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THE INFLUENCE OF EVAPOTRANSPIRATION RATES AND CROPPING
SEQUENCES IN SIZING LARGE SCALE LAND
APPLICATION SYSTEMS
by
DAVID R. GREGORY, B.S.
A THESIS
IN
CIVIL ENGINEERING
Submitted to the Graduate Faculty of Texas Tech University in
Partial Fulfillment of the Requirements for
the Degree of
MASTER OF SCIENCE IN
CIVIL ENGINEERING
Approved
August, 1982
ACKNOWLEDGMENTS
I would like to express my appreciation and thanks to Dr. R. H.
Ramsey III for his direction, guidance, and criticism throughout my
graduate program and towards completion of this thesis. Thanks are
also in order to the other committee members; Drs. B. J. Claborn,
D. R. Krieg, and R. M. Sweazy for their helpful criticism and assis
tance.
In addition I would like to thank my wife, Karen, for her
encouragement, patience and support throughout this study.
n
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
LIST OF TABLES vi
LIST OF FIGURES viii
I. INTRODUCTION 1
II. LITERATURE REVIEW 5
Utilization of Land Application 5
Institutional Incentives 6
Land Treatment Methods 8
Irrigation 9
Rapid Infiltration 10
Overland Flow 10
Treatment Performance of Land
Application Systems 11
Nitrogen 11
Phosphorus 14
Biochemical Oxygen Demand and
Suspended Solids 16
Pathogens 17
Heavy Metals 19
Evapotranspi ration 20
Blaney-Criddle Method 23
Jensen-Haise Method 25
Penman Method 26
Modified Penman Method 27
n 1
TABLE OF CONTENTS (cont)
Pan Evaporation Method 27
Crop Selection 28
Water Consumption 29
Nitrogen Utilization 30
III. DESIGN CONSIDERATIONS 32
Evapotranspi ration Estimates 32
Blaney-Criddle 32
Jensen-Haise 33
Penman 38
Modified Penman 46
Pan Evaporation 47
Selection and Application of
Crop Coefficients 47
Hydraulic Loading Rates 49
Soil Permeability Criterion 57
Nitrogen Loading Criterion 63
Field Area Requirements 64
Storage Area and Volume Requirements 54
Cost Comparison 65
IV. RESULTS AND DISCUSSION 66
Evapotranspi ration 66
Hydraulic Loading Rates 66
Land Area (Aw) 72
Storage Area and Volume 73
iv
Influence of Different Crops 73
Hydraulic Loading Rates 76
Land Area 76
Storage Area and Volume 76
Cost 78
V. CONCLUSIONS AND RECOMMENDATIONS 82
Conclusions 82
Recommendations 83
LITERATURE CITED 85
APPENDIX A 89
APPENDIX B 94
LIST OF TABLES
1. Nutrient Uptake Rates for Selected Crops 31
2. Mean Daily Percentage (p) of Annual Daytime
Hours for Different Latitudes 35
3. Mean Solar Radiation for Cloudless Skies 39
4. Values of Weighting Factor (W) for the Effect of
Radiation of ETp at Different Temperatures and
Altitudes 41
5. Values of Weighting Factor (1-W) for the Effect
of Wind and Humidity on ETp at Different
Temperatures and Altitudes 41
6. Extra Terrestrial Radiation (Ra) Expressed in
Equivalent Evaporation mm/day 43
7. Effect of Temperature f(T) on Longwave Radiation
(Rnl) 44
8. Effect of Vapor Pressure f(ed) on Longwave
Radiation (Rnl) 44
9. Effect of the Ratio Actual and Maximum Bright
Sunshine Hours f(n/N) on Longwave Radiation (Rnl) 44
10. Adjustment Factor (c) in Presented Penman
Equation 45
11. Pan Coefficient (Kp) for Class A Pan for
Different Groundcover and Levels of Mean
Relative Humidity and 24 Hour Wind 48
VI
12. Seasonal Development Stages and Planting Dates
for Selected Crops 50
13. Average Monthly ETp Estimates (mm/day). Period
of Record 1965-1980, from Lubbock Regional
Airport 68
14. Design Hydraulic Loading Rates (LwD) cm 69
15. Monthly Nitrogen Uptake, kg/ha 74
16. Land Area (Aw) and Storage (As) Requirements 75
17. Cost Comparison of Selected Crops and ETp Methods 79
Vll
LIST OF FIGURES
1. Map showing portions of Lubbock and Lynn Counties
and relative position of the Gray and Hancock
Farms Land Treatment Sites 3
2. Determination of ETp from Blaney-Criddle f factor
for different daytime wind velocities and high
sunshine duration, n/N 0.9 35
3. Determination of ETp from Blaney-Criddle f factor
for different daytime wind velocities and medium
sunshine duration, n/N 0.7 36
4. Determination of ETp from Blaney-Criddle f factor
for different daytime wind velocities and low
sunshine duration, n/N 0.45 37
5. Average kc value for initial crop development
stage for corn planted in April as related to ETp
and 7 day irrigation schedule 51
6. Crop coefficient curve for cotton at different
growth stages 52
7. Crop coefficient curve for corn at different
stages of growth 53
8. Crop coefficient curve for sorghum at different
growth stages 54
9. Crop coefficient curve for bermuda grass. 55
VI 1 1
LIST OF FIGURES (cont)
10. Crop coefficient curve for wheat at different
growth stages 56
11. Frequency analysis of monthly precipitation
for Apr., July, Nov 58
12. Frequency analysis of monthly precipitation
for Sept., Oct 59
13. Frequency analysis of monthly precipitation
for Aug., Dec 60
14. Frequency analysis of monthly precipitation •
for Feb., Mar., May 61
15. Frequency analysis of monthly precipitation
for Jan., June 62
16. Monthly ETp estimations, mm/day 67
17. Nitrogen uptake - LwD relationship 77
IX
CHAPTER I
INTRODUCTION
The city of Lubbock has used land as a treatment medium for
application and disposal of its treated municipal sewage effluent for
over 40 years. Frank Gray, a local farmer, contracted with the city
in 1937 to accept Lubbock's secondary wastewater (12). Since 1941,
with the exception of some 6 million gallons per day (mgd) diverted to
Southwestern Public Service Company's Jones Station for cooling water,
all the treated effluent from Lubbock's Southeast Sewage Treatment
Plant (SESTP) has been transported to the Gray farm for irrigation.
The initial inflow rate in 1937 was 1 - 1 . 5 mgd and was used
to irrigate approximately 200 acres of forage crops (12). With the
expansion of Lubbock, especially during the 1960's and 1970's, the
increase in wastewater inflow has surpassed the treatment capability
of the irrigated land. Currently more than 15 mgd of secondary efflu
ent is pumped from Lubbock's SESTP to storage reservoirs on Gray's
farm for irrigation of approximately 2600 acres.
Because of the continual flow of wastewater and the limited
capacity of the storage reservoirs, effluent must be applied to the
land throughout the year. However, in months when the land is fallow,
water is not removed from the system through transpiration. Evapora
tion from a saturated soil surface may occur at a rate equal to that
of a well-watered crop. As the soil dries, however, the rate drops
1
off sharply. Also, when the land treatment site is without crops,
nutrients and other wastewater constituents pass through the first
1 - 3 ft of soil unchecked, and ultimately contribute to the degrada
tion of the ground water below. This uninterrupted loading has caused
ground water levels to rise. In addition, nitrate nitrogen concentra
tions in samples taken from wells on the farm now exceed acceptable
levels established by the National Primary Drinking Water Regulations.
In 1978, planning studies were begun to remedy the overloaded
land application system at Gray's farm. Through a cooperative arrange
ment between Hancock Farms and Lubbock Christian College Institute of
Water Research (LCCIWR), some 4000 acres of land were made available
for a land application site. This area is near Wilson, Texas, approx
imately 18 miles to the south of the area now being irrigated with
wastewater. Concurrently, financial assistance was obtained through
an EPA grant to Lubbock Christian College to design, develop and con
struct a land application system to augment the existing facility
serving Lubbock.
A design for the proposed land treatment project was submitted
to LCCIWR by Sheaffer & Roland of Chicago, Illinois in March, 1980.
The nitrate-nitrogen concentration of the SESTP effluent used as the
basis for design is too low when compared to more recent data obtained
from wastewater storage ponds on the Frank Gray Farm. This study was
made to evaluate requirements under these higher loadings, and as an
independent design for comparison to the Sheaffer & Roland design.
The following independent design will comply with the EPA's Process
Design Manual for Land Treatment of Municipal Wastewater, and will
^«i
Fig. 1. Map showing portions of Lubbock and Lynn Counties and relative position of the Gray and Hancock Farms Land Treatment Sites.
serve as a review of the design monthly hydraulic loading rates and
related system parameters, such as required cultivated field area and
storage volume.
The purpose of this study was to find an ideal cropping
sequence to minimize the required land area, while achieving waste
water treatment goals for the EPA-LCCIWR land application project.
Specific objectives were to:
1. Compare evapotranspiration estimates determined by methods
which utilize different combinations of meteorological
parameters.
2. Find a cropping system that permits maximum hydraulic
loading based on crop specific nitrogen and water consump
tion characteristics.
3. Determine the land area required for both crops and stor
age in the land application system based on EPA require
ments.
4. Compare land area and storage variations affected by the
different evapotranspiration estimates.
Once actual evapotranspiration rates are determined lysimetrically,
evapotranspiration data generated in this study will be of use in
sizing land application systems located in similar climatic regions.
CHAPTER II
REVIEW OF LITERATURE
In an effort to provide insight into land application systems
and the mechanisms surrounding land treatment of wastewater in today's
society, an overview of the available literature is presented in the
following chapter. Included will be a brief review of the utilization
of land application systems both past and present, the methods cur
rently in use, as well as treatment performance with regard to princi
pal wastewater components, and the role of evapotranspiration and
crop selection in design and planning of land treatment projects.
Utilization of Land Application
Land application of sewage or human waste has been used
throughout history because it adequately solved a need that existed
with human settlement. Man no doubt buried sewage in trenches or
pits (a form of land application) earlier than available records show,
and evidence indicates that ancient Athens used land as a disposal
medium before Christ (28). Waste from Bunslau, Prussia was used in
an irrigation/treatment project beginning in 1559 that continued in
use for over 300 years (43), The Japanese, as well as others in Far
East cultures, have used "night soil" in their rice fields for cen
turies.
In the 19th century, several European countries applied
sewage effluent to farmland extensively. The application of sewage
5
effluent for irrigation purposes was the simplest disposal and treat
ment method available at that time (36). In fact, several land appli
cation systems initiated in the late 19th century are still in use
today, space-age technology notwithstanding! The rapid infiltration
system at Calumet, Michigan has been treating the town's untreated,
undisinfected municipal wastewater since 1887 (44).
Melbourne, Australia has practiced land application of waste
water for over 80 years. Currently their system operates year round
3
at a 435,000 m /day (115 mgd) capacity. The overall management opera
tion involves crop irrigation in the summer, spray-runoff in the win
ter, and features treatment lagoons for back-up during wet periods.
In addition, livestock are raised and fed on the 11,000-ha farm, with
revenues from the operation used to offset the overall cost of the
wastewater purification (43).
There has been a dramatic increase in the number of land
treatment systems in use over the past four decades. The EPA's 1981
Inventory of Municipal Waste Facilities lists more than 1100 land
treatment systems in use or under construction, a substantial increase
in the 304 and 571 facilities operating in 1940 and 1972 respectively
(10).
Institutional Incentives
Application of wastewater to land as a means of treatment or
disposal is fast becoming commonplace in the United States. Several
federal legislative events have been instrumental in fostering new
and greater interest in the land application approach to wastewater
treatment.
The National Environmental Policy Act of 1969 (NEPA) is the
foundation of federal environmental legislation, and mandates an
environmental impact statement for federally funded projects (27).
In addition, NEPA requires consideration of alternate courses of ac
tion where alternative uses of natural resources are in question (27).
By far the single most important recent legislative item
affecting land application of wastewater is Public Law 92-500 (PL 92-
500), also known as the Federal Water Pollution Control Act Ammend-
ments. This law, passed October 18, 1972, includes several specific
goals relevant to waste treatment. As stated
(1) it is the national goal that the discharge of pollutants into navigable waters be eliminated by 1985;
(2) it is the national goal that wherever attainable, an interim goal of water quality which provides for the protection and propagation of fish, shellfish, and wildlife and provides for recreation in and on the water be achieved by July 1, 1983;
(3) it is the national policy that the discharge of toxic pollutants in toxic amounts be prohibited;
(4) it is the national policy that federal financial assistance be provided to construct publicly owned waste treatment works;
(5) it is the national policy that areawide waste treatment management planning processes be developed and implemented to assure adequate control of sources of pollutants in each State; and
(6) it is the national policy that a major research and demonstration effort be made to develop technology necessary to eliminate the discharge of pollutants into the navigable waters, waters of the contiguous zone, and the oceans.
Prior to the passage of PL 92-500, the pollution control
required for domestic sewage and industrial wastewaters was largely
based on the purification capacity, assimilation potential of plant
nutrients, and overall resiliency of the receiving waters (27). The
zero discharge goal will eliminate attempts to argue or establish
pollution control based on the potential impact of discharge on
8
receiving waters.
The Safe Drinking Water Act (SDWA), also known as Public Law
92-523, pertains to the land application of wastes in that it calls
for the protection of underground sources of water which are used for
drinking water supplies (27). Through the provisions of SDWA, the
EPA established the National Interior Primary Drinking Water Regula
tions. These regulations allow the states to propose their own stand
ard, provided the states' standards are at least as strigent as those
proposed by EPA. The protection of ground water as a future source
of drinking water is assured through this act.
To provide designers and planners with an incentive to con
sider the land application alternative for publicly owned waste treat
ment facilities, EPA is authorized to make grants of up to 85 percent
of the construction cost if a proposed system is classified as Alter
nate and Innovative Technology. However, before such a grant can be
authorized, it must be shown that all waste management alternatives
have been explored and that the cost effective Best Practicable Waste
Treatment Technology has been found.
Land Treatment Methods
Irrigation, overland flow, and infiltration-percolation are
the three methods generally considered for the land application of
municipal and industrial wastewater (36). Other less publicized meth
ods include silvaculture and turf irrigation.
The methods vary in several ways. Classification into one of
the methods can be based on the application rate of the applied waste
water and the flow path followed within the treatment process (10).
Classification is also based on the vertical water transmission prop
erties of the soil (27). Each method has its own advantages and dis
advantages. Selection for use in a particular situation is governed
by the required degree of treatment or quality of product water, site
characteristics and subsurface conditions, climate and availability
of land.
Irrigation
Irrigation, or the slow-rate process, makes use of the soil-
plant complex to effect treatment. Most organic matter is retained
within the top few centimeters of soil by adsorption and filtration.
Organics are ultimately decomposed by soil microorganisms through
biological oxidation. The soil filters out and retains most of the
suspended solids in the soil matrix. Mechanisms such as adsorption,
chemical precipitation, and ion exchange remove most phosphorous,
trace elements, and some microorganisms present in applied wastewater.
Many nutrients, particularly nitrogen compounds, are removed
from the treatment site through plant uptake and harvest. Although
vegetation is a critical component in the slow-rate process, crop
production plays an ancillary role to wastewater treatment (37). The
slow-rate treatment process produces a relatively high quality efflu
ent capable of meeting drinking water regulations (29). There is a
trade-off, however, between quality of percolate effluent and quantity
of influent applied. Application rates for crop irrigation systems
are lower than those of the other two processes. Generally, no sur
face runoff occurs and much of the water applied is lost to evapo
transpiration (43).
10
Rapid Infiltration
In contrast, rapid infiltration methods have much higher ap
plication rates: 1.6 to 33 ft per week compared to 2 to 8 in per
week for slow rate systems. Deep, permeable, well-drained soils and a
water table that does not rise to the soil surface during wastewater
application are essential for rapid infiltration, high-rate systems W
Although rapid infiltration systems do not produce the quality
of product water provided in slow-rate methods, tertiary treatment is
achieved with regard to virtually all constituents normally removed in
advanced wastewater treatment. Again the straining and filtering ac
tion of the soil removes the largest portion of suspended solids, BOD,
and coliform bacteria. Chemical precipitation and adsorption are the
primary mechanisms in phosphorus removal. Obviously, the high appli
cation rates possible with this method reduces the land requirement
when compared to slow-rate systems.
Overland Flow
The overland flow method offers treatment capabilities and
land requirements intermediate to the two aforementioned methods.
Overland flow is suitable for gently sloped (2-6 percent) terrain com
posed of relatively impermeable soils. Wastewater is applied at the
upper reaches of grass covered slopes, and moves as sheet flow down
the vegetated surface into runoff collection basins (4, 10).
Organic matter and suspended solids are removed by biological
oxidation, sedimentation and filtration. Nitrogen is removed by a
combination of denitrification, volatilization of ammonia, and plant
11
uptake. Adsorption and chemical precipitation remove phosphorus in
the same manner as with the slow rate and rapid infiltration methods.
Treatment Performance of Land Application Systems
In general, the use of the soil mantle as a treatment medium
for the renovation or disposal of wastewater provides treatment com
parable to, or of higher quality than effluents from advanced waste
water treatment processes (7). Relative removal efficiencies with
regard to nitrogen, phosphorus, biochemical oxygen demand (BOD),
suspended solids (SS), and pathogens, are usually higher in land
treatment systems than in conventional advanced wastewater treatment
techniques (27, 28). In addition to its role in wastewater treatment,
the soil-piant interaction also dictates the limiting design parameter
of any given land application system. Key design considerations,
specifically the hydraulic loading rates and nitrogen loading rates,
are discussed in the next chapter.
Basically, "treatment" refers to the removal of waste con
stituents from wastewater. Applied wastewater in land treatment sys
tems is treated by a combination of physical, chemical, and biological
processes. In the following section the primary constituents in
wastewater and the mechanisms by which they are removed will be dis
cussed.
Nitrogen
The most important factor limiting application of wastes to
the land is the amount of inorganic nitrogen present in the waste
water (27). Excessive nitrogen in surface waters can cause an
12
increase in aquatic vegetation and ultimately eutrophication of a lake
or stream. Of greater importance is the potential health hazzard
created by nitrate nitrogen (NO^-N) in drinking water supplies. While
nitrate itself is relatively harmless, bacteria in the intestines of
infants convert nitrate to nitrite. In the blood, nitrite combines
with hemoglobin to form methemoglobin, which does not have the affin
ity for oxygen of hemoglobin. The condition methemoglobinia can lead
to respiratory distress and suffocation (2),
Nitrate nitrogen concentrations in Lubbock's renovated waste
water exceed acceptable levels for drinking water. In wet chemistry
analysis of water samples from the wells beneath Gray's farm and from
springs and seeps along the side walls of Yellowhouse Canyon, NOZ-N
concentrations averaged 20.0 mg/1 and 18.0 mg/1 respectively (26).
The National Primary Drinking Water Regulations call for a maximum
allowable level of 10 mg/1.
As mentioned previously, nitrogen in one form or another is
often the limiting design consideration in land application systems.
In wastewater, nitrogen can exist in four possible forms: organic
nitrogen, ammonia nitrogen (NH -N), nitrite nitrogen (NO2-N), and
nitrate nitrogen (NOZ-N). Organic and ammonia nitrogen are the prin
cipal forms found in untreated wastewater (30).
The most effective means for removing nitrogen from wastewater
in the renovation process is through plant uptake. Nitrogen is essen
tial in plants for the production of proteins, chlorophyll, amino
acids and some hormones (45), The demand for nitrogen varies with
plant species and is subject to environmental conditions and management
13
practices. Nitrogen uptake may range from 110 kg/ha-yr for some field
crops to over 650 kg/ha-yr for perennial forage grasses (10). For land
application design purposes, 70 percent of available nitrogen in the
soil can be assumed removed by grasses (13). Ultimately, nitrogen is
removed from the system by periodic harvesting.
The next most important mechanism for removing nitrogen is
biological denitrification (5). Initially, the ammonium ion is oxi
dized to nitrate by nitrifying bacteria. These bacteria under anaero
bic conditions use the oxygen of nitrates as an electron acceptor in
their metabolic processes, reducing the nitrate nitrogen to one of
three predominant forms of nitrogen gas which then diffuse into the
atmosphere (4, 5, 25).
The cation exchange capacity (CEC) of soil may contribute to
nitrogen removal via adsorption. Clay and organic matter present in
soils offer negatively charged sites to attract and hold positively
charged ammonium ions. Adsorption of ammonium ions is important in
slow rate systems because nitrogen is retained in the root zone. If
nitrogen as the ammonium ion (NH- ) is converted to nitrate and passes
below the root zone it is no longer available as a crop nutrient, and
may pass through the soil profile into the ground water. Thus, nitro
gen leached into the aquifer is not actually removed from the system.
So although the CEC may not in itself provide for long term nitrogen
removal, it helps restrict the downward movement of ammonium and retains
nitrogen in an inorganic form, allowing time for biological transforma
tion of ammonium to nitrate and subsequent plant uptake.
Nitrogen is also removed from wastewater by volatilization of
14
ammonia. . Ammonia and the ammonium ion exist in equilibrium in neutral
solutions. However, if pH increases, the equilibrium favors nitrogen
in the gaseous ammonia form (25), The amount of nitrogen removed by
this process is small compared to nitrogen removal by the nitrification-
denitrification process.
Phosphorus
Phosphorus, like nitrogen, is an essential nutrient for plant
and animal growth. And as with nitrogen, phosphorus can contribute to
an over-enrichment of nutrients, and subsequent eutrophication of re
ceiving waters. Increased phosphorus concentration of water entering
lakes and streams increases the probability of excessive plant growth
and algal blooms, and ultimately a reduction in dissolved oxygen and
productivity.
Phosphorus may be present in wastewater as orthophosphate,
polyphosphate, or organic phosphorus. Sources of phosphorus include
commercial washing and cleaning compounds and domestic wastes. Typical
ly, human wastes, kitchen disposals, and household detergents are the
largest contributors of phosphorus compounds to municipal wastewater (30)
The primary phosphorus-removing mechanisms in land treatment
systems are chemical precipitation and adsorption. Thorough and last
ing contact between the soil and wastewater interface is essential for
maximum removal. Metcalf and Eddy (30) indicate that less than 20
percent of applied phosphorus is used by the crop. In independent
studies, the relative amounts of phosphorus removed by plant harvest
is less than the nitrogen removed by a factor of 10 (16, 35).
15
Primary wastewater treatment may remove approximately 10 per
cent, or the portion of phosphorus that is insoluable, from wastewater
(30), Approximately 1/3 of the total phosphorus is removed through
the screening and sedimentation operations of primary treatment. The
phosphorus removed in secondary wastewater treatment is limited to the
small amount tied up in microbrial cells, the remainder being in insol
uable form (27),
In general, fine textured soils retain phosphorus in the phos
phate form better than do coarse textured soils. Iron and aluminum
hydrous oxides adsorb large quantities of phosphate over a wide pH
range. Additional adsorption occurs on other clay minerals (27),
Phosphate retention via chemical precipitation is a function of pH.
The solubility of iron and aluminum increases at low pH ranges, and
may react with soluble phosphate to form insoluble precipitates. For
mation of insoluble calcium phosphate precipitates begins at a pH of
around 6 (27),
Regardless of the mechanism, soils have the ability to fix
large amounts of phosphorus. It has been shown that a soil treated
with phosphorus fertilizer for 82 years had the same phosphorus ad
sorbing capabilities as the unfertilized soil (22), Wastewater efflu
ent has been used for crop irrigation in the Pennsylvania State Univer
sity Wastewater Renovation and Conservation Project. The phosphorus
concentration in the leachate was found to be less than 3 percent of
the phosphorus applied after 11 years of irrigation with wastewater (23)
Although phosphorus is seldom a limiting design consideration
16
in land treatment projects, it does play a role in the longevity of the
system. The soil's ability to retain added phosphorus ultimately
determines the maximum lifetime of a site. It has been found that in
terms of continued crop production, the value of a site will be greater
upon abandonment than when initially established (18),
Biochemical Oxygen Demand and Suspended Solids
Biochemical oxygen demand, or BOD, loosely defines water-
soluble and readily biodegradable organic matter. The concern for BOD
removal centers around objectionable odors and depletion of dissolved
oxygen in receiving waters and soils. Suspended solids which are
organic in nature can create an oxygen demand, and in land application
systems can cause pore clogging in fine textured soils.
Organic matter in wastewater can generally be divided into
four groups. In order of importance, they are proteins, carbohydrates,
fats and oils, and urea. Small quantities of synthetic organics, such
as phenols, surfactants and pesticides, may also be present (30).
BOD and SS loadings are rarely limiting factors in the design
of land treatment systems. An example of potential BOD removal
capacity of land application systems is in operation at Paris, Texas,
There, the Campbell Soup Company uses an overland flow site to treat
cannery wastes. Influent BOD averages 616 mg/1 and is reduced by 99
percent to less than 10 mg/1 (11),
The state of Texas requires that wastewater meet primary
treatment standards prior to application to lands that are accessible
to the public. Typical raw municipal wastewater contains approxi
mately 250 mg/1 each of BOD and SS, Primary sedimentation
17
removes about 35 and 60 percent respectively of these concentrations.
Consequently, in practice the true treatment capabilities of most slow
rate systems are not tested with regard to these two parameters.
Removal of BOD and suspended solids from treated wastewater
is readily accomplished by land treatment. Removal efficiencies are
frequently as high as 98 percent both in slow rate systems (10, 27, 30).
Organic matter or BOD is stabilized by oxygen-demanding micro
organisms in the soil. In an ideal acclimated environment, BOD is
reduced to carbon dioxide and water through complete oxidation. To
maximize BOD removal, management should be aimed at maintaining aerobic
conditions in soils. Alternate periods of rest following surface
application allows reaeration of the soil's macropores.
Pathogens
Pathogens endemic to wastewater pose a wery real threat to
human and animal health, A large portion of human excrement is com
posed of bacteria and viruses. The daily per capita coliform discharge
is between 100 and 400 billion organisms (30). While coliform bacteria
are generally not pathogenic, they serve as an indicator of the pres
ence of feces in wastewater. It was found that as many as 100,000
doses of hepatitis virus are emitted for each gram of feces excreted
from a person inflicted with the disease (1), For the enteric fevers
such as typhoid and paratyphoid, the infectious dose for humans is
usually higher than 100,000 organisms (19),
The key to pathogen removal in soils is retention. Bacteria
are greatly reduced after passing through a few feet of well-developed,
fine-textured soils. Much of the bacteria of wastewater is strained
18
out at the soil surface where they are exposed to sunlight and drying
conditions unfavorable for their survival. As effluent passes down
ward through the soil profile, more bacteria are removed by filtration
or adsorption (29), While retention of bacteria and viruses does not
in itself inactivate pathogenic organisms, soil adsorption and filtra
tion effectively prevent host contact. The literature contains numer
ous examples of prolonged pathogen survival in the soil; however, sur
vival of an isolated organism is not synonymous with virulent patho
gens being present in infective numbers (9),
There are several factors that affect the removal or survival
of pathogens present in the soil, many of which can be effectively
manipulated by the operation of land application systems. These in
clude (29):
1. bacteria survive better in neutral to alkaline soils than
in acidic soils (pH 3 to 5)
2, bacterial removal increases in soils with balanced micro
flora
3, viruses and bacteria survive longer in moist soils and
during periods of high rainfall
4. viruses and bacteria have longer survival at low tempera
tures
5, exposure of bacteria and viruses to sunlight at the soil
surface reduces survival
6. organic matter in the soil increases longevity of viruses
and promotes regrowth of some bacteria.
Aerosol pathogens in land treatment systems can also create
19
health problems. Some precautions that can be taken by the system
designer as well as the operator to provide adequate buffer zones and
prevent contamination by airborne pathogens outside the treatment site
are:
1, adjusting irrigation equipment to spray the largest prac
ticable droplet size to reduce aerosol dispersion
2, consideration of current weather conditions
3, providing a buffer zone between the irrigated land and adja
cent or surrounding lands.
Although the potential exists for the release of pathogens in
concentrations large enough to cause disease, it is worthwhile to point
out that no diseases have been documented from any planned and properly
operated land application system in the United States (27),
Heavy Metals
There is growing concern regarding the introduction of large
amounts of heavy metals into productive agricultural soil through waste
water and sludge application, Metals including copper, zinc, cadmium,
lead, nickel, and cobalt are not usually found in soils in appreciable
levels, but can be food chain hazards (41). Accumulation of cadmium
in the kidney and liver of humans has been associated with hypertension,
emphysema and other diseases in extreme cases (14), Few food chain
problems are caused by high levels of copper, zinc, nickel, and cobalt
because they become toxic to vegetation before they are passed on to
the next trophic level. However, copper concentrations in forage can
become high enough to be marginally toxic to sheep (41). In general,
the elements considered most likely to pose a threat of phytotoxicity
20
or animal toxication are cadmium, zinc, copper, boron, nickel, and
molybdenum (32).
Most potentially toxic elements are contained in sludges and
are removed in conventional waste treatment operations. The soil
does, however, effectively retain heavy metals in the soil matrix,
Specific adsorption, a cation exchange process that binds
metalic cations so tightly that they are not exchangeable, occurs on
the surfaces of soil colloids such as clay or humus. Potentially
toxic elements may become incorporated in the organic matter in the
soil through covalent and ligand bonding. In this mechanism the
organic matter functions as a chelating agent around the toxic ele
ment. These chelate complexes are more likely to be taken up by veg
etation (27),
Chemical precipitation is another mechanism for immobilizing
toxic elements. In highly alkaline soils toxic elements may be pre
cipitated as hydroxides. Sulfides and phosphates also form precipi
tates within soil pores,
Evapotranspiration
At the heart of the slow rate method of land treatment systems
is crop water consumption, which consists of the water evaporated from
the soil surface or plant surfaces and the water transpired by the
plant through stomata. This evaporation-transpiration process is
collectively called evapotranspiration. Estimation of evapotranspir
ation rates and selection of a crop or cropping sequence to maximize
water consumption are key elements in determining land area, irriga
tion schedules and storage requirements necessary in the design of a
21
land application project. Seasonal evapotranspiration averages between
1.5 and 4.0 acre-ft/acre-yr, depending upon climate, type of crop, and
other factors C27).
The relative amounts of evaporation and transpiration from a veg
etated area are controlled by the availability of energy at the soil and
plant surfaces, and by the resistance of the soil and plant pathways to
water flow (40). If water is not limited, it will be absorbed from the
soil by the roots, and transported through the stem to the leaves.
There water vapor diffuses through the stomatal openings into the atmos
phere. As water is lost from the mesophyll by outward diffusion, the
cells become less turgid and the concentration of solutes inside each
cell increases, forming a water potential gradient or plant water ten
sion (45). As water is pulled from the soil through the roots, soil
wetness decreases, causing soil water tension to increase. The soil
will deliver water to the root as long as this tension is less than
plant water tension. Soil water tension gradients help maintain contact
between root and soil water. If additional water can no longer move
through the soil toward the root, water uptake will cease (17).
The driving force and source of energy necessary for evaporation
and transpiration of water is solar radiation. The two major sources
of energy driving evapotranspiration are net radiation and convection
of warm air (27). Net radiation is the largest source of energy avail
able for evaporating water and is defined as:
where Rj is the net radiation, o<. is the reflectivity coefficient,
R . is the incoming shortwave radiation, and R, is the net longwave
22
radiation. Since longwave radiation is continually emitted even after
sunset, R^ is expressed as a deficit (8, 17, 27).
Climatic conditions determine the energy available for
evapotranspiration. Air temperature, wind direction and speed, rela
tive humidity, number of daylight hours, all play a role in determina
tion of evapotranspiration rates and will be discussed in greater
detail later in this chapter.
Of the many components that effect the design of land treat
ment systems including evapotranspiration, few can be considered
design variables in that they can not be controlled by the engineer or
operator. Only crop selection and irrigation scheduling can be man
aged to meet goals and needs of land application projects, and are
the two parameters that can be manipulated both in the planning and
operational stages.
Evapotranspiration rates (ET) can be determined by a number
of experimental methods. One of the most widely used instruments for
measuring ET rates in the field is the lysimeter, If care is taken
to make conditions in the lysimeter representative of surrounding
field conditions, lysimeters can provide an accurate measurement of
the soil water lost from the field through evaporation and transpira
tion (20), Other methods, including neutron scattering, electrical
resistance, and gravimetric (sampling and drying) are used for meas
urement of soil water content, but are limited in their use for deter
mining ET rates (17).
Unfortunately, ET data for a site under consideration may
not be available to an engineer or designer when needed during the
23
planning phase of the project. Hence, there is a need for reliable ET
estimates or potential evapotranspiration (ETp) estimates based on
available climatological data. Potential evapotranspiration refers to
the amount of water evapotranspiring from an actively growing grass
cover.crop 8-15cm high, completely shading the ground, never short of
water (8), Another source stipulates alfalfa as a reference crop (20).
As construction costs increase, along with the cost of land,
irrigation units, and other appurtenances, the need for more precise
estimates of water consumption also grows, A large number of methods
have been developed for this purpose. The large number of methods
available can in part be attributed to the number and complexity of
the factors involved in ET determination. Methods such as Penman's,
although producing relatively accurate results, are restricted in use
because availability of needed climatic data limits use to areas where
the necessary meteorologic measurements are made. On the other hand,
Christiansen (6) found the less accurate Blaney-Criddle formula in
use by eyery engineering firm contacted in countries located in the
Mediterranean area. Five methods of estimating evapotranspiration
that have been used in arid and semi-arid climates were investigated
in this study. These are discussed below,
Blaney-Criddle Method
The Blaney-Criddle method for predicting evapotranspiration
rates is used throughout the world and has been popular in the western
United States for many years. Initially, the formula was developed
relating evapotransporation and mean air temperature, percentage of
daytime hours and relative humidity (20). Later the equation was
24
modified by Blaney and Criddle, deleting the humidity term (3). Ex
pressed mathematically in English units the equations in use at
present are:
u = kf (2-2)
U = ^I^kf (2-3)
U = KF where, (2-4)
t = mean monthly temperature, in degrees Fahrenheit;
p = monthly percent of daytime hours of the year;
t * D • 1QQ = monthly consumptive-use factor;
u = monthly consumptive-use in inches;
U = seasonal consumptive use (or evapotranspiration in inches);
F = sum of the monthly consumptive-use factors for the period;
K = empirical crop consumptive-use coefficient for irrigation season or growing period;
k = monthly empirical crop consumptive-use coefficient (3),
Assumptions in applying the formula include:
1, Seasonal consumptive use (U) varies directly with the consumptive-use factor (F),
2. Actively growing crops have adequate water throughout the growing season.
3, Soil fertility is uniform across the site,
4. The yields of forage crops vary only with the length of the growing period (3),
Crop water requirements will vary between climates having
similar values of t and p, making accuracy greater than 25 percent
unlikely (8). This can be understood since other factors influencing
ET such as relative humidity and windspeed are not considered.
25
Jensen-Haise Method
As stated previously, a basic principle of the energy balance
concept is that evaporation of water requires large quantities of heat
energy and that the rate of ET from an actively growing crop with ade
quate water is controlled by the available heat energy.
Using ET data and incoming solar radiation (R^) estimations for
the same sample period, ET/R^ ratios were calculated for 15 crops in
four general climatic regions in the western United States (21). Mean
daily ET rates can be calculated from the equation
'' - (Ir'n ^S (2-5) ET
where (j^).. is the mean measured ratio for the period, and R^ is mean
daily solar radiation in equivalent inches per day, corresponding to a
specific stage of plant growth for the period which the estimate is
needed.
The ET/R,, r a t i o for potent ial ET can be estimated from mean a i r
temperatures with the fo l lowing equation:
( | I ) „ = 0.014 - 0,37 (2-6)
which can be rearranged to calculate ETp
ETp = (0.014T - 0,37)R3 (2-7)
where T is the mean air temperature in °F. ETp represents potential
evapotranspiration in inches per day (21).
Computed ETp values using equation (2-7) were compared with
lysimeter data for a 2.5 year period at Davis, Ca. ETp estimates were
in close agreement except during the periods from May to September.
Over all, computed values averaged 11 percent higher than the measured
values for the 2.5 year span (20).
26
Penman Method
Transpiration of water from plants involves several important
physical and biological features from a root system that can draw
available water through considerable soil suction to stomata openings
that allow vapor transfer through leaves only during daylight hours,
Evapotranspiration from bare soil entails complex soil factors as well
as atmospheric conditions, Penman sought to find an absolute relation
between climatic conditions and open water evaporation, and compara
tive relations between water lost from the soil and losses from open
water exposed to the same weather (32),
The approach used in determining these relationships was based
on a combination of the energy required to maintain evaporation and
the mechanism for vapor dispersal, namely eddy diffusion. The origin
al equation of estimating evaporation rate (EQ) from open water re
quired mean air temperature, mean dewpoint temperature, mean wind
velocity, and mean daily duration of sunshine. Then
E- = (HA + 0.27 E j / ( ^ + 0.27) mm/day where; (2-8) U a
H = net radiant energy available at the surface,
^ = temperature dependent constant,
E = expression for the "drying power" of the air, includ-^ ing the vapor pressure deficit and a function of wind
speed.
In addition. Penman concluded that evaporation from continuously wet
bare soil, and well watered turf is 0,9 and 0,8 times that of an open
water surface exposed to the same weather conditions respectively (33).
Although more meteorological data is required for ETp estima
tions using the Penman equation than for the Jensen-Haise, Thornwaite
27
and Blaney-Criddle methods, the former provides greater accuracy. One
source indicates that ETp estimations following the Penman approach
may be within 10 percent of ETp actual, compared to a ±25 percent
margin of error when using the Blaney-Criddle method (8).
Modified Penman Method
This estimating method is used by agronomists and soil
scientists at the Texas A&M Agriculture Experiment Station in New
Deal, Texas, This approach uses parameters adjusted experimentally to
estimate crop water consumption in the immediate area. It was
selected for use in this study because of its development under cli
matic conditions typical of the land treatment site 25 miles to the
south.
The equation used is
ETp = 0,000673 i^^^^^^l ^\^ " V o . 2 7 ^ ' ^
(1.0 + 0.01w)(e^ - e^)] (2-9)
where R^ = R factor (R^)
^ = temperature dependent slope constant
w = wind run in miles/day
e~-e . = function of saturation vapor pressure at maximum ^ and minimum temperatures and minimum and maximum
humidities.
Pan Evaporation Method
Several workers have attempted to establish a relation be
tween consumptive use of water by crops and evaporation from an open
water surface. Consumptive use of alfalfa was compared vvith tank
evaporation and evapotranspiration estimates by the Blaney-Criddle
28
and Thornthwaite methods (39). Data collected for a 32 year period
from a semi-arid portion of Washington indicated more favorable con
sumptive use estimates were obtained with the evaporation pan.
In a later study, a constant relationship was demonstrated
between pan evaporation and consumptive use by ladino clover (38),
Included in the study are comparisons between crop consumption and
estimates from the Penman, Blaney-Criddle and Thornthwaite methods.
Estimated consumptive use was nearer measured consumptive use when the
pan evaporation and Penman methods were used.
Potential evapotranspiration can be estimated by the following
equation:
^'? = ' et * Epan (2-1°)
where C . is dependent on the reference crop and type of pan used (20),
Hargreaves developed a formula for computing Class A pan evaporation
using a day length ratio, mean monthly relative humidity, and average
monthly temperatures for use in areas where pan evaporation data is
not available (15). Several authors maintain that in addition to the
type of pan and reference crop used, the environment surrounding the
pan should be considered (8, 20, 38). Doorenbos provides adjustment
of the pan coefficient based on type of setting, vegetation or bare
soil, at the upwind fetch (8),
Crop Selection
The hydraulic loading rate of a land application system may
be determined either by calculating the water balance existing in the
soils at the project site or by the allowable nitrogen limits for the
planned cropping system. The water balance includes the summation of
29
incoming precipitation, outgoing perco]ation ^nd evapotranspiration
(10), The nitrogen balance is a function of the nitrogen concentra
tions in the wastewater and percolate water; amounts of nitrogen re
moved by nitrification and volatilization; and the amount of nitrogen
removed by vegetation. Both methods for determining hydraulic loading
rates will be illustrated in the next chapter.
As previously mentioned, crop selection is an important part
of the planning and design of land application projects. A crop's
demand for nitrogen and rate of water consumption will largely govern
the amount of cultivated land needed to adequately treat or dispose of
the design inflow wastewater. Judicious choice of a crop or crop se
quence can greatly reduce the overall project cost, both at the outset
and in operation and maintenance,
The choice of vegetation used in a slow rate system is obvious
ly restricted by physical setting, soil characteristics, and climate.
The characteristics of the wastewater and volume of inflow must also
be considered. Even though wastewater treatment and/or disposal are
ultimate goals, crop marketability, farming practices, and the ability
of the crop to tolerate high soil moisture conditions can not be over
looked (10), A crop with a steady market value may be precluded from
consideration if crop production is highly labor intensive.
Water Consumption
The actual water consumption through crop evapotranspiration
may be estimated by multiplying a crop coefficient times the potential
evapotranspiration:
ET^,op=kcETp (2-11)
30
The crop coefficient (kc) is a function of the relative amounts of
resistance different plants display toward transpiration, such as
closed stomata during the day (pineapple) and waxy leaves (citrus)(8),
There is considerable variation in the kc values for crops;
however, if crops are grouped as either field or vegetable, the
differences in kc values are much less, This is in agreement with
Penman and others, who indicate that there are only small variations
among evapotranspiration rates of various plants, and that the water
needs of a crop are governed more by weather than by the plants them
selves (34), Several crops have kc values greater than 1.0; that is,
the actual evapotranspiration is greater than the potential evapo
transpiration from well watered grass, Doorenbos defines ETp as
reference crop evapotranspiration as (8):
the rate of evapotranspiration from an extensive surface of 8 to 15 cm tall, green grass cover of uniform height, actively growing, completely shading the ground and not short of water.
Contrary to conclusions mentioned by Penman (34) that transpiration
of a short green cover crop cannot exceed evaporation from an open-
water surface if both are exposed to the same weather conditions,
Pruitt demonstrated that consumptive use from ladino clover exceeded
evaporation from 3 different sized evaporation pans (38).
Nitrogen Utilization
Nitrogen uptake by plants is dependent on the crop, crop yield
and the nitrogen content of the plant at the time of harvest. The
rate of nitrogen assimilation is a function of dry matter production
and is crop specific (10), Nitrogen uptake rates for several common
ly selected crops are listed in Table 1.
TABLE 1
NUTRIENT UPTAKE RATES FOR
SELECTED CROPS
kg/ha-yr
31
Crop
Forage crops
Alfalfa*
Coastal bermudagrass
Reed canarygrass
Ryegrass
Sweet clover*
Field crops
Corn
Cotton
Grain sorghum
Wheat
Nitrogen
225-540
400-675
335-450
200-280
175
175-200
75-110
135
160
SOURCE: EPA, 1981. Process Design Manual for Land Treatment of Municipal Wastewater. U.S. Army Corps of Engineers, U.S. Dept. of Interior, U.S, Dept of Agriculture, EPA 625/1-81-013, EPA Technology Transfer, Washington, D,C,
*Legumes will also take nitrogen from the atmosphere.
CHAPTER III
DESIGN CONSIDERATIONS
In this chapter, the procedures utilized to size the compo
nents of a land application system capable of handling 7,5 mgd of
wastewater under soil and climatic conditions typical of those at the
Hancock site are presented. Procedures discussed in order of their
presentation are evapotranspiration estimates, crop coefficient deter
minations, hydraulic loading rate calculations, field area require
ments, storage volume estimations, and costs,
Evapotranspiration Estimates
Weather data obtained at the Lubbock International Airport
from 1965 to 1980 was used for the calculation of evapotranspiration
estimates unless otherwise noted,
Blaney-Criddle (8)
This method requires only the measurement of mean daily tem
perature over the month considered and is expressed as
ETp = c[p(0.46T + 8)] mm/day (3-1)
where: ETp = the rate of evapotranspiration from an extensive cover ^ of actively growing green grass completely shading the
ground with ample water.
T = mean daily temperature in °C for the month considered.
p = mean daily percentage of total annual daytime hours obtained from Table 2 for a given month and latitude.
32
33
c = adjustment factor which depends on the minimum relative humidity, hours of sunshine and estimated daytime wind velocity in m/sec.
Temperatures are given in °F and converted to 'C in calculat
ing p(0.46T + 8), The percentage of total annual daytime hours was
selected from Table 2. Percentage values corresponding to the 35°
latitude were selected as representative of Lubbock's latitude of
33°39'. Determination of ranges of minimum relative humidity (RHmin),
the ratio of actual to maximum possible sunshine hours (n/N), and
daytime wind speed (Uday) can be estimated. However, actual values
were verified through climatological data to minimize errors in range
selection.
Once p(0,46T = 8) was calculated for each month, Figures 2, 3
and 4 were used to estimate ETp graphically. Values of p(0,46T + 8)
are given on the abcissa and ETp can be read directly from the ordin
ate. These figures represent relationships between adjustment factors
RHmin, n/N, and Uday and estimated ETp,
Jensen-Haise (20)
Data needed to estimate ETp using the Jensen-Haise formula
include the maximum and minimum temperatures for the warmest month of
the year and the incoming solar radiation (R ), The basic equation
is:
ETp = C^(T - T^)R3 (3-2)
where ETp is potential evapotranspiration in langleys per day (ly/dy),
and Cj is defined as
34
CO Q i
O
<\i
CO •si:
>-<: a
—I oo CC LU =5 Q
Z I—
I—
o -J
>— UJ ca
UJ LU
O Q i Q: O LU L i . Q .
>-
u a
> o
en
CVJ
CM CM
CM CM
CO CM
CO CM
CM
4-> O O
in CM
•
tn CM
•
VO CM
•
Q . CD
C/)
0 0 CM
•
0 0 CM
•
0 0 CM
•
< : a
cr 3
•n
<r CO
•
CM CO
•
CM ro
•
&. Q .
<a:
o ro
•
o^ CM
•
0 ^ CM
•
X3
+->
4-» «T3
CO
CO CO
O CO
CM CO
O CO
CO
CM CO CO CO
CM CM CvJ
j Q OJ
LL.
^ CM
•
i n CM
•
LO CM
•
<Z. ea
•-3
CM CM
•
CO CM
•
«d-CM
•
O ir> o '::r CO CO
cr Cd
<u
a. o o en
+J u
• 1 * '
"O <u s-
O-
&-o
^-CO (U c
• r -1 — •
OJ •o •r— 3
CJ3 r
• r-. r- <T> r—
rs
, o
3
^ +J 4J • 1 —
3 L.
Q .
oa
• •-D
•» 00 o
JO c (U S-o o
Q
• • LU C_) Cd ZD o 0 0
• o .
*d-^r —
. OJ E O a:
A
I/) c o
•r— + j fO z -o <u
+J • r -
c 3 )
Q} - C 4->
M-o
O) s.
o
• o
• r -
s-cn
< o23
-a o o
Li-
• to
-(-> c <u
35
13
12
II
10
9
S>8 T3
LU
5
41
I -
3. U daytime = 5 - 8 m/sec
2. U daytime = 2 - 5 m/sec
1 . U daytime = 0 - 2 m/sec
3 4 5 6 7 f = pCO.46 + 8)
8 9
Fig. 2. Determination of ETp from Blaney-Criddle f factor
for d i f f e ren t daytime wind ve loc i t i es and high sunshine durat ion,
n / N - 0.9.
SOURCE: Doorenbos, J . & P r u i t t , W. 0 . , 1977. Predict ing Cropwater Requirements". Food & Agric. United Nations, Rome. 144p.
"Guidelines for Org, of the
36
13
12
II
10
9
^8
5
4
3
2
I
3. U daytime = 5 - 8 m/sec
2. U dayt-
3 4 5 6 7 f = p(0.46 + 8)
8 9
Fig. 3. Determination of ETp from Blaney-Criddle f factor
for different daytime wind velocities and medium sunshine duration,
n/N;=: 0.7.
SOURCE: Doorenbos, J. & Pruitt, W. for Predicting Cropwater Requirements". United Nations, Rome. 144p.
0., 1977, "Guidelines Food & Agric. Org, of the
37
5^
13
12
II
10
9
8
6 ^
5
4
3
2
I k
3. U daytime = 5 - 8 m/sec
2. U daytime = 2 - 5 m/sec
1, U daytime = 0 - 2 m/sec
3 4 5 6 7 f = p(0,46 + 8)
8 9
Fig. 4. Determination of ETp from Blaney-Criddle f factor
for different daytime wind velocities and low sunshine duration,
n/N C: 0.45.
SOURCE: Doorenbos, J . & P r u i t t , W. 0 . , 1977. "Guidelines for Predict ing Cropwater Requirements". Food & Agric. Org, of the United Nations, Rome, 144p.
and
where:
38
ru - 50mb ^^ - (e^ - e,) (3-4)
e^ and e, are the saturation vapor pressures at the mean maximum and mean minimum temperatures, respectively, for the warmest month of the year,
r - coop /ocor + elevation in ftx C^ - 68 F - (36 F * ^QQQ-^^ )
Cp = 13°F if calculations are in °F or 7.6°C if calculations are in °C,
T^ = 27.5°F - 0,25 (e2 - e^)° F/mb - (elevation in ft/1000 ft)
R^ = (0,35 + 0,61S)R^Q
where S represents the rates of actual to possible sunshine and R " so
the mean solar radiation for cloudless skies expressed in cal cm"
day . Values for R were interpolated from Table 3,
Saturation vapor pressure can be read directly from the Smith
sonian Meteorological Tables; however, to be expedient and to minimize
the chance for error, saturation vapor pressures were calculated in
this and all other methods where needed. Murray suggests the follow
ing formula for calculating saturation water vapor pressure e (T),
also expressed in this report as e or ea (31):
e = 6,112 e x p ( y i ^ ^ l ^ ) (3-5)
where e = the saturation vapor pressure in mbars and
T = Temperature in °C.
Penman (8)
The form of the equation used for ETp estimation in this
design was
ETp = c[W * R^ + (i-w)*f(u)*(e^-e^)] (3-6)
39
CO
CO
LU I—-I
CO
0 0 C;0 LU _ l Q ZD O _ l o or o
Q •sC a :
<: _ j o oo
I >>
• o
CM I E o
u cu
> o
o o
0 0
3
CO «!d-CM
CO r^ CO
r—
r«» CO
CO CM CO
o CO CO
r ro •v
vo CM «d-
^ r •=3-
as r— LO
JZ
c: o
r«> VD LO
CO O V£>
p*»
ro <X)
"^ r»«s VD
r* CT vo
CO o r-s
tn LD r-.
r— KO
rx
LD in r
3
<:
Xi
o o 00
o o CO
ro as ro
>> fO
s:
CM «d-r->.
CM ; r
CM «:;»• r>.
^x> o o ro
as CM uo
00 VD LO
O o <x>
(/> 4-> C 0)
E a> 3
ol
O) 4-> n3
sz o
•r -S-
• a c:
ro
O
CU to
cu >
CM E 3 to e o
CJ)
LD
CM
CM ro ^
to as ^
as ^ LD
I •r- CU -M - O Z fO 3 0
—I +-)
0 0 CM
LO
ro ro o
o ^3-
LD OO
O ro
«3- to r^ s-as Q) I— <u
• > - r —
• as LU C
LU
(U CJ to
<u o
>> ••->
, , OJ LU •!— O (_>
oc o = ) 0 0
o 00 c
o cu
40
where:
ETp = reference crop evapotranspiration in mm/day
W = temperature related weighting factor
R = net radiation in equivalent evaporation in mm/day
f(u) = wind related function
(e^-e^) = vapor pressure deficit between saturation vapor pressure at mean air temperature and mean actual vapor pressure in mbar.
c = adjustment factor to compensate for the effect of day and night weather conditions.
The wind related function f(u) is defined as:
f(u) = 0.27(1 + y ^ ) (3-8)
where U is the 24-hr wind run in km/day at 2m height. As of 1965, the
height of anemometer at the Lubbock Weather Station has been approxi
mately 4m. Corrections for wind measurements taken at different
heights are given below (8):
Measurement height m 0.5 1.0 1.5 2.0 3.0 4.0 5.0 6,0
Correction factor 1.35 1,15 1,06 1,00 0.93 0.88 0.85 0.83
The correction factor used in these calculations was 0.88.
The weighting factor W accounts in part for the effect of radi
ation on ETp. Values of W relating to altitude and temperature are
given in Table 4. Averages of the maximum and minimum temperatures can
be used for this table.
The effects of wind and humidity on ETp are represented through
the weighting factor 1-W, Procedure for selecting (1-W) values is
similar to that for W. Values for the (1-W) weighting factor are shown
41
oo LU =) h-<c a:
ca
Q
LU
< : l-H OO O LU < : Q ct: ZD
o h-CO o: h-
h-C_J LU
<
o U- <
LU
o
ca o f —
CU
a: cu
oo LU
O
00 ro
to ro
ro
CM
ro
O CO
00 CM
to CM
CM
CM CM
O CM
00
to
CM
CO
to
CM
CU
<_> o
Qi S-3 +J ra s-<u ex
E
3 +J •^ +J r— fO
-M
O O LO
o o o •-"
o o o CM
rt3
to CO •
LO CO •
«l3-00 •
CM 00 ,
r^ CO •
as
00 r*-. •
vo r*. •
':J-
r». •
CM r-«. •
o r-« •
r«* to •
LD to •
CM to •
O to •
r- LD •
«=f to •
^— iXi •
00
•
^ «3-
r CO •
to CO •
LO 00 •
CO CO •
C J 00 •
o CO
CTi p^ «
p- r •
LO r •
CO r •
r— r •
cr> to •
to to •
to «;r .
^— to «
CO LO •
LO LO •
CM LO •
O^
•
to «3-
00 CO •
p>» CO •
<o CO •
to 00 •
^ CO •
CM CO •
^— CO •
as r •
r r> •
lO r •
CO r , t—
r-» «
CO to •
to to •
CM to •
r— to •
00 LO •
LO LO •
CM LO •
as ^t
oo L!J ca \— < ca LU Q.
s: LU »—
J—
LU ca LU u. u_ (—4
1— «sC
a. LU
O
>-1— 1—1
Q h—1
2:
or
2r "SC
LO Q 2: I — 1
LU S _J CO Lu «=C O 1—
LU LL. Lu LU
LU or 1—
ca o L u .'—».
1 1
ca o \—
oo LU Q
1 — «
1— 1
Q
<
c_> o:
e3
cu
o
oo
o
00 CO
to CO
CO
C\i CO
o CO
CO CM
to CM
CM
CM CM
O CM
CO
to
^ CO CM
• •
CM
CO
to
CM
O O
<u
3
03
(U
E
4->
LO ^ CO
CO
• •
to to >5j-
CM 1— CM CM
•sj- ro CM CM
to LO CM OJ
CO r>« CM CM
o as CO CM
CO f— CO CO
to *3-CO CO
CO to CO CO
o as rj- ro
CO CM
tO LO «3- «3-
cn CO
CM 1— LO LO
to «3-LO LO
LO
CT> 00 to
r— O CO CM CM 1—
cn
CM
CO CM
LO CM
CM
cri CM
CO
«3-CO
to CO
ro
CM <3-
lO
CO
LO
E O O O o o o
OJ LO O O •a I— CM 3
to
(U E (U
3
cr cu ca &. (U 4-> no
Q.
o o CJ)
o 'r-
•o Q-
o
to cu c
<u -a •r-3 cu • = a.
« ^
as •
r— <u E
" O • ca • 00
o +J +-> +-> 03 •I- z: 3 s_ -a a. (u
c
cu to o
Xl e OJ S-o o
O
D1
Q O
.. cj ijj -i-
C_) S-
= ) < o to oO
O O
42
in Table 5.
Average relative humidity CRHmean) is used in determining the
mean actual water vapor pressure (e.) by the relationship e^ = e * u ^ a a
RHmean/100. The mean saturation vapor pressure e was calculated by
eq (3-5).
In determining total net radiation, values for net shortwave
radiation (R^^) and net longwave radiation (R ,) must be known as:
\ = ^s - nl (3-9)
and R^^ = (1 - <K )R^ (3-10)
where R^ is defined as the solar radiation reaching the earth's surface
and represents the potential energy available for evaporation and
transpiration of water, and o< is the reflectance or albedo.
The amount of incoming radiation received at the top of the
atmosphere (Ra) is dependent on latitude and the time of year only.
Values of Ra expressed in equivalent evaporation are given in Table 6.
R^ = (0.25 + 0,50 n/N)Ra (.3-11)
where n/N = the percentage of maximum possible sunshine hours.
Net longwave radiation R , is a function of temperature, vapor
pressure (e.) and the sunshine hour ratio n/N. Values relating these
functions to R^i are given in Tables 7, 8, and 9, R. is taken as the n I ^ n I
product of these three values f(e^) * f(T) * f(n/N),
The Penman equation assumes the most common, generally moderate
conditions with regard to relative humidity, radiation, and wind. To
account for instances when these weather conditions are not met, a
correction to the Penman equation through an adjustment factor (c) is
required. Adjustment factors are presented in Table 10 relating
to LU
1 CO <c 1—
Q LU 0 0 0 0 LU ca Q L -
X LU
^—^ (T3
ca ^-^ 2 : 0 H-H
h-• < \—i
Q
ca _ j
<c 1—I
Q : t— 0 0 LU ca ca LU t— < ca \— X LU
>> <T3
T3 * s ^
E E
2 J 0 1 — «
«=C oc: 0 0 . < > LU
1— -z. LU - J
«=c > l - H
=5 cy LU
o o
> o
o o
Q . (U
C3^ 3
C
o
3
C 3
rt3
Q .
•a:
J3 cu
•-3
I • r - CU +-> t 3 Z tT3 3 O _J +J
CsJ •
CO
CM •
CO
r—
. CO
O r -
( O
I— CM
o to
<ys
o
CO
LO
o
t o
CO
CM
as r-• •
•s:!- LO
CM
0 0
CO
CM
cr» to as
CO •
to
CM •
r<»
1 ^ •
r-
CO •
to
CO •
to
CO •
r^
LO
CO
as
o
CM •
CO
1 0 .
CO
CO •
CO
CM
to
0 0
43
to CO CO
CM CO
1 (U s^
•r— 3 c r (U
ca
s^ <u -M «TJ
s Q , 0 s..
<J>
o> c
• ^ 4J 0
• 1 —
- 0 (U ^ cu S-0
t » -
(/» cu c
'r-
^-0)
- 0 •^ 3
CU —
. p^ r> en r—
r^.
. 0
• 3
•« +J -M • r—
3 S-
CU
oej
• - D
A
in 0
J 3 C (U i . 0
• 0 .
";*• ^ r—
. (U E 0
ca
.\ to e 0
•r—
+-> f O
^ T3 <U 4-> •r—
c rs (U
j =
+ j
M-0
• 0 1 S-
0
• 0
•r— S. CTI
0 <c o
« • LU C_J a: ^ 0 0 0
oC
-t3 0 0
Lu
• {/)
-U» c 0)
ca
o •r— +J (X3
•r-
-o ca
>
TO c o
LU - J CQ <
M-
LU
ca
ca
o I—
CM
CO
to
CM
LO CO
CO
CM CO
O CO
00 CM
CM
CM
CM CM
O CM
00
LO
«^
• 00 '~
• p>. »—
CM •
P>. •—
P>. •
to r—
CO •
LO •—
CT> •
LO '
• LO r—
o •
LO •~
LO •
•—
CM «
'—
00 •
CO '—
LO •
CO
CO
p ^
CM
CM
O
CM
ca
CO
CQ
o ca
cu
o
• a <u
«3-
00 oo LU ca a.
O Cu <: Lu O
C_>
C_> O
CO
t o
CM
CO
to
<T3 JO
<U
44
o ^
CO CO
to CO
*:!•
CO
CM CO
O CO
CO CM
to CM
"^ CM
CM CM
O CM
to o • r*
o •
CO
o *
00
o •
C3 O •
o •
r—
•
CM r— *
CM r— .
CO
•
«a-1 ^
LO
to
0 0
as
o CM
CM CM
CO CM
(U
** o
« o
I
"^ CO
o II
-a a;
ca
ca
CU
o
oo ca
as
CO
oo
oo
cu I—I ca CO
X
Q
<:
C_)
ca
o I— C_3
LO
as
as
LO
o
CO t o
as
.85
CO ft
.75
•
.65
to ft
.55
LO ft
.45
•
.35
CO
LO CM
ft
CM
lO
.87
.82
CO
ft
.73
.69
.64
.60
.55
.51
.46
.42
.37
.33
.23
as ft
LO
o
o
as o
o II
IT c
to +J c (U E cu s.
•f— 3 cr (U
ca
&-(U
•M
ra
Q . O
s-
en
o
(U L.
Q .
S-
o
tn cu
<u -a
= Q .
«^
p^ as • f— <u
E •> O
• LO 3 C
O r. . ^
+J -J-) +J 03 3 S- XJ
Q. (U +-> e
O) » JZ
to +->
o Xi "4-C O CU s- • O cr| O i-
Q O
C_) s c i : CTi = : <3: o oo oC
• o o o
CM o CM CO r^ f— ro ro CM
o
II
X ro E zn ca
<T> o r*^ t o LO I— CM CM I—
• •
vo
ro
LO o o I—
o.—»— o
CM cr> «>f CO O CT> CT» 0 0
O CO CM CO 1— CM CM r—
<
czr UJ
CM LO crt cTt ^ O I— I— f—
o LU I— LU oo LU ca o .
o LO
II
X rt3
E
as
LO
o
II
.c C7>
•r—
• o
ro
LO f— I— CM O r - r - O
0 0 O LO CO CTt o cr> CO
t o CM LO t o en cr> CO r^
ca o I— CJ)
CM
ID
Q <
I
O
LU _ J QQ <
O CO
X
E I C
en
LO
ro
O P** CO o
o o^ en o^
O CM P^ CO o en CO r>
O ^ P^ LO CT> 0 0 I— LO
t o CT> 0 0 LO 0 0 P-«. t o LO
o ro II
+ j XI CD
• ^
O 0 0 LO t o r— r— I— O
• ft • •
LO ^ I— CM
o o o en
CM ^ LO 0 0 o CT» CO r>.
LO CM O LO o I— I— o
>> to •a
tn ca
o to
<T3
o ro to o^
LO LO CM CO O O O 0 0
0 0 LO 0 0 c n <T> O^ CO f ^
t o r^ p^ r-H CJ> CO P^ LO
O «d- 0 0 CM o e n 0 0 CO
O CO r— CM o CO 0 0 r>^
O >— CO LO cr> 0 0 LO LO
t o LO f— LO 0 0 P>» LO ^
o CO LO cr>
o CM
II
xz O )
ro -a
O « ^ CM LO I— 1— r— O
O O LO LO I— I— o e n
• • ft •
LO 0 0 CM r— O 0 > O^ 0 0
• • ft ft
CM CT> O^ t— O CO P^ P^
LO LO CM LO O O O <T>
LO e n ^ ^ o en en 00
CO r - o o CT> CT CO P»-
LO r o O CT> CT> CO P*>» LO
O CM ^d- t o O <T> 0 0 r« .
II
-u>
as •r-
c
O LO O 0 0
*;r LO P- LO
O LO .— 0 0 CT> P*". LO «!d-
to <T> ro r » CO LO LO CO
45 O LO O LO r— O O CT>
o ! — LO r^ I— o e n 0 0
LO CM CM CM O CT» 0 0 P^
CM LO CM CM o CO r^ LO
LO C3 CO P^ o c7^ e n 0 0
ft • •
LO ^ *;!• LO O CT» CO P^
CO LO o o CT» 0 0 r^ LO
LO 0 0 CM o Cr> P* t o LO
• • ft ft
O CO LO e n
o cy> en o O CO r^ p^
O CM CO CT O CO LO LO
O >— CO I— e n p^ LO ^
t o ^ CO r^ 0 0 LO "53- CM
O CO t o (T>
to •M c a E <U s-3
cr CO.
s_ a> + j
ciu o s-
C_)
en c
4-> U
• o
a . s-o
in
c
cu T3
3 • CU Q L
P^ pv. . en cu r— E
o r^ca
cz> « to
. c 3 O
•r— « +J
+-> fO -!-> Z
3 -O i - Qi
Ci- 4->
•73 CU
to O M-
^ O C (U • s- crj o s-o o Q
» U
LU S-c_) cm a: < O oO 0 0
"O O
o
46
different conditions of RHmax, R^, Uday, and Uday/Unight.
Modified Penman
The Texas A&M University Agriculture Research and Extension
Center near Lubbock combines a locally developed radiation coeffic
ient and a form of the Penman equation in estimating evapotranspir
ation rates. This technique was derived at the extension center
for use in determining irrigation schedules and frequencies (46).
ETp = 0.00673 ^ ;^Q^27 tRn) ^ ^ V o . 2 7 (T5.36)(1.0 + O.OIW)
( 7 - e^) (3-12)
where R„ = net solar radiation * R^ 4. n factor
— e + e e = smax smin
^sraax* srain ~ saturation vapor pressure for average daily max-raura and minimum monthly temperatures respective-
®d "" smax (maximum monthly relative humidity) + e . (minimum monthly relative humidity)(.5)
W = wind run in miles/day
A = temperature dependent slope constant.
For convenience, many of the calculations were programmed into a pro
grammable hand calculator, such as:
C^ = 0.069197 * exp(3,1030556 E-2 * Tavg) where T is temperature in F.
R . . = 2.02895 E-10(day no. )^ - 1.57 E-7(day no.)^ + 2.9057 fac tor £.5(ciay no.)^ + 0.0004Cday no.) + 0.278855
e = 2.4493 E-6(Tmax)^ - 0.000114(Tmax)^ + 0.00611(Tmax) + ^^^^ 0.026114
e = subs t i tu te Tmin for Tmax in e^^,„ equation, smin smax
R is average solar rad ia t ion measured in langleys and e is s smi n
47
determined by substituting Tmin for Tmax in the e equation. Input
data necessary for the Texas A&M modified Penman formula was taken from
May, 1966 through August, 1979. This period was limited to the months
for which solar radiation data is available. Solar radiation is meas
ured at the Texas A&M experiment station by a LI COR pyranometer.
Pan Evaporation
Reference crop evapotranspiration can be calculated from pan
evaporation (Ep^^) by applying empirically derived pan coefficients (kp)
in the equation
ETD = kp * E (3-13) P ^ pan ^ '
In addition to measured E data, knowledge of the pan type and sur
rounding environment are also necessary. Pan evaporation is affected
by the position of the pan in relation to ground cover, wind and humid
ity. A listing of crop coefficients related to these three variables
is given in Table IT. Pan evaporation data was provided by Mr. Oliver
Newton of the Texas A&M Agriculture Research and Extension Center. The
Extension Center uses a standard Class A pan, which is 121 cm in dia
meter and 25.5 cm deep.
Selection and Application of Crop Coefficients
The five methods described above were used to estimate the ref
erence crop evapotranspiration potential. To determine the actual
evapotranspiration for a specific growing crop (ET ), a crop co-
efficient must be applied. Values of the crop coefficient (kc) are
related to the plant characteristics, rate of development, length of
growing season, and climatic conditions. The procedure used in this
, ' UJ _ J CO
<c f—
u . <z>
try
U J > •
U J _ I '
Q 2 r <c Q^ L L I
O C_3 a "Zl ZD <=> ca cu
\— 2 ^ 111
ca LU LL_ L L . t—(
o ca: o Lu.
z : < : o .
< :
oo oo •St _ J
o U -
<»—>» ex
. ^
1— LU »—H
C_) 1—t
u_ LU LU O C_3
z : <c o .
o ^ 1—«
3 Q i I D O nr ^ CM
O ^C
<c > -1— 1 — •
Q t — 1
^Sl ZD ZC
LU >• t—i
\—
ELA
ca
<c LU ^
rea
<o •
o 1 ^ " "
. fO n
dry
• r -
- o 0) CJ fO
C3L
c Q_
• • CQ
CD to ra
c_>
<T3 <U ^ (TJ
T 3 <1) C3.
O s-o
c 0) cu
as + j
hor
to
c:
• o <u o n3 r— Ou
c fC
CU
• ft
<J:
cu CO fO
C_3
c rT3 C3L
<
to </1 <T3
C_>
high
>70
E O 3 P^
•1— 1 -o O , E
S O o ^
xz o cnp"^
2A
E O 3 r^
•r— 1 •o o <U " ^ E
s o
S «
d (T3 <U E
zn ca 1
u cr « E
+ J to
•r— • o s
o cu 1—
" O I— • r - ea CO M—
-o > , S> i? fO T J S
- O 4 -E O
CD
<o 4-> E to
- O Q . O
CU s--o o • r -in c
Qi -a Q) i . S-(T3 e n S
-a 4 -c: o
• 1 —
3
>> ta
• a T 3 c -^^
••- E 3 ^
i n LO 0 0 0 0 P^ P^
LO 0 0 P^ LO LO
LO r>. LO LO LO
LO 0 0 P>. LO LO
LO LO LO P^ LO LO LO
LO LO LO LO LO LO ^
LO LO p^ t o LO LO
LO LO i n LO LO LO ^
LO LO LO ^ ^
LO LO LO LO LO LO ^
LO LO LO « ^ ^
LO LO LO ^ <;J- 0 0
"— o o o r— O O
r - O p —
LO LO LO t o r^ 0 0 0 0 CO
LO LO LO LO r^ 0 0 CO
LO LO LO LO LO P^ P^
1— o o o r— O O
1— o —
4 J LO j c r^ CT^i—
--W
r - O O O I— o o
r— O p —
LO LO LO r^ CO 0 0
LO LO r^ p^ 0 0
LO LO LO LO P^
n- o o o 1— o o
.— o r—
Qi + J LO fO CM s - ^ Qi 1
- O LO o r^ s : <—
r— O O O •— o o
•— o r*"*
LO LO LO LO P^ P^
i n LO LO LO P^
LO LO i n ^ LO LO LO
r - O O O r— O O
1— o r^
o c n o c: r^ O 1 S- LO
+J OvJ oo «^
I— o o o 1— o o
r - O ^^
LO LO LO LO LO LO
LO i n «;f LO LO LO
LO LO <d- "sd- i n LO
-— o o o .— o o
r— O r ^
as sz o -M to
o > > o i - p^
^ A :> '
48
ents
'
E OJ
3
c r ca
Wate
r
Q . o
c_>
as c
-u> CJ
"O OJ s_
Q_
i . o
14-
tn OJ c
•r—
(U • 0
3
cu • = Q .
"^ "^
P-N.
r^ en . f— cu
E « 0 . ca
0
• to 3 C
0
-M fT3 • > - ^ 3
d . (U 4 - >
oS - ^ c
. = ) '"3
OJ n t~"
in 4-> 0
Xi '-*-c 0 a; s> . 0 CT 0 s-Q 0
ft
LU -r-0 : -ca o) ZD < 0 0 0 oes
- 0 0 0
LU
49
Study was adopted from the Guidelines for Predicting Crop Water Require-
inents C8)..
Monthly crop coefficients were determined by plotting kc values
for each of the four stages of crop development. These stages are:
1. initial stage: germination and early growth (groundcover
10 percent)
2. crop development stage: from end of initial stage to
attainment of full groundcover
3. raid season stage: from end of full groundcover until time
of plant maturing as indicated by discolored leaves
4. late season stage: from end of mid season until full matur
ity or harvest.
The duration of each development stage for each crop is shown in Table
12.
Crop coefficients for the initial stage were determined from Fig
ure 5. As shown, for corn planted in raid April, an ETp value of 5.3
rara/day tby th.e Jensen-Haise Method) will have an initial kc value of
0.44. In Figures 6 - 10, values of kc were plotted against the dura
tion of crop development in stages 2, 3 and 4.
Hydraulic Loading Rates
Hydraulic loading rates for land treatment systems are based on
either soil permeability, nitrogen limits or a combination of both com
ponents. The more conservative of the two for each month is taken as
the design hydraulic loading rate (LwD). The LwD was determined by
using the procedure discussed in the Process Design Manual for Land
Q . O CU
r— O) Qi ta > -M <U 0 0
Q
CM
CQ
OO o. o oa CJ
Q LU h-C_3
LU OO
ca o
CO LU I— <c Q
CU
- J CI.
Q
<C
OO LU CU
1— oo I—
LU
Q-O
LU Q
O 0 0 < LU OO
CU o 4-> to (O ns
—J Qi oo
o "O to • I— fO s: cu
t /1
LO CO
I
o ro
O CM
1 in r—
o CM
1 LO f —
o LO
o "^a-
o ro
o LO
* o as
50
<a Qi •I— as 4-> ra • I - 4-> E tn
c to '^ ^ o -a cu 1— O fO t o
O CU t — OO
en • I - cu 4-> +-> C «t3
LO O LO
O ro
LO CM
o CM
O ro
o CM
o I
i n ro
o ro
I LO CM
o CM
I LO LO
as o CO
o i-
CJ
r ^ •r—
s-CL
<
-o •r—
s:
>^ (T3
^ -a •r—
s:
+ j to
r—
(U E 3
""O
S-cu
- Q O
4 J CJ
o
-o •^ s
4 J
CJ
4 J Q .
0 0
en 3 O i-
2 o S-
as • o E 03
o t J
r ^
rtJ E O in i~ <U
Q -
0%
>s 4-> •r-
to s. <u >
• r -
E ^ t—
<J CU
1— to <a X. cu
1—
. CM CO en
ft
E (T3
•-3
T3 E na
m
ti Qi
Q
L»-O
+J LO O E as E
•r—
S-3
-a + j E (TJ E i_ O
• o
CU Xi
^-i-cx
<a: • a E 3 O
(a CL 3
E (U CU s-CT>
r ^ r ^ • 1 —
2 • o E <T3
r—
(T3 •r—
c E OJ S-<u Q .
ra I— to
Q I— -r-
E ^ O
C_?
C o •u> +-> o
C_)
E 3
. E cn s-o
m
4->
ro <u
- E 3
••« rC
-o 3 E s> cu
CQ
«S
C7 cu
•r—
S-:>
ft ft
LU C_> ca l U o oo
2 4-> 03 OJ
- E 2 S-<u
+J E
•r—
zs M
to to (T3 i-CD
«3 • o 3 E s_ (U
CQ •K •K
51
03 XJ
E E ro
• LO
II
Q-
(U as «3
to
rt3 •r-+J
E
as
CO
- r«~.
t o
LO
I I I I
CO
CM
00 to «;*• CM • ft • •
o o o o D>| *q.UaL0LJ.^9O3 dOvlQ
>> ta
-a • ^ ^
E E « Q-
1— LU
•r—
- D CU
+ J E «C
^-o. E S-
o u &-o L i
eu cn fO
+ J t o
+-> E
<u s. o r— CU
> cu
-o a. o s-LJ
r— ea
•f—
+-> • 1 —
E •r—
S-
o 4 -
<U 3
^-(T3
> U
j x :
(U CJ> OJ L. (U
> e t
ft
LO
• cn
• r -L_
• CU
1 ^
3
-o Q)
XZ
u to
E
o • 1 —
+ J 03
cn •r— i-
s-•r—
>> 03
-o 1 ^
•o E 03
O -1— LU
O
+-> -a Qi
4-> ra
1 —
(U S-
to 03
t—
• 1 —
s-o. <x.
1
a. o &-
L J
cn E
•r- ,
a ^ • 1 - «d-- o 1— (U
Q . • OJ
S- E O O
M- Q ;
to " Qi to E E
•r- O ^ - T -<U -M
•O 03 •r- 2 : 3
CD - O = CU
• M • r -
• E r^ ZD T^ as Qi r— x:
4-> A
• M-O O
• ft
3 CTi i-
x O + J -t-> • I - U 3 ' t -J- s-
Q. cn <
oej o a
• '^ -o
o « o to Lu
O X 5 E • CU = i_ to O -M O E
o <U E (U
• • J -LU •<-O 3 cs: cr O (U o ca oo
s_ OJ
- M 03 5
52
Q)
03
E O to 03 Q) to I
"O
LO
0 0
I Qi S-
• I — 3 cr Qi
ca
s-
• • ->
03
tn Q. Q) O cn s-03 c_) to C71
E
LO
CD 3
<C
E CU E Q . O
Q) > CU
-o Q . O s-CJ
cu cn 03
+-> to
03
J . J . _L J_ i . JL
o cn
E Qi
Qi
03
E O
+ J +-> o u
o
cu > 3
u
•u> E CU
i n - 1 -
i n
3 "-3
3 (U o u
Q . o i -
C_)
LO
ft
cn
LO
u •p—
CU &.
CI.
S-o
If-
in , cu Q. E «:3-
• I - « ^
CU • o • p - .
3 CU tD E = O
QC r>^ t o P^ E cn o
• cu 3 +•>
*> E •M =3 +-> • r - CU 3 XZ i - 4->
Q^ L -
oO O
«o in o •
JD U E T -<U J -
.S-.-C3TI O cC O
Q oes
•• o lU o C_J Lu ca o oo
o^ c:o p^ t o LO ^ • • • • , ,
o o o o o o D>| * ^ U 9 p L J . J . 9 0 0 dOvlQ
to E QJ E
53 I
J -
cu
03
E O to 03 Qi to I
T 3
E 03
I '-D
C_3 I
CQ
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cu E e:L o
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en
cd 0 0
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A.
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'
cn 4->
S-
as
to cu cn 03
to
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ca
s. O)
4-> 03
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C_3
cn E
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CU
3
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pv.
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en o
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<+ -oO O
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ca
LO
o o o o D>J *:;U9L0LJ.J.90D do,^3
ft
o o
o 00 to
CU
54
^
Q . CU
tn
^
cn 3
<c
,— 3
O
E 3
•-D
ft
in Qi cn OJ +-» 00
- E + J 2 O s-cn
+ j E CD i-Qi
M-i * -• r -
• o
4-> 03
E 3
.CI cn u o to
s-o
^-Qi > s-3 CJ
+J E (1)
• r -LJ
• (— M-L»-
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CL o s-
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ca s-Qi •M OJ
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CL o s.
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cu s-o.
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to cu E •
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-a ca • r -3 •>
CU to = E
o • • • - >
r^ 03 r- z as f— -a Qi
« 4_> • 'r-
O E ZD
3 Qi XZ
" -M 4-) +J M-•r- O 3 i - •
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to c r O <C
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SO
UR
CE
: D
q
uir
em
en
ts",
F
0)\ * : ;U9LDL^^90D dOUQ
55
I <u s -3 cr cu ca $-Qi
+-> 03
CL O S.
CJ
cn E
• -+->
• o cu s -
S-
o to CL cu « ^ E ^
CU - a • • I - cu 3 E
cu O = oc:
• to r- E r^ O cn •
03
o -a . cu
•> E +-> I D
• I - 0^ 3 . i- -M
Q-
r- oa o
o a s-
to O •
JD o E - 1 -CU ^
O <. O
Q oC
-o • • O
LU O C_3 Lu
ca o = oo •
to +J E Q)
oy\ *:;u9LDLj.j.900 douo
56
CL
CU
OJ
03
in cu cn 03
to
2 o cn
Qi
Qi
I
& -•p— 3 cr a; ca
Qi +-> OJ
o. o & -o cn E
CU S-
CI.
i.. o
(/) CL cu ^ E « ^
JQ Qi
E O in 03 Qi I/) I
T 3
E CU
CL E O CL S- O U I—
> cu -o
1. _L J.
03
J .
u (U
Q
> o
03
•M 03 CU
o
(U > 3
u E CU
'r-U
CU o o CL
o i_
CJ
as
cn ft
o
0 0 r^ LO LO <d-ft ft • ft ft
o o o o o 0>| * : ;U9pL^J .90D dOJO
cu -a • ..- cu 3 E
c u O = ca
• in r>. E p>« o OS T— I — 4->
03
o -a • cu
• p - Q)
3 SZ
C:L *+-
©a o
" o cn
tn O
j Q U E -p-Qi S-S- cn o «a: o
Q oa
• o .. o LU O CJ Lu ca
O • OO =
to • • ->
E CJ
57
Treatment of Municipal Wastewater.
Soil Permeability Criterion
The hydraulic rate based on soil permeability LwP is siraply
the component of a water balance equation stated as
LwP = ET - Pr + Pw C3-14) crop
where ET = evapotranspiration rate (.ETp * kc)
Pr = design precipitation rate
Pw = percolation rate.
A minimum soil permeability rate of 0.6 in/hr was taken from the Soil
Survey of Lynn County, Texas, a SCS publication. This rate is a con
servative description for the Amarillo soils, which are predominate
over the site. Percolation rates for system design were approximated
at 10 percent of the minimum soil permeability.
The design precipitation for each month was based on a 5 year
return period frequency analysis for monthly precipitation. Forty
years of precipitation data frora the cliraatological records of Lubbock
(1941-1980) were used in this analysis. The plots of the monthly
values are shown on Figures 11 to 15. The value obtained at the inter
section of the curve with the 80% probability value gives the 5 year return value.
Wastewater application frequencies of 1 day per unit area per
week, with 2 days of percolation for each irrigation event, were used
to calculate soil percolate amounts. In practice, this schedule will
be adjusted for wet weather periods and harvest.
The equation used in calculating the design percolation rate is
Pw = Ps(24 hr/day)C2.54 cm/in) (.0.1) (8 days/mo) (3-15)
58
Probabi l i ty Of Exceedance
99 98 95 90 8o 70 6o 50 ko 30 20 10 5 2 1 0.5
0) x: o c
c O <TJ
Z k
o 4)
Ju
;
y"'
No •
y /
/
/
/
/
/
/
—
!
i 1
1
10 20 50
Return period, yr
Fig 11. Frequency analysis of monthly precipitation for Apr., July, Nov.
59
in (U
Xi u C
c o
(0
u <u k. a.
P r o b a b i l i t y Of Exceedance
99 98 95 90 80 70 60 50 AO 30 20 10 5 2 1 0.5
Sef
Oc
t ^
/ t
/
/
/ /
/
/
/ /
/
/
/
1
1 !
1
1
1 1 1
10 20 50
Return period, yr
Fig. 12. Frequency analysis of monthly precipitation for Sept., Oct.
60
in <u
x : o c
c o
(TJ
Probabi l i ty Of Exceedance
99 98 95 90 80 70 60 50 '»0 30 20 10 5
^ k
o <U u
cu
1 0.5
Au
De
y 3
1 ^
1 1
i i
/ /
/ ! / ' : i
.( ' ! / ! ' • , 1
: \ i I 1
/
A /
1
/
•
1 1 1 !
i
1 I 1 1 i
2 5 10 20 50
Return period, yr
Fig. 13. Frequency analysis of monthly precipitation for Aug., Dec.
61
(U xz o c
c o
CO
Probabi l i ty Of Exceedance
99 98 95 90 80 70 60 50 lO 30 20 K) 5 2 1 0.5
-M i«
u (U
a.
14a
F
^
^
/
/
/
/
K '
/ /
1 /I
/ I / I
/
/
/
/ •
/
/
/ "
i 1
, 1 1 1
1
i 1 1 t
i 1 1
i ; 1
1 \
1
1 1
10 20 50
Return period, yr
Fig. 14. Frequency analysis of monthly precipitation for Feb., Mar,, May.
62
tn (U
xz o c
C
o 03
O (U
Probability Of Exceedance
99 98 95 90 80 70 60 50 ^0 30 20 10 5 2 1 0.5
Jun
Ja
e /
n "
/ /
/
/
/
/
i ,
i
i 1
1
1 1
1 1 ' 1
/ 1 i ^ / 1 ; 1
/ ' i ' i
1
5 10 20 50
Return period, yr
Fig. 15, Frequency analysis of monthJ/ precipitat ion for Jan,, June,
63
where Ps = soil permeability in in/hr. Pw for this site was calcu
lated to be 29.26 cra/mo.
Nitrogen Loading Criterion
The approach for establishing hydraulic loading rates based
on nitrogen'liraits centers around insuring that percolate water enter
ing a potable groundwater aquifer does not exceed 10 mg/1 nitrate
nitrogen. The equation used to determine allowable annual hydraulic
loading rates based on nitrogen limits is
^^'- (l-f)(Cnr-Cp ^'-''^ where LwN = allowable annual hydraulic loading rate based on nitrogen
limits, cm/yr
Cp = nitrogen concentration in percolate, mg/1
Pr = design precipitation rate, cm/yr
ET, = evapotranspiration rate, cm/yr crop r r
U = nitrogen uptake by crop kg/ha-yr
Cn = nitrogen concentration in applied wastewater, mg/1
f = fraction of nitrogen removed by denitrification.
The design precipitation rates and evapotranspiration rates
are the same in the soil permeability approach as in the nitrogen
limit approach in determining hydraulic loading. The value used for
percolate nitrate nitrogen concentration was 10 mg/1. Monthly nitro
gen demand by plants was assumed to be in proportion to the monthly-
to-total season crop water consumption ratio for each crop, with the
exception of wheat. Monthly nitrogen uptake estimates for wheat were
provided by the Division of Agricultural Services at Texas Tech Uni
versity.
64
A value of 26 mg/1 was used for nitrogen concentration in the
applied wastewater in this design, and is representative of nitrogen
present in the storage lagoon on the Gray Farm. The fraction of nitro
gen removed by denitrification was set at 20 percent.
Field Area Requirements
Calculation of field areas were made using the following equa
tion (10).
Aw = Q(365 d/yr) ^ ^ V s ^3^^^^
(10\^/ha)(LwD)(10'^m/cm)
where Aw = field area, ha
Q = 7.5 mgd = 28,387 m^/d
LwD = design hydraulic loading rate, cm/yr
A V s = net loss or gain in stored wastewater volume due to precipitation, evaporation and seepage, m3.
Storage Area and Volume Requirements
Calculations of the total storage volume and surface area
requirements were made using the following procedure (.10):
1. Construct a water balance table with 5 columns with headings
for month, hydraulic loading rate (LwD), available waste
water (Wa), change in storage, and cumulative storage,
. ,, Qm(10"^) where Wa = - -tr
3 Qm = month wastewater volume, m
Aw = field area, ha
2. Compute the net change in storage each month by subtracting
the monthly hydraulic loading from the available wastewater
in the same month.
65
3. Compute the cumulative storage at the end of each month by
adding the change in storage during one month to the accu
mulated quantity frora the previous month. The computation
should begin with the reservoir empty at the beginning of
the largest storage period. This month is usually October
or November, but in some humid areas it may be February or
March.
4. The required storage volume is computed using the maximum
cumulative storage and field area.
Vs = Aw(max. cumulative storage, cm)(10 m/ha)
ClO'Vcm) (3-18) Vs
5. Storage area. Aw = jr, ds = 4m.
Examples of calculations for field area, storage area and volume are
presented in the appendix.
Cost Comparison
An economic comparison of initial costs for land application
systems was made to demonstrate the importance of crop selection and
ETp estimating methods. Costs for land, equipment and construction
were estimated as follows:
Land $1,200/acre
Irrigation rigs $40,000/1300 ft pivot 3
Clay liner $3.50/yd providing a 2 ft liner over
the storage area
A cost comparison for the crop systems and ETp estimating methods used
in this study is presented in Table 17 in Chapter V.
CHAPTER IV
RESULTS AND DISCUSSION
To best evaluate the combined effects of varying ETp rates
and nitrogen utilization, each ETp estimation method was applied to
each crop, and to two cropping sequences. Examples calculations of
ET estimations, hydraulic loading rates, required land area, and
storage volumes are presented in the appendix.
Evapotranspiration (ETp)
Average monthly ETp estimates are shown graphically in Fig.
16. The highest and lowest annual ETp estimates are from the locally
derived Modified Penman Method and the Pan Evaporation Method. These
vary by almost 20 percent. The pan evaporation data indicate a lower
ETp rate from late April to early October. This period coincides
with the period of highest precipitation and relative humidity.
Hydraulic Loading Rates (LwD)
Monthly LwN values decreased as ET estimations for different
methods increased. This trend is not surprising since the Pr - ET^^^p
deficit in eq (3-16) increases as ET increases. Consequently, in arid
areas there is an apparent inverse relationship between ET and LwD
when LwD is governed by LwN (Tables 14 and 15 respectively).
No such relationship exists however, when LwP controls LwD.
When crops with a high nitrogen demand are chosen, the U factor in
eq (3-16) increases more than does Pr - ET^^^ of the same equation,
66
67
t o3 < :
cu •a "O • p —
s. CJ
1 >s Qi E OJ
t— CQ
CU to
• p —
03 zn
1 E CU to E CU
' -3
E CU
Q-
T3 OJ
•f—
4-•r— T 3 O
2 ^
E 03 F E CU
Q-
4-> 03 S. o CL OJ >
LU
E 03 a.
tn >s 03
to XI +-> c
(A E O • " +J 03 E
'r-• M to CU
-D O
E O
t o
cn
as 0 0 t o LO CO
/Cep/lUUi *^13
CVJ
68
TAELE 13
AVERAGE MONTHLY ETp ESTIMATES (mm/day)
PERIOD OF RECORD 1965-1980, FROM
LUBBOCK REGIONAL AIRPORT
Month
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
cm/yr
Blaney-Criddle
1.49
2.41
3.60
5.04
6.59
8.01
8.14
7.21
5.73
4.09
2.34
1.61
167.51
Jensen-Haise
1.24
2.17
3.30
5.30
6.54
8.54
8.40
7.31
5.55
3.82
2.08
1.37
166.18
Mod, Penman
2.93
4.00
6.00
7.66
8.67
9.47
8.57
7.36
5.70
5.38
3.92
3.26
214.58
Pan Evap.
2.50
3.50
4.84
5.47
5.62
7.58
7.25
6.18
4.25
4.08
3.37
2.67
154.49
Penman
1.84
2.39
4.83
6.64
7.08
7.85
8.51
6.88
5.28
3.84
2.47
1.96
177.08
TABLE 14
DESIGN HYDRAULIC LOADING RATES (LwD) cm
69
CORN
APR
MAY
JUN
JUL
AUG
total
SORGHUM
JUN
JUL
AUG
SEP
total
COTTON
MAY
JUN
JUL
AUG
total
B-C
11.6
21.1
33.7
39.8
29.3
135.5
19.0
25.2
24.3
18.7
87.2
13.7
14.7
19.5
21.4
69.3
J-H
11.0
20.2
34.5
38.9
28.1
132.7
19.0
25.4
23.1
18.2
85.7
14.0
15.0
18.9
20.2
68.1
TA&M
11.9
21.3
33.1
35.6
26.1
128.C
19.2
24.9
22.9
17.9
84.9
13.9
14.2
19.0
20.0
67.1
PENMAN
12.3
21.9
32.5
40.4
27.3
134.4
19.3
26.9
23.5
18.8
88.5
14.1
14.9
19.5
20.7
69.2
PAN
12.9
21.6
37.5
41.7
29.0
147.7
22.3
29.7
26.6
19.4
98.0
12.5
15.3
23.8
25.7
77.4
70
TABLE 1 4 . CONTINUED
WHEAT
JAN
FEB
MAR
APR
MAY
OCT
NOV
DEC
total
BERMUDA
APR
MAY
JUN
JUL
AUG
SEP
OCT
total
B-C
1.4
11.2
34.5
25.8
17.3
21.0
23.6
8.3
143.2
35.7
37.7
43.1
45.5
42.4
35.8
32.4
272.5
J-H
2.0
11.8
29.4
25.4
17.3
21.4
24.2
8.9
140.7
36.3
37.5
37.5
46.3
43.5
35.1
31.6
275,2
TA&M
-
7.3
22.7
22.2
15.3
20.6
20.5
3.8
113.4
41.6
43.7
43.7
46.9
43.7
35.7
48.4
307.5
PENMAN
.6
11.3
38.4
23.6
17.0
21.4
23.3
7.3
143.0
39.3
39,1
39.1
46.7
42.2
34.4
31.7
276.0
PAN
-
8.5
25.6
25.2
18.3
21.1
21.2
5.4
125.3
36.7
34.9
34.9
42.7
40.0
31.4
32.4
259.8
71 TABLE 14 . CONTINUED
B-C
WHEAT/BERMUDA
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
total
CORN/WHEAT
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
OCT
NOV
DEC
total
1.4
11.2
34.5
35.7
37.7
43.1
45.5
42.4
35.8
32.4
23.6
8.3
351.7
1.4
11.2
34.5
25.8
21.1
33.7
39.8
29.3
21.0
23.6
8.3
249.9
0-H
2.0
11.8
29.4
36.3
37.5
44.7
46.3
43.5
35.1
31.6
24.2
8.9
351.7
2.0
11.8
29.4
25.4
20.2
34.5
38.9
28.1
21.4
24.2
8.9
245.0
TA&M
-
7.3
22.7
41.5
43.7
47.5
46.9
43.7
35.7
20.8
28.8
11.2
349.6
-
7.3
22.7
22.2
21.3
33.1
35.6
26.1
20.6
20.5
3.8
213.2
PENMAN
.6
11.3
38.4
39.4
39.1
42.6
46.7
42.2
34.4
31.7
24.0
7.3
358.0
.6
11.3
38,4
23.6
21.9
32.5
40.4
27.3
31.4
23.3
7.3
248,1
PAN
-
8.5
25.6
36.7
34.9
41.8
42.7
40,0
31.4
32.4
21.2
5.4
320.0
-
8.5
25.5
25.2
21.6
37.5
41.7
29.0
21.1
21.2
5.4
219.5
72
causing values of LwN to exceed those of LwP. It follows then, that
the more conservative hydraulic loading rate, LwP will generally
serve as LwD when bermuda grass or other nitrogen demanding crops
are used.
Using the more conservative of the two loading rates for LwD
safeguards against a build-up of residue nitrogen and possible
percolation of nitrates into ground water supplies. Nitrate nitrogen
(NO^'-N) concentrations increase in the soil water as water is
evaporated from the soil surface. Nitrogen held in the soil as the
ammonium ion but not removed by plants is subject to oxidation and
in time leaches downward to the aquifer in the nitrate form. Ground
water contamination would be quite probable in arid regions if
hydraulic loading was in accord with the high ( ' - ''' 00 deficit
unless crops with high nitrogen demands were used. To prevent the
above situation from occurring, the hydraulic loading rate per unit
area must be decreased, causing an increased land area requirement
for the land application system. Alternately, cropping patterns could
be chosen to favor crops with a larger nitrogen demand or prior treat
ment measures employed to reduce the nitrogen level in the waste
water.
Land Area (Aw)
The land area necessary to safely handle the design flow rate is
dependent on the hydraulic loading rate. Obviously, ETp estimating
methods that indicated a relatively high LwD lead to lower calculated
field areas. For all crops or cropping sequences except those includ
ing bermuda grass production, procedures for determining Aw following
73
the Modified Penman Method gave the highest values for land area.
Conversely, the pan evaporation method showed the lowest required
field areas. This trend is basically reversed when bermuda grass is
considered. The high nitrogen demand of bermuda causes the LwD to
be governed by hydraulic loading rates instead of nitrogen limits.
Nitrogen utilization is crop specific and is assumed to be in
proportion to the rate of monthly cropwater consumption. Monthly
nitrogen uptake for each of the five crops is presented in Table 15.
Storage Area and Volume
Required storage area and volume did not vary appreciably between
the five different ETp estimating methods when applied to the same
crop. However, when applied to the cropping sequences of wheat/
bermuda, or corn/wheat, maximum variations in storage volume were 9
percent and 19 percent respectively. Similarly, required storage area
varied 12 percent between the lowest values of 2.77 x 10 m for the
6 3 Penman and TA&M approach, and 3.04 x 10 m for the pan evaporation
method when applied to wheat/bermuda, Comparison of all methods in
the crop sequence for corn/wheat showed a 30 percent maximum variation
in storage area between the Modified Penman and the Penman Method.
Influence of Different Crops
The effects of different crops or combination of crops on hydrau
lic loading rates, land area, and storage requirements are shown in
Tables 14 and 16. Variation of design parameters is much greater
between different crops than are variations caused by different ETp
estimations,
TABLE 15. MONTHLY NITROGEN UPTAKE,kg/ha 74
Crop
Corn
-
Cotton
"^orahum
Bermuda
Wheat
Month
Apr
May
Jun
Jul
Aug
May
Jun
Jul
Aug
Jun
Jul
Aug
Sep
Apr
May
Jun
Jul
Aug
Sep
Oct
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
B-C
14
23
49
62
42
12
16
32
14
25
44
4Z
24
52
87
110
117
104
78
53
21
29
11
3
16
37
30
13
J-H
14
22
51
62
41
12
17
32
39
26
45
41
23
54
85
115
120
11)4
74
49
TA&M
16
25
52
59
39
13
16
32
39
27
45
41
23
63
98
111
106
91
66
59
Penman
16
24
47
64
39
13
16
33
38
25
47
40
23
67
91
105
120
97
70
48
Pan
16
22
52
61
39
12
18
32
38
28
^6
41
21
63
83
115
117
100
65
59
* Not related to evapotranspiration rates
75
TABLE 16
LAND AREA (Aw) AND STORAGE (As) REQUIREMENTS
CROP
WHEAT
Aw*
As**
CORN
Aw
As
COTTON
Aw
As
SORGHUM
Aw
As
BERMUDA
Aw
As
WHEAT/BERMUDA
Aw
As
CORN/WHEAT
Aw
As
* ha 5 2
**ioV
B-C
659
8.64
648
15.1
1231
17.2
978
17.2
338
10.8
278
388
•
J-H
675
8.60
660
15.1
1253
17.3
995
17.2
335
10.8
279
5.2
398
TA&M
833
8.60
684
15.2
1272
17.2
1005
17.3
300
10.8
277
45.3
6.6
PENMAN
661
8.58
652
15.1
1233
17.2
964
17.2
334
10.8
277
368
4.6
PAN
754
8.60
593
15.1
1104
17.2
871
17.2
354
10.8
304
5,9
406
76
Hydraulic Loading Rates
The design hydraulic loading rates increase in proportion to the
nitrogen consumption of the selected crop. As shown in Fig.17 bermuda
grass with a relatively high nitrogen use value permits a greater
waste-application rate. On the other hand, relatively low hydraulic
loading rates are afforded by less nitrogen demanding cotton. Inter
mediate LwD values were obtained when the nitrogen use characteristics
of corn, sorghum, or wheat were used in the procedure for determining
design hydraulic loading rates.
Land Area
The field area requirement for the land application system varied
considerably between crops (Table 16). High nitrogen demanding crops
such as bermuda require less land area than low nitrogen demanding
crops such as cotton and sorghum. The lowest field area requirements
for this study were obtained when water use characteristics for double
cropping wheat and bermuda were used in calculating land area over a
12 month period.
Storage Area and Volume
The storage area needed varies directly with hydraulic loading
rates. The differences are significant in both storage area and
volume when hydraulic loading rates for different crops are substi
tuted into the equation for determining storage requirements. The
greatest variation in storage areas, nearly 70 percent, is evidenced
between cotton and the wheat/bermuda combination.
77
^ 100-
d s 200-
300-
40O
600-
500-
>>
400-
CJ) Jit: 300'
200-
tD
i 100'
4 J 03 Qi
E S-O
o
E O
o o
E 3
o us
(a -o 3
E OJ
J 3
*^«. 03 -M -a 03 3 CU =
JC S_
J 2
4-J E OJ 5- OJ O - E O 2
Figure 17. Nitrogen uptake - LwD relationship
78
Cost
In an attempt to put the variations discussed above into an
economic perspective, a basic comparison of land area cost, storage
pond liner cost, and required number of irrigation units was made. The
results of this comparison for each combination of crop and ETp
estimation method is presented in Table 17.
79 invD O O
CJ I—
rtJ OJ
CM (U E a m CO o s - r -
o oo
0 0 Q O
LU
Q . I— LU
z: <c oo c O ca o o LU H -CJ LU _ ] LU OO
o 0 0 I—« ca < a. :E: o CJ
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80
CM CM CO CM CM
r^ p^ r^ r>. r^ 0 0 CO CO CO CO
• • • • ft
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LO
CM
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CM
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cu 4-> <o
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cn o r— CM
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81
CO C^ f<0 CO CO
CM r>. v o CM 0 0 . , » » .
LO LO LO vo v o
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r o CO
CM LO t—
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cr<: <u Q::
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&->>
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cn ji^
CO CO cn r^ CD CO as LO r— CD CO CO ';a- «a- «vf
o LO CM
LO «^ CM
CO p—
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as r—
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LO CM cn
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<u E
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03 cn
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03 J 2
I
US O
CJ
CHAPTER V
CONCLUSIONS AND RECOMMENDATIONS
Conclusions
The conclusions made from this study with regard to several
considerations in the design of slow rate land application systems in
climatic regions typifying the Lubbock area are:
1, Estimations of ETp using methods described in this study vary
by as much as 20 percent,
2. The estimated crop water deficit (Pr - ET ) may be as much crop' "
as -15.4 mm per day for bermuda grass during July, or as
little as -.8 mm per day for cotton during the same month. In
addition, crops such as bermuda have high crop water consump
tion values during months when crops such as sorghum or cotton
have yet to germinate or have matured to the stage when
irrigation is detrimental to crop yields.
3, An inverse relationship exists between ETp rates and design
hydraulic loading rates when crops with low to intermediate
demands for nitrogen are considered in arid regions.
4. Hydraulic loading rates will be dictated by the more conserva
tive LwN value when moderate to low nitrogen-using crops are
incorporated into the design; consequently, except when high
nitrogen-using crops are planned, variations in ETp estimates
are of little significance. 82
83
5. When heavy nitrogen-using plants, such as bermuda, are
planned for the cover crop, calculation of the design hydrau
lic loading rates are governed by the water balance equation
(3-14).
6. Crop selection is by far the single most important change-
effecting factor with regard to hydraulic loading rates,
when the goal is maximization of loading rates without
nitrate contamination of the aquifer below.
7. The initial cost for land aquisition and construction could
vary by more than 300 percent when comparing cotton-produc
ing land treatment sites to sites planted in bermuda/wheat
combination.
8. In the planning stages of slow rate land application systems
in arid climates, the problems associated with crop selec
tion are inherently more critical than problems stemming
from choice of ETp estimating methods.
Recommendations
1. Selection of a method most suitable for estimating ETp rates
at the site should be made. To determine accuracy and reli
ability of the chosen ETp estimation method, actual measurement
of crop water consumption at the site should be compared to
calculated ETp rates. Pertinent meteorological data should
be collected at the site if possible.
2. Few data are available concerning the response of crops to
"unlimited" water and nitrogen. Studies should be done to
determine the upper limit of wastewater application with
84
regard to sustained crop yields.
3. An investigation of crop economics should be made including
demand, market stability, and transportation of crops suited
to this area to determine the economic feasibility of empha
sizing crop production over wastewater treatment objectives.
4. Advantage should be taken of the opportunity to test the
nitrogen and hydraulic loading capabilities of the site under
various crop programs.
5. Effects of continual application of primary treated water
with regard to long term treatment performance of the test
site should be studied.
6. Performance data of the land treatment site should be pub
lished periodically so that adjustments in design can be
made retrospectively when compared to treatment objectives.
LITERATURE CITED
1. Berg, G. 1965, Transmission of Viruses by the Water Route, Wiley, New York. 165p.
2. Biology Today. 1972, CMR Books, Del Mar, Cal, 1020p.
3. Blaney, H, F, and Hanson, E. G, 1965. "Consumptive Use and Water Requirements in NewMe:xico", Technical Report, New Mexico State Engineer, 32, p 23-27,
4. Bouwer, H., et al. 1978. "Land Treatment of Wastewater in Today's Society", Civil Engineering - ASCE, 48:1, p 78-81,
5. Brar, N., et al, 1978, "Some Factors Affecting Denitrification in Soils Irrigated with Wastewater", Jour, Water Poll. Control Fed,, 50:4, p 709-717,
6. Christiansen, J. E, 1968, "Pan Evaporation and Evapotranspiration frora Climatic Data", J. Irrig. and Drain, Div., Am. Soc. Civ. Engr,, 94. June, p 243-263,
7. Crites, R. W. and Pound, C, E. 1976. "Land Treatment of Municipal Wastewater". Environ, Science & Technology, 10:6. p 548-551,
8. Doorenbos, J, and Pruitt, W. 0, 1977. "Guidelines for Predicting Crop Water Requirements". Food & Agric. Org, of the United Nations, Rome, 144p,
9. Elliot, L, F. and Ellis, J, R, 1977, "Bacterial and Viral Pathogens Associated with Land Application of Organic Wastes". J, Environ, Qual., 6:3. p 245-250,
10. Environmental Protection Agency, 1981. Process Design Manual for Land Treatment of Municipal Wastewater. U.S. Army Corps of Engineers, U.S. Dent, of Interior, U.S, Dept. of Agriculture, EPA 625/1-81-013. EPA Technology Transfer, Washington, D.C.
11 Gilde, L. D., et al. 1971, "A Spray Irrigation Systera for Treatment of Cannery Wastes", J. Water Poll, Control Fed., 43:10. p 2011-2025.
12. Gray, F. 1981. 3509 96th Street, Lubbock, Tx. Personal communication.
85
86
13. Haith, D. A., et al. 1977, "Preliminary Design of Wastewater Land Application Systems". J. Water Poll. Control Fed., 49:12. p. 2371-2379.
14. Hammer, M. J. 1972. Water and Wastewater Technology. John Wiley & Sons, Inc., New York. 502p.
15. Hargreaves, G, H, 1968, "Consumptive Use Derived from Evaporation Pan Data", J, Irrig, & Drain, Div., Am, Soc, Civ, Engr,, 84, March, p 97-105.
16. Hart, R. H. 1974. "Crop Selection and Management", p 178-200. In: Factors Involved in Land Application of Agricultural and Municipal Wastes! (DRAFT) ARS USDA, Beltsville, Md. 200p.
17. Hillel, D. 1971. Soil and Water: Physical Principles and Processes. Academic Press, New York. 288p.
18. Hinesly, T. D, 1973, "Water Renovation for Unrestricted Reuse", Water Spectrum, 5:2, p 1-8,
19. Jawetz, et al. 1978. Review of Medical Microbiology. Lange Medical Publications, Los Altos, Calif. 55Cp,
20. Jensen, M, E. 1974, Consumptive Use of Water and Irrigation Water Requirements, American Society of Civil Engineers. 215p.
21. Jensen, M, E. and Haise, H. R. 1963. "Estimating Evapotranspiration from Solar Radiation", J. Irrig, & Drain. Div., Am. Soc. Civ, Engr., 89, December, p 15-41.
22. Kao, C. W. and Blanchard, R. W. 1973, "Distribution and Chemistry of Phosphorus in an Albaqualf Soil After 82 Years of Phosphate Fertilization", J, Environ. Dual,, 2, p 237-240.
23. Kardos, L. T. and Hook, J. E. 1976, "Phosphorus Balance in Sewage Effluent Treated Soils", J, Environ, Qual., 5:1. p 87-90,
24. Krieg, D. 1982. Texas Tech University, Dept of Plant and Soil Science. Personal Communication.
25 Lance, J, C. 1972, "Nitrogen Removal by Soil Mechanisms". ih_ Water Poll, Control Fed., 44:7. p 134-136.
26, LCCIWR. 1981. 11th Quarterly Report, July 1 - Oct. 15. Lubbock Christian College Institute of Water Research,
87
27. Loehr, R. C , et al. 1979, Land Application of Wastes. 2 Vols. Van Nostrand Reinhold Environmental Series, New York. 431 p.
28. Metcalf & Eddy, Inc. 1972. Wastewater Engineering: Collection, Treatment. Disposal, McGraw-Hill, New York, 456p,
29. Metcalf & Eddy, Inc, 1977. Process Design Manual for Land Treatment of Municipal Wastewater. U,S, EPA, U.S, Army Corps of Engineers, U,S. Dept of Agriculture, EPA 625/1-77-008, EPA Technology Transfer, Washington, D,C.
30. Metcalf & Eddy, Inc. 1979. Wastewater Engineering: Treatment, Disposal, Reuse. McGraw-Hill, New York, 476p,
31. Murray, F, W, 1967, "On the Computation of Saturation Vapor Pressure", J. Applied Meteor,, 6:2, p 203-204,
32. Page, A, L. 1974, Fate and Effects of Trace Elements in Sewage Sludge when Applied to Agricultural Lands. A Literature Review Study, U.S, EPA 670/2-74-005. Washington, D.C,
33. Penman, H, L, 1948. "Natural Evaporation for Open Water, Bare Soil, and Grass"."Troc, Roy, Soc, London, A193, p 120-146.
34. Penman, H. L. 1956. "Evaporation: An Introductory Survey". Neth, J. Agr. Sci., 4. p 9-29,
35. Peterson, M., et al, 1973, A Guide to Planning and Designing Effluent Irrigation Disposal Systems in Missouri. Univ. Mo. Ext, Div, NP 337 3/73/1250.
36. Pound, C. E. and Crites, R. W. 1973, Wastewater Treatment and Reuse by Land Application, Vol II. Office of Research and Development, EPA-660-2-73-C06B, Washington, D.C, 249p,
37. Pound, C. E., et al. 1978. "Land Treatment: Present Status, Future Prospects:". Civil Engineering - ASCE, 48:6. p 98-102.
38. Pruitt, W. 0. 1960, "Large Weighing Lysimeter for Measuring Evapotranspiration", Trans, Amer. Soc. Agr. Eng., 3:1. p 3-18.
39. Pruitt, W, 0. and Jensen, M. C. 1955. "Determining when to Irrigate". Agr. Engr., 36:6, p 389-393.
40. Ritchie, J, T. and Burnett, E. 1971, "Dryland Evaoorative Flux in a Subhumid Climate II. Plant Influences". Agron. Jour., 63:1. p 56-72,
88
41. Sidle, R, C ; Hook, J. E.; and Kardos, L, T, 1977. "Accumulation of Heavy Metals in Soils from Extended Wastewater Irrigation", J, Water Poll, Control Fed.. 49:2. p 311-318,
42. Sweazy, R. M.; Ramsey, R, H,, III; and Whetstone, G, A, 1982, "Critical Analysis of Case Histories of Agricultural Reuse Application". Unpublished paper for presentation at workshop on Water Cons, and Reuse in Industry & Agriculture: Research Needs, Kiawah Is., S,C. 3-5 March 1982.
43. Thomas, R. E, 1973, "Land Disposal II: An Overview of Treatment Methods". J, Water Poll, Control Fed., 45:7. p 1476-1483,
44. Uiga, A, and Sletten, R. S, 1978. "An Overview of Land Treatment from Case Studies of Existing Systems", J. Water Poll, Control Fed,, 50:2. p 277-284.
45. Weier, T. E.; Stocking, C. R.; and Barbour, M. G. 1970, Botany. John Wiley & Sons, Inc., New York. 708 p,
46. Wells, D, M.; Sweazy, R. M,; and Whetstone, G. A. 1979. "Long-term Experiences with Effluent Reuse", J, Water Poll, Control Fed,, 51:11. p 2641-2648.
47. Wendt, C. W, 1981. Texas A & M Agriculture and Extension Center, Personal Communication.
APPENDIX A: EXAMPLE CALCULATIONS OF ETp BY THE
FIVE METHODS USED IN THIS STUDY
Source data
Lubbock, Tx. Ju ly , 1973
Lat i tude: 33.6^
Elevat ion: 3254 f t
Meteoroloaical data fo r July 1973
Air temperature °F, °C
Mean max. 85.9°F = 30.1''C
Mean min. 67.6°F = 19.8°C
Mean 77.3°F = 25.2*='C
Saturation vapor pressure, at
86.9°F = 43.7 mb
77.3°F = 31.9 mb
67.6°F = 23.1 mb
Wind speed
Mean day 4.3 m/sec
Mean night 2.26 m/sec
Average wind run per day 232.8 mi = 374.6 km
Relative humidity
Mean max. 72 -
Mean min. 39 ^
Mean 55.5 °^
Percent of possible sunshine hours n/N = .83
Reflectance c o e f f i c i e n t , «< = 0.25
85
90 Blaney-Criddle
ETp = C[P(0.46T + 8)]
Uday = 4.3 m/sec
P = 0.32 (Table 7)
m/N =0.83
P(0.46T + 8) = 6.27
ETp = 8.1 mm/dy (fig. 5 & 6)
Jensen-Haise
ETp =
h-ho "
s =
h-' j -
' H -
^1 =
^ 2 -
' j -
h-h-
C^(T - Tx)Rs
(0.35 + 0.61S)R3Q
759.4 cal cm"
n/N = 0.83
550.3 cal cm'
1
^1 " ^2^H 50mb _ 1
(e^ - e^)
68° F
13°F
.012
'•day ^
•^day-^
.34
27.5°F - 0.25 {e^'i
17.46°
Elevation
(Table 8)
(eq. 3-3)
(eq. 3-^)
ET = .012(77.3 - 17.46)650.3 = 484.9 langleys/day
ETp = 8.32 mm/day
TA&M
Julian day for July 15 = 196
Solar radiation = 607 langleys
ETp = 0.000673 ^ - ^ ^ (Rn) ^ ^ ^ O5.36)(1.0 - O-OV..,-) (is-e,^
^ = 0.069197 EXP(3.1030556 x 10"^ x T ) 91 avg
A = 0.764
R„ = Solar radiat ion {RJR ) " n ns
V ^ n s " 2.02895 E-10(day no.)^ - 1.57 E-7(day no.)^ + 2.9057 E-5
(day no.)^ + 0.0004(day no.) + 0.278855
V ^ s = 0-5
R = 0.752(607)
R = 358.6
^s =!^IBM.l!imil (33.86)
1 , ^^^-[^ - saturation vapor pressure for average daily maximum and minimum monthly temperatures respectively.
^smax = 2.4493 E.6(T^^^)2 - 0.000114(T^^^)2 . 0.00611(T^^^) .
0.0026114
e.„,-p, = substitute T„. for T^^^ in e^^^^ equation smm m m max smax
i^ = ^-^Q ^ : ^ (33.86)
i^ = 33.5
ej = e (maximum monthly relative humidity) + e.^. (minimum d smax smin monthly relative humidity) (.005)
^d = ^^-5
ETp = .323in/day = 8.29 mm/day
Penman
Average temperature = 77.3°F
Average relative humidity (R^avg' ^ ' °'
Maximum relative humidity (R^max^ ' ''''
n/N = .83
Uj /U . u^ = 1-9 day^ night
e, = 31.9mb a
92
^d = ^a(f^Havg) = ^^'^mb
U = 374.6 km/day (a 4m; U = 329.6 km/day 0 2m
f, = 1.02
R. = (0 .25 + 0.50 n/M)R o a
Rg = 16.8 mm/day (Table 11)
R3 = 11.17
^ns " ^ • -25)11.17 = 8.38
^n l " ^ ^ ^ d ^ * ^^^°^^ * ^^^^^^^ (Tables 12, 13 & 14)
^ n l " ^^^••^ * ^ '^^^ * ^-^^^
^n l = 2.00
R = 8 .38 - 2.00 = 6.38 n
(1 - I'i) = 0.24 (Table 9)
W = 0.77 (Table 10)
C = 1.03 (Table 15}
ETp = C[W * R^ + (1-W) * f u * (ea - ed ) ]
ETp = 8.6 mm/day
Pan e v a p o r a t i o n
Pan data f rom Texas A&M U n i v e r s i t y A g r i c u l t u r e Research and Ex ten
s i on Cen te r . Data f o r 1973 no t a v a i l a b l e .
For J u l y 1977
.41 i n = 1.04 cm
wind range moderate
Rn average or medium
93 Pan coefficient .75 (Table 16)
ETp = .31 in/day = 7.8 mm/day
APPENDIX B: DETERMINATION OF DESIGN HYDRAULIC
LOADING RATES (LwD), FIELD AREA (Aw). AND STORAGE Volume (VS)
LwD
Determination of design hydraulic loading rates (LwD) for corn
using the Jensen-Haise method for estimating potential evapotranspira
tion. Design precipitation (Pr) for each month based on a 5 year
return frequency analysis for monthly precipitation. (Figs. 14-18)
Estimation of ET crop
1. Using the ETp during the initial stage (the month planting
normally occurs in area) find the corresponding kc value from
fig. 8,
Eg. Crop - corn
Planting date - April 15
ETp Jensen-Haise, April =5.3 mm/day
kc initial =0,44
2. Following seasonal development stages in Table 17, plot kc
values for each stage (Table 4) against the time span for
each stage (Fig. 10). Since time span did not correspond
evenly to monthly periods, monthly kc values were calculated
as a percentage of area under curve.
3. ET , cm/July = kc July • ETp July(.J-H) • 31 (no. of ice-
free days per month)
Percolation rate Pw = 29,26 cm/rao (eq. 3-13)
LwD cm/mo = ET^^^ - Pr + Pw (eq. 3-12)
LWN = ^P(P^ - ^^crop) ' ^^^Q) (eq. 3-U) 1-f (Cn) - Cp
94
Example calculations of LwD
Crop - corn
^^crop ^^^^^^ ' Jensen-Haise
95
Month
Apr
May
Jun
Jul
Aug
Pr-ET cm
- 2,10
- 0,14
-13.70
-19.94
-10.65
U kg/ha
14
22
51
62
41
LwN cm/mo eq, 3-14
11.0
20,2
34.5
38,9
28.1
LwP cm/mo eq. 3-12
31,4
29.4
42.9
49,2
39.9
LwD c:n/mo
11,0
20.2
34.5
38.9
28,1
190 132.7 192.8 132.7
Field area required (Aw), ha
Q 365 d/yr + Vs Aw =
(lc4m2/ha)(LwD)(10-2m/cm) 3
Q = Average daily flow = 28387.6 m /day
LwD = 132.7 cm/yr
Vs*= Storage volume
Aw = 781 ha
3 Storage volume required (Vs), m
Aw = 781 ha
Vs = (77.5 cm)(781 ha)(lo'^ m2/ha)(10"2m/cm)
Vs = 6,05 * 10^ m3
Storage area. As, m2 = ^^^ ; depth was selected as 4 m
As = 1.51 * 10^ m2
96
Vs = (Pr - Evaporation - seepage) As(10"^ m/cm)
seepage = assumed 0
Pr = 76,6 cm/yr
Evaporation = 72 in/yr = 183 cm/yr
- Vs = (106 cm/yr) As(10"^ m/cm)
^ Vs = 1.60 * 10^ m^/yr
Field Area with Storage Adjustment (cm)
(1)
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Aw' =
Aw' =
LwD
660
(2)
LwD
-
-
-
-
-
-
11.0
20.2
34.5
38.9
28.1
^
132.7
Q 365 - Vs
(10^ m2/ha)(10-
ha
(3) Available wastewater
11.1
11.1
132.7
'2m/cm)
(3) - (2) Change in storage
1 1 • 1
11.1
1 1 • 1
11.1
1 1 • 1
1 1 « 1
- 0.1
- 9.1
-23.4
-27.8
-17.0
11,1
Cumulative storage
11,1
22.1
33.2
44.2
55.3
66.3
77.4
*77.5
68.4
45.0
17.2
0
97 Final Storage Volume Requirement
m- * 10^
( ) (2) (3) (4)
Vs Qm Vw Net Available Applied
Month Gain/Loss wastewater wastewater
Oct - 1.0 8.63
Nov - 0.93
Dec - 0.39
Jan - 0.27
Feb - 0.38
Mar - 1.0
Apr - 1.8 " 7.26
May - 1.9 " 13.3
Jun - 2.8 " 22.8
Jul - 2.5 " 25.7
Aug - 2.2 " 18.5
Sep - 0.91
Qm = Qday (365 d/yr)/12 mo/yr ^ 0
*Maximum storage volume for the year is approximately 5.56 * 10'm^
in April.
(5)
= 2 + 3 - 4 Change in storage
7.6
7 .7
8.2
8 .4
8.3
7.7
- n.4
- 6.6
-16.9
-19.5
-12.1
7.7
(6)
Cum. storage
7.7
15.3
23.0
31.2
39.6
47.9
*55.6
55.2
48.6
31.7
12.2
0
Recommended