M42P03
2M43M38P02
1H23S02S03
1M50M28P03
2M29P02S04S05
2M26P05
3M53P04
1S02S03M32
1P03M40M41M42
2P02M39M38
1M33S02S03
1M44M41M42P03
2M43M38P02
1M23S02S03
1M50M28P03
2M29P02S04S05
2M26P05
3M53P04
1S02S03M34M38
1P03M37
2P02M36
1M35S02S03
1M44M41M42P03
2M43M38P02
1M21S02S03
1M27M28P03
2M25S04S05P02
2M26P05
3M53P04
1M24S02S03
1M52M28P03
2M51P02S04S05
2M26P05
3M53P04
367
-------
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
COSTG
COSTG
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COSTG
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COSTG
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COSTG
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COSTM
COSTM
COSTM
COSTM
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COSTM
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COSTM
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END
02
02
02
10
10
10
18
18
18
18
18
36
36
36
36
36
1
2
3
4
5
6
7
8
9
10
11
12
13
21
22
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
41
42
43
44
50
51
52
53
17 1 1S02S03M34M38
17 2 1P03M37
17 3 2P02M36
17 1 1M35S02S03
17 2 1M44M41M42P03
17 3 2M43M38P02
17 1 1M21S02S03
17 2 1M27M28P03
17 3 2M25S04S05P02
17 4 2M26P05
17 5 3M53P04
17 1 1M24S02S03
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40000.
10000.
20000.
5000.
1000.
1000.
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10000.
20000.
5000.
1000.
1000.
1000.
1200.
800.
3500.
1200.
1200.
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7000.
45000.
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1200.
1200.
1800.
3000.
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1000.
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150.
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5000.
1000.
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150.
150.
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200.
100.
300.
200.
20.
300.
400.
500.
20.
300.
300.
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400.
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350.
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1
2
2
2
2
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1
8
8
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8
6
11
12
12
13
11
10
11
9
12
7
6
7
5
7
5
5
4
6
6
3
3
7
7
12
13
13
13
368
-------
CANDIDATE 2.1 RESULTS
DESIGN TYPE » F SYSTEM OUR. * 1.00 NO. OF MONTHS = 60 FLO* SCALING FACTORS = 1.0 5.0 2.0 .5 .3
STA. NO. STA. 1.0.
SEG. MO. SEG. ASSOCIATION
1
2
3
it
5
6
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a
PARAMETER
REACH NO.
,
2
3
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29
30
31
32
33
3".
35
36
37
38
PARAMETER
REACH MO.
1
2
3
4
b
6
7
8
9
10
11
12
13
14
15
16
17
IS
19
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21
12
23
24
25
26
27
28
29
30
31
32
f
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-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
370
-------
33
34
35
36
37
38
PARAMETER
REACH NO.
1
2
3
4
5
6
7
a
9
in
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
26
29
30
31
32
33
34
35
36
F
F
F
F
F
F
NUMBER
IMPL.
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
= 11
MM. PLCf.
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
0.000
0.000
0.000
0.000
0.000
0.000
CT
.100
.100
.100
.100
.100
.100
.100
.100
.100
.100
.100
.too
.005
.005
.oos
.DOS
.005
.005
.COS
.005
.100
.100
.100
.100
.100
• 100
.100
.100
.100
.005
.005
.005
.005
.005
.005
.005
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
DELTA
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-0.00
-0.00
-o.oo
-0.00
-o.oo
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
.04
-0.00
-o.oo
-o.oo
-o.oo
-0.00
-o.oo
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
IMPL. LOG.
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
37.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
31.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
12.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
EPS I
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.005
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.005
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.005
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
•0.00
-0.00
-0.00
-0.00
-0.00
TDO*N
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
371
-------
37
38
AMETER
CH NO.
1
2
3
4
5
6
7
a
9
10
11
12
13
J4
IS
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
3*
35
36
37
38
F
F
NUMBFR
IMPL.
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
f
F
F
F
T
F
F
F
F
= 17
MM. PLCY.
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
.005
.005
CT
5.000
5.000
5.000
3.000
5.000
b.OOO
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
-0.00
-0.00
DELTA
-o.oo
.0*
-o.oo
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
.04
-o.oo
-o.oo
-o.oo
-o.oo
-0.00
-o.oo
-0.00
.04
-o.oo
-o.oo
-o.oo
-o.oo
-o.oo
-0.00
-o.oo
-o.oo
-o.oo
-o.oo
-o.oo
-o.oo
-o.oo
-o.oo
-0.00
-0.00
-0.00
.04
-o.oo
-0.00
-o.oo
-o.oo
IMPL. LOC.
-0.00
82.50
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
31.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
36. HO
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
7.80
-0.00
-0.00
-0.000
-0.000
EPS I
-0.000
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
.050
-0.000
-o.ooo
-0.000
-0.000
SEPSI
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.150
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.150
-0.000
-0.000
-0.00
-0.00
TUP
-0.00
6.75
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.oo
6.75
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.oo
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
TOONI
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
372
-------
MEANS NO.
STATE 1 =
MTTFS-1 MTTFb-2
STATE
MTTFA-1
= STAND-BY
HTTFA-2 MTTRA-1
MTTHA-2
21
22
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
<•!
42
43
44
50
51
52
53
.20
.20
.20
.?0
.20
.01
.?U
.'11
.20
.20
.20
.20
.20
.20
.20
.20
.01
.20
.20
.01
.01
.20
.20
.20
.20
.20
.01
.01
.ul
.01
.ui
.ul
,ji
.01
.Ul
.ul
.Ul
.01
.ul
.01
.ul
.01
.01
.01
.Ul
.01
.01
.01
.01
.01
.Ul
.Ul
.01
.01
5.00
5.00
6.00
5.00
3.00
2.00
5.00
3.00
3.00
6.00
6.00
6.00
5.00
5.00
3.00
3.00
2.00
3.00
5.00
S2.00
3.00
3.00
5.00
5.00
3.00
5.00
2.00
365.00
365.00
365*.00
365.00
.30
.50
1.00
3.00
.30
365.00
365.00
368.00
365.00
365.00
.30
.30
.50
.30
1.00
52.00
3.00
.30
1.00
1.00
.30
1.00
.50
100.00
100.00
100.00
100.00
100.00
365.00
137.00
365.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
365.00
100.00
137.00
9999.00
36S.OO
100.00
137.00
137.00
100.00
137.00
365.00
365.00
365.00
365.00
365.00
45.00
36S.OO
137.00
365.00
45.00
365.00
365.00
365.00
365.00
365.00
45.00
45,00
365.00
45.00
137.00
9999.00
365.00
45.00
137.00
137.00
45.00
137.00
365.00
PARAMETER NUMBER « 5 ELEMENT DESIGN FOR SURV1VA81LITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
30
30
30
30
30
1 M2ZS 2S 3 -0 -0 -0 -0 -0 -0 -0
1 M50M28P 3 -0 -0 -0 -0 -0 -0 -0
2 M29P 2S 4S 5 -0 -0 -0 -0 -0 -0
2 M?6P 5 -0 -0 -0 -0 -0 -0 -0 -0
3 M53P * -0 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER » 5 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
30 1 1
30 2 1
30 3 2
30 * 2
30 5 3
M S LIUERTST) ••• HAMMING
M S L(UERTST) ••* WARNING
M22S 2S 3 -0 -0 -0 -0 -0 -0 -0
M50M28P 3 -0 -0 -0 -0 -0 -0 -0
M29P 25 4S S -0 -0 -0 -0 -0 -0
M?6P 5 -0 -0 -0 -0 -0 -0 -0 -0
M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
LUO»TF 2
LEOT1F 2
PARAMETER NUMBER > 5
REACH NO. * 30 CAP - 7.63925E-03 SURV
9.B0935E-01 AVAIL • 9.99296C-01 ELEMENT EFF. « 7.4B834E-03
PARAMETER NUMBER * 10 ELEMENT DESIGN FOR SURV1VABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
21
21
1 M31S 2S 3 -0 -0 -0 -0 -0 -0 -0
1 M44M41M42P 3 -0 -0 -0 -0 -0 -0
2 M43M3BP 2 -0 -0 -0 -0 -0 -0 -0
373
-------
PARAMETER NUMBER = 10 ELEMENT DESIGN FOR A/ULABILITV
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
tl
21
S L(UERTST)
S L(UERTST)
2
3
••« WARNING
*•• WARNING
mis as 3 -o -o -o -o -o -o -o
M44M41M42P 3 -0 -0 -0 -0 -0 -0
M43M3SP 2 -0 -0 -0 -0 -0 -0 -0
LUDATF 2
LEOT1F 2
PARAMETER NUMBER = 10
REACH NO. « 21 CAP = 3.3682tE-02 SUHV a 9.80095e-01 AVAIL * 9.78445E-01 ELEMENT EFF.
3.23004E-42
PARAMETER NUMBER = 11 ELEMENT DESIGN FOR SURVIVABILITV
REACH NO. PATH NO. NORMAL STATUS ELEMENT OESIGN
9
9
9
21
Zl
21
30
30
30
30
30
PARAMETER NUMBER
S 2S 3M32 -0
P 3M40M41M42
P 2M39M38 -0
M33S 2S 3 -0
M44M41M42P 3
M43M38P 2 -0
142 35 2S 3 -0
MSOM28P 3 -0
M29P 25 4S 5
M26P S -0 -0
MS3P 4 -0 -0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
i i l i l i i i i i i
i i l l l i l i i l i
-0
-0
-0
-0
-0
-9
-0
-0
-0
-0
-0
1 1 1 1 1 1 1 1 1 1 1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
1
1
2
1
1
2
1
1
2
2
3
11 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT OESIGN
9 I 1
9 2 1
93 2
21 1 1
IMS L(UERTST) •*• WARNING
IMS L'UERTST) ••• WARNING
21 2 1
21 3 2
30 1 1
I M S L ••• WARNING
IMS LIUERTSTI ••• WARNING
30 Z 1
30 3 2
30 *. Z
30 5 3
I M S L(UERTST) ••• WARNING
I M S L(UERTST) *•• WARNING
S 2S 3M32
-0
P 3M40M41M42
P 2M39M3S
M33S 2S 3
LUDATF
LEQT1F
M44M41M42P
M43M38P 2
M33S 2S 3
LUDATF
LEOT1F
M«iOM28P 3
M?9P 2S 45
M26P 5 -0
M53P * -0
LUOATf
LEOTJF
-0
-0
3
-0
-0
-0
5
-0
-0
-0
-0
-0
-0
2
2
-0
-0
-0
2
2
-0
-0
-0
-0
?
i
-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
PARAMETER NIIMRFR * 11
REACH NO. * 9 CAP •
REACH NO. » 21 CAP «
REACH NO. « 3o CAP *
3.62958E-02 SURV •
1.02833E-02 SURV *
B.737ME-03 SURV «
9.80095E-01 AVAIL •
9.8009SE-01 AVAIL »
9.80935E-01 AVAIL »
9.78445E-01 ELEMENT EFF. « 3.*B066E-02
9.784*SE-oi ELEMENT EFF. > «.86iasE-o3
9.99296E-01 ELEMENT EFF. « 8.S6480E-03
374
-------
PARAMETER NUMBER * 17 ELEMENT DESIGN FOR SURVIVABILITr
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
c
2
10
10
10
18
i
3
1
2
3
1
3 £3 JPIJ^WJO -
P 2M36 -0 -0 -0 -0 -0 -0 -0 -0
M35S 2S 3 -0 -0 -0 -0 -0 -0 -0
M44M41M42P 3 -0 -0 -0 -0 -0 -0
M21S 2S 3 -0 -0 -0 -0 -0 •
•0 -0
18 3 2 M?5S 45 5P 2 -0 -0 -0 -0 -0 -0
18 4 2 M?6P 5 -0 -0 -0 -0 -0 -0 -0 -0
18 5 3 M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
36 1 1 M24S 2S 3 -0 -0 -0 -0 -0 -0 -0
36 2 1 MS2M2BP 3 -0 -0 -0 -0 -0 -0 -0
36 3 2 M51P 2S 4S 5 -0 -0 -0 -0 -0 -0
36 4 2 M?6P S -0 -0 -0 -0 -0 -0 -0 -0
36 5 3 M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER ' 17 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
2 1 1 S 25 3M34M3A -0 -0 -0 -0 -0 -0
22 IP 3M37 -0 -0 -0 -0 -0 -0 -0 -0
23 2 P 2M36 -0 -0 -0 -0 -0 -0 -0 -0
.*. 1
••• I
t«» I
.«• I
»«• I
• •• I
• *• I
«»• I
M S
M S
M S
M S
M S
M S
M S
M S
PARAMETER
REACH
REACH
REACH
REACH
NO.
NO.
NO.
NO.
HUERTST)
L(UERTST)
1 A
IV
1 A
IV
18
L(UERTST)
L(UERTST)
1 A
1 O
18
18
18
36
L IB CAP
' 36 CAP
i
»•• WARNING
••• WARNING
1
**• WARNING
••• WARNING
3
4
5
1
*•* WARNING
••• WARNING
Z
3
4
•i
••• WARNING
»•• WARNING
17
« 9.23774E-03
• 2.16616E-03
» 3. 14204E-02
« 3.03844E-02
A
1
2
2
3
1
1
2
2
3
SURV •
SURV *
SURV «
SURV «
n JJ-? c 9 j
LUOATF
LEOT1F
U^IM^BB'*!''
M21S 2S 3
LUDATF
LEQT1F
M?5S 45 5P
M?6P 5 -0
MS3P 4 -0
M24S ?S 3
LUDATF
LEOT1F
M42M2BP 3
-0
2
-0
-0
-0
-0
M51P 2S 4S 5
M?6P 5 -0
M53P 4 -0
LUDATF
LEQT1F
7.95719E-01
9.80095E-01
9.80935E-01
9.80935E-01
-0
-0
2
2
-0
2
2
-0
-0
-0
2
2
-0
-0
-0
-0
2
2
-0
-0
-0
-0
-0
-0
-0
-0
AVAIL »
AVAIL -
AVAIL •
AVAIL *
-0
-0
-0
-0
-0
-0
-0
-0
9
9
9
-0
-0
-0
-0
-0
-0
-0
-0
-0 -0
-0 -0
-0 -0
-0 -0
-0 -0
-0 -0
-0 -0
-0 -0
.46683E-0
.78261E-0
.99296E-0
9.99296E-0
6.9S873E-03
2.07689E-03
3.08001E-02
2.97842E-02
SYSTEM EFFECTIVENESS • 2.95857E-01
TOTAL COST • Z.OOV»OEt05
COST/EFF. » 6.77657E«05
375
-------
CANDIDATE 1. 2 DATA DECK
CONTROL F 001020011221011120 T.
USGS 01
USGS 02
USGS 03
USGS 04
USGS 05
USGS 06
USGS 07
USGS OH
END
"RIBAM
CHAR0501
CHAR0502
CHAR 050 3
CHAROSO<»
CHAH0505
CHAR0506
CHAR0507
CHAK050H
CHAR0509
CHA&0510
CHAR0511
CHAR0512
CHAR0513
CHAR051<»
CHAR0515
CHAR0516
CHAR0517
CHAROSlfl
CHAR0519
CHAR0520
CHAR0521
CHAR0522
CHAR0523
CHAR0524
CHAR0525
CHAR0526
CHAROS27
CHAROc52rt
CHAR0529
CHAR0530TT
CHAR0531
CHARQ53?
CHAR0533
CHAR0534
CHAR0535
CHAR0536
CHAR0537
CHAH053fl
END
CHA91001
CHAP1002
CHAH1003
CHAR1004
CHAR1005
CHAPIOO^
CHAR1007
CHAR1008
CHAP1009
CHAP1010
CHAR1011
CHAR1012
03091500 05 010?030405
03094000 07 0807080910
0309HQOO ?S •Z\?ttW*2l*
03099500 29 27PH293U31
03103500 13 1314151617
03105500 33 3?3334
03107500 36 35363738
03095500 11 111?
SDD"
1500.
1500.
1500.
1500.
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i500.
1500.
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1500.
1500.
1500.
500.
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ton 1,
2.
11.0
15.0
lb.0
365.
376
-------
CHAR 1011
CHAR1014
CHAR1015
CHAR1016
CHAR1017
CHARlOlfl
CHAR1019
CHAR1020
CHAR1021TT
CHAR1022
CHAR1023
CHAR1024
CHAR 1025
JCHAR1026
CHAR1027
CHAR1028
CHAR1029
CHAR1030
CHAR1031
CHAR 10 32
CHAR1033
CHAR1034
CHAR1035
CHAR1036
CHAR1037
CHAR103S
END
CHAR1101
CHAR1102
CHAR1103
CHAR 11 04
CHAR1105
CHAR 1106
CHAR1107
CHAR1108
CHAR1109TT
CHAR1110
CHAR1111
CHAR1112
CHAR1113
CHAR1114
CHAR1115
CHAR1116
CHAR 11 17
CHAR1118
CHAR1119
CHAR 11 20
CHAR1121
CHAR 11 22
CHAR 11 23
CHAR 11 24
CHAR 11 25
CHAR 11 2ft
CHAR1127
CHAR112H
CHAR 1129
CHAR1130TT
CHAR1131
CHAR 11 32
CHAR1133
CHAR 11 34
CHAR 11 35
CHAR 11 36
CHAR1137
CHAR113S
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0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.005
0.005
0.005
0.005
0.005
0.005
0.005
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3.5 30.0 0.05 0.10 365. o.
37.0 .001 .002 365.
30.6 0.001 0.002 365,
11.u 0.011 0.002 36^. 0.
377
-------
CHAW 1701
CHAR1707TT
CHAR 170 3
CHAR1704
CHAR 1705
CHAR 1706
CHAW1707
CHA»170«
CHAP1709
CHAR1710
CHAR1711
CHAR171?
CHAR1713
CHAR17U
CHAR1715
CHAR1716
CHAR1717
CHAR1718TT
CHAR1719
CHAR 1720
CHAR1721TT
CHAR 1722
CHAR1723
CHAR 1724
CHAR 1725
CHAR 1726
CHAR1727
CHAR 1728
CHAR 1729
CHAR1730
CHAR1731
CHAR 1732
CHAR1733
CHAR1734
CHAR 1735
CHAR1736TT
CHAR1737
CHAR1738
END
MTTF 01
MTTF 02
MTTF 03
MTTF 04
MTTF 05
MTTF 06
MTTF 07
MTTF OB
MTTF 09
MTTF 10
MTTF 11
MTTF 12
MTTF 13
MTTF 14
MTTF 15
MTTF 16
MTTF 17
MTTF 18
MTTF 19
END
5.0
s.o
5.o
5.')
5.0
S.O
5.0
5.0
5. a
S.O
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
• 5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
0.2
0.01
0.01
0.2
0.02
0.2
0.01
0.01
0.2
0-.2
0.01
0.2
0.2
0.02
0.2
0.01
0.2
0.2
0.2
40.
7.
3. is
7.0
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.01
0.01
0.01
0.01
0.1
n'r>f-> o.o?
36.8 0.03
30.6 0.0?
4.0 0.0?
2.0 1.0
2*0 0.01
2«u 0.01
4.0 ?.0
4.0 0.1
2.0 1.0
2.0 0.01
2.0 0.01
4.0 7.0
2.0 1.0
2.0 0.01
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4.0 ?.0
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4.0 1.0
v . 1 0
0.10
0.10
0.10
365.
365.
365.
365.
S2.
365.
365.
365.
365.
365.
365.
365.
365.
52.
365.
365.
365.
365.
122.
3OS.
365.
365.
365.
365.
365.
365.
366.
52.
365.
365.
36b.
365.
365.
365.
366.
36b.
52.
365.
363.
365.
36b.
122.
0.
0.
0.
0,
378
-------
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
COSTG
COSTG
COSTG
COSTG
3.0
30
30
30
30
30
21
21
21
21
21
21
09
09
09
?1
21
21
30
30
30
09
09
09
21
21
21
30
30
30
02
02
02
18
18
18
21
21
21
36
36
36
02
02
02
16
18
18
21
21
21
36
36
36
1
2
3
A
05 1
05 2
05' 3
05 1
05 2
05 3
10 1
10 2
10 3
10 1
10 2
10 3
11 1
1 2
1 3
1 1
1 2
1 3
1 1
1 2
11 3
11 1
11 ?
11 3
11 1
11 2
11 3
11 1
11 2
11 3
17 1
17 ?
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
17 1
17 2
17 3
40000.
10000.
20000.
5000.
1S02S03
1M10M13P03
2M15M18P02
1S02S03
1M10H13P03
2M15M1SPQ2
IS02S03
1M01M02P03
2MO^)M07P02
1S02S03
1M01M02P03
2M06M07PO?
1MU5S02S03
1M01M03P03
2M06M08MO?
1SO?S03MOC5
1M01MQ3P03
2MO*M08PO?
1M14SO?S03
1M1JM1 1P03
2M15M16PO?
l^j->So?S J3
1M01M03P03
2MO*iMOftPu2
1S(J?S03M05
1MQ1M03P03
2MO*MOBP02
1M14SO?S03
1M10M11P03
2MlSMlhP02
1S02S03M19
1MU1MQ4P03
2M06M09P02
1S02S03
1M10M12P03
2M15M17P02
1S02S03
1M01M04P03
2M06M09P02
1S02S03
1H10M12P03
2M15M17P02
1S02S03M19
1M01M04P03
2MOhM09P02
1SO?S03
•1M10M12P03
2M1'5M17P02
1S02S03
1M01MO«»P03
2M06M09P02
1S02S03
1M10M12P03
2M15M17P02
0. U.
20000. y.
22500. 5000. 10000.
12500. 2500. 1000.
0
1
2
2
379
-------
COSiu 5 10000. 25000.
COSTG 6 20000. 32500.
COST6 7 5000. 7500.
COSTG 8 5000. 7500.
COSTM 1 5200. 50000.
COSTM 2 400. 5000.
COSTM 3 400. 2000.
COSTM 4 600. 100.
COSTM 5 1500. 250.
COSTM 6 3000. 5000.
COSTM 7 400. 250.
COSTM 8 400. 250.
COSTM 9 600. 25.
COSTM 10 5200. 35000.
COSTM 11 400. 5000.
COSTM 12 600. 50.
COSTM 13 300. 100.
COSTM 14 1500. 250.
COSTM 15 5?00. 35000.
COSTM 16 400. 250.
COSTM 17 600. 50.
COSTM 18 300. 50.
COSTM 19 1500. 1000.
END
CANDIDATE 1. 2 RESULTS
DESIGN TYPE * F SYSTEM OUR. * 4.00 NO.
STA. NO. STA. 1.0. SEl,. NO.
1 30-ilSOO <=,
2 309*000 7
3 3098000 ->•=>
1250. 1000. 5
l?Su. luOO. 5
3000. 1500. 4
0 . 0 . 4
0. 0. 4
1000. 50. 4
0. 1SOO. 3
2000. 500. 4
0. 0. 4
U. 0.4
250. 0. 4
2000. 1500. 7
0. 0. 7
500. 50. 7
500. SO. 7
0. 1500. 6
2000. 1500. &
0. 0. H
500. 50. 8
?50. 50. B
500. ?DO. 4
OF MONTHS s 60 FLO* SCALING FACTORS » 1.0 5.0 2.0
SEG. ASSOCIATION
1 2 3 « 5-u-U-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O
b 7 b 410-0-U-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O
/?l??232*252b-0-0- 0-0 -0-0-0-0-0-0 -0-0-0-0-0-0-0-0 -0-0-0-0
? 7 21*29 3u 31 -0-0-0- U-0 -0-0-0-0-0-0 -0-0-0-0-0-0-0-0-0-0-0-0
131*1516 17 Ibl^o-U-O-O-O-O-O-O-O-O-O-D-t-O-O-O-O-O-O-O-O
3233. C.-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
3536 3738-0-0-0- 0-U-O-O-O-O-O- 0-0 -0-0-0-0-0-0-0-0-0- 0-0-0
1 1 12-0-u-U-O-O-O-U-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O-O
IMPL. LOC. EPSI SEPSI TUP TOOWN
-ii. co -o.ooo -o.ooo -o.oo -o.oo
-O.CO -0.000 -0.000 -0.00 -0.00
-j.u.) -0.000 -0.000 -0.00 -0.00
-O.uO -O.uOO -0.000 -0.00 -0.00
-a.uo -o.ooo -o.ooo -o.oo -o.oo
-0.00 -0.000 -0.000 -0.00 -0.00
-0.00 -0.000 -0.000 -0.00 -0.00
-O.'iO -0.000 -0.000 -0.00 -0.00
-0.00 -0.000 -0.000 -0.00 -0.00
-o.uo -o.ooa -o.aoo -o.oo -o.oo
-o.oo -o.ooo -o.ooo -o.oo -o.oo
.3
380
-------
12
13
14
IS
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
PARAMETER
REACH NO.
1
2
3
*
b
*
7
H
"
10
11
12
13
14
F
F
F
F
f
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
NUMBER
IMPL.
f
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
* In
MM.
f
f
f
f
f
F
F
F
f
f
f
f
F
F
150U.OOO
bOO. 000
•500.000
500.000
500.000
500.000
500.000
500.000
500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
1500.000
500.000
500.000
500.000
SOO.OOO
500.000
500.000
SOO.OOO
SOO.OOO
500.000
"LCI. cr
.no-
.00,
.Oft1!
.110-
.J^
..in.
.OOs
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0.000
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-0.00
-0.00
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-0.00
-0.00
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-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
3.50
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
OFLT4
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-0.00
-n.oo
-O.l'O
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-0.00
-0.00
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-0.00
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-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
11.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
IMPL. LOC.
-o.co
-0.nl>
-d.O'J
-0.1.0
-f'.(|0
-I). (Ml
-0.00
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15.000
-0.000
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-0.000
-o.ooo
-0.000
-0.000
-0.000
EPS1
-0.000
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-0.000
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-o.uuo
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-U.UOO
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-0.000
-0.000
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-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
15.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-O.UOO
-0.000
-0.000
-0.000
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-0.00
-0.00
-0,00
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-0.00
-0.00
-0.00
-0.00
-0.00
365.00
-0.00
-o.oo •
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-o.oo
-U.OO
-o.oo
-0.00
-0.00
-U.OO
-0.00
-U.OO
-o.oo
-U.OO
-0.00
-o.ou
-0.00
-U.OO
-o.oo .
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TOOWN
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
381
-------
15
16
17
18
19
20
21
22
23
?4
25
26
27
?8
29
30
31
32
33
34
35
36
37
38
PARAMETER
REACH NO.
1
2
3
4
5
6
7
a
.9
10
n
12
13
14
IS
16
17
18
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
NUMBER
IKPL.
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
f
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
* 11
MN. PLCr.
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
u.OOO
0.000
0.000
n.ooo
0.000
o.OOO
.OOS
.OOi
.DOS
.OOi
.OOb
.OOb
.OOS
.005
• COS
0.000
0.000
o.ooo
o.OOO
0.000
0.000
o.ooo
0.000
u.OOO
CT
.100
.100
.100
.100
.100
.100
.luo
.100
.100
.100
.100
.100
.00*
.DOS
.00%
• DOS
.00%
.OOb
-O.UO
-0.00
-0.00
-0.00
-o.oo
-o.oo
1.SO
-0.00
-0.00
-o.oo
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
DELTA
-o.oo
-0.00
-0.00
-o.oo
-0.00
-O.UO
-o.oo
-o.oo
7.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-O.bO
-O.uO
30.00
-O.UO
-0.00
-0.00
-0.00
-0.00
-O.UO
-o.oo
-0.00
-O.UO
-0.00
-0.00
-0.00
-0.00
-O.UO
-0.00
-0.00
-0.00
IMPL. LOC.
-0.00
-o.oo
-0.00
-O.uO
-O.dO
-O.nn
-O.OU
-(1.1,0
3t.uo
-O.UO
-C.oO
-c.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.uSu
-0.000
-o.ooo
-0.000
-0.000
-o.oou
-0.000
-o.ooo
-0.000
-o.oou
-o.oou
-o.ooo
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
EPS I
-0.000
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-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
.001
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.100
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
SEPSI
-0.000
-0.000
-0.000
-0.000
-0.000
-0,000
-0.000
-0.000
.002
-0.000
-0.000
-0.000
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-o.ooo
-0.000
-0.000
-0.000
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-0.00
-0.00
-0.00
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
J6S.OO
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
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-0.00
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-0.00
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-0.00
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-0.00
'-0.00
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-0.00
-0.00
-0.00
-0.00
-0.00
TOOWN
-0.00
-0.00
-0.00
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-0.00
-0.00
-0.00
-0.00
0.00
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-0.00
-0.00
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-0.00
-0.00
-0.00
-0.00
382
-------
19
20
2i
22
23
24
25
26
27
26
29
30
31
32
33
34
35
36
37
38
PARAMETER
BEACH NO.
1
2
3
<>
5
6
7
ft
9
10
11
J2
13
I*
IS
16
17
18
19
20
21
22
23
F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
'• F
r
F
F
F
NUMBER a
IMPL. HI
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
17
N. PLCY.
F
T
F
<=
F
F
F
F
F
F
K
F
F
F
F
F
F
T
F
F
T
F
F
• DOS
.DOS
• 100
.100
.100
• 100
• 100
• 100
.100
.100
• 100
.005
.005
• 095
• 005
• 005
.005
• 005
• 005
• DOS
CT
3.000
3.000
a.rjOU
3 • 'J 0 it
3.000
3.000
3.UOO
.5. '19(1
3.:iOO
•3. JOG
3.000
3,000
3.0ftO
3.000
3.000
3.000
3.000
' 5-000
5.000
3.000
3.000
i.OOO
5.000
-0.00
-0.00
7.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
1.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
OFLTA
-0.00
90.00
-0.00
-0.00
-0.00
-o.ua
-0.00
-o.oo
-O.iJU
-o.oo
-n.oo
- o • u o
-n.oo
-o.uo
-o.oo
-0.00
-0.00
7.00
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•J.50
-o.oo
-o.ou
-0.00
-0.00
30.60
-0.00
-0.00
-o.oo
-o.oo
-0.00
-0.00
-o.uo
-0.00
11.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
IMPL. IOC.
-O.uO
H2.50
-tl.Uu
-fl.ly'J
-U.O't
-O.UO
- 0 . L' '•)
-d. 00
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-fl.ll'J
-0.00
-O.UO
-0.00
-0.00
-0.00
-0.00
36. BO
-0.00
-o.oo
30. 60
-0.00
-0.00
383
-0.000
-0.000
.001
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-0.000
-0.000
-0.000
-0.000
-g.OOO
-o.ooo
-0.000
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
EPS I
-0.000
.020
-o.uoo
-o.ooo
-u.ouo
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-o.uoo
-0.000
-0.000
.020
-0.000
-o.ooo
.020
-0.000
-0.000
-0.000
-0.000
.002
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-O.uoo
-0.000
.002
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
SEPSI
-0.000
.100
-0.000
-0.000
-o.uoo
-0.000
-o.uoo
-0.000
-O.UOO
-0.000
-0.000
-0.000
-0.000
-o.uoo
-0.000
-0.000
-0.000
.100
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-0.000
.100
-0.000
-0.000
-0.00
-0.00
36S.OO
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
36S.OO
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TUP
-0.00
365.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
365.00
-0.00
-0.00
365.00
-0.00
-0.00
-0.00
-0.00
, 0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
. -0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
TDOWN
-0.00
0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
0.00
-0.00
-0.00
-------
2* F F
25 F f
26 F F
27 F F
28 F F
29 F F
30 F f
31 F F
32 F F
33 F F
3* F f
35 F F
36 T T
37 F F
38 F F
STATl
MEANS NO.. MTTFS-1
1 .26
2 .01
3 .01
^ ,2'>
5^
. u?
6 ?H
H *'"
a •* ,
. f >
11 *^1'
13 '*' '
12 . ^ u
13 .?')
1" .02
• ?o
16 , ;j J
fZ *?"
l** . 2u
19 .?<>
PARAMETER NUMBER «
REACH NO. PATH NO
30 1
30 2
30 3
PARAMETER NUMBER *
REACH NO. PATH NO
30 1
30 ?
30 3
3.000 -0.00 -0.00 -0.000 -0.000 -0.00
3.000 -0.00 -0.00 -0.000 -0.000 -0.00
3.000 -0.00 -0.00 -0.000 -0.000 -0.00
3.000 -0.00 -0.00 -0.000 -0.000 -0.00
3.000 -0.00 -0.00 -0.000 -0.000 -0.00
5.000 -0.00 -0.00 -0.000 -0.000 -0.00
5.000 -0.00 -0.1)0 -0.000 -0.000 -0.00
5.000 -0.00 -0.00 -0.000 -0.000 -0.00
5.000 -0.00 -0.00 -0.000 -0.000 -0.00
5.000 -0.00 -O.Ou -0.600 -0.000 -0.00
5.000 -0.00 -0.00 -0.000 -0.000 -0.00
5.000 -0.00 -0.00 -0.000 -0.000 -0.00
5.000 7.00 <».oo .QUO .100 365.00
5.000 -0.00 -0.00 -0.000 -0.000 -0.00
S.OOO -0.00 -0.00 -0.000 -0.000 -0.00
- i « OPERATING, STATE 2 = siANO-dr
Mm»-2 uTTFA-l MTTFA-2 MTTRA-1 MTTRA-2
ui 2.00 1.00 365.00 365.00
"1 2.00 .01 J6S.OO 365.00
01 2.00 .01 365.00 365.00
ul ».00 ?.UO 363,00 365,00
°^ ».00 .10 32.00 32.00
J1 2.00 1.00 Jo5.00 365.00
1 2.00 .01 36b.OO 365.00
1 2.00 .01 Job, 00 365.00
* 4.00 ?.UU JO3.00 365.00
1 2.00 1.00 Job. 00 365.00
1 2.00 .01 365.00 365.00
1)1 *.»0 P.OU 303. UO Job. 00
wi **.OCi ?.00 Job'. 00 36b~.00
U£! ".D'J .lU 32.00 32.00
u* 2.00 1.00 305.00 305.00
01 2.3C .01 Job. 00 365.00
"1 t.Ud ?.oi) Job. 00 365.00
Jl '••OO *>.l)0 Job. 00 365.00
lj ".00 l.ou 122.00 122.00
5 ELEMENT UESIGN FOB SUMVIVA8ILITY
. NORMAL STATUS ELEMENT DESIGN
1 S 2S 3 -0 -0 -0 -0 -0 -0 -0 -0
1 M10M13P 3 -0 -0 -0 -0 -0 -0 -0
2 M15M18P 2 -0 -0 -n -0 -0 -0 -0
s ELEMENT OESIC.N KUX AVAILABILITY
. NOrfMuL STATUS ELEMENT of SIGN
I S 2S 3 -0 -0 -0 -0 -0 -0 -0 -0
1 MIOM13P 3 -0 -U -0 -0 -0 -0 -0
2 MISMHP ? -o -o -o -o -o -o -o
-o.oo
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
-0.00
-0.00
••• I *t S L(UE«TST) ••• KAwNING
••• IMS LJUERTSTt •*• WARNING
PAHAMETER NUMBER « 5
REACH NO. * 30 CAP » 5.55207E-0 1 SiJ"»V
LUDATf
LfuTIF
3.92912E-01 AVAIL ' 9.99B01E-01 ELEMENT EFF. • 2.18136E-03
384
-------
PARAMETER NUMBER = 10 ELEMENT JESICiN FOH SUKVIVAHILITY
REACH NO. PATH MO. NO«MaL STATUS El.EMENT DESIGN
21
21
21
1
s as 3 -o -o -o -o -o -o -o -o
M 1M ?K 3 -0 -0 -0 -0 -0 -U -0
M *M /t3 ? -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER = 10 ELEMENT DESIGN FOP SVATLABILITY
REACH NO. PATH NO. NORMAL STATUS. ELEMENT DESIGN
21 1 1
21 2 1
21 3 2
••• I M S L(UEHTST) ••• WARNING
*•« IMS L(UERTST) ••* WARNING
S 25 3 -0 -0 -0 -0 -0 -0 -0 -0
M 1M 2P 3 -0 -0 -0 -0 -0 -0 -0
M 6M 7P Z -0 -0 -0 -0 -0 -0 -0
LUOATF 2
LE'JTlF 2
PARAMETER NUMBER = 10
REACH NO. = PI CAP =
SUPtf
6.9959-IE-01 AVAIL = 9.99925E-01 ELEMENT EFF. « 1.77U9E-02
PARAMETER NUMBER = 11 ELEMENT UESI6N Fo» SIIHi/IVABlL ITY
REACH NO. PATH NO. NOHMflL STATUS ELEMENT OESIGN
9
9
9
21
21
21
30
30
30
M 5S 2S 3 -0 -0 -0 -0 -0 -0 -0
M 1"> 3F 3 -0 -I) -0 -0 -0 -0 -0
M hM «P ? -0 -0 -0 -0 -0 -0 -0
S 2S 3rt S -0 -0 -U -0 -U -0 -0
M 1M JP 3 -0 -0 -0 -0 -0 -0 -0
M h« «P ? -0 -0 -U -0 -0 -0 -0
Ml
1
***
1 M SS 2S 3 -0 -0 -0 -0 -0 -0 -0
1 M 1M 3H 3 -0 -0 -l> -0 -I -U -U
? * 6" BP ? -0 -0 -U -0 -Cl -0 -0
1 S 25 3.< 5 -0 -0 -0 -0 -U -U -0
HJOATF >
Li-iim ?
1 1 1« In1 3 -0 -0 -U -0 -0 -0 -0
2 M 1M rtK> ^ -(I -0 -I) -0 -0 -0 -0
1 Ml^S ?S 3 -0 -U -U -0 -U -0 -0
1 '110'* IIP 3 -0 -0 -U -0 -0 -U -0
? M|5Mi»,H 2 -n -o -u -o -o -o -c
LE'11 IF ?
PARAMETER NUMHER = 11
REACH NO. -» 9 CAP = 1.951SBE-0? SUOV
REACH NO. - 30 CAP * 6,*940U£-OJ
1 Ai/AIL = 9.28502fc-01 ELEMENT EFF. = 1.1472*6-02
f-.J30?2E-01 AVAIL = 9.
-------
PARAMETER NUMBER « 17 ELEMENT UESIGN FOR SUP.VIVABIL ITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
2
2
2
IB
18
18
21
31
31
36
3k
36
S 2S 3M1<3
M 1M <«P 3
M 6M >M -JP ?
S 2S 3 -0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 t 1 1
1 1 1 1 1 1 1 t 1 1 1 1
-0
-U
-0
-0
-0
-0
-0
-a
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-U
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
PARAMETER NUMBER = 17 ELEMENT OF^IGN
AVAILAH1L1TY
REACH NO. PATH NO. NOrtMAL iTATUS E|_EM£NT DESIGN
•"• IMS
••• IMS
I M S
I M S
I M S
I M S
I M S
I H S
2
2
2
ie
L(UERTST)
L(UERTST)
16
16
21
L1UERTST)
LIUERTST)
21
21
36
L(UEHTST)
L(UERTST)
36
36
L(UERTST)
L(UERTST)
WAPNING
WAKNING
WARMING
WARNING
WARNING
WARNING
• #•
•»•
WARNING
WARNING
PARAMETER NUMBER « 17
REACH NO. «
REACH NO. *
REACH NO. »
REACH NO. »
Z CAP «
18 CAP *
21 CAP *
36 CAP «
2.577UE-0« SO»V
1.7112UE-G? SURV
2«663^E-u2 SO^V
l«747*mE-ii2 SUSV
S 2S 3M|9 -0 -0 -0
M IM ttp 3 -0 -0 -U
M 6M yP 2 -0 -0 -0
S 25 3 -0 -0 -0 -0
LUHATF ?
LEOT1F 2
M10M12P 3 -0 -0 -0
M|5M17P ? -0 -0 -0
S 2S 3 -0 -0 -0 -0
LUOATF ?
LEOT1F 2
M IM 4P 3 -0 -0 -U
M 6M <5P 2 -0 -0 -0
S 2S 3 -0 -0 -0 -0
LUOATF 2
LtuTlF 2
M10M12P 3 -0 -0 -0
M15M17P 2 -0 -0 -0
LUOATF 2
LEOT1F 2
•0 -0
•0 -0
•0 -0
-0 -0
•0 -0
•0 -0
•0 -0
• o -o
•0 -0
•0 -0
•0 -0
•0 -0
-0 -0
-0 -0
•0 -0
-(I -o
•0 -0
•u -o
•0 -0
•0 -0
•0 -0
-0 -0
•0 -0
•0 -0
l AVAIL >
3.92912E-01 AVAIL *
3.W12E-01 AVAIL »
3.9?Ml?E-01 AVAIL =
9.t>ao6iE-oi ELEMENT EFF. » 3.6Qt>o9E-os
9.99801E-01 CLEMENT EFF. * 6.722SOE-03
9.99801E-01 ELEMENT EFF. « i.o«633E-o2
9.99801E-01 ELEMENT EFF. » 6.8647JE-03
SYSTEM EFFECTIVENESS « 1.0»351f-01
TOTAL COST • 4.36675t»05
COST/EFF. « *.030?OE»06
CANDIDATE 2. 2 DATA DECK
CONTROL F 001020011221011120 5. 60
USGS
USGS
USGS
USGS
USGS
USGS
USGS
USGS •
END
01
02
03
04
05
06
07
08
03091500
03094000
03098000
03099500
03103500
03105500
03107500
03095500
05
07
25
29
13
33
36
11
010?0 30405
0607080910
212223242526
2728293031
131<»1516171B1920
323334
35363738
1112
2.
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386
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CHAR1105
CHAR 11 Oft
CHAR1107
CHARllOft
CHAR1109TT
CHAR1110
CHAR1111
CHAR 11 12
CHAR 11 13
CHAR1114
CHAR1115
CHAR1116
CHAR1117
CHAR1118
CHAR 1 11<»
CHAR1120
CHAR1121TT
CHAR1122
CHAR1J23
CHAR1124
CHAR 1125
CHAR1126
CHAR1127
CHAR1128
CHAR 1129
CHAR1130TT
CHAR1131
CHAR1132
CHAR 11 33
CHAR 11 34
CHAR 11 35
CHAR 11 36
CHAR1137
CHAR 11 38
END
CHAR1701
CHAR1702TT
CHAR1703
CHAR1704
CHAR1705
CHAR1706
CHAR 170 7
CHAR1708
CHAR1709
.005
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0.0
0.0
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0.0
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0.1
0.1
0.1
0.1
0.1
0.1
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0.005
0.005
0.005
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5.0
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37.00
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0.0417
82.3
0.05
0.15
6.75
O.Z5
388
-------
CHAR1710TT
CHAR1711
CHAR1712
CHAR1713
CHAR1714
CHAR1715
CHAR1716
CHAR1717
CHAR1718TT
CHAR1719
CHAR1720
CHAR1721
CHAR1722
CHAR1723
CHAR 172*
CHAR 1725
CHAR 1726
CHAR1727
CHAR1728
CHAR 1729
CHAR1730
CHAR1731
CHAR1732
CHAR 1733
CHAR 1734
CHAR 1735
CHAR1736TT
CHAR 1737
CHAR1738
END
MTTF 21
MTTF 22
MTTF 23
MTTF 24
MTTF 25
MTTF 26
MTTF 27
MTTF 28
MTTF 29
MTTF 31
MTTF 32
MTTF 33
MTTF 34
MTTF 35
MTTF 36
MTTF 37
MTTF 38
MTTF 39
MTTF 40
MTTF 41
MTTF 42
MTTF 43
MTTF 44
MTTF 50
MTTF 51
MTTF 52
MTTF 53
END
SURV 30
SURV 30
SURV 30
SURV 30
SURV 30
END
AVAIL 30
AVAIL 30
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
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5.0
5.0
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5.0
5.0
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100.
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45.
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45.
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75
75
75
•
1M22S02S03
1M50M28P03
2M29P02S04S05
2M26POS
3M53P04
1M22S02S03
1M50M28P03
0.25
0.25
0.25
389
-------
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
AVAR
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
30
30
30
21
21
21
21
21
21
09
09
09
21
21
21
30
30
30
30
30
09
09
09
21
21
21
30
30
30
30
30
02
02
02
10
10
10
16
18
16
18
18
36
36
36
36
36
02
02
02
10
10
10
18
18
18
18
18
36
36
05
05
05
10
10
10
10
10
10
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
3
4
5
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
4
5
1
2
3
1
2
3
1
2
3
4
5
1
2
3
1
2
3
1
2
3
4
5
1
2
3
4
5
1
2
3
1
2
3
1
2
3
4
5
1
?
2M?S>P02S04S05
2M26P05
3M53P04
1M31S02S03
1M44M41M42P03
2M43M38P02
1M31S02S03
1M44M41M42P03
2M43M38P02
1S02S03M32
1P03M40M41M42
2P02M39M38
1M33S02S03
1M44M41M42P03
1M23S02S03
1M50M28P03
2M29P02S04S05
2M26P05
3M53P04
1S02S03M32
1P03M40M41M4P
2P02M39M38
1M33S02S03
1M44M41M42P03
2M43M38P02
1M23S02S03
1M50M28P03
2M2VP02S04S05
2M26P05
3M53P04
1S02S03M34M38
1P03M37
2P02M36
1M35S02S03
1M44M41M42P03
2M43M38P02
1M21S02S03
1M27M28P03
2M?5S04S05P02
2M26P05
3M53P04
1M24S02S03
1M52M28P03
2M51P02S04S05
2M26P05
3M53P04
1S02S03M34M38
1P03M37
2P02M36
1M3SS02S03
1M44M41M42P03
2M43M38P02
1M21S02S03
1M27M28P03
2M25S04S05P02
2M?6P05
3M53P04
1M24S02S03
1M52M28P03
390
-------
AVAIL
AVAIL
AVAIL
END
COSTS
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTG
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
COSTM
END
#
36
36
36
1
2
3
4
5
6
7
8
9
10
11
12
13
21
22
S3
24
25
26
27
28
29
31
32
33
34
35
36
37
30
39
40
41
42
43
44
50
51
52
53
17 3
17 4
17 5
40000.
10000.
20000.
6000.
1000.
1000.
1000.
10000.
20000.
5000.
1000.
1000.
1000.
1200.
800.
3500.
1200.
1200.
5200.
7000.
45000.
1200.
3500.
3500.
3500.
1200.
1200.
1200.
1800.
5200.
1200.
4500.
0.
40000.
1200.
4500.
7000.
1200.
7000.
3000.
2M51P02S04S05
2M26P05
3M53P04
0.0
2SOOO.
5000.
12500.
750.
750.
7SO.
25000.
5000.
12500.
750.
750.
750.
1000.
500.
1500.
1000.
100.
25000.
2000.
2500.
100.
1500.
1500.
1500.
1000.
1000.
100.
100.
25000.
100.
2000.
60000.
2000.
100.
2000.
2000.
100.
2000.
2SOOO.
0.0
0.0
0.0
2500.
1750.
1750.
17SO.
.0
0.0
2500.
1750.
1750.
1750.
1000.
250.
1750.
1000.
250.
2000.
5000.
5000.
250.
1750.
1750.
17SO.
1000.
1000.
25U.
250.
2000.
250.
4500.
0.
5000.
250.
4500.
5000.
250.
5000.
2000.
0.0
0.0
10000.
1000.
0.
0.
0.
0.0
10000.
1000.
0.
0.
0.
•300.
100.
500.
SCO.
100.
1^00.
1000.
20000.
100.
¥.00.
500.
500.
500.
500.
100.
100.
1500.
100.
1000.
0.
20000.
100.
1000.
1000.
100.
1000.
500.
0
1
2
2
2
2
2
1
8
8
ft
8
8
11
12
12
13
11
10
11
9
12
7
6
7
5
7
S
5
4
6
6
3
3
7
7
12
13
13
13
CANDIDATE 2.2 RESULTS
DESIGN TYPE * F SYSTEM OUR.
'i.OO NO. OF MONTHS
60 FLOW SCALING FACTORS * 1.0 5.0 2.0
STA. NO.
ST«. I.D.
SEC. NO.
SEG. ASSOCIATION
1
2
3
4
5
6
7
B
3091500
3094000
309AODO
3099500
3103500
3105500
3107500
3095500
*>
7
25
29
13
33
36
11
1234 5-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
678 910-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
313223342526-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
372B3930 31-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
1314151617181920-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
323334-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
35363738-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
1112-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0-0
391
-------
PARAMETER NUMBER = 5
BEACH NO. IMPL. MN. PLCr.
CT
DFLT» IMPL. LOC. EPSI
SEPS!
TUP
TOOXN
1
-1
3
4
5
h
7
8
9
10
11
12
13
1A
15
16
IT
18
19
20
21
22
23
2*
25
26
27
28
29
30
31
32
33
34
35
36
37
38
F
F
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F
F
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F
F
F
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F
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1500.000
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1500.000
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500.000
500.000
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6. 75
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392
-------
PARAMETER NUMBER » 10
REACH NO. IMPL. MN. PLCY. CT
DELTA IMPL. LOC. EPSI
SEPSI
TUP
TDOWN
1
2
3
«
5
6
1
8
9
10
11
12
13
14
15
16
17
IB
19
10
21
22
23
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?6
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31
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1h
17
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F
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-O.L'O
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-o.ooo
-0.000
.030
-0.000
-0.000
-0.000
-0.000
-0.000
-u.ooo
-0.000
-0.000
-o.ooo
-o.ooo
-0.000
-o.ooo
-0.000
-O.UOO
-0.000
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-0.000
-o.ooo
-o.ooo
-o.ooo
-0.000
-0.000
-0.000
-o.ooo
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.7S
-0.00
-0.00 .
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-n.OO
-0.00
-n.oo
-n.OO
-n.no
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00'
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-o.oo
-0.00
-0,00
-0.00
-o.oo
-0.00
393
-------
PARAMETER NIIM8F9 = 11
REACH NO. IMPL. MN. PLCY.
cr
DFLT4 JMPL. LOC. EPSI
SEPSI
TDOWN
1
2
3
4
•=<
ft
7
A
t
10
11
12
13
l
-------
PARAMETER NUMBER * 17
REACH NO. IMPL. MM. PLCY. CT
DELTA IMPL. LOC. EPSI
SEPSI
TUP
TDOWN
1
2
3
it
5
6
7
8
9
10
11
12
13
14
IS
16
17
18
19
'0
21
22
23
24
25
26
27
26
29
30
31
32
33
34
35
36
37
38
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
F
f
T
F
F
F
F
F
F
f
F
F
F
F
F
F
F
F
f
F
T
F
F
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
f
F
T
F
F
5.000
5.000
5.000
5.000
5.000
b.OOU
3.000
3\.ooo
5.000
3.000
5.000
5.000
S.OOO
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
3.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
-0.00
.04
-0.00
-A. 00
-0.00
-0.00
-0.00
-0.00
-n.oo
.04
-o.oo
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
.04
-0.00
-n.oo
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-o.oo
-0.00
-0.00
82.50
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
31.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
36.80
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
7. HO
-0.00
-0.00
-0.000
.050
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
.050
-o.ooo
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
.050
-0.000
-0.000
-0.000
.150
-o.ooo
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.150
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
.150
-0.000
-0.000
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
J-0'00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-n.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.oo
-0.00
-0.00
-o.to
-0.00
-0.00
-0.00
6.7S
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
395
-------
MEANS NO.
ST&TE 1 = OPErtATlMG. STATE 2 = STAND-BY
MTTFS-1 MTTFS-2 MTTFA-I MTTFA-2 MTTRA-1
MTTRA-2
21
22
23
?4
25
26
27
2H
? 5
BEACH HO. • 30 CAP « 7.6392SE-03 SUOV = 7.25916E-01 AVAIL * 9.99296E-01 ELEMENT EFF.
5.541S6E-03
PAHA-'ETER NUMBED * 10 ELEMENT DESIGN FnS SUKVIVABIL ITT
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
21
21
?S 3 -0 -0 -0 -0 -0 -0 -0
^ 3 -0 '0 -0 -0 -0 -0
M43M3JP ? -0 -0 -0 -0 -0 -0 -0
396
-------
PARAMETER NUMBER « 10 ELEMENT DESIGN FOX AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
21
21
•••INS L(UERTST)
••• IMS L> ?S 4S 5 -0 -0 -0 -0 -« -0
? d?6P b -0 -0 -0 -0 -0 -0 -0 -0
3 M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
LUDATF 7
LEOT1F I
PARAMETER NUMBER * 11
REACH NO. « 9 CAP * 3.62958E-U? SUQV «
REACH NO. • 21 CAP > 1.0Z633E-02 SURV '
REACH NO. « 30 CAP « 8.737-.1E-03 SURV «
7.172B3E-01 AVAIL * 9.78445E-01 ELEMENT EFF. - 2.5*732E-02
7.17283E-01 AVAIL « 9.7B
-------
PARAMETER NUMBER * 17 ELEMENT DESIGN FOR SURVIVABlLITr
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
2
a
3
10
10
10
18
18
18
36
36
36
36
36
S 2S 3M34M3B -0
P 3M37 -0 -0 -0
P 3M36 -0 -0 -0
MISS ?S 3 -0 -0
M43M3RP ? -0 -0
M?1S ?S 3 -0 -0
M77M28P 3 -0 -0
*?5S 4S 5P 2 -0
M76P b -0 -0 -0
MS3P 4 -0 -0 -0
*:>4S 2S 3 -0 -0
MS2M2SP 3 -0 -0
MmP 2S 4S S -0
M76P 5 -0 -0 -0
HS3P 4 -0 -0 -0
-0 -0
-0 -0
-0 -0
-o -o
-0 -0
-o -o
-o -o
-o -o
-o -o
-0 -0
-o -o
-0 -0
-0 -0
-o -o
-0 -0
-o -o
-0 -0
-0 -0
-0 -0
-o -o
-0 -0
-o -o
-o -o
-o -o
-o -o
-0 -0
-o -o
-0 -0
-0 -0
-o -o
-0 -0
-o -o
PARAMETER NUMSER = 17 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
2
2
2
10
I M S L(UERTST)
I M S L(UERTST)
10
10
ia
I M S L(UERTST)
1 M S L(UERTST)
18
IB
18
18
36
I M S L(UERTST)
I M S L(UERTST)
36
1
2
3
1
«•• WARNING
*»• WARNING
2
3
1
•»• WARNING
••• W/IPNING
£
3
4
S
1
• •« HONING
••* WARNING
?
36
16
•••IMS L(UERTST)
•••IMS L(UERTST)
PARAMETER
REACH HO. s ? TftP ±
REACH NO. = 1 :< CAP =
REACH NO. = 1R CAP s
REACH NO. = 36 cap =
WARNING
WARNING
E- J 5UPV =
SiJJV =
S 2S 3M34M3B
P 3M37 -0
P 3M36 -0
M15S 2S 3
LUnATF
LEOTlF
M44M41M42P
M43M3HP 2
"I21S 2S 3
LUOATF
LEOT1F
M77M2BP 3
M?5S 4S 5P
M»6P •; -0
MS3P 4 -0
M?4S 2S 3
LUDATF
LEOT1F
H^2M28P 3
mmp ?s 45
M76P 5 -0
H«;3P 4 -0
LUnATF
LEOT1F
-0
-0
-0
3
-0
-0
-0
2
-0
-0
-0
-0
s
-0
-0
-0
-0
-0
-0
2
2
-0
-0
-0
2
2
-0
-0
-0
-0
-0
?
2
-0
-0
-0
-0
2
2
-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
-o
-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
?.543
-------
CANDIDATE 2. 3 DATA DECK
CONTROL F 0010200112?10111?0 -5.
USGS
USGS
USGS
USGS
USGS
USGS
USGS
USGS
END
01
02
03
04
05
06
07
08
03091500
0309*000
0309*000
03099500
03103500
03105500
03107500
03095500
05 010?030405
07 06U70SG910
?5 21?2232425
39 ?7?H?93031
13 1314151617
33 323334
36 353t>3738
11 111?
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CHAS0501
CHAR050?
CHAU0504
CHAHQ505
CHAR0507
CMAR050B
CHAR0510
CMAR0511
CHAR0512
CHAW0513
CHAR0514
CHAR0515
CHAR0516
CHAR0517
CHAR05l«
CHAR0520
CHAR0521
CHAR0522
CHAR0523
CHAR0524
CHAR0525
CHAR0526
CHAR05Z7
CHAR0529
CHAR0530TT
CHAROS31
CHAR0532
CHAR0533
CHAR0535
CHAR0536
CMAR0537
END
CHAR1001
CHAR1002
CHAR1003
CHAR1005
CHARIOOA
CHAR1007
CHARlOOfl
CMAR1009
CHAR1010
CHAR1011
CHAR101?
1500.
1500.
1500.
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399
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CHAR 10 13
CHAR1014
CHAR1015
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CHAR 10 17
CHAR101H
CHARIOT
CHAR1020
CHAR102JTT
CHAR1022
CHAR1023
CHAR1024
CHAR1025
CHAR 1026
CHAR1027
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CHAR1032
CHAR1033
CHAR103**
CHAR1035
CHAR 10 36
CHAR1037
CHAR103H
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CHAR1101
CHAR110?
CHAR 11 03
CHAR1104
CHAR1105
CHAR 11 06
CHAR1107
CHAR110H
CHAR1109TT
CHAR! 110
CHAR1111
CHAR1112
CHAR 11 13
CHAR 111*
CHAR 11 15
CHAR1116
CHAR1117
CHAR111B
CHAR1119
CHAR 11 20
CHARU21TT
CHARU22
CHAR 1123
CHAR112<»TT
CHAR1125
CHAR1126
CHARH27TT
CHAR1128TT
CHAR1129TT
CHAflU30TT
CHAR1131
CHAR 11 32
CHAR 11 33
CHAR 11 34
CHAR 11 35
CHAR 11 36
CHAR1137
CHAR1138
END
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0.00
0.0
0.0
0.00
0.0
0.0
0.0
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.005
0.005
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0.005
0.005
0.005
0.005
0.005
0.1
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0.
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0.005
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0. 0<»17 31.0
0.0417 37. 00
0.0417 31« 0
O.OM7 33.5 .001
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0,0^17 16.5 .001
O.OM7 15.5 .001
0.0417 12«i
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6.75
0.25
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6.75
0.25
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6.75
0.25
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6.75
6.75
6.75
6.75
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0.25
0.25
0.25
0.25
0.25
400
-------
CHAR1701
CHAR1702TT
CHAR1703
CHAR170<»
CHAR1705
CHAR1706
CHAR 170 7
CHAR 170 8
CHAR1709
CHAR1710TT
CHAR1711
CHAR1712
CHAR1713
CHAR1714
CHAR1715
CHAR1716TT
CHAR1717TT
CHAR1718TT
CHAR1719TT
CHAR1720
CHAR1721
CHAR1722
CHAR1723
CHAR 1724
CHAR 1725
CHAR 1726
CHAR 1727
CHAR1728
CHAR1729
CHAR1730
CHAR1731
CHAR1732
CHAR 173 .1
CHAR 1734
CHAR1735TT
CHAR1736TT
CHAR1737
CHAR1738
END
MTTF 21
MTTF ?2
MTTF ?3
MTTF 24
MTTF 25
MTTF 26
MTTF 27
MTTF 28
MTTF 29
MTTF 31
MTTF 32
MTTF 33
MTTF 34
MTTF 35
MTTF 36
MTTF 37
MTTF 38
MTTF 39
MTTF 40
MTTF 41
MTTF 42
MTTF 43
MTTF 44
MTTF 50
MTTF 51
.MTTF 52
\MTTF 53
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
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5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
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.2
.2
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.2
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36S. 100.
3SS. 100.
365. 100.
365. 100.
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3. 365.
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0.25
0.25
0.25
0.25
0.25
0.25
0.25
0.25
401
-------
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
MTTF
END
SURV
SURV
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
END
AVAIL
AVAIL
AVAIL
END
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
SURV
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
30
30
30
30
30
30
30
30
30
30
21
21
21
21
21
21
09
09
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21
21
24
24
24
27
27
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28
29
29
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11
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30
30
09
09
09
21
21
21
24
24
24
27
27
27
28
28
28
29
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16
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17
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18
18
18
18
19
19
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19
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35
35
35
35
35
36
36
36
36
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02
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11
11
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AVAIL
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10
10
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16
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16
16
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23
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26
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*
32
33
34
35
36
37
38
39
40
41
42
43
44
50
51
5?
53
71
72
73
74
75
76
77
78
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80
81
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84
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92
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CANDIDATE 2. 3 RESULTS
DESIGN
TYPE =
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PARAMETER NDMrtFH = -,
REACH NO. IMPL. MN. PLCY.
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PARAMETER NUMBER . 10
REACH NO. IMPL. «N. PLCt. CT
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PARAMETER NUMBER * 11
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-0.00
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.04
.04
.04
.04
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-o.oo
-o.oo
-0.00
-0.00
-0.00
-o.ou
-0.00
-o.oo
-0.1)0
-o.oo
37.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
31.00
-0.00
-o.oo
23.50
-t.oo
-0.00
18.50
16.50
15.50
12.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
.001
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
.001
-0.000
-0.000
.001
-0.000
-0.000
.001
.001
.001
.001
-o.ooo
-0.000
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-o.ooo
-0.000
-o.aoo
.005
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.005
-0.000
-0.000
.005
-0.000
-0.000
.005
.oos
.oos
.oos
-o.ooo
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.7S
-0.00
-0.00
6.75
-0.00
-0.00
6.75
6.75
6.75
6.75
-o.oo
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
.25
-0.00
-0.00
.25
.25
.25
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
•0.00
408
-------
PARAMETER NUMBER • 17
REACH NO. IMPL. MM. PLCY.
CT
DELTA IMPL. LOC. EPSI
SEPSI
TUP
TDOWN
1
2
3
4
5
6
7
e
9
10
11
12
13
14
IS
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
39
34
35
36
37
38
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
T
T
T
T
F
F
F-
F
F
F
F
F
F
F
F
F
F
F
F
T
T
F
F
F
T
F
F
F
F
F
F
F
T
F
F
F
F
F
1
T
T
T
F
F
' F
F
F
F
F
F
F
F
F
F
F
F
F
T
T
F
F
5.000
S.OOO
5.000
5.000
5.000
b. 000
S.OOO
5.000
5.000
5.000
3.000
b.OOO
5.000
s.ooo
5.000
5.000
5.000
s.ooo
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
5.000
S.OOO
5.000
5.000
5.000
5.000
5.000
-0.00
.04
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
-0.00
.04
-0.00
-0.00
-0.00
-o.oo
-0.00
.04
.04
.04
.04
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.04
.04
-0.00
-0.00
-0.00
82.50
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
31.00
-0.00
-0.00
-0.00
-0.00
-0.00
44.80
42.40
36. 80
35.60
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-o.oo
-0.00
-0.00
-0.00
-0.00
7.80
4.60
-0.00
*-0.00
-0.000
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-o.ooo
-0.000
.050
-0.000
-0.000
-0.000
-0.000
-0.000
.050
.050
.050
.050
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.050
.050
-0.000
-0.000
-0.000
.ISO
-0.000
-0.000
-0.000
-o.ooo
-0.000
-0.000
-0.000
.150
-0.000
-0,000
-0.000
-0.000
-0.000
.ISO
.150
.ISO
.ISO
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
-0.000
.ISO
.ISO
-0.000
-0.000
-0.00
6. 75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
-0.00
-0.00
-0.00
-o.oo
-0.00
6.75
6.75
6.75
6.75
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
6.75
6.75
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.25
-0.00
-0.00
-0.00
-0.00
-0.00
.25
.25
.25
.25
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
-0.00
.2S
.25
-0.00
-0.00
409
-------
MEANS NO.
STUTt 1 = UPexnTInG. STATE 2 = STANO-HY
••1TTFS-1 MTTKS-? -tTTFfl-1 MFTFA-2 MTFrtA-1
MTTHA-2
21
22
23
2.4
25
2b
27
28
29
31
32
33
3*
35
36
37
38
39
40
41
42
43
44
50
51
52
53
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
.20
.?u
.ril
.?u
.20
.01
.01
.20
.20
.20
.20
.20
.01
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.2(1
.21)
.20
.20
.20
.20
.20
.20
.20
.20
.20
.20
.01
.ul
.01
.01
.01
.01
.01
.01
.01
.01
.ul
.01
.01
.Ul
.01
!ol
.01
.ul
.Ul
.01
.ul
.Ul
.Ul
.Ul
.Ul
.Ul
.Ul
.ul
.ul
.Ul
.01
.Ul
.01
.Ul
.Ul
.01
.01
.01
.01
.01
.ul
.01
5. on
5.00
6.01'
5.00
1.00
2.00
s.oo
3. OP
1.00
6.00
6.00
6.00
5.00
5.00
3.00
3.00
2.00
3.00
5.00
52.00
3.00
3.00
5.00
5.00
3.00
5.00
2.00
6.00
3.00
5.00
6.00
3.00
5.00
6.00
3.00
5.00
6.00
3.00
5.00
5.00
3.00
5.00
5.00
3.00
5.00
5.00
3.00
5.00
5.00
3.00
5.00
365.00
J65.0U
3*5.00
305.00
.30
.50
1.00
3.00
.30
365.00
365.00
365.00
365.00
365.00
.30
.30
.50
.30
1.00
52.00
3.00
.30
1.00
1.00
.30
1.00
.50
365.00
.30
1.00
365.00
.30
1.00
365.00
.30
1.00
365.00
.30
1.00
365.00
.30
1.00
365.00
.30
1.00
365.00
.30
1.00
365.00
.30
1.00
100.00
100.00
100.00
100.00
100.00
365.00
137.00
365.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
365.00
100.00
137.00
9999.00
365.00
100.00
137.00
137.00
100.00
137.00
365.00
100.00
100.00
137.00
100.00
100.00
137.00
100.00
100.00
137.00
100.00
100.00
137.00
100.00
100.00
137.00
100.00
100.00
137.00
100.00
100.00
137.00
100.00
100.00
137.00
365.00
365.00
365.00
365.00
45.00
365.00
137.00
365.00
45.00
365.00
365.00
365.00
365.00
365.00
45.00
45.00
365.00
45.00
137.00
9999.00
365.00
45.00
137.00
137.00
45.00
137.00
365.00
365.00
45.00
137.00
365.00
45.00
137.00
365.00
45.00
137.00
365.00
45.00
137.00
365.00
45.00
137.00
365.00
45.00
137.00
365.00
45.00
137.00
365.00
45.00
137.00
PARAMETER NUMBER » 5 ELEMENT UESIGN Foft SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
30
30
30
30
30
PARAMETER
REACH NO.
30
30
30
30
30
'••IMS L(UERTST)
'••IMS LIUERTST)
1
2
3
4
5
NUMBER « 5
1
1
2
2
3
M22S 2S 3 -0 -0 -0 -0 -0 -0 -0
M50M28P 3 -0 -0 -0 -0 -0 -0 -0
M29P 2S 4S 5 -0 -0 -0 -0 -0 -0
M26P 5 -0 -0 -0 -0 -0 -0 -0 -0
MS3P 4 -o -0 -0 -0 -0 -0 -0 -0
ELEMENT DESIGN FOR AVAILABILITY
PATH NO. NORMAL STATUS
1
2
3
4
5
••• HAPNING
••• WARNING
1
1
2
2
3
ELEMENT DESIGN
M22S 2S 3 -0 -0 -0 -0 -0 -0 -0
MSOM2PP 3 -0 -0 -0 -0 -0 -0 -0
M29P 2S 4S 5 -0 -0 -0 -0 -0 -0
M?6P 5 -0 -0 -0 -0 -0 -0 -0 -0
M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
LUOATF 2
LEOT1F 2
PARAMETER NUMBER * ?
REACH NO. * 30 CAP «
7.6392SE-03 SURV
7.25916E-01 AVAIL
410
9.99296E-01 ELEMENT EFF.
5.54156E-03
-------
PARAMETER NUMBER » 10 ELEMENT DESIGN FOR SURVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
21
31
21
1 M31S 25 3 -0 -0 -0 -0 -0 -0 -0
1 M44M41M42P 3 -0 -0 -0 -0 -0 -0
2 M43M38P 2 -0 -0 -0 -0 -0 -0 -0
PARAMETER NUMBER * 10 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
•*•
21
21
21
IMS LIUERTSTI
I H S LIUERTST)
WARNING
WARNIN6
PARAMETER NUMBER • 10
REACH NO. * 21 CAP * 3.36824E-02 SURV
M31S 35 3 -0 -0 -0 -0 -0 -0 -0
M44M41M42P 3 -0 -0 -0 -0 -0 -0
M43M38P 2 -0 -0 -0 -0 -0 -0 -0
LUOATF ?
LEOT1F 2
7.172B3E-01 AVAIL • 9.78445E-01 ELEMENT EFF. « 2.36390E-02
PARAMETER NUMBER * 11 ELEMENT UES1GN FOR SUHVIVABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
9
9
9
21
21
21
24
24
34
27
27
27
28
28
28
29
29
29
30
30
30
30
30
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
4
5
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
2
3
S 2S 3M32 -0 -0
P 3M40H41M42 -0
P 2M39M38 -0 -0
M33S 2S 3 -0 -0
M44H41M42P 3 -0
M43M38P 2 -0 -0
M71S 2S 3 -0 -0
M73M41M42P 3 -0
M72M3BP 2 -0 -0
M74S 2S 3 -0 -0
M76M41M42P 3 -0
M75M3BP 2 -0 -0
M77S 2S 3 -0 -0
M79M41M42P 3 -0
M78M3BP 2 -0 -0
MHOS 2S 3 -0 -0
M42M41M42P 3 -0
MH1M38P 2 -0 -0
M23S 2S 3 -0 -0
MSOMZBP 3 -0 -0
M?9P 2S *S 5 -0
M26P 5 -0 -0 -0
M53P 4 -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
-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
PARAMETER NUMBER - 11 ELEMENT DESIGN FOR AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
IMS
I M S
I M S
I M S
I M S
IMS
I M S
9
9
9
21
LIUERTST)
LIUERTST)
21
21
24
LIUERTST)
LIUERTST)
24
24
27
LIUERTST)
LIUERTST)
27
?7
2B
LIUERTST)
1
i
3
1
*•* WARNING
**» WARNING
2
3
1
••« WARNING
••* WARNING
;j
3
1
•** WAPNING
••* WARNING
2
3
1
••* WARNING
1 S 25 3M32 -0 -0 -0 -0 -0 -0 -0
1 P 3M4QM41M42 -0 -0 -0 -0 -0 -0
2 P 2M39M38 -0 -0 -0 -0 -0 -0 -0
1 M33S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUOATF ?
LEOT1F 2
1 M44M41M42P 3 -0 -0 -0 -0 -0 -0
2 M43M3>»P 2 -0 -0 -0 -0 -0 -0 -0
1 M71S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUDATF ?
LEOT1F 2
1 M73M41M42P 3 -0 -0 -0 -0 -0 -0
2 M72M38P ? -0 -0 -0 -0 -0 -0 -0
1 M74S ?S 3 -0 -0 -0 -0 -0 -0 -0
LUPATF ?
LEOT1F 2
1 M76M41M42P 3 -0 -0 -0 -0 -0 -0
2 M75M38P ? -0 -0 -0 -0 -0 -0 -0
1 H77S 25 3 -0 -0 -0 -0 -0 -0 -0
LUD4TF ?
411
-------
••• I M S L(UEKTST) »«* WARNING
•*• I
••• I
••• I
••• I
*•* I
••• I
?8 3
29 1
M S LIUERTST) «•* WARNING
M S LtUEfiTST> ••• WAwNING
29 2
29 3
30 1
M S LIUERTST) «•• WARNING
M S LIUERTST) •«• WARNING
30 2
30 3
30 4
30 5
M S LIUERTST) «** WAWNING
M S LIUERTST) ••• WARNING
1
1
1
2
1
1
2
2
3
M79M41M42P 3 -0 -U -0 -0 -0 -0
M78M3SP 2 -0 -0 -0 -0 -0 -0 -0
MUOS ?S 3 -0 -0 -0 -0 -0 -0 -0
LUfHTF 2
LfiJTlF 2
MR2M41M42P 3 -0 -0 -0 -0 -0 -0
M81M38P 2 -0 -0 -0 -0 -0 -0 -0
M?3S ?S 3 -0 -0 -0 -0 -0 -0 -0
LUOATF 2
LEOTIF 2
M^OM2SP 3 -0 -0 -0 -0 -0 -0 -0
M39P 2S 4S 5 -0 -0 -0 -0 -0 -0
M26P 5 -0 -0 -0 -0 -0 -0 -0 -0
M53P 4 -0 -0 -0 -0 -0 -0 -0 -0
LUOATF 2
LEOTIF 2
PARAMETER NUMBER = 11
REACH
REACH
REACH
REACH
REACH
REACH
REACH
NO. =
NO. =
NO. *
NO. =
NO. =
NO. =
NO. =
9
21
24
21
28
21
30
CAP *
CAP =
CAP »
CAP =
CAP =
CAP =
CAP =
3
1
4
4
4
5
3
.62958E-02
.02833E-02
.245«4E-U2
.31212E-03
.S8136E-02
,563il£-02
.4770HE-02
SURV =
SURV =
SURV =
SURV =
SURV =
SURV =
SURV =
7.
7.
7.
7.
7.
7.
7.
17283E-01
17283E-01
17263E-01
17283E-01
17283E-01
17283E-01
25916E-01
AVAIL «
AVAIL =
AVAIL «
AVAIL =
AVAIL *
AVAIL =
AVAIL *
9.
9.
9.
9.
9.
9.
9.
78445E-I
78445E-I
78445E-I
78445E-I
78445E-I
78445E-I
99296E-I
2.5«732t-02
7.21703E-03
3.02634E-03
3.21530E-02
3.90459E-02
2.5Z226E-02
PARAMETER NUMBEP = 17 ELEMENT UESIGN FOR SDMVIVA6ILITr
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
2
2
2
10
10
10
16
16
16
16
16
17
17
17
17
17
18
18
18
18
18
19
19
19
19
19
35
35
35
35
35
36
36
36
36
36
1
1
2
1
1
2
1
1
2
2
3
1
1
2
2
3
1
1
2
2
3
I
1
2
2
3
1
1
2
2
3
1
1
2
p
3
S 2S 3M34M38
P 3M37 -0 -0
P 2M36
M3SS
M44M'
2S
»1H
M43M3HP
Mtns
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3
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3
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3
3
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-0
3
3
5P
-0
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3
3
5P
-0
-0
3
3
4S
-0
-0
-0
-0
3
-0
-0
-0
2
-0
-0
-0
-0
2
-0
-0
-0
-0
2
-0
-0
-0
-0
2
-0
-0
-0
-0
2
-0
-0
-0
-0
5
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
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-0
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-0
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-0
-0
-0
-0
-0
-0
-0
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-0
-0
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-0
-0
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-0
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-0
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-0
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-0
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412
-------
PARAMETER NUMBER = 17 ELEMENT DESIGN FOrt AVAILABILITY
REACH NO. PATH NO. NORMAL STATUS ELEMENT DESIGN
2
2
2
10
••• IMS LIUERTST)
••• IMS LIUERTST)
10
10
16
*•• IMS LIUEftTST)
••• IMS LIUERTST)
16
16
16
16
17
••• IMS LIUEHTST)
••• IMS LIUERTST)
17
17
17
17
18
••• IMS LIUFRTST)
••• IMS LIUERTST)
18
18
18
18
19
••• IMS LIUERTST)
••• IMS LIUERTST)
19
19
19
19
35
••• IMS LIUERTST)
••• IMS LIUERTST)
35
35
35
35
36
••• IMS LIUERTST)
•••IMS LIUERTST)
36
36
36
36
••• IMS LIUERTST)
••• IMS LIUERTST)
PARAMETER NUMBER •
REACH NO. . 2 CAP
REACH NO. . lo CAP
REACH NO. . 16 CAP
REACH NO.' « 17 CAP
REACH NO. » 18 CAP
REACH NO. * 19 CAP
REACH NO. * 35 CAP
REACH NO. - 36 CAP
1 1
2 1
3 2
1 1
••* WARNING
*•* WARNING
2 1
3 2
I 1
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2 1
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4 2
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2 l
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3 j
4 2
5 3
1 1
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••• WARNING
2 1
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4 5
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17
* 9.23774E-Q3 SURV »
• 2.16616E-Q3 SURV »
' 2.17199E-03 SURV *
* 2.06497E-02 SURV •
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= 4.68920E-02 SURV *
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» 4.96172E-02 SURV *
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M3SS 2S 3 -0 -0 -0 -0 -0 -0 -0
LUOA.TF i
LEUTlF 2
I4A4M41M42P 3 -0 -0 -0 -0 -0 -0
H43M33P 2 -0 -0 -0 -0 -0 -0 -0
*«3S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUOATF ?
LEOT1F 2
MH5M2SP 3 -0 -0 -0 -0 -0 -0 -0
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MS3P S -0 -0 -0 -0 -0 -0 -0 -0
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MS6S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUDATF t
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MR8M23P 3 -0 -0 -0 -0 -0 -0 -0
MH7S «S 5P 2 -0 -0 -0 -0 -U -0
M53P 5 -0 -0 -0 -0 -0 -0 -0 -0
M»6P 4 -0 -0 -0 -0 -0 -0 -0 -0
M?1S 25 3 -0 -0 -0 -0 -0 -0 -0
LUOATF 2
LEOT1F 2
MP7M28P 3 -0 -0 -0 -0 -0 -0 -0
M?SS 4S 5P 2 -0 -0 -0 -0 -0 -0
M36P 5 -0 -0 -0 -0 -0 -0 -0 -0
HS3P 4 -0 -0 -0 -0 -0 -0 -0 -0
H*9S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUDHTF 2
LEOT1F 2
M53P S -0 -0 -0 '0 -0 -0 -0 -0
M?6P 4 -0 -0 -0 -0 -0 -0 -0 -0
M92S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUOATF 2
LEOT1F 2
M94M28P 3 -0 -0 -0 -0 -0 -0 -0
M?6P 4 -0 -0 -0 -0 -0 -0 -0 -0
K24S 2S 3 -0 -0 -0 -0 -0 -0 -0
LUDATF 2
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M52M28P 3 -0 -0 -0 -0 -0 -0 -0
M51P 2S 4S 5 -0 -0 -0 -0 -0 -0
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LUOATF 2
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2.54304E-01 AVAIL « 9.46683E-01 ELEMENT EFF. •
7.17283E-01 AVAIL ' 9.78261E-01 EtEMENT EFF. •
7.25916E-01 AVAIL • 9.99229E-01 ELEMENT EFF. •
7.25916E-01 AVAIL » 9.99229E-01 ELEMENT EFF. •
7.25916E-01 AVAIL • 9.99296E-01 ELEMENT EFF. •
7.25916E-01 AVAIL « 9.99229E-01 ELEMENT EFF. «
7.25916E-01 AVAIL « 9.99229E-01 ELEMENT EFF. «
7.25916E-01 AVAIL « 9.99296E-01 ELEMENT EFF. «
2.Z239b£-03
1.51997E-03
I.b75*7£-03
1.49784E-02
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3.40135E-02
2.20396E-02
3.59926E-02
0U.S. GOVERNMENT PRINTING OFFICE: l»74-546-317/2U-I-3
413
-------
SELECTED WATER
RESOURCES ABSTRACTS
INPUT TRANSACTION FORM
7. Rep~!ttfo.
3. Accession No.
4. Title
DESIGN OF COST-EFFECTIVE WATER QUALITY
SURVEILLANCE SYSTEMS
7. Author(s) Charles V. Beckers
Stanley G. Chamberlain
5.
6.
$. Performis" Organisation
Report No.
9. Organization
Raytheon Company
Oceanographic § Environmental Services
Portsmouth, R.I. 02871
10. Project Wo.,
1BA030
. Contract JGrant No.
68-01-0705
13. Type-c* Repot-', and
Period Covered
12. Sponsoring O'ganizst'on
IS. Supplementary Notes
Environmental Protection Agency report number,
EPA-600/5-74-004, January 1974.
16. Abstract This report presents the development and successful demonstration
of quantitative methods for the design of river basin water quality sur-
veillance systems for pollution abatement. The methods provide a system-
atic approach to the consideration of expected stream conditions, system
characteristics, equipment performance, and cost in the selection of a pre
ferred system design from among a number of candidates. In the systems
approach, the total system is evaluated for cost and effectiveness. Math-
ematics previously developed to describe the effectiveness of sampling is
used. The analysis of performance draws heavily on reliability and main-
tainability technology. Data availability remains a constraint to the
general application of the methods. The methods are computerized and the
computer programs are detailed in this report. They make use of the in-
formation available from the computerized river basin models now under gen
eral development. They are demonstrated to function satisfactorily on the
Beaver River Basin when artificial data is used to supplement the data
base. It is concluded that the methods are acceptable for use by govern-
mental water quality agencies under the existing constraints. The report
includes 31 references. This report is submitted in fulfillment of C9n-
tract Number 68-01-0703, by the Raytheon Company, Oceanographic.§ Environ-
mental Services Dejartmen^ Portsmouth, RI, under the sponsorship of the
Environmenta
»rtinn
i7a. Descriptors *Network Design, *Monitoring, *Mathematical Models, *Systems
Analysis, *Data Collection, Reliability, Maintenance, Costs, Water
Quality, Pollution Abatement, Ohio, Pennsylvania, Water Pollution, Water
Measurement, Water Quality Control, Water Quality Act
17b. Identifiers
*Monitoring Network Design, *Beaver River Basin, *Beaver
River, *Cost-Effectiveness, Surveillance, Ohio Basin
I7c. COWRRFie]<(& Group
18. Availability
19. Sr-urityC'>ass.
(Report)
None
20. Security Class.
21. A";>. of
pm
22. Price
Send To:
WATER RESOURCES SCIENTIFIC INFORMATION rFK,T--,
U.S. DEPARTMENT OF THE INTERIOR -0-1"**-" CENTER
WASHINGTON, O. C. 2O24O
A**tractor C. Beckers
Institution Ravtheon Comqany
WRSIC 102 (REV. JUNE 197 O
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