EPA/600/ R-10/ 032 

March 2010 

Alternative Futures Analysis of Farmington Bay Wetlands 
 

in the Great Salt Lake Ecosystem 
 

USEPA Office of Research and Development, 
 

National Risk Management Research Laboratory, 
 

26 West Martin Luther King Drive 
 

Cincinnati, Ohio 45268 
 
 

Notice
 


Information presented and the views expressed herein are strictly the opinions of the authors and 
 

in no manner represent or reflect current or planned policy by the USEPA. Mention of trade 
 

names or commercial products does not constitute endorsement or recommendation of use. 
 

The correct citation for this document is: 
 

Sumner, R.1

, J. Schubauer-Berigan 2, T. Mulcahy 3, J. Minter4, B. Dyson 2, C. Godfrey3 and J. 
 

Blue 3 2010. Alternative Futures Analysis of Farmington Bay Wetlands in The Great Salt Lake 
 

Ecosystem. U.S. Environmental Protection Agency, Cincinnati, OH, EPA/ 600/ R-10/ 032. 
 

. 
 

1 U.S. Environmental Protection Agency, Office of Wetlands Oceans and Watersheds, 

35th Street, Corvallis, OR 97333 

2 U.S. Environmental Protection Agency, National Risk Management Research Laboratory, 

26 W. M. L. King Drive, Cincinnati, OH 45268. 

3 The Cadmus Group, Incorporated, 57 Water St., Watertown, MA 02472 

4 U.S. Environmental Protection Agency, Region 8, 1595 Wynkoop St., Denver, CO 80202. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) II 
 

Executive Summary 
 

Introduction 

The Farmington Bay wetlands are an integral part of the Great Salt Lake Ecosystem. The 

wetlands support the delivery of a wide range of ecosystem services including support for avian 

habitat and control of excess nutrient pollutants. The principal risks posed to the wetlands are 

the conversion to upland development, degradation from pollutants and change in freshwater 

availability. 

Purpose, Objectives and Approach 

An Alternative Futures Analysis (AFA) was conducted to demonstrate how models can be used 

to evaluate landscape design scenarios developed for the Farmington Bay area of the Great Salt 

Lake. Scenarios were developed which featured the design of a conservation “future” focused 

on a set of wetland protection, restoration, and conservation practices. The conservation design 

was contrasted with scenarios that reflect current day wetland management practices and an 

extrapolation of those practices into the future. Each of the future scenarios was described in 

context with the average water level elevation of the Great Salt Lake and a high water level 

elevation (4,200 feet and 4,212 feet, respectively). In addition, a set of wetland “templates” was 

developed and embedded into each scenario to aid scenario design and evaluation. Each 

template represents a typical cluster or complex of wetlands with a dominate wetland class: 

impoundment wetlands, playa wetlands and fringe/emergent wetlands. Evaluation of the 

scenarios was based on risks to avian habitat support caused by degradation in wetland 

abundance, distribution, and condition. The evaluation entailed the use of four ecological 

modeling approaches. A wetland landscape profile was developed to track change in wetland 

abundance, by class, across the scenarios. A Geographic Information System (GIS) based avian 

wetland habitat assessment (AWHA) was developed to predict the availability of suitable avian 

habitat. The ArcView Generalized Watershed Loading Function (AVGWLF) model was 

calibrated to predict nutrient loads to the wetlands. A wetland cellular water quality model was 

developed to evaluate nutrient retention in impoundment class wetlands. No specific analysis 

was conducted to determine the effects of nutrient loads on the ecological condition of receiving 

wetlands. 

Major Significance 

The development and demonstration of the evaluation models was the key objective of the study 

and the results are presented in detail. The interpretation of those results, in terms of setting 

wetland management goals for the study area, is purposely kept general in nature. New scenario 

development and community-based planning can take advantage of this first iteration of 

scenarios and evaluation models. For example, general project results reveal that most (97%) of 

wetlands in the study area are located within an elevation band of 4,200 feet to 4,217 feet. 

Results from the AFA show a dramatic loss of wetlands in the Plan Trend 4,212 feet and the 

Conservation 4,212 feet scenarios. The Plan Trend scenarios observe the greatest decline in the 

most suitable category of avian habitat for three bird groupings: migratory shorebirds, migratory 

waterbirds, and migratory waterfowl. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) III 
 

The Conservation 4,200 scenario protects the most wetland acreage and highest category of 

suitable avian habitat. The Plan Trend 4,200 scenario observes the greatest decline in the highest 

class of suitable avian habitat. A substantial increase in watershed loading of nutrients delivered 

to all the templates for the Conservation and Plan Trend scenarios was predicted using the 

AVGWLF model. Results from this model indicate that total phosphorus and total nitrogen 

loads delivered to the templates from the Jordan River watershed are heavily influenced by the 

two major point sources in the Jordan Basin. The wetland water quality model predicted a 

removal efficiency of 74% for phosphorus, and -11% for sediment for Impoundment class 

wetlands. The approach used for this project, incorporating GIS based evaluation models and 

including an Alternative Futures Analysis, is a transparent way of organizing and communicating 

complex scientific information to a diverse group of stakeholders and improving communication 

among the stakeholders. 

The authors of this report encourage examination of the methods and results produced by this 

research project. Our hope is that lessons learned will be applied in renewed effort toward 

envisioning ways to sustain and improve the health of the Great Salt Lake Ecosystem. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) IV 
 

 

Foreword
 


The U.S. Environmental Protection Agency (EPA) is charged by Congress with protecting the 

Nation’s land, air, and water resources. Under a mandate of national environmental laws, the 

Agency strives to formulate and implement actions leading to a compatible balance between 

human activities and the ability of natural systems to support and nurture life. To meet this 

mandate, EPA’s research program is providing data and technical support for solving 

environmental problems today and building a science knowledge base necessary to manage our 

ecological resources wisely, understand how pollutants affect our health, and prevent or reduce 

environmental risks in the future. 

The National Risk Management Research Laboratory (NRMRL) is the Agency’s center for 

investigation of technological and management approaches for preventing and reducing risks 

from pollution that threaten human health and the environment. The focus of the Laboratory’s 

research program is on methods and their cost-effectiveness for prevention and control of 

pollution to air, land, water, and subsurface resources; protection of water quality in public water 

systems; remediation of contaminated sites, sediments, and ground water; prevention and control 

of indoor air pollution; and restoration of ecosystems. NRMRL collaborates with both public 

and private sector partners to foster technologies that reduce the cost of compliance and to 

anticipate emerging problems. NRMRL’s research provides solutions to environmental 

problems by: developing and promoting technologies that protect and improve the environment; 

advancing scientific and engineering information to support regulatory and policy decisions; and 

providing the technical support and information transfer to ensure implementation of 

environmental regulations and strategies at the national, state, and community levels. 

This publication has been produced as part of the Laboratory’s strategic long-term research plan. 

It is published and made available by EPA’s Office of Research and Development to assist the 

user community and to link researchers with their clients. 

 Sally Gutierrez, Director

 National Risk Management Research Laboratory 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) V 
Table of Contents 

NOTICE ......................................................................................................................................................................II
 


EXECUTIVE SUMMARY ......................................................................................................................................III
 


INTRODUCTION ......................................................................................................................................................III
 


PURPOSE, OBJECTIVES AND APPROACH ...............................................................................................................III
 


MAJOR SIGNIFICANCE ...........................................................................................................................................III
 


FOREWORD ..............................................................................................................................................................V
 


LIST OF FIGURES............................................................................................................................................... VIII
 


ACKNOWLEDGEMENTS .......................................................................................................................................X
 


1.0 INTRODUCTION .................................................................................................................................................1
 


1.1 PROBLEM STATEMENT.......................................................................................................................................1
 


1.2 OBJECTIVE .........................................................................................................................................................1
 


2.0 METHODS.............................................................................................................................................................2
 


2.1 ALTERNATIVE FUTURE APPROACH ...................................................................................................................2
 


2.2 STUDY AREA DESCRIPTION ...............................................................................................................................3
 


Jordan River Watershed.................................................................................................................................................... 6
 


Farmington Bay Wetlands ................................................................................................................................................ 7
 


2.3 MANAGEMENT SCENARIOS AND TEMPLATE DESCRIPTIONS ............................................................................9
 


2.3.1 Current Scenario 2003............................................................................................................................................ 9
 


2.3.2 Future Scenarios................................................................................................................................................... 10
 


2.3.3 Plan Trend 2030 Scenarios................................................................................................................................... 11
 


2.3.4 Conservation 2030 Scenarios................................................................................................................................ 12 
 


2.3.5 2030 Lake Level Rise Scenarios............................................................................................................................ 14
 


2.3.6 Study Templates .................................................................................................................................................... 16
 


2.3.6.1 Impoundment Template...................................................................................................................................... 16
 


2.3.6.2 Fringe/Emergent Template ................................................................................................................................ 17 
 


2.3.6.3 The Playa Template............................................................................................................................................ 17
 


2.4 ECOSYSTEM SERVICES AND EVALUATION MODELS .......................................................................................18
 


2.4.1 Ecosystem Service - Support for avian habitat...................................................................................................... 19
 


2.4.1.1 Development of the Avian Wetland Habitat Assessment (AWHA) Model........................................................... 20
 


2.4.1.2 Calibration of the AVGWLF Model for the Jordan River Basin ........................................................................ 24
 


2.4.1.3 Calibration Statistics.......................................................................................................................................... 26
 


2.4.2 Ecosystem Service-Assessing GSL Wetland Retention of Nutrients ...................................................................... 26
 


3.0 RESULTS.............................................................................................................................................................29
 


3.1 WETLAND LANDSCAPE PROFILES ...................................................................................................................29
 


3.2 AVIAN WETLAND HABITAT ASSESSMENT .......................................................................................................34
 


3.3 AVGWLF WATERSHED LOADING MODEL ....................................................................................................38
 


Future scenario nutrient and sediment loading ................................................................................................................. 41
 


3.4 NUTRIENT RETENTION CAPACITY OF IMPOUNDMENT WETLANDS..................................................................44
 


4.0 DISCUSSION AND CONCLUSIONS ...............................................................................................................47
 


4.1 SETTING WETLAND GOALS – CONNECTING RESULTS TO A DECISION-MAKING FRAMEWORK...................47
 


4.1.1 Decision Making: Landscape Change and Conservation ...................................................................................... 47
 


4.1.2 Predicting Change: Understanding the Consequences of Management Decisions................................................ 48
 


4.1.3 Predicting Change: Designing Plausible Scenarios Representing the Landscape Based on Past and Innovative 
 

Practices ......................................................................................................................................................................... 49
 


4.1.4 Evaluating the Current State of the Landscape...................................................................................................... 51
 


4.1.5 Describing How the Landscape Functions............................................................................................................. 51
 


5.0 MODEL PERFORMANCE AND RECOMMENDATIONS FOR IMPROVEMENTS...............................51
 


5.1 RECOMMENDATIONS FOR THE WETLAND LANDSCAPE PROFILES .................................................................51
 


5.1.1 Avian Wetland Habitat Assessment (AWHA) Performance.................................................................................... 52
 


Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 
 VI 
 

 

 

 

5.1.1.1 Recommendations for AWHA.............................................................................................................................. 52
 


5.1.2 AVGWLF Performance .......................................................................................................................................... 53
 


5.1.2.1 Recommendations for AVGWLF ......................................................................................................................... 55
 


5.1.3 Recommendations Wetland Cellular Water Quality Model ................................................................................... 56
 


6.0 SUMMARY..........................................................................................................................................................57
 


7.0 REFERENCES ....................................................................................................................................................58
 


8.0 APPENDICES......................................................................................................................................................64
 


8.1 APPENDIX A. SHORELAND ELEVATION ZONES ..................................................................................................64
 


8.2 APPENDIX B. 2008 NATIONAL WETLANDS INVENTORY ....................................................................................66
 


National Wetlands Inventory .......................................................................................................................................... 66
 


The Lacustrine System.................................................................................................................................................... 66
 


The Palustrine System..................................................................................................................................................... 66
 


8.3 APPENDIX C. RESTORATIONS OPPORTUNITY ASSESSMENT................................................................................68
 


Public or Private High Potential Restoration Opportunity .............................................................................................. 68
 


Public or Private Potential Restoration Opportunity ....................................................................................................... 68
 


Phragmites Removal Potential ........................................................................................................................................ 68
 


Restorations Opportunity GIS Methodology................................................................................................................... 69
 


Parcel Evaluation ............................................................................................................................................................ 69
 


Interior Habitat................................................................................................................................................................ 70
 


Hydric Soils Classification.............................................................................................................................................. 71
 


Conveyance and Water Rights Data................................................................................................................................ 72
 


Presence of Phragmites ................................................................................................................................................... 73
 


NWI Wetlands ................................................................................................................................................................ 73
 


Elevation Zone Assessment ............................................................................................................................................ 73
 


8.4 APPENDIX D. METHODOLOGY FOR THE AVIAN WETLAND HABITAT ASSESSMENT (AWHA) ...........................74
 


Selecting Variables ......................................................................................................................................................... 74
 


Assigning a Variable Strength and Weight to Each Variable.......................................................................................... 74
 


Raster Calculation........................................................................................................................................................... 77
 


Habitat Value Maps ........................................................................................................................................................ 78
 


8.5 APPENDIX E. CALIBRATION OF THE AVGWLF MODEL IN THE JORDAN RIVER BASIN......................................79
 


AVGWLF Model: Jordan River Basin............................................................................................................................ 82
 


AVGWLF Model Simulation Results ............................................................................................................................. 84
 


8.6 APPENDIX F. WETLAND WATER QUALITY MODEL ...........................................................................................91
 


Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 
 VII 
 

 

 

 

List of Figures 

Figure 1. Great Salt Lake Eco-region and Farmington Bay, NLCD 2001....................................................................3
 


Figure 2. Level of Great Salt Lake in 1988 and 2003 (Miller and Hoven, 2007).........................................................4
 


Figure 3. Hydrograph depicting Great Salt Lake surface elevation fluctuation at the South Arm from 1992-2008,....5
 


Figure 4. Jordan River basin and conveyances.............................................................................................................6
 


Figure 5. Baird Creek, Holmes Creek, and Kays Creek basins and conveyances. .......................................................7
 


Figure 6. Functional wetland classification based on the 2008 NWI data....................................................................8
 


Figure 7. Current Scenario: Land Use and Wetland GIS Layers................................................................................10
 


Figure 8. Plan Trend 4,200 Lake-level Scenario: Land Use and Wetland GIS Layers...............................................12
 


Figure 9. Conservation 4,200 Lake-level Scenario: Land Use and Wetland GIS Layers...........................................13
 


Figure 10. Potential restoration opportunity. ..............................................................................................................14
 


Figure 11. Plan Trend 4,212 Lake-level Scenario: Land Use and Wetland GIS Layers.............................................15
 


Figure 12. Conservation 4,212 Lake-level Scenario: Land Use and Wetland GIS Layers.........................................15
 


Figure 13. Impounded template, associated wetlands, basin boundary, and conveyances. ........................................16
 


Figure 14. Fringe/Emergent template, associated wetlands, basin boundaries, and conveyances..............................17
 


Figure 15. Playa template, associated wetlands, basin boundary, and conveyances. .................................................18
 


Figure 16. Example of raster datasets that represent variables used to calculate availability of suitable habitat. ......21
 


Figure 17. Variable weight hierarchy: Variables are assigned a “strength” (VS).......................................................22
 


Figure 18. Suitable Migratory Shorebird habitat available in total study area under current scenario conditions......23
 


Figure 19. Suitable Migratory Waterfowl habitat available in total study area under current scenario conditions. ...23
 


Figure 20. Suitable Migratory Waterbird habitat available in the total study area. ....................................................24
 


Figure 21. Screen-Capture of Jordan River ArcView Generalized Watershed Loading Function (AVGWLF).........25
 


Figure 22. Ambassador Wetland cells and STORET stations. ...................................................................................28
 


Figure 23. Distribution of total wetland acres among elevation zones. ......................................................................29
 


Figure 24. Wetland landscape profile for the Total study area...................................................................................30
 


Figure 25. Wetland landscape profile for the Fringe/Emergent template. ..................................................................31
 


Figure 26. Wetland landscape profile for the Playa template. ....................................................................................32
 


Figure 27. Wetland landscape profile for the Impoundment template........................................................................33
 


Figure 28. The above map displays the highest class of suitable habitat for Migratory Shorebirds available under 
 

various future scenarios in the Fringe/Emergent Template................................................................................34
 


Figure 29. Proportional analysis of the most suitable habitat class for the Total study area. .....................................35
 


Figure 30. Proportional analysis of the most suitable habitat class for the Fringe/Emergent template. .....................36
 


Figure 31. Proportional analysis of the most suitable habitat class for the Playa template. .......................................37
 


Figure 32. Proportional analysis of most suitable habitat class for the Impounded template. ....................................38
 


Figure 33. Mean Monthly Flows and Loads in the Jordan River................................................................................39
 


Figure 35. Nitrogen Loads By Source. .......................................................................................................................40
 


Figure 36. Sediment Loads By Source. ......................................................................................................................40
 


Figure 37. Percent Change of basin delivered loads from the Jordan River basin and the Davis County sub-basins
 


under Plan Trend and Conservation scenarios. ..................................................................................................42
 


Figure 38. Retention of Total Phosphorous and Sediment modeled for the Impoundment template under three future
 


watershed-loading scenarios. .............................................................................................................................44
 


Figure 39. Impoundment Conceptual Framework. .....................................................................................................45
 


Figure 40. Observed and Simulated Results for Total Phosphorous. .........................................................................45
 


Figure 41. Observed and Simulated Results for Sediment .........................................................................................46
 


Figure A1. Shoreland Elevation Zones.......................................................................................................................65
 


Figure C1. Parcel Evaluation......................................................................................................................................69
 


Figure C2. Interior Habitat with Interior Buffers........................................................................................................70
 


Figure C3. Hydric Soils Classification. ......................................................................................................................71
 


Figure C4. Example of Shoreland Conveyances and Water Rights............................................................................72
 


Figure C5. Phragmites Presence. ................................................................................................................................73
 


...........................................................................................................................................................................81
 


Figure E1. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Phosphorous.
 


Figure E2. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Nitrogen...81
 


Figure E3. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Suspended 
 

Solids..................................................................................................................................................................82
 


Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 
 VIII 
 

 

 

Figure E4. AVGWLF Input Transport File. ...............................................................................................................84
 


Figure E5. AVGWLF Input Nutrient File. .................................................................................................................85
 


Figure E6. Simulated Hydrology Transport Summary. ..............................................................................................86
 


Figure E7. Simulated Nutrient Transport Summary. ..................................................................................................87
 


Figure E8. Simulated Total Loads by Source. ............................................................................................................88
 


Figure F1. Impoundment Template Wetland Cells with Simulated (red) and Observed (black) TP Concentrations
 


(mg/L). ...............................................................................................................................................................92
 


Figure F2. Impoundment Template Wetland Cells with Simulated (red) and Observed (black) TSS Concentrations.
 


...........................................................................................................................................................................93
 


List of Tables 

Table 1. Proportional analysis of wetland acreage for the Total study area. ..............................................................30
 


Table 2. Proportional analysis of wetland acreage for the Fringe/Emergent template. ..............................................31
 


Table 3. Proportional analysis of wetland acreage for the Playa template. ................................................................32
 


Table 4. Proportional analysis of wetland acreage for the impounded template. .......................................................33
 


Table 5. Change in habitat availability for each future scenario for the Total study area...........................................35
 


Table 6. Change in habitat availability for each future scenario for the Fringe/Emergent template...........................36
 


Table 7. Change in habitat availability for each future scenario for the Playa template.............................................37
 


Table 8. Change in habitat availability for each future scenario for the Impounded template. ..................................38
 


Table 9. Phosphorus Loads-By-Source. .....................................................................................................................39
 


Table 10. Nitrogen Loads By Source..........................................................................................................................40
 


Table 11. Sediment Loads By Source.........................................................................................................................40
 


Table 12. Current Scenario Model Output: net loads after withdrawals and extractions............................................41
 


Table 13. Percent change in loads from current conditions under future scenarios....................................................41
 


Table 14. Plan Trend Future Scenario Watershed Loading: percent change indicates change in loading from Current
 


scenario. .............................................................................................................................................................42
 


Table 15. Conservation Future Scenario Watershed Loading: percent change indicates change in loading from
 


Current scenario. ................................................................................................................................................42
 


Table 16. Current scenario wetland retention of nutrients and sediment....................................................................43
 


Table 17. Plan Trend scenario wetland retention: percent change indicates change in wetland retention from the 
 

Current scenario. ................................................................................................................................................43
 


Table 18. Conservation scenario wetland retention: percent change indicates change in wetland retention from the 
 

Current scenario. ................................................................................................................................................43
 


Table 19. Predicted vs. Observed Removal Efficiencies: Impoundment Template....................................................44
 


Table 20. Wetland Cellular Water Quality Model Results. ........................................................................................46
 


Table D1. Variable Strength and Weights Worksheet for One Bird Grouping. .........................................................76
 


Table D2. Final matrix of weights for all bird groupings. ..........................................................................................77
 


Table E1. Information Sources for AVGWLF Model Parameterization. ...................................................................83
 


Table E2: Jordan River Land Use Acreage Distribution. ............................................................................................89
 


Table E3. Simulated Phosphorus Loading Allocations; pounds per year...................................................................89
 


Table E4. Simulated Sediment Loading Allocations; Pounds per year. .....................................................................90
 


Table E5. Simulated Total Nitrogen Loading Allocations; Pounds per year..............................................................90
 


Table E6. Mean Annual Loadings to the Surplus Canal.............................................................................................90
 


Table F1. STORET data used in model development. ...............................................................................................92
 


Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 
 IX 
Acknowledgements 

We thank the members of our design team who participated in the project and represented 

stakeholder interests for the wetlands in Farmington Bay. Members of the design team included: 

Dick Gilbert, Ambassador Duck Club; Pam Kramer, U.S. Fish and Wildlife Service; Theron 

Miller, formerly with the Utah State Department of Environmental Quality; Leland Myers, 

Central Davis Sewage District; Ann Neville, Kennecott Utah Copper Corporation; Maunsel 

Pearce, Great Salt Lake Alliance; Florence Reynolds, Salt Lake City Public Utilities; Tom 

Roach, Salt Lake County Public Works; and Don White, Zion Investments. The project was 

made possible by funds from EPA's Regional Applied Research Effort (RARE) Program to EPA 

Region 8. The Cadmus Group, Inc. performed the GIS modeling and analyses under the 

direction of the U.S. Environmental Protection Agency as part of Scientific, Technical, Research, 

Engineering and Modeling Support (STREAMS) contract EP-C-05-058 TO # 44. We thank 

Bernie Daniel and Douglas Grosse for their comments and suggestions for improving an earlier 

draft of the document and Jennifer Lantz for her help with editing and formatting. The cover 

photograph was taken by Bruce Thompson/LightHawk October 4, 2004. Joseph P. SchubauerBerigan, USEPA NRMRL was the Technical Project Lead and Contract Project Officer and is 

the corresponding author for this report. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) X 
Acronyms 

AFA Alternative Futures Analysis 

AMSL Above Mean Sea Level 

APEL American Pelican 

APWA American Public Works Association 

ASCE American Society of Civil Engineers 

AVGWLF ArcView Generalized Watershed Loading Function 

AWHA Avian Wetland Habitat Assessment Model 

DCDCED Davis County Department of Community and Economic Development 

DEM Digital Elevation Model 

EWRI Environmental and Water Resources Institute 

FEMA Federal Emergency Management Administration 

FHWA Federal Highway Administration 

GIS Geographic Information System 

GSL Great Salt Lake 

GWLF Generalized Watershed Loading Function 

HGM Hydrogeomorphology 

HLR Hydrologic Loading Rate 

IWS Institute for Watershed Sciences 

KLSCP K, LS, and CP (factors used in the Universal Soil Loss Equation) 

LBCR Long Billed Curlew 

MEA Millennium Ecosystem Assessment 

MGSG Migratory Shorebirds 

MGWB Migratory Waterbirds 

MGWF Migratory Waterfowl 

N Nitrogen 

NCSH Nesting Colonial Shorebirds 

NCWB Nesting Colonial Waterbirds 

NPS Nonpoint Source 

NRMRL National Risk Management Research Laboratory 

NWI National Wetland Inventory 

P Phosphorous 

PER Perimeter Expansion Rate 

POTW Publicly Owned Treatment Works 

PSIE Pennsylvania State Institutes of the Environment 

SLCPZ Salt Lake County Planning & Zoning Division Department of Community Development 

SLCWRPR Salt Lake County Water Resources Planning and Restoration 

SNPL Snowy Plover 

SSURGO Soil Survey Geographic (Database) 

STORET STOrage and RETrieval (System for Water Quality Data) 

TMDL Total Maximum Daily Load 

TP Total Phosphorous 

TSS Total Suspended Solids 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) XI 
USEPA US Environmental Protection Agency 

USFWS US Fish and Wildlife Service 

USGS US Geological Service 

USLE Universal Soil Loss Equation 

UTDEQ Utah Department of Environmental Quality 

UTDNR Utah Department of Natural Resources 

UTDOT Utah Department of Transportation 

UTDWQ Utah Division of Water Quality 

UTDWRe Utah Division of Water Resources 

UTDWRi Utah Division of Water Rights 

WAQSP Water Quality Stewardship Plan 

WERF Water Environment Research Foundation 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) XII 
1.0 INTRODUCTION 

1.1 Problem Statement 

The Farmington Bay wetlands provide essential habitat for migratory shorebirds, waterfowl, and 

waterbirds from both the Pacific and Central flyways of North America (Paul and Manning, 

2002). The valued wetland resource is at risk from encroaching development along the Wasatch 

Front. Current trends toward intensification of land uses and increasing water uses are likely to 

continue as future projections of population growth in Davis County and Salt Lake County are 

realized. An average annual population increase of 2.0% and 1.9% was projected for the 

counties, respectively, between 2005 and 2020 (DCDCED, 2005; SLCWRPR, 2008; SLC, 

2009). If population growth rates continue as forecast, then there will be significant impact to 

the quantity and quality of wetlands surrounding Farmington Bay. 

For example, effluent from nine Publicly Owned Treatment Works (POTWs) discharge to 

waterbodies and wetlands adjacent to Farmington Bay. Pollution from this type of discharge has 

been shown to be detrimental to the function and health of wetlands (Mitsch and Gosslink, 

2000). The problem is exacerbated by continued wetland loss resulting from upland 

development. Future growth projections for the area signify an increase in pollutant loading, 

additional impacts to wetland hydrology, and more wetland loss due to urban land conversion. 

At present, the condition and vulnerability of the Farmington Bay wetlands is not well 

understood. Efforts are underway to assess the nutrient enrichment problem affecting the 

Farmington Bay wetlands (Hoven and Miller, 2009). The effects of groundwater flow disruption 

also have been studied (Bishop et al., 2009) and other work is underway to prioritize habitat 

areas in need of protection (D. Paul, Avian West, personal communication). State and local 

environmental managers will benefit from this new information if it can be structured in a way 

that helps integrate and guide ongoing wetland management activities. An integrated strategy 

that protects both wetland quantity and quality is a prerequisite for promoting and sustaining the 

delivery of ecosystem services, including avian use support. 

1.2 Objective 

This research project was conducted to develop a way of forecasting and quantifying the 

cumulative effect of management practices on the future management of wetland ecosystem 

services. The study is focused on wetland support for biodiversity, and specifically examined 

management risks to the avian habitat. Retention, recovery, and removal of excess nutrients by 

the wetland resource were also analyzed. No specific analysis was conducted to determine the 

effects of nutrient loads on the ecological condition of receiving wetlands. It was beyond the 

scope of the project. Future efforts to determine the effects of nutrient loads on the ecological 

condition of receiving wetlands will likely involve the systematic monitoring and assessment of 

wetlands in the project area over time. Information about the development and deployment of a 

wetland-monitoring program for the Great Salt Lake can be found on the Utah Department of 

Environmental Quality website (http://www.deq.utah.gov/Issues/gslwetlands/index.htm). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 1 
 

The study’s design is structured around use of the Alternative Futures Approach (AFA) 

developed by Carl Steinitz (1990). The AFA has been applied to a variety of temporal landscape 

change assessments throughout the United States (Steinitz, et al., 2002). Toth (2002) applied a 

similar approach in the Wasatch Front region of Utah. AFA is a planning framework developed 

to help communities consider their options for managing land and water use. This type of 

planning helps communities articulate and understand the relationships between and 

consequences of different decision or management scenarios. 

An AFA project generates a collection of alternative landscape design scenarios for a 

geographical area. The scenarios are illustrated on maps by showing future land use. Plan trend 

scenarios depict future land use based on assumed implementation of current day management 

practices into the future. Conservation-based scenarios depict future land use based on assumed 

implementation of a plausible set of innovative protection, restoration, and treatment practices. 

Once developed, AFA design scenarios are modeled and evaluated with respect to a set of 

ecological endpoints or outcomes. In this project, the ecological outcomes of water quality and 

avian habitat use are interpreted as forecasts of ecosystem services. The application of 

evaluation models, to a hypothetical set of landscape design scenarios, demonstrates how the 

models can be used in community planning projects within the Great Salt Lake ecosystem. The 

evaluation models are the major product of this research project. 

2.0 METHODS 

2.1 Alternative Future Approach 

The Alternative Futures Approach served as the study framework for this research project. The 

AFA consists of six levels of inquiry. Each level is distinguished with a design-type question. 

The questions helped guide the development and evaluation of scenarios for managing 

Farmington Bay wetlands in context with their surrounding environment. Individual analytical 

tasks were completed with the objective of answering each of the questions. Subsections within 

this Methods section and the remaining sections of the report correlate with a specific design 

question. 

The six design questions used to structure the AFA are: 

(a) How should the landscape be described? How does the landscape operate? 

See Section 2.2: Study Area 

(b) By what actions might the current representation of the landscape be altered? 

See Section 2.3: Scenarios and Templates 

(c) How does one judge whether the current state of the landscape is working well? 

See Section 2.4: Ecosystem Services 

(d) What predictable differences might the changes cause? 

See Section 3.0: Results 

(e) “How is a decision to change or conserve the landscape to be made? 

Section 4.2: Setting Wetland Goals 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 2 
 

To complete the use of AFA, each of the design questions is addressed a second time in the 

Discussion section of this report. The flow of that discussion presents the question and topics in 

reverse order. In this manner, the discussion sets the stage for a second iteration of the AFA. 

The second iteration can be conducted by government officials and community stakeholders 

interested in sustaining the delivery of ecosystem services associated with Farmington Bay 

wetlands. 

2.2 Study Area Description 

The study area consists of the contributing watersheds and shorelands of Farmington Bay. 

Farmington Bay is a large inlet located in the southeastern quadrant of Great Salt Lake (GSL). 

Farmington Bay is located northwest of Salt Lake City and includes parts of Salt Lake County 

and Davis County (Figure 1). The major geographical features of the study are: The Great Salt 

Lake, the Jordan River Watershed, and the Farmington Bay Wetlands. 

Figure 1. Great Salt Lake Eco-region and Farmington Bay, NLCD 2001. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 3 
 

The Great Salt Lake 

The GSL is the largest saline lake in North America and the fourth largest in the world. It 

measures approximately 128 kilometers at its greatest length, 2,414 square kilometers in area, 

and 4 meters in average depth. The GSL is a terminal lake of recent geologic age (approximately 

13,000 years old). It is a remnant of Lake Bonneville, a pluvial Pleistocene lake. The Great Salt 

Lake ecosystem includes 161,880 hectares (approximately 400,000 acres) of wetlands in addition 

to other associated uplands and drainage systems. 

Its large surface area and low topographical relief make the Great Salt Lake very sensitive to 

climate-related fluctuations. Long-term patterns and trends in the rise and fall of the lake level 

are difficult to predict, although lake level is essentially determined by the balance between 

inflows and outflows. Inflows come from three major rivers (Bear River, Weber River, and 

Jordan River) and precipitation. The only outflow is evaporation. Evaporation is sensitive to 

lake area, which changes with lake level according to the bathymetry. Evaporation is also 

sensitive to salinity, which changes the lake surface saturation vapor pressure. Salinity changes 

with lake volume as the total salt load in the lake becomes concentrated or diluted (Mohammed, 

2006). The level of the Great Salt Lake has fluctuated dramatically over the years; the lowest 

water surface elevation in recent history was about 4,191 feet above mean sea level (AMSL), and 

the highest elevation was approximately 4,212 feet AMSL in 1986 (UTDNR, 2000). In 

Farmington Bay, even small fluctuations in elevation can create drastic changes in the landscape. 

Figure 2 displays the difference in lake level between 1988 and 2003. 

1988 2003 

Figure 2. Level of Great Salt Lake in 1988 and 2003 (Miller and Hoven, 2007). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 4 
In recent years, the lake level has dropped significantly due to persistent drought in the region. 

Nevertheless, the lake-level continues to fluctuate erratically. Local, county, and state managers 

are kept mindful of the potential impacts associated with lake level fluctuation. Figure 3 displays 

a hydrograph for the Great Salt Lake for the period 1992 – 2008. 

Figure 3. Hydrograph depicting Great Salt Lake surface elevation fluctuation at the South Arm from 1992-2008, 
 

USGS 2008. 
 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 5 
 
Jordan River Watershed 

Figure 4 displays the Jordan River Watershed and its conveyances. The Jordan River originates 

at the north end of Utah Lake, where a pumping station has been used to regulate its flow. It 

flows north past the Turner Dam, where water is diverted into a series of canals. The Jordan 

River is then impounded and diverted in numerous locations for agricultural irrigation and 

municipal and industrial purposes (CH2MHILL, 2005). The river continues north into the Salt 

Lake City metropolitan area, where the outflows of the Central Valley Water Reclamation 

Facility and South Valley Water Reclamation Facility are introduced to the river. The majority 

of the flow is eventually diverted to the Surplus Canal. The remaining flow of the Jordan River 

disperses into impounded wetlands located in the southeast portion of Farmington Bay. 

Figure 4. Jordan River basin and conveyances. 

As the Jordan River flows through its watershed and into Farmington Bay, the river receives 

water from many streams flowing down from the Wasatch and Oquirrh mountain ranges. It also 

receives water from sources outside of the basin via several aqueducts and canals. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 6 
Farmington Bay Wetlands 

The Farmington Bay wetlands are part of a shorelands environment that is defined by elevation. 

The upland boundary for the shorelands is 4,230 feet, and the lowland boundary is 4,200 feet 

above mean sea level (AMSL). Although the lowland boundary will change with the rise and 

fall of lake level, 4,200 feet is considered the historical average lake level. It serves as a 

boundary for our study area. See Appendix A for details on how these boundaries were 

quantified for the AFA. 

The wetlands of the Farmington Bay receive runoff and treated effluent from the Salt Lake and 

Davis County areas, and stream flows from the Jordan River and local canyons (Myers and 

Miller, 2007). The contributing tributaries in Davis County all originate from the Wasatch 

Range. They are Baird Creek, Kays Creek, and Holmes Creek, and they comprise the majority 

of drainage area for the eastern wetlands in Farmington Bay. The Davis County drainage basins 

are presented in Figure 5. 

Figure 5. Baird Creek, Holmes Creek, and Kays Creek basins and conveyances. 

The hydrology of the shorelands environment is deltaic in structure, but highly altered. All 

streams draining to Farmington Bay have been altered for agricultural and urban uses. Flow is 

predominately conveyed to and through the shorelands area in a series of canals and drainage 

ditches. The classes of wetlands that have developed in response to the drainage network vary in 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 7 
 

terms of their hydrogeomorphology (HGM) and vegetation. Many of the wetland systems have 

been impounded for waterfowl management uses. 

A functional wetland classification system was generated to reflect the highly variable and 

dynamic conditions of the landscape. The classification system takes into account the HGM and 

vegetation characteristics of individual wetland patches. It also factors the abundance, 

distribution, and condition of those patches within the larger shorelands context and in 

relationship to the delivery of ecological services. 

The four wetland classes developed for the study are: fringe, impoundment, playa, and 

emergent. The wetlands were mapped by spatially organizing and reclassifying individual 2008 

National Wetland Inventory (NWI) data (USFWS, 2008). The reclassification is displayed in 

Figure 6. 

Figure 6. Functional wetland classification based on the 2008 NWI data. 
 

*The black ovals represent the general location of each template. The final functional wetland classification is 
 

defined and represented on the right map panel as follows: White = (upland); Purple = Impounded;
 


Gray = Fringe; Dark Blue = Open water; Green = Emergent; and Peach = Playa. 
 

Playa wetlands are classified by NWI data as palustrine unconsolidated shore. Playas generally 

occur in topographic depressions (i.e., closed elevation contours) allowing for an accumulation 

of surface water. Fringe wetlands are classified by NWI data as lacustrine emergent, lacustrine 

aquatic bed, and lacustrine unconsolidated shore. Fringe wetlands are adjacent to lakes, where 

the water elevation of the lake maintains the water table in the wetland. The boundary of the 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 8 
fringe wetlands in Farmington Bay is the edge of the seasonally flooded zone, as identified by 

NWI data. The emergent wetlands are classified by NWI as palustrine emergent. Emergent 

wetlands are generally found in association with the discharge of groundwater to the land surface 

or sites with saturated overflow with no channel formation. The predominant source of water is 

groundwater or interflow discharging at the land surface. The impoundment wetlands are a 

conglomerate of all NWI wetland classes in the Farmington Bay region that are controlled by 

engineered structures. Appendix B presents a more detailed discussion of the base-line NWI 

classification. 

2.3 Management Scenarios and Template Descriptions 

The project team developed five scenarios and three templates for the project. Each scenario is a 

mapped representation of land use across the study area, including wetland management 

practices within the shorelands of Farmington Bay. The set of scenarios depict the current 

landscape setting and four alternative visions of the future. 

Each future scenario reflects a common set of urban growth and water use/availability 

projections for broader study area. The scenarios diverge relative to specific wetland and habitat 

management assumptions directed within the Farmington Bay shorelands. The assumptions are 

correlated to variables with the evaluation models used in the study. The future scenarios 

selected for this project are as follows: a) Plan Trend 4,200; average lake level ; b) Conservation 

4,200; average lake level; c) Plan Trend 4,212; high lake level and d) Conservation 4,212; high 

lake level 

The templates are a representation of “typical” landscape patches that are common across the set 

of scenarios. They are presented as functional units of the landscape. The templates are used to 

analyze how different classes of wetland patches along the shorelands respond to the 

management practices assumed in the broader scenarios. The three templates are: a) 

Impoundment Template, b) Fringe/Emergent Template, and c) Playa Template. 

2.3.1 Current Scenario 2003 

The current scenario is a baseline for measuring the cumulative effects of land use and water use 

change, as predicted for each future scenario. Data from the year 2003 were the most readily 

available for the past ten years; therefore 2003 was the year selected for the Current Scenario. 

Figure 7 presents a map of current land use and wetland class that characterize the current 

scenario. 

For Salt Lake County, current water availability estimates were obtained for the Jordan River 

Watershed from the 2005 CH2MHILL’s Flow and Return Study conducted for the Recycled 

Water Coalition (CH2MHILL, 2005). Annual estimates of ground and surface water 

withdrawals for different uses (e.g., municipal, agricultural) were obtained from publically 

available state and county reports (UTDNR, 1997; SLCWRPR, 2008; SLC, 2009). Assignment 

of withdrawals for the different months was based on observed weather patterns, stream flows, 

and seasonality of water usage. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 9 
Figure 7. Current Scenario: Land Use and Wetland GIS Layers. 

Point source discharge data were obtained from the EPA STORET database (USEPA, 1996; 

2006a). Turner Dam flows and irrigation canal flows were obtained from the Utah Division of 

Water Rights (UTDWRi, 2005). Measured monthly data were used where available and 

typically included: 1) canals with measured flow data and 2) point source dischargers. 

In Davis County, annual estimates of water imported via the Davis Aqueduct were obtained from 

the Utah Geological Survey. It was assumed that the majority of this imported water was used 

for agriculture and that a certain amount would return to streamflow after irrigation. The basins 

in Davis County also contain one major point source, and data for flows and concentrations of 

nutrients and sediment from that facility were obtained from the EPA STORET database 

(USEPA, 1996; 2006a). 

2.3.2 Future Scenarios 

The four alternative future scenarios are based on land use projections for the year 2030. Those 

projections are available from development planning agencies in Salt Lake and Davis Counties. 

For example, Salt Lake County has produced estimates of land use change based on population 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 10 
projections to the year 2030 (WAQSP, 2009). These data were used in this study to adjust land 

use in the entire Jordan River Basin. Land Use adjustments were further adjusted using proposed 

changes presented by the Northwest Quadrant Master plan (SLCPZ, 2007). 

Also, all four alternative future scenarios are based on the same set of assumptions about future 

water availability in 2030. Water availability reflects the flow return projections from 

wastewater treatment plants, groundwater discharge, municipal and industrial discharges, inputs 

from canal diversions and other withdrawals. 

Future projected flow estimates from Salt Lake County wastewater treatment plants were 

obtained from the County and included an additional facility in Riverton (SLCWRPR, 2008). 

Future projected withdrawals for various uses in the year 2030 were estimated based on 

information from multiple sources (Utah Water Data Book, 1997 and CH2MHILL, 2005). 

In Davis County, point source flow data were altered for the future scenarios based on population 

projections from the Central Davis Sewer District 2008 Operating Budget (CDSD, 2007). 

Assumptions were not made regarding future nutrient concentrations in wastewater flows. 

2.3.3 Plan Trend 2030 Scenarios 

Figure 8 presents a map of land use and wetland class that characterizes the Plan Trend scenario. 

The Plan Trend scenarios characterize the future landscape under two different water level 

elevations for the Great Salt Lake. One elevation is 4,200 feet. It is the average lake level and 

reflects associated landscape conditions. The other elevation is 4,212 feet. It is the highest lake 

level elevation. The two scenarios are called Plan Trend 4,200 and Plan Trend 4,212. Each of 

the Plan Trend scenarios assumes that current policies and development/conservation trends will 

continue into the future (Baker, et al. 2004). The Plan Trend scenarios were constructed based 

on projected population growth, land use change, increase in flow delivery and nutrient loads, 

and a decrease in the quantity of upland wetlands. For the Plan Trend scenario, wetlands and 

associated “interior habitat” above 4,212 feet elevation were removed from the land use data 

layer. Interior habitat is described in the next Section and Appendix C. Wetlands between the 

4,212 feet and 4,217 feet elevation are assumed to be at risk from conversion, and are likewise 

converted within the scenario to upland land use. The design assumption is that “lost” wetlands 

will be replaced with a mix of low-density development and parks. Below 4,212 feet elevation, 

wetlands are assumed generally safe from development. The design assumption regarding loss 

of Plan Trend wetlands in the 4,212-4,217 feet elevation zone takes into account that the Federal 

Emergency Management Administration (FEMA) has established a critical elevation line for 

planning around Farmington Bay at 4,217 feet (SLCPZ, 2008). Development below 4,217 feet 

poses risk of significant damage to property, persons, and structures as lake levels increase and 

recede. Based on FEMA’s evaluation, Salt Lake County and, to a lesser extent, Davis County 

adheres to a “no build” zone below 4,217 feet. For purposes of the Plan Trend scenario, the 

assumption is that development adapts to that restriction through engineering practices (e.g., 

elevated floodplain filling). The other design assumption is that the current extent of the 

invasive plant, Phragmites, will increase by a perimeter rate of 5 meters per year. The 

assumption is based on an average of perimeter expansion rate (PER) values (Phelps, 2005). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 11 
Phragmites is an invasive species that has been monitored and actively managed in the 

Farmington Bay wetlands. Appendix C presents additional information about Phragmites. 

Figure 8. Plan Trend 4,200 Lake-level Scenario: Land Use and Wetland GIS Layers. 

Wetlands are removed above 4,212 and replaced with low-density development. 

2.3.4 Conservation 2030 Scenarios 

Figure 9 presents a map of land use and wetland class that characterize the Conservation 

scenario. A Conservation scenario assumes a priority emphasis on ecosystem protection and 

restoration strategies that are realistic and feasible for all stakeholders (Baker, et al., 2004).The 

Conservation scenarios focus on restoration and conservation of wetlands. The Conservation 

scenarios (“4,200” and “4,212”) use the same land use and water use assumptions for Salt Lake 

County and Davis County as presented in the Plan Trend scenario. Those assumptions reflect the 

use of conventional management practices to manage population growth. However, the 

Conservation scenario differs notably from the Plan Trend scenario in that certain wetlands are 

categorically designated for conservation and restoration. The Conservation Scenario identifies 

all natural wetlands below 4,217 feet as critical lands for protection and restoration. The 

Scenario also assumes that there will be no net loss in the quantity and quality of wetlands above 

4,217 feet elevation within the shorelands area (i.e., between 4217 feet and 4230 feet elevation). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 12 
Figure 9. Conservation 4,200 Lake-level Scenario: Land Use and Wetland GIS Layers. 

Low density development increases, but wetlands above 4,217 are not removed. 

The “no net loss” design assumption includes provision for the restoration of wetlands and 

associated habitat in the shorelands area to offset wetland degradation and conversion. An 

assessment of potential restoration opportunity was performed to identify areas suitable for 

restoration under the Conservation scenarios. Those mapped areas provide the resource capacity 

needed to sustain the no net loss design. 

Rules for locating restoration opportunities were established prior to development of the GIS 

methodology. A full description of those mapping rules, along with the methodology and 

representation of the GIS datasets used to create the restorations opportunity map, can be found 

in Appendix C. GIS variables selected to identify potential restoration opportunities are: 30-

meter buffer around all conveyances, wetland class, hydric soils, interior habitat, and 

Phragmites. The categories of restoration opportunities are as follows: Public or Private High 

Potential, Public or Private Potential, Phragmites Removal Potential, and presence of Hydric 

Soils. These are the areas identified in the Conservation scenario. The restoration opportunity 

map is shown in Figure 10. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 13 
Figure 10. Potential restoration opportunity. 

High potential restoration opportunity is mapped as areas they have been “screened” to take into 

account the following factors: 30-meter buffer around flow conveyances, all-hydric soils, interior 

habitat of at least 30 meters, and not categorized as seasonally or permanently flooded wetlands 

by NWI data. Potential restoration opportunity is mapped as all-hydric or partially-hydric soils 

and not categorized as seasonally or permanently flooded wetlands in NWI. Any wetlands or 

areas immediately adjacent to wetlands that have Phragmites are considered potentially 

restorable and therefore fall into the potential Phragmites removal class. Any areas that display 

all-hydric or partially-hydric soils are noted as having a hydric-soils potential for restoration 

opportunity. 

2.3.5 2030 Lake Level Rise Scenarios 

For both the Conservation and Plan Trend scenarios, the effects of a lake level rise to 4,212 feet 

were taken into account. FEMA flood assessment GIS data, along with a digital elevation model 

(DEM), were used to produce a simulation of lake level rise to 4,212 feet. That simulation 

allowed for an evaluation of wetland acreage change resulting from higher lake water levels. 

Figures 11 and 12 depict the lake level rise scenarios. In Figures 11 and 12, the open water 

(blue) of the 4,212 Scenarios inundates the wetlands along the lake shore when compared to the 

4,200 scenarios (see Figures 7, 8, and 9). The Conservation 4,212 Scenario (Figure 12) shows 

more emergent wetlands then the 4,212 Plan Trend scenario (Figure 11). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 14 
 

Figure 11. Plan Trend 4,212 Lake-level Scenario: Land Use and Wetland GIS Layers. 

Wetlands are removed above 4,217 and replaced with low density development. 

Open water is increased to 4,212 feet. 

Figure 12. Conservation 4,212 Lake-level Scenario: Land Use and Wetland GIS Layers.
 


Low-density development increases, but wetlands above 4217 are not removed. 
 

Open Water is increased to 4,212 feet. 
 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 15 
2.3.6 Study Templates 

The templates are a representation of “typical” landscape patches that are common across the set 

of Farmington Bay shorelands scenarios. They are presented as functional units of the 

landscape. The templates are used to analyze how different classes of wetland patches along the 

shorelands respond to the management practices assumed in the broader scenarios. The name of 

each template corresponds to the dominate class of wetland within the template. 

The boundaries of a template were identified using the following criteria: A complex of 

wetlands, fed by a conveyance, with an established entry point, a delineated drainage basin, a 

hydrology connected by surface waters, and with a down-gradient boundary defined by the edge 

of the temporally flooded lacustrine unconsolidated shoreline zone at 4,200 feet AMSL (the 

Great Salt Lake surface elevation). Templates were selected with guidance from the project 

team based on data availability and whether or not the area was a typical example of occurrence 

of wetland complex types (e.g., impoundment, fringe, playa). 

2.3.6.1 Impoundment Template 

Figure 13 displays the Impoundment template. The “Impoundment” template is a 2,230-acre 

wetland complex consisting of a string of several diked units located primarily within the 

boundaries of the Ambassador Duck Club. The major conveyance delivering flows to this 

template is the Ambassador Cut, which carries diverted water from the Jordan River via the 

Surplus Canal, through the template and into Farmington Bay. Flows to the Ambassador cut are 

first subjected to a series of dams, diversions, and wetlands. There is a flow gauge with minimal 

data on the Ambassador cut. Impoundments are critical for controlling high flows, administering 

water rights allocations, and managing habitat for migratory waterfowl. 

Figure 13. Impounded template, associated wetlands, basin boundary, and conveyances. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 16 
2.3.6.2 Fringe/Emergent Template 

The “Fringe/Emergent” template is a large, 10,922-acre complex of wetlands located on the 

eastern shore of Farmington Bay. The fringe template is comprised mainly of lacustrine wetland 

types on the southwestern edge of the template. Moving up slope, the Fringe template becomes 

dominated by emergent class wetlands. Three major conveyances deliver flows to this template 

(i.e., Baird Creek, Holmes Creek, and Kays Creek). The Central Davis Sewer District is located 

at the outflow of Baird Creek into the Farmington Bay wetlands. The Central Davis Sewer 

District is a publicly owned collection system and treatment plant serving the Farmington, Fruit 

Heights, and Kaysville areas. Also located in this template is the 4,000-acre Great Salt Lake 

Shorelands Preserve. There are no observed flow gauges on the creeks. Figure 14 displays the 

Fringe/Emergent template. 

Figure 14. Fringe/Emergent template, associated wetlands, basin boundaries, and conveyances. 

2.3.6.3 The Playa Template 

Figure 15 displays the Playa template. The “Playa” template is a 1,167-acre wetland complex 

located in the northwest corner of Salt Lake County, just north of Interstate 80. The major 

conveyances delivering flows to this template is the North Pointe Consolidated Canal and the 

Goggin Drain. Both structures carry diverted water from the Jordan River and flow into the 

Great Salt Lake at the Kennecott Mitigation wetlands. The gauge on the Goggin Drain is located 

approximately 7 miles downstream from the Surplus Canal, 3.3 miles north of Saltair, and 7.2 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 17 
miles north of Magna. The Goggin Drain carries natural drainage and surplus water spilled from 

canals, with an annual mean flow of 245 cubic feet per second. The maximum recorded 

discharge of the Goggin Drain is 1,850 cubic feet per second on June 10, 2006. In many years, 

there were periods of time with no observed flow (USGS, 2008). 

Playa class wetlands represented in the template are shallow depressional systems that have 

highly variable hydric periods. Playa wetlands can fluctuate from dry and wet throughout the 

entire year. A Playa can be vegetated or non-vegetated. If vegetated, the cover type will depend 

on frequency of inundation with saline water. The wetlands in this template are managed by the 

Inland Sea Shorebird Preserve. Water level fluctuation within the wetlands is controlled to 

support their use by migratory shorebirds and waterbirds. 

Figure 15. Playa template, associated wetlands, basin boundary, and conveyances. 

2.4 Ecosystem Services and Evaluation Models 

The Millennium Ecosystem Assessment (MEA, 2005) provides a comprehensive discussion and 

analysis of the wetland ecosystem services. The MEA also provides rationale for using 

ecosystem services as an endpoint for strategies aimed at the wise management and use of 

wetlands. For purposes of this study, we focused on two specific services attributed to 

Farmington Bay wetlands: (1) Support for avian habitat and (2) control of excess nutrients and 

pollutants. These two services were selected in response to perceived community concern about 

human well-being and their consideration for the intrinsic value of avian species and associated 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 18 
ecosystems. The two services were also selected to help develop a better understanding of the 

interplay between ecosystem services. 

2.4.1 Ecosystem Service - Support for avian habitat 

Farmington Bay wetlands currently provide important avian habitat as assessed by surveys of 

bird presence and use. They support approximately one million breeding shorebirds and several 

million transients. Snowy Plovers (Charadrius alexandrinus), American Avocets (Recurvirostra 

americana), Black-necked Stilts (Himantopus mexicanus), and Long-billed Curlews (Numenius 

americanus) use the Farmington Bay wetlands for nesting and migratory purposes. Huge 

numbers of transients, including a large percentage of the world’s adult Wilson’s Phalaropes 

(Phalaropus tricolor), large numbers of Red-necked Phalaropes (P. lobatus), Long-billed 

Dowitchers (Limnodromus scolopaceus), Western Sandpipers (Calidris mauri), and Marbled 

Godwits (Limosa fedoa) use these wetlands (Orning et al. 2006). The abundance, distribution, 

and condition of various types of wetland patches that are correlated with specific avian life 

history uses (e.g. nesting grounds, foraging and staging areas for migratory shorebirds and 

waterbirds) are additional measures of habitat suitability and availability. Wetland managers in 

Farmington Bay have historically utilized the existing topography and water management of the 

Jordan River to manage shorebird and waterbird habitat with water control structures and 

impoundment wetlands. The diverse shorebird habitats of Farmington Bay include: 1) large 

saline lake systems primarily of importance to post-breeding and migrant shorebirds, 2) complex 

freshwater marshes of importance to breeding and migrating shorebirds, 3) vast upland areas 

near wetlands, providing critical breeding habitat to several species, and 4) agricultural fields 

that serve both as breeding and foraging sites. Additional shorebird habitat is provided 

periodically by a vast array of ephemeral wetlands and playas, numerous human-made 

impoundments, and riparian areas (Orning et. al. 2006). 

An Avian Wetland Habitat Assessment Model (AWHA) was developed to help formalize 

relationships about expected bird use based on the abundance and distribution of wetland habitat 

types. Wetland landscape profiles were developed as part of the AWHA. A wetland landscape 

profile is way of tallying and reporting the abundance of wetland classes within a defined area. 

The theory behind using wetland landscape profiles is that the abundance, distribution, and 

condition of wetlands in the landscape reflect the broad scale of processes that sustain 

ecosystems (Bedford 1996, Bedford 1998, Gwin 1999, Johnson 2005). Those same processes 

factor into the delivery of ecosystem services. The wetland landscape profiles that were 

developed for the AWHA can be viewed as a coarse index of wetland support for avian habitat, 

one of the key ecosystem services provided by these wetlands. 

Lastly, a nutrient and sediment transport model was calibrated for the study area to develop an 

understanding of pollutant risk posed to wetland habitats. The AWHA model and watershed 

transport model are described in the following sections. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 19 
 

2.4.1.1 Development of the Avian Wetland Habitat Assessment (AWHA) Model 

The Avian Wetland Habitat Assessment (AWHA) is a GIS-based model developed for this 

project to evaluate the availability of suitable avian habitat in Farmington Bay under a variety of 

future scenarios. The model framework combines GIS data and a priori knowledge to apply 

spatial weights indicating the availability of different classes of suitable habitat for various bird 

groupings. GIS data that represent different anthropogenic and environmental variables are used 

to predict where a particular species is most likely to be located on the landscape. 

The first phase of the spatial analysis involved establishing the indicative variables of species 

distribution. Variables were assigned a spatial weight commensurate with their influence on the 

distribution of a particular bird grouping on the landscape. For instance, the presence of 

Phragmites may be an indicator of poor habitat for some species, but it may not be an indicator 

of poor habitat for another species. Variables used to determine the preferred location of a 

species in the landscape can have a gradient of influence. Therefore, the weight is considered 

“fuzzy” (i.e., not confined to Boolean classification, where there is either a “1” value assigned 

for presence or a “0” value assigned for absence). 

For each species, a particular variable may also hold a greater or lesser importance when 

compared to another variable. Consequently, not only is a weight assigned for each variable as 

an indicator for a particular species, but the variables are also weighted in relation to each other. 

This secondary weight is referred to as variable strength. Local avian experts assisted with the 

preliminary assignment of weights to the variables. The GIS raster, vector and imagery datasets 

used to develop AWHA were obtained from the following sources: Utah Department of 

Environmental Quality, Utah Department of Transportation, Ducks Unlimited, and SWCA 

Environmental Consultants. Figure 16 depicts an example of the raster datasets created using the 

weighted variables as determined by the local GSL experts based on best professional 

judgement. These data layers, when combined, yield maps of habitat suitability. These maps are 

used to describe the current and predicted species distributions across the Farmington Bay 

wetlands. The highest index value (5) represents the highest class of suitable habitat available in 

the template. As the index trends toward lower values (1), the scores are decreasing and the 

habitat is progressively “less suitable”. Figure 17 presents the variables weighting system and 

raster calculation applied to estimate avian habitat. Figures 18, 19, and 20 display the resulting 

avian habitat suitability index for Migratory Shorebirds, Migratory Waterfowl, and Migratory 

Water birds. A summary of the data matrices, variables, and processes used for the development 

of AWHA is presented in Appendix D. It should be emphasized that the habitat index produced 

by this model does not indicate the presence or absence of a species. Rather, the model predicts 

the change in the highest class of suitable habitat available for each bird grouping under 

conditions set by the future scenarios that were defined as part of the AFA. All proportional 

results evaluate the departure of each future scenario from the current scenario. The lower 

classes of habitat suitability could be similarly evaluated; however, this analysis focuses solely 

on the highest class of habitat suitability. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 20 
 

Figure 16. Example of raster datasets that represent variables used to calculate availability of suitable habitat. 

The final value of the weighed raster cell is calculated by summing the products of weighted variable strengths 

(1-6). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 21 
Figure 17. Variable weight hierarchy: Variables are assigned a “strength” (VS). 
 

Which relates the variables to one another, and a weight (wt) to grade levels within each variable. 
 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 22 
Figure 18. Suitable Migratory Shorebird habitat available in total study area under current scenario conditions. 

Red (#5) represents highest availability ranking. 

Figure 19. Suitable Migratory Waterfowl habitat available in total study area under current scenario conditions. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 23 
Figure 20. Suitable Migratory Waterbird habitat available in the total study area. 

Under current scenario conditions. 

2.4.1.2 Calibration of the AVGWLF Model for the Jordan River Basin 

An ArcView-enabled, enhanced version of the Generalized Watershed Loading Function 

(GWLF) Model was used to model nutrient and sediment transport for the Jordan River Basin. 

The objective of this modeling was to build understanding about the risks posed by the delivery 

of pollutants to wetlands and avian habitat. The AVGWLF model is an ArcView-enabled, 

enhanced version of the Generalized Watershed Loading Function (GWLF) Model originally 

developed by Haith and Shoemaker (1987). The original GWLF model was developed in the 

state of New York to simulate runoff, sediment, and nutrient (nitrogen and phosphorus) loadings 

from a watershed with various land uses, soil distributions, and management practices. The 

enhanced AVGWLF model was developed by Dr. Barry Evans at Pennsylvania State University 

for use by the Pennsylvania Department of Environmental Protection. It has been used by 

numerous state and federal agencies for simulating watershed processes and allocating pollutant 

loadings among various sources. The final calibrated model allowed the outputs of water flow, 

sediment, and nutrients being delivered to the Farmington Bay wetlands from the various sources 

throughout the watershed to be simulated. Based on these known sources of present-day loading, 

various future scenarios can be modeled in AVGWLF to predict future loads in the wetlands due 

to various changes in the watershed. Figure 21 displays a screen-capture of the AVGWLF 

application in an Arc GIS user window. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 24 
Figure 21. Screen-Capture of Jordan River ArcV iew Generalized Watershed Loading Function (AVGWLF). 

Model calibration was performed for the period 1995-2005. During this task, adjustments were 

iteratively made in various model parameters until a “best fit” was achieved between simulated 

and observed stream flow and sediment and nutrient loads. Based on the calibration results, 

revisions were made in various AVGWLF routines to alter the manner that model input 

parameters were estimated. Statistical evaluations of the accuracy of flow and load predictions 

were made. Appendix E presents a more detailed discussion of the calibration results and 

statistics. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 25 
Yearly estimates of ground and surface water withdrawals for different uses (e.g., municipal and 

agricultural) were obtained from publically available state and county reports (UTDNR, 1997; 

SLCWRPR, 2008). These yearly estimates were spread out among the 12 months of the year 

and over the 11 years of simulation (1995-2005) based on best professional judgment. Observed 

weather patterns, stream flows, and seasonality of water usage were taken into account. All 

point source discharge data were obtained from the US EPA STORET database (USEPA, 1996; 

2006a). Turner Dam flows, as well as irrigation canal flows, were obtained from the Utah 

Division of Water Rights (UTDWRi, 2008). Daily flow data for the Surplus Canal gauge were 

obtained from the USGS National Water Information System (USGS, 2008). Corresponding 

water quality data were obtained from EPA’s STORET database (USEPA, 1996; 2006a). To 

derive historical nutrient loads, standard mass balance techniques were used. First, the in-stream 

nutrient concentration data and corresponding flow rate data were used to develop load (mass) 

versus flow relationships for each watershed. Using the daily stream flow data obtained from the 

USGS, daily nutrient loads for the 1995-2005 periods were computed for the watershed using the 

appropriate load versus flow relationships. Loads computed in this fashion were used as the 

“observed” loads against which model-simulated loads were compared. 

During this process, adjustments were made to various model input parameters to obtain a “best 

fit” between the observed and simulated data. With respect to stream flow, adjustments were 

made for evapotranspiration and “lag time” (i.e., groundwater recession rate) for subsurface 

flow. For nutrient loads, changes were made to the estimates for subsurface nitrogen and 

phosphorus concentrations. For sediment loads, revisions were made to the estimates of stream 

bank erosion. Further information regarding the calibration of AVGWLF can be found in 

Appendix E. 

2.4.1.3 Calibration Statistics 

For the monthly comparisons of actual data and model results, mean R2

 values of 0.86, 0.80, 

0.94, and 0.90 were obtained for flow, sediment, phosphorus, and nitrogen, respectively. 

Considering the inherent difficulty in achieving optimal results across all measures (along with 

the potential sources of error), these results are very good. The monthly Nash-Sutcliffe 

coefficients of 0.86, 0.80, 0.92, and 0.74 were high considering that they approach their 

respective R2 values. A detailed description of the statistical analysis for the AVGWLF 

calibration is presented in Appendix E. 

2.4.2 Ecosystem Service-Assessing GSL Wetland Retention of Nutrients 

The Farmington Bay wetlands buffer the effects of watershed nutrient loading (UTDNR, 2000; 

Hoven et al, 2006; UTDEQ, 2008; SLCWRPR, 2008; Bishop et al, 2009; SLC, 2009). Since 

2004, the Utah Division of Water Quality has been characterizing the wetland ecosystems of 

Farmington Bay. They have also been assessing the potential effects of nutrient loads from 

publicly-owned treatment works (POTWs) and other natural and anthropogenic sources on the 

assimilative capacity of the Farmington Bay wetlands (UTDEQ, 2008). However, no similar 

research to quantify nutrient retention by these wetlands was available at the time the current 

study was conducted. Natural wetlands have been shown to “buffer” the impacts of nutrient 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 26 
 

 

delivery to a lacustrine system (Coveney et al, 2002). However, there is a limit to a natural 

wetland’s capacity for retaining nutrients (Richardson and Qian, 1999). It has also been 

demonstrated that wetland nutrient retention efficiency can be reduced as nutrient loads increase 

above a certain threshold (Richardson and Qian, 1999). Furthermore, when considering 

phosphorus, it has been demonstrated that once a natural wetland is saturated, unacceptable 

amounts of phosphate can actually be exported from a wetland that was once effective at 

retaining nutrients (Qian and Richardson, 1997b; Richardson and Qian, 1999). 

An important ecosystem service provided by wetlands is water quality improvement through 

pollutant retention. A large volume of water is diverted from the Jordan River and into various 

wetland complexes before reaching Farmington Bay. This water has nutrient and sediment loads 

associated with it, and the wetland complexes in Farmington Bay are assumed to provide a 

certain amount of treatment to these loads. Understanding the capacity of the Farmington Bay 

wetlands to retain nutrients and sediment is necessary for a quantitative valuation of this 

particular ecosystem service. As a practical first step to analyze the assimilative capacity of GSL 

wetlands, a rudimentary wetland cellular water quality model was developed was developed for 

GSL impounded wetlands based on a first-order removal rate calculation: 

 (-k/HLR) Cout = Cin e 

Cout = concentration of outflow pollutant, mg/l 

Cin = concentration of inflow pollutant, mg/l 

k = pollutant removal rate constant, m/yr 

HLR = hydraulic loading rate (Q/A), m/yr 

Q = annual runoff (i.e., surface water inflow rate), m3/yr 

A = wetland surface area, m2 

As shown in Figure 22, ten individual wetland cells were identified within the Impoundment 

Wetland Template (Template Description – See Section 2.3.6.1). The cellular water quality 

model equation was applied to each cell to simulate phosphorus and sediment retention. The 

Impoundment Template was chosen as a demonstration site due to its configuration in the 

landscape and the availability of water quality and flow data from the US EPA STORET 

database (USEPA, 1996; 2006a). These observed data were used to calibrate the wetland water 

quality model for conditions specific to the Impoundment Template. A detailed discussion of the 

development and calibration of the wetland cellular water quality model is presented in 

Appendix F. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 27 
Figure 22. Ambassador Wetland cells and STORET stations. 

Located within the boundary of the Impounded Template. 

The AVGWLF watershed-loading model was used to simulate nutrient and sediment delivery to 

the Impoundment Template. This watershed loading was applied as the initial input to the 

wetland cell model. Output concentrations were calculated for each cell using the first-order 

removal rate equation described above. The wetland cells are arranged in such a way that output 

concentrations for one cell serve as the input concentrations for the following cell. This 

approach was used to simulate nutrient retention in the Impoundment Template for the baseline 

condition as well as for various future watershed-loading scenarios. The approach is 

transferrable to other wetland templates that have relatively well defined boundaries. Flow and 

water quality data is necessary in order to calibrate the model for each template, as wetland 

retention rates vary widely and are site-specific. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 28 
 

3.0 RESULTS 

Study results are presented in four sections. The first section (3.1) describes data from analysis 

of wetland acreage differences among the scenarios and associated templates. Section 3.2 

describes how differences in wetland acreage among the scenarios and templates affect the 

availability of suitable habitat for migratory waterfowl, shorebirds, and waterbirds. Section 3.3 

presents predicted trends in nutrient and sediment pollutant loading to wetlands based on the 

AVGWLF model. The last section (3.4) presents results from the cellular water quality model 

for the impoundment wetlands. 

3.1 Wetland Landscape Profiles 

The wetland landscape profiles for the total study area and for each template are presented in the 

following tables, charts, and narrative. Figure 23 displays the acreage of wetlands, as distributed 

in each elevation zone for the Current Scenario. The majority (76%) of wetland acreage is 

located in the zone from 4,200 to 4,212 feet, which spans the range of the historical average 

water level elevation to the high water level elevation. Changes to land use or land cover in this 

elevation range will have the greatest effect on wetland landscape profiles. Wetland acreage 

decreases in elevation zones that exceed the high water level. The 4,212 - 4,217 feet zone 

accounts for 21% of wetland acreage, the 4,217 - 4,220 feet zone accounts for 2%, and the 4,220 

- 4,230 feet zone accounts for the remaining 1%. 

76% 

21% 

2% 1% 4200-4212 

4212-4217 

4217-4220 

4220-4230

 Figure 23. Distribution of total wetland acres among elevation zones. 

Figure 24 and Table 1 display the wetland landscape profiles for the total study area, with 

wetlands distributed by wetland functional class. Wetland acreage is lost for all wetland classes 

under each scenario. For both lake elevations, 4,200 feet and 4,212 feet, the total wetland 

acreage lost is less for the Conservation scenario, 16% and 14% respectively, as compared to the 

Plan Trend scenario. The Conservation 4,200 and Plan Trend 4,200 scenarios are the most 

protective of the Fringe wetland class and least protective of the Impounded and Emergent 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 29 
0

10000

20000

30000

40000

50000

60000

70000

Current Conservation

4200

Plan Trend

4200

Conservation

4212

Plan Trend

4212

Scenario

Acres

Impounded Fringe Playa Emergent

wetland classes respectively. The Conservation 4,212 and Plan Trend 4,212 scenarios are the 

most protective of the Playa wetland class and least protective of the Fringe wetland class. 

0 

10000 

20000 

30000 

40000 

50000 

60000 

70000 

Current Conservation 

4200 

Plan Trend 

4200 

Conservation 

4212 

Plan Trend 

4212 

Scenario 

Acres 

Impounded Fringe Playa Emergent 

Figure 24. Wetland landscape profile for the Total study area. 

Table 1. Proportional analysis of wetland acreage for the total Farmington Bay study area. 

Total wetland acreage for each wetland class under different scenarios 

Wetland 

Class 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Impounded 27722 22182 19929 6569 4609 

Fringe 16893 16530 15709 612 99 

Playa 5602 5322 3667 5169 3531 

Emergent 20532 19320 12916 10377 4191 

Total Wetland 70749 63354 52221 22727 12430 

Percent change for each wetland class under different scenarios 

Impounded - -20% -28% -76% -83% 

Fringe - -2% -7% -96% -99% 

Playa - -5% -35% -8% -37% 

Emergent - -6% -37% -49% -80% 

Total Wetland - -10% -26% -68% -82% 

Figure 25 and Table 2 display the proportional wetland landscape profiles for the Fringe/ 

Emergent template. When assessing the change to wetland acreage in the Fringe/Emergent, 

Playa, and Impoundment wetland templates separately (Figs. 25-27 and Tables 2-4), 

Conservation 4,200 and Plan Trend 4,200 are the most protective of the Fringe wetland class for 

all three templates, consistent with the total study area results. Conservation 4,212 and Plan 

Trend 4,212 are the most protective of the Playa wetland class and least protective of the Fringe 

wetland class for all three templates, consistent with the total study area results. For all three 

templates, the Conservation scenario results in less wetland acreage lost as compared to the Plan 

Trend scenario. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 30 
 

In summary, the Conservation scenario leads to less wetland acreage loss than the Plan Trend 

scenario at both the 4,200 feet and 4,212 feet lake elevations for the three templates and the total 

study area. At the 4,200 feet lake elevation, the Fringe wetland class is the most protected and at 

the 4,212 feet lake elevation, the Playa wetland class is the most protected for all three templates 

and the total study area for either scenario. 

0 

1000 

2000 

3000 

4000 

5000 

6000 

7000 

8000 

9000 

10000 

11000 

Current Conservation 

4200 

Plan Trend 

4200 

Conservation 

4212 

Plan Trend 

4212 

Scenario 

Acres 

Impounded Fringe Playa Emergent 

Figure 25. Wetland landscape profile for the Fringe/Emergent template. 

Table 2. Proportional analysis of wetland acreage for the Fringe/Emergent template. 

Total wetland acreage for each wetland class under different scenarios 

Wetland 

Class 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Impounded 1 0 0 0 0 

Fringe 5365 5360 5311 2 2 

Playa 470 470 413 460 404 

Emergent 4706 4687 3717 2056 1081 

Total Wetland 10542 10517 9441 2518 1487 

Percent change for each wetland class under different scenarios 

Impounded - -100% -100% -100% -100% 

Fringe - 0% -1% -100% -100% 

Playa - 0% -12% -2% -14% 

Emergent - 0% -21% -56% -77% 

Total Wetland - 0% -10% -76% -86% 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 31 
cenar o

0 

100 

200 

300 

400 

500 

600 

700 

800 

900 

1000 

1100 

Current Conservation 

4200 

Plan Trend 

4200 

Conservation 

4212 

Plan Trend 

4212 

S i 

Acres 

Impounded Fringe Playa Emergent 

Figure 26. Wetland landscape profile for the Playa template. 

Table 3. Proportional analysis of wetland acreage for the Playa template. 

Total wetland acreage for each wetland class under different scenarios 

Wetland 

Class 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Impounded 162 157 120 6 4 

Fringe 697 687 613 9 7 

Playa 103 99 90 92 83 

Emergent 48 47 37 14 8 

Total Wetland 1010 990 860 121 102 

Percent change for each wetland class under different scenarios 

Impounded - -3% -26% -96% -98% 

Fringe - -1% -12% -99% -99% 

Playa - -4% -13% -11% -19% 

Emergent - -2% -23% -71% -83% 

Total Wetland - -2% -15% -88% -90% 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 32 
 

0 

200 

400 

600 

800 

1000 

1200 

1400 

1600 

1800 

2000 

2200 

Current Conservation 

4200 

Plan Trend 

4200 

Conservation 

4212 

Plan Trend 

4212 

Scenario 

Impoundment Fringe Playa Emergent 

Acres 

Figure 27. Wetland landscape profile for the Impoundment template. 

Table 4. Proportional analysis of wetland acreage for the Impoundment template. 

Total wetland acreage for each wetland class under different scenarios 

Wetland 

Class 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Impounded 1567 1544 1421 393 333 

Fringe 432 430 422 5 3 

Playa 75 72 54 67 49 

Emergent 38 38 29 11 7 

Total Wetland 2112 2084 1926 476 392 

Percent change for each wetland class under different scenarios 

Impounded - -1% -9% -75% -79% 

Fringe - 0% -2% -99% -99% 

Playa - -4% -28% -11% -35% 

Emergent - 0% -24% -71% -82% 

Total Wetland - -1% -9% -77% -81% 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 33 
 

3.2 Avian Wetland Habitat Assessment 

The results of the avian wetland habitat assessment for total study area and for each template are 

presented in the following tables, charts, and narrative. Figure 28 displays an example of the 

spatial analysis performed for migratory shorebirds in the Fringe/Emergent template. The 

highest index value (5) represents the highest class of suitable habitat available in the template. 

Class 5 indicates areas where the maximum combination of the six weighted variables sums to 

yield the highest scores. As the index trends towards lower values (1), the scores are decreasing 

and the habitat is progressively “less suitable”. Further interpretation of these results is 

presented in Section 4.0 (Discussion and Conclusions). 

Figure 28. The above map displays the highest class of suitable habitat for Migratory Shorebirds available under 

various future scenarios in the Fringe/Emergent Template. 

Figure 29 and Table 5 display the change in the acreage of the most suitable habitat for each bird 

group for the total study area. Habitat is lost for all bird groups under each scenario at the 4,200 

feet elevation. There is a 2% increase in suitable habitat acreage for the Migratory Waterfowl 

bird group under the Conservation 4,212 scenario. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 34 
 

 

-16% 

-14% 

-12% 

-10% 

-8% 

-6% 

-4% 

-2% 

0% 

2% 

4% 

Conservation 

4200 

Plan Trend 

4200 

Conservation 

4212 

Plan Trend 

4212 

Scenario 

% change from Current Scenario 

Migratory Shorebirds Migratory Waterfowl Migratory Waterbirds 

Figure 29. Proportional analysis of the most suitable habitat class for the Total study area. 

Table 5. Change in habitat availability for each future scenario for the Total study area. 

Total acreage of most suitable habitat for each bird group under different scenarios 

Bird 

Group 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Migratory Shorebirds 16285 15796 14323 15980 14515 

Migratory Waterfowl 12536 12102 11100 12734 11710 

Migratory Waterbirds 14135 13667 12286 13811 12412 

Change in most suitable habitat acres for each bird group under different scenarios 

Migratory Shorebirds - -489 -1962 -305 -1770 

Migratory Waterfowl - -434 -1437 197 -826 

Migratory Waterbirds - -468 -1849 -324 -1723 

Percent change in most suitable habitat for each bird group under different scenarios 

Migratory Shorebirds - -3% -12% -2% -11% 

Migratory Waterfowl - -3% -11% 2% -7% 

Migratory Waterbirds - -3% -13% -2% -12% 

Suitable habitat changes across the three wetland templates (Figs. 30-32 and Tables 6-8, below) 

show habitat loss for all bird groups at the Conservation 4,200 and Plan Trend 4,200 scenarios. 

Increases in suitable habitat for migratory waterfowl in the Fringe/Emergent and Playa templates 

account for the sole increase in habitat for the Conservation 4,212 scenario in the total study area 

analysis. Despite modest increases in suitable habitat for migratory waterfowl and migratory 

waterbird groups at the 4,212 feet lake elevation, the overall trend is decreasing habitat 

suitability for each scenario. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 35 
 

-24% 

-21% 

-18% 

-15% 

-12% 

-9% 

-6% 

-3% 

0% 

3% 

6% 

Conservation 

4200 

Plan Trend 

4200 

Conservation 

4212 

Plan Trend 

4212 

Scenario 

% change fromCurrent Scenario 

Migratory Shorebirds Migratory Waterfowl Migratory Waterbirds 

Figure 30. Proportional analysis of the most suitable habitat class for the Fringe/Emergent template. 

Table 6. Change in habitat availability for each future scenario for the Fringe/Emergent template. 

Total acreage of most suitable habitat for each bird group under different scenarios 

Bird 

Group 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Migratory Shorebirds 1847 1833 1509 1838 1511 

Migratory Waterfowl 918 905 880 987 953 

Migratory Waterbirds 2754 2667 2112 2669 2112 

Change in most suitable habitat acres for each bird group under different scenarios 

Migratory Shorebirds - -14 -339 -10 -336 

Migratory Waterfowl - -12 -38 69 35 

Migratory Waterbirds - -87 -642 -85 -641 

Percent change in most suitable habitat for each bird group under different scenarios 

Migratory Shorebirds - -1% -18% -1% -18% 

Migratory Waterfowl - -1% -4% 7% 4% 

Migratory Waterbirds - -3% -23% -3% -23% 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 36 
 

 

-24% 

-21% 

-18% 

-15% 

-12% 

-9% 

-6% 

-3% 

0% 

3% 

6% 

Conservation 

4200 

Plan Trend 4200 Conservation 

4212 

Plan Trend 4212 

Scenario 

%change from Current Scenario 

Migratory Shorebirds Migratory Waterfowl Migratory Waterbirds 

Figure 31. Proportional analysis of the most suitable habitat class for the Playa template. 

Table 7. Change in habitat availability for each future scenario for the Playa template. 

Total acreage of most suitable habitat for each bird group under different scenarios 

Bird 

Group 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Migratory Shorebirds 384 378 335 386 345 

Migratory Waterfowl 307 302 259 320 281 

Migratory Waterbirds 270 265 211 283 232 

Change in most suitable habitat acres for each bird group under different scenarios 

Migratory Shorebirds - -6 -48 2 -38 

Migratory Waterfowl - -4 -48 13 -26 

Migratory Waterbirds - -6 -60 12 -38 

Percent change in most suitable habitat for each bird group under different scenarios 

Migratory Shorebirds - -2% -13% 1% -10% 

Migratory Waterfowl - -1% -16% 4% -8% 

Migratory Waterbirds - -2% -22% 5% -14% 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 37 
 

 

-12% 

-10% 

-8% 

-6% 

-4% 

-2% 

0% 

2% 

Conservation 

4200 

Plan Trend 

4200 

Conservation 

4212 

Plan Trend 

4212 

Scenario 

% change fromCurrent Scenario 

Migratory Shorebirds Migratory Waterfowl Migratory Waterbirds 

Figure 32. Proportional analysis of most suitable habitat class for the Impounded template. 

Table 8. Change in habitat availability for each future scenario for the Impounded template. 

Total acreage of most suitable habitat for each bird group under different scenarios 

Bird 

Group 

4,200 4,212 

Current Conservation Plan Trend Conservation Plan Trend 

Migratory Shorebirds 1077 1047 963 1063 986 

Migratory Waterfowl 971 937 872 961 899 

Migratory Waterbirds 844 830 768 840 779 

Change in most suitable habitat acres for each bird group under different scenarios 

Migratory Shorebirds - -30 -114 -14 -91 

Migratory Waterfowl - -34 -99 -9 -72 

Migratory Waterbirds - -15 -76 -4 -65 

Percent change in most suitable habitat for each bird group under different scenarios 

Migratory Shorebirds - -3% -11% -1% -8% 

Migratory Waterfowl - -3% -10% -1% -7% 

Migratory Waterbirds - -2% -9% -1% -8% 

3.3 AVGWLF Watershed Loading Model 

The AVGWLF model was calibrated for current conditions in order to provide estimates of 

future watershed loading of nutrients and sediment under various scenarios. Figure 33 displays 

the monthly flows and loads for an average year in the Jordan River basin (1995-2005). Field 

monitored sediment transport for the Jordan River basin is reported here as Total Suspended 

Solids (TSS).Figures 34, 35, and 36 and Tables 9, 10, and 11 display the loads by source for the 

Jordan River basin. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 38 
Figure 33. Mean Monthly Flows and Loads in the Jordan River. 

Table 9. Phosphorus Loads-By-Source. 

Source TP (lbs/yr) 

Point Sources 804,230 

Turner Dam & Canals 64,132 

Hay/Pasture 328 

Cropland 359 

Forest 272 

Developed Open Space 561 

Quarry/Barren Land 1,287 

Low Intensity Development 1,682 

High Intensity Development 3,890 

Stream Bank 450 

Septic Systems 190 

Groundwater 4,690 

Wetlands 4 

Unpaved Roads 2 

TOTAL 882,077 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 39 

Turner 

Dam & Nonpoint

Canal Sources 

Flows 2% 

Point 

Sources 

91 % 

7% 

Figure 34. Phosphorus Loads By Source. 
 

 

 

Table 10. Nitrogen Loads By Source. 

Source TN (lbs/yr) 

Point Sources 2,436,212 

Turner Dam & Canals 1,355,373 

Hay/Pasture 2,456 

Cropland 2,457.7 

Forest 2,246 

Developed Open Space 1,057 

Quarry/Barren Land 5,953 

Low Intensity Development 10,093 

High Intensity Development 35,716 

Stream Bank 1,022 

Septic Systems 2,216 

Groundwater 853,644 

Wetlands 128 

Unpaved Roads 15.5 

TOTAL 4,708,589 

Sources of Nitrogen Loading 

Nonpoint 

Sources 

19% 

Point 

Sources 

52% 

Turner 

Dam & 

Canal 

Flows 

29% 

 Figure 35. Nitrogen Loads By Source. 

Table 11. Sediment Loads By Source. 

Source TSS (lbs/yr) 

Turner Dam & Canals 61,202,881 

Hay/Pasture 27,976.7 

Cropland 123,789.6 

Forest 363,255.7 

Developed Open Space 32,231.6 

Quarry/Barren Land 1,976,841 

Low Intensity Development 93,344 

High Intensity Development 12,941 

Stream Bank 20,438,355 

Wetlands 331 

Unpaved Roads 2,755.8 

TOTAL 84,274,702 

Sources of Sediment Loading 

Stream 

Bank 

Erosion 

24% 

Other 

Sources 

3% 

Turner 

Dam & 

Canal 

Flows 

73% 

 Figure 36. Sediment Loads By Source. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 40 
Flows and loads of sediment, phosphorus, and nitrogen were modeled for six sub-basins draining 

to the Farmington Bay wetlands under current conditions using the data and assumptions 

previously described (see Appendix E). Table 12 displays the net-modeled flows and loads for 

the current scenario after accounting for all withdrawals and extractions. 

Table 12. Current Scenario Model Output: net loads after withdrawals and extractions. 

Basin 

Flow Total Phosphorus Total Nitrogen Sediment 

Cfs mg/l pounds mg/l pounds mg/l pounds 

Jordan 628.3 0.69 859,723 3.40 4,213,152 51.03 63,165,452 

Impoundment 34.95 0.79 54,291 3.86 266,054 28.28 1,947,677 

Playa 299.13 0.83 486,290 4.08 2,403,814 39.49 23,273,750 

Total Fringe 37.07 0.77 56,562 5.36 391,118 8.18 597,118 

Baird 16.87 1.68 55,656 9.84 326,976 4.46 148,334 

Holmes 7.63 0.02 284 1.58 23,829 11.32 170,143 

Kays 12.57 0.03 621 1.63 40,311 11.25 278,640 

In the Current scenario, the Goggin Drain flows and loads are almost entirely dependent on flows 

and loads leaving the Jordan River at the Surplus Canal diversion. The Jordan River, in turn, is 

heavily influenced by the two major point sources in the Jordan Basin. Model results show that 

Total nitrogen (TN) and Total Suspended Solids (TSS) both increase and decrease on a monthly 

basis along with flow. In contrast, Total Phosphorus (TP) loading remains relatively constant 

throughout. This information suggests that TP is derived predominately from point source 

discharge since environmental flows seem not to affect TP loading. Thus, conditions in the 

Goggin Drain appear to be heavily influenced by the Jordan Basin point source dischargers. 

Sediment loads derive largely from streambank erosion in the Jordan Basin and Turner Dam 

canal flows entering the Jordan Basin. 

Future scenario nutrient and sediment loading 

Table 13 displays the modeled flows and loads for the six sub-basins under the two future 

scenarios. Figure 37 presents the change in delivered watershed loads estimated for the Jordan 

River and for the Davis County sub-basins for the Plan Trend and Conservation scenarios. 

Tables 14 and 15 describe the change in watershed loadings for each scenario and template. 

Table 13. Percent change in loads from current conditions under future scenarios. 

Basin 

Total Phosphorus Total Nitrogen Sediment 

Plan Trend Conservation Plan Trend Conservation Plan Trend Conservation 

Jordan 50% 50% 24% 24% -8% -9% 

Impoundment 36% 34% 15% 6% 18% 15% 

Playa 38% 38% 18% 17% 39% 39% 

Total Fringe 33% 26% 27% 20% -3% -5% 

Baird 33% 26% 32% 24% 17% 13% 

Holmes 16% 13% 0% -3% -2% -3% 

Kays 21% 17% 0% -3% -15% -16% 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 41 
Figure 37. Percent Change of basin delivered loads from the Jordan River basin and the Davis County sub-basins 

under Plan Trend and Conservation scenarios. 

Table 14. Plan Trend Future Scenario Watershed Loading: percent change indicates change in loading from 

Current scenario. 

Flow Total Phosphorus Total Nitrogen Sediment 

% % % 

Basin cfs mg/l pounds change mg/l pounds change mg/l pounds change 

Jordan 713.2 0.92 1,293,884 50% 3.72 5,231,031 24% 41.17 57,842,230 -8% 

Impoundment 40.4 0.92 73,937 36% 3.57 307,127 15% 28.35 2,307,498 18% 

Playa 402.8 0.85 671,585 38% 3.57 2,830,445 18% 40.89 32,449,376 39% 

Total Fringe 37.7 0.70 75,362 33% 5.05 494,950 27% 11.48 577,899 -3% 

Baird 19.0 2.02 74,280 33% 11.68 430,957 32% 4.99 173,542 17% 

Holmes 7.2 0.03 331 16% 1.66 23,739 0% 15.33 167,314 -2% 

Kays 11.4 0.04 752 21% 1.81 40,255 0% 14.12 237,043 -15% 

Table 15. Conservation Future Scenario Watershed Loading: percent change indicates change in loading 

from Current scenario. 

Flow Total Phosphorus Total Nitrogen Sediment 

% % % 

Basin cfs mg/l pounds change mg/l pounds change mg/l pounds change 

Jordan 711.2 0.92 1,293,590 50% 3.73 5,222,649 24% 41.24 57,777,645 -9% 

Impoundment 39.7 0.93 72,740 34% 3.61 282,282 6% 28.72 2,347,832 15% 

Playa 401.7 0.85 671,086 38% 3.57 2,821,833 17% 40.97 32,417,914 39% 

Total Fringe 37.7 0.96 71,201 26% 6.29 467,547 20% 7.62 566,136 -5% 

Baird 19.0 1.87 70,153 26% 10.82 405,570 24% 4.49 168,258 13% 

Holmes 7.2 0.02 321 13% 1.62 23,058 -3% 11.58 164,953 -3% 

Kays 11.4 0.03 727 17% 1.73 38,919 -3% 10.33 232,924 -16% 

Tables 16, 17, and 18, display the wetland retention for the sub-basins under the three scenarios. 
 

The retention rates of individual wetlands were not changed for the different scenarios. Only the 
 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 42 
 

amount of wetland available to retain nutrients and sediments was changed. Nutrient retention 

by the wetlands located in the upper portions of the Jordan River basin was negligible because 

those wetlands comprise a negligible percentage of the total basin area. Wetland retention rates 

were estimated from literature values compiled by the project team into a wetland BMP 

database. Much of the information summarized in the database is available from the 

International Stormwater Best Management Practices Database (ISBMP, 2008). 

Table 16. Current scenario wetland retention of nutrients and sediment. 

Basin 

Estimated % of Basin that 

drains through a wetland 

Basin Wetland Retention (lbs) 

TP TN Sediment 

Ambassador Cut 95% 501 15,782 41,226 

Goggin Drain 29% 116 1,757 7,253 

Total Fringe 14% 3937 29,447 24,380 

Baird 13% 3869 24,196 5,560 

Holmes 18% 28 2,513 9,000 

Kays 12% 40 2,738 9,820 

Table 17. Plan Trend scenario wetland retention: percent change indicates change in wetland retention from 

the Current scenario. 

Basin 

Estimated % 

of Basin that 

drains 

through a 

wetland 

Basin Wetland Retention 

TP TN Sediment 

lbs % change lbs % change lbs % change 

Ambassador Cut 95% 1,079 115% 22900 45% 51,500 25% 

Goggin Drain 2% 17 -85% 171 -90% 617 -91% 

Total Fringe 7% 797 -80% 7696 -74% 11,280 -54% 

Baird 2% 750 -81% 4617 -81% 920 -83% 

Holmes 13% 23 -18% 1757 -30% 6,320 -30% 

Kays 6% 23 -41% 1322 -52% 4,040 -59% 

Table 18. Conservation scenario wetland retention: percent change indicates change in wetland retention 

from the Current scenario. 

Basin 

Estimated % 

of Basin that 

drains 

through a 

wetland 

Basin Wetland Retention 

TP TN Sediment 

lbs % change lbs % change lbs % change 

Ambassador Cut 95% 971 94% 20927 33% 48,590 18% 

Goggin Drain 29% 218 88% 2216 26% 8,047 11% 

Total Fringe 14% 4955 26% 35087 19% 23,180 -5% 

Baird 13% 4877 26% 30012 24% 6,260 13% 

Holmes 18% 32 13% 2432 -3% 8,800 -2% 

Kays 12% 46 17% 2643 -3% 8,120 -17% 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 43 
 

3.4 Nutrient retention capacity of impoundment wetlands 

The calibrated wetland cellular water quality model for the “Impoundment” template performed 

well for a newly tested approach. The predicted removal efficiency for phosphorus was 74% 

and -11% for sediment removal. Table 19 displays the predicted vs. observed values for each 

cell in the template under current watershed loading conditions. The model was calibrated to 

approximate outflow concentrations at Cell I by using an average pollutant removal rate constant 

in all cells. See Appendix F for further discussion of model development and calibration. 

Figure 38 below displays the predicted retention of Total Phosphorus and Sediment in the 

Impounded template as predicted by the Wetland Cellular Water Quality Model for each 

scenario. Figure 39 presents the spatial framework generated for the model. Figure 40 and 

Figure 41 below display the calibrated results for cells that had observed data, as well as the 

predicted results for cells without data. 

Table 19. Predicted vs. Observed Removal Efficiencies: Impoundment Template, NA=Not Available. 

Wetland Cell TP Outflow (mg/l) Sediment Outflow (mg/l) 

Predicted Observed Predicted Observed 

Utah Duck Club 0.48 0.44 28 23 

A 0.45 0.65 28 23 

B 0.44 NA 28 NA 

C 0.44 NA 28 NA 

D 0.43 NA 28 NA 

E 0.41 NA 28 NA 

F 0.26 NA 30 NA 

G 0.21 0.22 30 29 

H 0.17 0.16 31 41 

I 0.13 0.14 31 33 

Total Phosphorous Sediment 

Figure 38. Retention of Total Phosphorous and Sediment modeled for the Impoundment template under three future 

watershed-loading scenarios. 

As can be observed in Figure 40, Cell A is particularly notable as it is the only cell that appears 

to export phosphorus (the concentration is higher than the previous cell’s concentration). This 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 44 
could be due to a number of factors, including groundwater inputs, unidentified surface inputs, 

differences in soil or vegetation type, and saturation of the cell with phosphorus. There is also an 

overall increase in sediment concentration in the Impoundment template wetlands, although the 

first two cells remove a small amount of sediment. Cell H is particularly notable for its large 

increase in sediment concentration between the inlet and the outlet. It is likely that there is an 

unknown surface input here (see Appendix F). The overall increase in sediment concentration 

could be due to pulsing flows that re-suspend deposited sediments or to unidentified surface 

inflows carrying additional sediment. 

Figure 39. Impoundment Conceptual Framework. 

Figure 40. Observed and Simulated Results for Total Phosphorous. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 45 
 

Sediment

0

5

10

15

20

25

30

35

40

45

UT A B C D E F G H I

Duck

Club

Wetland Cell

Sediment (mg/l)

Simulated

Observed

Figure 41. Observed and Simulated Results for Sediment 

Table 20 displays the results of model runs for the template under the current scenario and two 

future scenarios. “TP in” and “Sediment in” are AVGWLF model outputs and serve as the 

inputs, or watershed loading to the impoundment template. “TP out” and “Sediment out” are the 

concentrations leaving the wetland template and entering Farmington Bay. 

Table 20. Wetland Cellular Water Quality Model Results. 

Scenario TP in TP out Sediment in Sediment out 

Current 0.51 0.13 27.81 31.43 

Conservation 0.57 0.18 21.19 23.49 

Plan Trend 0.56 0.18 20.76 22.96 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 46 
4.0 DISCUSSION AND CONCLUSIONS 

The main objective to this study was to demonstrate use of the Alternative Futures Approach for 

wetland protection and conservation planning for Farmington Bay of the Great Salt Lake. An 

outcome of the study is an analysis of evaluation models that can be used in that approach. This 

discussion provides an interpretation of how study results can be used to set wetland 

management goals for Farmington Bay and the Great Salt Lake. A detailed analysis of the 

evaluation models used in the study is found in the appendices of this report. 

4.1 Setting Wetland Goals – Connecting Results to a Decision-Making Framework 

This research project focused on use of the AFA to compile, organize, and analyze technical 

information. The desired outcome of study was to produce information that will help inform 

decisions and build strategies for conserving the landscape that supports the wetlands of 

Farmington Bay. This discussion sets the stage for the technology transfer of methods and 

results to project partners working to protect the Great Salt Lake Ecosystem and its valued 

wetlands. The discussion is guided by the same “questions” listed at the beginning of major 

section of this report, except the questions are presented in reverse order. 

4.1.1 Decision Making: Landscape Change and Conservation 

Landscape ecology and information technology have matured together as a powerful toolkit for 

ecosystem analysis and goal setting. Conceptually, the conservation of natural processes is the 

ecological foundation of restoration planning, implementation and the evaluation of project 

success. Those processes, such as flowing water, produce physical structure within the 

environment. The structure helps to support life. Life is sustained because the flow of water and 

materials through the structure is not impeded beyond levels to which it has evolved and adapted 

to (i.e. life history or ecological “niche”). Decisions to change or conserve the landscape should 

be made reflective of these relationships. 

Along these lines, public and private investments made to protect the Great Salt Lake Ecosystem 

and its valued wetlands continue to grow. However, stress on the Ecosystem likewise continues 

to increase due to the intensification of land use, increasing demand for water and climate 

change. Environmental managers are challenged to develop ways of keeping pace with the rate 

of landscape degradation and associated loss of ecosystem services. 

Looking at the problem from the ground up reveals a basic fact: Project-by-project 

environmental review by communities leaves too little time and money for regulatory, 

conservation and development to adequately plan and assess land and water use. Monitoring is 

frequently inadequate to reveal problems or trigger corrective actions. Looking down from the 

landscape level reveals a path toward problem reconciliation. The path follows upon a strategic 

scaling-up of project planning through environmental program integration. Such integration can 

be guided through consideration and adoption of explicit ecosystem management goals for the 

wetlands and associated habitats of the Great Salt Lake. Those goals can be developed through 

an open community process that examines a plausible set of Alternative Futures. Once 

established, the goals are used to guide decisions about how to conserve or change the 

environmental landscape. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 47 
4.1.2 Predicting Change: Understanding the Consequences of Management Decisions 

The choice to adopt environmental goals as a guide for decision-making can be influenced by a 

number of factors. This AFA provides insight about the consequences of a choice in actions or 

scenarios. Key to that type of analysis is the development and calibration of evaluation models 

that are applied to a set of design scenarios. The water quality models, avian use model and 

wetland landscape profiles used in the project all show promise as useful tools in a future 

community-based application of the AFA. 

Project results also provide a starting point for the design of a more elaborate conservation 

scenario. For example, future conservation design can take into account the following results 

from this study: 

(1) The wetland landscape profiles for the total study area, under conditions set by all future 

scenarios, predict a reduction of acreage in each class of wetland landscape as described by the 

templates. 

(2) The most notable difference between the Conservation and the Plan Trend scenarios at both 

the 4,200 and 4,212 feet elevations, occurs in the Emergent and Playa wetland classes. The 

Conservation scenario protects approximately 30% more wetlands than the Plan Trend for both 

classes. 

(3) The AWHA model predicts that availability of the most suitable category of habitat for each 

bird grouping will decrease in all of the future scenarios for the total study area except for 

Migratory Waterfowl in the Conservation 4,200 scenario. 

(4) The Wetland Cellular Water Quality model predicts that, for the system as a whole, the 

impoundment wetlands in the Farmington Bay shoreland area will remove phosphorus and 

export sediment, which is consistent with observed data. However, discrepancies in removal 

efficiencies for individual wetlands within the impoundment template indicate that there are 

unaccounted sources of phosphorus and sediment in the present model. A better conceptual 

model and more data would improve the reliability of the Wetland Cellular Water Quality model 

predictions. 

(5) All future scenarios show a large increase in watershed loading of both Total Phosphorus and 

Total Nitrogen in the evaluated sub-basins. The results are attributed to the overwhelming 

influence of the point sources and loads entering the Jordan River at Turner Dam. Changes in 

the land use of the sub-basins do not affect loads from these two sources. 

These results suggest that the conservation scenario designed for the study was not sufficiently 

robust to address the risk of loss in the delivery of ecosystem services of interest. A more 

rigorous analysis of plausible protection, conservation, and treatment practices is needed. At the 

same time, better information about the effectiveness of those practices will be needed to guide 

their deployment and justify their cost. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 48 
4.1.3 Predicting Change: Designing Plausible Scenarios Representing the Landscape Based on 

Past and Innovative Practices 

Each of the project’s future scenarios reflects the cumulative outcome of environmental policy, 

practices, and individual project decisions. Experience gained during the project revealed that at 

least three environmental management “workstreams” influence the abundance, distribution, and 

condition of wetlands in the project area. Each workstream represents a cadre of environmental 

professionals and their community partners working with clear intent to protect and conserve the 

Great Salt Lake and its associated habitats. 

The most profound influence on the wetland landscape is produced by practitioners with the job 

of conservation delivery. Both private and public wildlife managers have over many decades 

worked to control the abundance, distribution, and condition of wetlands in the project area to 

optimize the resource for avian use. Another influential group of practitioners are those involved 

in the federal Clean Water Action Section 404 regulatory program. The interplay between 

agency regulators, resource agency staff, public and private development interests, and 

environmental consultants leads to permit decisions that control the rate of conversion of 

wetlands to uplands. The third workstream involves the work of water quality managers. Both 

private and public water quality managers play a pivotal role in attempting to protect the 

wetlands of the Great Salt Lake from degradation caused by pollution and pollutants. 

The design of the Plan Trend and Conservation Scenarios used in this study present two different 

examples of the way these workstreams function in the project area. The Plan Trend Scenarios 

(like the Current Scenario) assume that each workstream operates independent from one and 

another. In contrast, the Conservation Scenarios are organized around a common set of mapped 

wetland restoration opportunities. The only way that the opportunity can be fully realized is 

through cross-program collaboration that is guided by a common set of environmental goals. 

For example, the AFA reveals that the risk of wetland loss or degradation can be correlated to 

resource occurrence within different elevation strata controlled by Great Salt Lake level. 

Wetlands located below 4212’ elevation are primarily at risk of degradation from nutrient loads 

in their receiving waters. Wetlands located between 4212 - 4217 feet are confronted with the 

combined risk of pollutant degradation and conversion to upland development. Wetlands above 

4217 feet are at high risk of conversion to uplands. A conservation scenario designed to manage 

this pattern of risk will need to be much more explicit than described in this study. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 49 
However, that scenario can build on the results of the study by more specifically describing the 

coordinated placement and design of protection, restoration, and treatment practices within the 

three project templates. The scenario also can articulate how environmental policy is 

coordinated across programs and authority to ensure the delivery of those practices. The types of 

practices include: 

1. Wetland protection and preservation, 

2. Wetland restoration 

3. Aquatic buffer conservation 

4. Flow conveyance conservation (“conservation pool”) 

5. Constructed wetland treatment systems 

6. Waste water treatment system technological upgrades. 

The types of environmental programs and authorities needed to coordinate the delivery of those 

management practices include: 

•	 The Great Salt Lake Ecosystem Program, including state wildlife conservation programs 

•	 Utah’s State Water Quality Management Program 

•	 Great Salt Lake Comprehensive Management Planning Program 

•	 The federal Clean Water Act Section 404 Regulatory Program 

•	 Salt Lake City Corporation, Salt Lake County, Davis County Community Development 

and Public Works Departments 

•	 Private, corporate and not-for-profit community-based conservation programs 

One type of innovative environmental initiative that might serve as a catalyst to align the 

authorities and practices is a water quality-trading program. Water quality trading is based on 

the premise that pollutant sources in a watershed can face very different costs to control the same 

pollutant. Trading programs allow facilities facing higher pollution control costs to meet their 

regulatory obligations by purchasing environmentally equivalent (or superior) pollution 

reductions from another source at lower cost, thus achieving the same water quality improvement 

at lower overall cost (USEPA, 2003). 

The commissioning of a study on the feasibility of building a water quality-trading program to 

serve portions of the Great Salt Lake may be an attractive idea for several reasons. The primary 

reason for considering a trading program is that constructing or restoring wetlands, in addition to 

traditional abatement technologies, have a demonstrated capacity to reduce sediment or nutrient 

loadings, while also supporting habitat and other ecosystem services (USEPA, 2007 a, b). 

Lessons learned from wetland compensatory mitigation banking and the study of conservation 

delivery programs can provide added clarity about the opportunities and challenges using 

wetland construction and restoration to meet multiple program objectives (Rafini and Robertson, 

2005; Gleason et al., 2008). There are many economic considerations that will have to be 

studied before incorporating wetlands in a water quality-trading program (Heberling et al, 2007). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 50 
4.1.4 Evaluating the Current State of the Landscape 

Perhaps the largest information gap encountered during this AFA was the limited amount of 

monitoring and assessment data on Farmington Bay wetlands and their associated habitats. Such 

data is needed to build an understanding, with known certainty, about how changing wetland 

abundance, distribution, and condition affect the delivery of valued ecosystem services. The data 

also can be used to build and implement the assessment framework used to set environmental 

goals, integrate programs, prioritize projects and practices, and report on the cumulative 

environmental effectiveness of management actions, including water quality crediting and trades. 

The US EPA has provided to states technical guidance on the implementation of wetland 

monitoring and assessment programs (USEPA, 2006b). Part of the guidance describes use of a 

three-level assessment strategy. The strategy describes an integrated use of landscape-scale, 

rapid and intensive assessment protocols for evaluating whether a wetland landscape is “working 

well” or not. This AFA demonstrated how landscape-scale information (i.e., wetland landscape 

profiles) can be a valuable tool for guiding wetland management decisions. As each new level of 

assessment comes on line, the certainty of environmental predictions, forecasts, and effectiveness 

reporting will increase. A study of the feasibility of expanding the scope of wetland monitoring 

and assessment in Farmington Bay and across the broader Great Salt Lake is a prerequisite for 

alternative analysis work in the region. 

4.1.5 Describing How the Landscape Functions 

As mentioned above, the AFA demonstrated how broad-scale assessment information can be 

organized and used to describe management scenarios. The project also demonstrated the use of 

environmental modeling to forecast the possible consequences of those scenarios. Field level 

monitoring and assessment information is used to strengthen the technical efficacy of those 

landscape assessment and modeling approaches. Additional research is also needed to build the 

scientific underpinnings and complete the science portfolio of tools needed to describe the 

functioning of the Farmington Bay wetland landscape and explain how it works. A specific set 

of recommendations about how to improve the next iteration of Farmington Bay Wetland AFA 

are presented in section 5.0. 

5.0 Model Performance and Recommendations for Improvements 

5.1 Recommendations for the Wetland Landscape Profiles 

In all templates, the playa wetlands are the least affected by lake-level rise, although this result is 

somewhat misleading. Certain areas of Farmington Bay display a topography that is too flat for 

the 10-meter digital elevations model (DEMs) to adequately represent the effects of lake-level 

rise. It is probable that a higher percentage of topographical depressions are located below 4,212 

feet than is currently represented by the 30 meter DEM used for this study. Therefore, it is also 

possible that the playa wetlands in all templates could be flooded and subsequently transformed 

to fringe or semi-permanent and permanently flooded lacustrine class in a scenario with a lakelevel of 4,212 feet. To improve the wetland scale profiles, it is recommended that a more 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 51 
detailed elevation dataset be obtained and processed. The most promising strategy for obtaining 

a refined elevation dataset involves the processing of available Light Detection and Ranging 

(LIDAR) remote sensing data. 

Considering the recent trend towards drier conditions in the Great Salt Lake eco-region, it would 

be advantageous to develop future scenarios that consider lake level and water table decline. In 

recent years, the lake has dropped well below the average lake level of 4,200 feet. Additional 

research on lake-level fluctuation patterns and groundwater interactions would improve 

predictions of future impacts to the current wetland landscape profile for Farmington Bay. 

Bishop et al. (2008) conducted a study on groundwater, ranging from the Wasatch Range in 

Davis County to the palustrine wetlands of the Eastern Shore of Farmington Bay. This research 

suggested how vegetative changes in the palustrine fringe wetlands could be realized as water 

withdrawals increase and lake level fluctuates. Mohammed (2006) evaluated the complex 

variables controlling the Great Salt Lake level. 

It is recommended that the 2008 NWI data used in the functional classification be evaluated for 

accuracy. For this study, several errors in classification were noted and corrected by the research 

team. Errors in the NWI data typically fell into one of two categories: 1) misclassification of 

unconsolidated bottom and aquatic bed in the impounded wetland classes, or 2) misclassification 

of lacustrine wetlands, possibly associated with inaccurate representation of bathymetry. 

5.1.1 Avian Wetland Habitat Assessment (AWHA) Performance 

AWHA represents the “first cut” of a spatial modeling methodology that can be easily modified 

with both updated GIS data and revised variables and weights. The model functioned well in 

ArcGIS and produced logical results, which are in-line with the overall expectations for habitat 

suitability in Farmington Bay. Efforts are already underway to refine this preliminary modeling 

assessment. Utah Department of Natural Resources has funded a research project to improve 

and validate the methodology developed for the AWHA model. The variables and weights used 

for this project will be closely evaluated and revised as necessary to produce refined results. An 

analysis of this framework’s potential to predict presence or absence of bird species and/or 

habitat abundance will be evaluated using various spatial statistics. The goal of the new project 

is that a validated model will be applied to the entirety of the eastern shore of the GSL for 

identification of wetland habitat areas for multiple bird groupings. By utilizing the resulting 

species-specific, statistically validated habitat data, managers will be able to prioritize the 

development of conservation and management strategies for wetland units. 

5.1.1.1 Recommendations for AWHA 

A number of revisions can be made to produce more accurate results for the AWHA spatial 

model. The most imperative revision may be the utilization of a higher quality elevation dataset. 

As previously stated, the current elevation data layer (10 meter DEM) is inadequate for 

representing the low relief displayed in the Farmington Bay topography, particularly for the 

Playa template in the “Northwest Quadrant”. Refined elevation data will result in a more 

accurate representation of water depth in the Fringe and Playa wetlands, while also potentially 

allowing for a more precise evaluation of management scenarios in the Impoundment wetlands. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 52 
 

Watershed loading variables can potentially be included in an evaluation of suitable habitat in the 

Farmington Bay wetlands. Estimates of nutrient (nitrogen and phosphorous) loads, sediment 

loads, and conveyance flow rates were delivered to the wetlands using the AVGWLF watershed 

loading model. These three watershed-loading variables (flow, nutrients, and sediment) were 

weighted for potential use in the avian model; however, no GIS data was identified to adequately 

spatially represent the variables. A recommendation for future work is to explore the feasibility 

of creating spatial datasets to support these additional watershed-loading variables. Including the 

effects of watershed loads on habitat suitability would enhance model predictions. For example, 

under higher nutrient loading conditions, Phragmites will out-compete alkali bulrush, causing a 

loss of forage. All of the conveyances eventually output to the Fringe wetlands. Increased 

nutrients may be particularly problematic for Migratory Waterbirds, which use the Fringe 

wetlands for foraging. Another example is that increased conveyance flows might boost the 

functional habitat acreage in the playa wetlands, particularly during high-flow events. Overbank 

flows give rise to sheet-flow and create new foraging habitat outside of the standard boundaries 

of the wetlands. 

5.1.2 AVGWLF Performance 

The utility of models such as AVGWLF lies in their ability to predict watershed loading with 

reasonable accuracy in the presence of limited data. The AVGWLF data preparation and 

calibration used for this study could be valuable for managers interested in estimating nutrient 

and sediment loads for a variety of endpoints. The model and the supporting data could be 

transferred for use in other parts of north-central Utah with relative ease through the 

incorporation of local data or knowledge regarding the watershed budget (inputs and outputs). 

During the calibration process, adjustments were made to the various input parameters to obtain 

a “best fit” between the observed and simulated data. One of the challenges to calibrating a 

model is to optimize the results across all model outputs. In the case of AVGWLF, the outputs 

are stream flow and sediment, nitrogen, and phosphorus loads. As with any watershed model 

such as GWLF, it is possible to focus on a single output measure (e.g., sediment or nitrogen) in 

order to improve the fit between observed and simulated loads. Focusing on one model output, 

however, can lead to less acceptable results for other measures. Consequently, it is sometimes 

difficult to achieve very high correlations across all model outputs. In spite of this limitation, it 

was determined that highly consistent results were obtained for the calibration site. 

The AVGWLF watershed-loading model allows for a monthly and annual analysis of nutrient 

and sediment loads by source. This analysis shows that flows and loads in the Jordan River 

Basin are largely influenced by point source dischargers and Turner Dam releases. When the 

Turner Dam releases enter the Jordan River, water is diverted from the river almost immediately 

by many canals. These canals remain within the basin and, along with the Turner Dam flows in 

the river itself, carry a large amount of water, sediment, and nutrients. There are two major point 

source dischargers located above the surplus canal in the Jordan River Basin. These facilities are 

the Central Valley Wastewater Treatment Plant and South Valley Waste Water Treatment Plant. 

The treatment plants represent the largest contributors of phosphorus and nitrogen to the Surplus 

canal and Goggin Drain. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 53 
It should be noted that additional, related studies are currently underway or being completed in 

the Jordan River watershed. Of particular interest are the Jordan River Total Maximum Daily 

Load Project (TMDL) (SLC, ongoing) and the recently completed Salt Lake County Water 

Quality Stewardship Plan (SLC, 2009). Preliminary analyses from the Jordan River TMDL 

study are summarized in the Jordan River Water Quality Total Maximum Daily Load Assessment 

(UTDWQ, 2005). Various segments of the Jordan River are listed by Utah DEQ as being 

impaired for dissolved oxygen, temperature, total dissolved solids, and E. coli. The referenced 

2005 water quality assessment provides analyses for all of these parameters and identifies 

phosphorus as the primary cause of the dissolved oxygen impairment. 

The Jordon River TMDL project team is currently developing a water quality model (QUAL2K) 

to assess the impacts of various sources of phosphorus in the Jordan River watershed on 

dissolved oxygen levels. Preliminary source assessments indicate that publically owned 

treatment works (POTWs) contribute 79% of the phosphorus load in the Jordan River (Utah 

Division of Water Quality, 2008). While this figure differs somewhat from the estimate of 91% 

in the AFA, it must be noted that two very different watershed boundaries were used in these 

studies. The AFA used a boundary with an outlet at the Surplus Canal diversion, commonly 

referred to as 2100 South, while the TMDL study is using a watershed boundary with an outlet at 

the Great Salt Lake. The larger drainage area in the TMDL study predictably results in a large 

increase in surface runoff, decreasing the relative proportion of phosphorus loading attributed to 

POTWs. 

The reasons for using different watershed boundaries in the two analyses are related to the 

different goals of each analysis. The TMDL study is being conducted in a regulatory 

environment. It is intended to identify all sources of impairment in the Jordan River watershed. 

Based on an understanding of these sources of impairment, the TMDL study will formulate a 

restoration strategy that will allow for the attainment of water quality standards in all segments 

of the river. The AFA, on the other hand, was a research project with the goal of simulating 

watershed conditions and resultant nutrient loads to the Farmington Bay wetlands under 

alternative future scenarios. Identification of sediment and nutrient sources was necessary to 

estimate future loadings due to population increases and land use change. The chosen watershed 

boundary facilitated estimation of flow, sediment, and nutrients delivered to the playa and 

impoundment wetland templates via the Surplus Canal. 

It is important to use long-term datasets when analyzing water quality data in systems with 

highly variable climatic and human influences, such as the Jordan River watershed. Assessing 

pollutant sources under drought conditions will result in overestimation of point source 

contributions, while source assessment under very wet conditions will result in overestimation of 

non-point source contributions. Consequently, a ten-year period (1995-2005) was chosen for 

analysis, which included both wet and dry conditions. Inclusion of a drought period in the 

analysis is appropriate given that future climate in the Jordan River watershed is expected to be 

drier than present day conditions (Cromwell et al., 2007). Water quality data presented in the 

Jordan River Water Quality TMDL Assessment (UTDWQ 2005) and Salt Lake County Water 

Quality Stewardship Plan (SLC 2009) are consistent with the water quality data obtained for this 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 54 
project. These reports also provide guidance on the selection of other important watershed data 

including water use, population, and land use. 

5.1.2.1 Recommendations for AVGWLF 

In the Farmington Bay sub-basins, there is a large amount of variability in flows due to intense 

management of the basin’s water resources. As a result, variability in the predicted nutrient and 

sediment loads correlates with variability in the flow. Due to this large, month-to-month 

variability, a number of assumptions were necessary when calibrating and running the model. 

This was particularly true for the withdrawal amounts in the basins. The project team made all 

efforts to obtain data from private, local, state, and federal databases to support this calibration 

and the subsequent modeling. If higher quality data is available, it could be incorporated into the 

model to produce updated results. 

Monthly conveyance flow inputs should be better quantified using a hydrologic model. It is 

recommended that a hydrologic model for the shoreland conveyances be developed to evaluate 

scenarios of flow and runoff in canals. Flow simulations in the shorelands would be very useful 

for improving the data inputs to the AVGWLF model and for estimating nutrient loads to the 

wetlands. Calibration of a hydrologic model would help with future management decisions 

regarding water use and flow. 

Calibrating a hydrologic model would require a comprehensive understanding of the current 

management strategies for individual conveyance flows and water rights in the shorelands. The 

conveyance system in the shorelands is complex and difficult to quantify. Canal flows are 

regulated based on water rights and are, therefore, erratic. The temporal variability of the canal 

flows poses the greatest challenge for modeling hydrologic processes in the shoreland. 

Therefore, documenting water rights and conveyance delivery under different flow regimes 

should be the first step in the development of a hydrological model. Assessing current water 

management strategies in both the shorelands and the drainage basins would help to ensure that 

as water availability decreases in the future, water distribution will continue to sustain the 

wetlands. 

Land use estimates are based solely on the maps provided in the Salt Lake County WatershedWater Quality Stewardship Plan report (SLC, 2009). Procurement of the actual land use GIS 

files is recommended to further improve the watershed loading estimates. Additional 

information regarding localized development (such as CAD or GIS data representations for the 

Northwest Quadrant master plan) would be useful to better estimate specific changes in the 

future. 

Additional watershed analysis should be performed on the following stream networks: a) the 

lower portion of the Jordan River Basin that delivers water to the Jordan River below the Surplus 

Canal diversion; b) the lower Jordan River drainage sub-basins, which include wastewater 

treatment facilities serving Salt Lake City; c) the Davis County drainage basins that delivers 

nutrients and flows to the Utah State Impoundments south of Baird Creek; and d) all drainage 

basins north of Kays Creek that discharge into Farmington Bay. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 55 
5.1.3 Recommendations Wetland Cellular Water Quality Model 

The wetland water quality model requires wetland cells with relatively well-defined boundaries, 

initial flow estimates, and known flow pathways between cells, and a pollutant removal rate 

constant. Pollutant removal rate constants are highly variable among sites and even among 

individual cells. Concentration estimates are thus desirable in order to calibrate the model. 

However, if unavailable, these values can be obtained from the literature. This calculation is 

applied to each cell in the template with the outflow concentration of one cell serving as the 

inflow concentration in the next cell. The hydrologic loading rate (HLR) will differ for each cell 

based on the area of the cell and the flow rate. 

The impoundment template was selected for modeling because it had readily available data and 

relatively well-defined cell boundaries. The resulting phosphorus removal rate of 74% 

corresponds with the observed values. The model simulated phosphorus retention for the 

template as a whole very well. Cell A has an observed export of phosphorus that was not 

accounted for in the model. This may suggest that wetlands that receive sustained nutrient 

loading can reach a threshold for nutrient retention. It is possible that this is occurring in Cell A, 

though more investigation is necessary to confirm this. Phosphorus export could also be 

explained by a number of other mechanisms including alternating wet and dry periods, or resuspension of sediment phosphorus due to pulsing flows. 

The model is simplified in that it disregards many components of nutrient cycling in wetlands. 

However, the model performs well at characterizing the retention of nutrients. After further 

development and improvement, the approach presented for this project could be transferred to 

other impounded wetland areas. While the utility of models lay in their ability to simulate 

systems where data is lacking, the collection of additional water quality data will always result in 

a better model calibration. For example, additional nutrient and sediment data can be used to 

better calibrate a nutrient decay model for the various classes of wetlands found in the 

Farmington Bay shorelands. This would allow the establishment of more relevant nutrient 

retention coefficients. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 56 
6.0 SUMMARY 

An “Alternative Futures Analysis” was conducted to demonstrate how models can be used to 

evaluate landscape design scenarios developed for the Farmington Bay area of the Great Salt 

Lake. Scenarios were developed which featured the design of a conservation “future” focused 

on a set of wetland protection, restoration, and conservation practices. The conservation design 

was contrasted with scenarios that reflect current day wetland management practices and an 

extrapolation of those practices into the future. Each of the future scenarios was described in 

context with the average water level elevation of the Great Salt Lake and a high water level 

elevation (4,200 feet and 4212 feet, respectively). In addition, a set of wetland “templates” was 

developed and embedded into each scenario to aid scenario design and evaluation. Each 

template represents a typical cluster or complex of wetlands with a dominant wetland class and 

they included: Impoundment wetlands, playa wetlands and fringe/emergent wetlands Evaluation 

of the scenarios was based on risks to avian habitat support caused by degradation in wetland 

abundance, distribution and condition. The evaluation entailed the use of four ecological 

modeling approaches. A relatively simple wetland landscape profile was developed to track 

change in wetland abundance, by class, across the scenarios. A Geographic Information System 

(GIS) based avian wetland habitat assessment (AWHA) was developed to predict the availability 

of suitable avian habitat. The ArcView Generalized Watershed Loading Function (AVGWLF) 

model was calibrated to predict nutrient loads to the wetlands. A wetland cellular water quality 

model was developed to evaluate nutrient retention in impoundment class wetlands. 

Project results reveal that most (97%) of wetlands in the study area are located within an 

elevation band of 4,200 feet to 4,217 feet. Results from futures analysis show a dramatic loss of 

wetlands for all templates embedded in the Plan Trend 4,212 Scenario and the Conservation 

4,212 Scenario. The Plan Trend Scenarios observe the greatest decline in the most suitable 

category of avian habitat for three bird groupings: Migratory Shorebirds, Migratory Waterbirds, 

and Migratory Waterfowl. The Conservation 4,200 Scenario protects the most wetland acreage 

and highest category of suitable avian habitat. The Plan Trend 4,200 Scenario observes the 

greatest decline in the highest class of suitable avian habitat. A substantial increase in watershed 

loading of nutrients delivered to all the templates for the Conservation and Plan Trend scenarios 

was predicted using the AVGWLF model. Results from this model also indicate that total 

phosphorus and total nitrogen loads delivered to the templates from the Jordan River watershed 

are heavily influenced by the two major point sources in the Jordan Basin. The wetland cellular 

water quality model predicted a removal efficiency of 74% for phosphorus, and -11% for 

sediment for impoundment class wetlands. 

The approach used for this project, incorporating GIS based evaluation models and including an 

“Alternative Futures Analysis”, is a transparent way of organizing and communicating complex 

scientific information to a diverse group of stakeholders and improving communication among 

stakeholders. 

The authors of this report encourage examination of the methods and results produced by this 

research project. Our hope is that lessons learned will be applied in renewed effort toward 

envisioning ways to sustain and improve the health of the Great Salt Lake Ecosystem. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 57 
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Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 63 
8.0 APPENDICES 

8.1 APPENDIX A. SHORELAND ELEVATION ZONES 

Several elements of this study relied on the use of a lake-level fluctuation simulation. The low 

relief of elevation in Farmington Bay makes determining the proper location of the lake-shore 

(meander-line) particularly important for assessing the acreage of wetlands, assessing restoration 

opportunity, and identifying avian habitat. The elevation product used for this study was a 10 

meter USGS DEM obtained in 9 coverage quads from the Utah State Geographic Information 

Database (SGID). The 9 quads were merged to a single coverage and 1 foot contours were 

interpolated. The contours were clipped to the study area. 

The location of the lakeshore meander-line is quite important when evaluating wetland acreages 

in and around Farmington Bay. With even a one foot change in lake level, open water in 

Farmington Bay can increase by thousands of acres. Generalized shoreland elevation zones were 

established to better evaluate notable elevation thresholds occurring in the landscape as well as to 

more clearly report acreage data associated with lake-level fluctuation and upland management 

decisions. 

The current scenario lake level for this study was established at the historical average of 4,200 

feet. Elevations below 4,200 feet are considered open lake-water. The high lake level was 

established at 4,212 feet based on the historical high. Wetlands between 4,212 feet and 4,217 

feet were denoted as significant. These wetlands are protected from development by zoning and 

local building practices. The Federal Emergency Management Administration (FEMA) has 

established a critical elevation line for planning around Farmington Bay at 4,217 feet (SLCPZ, 

2008). Any development below that line could result in significant damage to property, persons, 

and structures as lake levels increase and recede. FEMA 100-year flood assessments provide the 

most adequate information regarding the effects of lake level rise on both the wetlands and on 

Salt Lake and Davis County infrastructure. Wetlands located between 4,217 feet and 4,220 feet 

are considered significant. The spatial complexity and diversity of wetland types is pronounced 

despite encroaching development and the diminished water table. Above 4,220 feet, wetland 

acreage and complexity are reduced. Wetlands in that zone are at high risk for conversion to 

upland for development purposes. Figure A1 displays the shoreland elevation zones established 

for this study. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 64 
Figure A1. Shoreland Elevation Zones. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 65 
8.2 Appendix B. 2008 National Wetlands Inventory 

National Wetlands Inventory 

Although the wetlands were generalized into functional complexes, the original polygon data 

were from the 2008 NWI classification. The following paragraphs describe the NWI wetland 

types employed for this functional classification. Riverine and Lacustrine Limnetic (deep-lake 

water) wetlands were present in the landscape, but not included in this analysis or described 

below. 

The Lacustrine System 

[L] The “Lacustrine” System includes wetlands and deepwater habitats with all of the following 

characteristics: (1) situated in a topographic depression or a dammed river channel; (2) lacking 

trees, shrubs, persistent emergent vegetation, emergent mosses or lichens with greater than 30% 

areal coverage; and (3) total area exceeds 8 hectares (20 acres). The majority of lacustrine 

wetlands located in and around Farmington Bay are generally described as Littoral. Littoral 

wetlands extend from the lake-shore boundary to approximately 2 meters (6.6 feet) below annual 

low water or to the maximum extent of non-persistent emergents; if these grow at depths greater 

than 2 meters. 

The Palustrine System 

[P] The Palustrine System includes all non-tidal wetlands dominated by trees, shrubs, emergent 

vegetation, mosses or lichens, and all such wetlands that occur in tidal areas where salinity due to 

ocean derived salts is below 0.5 ppt. Wetlands lacking such vegetation are also included if they 

exhibit all of the following characteristics: 1) are less than 8 hectares (20 acres); 2) do not have 

active wave-formed or bedrock shoreline features; 3) have during low water a depth less than 2 

meters (6.6 feet) in the deepest part of the basin, and 4) salinity due to ocean-derived salts of less 

than 0.5 ppt. 

Hydrogeomorphic conditions of both the Lacustrine Littoral system and the Palustrine system 

can be classified using NWI as follows: 

1.	 [UB] Unconsolidated Bottom - Includes all wetlands and deepwater habitat with at least 

25% cover of particles smaller than stones (less than 6-7 cm), and a vegetative cover less 

than 30%. 

2.	 [US] Unconsolidated Shore - Includes all wetland habitats having the following three 

characteristics: 

a.	 unconsolidated substrates with less than 75% areal cover of stones, boulders, or 

bedrock; 

b.	 less than 30% areal cover of vegetation other than pioneering plants; and 

c.	 any of the following water regimes: irregularly exposed, regularly flooded, 

irregularly flooded, seasonally flooded, temporarily flooded, intermittently flooded, 

saturated, seasonal-tidal, temporary-tidal, or artificially flooded. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 66 
Contour Interval Classification
 

4,195 - 4,200 L2USC
 

4,194 - 4,195 L2UBF
 

4,191 - 4,194 L2UBG
 

4,189 - 4,191 L2UBH

 < 4,189 L1UBH 
 

Vegetation conditions of both the Lacustrine Littoral system and the Palustrine system can be 

classified using NWI as follows: 

1.	 [AB] Aquatic Bed - Includes wetlands and deepwater habitats dominated by plants that 

grow principally on or below the surface of the water for most of the growing season in 

most years. Aquatic beds generally occur in water less than 2 meters (6.6 feet) deep and 

are placed in the Littoral Subsystem (if in a Lacustrine System). 

2.	 [EM] Emergent - Characterized by erect, rooted, herbaceous hydrophytes, excluding 

mosses and lichens. This vegetation is present for most of the growing season in most 

years. These wetlands are usually dominated by perennial plants. 

Impounded areas of the Lacustrine Littoral system and the Palustrine system can be identified 

with the [h] modifier and are referred to as “Diked or Impounded”. These wetlands are created 

or modified by a man-made barrier or dam, which obstructs the inflow or outflow of water. 

Originally, “Diked” and “Impounded” were described as separate modifiers (Cowardin et al. 

1979). They have been combined in the NWI classification due to photo-interpretation 

limitations. 

According to USFWS NWI Staff, when the NWI was ground-truthed, the new photography was 

compared to the old project data. In most cases, it appeared that conditions were very similar in 

relation to water levels and hydrology. The old photography was color infrared and the new 

photography was black and white, but for the most part, they correlated fairly well. The old 

photography was taken in 1981, which was prior to the flooding events that occurred during the 

period of 1983-1986. The new photography was taken during 1997-1998. Actual months were 

not available at the time of this analysis. The contour scheme used on the lake for both mapping 

efforts is shown below. Since the lake was originally contoured manually and subsequently 

digitized using topographic maps, changes were not made to this portion of the data except 

where obvious changes occurred (vegetation, fill, road construction, etc.). Most of these changes 

occurred within the L2USC area (Kevin Bon, USFWS, personal communication). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 67 
8.3 APPENDIX C. RESTORATIONS OPPORTUNITY ASSESSMENT 

Parameters for locating restoration opportunities on the Farmington Bay landscape were 

established prior to development of the actual GIS methodology. The rules were purposefully 

kept separate from the analyses of valuable avian habitat and nutrient loading so as not to 

introduce bias into the assessment. Furthermore, the rules are designed to be simple. They are 

based on data that are easily obtainable and a GIS that is easily replicable. Rules governing the 

designation of areas as a “high potential” or “potential” restoration opportunity were developed. 

The rules defining each category of restoration potential are described below. 

Public or Private High Potential Restoration Opportunity 

A wetland must meet the following spatial criteria to be identified as presenting a “high potential 

restoration opportunity”: 

1.	 Must intersect a “30 meter buffer” around conveyances. Intersection of 30 Meter 
 

Conveyance Buffer is an indicator of high restoration potential because of the 
 

conveyance’s ability to deliver managed flows to the wetland. 
 

2.	 Must exhibit “All-hydric” soils. All-hydric soils are an indicator of areas that may 

contain existing wetlands or suitable for wetland restoration. 

3.	 Must possess “Interior Habitat” of at least 30 meters from wetland edge. Interior Habitat 

is defined as areas with no major roads, train tracks, power lines, or developed structures. 

4.	 Must not be categorized in NWI as L2USC. These are seasonally flooded lacustrine, non 

vegetated wetlands that are typically found below 4,200 feet. 

Public or Private Potential Restoration Opportunity 

A wetland must meet two or more of the following spatial criteria to be identified as presenting a 

“potential restoration opportunity”: 

1.	 Must exhibit “All-hydric” or “Potentially-hydric” soils. All-hydric soils are an indicator 

of areas that may contain existing wetlands or suitable conditions for wetland restoration. 

Potentially hydric soils are an indicator of areas with less certainty of wetland occurrence 

and restoration potential. 

2.	 Must not be categorized as L2USC. These are seasonally flooded lacustrine, non 
 

vegetated wetlands that typically are found below 4,200 feet and cannot be easily 
 

managed. 
 

Phragmites Removal Potential 

Any wetlands or areas immediately adjacent to wetlands that have Phragmites are considered 

potentially restorable. Wetlands with Phragmites can include upland areas or seasonally flooded 

areas. The removal of Phragmites will increase the habitat value of wetlands and adjacent areas. 

Statistics about Phragmites and restoration opportunity are reported separately from the other 

potential restoration categories. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 68 
 

Restorations Opportunity GIS Methodology 

The Restorations Opportunity assessment map is derived from a standard overlay analysis using 

the following GIS data sets: Salt Lake and Davis County Parcel Data; Interior Habitat; 

SSURGO soils data; phragmites; conveyance and water rights data; 2008 USFWS National 

Wetlands Inventory (NWI); and Elevation Zone Assessment. The remainder of this appendix 

summarizes how these data sets were incorporated into the restoration opportunity assessment. 

Parcel Evaluation 

The presence of public or private lands is an important indicator of areas most viable for 

conservation or restoration activities. Public lands include those that are owned by the county, 

state, or federal government. Wetlands in these areas would provide the most immediate 

opportunity for restoration and conservation, as there would likely be fewer barriers for obtaining 

these wetlands. For this study, public lands also included areas currently protected and managed 

by organizations such as the Audubon Society and the Kennecott Copper Corporation Mitigation 

Wetlands. Private lands include all other categories of private ownership and acreage in the 

shorelands and are mainly comprised of the several duck clubs within the project area. For both 

private and public lands, individual tax parcel polygons were merged in the GIS into the 

appropriate public or private category based on the “ownership” attribute. Figure C1 presents 

the parcel evaluation completed for the restorations opportunities assessment. 

Figure C1. Parcel Evaluation. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 69 
Interior Habitat 

Interior Habitat is described as non-fragmented areas with no major roads, train tracks, or 

developed structures that can interfere with the movements and activities of avian species. The 

framework for this methodology was developed by Frontier Corporation (Providence, Utah) for 

the Brigham City and Perry City Special Area Management Plan Project (BCSAMP, 2006). An 

initial 15 meter buffer was applied to the NWI wetlands layer to identify adjacent roads or 

railroad tracks. Then, gaps between wetland polygons of less than 60 meters were filled creating 

larger wetland complexes. The 60-meter buffer value was chosen based on the existence of 100 

foot (30 meters) right-of-way widths for arterial roads and railroad tracks in this area. By filling 

the gaps created by these right-of-ways, the artificial separation of the wetland complexes by 

roads and railroads is eliminated. Once this initial step of identifying areas of un-fragmented 

wetland complexes was complete, interior buffers of 0 meters, 30 meters, 60 meters, and greater 

than 60 meters were applied to the resulting wetland complex polygons to “trim” back the 

interior habitat at 30 meter intervals. Areas of less than 0.05 acres were not assessed for this 

analysis. Figure C2 displays an example of creating and applying interior buffers to wetland 

complexes. 

Figure C2. Interior Habitat with Interior Buffers. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 70 
Hydric Soils Classification 

The SSURGO datasets for Davis County and Salt Lake County were obtained and reformatted to 

identify all hydric and partially hydric soils for the restorations opportunity assessment. 

SSURGO soil data were downloaded in a Microsoft Access database. The following steps were 

undertaken in Microsoft Access to adequately format and organize the SSURGO soils data for 

the various aspects of this project: 

1. Create a new table parameter denoted by a unique Component Key 

2. Group the required soil parameters 

3. Create a new table with data for the first and second highest soil layer 

4. Join data from highest soil layer table to the data from the second highest soil layer 

5. Compute the K effective factor analogously 

The resulting horizon table has a total number of records equal to the total number of unique 

Component Keys from the original C horizon table. The newly created table was then connected 

to soil survey boundaries. For the restorations opportunity map, the “Hydric Classification” field 

was used to reclassify the soil survey polygons and to identify All-Hydric and Partially Hydric 

soils. The resulting map is presented in Figure C3. 

Figure C3. Hydric Soils Classification. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 71 
Conveyance and Water Rights Data 

Although the 1:24,000 NHD stream data is sufficient for evaluating the streams and conveyances 

of the Jordan River watershed and in Davis County, these coarse spatial data are inadequate for 

an accurate assessment of the complex conveyance system at work in the shoreland wetlands. 

For an evaluation of how water and nutrient delivery may be altered in the future, it was first 

necessary to digitize the conveyances in the shorelands in greater detail than was offered by the 

NHD. Using 2006 aerial imagery, a refined shorelands conveyance layer was created for this 

project. The updated conveyance layer also incorporated water-rights information where 

available. These data were obtained from Dick Gilbert, Ambassador Duck Club, and Anne 

Neville, Kennecott Copper Corporation and documented in a GIS. Water rights information is 

important for understanding the monthly and seasonal patterns of flow being delivered to the 

shoreland wetlands. The data compiled for this analysis are incomplete and were not used to 

assess restoration opportunity. However, a future documentation of shoreland water rights in a 

GIS would be valuable for such an assessment. An example of these data is presented in Figure 

C4 below. 

Figure C4. Example of Shoreland Conveyances and Water Rights. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 72 
Presence of Phragmites 

The 2008 Ducks Unlimited Vegetative Cover (DU, 2008) and the 2006 Salt Lake County Special 

Area Management Plan Functional Assessment (Hoven et al, 2006) vegetative cover provided 

Phragmites distribution data. The difference in time periods for these data sets introduces error 

into the size estimates of independent Phragmites colonies; however, these were the best data 

available for the Farmington Bay area. Figure C5 displays the merged Phragmites polygon data. 

For the future scenarios, a growth Perimeter Expansion Rate (PER) of 5 meters per year was 

applied based on an average of the standard Phragmates PER range (.2 m – 10 m per year) 

presented in Phelps (2006). 

Figure C5. Phragmites Presence. 

NWI Wetlands 

The 2008 NWI wetlands layer was used as a base map to join the other variable data for the 

restorations opportunity assessment. For more information on the NWI classification employed 

for this study, see Appendix B. 

Elevation Zone Assessment 

Elevations zones identified as having significant management potential were identified using a 

3D simulation of lake-level-rise. For more information on significant elevation zones, see 

Appendix A. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 73 
8.4 APPENDIX D. METHODOLOGY FOR THE AVIAN WETLAND HABITAT ASSESSMENT (AWHA) 

Avian Wetland Habitat Assessment (AWHA) is a predictive tool developed to assess the 

capabilities of various wetland types around Farmington Bay to provide suitable habitat for 

migratory shorebirds, migratory waterfowl, and migratory water birds. The foundation of this 

approach is a decision support system. It includes “rules” for assessing viable wetland habitat. 

The rules were developed for noteworthy avian species or groups of species located on the 

landscape. Rules are based on the influence of significant environmental and anthropogenic 

variables, as identified by local wetland and ornithological experts using a priori knowledge. 

That knowledge was used to determine species distribution within a landscape. The expert panel 

consisted of Don Paul (Avian West), Dr. John Cavitt (Weber state University), and Dr. Heidi 

Hoven (Institute of Watershed Sciences). 

The methodology involves the following steps: 1) selecting appropriate variables that determine 

the presence of a species on the Farmington Bay landscape; 2) assigning a numerical strength to 

each variable with respect to other variables for each species; 3) assigning weights for describing 

the spatial effect of a particular controlling variable; 4) applying the weighted variables to GIS 

raster data independently for each species; and 5) performing raster calculations to create maps 

denoting habitat value based on five natural breaks of classification. Natural break classification 

indicates the relative quality of a habitat’s value compared to the values of the entire dataset. 

Selecting Variables 

The first step of this analysis involves establishing the dependent and independent variables. 

The dependent variable is the presence or absence of a species. The independent variables are 

the anthropogenic and environmental variables that most strongly determine where a particular 

species will be located. For this study, the main independent variables are: proximity to 

Phragmites colonies, wetland habitat as denoted by National Wetland Inventory (NWI) types, , 

and depth of interior habitat, proximity to roads and highways, proximity to developed land use 

types, and the presence of key vegetative cover. Furthermore, for the template scale future 

scenarios analysis, nutrient loading and conveyance flow delivery as predicted from AVGWLF 

were added to the spatial assessment. 

Assigning a Variable Strength and Weight to Each Variable 

A preliminary assignment of variable strength was undertaken to establish an autonomous 

influence of each independent variable for each species. The variables are assigned different 

strengths that reflect their relative importance when compared to one another as determined by 

the experts. In order to estimate the importance of each independent variable to the distribution 

of a species, spatial weights were established for the raster cells. A common method of 

assigning raster values is Boolean Classification. In Boolean Classification, a pixel is assigned a 

value of either “true” (1) or “false” (0), based on whether or not the value of a variable at that 

location exceeds a specified threshold. In situations where uncertainty in the precise delineation 

of a threshold value exists, applying Boolean Classification may unnecessarily discard 

intermediate values of a variable that are still relevant to the analysis. This analysis relies on 

datasets, such as avian occurrence data, with imprecise boundaries. Zadeh’s fuzzy set theory 

(Zadeh, 1965, 1990a, and 1990b) offers an alternative approach that accommodates situations 

where the inclusion or exclusion of an element within a set or class is subject to imprecision. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 74 
Fuzzy set theory yields values that range from 0 to 1 based on derived relative weights for 

suitable variables (Banai, 1993). 

Table D1 below displays an example of the workbook used to weigh the variables. Table D2 

displays the final weighted variable matrix for all bird groupings completed for this analysis. 

This matrix was completed for eight avian groupings several times during the summer of 2008 

by a panel of local avian and wetland experts. 

Migratory Waterfowl (MGWF) and Migratory Waterbirds (MGWB) were analyzed for this AFA 

analysis. The other groupings that were weighted, but not analyzed for the AFA are as follows: 

Nesting Colonial Shorebirds (NCSH), Nesting Colonial Waterbirds (NCWB), Long Billed 

Curlew (LBCR), American Pelican (APEL), and Snowy Plover (SNPL). The initial variable 

strengths and weights changed depending on the feasibility of producing desired data in 

ArcView in an efficient manner. Variable strengths and weights also changed as the experts 

become more familiar with the process and sought to represent more adequately these indicators. 

Caveats associated with the suitability of a variable to represent (or not represent) a particular 

species were documented in the matrix. The weighting system is designed on a scale from 0-1, 

with 1 denoting the most positive indication of suitable habitat for a bird grouping. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 75 
 

 

 

 

 

 

 

 

 

Table D1. Variable Strength and Weights Worksheet for One Bird Grouping. 

Base Variable for Habitat Suitability Index 

Variable- Variable Strength GIS Fuzzy Operator Weight (0-1) Final GIS 

Description (Vs) Value GIS Descriptor (Wt) G values 

Wetland Type 0.50 

0.00 Non-wetland 0.00 0.00 

1.00 Open Water 1.00 0.50 

2.00 Impounded 1.00 0.50 

3.00 Playa 0.50 0.25 

4.00 Fringe 0.50 0.25 

8.00 Emergent 1.00 0.50 

Vegetation 1.00 

1.00 Open Water 1.00 1.00 

3.00 75 Akali Bulrush 0.20 0.20 

4.00 75 Cattail/Bulrush 0.00 0.00 

6.00 50-75 Alkali Bulrush 0.20 0.20 

7.00 Playa Mudflat Unvegetated 1.00 1.00 

8.00 Playa Mudflat Vegetated 0.40 0.40 

9.00 Mixed Emergent 1.00 1.00 

10.00 Upland 1.00 1.00 

11.00 Tamarisk 0.00 0.00 

13.00 River/Channel 0.30 0.30 

0.00 Other 0.00 0.00 

Phragmites 0.10 

2.00 Greater than 75% Phragmites 1.00 0.10 

1.00 Between 51-75% Phragmites 0.00 0.00 

0.00 No Phragmites 0.00 0.00 

Interior Habitat 0.60 

0.00 Zero Interior Habitat 0.00 0.00 

1.00 Interior habitat 0- 100 from edge 1.00 0.60 

2.00 Interior habitat 100 from edge 0.50 0.30 

3.00 Interior habitat 200 from edge 0.50 0.30 

4.00 Interior habitat 300 + from edge 1.00 0.60 

Roads 0.10 

1.00 Four-Lane Highway 1.00 0.10 

2.00 Two-lane Paved Road 0.00 0.00 

3.00 Near Grade; Dirt Roads; Trails 0.30 0.03 

0.00 No roads 0.50 0.05 

Land Use 0.60 

1.00 High Development Areas 0.00 0.00 

2.00 Low Development Areas 0.00 0.00 

3.00 Golf Courses/Turf Areas 0.00 0.00 

4.00 Row Crops 0.00 0.00 

5.00 Forested Areas 1.00 0.60 

7.00 Hay/Pasture or Scrub Shrub 0.00 0.00 

8.00 Open Space/Barren Land 0.00 0.00 

12.00 Barren Land 0.30 0.18 

13.00 Turf Grass/Golf 0.00 0.00 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 76 
 

Table D2. Final matrix of weights for all bird groupings. 

Base Variable for Habitat Suitability Index 

Value Variable Descriptor Mgsh Ncsh Mgwf Mgwb Ncwb Lbcr Apel Snpl 

0.00 Wetland Non-Wetland 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

1.00 Wetland Lacustrine Types 0.50 0.50 0.50 0.50 0.50 0.00 0.50 0.00 

2.00 Wetland Impounded 0.50 0.50 0.50 0.50 0.50 0.50 0.00 0.50 

3.00 Wetland Fringe 0.25 0.25 0.50 0.25 0.50 0.00 0.50 0.00 

4.00 Wetland Playa 0.25 0.25 0.25 0.00 0.50 0.00 0.00 0.00 

8.00 Wetland Emergent 0.50 0.50 0.50 0.25 0.50 0.00 0.00 0.00 

1.00 Vegetation Open Water 1.00 1.00 1.00 0.90 0.90 0.00 0.70 0.00 

3.00 Vegetation 75 Alkali Bulrush 0.20 0.00 0.80 0.00 0.72 0.00 0.00 0.00 

4.00 Vegetation 75 Cattail/Bulrush 0.00 0.00 0.60 0.00 0.72 0.00 0.00 0.00 

6.00 Vegetation 50-75 Alkali Bulrush 0.20 0.00 0.80 0.00 0.72 0.00 0.00 0.00 

7.00 Vegetation Playa Mudflat Unveg 1.00 0.60 0.80 0.90 0.63 0.80 0.00 1.00 

8.00 Vegetation Playa Mudflat Veg 0.40 0.40 0.80 0.00 0.36 0.80 0.00 0.00 

9.00 Vegetation Mixed Emergent 1.00 0.00 1.00 0.36 0.90 0.00 0.00 0.00 

10.00 Vegetation Upland 1.00 0.00 0.70 0.90 0.27 1.00 0.00 0.00 

11.00 Vegetation Tamarisk 0.00 0.00 0.20 0.00 0.27 0.00 0.00 0.00 

12.00 Vegetation River Channel 0.30 0.00 0.30 0.00 0.45 0.00 0.35 0.00 

0.00 Vegetation Other 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

0.00 Phragmites na 0.10 0.10 0.30 0.30 0.60 0.00 0.00 0.30 

1.00 Phragmites 50-75 0.00 0.00 0.09 0.00 0.42 0.00 0.00 0.00 

2.00 Phragmites 75-100 0.00 0.03 0.15 0.00 0.60 0.00 0.00 0.00 

0.00 I. Habitat 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

1.00 I. Habitat 1-100 0.60 0.06 0.80 0.18 0.14 0.04 1.00 0.21 

2.00 I. Habitat 100-200 0.30 0.06 0.40 0.24 0.21 0.12 1.00 0.21 

3.00 I. Habitat 200-300 0.30 0.06 0.40 0.30 0.49 0.20 1.00 0.28 

4.00 I. Habitat 300+ 0.60 0.06 0.80 0.42 0.70 0.32 0.10 0.56 

0.00 Roads none 0.10 0.50 0.40 0.30 0.20 0.20 0.00 0.40 

1.00 Roads 4 lane 0.00 0.10 0.08 0.06 0.04 0.00 0.00 0.12 

2.00 Roads 2 lane 0.03 0.05 0.08 0.06 0.04 0.00 0.00 0.12 

3.00 Roads dirt/path 0.05 0.25 0.16 0.15 0.08 0.16 0.00 0.32 

1.00 Land Use Open Water 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

2.00 Land Use Low Dev 0.00 0.00 0.21 0.48 0.00 0.00 0.00 0.00 

3.00 Land Use High Dev 0.00 0.00 0.14 0.80 0.03 0.00 0.00 0.00 

4.00 Land Use Row Crop 0.00 0.00 0.56 0.48 0.00 0.00 0.00 0.00 

5.00 Land Use Hay/Past 0.60 0.10 0.49 0.80 0.00 0.64 0.00 0.00 

7.00 Land Use Coniferous 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

8.00 Land Use Mixed Forest 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

9.00 Land Use Deciduous 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

10.00 Land Use Wood Wetland 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

11.00 Land Use Emer Wetland 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

12.00 Land Use Barren Land 0.18 0.02 0.00 0.00 0.06 0.48 0.00 0.18 

13.00 Land Use Turf Grass/Golf 0.00 0.00 0.49 0.16 0.00 0.00 0.00 0.00 

Raster Calculation 

In map algebra, operators and functions evaluate expressions only for input cells that are 

spatially coincident with the output cell. Therefore, rasters of an equal scale and pixel dimension 

must be created to hold the weighted variables. For each of the independent variables, a 30 

meter by 30 meter raster was produced from raw vector and raster data to support the raster 

calculations. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 77 
Once weighted avian occurrence values for the presence of a bird grouping were established, 

these data were spatially joined to the independent variable raster datasets, resulting in weighted 

rasters for each species. Raster calculation in map algebra was used to apply the calculation in 

Figure B.1 for the all scenarios. 

Habitat Value Maps 

The results are maps for each species grouping denoting areas of high and low habitat value on 

the Farmington Bay landscape. The highest index value (5) represents the “most suitable” 

habitat available in the template and, in effect, displays the maximum combination of weights for 

all variables indicating suitable habitat. As the index trends towards lower values (1), the 

combinations of weights are decreasing and the habitat is viewed progressively as “less suitable”. 

It must be emphasized that the habitat index produced by this model does not implicate “poorquality” or “low value” habitat and therefore absence of a species. Rather, the model seeks to 

assess changes in the availability of the most suitable habitat based on the weighted variables. 

The AWHA analysis was undertaken only for Migratory Shorebirds, Migratory Waterbirds, and 

Migratory Shorebirds due to limited resources and time availability. Landscape predications 

were preformed for these three bird groupings. The below list displays the general steps for 

connecting variable weights to the raster datasets and to produce maps and proportional results: 

1. Join weighted variable data to the appropriate GIS raster coverage 

2. Export as a new raster (preserving the weights) 

3. For each variable, create a bird grouping raster 

4. Sum the variable weights for each group using Map Algebra 

5. Reclassify the resulting raster calculation into 5 Natural Break (Jenks) classes 

6. If the model run is for a Future scenario, import Current scenario classification 

7. Save reclassified raster to create a final reporting file 

8. Load template boundary 

9. Convert template boundary to raster 

10. Extract by mask using the template boundary raster 

11. Calculate acres 

12. Create graphs 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 78 
8.5 APPENDIX E. CALIBRATION OF THE AVGWLF MODEL IN THE JORDAN RIVER BASIN 

The AVGWLF model was calibrated for the Jordan River watershed in Salt Lake County, Utah 

for the purpose of quantifying the flow, sediment, and nutrients currently being delivered to the 

Farmington Bay wetlands from the various sources throughout the watershed. Multiple future 

scenarios were also modeled in AVGWLF to determine the resultant loads expected in the 

Farmington Bay wetlands as a result of land use and water use changes in the watershed. 

Model calibration was performed for the period 1995-2005 at the Surplus Canal diversion. Stream 

flow was calibrated to the combined Jordan River and Surplus Canal flows at USGS gage 

10170490. Total Phosphorus and Suspended Sediment concentrations were obtained from 

STORET station 4992320 in the Surplus Canal, while Total Nitrogen concentrations were obtained 

from USGS gage 10171000 in the Jordan River immediately below the Surplus Canal diversion. To 

derive historical nutrient loads, standard mass balance techniques were employed. First, the instream nutrient concentration data and corresponding flow rate data were utilized to develop load 

(mass) versus flow relationships for each watershed for the period in which historical water quality 

data were obtained. Using the daily stream flow data obtained from USGS, daily nutrient loads for 

the 1995-2005 period were subsequently computed for the watershed using the appropriate load 

versus flow relationship (i.e., “rating curves”). Loads computed in this fashion were used as the 

“observed” loads against which model-simulated loads were compared. 

During this process, adjustments were made to various model input parameters for the purpose of 

obtaining a “best fit” between the observed and simulated data. As the AVGWLF model uses 

empirically derived relationships to simulate watershed processes, adjustments were necessary to 

better reflect conditions specific to the Jordan River basin. With respect to stream flow, adjustments 

were made that decreased the amount of the calculated evapotranspiration. Based on watershedspecific conditions and the modelers’ previous experience, these values were deemed too high. 

With respect to nutrient loads, changes were made to the estimates for sub-surface nitrogen and 

phosphorus concentrations. The empirically derived estimates were not correctly representing these 

parameters in the Jordan River basin. With regard to sediment, revisions were made to the sediment 

“a” factor, which reflects the erodibility of stream banks. This value was decreased due to the large 

number of hardened canals in the basin. The erosivity coefficients were decreased based on the 

differences exhibited between these values in western versus eastern regions of the U.S. 

As a result of the relatively large amount of anthropogenic influence in the Jordan River 

watershed, it was necessary to “externalize” a number of the model components in order to more 

accurately simulate yearly variations in monthly loading and flow. AVGWLF uses monthly 

averages for the entire period of simulation to estimate the effects of point source loadings and 

withdrawals. However, in the Jordan River basin, point source loadings and withdrawals are 

highly variable from year to year. Thus, flows and loads from these two components were 

calculated in a spreadsheet and added to (point sources) or subtracted from (withdrawals) the 

AVGWLF output for each month during the entire period 1995-2005. This method proved 

invaluable to the calibration procedure, as the largest contributors of flow, sediment, and nutrient 

loading in the Jordan River basin are entirely under human control. 

To assess the correlation between observed and predicted values, two different statistical 

measures were utilized: 1) the Pearson product-moment correlation (r

2

) coefficient and 2) the 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 79 
Nash-Sutcliffe coefficient. The r

2

 value is a measure of the degree of linear association between 

two variables, and represents the amount of variability that is explained by another variable (in this 

case, the model-simulated values). Depending on the strength of the linear relationship, the r

2

 can 

vary from 0 to 1, with 1 indicating a perfect fit between observed and predicted values. Like the r

2 

measure, the Nash-Sutcliffe coefficient is an indicator of “goodness of fit,” and has been 

recommended by the American Society of Civil Engineers for use in hydrological studies (ASCE, 

1993). With this coefficient, values equal to 1 indicate a perfect fit between observed and predicted 

data, and values equal to 0 indicate that the model is predicting no better than using the average of 

the observed data. Therefore, any positive value above 0 suggests that the model has some utility, 

with higher values indicating better model performance. In practice, this coefficient tends to be 

lower than r

2

 for the same data being evaluated. 

Adjustments were made to the various input parameters for the purpose of obtaining a “best fit” 

between the observed and simulated data. One of the challenges in calibrating a model is to 

optimize the results across all model outputs (in the case of AVGWLF, stream flows, as well as 

sediment, nitrogen, and phosphorus loads). As with any watershed model like GWLF, it is possible 

to focus on a single output measure (e.g., sediment or nitrogen) in order to improve the fit between 

observed and simulated loads. Isolating on one model output, however, can sometimes lead to less 

acceptable results for other measures. Consequently, it is sometimes difficult to achieve very high 

correlations (e.g., r

2

 above 0.90) across all model outputs. Given this limitation, it was felt that very 

good results were obtained for the calibration site. 

For the monthly comparisons, mean r

2

 values of 0.86, 0.80, 0.94, and 0.90 were obtained for flow, 

sediment, phosphorus, and nitrogen, respectively. When considering the inherent difficulty in 

achieving optimal results across all measures as discussed above (along with the potential sources of 

error), these results are quite good. The sediment load predictions were less satisfactory than those 

for the other outputs, and this is not entirely unexpected given that this constituent is usually more 

difficult to simulate than nitrogen or phosphorus. Nitrogen and phosphorus predictions were very 

accurate due to the availability of data for the two large WWTPs in the basin, which are the largest 

contributors of nutrients to the river. 

The monthly Nash-Sutcliffe coefficients of 0.86, 0.80, 0.92, and 0.74 were very high considering 

that they approach their respective r

2

 values, which is often difficult in studies of this kind. As 

described earlier, this statistic is used to iteratively compare simulated values against the mean of 

the observed values, and values above zero indicate that the model predictions are better than just 

using the mean of the observed data. In other words, any value above zero would indicate that the 

model has some utility beyond using the mean of historical data in estimating the flows or loads for 

any particular time. As with r

2

 values, higher Nash-Sutcliffe values reflect higher degrees of 

correlation than lower ones. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 80 
Figures E1, E2 and E3 below present a representation of the calibration results for a ten year time 

period, 1995- 2005. 

20000 

22000 

24000 

26000 

28000 

30000 

32000 

34000 

36000 

38000 

40000 

Jan-95Jan-96Jan-97Jan-98Jan-99Jan-00Jan-01Jan-02Jan-03Jan-04Jan-05 

Year 

Grams 

Observed Simulated 

Figure E1. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Phosphorous. 

50000 

75000 

100000 

125000 

150000 

175000 

200000 

225000 

250000 

275000 

300000 

325000 

350000 

Jan-95Jan-96Jan-97Jan-98Jan-99Jan-00Jan-01Jan-02Jan-03Jan-04Jan-05 

Year 

Grams 

Observed Total Simulated 

Figure E2. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Nitrogen. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 81 
Figure E3. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Suspended 

Solids. 

AVGWLF Model: Jordan River Basin 

Using data for the time period 1995-2005, the calibrated AVGWLF model was used to estimate 

flow, sediment, nitrogen, and phosphorus loading to the Surplus Canal. Table E1 provides the 

sources of data used for the AVGWLF modeling analysis. Adjustments made to these data 

sources were discussed above. Screenshots of the AVGWLF model with input values are shown 

in Figures E4 and E5. Screenshots of model output are shown in Figures E6 through E8. These 

figures do not include point source data, as this was simulated outside of the AVGWLF 

watershed model. Additional explanation of model parameters and processes is available in the 

AVGWLF Users Guide (Evans, 2008). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 82 
Table E1. Information Sources for AVGWLF Model Parameterization. 

WEATHER.DAT file 

Data Source or Value 

Precipitation and Temperature 

Historical weather data from Salt Lake City, UT and 

Provo, UT National Weather Service Stations 

TRANSPORT.DAT file (See Figure 13.1.2) 

Data Source or Value 

Basin size GIS/derived from basin boundaries 

Land use/cover distribution GIS/derived from land use/cover map 

Curve numbers by source area GIS/derived from land cover and soil maps 

USLE (KLSCP) factors by source area GIS/derived from soil, DEM, & land cover 

ET cover coefficients GIS/derived from land cover (adjusted) 

Erosivity coefficients GIS/derived from physiography map (adjusted) 

Daylight hrs. by month Computed automatically for state 

Growing season months Input by user 

Initial saturated storage Default value of 0 cm 

Initial unsaturated storage Default value of 10 cm 

Recession coefficient 

Calculated using standard hydrograph separation 

techniques 

Seepage coefficient Default value of 0 

Initial snow amount (cm water) Default value of 0 

Sediment delivery ratio GIS/based on basin size 

Sediment “a” factor GIS/empirically derived (adjusted) 

Soil water (available water capacity) GIS/derived from soil map 

NUTRIENT.DAT file (See Figure 13.1.3) 

Data Source or Value 

Dissolved N in runoff by land cover type Default values by land cover type 

Dissolved P in runoff by land cover type Default values by land cover type 

N/P concentrations in manure runoff Default values (from GWLF Manual) 

N/P buildup in urban areas Default values (from GWLF Manual) 

N and P point source loads Derived from EPA STORET database 

Background N/P concentrations in GW Derived from background N map (adjusted) 

Background P concentrations in soil Derived from soil P loading map 

Background N concentrations in soil Based on map in GWLF Manual 

Months of manure spreading Input by user 

Population on septic systems Derived from census tract maps for 2000 

Per capita septic system loads (N/P) Default values (from GWLF Manual) 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 83 
 

Data that were critical to the model calibration, but simulated outside of AVGWLF, include 

Turner Dam and canal flows and concentrations, point source flows and concentrations, and 

withdrawal amounts. Turner Dam and canal data were obtained from the Utah Division of Water 

Rights, (UTDWRi, 2008). Point source data were obtained from the US EPA STORET database 

(USEPA, 2006a). Yearly estimates of ground and surface water withdrawals for different uses 

(e.g., municipal, agricultural) were obtained from publically-available state and county reports 

(UTDWRe, 1997; SLC, 2009). These yearly estimates were then split among the 12 months of 

the year for the 11 years of simulation (1995-2005) based on best professional judgment and 

taking into consideration observed weather patterns, stream flows, and seasonality of water 

usage. Figures E4 though E8 and Tables E2 though E6 present the results of the AVGWLF 

modeling. 

AVGWLF Model Simulation Results 

Figure E4. AVGWLF Input Transport File. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 84 
Figure E5. AVGWLF Input Nutrient File. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 85 
 
Figure E6. Simulated Hydrology Transport Summary. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 86 
 
Figure E7. Simulated Nutrient Transport Summary. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 87 
 
Figure E8. Simulated Total Loads by Source. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 88 
 
Table E2: Jordan River Land Use Acreage Distribution. 

Land Use Category Acres % of Drainage Basin 

Open Water 613 0.20% 

Agriculture 30,475 8.40% 

Hay & Pasture 22,667 6.20% 

Cropland 7,808 2.20% 

Developed Land 97,594 26.80% 

Low Intensity 84,819 23.30% 

High Intensity 12,775 3.50% 

Forest 202,542 55.60% 

Wetlands 3,283 0.90% 

Quarry/Barren Land 12,191 3.30% 

Developed Open Space 17,473 4.80% 

TOTAL 364,171 100% 

Table E3. Simulated Phosphorus Loading Allocations; pounds per year. 

Source 

Total Phosphorus 

(lbs/yr) 

Point Sources 804,230 

Turner Dam & Canals 64,132 

Hay/Pasture 328 

Cropland 359 

Forest 272 

Developed Open Space 561 

Quarry/Barren Land 1,287 

Low Intensity Development 1,682 

High Intensity Development 3,890 

Stream Bank 450 

Septic Systems 190 

Groundwater 4,690 

Wetlands 4 

Unpaved Roads 2 

TOTAL 882,077 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 89 
Table E4. Simulated Sediment Loading Allocations; Pounds per year. 

Source (lbs/yr) 

Turner Dam & Canals 61,202,881 

Hay/Pasture 27,976.70 

Cropland 123,789.60 

Forest 363,255.70 

Developed Open Space 32,231.60 

Quarry/Barren Land 1,976,841 

Low Intensity Development 93,344 

High Intensity Development 12,941 

Stream Bank 20,438,355 

Wetlands 331 

Unpaved Roads 2,755.80 

TOTAL 84,274,702 

Table E5. Simulated Total Nitrogen Loading Allocations; Pounds per year. 

Source Total Nitrogen (lbs/yr) 

Point Sources 2,436,212 

Turner Dam & Canals 1,355,373 

Hay/Pasture 2,456 

Cropland 2,457.70 

Forest 2,246 

Developed Open Space 1,057 

Quarry/Barren Land 5,953 

Low Intensity Development 10,093 

High Intensity Development 35,716 

Stream Bank 1,022 

Septic Systems 2,216 

Groundwater 853,644 

Wetlands 128 

Unpaved Roads 15.5 

TOTAL 4,708,589 

Table E6. Mean Annual Loadings to the Surplus Canal. 

Parameter Total Inputs 

Total 

Extractions 

Net Totals 

Flow (acre-feet) 574,416 119,187 455,229 

Sediment (lbs) 84,274,702 21,109,250 63,165,452 

Total Phosphorus (lbs) 882,077 22,354 859,723* 

Total Nitrogen (lbs) 4,708,589 495,436 4,213,153 

* Accounts for 6% stream attenuation 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 90 
8.6 Appendix F. Wetland Water Quality Model 

Wetland ecosystems provide numerous environmental services in the greater landscape of which 

they are a part. In addition to providing valuable wildlife habitat, water quality improvement is 

considered one of their more important functions. In recognition of this important function, 

many studies have been conducted to examine the nutrient retention efficiencies of constructed 

wetlands created to treat wastewater effluent from treatment plants (Kadlec and Knight, 1996; 

Carleton et al., 2001; Kivaisi, 2001; Tanner, 2001; Vymazal, 2005, Jordon, 2007). Fewer studies, 

however, have examined nutrient retention efficiencies in natural wetlands (Fisher & Acreman, 

2004), and fewer still have examined sediment retention in natural wetland systems. Nutrient 

and sediment retention in natural wetlands are much more difficult to quantify than in 

constructed wetlands due to variability in flows, vegetation types, soils, and because they were 

not constructed with the goal of water quality improvement in mind (Newbold, 2002). 

The three primary controlling variables acting on nutrient and sediment retention in constructed 

wetlands are the area of the wetland, flow rate of water entering the wetland, and concentration 

of pollutant in the inflowing water (Newbold, 2002). While other biological, chemical, and 

physical variables influence retention rates, the three primary controlling variables can be used to 

predict removal efficiencies with a reasonable degree of accuracy in constructed wetlands using 

a first-order removal rate (Newbold, 2002). The following equation is an example of a firstorder removal rate calculation: 

(-k/HLR) Cout = Cin e 

Cout concentration of outflow pollutant, mg/l 

Cin concentration of inflow pollutant, mg/l 

k pollutant removal rate constant, m/yr 

HLR hydraulic loading rate (Q/A), m/yr 

Q annual runoff (i.e., surface water inflow rate), m3

/yr 

A wetland surface area, m2 

A calibrated wetland water quality model for a demonstration site in the impoundment template 

was produced based on a first-order removal rate. The impoundment wetland template is 

particularly well-suited to application of the first-order removal rate calculation described above 

because it contains a number of wetland “cells” that can be analyzed independently or in series. 

Each cell contains relatively defined boundaries, allowing for determination of an estimated 

acreage in which pollutant retention may be occurring. Flow estimates between the cells are also 

available and this, combined with inflow concentration data, allows for the development of a 

model based on the first-order removal rate calculation. The US EPA STORET database 

contains a limited amount of flow, total phosphorus, and total suspended solids data for the 

Ambassador Duck Club wetland impoundment. Estimates were obtained from local sources or 

were inferred from the data for flow rates in cells that were not represented in the STORET 

database. Table F1 display the STORET data used and the locations of the sampling stations. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 91 
Table F1. STORET data used in model development. 

Figures F1 and F2 display the configuration of the 10 cells identified within the impoundment 

template and their respective flow paths, phosphorus, and sediment concentrations. The Jordan 

watershed loading is the Jordan River water that is diverted to the Surplus Canal and routed to 

the Ambassador Duck Club. This loading has been simulated with the calibrated AVGWLF 

watershed model and can be adjusted for future conditions in the Jordan River watershed. For 

example, the AVGWLF model was used to simulate watershed loading under two different 

future conditions of land use described in other sections of this report. The outputs of these 

future scenario watershed modeling exercises can be used as the inputs to the wetland water 

quality model, allowing for a prediction of future nutrient retention. 

Figure F1. Impoundment Template Wetland Cells with Simulated (red) and Observed (black) TP Concentrations 

(mg/L). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 92 
Figure F2. Impoundment Template Wetland Cells with Simulated (red) and Observed (black) TSS Concentrations. 

Data limitations necessitated different data types be used in the calibration and prediction phases 

of sediment water quality modeling. As shown in Table F1, total suspended solids (TSS) data 

was used for calibration but during predictive modeling, AVGWLF simulated suspended 

sediment data. There is a qualitative difference in the two measures (see Gray et al. 2000), 

primarily that TSS is a component of the more inclusive suspended sediment measure. 

AVGWLF simulates "true" sediment, whereas most monitoring data is for total suspended solids 

(TSS). In reality, the total sediment load is usually by far the largest component of the TSS load 

in any given stream. An example of an exception to this general trend may be the case where 

many wastewater treatment plants are discharging organic loads to a slow-moving stream in a 

flat landscape where both upland erosion and stream channel erosion are minimal. Suspended 

sediment monitoring data is preferable for model calibration, but is not usually available (and 

was not available for the Jordan River). However, given the topography and the "flash flooding" 

nature of the watershed surrounding the Jordan River, it can be assumed that the TSS load was 

predominantly contributed by sediment (Barry Evans, Pennsylvania State University, personal 

communication). The model was calibrated to TSS monitoring data, which is what is typically 

done in watershed modeling projects, even though it is not always ideal. So, in this report when 

we are talking about model results we are referring to sediment, however, when the monitoring 

data we used to calibrate the model was TSS (by necessity). 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 93 
Calculated rate constants were averaged for each pollutant (phosphorus and sediment) so that 

they could be applied to each of the wetland cells in the first-order removal rate calculation. An 

average removal rate constant of 3.28 was calculated for total phosphorus (TP) and a rate 

constant of -0.3 was calculated for total suspended solids (TSS). The TP average rate constant 

does not include the calculated value for cell A, as it was grossly misrepresentative of the 

template as a whole. Outflow concentrations for each cell were simulated using the calibrated 

first-order equation. 

Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 94