EPA-600/2-76-043
February 1976
Environmental Protection Technology Series
MODELING PESTICIDES AND NUTRIENTS
ON AGRICULTURAL LANDS
Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Athens, Georgia 30601
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into five series. These five broad
categories were established to facilitate further development and application of
environmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The five series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
This report has been assigned to the ENVIRONMENTAL PROTECTION
TECHNOLOGY series. This series describes research performed to develop and
demonstrate instrumentation, equipment, and methodology to repair or prevent
environmental degradation from point and non-point sources of pollution. This
work provides the new or improved technology required for the control and
treatment of pollution sources to meet environmental quality standards.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/2-76-043
February 1976
MODELING PESTICIDES AND NUTRIENTS ON
AGRICULTURAL LANDS
by
Anthony S. Donigian, Jr.
Norman H. Crawford
Hydrocomp, Incorporated
Palo Alto, California 94304
Research Grant No. R803116-01-0
Project Officer
George W. Bailey
Environmental Research Laboratory
U.S. Environmental Protection Agency
Athens, Georgia 30601
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
ENVIRONMENTAL RESEARCH LABORATORY
ATHENS, GEORGIA 30601
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DISCLAIMER
This report has been reviewed by the Environmental Research
Laboratory, U.S. Environmental Protection Agency, and approved
for publication. Approval does not signify that the contents
necessarily reflect the views and policies of the U.S. Environ-
mental Protection Agency, nor does mention of trade names or
commercial products constitute endorsement or recommendation
for use.
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ABSTRACT
Modifications, testing, and further development of the Pesticide Transport
and Runoff (PTR) Model have produced the Agricultural Runoff Management
(ARM) Model presented in this report. The ARM Model simulates runoff,
snow accumulation and melt, sediment loss, pesticide-soil interactions,
and soil nutrient transformations. The Model is capable of simulating
sediment, pesticide, and nutrient content of runoff from small
agricultural watersheds. The report discusses the major modifications to
and differences between the PTR and the ARM Models. Detailed presentation
of an energy-balance method of snow simulation, and a first-order
transformation approach to nutrient modeling are included. Due to lack of
data, the nutrient model was not tested with observed data; testing and
refinement are expected to begin in the near future.
Instrumented watersheds in Georgia provided data for testing and
refinement of the runoff, sediment and pesticide portions of the ARM
Model. Comparison of simulated and recorded values indicated good
agreement for runoff and sediment loss, and fair to good agreement for
pesticide loss. Pesticides which are transported only by sediment
particles were simulated considerably better than pesticides which move
both in solution and on sediment. These results indicate the need for
further study of methods to simulate those pesticides which are
transported by both mechanisms. A sensitivity analysis of the ARM Model
parameters demonstrated that soil moisture and infiltration, land surface
sediment transport, pesticide-soil interactions, and pesticide degradation
are the critical mechanisms in simulating pesticide loss from agricultural
watersheds. Recommendations are included for (1) additional research on
these mechanisms, (2) modification of the ARM Model to simplify
application and use, and (3) demonstration of the use of the ARM Model in
agricultural land planning and management.
This report was submitted in fulfillment of Research Grant No.
R803116-01-0 by Hydrocomp, Incorporated under the sponsorship of the
Environmental Protection Agency. Work completed as of September 1975.
m
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CONTENTS
Page
Abstract iii
List of Figures vi
List of Tables x
Acknowledgments xiii
Sections
I Conclusions 1
II Recommendations 3
III Introduction 5
IV The Agricultural Runoff Management (ARM) Model ... 8
V Snow Accumulation and Melt Simulation 29
VI Nutrient Modeling 41
VII Data Collection and Analysis Programs 63
VIII ARM Model Testing and Simulation Results 68
IX Sensitivity Analysis 112
X Conclusions and Recommendations 126
XI References 130
XII Appendices 135
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FIGURES
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
ARM Model Structure and Operation
Assumed Soil Depths for Pesticide and
Nutrient Storages
Pesticide and Nutrient Movement in the ARM Model .
LANDS Simulation
Infiltration Capacity and Areal Source-Zone Functions
Comparison of Land Cover Algorithms in the
PTR and ARM Models
Adsorption/Desorption Algorithms in the ARM Model
Snow Accumulation and Melt Processes
Snowmelt Simulation
Nitrogen Cycle
Phosphorus Cycle
Nutrient Transformations in the ARM Model ....
Experimental Watersheds in Georgia
Experimental Watersheds in Michigan
PI Watershed, Watkinsville, Georgia
P3 Watershed, Watkinsville, Georgia
1973 Monthly Rainfall, Runoff, and Sediment Loss
for the PI Watershed
1973 Monthly Rainfall, Runoff, and Sediment Loss
for the P3 Watershed
Page
9
11
. 12
. 14
17
22
. 25
30
33
43
44
50
. 65
. 67
. 69
70
71
72
VI
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FIGURES (Continued)
No.
19 Runoff and Sediment Loss from the PI Watershed
on May 28 (a.m.), 1973 76
20 Runoff and Sediment Loss from the PI Watershed
on June 6, 1973 77
21 Runoff and Sediment Loss from the PI Watershed
on June 13, 1973 78
22 Runoff and Sediment Loss from the PI Watershed
on June 21, 1973 79
23 Runoff and Sediment Loss from the PI Watershed
on September 9, 1973 80
24 Runoff and Sediment Loss from the P3 Watershed
on May 28 (a.m.), 1973 81
25 Runoff and Sediment Loss from the P3 Watershed
on June 6, 1973 82
26 Runoff and Sediment Loss from the P3 Watershed
on July 8, 1973 83
27 Runoff and Sediment Loss from the P3 Watershed
on July 14, 1973 84
28 Runoff and Sediment Loss from the P3 Watershed
on September 9, 1973 85
29 Monthly Paraquat Loss from the PI and P3 Watersheds
for the 1973 Growing Season 90
30 Paraquat Loss from the PI Watershed on June 13, 1973 . 92
31 Paraquat Loss from the PI Watershed on June 21, 1973 . 93
32 Paraquat Loss from the PI Watershed on
September 9, 1973 94
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FIGURES (Continued)
No.
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Paraquat Loss from the P3 Watershed on July 8, 1973 .
Paraquat Loss from the P3 Watershed on July 14, 1973
Paraquat Loss from the P3 Watershed on
September 9, 1973
Monthly Diphenamid Loss from the PI and P3
Watersheds for the 1973 Growing Season ....
Diphenamid Loss on Sediment from the PI Watershed
on June 13, 1973
Diphenamid Loss in Water from the PI Watershed
on June 13, 1973
Diphenamid Loss on Sediment from the PI Watershed
on June 21 , 1973
Diphenamid Loss in Water from the PI Watershed
on June 21 , 1973
Diphenamid Loss on Sediment from the P3 Watershed
on July 8, 1973
Diphenamid Loss in Water from the P3 Watershed
on July 8, 1973
Diphenamid Loss on Sediment from the P3 Watershed
on July 14, 1973
Diphenamid Loss in Water from the P3 Watershed
on July 14, 1973
Hydrology Parameter Sensitivity - Total Runoff
Hydrology Parameter Sensitivity - Peak Runoff
Page
95
96
97
100
102
103
104
105
106
107
108
109
115
(PI Watershed, storm of June 21, 1973) ... 116
vi i i
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FIGURES (Continued)
No. Page
47 Sediment Parameter Sensitivity - Total Sediment Loss . 118
48 Sediment Parameter Sensitivity Peak Sediment Loss
(PI Watershed, storm of June 21, 1973) .... 119
49 Pesticide Parameter Sensitivity - Total Pesticide Loss 121
50 Pesticide Parameter Sensitivity - Peak Pesticide Loss
in Water (PI Watershed, storm of June 21, 1973) 122
51 Pesticide Parameter Sensitivity - Peak Pesticide Loss
on Sediment (PI Watershed, storm of June 21, 1973) 123
52 ARM Model Structure and Operation 137
IX
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TABLES
No.
1
I
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
ARM Model Components
Hydrologic Model (LANDS) Parameters
Sediment Production Parameters
Pesticide Simulation Parameters
Snowmelt Parameters
Coupled System of Differential Equations for
Nitrogen Transformations
Coupled System of Differential Equations for
Phosphorus Transformations
Test Watersheds for ARM Model Testing
1973 Summary of Rainfall, Runoff, and Sediment Loss
for the PI Watershed (Recorded and Simulated)
1973 Summary of Rainfall, Runoff, and Sediment Loss
for the P3 Watershed (Recorded and Simulated)
Sequence of Critical Events and Operations on the
PI and P3 Watersheds during the 1973 Growing Season
Monthly Paraquat Loss from the PI and P3 Watersheds
during the 1973 Growing Season
Diphenamid Loss from the PI Watershed during the
1973 Growing Season
Diphenamid Loss from the P3 Watershed during the
1973 Growing Season
Hydrology Parameter Values for the Sensitivity Analysis
Sediment Parameter Values for the Sensitivity Analysis
Page
10
15
20
26
40
51
58
64
73
74
86
91
101
101
113
113
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TABLES (Continued)
No. Page
17 Pesticide Parameter Values for the Sensitivity Analysis 114
18 ARM Model Components 138
19 ARM Model Input Parameter Description 139
20 Calibration Run Output - Monthly Summary (pesticide
simulation) 143
21 Production Run Output - Monthly Summary (pesticide
and nutrient) 144
22 Calibration Run Output Storm Events (hydrology
and sediment simulation only) 147
23 Calibration Run Output Storm Events (pesticide
simulation) 148
24 Calibration Run Output Storm Events (nutrient
simulation) 149
25 Production Run Output - Daily Printout (pesticide
simulation) 150
26 Meteorologic Data Input Sequence and Attributes . . . 152
27 Input Sequence for the ARM Model 154
28 ARM Model Parameter Input Sequence and Attributes
(excluding nutrient parameters) 155
29 ARM Model Nutrient Parameter Input Sequence and
Attributes 159
30 Sample Input and Format for Daily Meteorologic Data . 170
31 ARM Model Precipitation Input Data Format 171
32 Daily Snowmelt Output (Calibration Run, English Units) 172
XI
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TABLES (Continued)
No. Page
33 Daily Snowmelt Output Definitions (Calibration
Run, English Units) 173
34 ARM Model Output Heading (excluding nutrients) . . . 174
35 Nutrient Simulation Output Heading 176
36 PI and P3 Watershed Parameters 180
xi i
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ACKNOWLEDGEMENTS
Many people and organizations were instrumental to the successful
completion of this project. Dr. George W. Bailey, and his staff at the
EPA Environmental Research Laboratory in Athens, Georgia (ERL-Athens),
provided coordination, data, and assistance critical to the project work.
The ERL-Athens sponsored cooperative agreements for data collection and
analysis programs with the USDA Southern Piedmont Conservation Research
Center (SPCRC) in Watkinsville, Georgia and the Michigan State University
Departments of Crop and Soil Science, and Entomology in East Lansing,
Michigan. Dr. Ralph Leonard and his staff at the SPCRC were responsible
for the watershed instrumentation and runoff sampling program in Georgia,
and provided assistance for hydrologic and sediment data analysis and
interpretation. The Michigan program was operated by Dr. Boyd G. Ellis
and his staff at MSU who supplied watershed information, meteorologic
data, and historical data for calibration purposes. The individual staff
members of all these supporting programs are too numerous to mention
without the possibility of omission; their dedication to the program and
their assistance to Hydrocomp is gratefully acknowledged.
Numerous individuals at Hydrocomp contributed to this project throughout
its duration. Dr. Norman H. Crawford, as principal investigator, provided
the general direction of the research effort. Mr. Anthony Donigian, Jr.,
project manager, supervised the project work and the final report.
Calibration, model development, and programming were ably performed by Mr.
Douglas C. Beyerlein and Mr. James Hunt; Mr. Hunt was singularly
responsible for the nutrient model development and wrote the corresponding
section of the final report. Data analysis and technical assistance were
provided by Mr. Howard Yamaguchi, Mr. John C. Imhoff, and Ms. Danielle
Wellander. Mrs. Margaret Muller patiently performed artistic and
graphical consultation, and supplied drafting expertise. Clerical
assistance and support throughout the project was provided by Ms. Suzi
Cummins and Ms. Donna D'Onofrio.
xm
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SECTION I
CONCLUSIONS
(1) The Agricultural Runoff Management (ARM) Model has been used
successfully for simulating runoff, sediment, and pesticide loss from
small agricultural watersheds. Model testing for sediment and
pesticide loss has been performed on watersheds in the Southern
Piedmont and is presently underway on watersheds in the Great Lakes
region.
(2) The simulation of surface runoff with the ARM Model has been verified
by split-sample testing for the Southern Piedmont watersheds. The
hydrology parameters calibrated on six months of 1972 data allowed
the Model to simulate 1973 data with reasonable accuracy. Past
experience with the hydrologic simulation methodology indicates that
similar accuracy can be expected in other geographical regions.
(3) The method of snowmelt simulation presented in this report has been
employed successfully on watersheds across the United States.
Although its use on small agricultural watersheds has been limited,
the methodology of energy balance calculations is conceptually valid.
Calibration and testing is presently underway on watersheds in the
Great Lakes region.
(4) Tillage operations and practices have a significant impact on both
surface runoff and sediment loss from watersheds in the Southern
Piedmont. The effect is relatively greater on sediment loss than on
surface runoff and tends to decrease with time since the last tillage
operation. Both total sediment loss and peak sediment concentrations
are increased by frequent tillage operations while peak runoff is
generally reduced and delayed in time.
(5) The ARM Model simulation of sediment production is relatively
accurate except for storms immediately following tillage operations.
In general, monthly sediment loss and storm concentrations are close
to observed values when the hydrologic simulation is accurate. The
sediment simulation methodology allows for the inclusion of tillage
operations, but further testing and calibration are needed to more
reliably quantify tillage effects.
(6) Simulation of pesticide loss from the Southern Piedmont watersheds
with the ARM Model indicates the following:
a. Simulation results are good for pesticides like paraquat that are
completely adsorbed onto sediment particles. In these cases, the
accuracy of the pesticide simulation is directly dependent upon
the accuracy of the sediment simulation.
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b. Simulation of pesticides that move both in water and on sediment
is dependent upon the partitioning between the two phases (water
and sediment) as specified by the adsorption/desorption function.
Simulation results for this type of pesticide (e.g. diphenamid)
using laboratory isotherm data is fair to poor. Initial
comparison of simulation results from single-valued (SV) and
non-single-valued (NSV) adsorption/desorption functions is
inconclusive. The SV function appears to simulate some storms
better than the NSV function, but the reverse is true for other
storms. Further comparisons and evaluations are warranted.
c. Pesticide attenuation processes are critical to the simulation of
pesticide loss since they determine the amount of pesticide
available for transport from the land surface. Storms, even
minor ones, occurring immediately or soon after pesticide
application are the major events for pesticide loss. The applied
pesticide has not attenuated to a significant extent; thus, it is
highly susceptible to transport. The first order degradation
rate presently used in the ARM Model appears to underestimate
attenuation at the beginning of the growing season and
overestimate it at the middle and end of the growing season.
Accurate simulation of pesticide attenuation would provide a more
valid base for the evaluation of adsorption/desorption functions
and improvement of the overall pesticide simulation.
(7) The ARM Model provides a structure for simulating the transport and
soil transformations of plant nutrients. Testing and comparison of
simulated and observed results will provide a basis for modification
and refinement of the nutrient algorithms presented in this report.
Data from the Southern Piedmont and Great Lakes watersheds is expected
to be available for nutrient model testing in the near future.
(8) A sensitivity analysis of the ARM Model parameters for hydrology,
sediment production, and pesticide loss indicates that the most
sensitive parameters are related to soil moisture and infiltration,
land surface sediment transport, pesticide-soil interactions, and
pesticide degradation. These mechanisms are the critical ones for the
accurate simulation of pesticide loss from agricultural watersheds.
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SECTION II
RECOMMENDATIONS
(1) Application and testing of the ARM Model on watersheds in different
regions of the country is of primary concern at this time. The
hydrologic methodology of the ARM Model has demonstrated its general
applicability from the results of testing on hundreds of watersheds;
similar testing is needed for the sediment production methodology.
In this way, the simulation of the transport mechanisms (runoff and
sediment loss) for agricultural pollutants can be tested, refined,
and verified for general application. Moreover, the relationship of
the ARM Model parameters to climatic and edaphic characteristics
could be investigated.
(2) Testing of the nutrient model is crucial to the reliable simulation
of plant nutrients. Although a nutrient model has been developed,
only testing and comparison with observed data can indicate the
validity of the model assumptions and the need for model refinements.
(3) The impacts of different agricultural management techniques on the
transport mechanisms of runoff and sediment loss need to be further
investigated. Since the ARM Model will be applied to managed
agricultural lands, the relationships between land management
techniques and the ARM Model parameters must be established. This is
a necessity if the Model is to be used for evaluating the efficacy of
land and agricultural management plans. Also, for widespread use,
the Model must accommodate practices employed in different
agricultural regions of the country.
(4) Pesticide-soil interactions and pesticide attenuation processes must
be further investigated in order to improve the accuracy and
reliability of the pesticide simulation. Both the single-valued and
non-single-valued adsorption/desorption functions warrant further
investigation, in addition to a kinetic, or non-equilibruim, approach
to the pesticide-soil interaction processes. First-order pesticide
degradation should be replaced with a more sophisticated degradation
model. Various candidate approaches are presently under
investigation. Environmental conditions (e.g. soil temperature, soil
moisture, and oxygen content) need to be included where they are
significant.
(5) To promote the general use of the ARM Model for investigation,
evaluation, and management of agricultural runoff, the following
recommendations are extended:
a. The ARM Model structure should be modified to allow a
more user-oriented method of application. The acceptance and
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use of the ARM Model by the user community is contingent upon
the ease of Model application, calibration, parameter
evaluation, data management, and output interpretation. To
date, Model development has concentrated on the testing and
evaluation of algorithms to simulate the physical processes.
Efforts should now be directed to the goal of making the
Model more amenable for use by potential users.
b. The use of the ARM Model as a tool for the planning and
evaluation of agricultural management techniques for the
control of sediment, pesticides, and nutrients should be
demonstrated. It is insufficient to develop and document a
model like the ARM Model without a clear demonstration of its
potential application in the planning and management process.
In addition, recommendations, guidelines, and a proposed
methodology should be developed to insure the effective
use and to avoid misuse of the ARM Model.
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SECTION III
INTRODUCTION
MODELING PROGRAM
The development of models to simulate the water quality impact of nonpoint
source pollutants is receiving considerable attention by the engineering
and scientific community. One of the major reasons for this interest was
the passage of the Federal Water Pollution Control Act Amendments of 1972,
specifically requiring the evaluation of the contribution of nonpoint
source pollution to overall water quality. This report describes a
modeling effort whose goal is the simulation of water quality resulting
from agricultural lands. The beginnings of this research modeling effort
date from 1971 when the U.S. Environmental Protection Agency, through the
direction of the Environmental Research Laboratory in Athens, Georgia
(ERL-Athens), sponsored the development and initial testing of the
Pesticide Transport and Runoff (PTR) Model.1 The Agricultural Runoff
Management (ARM) Model presented in this report is the combined result of
further model testing and refinement, algorithm modifications, and
inclusion of additional capabilities not present in the PTR Model.
Moreover, the ultimate goal of the continuing ARM Model development effort
is the establishment of a methodology and a tool for the evaluation of the
efficacy of management practices to control the loss of sediment,
pesticides, nutrients, and other nonpoint pollutants from agricultural
lands. The present version of the Model, presented in this report, is a
'snapshot' of the ARM Model in its testing and refinement process. When
recommended for public use, the final ARM Model will be a tool for
evaluating the water quality impact of agricultural management practices.
MODELING PHILOSOPHY
The guiding philosophy of the modeling effort is to represent, in
mathematical form, the physical processes occurring in the transport of
nonpoint source pollutants. The hydrologic and water quality related
processes occurring on the land surface (and in the soil profile) are
continuous in nature; hence, continuous simulation is critical to the
accurate representation of these physical processes. Although nonpoint
source pollution from the land surface takes place only during
runoff-producing events, the status of the soil moisture and the pollutant
prior to the event is a major determinant of the amount of runoff and
pollutants that can reach the stream during the event. In turn, the soil
moisture and pollutant status prior to the event is the result of
processes which occur between events. Cultivation and tillage practices,
pesticide and fertilizer applications, pesticide degradation and nutrient
transformations, all critically affect the mass of pollutant that can
enter the aquatic environment during a runoff-producing event. Models
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that simulate only single events cannot accurately evaluate agricultural
land management practices since between-event processes are ignored.
Although all between-event processes cannot be quantitatively described at
the present state of technology, continuous simulation provides a sound
framework for their approximation and for further research into their
quantification.
When modeling nonpoint source pollution, the above stated philosophy is
joined by the fact that the transport mechanisms of such pollutants are
universal. Whether the pollutants originate from pervious or impervious
lands, from agricultural or urban areas, or from natural or developed
lands, the major transport modes of runoff and sediment loss are
operative. (Uind transport may be significant in some areas, but its
importance relative to runoff and sediment loss is usually small.) In this
way, the simulation of nonpoint source pollution is analogous to a
three-layered pyramid. The basic foundation of the pyramid is the
hydrology of the watershed. Without accurate simulation of runoff,
modeling nonpoint pollutants is practically impossible. Sediment loss
simulation, the second layer of the pyramid, follows in sequence the
hydrologic modeling. Although highly complex and variable in nature,
sediment modeling provides the other critical transport mechanism. The
pinnacle or final layer of the pyramid is the interaction of various
pollutants with sediment loss and runoff, resulting in the overall
transport simulation of nonpoint source pollutants.
The general goals of the research effort described in this report are (1)
to utilize the most advanced state of present technology in the simulation
of nonpoint source pollutants, and (2) to delineate critical areas for
further research and investigation. In addition, the final version of the
ARM Model will be designed for general applicability throughout the United
States and for use by state and local agencies for the water quality
evaluation of agricultural land management practices.
REPORT CONTENTS AND FORMAT
As stated previously, this report describes the progress of the continuing
ARM Model development work. Further testing and refinement of Model
algorithms is in progress at the present time; thus, this report provides
a detailed look at the existing version of the Model and a glimpse at
projected future modifications. The major differences between the present
ARM Model and its predecessor, the PTR Model, are as follows:
(1) Modifications of the input and output (I/O) procedures
(2) Modifications to the sediment model, SEPT, algorithms
(3) Option to utilize non-single-valued adsorption-desorption
function
(4) Simulation capability for snow accumulation and melt
(5) Simulation capability for plant nutrients (not tested
on observed data).
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In order to prevent a duplication of material presented in the PTR Model
report,1 this report will be restricted to an explanation of the major
modifications listed above and a presentation of the results of testing
the ARM Model on new data. However, some duplication is necessary in
order to provide a cohesive presentation. The reader will be referred to
the PTR Model report for elaboration of material summarized here.
Modifications to the I/O procedures will be described in the User Manual
(Appendix A) along with a complete explanation of Model operation and use.
Section IV provides a brief description of the overall ARM Model
structure, including modifications to the sediment model and the addition
of the non-single-valued adsorption/desorption option. Since major
efforts were devoted to addition of the snow accumulation and melt routine
and development of the plant nutrient model, Section V and Section VI
describe the respective physical processes and algorithms. Following a
brief presentation of the companion data collection programs in Section
VII, the results of Model testing are presented in Section VIII. A
sensitivity analysis of Model parameters is reported in Section IX.
Finally, Section X summarizes the overall conclusions and recommendations.
The appendices include a brief user manual, a sample input listing, and a
source code of the ARM Model.
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SECTION IV
THE AGRICULTURAL RUNOFF MANAGEMENT (ARM) MODEL
The ARM Model simulates runoff (including snow accumulation and melt),
sediment, pesticides, and nutrient contributions to stream channels from
both surface and subsurface sources. No channel routing procedures are
included. Thus, the Model is applicable to watersheds that are small
enough that channel processes and transformations can be assumed
negligible. Although the limiting area will vary with climatic and
topographic characteristics, watersheds greater than one to two square
miles are approaching the upper limit of applicability of the ARM Model.
Channel processes will significantly affect the water quality resulting
from larger watersheds.
Figure 1 demonstrates the general structure and operation of the ARM Model
The major components of the Model individually simulate the hydrologic
response (LANDS) of the watershed, sediment production (SEDT), pesticide
adsorption/desorption (ADSRB), pesticide degradation (DEGRAD), and
nutrient transformations (NUTRNT). The executive routine, MAIN, controls
the overall execution of the program; calling subroutines at proper
intervals, transferring information between routines, and performing the
necessary input and output functions. Table 1 describes the functions of
each of the ARM Model components.
In order to simulate vertical movement and transformations of pesticides
and nutrients in the soil profile, specific soil zones (and depths) are
established so that the total soil mass in each zone can be specified.
Total soil mass is a necessary ingredient in the pesticide
adsorption/desorption reactions and nutrient transformations. Figure 2
depicts the zones and depths, assumed in the ARM Model. The depths of the
surface and upper soil zones are specified by the model input parameters,
SZDPTH and UZDPTH, respectively. The upper zone depth corresponds to the
depth of incorporation of soil-incorporated chemicals. It also indicates
the depth used to calculate the mass of soil in the upper zone whether
agricultural chemicals are soil-incorporated or surface applied. The
depths of the surface and lower zones are important because the active
surface zone is crucial to the washoff and degradation of agricultural
chemicals, while the extent of the lower zone determines to what degree
soluble pollutants will contaminate the groundwater. The zonal depths
will vary with the geology and topography of the watershed. Although the
relative specification of the soil depths indicated in Figure 2 is
reasonable, further evaluation of these zones is presently in progress.
The transport and vertical movement of pesticides and nutrients, as
conceived in the ARM Model, is indicated in Figure 3. Pollutant
8
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ARM Model structure and operation
INPUT
OUTPUT-«-
MAIN
EXECUTIVE
PROGRAM
LANDS
HYDROLOGY
AND SNOW
SEDT
SEDIMENT
PRODUCTION
-*-CHECKR CHECK INPUT SEQUENCE
-»-NUTRlO READ NUTRIENT INPUT
--OUTMON OUTYR OUTPUT SUMMARIES
PEST
NUTRNT
NUTRIENT TRANSFORMATION
AND REMOVAL
YtS
yes
NUTR *-
ADSRB
PESTICIDE ADSORPTION
AND REMOVAL
DEGRAD
PESTICIDE
DEGRADATION
Figure 1
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Table 1. ARM MODEL COMPONENTS
Major
Program
MAIN
Component
Subroutine
LANDS
SEDT
ADSRB
DEGRAD
NUTRNT
CHECKR
BLOCK DATA
NUTRIO
OUTMON
OUTYR
DSPTN
TRANS
Function
Master program and executive control
routine
Checks input parameter errors
Data initialization for common
variables
Reads and checks nutrient input data
Prints -monthly output summaries
Prints yearly output summaries
Performs hydrologic simulation and
snowmelt calculations
Performs sheet erosion simulation
Performs pesticide soil adsorption/
desorption simulation
Performs desorption calculations
Performs pesticide degradation
simulation
Performs nutrient simulation
Performs nutrient transformations
10
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Assumed soil depths for pesticide and nutrient storage
Isiim NtMMKI ""' *"**'' '"'v' ' :T^.'' SURFACE ZONE
UZDPTH '•:'•:'. ::::::::••: •:•:• •:••:::: •:• -x- •:• •:•::::: :•:•':'•': ':'•': :::::::::>::::::::::::::: :^:^:-:^'^:>^:^:
[[[ ^^.^^^^^ ^^^^ ^^^^
1.83 M : ::;'::.;:;:-:;:'-;:.:./ ;:!:i!i:i:!H:::::iii:::::i:::::;;'i::::" =.:::: '"• ;;" . ;; -;'^r =••-••• :'•' LOWER ZONE
"^"^^^^^^^^^^^^^^^^"""^^^^^^^^^^^^^^18^8^^ GROUNDWATER ZONE
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Pesticide and Nutrient movement in the ARM model
TOTAL UPTAKE
AND DEGRADATION
P/N ON SEDIMENT
PESTICIDE PARTICLES
P/N IN OVERLAND FLOW
IN INTERFLOW
PERCOLATION
UPTAKE AND
DEGRADATION
LOWER ZONE P/N
STORAGE
LOWER ZONE P/N
INTERACTIONS
LOSSES TO GROUNDWATER
KEY
( INPUT )
P-PESTICIDE
N-NUTRIENT
TO
Figure 3
-------
contributions to the stream can occur from the surface zone, the upper
zone, and the groundwater zone. Surface runoff is the major transport
mechanism carrying dissolved chemicals, pesticide particles, or sediment
and adsorbed chemicals. The interflow component of runoff can transport
dissolved pesticides or nutrients occurring in the upper zone. Vertical
chemical movement between the soil zones is the result of infiltrating and
percolating water. From the surface, upper, and lower zones, uptake and
transformation of nutrients and degradation of pesticides is allowed. On
the watersheds tested, the groundwater zone has been considered a sink for
deep percolating chemicals since the groundwater flow contribution has
been negligible. However, on larger watersheds this contribution could be
significant.
HYDROLOGY
To truly comprehend the movement of pesticides and nutrients in the ARM
Model, one must have a basic understanding of the hydrology subprogram,
LANDS. A flowchart of LANDS is shown in Figure 4 (the snowmelt subroutine
will be described in Section V). The mathematical foundation of LANDS was
originally derived from the Stanford Watershed Model2, and has been
presented, with minor variations, in numerous subsequent publications.1-3
For this reason, the algorithms will not be fully described here. The
major parameters of the LANDS subprogram are defined in Table 2, and in
the User Manual (Appendix A). These parameters are identical to those in
the PTR Model and also in the Hydrocomp Simulation Program, HSP3. In
brief, the LANDS subprogram simulates the hydrologic response of the
watershed to inputs of precipitation and evaporation. LANDS simulates
runoff continuously through a set of mathematical functions derived from
theoretical and empirical evidence. It is basically a moisture accounting
procedure on the land surface for water in each major component of the
hydrologic cycle. The parameters (Table 2) within the mathematical
functions are used to characterize the land surface and soil profile
characteristics of the watershed. These parameters must be selected,
tested, and modified when LANDS is applied to a new watershed.
Calibration is the process whereby the parameters are modified as a result
of a comparison of simulated and recorded runoff data for the watershed.
The calibration procedure is described in the User Manual (Appendix A).
Modifications to the Stanford and HSP versions of the LANDS algorithms
have been discussed in the PTR Model Report.1 The present version of
the LANDS subprogram of the ARM Model includes these modifications to
simulate the areal variation in agricultural chemical concentrations on
the land surface. For completeness and clarity, the following section
entitled, "Areal Zone Concept", describing the LANDS modification is
abstracted from the PTR Model Report.
13
-------
LANDS Simulation
/ ACTUAL
ET
POTENTIAL ET
PRECIPITATION
TEMPERATURE
RADIATION
WIND.OEWPOINT
( INPUT >
(" OlJfPUT'>
FUNCTION
| STORAGE |
EVAPOTRANSPIRATION- ET
Figure 4
-------
Table 2. HYDROLOGIC MODEL (LANDS) PARAMETERS
A A fraction representing the impervious area in a
watershed.
EPXM The interception storage parameter, related to vegetal
cover density.
UZSN The nominal upper zone soil moisture storage parameter.
LZSN The nominal lower zone soil moisture storage parameter.
K3 Index to actual evaporation (a function of vegetal
cover).
K24L,
K24EL Parameters controlling the loss of water from
groundwater storage. K24L is the fraction of
groundwater recharge that percolates to deep groundwater
tables. K24EL is the fraction of the segment area
where shallow water tables put groundwater within reach
of vegetation.
INFIL This parameter is a function of soil characteristics
defining the infiltration characteristics of the
watershed.
INTER This parameter defines the interflow characteristics
of the watershed.
L Length of overland flow plane.
SS Average overland flow slope.
NN Manning's "n" for overland flow.
IRC,
KK24 The interflow and groundwater recession parameters.
KV The parameter KV is used to allow a variable recession
rate for groundwater discharge.
15
-------
Area! Zone Concept
The major concern in modifying the HSP LANDS module for pesticide
transport was the desire to accommodate the expected areal variation in
pesticide concentration over the land surface. It is generally accepted
in hydrology that infiltration is time and area dependent. Infiltration
capacity will vary even within small watersheds with reasonably
homogeneous soil characteristics. This areal variation in infiltration
results in source areas, or zones, with low infiltration capacity within
the watershed, contributing a large component of overland flow. Since
overland flow and sediment loss are the major mechanisms of pesticide
transport to the watercourse, the low infiltration source areas will also
experience a greater loss of pesticide than the remainder of the
watershed. Consequently, the pesticide concentration on the land surface
will vary, in spite of an initially uniform application. The pesticide
concentration within the soil profile will also vary as a function of the
volume of infiltration. Obviously, the extent of pesticide areal
variation depends upon the solubility and transport characteristics of the
specific pesticide applied and upon topographic and watershed
characteristics. Natural hydrologic conditions and watershed
characteristics are sufficiently non-uniform to justify the above
described mechanisms leading to areal variations in infiltration and
pesticide concentrations.
HSP LANDS employs a cumulative frequency distribution of infiltration
capacity to account for the areal variation. Figure 5a graphically
presents the infiltration function of HSP LANDS. A mean infiltration
capacity, f, is calculated and a linear approximation to the actual
cumulative distribution is assumed. Interflow is determined as a function
of infiltration and lower zone moisture storage. It is evaluated in
Figure 5a as a second linear cumulative distribution denoted by f(c-l).
Since the X-axis is unity (i.e. 100 percent of watershed area), the area
of each wedge in Figure 5a represents the portion of the moisture supply
allocated to each component. During any time interval, the available
moisture supply is distributed to surface detention, interflow detention,
and infiltration. Overland flow and interflow are determined as losses
from surface detention and interflow detention respectively. Lower zone
moisture storage and groundwater components are derived from the
infiltration component.
The LANDS subprogram of the ARM Model employs the same infiltration
function as HSP LANDS, with one modification; the watershed is divided
into five zones, each representing 20 percent of the total area. The
zonal division is based on infiltration capacity. Schematically, Figure
5b shows that zone 1 will infiltrate much less water than zone 5.
Conversely, zone 5 will provide less overland flow than zone 1. Thus, the
areal variation in infiltration capacity is approximated. Zones with
lower infiltration capacity will serve as the major source areas for
16
-------
Figure 5a. Cumulative frequency distribution of infiltration
capacity showing infiltrated volumes, interflow
and surface detention
INCREMENT
TO SURFACE
'DETENTION
INCREMENT
TO INTERFLOW
DETENTION
- ZONE 1
0 20 40 60 80
% OF AREA WITH INFILTRATION CAPACITY ^ INDICATED VALUE
Figure 5b. Source-zones superimposed on the infiltration
capacity function
Infiltration capacity and areal source-zone functions
Figure 5
17
-------
overland flow, sediment, and pesticide loss. Generally, zones with high
infiltration will contain more pesticide in the soil profile because of
the greater amount of infiltrated water.
Conceptually, the zones are not necessarily concentric, continuous, or
contiguous. Each is connected directly to the stream channel by the
overland flow plane. As with any simulation model, this source zone
concept is an approximation. It is an attempt to portray mechanisms which
are known to occur, but are impossible to simulate in detail.
A full description of the operation and calibration procedures for the
LANDS subprogram is included in the User Manual (Appendix A).
SEDIMENT LOSS SIMULATION
The basis for sediment loss simulation in the PTR Model was derived from
work by Moshe Negev at Stanford University.** Although Negev simulated
the entire spectrum of the erosion process, only sheet and rill erosion
were included in the the PTR Model since gully erosion was not significant
on the small test watersheds, the two component processes of sheet and
rill erosion pertain to (1) detachment of soil fines (silt and clay
fraction) by raindrop impact, and (2) pick-up and transport of soil fines
by overland flow. These mechanisms were represented in the PTR Model by
the following algorithms:
Soil fines detachment:
RER(t) = (1 - COVER(T))*KRER*PR(t)JRER (1)
Soil fines transport:
SER(t) = KSER*SRER(t)*OVQ(t)JSER (2)
ERSN{t) = SER(t)*F (3)
where RER(t) soil fines detached during time
interval t, tonnes/ha
COVER(T) = fraction of vegetal cover as a function of
time, T, within the growing season
KRER = detachment coefficient for soil properties
PR(t) = precipitation during the time interval, mm
JRER = exponent for soil detachment
SER(t) transport of fines by overland flow, tonnes/ha
JSER exponent for fines transport by overland flow
18
-------
KSER = coefficient of transport
SRER(t) = reservoir of soil fines at the beginning
of the time interval, t, tonnes/ha
OVQ(t) = overland flow occurring during the time
interval, t, nun
F = fraction of overland flow reaching the
stream during the time interval, t
ERSN(t) = sediment loss to the stream during the
time interval, t, tonnes/ha
Since the original equations by Negev were designed for simulation on an
hourly basis, the coefficients KSER and KRER were modified to allow 5 and
15 minute simulation. In the operation of the algorithms, the soil fines
detachment (RER) during each interval is calculated by Equation 1 and
added to the total fines storage or reservoir (SRER). Next, the total
fines transport (SER) is determined by Equation 2 and the sediment loss to
the stream (ERSN) is calculated in Equation 3 by the fraction of overland
flow which reaches the stream. A land surface flow routing technique3
determines the overland flow contribution to the stream in each time
interval. After the fines storage (SRER) is reduced by the sediment loss
to the stream (ERSN), the algorithms are prepared for simulation of the
next time interval.
Although the general operation of the algorithms described above is
identical in the ARM Model, certain modifications have been necessary. A
more comprehensive vegetal cover function and an attempt to simulate the
effects of tillage operations have been included. Also, Equation 2 has
been modified to more closely represent the physical process of sediment
transport by overland flow. Table 3 defines the sediment parameters
included in the ARM Model.
The goal of simulating sediment washoff by overland flow is to approximate
the capacity of the flow to transport detached soil fines. Equation 2,
derived from Negev's formulation, actually calculates transport as a
continuous function of the detached fines. If Equation 2 is rearranged as
follows,
JSER
SER(t)/SRER(t) = KSER*OVQ(t) (4)
it becomes obvious that this formulation is calculating the fraction of
detached fines which can be transported in any time interval, regardless
of the physical transport capacity of the overland flow. This is
conceptually incorrect; transport capacity is a function of overland flow,
soil and surface characteristics?'6 As long as the transport capacity
is less than available detached fines, it should be independent of the
fines storage, SRER. Thus, the formulation of Equation 2 in the ARM Model
is
19
-------
Table 3. SEDIMENT PRODUCTION PARAMETERS
COVPMO Fraction of land cover on a monthly basis (12 values).
TIMTIL Time when soil is tilled (Julian day, i.e., day of
the year, e.g., January 1 is 1, December 31 is 365 or
366, etc.), (5 dates).
YRTIL Corresponding year (last two digits only) for TIMTIL
(5 values).
SRERTL Fine deposits produced by tillage corresponding to
TIMTIL and YRTIL (5 values).
JRER Exponent of rainfall intensity in soil splash equation.
KRER Coefficient in soil splash equation.
JSER Exponent of overland flow in sediment washoff equation.
KSER Coefficient in sediment washoff equation.
SRERI Initial detached soil fines deposit.
20
-------
SER(t) = KSER*OVQ(t)JSER (5)
subject to
SER(t) iSRER(t) (6)
Although this remains a simple representation of the complex erosion
process, the formulation is conceptually sound and provides an opportunity
for future improvements. The effects of slope, surface roughness,
rainfall intensity, etc. on transport capacity can be included in this
formulation as required by future testing and research.
The vegetal cover or crop canopy function in the PTR Model required the
input of the maximum vegetal cover attained in the growing season and
dates of application (assumed to coincide with planting), crop maturity,
and harvesting. As shown in Figure 6a, the vegetal cover was assumed to
increase linearly from zero at the time of application (TIMAP) to the
maximum cover fraction (COVMAX) at the time of crop maturity (TIMAT). The
cover remained at the maximum value until harvesting when it returned to
zero. Land cover was assumed to be zero before and after the growing
season. This assumption proves to be invalid to varying degrees on most
agricultural watersheds. Consequently, the land cover algorithm shown in
Figure 6b is used in the ARM Model. Monthly cover values assumed to occur
on the first of the month, are specified by the user. Cover on any day is
determined by linear interpolation between the monthly values. This
algorithm allows greater flexibility than the original PTR Model
algorithm, but additional investigation into plant growth and crop canopy
functions is needed. Various research efforts7i8>9 have related the
concept of leaf area index (LAI) to light interception by a crop canopy.
An analogy between light interception and rainfall interception could lead
to a more precise crop canopy function, if an algorithm for the changes in
LAI (for different crops and cropping patterns) with time could be
developed. Research on this topic by Watson10 and McCollum11 appears
promising. At the present state-of-the-art, the cover function in the ARM
Model is adequate until a more physically representative function can be
developed.
Tillage operations and conservation practices have a major effect on the
sediment loss from an agricultural watershed. Although this is obvious,
the magnitude and mechanism of tillage operations could not be evaluated
with the seven months of data (July 1972-February 1973) available for the
PTR Model development. Minimum tillage practices were followed and
numerous non-runoff-producing events helped to compact the land surface
prior to the first major runoff-producing event. However, during the 1973
growing season several severe storms immediately following tillage and
planting operations (see Section VIII) served to dramatize the need to
21
-------
Figure 6a. Land cover algorithm in the PTR model
TIMAP TIMAT TIMHAR
.75
.50
25
."
5.75
JAN ' FEB ' MAR ' APR ' MAY ' JUN ' JUL ' AUG ' SEP ' OCT ' NOV ' DEC ' a
COVMAX
i r i I i i i i I T r
JAN ' FEB ' MAR ' APR ' MAY ' JUN ' JUL ' AUG ' SEP ' OCT ' NOV ' DEC '
Figure 6b. Land cover algorithm in the ARM model
Comparison of land cover algorithms in the PTR and ARM
models
Figure 6
22
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accommodate tillage operations within the Model structure. With regard to
sediment production, the effect of tillage operations is to increase the
mass of soil fines available for transport and produce a reasonably
uniform distribution of fines across the watershed. , Consequently, the ARM
Model allows the user to specify the dates of tillage, planting, or other
land-surface disturbing operations. For each of these dates the user must
specify a new detached soil fines storage (SRERTL) resulting from the
operation. At the beginning of each tillage day the ARM Model resets the
fines storage in each of the areal zones to the new value, resulting in a
uniform fines distribution across the watershed. The amount of fines
storage produced by different tillage operations is related to the depth
and extent of the operation, and edaphic characteristics. Further study
is needed to develop guidelines for the specification of fines storage as
affected by tillage and other agricultural management operations.
In conclusion, the present version of the sediment loss algorithms of the
ARM Model is a stepping stone on the continuing path of model development.
As additional testing, refinements, and retesting is performed, a greater
understanding of the erosion process and methods for its simulation will
evolve.
PESTICIDE ADSORPTION/DESORPTION SIMULATION
Once the hydrology and sediment production of a watershed have been
simulated, the process of pesticide adsorption/desorption onto sediment
particles is a major determinant of the amount of pesticide loss which
will occur. This process establishes the division of available pesticide
between the water and sediment phases, and thus specifies the amounts of
pesticide transported in solution and on sediment. The algorithm employed
to simulate this process .in the PTR Model was described as follows:
X/M KC(1/N) + F/M (7)
where X/M = pesticide adsorbed per unit soil, yg/gm
F/M = pesticide adsorbed in permanent fixed
state per unit soil. F/M is less than
or equal to FP/M, where FP/M is the
permanent fixed capacity of soil in mg/gm
for pesticide. This can be approximated by
the cation or anion exchange capacity for that
particular soil type.
C = equilibruim pesticide concentration in solution,
mg/1
N = exponent
K = coefficient
23
-------
Basically this algorithm is comprised of an empirical term, F/M, plus the
standard Freundlich single-valued (SV) adsorption/desorption isotherm
(Figure 7a). The empirical term, F/M, accounts for pesticides which are
permanently adsorbed to soil particles and will not desorb under repeated
washing. As indicated in Figure 7a, the available pesticide must exceed
the capacity of the soil to permanently adsorb pesticides before the
adsorption/desorption equilibrium is operative. Thus the pesticide
concentration on soil particles must exceed FP/M before the equilibrium
soil and solution pesticide concentrations are evaluated by the Freundlich
curve. An in-depth description and discussion of the underlying
assumptions is presented in the PTR Model report.1
A major conclusion of the PTR Model development work was that the above
algorithm did not adequately represent the division of pesticides between
the sediment and solution phases. This was especially true for pesticides
which are transported by both sediment and surface runoff, i.e. soluble
pesticides which also adsorb onto soil particles. Research has indicated
that the assumption of single-valued adsorption/desorption (Figure 7a) is
not valid for many pesticides . 12- 13- ^ In these cases, the adsorption and
desorption processes would follow different curves as indicated in Figure
7b. Although a controlled laboratory experiment cannot hope to duplicate
the vagaries of nature present in a field situation, the basic mechanisms
should be similar in both circumstances. Since field data has been
inconclusive, the present version of the ARM Model allows the user to
specify the use of either single-valued (SV) as in Figure 7a or
non-single-valued adsorption/desorption (Figure 7b). Table 4 defines the
pesticide simulation parameters in the ARM Model. The DESORP parameter
indicates the adsorption/desorption function to be used. The NSV
algorithm (Figure 7b) utilizes the above SV algorithm (path No. 1) as a
base from which different desorption curves are calculated. The form of
the desorption curve is identical to Equation 7 except that K and N values
are replaced by K' and N1 respectively. The prime denotes the desorption
process. The user specifies the N1 value as an input parameter (NP), and
the ARM Model calculates K' from the following expression based on work by
Davidson e-t al. 14
, _ (N/N'). (1-N/N1)
(8)
where K1 = desorption coefficient
K = adsorption coefficient
N' desorption exponent
N adsorption exponent
S = solution pesticide concentration prior to
x initiating desorption
When the desorption process is initiated, the maximum attained solution
concentration Smax, is utilized with K, N, and N1 to calculate a value of K'
24
-------
Figure 7a. Single-valued adsorption/desorption algorithm
_FP
M
_L
CJ
<=>
CJ
C£
GO
T
If.
M
J_
1-AOSORPTION
2-DESORPTION
3-NEW ADSORPTION
4-NEW DESORPTION
PESTICIDE SOLUTION CONC. (C) MG/ML
Figure 7b. Non-single-valued adsorption/desorption algorithm
Adsorption/desorption algorithms in the ARM Model
Figure 7
25
-------
Table 4. PESTICIDE SIMULATION PARAMETERS
APMODE Application mode, SURF-surface applied, SOIL-soil
incorporated.
DESORP NO-single-valued adsorption/desorption algorithm used,
YES-non-single-valued adsorption/desorption algorithm used.
SSTR Pesticide application for each block (5 values).
TIMAP Time of pesticide application (Julian day).
YEARAP Year of pesticide application (last two digits only).
CMAX Maximum solubility of pesticide in water.
DD Permanent fixed pesticide adsorption capacity of the soil.
K Coefficient in Freundlich adsorption equation.
N Exponent in Freundlich adsorption equation.
NP Exponent in Freundlich desorption equation.
SZDPTH Depth of the surface zone.
UZDPTH Upper zone depth or depth of soil incorporation.
BULKD Bulk density of soil.
DEGCON First-order pesticide degradation rate.
26
-------
As desorption continues (path No. 2), the Model continues to use the K1
and N' values to calculate the soil and solution concentrations. When
re-adsorption is initiated (path No. 3), the Model follows the desorption
curve back to the junction with the SV adsorption curve, and continues on
this curve until desorption again occurs. At the new occurrence of
desorption, a new K1 is calculated resulting in a new desorption curve
(path No. 4). The process is continued indefinitely producing a series of
desorption curves emanating from the base SV adsorption curve.
The results of testing both algorithms is presented in Section VIII, ARM
Model Testing and Simulation Results. Further testing on different
pesticides on different soil types is presently in progress. Brown15
has indicated that the equilibrium type algorithms presented above may not
be valid under field conditions. Consequently, a kinetic non-equilibrium
approach is another possibility for future investigations.
PESTICIDE ATTENUATION
The attenuation processes of degradation and volatilization of pesticides
are critical to the simulation of pesticide loss since these mechanisms
control the mass of chemical available for transport at any time following
application. Highly volatile or degradable pesticides can be reduced to
insignificant levels after only one month of exposure in the field (see
Section VIII). On the other hand, non-volatile or non-degradable
pesticides can continue to contribute to stream pollution months, or
possibly years, after the initial application. In addition,
volatilization and degradation, by microbial, chemical, or photochemical
means, often accounts for the great majority of the applied pesticide
removed from the soil environment; surface runoff and erosion removal of
pesticides is generally a small fraction of the total application amount.
The PTR Model included surface and soil-incorporated volatilization models
and a general pesticide degradation model. However, the volatilization
models, derived from work by Farmer and Letey16 were not utilized in
the pesticide simulation due to lack of field data for testing purposes.
The degradation model assumed a simple first-order decay. It was needed to
estimate the amount of pesticide available for transport at any time
during the growing season. In this way the runoff and erosion transport
processes occurring during storm events could be evaluated. Neither model
allowed for the effects of environmental conditions on the attenuation
processes.
Due to the lack of data for testing, the volatilization models are not
included in the present version of the ARM Model. The simple first-order
degradation model remains so that the surface transport mechanism can be
simulated and evaluated. Further research on these attenuation processes
and on the effects of soil moisture, soil temperature, pH, etc. is needed
27
-------
before reliable models can be developed and utilized in the ARM Model.
Steen17 has suggested a subsurface pesticide attenuation model which
attempts to account for soil temperature and moisture conditions. This
model is presently under evaluation for addition to the ARM Model.
28
-------
SECTION V
SNOW ACCUMULATION AND MELT SIMULATION
In the simulation of water quality processes, the mechanisms of snow
accumulation and melt are often neglected. The stated reasons for this
omission generally pertain to an assumed minor influence on water quality,
the extensive data requirements, and the extreme complexity of the
component processes. Obviously, in the southern latitudes of the United
States and at many coastal locations, snow accumulation during winter
months is often negligible. However, considering its location in a
temperate climatic zone, over 50 percent of the continental United States
experiences significant snow accumulation. In many areas streamflow
contributions from melting snow continue throughout the spring and well
into the summer. For many urban areas, the supply of water during the
critical summer period is entirely a function of the extent of snow
accumulation during the previous winter. Section III stressed the
importance of continuous simulation in the modeling of agricultural
nonpoint source pollutants. Snow accumulation and melt is a major factor
in continuous hydrologic simulation. Thus, the consideration of these
processes is an important part of any hydrologic model which is to provide
a basis for the simulation of water quality processes.
PHYSICAL PROCESS DESCRIPTION
Snow accumulation and melt are separate but often concurrent mechanisms.
The initial snow accumulation is largely a function of air (and
atmospheric) temperature at the time of precipitation; whereas, snowmelt
is an energy transfer process in the form of heat between the snowpack and
its environment. Basically, 80 cal/cm2 of heat must be supplied to obtain
one centimeter of water from a snowpack at 0 °C (203 cal/cnror750 Btu/ft2
for one inch of melt at 32 °F). This heat or energy requirement is
derived from the following sources:
(1) Solar (shortwave) radiation
(2) Terrestrial (longwave) radiation
(3) Convective and advective transfer of sensible heat from
overlying air
(4) Condensation of water vapor from the air
(5) Heat conduction from soil and surroundings
(6) Heat content of precipitation
The complexity of the snowmelt process is due to the many factors that
influence the contributions from each of the above energy sources. Figure
8 conceptually indicates the factors and processes involved in snow
accumulation and melt on a watershed. The combination of precipitation
and near or below freezing temperatures results in the initial
29
-------
CO
o
TERRESTRIAL
RADIATION
+4
+ RAIN/SNOW
AIR
TEMPERATURE
DETEMINATION
/
+ + + •¥
CONDENSATION i
TEMPERATURE
SNOW
COMPACTION-^/ SNOW SURFACE
AND DEPTH
HEA.T EXCHANGE
LIQUID STORAGE
IN SNOWPACK
WIND
GROUNDMELT
LAND SURFACE
AREAL EXTENT
OF SNOW COVER
Snow accumulation and melt processes Figures
-------
accumulation of the snowpack. Although relative humidity and air pressure
influence the form of precipitation, temperature is the major determining
factor in the rain/snow division. The rain/snow division is important to
the hydrologic response of the watershed. Precipitation in the form of
rain can become surface runoff immediately, and will contain sufficient
heat energy to melt a portion of the snowpack. On the other hand,
precipitation in the form of snow will augment the snowpack, and is more
likely to contribute to soil moisture, groundwater, and subsurface flow as
the snowpack melts.
Just as the snow begins to accumulate, the major melt processes are
initiated. Both solar (shortwave) radiation and terrestrial (longwave)
radiation are contributors to the snowmelt process, although solar
radiation provides the major radiation melt component. The effective
energy transfer to the snowpack from solar radiation is modified by the
albedo, or reflectivity, of the snow surface and the forest canopy in
watersheds with forested land. Terrestrial radiation exchange occurs
between the atmosphere, clouds, trees, buildings and even the snowpack
itself. Generally, solar radiation dominates the net radiation exchange
during daylight hours resulting in a heat gain to the snowpack.
Terrestrial radiation continues during the night causing a net heat loss
from the snowpack during the dark hours. The radiation balance, in
addition to the other heat exchange processes, allows melting of the pack
during the day and a refreezing during the night.
When air temperatures are above freezing, convective and advective heat
transfer to the snowpack producess another melt component. Condensation
of water vapor on the snowpack from the surrounding air, and the opposing
mechanism of snow evaporation from the pack, respectively add and subtract
a component in the snowpack heat balance. Wind movement is a significant
factor in all of these processes; its effect on heat transfer is readily
acknowledged by anyone who has experienced a chilling northeaster.
Depending on climatic conditions condensation and convection can
contribute to a significant portion of the snowmelt.
The remaining melt mechanisms include the ground melt component resulting
from heat from the land surface and surroundings, and rainmelt due to the
heat input of rain impinging on the snowpack. Ground melt is due to the
temperature difference between the snowpack and the land surface and
subsurface. Areas that experience relatively light snowfall and low
temperatures will have a small ground melt component due to the insulating
effects of frost and frozen ground conditions. On the other hand, ground
melt can be significant in areas with rapid accumulation and deep
snowpacks. Also, urban areas with heat input from roads, buildings, and
underground utilities, and special geologic areas (hot springs, volcanic
activity, etc.) can experience an unusually high ground melt contribution.
Snowmelt caused by rain on a pack is usually quite small. Twenty-five
millimeters (1 inch) of rainfall at 10 °C (50 °F) will produce only 3.2
31
-------
millimeters (0.125 inch) of melt. However, rain often occurs at high
atmospheric humidity when condensation of water vapor can take place;
condensation of 25 millimeters (1 inch) of water vapor (water equivalent)
can produce 190 millimeters (7.5 inches) of melt. Thus, water vapor
condensation can cause rapid snowmelt, and seems to be responsible for the
myth that rainfall causes rapid snowmelt.
The release of melt from the snowpack is a function of the liquid
moisture holding capacity of the snowpack and does not necessarily occur
at the time of melt. The snowpack contains moisture in both frozen and
liquid form; spaces between snow crystals contain water molecules. As
melt occurs, more water molecules are added to the spaces in the snowpack
until the moisture holding capacity is reached. Additional melt will
reach the land surface and possibly result in runoff. As the snowpack
increases in depth over the season, compaction of the pack results in a
lower depth and a higher snow density. As density increases the moisture
holding capacity of the snowpack decreases due to less pore space between
snow crystals and a change in crystal structure.
Thus, the snowmelt reaching the land surface results from complex
interactions between the melt components, climatic conditions, and
snowpack characteristics. For the most part, the snowpack behaves like a
moisture reservoir gradually releasing its storage. However, the
combination of extreme climatic conditions and snowpack characteristics
can lead to abnormally high liquid moisture holding capacity and sudden
release of melt in relatively short time periods.18 The damage which
can occur during such events emphasizes the need to further study and
understand the snowmelt process.
ALGORITHM DESCRIPTION
The objective of snow accumulation and melt simulation is to approximate
the physical processes (described above) and their interactions in order
to evaluate the timing and volume of melt water released from the
snowpack. The algorithms used in simulating the processes shown in Figure 8
are based on extensive work by the Corps of Engineers,19 Anderson and
Crawford,20 and Anderson.21 Empirical relationships are employed when
quantitative descriptions of the process are not available. The
algorithms presented below are identical to those employed in HSP and have
demonstrated reasonably successful results on numerous watersheds.22- 23> 2**- 25
A flowchart of the snowmelt routine is shown in Figure 9. The major
simulated processes can be divided into the two general categories of melt
components and snowpack characteristics. The algorithms for the
individual processes within each of these categories are briefly presented
below in computer format and English units to promote recognition of the
equations in the Model source code. The interested reader is referred to
the original source materials for a more in-depth explanation.
32
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CO
CO
KEY
HEAT
CD INPUT/OU1PUT
FUNCTION
STORAGE
PRECIPITATION
TEMPERATURE
WIND
PENPOINT
RADIATION
NET
CONDENSATION
CONVECTION
WATER RELEASED
FROM SNOWPACK
Snowmelt simulation
Figure 9
-------
Melt Components
Radiation Melt-
The total melt component in each hour due to incident radiation energy is
RM = (RA + LW)/203.2 (9)
where RM = radiation melt, in/hr
RA = net solar radiation, langleys/hr
LW = net terrestrial radiation, langleys/hr
203.2 = langleys required to produce 1 inch of melt from snow at 32 °F
The effects of solar and terrestrial radiation are evaluated separately.
An input parameter, RADCON, allows the user to adjust the solar radiation
melt component to the conditions of the particular watershed. Daily solar
radiation is required input data for the present version of the snowmelt
routine. Hourly values are derived from a fixed 24-hour distribution and
are modified by the effective albedo (calculations described under
'snowpack characteristics') and the watershed forest cover. An input
parameter, F, indicates the fraction of the watershed covered by forests.
On small agricultural watersheds F will usually be zero. However, forest
cover affects many snowmelt processes and must be included whenever the
snowmelt routine of the ARM Model is applied to forested watersheds or
forested portions of agricultural watersheds.
Terrestial radiation is not generally measured; hence, an estimate must be
obtained from theoretical considerations and modified by environmental
factors (e.g. cloud cover, forest canopy, etc.). The following
relationship for terrestrial radiation based on Stefan's Law of Black Body
Radiation is found in "Snow Hydrology".19
R = aTAMF + (1-F)0.757> - aTSf* (10)
where R = net terrestrial radiation, langleys/min
F = fraction forest cover
TA = air temperature, °K
TS = snow temperature, °K 1Q
a = Stefan's constant, 0.826 x 10" , langleys/min/°K
The snowmelt routine employs a linear approximation to the above
relationship and modifies the resulting hourly terrestrial radiation for
cloud cover effects. Back radiation from clouds can partially offset
terrestrial radiation losses from the snowpack. Since cloud cover data
information is not generally available and transposition of data from the
34
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Dsest observation point can be highly inaccurate, a daily cloud cover
rrection factor is estimated to reduce this radiation loss from the
ck. For days when precipitation occurs, terrestrial radiation loss from
a pack is reduced by 85 percent to account for the effects of complete
oud cover; this reduction factor decreases to zero in the days following
2 storm event.
ndensation-Convection Melt-
e melt resulting from heat exchange due to condensation and convection
often combined in a single equation. A constant ratio between the
efficients of convection and condensation (Bowen's ratio) is generally
sumed. Since the two mechanisms are operative under different climatic
tuations, the algorithms are presented here separately. Condensation
curs only when the vapor pressure of the air is greater than saturation,
areas convection melt occurs when the air temperature is greater than
sezing. The algorithms are as follows:
CONV = CCFAC*.00026*WIN*(TX-32)*(1.0-0.3*(MELEV/10000)) (11)
CONDS = CCFAC*.00026*WIN*8.59*(VAPP-6.108) (12)
ere CONV = convection melt, in/h
CONDS = condensation melt, in/hr
CCFAC = input correction factor to adjust melt values to
field condi-tions
WIN = wind movement, mi/hr
TX = air temperature, °F
MELEV = mean elevation of the watershed, 1000's ft
(Note: the expression 1.0-0.3*(KELEV/10000) is a
linear approximation of the relative change in air
pressure with elevation, and corresponds to P/Po
in "Snow Hydrology".)
VAPP = vapor pressure of the air, millibars
6.108 = saturation vapor pressure over ice at 32 °F, millibars
0.00026,
8.59 = constants in the analogous expression in "Snow Hydrology"
(Note: 0.00026 corresponds to the daily coefficient,
0.00629, adjusted to an hourly basis.)
in melt-
enever rain occurs on a snowpack, heat is transmitted to the snowpack,
d melt is likely to occur. The quantity of snowmelt from this component
calculated as follows, assuming the temperature of the rain equals air
mperature:
35
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RAINM = ((TX-32)*PX)/144 (13)
where RAINM = rain melt, in/hr
PX = rain, in/hr
TX = air temperature, °F
144 = units conversion factor, °F
Ground melt-
As mentioned previously, melt due to heat supplied from the land surface
and subsurface can be significant in the overall water balance. Since
ground melt is relatively constant, an input parameter specifies the daily
contribution. Heat loss from the snowpack can result in snowpack
temperatures less than 32 °F. When this occurs, the ground melt component
is reduced 3 percent for each degree below 32 °F.
Snowpack Characteristics
Rain/Snow Determination-
The form of precipitation is critical to the reliable simulation of runoff
and snowmelt. The following empirical expression based on work by
Anderson21 is used to calculate the effective air temperature below
which snow occurs:
SNTEMP = TSNOW + (TX-DEWX)*(0.12 + 0.008*TX) (14)
where SNTEMP = temperature below which snow occurs
TSNOW = input parameter
TX = air temperature
DEWX = dewpoint temperature
Variable meteorologic conditions and the relatively imprecise estimates of
hourly temperature derived from maximum and minimum daily values can cause
some discrepancies in this determination. For this reason, the use of
TSNOW as an input parameter allows the user flexibility in specifying the
form of precipitation recorded in meteorologic observation. The above
expression allows snow to occur at air temperatures above TSNOW if the
dewpoint temperature is sufficiently depressed. However, a maximum
variation of one Fahrenheit degree is specified resulting in a maximum
value for SNTEMP = TSNOW + 1.
Snow Density and Compaction-
The variation of the density of new snow with air temperature is obtained
from "Snow Hydrology"19 in the following form:
DNS = IDNS + (TX/100)2 (15)
36
-------
where DNS = density of new snow
IDNS = density of new snow at an air temperature of 0 °F
TX = air temperature, °F
Snow density is expressed in inches of water equivalent for each inch of
snow. With snow fall and melt processes occurring continuously, the snow
density is evaluated each hour. If the snow density is less than C.55,
compaction of the pack is assumed to occur. The new value for snow depth
is calculated by the empirical expression:
DEPTH2 = DEPTH1*(1.0-0.00002*(DEPTH1*(.55-SDEN))) (16)
where DEPTH2 new snow depth, in
DEPTH1 = old snow depth, in
SDEN = snow density
Area! Snow Coverage-
The areal snow coverage of a watershed is highly variable. Watershed
response differs depending on whether the precipitation, especially in the
form of rain, is falling on bare ground or snow covered land. The areal
snow coverage is modeled by specifying that the water equivalent of the
existing snowpack, PACK, must exceed the variable IPACK for complete
coverage. IPACK is initially set to a low value to insure complete
coverage for the initial events of the season and is reset to the maximum
value of PACK attained to date in each snowmelt season. Since the ratio
PACK/IPACK indicates the fraction of the watershed with snow coverage,
less than complete coverage results as the melt process reduces the value
of PACK. An input parameter, MPACK, allows the user to specify the water
equivalent required for complete snow coverage. Thus MPACK is the maximum
value of IPACK, resulting in complete coverage when PACK is greater than
MPACK, and less than complete coverage (PACK/MPACK) when PACK decreases to
values less than MPACK.
Albedo-
The albedo or reflectivity of the snowpack is a function of the condition
of the snow surface and the time since the last snow event. During the
snow season, the maximum and minimum values for albedo are specified as
0.85 and 0.60, respectively. It is reset to approximately the maximum
value with each major snow event and decreases gradually as the snowpack
ages.
Snow evaporation-
Evaporation from the snow surface is usually quite small, but its
inclusion in snowmelt calculations is necessary to complete the overall
water balance of the snowpack. The physical process is the opposite of
condensation occurring only when the vapor pressure of the air is less
than the saturation vapor pressure over snow. The following empirical
37
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relationship is used to calculate hourly snow evaporation:
SEVAP = EVAPSN*0.0002*WIN*(VAPP-SATVAP)*PACKRA (17)
where SEVAP = snow evaporation, in/hr
EVAPSN - correction factor to adjust to field conditions
WIN = wind .novement, mi/hr
VAPP = vapor pressure of the air, millibars
SATVAP = saturation vapor pressure over snow, millibars
PACKRA = fraction of watershed covered with snow
Snowpack Heat Loss-
Heat loss from the snowpack can occur if terrestrial back radiation from
the pack is large, or if air temperatures are very low. Since this heat
is emitted by the pack, it is simulated as a negative heat storage,
NEGMLT, which must be satisfied before melt can occur. Any heat available
to the snowpack first offsets NEGMLT before melting can occur. The hourly
increment to NEGMLT is calculated from the following empirical relation
whenever the air temperature is less than the temperature of the pack:
GM = 0.0007*(TP-TX) (18)
where GM = hourly increment to negative heat storage, in
TP = temperature of the pack, °F
TX = air temperature, °F
NEGMLT and GM are calculated in terms of inches of melt corresponding to
the heat loss from the pack. The current value of NEGMLT is used to
calculate the temperature of the pack simulating the drop in temperature
as heat loss from the pack continues. A maximum value of NEGMLT is
calculated as a function of air temperature and the water equivalent of
the pack by assuming that the temperature in the pack varies linearly from
ambient air temperature at the snow surface to 32 °F at the soil surface.
This maximum negative heat storage is calculated as follows:
NEGMM = 0.00695*(PACK/2.0)*(32.0-TX) (19)
where NEGMM = maximum negative heat storage, in
PACK = water equivalent of the snowpack, in
TX = air temperature, °F (<32 °F)
0.00695 = conversion factor, °F-i
38
-------
Snowpack Liquid Water Storage-
Liquid water storage within the snowpack is limited by a user input
parameter, WC, which specifies the maximum allowable water content per
inch of snowpack water equivalent. Thus, the maximum liquid water storage
is calculated as WC x PACK. However, this value is reduced if high snow
density values are attained.
MODEL OPERATION AND DATA REQUIREMENTS
The snowmelt routine operates on an hourly interval calculating the
various components of the snow accumulation and melt process and providing
hourly values of the water released from the snowpack (Figure 9). Since
the LANDS simulation is performed on 5 or 15 minute intervals, the hourly
melt values are divided into the shorter time intervals to continue the
simulation. Because the snowmelt process is much slower than the runoff
process, the hourly time interval appears to be adequate.
In addition to precipitation and evaporation, the present version of the
snowmelt routine in the ARM Model requires continuous data series for
daily max-min air temperature, daily wind movement, daily dewpoint
temperature, and daily solar radiation. Since the routine operates on an
hourly basis, hourly values for each of these meteorologic values would be
preferable. However, with the exception of experimental watersheds, few
locations would have such detailed data on a regular basis. Consequently,
the routine provides an empirical hourly distribution for wind movement
and solar radiation, and assumes that dewpoint temperature is relatively
constant throughout the day. The daily max-min air temperature values are
fitted to a sinusoidal distribution assuming minimum and maximum
temperatures occur during the hour beginning at 6:00 AM and 3:00 PM.
Thus, daily values are required for the meteorologic data series.
Table 5 defines the input parameters required for model operation, many of
which have been discussed above. Parameter evaluation and model
calibration are discussed in Appendix A. An understanding of the physical
processes and the algorithm approximations is critical to the intelligent
use of the snowmelt routine. Consequently, the potential user is advised
to re-read and study the algorithm descriptions and parameter definitions
prior to attempting application of the snowmelt routine.
39
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Table 5. SNOWMELT PARAMETERS
RADCON: Parameter to adjust theoretical solar radiation melt
equations to field conditions
CCFAC: Parameter to adjust theoretical condensation and convection
melt equation to field conditions
EVAPSN: Parameter to adjust theoretical snow evaporation to
field conditions
MELEV: Mean elevation of the watershed
ELDIF: Elevation difference between the temperature station and
the midpoint of the watershed
TSNOW: Wet-bulb air temperature below which snowfall occurs
MPACK: Water equivalent of the snowpack required for complete
coverage of the watershed
DGM: Daily groundmelt
WC: Maximum water content of the snow
IDNS: Index density of new snow at 0°F
SCF: Snow correction factor to compensate for deficiencies in
the gage during snowfall
PETMAX: Temperature below which input potential evapotranspiration
is reduced by 50 percent
PETMIN: Temperature below which input potential evapotranspiration
is reduced to zero
PETMUL: Potential evapotranspiration multiplier to adjust observed
daily input values
WMUL: Wind multiplier to adjust observed daily wind values
RMUL: Solar radiation multiplier to adjust observed daily solar
radiation values
F: Fraction of watershed with forest cover
KUGI: Index to the extent of undergrowth in forested areas
-------
SECTION VI
NUTRIENT MODELING
Water pollution from agricultural land has been increasing due to greater
use of machinery and chemicals to improve crop yields. Chemicals are
applied to prevent unwanted plants (herbicides) and animals (pesticides),
and to increase available plant nutrients (fertilizers). After
application, herbicides persist in the soil until they are degraded to
less harmful compounds or are removed from the soil by washoff or
leaching. Fertilizers on the other hand are applied as a supplement to
nutrients present in the soil profile. Plants do not absorb all the
applied fertilizer. Typically, only 5 to 10 percent of the applied
phosphorus and about 50 percent of the applied nitrogen is recovered in
the crop. The remaining nutrients can be retained in the soil in
unavailable forms or lost by volatilization, leaching, and surface
washoff. Although greater fertilizer application will improve crop
yields, it will increase nutrients in the soil available for contamination
of streams and groundwaters.
Excess nutrient applications are undesirable from three viewpoints:
health, aesthetics, and economics. Drinking water containing high nitrate
concentrations may cause methomoglobinemia in small children. High
nitrates can result from natural soil conditions or excess fertilization
from agriculture or silviculture. The U.S. Public Health Service Drinking
Water Standards for nitrate were set to prevent the occurrence of this
disease. Aesthetically, addition of nitrogen and phosphorus in surface
waters can greatly accelerate the eutrophication process causing unsightly
algal blooms and preventing recreational and other uses of the water body.
The final point of concern is the efficient utilization of energy
resources. Ammonia, the most common nitrogen fertilizer, requires natural
gas for its production. Thus, unnecessary loss of fertilizer is a waste
of scarce energy supplies. Recent increases will tend to reduce
fertilizer use; this alone may not be sufficient to ameliorate the impact
of nutrients from agriculture on the aquatic environment.
Methods for nutrient control can be investigated and developed through
costly field experiments or through the use of a mathematical model of the
important processes occurring on and in the soil profile.
Nutrient simulation in the ARM Model attempts to predict nutrient losses
from erosion, surface washoff, leaching, and biological conversion. With
testing and calibration the Model could be used to develop fertilizer
management plans to maximize fertilizer efficiency and minimize the water
quality impact of fertilizer use.
41
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NUTRIENT CYCLES
Nitrogen
Many nitrogen compounds are indigenous to the soil and undergo chemical
and biological transformations of importance to crop production and
pollution control. A general nitrogen cycle for agricultural lands is
depicted in Figure 10. Most soil nitrogen is in the organic form as
decaying plant residues and rather resistant soil humus.26 Organic
nitrogen can be broken down to ammonia through the process of
mineralization, also called ammonification. Ammonia is usually strongly
adsorbed to soil surfaces and can undergo nitrification to nitrite and
nitrate. Nitrite is rapidly converted to nitrate which is the most common
form of the mobile nitrogen compounds. Dissolved nitrates can be removed
by overland flow and interflow, and leached to groundwater. Biologically,
nitrate can be absorbed by plants, reduced anaerobically to various
nitrogen gases and immobilized by microorganisms in the presence of
nitrogen-deficient organic material. Nitrogen absorbed by plants is often
lost from the soil through harvesting. Nitrogen input to the soil occurs
by a number of pathways including rainfall, plant residues, dry fall of
dust and dirt, biological fixation of atmospheric nitrogen, and direct
application of fertilizer nitrogen. Although the soil nitrogen cycle is
quite complex, the major pathways can be sufficiently quantified to allow
mathematical simulation.
Phosphorus
While phosphorus does not exist in as many forms as nitrogen, phosphorus
compounds undergo transformations important to agriculture as shown in
Figure 11. Organic phosphorus can be mineralized to inorganic phosphates
and under special circumstances, the reaction can be reversed to
immobilization of inorganic phosphates to organic phosphorus. Inorganic
phosphates are either strongly adsorbed to clay particles, or present as
insoluble calcium, magnesium, iron or aluminum phosphates. Soluble
phosphate concentration rarely exceeds 0.2 mg/1. Thus, the major
mechanism for the loss of phosphorus compounds is soil erosion.27
PAST WORK
A number of models have been developed recently to predict nutrient
washoff from agricultural lands. Models in which actual soil processes
were considered are discussed below.
A complex watershed model for irrigated land was developed by Dutt and
others28 at the University of Arizona. The model includes procedures
42
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CO
ATMOSPHERIC
NITROGEN
N2
REMOVED FROM
CYCLE
BY HARVESTING
REMOVED FROM
CYCLE
BY LEACHING
Nitrogen Cycle
Figure 10
-------
WEATHERING
OF PHOSPHATE•
ROCKS
PHOSPHATE
FERTILIZER
SOURCE
REMOVED FROM CYCLE
BY HARVESTING
DECOMPOSITION
AND EXCRETA
INSOLUBLE
PHOSPHATES
BLEACHING
Phosphorus Cycle
Figure 11
-------
for calculating moisture flow and chemical and biological nutrient
reactions. The nitrogen transformation rates were developed by regression
analysis on data from arid regions. The following assumptions were made:
(1) no denitrification or volatilization occurs
(2) soil pH is in the range of 7.0 to 8.5
(3) symbiotic and non-symbiotic nitrogen fixation is small compared
to other nitrogen transformations
(4) nitrite is only present in trace amounts
(5) fertilizers and other nitrogen additions are applied uniformly
and thoroughly mixed with the soil
(6) the microbial populations of different soils are approximately
equivalent in their responses to parameters associated with
nitrogen transformations.
The model would be difficult to use in non-arid regions because the
reaction rates are permanently fixed by the regression equations.
Hagin and Amberger29 have developed a computer model for predicting
nitrogen and phosphorus movement and transformations on agricultural land.
They used the IBM Continuous System Modeling Program (CSflP) for
simulating ecological processes and transport phenomena in the soil. The
model includes mineralization and immobilization of nitrogen,
nitrification, denitrification, sediment washoff of phosphate and
transport of oxygen and heat. The report is particularly useful because
it contains considerable information on the effect of various
environmental factors on the reaction rates. Graphs are included for
correcting reaction rates for temperature, pH, moisture and oxygen level.
Unfortunately, the model was not tested on observed data. Thus, the model
assumptions have not been verified.
The Agricultural Research Service has developed the Agricultural Chemical
Transport Model (ACTMO)30 which includes hydrologic, sediment, and
chemical transport simulation. The nitrogen simulation considers
mineralization of organic nitrogen to nitrate, plant uptake of nitrate,
and nitrate removal by overland flow and leaching. The mineralization
rate is a first-order reaction modified for temperature and moisture
levels. The rate of nitrate uptake by plants is a function of the
evapotranspiration rate. The model does not include the loss of nitrogen
by sediment transport or denitrification. ACTMO was tested with available
hydrologic, sediment and pesticide data on a small watershed, but no
testing of the nitrogen model was reported.
A preliminary model of nitrogen transformations in agricultural soils was
reported by Mehran and Tanji.31 They developed a complex nitrogen
transformation model for batch reactors assuming all reactions proceed by
first-order kinetics. The model will be added to a water movement model
in the future to allow for advective movement of nitrogen compounds in the
soil column. The model did not adjust reaction rates for environmental
45
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factors such as temperature, pH, water content, aeration and organic
matter. Through adjustment of reaction rates, the model was able to
reproduce data collected in four different laboratory experiments.
ALGORITHM DESCRIPTIONS
In the ARM Hodel, as a first approximation, all chemical and biological
reactions are represented by first-order kinetics. The rate of a first
order reaction is proportional to the amount of the reactant; the
proportionality factor is the rate constant. Below is a general
discussion of first-order kinetics as they relate to biological and
chemical reactions. The method of temperature correction for the reaction
rates is also discussed, followed by a presentation of the algorithms
which represent the nitrogen and phosphorus transformations in the ARM
Model.
First-Order Kinetics
The biological conversion of compound A to compound B with reaction rate
constant k can be expressed as
(20)
The rate of this reaction is expressed in terms of the rate of change in
A and B with time or
- 3t {A} = it {B} = k (21)
Solution of the differential equation for A and B yields
,-kt
o"
A = A.e" - (22)
B = AQ (1 - e-) (23)
where AQ = initial amount of compound A at time t = 0.
reaction of B 9°in9 to A,
46
-------
*f
A< -B (24)
kb
and
{A} ^ {B} - kf {A} - kb {B} (25)
where kf = forward rate constant
kfc = backward rate constant
At equilibrium when the rate of change in concentration is zero,
Equation 25 becomes
0 = kf {A} - kb(B} (26)
On solving for A, a linear relationship is obtained between A and B at
equilibrium
{A} = (B) (27)
Kf
Chemical reactions that proceed rapidly can be viewed as instantaneously
obtaining equilibrium or quickly approaching equilibrium with rapid
forward and backward reaction rates. Modeling of adsorption-desorption
chemical reactions with first-order kinetics produces a linear
relationship between adsorbed and dissolved compounds at equilibrium.
This is a simplification of the equilibrium relationship defined by more
complex methods.
Two equations are commonly used to describe the equilibrium distribution
of a compound between adsorbed and dissolved states. The Freundlich
equation is
x KCl/n (28)
m ~
where x^ = amount adsorbed per unit weight adsorbent
m
47
-------
C = equilibrium concentration of adsorbate in solution after
adsorption
K,n = empirical constants
Usually n is greater than 1.0. However, if n is set to 1.0, the
equation reduces to a linear relationship between the amount adsorbed
and dissolved. The Langmuir equation is another relationship relating
adsorbed concentration to the dissolved concentration at equilibrium:
(29)
x_
where m = amount adsorbed per unit weight adsorbent
C = equilibrium concentration of adsorbate in solution after
adsorption
a,b = empirical constants
When the solution concentration is small such that 1/b » C, the Langmuir
equation reduces to a linear isotherm
m
Thus, a first-order kinetic approach to adsorotion-desorption reactions
results in a linear isotherm which is also obtainable from the Freundlich
and Langmuir equations. A general discussion of adsorption-desorption
reaction kinetics is given by Oddson et al . 3Z
Temperature Correction of Reaction Rates
In chemical and biological reactions, an increase in temperature will
cause an increase in the reaction rate for a certain temperature range.
Reaction rates can be adjusted for different temperatures by a
simplification of the Arrhenius Equation:33
kT * k356 (31)
where w = reaction rate at temperature T
k' = reaction rate at 35 °C
e = temperature correction coefficient
T = temperature in degrees Celsius
Typically biological reaction rates will double with each ten Celsius
degree rise in temperature. This corresponds to 8 = 1.07. For nutrient
48
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transformations in the ARM Model, the reaction rates are modified for
temperatures less than 35 °C. At temperatures of 35 °C or greater, the
reaction rates are assumed to remain constant. In this temperature range
the assumption of a constant temperature correction coefficient, 0, is
doubtful, and different bacterial species demonstrate widely varying
behavior. Each nutrient reaction rate requires its own temperature
correction coefficient.
Nitrogen Transformations
Seven different forms of nitrogen and ten reaction rates are used to
represent nitrogen transformations in the soil. Figure 12a is a diagram
of the nitrogen forms, and their interaction. Table 6 presents the
resulting system of coupled differential equations. The reaction rate
equations for the specific transformations are developed below.
Mineralization and Immobilization-
These processes are difficult to measure independently so researchers
usually report only the net amount of mineralization or immobilization.
The basic mechanisms occurring in the soil can be visualized as
microbial
mi nerali zati on i mmob i1i zati on
Organic -N »-NH4, N03 ^protein complexes (32)
(uptake)
There is net mineralization when mineralization exceeds microbial uptake,
and net immobilization when uptake exceeds mineralization. The amount of
organic nitrogen in the soil far exceeds other nitrogen forms.
Mineralization, even at the slow rate, can have considerable impact on the
amount of inorganic nitrogen available for plant uptake and leaching. The
most significant studies to date on quantifying the rate of organic nitrogen
mineralization have been done by George Stanford and his co-v/orkers at the
Agriculture Research Service, Beltsville, Maryland-3ltl 35> 36 Stanford
incubated 39 different soils to determine the soil nitrogen mineralization
potentials and mineralization rates. The soil nitrogen mineralization
potential is the amount of organic nitrogen in the soil which is
susceptible to mineralization. The incubation studies found that 5 to 41
percent of the organic nitrogen was mi neralizable, and that the
first-order decay rate was relatively uniform for the different soils.
Mineralization rates were also measured at different temperatures for
selected soils. The reaction rate approximately doubled for each ten
Celsius degree increase in the temperature range investigated.
The mineralization rate was also found to be dependent on soil moisture.
The rate increased up to a maximum, at about 80 to 90 percent filled pore
space, and then declined with higher soil moisture. At higher moisture
levels the rate of oxygen diffusion into the soil was retarded, resulting
in lower mineralization due to the lack of oxygen.
49
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en
o
Nutrient transformations in the ARM model
N2
KD
PLNT-N
KK2
KPL
NO2
K1
NH4-A
K1
NH4 - S
KAM
KIM
ORG-N
A. Nitrogen transformations in ARM model
KKIM
PLNT-P
ORG
-P
KM
•• —.
KIM
KPL
P04-S
P04-A
B. Phosphorus transformations in ARM model
Figure 12
-------
Table 6. COUPLED SYSTEM OF DIFFERENTIAL EQUATIONS
FOR NITROGEN TRANSFORMATIONS
Organic Nitrogen:
^- {ORG-N} = KIM {NH4-S} + KKIM {N03} - KAM {ORG}
Solution Ammonia:
^- {NH4-S} = KAM {ORG-N} - (KSA + Kl + KIM){NH4-S} + KAS {NH4-A}
Adsorbed Ammonia:
{NH4-A} = KSA {NH4-S} - (KAS + K1){NH4-A}
Nitrite:
|f {N02} = Kl {NH4-S} + Kl {NH4-A} - (KD + K2){N02} + KK2{N03}
Nitrate:
i *
|f {N03} = K2 {N02} - (KK2 + KKIM + KPL){N03}
Nitrogen Gas:
(N2) KD{N02)
Plant Nitrogen:
- {PLNT-N} = KPL{N03>
51
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The mineralization rate equation used in the ARM Model is
^.{ORG-N} = KAM{ORG-N}6KA|^T"35) (33)
where ORG-N = organic nitrogen mass, kg/ha
KAM = mineralization rate constant at 35° C, per day
e*AM = temperature correction coefficient for mineralization
T = soil temperature, °C
The decrease in organic nitrogen will result in an increase of ammonia as
shown in Figure 12a. At this time corrections for oxygen and moisture
levels are not included. Work is presently underway to incorporate the
effects of these environmental factors.
Immobilization of inorganic nitrogen in the soil has been reviewed by
Bartholomew.37 When plant residues low in nitrogen are added to the
soil, ammonia or nitrate will be removed from the soil solution to make
more protein needed for larger microorganism populations. The
immobilization process has not been studied extensively and immobilization
rates are not readily available. Bartholomew indicated immobilization was
a first order reaction with temperature and moisture dependence. More
reaction rate and temperature dependence data are needed to adequately
model this process.
The ARM Model represents immobilization as potentially removing ammonia
and nitrate according to the following equations:
} = KIM{NH4-S}8|(I|JIT"35) (34)
(35)
where KIM, KKIM = immobilization rate constants at 35 °C, per day
NH4-S, N03 = ammonia in solution and nitrate concentration, kg/ha
6KIM, 9KKIM = temperature correction coefficients
T = temperature, °C
Nitrification-
Nitrification is a two-step process in which ammonia is oxidized first to
nitrite and then to nitrate. This is an important soil reaction because a
largely immobile form of nitrogen, ammonia, is converted to a highly
mobile form, nitrate, which may be absorbed by plants, lost by leaching
and demtrification, or removed by surface runoff. Alexander38
52
-------
provided a good description of the nitrification process and an overview
of current research. Quantification of the nitrification process can be
approached from a simplification of the works of A, D. McLaren,39 of
U.C. Berkeley, who has published many articles relating nitrogen
transformations to enzyme kinetics and bacterial growth dynamics. The
basic equation is
•* f + - + rfff! (36)
where {s} = nitrogen substrate concentration
m = biomass
A = nitrogen oxidized per unit weight of biomass synthesized
a = nitrogen oxidized per unit weight of biomass per unit time for
maintenance
B = amount of enzyme per unit biomass involved in waste metabolism
k" = proportionality constant
k = half saturation constant
m
The first term on the right side of Equation 36 represents consumption for
microbial growth, the second is for maintenance, and the third term
accounts for substrate oxidized by the enzyme system but not needed for
growth or maintenance. The basic equation can be simplified by assuming a
fully enriched soil where dm/dt = 0, and small substrate concentrations
(s«K ). Following these assumptions, Equation 36 becomes
- at • °+ K(s) (37)
This equation can be simplified further when the first term is much
smaller than the second, resulting in the first-order rate equation.
= k{s} (38)
Although McLaren was able to evaluate the parameters appearing in Equation
36, parameter estimates are not available for other soil types under field
conditions. Alexander38 presented some discussion on the effects of
temperature, pH, aeration, and moisture on the nitrification process.
More quantitative information on environmental factors was published in a
report by Hagin and Amberger.29
53
-------
In the ARM Model nitrification is represented as a two-step process, each
step with its own rate constant and temperature correction (actor The
oxidation of solution and adsorbed ammonia to nitrite is followed by the
rapid oxidation of nitrite to nitrate. These reactions are
. d_{NH4-S + NH4-A} = Kl {NH4-S + NH4-A}6K[T"35) (39)
_ = K2 {N02>e^T-35) (40)
where NH4-S + NH4-A = mass of ammonia in solution and adsorbad, kg/!ia
N02 = mass of nitrite, kg/ha
Kl, K2 = first and second step rate constants at
35 °C, per day
em> Qw = first and second step temperature correction
^ N coefficients
T = temperature, °C
Dem'trification-
Until recently prediction of denitrifi cation rates has not been possible
although the mechanisms have been known for some time. Denitrification is
favored in wet, poorly aerated soils that have sufficient decomposable
organic matter. The tremendous increase in the use of nitrogen
fertilizers and the possibility of losing over 30 percent of the applied
nitrogen through denitrification has sparked recent interest in
quantifying and predicting these losses.40
The most quantitative description of the denitrification process has been
published recently by Stanford et al.1*1'1*2 Similar to the incubation
studies used for measuring mineralization rates and potentials, 30 soil
types were mixed with water and incubated at 35 °C following the addition
of nitrate. The rate of nitrate disappearance was used to measure the
denitrification rate. The authors found denitrification fit a first-order
process better than a zero-order process. Unlike the results from the
mineralization studies where the mineralization rate was relatively
constant among the soils, the denitrification rate constant varied by a
factor of 30 from the slowest rate to the fastest rate. Seventy-eight
percent of this variation could be predicted by a regression equation
based on a soluble carbon index. The soluble carbon index was better than
a total carbon index because much of the total carbon of soils is highly
resistant to decomposition.
Stanford et al.**1-1*2 also evaluated the denitrifi cation rate constant
at temperatures other than 35 °C. They found the reaction rate increased
54
-------
about twofold for each ten Celsius degree increase in temperature over the
range 15 to 35 °C. There was little change in the rate constant when the
temperature increased from 35 °C to 45 °C.
Denitrification is represented in the ARM Model as a two-step process,
first reduction of nitrate to nitrite, and then reduction of nitrite to
nitrogen gas. The rate equations are
= KK2 {N03}6K^T-35) (41)
and
= KD (N02}e^T-35) (42)
where N03, N02 = nitrate and nitrite mass, kg/ha
KK2, KD = first and second step rate constants at 35 °C,
per day
KK2' KD = temperature correction coefficients
T = temperature, °C
In spite of the importance of oxygen level on the denitrification rate, it
was not possible to include a correction for oxygen level because it is
not simulated in the present model. Thus, at this time, the
denitrification reactions are either turned on or turned off all the time
depending on the values of KK2 and KD. Future work will attempt to
include oxygen uptake and diffusion in the soil and allow for internal
adjustment of denitrification rate as a function of oxygen level.
Plant Uptake-
The primary mechanism for removal of nitrogen from agricultural land is
through plant uptake. Viets43 provided a general review of nitrogen
uptake by plants. Van der Honert and Hooymons1*1* showed that the rate of
nitrate uptake was a first-order reaction at nitrate concentrations less
than 5 mg/1 and a zero-order reaction at higher concentrations. The
effect of temperature and pH on the rate of uptake was also discussed.
The ARM Model represents plant uptake of nitrates according to the
following equation:
KPL
55
-------
where PLNT-N = mass of nitrogen taken up by plants, kg/ha
N03 = mass of nitrate, kg/ha
KPL = plant uptake rate constant, per day
QKPL = temperature correction coefficient
T = temperature, °C
All plant nitrogen is assumed to be removed during harvesting. Future work
will need to evaluate the extent to which plant nitrogen contributes to soil
nitrogen in the form of plant residues remaining on the watershed.
Ammonia Adsorption-Desorption-
Ammonia can exist in three different forms in the soil: dissolved in soil
water, adsorbed to surfaces of soil particles and fixed inside crystal
lattices. Mortland and Wolcott1*5 discussed the various ammonia
complexes with clays but did not present a general theory to allow
prediction of the different forms. Instead of developing a complex model
for specific soil types and conditions, a much simpler approach was used
that might represent a much broader range of soils. The ARM Model assumes
two forms of ammonia exist in the soil: the adsorbed ammonia attached to
the soil particles, and dissolved ammonia which moves with the soil water.
Rate of transfer from one type to the other is governed by first-order
reactions. These reactions can be represented by
KSA
..{NH4-A> (44)
KAS
and the rate equations are
(45)
- KAS{NH4-A}6KAS(T"35)
where NH4-S mass of ammonia in solution, kg/ha
NH4-A = mass of ammonia adsorbed to soil, kg/ha
KSA = first-order rate constant for adsorption
reaction at 35 °C, per day
KAS = first-order rate constant for desorption
reaction at 35 °C, per day
8KSA' eKAS = temperature correction coefficients
T = temperature, °C
Usually very little ammonia is in solution; most is adsorbed to soil
particle surfaces. This would correspond to an adsorption reaction rate
much greater than the desorption rate or KSA»KAS reaction rate
56
-------
Phosphorus Transformations
Phosphorus was assumed to exist in only four forms: organic phosphorus,
solid phosphate compounds, dissolved phosphates, and phosphorus absorbed
by plants. The reactions of mineralization-immobilization,
adsorption-desorption, and plant uptake are modeled as first-order rates.
A diagram of the phosphorus cycle as represented by the ARM Model is given
in Figure 12b, and Table 7 contains the system of coupled differential
equations developed below.
'lineralization-Iriiniobilization-
Organic phosphorus is not as important in the phosphorus cycle as organic
nitrogen is in the nitrogen cycle. Larsen46 reviewed the literature on
soil phosphorus and did not present any general findings on mineralization
and immobilization rates. In the ARM Model, phosphorus mineralization and
immobilization mechanisms were assumed to be similar to the corresponding
nitrogen processes. Thus, they are represented as
- £r(ORG-P} - KM {ORG-P}eJ.T~35) (46)
^{P04-S} = KIM {P04-S}e|(I|JIT'35) (47)
where ORG-P - mass of organic phosphorus, kg/ha
P04-S = mass of phosphate in solution, kg/ha
KM = first-order mineralization rate at 35 °C, per day
KIM = first-order immobilization rate at 35 °C, per day
8KM' eKIM = temperature correction coefficients
T = temperature, °C
Soil organic phosphorus is assumed to be insoluble and only leaves the
watershed with the eroded sediment.
Adsorption-Desorption-
Organic phosphorus mineralization results in the release of inorganic
phosphates which can remain in the soil solution, precipitate as sparingly
soluble salts of calcium, magnesium, aluminum, or iron phosphates, or
adsorb onto the surface of clay or calcium carbonate soil particles/*b
The Model represents these three forms of phosphate in two categories;
that is, phosphates in solution, and phosphates in solid form including
both adsorbed and precipitated forms. Solid phosphates will be referred
to as adsorbed phosphates, and the transfer between solution and adsorbed
phosphates is modeled by adsorption and desorption reactions:
57
-------
Table 7. COUPLED SYSTEM OF DIFFERENTIAL EQUATIONS
FOR PHOSPHORUS TRANSFORMATIONS
Organic Phosphorus:
{ORG-P} = - KM {ORG-P} + KIM {P04-S}
Solution Phosphate:
{P04-S} = KM {ORG-P} - (KIM + KSA + KPL) {P04-S} + KAS {P04-A}
Adsorbed and Combined Phosphate:
{P04-A} = KSA {P04-S} - KAS {P04-A}
Plant Phosphorus:
{PLNT-P} = KPL {P04-S}
58
-------
{R04-S}:
KSA
KAS
The resulting rate expressions are
:{P04-A}
(48)
' 3t(P04'S} =
where
P04-S
P04-A
KSA
KAS
9KSA 0KAS
T
KSA{P04-S}8
(T-35)
KSA
- KAS{P04-A}6
(T-35)
KAS
(49)
= mass of phosphate in solution, kg/ha
= mass of phosphate adsorbed, kg/ha
= first-order rate constant for adsorption
at 35 °C, per day
= first-order rate constant for desorption
at 35 °C, per day
= temperature correction coefficients
- temperature, °C
Fried et al.1*7 studied the desorption reaction and found that the data
fit a first-order rate equation. The reaction rate increased by 80
percent for a temperature increase of 12 Celsius degrees. Enfield and
Shew'ts studied both reactions and found that the magnitude of the
adsorption rate was much greater than the desorption rate, or KSA » KAS.
At equilibrium, in most soils the dissolved phosphates rarely exceed 0.2
Rig/1 and the majority of the phosphates are in solid form.
Plant Uptake-
Fried et a!47 also studied the rate of phosphate uptake by plant roots
under laboratory conditions and found that the absorption rate was
approximately proportional to the solution concentration, thus a first
order mechanism. Van der Honert et al.1*1* showed that phosphate uptake
was a first-order reaction up to 1.0 mg P04/1. Since soil solutions
rarely exceed this concentration, a first-order uptake mechanism is a
reasonable assumption.
The rate expression used in the ARM Model is
= KPL {P04-S}0
T"35)
(50)
Kp
where PLNT-P = mass of plant phosphorus, kg/ha
P04-S = mass of phosphates in solution, kg/ha
KPL = first-order absorption rate, kg/ha
9KPL = temperature correction coefficient
T = temperature, °C
59
-------
The nutrient model assumes that plant phosphorus can be removed from the
watershed only by harvesting. This assumption is valid for plants, such
as grain crops, that contain phosphorus largely in the portion harvested.
Moreover, the conversion of phosphorus is plant residues to soil organic
phosphorus is a slow process especially in dry, cold regions. However, in
warm, humid areas and where substantial plant residues remain on the
watershed, the conversion of plant phosphorus to soil organic phosphorus
may be significant. Further development of the nutrient model will need
to evaluate the importance of this process and possibly allow for its
simulation.
Review of Assumptions
The nutrient model required many assumptions in its development. A review
of these assumptions is essential to a full understanding of the model.
The assumption of first-order kinetics is generally valid for chemical and
biological reactions when the reactants are not in high concentrations.
From the literature cited, it appears conditions existing in the soil are
such that first-order kinetics is a reasonable assumption. Temperature
correction of reaction rates using a simplified form of the Arrhenius
equation is flexible and can closely approximate changes in rates reported
in the literature. The reaction rates were assumed to be constant for
temperatures greater than 35 °C because the behavior of chemical and
biological reactions is not well defined at high temperatures. Until the
ARM Model is able to simulate soil temperatures, the average daily air
temperature will be used to approximate soil temperatures.
The environmental factors of pH, moisture, oxygen, and organic matter are
not directly taken into account for reaction rate modification. Soil pH
is relatively constant due to the high buffering capacity of the soil
itself. Any pH correction could be done when the reaction rates are input
to the Model. Reaction rates should be corrected for moisture levels
because biological activity is dependent on soil moisture. Oxygen levels
in the soil are needed to determine if oxidative processes like
mineralization and nitrification, or reductive processes, like
denitrification, will occur. Organic matter in the soil can deplete the
oxygen in the soil and accelerate the rate of denitrification.
Some of the limitations in the nutrient model due to neglecting pH,
moisture, oxygen, and organic matter can be circumvented by having
separate reaction rates for each of the four soil layers. For example,
the denitrification rate could be set to zero in the surface and upper
zone because they are usually well aerated. Likewise the denitrification
rate would be close to zero in the groundwater zone because of low organic
content. Thus, the input of four values, one for each soil layer, is a
temporary correction for soil properties and environmental factors at
different depths.
60
-------
Numerical Solution Techniques
Tables 6 and 7 display the nitrogen and phosphorus rate equations which
result from the assumption of first-order kinetics. Analytic solutions of
coupled systems of equations for constituent concentrations are quite
difficult when advective processes, like leaching and sediment loss, are
simulated in addition to reaction rate adjustments for temperature.
Because of the problems with analytic solutions, the nutrient model
numerically solves the coupled system of differential equations for the
nitrogen and phosphorus masses in each soil layer.
There are numerous solution techniques available. The choice depends upon
the equations to be solved, the accuracy desired and the amount of
computer time available. The technique used in the nutrient model is
a simple Euler integration scheme illustrated by the following example.
Given the differential equation for a first-order reaction rate
(51)
where y(t) = mass at time t
k = rate constant
the time derivative can be approximated by
d vm-y(t + At) - y(t) (52)
dTyUj~ At
when At, the time step, is small. Substitution of the derivative
approximation into the differential Equation 51, yields
v(t + At) - y(t) _ (53)
Rearranging and solving for y(t + At) gives
y(t + At) «y(t) - Atky(t) (54)
Thus, the mass at the next time step can be approximated with the mass at
the present time; the differential equation is integrated step by step to
obtain the mass for future time steps. The coupled system of differential
61
-------
equations of nitrogen and phosphorus transformations are solved by a
similar procedure in the ARM Model. The accuracy of the solution depends
on the size of the term Atk which should be much less than one in order
to change the mass by only a small amount in each time step.
CONCLUSIONS
A preliminary model of nitrogen and phosphorus compounds has been
developed for agricultural lands. The model includes advective losses to
the stream through sediment, overland flow and interflow, and leaching to
groundwater. An attempt was made to represent with actual first-order
kinetics chemical and biological transformations occurring in the soil.
Numerous assumptions were necessary for model development; verification
of the nutrient model must await the comparison of simulated results with
recorded field data. Further development of model algorithms and testing
with field data will be undertaken in a continuing research grant.
62
-------
SECTION VII
DATA COLLECTION AND ANALYSIS PROGRAMS
The ARM Model development effort is supported by an extensive data
collection and analysis program sponsored by the U.S. Environmental
Protection Agency's Environmental Research Laboratory in Athens, Georgia
(ERL-Athens). Test sites located in Georgia and Michigan have been
instrumented for the continuous monitoring and sampling of runoff and
sediment. Collected samples are refrigerated on site and later analyzed
for pesticide and nutrient content. In addition, meteorologic conditions
are continuously monitored and soil core samples are taken and analyzed
immediately following application and periodically throughout the growing
season. Table 8 presents pertinent details on the test watersheds. The
individual programs in Georgia and Michigan are described below.
GEORGIA TEST SITE
This program is a joint effort between the ERL-Athens and the U.S.
Department of Agriculture's Southern Piedmont Conservation Research Center
(SPCRC) in Watkinsville, Georgia (see Location Map, Figure 13). Two test
watersheds (PI, P3) since 1972 and two additional test watersheds (P2, P4)
since 1973 have been instrumented, in addition to two small runoff plots
(SP1, SP3). A series of twelve 6x9 meter attenuation plots were
instrumented to study the degradation and vertical movement of pesticides
in the soil profile. Recording rain gages have been established at each
test watershed, and a weather station was set up at the attenuation plots
to record air temperature, pan evaporation, and wind data. The
attenuation plots were also instrumented to record soil moisture and
temperature at various soil depths, wind velocity and direction, solar
radiation, air temperature, and relative humidity at different heights
above the soil surface. This data is automatically recorded on magnetic
tape by a PDP-8 computer.
The SPCRC is responsible for the general care (pesticide applications,
planting, harvesting, etc.) of the test watersheds, the collection,
operation, and analysis of rainfall, runoff, and sediment data, and the
nutrient analyses of runoff samples. Automated stage recording and
sampling instrumention provides continuous monitoring of the watersheds.
Minimum-till age procedures are followed whereby tillage operations are
performed only as preparation for planting. Runoff and sediment samples
are transferred to the ERL-Athens where pesticide analyses are performed.
The pesticide analyses are accomplished by an integrated method involving
gas chromatographic and calorimetric analysis techniques.50 At the end
of the 1975 growing season the joint ERL-Athens/ USDA program in Georgia
will have completed four seasons of continuous data collection and
analysis of agricultural runoff.
63
-------
Table 8. TEST WATERSHEDS FOR ARM MODEL TESTING
CT»
•P*
Watershed Location
Designation
PI
P2
P3
OOo(East)
Watkinsville,
Georgia
Watkinsville.
Georgia
Watkinsville,
Georgia
Owner/
Operator
USDA/EPA
USDA/EPA
Watkinsville, USDA/EPA
Georgia
USDA/EPA
East Lansing, Michigan
Michigan State Univ
007(West) East Lansing, Michigan
Michigan State Univ
Area Mean Soils
(ha) Elevatior
(m above tnsl)
Conservation
2.70 238 Cecil non-terraced
sandy loam
1.30 231 Cecil non-terraced
sandy loam
1.26 239 Cecil terraced
sandy loam
1.38 239 Cecil terraced
sandy loam
0.80 272 Spinks non-terraced
sandy loam,
Also Traverse
Hillsdale, Tuscola
loam
0.55 271 Spinks non-terraced
sandy loam,
Also Traverse
Hillsdale, Tuscola
loam
1973 Growing Season
Crop Pesticide Application
Applied (kg/ha)
soybeans paraquat 1.12
diphenamid 3.36
trifluralin 1.12
corn
paraquat
atrazine
corn
paraquat
atrazine
1.12
3.36
soybeans paraquat 1.12
diphenamid 3.36
trifluralin 1.12
1.12
3.36
soybeans paraquat 1.12
diphenamid 3.36
trifluralin 1.12
soybeans paraquat 1.12
diphenamid 3.36
trifluralin 1.12
-------
Experimental watersheds in Georgia
CTl
EXPERIMENTAL
AREA
GEORGIA
Figure 13
-------
MICHIGAN TEST SITE
The Michigan test site is operated by the Michigan State University's
Department of Crop and Soil Science and Department of Entomology in a
cooperative agreement with the ERL-Athens. The two test watersheds
(listed in Table 8) are located approximately two miles south of East
Lansing, Michigan on the MSU Campus (Figure 14). Initially instrumented
in 1941, the watersheds have been operated since that time under various
research projects. A permanent weather station (East Lansing 3 SE, Index
No. 2395) adjacent to the watersheds provides continuous information on
rainfall, evaporation, solar radiation, air temperature, and wind
movement.
Similar to the program at the ERL-Athens, the Michigan test watersheds are
instrumented for continuous monitoring and sampling of runoff and
sediment; a Coshocton wheel for sample splitting is included in the
automated instrumentation. Pesticides are applied and analyzed in soil
core and runoff samples by a gas chromatograph feeding directly to a
computer for data logging. In addition, snow depth and water equivalent
is recorded, and snowmelt runoff samples are analyzed for pesticide and
nutrient content. Pesticides have also been applied in the fall to
facilitate detection in the snowmelt. Initiated in 1973, the MSU project
is expected to continue in operation for both pesticide and nutrient
monitoring until Spring 1976.
66
-------
Experimental watersheds in Michigan
EAST LANSING
MT. HOPE ROAD
FOREST ROAD
MICHIGAN
STATE
UNIVERSITY
UJ
PESTICIDE FIELD
LABORATORY
W. 007 006 E.
MSU WATERSHEDS
BENNET
ROAD
Q
Z
cc.
O
Q
I
i
Figure 14
-------
SECTION VIII
ARM MODEL TESTING AND SIMULATION RESULTS
Hodel testing for runoff, sediment loss, and pesticide loss was completed
on one additional year of data (January 1973-December 1973) from the PI
and P3 watersheds in Watkinsville, Georgia. Data for 1974 and for the
four remaining watersheds (Section VII) in Georgia and Michigan is
presently being analyzed and prepared for testing purposes. In addition,
nutrient runoff data for 1974 from both the Georgia and Michigan sites
will become available for future testing of the nutrient portions of the
ARM Model.
Figures 15 and 16 present detailed maps of the PI and P3 test watersheds
in Georgia. As indicated in Table 8, PI is a natural watershed while P3
is a terraced watershed with a grass waterway. This difference is
especially important in the relative sediment loss from the two
watersheds. PI and P3 received identical management practices during
1973: minimum tillage was employed, soybeans were planted, and the
herbicides paraquat (l,r-dimethyl-4,4-bipyridinium ion), diphenamid (N,
N-dimethyl-2, 2-diphenylacetamide), and trifluralin (a,a,a-trifluoro-2,
6-dinitro-N, N-dipropyl-p-toluidine) were applied at 1.1, 3.4 and 1.1
kg/ha, respectively. Pesticide simulations were performed for paraquat
and diphenamid; trifluralin was not simulated due to the lack of reliable
laboratory isotherm data. The following portions of this section discuss
the hydrology, sediment production, and pesticide simulation results for
the PI and P3 watersheds. Results are presented and analyzed, and data
and simulation problems are enumerated. This section concludes with a
discussion on indicated future topics of research and major conclusions
from the ARM Model testing.
HYDROLOGY AND SEDIMENT PRODUCTION SIMULATION
The hydrologic subroutine, LANDS, is the most highly developed and tested
portion of the ARM Model. The algorithms have been employed and tested in
the Stanford Watershed Model and the Hydrocomp Simulation Program on
numerous watersheds of differing size across the country. Although their
use on extremely small watersheds has been limited, the simulation results
on the PI and P3 watersheds are highly promising. Figures 17 and 18 and
Tables 9 and 10 present the recorded monthly rainfall and recorded and
simulated monthly runoff and sediment loss for the PI and P3 watersheds,
respectively. In both cases, monthly runoff is reasonably well simulated
for 1973, especially for the critical summer period, June through October.
On the PI watershed, the summer period appears to be more accurately
simulated than the winter-spring period. This may indicate a possible
seasonal variation in hydrologic parameters that warrants further
68
-------
SAMPLING SITE AND
INSTRUMENTATION
RECORDING RAIN GAGE
DRAINAGE PATTERN
CONTOUR LINES
P1 Watershed. Watkinsville, Georgia (2.70 ha)
Figure 15
69
-------
•V*"
SAMPLING SITE AND
INSTRUMENTATION
DRAINAGE PATTERN
RECORDING RAIN GAGE
CONTOUR LINES
GRASS WATERWAY
BOUNDARY LINE
P3 Watershed, Watkinsvitle, Georgia (1.26 ha)
Figure 16
-------
200
<
u_
5 100
on
o
z
o;
I OO
00
60
40
20
16
8
i i I I
I I
I T
RECORDED
SIMULATED
T T
T T
M
A M J J
TIME, MONTHS
A
0 N
Figure 17. 1973 monthly rainfall, runoff, and sediment
loss for the PI watershed
71
-------
o
ID
oi
CO
CO
CO
o
Ul
o
LU
CO
I I I I I
RECORDED
SIMULATED
FMAMJJA
TIME, MONTHS
OND
Figure 18. 1973 monthly rainfall, runoff, and sediment
loss for the P3 watershed
72
-------
Table 9. 1973 SUMMARY OF RAINFALL, RUNOFF, AND SEDIMENT LOSS FOR THE
PI WATERSHED (RECORDED AND SIMULATED)
OJ
Month Rainfall
mm (in)
Jan 135.4 (5.33)
Feb 69.3 (2.73)
Mar 250.7 (9.87)
Apr 127.5 (5.02)
flay 174.0 (6.85)
Jun 135.1 (5.32)
Jul 65.3 (2.57)
Aug 31.8 (1.25)
Sep 119.9 (4.72)
Oct 6.6 (.26)
llov 44.5 (1.75)
Dec 196.1 (7.72)
Total
1356.2 (53.39)
* Estimated values
Total
Recorded
mm (in)
1.3
7.4
51.6
15.0
49.8
43.9
19.1
1.3
23.1
0
0
10.5
(.05)
(.29)
(2.03)
(.59)
(1.96)
(1.73)
(.75)
(.05)
(.91)
(0)
(0)
(.73)
Runoff
Simulated
mm (in)
7.
8.
62.
40.
66.
41.
14.
2.
20.
0
•
15.
9
6
7
1
3
0
7
3
3
5
0
(.31)
(.34)
(2.47)
(1.58)
(2.61)
(1.65)
(.58)
(.09)
(.80)
(0)
(.02)
(.59)
Sediment Loss
Recorded Simulated
tonne/ha ton/ac tonne/ha ton/ac
0
(0)
.002
4.
19
.83
16
16
2
1
0
0
.9
.6
.0
.09
.1
.85
(.
(1
(.
(7
(7
(.
(
(
(
001)
.87)
37)
.54)*
.42)*
89)
.04)
.49)
(0)
(0)
.38)
.09
.13
3.43
.96
10.5
7.7
2.62
.11
1.64
0
.02
.60
(
(
(
(
.04)
.06)
1.53)
.43)
(4.70)
(
(
3.47)
1.17)
(.05)
(.73)
(0)
(.01)
(.27)
231.0 (9.09) 280.3 (11.04)
due to equipment malfunction.
42.56 (19.00) 27.97 (12.46)
-------
Table 10. 1973 SUMMARY OF
RAINFALL, RUNOFF, AND SEDIMENT LOSS FOR THE P3 WATERSHED
(RECORDED AND SlflULATED)
Month Rainfall
mm (in)
Jan 100.8 (3.97)
Feb 73.9 (2.91)
Mar 239.5 (9.43)
Apr 34.8 (1.37)
May 156.0 (6.14)
Jun 120.4 (4.74)
Jul 123.2 (4.85)
Aug 22.9 (.90)
Sep 135.1 (5.32)
Oct 5.1 (.20)
Nov 43.2 (1.70)
Dec 180.9 (7.12)
Total
Recorded
mm (in)
18.8
10.4
66.3
0
35.3
20.0
35.3
0
21.8
0
0
11.7
(.74)
(.41)
(2.61)
(0)
(1.39)
(.79)
(1.39)
(0)
(.86)
(0)
(0)
(.46)
Runoff
Simulated
mm (in)
6.4
9.9
65.3
4.3
45.0
22.6
41.7
0
20.1
0
.8
14.0
(-25)
(.39)
(2.57)
(.17)
(1.77)
(.89)
(1.64)
(0)
(.79)
(0)
(.03)
(.55)
Sediment Loss
Recorded Simulated
tonne/ha ton/ac tonne/ha ton/ac
.31
.02
.61
0
2.77
1.48
1.48
0
.08
0
0
.11
(.14)
(.01)
(.27)
(0)
(1.24)
(.66)
(.66)
(0)
(.04)
(0)
(0)
(.05)
.09
.13
.83
.02
2.02
1.16
2.37
0
.34
0
.01
.18
(.04)
(.06)
(.37)
(.01)
(.90)
(.52)
(1.06)
(0)
(.15)
(0)
(.01)
(.08)
Total
1235.8 (48.65) 219.6 (8.65) 230.1 (9.05) 6.86 (3.07) 7.15 (3.20)
-------
investigation. The terraces and grass waterway on P3 seemed to have
little effect on monthly runoff volumes. In fact, the LANDS parameters
initially calibrated on the PI watershed performed somewhat better on the
P3 watershed as indicated by the monthly runoff volumes. In any case, the
runoff results presented in Figures 17 and 18 are a true verification of
the LANDS subroutine and the calibration. Verification refers to the
results of split-sample testing, i.e., a comparison of simulated and
recorded values for a period of record other than that on which a model is
calibrated. The results in Figures 17 and 18 were obtained with
parameters calibrated in the PTR Model development work on data for July
to December 1972. The agreement between the 1973 simulated and recorded
values verifies the hydrologic simulation by the LANDS subroutine.
The simulation of sediment loss continues to require algorithm refinement
and testing. Due to sediment algorithm changes (Section IV), the sediment
parameters were re-calibrated to obtain the results presented in Figures
17 and 18. Even with the re-calibration efforts, certain discrepancies
remain between recorded and simulated monthly sediment loss. The
simulated sediment values on PI agree reasonably well with recorded values
except for the extremely large amounts in May and June. In these months,
a major portion of the monthly sediment loss was estimated because an
unusual sequence of events (described below) resulted in equipment
malfunctions on the PI watershed. Consequently, the recorded values
contain a certain margin of error. The P3 monthly sediment loss (Figure
18) is substantially less than the PI values due to the effects of
terracing and the grass waterway. The simulated monthly sediment loss for
P3 is somewhat closer to recorded values but further improvement is
needed. A more detailed examination of the effects of the grass waterway,
the terraces, and the existence of a winter cover crop on the P3 watershed
sediment loss is indicated.
Simulated and recorded storm hydrographs and curves of sediment
concentration (gm/1) and sediment mass flow (kg/min) for the PI watershed
are presented in Figures 19-23 for the 1973 storms of May 28 (AM), June 6,
June 13, June 21, and September 9. Corresponding results for the P3
watershed are shown in Figures 24-28 for the 1973 storms of May 28 (AM),
June 6, July 8, July 14, and September 9. Although these storms occurred
during a five-month summer period, the simulation accuracy is
representative of the results obtained throughout the 1973 calendar year.
These storms were chosen because they (1) demonstrate the effects of
tillage operations or (2) occur during the critical period for pesticide
loss, i.e. one to three months following application.
In general the agreement between recorded and simulated runoff is quite
good, while the agreement between recorded and simulated sediment loss is
fair to good. Numerous factors could be responsible for the deviations in
both runoff and sediment loss. However, before a full evaluation of the
simulation results can be performed, the sequence of events which occurred
on the watersheds during this period must be specified. Table 11 presents
75
-------
oo
s
o
rs
Ll-
Ll-
O
0.4
0.2
to
GO
o
LU
O
LU
CO
60
40
20
1200 -
co
O
LU
O
LU
OO
T r
_-^ \
i
RECORDED
SIMULATED
•EQUIPMENT MALFUNCTION
0
TIME, HOURS
Runoff and sediment loss from the PI watershed
on May 28 (a.m.), 1973
76
-------
cj
0.4
0.3
0.2
0.1
0.0
60
40
5 20
800
2 400 -
\*
RECORDED
SIMULATED
EQUIPMENT MALFUNCTION
MALFUNCTION CORRECTED
JLll=i—L L
1200
Figure 20.
1230
1300
1330
TIME. HOURS
Runoff and sediment loss from the PI
watershed on June 6, 1973
77
-------
B.4
8.3
bO
as
CJ
uT 0.2
0.1
8.0
ts>
60 h
40
- 20
1000
5 500
r; i
T r
RECORDED
SIMULATED
11
/ \
I \
i >h--4. L
1800
Figure 21.
1830 1900
, HOURS
1930
Runoff and sediment loss from the PI
watershed on June 13, 1973
78
-------
0.25
6.20
0.15
0.10
0.05
40
~ 20
300
2 200
!r 100
'0
1800
—I 1 L
347.2/1 \
^x
1 1 1 - 1 1 '
II 1 1 1
•A
:A
RECORDED
SIMULATED
I
I
I
I
I
f
1830 1900
TIME.HOURS
1930
Figure 22.
Runoff and sediment loss from the PI
watershed on June 21, 1973.
79
-------
0.20
0.15
8.10
0.05
0.00
12
P—I
too
80
40
T 1 1 T
1 T
T—q
2030
2100
2130
HME. HOURS
2200
Figure 23. Runoff and sediment loss from the PI watershed
on September 9, 1973
80
-------
co
o
0.12
0.08
0.04
0.00
8
CO
CO
O
o
LU
CO
CO
CO
o
o
UJ
CO
0
60
40 -
20 -
0
T T
T T
1 T
/ X_
I I
I I I I
L I
1 i i i i i i r
\ i
/ \
RECORDED
SIMULATED
——_>
-3 L
J L
j I
400
430 500
TIME, HOURS
530
Figure 24. Runoff and sediment loss from the P3 watershed
on May 28 (a.m.), 1973
81
-------
CO
s
o
A
u_
u_
o
z:
^
Oi
0.16 -
0.12 -
0.08 -
co
CO
O
Q
UJ
CO
CO
CO
o
LL)
5:
i—i
o
LU
CO
0
1200
1230
1330
TIME, HOURS
Figure 25. Runoff and sediment loss from the P3 watershed
on June 6, 1973
82
-------
00
o
f\
U_
u_
o
0.10
0.05
0.00
12
8
CO
00
o
UJ
o
UJ
CO
CD
ixi
CO
CO
o
LU
Q
LU
CO
I I I I
0
80
40
0
RECORDED
SIMULATED
430
600
TIME, HOURS
Figure 26. Runoff and sediment loss from the P3 watershed
on July 8, 1973
83
-------
co
o
i
CO
co
O
O
Ul
CO
CO
CO
o
LU
»-4
o
LU
CO
0.06
t 0.04
o
0.02
0.00
0
16
12
8
i—i r
T 1 \ T
1 1 l I i i
I SJ 1
i t l
i l i
X
i
RECORDED
•— SIMULATED
1800
1830
TIME, HOURS
J L
1900
1930
Figure 27. Runoff and sediment loss from the P3 watershed
on July 14, 1973
84
-------
o
A
u_
Lu.
O
OS
CO
CO
O
O
LU
CO
CO
CO
o
s
CO
RECORDED
SIMULATED
2100
2130
2200
2230
TIME, HOURS
Figure 28. Runoff and sediment loss from the P3 watershed
on September 9, 1973
-------
Table 11. SEQUENCE OF CRITICAL EVENTS AND OPERATIONS
ON THE PI AND P3 WATERSHEDS DURING THE 1973 GROWING SEASON
Date Watershed Event/Operation
Prior to PI Watershed was covered with soybean stubble and residue*
5-22-73
P3 Winter cover crop (barley) was harvested and removed.
5-22-73 PI, P3 Fertilizer was applied and incorporated with a
disc harrow.
5-28-73 PI, P3 Severe storms occurred (AM and PM storms) resulting
in high sediment loss from the freshly tilled land
surface.
6-4-73 PI, P3 Watersheds were refertilized and tilled (fertilizer
incorporation) with a disc harrow.
6-6-73 PI, P3 Severe storms occurred with high sediment loss from
the PI watershed.
6-7-73 PI Watershed was re-fertilized and tilled (fertilizer
incorporation) with a disc harrow.
6-13-73 PI Watershed was planted in the morning. Planting
operation includes a rolling cultivator which
lightly tills the soil. A severe evening storm
resulted in heavy sediment loss.
P3 No storm occurred.
6-15-73 P3 Watershed was planted and a rolling cultivator was
used.
6-21-73 PI Medium intensity storm occurred.
P3 No storm occurred.
11-7-73 P3 Soybeans were harvested.
11-14-73 P3 Winter cover crop, rye, was planted with a grain drill.
11-19-73 PI Soybeans were harvested and residue remained on the
watershed. No winter crop was planted.
86
-------
the dates and corresponding events and operations which occurred on the PI
and P3 watersheds during the 1973 growing season. In light of these
events and the simulation results for runoff and sediment loss, the
following conclusions are indicated:
(1) Tillage operations have a major effect on runoff and sediment
loss from small agricultural watersheds. The effect on
sediment loss appears to be somewhat greater than the effect
on runoff.
(2) Peak flow tends to increase, and the rising limb of the
hydrograph becomes steeper as the time since tillage
operations increases, i.e., freshly tilled soil tends to
dampen the peak and retard the overland flow. This is
especially noticeable when comparing early storms (Figures
19, 20, 21, 24, 25) with storms later in the season (Figures
22, 23, 26, 27, 28). Natural compaction of the land surface
and the compacting effect of rainfall tend to increase the
hydrologic responsiveness of the land surface as the growing
season progresses. The present version of the ARM Model does
not account for this phenomenon. Thus, the simulated
hydrographs indicate what might be expected from a no-tillage
cropping system.
(3) The storms of May 28 (Figures 19 and 24) and June 6 (Figures
20 and 25), especially on the PI watershed, dramatize the
enormous influence of tillage operations prior to a storm
event. Although the recorded data is sketchy due to
equipment malfunction, the general indication is that the
simulated PI sediment loss is considerable less than what
would have been observed. However, the June 21st storm on
PI, which occurred approximately one week after tillage
operations and after the June 13th event, is well simulated
for both runoff and sediment loss. Consequently, more
testing is needed to fully evaluate the discrepancies in
simulated and recorded sediment loss for the early season
storm events.
(4) The combined influence of the terraces and the grass waterway on
the P3 watershed results in much lower sediment loss than on
the PI watershed. In addition the winter cover crop on the
P3 watershed tends to lower the winter sediment loss from
what is observed on the PI watershed. In general, the
simulated monthly sediment loss and storm sediment curves are
reasonably close but somewhat higher than recorded values.
Further research is needed into the effects of terracing,
contour planting, grass waterways and other management
practices on the ARM Model parameters.
87
-------
(5) The spatial variation in rainfall is a critical factor in
simulation, especially in thunderstorm-prone areas such as
Georgia. Although the PI and P3 watersheds are only 2 miles
apart, the monthly rainfall shown in Figures 17 and 18 can
vary significantly. This is most noticeable in the months of
April and July. Also, the storms of June 13 and June 21 on
the PI watershed did not even occur on the P3 watershed while
the July 14 storm on P3 completely missed the PI watershed.
The spatial variation is especially critical if the rainfall
measured at the gage is not representative of what actually
fell on the watershed. The June 6th storm (Figure 20) on the
PI watershed is a possible example. Runoff volume and peak
flows for all the other major summer storms are either well
simulated or slightly higher than recorded; both are below
recorded values on June 6. Since the ARM Model does not
recognize the hydrologic effects of tillage operations, one
would expect the June 6th simulated values to be higher than
recorded. Thus the spatial variation in rainfall is a prime
suspect. This aspect needs to be evaluated in all areas
where thunderstorms occur.
In summary, although some discrepancies exist between simulated and
recorded runoff and sediment loss, the results presented here indicate
that the ARM Model can represent the general behavior of the PI and P3
watersheds. This provides a workable foundation for the analysis and
evaluation of the pesticide simulation results presented below.
PESTICIDE SIMULATION
The goal of the pesticide simulations was to evaluate the use of a
non-single-valued (NSV) adsorption/desorption function (described in
Section IV) to represent the pesticide-soil interactions. A conclusion of
the PTR Model work was that the single-valued (SV) adsortion/desorption
function did not appear to adequately simulate these interactions.1 The
major problems were associated with the simulation of pesticides contained
in both the water and sediment components of surface runoff, and the
division between the two transport phases. Since the goal of the
pesticide modeling effort is to use pesticide characteristics determined
from laboratory experiments, the pesticide parameters are not subject to
calibration. The values used to obtain the simulation results were those
derived from laboratory isotherm data. The parameter values are identical
for both the SV and NSV functions in order to provide a meaningful
evaluation of the performance of the different functions. The simulation
results will be described separately for each pesticide since paraquat and
diphenamid have quite different chemical and transport characteristics.
88
-------
Paraquat
Simulated and recorded monthly paraquat loss is presented in Figure 29 and
Table 12 for the PI and P3 watersheds. Paraquat is a highly ionic
herbicide that rapidly and essentially irreversibly adsorbs onto sediment
particles. Consequently, the question of single-valued versus
non-single-valued adsorption/desorption is irrelevant for paraquat
simulation since paraquat is entirely and permanently bound to the
sediment. Comparison of Figure 29 with Figures 17 and 18 will show that
the monthly paraquat loss closely follows the monthly sediment loss. This
is also true for the simulated curves. Deviations in the simulated
sediment loss are reflected by the simulated paraquat loss. This is also
evident in the storm graphs of paraquat concentration and mass removal
shown in Figures 30, 31 and 32 for the June 13, June 21 and September 9
storms on PI, and Figures 33, 34, and 35 for the July 8, July 14, and
September 9 storms on P3. For example, the June 21 storm on PI is
accurately simulated for both runoff and sediment loss (Figure 22). The
simulated paraquat concentrations and mass removal for this storm (Figure
31) are also in agreement with recorded values. On the other hand, the
June 13 storm on PI is under-simulated for sediment loss (Figure 21);
thus, the paraquat mass removal for this storm (Figure 30) is also
under-simulated, even though simulated and recorded concentrations are in
good agreement. This same relationship can be recognized in other storms
on both watersheds. In general, although concentration (ppm) is a
significant unit of measurement in terms of environmental effects, mass
removal (kg/min) is a more indicative measurement unit for simulating
pesticide transport. Pesticide concentrations can vary considerable
during a storm event for no apparent reason. This could be a result of
equipment problems leading to non-uniform application, or preferential
pesticide adsorption on particles passing the gage at any time. Pesticide
mass removal demonstrates the close association between pesticide loss and
the transport mechanisms of runoff and sediment loss.
For paraquat, the measured pesticide concentrations are almost independent
of the instantaneous flow and sediment concentrations. Comparison of the
paraquat concentrations measured on sediment from the PI and P3
watersheds, demonstrates that the P3 recorded paraquat concentrations are
considerably higher than those on PI. For pesticides like paraquat that
are permanently bound to the soil particles, the measured concentrations
are a direct function of the following factors:
(a) the amount of pesticide applied
(b) the amount of pesticide in the surface zone prior to application
(c) the depth of the active surface zone
(d) the rate of pesticide attenuation and degradation
The present version of the ARM Model includes input parameters to
accommodate factors a, c, and d (above). However, the Model assumes no
89
-------
600
400
200
co
CO
CO
o
<
a.
0
120
80
40
0
RECORDED
— SIMULATED
^PESTICIDE ANALYSIS DIS-
CONTINUED AFTER 9/9/73
PI Watershed
P3 Watershed
TIME, MONTHS
Figure 29. Monthly paraquat loss from the PI and P3
watersheds for the 1973 growing season
90
-------
Month
June
July
August
September**
October
November
December
Table 12. MONTHLY PARAQUAT LOSS
FROM THE PI AND P3 WATERSHEDS DURING THE
1973 GROWING SEASON
PI Watershed
Recorded Simulated
gm (Ibs) gm (Ibs)
703.5 (1.551) 298.7 (.658)
153.9 (.339) 204.8 (.451)
9.1 (.020) 6.8 (.015)
45.0 (.099) 87.6 (.193)
0.0 (0.0)
1.4 (.003)
34.1 (.075)
P3 Watershed
Recorded Simulated
gm (Ibs) gm (Ibs)
0.
98.
0.
4.
_
0
2
0
3
(0
(
(0
(.
.0)
.217)
.0)
010)
-
•
114
0
14
0
45
.4
.0
.5
.0
(.
(.
001)
252)
(0)
(.
(0
032)
.0)
.45 (.001)
5.9 (.013)
all paraquat loss was detected on sediment, paraquat was not found
in solution for any events.
**
pesticide analyses were discontinued after 9/9/73.
-------
RECORDED
SIMULATED
1800
1830
TIME, HOURS
Figure 30. Paraquat loss from the PI watershed on June 13, 1973
92
-------
Q-
Q.
o 40
o
o
20
0
12
8
o
ce
i
o-
0
1800
RECORDED
SIMULATED
1830
TIME, HOURS
1900
Figure 31. Paraquat loss from the PI watershed
on June 21, 1973
93
-------
30 -
a.
o.
« 20
O
O
<£.
3
cr
10
0
3.0
2.0
03
>
O
LU
C£
-------
Q.
Q.
60
o
o
-------
Q.
QL.
80-
O
o
O
40
0
0.8
i
UJ
C£
0.4
0.0
RECORDED
SIMULATED
1800 1830
TIME, HOURS
Figure 34. Paraquat loss from the P3 watershed
on July 14, 1973
96
-------
a: 80
40
o
o
0
0.8
0.6
o
Cu
01 0.4
-------
pesticide is present in the soil prior to application; future
modifications will include this capability. Thus, with the present Model,
some variation from measured concentrations was expected. The initial
simulation runs on the PI watershed produced paraquat concentrations much
lower than recorded. The depth of the active surface zone (SZDPTH
parameter) was then reduced from 3.2 mm to 1.6 mm and the daily
degradation rate (DEGCON parameter) was increased from 0.0001 to 0.002 per
day. These changes produced the results presented here. The parameter
changes are within reasonable limits for these parameters since little
information is available on the extent of an active surface zone, and mass
balance calculations have not produced reliable information on degradation
rates for paraquat. These are two areas which require further
investigation.
Although the parameter changes gave reasonable results for the PI
watershed, the same changes on the P3 watershed yielded low simulated
concentrations as shown in Figures 33, 34, and 35. These low
concentrations resulted in monthly paraquat loss close to recorded values
because simulated monthly sediment loss was much higher than recorded;
thus compensating errors occurred. Further investigation indicated that
prior to application, almost twice as much paraquat was present in the top
centimeter of the soil profile on the P3 watershed as compared to the PI
watershed, i.e. approximately 6.8 kg/ha of paraquat was detected on the PI
watershed and 12.5 kg/ha on the P3 watershed in the top centimeter of the
soil. The terraced P3 watershed experiences only much less sediment loss
and corresponding paraquat loss, resulting in more paraquat remaining on
the watershed from the previous season. This additional paraquat would,
in effect, double the stated application rate on the P3 watershed when
proportioned to the depth of the active surface zone. The result would be
a doubling of the simulated paraquat concentrations in Figures 33, 34, and
35 and closer agreement between simulated and recorded values. This
phenomenon did not occur in the PTR Model work because 1972 was the first
year of paraquat application. Thus, inclusion of the paraquat present in
the soil prior to application would further improve the agreement between
simulated and recorded values.
Diphenamid
The simulation of diphenamid loss allowed an initial evaluation and
comparison of the single-valued (SV) and non-single-valued (NSV)
adsorption/desorption functions. Since the majority of pesticides are
transported by both runoff and sediment, the behavior of these chemicals
in the soil-water environment is an important factor in simulating their
movement. The division between the water and sediment phase is critical
to the evaluation of the impact of different pesticides. Highly soluble
pesticides will infiltrate to greater depths in the soil profile than less
soluble ones. Soil erosion prevention practices will have a greater
effect on pesticides whose major transport mechanism is sediment loss
98
-------
while water-trans ported pesticides will be affected more by runoff
reduction practices. In addition, attenuation and degradation processes
are influenced differently by the solution and adsorbed states of the
pesticide. These processes determine the length of time following
application that a pesticide will be susceptible to transport by runoff
and sediment, and thus are critical to the simulation of pesticide
transport.
Figure 36 and Tables 13 and 14 (NSV function only) present the monthly
diphenamid loss for both the PI and P3 watersheds. The results of
employing both the SV and NSV functions are included in Figure 36. The
storm event simulations for diphenamid concentrations and mass removal are
presented in Figures 37, 38, 39 and 40 for the June 13 and June 21 events
on the PI watershed. Each figure presents the concentration (top graph)
and mass removal (bottom graph) for either the water or sediment phase.
Thus, for June 13, Figure 37 displays the diphenamid loss by sediment and
Figure 38 displays diphenamid loss by runoff. Figures 39 and 40 are the
analogous graphs for the storm of June 21. The corresponding results for
the P3 watershed for the July 8 and July 14 events are contained in
Figures 41, 42, 43 and 44. Results of employing both the SV and NSV
adsorption/desorption functions are displayed in all figures.
Since diphenamid is a highly degradable herbicide, recorded concentrations
in the runoff are essentially negligible within two months following
application. Consequently, the first runoff-producing storms after
application are the critical events for diphenamid loss. Since the major
storm events after application occurred in June on the Pi watershed,
essentially all the diphenamid loss occurred in June. However, July was
the major month for storms on the P3 watershed; thus, the recorded
diphenamid loss for P3 occurs in July.
In general, the simulation of diphenamid transport often shows
considerable deviation from the recorded values. The simulated monthly
diphenamid loss (Figure 36) on the PI watershed is reasonably close to the
observed values, while on the P3 watershed the values are quite different.
The monthly diphenamid loss on P3 emphasizes the need for accurate
hydrology and sediment simulation on storms following pesticide
application, especially for degradable pesticides like diphenamid. On
June 20, 1973 a relatively minor, but intense, thunderstorm (9.65 mm, 0.38
inches, in 9 minutes) on the P3 watershed produced a simulated peak flow
of 0.013 cms (0.46 cfs) although no actual runoff or sediment loss was
observed. This minor storm produced the entire simulated monthly
diphenamid loss for the month of June shown in Figure 36. Since the storm
occurred within five days of application, the diphenamid on the land
surface was exceptionally susceptible to movement even by the relatively
small amount of runoff simulated. Thus the diphenamid loss is
99
-------
800
600
400
CO
<
O£
CD
•s
CO
8 200
_J
O
t— c
1
Ll 1
UJ
§ 0
O
40
20
0
1 1 1 1 1 1 1 1
I
\
\
1
i\ PI Watershed
\\
v\
~ \'\
VI
\\\ , RECORDED
\\\ NSV SIMULATION
V,\ SV SIMULATION
\\\ PESTICIDE DISCONTINUED
\V AFTER 9/9/73
V
\
¥i
^
\
1 L-l^.^* L _ J. 1 I
1 1 I 1 1 1 1 1
\
. \
\
\ P3 Watershed
x \
\\
\ I
\ \ i \
- \ Y \ _
f \ \
/ ^\ \
/ X>^\
/ 1 NN\ * II i i
J J A S 0 N D
TIME, MONTHS
Figure 36. Monthly diphenamid loss from the PI and P3
watersheds during the 1973 growing season
100
-------
Month
June
July
August
September*
October
November
December
Table 13. DIPHENAMID LOSS FROM THE PI WATERSHED
DURING THE 1973 GROWING SEASON
On Sedinent In Water Total
Recorded Simulated Recorded Simulated Recorded Simulated
gm (Ibs) gm (Ibs) gm (Ibs) gm (Ibs) gm (Ibs) gm (Ibs)
12
2
7
01
,14
(.027)
(.002)
(0.0)
(0.0)
-
-
49.9
0.0
0.0
0.0
0.0
0.0
0.0
(.11)
0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
636.5
2.7
.03
0.0
-
-
-
(1.404)
(.006)
(0.0)
(0.0)
-
-
667.4
.9
0.0
0.0
0.0
0.0
0.0
(1.47)
(.002)
(0.0)
(0.0)
(o.o)
(0.0)
(0.0)
648.7
3.4
.04
.14
-
-
-
(1.44) 721.9
(.007) .9
(0.0)
(0.0)
-
-
0.0
0.0
0.0
0.0
0.0
(1.59)
(.002)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
pesticide analyses were discontinued after 9/9/73
Month
Table 14. DIPHEMAMID LOSS FROM THE P3 WATERSHED
DURING THE 1973 GROWING SEASON
On Sediment In Water Total
Recorded Simulated Recorded Simulated Recorded Simulated
gm (Ibs) gm (Ibs) gm (Ibs) gm (Ibs) gm (Ibs) gm (Ibs)
June
July
August
September *
October
November
December
0.0
1.1
0.0
.001
(0.0)
(.002)
(0.0)
(0.0)
0.0
1.1
0.0
0.0
0.0
0.0
0.0
(0.0)
(.002)
(0.0)
(0.0)
(o.o)
(0.0)
(0.0)
0.0
24.0
0.0
.15
(P. 3)
(.053)
(0.0)
(0.0)
32.2
9.1
0.0
0.0
0.0
0.0
0.0
(.071)
(.020)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
0.0
25.1
0.0
.15
(0.0)
(.055)
(0.0)
(0.0)
32.2
10.0
0.0
0.0
0.0
0.0
0.0
(.071)
(.022)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
pesticide analyses were discontinued after 9/9/73
-------
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3.2
1.6
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18
1 , 1 ! 1 1 1 1 1
%
_ \ -
\
\
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\
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- V ^
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\ RECORDED
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\ SV SIMULATION
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li i ,^iS"' _iv ^Tr | J ^.^J p !
00 1830 1900 1930
TIME, HOURS
Figure 37. Diphenamid loss on sediment from the PI
watershed on June 13, 1973
102
-------
o
i— a.
z o-
UJ
o •>
Z Oi
O LU
O I—
16 -
Q.
i—I
Q
O
v— i
LU
I
Q.
HH
Q
0
1800
RECORDED
NSV SIMULATION
SV SIMULATION
1830 1900
TIME, HOURS
Figure 38. Diphenamid loss in water from the PI watershed
on June 13, 1973
103
-------
I— o.
O I—
z z
O UJ
OS
t-H
O Q
i—< UJ
SI i/)
-------
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=r o:
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g~0.4
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o:
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t—i
Q
0.0
- RECORDED
--- NSV SIMULATION
-- SV SIMULATION
a.;
I-H I
O
1800
1830
TIME, HOURS
Figure 40.
Diphenamid loss in water from the PI watershed
on June 21, 1973
105
-------
o
C£ d.
f- 0-
LU «
01—
o uj
o s
UJ O
3:
CL.
0.8
0.4
0.0
0.03
O
UJ
to
o
a:
o
a.
i—i
o
0.02
0.01
0.00
i\
RECORDED
NSV SIMULATION
SV SIMULATION
430
500
530
TIME, HOURS
Figure 41. Diphenamid loss on sediment from the P3 watershed
on July 8, 1973
106
-------
RECORDED
— NSV SIMULATION
SV SIMULATION
0.0
430
Figure 42.
500 530
TIME, HOURS
Diphenamid loss in water from the P3 watershed
on July 8, 1973
107
-------
0.6
0.
O.
Q
LU
CO
o
o
0.4
0.2
D-
i—i
O
0.0
0.008
Q h^
i§ 0.004
LU Q
HI LU
D. CO
i—i
Q
0.000
RECORDED
NSV SIMULATION
SV SIMULATION
1800
1830
TIME, HOURS
Figure 43. Diphenamid loss on sediment from the
P3 watershed on July 14, 1973
108
-------
~ 0.08
2.
Q.
I— 0.
Z LU
O I—
D-
i—t
a
CD
LU
-------
directly dependent on the timing and magnitude of the individual storm
events on the watershed.
From an analysis of the simulated and recorded results in Figures 37 to
44, the following points are indicated:
(1) The results of comparing the SV and NSV adsorption/desorption
functions are inconclusive. The NSV function produces greater
diphenamid concentrations on sediment and less in solution than
the SV function. For the June 21 storm on the PI watershed
(Figures 39 to 40) the SV function represents reasonably well
the mass diphenamid removal both on sediment and in solution.
While on the P3 watershed, the NSV function is generally closer
to the recorded values.
(2) Although the June 13 simulated flow and sediment loss (Figure
21) are less than recorded, the simulated diphenamid loss is
much greater than recorded. Since the storm occurred
approximately six hours after pesticide application, the
discrepancy could be due to an inaccurate estimation of the
actual amount of pesticide applied or the amount lost by
degradation/volatilization in the intervening six hours. In
addition to the adsorption/desorption function, the assumed
depth of the surface zone has a critical impact on diphenamid
concentrations, especially during the initial storm events.
Since the initial storms following pesticide application are the
important events for pesticide loss, the uncertainties and
behavior of the attenuation and adsorption/desorption be further
investigated during this time period.
(3) Comparison of diphenamid concentrations for all four storms
indicates that simulated concentrations are greater than
recorded for the June storms (Figures 37 to 40) and less than
recorded for the July storms (Figures 41 to 49). Although the
storms occurred on different watersheds, this trend demonstrates
the possibility that the assumed first-order degradation rate
underestimates degradation during the initial month of the
growing season and overestimates degradation near the middle and
end of the growing season. A similar conclusion resulted from
the PTR Model work. The accurate representation of pesticide
attenuation processes is crucial to the evaluation of the amount
of pesticide available for movement by any storm event. Efforts
are presently underway to develop such a representation.
(4) As noted in the discussion of the paraquat simulation, the unit
of pesticide mass removal (grams/minute) is more indicative of
pesticide loss than the instantaneous pesticide concentrations.
This is especially noticeable in Figure 41. The instantaneous
diphenamid concentrations vary erratically throughout the event
110
-------
while the diphenamid mass removal is similar to the hydrograph
and the sediment mass loss. Thus the connection between
pesticide loss and its transporting mechanisms is clearly
displayed by the pesticide mass removal graphs.
CONCLUSIONS
The testing of the ARM Model has indicated that the hydrology and sediment
simulations reasonably represent the observed data while the pesticide
simulations can show considerable deviation from recorded values. This is
especially true for pesticides that move by both runoff and sediment loss.
The effects of tillage operations and management practices need to be
further evaluated for hydrology and sediment production. Parameter
changes as a result of agricultural practices need to be quantified.
Although the results of sediment simulation have been promising, certain
deviations in the results indicate a lack of understanding of certain
aspects of the physical process. Other processes in the soil erosion
mechanism, such as natural compaction of the surface following tillage and
the effect of rainfall intensity on the transport capacity, need to be
evaluated for possible inclusion in the Model. Although the hydrology
model has been applied to hundreds of watersheds in the United States, the
accompanying sediment model has been applied to only a few. If the ARM
Model is to be generally applicable, the most immediate need is to
evaluate the sediment simulation capability in varying climatic and
edaphic regions.
For pesticide simulation, the results demonstrate the need to further
investigate the processes of pesticide degradation and pesticide-soil
interactions. Both the SV and NSV adsorption/desorption functions require
further research. A non-equilibrium approach should be investigated to
determine its applicability. The interactions in the active surface zone
appear to control the major portion of pesticide loss especially for
highly sediment-adsorbed pesticides like paraquat. The depth of the
active surface zone and the extent of pesticide degradation in that zone
are critical to the simulation of pesticide loss for any storm event.
The need for testing the ARM Model in other regions also pertains to the
pesticide functions. The mechanisms recommended for further research
should be studied and evaluated in many regions of the country.
Investigations of these mechanisms is presently continuing for the Georgia
and Michigan watersheds. Other agricultural areas must be included in
future studies in order to establish the general applicability of the ARM
Model.
Ill
-------
SECTION IX
SENSITIVITY ANALYSIS
To fully evaluate, quantify, and display the effects of parameter changes
on simulation results, sensitivity analyses were performed for the
hydrology, sediment, and pesticide parameters of the ARM Model. The
sensitivity of the snowmelt and nutrient parameters will be investigated
in future work. The analyses involved a series of Model runs on the PI
watershed in Georgia. Each run was performed while changing the value of
a single parameter. The calibrated parameter set provided baseline
simulation results. Two Model runs were performed for each parameter with
parameter values greater than and less than the calibrated value. Thus, the
change in simulation results obtained from a change in the parameter value
indicates the sensitivity of the Model to the specific parameter. Tables
15, 16, and 17 present the ARM Model hydrology, sediment, and pesticide
values respectively chosen for the sensitivity analyses. The hydrology
parameters were analyzed on a six-month period, April 1973 to September
1973, while the sediment and pesticide parameters were analyzed on the
critical summer period, June 1973 to September 1973. -The results are
presented in Figures 45 to 51 in terms of the effects of parameter changes
on (1) total runoff, sediment, and pesticide loss during the simulation
period, and (2) peak runoff, sediment mass, and pesticide mass removal (in
water and on sediment) for the storm of June 21, 1973. The ARM Model
parameters are defined in Section IV, Tables 2, 3, and 4. The sensitivity
results are displayed in terms of percent parameter change versus the
resulting percent change in runoff, sediment, or pesticide loss. Thus the
slope (positive or negative) indicates the relative sensitivity of the
parameters; i.e., steeper slopes correspond to the more sensitive
parameters. The shaded areas in each figure indicate the region where the
stated parameter change produces a greater percent change in the quantity
of interest, e.g. a +44 percent change in JSER results in a +60 percent
change in sediment loss in Figure 46. The hydrology, sediment, and
pesticide parameter sensitivities are discussed separately below.
HYDROLOGY PARAMETERS
Figures 45 and 46 display the effects of changes in the hydrology
parameters on the total runoff for the April to September 1973 period and
the peak runoff for the June 21 storm, respectively, on the PI watershed.
Infiltration (INFIL) and lower zone soil moisture (LZSN) characteristics
have the greatest impact on total runoff volumes. This is generally true
in most areas of the country. For this reason, the INFIL and LZSN
parameters are most directly involved in the hydrologic calibration of a
specific watershed. Although the topographic (L, SS, NN) and vegetal
canopy (EPXM) parameters do affect runoff volume, their relative impact is
112
-------
Table 15. HYDROLOGY PARAMETER VALUES FOR SENSITIVITY ANALYSIS
(English Units)
Parameter
UZSN
LZSN
INFIL
INTER
SS
L
NN
K3
EPXM
Baseline Value
0.05
18.0
0.5
0.7
0.05
160.0
0.20
0.40
0.12
Trial #1
0.01
14.0
0.2
0.4
0.02
100.0
0.10
0.20
0.06
Trial #2
0.25
22.0
0.8
1.0
0.08
220.0
0.30
0.60
0.18
Table 16. SEDIMENT PARAMETER VALUES FOR SENSITIVITY ANALYSIS
(English Units)
Parameter
Baseline Value
Trial #1
Trial #2
JRER
KRER
JSER
KSER
COVPMO
SRERTL
2.2
0.17
1.8
1.2
J 0 A S 0
0.0, 0.0, 0.25, 0.5, 0.7
5.0, '2.0
1.4
0.10
1.0
0.8
3.0
0.24
2.6
1.6
increased 20% decreased 20%
increased 20% decreased 20%
113
-------
Table 17. PESTICIDE PARAMETER VALUES FOR SENSITIVITY ANALYSIS
CEnglish Units)
Parameter
CMAX
DD
BULKD
K
N
NP
SSTR
UZDPTH
SZDPTH
DEGCON
DESORP
Baseline Value**
0.00026
0.0
103.0
1.8
1.6
3.7
5*4.002
6.125
0.125
0.08
YES
Trial #1
0.00013
0.00010
93.0
0.6
1.0
2.3
5*2.0
4.125
0.062
0.04
NO
Trial #2
0.00052
0.00020
113.0
3.0
2.2
5.1
5*6.0
8.125
0.250
0.12
**
Baseline pesticide values are for diphenanrid characteristics
114
-------
-1-30 -
-30 -
-30
-20 -10 0 +10 +20
% CHANGE IN INDICATED PARAMETERS
+ 30
+40
Figure 45. Hydrology parameter sensitivity - total runoff
-------
+ 30
« 9/9/73 STORM-
USED FOR EPXM
-40 -30 -20 -10 0 +10 +20
% CHANGE IN INDICATED PARAMETERS
+ 30
+ 40
Figure 46. Hydrology parameter sensitivity - peak runoff
(PI watershed, storm of June 21, 1973)
-------
less than what might be expected. The interflow parameter (INTER) is
generally thought to have no effect on runoff volume. This is generally
true, especially in large watersheds. The runoff change shown in Figure
45 due to the interflow parameter is a result of the manner in which
interflow is calculated in the ARM Model. The interflow component is
subtracted from the moisture available for surface runoff, and reaches the
stream channel through a delaying storage mechanism. The remaining
surface runoff undergoes a kinematic overland flow routing technique which
determines the amount of surface runoff reaching the stream channel during
the time interval. The surface runoff which does not reach the stream is
available to infiltrate during the next time interval. Thus as interflow
increases a larger fraction of surface moisture is assured of reaching the
stream through the interflow storage mechanism resulting in a minor
increase in runoff volume.
The effects of parameter changes on peak runoff (Figure 46) are similar
but not as dramatic. Infiltration and soil moisture characteristics
remain important. However, topographic factors such as slope, length of
flow, and surface roughness have a significantly greater impact on peak
runoff rates as compared to runoff volumes. The relative ranking of the
parameters is much the same in both Figures 45 and 46. However, overland
flow length (L) and surface roughness (NN) increase in importance, and the
impact of the interflow parameter (INTER) is reversed. An increase in
interflow will reduce peak runoff while slightly increasing total runoff.
In general, Figures 45 and 46 indicate that agricultural management
practices which influence land slope, surface roughness, and overland flow
length have a relatively greater impact on peak runoff than on total
runoff volumes.
SEDII-IENT PRODUCTION PARAMETERS
The effects of sediment parameter changes on total sediment production
(June to September 1973) and peak sediment loss (storm of June 21, 1973)
on the PI watershed are shown in Figures 47 and 48, respectively. A
review of the sediment algorithm and parameters described in Section IV
would be helpful to the understanding of this discussion. In general, the
washoff parameters (JSER, KSER) appear to have the greatest impact on both
total and peak sediment loss. Since the simulation period for the
sensitivity analysis was during the summer growing season, tillage
operations produced a large volume of detached soil fines. Thus, sediment
transport by flow was not restricted by the amount of soil fines available
for transport. The singular importance of the washoff, or transport,
parameters is because the washoff process was the controlling mechanism
during the simulation period. In areas where tillage operations are not
performed, or during seasons when the land surface is not disturbed, the
soil splash parameters (JRER, KRER) would have a greater impact than is
indicated in Figures 47 and 48. In such circumstances, the soil splash
mechanism could control sediment loss by limiting the amount of detached
117
-------
Co
+ 30 -
-30
-40 -30 -20 -10 0 +10 +20 +30 +40
% CHANGE IN INDICATED PARAMETERS
Figure 47. Sediment parameter sensitivity - total sediment loss
-------
-F30 -
* 9/9/13 STORM USED
FOR COVPMO
-30 -
-40
-20 -10 0 +10 -1-20
% CHANGE IN INDICATED PARAMETERS
Figure 48. Sediment parameter sensitivity - peak sediment loss
(PI watershed, storm of June 21, 1973)
-------
soil fines available for washoff by overland flow, i.e., detached soil
fines would be less than the transport capacity of overland flow Since
the soil splash parameters determine the detachment of soil fines, their
effect on sediment loss would be greater than the effect of the washoff
parameters when the land surface is undisturbed.
The two remaining sediment parameters are the monthly vegetal cover
fraction (COVPI10) and the detached fines produced by tillage operations
(SRERTL). The sensitivity of each of these parameters indicated in
Figures 47 and 48 is influenced by the fact that the analysis was
performed on a summer period. The major events during this period
occurred in June and July when vegetal cover was minimal; hence, the
effect of COVPMO on the total sediment loss is rather small. Since no
crop canopy had developed for the June 21 stoni, the COVPMO sensitivity in
Figure 48 was derived from the September 9 storm on PI. The impact of
cover would be much greater during the late fall when a full canopy would
exist. On the other hand, the impact of SRERTL as shown in Figures 47 and
48 is relatively greater during the summer period due to the possible
occurrence of storms following tillage operations. This is indicated by
the greater impact of SRERTL on peak sediment loss (Figure 48) than on
total sediment (Figure 47) because the June 21 storm occurred within one
week of planting and tillage operations. In reality little is known about
the absolute value of detached fines resulting from different tillage
operations. Logically, one would expect that the effects of tillage would
not extend more than one to two months, i.e. the amount of detached fines
from tillage operations would not limit transport of sediment by overland
flow until one to two months following the operation. However, further
investigation of this topic is needed.
Although the sensitivity of the sediment parameters is affected by the
period on which the analysis was performed, the summer period is the
critical time for simulation of pesticide loss. Consequently, the
analysis also indicates the relative importance of sediment parameters for
simulating pesticides transported by sediment particles.
PESTICIDE PARAMETERS
{neFiaur^S4Qf l^^ r^V0" the Pesti<^* parameters are shown
in Figures 49, 50 and 51. The effects of parameter changes on total
pesticide loss (June to September 1973) is presented in Figure 49 while
^ °6-k PeSt1c1de ™»val iJ watlr ani on
dlEin? ^t?^ °Si?6-k PeSt1c1de ™»val i watr ani on
sediment (June 21 storm on Pi) is shown in Figures 50 and 51
respectively. The relative positions of the parameter sensitivity lines
™re°n ''1 "
int -
points are noteworthy:
^ *? "f1^1*
of values tested for the present version of the
he * "1^1* 1"P«ct on pesticide loss
the
120
-------
+30 -
-30 -
-40 -30 -20 -10 0 -1-10 +20
% CHANGE IN INDICATED PARAMETERS
+ 30
40
Figure 49. Pesticide parameter sensitivity - total pesticide loss
-------
+ 80
-1-60
-30
Figure 50.
-10 0 +10 +30 +50 +70
CHANGE IN INDICATED PARAMETERS
iH6 farameter sensitivity peak
water "
122
-------
-1-80
-70 -50 -30 -10 0 -HO +30 +50 +70
% CHANGE IN INDICATED PARAMETERS
Figure 51. Pesticide parameter sensitivity peak
pesticide loss on sediment (PI watershed, storm
of June 21, 1973)
123
-------
pesticide algorithms. In effect, the equilibrium pesticide
concentration in runoff never approaches the pesticide
solubility.
(2) As a corollary to (1), the adsorption/desorption characteristics
for the specific pesticide-soil combination are the major
determinants of pesticide loss. Other than pesticide
application (SSTR) which obviously has a critical effect on
pesticide loss, the adsorption/desorption characteristics (K, N,
NP) have the greatest impact (i.e. steepest slopes in Figures
49, 50, and 51) on both total and peak pestictde loss.
(3) The soil bulk density (BULKD) is an important parameter since it
determines the mass of soil involved in the pesticide-soil -water
equilibrium in each vertical soil zone. An increase in BULKD
results in a greater mass of soil in each zone. For pesticides
which move by both runoff and sediment loss, the larger surface
soil mass would retain more pesticide in the surface zone.
Thus, more pesticide would be available for transport from the
active surface zone. The increase in pesticide loss with BULKD
in Figures 49, 50 and 51 demonstrates this effect. On the other
hand, pesticides like paraquat that are completely adsorbed onto
sediment particles would behave differently. Since complete
mixing is assumed in the surface zone, the greater surface soil
mass resulting from a larger BULKD would produce lower pesticide
concentrations in the surface zone for the same application
rate. The lower concentrations would result in less total and
peak pesticide loss. Consequently, the relative impact of
changes in soil bulk density is dependent upon the
adsorption/desorption characteristics of the specific
pesticide-soil combination.
(4) The depth of the active surface zone (SZDPTH) has essentially
identical effects on pesticide loss as described above for bulk
density. Increasing SZDPTH results in a greater soil mass in
the active surface zone. The effects on pesticide loss
described above are due to the greater soil mass. Comparison of
the SZDPTH and BULKD sensitivity lines in Figures 49, 50 and 51
demonstrates the parallel effects. The differences between
S*f J™DTuare du(: to the effect of BULKD °* all the soil zones
t^+lf I7n5futains-,0nly to the surface zone- Thus* the
conation 1S * function of the pesticide-soil
(5) f J^TT soil zone (UZDPTH) ha* a relatively minor
P?h«1C1?e 10S^ Wlth1n the ran9e of Parameter values
5nt ^ ^^ism for pesticide loss from the upper
small oortnn n i€0mp°!;!nt of runoff- Since Interflow Is a
small portion of total runoff during the summer months on the PI
124
-------
watershed, Figures 49, 50 and 51 indicate the minimal effect of
UZDPTH. However, for highly soluble pesticides in areas with
significant interflow, the UZDPTH parameter would have greater
impact.
(6) The pesticide degradation rate (DEGCON) has a greater influence
on total pesticide loss than is indicated in Figure 49.
Degradation determines the time during which significant
pesticide loss can occur. During the pesticide sensitivity
trials, the only significant events for the loss of degradable
pesticides occurred on June 13 and June 21. Since pesticides
were applied on June 13, the daily first-order degradation rate
had no effect on pesticide loss for that storm. Figures 50 and
51 demonstrate the influence of degradation for the storm of
June 21 on peak pesticide loss in water and on sediment
respectively. Thus, the DEGCON sensitivity lines in Figures 50
and 51 are more indicative of the importance of degradation
rates on pesticide loss than the corresponding lines in Figure
49.
CONCLUSIONS
The utility of the sensitivity analyses performed on the ARM Model
parameters (excluding snow and nutrient parameters) is the information and
understanding gleaned from an analysis of Model behavior resulting from
parameter variations. Comparing the ARM Model results with the physical
processes simulated can provide a sound base for further algorithm
refinements. Highly sensitive parameters indicate topics for additional
investigation. Moreover, an understanding of the ARM Model is critical to
successful calibration and application to other areas. Although the
results presented here should not be extrapolated beyond the individual
parameter values in Tables 15, 16, and 17, the relative importance and
impact of the various parameters is generally valid for agricultural
watersheds in the southern Piedmont. Experience indicates that the.
relative ranking of the hydrology parameters is more widely applicable
across the United States. However, testing in other climatic,
topographic, and edaphic regions, and with a larger range of parameter
values is needed before a similar claim can be made for the sediment and
pesticide parameters. In general, the results indicate that the most
sensitive parameters are related to soil moisture and infiltration, land
surface, sediment transport, pesticide-soil interactions, and pesticide
degradation. Study of these topics would provide the greatest benefit to
further algorithm refinement.
125
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SECTION X
CONCLUSIONS AND RECOMMENDATIONS
Unfortunately, as man acquires a greater understanding of his physical
environment, the number and complexity of the questions which probe his
mind tend to increase rather than decrease. In other words, research
often tends to raise more questions than it answers. In many respects
this is true for the research effort on the continued development and
refinement of the ARM Model described in this report. Some questions have
been answered while new problems have been uncovered. Perhaps the
greatest benefit derived from this work is the insight and increased
understanding of the processes controlling the quantity and quality of
agricultural runoff. As these processes are further studied, better
simulation methods will develop. This understanding is a significant
addition to the existing body of knowledge on this topic. This report is
an attempt to distribute this additional knowledge to the scientific
community for general review and comment. Thus, the major findings of
this research effort are as follows:
(1) The Agricultural Runoff Management (ARM) Model has been used
successfully for simulating runoff, sediment, and pesticide loss
from small agricultural watersheds. Model testing for sediment
and pesticide loss has been performed on watersheds in the
Southern Piedmont and is presently underway on watersheds in the
Great Lakes region.
(2) The simulation of surface runoff with the ARM Model has been
verified by split-sample testing for the Southern Piedmont
watersheds. The hydrology parameters calibrated on six months
of 1972 data allowed the Model to simulate 1973 data with
reasonable accuracy. Past experience with the hydrologic
simulation methodology indicates that similar accuracy can be
expected in other geographical regions.
(3) The method of snowmelt simulation presented in this report has
been employed successfully on watersheds across the United
States. Although its use on small agricultural watersheds has
been limited, the methodology of energy balance calculations
is conceptually valid. Calibration and testing is presently
underway on watersheds in the Great Lakes region.
(4) Tillage operations and practices have a significant impact on
both surface runoff and sediment loss from watersheds in the
Southern Piedmont. The effect is relatively greater on sediment
loss than on surface runoff and tends to decrease with time
since the last tillage operation. Both total sediment loss and
126
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peak sediment concentrations are increased by frequent tillage
operations while peak runoff is generally reduced and delayed in
time.
(5) The ARM Model simulation of sediment production is relatively
accurate except for storms immediately following tillage
operations. In general, monthly sediment loss and storm
concentrations are close to observed values when the hydrologic
simulation is accurate. The sediment simulation methodology
allows for the inclusion of tillage operations, but further
testing and calibration are needed to more reliably quantify
tillage effects.
(6) Simulation of pesticide loss from the Southern Piedmont
watersheds with the ARM Model indicates the following:
a. Simulation results are good for pesticides like paraquat
that are completely adsorbed onto sediment particles. In
these cases, the accuracy of the pesticide simulation is
directly dependent upon the accuracy of the sediment
simulation.
b. Simulation of pesticides that move both in water and on
sediment is dependent upon the partitioning between the two
phases (water and sediment) as specified by the
adsorption/desorption function. Simulation results for this
type of pesticide (e.g. diphenamid) using laboratory
isotherm data is fair to poor. Initial comparison of
simulation results from single-valued (SV) and
non-single-valued (NSV) adsorption/desorption functions is
inconclusive. The SV function appears to simulate some
storms better than the NSV function, but the reverse is true
for other storms. Further comparisons and evaluations are
warranted.
c. Pesticide attenuation processes are critical to the
simulation of pesticide loss since they determine the amount
of pesticide available for transport from the land surface.
Storms, even minor ones, occurring immediately or soon after
pesticide application are the major events for pesticide
loss. The applied pesticide has not attenuated to a
significant extent; thus, it is highly susceptible to
transport. The first order degradation rate presently used
in the ARM Model appears to underestimate attenuation at the
beginning of the growing season and overestimate it at the
middle and end of the growing season. Accurate simulation
of pesticide attenuation would provide a more valid base for
the evaluation of adsorption/desorption functions and
improvement of the overall pesticide simulation.
127
-------
(7) The ARM Model provides a structure for simulating the transport
and soil transformations of plant nutrients. Testing and
comparison of simulated and observed results will provide a
basis for modification and refinement of the nutrient algorithms
presented in this report. Data from the Southern Piedmont and
Great Lakes watersheds is expected to be available for nutrient
model testing in the near future.
(8) A sensitivity analysis of the ARM Model parameters for
hydrology, sediment production, and pesticide loss indicates
that the most sensitive parameters are related to soil moisture
and infiltration, land surface sediment transport,
pesticide-soil interactions, and pesticide degradation. These
mechanisms are the critical ones for the accurate simulation of
pesticide loss from agricultural watersheds.
The questions that have been raised or left unanswered by this research
effort are presented below in terms of needs, or opportunities, for
further study of the simulation of agricultural runoff. It is hoped
that others in the research community will recognize the importance of
these topics and provide impetus for further research efforts.
(1) Application and testing of the ARM Model on watersheds in
different regions of the country is of primary concern at this
time. The hydrologic methodology of the ARM Model has
demonstrated its general applicability from the results of
testing on hundreds of watersheds; similar testing is needed for
the sediment production methodology. In this way, the
simulation of the transport mechanisms (runoff and sediment
loss) for agricultural pollutants can be tested, refined, and
verified for general application. Moreover, the relationship of
the ARM Model parameters to climatic and edaphic characteristics
could be investigated.
(2) Testing of the nutrient model is crucial to the reliable
simulation of plant nutrients. Although a nutrient model has
been developed, only testing and comparison with observed data
can indicate the validity of the model assumptions and the need
for model refinements.
(3) The impacts of different agricultural management techniques on
the transport mechanisms of runoff and sediment loss need to be
further investigated. Since the ARM Model will be applied to
managed agricultural lands, the relationships between land
management techniques and the ARM Model parameters must be
established. This is a necessity if the Model is to be used for
evaluating the efficacy of land and agricultural management
plans. Also, for widespread use, the Model must accommodate
practices employed in different agricultural regions of the
country.
128
-------
(4) Pesticide-soil interactions and pesticide attenuation processes
must be further investigated in order to improve the accuracy
and reliability of the pesticide simulation. Both the
single-valued and non-single-valued adsorption/desorption
functions warrant further investigation, in addition to a
kinetic, or non-equilibruim, approach to the pesticide-soil
interaction processes. First-order pesticide degradation should
be replaced with a more sophisticated degradation model.
Various candidate approaches are presently under investigation.
Environmental conditions (e.g. soil temperature, soil moisture,
and oxygen content) need to be included where they are
significant.
(5) To promote the general use of the ARM Model for investigation,
evaluation, and management of agricultural runoff, the following
recommendations are extended:
a. The ARM Model structure should be modified to allow a more
user-oriented method of application. The acceptance and use
of the ARM Model by the user community is contingent upon
the ease of Model application, calibration, parameter
evaluation, data management, and output interpretation. To
date, Model development has concentrated on the testing and
evaluation of algorithms to simulate the physical processes.
Efforts should now be directed to the goal of making the
Model more amenable for use by potential users.
b. The use of the ARM Model as a tool for the planning and
evaluation of agricultural management techniques for the
control of sediment, pesticides, and nutrients should be
demonstrated. It is insufficient to develop and document a
model like the ARM Model without a clear demonstration of
its potential application in the planning and management
process. In addition, recommendations, guidelines, and a
proposed methodology should be developed to insure the
effective use and to avoid misuse of the ARM Model.
129
-------
SECTION XI
REFERENCES
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Runoff Model for Agricultural Lands. Office of Research and
Development, U.S. Environmental Protection Agency, Washington D.C.
EPA 660/2-74-013. December 1973. 211 p.
2. Crawford, N.H. and R.K. Linsley. Digital Simulation in Hydrology:
Stanford Watershed Model IV. Department of Civil Engineering,
Stanford University. Stanford, California. Technical Report No.
39. July 1966. 210 p.
3. Hydrocomp Simulation Programming: Operations Manual. Hydrocomp
Inc. Palo Alto, California, 2nd ed. 1969. p.1-1 to 1-27,
p. 3-5 to 3-16.
4. Negev, H.A. Sediment Model on a Digital Computer. Department of
Civil Engineering, Stanford University. Stanford, California.
Technical Report No. 76. March 1967. 109 p.
5. Meyer, L.D., and W.H. Wischmeier. Mathematical Simulation of the
Process of Soil Erosion by Water. Trans. Am. Soc. Agric. Eng.
12(6):754-758, 762, 1969.
6. David, W.P., and C.E. Beer. Simulation of Sheet Erosion, Part I.
Development of a Mathematical Erosion Model. Iowa Agriculture and
Home Economics Experiment Station, Ames, Iowa. Journal Paper No.
J-7897. 1974. 20 p.
7. Baker, D.N., and R.E. Meyer. Influence of Stand Geometry on Light
Interception and Net Photosynthesis in Cotton. Crop Science.
6:15-19, January-February 1966.
8. Duncan, W.G., R.S. Loomis, W.A. Williams, and R. Hanan. A Model
for Simulating Photosynthesis in Plant Communities. Hilgardia.
38(4):181-205, March 1967.
9. Richie, J.T. Model for Predicting Evaporation from a Row Crop with
Incomplete Cover. Water Resour. Res. 8(5):1204-1213, October 1972.
10. Watson, D.J. Comparative Physiological Studies on the Growth of
Field Crops: I. Variation in Net Assimilation Rate and Leaf Area
between Species and Varieties, and within and between Years.
Annuals of Botany. 11(41):41-76, January 1947.
130
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11. McCollum, R.E. Department of Soil Science, North Carolina State
University, Raleigh, N.C. (unpublished material).
12. Davidson, J.H., and J.R. McDougal. Experimental and Predicted
Movement of Three Herbicides in a Water-Saturated Soil. J. Environ.
Qual. 2(4):428-433, October-December 1973.
13. Van Genuchten, M.Th., J.M. Davidson, and P.J. Wierenga. An
Evaluation of Kinetic and Equilibrium Equations for the Prediction
of Pesticide Movement through Porus Media. Soil Sci. Soc. Amer. Proc.
38:29-35, January-February 1974.
14. Davidson, J.M., R.S. Mansell, and D.R. Baker. Herbicide
Distributions within a Soil Profile and their Dependence Upon
Adsorption-Desorption. Soil Crop Sci. Soc. Florida Proc. 1973. 26p.
15. Brown, D.S. U.S. Environmental Protection Agency, Southeast
Environmental Research Laboratory, Athens, Georgia, (personal
communication). February 1975.
16. Farmer, W.J. and J. Letey. Volatilization Losses of Pesticides
from Soils. Office of Research and Development, U.S. Environmental
Protection Agency. Washington D.C. EPA-660/2-74-054. August 1974.
80 p.
17. Steen, W.C. U.S. Environmental Protection Agency, Southeast
Environmental Research Laboratory. Athens, Georgia, (personal
communication). November 1974.
18. Crawford, N.H. Simulation Problems. Simulation Network
Newsletter. Hydrocomp Inc. Palo Alto, California. Vol. 6 No. 4.
May 15, 1974.
19. Snow Hydrology, Summary Report of the Snow Investigations. U.S.
Army Corps of Engineers, North Pacific Division. Portland, Oregon.
1956. 437 p.
20. Anderson, E.A., and N.H. Crawford. The Synthesis of Continuous
Snowmelt Runoff Hydrographs on a Digital Computer. Department of
Civil Engineering, Stanford University. Stanford, California.
Technical Report No. 36. June 1964. 103 p.
21. Anderson E.A. Development and Testing of Snow Pack Energy Balance
Equations. Water Resour. Res. 4(1):19-37, February 1968.
22. Hydrocomp Inc. Probable Maximum Floods of the Baker River,
Washington. Report prepared for the Puget Sound Power and Light
Company. Palo Alto, California. 1969. 70 p.
131
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23. Hydrocomp Inc. Simulation of Discharge and Stage Frequency for
Floodplain Mapping on the North Branch of the Chicago River. Report
prepared for the Northeastern Illinois Planning Commission. Palo Alto,
California. February 1971. 75 p.
24. Hydrocomp Inc. Determination of Probable Maximum Floods on the
North Fork of the Feather River. Report prepared for Pacific Gas and
Electric. Palo Alto, California, October 1973. 104 p.
25. Hydrocomp Inc. Simulation of Standard Project Flood Flows for the
Bull Run Watershed. Report prepared for Bureau of Water Works of the
City of Portland. Palo Alto, California. March 1974. 67 p.
26. Stevenson, F.J. Origin and Distribution of Nitrogen in Soil.
In: Soil Nitrogen, W.V. Bartholomew and F.E. Clark (eds.), Madison,
Wis., Am. Soc. Agron. Agronomy Monograph No. 10, 1965. p. 1-42.
27. Loehr, R.C. Agricultural Waste Management: Problems, Processes,
and Approaches. New York, Academic Press, 1974. 576 p.
28. Dutt, G.R., M.T. Shaffer, and W.J. Moore. Computer Simulation
Model of Dynamic Bio-Physiochemical Processes in Soils. University
of Arizona, Department of Soils, Water and Engineering Agricultural
Experiment Station. Tucson, Ariz. Technical Bulletin 196. 1972.
101 p.
29. Hagin, J., and A. Amberger. Contribution of Fertilizers and Manures
to the iJ- and P- Load of Waters. A Computer Simulation. Report
Submitted to Deutsche Forschungs Gemeinschaft. 1974. 123 p.
30. Frere, M.H., C.A. Onstad, and H.N. Holtan. ACTMO, an Agricultural
Chemical Transport Model. U.S. Department of Agriculture,
Agricultural Research Service. Hyattsville, Maryland. ARS-H-3.
1975. 54 p.
31. Hehran, M., and K.K. Tanji. Computer Modeling of Nitrogen
Transformations in Soils. J. Environ. Qual. 3(4):391-395, 1974.
32. Oddson, J.K., L. Letey, and L.V. Weeks. Predicted Distribution of
Organic Chemicals in Solution and Adsorbed as a Function of
Position and Time for Various Chemicals and Soil Properties. Soil
Sci. Soc. Amer. Proc. 34:412-417, 1970.
33. Sawyer, C.N., and P.L. McCarty. Chemistry for Sanitary Engineers,
2nd ed. New York, McGraw-Hill Book Company, 1967. p. 204-205.
34. Stanford, G., and S.J. Smith. Nitrogen Mineralization Potential in
Soil. Soil Sci. Soc. Amer. Proc. 36:465-472, 1972.
132
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35. Stanford, G., M.H. Frere, and D.E. Schwaninger. Temperature
Coefficient of Soil Nitrogen Mineralization. Soil Sci.
115:321-323, 1973.
36. Stanford, G., and E. Epstein. Nitrogen Mineralization—Water
Relations in Soils. Soil Sci. Soc. Amer. Proc. 38:103-107, 1974.
37. Bartholomew, W.V. Mineralization and Immobilization of Nitrogen in
the Decomposition of Plant and Animal Residues. In: Soil Nitrogen,
W.V. Bartholomew and F.E. Clark (eds.), Madison, Wis. Am. Soc. Agron.
Agronomy Monograph No. 10, 1965. p. 285-306.
38. Alexander, M. Nitrification. In: Soil Nitrogen, W.V. Bartholomew and
F.E. Clark (eds.), Madison, Wis., Am. Soc. Agron. Agronomy Monograph
No. 10, 1965. p. 307-343.
39. McLaren, A.D. Temporal and Vectorial Reactions of Nitrogen in
Soil: A Review. Can. J. Soil Sci. 50(2):97-109, 1970.
40. Broadbent, F.E., and F. Clark. Denitrification. In: Soil Nitrogen,
W.V. Bartholomew and F.E. Clark (eds.), Madison, Wis. Am. Soc. Agron.
Agronomy Monograph No. 10, 1965. p. 344-359.
41. Stanford, G., R.A. Vander Pol, and S. Dzienia. Denitrifi cation
Rates in Relation to Total and Extractable Soil Carbon. Soil Sci.
Soc. Amer. Proc. 39:284-289, 1975.
42. Stanford, G., S. Dzienia, and R.A. Vander Pol. Effect of
Temperature on Denitrification Rate in Soils. Soil Sci. Soc. Amer.
Proc. 39(5):867-875, August-September 1975.
43. Viets, Franck G. The Plant's Need for and Use of Nitrogen.
In: Soil Nitrogen, W.V. Bartholomew and F.E. Clark (eds.), Madison,
Wis., Am. Soc. Agron. Agronomy Monograph No. 10, 1965. p.503-549.
44. Van den Honert, T.H., and J.J.M. Hooymons. On the Absorption by
Maize in Water Culture. Acta Bot Neerlandica 43:376-384, 1955.
45. Mortland, M.M., and A.R. Wolcott. Sorption of Inorganic Nitrogen
Compounds by Soil Materials. In: Soil Nitrogen, W.V. Bartholomew
and F.E. Clark (eds.), Madison, Wis., Am. Soc. Agron. Agronomy
Monograph No. 10, 1965. p. 150-197.
46. Larsen, S. Soil Phosphorus. Advan. Agron. 19:151-210, 1967.
47. Fried, M., C.E. Hagen, J.F. Saiz del Rio, and J.E. Leggett. Kinetics
of Phosphate Uptake in the Soil-Plant System. Soil Sci. 84(6):427-437,
1957.
133
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48. Enfield, C.G., and D.C. Shew. Comparison of Two Predictive
Nonequilibrium One-Dimensional Models for Phosphorus Sorption and
Movement through Homogeneous Soils. J. Environ. Qual. 4(2):198-202,
1975.
49. Acton, F.S. Numerical Methods that Work. New York, Harper & Row,
1970. 541 p.
50. Payne, W.R., Jr., J.D. Pope, Jr., and J.E. Benner. An Integrated
Method for Trifluralin, Diphenamid, and Paraquat in Soil and Runoff
from Agricultural Land. J. Agr. Food Chem. 22(l):79-82, January-
February 1974.
51. Barnes, B.S. Discussion of Analysis of Runoff Characteristics.
Trans. Am. Soc. Civil Eng. 105:106, 1940.
52. Wischmeier, W.H., and D.D. Smith. Predicting Rainfall-Erosion
Losses from Cropland East of the Rock Mountains. U.S. Department
of Agriculture, Agricultural Research Service. Agricultural
Handbook No. 282. 1965. 47 p.
53. Wischmeier, W.H., L.B. Johnson, and B.V. Cross. A Soil
Erodibility Nomograph for Farmland and Construction Sites.
J. Soil Water Cons. 26(5):189-193, 1971.
54. Wischmeier, W.H. Estimating the Soil Loss Equation's Cover and
Management Factor for Undisturbed Areas. In: Present and Prospective
Technology for Predicting Sediment Yields and Sources. U.S.
Department of Agriculture, Agricultural Research Service.
ARS-S-40. June 1975. p. 118-124.
134
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SECTION XII
APPENDICES
A. ARM Model User Manual
Model Operati on and Parameters 136
Data Requirements and Model I/O 146
Parameter Evaluation and Calibration 179
B. ARM Model Sample Input Listing 190
C. ARM Model Source Listing 201
135
-------
APPENDIX A
ARM MODEL USER MANUAL
MODEL OPERATION AMP PARAMETERS
The general structure and operation of the ARM Model was discussed in
Section IV, and is depicted graphically in Figure 52. The Model
consists of a series of subprograms whose execution is controlled by the
executive program, MAIN. Table 18 lists all subprograms of the ARM
Model, defines their functions, and includes the beginning line number
of each subprogram in the Model source listing (Appendix C). The Model
operates on a number of different time intervals. The major interval of
model operation is specified by the user and corresponds to the time
interval of available precipitation data; 5 or 15 minute intervals are
allowed by the present version of the ARM Model. For days on which
storms occur, the LANDS, SEDT, and ADSRB subprograms perform
calculations on the 5 or 15 minute interval. For days on which storms
do not occur, the LANDS subprogram continues to operate on the 5 or 15
minute interval while the remaining programs operate on a daily basis.
In the present version of the Model, the DEGRAD subprogram always
operates on a daily basis, and snowmelt calculations are performed
hourly. The time interval for nutrient transformations is determined by
a user-specified input parameter. The MAIN program monitors the passage
of real time and keys the operation of the separate subprograms at the
proper time intervals.
Table 19 includes a complete list and descriptions of the ARM Model
parameters. The 'control' parameters (i.e. HYCAL, INPUT, OUTPUT, PRINT,
SNOW, PEST, NUTR, ICHECK) and 'nutrient control' parameters (TSTEP, NAPPL,
TIMHAR) specify the mode of operation, the units and type of input and
output, and the simulation calculations to be performed in each Model run.
The HYCAL and PRINT parameters determine the mode of Model operation and
the frequency of printed output, respectively. The two modes of operation
allowed by the present version of the ARM Model are referred to as
calibration (HYCAL = CALB) and production (HYCAL = PROD) runs. The
monthly and yearly summaries obtained from calibration and production runs
are basically similar. The production summaries provide more detailed
information for pesticide and nutrient concentrations in the soil profile.
Tables 20 and 21 are sample monthly summaries for the calibration and
production modes of operation, respectively. Note that the word 'BLOCK'
is used to indicate the areal-source zones discussed in Section IV, in
order to prevent confusion with the vertical soil zones (i.e. surface,
upper, lower, groundwater). The basic difference between the calibration
and production modes is the type and form of information obtained for
simulation periods between the monthly summaries. A calibration run
provides detailed information on runoff, sediment concentration and mass
136
-------
ARM Model structure and operation
CO
INPUT
OUTPUT*
MAIN
EXECUTIVE
PROGRAM
LANDS
HYDROLOGY
AND SNOW
SEDT
SEDIMENT
PRODUCTION
»-CHECKR CHECK INPUT SEQUENCE
^NUTRIO READ NUTRIENT INPUT
»-OUTMON, OUTYR OUTPUT SUMMARIES
PEST
NUTRNT
NUTRIENT TRANSFORMATION
AND REMOVAL
yes
NO
YES
NUTR
ADSRB
PESTICIDE ADSORPTION
AND REMOVAL
DEGRAD
PESTICIDE
DEGRADATION
Figure 52
-------
Table 18. ARM MODEL COMPONENTS
Major
Program
MAIN
Component
Subroutine
LANDS
SEDT
ADSRB
DEGRAD
NUTRNT
CHECKR
BLOCK DATA
NUTRIO
OUTMON
OUTYR
DSPTN
TRANS
Beginning
Function Line No.
Master program and executive 10.
control routine
Checks input parameter errors 1200.
Data initialization for common 1600.
variables
Reads and checks nutrient input 6200.
data
Prints monthly output summaries 8000.
Prints yearly output summaries 9000.
Performs hydrologic simulation 2000.
and snowmelt calculations
Performs sheet erosion simulation 4000.
Performs pesticide soil adsorption/ 5000.
desorption simulation
Performs desorption calculations 5800
Performs pesticide degradation 6000.
simulation
Performs nutrient simulation 7000.
Performs nutrient transformations 7800.
138
-------
Table 19. ARM MODEL INPUT PARAMETER DESCRIPTION
TYPE
Control
NAME
HYCAL
Hydrology
INPUT
OUTPUT
PRINT
SNOW
PEST
NUTR
ICHECK
IMTRVL
HYMIN
AREA
BGNDAY
BGNMON
BGNYR
ENDDAY
ENDMON
EMDYR
UZSN
UZS
LZSN
LZS
L
SS
NN
A
K3
EPXM
INFIL
INTER
IRC
DESCRIPTION
Specifies type of information desired
PROD-production run, prints full tables for each
interval as specified by PRINT
CALB-calibration run, prints removal values for
each interval as specified by PRINT
Input units, ENGL-english, METR-metric
Output units, ENGL-english, METR-metric, BOTH-both
Denotes the interval of printed output, INTR-each
interval, HOUR-each hour, DAYS-each day, MNTH-each
month
NO-snowmelt not performed, YES,snowmelt calculations
performed
No-pesticides not performed, YES-pesticide calculations
performed
NO-nutrients not performed, YES-nutrients calculations
performed
ON-checks most of the hydrology, snow (if used),
sediment, and pesticide (if used) input parameter
values and prints out error and warning statements
for input parameter values that are outside of
acceptable value limits, OFF-no check is made
Time interval of operation (5 or 15 minutes)
Minimum flow for printed output during a time interval
Watershed area
Date simulation begins-day, month, year
Date simulation ends-day, month, year
Nominal upper zone storage
Initial upper zone storage
Nominal lower zone storage
Initial lower zone storage
Length of overland flow to channel
Average overland flow slope
Manning's for overland flow
Fraction of area that is impervious
Fraction index to actual evaporation
Maximum interception storage
Mean infiltration rate
Interflow parameter, alters runoff timing
Interflow recession rate
139
-------
Table 19. (Continued)
Snow
Sediment
K24L Fraction of groundwater recharge percolating to deep
groundwater
KK24 Groundwater recession rate
K24EL Fraction of watershed area where groundwater is within
reach of vegetation
SGW Initial groundwater storage
GWS Initial groundwater slope
KV Parameter to allow variable recession rate for
groundwater discharge
ICS Initial interception storage
OFS Initial overland flow storage
IFS Initial interflow storage
RADCON Correction factor for radiation melt
CCFAC Correction factor for condensation and convection melt
SCF Snow correction factor for raingage catch deficiency
ELDIF Elevation difference from temperature station to mean
watershed elevation
IDNS Initial density of new snow
F Fraction of watershed with complete forest cover
DGM Daily groundmelt
WC Water content of snowpack by weight
MPACK Water equivalent of snowpack for complete watershed
coverage
EVAPSN Correction factor for snow evaporation
MELEV Mean elevation of watershed
TSNOW Temperature below which precipitation becomes snow
PACK Initial water equivalent of snowpack
DEPTH Initial depth of snowpack
PETMIN Minimum temperature at which PET occurs
PETMAX Temperature at which PET is reduced by 50 percent
PETMUL Potential evapotranspi ration data correction factor
WMUL Wind data correction factor
RMUL Radiation data correction factor
KUGI Index to forest density and undergrowth
COVPMO Fraction of crop cover on a monthly basis (12 values)
TIMTIL Time when soil is tilled (Julian day, i.e. day of the
year, e.g. January 1=1, December 31 = 365/366)
(5 dates)
YRTIL Corresponding year (last two digits only) for
TIMTIL (5 values)
SRERTL Fine deposits produced by tillage corresponding to
TIMTIL and YRTIL (5 values)
SZDPTH Depth of the surface zone
UZDPTH Upperzone depth or depth of soil incorporation
BULKD Bulk density of soil
JRER Exponent of rainfall intensity in soil splash equation
KRER Coefficient in soil splash equation
140
-------
Table 19. (Continued)
JSER Exponent of overland flow in sediment washoff equation
KSER Coefficient in sediment washoff equation
SRERI Initial fines deposit
Pesticide PESTICIDE Title word to begin the reading of pesticide input
parameters
APMODE Application mode, SURF-surface applied, SOIL-soil
incorporated
DESORP NO-single-valued adsorption/desorption used, YES-non-
single-valued adsorption/desorption algorithm used
SSRT Pesticide application for each block (5 values)
TIf-iAP Time of pesticide application (Julian day)
YEARAP Year of pesticide application (last two digits only)
CMAX Maximum solubility of pesticide in water
DD permanent fixed capacity
K Coefficient in Freundlich adsorption equation
N Exponent in Freundlich adsorption equation
NP Exponent in Freundlich desorption equation
DE6CON First order pesticide decay rate
Nutrient
Control TSTEP
NAPPL
TIMHAR
Timestep of chemical and biological transformations,
must be an integer number of time steps in a day,
and an integer number of simulation intervals
(INTRVL) in a TSTEP, range of TSTEP is 5 or
15 minutes to 1440 minutes
Number of fertilizer applications, values may range
from 0 to 5
Time of plant harvesting, Julian day of the year,
value may range from 0 to 366
Nitrogen Reaction Rates
Kl
K2
KK2
KD
KPL
KAM
KIM
KKIM
KSA
KAS
Oxidation rate
to nitrite
Oxidation rate
Reduction rate
of ammonia (dissolved and absorbed)
of nitrite
of nitrate
to
to
nitrate
nitrite
gas
Reduction rate of nitrite to nitrogen
Uptake rate of nitrate by plants
Ammonification or mineralization rate
ammonia
rate of dissolved ammonia
of ORG-N to
immobilization
to ORG-N
Immobilization rate
Transfer rate of ammonia
adsorbed (adsorption)
Transfer rate of ammonia
solution (desorption)
of nitrate to ORG-N
from solution to
from adsorbed to
141
-------
Table 19. (Continued)
Phosphorus Reaction Rates
KM
KIM
KPL
KSA
KAS
Nitrogen Storages
ORG-N
NH3-S
NH3-A
N02
N03
N2
PLNT-N
Phosphorus Storages
OR6-P
P04-S
P04-A
PLNT-P
Chloride Storage
CL
Mineralization rate of ORG-P to P04-P
Immobilization rate of P04-P to ORG-P
Uptake rate of phosphate (adsorbed and in solution)
by plants
Transfer rate of phosphate from solution to
adsorbed form
Transfer rate of phosphate from adsorbed to
solution form
Organic nitrogen assumed to be
solid or attached to soil
Ammonia in solution
Ammonia adsorbed to soil
Nitrite
Nitrate
Nitrogen gas from denitrification
Plant nitrogen
Organic phosphorus attached to soil
Phosphate in solution
Phosphate adsorbed to soil
Plant phosphorus
Chloride
142
-------
Table 20. CALIBRATION RUN OUTPUT - MONTHLY SUMMARY
(Pesticide Simulation)
SU20UI.ECB.HOUU.Of JUW 1SJ3
SLOCK 1 BLOCK 2 BLOCK 3
kATER. INCHES
CLOCK 4 BLOCK 3
TCTAl
•UKCFF
OV'RLANC fLOU
INTEPFinh
I»PCP.VICUS
TOT/I
O.M2
C.C34
0.396
0.290
0.061
0.311
0.141
0.013
0.210
C. C*T
0.09*
0.132
o.orr
0.«A4
0.971
0.163
0.065
0.0
0.22 B
BASE FLCk
(MOhATCH RECHARGE
0.0
0.191
PRECIPITATION
0.75
0.7!
0.7)
0.75
0.7$
0.75
PCTtNTIAL
NET
CPOP COVER
0.27
0.27
0.27
0.27
C.27
0.27
0.27
C.27
0.27
0.27
0.27
0.27
1.00
STORAGES
UPPER JUKE
LCrfEft
-------
Table 21. PRODUCTION RUN OUTPUT MONTHLY SUMMARY
(Pesticide and Nutrient Simulation)
sueetii-Eci-aQtiiu.u—JIKE—1121
BLOCK I BLOCK Z SLOCK )
BLOCK 4 BLOCK
TOT41
»»TER, INCHES
RUKCFF
GVERKNC FLO*
|NPE"VIOU3
TOfM.
BiSt FLOk
CRDkATER RECHtRt!
PREC1PIT1TION
1.141
0.413
1.604
».T40
O.BBT
0.464
1.351
4.7*0
0.567
O.JM
0.9SS
4.140
0.401
O. ISO
0.751
4.740
0.305
0.110
0.615
4.740
0.671
0.385
O.O
I .OS*
0.0
1.66B
4.740
POT 1ST ML
f£T
CHOF COVER
STOMGES
UPPER lUHE
104ER ZCNE
C« 1U1CM4TE*
INTE'CEPTIOS
CV5Rt»NO FLOk
J.49J
2.621
««TER BM.4NCE- O.OOM
StDIPEKT, TOMS/«CRC
TOTK S(ClrE»T L«$
FINES Ot POSIT
PEJT1CIOE. POJKOS
!UF»CF LITER
• OSOBCEC
1.493
2.62J
1.4«
2.42]
3.491
Z.«21
S.4«
2.621
O.C02
M.750
0.0
0.0
0.0
0.0
0.002
1B.7SO
0.0
0.0
0.0
0.0
0.002
1B.7SO
0.0
0.0
0.0
0.0
0.002
IB .750
O.J
0.0
0.0
0.0
0.002
11.750
9.4
0.0
0.0
0.0
(ISSOLVEO
UMF.R AWE L*TtR
tOSCRBEO
CRY£T»llIN»
CISSOLVEC
INTERFLCM STOftttt
LOkFR lOtt UYER
«OSORBEO
CKTS74LL 1HE
CISSOLVtO
CRCUNOMTER L»TIR
(CSCRSEO
CRTSTALLINt
OISSOLVEO
PESTICIDE RENCVAL. IBS.
0.899
1.C94
0.596
0.544
0.0
0.0
0.0
0.0
0.0
0.0
0^
0.9)4
1.10S
0.594
0.596
0.0
0.0
0.0
0.0
0.0
0.0
«.0
0.540
1.1)6
0.597
0.5«7
0
C
0
0
0
0.0
0.0
0.176
1.109
0.597
0.597
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2BS
1.110
0.99T
0. S97
0.0
0.0
0.0
0.0
0.0
0.0
0.1
o.ooi
o.ooo
o.ood
0.000
o.ow
J.4M
2.621
0.191
0.001
11.750
0.0
0.0
0.0
0.0
O.tOT
1.105
2.9(2
2.911
0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.ooi
OVERLAND FLOK UWWL 0.0
SEOtXEHT R.EHOVM. 0.001
IMERFLOM RECOVU. 0.0
PESTICIDE OEOH»0»TIOH LOSS. IIS.
10TM.
»CN SURFKE
FRO» UPPER ICNE
MOM LOHR ZONt
MSTIC10t_B«UNCr> 0^
0.0
0.000
0.0
0.0
0.000
0.0
0.0
0.000
0.0
lloo
0.0
0.0
0.0
0.097
0.097
0.0
0.0
144
-------
Table 21. (Continued)
ORG-K NH3-S NH3-A
102
N2 PLNT-N ORG-P PO4-S P04-A HIT-'
:L
STtHCE
SURIACF LAYER
BLOCK 1
BLCCK 2
BLOCK 3
BLCCK 4
flCCK 5
U>PIR *ot.E
BLOCK 1
BLCCK 2
BLCCK 3
CLOCK 4
BLOCK 5
INTERFLOW
BLOCK 1
BLCCK 2
BLOCK 1
CLOCK *V
BLCCK S
LOntR I CUE
GRCLNOMATER
REKVA'L
micrivE
SEDIMENT
BLCCK 1
BLOCK 2
(LOCK 3
CLOCK 4
BLOCK 5
OVEALfMO FLOW
CLOCK 1
BLCCK 2
BLOCK 1
8LCCK 4
BLOCK 5
I NT IF Fl CM
CLOCK 1
(LCCK 2
BLOCK 1
CLOCK 4
BLOCK 5
TOTAL TO STREAM
FEFCCIATIOK TC
GUCUMOWATER
81CIOGICAL - TOTAL
SLR FACE
UPFEA ZONE
LONER 20AE
GROLNCkATER
HARVEST
"ASS 8AIAKI
M1IOGEN • -0.141
FHtSPMfRUS • -0.007
CUM IDE . -C.001
23.
23.
23.
23.
24.
24.
1127.
1127.
1127.
1127.
1127.
1127.
0.
C.
0.
0.
0*
0.
11078.
0.
C.
1.
1.
0.
0.
0.
9.
0.
0.
0.
0.
0
0
0
0
0
0
0.
a.
0.
0.
0.
0.
0.
V.
0.092
0.090
0.091
0.092
0.093
0.093
6.701
9.480
6.975
6.033
5.760
5.256
0.0
0.0
0.0
0.0
55.911
0.321
0.0
0.0
0.0
0.0
0.0
0.000
0.001
0.000
0.000
o.ooc
0.000
1.959
4.056
5.156
4.897
1.597
2.090
3.959
0.5ST
0.0
0.0
0.0
0.0
0.0
o.o
9.1(1
0.177
a. 179
0.1(1
0.1(3
0.1(4
9.117
9.275
9.137
9.08<
9.062
9.025
0.0
0.0
0.0
0.0
4.731
0.015
0.006
O.C15
0.010
0.00!
0.001
Of±
»v
0.9
0.0
0.0
0.0
0.0
0.0
o.o
0.0
0.0
0.0
0.0
0.006
0.0
0.0
0.0
0.0
0-0
0.0
0.0
O.I 10
0.107
0.109
0.110
0.111
0.111
(.222
11.779
8.576
7.371
7.018
6.368
0.0
0.0
0.0
0.0
41.749
0.301
0.0
0.0
0.0
C.O
0.0
0*000
0.901
0.000
0.900
0.000
0.000
5.4(4
5.617
7.141
6.783
4.911
2.895
5.484
0.456
0.0
0.0
0.0
0.0
0.0
0.0
9.069
O.C'. (
•3.0*9
0.060
0.061
0.062
35.633
73.7(8
40.t02
28.439
22. (Sf
12. (39
0.0
0.0
0.0
0.0
6(5.735
5. (69
0.0
0.0
0.0
0.0
0.0
01*1*1
• HI
0.003
0.002
0.001
0.000
0.000
25.696
26.322
33.462
31.7(3
23.348
13.3*5
25.69T
5. !41
0.0
o.o
o.o
o.o
0.0
0.*
0.3
o.o
o.o
0.0
o.o
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0. 0
0.0
0.0
9.0
0.0
0.0
0.0
0.0
P.O
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.069
0.069
0.969
O.C69
0.069
C. 069
1. (31
3.9(8
3.6(1
3.570
3. 506
1.409
0.0
0.0
0.8
0.0
25.136
0.850
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.c
0.0
C. •
0.8
0.8
0.0
o.o
O. 8
0.0
0.0
0.8
0.0
2(.8(6
0.069
3.631
25.136
0.050
0.0
5.
5.
5.
5.
5.
5.
225.
225.
225.
225.
225.
225.
0.
0.
0.
0.
2240.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.020
0.019
0.019
0.020
0.020
0.020
.103
.323
.114
.033
.029
.917
0.0
0.0
0« 0
0.0
14.666
0.0(0
0.9
0.0
0.0
0.0
0.000
0.000
0.000
0.000
0.000
0.311
0.321
0.407
0.387
0.284
0.165
0.111
0.112
0.0
0.0
0.0
0.0
0.0
0.0
O.tOO
0.5(6
0.594
0.602
0.637
0.609
29. 726
29.904
2 '.. 746
29.6(8
29.664
29.627
0.0
0.0
0* 0
0.0
117.145
0.052
0.010
0.024
0.015
O.007
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.c
0.010
0.0
0.0
0.0
0.0
0.0
0.0
o.«
0.001
0.031
0.011
0.031
0.03 1
0.031
0.0k 3
0.042
o.oto
0.040
0.043
0.039
0.0
0.0
0.0
0.0
0.375
0.030
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.417
0.031
O.OV3
0.175
0.030
0.0
-O. 000
-3.000
-3.000
-0.000
-3.010
3.0
li.IBB
34.984
H.sji
12.728
9.613
4.727
3.3
3.3
0.0
3.3
68.790
0.443
3.0
3.3
3.3
0.0
3.002
0.001
3.430
3.333
3.333
14.579
14.934
18.985
13.932
13.247
F.»»A
14.57*
3.441
3.3
3.0
3.9
3.)
0.0
3.0
145
-------
removal, and pesticide or nutrient concentrations and mass removal for
each simulation interval (5 or 15 minutes). Tables 22, 23, and 24 present
the type of output obtained from calibration runs with various simulation
options. The goal of the calibration form of operation is to provide the
information needed to compare simulated runoff, sediment loss, and
pesticide or nutrient loss with recorded values for storm events. Since
information is provided in each simulation interval the PRINT parameter
must be specified for interval output (i.e. PRINT = INTR) for all
calibration runs. Due to output printing limitations, pesticides and
nutrients cannot be run simultaneously in the calibration mode.
The production mode of operation provides summaries of runoff, sediment,
pesticide, and nutrient loss, in addition to the amount of pesticide and
nutrients remaining in the various soil zones. Thus, the production
mode provides a complete picture of the mass balance of pesticides and
nutrients applied to the watershed. Pesticide and nutrient simulation
can be performed simultaneously in the production mode. The production
output is printed in tables similar to the monthly summaries. The
frequency of printing is controlled by the PRINT parameter which allows
printing to be done on each interval (PRINT = INTR), each hour (PRINT =
HOUR), or at the end of each day (PRINT = DAYS) or each month (PRINT =
MNTH). Table 25 presents a sample production output for daily printout.
Generally, production runs will be employed for daily or monthly print
intervals. Use of the interval (INTR) or hourly (HOUR) printout in the
production mode should be restricted to short simulation periods due to
the large amount of printed output provided, e.g. over 500 pages of
output is provided each day of simulation for a production run which
prints output for each 5 minute interval.
The SNOW, PEST, and NUTR control parameters specify whether or not
snowmelt, pesticide, or nutrient calculations, respectively, will be
performed in each model run. As indicated above, pesticide and nutrient
calculations can be performed simultaneously in a production run but not
in a calibration run. An error message will be printed, and execution
will be prevented, if this rule is violated.
The remaining control parameters, INPUT, OUTPUT, and ICHECK will be
discussed in the following section on Model input and output (I/O).
DATA REQUIREMENTS AND MODEL INPUT/OUTPUT (I/O)
Data requirements for use of the ARM Model include those related to
operation, parameter evaluation, and calibration. This section will
discuss the data requirements for Model operation and I/O while the
following section will discuss parameter evaluation and calibration. Once
initial parameter values have been chosen, the driving force of Model
operation is the input meteorologic data series. Table 26 describes the
input sequence and attributes of the meteorologic data series required for
146
-------
Table 22. CALIBRATION RUN OUTPUT - STORM EVENTS
(Hydrology and Sediment Simulation Only)
DATE
TIMfc
FLUVMCFS-CKSI
SEUHENT UBS-KG-KG/HIN-GH/L)
PESTICIDE IGH-GM/HIN-PPHI
MATE*
SEDIMENT
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
8
it
a
8
8
8
8
8
0
a
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
a
8
8
8
8
8
8
8
4:25
4130
4:35
4:40
4145
4:50
4:55
5: 0
5: 5
5UO
5U5
5:20
5J25
5:30
5:35
5:40
5:45
5:50
5:55
6: 0
6: 5
6:10
6:15
6:20
6:25
6:30
6:35
6:40
6:45
6:50
6:55
7: 0
7: 5
7:10
7H5
0.008
0.029
0.825
2.999
2.770
1.923
2.717
5.440
5.440
3.500
2.50?
1.977
2.6!>8
4.163
4.539
3.297
1.7o5
1.000
0.638
0.421
0.300
0.200
0.136
0.095
0.070
0.046
0.031
0.021
0.014
0.009
0.006
0.004
0.003
0.019
0.019
0.000
0.001
0.023
0.085
0.078
O.C54
0.077
0.154
0.154
0.099
0.071
0.056
O.C75
0.118
3.126
O.C93
0.050
0.028
0.018
0.012
0.008
0.006
0.004
0.003
0.002
0.001
O.C01
0.001
0.000
0.000
0.000
0.000
0.000
0.001
0.001
0.06
3.01
473.03
2J43.B4
1346. dO
742.54
1J*1.41
2
143.43
41.92
Ib.ta
7.U
5.09
2.04
O.Sil
O.OJ
j. a
0.0
0.0
0.0
0.0
0.0
0.0
0.0
U.Oi
0.02
O.J
0.03
1.37
214.76
927.90
611.45
337.11
481.88
1031.40
922.31
444.22
228.07
141.15
200.20
350.48
375.74
199.24
65.12
19.03
6.99
3.23
2.31
0.93
0.23
0.02
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.01
0.01
0.0
0.01
0.27
42.95
185.58
122.29
67.42
96.38
206.28
184.46
88.84
45.61
28.23
40.04
70.10
75.15
39.85
13.02
3.81.
1.40
0.65
0.46
0. 19
0.05
0.00
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.00
0.00
0.0
0.38
5.62
30.63
36.42
25.98
20.64
20.88
22.32
19.95
14.94
10.71
8.40
6.87
9.91
9.74
7.11
4.34
2.24
1.29
0.90
0.91
0.55
0.20
0.02
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.52
0.07
0.0
*
*
**
***
**
**
**
• »
***
***
**•
»•*
**
**
*
*
*
Note: Asterisks (*) indicate that the detached fines storage is less than the overland flow
sediment transport capacity in an area! zone (or block), e.g. three asterisks (***)
indicate that this occurs in three such zones.
-------
Table 23. CALIBRATION RUN OUTPUT - STORM EVENTS
(Pesticide Simulation)
cm
TIME
FLOM(CFS-CMS)
SEOIMEftT (LBS-KG-KG/MIN-GM/L)
J>
00
JULY
JULY
JUV
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JLLY
JULY
JUL>
JULY
JULY
JULY
JULY
JULY
JLLY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JU.Y
JULY
JULY
JULY
JULY
JULY
JULY
JULY
JLLY
JULY
JULY
JULY
8
8
8
8
8
8
E
8
8
8
8
8
8
8
8
a
8
8
8
a
8
8
a
8
8
8
E
8
8
8
8
8
8
a
8
8
8
8
8
8
8
4:25
4: 30
4:35
4:40
4J45
4:50
4:55
5i C
S: 5
5:10
5:15
5:20
5:25
5:30
5:35
5:40
5:45
5:50
5:55
tl 0
6: 5
6:10
6:15
6:20
6:25
6:30
6:35
6:40
<:45
6:50
6:55
7: 0
7: 5
7:10
7:15
7:20
7:25
7:30
7:35
7:40
7:45
0.010
0.032
0.877
3.119
2.847
1.967
2.766
5.504
5.5B3
3.662
2.587
2.025
2. 70S
4.213
4.581
3.328
1.752
1.006
0.644
0.426
0.306
0.205
0.139
C.097
0.071
0.047
0.032
0.021
0.014
0.009
C.C06
C.004
0.003
0.020
0.019
0.013
0.009
0.006
0.004
C.003
0.002
0.000
0 .001
0.025
0.088
0.031
O.OSo
U.07E
0.156
0 .1*8
0.104
0.073
0.057
0.077
0.119
3.130
0.094
0.05C
0.028
O.OIE
0.012
0.009
0.006
0.004
0.003
0.002
O.OC1
O.OC1
0.001
0.000
0.000
O.JOO
0.000
o.occ
0. 001
O.OC1
0.000
0.000
0.000
0.000
0.000
o.ooc
0.02
1.02
146.45
666.61
405.25
228.90
41E.41
1070.46
946.60
475. £7
243.96
157.09
209.54
377.55
3S«.«4
203.45
59.21
18.45
6.99
3.73
1.77
0.62
0.16
o.ei
0.0
C.C
o.e
0.(
0.0
0.0
0.0
0.0
0.01
c.a
o.e
0.0
0.0
0.0
0.0
0.0
0.0
o.d
0.46
66.49
302.64
183.96
103.92
190.05
486.08
429.76
21 5. SI
110.76
71.32
95.13
171.41
181.43
92.46
26.88
8.47
3.17
1.69
0.80
0.28
0.07
0.01
O.C
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.03
0.00
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.00
0.09
13.30
60.53
36.80
20.78
38.01
97.22
85.95
43.18
22.15
14.26
19.03
34.28
36.29
18.49
5.36
1.69
C.63
0.34
0.16
0.06
0.01
0.00
0.0
0.0
0.0
0.0
0.0
c.o
0.0
0.0
0.00
0.00
0.0
0.0
0.0
c.o
0.0
0.0
0.0
0. 13
1.71
8.92
11.42
7.61
6.22
8.09
10.39
9.06
6.94
• 5.04
4.15
4.14
4.79
4.66
3.27
1.81
0.99
0.58
0.47
0.31
0.16
0.06
0.01
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.15
0.02
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.7
0.0
C. 0
0.0
0.3
0.0
0.0
0.0
0.1
e.o
C.O
0.0
0.0
e.o
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.0
0.0
0.0
0.0
0.3
0.0
e.o
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.033
0.019
2.715
12.336
7.359
4.113
7.4)9
19. 234
16.678
8.233
%. IS?
2.6SS
3.585
6.512
6.831
3. 45 2
0.934
0.314
0.1U
O.OSl
0.029
0.010
3.033
0.033
0.0
0.0
0.0
0.0
0.0
0.0
o. n
0.0
0.030
0.033
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.000
3.004
3.543
2.4&1
1.472
0.823
1.500
3.841
3.336
1.646
3.934
3.533
0.717
1.302
1.376
9.692
0.197
3.061
3.323
3.312
0.006
0.002
0.001
0.003
0.0
0.0
0.0
0.0
0.0
3.3
3.3
0.0
0.000
0.000
0.0
0.0
0.0
3.3
3.3
0.0
0.0
40.811
40.812
40.826
43.663
39.996
39.580
39.459
39.538
38.808
38.120
37.639
37. 388
37.680
37.991
37.928
37.4V9
36.608
36.178
36.089
36.066
36.056
36.052
3S.053
35.053
0. 0
0.0
0.0
0.0
0.0
3.0
3.0
0.0
36.050
34.050
0.0
0.0
0.0
3.0
3.3
0.0
0.0
-------
Table 24. CALIBRATION RUN OUTPUT - STORM EVENTS
(Nutrient Simulation)
DISSOLVED IN WATER
GATE
VILLAGE CF
TI1E
IKE SCIL
NUTRIENT APPLICATION
JUKE 13
JUKE 13
JUKE 13
JUKE 13
JUKE 13
JUOf 13
JUNE 13
JUKE 13
JUNF 13
jUKF 13
JUKE 13
JUKF 13
1EHO
lEilS
ut 20
1B:25
1E:30
16:35
1E>40
18: '.5
lEt«0
IttS*
19t 0
ISt 5
FLOW
3
114. 1
5.548
135.4
4.925
226.4
4.006
292.6
2.895
325.1
2.141
361.5
1.63C
402.7
1.286
427.1
0.857
427.5
• 164)
C.OOO
0.0
1.721
15.9
3. 218
ee.i
3.417
82.4
4. COS
97.8
3.556
163.5
2.892
212.0
2.390
234.7
1.546
260.3
1.177
290.7
C.928
3CE.6
C.61S
308.6
PCM CL
(LSI (LB)
(KG/L) IMS/L)
IK A NEW FINES
0.000 0.001
3.0 0.3
0.136 6.336
1.3 58.5
0.254 11.851
7.0 224.5
C.270 12.583
6.5 303.4
0.317 14.746
7.7 3t3»0
0.281 12.094
12.9 602.0
C.22S 1C. 651
16.8 760.5
0.165 7.696
18.5 E64.3
0.122 5.692
23.6 «58j4
0.093 4.333
23.0 1C70.6
0.073 3.419
24.4 11*6*5
0.049 2.279
24.4 1126*5
NH3
ILB)
IPPM)
DEPOSIT
0.013
8.7
0.019
B.6
0.003
8.9
0.004
8.4
0.002
8.4
0.000
8.4
0.000
8.3
0.300
8.3
0.000
8.3
0.0
0.0
0.0
0.0
0.0
0.0
ORG-N
ILB)
(PPM)
STORAGE
0.740
506.6
1.107
502.7
0.164
493.3
0.243
494.2
0.138
491.6
0.027
488.7
0.007
487.3
0.002
487.4
0.000
487.4
0.0
0.0
0.0
0.0
0.0
0.0
PC4
«L6)
IPPM)
OF 2.000
0.019
13.3
0.029
13.2
0.004
13*0
0.006
12*9
0.004
12*9
0.001
12.8
0.000
1218
0.000
1218
0.000
12.8
0.0
0.0
0.0
0*0
0.0
0*0
ORG-P
ILB)
IPPM)
TONS /AC RE
0.148
101.3
0.221
100.3
0.033
99.)
0.049
98. S
0.028
98.3
0.005
97.7
0.001
97.5
0.000
97.5
0.000
97.5
0.0
0.)
0.3
0.0
0.0
0.3
TOT-N
ILB)
0.759
16.404
28.731
30.976
33.688
31.988
29.680
18.951
13.720
10.443
8.240
5.493
TOT-P
ILB)
0.167
0.386
0.291
0.323
0.348
0.287
0.230
0.166
0.122
0.093
3.073
0.049
-------
Table 25. PRODUCTION RUN OUTPUT - DAILY PRINTOUT
(Pesticide Simulation)
HATER, INCHES
RUNOFF
OVERLAND I-LOW
IKTEPFl.nn
TOTAL
BASE FLOW
GROWATcR RECHARGE
PRECIPITATION
EVAPfTHANSPIKATICN
POTENTIAL
KFT
CROP C'WF.R
STORAGES
UP°fcR ZPNF
'-'r> PLHW
INTf PP| PW
HATER BALAMCf* 0.0
Tr)NS/AC«F
t^OOFO
UNES OFP'TSIT
SUHFACF LAYER PFSTITIOF
PESTICIDE, LPS
CRYSTALLINE
CISSOLVFO
PFSTICIOf, PPM
AOSCRBEP
CHYSTALLINF
OISSHl VFO
PEMOVAL, LPS
s= 01 HE NT
OVFOLANO FLOh
P?BCrLATIUN
UPPER ZONE LAYER PFSTICICE
PFSTICID?, LBS
BLOCK 1
O.d^J
O.ilf
1.1 in
bLUCR. 2 ttLJC* 3 «n.nCK 4 PLOCK 5
CPYSTALL INF
CI1SCLVFO
INTERFLOW STORAGE
o.o/
0.07
0.132
20.5UU
0.0
O.OM3
O.J
0.003
O.UoJ
O.JOl
O.oOtt
O.bOo
0.0
0.0
42.273
42.270
0.0
0.0
0.003
O.OviJ
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0. JUt>
O.lvO
2.10
0.07
0.110
<20.->oo
0.0
U.OJ3
0.0
0.000
O.OoJ
0.013
O.o OSl
0.0
0.0
0.0
0.0
0.003
0.003
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2 JO
o. lt>9
2.10
0.135
0.157
0.292
2.10
0.072
0.156
0.227
2.10
0.07
J.o7
o.lu»
0.0
J.063
0.0
0.000
U.028
0.010
0.610
0.0
0.0
*1.370
<»^.370
0.0
0.0
0.003
0.033
0.0
o.O
0.0
0.0
0.0
0.0
0.0
0.07
0.07
0.105
20.568
0.0
0.083
0.0
0.000
0.059
0.054
0.611
0.611
0.0
0.0
42.462
42.462
0.0
0.0
0.003
0.003
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.07
0.07
0. 106
20.568
0.0
0.083
0.0
0.000
0.033
0.088
0*613
0.613
0.0
0.0
42.586
42.586
0.0
0.0
0.002
0.002
0.0
0.0
0.0
0.0
0.0
0.0
0.0
TOTAL
0.335
0.196
0.0
0.531
0.0
0.903
2.10
0.07
0.07
0.59
0*112
20.568
0.0
0.093
0.0
0.001
0.054
0.037
3.052
3.052
0.0
0.0
42.400
42.400
0.0
0.0
0.014
0.014
0.0
0.0
0.0
0.0
0.0
0.0
0.0
150
-------
Table 25. (Continued)
PF.STICITEt PPM 0.0 0.0 0.0 0.0 0.0 0.0
AUSORHFO 0.0 0.0 J.O 0.0 0.0 0.0
CPYSTALLINC 0.0 0.0 0.0 0.0 0.0 0.0
DISSOLVED 0.0 0.0 0.0 0.0 0.0 0.0
P.tMCVAL, LBS 0.0 0.0 0.0 0.0 0.0 0.0
INTERFLOW O.J 0.0 0.0 0.0 0.0 0.0
PFRCOLATIOM 0.0 0.0 0.0 0.0 0.0 0.0
LCHE" ZONE LAYER PESTICIDE
PESTICIDE, LBS 0.0
ADSORBED o.o
CRYSTALLINE 0.0
DISSOLVED 0.0
PFSTICIOe, PPM
ADSOOHCl) 0.0
CRYSTALLINF 0.0
CISSCLVFI) 0.0
PFMCVALt L8S 0.0
PCRCCLATION 0.0
GinUN3KATEP LAYFR PCSTICtDE
PESTItlOE, LBS 0.0
ATSOPOEO 0.0
CRYSTALLINE 0.0
DISSOLVED 0.0
PESTICIDE CEOP4DATION LLSSi LBS.
TOTAL 0.006
SURFACC 0.006
UPPFR ZHNE 0.0
F-KOM LOWER IOHP. 0.0
151
-------
Table 26. METEOROLOGIC DATA INPUT SEQUENCE AMD ATTRIBUTES*
ui
ro
Data
Interval
Potential
Evapotransplration Daily
Max-Min
Air Temperature Daily
Mind Daily
Solar Radiation Daily
Dewpoint
Daily
Units
English Metric
in x 100 mm x 1000
degrees F degrees C
miles/day km/day
langleys/ langleys/
day day
degrees F degrees C
Comments
Assumed equal to lake evaporation and
lake evaporation = pan evaporation x pan
coefficient
1. Caution: Time of observation
determines whether the recorded values
refer to the day of observation or the
previous day.
2. Required only for nutrient and snow
simulation.
Required only for snow simulation.
1. Total incident solar radiation.
2. Required only for snow simulation.
3. 1 langley = 1 calorie/cm2
1. Required only for snow simulation.
2. Average daily value since variations
during the day are assumed minor.
Precipitation 5 minutes in x 100 mm x 1000
15 minutes
* All meteorologic data is input in integer form. Format specifications are described in Table 30.
-------
Model operation. Except for precipitation which is input on 5 or 15
minute intervals, daily meteorologic observations are needed. The extent
of data requirements is dependent upon the simulation options. Thus for
hydrology, sediment, and pesticide simulation, without snowmelt
calculations, only precipitation and evaporation are required in the
present version of the ARM Model. For nutrient simulation, max-min air
temperature is an additional requirement, and for snow simulation, the
required data series include max-min air temperature, daily wind movement,
daily solar radiation, and daily dewpoint temperature (in addition to
precipitation and evaporation).
The ARM Model accepts parameter and data input on a 'sequential' basis in
either English or Metric units, as specified by the INPUT parameter, i.e.
INPUT = ENGL or INPUT - METR. Table 27 presents the overall input
sequence for the ARM Model. Model parameters are input in two different
formats depending on the simulation options chosen. The majority of the
ARM Model parameters (except the control parameters) are input in the
FORTRAN 'namelist1 format. The input sequence and attributes for these
parameters are described in Table 28. The nutrient parameters (except for
the 'nutrient control1 parameters) are input under format control due to
the number of transformations, reaction rates, and storages which must be
defined. Table 29 describes the input sequence and attributes for the
nutrient parameters. Study of Tables 28 and 29 and comparison with the
sample input listing in Appendix B should clarify the ordering of the
parameter input sequence.
As described in Table 28, the first two lines of the input sequence
provide space for specifying the watershed name, pesticide or chemical
name, and other information describing the Model run. Next, eight
control parameters and three control namelists (CNTL, STRT, ENDD) are
input. The ICHECK control parameter allows the user to direct the ARM
Model to check for errors and reasonableness of the parameter values;
the CHECKR subroutine performs this function. With ICHECK = ON, the
Model checks the input sequence, indicates errors, and then stops if any
errors are found. After errors have been corrected the Model can be run
again with ICHECK = ON in order to check corrections and to perform the
simulations.
The control namelist statements specify the simulation interval
(INTRVL), the minimum flow for hydrograph output (HYMIN), the area of
the watershed (AREA), and the beginning and ending dates of simulation
(namelists STRT and ENDD respectively).
Next in sequence are the four hydrologic parameter namelist statements
(LND1, LND2, LND3, and LND4). If snowmelt simulation is specified by
the SNOW control parameter (SNOW = YES), the corresponding snowmelt
namelists (SN01, SN02, SN03, SN04) are next in line. Otherwise, the
sediment namelist statements (CROP, MUD1, DIRT, SMDL) would follow. If
153
-------
Table 27. INPUT SEQUENCE FOR THE ARM MODEL
ARM Model Parameters
Potential Evapotranspiration
Max-Min Air Temperature
Wind Movement > 1st Year
Solar Radiation
Dewpoint Temperature
Precipitation
Potential Evapotranspiration
Max-Min Air Temperature
Wind Movement
Solar Radiation
Dewpoint Temperature
Precipitation
>*2nd Year
etc.
154
-------
Table 28. ARM MODEL PARAMETER INPUT SEQUENCE AND ATTRIBUTES
(excluding nutrient Input and parameters)
Namelist
Name
CNTL
STRT
ENDD
LND1
LND2
LND3
Parameter
Name
Type
English Units
Metric Units
Watershed name (up to 80 characters)
Chemical name and/or run information (up to 80 characters)
HYCAL
INPUT
OUTPUT
PRINT
SNOW
PEST
NUTR
ICHECK
INTRYL
HYMIN
AREA
BGNDAY
BGNMON
BGNYR
ENDDAY
ENDNON
ENDYR
UZSN
UZS
LZSN
LZS
L
SS
NN
A
K3
EPXM
INFIL
INTER
IRC
K24L
KK24
K24EL
character
character
character
character
character
character
character
character
integer
real
real
integer
integer
integer
integer
integer
integer
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
minutes
cubic feet/sec
acres
minutes
cubic meters/sec
hectares
inches
inches
inches
inches
feet
mi 11imeters
mi 11imeters
millimeters
mi 11imeters
meters
inches
inches/hour
millimeters
millimeters/hour
155
-------
Table 28.
LND4
SN01
SN02
SN03
SN04
(Continued)
S6W
GWS
KV
ICS
OFS
IPS
RADCON
CCFAC
SCF
ELDIF
IDNS
F
DGM
we
MPACK
EVAPSN
MELEV
TSNOW
PACK
DEPTH
PETMIN
PETMAX
PETMUL
WMUL
RMUL
KU6I
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
real
integer
CROP
COVPMO
inches
inches
inches
inches
1000 feet
inches/day
inches
feet
degrees F
inches
inches
degrees F
degrees F
real
MUD1
DIRT
SMDL
TIMTIL
YRTIL
SRERTL
SZDPTH
UZDPTH
BULKD
JRER
KRER
JSER
KSER
SRERI
PESTICIDE
APMODE
DESORP
integer
integer
real
real
real
real
real
real
real
real
real
character
character
character
millimeters
mi 11imeters
millimeters
millimeters
kilometers
millimeters/day
millimeters
meters
degrees C
mi 11imeters
mi 11imeters
degrees C
degrees C
days
year
tons/acre
inches
inches
pounds/cubic foot
days
year
tonnes/hectare
millimeters
millimeters
grams/cubic cm
tons/acre
tonnes/hectare
156
-------
Table 28. (Continued)
AMDL SSTR real pounds/Block kilograms/block
TIMAP integer days days
YEARAP integer year year
CMAX real pounds/pound kilograms/kg
DD real Ibs. pesticide/ kgs. pesticide/
IBs. soil kgs. soil
K real
N real
NP real
DEG1 DEGCON real per day per day
157
-------
pesticide simulation is to be performed, the sediment namelists are
followed by the title word 'PESTICIDE1 (starting in column 1), the
pesticide parameters APMODE and DESORP and the pesticide namelist
statements (AMDL, DEG1). This completes the parameter input sequence
for hydrology, sediment, and pesticides.
If nutrient simulation is to be performed, as indicated by the control
parameter NUTR (i.e. NUTR = YES) then the nutrient parameters must
follow in sequence. Reference to Table 29 and Appendix B is important
to understanding the nutrient input sequence. The sequence begins with
the title word 'NUTRIENTS' (in column 1) and is followed by the namelist
statement, NUTRIN. This is the only namelist statement in the nutrient
parameter input sequence. The remaining input of nutrient information
is done under format control. Also, character strings are input and
checked by the program to verify the accuracy of the input sequence.
The section begins with the character string 'REACTION RATES' and then
the words 'NITROGEN' or 'PHOSPHORUS' to indicate which rates are being
input. First order reaction rates may be input for both nitrogen and
phosphorus chemical and biological transformations. Separate rates are
allowed for the four soil zones: SURFACE, UPPER, LOWER, and
GROUNDWATER. Following the character string, 'NITROGEN', the word
'SURFACE1 appears on the next line; then 10 reaction rates are listed in
F8.0 format on the following line. These reaction rates refer to the
various nitrogen forms described in Table 29. Following the surface
rates, the word 'UPPER' appears in column 1, and the reaction rates for
the upper zone are input on the next line. Lower zone and groundwater
rates follow in a similar manner. The word 'TEMPERATURE COEFFICIENTS'
appears after the groundwater rates and the following line contains the
ten constants used for correcting the corresponding reaction rates for
non-optimal temperatures. Phosphorus reaction rates and temperature
coefficients are input in a similar manner except that there are only
five reaction rates appearing in an F8.0 format (see Appendix B). The
word END terminates input of reaction rates. Specifying nitrogen or
phosphorus rates is optional, and if values are not given, the program
will default the rates to 0.0.
The next section of nutrient input specifies the initial nitrogen,
phosphorus, and chloride concentration present in the four soil layers.
The word 'INITIAL' begins this section; title words are used in the
manner described above. The seven different nitrogen forms, four
various constituents are described in Table 29. The sequence is
demonstrated in Appendix B. Nutrient concentration is input by soil
layer. If initial values are not given for the nitrogen, phosphorus, or
chloride forms, the program defaults them to 0.0. The character string
'END' terminates the initialization section.
The final section of the nutrient input sequence indicates the date and
amount of application of nutrients during the simulation period. Each
158
-------
Block
NUTRIENT
Section &
Subsection
&.NUTRIS
Table 29. ARK MODEL NUTRIENT PARAItTER INPUT SEQUENCE AND ATTRIBUTES
flare Type Column Units Comments
01
REACTION RATES
TSTEP
NAPPL
TII-HAR
&END
Type
Character
Character
Integer
Column Units
Position English Metric
1-8
2-7
Any minutes minutes
Integer
Integer
Character
Any
Any
Any
day day
NITROGEN
SURFACE
Kl
K2
KK2
KD
KPL
KAK
KIM
KKIM
Character
Character
Character
Real
Real
Real
Real
Real
Real
Real
Real
1-14
1-8
1-7
1-8
9-16
17-24
25-32
33-40
41-48
49-56
57-64
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
Name to Indicate start of
nutrient input sequence.
Naroelist name of nutrient
control information.
Length of timestep for
chemical and biological
transformations. There must
be an even number of tine
steps in a day, and an even
number of simulation intervals
in a TSTEP. Range= 5 or 15
to 1440.
Number of nutrient applica-
tions over a year of simula-
tion. Values may range from
0 to 5.
Time of plant harvesting,
Julian day of the year.
Value may range from
0 to 366.
Indicate end of namelist
input of nutrient control
information.
Name to indicate start of
nutrient input sequence.
Indicates nitrogen reaction
rate will follow.
Surface layer reaction
rates follow.
Oxidation rate of ammonia
(dissolved and adsorbed) to
nitrite.
Oxidation rate of Nitrite
to nitrate.
Reduction rate of nitrate
to nitrite.
Reduction rate of nitrite
to nitrogen gas.
Uptake of nitrate by plants.
Ammonification or mineraliza-
tion rate of organic-N to
ammonia.
Immobilization rate of dissolved
amoonia to organic-N.
Immobilization rate of nitrate
to organic-H.
-------
Table 29. (Continued)
Block
Section & Name
Subsection
Type Column Units
Position English Metric
UPPER ZONE
en
o
LOWER ZONE
KSA
KAS
Kl
K2
KK2
KO
KPL
KAM
KIM
KJCIM
KSA
KAS
Kl
K2
KK2
KO
KPL
KA!1
KIK
KXIM
KSA
KAS
Real
Real
Character
Real
Real
Real
Real
Real
Real
Real
Real
Real
Real
Character
Real
Real
Real
Real
Real
Real
Real
Real
Real
Re.il
65-72
73-80
1-10
1-8
9-16
17-24
25-32
33-40
41-43
49-56
57-64
65-72
73-80
1-10
1-8
9-16
17-24
25-32
33-40
41-48
49-56
57-64
65-72
73-80
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
Conments
Transfer rate of amrvonia frotr.
solution to adsorbed (adsorption).
Transfer rate of ammonia from
adsorbed to solution (desorptlon).
Upper zone reaction rates follow.
Oxidation rate of aimonia
(dissolved .and adsorbed) to
nitrite.
Oxidation rate of Nitrite
to nitrate.
Reduction rate of nitrate
to nitrite.
Reduction rate of nitrite
to nitrogen gas.
U?taka of nitrate by plants.
Anronification or islneraliza-
tion rate of organic-N to
Irmobilization rate of dissolved
anronla to organ 1c-H.
Immobilization rate of nitrate
to organic-!!.
Transfer rate of a anon i a from
solution to adsorbed (adsorption).
Transfer rate of airaonia from
adsorbed to solution (desorption).
Lower zone reaction rates folow.
Oxidation rate of anrnonia
(dissolved and adsorbed) to
nitrite.
Oxidation rate of Nitrite
to nitrate.
Reduction rate of nitrate
to nitrite.
Reduction rate of nitrite
to nitrogen gas.
Uptake of nitrate by plants.
Anmonif (cation or mineraliza-
tion rate of organic-H to
ammonia.
Irrcobilization rate of dissolved
annonla to organic-)!.
loaobilization rate of nitrate
to organ ic-N.
Transfer rate of errnonia from
solution to adsorbed (adsorption).
Transfer rate of annonia from
adsorbed to solution (desorption).
-------
Table 29.
cr>
(Continued)
Block Section & Nans
Subsection
GROUNDWATER
Kl
K2
KX2
Kf)
KPL
KAM
KIM
KKIM
KSA
KAS
TEMPERATURE
COEFFICIENTS
THK1
THK2
THKK2
THKD
THKPL
THKAM
THKIM
THKK1M
THKSA
THKAS
Type
Character
Real
Real
Real
Real
Real
Real
Real
Real
Real
Real
Character
Real
Real
Real
Real
Real
Real
Real
Real
Real
Real
Col urn
Position
l-Ii
1-8
9-16
17-24
25-32
33-40
41-48
49-56
57-64
65-72
73-80
1-23
1-8
9-16
17-24
25-32
33-40
41-48
49-56
57-54
65-72
73-80
Units
English Metric
per
per
per
per
per
per
per
per
per
per
per
per
per
per
per
per
per
per
per
per
day
day
day
day
day
day
day
day
day
day
day
day
day
day
day
day
day
day
day
day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
Comments
Groundwater reaction rates follow.
Oxidation rate of ammonia
(dissolved and adsorbed) to
nitrite.
Oxidation rate of nitrite
to nitrate.
Reduction rate of nitrate
to nitrite.
Seduction rate of nitrite
to nitrogen gas.
Uptake of nitrate by plants.
Ammonification or mineraliza-
tion rate of organic-M to
ammonia.
Immobilization rate of dissolved
znronia to organic-N.
Iwr.cbilizatiOR rate of nitrate
to organic-N.
Transfer rate of annonia from
solution to adsorbed (adsorption).
Transfer rate of anmonia from
adsorbed to solution (desorption).
Temperature coefficients for
reaction rates.
Tenperature coefficients for
corresponding nitrogen
reactions, should be greater
than or equal to 1.0.
-------
Table 29. (Continued)
Block
ro
Section &
Subsection
PHOSPHORUS
SURFACE
UPPER ZONE
llame
KM
KIM
K?L
KSA
KAS
m
Kit!
KPL
KSA
KAS
Type
Character
Character
Reel
Real
Real
Real
Real
Character
Real
Real
Real
Real
Real
Col urn
Position
1-10
1-7
1-C
9-16
17-24
25-32
33-43
1-10
1-8
9-16
17-24
25-32
33-40
Units
English
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
ffetrlc
per day
per day
per day
per day
per day
per day
per day
per day
per day
per day
LOWER ZONE
GROUriDUATER
KI1
KIM
KPL
KS^
KAS
KM
Character 1-10
Real 1-8
Real
Real
Real
Real
Character
Real
9-16
17-24
25-32
33-43
1-11
1-8
per day per day
per day per day
per day per day
per day per day
per day per day
per day per day
Corantnts
Indicates phosphorus
reaction rates will follow.
Surface layer reaction
rates.
Vlneralization rate of
Organic-? to P04-5
Immobilization rate of
dissolved P04-P to Organic-P.
Uptake of phosphate
(dissolved and adsorbed)
by plants.
Transfer rate of phosphate
from solution to adsorbed.
Transfer rate of phosphate
from adsorbed to solution.
Upper zone reaction rates
follow.
Mineralization rate of
Organic-P to P04-P
dissolved.
Imobilization rate of
dissolved P04-P to Organic-P.
Uptake of phosphate
(dissolved and adsorbed)
by plants.
Transfer rate of phosphate
from solution to adsorbed.
Transfer rate of phosphate
from adsorbed to solution.
Lower zone reaction rates
follow.
Mineralization rate of
Organic-P to P04-P
dissolved.
Immobilization rate of
dissolved P04-P to Organic-P.
Uptake of phosphate
(dissolved and adsorbed)
by plants.
Transfer rate of phosphate
from solution to adsorbed.
Transfer rate of phosphate
from adsorbed to solution.
Lower zone reaction rates
fellow.
Mineralization rate of
Organic-P to P04-P
dissolved.
-------
Tab7e 29. (Continued)
Block
cr>
CO
END
INITIAL
Section £
Subsection
Name
KIM
KPL
KSA
KAS
TEI1PERATURE
COEFFICIENTS
THKM
THKIH
THKPL
THKSA
THKAS
Type
Real
Real
Real
Real
Character
Real
Real
Real
Real
Real
Character
Column
Position
9-16
17-24
25-32
33-40
1-23
1-8
9-16
17-24
25-32
33-40
1-3
Units
English
per day
per day
per day
per day
per day
per day
per day
per day
per day
rVitric
per day
per day
per day
per day
per day
per day
per day
per day
per day
NITROGEN
SURFACE
NBLK
Character
Character
Character
Integer
1-7
1-8
1-7
16
ORG-N
NH3-S
Real
Real
1-8
9-16
Ib/ac kg/ha
Ib/ac kg/ha
Comments
Ircnobilization rate of
dissolved P04-P to Organic-P.
Uptake of phosphate
(dissolved and adsorbed)
by plants.
Transfer rate of phosphate
fron solution to adsorbed.
Transfer rate of phosphate
from adsorbed to solution.
Temperature coefficients
for reaction rates.
Temperature coefficients
for phosphorus reactions,
should be greater than or
equal to 1.0.
'END' terminates input of
rates. Nitrogen and phosphorus
rates are optional, program
defaults them to 0.0 if not
specified.
Initialization of soil
constituents follows.
Initial nitrogen forms follow.
Surface layer initialization
follows.
Hurfcer of blocks which will be
input. 0 or 1 indicate the
average concentration over the
surface layer in input on one
line, and NBLK=5 means five lines
of input follow, one line per
block. Only 0,1,5 allowed.
A blank in co. 16 is read as 0.
Potentially mineralizable nitrogen.
Ammonia in solution
-------
Table 29.
(Continued)
Block Section & Name
Subsection
HH3-A
N02
N03
N2
PLNT-N
UPPER ZONE
NBLK
OR6-N
NH3-S
NH3-A
N02
N03
N2
PLNT-N
LOWER ZONE
ORG-N
NH3-S
NH3-A
N02
N03
N2
PLNT-N
Type
Real
Real
Real
Real
Real
Character
Integer
Real
Real
Real
Real
Real
Real
Real
Character
Real
Real
Real
Real
Real
Real
Real
Column
Position
17-24
25-32
33-40
41-48
49-56
1-10
16
1-8
9-16
17-24
25-32
33-40
41-48
49-56
1-10
1-8
9-16
17-24
25-32
33-40
41-48
49-56
Units
English
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
^etri<
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
Comments
Ammonia adsorbed to soil.
Nitrite
Nitrate
Nitrogen gas from demitrification.
Plant nitrogen
Upper zone initialization
follows.
Number of blocks which will be
input. 0 or 1 indicate the
average concentration over the
surface layer is input on one
line, and NBLK=5 means five lines
of input follow, one line per
block. Only 0,1,5 allowed.
A blank in co. 16 1s read as 0.
Potentially mineralizable nitrogen.
Ammonia in solution
Ammonia adsorbed to soil.
Nitrite
Nitrate
Nitrogen gas from demitrifi cation.
Plant nitrogen
Lower zone initialization.
Potentially mineral izable nitrogen.
Ammonia In solution
Ammonia adsorbed to soil.
Nitrite
Nitrate
Nitrogen gas from demitrifi cation.
Plant nitrogen
-------
Table 29. (Continued)
Block
in
Section &
Subsection
GROUNDWATER
PHOSPHORUS
SURFACE
UPPER ZONE
LOWER ZONE
Name
ORG-N
NH3-S
NH3-A
N02
N03
H2
PLNT-N
NBLK
ORG-P
P04-S
P04-A
PLNT-P
N3LK
ORG-P
P04-S
P04-A
fLNT-P
ORG-P
Type
Character
Real
Real
Real
Real
Real
Real
Real
Character
Character
Integer
Real
Real
Real
Real
Character
Integer
Real
Real
Real
Real
Character
Real
Coluon
Position
i-11
1-8
9-16
17-24
25-32
33-40
41-48
49-56
1-10
1-7
16
1-8
9-16
17-24
25-32
1-10
16
1-8
9-16
17-24
25-32
1-10
1-8
Units
English
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Itetrtc
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
Comments
Groundwater zone Initialization.
Potentially mlnerallzable nitrogen.
Airreonia in solution
Ammonia adsorbed to soil.
Nitrite
Nitrate
Nitrogen gas from demitriflcatlon.
Plant nitrogen
Initial phosphorus forms follow.
Surface layer.
Number of blocks which will
be input.
Organic phosphorus.
Phosphate in solution.
Phosphate adsorbed to soil.
Plant phosphorus.
Upper zone phosphorus
initialization.
Number of blocks which will
be input.
Organic phosphorus.
Phosphate in solution.
Phosphate adsorbed to soil.
Plant phosphorus.
Lower zone initialization.
Organic phosphorus.
-------
Table 29.
Ok
at
(Continued)
Block Section & Name
Subsection
P04-S
P04-A
PLNT-P
GROUNOWATER
ORG-P
P04-S
P04-A
PLNT-P
CHLORIDE
SURFACE
NBLK
CL
UPPER ZONE
NBLK
CL
LOWER ZONE
a
GROUNDWATER
CL
END
Type
Real
Real
Real
Character
Real
Real
Real
Real
Character
Character
Integer
Real
Character
Integer
Real
Character
Real
Character
Real
Character
Column
Position
9-16
17-24
25-32
1-11
1-8
9-16
17-24
25-32
1-8
1-7
16
1-8
1-10
16
1-8
1-10
1-8
1-11
1-8
1-3
Units
English
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Metric
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
APPLICATION
APDAY
Character
Integer
1411
14-16
Comments
Phosphate in solution.
Phosphate adsorbed to soil.
Plant phosphorus..
Groundwater initialization.
Organic phosphorus.
Phosphate in solution.
Phosphate adsorbed to soil.
Plant phosphorus.
Initial chloride levels follow.
Surface layer chloride.
Number of blocks which will be
input.
Chloride storage.
Upper zone Initialization.
Number of blocks which will be
input.
Chloride storage.
Lower zone.
Chloride storage.
Groundwater.
Chloride storage.
"END" terminates input of
initial nutrient storages.
Nitrogen, phosphorus, and
chloride storages default to
0.0 if not input in this
SEC'IO'i.
Mane to indicate start of
nutrient application section,
expected the number of
applications is greater
than 0.
Application day of the year
(Julian Day).
-------
Table 29. (Continued)
Block
Section &
Subsection
NITROGEN
SURFACE
Name Type Column Units
Position English i-'etric
(ft
UPPER ZONE
N3LK
ORG-N
NH3-S
NH3-A
N02
N03
N2
PLNT-N
NBLK
ORG-N
NH3-S
NH3-A
N02
N03
N2
PLHT-N
Character
Character
Integer
Real
Real
Real
Real
Real
Real
Real
Character
Integer
Real
Real
Real
Real
Real
Real
Real
1-8
1-7
16
1-8
9-15
17-24
25-32
33-40
41-43
49-56
1-10
16
1-8
9-16
17-24
25-32
33-40
41-48
49-56
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
Cements
Nitrogen applications follow.
Surface applications follow.
Nunber of blocks which will
be input, 0 or 1 indicate one
line follows containing the
average application over the
watershed. A 5 indicates
five lines follow, one line
for each block.
Potentially mineral izable
nitrogen applied.
Ammonia in solution.
Armenia adsorbed to soil.
Nitrite
Nitrate
Nitrogen gas.
Plant nitrogen.
Upper zone applications follow
Nunber of blocks which will
be input.
Potentially mineral izable
nitrogen applied.
in solution.
Ammonia adsorbed to soil.
Nitrite
Nitrate
Nitrogen gas.
Plant nitrogen.
Note: nutrients can only
be applied to surface and
upper zone.
-------
Table 29. (Continued)
Block
00
END
Section &
Subsection
PHOSPHORUS
SURFACE
UPPER ZONE
CHLORIDE
SURFACE
UPPER ZONE
Name
NBLK
ORG-P
P04-S
P04-A
PLNT-P
NBLK
ORG-P
P04-S
P04-A
PLNT-P
NBLK
a
NBLK
CL
Type
Character
Character
Integer
Real
Real
Real
Real
Character
Integer
Real
Real
Real
Real
Character
Character
Integer
Real
Character
Integer
Real
Character
Col umi
Position
1-10
1-7
16
1-8
9-16
17-24
25-32
1-10
16
U8
9-1S
17-24
25-32
1-8
1-7
16
1-8
1-10
16
1-8
1-3
Units
English
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
Ib/ac
!*stri<
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
Cements
Phosphorus applications follow
Surface layer application.
Number of blocks which will
be input.
Organic phosphorus.
Soluble phosphate.
Adsorbed phosphate.
Plant phosphorus.
Upper zone application.
Nunber of blocks which will
be input.
Organic phosphorus.
Soluble phosphate.
Adsorbed phosphate.
Plant phosphorus.
Chloride applications follow
Surface layer application.
Number of blocks which
will be input.
Chloride applied.
Upper zone applications.
Number of blocks which will
be input.
Chloride applied.
"END" terminates input
of applications for that
day.
Note: Nitrogen, phosphorus
and chloride do not need
to be specified on input
sequence if none are applied
that day. Program defaults
all applications to 0.0.
-------
nutrient application begins with the word APPLICATION followed by the
Julian day of application (e.g. 164 in Appendix B). The words following
indicate which constituents are to be applied: NITROGEN, PHOSPHORUS, or
CHLORIDE. Below the constituent type, the application amounts are
entered for the surface and upper zone only. The character string END
terminates the input of the nutrient application at one time. For
multiple applications, the sequence is repeated with the character
string APPLICATION and the Julian day of application. Applications have
to be sequential with the first one applied in the year appearing first
in the input sequence. This completes the nutrient input sequence and
the entire ARM Model parameter input sequence.
As indicated in Table 27, the ARM Model parameters are followed by the
meteorologic data in the input sequence. The daily meteorologic data is
input as a block of 31 lines (or cards) with 12 values in each line.
Thus, the 31 x 12 matrix corresponds to the 12 months of the year with a
maximum of 31 days each. Table 30 demonstrates the format for the daily
meteorologic data. The only modification to this is for daily max-min
air temperature since two values are input for each day. In this case,
the six spaces allowed for each daily value are divided in half. The
first three spaces contain the maximum, and the second three spaces
contain the minimum air temperature for the day. Table 31 indicates the
format for precipitation data input on 5 or 15 minute intervals. For
further clarification of these formats, see the sample input listing in
Appendix B.
The Model operates continuously from the beginning to the end of the
simulation period. To simplify input procedures and reduce computer
storage requirements, the meteorologic data is input on a calendar year
basis. Each block of meteorologic data indicated in Table 27 must
contain all daily values for the portion of the calendar year to be
simulated. Thus if the simulation period is July to February, the Model
reads and stores all the daily meteorologic data for the July to
December period. The Model then reads the precipitation data, on the 5
or 15 minute intervals, and performs the simulation day-by-day from July
to December. When the month of December is completed, the Model reads
the daily meteorologic data for January and February, and then continues
stepping through the simulation period by reading the precipitation and
performing the simulation day-by-day for the months of January and
February. Thus the input data must be ordered on a calendar year basis
to conform with the desired simulation period.
The major forms of Model output have been presented in Tables 20 through
25 with the discussion of the calibration and production modes of
operation. Daily snowmelt output for calibration runs is presented in
Table 32; the values are defined in Table 33. Prior to simulation, the
ARM Model prints a heading which contains run information, input
parameters, and initial storage values. Table 34 presents the heading
for the hydrology, sediment, and pesticide parameters, while Table 35
169
-------
Table 30. SAMPLE INPUT AND FORMAT FOR DAILY METEOROLOGIC DATA
Month
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
EVAP73
c
«o
18
18
18
0
35
28
28
28
28
28
28
28
28
28
27
33
19
41
41
54
54
55
118
32
24
24
24
25
25
91
17
14
^
01
u.
74
90
60
61
61
82
121
69
7
20
21
21
16
54
46
47
45
45
46
46
81
83
101
45
46
46
28
60
1
20
i.
(T3
60
170
43
43
43
71
4
41
35
20
20
21
123
123
132
103
61
61
61
61
112
44
104
87
87
87
72
86
50
31
31
26
a.
29
29
30
60
112
15
15
15
15
15
16
16
113
113
113
113
1
88
88
88
88
88
88
13
13
19
332
58
58
58
l
32
^
£
13
13
14
4
202
99
100
34
135
210
202
219
145
176
192
222
171
173
159
72
103
198
154
232
153
114
90
152
3
153
198
t
38
Column
c
3
•-3
266
70
65
70
171
8
72
70
37
108
68
142
132
90
156
121
160
70
72
161
84
149
183
62
262
109
126
59
137
213
1
44
Number
_
•"3
131
163
140
156
145
185
87
145
62
185
175
133
185
154
246
140
89
58
80
46
168
129
136
141
71
65
27
43
148
155.
103
•
50
O>
3
103
96
53
162
34
122
65
105
130
36
139
162
4
72
208
115
123
92
72
130
205
178
143
122
112
136
52
170
37
249
38
56
a.
O)
CO
19
63
189
124
115
24
161
92
145
218
185
145
99
211
125
158
191
139
112
119
73
79
132
152
112
92
33
66
79
165
i
62
^
o
o
41
69
97
104
117
138
124
90
117
159
76
34
110
117
76
83
90
110
117
104
83
83
83
77
71
65
59
53
48
69
14
t
68
>
o
90
72
48
48
114
54
12
0
78
72
60
48
48
54
24
24
60
120
66
24
48
36
66
36
30
48
24
78
54
204
I
74
u
8
68
68
47
52
47
42
31
57
36
10
57
36
57
36
36
104
73
47
57
73
104
109
99
83
10
42
68
36
16
47
68
i
80
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15 Day
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Notes: 1. Columns 1-7 are ignored. They can be used to identify the data.
2. All data is input in integer form.
3. Identical format for evaporation, wind, solar radiation, and
dewpoint temperature.
4. For Max-Min air temperature data, the six spaces allowed for
each daily value (above) are divided in half; the first three
spaces contain the maximum temperature, and the second three
spaces contain the minimum temperature. See listing in
Appendix B.
170
-------
Table 31. ARM MODEL PRECIPITATION INPUT DATA FORMAT
Column No.
1
2-7
8
Description and Format
Blank
Year, Month, Day (e.g. January 1, 1940 is 400101).
Card Number: each card represents a 3-hour period
Card #1 Midnight to 3:00 AM
#2 3:00 AM to 6:00 AM
#3 6:00 AM to 9:00 AM
9-80
Notes: 1,
2.
#8 9:00 PM to Midnight
All eight cards are required if rain occurred any
time during the day. A card number of 9 signifies
that no rain occurred during the entire day, and
no other rainfall cards are required for that day.
Precipitation data (OOO's of millimeters
(00's of inches)).
15-minute intervals:
6 column per each 15-minutes in the 3-hour period
of each card. Number must be right justified,
i.e. number must end in the 6th column for the
15-minute period.
5-minute intervals:
2 columns per each 5-minute interval, i.e. the
15-minute period still occupies 6 columns, but
it is broken down into three 5-minute intervals.
Appendix B contains a sample of input data.
At least one precipitation card is required for each day
of simulation.
Blanks are interpreted as zeros by the Model: consequently,
zeros do no need to be input.
171
-------
Table 32. DAILY SNOWMELT OUTPUT
(Calibration Run, English Units)
DATE
TIME
H.CWICFS-CMS)
StUIHLMT (LoS-KO-Ko/HIN-GM/l. I
PESTICIDE (GH-GM/HIN-PPHI
HATER SEDIMENT
SNChMELT OUTPUT FOB
UECtHBCK
HOUR
1
2
3
-------
Table 33. DAILY SNOWMELT OUTPUT DEFINITIONS
(calibration run, English units)
HOUR: Hour of the day, numbered 1 to 24
PACK: Water equivalent of the snowpack, inches
DEPTH: Snow depth, inches
SDEN: Snow density in inches of water per inch of snow
ALBEDO: Albedo, or snow reflectivity, percent
CLDF: Fraction of sky that is cloudless
NE6MELT: Heat loss from the snowpack, equivalent inches of melt
LIQW: Liquid water content of the snowpack, inches
TX: Hourly air temperature, degrees Fahrenheit
RA: Incident solar radiation, langleys
LW: Net terrestrial radiation, langleys (.negative value indicates
outgoing radiation from the pack)
PX: Total snowmelt reaching the land surface, inches
MELT: Total melt, inches
CONV: Convection melt, inches
RAINM: Rain melt, inches
CONDS: Condensation melt, inches
ICE: Ice formation at the land surface, inches
173
-------
Table 34. ARM MODEL OUTPUT HEADING
(Excluding Nutrients)
THIS IS A PRCDUCTICN RUN FOR PESTICIDES
WATERSHED: P-3 kATERShED. NEAR .hATKI NSVILLE, GEORGIA
CHEMICAL: FA PA cu AT 22C.0000
INFIL- 0.5CCC
SGV- 0.0
UZS« 3.0023
SS» 0.03CC
INTER- 0.700C
GHSo 3.0
LZSM 18.0000
NN- 0.2000
IRC- 0.0
KV" 0.0
LZS« 19.3600
A- 0.0
K24L" 110000
ICS» O.C
K3« 0.4000
KK24» 0.6000
OFS- 0.0
O.UOO
K2«EL» 0.0
!=$• 3.0
-------
Table 34. (Continued)
CCVPHC* C.60 0.70 0.70 0.70 0.0 O.C Q.2C 0.60 0.65 O.£0 0.70 C.30
TIHTIL- 0 0 142 155 16$ YRT1U" 73 73 73 73 73 SRERTL- 2.000 2.000 2.000 2.003 1.033
SZOFTh- 0.0625 UZOPTH* 6.0625 EULKO- 1Q3.CCCO
JRER- 2.2CCO KRER- 0.0700 JSER- 1.8000 KSER- 0.3500 SRER!> 0.0
TIKF. 364 Y6ARAP- 73 SSTR- 0. tit C.616 0.616 0.616 0.616
CHAX» C.CCOC1C CO- 0.000300 K- 120.0003 N> 2.0000 NP» 4.tOOO
06GCON- 0.002000
I—«
^1
tn
HYCAL-PRCO JUPOT-ENGL OU7PUT-BOTH PR1NT-CAVS SSCW-NC PEST-YES NUTR»^0 ICHECK-ON
DSSO»P»YSS
-------
Table 35. NUTRIENT SIMULATION OUTPUT HEADING
THIS IS A PRCDUCTI6N RUN FOR NUTRIENTS
cn
INtRVL- 5
BGNCAY. 12
ENCCAY* 13
WATERSHED!
CHEMICAL!
INPUT UNITS:
OUTPUT UNITS:
PPINT INTERVAL: EACH 04 V
SKCMMELT N01 PERFORMED
TEST INPUT SEQUENCE
NITR03EN, PHOSPHORtSt ANOCKORIOE
ENGLISH
HYHIN- 0. C010
BGNHON- 6
ENCMON- 6
AREA- 6.6700
BGNYR- 1973
6NDYR- 1973
UZSN- C.C5CO
L» 16C.OOOJ
INFIL« C.5000
SGfc- 0.0
UZS- J.1000
£S« 0. 0500
INTER- 0.700C
CMS- 0.9
LZSN- 18.0000
m* 0.2 ooo
IRC" 0.0
KV- 0.0
LZS- 20.3900
A- 0.0
K24t« 1.0000
ICS- 0.0
KK24-
OFS-
0.4000
0.6000
0.0
ISS-
0.1230
0.0
0.0
CCVPMO l.OC 1.00 1.00 1.00 l.CO 1.00 1.00 1.00 1.40 l.CO 1.00 1.00
TIKTU- 0 0 0 155 16* »RTIL- 73 73 73 73 73 SRf-RTL- 5.000 5.000 5.000 5*000 2.300
SZCPTI— 0.12JO t'ZOPTH- £.1250 8ULKO- 103.0000
JRcR- 2.2CCO KRER.- C.1700 JSER- 1.8000 KSER- 1.2030 SH£«I- 2.6303
-------
Table 35. (Continued)
HVCAL-PRCC IMPUT-E.NGL OUTPUT-ENGL PRINT-CAYS SNOH»NC
PEST«NO
NUTR-VeS ICHECK-OFF
NUTRIENT SIMULATION INFCRMATION
»<4»4 4 *»»»«<* •***«***»****»*:» ************
* *
* VABMNG: NUTRIENT ALGORITHMS *
» h/VE NOT SEEN VERIFIED »ITH *
« CBSEPVEO DATA *
* *
4**4444******************* 4*****
TIKE STEP FOR TRANSFORMATIONS
sjtBEft OF NUTRIENT APPLI
DATE CF PLANT hAS'/ESTIKC
N11ROGEN REACTION RATFS
SURFACE
UPPER ZCNS
LC1.E* 20.ME
OF-CUNCV.ATER
TECFERATURE C3EF.
FHCSFHOfCS REACTION RATES
SURFACE
UPPFK iCKE
iONE
TEMPERATURE CCEF.
,TIONS •
CATIONS
, = 360
Kl
2.000J
2.0300
2.J)?0
2.0030
1.05J
KM
0.0077
O.J077
0.0077
J.0077
1.350
60 MIN
» 1
K2
4. COCO
4.0000
4.00CO
4.0000
1.050
KIM
0.0
0.0
0.0
O.C
1.050
KK2
0.0
0.0
0.3
C.O
1.050
KPL
fl. 0180
0.0180
0.0180
0.0130
1.C50
KD
0.0
0.0
0.0
0.0
1.050
KCA
2.0000
2.0000
2.0000
2.0003
1.050
KPL
0.336.)
0.0363
0.0363
0.03EC
1.C5C
K«S
0.10CC
C, 1003
0.10CC
0.1003
1.053
KAM
0.0077
0.0077
0.3077
O.OC77
1.050
KIN
0.0
0.0
0.0
C.O
1.053
KK 1H
0.0
0.0
0.0
0.0
1.050
-------
Table 35. (Continued)
UPFEA ZONE
iVERACE
ULCCK 1
eLCCK 2
ELCCK 3
ELOCK 4
8LCCK 5
LOfcEP ZONE
I14'l.
1144.
1144.
1144.
1144.
1144.
0.0
0.0
0.0
0.0
3.0
0.0
43.000
4S.COO
48. COO
48.000
48.000
43.00G
C.O
0.0
C.O
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.c
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0. 0
228.
228.
228.
22 8.
228.
228.
0.0
0.0
0.0
0.0
0.0
0.0
9.600
9.600
9.600
9.600
9.600
9.600
0.0
0.0
0.0
0.0
0.0
0.0
3.0
3.3
3.0
3..1)
0.3
3.3
00
STCRACE
GRCLAtkATER
ST CRAGS
TOTAL NITROGEN IN SYSTEM »
TCTAl fHCSPHORUS IN SYSTEM
T3TAL CHLGRIDc IN SYSTEM •
11250. 0.0 480.000 0.0
3.
0.0
O.C
12947.300 LB/AC
2613.600 LB/AC
C.3 LB/AC
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2275.
0.0
0.0
96.000 3.3
0.0
0.0
3.0
J.3
SUTiiisKS - L9/AC
APPLICATION fCH DAY 164
SLKFACe LAYER
AVERAGE
BLOCK I
BLOCK 2
BLOCK 3
BLIT.K 4
bLCCK 5
UPPER ZONE
JVERAGE
SLOCK 1
ELOCK 2
BLCCK 3
ELCCK 4
dLCCK 5
ORG-N NH3-S NH3-A
J.
0.
3.
0.
0.
0.
0.
0.
3.
0.
3.
0.
C.C
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
4.000
4.0CO
4.000
4.000
4.3.70
4.000
1«6.CCC
166. OOC
196.000
1«6. COO
196.003
166.000
0.3
0.0
0.0
0.3
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
N02 NC3 N2 PLVT-V ORG-P PD4-S P04-A PLST-»
0.0 0.0 0.0
0.0 0.0 0. 0
0.0 0.3 0.0
0.0 C.O 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
O.C 0.0 0.0
0.0 0.0 0.0
0.0 0.3 0.0
0.0 0.0 0.0
CL
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.400
C.400
0.430
0.400
0.400
0.400
19.600
19. £00
19.600
19.600
19.600
19.600
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0,0
0.0
0.0
0.0
0.0
2.030
J.333
2.030
2.300
2.333
2.030
91.333
93.333
93.000
93.333
98. 000
93.330
-------
presents the heading for the nutrient parameters. The control parameter
OUTPUT allows the user to specify Model output for the production mode
in English (OUTPUT = ENGL) or Metric (OUTPUT = METR) units, or both
(OUTPUT = BOTH). The option for output in both sets of units should be
used sparingly due to the vast amount of computer printout which
results. The calibration mode output for storm events is provided in a
mixed set of units (see Tables 22, 23, and 24) to simplify comparison of
simulated and recorded values in the calibration process.
PARAMETER EVALUATION AND CALIBRATION
The process of applying the ARM Model to a watershed requires a fitting
or calibration of the Model parameters to the specific watershed. The
large majority of the parameters are easily determined from topographic
maps, watershed and soil characteristics, or pesticide chemical
properties. Hydrology and sediment parameters which cannot be
deterministically evaluated must then be evaluated through the
calibration process as a result of comparison of simulated and recorded
results. The following discussion provides guidelines for estimating
the ARM Model parameters relating to hydrology, snowmelt, sediment, and
pesticide simulation. Nutrient parameters are excluded due to lack of
testing and experience with the nutrient nfodel. In addition, the
parameters included below are limited to those which are not
self-explanatory by their definitions in Table 19. A complete list of
the PI and P3 watershed parameters is provided in Table 36.
179
-------
Table 36. PI and P3 WATERSHED PARAMETERS
Parameter
Hydrology
UZSN
LZSN
L
SS
NN
A
K3
EPXM
INFIL
INTER
IRC
K24L
KK24
K24EL
KV
Sediment
COVPMO
January
February
March
April
May
June
July
August
September
October
November
December
TIMTIL, YRTIL
BULKD
JRER
KRER
JSER
KSER
PI
Watershed
0.05
18.0
160.0
0.05
0.20
0.0
0.40
0.12
0,50
0.70
0.0
1.0
0.6
0.0
0.0
0.30
0.30
0.30
0.30
0.0
0,0
0.0
0.25
0.50
0.70
0,70
0.60
, SRERTL
0, 73, 0.0
0, 73, 0.0
142, 73, 5.0
155, 73, 5.0
164, 73, 2.0
103.0
2.20
0.17
1.80
1.20
P3
Watershed
0.05
18.0
220.0
0.03
0.20
0.0
0.40
0.12
0.50
0.70
0.0
1.0
0.6
0,0
0.0
0.60
0.70
0.70
0.70
0.0
0.0
0.20
0.60
0.85
0.70
0.70
0.30
0, 73, 0.0
0, 73, 0.0
142, 73, 2.0
155, 73, 2.0
166, 73, 1.0
103.0
2.20
0.07
1.80
0.35
180
-------
Table 36-(continued)
Pesticide
TIMAP 164
YEARAP 73
AREA 6.67
Pesticide-Diphenanrid
SSTR!>*4.002
CMAX 0.00026
DD 0.0
K 1.8
N 1.6
NP 3.7
DEGCON 0.08
APMODE SURF
SZDPTH 0.125
UZDPTH 6.125
Pesticide Paraquat
SSTR 5*1.340
CMAX 0.00001
DD 0.0003
K 120,0
N 2.0
NP 4.6
DEGCON 0.002
APMODE SURF
SZDPTH 0.0625
UZDPTH 6.0625
Initial Conditions (January 1, 1973}
UZS 0.02
LZS 19.51
SGW 0.0
GWS 0.0
ICS 0.0
OFS 0.0
IFS 0.0
SRERI 1.8
166
73
3.08
1.848
0.00026
0.0
1.8
1.6
3.7
0.08
SURF
0.125
6.125
5*0.616
0.00001
0.0003
120,0
2.0
4.6
0,002
SURF
0.0625
6.0625
0.2
18.0
0.0
0.0
0.0
0.0
0.0
0.3
181
-------
HYDROLOGY PARAMETERS
A: A is the fraction representing the impervious area in the
watershed. Usually A will be negligible for agricultural
watersheds, except in cases of extensive outcrops along
channel reaches.
EPXM: This interception storage parameter is a function of cover
density.
Grassland 0.10 in.
Forest cover (light) 0.15 in.
Forest cover (heavy) 0.20 in.
UZSN: The nominal storage in the upper zone is generally related to
LZSN and watershed topography. However, agriculturally
managed watersheds may deviate significantly from the
following guidelines:
Low depression storage,
steep slopes, limited
vegetation O.OSxLZSN
Moderate depression storage
slopes and vegetation O.OSxLZSN
High depression storage,
soil fissures, flat slopes,
heavy vegetation 0.14xLZSN
LZSN: The nominal lower zone soil moisture storage parameter is
related to the annual cycle of rainfall and evapotranspiration.
Approximate values range from 5.0 to 20.0 inches for most of the
continental United States depending on soil properties. The
proper value will need to be checked by computer trials.
K3: Index to actual evaporation. Values range from 0.25 for open
land and grassland to 0.7-0.9 for heavy forest. The area
covered by forest or deep rooted vegetation as a fraction of
total watershed area is an estimate of K3.
K24L, K24EL: These parameters control the loss of water from near
surface or active groundwater storage to deep percolation and
transpiration respectively. K24L is the fraction of the
groundwater recharge that percolates to deep groundwater
table. Thus a value of 1.0 for K24L would preclude any
groundwater contribution to surface runoff. K24EL is the
fraction of watershed area where shallow water tables put
groundwater within reach of vegetation.
182
-------
INFIL: This parameter is an index to the mean infiltration rate on
the watershed and is generally a function of soil
characteristics. As for LZSN, approximate or initial values
will need to be checked by computer trials. INFIL can range
from 0.01 to 1.0 in/hr depending on the cohesiveness and
permeability of the soil.
INTER: This parameter refers to the interflow component of runoff and
generally alters runoff timing. It is closely related to
INFIL and LZSN and values generally range from 0.5 to 5.0.
Examples of its effect are discussed below and in Section IX,
Sensitivity Analysis.
L: Length of overland flow is obtained from topographic maps and
approximates the length of travel to a stream channel. Its
value can be approximated by dividing the watershed area by
twice the length of the drainage path or channel.
SS: Average overland flow slope is also obtained from topographic
maps. The average slope can be estimated by superimposing a
grid pattern on the watershed, estimating the land slope at
each point of the grid, and obtaining the average of all
values measured.
NN: Manning's n for overland flow. Approximate values are:
Asphalt 0.014
Packed Clay 0.03
Turf 0.25
Heavy Turf and
Forest Litter 0.35
IRC,
KK24: These parameters are the interflow and groundwater recession
rates. They can be estimated graphically (51) or found by
trial from simulation runs. Since these parameters are
defined below on a daily basis, they are generally close to
0.0 for small watersheds that only experience runoff during or
immediately following storm events.
_ Interflow discharge on any day
1RL " Interflow discharge 24 hours earlier
_ Groundwater discharge on any day
- Groundwater discharge 24 hours earlier
KV: The parameter KV is used to allow a variable recession rate
for groundwater discharge. If KV = 1.0 the effective
recession rate for different levels of KK24 and the variable
groundwater slope parameter GWS is as follows:
183
-------
GWS
KK24 0.0 0.5 1.0 2.0
0.99 0.99 0.985 0.98 0.97
0.98 0.98 0.97 0.96 0.94
0.97 0.97 0.955 0.94 0.91
0.96 0.96 0.94 0.92 0.88
For small watersheds without a groundwater flow component, a
value of 0.0 is generally used.
SNOWMELT PARAMETERS
RADCON,
CCFAC: These parameters adjust the 'theoretical melt1 equations for
solar radiation and condensation/convection melt to actual field
conditions. Values near 1.0 are to be expected. RADCON is
sensitive to watershed slopes and exposure.
SCF: The snow correction factor is used to compensate for catch
deficiency in rain gages when precipitation occurs as snow.
Px(SCF-l.O) is the added catch. Values are generally greater
than 1.0.
ELDIF: This parameter is the elevation difference from the temperature
station to mean elevation in the watershed in thousands of feet
(or kilometers). It is used to correct the observed air
temperatures for the watershed using a lapse rate of 3 degrees F
per 1,000 feet elevation gain.
IDNS: This parameter is the density of new snow at 0 degrees F. The
expected values are from 0.10 to 0.20. Equation 15 gives a
variation in snow density with temperature.
F: This parameter is the fraction of the watershed that has complete
forest cover. Areal photographs are the best basis for
estimates.
DGM: DGM is the daily groundmelt. Values of 0.01 in/day or less are
usual.
WC: This parameter is the maximum water content of the snowpack by
weight. Experimental values range from 0.01 to 0.05.
MPACK: The estimated water equivalent of the snowpack for complete areal
coverage in a watershed.
184
-------
EVAPSN: Adjusts the amounts of snow evaporation given by an analytic
equation. Values near 0.1 are expected.
MELEV: The mean elevation of each watershed segment in feet (meters).
TSNOW: Temperature below which snow is assumed to occur. Values of 31
degrees to 33 degrees F are often used.
PETMIN, PETMAX: These parameters allow a reduction in potential
evapotranspiration for air temperatures near or below 32 degrees
F. PETMIN specifies the air temperature below which potential
evapotranspiration is zero. For air temperature between PETMIN
and PETMAX, potential evapotranspiration is reduced by 50 percent
while no reduction is performed for temperatures above PETMAX.
Values of 35 degrees F and 40 degrees F have been used for PETMIN
and PETMAX, respectively.
PETMUL, WMUL, RMUL: These three parameters are used to adjust input
potential evapotranspiration, wind movement, and solar radiation,
respectively, for expected conditions on the watershed. Values
of 1.0 are used if the input meteorologic data is observed on or
near the watershed to be simulated.
KUGI: KUGI is an integer index to forest density and undergrowth for
the reduction of wind in forested areas. Values range from 0 to
10; for KUGI = 0, wind in the forested area is 35 percent of the
input wind value, and for KUGI = 10 the corresponding value is 5
percent. For medium undergrowth and forest density a value of 5
is generally used.
SEDIMENT PARAMETERS
JRER: JRER is the exponent in the soil splash equation (Equation 1) and
thus approximates the relationship between rainfall intensity and
incident energy to the land surface for the production of soil
fines. Values in the range of 2.0 to 3.0 have demonstrated
reasonable results on the limited number of watersheds tested.
(A value of 2.2 was chosen for the Georgia watersheds.)
KRER: This parameter is the coefficient of the soil splash equation and
is related to the credibility or detachability of the specific
soil type. KRER is directly related to the 'K' factor in the
Universal Soil Loss Equation (52). Initial estimation of KRER
can be performed in the same manner as the evaluation of the K
factor (52, 53). However, this initial value will need to be
checked through calibration trials.
185
-------
JSER: JSER is the exponent in the sediment washoff, or transport,
equation (Equation 5), and thus approximates the relationship
between overland flow intensity and sediment transport capacity.
Values in the range of 1.0 to 2.5 have been used on the limited
number of watersheds tested to date. (A value of 1.8 was chosen
for the Georgia watersheds).
KSER: This parameter is the coefficient in the sediment washoff, or
transport, equation. It is an attempt to combine the effects of
(1) slope, (2) overland flow length, (3) sediment particle size,
and (4) surface roughness on sediment transport capacity of
overland flow into a single calibration parameter. Consequently,
at the present time calibration is the major method of evaluating
KSER. Terracing, tillage practices, and other agricultural
management techniques will have a significant effect on KSER.
Limited experience to date has indicated a possible range of
values of 0.01 to 5.0. However, significant variations from this
can be expected. (The values determined on the PI and P3 Georgia
watersheds were 1.2 and 0.35, respectively.)
SRERI, SRERTL: These parameters indicate the amount of detached soil
fines on the land surface at the beginning of the simulation
period (SRERI) and the amount produced by tillage operations
(SRERTL). Very little research or experience relates to the
estimation of these parameters. Thus, calibration is the method
of evaluation. For SRERI, one would expect that spring and
summer periods on agricultural watersheds would require higher
values than fall and winter periods due to the growing season
disturbances and activities on the watershed. Values of SRERTL
are related to the severity or depth of the tillage operation, and
must be input to correspond with the dates of tillage operations
(TIMTIL, YRTIL). Values of these parameters on the Georgia
watersheds have ranged from 0.5 to 5.0 tons/ac.
COVPMO: This parameter is the percent land cover on the watershed, and is
used to decrease the fraction of the land surface that is
susceptible to soil fines detachment by raindrop impact. Twelve
monthly values for the first day of each month are input to the
Model, and the cover on any day is determined by linear
interpolation. COVPMO values can be evaluated as one minus the
C factor in the Universal Soil Loss Equation, i.e. COVPMO = 1 - C,
when C is a monthly value. Evaluation methods for the C factor
have been published in the literature (52, 54).
186
-------
PESTICIDE PARAMETERS
DD, K, N, NP: These parameters define the adsorption/desorption
functions used in the present version of the ARM Model. Their
values must be determined for each pesticide-soil combination
from laboratory experiments or from published research results.
CflAX: CMAX is the water solubility of the specific pesticide being
simulated. Literature values are generally used, and no
temperature correction is performed. As indicated in Section IX,
simulation results are relatively insensitive to CMAX.
DEGCON: This parameter defines the daily first-order general attenuation,
or degradation, rate for the pesticide. Values can be derived
from observed field measurements or from the literature.
SZDPTH, UZDPTH: Although these parameters specify the depth of the
vertical soil layers, their major impact is on pesticide
simulation. Very little experience exists for evaluation of
these depths. UZDPTH is generally evaluated as the depth of
tillage or pesticide soil incorporation while SZDPTH is the depth
of the active surface zone. UZDPTH must be greater than SZDPTH.
Expected ranges for these parameters would be 2.0 to 6.0 inches
for UZDPTH and 1/16 to 1/4 inches for SZDPTH.
BULKD: This soil parameter also has a major impact on pesticide
simulation. BULKD, the soil bulk density, can be evaluated in
the laboratory or from the literature.
187
-------
CALIBRATION
Calibration is an iterative procedure of parameter evaluation and
refinement as a result of comparing simulated and observed values of
interest. It is required for parameters that cannot be deterministically
evaluated from topographic, climatic, edaphic, or physical/chemical
characteristics. Fortunately, the large majority of the ARM Model
parameters do not fall in this category. At the present time, calibration
of the ARM Model generally involves only hydrolgy and sediment parameters.
As indicated in Section VIII, the goal of pesticide transport modeling is
to develop a model which can be used in various regions of the country
with pesticide parameters evaluated from laboratory experiements or from
the literature. If calibration is required for determining pesticide
parameters, then recorded pesticide data would be required for each
watershed simulated. This would limit application to few watersheds
across the country. Although future developments may require calibration
of pesticide parameters, the goal of the ARM Model development at present
is to limit calibration to hydrology and sediment parameters for which
data is more generally available.
Hydrology calibration must preceed sediment calibration since surface
runoff is the transport mechanism by which sediment loss occurs. The
procedure is to compare simulated and recorded monthly runoff volumes (as
indicated in Section VIII for the PI and P3 watersheds) obtained from
initial parameter values. Calibration trials should not be performed for
periods of less than 9 months to avoid the effects of initial soil
moisture conditions. The hydrology parameters LZSN, INFIL, and INTER are
the ones most directly evaluated by calibration; for managed, or
disturbed watersheds UZSN is often included in this list. LZSN and
INFIL have the greatest effect on runoff volumes and thus are most often
modified to increase agreement between simulated and recorded monthly
runoff volumes. When monthly values are in reasonable agreement, the
INTER parameter is often used to modify hydrograph shape to improve
simulation of storm hydrographs. Minor adjustments to INFIL and UZSN (in
the case of small agricultural watersheds) can also be employed to improve
storm hydrograph simulation. Thus, hydrologic calibration involves
comparison and parameter modification for the simulation of both monthly
runoff volumes and storm hydrographs. The sensitivity analysis in Section
IX indicates the relative effects of parameter changes as an aid to
calibration. A detailed discussion of the hydrologic calibration process
is available to the interested user in other publications.1- 2- 3
Sediment parameter calibration is more uncertain than hydrologic
calibration due to less experience with sediment simulation in different
regions of the country. The process is analogous; the major sediment
parameters are modified to increase agreement between simulated and
recorded monthly sediment loss and storm event sediment removal. A
188
-------
balance between the generation of detached soil fines and the transport,
or removal, of soil particles must be developed so that the storage of
detached fines is not continually increasing or decreasing throughout the
calibration period. The KRER and KSER parameters are most directly
involved in sediment calibration and the development of this sediment
balance since they are relatively less well defined by theoretical and
physical considerations. Thus a balance must be established between the
KRER and KSER parameters in the agreement of simulated and recorded
monthly sediment loss. The SRERTL parameter has a major effect on
sediment simulation on agricultural watersheds since it specifies the
amount of detached soil fines produced by tillage operations. The soil
fines are then available for transport by overland flow from the
watershed. The value of SRERTL is also instrumental in the balance
between soil fines generation and transport. Storms occurring soon after
tillage operations would likely transport sediment at or near the
transport capacity of the overland flow, while storms occurring later in
the growing season would have sediment loss limited by the amount of fines
available for transport. SRERTL should be large enough to have a major
impact on sediment loss by storms soon after tillage, but small enough to
have a minor effect on sediment loss late in the growing season. As an
aid to calibration, an asterisk is printed in the ARM Model sediment
calibration output (see Table 22) whenever sediment removal is limited in
each areal zone (or block) by the availability of soil fines. Thus when
asterisks are printed, sediment removal is being controlled by the
generation and availability of soil fines. Whereas, when no asterisks are
printed, the washoff or transport mechanism is the major controlling
factor. When the washoff mechanism is controlling, the JSER parameter can
be modified to improve the shape of the simulated sediment removal graph.
In a similar manner, the JRER parameter will affect the sediment removal
graph when the generation and availability of detached soil fines is
controlling sediment removal.
In summary, the calibration process requires an understanding of the
physical process being simulated and of the impact of the critical ARM
Model calibration parameters. Study of the parameter definitions,
algorithm formulation, and sensitivity analyses results presented in this
report should allow the user to become reasonably effective in calibrating
and applying the ARM Model.
189
-------
APPENDIX B
ARM Model Sample Input Listing
//CCB75C8 JCB (C5lOt510fl,30).',;-|508BEYtRLElN'
//JOBLIB 00 CSMME=C510.DCB.J15Ce.ARM,DISPMOLD,K£EP)i
// UMT»2214,VQL»SER=FILEC
//STEP! EXEC FGMARf
X/SYSPP-INT CC <\£QIT«A
//FT06FC01 CC SYSGUT»A
//FT05FCC1 CD «
SAMPLE INPUT FCP HYPCTI-ETICAL M1ERSHED
CATA SET UP FCP SNO, PESTICICE, *ND NUTRIENTS
HYCAL=PRCO
IKFUT»ENGL
CUPUT^ENGL
PR1NT=CAYS
PES1=YES
MTR=YES
!ChECK=CN
ECNTL INTPVl=5t HYHU-O.OC1. *REA=3.08
6STRT
6ENOO
CLN01
SLND2
6LN03
BGNKCN=l2t EGKYR=1973 CcNO
C.ENO
6SN01
8SN02
6SN03
6SNQA
CCROP
CKUD1
6CIRT
ESMOL
U2SN = O.C5, UZS=0.002, L2SN = 16.0, LZS>19.36 (.END
L = 220., SS=0.03t NN = 0.20, A=0.00, K3=0.^0t cPXM=0.12
INFIL=C.50, !NTER=0.7i IFC=O.Of Ki4L=1.0, KK2^=0.6f K2ASL=0.0 6ENO
SGW=0.0, GWS=O.C, KV=C.C, ICS=0.0, OFS=0.0, 1FS=0.0 EENO
PAOCCN=1.0tCCF*C=1.0,SCF = 1.0,ELL)If:=O.Of IUNS=0. l^t F=0. 0 £ENO
OGH=0,CfWC==0.03,KPACK=l.O,EVAPSN=1.0,MtLcV=0.0,TSNOW=32.0 &ENO
PACK=C.C, OEFTH*0.0 6ENC
PETMK»^C.O,PET^AX=5C.OtFETMljL=UatWrtUL=l.O,RMUL=1.0,KUGI=0.0 6ENO
CCVFKO>=C.6,0.7iC.7,(.l,C.CtC.O,U.2,0.6,0.8i>f O.dfO.7,0.3 fiEND
TIMIl*C,0(142,155,U6,
YRTIL*£*73, £PEPTL=J. 0,2. 0,2. 0,2. 0,1.0 &£NO
.CC25, BULKO=L03.0 tENO
*l.a, KSER«0.35t S*fcRi=0.0 6ENO
PESTICICE
SSTF=5*C.tl6,
DC = C.CC03, K=-l20.t M2.Ct NP*4.6
CCEG1 DEGCCN=C.0020 «ENC
NURIEKT
CNUTRIN 1STEF=60, KAPPL=1, 11KHAR=34t
REACTICN PATES
MTROCEN
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2.0 4.0
GFCUNChATER
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TEPPERATUFE CCEFFIC1ENTS
1.C5 I.C5
, CMAX=0.00001,
6END
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1.0
1.05
H-CSPHCRLS
SURFACE
.0011
UFER ZCKE
O.C
.01£
2.C
0.1
190
-------
Appendix B (continued)
.0077
LChER ZCNE
.OC77
GBCUNCHJT6R
.0077
TEHPERMbRE
1.05
EM
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O.C .018 2.C 0.1
C.C .018 2.C 0.1
0.0 .018 2.C 0.1
CCEFFICIEN1S
1.C5 1.05 1.0! 1.05
O.C 1.0 O.C 0.0
C.O 48. C.C 0.0
O.C 480. C.C 0.0
0.0 0.0 O.C 0.0
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0.0 5.£ C.C
C.C St. C.C
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3C4
0.0 4.0 C.C 0.0
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O.C 19.6 C.C
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
191
-------
Appendix B (continued)
ENC
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192
-------
Appendix B (continued)
TEKP73
TEKP73
TEMP 73
UIND73
NIN073
MIN073
59 52 68 57 79 55 92 69 65 A7 55 22 39 19 36 22
•7 45 72 55 81 60 &S oti 65 A7 51 36 49 24 24 16
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193
-------
Appendix B (continued)
RACI73
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7212206
7212207
7212208
7212211
7212212
7212213
7212214
7312215
121221*
7212211
7312218
7312229
1:1222-5
7212249
7212251
7212252
7212253
7312254
1312255
C
0
0
C
0
c
0
0
0
0
c
0
0
0
0
0
0
0
0
0
c
0
c
0
0
c
0
c
c
0
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162510
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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0
0
0
0
0
0
0
0
0
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c
0
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0
0
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0
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c
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c
c
0
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
0
c
c
c
1 4
61
.52
33
39
38
44
53
55
57
48
44
49
39
30
35
36
33
34
46
40
54
56
56
54
5S
51
56
57
52
47
56
>12
61
62
68
67
63
61
60
62
36
69
69
66
51
55
63
67
63
67
66
57
56
59
61
58
58
65
62
60
58
62
0
4-
63
68
67
t>0
59
62
68
71
67
69
38
60
65
6i
54
50
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67
08
64
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71
70
72
60
59
59
66
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66
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ot>
67
72
72
63
6b
60
58
64
57
59
67
62
66
61
54
54
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ol
69
75
/3
72
70
68
70
75
68
71
66
63
49
51
51
51
57
48
46
49
51
51
44
47
45
49
41
48
59
49
52
66
67
69
57
58
52
0
61
59
57
63
43
42
51
61
63
63
58
63
58
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41
35
23
36
49
38
44
45
46
47
52
43
48
45
46
46
45
47
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1C2
161
24
29
21
30
30
29
30
32
31
31
24
43
£0
41
40
32
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41
39
40
42
46
40
57
38
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21
29
28
0
48
81
68
102
175
22
36
47
49
31
25
19
24
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19
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22
9
-10
-5
-5
-I
-143
10
12
6
-3
24
23
37
29
26
29
14
6
5
194
-------
Appendix B (continued)
12122£<
1312251
121225C
13122(1
7212262
1312263
1212244
7312265
1212264
7212261
121226E
1312275
7212261
12122E2
1212263
1212264
1312265
12122C6
13122C7
72122(6
1312259
1212301
13122C2
1212303
1312304
1212305
11 1 o*ar x
• JL£ 3 I C
1212201
731220C
1212311
1312312
1212313
1212214
1212315
12123U
1212211
1312316
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
EWP74
EXAP74
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
ESAP74
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
EVAP74
15
£
3 4
212
1 2
3 4
212
92
£6
66
16
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52
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43
11
5
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66
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66
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22
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27
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22
49
58
£4
1
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2? 5
C. €.
1 1
212
1
222
1 1
212
76
69
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158
132
94
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50
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94
69
69
19
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126
69
107
69
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410
16
1 1
11
1
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121
1 1
1 1
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1 2 1
126
141
126
111
146
7
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118
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133
170
170
141
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114
167
V3
271
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1
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77
34
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237
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157
192
0
140
203
45
325
202
156
72
260
195
207
92
110
211
271
276
LO 1 3
211
121
1 1
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121
206
120
217
174
109
28
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120
102
210
217
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131
77
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94
197
52
510
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158
Io3
82
1
2111
1212
1393
2111
1212
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103
70
113
175
185
0
49
136
213
76
61
116
209
195
71
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224
206
301
132
215
3 A fl9ai£. i i n o *5 i i
H alolo 1 l(J £ <£ 1 3
21111111122
1111 1 1
3 4 82816 110 2213
^1111111122
1111 1 I
177
155
57
172
131
7
20
32
34
63
84
125
100
92
26
98
66
46
117
101
11
95
95
195
-------
Appendix B (continued)
EVAP74
EVAP74
E\AP74
S*AP74
EVAP74
EVAP74
ESAP74
E\AP74
1EPP74
1EPP74
TE*P74
TEMP74
TEKP74
IE HP 7 A
1EPP74
TEKP74
TEMPTS
TEPP74
1EPP74
TEKP74
TEPP74
7EPP74
1EMP74
1EPP74
1E*P14
7ENP74
1E*P<4
TEMP74
TEPP74
TEfP74
TEMPTS
TEfP74
7EPP14
7EKP74
UKP74
1EKP74
TE*P74
1EMP7A
TEKP7A
VIKD74
VIND74
V.IN074
k!ND14
h!N014
HN07
-------
Appendix B (continued)
UND74
hINDIA
hI»»D74
HND74
V.IND74
UKD14
WIND 14
hIND74
HND14
UND74
MC174
PADI14
1:00174
fSAOI74
RAOI74
MCI74
PAOI14
RACI74
SACI74
RAOI74
RAOI74
SACI74
RACI74
RAC174
P 401 14
RADI74
C4U7*
RAOI74
PACI74
FACI74
RACI74
RICI74
RA0174
RAOI74
CACI74
ISACI74
RACI74
BACI74
RAOI74
CACI74
RAOI74
CEWT74
C£kPT74
ClliPTl4
CEhPT74
CEHPT14
CEWPT14
CEMPT74
CEkPT74
CEhPT14
CEVIPT74
CEMPT74
CEkPT74
CEhPTl4
CEhPT74
CEhPT14
CEMM74
CEHP174
CEI.PT14
CEMPT74
140
10
100
14C
ISC
110
8C
220
190
30
193
166
247
149
160
274
107
178
155
195
67
112
79
169
24
115
198
67
44
125
25
17£
164
25
35
21
47
47
1C2
161
175
14
19
11
10
10
29
10
12
11
11
24
23
20
21
20
12
10
21
19
110
100
150
250
100
150
200
175
165
175
75
75
125
72
80
67
65
117
161
29
166
152
193
215
118
75
88
183
104
100
133
32
56
48
61
22
36
47
49
31
25
19
24
29
19
25
22
9
10
S
5
1
13
10
197
-------
Appendix B (continued)
CEkP774
CEWT74
CEHP774
CEKPT74
CEWPT74
CEkPT74
CEKPT74
C£hPT74
CEKPT74
CEWPT74
CEfcPT74
7401019
1401029
1401C39
740101?
7401069
1401C7S
7401061
7401C82
7401063
1401064
7401C65
7401C66
7401067
1401C88
74010*9
1401 1C9
740111S
7401129
140113S
7401149
7401159
7401161
7401U2
7401163
7401164
7401US
7401166
7401167
7401166
1401171
7401172
7401173
7401174
7401175
7401176
74C1177
7401178
7401189
7401159
74012C9
7401219
740122S
1401239
7401249
1401251
7401252
7401253
20
22
26
20
27
16
21
26
11
14
6
12
6
3
24
23
37
29
26
29
333
2586526993
3 3
252
I 4 614 I
20 4
141
198
-------
Appendix B (continued)
1401254
14C1255
140125*
1401257 2
14C12S8 23 14
1401269
1401279
1401289
1401299
1401301
1401302
14013C3
1401304
1401305
14013C6
14013C7 13383911 5 4
14013C8
1401319
1402011
1402012
1402013
7402014
1402015
1402016
1402017 652 262
1402018
1402029
1402C39
1402049
1402059
1402CC9
1402019
1402C69
1402CSS
140210$
7402119
1402129
1402139
1402149
1402159
1402 U9
1402171
7402172
1402173
14C2174
1402175 22 3
140217CLO 5
1402177
740217£
1402181
1402162
1402183
H021E4 101010 5
14021£5
1402166
7402167
7402188
1402199
14022C9
1402219
199
-------
Appendix B (continued)
•540222S
1402239
1402249
200
-------
APPENDIX C
ARM Model Source Listing
1.
2.
3.
4.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
21.
22.
23.
34.
25.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
46.
49.
50.
£1.
£2.
£3.
54.
55.
56.
57.
£e.
59.
60.
61.
«al
64.
/
/
/
/
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
/CCE7508 JOB (C51C , 51C ,6 ,251,'J750aBcY£RLEIN»
/< SERVICE CLASS=LAFC-£
//STEF1 EXEC FCPThCl,LEVEL-BIG,PARM.FORT='OPT=1,MAP,XREF*
//FCF1.SYSIN CC *
*
*
*
AGRICLLTURAL RUNOFF MANAGEMENT (ARM) POOEL
DEVELOPED BY:
FOR:
HYCRCCOVP, INCCRPCRATED
1502 PAGE PILL RQAO
PALC ALTO, CA. 94304
415-493-5522
U.S. ENVIRONMENTAL
PRCTECTIGN AGENCY
UFFICE CF RESEARCH
AND DEVELOPMENT
SOUTHEAST ENVIPCN^E^AL
RESEARCH LAOOPATORY
ATHENS, GA. 30601
404-546-3147
MAIN PROGRAM
IMPLICIT PEXL(l)
CIPEhSICN FESE {51,RESBl(5),RjS3(3),SftGXi:>),INTF(5),RGX(5),INFL<5) ,
1 LZSE(5l,APERCe«5),RIB(5),cRSN(5J
CIMENSICN SPER(«) .PCBTGWS),KOBTCT15),INFTOM(5),INFTOT(5),
I ROITCM5) ,fCITCT(5),RXB(5),cKSTCMO),ciiiTuT(5),MNAM(12),RAO(24),
2 TEMPX(24) , HNOM24) ,RAIN (28tt), SRE«MT(b) ,fcn.SNNTt 5 )
CIFENSICN PFSTCHE),PRSTOT(5),PRCrGrt(5),PROTOT(5),UPITCMI5) ,
1 IPITOTC5) ,J ,oOS< 5 ) ,SSTP(5),
2 LAS(5),UCS(5),ICS(5),USTR(S),UPRIS(5)
CI^ENSICN IF/IN (288),IRAD(12,3L>,
2 IEV*PM2,21),IC£W( 12,311
Dlf^SICN hSN/l"E (20) ,CHNAME120),CUVPMQI12),DPM(121
CIMENSICN TIMIL(S) ,YRTIL(5J,SRERTU5)
COMNCN /ALL/ RU,HYPIN,PRNTKE»HYCAL.,OPST,OUTPUT,TIMFAC,LZStAREA»
1 RESBl,RCSE,SPGX,INTF,RGX,INFL,UZSo,APERCfl,Kie,ERSN,M,P3,A,
2 CALe,PPOC,PEST^LTP.,ENGL,McTA,BCThfRESd,Y£S,NO,IKIN,IHR.TF,
3 JCOlNT,PRIM,IMP,DAYSrHOUR,MNTH
CCMMCN /LANC/ Nh ft- ,PRTOT , ERSNTT, FRTuM.ERSNTM ,CAY,
1 RUTOl^.NEPTCf.RCSTCM.RITljM.RINTuM^ASTaM.RCHTOM.RUTOT,
2 NEFTOT,PCSTCT,FITCT,RINTOT,BASToT,RCHTOI,ThBAL,EPTOM,EPTOT,
3 UZS,l;ZSN,LZ^,UFIL,IHTcR,lRC.NN,l-,SS,SGWl,PR,SGW,GWS,KV,
4 K24L,KK24,K2
-------
Appendix C (continued)
65. 7 CEVX,.P/CK,CEfT»-,KlNThfSDEN,lPACK,TMIN,SUMSNM,PXSNM,XK3,
£6. 8 KELRAM,RACKEK ,CCPMEP,CKAINM,CGNMcM, S&MM. SNfcGfM,SEVAPM,SUPSNYt
67. 9 PXSNY,*ELP*Y,R*^E»,CDkMEY,SGMY,CuNKEY,CRAINY,SNEGMY,SEVAPY,
66. * TSNeAL,CCVEF,CCVFKX,ROBTOM,kOBTGT,RXB,RJITCN,RCITOT,lKFTCM,
69. 1 INFTCTtEPSKf , EFSTGT.SrieF^TErtPX.RAU ,WINUX.RAIN,INPUT
10. C
71. COMMCN /PES1C/ '1ST,SPROTM,SPRSTM,SAiT,SCST,SDST,UTST.UAST,UCST,K ,
72. I UCST,FP,CI*A>,M,SFRCTT,SPKSTT,MUZ,FWU,UPRITP,
13. 2 LPRm,KGPlP.«FFlZ,Hl.Z,LSTR,LAS,LCS,LDS,li$TR,GAS,GCS,GDS,
7*. 3 APMCOE.TFEAL.
15. 4 DEGSCC.OEGSCt.CEGUCf ,
76. 5 DEGUOT.CEGt,CEOS,NIP,DEGGON,OEGLOM,DEGLOT,NCOHt
77. 6 PRSTCf,PRSlC1,FFCTCP,PRGTQT,UPITOM,UPITuT,STS,UTS,SAS,
78. 1 SCS,SC£,SSTP,l./S,LCS,UUStUSTR,UPRI$,UIST,TOTPAP,TIMAP,YEARAP,
79. 8 DESORP,SURF,SOIL,SULG
60. C
81. CCMHCN /NLT/ DEn,STEMP,SN,SNT,:>Nh:>M,$NROM,UN,UNT,UNI,UMT,
82. 1 LNRI*,NRS»',LN,LNRPM,l>N,SNRaM,UNkB»',LNRBK,GNRe»',TNi:BM,
83. 2 SNRJY,SNPO)r,UNiUY,NrNKBY,UNRBY,LNReY,GNRBY,
84. 2 lfvRe>,TNKHVtTNRHVMtTNKHVYtTNA*TPAtTCLAf
£5. 4 Krv,7t-Kh,KP,THKP,MtJAL,PHBAl_,CL8ALt
£«. 5 1£TEF,NSTcP,SFLG,UFLG,LFLG,GFLG
67. C
tfi. C
89. INTEGER 6GM1JY, EGN^CN, BGNYRt EN00AY, cNOMCN, ENOYR
90. INTEGER CYSTRTt CYENCt YEAR, MONTH, DAY, H, HYCALt TIME
SI. INTEGER YR, PC, CY, CM, TF, PRNTKE, PRINT, DA, APMOCe, OUTPUT
92. INTEGER INFLT, JKCh, LiESORP, SURF, SOIL, TIfFAC, ON, CFF
93. INTEGER CALE»PFCC,KUTR.feST,cNGL,H£TR,dUTH,INTR.HOUR.CAYS.NO ,YES
9A. INTEGER hSNA*E ,C»-NA^E,DPM
95. INTEGER JCCLNT ,T IfAP.TIMTIL,YRTIL.YEARAP.MNTH
96. C
97. PEAL*6 KKAC
98. REAL*8 PEST IC/ •FESTICIO1/
99. REAL*8 CHAF
ICO. C
101. PEAL 1PC, hf>, KV, K24L, KK24, INFILt INI£R, INFL
102. REAL IFS, 1CS, K2EUFT, KGPLB
1C7. REAL SPRTKT, EFShTT, ERSNMT
1C8. REAL NF, MF, NCCH
1C9. REAL IChS, hFACK, MELEV, KUG1, HELKAM, HELRAY, IPACK
110. C
111. C NUTRIENT VAFUBIES — DECLARED, DIMENSIONS, IN IT IALIZED
112. C
113. C
114. INTEGER*^ 1STEF,KSTEP,SFLG,UFLG,LFLG,GFLG
115. C
116. PEAL*A CELl,JTt>F(^,2^),
117. 1 SN(2Ct5),SNT<20),SNRSM(2G,5) ,SNROM(20 ,5),
118. 2 UN() .UMTt^OJ ,UNRIK (20,5 ) ,
119. 2 NRSM20.5), LN( 20) ,UNkPM(20», GN(2C>,
120. 4 SKREM(2C,5)tUNRbM(20,b) ,LNRbMUO) ,GNR6K(20) ,TNRBf (20)t
121. 5 SNRSYC2C.5) .SNkOY (20, 5 ) ,U,\Ki Y( 20,i) ,NRSY(20,5) t
122. 6 LNPFYC2C),SNRBY(20,5),UNRbY(tO,p),LNRBY(20),GNRBYt20).
123. 7 TNRjEY(2C),TNRhV(20),TNA.HVM120) ,TNKHVY(20) ,TNA, TP A,TCLA»
8 KNUO,4),1HKM10) ,KPl 5 ,^ ) , THKP («>) ,N6ALt PHBAL,CLBAL
202
-------
Appendix C (continued)
125.
126.
127.
128.
129.
130.
121.
122.
123.
134.
135.
136.
137.
138.
139.
140.
HI.
142.
143.
144.
145.
146.
147.
148.
149.
150.
151.
152.
153.
154.
155.
156.
157.
156.
159.
UO.
161.
162.
163.
164.
165.
166.
167.
168.
169.
170.
171.
172.
173.
174.
175.
176.
177.
178.
179.
160.
181.
1£2.
183.
184.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
REAL*4 SNAFL(2C,5,5),UNAPL(20,5,5),KNI(10,4) ,KP 1(5,4)
INTEGER*4 /PC AY (* » , APLCNT/1/ , JHuUR, NAPPL, J , IBLK.TIHHAR,
1 S ELH V (20 )/C, 0,0, 0,0, 0,1, 0,0, 0,0, 0,0, 1,0, 0,0,0
INTEC-EM4 C F* H( 12 )XO, 31, 26, 3 1, 30, 31, 30, 31, 3 1, 30, 3 1, 30 X
CATA TIMTHX5*CX,YRTIL/5*0/,SRERTLXi>*O.OX
CATA CCVFfC/12*C.O/
CATA ICS, CFS/2«C.O/
CATA CN/'CN'X.CFFX'CFF'/
CATA GRAC/O.C*,C.C4, 0.03, 0.02,
* C. 02, C. 02.0. 02, C. 06,0.14,0. 13, 0.20, 0.1 7. 0.1 3, 0.06, 0.03,0
* C. 07, 0.10, 0.12, C.I 5, 0.13, 0.12.0. Oa/
CATA RACCIS/t«O.C, 0.019,
*0. 04 1,0. 06 7, 0.Ctf , O.lOi, 0.110, 0.11 0,0. 110,0.105,0.095,0.
*0.017,5*O.C/
CATA V>INCIS/1*O.C34, 0.035,
* C. 037,0. 04 l,O.C<*,C.flSO, 0.053, 0.054, 0.058, 0.057, 0.056,0.
* C. 040,0. 036, 0.C36.0. 036, 0.035/
DATA CPH/2 1,2 1,2 1,30, 31, 30, 31, 31 ,30, 31 ,30, 3 1/
CATA PETKLL ,hMJl ,FMUL/3*l .O/
CfTA INPUT — NAME LIST VARIABLES
NAMELIST XCNTLX IN1RVL.HYMIN.AREA
NAMELIST /SIR!/ EGNCAY,dGNMUN,8GNYR
NAMELIST XENCCX f NDOAY.E NUKON.cNDYR
NAMELIST /L^C1/ LZSN.UZS ,L2SN,LZS
KAPELIS1 /LhC2/ L , Si ,NN, A, K3 , EPXM
KAHELIST /Lf>C2/ INF IL, INTER, IRC ,K24L,KK24, K24EL
NAfELISI /L^C4/ SGh ,GHS, KV,ICS,CFS, IFS
NA^ELIST /SrCl/ FACCCN,CCFAC,SCF,ELOIF,IONS, F
NAMELIS1 /SNC2/ CGM ,V»C, MPACK ,E VAPS^ ,McLEV, TSNOM
KAVELIST /SK3/ FACK.OcPTH
NAMELIS1 XSNC4/ FETKIN.PETKAX, PETKUC,*MUL,RMUL,KUGI
hA^ELIST /CFCF/ CGVFMO
^A^'ELIST /NLC1/ TINTIL.YRTIL.SRERTL
KAMELIS1 XD1R1/ 5ZCPTH,UZDPTH,BULKO
NAMELIST XS^CLX JPER.KRtR, JSER.KSER ,SREKI
NAHELIST XAfCL/ SSTR ,T IMAP,Y£ARAP,CMAX,DD, K» K,NP
hAMELIST XDEG1X CEGCON
INPLT PAFAt-ElEF CESCRIPTION
kSNAME: V>ATERShE[ hAfE (80 CHARACTERS)
CK*AME: CHEMC«L ^A^E (80 CHARACTERS)
MCAL : INCICA1ES VF/T FACTORS ARc TO fafc SIMULATED
- FRCD fFCCLCTICN RUN-
> CAL6 CALieF/TION RUN
IhFtT : INFLT LMTS; ENGLISH(ENGL) , McTRIC(METR)
,0,0/
.01,0.05,
C81, 0.055.
050,0.043,
OlTPLTs OlTPLT LM1S: ENGLISH! ENGL) , METR1C(H£TR ), BOTH(BOTH
PPINT : DENOTES FRECLENCY OF OUTPUT; EACH INTERVALIIMTR) ,
EACH KtF(l-CUP), OK EACH OAY(bAYS),JR eACH MONTH(MNTH)
SNCW J (NO ShCkfELT NCT PcKFGAMEO, (Y£S) SNOhMELT CALC'S
PEST : (NO PESTICICES NOT PcRFJKMcO, (YES) PESTICIDE CALC
NL1R : (NO MTRIEMS NCT PERFURMED, (YfcS) NUTRIENT CALC'S
PERFORMED
•S PERFORMED
PERFCRMEC
IChECK: ChECKS ^ST CF THE INPUT IF SET EQUAL TO CN, OTHERWISE SET
203
-------
Appendix C (continued)
185.
186.
1£7.
166.
169.
190.
191.
192.
193.
194.
195.
196.
197.
196.
199.
200.
201.
202.
203.
204.
205.
2C6.
207.
2Cfi.
2C9.
210.
211.
212.
213.
214.
215.
216.
217.
218.
219.
220.
221.
222.
223.
224.
225.
226.
227.
228.
229.
230.
221.
232.
223.
234.
235.
236.
237.
236.
239.
240.
241.
242.
243.
244.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
INTRVL
HYMN
AREA
BGNCAY
ENCCAY
UZSN
LZS
L2SN
L2£
L
< t
NN
A
K2
EF>H
INFIL
INTER
IRC
K24L
KK24
K24EL
SGK
GVJ
KV
ICS
CFI
IFS
CMY IF
PACCCN
CCFAC
SCF
ELCIF
ICNJ
F
BGK
KC
KF*CK
EV/FSN
fELEV
1JNCW
PACK
DEPTH
PETKIN
FEUAX
PE1KUL
V.KL
PML
KLGI
CCVFKO
TIMIL
KR1IL:
SFERTL:
SZCPTH:
TC OFF
Tlf-E IMERV/L ( 5 OR 15 MINUTES)
MNIPUf FLCfc FCR OUTPUT DURING A TINE INTERVAL (CFS, CMS)
hAlERShEC /FEA (AC, HA)
BGNKCN, EGMP : DATE SIMULATION BEGINS
ENCKCN, ENCVF : DATE SIMULATION ENDS
NCCIFAl LPFER ZCNfc STORAGE (IN, MM)
INITIAL LFFEP ZCNb STORAGE (IN, MM)
NCMNAL LCVEP ZCNE STORAGE (IN, MM)
INITIAL LQVEP ZCNE STORAGE (IN, MM)
LENGTH CF CVERLAND FLCW TO CHANNEL (FT, K)
AVERAGE CVEPLANO FLOW SLOPE
f'ANMNC'S f FOR GVERLANO FLOW
FRACTICN CF 4RE/ THAT IS IMPERVIOUS
INCEX 1C /C1LAL EVAPORATION
^»XIfL^ INTERCEPTION STORAGE (IN, MM)
INFILTRiTICh RATE (IN/HR, MM/hR)
IKTERFLCk F/PAKETER, ALTERS RUNuFF TIMING
IMERFLCV FECESSION RATE
FPACTICN CF GPGUNOWATER RECHARGE PERCOLATING TO DEEP
GFCLNCVMEF
GPCCNChAIEF FECESSION RATE
FPfCTICN CF VATERSHEO AREA WHERE GRUUNDWATER IS WITHIN
REACH CF VECETATION
INITIAL GRCLNOWATER STORAGE (IN, MM)
GFCLNGtMEf SLOPE
PAF-APEIEF 1C ALLOW VARIABLE RECESSION RATE FCR GRCUNCHATER
CISChAFCE
INITIAL IMEPCEPTION STORAGE (IN, MM)
INITIAL CVERIANO FLOW STORAGE (IN, MM)
INITIAL IMEFFLCW STORAGE (IN, KM)
SNCW=YEJ SFCLLD PARAMETERS RAOCCN THROUGH KUGI BE INPUTTED
CCPRECTICN FACTCR FOR RAOIATICN
CCPRECTICN F*CTCR FOR CONDENSATION AND CONVECTION
SNCW CCPRECTICN FACTOR FOR RAiNGAGE CATCI- DEFICIENCY
ELEVAT1CN tIFFERfcNCc FROM TcMP. STATION TO MEAN SEGMENT ELEVATION
(1COC FT, KM
CENSIT> CF NEW SNOW AT 0 DEGREES F.
FRtCTICh CF SEGMENT WITH COMPLETE FOREST COVER
CAILY CPCIM>ELT (IN/DAY, KM/DAY)
MAXIfliK kAlEU CCNTEUT OF SNuMPACK BY WEIGHT
ESTIfATEC h/TER EQUIVALENT OF SNOWPACK FCR COMPLETE COVERAGE
CCPRECTICN FACTCR FOR SNCW cVAPCRATION
KE*N EIEVAT1CN CF WATERSHED (FT, M)
TE»>PEPATLRE BELOW KHiCH SNCta FALLS IF, C)
INITIAL kAlER EQUIVALENT OF SNuhPACK (IN, MM)
INITIAL CEFTK CF SNJtaPACK (IN, KM I
TEfFEP/TLRE «T WHICH ZERO PET OCCURS (F, C)
TEfPERMLRE AT WHICH PET IS RtLUCED BY 5C* (r, C)
PCTENTIAL EVAPCTRANSPIRATICN MULTIPLICATION FACTOR
V^INO t-LLTIFLlCATION FACTOR
R/CIATIcr »LLTIPLICATiCN FACTOR
INDEX 1C FCFEST DENSITY AND UNDERGROWTH (0.0-10.0)
PERCENTAGE CFOP COVER ON MONTHLY BASIS
TIKE (IN JLLIAN CAYS) WricN SOIL IS TILLEC
THE CCRRESFCNDING YEAR IN WHICH TIMTIL APPLIES
FINE CEFCSITS PRCDUCED BY TILLAGE (TONS/ACRE, TONNES/HECTARE)
SLRFACE LAYEF SOIL DEPTH (IN THE RANGE OF 1/8 INCH (IN, KM)
204
-------
Appendix C (continued)
245.
246.
247.
248.
249.
250.
2!1.
252.
253.
254.
255.
2 £6.
257.
256.
2£9.
260.
261.
262.
263.
264.
265.
266.
267.
268.
269.
270.
271.
272.
273.
274.
275.
276.
277.
278.
275.
2CO.
261.
262.
283.
264.
2£5.
286.
287.
268.
289.
290.
291.
292.
293.
294.
255.
296.
297.
296.
299.
300.
301.
302.
303.
304.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
UZCFTHI CEFTf (F SCR INCORPORATION AND UPPER ZONE (IN, MM)
6UKD : BL'IK DENSITY OF SOIL (LB/FT<3}|, (G/CM(3M
JRER * EXFCNE^ CF RAINFALL INTENSITY IN SOIL SPLASH EQUATION
KPER : COEFFICIENT IN SCIL SPLASH EUUATION
JSER : EXFCNENT Of CVERLANO FLOW IN SURFACE SCOUR ECUATICN
KSEP : CCEFFIC1ENT IN SURFACE SCOUR EuUATION
SPERI : IMTIAl FINES DEPOSIT (TONi/ACKE, TONNES/HECTAREI
CM.Y IF PEST=YES SI-CULD TITLE PcSTICIOc AND PARAMETERS APHOCE
UPCUGH DEC-CCN BE SPITTED
TITLE UCRC PESTICICE MUST BE INCLUDED IN THE INPUT
PBICR TO AKY PESTICICE INPUT PARAMETERS
AFPODE: APFLIC/TICr fOOEi SURFACE APPLIED (SURF),
SOIL INCORPORATED (SCIL)
DESORP: (hC) CrLY /CSOPPTION ALGORITHM USED, (YES)
ANC OESCRP1ICN LStO
SS1R PESTICICE /FFLICATION FOR EACH BLOCK (LB,
TII"«P TI*E CF fESTICIOE APPLICATION (JULIAN DAY)
SEQUENCE
BCTH ADSORPTION
KG)
YE*R*P TI-E CCFRESFC^DI^G YcAR IN WHICH TIMAP APPLIES
CMX MXIfLI> SCLtlBILITY CF PcSTICIOc IN WATER
(L6/LB)
CC PERMANENTLY FI>£0 CAPACITY (LB PESTICIDE/LB SOIL)
K CCEFIC]E^T IK FKEUNuLICH AOSORHTIUN CURVE
N EXFCNENT 11 FREUNLICH ADSORPTION CURVE
KP DESOPP1ICN EXFCNcNT IN FRcUNDLlCH CURVE
CEGCCN FIFST CPCEF PESTICIDE CECAY KATE (PER DAY)
PEAC
READ
REAC
REAC
READ
REAC
READ
READ
REAC
PEAC
PEAC
REAC
REAC
PEAC
RE /SO
REAC
READ
IF ^
REAC
REAC
REAC
READ
4GC REAC
READ
REAC
REAC
£,1096) (t^APEU),l*l,20)
5.1C9C) (Of>A*E{I),I=l,20)
5.1C57) h^CAL
5.1C9U IKFUT
5.1C5E) C11PLT
5,1C91) FRIN1
£,1C9S) !KU
5,IC9«) fEST
5,lC9
-------
Appendix C (continued)
305.
206.
307.
3C8.
309.
310.
211.
212.
•13.
214.
215.
216.
217.
218.
215.
220.
221.
222.
223.
224.
225.
326.
227.
328.
229.
330.
231.
232.
233.
334.
335.
336.
337.
338.
339.
340.
341.
242.
243.
344.
345.
346.
347.
348.
349.
350.
351.
•52.
353.
354.
255.
356.
351.
358.
359.
360.
361.
362.
363.
364.
IF (CHAO.EC.FES1IC) GO TO 401
WRITE (6,1122)
CC 10 1C6C
C
401 REAC (5.1CSU 4FK30E
REAC (5, 10S£) CESOPP
READ (5,APCU
REAC (5.CEG1)
C
C
C PPHTING OF INPUT PARAMETERS
C
402 IF (HYCAL.EC.CAIE) GC TO 1002
WRITE «,10«1)
IF (PES1.EQ.YES.AND.NUTR.EQ.NO) WRITE
IF (PEST. EC. NC .ANO.NUTR.cU.YES) WRITE
IF (PEST. EC. hC .ANO.NUTR.EQ.N01 WRITE
IF (PES1.EQ.YES.AND.NUTR.EQ.YES) WRITE
WRITE U.10S2)
GC TO 1C03
C
1002 WRITE U,10<3)
IF (PES1.EQ.YES.AND.NUTR.EQ.NO) WRITE
IF (PES1.EC.NC .AND.NUTR.EQ.YES* WRITE
IF (PEST.EC.NC .ANO.NUTR.EU.iMO) WRITE
WRITE «ilC*2>
IF (PEST. EC .KC .OR. NUTR.EQ.NO) GO TO
WRITE (6,1121)
GG TC icec
C
1003 WRITE (6,11C1) USNAMEU ), 1-1,20)
WRITE (6,11C6) (CI-NAME(I) ,1 = 1,20)
IF (1NPLT .EC. EltOL) WRITE (6,1108)
IF (INPIT .EC. KE1R) WRITc (6,1109)
IF (CUT PUT .EC. EKGL) WRITE (6,1110)
IF (OL1PLT .EC. CETR) WRITE (o,llll)
IF (CLTPLT .EC. ECTH) WRITE (6,1112)
IF (PRIM .EC. 1MR) WRITE (6,1113)
IF (PRINT .EC. KIR) WRITE (6,1114)
IF (PRIM .EC. COS) WRITE (6,1115)
IF (PRUT .EC. CMH) WRITE (6,1126)
IF (SNCV .EC. YES) WRITE (6,1116)
IF (SNCt .EC. NO WRITE (6,1117)
IF (PEJT .EC. NO GO TO 1010
IF (CESCPF .EC. YES) WRITE (6,1110)
IF (DESCRP .EC. K) WRITE (6,1119)
IF (AFKCE .EC. SCIl) WRITc (6,1105)
IF (AFfCCE .EC. URF) WRITE (6,1104)
101C WRITE U,1C*2)
C
WRITE (6,1164) 1MRVL,HYMIN,AREA
WRITE (6,1165) e<^DAY,BGNMUN.BGNYR
WRITE (6,1166) CKCOAY,ENDMON,ENOYR
WRITE (£,!!£-<) 12 JN ,US,LZSN, LZS
WRITE (6,1166) USS,NN,A,K3,EPXH
(6,1123)
(6,1124)
(6,1125)
(6,1126)
(6,1123)
(6,1124)
(6,1125)
1003
WRITE (6,1169) UFIL, INTER, IRC, K24L,KK24,K24EL
WRITE (6,1170)
-------
Appendix C (continued)
363.
366.
367.
368.
369.
370.
271.
372.
373.
374.
375.
376.
377.
376.
379.
3EO.
381.
362.
263.
364.
265.
286.
367.
368.
269.
390.
3S1.
292.
3S3.
(SSTR(I),1=1,51
C
C
C
WRITE (6,1173) MCK,DEPTH
WRITE (6,1174) FETMIN,PETMAX,PET«UL,WMUL,RMUL,KUG1
1011 fcRITE (6,1175) (CCVFHG(I),I»1,12)
WRITE <6,llE2)mmL(I>,I-l,5),(YRTlL(I),l=l,5)f (SRERTL (I), I'
WRITE (6,1176) SZCPTH.UZOPTH.BULKD
WRITE (6,1177) vFER,KRER,JS£R,KS£R,SR£RI
IF (PEST .EC. NO GC TO 1012
WRITE (6,11761 7HAP, YtARAP,
WRITE U,mS) CJ-/X,DD,K,N,WP
WRITE (6,1162) CECCON
1C12 WRITE (6,1120) MCA I,INPUT,OUTPUT,PR INT,SNOW,PEST,NUTR,ICKECK
IF (PEST.EG.YES) WRITE (6,1127) APMCOc.DESORP
WRITE U,1C<2)
IF ( INPLT .EC. fETR) GO TC 559
GO TC 449
CCKVERSICN OF METRIC INPUT DATA TO tNGLISH UNITS
559
l,5)
LZSN =
LZSN =
INFIL=
L =
Lzs^/^^'FJ^
L*3.2€l
LZJ/^^FI^
LZS
SGW
ICS
CFS
IPS »
EPXM =
UZCPTh=
- ICS/ffFI*
= CFS/KfFU
396.
397.
3*8.
399.
400.
401.
402.
4C3.
404.
4CS.
406.
407.
4C8.
409.
410.
411.
412.
413.
28326. = LMT CCNVERSIUN, CN(3)/FT(3)
eULKC = BULKC*2E228./454.
SRERI= SRER1/(HE1CPT*2.471I
CO 451 1=1,«
451 SREPTL(I) « 5PERTL(I)/(METOPT*2.471)
IF (SNCV .EC. NO GO TO 403
ELOIF r ELCIF43.2CI
fELEV f£LEV«2.Z€l
TSNCk - l.8*1SNCfr * 32.0
PACK « PACK/>MU
CEPTH - OEPTh/t'hFIN
F6TfAX« 1.8*FETMX + 32.0
= l.£«PETHK + 32.0
415.
416.
417.
418.
420.
422.
423.
424.
403 IF (PEST .EC. NO GO TO 449
DO 501 I=ltJ
501 SSTR(I) * S51F(I)*2.205
44S IEPRCR « 0
IF (ICMCK .EC. CFF) GO TO 452
CALL Ch£CKR fl-YMK, INTRVL ,UZSN,LZSN, 1RC,NN,L, SS,A,UZS,LZS,
1 K24L,KK24,K24EL,K3,SSTR,UZDPTH,
2 CH/>,BLLKD,ARcA,HYCAL,INPUT,OUTPLT,PRINT,PEST,
3
-------
Appendix C (continued)
425. 4 EGhYP,BGNMON,BGrtDAY,iERkOR,CAL6,PROD,
«26. 5 ENCl,PETR,bUTHtirtTK,HCUK,DAYS,MNTH,YES,NO,StlRFi
427. 6 SCIL.CN.OFH,SZOPTH,COVPKu,TIMTIL,RflDCCN,CCF*C,
428. 7 £CI,ELCIF,IUNS»F,DGK,hC,cV/APS>N,MELEV,TSNOV(,
429. 8 FElMN,PETKAX,PETMUL.fcf1UL,AMUL,KUGl,TIMAP,
430. S >EAPAP,DcGCUNtNUTR)
431. C
422. IF (IERROR .GT. Cl GG TO 1080
433. C
434. 452 IF (NLTP .EC. NO GO TO 4-50
435. CALL M.TFIC UOERR,INTRVL,NAPPL,SNAPL,UNAPL,TIMHARt
436. 1 INFLT,OUTPUT,APOAY,KNI,KPI)
437. IF (10EPF .EC. 1) tO TO 1080
438. C
439. C AC.LSTMENT OF CONSTANTS
440. C
441. 45C h = 60/1NTPU
442. TIMFAC - 1NTPVC
443. INTRVL " 24«l-
444>. C
445. KRER = KRER'M* UPER-l. )
446. KSER - KSER*M*(JSER-U)
447. C
448. P => BUlKD*(I2CFU/l2-0»*'»3560.*AReA*0.2
449. C INITIALIZE TEMP OIST VARIABLES
450. TEMPI - 35.
4J1. CHANGE » -12.
452. GRAC(l) * 0.04
453. GRACI2) > 0.C4
454). C
455. IPACK>0.01
456. C
457. JCOUNT * EGNC4Y
458. cc 601 I=l,eG^^c^
459. JCCIM * JCCINT + OPMMIUI
460. 601 CCNTIKUE
4£1. IF CFS
467. SRGXdl * IF*
4(6. 1005 CCNTIME
469. C
470. RESS1 * OFS
471. PESS « CFS
472. JCEP - 1CS
473. SCEP1 - ICS
474. SRGXT * IFS
475. SRGXT1 » IFS
476. SGhl - SGh
477. >K3 > K3
478. COVRMX « C.C
479. CC 1006 1-1*12
460. 1CC6 IF (CCtFPX.ll.CCVPMOmi COVRMX-COVPMOC11
481. C
482. IF (PEST .EC. KC) GC TO 1007
483. C
4£4. IIFLAG « 0
208
-------
Appendix C (continued)
1
465. IJFLAG « 0
4fi6. M * 1.0/N
4£7. MP * 1.0/NF
4€8. NCCf » MP/M
489. C
490. *U •= BUKO*MIZCFTH-SZOPTH)/12.0)
491. M. * BLIKC»6.C
4*2. *UZ = PU*43560.«;PEA*0.2
493. *LZ * H*4356C.* 12
515. IF (YEAR .EC. EGhYR) HNSTRT = 6GNHON
516. IF (YEAR .EC. ENCYR) MNEND ' EMJWON
517. C
518 C
£19. C EVAP, TE^Fd'AX-MN), KtC, AND HIND UATA INPUT
520. C
521. CC 1008 It * 1,31
522. ICCfi REAC (5,12£4) (IEVAP(MM,DA), MN *1 ,12)
523. C
524. C
525. IF (SKCW.EC.tO .«NC. NUTk.EO.NOi GC TO 610
526. CC 1013 C4 = 1,31
527. 1013 RE/0(£,12<5) ((1TEHP(MN,DA,IT ), IT=1,2),MN=1,12»
528. C
529. IF (SNCfc .EC. NO GO TO 610
530. DC 1C14 It * 1,31
£31. 1014 RE*C(5,1264) (IfcINCIHN,DA), HN=1,12)
532. C
533. 00 6CC CA =1,21
534. 600 RE4C (5,12«) (IRAC(MN, DA), MN~1,12)
535. C
536. CC 605 CA'1,31
537. 605 REAC (5,12*4) ( IOEW(MN,OA), MN«=1,12)
538. C
-39. 61C IF (INPUT .EC. ENGU GO TO 625
DC 7CC CA«1,31
DC 65C H*«l,12
IEV/F(K^,CA) ~ IEVAP(MN,OA)*3.937
IF (SNCfc.EC.YESI IaIND(Mfc,DA) = 1 MI NO(MN,OA)*0.621*
5*4. IF
-------
Appendix C (continued)
640
£47.
£48.
£49.
££0.
551.
££2.
£53.
£54.
555.
£56.
557.
559.
£60.
561.
562.
£<3.
564.
£(5.
566.
567.
568.
£69.
570.
£71.
572.
£73.
£74.
575.
£76.
577.
£78.
£79.
£60.
£61.
£E2.
583.
£64.
5€5.
£66.
5E7.
££8.
5E9.
59ll
£92.
£93.
£94.
£95.
596.
£97.
598.
599.
6CC.
601.
t02.
(C3.
6C4.
1
C£C
7CC
C
625 IF
C
C
C
C
C
C
C
C
C
C
8CO
C
1CC9
C
C
C
C
C
c
loie
1019
c
c
CC <4C IT«L,2
IP (StvCfc.EC.YES .OR. NUTR.EQ.YES)
ITE»P(KN,OA,m * l.o*ITcMP(MN,OA,ITI * 32.5
CCNTIM.E
CCKTIM.E
SAV THIN OF JAN 1 CN 11/31
(SNCfc.EC.YES .CR. NUTR.EQ.YeS) ITEMP(11,31 ,2) - ITEKP(1,1,2)
CO 1C60 KN1l--MMSTRTtMN£NO
BEGIN MONTHLY LOOP
CCVER1 « CCVPKCIMONTH1
IF (PCMH.LT.12) COVtRZ > COVPMOlMONTH+ll
IF (KMh.EC.12) COVER2 - CGVPMOU)
IF (t-YCAl .EC. PROD) GO TO 1009
IF (MTF.EC.YES) GO TO 800
VRITE (6,12(3)
VRITE «,2€2)
WRITE «,U<2)
€C 1C 1COS
NUTRIENT CALIBRATION OUTPUT FORMAT
WRITE U,4CC1>
IF (C17FL1.EQ.ENGL .OR. OUTPUT .cQ. BOTH)
IF (CITFUT .EQ. METR) riftlTE (6.4003)
WRITE (6,4002)
CNSTP1 - 1
CYEKC > DFKHCNTHJ
IF (KCC(YE ENOOAY
BEGIN DAILY LCOP
DC 1C5C t/Y-CYSTRT,OYENO
IF ((PCtTH .EQ. 1) .AND. (DAY .cQ. 1)) JCOUNT > 0
TII-E - C
RAIM » C.C
EP * PETMJL*ltVAP(MJNTH,OAY)/lOOO.
IF (SKCV.EC.NO .AND. NUTR.£Q»NU) GO TO 1018
TE*F « (ITECP(MONTHfDAY,l)+ITEMP(MONTHfOAYt2) I*. 5
IF (SNCV .EC. NO) GO TO lOltt
ViUC > IUND (MOUTH, DAY)
DEV> - ICEK(MONTHtDAY)
CC 1CI? I«1,I.
-------
Appendix C (continued)
£05.
606.
607.
tee.
£09.
£10.
<11.
£12.
£13.
£14.
£15.
£16.
£17.
£18.
£19.
£20.
£21.
£22.
£23.
£24.
£25.
£26.
£27.
£26.
£29.
630.
£21.
£32.
£33.
£34.
£35.
£36.
£37.
£38.
£39.
£40.
£41.
£42.
£43.
£44.
£45.
£46.
£47.
£46.
£49.
££0.
£51.
£52.
£53.
£54.
£55.
£56.
£57.
£58.
£5S.
££0.
£61.
££2.
£63.
£€4.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
sec
910
S25
940
945
941
946
949
950
951
CFI
CHECK 1C J6E IF SNOHMELT CALC'S WILL BE DONE - IF YES THEN
CALCLLATE CCNTINUOUS TEMP, WIND, RAO ANC APPLY CCRPES MULT
FACTCfS
IF (SNCK .EC. NO GO TO 949
hINF=(1.0-F) « F«(.35-.03*KUGI)
HINF REDUCES WIM) FCR FORESTED AREAS
/* KLGI IS UDEX TO UNDERGROWTH ANU FOREST DENSITY,*/
/* WITH VALLES 0 TO 10 - HI*0 IN FOREST IS 35* OF */
/* MftC IN CFEN WHEN KUGI=0, ANC 5% WHEN KUGI«=10 - */
/* V.INC IS aSSLA'EO MEASURED AT l-a FT ABCVE GROUND */
/•» OB JNCW SLRFACE */
TMIN = ITEKF(KMH,DAY,2)
CEfcX » CEkX - l.C*ELDIF
DEhPT LSES A LAPSE RATE OF 1 DEGREE/1000 FT
IF ((PACK .IE. C.C).AND.(TMIN .GT. PETMAX)J GO TO
CALCLLATE CCMIKCUS TEMP, WIND, AND RAD
TGRAC * 0.0
P •
CO
IF ( 1-7) <40, C.CO, 910
CHANGE = ITEMF^CNTH.DAY,!) - TEMPI
IF (I.NE.171 CC TC 940
IMDEND IS LAST DAY OF PRESENT MONTH
IF (CAY .N£. IPCENC) CHANGE =IT£MP(MONTH,OAY+1,2) -
IF (fCNTh.NE.12) GO TO 925
IF (CAY .EC. ^CENC) CHANGE * ITcMP(11,31,2) - TEMPI
GO TO 940
IF (CAY .EC. I>CEKD» CHANGE ' lTcMP(MONTH+l,1,2) - TEPPI
IF (AESKHAtGEl.GTtO.OOl) GO TO 945
TGRAC * 0.0
GO TC 947
TGRAC * GF/CUXCHANGE
TEMPMI) • TE^FI * TGRAO
hlNCX(I) - Vt^LL*WIND*HINF*MINOIS( I)
RAC(I) * RCLL*F*RADCON*RADDIS(II
TEHPI * TEh-PI * TGRAO
CCNTINLE
CHECK OF TILLAGE TIfE
JCCLNT » JCCUNT + I
CC 951 1*1,5
IF (JCCUNT.NE.TIMTIL(I) .OR. YEAR ,NE.(YRTIL(11+1900) 1
1 GG TO 951
URITE (6,10«2) MNAM(MONTH), DAY, TIKTIL(I), SRERTL(I)
CC 550 J*l,5
SFER(J) = SRERTL(I)
CCMIKUE
COT1MC
CFCP CANCFY EFFECTS - ASSUMES LINEAR CHANGE BETWEEN MONTHLY VALUES
COVER
1
CCVEB1 « (1.0 - (FLOAT(OYENO*1-UAY)/FLCAT(DYENCJ)I*
(CCVEP2-CCVERI)
211
-------
Appendix C (continued)
(£5. C
666. IF (NUTfl .EC. NU GO TO 1020
(67. C
(66. C NUTRIENT DAILY CALCULATICNS.
(69. C
670. C FILL IN SOIL TEMP ARRAY WITH AVG. AIR TEKP
671. C
(72. CC £10 JHClP»lf24
673. DC CCS IZCM»lt4
674. SIEtPUZCKEtJt-QUR) * TEMP
(75. 8C5 CCN1INLE
676. 810 CONTINUE
(77. C
678. C TEST FOR APPLICATION OF FERTILIZERS
675. C
6CO. 615 IF (APLCKT .GT. MPPL) GO TO 860
681. IF (APCAY(AFLCNl) .GE. JCCUNT) GO TO 820
6£2. APLCNT = AFLCM * 1
(£3. GO 1C 615
(£4. 820 IF (JCCINT .NE. 4FOAYUPLCNT) ) GO TC b60
(£5. C
666. C ADD NUTRIENT APPLICATIONS TO STORAGES
667. C AND INCREMENT MASS TOTALS IK SYSTEf
(£8. C
(£9. CO €30 ieLK=l,«
(90. CC 625 ,1*1,2C
691. SMJtlGLK) - SNUtlBLK) * SNAPL( J, iBLK, APLCNT )
692. LN(JtlBLK) = UNUtlBLK) * UNAPLU, IBLK, APLCNT»
693. £25 CCNTINLE
694. 820 CCNTINLE
(95. C
696. CO £40 J*l,7
697. SUM " 0.0
69£. DC £25 IEIK>1,5
(99. SIP * SIP + SNAPLUtlELK, APLCNT) * UNAPLUt IBLK, APLCNT )
700. 835 CONTINUE
701. TKA = TN< « UF/5.
702. 640 CCNTINLE
703. CC 850 J=ll,14
704. SLH » O.C
70S. CC £45 IELK»1*5
706. SLP = SL>> •» SNAPLUtlBLKt APLCNT) * UN APLI J, IBLK, APLCNT )
707. 845 CCMINLE
7C8. TPA * TF/ * JL*/5.
7C9. 65C CCNTINLE
710. SUP « C.O
711. CC £55 ieil"l,*
712. SLM * SL» + Sh*PL(20iIBLK,APLCNT) «• UNAPL(20, IBLK,APLCNT)
713. £55 CCNTINLE
714. TCLA » TCLA * St>/5.
715. C
716. hRITE (6.4CC5) *FICNT, MNAMtMONTH), DAY, JCOUNT
i!7. APLCNT « APlC^^ « 1
718. C
719. £60 IF IJCCLNT .NE. T1MHAR) GO TO 881
720. C
721. C CCMPUTE AMOUNT HARVESTED AND CECREASE STORAGES
722. C
723. CO £70 J*l,20
724. TNRhV(J) =• 0.0
212
-------
Appendix C (continued)
125.
726.
127.
720.
729.
130.
131.
132.
133.
134.
135.
136.
137.
738.
139.
140.
141.
142.
143.
144.
145.
146.
147.
146.
149.
150.
151.
752.
153.
754.
755.
156.
157.
158.
159.
ICO.
lei.
162.
163.
164.
765.
166.
767.
168.
l«.
170.
171.
772.
773.
174.
775.
176.
777.
778.
779.
7£0.
162!
1£3.
164.
665
£70
C
C
C
C
C
C
861
8£2
883
££4
C
££5
C
C
C
C
1C2C
7C6
7CE
1C21
1022
C
C
1023
IF (£ELhV(.) .EQ. 0) GO TO 870
SU* * O.C
00 tt5 ICLK'1,5
SLH » C.O
TNRHVMU) > 1NPHVMJ) * INRHV(J)
CCNTINIE
kRITE (6.40C6) I^AMMONTHI, DAY
CC ££4 IZCNE»lt4
CC £62 »»ltlC
KN(J, IZCNE)
CCNTINCE
DC £€3 J»l,5
KF(JtI2CNE)
CONTINUE
CCNTIME
TRANSFER INPUT REACTION RATES (KNI.KPII INTO
REACTION RATES IN COMMON /NUT/ (KN.KP)
PLANT UPTAKE fcATcS ARE INPUT FOR 100« COVERt
RATES DECREASED LINEARLY FOR COVER < 1001.
KNHJ.IZONE)
KPI(J.IZONE)
oo ees
KN(£»IZCNEI * KN(5»IZONE1*COVER
KF(3TIZCNE) * KP(3,IZONE»*COV£R
CONTINUE
PRcCIP READ L.OOP
00 1021 J*lt8
JK « J«1EC/TIKFAC
J4 » JK - 16C/TIMFAC * 1
IF (TIfFAC.EC.5) READ (5,1095* YR.MO,OY,CN.(IPAINIII,I-JJtJK»
IF (TIfF4C.EC.15) REAi) (5, 10«<*> YR»MO, OY,CN. (IRAIN( I) ,I*JJ,JK)
IF «YR+19CO).LE.BGNYR .AND. MO.LE.bGNMON .AND. DY.UT.BGNOAY)
I GC TC 1020
IF UNFtT.EC.ENGU GO TO 706
OC K6 I«JJ,JK
IPAINdJ - IRAIN(I)*3.937 * 0.5
CCNTINtE
JJJ « J
YR » YP * 19CC
IF (CN.EC.SI ^JJ * 9
IT * (YE*P-YP) * (MONTH-MO) + (CAY-OY) * (JJJ-CN)
IF (IT.NE.C) CC TO 1022
IF (CN.EC.S) CC TO 1025
CCNTIME
GO TC 1C22
fcRITE UtlCtO) »JJ,KNTH,OAY,YEAR,CN,MO,DY,YR
GO TO 1C80
CC 1024 I«1,INTRVL
213
-------
Appendix C (continued)
145.
166.
787.
788.
789.
790.
1S1.
7S2.
193.
794.
795.
196.
797.
198.
799.
£00.
£01.
£02.
£03.
EC4.
ECS.
£C6.
€C7.
808.
£09.
CIO.
Ell.
£12.
£13.
£14.
£15.
£16.
€17.
£18.
£19.
£20.
821.
£22.
£23.
£24.
£25.
£26.
£27.
£28.
£29.
£30.
£21.
£32.
£23.
C34.
£35.
836.
£37.
£38.
£39.
£40.
£41.
€42.
£43.
£44.
C
C
C
C
C
C
C
C
C
C
C
C
1024
USE
1025
1026
1028
1C29
1030
C
C
1031
1033
1034
C
1035
]
1C37
FMMI) f IRAINID/100.
R/IM = RAINT + RAIN(I)
CCNTINUE
IF (RA1M.GT.O.O) 60 TO 1026
RAIN LCCP IF PCUTURE STORAGES ARE NOT EHPTY
IF ((REJS. IT. 0. COD. AND. (SRGXT.LT. 0.001)) GO TO 1040
FAIN LCOP
CC 1C3< I=1,INTRVL
TIME « TIME * 1
TF « 1
PR - PAIN(I)
1UI * POD(TIME,H)
IhP - (TIME - IHIN)/H
IMf » TIMFAC*IMIN
FFNTKE = 0
IF (PRINT.EQ.HOUR) GO TO 1028
IF (FPINT.EQ.DAYS) GO TO 1029
IF (FFINT.EQ.HNTH) PRNTKE * 2
IF (FPINT.EQ.INTR) PRNTKE - 1
CC TC 1030
IF (IPIN .LT. 1) PRNTKE - 1
CC TO 1030
IF (IHR .EQ. 24) PRNTKE - 1
IF (FPNTKE .NE. 1) GO TO 1031
IF (t-YCAL .EQ. CALB) GO TO 1031
WRITE (6,1101)
VFI1E (6,1102)
WRITE (6,11031
IHR, IMIN, OAy,HKAf(MCNTH)
CALL LANDS
IF URESS .GE. 0.001).OR.(PR .GT. 0.0011)
CC 1C33 J«l,5
EFSN(J) = 0.0
CCNTINUE
IF (FFNTXE .EQ. 0) GO TO 1035
CALL
-------
Appendix C (continued)
£45.
£46.
£47.
£48.
£49.
£50.
£51.
£52.
££3.
£54.
£55.
£56.
£«7.
£58.
£59.
£60.
£61.
£62.
£63.
£64.
€65.
£66.
£67.
£68.
669.
£70.
£71.
£72.
£73.
€74.
£75.
£76.
£77.
£76.
679.
680.
£81.
£82.
£63.
£84.
£€5.
886.
£87.
£88.
€69.
€90.
891.
692.
£93.
£94.
£95.
696.
£97.
698.
899.
900.
SOI.
902.
SC3.
9C4.
1C36
971
C
C
1036
C
C
C
C
1C4C
1042
1C43
1041
10E1
C METRIC
1163
1044
CC TC 971
CtLl CEGRAD
IF (M.TF .EQ. NO) GO TO 1036
C/LL MJTRNT
CCN1IMJE
GC TC 1C50
NC FAIN LOOP
TF IMFVL
PR - O.C
F3 O.C
CC 10*2 I»l,5
FESE1U) = 0.0
FRMKE * 1
IF (FR1M.EQ.MNTH) PRNTKE « 2
ICIK - CC
I»-P « 24
IF O-VC4L.EQ.CALB .OR. PRNTK£.EU.i) GO TO 1043
WRITE (£,1101) IHR, IMINi DAY, MNAM(MONTH), YE«R
hRITE Utll02J
ViRITE «t!103)
CALL LA^CS
SRJRT = 0.0
£R£rT « C.O
CC 1C41 J=l,5
SPEFT = SRERT
ERSr(J) = 0.0
CCKTIMIE
IF (HYC/L.EC.CAL6
IF (ClIPll.EC. MtfTR)
WRITE (6,1209)
VRITE «,1210) ERSN, ERSNT
hRJTE (6,1211) SRER, SRERT
IF (CimT.tC. cNtL) GC TG 1044
CChVEPSI^S fCR COTPUT
ERJNTT«EPSM*M£TOPT*2.471
SRP1M*JFEPT*METOPT*2.471
CC 116- 1=1,5
EFSM-TU )=ERSMI)*METCiPT*2.47l
JPEP^T(I)=SRER
-------
Appendix C (continued)
905.
9C6.
SC7.
SC8.
S09.
910.
911.
S12.
913.
914.
915.
S16.
917.
918.
919.
920.
921.
922.
923.
924.
925.
926.
927.
928.
929.
920.
931.
€39
«3£*
933.
934.
935.
936.
937.
938.
939.
940.
941.
942.
943.
944.
945.
946.
947.
948.
949.
950.
951.
952.
953.
954.
955.
956.
957.
958.
959.
S6C.
961.
962.
963.
964.
CALL CECFAC
S7i
IF
(M1F .EC. NO GO TO 1050
CALL M1FNT
C
C
C
C
105C
END DAILY LOOP
CCMINLE
MCMHLY SUMMARY
CALL CLTfQN (YEAR)
C
C
C
C
C
1C6C
END MONTHLY LOOP
CCNTIHE
YE /FLY SUMMARY
CALL CUYR (YEAR)
C
AFLCNT
C
C
C
C
C
107C
10EG
1C9C
*
1C82
1
1
1C91
1C 9.2
1C93
1C94
1C95
1096
1C 91
1C98
1C9S
11CC
1101
1102
1102
« 1
END YEARLY LOOP
CCNTIMJE
WRITE (6
FORMAT (
,12£C)
•1',
•CARC ',1
FORMAT CO',
FCFf-AT STATEMENTS
i4*4*4£Rj)Ci<***** INCORRECT INPUT DATA DESIRED '
1,' FCR 'tI2»'/*t UtVSI^t1; RtAC CARD -,Il,' FOR ',
•ULLAGE CF THE SOIL OCCURS ON' , IX, A8 ,IX, I 2, 2X»
MTIMIL*' t!3,' ), RESULTING IN A NcH FINES DEPOSIT ;,
•STCFAGE CF'fF6.3,' TONS/ACRE')
FCRMAT (•!' ,25X, 'THIS IS A PRODUCT ION RUN* )
FCRMAT (
FCPMAT (
• 0')
• 1' ,<«X,'THIS IS A CALIBRATION RUN1)
FCRMAT (IX, 312,11*1216)
FCRMAT 1
IX, 2
12,11,3612)
FCRMAT (20A4)
FCRMAT (6X,*4)
FORMAT (7X./4)
FCRMAT (5X./4)
FCRMAT (AC)
FCRMAT
FCRMAT
FCRMAT
C 5X,'T
1104
110*
lice
11C1
lice
lies
1110
1111
1112
1113
1114
111£
1126
1116
1117
FCRMAT
FCRM/T
FCRMAT
FORMAT
FCRMAT
FORMAT
FCRMAT
FORMAT
FORMAT
FORMAT
FORMAT
FORMAT
FORMAT
FORMAT
•1',2SX,1Z,' :'iI2t- ON • ,1 2, 1X,A8 , 1X.I4)
•+' .25X.' ,_ _ „ , ' )
•0«,24X,'eLCCK 1 BLOCK 2 BLOCK 3 BLCCK 4 BLOCK 5*
TAL')
•0'
• 0'
•0'
•0'
•C'
•C'
'0'
«o«
•C'
• o«
•C'
•0'
'0'
• C'
FCRMAT CO'
22X, 'PESTICIDE APPLICATION: SURFACE-APPLIED')
22X, 'PESTICIDE APPLICATION: SOIL-INCCRPCRATEO* )
22X, 'CHEMICAL: '.20A4)
22X,'VATEkSHED: ; *20A4)
22X, 'INPUT UNITS: ENGLISH')
22Xt'INFlT UNITS: METRIC1)
22X,'CliTPUT UNITS: ENGLISH')
22Xt'CUTPUT UNITS: METRIC')
22X,'CLTPUT UNITS: BCTH cNGLISH AND METRIC*)
22x»'FRiNT INTERVAL: EACH INTERVAL')
22X,'PPINT INTERVAL: EACH HOUR*)
•2x, 'PRINT INTERVAL: EACH DAY*)
22x, 'PRINT INTERVAL: EACH MONTH*)
22X,'JNCKMtLT CALCULATIONS PERFORPEC*)
22Xt'SNCbKELT NOT PERFORMED')
216
-------
Appendix C (continued)
965.
966.
967.
966.
969.
970.
971.
972.
973.
974.
975.
976.
577.
978.
979.
9£0.
981.
982.
9£3.
9£4.
9E5.
9 86,
987.
see.
989.
990.
991.
992.
993.
994.
995.
996.
997.
998.
999.
1000.
1C01.
10Q2.
1003.
1004.
1005.
1006.
1CC7.
1C08.
1C09.
1010.
1011.
1012.
1C 13.
1014.
1015.
1016.
1017.
1018.
1019.
1020.
1021.
1022.
1023.
1024.
1118 FCRPAT ('0',22>,'*DSCRPTION AND OESORPTION ALGORITHMS USED*)
1119 FCRMAT CO' ,22X,'ADSORPTION CALCuLATfcl) ONLY , NO DESOftPTICN')
112C FCRMAT CO' ,/'0 ' , «HYCAL=' ,A4, 2X , • INPUT=« , A4 , 2X, 'OUTPUT* • ,A4,
2X,
1121
1122
1123
1124
1126
1127
1164
1165
1166
1167
1166
1169
U7C
1171
1172
1173
1174
11 <£
1176
1177
1178
1179
1182
1183
362
12CE
12C9
1210
1211
126C
1263
l'PRINT = ',A4,2>, '= ' ,F8.4, 10X, »GvJS=
l'ICS= «,F8.<,1C>,'CFS= ',F8.4,10X,
>,8X,'AREA> *,F10.4)
•,12,13X,'BGNYR= ',14)
•,I2,13X,'ENDYR= ',14)
•,Fb.4,10X,'LZSN» ',F8,4,
N= ',F8.4,11X,
•,F8.4,eX,«IRC= '.F8.4.10X,
1,F8.4)
.4,iOX,'KV= ',F8.4,11X,
•IFS= •,F8.4)
FCRMAT CO*
1F8.4,1C>,'ELCIF=
FCRMAT (•0•,•CC^
l'EVAFSh= ' »FE.4f'
^ • ,F d.4, 7X, 'CLFAC=
,F8.4,dX , • I DNS= ' , F8 .
' ,F8.*,10X, • WC= ' ,H6.
f 'MtLEV= • , F8.0, 8X , • TSNOH
,F8. 4, 8X, • SCF=
F= ',F8.4)
• PPACK= '.FS
-,F8.4)
•,F8.4,7X,'BULKD= ',F8.4)
.4,9X,'JSER= ',F8.4,9X,
1265
1264
4CC1
FORMAT CC'i'FACM ' ,Fo.4 ,9X, • DEPTh= ',Ftt.4)
CO','FETHN= ',Ftt.4,7X,'PETMAX= ' ,Fb. 4,7X , ' PETCUL
1= :,FE.4,9X,'RMUL= •,Fb.4,9X ,'KUG1- «,F8.4)
FCRMAT {'C',/'0',«CCVPMO= '. !<:(Ft.2t2X) )
FORMAT {'0','SZCFTH= ',F8.4,7X,
FORMAT ('0','JREF= • ,F6.4 ,9X,•KRER
l'KSER= ',F£.4,9>,'SRERI= «,f8.4)
FCRMAT CO',/'0« ,'TIKAP= • , 18 ,8X,'Yt ARAP= ',I8,7X,
1 '<£TP» •,5(F6.3,3X))
FORMAT C'0«,'CM/>» ' ,Ffa.6 ,9X, '00= ',Fd.6,UX,
l'K= ',F8.4,12X,'h= • ,F8.4,12X,'NP= ' ,F8.4)
FCRMAT '0'.'CE(CCN= •,Fb.6)
FORMAT '0',MIM1L= ; ,5 ( 13 ,2X) , 4X, • YRTIL* • , 5( 12 »2X) , 4X ,
1 «JREFTL= i,i(F6.3,2X))
FORMAT • ',£7X,'VATER',24X,'SEDIMENT')
FCRM.AT '0', EXt'SEOIffci-IT , TONS/ACRE')
FCRKAT • • ,11X,'ERCDED SEDIMENT • ,5(3X,F7.3),4X,F7.3 )
FCRMAT • ' ,11X, 'FINES DEPOSIT' ,oX,5 (3X,»-7 . 3) ,4X,F7. 3)
FCRMAT '1','ENC CF SIMULATION')
FCRMAT •!• I£X,'C*TE',4X,'TIME',4X,'FLUH(CFS-CMS)',6X,
i •SECI^E^^ (LBS-KG-KG/MIN-GM/L)',23Xf
i 'PESTICIIE (Gf-OM/MIN-PPM)')
FCRKAT (8X.24I3)
FCRMAT (8Xt12I6)
FCRMAT (•!',40X,'I' ,10X,'DISSOLVED IN WATER' , 11X ,'I ' ,
1 6X,'ACSCFEEC TO SEDIMENT',iX ,'I',/,
! • ',4X,«CATE»,6X,'TIME',7X,'FLOW SEDIMENT1,
,5X,'NH3' OX,'P04' ,6X,«CL'.
,3X,«ORG-P',6X,
,F8.4f
217
-------
Appendix C (continued)
102$.
1026.
LC27.
1028.
1C2-5.
1030.
1C31.
1032.
1033.
IC24.
1C35.
1C36.
12CO.
1201.
12C2.
1203.
12C4.
1205.
1204.
1207.
1208.
1209.
1210.
1211.
1212.
1213.
1214.
1215.
1216.
1217.
1218.
1219.
1220.
1221.
1222.
1223.
1224.
1225.
1226.
1227.
1228.
1229.
1230.
1231.
1232.
1233.
1234.
1235.
1236.
1231.
1238.
1239.
1240.
1241.
1242.
1243.
1244.
1245.
124t.
1247.
•TC1-M ,2>,'TCT-P'I
4002
4C03
4CC4
4005
4C06
C
C
C
C
C
FORNAT
1
FORMAT
1
FCRMAT
FORMAT
1
FCRMAT
HOP
END
('
4X,
( •
4X,
('
CO
,
(
24>,'
16)')
,24>,'
(
t
,
*G)')
40>,5
(CFS)
(CMS)
(2X,«
•NLTPIENT
Afi,2»,I2,
CO',
',
'.
5X,«
5X,'
(HG/L)
(LB)'
(KG)'
') ,4(
APPLICATION
• (DAY
•PLANT HARVE
= i
t!3,'
,2X,
9(4X,
,2X,9UX,
3X,»
MC.
)• )
STING OCCURS
(PPM)
•»12
ON • ,
MLB)' ),7X,ML8)«,
MKG)«),7X,' (KG)f,
') I
,' OCCURS ON ',
A8,1X,I2)
SUBROUTINE ChECKP
1
2
3
4
5
£
7
€
O-YMIN,INTRVL,UZSN,LZSN,IRC,NN,L,SS,A,UZS.LZS,
K24L,KK24,K24EL,K3,SSTR,bZDPTH,
CMAX,BULKO,ARcA,HYCAL>INPUT,OUTPUT,PR INT,PEST,
SNCw,APMOUc,OtSCKP,ICHECK.,ENCYR,ENOMCh,ENOCAY,
eCNYfi.,BGNMJu.BGNuAY,I£RKURtCALfl,PROD,
ENGL,METR,BOTH,INTR,HOUR,DAYS,MNTH,YES,NO,SURF,
SOlL,ON,OFF,S/UPTH,CdVPMO,TIMTIL,RAOCCN,CCFAC,
SCFfELDIF,IONS,F,DGH,WC,kVAPSNtMELEVtTSNOH,
PETMIN,PcTMAX,PcIKJL,HMUL,PHUL,KUGI,TIMAP,
YEAKAP,DcGCON,NUTR)
DIKENSICN S3TR(£),CCVPHO(12),TIMTIL(5)
PEAL LZSN.IFC,^ tL,lZS,K24U,KK2<»,K24EL,K3
PEAL ICNS,fELEV,KUGI
INTEGER hYCAl , ItFLT ,CUTPUT ,PRI NT,SNCrt,APMODE tOESORP, ICt-ECK
INTEGER ENCYR,E^C^'C^,El^OOAY,6GNYR,BGNMUN,BGNDAY, FEST
INTEGEP CAL6,FFCC,ENGL.METR,BOTH,iNTR.HOUK,DAYS,YES,NO
INTEGER SLRF IEFFQR + 1
15C4 IF (NN .LE. 1.0) CC TC 1505
ViRITE U.UC4) NN
IEFRCR = IEFFOF * 1
1505 IF (L .C-T. l.C) CC TC 1506
fcRITE «,HC5) L
IEFRCP > IEFFCR + 1
1506 IF
-------
Appendix C (continued)
1248.
1249.
1250.
1251.
1252.
1253.
1254.
1215.
1256.
1257.
1258.
1259.
1260.
1261.
1262.
1263.
1264.
1265.
1266.
1267.
1266.
1269.
1270.
1271.
1272.
1273.
1274.
1275.
1276.
1277.
1276.
1279.
1280.
1261.
1282.
1283.
1264.
1285.
1286.
1287.
1288.
1289.
1290.
1291.
1292.
1293.
1294.
1295.
1296.
1297.
1298.
1299.
1300.
1301.
13C2.
1303.
1304.
1305.
1306.
12C7.
isoe
15C9
151C
1511
1512
1513
1514
1515
1516
1526
1516
1519
152C
1521
1522
1523
1524
152J
152?
IF
IF
IF
IF
IF
IF
IF
CC
IF
IEPRCR * IEFFOR * 1
(LZS .LT. LZS) GC TO 1509
WRITE (6.KC8)
IEFRCR * IEFFOR * 1
(K24L .LE. l.C) GC TO 1510
WRITE (6,UCS) K24L
IEFRCR * IEFFOR * 1
(KK24 .LE. l.C) GC TO 1511
WRITE (6, UK) KK24
IEFRCR * IEFFOP + 1
(K24EL .LE. l.C) GO TO 1512
WRITE (6,1611) K24EL
IEPRCR = IEFFCR * 1
(K3 .LE. 1.0) GO TC 1513
VPITE (6,1612) K3
IEPRCR » IEFPOR + 1
(LZCPTI- .Gl. SZDPTh) GO TO 1514
WRITE (6,1613)
IEPRCR = IEFFOR * 1
(SZCFTh .LT. 1.0) GO TO 1515
WRITE (6,1614) SZOPTH
IERRCR= IEFPCR * 1
1516 1=1,12
(CCVFPC(I) .LE. 1.0) GO TO 1516
WRITE (6,124
WRITE (6,1623) PRINT
IEFRCP = IEFFOR + 1
(SNCW .EC. YES .OR. iNOW .EQ. NO) GO TO 1525
WRITE (6,1624) SNOri
IERRCR 1EFROR * 1
(SNCW .EC. NO GO TO 1550
(FACCCN .CT. C.O) GO TO 1529
WRITE (6,162E) RADCON
IEFRCR* IEFFCR * I
(CCFAC .GT. C.C) GC TO 1530
219
-------
Appendix C (continued)
12C8.
12CS.
1310.
1211.
1212.
1213.
1214.
1215.
1216.
1217.
1218.
1219.
1220.
1221.
1222.
1323.
1224.
1225.
1326.
1221.
1228.
132-5.
1230.
1331.
1222.
1333.
1234.
1225.
1336.
1337.
1336.
1339.
1240.
1241.
1242.
1243.
1344.
1345.
1246.
1347.
124£.
1349.
1350.
1351.
1352.
1353.
1254.
1355.
1256.
1357.
1258.
1359.
1260.
1261.
1362.
1263.
1364.
1365.
1266.
1367.
1530 IF
1521 IF
1532 IF
1533 IF
1534 IF
1525 IF
1536 IF
1537 IF
1536 IF
153« IF
154C IF
1541 IF
1542 IF
1543 IF
1544 IF
1550 IF
1551 IF
IF
1553 IF
1554 CO
IF
WPITE (6.U2S) CCFAC
IEPRCR* IEFFCR + 1
(SCF .GT. C.C) GC 10 1531
WRITE (6,16201 SCF
IEPRCR= 1EPFCR + I
(ELC1F .LT. 20.0) GO TO 1532
WRITE U.U21) ELD IF
IERRCR= IEPFCR * I
(ICf>S .LI. 1.0) GC TO 1533
WRITE U.K22) IONS
IEFPCR* 1EFFCR * 1
(F .IE. 1.0) GO TC 1534
WRITE UiU23) F
IEFRCP= IEFFCR * I
(CGK .LT. l.C) GG TO 1535
WRITE (6,1(24) OGM
IEFRCP' IEFFCR + 1
(WC .LT. 1.0) GO TC 1536
WRITE (t,U2i) UC
IEPRCR* IEFPCR * 1
(EVAPSN .€1. C.O) GO TO 1537
WPITE It,1(26} EVAPSN
IEFRCR" IEFFCR * 1
(PELEV .LI. 3CCOO.O) GO TO 1538
WRITE U,U37) I-ELEV
IERROR* IEPFCR
(TSNCW .CT. 20.0
WRITE (6,U26)
IEPPCF= IEFFCR
(PETMN
WRITE
+ 1
.AND
TSNOM
* 1
.GT. 3C.O) GO TO
U.U2S) PETHIN
TSNOH .LT. 40.U) GO TO 1539
1540
IEPPCP= IEFFCR + I
(PETKA> .LI. 6C.O) GO TO 1541
WRITE U.U4C) PETMAX
IEPRCP= IEFFCR + 1
(PETt'LL .Gl. C.O) GO TO 1542
WRITE UtU41) PETMUL
IEFPCP* IEFFCR » 1
(WKCL .G1. 0-C) GO TO 1543
WPITE (6,H42) rtMUL
IEPRQR* IEFFCR + 1
(RHLL .Gl. O.C) GC TO 1544
WRITE (£,1£43) RMUL
IEPRCP= IEPFCR * 1
(KUGI .GE. O.C .«NO. KUGI .Lt. 10.0) GO TO 1550
WRITE ES .CR. OESORP .EQ. NO) GO TC 1554
WPITE U,l£*3) OtSOKP
IERRCR = IEFPCR * 1
1555 1=1,5
(SSTR(I) .CT. 0.0) GO TO 1555
WRITE U,l<*4)
220
-------
Appendix C (continued)
1366. IEPRCR * MFFCP * 1
1369. 1SJJ CONTIME
1370. IF (CMX .LE. 1.0) GC TO 1557
1271. WRITE (6,U«6) CMAX
1372. IEPRCR = IEFFOR + 1
1373. 1557 IF (TlftP .GT. C .AND. TIMAP .LT. 367) GO TO 1558
1374. hRITE U.H57) TIHAP
1275. IEPRCP* 1EFFCR «• I
1276. 1556 IF OEARAP + 1SCC .GE. dGNYR .ANC. YcARAP * 1900 .LE. ENCYR)
1377. 1 GC 7C 15S9
1276. kRITE (6,1«!€)
1379. IEPRCR- IEFFCR * 1
1360. 155S IF (CEGCCN .LI. 1.0) GO TO 1565
1381. kRITE (6,1659) OEGCON
1362. IEPROR= 1EFFCR + 1
1383. 156J IF CMJTF .EC. YES .CR. NUTR .EQ. NU GO TO 1560
1284. KRITE (6,16<5) NUTR
1385. IEFPCP* IEFFCR .«• 1
13£6. 158C IF (ICHECK .EC. CM GC TO 1581
1387. V.RITE U,U€C) 1C HECK
1288. IERRCR - IEFFOP * 1
1289. 1561 IF (ENOR .CT. EGNYR) GO TO 15S2
1390. IF (ENOR .EC. CCNYR .AND. ENDMON .&T. UGNMGN) GO TO 1582
1291. IF (ENCYR .EC. EGKYR .AND. ENOMON .£C. BGNMON .AND. ENCOAY
1392. 1 .CE. EC^AYJ GO TO 1532
1393. UPITE (6,U61)
1294. IEPRCP = IEFPOP * 1
1295. 1582 IF (IEPPCR .GT. C) kRITc (6,1682) IERROR
1396. C
1297. C CHECKR ERRCR ST/1EPEMS
1398. C
1299. 16CC FORMAT ('0','ERFCP: hYMIN HAS BEEN INPUTTED AS ',F6.4,•; IT MLST 6
1400. IE SET GREATER TMN O.G')
1401. 16C1 FCRMAT ('0','EFFCP: ^TRVL HAS BEEN INPUTTED AS ',14,'; IT MUST BE
1402. 1 SET ECLAL 1C EITHER 5 OR 15 MINUTES')
1403. 1602 FORfAT CO't'EPFCP: UZSN HAS BEEN INPUTTfcD GREATER THAJk CR ECLAL T
1A04. 1C LZSKt THJ IS ^CT REALISTIC')
1*05. UC2 FCRKAT CC't'ERFCR: IRC HAS BEEN INPUTTED AS 'fFB.4,'; IT MUST 8E
1406. 1 RUN AGAIN1)
1414. 16C1 FCRKA1 ('0',' VAPMNGi A HAS bEEN INPUTTED AS ',F8.4,'; IfPERVIOUS
K15. KREA JJ NCT CCMICEP.ED IN SEDIMcNT REMOVAL AS THE MODEL IS BASICAl
1416. 2LY FCR ',/,« ', 'AGRICULTURAL AREAi, hd^tVER IF IMPERVIOUS AREA IS
1417. 2DESIREC SET IChECK=CFF AND RUN AGAIN')
1418. 16CE FORMAT CO'.'EPFCR: UZS HAS BEEN INPUTTED GREATER THAN CF ECU4L TC
1419. 1 LZS, TUS IS NCT REALISTIC')
1420. 16CS FORMAT ('0','EPPCR: K24L HAS BEEN INPUTTfcO AS ',F8.4,»; IT MUST BE
1421. I SET LESS T^A^ CR ECUAL TO 1.0')
1422. 161C FORMAT CC'.'EPFCR: KK24 HAS BEEN INPUTTED AS ',F8.4,«: IT MUST BE
1423. 1 SET LESS TMf CF ECUAL TO 1.0')
1424. 1611 FORMAT ('0','EPFCF: K2*£L HAi BtcN INPUTTED AS »,F8.4,•; IT MLST B
1425. IE SET LESS 1MN CR ECtAL TO 1.0')
1426. 1612 FCRMAT ('0','EFFCF: K3 HAS BEcN INPUTTED AS ',F8.4,'; IT MUST BE S
1*27. 1ET LESS THAh CR ECU«L TO l.O'l
221
-------
Appendix C (continued)
1428.
1429.
1420.
1421.
1422.
1433.
1424.
1435.
1426.
1437.
1436.
1439.
1440.
1441.
1442.
1443.
1444.
1445.
1446.
1447.
1448.
1449.
1450.
1451.
1412.
1453.
1454.
1455.
1456.
1457.
1456.
1459.
14(0.
1461.
1462.
1<63.
1464.
1465.
1466.
1467.
1468.
1469.
1470.
1471.
1472.
1473.
1474.
1475.
1476.
1477.
1478.
1479.
14€C.
1481.
1462.
1483.
1484.
1485.
1486.
1487.
1613 FCRMAT ('0','ERFCP: UZDPTH HAS BEEN INPUTTED LESS THAN CP ECUAL TC
1 SZCPTH; THIS IS NOT REALISTIC')
1614 FCRMAT CC'.'EPFCF: SZOPTH HAS BEcN INPUTTED AS ',F8.4,'; IT MUST
1EE LESS THAh l.C INCHES')
1615 FCRMAT ('0','EPFCP: CNE OF THE VALUES FOR COVPMO HAS BEEN INPUTTEC
I AS ',F€.4,': CCVFMC MUiT BE LESS THAN 1.0'*
1617 FORM.AT CO'.'ERFCR: CNc OF THE VALUcS FUR TIMTIL HAS BEEN INPUTTED
1 AS •,!£,': TIMTIL MUST BE A POSITIVE INTEGER LESS THAN 367')
161E FCRMAT {'0','EPFCP: BULKD HAi> BEcM INPUTTED AS «,F8.4, '; IT MUST 6
IE GREATER THAN 62.4 LB/FT(3)')
161S FORMAT CO'.'EPFCR: AREA HAS BEEN INPUTTED AS >,F8.6,'; IT SHCULO
1BE INPUTTEC IN ACRES, HOWEVER IF THIS IS ACTUALLY THE CASE THEN SE
2T ICHECK=CFF',/,' '.'AND RUN AGAIN1)
162C FCPMAT ('0','ERFCR: HYCAL HAS BEcN INPUTTED AS ',A4,'; IT MUST BE
1SET EQUAL TC CAIE OR PROD')
1621 FCRMflT CO','ERFCF: INPUT HAS BEEN INPUTTED AS ',A4,'; IT MUST BE
1SET ECUAL TC ENCl OR METR')
1622 FORMAT ('0','ERFCP; CUTPUT HAS BEEN INPUTTED 13 *,A4,'; IT MUST BE
1 SET ECUAL TC EITHER ENGL, M.cTR, OR BOTH')
1623 FORMAT ('0' ,'ERFCB: PRINT HAS BEcN INPUTTED AS *,A4,
1SET ECUAL TC EITHER INTR, HOUR, DAYS, OR HNTH')
iA4,
IT MUST BE
IT MUST BE S
1624 FCRMAT CO'.'EFFCP: SNOW HAS BEEN INPUTTED AS
1ET ECL/L TC ^ES CP NC')
162E FCRMAT <'0','ERFCR: RAOCON HAS BEEN INPUTTED AS ',F8.4,'; RADCON M
UST BE GREATER THAN 1.0')
162? FCRMAT ('0','ERFCP: CCFAC HAS BEEN INPUTTED AS ',F8.4,'; CCFAC MUS
IT BE GPEATEP THIN 0.0*)
1«2C FCRKM ('0','ERFCR: SCF HAS BEEN INPUTTED AS ',F8.4,'; SCF MUST BE
I GREATER TH/N O.C')
1621 FORMAT CC't'ERFCP: ELDIF HA* BEEN INPUTTED AS ',F8.4, •; ELOIF SHC
ItLD BE INPUT IN THCUSAtJDS OF FEET AND CANNOT EXCEED 30.0')
1622 FCRMT CO'.'EPfCF: ICNS HAS BEEN INPUTTED AS (,Fe.4f': IONS MUST
1BE LESS THAN l.C*)
1633 FORFAT («0','ERFCR: F HAS BEEN INPUTTED AS ',F8.4,'; F MUST BE LES
IS THAN CR ECLfL TC 1.0«)
1634 FORMAT I '0 • ,' fcAPN ING: DGM HAS BEEN INPUTTED AS ',F8.4,*; VALUES GP
1EATEP THAN 1.0 UCHES FOR DGM ARt QUESTIONABLE* I
1635 FCRMAT ('0','ERFCR: .WC HAS BEEN INPUTTED AS ',F8.4,•; MC MUST BE L
1ESS THAN l.C1)
1636 FCRfAT ('0','ERFCF: EVAPSN HAS BEEN INPUTTED AS *,F8.4('; EVAPSN C
1ANNCT EE I NEGATIVE NUMBER')
1637 FORM/T {'0','ERFCR: MELEV HAS BEcN INPUTTED AS ',F9.1, •; K6LEV CAN
1NCT HAVE A VALUE GREATER THAN 30000.0')
163E FCRPAT CO', "EFFCR: TSNUH HAS BEEN INPUTTED AS ',F8.4,'; TSNCW ML
1ST HAVE A V/LIE CPEATER THAN 20.0 ANL LESS THAN 40.0')
163« FORMAT CO't'ERFCF: PcTMIN HAS BEcN INPUTTED *S ',F8.4,'; PETFIN f
UST BE GREATER THAN 30.0')
164C FORMAT CC'.'ERFCP: PETMAX HAS BEEN INPUTTED *S ',F8.4,'; PETKAX X
1UST EE LESS THAf 60.0')
1641 FCRMAT CO't'ERFCP: PETMUL HAS BEEN INPUTTED AS 'tF8.4,'; PETKUL H
1LST BE GREATER THAN 0.0')
1642 FORMAT ('0','ERfCF: WMUL HAS BEEN INPUTTED AS f,Fe.4,f; WMUL MUST
1EE GREATER THAN C.O*)
1643 FCRMAT CO't'ERPCR: RMUL HAS BEEN INPUTTED AS ',F6.4,«; PKLL MUST
1EE GRE/TER TH#N C.O')
1644 FORMAT ('0','ERFCR: KUGI HAS BEEN INPUTTcO AS •,F8.4,'; KUGI MUST
1BE A PCSITIVE NUMBER LESS THAN 10.0*)
165C FORMAT ('0','ERFCR: PEST HAS BEEN INPUTTED AS ',A4,«; IT MUST BE S
1ET EQUAL TC YES CR KG')
1452 FORMAT ('0','EPKR: JPMODE HAS BEEN INPUTTcO AS • ,A4,' ; IT MUST BE
222
-------
Appendix C (continued)
I486.
1489.
1490.
1491.
1492.
1493.
1494.
1495.
1496.
1497.
1499.
15CO.
15C1.
1502.
1*03.
1504.
1505.
1506.
1507.
1506.
150S.
1510.
1511.
1512.
1513.
1600.
1601.
16C2.
1603.
1604.
UC5.
1606.
14C7.
1608.
160S.
1610.
1611.
1612.
1613.
1614.
16161
1617.
1618.
1619.
1620.
1621.
1622.
1623.
1624.
1625.
1626.
1627.
1628.
1629.
1630.
1631.
1632.
1633.
C
C
C
C
C
C
C
C
C
C
C
C
C
1 SET ECLAL 1C SIPF CR SOIL1)
1653 FORM/IT <«0«,•fPFCF: DESORP HAS BEEN INPUTTED AS -,A4,'; IT MUST BE
1 SET ECIAL 1C YES CR NO')
1654 FORMAT (»0», • fcAPMNG: SOME OF THc FIVE
1LAL TC
2INM
llSt FCRMAT
1EE SET
1651 FORMAT
SSTR
0.0; IF TUS IS ACTUALLY OtSlktD ScT
VALUES INPUTTED APE EC
ICHECK=OFF AND RUN AG4
CO' .'ERFCP:
LESS THAN CR
(•C't'ERFCP:
^8.4,'; DEGCON M
IT MUST BE $
; IT MUST BE
OC
CM.AX HAS BEEN INPUTTED AS '.F8.4,*; IT SHCULO
EGUAL TC l.O1)
TIMAP HAS BtEN INPUTTED AS ',14,'; TIMAP MUST
16E A FCSITIVE IMEGEK LESS THAN 3b7« )
1656 FORM/1 ('0','EPFCP: THE INPUTTED YEAR OF APPLICATION DCES NOT OCCU
1R KITHIN THE FEHCD OF SIMULATION1)
165< FORMAT CO't'EPFCF: CEGCOM HAS BEEN INPUTTED AS
1LST BE LESS ThAN 1.0.«)
1665 FCRMAT 1*0* ,(EF:FCP: NUTR HAS BEEN INPUTTED AS
1ET ECLAL TC YES CF HC*)
168C FORMAT ('0','ERFCF: ICHECK HAS BEEN INPUTTED AS
1 SET ECLAL TC CN CR CFF«)
1661 FORMAT ('0','EFFCP: THt INPUTTED £NO DATE (ENCDAYtENDMCN .ENOYP)
1CURS BEFORE ThE EEGIN DATE (BGNOAY,&GNHONtBGNYR)•)
1662 FORMAT CO'i'lhE TCTAL NUMBtR UF DETECTED ERRCRS IN THE INPUT SEQU
1ENCE EGUALSS13,', PLEASE CORRECT AND TRY AGAIN OR CONTACT HYCROCC
2*Pf INC.*)
RETURN
END
ELCCK
ELCCK CATA TO INITIALIZE VARIABLES
IMPLICIT RE/111)
CIFENSICN FESE(J),RESEH5)tROS6(5),SRGX{5),INTF(5),RGX(5l,INFL(5» ,
1 UZSe(£).APERCB(5)fPIB(5),ERSNiS)
CIII'E^SICN SFEF(J),RCbTOM(5)fROBTUT<5)f INFTOM( 5) , INFTOTC 5 ) ,
1 RCITCfCS) tPOITCT(5) , RXd(5) f ERSTCM (5 ), cRSTOT( 5) ,MN!AM( 12) fRAD( 2*),
2 TEMPX(24),V>IND>(24),RAIN(2*a)
DIMENSICN FFSTC^<;),PRSTOT{5)^PROTOM(5),PROTOT(5),UPITCMI5),
1 UPITOTlSlfSlHf) tUTS(b)»SAS(5J ,SCS) iSOS(5) tSSTP(5),
2 UAS(5),UCS(5),US(5),USTR15) ,UPRIS<5)
COMMCN /ALL/ RL ,1-YMIN ,PRNTKc,HYCALtOPST(OUTPUTtTIt'FAC,LZS,AREA,
I RESeitPCSetSPGXtINTFiRGXrlNFLfUZSt,AP£ACd,Rie,ERSNtM,P3fA,
2 CALe,PPOD,PESTf^LTP,ENGL,M6Tft,BCTh,RtibfYES,^C,I^'INtIHP.fTF,
3 JCCLNl.FPIMt IMF .CAYS,HOUR.MNTH
CCMMCN /LANC/ »'^#^,PRTOT,ERSlnT, PRTOM.ERSNTMtCAY,
I RLTCC'tNEFTCK.PCSTCt'fRirUMiRIiNTOMffaASTOM.RCHTCMtRUTOT,
2 NEPTCT,RCSlCTfPnCT,RINTLT,dASTOTtRCHTQT,TwBALtEPTO«f EPTCTt
3 CZS,LZSNtL2SN,^FIL,INTER,iRC,NN,L, SS.iGHl ,PR tSGK.GWS ,KV,
4 K24L,KK24,K24El,EP,I«:S,K3tEPXH,kEii.l,RESS,SCEP,SCEPl,SRGXTt
5 SRGXT1.JRER.KREP ,JSER»KSERti*£AT,MMPIN,McTOPT,SNCHfCCFACt
6 SCF.ICNStF.CGK.kCiMPACKtEVAPSN.MfcLfcV.TS^OVI.PETHIN.PETMAXtELOIF,
7 OEWX,PACK,CEFTI-,»'CMHfSDENfIPACKtTHlNfSUMSNMfPXSNM,XK3»
223
-------
Appendix C (continued)
1634.
1635.
1636.
1637.
1638.
1639.
1640.
1641.
1642.
1643.
1644.
1645.
1646.
1647.
1648.
1649.
1650.
1651.
1652.
1653.
1654.
1655.
1656.
1657.
1656.
1659.
166C.
1661.
1662.
1663.
1664.
1665.
1666.
1667.
1668.
1669.
1670.
1671.
1672.
1673.
1674.
1675.
1676.
1677.
1678.
1679.
16EO.
1681.
1662.
1663.
16E4.
1685.
1686.
1687.
1688.
1689.
1690.
1691.
1692.
1693.
C
C
C
C
C
C
C
,RObTuT,RXofAuITOf,ROITOT,INFTCM,
TEMPX,RAD,WiNJX,KAlN,INPUT
CCKPCN /PESTC/ £TST,SPR(jTM,SPRSTM,SAST,$CST,SOST,UTST,UAST,UCST,K,
1 LDST,FP,ChA>,M,£PPCTT,SPRSTT,MUZ,FPUZ,UPRIT*,
2 UPPITT,KGPie,FK2,HLZ,LSTR,LAS,LCS,LDS,GSrR,GAS.GCS,GCS,
2 AFMCOE.TFE/L,
4 OEC-SCN,OEG£CT.CEGUCh,
5 DEGLCT,CEGL,CECS,NIP,OEGCON,DeGLuM, OfcGLOT.NCCH,
6 PR£TCM,PRSKT,FFCTCH,PkOTOT,UPITOM,UPITOT,STS,UTS,SAS,
7 SCS,SCSfSSlPtlAStUCS,ULiSfUSTRfUP»USfUlST,TOTPAP,TIfAP,YEARAP,
e DESGRF ,SliRF,SCIL,SULG
CCMHCN /NUT; CELT, STEMP, SN,SNT,SNRiM,SNROM ,UN,UNT,UNI ,UMT ,
1 L^RI^,^RS^•,L^,L^RPM,GN,SNR6M,UNRBH,LNRBM,GNREM,TNRBM,
2 JSR£Y,SNROY,UNRIYtNRSYtLNRPYtSNRBY,UNR8Y,LNReY,GNRBY,
3 TNREY,TNRhV,TNRHVM,TNfcHVY,TNA,TPA,TCLA,
4 Kfk,UKK,KP,THKP,NBAL,PHBAL,CL8ALt
5 TSTEP,KSTEP,SFLG,UFLG,LFLG,6FLG
INTEGEF PRMKE.CLTPUT.HYCAL.CALb, PROD, NUTR, PEST, ENGL.METR, BOTH
INTEGER SLRF,SCll,TIMFAC,YdS,NC,JCaUlT,TIMAP
INTEGEP PRIM, IMR, HOUR, DAYS ,MNTH
REAL*E
PEAL
FEAL
PEAL C( K, M, MZt HLZ
REAL L2SN, IPC, NN, L, LZS, KV, K24L, KK24f INFIL, INTER
PEAL IFS, K24EI, K3, NtPTOM, NcPTOT
INFTC», UF7CT, INTF, INFL
^MPIN, >E1CFT, KGPLB
PEAL NF, MFt KCM
REAL ^ELRA^I fELPAY
REAL*4 CEL1,STE>F<4,24),
1 SN(2C,5),£NT(20),SNRSM(20f5) ,SNROM< 20 ,5) ,
2 UN ( 2 C, 5 ), INT (20), UNI (20, 5) ,UM Tl 20) ,UKRIM (20,5 ) ,
3 NRSf(20,5l, LN(20),LURPH(20), GN(20»,
4 SNRE^(2C,5) ,UNRbM(20,5) ,LNRBH(2UJ ,GNRBM(20) ,TNRBf (20) ,
5 SKRSY(2C.£) ,SNROY (20, i ) ,UMKI Y(20, 5) ,NPSY(?0,5) ,
6 LKPFY(2C),SNRBY(20f5) , UNRdY(^Oo) ,LNRBY (20) , GNRBY (20 ) ,
7 TNREY(2C)(TNfiHV(20) ,TNKHVrt(20) ,TURHVY(20) ,TNA , TF A,TCL A,
£ KN(lCf4),1hKN(10) ,KP( 3 ,4 ) ,THKP(5) t NfaALt PhBAL,CLB AL
DATA FFTCT, EP£hTT/2+0.0/
DATA PRTCC, ER £^TM/2*0.0/
CATA PLTCK, FCSKM, RITOM, RINTCM, NEPTuM/ 5*0. 0/
DATA RLTCT, PCSTCT, RITOT, RINTCTt NEPTOT/5*0.0/
CATA PCETCI^f RCETOT, INFTOK, INFTCIt ROlTOMt ROITOT/30*0.0/
CATA FPCTC>f FKTCT, PRSTUM, PRSTOT , UPiTOM, UPITOT/3C*0.0/
CATA TkBALi FE£E, SRGX, INTF, EKSTOM, EKSTCT, SDST/27*0.0/
CATA PESEli EASTCH* RCHTOM, BASTOT, RCriTUT/9*0.0/
CATA SFRCTK, SFRSTt-, fcPTCM, EPTCT/4*0.0/ , PRNTKE/0/
CATA SIS, £1ST,
-------
Appendix C (continued)
1694.
US5.
1696.
1698.
1699.
1700.
17C1.
1702.
1703.
1704.
1705.
1706.
1707.
1708.
1709.
1710.
1711.
1712.
1713.
1714.
1715.
1716.
1117.
1118.
1719.
1120.
1721.
1722.
1123.
1724.
1725.
1726.
1727.
2COO.
2C01.
2C02.
2003.
2C04.
2005.
2CC6.
2CC7.
2CC8.
2CCS.
2010.
2011.
2012.
2013.
2C14.
2015.
2016.
2C17.
2C18.
2C19.
2020.
2C21.
2022.
2023.
2024.
2025.
C
C
C
C
C
C
C
C
C
C
C
C
C
CATA
CATA
CATA
CATA
DATA
DATA
CATA
CATA
CATA
*
*
CATA
CATA
CATA
CATA
CATA
CATA
CATA
CATA
CATA
CATA
CATA
1
2
3
4
C
€
EPSN/5«C.C/, SRER/5*0.0/, SRERT/0.0/
SAS/5»0.0/t SCS/i*0.0/, SOS/5*0.0/, AREA, H, K/3*0.0/
M, FF, CM>, SSTR/8*0.0/
SFRC.T1, SfFSTT/2*0.0/
LAS/5«0.0/, UC •,' JUNt •,• JULY •,' AUGUST ;,
•SEFT^eEPl ,« OCTOBER1,'NuVEMBER' .'CECEMBER'/
f^PIN/25.1/, ^£TOPT/0.9072/, KGPLB/0.4536/
CEGSC^, DEC-SOT, UEGUOM, DEGUOT, OfcGU, OEGS/6*0.0/
C6GIC>, OEGLCT/2*0.0/,TOTPAP/0.0/
MP, hCCH/i*0.0/, TPBAL/0.0/, SULG/0.0/
SlJ^•s^^, FxihH, MELRAM, RADMEM, CORMCM, CRAINH,
cc^^'E^, sct-M, SNEGfM, SEVAHM, SUMSNY, PXSNY, MELRAY,
PACfEY, CCP^EY, CONMtY, GRAINY, SGMY . SNEGKY, SEVAPY,
TSI\E/L/21Y/100*0.O/.SNRCY/100*0. OX,
LKRIY/1CCtG.O/.NRSY/100*0.O/.LNRPY/20*0.O/.SNPBY/1CO*O.C/,
LNRBY/100«C.O/,LNKBY/20*0.0/,GNRBY/20*0.0/,TNRBY/2C*0.0/,
TNRHV/20*C.O/,TNKHVM/20*0.0/,TNKHVY/20*0.0/,
TNA/C.C/,TFA/0*0/,TCLA/0.0/
END
SU8RCUTINE
HSP LANDS
IMPLICIT
CIKENS1CN FESI (f ) ,RESB1I5 ) , ROSB(5 ) ,SRGX(5 ), INTF ( 5 ), RGX ( 5 ) ,RUZ8( 51 ,
1 LZ£e<5),APERCe<5),PIB<5) ,ERSN(5)
CIKENSICN SFEF(5),PCbTOM(5),ROBTOT(i),INFTUM(5),INFTOT<5),
1 ROnCK5),FCITCT(5),RX6(5),ERSTCM(5),£RSTCJT(5),MNAH(12),RAO(24),
»
2 SRERI*T(5J
CICENSICN ShPC(3»,RXX(3),DEEPL(5),UZRA,INTF,RGX,£NFL,UZSc,APERCB,KlB,ERSN,M,P3,A,
2 CALe,FFQC,PEST,iaTR,EN(;L,McTRiBGThtKESB,YES»NCfI*INflHP,TF.
2 JCC LNT, PP 1 rT, IMF, CAYS, HOUR, MNTH
225
-------
Appendix C (continued)
2026.
2027.
2028.
2029.
2C30.
2011.
2032.
2033.
2034.
2035.
2036.
2037.
2038.
2C39.
2040.
2041.
2042.
2C43.
2044.
2C45.
2046.
2Q47.
2048.
2C49.
2C50.
2C51.
2052.
2053.
2054.
2055.
2056.
2057.
2C58.
2C59.
2C60.
2C61.
2CC2.
2C63.
2C64.
2065.
20«6.
2047.
2C68.
2C69.
2C70.
2071.
2072.
2073.
2C74.
2075.
2076.
2C77.
2C78.
2C7S.
2060.
2C81.
2C€2.
2C83.
2C84.
2C65.
C
C
C
C
C
C
C
C
COMPCN /LAKC7 MMK,PRTOT,ERSNTT,FRTOH,ERSNTM,CAY,
1 RU10PtNEF7£ftPCS7CfSRITUM,RINTOM,&ASTOM,RCHTCMtRUTaTt
2 KEPTCT,PCSUT,f 1TOT.RINTOT ,bASTOT ,RCHTOT ,Tk«BAL,EPTOM, EPTOT,
3 UZS,UZSN,LZSf>, 1NFIL , INTE R i IRC.NN.L, Si ,SGW1 ,PB ,SGW,GWS ,KV,
4 K24L,KK24,K;ETCFT, KGPLB
REAL INFIL, INTER, KN, INFLT, IRC,
REAL IRC4, 1CS, IPS, NcPTOH, NEPTOT
PEAL IKFTC*, UFTCTf QME TRC
REAL KKPIN, >ETCFT, KGPLB
REAL L2SfET, L2SFET, SGWMET, SCcPHT , RESSMT
REAL ThBLMT, SFOTK, RES6MT, SRGXMT
REAL ICN.S, hFACK PELEV, KUGI, NEGMLT, NEGMM
REAL fELT, INCT, KCLU, IPACK, ME LA AM, MELRAY,
MEL RAO
CATA lKRR,, riBAL, SEVAP72 1*0.07
SNCLT/3e4*C.O/,CLDf:7-1.07,ALbECa70.6/
SLMSKC ,FX ShC , FELRAD ,RADMfcO,CDRMEO,CONMEC,CRAIND, SGKD,
CATA
CATA
CATA
CATA
CATA
LZS1 = L2S
LZS1 » LZS
NUMI > 0
OPST » C.O
PACK1 * PACK
LlCfcl =• LICh
ZEFCING OF VARIABLES
226
-------
Appendix C (continued)
2066.
20€7.
2C£S.
2C89.
2C90.
2C91.
2C92.
2CS3.
2094.
2C95.
2C96.
2097.
20S6.
2C99.
2100.
21C1.
2102.
2103.
2104.
2105.
2106.
2107.
21C8.
2109.
2110.
2111.
2112.
2113.
2114.
2115.
2116.
2117.
2118.
2119.
2120.
2121.
2122.
2123.
2124.
2125.
2126.
2127.
2128.
2129.
2130.
2131.
2132.
2133.
2134.
2135.
2136.
2137.
2138.
2139.
2140.
2141.
2142.
2143.
2144.
214S.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
PRR * I
CO 184
• C.C
184
LIRC«=1.C-IFC4
KK4=KKi4**U.C/*C.C)
LKK4 = 1.0 - KM
IF ((1440./llfFlU.LE. 100.) GO TO 187
LIRC4 • LIPC4/3.0
LKK4 * LKK4/3.0
1£7 DEC* O.COS£2*mN*L/SQRT(SS))**0.6)
SRC- 1C20.* = (l.C -MCE)
IF (04FX .LI. 0.1) 04FX * 0.1
D4F = C4F*C4FX
186 RATIC= INTEP«EXF(C.6S3147*LNRAT)
IF ((RJTIC).Ll.(l.On RATIO=1.0
C4F*R/TIC
TF/24
TF IS 1 FUR RAIN DAYS, AND 96
OR 2t>8 FOR NON-RAIN DAYS
IF (TF ,GT. 2» IhRR«0
CO 155 IIIM.TF
LNRAT * L2J/L2SK
IF JTF .LT. 2) GC TC 4
NL^I =^LMI + 1
IF (M>I .N£. hJ GC TO 4
KUMI - 0
S6AS * 0.0
SRCH C.C
RCS = C.O
PU > 0.0
GWF = C.O
PGXT = 0.0
PERC » C.O
INFLT » 0.0
T1CFAC - 1II»E INTERVAL IN MINUTES
L - LENGTH OF CVERLAND SLOPE
Mt - f-ANMKC'* N FCR OVERLAND SLOPE
227
-------
Appendix C (continued)
2146.
2147.
2148.
2149.
2150.
2151.
2152.
2153.
2154.
2155.
2156.
2157.
2156.
2159.
2160.
2161.
2162.
2163.
2164.
2165.
2166.
2167.
2166.
2169.
2170.
2171.
2172.
2173.
2174.
2175.
2176.
2177.
2178.
2179.
2180.
2181.
2182.
2183.
2184.
2185.
2166.
2167.
2168.
2169.
2190.
2191.
2192.
2193.
2194.
2195.
2196.
2197.
2198.
2199.
2200.
2201.
2202.
2203.
22C4.
2205.
C / - IMPEPV101S AREA
C FA FERVICLJ *PEA
C
C
C
C
C PP IS INCCMNG FAINF/IL
C P3 IS RAIN PEACUNG SURFACE! .OO'S INCHES)
C P4 IS TOTAL MOISTLRE AVAILABLE! IN.)
C RE'S IS OVERLING FICfc STORAGE! IN.)
C C4F IS 'E1 IN CF. M0NLAL
C PA11C IS 'C' IN CF. MNUAL
C EP - DAILY EVAF ( IN.)
C EFhP - HOURLY EVAF
C EFIN - INTEFVAL EVAf
C EPXX - FACTCR FCR RECLCUG EVAP FOR SNOW AND TEMP
C
C
C
C
C DETERMINE IF J>ELT IS TO BE DONE
C
HRFLAG-0
ITEST = IMN/mFAC
IF (NLM .EC. 1 ) HRFLAG = 1
IF (ITEST. EC. 1) hRFLAG - l
C
C HRFLAG=1 INC1CA1ES BEGINNING OF THE HOUR
C
IF (HRFLAG. EC. 03 GO TC 999
IEND C
IF (IHP.EC.24) CC TO 202
IHRR = IhP •» 1
GO TO 5C1
202 IHRR IHRR * 1
5C1 EPhR = EVC1SK 1HPR1*EP
IF (EPHR.LE.(C.CCOD) EPHR=0.0
EFIN= EPHR
EP1M=EPIN
IF (SNCV .EC. NO GC TO 999
IF UFACK .IE. C.O).AND.(TMIN .GT. PfcTMAXJJ GO TO 999
C ******************** 4 **********
C faEiilN SNOWMELT
4***
C ******************** 4******** 4* 4***
1SNOH = ISNCfc * 1.
SKTEHP * 22.
SEVAP - 0.0
SFLAG - 0
FRHR=O.C
EPXX = 1.0
IKENC = 60./(TII>FAC)
IPT = (IHPR-1)*1I«END
C SUM PREC1P FOR THE HOUR
PX=0.0
CO 502 II ' l.IKEND
5C2 PRHR = FRHR + R/IMIPT + II)
C CORRECT TcMP FOR ELEVATION
OIFF
C USING LAPSE RATE OF 3.5 DUPING RAIN
C PERIODS, AND AN HOURLY VAR
C LAPSE RATc (LAPSE(I)) FCR
IATION IN
CRY PERIOC
228
-------
Appendix C (continued)
22C6.
2207.
2208.
2209.
2210.
2111.
2212.
2213.
2214.
2215.
2216.
2217.
2218.
2219.
2220.
2221.
2222.
2223.
2224.'
2225.
2226.
2227.
2228.
2229.
2220.
2231.
2232.
2233.
2234.
2225.
2226.
2237.
2228.
2239.
2240.
2241.
2242.
224.3.
2244.
2245.
2246.
2247.
2248.
2249.
2250.
2251.
2252.
2253.
2254.
2255.
22*6.
2257.
225€.
2259.
2260.
at i.
22C2.
2263.
2264.
2265.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
LAPS = LAFSEUHFP)
IF (PPhR .G1. O.OJJ LAPS = 3.5
IX = TEfPX(IHFR) - LAPS*ELDIt;
REDUCE RfcG 6VAP FCR SNOWMELT
CONDITIONS BASED CN PETMIN AND
PcTMAX VALUES
IF (PACK.LE.IFACM GC TO 504
E1E=0.0
FACKPA = l.C
GO TC 5C5
•04 PACKRA = PACK/IFKK
ElE=l.O - F/CKR*
5C£ EPX> » (1.C-F)*E1E •» F
IF ) GO TO 512
IF (EPXX .GT. 0.5) EPXX=0.5
IF (TX.LT.PETMM EPXX
RcDUCE EVAP BY 50% IF TX IS BETWEEN
PETMIN ANC PETMAX
0.0
512 EPhR = EPhR«EFX>
EFIN = EPIMEfXX
IEND=0
SNEAL = 0.0
IF ((TX .GT. TSKta) -AND. (PRHR .GT. .02)) DEMX = TX
SET CEVFT 7ECF ECtAL TO AIR TEMP WHEN RAINING
CK SNCV TO INCREASE SNOUMELT
IF (DEhX .GT. TX) OEtaX = TX
SNTEHP = TShCh * (T>-OEWX)*(0.12 + 0.008*TX)
RAI^/S^CV TEI^F. C1VISICN - SEE AMJERSONt rtRR. VOL. 4, NO. 1.
FEE. 1S68, F. 21i EG. 2d
IF (SNTEHF .Gl. 1
-------
Appendix C (continued)
2267.
2268.
2269.
2270.
2271.
2272.
2273.
2274.
2275.
2276.
2277.
2278.
2279.
2280.
2281.
2282.
2283.
2284.
2285.
2266.
22€7.
2288.
2289.
2290.
2291.
2292.
2293.
2294.
2295.
2296.
2297.
2298.
2299.
2200.
22C1.
2202.
22C3.
2304.
22C5.
2206.
23C7.
23C8.
2309.
2210.
2*11.
2212.
2213.
2214.
2215.
2216.
2317.
2218.
2219.
2220.
2221.
2222.
2223.
2224.
2225.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
PX = PX*SCF
APR = APR * (SCF-1.0)*PRHR
PPHR = FRHtXSCF
SLMSN » SLf£N + FX
CNS = ICNS
IF (TX .GT. C.O) DNS = DNS * ((TX/100.)»*2)
SNOW DENSITY MU TECP. - APPROX Tb FIG. 4, PLATE B-l
SNCV. HYDRCLCGY SEE ALSO ANbERSGN, TR 36, P. 21
PACK = FACK 4 F>
IF (FACK.LE.IFACK ) GO TO 548
IPACK = PACK
IF (IPACK .CT. >FACK) IPACK
MPACK
546 DEPTH = DEPTH + (PX/CNS)
IF (DEPTH .CT. C.O SOEN - PACK/DEPTH
INDT = INCT - 1CCC*FX
IF (INCT .LI. O.C) INDT - 0.0
PX = 0.0
GO TO 555
55C KCLD - KCLC - 1.
555 IF (KCLC .IT. O.C) KCLO = 0.0
PACKRA - PACK/IFICK
IF (PACK .GT. HACK) PACKRA = 1.0
IF (PACK.CE.C.CC5) GO TO 580
IPACK IS AN UDE> TC AREAL COVERAGE OF THE SNCHPACK
FCR INITIAL STCFI>£ IPACK = .1*MPACK SO THAT CCMPLETE
/REAL CCVER/CE FESULTS. IF EXISTING PACK > .1 *MPACK THEN
IPACK IS SET EGLJl TC HPACK WHICH IS THc WATER ECUI. FCR
CCPFLETE ACE^L CCVERAGE PACKRA IS THt FRACTION AREAL COVERAGE
AT ANY TI»>E.
IPACK = O.MKFACK
XICE = C.C
XLNHLT - O.C
NEG^LT » C.C
PX = PX * P/CK « LIQM
PACK 0.0
LIQK * C.Q
ZERC SNCVihELT CLTFLT ARRAY
CO 570 I-lt<4
DC 510 FMltU
57C SNOLTd.HH) » O.C
GO TO SS7
5iC PXCNSN FXCNSN « PX
IF (DEPTH .CT. C.C) SD£N * PACK/OEPTH
IF (INCT .LT. 8CC.) INDT = INOT * 1.
INOT IS INDEX TO ALBEOC
KELT ^ C.O
IF (SOEN .LT. 0.55) DEPTH=CEPTH*(1.0 - 0.00002*CDEPTH*(.55-SOEN)))
EMPIRICAL RELfTICNSHIP FOR SNOW COMPACTION
IF (DEPTH .CT. C.O) SDEN ' PACK/DEPTH
230
-------
Appendix C (continued)
2226.
2227.
2228.
222S.
2230.
2231.
2232.
2333.
2234.
2335.
2226.
2237.
2238.
2239.
2340.
2241.
2242.
2343.
2244.
2345.
2246.
2247.
2348.
234S.
2250.
2251.
2252.
2253.
2254.
2255.
23*6.
2357.
2358.
225S.
2360.
2361.
2262.
2263.
2364.
2265.
2366.
2367.
2368.
2369.
2370.
2271.
2372.
2273.
2374.
2275.
2376.
2377.
2578.
2379.
22£0.
2381.
2382.
2-83.
2284.
2365.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
VIN «
HOOPLY HNC V/LLi
LREF = (TX 4 1CC.)/S
LREF = IFIX(LPEF)
SVPP = SVP (LPEF)
ITX = IFIX(IX)
SATVAP n SVFP *(»-CD(ITX,5)/5>*(SVP(LftEF * 1) - SVPP)
LREF = (CEfc> 4 KC.)/5
LREF = IFIX(LPEf)
SVPP = SVF (LPEF)
ICEV»X * IFIX(CEfr»
VAPP SVFP 4 (KC( ICEHX,5)/5)*(SVH(LREF * 1) - SVPP)
CALCULATION OF VAPt« PRESSURE AT AIRTEMP
*rD CEMPOINT
SEVAP > 0.0
IF (V4PF.LE.6.1CU GC TO 610
CNK = €.59*(WPF - 6*10ti)
GO TC 620
61C CNV = 0.0
OLfMY=(\iAPP-S/TWF)*PACKRA
IF (VAFP .LI. SMVAP) SEVAP EVAPSN*0.0002*HIN*DCMMY
PACK = PACK 4 SEV/P
SEVAP7 SE\AFT - SEVAP
CONDEt^SATI^ - CCNVECTION MELT, EQ. T-29B, P. 176, SNOH HYDROLOGY
CCNV - CONVECTICN, CCNDS - CONDENSATION
SEVAP - EVAF FRCh SNOw (NEGATIVE VALUE)
62C CNV = C.O
IF (TX .GT. 22.) CNV = (TX-32.)* 11.0 - 0.3*(MELEV/10000. ))
CCXC = CCFAC*.OCC26*WIN
.COC26 = .GU25/24, I.E. .00026 IS THE DAILY COEFFICIENT
(FRCK S^0^ hYCRClCGY) REDUCED TO HOUKLY VALUES.
CCNV = CNV*COC
CCNCS « CNMCCXC
CLCUD COVER
CLCF IS FRACTION OPcN SKY - MINIMUM VALUE 0.15
IF (IHFF.EC.l .CF. CLUF.LT.0.0) CLDF (1.0 - 0.085*(KCLC/3.5))
ALBEDO
IF (CCMt-.Gl.S) GC TC 640
IF (MGMh.LT.4) GC TC 640
AL8ECO = 0.€ - C.l*(S«AT(INDT/24.))
IF (ALEECC .IT. C.45) ALBEDO = 0.45
GO TC 650
640 ALBECC = 0.£5 - C.C7*(SaRT(l,NDT/24.0))
IF (ALEECC .LT. C.6) ALBEDO * 0.6
SHORT fcAVE RADIATION-RA - POSITIVE INCOMING
65C PA RAC( IhFR)*(I.O -ALBEDO)*(i.O-F)
LCNG WAVE RACIATICN - LH - POSITIVE INCOMING
CEGHR = TX - 22.C
IF (CEGI-R.LE.C.C) GC TO 660
LK = F* 0.26*CECH: + (1.0 - F)*(0.2*Ok:GHR - 6.6)
GC TC 665
66C LV> * F*C.2*CECHP * (1.0 - F)* (0.17*OEGHR - 6.6)
LH IS A LINEAR APPROX. TO CURVES IN
231
-------
Appendix C (continued)
2286.
2387.
2388.
2289.
2290.
2391.
2292.
2293.
2294.
2295.
2396.
2297.
2298.
2299.
2400.
2401.
2402.
2403.
2404.
2405.
2406.
2407.
24C8.
2409.
2410.
2411.
2412.
2413.
2414.
2415.
2416.
2417.
2*16.
2419.
2420.
2<21.
2422.
2*23.
2424.
2<25.
2426.
2427.
2428.
2429.
2430.
2421.
2432.
2433.
2424.
2435.
2426.
2427.
2438.
2429.
2440.
2441.
2442.
2443.
2444.
2445.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
FIG. 6, PL 5-3, IN SNUW HYDROLOGY.
6.6
IS AVc BACK. RALIAT1UN LOST FROM THE SNOUPACK
IN OPEN AkfcAS. IN LANGLEYS/HR.
CLUUU COVER CORRECTION
665 IF (LK .LT. C.O) LW « LW*CLOF
RAIN MELT
PAINF 0.0
RAINMcLT IS OPERATIVE IF
RAIMNb AND TEMP IS ABOVE
IF USFLAG .LT. 1).«ND.(TX .L.T. 32.)) RAINM DEGHR*PX/
TOTAL MELT
PM (Lk + M)/2C2.2
203.2 LANGLtYS REQUIRED TO PRODUCE
RUNOFF FRCM SNGrf AT 32 CEGREES F
IF (FACK.GE.IFACK) GO TO 680
Rf = RMP/CKF/
CCNV = CCNV1F/CKF*
CCNDS CCNCS«F*CKRA
RAINP = RAUMFKKRA
IF (IhPP.NE.t) CC TC 680
XLNEf = 0.01*(2Z.C - IX)
IF (XLNEM .CT. HNKLT) XLNMLT =* XLNEM
6€C PACKE RACK 4 F*
CORFE CCP^E * CCNCS
CCKME » CCKt-E + CCNV
CRAIN = CP 0.0
IF (TX .LT. 22.) r-EGM = 0.00695* (PACK/2.0) »( 32.0 - TX )
IT IS
32 F
144.
I INCH
HALF CF PACK IS USED TO CALCULATE
MAXIMUM NEGATIVE MELT
TP * 22.0 - (NECMT/(0.00695*PACK))
IP IS TEMF CF TK SNOkPACK
0.00695 IS IN. fELT/IN. SNOli/DEGREE F
IF (TP.LE.T» GC 10 695
GM = O.CC07<(1P - TX)
NEG*LT = NEChLT ^ Gf
SNEGM « SNECC 4 C>
695 IF (NEGJ-LT .CT. NEGMfr) NEGMLT * NEGMM
t'ELT * C.C
PELTING PROCESS BALANCE
7CO FXBY = (l.C - PK*RA)»PX
PX PACKPMFX
FXBY IS FRACT1CK CF PREC1P FALLING ON BARc GROUND
IF ((MELT 4 P».IE.O.O) GO TO 795
SATISFY NEGH1 ffCH PRECIP(RAIN) AND SNOWMELT
232
-------
Appendix C (continued)
2446.
2447.
2449.
2450.
2451.
2452.
2453.
2454.
2455.
2456.
2457.
2458.
2459.
2460.
2461.
2462.
2464.
2465.
2466.
2467.
2466.
2469.
2470.
2471.
2472.
2473.
2474.
2475.
2476.
2477.
2478.
2479.
2480.
2481.
2482.
2463.
24£4.
24£5.
2486.
24£7.
2488.
24£9.
2490.
2491.
2492.
24S3.
2494.
2495.
2496.
2497.
2498.
2499.
2500.
2£0l.
2502.
2503.
2504.
2505.
C
C
C
C
C
C
C
C
C
C
C
C
IF (PELT.GE.NEGHT) GC TO 720
NEGHLT = NECMT PELT
PELT - 0.0
GC TO 725
72C PELT = PELT - NEOLT
tvEGHLT - O.C
725 IF (PX.CE^ECMTJ GC TO 735
hEGPLT - NEC-MT - PX
PACK = PACK » F>
PX = 0.0
GO TC 740
735 PX = PX - NEGHT
PACK = PACK * NECM.T
NEGPLT - O.C
74C IF ((PX + MELT) .EQ. 0.0) GC TO 800
CCPPAPE SNC^ELl TC EXISTING SNOwPACK AND WATER CCNTENT CF
THE PACK
IF (PELT.LE.F4CH GC TO 750
75C
PELT =
CEPTH
PACK -
LIC* =
INDT *
GO TC
PACK =
PACK +
0.0
C.O
0.0
c.c
765
PACK -
LKh
76C
IF (SCEN .C-T.
IF (PACK .GE.
IF (PACK.CE.C
LIQVi - LKV« 4 P4CK
PACK - 0.0
LIQS = VC*P*CK
IF (SCEh .GT. 0.6)
IF (LICS .LT. O.C)
KEIT
O.C) DEPTH = DEPTH
(C.S*CEPTH)J DEPTH
CC1) GC TO 760
(MELT/SDEM
1.UNPACK
LICS
LIQS
MC*(3.0
0.0
- (3.33)*SDEN)*PACK
CCMFARE AVAILABLE MCISTURE WITH AVAILABLE STORAGE IN SNOWPACK
-LIQS
765 IF ((LICt. + fELT •• PX).LE.LIQS) GO TO 775
PX = KELT + P> « LKh - LIQS
LICH LICS
GC TC 760
775 LIQU = LICh * PELT « FX
FX = 0.0
7£C IF (PX.IE.XLM*L1) GC TO 790
FX = PX - XLM^Ll
PACK PACK •»
>ICE = MCE +
XLNKLT * 0.0
GO TO 7S5
7SC PACK = PACK + F>
XICE = XICE + F>
XLMLT = XL^^1lT - PX
PX = O.C
795 IF (XICE .Gl. P/CK) XICE - PACK
233
-------
Appendix C (continued)
2506.
2507.
2508.
250S.
2*10.
2:il.
2512.
2513.
2114.
2515.
2J.16.
2517.
2518.
2 5 IS.
2*20.
2*21.
2122.
2*23.
2524.
2525.
2526.
2527.
2*28.
2S2S.
2*20.
2*31.
2532.
2523.
2134.
2535.
2536.
2527.
2528.
2539.
2540.
2541.
2542.
2543.
2544.
2545.
2546.
2547.
2*48.
2549.
2550.
2551.
2552.
2553.
2554.
2555.
2556.
2557.
2558.
2559.
25tO.
25*1.
25fe2.
25<3.
2564.
25<5.
C
C END KELT ING PROCESS BALANCE
C
8CC If (CEFTh .CT. C.O) SOEN * PACK/DEPTH
IF (SCEh .LI. 0.1) SCEN * 0.1
C GROUNOMELT
If UHRR.NE,li) CC TC 630
CGPK = CGP
IF (IP .LT. 5.CJ IP - 5.0
IF (IP .LT. 2Z.) DGHN = OGMM - OGM*.03*(32.0 - IP)
IF (PACK.LE.CCfrM GC TO 825
PX = P> * CO*
PACK FACK CCM»
CEPTK- - DEPTH - (CG>K/SDEN)
SGH * 4 LICK
SGH = SGK •» PACK
PACK = C.O
CEPTH * 0.0
LICU ^ 0.0
NEGKLT » C.C
83C CONTINUE
FX * F> + F>E>
SPX = £FX + F>
C
C HOUR VALUE ASSIGNMENT
SS7 JUMSNH » SL»«SN
PXSKI- - FXCKSh
SPXH = SPX
RADF'EH = RACKE
CCRfEH - CCffrE
CCNfEh » CC^^'E
CRAINH - CR/1>
SG^H = SGK
SNEGHH = SNEGK
SEVAPI- ~ SEV/FT
C
C DAILY SUNS
IF (FRira.M.CMSl GO TO 996
SUMSND » SLCiNO + SU^SN
FXSNC = PXSNC * PXCNSN
KELRAO =• >>EIPAC « SPX
PACKED P4OEC « RAOKE
CCPfEC CCFMC < CCRKE
CCNMED - COfEC « CC^^'E
CRAINC CPMKD 4 CRAIN
SGMO = SG^C * SGW
SNEGMD SNEGt-0 « SNEGM
SEVAPC » SEN4FC + SEVAPT
C
C MONTHLY SUMS
«6 SUMSNM = SL^SKF t SLKSN
FXSNW * PXJhl- PXCNSN
*ELRA* » ^ElPAf SPX
RAOMEK => RAChEf RAOME
CCPfEK CCFFEJ- CCRME
CCNHEH = CCff-Ef CCNME
CRAINK CPMKf- 4 CRAIN
SGPf « SGff 4 SGI1
234
-------
Appendix C (continued)
2566.
2567.
25*8.
2569.
2570.
2571.
2572.
2573.
2574.
2575.
2576.
2577.
2578.
2579.
25EO.
2561.
2582.
2163.
25£4.
2585.
2566.
2567.
2568.
2569.
2590.
2591.
2592.
2593.
2594.
2595.
2J96.
2597.
2598.
2599.
2(00.
2601.
26C2.
26C3.
26C4.
2605.
2606.
2607.
2608.
2609.
2610.
2611.
2612.
2613.
2614.
2615.
2616.
2617.
2618.
2619.
2620.
2621.
2<22.
2623.
2624.
2625.
C
C
C
C
C
C
C
C
C
C
C
C
C
SNEGHM - SNECf-C-
SEVAPK • SEWf*
SUMSNY « SL*SM
PXSNY = PX£M
*ELRAY = *EIP*Y
RADMEY - RAl>EY
CCRMEY - CCFfEY
CONMEY - CCmY
GRAINY * CRMM
SGHY » SG^Y
SN6GPY « ShEG^Y
SEVAPY - SE^AFY
SUMSN « 0.0
PXCKSh - O.C
SPX = 0.0
RACHE > 0.0
CDRHE » 0.0
CCN^E - 0.0
GRAIN - 0.0
SGH =• C.O
SNEGC * 0.0
JEVAPT - O.C
SNOUTdl-RRtlJ
SNOCK IhRRti
SNC(-T
418EDG
CLDF
^EG^LT
HQt<
IX
FA
LW
FX
>ELJ
CQFV
PA IAN
CO^OS
>ice
f^GL) GO TO 345
ECTH .AND. INPUT ,EU. tNGL) GO TC 845
1C SNCVi OUTPUT
* PACK*MMPIN
- OEP7H*MMPIN
- ^EG^LT*MMPIN
» LKXVMMPIN
= 0.556*( TX-32.0)
-11,16
»I«NCOT) = SNOUT (JHRR,iSNOUTJ*KHPIN
235
-------
Appendix C (continued)
2(26.
2627.
2628.
2629.
2630.
2631.
2632.
2633.
2634.
2<35.
2636.
2637.
2638.
2635.
2640.
2641.
2642.
2643.
2644.
2645.
2646.
2647.
2648.
2649.
2650.
2651.
2652.
2653.
2654.
2655.
2656.
2657.
2658.
2659.
2660.
2661.
2662.
2663.
2664.
2665.
2666.
2667.
2668.
2669.
2670.
2671.
2672.
2673.
2674.
2675.
2676.
2677.
2678.
2679.
26EO.
26E1.
26£2.
26£3.
26£4.
2685.
842 CCM1MIE
C
845 IF (MCJL.EC.FPCC) GO TO 998
C
IF ( IKPP .KE. 24 > GC TO 998
IF (PACK. LE. 0.0) GC TO 998
WRITE 16,592) fMM f-CNTH) ,OAY
WRITEU,55C)
C
00 EEO 1-1,24
WRITE 16.991) I,(, 'C*TEJ ,4X , • TIME1 ,4X , • FLOH (CFS-CMS 1 • , 6X,
> 'SECIhEM (LBS-Ko-KG/MIN-Gh/L)1 ,23X,
X 'PESTICICE IGM-GM/MIN-PPM)')
SS5 FCRHAT «• • ,f IX , "VATtR1 ,24X,« SEDIMENT' )
C
C CORRECT l. ATE* BALANCE FOR SNOWHELT
C PACK AND £NGri EVAP
C
C PRR IS INCOMING PRECIP
C PX IS MOISTURE TO THE LAND SURFACE
C SEVAP IS SNO*» cVAP - NEGATIVE
556 IF (IEKC.EC.U JIvfiAL PRMR+SEVAP-PX-PACK+PACK1-LIQW*LIQHI
IF ( (SNEAL.n.C.CCOl). AfJi3.(SN6AL.viT. -0.0001) ) SNBAL*0.0
1SN6AL 1SFEAL « SNEAL
C
C
PACKl * PAO
LIQH1 * LIQk
Q **4*4 4*** ********* ****************
C END SNOhMELT
C 4444444*4************************
C PX IS TOTAL MOISTURE INPUT
TO
C THE LAND SURFACE FRCf PRECIP
C AND SNOHMELT CURING THE HOUR
C
955 IF (IEKC .G1. 0) FR=«PX*TI MFAC/60.
C IfcNL>0 INDICATES SNOWKELT
C OCCORKED DURING THE HCUC
C
C
C
C
C 4 * * INTEFCEP1ICN FUNC . * » »
C
C
C EPXf - VAX. INTEPCEfTION STORAGE
236
-------
Appendix C (continued)
26E6.
2tB7.
26C8.
2£E9.
2650.
2691.
2692.
2693.
2CS4.
2695.
2696.
2657.
2658.
2699.
2700.
2701.
27C2.
2703.
2704.
27C5.
2706.
2707.
27C8.
27C9.
2710.
2711.
2712.
2712.
2714.
2715.
2716.
2717.
2718.
<719.
2720.
2721.
2722.
2723.
2724.
2725.
2726.
2727.
2728.
2729.
2730.
2731.
2732.
2733.
2734.
2135.
2736.
2737.
2738.
2739.
2740.
2741.
2142.
2743.
2144.
2145.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
SCEF - 1
EFX -
RLI -
IF
SN
sc
EP
GO
204 E
Ii
I
203 P
R
1
SI
Gl
205 S<
P
Rl
Rl
4*4
206 IF
IF
IF
EP
SNI
SCI
GC
210 SCI
SNI
EP
***
P4 IS "
st-Rcm
R>X(I) =
RC-»(I)
RGX(I)
BE)
221 CC :
F4 '
PESI
IF i
ShPt
IF
SCEF - EXISTING IMEF. STORAGE
- AVAILABLE INTEP. STORAGE
- IPPERVICIS PINCfF CURING INTERVAL
IF (CCVER.GT.C.CC01) GO TO 204
= SNET « JCEP
* 0.0
C.C
GO TC 203
(C(VEF/COVRMX)-SCEP
IF(EP>.LT.(C.CCCin EPXaO.O
IF (FF.LT.EPX) GO TO 205
P3= FP.-EP)
RL= P3*A
FLI-PL
SCEF4if>
GC TC 206
SCEP - SCEF*FF
P3-O.C
RU=0.0
RLI-C.O
INTEPCEFTICN £VAP
r * *
IF UNLMI.NE.OJ.CR.UMIN.NE.O)) liC TO 221
IF (SCEP.LE.C.C) GC TO 221
IF (SCEP.OE.EPJM GC TO 210
- EFU - SCEP
SNET - SNET « KEP
- 0.0
GC TC it I
SCEP*SCEP-EF1K
EPIN * 0.0
FUNC. ***
I-CISTUFE IN STORAGE OLOCK
> SLRFACE CETENTICN AND INTERFLOh FHtlH 6LCCK I
SLRFJCE CETENTICN FRCM BLOCK I
- INTEPFLCH CCCPCNENT fKuM BLCCK I
* VCLLHE TO INTER. OETEN STOR. FROM BLOCK I
BEGINNING CF BICCK LOOP
ICO 1=1,!
F2 * FESE(I)
(I) = FESeU)
mO,*F4).lE.H(2*I)-l J*04FH GO TO 10
) = (f4-( I J2*N-l)vD
-------
Appendix C (continued)
2146.
2141.
2146.
2149.
2150.
2751.
2152.
2153.
2154.
2155.
2156.
2157.
2158.
2159.
2740.
2U1.
2762.
2163.
2164.
2165.
2166.
2167.
2168.
2169.
2110.
2171.
2112.
2113.
2114.
2175.
2176.
2177.
2778.
2179.
2760.
2181.
21(2.
2763.
2184.
2165.
2166.
2767.
2168.
2769.
I ISO.
2191.
2192.
2793.
2794.
27SS.
2796.
2197.
2198.
2799.
2€CO.
2801.
2EC2.
2E03.
2604.
2605.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
RXXd) « (F«-(( (2«I)-1)*D4RA/10.)>
CO TO 31
10 shRcm - o.c
25 RXX(I) > C.C
21 RGXX * ShPC(I)-F>Xm
«»» LFFEF ZCtE FIKTICN ***
FPE(I) - * SURFACE CETEMION TO OVERLAND FLOW
LZSE(I) - tPFEP 2CHE STORAGE IN EACH BLOCK
LZS - TOTAL UFFEF iOE STORAGE
RLZE(I) - ACDITlCft 1C U.2. STORAGE DURING INTERVAL
IF azsEm.ii.c.o LZSBUMO.O
LZRA(I)« LZSEID/LZSN
IF (UZRA(I).CT.6.C) GC TO 7
IF (UZR«( I ) .GT.Z.C) GC TO 8
LZIU)= 2.C= RXX(I)* FFE(i)
RGXU)=RG»«PFEU)
RGXX=C.O
RLZB(I)=-£»-RC(n-RGX(I)-RX8(I)
UZSE(n=UZ£E(l)-»RUZ6(I)
RIE(I) * F4 - F»B(I>
• * * CFFEB 2CKE EVAP * * *
REflK - «CCLM CMLY EVAF POT. FOR L.I. AND GRDMATERt I.E
PCHTICN NCI SATISFIED FROM U.Z.
IF ( (^U^'I.^E.£ UCR.dMlN.NE.O)) GO TO 290
IF (EPIh.lE-.U.CM GO TO 290
EFFECT=1.C
IF(CZRA(I).IE.2.0) GO TO 230
IF (liZSUn.LE.EPIN) GO TO 270
L.ZSBm*l.Z £^E1 « (PA*EPIN*EFFECT)*0.20
238
-------
Appendix C (continued)
26C6.
2£07.
2608.
2£09.
2610.
2811.
2612.
2E13.
2614.
2615.
2616.
2E17.
2filB.
2€19.
2820.
2E21.
2£22.
2623.
2824.
2E25.
2826.
2€27.
2E28.
2E29.
2£30.
2831.
2632.
2€33.
2634.
2E35.
2E36.
2£37.
2838.
2£39.
2640.
2E41.
2E42.
2843.
2644.
2£45.
2 £46.
2E47.
2£48.
2E49.
2£50.
2££1.
2852.
2153.
2 654.
2ES5.
2€56.
2E57.
2858.
2(29.
2£60.
2£61.
2C62.
2€«3.
2864.
2(«5.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
GC TC 2SO
27C EDIFF* EFIN - UZSBdl
REF1N= FEFU « EOIFF*0.20
ECIFF=0.0
SKET- ShET -i FA*UZSB( I)»0.20
U2S£(I)»C.O
PL2Ed)'0.0
* * * *
IMEPFLCW FUNCTION * * *
SRGX(I) - IMERflCW DETENTION STORAGE FROM BLOCK I
1NTFU) - IMERFLCW LEAVING STORAGE FROM BLOCK I
SRGX7 - TCT/L IMERPLCW STORAGE
RGX7 - TCT/L IfTERFLGW LEAVING STCAAGc DURING INTERVAL
290 IKTF(I) =• LIRC«*SRGXd»
SRGXd) = SP-CX(I )4(RGXd)*PA)-INTF(IJ
RL-Rl + IMF(I)*0.20
SRGXTj* SHOT 4 (RGXd)*PA-INTFd)>*0.20
RGXT-RGXT + IMF(I)*0.20
*** CVERIAKC FICk FOOTING ***
RXE(I) * VCLLfE TC CVERL/NO SURFACE DETENTION FROM BLCCK I
RCJE(I) = VCLUPE OF CVERLAND FLOW TC STREAM FROM BLOCK I
PtSe(I) * V(OLU»E Cf CVERLANO Q REMAINING ON SURFACE
FRCf BUCK I
Fl- RXEdl-(FEE(I*
IF (RXfi(I).lE.(FESE(I))) GO TO 34
CE= OEC*((F1)4*C.6)
GC 7C 35
24 CE» (F31/2.C
31 IF CF3.GT.(2.C*CE)) OE - F3/2.0
IF (F3.LE.O.CC5) GO TC 40
DIMV* c.o
42 RESB(I)- RXE(I)-fCSEd)
RCSE(I) PCSE(I)*PA
PCSIM(I) * FtJf(I) * INTF1I)
* * » LPFEP 2CNE DEPLETION » * *
OEEPL(I) - CIFFEFEKE IN UPPER AND LOhER ZONE RATIOS
pEPcem - UPPER zc^E DEPLETION FROM EACH BLOCK
FEFC - TCTAL L.2. CEPLETION
If^FLT - 1CTAL HFILTRATICN
PCS - TCKL C\EPL*hC FLCW TO THE STREAM FROM ALL BLOCKS
IF ((NUPI .EC. OJ.ANO.UMIN .EQ. 0))
PEPCE(I) - 0.0
GO TC 4?
GO TC 44
239
-------
Appendix C (continued)
2666.
2667.
26*8.
2«69.
2670.
2671.
2E72.
2£73.
2674.
2675.
2676.
2477.
2678.
2679.
2660.
2681.
2C£2.
2683.
2864.
2665.
2866.
2667.
2868.
2889.
2690.
2891.
2£92.
2893.
2894.
2695.
2896.
2697.
2696.
2899.
2900.
29C1.
29C2.
2903.
2904.
2905.
2906.
2907.
29C8.
2909.
2910.
2911.
2912.
2913.
2914.
2915.
2916.
2917.
2918.
2919.
2920.
2921.
2922.
2923.
2924.
2925.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
44
CEEFL(I)- ( (l2Sem/UZSN)-(LZS/LZSNI)
IF (CEEPL(I) .LE.O.C1) GO TO 47
PEPCBCI )«C.1*INFIL*UZSN*(OEEPL C.O
302 IF JSPGXT.CE.It.CCOllJ GO TO 305
LZS » LZS 4 SFCXT/PA
SRGX1 * O.C
DO 304 III* 1,5
304 SPGXIIK)- O.C
* * * LCfcEP 2C^E /KD GRCUNOHATER * * *
SE4S - E4SE
SRCh - SLP CF CFOV/TER RECHARGE
PPEL - * CF INF1LTRMICN AND U.Z. DEPLETION ENTERING L.Z
Fit - GPCLNCkATEP Ff CHARGE - IE. fCKTION OF 1NFIL.
ANC U.Z. CEFLETICN ENTERING GROWATfcR
K24L - FR/CTICN CF H^ LOST TO OEcP GAD WATER
305
LZI-l. 5*/6S I (LZS/LZSN)-!. 0)4-1.0
PFELM1.C/H.O+LZI))**LZI
IF (LZS.LT.L2SM PREL*l.O-PREL*LNRAT
3C9
F1A » (l.C-FFEL)*INFLT
IF «MM.K£.0).OR.(lMIN.NE.O)) GO TO 309
F2 = F2 4 FFEL*PfcRC
F1A » fit 4 (1.0-PREL)*PERC
L2S= LiS«F2
> F1A*(1.C - K24L)*PA
SGh*LKK44(1.0 * KV*GMS)
Rt » Pt * CfcF
SEAS* GWF
SP-Ch* F1A4K24KFA
240
-------
Appendix C (continued)
2926*
2927.
2928.
2929.
2930.
2921.
2932.
2933.
2S34.
2935.
2936.
2937.
2938.
2939.
2940.
2941.
2942.
2943.
2944.
2945.
2946.
2947.
2948.
2949.
2950.
2951.
2952.
2953.
2954.
2955.
29*6.
2957.
2958.
2959.
29 tO.
29(1.
2962.
2963.
29(4.
2965.
2966.
29«7.
2968.
2969.
2970.
2971.
2972.
2973.
2914.
2975.
2976.
2977.
2978.
2979.
29€0.
2981.
29£2.
2963.
2984.
2965.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
SCk'SGU - GHF * Fl
GhS»GMS « Fl
« * * GPCLNCKTER EVAP * * *
LCS - EVAP LCS1 FRO GRCUNDWATER
NOTE: EVAP FPO CRChATER AND LZ IS CALCULATED ONLY DAILY
IF ( (»-PFL/G.EC.C).OR.(IhRR.NE.21J) GO TO 101
IF (GfcS .CT. (.COOn GV.S =« 0.97*GHS
LCS= SGV>*H24Et0.0
« » * LChEP 2CKE EVAP * * *
AE1R - EVAP LCS1 FRC> L.2.
IF (REFIK.LT.(C.COOD) GO TO 351
LNP*T - L2
220 IF (FEPirs.U. m*LNRAT) ) GO TO 340
AETR= REP^*( 1.C-(REP1N/(2.0*KF*LNRAT)I)
GC TC 35C
340 AETR« 0.5<(KF AETR=AETR*(2.0*K3>
LZS=L2S - AETP
SK£T= ShET -i F/4AETR
ASNET AJhET + LCS + PA*AETR
351 PEFIK 0.0
1C1 SNETI = ShET - SNEI1
V.EAL Is/TEP EJLlhCE IN THE INTERVAL
ThE/L - ACCLPLL/1EO V^TER BALANCE
H8AL *
-------
Appendix C (continued)
2*86.
2*87.
2*E8.
2S89.
2*90.
2**1.
2S92.
L2S1-L2S
U2S1»UZS
PESS1»RESS
SCEPl'SCEP
SRGXTl=SPGXT
SNE11-SNET
2*S4.
2*95.
2**6.
2*97.
2*98.
2999.
2CCO.
3CC1.
3C02.
2003.
3004.
3CC5.
3006.
3007.
2C08.
3009.
3010.
2C11.
3012.
2013.
3C14.
3015.
2016.
2017.
2018.
2C19.
3020.
3C21.
3C22.
3C23.
3024.
3025.
3C26.
2C27.
3028.
3029.
3C30.
3C31.
3032.
3033.
2C34.
3035.
3C36.
2C37.
3C38.
3039.
3C40.
3041.
3C42.
3043.
3C44.
3C45.
ASEAS * ASEAJ « JflAS
ASRCH * ASFCt- 4 SRCH
APR = AFR 4 FPP
APU = API 4 Fl
ARUI = AFU 4 fUI
APOS - AFC5 4 FQS
APGXT * *FGX1 4 PGXT
IF ((NUM.NE.O.CR.dMIN.UE.O)l
AEP1K AEFIh 4 EPIN1
ASKE1 "
-------
Appendix C (continued)
3046.
2047.
3048.
3049.
3CSO.
3C51.
3052.
3053.
3054.
3C5S.
3056.
3057.
3C58.
2059.
3060.
3061.
2062.
3063.
3064.
3C65.
2066.
3C67.
2C68.
3C69.
3C70.
3071.
3C72.
2C73.
3014.
3075.
3076.
3C77.
3C78.
3C79.
3C60.
3C61.
3C82.
3C£3.
3C64.
3CE5.
3C66.
3C87.
3C£8.
3C89.
3090.
3C«l.
3092.
3C93.
2CS4.
3095.
2096.
3C97.
3C9B.
3C99.
3100.
2101.
2102.
3103.
2104.
2105.
C
C
C
C
C
S
r.
C
C
C
C
IF (hYCAL.EC.FRCC) CC TO 160
CUFUT FOR HSP LANDS CALIBRATION RUN
IF (IF .GT. 2) CC TO 170
RU « |Plp*ARM*42i6C.J/(TIMFAC*720.J
IF ETR|
1 WRITE (6,4*01) MNAWMONTH) , DAY, IHR, IHN, QMETRC
GC TC 170
16C IF (SKCW.EQ.K .Cf. PRINT.NE.OAYS) GO TO 169
StPSNh « SLf'hC
PXSNH - F>JNC
SPXh » fELPAt
RAC^EH * F/CCEC
CORKEh - CDRhEC
CCKfEH - CC^^EC
CR^IKI- * CFJIfC
SGI'H = SCMC
s^EG^^l * SKECCO
SEVAPH * SEV/fC
169 IF (CUTFLT.EC.
WRITE (6.26CI
WRITE (6,362)
VRITE (6,362)
CLTFUT FUk HSP LANCS PRODUCTION RUN ANO SUMMARIES
^ETR) GO TO 161
hRITE
VRITE
KRITE
WRITE
WRITE
IF
(C,2ti)
(6,264)
U.36C)
(£,381)
(6,361)
/FCSB.AROS
A1MF,ARGXT
AFtI
/FCSIT,ARU
A«E»S
(6,47t)
(6,479)
.._ AFF,*PR,APfc,APR.APR,APR
((SNCV.EC.NC).CR.(PACK.LE.O.OJ) GO TO 181
SNCIkMELT OUTPUT
WRITE
WRITE
WRITE
WRITE
WRITE (6,482) P/CKEh
WRITE (6,482) CO>EH
WRITE (6.48O CCF>6H
WRITE (6,48*1 CF/INH
WRITE (6,466) SCMi
WRITE (6,4£7) SfEGMH
WRITE (6,49C) F/CK
CCVR = ICO.
IF (FACK .LT. IPACK) COVR (PACK/IPACK)*100,
IF (FACK.GT.C.C1) GO TO 1078
243
-------
Appendix C (continued)
2106.
2107.
3108.
2 I OS.
3110.
3111.
2112.
3113.
3114.
3115.
3116.
2117.
3118.
•119.
3120.
3121.
•122.
3123.
2124.
2125.
2126.
1127.
3128.
2129.
2120.
3131.
2132.
2133.
2134.
2125.
2136.
2137.
2138.
3139.
3140.
3141.
3142.
2143.
2144.
2145.
2146.
3147.
2148.
3149.
2150.
3151.
2152.
2153.
2154.
2155.
2156.
3157.
215fi.
2159.
3160.
2161.
2162.
3U3.
3164.
3165.
CCVP-0.0
SOEMO.O
1C1£ WRITE (6,491) SCEh
WRITE (6,492) CCVF
WRITE (6,4€U JEVAPH
161 WRITE (6,361)
WRITE (6,26£) AEFIN, AEPIN, AEPIN, AEPIN, AePIN, AEPIN
WRITE (6,26S) A£hET,ASNET,ASN6T,ASNtT,ASNET
WRITE (6,382) CCVER
WRITE U,37C)
WRITE (6,271) U2JE,L2S
WRITE (6,272) li«,LZS,LZS,LZS,LZS,LZS
WRITE (6,372) SGV,SGW,SGW,SGW,SGW,SGW
WRITE (6,274) SC E F,SCEP,SC£P, SCEP,SCfcP ,SCEP
WRITE (6,27!) REJE,RESS
WRITE (6,37C) SFG>,SRGXT
WRITE (6,371) TVEAL
IF ((SNCW.EC.VES).AND.(PACK.GT.O.OI) WRITE
161 IF (CLTFCT.EC. EKL) GO TO 171
C
C METRIC CCNVERSICKS FCR CUTPUT
APR *«PP.*tfFIh
ARCS ^AROS^^XPH
ARGXT *«RCX74MiFlK
ARtl =ARtI«fhFIf
ARU «AR(J*^^FI^
/SEAS aASCAClfPF Ih
A£RCH =ASRCKM'Hh
AEPIN **EPIMi>Mnfc
A!NET >AS^E1*^HH^
tzsMET*^.zs*^»•FI^
Lzs^•ET»Lzs*^^'FI^
SGWMET-SGWOHFI*
SCEFCT-SCEP^^fP^
RESS^TaF.ESS*^^•Fl^
TWBLf'T-TWEAl^^MFIh
£PGXTf>£RGX14»KllN
C SKCW
IF (SNCV .EC. NO GC TO 163
SLMSM- = SOfSNhOfPIN
PXSNH = PXSM-*^'^FIN
SPXh * SPXKJ-^PH
PAOMEH * RACPEMtfPIN
CCNHEH » CChNEKhCPIN
CCPf-EH - CCFfEMffPIN
CRAINH < CR^lKKfMPIN
SGNh * SG^'^•<^^PI^
SNEGKH « SKEOMf^PIN
PACKfL > PACK4>->FIN
SEVAPI- - SEVAFMFfPIN
TSNer'L = ^s^E*^.«^^PI^
162 00 162 1=1, I
APCSE(I) >4FC£E(I)*MMPIN
AINTF(I) *AIMF(I)*KMPIN
AFCSn(I) = AFC£lT(I)*MMPIN
UZSefT(I)*l2SE(I)*MKPIN
RESefT(I)=RESE(I)*ffPIN
SRGXCT ( I )«SPG> ( I )*»>KPIN
162 CCNTIME
WRITE I6,46C)
,ASNET
(6,489)
TSNBAL
244
-------
Appendix C (continued)
2166.
2167.
3166.
2169.
3170.
3171.
3172.
2173.
-114.
3175.
3176.
3177.
3176.
2179.
3160.
3181.
3182.
3183.
3184.
2185.
3186.
3187.
2168.
3169.
3190.
2191.
31*2.
3193.
3194.
3 IS 5,
2196.
3197.
2158.
3199.
3200.
3201.
3202.
3203.
3204.
3205.
22C6.
3207.
3208.
3209.
3210.
2211.
3212.
2213.
3214.
3215.
3216.
3217.
2218.
2219.
3220.
2221.
3222.
2223.
2224.
3225.
hRITE (6,3621
hRITE (6,363) AfCS6,AROS
hRITE (6,364) A1MF.ARGXT
hRITE (6,265) AFU
hRITE (6,360 APC5I7,ARU
hRITE (6,38C) A«f«
WRITE (6,36)) AJFCH
hRITE (6,361) AFF,APP(APR,AP*fAPR,Af>H
IF (SKCV.EC.KC .CF. PACK.LE.0.0) GO TO 162
hRITE (6,411) H>ShH
hRITE (6,475) f>SNH
hRITE (6,48C) JF>H
hRITE (6,4€1)
hRITE (6,482) MCMEH
hRITE (6,4€2) CCMEH
hRITE (6,484) CCRMEH
hRITE (6,465) CFJIMi
hRITE (6,4€«) «C>H
hPITE (6,461) ffEGfh
hRITE (6,49C) FACKPL
CCVR * 1CO.O
IF (FACK.LT.1F/CK) COVR => (PACK/ IPACK)»100.
IF (FACK.G1.C.C1) GO TO 1079
CCVP » O.C
SCEN * O.C
1C7S WRITE (6,491) J) GO TO 170
SL'MSNC C.C
PXSKC C.O
HELR/C C.C
RAO'EC C.C
CCRCEC C.O
CCKPEC .0
CRAUC ,C
SOC .C
SNEGfC .C
SEVAFC .0
C
C FCFPAT STATEMENTS
C
378 FORMAT (• + • ,i 1X,F«.2,2X,F6.3)
379 FCPM/T (' •,/l£,l>,I2,2X,I2,«:l,I2)
36C FCPH/T (•0«,€>,fVATER, INCHES'!
362 FCRMM ( «0« , 1 IX .'PLNCFF* )
245
-------
Appendix C (continued)
3226.
3227.
3228.
2229.
3230.
3231.
3222.
3233.
2224.
3235.
2226.
3237.
3236.
2239.
3240.
2241.
3242.
3243.
2244.
3245.
2246.
3247.
3248.
2249.
3250.
2251.
3252.
3253.
3254.
3255.
3256.
3257.
3253.
2259.
3260.
3261.
3262.
3263.
2264.
3265.
2266.
3267.
3268.
3269.
2270.
3271.
3272.
3273.
3274.
3275.
3276.
3277.
3278.
3279.
3280.
3281.
3262.
3263.
3284.
32£5.
363 FCRMAT
364 FCRHAT
365 FCPMAT
366 FORMAT
380 FCPMAT
361 FORMAT
261 FORMAT
47£ FCRfAT
47« FCRHAT
46C FORMAT
461 FC"PAT
482 FORMAT
483 FCRMT
464 FORMAT
465 FCRMAT
486 FCRMAT
461 FORMAT
• • ,14X,«CVEPLANO FLOW ,5X,5 (F6.3 ,2X ) , IX, F8
• • , 14 X,' INTERFLOW ,9X, 5(Fb. 3 t2XJ , 1X.F8.3)
• • ,14X,MMFERVlUUS't59X,Fb. J)
• • .14X ,'IOTAL1 |13X,5(F8.3,2X) , 1X.F8.3)
•C' illX.'EASc FLUVi' ,o3X,fa.3)
• • tllX,»C-RChATER KECHARGESSSX.FS.S)
.3)
•O1 ,1 IX, 'PRECIPITATION' ,bX,5 (F7.2.JX) ,1X,F7.2)
' • ,14X,'S.AC*',65X,F7.2)
• •,14X,«PAIN CN SNOW ,57X,F7.2J
• •f^Xt'f'ELT £ R.A1N1 ,58X,F7.2>
'O1 ,11X,'>ELT« )
' • ,14>, 'RADIATION' ,60X,F7.2)
• • ,I4X, 'CONVECTION', 59X,F7. 2)
• • ,14X, 'CONDENSATION1 ,57X,F7.2)
• • ,14X,'PAIA McLT' ,60X,P7.2)
' • ,14X,'CRCUNO MELT' ,58X,f7.2>
• •«14»,«CU»' K£G HcAT' ,57X,F7.2J
490 FCRMAT ( «0 • 1 1 IX . 'SNCfc PACK* ,63X,F7.2 )
4«1 FORMAT (• -tllXt'SNCti DENSITY' .60X.F7.2)
492 FORMAT
46£ FORMAT
361 FCRMAT
366 FCRMAT
36< FORMAT
363 FCRMAT
27C FCRMAT
371 FORMAT
372 FCRMAT
272 FCRMAT
314 FCRMAT
215 FCRMAT
316 FORMAT
371 FCRMAT
46< FORMAT
460 FCRMAT
1 '.IIX.'J 5NCM CCVEK* .60X.F7.2)
•0« ,llX,»SNCh EVAP" ,63X,F7.2)
•0' ,11X,'EVAPCTRANSPIRAT1CN' 1
• • ,14X,' POTENTIAL' ,9X, 5 (F7. 2,3X) , IX,F7.2I
' • ,14X,'NET' ,15X,5(F7.2,3XJ ,1X,F7.2)
• -,14X,'CROP COVeR' ,59X,F7.2)
•0' ,llX,'STCRAGcS' )
' I,14X, 'UPPER ZONE' ,8X,5(Fd.3,2X) .1X.F8.3)
• - ,14X,'LCV«ER ZONE' ,UX,3(Fo.3,2X), IX.F8.3)
1 • ,14X,'CRCUNOHATER' ,7X,5 (F d.3 ,2X) ,1X,F8.3I
• •,14X,' INTERCEPTION' , 6X, 5( Fd.3 ,2X) , IX ,F8.
' • ,14X,'CVERLAND FLOrJ' ,5X,i (Ftf.3 ,2X ) , IX, F8
• • ,14X,« INTERFLOW ,9X, 5(F6. 3,2X1 ,1X,F8.3)
•0' ,11X,'VATER BALANCE=>',F8.4J
• (,llX,'SNCh BALANCED • ,F6.4)
•O1 ,6>,'VATER, MILLIMETERS*)
4901 FCRMAT ( »C' tA6 , IX , 12 ,2X,I2 t • : • ,12, 3X.F6.3)
C
17C APR * 0.0
AEPIN > 0.0
ARU = 0.0
ARUI •= 0.0
AROS » 0.0
ARGXT * 0.0
ASNET - 0.0
AS8AS - 0.0
ASRCH » 0.0
CC 172 I«l,5
APCSE(I) * O.C
AIMFU) > 0.0
ARCSIT(I) * C.C
172 CONTINUE
C
16C IF (SNCh.EC.m GO 7C 190
C
C ZER& HOURLY VALUES
SLMSNH - O.C
PXSKH * 0.0
RACMEH * O.C
CORK EH - O.C
CCMEh " O.C
3)
.3)
246
-------
Appendix C (continued)
3286.
3267.
3266.
3269.
3290.
3291.
3292.
4COO.
4001.
4CC2.
4003.
4004.
4CC5.
4006.
4007.
40C8.
4CC9.
4C10.
4011.
4012.
4013.
401-4.
4015.
4016.
4017.
4018.
4019.
4020.
4021.
4022.
4C23.
4C24.
4025.
4026.
4027.
4028.
4029.
4C30.
4C31.
4032.
4033.
4034.
4035.
4C36,
4037.
4038.
4039.
4C40.
4041.
4042.
4043.
4044.
4045.
4C46.
4C47.
4048.
4C49.
4050.
4C51.
4CS2.
C
C
C
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
CRAINH » O.C
SGPH * C.O
SNEGMH * O.C
SEVAPh - O.C
SPXH - 0.0
19C PETLRK
ENC
SIERCUTINE SECT
StDIMcNT EROSION MODEL
CIMENSJCN PESE(5 ) ,PESB1(5 ) ,ROSB( 51 ,SRGX(5 ), INTF ( 5 » ,RGX( 5 ) ,INFL(5) ,
1 LZSe,RJB(5),ERSN(5)
CIKENSICN SFER(J),RCBTCM(5J,ROBToT(bl,INFTOM(5),INFTOT(5),
1 ROITCM5) ,RCITC1 (5 ) ,RX8(5 ) ,ERSTCMO J ,£RSTOT ( 5 ) ,MKAH( 12 ) ,RAD( 24) ,
2 TEMPX(24),HNC><24) ,RAIN (268 ) ,UZSBMT( 5J ,R£SB*T (5 ) , SRGXPT (5) ,
3 SREPHT(S)
DIMENSICN AEPJN<5),AERSNM(5)
CI*ENSICN IST/R1J)
COMKCN /ALL/ RU ,hYMI N ,PRNTKE,HYCAL .DPST.GUT PUT.TIKFAC, LZS,AREA,
1 RESBl,FOSe,SFGX,INTffRGXfINFL,lUSfc,APtRCB,RIB,ERSN,M,P3,A,
2 CALE,FPQC,FEJT ,NLTP,£N)jL ,M£TR»BCTH,fil:SB,YES,NC,II*IN,IHR,TF»
3 JCCLNT,PRIM,IMP.,CAYS,HOUR,MNTH
CCHMCN /LANC/ f ltt> ,PRTOT, ERSNTT, PRTOW,EKSNTM,CAY,
I RUTCMtNEFTCW,RCS10H,RITuM,KIiNTOK,BAiTuMtRCHTCf,RUTOT,
2 NEP1CT,RCSKT,F ITOT .RINTOT .OASTCT ,nUHTUT ,Th6 AL, EPTOM, EPTOTt
2 OZStUZSN,LZ£N, INFIL,lNTcR ,IRC,NN,L, Si,SGWl ,PP,SGh,GWS ,KVt
4 K24L,KK24,K24El,EP,IFS,K3,£i>XM,RES^l,KcSS,SCEP,SCEPl,SRGXT,
* SRGXT1,JREP tKREF,JSER,KS£R,SRERT,MMf-lN,METGPT,SNCW,CCFAC,
6 SCF,ICNS,F,CGH,V.C»"PACK, EVAPSN.HtLE V, TiNUH ,PETMI N, PETHAX,ELDIFt
7 DEh>fPACK,CEFTl-tKNTHtSDEN,iPACK,TMlN,$JMSNM,PXSNMtXK3,
8 l•ELRA^',RAC^E^',CCP^•EHfCRAiNM,CUNME^•.,SoMM,SN£G^'H,SEVAPK,SL^•SNYt
9 PXSNY,l"ELR/Y,PEY,CORH£Y,SGMY,CCNKcY,CkAINY,SNEGMY,SEVAPY,
* 1SNEAL,CCVER,CCVfiMX,ROaTOM,ROBTCT,RXB,RJITC^,ROITOT,INFTCM,
1 INFTCT,ERSTC»',EFSTCT,SRERtTEMPX, HAD, WINUX.KA IN, INPUT
INTEGER PPMKE,h\CAL,OUTPUT,CALB,PRGO,ENGL,METR,BOTH,TIfFAC
INTEGER FEST,NLTP,YES,NO
REAL*8 PNA*
PEAL JREP, KPER, .SER, KSER
REAL EFSNT1, SFFTMT
REAL ^^PI^, ^E1CFT, KGPLB
CATA ERSNT/C.O/, AERSN/5»0.0/
CATA IASTPK/»*«/, IELANK/* •/
SEF - TRANSFCPT CAPACITY OF OVERLAND FLOW IN TUNS/ACRE
ERSN = ERCSICN PEACHING STREAM
SRER ~ FINES CEFCSI1 IN TONS/ACRE
ZEKING OF VARIABLES
247
-------
Appendix C (continued)
4CS3.
4C54.
4055.
4056.
4057.
4058.
4059.
4C60.
4C61.
4C62.
4063.
4C64.
4065.
4C66.
4067.
4C68.
4C69.
4C70.
4071.
4C72.
4013.
4C14.
4075.
4C76.
4C77.
4C7S.
4079.
4CEO.
4C81.
4CE2.
4063.
4C64.
4CC5.
40£6.
4CC7.
4068.
4Ct9.
4CSO.
4091.
4C92.
4093.
4094.
4CS5.
40S6.
4C97.
4C98.
4C99.
4100.
4101.
41C2.
4103.
4104.
4105.
4106.
4107.
4108.
4109.
4110.
4111.
4112.
C
45SS
C
C
C
C
C
4444
C
4501
C
4446
4452
C
C
4456
C
C
C
C
C
C
C
C C
C
C
SRERT > 0.0
CO 459S I«l,5
ISTAR(I) -
ERSNT =• O.C
SCIL EROSION LOOP
REP - II. 0 - CCVER)*KRER*PR**JRER
CO 4452 I-ltS
SPER(l) - SFER(I) * RER
IF URCSEdHFESEdM.GT.O.O) GO TO
EFSKMJ * G.O
SER = C.
C-C TC 444«
SER » K SRER(I) - ERSN(I)
IF (SFEFU) .LT. 0.) SRER(I) - 0.
AERSKdl * «£F£N(I) 4- ERSN(I)
CCMINOE
IF (PFMKE .EC. CJ GC TO 4490
CC 4456 I«l,I
ERSNT * EFSKT * AERSN(I)*0.2
JRERT » SFEPT .+ SRER(I)*0.2
EPSTCKI) * ERSTGH(I) + AEKSN(I)
ERSTCKI) » ERSTOTII) * AERSN(I)
CCMIME
CIMLATIVE RECORDS
ERSNTf* « ERSMM « ERSM"
ERSNTT - ERENT LOSS TO LBS.t KGS.t K6.S/HINUTE, AND
GM/L FOR OUTPUT
EPSM«2CCO,»AREA
EFSNTF4.454
ERSNTF
ERSMK
ERSKKP-
ERSNCf = EF«KTF«454./(RU*TIHFAC*60.*2d.32l
248
-------
Appendix C (continued)
4113.
4114.
4115.
4116.
4117.
4118.
4119.
4120.
4121.
4122.
4123.
4124.
4125.
4126.
4127.
4128.
4129.
4130.
4131.
4122.
4133.
4134.
4135.
4136.
4137.
4138.
4139.
4140.
4141.
4142.
4143.
4144.
4145.
4146.
4147.
4148.
4149.
4150.
4151.
4152.
4153.
4154.
'155.
4156.
4157.
4158.
4159.
4UO.
5COO.
5001.
5CC2.
5C03.
5CC4.
5CC5.
SCC6.
SCOT.
5008.
5C09.
soio.
5011.
C
C
6S2
C
ES3
4SSS
C
C
C
C
446C
4462
4461
C
C
C
4480
44E1
44E2
4484
4485
49C2
C
44C1
448$
C
44SC
C
C
C
C
C
C
C
C
C
IF (NUTP .EC. YE5) C-C TO 892
WRITE (6,4*64) ERSNTP, ERSNTK, ERSNM, ERSNCf
GO TC ES3
IF (OUTPUT. EC. ENGU .OR. OUTPUT. EU. BOTH) WRITE (6,4902) ERSNTP
IF (OUFUT .EC. >ETR) *R1TE (o,<,902) ERSNTK
IF (HYCAL.EC.CALE .ANC. PEST. EQ. NO .AND. NUTR.EO.NO)
1 WRITE (0,4999) (ISTAR( I) ,1*1 ,5)
FCRhM <«*',74X,5AU
GO TO 4487
PRINTING OF OUTPUT
IF (CUTPUT.EC. FETR) GO TO 4462
WRITE U,44EC)
WRITE (6,44(1) (4EPSMI), 1 = 1,5), ERSNT
WRITE (6,44(2) <ETCFT*2.471
CO 4461 1=1,5
AERSMk(I)=AEFJN(I )*)»ETOPT*2.471
SRERfT(I)=SPEP(l)*^ETOPT*2.471
CCNTIhUi
WRITE (6,44(5)
WRITE (6,44(1) 4EPSKP, ERSNTI
WRITE (6.44E2) SFEPM, SRRTHT
FCRfAT STATEMENTS
FCRMAT J«C' ,€>, 'SEDIMENT, TONS/ACRE')
FCRI»AT (• ' .IIX.'ERCCEU SEUIrtENT • ,4X,5 (3X,f 7.3) ,4X,F7.3)
FORMAT (• • ,11X, 'FINES D£PCS1T' ,bX,5 (JiA,F7. 3) ,4X,F7.3)
FCRMAT (•*• ,26X,4(2X,F7.2)I
FORMAT CO' ,€>,'SEOI*ENT, TCNNES/HECTARE' )
FQRP/T ('+' ,20X,F€.2)
CO 448S 1=1, J
AERSN(I) a 0.0
CONTINUE
CONTINUE
RETURN
END
SUBROUTINE /CSPE
IMPLICIT PE/ld)
OIKENSICN PESE(5),RESei(5),ROSB(5),SRGXr5),INTF(5),RGX(5),INFL(5),
1 LZSe(5),AFEFC8(«),RIB(5) ,ERSN(5)
249
-------
Appendix C (continued)
5012.
5013.
5014.
5015.
5016.
5C17.
5018.
5019.
5020.
5021.
SC22.
5023.
5024.
5025.
5C26.
5027.
5028.
5029.
5C30.
5031.
5C32.
5033.
5034.
5C25.
5036.
5C27.
5038.
5039.
5C40.
5041.
JC42.
5043.
5C44.
5045.
£046.
5047.
5048.
5C49.
5C50.
SCSI.
5052.
5053.
5054.
5055.
5C56.
5057.
5058.
SC59.
5C60.
5061.
5062.
SCO.
5C64.
5C65.
5C66.
5067.
5C68.
5C69.
5C70.
5C71.
C
C
C
C
C
C
C
C
C
C
C
,AUPRP(5J.UPRISMiil
u« «j\. * - * f *• w r n \ * i 9 wr r\ i, \ j t f Mur r\r \ s M ffurr\A^n%«*f
CIMEf^SlCN CTL(5).fFLAGC5),CAOL(5),STLC5) ,KDL(51
CCMMCN /ALL/ RL ,h\MIN,PRNTK£,HYCAL fUPSTf OUTPUT, TIKFAC, LZS, AREAf
1 RESeitPCSetSFGX«INTFTRGX.lNi'LtUZ^B,APEKC8,RIB,ERSNfM»P3«A*
2 CALe,FRCD,FEST,NLTP,ENGL,METR,BCTH,RtSd,YES, KC, IMN, IhR ,TF,
3 JCCLNT, FFIM.I MR, CAYS, HOUR, MNTH
CCMMCN /PES1C/ <1 ST,SPROTMtSPRST»<,SAST, SCSI t SCSI, LIST, U AST, UCST,K,
2 UPRITT,KGPie,FFL2,CL2,LSTR,LAS,LCS,LUS,GSTR,CAS,GCS,GOS,
3 AFMCCE,TFe*Lt
4 CEGSC»>,CEG£C7,CECUCf t
5 OEGLCl,OEGL*CEC£tNIP,OEGCON,OEGI.CH,OEGLJT,NCCfL, OUTPUT, CALB,PRCU,NUTR,PEST,ENGL,PETR, BOTH
INTEGER CESCFP,YES,NC,TIMFAC
REAL f, M, ft Kh, INFW, INfL
REAL S1STKT, S^STfT, SCSTHT, SOSTMT
REAL STSPE1, S/£t-El, SCSMET, SOSMET
PEAL t-PFIN, ^EICFT, KGPLB
PEAL ^P, MF, hCCM, KD, CT, ST , CAD
REAL LTSTM, U/STMT-, UCSTMT, UOSTHT
REAL L1SHE1, C/Sf'ET, UCSMET, UOSMET
REAL fUZ, jNFh, 1N7F
REAL KCU, CTL» £TU, CAOU
REAL KNFh, MZ
PEAL LSTRM, L/S^ET, LCSMET, LOSHET
REAL GSTRF1, G/£fETt GCSHET, GDSMfcT
REAL KCL, CU, STL
REAL CtZ,X,FF,FTCT,FPUZ,CAOL,FPLZ
INTEGER rFLAC* JFLAG« KFLAG
CATA SPS1, SASCT, SCSCT, SPRT, SPRST, SPRTT, SPRPTT/7*0.0/
CATA SPRC7, «PFF1/2*0.0/, INFH/O.O/
CATA ASPP, /!£PF<, 4SFRO, ASPRP/20*0 .0/
CATA SCSC. SFCFJ, SCSCT/ 11*0. O/
CATA LPST, l/SCT, LCSCT, UPRT/4*0.0/
CATA LCSCT, IPF F1/2*0. 0/ , JNFM/5*0.0/> UPRIT/0.0/
CATA /LPP, AUPFI, AUPRP/15*0.0/
CATA ALPRF/C.O/
DATA CT/5*C.(/,JFL#G/5*0/,CAO/5*0.0/tST/5*0.0/
250
-------
Appendix C (continued)
SC72.
5013.
5C74.
£075i
5C16.
5C77.
5C78.
5C79.
5C60.
5CE1.
5C62.
5CC3.
5CE5.
5C86.
5087.
5088.
5C£9.
5090.
5091.
£C92.
5CS3.
5CS4.
5095.
5C96.
5CS7.
5C98.
510ol
5101.
5102.
£103.
£ 104.
5105.
5106.
5107.
5108.
£109.
5110.
5111.
5112.
5113.
5114.
5115.
5116.
5117.
5116.
5119.
5120.
5121.
£122.
5123.
5124.
£125.
£126.
£127.
£128.
£129.
5130.
5121.
DATA
CATA
C
C
C
C
C
C
STST
SAST
SCST
SCST
CD CkJ
t " lj 11
esPTi
C
C
C
C
PA -
2 =
KK =
CC 5
II
F
A
I
£215 X
F
I
C
£316
C
C
C
£3Z1
5317
C
5319
CTU/5*C.C/,KFLAG/5*0/,CADU/5*0.0/,STU/5*0.0/
CTL/5*O.C/f*FlAG/i>*0/tCADL/5*0.0/,STL/5*0.0/,KDL/5*0.0/
SURFACE SOLUTICN ADSORPTION-CESORPTION KJDEL
ZEFCUG VARIABLES
> 0.0
' 0.0
' C.O
' 0.0
- 0.0
r * o.c
ACSCPPTION-OESORPT10N SOLUTION LOOP
WITH REVERSIBLE UESQftPTION
1.0 - t
= LOCCOOO.*«(M-l»
5320 1*1,£
INFh C.2*AF
FTOT = S/SU ) * SCS(l)
ASP1CT = ASFUT + PTOT
(F7CT.G1.FF) GC TO 5315
S*S
SCSU) * FILO
SCS(I) - Ch*X*INF«
JFLAG(I) > C
CT(I) = 0
GC TC 522C
I))*226512.
SOS(I) * SSTRIII
+ FP
- INFW*CMAX
O) GO TO 5316
SCSII I < C.C
IF (IM^.CE.O,
SAS(I) •* F1CT
SCS(I) « C.O
JFLAGII) * C
CTUI « 0
GC TC £22C
001) GO TO 5321
CCt-PLTE C
X BY THE ADSORPTION cUUATICN
INFWOCMAX)
C = C>/>*F1C1/(X
X = KI«*C*^M * FP
C - (F1C1/O+INFW*O) - 1.
IF (AE«(C).LE.O.Ol) GO TO 5319
C « C*FTCT/(X * INFW*CI
GC 1C £217
IF (CE5CFP .EQ. NO) GC TO 5324
251
-------
Appendix C (continued)
£133.
5134.
£135.
£126.
5137.
5138.
£139.
5140.
£141.
£142.
5143.
5144.
5145.
£146.
£147.
£148.
£149.
5150.
£151.
£152.
5153.
5154.
£155.
5156.
5157.
5158.
£15S.
£160.
£161.
£162.
£163.
5164.
£165.
£166.
£167.
5168.
5169.
£170.
£171.
£172.
£173.
5174.
£175.
£176.
£177.
£178.
517S.
£180.
51E1.
5182.
5163.
5184.
£185.
5186.
£187.
5168.
51E9.
5 ISO.
5191.
1
1
C
5324
C
£22C
C
C
C
C
C
C
£22?
C
C
C
C
£33C
C
C
C
C
C
C
CALL OSFTN (I ,CT ,(, JFLAG,CAD,KO,K, Z, NC.OM,
SCJCIJ •
(C*1NFH)*(PTOT/U*C*INFW)»
X*(PTOT/(X+C*INFH) )
CONTINUE
CO 5330
PESTICIDE REMOVAL LOOP
CS * 4C0.4«REMERSM(I>/H
IF (CS .CT. l.C) CS = 1.0
SAPS
scsm*QS
SAFS(I) * SCPS(I)
SCPS
SPPS
SAS(
SCSI
> * SAfs
= S*S(I> - SAPS(I)
- scsii) - SCPS(u
SFRC(I) =
SFCFS(l)
SPRPM) '
SPRU ) «
C.O
* 0.0
C.O
C.C
IF
ASPRS(I)
ASPPC(I)
ASPRP(I)
> SCS (I)* - SPKO(I) - SPCFS(I)
SFPC(I) » 3PKSU) + SPRP(l)
£FCF«(I)
ASFP(I) 4
ASFPSdl
* ASFFF(I)
SPR(I)
* SPRS(l)
* SPRG(I)
+ SPRP(I»
RESEKI) * C.C
CCMINtE
IF (FRNTKE .EC. C) GC TJ 5390
PFEFARATION OF OUTPUT
DC £22£
SPRT '
SFRCT
SFRST
SPRPT
SFFT +0SPRU )
SFFCT *ASPKO(I1
SFFST *ASPRS(I)
SFFFT »ASPRP(I»
S«ST - SAJT «• SASCI )
SCST =« SCSI * SCSCII
SCST -
-------
Appendix C (continued)
51S2.
£193.
£194.
£195.
•156.
5197.
5198.
5199.
5200.
•201.
5202.
£203.
£204.
5205.
£206.
£207.
£208.
£209.
5210.
•211.
5212.
£213.
5214.
£215.
£216.
£217.
£218.
£219.
£220.
£221.
£222.
5223.
£224.
£225.
5226.
5227.
£228.
5229.
£230.
£231.
£232.
5233.
£234.
£235.
5236.
£237.
£238.
5239.
5240.
5241.
5242.
£243.
£244.
5245.
£246.
£247.
£248.
1249.
£250.
5251.
C
C
I
C
C
SCSCT - SC5CT * SCSCU)*0.2
scscm = PRSTuT(l) * ASPRS(i)
SFRCTP SFRCTf * SPROT
SPFSTM =» SFRSTJ- + SPRST
SFfTT - SFFTT * SPRT
SFRCTT » SFPCTT » SPRQT
SPRPTT JFPfTT * SPRPT
SPRSTT * SFRSTT » SPRST
IF (PF.NTKE .EC. 2) GC TO 5370
IF (I-YCAL .E(. PPOC) GO TO 5340
IF (RU .17. MMM GO TO 5370
SFRTGV « IFPOT*454.
SPRTCV - (SFPCT/(RU*TIHFAC*60.*62.43))*1000000.
SPRIGS « JFPST*454.
SFPTCS • C.O
IF (EFSM.CT.0.0) SPRTCS= (SPRST/(ERSNT*2000. ) 1*1000000.
GG TC £27C
PFUTUG OF OUTPUT
£340
IF (OUTPUT.EC.
tRITE (£t53£C)
URITE ((,5311)
VRITE (t,53£2)
fcRITE (£,53£3)
VRITE (£,£3C1)
fcRITE (£>53£4)
kRITE (£,£2*2)
hRITE (6,5313)
kRITE (t,53«l)
hRITE (6t53*£)
VRITE U,53££>
VRITE «,53£1)
VRITE (6,53£S)
£341 IF (OUTFIT.EC.
»ETR) GO TO 5341
JTS, STST
<«S, SAST
JCS, SCST
JCf, SOST
JFS, SPST
<^
-------
Appendix C (continued)
£252.
5253.
£254.
£255.
5256.
5257.
5258.
£259.
£260.
5261.
5262.
5263.
5264.
£265.
5266.
5267.
5268.
5269.
5270.
£271.
5272.
5273.
5274.
5275.
5276.
5277.
£278.
5279.
5260.
£2£1.
5282.
5263.
£284.
5285.
£286.
5267.
5288.
£269.
5290.
5291.
5292.
S293.
£294.
5295.
5296.
5297.
£298.
5299.
5200.
5301.
5202.
5203.
5304.
52C5.
5306.
5207.
5208.
5309.
£210.
5211.
SPRT =SPPT*KCFIE
SPRST *SPRS1*KGFIE
SPFGT = SPRCT»KGFie
SPRPT =£PRF1*KC-FIE
DO £342 I»l,5
STSfEK I)=STS(I)*KGPLB
SASMET(I)=S/Sm*KGPLB
SCSMEK I)=SCS(I)*KGPLB
SCSPET(I)=SCS(1)*KGPLB
ASPR(I) »ASFF(I)*KGPLB
HSPRS(I) =*SPFS(I )*KGPLB
ASFFC(I) **SPFC«I)*KGPLB
ASPRP(I) =/JPFF(I)*KGPLB
£342 CCNTINLE
VRITE (6,53£C)
V.RITE It, 5363) JTSHET, STSTMT
fcRITE (6t53f2) S/SMET, SASTMT
hRITE (t,53i2) JCJMEJ, SCSTHT
hRITE (6,5361) O.C
JSPFFd) * O.C
£36C CCMIM.E
C
£39C SPST * 0.0
SASCT - 0.0
SCSCT » 0.0
SDSCT • 0.0
SPRT « C.O
SPRST « 0.0
SPPCT * 0.0
SPRPT - 0.0
C
CO 5391 I- 1,5
£391 SSTR(I) * 0.0
C
C
C
C IPPER ZONE SOLi
C
C
C ZEFCUG VARIABLES
C
ITST - 0.0
LAST * C.O
254
-------
Appendix C (continued)
5312.
5313.
5314.
£315.
5316.
5317.
£218.
£319.
5220.
5321.
5322.
5323.
5324.
5225.
£226.
5227.
•328.
5329.
5330.
£331.
5332.
5333.
5224.
5335.
5236.
£237.
£338.
5339.
5340.
£341.
5242.
5343.
5344.
£345.
£246.
5347.
5348.
£249.
5350.
5351.
£2£2.
5253.
£354.
£355.
5356.
£257.
5356.
£359.
£260.
5361.
5362.
5363.
5364.
5265.
5366.
5267.
£268.
5369.
5270.
£371.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
LCST = 0.0
LOST * C.O
LIST = C.C
*UPTCT - O.C
SCILTICN AOSORPTiQN-DcSORPTION LOOP
45202.4 - C.2 * <2£*C FT(2)/ACRE * 1 FT/U INCHES * 62.4
KK - PL2*K*2
CO 6320 IM,£
JKFMI) « *RE**Pa*(UZSB(I)+APERCB(I)+INFL( I)+RGX(I)
FTCT = U*S(I) •» LCSd) * UOS(I) + SPKP(I) + USTR(I)
ALPTCT * /LFTCT + PTOT
C5 * O.C
IF (JMFWdl .GT. 0.0) C5 =« UCS (1 )/ JNFH( I )
IF (FTCT.C1.FFLZ) GO TO 6315
L*Sd) " FTCT
LCSd) • C.C
LCSd) - C.C
KFLAG II ) * 0
CTUd) * C
GC TC 622C
6315 X - KK*CHX**M * FPUZ
PSLC = PICT - X - JHFM + JNFW(I)*O) - 1.
IF (AES(C).LE.O.Ol) GC TO 6319
C = C*fTCT/(X*JNFW(I)*C)
GC TC 6217
631S IF (JNFV(I) .LE. 0.001) X = PTOT
IF (CESCFP .EVi. NO) GO TO 6324
FJf^Fl. > JNFM(I)
CALL OSFTN ( I , C1L ,C, KFLAGt CAOU.KLU ,K ,Z ,NCOM,
1 SlLtXtHtZ.NIPtFPUZfPTCT.RJ/MfM)
6324 LOJd) « (C*JNFWd))*(PTCT/IX+C*JNFH(III)
U4£d) * X*(PTOT/(X+C*JNFktd)M
632C CCNTINLE
PESTICICE REMOVAL LOOP
LB/FT<3»
1*45302.4
255
-------
Appendix C (continued)
£372.
5373.
5374.
5375.
£376.
5377.
£378.
5379.
£260.
£281.
5382.
£263.
5384.
5365.
5386.
5387.
£388.
£389.
£390.
5391.
53S2.
£293.
5394.
5395.
52*6.
5397.
£398.
5399.
5400.
54C1.
5402.
5403.
5404.
5405.
5406.
5407.
5408.
5409.
5410.
5411.
5412.
5413.
5414.
5415.
£416.
5417.
5418.
5419.
5420.
5421.
5422.
5423.
5424.
£425.
5426.
5427.
5428.
5429.
5430.
5431.
C
£327
£229
6326
C
C
£33C
C
C
C
C
C
C
€322
6334
C
C
C
6335
C
C
C
CO 633C I«l,5
IF (JNFM(I) .IE. 0.0001J 60 TO 6327
CSP > AREA*F/* AUfF(I) * UPR(I)
AUPRKI) = ALFPKI) + UPRKI)
AUPPP(I) = ALFFP(I) + UPRP(I)
LIST * LIST « LPRIS(I)
CCMINLE
IF (PRKTKE .EC. C) GO TO 6380
fFEPARATION OF OUTPUT
DC
LPRT >
LPRIT
LPRF7
LAST •
LCST '
LCST '
LPP1 *
• IFF IT
• 11FFFT
AtPR(I)
* AUPRKI)
+ AUPRP(I)
LAST * UAS(I)
ten * ocsci)
LCST » ODS(I)
LASCM) * CIAS(I)/MUZ)*1000000.
LCSC(I) > (LCS(I)/NUZ)*1000000.
IF (U2SEII) .LE. 0.0001) GU TO 6333
UCSC(I) » (LDS(I)/(UZSB(I)*ARcA*45302
GC TC £334
LCSC(I) - C.O
UPS(I) * l/SCII) * UCSC(I) + UOSC(I)
» UASC(I)*0.2
* UCSC(I)*0.2
* UOSC(I)*0.2
IPS(I)*0.2
)*1 000000.
L'ASCT
UCSCT * tCSCT
(JCSCT > LCSCT
UPST » LPST +
LTS(I) • C*J(I) + UCStI)
fTST « LTST * UTS(I)
UOS(I) * UPRISCI)
CCNTIME
CLMLATIVE RESULTS
oc
6340 I* It5
UPITOMI) « UPITCM(I)
* AUPRKI)
256
-------
Appendix C (continued)
5432.
•432.
5434.
£435.
£436.
£437.
£438.
5439.
£440.
£441.
£442.
£443.
£444.
£445.
5446.
5447.
£446.
5449.
£4£0.
5451.
5452.
£453.
5454.
5455.
£456.
5457.
£45£.
5459.
5460.
5461.
5462.
£463.
£464.
5465.
5466.
5467.
5468.
£469.
5470.
5471.
£472.
5473.
£474.
5475.
5476.
5477.
5478.
5479.
5480.
5481.
£482.
5483.
£464.
54E5.
5486.
5487.
5488.
5489.
5490.
5491.
634C LFITC1U) " UPITCT(I) + AUPRI(I)
IPRITM * LFFITf + UPRIT
LPRITT - UPFITT 4 UPRIT
C
IF (PRKTKE .EC. 2) GC TO 6365
C
IF (HYC*L .EC. FFCD) GO TO 6341
IF (RU.LT.hYMM GO TO 6365
UPPTGfc - LFRIH454.
LPPTCW - 1CCCCCC.*LPRI T/(RU*TIMFAC*60.*62.43)
TPRTGV. = LPRTC-h + SPRTGW
TPRTCh = LFRTCV + SPRTCW
TPRTGM - TFRTGWUMFAC
SPR1GN » SFP1CS/TIMFAC
hRITE (6,6440) 1 FPTGk ,TPR TGM, TPRTCW, SPRTGS , SPRTGM.SPRTCS
GC TO 6265
C
C PFlNTIhG OF OUTPUT
C
6241 IF (OUTFIT. EC. KETRI GO TO 6342
V«RITE (6,62£0)
VRITE (6*53*1) ITS, UST
kRITE U*£2*2) LAS, LAST
V.RITE (6,53«3) LCS, UCST
V>RITE (t.5261) LCS, LOST
V.RITE (6,63<2) LFRIS, UI ST
V-RITE (6,53£41 LFS, UPST
ViRITE (6,52fZ) l«£C, UASCT
V.RITE (6,53£2) LCSC, UCSCT
V.RITE «,526i) LCSC, UDSCT
VRITE (6,52£5) *LPR, UPRT
ViRITE (6,£3£8) /LPPI, UPRIT
V»RITE U,£3fc.) /LFPP, UPRPT
6342 IF (OUTPUT. EC. EKL) GO TO 6365
C
C KETRIC CCNVERSlChS FCR COTPUT
LTSTHT=LTST
-------
Appendix C (continued)
54*2.
5493.
5454.
5495.
5496.
5497.
5498.
5499.
5*00.
5501.
5502.
5503.
5504.
5105.
5506.
5507.
5508.
5509.
5*10.
5*11.
5512.
5513.
5514.
5fl5.
5 £16.
5517.
5516.
5519.
5520.
5*21.
5522.
5523.
5*24.
5525.
5526.
5*27.
5528.
5*29.
5530.
5*31.
5532.
5533.
5534.
5535.
5536.
5537.
5538.
5*39.
5540.
5541.
5542.
5543.
5544.
5*45.
5546.
5*47.
5548.
5549.
5550.
5551.
4345
C
C
C
C
€365
C37C
C
<28C
C
£261
C
C
C
C
C
C
C
C
C
C
C
C
C
73C5
C
C
IF (OUTFIT. EC. fCTH) GO TC 6345
VRITE U«53*4) LFS, UPST
tRITE (6,53*2) L/SC, UASCT
fcRITE U,53!3) LCSC, UCSCT
hRITE U,52U) LCSC, UOSCT
VRITE (£,53"i4) /IFF, UPRT
hRITE U,<35£) UPfllt UPRIT
VRITE «,5359) *LFRP, UPRPT
ZEFCING VARIABLES
CC 6370 1*1,5
ALPFU) * C.C
«UPRI(I} « C.C
AtPPF(I) « 0.0
CONTINLE
UPST * 0.0
LASC1 « 0.0
UCSCT - 0.0
LCSCT > 0.0
LPRT - C.O
LPPPT « 0.0
LPRIT « 0.0
CC £381 I* It!
LSTRdl * fl.O
LOWER ZONE AND GROUND VATEl
SOLUTION AUStiRPTION-DESOR
JCILTICN AD SORPT lON-Dc SORPTIUN LOOP
LCS > 0.0
LAS = 0.0
LOS - 0.0
LPRP > 0.0
ALPTCT « C.C
KNFM = AFE/« (LZ!*CPST»*226512.
KK * HL2*K*2
CO 7305 !•!,:
LSTR » LJ1P + LPRP(I)
ALFTCT « /IPTCT * LSTR
CCMINLE
IF (LSTP .LE. C.0001) GO TO 7330
1-1
FTCT « 1STR
C5 * 0.0
IF (KNFK .GT. O.CI C5 » LAS/KNFH
IF (PTCT.GT.FFL2) GC TO 7315
258
-------
Appendix C (continued)
£552.
5553.
5554.
5555.
5556.
5557.
5556.
5559.
5560.
5561.
5562.
5563.
5564.
5565.
5566.
5567.
5568.
5569.
5510.
5511.
5512.
5513.
5514.
5515.
5576.
5517.
5518.
5519.
5560.
5581.
55E2.
5583.
5564.
55£5.
5566.
55£7.
55E8.
5589.
55SO.
5591.
55S2.
2593.
5594.
5595.
55<6.
5597.
55S8.
5599.
5600.
5601.
5602.
5603.
56C4.
sees.
56Q6.
5<07.
56C8.
5609.
5C10.
5611.
C
C
C
C
C
C
C
C
c
c
c
c
c
c
c
c
c
c
c
c
LAS » FTCT
LCS - 0
LCS - 0
*FL*C-m * 0
cum = c
GO TC 7320
1315 X 3 KK*CMAX«*M 4 FFLZ
FSLO = FTCT - X - KfsfV,*CMAX
IF (PSLC .LT. O.C) GC TO 7316
LAS > X
LCS « FSIC
LOS O4X*MFfc
fFLAGU) » 0
CTLdl =" C
GG 1C 7320
12lt
7311
7319
LCJ - O.C
C - C5
IF (C .LE. O.CI C 0.001
X » Kk*C**M « FPLZ
C - (FTCl/(X*KhFk*C)) - 1.
IF (A6S(C).IE.C.C1) GO TO 7319
C = C*FTC1/(X+KNFW*C)
GC TC 1211
IF (Kr-Fh .LE. O.CCl) X = PTOT
IF (DESCPF .EC. K) GC TO
C*LL CSFTN (l.CILiCffFLAG.CAOLtKOLiK.Z.HCOM,
, NIP, FPLZ, PTGT.KNFW)
1324 LOS »
LAS X*(F1CT/(X*C*KNFUI1
1*2C CCMINliE
PES1ICICE REMOVAL LOCP
LPfiP ICS*CFST/(CPST*LZS)
LOS * LCS - LFRF
LSTR - LAS « 1C! + LOS
ALPRP * ALPFF * LFRF
133C IF (PRNTKE .EC. 2) GO TO 7379
IF (PRMKE.fE.l .CR. HYCAL. EQ.CALB) GO TO 7380
FfEFAPATION OF OUTPUT
LASC = (LASmZ)*lCOOOOO.
LCSC = (LC£/^LZ)«1CCCOOO.
LCSC (LCS/(LZS«AREA*226512.J)*1000000.
FPIKTING OF OUTPUT
IF (OUTFIT.EC. ^TR) GO TO 7340
259
-------
Appendix C (continued)
5(12.
5613.
5614.
5(15.
5(16.
5617.
5(18.
5(19.
5(20.
5(21.
5(22.
5(23.
5(24.
5(25.
5(26.
5(27.
5(28.
5(29.
5(30.
5(21.
5(32.
5(33.
5(34.
5(35.
5(36.
5(37.
5636.
5(3?.
5640.
5(41.
5(42.
5(43.
5(44.
5(45.
5(46.
5(47.
5(48.
5(49.
5(50.
5651.
5(52.
5££3.
5(54.
5(J5.
5656.
5(57.
5(58.
5659.
5((0.
5(61.
5((2.
5663.
5664.
5(65.
5666.
5667.
5668.
5669.
5670.
5671.
VRITE (6,73:01
VRITE (6,7351) IJTR
VRITE (6,7252) IAS
VRITE (6,7353) ICS
VRITE (6,73*4) LCS
VRITE (6,7355)
VRITE (6,7352) USC
VRITE (6,7353) LCSC
VRITE (6,7354) ICSC
VRITE ((,7351) *IPRP
VRITE ((,7359) *IPRP
734C IF (CLTPLT.EC. IKCL) GO TO 7379
C
C PETPIC CCNVEFSKhS FCR CUTPUT
LSTRMT=LSTR*KCPl£
LASMET = LAS*K-FLE
LCShET = LCS*KFLE
LDSPET=IOS*KGFLE
ALPRf = *LPPMKGflE
VRITE ((,73fC)
VRITE ((,72
-------
Appendix C (continued)
5672.
5613.
5614.
5675.
5616.
5677.
5678.
5679.
5660.
56E1.
56£2.
56£3.
56£4.
5665.
56£6.
5687.
5688.
5689.
56*0.
56*1.
56*2.
56*3.
56*4.
56*5.
56*6.
56*7.
56*8.
56*9
51CO
5101
•
•
•
5102.
5103
5704
5105
5106
57C7
5708
5709
51 10
5111
5112
5713
5714
5115
5716
5117
5718
5719
5120
5121
5122
5123
5124
5125
5726
5127
5128
5129
5130
5£00
•
•
•
•
•
*
•
•
•
•
•
•
•
•
*
•
•
•
•
•
•
»
•
•
•
•
•
•
•
IF CCFfNTKE .KE. I) .CR. (HYCAL.EQ.CALB) ) GO TC 7580
C
C PPHTING OF OUTPUT
IF IOLTPLT.EC. >ETR) GO TC 7530
WRITE (6,7££C)
WRITE (6.73£1) CJTR
WRITE (6.72J2) CAS
WRITE (6.73J3) CCS
WRITE (6,73£4) CCS
153C IF (OLTPLT.EC. EKL) GO TO 7580
C
C METRIC CCN\ER£ICFS FtR CCTPUT
GSTRMT=CSTR«I«GPIB
GASMET»GAS*I«GFIE
GCSMET = GCS*KFLE
GCSMET = GCS*KFIE
WRITE !6t75£C)
WRITE U,13
.EX,
,11>
,11X
,ex,
,8X,
,li>
,11X
,11X
1IX,
t
i
.
t
f
•SURFACE LAYER PESTICIDE*)
PESTICIDE, L8S' ,bX, MJX.F7 .3
•ACSCRBED* ,UX,M3X,F7.3),3X
'CRYSTALLINE.' , 8X,M 3X ,F7 .3 ) ,
)*3X
,F8.
.F8.3)
3)
2X,Ffi.3l
FESTlCIOfc, PPM',6X,M3X,F7.3),3X
'FEMCVAL, LBS' , 10X,i (3X, f 7 . 3 )
t
.
i
i
ex, «F
•SEDIMENT* ,11X,^(3X.F7.3),3X
•CVERLANU FLOH*,6X,5(3X,F7.3
•PERCOLATION' , 3X,5( 3X.F7 .3 ) ,
CISSOLVED' ,10X,5(3X,F7.3) ,3X
ESTIClDc, KGS* ,aX,5(3X,F7.3)
lEX.'FEMCVAL, KGS' , 10A.M 3X ,F7 .3 ) ,
«
i
«
(•+•
(
(
(
(
(
(
(
(
<
(
(
'0
•C
1
1
1
'0
•C
1
'0
•C
'0
i
,
t
i
•
•
i
i
i
i
i
. 5>
,11>
, 11X
«72>
. 5>
,EX,
,11X
,11X
,11X
,8X,
,£X,
,11)
,£X,
,£X,
,£X,
,
t
,
•
,
i
,
,
,
•
i
*
i
i
i
•UPPER ZONE L^YER PcSTICIDE'
,3X,
,F8.
),3X
2X.F
,F8.
,3X,
,F8.3)
F8.3)
3)
,F8.3)
8.3)
3)
F8.3)
3XtF£.3)
1
•INTERFLOH* ,10X,S(3X,F7.3) .3X.F8
•INTERFLOW STORAGE* ,2X, 312X.
2(2X,Fb.3,2X,F8.3,^X,F7.3))
•LCMER ZONE L/YER PESTICIDE'
PESTICIDE, LBS' ,61X,F8.3)
'ACSCRBED' ,64X,Fb.3)
•CRYSTALLINE' ,61X,F8.3)
•DISSOLVED', 63X,Fb.3)
PESTICIDE, PPM1 ,6lA,F8.3)
REMCVAL, LBS' ,OJX,F8.3)
•PERCOLATION' .61X.F8.3)
PESTICIDE, KGS' ,61X,F8.3)
REMOVAL, KGS' ,63X,Fb.J>
GRCONDMATER LAYER PESTICIDE*
F8.3
I
)
.3)
),3X,F8.3»
261
-------
Appendix C (continued)
5E01.
5602.
5603.
5604.
5605.
56C6.
5EC7.
56C8.
560-5.
5610.
5611.
5812.
5613.
5814.
5615.
5616.
5E17.
5818.
5619.
5620.
5821.
5622.
5623.
5824.
5625.
5826.
5827.
5628.
5629.
5830.
5621.
5632.
5633.
5634.
5635.
5836.
5837.
5638.
5639.
5E40.
5641.
5642.
5643.
5644.
5E45.
5646.
5647.
5648.
5E49.
5650.
5651.
5652.
5E53.
5E54.
5655.
5t56.
5E57.
5658.
5859.
5660.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
*
SLBCGUTINE CStTN ( I ,CT,C, JFLAG ,CAD,KO,K,Z,NCOf t
1 ST,X,M,NIP.FP,PTCT,1NFW)
ClfENSKN CT(5) ..iFLAGlS) , CADI 5} ,KD15 ) ,STi 5)
INTEGER I,JfLAC
REAL CT,C,C/C,KCtK,2,NCOM,STfX,M,NlP,FP,PTOTf INFW
THE OESCPFTICN /LGCP1THM IS BASED ON THc FREUNDLICH EQUATION; THE
C1FFERENCE BEING 1MT TI-E CONSTANT IK) AND EXPONENT (N) OF THE
DEJCRPTICN ECUATICN CIFFER FROM THc ADSORPTION VALUES. OESCRPTICN
CCCURS hhEN THE CCKENTRAT ION OF PESTIClUc IN WATER (C) IS LESS THAN
TI-E CCNCENTRATKN (CD AT THE LAST TIMt STEP. ThE DESORPTICN
EXFCNENT (NP -- INFLTTEO BY THE USER) ANU THE DESQRPTION CONSTANT
(KC — CALCULATED E* SETTING THE DESORPTiUN EQUATION EQUAL TO THE
ACJCRPTIGN EGL/TICN AND SOLVING FOR Kl>) THfcN DEFINE THE NEW DESORP-
TICN CURVE. TI-E ASSLMFTICN OF RtVefcSIbLfc OESUhPTIQN IS MADE. ONCE
CESORPTICN STCFS AtSCRPIIu.N BEGINS BY MCViNG BACK UP TH€ OESORPTION
CLFVE UNTIL IT 1NTEP!ECTS THE ADSORPTION CURV«£ (I.E., WHEN C EGUALS
OC — TI-E CCNCENTPmCN OF PESTICIDE IN WATER AT WHICH TI-E ADSORP-
TICN AND CESCPF1ICN CURVeS INTERSECT). THEN ADSORPTION CONTINUES UP
TI-E ADSCBF1ICN CLPVE UNTIL UESCRPTICN UCCUkS AGAIN. OEFINTIONS CF
TI-E DESORPTICN VJRIIELES FOLLOW BELOW.
Cl : CCNCENTRATICN OF PESTICICE IN WATER (LB/LB)
n TI-E LAST TIME INTERVAL
CU : CCKENTRAT10N C AT HH1CH THE ADSORPTION AND
CESOFPTION fcgUATIONi MEET. CAC IS SET
ECUAL TU CT WHEN UE5LRPTION BEGINS AS A
I**RKER TO LATER OETcRMINE WHEN THE ADSORP-
TICN PKCCtSi LEAVES THc REVERSIBLE DESCRP-
TICN CUhVE AND RcTUK^S TO THE NON-REVERSIBLE
ACSCPPTION CURVE
ST : CCNCENTRATION OF ADSORBcO PESTICICE IN THE SCIL
UE/L6) AT THE LAST TIME INTERVAL
JFLAG : FLAG WHICH NOTES WHcTHcK C MAS CALCULATED CN THE
ADSORPTION CURVE DURING LAST TIME STEP
-------
Appendix C (continued)
5E61.
5662.
5663.
5E64.
5665.
5666.
5867.
££68.
5669.
5670.
5671.
5672.
5E73.
5614.
5675.
6COO.
6CC1.
6002.
6C03.
6C04.
6C05.
6CC6.
6007.
6CC8.
6CCS.
6010.
ten.
6012.
6013.
6014.
6015.
6C16.
6C17.
6018.
6C19.
6C20.
6021.
6022.
6023.
6C24.
6025.
6026.
6C27.
6C28.
6C29.
6030.
6031.
6032.
6C33.
6C34.
6C35.
6036.
6C37.
6038.
6C39.
6C40.
6C41.
6042.
6043.
6044.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
53S5 JFLAG(I) - 1
CTU) » C
GO TO «2S£
J3«6 IF (JFUGfll.EC.C) GO TO 5397
IF (C.LT-CAC(I) ) GO TO 5393
!3S1 JFLAG(I) » C
CTU) » C
£T(Ii » X/l«
CAD(I) > 0
53S6 FETLRN
END
),SAS(p) ,5CS<5) ,SOS(5) ,SSTP(5),
2 LAS (5) fUCS(5),LCS(i)fUSTR(5t ,UPRIS(d),UPRISM(5)*
2 STSNET ( 5) ,£ AJf El (5 ) t
4 SCSMET(5),£CSf ET(5),UTSMET(5) ,UASHET(p),UCSHET(5),UOS^ET(5»
CCMMCN /ALL/ FL ,!-^FlN,PRNTK£,HYCALfDPST, JUT PUT, TI KFAC, LZS,AREAt
1 RESBl,PCSe,£RG>,INTF,R(.X,INFL,UZSB,APckCBfftIB,EP.SN,M, P3,A,
2 CALBfPRCC,FEST , MTR ,cNGL ,METK, BCTHfRESd,YcS,NQ,ICIN,I(-R»TFt
2 JCOUN1,PRIM,IMP,CAYS,HCUR,MNTH
COHMCN /PES1C/ 51ST,£PROTMfSPRSTMtSAST,SCST,SCST,UTSTfUAST,UCST,Kt
I LCSTtFF,C^*>f^J,£FFCTT,SPRSTT,rtUZ,FPUZ,UPRIT^•t
2 UPRITT,KGPie,FFL2,fLZ,LSTR,LAS,LCi>,LDS,ii3TR,GAS,CCS,GDS,
2 AFHCCEfTFe/Lt
4 DEGSCJ-,DEGiCT,CEGUC^,
* DEGUCT,OEGL,CEG<,NIP,DEGCQN,OEGLCM,DcGLOT,NCCH,
6 PRSTCf fPRSTCTtPFCTCCfPROTOT, JPITQH, UPITOT.STS.UTStSASt
7 JCS.SOJ,SS1F,L/£,LiCStUDS,USTR,UPKIStUIST.TOTPAP,TIMAP,YEARAPt
8 DESORP.SllRF.SCUtSLLG
REAL LSTP,t/£,lC£»LCS
REAL ffFU, mCPT, KGPLB
INTEGER API»CCE,PFNTKE,HYCALtOUTPUTfCALB, PROD tENGL,METRt BOTH
INTEGEF SLFF,SCIL,TIMFAC
DEGRADATION OF PcSTICIUE FROM ADSORBED (A),
CRYSTALLINE (C) , AND DISSOLVED (0) FORMS
OEGCON * FIRST ORDER DECAY RATE (PER DAY)
263
-------
Appendix C (continued)
6C45.
6C46.
6C47.
6C48.
6C49.
6C50.
6C51.
6C52.
6C53.
6C54.
60*5.
6056.
6C57.
6C58.
6059.
6060.
6061.
6062.
6063.
6C64.
6C65.
6C66.
6C67.
6C68.
6C69.
6C70.
6C11.
6C72.
6C73.
6C74.
6C7S.
6C16.
6077.
6078.
6C19.
6CCO.
6CE1.
6CE2.
6063.
6CE4.
6C85.
6C66.
6C£7.
6C68.
60E9.
6090.
6091.
6C92.
6093.
6CS4.
6C95.
6CS6.
60S7.
6CS8.
6CS9.
61CO.
6101.
6102.
61C3.
6104.
C
C UPPER ZONE
C
OEGU * C.O
IF (UTST .LE. O.C1 GC TO 8021
UST =« C.O
CO E02C I*l,£
CEGL/ = CEGCCMUAS(I)
LAS(I) = US!!) - CEGUA
UAST = LAST - CEGUA
CEGLC * CECCCMUCSU)
UCS(I) = LCSdl - OEGUC
UCST = UCST - CEGUC
DEGLC = CECCCMUOSUl
UCSU) = LCS(l) - OEGUO
UCST » LEST - CEGUO
CEGU = CEGL 4 CEGUA * OEGUC * OEGUO
LTS(I) * L'S(I) 4 UCS(I) * UOSU) + UPRISfl)
LTST * LTST + LTSUJ
8020 CONTINUE
C
C SURFACE ZONE
C
6C21 CEGS = C.C
IF (STST .LE. C.C) GO TO 8023
STST = 0.0
00 8022 1*1,5
CEGS* * CEGCCMSASU)
SAS(I) * S/SU) - OEGSA
SAST = SAST - CEGSA
CEGSC - CEGCCMSCS(I)
SCS(I) > SCS(I) - OEGSC
SCST - SCST - CEGSC
CEGSC > CECCCMSDS(I)
SDS(I) = iCS(I) - OEGSO
SCST * SCJT - CEGSO
OEGS - CECS 4 CEGSA 4- CEGSC * DEGSO
STS(l) = SAS(I) « SCSUJ 4- SOS(I)
STST = STST 4 STS(I)
EC22 CCNTINLE
C
C LOWER ZONE
C
£023 CEGL * 0.0
IF (LSTF .LE. O.C) GO TO 8090
CEGLA = DEGCCK*LA£
LAS * LAS - CEGU
CEGLC * DEGCCMICS
LCS = LCS - CEGLC
CEGLC * DEGCCMICS
LCS * LCS - CEGLC
DEGL = CEGL/ 4 CECLC * OEGLO
LSTR « LAS 4 LCS 4 LOS
C
£090 CCNTULE
C
C
C
C CLKLMIVE RESULTS
C
264
-------
Appendix C (continued)
61C5.
£106.
61C7.
6108.
61C9.
6110.
till.
6112.
6113.
6114.
6115.
6116.
6117.
6118.
611S.
6120.
6121.
6122.
6123.
6124.
6125.
6126.
6127.
612B.
6129.
6120.
6131.
6132.
6133.
6134.
6135.
6136.
6137.
6138.
6139.
6140.
6141.
6142.
6143.
6144.
6200.
62C1.
6202.
62C3.
62C4.
6205.
62C6.
6207.
6208.
6209.
6210.
6211.
£212.
6213.
6214.
6215.
<216.
6217.
6218.
(219.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
c
C
c
c
c
c
c
c
c
c
c
c
CEGSO » OEC5CI" * DECS
CEGSOT CEGSCT * DECS
CEGUCN - CECUf * DEGL
CEGLCT CECLCT < DEGU
CEGLCf * CEGICP -» OEGL
CEGLOT = CEGLCT + OEGL
TCEG * CEC-S » DEC-l * CEGL
IF ((FRNTI«E ^E. 1J.OR. (HYCAL.EQ.C ALB » ) GO TO £600
IF (CUTFUT.EC. *ETR) GO TO 8200
fcRITE (6,i505)
V.RITE (6, £501) TCXEG
WRITE U,Ef02 1 DECS
WRITE (6,£5C2) DEGU
WRITE (6,{f01) OEGL
€2CC IF (GLTFLT.EC. ENCL) GO TC 8600
METRIC CC^VEPS1C^S FCR OUTPUT
TDEGKT=TDEG*KGFIE
CEGSNT=CEGS«KCPie
CEGLKT=CEGO*KCFIE
CEGL^T*CEGL*KGPIE
WRITE (6,85C6)
WRITE (6.85C1) 1CEGKT
WRITE U.65C2) CEGSM
WRITE (6.85C2) CECU*T
WRITE (6.65C7) CEGLfl
£5Cl FORPAT • ',£>, 'TCTflL1 ,71X,F7.3)
£502 FCPPM • •,£),'FFCH SURF ACE1 ,64X, F7.3)
E5C3 FCRMM • •,£>t'FFG^ UPPER ZONE1 tblX fF7.3)
£505 FORMAT • C • , 5Xf • FESTICIDc OEGRAOATICN LOSS* LBS.M
£5Ct FCP^AT «0' ,5X,«FEST1CIOE OtGHADAT ION LOSS, KGS.'I
l5C~i FORMAT • •,E>,'FPO LOWER ZQNc1 , 6lX ,F7.3 )
£6CC RETLRN
END
SUBROUTINE MTP1C ( ICERRt INTRVL tNAPP ,SNAP Lt UNAPLt TIMHR,
1 INPUT, OUTPUT, APDAYfKNIfKPI 1
THIS SLBROUTINc RcAOS NUTRIENT INPUT SEQ
*
FOR REACTION KATti, INITIAL STORAGES, AND
APPLICATIONS. INPUT iNFCRMATICN IS SCANNED
FOR ERKORS WHICH ARE FLAGGED BY ICERR=l.
CN RETURN TO MAIN IOCRR=I WILL STOP THE
SUBROUTINE ALSO OUTPUTS REACTION RATES,
INITIAL STORAbcS, AND APPLICATIONS
DECLARATIONS
CCMHON VARIABLES
RUN
265
-------
Appendix C (continued)
6220.
(221.
6222.
6223.
6224.
6225.
6226.
6227.
6228.
6229.
6230.
6231.
6232.
6233.
6234.
6235.
6236.
6237.
6238.
6239.
6240.
6141.
6242.
6243.
6244.
6245.
6246.
6247.
6248.
6249.
6250.
6251.
6252.
6253.
6254.
6255.
6256.
6257.
6258.
6259.
6260.
6261.
6262.
6263.
6264.
6265.
6266.
6267.
6268.
6269.
6270.
6211.
6272.
6273.
6274.
6275.
6276.
6277.
6278.
6279.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
1
1
INTEGER 44 1S1EF ,KSTEP,SFLG,UFLG,LFLG,GFLG
REAL** CEL1,HE*F(4,24),
1 SM20,5I,SNT(20), SNRSM<20,5) ,S*ROM(20»5) ,
2 UNC2C.5 l,lNT(20),UNI(20,i) ,UMT(20) ,UNRIM(20,5),
3 NRSM2C.S), LM20) ,LNRPM(20) , GN(20),
4 SNREK l2C,5),UNRBM{20,S>),LNRbh(20),GNRBM(20),TNRBV(20)»
5 SNP«Y«2C,5) ,SI\KUY(20,5),UNRI YUO ,5),NRSY(20,5» ,
6 LNRFY(2C),SNR8YUO,5) , UNR6Y( 20,P) .LNRBYI20) ,GNRBY(20) ,
7 TNREY(2C»,TNRhV(20),TNRhVM120).TNRHVY(20),TNA,TPA,TCLAt
8 KM 1C,«),T(-KM10) ,KP(5,4),THKP(&) ,NEALf PHBAL ,CLB H.
CCMHCN /MT/ Ctn,STEMP,SN,iNTtSNRSM,SNROM,UK,UNT,UNI ,UMT,
2 Sr'R«Y,SMCY,UNRIY,NR;>Y,LiiiRPY,SNRBY,UNRBY,LNRElY,GNRBY,
3 lKPEY,TNRhV,TNRHVM,TNKHVY,TNA,TPA,TCLA,
4 KN,TI-Kf>,KP,THKP,NdAL,PhbAL,CLBALt
5 TSTEF,NSTEP,SFLG,UFLG,LFLG»6Ft.G
INTEGER** hAFPL«KAPP,TIMHAR,TIMHR
KAHELIST /^L^RI^/ TSTEP,NAPPL,TIMHAR
INTEGER** N£1R1,KENO,APDAY(5),1GERR,ICHK,IZCNE, IELK.J,
1 I^FPl.INPCT,OUTPUT
REAL*4 SNAFL(2C,5»5),SNAPLT(20),UNAPL(20,3,5).UNAPLTC20 I ,
REAL*8
CCNC, LEF«C/«LB/AC' /,
EUNK8/1
KGPHA/ 'KG/HA' /,
•/
NTRT/' NUTR IENT» /,
CHARACTER STRINGS USED TC COKPARE AND
INTERPRET INPUT SEQUENCE, NAHES OF
RcACTION RAT£S, AND INPUT UNITS OPTION.
INTEGER** CH*R,T>PE,BLANK/' •/,
I PHCJ/'PHCJ1/, CHLO/'CHLC1/,
2 UPPE/'tFFE'/, LOHE/'LOKE1/.
3 IMl/'IMT/i APPL/'APPL'/,
R£AC/«k£AC'/, NITR/•NITR•/,
ENQ/'ti^O •/, SURF/'SURF'/,
GRJU/'GKOU'/, TEMP/»TEHP'/t
METR/'McTPV, ENGL/• ENGL'/.
5
6
Kl1
KAM1
KM',
1 K21. '
1 KIM", '
KIM*. •
KK21
KKIM*
KPL'i
1 K0« ,
1 KSA', '
KSA'. •
KPL»,
KAS'/t
KAS'/
INITIALIZATION OF STORAGES AdO FLAGS
IOERR * 0
SFLG » 1
LFLG » 1
LFLG > 1
GFLG » 1
CC 130 J*1,2C
DC 120 ieiK'lt5
(.N(J.IELK)
LM( JiieiC
CCKTIMJE
LN(J) =• C.C
GN(J) * C.O
CCMIKLE
0.0
C.O
' 0.0
266
-------
Appendix
£260.
6261.
6262.
6263.
(284.
6265.
6286.
6267.
£288.
£265.
£290.
6291.
£292.
£293.
£254.
£295.
6296.
£297.
£2S8.
£299.
63CO.
£301.
(2C2.
6203.
£304.
£305.
£3C6.
£2C7.
£308.
£309.
£310.
£311.
£212.
(213.
£214.
£215.
£316.
(217.
£3l8.
£219.
£220.
£221.
£222.
£323.
£324.
£325.
£226.
6327.
£228.
6329.
£330.
£221.
£332.
6333.
£234.
£335.
(236.
£337.
6338.
£339.
C (continued)
122
134
12£
C
C
126
142
C
C
C
C
C
C
C
C
145
C
C
C
C
C
150
160
CO 135 IZChE«l,4
DC 122 -=1,1C
KM(J,I2ChE) * 0.0
CCMINLE
CC 134 v-l,S
KFI(J,I2OE) = 0.0
ccMiiae
CC NT IN IE
READ (£,2CC1) CI-JR6
IF (CHAP8 .EC. ELANK8I GO TO 136
IF (CMR8 .EC. MFT) GO TO 142
IOEPP = 1
hRITE (£,4JS«I CHARS
RETLRN
REAC (5.MTFIM
WRITE (£,46CCI
ViRITE (£,4CCS)
hRITE (£,4CC7)
fcRITE (£,4CC£>
ViRITE (£,4£1C) 1 0 MIN) AND CHECK THAT TSTEP IS
AN INTEGER MULT iPLc Uf ThE SIMULATICN
INTERVAL (5 OK 15 MINI .
CELT IS THE TIME JTEP IN HOURS BECAUSE
REACTION RATES ARE PER HCUR (INTERNALLY!.
IChK - 0
IF ( MCC(14«CtTnEP) ..Ne. 0) ICHK = i
IF ( fCCHSTEF.IMRVL) .NE. 0) ICHK*1
IF (IChK .EC. 0) GC TO 145
WRITE U.477O TSTEP
TSTEF = £0
DELT * 1STEF/£0.
f.STEF 144C/1STEF
INPUT REACTION RATES
PEAC (5,30CC) It-tR
IF (CMR .EC. eiAhK) GO TO 150
IF (CH/R .EC. RE/C) GO TO 160
ICEPR - 1
WRITE (£,4£1
-------
Appendix C (continued)
6340.
6 241.
6342.
6243.
6344.
6345.
6246.
6347.
6348.
6349.
6250.
«251.
6352.
6253.
6354.
6355.
6356.
6357.
6358.
6359.
6360.
6361.
6262.
6363.
6364.
6365.
6366.
6267.
6368.
6269.
6270.
6371.
6372.
6373.
6374.
6275.
6276.
6277.
6278.
6379.
6380.
6361.
6382.
62£2.
63E4.
63E5.
62£6.
6387.
6368.
63E9.
6390.
6291.
6392.
6293.
6394.
6295.
6296.
6397.
6398.
6399.
C
C
C
170
ISO
C
190
C
2CO
C
2C5
C
210
C
C
C
220
230
C
RETURN
NITROGEN RATES
REAC (5.3CCO CHAR
IF (CH/R .EC. SIPF) GO TO 180
ICERR « 1
WRITE (6.462C1 TYPE
WRITE (6.463C) SURF. CHAR
RETLRN
PE*C (5,301C) (KM(J.l),J»l,lO)
REAC (£,3CCC) CHAR
IF (CHAP .EC. UFFE) GO TO 190
IOERR 1
WRITE (6,462C) TYPE
WRITE (6«463C) LPPE, CHAR
RETLRN
RE«C (5.301O (KM(J,2) ,J*1( 10)
READ (5.3CCC) CH/R
IF (CH*P .EC. LCWE) GO TO 200
ICEPR - 1
WRITE (6,462O TYPE
WRITE (6,<63C) LCWE, CHAR
RETURN
REJC (5,3010 (*MU,3),J*1,10)
READ (5,2CCC) CHAR
IF (CHAF .EC. GFCL) GO TO 205
IOEPR - 1
WRITE (6.462C) TYPE
WRITE (6,4(30 GRCU, CHAR
PETLPN
RE4C (5,3010 (KM(J,4),J=l,lOi
REAC (5,3CCC) CH/R
IF (CH#P .EC. llt-f) GO TO 210
ICEPP - 1
WRITE (6,4£2C) TYPE
WRITE (6.463C) TEKP, CHAR
RETLRN
RE/>C (5,201C)
GC TC 160
,J=1,10)
PHOSPHORUS RATES
PEAC I5.3CCC)
IF (CH/iR .EC. Sim GO TO 230
IQERR = 1
WRITE (6t462C) 1YPE
WRITE <6,463C) SURF. CHAR
RETLRN
RE«C (5,301O (KFI
(5»30CC) CMR
IF (CHAR .EC. LFFE) GO TO 240
IOERR = 1
WRITE (6,4620 TYPE
WRITE <6«463C) LPPE, CHAR
268
-------
Appendix C (continued)
£400.
6401.
£402.
£403.
£404.
6405.
6406.
6407.
£408.
6409.
6410.
£411.
6412.
6413.
£414.
6415.
£416.
£<17.
£418.
£419.
6420.
6421.
£422.
£423.
(424.
(425.
6426.
€427.
£428.
£429.
6430.
6421.
£432.
£433.
6434.
£435.
£436.
£437.
£436.
£439.
6440.
£441.
6442.
£443.
6444.
£445.
£446.
£447.
£446.
£449.
£450.
£451.
£452.
£453.
6454.
£455.
£456.
6457.
£458.
£459.
240
C
250
C
260
C
21C
C
C
C
C
3CO
C
C
C
C
C
C
C
C
C
C
C
C
€
C
C
PETLPN
RE40 C,301C)
REAC (5.300CI O/P.
IF (OAR .EC. LCVE) GO TO 250
ICEPP = 1
kRITE (6.462C) WE
HR1TE U,/£3C1 LChE, CHAR
RETLPN
READ (5.301C) IfcFI C J ,3) , J«l,5)
REAC (5.30CC) O/R
IF (CHAR .EC. GFCU GO TO 260
IQERR * 1
ViRITE (6,4£2C1 1VPE
V.RITE U,*£3C1 GRCU, CHAR
PETLPN
READ (5.301C) (KPK J ,41 , J=«lt5l
READ C5.30CC) CI-/R
IF (CHAP .EC. TE*F) GO TO 270
IOEPR * I
VRITE (6.462CI TYPE
WRITE U,«3C) TEMP, CHAR
RETURN
REAC (5t3ClC)
GO TO 160
OUTPUT OF REACTION RATES AND TEMPERATURE
CORRECTION FACTORS.
HRITE |6t4£!CI
L
HRITE (£,46£C)
(KNNAPEUl.J-lflO) *
(» 0.0
2) VALIDITY OF NUMERICAL SOLUTION TECHNICUE
THE EXPRESSION K.NK J, IZONE) *DELT IS THE
FRACTION OF THE CONST ITUTENT REKCVEO
DURING THE TIMESTfcP. THIS NUMBER SHOULD
BE MUCH LESS THAN 1. FOR ACCURATE SOLUTION
CHECK SET AT 0.5.
3) ON OR OFF, IF KNI AND KPI ARE ALL ZERO FOR
A ZONE, THEN NO TrtANSFORPAT IONS *RE DCNE.
S»U,L, AND toH-G ARE FLAGS TO INDICATE
IF TRANSFORMATIONS ARE DONE (II CR NOT(O).
CO 311 IZOE-lt*
SLM * G.C
CO 303 J"1,K
KMfJ,I2OEI = KNI(J,lZONEI/24.
IF (KM(J,12CNE) .GE. 0.0) GO TO 301
ICEFP * I
VRITE (6,47801 KNNAMEU), IZONE, KNKJ.IZONEI
RE1LFN
IF (Cm**M(J«IZONE) .LT. O.f>) GO TO 302
hRITE (£,41.9C) KNNAME(J), IZONE
269
-------
Appendix C (continued)
6460.
£461.
6462.
6463.
6464.
6465.
6466.
6467.
6468.
6469.
6410.
6471.
6472.
(473.
6474.
6475.
6476.
6477.
6478.
6479.
64EO.
6481.
6482.
6483.
6484.
6465.
6486.
6487.
6488.
6489.
6490.
64S1.
6492.
6493.
6494.
6495.
6496.
6497.
6498.
6499.
65CO.
6501.
6502.
6503.
6504.
6«05.
65Q6.
6507.
6508.
6509.
6510.
6511.
6112.
6513.
6514.
6515.
6516.
6517.
6518.
6519.
302
303
3C4
3C5
3C6
307
ace
3C9
310
311
313
314
C
C
C
C
C
319
320
330
340
350
C
SI? = SIP « KM I U, I ZONE)
CONTINUE
CO 306 wit!
KFUJtHOEl - KPK J,IZQNE)/24
IF (KF!(U,12CNE) .GE. 0.0) GO
1CEFP « 1
WRITE U,48CO) KPNAMEU) ,
RETLFN
IF (CELT*1 = SO -t KPI(J,IZONE)
CGMIME
IF (SUf .IT. C.OCC01) GO TO (307
GC TC 211
SFLG = C
GC TC 311
UFLG » 0
GC TC 311
LFLG « 0
GC TC 211
GFLG * 0
CCNTINLE
CO 313 J=IilC
IF (THKN(J) .CE. 1.0) GO TO 313
WRITE (6,4612) KNNAHE(J)
CCNTINLE
CO 214 J=l,5
IF (THKP(J) .GE. 1.0) GO TO 314
hRITE (6,<€14) KPNAMEU)
CCNTINLE
•
TO IQt
I ZONE, KPHJ.IZCNEI
) GO TO 205
I ZONE
,308.309,310) , IZONE
INPUT CF INITIAL NUTRIENT STORAGES
READ (5.3CCC) CJ-/R
IF (CH/R .EC. el/^K) GO TO 319
IF (CH/P .EC. IMT) GO TO 320
IOEPR » 1
VtRITE (6,466!) CHAR
RETLRN
RE/10 (5,30CC) TYPE
IF (TYPE .EC. El/MO GO TO 320
IF (TYPE .EC. MTR) GO TO 330
IF (TYPE .EC. FI-CS) GO TO 340
IF (TYPE .EC. CUC) GO TO 350
IF (TYPE .EC. EH:) GO TO 560
ICEPR « 1
tiRITE (6,472!)
WRITE (6.474C) TYPE
RETLRN
NSTRT * 1
NENC = 7
GO TO 36C
NSTRT = 11
NENC = 14
GC TC 36C
NSTRT » 20
NENO * 20
270
-------
Appendix C (continued)
6520.
6521.
6522.
6523.
6524.
6525.
6526.
6527.
6528.
6529.
6530.
6531.
6532.
6533.
6524.
6535.
6536.
6537.
6538.
6539.
6540.
6541.
6542.
6543.
6544.
6545.
6546.
6547.
6548.
6549.
6550.
6551.
6552.
6553.
6554.
6555.
6556.
6557.
6558.
6559.
6560.
6561.
6562.
6563.
6564.
6565.
6566.
6567.
6568.
6569.
6570.
6571.
6572.
6573.
6574.
6575.
6576.
6577.
6578.
6579.
C
C
360
365
370
360
390
C
4CO
410
42C
43C
C
C
C
440
450
460
470
4£C
C
49C
SCO
SURFACE
PEAO (5,3020) CMR, NBLK
IF (CHAP .EC. SIPF) GO TO 365
IOEPP * 1
WRITE (6.467C) 1YP6
WRITE (6.463C) SLRF, CHAR
PETUPN
IF (NBLK.EC.C .CP. NELK.EQ.l .OR. NBLK.tQ.5J GO TO 370
IOERR * 1
WRITE (6.467C) 1YPE
WRITE (6.469O SURF, NBLK
RETURN
IF (NBLK .EC. 5) GC TO 400
READ (5,301C) (£NT(J),J=NSTRT,NENDJ
CC 390 J=NJTPT,NEND
DC 3EO IEIM1,5
JMJ.1EIK) - SNT(J)
CCNTINUE
CCNTINUE
GO TC 440
CO 41C IELM1,«
REAC (5,2010) (SN(J,IBLK),J-NSTRT,N£NO)
CCNTINUE
CC 430 J=N£TPT,NENO
SUM > O.C
OG <2C IELK-1,5
SLM = SUC * SN4J.IBLKJ
CCMINLE
SNT(J) SLH/5.
CCNTINUE
UPPER ZONE
READ (5,3C2C) CI-AR, NBLK
IF (CHAP .EC. UFFE) GO TO 450
ICEPP - 1
WRITE (6,467C) TYPE
WRITE U.463C) UPPE, CHAR
RETURN
IF (NGLK.EC.O .CF. NELK.EQ.l .OR. NBLK.EQ.5) GO TO 460
ICERR - 1
WRITE (6.467C) TYPE
WRITE (6,469C) LPPE, NBLK
RETURN
IF (KBLK .EC. 5) GC TO 490
REAC (5,301C) (LNT(J),J=NSTRT,N£NOI
CO 46C J=^^FT,^END
CC 470 IELK'1,5
UNtJ.ieiK) ' UNT(J)
CCNTINUE
CCNTINUE
GC TC 520
CO 50C IELK*1,5
PEAC (5,2010) (UN(J,IBLK),J=NSTRT,NEND)
CONTINUE
CO 520
SUP * O.C
271
-------
Appendix C (continued)
4180.
6561.
6*82.
6583.
6564.
6585.
6566.
€567.
6588.
6589.
6590.
6591.
6592.
6593.
6594.
6595.
6596.
6597.
6598.
6599.
t>t CO.
66C1.
6602.
66C3.
6604.
6605.
66C6.
6607.
6608.
66C9.
6(10.
6611.
6612.
6(13.
6614.
6615.
6616.
6617.
6618.
6619.
6620.
6621.
6622.
6623.
6624.
6625.
6626.
6627.
6628.
6629.
6630.
6(31.
6622.
6633.
6634.
6625.
6636.
6(37.
6636.
6(39.
510
52C
C
C
C
530
540
C
C
C
550
C
C
C
C
56C
C
C
C
C
565
DC 510 lElK-1,5
SIM - SIP « UMJ.IBLKI
CCNTINLE
LNT(J) - SIPS5.
CCMIME
LOWER ZONE
READ (5,3CCC) CHAR
IF (CHAR .EC. L(fcE) GO TO 540
IGEPR = 1
WRITE (6,467C) TYPE
WRITE (6|463C) LCWJc, CHAR
RETLRK
PEAC (5,301C) (LMJ), J»NSTRT,NEND)
GROUNOtiATER
REAC (5t3CCC) CHAR
IF (CHAR .EC. GFCL) GO TO 550
ICEFP = 1
WRITE (6,467C) TYPE
WRITE (6,4(3C) GRCU, CHAR
RETLRK
REAC (5,301C) (GMJ),J=NSTRT,NEND)
GO TO 220
OUTPUT OF INITIAL NUTRIENT STORAGES
WRITE (6,40CS)
WRITE (6.4CCS)
CCNC = LEFAC
IF UNFIT .EC. *ETR) CONC*KGPHA
WRITE (6.40CC) CCNC
WRITE (6.47CC)
WRITE (6,4010)
WRITE (6,4025) (SNT IJ) , J«l ,7 ) , (SNTl J) , J=li , 1«) ,SNT( 20 )
WRITE (6,«03C) (I8LI<,(SN(JfI8LK),J=l,7),(SN(J,IBLK),J-ll,14),
1 l,5
SK(J,1EIK) * SNU,IBLK)*.8*24
UN(J.IEIK) > UMJ,IBLK)*.8924
CCNTINLE
LN(J) = LMJ)<-8924
GN(J) CMJ)*.8924
272
-------
Appendix C (continued)
££40.
££ IN THE SYSTEM
UNITS = LB/AC.
TNA * 0.0
CC 575 J»l,7
SUM = O.C
CC 574 IEIKM.5
SLM = JLH + SMJ.IBLK) * UN(J,IBLK)
CCNTINUE
TNA * TN< + IMJ) + GNU) * SUM/5.
CCNTINLE
TPA » C.O
CC 5£5 J»llf14
SLM » C.C
DC ££C 1ELK * 1,5
SLP * SLf « Sh(J,IBLK) > UN(J,IBLK)
CCNIIKtE
TPA ^ TP* * IMJ) * GN(J) * SUM/5.
CONTINUE
TCLA » 0.0
CC 590 IELK-1,;
TCLA = TCL* •» 5N(20tIBLK) «• UNUO.IBLK)
CCNTINUE
TCLA = LNJ2C) » GM20) * TCLA/5.
IF (INFLT .EC. >ETRJ GO TO 595
CCNC = LEP/C
WRITE (£,4€2C) 1NA.CONC, TPA, CCNC, TCLA, CCNC
GO TC £CO
CCNC = KCPM
Ttvf-ET « ThA<1.121
TPMET * TFA*1.12l
TCL^ET = TCL/<1.121
hRITE J6,4£2C) 1NMET.CCNC, TPMcT ,CONC, TCLMET.CONC
NUTRIENT APPLICATIONS
IF (MAFPL.GE.C .AhO. NAPPL.Lii.5) GO TO 610
ICEPR « 1
hRITE (£,471C) NAPPL
RETLRN
IF (MFFL .EC. C) GO TO 910
CCNC = LEP*C
IF (INFLT .EC. *ETR) CONC=KGPHA
kRUE U.4CCC) CCNC
00 900 IAFFL-1 ,f/PPL
DC £14 J=1,2C
ShAFLT(j) > 0.0
LNAPLT(v) * 0.0
CC £12 IELK-1,5
Sh/FlU,IBLJ«,IAPPL) - 0.0
273
-------
Appendix C (continued)
6700.
6701.
67C2.
67C3.
61C4.
67C5.
67G6.
67C7.
6708.
67C9.
4710.
6711.
£112.
£113.
6114.
€115.
£116.
6117.
£118.
6119.
£120.
6121.
6122.
6723.
6124.
6125.
6126.
6127.
6128.
6129.
6130.
6131.
6122.
£133.
6134.
6125.
6136.
6137.
6126.
6139.
6140.
6141.
6142.
£143.
6144.
6145.
£146.
6747.
6148.
£149.
6750.
6151.
6152.
6153.
6154.
6755.
6156.
6157.
6158.
6159.
612
614
C
62C
£30
635
640
£50
6£C
67C
C
C
C
66C
6SC
7CO
71C
LN4FLU tlBLK.IAPPL)
CCMIME
CCNTINCE
0.0
REAC (5.-C2C)
IF
IF
IF
IF
IF
CUP,
ELANK)
(CHAR .EC.
(CI-AR .EC.
ICERR » I
WRITE (£,4120)
WRITE (£,<£20)
FETLRN
(APCAYUAFFD.GE.O
ICERP * 1
WRITE U,412C>
WRITE (£,4130) IAPPL,
APDAY(IAPPL)
GO TO 620
GO TO 630
APPLt CHAR
.AND. APUAY(IAPPL).LE.366) GC TC 635
APOAY(IAPPL)
(IAPPI .EC. 1) GO
l*PCM UAFFLI .GT.
ICERR * 1
TO 640
APOAY(IAPPL-D)
GO TO 640
WRITE (£.'1201
tPITE (£,4125)
RETIRN
REAC (5.2CCO) TYPE
IF (TYPE .EC. ELANK)
IF (TYPE .EC. MTR)
IF (TYPE .EC. FHCS)
IF (TYPE .EC. CHLC)
IF (TYPE .EC. ENU
ICERR « 1
WRITE (£,4120)
(£,4745)
NSTBT
NENC
GC
NS1RT
NENC
GC
NSTRT
NENC
WRITE
RETURN
« 1
7
TC £60
- 11
14
TC ££0
- 2C
2C
IAPPL
GO TO 640
GC TO 650
GO TO 660
GO TO 670
GO TO 870
TYPE. IAPPL
SURFACE
REAC (5,2C20) CHAR, NBLK
IF (CHAR .EC. JURF) GO TO 690
ICERP - I
WRITE (£,4120)
WRITE (£,4150) IAPPL, TYPc, SURF, CHAR
FETLRN
IF (NBLK.EC.C .OR. NBLK.EM.1 .OR. NBLK.EQ.5) CO TO 700
ICEPR =* I
WRITE (£,4120)
WRITE (£,*£SO) SURF, NBLK
PETtPN
IF (NBIK .EC. 51 GO TO 730
REAC (5.2C10) (SNAPLT(J),J=NSTRT,NENO)
CC 720 >*NSTFT,NENO
CC 71C IELK~1,5
SN/FL(«,1BLK,IAPPL) = SNAPLT(J)
CCNTIME
274
-------
Appendix C (continued)
6760.
6761.
6762.
6763.
6764.
6765.
6766.
6767.
6768.
6769.
6770.
6771.
6772.
6773.
6774.
6775.
6776.
6777.
6778.
6179.
6780.
67E1.
6782.
67£3.
6164.
67£5.
61E6.
67£7.
6788.
6789.
6790.
6791.
6792.
6793.
6794.
6795.
6796.
6797.
6798.
6799.
68CO.
6801.
6E02.
6£C3.
66C4.
6£C5.
68C6.
6£07.
6£C8.
6£C9.
6E10.
6611.
6612.
6£13.
6614.
6615.
6616.
6E17.
6ua.
6£19.
720
C
720
740
750
760
C
C
C
77C
78C
79C
, 8CC
810
C
820
820
84C
aso
£60
C
C
C
£70
1
2
C
CCMINLE
CC 1C 77C
CC 740 IEIK'1,5
REAC (S.2C1CI (SNAPL(J,IBLK.1APPL»,J=NSTRT,NEN01
CCNTINUE
DC 760 .^STFT,NEND
SIM = C.O
CC 75C IEIK»1,5
SL> * Sif + SNAPLU,I8LK,IAPPL)
CCNTIME
SNAPUCJI « SL*/5.
CCNtlNUE
LPPER ZONi
RE/C (5.2C20) Ch/R, N6LK
IF (CHAP .EG. LPPE) GO TO 780
1CEPR « 1
VRITE (6,41201
kPITE (6,41£0i 1APFL, TYPE, SIAF, CHAR
IF (NBLK.EC.C .OR. NBLK.EU.l .OR. NBLK.EQ.5) GO TO 790
ICEPR » I
fcRITE (6,4120)
kRITE U,«tSO) UPPE, NBLK
FETl^
IF (NBIK .EC. 5) GO TC 820
REAC (5.2C10) (LNAPLT(J),J=NSTRT,NENO)
CC 610 ..*fSTFT,NEND
CC ECC IEIK=1,5
UMFl(J,IBLKfIAPPL) = UNAPLT(J)
CCNTULE
CCMINUE
GC TC E6C
CC 820 IBLK'1,5
REAC (5,3C1C) *L* 4 UNAPL(J,IBLK,1APPLI
CCNTIME
tNAFLT(J) « SLH/5.
CC^TI^LE
GC TC 64C
OUTPUT OF NUTKIENT APPLICATIONS
kRITE (6.476C) APCAY(IAPPL)
HRITE (6i«025) (SNAPLT(J),J=l ,7 ) , (SNAPLT(J ),J- 11,141,SNAPLTI20)
kRITE (6,
-------
Appendix C (continued)
££20.
6821.
££22.
6823.
6624.
££25.
££26.
6E27.
6E28.
££29.
££30.
6631.
6832.
6632.
6834,
6E35.
6636.
6637.
££28.
6639.
6E40.
6E41.
6642.
££43.
6 £44.
6E45.
££46.
6647.
6648.
££49.
££50.
6651.
6£S2.
££53.
6654.
6E55.
6656.
££57.
6E58.
6659.
6660.
6661.
6662.
6663.
68£4.
6665.
6666.
6667.
6668.
6669.
6E70.
6E71.
6672.
6 £73.
££74.
6675.
6676.
6677.
6678.
££79.
1
2
C
C
C
IF (INI
CC ESO
CC (
I
860 CCN'
8SC CCNTIN
C
9CC CCNTINIE
C
C
SIC RETURN
C
C
C
3COO FCRPAT (
3CC1 FORMAT (
3C10 FCRN*T (
3C20 FCRfAT (
4CCO FCRMAT (•
1 •
2 3
4C05 FCRMAT (
4CC7 FORMAT (•
1 /t
2 /,
3 /,
4 /,
4C1C FCRMAT '
4C20 FCRMAT •
4C2E FCRMAT '
4C3C FCRMAT •
4C90 FORMAT '
411C FCRCAT •
412C FCRMM '
4599 FORMAT (
1
46CC FCRMAT (
4£10 FCRMAT (
1
2
4619 FORMAT (
4£20 FORMAT (
1
4£30 FCRMAT (
4£40 FCPMAT (
1
4£5C FORMAT (
1
2
2
4
5
466C FCRPAT (
1
,13)
CC',/,'C',*NLTRIENTS - « ,A5,11X, * ORG-N' ,3X,' NH3-S* ,3X,
2-A* ,EX, •NC2',5X,'N03I,6X,*N2',2X,•PLNT-N*,3X,'ORG-P't
3X,'FC4-S*,2X,'P04-A«,2X,« PLNT-P' ,6X,*CL*)
Oli4CC*«*)/i •f***,38X,**',
• ',«* WARNING: NUTRIENT ALGORITHMS*,6X,»**,
• •,«* HAVE NOT BccN VERIFIED WITH',7X,'*»,
• ',** OBSERVED DATA',21X,***,
• ','*• ,28X,•*',/• •t'tOC*') )
0' |2>,'£IRFACE LAYER')
0' ,£X, 'STORAGE*,12X,F8.0,6F8.3,F8.0,3F8.3fF8.3)
C',6X,'/VEPAGc',l2X,F8.0,6f6.j,F8.0,3F8.2,F8.3)
•.IZXt'ELCCK*,I2,6X,fa.O,6F8.3tF&.0,3F8.3,F8.3)
C',2>,*IFPE8 ZONE*)
C>,'Xv'lChER ZONE*)
C*,2X,'CPCUNOWATER*)
EXPECTING THE WORD NUTRIENT BUT *,
t0.f t ERROR—
•REAC H «,A8)
•l',40>,'NUTRIENT SIMULATION
'0',2X,'TIfE STEP FOR TRANSFORMATIONS * -,
/,' '.IX.'NCI'ack OF NUTRIENT APPLICATICNS
INFORMATION')
•-I5,'
KIN',
12.
t • • t z* t•LMic OF
C' ,' ERROR—-
PLANT HARVESTING = *.I4)
IN REACTION RATES SECTION OF INPUT*)
',12>,'EXPECTING ',A5,' BUT READ IN •,A4)
',12>,'EXPECTING NITR, PHOS, OR ENC, BUT REAO
0','MIFOGEN REACTION RATES', 1U(4XVA4)/,
• ,tX,«SLRFACE' ,12X,10(2X,F6.4)/
•,£X.'LPPcR ZONE*,9X,10«2X.F6.4)/
•,6X,'LCk«£H ZUNE',9X. 10(2X,F6.4)/
•,£X,'GRCUNUMATER',8X,10(2X,F6.4)/
•,2X,'TEKPERATURE CJcF.•,5X,IOF8.3)
'C1 .'FKSPHQhUS REACTION RATES', 5(4X,A4)/
' •,£X,*SCRFACE',12X,5(2X,F6.4j /
276
-------
Appendix C (continued)
£E60»
6881.
6662.
6££3.
6864.
66C5.
6686.
6687.
6688.
6689.
6890.
££91.
6892.
6893.
6694.
6695.
6696.
6697.
6698.
6899.
6900.
6901.
£902.
69C3.
69C4.
6905.
6906.
6907.
69C8.
69C9.
6910.
6911.
£912.
£913.
6914.
6915.
6916.
6917.
6918.
6919.
6920.
6921.
£<22.
6923.
6924.
£925.
£926.
£927.
6928.
6929.
7COO.
7C01.
7C02.
7CC3.
7C04,
7CC5.
7C06.
7007.
7008.
7C09.
4€£5
4£70
4690
47CC
4710
4720
4725
4730
4735
4140
4145
475C
476C
477C
47EC
479C
48CO
4810
4612
4tl4
4620
C
C
C
C
C
C
2
3
4
5
FORMAT
FGRMT
1
FGRf/T
1
FCRMA1
FORP/T
1
FCRJ"AT
FCRPAT
FCRPAT
1
2
FCRI*£T
1
FCPKJT
1
FCRPAT
1
FORMAT
1
FCRMAT
FORMAT
1
FORMAT
1
FGRHAT
1
2
5
"FORMAT
i
FCRMAT
i
2
3
FORMAT
1
FCRMAT
1
FCRMAT
1
2
END
• *.£
• • f
• ',£;
1 '.2
CO','
CO1,'
•INFL
C ',1
' IbH
1* «t3
CO','
•RANCI
CO'.'
CO'.'
(• '.1
•AFFL
* V 1 L L ' 1
(' ',1
' CCE
CO',1
•PEAC
CC',1
•RE/C
CO',1
1 E > F E1
CO','
( 'C • , '
1 EXE*
( '0 • »••
A4, •
CO','
' IN
• IS
•REEL
CO','
A4 , *
( '0 ' » '•
• Ih
•fi£CL
CO','
,» PE,
CO','
•FKJ
CO', 2;
' • ,2X
• • t2X
SLBPOIT1NE rail
C
C
C
G
C
,£X, UPPER ZUNE*,9X,5C2X,F6.4I /
IOUER ZONE',9X,5(2X,F6.4I /
,£X,'CPCUNO*ATER',8X,5(2X,F6.4) /
.'X.ME^tRATURE COEF.' , 5X.5F8.3)
,• --- EPROR --- EXPECTING 1NIT BUT READ IN «,A4)
EPRCR - IN INITIAL -,A5,' STORAGE SECTION OF
*FCfi «,A5,' EXPECTING BLOCKS»0, 1, OR 5',
VALUE - sm
't3X,« INITIAL STCRAGES')
APPLICATIONS
'
CAN
NUMBER OF NUTRIENT
FPCf C TO 5 ONLY, INPUT VALUE = ',131
EPRCR --- IN NUTKIENT APPLICATION SECTICK'I
EPRCR -- IN INITIAL STuRAGE SECTION')
t'IN APPLICATICN NO. '.IZi* THE DAY OF •,
/TICN IS NOT IN THE RANGE 1 TC 366, INPUT ',
FOR
','ThE CAY OF APPLICATION NO. *,I2,
NCT EXCEED THE PKEVlCUo APPLICATICN DAY')
>,'EXPECTING NITR, PHCS, CHLO, OR END, BUT *,
IN «,A5)
','EXPECTING NITR, PHCS, CHLO, OR ENC, BUT •
IN «,A5,' FOR APPL. NO. ;,I2)
','IN APPLICATION NO. ',U,( FCR ' ,A4,
',A5, ' BUT KcAD IN •,A51
ftTION FCR DAY •,IJ)
D TSTEP SPECIFIED, INPUT UAS ',14,
CONTINUING WITH TiTtP = £0 MIN.')
EFPCR INVALID NITROGEN REACTION RATE
I* ZCNE ',12,' INPUT VALUE =* »,F8.6)
|»0',i fcAPNlNG NlTKutEN REACTION RATE ',A4,
ZChE '.I2./14X,
TCC LARGE FCR TIME STtP SELECTED, CONSIDER ',
C1NC TSTEP FCR MORE ACCURATE SOLUTICN')
EFFCA I.4VALIU PKJ3PHORUS REACTION RATE
ir.ZONE ',12,' INPUT VALUE - §,F8.6)
VAPNING PHGSHLRLS REACTICN RATE •
2CNE ',I2/14X,
TCC LARGE FCR TIME STEP SELECTEC, CCNSIDEB '.
C1NG TSTEP FOR MORE ACCUATc SOLUTION')
— V.AFNING— TEMPERATURE COEFFICIENT FCR NITRCGEN*
ACTICN SATE '.A*,' SHuULJ dt >= l.O'l
i k«RNlNG TEMPei^ATURE COEFFICIENT FOR *t
REACTICN RATc ',A<»,' ShCULD EE >= 1.0*1
\L MTROGcN IN SY3TEM = • ,2X, F10.3,2X,A5/
L PHGSPHOAUS IN SfSTEM = ' ,F10.3,2X,*5/
L CHLORIDE IN SYSTEM - ',2X,F10.3,2X,A5I
FCR
THIS SUfaROUTINE IS CALLEC EVERY INTERVAL ON
A RAIN DAY UR ONLY ONCE » DAY ON A NC RAIN
CAY TO COMPUTE NUTRIENT LOSSES AND TRANS-
FORMATIONS. AOVECTIVE LCSS IS COMPUTED
277
-------
Appendix C (continued)
7010.
7011.
7012.
7013.
701*.
7015.
7016.
7C17.
7C18.
7019.
7C20.
7C21.
7022.
7C23.
7024.
7025.
7C26.
7C27.
7028.
1C29.
7030.
1C31.
7032.
7033.
7C3*.
7035.
7C36.
7037.
7038.
7C39.
7C*0.
70*1.
70*2.
7C*3.
1C**.
70*5.
70*6.
70*7.
70*8.
1C*9.
7050.
7051.
7C52.
7C53.
7C£*.
7055.
7056.
7C57.
7058.
7C59.
7C60.
7CC1.
7042.
7C63.
7C€*.
7065.
7066.
7C67.
7C68.
7C6S.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
EVERYTINE SUBROUTINE IS CALLED, WHILE
CHEMICAL AND 6 ILLOGICAL TRANSFORMATIONS
ARE CONE AT SELECTED INTERVALS AS
SPECIFIED BY INPUT PARAMETER TSTEP.
CECLARATIONS
COMMON VARIABLES
INTEGEP** 1SIEF ,KSTEP,SFLG,UFLG,LFLG,GFLG
PEAL** LEL1,£TE*H*,2*),
SM2C.5I tSNT(20),SNRSM(20t5) tSNROM (20 ,5) ,
UM20,5),LNT(20),UNI(20,5),UMr(20i , UNRIP (20,5 )»
NPSM2C.5), LNUOI,LNRPM(20), GN(20),
SNREM2C,£) ,UMRBM(20,5) ,LNKbK(20) ,GNREM(20) ,TNRBM20)t
SNPSY(2C,5) ,SNROY(20,:>),UNRIY(20,5) ,NfiSY(20,5) ,
Lh&FY(2C) ,SNRBY(20,5) .UNRBYCiO.i) ,LNR PY (201 , GNRBY (20 1 ,
TNREY(2C),TKRhV(20),TNRHVM(20)(TNRHVY(20) ,TNA, TP« ,TCL A,
Kh(10t*),THKM10),KP{5,*),THKt>(5l>NBAL»PHBAL,CL8AL
CCMMCN /NLT/ CELT, STEMP, SN.SNT ,SNRSN, SNROM.UN, UNT.UNI ,UMTf
LNP l^•,^RS^,LN,LNRPMfG^.S^RB^^,UNRB^',LNPeM,G^REM,TNRBM,
SNP <>tSNRCY,UNRIY,NRSY,LNRPY,SN*BY,UNRBY,LNREY,GNPBY,
1
2
3
*
5
6
7
8
1
2
3
*
INTEGER**
K^,^^-K^fKPfTHKPtNBAL,PI-oAL,CLUAL,
1JTEF,NSTEP,SFLG,UFLG,LFLG,GFLG
FR^TKE,HYCAL,OUTPUTfTIMFAC,IMIN, IHR, TF ,J COUNT,
C*LE, FFCC, ENGL,MtTR,80Tri,YcS. NO, PEST, KUTR
RL,l-YI"I*,CPST,LZS,AREA,R£Sei(5)fROSB(5),SPGX(5 ), INTF(S),
RGX(5),IKFL(5>,UZSB(5),APERCb(5),RIB(5),ERSN(5),f>ESBI5)f
REAL**
CCFKCh /ALL/ RL,hYMN,PRNTKE,HYCAL,UPST,OUTPtT,TIMFAC ,L2S,APEA,
1 FESBl,POSe,SRbX,INTF,KGX, INFL ,UZS 6 ,APE°CB,R IB ,ERSN ,
2 *,F3,A,CALB,PRCD,PEST,NUTfc,ENGL,METR,BCTH,RESE,YES,NO,
3 IHIN, IhR,TF,JCOUNr, PRINT, iNTft, DAYS , HOUR, MNTH
DECLARATIONS FOR INTERNAL STCRAGE ALLOCATION
REAL** SNF< UO,£t,SNRO(20,5) , SNRP (20,i) ,ASNRS(20,5 J /100*0.0/ ,
1 ASNCci(2C>,ASNRU(20,5)/lCO*0.0/, ASNPOT( 20) ,
ASNFF(2C,£)/lCO*0.0/,ASNRPT(20l,UNTl(20,5)tUNRH20t5)>
UNSF (20,5), NRS( 20,5 J.AUNRI (2U,iJ/100*0. 0/,AUNR IT 120),
ALNFF (2C,5)/iOO*0.0/,AUNRPT(20),ANRS(20,5)/100*'0.0/f
A^R5T(2C),L^RP(20),ALNRP(20l/20*0.0/t
ASN?E(2C,£)/100*0.0/,ASN*BT<20),
AUKFE (2C,5)/100*0.0/,AUNKBT(20),
ALKPE(2C)/20*0.0/, AGNRd(201/20*0.0/,ATNRB(20 )/20*0.0/
DECLARATIONS FOR OTHER INTERNAL VARIABLES
INTEGER** IT.1PE ^CYCLE.IHOUR, IBIOfI ZONE, IBLK
FEAL*8 CCNC,LeF/C/«LB/AC'/,KGPHA/«KG/HA«/
REAL** FS»FC,FF,TW,TViI,FII,FLItT(*) t
1 CELrE(2C,5),DELN(20),
2
2
*
€
7
£
278
-------
Appendix C (continued)
7C70.
7C71.
7C72.
7073.
7C74.
7C75.
7C76.
7C77.
7C78.
7C79.
7C60.
70£1.
7C62.
7C63.
7(64.
7065.
7C€6.
7C£7.
7068.
7C£9.
7C90.
7091.
7C92.
7093.
7C54.
7CS5.
7C96.
7C97.
7058.
7099.
7100.
7101.
7102.
7103.
7104.
7105.
7106.
7107.
7108.
7109.
7110.
7111.
7112.
7113.
7114.
7115.
7116.
7117.
7 lid.
7119.
7120.
7121.
7122.
7123.
7124.
7125.
7126.
7127.
7128.
7129.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
2 SU»>,SL*C,SUM,NDSM(20),NDSC(20),NASM(20I,
3 NASC^OI.ERSNT.CUNFC.CONFS.TbTN.TOTP,
4 CCNXF71.1217,SNMET(20,5I ,UNMtT(20,i) ,LNMET(20) ,GNMET(20),
5 SNTfET(2CJ,L'NTMET(20),UNlTMT(20).UNlMET(20,5),
C PA,CLfV(2C) ,DUMA(20,5J
INITIALIZATION AND DECLARATION OF SELECTCRS
CSEO FOR AOVECTING ANU REMOVING NUTRIENTS
BY MEANS OF SEDIMENT (SO), OVERLANC FLOW
(OF), INTERFLOW (IF), PERCOLATION (PCI,
BIOLOGICAL (8L).
INTEGER**. SELSC (201/1,0,1,0,0, 0,0,0,0,0,1,0, 1,0, 0,0,0 ,0,0,07,
1 SELCF(20)/0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,17,
2 SELIF(20)70,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,17,
3 JELPC(2C)/0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,17,
4 SELEI(20170,0,0,0,O.I,1,0,0,0,0.0,0,1,0,0,0,0,0,07
ERIEF DESCRIPTION OF VARIABLE NAMING CONVENTION:
1) FIFST TWO LETTERS SN,UN,LN,GN STAND FOR SLPFACE,
LFFER ZONE, LOrfER ZONE, AND GRCUNDWATER NLTRIENTS
LM INTERFLO» STORAGE OF DISSOLVED NUTRIENTS
2) FIFST LETTER A STANDS FOR AN ACCUMULATION OF A
MTRIEM LOSS OVER THc INTERVALS BETWEEN PRINTING
3) 11-E THIRD CR FOURTH LcTTE* 'R' STANDS FCR REMOVAL
4) FCLLCHING THE «R« A LETTER INDICATES THE CAUSE CF
PEfCVAL; "S^SEOIMENT, • 0' "OVERLAND FLCH,
•F'=FERCOLATION, •I•=iNTcKFLOH , •B«=BIOLCCICAL
5) LETTERS 'M1 AND 'Y« INUICATt MCNTHLY AND YEARLY
SLMS OF REMOVALS, MCNTHLY SUM IS ACCUMULATED IN
M1RNT ANi> PASSED TC MAIN FOR OUTPUT, AND YEARLY
4PCUNTS ARE CALCULATED AND PRINTED IN MAIN
£) THE LETTER «T« APPEARING AT THE VEFY ENC INDICATES
UE TOTAL OR AVERAGE MASS OF THE 5 BLOCKS IN THE
SLPFACE AND UPPER ZCNES
NLTRIENTS ARE STORED IN VECTORS ANC ARRAYS IN THE
FCLLCWING SEQUENCE CF ELEMENTS:
1 * CRG-N, ORGANIC NITROGEN
2 * NH3-S, AHMONIA IN SOLUTION
• ' NHJ-A, AMMONIA ACSORBEO TC SOIL
4 - NC2, NITRITE
5 - N03, NITRATE
t » N2-GAS, NITROGEN GAS FROM CENITRIFICATION
1 = PLNT-N, PLANT NITROGEN
t * CPEN
« « CPEN
1C = CPEN
II = CRG-P, ORGANIC PHOSPHORUS
12 * PC4-S, PHOSPHATE IN SOLUTION
13 = PC4-A, PHOSPHATE ADSORbEC TO SOIL
14 * PLNT-P, PLANT PHOSPHORUS
1* = OPEN
U - CPEN
17 - OPEN
IE OPEN
I? = CPEN
2C - CL,
CHLORIDE
279
-------
Appendix C (continued)
1130.
1131.
1132.
1133.
7134.
1135.
1136.
1137.
1138.
1139.
1140.
7142.
7143.
7144.
7145.
1146.
7147.
7148.
7149.
7150.
71*1.
7152.
7153.
7154.
7155.
1156.
1157.
1158.
1159.
1160.
7U1.
7162.
1163.
1164.
7165.
7166.
7167.
7168.
116?.
1170.
7171.
7172.
7173.
7114.
1115.
7176.
1171.
1178.
7179.
7180.
7181.
71C2.
7183.
1184.
7185.
7186.
7187.
71£8.
7189.
C
C
C
C
C
C
C
C
2C
4C
5C
C
C
C
6C
1C
8C
sc
C
C
C
C
ICO
11C
12C
C
C
C
C
C
C
C
PA
l.C -
DO 120 IELM1.J
ADVcCTIVc LOSSES
SURFACE ZONE
SEDIMENT REMOVAL
IF (ERSM1EIM .LE. 0.0) 60 TO 40
FS * 2CCC.*AFE**0.2*ERSN(IBLK)/H
IF (FS .CT. l.C) FS»1.0
CC 20 J*1,2C
SNRSUtlElK) * SELSD(J)*FS*SN(J,IBLKJ
CCMINLE
GC 1C tC
CO 50 JM.2C
SKPSJJ.IEIM * 0.0
CCKTINtE
OVERLAND FLOW AND PERCOLATION
IF ((P2»FESeiCieLK)) .LE. 0.0) GO TO 80
FC * PCSE(iem/(PA*(P3«-RESBi(IBLK)))
FP = RieciELK)/(F3+RESbl(IBLK))
DC 1C J«lt2C
SNRCU.IBLK) = SELOF(J)*FO*SN( J.IBLK)
SKRFU.IEIM = SELPC(J)*FP*SN(Jf IBLKI
CCMINLE
CC TC IOC
DC SC J«lt2C
SNRC(.,1BIK) ' 0.0
- 0.0
CHANGE SURFACE STORAGES AND ACCUMULATE
REMOVALS
CCKTINLE
DC 110 SM J.IBLK) - SNRSU.IBLK) - SNRO(J,IBLK|
1 SNPP(JtlBLK)
l^(J,lBLK) < UMJ.IBLK) + SNRP(JtldLK)
/SNRSiUiIElK) * ASNRS(JtlBLK) * SNRSC J.IBLK)
ASNRC(JtlElK) * ASNRO(JiIBLK) * SNRG(JtlBLK)
«SNRF(J,IELK) - ASNRPC J.IBLK) •»• SNRP( J.IBLK)
CCNTINtE
CONTIKLE
CO 220 IELf-1,!
UPPER ZONE
PERCOLATION AND INTERFLOW
UNTI - TRANSFER FROM OZ TO INTERFLCV
TK * UZSEdBlf) * RGX(IBLK) *
TVI > SPCXIEIK) # INTF(IBLK)
IF (TV, .LE. C.C) GO TO 140
FII * RGMI8LK)/TM
APfcRCBIIBLK)
UFL(IBLK)
280
-------
Appendix C (continued)
7190.
7191.
7192.
7193.
7194.
7195.
7196.
7197.
7198.
7199.
7200.
72CI.
72C2.
7203.
7204.
72C5.
7206.
•|2C7.
72C8.
12C9.
7210.
7211.
7212.
7213.
7214.
7215.
7216.
7217.
7218.
7219.
7220.
7221.
7222.
7223.
7224.
7225.
7226.
1227.
7226.
7229.
7230.
7231.
7232.
7233.
7234.
7225.
7236.
7237.
7238.
7239.
7240.
7241.
7242.
7243.
7244.
7245.
7246.
7247.
1248.
7249.
120
130
UC
150
C
C
C
16C
170
UC
ISC
C
C
C
2CC
210
22C
C
C
C
C
230
24C
C
C
C
FP
CC
IM( JtlELM =
CNPFU ,1EIM
CCNT1NLE
GC 1C 16C
CO 150 v=lt2C
LKTlUt 16I.K)
INRPU tiem
CCNTINCE
+ APERCBl IBLK) J/TK
» SELIF(J)*FII*UN(J,IBLK)
UNlUtlBLK) * UNTKJ.IBLK)
SELPC(J)*FP*UM J.IBLK)
0.0
0.0
LOSS FROM INTfckFLOW STORAGE
IF (TV.I .LE. C.O) GO TO 180
FL1 - INTFUELM/TViI
CC 170 J*1,2C
LNPI(v.IElK) = FLl*UNl(JtIBLK)
CCNTINLE
GC TC 20C
OC ISO J=lt2C
CCMlMiE
REMOVE AND ADO STORAGES />ND ACCUMULATE
CC 210 J'ltiC
LM(J,IELK)
ALNRI (J,IELK)
^LNRF (j.lELK)
LN(J) = U (J)
CCMIKLE
CONTINUE
CO 240 ieLK»l,5
CO 220 *»1,2C
^FS(J,l£lM
- UN(J>IBLK) - UNTI (J,ItJLK) - UNRP < J , IBLK)
CCKTINUE
CCNTINLE
UM(J»IBLK) - UNKltJ.IBLKJ
AUNRKJ.IBLK) *• UNRHJ.IBLK)
AUi«RP(J, IBLK) + UNRPUt IBLK)
* UNRP(J,IBLKJ*0.2
COMPUTE NUTRIENT REMOVAL TO STREAM (NRS)
AND ACCUMULATIONS
SNRSUtlBLK) 4- SNRO(JtlBLK) * UNRKJtIBLKl
= ANRS(JtlBLK) + NRS(JtlBLK)
LOWER ZONE
250
2*0
270
C
zee
Tli = L2S * CFJT
IF (TV. .LE. C.O) GC TO 260
FP = CFST/Tfc
CC 250 J=1,2C
LKBP(J) * JELFC(J)*FP*LN(JI
CCNTINLE
GO TO 260
CO 270 J*lt2C
LNFF(J) « 0.0
CONTINUE
OC 29C J'
LMJ) =
l,2C
t^(J) -
LNRPUJ
281
-------
Appendix C (continued)
7250.
7251.
7252.
72J3.
7254.
7255.
1256.
7257.
7258.
7259.
7260.
1261.
7262.
7263.
1264.
7265.
7266.
7267.
7266.
1269.
7270.
7271.
7272.
7273.
7274.
7275.
7276.
7277.
7278.
7279.
7zeo.
7261.
1262.
1283.
72E4.
72E5.
1266.
7267.
7266.
7269.
7290.
7291.
1292.
7293.
1294.
1295.
7296.
7297.
1298.
7299.
73CO.
7301.
7302.
7303.
7304.
7305.
73C6.
1307.
7308.
7309.
290
C
C
C
C
C
C
C
C
C
C
C
3CC
C
310
C
C
C
C
C
320
330
340
C
C
C
C
C
C
C
C
430
44C
C
C
C
450
C
C
GNU) » CHJ) « LNftP(J)
ALNRF(J» = ALNFP(J) +• LNRP(J)
CCNTINLE
GRCUNOHATER
NO ADVECTIVE LOSS FROM GROUNDWATER
CHECK TO SEc IF PHYSICAL AND BIOLOGICAL
TRAUSFCRMAT10NS ARE TO BE DONE THIS
INTERVAL UN A kAIN DAY, OR SETUP THE
NUMBER OF TIMtS TO LOOP FOR A NO RAIN
DAY
IF (TF .GT. 1) CC TO 300
ITIKE = IPIN + 1
CtLL TRANS ( CELT, IZONE ,DUMV,SN,KN ,THKN,KP, THKP ,T, OUMV ,CELNB)
CCMPUTE AND ACCUMULATE At-CUNT REMCVEC
BIOLOGICALLY
DO 440 IEIK«1,5
CC 43C J«l,20
ASNRE(JiIBLKI - ASNR6(J,I6LK) * SEL8H J) *DELNB ( J, IBLK)
CCNTINLE
CCN 1INLE
UPPER ZONE TRANSFORMATIONS
IF (LFLG .EC. C) GO TO 560
IZCNE - 2
CALL TRANS (CELT, I20Nfc,DUMV,UH,KN ,THKN,KP, THKP ,T,OUPV ,OELNB )
CC 550 IELK»1,5
282
-------
Appendix C (continued)
1210.
1211.
7212.
7213.
7214.
1215.
7216.
1317.
1218.
1219.
1220.
7321.
1322.
7223.
1224.
1225.
7326.
7227.
7228.
7329.
7230.
7331.
7332.
1233.
7234.
7235.
1236.
1237.
7238.
1239.
1240.
7241.
7342.
7343.
7344.
7345.
1246.
1347.
1348.
1249.
1350.
7251.
7252.
7353.
1254.
7355.
7356.
7357.
7258.
7259.
7360.
1261.
7362.
7363.
1364.
7365.
1366.
7367.
7368.
1369.
540
550
C
C
C
560
C
C
650
C
C
C
660
C
C
150
C
8CO
C
C
C
E1C
C
C
C
C
C
C
S10
92C
C
920
940
CC 54C J«l,20
AUNReU.IBLK)
CCNTINLE
CCN1INLE
AUNRB(J,IELK) * SELBLC J) *DELNB( J, 1BLKI
IF (LFLG .EC. C)
IZCNE » 2
LOWER ZONE TRANSFORMATIONS
GO TO 660
CALL TRANS I CELT , UONE,LN,DUMA,KN,THKN,KP,THKP,T,DELN,CUMAI
CC 650 c=l,;0
ALNRBU) * ALNRfc(J) + SELBL (J) *DELN(J)
CCNTINUE
IF (GFLG .EQ. C)
IZONE - 4
GROUNOUATER ZONE
GO TO 800
CALL TRANS {CELT , IZONc,GK,DUMA,KM,THKN,KP,THKP,T,DELN,CUMA)
CC 750 ^«1,2C
AGNR6U) - AGNRB(J) * SELBLC J) *DcLN(J)
CCNTINLE
CCNTINLE
IF (PRMKE .EC. C)
AUNRdl J , IBLK)
END OF NO RAIN INTERVAL LCOP
GC TO 1300
CCMPUTE BIOLOGICAL REMOVALS
ACCUMULATE MONTHLY VALUES OF AOVECTIVE
AND BIOLOGICAL REMOVALS
ATNKb * ACCUM. TOTAL NUTR REMOVAL BIOL.
CC 920 J-1,20
SUM - O.C
DC 910 IEIK«1,5
SIM = SLM « ASNRB(J,IBLK)
CCNTINLE
ATNRE(J) SLC/5. + ALNRB(J) * AGNRb(J)
CCNTINLE
CC 940 J=l,20
DC S20 IEIK«1,5
SNPSM (J,IELK) = SNRSMU, IBLK) * ASNRS ( J , IBLK)
= SNRCM(J,IBLK) * AS.JRUiJ, IBLK)
- UNklM(J.IBLK) «• AUNKI (J,IBLK)
= NRSM(J,IBLK) + ANnS(J,IBLK)
(J.IELK) = SfJKBMU.IBLK) + «SNRB ( J , IBLK )
LhPBf-(c.IELKJ = UNR8M(J,IBLK) + AUNRBt J , IBLK)
CCNTINLE
LNRFHJ) LrfFM(J) * ALNRP(J)
LNREMJ) - LNFEMJ) + ALNKB(J)
GNREf(j) G^pe^'(J) «• AGNRBIJJ
TNREMJ) - TNPEMIJ) * ATNRB(J)
CONTINLE
233
-------
Appendix C (continued)
1310.
1271.
7272.
1213.
1214.
1315.
1216.
1317.
1378.
1 279.
1280.
1281.
7282.
7383.
1384.
1385.
1366.
1267.
7388.
1289.
1290.
1291.
7292.
7293.
1394.
1295.
1296.
7397.
1298.
7299.
14GG.
1401.
7402.
7403.
1404.
7405.
7406.
74 C7.
74C6.
14C9.
7410.
74U.
1' 12.
1413.
1414.
7415.
1416.
1417.
7418.
7«19.
1420.
1421.
1<22.
7423.
1424.
1425.
7426.
1427.
1428.
1429.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
945
950
960
910
C
C
C
C
511
912
C
C
C
C
SEO
IF (FRNTKE .EC. 21 GC TO 1200
CUTPUT OPTIONS
IF (H*C«L .EC. FFCD) GO TO 1100
IF (TF.GT.l .CR. fU.LT.HYMIN) GO TO 1200
COMPUTE CONCENTRATIONS AND H/SSES IN STREAM
FOR CMLIBRATICN OUTPUT
NDSM=NUTRItNTS DISSOLVED IN STREAM,fASS
NUSC=^UTRIENTS DISSOLVED IN STREAM, CCNC.
NASM=NUTkIENTS ADSOivdkD IN STREAM, ("ASS
NASC=NLTRIENTS AOSOK3EC IN STREAM, CCNC.
CGNFC * CONVERSION FACTCP TC GET KG/I UNITS
CONFS » CCNV. FACTOR TO GET ADSORBED NUTR.
CONC. IN PPM OF SEDIMENT
ERSNT > O.C
CO 945 IELK=lt«
ERSM * EFJM + ERSNdBLKI
CCNTINLE
EPSNT =• EPSM/5.
CCNFC = 454CCC./(FU*TlMFAC*60.*2b.32)
IF
CC
(ERSNT .CT.
970 J-1.2C
SLI-C = O.C
SLK* x c.C
DC 950 lELKMiS
SLfC = SUt-C +
SlfA » £LM +
CCNTINLE
NCSMJ) » SU>C*AREA/5.
NOSC(J) - NC!MJ)*CCNFC
C.C) CONFS * 1.0E6/J ERSNT*2000.*AREA1
IF (ERSM .LE.
NASC(J) =
GC TC 97C
NASCU) * C.C
CONTINUE
ASN*OU.IBLK)
ASNRS(J.IBLK)
960
AUNRI ( J , I ELK )
0.0) GO TO
(J)*CCNFS
COMPUTE TOTAL MASS OF N (TCTN) AND F (TOTP)
IN STREAM
TCTN 0.0
TCTP 0.0
CO 971 J=l,7
TCTN = TCTN 4NCSHJ) + NASMU)
CCNTINLE
CO 972 J=ll,14
TOTF = TCTF 4 hDSfCJ) + NASM(J)
CCNTINLE
MODIFICATIONS FOR
CONVERT MASi FKCM
METRIC
LB. TO
OUTPUT
KG. CONC.
IN KG/L
IF (CLTPLT.EC.ENGl .CR. OUTPUT.Eu.BOTH) GO TC 1000
CO 980 J=1,2C
NCSI>(J) ' ^CE^ (JJ/2.205
NAS^(J) NA/2.205
CCNTINLE
284
-------
Appendix C (continued)
7430.
1432.
1433.
7434.
7435.
7436.
1437.
1438.
7439.
1440.
1441.
7442.
7443.
7444.
7445.
7446.
1447.
1448.
7449.
7450.
7451.
7452.
7453.
7454.
7455.
7456.
7457.
7458.
1459.
14(0.
7461.
7462.
1463.
7464.
7465.
7466.
7467.
7468.
7469.
7470.
1471.
7472.
7473.
7474.
7415.
7476.
7477.
1478.
1479.
7480.
7481.
1482.
7483.
7484.
7485.
7486.
1487.
7488.
1489.
C
1COO
C
C
C
C
11CC
1110
1120
C
1CTN - TCTNy2.2C«
1CTP - TGTP/2.2CJ
htRITE U,412C) KCSMSKNDSM*) ,NDSM(2) ,NOSK( 12),
1 MSM3),NASM(l)tNASMU3),NASM(ll)
V.RITE (6,4140) r»CSC (5) ,NDSC(4) ,NOSC Ul ,UOSC( 12 ),
1 MSC<31,NASCU),NASCU3),NASC(ll)
GO TO 1200
PRODUCTION OUTPUT
CCMPUTE UATcRSHEO AVG. FROM
CO 1120 J-1,20
SNT(J) • C.O
LNT(J) « 0.0
LM1U) - C.C
ASNPSTU) « C.C
ASKRCT(J) * C.C
ASNRPT(J) « C.C
ALfPIT(J) > C.O
ALNPPT(J) « C.O
ANRST(J) » O.C
ASKRET(J) > C.O
AUhFET(J) - C.C
CC 1110 IEIM1,5
£M(J) > lltl4),SNT(20)
( IBLK, (SN (J, IBLK) tJ=lt 7) t(SN(Jt IBLK), J*lltl4)»
tJ, IbLK), J=L,7), ( A SNRS ( J , IBLK ) , J= 1 1, 14 )
,J=l,7),lAiNKOT(J) , J=ll ,14),ASNRCT(20)
(IELK,USNRO(J,IBLK)t J=l,7), ( ASNRO ( J . IBLK ) , J= 11, 14 I
,*SNRGUO, IBLK), IbLK=l,!>)
(«SNfPT(J) ,J=l,7),UiNRPT(J),J"U,l4l,ASNPPT(20)
(IELK,(ASNRP(J, IBLK), J=l,7), (ASNRP(J, IBLK ), J= 1 1, 14 I
IBLK=l,5)
285
-------
Appendix C (continued)
4490.
7491.
4492.
7493.
74S4.
74S5.
7496.
7497.
14991
7500.
7501.
7502.
7503.
7504.
7505.
75C6.
7507.
75C6.
7509.
7510.
7511.
7512.
1513.
7514.
7515.
7516.
7517.
7518.
7519.
7520.
1521.
7522.
7523.
7524.
1525.
7126.
7527.
1528.
7J29.
1530.
7531.
7532.
7533.
7534.
7f35.
7136.
7537.
7538.
7539.
7540.
7541.
7«42.
7543.
1544.
7545.
7546.
7547.
7548.
7549.
C
C
C
C
C
C
C
1
C
C
C
C
C
WRITE (6,4C£0) (/SKABT(J),J=l,7),(ASNRBT
WRITE (6,40£C) (ZUNftBTJ J ), J=l ,7), (AUNR.BT (J )* J=ll ,14) , AUNR8T (20)
WRITE U,402C) (16LK, ^T(JJ*CCNVF
A£NRCT(J) « <^RCT{J)*CONVF
A£NFFT(J)
* /£^ReT(JJ*CCNVF
LMCET(J)
CNMKTIJ)
AtNPIT(J)
AINPFT(J)
AUNPCT(J)
LN»«ET(J) =
ALNRF(J)
ALKPE(J) •
GNKET(J) =
AGNFE(J) '•
CC 1140
IMT(J)*CUNVF
/L^PIT(J)*CONVF
'
-------
Appendix C (continued)
1550.
1551.
1552.
1553.
7554.
1555.
1556.
7557.
1556.
1559.
1560.
1561.
1562.
1563.
1564.
1565.
1566.
1567.
1566.
1569.
7570.
7511.
1572.
7573.
7514.
7575.
1576.
7577.
7518.
1519.
15£0.
1581.
1582.
1583.
1564.
75£5.
7 5 £6.
7587.
1586.
7589.
7590.
1591.
7592.
1593.
1594.
1595.
1596.
1597.
1598.
1599.
76GO.
7601.
7602.
7603.
1604.
7605.
1606.
1607.
76C8.
16C9.
1140
1150
C
C
C
1
2
1
1
1
1
C
C
C
1
2
1
2
1
1
1
C
C
C
SKPETfJ.iem * SN( J,IBLK)*CONVF
«SNRS(j,IEm - ASNRSU, I8LK)*CONVF
ASNRGU.IEIM * ASNROl J , IBLK)*CONVF
«SNRPU,IEIK) - ASNRP(J,IBLK)*CONVF
*SNRe(J,IElt) = ASNR8(J,IflLK)*CONVF
UMET(JiIElK) - UN( J,I6LK)*COAIVF
LMFETU.IEIK) = UNI(J,IBLK)+CCNVF
ALNRI(J.IEIK) = AUUK1(J,IBLK)*CONVF
JtNRFU.lELK) - AUNfcP(J,IBLK)*CONVF
/CNReU.IClM = AUNRfl(J,I8LK)»CONVF
CCMIME
CCNTIME
WRITE (6.40C5)
WRITE (6,4000) CCNC
SURFACE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
(6,4010)
(6,4020
(6,4020)
(6,4040)
(6,4C!C)
(6,4020)
(6,4060)
(6,4020)
(6.4C7C)
(6,4020)
U,4CEC)
(6,4020)
(6,4090)
(6,4020)
(6,4020)
(6.41CC)
(6,4020)
U,4C4C)
(6,4100)
(6,4020)
(6,4010)
(6,4020)
(6.4CEC)
(6,4020)
(SNTMET(J ),J=1,7),(SNTHET(J
(IBLK, (SNKcTJJ, IBLK) ,J=l,7)
l£NPET(J,IBLK) , J=ll, It},
S*MET(20,IBLK), I8LK=1,5)
(*SNPST(J ),J=1,7), (ASNRSTU
( I ELK, (ASNRSU, IBLK ),J=i,7),
,ASNRS(20, IBLK), IBLK=l,5)
) , J3 1 1
t
) , J*il
(ASNRS
(*SNPCT(J) ,J=1,7) , (AiNROT (J), J=ll
(IELK,(ASNRO(J,I6LK), J*l,7),
,/>£NPC(20, IBLK), IBLK-1,3)
(ASNPPTU ) ,J=1,7) , (ASNRPT(J
( IELK, (ASNRP(J, IBLK), J=l,7),
,/lSNRF(20, IBLK), IBLK=l,t>)
(/SNRBT(J) ,J=1,7),(ASNR0T(J
( IELK, (ASNRBU, IBLK ),J» 1,7).
,4SNRe(20,IBLK), IbLK=l,5)
UPPER ZONE
(ASNRO
) , J*ll
*14),SNTMET(20)
,14),ASNRST(20>
(J, IBLK),J=11,14)
,14),ASNROT(20)
(J,IBLK),J=11,14)
,14),ASKRPT(20)
(ASNRP(J,IBLK),J=11,14)
) , J= 1 1
(ASNRB
(tNTMET(J) ,J=l,7),(UNTMErU),J=ll
( IELK,(UNMfcTU,IBLK), J=l,7),
(L^HET(J,IBLK),J=ll,14)r
L^^'ET(20,IBLK) , IBLK =1,5)
(LNITHT(J),J=L,7), (UNITHT(J
(IBLK,(UNIMET(J,1BLK),J>1,7
(LMMEKJ.IBLK) , J=ill,14),
IMMEK20, IBLK), IBLK-1,5)
(ALNPIT(J),J=i,7), (AUNKIKJ
(IELK,(AUNRI (J, IBLK), J=l,7),
,f LNRI120, I8LK) , I6LK=i,5)
(/UNPPKJ ) ,J=1,7), (AUNRPTtJ
(IELK,(AUNRP(J,IBLK), J=l,7),
,/LNPP(20, IBLK), IBLK=l,5)
(/1UNRBT(J) ,J=1,7) , (AUNRBI (J
(IELK,(AUNRb(J,IBLK), J=l,7),
,*LNP£(20,IBLK), 1BLK=1,5)
) , J=ll
) t
) » J=l I
(AUNRI
), J=ll
(AUNRP
) , J= 1 1
(AUNRB
,14),4SNRBT(20)
(J,IBLK),J=11,14)
,14),UNTCET(20)
,14),UNITMT(20)
,14),AUKRIT(20)
(J,I8LK),J=11,14)
,14),AUNRPT(20)
(J,I8LK),J=11,14)
,14), AUKRBTI 20)
(J,IBLK),J=11,14)
LOWER ZONE AND GROUNOHATER
287
-------
Appendix C (continued)
7610.
7611.
7612.
7613.
7614.
7615.
7616.
7617.
7618.
7619.
7620.
7621.
7622.
1623.
7624.
7625.
7626.
7627.
7628.
1629.
7630.
7631.
7632.
7633.
7634.
7635.
7636.
7<37.
7638.
7639.
7640.
7641.
1642.
7643.
1644.
7645.
1646.
1647.
7648.
7649.
7650.
1651.
7652.
76S3.
1654.
7655.
7656.
7657.
7658.
7659.
7660.
7661.
7662.
7ECO.
7EC1.
7EC2.
7E03.
7C04.
7EC5.
7E06.
C
C
C
120C
121C
1220
C
C
1300
C
C
C
4CCC
4CC5
4C10
4C2C
4C30
4C40
4050
4C6C
4C70
4060
4CSC
4100
411C
4120
4130
4140
C
C
C
C
C
C
C
WRITE (6,411C)
WRITE (6,4020) (LNfET(J) , J»l ,7) , (LNMbT( J ), J= 11, 14) ,LNKET( 20)
WRITE (6,40«C)
WRITE (6,4010) (*LNRP(J) ,J«l ,7) , ( ALNRPU ) , J= 11,14) , ALNRPC20)
WRITE (6,40(C) (/LNRB(J) , J*l ,7) , ( ALKKB( J) , J» 11, 14) , ALNRG (20)
WRITE (6,412C)
WRITE (6,4G2C) (GKMETI J) ,J«1 ,7) , (GNKETC J ), J= 11,14) ,GNMET(20)
WRITE (6,404C)
WRITE (6,40EC) ( *GNR8(J) , J«l ,7) , ( AGNRB( J ) , J= 11,14) , AGNR6420)
ZERO OUT ACCUMULATIONS AFTER PRINTING
CO 122C J-1,2C
OC 1210 IBll-'ltS
ASNRS (* i lElM 0.0
ASNPC (« , I£l> ) 0.0
ASNPF <„ , If IK) 0.0
ASKRB («f IELK ) 0.0
ALNRK-.IEIK) 0.0
AINRPU.1EIK) 0.0
ALNR6 (J • IEIK) 0.0
AhRSU tJElM * 0.0
CCNTINLE
ALNFF(J) " O.C
ALNRC ( J) * O.C
AGNRE(J) * O.C
CCMINLE
PETLRK
FORMAT CC'.'MjTPIENTS - • ,A5,11X, 'ORG-N' ,3X, 'NH3-S' ,3X, 'NHS-A*
1 5X« *HC2' ,5X, 'N031 ,6X, «N2* , 2X , • PLNT-N1 »3X, 'ORG-P' ,3X,
2 'F04-S' ^2>,t9Q^-A< ,2X,'PLNT-Pf ,oX,'CL»)
FCRMAT CO')
FCRMAT 'C' ,3X,'SLRFACa LAYER' )
FORMAT •G* ,6>, 'JTORAGE1 , 12X.F8. Ot6F8. J,Ftt. 0, 3F8. 3tF8. 3)
FCRKAT ' • ,12X,'FLCCK'f 1 2,6X ,F8.0 ,6F8.3,FB.O ,3F8 .3, F8.3 )
FORMAT 'C'.tX.'FEMCVAL')
FCRMAT •G',S>,'t'CVERLAND FLCW ,3X,Fti.O,6FS.3f F8.0 ,3F8.3,F8.3)
FCPMAT 'C* ,S>t'FERCCLATiCN',5XfF8.0,6Ftt.3,F8.0,3F8.3,F8.3)
FCRMAT *C' ,9), 'E 1CLCGICAL' ,oX,F6.0,6F6.3,F6.0,3F 8.3,F8.3)
FCRMAT «C' ,i>» UPPER ZONE')
FORMAT '0' ,9>, 'IMERFUOH* ,7X,Fd.O,6Fd.3, Ftt.O ,3F8.3,F8.3 )
FORMAT '0' ,2>,'lCHEft ZONE')
FCRMAT ' 0 • , 2X, • CFCUNCHATER* )
FCRMAT (•*• «4CX,CF8.3,4X,2F8.3)
FCRMAT (' -,,SF8.1)
ENO
SL8RCLTIKE TP/KS (DELT, IZONE,N,NB,KN,THKN,KP,THKP ,T,OELN ,OELNB)
THIS SUBROUTINE
288
-------
Appendix C (continued)
1EC7.
76C8.
78C9.
7610.
7611.
7612.
7813.
7614.
7615.
7816.
"iU7.
7618.
7619.
7620.
7621.
7622.
7623.
7624.
7625.
7626.
7627.
7628.
7629.
7630.
7631.
7£32.
7633.
1*34.
7635.
7836.
7£37.
7638.
7139.
7(40.
76L*4 N(2C),OEL1,DELN(20)tC(20,20)/400*0.0/t
1 KNUG,4),Ti-KNUO» iKP ( 3 ,4) , THKP (5 ) ,T 14),
2 Ne(iC,£),C6LNB(20,5),SUM,RcLT,FTN(10),FTP(5),
3 KK(IC) ,KFC(5)
INTECEP44 IFCti,ICCL.IBLK,IZONE
IF (IZCfiE.EC.l .CP. IZQNE.EC.2) GO TO 310
TEMPERATURE CORRECT ION OF REACTION PATES
IF (TU2GKE) .GE. 35) GO TO 37
PELT = T(IZCKE) - 35k
CO 35 J*1*1C
FTh(J) * ThKKJJ**RcLT
CCNTINLE
CC 36 j-1,5
FTP(J) * TI^KI
CCNTINL'E
GC TC 4C
CO 38 J«1,1C
FTN(J) = 1.0
CCN7IME
289
-------
Appendix C (continued)
7667.
7£68.
7665.
7870.
7£7l.
7672.
7£73.
7874.
7£75.
7£76.
7£77.
7678.
7£79.
7660.
7681.
7662.
7683.
7££4.
7665.
7666.
7££7.
7888.
7E89.
7£50.
7651.
7652.
7£53.
7E54.
7855.
7656.
7£57.
7658.
7£59.
75CO.
7501.
7502.
7503.
7504.
75C5.
75C6.
7507.
75C8.
7509.
7510.
7911.
7512.
7513.
7514.
7515.
7516.
7517.
7518.
7519.
7520.
7521.
7522.
7523.
7524.
7525.
7526.
35
C
40
41
42
C
C
C
C
C
C
C
100
2CO
3CO
C
C
C
C
C
C
C
310
CO 39 J»lt!
FTF(J) -
CCNTINLE
CO
1.0
41 0*1,10
KNC(J) =• Ic<«)
> -KFCU)
) KFC(2I
) KFCC1)
) -«KPC(2) + KPCI4)
) K FC ( * )
) KFC(4I
) -KPCC5)
) * KFCOI
KNC17))
KNC(8)J
+ KPC(3)I
SOLUTION
DO 200 IRCV«1,2C
SUH « O.C
DC 100 KCL-1,20
SIM « SLK 4 CdROW, ICCL>*N(ICOLI
CCNTUUE
DELMIPCV) * CELT*SUN
CCNTINtlE
CO 300 J-1,20
MJ) * K(J) » CELN(J)
CCNTIhLE
PETLPN
FOLLOWING SECTION IS FOR THE BLOCKS
USED IN THE SURFACE ANU UPPF.R ZONE
TEHPERATURE CORRECTION OF REACTION PATES
IF (T(I2CNE) .CE. 35) GO TC 370
290
-------
Appendix C (continued)
7927.
7528.
7529.
7930.
7521.
7532.
7523.
7534.
7S35.
7936.
7S37.
7538.
7539.
7940.
7941.
7942.
7943.
7944.
7945.
7946.
7947.
7948.
7949.
7950.
7951.
7952.
7953.
7554.
7955.
7556.
7557.
7558.
7559.
7560.
7961.
7562.
7563.
7964.
7565.
7566.
1567.
7<68.
7569.
7570.
7571.
7572.
7573.
7574.
7575.
7576.
1577.
7578.
7579.
7580.
7581.
79E2.
79E3.
79£4.
79E5.
75E6.
350
360
370
3EC
350
C
4CO
410
420
C
C
C
C
C
C
C
4SO
SCO
PELT = T(IZCKE) - 35.
CC 350 J»1,K
FTN(J) = ThKKJ)**RELT
CONTIM.S
CO 360 J-li5
FTPU1 * 7»-KF(J|**RELT
CCN1ULE
CO TO 4CO
CC 380 J=l»10
FTN(J) » 1.0
CCNT1NIE
CC 390 J-ltS
FTP(^) » 1.0
CCNTINtE
CO 410 J*lilC
KNC(J) = KMv,lZCNE)*FTN(J)
CCNTINtE
CC 420 J=l,5
KPC(J) * KM.,IZCNE)*FTP(J>
CCNTINLE
DEVELOP COEFFICIENT ARRAY
C(lti) = -K>CI6I
C(lt2) « KhC(l)
C(l,5) K^C(E)
C(2.1) = K^C(6)
C(2,2) - -(KNC(S) * KNC(l) + KNC(7)1
C(2,3) = KrC(lO)
C(3,2) - K^C(5I
C(3i2) => -(^C(1C) * KNC(D)
C(4,2) * K^CU)
C(4,2I * KKC(l)
C(4,4) -tt » KNCI2U
CI4.5) K^C(3)
C(5,4) KNC(2)
C(5,5» -(Ch((2J » KNC(S) « KNC(8))
C(6»4) KtC(4)
C(7.5I - KNCC1
Cdl.ll) « -KFCU)
C(U,12) > KK(FC(5I
CUB. 12) * KFCIO
C(13,13) - -KFCC!)
C(14,12) - *-FC(2)
SOLUTION
CO 7CO m»*l«!
DC 500 IFCk'lfZO
SLM » C.O
CC 45C ICCL*1.20
Slh > SIK * C(lROWtICOL)*No(lCOL.I8LK>
CCNTIM.E
CELh6(IFCV,IELK) « C£LT*SUH
COMIKLE
291
-------
Appendix C (continued)
79E7.
7988.
7989.
7990.
7991.
7992.
7993.
ECCO.
ecoi.
ECC2.
8C03.
8CC4.
ecos.
ECC6.
8C07.
ECCS.
ECC9.
8010.
ECU.
8012.
8C13.
6C14.
8015.
8016.
8C17.
8018.
6C19.
8C20.
8C21.
8C22.
6C23.
8024.
8025.
8C26.
8C27.
8028.
EC29.
8C30.
8031.
8032.
8033.
EC34.
8C35.
8C36.
EC37.
EC38.
8C39.
8C40.
8041.
8C42.
8043.
8C44.
8C45.
8C46.
EC47.
8048.
EC49.
8C50.
8C51.
8CS2.
6CO
7CC
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
DC tCO >*1,2C
NE(J.IBLK) - NB(J,IBLK) * DELNBi J,I BLK)
CCNTINLE
CONTINUE
RETURN
END
SIBRGLTINE CITHC* ,F3,/,C*LB,PRCD,PEST,NUTR,cNGL,METR,BCTH,RESB,YES,NO,
2 IKIN,UR,JF,JCGUNT,PRINT,INTR,OAYS,hCUR,MNTH
1NTEGER*4 FRM *E ,»-YCAL, OUTPUT, TIHFAC, 1MIN, IHR,TF, JCOUNT ,
1 C ALE, FPCD,ENGL, MET*, BOTH, YES, NO, PEST, NUTR
REAL*4 RL',hmN,CPST,LZS,AREA,RESBl (b) ,ROSB<5) ,SPGX (5 1 , INTFC5),
1 RGX(5 )tINFL(5J,UZSB(5),APERCb(5),RittJ5),EPSN(5 J,RESB(5),
2 f ,F2 ,*
CCM>-CN /LfNC/ *Mh,PRTOT,ERSNTT,PRTOM,£RSNTM,CAY,
1 RLTC^I,^EPTC^,FC£^C^' ,RITOM,RI.NTOM,b*.STjM,RCHTCH,RlfrOT»
2 NEPTCT,RC£TCT,FITCT,RINTOT,oASTGT,KChTOT,TwBAL,EFTCM,EPTOT,
2 UZ £, LZ £K, L25^,1^FIL, INTER, IRC, NN,L,SS,^uMl,PR,SGh, CMS, KV,
4 K24L,KK24,KiAEL,EP,IFS,K3,EPXM,REiSl,KciS,SCEP,SCEPl,SRGXT,
5 £RGXTl,JFEF,KREF,JSER,KSER,6REKT,hMPIN,METOPT,SMCW,CCFAC,
6 SCF,ICNS,F,CGM,VC,^PACK,EVAPSN,MELtV,TSNOW,PETMIN,PETKAX,ELDIF,
7 DEkX,F*CK,CEFTh .KCNTh, SDfcN, I PACK, TM IN, SJrtSNM , PXSNM,XK3,
£ ^'ELR«^,RAC^E^',CCF^E^',CKAI^M,CUNMEM,iGMM,S^EGfM,SEVAPM,SUMSNY,
9 PX£NY^ELP/*,F/l>EY,CL)RMEY,SGMY,CCNKcY,CRAINY,SNEGMY,SEVAPY,
* 1SNEAL,CCVEF,CCVFMX,RUBTCM,KOBTCT,KXB,RUITOM,ROITOT,INFTOM,
1 INF TOT, ERSTC M, E F £TCT,SRER,TdMPX, RAD ,W1NUX, RAIN, INPUT
REAL*8 MN4M12)
REAL*4 PPTCT,EF£NTTtFRTOM,£RSNTM,RUTOH,KlTOMfRINTOM,BASTOM,
1 RCH1Cf-,FnOTfN£PTCT,RCSTOT,kITGT,RINTCT,e*STOT,RChTOT,
2 TV«E^L,EFTCM,EFTOT,U/S,UZiN,LZSN,INFIL,INTER,IRC,
2 NN, L,<£ ,£GW1,PR,SGW,GHS,KV,K^4L,KK24,K24EL,EP, IF£,
4 K3,EF>M,FESSl,RESS,SCEP,i>CLPl,SkGXT,SRGXTl,JRER,XRER,
5 J£EF,l«SEF,SFEfiT,M»'PlU,METOPT, NcPTLH. ,ROSTOH,
t CCF/C,£(F,ICNS,f ,DGM,rtC,»'PACK,=VAP^N,fELev,TSNCW,PETMIN,
7 PETM>, EICIF, DEUX, PACK, DEPTH, SoEN,IPACK,TMIN,SUM£NM,
9 PXSM"»XK2 ,HELRAM, RAOMEMfCUFiMtM t Ck AiNM ,SGMM,SNEGMM,SEVAPN,
A SL»-£NY,F>£NY,MELRAY,RAOMfcY,CDRMEY,SGMY,CaNKEYf
E CRAUY,^EGMV,S&VAPY,TSNtAL,CU^MEM,
C CCVERtCCVFMX,ROBTOH(^) , RCbTO T (5 ) , KXB ( 5 ) , R CITCM (5 I,
C RCITCTt '. ) ,INfTCH(5),iNFTbT(5),cK3IOM( 5),ERSTCT(5),
E £REF(5) ,TEMPX(24J ,RAU (24 ) ,W1NDX (24) ,R «1N( 288 I
292
-------
Appendix C (continued)
8C53.
8C54.
€C55.
£C56.
8CS7.
8C58.
8C59.
8C60.
6C61.
8062*
8063.
8C£4.
acts.
£C66.
€U7,
8C68.
8069.
8C70.
8071.
£C72.
8073.
8C7A.
8075.
£C76.
8C77.
8C78.
£C79.
8C80.
8C81.
8CE2.
8C£3.
EC£4*
8C£S.
6C86.
8C87.
8C88.
8C89.
8C50.
8C91.
8CS2.
8C93.
8CS4.
8CS5.
8CS6.
8CS7.
acse.
8C«.
8100.
8101.
8102.
8103.
8104.
8105.
8106.
£107.
8108.
8109.
8110.
8111.
8112.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
1
1
2
^
4
5
e
7
£
1
1
2
3
4
C
6
7
1
1
2
3
4
C
1
1
2
o
4
5
6
7
£
1
1
2
a
4
5
£
7
C
INTEGER** C,M,£PRCTT,SPRSTT,MlU,FPU£,UPRITK,
2 UPRmfKGPie,FH2,VlZ,LSTR,l_AS,LCS,LUS.GSTf<.,GAS,GCS,GOS,
DEGSCF,CEG£C1,CECUO,
DEGLC1.CECL tCECS .NIP.DEGCON,OEGLOM,OtGLOT,NCCM,
PRSTCf ,PPS1CT,FFCTC^,PROTCT,UPITOK,lJPIIaT,STStUTS.SASf
SCS,£CS,SSlF,U/i,UCS,UOS,USTR,UPKlS,UIST,IOTPAP,TlMAP,YEARAP.
£ DESOPP,SLRF,EGSOT, Lit GUUM.DEGUOT.DEGU, DECS.
MF,CEGCCN,D£GLJM,0£GLOT,NCOK,
PRSKM J),PRSTOT(b),PROTCM(5),PRaTCjT(5» tUFITOM(5»t
UFnCT{5),STS(5),UTSO),SA^(5J,SCSl5)fSDS(5)fSSTR(51,
LAS(i) ,ICS(5) ,UOS(3) ,USTK(5) ,UPhIS(5) tUIST
INTEGER** *F^CCE,DESCRP,SURF,SOILtTIMAP,Y6ARAP
COMMCN
/KLT/ C£Ll,STEMP,SN,SNT,SNRSH,SNROM,UN,UNT,UNI,tMT,
L^RI^•,NR5>',LNfL^KPM,GN,iNR6M,UNRB^',LNPBM,G^RE^lfTNRBM,
SKRIY,SNROY,UNRIY,NRSY,LNKPY,SNRBY,UNPBY,LNPeY,GNfBY,
INFEYfTNRhVrTNRHVMtTNKhVYfTNA.TPAtTCLA,
TSTEF,NSTcP,SFLG,UFLG.Lf CG.GFLG
S^(2C,5)ȣNT(20)tSNF^SM120>5) ,SNROM( 20,51
UK(2C,5),LNT(20) ,UNI(20,!>) tUMT(20) ,UNRIM (20t5 )
NRSM20,;).
., GN(20)i
,UNRBh(20t5),LNRBM(20),GNREM(20),TNRe»'(20»f
,SNKOY(20,5) ,LNRIY12U,5) ,NRSY(20,5) ,
LNFFY(2C),SNR6Y120,5) ,UNKaY120,5) ,LNRBY(20) ,GNRBY<20)t
TNPEY(2C) .TNRhV(20) tTNRHVM(^O) ,TNRHVY(20) ,TNA, TP A, TCL *t
,NbAL. PH EALt CLB AL
INTECEM4 1SIEI^STEP,SFLG,UFLG,LFLG,GFLG
HYDROLOGY AND PESTICIDE VARIABLES USED
INTERNALLY
REAL** PRT/C.Oy ,FRTT,PRTTCM(i) ,PRTTCT(5J ,OEGTOM,CEGTOT,
DEC 1/C.C/t PEAL, COVK.PACKMM.TSNBMM,
U2Sf-ET,L2SKEI,SG«KcT,SCcPMT,KtSSMT,
UASI^T.LCJTMT.UOSTMT.LSTKMT.LASMcT.LCSFET.LDSMET,
G£^F^^.C;S^'ET,GCS^'ET,GuS^'.ET,L.EGTrtT,CECSMT,DEGUMTt
DEGLM,lFEALM,UZS6MTt5) ,KfcSbHTl3» ,SRGXMT(5)»
SPEFFT(«),STSMcT(5) tSASMtTti ),SCiMET(5) ,SCSHET{51,
L1S»-ET(«),UASKET(5) .UCSMET (a ) .UDSMET (5) .UPRISM (5 I
293
-------
Appendix C (continued)
8113.
£114.
8115.
8116.
8117.
8118.
8119.
8120.
8121.
£122.
8123.
8124.
8125.
8126.
8127.
£128.
8129.
8130.
8131.
8 132.
8133.
£134.
8135.
8136.
8137.
8138.
6139.
£140.
£141.
8142.
8143.
6144.
8145.
£146.
8147.
£148.
£149.
3150.
8151.
£152.
8153.
8154.
8155.
6156.
£157.
8158.
8159.
BUO.
8161.
CU2.
£163.
8164.
8165.
8166.
£167.
£168.
£1£5.
£170.
8171.
8172.
C
C
C
1
2
3
4
C
t
7
C
C
C
C
C
C
1051
C
C
C
C
C
S73
C
C
C
C
C
C
S89
951
C
C
C
NUTRIENT INTERNAL VARIABLES
PEAL*8 CCNC, LEF/C/«LB/AC'/t KGPHA/ "KG/HA1/
PE*L*4 N6ALM f FI-ELPTfCLBLMTf
ShfE1(2C,5),SNTMcTl20),UNMET(20,5),UNTKET(20),
LM-E7(2C),GNMET(i:OJ,iNRiMT(20) ,SNROHT(20),
UNPIM(2C),SNRBMT(20),UNRBMT(20),NRSPT(20),
NPSYT(2C),SNRSYT(20>i SN*uYTUO),SNRBYT(20),
UNP.m(2C),UNRBYT(20),UNITMTUO*,UNI*ET(20,5),
TP(20)/2C*0.0/,TNR,TPK,TCLR,TNS,TPi,TCLS,
£Lf,£LK£,£UfO,SUMI,SUMd,iUKRS, CONVF/1.121/
PCNTHLY SUMMARY
IF (PEST .EC. NO GO TO 973
CC 1051 1- |,5
•PRnCMI) = FPSTCH(I) * PROTCM(I) + UPITOM(I)
CEGTCP - CEOSCM + DEGUCM + OEGLOM
CECT - CECT « DEGTOM
PRTM - JFPCTM * SPRSTM * UPR1TM
PPT PFT + ffJ*
P8*L * J15T + LTST * LSTR » GSTR *• P*T + CEGT - TOTPAP
IF ((FEAL .IE. 0.0). AND. (PBAL .GE. -0.0009)) PBAL = 0.0
IF (JCCIM.LI.TIJ'AP .AND. YEAK.LE. (YEARAP*1900) J PBAL » 0.0
7PEAL * TFE/L * PBAL
IF (NLTR .EG. NCI GO TO 990
COMPUTE MONTHLY NUTRIENT TOTALS BY /ONE,
ACCUMULATE YEARLY REMOVALS,
COMPUTE TOTAL N, P, CL MASS BALANCES
SURFACE
DC 991 J-1.2C
SL»»« * C.C
StPC * 0.0
SL*e - c.o
SNT(J) =• C.O
CC *E9 IEIK>1,5
Sl^S ' 5tfS * SNRSM(J,IBLK)
5LKC - StAC *• SNROM(J,lBLKi
SLfB * SL^E + SNRBM(J,IBLKJ
£NT(J) > £M(J) v SN(J,I8LK)
CCNTIKLE
SNPSt-T(J» • Sl.f'S/S.
SNRCKT(J) » SLfO/5.
SNRBMU) * SLfB/5.
SNT(JJ * £NT(J)/5.
CCNTINtE
UPPER ZONE
294
-------
Appendix C (continued)
6173.
£174.
£175.
8176.
£177.
6178.
8179.
8180.
eiei.
8162.
8183.
8184.
81£5.
8186.
£1€7.
8188.
8189.
8190.
£191.
8192.
8193.
8194.
8195.
£196.
8197.
8198.
€199.
8200.
£201.
8202.
82C3.
8204.
8205.
8206.
£207.
£2C8.
£209.
8210.
8211.
8212.
8213.
8214.
8215.
8216.
£217.
8218.
8219.
8220.
8221.
8222.
6223.
8224.
8225.
8226.
8227.
8228.
8229.
£230.
£231.
£232.
992
9S3
C
C
C
994
995
C
C
C
C
C
996
9S7
C
C
C
C
C
C
C
C
C
C
C
C
C
CC 993 J-1.2C
SLPI - 0.0
SUKB = C.C
LMTIJ) =• C.O
LMKJ) = c.C
CC S92 1ELK«1,5
SIM * SLM + UNRIMU.IBLK)
SIPB - UN(J.IBLK)
LMKJ) = LMKJ) * UNKJ.IBLK)
CCMINLE
LNPIf-T(J) = SLKI/5.
LNPEMN) = SL>B/5.
LNT(J) * LM(J)/5-
UMT(J) > LMT(J)/5.
CCNTINLE
TOTAL REMOVAL TO STREAM
CC 995 J=l,20
SLHRS - C.C
DO 994 ieiK«l,5
SLhRS SLKFS * NRSH(J,IBLK)
CONTINUE
NPSfKJI SlfFS/5.
CONTIME
YEARLY ACCUMULATIONS
CC 997 J=lf2C
CC 99fc IEIK'1,5
SNRCY(J,IEIK) =
Si4RSY(J,16LK)
SNRGY(J,IBLK)
SNRBY(JtlBLK)
UNRIY(J.IBLK)
UNKBY(J»IBLK)
F>PSY(J,ieiK) = NRSY(J.IBLK) «•
CCNTINUE
LNPFXJ) * I^FFY(J) + LNRPM(J)
LNREXJ) - LNPEY(J) + LNRBM(J)
GNREY(J) * GhFEY(J) * GNRBM(J)
TNPHVYIJ) * UFHVY(J) + TNRHVM(J)
CCNTINLE
<• SNRSM(J,I6LK)
«• SNROiKJtIBLK)
* SNRBM(J,IBLKI
* UNRIMU. IBLK)
* UNKBM(J»IBLK)
NRSM(J.IBLK)
MASS BALANCES AND TOTAL REHCVALS
TR(
-------
Appendix C (continued)
EZ33.
8234.
£235.
8236.
8237.
8238.
£239.
£240.
£241.
8242.
8243.
8244.
£245.
8246.
£247.
£248.
E24S.
8250.
8251.
6252.
£253.
6254.
8255.
£256.
£257.
£258.
8259.
£260.
8261.
£262.
8263.
8264.
£265.
8266.
£267.
£268.
8269.
£210.
£271.
£272.
£273.
£274.
(275.
£216.
8277.
C278.
£279.
62£0.
£281.
8282.
8263.
£2 £4.
8265.
€286.
82£7.
82£8.
6289.
8290.
£291.
6292.
502
503
£04
5C5
C
510
511
C
512
512
C
£14
C
C
55C
C
CC 502 1EIK«1,5
SLHB » SL»E «• NRSM(J,IBLK)
CCMIME
TR(J) - 1FU) 4 SUMB/5. * TNRHVH(J)
CCNTINLE
TNP = 0.0
CO 504 0=1,7
TNR « TNJ! « 1PIJ)
CCNTINLE
TPR =« C.O
CO 505 J*llt14
TPP - Iff * TFU)
CGNTINLE
TCLR « TP(20)
INS = 0.0
CO 511 J«l,7
SLHB » C.O
CC 510 1EIK « 1,5
SLHB = SLfE 4- SMJ,IBLK) + UN(JVIBLK) 4- UNKJ.IBLKI
CCNflNLE
INS - TKS * SL^B/5. *• LN(J) * GN(J>
CCNTINLE
TPS = C.O
CC 513 J>11,14
SLFE = O.C
CC £12 lELK-1,5
SLPB £U^E * SN(JtlBLK) »• UN(J,IBLK) * UNKJtIBLK)
CCMIKLE
TFS « TPJ + 5LKB/5. + LN(JI * GN(J)
CCNTINLE
PhEAL - TPS * TFP - TPA
SLHB * C.O
CC 514 lELK'lt:
SLHB = SLPE « SN(20tIBLK) * UNUO,IBLK> * UNI ( 20, IBLK )
CCNTINLE
TCLS * SUf.6/5. * LNI20) * GN(20j
CLBAL » TCLi < TCIR - TCLA
VRITE (6,12CO) MNAM(HONTH), YEAR
VPITE Utl2Cl)
VFITE (6,11C3I
IF (CUTFLT.EC. fETR) GO TO 1053
WRITE U.36C)
WRITE (6,262)
WRITE (6,362) PCETCC, ROSTOH
WRITE (6,364) IhFTCC, RINTOM
WRITE (6,26*) RITCN
WRITE (6,36<) PCITCf, RUTOH
WRITE (6,3£C)
WRITE (6,361)
WRITE (6,361) FFTCFfPRTOMTPRTOK,PRTOH,PRTOH,PRTOM
IF (SNCW .EC. NO GO TO 1071
WRITE (6,47£) SOSN»>
296
-------
Appendix C (continued)
8293.
6294.
€295.
6296.
8297.
6298.
6299.
6200.
82C1.
8202.
£303.
8304.
6305.
6306.
8201.
83CB.
82G9.
8210.
8311.
8212.
8213.
6*l,SRGXT
TVEAL
(6,489) TSNBAL
(SNO.EC.YES) ViRITE
WRITE U,12C9)
WRITE (6,1210) fcKSTOH, ERSNTM
WRITE (6,1211) SRER, SRERT
IF (FE51 .EC. NO GO TO 974
WRITE
WRITE
WRITE
WFITE
WRITE
VFITE
WRITE
WFITE
WRITE
WRITE
WFITE
WRITE
WPITE
WFITE
WRITE
WPITE
WRITE
WRITE
WRITE
WPITE
WRITE
WPITE
WRITE
WPITE
(6,1220)
(6,1221)
(6, 1222)
(6, 1223)
(6, 1227)
(6,1224)
(6,1222)
(6,1223)
(6,1227)
(6,1226)
(6, 1228)
(6,1229)
(6,1230)
(6,1221)
(6,1222)
(6,1229)
(6,1230)
(6,1221)
(6,1240)
(6,1241)
(6, 1242)
(6,1243)
(6,1248)
(6,1245)
STS, STST
SAS, SAST
SCS, SCST
SOS, SOST
UTS, UTST
UAS, UAST
UCS, UCST
UDS, UOST
UPMS, U1ST
LSTR
LAS
LCS
LOS
GSTR
GAS
GCS
COS
PRTTOM, PRTM
PROTCH, SPROTH
PRSTOK, SPRSTM
UPiTCH, UPR1TM
OEGTCH
297
-------
Appendix C (continued)
8353.
£354.
8355.
8356.
1357.
8358.
£359.
£360.
£361.
£362.
€263.
8364.
8265.
£366.
8367.
8368.
8269.
8370.
8271.
8372.
€273.
£374.
8275.
£376.
£277.
£378.
£379.
8380.
£281.
8282.
8283.
8284.
£365.
8386.
8287.
8288.
£389.
83SO.
8291.
8392.
8393.
8394.
8395.
8396.
8397.
£398.
8299.
£4CO.
£401.
£402.
£403.
8404.
64C5.
£4C6.
£407.
84C8.
£4C9.
£410.
8411.
£412.
C
C
C
C
C
C
C
C
C
C
S74
WRITE (6,1246) DEGSOM
ViRITE (6,1247) OEGUOM
WRITE (6,1252) DEGLGM
WRITE (6.1266) TPBAL
IF (NITP .EC. NO) GO TC 1053
CCNC
fcRITE
hRITE
V.PITE
kRITE
hRITE
1
hRITE
WRITE
1
WRITE
hRITE
1
V.RITE
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2
3
4
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(6,1C<2)
(6.4CCC)
<6,4CC«)
(6,4CC6)
(6,402C)
(6,4CC7)
(6.402C)
(6,4015)
(6.4C2C)
(6.4CC8)
(6,4CCS)
(6,4011)
(6,4012)
(6,4013)
(6,4C2C)
(6,4014)
(6,4C2C)
(6,4015)
(6,4C2C)
(6,4016)
(6,4C17)
(6,401£)
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(6,4021)
MONTHLY NUTRIENT OUTPUT
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(SNTU) ,J=1,7), (SNT( J),J=ll,14),SNT(20l
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,LN(20,IBLK), IfaLK=l,i>)
(LNIT(J),J=l,7),(UM J(J), J=ll,14) .UNIT (20)
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1,7) , (TNRHVH(J),
CLBAL
1052 IF (C11FIT.EC. EhCL) GC TO 1055
COVERJICN* 1C ^ETFIC
PARAMETERS CEFUED FCR VARIABLES NOT RESET TO ZERO.
PRTCt- =
POSTCf-
RITCK =
PLTC^ •
BASTCf
298
-------
Appendix C (continued)
£414.
6415.
8416.
E417.
6418.
£419.
£420.
£421.
6422.
£423.
£424.
£425.
6426.
£427.
£428.
6429.
£430.
£421.
8432.
£433.
£434.
£435.
£436.
£437.
£438.
£43S.
6440.
6441.
£442.
8443.
£444.
6445.
£446.
£447.
£448.
£449.
£450.
6451.
£452.
£453.
£454.
£455.
8456.
£457.
£458.
£459.
£460.
6461.
£462.
6463.
£464.
£465.
£466.
6467.
£466.
6469.
£470.
£471.
6472.
EPTC* -EFTCMtPFI*
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299
-------
Appendix C (continued)
6413.
RCI7CMI
UZSBfld
£415.
€416.
£417.
£418.
£479.
£460.
£4E1.
8482.
£4£3.
84E4.
8465.
8466.
£467.
8488.
£4£9.
8490.
£491.
8492.
£493.
8494.
8495.
£496.
£497.
£498.
£499.
£500.
£501.
£5C2.
E5C3.
E5C4.
85C5.
85C6.
£5C7.
£5C8.
65C9.
8fio.
8511.
€512.
8513.
8514.
£515.
8516.
£517.
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8519.
E*20.
£521.
£522.
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££25.
£526.
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E«29.
8530.
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300
-------
Appendix C (continued)
6 J33.
8534.
£535.
££36.
£537.
£538.
££39.
££40.
££41.
8542.
££43.
(£45.
8*46.
£547.
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(550.
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££56.
£557.
£558.
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£560.
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(£73.
£514.
(£75.
(576.
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8582.
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IF (
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WRITE
WRITE
WRITE
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WRITE
WRITE
WRITE
WRITE
WRITE
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(6,1210
(6*1211)
FEST .EC
(6,12C1)
(6,12211
(6, 1222 )
(6,1223)
(6,1221)
(6,1224)
(6,1222)
(6,1223)
(6,1221)
(6,1226)
U,122€)
(6,1229)
(6.123C)
(6,12-1)
(6,1232)
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- ShT(J)*CCNVF
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» IMT(J)*CCNVF
U(J)*CCNVF
GMJ)*CCNVF
301
-------
Appendix C (continued)
E5S3.
£594.
£595.
£596.
£597.
££98.
£599.
860C.
66C1.
£6C2.
££03.
££04.
86C5.
66C6.
8607.
£608.
86C9.
8610.
8611.
8612.
8613.
£614.
£615.
8616.
8617.
£618.
£619.
£620.
£621.
6622.
8623.
8624.
£625.
£626.
£627.
8628.
£629.
8630.
£631.
8632.
E633.
£634.
£635.
£636.
£637.
£638.
8639.
8640.
8641.
8642.
8643.
£644.
£645.
£646.
£647.
£648.
£649.
£650.
8651.
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CCNTIME
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(6,4013)
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(6,4015)
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ZEFC^G OF VARIABLES
FPTC»« « O.C
302
-------
Appendix C (continued)
8453.
865*.
8655.
8656.
£657.
8658.
8659.
8660.
8661.
£662.
8663.
£66*.
6665.
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£668.
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6670.
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8687.
8668.
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8693.
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£698.
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6709.
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0.0
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522 CCNTINU
C
1C6C RETVJRK
C
C FORMATS
303
-------
Appendix C (continued)
8113.
6114.
8115.
€116.
£117.
6118.
£719.
8720.
£121.
8122.
8723.
8124.
£125.
8120.
8127.
6128.
8129.
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6131.
8122.
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8140.
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£148.
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8750.
8751.
£752.
£153.
£154.
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3764.
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1221 FORMAT
1226 FORMAT
122S FCRMAT
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1221 FCPMAT
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1242 FORMAT
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• ; nx.'SECIMENT REMOVAL' ,t>X,5t 'PESTICIDE DEGRADATION LOSS, LES.'l
'0* 6>, 'PESTICIDE DEGRADATION LUSS, KGS.1}
•1' 25X,'£UMfAKY FOR ',I4»
• ' IIX.'FRCM LUHER ZONE ' t 5faX. F7.31
•C' 11X, 'PESTICIDE BALANCED ,F8.41
•0' ,£>,'VATER, INCHES')
'C' ,11X,'FLNOFF'1
' ' ,14X,'CVERLAND FLOW , 5X ,i (Fd.3 t2Xl ,1X, F8. 31
' ' t14X,MNTERFLOta',9X,5(F6.3,2X)tlX,F8.3)
1 ' ,14X, 'IMPERVIOUS' ,59X,Ffa. 31
' ' , 14X,'TOTAL' ,i3X,5(F8.3,2X) ,IX,F8.3)
•C* illXt'EASc FLOW ,&3X,FB.3l
• • ,1 IX, 'GREATER RECHARGE', 55X.F8. 31
*C* , HX,'FRECIPITATIJN',oX,SlF7.2,3X) ,IX,F7.21
' « ,14X,«SNCW,6f>X,F7.2)
• ',14X,'FAIN ON SNOW ,57X,F7.2)
' ',14X,'tELT f> KAIN1 ,58X,F7.2l
•C't llXt^ELT' J
' • tHXt'FACIATION' tOOX,F7.21
' • ,14X,'CCNVECT10N' ,59X,F7.2)
• • ,14X,'CC^DENSATIC.J•,57XtF7.2)
1 • ,14X,'PAIN MELT' ,oOX,F7.2l
' ' ,1OX,F7. 21
• '.11X,'? SNCM COVER' ,60X,F7. 21
•0',11X,'SNCV< EVAP' ,63X,F7.21
*0* .IIX.'EVAFQTRANSPIRATIUN* 1
5»
304
-------
Appendix C (continued)
6773.
£774.
£775.
£776.
£777.
£778.
£779.
8780.
8781.
8782.
£183.
8784.
£785.
E7E6.
£7£7.
£7£8.
8789.
£790.
8791.
8792.
£793.
6794.
8795.
8796.
8797.
€798.
8799.
8£00.
££01.
8802.
86C3.
££04.
88C5.
8EC6.
8807.
aecs.
88C9.
8£10.
8£11.
8812.
8813.
8£14.
8£15.
££16.
9COO.
9CC1.
9C02.
9C03.
9C04.
9C05.
SCC6.
9C07.
9CC8.
9CC9.
9C10.
9011.
9012.
9013.
SO 14.
9015.
C
C
C
3££
369
3E2
37C
371
372
372
374
375
376
311
489
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4COO
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FORMAT
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FORMAT
FORMAT
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FORMAT
FCRMAT
t
1
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•
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•
•
•
1
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1 .
FCPMAT CO1
1«X ,
14X,
llXt
14X,
14X,
14X,
14X,
1*X i
14X,
11X,
11X,
6 > i '
FORMAT 1'0','Ml
1 5X,«rC2i
4C05
4CC6
4C07
4CC£
4CC9
4011
4C12
4012
4014
4015
4C16
4C17
4C1£
4019
4021
4C3C
C
C
C
C
C
C
C
C
C
C
FCRMAT
FORMAT
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FORMAT
FORMAT
FCRMAT
FORMAT
1
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1
2
3
4
FORMAT
FCRMAT
1
2
3
FORMAT
END
C 1 OOfl
i lOKll.
f XJTC/tC
I PI 1 CUC
•0
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'0
•0
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•0
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•FCTENriAL',9X,p(F7.2,3X»,1X,F7.2I
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•LPFER ZONE',8X,5(Fb.j,2X»,lX,F8.3)
•LOhtR ZONE' ,ax,alho.^,2X),1X.F8.3)
•CRCUNUHATcK1 , /X,D(Fo.3,2X1 ,IX,F8 .3)
• INTERCEPT I OU« ,e>A,MFo.3,2x),lX,F8.3)
•CVERLAuO FLOht,5X,5(Fo.J,2X) ,1X,F8.3)
• INTERFLOW ,,«PhOSPHGROS
•,6>,'ChLCRIOE
•,6>,'ChLCRIOE = '.F8.3J
, 12X,'ELCCK«,I2,OX,F8.0,oF6.3,Fb.O,3F8.3,F8.3
(YEAR)
THIS SUdROUTINc OUTPUTS YEARLY
TABLES, AND ZhRCi ACCUMULATIONS
CCMMCN /ALL/ RL ,HYMIN,PfcNTKE,HYCAL,OPST,OUTPLT,TIMFAC ,LZStAREA,
" I ,POSe,SRGX,IfUF ,KGX, INFL,UZSe,APEPCB,RIBtERSN,
.- ,A«CALB,PRCO,PEST,NUTR,fcNGL,METR,BCTh,RESE»YES,NO,
INiIhRtTF,JCOUNr,PKINT,INTR,OAYS,HCUP,MNTH
305
-------
Appendix C (continued)
9C16.
9017.
SO 1 8.
9020.
9021.
9C22.
9C23.
5024.
9025.
9026.
9C27.
9028.
9C29.
9C30.
9031.
9C32.
9033.
9C34.
9035.
9C26.
9C37.
9C38.
9039.
9040.
9041.
9042.
9C43.
9C44.
9C45.
9046.
9C47.
9C48.
9C49.
9C50.
9CSI.
9C£2.
9053.
9C54.
SC55.
9C56.
9C57.
9C58.
9C59.
9C60.
9C61.
9062.
9063.
9C64.
9C«5.
9C66.
SC67.
9Ct8.
SC69.
9C70.
SC71.
9C72.
9C73.
SC74.
9C75.
C
C
C
C
C
C
C
C
INTEGEP*4 FPtvTKE.hYCAL, OUTPUT, T1MFAC,IMIN,IHR,TF,JCCUNT,
C/lE,FRCC,fcfcGL,MtTR,BQTh,Y£S,NO,PEST,NUTR
REAL*4
1
2
Rl,»-YMh,CPST,LZS,AREA,RESbl(5),KOSB(5),SRGX<5»,INTF(5)t
RGX(5), INFL(5),UZSt><^> - APERc c (5 ) ,RI B ( 5), ERSN (5 ) , PESB ( 5) ,
M,P2,^
COMfCN /LANCX *Mf ,PRTOT, ERSNTT ,PRTOK,ERSNTM, CAYt
2 NEPTCT,FCS1C1 , FHOT.RINTOT.BASTOT,KCHTOT,TWBAL,EPTOM,EPTOTt
2 LZS,LZ5N,L25N, UFIL,INTER,IkC,NN,L,6S,SGWl,PP,SGW,GWS,KV,
4 K24L.KK24,K21EI, EP , IFS,K3,EPXM.RESil.KtSS,SCEP.SCEPI,SRGXT,
5 SRGXT1.JPEF ,KREF,JSER,KSER,SRERT,MMPiN,METOPT,SNCW,CCFAC,
« SCF.ICNS.F ,CGy,K:,*PACK,EVAPSN,MEl_tV,TSNOn,PETMIN,PETHAXtei.DIF,
1r*c^v C / r* ^ FCCTk kOKTL^ v Fl C j\l T D A /~ V T M I Kl C I I Jul C Kt U D VC KlM W ^
UCWA^r^l_rvfLtr l(trUr\lrlfjL^Ci^lfirM%«^f inirMfOUnOMi^TrAjni^fA^jj
C rtLK*r^r\^l>rt* T t. L J* f t r* 11*»^ A 1 n>r>f 0 (Jl\ Me M f 5 w MM f ^i^CurMv 5 c V A H M yoUr^onivy
S PXSNY.J-FLP/Y ,P/C^EY,CURMEY.SGMY,CONVEY, GRAINY, SNEGMY.SEVAPY,
4 1SN6*L,CCVEP ,CCVFHX,ROBTGM,RG6TGT,RX6,RQITGM,ROITOT,INFTGM,
1 I NFTOT,ERSTCf,EF
REAL*4 FRTC1 ,EFJKTT ,PRTOM,ERSNT«,RUTOM,RITOM,RINTOM,BASTOM,
1 RCh1C*,FUOT,NtPTGT,KOSTOT,RITOT,RlNTCT,eASTOT,R(>TOT,
c T^E/LiEFTCM,EFTGT,UZS,UZSN,LiSN,1NFIL,INTER,IRC,
3 KN.L.SS ,£GW1 ,PR ,SGW,G^S ,KV ,«£<*(. , KK^4, K24EL,EP, IFS,
4 K3,EF>K,FESJ1,R£SS,SCEP,SCEP1,SKGXT,SRGXTI,JRER,KRER,
S J«EF,KSEF,SREfiT,M^PIN,MfcTUPT, NEPTOH.ROSTOM,
£ CCF*C,SCF,ICNS,f,OGH,WC,KPACK.EVAPSN,FELEV,TSNCW ,PETMIN,
7 PE7^AX,[lCIF,OtWX,PACK,4JfcPTh,SOfc^,IPACKfT^'IN,SU^'SNM,
9 PXShf ,Xf3,MELRAM,RACMcM,CDkM£M,CKAlNM,SGMf,SNEGMF,SEVAPM,
f ciuv.,RXe(5),RCITCM(5),
RCnCT(5),INFTGM(5)t INFTOT (5 ) ,£RSTUM( 5), ERSTOT (5 ) ,
SREF(5) ,TEMPX(24),RAU(24*,H1NOXC24),RAIN(288I
INTEGEP*4 C/Y,SKW»«CNTH
/PES1C/ il,M,SPPCTT,SPRSTT,MU£,F^U^,UPRIT»»,
2 UPRITT,KGPLE,FfL2,KLZ,LSTK,LAS,LCS,LDS,GSTR,GAS,GCS,GDS,
3 APHCDE.TFE/L,
4 DEGSCH,CEGSCT,C£GUCM,
5 CEGLGT,CEGl ,CEC£ ,NIP.DEGGCN,OcGLOM,CcGLOT, NCCH,
fc PRSTC^,PRS^CT,FFCTC^,PROTOT,UPITUM,UPITOT,STS,UTS,SASt
7 SCS,SCS,SSTF,l/<,UCS,Ui>S,USTR,UPKI$,UiST,TGTPAP,TIMAP,YEARAP,
£ OESCRP,SLRF,£CIL,SLLG
REALM SlS1,GFLB,FPl.G,MLZfLSTH,LAi,LCS,tDS,GSTR,GAS,
GC£,GCS,TFBAL,OcGSOM,UcGiUT,UcGUJM,OEGUOT,DEGUtOEGSi
MF,CEGCC^.CEGLJM,OEGLOT,NCO^,
PR SICK !),PRSTGT(b),PRGTCMlaJ,PROTOT(5»,UPITOM(5l,
UFITCT(5),STS(5).UTS(5),SAS15).SCS(5),SOS(5),SSTR|5).
tAS(5)flCS(5).UDS(5),USTR(f>) ,UPRIS (I>» tUIST
t.
2
4
c
t
7
306
-------
Appendix C (continued)
9C76.
9C77.
9C76.
9C79.
9C80.
9C81.
9C62.
9C£3.
9C84.
S0£5.
9C86.
9C87.
sees.
sees.
<»C90.
90S1.
9C92.
9093.
9094.
9C95.
9C96.
9C97.
9C98.
SCS9.
9100.
9101.
91C2.
9103.
9104.
9105.
9106.
9107.
9106.
9109.
9110.
Sill.
5112.
9113.
9114.
9 US.
9116.
9117.
9118.
9U9.
9120.
9121.
9122.
9123.
9124.
9125.
9124.
9127.
9128.
9129.
9130.
9131.
9132.
9133.
9134.
9135.
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
i
1
2
3
«
c
1
1
2
3
4
5
6
7
8
1
1
2
2
4
5
t
7
£
1
1
1
2
2
«
c
6
7
1061
INTEGEP.*4 *FKCE ,DESORP, SURF, SOIL ,T IMAP.YEARAP
CCNPCK /KCT/ CELTtSTEMP, SNtSNT , SNfcSM,SNhOM,UN,UNT,UNI »UMT,
,LNPBK,GNR EK.TNPBM,
UPEY,TKRhVfTNRHVM,TNkHVY,Ti1A,TPA,TCLA»
REAL** CEL1,) ,SKGXMT(5),
(;),STS^ET(5),SASMETlb),SCSH£T(5),SCSPET(5l,
5J ,UPRISM(51
NUTRIENT INTERNAL VARIABLES
REAL'S CCNC, LEftC/*LB/AC'/, KGPHA/'KG/HA1/
PEAL*4
NEALM.FhELf'T.CLBLHT,
SNFET(2C,5) ,SNTMET( 20), UNMET (20,5) ,UMKET(201,
L^^'ET(2C),G^NET(20),SNR5HT(20) ,SuROMT(20) t
UNF IM ( 2 C ) .SNFbMT (20) .UNRoHT (20 ) , NRSf T (20 ),
NR
-------
Appendix C (continued)
S136.
S137.
SI 38.
9139.
9140.
961
9142.
9143.
5144.
9146.
9147.
9148.
5149.
9150.
9151.
9152.
9153.
9154.
9155.
9156.
9157.
9158.
9159.
9160.
9161.
9162.
9163.
9164.
9 US.
9166.
9167.
9168.
9169.
9170.
9171.
9172.
9173.
9174.
9115.
9176.
9177.
9178.
9179.
9180.
9181.
9182.
5183.
9184.
9165.
91£6.
9187.
9168.
9189.
9190.
9191.
9192.
91S3.
9194.
9195.
IP
CO
523
524
526
C
C
971
(KtTR .EC. NO £0 TO 977
526 J*1,2C
SLfS « O.C
SUt'C » C.C
SUHB « 0.0
DC 523 ieiMl.5
SLMS
SLHC
SLfJ
SNKSY(J,IBLM
SNROY(J,1BLK)
CCM1ME
SKPJYTIJ)
SNPCYT(J)
SlKS/5.
JLI-0/5.
SlPB/5.
UNR[Y(J.I8LK)
UNRBY(J.IBLK)
» O.C
SLffi - C.C
DC 524 IEIK'1,5
SL^I = SUM *
SLMB » Sl>E *
CCNT1ME
LNPIYT(J) « JLM/5.
LKPEYT(J) » flfByS.
SLfFS » C.C
CC 525 IElK-1,5
Sl^RS = SL^FS * NRSY(JrI6LKI
CCNTIM.E
NFSYKJ) - FS/5.
CONTIME
k-RITE (6,1250
kRITE (6,12511
VR1TE (6,1103)
IF (CLTFCT.EC.
YEAR
VRI7E
hRITE
WRITE
VRITE
V.RITE
hRITE
WRITE
(6,36C1
(£,362)
«,362)
(6.36O
«,2£C)
U.3E1)
GO TO 1066
PCETOT,
UFTCT,
RHCT
PCI7CT,
E/HOT
RCHOT
ftOSTOI
RINTOT
RUTOT
oniic ictzcii rvriui
WRITE (£,361) PFTCT,PRTOT,PRTOT,PRTOT,PRTOT,PP.TOT
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
NO GC
Slf-SNY
IF (SNCV .EC. NO GC TO 1072
WRITE (6,47t)
(t,47«)
(6.46C) CEIFAY
U,4M)
(6,482)
(£,46-)
(£,464)
(6,48f )
(6*466)
(6,467)
(6.490
CCVP = ICC.
IF (PACK .IT. 1PACK) COVP. = (PACK/IPACK 1*100.
CC^^'EY
CCFCEY
CF/INY
ShEGMY
308
-------
Appendix C (continued)
9196.
9197.
9198.
S199.
9200.
9201.
9202.
9203.
9204.
9205.
92C6.
9207.
9208.
9209.
9210.
9211.
9212.
9213.
9214.
9215.
9216.
9217.
9218.
9219.
9220.
9221.
9222.
9223.
9224.
9225.
9226.
9227.
9228.
9229.
9230.
9231.
9232.
9233.
9234.
9235.
9236.
9237.
9238.
9239.
9240.
9241.
9242.
9243.
9244.
9245.
9246.
9247.
9248.
9249.
9250.
9251.
92S2.
9253.
9254.
9255.
IF (PACK.C1.C.C1I GO TO 1074
CCVP'0.0
SOEK'0.0
1C74 WRITE (6t491) SCEK
WRITE (6,492) CCVF
WRITE (6,4Et) SE\APY
1C72 WRITE (6,361)
WRITE (6,36£) EF7CT,£PTOT,EPTOT,EPTOT,EPTOT,EPTOT
WRITE (6.36S) NEFTOT,NEPTGT,NEPTGT,N£PTOT,NcPTOT,NEPTOT
WRITE (6,362) CCVER
WRITE (6,27C)
WRITE (£,371) L2ES) WRITE (6.469) TSNBAL
WRITE (6.120S)
WRITE (6.121C) EPSTOT, ERSNTT
WRITE (6,i;il) SRER, SRERT
C
IF (PES1 .EC. KC) GO TO 978
C
WRITE (6,122G)
WRITE (6.1221) SIS, STST
WRITE (6,1222) S4S, SAST
WRITE (6,1222) SCS, SCSI
WRITE (6,1221) SOS, SOST
WFITE (6,1224) LTS, UTST
WRITE (6,1222) UAS, UAST
WRITE (6,1222 ) LCS, UCST
WRITE (6,1227) LOS. UOST
WRITE (6,1226) UPRIS, UIST
WRITE (6.122O LSTR
WRITE (6,122<) LAS
WRITE (6.123C) LCS
WRITE (6,1231) LOS
WRITE (6,1232) GSTR
WRITE (6,122?) GAS
WRITE U.123C) GCS
WRITE (6,1231) COS
WRITE (6.124C) FRTTOT, PRTT
WRITE (6,1241) FRCTOT, SPROTI
WRITE (6,1242) FRSTUT, SPRSTT
WRITE (6,1242) UPITOT, tPRITT
WRITE (6,1246)
WRITE (6,124!) OEGTOT
WRITE (6.124O OEGSOT
WRITE (6,1241) DEGUOT
WRITE (6,1252) OEGLUT
WRITE (6,1266) TP6AL
C
97£ IF (NLTR .EC. NO CO TO 1066
C
C YEARLY NUTRIENT OUTPUT
C
C
CCNC > LBFAC
309
-------
Appendix C (continued)
9256.
9257.
9258.
9259.
9260.
9261.
9262.
9263.
9264.
9265.
9266.
S267.
9268.
9269.
9210.
S271.
9212.
9213.
9274.
9215.
9276.
9277.
9218.
9279.
92EO.
9281.
9262.
92E3.
9284.
9285.
9286.
92E7.
9268.
9269.
9290.
9291.
9292.
9293.
9294.
9295.
9296.
9297.
9298.
9299.
9300.
9201.
9302.
9303.
9304.
9305.
9306.
9307.
9308.
93C9.
9310.
9211.
9212.
9213.
9214.
9215.
C
C
C
C
C
WRITE
WRITE
WRITE
WRITE
WRITE
1
WRITE
WRITE
1
WRITE
WRITE
1
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
1
2
WRITE
WRITE
1
2
WRITE
WRITE
1
2
WRITE
WRITE
WRITE
1
2
WRITE
WRITE
(6.1C92)
(6.40CC)
(6.40C5)
(6.4CC6)
U,4G2C)
(6.4CCT)
(6,4020)
(6.4015)
(6,4030)
(6,4CC£)
(6,4CC«)
(6,40111
(6.4C12)
(6,4C13)
(6,4C2C)
(6,4014)
(6,4015)
(6,4C2C>
(6.401(1
(6,4017)
(6,4Clt)
(6,401S)
(6.4C21)
CCNC
(SNT(J),J'1,7),(SNT(J),J=11,14),SNT(20)
( 1ELK, (SN(J.ItJLK) ,J = 1 ,/),( SH< J,I8LK),J=«U,14)
,SN(20,IBLK), IBLK=1,5)
(INl(J) ,J-l,7) , (UNK J) ,J=11,14),UNT(20)
( IELK,(UN(J,1BLK),J=1,7),(UN(J,IBLK),J'11,14I
,LN(20,1BLK), I8LK=1,5)
(LNIT(J),J=1,7),(UNIT(J),J=11,14) ,UNIT(20I
IM(20,1SLK) ,
(LN(J),J=1,7),(LMJ) ,J=U,14) ,LN(20I
Y(J), J=ll,l4) ,LNRP>(201
(TNPBY(J) ,J=-1 ,7),(TNRBY(J) , J= 11, 1 4) ,TNR6Y(20 1 ,
(SNRBYT(J),J=1,7),(SNRBYI(J),J=ll,14),SNPBYT(201,
(LNReYTU) ,J=1,7), (UNRBYT(J), J»l 1 , 14 ) , UNRBYT ( 20) ,
(LNRBYlJ) ,J=1,7),(LNKBY(J),J=11,14),LNPBY(201,
(GNPEY(J),J=1,7),(GNRBY(J),J=11,14),GNRBY(201
(INRHVY(J),J»1,7).(TNAHVY(J),J=ll,141,TNPHVY(201
hEAL, PHriAL, CLBAL
1C6£ IF (CLTPLT .EC. EKGL1 CO TO 1065
PRTCT •FRTCTf'NMN
PCSTCT=PCSTCT*f>FIN
PIKTCT=PIMCT*K»'PIN
RITCT *PITC1*»-HMK
PLTCT
PCHTCT
EPTOT
PC^•TtT<^•^FIN
EPTC1»M"FIh
tzs^•ET«l.zs*^^FI^
T*fMFIK
310
-------
Appendix C (continued)
9217.
9218.
9219.
$320.
9222.
9223.
9224.
9225.
9226.
9227.
9228.
9229.
9230.
9231.
9332.
9223.
9334.
9235.
9336.
9237.
933e.
9239.
9340.
93*1.
9342.
9243.
9344.
9345.
9246.
9347.
9348.
9349.
9350.
93«l.
9252.
9353.
9354.
9355.
9356.
9257.
9358.
9359.
9360.
9361.
9262.
9363.
9364.
9265.
9266.
9367.
9366.
9369.
9270.
9371.
9272.
9373.
9314.
9375.
SKCfc
IF (SM> .EC. NO GC TO 982
SIMSNY * Sl>SM«**PIN
PXSNY = PXShY*»*>FIN
PAOMEY -
CCRMEY
GRAINY
£GNY «
SNEGKY
CfUIKYOKPIh
JEVAPY
1SN8MY
FISTICICE
PACK^frflN
SEWFYOf-PlA
^s^E*L<^•^•PIN
962 IF (PES1 .EC. NO GO TO 979
SCS^^T»SCST4KCFlE
SDSTM»SDSHKOFie
LAS1f'T-LAS7*K€FlE
tCS7HT»LCSKKC-Fie
ICSTCT=LCST(1)*^^PIN
I)*Mt70PT*2.471
I)*fETOPT*2.471
.EC. NCJ GO TC 1062
=SAS(I)*KGPLB
»SCS(I)*KGPL8
ȣCS(I)*KGPL8
311
-------
Appendix C (continued)
9376.
9377.
9378.
9279.
9260.
9261.
9-82.
93£3.
92E4.
S3€5.
9366.
93£7.
9286.
S390.
9391.
9392.
9293.
9394.
9295.
9296.
9397.
9*98.
9399.
9400.
9401.
9402.
9403.
9404.
S405.
9406.
9407.
S4C8.
9409.
9410.
9411.
9412.
9413.
9414.
9415.
9416.
9417.
9418.
9419.
9420.
9421.
9422.
9*23.
9424.
9425.
9426.
9427.
9428.
9429.
9430.
9431.
9432.
S433.
9434.
9435.
UCSHETd
UDSHETI I
UPPISMI
PRTTCTd
PRCTCTd
FRSTCTd
LPITCTd
1042 CCNTINLE
«LCSd)*KGPL8
»LCS(II*KGPLB
-IFP1SU)*KGPLB
*FFTUT(I)*KGPLB
*FPGKT(I)*KGPLB
=FFS1CT(I)*KGPLB
«LFI1CT(n+KGPl.B
KRITE
KRITE
KRITE
KRITE
KRITE
KRITE
WRITE
KRITE
WRITE
(6.46C)
(6.26«1
(6,362)
(6,26<)
FJCKMf
. IPACK)
. 0.01)
(6,3£C)
(6,381)
(6,361)
IF (SNCW .EC.
KRITE (6,471)
KRITE (6,47<) F>JNY
KRITE (6,48C) >ELR*Y
KRITE (6,4£1)
KRITE (6,4£2) FfCHEY
KRITE (6,482) CCKMEV
KRITE (6,4£4) CCFHEY
KRITE (6.48*) CFMNY
KRITE (6,4£6)
KRITE (6,4fi<)
KRITE (6.49C)
COVP * 1CC.C
IF (PACK .IT
IF (PACK .GT
CCVP = O.C
SDEN - 0.0
1C€£ WRITE (6,491)
KRITE (6,492)
KRITF (6.4£()
1C89 KRITE (6.261)
WRITE (6.26E)
WRITE (6,36«)
KRITE (6,3£2)
KRITE (6,37C)
KRITE (6,271)
WRITE (6.372)
WRITE U.272)
WRITE (6,374)
KRITE <6,37f)
WRITE (6,37£)
WRITE (6,377)
IF (SNCK .tC.
KRITE (6,12C£)
KRITE (6,121C)
WRITE (6,12111
PCETCT,ROSTOT
IhFTQT,RINTOT
P11CT
RCITOT.RUTOT
E^JTOT
PCHOT
FfKT,PRTOT,PRTGT,PRTOT,PRTOT,PRTCT
NC ) GO TO 1089
COVA = (PACK/1 PACK)* 100.
GO TO 1088
!CEN
CCVR
IEVAPY
EFTCT,EPTOT ,EPTOT,£PTOT,EPTOT,EPTOT
NEFTOT,NEPTOT,N£PTOT,NfcPTOT,NEPTOT,NEPTOT
CCVER
12
-------
Appendix C (continued)
9436.
9437.
9438.
9439.
9440.
9441.
9442.
9443.
9444.
9445.
9446.
9447.
9448.
9449.
9450.
9451.
9452.
9453.
9454.
9455.
9456.
9457.
9458.
9459.
9460.
9461.
9462.
9463.
9464.
9465.
S466.
9467.
9466.
9469.
9470.
9471.
9472.
9473.
9474.
9475.
9476.
9477.
9478.
9479.
9480.
9481.
9482.
9483.
9484.
9485.
9486.
5487.
9486.
9469.
9490.
9491.
9492.
9493.
9494.
9495.
C
C
9£(
C
C
C
C
C
529
520
WRITE (6,1223) iCSHEl.SCSTMT
WRITE (6,1227) SNRSY(J,IBLK)*CONVF
£NRCY(J,IEIK) = SNROY(J,I8LK)*CONVF
LrRIY(.,IEU) » UNRIY(J.IBLK)* CONVF
IF (MC4L .EC. CALB) GO TO 529
SNPE1 (v,lELK) * SMJ,IBLK)*CONVF
LNf'EKJtIELK) = UN( J, 1BLKJ*CONVF
LMfET(J ,1EIK) * UNHJ, IBLK)*CONVF
CCMINLE
CCMINCE
313
-------
Appendix C (continued)
9497.
949E.
9499.
9500.
9501.
9502.
9503.
95C4.
9505.
9506.
9507.
9508.
95C9.
9510.
9511.
9512.
9513.
9514.
9515.
?516.
9517.
9518.
9519.
9520.
9521.
9522.
9523.
9524.
9525.
9526.
9527.
9528.
9529.
9530.
9531.
9532.
9533.
9534.
9535.
9536.
9537.
9536.
9539.
9540.
9541.
9542.
9543.
9544.
9545.
9546.
9547.
9548.
9549.
9550.
9551.
9552.
9553.
9554.
9555.
C
C
C
C
C
C
C
KBALK.T
PhBLPT
CLBLM
CCNC - KGFh/
WRITE U,1C<2)
WRITE (6.40CO)
1
WRITE
WRITE
WRITE
L
WRITE
WRITE
I
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
HRITE
WRITE
1
2
1
2
1
2
3
4
U,4CC5)
(£,402C)
U,4CC7)
(6,4C2C)
(6,4020)
CCNC
(S^THET(J),J=l,7),(S^TMcT(J),J=ll,14),SNTMET(201
(IELK,(SNMET(JTlBLK), J=l,7), (SKHET (J , IBLK 1 , J= 1 1, 14 1
,£M"ET(20,lbLK), I6LK=1,5)
(INTMETU) ,J=l,7),(UNTMET(Jl,J*ll,14),UNTfET(20l
I I ELK, (UNMET! J ,IijLKJ , J=l, 7) , ( UNMET (J , IBLK ) ,J= 1 1 , 14 )
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
WRITE
HRITE
WRITE
(6.40C9)
(6t4011)
(t,40121
Ut4C13)
(£.4020)
(6,4014)
(6,4C2C)
(4,4015)
(6.4C2C)
(6,4Cltl
(6,4017)
(6,401E)
(6,4C19)
(6,40211
(INITMT(J) ,J=1,7*,(UMTMT( J ) , J=ll ,14 ) , UMTMT (201
( IBLK, ( UN IMcT( J, IBLK), J = l,7),
(LM fET (J, IBLK ),J=llt 141,
LMCET(20,IBLK), 1BLK=1,51
(LNfETl J) ,J=1,71 , (LMMnTiJl, J=ll,14) ,LNKET(20i
(GNCET(J) , J*l,7if (GNHET(J), J= 11 , 14) ,GNKET( 201
(£NPSYT(J) ,J=1,7) , (SNRSYTU) , J=ll ,141, SNPSYT(201
(1ELK,(SNHSY(J,IBLK),J=l,71,
(SftRSY(J,lBLK) ,J = 11,141,
£MJSY(20,lbLKI , !BLK=lf51
(£NPCYT(J),J=1,7),(SNROYT(J),J=ll,14),SNROYT(201
iIELK,(SNKQY(J,IBLK),J-l,7),
( 0.0
314
-------
Appendix C (continued)
9556.
9557.
•5558.
9559.
9560.
9561.
9562.
9563.
9364,
9S65.
9566.
<567.
9568.
9569.
9570.
9571.
9572.
9513.
9514.
9575.
9516.
9577.
9576.
<579.
S580.
95€1.
9562.
9563.
9£€4.
9585.
9566.
9567.
9588.
9569.
9590.
9591.
9592.
9593.
9594.
9595.
9596.
9597.
9598.
9599.
9600.
96C1.
96C2.
9603.
96C4.
9405.
96C6.
9607.
96C8.
9609.
9610.
9611.
9612.
9613.
9614.
9615.
SFPCTT - C.O
SPFSTT - 0.0
UPRI1T - C.C
CEGSCT » 0.0
CEGLCT « C.O
OEGLC7 * 0.0
SUPSNY * 0.0
PXSNY - 0.0
fELRAY - O.C
RADFEY - O.C
CDRKEY » O.C
CCNPEY - O.C
CRAINY -- C.C
SGMY ^ C.O
SNEGfY = O.C
SEVAPY « C.C
C
DC 1C£€ i«l|5
ERS7C1U) * 0.0
FCBTCHIJ « 0.0
IfvFTCT(I) - 0.0
PPTTCT(l) « 0.0
FPSTCT(I) - 0.0
FPCTCUI) = 0.0
LFUCTd) - 0.0
K68 FCITCT (I) » 0.0
C
IF (SLIP .EC. KC) GC TO 1070
C
C ZERO YEARLY NUTRIENT ACCCVULATICNS
C
CC 534 J»1,2C
LNRFY(J) * C.C
LNR6Y(J) « O.C
GNRBYiJ) * O.C
TNR6XJ) « O.C
TNRt-VYtJJ « C.C
DC 523 IEIK«1,5
ShRSY<^ tltlK) * 0.0
£NFCY<,,l£tKJ * 0.0
LKRI>(w) = 0.0
rPSYU.IELK) 0.0
s^ReY ( 3X, F7 .3 » * 4X.F7 .3 1
1211 FCRMAT • • .llXt'FINES DcPOi.IT' »6X,al3X,F7.3) ,4X,F7.3)
CLOCK 5«,
315
-------
Appendix C (continued)
9616.
9617.
9618.
9619.
9620.
9621.
9622.
9623.
9624.
9625.
9626.
9627.
9628.
9629.
9630.
9631.
9632.
9633.
9634.
9635.
9626.
9637.
9636.
9639.
9640.
9641.
9642.
9643.
9644.
9645.
9646.
9647.
9646.
9649.
9650.
9651.
9652.
96«3.
9654.
9655.
9656.
9657.
9656.
9659.
9660.
9661.
9662.
9663.
9664.
9665.
9666.
9667.
9666.
9669.
9670.
9671.
9672.
9673.
9674.
9675.
122C FCRMAT
1221 FCRMAT
1222 FCRM/T
1223 FORMAT
1224 FCRMAT
122< FORMAT
1227 FCRMAT
1226 FORMAT
1229 FCRMAT
123C FCRMAT
1221 FCRMAT
1222 FCRMAT
1239 FCRMM
124C FORMAT
1241 FORMAT
1242 FORMAT
1243 FORMAT
124S FCRMAT
124t FCRMAT
1247 FCRMAT
1246 FCRMAT
1249 FCRMAT
125C FCRMAT
1251 FCRMAT
1252 FCRMAT
1266 FCRMAT
36C FCRMAT
362 FCRMAT
362 FORMAT
3<4 FCRMAT
365 FORMAT
366 FCRMAT
38C FCRMAT
III FCRMAT
361 FCRMAT
47i FORMAT
479 FORMAT
46C FCRMAT
461 FORMAT
462 FCRMAT
462 FORMAT
464 FORMAT
465 FCPMAT
466 FCRMAT
461 FORMAT
49C FORMAT
491 FCRMAT
492 FCRMAT
466 FORMAT
367 FCRMAT
366 FORMAT
369 FORMAT
382 FCRMAT
27C FCRMAT
371 FCRMAT
272 FCRMAT
272 FORMAT
374 FCRMAT
375 FCRMAT
376 FCRMAT
• 0' ,
•0'«
' * »
• >
• 0'
1 •
1 •
•0'
• •
• •
t •
«0'
•0'
•C'
1 1
1 •
, «
• •
1 •
, •
•0'
•0' ,
• 1* ,
' + ' ,
• :,
•0' ,
•C',
•c» ,
• ,
* ,
• .
* 1
•c ,
• ,
•0 i
1 1
* *
' • 1
'C',
* * 1
• • 1
' " 1
' :
• '
' -1
•0'
1 '.
• •
•0'
•0'
• •
*
• •
•0'
• •
• 1
• •
• 1
, •
« •
,SX,'PESTICIDE , POUNDS')
EX,'SURFACc LAYER',9X,5(3X.F7.3),3X,F8.3)
,11X,'*OSCFBED' ,HX,5(3X,t-7.J),3X,F8.3)
11X,'CRYSTALLINE', tiX ,MJ X.F7.3),3X,F8.3)
8X,'LFFfcR ZONE L «YcH • ,6X, :>< 3X , F 7 .3) , 3X ,F8 .3 )
MX,' INTERFLOW ST JKAGE ' , 2A ,5 UX ,F 8.3) ,3X,F8.3)
IIX.'CISSCLVED',10X,i(3X,F7.3»,3X.F8.3)
tX,'LOWER ZONE LAYER' ,59X,F8.3)
11X,'ADSCRBED' ,6«tX,Fti.3)
1 IX,'CRYSTALLINE' ,61X,Fb.3)
IIX.'CISSCLVED',o3X,F8.3)
EX,'GRCUNDWATER LAYER', i>8X,F8.3)
fiX,'PESTICIDE REMOVAL, KGS.•,2X,5 (F7.3,3X),F8.3)
6X,'FESTICIUE REMOVAL, LBS.•,2X,5(F7.3,3X) , F8.3)
11X,'CVERLAND FLJn RtMOV AL ', IX,5(F7.3,3X),F8.3)
1IX,'SEDIMENT RErlOVAL* ,6X,b(F7.3 ,3X ) , F8.3)
1IX ,' INTERFLOW REMOVAL',bX,5(F7.3 ,3X),F8.3)
11X,'TOTAL',68X,F7.3)
IIX.'FRCM SURFACE' ,61X,F7.3)
IIX.'FPCM UPPER ZONE',baX,F7.3)
6>,'PESTICIDE .DEGRADATION LOSS, LES.')
,'FESTICIDc DEGRADATION LOSS, KGS.'I
,25X,'SUMMAKY FOR >,I4)
,11X,'FRCM LOWER ZONE',5UX,F7.3)
,11X,'PESTICIDE BALANCE*' ,F(Ftt.3,2X),LX,F8.3)
, 14X ,'IMPERVIOUS',59X,Fd.3)
14X,MOTAL',13X,5(F8.3,<;X) ,IX,F8.2»
,11X,'EASE FLOW ,63X,Fd.3l
, 11X,'GRCkATtR RECHARGE',i>5X,F 8. 3)
,llX,'FRECI*'lTAT10.N',6Xfa(F7.2,3X) , IX.F7.2)
,14X,'SNCN',6^X,F7.2)
•PAIN ON SNlivJ' ,57X,F7.2)
,14X,'f-ELT £. RAIN',5dX,F7.2)
tllX.'tELT*)
,14X,'FACIAT10N',60X,F7.2)
•CCNVECTICN1,59X,F7.2)
'CONUtNSATlCN' ,57X,F7.2)
•PA^ McLT' ,oOX,F7.2)
,14>,'CRCUNb MELT',5tiX,F7.2)
,14X,'Cl.M Ncto HEAT' ,t>7X,F7.2)
,llX,'SNCh PACK',b3X,F7.2)
,llX,'SNCVi DENSITY* ,OOX,I17.2)
9 SNCW CCVER',60X,F7.2)
,HX,'£NCk EVAP* ,o3X,F7.2)
,1IX,'EVAPCTRANSPI RATION1')
POTENTIAL',^X,S(F7.2,3X),1X,F7.2)
,14X,'KET',15X,5(F7.2,3X) ,1X,F7.2)
CCCP COVER',59X,F7.2)
,11X,'STCPAGES')
,]4X,'LPPER ZONE',8X,5(F8.3,2X),IX.F8.3)
, 14X,'LCK£R ZONE',aX,&(Fo.3,2X), 1X.F8.3)
,14X,'GRCLM>taATER',7X,S(Fti.3,2X),1X,F8.3)
, 14X,'INTERCEPT ION',6X,5(Fo.3,2X),IX,F8.3)
,14X,'CVERLAND FLUW ,3X,i> (F8.J.2X) ,1X,F8.3>
,14X,' INTERFLOW ,9X, 5 (F8. 3,2X) ,1X,F8.3)
316
-------
Appendix C (continued)
9676.
9677.
5678.
9679.
5660.
96£3.
5664.
9665.
9689.
9690.
9651.
9692.
9653.
5694.
9695.
5656.
5657.
5658.
9699.
9700.
9701.
5702.
5103.
97C4.
57C5.
57C6.
5707.
9108.
97C9.
9110.
9900.
5901.
5902.
9«C3.
55C4.
99G5.
371 FORMAT
489 FCRMAT
FCRMAT
FORMAT
1
2
FCRMAT
FORMAT
FCRMAT
FCRMAT
FORMAT
FORMAT
FORMAT
FCRMAT
FCRMAT
FORMAT
FCRMAT
FCRMAT
C
C
C
4CCC
4C05
4C06
4C07
4CC8
4CC9
4011
4C12
4C12
4C14
4015
4016
4CH
4C1£ FCRMAT
I
2
3
t.
4C15
4021
4C2C
C
FORMAT
FORMAT
1
2
3
CO'
CO'
,11X,'VATER BALANCED ,F8.4)
6ALANCt= *,F8.4I
, MILLIMETERS'!
NUTRIENT FORMATS
CO* ,'M.IF IEMS - ' ,A5,11X,'OKG-N' ,3X,'NH3-S» ,3X,»NH3-A't
5X,»NC2« ,5X,'N03' ,6X,•U2«t2X,'PLNT-N• ,3X,'ORG-P't3X,
•FC4-J* i2>t» FC4-A* f<£Xt • PLNT-f t6Xf • CL •)
•O'.JX.'STCRAGE* )
•0
•0
•0
•C
• t - A t . i un«v>cw i
• t9X,'£UPI-ACt LAYcR' ,3X ,F O.0.6F3 .3 ,F8.0, 3F8 .2 ,F8.3 I
»t?X, 'LFFtR iONc' t6X,t-b.O,6Fo.3tF8.0,3F8.3iF8.3)
• t9X,'LOk»EB ZONc't6X,F«.U,oFd.3,f 8 .0, 3F8.3t F8.3)
' t5> .'C-RCONUWATER' , 5X ,Fti. 0,oF8.3 ,F 8.0, 3F8.3 tF6.3)
t IV • C * U f tJ A 1 • 1
•C'.iX
CC1
CO'
CC1
i'O
F6
CO
/,'
/,'
/,;
/t-
CC
/,'
'lEOI^ENT'.eX.Fa.O.oFB.S.Fa
INTcRFLOn' ,7X,FtJ.O»
TO SlKc«M «,Fa.u,oFd
' t5X,«
.C,6F€
't6X,«
* 15> t
•»5>,
• t9>,
•»5),
1 ,2>
.0,3F8.3,F8.3)
.3,F8.0,3F8.3,F8.31
d.O,3F8.3,F8.3)
.3,F8.0,3F8.3,F8.3I
FERCCLATICN TO '/,• ',liXf 'GROUNOWATER•t2Xt
.3,fc.O,3Fo.3,F8.3)
EICLCG1CAL - TOTAL ',F3.0,
'SURFACE',9X,F6.0i6Fo.i,Fa
•UPPER /LONE',6X,F6.0»6F t
//LKEC.SVSIN CC *
/*
317
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
REPORT NO.
EPA-600/2-76-043
3. RECIPIENT'S ACCESSION-NO.
TITLE AND SUBTITLE
MODELING PESTICIDES AND NUTRIENTS ON
AGRICULTURAL LANDS
5. REPORT DATE
February 1976 (Issuing Date)
6. PERFORMING ORGANIZATION CODE
AUTHOR(S)
Anthony S. Donigian, Jr., and Norman H. Crawford
8. PERFORMING ORGANIZATION REPORT NO.
. PERFORMING ORGANIZATION NAME AND ADDRESS
Hydrocomp, Incorporated
1502 Page Mill Road
Palo Alto, California 94304
10. PROGRAM ELEMENT NO.
1BB039
11.KBNXeW(0CWGRANT NO.
R803116-01-0
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Athens, Georgia 30601
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
EPA-ORD
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Modifications, testing, and further development of the Pesticide Transport and Runoff
(PTR) Model have produced the Agricultural Runoff Management (ARM) Model. The ARM
Model simulates runoff, snow accumulation and melt, sediment loss, pesticide-soil
interactions, and soil nutrient transformations on small agricultural watersheds. The
report discusses the major modifications to and differences between the PTR and ARM
Models. An energy-balance method of snow simulation, and a first-order transformation
approach to nutrient modeling are included. Due to lack of data, the nutrient model
was not tested with observed data; testing and refinement are expected to begin in the
near future.
Instrumented watersheds in Georgia provided data for testing and refinement of the
runoff, sediment and pesticide portions of the ARM Model. Comparison of simulated
and recorded values indicated good agreement for runoff and sediment loss, and fair to
good agreement for pesticide loss. Pesticides transported only by sediment particles
were simulated considerably better than pesticides that move both in solution and on
sediment. A sensitivity analysis of the ARM Model parameters demonstrated that soil
moisture and infiltration, land surface sediment transport, pesticide-soil inter-
actions, and pesticide degradation are the critical mechanisms in simulating pesticide
loss from agricultural watersheds.
17.
KEY WORDS AND DOCUMENT ANALYSIS
a.
DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS
COSATI Field/Group
Simulation, Runoff, Hydrology, Soil
erosion, Nitrogen, Phosphorus, Snowmelt,
Watersheds, Pesticides
Agricultural runoff,
Hydrologic modeling,
Pollutant pathways,
Nitrogen compounds,
Phosphorus compounds,
Snowpacks, Small water-
sheds
12A
2A
6F
8H
18. DISTRIBUTION STATEMENT
RELEASE UNLIMITED
19. SECURITY CLASS (This Report)
UNCLASSIFIED
21. NO. OF PAGES
332
20. SECURITY CLASS (This page)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
318
U.S. GOVERNMENT PRINTING OFFICE 1976-657-695/5366 Region No. 5-11
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