311 /4&1

jNO< 7 9 7.S**

CONCEPTION AND DESIGN OF CONSTRUCTED WETLAND SYSTEMS

TO TREAT WASTEWATER AT THE BIOSPHERE 2 CENTER WITH USE

OF REACTION RATE MODELS AND THE HABITAT EVALUATION

PROCEDURE TO DETERMINE THE EFFECTS OF DESIGNING

FOR WILDLIFE HABITAT ON TREATMENT EFFICIENCY

THESIS

Presented to the Graduate Council of the

University of North Texas in Partial

Fulfillment of the Requirements

For the Degree of

MASTER OF SCIENCE

By

Glenn C. Clingenpeel, A.A., B.A., B.S.

Denton, TX

May, 1998

Clingenpeel, Glenn C , Conception and design of constructed wetland systems to treat

wastewater at the Biosphere 2 Center with use of reaction rate models and the habitat

evaluation procedure to determine the effects of designing for wildlife habitat on treatment

efficiency. Master of Science (Environmental Sciences), May, 1998, 261 pp., 33 tables, 31

figures, 4 appendices, references, 44 titles.

A study was undertaken to explore relationships between wetland characteristics which

make them efficient water purifiers versus their ability to serve as wildlife habitat. The

effects of designing constructed wetlands for improved habitat on water treatment

efficiencies were quantified. Results indicate that some sacrifice in treatment efficiency is

required and that the degree of efficiency reduction is dependant upon pollutant loading

rates. However, sacrifice in efficiency is much smaller than increase in habitat quality, and

can be offset by increasing wetland area. A practical, theoretical application was then

attempted.

311 /4&1

jNO< 7 9 7.S**

CONCEPTION AND DESIGN OF CONSTRUCTED WETLAND SYSTEMS

TO TREAT WASTEWATER AT THE BIOSPHERE 2 CENTER WITH USE

OF REACTION RATE MODELS AND THE HABITAT EVALUATION

PROCEDURE TO DETERMINE THE EFFECTS OF DESIGNING

FOR WILDLIFE HABITAT ON TREATMENT EFFICIENCY

THESIS

Presented to the Graduate Council of the

University of North Texas in Partial

Fulfillment of the Requirements

For the Degree of

MASTER OF SCIENCE

By

Glenn C. Clingenpeel, A.A., B.A., B.S.

Denton, TX

May, 1998

TABLE OF CONTENTS

Page

LIST OF TABLES vi

LIST OF FIGURES viii

Chapter

I. INTRODUCTION 1

II. LITERATURE CITED 7

Types of Constructed Wetlands Overview and Contrasts Treatment Efficiencies Hydrophyte Considerations Wildlife Habitat Production Design Considerations Habitat Evaluation with HSI Models Permits and Regulations

III. METHODOLOGY 37

Wastewater Characterization Design Tools Reaction Rate Equation Hydrology Water Budget/Mass Balance HSI Models Pre-Treatment Components Designing the Treatment System Designing the Habitat System Modeling Flow Through Wetland Designs Water Quality Modeling Designing the Hybrid System

iii

Page K t o and K b o d Calibration

IV. PRESENTATION AND DISCUSSION OF RESULTS 73

Treatment, Habitat, Hybrid Systems The Treatment System The Habitat Systems Water Quality Modeling Habitat Unit Determination Discussion of Limiting Factors The Hybrid System Testing The Hybrid The Biosphere 2 Center Constructed Wetlands SSF Sizing Treatment Goals Infrastructure Development Wetland Design Flow Modeling Water Quality Modeling Habitat Quality Determination: Computation of SI Scores and HUs

V. SUMMARY 133

APPENDICES

APPENDIX A 140

APPENDIX B 148

American Coot Great Egret Marsh Wren Muskrat Red-winged Blackbird Yellow-headed Blackbird

APPENDIX C 165

Treatment Wetland System Habitat Wetland Systems Hybrid Wetland System

APPENDIX D 236

Treatment, Habitat, Hybrid Wetland Systems

iv

Page

REFERENCES 138

LIST OF TABLES

Page

Table 1: Gross Removal Efficiency Averages for 94 Treatment

Wetlands 12

Table 2: Performance Summary of Constructed Wetlands in the US 12

Table 3: Commonly Used Plants in Wastewater Treatment 16

Table 4: Performance of Planted versus Unplanted SSF Systems 16

Table 5: Root Depth Penetration in SSF Wetlands 19

Table 6: Bird Counts from Incline Village, NV and Show Low, AZ Constructed Wetlands 21

Table 7: Wetland Birds of North America Known to Visit or Inhabit Southern Arizona, Constructed Wetlands and the Food Preferences of these Waterfowl 24

Table 8: Applicable Permits 34

Table 9: 1997 Visitor Counts, Estimated Future Visitor Counts And Estimated

Wastewater Production 41

Table 10: Reaction Rate Constants (k) 45

Table 11: Temperature Coefficients 47

Table 12: Monthly Evaporation, Evapotranspiration and Precipitation

Rates for the Biosphere 2 Center 52

Table 13: Preliminary SSF Sizing 55

Table 14: SSF Component Calculations: FC, TN, TDS and BOD 56

Table 15: Preliminary FWS Sizing 76

vi

Page

Table 16: HSI Model Variables 79

Table 17: HSI Model Variable Maximization 80

Table 18: HEP Summary for Habitat and Treatment Systems 90

Table 19: Water Quality Summary for Hybrid System 94

Table 20: HEP Summary for the Hybrid System 95

Table 21: Comparison of Habitat Quality and Treatment Efficiency in the Habitat,

Treatment and Hybrid Systems 101

Table 22: B2C SSF Physical Parameters 104

Table 23: Determination of Required Medium Conductivity 106

Table 24: Monthly Water Budget, 20kpgd, Cells A and B 114

Table 25: Monthly Water Budget, 1 Okgpd, Cells A and B 115

Table 26: Monthly Water Budget, 30kgpd, Cells A and B 116

Table 27: Monthly Water Budget, 40kgpd, Cells A and B 117

Table 28: Monthly Water Budget, lOkpgd, Cell B Only 121

Table 29: Monthly Water Budget, 20kgpd, Cell B Only 122

Table 30: Monthly Water Budget, 3Okgpd, Cell B Only 123

Table 31: TN Reduction in B2C Wetlands with Variable Flow and Wetland Area ... 130

Table 32: HSI Model Summary for B2C Wetlands 131

Table 33: KTO and KBOD Calibration Summary 140

vu

LIST OF FIGURES

Page

Figure 1: SSF Constructed Wetland 9

Figure 2: FWS Constructed Wetland 9

Figure 3: Guild Development for HSI Species Selection 29

Figure 4: Pre-Treatment System 57

Figure 5: Flow in Expanding Channels 63

Figure 6: Flow in Narrowing Channels 65

Figure 7: Flow Around Islands 66

Figure 8: KTO 5 Number Summary 69

Figure 9: KBOD 5 Number Summary 70

Figure 10: Treatment System Basic Spreadsheet Design 77

Figure 11: Mean Peak Flow Through Treatment System 78

Figure 12: Habitat System I, Basic Spreadsheet Design 81

Figure 13: Habitat System II, Basic Spreadsheet Design 82

Figure 14: Habitat System III, Basic Spreadsheet Design 83

Figure 15: Mean Peak Flow Through Habitat System 1 85

Figure 16: Mean Peak Flow Through Habitat System II 86

Figure 17: Mean Peak Flow Through Habitat System III 87

Vlll

Page

Figure 18: Estimated TN Removal Efficiencies in Treatment and Habitat Systems... 88

Figure 19: Hybrid System Basic Design in Spreadsheet Format 93

Figure 20: Mean Peak Flow Through Hybrid System 94

Figure 21:5 Number Summary for TN Removal in Habitat, Treatment and Hybrid Systems 97

Figure 22: 5 Number Summary for BOD Removal in Habitat, Treatment and Hybrid Systems 98

Figure 23: Comparison of Total SI Scores for Habitat, Treatment and Hybrid

Systems 100

Figure 24: B2C SSF Wetland Cells 105

Figure 25: Topographic Map of Lower B2C Campus 110

Figure 26: Topographic Map of Upper B2C Campus 111

Figure 27: Diagram of Biosphere 2 Center Constructed Wetlands 119

Figure 28: Cross-Section of Wetland Cells 120

Figure 29: Water Conservation Soil 125

Figure 30: B2C Wetland in Spreadsheet Format 127

Figure 31: Mean Peak Flow Through the B2C Wetlands 128

IX

CHAPTER I

INTRODUCTION

Within the past ten years the number of constructed wetlands in use to treat wastewater

has grown at a rapid pace. In 1991 the Environmental Protection Agency 's (EPA) Risk

Reduction Engineering Laboratory (RREL) identified 60 constructed wetlands being

operated by communities in the United States for this purpose (Brown and Reed, 1994).

In 1994, only three years later, the RREL released its North American Wetlands for Water

Quality Treatment Database (U.S. EPA, 1994) in which it identified over 200 natural and

constructed wetlands engineered to treat wastewater.

There are several reasons for the popularity of constructed wetlands (a term which

describes any wetland built for the purpose of water quality improvement). The first and

perhaps single greatest driving force behind their popularity, is the fact that these systems

are relatively inexpensive to build. Furthermore once in operation constructed wetlands

require little maintenance and, contrary to conventional treatment plants, do not require

highly trained, expensive personnel (Moos, 1993). The cost competitiveness of these

systems has grown in importance as federal grant money for wastewater treatment has

become scarce and responsibility for paying has shifted to states and small municipalities

who can least afford to pay for them (Smith, 1989). Accordingly, a growing number of

1

municipalities are opting to implement constructed wetlands. Although the majority of

systems in operation are designed to treat municipal or residential wastewater,

technological advances are now making it possible to use constructed wetlands in the

treatment of industrial and agricultural wastewater. There are also a number of ancillary

benefits associated with these systems which have helped to increase their popularity.

These additional benefits include the facts that they are aesthetically pleasing and produce

wildlife habitat.

One organization currently considering the implementation of a constructed wetland is

the Biosphere 2 Center (B2C) in Oracle, Arizona. The Biosphere 2 project began in the

late 1980's with the design and construction of a three acre, completely materially closed

structure. This building, known as Biosphere 2, was to contain a self-sustaining

"biosphere" complete with five different ecosystems. The apparatus with its associated

biomes was designed to provide the life support functions necessary for a crew of up to

ten. In September of 1991, the first of two enclosure missions began when eight people,

known as "Biospherians" were sealed inside the giant glass and steel structure for two

years. During this mission they were to receive only energy from the outside. Food,

oxygen, nutrients, and other requirements would be produced and recycled within.

Although no more enclosure missions are currently taking place or are planned for the

near fixture, the Biosphere 2 project continues. In January of 1996, Columbia University

took over stewardship of the project (now called the Biosphere 2 Center to include not

only the Biosphere 2 structure itself, but everything associated with the 200 acre facility).

Bill Harris, executive director of the B2C, aspires to make the center a world leader in

earth science and environmental education, as well as a Mecca for ecotourism (Bill Harris,

personal communication). Pursuant to these goals, the B2C has been expanded, complete

with on site housing for students enrolled in the B2C's college curriculum. The B2C also

has a 38 room hotel, swimming pool and restaurant. Approximately 150,000 visitors

frequent the B2C annually, spending anywhere from one to five hours on site. Plans call to

double this number to 300,000 visitors per year within the next couple of years, as well as

increasing student enrollment. These plans will necessitate expanding or replacing the

B2C's present wastewater treatment capabilities. Currently, wastewater is collected in

septic tanks and is then discharged to subsurface drainage field. There are a total of 17

septic systems with an associated 20 septic tanks currently in use, receiving an estimated

daily flow of 12, 250 gallons. Projected increases in the resident student population

coupled with efforts to increase visitor counts, are projected to increase this flow to more

than 20,000 gallons per day within the next five years. As a result, the Biosphere 2 Center

would be required to obtain an individual permit from the Arizona Department of

Environmental Quality (ADEQ). This would necessitate the construction of a wastewater

treatment plant at the site.

A constructed wetland should be seen as an excellent treatment option for the B2C in

that such a system could provide an efficacious, cost effective treatment mechanism to

deal with future wastewater treatment demands while remaining consistent with the

project's environmentally conscious philosophy. In order for the B2C to realize the

maximum potentials of a constructed wetland however, the system would have to be

designed in such a manner as to optimize its value as wildlife habitat. A visually attractive

wetland supporting an abundance of wildlife would provide a variety of benefits which

could help the B2C realize its goals of becoming a leader in environmental education and

ecotourism.

In most cases the use of constructed wetlands by wildlife is considered ancillary or

even accidental. The appearance of high quality wildlife habitat, however does not arise

passively. Considerations for the development and maintenance of such habitat must be

implicit in every aspect of the design phase and must be managed throughout the life of

the project. This raises an important question; will constructed wetlands for municipal

wastewater treatment designed to produce high quality wildlife habitat operate as

efficiently as similar systems designed only for water quality improvement? In other

words, does designing for wildlife habitat production decrease treatment efficiencies, and

if so, by how much? Furthermore, although specific design models exist for maximizing

treatment efficiency (i.e., pollutant reduction per unit area) within a constructed wetland

system, such tools do not consider the value of any wildlife habitat produced, Given a

design tool for wildlife habitat production, it should be possible to design a constructed

wetland which has both high water treatment efficiency and wildlife habitat value. The

primary purpose of this research was to test this hypothesis by using the US Fish and

Wildlife Service's Habitat Evaluation Procedure (HEP) with specific Habitat Suitability

Index (HSI) models as an habitat design tool.

Three constructed wetland types were designed for the B2C's wastewater. The first of

these systems, hereafter referred to as the "treatment system," was designed to treat

wastewater as efficiently as possible. Wildlife habitat production was not considered

during the design phase of this system. The second system type, the "habitat systems,"

5

focused on wildlife habitat production only, with no consideration of treatment efficiency.

These two system types were then compared in terms of their treatment efficiencies and

value of wildlife habitat. The third system, the "hybrid system," was a combination of the

first two and offers both high treatment efficiency and high quality wildlife habitat. It was

designed after the first two systems had been fully evaluated in order to minimize limiting

treatment efficiency and wildlife habitat factors.

A second objective of this research was to produce a viable constructed wetland design

for implementation at the B2C in compliance with all relevant permits and regulations.

This system, like the hybrid system, was designed for dual functions of providing high

quality wildlife habitat and high efficiency water treatment. This design can serve as a

meaningful example, lacking in the literature, of the processes and considerations involved

in designing a constructed wetland system when both water quality and habitat quality are

desired. It also serves to demonstrate how lessons learned in testing of the research

hypothesis can be applied to an actual constructed wetland design.

In Chapter II of this thesis there is a general discussion of constructed wetlands

including treatment efficiencies, major processes by which treatment occurs, and the role

of aquatic macrophytes in these systems. Some of the problems associated with

constructed wetlands will be discussed. This chapter will also briefly describe the Habitat

Evaluation Procedure and HSI model species selection. Finally, this chapter discuses state

and federal permits and regulations which must be considered when designing a

constructed wetland for use in Arizona.

Chapter III, the methodology section, will discuss in detail how each of the three

systems were designed and how the different models were applied to each. These models

6

resulted in numeric scores being awarded to each system for treatment efficiency and

wildlife habitat value. Design tools and models are described in detail. These models

include reaction rate models for determination of pollution reduction, along with

hydrologic equations for predicting flow rates and mass-balance equations to examine

effects of evapotranspiration and precipitation on flow and water quality. A mass-balance

equation was also used to predict the amount of make up water the B2C Wetlands would

require during periods of low waste-stream flow and or high evapotranspiration rates.

Results are discussed in Chapter IV. The Habitat Evaluation Procedure was applied to

each system as were reaction rate models to determine habitat quality and treatment

efficiency respectively. The results were used to test the habitat/efficiency hypothesis

which was not rejected. Chapter V summarizes the findings of this research and discusses

how they can be applied to future constructed wetlands.

CHAPTER II

LITERATURE REVIEW

In order to design an effective constructed wetland treatment system, it is necessary to

consider available treatment options, the efficiencies of these different options and thus

their ability to meet treatment goals and finally a treatment option's ability to provide

other important services such as wildlife habitat, education and research opportunities.

The purpose of this section is to discuss and summarize the considerable information

present in the literature concerning constructed wetlands used to treat wastewater.

Information is also presented on permit requirements and common problems, real and

imagined, associated with constructed wetlands. The information presented in this section

was used in the design phase of this project to customize and optimize the B2C Wetlands'

ability to fulfill the special needs of the B2C. This section also develops the cover and

feeding guilds associated with the HEP process.

Types of Constructed Wetlands

There exist a variety of natural treatments for wastewater and water pollution control

(Dinge, 1982). Constructed wetlands have become one of the more popular of these

8

"natural" technologies, with the use of these systems expected to increase (Brown and

Reed, 1994).

There are two major genres of constructed wetlands in use today. The first type fall

into the category of subsurface flow systems (SSF). Figure 1 illustrates the basic

components of a SSF constructed wetland. These systems are simply depressions filled

with a porous medium. Wastewater is introduced at one end and allowed to percolate

through the medium with the water level maintained below the surface. During this

process many of the pollutants present in the water are removed. SSF wetlands have been

used extensively in many European countries (Brix and Schierup, 1989) under the name

of "gravel bed" or "reed bed" systems. Although gravel is the most common medium used

in these systems, a variety of other substances have been used including various types of

soils and sand.

The second type of constructed wetlands are the free water surface (FWS) systems.

FWS constructed wetlands are again simple depression, usually rectangular in shape and

usually having a low permeable layer as their base. The depression is then planted with

aquatic macrophytes and water is introduced. The water slowly flows through the

depression and is discharged at the opposite end. Figure 2 details the major components of

a FWS system.

The primary advantage of SSF wetlands is that they require less land to treat the same

amount of water as a FWS system. This is seen in the fact that hydraulic loading rates for

FWS systems are typically between 0.7 to 5.0 cm/d, while SSF systems range from 2 to 20

cm/d (Kadlec and Knight, 1995). A second advantage realized with SSF systems is that

Influent pipe

Low Permeability Liner (Layer)

Emergent Macrophytes Transpiration

Hydraulic

Rhizosphere

Porous Filter Medium

ZZZZZZ rf Effluent Pipe

Substrate; Moderate K Permeability

Figure 1. Major components of a subsurface flow constructed wetland cell.

Influent Pipe

Hydraulic

Low Permeability V . / Liner (Layer) /

Transpiration

Evaporation

Water Surface

Effluent Pipe

Substrate Rhizosphere Anaerobic Zone

Figure 2. Major components of a free water surface constructed wetland cell (FWS)

10

wastewater remains below the surface of the treatment medium. This reduces odors,

mosquito problems and the possibility of contact between people or wildlife and

potentially dangerous pathogens. Drawbacks associated with these systems include their

price (purchase of the porous medium often accounts for a considerable amount of the

construction price) and the fact that they provide few if any benefits for wildlife. Another

potential problem with SSF systems is their propensity to clog over time. Considering that

rhizomes and root growth can occupy a large volume of the void spaces, void blockage

accrual has been estimated to be up to 10 percent per year (Kadlec and Knight, 1995).

Clogging rates depend primarily upon the porosity of the medium being used and the

amount of particulate matter being introduced to the system. When dealing with

wastewater containing a large amount of suspended solids, pretreatment is necessary to

prolong the operational life of these systems.

The advantages of FWS systems lie primarily in the ancillary benefits that they offer,

including wildlife habitat production, recreation and aesthetics. These settings are also well

suited for educational purposes. Many municipalities have created parks around their FWS

treatment wetlands which have subsequently become popular recreational destinations

within these communities (U.S. EPA, 1993). The disadvantages include potential

mosquito problems and the potential for exposure of wildlife and humans to pathogens. A

disadvantage common to both types of wetlands is that they require several years (two to

three growing seasons when plants are used) to mature and reach optimal treatment

efficiencies (Hammer and Bastian, 1989).

11

Treatment Processes and Efficiencies

There are generally five species of pollution which are of greatest concern in

municipal wastewater: BOD (biochemical oxygen demand), TSS (total suspended solids)

and turbidity, nitrogen, phosphorous, and pathogens. Other factors which may be of

concern at specific sites, but not at the B2C, include pH, temperature and heavy metals.

The North American Wetlands for Water Quality Treatment Database, NAWWQTD,

(U.S. EPA, 1994) has data on 203 constructed wetlands, including SSF and FWS systems.

Average removal efficiencies for BODs, TSS, TN (total nitrogen), NH4-N and TP for 94

of these sites are presented in Table 1 (U.S. EPA, 1994). Long-term average operational

performance (i.e., percent removal of important pollutants) of several North American

treatment wetlands is summarized in Table 2 (Kadlec and Knight, 1995). Kadlec and

Knight (1995) used these data to derive areal reaction rate models which are presented in

Chapter HI. It is important to note that a direct comparison of FWS and SSF systems

would need to consider not only loading rates but also cell sizes, detention times and

environmental factors like temperature, precipitation and evapotranspiration. All of these

factors directly influence the rate and degree to which different pollutants are removed.

Many of the removal processes are temperature dependant, with removal rates

proportional to temperature. Precipitation will dilute pollutants while evapotranspiration

will concentrate them. Conclusions drawn concerning the performance of one system type

against another which do not consider these factors are likely to be inacurate.

12

Table 1. Gross Pollution Removal Efficiencies from FWS and SSF Systems (US EPA, 1994)

Species % Removal Mean Effluent Concentration

BOD5 71% 10 mg/1

TSS 71% 16.1 mg/1

NH3-N 46% 3.2 mg/1

TN 54% 5.7 mg/1

TP 46% 2.0 mg/1

Table 2. Long-Term Average Performance of Key North American Wetlands (Kadlec and Knight)

Species Tvpe of Wetland Loading Rate (Kg/ha/d)

Percent Removal

BOD5 FWS 7.2 74% BOD5

SSF 29.2 69%

TSS FWS 10.4 70% TSS

SSF 48.1 79%

NH4-N FWS 0.93 54% NH4-N

SSF 7.02 25%

TN FWS 1.94 53% TN

SSF 13.19 56%

TP FWS 0.17 57% TP

SSF 1.14 32%

13

Biochemical Oxygen Demand

Biochemical oxygen demand is removed as particulate organics settle and dissolved

BOD is consumed by attached and suspended microbial growth (Watson et al., 1989). In

FWS systems oxygen needed for BOD removal enters via diffusion from the atmosphere

across the air water interface. In SSF systems the major pathway for oxygen is via

diffusion from plant roots. Because oxygen diffusion from roots is not the same for all

plants, the type of plants used influences BOD removal rates in SSF systems.

Total Suspended Solids

Removal of total suspended solids is very good in both SSF and FWS systems (Tables

1 and 2). Major removal pathways for suspended solids include settling and adhering to

biofilms on gravel/stem/root surfaces. In SSF systems most suspended solids removal

occurs within the first few meters of entering a system (Watson et al., 1989). Removal

rates and efficiencies depend upon water velocities, particulate properties and water

properties (Kadlec and Knight, 1995). Watson et al. (1989) found that plants did not seem

to be important factors in the removal of TSS.

Nitrogen

Nitrogen is present in wetlands in the form of NH4+, N02", N03, N20 and N2. Nitrogen

is most often measured as NH4+ (ammonium nitrogen), TKN (total kjeldahl nitrogen) and

TN (total nitrogen) where TKN is equal to the sum of organic nitrogen and NH4-N. A

portion of the ammonium nitrogen will be present in the un-ionized form, NH3. The

14

percentage of ammonium nitrogen present as ammonia is pH dependent, with higher pH

producing more ammonia. This compound is toxic to most aquatic organisms in

concentrations greater than 0.2mg/l. Ammonia exits wetlands directly via volatilization

and assimilation by plants; NH3 is the preferred form of nitrogen for most wetland plants.

Direct assimilation of nitrogen however, accounts for a relatively small amount (5 to 10%)

of the nitrogen removed by wetland systems (Cooke, 1994) . The greatest amount of

nitrogen removal occurs via nitrification/denitrification. Cooke (1994) determined that

between 60 and 70% of nitrogen lost was removed via denitrification. This process is

dependant upon soil redox-potential and available carbon. The amount of available

carbon is often limiting to denitrification rates in SSF systems. Another important exit for

nitrogen results during flooding when large quantities of nitrogen are flushed from

wetlands.

Phosphorous

The primary removal mechanism for phosphorous in constructed wetlands is through

adsorption of dissolved reactive phosphorous (DRP) by immobile sediment/detrital

surfaces (Cooke, 1994). Amount of phosphorous adsorption is largely controlled by the

amount of aluminum and iron in soils. Guardo et al. (1995) found that peat accretion

formed from dead plant matter was another major removal pathway for phosphorous.

Phosphorous removal in wetlands is generally considered to be poor (Tables 1 and 2).

Pathogens

The major pathways for removal of pathogens from wastewater include natural cell

15

die-off, bacteriophages, sedimentation, adsorption, aggregate formation, exposure to

sunlight (UV radiation), predators, competition for limited resources and exposure to

toxic substances excreted by other microorganisms. Pathogen removal efficiencies are

considered to be good; Kadlec and Knight (1995) found that when influent concentrations

of bacteria were high, removal efficiencies were nearly always above 90% for coliforms

and 80% for fecal streptococcus. It has also been found that planted SSF systems remove

greater percentages of pathogens than do unvegetated SSF systems (Gersberg et al.,

1989). It should be remembered however, that these bacteria are present in great numbers

in the feces of birds and other wildlife which are likely to frequent wetlands. Accordingly,

effluent goals of FWS systems should reflect this and not attempt low or zero discharges.

In fact, some treatment wetlands designed for wildlife useexperience negative removal

efficiencies (U.S. EPA, 1994).

Hydrophyte Considerations

The role of aquatic plants in constructed wetlands has been well studied (Brix, 1994;

Adcock and Ganf, 1994). The majority of research conducted in this area agrees that

aquatic plants play an important role in treatment processes. Table 3 lists some commonly

used aquatic macrophytes in constructed wetlands. In FWS systems hydrophytes are

essential in that they provide abundant surface area for bacterial growth. It is upon this

surface area that many of the treatment processes occur, such as nitrification and the

degradation of BOD as described earlier. Hydrophytes appear to be equally important in

SSF systems. This can be seen in Table 4 (Reed et al, 1988), which shows the

16

Table 3. Common Aquatic Plants Used in Constructed Wetlands

Common Name Scientific Name

Cattails Typha spp. T, latifolia*

Bulrush Scirpus spp. S. acutus*

Reeds Jurtcus spp Phragmites spp. P. communis*

Pickerelweed Potederia spp.

Duck potato Sagittaria spp. Arrow-head S. cuneata*

Duckweed Lemna spp. L. gibbet*

* Plants suitable for use at the Biosphere 2 Center location and elevation.

Table 4. Comparison of Macrophyte Efficiencies in Water Quality Improvement for Three Parameters of Interest and Comparison of Planted Versus Unplanted SSF Systems (Reed el ah, 1988)

Plant Type jEfflnent Quality

BODmg/1 SS mg/1 NH3 mg/1

Bulrushes 5.3 3.7 1.5

Reeds 22.3 7.9 5-4

Cattails 30.4 5.5 17.7

No vegetation 36.4 5.6 22.1 Q=3.04nrVday, hydraulic residence time = 6 days, bed dimension: L= 18,5m. W=3.5m, depth=().76m

17

performance of planted and implanted SSF systems. This table also allows a comparison

between the treatment efficiencies of various plants. Although there is a considerable and

contradictory amount of literature on the performance of different plant species (Reed, et

al., 1988; Kadlec and Knight, 1995), data for the three most common plants used in

constructed wetlands, Typha spp. (cattails), Phragmites spp. (Reeds) and Scirpus spp.

(Bulrush) from a California test facility are presented. Data from this site were chosen

because of the site's proximity to the Biosphere 2 Center.

The importance of aquatic macrophytes in SSF systems revolves around the

rhizosphere. This is the term used to describe the area around the rhizomes of hydrophytes

growing in wetlands. It is within this zone that much treatment occurs. As an adaptation to

living in hydric soils, aquatic macrophytes have adapted mechanisms by which they can

transport oxygen, passively or actively to their roots (Groose, 1989; Brix, 1994). Some of

this oxygen leaks out into the surrounding medium, causing localized aerobic zones.

Bacterial populations responsible for the treatment seen in constructed wetlands (as

previously described for FWS systems) thrive in these aerobic regions. Macrophytes are

also important in SSF systems in that they provide a source of carbon for denitrification.

Following the above discussion it can be seen that the depth of root penetration should be

proportional to treatment efficiency since deeper roots extend the rhizosphere downward,

resulting in a greater percentage of water in contact with this zone. Reed et al. (1988)

state that a difference in root depth penetration is the reason for the discrepancy seen in

treatment efficiencies of different plant species. Table 5 (Reed et al, 1988), which shows

the root depths of these three plants as observed at the Santee, CA test facility, supports

18

Table 5. Comparison of Macrophyte Root Depth Penetration at the Santee, CA Wetlands (Reed etal., 1988)

Plant Type Root Depth

Bulrush 76cm

Reeds >60cm

Cattails 30cm Bed depth was 76cm.

19

this idea.

Since wildlife habitat production is usually not a major factor in SSF systems, choosing

vegetation for these systems does not focus on a plant's value to wildlife. Accordingly, the

choice concerning which macrophyte to use for an SSF system should be based primarily

on treatment efficiencies. Other considerations would include transpiration rates, tolerance

of cold weather and aesthetic appeal. Choosing aquatic plants for FWS systems however,

can be more involved and site specific when the production of high quality wildlife habitat

is desired.

Wildlife Habitat Production

It has been estimated that in the U.S., wetlands contain 190 species of amphibians, 270

species of birds and over 5000 species of plants (Hammer and Bastian, 1989),

Furthermore, 26% of plants and 45% of animals listed as threatened or endangered are

dependant upon wetlands for survival (Feierabend, 1989). Unfortunately, these important

habitats are vanishing rapidly despite attempts to preserve them. Steinhert (1993) reports

that approximately 116,000 hectares of natural wetlands are destroyed annually in the US.

Although rare in comparison to other parts of the country, wetlands exist as cienegas,

bosques and other riparian zones along the infrequent streams and rivers of Arizona. In

the past century however, most of these wetland communities have been lost due to

human activity. Accordingly, the use of treated wastewater to restore these valuable

habitats has generated a lot of enthusiasm as well as controversy (Feierabend, 1989). In

light of the Kesterson marsh catastrophe in California (Carter, 1988), many people are

20

reluctant to encourage wildlife use of constructed wetlands. Kadlec et al (1995),

however have stated that not a single wetland created to treat municipal wastewater to

date has been documented to have toxicity to wildlife. McAllister (1993) examined two

mature FWS constructed wetlands in the arid west; Show Low, Arizona and Incline

Village, Nevada. Both of these systems were created to treat municipal effluent, and at the

time of that study had been in operation for 17 years and 12 years respectively. McAllister

found that in both systems, indicator values were within the range of values from non-

wastewater treatment wetlands and that bird species richness and densities were above the

range for non-treatment wetlands. Many other examples of successful wildlife habitat

production can be cited (Hardy, 1989; U.S. EPA, 1993; Wilhelm et al, 1989; Kadlec and

Knight, 1995). An EPA study of Incline Village, NV and Show Low, AZ in 1991, found

good bird usage and nesting in both sites (U.S. EPA, 1993). Results can be seen in Table

6. Likewise, the Pintail wastewater treatment system in northern Arizona was found to

receive heavy usage as breeding habitat for waterfowl; in 1982, a total of 380 nests of 8

different species of waterfowl were recorded (Wilhelm, et al, 1989). Based on these

studies it seems reasonable that a constructed wetland at the B2C could be designed in

such a way as to successfully produce high quality wildlife habitat. Due to the paucity of

wetlands in arid regions (in particular, southern Arizona), such a system could be

expected, as has been seen at the Incline Village, Show Low and Pintail systems, to attract

a large number of animals. Using treated wastewater to restore a sample of this rare

habitat is in keeping with Biosphere 2's environmentally conscious philosophy. Habitat

could also serve as an educational tool for visiting students, some of whom will have not

21

Table 6. Waterfowl Abundance at Incline Village Wetlands, NV and Show Low Wetlands, AZ (U. S. EPA, 1993)

Location CW arts Total Species

Incline Village 198ha 47 19,1

Show Low 284ha 42 13.8

22

seen a wetland prior to their visit. Seeing animals in such a setting is exciting for children

and conducive to the propagation of the conservation ideology necessary to preserve our

natural heritage. A second reason that wildlife is an important component of the B2C

treatment wetlands design lies in the fact that it creates the potential to increase ticket

sales and memberships.

The successful creation of high quality wildlife habitat can not be fully realized when

treated simply as an ancillary benefit; planning for habitat creation must be an implicit part

of the design process with special considerations. The most important of these

considerations is determining wildlife types desired to frequent or inhabit the wetland. This

decision must be made during early planning stages of any project (Kadlec and Knight,

1995; Knight et al., 1995). Wetlands can then be designed around selected species. It is

necessary to not only consider species requirements, but also requirements for that

species' prey/food items. Without knowing how habitat oriented design features might

affect treatment efficiency however, designers run the risk of producing systems incapable

of meeting desired treatment levels. This is particularly relevant in light of the fact that

many systems are designed to be as small as possible in order to keep down construction

costs.

Wetland habitats in arid regions can be thought of as islands. These island habitats are

often separated by great distances of dry terrain, making migration between them difficult

or impossible for many aquatic organisms. Wetland birds are the exception to this, and

benefit most from presence of constructed wetlands in arid regions. Since Arizona is a

corridor for migratory birds, waterfowl and otherwise, scarce desert wetlands are

23

particularly important. Thus, inclusion of wildlife habitat at the B2C treatment wetlands

should be considered to provide optimal habitat for wetland bird species.

Bird watching is a popular past time in the U.S. In Arizona this activity generates more

money for that state than any other ecotourism activity with ecotourism in turn being the

largest component of Arizona's tourist industry. In recent years, birders have found

constructed wetlands to be good birding locations. The Mt View Marshes, for example, a

combined wetland forest water treatment system, encourages visitors. The managers of

this site keep records of how many people visit and the reasons for their visits. In 1985, a

total of 320 people visited the marsh. Of these, 78% listed bird watching as the reason for

their visit, with 20% listing education (James and Bogaert, 1989). Technical interest

accounted for the remaining visitors. Thus, a well designed wetland capable of attracting a

variety of bird species could potentially augment ticket sales and memberships at the B2C.

Table 7 lists wetland birds which are known to inhabit, at least part of the year,

southern Arizona. Of these, many have been identified as using constructed wetlands

already in operation (Kadlec and Knight, 1995; Niering, 1985). Food preferences of many

of these birds are also given. This information was used to determine which species are

most likely to benefit from wetlands in southern Arizona. Selection of HSI model species

for wetland birds came from this list, but was limited by model availability. Table 7 also

identifies birds which breed in southern Arizona. Other criteria for HSI species selection

and weighting includes the characteristics of individual species. Some birds, for example

those which feed on flying insects, are highly desirable for their value in pest control.

Colorful or rare birds, on the other hand, have greater appeal with the visiting public.

Although it may not be necessary to take any special action to attract some birds, it may

24

Table 7, North American Wetland Birds Known to Visit or Inhabit Southern Arizona

Common Name Scientific Name Foods

Pied-billed grebe Podilymbus podiceps*+ Eared grebe Podiceps nigricollis* Green-winged teal Anas crecca* I/F/OA Mallard Anas platyrhynchos*+ I/F/OA Mexican duck Anas platyrhynchos diazi*+ I/F/OA Northern shoveler Anas clypeaia* I/F/OA Cinnamon teal Anas cyanoptera*+ I/F/OA Northern pintail Anas acuta * I/F/OA Canvasback Aythya valisineria* I/F/OA Redhead Aytbya americana* I/F/OA Ring-necked duck Aythya collaris* I/F/OA Lesser scaup Aytha affinis* I/F/OA Common merganser Mergus merganser* I/F/OA Common goldeneye Bucephala clangula I/F/OA Bufflehead Bucephala alheola I/F/OA Ruddy duck (hcyura jamaicensis I/F/OA Canada goose Branta canadensis* I/F/OA Great egret Casmerodius albus I/F/A Snowy egret Egretta thula*+ I/F/A Great blue heron Ardea herodias*+ I/F/A Black-crowned night-heron Nycticorax nycticorax*+ I/F/A American bittern Botaurus lentiginosus* I/F/A Least bittern Ixobtychus exilis*+ I/F/A Green-backed heron Butorides striatus* I/F/A American coot Fulica americana* I/F/OA Sora Porzana Carolina* I/F/OA Virgina rail Railus limicola*+ AO Common snipe Gallinago gallinago* I/F/A Belted kingfisher Ceryle alcyon* HF Northern rough-winged swallow Stelgidopteryx serripennis+ FN Marsh wren Cistothorus palustris* Lincoln's sparrow Melospiza lincolnii Common yellowthroat Geothlypis trichas *+ FN Red-winged blackbird Agelaius phoeniceus+ I/S Yellow-headed blackbird Xantkocephalus I/S

xanthocephalus *+ I/S

+Birds whose breeding range includes southern Arizona. ""Birds known to be associated with treatment wetlands in North America. A= amphibians, AO= aquatic organisms, F= fish, FN= flying insects, HF= feeds inflight, I-invertebrates, S= seeds.

25

be necessary to consider the needs of desired species during designing. In general for

instance, ducks, geese and other diving birds prefer open water, while wading birds prefer

mud-flats or areas of heavy vegetation. Because feeding, breeding and shelter

requirements differ among bird species, attention must be given to vegetation to be

planted. Submerged vegetation for instance, pondweed (Potemegeton spp.) and water

milfoil (Myriophyllum sibiricum), provide food for waterfowl and productive habitat for

macroinvertebrates. These invertebrates in turn can serve as food for other bird species

(Knight et al., 1995). High turbidity conditions which often exist in constructed wetlands

make use of submerged vegetation difficult. Turbidity is often a result of algal blooms in

the nutrient rich environment of constructed wetlands. Presence of dense stands of

emergent vegetation help maintain submerged vegetation by reducing turbidity and helping

suppress algal blooms.

Knight et al. (1995) recommend using native vegetation, stating that woody native

plants have been demonstrated to have a much higher habitat value for native birds than

non-native woody plants. Furthermore, the use of native plants is ecologically responsible

and accordingly, only native plants are recommended in the following design of the B2C

treatment wetlands. Appendix A of the Arizona Guidance Manuel for Constructed

Wetlands for Water Quality Improvement (Knight et al, 1995) contains a list of native

Arizona wetland plants.

While design work must be species specific, it is important to maximize the diversity of

habitats available in order to increase species richness. Knight et al. (1995) state that

animal diversity is a function of plant diversity within a wetland. Floral diversity provides

26

an abundance of niches necessary to support a variety of different species. This fact was

accounted for in the development of structural habitat guilds, from which representative

species were chosen and HSI models weighted (this topic will be expanded upon later).

Treatment wetlands however tend to transform into monocultures of rapidly growing

aquatic plants like Typha spp, which are adapted to proliferating in high nutrient

environments. A good example of this can be seen in the Everglades, where phosphorous

enrichment from farming activities is allowing cattails to replace the once dominant saw-

grass. Diversity of plant communities will therefore need to be managed. Periodic flooding

is one means of controlling weedy species but may not be effective with larger plants like

cattails.

Other animals which are likely to visit and benefit from a constructed wetland at the

B2C include deer, coyotes, javelinas, pumas, fox, bob-cats and a variety of reptiles and

other local desert animals. One major consideration to be made in terms of encouraging

wetland use by these animals is to provide them with a corridor by which they can easily

travel to and from the wetland. A corridor in the form of lands connecting the wetland to

desert habitat surrounding the B2C was a major site selection criterion.

Native desert animals, in particular coyotes, can be expected to visit the wetland system

in significant numbers, resulting in heavy predation pressure on birds and other small

animals. It would then be necessary to provide for protection, especially of birds, from this

predation. Construction of islands is an effective means of safeguarding wetland birds

from ground predation. Care should also be taken to protect wildlife from human

disturbance seggesting that wetland systems be built away from major visitor

27

thoroughfares, where viewing is restricted to well camouflaged sites. The Show Low

facility uses a "wildlife viewing blind" which serves as a classroom for up to 40 children

(Knight, et al., 1995). Finally, nature trails built beside a wetland should be separated from

water by dense vegetation. Interpretive signage along any such trails would improve

visitor appreciation of the system.

Fishes, amphibians and aquatic reptiles desired in the wetland system would have to be

imported. This procedure is recommended for several species of native fishes, turtles and

frogs. Any species likely to suffer from extremely heavy predation should be introduced

only if such a species could persist despite these conditions.

It is recommended that fishes be imported for two reasons, the first being for the

control of mosquitoes and the second to serve as a prey item for birds. The mosquito fish

(Gambusia affinis) has been used with success in other treatment facilities, and is

particularly well adapted to the low oxygen environments typical of such locations.

Because these fish are desired in great numbers, refuge sites like empty clay pots should be

provided in order to assure a large population despite predation pressures. Submerged

vegetation will also protect small fish from bird predation. Larger game fish should not be

introduced because they are not as well suited to the low oxygen levels likely to be

present, and because they will prey on more beneficial fishes. Bottom feeders like carp

should also be excluded from consideration, as they disturb bottom sediments increasing

suspended solids.

28

Habitat Evaluation

HSI models allow quantification of the value of a given area as habitat for a particular

species. (Terell, etal., 1982; Canter, 1996). HSI models have been developed for a

number of different animals. The models are either descriptive or mathematical, with the

later used in this study. The mathematical models are based on the determination of a

suitability index (SI), which compares various quantified habitat parameters (as

determined via the HEP) to what are considered to be the optimum values of these

parameters for the model species (U.S. FWS, 1980). The SI is expressed as a fraction

from 0 to 1, with 1 representing optimal habitat. Habitat Units (HUs) can then be

determined by multiplying the SI value by the total area of the study site. The HU value of

a location obtained for one or more HSI model species reflects in a single numeric score,

the relative habitat value of a sampled location.

Before HEP can be used, it is necessary to determine appropriate HSI models. A

suggested method for obtaining model species is to develop feeding, reproductive and

cover guilds. Guilds represent groups of animals which have similar habitat requirements.

Accordingly, a single representative species can be used to determine the suitability of a

particular habitat for the entire guild to which it belongs. Construction of guilds can be

accomplished through the development of a matrix. Figure 3 shows the matrix which has

been developed for this study. Normal HEP implementation entails the selection of one

species from each guild. An HSI model for each selected species is then acquired. Because

a maximum number of habitat parameter variables was desired for this research, all

relevant available models were chosen. These models are the American coot, great egret,

29

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marsh wren, muskrat, red-winged blackbird and yellow-headed blackbird. Models with

identical feeding loci, feeding preferences and cover requirements were given less weight

so that each guild was equally represented in HU determinations. Weighting was not

undertaken to reflect the relative importance of individual species, but to obtain HU

calculations which equally represent as many different species as possible. Since species

abundance is proportionally to habitat diversity, giving equal weight to all guilds results in

HU scores better representing all animal species as a whole.

Another means of evaluating the quality of wetland habitat is the Wetland Evaluation

Technique (WET). McAllister (1993) in a study of arid constructed wetlands used WET

to determine the habitat values of two wetlands. Results indicated that constructed

wetlands are good for migratory and wintering wildlife, but poor for breeding habitat.

WET ratings for aquatic diversity and abundance were also low. McAllister concluded

however, that the WET technique was not appropriate, and recommended that it not be

used with constructed wetlands or that it be given a low priority. Use of HSI models with

HEP may therefore be more appropriate.

Problems

Some of the potential problems which are of concern in constructed wetlands include

mosquitoes, odors, wildlife toxicity, human pathogens and the threat of dangerous

animals. The first two conditions are of concern because treatment wetlands, by necessity,

must be located next to sources of wastewater. The later two result from the increasing

use of constructed wetlands for recreational purposes.

31

When improperly designed, mosquitoes can be a nuisance resulting from constructed

wetlands (Dill, 1989). This is of particular concern for a constructed wetland built at the

B2C, as hundreds of visitors frequent the campus daily. In such a situation, there could be

concern that mosquitoes would serve as vectors for certain diseases like encephalitis,

which occurs in birds but can be transmitted to humans. Most mosquito transmitted

diseases, however have become rare in developed nations. Much of the concern expressed

about this issue stems from California's experiences ten to twenty years ago when five of

nine plants built after 1974 had to be closed because of mosquito problems (Martin and

Elridge, 1989). Most of the problems in California however, came from floating

vegetation ponds. These systems are ripe for mosquito production as floating aquatic

plants protect water surfaces from wind disturbance and impede oxygen diffusion, leading

to low concentrations of DO. In oxygen impoverished water, predatory invertebrates and

fishes which feed on mosquito larvae cannot survive. Fortunately, mosquitoes have not

been a major problem in modern FWS or SSF constructed wetlands. A 1991 sample of

Show Low constructed wetlands in Arizona yielded 9,938 invertebrates of which only 3

were mosquitoes (Knight et al, 1995). McAllister (1993) found only 5 mosquitoes out of

5,869 invertebrates collected at the Incline Village, Nevada constructed wetlands.

Biological control with gambusia (mosquito fish) and birds should be adequate to control

mosquito populations at the B2C treatment wetlands. It would also be desirable to

establish bat populations close to the marsh to help control insect populations as

suggested by Knight et al (1995). Visiting school children would appreciate seeing and

hearing about "bat houses." As a final control method, operators should not allow dense

32

mats of dead vegetation to collect at the surface, since such mats offer refuge for

mosquito larvae, protecting them from fish predation.

Although conventional wastewater treatment plants tend to be very malodorous,

constructed wetlands typically do not share this problem (Knight et al., 1995; Kadlec and

Knight, 1995). Strong odors in constructed wetlands are usually indicative of more serious

problems and can be used as a diagnostic tool.

As stated earlier, constructed wetlands for municipal wastewater treatment have not

been documented to pose a toxicity threat to wildlife. This is due to an absence of toxic

substances in influent waters. Wastewater entering the B2C system is also free of

potentially dangerous substances and therefore would not pose a threat to wildlife. Draw-

downs have however, been shown to contribute to cases of avian botulism and should

therefore be minimized. Botulism and avian cholera have also been found to be associated

with low DO levels (Knight et al., 1995).

The threat of human pathogens in constructed wetlands is primarily of concern only in

FWS systems, and can be avoided by restricting access to open surface waters which may

be contaminated. Use of a SSF system at B2C to pretreat water would help reduce

pathogen levels prior to introduction of water to open water areas where they would be of

concern (Gersberg, 1989).

The primary concern with dangerous animals at constructed wetlands is with poisonous

snakes. There are no poisonous aquatic snakes in Arizona. Rattlesnakes do exist in good

numbers however, and could be of concern should nature trails to the wetlands be

established. Preventative measures would include warning signs, and clearing of

33

vegetation around trails.

Permits

There are two classes of permits and regulations which were considered for the B2C

treatment wetlands: federal and state. Table 8 lists relevant permits along with the

regulatory agency responsible for issuing these permits. Although the clean air and water

act NPDES permit is listed, no such permit would be required for the B2C system. This

permit regulates discharges into "jurisdictional waters of the U.S." No such waters are

believed to exist at the B2C location. There are two basic types of state discharge permits

(aquifer protection permits) which need to be considered. These are the general and

specific aquifer protection permits. A general permit applies to all onsite wastewater

systems discharging less than 2,000 gpd of materials conforming to Paragraph 1 of

Subsection D, R18-9-801 (typical sewage). General permits can also be obtained for

systems discharging up to 20,000 gpd providing established criteria are met. The criteria

are as follow: 1. The bottom of subsurface disposal systems is at least 40 feet above the

static groundwater level where the soil percolation rate is slower than or equal to 1

minute/inch, 10 feet above the static ground water level where the soil percolation rate is

slower than or equal to 2 minutes/inch but faster than 10 minutes/inch, or 5 feet above the

static groundwater level where the soil percolation rate is slower than or equal to 10

minutes/inch and 2. total nitrogen content of discharged effluent is not greater than

ambient groundwater levels. General Permits do not require application to the Arizona

Department of Environmental Quality (ADEQ); meeting criteria is sufficient to satisfy

34

Table 8. Regulations and Permits

Permit/Regulation Regulatory Agency

Aquifer Protection Permit ADEQ

ADEQ EngineeringBuI letin #12 ADEQ

Clean Water Act NPDES (section 402) EPA

NPDES General Permit for Storm water Discharge from Construction Activities

EPA/ADEQ

Endangered Species Act USFWS

Arizona Native Plant Law Arizona Dept. Of Agriculture and Horticultures

35

permit requirements. Systems which do not meet these criteria or discharge more than

20,000 gallons per day require an individual permit. Individual permits are difficult to

obtain. Issuance of an Individual Permit is dependant upon the applicant's ability to

demonstrate compliance with aquifer water quality standards (AWQS) and that the facility

uses "best available demonstrated controlled technology (BADCT)" Although AWQS are

not particularly stringent, BADCT compliance is more difficult to demonstrate, and is

determined through negotiation with the ADEQ.

ADEQ engineering bulletins were designed to assure that wastewater treatment systems

meet ADEQ standards. Bulletin 12 (for alternative on site disposal systems) mandates the

use of septic tanks with a minimum of two compartments for preliminary solids settling

prior to a constructed wetland.

The wetland design to be proposed for development at the B2C is to have an area of

approximately 3 acres. Therefore, it would not be necessary to obtain a NPDES General

Permit for Storm water Discharges from Construction Activities. This permit applies to

construction sites where five or more acres of land are graded or disturbed. When this is

the case, an application must be made for coverage under EPA's general permit for storm

water discharges associated with construction activities.

There are not believed to be any endangered animals at the B2C. Accordingly, no

endangered species would be effected by construction at the B2C.

The Arizona Native Plant Law was designed to protect specified native plants from

collection and use, but does not protect these plants from destruction if (1) the land on

which the plant is found is in private ownership, (2) plants are not transported off-site and

36

offered for sale and (3) the owner notifies the Arizona Department of Agriculture and

Horticultures in writing 30 days prior to activity (for parcels of land less than 1 acre, only

20 day notice need be given, and only if specified plants are involved). No permit would

be required for the B2C treatment wetlands. In keeping with the B2C environmental

policy, an attempt to relocate any affected, native plants of particular interest is

recommended.

CHAPTER III

METHODS AND PROCEDURES

This chapter outlines criteria (i.e., wastewater characterization and statement of

treatment goals) used in designing different treatment and habitat systems. Various design

models are presented in detail along with other design tools used for hydrology and mass-

balancing. The fundamental model used for design was an areal reaction rate equation

developed from the NAWWQT database (U.S. EPA, 1994) by Kadlec and Knight (1995).

This equation correlates wetland area and volumetric flow with pollutant reduction. It was

used to determine minimum wetland area necessary to meet treatment objectives. This

basic equation was then applied to various habitat systems in order to determine each

system's treatment efficiency. The second basic model, used to design habitat systems,

was the Habitat Evaluation Procedure (HEP) with associated species HSI models (U.S.

FWS, 1980). These models were then applied to the treatment system in order to

determine its habitat value. Once both treatment and habitat systems had been designed

and scored, they were examined to determine limiting values. For instance, the treatment

wetland possessed certain definable physical parameters which resulted in it receiving a

less than optimal number of HUs. The habitat system on the other hand, had certain

characteristics which prevent it from operating as efficiently as the treatment system. Each

37

38

of these limiting features were modified when workable, in order to obtain the highest

scores possible for each of the models. These modifications were then incorporated into a

hybrid system. Once the hybrid wetland had been designed, it too was scored for efficiency

and habitat value.

In order to eliminate the potential problems which can arise from having exposed

sewage, as occurs in a FWS system receiving raw or primary wastewater, each of the

designed systems incorporates a SSF component. As previously mentioned, Arizona

Department of Environmental Quality Engineering Bulletin #12 mandates the use of a

bifurcated septic tank prior to introduction of water into a constructed wetland.

Accordingly, existing onsite septic tanks are to be used as preliminary components of the

pretreatment process. Water entering the SSF components is assumed to originate from

these septic tanks. Although pollutant reduction was determined for the SSF systems

(necessary to determine FWS influent quality) HEP was not applied due to the fact that

SSF wetlands serve little value as wildlife habitat.

Wastewater Characterization

A necessary first step in planning a constructed wetland is to characterize the

wastewater to be treated. Determination of both quantity and quality is required.

Characterization was accomplished by employing a multiplier used for the purpose of

establishing criteria for aquifer protection permits. This and other multipliers are found in

Appendix I of the 1997 amendments to the Arizona Environmental Quality Act of 1986

which establishes and mandates aquifer protection permit under the guidelines discussed in

39

Chapter 2.

As previously mentioned, the amount of wastewater produced at the B2C is

proportional to the number of visitors on site at a particular time. Although each visitor

contributes some minimum amount of wastewater via use of restrooms, hands washing,

drinking from water fountains, ect. those who dine at the restaurant produce much more.

The minimal estimated wastewater contribution of each visitor is estimated to be 5 gallons

per day. Approximately 1/3 of all visitors eat at the restaurant with an estimated 100

gallons produced per meal served. Thus, each visitor was assumed to contribute 38.3

gallons of wastewater. Although this value is almost certainly an overestimation of the

actual wastewater generated by visitors, it was used to compensate for other sources of

wastewater production which were not characterized. These sources of wastewater

include students living on site, employees, research activities and hotel guests.

As visitor numbers fluctuate greatly throughout the year, so does waste stream.

Accordingly, it was necessary to determine the busiest month when flow is expected to be

at maximum. Wetland designs had to be able to accommodate this peak flow. It was also

necessary to determine the least busy month when flow is at a minimum. This, in

conjunction with evapotranspiration and precipitation rates, allowed the amount of make-

up water the Biosphere 2 Center Wetlands design would need, to be calculated. Make-up

water, along with adjusting wetland flow regime, was used to prevent salinization of

wetland water.

The estimated quantity of wastewater was obtained by extrapolating actual monthly

visitor counts from 1997 to future goal of 300,000 visitors per year. Table 9 lists current

40

and target visitor counts along with estimated wastewater production. From this table, a

peak and off peak season can be identified. Peak season occurs from December to May

with an average flow of 169.3 m3/d. Off-peak season occurs from June to November with

an average flow of 69.43 m3/d. Average peak flow was used in water quality modeling and

habitat comparisons. Months of peak flow correspond with bird migrations and thus

wetland usage by birds. Accordingly, this time period is the most appropriate time to

employ HSI models. Current information suggests however, that the number of visitors

actually visiting the site is down from 1997, while student enrolment is up. This will have

the effect of reducing the month to month variability in wastewater production, while

increasing base flow. In January of 1998, the ADEQ estimated that an average of 12,250

gallons (46.4 m3) of wastewater were being produced daily at the B2C. Accordingly, the

Biosphere 2 Center Wetlands were designed not in accordance with the target visitor

count flow rates, but to accommodate an average flow of20,000 gpd (76 m3/d). This flow

rate is expected to be reached in the coming years, necessitating the construction of a

wastewater treatment facility. Peak flow for this wetland system was assumed to be twice

the normal flow (i.e., 40,000gpd or 151 m3/d) while low flow was assumed to be half the

average flow, or 10,000gpd (38 m3/d). Using peak target visitor counts to estimate peak

flow for the Biosphere 2 Constructed Wetlands would result in a seriously over designed

system for what is likely to be actual future needs. Using both methods of estimating

wastewater production gives the B2C a realistic wetland design while also estimating the

size a wetland would need to be to accommodate target visitor counts.

The quality of wastewater produced was assumed to be as follows: 200 mg/1 BOD and

41

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42

210 mg/1 SS. These values are established by the Aquifer Protection Act of 1986.

Nitrogen and phosphorous loading rates were assumed to be analogous to municipal

wastewater, having the following concentrations: TKN 40 mg/1, TN 40 mg/1, NH4-N 25

mg/1 and TP 8 mg/1 (Kadlec and Knight, 1995). Water discharged from septic systems

(SSF system influent) is assumed to have the following concentrations: TN 36 mg/1, TP 8

mg/1, BOD 162 mg/1, TSS 148 mg/1, FC 10,000 CFU/ml (Postma et al., 1992; Reneau et

al., 1975; Wilhelm etal, 1994).

Design Tools

Areal Reaction Rate Equation

Watson and Hobson (1989) state that all constructed wetlands are attached-growth

biological reactors and as such, performance is based on first-order, plug-flow kinetics

with the following relationship:

where Ce = effluent concentration in mg/1 Q= influent concentration in mg/1 K, = first order reaction rate constant (day"1) t = hydraulic residence time (day)

Kadlec and Knight (1995) expanded these equations using data from the NAWWQT

database (U.S. EPA, 1994) to developed an equation which can be used to calculate the

43

amount of area required by a constructed wetland to reduce concentrations of certain

pollutants to desired levels

(Ce). This equation is:

O ( c r c * ) A=365(%M— ~]

K (C-C*)

where Q = volumetric flow (m3/day) K = areal reaction rate (m/yr) C* = background concentrations (mg/1) A = surface area (m2) The multiplier 365 has units of days/yr

The equation is valid for both SSF and FWS wetlands and can be used to determine

wetland cell areas for desired reductions in BOD, TSS, TN, NH4-N, NOx, TP and FC.

Desired treatment levels for this project were as specified by the general Arizona APP

requirements which specify that TN concentrations in discharged waters are not to exceed

ambient ground water levels. The concentration of total nitrogen in ground water at the

site was assumed to be 3 mg/1. Reaction rate constants (K) are different in SSF and FWS

systems and vary from location to location according to a number of factors.

Nitrogen removal in constructed wetlands is temperature dependant. The relationship

between K and temperature for TN, NH4 and NOx is as follows:

44 where K = areal reaction rate (m/yr)

K20 = areal reaction rate at 20°C © = temperature coefficient T = temperature in Celsius

Temperature relationships are important in that temperatures in southern Arizona are

typically much higher than in most of the nation from which K values were determined.

Kadlec and Knight (1995) have determined average K20 values from the North American

Database (U.S. EPA, 1994). Table 10 lists average K20 values for BOD, TSS, TN, TP and

FC. These values were determined from a variety of different systems including natural

wetlands, constructed wetlands and systems using floating vegetation. Sources of

wastewater for these systems was also variable, including storm water and industrial and

municipal wastewater. For these reasons, it is desirable to adjust K values to reflect as

closely as possible the conditions anticipated in the constructed wetland to be designed.

Towards this end, only K values from wetlands conforming to a set criteria were selected

from the NAWWQT database (U.S. EPA, 1994). The selected sites were all of non-

natural origin and had a total flow of less than 2000 m3/day (52,8401.6 gpd) with an area

to flow ratio of less than or equal to 0.002 (eliminates over-designed systems). Only

systems listed as "marsh" systems were chosen since it was assumed that these systems

consist primarily of emergent vegetation with a minimum of open areas. KTO and KBOD

values from these systems were used to characterizing water treatment in vegetated areas

of the wetlands herein designed. Data from a constructed wetland using submerged

vegetation were used to characterize water treatment in open areas of both the habitat and

hybrid systems which were designed for this research. All open areas were assumed to

45

Table 10. Reaction Rate Constants,K20, (Kadlec and Knight, 1995)

Species SSE (m/year) FWS (m/year)

BOD 180 34

TSS 1000 1000

TN 27 22

TP 7.2 12

FC 95 100

46

contained submerged vegetation. Calibration of KTO and KBOD rates enabled water quality

to be modeled as water flows through different cells of each wetland, rather than on a

whole-system basis. Modeling at the system level would not allow consideration of

different wetland characteristics believed to influence water treatment, such as flow and

vegetation type and placement. Table 11 (Knight et al, 1995) lists temperature

coefficients for different water parameters for K determination. For the purpose of this

study, background rates were fixed at 1.5 mg/1 total nitrogen and 6.5 mg/1 BOD. These

levels are common background concentrations in natural wetlands. Natural concentrations

of fecal coliforms in wetlands are often in the range of 10 to 500 colony forming units

(CFU) per 100ml (Kadlec and Knight, 1995).

Hydrology

Darcy's equation (Fetter, 1994), Q = klA, where "k" is the hydraulic conductivity of a

medium through which water is moving and "I" is the hydraulic gradient (Aheight /

Alength), has been used to describe the movement of water through a SSF system. This

law however, is only valid for laminar flow; flow around gravel (as in SSF systems) is

turbulent. In this case Ergun's equation (Watson and Hobson, 1989) is appropriate:

p ^ , 5 0 H m ^ + 1 . 7 5 £ > 3 l ^ I)h2 D pe

47

Table 11. Reaction Rate (©K) Temperature Coefficients

Species SSE FWS

e K €>K

BOD 1.00 1.00

TSS 1.00 1.00

TN 1.05 1.05

NH4-N 1.04 1.04

NOx 1.09 1.09

TP 1.00 1.00

48

where p = density of water (kg/m3) S = slope g = gravitational acceleration (X = viscosity of water (kg/m/d) E = porosity Dp = particle diameter V = velocity

The porosity of gravel is approximately 0.35, with a particle diameter ranging from 4.75

mm to 76 mm (Fetter, 1994). The above equation accounts for mounding which can

cause surface flow. Ergun's equation however, assumes that the media is composed of

uniformly sized spheres. This is not an accurate assumption for SSF gravel media.

Conductivity of crushed, angular material can be determined by a modified Ergun's

equation (Kadlec and Knight, 1995):

j. m 3 1 D P2

1 127.5(1-e)n

Conductivities predicted with this equation are several times lower than with the

unmodified Ergun's equation. Adding a laminar contribution factor, a final equation

describing flow through a SSF system containing a randomly packed media of non-

homogeneous shaped is obtained. The equation is as follows (Kadlec and Knight, 1995):

1 _ 255(1 -e)n^ 2(1 -e)u

ke pge37Dp2 ge3Dp

where

u = velocity (m/d) ke = effective conductivity (m/d)

49

Short-circuiting of SSF wetlands due to surface flow has been a major problem with

many SSF systems currently in operation. It is believed that this is due to the fact that

most of these systems were not designed with proper hydraulic considerations and media

of appropriate conductivity (Watson and Hobson, 1989). To avoid these problems in the

B2C Wetlands, Ergun's modified equation was used to determine the type of media which

would be required to handle peak flow. This was done only after area determinations were

made according to FC effluent goals. As time progresses, roots, rhizomes and particulates

will fill pore spaces, causing a reduction in effective porosity. To accommodate the

inevitable reduction in hydraulic conductivity, it was assumed that conductivity would be

reduced by a full order of magnitude at maturation (Kadlec and Knight, 1995). The

hydraulic conductivity of clean media to be used must therefore posses a conductivity one

order of magnitude larger than will be required at maturation.

The volume of water in a SSF system at any time can be determined by multiplying the

porosity by the total volume of the system; 1 x w x h (where h is height of water in the

gravel bed). Contact time can be deduced by dividing the volume of water in the system by

the volumetric flow rate:

hvhz

Q

This study, however used areal reaction rate equations to determine the required area and

did not consider residence times. Methods using residence times are common, perhaps

more conventional ways of designing water treatment facilities. Accordingly, the above

50

information is included here for the sake of thoroughness and interested readers.

Water Budget, Mass-balance Equation

The water budget of a treatment system is the ratio of system inputs to outputs and can

be described as:

Qin Qout+Qp QET QIN ^

where Qjn = volumetric flow, in Qom = volumetric flow out QP = volumetric precipitation Qex = volumetric evapotranspiration QIN = volumetric infiltration V = volume of water in wetland

It is assumed that the volume of stored water within the systems will not change with time

so that dV/dt is equal to zero, and that the effective infiltration rate is also zero. While

precipitation can be easily measured and is readily available from historic meteorological

data, evapotranspiration must be estimated. For planted FWS systems, evapotranspiration

has been found to be approximately equal to 80% of class A pan evaporation rates

(Kadlec, 1989). Although more precise estimates can be obtained, (Wossenu, 1996;

Brown, 1988) the techniques rely on copious meteorological data which is most often not

at hand or easy to measure.

A study conducted by Bavor et al. (1988) estimated ET from SSF systems via water

budgets. The study obtained the following results:

51 Cattails/gravel: ET = 1.128 x pan evap + 0.072 mm/d Bulrush/gravel: ET = 0.948 x pan evap - 0.027 mm/d Gravel/ no plants: ET = 0.0757 x pan evap - 0.028 mm/d

These values were used to determine ET rates in the SSF systems. Because of the year-

round low humidity and intense solar energy typical of southern Arizona, these values

may underestimate losses via ET. Table 12 lists evaporation, evapotranspiration and

precipitation rates for the B2C region along with estimated SSF evaporation rates. The

later assumes SSF wetlands planted with a monoculture of cattails.

In order to determine the amount of area required to evaporate all remaining water in

the final stages of a zero discharge system, Qe would be set equal to zero. The mass-

balance equation can thus be rewritten as follows:

Qin=QET+QlN~Qp

Since ET, IN and P are directly proportional to area, the equation can again be rewritten

in order to solve for the area required to make QET + -QP equal to Qj„:

Qin Area= ——

ET+IN-P

Zero-discharge systems are particularly attractive in arid regions because

evapotranspiration rates are always much greater than precipitation rates. Zero-discharge

is therefore a reasonable goal and can be accomplished with much less land than would be

required in other areas. This option was not considered for this study since zero-discharge

systems where all water exits via evapotranspiration result in resident water which is very

52

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53

high in salinity, undermining attempts to create quality wildlife habitat. The mass-balance

equations discussed above were used to determine the amount of make-up water the B2C

Wetlands would require given different wetland areas and inflow rates. These equations

were also used to determine the amount of salinization the B2C Wetlands would

experience from month to month.

Pre-Treatment

Prior to designing a treatment system, it was necessary to design SSF pretreatment

components. Each FWS system was assumed to have an identical SSF precursor. Since

effluent from these systems was influent for all FWS systems, water quality needed to be

determined before proper wetland sizing could be conducted. The treatment criterion of

the SSF component was to reduce fecal coliform levels by at least 50%. Reduction in

pathogen concentrations was desired to reduce potential health related risks. A secondary

goal was to reduce BOD levels to improve FWS water quality for wildlife use, but no

specific BOD reduction goals were set. A minimum SSF wetland size of 635 m2 was

determined for FC treatment goals with peak flow (Table 13).

A SSF system of this size would result in peak flow effluent with a FC count of

approximately 5000 CFU/ml and a mean peak flow with fecal coliform concentrations of

approximately 3 ,680 CFU/ml. These figures were obtained from the areal reaction rate

equation with an absolute peak flow of 237 m3/d and an average peak flow of 164.8 m3/d

with a K f c of 95 m/yr. Allowing for concentration from evapotranspiration (Table 12), a

final SSF effluent fecal coliform concentration of 5,120 CFU/ml for absolute peak flow

54

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55

and 3,782 CFU/ml for mean peak flow is predicted. SSF effluent concentrations for FC,

TN, BOD and TDS, calculated in a similar fashion but on a month-to-month basis are

listed in Table 14. Data from this table, averaged for mean peak flow, were used in

wetland water quality modeling for the treatment, habitat and hybrid systems. Note that

reaction rate constants for the SSF component, taken from Kadlec and Knight (1995),

reflect long-term averages and do not consider vegetation presence or type. It is well

recognized that planted SSF systems outperform unplanted systems. Furthermore, reaction

rate equations for SSF systems do not consider media type, probably due to an absence of

reliable data. Actual effluent concentrations are likely to vary greatly from month to

month. Figure 4 is a diagram of the complete pre-treatment system. The SSF component is

to consist of multiple cells in parallel and series, and was designed in such a manner as to

facilitate experimentation. Cell la is vegetated while cell lb is not. It was assumed that a

significant amount of nitrification occurs in vegetated cells, while non-vegetated cells,

without plants to create a rhizosphere, have higher rates of denitrification. It is important

to recognize that carbon loading may be necessary prior to cell lb in order to maximize

denitrification rates. Nitrogen removal efficiencies could be compared against cell 2, which

is to be vegetated.

Hydrology models for SSF precursors were not run for the treatment, habitat, hybrid

comparison study, but were run for the Biosphere 2 Center Constructed Wetlands

example at the end of Chapter 4. For the comparison study it is assumed that media

conductivity matches requirements for specific cell dimensions. For the B2C Wetlands (the

actual proposed system), a specific medium is recommended.

56

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58

Designing the Treatment System

The first step of the actual design process was to determine the average flows the

system would need to handle. These values were then substituted for Q in the reaction rate

equation. Once values for Cis Ce and C* had been entered, the equations were solved for A

(area). This determined the amount of land required to reduce TN effluent levels to 3mg/I.

Having determined the area required, the system was then designed as a single rectangle

with a length to width ratio of 1.25. Although not specified in this study, a treatment

wetland should consist of multiple cells in parallel and or series to allow one or more cells

to be shut down for maintenance while the others remain operational. Water was assumed

to be introduced evenly across the entry face (left) of the wetland. Flow was assumed to

occur uniformly across and to exit uniformly through the rear (right). Treatment efficiency

of each design was determined for TN and BOD.

Once treatment efficiency had been determined, HSI models were applied to each

system. Habitat value was determined by multiplying mean SI score by wetland area to

produce an HU score which represents overall habitat value provided by each system. The

treatment system was assumed to have 100% canopy cover of emergent vegetation.

Vegetation was further assumed to be composed entirely of cattails.

Designing the Habitat System

Habitat systems were based on maximizing HSI model variables whenever possible.

Influent flow, water quality and total wetland area were assumed to be identical to the

treatment system. Because flow through systems will in large part determine degree of

59

treatment, it was necessary to arbitrarily design the habitat systems. Designing was

accomplished using a random number generator and a systematic means of using these

random numbers to construct the wetlands. Area of habitat systems, identical to the area

of the treatment system, was divided in order to produce numerous, 10m x 10m cells. The

wetland was composed of the resulting number (n) of these smaller areas. A series of n-1

random numbers (1 through 4) were generated; one for each of the sub-area (minus one).

Sub-areas (cells) were assembled in a spreadsheet according to the number each was

assigned until all cells were connected resulting in a wetland of desired area.

A similar methodology was employed to determine the location of pockets of

vegetation and or open water areas within the wetland. Analysis of HSI models suggested

that a greater amount of dispersion between pockets of vegetation resulting in an area to

edge ratio of seven to one would generate high suitability indices. It was thus decided that

vegetation would be placed in order to produce a ratio as close to this value as possible.

This was accomplished by assigning each cell a random number. Cells containing an even

number received vegetation while cells containing an odd number remained empty. Once

exactly fifty-percent of all cells had been assigned emergent vegetation, the locations of

these pockets of vegetation were grouped or thinned in order to obtain an area to edge

index of seven. Actual cells were not rearranged, only the location of vegetation.

Three different habitat systems were constructed in this manner. Designing of multiple

habitat systems was necessary in order to explore the affect of arbitrary design on

efficiency and to rule out the possibility that an "extreme" design was unknowingly

utilized.

60

Once the habitat value of these systems had been calculated, flow through the systems

was determined so that appropriate reaction rate equations could be applied. Water was

again assumed to be introduced to the wetland from the entry face and to exit from the

rear. When multiple cells occupied the face and identification of a single cell of

introduction was not possible, it was assumed that water was introduced evenly to those

cells. When no single exit cell was identifiable, it was assumed that water would exit from

all adjoining rear cells.

Manning's equation with appropriate friction coefficients (Chow, Maiden and Mays,

1988) was used to determine flow volume which would occur in both vegetated and

unvegetated areas:

V=±-^-R1,3Sf12

n

where V = velocity R = hydraulic radius S f= friction slope

n = Manning roughness coefficient

For flow through vegetated cells, a roughness coefficient of 0.1 was used. This is used to

describe flow through natural, winding channels with heavy brush and timber. Flow

through open areas was assigned a roughness coefficient of 0.05, which corresponds to

flow through winding natural channels with weeds and pools, mimicking flow through

submerged vegetation, a condition mandated by HSI models.

Volumetric flow has two components: velocity and cross-sectional area of the channel

through which water is flowing. Notice in the above equation that velocity is inversely

61

proportional to Manning's roughness coefficient. Because all other variables in Manning's

equation did not vary between vegetated and nonvegetated cells, and because the

roughness coefficient for vegetated cells is exactly twice as large as for nonvegetated

cells, only half the flow from a preceding open cell was assumed to flow into vegetated

cells. Remaining flow was added to flow occurring in adjacent open cells. When an open

cell was surrounded by vegetated cells, water velocity (and thus volumetric flow) in the

open cell was assumed to be identical to vegetated cells. In situations where two or more

open cells lay juxtaposed in the direction of flow, velocity in these cells was assumed to be

twice as large as in adjoining vegetated cells.

Modeling Flow Through Wetland Designs

Because the areal reaction rate equation used in water quality modeling is dependent

upon volumetric flow rate, it was necessary to determine as accurately as feasible, the

volume of water entering each cell. It was also necessary to know from which cells water

had come so that appropriate influent concentrations could be used.

As flow is traced through a wetland, the channel morphology changes, sometimes

widening and sometimes narrowing. In order to describe water movement in this dynamic

situation, a path of principle flow was determined for each system. This was accomplished

by examining wetland designs in spreadsheet format, and tracing the simplest most direct

path from face to rear. This path was assumed to contain the highest volumetric flow

rates. Once this path was identified, individual flow lines were drawn to described flow

direction in each cell.

62

As mentioned earlier, volumetric flow is defined as the velocity of water multiplied by

the cross-sectional area of the channel through which it is traveling. Velocity components

were determined using vector math to describe flow volume.

Effects of Wetland Morphology on Flow

In normal flow through a rectangular channel, flow is contained by the boundaries of

the channel itself. Once the channel widens, however, a portion of flow will expand into

the surrounding empty areas. The amount of flow which was assumed to deviate from the

main flow path was determined to be equal to the principal flow multiplied by the cosine

of the angle of the new direction of flow (see figure 5). This value represents the

magnitude of the velocity vector (and thus quantity of water) in that direction. When

channel narrowing occurred, water in affected cells was assumed to follow the direction of

flow determined for that cell (figure 6). Half of flow from a preceding cell was assumed to

enter cells on the edge of a wetland where narrowing occurs. When flow was interrupted

by an island, flow was split evenly around the object (Figure 7).

Water Quality Modeling

Once flow paths had been defined, the appropriate reaction rate equations for TN and

BOD were applied to each cell depending on presence or absence of emergent vegetation.

Each cell had a Cs and Ce for BOD and TN. Ce for one cell was Q for the next as

determined by flow patterns, with a corresponding final volume and Ce for BOD and TN.

Water loss via evapotranspiration or evaporation was subtracted from each cell in order to

63

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66

account for the concentrating effect of dissolved pollutants. Although contributions from

precipitation were found to be insignificant in affecting pollutant concentrations at the

0.01 mg/1 level, they were nontheless considered.

The treatment efficiency for these systems was determined as done for the treatment

wetland by dividing concentration of pollutant in influent by that of the effluent and

multiplying by 100% (i.e., percent removal). This was done for BOD and TN only.

Although K values are given by Kadlec and Knight (1995) for TSS, FC mid TP, data were

not available from the NAWWQT database (1994) to determine K values for emergent

vegetation and submerged vegetation. Thus reduction of these pollutants could not be

modeled on a cell to cell bases.

Designing the Hybrid System

Once treatment and habitat systems had been designed and evaluated, limiting factors

of each were identified. In this process, those characteristics which reduced HUs in the

treatment system and those characteristics of the habitat systems which reduced their

treatment efficiency were isolated. A system was then designed (the hybrid) in which these

limiting factors were eliminated to produce the highest possible combination of HU and

treatment efficiency.

K t n and Kbod Calibration

A total of four systems met selection criteria for KTO and KBOD calibration. For BOD,

Shellbyville, Missouri, Leaf River, Mississippi and Benton, Kentucky were used. For total

67

nitrogen, Leaf River, Mississippi, Des Plaines, Illinois and Benton, Kentucky were used. It

was not possible to use the same sites for KBOD and KTO calibration due to an absence of

relevant data at Des Plains (no BOD data) and Shellbyville (no TN data). The purpose of

these criteria was to select systems closely resembling the treatment system to be designed

herein and to determine the treatment which occurs in vegetated areas. Appendix A

contains raw data from sites which were used in K calibration. For each month data

existed, KTO and or KBOD values were calculated and averaged seasonally. Seasonal

averaging was used because data were often only given seasonally. Although it may seem

like this technique reduced the number of data points available for analysis, the number of

true data points used was increased, since many of the seasonal averages listed were

averaged from three data points. In determining KBOD, months for which BOD influent

was less than or equal to 15 mg/1 were not considered since KBOD levels for these months

were unrealistically low. Also, when effluent concentrations were below background rates

(6.5 mg/1), background rates were assumed to be zero. This allowed these data to be

included but did not inflate K values; assuming a zero background rate is conservative,

resulting in lower K values than with non-zero background rates. Table A. 1 (Appendix A,

p 142) summarizes KTO and KBOD values as determined from data in the NAWWQT

database. A total of 42 data points were available for KTO determination and 37 for KBOD.

The average KTO value was 32.2 m/yr with a standard deviation of 22.1 and a coefficient

of variation of 68%. Statistical analyses determined that the KTO data were significantly

different from a normal distribution (Shapiro Wilks, a=0.05, p=0.02). Accordingly, it is

more appropriate to use a five number summary to describe the KTO values calculated for

68

these systems (Figure 8). The 10th, 25th, 50th, 75th, and 90th percentile KJN values were

used to model water quality in the different systems.

Mean KBOD was determined to be 48.3m/yr with a standard deviation of 22.2 and a

coefficient of variation of 46%. Although these data were not significantly different from a

normal distribution (Shapiro Wilks, a=0.05, p=0.2289), the five number KBOD summary

was also used for water quality modeling (Figure 9). Because the 0th percentile has a

negative value, it could not be used to model water quality. Although it is realistic to

expect a wetland to actually contribute BOD above and beyond levels present in influent

under certain conditions, the negative coefficient had the effect of greatly exaggerating

the amount of BOD which might be added. For this reason, the 10th and 90th percentiles

were used for both KTO and KBOD for water quality modeling in lieu of the minimum and

maximum values.

K t o and Kbod values determined in this manner are larger than the K20 values suggested

by Kadlec and Knight, who recommend 18 m/yr for TN and 36 m/yr for BOD (Table 10).

It should be anticipated that wetlands with close to 100% emergent vegetation cover, as

was assumed for the sites chosen for K determination, will have greater relative K values

due to the extra surface area provided by the abundant vegetation and accordingly, these

results are not surprising.

No data existed in the NAWWQT database (1994) for constructed wetlands using

submerged vegetation. Kadlec and Knight (1995) list a mean KTO value for a constructed

wetland using submerged vegetation in Richmond, New South Wales at 14.76 m/yr. This

value was used to characterize wastewater treatment in open areas of the wetlands. The

variability of this figure was assumed to be proportional to that of the KTO values

69

KTN (m/yr)

100

90

80

70

60

50

40

30

20

10

Maximum Extreme

90th Percent!

75th Percentile

50th Percentile

25th Percentile

— 10th Percenti L

Minimum Extreme

90%: 44.8 75%: 33.4 50%

Figure 8. 5 number summary for KTN from three North American Constructed Wetlands. 10th and 90th percentile values are also shown.

70

KBOD (m/yr)

100

90

80

70

60

50

40

30

20

10

- 1 0

Maximum •extreme —- —

90th Percentile

75th Percentile

50th Percentile

25th Percent

10th PercentiJ

Minimum Extreme

;.le

90%: 80.45m/yr 75%: 67.87m/yr 50%: 45.33m/yr 25%: 32.06m/yr 10%: 24.95m/yr

Figure 9. 5 number summary for KBOD from three North American Constructed Wetlands. 10th and 90th percentile values are also shown.

71

calculated for vegetated areas. Accordingly, percentiles for this value were extrapolated

from vegetated KTO values, with 14.76 m/yr as the median. All KBOD values for submerged

vegetation were also extrapolated from this figure. It was assumed that BOD reduction in

areas of submerged vegetation would be smaller than BOD reduction in areas of emergent

vegetation and that the difference would be proportional to the difference seen in these

two areas with TN reduction. Because the primary mechanism for BOD and TN reduction

are in many ways similar (i.e., bacterial action), this is a reasonable assumption.

Kbod for submerged vegetation was assumed to have a variability identical to that of KB O D

for emergent vegetation, with percentiles calculated accordingly (e.g., the 90th percentile

KBODemergent was 1.77 times larger than the median value; the 90th percentile KBODsubmeigen,

was then assumed to be 1.77 times larger than the median KBODsubmergent).

CHAPTER IV

RESULTS AND DISCUSSION

This chapter first presents the designing of the treatment system according to areal

reaction rate equations for total nitrogen with a goal of reducing concentrations to 3 mg/1.

Flow and water quality were then modeled for this system. Three habitat systems were

next designed according to the methodology described in the preceding chapter, with an

area equal to that of the treatment wetland. Habitat units for all four systems were next

computed. The habitat systems were compared to each other in order to determine the

relative amount of variability in habitat quality and water treatment efficiency. This

variability is a result of differences in wetland shapes, vegetation placement and flow

characteristics. The systems were then compared to each of the other three in order to

determine what, if any limiting factors existed in habitat quality and treatment efficiency.

Limiting factors identified, the hybrid system was developed. After calculation of

habitat units and treatment efficiency, the hybrid system was compared to the others. This

comparison allows a quantified measure of the hybrid system's success at providing both

treatment and habitat services and was the basis for testing the hypotheses of this thesis.

In the final section of this chapter, the information gained in this endeavor is put to

72

73

practical use in the design and proposal of an actual system to treat wastewater at the

B2C; the Biosphere 2 Center Constructed Wetlands. The expected performance of the

resulting system in terms of wildlife habitat production and treatment efficiency is also

given. Specific design considerations for the SSF component of the B2C Wetlands are also

covered in this section.

Treatment, Habitat and Hybrid Systems

The Treatment System

The most efficient use of wetland space occurs when flow is evenly distributed

throughout the system. This avoids "dead spots" which reduce efficiency by consuming

space without treating water. The easiest and most cost effective way to engineer such

systems is by constructing a shallow rectangle. Kadlec and Rnight (1995) suggest a length

to width ratio of approximately 2:1, although their reasoning for doing so is based on

economics rather than treatment efficiency. The FWS treatment system designed for this

study was designed with a length to width ratio of 1.25 and a mean depth of 0.6 m. It was

assumed to contain a monoculture of cattails (Typha sp.) with no open areas. A free-board

of at least 0 .3 m is recommended to avoid problems during periods of peak flow.

The wetland area required to meet treatment goals was determined via reaction rate

equations using median KTO values previously determined. This procedure determined that

a nominal wetland area of approximately 0.8 hectares (2 acres) would be required

74

(Table 15). The dimensions of the wetland were set at 80m by 100m following the above

listed aspect. Figure 10 shows the basic treatment system as it appears in spreadsheet

format, ready for flow and water quality modeling. Figure 11 show flow as it was modeled

for the treatment wetland.

Habitat Systems

Evaluation of the HSI models (appendix B) revealed 5 important variables which could

be manipulated to increase the habitat value of a wetland. These variables included the

location of vegetation within the wetland, the depth of the wetland, the amount and

composition of emergent vegetation, and the existence of submerged vegetation. Other

variables included in the models were considered to be basic characteristics of constructed

wetlands and could or would not be controlled. These included the water regime and the

presence of larvae of emergent insects. Water regime, for instance, would remain a

function of wastewater production (as is the case for the treatment wetland). Table 16 lists

maximum HSI variable values for each model species. Table 17 lists values for these

variables which generate the highest combined SI scores for all models to which they

apply. These maximized variables were then used in the design of the habitat systems.

The habitat systems, named habitat systems 1 through 3, are shown in figures 12, 13

and 14. Emergent vegetation placement is indicated on each figure. The mean depth of

these systems was set at 23 cm, with each cell representing an area of 100m2 having

dimensions of 10m x 10m. Flow was modeled for each of the habitat systems according to

75

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Table 16. HSI Model Species with Associated Variables

Model Species Variables Condition Generating Max SI

Marsh Wren Percent canopy cover of emergent herbaceous plants 80% Water depth (m) >0.14

Percent canopy woody vegetation 0% Emergent hydrophyte type cattail

Muskrat Percent canopy cover of emergent vegetation 50-80%

Percent of year with surface water present 100%

Percent emergent vegetation consisting of cattail 80-100%

Emergent vegetation is broad leaved monocots

Red-winged Water regime Blackbird Presence of carp within wetland

Presence of larvae of emergent aquatic insects

Emergent herbaceous cover

yes

present year round

no

yes

open water = covered water

Percent of open water with submerged vegetation 80-100% Yel low-headed Length of PEM in contact with open 7-8

water blackbird Edge index 8

Percent of vegetation that is robust 100% Average water depth beneath emergent + 15cm

vegetation during spring

Length emergent vegetation / open water American Coot Water regime code

Percent of wetland dominated by herbaceous vegetation

4-5 semi-permanently

flooded 40-60%

Great Egret Percent of wetland with water depth 10-23cm 100%

Percent of vegetation cover in areas of above depth 40-60%

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the methodology described in the previous chapter. Figures 15, 16 and 17 represent flow

patterns determined to exist in each of these systems. Once again, mean peak flow

estimated from target visitor counts was used for influent flow.

Water Quality Modeling

TN and BOD attenuation models for the habitat and treatment systems are shown in

appendix C. Figure 18 shows the performances of the habitat and treatment systems using

10 to 90th percentile KTO and KBOD. Average percent removal of TN and BOD in the

habitat systems with median KTO and KBOD was 71.3% and 69.1% respectively. Percent

removals realized by the treatment system, also using median KTO and KBOD values, were

89.7% and 79.1%. Not only did the treatment system have the highest percentage removal

efficiency, it also had the least amount of variability. Habitat systems varied considerably

between and among themselves. This was expected, and involves the amount of flow

which passes through pockets of emergent vegetation and the number of dead spots within

each. Both of these characteristics varied between different habitat systems. Habitat

system I had the poorest removal efficiency of the habitat systems with a TN percent

removal ranging from 18.9% to 81.3%. Habitat II had the greatest treatment efficiency

with a TN percent removal ranging from 33.7% to 93.3%.

Habitat Unit Determinations

The first step in HU calculation concerns determination of SI scores for each of the

model species. This was conducted for each of the four wetlands. Appendix D provides

84

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results of each model for each wetland. Models for the American coot, great egret and

muskrat were weighted by multiplying their SI scores by three. This was done because the

marsh wren, yellow-headed blackbird and red-winged blackbird occupy the same feeding

and cover niches (Figure 3). Giving all species equal weight would have resulted in SI

scores more strongly favoring the niches shared by these three species. Because a greater

number of niches is desired when creating wildlife habitat (Livingston and Loucks, 1978;

Zedler and Zedler, 1992), weighting was undertaken. SI scores were multiplied by wetland

area (assumed to be one covertype). Resulting HUs determined for each species were

averaged for each system (Table 18). Notice that there is very little variation among the

habitat systems. Again, this was expected, since only one HSI variable, edge index,

changed between habitat wetlands. There was however, a significant difference between

the number of HUs the habitat systems received and the number determined for the

treatment system. The habitat systems had an average of 5,459 HUs compared with 3,824

HUs for the treatment system.

Discussion of Limiting factors

Two characteristics of the habitat systems were identified which limited their treatment

capabilities: wetland morphology and vegetation. Morphology of the arbitrarily designed

systems was not conducive to even flow, resulting in large dead zones. Also, flow tended

to remain concentrated in a small number of cells, as water sought the simplest path from

inlet to outlet. Having large amounts of flow in few cells reduces contact time and thus

treatment efficiency.

89

Table 18. HEP Summary for Habitat and Treatment Systems with HU Calculations

Wetland Species Weighted

H.S.I. Weight H.S.I. Area (mA2) Habitat Units

Habitat I American Coot 0.26 3 0.78 8000 6240 Great Egret 1.00 3 3.00 8000 24000 Marsh Wren 0.46 1 0.46 8000 3680 Muskrat 0.95 3 2.85 8000 22800 Red-winged Blackbird 1.00 1 1.00 8000 8000 Yellow-headed 0.73 1 0.73 8000 5840

Blackbird Mean: 0,73 0.74 4704

Habitat II American Coot 0.21 3 0.63 8000 5040 Great Egret 1.00 3 3.00 8000 24000 Marsh Wren 0.46 1 0.46 8000 3680 Muskrat 0.95 3 2.85 8000 22800 Red-winged Blackbird 1.00 1 1.00 8000 8000 Yellow-headed 0.89 1 0.89 8000 7120

Blackbird Mean: 0.75 Mean: 0.74 4709

Habitat III American Coot 0.21 3 0.63 8000 5040 Great Egret 1.00 3 3.00 8000 24000 Marsh Wren 0.46 1 0.46 8000 3680 Muskrat 0.95 3 2.85 8000 22800 Red-winged Blackbird 1.00 1 1.00 8000 8000 Yellow-headed 0.88 1 0.88 8000 7040

Blackbird Mean: 0.73 Mean: 0.74 4704

Treatment American Coot 0.00 3 0.00 8000 0 Great Egret 0.00 3 0.00 8000 0 Marsh Wren 1.00 1 1.00 8000 8000 Muskrat 0.95 3 2.85 8000 22800 Red-winged Blackbircl 0.30 1 0.30 8000 2400 Yellow-headed 0.63 1 0.63 8000 5040

Blackbird Total: 2.88 Mean: 0.40 2549

90

The second limiting factor to treatment efficiency, emergent vegetation cover, is in

direct conflict with HSI model maximization. It was earlier concluded that cells with

emergent vegetation will have greater treatment capabilities than open cells. Therefore, a

100% emergent vegetation cover should yield maximum removal efficiencies. HSI model

maximization however, states that only fifty percent of the wetland should contain

emergent vegetation. Following this requirement, it was necessary to sacrifice some

treatment efficiency to maximize habitat quality, or vice versa. Placement of vegetation

however, can be controlled, and was found to be of great importance. It was observed that

pockets of vegetation were often located such that water flowed around them, following

the path of least resistance. It should be possible to position pockets of emergent

vegetation in such a manner as to force water through them. Doing so will maximize the

benefit realized by emergent vegetation which is present. Habitat system II had the highest

treatment efficiency of the habitat systems due to the fact that it does not display the two

major problems discussed above. It is elongated, containing few branches, the presence of

which led to dead spots in other systems. Because it was elongated, water was usually

forced to flow through the existing pockets of vegetation. This finding suggests that it is

possible to create efficient systems which also offer quality wildlife habitat.

The two major limiting factors for habitat quality in the treatment system were the

complete canopy cover and low edge index. The edge index is a function of the ratio of

wetland area to the amount (length) of wetland/vegetation edge; the greater the length of

shore line and the greater the amount of emergent vegetation adjacent to open areas, the

higher the edge index. Higher edge indices generated higher SI scores. Complete canopy

91

cover and regular shore lines of the treatment system gave low scores for both of these

important variables. Reducing canopy cover and making shore lines irregular while

reducing the size of pockets of vegetation would greatly increase HUs in this system.

Hybrid

The hybrid system displayed in spreadsheet format in Figure 19 was designed to avoid

many of the limiting factors, while remaining a practical engineering design. It is long and

relatively narrow (aspect= 2.6 at widest point), with bands of emergent vegetation

separated by areas of open water. Placing vegetation in bands assures that water flows

through pockets of emergent vegetation. Three islands were included to promote even

flow through areas where channel width increases. Increasing channel width (i.e.,

producing uneven shore lines) was essential to increasing the edge index. The islands also

increase edge. Although not quantifiable in this study, islands are important features for

many ground-nesting wetland birds and semi-aquatic organisms, providing protection from

predation and human disturbance. Figure 20 shows flow patterns through the hybrid

system, while water quality modeling is shown in Appendix C. Table 19 summarizes

results of water quality modeling. Note the even flow which occurs through this system

with the exception of flow around islands, where flow is concentrated in two paths. Had

islands not been present much less flow would have occurred near edges of the wetland.

Results of HSI models run on this system are shown in appendix D while Table 20

92

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summarizes SI computations and provides HU calculations. Notice that the hybrid system

actually generated more HUs than any of the habitat systems since the habitat systems

were generated in an arbitrary fashion making morphology, and thus edge index,

uncontrolled. In designing the hybrid system this variable could be manipulated, resulting

in a higher SI score and thus a greater number of HUs.

Testing the Hypotheses

Figures 21 and 22 compare TN and BOD removal efficiencies in the five different

systems. In BOD removal efficiency, the hybrid system outperformed all of the habitat

systems and had less variability. Differences in performance between the hybrid and habitat

II system, however were very slight. Reduction in variability experienced by habitat system

II, the hybrid and the treatment system is due to the fact that these systems are expected to

be operating at near maximum efficiency (i.e., reducing BOD levels to near background

rates). Effluent BOD from the hybrid system was predicted to be lower than in any of the

habitat systems with the exception of habitat system II. Statistical analyses indicated that

system BOD removal efficiencies were significantly different (Kruskal-Wallis chi-square

approximation, a = 0.05, p=0.0001). A Student- Newman- Keuls test run on ranked data

(a = 0.05) grouped the systems into three different groups. The first group consisted of

the treatment, hybrid and habitat II systems. The second group consisted of the hybrid,

habitat II and habitat III systems, with habitat system I alone comprising group 3.

In terms of TN reduction, the hybrid again out preformed all of the habitat systems,

Table 20. HEP Summary for the Hybrid System

96

Wetland Species H.S.I. Weight Weighted

H.S.I. Area (mA2) Habitat Units Hybrid American Coot 0.22 3 0.66 8000 5280

Great Egret 1.00 3 3.00 8000 24000 Marsh Wren 0.46 1 0.46 8000 3680 Muskrat 0.95 3 2.85 8000 22800 Red-winged Blackbird 1.00 1 1.00 8000 8000 Yellow-headed 0.93 1 0.93 8000 7440

Blackbird Mean: 0.76 0.74 4746.67

97

Percent BOD Removal

100

90

80

70

60

50

40

30

20

10

¥ ¥

Hybrid HB I HB III HB II

Figure 21. 5 number summary with 10th and 90th percentiles used in lieu of min and max, for BOD removal efficiencies in habitat, hybrid and treatment systems. HB is Habitat System. Maximum posible efficiency with background rate of 6.5mg/l is 79.14%.

98

Percent TN Removal

100

90

80

70

60

50

40

30

20

10

HB I HB III HB II Hybrid Treatment

Figure 22. 5 number summary with 10th and 90th percentiles used in lieu of min and max, for TN removal efficiencies in habitat, hybrid and treatment systems. HB is Habitat System.

99

although the difference between TN removals for habitat II and the hybrid system was

again very slight. Statistical analyses failed to demonstrate that the TN removal efficiencies

of different systems were significantly different (Kruskal-Wallis chi-square approximation,

a = 0.05, p= 0.4772). Failure to demonstrate significant difference is believed to be due to

within system variability.

Figure 23 provides a graphical comparison of mean SI scores each system received.

HUs are not used here because wetland areas were defined as equal and using SI scores

better demonstrates differences between systems. The hybrid system received the highest

mean weighted SI score, with 0.742. The habitat II system came in second with 0.736,

while habitat systems I and III were tied with both receiving 0.735. The treatment system

received the lowest weighted mean SI score, with 0.398.

Table 21 summarizes data used to compare the different systems. Median TN and

BOD removal efficiencies are listed to simplify comparisons. It should be remembered

however, that a more accurate comparison requires a comparison of the full range, as was

provided in Figures 21 and 22.

In order to determine the extent to which the hybrid design was successful in increasing

wildlife habitat quality without substantially lowering treatment efficiency, it is

instructional to look at the percent increase in habitat quality (HU) per percent decrease

in median treatment efficiency. That is, exactly how much treatment efficiency is sacrificed

to increase habitat quality? An increase in wildlife habitat quality of 63% was realized by

the hybrid system over the treatment system. At the same time, median TN removal

efficiency was only 9% lower in the hybrid system while median BOD removal efficiency

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was only 2% lower. Based on median TN efficiency drop, a ratio of habitat quality

increase to treatment efficiency decrease of 7 to 1 is obtained. According to this ratio, it is

possible to double the quality of wildlife habitat with an associated drop in treatment

efficiency of only 7.1%. This quantitatively demonstrates that the design of the hybrid

system was successful in substantially raising wildlife habitat quality without substantially

lowering treatment efficiency. Drop in efficiency however, would require greater wetland

area (about 7%) to achieve the same absolute reduction in TN.

The Biosphere 2 Center Constructed Wetlands

The Biosphere 2 Center Constructed Wetlands was sized to treat a normal flow of

20kgpd, with a peak flow of twice this amount (40kgpd) and a low flow of half (lOkgpd).

Low and peak flows were assumed to occur during periods of lowest and highest visitor

counts. In order to meet these criteria, the wetland needed to be small enough that effluent

during low flow would not contain TDS concentrations incompatible with wildlife use

while being large enough to meet treatment goals for peak flow. With a peak flow

estimated at four times low flow in an arid region with low flow occurring during the

months of greatest evapotranspiration, this presented quite a challenge. The wetland also

needed to be designed according to lessons learned from the conception and testing of the

hybrid system. It had originally been planned to use the hybrid system design for the B2C

Wetlands. An absence of suitable sites however, made this impossible.

103

SSF Sizing

The SSF component of the B2C Wetlands is identical to the other systems, consisting

of three separate cells in series and parallel with a combined area of 635 m2. Table 22

summarizes physical parameters of three SSF cells while Figure 24 is a scaled

representation. The three systems needed to be filled with a medium capable of conducting

40kgpd. Ergun's equation modified for turbulence was used to determine acceptable

medium conductivity. This procedure suggested a clean medium with a hydraulic

conductivity of 2,647 m/d would be needed for SSF wetlands with dimensions given in

Table 22, should they be required to conduct 40kgpd at maturity. In order to conduct the

target peak flow of 62,616 gpd, a clean medium with a hydraulic conductivity of 4,144

m/d would be needed. Both of these conductivities can be achieved by using a very course

sand with a mean particle diameter of >0.7cm. It is recommended that gravel with a mean

diameter of more than 1cm be used in order to keep estimates conservative and minimize

possible future clogging and overflow problems. Calculations used to make the above

determinations concerning medium hydraulic conductivity are summarized in Table 23.

Required particle size was estimated from Kadlec and Knight (1995).

Planting cell la with bulrush and cell 2 with cattails should allow investigation into the

performance of these different plant species. Swivel pipes should be placed as outlet

structures to each cell to allow control over exit water depths. This extra expense gives

managers some measure of control should hydraulic problems develop later. The control

structure between cells la and lb should be designed to allow carbon loading should

carbon prove limiting to denitrification in cell lb. This would also provide a unique

104

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opportunity to conduct detailed experimentation into the effects of carbon loading on

denitrification rates, as well as facilitate water quality sampling for effluent from cell la.

Treatment goals

The B2C Wetlands were designed to operate under an individual aquifer protection

permit. Standard water quality criteria for operation under an individual permit are site

specific. As with a general permit, the primary pollutant of concern for the B2C Wetlands

would be total nitrogen, which must be in the range of 1 to 10mg/l. The exact permitted

limits or ranges are determined on a site to site basis. For this reason, the B2C Wetlands

will be tested to determine if TN levels can be reduced to 10mg/l at all flows, using the

10th percentile KTO. A second water quality parameter of concern is TDS. Because this

wetland is being designed to support wildlife, TDS levels should not be allowed to exceed

2000 mg/1 when possible, and should never be allowed to exceed 3000 mg/1. Salinity levels

between 1000 and 2999 were reported by the National Research Council Committee on

Water Quality Criteria, NRCCWQC, (EPA, 1972) to be very satisfactory for all classes of

livestock and poultry. Waters with concentrations above 3000 mg/1 are listed as poor

waters for poultry, thus setting the upper limit for use with the B2C Wetlands.

Salinity levels are also of concern with plants. The NRCCWQC states that waters with

500-1000 mg/1 can have detrimental effects on sensitive crops, and that use of waters with

salinity levels between 1000 and 2000 mg/1 requires careful management practices. Use of

waters with salinity above 2000 mg/1 is recommended for tolerant plants only. These

108

criteria, however were developed for irrigation purposes and are not directly applicable to

hydrophytes. Irrigated soils will rapidly accumulate salts when salinities in irrigation water

are high due to evapotranspiration. In an aquatic environment the same phenomenon will

occur. In this setting however, there will always be less saline water to dilute salt

accumulation, and serve as a transport mechanism to remove salts from the soil. This does

not mean that salinity is not a concern in aquatic environments, only that limits set for

terrestrial irrigation practices can not be directly applied to aquatic situations.

Furthermore, during periods of peak flow when salinity concentrations are lowest, many

of the salts which do accumulate in soils will be flushed out. In conclusion, it is doubtful

that hydrophytes could thrive for extended periods of time in salinity concentrations at

3000 mg/1, but would be expected to survive. This is especially true for cattails, which are

tolerant of higher salinity levels.

Site identification

There are a number of general concerns designers must consider when choosing a

location for development of a constructed wetland. These include adequate land

availability, location of site in relation to wastewater sources and probability of flooding

during heavy rain events. For the B2C Wetlands, and for any wetland seeking to provide

wildlife habitat, some additional requirements for site location include the distance to areas

of heavy traffic and the presence of wildlife corridors.

First and foremost, enough land must be available to allow construction of a wetland of

desired size. Second, this land must be topographically suited for development. Sites

109

which require extensive earth movement will be much more expensive to develop and may

cause the wetland option to become cost prohibitive. Because of its location at the foot of

the Catalina Mountains, few sites exist which are topographically suitable. This was a

major limiting factor to site selection. Three sites were identified as potential locations

based upon their topography (figures 25 and 26). Site one is located in what is currently a

non-paved auxiliary parking lot, which is seldom if ever utilized to capacity. A portion of

this parking lot could be used to construct a wetland. This location however, is at an

elevation significantly higher than the source of most wastewater. This means that

wastewater would need to be pumped up to the wetlands. This is not seen as a viable

option due to the required infrastructure development and long-term costs associated with

pumping water. There are however, a couple of advantages to locating the wetland uphill

of wastewater production beyond the fact that land manipulation would be minimal at that

site. These include protection from flooding and the possibility of discharging reclaimed

water into a wash running between the B2C apparatus and education center. This water

could be used in an effort to reconstruct riparian habitat along the aforementioned wash. It

is not believed however, that these benefits outweigh the disadvantages, or that the limited

amount of riparian restoration, which would be located in areas of high traffic, would

result in increased ticket sales. The remaining two sites, sites 2 and 3 (figure 24) are both

located downstream of most wastewater production, but are located immediately adjacent

to a dry creek bed. Wetlands at these locations could be subject to flooding should a

significant rain event occur. The cost of building diversionary dykes to prevent such

flooding, however, is far cheeper than the perpetual cost of pumping water would be, or

110

of Biosphere 2 Center

to 500 feet

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Figure 26. Topographicalirrap of Biosphere 2 Center Campus, major visitor areas. Scale = 1 inch to 500 feet.

112

grading steeply sloped land. Site 2 is relatively protected from human disturbance

although it is located immediately adjacent to a road which is used by students traveling to

and from student housing. Traffic on this road is light. Site 3, located to the south of the

student housing, is extremely well protected from disturbance, and would be well suited

from a wildlife perspective as it is surrounded by relatively undisturbed level land. Wildlife

corridors would not be a problem here. Site 2 has a significant corridor running uphill to

the north-east. Land across the road to the west is also relatively undisturbed. Peak non-

bird wildlife use would be expected to occur at night (deserts have a high percentage of

nocturnal animals) when crossing the road would not present a significant problem.

Site 2 is located at an elevation approximately 45 feet higher than the student houses.

In order to be treated in the constructed wetlands, wastewater generated there would need

to be pumped to the wetlands. Although this is a significant draw-back to using site 2, it is

off-set by its proximity to the B2C tour routes. A wetland located at site 2 could be added

to existing tours. A major contention of this thesis that a well designed constructed

wetland could significantly increase ticket sales. A wetland located at site 3 could not be

added to existing tours; it is simply too far for most people to walk in the Arizona sun. A

wetland at site 3 would however retain its educational value for Columbia B2C students,

as well as its research potential. The above arguments duly considered, it is recommended

that the wetlands be located at site 2. The potential for public education in water and

wildlife conservation and increased ticket sales outweigh the disadvantages of this site.

113

Infrastructure Development

As previously mentioned, wastewater is currently treated in 20 septic tanks and is

disposed of in subsurface drainage fields. In order to minimize infrastructure development,

these septic tanks should be retained. Pipes would be required to conduct water from

septic tanks to wetlands. This could be done by splicing pipes prior to entry into drainage

fields and linking pipes from different wastewater sources as topography permits. Any

water treatment facility, including a constructed wetland, will require a significant amount

of ground disturbance in order to link sources of wastewater, which are spread out over

the B2C campus, often separated by significant changes in elevation and paved paths.

Wetland design

Analyses of topographical maps suggested that a wetland of 1.25 hectares (3.1 acres)

could be constructed at site 2 with a minimum of land manipulation, although some

grading would be required. A major concern with using a wetland of this size is that

evapotranspiration would result in unacceptable TDS concentrations. Table 24 shows

results of mass balance calculations for a 1.25 hectare B2C Wetlands receiving 20kgpd,

while Tables 25, 26 and 27 show the same calculations for an inlet flow of 10 kgpd,

30kgpd and 40kgpd. It is obvious from these data that a wetland of this size is not

appropriate year round. In August for instance, a wetland of this size receiving 20kgpd

would have a negative water budget of 69.5m3/d, or 18,362gpd. This is almost as much as

the original waste stream. The addition of make-up water to offset this water deficit and

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keep TDS levels below 3000 mg/1 (the upper limit established earlier) would require 84.7

m3/d, or 22,378gpd. Clearly this is not an option. The same sized wetland receiving

40kgpd would only require make-up water during the month of August, when 16.4 m3/d,

or 4,333gpd, would need to be added in order to keep TDS concentrations below 2000

mg/1 (the preferred salinity limit). The addition of 16.4 m3/d is seen as a realistic option.

During periods of low flow (lOkgpd) a wetland this size would only be operable during

the months of December, January, February and March, when evapotranspiration rates are

lowest.

The data suggest that the wetland be divided into two large cells. During peak flow, or

normal flow during months of low evapotranspiration, the full 1.25 hectares would be

used. In months with reduced flow or high evapotranspiration rates, only one cell would

be used. Figure 27 shows the Biosphere 2 Center Constructed Wetlands, with 2 cells, A

and B. Topographic lines have been included to give an idea as to the extent of earth

works which would be required. Cell A is located to the north-west of cell B. During

periods of high flow/ low evapotranspiration rates, water is to enter cell A, and then flow

into cell B. The two cells are divided by a berm and a difference in elevation of five feet.

Figure 28 shows a cross-sectional view of the wetland cells. This diagram is not to scale.

Water introduced to cell A cascades down a ten foot concrete or rip-rap spill-way. This

serves to oxygenate the water. If desired, this spill-way could be fashioned into an

aesthetically pleasing waterfall. After passing through cell A, water passively flows over

the berm separating cells A and B. Water then flows down a five foot concrete or rip-rap

spill way into cell B. During periods of low flow, only cell B would be utilized. Tables 28,

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29 and 30 show water budgets for cell B receiving 10 kgpd, 20 kgpd and 30 kgpd.

Because there were no months for which cell B has a water deficit when receiving 30

kgpd, mass-balancing was not conducted for cell B only, receiving 40kgpd. A potential

draw back with this strategy is that wetland plants in cell A may die when flow to that cell

is cut-off Unfortunately, the months during which this cell is to be used for water

treatment are late fall, winter and early spring months. Complete regrowth should

therefore not be expected should plants in cell A die. Accordingly, it is necessary to keep a

portion of them alive during summer months. It has already been concluded, however that

keeping this cell online during these months is not an option. As a possible solution to this

problem, the soils in this cell could be layered (Figure 29). The top layer would consist of

a semi permeable clay, with a thick growing medium of sand underneath. Below the sand

is an impermeable clay cap. A small amount of make- up water would then be added at

specific locations throughout the cell where the upper-layer of clay is absent.

Theoretically, water should travel through the sand medium beneath the clay, preventing

complete desiccation of the soil, and allowing a percentage of the plants to survive.

Unfortunately no estimates are available to determine how much make-up water would be

required or how saline the soil would become. A second alternative could be to bring in

species which are more accustomed to seasonal desiccation. This problem warrants further

discussion and could ultimately require redesigning of the wetland.

Treated water would be discharged at the southeastern end of the wetland and should

be of sufficient quality to permit direct surface discharge. UV Radiation or ozonation

could be used to eliminate water born pathogens. Modifying the existing creek channel

122

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located in that area could create an aesthetically pleasing perennial stream which would

flow directly behind student housing. An alternative disposal method, piping the effluent to

a subsurface drainage field located at site 3 could be used alone or as a back-up to

discharging water to the modified creek.

Flow Modeling

Figure 30 shows the B2C Wetlands in spreadsheet format. Flow was modeled for this

system following the same methodology used for the treatment, habitat and hybrid

systems. Flow through this wetland is depicted in Figure 31. Prior to water quality

modeling, flow was modeled for 10, 20, 30 and 40 kgpd for cell A and B as well as for

cell B only. These models are presented in combination with associated water quality

models (appendix C).

Water Quality

Water quality was modeled through the wetland for four different sets of conditions:

20 kgpd with only cell B in operation, 30kgpd again only with cell B and 40kgpd and

62kgpd (peak target flow) with both cells A and B. When the model was run for 20 kgpd,

evapotranspiration rates for June were used since this month has the highest

evapotranspiration minus precipitation rates with the exception of August, when make-up

water needs to be added. ET rates for August were not used to avoid overestimating

wetland performance due to the dilution effect of the make-up water. When the model was

run for 30kgpd, evapotranspiration rates for August were used. Using months with high

127

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evapotranspiration rates keeps water quality estimates conservative since these months

are likely to have the highest concentrations of total nitrogen in wetland effluent. Models

were run for 40kgpd and 62kgpd using evapotranspiration rates averaged for months of

expected peak flow (assumed to be same as for treatment, habitat, hybrid systems).

For each flow listed above, water quality was modeled using 10, 25, 50, 75 and 90th

percentile KTO values. Full model outputs are given in appendix C, while results are

summarized in Table 31. Notice the dramatic increase in percent reduction between the

10th and 25th percentile KTO. These data suggest that the B2C Wetlands as designed

above could not be expected to consistently discharge water with TN levels less than or

equal to 10mg/l. Permitting would need to recognize this, and could be arbitrated by

monitoring monthly or yearly TN mass discharges. Limits could be placed upon the total

amount of TN discharged per unit time. Data from Table 31 suggest that median

discharge concentrations would range from around a high of 4.4 mg/1 to a low of 2.3 mg/1.

Accordingly, the wetland could be expected to meet even stringent limits on average TN

effluent concentrations.

Habitat Quality Determination; Computation of SI Scores and HUs

Because of the different flood regimes to be used for cells A and B, two cover types

were used in SI determinations and HU calculations. Cell B is a permanently flooded

herbaceous wetland while cell A is a seasonally flooded herbaceous wetland. HSI models

were run for each cell separately for each of the six model species. Appendix D shows the

results of the HSI models for each species and cover type while Table 32 summarizes SI

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scores and shows HU calculations. These data show that an average total 9,223 weighted

HUs would be produced in the construction of the B2C Wetlands. Cell A, with a mean

weighted SI score of 0.41 and average weighted HU of 5,712 offers poorer quality habitat

than cell B, which had a mean weighted SI score of 0.726 and mean weighted HU of

12,734. The difference is a result of the seasonal draw down of cell A, which was assumed

to be inundated exactly 50 percent of the time. Due to the fact that HUs are dependant not

only upon habitat quality but also quantity, the B2C Wetlands generated a higher number

of HUs than any other system. Comparing HUs is not an accurate method for determining

per unit area habitat quality, which should be done by comparing SI scores. The SI scores

of cell B were similar to those of the habitat systems and hybrid system, which had scores

ranging from 0.735 to 0.742. Even with the draw down of cell A, average SI score for the

B2C Wetlands was higher than the treatment system, which received a mean weighted SI

score of 0.398.

CHAPTER V

SUMMARY

This research has endeavored to demonstrate that constructed wetlands created to treat

municipal effluent can be designed in such a way as to increase the quality of wildlife

habitat they offer and that these design modifications can be undertaken without

significantly sacrificing treatment efficiency. This study was deemed necessary due to the

common misbelief that all constructed wetlands provide quality wildlife habitat. The

second objective of this research was to provide a detailed example of the methodology

involved and considerations necessary in designing a constructed wetland. This example

was also to serve as a realistic application of lessons learned concerning production of

wildlife habitat with minimal loss of treatment efficiency.

This study has quantitatively demonstrated that it is possible to substantially raise the

quality of wildlife habitat offered by a constructed wetland without substantially lowering

the treatment efficiency realized by that system. Wildlife quality modeling has also

demonstrated that habitat offered by a "conventional" constructed wetland (the treatment

system) is substantially lower than could be produced with a wetland of identical area

using a different design.

Because pollutant reduction has a logarithmic relationship with pollutant

133

134

concentrations, the ratio of habitat increase to efficiency decrease will be inversely

proportional to wetland size and loading rates. This is due to the fact that wetland systems

operate more efficiently with higher loading rates (thus the logarithmic relationship). For

instance a wetland receiving a given flow will not experience a doubling of percent

removal with a doubling of wetland size. In fact, the treatment efficiency (percent removal

per unit area) of the larger system will be smaller than that of the smaller system.

Therefore, modifying a small wetland with a given flow to increase habitat quality will

have a greater, negative effect on treatment efficiency than modifying a larger wetland

with the same flow and pollutant influent concentrations. The wetlands used in this study

were modeled with loading rates lower than typical for constructed wetlands, due to the

stringent treatment objectives of reducing TN to 3 mg/1. Consideration must be given to

this fact when extrapolating the findings of this study to other constructed wetlands.

Based on the KTO and KBOD reaction rates determined, manipulation of vegetation

placement will never reduce treatment efficiency by greater than 50% even if all emergent

vegetation were removed. It can therefore be expected that even small systems modified

to improve habitat quality would realize a greater increase in habitat quality than decrease

in treatment efficiency.

Wetland morphology was shown through flow and water quality modeling to

significantly impact the treatment efficiency of constructed wetlands. It has also been

discussed that wetland morphology plays an important role in determining wildlife habitat

quality. The hybrid system, which had the highest edge index SI score along with even

flow patterns demonstrates that by using islands or other flow barriers, edge indices can be

135

increased with little impact on treatment efficiency. Wetlands should therefore be designed

as rectangles with aspects defined by hydrology restrictions. Widened areas of open water

will further increase edge indices but may result in areas of low flow. Addition of islands

helps direct flow into such areas and increases habitat and aesthetic qualities. Restrictions

to implementing constructed wetlands with high edge indices are likely to be costs related

to increased and more intricate earth works and more extensive berms.

Placement and amount of emergent vegetation also plays a key role in both water

quality and wildlife habitat. A ratio of 50% emergent vegetation cover with a high edge

index (i.e., smaller irregular shaped pockets) was found to provide the best wildlife habitat

for the HSI models used. Maximum treatment efficiency however, is expected to occur

with close to 100% cover. Location of pockets of emergent vegetation was also found to

influence water quality indirectly by influencing flow. The best way for designers to reduce

impacts of open areas on water treatment efficiency is by placing vegetation in bands

perpendicular to flow direction. Doing so assures that water will flow evenly through

vegetated areas. Furthermore, because vegetated areas posses higher reaction rate

constants, and the logarithmic relationship between inflow concentrations and removal

efficiency, the greatest concentration of emergent vegetation should be placed near the

outlet. Forcing influent to flow directly though several meters of emergent vegetation is

also good practice, improving water quality prior to introduction to the remainder of the

wetland. A general, practical design for improving habitat quality while minimizing

treatment efficiency reduction is to place a small area of dense emergent vegetation

immediately surrounding the inlet, followed by a large open area with light, intermittent

136

bands of vegetation. Remaining wetland area should contain dense emergent vegetation

with patches of non-adjoining open water. Amount of emergent vegetative cover should

be approximately 50%. Although this figure comes from SI model species specific for the

B2C region, it should be a good general indicator. For smaller systems, a cover of 60 to

75% is recommended to reduce impacts on treatment efficiency. The simplest modification

that any wetland should be able to accommodate which will result in the greatest increase

in habitat quality is to create a band of open water near the inlet or center of a constructed

wetland cell. This provides, even if minimal, a location for waterfowl and other wetland

birds to land and forage. In areas where natural wetlands are plentiful, such minimal

modification based on habitat improvement may not be necessary. In areas such as the

Desert Southwest, however, these small patches of habitat can provide numerous resting

stops for migratory birds. Even in areas where natural wetlands are plentiful, larger

systems or systems with small loading rates can be designed with these modifications to

help offset the tremendous loss of wetland area which has occurred in the past couple

centuries.

Future studies

Despite the dynamic and complex nature of wetlands, more attempts should be made

at quantifying the relative treatment efficiencies of different within wetland areas, such as

vegetated versus non-vegetated areas. These data would allow designers to calibrate a

range of reaction rate constants as was attempted in this study, enabling more precise

water quality modeling, and allowing for a better understanding of the relationship

137

between wildlife habitat quality and treatment efficiencies.

The main factor limiting the application of design guidelines suggested by this research

to other regions lies in the choice of HSI models. Future studies could be undertaken for

each ecoregion, using HSI models for species expected to benefit from wetlands in those

regions. Design criteria could then be suggested for each region.

Another concern lies directly with the use of HSI models to quantify wildlife habitat.

Although it is believed that these models accurately predict the quality of wildlife habitat

as pertaining to the variables they encompass, consideration in future studies should be

given to the impact of water quality on wildlife. HSI models were not designed specifically

for use with constructed wetlands; the models therefore do not concern themselves with

parameters such as BOD and TN since these are assumed to be at or near background

levels. Perhaps the most important water quality parameter which should be included in

future studies is dissolved oxygen (DO). DO concentrations are very important in all

aquatic environments, particularly constructed wetlands which can receive high levels of

BOD. Low concentrations of DO would result in reduced habitat quality, since these

zones cannot support fishes and other prey items needed for wildlife. Having open water

areas in constructed wetlands should help increase levels of DO by allowing more wind

disturbance and surface mixing.

Future studies might also look at existing constructed (or natural) wetlands used for

water treatment. Water quality and wildlife habitat of these systems could be determined

and compared by direct measurement using appropriate water analyses and HSI models,

allowing for in situ determination of the relationship, or lack thereof, between treatment

138

efficiency and wildlife habitat quality.

The Biosphere 2 Center Constructed Wetlands

Examination of water quality and HSI models for the B2C Wetlands demonstrates

some of the complications involved in real world application of conclusions reached by

this study. First and foremost, these systems are artificial and subject to certain limitations

such as land availability. Other complications, like high evapotranspiration rates leading to

high salinity levels, force design modifications which may not be compatible with

maximum quality habitat, as seen in the draw-down of cell A. Applying the design

considerations suggested by this research will nevertheless result in a wetland with much

higher quality habitat.

A suitable site is available to construct a wetland capable of meeting the current and

future wastewater treatment needs of the B2C. If projected student growth is realized, the

B2C will be faced with developing a wastewater treatment plant within the coming years.

Construction of a wetland for this purpose may be the right choice for the B2C. Indeed it

is difficult to imagine a scenario where more might be gained by the construction of a

wetland for water quality improvement. Such a system is consistent with the B2C's

commitment to employing ecologically correct technology, and would provide a suite of

other functions from which the B2C as well as the environment could benefit. As an

educational institution with a functioning on site nutrient analyzer, the B2C could increase

current knowledge of constructed wetlands. The system could become a major draw for

researchers and students interested in this technology and could strengthen communication

139

and cooperation between the B2C and local schools and organizations. It could become an

academic focal point for learning how to better couple the dual functions of providing

wildlife habitat and water treatment. The habitat provided by the system would help offset

the destruction of natural wetland systems in the region, vital to resident and migratory

birds. In turn, this could increase visitor counts and memberships, while educating the

public on water conservation and habitat destruction issues.

Although cost is a major concern, constructed wetlands are economical choices.

Furthermore, it may be possible to mitigate some or all construction costs through EPA/

Bureau of Land Management grants. Volunteers from local organizations, such as the

Nature Conservancy, Boy Scouts and Audubon Society could also be employed (as has

been done at other locations) to further reduce construction costs. These volunteers could

help plant vegetation and build trails and board walks. Trained docents could be used to

give guided tours of the wetland.

Conclusion

In conclusion, this research can be used by wetland designers to implement features

aimed at increasing the quality of wildlife habitat offered by constructed wetlands.

Designers should realize that quality wildlife habitat does not arise passively but that

modifications aimed at increasing habitat quality do not necessarily reduce treatment

efficiencies. By using specific design guidelines discussed in this thesis, it should be

possible to construct wetlands for water quality improvement which also serve as high

quality wildlife habitat. In the future, perhaps constructed wetlands and similar emerging

technologies can better serve our natural environment while providing important services

to humankind.

APPENDIX A

140

141

Table 33. Summary of Seasonally Averaged KTN and KBOD Values Determined from Five North American Constructed Wetlands

KTN KBOD

4.6 73.76 4.7 49.49 5.1 68.43 6 32.11

7.6 32.06 9.1 75.77 11.4 68.34 11.4 21.5 12.5 59.9 13 28.46

14.8 81.63 15.1 25.6 15.7 48.61 17.5 49.46 20.2 22.61 20.6 80.45 21.3 67.87 21.5 -2.6 25.1 45.33 25.8 35.06 25.9 32.22 30.7 44.3 30.7 78.47 32,3 54.38 35.1 32.95 35.7 41.66 36.4 32.37 36.6 53.93 38.4 90.02 40 43.46

45.9 60.6 47.3 26.73 47.6 24.95 49.9 56.81 51.8 90.57 53.6 29.34 53.6 29.24 63

70.4 73.8 74.6 96.9

Data from the North American Wetlands for Water Quality Treatment Database (US EPA, 1994)

142

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APPENDIX B

148

149

American Coot

Percent Wetland Dominated bv Herbacious Vegetation 0 0.1

40 1 60 1

100 0

Edge Index: Emergent Vegetation to Open Water 1 0.1 4 1 5 1

Defined as the total length of water in contact with shore or emergent vegetation divided by two times the square root of the wetland area times pie.

Water Regime 1 0.3 1 = Permanently Flooded 2 0.9 2 = Intermittently Flooded 3 1 3 = Semipermanently Flooded 4 0.5 4 = Seasonally Flooded 5 0 5 = Temporarily Flooded 6 0 6 = Intermittently Flooded

150

American Coot Suitability Indices

Percent of Wetland Dominated by Emergent Vegetation

0.6 -

y 0.5

0.3 -

0.2

40 100

Percent

Edge Index of Open Water to Emergent Vegetation

0.8 --

0.7 --

y 0.5 -

Edge Index

151

American Coot Suitability indices

1

0.9

0.8 --

0.7-

£ 0.6

£ 0-5 CO 0.4 *

0.3 -

0.2

0.1 + 0

Water Regime

3 4

Regime Code

152

Great Egret

X1 Percent of the Wetland with Water Depth 10-23cm 0 0

100 1

X2 Percent of Vegetation Cover in Areas Where Water Dept is 10-23cm 0 0.1

20 0.55 40 1 60 1

100 0

H.S.I. = (X1+X2)/2

153

Great Egret Suitability Indices

Percent of Cover in Areas Where Water Depth is 10-25cm

O 0.6 O « 0,5 CO « 0.4

20 40

Percent 60 100

Percent Canopy Cover of Area Where Water is 10-25cm Deep

w 0.4

0.3

20 40

Percent

60 100

154

Marsh Wren

XI Emergent Hvarophvte Class Catt/cord/t 1 reed 0.5 button/mar 0.1 other 0

X2 Percent Canopy Cover of Emergent Vegetation 0 0

10 0.02 20 0.04 30 0.06 40 0.08 50 0.1 60 0.4 70 0.7 80 1

100 1

X3 Mean Water Depth 0 0

0.15 1 0.4 1

X4 Percent Canoov Cover Consisting of Woodv Vegetation 0 1

100 0

Habitat Suitability Index: ((X1)(X2)(X3)A0.33)(X4)

155

Marsh Wren Suitability Indices

Emergent Hydrophyte Class

Catt/cord/bul reed button/man

Hydrophyte Type

other

Mean Water Depth

a 0.7

£ 0.6

= 0 5

xi _ ^ S 0.4

w 0.3

0.15

Water Depth (meters)

0.4

156

Marsh Wren Suitability Indices

Canopy Cover

0.6

0.3 --

0.2 -

° ° 8 8 S 8 8 R 8 8

Percent Canopy Cover that is Emergent Vegetation

Canopy Cover that is Woody Vegetation

o 1

Percent Canopy Cover of Woody Vegetation

157

Muskrat

Cover

X1 Percent of the Canopy Cover Which is Emergent Vegetation 0 0.05

10 0.24 20 0.43 30 0.62 40 0.81 50 1 60 1 70 1 80 1 90 0.95

100 0.9

X2 Percent of year with surface water present 0 0

25 0 50 0 75 0.1

100 1

H.S.i. (Cover) = (X1*X2)A0.5

Foraging

X3 Percent of the Canopy Cover Which is Emergent Vegetation Same as for cover

X4 Percent of the Emergent Herbaceous Vegetation Consisting of Olnev. 3so bulrush or C; 0 0.1

20 0.1 40 0.4167 60 0.7334 80 1

100 1

H.S.I. (Foraging) = (X3*X4)A0.5

H.S.I. Muskrat = minimum of cover and foraging

158

Muskrat Suitability Indices

Percent of the Wetland Covered with Emergent Vegetation

0.7 --

S 0.5-

0.4 -

'"""""""1""" 50

Percent

60 70 80 90 100

Percent of Year with Surface Water Present

0.9 -

0.8 -

0.7 -

£ 0.6 -

o p CO 0.5-

w 0.4 -r

0 . 3 -

0.2

0.1 -

0 -25

Percent

100

159

Muskrat Suitability Indices

Percent of Herbaceous Canopy which is Olney, 3square Bulrush and/or Cattail

1

0.9 -

0.8

0.7 +

«, 0.6

| o , w 0.4

0.3

0.2 +

0.1

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Percent

160

Red-winged Blackbird

X1 Emergent Vegetation is Broad Leaved Monocot Yes 1 No 0

X2 Water Regime Water ususally present all year 1 Usually dry part of the year 0.1

X3 Presence of carp Present 0 Not presen 1

X4 Presence of larvae of emergent aguatic insects yes 1 no 0.1

X5 Emergent herbaceous cover 1 0.1 1 = Emergent < open 2 1 2 = Emergent = open 3 0.3 3 = Dense emergent

Habitat Suitability Index: (X1)(X2)(X3)(X4)(X5)

161

Red-winged Blackbird Suitability Indices

Ratio of Open Water to Emergent Vegetation

" 0.5

162

Yellow-headed Blackbird ~~~~

Vegetation Area to Edge Ratio 0 0 7 1

1.11= Area of vegetation /(length of edge)A2

Percent open H2Q with submeroent vegetation 0 0

40 0.5 80 1

100 1

Emerant Vegetation to Open Water 0 0

3.5 0.5 7 1 8 1

Percent of Vegetation that is Robust 0 0

20 0.2 40 0.4 60 0.6 80 0.8

100 1

Average Water Depth Beneath Emergent Vegetation 0 0

15 1 20 1

163

Yellow-headed Blackbird Suitability Indices

Average Water Depth Beneath Emergent Vegetation

0.6

£ 0-5

0.4

15

Water Depth (cm)

20

Edge Index

0.7 -

0 . 6 --

0.3 -

0.2 -

3.5 7

Edge/Open Water

164

Yellow-headed Blackbird Suitability Indices

Percent Open Water with Submerged Vegetation

0.7 +

0.6

H 0.5 0.4

0.3

0.2 +

0.1

0 40 80

Percent

100

Percent of the Emergent Vegetation which is Robust

£ 0.5

0.3 -

0.2 -

20 40 60 80

Percent Robust Vegetation 100

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APPENDIX D

236

Treatment System: Computation of H.S.I. Score

237

American Coot:

Variable: Score: S.I.

Percent Wetland Dominated by Herbacious Vegetation

1.00 0.00

Edge Index; Emergent Vegetation to Open Water

1.14 0.15

Water Regime Permanently Flooded 0.30

H.S.I = (SIV1 X SIV2)A1/2 X SIV3 0.00

Great Egret

Variable: Score: S.I.

Percent of the Wetland with Water Depth 10-23cm

0.00 0.00

Percent of Vegetation Cover in Areas Where Water Dept is 10-23cm

0.00 0.00

H.S.I. = (X1+X2)/2 o.oo

238

Marsh Wren

Variable: Score: S.I.

Emergent Hygrophyte Class Catt/cord/bul 1.00

Percent Canopy Cover of Emergent Vegetation

1.00 1.00

Mean Water Depth 0.60 1.00

Percent Canopy Cover Consisting of Woody Vegetation

0.00 1.00

H.S.I. 1.00 ((X1 )(X2)(X3)A0.33)(X4)

Muskrat Cover Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of year with surface water present

1.00 1.00

H.S.I. (Cover) = (X1*X2)A0.5 0.95

Foraging Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of the Emergent Herbaceous Vegetation Consisting of Olney, 3sq bulrush or Cattail

1.00 1.00

H.S.I. (Foraging) = (X3*X4)A0.5

H.S.I. Muskrat = minimum of cover and foraging

0.95

239

Red-winged Blackbird

Variable: Score: S.I.

Emergent Vegetation is Broad Leaved Monocot

Yes 1.00

Water Regime Water ususally present all year

1.00

Presence of carp Not present 1.00

Presence of larvae of emergent aquatic insects

yes 1.00

Emergent herbaceous cover Dense emergent 0.30

H S i (X1)(X2)(X3)(X4)(X5)

0.30

Yellow-headed Blackbird

Variable: Score: H.S.I. Vegetation Area to Edge Ratio Defined by to variables:

1.14 0.26

Percent open H20 with submergent vegetation

100.00 1.00

Percent of Vegetation that is Robust 1.00 1.00

Average Water Depth Beneath Emergent Vegetation

0.60 1.00

H.S.I. = minimum of (X1 + X2) / 2 and (X3 + X4) / 2 (X1 + X2)/2 0.63

(X3 + X4)/2 1.00

Habitat System 1: Computation of S.I. Score

240

American Coot:

Variable: Score: S.I.

Percent Wetland Dominated by Herbacious Vegetation

0.50 1.00

Edge Index 3.22 0.72

Water Regime Permanently Flooded 0.30

H.S.I = (SIV1 X SIV2)A1/2 X SIV3 0.26

Great Egret

Variable: Score: S.I.

Percent of the Wetland with Water Depth

1.00 1.00

Percent of Vegetation Cover in Areas Where Water Dept is 10-23cm

0.50 1.00

H.S.I. = (X1+X2)/2 1.00

Marsh Wreri

Variable: Score: S.I.

Emergent Hygrophyte Class Catt/cord/bu! 1.00

Percent Canopy Cover of Emergent Vegetation

0.50 0.10

Mean Water Depth 0.23 1.00

Percent Canopy Cover Consisting of Woody Vegetation

0.00 1.00

Habitat Suitability Index: ((X1)(X2)(X3)A0.33)(X4)

0.46

241

Muskrat Cover Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of year with surface water present

100.00 1.00

H.S.I. (Cover) = (X1*X2)A0.5 0.95

Foraging Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of the Emergent Herbaceous Vegetation Consisting of Olney, 3sq bulrush or Cattail

1.00 I

1.00

H.S.I. (Foraging) = (X3*X4)A0.5 0.95

H.S.I. Muskrat = minimum of cover and foraging

Red-winged Blackbird

Variable: Score: S.I.

Emergent Vegetation is Broad Leaved Monocot

Yes 1.00

Water Regime Water ususally present all year

1.00

Presence of carp Not present 1.00

Presence of larvae of emergent aquatic insects

yes 1.00

Emergent herbaceous cover Emergent = open 1.00

Habitat Suitability Index: (X1)(X2)(X3)(X4)(X5) 1.00|

242

Yellow-headed Blackbird

Variable: Score: S.I.

Vegetation Area to Edge Ratio Defined by to variables:

3.22 0.46

Percent open H20 with submergent vegetation

100.00 1.00

Percent of Vegetation that is Robust 1.00 1.00

Average Water Depth Beneath Emergent Vegetation

0.23m 1.00

H.S.I. = minimum of (X1 + X2) / 2 and (X3 (X1 + X2)/2

CM

r—'V

+

0.73

(X 3 + X4)/2 1.00

Habitat System II: Computation of H.S.I. Score

243

American Coot:

Variable: Score: S.I.

Percent Wetland Dominated by Herbacious Vegetation

0.50 1.00

Edge Index 3.47 0.50

Water Regime Permanently Flooded 0.30

H.S.I = (SIV1 X SIV2)A1/2 X SIV3 0.21

Great Egret

Variable: Score: S.I.

Percent of the Wetland with Water Depth

1.00 1.00

Percent of Vegetation Cover in Areas Where Water

0.50 1.00

H.S.I. = (X1+X2)/2 1.00

244

Marsh Wren

Variable: Score: S.I.

Emergent Hygrophyte Class Catt/cord/bul 1.00

Percent Canopy Cover of Emergent Vegetation

0.50 0.10

Mean Water Depth 0.23 1.00

Percent Canopy Cover Consisting of Woody Vegetation

0.00 1.00

Habitat Suitability Index: ((X1)(X2)(X3)A0.33)(X4)

0.46

Muskrat Cover Variable: Score: S. I .

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of year with surface water present

1.00 1.00

H.S.I. (Cover) = (X1*X2)A0.5 ! | 0.95

Foraging Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of the Emergent Herbaceous Vegetation Consisting of Olney, 3sq bulrush or Cattail

1.00 1.00

H.S.I. (Foraging) = (X3*X4)A0.5

H.S.I. Muskrat = minimum of cover and foraging

0.95

245

Red-winged Blackbird

Variable: Score: S.I.

Emergent Vegetation is Broad Leaved Monocot

Yes 1.00

Water Regime Water ususally present all year

1.00

Presence of carp Not present 1.00

Presence of larvae of emergent aquatic insects

yes 1.00

Emergent herbaceous cover Emergent = open 1.00

Habitat Suitability Index: (X1)(X2)(X3)(X4)(X5)

Tool

Yellow-headed Blackbird

Variable: Score: S. I .

Vegetation Area to Edge Ratio 3.44 0.77

Percent open H20 with submergent vegetation

100.00 1.00

Percent of Vegetation that is Robust 1.00 1.00

Average Water Depth Beneath Emergent Vegetation

0.23m 1.00

H.S.I. = minimum of (X1 + X2) / 2 and (X3 + X4) / 2 (X1 + X2)/2 0.89

(X3 + X4)/2 1.00

Habitat System III: Computation of H.S.I. Score

246

American Coot:

Variable: Score: S.I.

Percent Wetland Dominated by Herbacious Vegetation

0.50 1.00

Edge Index 3.37 0.48

Water Regime Permanently Flooded 0.30

H.S.I = (SIV1 X SIV2)A1/2 X SIV3 0.21|

Great Egret

Variable: Score: S.I.

Percent of the Wetland with Water Depth

1.00 1.00

Percent of Vegetation Cover in Areas Where Water Dept is 10-23cm

0.50 1.00

H.S.I. = (X1+X2)/2 1.00

247

Marsh Wren

Variable: Score: S.I.

Emergent Hygrophyte Class Catt/cord/bul 1.00

Percent Canopy Cover of Emergent Vegetation

0.50 0.10

Mean Water Depth 0.23cm 1.00

Percent Canopy Cover Consisting of Woody Vegetation

0.00 1.00

Habitat Suitability Index: I | 0.46 ((X1)(X2)(X3)A0.33)(X4)

Muskrat Cover Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of year with surface water present

1.00 1.00

H.S.I. (Cover) = (X1*X2)A0.5 0.95|

Foraging Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of the Emergent Herbaceous Vegetation Consisting of Olney, 3sq bulrush or Cattail

1.00 1.00

H.S.I. (Foraging) = (X3*X4)A0.5

H.S.I. Muskrat = minimum of cover and foraging

0.95

248

Red-winged Blackbird

Variable: Score: S.I.

Emergent Vegetation is Broad Leaved Monocot

Yes 1.00

Water Regime Water ususally present all year

1.00

Presence of carp Not present 1.00

Presence of larvae of emergent aquatic insects

yes 1.00

Emergent herbaceous cover Emergent = open 1.00

Habitat Suitability Index: (X1)(X2)(X3)(X4)(X5)

1.00

Yellow-headed Blackbird

Variable: Score: S.I.

Vegetation Area to Edge Ratio 3.37 0.76

Percent open H20 with submergent vegetation

100.00 1.00

Percent of Vegetation that is Robust 1.00 1.00

Average Water Depth Beneath Emergent Vegetation

0.23m 1.00

H.S.I. = minimum of (X1 + X2) / 2 and (X3 (X1 + X2)/2

+ X4) / 2 0.88

CXJ x: +

CO &

1.00

Hybrid: Computation of H.S.I. Score

249

American Coot:

Variable: Score: S.I.

Percent Wetland Dominated by Herbacious Vegetation

0.50 1.00

Edge Index; Emergent Vegetation to Open Water

3.85 0.55

Water Regime Permanently Flooded 0.30

H.S.I = (SIV1 X SIV2)A1/2 X SIV3 0.22|

Great Egret

Variable: Score: S.I.

Percent of the Wetland with Water Depth 10-23cm

1.00 1.00

Percent of Vegetation Cover in Areas Where Water Dept is 10-23cm

0.50 1.00

H.S.I. = (X1+X2)/2 1.00

Marsh Wren

Variable: Score: S.I.

Emergent Hygrophyte Class Catt/cord/bul 1.00

Percent Canopy Cover of Emergent Vegetation

0.50 0.10

Mean Water Depth 0.23 1.00

Percent Canopy Cover Consisting of Woody Vegetation

0.00 1.00

H.S.I. ((X1)(X2)(X3)A0.33)(X4)

0.461

250

Muskrat Cover Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of year with surface water present

1.00 1.00

H.S.I. (Cover) = (X1*X2)A0.5 0.95

Foraging Variable: Score: S.I.

Percent of the Canopy Cover Which is Emergent Vegetation

1.00 0.90

Percent of the Emergent Herbaceous Vegetation Consisting of Olney, 3sq bulrush or Cattail

1.00 1.00

H.S.I. (Foraging) = (X3*X4)A0.5

H.S.I. Muskrat = minimum of cover and foraging

0.95

Red-winged Blackbird

Variable: Score: S.I.

Emergent Vegetation is Broad Leaved Monocot

Yes 1.00

Water Regime Water ususally present all year

1.00

Presence of carp Not present 1.00

Presence of larvae of emergent aquatic insects

yes 1.00

Emergent herbaceous cover Emergent = open 1.00

H.S.I. (X1)(X2)(X3)(X4)(X5)

1.00

251

Yellow-headed Blackbird

Variable: Score: S.I.

Vegetation Area to Edge Ratio Defined by to variables:

3.85 0.87

Percent open H20 with submergent vegetation

100.00 1.00

Percent of Vegetation that is Robust 1.00 1.00

Average Water Depth Beneath Emergent Vegetation

0.23 1.00

H.S.I. = minimum of (X1 + X2) / 2 and (X3 (X1 + X2)/2

+ X4) / 2 0.93|

(X 3 + X4)/2 1.00

252 B2C Constructed Wetlands: Calculation of H.S.I Scores

American Coot:

Cell A. Cover type- seasonaly flooded herbaceous wetland Variable: Score: H.S.I:

Percent Wetland Dominated by Herbacious Vegetation

74% 0.65

Edge Index; Emergent Vegetation to Open Water

2.96 0.99

Water Regime Seasonally flooded 0.50

H.S.I = (SIV1 X SIV2)A1/2 X 0.40

Cell B. Cover type- permanently flooded herbaceous wetland Variable: Score: H.s.I:

Percent Wetland Dominated by Herbaceous Vegetation

42% 1

Edge Index; Emergent Vegetation to Open Water

2.82 0.95

Water Regime Permanently Flooded 0.3

H.S.I = (SIV1 X SIV2)A1/2 X 0.29

Great Egret

253

Cell A. Cover type- seasonaly flooded herbaceous wetland Score: H.S.I:

Percent of the Wetland 100% 1 with Water Depth 10-23cm

Percent of Vegetation Cover in Areas 74% 0.65 | Where Water Dept is 10-23cm

H.S.I. = (X1+X2)/2 0.825

Cell B. Cover type- permanently flooded herbaceous wetland Variable: Score: H.s.

Percent of the Wetland 100% 1 with Water Depth 10-23cm

Percent of Vegetation Cover in Areas 42% 1 I Where Water Dept is 10-23cm

H.S.I. = (X1+X2)/2

254

Marsh Wren

Cell A. Cover type- seasonaly flooded herbaceous wetland Variable: Score: H.s.i:

Emergent Hygrophyte Class Catt/cord/bul 1

Percent Canopy Cover of Emergent Vegetation

74% 0.82

Mean Water Depth 0.23 1

Percent Canopy Cover Consisting of Woody Vegetation

0% 1

Habitat Suitability Index: 0.94 ((X1)(X2)(X3)A0.33)(X4)

Cell B. Cover type- permanently flooded herbaceous wetland Variable: Score: H.s.i:

Emergent Hygrophyte Class Catt/cord/bul 1

Percent Canopy Cover of Emergent Vegetation

42% 0.08

Mean Water Depth 0.23 1

Percent Canopy Cover Consisting of Woody Vegetation

0% 1

Habitat Suitability Index: ((X1)(X2)(X3)A0.33)(X4)

0.44

Muskrat: Cover

255

Cell A. Cover type- seasonaly flooded herbaceous wetland Variable: Score: H.s.i:

Percent of the Canopy Cover Which is Emergent Vegetation

100% 0.9

Percent of Year with Surface Water Present

50% 0

H.S.I. (Cover) = (X1*X2)A0.5 0

Cell B. Cover type- permanently flooded herbaceous wetland Variable: Score: H.s.i:

Percent of the Canopy Cover Which is Emergent Vegetation

100% 0.9

Percent of Year with Surface Water Present

100% 1

H.S.I. (Cover) = (X1*X2)A0.5

Muskrat: Forage

0.95

Cell A. Cover type- seasonaly flooded herbaceous wetland Variable: Score: H.s.i:

Percent of the Canopy Cover Which is Emergent Vegetation

100% 0.9

Percent of the Emergent Herbaceous Vegetation Consisting of Oiney, 3sq bulrush or Cattail

100% * 1

H.S.I. (Foraging) = (X3*X4)A0.5

Cell B. Cover type- permanently flooded herbaceous wetland Variable: Score:

0.B5|

H.S.I:

Percent of the Canopy Cover Which is Emergent Vegetation

100% 0.9

Percent of the Emergent Herbaceous Vegetation Consisting of Olney, 3sq bulrush or Cattail

100% 1

H.S.I. (Foraging) = (X3*X4)A0.5 0.95

Red-winged Blackbird

256

Cell A. Cover type- seasonaly flooded herbaceous wetland Variable: Score: H.s.i:

Emergent Vegetation is Broad Leaved Monocot

Yes 1

Water Regime Ususally Dry Part of Year

0.1

Presence of carp Not present 1

Presence of larvae of emergent aquatic insects

yes 1

Emergent herbaceous cover Emergent = open 0.664

Habitat Suitability index: 0.07 (X1)(X2)(X3)(X4)(X5)

Cell B. Cover type- permanently flooded herbaceous wetland Variable: Score: H.S.I:

Emergent Vegetation is Broad Leaved Monocot

Yes 1

Water Regime Water ususally present all year

1

Presence of carp Not present 1

Presence of larvae of emergent aquatic insects

yes 1

Emergent herbaceous cover Emergent = open 0.86

Habitat Suitability Index: (X1)(X2)(X3)(X4)(X5)

0.86

Yellow-headed Blackbird

257

Cell A. Cover type- seasonaly flooded herbaceous wetland Variable: Score: H.S.I:

Vegetation Area to Edge Ratio 2.96 0.42

Percent open H20 with submergent vegetation

0% 0

Percent of Vegetation that is Robust 100% 1

Average Water Depth Beneath Emergent Vegetation

0.23m 1

H.S.I. = minimum of (X1 + X2) / 2 and (X3 + X4) / 2 (X1 + X2)/2 | 0.21

(X 3 + X4)/2 1

Cell B. Cover type- permanently flooded herbaceous wetland Variable: Score: H.S.I:

Vegetation Area to Edge Ratio 2.82 0.40

Percent open H20 with submergent vegetation

100% 1

Percent of Vegetation that is Robust 100% 1

Average Water Depth Beneath Emergent Vegetation

0.23m 1

H.S.I. = minimum of (X1 + X2) / 2 and (X3 + X4) / 2 (X1 + X2)/2

(X 3 + X4)/2

0.70

1

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