SEQUENCES IN SIZING LARGE SCALE LAND APPLICATION SYSTEMS

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


Land Area (Aw) 72

Storage Area and Volume 73

iv

Influence of Different Crops 73


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


for different daytime wind velocities and medium



for different daytime wind velocities and low


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


for Sept., Oct 59


for Aug., Dec 60

14. Frequency analysis of monthly precipitation •

for Feb., Mar., May 61


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 = Î^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

 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 

M-o

O) s.

o

• o

• r -

s-cn

< o23

-a o o

Li-

• to

-(-> c 8 T3

LU

5

41

I -

3. U daytime = 5 - 8 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


2. U dayt-

3 4 5 6 7 f = p(0.46 + 8)

8 9


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



1, U daytime = 0 - 2 m/sec

3 4 5 6 7 f = p(0,46 + 8)

8 9


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— - r —

• as LU C

LU

(U CJ to

> ••->

, , 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



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

 +-> 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 Rî 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^ 

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 •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 

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

 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 

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 + 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 

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 , 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^ CTî—

--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 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 "â-

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~ s 4-> •r-

to s. 

• 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- +-> o

C_)

E 3

. E cn s-o

m

4->

ro cu

CQ

«S

C7 cu

•r—

S-:>

ft ft

LU C_> ca l U o oo

2 4-> 03 OJ

- E 2 S-| *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

 cu

-o a. o s-LJ

r— ea

•f—

+-> • 1 —

E •r—

S-

o 4 -

 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 - 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 

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 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

E 03 E E CU

E Ou 03

E E - O CU o o. z:

cu E e:L o

cu > cu

• o

O

o

I— CM r o 03

en

cd 0 0

X LO

A.

I — CM CO

'

cn 4->

S-

as

to cu cn 03

to

E CU

I— i -3 0)

O 4 -

03

E S-O

u

o (U

>

3 cr cu

ca

s. O)

4-> 03

O L O S-

C_3

cn E

4J U

•r -"O

 3 •(->

•« E

• , - OJ 3 XZ

<+ -oO O

o cn

to o • -Q O E - r -Qi S. i - Oil o «a: o

Q oe5 •a

•• o LU O C_> Lu

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»-

CU o LJ

CL o s-

o

. 0 0

. as

•r— Lu

1 Q)

ca s-Qi •M OJ

~ g

CL o s.

o cn E

• r -

+J a

• r -

cu s-o.

• S- CL O ' ^

*+ - ^ —

to cu E •

• 1 - Qi -— E CU o

-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 - •

Q_ cn s-

oB O

. . •-D CJ

•r—

to c r O <C

Xi E oB 0) S- T 3 O O O O

SO

UR

CE

: D

q

uir

em

en

ts",

F

0)\ * : ;U9LDL^^90D dOUQ

55

I 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


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


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

"ôrahum

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

oo o CJ

o •r— - M fO

to - M • ^

CD E •p—

S-

^

• o E 03

_ J

r )

03 - O - E 

Q::

o • ^ p —

3 OJ s-

-a

L. >>

E u 1

a; 4-> 03 ca O)

>» c az • I —

-o 03 O

0 0 0 0

oo ISi

CO 00

ro CM

CD LO

CO LO LO VO LO VO

O CM co LO

Id

' d - ^ LT) LD VO VO VO LO VO

C ^ ^

«3- o^ O^ O^ O^ O^ 0 0

vo vo vo LO vo . . • . »

0 0 0 0 CO CO CO

r— r— CM f— O

LO LO LO Lfi LO

CM CO CM CM CM

r . r^ r«K r^ p^

*3-ft

CO

r^ •

ro

cn •

vo

^J-t

CO

CO <

LO

p— <:r ,— CM o

r o CO CO CO CM o

i LO CM

LO CM

CO «

LO CM

LO CM

CM CM

OS LO LO r^ v o LO

r o p— «:;3-CO LO LO 0 0 VO r^

CO ^r LO

o vo vo

0 0 «:r vo

CM LO vo

CO C3 LO

<— CO C^ LO CM CM

CM f O ^ r^ CO o CM CM I—

CO p— cn cn ^ '^ »— ^;r

LO CM

LO CO

CO CO

0 0 C^J CO

0 0 CT^ CO r ^ LO LO v o

cn vo

OQ

OJ to

ZD S-

SZ a 03 C D J E O " ^

4-> . ^

o xz

O J - M

o C_J

cu

LU

o LO

O O O

03 Qi

E 03

s: E CJ 3 : oo E

I 1 < : o

CJ

L J 1

CQ

I

1 • ^

t oC < h -

E (a 1= E O

Q_

C 03 a.

"K -fa*)-

tnvo o o

CJ 1—

vo

CO

ro LO

CO

as LO

CO

«!j-

00

vo o CO

r>. CM

' ^

vo CM

' d -

ro

'?r

vo CM

«a-

co ro

«;^

LO LO

CM-

O LO

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81

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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 =!ÎBM.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 (Râvg' ^ ' °'

Maximum relative humidity (R^max^ ' ''''

n/N = .83

Uj /U . u^ = 1-9 day^ night

e, = 31.9mb a

92

^d = â(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

Documents

SEQUENCES IN SIZING LARGE SCALE LAND APPLICATION SYSTEMS