EPA-600/2-76-218

August 1976
Environmental Protection  Technology  Series
                                                      icipal Environmental Research Laborato
                                                                           KM

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                 RESEARCH REPORTING SERIES

Research reports of the Office of Research and Development, U.S. 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:
                 ; . [  •  	.'.•,:. •*!"•,;• ;v ,!	<•• •   :•• /;,(>!' /; 4,, ",","••...,*•"    M   ; "   :
     1.    Environmental Health Effects Research
     2.    Environmental Protection Technology
     3.    Ecological Research
     4.    Environmental Monitoring
     5.    Socioeconomic Environmental Studies

This report  has  been assigned  to  the ENVIRONMENTAL PROTECTION
TECHNOLOGY series. This series describes research performed to develop and
demonstrate instrumentation, equipment, and metnodblogy to repair'or prevent
environmental degradation from point  and non-point sources of pollution. This
work provides  the new or improved technology required  for the control and
treatment of pollution sources to meet  environmental quality standards.
                                                                                iiiliii 11 iiii
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.

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                                          EPA-600/2-76-218
                                          August 1976
            DEVELOPMENT AND APPLICATION  OF  A
         SIMPLIFIED STORMWATER MANAGEMENT MODEL
                           by

                      John A. Lager
                   Theodor Didriksson
                     George B. Otte
                  Metcalf & Eddy, Inc.
              Palo Alto, California 94303
                   Grant NO. Y005141
                    Project Officer

                   Anthony N. Tafuri
            Storm and Combined Sewer Section
              Wastewater Research Division
Municipal Environmental Research Laboratory  (Cincinnati)
                Edison, New Jersey 08817
      MUNICIPAL ENVIRONMENTAL RESEARCH LABORATORY
           OFFICE OF RESEARCH AND DEVELOPMENT
          U.S. ENVIRONMENTAL PROTECTION AGENCY
                 CINCINNATI, OHIO 45268

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                         DISCLAIMER

This report has been reviewed by the Municipal Environmental
Research Laboratory, U.S.  Environmental Projection  Agency,
and  approved  for  publication.   Approval does not signify
that the contents necessarily reflect the views and policies
of the  U.S.   Environmental  Protection  Agency,  nor  does
mention  of  trade  names  or commercial products constitute
endorsement or recommendation for use.

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                          'FOREWORD

The Environmental Protection Agency was created,  .because  ;pf,
increasing  public  and government concern aboutithe ..d'angers,
of pollution 'to the  health _ and . "'we If,are,  .of  .the. American,
people.   Noxious  air, '-foul  water, 'and  'spoiled land are.
tragic  testimony  to  the  deterioration'  of  our;,  natural
envi ronment.- '  The  complexi ty  of  that ,e.nvironmeht and t'he,
interplay between its components require a concentrated;"and
integrated attack on the problem.

Research and development is that  necessary  first  step  in
problem  solution  and  it  involves  defining   the problem,
measuring its impact,  and  searching  for  solutions.   The
Municipal Environmental Research Laboratory develops new and
improved   technology   and   systems  for  the  prevention,
treatment,  and  management  of  wastewater  and   solid  and
hazardous waste  pollutant  discharges  from  municipal  and
community  sources,  for  the  preservation and  treatment of
public drinking water supplies and to minimize   the  adverse
economic,   social,   health,   and   aesthetic  effects  of
pollution.  This publication is one of the products of  that
research;  a  most  vital  communications  link  between the
researcher and the user community.

The  deleterious  effects  of  storm  sewer  discharges  and
combined sewer overflows upon the  nation's  waterways  have
become  of  increasing  concern in recent times.  Efforts to
alleviate the problem depend upon characterization of  these
flows  in  both  a  quantity and quality sense.  This report
describes the development and application  of  a  simplified
stormwater  management  model that can be used to provide an
inexpensive, flexible  tool  for  planning  and  preliminary
sizing of stormwater facilities.
                            Francis T. Mayo
                               Director
            Municipal Environmental Research Laboratory
                             iii

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                           ABSTRACT

A simplified stormwater management model has been created to
provide an  inexpensive,  flexible  tool  for  planning  and
preliminary sizing of stormwater facilities.

The model  delineates  a  methodology  to  be  used  in  the
management  of  stormwater  and  consists  of  a  series  of
interrelated  tasks that combine small computer programs and
hand computations.  The model successfully  introduces  time
and  probability  into  stormwater  analysis, promotes total
system consciousness on the part of the user, and assists in
establishing    size-effectiveness     relationships     for
facilities.

Throughout this report, data from the City of Rochester, New
York, is presented and analyzed as a working example,

This report was submitted in partial  fulfillment  of  Grant
No. YOO5141  to  the Monroe County Division of  Pure  Waters
under  the  sponsorship  of  the  Environmental   Protection
Agency.  Work was completed as of June 1976.

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                           CONTENTS

                                                         Page

SECTION I   - INTRODUCTION .,...........;	      1

   Purpose .....	....	..	      1
   Tasks	      2
   Organization	      2

SECTION II  - CONCLUSIONS		      3

SECTION III - RECOMMENDATIONS	 . .		      4

SECTION IV  - MODEL DEVELOPMENT 	      5

SECTION V   - DATA PREPARATION	 . . .	      8

   System Schematic	._...'	      8
      Overflows	      8
      Drainage Areas or Subareas 	.. . ..	      9
      Interceptors 	........ i . ...	      9
      Example of a System Schematic	     11
   Quantity and Quality	     11
      Quantity 	     11
      Quality	     15
      Example of Quantity and Quality Data	     18

SECTION VI  - RAINFALL CHARACTERIZATION 	     19

   Collection of Rainfall Data 	     19
   Correlation of Rainfall Data	     20
   Definition of Discrete Storm Events 	     21
   Ranking of Design Parameters from Each Storm  	     21
   Computer Program Logic and Input-Output
    Requirements 	     24
      Storm Event Definition Program  (EVENT) 	     27
      Snowfall Inclusion Program (SNOWIN) 	     27
      Minor Storm Event Exclusion Program (EXCLUD)  ..     31
      Storm Event Sequence List Program (LISTSQ)  ....     31
      Sorting and Ranking Program (SORT) 	     34
      Listing of Ranked Files Program (LISTRK) 	     34

SECTION VII - STORAGE-TREATMENT BALANCE 	     41
                              v

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                    CONTENDS (Continued)
SECTION VII (Concluded)
                                                         Page
    Characteristics of the Storage-Treatment Program..      41
       Concept of the Program	 . i .....      41
       Operational Controls and Data Requirements  ....      41
       Output Data and Application Philosophy!: ••'-.'•>..'.:...      43
    Computer Program Logic and Input-Output
     Requirements	    44
    Example of Storage-Treatment Program Application ...    51
       Data Development	 . . . . ..... .;   54
       Alternative Analysis	    54
       Comparison of Daily and Hourly Analysis  	    60

 SECTION VIII - OVERFLOW QUALITY ASSESSMENT	    63

    Regression Analysis 	    63
       Procedure	..........;.,........    64
       Example of Equations	 .,.	    65
    Analysis of Averages 	    66
       Procedure	,	    6.6
       Examples of Averages	    67

 SECTION IX   - RECEIVING WATER RESPONSE 	    71

    Characteristics of the Receiving Water Program 	    71
    Limitations of the Receiving Water Program  	    72
    Specific Requirements of the Receiving Water
     Program	    72
    Example of the Genesee River Program Applied to
     Stormwater Overflows	    73

 SECTION X    - APPLICATION OF THE SIMPLIFIED
                STORMWATER MANAGEMENT MODEL	    80

    Computer Requirements	    81
       Hardware Requirements 	    82
       Cost of Computer Usage	    82
    Application to Storm Sewer and Nonurban Areas  	    82
       Data Preparation	»	    84
       Rainfall Analysis 	    84
       Storage-Treatment Balance	    84
       Quality Assessment 	    85
       Receiving Water Response 	    85
    Simplified and Complex Modeling 	    85

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                     CONTENTS  (Concluded)

                                                         Page

SECTION XI   - OTHER STORMWATER CONSIDERATIONS  .	    87

   Sludges . ..	    87
   Nonstructural Alternatives	    90
      Source Control Alternatives		. .	    91
      System Control Alternatives	    91

REFERENCES	    93

APPENDIX A - EXAMPLE OF MONITORING DATA FROM
             ROCHESTER, NEW YORK	. . . .	• •	    95

APPENDIX B - PROGRAM LISTING AND LIST  OF VARIABLES  	    99

APPENDIX C - DETERMINATION OF K FACTOR	   127

APPENDIX D - OVERFLOW QUALITY ASSESSMENT-ALTERNATE
             METHODS			   130

GLOSSARY	*	   136
                              Vll

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                            FIGURES

No.                                                      Page

 1    Interrelationship of Tasks in the
        Simplified Stormwater Management Model 	   5

 2    PERT Diagram of Simplified Stormwater
        Management Model		   6

 3    Types of In-System Storage 	..	  10

 4    Example of Drainage Subareas and
        Overflow Locations 	.	  12

 5    Example of Functional Elements of
        Sewerage System	  14

 6    Example of System Schematic 	  17'

 7    Programs for Rainfall Analysis . .	  22

 8    Example Curve - Storm Magnitude
        vs. Frequency	  25

 9    Example Curve - Storm Intensity
        vs. Frequency .'	  25

10    Example Curve - Storm Duration
        vs. Frequency	  26

11    Example Curve - Percent of Storms
        Having Maximum 1-hr Intensity
        vs. Hour After Start of Storm	  26

12    Flow Chart for Storm Event Definition
        Program (EVENT)	 .  29

13    Flow Chart for Snowfall Inclusion
        Program (SNOWIN)  	  32

14    Flow Chart for Minor Storm Event
        Exclusion Program (EXCLUD)  	  33
                             Vlll

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                      FIGURES (Concluded)
No.

15


16


17

18


19


20


21


22

23


24

25

26

27

28


29

C-l
                                                   Page

Flow Chart for Storm Event Sequence
  Listing Program (LISTSQ)	  35

Flow Chart for Listing of Ranked Files
  Program (LISTRK) 	  39

Concept of Storage-Treatment Program	  42

Flow Chart for Control Block of
  Storage-Treatment Program	  45

Basic Flow Chart for Subroutines     '
  of Storage-Treatment Program	;	  47

Example of System Schematic - Existing
  Rochester West Side Interceptors	  55

Frequency of Occurrence of Runoff
  and Overflows ......'	  56

Rochester West Side - Alternative 1	  57
Example of System Schematic - Modified
  Rochester West Side Interceptors
58
Rochester West Side - Alternative 2	  59

Example of System Schematic - Alternative 2 '...*..  60

Comparison of Hourly and Daily Analysis 	  62

Example of Overflow Quality Trends	 .  70

Genesee River Reaches for the Receiving .
  Water Program	 .  76
Computed Dissolved Oxygen in Genesee River
80
Comparison of Rochester Data with
  Imperviousness Predicting Equation 	 129

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                            TABLES
NO,

 1

 2


 3

 4
 6

 7

 8

 9


10


11


12

13

14

15

16


17
Example of Drainage Subarea Characteristics;

Example of Calculation of Wet-Weather Flow
  Capacity
Example of In-System Storage by Subarea

Example of Subarea Characteristics Used
        in Storage-Treatment Task
      Example of Use of Storm Event Ranking —
        2-Year Storm
Format for Hourly Rainfall Data
Format for Storm Data
Format for Snowfall Data
Example of Output from Storm Event
  Sequence Listing Program (LISTSQ)

Example of Output from Listing of
  Ranked Files Program (LISTRK) ...
Format for Control Block Data of
  Storage-Treatment Program
Format for HOUCRD Subroutine Data

Format for DLYCRD Subroutine Data

Format for DLYTAP Subroutine Data
Format for HOUTAP Subroutine Data .......

Example of Output from Storage-Treatment
  Program for Daily Analysis
Example of Output from Storage-Treatment
  Program for Hourly Analysis 	
Page

 13
 15
 16
                                                    16
                                                    23
 28
 28
 31
 36
 40
 46
 49
 50
 50
 51
 52
                                                          53
                             x

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                      TABLES (Continued)

No.                                                      Page

18    Comparison of Daily and Hourly Time
        Increment Analysis 	   61

19    Equations for Quality Projection 	   65

20    Average Overflow Quality by Subarea 	   67

21    Example of Average Overflow Quality
        by Subarea and Time Increment .................   68

2.2    Format for Receiving Water Program Data .........   74

23    Example of Receiving Water Program
        Input Data for Base Condition .................   75

24    Example of'Data for Overflows from
        Storm on June 22, 1973	   77

25    Example of Receiving Water Program          :
        Input Data from Storm on June 22, 1973	   78

26    Example of Output from Receiving Water
        Program for Storm on June 22, 1973	   79

27    Approximate Computer Cost for Simplified
        Stormwater Management Model	   83

28    Composition of Sludge from the Treatment of
        Combined Sewage Overflows . ..'. . .... ;	   88

29    Nonstructural Control Alternatives	   90

A-l   Example of Monitoring Data from
        Rochester, New York	   96

B-l   Rainfall Task - Program Listing for EVENT	  100

B-2   Rainfall Task - List of Variables for EVENT .	.  103

B-3   Rainfall Task - Program Listing for SNOWIN 	  104

B-4   Rainfall Task - List of Variables for SNOWIN 	,  105

B-5   Rainfall Task - Program Listing for EXCLUD 	  106

B-6   Rainfall Task - List of Variables for EXCLUD 	  107

B-7   Rainfall Task - Program Listing for LISTSQ ......  108
              9-       ,      :     .     '.*•.,..

                             xi

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                    TABLES  (Concluded)

No.                                                     Page

B-8   Rainfall Task - List of Variables for LISTSQ..... 110

B-9   Rainfall Task - Program Listing for LISTRK	 Ill

B-10  Rainfall Task - List of Variables for LISTRK	 112

B-ll  Storage-Treatment Task - Program Listing	 113

B-12  Storage Treatment Task - List of Variables....... 125

D-l   Quality Constants for Loading from
      Sewer Systems	 131

D-2   Quality Constants for Concentrations from
     . Sewer Systems	 132

D-3   Regression Coefficient fi	 134

D-4   Regression Coefficient f2 • - • •	 134

D-5   Regression Coefficient f3	 134
                              XII

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           ABBREVIATIONS
ADWF
avg
BOD .
COD
ft/ft
hr
in.
mgd
mg/kg
mg/1
mil gal.
min
NOD
SS, ss
TSS
VS
VS. , vs.
yr
average dry-weather flow
average                   -
biochemical oxygen demand
5-day biochemical oxygen demand
chemical oxygen demand
feet per foot
hour
inch
million gallons per day
milligrams per kilogram,
milligrams per liter
million gallons
minute
nitrogenous oxygen demand
suspended solids
total suspended solids
volatile solids
versus
year
                xiii

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                      ACKNOWLEDGMENTS

Many persons have contributed to  this  report.   Metcalf  &
Eddy,  Inc.,  gratefully  acknowledges  the  cooperation  of
O'Brien  &  Gere  Engineers,  Inc.,  and  the  Monroe County
Division of Pure Waters.  This report has been prepared as ;a
subcontracted  portion  of  a  demonstration  project  being
conducted by ,O'Brien & Gere.

Especially  acknowledged  is  the  assistance  and  guidance
provided by Frank Dr.ehwing, Vice President,  Dr.   Cornelius
Murphy,   Managing   Engineer,  and  David  Carleo, , Project
Engineer, of O'Brien & Gere, Inc.

Appreciation is expressed to Dr.  Gerald McDonald, Director,
and  Robert Hallenbeck, Chief of Technical Operation, of the
Monroe  County Division of Pure Waters for their cooperation
and assistance.    -•••-•

The support of this effort by the Storm and  Combined  Sewer
Section,  (Edison,  New  Jersey)  of  the  USEPA,  Municipal
Environmental  Research  .Laboratory,  Cincinnati,  Ohio, and
especially of Anthony Tafuri, Project Officer,"'  and  Richard
Field,   Chief,   for   their   guidance,  suggestions,  and
contributions is acknowledged with gratitude.

This report has been prepared in the Western 'Regional Office
of Metcalf & Eddy, Inc.', in Palo Alto, California, by George
Otte and Theodor Didriksson  under  the  direction  o'f  John
Lager, Vice President.
                            xiv

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                        SECTION I                 .

                       INTRODUCTION

Computer  modeling  of  stormwater  systems   is   currently
achieving  a  high  degree of precision and complexity.  The
complex models provide very valuable data for the design and
final sizing of stormwater facilities.  At  the  same  time,
the  existing  models , are extremely expensive to set up and
operate, requiring large blocks of time on  extremely  large
computer  systems.   A void has thus appeared in the area of
computer modeling.  A tool is needed for  the  planning  and
preliminary   sizing  of  facilities.   This  tool  must  be
inexpensive to  set  up  and  use,  flexible  enough  to  be
applicable  to  a  variety  of  system  configurations,  and
accurate  even  though , only  very moderate expenditures are
made for data collection and preparation.

PURPOSE

The purpose of this  report  is  to  delineate  an  approach
methodology to be used for the management of stormwater that
meets  these  criteria.   The  approach  is  formulated as a
simplified stormwater management model.  The model  consists
of  a series of uncomplicated interrelated tasks that can be
used either singly or together.  This permits  the  user  to
build  on  his  individual  data  strengths  and to focus on
individual study objectives,

The goals of this simplified model are:

     • To  introduce  time  and  probability  to  stormwater
       analyses

     • To promote total system consciousness on the part  of
       the user or reviewer

     • To establish  size-effectiveness  relationships

Just as  time  and  probability  analyses  are  important  in
sizing   water  supply   impoundments   and  safe  yields, they
are—or  should  be—equally  important   in  determining  the

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effective use of  stormwater  facilities,  Since total capture
is  not  a  necessary goal,  as  it  is  in flood control works,
for example, there  is greater latitude  in  facility  sizing
and  staged  implementation.    The trick is to determine the
relative merits of  alternatives, a task for  which  modeling
is ideally suited,

This model is -based on the premise that the  simplest  model
that  will  do  the  job is  usually the best, and has as its
primary target the breaking  down of data into a form that is
meaningful to the user.  In  so  doing, a degree of  precision
is  sacrificed  for breadth  of  coverage,  Because pf the low
cost of the model (both for  setup and  execution),  multiple
assumptions  can  be  tested  with  relative ease and over a
short period of time,

TASKS

In this simplified model five tasks are performed:

     • Data preparation

     • Rainfall characterization

     • Storage-treatment balance

     • Overflow-quality assessment

     • Receiving water response

Each task  actually  is  a  combination  of  small  computer
programs and hand computations.

ORGANIZATION

In the presentation of the five tasks in  this  report,   the
logic  of  the  analysis  is discussed, the computer program
logic  in  the  form  of  flow  charts  and   the   computer
input-output  requirements  are documented, and examples are
presented.

Throughout this  report  a  system  of  combined  sewers  is
analyzed.    The  City  of  Rochester,  New York, is used  as a
working example.   The data on Rochester were supplied by the
Monroe County Division of Pure Waters.

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                        SECTION II

                        CONCLUSIONS

1,  A  schematic  of  the  existing   system  of  stormwater
    facilities,  outlining  major  conduits   and   overflow
    discharge  locations  and sizes, is an essential part of
    the data preparation.

2.  Overflow quantities and qualities must  be  measured  to
    provide information for calibration of the model.

3.  Rankings can be prepared from  long  historical  records
    for  important  storm  parameters,  such  as  magnitude,
    duration, and intensity.

4.  Frequency of occurrence curves are easily generated from
    the ranking of storm parameters.

5.  The interrelationship between containment of  runoff  in
    storage  and  the  capacity  of   treatment   plant   or
    interceptors   can   be   quickly   reviewed  using  the
    storage-treatment computer program.

6.  The quantity, frequency and duration of overflows can be
    accurately  tabulated by  the  storage-treatment  program
    because  it uses real rainfall records  for a long period
    of time as  the data  source.            .

7.  The quality of overflows can be predicted on  the  basis
    of  storm   characteristics   using   linear   regression
    techniques..

8.  Gross  averages  of   the  quality  data  .by   subarea  can
    provide  an  indication  of  overflow  quality  and  areal
    trends in  overflow  quality.

9,  The receiving water  analysis provides  the  final  test  of
    a  control  alternative  to  determine   if   an  ^adequate
    solution has been reached.

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                          SECTION  III
1.


2.



3.




4.


5.
                    RECOMMENDATIONS

The simplified stormwater  management  model  should  be
implemented as a preliminary design and planning tool.,

The rainfall characterization should be  used  to  check
 design storms" and to provide historical perspective on
storm events as they occur.

The storage-treatment program should be used  repeatedly
to analyze various combinations  of  storage  capacities
and  interceptor  rates  to  determine  possible'optimum
conditions.
                                          be  determined
Areal trends in overflow quality  should
using simple statistical techniques.

Any_promising control alternative should be tested on
reliable and operating receiving water simulation.

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                           SECTION IV

                      MODEL DEVELOPMENT

The simplified stormwater  management model  is  composed  of
five  tasks.   In   this  chapter an overview of each task is
presented,  The  interrelationship of the tasks,  highlighted
in Figure 1, is  also  discussed,
                   1.  DATA PREPARATION


                   2.  RAINFALL CHARACTERIZATION


                   3.  STORAGE-TREATMENT  BALANCE
                   4.  OVERFLOW QUALITY ASSESSMENT-
                   5.  RECEIVING WATER RESPONSE
             FIGURE 1.   INTERRELATIONSHIP OF TASKS
            THE  SIMPLIFIED STORMWATER MANAGEMENT  MODEL
A PERT diagram  for  the  simplified  model  is  presented   in
Figure    2,   This   diagram,  developed  for   the   Rochester
project,  illustrates the tying of the various  tasks together
while focusing  on the results.   The  broken   lines  in  the
diagram   indicate  where  information  is  exchanged between
tasks and  where critical decision points are reached in  the
flow of work.

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Task 1—DATA is the  data  preparation  task  of  simplified
modeling,   In this task, the questions, what do we have and
how does it work, are answered,  A schematic diagram of  the
system  is  synthesized, and data on overflow quantities and
qualities are collected.  The data  are  collected  for  the
primary purpose of calibrating other tasks in the simplified
model.  These data feed into both the storage-treatment task
(Task 3) and the overflow quality task  (Task 4).

Task 2—RAINFALL is the rainfall  characterization  task  of
the  model.   In  this  task,  the  raw  rainfall  data  are
collected  and  analyzed.  The emphasis is on the ranking of
critical  rainfall   characteristics—the   design-sensitive
parameters.   The  results of this rainfall characterization
depend to a great extent on obtaining data for a long period
of  record  (approximately  20  years),   While  not   every
community  has such long records, ways of synthesizing these
data from other available long historical records in concert
with local data are discussed.  The actual  rainfall  record
is a critical input for the storage-treatment task  (Task 3).

Task 3—STOR-TREAT is an assessment of  the storage-treatment
balance,  In this task, rainfall is imposed on the city  and
its   system   of   separate   or   combined   sewers.   The
interrelationship between storage volumes and interceptor or
treatment plant capacities is analyzed.  The primary  output
from  this task is the  time and volume  of stormwater that is
overflowing from the system.  This output is  a  significant
input to the river response task (Task  5),

Task 4—OVERF-QUALITY is an evaluation  of  the  quality  of
potential   overflows   from  a  system  of  interceptors  or
treatment facilities.   The  .data  prepared  in  Task  1  are
analyzed  using ; statistical  techniques  to develop trends.
The magnitude of  overflow  constituents  is  predicted  for
input into the river response task  (Task 5).

Task  5—RIVER is the task  in  which  the  response  of  the
receiving  waters  to   overflows  is  determined.   Overflow
volumes determined  in Task  3  are   paired  with overflow
qualities developed in  Task  4  to  become  loadings  on  the
river.   The  receiving waters  are  analyzed with the best
simulation that  is available.  For Rochester, a model of the
Genesee River, prepared by O'Brien and  Gere, is used.

The  relative  success of stormwater control alternatives  can
be   checked   at  two  major  points  in  the simplified model,
After the  storage-treatment  task  has   been  performed,  the
duration,  volume, and  frequency of  overflows can be checked
to determine  the  impact of an  alternative.  And,  after  the
river   task   has been completed, the  impact on  the  receiving
water of a control alternative can  also be checked,

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                           SECTION V                   • -  • <

                       DATA PREPARATION              .,   .<.

The  establishment  of  a firm data  base is  a  very  -iimportant
step  in   the modeling process.   The data that  are collected
must answer  the  questions:  What  do we have  and how does   it
work?     In   answering   these   questions,  input  for   the
storage-treatment  task and  the overflow- quality  task  will
be developed.

SYSTEM SCHEMATIC

A good way to gain an understanding of the sewer system   and
its   relationship  to  the  existing  overflow  points  is  to
prepare a  schematic of the  system  showing  the  overflows,
drainage   areas  associated  with   the  overflows,  and   the
pertinent  interceptor capacities.  An essential first step
in developing these data  is to acquire  the  best  and  most
recent sewer  and  storm drainage  maps for  the region under
investigation.

Overflows

Overflows  are defined  as any point  on  the  collection  and
interceptor  system   specifically   designed  to permit excess
flows  to bypass  routing to  the treatment plant. .Some of the
important  characteristics of the overflows as they relate to
the  system schematic  are:

     •  Location  of the overflows on the interceptor system

     •  The  hydraulic   capacity  of  the  overflows   and/or
       regulating structures that control the overflows

     •  The  capacity   of   any   restrictions   within   the
       interceptor system that restrict flow to the overflow
The overflows and their related  characteristics
identified by a unique numbering system.
should  be

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Drainage Areas or Subareas

Drainage areas or subareas are defined  by  delineating  the
sewered  area  that  is  tributary  to a particular overflow
structure (one overflow for each subarea).   These  drainage
subareas  fit ,together  so  that the entire sewered area is
subdivided.   The  significant   characteristics   of   each
drainage subarea are:

    *  The total surface area

    •  Percent of the subarea that is impervious

    •  Percent distribution of the  industrial,  commercial,
       and residential (single-family and multifamily)   land
       uses

    •  Average slope of the ground

    •  Average dry-weather flow

Interceptors

The interceptor system is the last  feature  of  the  system
that  is  developed  within  the  schematic.   The  specific
aspects of the interceptor systems that are analyzed are:

    •  The components  that  connect  each  subarea  to  the
       treatment plant                    .    ..      '

    •  The maximum capacity of these components

    •  The capacity  of  components  that  are  particularly
       restrictive in the system near an overflow   ,

    •  The available in-system storage

The maximum capacities of the interceptor system  are  often
calculated    using    Manning's   equation   and   assuming
unsurcharged,  open  channel  flow.   If  the   system   can
surcharge,  significantly  higher  flowrates can occur.  The
true maximum would therefore be for  flow  under  surcharged
conditions which would probably occur during a heavy storm.

Two types of in-system storage  can  be  created  for  storm
flows  by an overflow structure, as illustrated in Figure 3.
The type A configuration of an  overflow  usually  does  not
provide  a  significant  amount of storage, while the type B
configuration can retain a large volume in the system before
an overflow occurs.

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                                                  DEPTH OF
                                                ' STORM -FLOW
        DEPTH OF
        N ADWP
                            TYPE  A
                                                    LEGEND
                                                      VOLUME OF
                                                      IN-SYSTEM STORAGE
 DEPTH OF
STORM FLOW
                            TYPE B
          FIGURE 3.   TYPES  OF  IN-SYSTEM  STORAGE
                               10

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Each of the foregoing items—overflows, drainage areas,  and
interceptors—are connected in the system schematic.

Example of a System Schematic

Maps of the combined sewer system of the City  of  Rochester
were  carefully  studied.   The overflows on the system were
noted, and the drainage subareas were defined, as  shown  in
Figure 4,  The important characteristics of each subarea are
presented  in  Table 1, along with the  average  dry-weather
flow for each subarea,                             !

The interceptor system that connects the  subareas  and  the
overflows   is   presented  in  Figure  5,   The  number  in
parenthesis indicates the maximum flow that each segment  of
the  system  can  carry.   Of  particular  interest  is  the
connection  of  Subareas  8  and  9 to the main interceptor,
This connection is made via a siphon under the Genesee River
that  has   very   limited   capacity.    These   types   of
constrictions  can  significantly  affect both the number of
times that overflows occur and the volume of wastewater that
overflows, so they must be identified in the schematic,

An example of the calculation of wet-weather  flow  capacity
is presented in Table 2,  The sum of the average dry-weather
flow  (Column  2)   from  each subarea is subtracted from the
maximum interceptor capacity (Column  3)   to  determine  the
real available wet-weather capacity (Column 4),

An example of the calculation  of  the  available  in-system
storage  for each subarea is summarized in Table 3,  Most of
the overflows have the type A  configuration  and  therefore
very little in-system storage is available,

A summary of the important characteristics that will be used
in the storage-treatment task for each subarea is  presented
in  Table 4,  The schematic of the Rochester sewer system is
illustrated in Figure 6,

QUANTITY AND QUALITY

Quantity and quality data,.which are  usually  derived  from
the   monitoring   of   overflows,  are  necessary  for  the
calibration and development of the tasks,

Quantity

The first step  in  the  monitoring  of  overflows  is  flow
measurement  within  the  sewer  system  such  that both the
overflow and  intercepted  flow  can  be  determined,   This
                              11

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                       VANLARE
                       TREATMENT
                        PLANT
                                        SUBAREA NUMBER .
                                                    c .

                                        OVERFLOW NUMBER


                                        OVERFLOW LOCATION
                                        SUBAREA WITH  SEPARATE
                                            STORM SEWERS
FIGURE 4.   EXAMPLE  OF DRAINAGE SUBAREAS
         AND OVERFLOW LOCATIONS
                      12

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     Table 1.  EXAMPLE OF DRAINAGE SUBAREA CHARACTERISTICS
Sub-
area
6a
7
8
9
16
17
18
21
22
25
25Wa
26
23
29
31
50a
Total
area,
acres
1,277 '
715
984
2,603
826
235
541
821
569
348
1,390
554 ,
. 778
1-,V430
1,592
1,720


Land use.
%


Residential
Single- Multi-
family family
19.3
83.9
34.5
52.5
50.0
83.8
93.7
79.4
59.8
30.0
50.0
30.0
65.0
65.0
50.0
65.0
1.3
1.0
2.2
0
9.4
3.8
0.6
0
25.3
9.9
10.0
9.9
10.0
10.0
10.0
20.0 -
Commercial
1.9
7.3
47.0 *"
4.1
33.8
2.1.7-
3.8
9.0
6.7
44.9
20.0
44.9
10.0
10.0
20.0
5.0
Industrial Open
65.
0.
3.
37.
,1.
0
0
6.
4.
5.
10.
5.
4.
5.
15.
5.
8
2
2
1
1

8
9
0
0
2
9
0
0
0
11.8
5.5
13.2
6.4
5.7
10.2
2.2
4.9
3.3
10.2
10.0
9.9
10.0
10.0
5.0
5.0
Average
. slope,
ft/ft
0.0074
0.0118
0.0066
0.0060
0.0070
0.0067
0.0073
0.0065
0.0070
0.0080
0.0150,
0.0100
0.0100'
0.0100
O.OIO'O
0.0150
Impervious
area, %
55
. 50
45
50
55
•" ,40
40
35
50
80
35
65
50
55
47
40
.0
.0
.a •
•0
.0
.0
.0
.0
.0
.o.-;
•0,
• o' ;-
.0 '
• p
.0
.0
ADWF
(maximum
avg) , mgd
7.06
3.21
6.36
14.00
5.78
1.33
2.60
4.60
3.41
4.50
6.01
5.91
4.36
.'•' 7.86
10,13
11.90
    a. Serviced by separate storm sewers.
information  will  determine  the  total  runoff  from the area
for a particular storm and can be  used to  calculate or  check
the "K factor"  (gross runoff coefficient,)  The  K  factor  is
used  in  the   task  to  calculate  the  total   runoff   from
rainfall.

The flow data that are developed   can  include   faulty   data
because-  of  equipment  and  maintenance  weaknesses,   It is
essential, therefore, to screen the  data carefully to ensure
a reasonable  correlation  between  predicted   and  measured
values,   Time  history  (variation  of  a  parameter over  a
specific time period) and volumes  of runoff can be  compared
with  rainfall  records  to  check  if   the runoff actually
reflects the real storm event,
                              13

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LAKE: ONTARIO
LEGEND

SUBAREA NUMBER

OVERFLOW NUMBER

MONITORING LOCATION
                                           ELMWOOD AVENUE
                                          PUMPING STATION
   FIGURE  5.   EXAMPLE  OF  FUNCTIONAL ELEMENTS
                OF SEWERAGE  SYSTEM
                           14

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               Table 2.   EXAMPLE OF CALCULATION
                 OF WET-WEATHER FLOW CAPACITY,
                               mgd
1
Subarea
No.
West side
system
17 and 18
25
16
8 and 9
22
21
7
6
East side
system
26
31
28 and 29
ADWF,
maximum
avg
(1)


3.9
4.5
5.8
20.4
3.4
44. ?b
3.2
7.0

5. 9
22.0
12.2
Sum of
ADWF
(2)


3.9
8.4
14.2
34.6
38.0
82.7
85.9
92.9

5.9
27.9°
40.1°
Maximum
interceptor
capacity
(3)


416
123
47
35
84.7
173.4
. 10.0
184


200
200
Available
wet-weather
capacity
(4)


412.1
114.6
32.8
14. 6a
46.7
90.7
6.8a
100.0


200
200
              a.  The limiting segment is not on the main
                 interceptor.

              b.  Of this amount, 4.6 mgd is from Subarea 21;
                 40.1 mgd is from the East side trunk sewer.

              c.  The equivalent of ADWF is carried by the
                 east side trunk sewer.
Quality

The best   quality  data  from   a   monitoring  program   would
reflect   the   time  history  through various storm  events for
each overflow location.  The variations in  quality  through
time indicate the magnitude  of  the "first-flush" phenomenon,
The  measurement  of  quality   for each subarea  reflects the
impact of the mix of various land   uses  on  the   wastewater
discharged from each subarea,

The use of composite or  grab   samples  from  overflows,  by
subarea,   can  be  substituted  for the complete  time-history
measurements.  This may cause a distortion  in   the  results
because   the   first-flush  phenomenon,  if it occurs,  is not
acknowledged; yet it  provides  an  insight  into   the  real
                               15

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   Table  3.   EXAMPLE OF  IN-SYSTEM STORAGE  BY SUBAREA
Subarea
" " No.
7
8
9
16
17
18
21
22
25
26
28
29
31
Description
Maplewood Park
Lake and Lexington
West side trunk
Mill and Factory
Plymouth and RR
Brooks
Norton at Seth Green
Carthage
Central
Court
Screenhouse
Densmore bypass
Thomas Creek
Storage
volume,
mil gal.
0.009
0.004
0.006
0.011
0.004
0.005
0.298
0.035
0.007
* • * • •
0.250
0.026
0.023
   Table 4.   EXAMPLE  OF SUBAREA CHARACTERISTICS
           USED  IN STORAGE-TREATMENT TASK
                                                  Downstream
  Subarea ,   Area,  Impervious     In-system        interceptor
    No.    ?   acres   area, %    storage, mil gal.  capacity, mgd
West side
system
  17 and 18
  25
  16
  8 and 9
  22
  21
  7
  6
Bast side
system
  26
  31
  28 and 29
  776
  423
  650
3,666
  569
  800
  726
  554
1,592
2,178
40.0
80.0
55.0
48.0
50.0
35.0
50.0
65.0
47.0
53.0
0.01
6.01
0.04
0.30
0.02
0.28
412.1
114.6
 32.8
 14.6a
 46.7
 90.7

100.0
 751-
200
200
a.  The limiting segment is not on the main interceptor.
b.  This information is Jiot required because the area  is
    serviced by a. separate storm sewer.
c.  Estimated.
                              16

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                         VANLARE
                     TREATMENT PLANT
   LEGEND

31)  SUBAREA NUMBER


     OVERFLOW
     INTERCEPTOR
     CAPACITY, MGD

     STORAGE  VOLUME,
     MIL GAL.
                                         (200)
                                                     (200)
            FIGURE 6.   EXAMPLE  OF  SYSTEM -SCHEMATIC
                                 17

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quality  of  the  overflow.  Whether or not the first- flush
phenomenon occurs is dependent upon catchment area and storm
characteristics.

Measurements on a single overflow can also  be  extrapolated
into  results  for  the entire region.  This compromises the
impact of land uses on overflow quality and further  reduces
the reliability of quality modeling.

It  is  essential  to  have  some  quality  measurements  to
evaluate the quality of the  overflows.   "Textbook"  values
provide very little knowledge of the overflow quality caused
by a particular region's climate and terrain.

The reliability of the quality analysis is directly  related
to the data that are developed.  The more complete the data,
the  more  reliable  the  analysis.  A careful review of the
data is  important,  and  any  major  deviations  should  be
readily explainable.

Example of Quantity and Quality Data

The City of  Rochester  created  a  high-quality  monitoring
system  to  carefully  measure  the overflow on the combined
sewer system.  This system measured  the  quantity  and  the
quality  of  the overflows.  All of the data handling is via
paper tapes with computer processing  and  printing  of  the
output.  An example of this elaborate output is presented in
Appendix A.

The Rochester  data correlate  rainfall,  overflow  quantity,
and  overflow   quality for each subarea.  Although there are
some weaknesses  in the collection  and the data, the  results
do  represent what can be collected.  One  important parameter
that  was  not measured  is the quantity of water  intercepted
for any of the storms.  Otherwise,  the  Rochester  data  are
more  complete  than  required  for   the  simplified modeling
effort.   Measurement of  a  few of  the most  important  quality
constituents   and  of  overflow   and  interceptor  quantity as
these factors  vary  in time through the storm   would  be  the
ideal.    The   most  common  quality constituents of importance
are biochemical  oxygen  demand   (BOD)  or   chemical  oxygen
demand   (COD) ,  nitrogen,  and phosphorus.  Coliform or  fecal
coliform   could  also   be  measured   to   reflect   bacterial
contamination.
                              18

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                           SECTION VI

                  RAINFALL CHARACTERIZATION

Rainfall characterization provides valuable insight into the
characteristics of rainfall that occurs  in*  an  area.   The
specific  goal  of  this  task is to create a ranking of the
design parameters.  Four important analyses are performed:

     •  Collection of reliable historic rainfall data

     •  Correlation of rainfall data to study area

     •  Definition of discrete storm events

     •  Ranking of design parameters from each storm

These analyses  can  be  accomplished  with  the  aid  of  a
computer.   The  analyses  as  well  as the computer program
logic and input;-output requirements  will  be  discussed  in
this chapter.

COLLECTION OF RAINFALL DATA

Data from rainfall records over a long period  of  time  are
essential  for  the  characterization  of  storm  events and
future analysis.  If  at  least  20  years  of  records  are
analyzed,   statistically   valid   results  are  generated.
Rainfall records for storm definition should be available on
an hourly basis, i.e., a specific intensity for each hour of
rainfall for each day of record over the period  of  record.
The  hourly  intensity is short enough to record a variation
in rainfall intensity for the length of most storms but long
enough to be manageable within the framework  of  simplified
modeling.

Rainfall  data  are  available   from   many   sources—fire
departments,   sewage   treatment  plants,  water  treatment
plants, and local water supply facilities.  The most readily
obtainable data and the most compatible data  with  computer
analysis  are  obtained  from  U.S.  Weather Bureau records,
                             19

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either through tape files  or  published  daily  and  hourly
summaries.  Tapes are issued by:             ' ,

     U.S. Department of Commerce
     National Climatic Center
     NOAA Environmental Data Service           •
     Federal Building
     Asheville, NC 28801
     Tel. (704) 258-2850

Data are available  on  two  record  files:   Deck  488-USWB
HOURLY  PRECIPITATION  and  Deck  345-WBAN  SUMMARY  OP DAY.
These stations range in number from 1 in Delaware to  19  in
Texas.   The period of record is generally from 1948-1949 to
the current date with some gaps.  Tapes are furnishesd  on  9
track-800 BPI, unless otherwise specified, and are forwarded
air  parcel  post.   (Recent experience with these tapes has
been excellent.  The  two  tape  files  for  Rochester  were
ordered  and  received within 15 days for a combined cost of
approximately $140).

CORRELATION OF RAINFALL DATA

The rainfall data that  are  available  on  tapes  are  from
Weather  Bureau primary gages.  The closest primary gage may
or may not be close enough to  the  area  being  studied  to
portray  local  rainfall  conditions accurately.   Local rain
gage data from one of the sources mentioned earlier, or from
a gage specifically set up for comparison purposes,  can  be
used  to  check  local  performance  with the Weather Bureau
primary gage.  If a major difference is  found,  it  may  be
possible to apply a factor to the Weather Bureau data.

In Rochester,  12  local  rain  gages,  which  recorded  the
rainfall  in  O.1-inch  increments,  were  set up across the
city.  Records from these  rain  gages  were  compared  with
those of the primary gage, located at the Rochester Airport,
which  records  rainfall  to  the nearest 0,01 inch,  On the
basis of an  analysis  of - 19  storms  between  January  and
August, 1975, the Weather Bureau gage recorded an average of
0.44  inch per storm and the local gages recorded an average
of 0.51 inch per  storm.   Thus,  the  Weather  Bureau  gage
recorded  magnitudes  14  percent  lower  than  the  average
magnitudes  recorded  by  the  in-town  gages.   The Weather
Bureau gage also records  durations  of  storms  46  percent
longer  than  the  average durations recorded by thes in-town
gages.  The Weather Bureau gage recorded an average of  8.05
hours  per  storm, while the local gages recorded an average
duration of only 5.5 hours per  storm.   The  difference  in
duration  is mostly due to the lag inherent in the measuring
                             20

-------
equipment,. The local gage must accumulate 0.10 Inch of rain
before signaling the start of a storm,  While the local rain
gages exhibited some variation in  results,  they  indicated
that rainfall across the entire city is fairly uniform,

DEFINITION OP DISCRETE STORM EVENTS

The  hourly  rainfall  record  is  a  continuous  record  of
rainfall and can be segregated into discrete  storm  events,
This  segregation  is essential to the characterization of a
particular storm event,  For this analysis, Metcalf  &  Eddy
has  defined  a  storm  event  as  starting  with  the first
measurable rainfall after a  minimum  of  6  hours  with  no
rainfall   and  ending  when  a  gap  in  measured  rainfall
(precipitation) of at least 6 hours  is  first  encountered.
Trace  rainfall amounts are disregarded.  The 6-hour gap was
selected to ensure relative independence between events.  In
addition to.defining the storm, a check for the presence,  of
snowfall  for  each  storm  event  can  be made, and, in the
process of listing the storm events, the  annual  totals  of
important  characteristics  can  also be tabulated.  Each of
these tasks is accomplished by a separate computer  program.,
The flow of these programs is illustrated in Figure 7.

For each event in the historical record, the  .following  are
noted  and  punched  on  data cards or filed on disk:  date,
starting hour,  duration,  total  rainfall,  maximum  hourly
rainfall  and  the  hour  in which it occurred, elapsed days
since the  previous  storm,  and  occurrences  of  excessive
precipitation and snow.

RANKING OF DESIGN PARAMETERS FROM EACH STORM

The sorting and ranking of the  storm  events  develops  the
data in a format from which characteristics of the storm can
be  readily  obsexved,   The  items that can be examined are
those characterized in the storm event definition,

Careful  observation  of  the  ranked  characteristics   can
provide  valuable  information on the nature of the rainfall
that occurs in an area.  An example of the first page of the
ranking by magnitudetof the Rochester rainfall is  presented
in  Table 5,  The storms that are highlighted are those that
would have a recurrence interval of approximately 2 years,.
The events with  a  different  recurrence
calculated using the following formula:
             interval  can  be
                          RC  =
N + 1
  M
                             21

-------
DAILY  RAINFALL    HOURLY  RAINFALL
                                                    TAPE OF WEATHER BUiEAU  RAINFALL
                                                    RECORD.
                                                    TRANSFER TO DISK STORAGE AND
                                                    EDIT FOR DIRECT ACCESS.
                                                    RAINFALL RECORD  ON  DISK.
                                                    STORM EVENT DEFINITION
                                                    PROGRAM (EVENT).
                                                    SNOWFALL INCLUSION  PROGRAM
                                                    (SNOWINHOPTIONAL),
                                                    MINOR STORM EVENT  EXCLUSION
                                                    PROGRAM (EXCLUD)(OI»TIONAL).
                                                    STORM EVENT SEQUENCE LIST
                                                    PROGRAM(LISTSQ).
                                                     SORTING PROGRAM (IBM  PACKAGE
                                                     PROGRAM'.OS SORT/MERGE PROGRAM
                                                     -GC 28-6543).
                                                    LISTING OF RANKED  FILES
                                                    PROGRAM (LISTRK).
              FIGURE  7.    PROGRAMS  FOR RAINFALL  ANALYSIS
                                        22

-------
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            zzzzzzzzzzz SB jff«zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz
                                                                i^4    ram
            OOOO>-«OOOO.-lO   O ~< -I
                              „ V <•
             jlffi<jsserSatasasS?;
BtoUtaozoHO,
ujuiO3-^3O3.
                                              23

-------
where M = number of event  (13 for RC = 2)
      N = number of years  of record  (25 for Rochester)
     RC = recurrence  interval in years

Several other facts can be gleaned from  careful  review  of
the data:                                     "~~

    «  The number of  storms having a total rain of less than
       0.1O inch

    «  The number of  storms having duration greater than  24
       hours

    9  The average number  of days between storms

    •  The number of  storms starting between midnight and  6
       a.m., or at any one particular hour

The list of questions is limited only by the imagination  of
the  user.   The  more  these rankings are studied, the more
useful the tool becomes.   Examples of frequency  curves,  on
the  basis of ranked data  for the rainfall in Rochester, are
presented in Figures  8, 9, 10, and 11.  These curves can  be
compared with curves  for a design storm.

The validity of these curves  is  directly  related  to  the
length  of the period of record that is being analyzed.  The
longer the period of record,  the  greater  the  statistical
significance.

COMPUTER PROGRAM LOGIC AND INPUT-OUTPUT REQUIREMENTS

Five  small  computer  programs  are  used  to  perform  the
complete analysis of the rainfall records:

    1.  Storm Event Definition Program (EVENT)

    2.  Snowfall Inclusion Program (SNOWIN),

    3.  Minor Storm Event  Exclusion Program (EXCLUD)

    4.  Storm Event Sequence List Program (LISTSQ)

    5.  Listing of Ranked Files Program (LISTRK)

These programs are normally used  in  the  sequence  listed.
The  Snowfall  Inclusion  Program  and the Minor  Storm Event
Exclusion Program are optional.   The input and  output  data
                             24

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  1 0
                                              25 YEARS OF RECORD
                                              ROCHESTER AIRPORT GAGE
     0.1    0.2    0.40.6    1     2      46810
                            OCCURRENCES PER YEAR
20
      40   60 80  100
  FIGURE 8.   EXAMPLE CURVE -  STORM  MAGNITUDE VS.  FREQUENCY
  i o
^  0.8
   0. 6
  0. 4
   0. 2
   0. 1
                                               25 YEARS OF RECORD
                                               ROCHESTER AIRPORT GAG!
     0.1    0.2    0.40.6   1
                                      4   6810
                                                    20
                                                          40  6080100
                            OCCURRENCES PER YEAR

  FIGURE 9.   EXAMPLE CURVE - STORM  INTENSITY  VS.  FREQUENCY
                                 25

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  ID

<=>  8
ui
Q
ui  o
ui
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X
a
ui
 .  0.8
CO

2!  0. B
o
»—
CO

u.  ••«
  0. 2
   0. t
25 YEARS OF  RECORD
ROCHESTER AIRPORT GAGE
     O.I   0.2    0.40.6   1     2     4   6810

                          OCCURRENCES PER YEAR
     20
                                                       40   60 80 100
 FIGURE 10.   EXAMPLE  CURVE -  STORM DURATION VS.  FREQUENCY
JU
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25 YEARS OF RECORD
ROCHESTER AIRPORT GAGE


















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                       8    10   12    14    16   1


                         HOUR  AFTER START OF STORM
                                               8    20
                                                                           I
                                                                           i
                                                                          i
                                                                          	!
                                                                           m|i
  FIGURE 11.   EXAMPLE  CURVE  -  PERCENT  OF STORMS  HAVING
 MAXIMUM 1-HOUR INTENSITY VS.  HOUR AFTER START  OF STORM
                               26

-------
for each program are compatible; therefore, the programs can
be run in any desired sequence.  The programs are written in
FORTRAN,  and,  while  not  extremely complex, they could be
used most effectively  by  a  person  with  the  ability  to
manipulate the input and output files on the computer system
that  is being used.  The complete listing of these programs
is given in Appendix B.

Storm Event Definition Program  (EVENT)

EVENT, the first program in the sequence, is used to perform
the initial translation of  the  hourly  record  into  storm
events using the prescribed definition.  The program listing
for  EVENT is presented in Table B-l and Table B-2 is a list
of variables for EVENT.  The input for this program  is  the
hourly  rainfall  record  in  the  format listed in Table 6,
which corresponds  with  the  format  used  on  the  Weather
Bureau's hourly tapes.

The flow chart displaying the program logic is presented  in
Figure 12.  This program initially reads the hourly rainfall
records  one  day at a time and inspects it for errors.  The
program then starts checking if rain is occurring  and  when
the  last  rain  occurred.   If it just started raining, the
interval  between  storms  is  checked.   The  peak   hourly
intensity    for   the   storm   is   also   checked.    The
characteristics of each storm  are  accumulated.   When  the
storm ends, the characteristics of the storm are recorded on
disk  in  the  format  listed   in  Table  7.  The. program is
terminated when all of the data have been read.

The output format for this program is  compatible  with  the
input   format   for   each   of  the  succeeding  programs.
Therefore, any of the following programs can  be  used.   If
the user would like to see the  results of this analysis, the
Storm  Event  Sequence List Program or the Listing of. Ranked
Files Program could be used with the output  file  that  has
been created.

Snowfall Inclusion Program (SNOWIN)

The input for the SNOWIN program consists of both the output
from the Storm Event Definition Program and  data  from  the
Weather  Bureau daily rainfall  records.  The program listing
for SNOWIN is presented in Table B-3 and a list of variables
for SNOWIN is shown in Table B-4.  The storm event data  are
in  the  format  presented  in  Table 7.  The daily rainfall
records are in the format presented in  Table  8,  which  is
compatible with the Weather Bureau daily rainfall tapes.  In
this  program  the  daily - records are inspected for days on
which snowfall occurs, and these days are matched with storm
                              27

-------
Table 6.  FORMAT FOR HOURLY RAINFALL DATA
Card
group Forjnat
312



11
12P3.2


12P3.2

12

Card
group Format
14
313


2F6.2

213

12
13
15
15
Card
columns
7-12
(7-8)
(9-10)
(11-12)
13
14-16
16-18
•
•
47-49
14-16
•
•
47-49
79-80
Table
Card
columns
2-5
6-8
9-11
12-14
15-20
21-26
27-29
30-32
33-34
35-37
43-47
43-47
Description
Date of rainfall
Year (last 2 digits)
Month
Day
Switch indicating time of day;
0 indicates a.m. and 1 indicates p.m.
Quantity of rainfall in Hour 1
Quantity of rainfall in Hour 2
Quantity of rainfall in Hour 12
Quantity of rainfall in Hour 13
Quantity of rainfall in Hour 24
Day of next recorded rainfall
7. FORMAT FOR STORM DATA
Description
Number of year of storm
Number of month of storm
Day of month of storm
Duration of storm
Total rainfall for storm
Maximum 1-hour intensity for storm
Number of hours into storm that
peak intensity occurs
Number of days between storms
Snowfall index
Clock hour for start, of storm
Sequence numbers
Magnitude sequence number
Variable
name

NY (I)
MO (I)
KID (I)
NX (I)
FR(I,1)
FR(I,2)
E'R(I,12) .
FR(I,13)
•
FR(I,24)
NEXT (I)

Variable
name
NYA/IYE
MOA/MON
NDA/NDA
LD/NDU
FRS/'TR
FAX/TMR
ITA/NHR
LLD/NDT
IS/ISN
IRT/IHR
IFXX/NRR/IPP
IQ/IFXX
                  28

-------
                                    READ DATA  IN 24-HOUR BLOCKS:
                                      YEAR,  MONTH.  DAY,  HOUR,
                                      RAINFALL.AND DAY OF  NEXT
                                      RAINFALL.
                                     DATA CHECK: EXCESSIVE NUMBER
                                      OF DAYS BETWEEN STORMS.

                                     ERROR MESSAGE.
                                     TERMINATE PROGRAM.

                                     DATA CHECK: IS  STORM OCCURRENCE
                                       AT END OF DAY?
                                     IS STORM STARTING?
                                     DETERMINE HOUR, DAY, MONTH,
                                       AND YEAR OF START OF STORM
                                       AND DAYS SINCE LAST STORM.
                                     IS  IT RAINING?
                                     HAS  IT NOT RAINED FOR
                                     MORE THEN 6 HOURS?
                                     SIGNAL END OF  STORM.
FIGURE  12.    FLOW CHART  FOR STORM EVENT
        DEFINITION PROGRAM  (EVENT)
                         29

-------
                   IS  THIS THE PEAK INTENSITY
                   FOR THIS STORM?
                   DETERMINE WHEN THIS PEAK  OCCURS
                   AFTER START OF STORM.
                   DETERMINE TOTAL RAINFALL
                   AND DURATION OF STORM.
                   DID STORM OCCUR?
                  RECORD ON DISK:  STORM EVENT
                   HAS ALL DATA  BEEN READ?
                  TERMINATE PROGRAM.
FIGURE 12.   (CONCLUDED)
         30

-------
events.  An index is set  if  snowfall  is  present  or  not
present  for  a  particular  storm.  The flow chart for this
program is presented in Figure 13.  The  output  is  in  the
format  presented  in  Table  7, and is listed on a disk for
future reference.

              Table 8.  FORMAT FOR SNOWFALL DATA
Card
group





Card
Format columns
312 6-11
(6-7)
(8-9)
(10-11)
F3.1 22-24
Description
Date of precipitation
Year (last 2 digits)
Month
Day
Quantity of snowfall
Variable
name

NYB
MOB
NDB
SNOW
Minor Storm Event Exclusion Program  (EXCLUD)

The  function of  the EXCLUD program is  to eliminate  the  very
small   rainfalls  that  occur   from  the   storm   file.  This
reduces the amount of data to be  sorted and   ranked,   These
small   storms  are sometimes the tailing or leading  edge of  a
large   storm   that  became  isolated   due    to    the   rigid
application  of  the  6-hour  storm event definition, or they
are  parts of large storms that  fell  somewhere else in   the
region   and  are  just  passing through.   In either case,  in
Rochester  these  storms  amount  to   an   average   of    51
occurrences, for a total of 1.21  inches of rain  annually,  or
4.1  percent   of  the total annual rainfall.  Metcalf & Eddy
has  defined small storms as those with rainfall  amounting  to
O.05 inches or less.  The  program   logic  is presented   in
Figure   14.    The  program also uses the format  presented  in
Table 7 for both input  and output.   The  input and output   is
handled on disks.  A program  listing for EXCLUD  is  presented
in   Table  B-5  and  the  list  of   variables for  EXCLUD is
presented  in Table B-6.

Storm Event Sequence List Program (LISTSQ)

The  output from  the  Snowfall  Inclusion Program or the  Minor
Events   Exclusion  Program   is  usually  used with the LISTSQ
                             31

-------
                                 READ STORM EVENT DATA.
                                 READ SNOWFALL DATA:
                                  YEAR,  MONTH, DAY, SNOWFALL.
                                COMPARE RAIN DATE WITH SNOW DATE.
                                SET INDEX: NO SNOW  IS PRESENT.
                                SET INDEX: SNOW IS PRESENT.
                                RECORD ALL STORM EVENT DATA
                                AND  ADD SNOW INDEX.
                                HAS  ALL DATA  BEEN READ?
                                TERMINATE PROGRAM.
FIGURE  13.   FLOW  CHART FOR SNOWFALL
      INCLUSION  PROGRAM (SNOWIN)
                     32

-------
                               READ :  STORM EVENT DATA.
                               DOES THE STORM HAVE LESS THEN 0.05
                               INCH OF RAIN ?
                               RECORD:  EDITED  STORM EVENT DATA.
                               HAS ALL DATA BEEN READ?
                               TERMINATE PROGRAM.
FIGURE 14.    FLOW  CHART  FOR  MINOR  STORM EVENT
           EXCLUSION  PROGRAM  (EXCLUD)
                            33

-------
program  in  the  format  presented  in  Table  7.   The   logic   for
the program is  presented  in  Figure  15.  Its  primary  function
is  to   provide  a   chronological listing of the  storm event
data.  In the program, data  on the  duration  of  storms';   the
total  rainfall,  and  the maximum  hourly intensity  for  each
year are accumulated and  listed  at  the  end   of   each  year.
When  all   of   the   data  have   been  read,   the   program is
terminated.  The  results  of  this analysis   are   printed   by
this program.   An example of the output for  the year 1962 is
presented   in   Table  9.  Table  B-7 is a program  listing  for
LISTSQ.  Table  B-8  is  a list of  variables for LISTSQ.
Sorting and Ranking Program  (SORT)
The SORT program used  to  analyze  rainfall  is  a  package
program  developed by  IBM  (OS SORT/MERGE Program GC28-6543)»
An important characteristic of this program is that it sorts
the data on the basis  of   a  particular  characteristic  and
carries  along  with it the remaining characteristics of the
particular storm.                                   ,     .

This program uses the  same input-output format presented  in
Table 7, and also uses disks for input and output files.

Listing of Ranked Files Program  (LISTRK)

The LISTRK program provides output from any of the  previous
programs.   The program listing for LISTRK is shown in Table
B-9 and Table B-10 is  a list of variables for  LISTRK.   The
program  logic is presented in Figure 16.  The program reads
disk files in the format presented in  Table  7,  assigns  a
sequence  number,  and  prints  the  information on the line
printer.  An example of the output is presented in Table 1O.
This output has been ranked by maximum 1-hour intensity.
                             34

-------
READ
                                       READ STORM EVENT  DATA.
         ERROR
 STOP
         YES
                      WRITE
STOP
                             J
                       WRITE
                DATA CHECK: MONTHS IN  YEAR.
                                       ERROR MESSAGE.
TERMINATE PROGRAM.


CHECK  FOR END OF YEAR.


LIST:  TOTAL DURATION  OF RAIN
FOR YEAR, TOTAL ANNUAL RAINFALL,
AND MAXIMUM  INTENSITY RAINFALL
FOR YEAR.
                                        CALCULATE:  TOTAL DURATION  OF RAIN
                                        FOR YEAR,  TOTAL ANNUAL RAINFALL,
                                        AND MAXIMUM INTENSITY.


                                        LIST: STORM EVENT  DATA.
                                           t
                                        HAS  DATA FOR EACH  STORM BEEN  READ?
                                        TERMINATE PROGRAM.
        FIGURE  15.    FLOW  CHART  FOR STORM EVENT
            SEQUENCE  LISTING  PROGRAM  (LISTS.Q)
                               35

-------
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-------
                              READ:RANKED STORM EVENT DATA.
                              ASSIGN SEQUENCE NUMBERS AND INDEX
                              COUNTERS.
                              LIST:RANKED STORM EVENT DATA.
                              HAS ALL DATA BEEN READ?
                              TERMINATE  PROGRAM.
FIGURE  16.   FLOW  CHART FOR LISTING  OF  RANKED
            FILES PROGRAM  (LISTRK)
                          39

-------
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-------
                         SECTION VII
   " .' '*

                 STORAGE-TREATMENT BALANCE

In the storage-treatment task, rainfall  is  converted  into
runoff   and   overflows.    In  this  chapter  the  general
characteristics  of  the  program  will  be  presented,  the
program logic and specific  input  and  output  requirements
will  be  discussed, and examples using portions of the City
of Rochester will be modeled to illustrate the  utility  and
versatility of the program.

CHARACTERISTICS OF THE STORAGE-TREATMENT PROGRAM

The program is described in three parts:   (1)  the  concept
upon  which  it is based, (2)  the major operational controls
and general data requirements, and  (3)  the  philosophy  or
method  of approach to its application and the usefulness of
its output.

Concept of the Program

The concept of the storage-treatment  program  is  presented
graphically  in  Figure  17.   In  the  program  rainfall is
converted  into  runoff  using  a  K  factor  (gross  runoff
coefficient).  This runoff is stored in a  specific  storage
volume  that  is  drained by a specific treatment rate.  The
treatment rate could be determined by  an  actual  treatment
facility  or  an  interceptor  capacity.   When  the  runoff
exceeds  the  storage  capacity  and  the treatment rate, an
overflow occurs.                                           .

Operational Controls and Data Requirements

The program, can function on either a daily  or  hourly  time
step.   The  daily  time step is used initially for analysis
based on the entire period of record.  For specific  periods
of  interest—including critical storms—the analysis may be
performed on the hourly time step.

The starting of the treatment rate also can  be  controlled.
In  the daily analysis, the percentage of the full treatment
                             41

-------
                        x
R
U
N
0
F
                                EFFLUENT
        FIGURE 17.  CONCEPT OF STORAGE-TREATMENT PROGRAM
rate for the first day of  rain  can  be  controlled.   This
control  can  be  used  to reflect the uncertainty of when a
storm starts during the day or the length of  time  required
to  start a treatment facility.  In the hourly analysis, the
start of the treatment  rate  can  be  delayed  a  specified
number of hours  to  reflect  the  real  time  required  for
start-up of a stormwater treatment facility.
                             42

-------
The program, when used with a  computer  system  capable  of
on-line  storage of input and output files, can also be used
to analyze a system of linked subareas.  The treatment  rate
for a system would represent the capacity of the 'interceptor
system  between  subareas.   The  program has the ability to
create a  time-varying  interceptor  capacity  for  upstream
areas   based  on  the  runoff  from  downstream  areas  and
downstream interceptor capacities.

The major data requirements for the program are  simply  the
land  area,  the  K  factor,  the  storage capacity, and the
treatment rate.  The area of land -for a  particular  subarea
is developed as described in Section V.  The K factor can be
developed  and  checked  from  (1)  quantity measurements as
described in Section V; (2)  analysis  of  detailed  computer
programs,  such  as the Storm Water Management Model (SWMM);
or (3) other traditional empirical equations based  on  land
use  or impervious area (as illustrated in Appendix C).  The
storage capacity should be the real in-system storage,  again
as presented in Section V, added to the existing or proposed
tunnel, cavern, and/or diked storage volume.  The  treatment
rate  is the existing or proposed available peak wet-weather
treatment   capacity   or   excess   interceptor    capacity
immediately downstream from the subarea.

The other input variables trigger the operational  controls.
The  factor  for  starting of the treatment rate is the most
significant of these triggers.  This factor  would  normally
be  zero  when  an  interceptor  is downstream rather than a
treatment facility.  There is a switch for daily  or  hourly
analysis, and the number of upstream interceptors converging
on the area must also be noted.

Output Data and Application Philosophy

The output from the program is the record of  the  time  and
volume  of  overflows  and  runoff, arid a summation of  these
parameters.  The summation is terminated at the end of   each
year for the daily analysis and at the end of each month for
the hourly analysis.

The program is intended primarily for use in the analysis of
alternatives  and  general  evaluation  of  the  number   of
occurrences and volumes of overflows.

The storage capacities or  treatment  rate  can  be  varied.
Generally,   one   parameter   is  varied  while  the  other
parameters  are  held  constant,   so  that  curves  can   be
generated  to indicate the impact of the particular variable
on the system.
                             43

-------
The base or  uncontrolled  condition  is  run  initially  to
provide  a  base  for  comparison of the control approaches,
The success of an overflow abatement program can be measured
by a reduction  in  the  volume,  duration,  and  number  of
overflows.   The objectives of the control philosophy should
be defined early in the analysis and should be correlated to
to some improvement in receiving water quality.

The program operates  on  the  real  rainfall  records,  and
therefore  it  internally takes into account the synergistic
effects of storms coming  close  together  with  overlapping
demands  on  storage  capacities.  If the period of rainfall
records is long enough—say  2O  to  50  years—the  runoff,
overflow volumes, and durations can be filed and ranked, and
statistically significant frequency of occurrence curves can
be generated.

A series of linked  subareas  are  analyzed  by  independent
computer runs.  The analysis starts with the subarea closest
to  the  treatment  plant  or  discharge  point and proceeds
upstream through the series of subareas.  The important data
are passed from one computer run to the  next  by  means  of
files stored on the computer system.

COMPUTER PROGRAM LOGIC AND INPUT-OUTPUT REQUIREMENTS

The storage-treatment program is written in FORTRAN computer
language.  This program records  information  on  input  and
output  files and therefore can be most productive when used
by a person familiar with the manipulation of files  on  the
computer  system.   The  complete listing of this program is
presented in Appendix B.

The program  is  composed  of  a  control  block  with  four
subroutines:

    »  HOUCRD - Hourly analysis from card input

    9  DLYCRD - Daily analysis from card input

    9  DLYTAP - Daily analysis from tape input

    »  HOUTAP - Hourly analysis from tape input

These subroutines are quite similar; the  major  differences
are  in  the types of computer input used  (cards or magnetic
tape) and  in  the  time  steps  being  analyzed  (daily  or
hourly).   The  logic  for the control block is presented in
Figure 18.  The format for the control block input  data  is
presented in Table 11.
                             44

-------
  READ
DECISION
           DAILY
     HOURLY
             DECISION.
                  TAPE
                         CARD
 GENERAL DATA: AREA, RUNOFF
 COEFFICIENT,  MINIMUM STORAGE,
 NUMBER  OF YEARS  TO BE ANALYZED,.
 DAILY/HOURLY  SWITCH,, TAPE/CARD
 SWITCH. INFLOW FROM UPPER REACHES.
 FACTOR FOR TREATMENT PLANT FLOW
 ON FIRST DAY  OF STORM.
IS TIME PERIOD OF ANALYSIS
DAILY OR HOURLY?
ARE DAILY RAINFALL RECORDS ON
TAPE/DISK OR CARDS ?
                                           CALL SUBROUTINE DLYCRD.
                                            CALL  SUBROUTINE DLYTAP.
                                            ARE HOURLY RAINFALL  RECORDS ON
                                            TAPE/DISK OR  CARDS.
                                           CALL SUBROUTINE HOUCRD.
                                            CALL SUBROUTINE  HOUTAP.
  FIGURE  18.    FLOW CHART FOR  CONTROL  BLOCK  OF
               STORAGE-TREATMENT  PROGRAM
                                   45

-------
            Table 11.   FORMAT FOR CONTROL BLOCK DATA
                     OF STORAGE-TREATMENT PROGRAM
Card
group

Card
Format columns
5A4 1-4
5-8
•
Description
Identifier of first area to be
analyzed
Identifier of second area to be
analyzed
Variable
name
ARtf(l)
ARN(2)
•
            5F8.0
            12


            311.
            14

            IX

            FIDO
17-20


21-28

29-36

37-44

45-52


53-60

61-62


 63


 64


 65


66-69

 70

71-80
Identifier of last area to be
analyzed

Area of area to be analyzed
Gross runoff coefficient "K factor"
Maximum volume of storage available

Treatment rate or adjacent down-
stream interceptor capacity

Minimum volume of storage

Number of years or months of
record to be analyzed

Switch 0 for daily analysis;
1 for hourly analysis

Switch 0 for card input;
1 for'tape input
Number of interceptors converging
at point of runoff

Years or months to be analyzed
Factor used to determine volume
of runoff routed to treatment
plant on first day of rain
ARN(5)


AREA

COEF

STMAX

TREAT


STOPS

NYEAR


NSS


IOTAP


IPFL


MYEAR
TFAC
The  four  subroutines  function on  basically the  same   logic,
which is  presented in Figure 19.   The  slight differences   in
input requirements and other minor functional  differences  in
the   four  subroutines  are  described  in the discussion that
follows.
                                  46

-------
                            GENERAL  DATA FROM COMMON  BLOCK.
                            START CALCULATIONS FOR A  YEAR/MONTH.
                            YEAR/MONTH TO BE ANALYZED,(NUMBER OF DATA CARDS)
                            RAINFALL  DATA: MONTH/DAY,  DAY/HOUR.  QUANTITY
                                          OF RAINFALL. (10 DAYS RECORDED
                                          ON EACH  DATA CARD).
                            DATA CHECK: NUMBER OF DAYS  IN MONTH/HOURS
                                       IN DAY.  NUMBER  OF MONTHS IN
                                       YEAR/DAYS IN  MONTH.
                            ERROR MESSAGE.
                            TERMINATE PROGRAM.
                            START CALCULATIONS ON DAILY/HOURLY BASIS.
                            PROCEED  TO NEXT DAY'S  DATA.
                            RAINFALL CHECK: DID  RAINFALL OCCUR IN THIS  DAY/
                            HOUR?
                            STORAGE  CHECK: is AVAILABLE STORAGE
                                          EMPTY?
                            DETERMINE QUANTITY  OFRAINFALL AND  RUNOFF.
                            PUT RUNOFF INTO STORAGE.
FIGURE  19.   BASIC  FLOW  CHART  FOR  SUBROUTINES
            OF  STORAGE-TREATMENT  PROGRAM
                               47

-------
             IS TREATMENT OPERATIONAL FOR THIS  CYCLE?
             REDUCE  STORAGE AT RATE'OF TREATMENT.
             START  TREATMENT FOR NEXT CYCLE.
             IS MAXIMUM STORAGE EXCEEDED?
             CALCULATE QUANTITY OF WATER IN EXCESS OF
             MAXIMUM STORAGE AND DECLARE IT TO BE
             OVERFLOW.
             CALCULATE:  TOTAL  RAINFALL FOR MONTH/EIAY,
                        QUANTITY OF RUNOFF, OVERFLOW
                        TREATED, STORED, AND DAYS/HOURS
                        OF  RAIN AND OVERFLOW TO DATE
                        FOR YEAR/MONTH.

             LIST: DATE  (MONTH AND DAY)/
-------
In the HOUCRD  subroutine,   the   input  data  are  read  from
computer cards  in the  format  presented in Table 12,  Of  the
four  subroutines,   this   one has the most limited capacity.
Subareas cannot be connected  for analysis, and the treatment
rate cannot be  turned  off  for the first hours  of,  a  storm.
The hourly time increment  is  used,

In the DLYCRD  subroutine,   the   input  data  are  read  from
computer cards 'in the  format  presented in Table 13, which is
very  similar   to  the format of the hourly data,   Connected
subareas cannot  be  analyzed,   but   the  treatment  can  be
adjusted on the first  day  of  rain.   Calculations are made on
a daily time step.

In the DLYTAP  subroutine,   the   input  data  are  read  from
magnetic tape or disks in  the format presented in  Table  14,
which is compatible  with the  Weather Bureau's daily rainfall
record  tapes,   This  subroutine can be used with  all of the
operational controls described  earlier in this chapter.  The
daily time increment is used.


         Table 12.   FORMAT FOR  HOUCRD SUBROUTINE DATA
Card
group











Format
2110

10(212, F4. 2)
(212)

(F4.2)

(212)

(F4.2)

Card
columns
1-10
2-20.
1-8
(1-2)
(3-4)
(5-8)
9-16
(9-10)
(11-12)
(13-16)
17-24
Description
Number of month to be analyzed
Number of data cards to be read
First hour and quantity of rainfall
Day
Hour
Quantity
Second hour and quantity of rainfall
Day
Hour . .
Quantity
Third hour and quantity of rainfall
Variable
name
MYEAR
NCARD

MON(l)
MDAT{1)
RAIN(l)

MON(2)
MDAT(2)
RAIN (2)

                    73-80   Tenth hour and quantity of rainfall

                          Ten hours and quantities on each
                          data card
                             49

-------
 Table  13.   FORMAT  FOR DLYCRD  SUBROUTINE- DATA
Card
group
Format'
Card
columns
Description
Variable
name
2iio            1-10   Number of year to be analyzed          MYEAR
               11-20   Number of data cards to be read        NCARD
10{2F2,F4.2)     1-8    First date and quantity of rainfall
(212)           (1-2)     Month                               MON(l)
               (3-4)     Day                                 MDAT(l)
(F4.2)          (5-8)     Quantity                            RAIN(l)
                9-16   Second date and quantity of rainfall
(212)           (9-10)    Month                               MON(2)
              (11-12)    Day                                 MDAT(2)
(F4.2)         (13-14)    Quantity                            RAIN(2)
               17-24   Third date and quantity of rainfall
               73-80   Tenth date and quantity of rainfall
                       Ten dates and quantities on each
                       data card
  Table 14.   FORMAT  FOR  DYLTAP  SUBROUTINE DATA
  Card             Card
  group   Format  columns
Variable
  name
          312        6-11   Date of precipitation
                   (6-7)     Year (last 2 digits)      NYZ
                   (8-9)     Month                    MON
                  (10-11)    Day                      MDAT
          F4.2     18-21   Quantity of rain for day   RAIN
                              50

-------
In the  HOUTAP subroutine, the  input data  are   read  in  the
format   presented  in  Table 15, which is compatible with  the
Weather  Bureau's   hourly  tapes.     Again,    all   of   the
operational  controls  can  be   used.  The  time increment  is
hourly,

In all  of the subroutines, basically the same  output  format
is  used.   The daily and hourly times are  recorded slightly
differently,  An example of the  daily output  is presented  in
Table  16, and an example of the  hourly output   is  presented
in Table 17.

EXAMPLE OF STORAGE-TREATMENT  PROGRAM APPLICATION

The storage-treatment  program  was  used   on   the  City   of
Rochester   system   of   combined  sewers   to  analyze  the
performance of the existing system as well   as  to  evaluate
the   suggested  overflow  control alternatives.  Examples  of
the results are presented in  this section,


          Table 15.   FORMAT FOR HOUTAP SUBROUTINE DATA
Card          Card
group  Format columns
                                 Description
                                                         Variable
                                                           name
          312      7-12   Date of rainfall

                 (7-8)    Year (last 2 digits)               NY(I)

                 (9-10)   Month                           MO (I)

                 (11-12)   Day                             ND(I)

          II       13    Switch indicating time of day;        NX(I)
                        0 indicates a.m. and  1 indicates p.m.

          12F3.2  14-16   Quantity of rainfall  in Hour 1        FR(I,1)

                 16-18   Quantity of rainfall  in Hour 2        FR(I,2)
                 47-49   Quantity of rainfall in Hour 12

          12F3.2  14-16   Quantity of rainfall in Hour 13
                                                      FR(I,12)

                                                      FR(I,13)
          12
              47-49  Quantity of rainfall in Hour 24

              79-80  Day of next recorded rainfall
                                                         FR(I,24)

                                                         NEXT(I)
                                 51

-------
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Data Development

The characteristics of the system were developed in Table 4,
which   contains   the   basic   information   on    subarea
characteristics.   These  characteristics must be considered
fixed during the alternative analysis so that  the  critical
parts of the alternatives can be analyzed,

In the City of Rochester, the subareas 'that  drain  directly
to  the  Genesee  River were analyzed.  Initially, the areas
indicated in the schematic shown in Figure 20 were  analyzed
to determine the level of  runoff  control  offered  by  the
existing  sewer  system.   The  output  from the program was
translated into a plot showing the frequency  of  occurrence
of runoff and overflows versus volume as presented in Figure
21.

Several alternatives were analyzed.  The results  from  each
analysis were translated into plots showing the frequency of
occurrence   versus   volume.    Two  of  the  alternatives,
identified as Rochester West  Side  Alternatives  1  and  2,
appear  to  have a distinct advantage in reducing the number
of overflows.

Alternative Analysis

In West Side Alternative 1, large  drainage-storage  tunnels
would  be  connected  to a modified interceptor system.  The
drainage  tunnels  would  be  constructed  in  the  City  of
Rochester as shown in Figure 22.  The flow capacities of the
modified   interceptor   sewer   and   the   size   of   the
drainage-storage     tunnels     are     indicated.      The
drainage-storage tunnels could  be  connected  to  the  main
interceptor  by  pumps  or  by  some  other flow-controlling
structure.  This alternative is presented  schematically  in
Figure 23.

In West Side Alternative 2, an interceptor tunnel  would  be
used  along  the  river  to  connect  the drainage-collector
tunnels.  This interceptor tunnel would be connected to  the
existing   interceptor   downstream   of   the  city.   This
connection would also have a controlled discharge rate.  The
configuration of this alternative  is  presented  in  Figure
24, and the schematic is presented in Figure 25,

A major assumption of these two alternatives  is  that  each
subarea,   when  improved,  will  have  a  single  point  of
overflow.
                             54

-------
   ©
LEGEND

  SUBAREA


  OVERFLOW
                                VANLARE
                            TREATMENT PLANT
   /onn-v  INTERCEPTOR
   (.ZOO.)  CAPACITY, MGD
         STORAGE  VOLUME.
         MIL GAL.
* THESE VALUES DO NOT REFLECT
  MOST RECENT ANALYSIS OF SEWER
  SYSTEM PRESENTED IN TABLE 5-4
FIGURE 20.   EXAMPLE OF  SYSTEM SCHEMATIC -
 EXISTING  ROCHESTER WEST SIDE INTERCEPTORS
                        55

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                                              56

-------
7,000
                                             VANLARE
                                        /   TREATMENT
                                               PLANT
 8,000 (12)-
 13,000
                                                            SUBAREA BOUNDARY

                                                            DRAINAGE TUNNEL
                                                            LENGTH AND
                                                            (DIAMETER). FT

                                                            MOD IFIED INTERCEPTOR
            FIGURE  22.   ROCHESTER WEST  SIDE  - ALTERNATIVE 1
                                      57

-------
                                 VANLARE
                             TREATMENT PLANT
        LEGEND


     31 }  SUBAREA


          OVERFLOW
          INTERCEPTOR
          CAPACITY. MGD
    I - 1  STORAGE VOLUME,
    I _ I  MIL GAL.
* THESE VALUES DO NOT REFLECT
  HOST RECENT ANALYSIS OF SEWER
  SYSTEM PRESENTED IN TABLE 5-4
 FIGURE  23.   EXAMPLE OF SYSTEM SCHEMATIC  -
 MODIFIED ROCHESTER WEST SIDE INTERCEPTORS
                         58

-------
5,000  (10)
                        2,000/(16)
                              2,000 (18)
                            — 4,000 (16)
8,000 (12)	J6,000 (16)
          /-^_!/'-K   ^~

          ^2,000 (16)

  13,000/(16)
       U-


 7,000 (12
                                                   LEGEND
                                                      SUBAREA BOUNDARY
                                                      DRAINAGE TUNNEL
                                                      LENGTH  AND
                                                      (DIAMETER).  FT
 FIGURE  24.   ROCHESTER WEST  SIDE  -  ALTERNATIVE 2
                              59

-------
The results  from  the analysis,  presented in Figure  21,  are
based on  use of the  daily time  step and the last 20 years of
record  from the  Weather  Bureau tapes.   The volume of runoff
and overflow for  each day that  runoff or  overflow  occurred
was  ranked,  and  the the  frequency of occurrence curves were
developed.   These curves  are based on real  rainfall  for  a
long  period  of   record  and therefore  present statistically
valid data,

Comparison of Daily  and Hourly  Analysis

Two critical  periods were analyzed using the hourly interval
on Alternative  2.    These  periods  covered  three  of  the
largest   storms   in  the  period   of  record.   The  hourly
analysis, as_expected, provides more sensitive data than the
daily analysis.   These two analyses are  compared  in  Table
18.

The daily and hourly results are   compared  graphically  in
Figure 26.   One of the periods  analyzed represents a  large
storm that was known locally as hurricane Agnes,

The  concept  of   simplified modeling   and  the  degree  of
precision in  the  basic assumption  of the  input  data  limit
analysis on  any finer time step than hourly.  The input data
to  the  model  are   limited by three assumptions:   (1)  that
rainfall over the subarea is uniform, (2)  that the K  factor
is  a gross runoff coefficient,  and (3)  that travel times in
the sewers (displacement  of  peak   flow)   are  not  accounted
for.
                   VANLARE
               TREATMENT  PLANT
                 (100)
                   f.21.2:
                 (8-9,16,25^
                 1,17-18,26^
                    31
,  INTERCEPTOR
i  CAPACITY.MGD
  STORAGE VOLUME,
  MIL GAL.
   FIGURE 25.   EXAMPLE OF SYSTEM SCHEMATIC - ALTERNATIVE 2
                             60

-------
  Table 18.   COMPARISON OF DAILY AND  HOURLY
            TIME  INCREMENT ANALYSIS3
                         Test Period 1  Test Period 2
Number of days

Number of days
of rainfall

Total rainfall,  in.

Percentage above
20-yr average
91


29
11.4


50.9
92


33

11.1


32.5
Total runoff, mil gal
Total overflow
volume, mil gal.a
Overflow, % of
total runoffa
Total number of
days of rain
Total number of days
of overflow9
a. Totals represent
b. Storm of January
Daily
increment
.a 2,679.3
238.7
8.9
62
3
sum of Test Periods
22-23 overflowed on
Hourly
increment
2,679.3
383.6
14.3
62
5b
1 and 2.
both days
    when computed hourly.   The second added overflow
    occurred on June 29-30 from a 6-hr  storm that
    started 3 hrs before midnight and ended 3 hrs
    after midnight.  The daily simulation distributed
    the storm's impact over, 48 hrs;  thus, no overflow.
    The hourly simulation  properly compacted the
    storm to 6 hrs and the system capacity was ex-
    ceeded between 12:00 midnight and 3:00 a.m. on
    June 30.
                          61

-------

50-


40-

30-
o
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j 380-
S 240-
;f 120-
* 0-

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n -
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TOTAL RUNOFF RATE





r

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OVERFLOW






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	 HOURLY CALCULATIONS
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1 HOURLY RESULTS
	 DAILY RESULTS



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111
ll
    90-
          12    24   12   24    12
         6/20       6/21       8/22
24
     12    24    12
     6/23       6/24
?4
FIGURE  26.   COMPARISON  OF HOURLY AND  DAILY ANALYSIS
                           62

-------
                         SECTION VIII

                OVERFLOW QUALITY ASSESSMENT

The assessment of overflow quality can be approached by  two
methods.   In the first method, dirt and nutrient suspension
and transportation are taken into consideration as  in  SWMM
and  STORM,  In the second method, regression techniques and
statistical  manipulations  of  observations  are  used   to
extrapolate  quality  parameters  from  existing  data.  The
second method is more direct and quite consistent  with  the
concept  of  simplified  modeling.   A  third  method  using
geographic  and  demographic  data   based   on   nationally
collected  statistics  also  can be used.  This technique is
summarized in Appendix D,

Using the second method, two analyses are performed in  this
chapter  to  derive  quality  characteristics.  In the first
analysis, regression equations are developed on the basis of
measured data that  have  been  collected.   In  the  second
analysis,  averages of selected subsets of the measured data
are used to develop quality parameters.

(A third analysis based on polynominal regression techniques
is presented in Appendix D.  This third  technique  was  not
applied successfully in Rochester.)

The quality characteristics are developed in the form  of  a
concentration  that  can  be paired with an overflow volume.
The  volume  overflowing  is  a  function   of   the   storm
characteristics, the configuration of the drainage area, and
the  control  alternative.  This volume is calculated in the
storage-treatment task.  The quality of the overflow is also
a function of the storm  characteristics  and  the  drainage
area configuration.
 REGRESSION ANALYSIS

 The   regression   analysis   is   described
 procedure  and  example  of equations.
in   two   parts:
                              63

-------
 Procedure

 Regression analysis is part of the  broad   area  of   fitting
 curves  to measured data.   In this analysis,  equations  based
 on linear regression  are   developed.    (Specific equations
 based   on  the  data  acquired in Rochester are used  in this
 discussion) .

 The linear regression  analysis  creates   equations   of  the
 following form:
         = ax
                            bx
                                  CX
where
      x
        1'
        a.
Q, = quality parameter

x  = measured parameters

 z = calculated regression coefficient
By  using  logarithms of  the measured values and the same type
of  linear  regression analysis, an equation of the  following
form can  be developed:
                 Ql =
The quality of the regression analysis can be  evaluated  by
checking  the  correlation  of the values predicted from the
equation with the real measured values using the correlation
coefficient.  The  correlation  coefficient  has  a  maximum
value  of  one  and a minimum value of zero.  The closer the
calculated coefficient is to one, the better the correlation
and, therefore, the better the predicting  equation.   These
analyses can be performed with a package computer program, a
programmable desk-top calculator, or hand calculations using
matrix techniques.

Prom experience in the analysis of combined sewer overflows,
it is known that the quality of  the  overflow  varies  with
many   factors.    The  most  significant  factors  are  the
intensity of the rainfall, the  antecedent  condition  (days
since  last  rain), and the duration of the storm.  Land use
parameters,  such  as  population   density,   quantity   of
commercial-industrial  areas,  and street cleaning policies,
can also affect overflow quality.
                             64

-------
Example of Equations

The regression  equations are based on the quality data  that
are  collected,  as described in Section V,   In  the following
analysis, two data sets are used,  Data Set  1  (not included)
contains the average of  the  composite  samples  from  each
subarea  for  each  storm,   This  data set  covers 29 storms
between March 1974 and August 1975; two  to  seven  subareas
were averaged for  each storm.

Data Set 2  (not included)   contains  all  of  the  composite
samples of all  of  the storms for each of the subareas.  This
data  set  covers  the same storm period as Data Set 1 and is
the unaveraged  data set used  to  create  Data   Set  1,   It
contains 142 points covering 29 storms and 12  subareas,

Equations were  fitted to these data using a  package computer
program that performs linear regression  analysis,   Several
sets  of  equations  to  project  COD, suspended solids, and
nitrogenous oxygen demand  (NOD)  were  developed.   In  the
first    and    best   set   of   equations,    the   rainfall
characteristics and Data Set 1 were used to  create equations
to project  the   quality  parameters.   These  equations  are
presented   in   Table  19,   The quality parameters projected
from these equations were correlated  with   Data  Set  1  to
check   the  equations.  The correlation coefficients are not

         Table  19.   EQUATIONS FOR QUALITY PROJECTION
                   Equation
                                           Correlation
                                           coefficient
                      0.0705 v-0.0761 y-O.'tp?
COD = 50.17 Xj

TSS = 159.62 Xj'220 X2-°-31tS X3-°-329

NOD = 1.89 X,-°-191  X,-0-*39 X;0-"9*
                                              0.257

                                              0.181

                                              0.487
           where COD = chemical oxygen demand, mg/1
                TSS = total  suspended solids, mg/1
                NOD = nitrogenous oxygen demand, mg/1
                 Xi = number of days since last rain, days
                 X2 = duration of rainfall,  hr
                 X3 = average intensity of rainfall, in./hr
                               65

-------
 high  because stormwater  quality is  highly variable,  and   the
 data   that  were developed  from the  sampling  program  had  some
 major irregularities.

 Attempts were  also  made   to   develop   equations   including
 population   density  to  reflect the   impact   of  land   use
 patterns   on  stormwater   quality.   These  equations   were
 correlated  with Data Set  2.    The   correlation coefficient
 indicated  that there  was  essentially no correlation between
 the measured values and  the   predicted   values from  these
 equations.    This  lack  of correlation  may   be  because of
 irregularities  in  the  data and  because   of  the   particular
 blend of land uses in  the  City of Rochester.

 The composite samples  used for the  regression analysis   were
 composited   from  individual   samples    taken   at  regular
 intervals in time  starting with the  beginning of an  overflow
 occurrence.   The  individual samples that were  taken are  not
 directly related  to  flow and do not reflect  quality
 variations  that are flow related.  A possibly more realistic
 composite  would be one  that is sampled  proportionately  with
 flow.  A flow proportionate average  could also  be  calculated
 if both  the  time of  sample and volume  of  overflow   were
 correlated.   This correlation was  not  effectively  achieved
 even  with the extensive  data collected in Rochester.
ANALYSIS OF AVERAGES

The analysis of averages  is also  described
procedure and example of  averages.

Procedure
in  two  parts:
A large volume of data is generated from a sampling program.
These data can be manipulated in several ways.  One  of  the
easiest  ways is to calculate averages of meaningful subsets
of the data.  Two of the significant averages are (1)   gross
averages  of  the  data by subarea and (2)  averages for time
increments by subarea.

These subarea averages can be  ranked  to  indicate  trends.
The significant land use or surface characteristics can also
be  ranked.  If these rankings are indicated on a simplified
map of the study area, areal trends in overflow quality  can
be  noted.   The areas that create the most pollution can be
assigned a high priority when projects to relieve  overflows
are to be designed and constructed.

While averaging by time increment and  subarea  can  provide
information  on  trends,  it  also  can  have  another  more
valuable  use.   Because  of the first-flush phenomenon, the
                             66

-------
concentrations of the overflow change,   If the  first  flush
is   captured   by   a    storage   facility,  then  only  the
higher-quality wastewater  overflows,    This  time  increment
average can provide more  realistic quality values,

Examples of Averages

In Table 20, the average  data from 31  storms  in  1974  and
1975  are  presented  by   subarea.   Approximately  500 data
points were averaged for  each subarea.   The values in  Table
20  are  arithmetic  averages  of  the  measured values.  The
geometric  mean  is  usually  used  to   characterize   these
phenomena,  but,  because of the  large  number of zero values
from both actual measurement and  inoperative equipment,  the
geometric  mean  is not truly valid and the arithmetic value
more closely reflects the data.

In Table 21, the data have been averaged in time  increments
from  the  start  of the  storm and by subarea.  These values
are also arithmetic averages,  From the data  in  Table  21,
the  phenomenon  of  decreasing concentrations of pollutants
with time through the storm can be clearly seen,
       Table  20.   AVERAGE OVERFLOW QUALITY BY SUBAREA
                             mg/1
                   Total   Biochemical   Total   Nitrogenous
          Subarea   inorganic   oxygen    suspended     oxygen
            No.    phosphate   demand     solids      demand
7
8
9
16
17
18
21
22
25
26
28
31
1.42
1.28
1.37
1.37
1.38
1.37
1.34
1.35
1.04
1.08
2.85
0.50
161
158
178
188
186
183
203
205
53
52
66
60
316
319
358
366
358
354
381
• • *
• • •
205
291
168
4.09
4.21
4.42
4.31 '
4.29
4.25
4.04
4.06
2.35
2.27
3.38
2.41
                               67

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             Table 21.  EXAMPLE  OF AVERAGE OVERFLOW
              QUALITY BY SUBAREA AND TIME INCREMENT
BOD, mg/1
Subarea
7
8
9
16
17
18
21
22
25
26
28
29
31
0-30
rain
224
208
14 6b
152
13 lb
143
83
	 a
75
48
74
33
196
30-60
min
136
63
17 6b
159
	 c
140
45
	 a
48
68
61
34
105
60-90
min
66
53
147b
138
14 Ob
65
43
	 a
65
17
55
39
83
90+
min
— a
59
122
55
23
50
75
	 a
44
13
62
22
47
0-30
min
578
247
	 c
260
114
368
147
836
435
685
270
165
251
TSS, mg/1
30-60
min
506
136 •
200b
357
— c
586
101
559
347
	 a
231
137
216
60-90
min
216
137
22 8b
718
469b
229
80
539
316
429
244
158
227
90+
min
198
210
219
313
129
142
127,
425
123
117
239
120
140
      a.
      b.
Average values are extremely high due to data
irregularities and therefore are not valid.

Insufficient data for statistically significant
results.
      c.  No data recorded.
In Figure  27,  the rankings of  population  density  and  the
runoff coefficients are presented along with  the  rankings of
some  significant quality parameters  (based on data  in Table
20).  The  land use-population density ranking was developed
by  creating   a  weighted  average   of   the   ranking   of
commercial-industrial land and the ranking of the population
density.    This  means  that  the  area  with  the  greatest
population  density  and the most commercial-industrial land
would be the source of  the  greatest  pollution,    In  this
figure,  the   low  numbers  imply the worst conditions.  The
                              68

-------
five areas with the lowest  numbers^ in  each  category  are
shaded  for emphasis and to highlight any trends that may be
present.

The area served by the West Side trunk sewer (Area 9—shaded
in the lower half of Figure  27)  are  not  the  sources  of
highly   concentrated  pollutants  that  might  be  expected
(possibly because of the location of the overflow and system
characteristics).  The information presented  in  Figure  27
can assist the decision maker in translating an abundance of
data  into  specific  problems  in various parts of the study
area.
                              69

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        12
                 (21
            f
            ..L  1
          (1 7,
                       11
         10
                         (31.
LAND USE-POPULATION DENSITY
       13 j
              :1
    7
I     (R
                      10
                   11
 CHEMICAL  OXYGEN  DEMAND -
  TOTAL SUSPENDED SOLIDS
                                          12
                                                 10
                                                    (21.
                                              •t.*
                                              Lit,;
                                              12,
                                          11
                                           ?'',fto. 8M2 9
                            RUNOFF  COEFFICIENT
                           (PERCENT  IMPERVIOUS)
                                                   (21
                                              ,10
                                                  11
                                        (25
                                                      12
                        TOTAL INORGANIC  PHOSPHATE
 LEGEND: LOWEST RANKING NUMBER GIVEN TO HIGHEST CONCENTRATION
        POPULATION, OR PERCENTAGE OF COMMERCIAL INDUSTRIAL   '
        AREA. RANKS 1-5 SHADED FOR EMPHASIS.
   (3J)  SUBAREA NUMBER
     7   RANK NUMBER
 FIGURE  27.   EXAMPLE  OF  OVERFLOW QUALITY TRENDS
                             70

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                          SECTION IX

                  RECEIVING WATER RESPONSE

The impact of combined  sewer  overflows  on  the  receiving
water  is the most difficult and the most critical task that
must be  performed.   At  the  present  time,  a  simplified
solution does not exist.  The next alternative is to use the
best  available simulation of the receiving water that has a
record of use in the  area,   Even  when  a  program  has  a
history  of  use,  it  is  important  to define the specific
characteristics, limitations, and input-output  requirements
of the program as they apply to the system of discharges and
receiving water being analyzed.

CHARACTERISTICS OF THE RECEIVING WATER PROGRAM

The basic approach and assumptions of  the  receiving  water
program  are  important,  There are many approaches that can
be used, and  it  is  important  to  document  the  specific
approach so that any internal limitations of the program are
clearly understood.

Some of the most significant aspects of the approach are:

    •  The quality parameters that are analyzed

    •  The time  frame  of  the  program:  steady  state  or
       dynamic

    •  The basic equations that are used

    •  The source of reaction or decay rates

    •  The factors used for calibration of the program

For the City of Rochester, a program of  the  Genesee  River
prepared   by   O'Brien   and  Gere  for  the  Environmental
Protection Agency (Contract No,   68-01-1574)  was  used[l].
In  this  program a modified Streeter-Phelps formulation was
used   to   calculate    steady-state    dissolved    oxygen
concentrations  in  the  Genesee  River,  The purpose of the
                             71

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modification was to allow the use of  separate  decay  rates
for  carbonaceous material and for nitrogenous material.  An
additional term was also added to the equation to  calculate
the  benthic oxygen demand.  This benthic factor was used to
calibrate the program.

The decay coefficients used in the program  were  calculated
for  each  section  of  the  river  by the standard O'Connor
equation.  These coefficients are based  on  existing  river
characteristics  and  were  not  adjusted  to  calibrate the
program.

LIMITATIONS OF THE RECEIVING WATER PROGRAM

Many factors can limit the applicability of a program.   The
most  significant  limitations  are  the  range of flows and
conditions for which the program is calibrated.  The program
could be calibrated for only summer conditions which may  be
significantly   different  from  winter  conditions.   Flows
during the spring  rainy  season  and  winter  thaw  may  be
substantially different from flows during a dry spell in the
fall.  If the program is not calibrated for the time of year
and  flow  conditions  that  are  thought  to  be  critical,
recalibration  may be required, or a new program may have to
be found.

The Genesee River program was calibrated  for  an  "average"
condition.   This  average  condition  is  the  period  from
mid-July  through mid-October of 1973.  The program was also
operated under the Minimum  Average  Seven  Consecutive  Day
flow  condition  that is expected to recur once in a 10-year
period (MA7CD/10).  Data on river flows and  reaction  rates
were  developed  for  these two conditions.  While these two
conditions represent critical flow period in the river, they
do not necessarily represent a typical condition when  storm
overflows would occur.

The average condition that the  Genesee  River  program  was
calibrated  for  does not represent the river during storms.
Imposing simulated storm overflows on this average condition
will result in  dissolved  oxygen  depletions  greater  than
those  actually  occurring during storms^  This deviation is
not expected to be extreme enough to  warrant  recalibration
of the program.

SPECIFIC REQUIREMENTS OF THE RECEIVING WATER PROGRAM

This program and the Genesee River are discussed  at  length
in  the  report  prepared  for  the Environmental Protection
Agency titled  The Investigation of Eleven Special Attention
Areas  -in the Great Lakes Region - Genesee Rivev Basin  [1] .
                             72

-------
The  specific  details  of the program are presented in that
report.  The program itself is written in  FORTRAN  and  was
modified slightly for use in the simplified approach,

The format for the input data  is  presented  in  Table  22.
Most  of  the  data that are required describe the river and
its reaction rates.  The data for  the  base  condition  are
presented  in  Table 23.  Only a small portion of these data
must be altered for input of a stormwater overflow.

The river was modeled by a series of "reaches."  Each  reach
is  a  segment  of  the  river that has, at its beginning, a
pollution source,  The reaches are shown in Figure 28.

For each reach the characteristics of the river and data  on
any  discharges  to  the river are input to the program,  To
include a stormwater overflow, the loading from an  overflow
is  added  to  the  existing parameters.  This creates a new
data set that can be input to the program,
EXAMPLE OF THE GENESEE RIVER PROGRAM APPLIED
OVERFLOWS
TO  STORMWATER
The data for  the  base  condition,  as  mentioned  earlier,
represent  an  average  of  the summer-fall flow conditions.
The overflow data are derived from the storage-treatment and
quality tasks.

The important flow and quality parameters for  the  overflow
from  the  existing interceptor system that occurred on June
22, 1973, are presented in Table 24.   This  information  is
combined  with  the  data for the base condition and forms a
new data set for the program.  The data are combined on  the
basis  of  a  mass  loading.  This means that if a discharge
exists, the flows are added.   The  quality  parameters  are
combined  by  adding  the  individual  flows  multiplied  by
quality concentration and divided by the total flow to get a
new  quality  value.   This method was used for the Court SW
discharge.  There was no storm flow for  the  Maplewood  and
Sethgreen   overflows,   and   the  stormwater  quality  was
substituted  for  the  existing  discharge  quality.   (This
substitution may not  be  valid  and  would  depend  on  the
specific  relationship  between  the existing discharges and
the stormwater discharges),  The new data set  is  presented
in Table 25,

A partial sample of the output for  the  condition  that  is
discussed  is  presented in Table 26.  The dissolved  oxygen
concentrations calculated for the portion of the river  that
                              73

-------
Table 22.  FORMAT FOR RECEIVING WATER PROGRAM DATA
Card Card
group Format columns
3X2 1-6
(1-2)
(3-4)
(5-6)
2F5.0 41-45
46-50
29A1 52-80
11 1
14A1 2-15
12F5.0 16-20
21-25
26-30
31-35
36-40
41-45
46-50
51-55
56-60
61-65
66-70
71-75
76-80
14F5.0 11-15
16-20
21-25
26-30
31-35
36-40
41-45
46-50
51-55
56-60
61-65
66-70
71-75
76-80
Description
Date of computer printout
Month
Day
Year
Calculation interval in river miles
Print interval in river mile
Title
Card number
Name of reach
Distance of reach
Velocity in reach
Time in reach
Streamflow
Dissolved oxygen level
Carbon oxygen demand
Nitrogen oxygen demand
Deoxygenation coefficient (carbon)
Deoxygenation coefficient (nitrogen)
Reaeration coefficient
Dispersion coefficient (estuary)
Benthic "demand
Bottom surface area
Dissolved oxygen concentration
at saturation
Distance before first reach
Velocity before first reach
Time before first reach
Streamflow
Dissolved oxygen level
Carbon oxygen demand
Nitrogen oxygen demand
Deoxygenation coefficient (carbon)
Deoxygenation coefficient (nitrogen)
Reaeration coefficient
Dispersion coefficient (estuary)
Benthic demand
Bottom surface area
Variable
name

NMO
NDAY
NYR
CINT
PINT
ITIT
LX
KCARD
XIN(l)
XIN(2)
XIN(3)
XIN(4)
x:iN(5)
XIN(6)
XIN(7)
XIN(8)
XIN(9)
XIN(IO)
XIN(ll)
XIN(12)
XIN(13)
DOSAT
DO
UO
TO
FO
D00
0DCO
0DNO
XK10
XK20
XK30
EO
BO
AO
                         74

-------
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                          75

-------
                                                     LAKE ONTARIO
                                              CENTRAL CSO

                                              COURT CSO
                        EASTMAN KODAK

                           MAPLEWOOD

                           LEXINGTON
                            IRONDEQUO
                            ST.  PAUL SIP
                            SETHGREEN

                            CARTHAGE
                            BAUSCH-LOMB
 PLYMOUTH
BROOKS CSO
               SCOTTSVILLE
                                       NOTE: REACHES  IDENTIFIED BY
                                            DISCHARGE NAMED AT
                                            UPSTREAM END
AVON  STP
    FIGURE  28.   6ENESEE RIVER  REACHES  FOR
          THE RECEIVING  WATER  PROGRAM
                          76

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             Table 24.  EXAMPLE OF DATA FOR  OVERFLOWS
                   FROM STORM ON JUNE 22,  1973
                            Dissolved Carbonaceous  Nitrogenous
                      Flow,  oxygen,     oxygen      oxygen
           Reach name     mgd    mg/1    demand," mg/1  demand, mg/1
Plymouth SW
Court SW
Central SW
Mill-Factory
Lexington
Sethgreen
Maplewood

16.29
8.88
5.14
46.93
77.73



3.5
3.8
3.5
3.5
3.5
3.5
3. 5

74.0
154.3
87.0
94.0
145.9
134. 0
82. 0

14.2
36.5
9.9
5.0
15.1
32 4
•J £• » *x
14 <3
j»** • y
          a.  Carbonaceous oxygen demand - 5-day biochemical oxygen
             demand is used.

          b.  Nitrogenous oxygen demand - usually the concentration
             of ammonia plus organic nitrogen is used. A stochio-
             metric factor is used to calculate the oxygen demand
             for these compounds.
was   analyzed  are presented  graphically  in  Figure  29,  The
dissolved  oxygen concentrations for the base  condition  are
also  indicated as a reference.

There  are  two specific limitations in the analysis of  storm
flows.   During storms the  flow in the river would be higher
than  the condition that  is  modeled due to rainfall over  the
entire basin.  The effect of  this increase in  flow cannot be
readily  tabulated.   The program also uses  a  plug flow type
of analysis.   This means that a  specific  volume  of  water
moves  downstream  as  a  slug, with reactions occurring and
pollutants accumulating within  this slug.

These  two  limitations are significant,  and  therefore  this
particular  program  (type  of  model)  should be used only to
indicate trends and not to  tabulate the  specific  dissolved
oxygen concentration.  A revision to this program, currently
being  prepared by O'Brien and Gere, will make  it possible to
analyze  more constituents  and  will also result in a dynamic
representation of the river.
                               77

-------
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                               78

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Table 26. EXAMPLE OF OUTPUT FROM RECEIVING WATER
PROGRAM FOR STORM ON JUNE 22, 1973
	 CX>35N DEMAND 	 OXYGEN 	
CMBCNACECIS MTRCGENEOLS 6ENTHIC TOTAL DEFICIT LEVEL FLCW
ME DIST. MG/L POLNDS *G/L PCINDS MG/L PCUNCS fG/L PCUND'S MG/L HG/L MGO
co
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83
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                 80

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                          SECTION X           '••.:•"'


  APPLICATION OF THE SIMPLIFIED STORMWATER MANAGEMENT MODEL


 In the introduction  the  characteristics  of  a  simplified
 model were enumerated,


      "...This tool must be inexpensive to set " up  and  use
      flexible enough to be applicable to a variety of system
      configurations,  and  accurate  even  though  only very
      moderate expenditures are made for data collection  and
      preparation."


 In this chapter the specifics  of how  the  simplified  model
 m<^\ t5?Se   needs wil1 be Presented.   Among the items that
 will  be discussed  are:


 •  The computer size requirements and operating  costs


 •  The ability of the simplified   model   to  analyze   various
 drainage basins


 •  The relationship between  simplified  stormwater  management
 modeling and  the more complex  models.


 COMPUTER REQUIREMENTS


 In  the  simplified  stormwater management model a   high   speed
 digital  computer is  used  in three tasks:


      •  Rainfall  Characterization


      •  Storage-Treatment  Balance


     •  Receiving Water Response


As  described   in  Section  I  small  independent   computer
programs  are  used  for  each  analysis.   The  use of small
programs effectively reduces the overall  computer  hardware
requirement of the  simplified model.
                             81

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Hardware Requirements

The  computer  programs  for   the   simplified   stormwater
management  model  have  been  developed  on  an  IBM 360/67
digital computer.  The storage-treatment program  (the  most
complex  program in the model) has been used successfully on
a XEROX 560  computer  (approximately equal .to an  IBM  1620)
and  an  IBM  113O.    For  continued use on an IBM 1130 some
program modifications  would have to be made.

For  general  use  of  all  of  the  simplified   stormwater
management  model's  programs  a computer with approximately
40K  of  core  storage and  a  FORTRAN  compiler  would  be
required.  In addition, the programs use both disk and  tape
peripheral storage devices and a card reader.

Cost of Computer Usage

The programs are currently being  used  on  an  IBM  370/168
computer.   Approximate  CPU  (central processing unit) time,
execution time, and dollar cost for using this  computer  on
each of the programs is summarized in Table 27.

It is  important to note that these costs represent a  single
computational  run  for the computer.  The  rainfall analysis
will require several runs of the SORT and   LISTRK  programs.
One  run of each program is required to provide a listing of
the  ranking  of  each of  the  rainfall   parameters.   The
storage-treatment program also may be run many times in  the
course of  analyzing  a system of alternatives.  The actual
number of runs will  vary   significantly  depending  on  the
configuration of the system being analyzed  and the number of
control strategies that are investigated.

No costs or times are  presented  for   the  receiving  water
analysis  because  these costs are dependent on the specific
river  model used for the area being analyzed.

APPLICATION TO STORM SEWER  AND NONURBAN AREAS

In this  report  primary  attention  has  been  directed  at
applying  the  simplified   stormwater   management model to  a
system of  combined   sewers.   This    simplified   modeling
approach  is  equally  valid  for  drainage basins served by
separate storm sewers  and for nonurban  drainage basins.

Because the  simplified model  is   a  series  of  interrelated
tasks, it   is extremely  flexible and can be  readily  adapted
to various  types of drainage  basins.  The   data  preparation
task   is the  only  task that is directly affected by  the type
                              82

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              Table 27.   APPROXIMATE COMPUTER COST FOR
               SIMPLIFIED STORMWATER MANAGEMENT MODEL
                    Program
CPUa
min
Exec
min
 Cost""
  $
                Rainfall
                characterization

                  TAPE-Disk

                  EVENT

                  SNOWIN

                  EXCLUD

                  LISTSQ

                  SORT

                  LISTRK

                Storage-Treatment
                20 years of record

                  DLYCRD

                  DLYTAP .

                1 year of record

                  HOUCRD

                  HOUTAP
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.07
0.25;
0.60'
0.10
0.50
0.18
0.25
0.61
5.80
0.10
1.10
0.90
4.40
3.93
0.79

0.90
0.60

0.74
0.84

0.96
0.64

0.80
14.50

16.25
13,45
14.25
                a.  Actual computation time in computer
                    core not including the time needed
                    to execute the read and write (I/O)
                    statements or to run the peripheral
                    devices.

                b.  Time required in the computer
                    including I/O statements.
                c.  Cost based on use of IBM 370/168.
of basin being  analyzed.   The other  tasks are affected  only
by   the  data   that is collected.  The  alternatives that  are
analyzed with the  model may also be  significantly  different
for   a   system   of combined sewers than for a nonurban area,
but  the basic principles of the analysis  remain   unchanged.
When  applying   the  model  to any area, the determination of
the  K factor (see   Section   VII  and  Appendix  C)   and   the
determination of the quality associated with the  runoff (see
Section  VIII and  Appendix  D)  are portions of the model that
are  accomplished by hand computations   rather   than  by   the
computer program.
                                83

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Data Preparation                                 .

The system schematic that is developed for a drainage  basin
reflects  the  type  of  basin  being  analyzed, and differs
significantly for combined sewers,  separate  storm  sewers,
and  nonurban  areas.   Yet  the  quantity  and quality data
requirements for analysis of various drainage basins do  not
change.

For separate sewer systems and nonurban areas, the point  of
discharge  to receiving waters that would be focused on is a
storm sewer outlet or the mouth of  creeks  rather  than  an
overflow   structure   on   an  interceptor.   In  fact,  an
interceptor system would probably not  exist  for  a  system
that  is  affected  only  by  flows during wet weather.  The
drainage areas for a system of separate storm  sewers  or  a
nonurban  area  would follow natural topography very closely
and may have a very low total percentage of impervious area.

The need for collection of quantity and quality  information
is  still  the  same for separate sewer systems and nonurban
areas as it is for combined  sewers.   It  is  necessary  to
collect  some  data  to provide a point from which the model
can be calibrated.  For nonurban areas "textbook" values for
quality are a partial guide, but a few good quality  samples
are valuable to provide a firm reference point.

Rainfall Analysis

The analysis of rainfall is completely  independent  of  the
specific  type  of  drainage  basin being analyzed.  Because
nonurban areas would  possibly  be  remote  from  a  primary
weather  bureau gage, it is useful to check a reliable local
gage with the weather bureau gage.  A factor may have to  be
applied  to  the  primary  gage  data  to  provide rain data
reflecting local conditions.

Storage-Treatment Balance

The  analysis  of  alternatives   and   the   use   of   the
storage-treatment  program  should  be  less  complex  for a
system of separate sewers or a nonurban area.  The need  for
running  the  storage-treatment program sequentially working
upstream along an interceptor may be  completely  eliminated
for  nonurban  areas.   Each  drainage area may be looked at
independently.   Yet   the   ability   to   investigate   an
alternative  that  considers  collecting  stormflows  in  an
interceptor  with overflows at points on the system is still
within the capabilities of the program.
                             84

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Quality Assessment

The techniques of monitoring and  analysis  used  to  assess
stormwater quality are also independent of the drainage area
being   analyzed,    The  actual  quality  values  that  are
generated  may  be  significantly  different   for   various
drainage basins particularly in the relationship between BOD
and  suspended  solids,  but  these values do not affect the
techniques  being   used.    The   quality   assessment   is
accomplished through a series of hand computations.

Receiving Water Response

The analysis of  receiving  water  is  based  on  a  locally
available  river model and again would be independent of the
specific drainage basin being analyzed.

SIMPLIFIED AND COMPLEX MODELING

The model that has  been  presented  in  this  report  is  a
simplified  stormwater management model.  Complex stormwater
management  models  exist  [2,  3]  and   have   been   used
extensively  in  several  cities  and  parts of the country.
These two types of modeling effort are  compatible,  and  in
fact, complementary,

The advantage of  a  simplified  model  is  the  ability  to
process  long  periods of record and broad areal coverage at
low cost.  The advantage of a detailed model is the  ability
to  make  a  comprehensive  analysis  of singular events and
systems with  a  corresponding  increase  in  accuracy  when
supported by a viable data base.                            •

An example of the difference between the simplified and  the
complex   modeling   effort   is   clearly  evident  in  the
development and use  of  design  storms.   In  the  rainfall
analysis   of  simplified  modeling,  hourly  increments  of
rainfall are examined and grouped into storms,.   When  these
storms are ranked and arrayed, statistical techniques can be
used  to indicate the characteristics of design storms.  The
entire analysis of alternatives, however,  is  performed  on
the  actual  rainfall records for a selected extended period
of time.  For complex modeling, rainfall  for  shorter  time
increments  would be examined, and critical intensities from
the entire period of record may be composited into a  single
storm   that   would   represent   the  design  storm.  .All
atlernatives would then be analyzed  using  this  particular
design  storm,,   An alternative to the use of ,a design storm
is the use of an historical storm event  for  comparison  of
sewer system modification alternatives.
                             85

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It is readily apparent that the design  storm  developed  in
the  course  of  a  complex  modeling  effort  is  clearly a
precise, discrete, critical event,  This kind of  precision,
characteristic  of  complex  modeling,  is  necessary for an
accurate technical evaluation of  closely  competing  plans.
Yet  in  planning  studies,  the  simplified  models offer a
flexible screening device to  identify  consequential  storm
events and potentially attractive alternatives.

Further, in the design phase,  the  complex  and  simplified
models   can   continue   to   interact  providing  valuable
information on the selected plan.  The complex model can  be
used  to  fix  component  size  and  configuration while the
simplified model can be used to test the decisions that  are
made against the historical record.
                             86

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                         SECTION XI

              OTHER STORMWATER CONSIDERATIONS

Within the broad area of  stormwater  management  there  are
many complex problems.  Two areas not specifically addressed
by  this simplified mathematical model are sludges generated
within stormwater systems and  "nonstructural"  alternatives
for stormwater quality improvement.

SLUDGES

Sludge is a byproduct of any water collection, and treatment
system  and  stormwater  systems  are  not   an   exception.
Stormwater  sludges  are  the  solids that accumulate in the
stormwater system  and  the  solids  that  are  specifically
removed  by  stormwater treatment facilities.  This area has
been studied in recent literature [4, 5].

Stormwater sludges are typically high in grit and silt,  and
usually  low  in organic materials.  These sludges also tend
to  accumulate  high  concentrations  of  heavy  metals   as
compared with sludges from typical domestic sewage.  Typical
composition  of  sludge from combined stormwater systems are
presented in Table 28.

Solids in the stormwater system are important in  two  ways:
(1) they are generally a settleable fraction of the flow and
can  affect the capacity of facilities, and  (2) solids are a
treatment and disposal problem.

The solids in stormwater that form the sludges  are  subject
to  the  basic  rules  governing  settling  of  materials in
sewers.  Typically,  if  velocities  exceeding  2  feet  per
second  are  maintained  in the collection system, excessive
sedimentation  should  not  occur.   Problems  with   sludge
deposits  can  occur  in  stormwater  storage  or  detention
facilities.  Specific provisions must be made to provide for
cleaning of these  facilities  so  that  the  total  storage
volume will not be affected.
                             87

-------
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-------
The treatment and disposal of these sludges is a complex and
unique  problem.   Three  major   alternatives   have   been
investigated by recent research in this area:

     •   "Bleedback" to dry-weather facilities

     •   Onsite treatment

     •   Land disposal

Bleedback to dry-weather facilities  is  the  most  commonly
considered  alternative.   In  this system, sludges that are
separated from storm flows are stored during the  storm  and
slowly metered into an existing dry-weather sewage treatment
facility  after  the  storm  has  passed.   This  system  is
constrained by the hydraulic and solids handling capacity of
the        dry-weather.treatment facility.

The  second  alternative  for  sludge  handling  is   onsite
treatment.   In this alternative facilities for treating the
stormwater flows and solids would be  constructed  near  the
point  of  discharge  of  the sewer or overflow.  Most often
this onsite  system  takes  the  form  of  physical-chemical
treatment  plant.  The sludge is treated and dewatered using
mechanical  equipment.   Typical  processes  that   may   be
employed are:

     •   Dissolved air flotation

     •   Vacuum filtration

     •   Centrifugation

     •   Anaerobic digestion

     •   Gravity thickening


Land disposal is also being considered as a sludge handling
option.  Initial investigations  (4, 5) dictate sludge sta-
bilization prior to disposal and maximum loading rates based
on the sludge nitrogen and heavy metal concentrations.  Re-
sidual solids from the other two alternatives must be placed
in a landfill or some other ultimate disposal site.
                             89

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NONSTRUCTURAL ALTERNATIVES

Nonstructural  alternatives  are   those   alternatives   that
affect  a  reduction in quantity or  improvement in quality of
of the runoff, yet can be implemented  without  construction
of  major   new  facilities.   These  alternatives  have been
discussed  extensively in the  literature  [6,   7,  8].   The
possibilities  are  limited only by  the  imagination of those
charged with  management of the stormwater facilities.

The nonstructural alternatives can generally be discussed in
two categories:   (1)  alternatives  that control the source of
pollutants and runoff,  and  (2)   alternatives  that  affect
control  and   management of pollutants and runoff within the
system  of sewers.   Some  typical  nonstructural   control
alternatives  are listed in Table 29.

          Table  29.  NONSTRUCTURAL CONTROL ALTERNATIVES
                 Source Control Alternatives
                     Roof storage
                     Ponding

                     Porous pavements
                     Erosion control
                     Street cleaning
                     Deicing methods

                     Utilize natural drainage features

                 Collection System Control Alternatives
                     Sewer flushing

                     Inflow/infiltration
                     Sewer cleaning
                     Polymer injection

                     Inline storage

                     Remote Monitoring and Control
                              90

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Source Control Alternative

Three examples  of  source  control  measures  that  may  be
important in an urban area are:

     •   Street sweeping

     •   Deicing methods

     •   Erosion control

Street Sweeping.  There is a direct relationship between the
amount of dirt and grit that accumulates on city streets and
the quality of runoff.  Recent research  has  shown  that  a
great  portion of the pollution is related to fine materials
relatively unaffected  by  conventional  broom  type  street
sweeping  equipment.   Modern  vacuum  type  street cleaning
equipment can remove as much  as  95  percent  of  the  fine
materials.   No  parking  signs can be posted indicating the
hours  of  street  cleaning  operation   to   maximize   the
effectiveness  of  the  cleaning equipment that is currently
being used.

Deicing Methods.  In cold climates  various  chemicals  have
beenusedon pavement for control of ice.  These chemicals
enter the stormwater collection system  as  thawing  occurs.
Recent  studies  in  Michigan  have  suggested:  (1) no salt
application on straight, flat sections, (2) better  training
for  operators  of salt spreading equipment, and (3) keeping
records of salt use as a means of reducing salt consumption.
At a minimum, salts without highly toxic substances, such as
cyanide or chromium compounds, should be used.  These  toxic
chemicals   have   been  added  to  some  deicing  salts  as
anticaking agents or corrosion  inhibitors,  but  have  very
damaging effects on the environment.

Erosion Control.  In an urban situation,  a  heavy  load  of
silt  and  dirt  often  can  be  generated  by  simply  poor
management  of  a  construction site.  Graveling of entrance
roads to the site and control of runoff from the site during
construction can help minimize  pollutants  that  enter  the
sewer system.
System Control Alternatives

Two examples of system control alternatives  for
urban area might be:

     •   Sewer cleaning and flushing

     •   Inflow/infiltration control
a  typical
                             91

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Sewer Cleaning and Flushing.  This control measure may  have
a dual benefit, particularly on a system of combined sewers.
The  capacity  of a sewer system is inversely related to the
quantity  of  grit  that  deposits  within  it.   A  regular
cleaning program can maintain flow capacity  throughout  the
collection  system, but special attention should be directed
at any area where deposits regularly occur  along  the  main
interceptor lines.  If the capacity of the main interceptors
are  reduced by sediment , overflow will occur on the system
unnecessarily.  The cleaning and flushing maintains capacity
in lines while at the same time reducing the total volume of
pollutants that  will  be  scoured  out  of  the  lines  and
discharged to receiving waters during periods of high flow.

Inflow/Infiltration Control.  Inflow is the stormwater  that
enters  the  system  unnecessarily  from  the surface of the
ground.  Examples of this may be roof leaders or area drains
connected directly to the  sewer  system.   Infiltration  is
groundwater  that enters the sewer unnecessarily.  Typically
infiltration  occurs  through  leaking   pipe   joints   and
structurally   damaged  pipe.   It  is  somewhat  costly  to
determine sources  of  inflow/infiltration.   Usually  smoke
testing  or  television inspection is required.  Quite often
though significant reductions in flow can be realized from a
thorough location and correction program.
                             92

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               J
               9
                           REFERENCES

1.  Moffa, P.E.  Water Pollution Investigation- Genessee River
    and Rochester Area - Great Lakes Initial Contract Program.
    EPA-905/9-74-016, U.S. Environmental Protection Agency, Cin-
    cinnati, Ohio, January 1975.  234 pp.

2.  Storm Water Management Model, Volume I, Final Report.
    11024DOCO7/71, U.S. Environmental Protection Agency, Cincin-
    ati, Ohio, July 1971.  353 pp.

    Storm Water Management Model, Volume II, Final Report.
    11024DOC08/71, U.S. Environmental Protection Agency, Cincin-
    nati, Ohio, August- 1971.  173pp.

    Storm Water Management Model, Volume III, Final Report.
    11024DOCO9/71, U.S. Environmental Protection Agency, Cincin-
    nati, Ohio, September  1971.  360 pp.

    Storm Water Management Model, Volume IV, Final Report.
    11024DOC10/71, U.S. Environmental Protection Agency, Cincin-
    nati, Ohio, October 1971.  249 pp.

 3.  DiGiano, Francis T., et al.  Short Course Proceedings, Appli-
    cation of Stormwater Management Models, EPA-670/2-75-065,
    U.S. Environmental Protection Agency, Cincinnati, Ohio, 1975.
    427 pp.

 4.  Gupta, M.K., et al. Handling and Disposal of Sludges Arising
    from Combined~Sewer Overflow Treatment - Phase 1. (Draft Re-
    port), U.S. Environmental Protection Agency, Cincinnati,
    Ohio,  Contract No. 68-03-0242, 1975.  100 pp.

 5.  Clark, M.J. and Geinopoulos, A.  Assessment of the Handling
    and Disposal of Sludges Arising from Combined Sewer Overflow
    Treatment.   (Draft Report), U.S. Environmental Protection
    Agency, Cincinnati, Ohio, Contract No. 68-03-0242, February
    1976. 260 pp.

 5.  Lager, J.A. and Smith, W.G.  Urban Stormwater Management and
    Technology, an Assessment.  EPA-670/2-74-040, U.S. Environ-
    mental Protection Agency, Cincinnati, Ohio, June 1971.
    447 pp.
                               93

-------
  7.  Edison Water Quality Laboratory, Environmental Impact of
     Highway Deicing.  11040GKK06/71, U.S. Environmental Pro-
     tection Agency, Cincinnati, Ohio, June 1971.  Ill pp.

  8.  American Public Works Association. Control of Infiltration
     and Inflow into Sewer Systems.  11022EFF12/70.  U,,S. Envi-
     ronmental Protection Agency, Cincinnati, Ohio, December
     1970.  124 pp.

  9.  Heaney, J.P. et al.  Nationwide Evaluation of Combined
     Sewer Overflows and Urban Stormwater Discharges, Volume II:
     Cost Assessment and Impacts.   (Draft Report), U.S» Environ-
     mental Protection Agency, Cincinnati, Ohio, Contract No.
     68-03-0283, May 1976.  376 pp.

10.  Metcalf & Eddy, Inc. Reconnaissance Study of Combined Sewer
     Overflows and Storm Sewer Discharges.  District of Columbia,
     Department of Environmental Services Engineering and Construc-
     tion Administration.  March 1973.

11.  Hydrologic Engineering Center, Corps of Engineers,,  Urban
     Stormwater Runoff: STORM.  Generalized Computer Program.
     723-58-L2520, 1975.

12.  Davis, P.L. and Borchardt, F.  Combined Sewer Overflow
     Abatement Plan, Des Moines, Iowa.  EPA-R2-73-170.  U.S. En-
     vironmental Protection Agency, Cincinnati, Ohio, 1974.
     312 pp.
NOTE:  The following report is recommended as a companion docu-
       ment for this report:

     Heaney, J.P. Stormwater Management Model Level I, Prelimin-
     ary Screening Procedure for Wet-Weather Flow Planning.
     (Draft Report), U.S. Environmental Protection Agency, Office
     of Research and Development, Cincinnati, Ohio, June 1976.
                               94

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1
X:
           Appendix A

   EXAMPLE OF MONITORING  DATA
    FROM ROCHESTER, NEW YORK
                95

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              Appendix B




PROGRAM LISTING AND LIST OF VARIABLES
                  99

-------
Table  B-l.   RAINFALL TASK  - PROGRAM  LISTING FOR EVENT
     //J4073 JOB 'C802,322','DIDRIKSSON'
     /* SERVICE EXEC=U
     //STEP1 EXEC WATFIV
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     //GO. SYS IN DD *
     $ WATFIV
           DIMENSION MON(12) ,NY(100) ,MO(100) ,ND(100) ,NX( 100) , FR(100,24) ,
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          *ITA(100) ,IRT(100) ,LLD(100) ,NEE(100) ,NR(100) ,LCC(100)
           DATA MON/31,28,31,30,31,30,31,31,30,31,30,31/
12

14

142

144

1444

145

146
15
16

161
1614
162
17

174
175

176
       NLAST=0
         NLM=0
       LL=0
       00111=1,100
        LCC( I) =0
       IiLD(I)=0
       CONTINUE
      •1=1
       CONTINUE
       MON(2)=28
       CONTINUE
       READ(5,144)-NY(I) ,
       FORMAT(6X,3I2,I1,12F3.2)
        IF(NY(I)-99)1444,8,8
          CONTINUE
       IF(NX(I}-1)142,145,142
        CONTINUE
       READ(5,146) (FR(I,J) ,J=13,24) ,NEXT(I)
       FORMAT(13X,12F3.2,29X,I2)
       NY(I)=NY(I)+1900
       XL=NY(I)
       XL=XL/4 .
                                              (FR(I,J) ,J=1,12)
           IF(XL-XXI,)16,15r16
           MON(2)=29
           CONTINUE
             IF(MO(I)-NLM)161,1614,161
               NE=NQ+NE
               NLM=MO(I)
                NQ=MON(NLM)
                 CONTINUE
                  NR(I) =ND(I)+NE
           IC=MO(I)
           CONTINUE
          IF(I-100)176,176,174
            CONTINUE
          L=I-1
          WRITE(6,175)NY(L) ,MO(t) ,ND(L)
          FORMAT(1H , 'ERROR' ,312)
          STOP
          CONTINUE
          GOTO14
                                  100

-------
        Table B-l  (Continued)
18    CONTINUE
      IC=ND(I)+1-NEXT(I)
      IF(IC)21,17,21
21    CONTINUE
      DO22 IA=1,100
      FAX(IA)=0.
      FRS(IA)=0
      LD(IA)=0
22    CONTINUE
      JX=0
      JXX=0
      JCC=0
      DO40IA=1,I
      DO38IB=1,24
      IF(JXX)24,222,24
222   IF(FR(IA,IB))38,38,224
224   CONTINUE
      JXX=1
      JX?=JX+1
        NEE(JX)=NR(IA)
         IF(JX-1)228,226,228
226        LLD(JX)=NEE(JX)-NLAST
           GOT023
228       LLD(JX)=NEE(JX)-NEE(JX-1)
23          CONTINUE
      IRT(JX)=IB
      NYA(JX)=NY(IA)
      MOA(JX)=MO(IA)
      NDA(JX)=ND(IA)
24    CONTINUE
      IF(FR(IA,IB))25,25,26
25    JCC=JCC+1
             LCC(JX)=JCC
      IF(JCC-6)262,262,252
252   JXX=0
26    CONTINUE
           NEE(JX)=NR(IA)
            NLAST=NR(IA)
      JCC=0
262   CONTINUE
      IF(FR(IA,IB)-FAX(JX) )29,29,28
28    FAX(JX)=FR(IA,IB)
         IF(MOA(JX)-MO(IA))282,286,282
282          LL=MOA(JX)
                  IFAC=ND(IA)+MON(LL)-NDA(JX)
               GOTO288
286         CONTINUE
      IFAC=ND(IA)-NbA(JX)
288         CONTINUE
      ITA(JX)=IFAC*24+IB-IRT(JX)+1
29    CONTINUE
      FRS(JX)=FRS(JX)+FR(IA,IB)
      LD(JX)=LD(JX)-H
38    CONTINUE
40    CONTINUE
       IF(JX)12,12,41
41     CONTINUE
        DO414IA=1,JX
                 LD(IA)=LD(IA) -LCC(IA)
                     101

-------
                  Table B-l   (Concluded)
414      CONTINUE
      DO44 IA=1,JX
      WRITE(8,42)NYA(IA),MOA(IA),NDA(IA),LD(IA),FRS(IA),PAX(IA)
     *ITA(IA),LLD(IA),IRT(IA)
42    FORMAT(1H ,14,313,2F6.2,2I3,2X,I3)
44    CONTINUE
            D05IA=1,100
5         LCC(IA)=0
      GOTO12
8     CONTINUE
         WRITE(8,82)
82       PORMATC  9999')
      STOP
      END
                            102

-------
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-------
Table  B-3.    RAINFALL TASK  - PROGRAM LISTING  FOR SNOWIN
//J4073 JOB (C802,322),'T.DIDRIKSSON"
// EXEC WATFIV
//GO.PT08F001 DD DSN=C802. STORMS, UNIT=2314,VOI,=SER=SYS17,DISP=OLD
//GO.FT09P001 DD DSN=C802.CARb.C345,UNIT=2314,VOL=SER=SYS14,DISlP=OI,D
//GO.FT10F001 DD DSN=C802.STORM2,UNIT=2314,DISP=(NEW,KEEP),
//        SPACED(TRK,(50,2),RLSE),DCB=(RECFM=FB,LRECL=80,BLKSIZE=3520)
//GO.SYSIN DD *
$WATFIV
           N=0
              M=0
            NRR=0
             SNOW=0.
             NDB=0
             NYB=0
             MOB=0
12        CONTINUE
            READ(8,2)NYA,MOA,NDA,LD,FRS,FAX,ITA,LLD,IS,IRT
2           FORMAT(1X,I4,3I3,2F6.2,2I3,I2,I3,5X,I5)
             NRR=NRR+1
              NYX=NYA-1900
            GOTO32
22        CONTINUE
           READ(9,3)NYB,MOB,NDB,SNOW
3            FORMAT(5X,3I2,10X,F3.1)
32            CONTINUE
               IF(NYA-3000)324,8,8
324           IF(NYB-99)325,64,64
325           IF(NY»-NYB)64,326,22
326           IF(MOA-MOB) 64,328,22
328           IF(NDA-NDB)64,6,22
6             IF(SNOW)64,64,66
64           IS=0
              GOTO?
66            IS=1
7         CONTINUE
                 WRITE(10,2)NYA,MOA,NDA,I,D,FRS,FAX,ITA,LLD,IS,I!IT,NRR
            GOTO12
8           CONTINUE
                 WRITE(10,9)NYA
9           FORMAT(IX,14)
             STOP
             END
                                 104

-------













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-------
Table  B-5.    RAINFALL TASK - PROGRAM LISTING FOR EXCLUD
  //J4073 JOB (C802,322),'T.DIDRIKSSON'
  // EXEC WATFIV
  //GO.FT08F001 DD DSN=C802.STORM2,UNIT=2314,VOL=SER=SYS13,DISP=OLD
  //60.FT10F001 DD DSN=C802.STORM4,UNIT=2314,DISP=(NEW,KEEP) ,
  //        SPACE=(TRK,(50,2),RLSE),DCB=(RECFM=FB,Z,RECL=80,BLKSIZE=3520)
  //GO.SYSIN DD *
  $WATFIV
  12        CONTINUE
              READ(8,2)NYA,MOA,NDA,LD,FRS,FAX,ITA,I,LD,IS,IRT,NRR
  2           FORMAT(1X,I4,3I3,2F6.2,2I3,I2,I3,5X,I5)
                 IF(NYA-3000)324,8,8
  324           CONTINUE
                IF(FRS-0.05)12,12,6
  6             CONTINUE
                   WRITE(10,2)NYA,MOA,NDA,LD,FRS,FAX,ITA,I,LD,IS,IRT,NRR
              GOTO12
  8           CONTINUE
                   WRITE(10,9)NYA
  9           FORHAT(1X,I4)
               STOP
               END
                                 106

-------




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-------
Table  B-7.   RAINFALL  TASK -  PROGRAM LISTING FOR LISTSQ
258
246
248
25
 //J4073TED JOB 'C802,322,1.0,10' , 'T DIDRIK'
 /* PRINT COPIES=2
 /* SERVICE  CLASS=Q
 //STEPl EXEC WATPIV
 //GO.SYSIN DD *
 $WATFIV
 C          SEQONCE ALL YEAR
       DIMENSIONA(12) ,B(2)
       DATA A/ 'JAN' , 'FEE' , 'MAR' , 'APR' , 'MAY* , 'JUNE' , 'JULY' , 'AUG' , 'SEPT' , '0
       ICT' , 'NOV', 'DEC'/,B/'NO', 'YES'/
       TTR=0.
          1=0
       NTDU=0
18
19



2

24

22
224
226

228
242
244

252
254
       IL=*0
       WRITE(6,18)
       FORMAT( 1H1 ,//2X, 4HYEAR, 2X, 5HMONTH, 3X, 3HDAY, 2X, 6HDURAT.   , 3X, 5HTOTA
       1L,2X,8HMAX HOUR,2X, 10HHOUR AFTER, IX, 10HDAYS SINCE, 4X,6HEXCESS
       23X,9HREAL TIME,4X,4HSNOW, 9X,8HSEQUNCE
       3   /21X,5HHOURS,2X,8HRAINFALL, 1X,8HRAINFALL,4X,5HSTART,4X,10HLAST
       4STORH,4X, 6HPRECIP       ,3X,10HSTART HOUR,2X,8HINCLUDBD
              CONTINUE
           1=1+1
       READ (5, 2) IYE,MON,NDA,NDU,TR,TMR,NHR,NDT,ISN,IHR,IFXX
           IX=0
       FORMAT(1X,I4,3I3,2F6.2,2I3,I2,I3,5X,I5)
       IF(2000-IYE)9,9,24
       CONTINUE
       IF(MON)224,224,22
       IF(MON-12)228,228,224
       WRITE(6,226)
       FORMAT(6H ERROR)
           STOP
       CONTINUE
        ISN=ISN+1
        IF(I-1}244, 242,244
        IO>IYE
        CONTINUE
        IF(ICC-IYE) 252,258,252
        WRITE(6,254)NTDU,TTR,TXR
        FORMAT(////10X,I15,2F9.2)
        IL=0
        NTDU=0
        TTR=0.
        ICC^IYE
       WRITE (6, 18)
       CONTINUE
       INN=INN+1
       NTDU=NTDU+NDU
        IF(THR-TXR) 248,248,246
        TXR=TMR
        CONTINUE
        IF(IX-2)25,25,224
         IF(ISN-2)272,272,224
                                   108

-------
                    Table B-7  (Concluded)
272      CONTINUE
      WRITE(6,26)IYE,A(MON),NDA,NDU,TR,TMR,NHR,NDT,B(IX),IHR,B(ISN),INN
26    FORMAT(1H ,16,2X,A4,15,17,4X,F6.2,3X,F6.2,4X,I7,5X,I6,8X,A4,5X,I7,
     17X,A4,7X,I4)
      IF(49-IL)28,8,8
28    CONTINUE
      WRITE(6,18)
      IL=0
8     CONTINUE
         GOT019
9     CONTINUE
      WRITE(6,254)NTDU,TTR,TXR
      WRITE(6,92)
92    FORMAT(lHl)
      STOP
      END
                                 109

-------
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 Table B-9.   RAINFALL  TASK -  PROGRAM LISTING FOR  LISTRK
//J4073TED JOB 'C802,322,1.,5','T DIDRIK'
/* PRINT COPIES=2
/* SERVICE  CLASS=Q
//STEP! EXEC WATFIV
//GO.SYSIN DD *
$WATFIV
      DIMENSIONA(12),B(2)
C        RANK ALL YEAR
      DATA A/'JAN','FEE','MAR','APR','MAY','JUNE','JULY','AUG','SEPT','o
     ICT','NOV','DEC'/,B/'NO','YES'/
      INN=0
      IL=0
      WRITE(6,18)
18    FORMAT(1H1,//2X,4HYEAR,2X,5HMONTH,3X,3HDAY,2X,6HDURAT.   ,3X,5HTOTA
     1L,2X,8HMAX HOUR,2X,10HHOUR AFTER,IX,10HDAYS SINCE,4X,6HEXCESS   ,
     23X,9HREAL TIME,4X,4HSNOW, 9X,6HRANKED,5X,9HRANKED BY,
     3   /21X,5HHOURS,2X,8HRAINFALL,IX,8HRAINFALL,4X,5HSTART,4X,10HLAST
     4STORM,4X, 6HPRECIP       ,3X,10HSTART HOUR,2X>8HINCLUDED,
     517X,9HMAGNITUDE///)
12        CONTINUE
      READ(5,2) IYE,MON,NDA,NDU,TR,TMR,NHR,NDT,ISN,IHR,IPP,IFXX
2     FORMAT(I4,3I3,2F6.2,2I3,I2,I3,5X,I5,5X,I5)
         IX=0
      IF(2000-IYE)9,9,24
24    CONTINUE
      IX=IX+1
      ISN=ISN+1
      INN=INN+1
      IL=IL+1
      WRITE(6,26) IYE,A(MON) ,NDA,NDU,TR,TMR,NHR,NDT,B(IX) ,IHR,B(ISN),INN
     1,IFXX
26    FORMAT(1H ,16,2X,A4,I5,I7,4X,F6.2,3X,F6.2,4X,I7,5X,I6,8X,A4,5X,I7,
     17X,A4,7X,I4,5X,I10)
      IF(49-IL)28,8,8
28    CONTINUE
      WRITE(6,18)
      IL=0
8     CONTINUE
          GOTO12
9     CONTINUE
      WRITE(6,92)
92    FORMAT(1H1)
      STOP
      END
                                   111

-------









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-------
Table  B-ll.   STORAGE-TREATMENT TASK  - PROGRAM LISTING
 //J4073TED JOB  'C802,322,l.,3','T DIDRIK'
 //STEP1 EXEC  FORTHC,FARM.FORT='MAP'
 //GO.FT08F001 DD  DSN=C802.STORM1,UNIT=2314,
 //     DISP=(NEW,KEEP) ,SPACE=(TRK,(100,10) ,RLSE) ,
 //     DCB=(RECFM=FB,LRECL=80,BLKSIZE=3520)
 //GO.FT11F001 DD  DSN=C802.STORMS,UNIT=2314,VOL=SER=SYS17,DISP=OLD
 //GO.FT09F001 DD  DSN=C802.CARD.C345,UNIT=2314,VOL=SER=SYS14,DISP=OLD
 //GO.FT10F001 DD  DSN=C802.STORM2,UNIT=2314,DISP=(NEW,KEEP),
 //GO.SYSIN DD *
 C      STORAGE  -  TREATMENT
 C                  THEODOR DIDRIKSSON
 C                  METCALF &  EDDY, INC., ENGINEERS
 C                  1029 CORPORATION WAY
 C    '              PALO ALTO,  CALIF. 94303
        DIMENSIONM(13),ARN(5),MXX(13)
        COMMONM,AREA,COEF,STMAX,TREAT,STOPS,NYEAR,STOR,COEFX,
      *NFL,LD,ND,TRD,FAC,IOTAP,MYEAR
        DATA MXX/0,31,28,31", 30,31,30,31,31,30,31,30,31/
        D011I=1,13
 11     M(I)=MXX(I)
        READ{5,12)(ARN(I),1=1,5),AREA,COEF,STMAX,TREAT,STOPS,NYEAR,
      *NSS,IOTAP,IPFL,MYEAR,TFAC
 C      NSS=0  FOR  DAILY & NSS=1  FOR HOURLY
 C      IOTAP=0  INPUT  ON CARDS &  IOTAP=1 INPUT ON TAPE OR DISK
 C      IPFL NUMBER OF INFLOW FROM UPPER REACHES BY  INTERSEPTOR
 C      TFAC FACTOR TO DETERMIND VOLUMN ROUTED TO TREATMENT PLANT
 C      THE FIRST  DAY  OF RAINFALL OR NUMBER OF HOURS BEFORE
 C      TREATMENT  STARTS FOR HOURLY SIMULATION
 C      NYEAR  NUMBER OF YEARS OR MONTHS READ OF CARDS
 C      ARN NAME OR NUMBER OF THE AREA UNDER CONSIDERATION
 12     FORMAT(5A4,5F8.0,I2,3I1,I4,1X,F10.0)
        STOR=STOPS
        COEFX=AREA*COEF* 0.027156
        TRD=0.
         FAC=1.
        NFL=0
        LD=0
        ND=0
           NFAC=TFAC
        WRITE(6,13)(ARN(I),1=1,5)
 13     FORMAT(1H4,60X,'ROCHESTER',10X,5A4,    ///43X,4HAREA,8X,6HR
      ItJNOFF,5X,11HMAX STORAGE,3X,14HTREATMENT RATE/43X,5HACRES,6X,10HCOE
      2FFICENT,7X,2HMG,11X,3HMGD///)
     -   WRITE(6,132)AREA,COEF,STMAX,TREAT
 132   FORMAT(1H ,38X,F10,0,5X,F7.2,4X, F10.0,4X,F10.0)
        WRITE(6,14)
 14      FORMAT(1H3,8sx,'METCALF & EDDY, INC., ENGINEERS'/
      *85X,'1029 CORPORATION WAY'/85X,'PALO ALTO, CALIF. 94303')
            IF(NSS)2,2,3
 2       IF(IOTAP)22,22,24
 22      CALL  DLYCRD(TFAC)
           GOTO4
 24      CALL  DLYTAP(IPFL,TFAC)
               GOTO 4
 3       IF(IOTAP)32,32,34
 32         CALL  HOUCRD
         GOT04
 34      CALL  HOUTAP(IPFL,NFAC)
 4         CONTINUE
                                   113

-------
                 Table B-ll  (Continued)
             STOP
          END
           SUBROUTINE HOUCRD
      COHMONM,AREA,COEP,STMAX,TREAT,STOPS,NYEAR,STOR,COEFX,
     *NFL,LD,ND,TRD,FAC,IOTAP,MYEAR
      DIMENSIONM(13),MON(10),MDAT(10),RAIN(10)
      TREAT=TREAT/2 4.
      D060I1=1,NYEAR
      RUNOF=0.
      NDR=0
      NOV=0
      CTD=<0.
      STOS=STOPS
      TRUN=0.
      TOV=0.
      TRE=0.
      LSD=0
      READ(5,14)MYEAR,NCARD
14    FORMAT(2110)
      WRITE(6,142)MYEAR
142   FORMAT(1H1,///5X,5HMONTH,16,14X,
     A                20HOCCURING ON THE HOUR,19X,SSHACCUMULATED FROM STA
     1RT OF THE MONTH/24X,34H	,5X,
     C5 6H""""*"""~""""'<~~"'M"-"--"""-"---~"--™—•"——"•——"—"-—"———•""——"-———-——••••"-"••••-"—//
     D              6H DAY   ,1X,4HHOUR,2X,4HRAIN,2X,4HRAIN,2X,6HRUNOFF,2
     2X,7HSTORAGE,2X,8HOVERFLOW,2X,7HTREATED,5X,9HT.  RUNOFF,2X,10HT.OVER
     3FLOW,7H  OVERFL,8H  T.TREAT,7H   TREAT,13H  MAX STORAGE/13X,2HIN,3X,4
     4HHOUR,4X,2HMG,6X,2HMG,8X,2HMG,7X,2HMG,12X,2HMG,10X,2HMG,5X,4HHOUR,
     55X,2HMG,5X,4HHOUR,7X,2HMG//)
      MY=MYEAR+1
      MT=M(MY)
      LTOT=0.
      DO166II=1,MT
166   LTOT=I,TOT+24
      DO50I2=1,NCARD
      READ(5,168)(MON(J),MDAT(J),RAIN(J),J=1,10)
168   FORMAT(10(2I2/F4.2))
      DO17J=1,10
      IF( MON(J)-MT)1684,1684,1688
1684  IF(MDAT(J)-24)17,17,1688
1688  WRITE(6,1689)
1689  FORMAT(6H ERROR)
      STOP
17    CONTINUE

      003013=1,770
      IF(NFL-0)178,178,176
176   NFL=NFL+1
178   CONTINUE
      TRD=0.
      OVFL=0.
      RUNOF=0.
      RIN=0.
      IF(JC-10)18,18,32
18    CONTINUE
      MX=MON(JC)
      LSD=LSD-H
      IF(LTOT-LSD)2604,21,21
21    CONTINUE
                                   114

-------
               Table B-ll  (Continued)
      IF(MX)26,26,214
214   CONTINUE
      LTD=-24
      DO22I4=1,MX
22    LTD=LTD+24
      ND=LTD+MDAT(JC)
23    CONTINUE
      IF(LSD-ND)26,24,26
24    RUNOF=COEFX*RAIN(JC)
      NFL=NFL-H
      TRUN=TRUN+RUNOF
      RIN=RAIN(JC)
      JC=JC+1
      STOR=STOR+RUNOF
      NDR=NDR+1
26    CONTINUE
      IF(LSD-l)2601,2608,2601
2601  CONTINUE
      LTD=0
      DO2602IQ=1,MT
      LTD=LTD+24
      IF{LTD-LSD+1)2602,2604,2602
2602  CONTINUE
      GOT02608
2604  CONTINUE
      WRITE(6,2603)SRIN
2603  FORMAT(///11H TOTAL RAIN,F6.2)
      SRIN=0.
      IF(LTOT-LSD)60,2606,2606
2606  CONTINUE
      WRITE(6,142)MXEAR
2608  CONTINUE
      STORA=STOR
      IF(NFL-l)271,271,263
263   STOR=STOR-TREAT
2'64   IF(STOR-STOPS) 266,266,27
266   NFL=0
      STOR=STOPS
27    CONTINUE
      TRD=STORA-STOR
      CTD=CTD+TRD/TREAT
      TRE=TRE+TRD
271   CONTINUE
      STM=STOR-STMAX
      IF(STM)274,274,272
272   NOV=NOV+1
      OVFL=STM
      TOV=TOV+STM
      STOR=STMAX
274   CONTINUE
      IF(STOS.LT.STOR)STOS=STOR
      ILL=0
      MXQ=0
      DO276IL=1,MT
      IF(MXQ-LSD)275,278,278
275   MQQ=MXQ
      MXQ=MXQ+24
      ILI,= ILL+1
276   CONTINUE
278   LSX=LSD-MQQ
                                  115

-------
 282
 29
 30
 32
 50
 60

 64
14

142
15

154
16
166
168
                       Table  B.-ll  (Continued)
 SRIN=SRIN+RIN
 WRITE (6, 28 2) ILL   ,LSX,RIN,NDR,RUNOF,STOR,OVFL,TRD,TRUN,TOV,NOV,TRE
 1  ,CTD,STOS
 FORMAT(1H ,I3,I5,F6.2,I5,F9.2,F10.2,2F9.2,F14.2,F11.2,I6,1?10.2,
 1F8.2,F10.2)
 IF(JC-11}30,29,30
 IF(I2-NCARD)32,30,32
 CONTINUE
 CONTINUE
 CONTINUE
 CONTINUE
 WRITE (6, 64)
 FORMAT (1H1)
 STOP
 END
       SUBROUTINE DLYCRD(TFAC)
 COMMONM, AREA, COEF,STMAX, TREAT, STOPS, NYEAR,STOR,COEFX,
 *NFL,LD,ND,TRD,FAC,IOTAP,MYEAR
 DIMENSIONM{13) ,MON(10) ,MDAT(10) ,RAIN(10)
 D060I1=1,NYEAR
 NDR=0
      CTD=0.
      SRIN=0.
      RUNOF=0.
      STOS=STOPS
      TRUN=0.
 TRE=0.
 LSD=0
 M(3)=28
 READ(5,14)MYEAR,NCARD
 FORMAT(2I10)
 KRITE(6,142)MYEAR
 FORMAT(1H1,///5X,4HYEAR,16,14X,
A               20HOCCURING ON THE DATE,19X,34HACCUMULATED FROM STA
1RT OF THE YEAR/24X,34H	,5X,
C56H	•	//
D               6H MONTH,1X,3HDAY,2X,4HRAIN,2X,4HRAIN,2X,6HRUNOFF,2
2X,7HSTORAGE,2X,8HOVERFLOW,2X,7HTREATED,5X,9HT. RUNOFF,2X,10HTJOVER
3FLOW,7H OVERFL,8H T.TREAT,7H  TREAT,13H  MAX STQRAGE/13X,2HIN,3X,4
4HDAYS,4X,2HMG,6X,2HMG,8X,2HMG,7X,2HMG,12X,2HMG,10X,2HMG,5X,4HDAYS,
55X,2HMG,5X,4HDAYS,7X,2HMG//)
 XL=MYEAR
 XL=XL/4.

 XXL=L
 IF(XL-XXL)16,15,16
 M(3)=29
 WRITE(6,154)MYEAR
 FORMAT(10H LEAP YEARI10)
 CONTINUE
 LTOT=0.
 0016611=1,13
 LTOT=LTOT+M(II)
 D050I2=1,NCARD
 READ(5,168)(MON(J),MDAT(J),RAIN(J),J=1,10)
 FORMAT(10(2I2,F4.2))
      IF{ MON(J)-12)1684,1684,1688
                                  116

-------
       Table  B-ll  (Continued)
1684  IF(MDAT(J)-31)17,17,1688
1688  WRITE(6,1689)
1689  FORMAT(6H ERROR)
      STOP
17    CONTINUE
      JC-1
      DO30I3=1,370
      IF(NFL-0)178,178,176
176   NFL=NFL+1
178   CONTINUE
           IF(TRD)1798,1798,1792
1792       IF(RUNOF)1798,1798,1793
1793       NFL=NFL+1
           FAC=1.
1798       CONTINUE
      TRD=0.
      OVFL=0.
      RUNOF=0.
      RIN=0.
      IF(JC-10)18,18,32
18    CONTINUE
      MX=MON(JC)
      LSD=LSD-H
      IF(LTOT-LSD)2604,21,21
21    CONTINUE
      IF(MX)26,26,214
214   CONTINUE
      LTD=0
      D022I4=1,MX
22    LTD=LTD+M(I4)
      ND=LTD+MDAT(JC)
23    CONTINUE
      IF(LSD-ND)26,24,26
24    RUNOF=COEFX*RAIN(JC)
      NFL=NFL+1
      TRUN=TRUN+RUNOF
      RIN=RAIN(JC)
      JC=JC+1
      STOR=STOR+RUNOF
      NDR=NDR+1
26    CONTINUE
      IF(LSD-l)2601,2608,2601
2601  CONTINUE
      LTD=0
      DO2602IQ=1,13
      LTD=LTD+M(IQ)
      IF(LTD-LSD+1)2602,2604,2602
2602  CONTINUE
      GOT02608
2604  CONTINUE
      WRITE(6,2603)SRIN
2603  FORMAT(///11H TOTAL RAIN,F6.2)
      SRIN=0.
      IF(LTOT-LSD)60,2606,2606
2606  CONTINUE
      WRITE(6,142)MYEAR
2608  CONTINUE
      STORA=STOR
      IF(NFL-1)271,271,263
263   STOR=STOR-TREAT*FAC
                                  117

-------
                    Table  B-ll  (Continued)
264
266

27
271

2712

2718
2719


272



274
       IF(STOR-STOPS)266,266,27
       NFI,=0
       STOR= STOPS
       CONTINUE
       TRD=STORA-STOR
       CTD=CTD+TRD/TREAT
       TRE=TRE+TRD
          GOTO  2719
       CONTINUE
           IF(NFL-l) 2712, 2712, 2718
           FAC=TFAC
           GOTO 263
           FAC=1
           CONTINUE
       STH=STOR-STMAX
       IF(STM) 274, 274,272
       NOV=NOV+1
       OVFL=STH
       TOV=TOV+STM
       STOR=STMAX
       CONTINUE
       IF ( STOS . LT . STOR) STOS=STOR
       ILL=0
       MXQ=0
       DO276IL=1,13                                             "
       MXQ=MXQ+M(IL)
       IF(MXQ-LSD)275,278,278
275    MQQ=MXQ
       ILL=ILL+1
276    CONTINUE
278    LSX=LSD-MQQ
       SRIN=SRIN+RIN
       WRITE(6,282)ILL  ,LSX,RIN,NDR,RUNOF,STOR,OVFL,TRD,TRUN,TOV,NOV,TRE
     1 ,CTD,STOS
282    FORMAT(1H ,I3,I5,F6. 2,I5,F9.2,F10. 2,2F9. 2,F14. 2,F11.2,I6,1?10.2,
     1F8.2,F10.2)
       IF(JC-11)30,29,30
29     IF(I2-NCARD) 32,30,32
30     CONTINUE
32     CONTINUE
50     CONTINUE
60     CONTINUE
       WRITE (6, 64)
64     FORMAT (1H1)
       STOP
       END
            SUBROUTINE DLYTAP( IPFI,,TFAC)
       COMMONM , AREA , COEF , STMAX , TREAT , STOPS , N YEAR, STOR , COEFX ,
     *NFL,LD,ND,TRD,FAC,IOTAP,MYEAR
       DIMENSIONM(13)  ,MON(370) ,MDAT(370) ,RAIN(370) ,FINT(370) ,FP1(370) ,
     *FP2(370) ,FP3(370)
        READ(5,167)NZA,MON(1) ,MDAT(1) ,RAIN(1)
12      CONTINUE
        MYEAR=NZA+1900
        D0122IQ1=1,370
         FP1(IQ1)=10000.
         FP2(IQ1)=0.
         FP3(IQ1)=0.
122      FINT(IQ1)=0.
        IF(IPFL)14,14,124
                                  118

-------
                     Table  B-ll  (Continued)
124        READ(11,1678)Jll
        READ(11,1679)(FPl(JXX),JXX=1,J11)
14      CONTINUE
        FAC=TFAC
      NDR=0
      NOV=0
      CTD=0.
      SRIN=0.
      RUNOF=0.
      STOS=STOPS
      TRUN=0.
      TOV=0.
      TRE=0.
      LSD=0
      M(3)=28
      WRITE{6,142)MYEAR
142   FORMAT(1H1,///85X,'METCALF & EDDY, INC., ENGINEERS /
     *85X,'1029 CORPORATION WAY'/
     *85X,'PALO ALTO,CALIF.94303'
     *          ,///5X,4HYEAR,I6,14X,
     A               20HOCCURING ON THE DATE,19X,34HACCUMULATED FROM STA
     1RT OF THE YEAR/24X,34H	;	/5X,
     C5 6H—"~—————————————-——'-———————————————————————— —————/ j
     D               6H MONTH,1X,3HDAY,2X,4HRAIN,2X,4HRAIN,2X,6HRUNOFF,2
     2X,7HSTORAGE,2X,8HOVERFLOW,2X,7HTREATED,5X,9HT, RUNOFF,2X,10HT.OVER
     3FLOW,7H OVERFL,8H T.TREAT,7H  TREAT,13H  MAX STORAGE/13X,2HIN,3X,4
     4HDAYS,4X,2HMG,6X,2HMG,8X,2HMG,7X,2HMG,12X,2HMG,10X,2HMG,5X,4HDAYS,
     55X,2HMG,5X,4HDAYS,7X,2HMG//)
      XL=MYEAR
      XL=XL/4.
      L=XL
      XXL=L
      IF(XL-XXL) 16,15,16
15    M(3)=29
      WRITE(6,154)MYEAR
154   FORMAT(10H  LEAP YEARI10)
16    CONTINUE
      LTOT=0.
      0016611=1,13
166   LTOT=LTOT+M(II)
       J=l
1664    CONTINUE
          J=J+1
      READ(5,167)NYZ,MON(J),MDAT(J),RAIN(J)
167   FORMAT(5X,3I2,6X,F4.2)
             IF(NYZ-NZA)1682,1664,1682
1674    CONTINUE
          J=KK
          NZA=NYZ
         MON(1)=MON(J)
        MDAT(1)=MDAT(J)
       RAIN(1)=RAIN(J)
        WRITE(8,1678)J11
1678    FORMAT(I10)
        WRITE(8,1679) (FINT(IXX) ,IXX=1,J11)
1679     FORMAT(10F8.2)
        WRITE(9,1678) Jll
        WRITE(9,1679) (FP2(IXX) ,IXX=1,J11)
           IF(NYZ-90)12,62,62
1682     CONTINUE
                                   119

-------
    Table  B-ll  (Continued)
          KK=J
           D017J=1,KK
       IF( MON(J)-99)1683,17,1683
 1683  IP( MON(J)-12)1684,1684,1688
 1684  IF(MDAT(J)-31)17,17,1688
 1688  WRITE(6,1689)MON(J),MDAT(J)
 1689  FORMAT(6H ERROR,2110)
       STOP
 17    CONTINUE
       JC=1
       DO30I3=1,370
       IF(NFL-0)178,178,176
 176   NFL=NFL+1
 178   CONTINUE
            IF(TRD)1798,1798,1792
 17.92       IF(RUNOF) 1798,1798,1793
 1793       NFL=NFL+1
            FAC=1.
 1798       CONTINUE
       TRD=0.
       OVFL=0.
       RUNOF=0.
       RIN=0.
       IF(JC-370)18,18,32
 18    CONTINUE
       MX=MON(JC)
       LSD=LSD+1
       IF(LTOT-LSD)2604,21,21
 21    CONTINUE
       IF(MX)26,26,214
 214    CONTINUE
       LTD=0
       D022I4=1,MX
 22    LTD=LTD+M(I4)
       ND=LTD+MDAT(JC)
 23    CONTINUE
       IF(LSD-ND)26,24,26
 24    RUNOF=COEFX*RAIN(JC)
        RINT=FP1(JC)
       NFL=NFL+1
       TRUN=TRUN+RUNOF
       RIN=RAIN(JC)
       JC=JC+1
       STOR=STOR+RUNOF
        IF(RUNOF)25,26,25
 25      CONTINUE
      NDR=NDR+1
 26    CONTINUE
       IF(LSD-l)2601,2608,2601
 2601  CONTINUE
      LTD=0
      DO2602IQ=1,13
      LTD=LTD+M(IQ)
      IF(LTD-LSD+1)2602,2604,2602
2602  CONTINUE
      GOTO2608
2604  CONTINUE
      WRITE(6,2603)SRIN
2603  FORMAT(///11H TOTAL  RAIN,F6.2)
      SRIN=0.
1.}
                                  120

-------
                     Table B-11  CContinued)
      IF(LTOT-LSD)60,2606,2606
2606  CONTINUE
      WRITE(6,142)MYEAR
2608  CONTINUE
      STORA=STOR
      IF(NFL-l)271,271,263
263      CONTINUE
         IF(TREAT-RINT) 2632,2632,2634
2632       TREET=TREAT
          GOT02638
2634     TREET=RINT
2638     CONTINUE
       STOR=STOR-TREET*FAC
264   IF(STOR-STOPS)266,266,27
266   NFL=0
      STOR=STOPS
27    CONTINUE
      TRD=STORA-STOR
         IF(TREET)2704,2719,2704
2704       CONTINUE
      CTD=CTD+TRD/TREET
      TRE=TRE+TRD
          GOTO 2719
271   CONTINUE
           IF(NFL-l)2712,2712,2718
2712       FAC=TFAC
           GOTO 263
2718       FAC=1.
2719       CONTINUE
      STM=STOR-STMAX
      IF(STM)274,274,272
272   NOV=NOV+1
      OVFL=STM
      TOV=TOV+STM
      STOR=STMAX
274   CONTINUE
      IF{STOS,LT.STOR) STOS=STOR
      ILL=0
      MXQ=0
      D0276IL=1,13
      MXQ=MXQ+M(IL)
      IF(MXQ-LSD)275,278,278
275   MQQ=MXQ
      ILL=ILL+1
276   CONTINUE
278   LSX=LSD-MQQ
      SRIN=SRIN+RIN
        IF(IPFL-2)2784,279,279
2784    CONTINUE
         FINT(13)=TREET-TRD
         GOTO 28
279      FINT(I3)=RINT-TRD
28        CONTINUE
         FP2(I3)=RUNOF
          J11=I3
      WRITE(6,282)ILL   ,LSX,RIN,NDR,RUNdF,STOR,OVFL,TRD,TRUN,TOV,NOV,TRE
      1  ,CTD,STOS
282   FORMAT(1H  ,I3,I5,F6.2,I5,F9.2,F10.2,2F9.2,F14.2,F11.2,I6,F10.2,
      1F8.2,F10.2)
30    CONTINUE
                                  121

-------
 32
 50
 60

 62

 64
 122
 13
 142
144

145

148

149

15

152



154
                     Table  B-ll  (Continued)
   CONTINUE
  CONTINUE
  CONTINUE
      GOTO1674
    CONTINUE
  WRITE (6, 64)
  FORMAT (1H1)
  RETURN
  END
       SUBROUTINE HOUTAP( IPFL,NFAC)
  COMMONM , AREA , COEF , STMAX , TREAT , STOPS , N YEAR , STOR, COEPX ,
 *NFr,,LD,ND,TRD,FAC,IOTAP,MYEAR
  DIMENSIONM(13) ,MON(24) ,MDAT(24) ,RAIN(24)
  TREAT=TREAT/ 2 4 .
   CONTINUE
   READ(5,148)MYEAR,MA,MD,NX,(RAIN(J),J=1,12)
   IF(MYEAR-99)122,63,122
    IF(NX-2)13,12,12
    CONTINUE
  SRIN=0.
  RUNOF=0.
  NDR=0
       CTD=0.
       STOS=STOPS
       TRUN=0.
 TRE=0.
 LSD=0
 WRITE(6,142)MA
 FORMATC1H1,///5X,5HMONTH,I6,14X,
A               20HOCCURING ON THE HOUR,19X,35HACCUMULATED FROM STA
1RT OF THE MONTH/24X,34H	,,5v
C56H	LJ/'/
D             6H DAY  ,1X,4HHOUR,2X,4HRAIN,2X,4HRAIN,2X,6HRUNOFF,2
2X,7HSTORAGE,2X,8HOVERFLOW,2X,7HTREATED,5X,9HT.  RUNOFF,2X,]0HT.OVER
3FLOW,7H OVERFI,,8H T.TREAT, 7H  TREAT,13H  MAX STORAGE/13X, 2IHIN, 3X,4
4HHOUR,4X,2HMG,6X,2HMG,8X,2HMG,7X,2HMG,12X,2HMG,10X,2HMG,5X,4HHOUR,
55X,2HMG,5X,4HHOUR,7X,2HMG//)
 MY=MA+1
 MT=M(MY)
 LTOT=0.
 0014411=1,MT
 LTOT=LTOT+24
 GOTO 15
   CONTINUE
   READ(5,148)IC,MA,MD,NX>(RAIN(J) ,J=1,12)
  FORMAT(6X,312,II,12F3. 2)
  IF(IC-99)149,63,149
  CONTINUE
  IF(NX-2)15,145,145
  CONTINUE
   READ(5,152)(RAIN(J),J=13,24),NEXT
   FORMAT(13X,12F3.2,29X,I2)
   DO154IA=1,24
    MON(IA)=MD
    MDAT(IA)=IA
    CONTINUE
 D017J=1,24
 IF(  MON(J)-MT) 1684,1684,1688
                                  122

-------
 Table  B-ll  (Continued)
1684  IF(MDAT(J)-24)17,17,1688
1688  WRITE(6,1689)
1689  FORMAT(6H ERROR)
      STOP
17    CONTINUE
      JC=1
      003013=1,770
      IF(NFL-NPAC)178,176,176
176   NFL=NFL+1
178   CONTINUE
      TRD=0.
      OVFL=0.
      RUNOF=0.
      RIN=0.
      IF(JC-24)18,18,32
18    CONTINUE
      MX=MON(JC)
      LSD=LSD-fcl
      IF(LTOT-LSD)2604,21,21
21    CONTINUE
      IF(MX)26,26,214
214   CONTINUE
      LTD=-24
      D022I4=1,MX
22    LTD=LTD+24
      ND=LTD+MDAT(JC)
23    CONTINUE
      IF(LSD-ND)26,24,26
24    RUNOF=COEFX*RAIN{JC)
      NFL=NFL+1
      TRUN=TRUN+RUNOF
      RIN=RAIN(JC)
      JC=JC+1
      STOR=STOR+RUNOF
        IFCRIN)25,26,25
25      CONTINUE
      NDR=NDR+1
26    CONTINUE
      IF(LSD-l)2601,2608,2601
2601  CONTINUE
      LTD=0
      D02602IQ=1,MT
      LTD=LTD+24
      IF(LTD-LSD+1)2602,2604,2602
2602  CONTINUE
      GOT02608
2604  CONTINUE
      WRITE(6,2603)SRIN
2603  FORMAT(///11H  TOTAL RAIN,F6.2)
      SRIN=0.
      IF(LTOT-LSD)60,2606,2606
 2606  CONTINUE
      WRITE(6,142)MA
 2608  CONTINUE
      STORA=STOR
       IF(NFL-1)271,271,263
 263  STOR=STOR~TREAT
 264   IF(STOR-STOPS)266,266,27
 266  NFL=0
       STOR=STOPS
                                   123

-------
           Table B-ll  (Concluded)
27
271
272
274
275
276
278
282
29
30
32

60

63
64
 CONTINUE
 TRENSTORA-STOR
 CTD=CTD+TRD/TREAT
 TRE=TRE+TRD
 CONTINUE
 STM=STOR-STMAX
 IF(STM)274,274,272
 NOV=NOV+1
 OVFL=STM
 TOV=TOV+STM
 STOR=STMAX
 CONTINUE
 IF(STOS.LT.STOR) STOS=STOR
 D0276IL=1,HT
 IF(MXQ-LSD) 275,278,278
 MQQ=MXQ
 MXQ=MXQ-f24
 ILL=ILL+1
 CONTINUE
 LSX=LSD-HQQ
 SRIN=SRIN+RIM
 WRITE(6,282) ILL  ,LSX,RIN,NDR,RUNOF,STOR,OVFL,TRD,TRUN,TOV,NOV,TRE
1 ,CTD,STOS
 FORMAT(1H ,I3,I5,F6. 2,I5,F9. 2,F10. 2,2F9. 2,F14. 2,F11. 2,I6,F10. 2,
1F8.2,F10.2)
 IF(JC-25)30,29,30
 IF(NEXT-1)32,30,32                                            ;
 CONTINUE
 CONTINUE
    GOTO 145
 CONTINUE
   GOT012
 WRITE(6,64)
 FORMAT(lHl)
 STOP
 END
                            124

-------










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-------
       Appendix C



DETERMINATION OF K FACTOR
            127

-------
                           Appendix C

                  DETERMINATION OF K FACTOR

 The gross runoff coefficient (K factor) is an  integral   part
 of  the  storage-treatment  program.   This  factor   can  be
 determined  from reliable measurements of rainfall and  total
 runoff quantities as-described in Section  V.   This   factor
 can also be predicted based  on geographic data.

 Recent  research  has  developed   a   correlation    between
 population  density and  the  fraction of impervious land  in a
 region [9].  This relationship is of the form:
                1-9.6 PDd
                         (0-573 - °'0391
                           (1)
        where   I — imperviousness in percent
             PD, - population density in developed portion
                  of urbanized area, persons/acre


The  results from this equation  can  be  checked  with  values
for   a   known  region.   in   Figure  C-l the actual data  for
Rochester  are plotted along  with  the  curve  resulting  from
the  predicting equation  shown above.

The  fraction of imperviousness  can  be used directly as  a  K
factor   or  it  can be adjusted to  reflect local conditions.
The   computer  model  STORM[11,12]   weights   pervious   and
impervious fractions with the following equation[9].
               K = 0.15 (l-I) •*• 0.901

               K - 0.15 + 0.751
                                                    (2)
        where  K = gross runoff coefficient

              I = fraction imperviousness
The values of  0.15 and
STORM.
0.90  are  default   values  used  in
                              128

-------
                                       LEGEND

                                       PREDICTING EQUATION
                                    ©  DATA POINT FOR- ROCHESTER
                 15    20     25     30    35

            POPULATION DENSITY, PERSONS  PER ACRE
FIGURE  C-1 .   COMPARISON  OF ROCHESTER  DATS'WITH
      IMPERVIOUSNESS PREDICTING  EQUATION
                         129

-------
                           Appendix  D

        OVERFLOW  QUALITY ASSESSMENT-ALTERNATE METHODS

 In this section  two  alternative procedures for computing  the
 quality of stormwater  discharges from  combined and  separate
 sewer systems are  presented.  The  first  method was developed
 in the course of the nationwide assessment of the stormwater
 problem  [9],    This  method uses  geographic and demographic
 characteristics  to predict quality parameter.   The  second
 procedure that will  be discussed is a  regression technique.

 QUALITY PREDICTION FROM GEOGRAPHIC AND DEMOGRAPHIC DATA

 Stormwater quality is  a function   of   land  use,  population
 density,  and precipitation.  From the nationwide assessment
 the  following relationships were developed[9]:
          Separate areas:  Mg » a(i,j) x P x f(PD)

          Coiribined areas:  M,, = b(i,j) x P x f (PD)
                                  (1)

                                  (2)
    M

a(i,j)
          where      M = lb of pollutant, Ib/acre-yr

                       constant for separate storm systems for
                       i land use and j constituent, lb/acre-iii.,

                       constant for combined storm systems for
                       i land use and j constituent, Ib/acre-in.

                    P = annual precipitation, in./yr

                f (PD) = population density function
This   equation  when  provided  with  appropriate  constants
summarized in Table D-l,   will  calculate  annual  pollutant
loadings.

However,  for use in  the   simplified  mathematical   model  a
concentration  of  pollutants  is required that can  be paired
with   the   volume   of    overflow   generated     in    the
                              130

-------
             Table  D-l.  QUALITY CONSTANTS FOR
                LOADINGS FROM SEWER  SYSTEMS
                     Pounds  per Acre-Inch
Pollutant,
Land use, i
Separate areas a(i,j)



Combined areas b(i,j)


"
1.
2.
3.
4.
1.
2.
3.
4.
Residential
Commercial
Industrial
Other
Residential
Commercial
Industrial
Other
1.
0
3
1
0
3
13
5
0
BOD5
.799
.20
.22
.18
.29
.2
.00
.47
2. SS
16
22
29
2
67
91
120
11
.3
.2
.1
.7
.2
.8
.0
.1
3.
9.
14.
14.
2.
38.
57.
59.
10.
VS
48
0
4
60
9
9
4
8
j
4
0
0
0
0
0
0
0
0

. P04*
.034
.076
.071
.010
.139
,312
.291
.041

5. N**
0.540
0.296
0.276
0.061
0.540
1.22
0.140
0.250
* Total P as PO4.
**Total N as N.
storage-treatment  task.    Following  the  format  used in the
nationwide assessment  the relationship would be of  the form:
          Separate areas: Qs = c(i,j) x f(PD)
          Combined areas: Qc = d(i,j) x f(PD)
(3)
(4)
          where      Q = concentration of pollutants, mg/1
                c(i,j) = constant for separate storm systems for
                        i land use and j constituent, mg/1
                d(i,j) = constant for combined sewer systems for
                        i land use and j constituent, mg/1
                 f (PD) «* population density function

The  constants  a(if j)  and b(i,  j) were  derived  from  surface
loading  to  be used with precipitation.   These  constants  can
be  adjusted  to be  used  with   runoff   and  for  dimensional
                                131

-------
 consistency  with   simplified   modeling,
 be effected by the  following equation:
                                      x P]/k
                                      x F]/k
The conversion can

         (5)
         (6)
         where  F » 4.14, constant,  [(mg/l)/(lb/acre-in.)]
               k * 0.34 national average runoff coefficient
                  for seven cities [9]
 These constants, summarized  in  Table D-2,  can  be   used  with
 the   following  population   density  functions   (f(PD))   to
 predict quality values that  can be used   in  the,  simplified
 mathematical  model.
          Residential
           f(PD) = 0.142 + (0.218 x PD°'54)
          Commercial and industrial
           f(PD) = 1.0
          Other (open and nonurban)
           f(PD) - 0.142
       (7)
       (8)
       (9)
              Table D-2.   QUALITY  CONSTANTS FOR
              CONCENTRATIONS FROM  SEWER SYSTEMS
Pollutant, j
Land use, i
Separate areas, c(i,j)



Combined areas, d(i,j)



1.
2.
3.
4.
1.
2.
3.
4.
Residential
Commercial
Industrial
Other
Residential
Commercial
Industrial
Other
1. BOD5
10.
41.
15.
1.
42.
171.
64.
6.
4
5
8
5
7
3
9
1
2. SS
211.
288.
377.
35.
871.
1,191.
1,557.
144.
5
1
6
0
9
2
0
0
3. VS
123.
181.
186.
33.
123.
751.
770.
140.
0
7
8
7
0
3
8
1
4.
0.
0.
0.
0.
1.
4.
3.
0.
:po4*
44
98
91
13
80
05
78
521
5. N**
7.01
3.84
3.58
0.79
7.01
15.83
1.82
3.24
* Total P as PO4.
**Total N as N.
                                132

-------
An important fact to remember  is that the  values  predicted
by  these  equations reflect  the characteristics  of the seven
cities  on  which  sampling  data  was  available  from  the
nationwide assessment.   It would be very beneficial to  have
sampling   data  collected  that could be used  for comparison
and/or  adjustment  of   these   equations  to   reflect  local
conditions

QUALITY PREDICTION USING REGRESSION TECHNIQUES

In the body of the text  two  regression techniques, developed
for use in Rochester, were described.   A  third  regression
analysis,   originally  developed for analyzing stormwater in
Washington, B.C., is presented here as  another   option  for
predicting   quality   parameters[10].    The   procedure  is
outlined  sequentially.
1.  Compute suspended  solids (degritted
from  the  following expression:
                                  fraction)   in  mg/1
                     ss
               400 x £]. x £2 x £3
                                                   (10)
where
                400 = an average suspended solids value
                     that can be changed if local data
                     are available for a closer fit

                 f i = a function of days since the last
                     rain and time from the start of
                     overflow or discharge

                 f2 = a function of rainfall intensity

                 £3=3 funqtion of catchment population
                     density
For  each time increment compute a value  for  ss  reading   f^,
±2,  and fa from Tables  D-3, D-4, and D-5,  respectively.

The  computed values   will  suffice,  for  both  combined   and
separate systems.

2.   Compute BOD for  separate storm drains  from the following
expressions:
BOD,, (storm)
   3

BOD- (storm)
   5
           .10.x ss for ss values equal to
                  or less than 300 mg/1

           30 + (ss - 300) x .08 for ss values
                      greater than 300 mg/1
                                                      (12)
                               133

-------
 Table D-3.   REGRESSION  COEFFICIENT  f-.
Time since start of
overflow, hr/or min
1st hr/or less than 30 min
2nd hr/30-90 min
3rd hr/90-180 min
4fch-6th hr/180-360 min
7th-12th hr/360-720 min
13th or more hr/more than
720 min

0-6
1.2
.9
.6
.5
.4
.3
Days since
7-12
1.9
1.2
.7
.5
.4
.3
last
13-18
2.3
1.5
.7
.5
.4
.3
rainstorm
Over
18
2.6
1.7
.7
.5
.4
.3
Unknown
1.9
1.2
.7
.5
.4
.3
Table D-4.   REGRESSION COEFFICIENT
            Rainfall intensity, in./hr
       .01-.09   .10-.20   .21-.50  Over .50
   f 2 =   .5
    .9
1.2
                     1.5
Table D-5.   REGRESSION COEFFICIENT f-
        Populatiqn density, persons per acre



       0.10   11-20   21-30   31-40   Over 40
        .5
.65
                     .80
                            .95
                                    1.0
                    134

-------
3.  Compute  BOD for combined overflows  from  the  following
expression:
               BOD5(comb.) = aD + (1 - a) x BODg(storm)
(13)
       where  a = proportion of combined flow attributed to
                average dry-weather sanitary flow

             D = average BOD5 concentration of dry-weather
                sanitary flow
Note:  Knowing  the average dry-weather  flow from the area  in
mgd, the  hourly rate is simply this   value  divided  by  24.
Where a is  therefore the hourly  sanitary flow plus the storm
runoff  that  hour  divided  by  the  sum of the two,.  A new  a
must be computed each time step.

4.  Compute total nitrogen (all  forms as N, mg/1)   for  both
combined  and  separate systems from the  following expression:
       N = o.io BOD,
                                                   (14)
5.  Finally,  compute total phosphorus  (all forms as P, mg/1)
for both combined and separate systems   from  the  following
expression:
          0.033 BODC
(15)
The above method gives concentrations   in  a  general  sense
only  and   should  not  be  used   for  other than first level
approximations  without substantial corroborating data.

Total  coliforms  can  be  computed  similarly,  but  it   is
doubtful that  the effort is warranted  considering  the  high
order numbers  involved.
                              135

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                          GLOSSARY

Combined sewage—Sewage containing both domestic sewage  and
surfacewateror  stormwater,  with  or without industrial
wastes.  Includes flow in heavily infiltrated sanitary sewer
systems as well as combined sewer systems.
Combined sewer—A sewer receiving both
runoff and municipal sewage.
intercepted  surface
Combined sewer  overflow—Flow  from  a  combined  sewer  in
excess of the interceptor capacity that is discharged into a
receiving water.

First flush-—The condition, often occurring in  storm  sewer
discharges   and   combined  sewer  overflows,  in  which  a
disproportionately high pollutional load is carried  in  the
first portion of the discharge or overflow.

Infiltration—The water entering a sewer system and  service
connections  from the ground, through such means as,, but not
limited to, defective pipes, pipe  joints,  connections,  or
manhole  walls.   Infiltration  does  not  include,  and  is
distinguished from, inflow.

Inflow—The water discharged into a sewer system arid service
connections from such sources as, but not limited  to,,  roof
leaders,  cellar,  yard, and area drains, foundation drains,
cooling water discharges, drains  from  springs  and  swampy
areas,  manhole  covers, cross connections from storm sewers
and  combined  sewers,  catchbasins,  stormwaters,   surface
runoff,  street  wash  waters, or drainage.  Inflow does not
include, and is distinguished from, infiltration.
In-system—Within the physical confines of
network.
    the  sewer  pipe
Interceptor—A sewer that receives dry-weather flow  from  a
number   of   transverse   combined  sewers  and  cidditional
predetermined quantities of intercepted surface  runoff  and
conveys such waters to a point for treatment.
                            136

-------
Municipal sewage—Sewage  from  a  community  which  may  be
composed of domestic sewage, industrial wastes, or both.

Overflow—(1) The flow discharging from  a  sewer  resulting
from  combined sewage, storm wastewater, or extraneous  flows
and normal flows that exceed the sewer  capacity.    (2)  The
location at which such flows leave the sewer.

Physical-chemical treatment processes—Means of treatment in
w.hich the removal, of pollutants is brought  about  primarily
by  chemical  clarification  in  conjunction  with   physical
processes.     The   process   string   generally    includes
preliminary treatment, chemical  clarification,  filtration,
carbon adsorption, and disinfection.

Plug flow—The passage of liquid through a chamber such that
all increments of liquid move only in the direction  of  flow
and at equal velocity.

Pollutant-—Any  harmful  or  objectionable  material , in  or
change in physical characteristic of water or sewage.

Sewer—A pipe or conduit generally closed, but normally ,npt
flowing full, for carrying sewage or other waste liquids.

Storm flow—Overland flow, sewer flow, or  receiving  stream
flow  caused  totally, or  partially  by  surface  r.unoff or
snowmelt.                                              •   ,

Storm,  sewer—A  sewer  that  carries  intercepted   surface
runoff,  street wash and other wash'waters, or drainage, but
excludes domestic sewage and industrial wastes.
Storm,sewer discharge—Flow   from  a
discharged into a receiving water.
storm  sewer  that  is
Stormwater—Water resulting from precipitation which  either
•percolates  into the soil, runs off  freely  from the surface,
or  is captured by storm sewer,  .combined  sewer,  and  to  a
limited degree sanitary sewer facilities.

Surcharge-—The flow condition occurring in  closed, conduits
whenthe  hydraulic  grade  line  is above the crown of the
sewer.

Surface runoff—Precipitation -that falls onto  the  surfaces
of  roofs,  streets, ground, etc., and is not absorbed .or or
retained by that surface,  thereby   collecting  and  running
off.
                             137

-------
Urban runoff—surface runoff from  an  urban  drainage  area
that  reaches  a  stream  or other body of water or a sewer.
Wastewater—The spent water of a community.
Sewage and Combined Sewage.
See  Municipal
                             138

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                              TECHNICAL REPORT DATA
                        (Please read Instructions on the reverse before completing)
1. REPORT NO.
  EPA-600/2-76-218
                                                  3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
                                                  5. REPORT DATE
  Development  and Application of a
  Simplified Stormwater Management Model
                                                     August 1976 (Issuing Date)
           6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)   -                 •
  John A.  Lager, Theodor  Didriksson, and
  George B.  Otte
           8. PERFORMING ORGANIZATION REPORT NQ.
9. PERFORMING ORG \NIZATION NAME AND ADDRESS
  Metcalf &  Eddy, Inc.
  1029 Corporation foay
  P.O.Box 10-046
  Palo Alto,  California 94303
           10. PROGRAM ELEMENT NO.

              1BC611
           II.CSMWJfcSK'GRANTNO.


              Y005141
12. SPONSORING AGENCY NAME AND ADDRESS
 "Municipal  Environmental  Research Laboratory
  Office of  Research and Development
  U.S. Environmental P-rotection Agency
  Cincinnati,  Ohio 45268
           13. TYPE OF REPORT AND PERIOD COVERED
              Final Report
           14. SPONSORING AGENCY CODE

              EPA-ORD
15. SUPPLEMENTARY NOTES
  Project Officer:  Anthony N. Tafuri, 201/548-3347 x512 (8-342-7512)
16. ABSTRACT         •

  A simplified  stormwater management model  has  been created  to
  provide an   inexpensive,   flexible  tool   for  planning  and
  preliminary  sizing of stormwater facilities.

  The model  delineates  a   methodology  to  be  used  in  the
  management   of   storrawater   and  consists  of  a  series   of
  interrelated   tasks that combine small computer programs and
  hand computations.  The model  successfully  introduces  time
  and  probability  into  stormwater  analysis, promotes total
  system consciousness on the  part of the user, and assists  in
  establishing     size-effectiveness     relationships     for
  facilities.

  Throughout the  report, data  from the City of  Rochester,  ISiew
  York, is presented and analyzed as a working  example.
17.
                           KEY WORDS AND DOCUMENT ANALYSIS
               DESCRIPTORS
                                       b.lDENTIFIERS/OPEN ENDED TERMS
                       c. COSATI Field/Group
  *Combined sewers,  Drainage, *Mathe-
  matical models,  *0verflows—sewers,
  Regression analysis,  *Runoff,
  *Surface water runoff, *water crual-
  ity
  *Corabinec2 sewer
  overflows, Drainage
  systems, Pollution
  abatement, *Storrrr
  runoff, * Urban
  hydrology
      13B
18. DISTRIBUTION STATEMENT


  RELEASE TO PUBLIC
19. SE'CUfrl'TY"CLASS (ThisReport)"
  UNCLASSIFIED
21. NO. OF PAGES

     153
                                       20. SECURITY CLASS (Thispage)
                                         UNCLASSIFIED
                                                              22. PRICE
EPA Form 2220-1 (9-73)
                                     139

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