United States Office of Water and SW-868
Environmental Protection Waste Management September 1980
Agency Washington DC 20460 /> i
&EPA Hydrologic
Simulation on Solid
Waste Disposal
Sites
-------
HYDROLOGIC SIMULATION ON SOLID WASTE DISPOSAL SITES (HSSWDS)
by
Eugene R. Perrier and Anthony C. Gibson
Water Resources Engineering Group
Environmental Laboratory
U. S. Army Engineer Waterways Experiment Station
Vicksburg, Miss. 39180
Contract No. EPA-IAG-D7-01097
Project Officer
Robert E. Landreth
Solid and Hazardous Waste Research Division
Municipal Environmental Research Laboratory
Cincinnati, Ohio 45268
MUNICIPAL ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U. S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OHIO 45268
60604
-------
DISCLAIMER
This report has been reviewed by the Municipal Environmental Research
Laboratory, U. S. Environmental Protection Agency, and approved for publica-
tion. 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 rec-
ommendation for use.
, PROTECTION
ii
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Permit Writers Guidance Manual/Technical Resource Document
Preface
The land disposal of hazardous waste is subject to the requirements
of Subtitle C of the Resource Conservation and Recovery Act of 1976.
This Act requires that the treatment, storage, or disposal of hazardous
wastes after November 19, 1980, be carried out in accordance with a
permit. The one exception to this rule is that facilities in existence
as of November 19, 1980 may continue operations until final administrative
dispostion is made of the permit application (providing that the facility
complies with the Interim Status Standards for disposers of hazardous
waste in 40 CFR Part 265). Owners or operators of new facilities must
apply for and receive a permit before beginning operation of such a
facility.
The Interim Status Standards (40 CFR Part 265) and some of the
administrative portions of the Permit Standards (40 CFR Part 264) were
published by EPA in the Federal Register on May 19, 1980. EPA will soon
publish technical permit standards in Part 264 for hazardous waste
disposal facilities. These regulations will ensure the protection of
human health and the environment by requiring evaluations of hazardous
waste management facilities in terms of both site-specific factors and
the nature of the waste that the facility will manage.
The permit official must review and evaluate permit applications to
determine whether the proposed objectives, design, and operation of a
land disposal facility will be in compliance with all applicable pro-
visions of the regulations (40 CFR 264),
EPA is preparing two types of documents for permit officials
responsible for hazardous waste landfills, surface impoundments, and
land treatment facilities: Permit Writers Guidance Manuals and Technical
Resource Documents. The Permit Writers Guidance Manuals provide guidance
for conducting the review and evaluation of a permit application for
site-specific control objectives and designs. The Technical Resource
Documents support the Permit Writers Guidance Manuals in certain areas
(i.e. liners, leachate management, closure, covers, water balance) by
describing current technologies and methods for evaluating the performance
of the applicant's design. The information and guidance presented in
these manuals constitute a suggested approach for review and evaluation
based on best engineering judgments. There may be alternative and
equivalent methods for conducting the review and evaluation. However,
iii
-------
if the results of these methods differ from those of the EPA method,
their validity may have to be validated by the applicant.
In reviewing and evaluating the permit application, the permit
official must make all decisions in a well defined and well documented
manner. Once an initial decision is made to issue or deny the permit,
the Subtitle C regulations (40 CFR 124.6, 124.7 and 124.8) require
preparation of either a statement of basis or a fact sheet that discusses
the reasons behind the decision. The statement of basis or fact sheet
then becomes part of the permit review process specified in 40 CRF
124.6-124.20.
These manuals are intended to assist the permit official in arriving
at a logical, well-defined, and well-documented decision. Checklists and
logic flow diagrams are provided throughout the manuals to ensure that
necessary factors are considered in the decision process. Technical data
are presented to enable the permit official to identify proposed designs
that may require more detailed analysis because of a deviation from suggested
practices. The technical data are not meant to provide rigid guidelines for
arriving at a decision. References are cited throughout the manuals to pro-
vide further guidance for the permit official when necessary.
IV
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ABSTRACT
The purpose of this research project was to provide an interactive com-
puter program for simulating the hydrologic characteristics of a solid and
hazardous waste disposal site operation. A large number of stations (cities)
within the United States for which 5 years of climatic records exist have
been put on tape for easy access and can be used in lieu of on-site measure-
ments. In addition, to expedite model usage, the model stores many default
values of parameter estimates which can be used when measured and existing
data files are not available. The user must supply the geographic location,
site area and hydrologic length, the characteristics of the final soil and
vegetative cover, and default overrides where deemed necessary. From minimal
input data, the model will simulate daily, monthly, and annual runoff, deep
percolation, temperature, soil-water, and evapotranspiration.
The model, which is a modification of the SCS curve number runoff method
and the hydrologic portion of the USDA-SEA hydrologic model (CREAMS), has
been modified to conform to the design characteristics of solid and hazardous
waste disposal sites. The model takes hydrologic parameter input data and
operates sequentially as precipitation information is read. The user can re-
quest a final cover soil with a vegetative and a barrier layer or with a uni-
form final cover soil. The user can select an "impermeable liner" separating
the final cover soil material from the solid waste cells and select the life
expectancy of the liner. The model is designed for use in a conversational
manner, that is, the user interacts directly with the program and receives
output immediately. No prior experience with computer programming is re-
quired for model usage. All necessary commands to use the model are pre-
sented in the user's manual.
v
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CONTENTS
Preface ........ ill
Abstract v
Figures vii
Tables x
Acknowledgements xi
1. Introduction 1
2. General Description of HSSWDS Program 2
3. HSSWDS User's Manual 4
Model operation using default data 6
Input data files 23
Output 43
4. Conclusions 50
Future considerations 50
References 52
Appendices
A. Hydrologic Simulation 54
Runoff 54
Evapotranspiration 59
Drainage 61
B. Cost Breakup of Boeing Computer Services 63
C. Sensitivity Analysis 64
Impermeable liner 64
SCS curve number 75
Winter cover factor 79
Depth of barrier soil 81
Depth of vegetative soil 85
Leaf area index (LAI) 89
Barrier soil compaction 95
Soil texture 99
Summary of sensitivity study 107
D. Operation of COMNET Computer System 109
Cost breakup for the COMNET-TSO System Ill
VI
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FIGURES
Number Page
1 Generalized flowchart for the hydrologic simulation
Model HSSWDS 3
2 Schematic diagram of the hydrologic cycle on a solid
waste disposal site 5
3 General relation between soil-water, soil texture, and
hydraulic conductivity 6
4 USDA classification system 8
5 Steps to log on and off BCS 14
6 Default data worksheet 15
7 Power law relations used to estimate the effective aging
of an impermeable liner 22
8 Data input requirements (no defaults) 26
9 SCS curve number for several vegetative covers in relation
to the minimum infiltration rate (MIR) 42
A-l Relation between the fraction of runoff and the fraction
of retention 56
A-2 SCS rainfall-runoff relation standardized on retention
parameter S 58
C-l Data input requirements for climatological and
hydrological modules 65
C-2 Annual Cincinnati, Ohio, precipitation from 1974 to 1978 .... 72
C-3 Annual waste drainage as related to the impermeable liner .... 74
C-4 Annual soil drainage as related to the impermeable liner .... 75
C-5 Annual runoff as related to the SCS curve number 76
C-6 Annual evapotranspiration as related to SCS curve number .... 77
vii
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FIGURES (continued)
Number Page
C-7 Annual waste drainage as related to the SCS curve number 78
C-8 Average monthly evapotranspiration as winter cover factor .... 79
C-9 Average monthly waste drainage as related to the winter
cover factor 80
C-10 Average monthly runoff as related to the winter cover factor ... 81
C-ll Annual surface runoff as related to depth of barrier soil .... 82
C-12 Total waste drainage versus year of occurrence as related to
depth of barrier soil 83
C-13 Average monthly surface runoff as related to depth of
barrier soil 84
C-14 Average monthly waste drainage as related to depth of
barrier soil 85
C-15 Annual waste drainage as related to the depth of
vegetative soil 87
C-16 Average monthly soil water for the 5-year data set and the 1976
data set for January 1976 through February 1977 with
vegetative soil depth as the parameter 88
C-17 Average annual soil water as related to the vegetative
soil depth 89
C-18 Average monthly evapotranspiration as related to the LAI 91
C-19 Average monthly waste drainage as related to the LAI 92
C-20 Average monthly surface runoff as related to the LAI 93
C-21 Average monthly soil water as related to the LAI 94
C-22 Annual surface runoff as related to the barrier soil
compaction 96
C-23 Annual waste drainage as related to the barrier soil
compaction 97
C-24 Comparison of average monthly precipitation to 1976
precipitation 98
viii
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FIGURES (continued)
Number Page
C-25 Waste drainage and precipitation during the month of
occurrence for 1978 100
C-26 Waste drainage as related to time in days for various soil
textures (V = vegetative soil, BS = barrier soil,
comp = compacted) 106
ix
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TABLES
Number Page
1 Solid waste cover soil characteristics (default) 7
2 Mean daily solar radiation (Langleys) 9
3 Typical leaf area index distributions for various
vegetative covers 35
C-l Parameters varied for sensitivity analysis 73
C-2 Percentages of the surface runoff, waste drainage, and
evapotranspiration to the average annual precipitation
for the SCS curve number 78
C-3 Percentages of the surface runoff, waste drainage, and
evapotranspiration to the average annual precipitation
for depth of vegetative soil 86
C-4 Percentages of the surface runoff, waste drainage, and
evapotranspiration to the average annual precipitation
for the leaf area index (LAI) 90
C-5 Hydraulic conductivity, available water content, and
porosity values used to evaluate barrier soil compaction .... 95
C-6 Percentages of the surface runoff, waste drainage, and
evapotranspiration to the average annual precipitation
for barrier soil compaction 95
C-7 Soil parameter values used in the sensitivity study 101
C-8 Percentages of the surface runoff, waste drainage, and
evapotranspiration to the average annual precipitation
for various soil textures 102
C-9 Amount of waste drainage and precipitation as a function of
time and soil texture (VS = vegetative soil, BS = barrier
soil, comp = compacted) 103
C-10 Summary of sensitivity study results 108
D-l Telephone numbers needed to log on the COMNET computer system . . 110
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ACKNOWLEDGEMENTS
The authors would like to express their sincere appeciation to
Dr. Arlin D. Nicks, Agricultural Engineer, USDA, SEA-AR, Chickasha, Okla.,
for a copy of the CREAMS model and for his helpful criticisms and suggestions.
Acknowledgement is made to Mr. James H. Terry, Operations Research Analyst,
for developing the city/state climatological tape and to Mr. Robert J.
Wills, Jr., for constructive suggestions and writing Appendix C of this re-
port. For contributing constructive suggestions during the project develop-
ment and preparation of this manual, acknowledgement is made to Ms. Jane
Harris, Hydrologist, S.E. Huey Co., Monroe, La., and to Mr. Bryan Young,
Co-op Student, US-EPA, Cincinnati, Ohio.
Also, acknowledgement is made to Mr. Andrew J. Green, Chief, Environ-
mental Engineering Division (EED), Dr. Raymond L. Montgomery, Chief, Water
Resources Engineering Group, EED, of the Environmental Laboratory, and
Dr. Richard L. Lutton, Geotechnical Laboratory, for their help and guidance.
A special thanks to Mr. Robert E. Landreth, Project Officer, Drs. Dirk
Brunner and Mike Roulier, Solid and Hazardous Waste Research Division,
US-EPA, Cincinnati, Ohio, for their valuable help and guidance through
Operation Fast Track.
XI
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SECTION 1
INTRODUCTION
Percolation and runoff of precipitation is of particular concern on
solid waste disposal sites as a potential for contamination of ground and
surface waters by leachate. The proper landfill site design and operational
approach is to minimize or eliminate percolation through the solid waste.
The purpose of this report is to provide a communication-type computer pack-
age to aid in the evaluation of disposal facilities by stimulating hydrologic
characteristics of sanitary landfill operations. The HSSWDS model permits
rapid evaluation of design, final soil cover materials, and operational
methodologies by estimating leachate generation on solid waste management
systems.
The design of municipal solid waste facilities and sanitary landfills
has been discussed in detail by Brunner and Keller (1), Pavoni et al. (2),
Geswin (3), Beck (4), and Bartos (5). Most solid waste is ultimately dis-
posed on land in a landfill where solid waste is covered with soil at the end
of each day's operation. A general description of a sanitary landfill opera-
tion follows the process where solid waste is spread on the ground and com-
pacted to the maximum density practical. At the end of each working day, all
solid waste delivered to the site during the day is covered with compacted
soil. This constitutes a solid waste cell. A sanitary landfill consists of
one or more lifts of solid waste cells. If two or more lifts are placed,
each lift is covered by an intermediate cover. All completed sanitary land-
fills are covered with a thick final layer of a cover soil.
Although a large variety of types and designs of solid waste sites does
occur, this report deals only with the hydrology of the final cover material
(see Lutton et al. (6)). The simulation model assumes that the moisture con-
tent of the solid waste material is at field capacity. That is, drainage due
to gravitational forces has ceased. Therefore, the volume of water entering
the solid waste by percolation through the final cover material will immedi-
ately be lost into leachate drainage at the bottom of the cell.
The hydrologic simulation models considered were deterministic, that is,
the behavior of a hydrologic variable is assumed known and its characteris-
tics can be predicted without uncertainty. These models are termed "lumped
systems." That is, the dynamic equations governing their behavior are not
involved with space coordinates. In models of this type (Perrier et al. (7),
Fenn et al.(8)), position is not important, and all components may be re-
garded as being located at a single vertical line in space. These models are
described by ordinary differential equations and assume uniform slope and
uniform final soil and vegetative cover materials.
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SECTION 2
GENERAL DESCRIPTION OF HSSWDS PROGRAM
The HSSWDS program was developed to evaluate permit applications. The
program may also assist engineers and planners in producing a feasible plan
for the design and implementation of a solid waste disposal site. The pro-
gram is a set of computer-based modules which perform water balance calcu-
lations on various cover materials and operational methodologies to develop
the planning level design. The program has been written for the user who
may not have any background in computer programming. The only equipment
required to run the program is a small computer terminal and a telephone.
The input and output is interactive so the user can have instant results.
The hydrologic portion of the USDA-SEA model entitled Chemicals Runoff
and Erosion from Agricultural Management Systems (CREAMS) (9) has been modi-
fied to conform to the general design characteristics of solid waste disposal
sites (for a detailed description see Appendix A). The flowchart for the hy-
drology simulation model is shown in Figure 1 for daily time steps. From
minimal input data, the model will simulate daily, monthly, and annual values
of runoff, cover and waste drainage, temperature, soil-water, and evapotrans-
piration. To expedite model usage, the model stores many default values of
parameter estimates to be used when measured and existing data are not avail-
able, for example, soil-water characteristics, precipitation, mean monthly
temperatures, mean monthly solar radiation, and vegetative characteristics.
In addition, a large number of stations within the United States which con-
tain 5 years of climatic records are on tape for easy access to be used in
lieu of onsite measurements. The user must supply the title, geographical
location, the site area, length and slope, and the characteristics of the
landfill material, soil, and vegetative cover. A sensitivity study for the
model is given in Appendix C.
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ENTER CLIMATOLOGICAL
DATA; RAIN, TEMP, RAD, LAI.
ENTER HYDROLOGICAL DATA;
SOLID WASTE PARAMETERS
COMPUTE DAILY TEMPERATURE
RADIATION AND LEAF AREA INDEX
READ ONE YEAR'S
DAILY PRECIPITATION
COMPUTE
EVAPOTRANSPIRATION
AND SOIL WATER MOVEMENT
CALCULATE OVERALL
STATISTICS
Figure 1. Generalized flowchart for the hydrologic simulation
Model HSSWDS.
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SECTION 3
HSSWDS USER'S MANUAL
All major hydrologic processes which occur during a rainstorm, such as
rainfall, infiltration, soil-water, deep drainage and surface water flow, can
be simulated in various levels of detail. This model scales the field hydro-
logic response during and between storm events. It is a continuous simula-
tion model which uses a day as the time step for evapotranspiration, soil-
water movement, and deep percolation. This section is presented as an aid to
the planner and technician to develop climatological input and site parameter
information and, if necessary, to set up data files for running the model.
The hydrologic processes that the model addresses are shown in Figure 2
for a solid waste disposal site. A portion of the precipitation in the form
of rain or melted snow which infiltrates the soil cover at the surface perco-
lates to the interface of the soil cover and solid waste. The model limits
the user to only two layers in the final cover soil, a vegetative soil and a
barrier soil. At the interface of the final cover soil and the solid waste,
the user may specify an impermeable liner usually of a polymeric material.
The model will evaluate the life of the liner using the age equations (power
law). The solid waste material is assumed to be at field capacity and,
therefore, any water percolating across the interface will eventually drain
either out of the site or into the soil layers beneath the solid waste stor-
age. The model permits an examination of the soil cover/impermeable liner
type scenario to better design these parameters under existing climatic
conditions.
A conceptual understanding of soil-water contents and movement is shown
in Figure 3. Individual soils have values different from these shown; how-
ever, the general relation of soil-water to soil texture is presented. The
terminology (11) used is defined as follows:
Field capacity is the water content that a soil retains after drainage
ceases (due to the forces of gravity).
Wilting point is the water content a soil retains after plants
cannot extract any more soil-water and they remain wilted.
Available water capacity is the difference between the soil-water at
field capacity and the wilting point.
Hydraulic conductivity is the rate of soil-water movement (due to the
forces of gravity) between the soil-water contents at saturation and
field capacity.
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PRECIPITATION
VEGETATIVE SOIL
BARRIER SOIL
SOLID
WASTE
DRAINAG
FINAL COVER
DRAINAGE
LEACHATE
Figure 2. Schematic diagram of the hydrologic cycle on a solid waste
disposal site.
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0.30
0.24
o
O 0.18
O
o
0.12
0.06
: PLANT-
AVAILABLE WATER
»; ^UNAVAILABLE WATER |:'f
J? , . „ ' "•* ^^ ~* W '•&' 4 ^•^•S'^^f.s^WW^. =• = '
o^ ^ . j, ' ; >- * * "-5^ - * s^>s 1'i ,<-'*•
O
to
cr
Ui
X
u
J 0
SAND
SANDY
LOAM
LOAM
SILT
LOAM
CLAY
LOAM
CLAY
DECREASING HYDRAULIC CONDUCTIVITY
Figure 3. General relation between soil-water, soil texture, and
hydraulic conductivity (10).
MODEL OPERATION USING DEFAULT DATA
To expedite model usage, one portion of the model inputs evapotranspira-
tion, evaporation, and soil-water characteristics as defaults. A portion of
these values is shown in Table 1. Figure 4 is provided to assist the user in
the soil classification system of the USDA. In addition, several stations
within the United States which contain 5 years of climatic records are on
tape for easy access to the geographical location of interest. The locations
available for using default data are presented in Table 2. The steps to log
on/off the Boeing Computer System (BCS)* are shown in Figure 5, which pre-
sents the 9 steps to log on the computer and 1 step to log off.f
To obtain information on using BCS for an account number and password
(ID, PASSWORD), call 1-800-426-7676 and ask for EKS customer service.
(See Appendix B.)
t See Appendix D for log on/off information for the EPA COMNET system.
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TABLE 1. SOLID WASTE COVER SOIL CHARACTERISTICS* (DEFAULT)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Solid
Texture
USDA
CoS
CoSL
S
FS
LS
LFS
LVFS
SL
FSL
VFSL
L
SIL
SCL
CL
SICL
SC
SIC
C
waste
class
USCS
GW
GP
SW
SM
SM
SM
SM
SM
SM
MH
ML
ML
SC
CL
CL
CH
CH
CH
MIR
in. /hr
0.50
0.45
0.40
0.39
0.38
0.34
0.32
0.30
0.25
0.25
0.20
0.17
0.11
0.09
0.07
0.06
0.02
0.01
Porosity
vol/vol
0.351
0.376
0.389
0.371
0.330
0.401
0.390
0.442
0.458
0.511
0.521
0.535
0.453
0.582
0.588
0.572
0.592
0.680
0.526
Ksat
in./hr
11.950
7.090
6.620
5.400
2.780
1.000
0.910
0.670
0.550
0.330
0.210
0.110
0.084
0.065
0.041
0.065
0.033
0.022
0.030
AWC
vol/vol
0.067
0.087
0.133
0.122
0.101
0.540
0.086
0.123
0.131
0.117
0.156
0.199
0.119
0.127
0.149
0.078
0.123
0.115
0.156
Evap
coef .
3.3
3.3
3.3
3.3
3.4
3.3
3.4
3.8
4.5
5.0
4.5
5.0
4.7
3.9
4.2
3.6
3.8
3.5
4.5
USDA = USDA Soil Classification System, Co = coarse, C = clay,
SI = silt, S = sand, L = loam, F = fine, V = very;
USCS = Unified Soil Classification System, S = sand, M = silt,
L = low liquid limit, H = high liquid limit, W = well graded;
MIR = Minimum Infiltration Rate;
Ksat = Hydraulic Conductivity; and
AWC = Available Water Capacity.
-------
PERCENTAGE OF SAND SIZES IN SUBCLASSES OF
SAND, LOAMY SAND, AND SANDY LOAM BASIC
TEXTURAL CLASSES AS DEFINED BY THE U S
DEPARTMENT OF AGRICULTURE
SAND-20 to 005 mm DIAMETER
SILT-005 to 0.002 mm DIAMETER
CLAY-SMALLER THAN 0002 mm DIAMETER
1 S DEPARTMENT OF AGRICULTURE TEXTURAL CLASSIFICATION CHART
Basic
soil
class
I
"g
S
1
1
I
to
Subclass
Coarse sand
Sand
Fine sand
Very fine sand
Loamy coarse sand
Loamy sand
Loamy fine sand
Loamy
very fine sand
Coaise sandy loam
Sandy loam
Fine sandy loam
Very fine sandy loam
Soil separates
Very coarse
sand,
2.0-
1.0 mm
Coarse
sand,
1.0-
0.5 mm
25% or more
Medium
sand,
0.5-
0.25 mm
Less than
50%
25% or more
-or-
Less than 25%
25% or more
Less than
50%
25% or more
-or-
Less than 25%
25% or
more
Less than
50%
30% or more
Less than
25%
-or-
Between 15 and 30%
-or-
Less than 15%
Fme
sand,
0.25-
0.1 mm
Less than
50%
Less than
50%
50%
or more
Less than
50%
Less than
50%
50%
or more
Less than
50%
and-
Less than
30%
30%
or more
Very fine
sand,
0.1-
0.05 mm
Less than
50%
Less than
50%
Less than
50%
50%
or more
Less than
50%
Less than
50%
Less than
50%
50%
or more
Less than
50%
Less than
30%
Less than
30%
30%
or more
More than 40%*
* Half of fine sand and very fine sand must be very fine sand.
Figure 4. USDA classification system (12).
-------
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STEP OPERATION
1 Turn on data terminal.
2 Dial 1-800-426-7676 (if a local number is available, it is
less expensive).
3 Ask operator for: EKS1, 30 CPS data line. (Company)
4 Put telephone handle in the handset muff.
5 Wait for green light to come on (on line), then press RETURN
key.
6 The computer system types:
USER NUMBER:
You type:
ID,PASSWORD (press RETURN key).
7 The computer system types:
RECOVER/USER ID:
You type:
(your last name) (press RETURN key).
First Run:
8a The computer system types:
C>
You type:
-HYDBAT (press RETURN key), (-minus sign).
Second Run:
8b The computer system types:
C>
You type:
-HYDGO (press RETURN key).
9 At this point, the program prints a heading (see page 15) and
begins to ask questions (see page 16) for entry of site and
program operation.
10 When program is finished, the computer system types:
C>
You type:
BYE (press RETURN key) or repeat step 8b for reruns.
Figure 5. Steps to log on and off BCS.
14
-------
A worksheet is presented in Figure 6 for the entry of site and soil
characteristics data necessary to run the model. Most computer input re-
quests are self explanatory. The computer terminal that the user is operat-
ing should be set to enter information using all CAPITAL LETTERS. Initially,
the program prints a heading as shown below which details the title, name and
address of the authors, and the telephone numbers to call for information
about the program and to clarify problems if and when they arise.
STATE:
CITY:
STUDY TITLE:
AREA LOCATION:
YEARS OF INTEREST:
Surface area of solid waste site acres
Depth of soil cover inches
Depth of vegetative cover inches
Depth of barrier cover inches
Depth of solid waste inches
Solid waste site slope ft/ft
Hydrologic channel length ft
Figure 6. Default data worksheet.
15
-------
HYCFOLOGIC SIMULATION ON SOLID h'ASTE DISPCS/IL SITES
WRITTEN 5Y
EUGENE R. PERPIER AND ANTHONY C. GIBSON
OF THE
ft'ATE? RESOURCES ENGINEERING GROUP
ENVIRONMENTAL LABORATORY
USAE, WATERWAYS EXPERIMENT STATION
D.0. 30A 631
VICKSBURS, MS 39180
* *
* USER'S MANUAL AVAILABLE UPON RF.QUEST *
* FOR CONSULTATION CONTACT AUTHORS AT *
* (64)1) 634-371^ *
i'f * * # # * * * * * * * * * * )'f * * * * * * * * * * * * * $ * # * * * * * * * # * * >;« * * ;jt * % >'f jjc * * * * »jc * * * * * * ** * * &
>'f >;< ;|c * ^ i'f * * sjc s|s j|c * i'f >;s * j^ * * 5^ * * >'f * * * * # ;X * * * * * * * * * * * * ************ * * * * * * * * * * * * * *
Example. The following example illustrates the interaction that occurs
between the program and the user to obtain 5 years of default data for Los
Angeles, California. To use default data, it must be a city given in Table
2. After the heading, the computer will ask:
DO YOU WANT TO USE DEFAULT CLIMATOLOGIC AND HYDPOLOGIC DATA?
ENTER YES OR NO
I>YES
The computer will type a table of the cities and states from which the clitna-
tological default data is available.
ENTER NAME OF STATE OF INTEREST
I>CALI?ORNIA
ENTER NAME OF CITY OF INTEREST
I)LOS ANGELES
16
-------
CLIMATOLOGICAL DATA WILL BE ENTEPED
TYPE BYS AND WAIT AT LEAST 30 MINUTES
Note: the user must enter a word or value for each input prompt I> and after
the word or value has been entered the user must press the RETURN key.* In
the event an error was committed when typing CAILFORNIA, press and hold the
CONTROL (CTRL) key, and press the H key 8 times (8 backspaces).t Then type
LIFORNIA to correct the spelling, and press the RETURN key as shown.
ENTER NAME OF STATE OF INTEREST
H-'CAILCFORNIA
To correct an entire line error, the user may press the BREAK key and
the computer will type *DEL*. Then the user should type in the correct
message as shown.
ENTEE NAME OF CITY OF INTEREST
I>LOO ANGELES *DEL*
LOS ANGELES
The first run of the computer program (using 8a) calls the tape from
which the cities and states climatological data is stored. This step
* COMNET does not use input prompts.
t Some computer terminals use a different backspace command.
17
-------
requires a waiting period of at least 30 minutes for operators to mount the
climatological tape on a tape drive and for the computer to execute the
initial program.
After the 30-minute waiting period, the second run requires the user to
repeat steps 1 through 7 in Figure 5; however, step 8a is not repeated; in-
stead step 8b is performed. With this process, default climatological data
have been put on a permanent file for the specific city/state requested by
the user. Thus, countless runs can be made by using steps 1-7 and step 8b
without recalling step 8a.
After the program retrieves the climatological data on precipitation,
solar radiation, and leaf area index (LAI) for the city requested, the pro-
gram reprints the heading (page 16) and asks the following questions.
ARE YOU USING DEFAULT
ENTER YES OB NO
I>YES
CLIMATCLOGICAL DATA?
CLIMATOLOGICAL DATA FROM LOS ANGELES CALIFORNIA ABE ON FILE.
Because the climatological data are already on file, when the prompt I>
is printed for the second question, the user types a 2 for the hydrological
input.
DO YOU WANT CLIMATOLOGY, HYDROLOGY OR OUTPUT?
ENTER 1 FOP CLIMATOLOGICAL INPUT,
2 FOP HYDROLOGICAL INPUT,
3 FOR OUTPUT OR
4 TO STOP PROGBAM .
The program queries the following for the user's information only and this
information is printed twice in the output for the user's interest only. The
study title could include site and vegetation information.
ENTF.P TITLE ON LINF 1,
LOCATION OF SOLID WASTE SITE ON LINE 2
AND TODAY'S DATE ON LINE 3.
OHYDROLOGY OF A SOLID WASTE DISPOSAL
nLOS ANGELES, CALIFORNIA — 10 MILES
I> 12 JUNE 1980
SITE (EXAMPLE 1)
NORTH OF DOWTQlJLN
18
-------
At this point, the user has the option of designing the final cover soil
with a vegetative and a barrier layer or with a uniform cover soil. If the
user desires a two-layered system, the following commands are answered.
DO YOU HAVE A LAYERED SOIL COVER?
(ONLY 2 LAYERS PERMITTED VEGETATIVE PLUS
ENTER YES OR NO
BARRIER)
I>YES
ENTER TOTAL DEPTH OF SOIL COVER
(VEGETATIVE PLUS BARRIER)
(INCHES
I>36
Now the user must select the general texture class of vegetative soil cover.
This enables the user to select one of the values that are shown in Table 1.
The vegetative soil cover is assumed to be spread as uniformly as possible by
depth and surface roughness. If a vegetative cover of a grass or row crop is
assumed, then the appropriate cultivation and seedbed preparation is also
accomplished.
ENTER SOIL TEXTURE OF VEGETATIVE SOIL COVER
SELECT THE TEXTURE CLASS OR GROUP SYMBOL OF SOIL MATERIAL
ENTER NUMBER
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(16)
(17)
(18)
COARSE
COARSE
LOAMY
LOAMY VERY
FINE
VERY FINE
SANDY
SILTY
SANDY
FINE
LOAMY
FINE
FINE
SANDY
SANDY
SANDY
SILT
CLAY
CLAY
CLAY
SANDY
SILTY
SAND
LOAM
SAND
SAND
SAND
SAND
SAND
LOAM
LOAM
LOAM
LOAM
LOAM
LOAM
LOAM
LOAM
CLAY
CLAY
CLAY
3W
GM
SW
SM
SM
SM
SM
SM
SM
MH
ML
ML
SC
CL
CL
CH
CR
CH
19
-------
The user must enter the depth of the barrier soil (inches), the texture
of the soil material, and answer as to whether or not the barrier soil was
compacted. If the barrier soil was compacted, the values of hydraulic con-
ductivity are reduced by a factor of 20, and the values of available water
capacity and porosity are halved.
ENTER DEPTH OF EASIER SOIL .INCHES)
IX12
ENTER SOIL TEXTURE OF BARPIER SOIL COVER
SELECT THE TEXTURE CLASS OP GROUP SYMBOL OF SOIL MATERIAL
ENTER NUMBEP
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(16)
(17)
(18)
C
COARSE
LOAMY
LOAMY VE^Y
FINE
VERY FINE
SANDY
SILTY
OARSE
SANDY
FINE
LOAMY
FINE
FINE
SANDY
SANDY
SANDY
SILT
CLAY
CLAY
CLAY
SANDY
SILTY
SAND
LOAM
SAND
SAND
SAND
SAND
SAND
LOAM
LOAM
LOAM
LOAM
LOAM
LOAM
LOAM
LOAM
CLAY
CLAY
CLAY
Stf
GM
^W
SM
SM
SM
SM
SM
SM
MF
ML
ML
SC
CL
CL
CH
CE
CH
IM4
LID YOU COMPACT THE
ENTER YES OR NO
SOIL?
I>YES
20
-------
If the user does not request a layered final cover soil, the user must
select the soil texture and enter the depth of the soil cover (inches). The
computer now responds with:
SELECT THE TYPE OF VEGETATIVE COVER
ENTER NUMBEB (l) BARE&ROUND
(2) GRASS (EXCELLENT)
(3) GRASS (GOOD)
(4) GRASS (FAIR)
(5) GRASS (POOR)
(6) ROW CROP (GOOD)
(7) ROW CROP (FAIR)
An explanation of some of the terms may be in order (for further expla-
nation see Appendix C). For example grass (excellent) implies that the soil
cover will be planted with a grass which has excellent production. This
assumes that the vegetative cover is well managed; that is, fertilizer, weed
control, and harvest (no grazing) are maintained to maximum production. Ob-
viously, this is the best type of vegetative cover available but, realisti-
cally, is difficult to achieve. Row crop assumes some type of cultivation
will be maintained throughout the season, and it is assumed the crop will
produce well. It should be remembered that loam is the ideal soil texture to
maximize vegetative production and that soil textures either side of loam
will lower production. Of course, good management may circumvent some of the
production loss, but a clay or sand cannot maintain even a fair grass cover
without management difficulties.
The user now enters 2 values of characteristics of the solid waste site
at each input prompt, I>. It must be remembered that the program uses only
English units such as acres, feet, and inches.
ENTER 2 VALUES, SURFACE AREA OF SOLID WASTE SITE(ACRES)
AND DEPTH OF SOLID WASTE (INCHES).
I>180
As shown in Figure 2, some solid waste sites may be designed with some
type of an "impermeable liner" separating the final cover soil material from
the waste cells (6). However, as most "impermeable liners" age and eventu-
ally deteriorate, due to known and unknown causes, the power law was used for
functional age relations as shown in Figure 7. The indefinite life of a
liner was limited to 100 years. The computer asks the following questions:
21
-------
0.001
1.0
10.
100. 1,000
EFFECTIVE LIFE, DAYS
10,000
100,000
Figure 7. Power law relations used to estimate the effective aging
of an impermeable liner.
IS THEP.E AN IMPERMEABLE LINER AT THE INTERFACE?
ENTER YES OR NO
I>YES
WHAT IS THE EXPECTED LIFE OF THE LINER?
ENTER 0 FOP FIVE YEARS,
1 FOR TEN YEARS,
2 FOR FIFTEEN YEARS,
3 FOR TWENTY YEARS OR
4 FOP INDEFINITE LIFE.
22
-------
With the above answers to the prompt commands, initially, the flow of water
through the "impermeable liner" is totally impeded. But, as a function of
time, the volume of water percolating through the soil cover increases and in
five years the "impermeable liner" has no effect on the volume of water per-
colating into and through the solid waste. However, with proper management,
some of the problem may be alleviated; that is, the vegetative cover may have
established an excellent grass cover and the amount of deep percolation would
be controlled by the increased evapotranspiration demand.
At this point, and if there was no "impermeable liner," the user enters
the site slope (ft/ft) and the site channel length (ft). The site slope
(ft/ft) is the length of slope divided by the relative relief (difference be-
tween high and low elevations along the slope). The decimal fraction should
be entered in the program. For example, a slope 3000 ft long with a 30 ft
change in elevation would give a site slope ratio of 0.010 to be entered in
the program. The hydrologic or site channel length is determined from the
overland flow outlet along the main flow path to the most distant point on
the upper site boundary (see Figure 1).
ENTER 2 VALUES, SITE SLOPE (FT/FT),
AND SITE CHANNEL LENGTH(FT)
I>.022
The hydrologic or site channel length and the area (acres) of the solid waste
site are used to determine the rectangular shape of the site. Thus, for sim-
ulation purposes the surface geometry of the site is in the simplistic form
of a rectangle whose length is the site channel length.
Now all of the necessary data inputs have been entered for climatology
and hydrology when using the default mode and the user is ready for output.
However, the user still must specify the number of years of output and
whether or not daily or annual summaries are required. As output for both
the default and input options are the same, the discussion of output will
follow the section on input data files.
INPUT DATA FILES
When default data are not used, the worksheets for input data, as shown
in Figure 8, are required. At this time, there is no method available to use
only part of the default data and then override specific default parameters
with better input data; however, at some future date this option will be
available. The most difficult part of this aspect of the model operation is
to input the precipitation data. Daily precipitation data are available from
local libraries or from the National Weather Service* climatological data
Director, National Climatic Center, NOAA, Federal Building,
Asheville, N.C. 28801
23
-------
records. When the precipitation data are to be input, if the entire field of
ten (10) values is zero (0), only one zero needs to be entered before the
RETURN is pressed (right justified). If you have a line partially filled
with precipitation data and the remainder is to be filled with zeros, after
typing the precipitation data only a RETURN is required. Each year requires
10 values per line and 37 lines of input. The model, as written, will only
accept a minimum of 2 years and a maximum of 5 years of precipitation data.
For best results, at least 5 years of precipitation data should be used.
When the user enters the program, the following commands are given to
input the data files.
ARE YOU USING DEFAULT CLIMATOLOGICAL DATA?
ENTER YES OP NO
I>NC
DO YOU WAMT CLIMATOLOGY, HYrPOLOGY O15 OUTPUT?
ENTEP I FOP CLIMATOLOGICAL INPUT,
2 FOR HYDPOLOGICAL INPUT,
3 FOP OUTPUT Op
4 TO STOP PROGRAM.
USE ONLY ENGLISH UNITS OF ACPIS ,1 N CHES , AND DAYS
UNLESS OTHERWISE INDICATED
ALL
* # >;« >;< s[e >!c >;« <« sj: >;< >^ >;< >;« * s;« ^t >|< >;e >;t sjc * sje j;c sis
A VALUE **MUST** BE ENTEPED FOR EACH COMMAND
DO YOU WANT TO ENTER PRECIPITATION DATA?
ANSWER YES OR NO
I>YES
##############*############## NOT ICE ####################*########
PRECIPITATION INPUT WILL ACCEPT ONLY **FIVE** (5) YEAPS MAXIMUM
AND ONLY *#TWO** (2) YEARS MINIMUM
24
-------
The climatological module input data includes the precipitation, mean monthly
temperature and solar radiation, and the growth characteristics of the vege-
tative cover in terms of the LAI. The hydrologic module input data include
site, soil-water, and evaporation characteristics. The output module prints
tables of the input and simulated data.
Mean monthly air temperature and mean monthly solar radiation (insola-
tion) data are required inputs (12 values each) which are used to compute the
daily evapotranspiration. Temperature data are regularly published by the
National Weather Service. Solar radiation data in Langleys/day can be ob-
tained from the Climatic Atlas of the United States* or from Table 2 for
specific locations. For each year of input, the following commands are
printed, and for this example the year of the data to be input is 74.
ENTER DAILY RAINFALL .
ENTER YEAR OF RAINFALL (EXAMPLE 76)
OR ZERO (0) TO END RAINFALL INPUT.
**********#*** ******************#***##*##*# ##i!c#j>c$i}:s[:*#**#s!e ****** *s;«sj
a****************************************************************:;:
WHEN PRECIPITATION DATA ARE TO BE INPUT,
IF THE ENTIRE FIELD OF TEN (10) VALUES
ARE ZERO (0) ONLY ONE NEED BE ENTERED
BEFORE CARRIAGE RETURN (RIGHT JUSTIFIED)
IF YOU HAVE A LINE PARTIALLY FILLED VITH
PRECIPITATION DATA AND THE REMAINDER IS TO
BE FILLED WITH ZEROS #ONLY* A CARRIAGE
RETURN IS REQUIRED
**************** ********************************#***##********##*>;<
******************************************* ***********************
* U. S. Dept. of Commerce, 1968, "Climatic Atlas of the United States,"
U. S. Govt. Printing Office, Washington, D. C.
25
-------
CLIMATOLOGIC INPUT
DAILY PRECIPITATION (INCHES)
1 YEAR (10 VALUES/LINE, 37 LINES)
YEAR:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
(continued)
Figure 8. Data input requirements (no defaults)
26
-------
YEAR:
Figure 8. (continued)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
(continued)
27
-------
Figure 8. (continued)
Mean Monthly Mean Monthly
Temperature Insolation
Month (°F) (Langleys/Day)
January
February
March
Ap r i 1
May
June
July
August
September
October
November
December
Leaf Area Index Values
Day Area
1
366
(continued)
28
-------
Figure 8. (concluded)
Hydrological Input
Study Title:
Area Location:
Today's Date:
Date of first storm event (Julian date)
(example = 73038, 1973 and 38 Julian day)
Surface area of solid waste site
Hydraulic conductivity of vegetative soil .
Hydraulic conductivity of barrier soil . .
Depth of soil cover
Depth of vegetative layer
Depth of barrier layer
Depth of solid waste
Soil porosity of vegetative soil
Soil porosity of barrier soil
SCS curve number
Channel slope
Hydrologic channel length
Available water capacity of vegetative soil
Available water capacity of barrier soil
Winter cover factor
Evaporation coefficient of vegetative soil
Evaporation coefficient of barrier soil . .
_acres
in./hr
in./hr
Cinches
inches
inches
inches
jvol/vol
vol/vol
_ft/ft
ft
_vol/vol
vol/vol
29
-------
At this point, 37 lines of data, with 10 values per line, are entered in the
following manner:
ENTEP RAINFALL DATA OF 10 VALUES PER LINE
WITH 37 LINES PER YEAE.
ENTER LINE 1
I>.04 0 .25 1.7 .47 1.07 1.67 .06 .02
ENTEP LINE 2
i>0 0 tf 0 e .11 .1 0 k? .11
ENTER LINE 3
ENTEP LINE 4
I>0 0 0 .05
ENTEP LINE 5
I>0 .04 0 0 0 .85 .26
ENTER LINE 6
I>1.0 .04 000 .85 .06
ENTEP LINE 7
ENTER LINE 8
I>0 0 0 0 .01 .26 0 0 .02
ENTER LINE 9
I>.12 .02 0 .01
ENTEP LINE 10
After each year's entry, the heading is printed; however, when all the
precipitation data have been entered (2 year minimum and 5 year maximum), a
zero is entered at the prompt I> and all input data previously entered are
printed so that the user can detect and change any input errors.
30
-------
ENTER LINE 35
I>0 0 0 0 0 .1
ENTER LINE 36
ENTER LINE 37
I>.99 .99 .99 .99 .99
ENTER DAILY RAINFALL .
ENTER YEAR OE RAINEALL (EXAMPLE 76)
OR ZERO (0) TO END RAINFALL INPUT.
If an error has been made, as in the example (year 74 and on line 37)
where five 0.99's were incorrectly entered, the following questions would
have to be answered and the corrected precipitation values entered:
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 21
74 £.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22
74 0.00 0.00 0.00 0.00 0.00 0.0? 0.00 0.00 0.00 0.20 23
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 24
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 0.00 25
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 26
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 27
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 28
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 29
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 0.00 0.00 30
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 31
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 32
74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 0.00 33
74 0.00 0.00 0.00 0.00 2.00 0.00 0.00 0.00 0.00 0.00 34
74 0.00 0.00 0.00 0.00 0.00 .10 0.00 0.00 0.00 0.00 35
74 0.00 0.00 0.00 0.00 9..00 0.00 0.00 0.00 0.00 0.00 36
74 .99 .99 .99 .99 .99 0.00 0.00 0.00 0.00 0.00 37
31
-------
APE THESE VALUES CORRECT?
DO YOU WANT TO USE THEM?
ANSWER YES OR NO
I>NO
ENTER YEAR OF INTEREST
ENTER LINE OF INTEREST
I>37
ENTER 10 CORRECTED PRECIPITATION VALUES
I>0 0 i3 0 .01
ARE THERE ANY MORE ERRORS?
ANSWER YES OR NO
I>NO
The precipitation tables are reprinted and the question as to their correct-
ness is asked before proceeding to the entry of mean monthly temperature
data .
After the entry of data files for daily precipitation, mean monthly tem-
perature, mean monthly solar radiation, and LAI (see Figure 8), the program
reprints the input data and asks, "Do you want to change them?". The user
has the option of changing any of the data entered before advancing to the
next data entry. The following commands are used to enter mean monthly
temperature data:
32
-------
DO YOU WANT TO ENTEF TEMPERATURE DATA?
ANSWER YES OR NO
I>YES
ENTFE 6 TEMPERATURE VALUES
JAN.-JUNE (DEGREES F.)
I>62.7
IN61
I>68.7
I>59.6
I>69.1
I>70.7
ENTER 6 TEMPERATURE VALUES
JULY-DEC. (DEGREES F.)
I>66.9
I>70.0
I>78.5
I>57.5
I>52.6
THESE ARE TFE INPUT TEMPERATURES VALUES
JAN. -JUNE JULY-PEC.
62.7
61.0
68.7
59.6
69.1
70 .7
66.9
70.0
78.5
71.4
57.5
52 .6
DO YOU WANT TO CHANGE THEM?
ENTER YES OR NO
I>NO
33
-------
To enter solar radiation (13) data, the following commands are used (the
city of Los Angeles, California, is the example):
DO YOU WANT TO ENTEP SOLAR RADIATION DATA?
ANSWER YES OR NO
I>YES
ENTER 6 SOLAR RADIATION VALUES
JAN.-JUNE (LANGLFYS/DAY)
I>248
I>331
I>397
I>457
I>486
ENTER 6 SOLAR RADIATION VALUES
JULY-DEC. (LANGLEYS/DAY)
I>497
I>464
I>389
I>320
I>2?7
I>221
THESE ARE THE INPUT RADIATION VALUES
JAN.-JUNE JULY-DEC.
248.0
331.0
397.0
457.0
506.0
486.0
497.0
464.0
389.0
320.0
277.0
221.0
DO YOU WANT TO CHANGE THEM?
ENTER YES OR NO
I>NO
34
-------
The LAI is used to estimate the amount of vegetative ground cover of a
particular crop and is an effective partition of the plant transpiration to
soil evaporation ratio which is used in both model options. For example, a
conceptual understanding of LAI is made by considering a one square foot area
of a soil surface with no vegetation (bare ground) on the 5th of January.
However, 100 days later on the 15th of April, vegetation has grown on the
example area. When viewing this area from above, the veget ition now covers
50 percent of the surface area which gives an LAI value of 1.50. Table 3
gives some leaf area index distributions for normalized times through a grow-
ing season for several crops. These values must be apportioned between
actual local planting and harvesting dates.* Points for day = 1 and day =
366 are necessary for model operation. There must be exactly 13 LAI values
entered for a specific vegetative ground cover. The program interpolates be-
tween the LAI values for daily estimates.
TABLE 3. TYPICAL LEAF AREA INDEX DISTRIBUTIONS FOR VARIOUS
VEGETATIVE COVERS (9)
Portion of
growing
season
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Corn
0.00
0.09
0.19
0.23
0.49
1.16
2.97
3.00
2.72
1.83
0.00
Oats
0.00
0.42
0.84
0.90
0.90
0.98
2.62
3.00
3.00
3.00
0.00
LAI**
Wheat
0.00
0.47
0.90
0.90
0.90
0.90
1.62
3.00
3.00
0.96
0.00
Grasst
0.00
1.84
3.00
3.00
3.00
3.00
3.00
2.70
1.96
0.96
0.50
Soybeans
0.00
0.15
0.40
2.18
2.97
3.00
2.96
2.92
2.30
1.15
0.50
Good production assumed for all crops.
production.
LAI should be lowered for poor
f No grazing assumed. LAI must be lowered if grazed or not managed.
USDA, 1941, "Climate and Man, Yearbook of Agriculture," U. S. Govt.
Printing Office, Washington, D. C.
35
-------
To enter the data in the model, the following approach is required:
DOES THE SOIL SURFACE HAVE VEGETATION?
ENTER YES OR NO
I>YES
DO YOU ¥ANT TO ENTER LEAF AREA INDEX DATA?
ANSWER YES OR NO
I>YES
The condition for bare ground is entered automatically if no vegetation
is to be required. Some of the input and inspection of the input follows.
ENTER TWO VALUES,
ONE FOR DAY OF MEASUREMENT JULIAN DAY)
AND ONE FOR LEAF AREA INDEX.
(EXAMPLE, 100 1.65)
36
-------
I>1 0
ENTER ANOTHER SET OF VALUES
0
ENTER ANOTHEP SET OF VALUES
I>59 .61
ENTEP ANOTHER SET OF VALUES
I>77 1
ENTER ANOTHER SET OF VALUES
I>95 1
ENTEP ANOTHER SET OF VALUES
I>113 1
ENTEP ANOTHER SET OF VALUES
I>131 1
INTER ANOTHER SET OF VALUES
I>149 1
ENTEP ANOTHER SET OF VALUES
I>167 .9
ENTER ANOTHER SET OF VALUES
I>185 .71
ANOTHER SET OF VALUES
I>203 .65
ENTE? ANOTHER SET OF VALUES
I>221 0
ENTER ANOTHER SET OF VALUES
I>366 0
37
-------
THESE ARE THE DAYS AND LAI VALUES INPUT
DAYS LAI
1 0.00
41 0.00
59 .61
77 1.00
95 1.00
113 1.00
131 1.00
149 1.00
167 .90
185 .71
203 .65
221 0.00
366 0.00
DO YOU WANT TO CHANGE THEM?
ENTER YES OR NO
I>NO
CLIMATOLOGICAL INPUT IS COMPLETE
*$***#*###*###*#####*# *#######*$#*>jc#######^
At this point, the user can Make appropriate corrections to the data set if
so required. It should be remembered that 13 LAI values must be entered, no
more — no less.
This completes the entry of data into the climatological module and data
are now to be input into the hydrological module as requested.
DO YOU WANT CLIMATOLOGY, HYDROLOGY OR OUTPUT?
ENTER 1 FOR CLIMATOLOGICAL INPUT,
2 FOR HYDROLOGICAL INPUT,
3 FOR OUTPUT OR
4 TO STOP PROGRAM.
The program user now enters the study title, site location, and today's date.
This information is used for table headings in the output only and is not
used in the model operations.
38
-------
ENTEP TITLE ON LINF 1,
LOCATION OF SOLID WASTE SITE ON LINE 2
AND TODAY'S DATE ON LINE 3.
I>HYDROLOWLJOiF A SOLID WASTE DISPOSAL,^ ITJL.IEXAMPLE 1}
INLOS ANGELES., CALIFOPMIA — 10 MILES NORTH OF DOWN TOWN
I>18 A^RIL 1980
The user must now enter the year and Julian date of the day before the
first storm event. Thus, if the first year's data are only a partial data
set with, say, the first 138 days set to zero for 1973 data, this entry would
follow as 73138. But, for the Los Angeles data set, it rained on 1 January
1974, and the entry appears as:
ENTEP YEAP AND DATF OF FIRST STORM .EVENT (JULIAN DATE/
-(EXAMPLE = 73138, 1973 AND 138 JULIAN DAY)
I>74000
If the soil cover has a vegetative layer plus a barrier layer, then this
information is entered here:
DO YOU HAVE A LAYERED SOIL COVER?
(ONLY 2 LAYERS PERMITTED VEGETATIVE PLUS BARRIER)
ENTSP YES OR NO
I>YES
ENTER TOTAL DEPTH OF SOIL COVER (INCHES)
(VEGETATIVE PLUS BARRIER)
I>36
39
-------
ENTER VALUES FOR VEGETATIVE SOIL COVEP
ENTEE 4 VALUES, HYDRAULIC CONDUCTIVITY, (IN/ER)
SOIL POROSITY, (VOL/VOL)
EVAPORATION COEFFICIENT AND
AVAILABLE WATER CAPACITY (VOL/VOL)
1X51
I>.41
I>4.5
I>.13
ENTEP DEPTH OF BARRIER SOIL (INCHES)
ENTER VALUES FOR BAPRIER SOIL COVER
ENTER 4 VALUES, HYDRAULIC CONDUCTIVITY, (IN/HR)
SOIL POROSITY, (VOL/VOL)
EVAPORATION COEFFICIENT AND
AVAILABLE '*ATER CAPACITY (VOL/VOL)
I>.004
I>.29
I>.064
The effective hydraulic conductivity (14,15) of the vegetative and barrier
soil must be entered at this point. Experiments and theory suggest that ap-
proximations of the variation of this parameter can also be related to soil
conditions (9). Thus, the relative value entered for the effective hydraulic
conductivity should reflect the conditions of the cover materials. If com-
paction of the barrier soil is requested, then its effect on the hydraulic
conductivity should be estimated. The actual value of the hydraulic conduc-
tivity to reproduce the same runoff as predicted by the SCS curve number
method (16) depends to a large extent on the storm depth and duration. Thus,
for daily values, the hydraulic conductivity is moderately sensitive and the
quality of the input is generally only fair to good. Should measured values
from laboratory or field data be available, they can be used to develop
better parameter estimates.
The soil porosity is usually half water and half air. When a soil is
totally saturated, the volume of water to volume of solid material (mineral
40
-------
plus organic matter) is the porosity. The total pore space for soils is be-
tween 0.50 to 0.60, being somewhat less for sandy soils and somewhat greater
for loamy soils with high contents of organic matter.
The SCS curve number technique is the method used for predicting runoff
from daily rainfall. Figure 9 shows a graphical example of estimating the
curve number from the minimum infiltration rate (MIR) if not known from other
sources. The evaporation coefficient (9) is a cover soil evaporation param-
eter dependent on soil water transmission characteristics and is used to
1/2
fraction the evapotranspiration (ranges from about 3.3 to 5.5 mm/d ). It
is suggested that a value of 4.5 be used for loamy soils, 3.5 for clays, and
3.3 for sands; however, it cannot be less than 3.0. The available water
capacity, AWC, was previously discussed in conjunction with Figure 3.
The surface area of the solid waste site, channel slope, and hydrologic
channel length should be measured from a map or design plan, when available.
The hydrologic channel length is determined by measuring the distance from
the solid waste site surface outlet along the main flow path to the most dis-
tant point on the solid waste site boundary.
ENTEP 2 VALUES, SURFACE AREA OF SOLID WASTE SITE (ACRES),
AND DEPTH OF SOLID WASTE (INCHES).
I>180
The next question the program asks is whether or not an "impermeable
liner" was used. The discussion of the usage of an "impermeable liner" was
presented under the default data option and will not be repeated at this
point.
IS THERE AN IMPERMEABLE LINE? AT THE INTEPFACE?
ENTER YES OR NO
I>NO
ENTER 3 VALUES, SCS CURVE NUMBER,
CHANNEL SLOPE AND
HYDROLOGIC SLOPE LENGTH (FT).
I>79.3
I>.022
I>541
41
-------
100 r-
BAREGROUND
ROW CROP (FAIR)
GRASS (POOR)
CO
cc
LJU
CO
uu
>
cc
D
o
0
MIR, IN/HR
Figure 9. SCS curve number for several vegetative covers
in relation to the minimum infiltration rate (MIR)
Lutton et al. (6) have presented an excellent review of the SCS curve number
technique with graphs and tables for estimating runoff curve numbers for a
wide variety of soil and moisture conditions.
The winter cover factor is used to reduce soil evaporation as a result
of ground cover, for example, dormant grass or a heavy crop residue (mulch).
The value of the winter cover factor usually varies from 0.5 for an excellent
grass cover to 1.0 for bare ground or harvested row crop (9). The value must
be estimated for each type of vegetative cover.
42
-------
ENTER WINTER COVER FACTOR
OUTPUT
If 5 years of climatological data are input, the printing of the output
starts with the first year entered. For example, if climatological data were
entered for 1974, 1975, 1976, 1977, and 1978, but only 2 years of printed
output were requested, the program would print only the 1974 and 1975 data
sets. At this time, the consecutive output dates cannot be user specified.
In addition, the user input or default data files, once entered, will remain
on line indefinitely or until the user changes the files or terminates the
program. The output for both the default and input data options are the
same, and the questions about output follow:
DO YOU WANT CLIMATOLOGY, HYDROLOGY OP OUTPUT?
ENTER 1 FOR CLIMATOLOGICAL INPUT,
2 FOR HYDROLOGICAL INPUT,
3 FOR OUTPUT OP
4 TO STOP PROGRAM.
HOW MANY YEARS OF OUTPUT DO YOU WANT?
TWO (2) YEARS MINIMUM AND
FIVE (5) YEARS OF PRECIPITATION APE MAXIMUM
DO YOU WANT DAILY PRECIPITATION OUTPUT?
(NO PRINTS THE ANNUAL SUMMARIES)
ANSWER YES OR NO
I>YES
Hydrologic output is composed of input information and calculated
values. Daily and annual summaries of simulated output data are available
for both options. Output for the simulation period includes monthly totals,
means of rainfall, runoff, evapotranspiration, drainage, and average soil-
water content. The data include annual totals for each component.
43
-------
For the hydrologic output, first the program prints the title of the
project, the location, and current date of the run. Then for reference pur-
poses, the program prints the input values. The input of the climatological
module is printed first and then the input of the hydrological module.
LAI-DAYS is an indicator of the potential growth index. It is obtained by
integrating the LAI versus time (days) data and is used to check the model
EYDROLOGIC OUTPUT
(DAILY PRECIPITATION VALUES)
HYDROLOGY OF A SOLID WASTE DISPOSAL SITE (EXAPLE 1)
LOS ANGELES, CALIFORNIA — 10 MILES NOPTH OF DOWNTOWN
18 APRIL 1980
MONTHLY MEAN TEMPERATURES, DEGREES FASRENEEIT
JAN/JUL FE3/AUG MAR/SEP APR/OCT MAY/NOV JUN/DFC
59.33 59.71 61.71 64.7B 68.10 70.79
72.12 71.74 69.74 66.67 63.35 60.66
MONTHLY MEAN RADIATION, LANGLEYS PEP. DAY
JAN/JUL FEB/AUG MAR/SEP APR/OCT MAY/NOV JUN/DEC
265.39 315.13 382.99 450.79 500.36 518.41
500.11 450.37 382.51 314.71 265.14 247.09
LEAF AREA INDEX TABLE
DATE LAI
1 0.00
41 0.00
59 .61
77 1.00
95 1.00
113 1.00
131 1.00
149 1.00
167 .90
185 .71
203 .65
221 0.00
366 0.00
44
-------
WINTER C FACTOR = .60
LAI-DAYS = 141.66
SOLID WASTE AREA = 6.00000 ACRES
EFFECTIVE EYBRA'.TLIC COND SOIL = .51020 IN/HB
EFFECTIVE HYDRAULIC COND BARRIER = .F04P0 IN/HR
EIE.LD CAPACITY = .52500 VOL/VOL
CHANNEL SLOPE = .02200 FT/FT
SCS CURV7 NUMBER = 79.30000
SITE CHANNEL LENGTH = 541.00000 FT
UPPER LIMIT OF STORAGE = 2.4S200 IN
INITIAL SOIL WATER STORAGE = 1.74602 IN
UPPER LIMIT OF STORAGES IN COVER (INCHES)
EIPTF 1.000 6.000 12.300 18.00e 24.00C1 30.000 36.
.130 .650 .780 .78? .384 .384 .384
INITIAL SOIL WATER STORAGE IN COVER (INCHES)
TEPTE 1.000 6.000 12.000 18.000 24.000 T0.000 36.U0e
.065 .325 ,390 .3£0 .192 .192 .182
An example of daily output is given which shows the amount of water that
percolated through a vegetative soil cover of a fine sandy loam soil, 7, and
a barrier soil of clay loam texture, 12, which had been compacted. However,
no "impermeable liner" was used so that all the water that infiltrated and
percolated to the interface of the final soil cover and solid waste material
drained into and out of the solid waste material (waste drain).
45
-------
DATE RAINFALL
JULIAN INCHES
?8004
78005
7800?
78010
78011
78015
78016
78017
78018
78020
78037
78038
78039
78040
78041
78042
78044
78045
78058
78059
^8060
78061
78062
78063
78064
78065
78069
78071
78081
78382
78090
78091
78095
78097
78106
78116
78248
78249
78294
78315
78316
78318
78326
78327
78335
78351
76352
78353
78354
.21
.76
1.02
1.45
1.09
1.51
.13
1.09
.02
.20
1.42
.05
.89
.70
.92
.32
.i*>
.23
.20
.07
1.61
1.48
.42
.19
2.27
.02
.13
.04
.06
.58
.28
.28
.23
.27
.69
.04
.03'
.36
.04
.10
.26
.32
.40
.12
.01
.06
.10
.61
.05
RUNOF*
INCHES
0.00
.23
.78
1.07
1.02
.90
.06
.87
0.00
0.00
0.00
0.00
.55
.60
.65
.72
.31
.12
0.00
0.00
.03
1.18
.28
0.00
1.93
0.00
0.00
0.02
0.B0
0.00
0.00
0.00
0.00
0.00
0.00
-0.00
0.00
0.00
0.00
0.00
0.00
-------
Daily output is printed only for days when precipitation occurred. The
runoff is the predicted overland flow. The cover drainage is only that which
flows out of the cover and does not percolate into the waste drainage. The
average temperature, is that predicted by the model and the accumulative
evapotranspiration carries through the model and keeps track of the potential
evapotranspiration and the available water capacity. The average soil water
is the fractional water content (volume basis) of the final soil cover. This
is an average of each of seven soil storages permitted by the CREAMS model
for the final soil cover. The CREAMS model (9) permits the top storage depth
to equal 1/36 of the final soil cover depth, 2nd storage depth to equal 5/36
of the final soil cover depth, and the other storage depths to equal 1/6 of
the final soil cover depth. For example, if the final soil cover had a depth
of 24 inches, then the 7 depths for computational purposes would be 0.67,
3.33, 4, 4, 4, 4, 4 inches, respectively. The program apportions these frac-
tions which are printed in the initial input data along with the depth
considered .
The annual totals for the particular year in question is then printed
and the water budget balance is presented (should be about zero) which shows
whether or not the parameters were properly computed and time changes
correctly evaluated.
ANNUAL TOTALS FOR 1979
PRECIPITATION *=
PREDICTED RUNOFF =
TOT SOIL DRAIN =
TOT WASTE DRAIN =
TOTAL ET =
BEGIN SOIL WATER =
FINAL SOIL WATER =
WATER BUDGET BAL. -
(INCHES)
24.58
11.30
.3462
8550
58
1
11
2.51
2.01
0.00
Next, the average annual values are printed for a quick glimpse at the
model output, in this case, 5-year averages.
AVERAGE ANNUAL VALUES (INCHES)
PRECIPITATION * 13.52
PREDICTED RUNOFF = 3.67
TOT SOIL DRAIN = .4539
TOT WASTE DRAIN « .5641
TOTAL ET * 8.68
For the second phase of the data output, the heading is reprinted and
monthly averages for each year and for monthly annual averages are printed as
shown for 1978 and 5-year annual averages.
47
-------
1978
MONTE
JAN
FEE
MAP
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
RAIN
7.48
6.05
7.08
1.51
0.00
0.00
0.00
0.00
.39
.04
1.20
.83
PUNOFF
4.93
2.96
3.41
0.00
0.00
0.00
0.00
0.00
0 .00
0.00
0.00
0.00
ET
2.17
2.42
3.73
1.71
0.00
0.00
0.00
0.00
.39
.04
.59
.53
SOIL
DRAIN
.1048
.1609
.0306
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
WASTE
DRAIN
.4997
.8696
.4857
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
AVG SW
2.16
1.73
1.19
.06
0.00
0 .00
0.00
0.00
.06
.00
.31
.71
TOT/AVE
24.58
11.30
11.58
.35
1.36
.52
48
-------
ANNUAL AVERAGES
MONTH
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
TOT/AVE
RAIN
3.30
2.36
2.92
.63
.52
.06
.00
.50
.45
.46
.42
1.88
13.52
RUNOFF
1.98
.69
.68
0.00
.00
0.00
0.00
.02
0.00
.01
0.00
.29
3.67
ET
1.32
1.57
2.57
.71
.52
.06
.00
.27
.36
.32
.39
.55
SOIL
DRAIN
.1768
.1585
.0711
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0 .0000
.0196
.0279
8.66
.45
WASTE
DRAIN
.1812
.2106
.1170
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
.0298
.0255
.56
AVG SW
1.36
1.08
.65
.02
.06
.00
.00
.13
.31
.29
.41
.76
.42
ENTER -HYDGO TO RERUN PROGRAM OR
ENTER BYE TO LOGOFF COMPUTER SYSTEM
O3YE
If the programming session is completed, then the logofi command BYh is
typed at the next prompt. However, if the user would like to reenter the
hydrologic model using the same climatological data, the user should enter
-HYDGO. At this point, the program heading would be reprinted and the begin-
ning questions asked (Figure 5). If the user would like to change the clima-
tological input data, -HYDBAT should be entered and the user should follow
the steps outlined in Figure 5 (page 14).
49
-------
SECTION 4
CONCLUSIONS
Runoff is significantly affected by the type of soil and vegetative
cover, as well as management practices, and they affect the routing of runoff
water from the final soil cover surface. A loam soil with an excellent well-
managed grass cover can reduce percolation into the solid waste to negligible
amounts. Management practices during the growing season affect the hydraulic
runoff through changes in the LAI. Increasing LAI causes greater water use
(higher evapotranspiration), and thus soil-water storage is reduced along
with a significant reduction in percolation and eventually leachate.
In addition, increasing the SCS curve number increases the amount of
surface runoff. Paved and impervious water surfaces are always a curve num-
ber of 100, whereas a curve number of 1 would imply a totally porous system.
FUTURE CONSIDERATIONS
1. Sensitivity and verification analysis should be accomplished to com-
pare model output to solid waste disposal site measurements.
2. Interaction between default data and input data usage: This would
allow the user to select default data for the input data mode and
permit broader model usage.
3. Program scenarios: This would permit the user to change the vegeta-
tive cover, temperature, solar radiation, soil porosity, hydraulic
conductivity, etc., on a year to year basis.
4. Design a synthetic storm on a 25-, 50-, or 100-year probability of
occurrence using hourly records (duration-frequency data) to design
and evaluate solid waste disposal sites under intense storm
conditions.
5. To estimate the amount of erosion anticipated on the final cover
soil and vegetation which can be accomplished by using the output of
the surface runoff.
6. A nutrient and pesticide routine can be added to evaluate the "Best
Management Practices" of the vegetative cover and thus increase
evapotranspiration and reduce percolation.
50
-------
7. Chemical leachate algorithms can be added to estimate specific
parameters that would accompany the leachate.
8. Gaseous diffusion algorithms can be added to evaluate gaseous losses
through the soil cover.
9. An economic package can be added to estimate the carrent cost of
construction and maintenance of the solid waste disposal site using
various materials and management practices.
51
-------
REFERENCES
1. Brunner, D. R. and D. J. Keller, "Sanitary Landfill Design and Opera-
tion," EPA-SW-65ts, 1972, Environmental Protection Agency, Rockville,
Md.
2. Pavoni, J. L. et al., Handbook of Solid Waste Disposal: Materials and
Energy Recovery, Van Nostrand, New York, 1975.
3. Geswin, A. J., "Liners for Land Disposal Sites, An Assessment,"
EPA/530/SW-137, Mar 1975, Environmental Protection Agency, Washington,
D.C.
4. Beck, W. M., Jr., "Building an Amphitheater and Coasting Ramp of Munici-
pal Solid Waste," EPA/530-SW52d-OF, 1973, Virginia Beach, Va.
5. Bartos, M. J., Jr., "Use of Dredged Material in Solid Waste Management,"
Technical Report D-77-11, Sep 1977, U. S. Army Engineer Waterways
Experiment Station, CE, Vicksburg, Miss.
6. Lutton, R. J., G. L. Regan and L. W. Jones, "Design and Construction of
Covers for Solid Waste Landfills," Aug 1979, EPA-600/2-79-165, Environ-
mental Protection Agency, Cincinnati, Ohio. PB 80-100381.
7. Perrier, E. R., J. Harris and W. B. Ford III, "A Comparison of Determin-
istic Mathematical Watershed Models," ASAE, Paper No. 77-2047, Jun
1977, St. Joseph, Mich.
8. Fenn, D. G., K. J. Hanley and T. V. DeGeare, "Use of the Water Balance
Method for Predicting Leachate Generation from Solid Waste Disposal
Sites," EPA/630/SW-168, 1975, US-EPA, Cincinnati, Ohio.
9. Knisel, W. J., Jr, Editor, "CREAMS, A Field Scale Model for Chemical
Runoff and Erosion from Agricultural Management Systems," Vols. I, II,
and III, Draft Copy, USDA-SEA, AR, Cons. Res. Report 24, 1980.
10. Buckman, H. 0. and N. C. Brady, "The Nature and Properties of Soils,"
1960, The Macmillan Co., Inc., New York.
11. Baver, L. D., W. H. Gardner and W. R. Gardner, "Soil Physics," 1972,
John Wiley & Sons, Inc., New York.
12. Bartos, M. J., Jr., "Classification and Engineering Properties of
Dredged Material," Technical Report D-77-18, Sep 1977, U. S. Army Water-
ways Experiment Station, CE, Vicksburg, Miss.
52
-------
13. Robinson, N., "Solar Radiation," 1966, Elsevier Publ. Co., New York.
14. USDA, Soil Conservation Service, "National Engineering Handbook, Section
4, Hydrology," 1972, U. S. Government Printing Office, Washington, D.C.
15. Holtan, H. N., G. J. Stilner, W. H. Hensen and N. C. Lopez, "USDAHL-74,
Revised Model For Watershed Hydrology," USDA, Agr. Res. Service, Tech.
Bulletin No. 1518, December 1975, Washington, D. C.
16. Hjelmfelt, A. T., Jr. and J. J. Cassidy, "Hydrology for Engineers and
Planners," 1975, Iowa State University Press, Ames, Iowa.
17. Williams, J. R. and W. V. LaSeur, "Water Yield Model Using SCS Curve
Numbers," Jour, of the Hydraulics Div., ASCE, Vol. 102, No. HY9, 1976,
pp. 1241-1253.
18. Hawkins, R. H., "Runoff Curve Numbers with Varying Site Moisture," Jour.
of the Irrig. and Drain. Div., ASCE, vol. 104, No. IR4, 1978, pp. 389-
398.
19. Hawkins, R. H., "Runoff Curve Numbers from Partial Area Watersheds,"
Jour, of the Irrig. and Drain. Div., ASCE, Vol. 105, No. IR4, 1979, pp.
375-389.
53
-------
APPENDIX A
HYDROLOGIC SIMULATION
Model development will be presented in this section for daily water
movement on the surface and through the final cover soil. The following de-
scription of the principles on which the model was developed is from Knisel
(9), SCS-NEH (14), and Hjelmfelt and Cassidy (16). In the model, precipita-
tion is separated into runoff, evapotranspiration, and subsurface drainage to
maintain a continuous water balance.
"Computerized rainfall-runoff models have been used extensively since
the mid-50's. However, confusion and misunderstanding over their application
still exist. There are those who will not accept the results of any model,
no matter how well documented and verified. At the other extreme, there are
those so in awe of computer technology that they accept the results of all
such models without adequate scrutiny. These attitudes have promoted the
feeling that hydrologic simulation models can only be properly understood by
the hydrologist specializing in this seemingly esoteric computer-oriented
discipline. There is, however, no merit to that conclusion which often
leaves models categorized as intellectual toys."
Mathematical modeling concepts deal with deterministic and stochastic
variables. A deterministic variable is one whose temporal and spatial prop-
erties are known, i.e., it is assumed that the behavior of a hydrologic vari-
able is definite and its characteristics can be predicted without uncer-
tainty. The HSSWDS model is deterministic in its modeling concepts. A
general weakness with most research efforts employing deterministic models is
that they have focused on obtaining "best" estimates of runoff and percola-
tion parameters which are then used as the "true" values of the process.
A stochastic variable is one whose properties are governed by purely
random-time events, sequential relations, as well as functional relations
with other hydrologic variables. Precipitation is an excellent example of a
stochastic parameter. It includes all forms of water delivered to the land
surface. It may occur in the form of rain, snow, hail, sleet, or dew and the
form of precipitation is an important factor in determining its flow path.
On the average, precipitation occurs only 5 percent of the time throughout a
year and the distribution of precipitation is seldom uniform in space and is
never uniform in time.
RUNOFF
During a given rainfall, water is continually being intercepted by
54
-------
trees, plants, root surfaces, etc., and at the same time, transport and
evapotranspiration are occurring simultaneously throughout the period. Once
rain begins to fall and the initial requirements of infiltration are ful-
filled, natural depressions collect the excess rain to form small puddles.
In addition, minute depths of water begin to build up on permeable and imper-
meable surfaces within the waste disposal site. This stored water collects
in small rivulets conveying the water into small channels, i.e., overland
flow or surface runoff.
The SCS curve number technique (14) was selected (9) for the runoff pro-
cess for the following reasons: (17)
a) a well established reliable procedure,
b) computationally efficient,
c) required inputs available, and
d) soil types, land use, and management can be estimated.
A plot of the accumulative rainfall versus the accumulative runoff can be
used to develop the relation (14) between rainfall, runoff, and retention
(the rainfall not converted to runoff). Although rainfall and runoff do not
start at the same time (initial abstraction I ), this relation as shown in
Figure A-l can be expressed as:
F_= Q
S' P
where
F = actual retention
S' = potential maximum retention (ST :> F)
Q = actual or direct runoff
P = potential maximum runoff (P >_ Q)
The retention S' is a constant for a particular storm because it is the
maximum that can occur under the existing conditions if the storm continues
without limit. The time delay I between rainfall and runoff consists
a
mainly of interception, infiltration, and surface storage, all of which occur
before runoff begins. Therefore, the initial abstraction I is brought
into the relation by subtracting it from the rainfall, thus:
S' = S - I or S = S' + I
a a
P = P - I
a
which is represented by the dashed line in Figure A-l. The retention F
(amount that infiltrates) varies because it is the difference between P and
Q at any point along the plotted curve, e.g.
F = P - Q
and
F = (P - I ) - Q
a
where
55
-------
1.0
Figure A-1. Relation between the fraction of runoff and the
fraction of retention.
F > S
Q < (P - I )
a
Now combining terms, it follows:
(P - I ) - Q
P - I
After algebraic manipulation this expression becomes:
(P - IJ
Q =
(P - i ) + s
Rainfall and runoff data from a large number of small watersheds showed the
relation between I and S (which includes I ) as:
a a
I =0.25
a
56
-------
Thus, the runoff is predicted for daily rainfall for hazardous and solid
waste disposal sites using:
Q = - -_ (1)
W P + 0.8S V J
where
Q = the daily runoff
P = the daily rainfall
S = the retention parameter
all having the dimensions of length. This equation represents a family of
curves of Q on P for a range of values of S from 0 to °°
Expanding the numerator, applying polynomial division, and dividing
through by S yields (18,19):
?=?- 1.2+
s s yp + o.ss
where the term in the brackets is the remainder from division which ap-
proaches 0 as P approaches °° . This relation can be seen in Figure A-2
and shows that the maximum possible amount that can be stored or infiltrated
is:
P - Q = 1.2S (2)
or
!•!-'•*
where P approaches °° . Upon rewriting equation 1 by dividing through by
2
S and rearranging gives:
(I - 4
for all P/S >_ 0 . 2 . This relation is also shown in Figure A-2 which shows
that the value of Q/S approaches P/S - 1.2 asymptotically.
A convenient method was selected to transform the site storage S into
curve numbers CN which had a range of 0 to 100 (14) .
- ooo
As stated the system is in inches and must be converted to use metric units.
The potential site retention parameter S is related to the soil water
content (9) by the expression:
- s
" rox UL
where
57
-------
Q/S 1.0 —
Q/o-(P/S-1.2)2
u'6 P/S + 0.8
3.0
Figure A-2. SCS rainfall-runoff relation standardized on
retention parameter S
SM = soil water content in the final soil cover
UL = upper limit of soil water storage
S = maximum value of S
mx
The maximum value of S is estimated with the initial moisture condition I
for the curve number CN by combining equations 2 and 3 as:
S = 1.:
mx
- 10
In this model, the moisture condition II was related to CNI using the
polynomial:
CN = -16.91 + 1.348(CNI:[) - 0.01379(CNI];)2 + 0.0001177(CNTT)3
II
58
-------
The hydrologic condition II can be estimated using Figure 8 or the detailed
listings in the SCS-HEC (14) manual for the specified final soil cover
complex.
To assist in uniformly distributing the soil-water in the profile, a
weighting technique was developed that divided the soil profile into seven
layers and weighting factors with the equation:
S = S 1 -
mx
Y> SM.
i-i i VL.
where
W. = weighting factor at depth i
The weighting factors decrease with depth according to the default values:
0.111, 0.397, 0.254, 0.127, 0.063, 0.032, and 0.016. Using this procedure,
runoff is predicted for the solid waste disposal site.
Generally, each solid waste disposal site is thought to be unique; how-
ever, uniqueness suggests a lack of information as well as a limitation in
data gathering capabilities. It is necessary to place in proper perspective
the role that such items as rainfall intensity, storm duration, interception,
site slope, shape, size, and roughness play upon the time distribution of
runoff. Between storms, however, water within the soil also moves upward
(capillary rise) because of the flux of water from soil to atmosphere. Also,
the vaporization of rainfall or snow resting on the outer plant surfaces is
gained by the atmosphere. These processes are usually called evaporation.
EVAPOTRANSPIRATION
The major portion of solar radiation is used in the process of evapo-
transpiration. Evapotranspiration is the amount of water lost by evaporation
and transpiration from a plant surface. For example, if thermal energy is
added to a body of water with a free surface, the kinetic energy of the mole-
cules is increased to the extent that some of the water molecules at the sur-
face can overcome their surrounding cohesive bonds and are able to escape
across the air/water interface (16). As the molecule of water passes from the
liquid to the vapor state, it absorbs heat energy, thus cooling the water
left behind. As water enters the soil it becomes either evapotranspiration,
storage, or drainage below the final soil cover. In this simulation model a
daily time interval is used to evaluate the components of the water balance
equation such as,
SM. = SM. , + FR. - ET. -DR. + M
i i-l 1111
where
SM = soil water storage on day i
FR = water entering the soil
ET = evapotranspiration
DR = drainage below the final soil cover
M = amount of snowmelt
59
-------
When precipitation occurs and the temperature is below freezing, 32°F
(0°C), that precipitation is stored in the form of snow. When snow storage
exists and the temperature T is above freezing, snowmelt M occurs by the
following equation as:
M. = 0. 1ST
i
where i is the number of days. This relation is used unless M is greater
than the amount of surface snow.
To compute the potential evaporation a modification of the Penman method
that uses energy balance principles is used in the model as:
1.28 AH
E = _ 9.
o A + y
where
E = potential evaporation
A = slope of the saturation vapor pressure curve at the mean air
temperature
H = net solar radiation, and
o
Y = is the psychrometric constant
The slope A of the saturation vapor pressure curve for water at the mean
air temperature is computed from:
. _ 5304 (21.255-5304/T)
A - — 3- e
T
where T is the daily temperature in degrees Kelvin. The net solar radia-
tion K is computed from the equation:
o - 58.3
where
A = albedo for solar radiation, i.e., 0.23
R = daily solar radiation
When the potential evaporation E is known, the potential soil evapora-
tion E at the soil surface is predicted by:
so r
E = E e°-4 LM
so o
where LAI is the leaf area index defined as the area of plant leaves relative
to the soil surface, i.e., a ground cover component. The actual soil evapo-
ration is computed in two stages. In the first stage, soil evaporation is
limited only by the energy available at the soil surface and, therefore, is
equal to the potential soil evaporation. When the accumulated soil
60
-------
evaporation exceeds the stage one upper limit, the stage two evaporative
process begins. The stage one upper limit U is estimated by:
U = 9 (
-------
At = the routing interval (24 hours)
a = the storage coefficient
If the inflow plus the storage does not exceed the field capacity FC ,
drainage cannot occur. The storage coefficient a is a function of the
travel time t through the storage and is expressed by the equation:
2At
The travel time t is estimated by the equation:
SM - FC
sat
where
SM = soil water storage
K = hydraulic conductivity
sat
Each soil storage layer is subject to evapotranspiration ET losses be-
sides those due to deep drainage. The water use rate U as a function of
final cover depth D is given by:
where U is the water use rate at the surface and U is the water use rate
by the crop at depth D . The evapotranspiration ET for any depth can be
obtained by integrating the above equation:
ET =
The value of U is determined for the depth D each day.
Drainage from the final soil cover occurs when the saturated volume of
the soil exceeds the field capacity. The total soil water storage UL is
equal to the porosity times the final soil cover depth D as:
UL = *D
62
-------
APPENDIX B
COST BREAKUP OF BOEING COMPUTER SERVICES
1. There are three cost parameters associated with Boeing Computer
Services (BCS); connect, storage, and central computer unit costs.
2. These costs are for the Giber 175 computer system. This is the com-
puter used by the Water Resources Engineering Group.
3. The connect cost occurs during the interactive mode. This cost is
$8.50 per hour for the 30 characters per second printed.
4. Disc and magnetic tape are the two types of storage costs. The disc
storage cost is $0.007 per day for the first 8,000 sectors; 8,001 sectors to
16,000, the cost is $0.005 per day; 16,001 sectors to 24,000, the cost is
$0.0035 per day; 24,001 sectors to 50,000, the cost is $0.0025 per day;
50,001 sectors and up, the cost is $0.0015 per day. The magnetic tape cost
for the first 200 sectors is $0.20 per day for Government users. The next
200 sectors are $0.15 per reel per day; over 400 sectors, the cost is $0.10
per reel per day.
5. The computer charging units (CCU) costs depend on the mode interac-
tive or remote batch. The interactive process during prime time is $0.20 per
CCU. The CCU costs for the remote batch process for one-half an hour is
$0.15 per CCU; for 1 hour, $0.125 per CCU; for 4 hours, $0.10 per CCU; for
8 hours, $0.085 per CCU; for 16 hours, $0.075 per CCU; for 48 hours, $0.06
per CCU.
6. These costs presented above are given without the Government
discount (30 percent).
63
-------
APPENDIX C
SENSITIVITY ANALYSIS
By
R. J. Wills, Jr., E. R. Perrier, and A. C. Gibson
The Hydrologic Simulation of Solid Waste Disposal Sites (HSSWDS) is a
simulation model with two input options. The default option inputs climato-
logical and hydrological data from permanent data files stored in the com-
puter, and the data input option permits the user to input all the necessary
data from external or measured sources. However, both input options use the
same output formats. To facilitate the data handling for the sensitivity
analysis only the complete data input option was used.
The climatological and hydrological data were input for Cincinnati,
Ohio, area and the values used are shown in Figure C-l. The climatological
data consist of 5 years of daily precipitation values and the yearly means
are shown in Figure C-2, as well as mean monthly temperature, mean monthly
solar radiation, and the Leaf Area Index (LAI) values. In addition, Table
C-l presents the hydrological data for a fictitious solid waste site some-
where in the Cincinnati area.
Table C-l presents the sensitivity runs to be made for each parameter
with other variables being fixed as shown in Figure C-l. A total of 36 com-
puter runs were made to demonstrate the sensitivity of the selected param-
eters to changes in climatological and hydrological data of the solid waste
site. The discussion of each parameter will follow the organization pre-
sented in Table C-l.
IMPERMEABLE LINER
As shown in Table C-l the life of the impermeable liner (see Figure 2 of
main text) was varied for values of 5, 10, 15, and 20 years as well as an op-
tion of indefinite life. As expected, the impermeable liner is only affected
by water that has percolated past a point beyond runoff and evapotranspira-
tion. The main effect upon the liner is whether the percolated water drains
from the site as soil drainage or waste drainage (see Figure 2 of main text).
As shown in Figure C-3, a liner with a 5-year life accounted for only
9.6 percent of the total percolation for waste drainage the first year;
whereas, waste drainage accounted for 89 percent of the total pecolation by
the 5th year. By comparison, the indefinite life liner accounted for
64
-------
CLIMATOLOGIC INPUT
DAILY PRECIPITATION (INCHES)
1 YEAR (10 VALUES/LINE, 37 LINES)
YEAR: 1974
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
0.02
0.38
0.53
1.03
0. 18
0.12
0.02
0.20
0.41
0.55
0.45
0.30
0.71
0.04
0.37
0.21
0.63
1.03
0.09
0.14
0.13
0.05
0.04
2.03
0.05
0.49
0.09
0.03
0.02
0.23
0.62
0.01
0.07
0.01
0.46
0.03
1.55
0.45
0.05
0.21
0.03
0.01
0.39
0.01
0.17
0.41
0.20
0.57
0.34
0.10
0.16
0.64
1.02
0.06
0.63
0.21
0.20
0.05
0.22
0.03
0.32
0.57
0.02
0.19
0.72
0.14
0.03
0.03
0.42
0.42
0.29
0.05
0.15
0.30
0.03
0.11
0.75
1.81
0.58
0.17
0.04
0.42
0.20
0.73
0.03
0.57
0.61
0.08
0.02
0.03
0.16
0.03
0.32
0.02
0.52
f 0.78
0.19
0.31
0.04
0.54
0.06
0.26
0.60
0.68
0.05
0.67
0.36
0.10
0.09
0.15
0.20
0.80
0.42
0.26
0.15
0.34
0.80
0.41
0.05
0.02
0.36
0.11
0.64
0.33
0.43
0.46
1.11
0.34
0.54
0.81
0.02
2.09
0.16
(continued)
Figure C-l. Data input requirements for
climatological and hydrological modules.
65
-------
YEAR: 1975
Figure C-l. (continued)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
0.02
0.46
0.96
0.38
0.50
1.12
0.05
0.25
0.09
0.03
0.71
1.18
0.38
0.19
0.02
0.04
0.01
0.07
0.02
0.01
0.01
0.98
0.27
0.10
0.20
0.82
0.05
0.07
1.38
0.07
0.12
0.28
0.02
r~b~T2i
0.19
0.32
0.54
0.60
0.32
0.13
0.08
0.14
0.23
0.02
0.77
0.14
0.08
2.32
0.22
1.56
0.01
0.27
0.15
1.75
0.39
0.04
0.55
0.04
0.33
0.17
0.17
0.05
0.53
0.01
0.02
1.52
0.21
0.43
0.54
0.27
0.18
0.02
0.96
0.03
0.01
0.03
0.23
0.07
0.22
0.35
0.33
0.09
0.02
0.02
0.88
0.04
0.07
0.08
0.31
0.50
0.05
0.04
0.13
0.44
0.69
0.04
0.04
0.03
0.67
0.26
0.78
0.05
0.03
0.42
0.44
0.07
0.15
0.08
0.70
1.41
0.12
0.24
0.06
0.02
0.01
0.14
0.33
0.28
0.01
0.55
0.44
0.02
0.41
0.07
0.22
0.06
0.90
0.63
1.04
0.13
0.09
0.04
0.18
0.13
0.20
1.90
0.51
0.35
0.19
(continued)
66
-------
YEAR: 1976
Figure C-l. (continued)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
0.01
0.23
0.05
0.15
0.33
0.51
0.20
0.16
0.46
0.37
0.15
0.48
0.24
0.36
0.69
0.97
0.01
0.01
0.67
0.09
0.16
0.07
0.02
0.05
1.07
0.06
0.03
0.04
0.48
0.01
0.53
0.09
0.16
0.02
0.08
0.01
0.26
0.05
0.33
0.70
0.76
0.02
0.65
0.06
0.14
0.21
0.04
0.01
0.16
0.18
0.05
0.13
0.05
0.46
0.23
0.20
0.06
0.20
0.19
0.12
0.74
1.04
0.03
0.43
0.01
0.18
0.12
0.01
0.10
0.15
0.41
0.04
1.00
0.02
0.01
0.01
0.05
0.59
0.92
0.18
0.41
0.72
0.10
0.70
0.07
0.73
0.19
0. 12
0.95
0.18
2.40
0.22
0.48
0.07
0.04
0.01
0.78
0.05
0.60
0.21
0.09
0.41
0.49
0.03
(continued)
67
-------
YEAR: 1977
Figure C-l. (continued)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
0.01
0.02
0.62
0.08
0.15
1.07
0.36
0.01
0.45
0.02
0.10
0.30
0.01
1.12
1.84
0.23
0.02
0.75
0.16
0.10
^0.53
0.03
0.48
0.13
0.06
0.01
0.02
0.10
0.01
0.07
0.11
0.51
0.04
0.56
0.59
0.08
0.04
0.15
0.04
0.05
0.45
0.38
0.28
0.40
0.02
0.21
0.10
0.01
L 0.29
0.85
0.57
0.04
0.08
0.33
1.18
0.02
0.04
0.90
0.01
0.03
0.03
0.20
0.05
0.04
0.07
0.02
0.01
0.01
0.27
0.13
0.03
0.01
0.02
0.08
0.22
0.41
2.34
0.11
1.53
0.05
0.05
0.02^
0.03
0.05
0.77
0.07
0.14
0.77
0.10
0.18
0.33
0.03
0.02
0.38
0.71
0.34
0.01
0.34
0.52
0.14
0.07
1.40
0.54
0.17
0. 19
0.15
0.15
0.18
0.50
1.05
0.03
0.07
0.02
0.13
0.10
0.03
0.01
1.07
0.15
0.04
0.29
0.30
0.40
0.12
0.04
0.27
1.05
L_0.38
(continued)
68
-------
YEAR: 1978
Figure C-l. (continued)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
0.03
0.01
0.01
0.01
0.17
0.26
0.05
0.02
0.26
0.01
0.35
0.03
0.02
0.62
0.58
0.02
0.08
0.02
0.11
0.05
0.11
0.61
0.11
1.12
0.11
1.05
1.80
0.06
0.02
0.49
0.57
0.01
0.40
0.75
0.94
0.01
0.16
1.41
0.60
0.32
0.09
0.03
0.02
0.22
0.13
0.02
0.06
0.20
0.46
0.37
0.66
0.13
1.02
0.60
0.46
0.28
0.45
0.02
0.09
0.04
0.07
0.02
0.02
0.02
0.37
1.91
0.49
1.32
0.09
1.02
0.88
0.35
0.31
0.04
0.08
0.34
0.05
1.31
0.03
0.66
0.49
1.45
0.09
0.22
0. 10
0.03
0.43
0.31
0.03
0.24
0.07
0.11
0.6
0.6
0.66
0.19
1.45
1.32
0.01
1.03
0.68
0.61
0.02
0.56
0.06
0.19
0.09
0.16
0.04
0.03
0.03
0.20
0.01
0.04
0.14
0.26
1.08
0.35
0.15
0.12
0.02
0.56
0.48
0.51
0.18
0.02
0.19
0.08
0.06
0.22
0.01
0.02
0.01
0.16
0.06
(continued)
69
-------
Month
January
February
March
April
May
June
July
August
September
October
November
December
Figure C-l. (continued)
Mean Monthly
Temperature
11.3
18.8
25.3
54.3
59.6
72.9
73.8
72.5
74.6
58.8
50.0
40.8
Mean Monthly
Insolation
(Langleys/Day)
128
200
297
391
471
562
542
477
422
286
176
129
Leaf Area Index Values
Day
Area
92
104
116
128
140
152
164
176
188
200
213
366
.61
.99
.99
.99
.99
.99
.89
.71
.65
.61
(continued)
70
-------
Figure C-l. (concluded)
Hydrological Input
Study Title: Sensitivity Study
Area Location: Cincinnati, Ohio
Today's Date: 18 July 1980
Date of first storm event (Julian date) 74003
(example = 73038, 1973 and 38 Julian day)
Surface area of solid waste site 24 acres
Hydraulic conductivity of vegetative soil .33 in./hr
Hydraulic conductivity of barrier soil .0011 in./hr
Depth of soil cover 24 inches
Depth of vegetative layer 18 inches
Depth of barrier layer 6 inches
Depth of solid waste 180 inches
Soil porosity of vegetative soil .621 vol/vol
Soil porosity of barrier soil .226 vol/vol
SCS curve number 90
Channel slope . 1 ft/ft
Hydrologic channel length 1446 ft
Available water capacity of vegetative soil . 156 vol/vol
Available water capacity of barrier soil .038 vol/vol
Winter cover factor .J5
Evaporation coefficient of vegetative soil 4.5
Evaporation coefficient of barrier soil 3.1
71
-------
60
50
40
o
UJ
oc
30
20
74
75
76
YEAR
77
78
Figure C-2. Annual Cincinnati, Ohio,
precipitation from 1974 to 1978.
72
-------
TABLE C-l. PARAMETERS VARIED FOR SENSITIVITY ANALYSIS
Number
of
runs Parameters
Parameter variation
5
3
3
3
3
5
2
Impermeable liner
SCS curve number
Winter cover factor
Depth of barrier soil
Depth of vegetative soil
Leaf area index
Barrier soil compaction
5, 10, 15, 20, Ind. (years)
81, 90, 99
0.5, 0.8, 1.0
6, 12, 18 (inches)
12, 24, 36 (inches)
Ex, Gd, Fr, Pr, Brgnd*
Compacted, not compacted
12
Soil texturef
Vegetative soil
S
SL
L
SCL
SCL
Barrier soil
S, SL, L, SCL, C
L, SCL, C
SCL, C
C
C (compacted)
* Excellent, Good, Fair, Poor, Bare ground.
t S = sand, L = loam, C = clay.
73
-------
3.0 i-
2.0
Q:
Q
1 0
74
75
76
77
IS
YEAR
Figure C-3. Annual waste drainage as
related to the impermeable liner.
2.5 percent of total percolation for waste drainage the first year which in-
creased to 13 percent of total percolation for waste drainage by the 5th
year. The final percentages of percolation accounted for by waste drainage
for the 10-, 15-, and 20-year options were 31, 38, and 50 percent, respec-
tively.
Figures C-3 and C-4 show that the 10-, 15-, and 20-year life options
correlated with the indefinite life liner. Based upon the 5-year data set,
waste drainage increased by 585 percent with the 5-year liner life as com-
pared to 285 percent with the indefinite liner life.
74
-------
QC
Q
YEAR
Figure C-4. Annual soil drainage as
related to the impermeable liner.
SCS CURVE NUMBER
The results for the SCS curve number are interpreted for the yearly to-
tals because the curve number is not a time dependent variable. As expected,
this variable is a primary factor for surface runoff (Figure C-5) and a sec-
ondary factor for evapotranspiration (Figure C-6) and waste drainage. As
presented in Table C-2, the average annual totals for a curve number of 81
shows that surface runoff was 17 percent of the total precipitation; whereas,
for a curve number of 99, the surface runoff increased to 52.2 percent or an
increase of 35 percentage points. Evapotranspiration decreased by 26 per-
centage points from 73.8 percent for a curve number of 81 to 47.5 percent for
a curve number of 99. These differences in evapotranspiration accounted for
most of the increase in surface runoff with the remainder (about 9 percentage
points) being accounted for by decreases in waste drainage and soil water.
75
-------
30.0
r
20.0
D
o:
10.0
\x
\\
\
\
• 90
•81
74
75
76
YEAR
77
_J
78
Figure C-5. Annual runoff as related to the SCS curve number.
76
-------
40r-
30
g
<
<
a:
99-
20
1 0
74
75
76
77
78
YEAR
Figure C-6. Annual evapotranspiration as
related to SCS curve number.
77
-------
TABLE C-2. PERCENTAGES OF THE SURFACE RUNOFF, WASTE DRAINAGE, AND
EVAPOTRANSPIRATION TO THE AVERAGE ANNUAL PRECIPITATION*
FOR THE SCS CURVE NUMBER
Parameter
Surface runoff, percent
Waste drainage, percent
Evapotranspiration, percent
81
17.0
7.1
73.8
SCS curve number
90
21.6
5.6
70.8
99
52.2
0.1
47.5
* Average annual precipitation =40.6 inches.
Table C-2 shows that the percentages for the curve numbers of 81 and 90 were
more comparable than the percentages for the 99 curve number.
Figure C-7 shows that waste drainage changed from an average of
2.87 in./year for a curve number of 81 down to nearly zero (0.0549 in./year)
for a curve number of 99.
4.0r-
a:
Q
in
I
99
78
Figure C-7. Annual waste drainage as related
to the SCS curve number.
78
-------
WINTER COVER FACTOR
The winter cover factor is seasonally dependent and directly effects the
process of evapotranspiration. Figures C-8, C-9, and C-10 demonstrate that
the winter cover factor affects the results from September through April un-
til the growing season starts April 1st and declines after July 31st. Since
the winter cover factor is seasonally dependent monthly evaluation is
preferable.
JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV
Figure C-8. Average monthly evapotranspiration
as winter cover factor.
79
-------
I
05
JAN
FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV
MONTH
DEC
Figure C-9. Average monthly waste drainage as
related to the winter cover factor.
80
-------
JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT MOV DEC
MONTH
Figure C-10. Average monthly runoff as related
to the winter cover factor.
When comparing each parameter as a percentage of average annual precipi-
tation, evapotranspiration was shown to increase by 10.3 percentage points as
the winter cover factor went from 0.5 to 1.0. Over the same range of winter
cover factors, surface runoff and waste drainage decreased by 6.9 and
2.6 percentage points, respectively. The winter cover factor of 0.5 implies
an excellent grass cover while the winter cover factor of 1.0 implies the
bare ground condition; however, in this study these values were linked with
the LAI for a grass in fair condition. While this contradiction is necessary
to protect the integrity of the study, it should be noted that these extreme
conditions would rarely be found in a field situation. If the user chooses
the default option, the winter cover factor that corresponds to the selected
LAI is automatically assigned.
DEPTH OF BARRIER SOIL
To evaluate the effect of varying barrier soil depth the total soil
depth was set at 24 inches and the barrier soil was assigned depths of 6, 12,
and 18 inches. Therefore, the depth of vegetative soil computed by the model
varied accordingly.
Figures C-ll and C-12 show the yearly significance of the barrier soil
81
-------
180i—
16.0 -
14.0 ~
12.0 -
D
o:
10.0 -
Figure C-ll. Annual surface runoff as related
to depth of barrier soil.
82
-------
4.0r
3.0
en
D
H
-------
1.0,-
cc
O
0.5P
JAN
FEB MAR APR
J_
MAY JUN JUL AUG SEPT OCT
MONTH
NOV DEC
Figure C-13. Average monthly surface runoff
as related to depth of barrier soil.
84
-------
3 or
, 18"
12"
JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV DEC
MONTH OF OCCURANCE
Figure C-14. Average monthly waste drainage
as related to depth of barrier soil.
rainfall, solar radiation, temperature, and LAI suggest that the barrier soil
depth should be considered time dependent.
Comparison of each parameter as a percentage of the average annual pre-
cipitation showed that the surface runoff increased by 12.5 percentage points
from the 6- to the 18-inch barrier soil depth. However, waste drainage and
evapotranspiration decreased by 4.6 and 6.7 percentage points, respectively.
It should be noted that the selection of the 18-inch depth of barrier soil
was for test purposes only. In most instances, a 6-inch vegetative soil
layer would not support an adequate plant growth and is not recommended for
field applications.
DEPTH OF VEGETATIVE SOIL
For this part of the study, the depth of the vegetative soil layer var-
ied 12, 24, and 36 inches and no barrier soil was used. Table C-3 compares
the percentages of the surface runoff, waste drainage, and evapotranspiration
to the average annual precipitation for each depth of vegetative soil. Sur-
face runoff showed the least change as soil depth was varied. The greatest
difference was only 0.3 percentage points and was not considered significant.
85
-------
TABLE C-3. PERCENTAGES OF THE SURFACE RUNOFF, WASTE DRAINAGE, AND
EVAPOTRANSPIRATION TO THE AVERAGE ANNUAL PRECIPITATION*
FOR DEPTH OF VEGETATIVE SOIL
Vegetative soil depth, inches
Parameter 12 24 36
Surface runoff, percent
Waste drainage, percent
Evapotranspiration, percent
15.1
16.7
67.9
15.2
12.1
72.2
14.9
8.7
75.7
* Average annual precipitation =40.6 inches.
The largest differences of the vegetative soil depth affected the amount
of the initial soil water storage and the upper limit of the soil water stor-
age resulting from the increased soil depth. For a vegetative soil depth of
12 inches the initial soil water was 0.936 inches and the upper storage limit
was 1.87 inches; however, for the 36-inch vegetative soil depth the initial
soil water increased to 2.81 inches and the upper limit of storage increased
to 5.62 inches. As the soil depth increased, larger volumes of water were
available to the plants which resulted in an increased evapotranspiration.
Table C-3 shows that evapotranspiration increased by 7.8 percentage points
and waste drainage decreased by 8.0 percentage points as the vegetative soil
depth increased.
Figure C-15 shows the relation of the annual waste drainage to year of
occurrence with the vegetative soil depth as the parameter. It shows that
waste drainage is not uniform with time, a condition caused by the initial
soil water storage and the upper limit of soil water storage that result in
soil water storage difference for each vegetative soil depth. This stored
soil water is sensitive to replenishment by precipitation and to depletion by
evapotranspiration and waste drainage. A distortion in the waste drainage is
noticeable for the years of 1976 and 1977.
86
-------
10.0r-
oc
O
UJ
78
Figure C-15. Annual waste drainage as related
to the depth of vegetative soil.
Figure C-16 for average monthly values for the 5-year data set and the
1976 data set is an expansion of Figure C-17 for the average annual soil
water with vegetative soil depth as the parameter for both figures. It was
shown in Figure C-l that 1976 was the driest year in the 5-year study period
with only 30.07 inches of precipitation during the year. The lack of pre-
cipitation affected the 12-inch soil depth waste drainage immediately (see
Figure C-15) since percolation for waste drainage was reduced. However, at
the 36-inch soil depth the volume of water was greater for percolation re-
sulting in less waste drainage. The lack of precipitation becomes more acute
since the drier months occurred in the last quarter of the calendar year when
evapotranspiration decreased thus allowing higher waste drainage than would
occur normally. The situation is reversed for the first half of 1977 as the
seasonal precipitation refills the soil profile to the 36-inch depth while at
the 12-inch depth percolation to waste drainage occurs at an earlier time.
This relation of soil water storage with time effects the evapotranspiration;
however, evapotranspiration is not as effective during October through Febru-
ary, the critical time period under observation.
87
-------
5.0 r
4.0
3.0
2.0
1.C
MONTHL Y A VERAGES /
36" DEPTH '
' 1976 ACTUAL
MONTHL Y A VERAGES
12" DEPTH
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB
1976 MONTH 1977
Figure C-16. Average monthly soil water for the 5-year data set
and the 1976 data set for January 1976 through February 1977
with vegetative soil depth as the parameter.
88
-------
Figure C-17. Average annual soil water as related
to the vegetative soil depth.
LEAF AREA INDEX (LAI)
The LAI is a measurable scale of the amount of vegetative ground cover
that exists as a function of time and is an effective partition of the plant
transpiration to soil evaporation ratio. This part of the sensitivity study
was designed to investigate changes resulting from using five different LAI
distributions as inputs. Bare ground conditions, as the name indicates, has
a 0.0 LAI for the entire year. An excellent crop condition is regraded as
89
-------
the best possible condition and an occurrence of good, fair, and poor crop-
ping conditions are designated as 66.6 percent, 33.3 percent, and 16.7 per-
cent of an excellent crop value, respectively. For the Cincinnati, Ohio,
climatic condition, the growing season starts on day 92 (April 1st) and con-
tinues until day 213 (July 31st).
As expected, the parameter most sensitive to changes in LAI was evapo-
transpiration. The percentages in relation to average annual precipitation,
as presented in Table C-4, show that evapotranspiration decreased by
14.5 percentage points between the extreme values for an excellent crop and
bare ground. Surface runoff increased by 7.6 percentage points, while waste
drainage increased by 6.1 percentage points. However, the greater portion of
the variation occurred between the values of poor crops and bare ground.
From excellent to poor crop conditions, the increases for surface runoff and
waste drainage were 3.1 and 1.2 percentage points, whereas evapotranspiration
increased by 4.5 percentage points.
TABLE C-4. PERCENTAGES OF THE SURFACE RUNOFF, WASTE DRAINAGE, AND
EVAPOTRANSPIRATION TO THE AVERAGE ANNUAL PRECIPITATION*
FOR THE LEAF AREA INDEX, LAI
Leaf Area Index
Parameter Excellent
Surface runoff 19.9
Waste drainage 5.1
Evapotranspiration 73.1
Good Fair Poor Bare ground
20.4 21.5 23.0 27.5
5.2 5.6 6.2 11.1
72.5 70.8 68.6 58.6
Average annual precipitation = 40.6 inches.
Figures C-18, C-19, and C-20 show the large variation that occurred be-
tween the values for a poor crop condition and a bare ground condition. As
expected, Figures C-18 and C-20 demonstrate that LAI is seasonally dependent
and for parameters such as evapotranspiration and surface runoff the LAI
changes do not affect the results before the growing season begins. After
the growing season starts, differences between the parameters affected by the
LAI accumulate until the peak of the growing season; then, there is a sharp
decline until the end of the growing season.
90
-------
EXCELLENT
JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV DEC
Figure C-18. Average monthly evapotranspiration
as related to the LAI.
91
-------
a
<
2
JAN
FEB MAR APR MAY JUN JUL AUG SEPT ~ OCT MOV DEC
MONTH
Figure C-19. Average monthly waste drainage as
related to the LAI.
92
-------
20r-
o
z
en
JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV DEC
MONTH
Figure C-20. Average monthly surface runoff as
related to the LAI.
93
-------
Figure C-19 shows that the waste drainage parameter differences in LAI
values are evident early in the year caused by accumulated differentials in
the soil water parameter. The effect of the soil water condition is also
shown in Figure C-21. When comparing the various LAI options of a vegetative
cover to that of bare ground, the significant beneficial effect of the vege-
tative cover is to provide additional control to waste drainage. This effect
is also noted in Figure C-19 showing that any LAI value increase from a poor
to an excellent crop condition decreases waste drainage during the growing
season to nearly zero.
JAN FEB MAR APR MAY
JUN JUL
MONT4H
AUG SEPT OCT NOV DEC
Figure C-21. Average monthly soil water as
relate,! to the LAI.
An unusual result of this LAI computation is shown in Figure C-18 when
evapotranspiration is related to time. For the month of April, the order of
the cropping options from the highest to the lowest evapotranspiration was
excellent, good, fair, poor, and bare ground. However, for the month of May,
the cropping order was changed to fair, poor, good, excellent, and bare
ground. Figure C-21 explains this apparent inconsistency by displaying the
average soil water results. The higher LAI values for the good and excellent
cropping options resulted in increased evapotranspiration that lowered the
soil water in April to a level where further evapotranspiration in May was
limited. The increase in evapotranspiration of the poor and fair cropping
options was not large enough to affect the soil water. The difference be-
tween the extreme cropping options, excellent and fair, was about 0.4 inches
during May.
94
-------
BARRIER SOIL COMPACTION
For this section of the sensitivity study the concern was whether the
barrier soil had been left as placed or compacted by some means. In the
model, compaction reduces the values for hydraulic conductivity, porosity,
and available water. When using the model default option, the hydraulic con-
ductivity is reduced by a factor of 20 and the values of a.ailable water con-
tent and porosity are reduced by a factor of 2. The input values for these
parameters in the sensitivity analysis are shown in Table C-5. These values
resulted in an upper limit for soil water storage of 2.8 inches for the com-
pacted barrier soil as opposed to 3.1 inches for the noncompacted barrier
soil.
TABLE C-5. HYDRAULIC CONDUCTIVITY, AVAILABLE WATER CONTENT, AND
POROSITY VALUES USED TO EVALUATE BARRIER SOIL COMPACTION
Parameter
Hydraulic conductivity (in/hr)
Available water content (vol/vol)
Porosity (vol/vol)
Noncompacted
0.022
0.076
0.452
Compacted
0.0011
0.038
0.226
The most sensitive parameters to the degree of compaction for the bar-
rier soil were surface runoff and waste drainage. Over the 5-year study
period, the waste drainage averaged 13.2 percent of precipitation in the non-
compacted barrier soil (Table C-6) , and was 5.6 percent for the comparted
barrier soil showing a decrease of 7.6 percentage points. The surface runoff
showed a decrease of 6.6 percentage points between the compacted and noncom-
pacted barrier soil. The effect of barrier soil compaction on evapotranspi-
ration was negligible.
TABLE C-6. PERCENTAGES OF THE SURFACE RUNOFF, WASTE DRAINAGE, AND
EVAPOTRANSPIRATION TO THE AVERAGE ANNUAL PRECIPITATION*
FOR BARRIER SOIL COMPACTION
Parameter Compacted Noncompacted
Surface runoff, percent 21.5 15.0
Waste drainage, percent 5.6 13.2
Evapotranspiration, percent 70.8 71.0
* Average annual precipitation = 40.6 inches.
95
-------
The relationship of barrier soil compaction to surface runoff and waste
drainage need not be limited to analysis on a yearly basis, but can affect
the parameters monthly and seasonally. Figures C-22 and C-23 show that
surface
14 or
120 -
10.0 -
80
O
6.0
40
2.0
COMPACTED
74
75 76
YEAR
77
78
Figure C-22. Annual surface runoff as related
to the barrier soil compaction.
96
-------
cc.
o
80
70
6.0
5.0
4.0
30
2.0
1.0
NONCOMPACTED
COMPACTED
74
75
76
77
78
YEAR
Figure C-23. Annual waste drainage as related
to the barrier soil compaction.
runoff is not as sensitive to compaction as is waste drainage. Figure C-23
shows that the waste drainage parameter during 1976 and 1977 has a delay or
time lag associated with the lower hydraulic conductivity of the compacted
barrier soil. Also, the waste drainage parameter is very sensitive to the
delay in the downward water movement process. The primary times of the year
when waste drainage is significant are the early spring (January-May) and the
late fall (October-December).
97
-------
As noted earlier, the Cincinnati, Ohio, growing season runs from April
1st to July 31st. For the majority of this season, the increased evapotrans-
piration which resulted from increased LAI, decreased the soil water to a
level where waste drainage was zero. Later in the season the precipitation
restored the soil water and the waste drainage continued to cycle through the
winter and into early spring. Since the precipitation cycle typically starts
in the last quarter of the year and continues to the first quarter of the
next, yearly totals can be deceptive, especially when the results of abnormal
rainfall are affected by time dependency.
When considering Figure C-23, for instance, the waste drainage for the
1976 noncompacted soil showed a much larger drop in waste drainage than the
compacted barrier soil. However, in 1977 the waste drainage from the noncom-
pacted soil increased while the waste drainage from the compacted soils con-
tinued to drop. This apparent inconsistency is explained by the increased
time lag associated with the compacted barrier soil.
Figure C-24 shows that the total precipitation for 1976 is significantly
less than the average (30.37 inches as compared to 40.64 inches), the largest
deficits occurring from March to May and late in the year from November
through December. The precipitation during the middle of the year (see Table
C-l) was not too much below average but since it occurred during the time of
year when evapotranspiration was at a peak, waste drainage was negligible.
AVERAGE MONTHLY RAINFALL
ACTUAL 1976 MONTHL Y RAINFALL-
AUG SEPT OCT NOV DEC
Figure C-24. Comparison of average monthly
precipitation to 1976 precipitation.
98
-------
Later in 1976, when precipitation could have had a more direct effect on
waste drainage, the lack of rainfall meant that soil water remained depleted
and waste drainage was lowered. Had the precipitation reached normal levels
during this time period, the soil water would have been replenished and some
waste drainage would have occurred. When the barrier soil is noncompacted,
normal precipitation increases waste drainage during November and December,
but the compacted barrier soil permits less water to percolate and therefore
some waste drainage occurs in December, January, and February of 1977. With
normal late year precipitation, the waste drainage from noncompacted soil
occurs soon after the rainfall but for compacted barrier soils some of the
waste drainage occurs during the next year.
Figure C-25 shows a comparison of the monthly waste drainage to the cor-
responding precipitation for 1978. Once again the effect of the time lag is
shown as the precipitation during February was extremely low. The immediate
effect was to reduce waste drainage for the noncompacted soil while the com-
pacted barrier soil shows the time lag of the waste drainage for December
1977 and January 1978. Also, the waste drainage decreases to zero from May
through September as precipitation increased which is the effect of increased
evapotranspiration. It isn't until later in the year when soil water in-
creases and evapotranspiration decreases that waste drainage again occurs.
SOIL TEXTURE
The purpose of this section was to evaluate the sensitivity of the hy-
drologic modeling processes to changes in the soil texture of the vegetative
and barrier soil. Varying the soil texture changes many of the other input
parameters such as the hydraulic conductivity, soil porosity, evaporation co-
efficient, and available water capacity. Parameter values which were used
with the various soil textures are presented in Table C-7.
Changing the hydraulic conductivity, soil porosity, evaporation coeffi-
cient, and available water capacity for the vegetative and barrier soil re-
sulted in small changes in the upper storage limit and the initial water
storage. Since these variables are used in computations such as surface run-
off, evapotranspiration, and waste drainage, it would be expected that these
processes reflect these changes. However, these processes do not show a uni-
form change with respect to a single variable when evaluated on a yearly
basis. Table C-8 presents each process for each parameter computed as a
percentage of the average annual precipitation. Waste drainage changed by
9.8 percentage points from one soil texture extreme to the other while evapo-
transpiration and surface runoff changed by 3.5 and 8.5 percentage points,
respectively. However, most of the variation is attributable to case No. 12
sandy clay loam/clay (compacted). Disregarding the results of this soil tex-
ture , waste drainage only changes by 2.3 percentage points while evapotrans-
piration changes by 3.5 percentage points and surface runoff by 2.1 percent-
age points. The variations resulting from changing the soil texture are
small in comparison to variations found with other parameters. Most of the
changes caused by soil texture are a result of the previously mentioned
variations in soil-water relationships which are compounded by conditions in
the late fall and winter. These conditions involve the replenishment of the
99
-------
70
60
40
£ 3.0
DEC JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV DEC
77 78
20
10
NONCOMPACTED
COMPACTED-^ '
1\
DEC JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV DEC
MONTH
Figure C-25. Waste drainage and precipitation
during the month of occurrence for 1978.
100
-------
TABLE C-7. SOIL PARAMETER VALUES USED IN THE SENSITIVITY STUDY
Soil
texture
Sand
Sandy loam
Loam
Sandy clay loam
Clay (noncompacted)
Clay (compacted)
Hydraulic
conductivity
(in./hr)
5.4
0.67
0.21
0.084
0.022
0.0011
Soil
porosity
(vol/vol)
0.389
0.442
0.521
0.453
0.680
0.226
Evaporation
coefficient
3.3
3.8
4.5
4.7
3.5
3.1
Available
water
content
(vol/vol)
0.133
0.123
0.156
0.199
0.115
0.038
In all, 12 different combinations of vegetative and barrier soils were run
as follows:
No.
Vegetative soil
Barrier soil
1
2
3
4
5
6
7
8
9
10
11
12
Sand
Sand
Sand
Sand
Sand
Sandy loam
Sandy loam
Sandy loam
Loam
Loam
Sandy clay loam
Sandy clay loam
Sand
Sandy loam
Loam
Sandy clay loam
Clay
Loam
Sandy clay loam
Clay
Sandy clay loam
Clay
Clay (noncompacted)
Clay (compacted)
101
-------
TABLE C-8. PERCENTAGES OF THE SURFACE RUNOFF, WASTE DRAINAGE,
AND EVAPOTRANSPIRATION TO THE AVERAGE ANNUAL
PRECIPITATION FOR VARIOUS SOIL TEXTURES
No.
1
2
3
4
5
6
7
8
9
10
11
12
Soil textures
Sand/sand
Sand/sandy loam
Sand/loam
Sand/sandy clay loam
Sand/clay
Sandy loam/loam
Sandy loam/sandy clay loam
Sandy loam/clay
Loam/sandy clay loam
Loam/clay
Sandy clay loam/clay (non)
Sandy clay loam/clay
Surface
runoff
percent
16.7
16.7
16.7
16.7
16.1
15.8
15.8
15.2
15.3
14.6
14.5
23.1
Waste
drainage Evapotranspiration
percent percent
14.7
14.8
14.4
14.9
14.8
13.8
14.4
14.2
12.6
12.5
13.7
5.1
68.1
68.0
68.4
68.0
67.9
69.9
69.4
69.3
71.6
71.6
70.6
69.8
soil water to levels approaching the storage limit by the precipitation later
in the year. Waste drainage, which is dependent on the level of soil water,
is sensitive to the precipitation rate as well as the effect of soil texture
on percolation.
To illustrate relationships on a daily basis as well as to evaluate the
time lag of waste drainage for the different soil textures, the first 4
months of 1978 were selected for detailed analysis. Table C-9 shows the
waste drainage as a function of time and displays precipitation data for the
first 114 days of 1978. Waste drainage was zero after 114 days (continuing
through summer and early fall) for all cases except the sandy clay loam -
vegetative soil and the clay (compacted) - barrier soil. This occurred be-
cause of the increased evapotranspiration following the start of the growing
season on day 92.
The waste drainage output will be evaluated first, for those conditions
without a barrier soil of clay and second, for those conditions with a
102
-------
TABLE C-9. AMOUNT OF WASTE DRAINAGE AND PRECIPITATION
AS A FUNCTION OF TIME AND SOIL TEXTURE
(VS = vegetative soil, BS = barrier soil, comp = compacted)
1
2
5
7
8
12
13
14
15
16
17
19
20
21
24
25
26
28
31
36
44
47
49
51
52
53
0.03
0.02
0.45
0.43
1 32
0.08
0.06
0.02
0 02
0.35
0.31
0.04
0 18
0.01
0 22
0.09
0.31
0.01
0.01
0.04
0.13
0.03
0.03
0.01
0.02
0.02
vs-s vs-s vs-s vs-s vs-s
BS-S BS-SL BS-L BS-SCL BS-C
0.1854 0 1854 0.1853 0.1853 0.1013
0.3103 0.3103 0.3103 0 3103 0.2426
0.5476 0.5476 0.5476 0.5476 0 3814
0 3052
0 0264 0.0264 0 0264 0.0264 0.0172
0.0086
0 0034
0.2733 0 2733 0.2733 0.2733 0.1466
0.2519 0,2519 0.2519 0.2519 0.2119
0.1448
0.1480 0.1480 0.1480 0.1480 0 0931
0.0474
0.1326 0.1326 0.1326 0.1326 0.0984
0.0656 0.0656 0 0656 0 0656 0 0738
0.2504 0.2504 0 2504 0.2504 0 1673
0. 1191
0 0175
0 0006
VS-SL VS-SL VS-SL
BS-L BS-SCL BS-C
0 1851 0 1851 0.1012
0. 3114 0.3114 0.2431
0 5476 0.5476 0.3816
0.3503
0.0264 0 0264 0 0173
0 0086
0.0034
0.2735 0 2735 0 1467
0.2519 0 2519 0.2120
0 1448
0.1480 0.1480 0.0932
0.0475
0 1329 0. 1329 0.0986
0.0656 0.0656 0 0739
0 2504 0.2504 0.1674
0.1191
0.0175
0 0006
BS-SCL BS-C
0 1763 0.0965
0.3085 0.2380
0.5476 0 3805
0 3G47
0 0264 0.0173
0.0086
0.0034
0 2729 0. 1464
0.2519 0.2118
0. 1447
0.1479 0 0931
0.0475
0.1320 0.0980
0.0656 0 0736
0 2504 0 1673
0 1190
0 0175
0 0006
&S-C
u 1019
0 2439
0. 3818
0 3054
0 0173
0.0086
0 0034
0 1467
0.2120
0 1448
0 0932
0 0475
0 0986
0 0739
0. 1674
0 1191
0 0175
0. 0006
VS-SCI
BS-C -Comp
0 0631
0 0115
0 0394
0 OT90
0 0187
0 0698
0 0170
0 0166
0 0162
0 0211
0 0187
0 0360
0 0200
0 0187
0 0561
0 018'
0 020~
0 0369
0 05 lf»
0 0766
0 1036
0 0337
0 0211
0 0200
0 0096
0 1X194
103
-------
59
60
61
62
66
67
70
71
72
73
75
79
81
82
83
84
91
93
94
96
99
101
108
109
110
113
114
0.03
0.02
0.17
0.11
0.08
0.24
0.19
0.06
0.05
0.49
0.04
0.20
0.05
0.11
0.57
0.02
0.02
0.01
0.06
0.34
0.01
0.26
1.03
0.04
0.08
0.40
0.20
VS-S VS-S VS-S VS-S VS-S
BS-S BS-SL BS-L BS-SCL BS-C
0.1565 0.1565 0.1565 0.1565 0.0832
0.0634
0.0098
0.001
0.2845 0.2845 0.2845 0.2845 0.1513
0.0819
0.0513
1st day of growing season
0.0268 0.0268 0.0268 0.0268 0.0143
0.0077
0.0031
0.0016
VS-SL VS-SL VS-SL VS-L VS-L VS-SCL VS-SCL
BS-L BS-SCL BS-C BS-SCL BS-C BS-C BS-C-Comp
0.0516
0.0078
0.0076
0.0074
0.0274
0.0059
0. 0150
0.0041
0.0037
0.0377 0.0377 0.0201 0.0258 0.0137 0.0111 0.0045
0.0153 0.0105 0.0085 0.0102
0 0024 0.0016 0.0013 0.0198
0. 0082
0.0036
02798 0.2798 0.1488 0.2689 0.1430 0.1496 0.0104
0.0806 0.0774 0.0801 0.0127
0.0506 0.0484 0.0507 0.0803
0. 0204
0. 0098
0.0189
0.0266
0.0166
0.0516
0.0063
0. 0058
0.0147
0.0040
104
-------
barrier soil of clay. The waste drainage characteristics of the barrier
soils without clay demonstrate that leachate production occurs on a day of
heavy precipitation. As these soil textures have relatively high hydraulic
conductivities, water percolates within the 24-hour period and rapidly ap-
pears as waste drainage. Even though some of the hydraulic conductivities
are 60 times as large as others (sand equals 5.4 in./hr and sandy clay loam
0.084 in./hr) all waste drainage is completed within the 24-hour time inter-
val. During the early part of the season, waste drainage is essentially the
same for cases without a clay barrier soil. Some differences begin to show
after the 72nd day resulting from increased evapotranspiration as solar ra-
diation and temperature increases. After the growing season starts on the
92nd day, increased evapotranspiration causes the waste drainage to go to
zero except for the sand vegetative soil layers where the available water
capacity has reduced to a level unavailable to plants.
Secondly, to be considered is the output from those cases with a barrier
soil of clay. The low hydraulic conductivity (0.022 in./hr) results in per-
colation that exceeds the 24 hour model time period. From days 5 through 36,
waste drainage occurred continually for all clay barrier soils. In compari-
son, nonclay barrier soils had five events during the 31-day time period when
no waste drainage occurred. Also, the peak values of waste drainage for clay
barrier soils was not as high as nonclay barrier soils.
The waste drainage is virtually identical for clay barrier soils which
was a similar relation noted for nonclay barrier soils. When the clay bar-
rier soil was compacted and the hydraulic conductivity was lowered to 0.0011
in./hr, the percolation continued through the first 125 days although at a
greatly reduced rate and magnitude (1.2452 inches of leachate in 117 days for
the compacted clay barrier soil and 2.5909 inches of leachate in 117 days for
the noncompacted clay barrier soil). The time lag on percolation was great
enough to provide leachate through the dry period, from day 36 through 72.
Figure C-26 shows the time lag for the three extreme soil texture com-
binations. While some correlation of peak waste drainage is shown, the re-
duced magnitude and time lag effect is readily apparent.
105
-------
vs-s -
BS-S
^VS-SLC
BS-C I COM PI
A,
\v.
50
DAYS
Figure C-26. Waste drainage as related to time in days for
various soil textures (V = vegetative soil,
BS = barrier soil, comp = compacted).
106
-------
SUMMARY OF SENSITIVITY STUDY
In summarizing the sensitivity study performed, Table C-10 was con-
structed from the results. It demonstrates the relative effect of the
changes in the selected parameters on the more salient features of the simu-
lation. However, it should be noted that the study was for a particular area
in or near Cincinnati, Ohio. The responses shown may change somewhat for
hazardous and solid waste sites with radically different climatological and
hydrological data sets.
The general summarization of the sensitivity study conclusions are pre-
sented as follows:
1. Waste drainage and evapotranspiration are significantly affected by
changes in the soil-water storage and the available water capacity.
2. The winter cover factor is seasonally dependent and directly affects
sensitivity of the evapotranspiration.
3. The SCS curve number primarily affects the surface runoff and
secondarily affects both the evapotranspiration and the waste
drainage.
4. The impermeable liner only affects water that has percolated past
where there is control by evapotranspiration and surface runoff.
5. The surface runoff was the most sensitive parameter when varying the
barrier soil depth.
6. The effects of the LAI are seasonally dependent and the parameters
most sensitive to changes in LAI were evapotranspiration and waste
drainage.
7. The primary parameters affected by the barrier soil compaction were
waste drainage and surface runoff.
8. Changes in soil texture are highly time dependent and produce condi-
tions where other parameters are very sensitive.
107
-------
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-------
APPENDIX D
OPERATION OF COMNET* COMPUTER SYSTEM
1. Turn on data terminal.
2. Dial appropriate telephone number given in Table D-l.
3. Put telephone handle in handset muff (or depress telephone line button).
4. Wait for green light to come on (on line), then press RETURN key.
5. You type: WCCTSO (press RETURN key)-t
6. The computer system types:
TSO SYSTEM AT COMNET - ENTER LOGON -
You type on the same line
LOGON (identification number)/Password (press RETURN key)
7. The computer system types:
READY
You type:
RUNHYDRO (press RETURN key)
8. At this point, the program prints a heading and begins to ask questions.t
9. When program is finished, you type:
LOGOFF (press RETURN key) or repeat step 7 for reruns.
* Computer Network Corporation (COMNET).
t To correct typing error use the BACKSPACE key.
t There are no input prompts.
109
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TABLE D-l. TELEPHONE NUMBERS NEEDED TO LOG ON
THE COMNET COMPUTER SYSTEM
State
Alabama
California
Colorado
Connecticut
Dist. of Col.
Georgia
Illinois
Louisiana
Massachusetts
Michigan
Missouri
Nevada
New York
Ohio
Pennsylvania
North Carolina
South Carolina
Tennessee
Texas
Washington
City*
Montgomery
San Francisco
Denver
Wethersf ield
Washington
Athens
Atlanta
Chicago
New Orleans
Boston
Grosse lie
Kansas City
Las Vegas
New York
Cincinnati
Philadelphia
Raleigh/Durham
Columbia
Nashville
Dallas
Seattle
Telephone
(205)
(415)
(303)
(203)
(202)
(404)
(404)
(312)
(504)
(617)
(313)
(816)
(702)
(212)
(513)
(215)
(919)
(803)
(615)
(214)
(206)
277-9390
546-1395
837-0843
529-3378
966-9510
549-3882
873-6431
663-1640
566-0041
742-0420
675-8936
474-3540
736-1988
962-7943
751-5800
925-4407
541-2000
256-1018
244-8020
651-1723
682-6456
•- Other cities (800) 424-3690.
110
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COST BREAKUP FOR THE COMNET-TSO SYSTEM
1. There are two cost parameters associated with the Computer Network
Corporation Time Sharing Operation (COMNET/TSO). These are storage
charges and central computer processing costs. There is no connect cost
with the COMNET/TSO system.
2. There are three types of data storage on COMNET/TSO. The public online
disk storage charge is $.00666 per track per day. Private online disk
cost is $1000.00 per pack per month and private mountable disk cost is
$50.00 per pack per month. There is no charge for private disk pack
mounts.
3. COMNET time sharing charges are computed by the TSO Utilization Unit
(TUU) algorithm. The TUU costs are $0.56 per TUU.
Ill ou.t mmiiimiT mmm« off ice mo -757-064/010
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