EP A/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
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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
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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 Arc View 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
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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
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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
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Table of Contents
NOTICE II
EXECUTIVE SUMMARY Ill
INTRODUCTION Ill
PURPOSE, OBJECTIVES AND APPROACH Ill
MAJOR SIGNIFICANCE Ill
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 ThePlaya 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
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5.1.1.1 Recommendations for AWHA 52
5.1.2 AVGWLFPerformance 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
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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 Arc View Generalized Watershed Loading Function (A VGWLF) 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 forthe Playa template 32
Figure 27. Wetland landscape profile forthe 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 forthe 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 Al. Shoreland Elevation Zones 65
Figure Cl. 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
Figure El. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Phosphorous.
81
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
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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 Fl. 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 Dl. Variable Strength and Weights Worksheet for One Bird Grouping 76
Table D2. Final matrix of weights for all bird groupings 77
Table El. 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 Fl. STORET data used in model development 92
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
IX
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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. Schubauer-
Berigan, 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
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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 Arc View 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
FFIWA 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
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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
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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 fly ways 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)
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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)
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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.
0 4 8 16 24
Figure 1. Great Salt Lake Eco-region and Farmington Bay, NLCD 2001.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
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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)
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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.
4208
4204 —
5 < 4200 —
;41»4
M4192
4190'
DATA U.S.
LAKE
SEA
I
I
YEAR
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)
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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.
Legend
• Stream?
• Ionian Rivri
Great Salt Lake
Jordan River Watershed
•Miles
0 1.5 3
Figure 4. Jordan River basin and conveyances.
i:
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)
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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.
:/ramuuKtoa
3^ Girnt Salt Lifcr
' "- 1 3
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)
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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.
tn.i*rnm.' I biv. • : Bl ' ' •
| I-icvstrim
nvcjfcrtJ Impounded
lL'i.1 liii[Y:iiiiulLiL l*iii:>1n;K' In
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
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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)
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elates
Open Water
Impounded
Fringe
Playa
Emergent
Low Development
High Development
Hay/Pasture
Row Crops
Conifer Forest
Mixed Forest
Decidous Forest
Barren
Parks
"V ' 00.51 234
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).
2.5.2 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
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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
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Phragmites is an invasive species that has been monitored and actively managed in the
Farmington Bay wetlands. Appendix C presents additional information about Phragmites.
Touplataa
..'pen Wi
Impounded
layit
Emerutnl
Low Development
High Development H
I: iv I'.istUK ^B
Rr.v. i. Yops
"jiiter Forest H
Mixe J Forest
I>ecidou.«i Forest ^^
Bill tell ^0
' F-'nk:,
Miles
0061
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
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DOOR Forest
feed Forest
tviJiHJN purest
wren
"V" £X>51 '~ 4"
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
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TTigh Potentinl Potential
^| Public Hi Public
Private Private
| Hydric Soils
| Phragmite.s Removal
3Miles
N
4-
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)
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8 11.iv f'j
• Row V.|>
I '."otuicr Furesl
•
w KlixcJ I'
« DcciJ
; ' Barren
I l;lirb
00.51 2 3 4
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.
•Mil; :-
•9* 0451 2 3 4
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)
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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.
" H.5 M5 1
Figure 13. Impounded template, associated wetlands, basin boundary, and conveyances.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
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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.
Kays Creek
BllSM
] Ki- in boundary
Great Salt I.nke
Streams
Fnnge Template
i.i U5 1 2 3 I
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, 33 miles north of Saltair, and 7.2
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
17
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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.
C,-Mt Salt Ltikf
•I\o,fl> Pot/ife Consolidated Co/ml
Pl;iy:i Template
,Mllr*
H^K.
i.» 02 ij I 0.8 1.2
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
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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 avion 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 (Limosafedoa) 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
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2.4.1.1 Development of the Avian Wetland Habitat Assessment (A WHA) 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 SWC A
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
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Raster Calculation
1. Interior H abitat (.5)
2. Vegetation (.8)
3. Roads .(5)
4. WettandTjpe (.9)
5. Land Use (.5)
o". Fh-a^niiss (.6)
X <2QQfeet(p.3)
X < 50 % Alkali B rirush (0.3)
X >30m2-lane Paved (0.2)
X P alustrine Em er gent (.9)
X Low Development(0.1)
X < 25 % Pfoagnites (0.3)
Score = 1.53
Likelihoodof
Species Presence
in this Cell
S(
Variable Strength
(VS)
Weight Gradtents
\
Weighted
Raster
CeU
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
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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
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Hi - F 1 •* [ I 'IbnpUlc EkwnJari
Figure 18. Suitable Migratory Shorebird habitat available in total study area under current scenario conditions.
Red (#5) represents highest availability ranking.
I ] J | ] 4 |~~] Tcmptilc Uumulnn
Figure 19. Suitable Migratory Waterfowl habitat available in total study area under current scenario conditions.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
23
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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 Arc View-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 Arc View-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
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Figure 21. Screen-Capture of Jordan River Arc View 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
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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:
Cout = concentration of outflow pollutant, mg/1
Cin = concentration of inflow pollutant, mg/1
k = pollutant removal rate constant, m/yr
FILR = 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
-------
Ambassador Wetland Cells and STORET Stations
n
+
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
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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%.
21%
• 4200-4212
• 4212-4217
D 4217-4220
D 4220-4230
76%
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
-------
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.
70000
60000
50000
40000
30000
20000
10000
Current Conservation Plan Trend Conservation Plan Trend
4200 4200 4212 4212
Scenario
• Impounded D Fringe D Playa D 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
Impounded
Fringe
Playa
Emergent
Total Wetland
4,200
Current
27722
16893
5602
20532
70749
Conservation
22182
16530
5322
19320
63354
Plan Trend
19929
15709
3667
12916
52221
4,212
Conservation
6569
612
5169
10377
22727
Plan Trend
4609
99
3531
4191
12430
Percent change for each wetland class under different scenarios
Impounded
Fringe
Playa
Emergent
Total Wetland
-
-
-
-
-
-20%
-2%
-5%
-6%
-10%
-28%
-7%
-35%
-37%
-26%
-76%
-96%
-8%
-49%
-68%
-83%
-99%
-37%
-80%
-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
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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.
1 1 (1(1(1
1 (1(1(1(1
oUUU
7(1(1(1
^6000 -
o
A (1(1(1
ZUUU
1 (1(1(1
n
Current Conservation Plan Trend Conservation Plan Trend
4200 4200 4212 4212
Scenario
• Impounded D Fringe D Playa D 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
Impounded
Fringe
Playa
Emergent
Total Wetland
4,200
Current
1
5365
470
4706
10542
Conservation
0
5360
470
4687
10517
Plan Trend
0
5311
413
3717
9441
4,212
Conservation
0
2
460
2056
2518
Plan Trend
0
2
404
1081
1487
Percent change for each wetland class under different scenarios
Impounded
Fringe
Playa
Emergent
Total Wetland
-
-
-
-
-
-100%
0%
0%
0%
0%
-100%
-1%
-12%
-21%
-10%
-100%
-100%
-2%
-56%
-76%
-100%
-100%
-14%
-77%
-86%
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
31
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1100
1000
900
800
700
J8 600
< 500
400
300
200
100
0
Current
Conservation
4200
Plan Trend
4200
Conservation
4212
Plan Trend
4212
I Impounded D Fringe D Playa D 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
Impounded
Fringe
Playa
Emergent
Total Wetland
4,200
Current
162
697
103
48
1010
Conservation
157
687
99
47
990
Plan Trend
120
613
90
37
860
4,212
Conservation
6
9
92
14
121
Plan Trend
4
7
83
8
102
Percent change for each wetland class under different scenarios
Impounded
Fringe
Playa
Emergent
Total Wetland
-
-
-
-
-
-3%
-1%
-4%
-2%
-2%
-26%
-12%
-13%
-23%
-15%
-96%
-99%
-11%
-71%
-88%
-98%
-99%
-19%
-83%
-90%
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
32
-------
ZZUU "
2000 "
1800 "
i t^f\f\
loUU
1 A C\C\
14UU
1200
i nnn
vi 1000
0)
L* Qnn
g oOO
^ 600
/inn
4UU
onn
200
1 1=1
1
—
1=1
1
1 i i ii
Current Conservation Plan Trend Conservation Plan Trend
4200 4200 4212 4212
Scenario
"impoundment D Fringe DPlaya D Emergent
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
Impounded
Fringe
Playa
Emergent
Total Wetland
4,200
Current
1567
432
75
38
2112
Conservation
1544
430
72
38
2084
Plan Trend
1421
422
54
29
1926
4,212
Conservation
393
5
67
11
476
Plan Trend
333
3
49
7
392
Percent change for each wetland class under different scenarios
Impounded
Fringe
Playa
Emergent
Total Wetland
-
-
-
-
-
-1%
0%
-4%
0%
-1%
-9%
-2%
-28%
-24%
-9%
-75%
-99%
-11%
-71%
-77%
-79%
-99%
-35%
-82%
-81%
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
33
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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).
Conservation 4,200
Conservation 4,212
'
Plan Trend 4,200
Habitat Suitability Index
-^CD-IMS
Plan Trend 4,212
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
-------
4%
-16% -•
Conservation
4200
Plan Trend
4200
Conservation
4212
Plan Trend
4212
Scenario
Migratory Shorebirds • Migratory Waterfowl D 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
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
4,200
Current
16285
12536
14135
Conservation
15796
12102
13667
Plan Trend
14323
11100
12286
4,212
Conservation
15980
12734
13811
Plan Trend
14515
11710
12412
Change in most suitable habitat acres for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-489
-434
-468
-1962
-1437
-1849
-305
197
-324
-1770
-826
-1723
Percent change in most suitable habitat for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-3%
-3%
-3%
-12%
-11%
-13%
-2%
2%
-2%
-11%
-7%
-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
-------
Conservation
4200
Migratory Shorebirds
Plan Trend
4200
Conservation
4212
Plan Trend
4212
Scenario
I Migratory Waterfowl D 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 tern
Total acreage of most suitable habitat for each bird group under different scenarios
Bird
Group
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
4,200
Current
1847
918
2754
Conservation
1833
905
2667
Plan Trend
1509
880
2112
4,212
Conservation
1838
987
2669
Plan Trend
1511
953
2112
Change in most suitable habitat acres for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-14
-12
-87
-339
-38
-642
-10
69
-85
-336
35
-641
Percent change in most suitable habitat for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-1%
-1%
-3%
-18%
-4%
-23%
-1%
7%
-3%
-18%
4%
-23%
)late.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
36
-------
6%
-24%
Conservation
4200
CH Migratory Shorebirds
Plan Trend 4200 Conservation Plan Trend 4212
4212
Scenario
• Migratory Waterfowl CD 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
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
4,200
Current
384
307
270
Conservation
378
302
265
Plan Trend
335
259
211
4,212
Conservation
386
320
283
Plan Trend
345
281
232
Change in most suitable habitat acres for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-6
-4
-6
-48
-48
-60
2
13
12
-38
-26
-38
Percent change in most suitable habitat for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-2%
-1%
-2%
-13%
-16%
-22%
1%
4%
5%
-10%
-8%
-14%
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
37
-------
-12%
Conservation Plan Trend Conservation Plan Trend
4200 4200 4212 4212
Scenario
CH Migratory Shorebirds • Migratory Waterfowl D 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
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
4,200
Current
1077
971
844
Conservation
1047
937
830
Plan Trend
963
872
768
4,212
Conservation
1063
961
840
Plan Trend
986
899
779
Change in most suitable habitat acres for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-30
-34
-15
-114
-99
-76
-14
-9
-4
-91
-72
-65
Percent change in most suitable habitat for each bird group under different scenarios
Migratory Shorebirds
Migratory Waterfowl
Migratory Waterbirds
-
-
-
-3%
-3%
-2%
-11%
-10%
-9%
-1%
-1%
-1%
-8%
-7%
-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
-------
Flows and Loads
11OU
h \ov,
(mean cfs)
TP
(Ibi/iuo}
TH
• TSS
(Ibs/ 10,OOO)
Figure 33. Mean Monthly Flows and Loads in the Jordan River.
Table 9. Phosphorus Loads-By-Source.
Source
Point Sources
Turner Dam & Canals
Hay/Pasture
Cropland
Forest
Developed Open Space
Quarry/ Barren Land
Low Intensity Development
High Intensity Development
Stream Bank
Septic Systems
Groundwater
Wetlands
Unpaved Roads
TOTAL
TP (Ibs/yr)
804,230
64,132
328
359
272
561
1,287
1,682
3,890
450
190
4,690
4
2
882,077
Turner
Dam&
Canal—
Flows
Nonpoint
~ Sources
2%
Figure 34. Phosphorus Loads By Source.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
39
-------
Table 10. Nitrogen Loads By Source.
Source
Point Sources
Turner Dam & Canals
Hay/Pasture
Cropland
Forest
Developed Open Space
Quarry /Barren Land
Low Intensity Development
High Intensity Development
Stream Bank
Septic Systems
Groundwater
Wetlands
Unpaved Roads
TOTAL
TN (Ibs/yr)
2,436,212
1,355,373
2,456
2,457.7
2,246
1,057
5,953
10,093
35,716
1,022
2,216
853,644
128
15.5
4,708,589
Sources of Nitrogen Loading
Turner
Dam&
Canal
Flows
29%
Figure 35. Nitrogen Loads By Source.
Table 11. Sediment Loads By Source.
Source
Turner Dam & Canals
Hay/Pasture
Cropland
Forest
Developed Open Space
Quarry/Barren Land
Low Intensity Development
High Intensity Development
Stream Bank
Wetlands
Unpaved Roads
TOTAL
TSS (Ibs/yr)
61,202,881
27,976.7
123,789.6
363,255.7
32,231.6
1,976,841
93,344
12,941
20,438,355
331
2,755.8
84,274,702
Sources of Sediment Loading
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
Jordan
Impoundment
Playa
Total Fringe
Baird
Holmes
Kays
Flow
Cfs
628.3
34.95
299.13
37.07
16.87
7.63
12.57
Total Phosphorus
mg/1
0.69
0.79
0.83
0.77
1.68
0.02
0.03
pounds
859,723
54,291
486,290
56,562
55,656
284
621
Total Nitrogen
mg/1
3.40
3.86
4.08
5.36
9.84
1.58
1.63
pounds
4,213,152
266,054
2,403,814
391,118
326,976
23,829
40,311
Sediment
mg/1
51.03
28.28
39.49
8.18
4.46
11.32
11.25
pounds
63,165,452
1,947,677
23,273,750
597,118
148,334
170,143
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
Jordan
Impoundment
Playa
Total Fringe
Baird
Holmes
Kays
Total Phosphorus
Plan Trend
50%
36%
38%
33%
33%
16%
21%
Conservation
50%
34%
38%
26%
26%
13%
17%
Total Nitrogen
Plan Trend
24%
15%
18%
27%
32%
0%
0%
Conservation
24%
6%
17%
20%
24%
-3%
-3%
Sediment
Plan Trend
-8%
18%
39%
-3%
17%
-2%
-15%
Conservation
-9%
15%
39%
-5%
13%
-3%
-16%
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
41
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!T :-ir: ' .-
PlanTrend Conservation
Kays
• Total Phosphorus
I Totsl Nitrogen • TdalSuspeid«d Solids
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.
Basin
Jordan
Impoundment
Playa
Total Fringe
Baird
Holmes
Kays
Flow
cfs
713.2
40.4
402.8
37.7
19.0
7.2
11.4
Total Phosphorus
mg/1
0.92
0.92
0.85
0.70
2.02
0.03
0.04
pounds
1,293,884
73,937
671,585
75,362
74,280
331
752
%
change
50%
36%
38%
33%
33%
16%
21%
Total Nitrogen
mg/1
3.72
3.57
3.57
5.05
11.68
1.66
1.81
pounds
5,231,031
307,127
2,830,445
494,950
430,957
23,739
40,255
%
change
24%
15%
18%
27%
32%
0%
0%
Sediment
mg/1
41.17
28.35
40.89
11.48
4.99
15.33
14.12
pounds
57,842,230
2,307,498
32,449,376
577,899
173,542
167,314
237,043
%
change
-8%
18%
39%
-3%
17%
-2%
-15%
Table 15. Conservation Future Scenario Watershed Loading: percent change indicates change in loading
from Current scenario.
Basin
Jordan
Impoundment
Playa
Total Fringe
Baird
Holmes
Kays
Flow
cfs
711.2
39.7
401.7
37.7
19.0
7.2
11.4
Total Phosphorus
mg/1
0.92
0.93
0.85
0.96
1.87
0.02
0.03
pounds
1,293,590
72,740
671,086
71,201
70,153
321
727
%
change
50%
34%
38%
26%
26%
13%
17%
Total Nitrogen
mg/1
3.73
3.61
3.57
6.29
10.82
1.62
1.73
pounds
5,222,649
282,282
2,821,833
467,547
405,570
23,058
38,919
%
change
24%
6%
17%
20%
24%
-3%
-3%
Sediment
mg/1
41.24
28.72
40.97
7.62
4.49
11.58
10.33
pounds
57,777,645
2,347,832
32,417,914
566,136
168,258
164,953
232,924
%
change
-9%
15%
39%
-5%
13%
-3%
-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
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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
Ambassador Cut
Goggin Drain
Total Fringe
Baird
Holmes
Kays
Estimated % of Basin that
drains through a wetland
95%
29%
14%
13%
18%
12%
Basin Wetland Retention (Ibs)
TP
501
116
3937
3869
28
40
TN
15,782
1,757
29,447
24,196
2,513
2,738
Sediment
41,226
7,253
24,380
5,560
9,000
9,820
Table 17. Plan Trend scenario wetland retention: percent change indicates change in wetland retention from
the Current scenario.
Basin
Ambassador Cut
Goggin Drain
Total Fringe
Baird
Holmes
Kays
Estimated %
of Basin that
drains
through a
wetland
95%
2%
7%
2%
13%
6%
Basin Wetland Retention
TP
Ibs
1,079
17
797
750
23
23
% change
115%
-85%
-80%
-81%
-18%
-41%
TN
Ibs
22900
171
7696
4617
1757
1322
% change
45%
-90%
-74%
-81%
-30%
-52%
Sediment
Ibs
51,500
617
11,280
920
6,320
4,040
% change
25%
-91%
-54%
-83%
-30%
-59%
Table 18. Conservation scenario wetland retention: percent change indicates change in wetland retention
from the Current scenario.
Basin
Ambassador Cut
Goggin Drain
Total Fringe
Baird
Holmes
Kays
Estimated %
of Basin that
drains
through a
wetland
95%
29%
14%
13%
18%
12%
Basin Wetland Retention
TP
Ibs
971
218
4955
4877
32
46
% change
94%
88%
26%
26%
13%
17%
TN
Ibs
20927
2216
35087
30012
2432
2643
% change
33%
26%
19%
24%
-3%
-3%
Sediment
Ibs
48,590
8,047
23,180
6,260
8,800
8,120
% change
18%
11%
-5%
13%
-2%
-17%
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
43
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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
Utah Duck Club
A
B
C
D
E
F
G
H
I
TP Outflow (mg/1)
Predicted
0.48
0.45
0.44
0.44
0.43
0.41
0.26
0.21
0.17
0.13
Observed
0.44
0.65
NA
NA
NA
NA
NA
0.22
0.16
0.14
Sediment Outflow (mg/1)
Predicted
28
28
28
28
28
28
30
30
31
31
Observed
23
23
NA
NA
NA
NA
NA
29
41
33
Current Conservation Plan Trend
-5%
-10%
-15%
Current Conservation Plan Trend
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
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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.
E
Figure 39. Impoundment Conceptual Framework.
Total Phosphorus
Predtc ted
Observed
H
Wetland Cell
Figure 40. Observed and Simulated Results for Total Phosphorous.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
45
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Sediment
I Simulated
I Observed
Wetland Cell
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
Current
Conservation
Plan Trend
TPin
0.51
0.57
0.56
TPout
0.13
0.18
0.18
Sediment in
27.81
21.19
20.76
Sediment out
31.43
23.49
22.96
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
46
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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
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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
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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
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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 (Rafmi 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
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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 lake-
level 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
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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 A WHA
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
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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 A VGWLF 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
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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
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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 A VGWLF
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 Watershed-
Water 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
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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 re-
suspension 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
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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 Arc View 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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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 Al displays the shoreland elevation zones established
for this study.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 64
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• 4200-4212 | ' 4217-4220 :
42 12 42 1~ [ ^ 422M 423' i Rmnmgtoa Pay Shoi'claads
Figure Al. Shoreland Elevation Zones.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
65
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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
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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).
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
Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 67
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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
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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 Cl presents
the parcel evaluation completed for the restorations opportunities assessment.
Public | | Private
Figure Cl. Parcel Evaluation.
Parcels
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
69
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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.
Goggin Drain
Surplus Canal
2008_NWI_UTM
Inthab_neg100
Interior Habitat
-f
Figure C2. Interior Habitat with Interior Buffers.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
70
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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.
All liydnr
Not Imli if
Piiiliiilly liy
I 'nknoxvn
1 2
Ilvdnc Ckssifcation
Figure C3. Hydric Soils Classification.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
71
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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.
umoers Kepresen
Autumn Monthly Water
Rights icfs).
Major Landowners
Ambassador D"JCi< Club
Ai.it L: on
| Epperson Assooate-s-
I Hamsun Duck Club I
Now State Duck Club
I Worth Point Fir S Rsclamaliim I
RudyAunr.lub
Ulalil-SW
Utah Lake Duck Club
Figure C4. Example of Shoreland Conveyances and Water Rights.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
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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).
^f Phdgimles Colonies
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)
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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
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Fuzzy set theory yields values that range from 0 to 1 based on derived relative weights for
suitable variables (Banai, 1993).
Table Dl 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
Arc View 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
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Table Dl. Variable Strength and Weights Worksheet for One Bird Grouping.
Base Variable for Habitat Suitability Index
Variable-
Description
Wetland Type
Vegetation
Phragmites
Interior Habitat
Roads
Land Use
Variable Strength
(Vs)
0.50
1.00
0.10
0.60
0.10
0.60
CIS
Value
0.00
1.00
2.00
3.00
4.00
8.00
1.00
3.00
4.00
6.00
7.00
8.00
9.00
10.00
11.00
13.00
0.00
2.00
1.00
0.00
0.00
1.00
2.00
3.00
4.00
1.00
2.00
3.00
0.00
1.00
2.00
3.00
4.00
5.00
7.00
8.00
12.00
13.00
Fuzzy Operator
GIS Descriptor
Non-wetland
Open Water
Impounded
Playa
Fringe
Emergent
Open Water
75 Akali Bulrush
75 Cattail/Bulrush
50-75 Alkali Bulrush
Playa Mudflat Unvegetated
Playa Mudflat Vegetated
Mixed Emergent
Upland
Tamarisk
River/Channel
Other
Greater than 75% Phragmites
Between 5 1-75% Phragmites
No Phragmites
Zero Interior Habitat
Interior habitat 0- 100 from edge
Interior habitat 100 from edge
Interior habitat 200 from edge
Interior habitat 300 + from edge
Four-Lane Highway
Two-lane Paved Road
Near Grade; Dirt Roads; Trails
No roads
High Development Areas
Low Development Areas
Golf Courses/Turf Areas
Row Crops
Forested Areas
Hay /Pasture or Scrub Shrub
Open Space/Barren Land
Barren Land
Turf Grass/Golf
Weight (0-1)
(Wt)G
0.00
1.00
1.00
0.50
0.50
1.00
1.00
0.20
0.00
0.20
1.00
0.40
1.00
1.00
0.00
0.30
0.00
1.00
0.00
0.00
0.00
1.00
0.50
0.50
1.00
1.00
0.00
0.30
0.50
0.00
0.00
0.00
0.00
1.00
0.00
0.00
0.30
0.00
Final GIS
values
0.00
0.50
0.50
0.25
0.25
0.50
1.00
0.20
0.00
0.20
1.00
0.40
1.00
1.00
0.00
0.30
0.00
0.10
0.00
0.00
0.00
0.60
0.30
0.30
0.60
0.10
0.00
0.03
0.05
0.00
0.00
0.00
0.00
0.60
0.00
0.00
0.18
0.00
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
76
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Table D2. Final matrix of weights for all bird groupings.
Base Variable for Habitat Suitability Index
Value
0.00
1.00
2.00
3.00
4.00
8.00
1.00
3.00
4.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
0.00
0.00
1.00
2.00
0.00
1.00
2.00
3.00
4.00
0.00
1.00
2.00
3.00
1.00
2.00
3.00
4.00
5.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
Variable
Wetland
Wetland
Wetland
Wetland
Wetland
Wetland
Vegetation
Vegetation
Vegetation
Vegetation
Vegetation
Vegetation
Vegetation
Vegetation
Vegetation
Vegetation
Vegetation
Phragmites
Phragmites
Phragmites
I. Habitat
I. Habitat
I. Habitat
I. Habitat
I. Habitat
Roads
Roads
Roads
Roads
Land Use
Land Use
Land Use
Land Use
Land Use
Land Use
Land Use
Land Use
Land Use
Land Use
Land Use
Land Use
Descriptor
Non- Wetland
Lacustrine Types
Impounded
Fringe
Playa
Emergent
Open Water
75 Alkali Bulrush
75 Cattail/Bulrush
50-75 Alkali Bulrush
Playa Mudflat Unveg
Playa Mudflat Veg
Mixed Emergent
Upland
Tamarisk
River Channel
Other
na
50-75
75-100
0
1-100
100-200
200-300
300+
none
4 lane
2 lane
dirt/path
Open Water
Low Dev
HighDev
Row Crop
Hay/Past
Coniferous
Mixed Forest
Deciduous
Wood Wetland
Emer Wetland
Barren Land
Turf Grass/Golf
Mgsh
0
0
0
0
0
0
1
0
0
0
1
0
1
1
0
0
0
0
0
00
50
50
25
25
50
00
20
00
20
00
40
00
00
00
30
00
10
00
0.00
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
00
60
30
30
60
10
00
03
05
00
00
00
00
60
00
00
00
00
00
18
00
Ncsh
0.00
0.50
0.50
0.25
0.25
0.50
1.00
0.00
0.00
0.00
0.60
0.40
0.00
0.00
0.00
0.00
0.00
0.10
0.00
0.03
0.00
0.06
0.06
0.06
0.06
0.50
0.10
0.05
0.25
0.00
0.00
0.00
0.00
0.10
0.00
0.00
0.00
0.00
0.00
0.02
0.00
Mgwf
0.00
0.50
0.50
0.50
0.25
0.50
1.00
0.80
0.60
0.80
0.80
0.80
1.00
0.70
0.20
0.30
0.00
0.30
0.09
0.15
0.00
0.80
0.40
0.40
0.80
0.40
0.08
0.08
0.16
0.00
0.21
0.14
0.56
0.49
0.00
0.00
0.00
0.00
0.00
0.00
0.49
Mgwb
0.00
0.50
0.50
0.25
0.00
0.25
0.90
0.00
0.00
0.00
0.90
0.00
0.36
0.90
0.00
0.00
0.00
0.30
0.00
0.00
0.00
0.18
0.24
0.30
0.42
0.30
0.06
0.06
0.15
0.00
0.48
0.80
0.48
0.80
0.00
0.00
0.00
0.00
0.00
0.00
0.16
Ncwb
0.00
0.50
0.50
0.50
0.50
0.50
0.90
0.72
0.72
0.72
0.63
0.36
0.90
0.27
0.27
0.45
0.00
0.60
0.42
0.60
0.00
0.14
0.21
0.49
0.70
0.20
0.04
0.04
0.08
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
Lbcr
0.00
0.00
0.50
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.80
0.80
0.00
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.12
0.20
0.32
0.20
0.00
0.00
0.16
0.00
0.00
0.00
0.00
0.64
0.00
0.00
0.00
0.00
0.00
0.48
0.00
Apel
0.00
0.50
0.00
0.50
0.00
0.00
0.70
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.35
0.00
0.00
0.00
0.00
0.00
1.00
1.00
1.00
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Snpl
0.00
0.00
0.50
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.30
0.00
0.00
0.00
0.21
0.21
0.28
0.56
0.40
0.12
0.12
0.32
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.18
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
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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.I 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 "poor-
quality" 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
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8.5 APPENDIX E. CALIBRATION OF THE AVGWLF MODEL IN THE JORDAN RTVER 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 in-
stream 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 watershed-
specific 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 (r2) coefficient and 2) the
Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 79
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Nash-Sutcliffe coefficient. The r2 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 r2 can
vary from 0 to 1, with 1 indicating a perfect fit between observed and predicted values. Like the r2
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 r2 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., r2 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 r2 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 r2 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 r2 values, higher Nash-Sutcliffe values reflect higher degrees of
correlation than lower ones.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 80
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Figures El, E2 and E3 below present a representation of the calibration results for a ten year time
period, 1995-2005.
40000 -
38000 -
36000 -
34000 ---
32000 ---
30000 \
28000
26000 --'
24000 -
22000 -
20000
Year
•Observed Simulated
Figure El. Comparison of Observed and Simulated Watershed Loading to the Surplus Canal for Total Phosphorous.
350000 -
325000 -
300000 -
275000 -
250000 -
225000 -
200000 -
175000 -
150000 -
125000 -
100000 -
75000 -
50000 -
ON
ON
ON
00
ON
ON
ON
o
9
§
9
§
-------
(7v
a
o o o o o o
J. J, _L I, J. JL
S S S i H S
Year
• Observed Simulated
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 El 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
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Table El. Information Sources for AVGWLF Model Parameterization.
WEATHER.DAT file
Data
Precipitation and Temperature
Source or Value
Historical weather data from Salt Lake City, UT and
Provo, UT National Weather Service Stations
TRANSPORT.DAT file (See Figure 13.1.2)
Data
Basin size
Land use/cover distribution
Curve numbers by source area
USLE (KLSCP) factors by source area
ET cover coefficients
Erosivity coefficients
Daylight hrs. by month
Growing season months
Initial saturated storage
Initial unsaturated storage
Recession coefficient
Seepage coefficient
Initial snow amount (cm water)
Sediment delivery ratio
Sediment "a" factor
Soil water (available water capacity)
Source or Value
GIS/derived from basin boundaries
GIS/derived from land use/cover map
GIS/derived from land cover and soil maps
GIS/derived from soil, DEM, & land cover
GIS/derived from land cover (adjusted)
GIS/derived from physiography map (adjusted)
Computed automatically for state
Input by user
Default value of 0 cm
Default value of 10 cm
Calculated using standard hydrograph separation
techniques
Default value of 0
Default value of 0
GIS/based on basin size
GIS/empirically derived (adjusted)
GIS/derived from soil map
NUTRIENT.DAT file (See Figure 13.1.3)
Data
Dissolved N in runoff by land cover type
Dissolved P in runoff by land cover type
N/P concentrations in manure runoff
N/P buildup in urban areas
N and P point source loads
Background N/P concentrations in GW
Background P concentrations in soil
Background N concentrations in soil
Months of manure spreading
Population on septic systems
Per capita septic system loads (N/P)
Source or Value
Default values by land cover type
Default values by land cover type
Default values (from GWLF Manual)
Default values (from GWLF Manual)
Derived from EPA STORET database
Derived from background N map (adjusted)
Derived from soil P loading map
Based on map in GWLF Manual
Input by user
Derived from census tract maps for 2000
Default values (from GWLF Manual)
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
83
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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
RualLU
A, ,-o (M
Cropland
Forest
Wetland
Land
Uifaan I.U
Month Ket Oar Scaion LIDS
Sticam
Extract
Giound
Enlracl
Hour*
fbl
feb o 10.4
M*t 062 |118
065
Iml Unut Sloi (cm) II
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Untat Avail Wai (en)
Coafficieiri JftOI
Factor |9397Q£-06
Load Fie
Save Fd*
Eitpot!
tkpie
Figure E4. AVGWLF Input Transport File.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
84
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Runoff Coeffciftrtts by Soufce
Rural Rural fts N mgA D« P mjfl.
Manure
iJrten &j«h-Up N Kg/ta/d P Kg*ajy
Lo_lnU>w (0012 |0.002
HiJnLDev [0101 |0011
(mg/L)
frs
oi
Phosphorus Loads Fran Point Sources and Sepfc Systems
Port SouFce Loads/Discharge
Kj N Kg P ftators
U3D
foofob"
|oo foo
"5
foo foo
~"
Sepfc 5/stem PopUaliofis
ffcumal Pond
Systems Systems
|3U5 [o~* [ITT
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|3U5
1 31 45
ITT
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1TT
pt77
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N P Sad
ITT" faT ficT
PwcaptotarKabert
Systems
JO
0
Growing ss&onWP uptake Sedmert
Njmg^o)
fsocoo
o
Loadfae | Save Ffe | ExpoH to JPi'li [ Cta»
Figure E5. AVGWLF Input Nutrient File.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
85
-------
GWLF-E Hydrology for file: Jordan-1
Period of analysis: 1 2 years from 1 994 to 2005
Units in Centimeters
Month
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Ocl
Nov
Dec
Totals
Prec
[4.45
[4.29
|4.11
|5.68
|4.76
|aos
[1.18
|1.S1
|262
|3.90
J4.00
[3.90
[43.55
Go Back
ET
" |0.49
" [0.82
" |2.05
" [3~33~
" |6.07
" [7.12
" [223
" |1.35
" 1 2.1 7
" |1.57
foir
" |0.40
" |2B.42
Extraction Runoff
|0,00
|000
IO.OQ
|000
|o oo
|o oo
[ooo
[O.QO
|ooo
[000
1 0.00
|ooo
IG.OO
Monthly Loads
[0.22
|0,10
|0,07
|0.04
|0.03
fo. 03
[000
lo.oo
IQ.OO
[0.08
[0.16
[0.12
[0,85
III'*
Subsufface
Flow
[094
[131
|l.84
[1,93
[115
[1.73
[135
[0.93
[0.70
[054
1042
[0.55
[14.46
port to7PEET
Point Src
Flow
|000
fo~oo
[0,00
[0.00
[000
[0.00
po
[o.oo
|aoo
faro
[0.00
[0.00
[0,00
| Print
Tite Drain Stream
Flow
IO.OQ
[000
(000
[aiT
|o.oo
[aoo
|abo~
[aw
(aoo
[0.00
(0.00
[aoo
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I
|115
|1.41
1 1.91
[1.97
|2.18
|1.76
™ r~"
1 1.35
[0.99
|a?i
fosi
[0.58
(as?
|15.31
Close
^v
^^
^B>
Figure E6. Simulated Hydrology Transport Summary.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
86
-------
GWLF-E Loads for file: Jordan-1
Period of analysis: 12 years from 1994 to 2005
Kg X 1000
Month
Jan
Feb
MM
Apt
M«
Jim
Erosion
Sediment
[1498,6 J725.9
(2803.2
883.3
(2352,8 J1014.6
[1107.4 [1085.3
[1857,3 [1219.1
(1876.6 J1105.9
.1"' [23227 [811.4
Aug
Sep
Oct
Nov
Dec
Totals
(1956.5 (673.5
(16630
571 5
(1257,1 1638.7
(1501.8 (700.9
[3219.7 [1035.3
J23421J (104652
DisN
(26113.0
(35544.8
(49572,2
(51310.1
(57774.3
(46548.7
(38278,2
(26582.1
(189429
(14668.4
(11955.4
(153754
1 391 265.4
Nutrient Loads (Kg)
Total N
(29412.7
[37906.9
[51761,3
[54779.9
(59501.7
[47930.9
[36354.0
(268325
119521.0
[17221.8
(15205.5
(13518.2
(4159462
DtsP
(293.6
(261.8
(3128
(238.5
(329.3
(2757
[204.9
(151.7
(109.6
(1293
(2054
(173.4
(27459
Total P
(723,4
(563.9
(599.6
(658,0
(586,9
(496.3
(2271
(190.3
(184,9
(4834
(673.0
(834.6
(62212
Go Back Loads by Source Export to JPEG Print Close
1 1 '"- • • -1 . 1
Figure E7. Simulated Nutrient Transport Summary.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
87
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GWLF Total Loads for file: Jordan-1
Period of analysis: 1 2 years from 1 994 to
2006
Source
Hay/Pasl
Qoptand
Foief*
Wetland
Quatiy
Lfnpav*d_Rd
Lc.jm_Dev
Hi_lnt_0sv
Farm Animals
Tile Diamage
Sir earn Bank
Ground water
Point Sources
Septic Systems
Total*
•VI KgX Total Load* (Kg)
IH«! Icml Elation
Sedimenl Dit N
S3172 (0,5 }24&9 |12.7
JSIM |l
,2 [1101.0
(56.2
[81969 |03 [32307 |164,3
(1329 |2.3 [23
14339 |1
,7 [17532.0
[7071 fo.3 [286.7
i5 |2.3 [24.4
[34321
.3 [330.1
|0.2
|89&7
|14.6
jl.3
142.3
[5167 fs.9 [115.1 |5.9
I I
1
[147133 [0.8 [23421.7
Go Back
1
1
r
|oo
19270.7
)1 0465.2
Pathogen Loads [TE
[107S.1
[346,3
[524,5
|57.7
[103
[435.7
[13
[0.0
ID.O
1
1
r
[387206.3
|o
[1005.2
[391265.4
Kpoct to JPEG j
Total N
|1114.1
(1114.3
(Toisl
|58.2
12700.3
(4735
(71
(4577.3
(16200.4
1
1
1
(o.o
(0.0
(463.5
(387206.3
(o
(10052
(415946.2
Print
Di*P
[140.7
[126.3
[its
pn
|1.7
[245.0
[0.2
[0.0
[00
1
1
r
[2127.5
|o
[86.1
[2745.9
Close
Total P
|uas
|162.7
|i2as
|1,9
[5837
(254.5
lil
[763.0
(1764.4
I
I
I
(0.0
(0.0
[204.0
[2127.5
[0
[86.1
(6221.2
Figure E8. Simulated Total Loads by Source.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
88
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Table E2: Jordan River Land Use Acreage Distribution.
Land Use Category
Open Water
Agn culture
Hay & Pasture
Cropland
Developed Land
Low Intensity
High Intensity
Forest
Wetlands
Quarry/Barren Land
Developed Open Space
TOTAL
Acres
% of Drainage Basin
0.20%
8.40%
6.20%
2.20%
26.80%
23.30%
3.50%
55.60%
0.90%
3.30%
4.80%
100%
Table E3. Simulated Phosphorus Loading Allocations; pounds per year.
Source
Point Sources
Turner Dam & Canals
Hay/Pasture
Cropland
Forest
Developed Open Space
Quarry/Barren Land
Low Intensity Development
High Intensity Development
Stream Bank
Septic Systems
Groundwater
Wetlands
Unpaved Roads
TOTAL
Total Phosphorus
(Ibs/yr)
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
89
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Table E4. Simulated Sediment Loading Allocations; Pounds per year.
Source
Turner Dam & Canals
Hay/Pasture
Cropland
Forest
Developed Open Space
Quarry/Barren Land
Low Intensity Development
High Intensity Development
Stream Bank
Wetlands
Unpaved Roads
TOTAL
(lbs/yr)
61,202,88
27,976.70
123,789.60
363,255.70
32,231.60
1,976,841
93,34
12,941
20,438,355
331
2,755.80
84,274,702
Table E5. Simulated Total Nitrogen Loading Allocations; Pounds per year.
Total Nitrogen (lbs/yr)
Source
Point Sources
Turner Dam & Canals
Hay/Pasture
Cropland
Forest
Developed Open Space
Quarry/Barren Land
Low Intensity Development
High Intensity Development
Stream Bank
Septic Systems
Groundwater
Wetlands
Unpaved Roads
TOTAL
Table E6. Mean Annual Loadings to the Surplus Canal.
Parameter
Total Inputs
Flow (acre-feet)
Sediment (Ibs)
Total Phosphorus (Ibs)
Total Nitrogen (Ibs)
574,416
84,274,702
882,077
4,708,589
* Accounts for 6% stream attenuation
Total
Extractions
119,187
21,109,250
22,354
495,436
Net Totals
455,229
63,165,452
859,723*
4,213,153
Alternative Futures Analysis of Farmington Bay Wetlands (GSL)
90
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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 first-
order removal rate calculation:
c = r
'-'out ~~ Mn
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 Fl display the STORET data used and the locations of the sampling stations.
Alternative Futures Analysis of Farmington Bay Wetlands (GSL) 91
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Table Fl. STORET data used in model development.
STOHET Data (M». - Sept. 2003 - 20 07)
Station
4985315
498532C
4385330
4985340
4985350
Avg. Flow (cfsj
3.60
B.25
1.97
Avg. TP (mg/l)
0.44
0.65
0.22
0.16
0.14
Avg.TSS(mg/l)
23.23
22.84
29 .OB
41.39
32.62
Figures Fl 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.
1.43 to.44 f
0.44
0.44 .0.44 ...
0.51
Jordan
Watersted
Loading
Numbers in red = simulatedTP concent ration (mg/L)
Numbers in black = observed TP can cent rat inn (mg/L)
Figure Fl. Impoundment Template Wetland Cells with Simulated (red) and Observed (black) TP Concentrations
(mg/L).
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28.2
27.8
Jordan
Watershed
Loading
Numbers in red = simulated TSS concentration (rni/L)
Numbers in black = observed TSS concentration (mg/L)
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 Fl, 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).
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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.
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