INVESTIGATIVE SURVEY OF STORMWATER LOADING – NITROGEN AND PHOSPHORUS IMPACTS ON URBAN EUTROPHIC LAKE: LONG LAKE, LACEY, WASHINGTON

Item

Title

Eng INVESTIGATIVE SURVEY OF STORMWATER LOADING – NITROGEN AND PHOSPHORUS IMPACTS ON URBAN EUTROPHIC LAKE: LONG LAKE, LACEY, WASHINGTON

Date

Eng 2021

Creator

Eng Converse, Jessica

Identifier

Eng Thesis_MES_2021_Converse

extracted text

INVESTIGATIVE SURVEY OF STORMWATER LOADING –
NITROGEN AND PHOSPHORUS IMPACTS ON URBAN EUTROPHIC LAKE:
LONG LAKE, LACEY, WASHINGTON

by
Jessica K. Converse

A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
June 2021

© 2021 by Jessica Converse. All rights reserved.

This Thesis for the Master of Environmental Studies Degree
by
Jessica K. Converse

has been approved for
The Evergreen State College
by

________________________
Erin Martin, Ph.D.
Member of the Faculty

________________________
Date

ABSTRACT
Investigative Survey of Stormwater Loading – Nitrogen and Phosphorus Impacts on Urban
Eutrophic Lake: Long Lake, Lacey, Washington
Jessica K. Converse
Harmful algal blooms are increasing in prevalence and duration worldwide as a result of global
environmental perturbations including nutrient enrichment and climatic changes. Such is the case
for Long Lake, one in a chain of three lakes located in Lacey, Washington. This urban, eutrophic
lake experiences summer long closures due to cyanotoxins released from bloom-forming
cyanobacteria. As a result, the Long Lake Management District ordered an investigative study be
completed to assess the nutrient contribution of stormwater flowing into Long Lake. Grab
samples were collected from multiple sites around the lake during three storm events and two
non-storm events between November 2020 and March 2021. Samples were analyzed for total
nitrogen (TN), total phosphorus (TP), and soluble reactive phosphorus (SRP) due to the influence
these nutrients have on primary production and cyanobacterial blooms. Results indicated that the
earlier seasonal storm events (November, December) transported higher concentrations of
nutrients into the lake rather than later seasonal storms (February). Additionally, the highest
concentrations of TP and SRP were delivered during storm events from the storm drain outfalls.
Measured between January and March 2021, dissolved oxygen (DO) readings were highest at the
surface of the lake. However, several meters below the surface DO levels were near 0 mg/L
demonstrating that Long Lake was stratified. It is uncommon for the lake to be stratified during
the winter months and could suggest that the lake’s surface temperature is warming earlier in the
year. Conductivity readings differed between Long Lake’s two basins with the south basin
reading higher in conductivity than the north. The Long Lake Management District would benefit
from further study of stormwater nutrients in the form of nitrates and nitrites as those nutrients
were not analyzed for during this study. Furthermore, DO and temperature readings should be
conducted throughout the year to better understand Long Lake’s nutrient turnover rate.

TABLE OF CONTENTS
TABLE OF CONTENTS ............................................................................................................IV
LIST OF FIGURES .........................................................................................................................VI
LIST OF TABLES........................................................................................................................ VIII
ACKNOWLEDGEMENTS ...............................................................................................................IX
1. INTRODUCTION...................................................................................................................... 1
2. LITERATURE REVIEW ......................................................................................................... 4
2.1 INTRODUCTION ....................................................................................................................... 4
2.2 THERMAL STRATIFICATION OF LAKES ................................................................................... 5
2.3 NUTRIENT CYCLING IN LAKES ............................................................................................. 10
2.3.1 Nitrogen Cycle .............................................................................................................. 10
2.3.2 Phosphorus Cycle ......................................................................................................... 15
2.3.3 Hydraulic Residence Time ............................................................................................ 17
2.4 TROPHIC STATE INDICATORS ............................................................................................... 18
2.4.1 Secchi Disk .................................................................................................................... 19
2.4.2 Chlorophyll-a ................................................................................................................ 21
2.5 IMPACTS OF LAND-USE ON NUTRIENT CYCLING IN URBANIZED EUTROPHIC LAKES .......... 21
2.6 URBAN STORMWATER POLLUTION ...................................................................................... 24
2.7 STORMWATER MANAGEMENT ............................................................................................. 26
2.8 STORMWATER MITIGATION ................................................................................................. 31
2.9 PUBLIC HEALTH RISKS ASSOCIATED WITH CYANOHAB EXPOSURE .................................. 33
2.12 SUMMARY .......................................................................................................................... 34
3. METHODS ............................................................................................................................... 35
3.1 INTRODUCTION ..................................................................................................................... 35
3.2 RESEARCH METHODS ........................................................................................................... 38
3.3 Site Selection .................................................................................................................... 38
3.4 FIELD SAMPLING METHODS ................................................................................................. 43
3.4.1 Water Quality and Depth Profile Measurements .......................................................... 45
3.4.2 Sample Analysis ............................................................................................................ 46
3.5 STATISTICS ........................................................................................................................... 48
3.5.1 NUTRIENT DATA ............................................................................................................... 48
3.5.2 STORM DRAIN TO LAKE COMPARISONS ............................................................................ 49
3.5.3 STORM EVENT TO BASELINE COMPARISONS .................................................................... 49
3.5.4 NUTRIENT LOAD ALLOCATION LIMITS ............................................................................. 49
4. RESULTS ................................................................................................................................. 51
4.1 TOTAL NITROGEN ................................................................................................................ 51
4.1.2 Storm Verses Baseline Sampling Events .................................................................... 51
4.1.3 Storm Drain Verses Lake TN Concentrations ............................................................ 52
4.1.4 Inlet and Outlet Comparisons .................................................................................... 52
4.2 TOTAL PHOSPHORUS ............................................................................................................ 57
4.2.2 Storm Verses Baseline Sampling Events .................................................................... 58
4.2.3 Storm Drain Verses Lake TP Concentrations ............................................................ 58
4.2.4 Inlet and Outlet Comparisons .................................................................................... 58
4.3 SOLUBLE REACTIVE PHOSPHORUS ....................................................................................... 63
4.3.2 Storm Verses Baseline Sampling Events .................................................................... 64

iv

4.3.3 Storm Drain Verses Lake SRP Concentrations .......................................................... 64
4.3.4 Inlet and Outlet Comparisons .................................................................................... 64
4.4 DEPTH PROFILES .................................................................................................................. 68
4.4.1 Dissolved Oxygen.......................................................................................................... 68
4.4.2 Conductivity .................................................................................................................. 71
4.4.3 Temperature and pH ..................................................................................................... 73
5. DISCUSSION ........................................................................................................................... 78
5.1 Dissolved Oxygen............................................................................................................. 78
5.2 Actionable Nutrient Load Allocation Limits .................................................................... 80
5.3 Temporal Variability of Storm Events.............................................................................. 81
5.4 Storm Drain Effluent ........................................................................................................ 82
5.5 Inlet vs. Outlet .................................................................................................................. 82
5.6 Study Issues ...................................................................................................................... 83
6. CONCLUSION & FUTURE WORK ..................................................................................... 84
6.1 CYANOHAB ASSESSMENT & MANAGEMENT ...................................................................... 84
6.2 LONG LAKE MANAGEMENT ................................................................................................. 85

v

List of Figures
Figure 1 Thermal Stratification in Lakes ........................................................................................ 7
Figure 2 Nitrogen Cycle................................................................................................................ 12
Figure 3 Phosphorus Cycle in Lakes............................................................................................. 17
Figure 4 Secchi Disk ..................................................................................................................... 20
Figure 5 Overview of pathways and sources of nutrients in urban environment. ......................... 23
Figure 6 Impervious Cover Model. ............................................................................................... 24
Figure 7 Wellhead Protection Areas within the City of Lacey. .................................................... 29
Figure 8 Critical Aquifer Recharge Areas within the City of Lacey............................................. 30
Figure 9 Topographic map of chain of lakes: Hicks, Pattison, Long Lake, Lake Lois. ................ 37
Figure 10 Sampling Locations across Long Lake. ........................................................................ 40
Figure 11 Sampling sites in the southern basin sans LO4. ........................................................... 41
Figure 12 Sampling sites in the northern basin sans LO3. ............................................................ 42
Figure 13 Outlet sampling sites. ................................................................................................... 43
Figure 14 Total nitrogen concentrations across all sites. .............................................................. 54
Figure 15 Site Casino, Drain Vs. Lake: Total Nitrogen ................................................................ 55
Figure 16 Site Lorna, Drain Vs. Lake: Total Nitrogen ................................................................. 56
Figure 17 Total nitrogen entering and exiting Long Lake. ........................................................... 57
Figure 18 Total phosphorus across all sites. ................................................................................. 60
Figure 19 Site Casino, Drain Vs. Lake: Total Phosphorus ........................................................... 61
Figure 20 Site Lorna, Drain Vs. Lake: Total Phosphorus ............................................................. 62
Figure 21 Total phosphorus entering and exiting Long Lake. ...................................................... 63
Figure 22 Soluble Reactive Phosphorus concentrations across all sites. ...................................... 66
Figure 23 Site Casino, Drain Vs. Lake: Soluble Reactive Phosphorus......................................... 66
Figure 24 Site Lorna, Drain Vs. Lake: Soluble Reactive Phosphorus. ......................................... 67
Figure 25 Soluble Reactive Phosphorus entering and exiting Long Lake. ................................... 67

vi

Figure 26 Changes in oxygen with depth at LO3 & LO4, 2/17. ................................................... 69
Figure 27 Changes in oxygen with depth at LO3 & LO4, 2/22. ................................................... 70
Figure 28 Changes in oxygen with depth at LO3 & LO4, 3/23. ................................................... 70
Figure 29 Changes in conductivity with depth, 2/17. ................................................................... 71
Figure 30 Changes in conductivity with depth, 2/22. ................................................................... 72
Figure 31 Changes in conductivity with depth, 3/23. ................................................................... 72
Figure 32 Changes in temperature with depth, 2/17. .................................................................... 74

vii

List of Tables
Table 1 Classes of TSI values and their ecological attributes. ...................................................... 19
Table 2 Sampling dates, event type, and weather on sample day. ................................................ 44
Table 3 Washington state nutrient load allocation guidance. ........................................................ 48
Table 4 Summary statistics for site sample concentrations of total nitrogen. ............................... 52
Table 5 Summary statistics for site sample concentrations of total phosphorus. .......................... 59
Table 6 Summary statistics for site sample concentrations of soluble reactive phosphorus (SRP).
....................................................................................................................................................... 65
Table 7 Wilcoxon Rank Sum Test Results.................................... Error! Bookmark not defined.
Table 8 Wilcoxon Signed Rank Test Results ................................ Error! Bookmark not defined.
Table 9 Dissolved oxygen readings: February 17, 2021. .............................................................. 69
Table 10 Dissolved oxygen readings: February 22, 2021. ............ Error! Bookmark not defined.
Table 11 Dissolved oxygen readings: March 23, 2021. ................ Error! Bookmark not defined.
Table 12 Conductivity with depth, 2/17. ....................................... Error! Bookmark not defined.
Table 13 Conductivity with depth, 2/22. ....................................... Error! Bookmark not defined.
Table 14 Conductivity with depth, 3/23. ....................................... Error! Bookmark not defined.
Table 15 Temperature and pH readings, 2/17. .............................................................................. 73
Table 16 Temperature and pH readings, 2/22. .............................................................................. 74
Table 17 Temperature and pH readings, 3/23. .............................................................................. 75
Table 18 Dissolved Oxygen Criteria for Aquatic Life in Fresh Water ......................................... 78
Table 19 Storm Event Nutrient Concentration Ranges. ................ Error! Bookmark not defined.

viii

Acknowledgements
This thesis would have been impossible without a project, so muchísimas gracias a ¡Paula
Cracknell! for your instruction, generosity, and guidance. Thank you for the laughs and for the
doors you have opened for me.
I am so grateful to my reader, Erin Martin, for offering her time, feedback, and humanity. You
have helped me and many others to achieve their dreams.
Gracias a mi amor, vb. Your abundant and unerring support never fails to surprise me, to lift me
up, and make me fall in love with you all over again. You’re a tip-top, first mate.
To my mother who has never doubted me, who gave me life. My greatest teacher. Your love (&
Dad’s) of science is contagious!
To ALL of my teachers - you inspired and guided me. You vouched for me. You lead and light
the way for others. Where would we be without you. Thank you.
I would not be here without the loving support of all the friends who believe in me, (and Jennifer,
thank you for feeding this college student!) I aim to give back to the world what has been so
freely given to me.
Thank you.

ix

1. INTRODUCTION
Due to the regular and increasing presence of cyanobacterial caused harmful algal blooms
(henceforth referred to as cyanoHABs) in Long Lake (Lacey, WA), a research study was
conducted to see if the limiting nutrients for these bacteria are being deposited through
stormwater runoff. The nutrients to be analyzed, nitrogen and phosphorus, are regularly
occurring within this environment. Long Lake is a eutrophic and highly productive lake
(Thurston County Environmental Health Division, 2019). High concentrations of nutrients are
present as a result of the historical dumping of logging pulp into the lake (Cracknell, P., personal
communication, September 2020) as well as from the subsequent effects of urban development
around the lake. Increased sediment transport due to deforestation, construction and impervious
surfaces contribute nutrients into the lake that would otherwise be sequestered on land (Lathrop et
al., 1998; Smith et al., 2020; Yang & Lusk, 2018).
Since 1989, Long Lake’s water quality has been visibly deteriorating. Largely as a result
of aquatic plant growth, the lake has become increasingly colonized by native and invasive
species (Entranco, 1994). Additionally, increased nutrients, warmer temperatures, sunlight, and
reduced water flow provide the optimal growing conditions for freshwater cyanobacteria (Ho &
Michalak, 2015; Jacoby et al., 2000). Cyanobacteria, also known as “blue-green algae” have
been attributed to the toxic algal blooms in Long Lake based on the cyanotoxins present including
microcystin, anatoxin-a, cylindrospermopsin, and saxitoxin (Washington State Freshwater Algae
Control Program, 2020). While not every algal bloom is toxic, data collected from Long Lake
over the past decade show that toxic algal blooms are becoming increasingly regular with six
years out of the past decade (2010-2020) testing above recommended limits for the cyanotoxin,
microcystin and one year (2016) testing above recommended limits for anatoxin-a (WADOE
2020).

1

Microcystin is a type of cyanotoxin which can impair liver function and may be
carcinogenic (Carmichael, 1991; Corbel et al., 2014). Anatoxin-a is a neurotoxin which disrupts
signaling at nervous and neuromuscular junctions, causing paralysis which can lead to respiratory
failure and death (Aronstam & Witkopt, 1981). Cyanotoxins can be lethal to livestock and pets
that drink affected waters, and numerous fish and bird kills have been attributed to toxic bacteria
(US EPA, 2013). The algal blooms themselves look like a green “scum” or paint spilled across
the surface. When extremely dense, as it was last summer on Long Lake (2020), the blooms can
become thick enough to block sunlight from reaching aquatic plants below the water’s surface
(Wehr et al., 2015).
For example, this past summer (2020), cyanobacteria proliferated the lake’s warm,
nutrient rich waters producing thick mats of malodourous, green “scum” on its surface
(Cracknell, 2020). Whether lake residents would choose to swim in such conditions or not, Long
Lake residents were prohibited from entering the lake due to the presence of the cyanobacterial
hepatotoxin, microcystin, the same toxin that has precluded recreation at some point in Long Lake
for most summers over the past decade (Ecology, 2020). It is still unknown precisely under what
conditions cyanobacteria will produce their toxins, however warmer temperatures and high levels
of nutrients, specifically nitrogen (N) and phosphorus (P), have been noted as precursors to the
blooms themselves (Ho & Michalak, 2015; Jacoby et al., 2000). Understanding how to adjust to
and possibly ameliorate cyanoHABs is a priority for those concerned with water quality and has
become the top priority for Long Lake’s Lake Management District (LLMD).
The process of nutrient cycling within this waterbody is complex, and the LLMD has
prioritized known areas of concern for nutrient enrichment including invasive species
management, septic system upkeep, and lawn fertilizer runoff (Lake Management District #21,
2017). However, stormwater outfalls have yet to be taken into account. This study aims to answer
whether or not stormwater is a contributing source of total nitrogen (TN), total phosphorus (TP),
or orthophosphate (PO43-) for the Long Lake system during the winter storm period. These

2

nutrients were selected due to their influence on cyanobacteria growth (Beversdorf et al., 2017;
Bhateria & Jain, 2016). This investigative survey will compare water samples collected from
stormwater outfalls around the basin to those collected in the lake to understand how significant
an issue stormwater pollution may have on this waterbody.
The subsequent literature review will address nitrogen and phosphorus cycling in lake
ecosystems, discuss some of the impacts land-use has on nutrient cycling in urban-eutrophic
lakes, the role of stormwater outfalls as nutrient inputs, what is currently known about the health
risks associated with cyanoHAB exposure, as well as how the LLMD has treated toxic blooms in
the past. Additionally, watershed management practices that show promise for curbing
cyanobacteria growth will be posited for their utility to the Long Lake drainage basin.

3

2. LITERATURE REVIEW
2.1 Introduction
Long Lake (47.02°N, 122.77°W) is the third and largest basin in a chain of four lakes
located in Lacey, Washington and provides recreational, aesthetic, and groundwater filtration
benefits to the residents throughout its drainage basin. Initially formed through glaciation, the
lakes are connected by extensive wetlands draining to Woodland Creek, one of five major
tributaries to Henderson Inlet at the southern terminus of the Puget Sound estuary (Thurston
County, 1995a). The lakes are hydraulically connected by surface and subsurface flow ways
beginning at the headwaters of Hicks Lake which flows into Pattison Lake, then to Long Lake
through a series of wetlands, and finally to Lake Lois via Woodland Creek, formed at the outlet
of Long Lake. All four lakes lie between 40 – 48 meters above sea level (United States
Geological Survey, 1989). The surface area of Long Lake is approximately 8.25 square miles
with mean and maximum depths of 3.7 meters (12 feet) and 6.4 meters (21 feet), respectively
(Thurston County Environmental Health Division, 2019).
As much of the wetland structure of this area has been replaced by fill soil displaced by
urban development, the natural ability of this chain of lakes to minimize nutrient concentrations
has been substantially altered over time (Thurston County, 1995a). Wetlands provide essential
ecosystem services to the area including the removal of sediment and pollution from surface
water, groundwater filtration, and habitat for birds, insects, and spawning salmonoids (Thurston
County, 1995a). Suspended sediment transported through the wetlands bring essential minerals
into the lake ecosystem. This sediment either settles on the lake bottom or remains suspended in
the water column, sustaining organismal growth and nutrient cycling within the lake system
(Feng et al., 2020). Anthropogenic activities can influence nutrient cycling most notably through
land-use practices. By covering landscapes with impervious surfacing or diverting and channeling
water for industrial and agricultural purposes, the natural hydrologic processes of filtration are

4

impacted. This allows associated runoff to flow directly into our waterways increasing their
overall nutrient load (Conway & Lathrop, 2005; Dodson et al., 2007). The excess nutrients
encourage plant and algal productivity which inevitably reduces clear water for drinking,
swimming, boating, and fishing.
Trophic State Indicators (TSI) identify parameters which correlate with a lake’s algal
biomass, endemic or invasive, although invasive plants are cause for concern due to their
propensity to overwhelm and dominate new territory. Invasive plant species have flourished in
Long Lake, brought unknowingly into the lake by boat recreators and thrown away haphazardly
by bygone aquarium aficionados (EnviroVision Corp., 2004). Around the basin, impervious
surfaces increase as asphalt is laid for new construction, and oak forests are replaced by
manicured lawns which likely are accompanied by the heavy use of fertilizers. Nutrients flow into
Long Lake through multiple inputs including groundwater seepage, lawn overflow, stormwater
conveyance, diffuse non-point source pollution, and from the lake’s own biotic activity. The
following sections will provide a basic overview of limnological processes needed to be
understood, which then informs future nutrient mitigation options.
2.2 Thermal Stratification of Lakes
Lake productivity is largely determined by the basin’s depth, light requirements and
nutrient supply. If the lake is deep enough, thermal stratification will occur in which distinct
layers or “strata” are formed and separated by differences in temperature. The warm upper strata
is known as the epilimnion. It is where most photosynthetic activity occurs as the surface receives
the greatest amount of solar radiation. The sun’s light may be reflected, absorbed or transmitted
through the water column based on the light’s wavelength and water clarity as suspended solids,
partially decomposed organic matter, and plankton can block the light’s path. Turbid waters, rich
in suspended clays, can prevent the sun’s radiation from reaching even a few centimeters below

5

the surface. Conversely, light traveling through clear water can penetrate meters below the
surface (Vallentyne, 1974).
The epilimnion is the warmest lake layer as it receives the most radiation from sunlight.
As a lake’s depth increases, the energy of the sun’s visible light decreases; 50% of which is
absorbed by water within the first 10 meters if unimpeded by the lake’s clarity. Light attenuation
is the gradual decrease in light intensity as it travels through matter. Light attenuation also affects
the colors that permeate water at depth with the blue range of visible light traveling the farthest
(University of Hawai’i, 2021). With diminished energy, the temperature of water decreases. As
water (H2O) molecules cool, they slow down, get slightly closer to one another and occupy a
smaller volume resulting in an increase in density (American Chemical Society, 2021).
Water is an interesting compound as it actually becomes lighter when in a solid state. As
a general rule however, the change in the density of water per degree change in temperature
increases as the temperature departs from 4 C, waters maximum density, both above and below
(Vallentyne, 1974). As such, density increases as temperature decreases below freezing.
Thus, below the epilimnion lies the colder and denser waters of the hypolimnion. As
organisms die, detritus sinks from the epilimnion to the lake bottom. Sedimentation of nutrients
occurs here, storing macronutrients (carbon, nitrogen, phosphorus, hydrogen, and sulfur) and
micronutrients (silicon, magnesium, copper, and zinc) for future use. Decomposition dominates
over photosynthesis here, consuming oxygen and releasing nutrients back into the water column
at a rate determined both by seasonality and biotic activity (Tundisi & Tundisi, 2011).
Between the epilimnion and the hypolimnion lies a zone of transition where the water’s
temperature changes rapidly. A layer is formed known as the metalimnion or thermocline which
actually creates a physical barrier between the epilimnetic and hypolimnetic strata. This occurs
due to the density gradient between strata which prevents their vertical mixing. It takes physical
work to mix layered masses of water of varying density, similar to the work it takes to mix oil and
vinegar. Additionally, the thermocline acts as a biological barrier creating niches for aquatic plant

6

and animal life based on their own requirements for life. The epilimnion provides a warmer,
more illuminated environment for many species of green plants, insects, plankton, and fish to
thrive.
Figure 1 Thermal Stratification in Lakes

Note. Typical orientation in lakes at temperate latitudes during summer months (Vallentyne,
1974).

Cold-water species prefer the hypolimnion, and still others find their requirements met in the
metalimnion. Some aquatic species may even migrate between the layers (Vallentyne, 1974).
By converting sunlight into calories of edible food through photosynthesis, autotrophs
(i.e., algae, higher plants, and some protists and bacteria) form the base of the food chain as
primary producers. The abundance and rate of production at this trophic level is the foremost
determinant of productivity at all higher levels of the food chain. In lake ecosystems, much of the
production is done by algae suspended in the water column, known collectively as phytoplankton,
and larger flora. The term “algae” is an informal term used for a very large and diverse group of
photosynthetic, mostly eukaryotic aquatic organisms. Types of phytoplankton include diatoms,
chrysophytes, cryptophytes, dinoflagellates, green algae (chlorophytes), and cyanobacteria (Allan

7

& Castillo, 2007; Schindler & Vallentyne, 2008). Many species of cyanobacteria possess gas
vacuoles which allow them to move throughout the water column as their needs require . This
includes the bacterium Microcystis aeruginosa, the most common bloom-forming and frequently
toxic cyanobacterium found in lakes (United States Environmental Protection Agency, 2021b).
By floating in the upper strata of stratified lakes, they take advantage of the euphotic zone, an
area with sufficient light for photosynthesis to occur. Cyanobacteria are then capable of “dipping”
into the hypolimnion to obtain nutrients before returning back to this zone of production
(Cottingham et al., 2015).
Other physical and chemical consequences occur in the water as a result of the thermal
stratification. In addition to biotic life, the vertical distribution of gases and nutrients may vary
throughout the column or they may become concentrated in individual strata. Strong winds and
other climactic forces may interrupt this stratification, contributing the work necessary for
mixing. When this occurs, nutrient-rich hypolimnetic waters are brought up toward the surface.
Algal blooms may be observed after strong wind activity as both benthic nutrients and organisms
are brought toward the surface and photic zone (Carrick et al., 1993). Seasonal shifts in
temperature also cause a lake to “turn-over,” redistributing nutrients at that time. This turn-over
occurs as a result of surface waters becoming colder and denser than the hypolimnion at which
point the epilimnion falls below and replaces it (Schindler & Vallentyne, 2008).
Dissolved oxygen (DO) produced by photosynthetic organisms in the epilimnion is often
transported to the hypolimnion during these seasonal and climatic events. Consequently, the
amount of oxygen available in the hypolimnion is finite and is consumed at a rate proportional to
the amount of biotic activity occurring within the strata. Once a lake turns over in the spring,
seasonal warming initiates the layered stratification that inevitably locks in dissolved oxygen
levels. Bacteria gradually deplete dissolved oxygen levels as they decompose dead plant and
animal matter falling from the epilimnion. The greater the supply of organic matter from the
epilimnion, the more rapid the oxygen depletion will be in the hypolimnion. Highly productive

8

eutrophic lakes with smaller hypolimnetic volumes can lose their dissolved oxygen in a matter of
weeks. The opposite is true of low productive oligotrophic lakes with larger hypolimnetic
volumes which can retain oxygen levels throughout the year (Schindler & Vallentyne, 2008).
Increasing temperatures and seasonal shifts occurring as a result of climate change compound this
issue.
Warming surface waters are the most direct response to global temperature increases, and
unfortunately for Long Lake, lakes located within temperate regions are the most responsive to
those changes (Piccolroaz et al., 2020). Furthermore, cyanobacteria taxa Anabaena
and Microcystis, both prevalent species in the lake, are responsive to concurrent increases in both
temperature and nutrients (Rigosi et al., 2014). Lake surface water temperature trends have been
increasing in excess of ambient air temperatures worldwide, and are projected to accelerate
(Adrian et al., 2009; O’Reilly et al., 2015; Paerl & Paul, 2011). High-latitude regions that
experience ice cover in wintertime are having shorter periods of icing or none at all. This leads to
stronger vertical temperature stratification for longer periods of time, and fish die-off events
increase due to the hypoxic water conditions (Carmichael, 1991). Alterations in top predator
populations in lakes can in turn alter the balance of productivity, predation, and energy flow
throughout the food web, a concept also known as a “trophic cascade”.
While not the subject of this thesis, exploring the cascading trophic interactions of Long
Lake may lead to a better understanding of the dominance of cyanobacteria there as well.
Zooplankton largely graze on algae, but do not graze on cyanobacteria due to their size and
toxicity (Entranco, 1994). Research has shown that in addition to the harmful effects microcystin
poses to animals and humans it can even inhibit the ingestion process by Daphnia galeata, a
typical filter-feeding grazer in eutrophic lakes (Rohrlack et al., 1999). Trophic cascade
researchers believe trophic interactions may explain the differences in productivity among lakes
with similar nutrient supplies but contrasting food webs (Carpenter et al., 1985; Ripple et al.,
2016).

9

2.3 Nutrient Cycling in Lakes
The profusion of primary producers in lakes is related to the availability of nutrients, in
particular macronutrients: phosphorus (P) and nitrogen (N). Phosphorus and nitrogen are two of
the six principal elements (hydrogen, oxygen, carbon, nitrogen, phosphorus and sulfur) that form
the backbone of life on Earth, and are also important due to their effect on eutrophication (S.R.
Carpenter et al., 1998; Dean, 1999; Pick & Lean, 2010; Vallentyne, 1974). Together, N and P
limit rates of primary production in most ecosystems on this planet including inland waters. The
ratio of algal demand relative to supply for phosphorus is, on average, higher than for other
elements found in plant tissue. Phosphorus does not have a gaseous phase so the atmosphere is
not a significant source, unlike nitrogen and carbon (Schindler & Vallentyne, 2008; Welch et al.,
2005). Human activity inhibits lake ecosystem resilience through its contribution of synthetic
fertilizers, fossil fuel emissions, and altered watersheds ultimately contributing to the flux of
nitrogen and phosphorus into aquatic ecosystems.
2.3.1 Nitrogen Cycle
Nitrogen (N) is the fourth most abundant element found in living biomass after hydrogen,
carbon, and oxygen (R. Howarth, 2009; Stein & Klotz, 2016). Due to its very active oxidationreduction cycle, nitrogen transitions between forms and is recycled within ecosystems at a higher
rate than phosphorus (R. Howarth, 2009). Aquatic organisms use N primarily to synthesize
proteins and amino acids (Tundisi & Tundisi, 2011). Nitrogen occurs in aquatic ecosystems in
both organic and inorganic forms and has multiple fates once it enters surface waters. “Reactive
N,” that which supports or are products of cellular metabolism and growth, may be permanently
removed via denitrification, stored in the sediment, or stored temporarily in biomass (Stein &
Klotz, 2016). Organic forms of N are supplied by particulate and dissolved nitrogen found in
living biomass and detritus.

10

Inorganic forms include dissolved N2 gas, oxidized ions such as nitrate (NO3-) and nitrite
(NO2- ), the reduced ammonium ion (NH4+), and the reduced ammonia gas (NH3) (Howarth,
2009). Not surprisingly, many commercial fertilizers include a combination of these forms
(Mattson et al., 2009). Additionally, household sewage contributes forms of inorganic N to
waterways via sewage treatment effluent and leaking septic tanks. Even functioning systems
contribute nitrogen to groundwater. They are generally considered nonpoint source pollution
unless the effluent reaches stormwater infrastructure that is covered by a general permit
(Washington State Department of Ecology, 2015). In 2015, the City of Lacey reported a moderate
to high level of nutrient, pathogen, and toxin delivery as a result of urban land uses including
septic tanks, fertilization, and impervious surfaces (City of Lacey, 2015). The latter is
consistently a topic of discussion for the Long Lake community and is brought up in their
monthly newsletters with LLMD members urging their neighbors to stay on top of septic
maintenance (Lake Management District #21, 2017; Long Lake Management District #21, 2019).
The most common forms of N taken up by algae, rooted plants, fungi and bacteria are
ammonium (NH4+), nitrate (NO3- ), nitrite (NO2- ), and urea ((NH2)2CO) with nitrate and nitrite
being most available in freshwater (Howarth, 2009; Stein & Klotz, 2016; Tundisi & Tundisi,
2011). Ammonium, whether taken up directly, hydrolyzed (chemically broken down by its
reaction with water), or reductively assimilated in the organism, is used to produce organic
nitrogen compounds. Nitrogen flows throughout the food web through predation and
decomposition and is mineralized by its conversion from organic to inorganic forms (Howarth,
2009). Bacteria play a pivotal role in the conversion of nitrogen in aquatic ecosystems and are
labeled by their participation in the cycle (e.g., “nitrifiers,” “denitrifiers,” and “nitrogen fixers”).

11

Figure 2 Nitrogen Cycle

Note. A simplified diagram of the nitrogen cycle in aquatic ecosystems (RW Howarth, 2002).
Nitrogen fixation is the process by which atmospheric N2 is converted to NH4+. Nitrogen
gas (𝑁2 ) constitutes approximately 78% of the gaseous composition of our earth’s atmosphere
(Wallace & Hobbs, 2006), although only organisms that can fix N in its gaseous form are able to
benefit from its abundance. As nitrogen is evident in the composition of most life on Earth,
“nitrogen fixers” are essential for its provision in biologically available forms. Cyanobacteria are
well adapted for this uptake as many cyanobacterial strains, both with and without a heterocyst - a
specialized nitrogen-fixing cell, are capable of nitrogenase activity. Additionally, these bacterium
contain protein polymers, cyanophycin and phycocyanin, endowing them with the ability to store
nitrogen (Watzer & Forchhammer, 2018; B.A. Whitton & Carr, 1982). Interestingly enough,
phycocyanin is the blue pigment-protein also responsible for cyanobacteria’s earlier classification
as a “blue-green algae” (Brian A. Whitton & Potts, 2000).
Nitrogen fixation used to be exclusive to heterotrophic bacteria, cyanobacteria and
archaea until the early 20th century. It was during this time that the Haber-Bosch process was

12

invented and allowed for the industrial conversion of N2 to ammonia, NH3 (Gold et al., 2019;
Stein & Klotz, 2016). The advent of the Haber-Bosch process is a double-edged sword as
nitrogen has become both more plentiful and toxic. Atmospheric nitrogen converted to nitrogenbased fertilizers has enabled agricultural practices to expand to industrial levels of production as
well. The resulting fertilizer runoff has had disastrous effects downstream and will be discussed
later in this thesis.
Nitrification is the process by which bacteria sequentially oxidize ammonia into nitrite
(1), then nitrite to nitrate (2) (American Water Works Association & Economic and Engineering
Services, 2002):
(1) NH3 + O2 → NO2 - + 3H+ + 2e(2) NO2- + H2O → NO3 - + 2H+ +2e-

There are two primary genera of autotrophic bacteria, Nitrosomonas and Nitrobacter, that
preform nitrification, although other autotrophic and heterotrophic bacteria as well as some fungi
can carry out this process also (American Water Works Association & Economic and
Engineering Services, 2002). Nitrification provides the energy necessary for chemosynthesis, a
process in which carbon dioxide is fixed to produce biomass. The growth of nitrifying bacteria is
relatively slow compared with other chemosynthetic processes (e.g., oxidizing sulfur or iron
compounds), and in combination with their predation by other trophic grazers, can result in a
slower population growth rate (R. Howarth, 2009). Due to their slow growth rate, ammonia is
allowed to accumulate and is made available for use by other organisms. Nitrifiers are obligate
aerobes and require oxygen for the denitrification process to occur. As dissolved oxygen levels
drop, denitrification is made possible (Tundisi & Tundisi, 2011).
Denitrification is the process by which nitrite and nitrate are reduced to the inert gas, N2.
This process requires adequate carbon and nitrate sources, the latter produced primarily in lake
sediments through the nitrification of ammonium. However, nitrate may also be diffused through

13

the overlying water (Eyre et al., 2013; Seitzinger et al., 2006). Denitrification is catalyzed by
heterotrophic bacteria which decompose detritus, and use nitrogen as an electron acceptor much
like organisms use oxygen as an electron acceptor to perform respiration (Stein & Klotz, 2016).
This typically occurs in oxygen reduced or anoxic environments as is frequently the case in
aquatic sediments and stratified lakes (R. Howarth, 2009; Illinois State Environmental Protection
Agency, n.d.). Denitrification provides a mechanism by which nitrogen can be reduced and
released back into the atmosphere with lakes and reservoirs accounting for 33% of the total global
nitrogen removal (Harrison et al., 2009).
Denitrification can be expressed as a redox reaction (1; Boundless, 2021):
(1) 2 NO32− + 10 e− + 12 H+ → N2 + 6 H2O
Additionally, the bacterium Thiobacillus denitrificans is an example of a denitrifying organism.
Widely distributed in soil and aquatic environments, T.denitrificans also links the geochemical
cycles of sulfur and nitrogen (Tundisi & Tundisi, 2011):
(2) 5 S + 6 NO3 + 2 H2O → 5 SO4 + 3 N2 + 4 H + energy
Denitrification and nitrogen fixation perform an essential role together in that these
processes regulate the balance of nitrogen within aquatic ecosystems. While nitrogen fixation
makes nitrogen available to the aquatic environment, denitrification releases nitrogen back into
the atmosphere from laden benthic sediments and anoxic lake strata, acting as a control on system
level primary productivity (Eyre et al., 2013). In general, the rate of nitrogen removal has been
observed to correlate positively with the rate of nitrogen loading, water residence time, and
negatively correlated with lake mean depth (Kelly et al., 1987; Saunders & Kalff, 2001).
The samples collected for this study were analyzed for their concentrations of total
nitrogen (TN) utilizing the kjeldahl 4500-N (organic) C method. This method determines nitrogen
in the tri-negative state. It fails to account for nitrogen in the form of azide, azine, azo, hydrazone,
nitrate, nitrite, nitrile, nitro, nitroso, oxime, and semi-carbazone. "Kjeldahl nitrogen" is the sum of
organic nitrogen and ammonia nitrogen (Baird & Eaton, 2017).

14

2.3.2 Phosphorus Cycle
As the 12th most abundant element in the Earth’s crust, phosphorus is widely distributed
throughout the globe. Phosphorus is essential for the growth and maintenance of living
organisms, and is a component of nucleic acids, adenosine triphosphate (ATP), and phospholipids
(Tundisi & Tundisi, 2011). Phosphorus is highly reactive and as such does not occur as a free
element on Earth. This means that it is regularly bonded with other elements as phosphates
(PO43-) (Déry & Anderson, 2007). The most common forms of organic phosphorus are biological
in origin, although dissolved phosphates are also delivered through the weathering of rock
phosphate. While phosphorus moves quickly through plants and animals, the phosphorus cycle is
one of the slowest biogeochemical cycles on Earth. Phosphorus moves slowly through the soil
and ocean until it reaches both its beginning and end in the subduction zones of the Earth’s crust
(Turner et al., 2005).
In natural waters, phosphorus is categorized into three component parts: soluble reactive
phosphorus (SRP), soluble unreactive or soluble organic phosphorus (SUP), and particulate
phosphorus (PP) (Rigler, 1973). SRP consists of the soluble inorganic orthophosphate (PO4)
which is the primary source of phosphate for aquatic plants and phytoplankton (Carlson &
Simpson, 1996; Tundisi & Tundisi, 2011). For this reason, SRP is one of the phosphorus tests
being analyzed in this study. The concentration of SRP would be indicative of the amount of P
immediately available for algal uptake. The difference between TP and SRP is the measurement
of orthophosphate pre- and post- filtering as TP includes P attached to particulate matter and SRP
measures solely dissolved P.
The accumulation of phosphorus in lake sediments is an important component of the
phosphorus cycle. Phosphorus is often attached to sediment particles which leads to its
accumulation through sedimentation, forming an important nutrient reservoir (Tundisi & Tundisi,
2011; Wetzel, 2001). During oxic periods within the hypolimnion, phosphorus undergoes a
complexation process and is bound to metal ions making it biologically unavailable (Tundisi &

15

Tundisi, 2011). However, as the hypolimnion loses oxygen to biological processes (i.e.,
decomposition and productivity) and becomes anoxic, phosphorus is released from the sediment
into the lake’s water column causing further eutrophication (Niirnberg, 1994; Song et al., 2017;
Spears et al., 2007; Yuan et al., 2019).
The condition of phosphate release is widely accepted, yet still not precisely understood.
Under certain conditions, phosphates are retained in lake sediments due to a micro-layer of ferric
acid [FeO(OH)] at the sediment-water interface which absorbs phosphorus in oxic conditions.
However, under anoxic conditions, this micro-layer loses its ability to absorb phosphorus and
both elements are released to the water column (Mortimer, 1941). While this is a widely accepted
theory for phosphate release from sediments, others oppose the simplicity of this explanation and
its universal application (Golterman, 2001; Hupfer & Lewandowski, 2008). They insist that it is
not merely the lack of oxygen that allows for the dissolution of phosphates into the water column,
rather a combination of dynamic factors contribute to its release.
Biotic respiration and bacterial decomposition in lakes releases carbon dioxide into the
water column. The release of carbon dioxide (CO2) often occurs concomitantly with acidification
as CO2 trapped in the hypolimnion will lower the water’s pH. Researchers suggests the
solubilization of apatite, a phosphate loaded mineral, would occur in such conditions leaching
minerals into the water column (Golterman, 2001). Microbial activity by sediment bacteria
(Kleeberg & Dudel, 1997) and other redox conditions (e.g., dissolution of calcium-bound P)
could also contribute to the internal phosphorus loading mechanisms within a lake (Hupfer &
Lewandowski, 2008). These hypotheses posit the need for greater study on phosphorus release
mechanisms rather than relying solely on measuring a lakes anoxic factor. It is possible that this
simplification is affecting modeling capabilities which will have far-reaching consequences on
lake management.
Macroscopic animals (e.g., fish, insects) play major roles in nutrient cycling within lakes.
Sediment disturbance by benthic dwelling animals resuspends sedimented phosphorus into the

16

water column. Their excretion and the decay of their carcasses remineralize significant quantities
of nutrients that then become available for algal uptake (Welch et al., 2005). The common carp,
Cyprinus carpio, a non-native bottom-feeder, was found to release phosphorus at rates similar to
external loading of phosphorus into a series of Minnesotan ponds (Lamarra, 1975). Figure 3
depicts many aspects of the phosphorus cycle described courtesy of the Lake Simcoe Region
Conservation Authority.
Figure 3 Phosphorus Cycle in Lakes

Note. A simplified diagram of the phosphorus cycle in lakes (Phosphorus Cycle, 2016).
2.3.3 Hydraulic Residence Time
The amount of time it takes for all water to flow through a lake system completely is
known as its hydraulic residence time (HRT). The HRT includes all water flowing into the lake
from river, groundwater, and rainfall inputs which takes approximately two years to occur for
Long Lake (P. Cracknell, personal communication, 2021). The HRT:

17

…affects the chemical composition of lake waters by controlling the time available for
biogeochemical and photochemical processes to operate, the extent of accumulation, loss
of dissolved and particulate materials and the duration of biogeochemical interactions
with the lake sediments and littoral zone. (Bhateria & Jain, 2016).
Shifts in precipitation and evaporation alter a lake’s water budget and HRT, and shallow lakes
can be severely affected by changes in climate due to their large surface area to volume ratios
(Adrian et al., 2009; Bhateria & Jain, 2016; Zhang et al., 2016). A prolonged residence time
caused by reduced precipitation and inflows could result in amplified phosphorus accumulation
and eutrophication. In lakes that experience anoxic hypolimnetic conditions, nutrients released
from benthic sediments leads to increased internal phosphorus loading (Bhateria & Jain, 2016).
On the other hand, an increase in precipitation might decrease a lake’s HRT but the precipitation
might also bring with it more frequent concentrations of nutrients through stormwater (Wu &
Malmström, 2015).
The samples collected for this study were analyzed for total phosphorus (TP) which
includes orthophosphate, condensed phosphate, and organic phosphate. Additionally, samples
were analyzed for their concentrations of soluble reactive phosphorus (SRP), the most
biologically available form of phosphorus.
2.4 Trophic State Indicators
Long Lake is considered to be a eutrophic lake based on the Trophic State
Indicators/Index (TSI) utilized by lake managers and limnologists (Bell-McKinnon, 2010;
Butkus, 2004). The TSI, as developed by Robert Carlson, use algal biomass as the basis of a
waterbody’s trophic state classification, and notes Secchi depth/transparency (SD), chlorophyll-a
(Chl), total nitrogen (TN) and/or total phosphorus (TP) considerations. While this is a rough
estimate of the trophic condition of a waterbody, water quality managers can assess the trophic
state based on: changes in nutrient levels (measured by total phosphorus and total nitrogen) that

18

may cause changes in algal biomass (measured by chlorophyll-a) which in turn can result in
changes in lake clarity (measured by Secchi disk transparency) (Pavluk & De Vaate, 2018).
Table 1 Classes of TSI values and their ecological attributes.

Adapted from Carlson, R.E., Simpson, J., 1996. A coordinator's guide to volunteer lake
monitoring methods. USA: North American Lake Management Society Madison (Pavluk & De
Vaate, 2018)
TSI can be formulated based on the above influencing factors and are presented below (Pavluk &
De Vaate, 2018):
TSI (SD) = 60 – 14.41 ln Secchi disk depth (meters)
TSI (Chl) = 9.81 ln chlorophyll-a (g/L) + 30.6
TSI (TP) = 14.42 ln total phosphorus (g/L) + 4.15
Each of these values can be used to classify a waterbody as they are interrelated by linear
regression. If the TSI values are not similar, it may suggest that algal growth is limited by
something else including light or other necessary elements. Secchi transparency can be affected
also by variables other than algae such as erosional silt or construction runoff (Pavluk & De
Vaate, 2018). Because the nutrients nitrogen and phosphorus were described in depth earlier, the
following sections will describe only the Secchi disk and chlorophyll-a measurements.

2.4.1 Secchi Disk
The Secchi disk, named for papal scientific advisor Pietro Angelo Secchi, has been
employed since the 19th century to measure the transparency of the water. While developed for
use primarily in lakes, the Secchi disk can be used in riverine and marine environments. The
information provided by Secchi readings can be discounted based on the subjective nature of

19

observer measurements. However, the Secchi disk is easy to use and provides useful information
to those engaged in water quality studies (Carlson & Simpson, 1996). The Secchi disk is a
contrast instrument. As the disk is lowered into the water, an observer watches to discern at what
depth the disk disappears behind the ambient background.
Figure 4 Secchi Disk

Note. Photo courtesy of NASA Earth Observatory (Plumbing the Depths, 2002)
This contrast relationship is represented by the simplified equation (Carlson & Simpson, 1996):
𝐶𝑜𝑛𝑡𝑟𝑎𝑠𝑡 =

𝑂𝑏𝑗𝑒𝑐𝑡 𝑙𝑢𝑚𝑖𝑛𝑎𝑛𝑐𝑒 – 𝐵𝑎𝑐𝑘𝑔𝑟𝑜𝑢𝑛𝑑 𝑙𝑢𝑚𝑖𝑛𝑎𝑛𝑐𝑒
𝐵𝑎𝑐𝑘𝑔𝑟𝑜𝑢𝑛𝑑 𝑙𝑢𝑚𝑖𝑛𝑎𝑛𝑐𝑒

And based on the theoretical equation by (Preisendorfer & Duntly, 1952):
𝐶𝑅 = 𝐶𝑂 𝑒 −(−𝐾)𝑧
𝐶𝑅 is the apparent contrast; 𝐶𝑂 , the inherent contrast; z, the depth of disk disappearance (Secchi
depth); , the beam attenuation coefficient; and K, the vertical attenuation coefficient.

This equation can be rearranged to examine the factors affecting the depth at which the Secchi
disk disappears (ZSD):

𝑍𝑆𝐷 =

𝐶
ln (𝐶𝑂 )
𝑅

( + K)

The depth of disappearance will depend on the contrast of the disk relative to the background. In
theory, the Secchi disk should disappear into a light consuming black background. This type of
background might exist in the open ocean but is not typical of lakes as they are often filled with

20

suspended silts and clays. Measuring Secchi depth is a subjective art and limited to the sensitivity
of the human eye itself (Carlson & Simpson, 1996).

2.4.2 Chlorophyll-a
Chlorophyll-a is the principal pigment that captures light for photosynthesis within the
chloroplast. Absorbing light in the 429 (violet-blue) and 659 (orange-red) nanometer range,
chlorophyll-a reflects blue-green in color and is present in all plants, algae, and cyanobacteria
(Panawala, 2017). Chlorophyll-a is used to measure photosynthetic activity and algal biomass in
lakes. There are several ways to measure chlorophyll-a including: water sampling, filtration, and
analysis using electromagnetic spectroscopy methods in the laboratory, and/or satellite photos can
be referenced to measure the intensity of colors in the area of interest (United States
Environmental Protection Agency, 2021a).
2.5 Impacts of Land-use on Nutrient Cycling in Urbanized Eutrophic Lakes
In natural conditions, those unaffected by anthropogenic pressures, ammonium can be
relatively low in the lake’s epilimnion. The process of nutrient enrichment is known as
eutrophication, and often parallels the senescence of a lake waterbody. Over time, a lake’s
trophic state transitions from clear “young” waters, relatively devoid of nutrients, to waterbodies
less clear and filled with biotic activity. Eventually, the lake becomes shallower, filling in with
sediment and detritus from decomposing plant matter (Tundisi & Tundisi, 2011). This transition,
commonly known as succession, occurs over the course of centuries, if not millennia (BellMcKinnon, 2010). However, human activities accelerate eutrophication, henceforth known as
cultural eutrophication, through increased nutrient loading. Inputs may include nitrogen,
phosphorus and other pollutants via wastewater discharges, septic systems, construction,
agricultural runoff, and stormwater.

21

Cultural eutrophication is a common and growing problem in lakes. In 1998, 45% of
lakes in the United States were impaired by eutrophic conditions and considered not clean enough
to support fishing or swimming (United States Environmental Protection Agency, 1998). In 2004,
64% of lakes were impacted (United States Environmental Protection Agency, 2004). As of 2012,
national lake conditions have worsened in regard to: cyanobacteria density, microcystin
concentrations, and biological condition (i.e., degraded benthic macroinvertebrate communities).
The National Lakes Assessment determined that one in three lakes (35%) have excess nitrogen
and two out of five lakes (40%) have excess phosphorus. Lakes with high levels of phosphorus
are 2.2 times as likely to have degraded benthic macroinvertebrate communities, and 1.6 times as
likely when in excess of nitrogen (United States Environmental Protection Agency, 2012).
Eutrophic conditions can remain stable due to several mechanisms at play within them
including: the internal loading and recycling of phosphorus, the loss of rooted macrophytes which
results in the destabilization and resuspension of nutrient laden sediments, and changes in the
food web that reduce grazing of nuisance algae (Stephen R. Carpenter & Cottingham, 1997).
Eutrophication is a factor in the loss of aquatic biodiversity (Seehausen et al., 1997), and the toxic
cyanobacterial blooms that flourish in such ecosystems contribute to a wide range of water related
issues. CyanoHABs contribute to summer fish kills (Carmichael, 1991), foul odors (Paerl et al.,
1985), unpalatable drinking water (Hardy et al., 2015; Li et al., 2011; Weirich & Miller, 2014),
and the formation of trihalomethane, a known carcinogen, when cyanobacteria are treated with
chlorine in water treatment facilities (Palmstrom et al., 2009).
Agricultural practices are infamous for their excessive nutrient runoff leading to such
events as the record-setting algal bloom on Lake Erie, Michigan in 2011, three times greater than
ever recorded (Michalak et al., 2013). Land-use practices are significant drivers of ecosystem
imbalances due to alteration of the natural landscape and connected hydrology, disrupting water
flow and overloading nutrient budgets in surface waters (Dodson et al., 2007; Mohamedali et al.,
2011; O’Driscoll et al., 2010). Land-use practices that replace vegetation and soil with

22

impervious surfaces are often associated with degraded water quality due to stormwater runoff
(McGrane, 2016). Impervious surfaces allow water to flow overland picking up a slurry of
contaminants including sediment, chemicals and bacteria. Stormwater is then transported to our
waterways via storm drains and treatment structures (e.g., ponds, swales, waste effluent), and
eventually discharged to lakes, groundwater, streams, rivers, and estuaries (Fig.4) (Yang & Lusk,
2018).
Figure 5 Overview of pathways and sources of nutrients in urban environment.

Note. “(A) Urban stormwater runoff is generated when precipitation from rain/snowmelt events
over impervious surfaces. (B) Runoff water then makes its way into storm drains and discharges
into streams, rivers, and estuaries untreated. (C) Excessive amounts of nutrients in water bodies
can cause eutrophication, often leading to fish kills. The potential nutrient sources in urban
stormwater runoff include (1) atmospheric deposition, (2) pet waste, (3) improperly functioning
septic systems, (4) landscape irrigation, (5) use of chemical fertilizers on lawns, (6) soil and
decomposition plant materials, (7) leaking sanitary sewers, and (8) microbial sources” (Yang &
Lusk, 2018).
The degree to which an area is covered by impervious surfaces can determine the health
and function of associated waterways. In 1994, the Impervious Cover Model (ICM) was
developed to predict the behavior of urban stream indicators based on the percent impervious
cover in their contributing subwatershed. A subwatershed being defined as an area of land that

23

water passes through before draining into a larger body of water. The researchers’ hypothesis was
that increasing the amount of impervious surface will degrade stream quality along a reasonably
predictable gradient. Schueler (2009) followed up on their model by conducting a meta-analysis
of 61 research studies which employed the ICM and found that the majority of studies either
confirmed or reinforced the ICM hypothesis. It was concluded that stream health became severely
impacted once the subwatershed became 10% covered with impervious surfaces (Fig. 5).
Figure 6 Impervious Cover Model.

Note. Courtesy of Schueler et al., 2009.

The model was updated in 2012 to make it more accessible to watershed planners, stormwater
engineers, water quality regulators, economists, and policy makers. The improvement came with
the implication that managers should test their ability to apply a multiple management strategy
toward improving the gradient of stream degradation rather than reinforcing it (Schueler et al.,
2009).
2.6 Urban Stormwater Pollution

24

Nonpoint source pollution is undoubtedly a major contributor of pollutants to aquatic
ecosystems (Abrams & Jarrell, 1995; Mohamedali et al., 2011; Washington State Department of
Ecology, 2012; Welch & Jacoby, 2001). As one type of diffuse pollution, stormwater is capable
of amassing pollutants at the catchment scale and has a very significant effect on receiving waters
(Kim et al., 2007; Scottish Environment Protection Agency (SEPA), 2021). At a micro level,
pollutants can be relatively innocuous individually, but their collection over a larger area
concentrates their potency. As the name suggests, treating nonpoint source pollution is made
more complicated due to the inability to directly identify its source.
Depending on the area, stormwater effluent may contain petroleum products, agricultural
residues, organic matter, nutrients and anything else in its path (Burton & Pitt, 2001; Lee & Bang,
2000; O’Driscoll et al., 2010; Walsh et al., 2005; Washington Department of Ecology, 2010).
Several stormwater models have attributed higher magnitudes of pollutant loading to the amount
of impervious cover within a studied watershed (Lee & Bang, 2000; Schueler et al., 2009). Lee
and Bang (2000) characterized stormwater loading in nine urban watersheds and found that both
particulate and dissolved nutrient concentrations were highest in residential watersheds. Higher
concentrations of pollutants in areas with reduced impervious cover exceeded areas with more
impervious cover only when combined sewer systems (CSOs), which collect rainwater runoff,
domestic sewage, and industrial wastewater in the same pipe, were present. Although heavy
metals were in higher concentrations most often in industrial areas, this research suggests that the
relative ease of transport (impervious cover) and proximity to human developments largely
determines the concentration of pollutants downstream. It was recently discovered by University
of Washington researchers that a highly ubiquitous chemical component of tire rubber [N-(1,3dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD)] was the cause of regular acute Coho
salmon mortality events. These events were tied specifically to their return to streams within
urban and suburban areas of the Pacific Northwest. Analysis of roadway runoff and stormwater-

25

affected creeks in these areas determined a widespread occurrence of the toxic 6PPD quinone
transformation (Tian et al., 2021).
It is widely accepted that diffuse pollution has pervasive effects on the environments
receiving its effluent (Lusk et al., 2020; T. L. C. Moore et al., 2011; O’Driscoll et al., 2010;
Rodríguez-Rojas et al., 2018; United States Environmental Protection Agency, 2020a). Many
argue that it is resulting in the eutrophication of lakes, a status that remains relatively stable,
unless active intervention is taken (S.R. Carpenter et al., 1998; Paerl, 2017; Silva et al., 2019;
Smith et al., 2020; Wium-Andersen et al., 2013; Wu & Malmström, 2015). Researchers within
the field of civil engineering are even pressing the necessity and capability of Life Cycle
Assessments (LCA), models that estimate the environmental impacts associated with all stages of
a products life (i.e., raw material extraction, material processing, manufacture, distribution, and
use), to include stormwater impacts (Phillips et al., 2018). Similar to the LCA’s ability to quantify
the impact land-use has on soil erosion, urban stormwater pollution can also become a
quantifiable unit to predict and mitigate. The LCA model Phillips et al. (2018) produced
demonstrated the influence pollutants in urban stormwater has throughout human, freshwater,
marine, and terrestrial ecosystems. Their results determined that “urban stormwater pollution has
the highest relative contribution to the eutrophication potentials” (Phillips et al., 2018).
2.7 Stormwater Management
Since the Clean Water Act (CWA) of 1970, the United States has made a concerted effort
to “restore and maintain the chemical, physical, and biological integrity of the Nation’s
waterways” (Federal Water Pollution Control Act, 2002). Remediation of point sources of
pollution has been relatively successful considering that today U.S. states recognize non-point
pollution to be the leading remaining sources of water pollution (US Environmental Protection
Agency, n.d.). Management of these pollutants is an evolving field of possibilities. Currently,
stormwater discharges are authorized under the CWA and regulated by the EPA through a

26

permitting system known as the National Pollutant Discharge Elimination System (NPDES). The
NPDES permit program authorizes states to regulate stormwater discharge in compliance with
total maximum daily load (TMDL) parameters based on water quality standards determined by
the state. NPDES permits allow monitored quantities of stormwater to be discharged to the
municipal storm sewer system (MS4) or discharged into the ‘waters of the state.’
Even though the City of Lacey was not incorporated until 1966, New American settlers
have altered the landscape since the 1840s. Farming, logging, and housing development has
altered the Henderson Inlet watershed to the point that migrating salmon can no longer return to
these natal waterways. Even after the passage of the CWA, wetlands continued to be filled to
make way for new construction (Thurston County, 1995b). The Shoreline Management Act
passed close behind the CWA (1971) and is another statute implemented for the protection of
Washington state shorelines from further development. County designed Shoreline Master
Programs are regularly updated to help rein in urban development and in tandem with municipal
Stormwater Design Manuals (SDM) can help mitigate future impacts.
The City of Lacey Department of Public Works updates their SDM with improved
management practices based on the best available science. The department manages stormwater
conveyance and discharges throughout the city, and under their jurisdiction, stormwater
catchments, drains, and outfalls are designed for allowable quantities of stormwater to enter local
waterways. Yet improvements to stormwater conveyance, retention, and treatment apply
primarily to new development which has the opportunity to incorporate such changes.
Long Lake is protected for multiple designated uses under Washington’s Water Quality
Standards for Surface Waters (WAC 173-201A-600, 1992) including for the protection of
wildlife habitat, boating, and aesthetic values. Equally important to consider are the groundwater
contributions the chain of lakes provide to the critical aquifer recharge areas surrounding them.
Long Lake dominates the maps of the wellhead protection and critical aquifer recharge areas (Fig.
7 & 8). These critical sites are essential for the replenishment of local drinking water. The water

27

flowing through these basins seeps into the groundwater table where it is eventually extracted for
drinking water from the nearby McCallister Park Well (Kevin Hansen, Thurston County
Hydrologist, personal communication, November 5, 2020).
On the Wellhead Protection Areas map (Fig. 7), the colors represent the area that could
drain through the soil underground to a water source well during the time interval. For example,
the purple area around a well is the area where a contaminant could reach the well within a 6month time interval. The wells are generally at several hundred feet depth below the ground
surface, so the travel time is downward as well as laterally through the soil and rock. The Critical
Aquifer Recharge Areas (Fig.8) are in different categories based on how permeable the soils
are. Soils that drain quickest and provide the least amount of natural protection for aquifers are
Category I, which would require the highest level of stormwater runoff treatment and protection
from contamination (Doug Christenson, City of Lacey Water Resources Engineer, personal
communication, March 31, 2021).

28

Figure 7 Wellhead Protection Areas within the City of Lacey.

Note. Map courtesy of the City of Lacey’s Stormwater Design Manual (City of
Lacey Department of Public Works, 2016).

29

Figure 8 Critical Aquifer Recharge Areas within the City of Lacey.

Note. Map courtesy of the City of Lacey’s Stormwater Design Manual (City of Lacey Department
of Public Works, 2016).

30

As will be discussed later in this thesis, the research on the residual effects of
cyanoHABs to groundwater is lacking. However, there is research to support the need for focused
attention and decisive action to curb the overwhelming presence of cyanoHABs throughout
freshwater systems. In the following section, a brief overview of some stormwater management
practices will be presented.
2.8 Stormwater Mitigation
Stormwater control measures (SCMs) take many forms including but not limited to
stormwater treatment ponds, bioretention cells (“rain gardens”), permeable pavers, vegetated
buffer strips, natural riparian buffer zones, and wetlands. Stormwater channeled to SCMs can
mitigate the negative impacts of pollutants on receiving waters by detaining water, allowing
particle sedimentation, and increasing soil infiltration capacity (Welch et al., 2005; WiumAndersen et al., 2013; Yang & Lusk, 2018). SCM treatment efficacy varies due to the variable
amount of pollutant loading, flow volume, site location, and climate all of which make it difficult
to compare treatments. Nonetheless, SCMs should be considered when designing water quality
management programs as the removal of nitrogen and phosphorus does occur within these
systems, and sometimes to great effect.
In the research study of riparian buffers conducted by Polyakov et al. (2005) they found
phosphorus removal rates as high as 93% although more often within 60-90%. Removal rates
were closely associated with the retention time of P in the SCM and sediment particle size. The
removal mechanisms largely depended on the form of P entering the buffer with soluble P being
most available for plant uptake. Buffers were assessed to be most effective at trapping sediment
bound P with soluble P passing through over time. Riparian zones are effective at removing
nitrogen from shallow subsurface water and most effective when groundwater has increased
interaction with vegetation. Another study found these areas reduced nitrogen in groundwater by
95% with 65-75% attributed to denitrification (Polyakov et al., 2005). The variability of riparian

31

buffer efficacy was reiterated in Yang & Lusk’s (2018) study as well as the recommendation that
further study on the types of plants most suitable for long term nutrient sequestration and removal
be conducted (Yang & Lusk, 2018).
Stormwater ponds (dry and wet) were found to reduce total nitrogen by 27±23 and
40±31% respectively and phosphorus by 19 – 50% when studied in wet ponds in Bellevue,
Washington (Comings et al., 2000). As a result of their higher residence times, wet ponds were
credited with a higher N and P removal capacity. This allowed for sediment-bound P time to
settle and interact with anaerobic zones promoting denitrification of N and stabilization of P and
an overall improved performance (Bettez & Groffman, 2012; Comings et al., 2000). In the study
conducted by Bettez & Groffman (2012) near Baltimore, Maryland, they found that the
denitrification potential of SCMs were comparable if not higher in some cases than natural
riparian zones in this urbanized area. They deduced that the higher rate of denitrification [1.2 mg
N kg-1 hr -1 (SCM) to 0.4 mg N kg-1 hr -1 (natural buffer)] was likely due to the interaction
opportunity nutrient-laden stormwater had with denitrifying sediments as they were engineered to
reduce flow of peak stormwater discharge (Bettez & Groffman, 2012). While wet ponds are a
form of nutrient mitigation, they can succumb to eutrophication at higher rates due to the high
nutrient input to pond volume, age, and the lack of biodiversity within them (Dodson et al., 2007;
Wium-Andersen et al., 2013). Song et al., (2017) found stormwater ponds to be unsatisfactory
phosphorus retainers as minerals were resuspended back into the water column following
sedimentation due to the high rate of decomposition occurring within these ecosystems. Even so,
the use of stormwater retention ponds is increasing as individual states continue to construct them
in relation to an increase in urban development (Siewicki et al., 2007).

Whether or not cyanoHABs will occur as a direct result of this year’s stormwater
contribution waits to be seen, knowing full well that stormwater is not the only contributing
source of nutrients to this system. Phosphorus stored in the benthic sediment is the supply of

32

nearly half the amount of phosphorus loading to Long Lake (Entranco, 1994; EnviroVision Corp.,
2004). Even if all phosphorus inputs were to completely stop today, the amount of phosphorus
stored in the sediment may be enough to fuel cyanoHABs for decades (Lathrop et al., 1998).
Nevertheless, the County and LLMD should be aware of all inputs which may be contributing to
these blooms as well as where to direct mitigation efforts.
2.9 Public Health Risks Associated with CyanoHAB Exposure
Analogous to the flaming Cuyahoga River of 1969, harmful algal blooms (HABs) may
well prove to be as fiery an indicator of the cumulative impacts of humans on freshwater
ecosystems (A. W. Griffith & Gobler, 2020; Hallegraeff, 2010). The United States responded to
the challenge of industrial waste disposal in public waterways by restructuring the Federal Water
Pollution Control Act (1948) into what is recognized today as the Clean Water Act (1972). The
Clean Water Act regulates pollution control programs and allows for controlled amounts of
polluting effluent to be discharged based on permitted allowances (United States Environmental
Protection Agency, 2020b). Such allowances are set by researched parameters for water quality
safety. When such standards do not exist, the phrase “free from toxic substances in toxic
amounts” may be used as an equivalent directive. Nonetheless, the water quality criteria by which
U.S. states and tribes protect aquatic life or human health do not exist for algal toxins, those
which are produced by harmful algal blooms (United States Environmental Protection Agency,
2020c).
Researchers argue that without increased assessment and monitoring of algal toxins, the
appropriate safety standards regarding cyanoHAB exposure cannot be determined (Hudnell,
2009; Weirich & Miller, 2014). Methodologies for addressing cyanoHABs vary across state, tribe
or territory although many do not have formal algal toxin management programs for surface
waters (Brooks et al., 2016). HABs may even be the greatest threat to inland water quality due to
the magnitude, frequency, and duration of the blooms (Brooks et al., 2016). Moreover, greater

33

risk may be attributed to unclear safety risks associated with various levels of exposure to
cyanotoxins (Hudnell, 2009; Weirich & Miller, 2014). Cyanotoxins are not present in every algal
bloom, however it is theorized that cyanobacteria produce these non-essential secondary
metabolites to provide some benefit to the organism (Carmichael, 1991; Dziallas & Grossart,
2011; Percival et al., 2014; Rohrlack et al., 1999).
2.12 Summary
The purpose of this literature review was to familiarize the reader with some basic
concepts of limnology that are important for lake management. Additionally, specific attention to
the impact land-use, impervious cover, and the subsequent stormwater runoff have on lake
ecosystems was presented as well as their influence on cyanoHAB occurrence. The adaptive
qualities and toxic possibilities of cyanobacteria dominance were presented to demonstrate the
need for equally adaptive human management. Overall, lake productivity is largely determined by
its basin size, light availability, and its aquatic plant community. A lake’s resilience and ability to
remain balanced depends on limiting nutrient concentrations within its water column. Long Lake
has required adaptive management methods to make improvements to its water quality, and the
community remains committed to identifying best management practices as exemplified by this
investigative study.

34

3. METHODS
3.1 Introduction
Located within the Lacey (Washington) city limits, Long Lake is a part of the Henderson
Inlet watershed. Long Lake consists of two basins which together measure 8.25 square miles. The
mean depth of the lake is 3.7 meters (12 feet) with a maximum depth of 6.4 meters (21 feet). The
volume of the lake is ≈ 4,810,600 cubic meters and 3,900 acre-feet, qualifying Long Lake as a
shoreline of statewide significance (lakes or reservoirs covering at least 1,000 surface acres)
under the Shoreline Management Act of 1971 (RCW 90.58). The land around Long Lake is
primarily used for residential property with a small percentage remaining forested or in use for
agricultural purposes. The shoreline is heavily developed with dense residential property. The
lake itself is primarily used for fishing, swimming, boating, and other water sports. Overall, the
general topography of the lake is flat with extensive wetlands between the chain of lakes
(Thurston County Environmental Health Division, 2019).
Long Lake is the third in a chain of four lakes that largely comprise the Woodland Creek
basin. The headwaters of this basin begin at Hicks Lake where water enters the system through
groundwater seepage and surface flow. It is eventually discharged into Pattison Lake through a
38-acre palustrine wetland located at the southwest border of Hicks Lake. Pattison Lake flows
into Long Lake through a 119-acre palustrine wetland located between them. While this wetland
floods seasonally and connects the two lakes during flooding, a ditch constructed to float logs
from one lake to the other connects the lakes permanently. Water leaves the Long Lake system
through a surface outlet in the north basin becoming Woodland Creek. The creek flows into Lake
Lois, completing the chain, and finally discharges into Henderson Inlet located in north Thurston
County (Thurston County, 1995a).
Long Lake can be divided up into two basins based on volume characteristics and
morphology: The North and South basins. For the last year that data was available (2019),

35

thermal stratification of Long Lake began in May and was apparent in the north basin until
September. In September, fall turnover was evident in the north basin and almost completely
mixed in the south basin due to its shallower depth. The north basin (LO3) which contains
Holmes Island was classified as eutrophic (TSI > 50) from 2016 to 2019, with a higher trend of
productivity and reduced transparency from 2008 to 2018. The south basin (LO4) has been
considered eutrophic intermittently over the past decade (2010-2020). In 2019, average surface
TP concentrations ranged from 0.030 to 0.032 mg/L at LO3 and 0.030 mg/L to 0.035 mg/L at
LO4 testing above the action level (0.020 mg/L) for the Puget Lowlands (Thurston County
Environmental Health Division, 2019). According to Washington State’s water quality standards
for surface waters:
If TP values are higher than the ecoregional action value, then the lake would be placed
on the 303(d) list of water bodies with water quality limitations. Lakes placed on the
303(d) list receive priority status for lake-specific studies (A. Moore & Hicks, 2004).
An “ecoregion” being classified as a major ecosystem defined by distinctive geography
and receiving uniform solar radiation and moisture. In 2018, the average total nitrogen levels in
both basins ranged from 0.5 to 0.6 mg/L with a significant upward trend (p-value < 0.05) from
July to October (Thurston County Environmental Health Division, 2019). While nitrogen is
known to be a contributing factor for algal growth, the State of Washington does not have
established action or cleanup levels for surface total nitrogen (Thurston County Environmental
Health Division, 2019).

36

Figure 9 Topographic map of chain of lakes: Hicks, Pattison, Long Lake, Lake Lois.

Note. Water flows between the chain of lakes in the following order: Hicks, Pattison, Long, and
Lois. Map courtesy of (United States Geological Survey, 2020).

37

3.2 Research Methods
The methods for this investigative study were based on the Department of Ecology’s
standard operating procedures (SOP) for collecting grab samples from stormwater discharges
(State Department of Ecology, 2018). The larger study designed by Thurston County
encompasses the entire 2021 water year (October 2020 to September 2021). For the purposes of
this thesis however, only storm events (i.e., periods of heavy rainfall with daily precipitation 6.35
millimeters or greater) from November 2020 to April 2021 were included. Sampling of
stormwater effluent was collected from catchment outfalls around Long Lake during these events.
Storm events were selected because they might contain typical “first flush effect” concentrations
(Bach et al., 2010; Lee & Bang, 2000). The first flush effect can be defined as:
a phenomenon in which a greater proportion of pollutant loads are washed off during the
beginning of a rainfall event than other periods…[and] is more likely to occur in a smaller
catchment with more impervious land surfaces (Qin et al., 2016).
Meteorological information was obtained from the regional office of the National Oceanic and
Atmospheric Administration (https://forecast.weather.gov/). All water sampling was done
manually using grab sampling techniques. Grab samples are single discrete samples collected
during a very short time period at a single location (United States Environmental Protection
Agency, 2013). Samples were collected in 250 ml narrow-mouth polyethylene bottles, cleaned
with a non-phosphate detergent (i.e., Alconox) that were rinsed thoroughly with tap then
deionized water and air dried.
3.3 Site Selection
Per the Department of Ecology protocol, stormwater outfalls were selected based on their
representational qualities of the urban area. Stormwater catchments, areas designed to channel
neighborhood ditches to county installed outfalls, were identified and visited to assess
accessibility. Sampling sites were determined to be free-flowing and unaffected by stagnated

38

water. These sites were also appropriate representations of mixing due to the catchment design
which pools multiple neighborhood ditch channels together before discharging into the lake. The
locations of the two stormwater outfalls known as “Casino Drain” and “Lorna Drain” are depicted
in Figures 10 and 11. Casino Drain is located in the north basin, whereas Lorna Drain is located
in the south basin. These represent two of the nine stormwater outfalls present around Long Lake.
Also depicted in the figure are sampling points at Long Lake’s inlet “Pattison Inlet”, and
two outlet sampling locations “Lake Lois” and “RR Outlet” (Fig. 10-13). Note that the inlet
sampling does not represent water upstream of Long Lake; rather, the sampling location is in
Long Lake, close to the inlet. As such, it represents the portion of Long Lake most influenced by
the inlet from Pattison Lake. Similarly, the Lake Lois outlet represents water quality leaving the
Long Lake system. The Lake Lois site is located within Long Lake opposite the RR Outlet.
Finally, the RR Outlet site represents water quality exiting Long Lake after it has passed through
the wetland structure which separates Long Lake from the beginning flow of Woodland Creek.
The deepest points of each basin, north “LO3” and south “LO4,” were also sampled (Fig. 10).
These sites were selected as they are relatively central within their respective basins representing
where the confluence and mixing of water across the epilimnion in that basin would be
maximized. Samples were collected at sites other than the stormwater outfalls to better
understand water quality throughout the lake system: as water entered the lake, mixed between
basins, and exited the lake.

39

Figure 10 Sampling Locations across Long Lake.

Note. A single sample was taken at each location. LO3 (North basin) and LO4 (South basin) are
located above the lake’s maximum depth in each basin. Image courtesy of Google Earth.

40

Figure 11 Sampling sites in the southern basin sans LO4.

Note. The Pattison Inlet sampling area is approximately eight meters in width. Image courtesy of
Google Earth.

41

Figure 12 Sampling sites in the northern basin sans LO3.

Note. Image courtesy of Google Earth.

42

Figure 13 Outlet sampling sites.

Note. Image courtesy of Google Earth.
3.4 Field Sampling Methods
Sampling on storm event days included: one sample collected three to five meters from the
outfall at five to ten centimeters depth from the lake surface. Another sample was collected midstream of stormwater effluent. Lake samples taken at this distance from the outfall might
illustrate the gradient of nutrient concentrations between the drain and lake sites, as well as the
influence of stormwater drains on the near-shore environment. A single sample was taken at both
the inlet and outlet of the lake at the surface (5-10 cm depth) and within each basin at the surface

43

above their deepest point respectively. A total of eight field samples were taken during each
rainfall event in addition to one field blank for accuracy.
Storm Event Sites:
Two stormwater outfalls (Casino, Lorna) + two near-outfall (Casino Lake, Lorna Lake) +
one inlet (Pattison) + one outlet (RR Outlet) + one north basin (LO3) + one south basin
(LO4) + one field blank = eight samples plus one field blank.

On non-storm event (baseline) days, seven samples plus one field blank were collected.
Stormwater outfalls were excluded from this sampling event as they were not running at the time.
Additionally, the “outlet” site, Lois Lake, was taken during baseline events to monitor nutrients
exiting the Long Lake system within the boundary of the lake.
Baseline Sites:
Two near-outfall (Casino-lake, Lorna-lake) + one inlet (Pattison) + two outlet (Lake Lois, RR
Outlet) + one north basin (LO3) + one south basin (LO4) + one field blank = seven samples
plus one field blank.

Samples were taken on the following dates: November 3, 2020; December 16, 2020;
February 17, 2021; February 22, 2021; March 23, 2021. Of these dates, November 3, December
16, and February 22 were storm events, indicating three storm events sampled and two baseline
events occurred.
Table 2 Sampling dates, event type, and weather on sample day.
Date
Weather on Sample Day
November 03, 2020
(storm event)

December 16, 2020
(storm event)

44

Mostly cloudy, raining
6.35 mm precipitation over 24
hours
0.2 - 4.4 mph ESE wind
Partly cloudy, raining
13.208 mm precipitation over
24 hours

Temperature (C)
Monthly Average (Low/High)
10.5 (0/15)

6 (-3/10)

0.2 – 4.5 mph ESE wind
February 17, 2021
(baseline)

February 22, 2021
(storm event)

March 19, 2021
(baseline)

March 23, 2021
(baseline)

Partly sunny
0.00 mm precipitation over 24
hours
0.3 – 4.4 mph ESE wind
Mostly cloudy, raining
10.16 mm precipitation over
24 hours
0.4 – 4.4 mph ENE wind
Cloudy
3.556 mm precipitation over
24 hours
0-6 mph ENE wind
Partly sunny
1.778 mm precipitation over
24 hours
2-3 mph SSW wind

6 (-3/13)

7 (3/14)

12 (2/13)

11 (2/13)

Samples were immediately stored on re-freezable ice packs in a portable cooler during
collection and transport to the laboratory. All samples were analyzed within 24 hours of
collection. IEH Analytical Laboratories located in Lake Forest Park, Washington performed the
analysis. Water samples were analyzed for total nitrogen (TN), total phosphorus (TP), and soluble
reactive phosphorus (SRP). TP and SRP were analyzed using the 365.1 method by semiautomated colorimetry. TN was analyzed using the 4500-N(Organic)- C. Semi-Micro-Kjeldahl
method.
3.4.1 Water Quality and Depth Profile Measurements
Dissolved oxygen (DO), temperature, conductivity, and pH were measured at the same
time as stormwater sampling using portable meters (Oakton Ion 6 Acorn Series for pH and YSI
Pro2030 for the other measurements). These measurements of DO, pH, conductivity, and
temperature were collected on February 17, February 22, and March 23, 2021. These are regular
variables measured to understand water quality and overall lake health. Furthermore, low pH is
indicative of anoxic conditions that can lead to the internal phosphorus loading Long Lake’s
water quality program hopes to address. Water quality measurements were collected at the

45

surface of the LO3, LO4, Lorna Lake, Pattison Inlet, Casino Lake, Lake Lois, and RR Outlet sites
on February 17. A more extensive depth profile (1 to 10 meters) was completed at LO3 and LO4
on February 22, and complete depth profile measurements (1 to 10 meters) were taken at Casino
Lake, Lake Lois, LO3 and LO4 on March 23. Surface measurements at RR Outlet, Pattison Inlet,
and Lorna Lake were taken on March 23 as well due to the shallow depth of these sites. Due to
restrictions pertaining to the length of the Oakton pH meter cord, pH could only be taken at
surface on all occasions.
3.4.2 Sample Analysis
Total phosphorus was measured following EPA’s methodology 365.1 method analysis
which is composed of two general procedural steps: (1) conversion of total phosphorus
(orthophosphate, condensed phosphate, and organic phosphate) to dissolved orthophosphate, and
(2) colorimetric determination of dissolved orthophosphate.
All samples are first mixed with a sulfuric acid solution, which a solution of ammonium
persulfate is then added to. The sample is then boiled down and acidified using an acid wash
solution composed of sulfuric acid and reagent water which converts all phosphorus forms (i.e.,
condensed and organic P) to orthophosphate. (Note: the acid wash is only applied to samples
tested for TP and not SRP. Testing for SRP includes a filtration step before the colorimetric test.
This biologically available, dissolved form of phosphorus is what is considered present in the
filtrate of a sample filtered through a phosphorus-free filter of 0.45-micron pore size.) The test
measures both dissolved and particulate orthophosphate before filtration. Ammonium molybdate
and antimony potassium tartrate are then added to the treated sample. These compounds react in
an acid medium with the dilute solutions of phosphorus to form an antimony-phosphomolybdate
complex. This complex is reduced to an intensely blue-colored complex by ascorbic acid. The
color is proportional to the phosphorus concentration which can then be measured by colorimetry
(United States Environmental Protection Agency, 1993).

46

Only orthophosphate can be directly measured, as such other phosphorus compounds
must be converted to this reactive form by various sample pretreatments described in the method
(United States Environmental Protection Agency, 1993). The samples are then measured using
colorimetry, a technique used to determine the number of colored compounds in a solution. This
is accomplished using a colorimeter which can test the concentration of a solution by measuring
its absorbance of a specific wavelength of light (Housecroft, 2006). A colorimetric test takes
place at 650 to 660 or 880 nm in a 15-mm or 50-mm tubular flow cell. Higher concentrations can
be determined by diluting the sample. IEH Analytical Laboratory uses the Astoria Pacific
Segmented Flow instrument for their analysis which has a detection limit of 0.002 mg/L for TP
and 0.001 mg/L for SRP.
Total nitrogen was measured following the 4500-N C. semi-micro Kjeldahl method as
described in Standard Methods for the Examination of Water and Wastewater 23rd edition (2017).
This protocol consists of three main steps: sample digestion, distillation, and ammonia
determination. Using sulfuric acid, a variety of catalysts, and salts, this method converts
organically bound nitrogen in samples to ammonium and is subsequently measured. This is the
standard method for determining organic and ammonia nitrogen from water, and is applicable to
samples containing high concentrations of organic nitrogen with the sum of organic N plus
ammonia nitrogen (Baird & Eaton, 2017). IEH Analytical Laboratory uses the Alpkem Rapid
Flow instrument for their analysis. The detection limit for total nitrogen was 0.050 mg/L.

47

3.5 Statistics
3.5.1 Nutrient Data
Two-sample t-test analyses were performed to identify whether drain nutrient
concentrations were significantly different from lake nutrient concentrations using the RStudio
Statistical Environment, Version 1.4.1106 (R Core Team, 2021). Prior to running tests, the data
was assessed for normality. For each sampling event, sample location was the independent
variable, whereas the nutrient concentration (TP, SRP, and TN) were the dependent variables.
Variables were deemed significant when the p value was less than 0.05. TP and SRP were log
transformed to achieve normal distributions. Relationships between the sample locations were
assessed using the Wilcoxon Signed-Rank test.
Additionally, median nutrient (TP, SRP, TN) concentrations were compared with
Washington State’s nutrient load allocation limits and/or action levels as designated by reporting
from the Puget lowlands ecoregion (Table 3). While various forms of nitrogen have suggested
nutrient load limits, there is no definite limit for TN. Furthermore, sample analysis of TN was
inclusive of ammonia and organic nitrogen only. As such, the sum of ammonia (0.034 mg/L) and
organic nitrogen (0.007 mg/L) for a total of 0.041 mg/L was used as the comparative action limit.
Additionally, the action level for TP (0.02 mg/L) was used for SRP as the Washington
Administrative Code for surface water does not differentiate between the different forms of
phosphorus. Nutrient concentrations were then analyzed for their distribution from this allocation
level using the one-sided nonparametric Wilcoxon Rank-Sum test also known as the MannWhitney U-test.
Table 3 Washington state nutrient load allocation guidance.
Washington State Nutrient
Water Type
Load Allocation
WAC-173-200-040 –
Groundwater
Washington State Legislature
WAC 246-290-310 –
Maximum Contaminant
Washington State Legislature Level (MCL) for drinking
water

48

Nutrient Load Allocation /
Action Limit
10 mg/L - Nitrate as Nitrogen
10 mg/L – Nitrate as Nitrogen
1 mg/L – Nitrite as Nitrogen

Deschutes River Total
Maximum Daily Load:
(Washington State
Department of Ecology,
2015)

Groundwater

WAC 173-201A-230 –
Washington State Legislature

Surface waters

0.054 mg/L - organic
phosphorus
0.052 mg/L - inorganic
phosphorus
0.616 mg/L - nitrate
0.034 mg/L – ammonia
0.007 mg/L - organic nitrogen
0.02 mg/L – ambient total
phosphorus

Note. Nutrient load allocation limits in bold are the levels used for subsequent statistical analysis
i.e., TP and SRP.
3.5.2 Storm Drain to Lake Comparisons

The Wilcoxon signed-rank test uses the ranks of the data measurements to test whether
the frequency distributions of the two sample groups are the same. If the distribution of the two
groups has the same shape, the test compares the location of the sample medians or means of the
two groups (Whitlock & Schluter, 2015). The Wilcoxon signed-rank test was used to compare
“drain” to “lake” nutrient concentrations, and to assess whether storm drains were a significant
contributor of nutrients over the sampling period.
3.5.3 Storm Event to Baseline Comparisons

As the Wilcoxon signed-rank test requires equally comparable datasets (i.e., equal
number of data points), the November 3 storm event was removed to refine the data to meet these
parameters. This storm event was selected for removal as it was least similar to the other
sampling events based on the time of year and season in which it was collected. The remaining
sampling dates were closer in temporal and seasonal range.
3.5.4 Nutrient Load Allocation Limits
The median nutrient concentration was evaluated against Washington State’s nutrient
load allocation limits (Table 3) using the Wilcoxon rank-sum test. This test evaluates how far
from the hypothesized median (i.e. nutrient load allocation limit) each data point lies. For the

49

purposes of this study, the null hypothesis was that the median nutrient concentration was less
than or equal to 0.041 mg/L (TN), 0.02 mg/L (TP), and 0.02 mg/L (SRP). The alternative
hypothesis is that the median nutrient concentration is higher.

50

4. RESULTS
4.1 Total Nitrogen
Total nitrogen ranged from being below the detection limit of the instrument (< 0.05
mg/L) to 1.74 mg/L across all sites between November 3, 2020 to March 23, 2021. The average
concentration was 0.74 mg/L with a standard deviation of 0.49 mg/L. Minimum values were
found at the following sites: Lorna Drain and Pattison Inlet, whereas high values were found at
these sites: Casino Drain, Casino Lake, Lorna lake, Lake Lois, and RR Outlet.
4.1.1

Values Relative to Action Limit
TN does not have specified nutrient criteria in Washington State, so there is no concrete

action limit from which to compare the sample concentrations. However, due to the fact that
sample analysis of TN for this study includes only the sum total of ammonia and organic
nitrogen, the various forms of nitrogen that are delimited for the Budd Inlet, Capitol Lake, and
Deschutes River watershed (Table 3) can be used as a comparative limit. The nitrogen values for
ammonia (0.034 mg/L) and organic nitrogen (0.007 mg/L) from Table 3 were used to compare
sample concentrations to an extrapolated action limit (0.041 mg/L) for the purposes of this study.
4.1.2

Storm Verses Baseline Sampling Events
Storm TN concentrations were not significantly higher than baseline values (V = 50, p

value = 0.9), with the one exception being Casino Lake, where all storm events had higher
concentrations. The December 16 storm event consistently had the highest TN concentrations
across all sites, except for the Inlet, Outlet and Casino Drain values. Out of the three storm events
where sampling occurred, the later season event (Feb. 22) almost always had lower TN
concentrations relative to the other sites.

51

4.1.3

Storm Drain Verses Lake TN Concentrations
At the two sites (Casino Drain and Lorna Drain) where comparative measurements of the

storm drain TN concentrations could be made with lake measurements, no significant difference
was observed in storm drain concentrations relative to the lake near the storm drain. This
accounts for the two dates where storm events happened, and lake samples were concurrently
collected. Unfortunately, for the 2/22 storm event, lake data was unable to be collected.
4.1.4

Inlet and Outlet Comparisons
Pattison Inlet had much less variability in TN concentrations relative to the outlet of the

lake (Fig. 17). Interestingly, TN concentrations were lower at Pattison Inlet for the first three
sampling events relative to the outlet, including the two storm events. This trend did not hold for
the 3rd late season storm event, with higher concentrations of nutrients at the inlet. There was no
significant difference between Inlet and Outlet concentrations (i.e., RR Outlet) when all the data
was combined.
Table 4 Summary statistics for site sample concentrations of total nitrogen.
Site Location
Total Nitrogen (mg/L)
Casino Drain

Range: 0.00 – 1.60
Average: 0.74
Standard deviation: 0.81

Casino Lake

Range: 0.00 – 1.68
Average: 0.91
Standard deviation: 0.73

Lorna Drain

Range: 0.00 – 0.45
Average: 0.28
Standard deviation: 0.25

52

Lorna Lake

Range: 0.44 – 1.05
Average: 0.75
Standard deviation: 0.32

Pattison Inlet

Range: 0.47 – 0.86
Average: 0.65
Standard deviation: 0.17

Lake Lois Outlet

Range: 0.26 – 1.57
Average: 0.92
Standard deviation: 0.93

RR Outlet

Range: 0.38 – 1.74
Average: 0.88
Standard deviation: 0.57

53

Figure 14 Total nitrogen concentrations across all sites.

Note. The solid black dash represents the mean TN concentration at each site.

54

Figure 15 Site Casino, Drain Vs. Lake: Total Nitrogen

Note. The solid black dash represents the mean TN concentration at each site.

55

Figure 16 Site Lorna, Drain Vs. Lake: Total Nitrogen

Note. The solid black dash represents the mean TN concentration at each site.

56

Figure 17 Total nitrogen entering and exiting Long Lake.

Note. The solid black dash represents the mean TN concentration at each site.

4.2 Total Phosphorus
Total phosphorus ranged from 0.01 mg/L to 0.41 mg/L across all sites between
November 3, 2020 to March 23, 2021. The average concentration was 0.05 mg/L with a standard
deviation of 0.07 mg/L. Minimum values were found at the following sites: Lake Lois, Lorna
Lake, Pattison Inlet, and RR Outlet, whereas high values were found at these sites: Casino Drain,
Casino Lake, and Lorna Drain.
4.2.1

Values Relative to Action Limit
The action level for total phosphorus as determined by Washington State surface water

nutrient criteria was set at 0.02 mg/L (Table 3) (WAC 173-201A-230, 2006). Using all sites
together, values were significantly higher than the action level (V = 469, p-value = 6.49e-05).

57

Values were higher than the action level at all sites and on all sampling occasions except for
Casino Lake, LO3, Lorna Lake, Pattison Inlet (February 17, 2021) and Lake Lois, LO3, Lorna
Lake, and Pattison Inlet (March 23, 2021) which were also baseline sampling events (Fig. 18).
Values fell above 0.02 mg/L at every site except Lake Lois, which had the lowest concentration
of TP values.
4.2.2

Storm Verses Baseline Sampling Events
Storm TP concentrations were significantly higher than baseline (V = 11, p value = 0.01).

The November 3 storm event consistently had the highest TP concentrations across all sites. Out
of the three storm events where sampling occurred, the later season event (Feb. 22) almost always
had lower TP concentrations relative to the other sites.
4.2.3

Storm Drain Verses Lake TP Concentrations
At the two sites (Casino Drain and Lorna Drain) where comparative measurements of the

storm drain TP concentrations could be made with lake measurements, no significant difference
was observed in storm drain concentrations relative to the lake near the storm drain. Nonetheless,
discharge from the storm drains did contain higher concentrations of TP compared to the lake
samples. This accounts for the two dates where storm events happened, and lake samples were
concurrently collected. Unfortunately, for the February 22 storm event, lake data was unable to be
collected.
4.2.4

Inlet and Outlet Comparisons
Similar to TN, Pattison Inlet had much less variability in TP concentrations relative to the

outlet of the lake (Fig. 21). Interestingly, TP concentrations were lower at Pattison Inlet for the
first three sampling events relative to RR Outlet, including the two storm events. This trend did
not hold for the 3rd late season storm event, with concentrations higher at the inlet. There was no

58

significant difference between Inlet and Outlet concentrations (i.e., RR Outlet) when all the data
was combined.

Table 5 Summary statistics for site sample concentrations of total phosphorus.
Site Location
Total Phosphorus (mg/L)
Casino Drain

R: 0.03 – 0.41
Avg: 0.18
SD: 0.21

Casino Lake

R: 0.01 – 0.12
Avg: 0.06
SD: 0.05

Lorna Drain

R: 0.03 – 0.14
Avg: 0.08
SD: 0.06

Lorna Lake

R: 0.02 – 0.06
Avg: 0.03
SD: 0.02

Pattison Inlet

R: 0.02 – 0.03
Avg: 0.02
SD: 0.003

Lake Lois Outlet

R: 0.02 – 0.02
Avg: 0.02
SD: 0.004

59

RR Outlet

R: 0.03 – 0.05
Avg: 0.04
SD: 0.01

Figure 18 Total phosphorus across all sites.

Note. The solid black dash represents the mean TP concentration at each site.

60

Figure 19 Site Casino, Drain Vs. Lake: Total Phosphorus

Note. Solid black dash represents the mean TP concentration at each site.

61

Figure 20 Site Lorna, Drain Vs. Lake: Total Phosphorus

Note. Solid black dash represents the mean TP concentration at each site.

62

Figure 21 Total phosphorus entering and exiting Long Lake.

Note. Solid black dash represents the mean TP concentration at each site.

4.3 Soluble Reactive Phosphorus
Soluble reactive phosphorus ranged from being below the detection limit of the
instrument (< 0.001 mg/L) to 0.05 mg/L across all sites between November 3, 2020 to March 23,
2021. The average concentration was 0.01 mg/L with a standard deviation of 0.01 mg/L.
Minimum values were found at the following sites: Lake Lois, RR Outlet, Lorna Lake, Casino
Lake, and Pattison Inlet, whereas high values were found at these sites: Casino Drain and Lorna
Drain.

63

4.3.1

Values Relative to Action Limit
The action level used for SRP was the same action level for TP (0.02 mg/L) as the

Washington Administrative Code for surface water does not differentiate between the different
forms of phosphorus. Using all sites together, values were not significantly higher than the action
level. Values rarely rose above 0.02 mg/L except during the November 3 storm event from each
drain.
4.3.2

Storm Verses Baseline Sampling Events
Storm SRP concentrations were not significantly higher than baseline. However, drain

sites consistently contributed higher concentrations during storm events. The November 3 storm
event had the highest SRP concentrations across all sites, except at the Inlet and Outlet. Out of the
three storm events where sampling occurred the later season event (Feb. 22) almost always had
lower SRP concentrations relative to the other sites.
4.3.3

Storm Drain Verses Lake SRP Concentrations
At the two sites (Casino Drain and Lorna Drain) where comparative measurements of the

storm drain SRP concentrations could be made with lake measurements, no significant difference
was observed in storm drain concentrations relative to the lake near the storm drain. Nonetheless,
the storm events transported higher concentrations of SRP into Long Lake. This accounts for the
two dates where storm events happened, and lake samples were concurrently collected.
Unfortunately, for the February 22 storm event, lake data was unable to be collected.
4.3.4

Inlet and Outlet Comparisons
The variability in SRP concentrations amongst Pattison Inlet, Lake Lois, and RR Outlet

were relative similar (Fig. 25). SRP concentrations were highest at Pattison Inlet for the first three
sampling events relative to the inlet, including the three storm events. There was no significant

64

difference between Inlet and Outlet concentrations (i.e., RR Outlet) when all the data was
combined (V = 10, p-value = 0.1).

Table 6 Summary statistics for site sample concentrations of soluble reactive phosphorus (SRP).
Site Location
Soluble Reactive Phosphorus
(mg/L)
Casino Drain

R: 0.001 – 0.029
Avg: 0.013
SD: 0.014

Casino Lake

R: 0.001 – 0.004
Avg: 0.002
SD: 0.001

Lorna Drain

R: 0.001 – 0.046
Avg: 0.020
SD: 0.023

Lorna Lake

R: 0.003 – 0.013
Avg: 0.002
SD: 0.005

Pattison Inlet

R: 0.002 – 0.006
Avg: 0.004
SD: 0.002

Lake Lois Outlet

R: 0.00 – 0.00
Avg: 0.00
SD: 0.00

RR Outlet

R: 0.00 – 0.003
Avg: 0.001
SD: 0.001

65

Figure 22 Soluble Reactive Phosphorus concentrations across all sites.

Note. The solid black dash represents the mean SRP concentration at each site.

Figure 23 Site Casino, Drain Vs. Lake: Soluble Reactive Phosphorus.

Note. The solid black dash represents the mean SRP concentration at each site.

66

Figure 24 Site Lorna, Drain Vs. Lake: Soluble Reactive Phosphorus.

Note. The solid black dash represents the mean SRP concentration at each site.

Figure 25 Soluble Reactive Phosphorus entering and exiting Long Lake.

Note. The solid black dash represents the mean SRP concentration at each site

67

4.4 Depth Profiles

Depth profiles for dissolved oxygen (DO), conductivity, and temperature were
constructed from data collected by the Oakton Ion 6 Acorn Series and YSI Pro2030 portable
meters on February 17 (9 data points collected), February 22 (12 data points collected), and
March 23, 2021 (26 data points collected).
4.4.1 Dissolved Oxygen

Dissolved oxygen ranged from 0.17 mg/L to 13.66 mg/L between 1- and 10-meters depth
across all sites on February 17, February 22, and March 23, 2021. The total average concentration
was 6.65 mg/L with a standard deviation of 5.69 mg/L when all dissolved oxygen readings were
included. Due to the rapid decrease in DO, it was surmised that the lake was stratified. As such,
DO readings taken near the surface, and before DO concentrations dropped massively, were
considered to be within the epilimnion. Readings below 1 mg/L were then considered to be
hypolimnetic. Average DO at all sites and dates where values were greater than 1 mg/L was 11.12
mg/L and 0.303 mg/L throughout the hypolimnion. DO was at its highest throughout the water
column on February 22 (average epilimnion: 13.52 mg/L, average hypolimnion: 0.4 mg/L) (Table
10) and lowest during the March 23 readings (average epilimnion: 9.58 mg/L, average
hypolimnion: 0.29 mg/L) (Table 11).
The two deepest points in Long Lake, LO3 (North basin) and LO4 (South basin), were
graphed to display the changes in oxygen with depth (Fig. 26-28). Over the course of the three
monitoring events, DO decreases in the epilimnion. There is an apparent decrease in the depth of
the epilimnion as DO readings below 1 mg/L occur closer to the surface of Long Lake.
Additionally, DO readings taken from the Lorna Lake and Pattison Inlet sites are especially low
compared, which is further surprising given that data was collected near the surface.

68

Table 7 Dissolved oxygen readings: February 17, 2021.
Location
Date

DO (mg/L)

DO%

11.29

87.8

1m/surface

13.06

101.7

Pattison Inlet

6.42

49

Lorna Lake

5.93

45.1

LO3: 10 m

0.27

2.1

0.3 m/surface

12.16

95.6

Lake Lois Outlet

12.74

100.6

Casino Lake

12.84

101

RR Outlet

12.38

98.5

LO4 (Island): 10 m

17-Feb

Figure 26 Changes in oxygen with depth at LO3 & LO4, 2/17.

Changes in Oxygen with depth on 2/17
0
0

2

4

6

8

10

12

14

-2

Depth (m)

-4
L03

-6

LO4
-8
-10
-12

DO (mg/L)

69

Figure 27 Changes in oxygen with depth at LO3 & LO4, 2/22.

Changes in Oxygen with depth on 2/22
0
0

2

4

6

8

10

12

14

16

-2

Depth (m)

-4
L03

-6

LO4

-8
-10
-12

DO (mg/L)

Figure 28 Changes in oxygen with depth at LO3 & LO4, 3/23.

Changes in Oxygen with depth on 3/23
0
0

2

4

6

8

10

12

-2

Depth (m)

-4
L03

-6

LO4
-8
-10

-12

70

DO (mg/L)

4.4.2 Conductivity

Conductivity ranged from 113.7 uS/cm to 190.7 uS/cm between 1- and 10-meters depth
across all sites on February 17, February 22, and March 23, 2021. The total average conductivity
was 131.02 uS/cm with a standard deviation of 18.1 uS/cm when all conductivity readings were
included. The average conductivity within the epilimnion across all sites and dates was 124.73
uS/cm and 140.28 uS/cm within the hypolimnion. Conductivity readings were at their highest and
lowest points throughout the water column on March 23 (epilimnion: 113.7 uS/cm, LO3;
hypolimnion: 190.7 uS/cm, Casino Lake) (Table 14) and lowest on average during the February
17 readings (average epilimnion: 126.425 uS/cm, average hypolimnion: 118.8 uS/cm) (Table 12).
Conductivity was consistently higher in the South basin (LO4) except 10 meters below the
surface within the hypolimnion of LO3 on February 22 (Fig. 29 – 31).

Figure 29 Changes in conductivity with depth, 2/17.

Changes in Conductivity with depth on 2/17
0
118

120

122

124

126

128

130

-2

Depth (m)

-4
L03

-6

LO4
-8
-10
-12

Conductivity (SPC-uS/cm)

71

Figure 30 Changes in conductivity with depth, 2/22.

Changes in Conductivity with depth on 2/22
0
120

122

124

126

128

130

132

134

-2

Depth (m)

-4
L03

-6

LO4
-8

-10
-12

Conductivity (SPC-uS/cm)

Figure 31 Changes in conductivity with depth, 3/23.

Changes in Conductivity with depth on 3/23
0
110

115

120

125

130

135

140

-2

Depth (m)

-4
L03

-6

LO4
-8
-10
-12

72

Conductivity (SPC-uS/cm)

4.4.3 Temperature and pH
Temperature ranged from 3.7 C and 11 C between 1- and 10-meters depth across all
sites on February 17, February 22, and March 23, 2021. The total average temperature was 7.4 C
with a standard deviation of 1.9 C when all temperature readings were included. The average
temperature on each date was as follows: February 17 (4.8 C), February 22 (5.9 C) and March
23 (9 C). The average temperature within the epilimnion across all sites and dates was 6.8 C
and 8.3 C within the hypolimnion. Temperature was at its highest on March 23 (Table 17: 11 C,
RR Outlet) and lowest on February 17 (Table 15: 3.7 C, Lorna Lake). The temperature was
consistently higher in the North basin (LO3) except within the hypolimnion of LO4
(approximately 8 – 10 meters depth) on March 23 (Fig. 32 – 34).
The pH meter itself was less than a meter long (approximately 0.6 m). As such, pH
readings were logged only at the lake surface. The average pH on each date was as follows:
February 17 (7.5), February 22 (7.3) and March 23 (6.9). The average pH across the three dates
was 7.2. The lowest reading was at the RR Outlet site on March 23 (Table 17: 6.6 pH), and the
highest reading was logged at Lorna Lake on February 17 (Table 15: 7.3 pH).

Table 8 Temperature and pH readings, 2/17.
Location
LO4 (Island): 0.3 m/surface

pH
7.65

10 m

Temp (C)
4.6
4.7

Lorna Lake/inlet

7.46

3.8

Lorna Lake

7.26

3.7

LO3: 0.3 m/surface

7.76

4.9

10 m

5.4

73

Lois Lake Outlet

7.62

5.1

Casino

7.67

5.2

RR

7.46

5.6

Figure 32 Changes in temperature with depth, 2/17.

Changes in Temperature with depth on 2/17
0
4.5

4.6

4.7

4.8

4.9

5

5.1

5.2

5.3

5.4

5.5

-2

Depth (m)

-4
L03

-6

LO4

-8
-10
-12

Temperature ℃

Table 9 Temperature and pH readings, 2/22.
Location
pH
LO4 (Island): 0.3 m/surface

7.65

Temp (C)
5.9

2m

5.9

6m

5.9

8m

5.9

10 m

5.9

LO3: 0.3 m/surface

7

6

1m

6

2m

6

74

4m

5.9

6m

5.9

8m

5.9

10 m

6

Figure 33 Changes in temperature with depth, 2/22.

Changes in Temperature with depth on 2/22
0
5.88

5.9

5.92

5.94

5.96

5.98

6

6.02

-2

Depth (m)

-4
L03

-6

LO4
-8

-10
-12

Temperature ℃

Table 10 Temperature and pH readings, 3/23.
Location
pH

Temp (C)

LO4 (Island): 10 m

8.7

7m

8.7

5m

8.6

2m

8.4

0.3 m/surface

6.95

8.5

Pattison Inlet

7.35

7.9

Lorna Lake

6.74

7.8

75

LO3: 10 m

8.5

8m

8.5

6m

8.5

4m

8.4

2m

8.8

0.3 m

6.83

10.2

Lois Lake Outlet: 10 m

8.8

7m

8.7

5m

8.7

3m

8.8

0.3 m/surface

6.56

9.5

Casino Lake: 10 m

9.3

8m

9.3

6m

9.2

4m

9.3

2m

9.4

1m

9.4

0.3 m/surface

7.32

10.2

RR

6.6

11

76

Figure 34 Changes in temperature with depth, 3/23.

Changes in Temperature with depth on 3/23
0
0

2

4

6

8

10

12

-2

Depth (m)

-4
L03

-6

LO4
-8
-10

-12

Temperature ℃

77

5. DISCUSSION
5.1 Dissolved Oxygen
An important outcome of this study is that it has demonstrated that dissolved oxygen
concentrations at depth were remarkably low. This is consistent with previous work at Long Lake
(Thurston County Environmental Health Division, 2017, 2019). How do these low oxygen
concentrations potentially impact the organisms found in the water? According to the Water
Quality Standards for Surface Waters of the State of Washington (2004), dissolved oxygen
criteria for aquatic life are as follows:
Table 11 Dissolved Oxygen Criteria for Aquatic Life in Fresh Water
Category
Lowest 1-Day Minimum
Char Spawning and Rearing

9.5 mg/L

Core Summer Salmonid Habitat

9.5 mg/L

Salmonid Spawning, Rearing, and Migration

8.0 mg/L

Salmonid Rearing and Migration Only

6.5 mg/L

Non-anadromous Interior Redband Trout

8.0 mg/L

Indigenous Warm Water Species

6.5 mg/L

Note. Table adapted from Water Quality Standards for Surface Waters of the State of
Washington, Table 200 (1)(d) (2004).
According to Washington State water quality standards, DO levels should not decrease
more than 0.2 mg/L from the standards set in Table 18 in a single day to maintain habitat viable
for the aforementioned fish. Furthermore, DO levels less than 4 mg/L would not support many
fish at all (Wetzel, 2001). The dissolved oxygen standards above give appropriate levels to
consider. As such, the lowest DO levels recorded in the epilimnion measured during February and
March ranged from 5.93 – 7.35 mg/L, which was supportive of life, but not for all types of fish
listed in the above table. Furthermore, while the surface waters tended to have acceptable DO
concentrations, it is worth noting that two locations (Lorna Lake and Casino Lake) consistently

78

had lower DO concentrations. The Lorna sites are located in a channel leading to the south basin,
and the Casino sites are located in a cove on the far north side of Long Lake. As such, both areas
do not receive much wind action as they are relatively sheltered. As a result, both of these areas
are less aerated than the majority of the lake which may explain their lower DO levels (personal
communication with Paula Cracknell, Aquatic Resource Specialist, 2021). However, the
proximity of Lorna and Casino Lake sites to a stormwater outfall might also be a contributing
factor. It is interesting that DO dropped significantly near the surface at the Casino Lake site.
Future site-specific study as well as the impact stormwater has on near-shore environments is
warranted.
DO levels were 0.27 mg/L (LO3) on February 17, 0.33 mg/L (LO4) on February 22, and
0.2 mg/L (Casino Lake and Lake Lois) on March 23 within the hypolimnion. The lowest DO
concentrations were recorded concurrently with warmer temperature readings. It is possible that
increased biotic activity utilized more DO as a result. Low DO levels are not uncommon in Long
Lake. Water quality reporting for Long Lake has noted DO approaching 0 mg/L near the bottom
of the lake during periods of stratification (Thurston County Environmental Health Division,
2017). Low levels of DO are expected as oxygen is utilized for redox processes occurring within
the hypolimnion. Long Lake is eutrophic, thus a highly productive system (Thurston County
Environmental Health Division, 2017, 2018, 2019). Invasive plants, algal blooms, and native
species contribute to the abundance of organic matter which decays in the hypolimnion
consuming oxygen.
Anoxic conditions cause phosphorus to be released from benthic and littoral sediments
due to the diminished effect of a micro-layer of ferric acid [FeO(OH)] at the sediment-water
interface which absorbs phosphorus in oxic conditions (Kleeberg & Dudel, 1997; Mortimer,
1941; Tammeorg et al., 2017). Additionally, absorption of CO2 from abundant macrophyte
growth can alter water chemistry by raising the pH and affecting nutrient dynamics as well
(Welch et al., 2005). For example, an increase in pH from 8.0 to 9.0 at least doubles the rate of P

79

released from oxic littoral sediments (Barko & James, 1998). This pH change can easily occur in
actively growing macrophyte beds. Furthermore, anoxic conditions caused by night respiration
can enhance sediment P release as discussed above (Welch et al., 2005). The impact abundant
macrophyte growth has on lake water quality can be an important reason for their control as
exhibited by the efforts of Long Lake’s LMD. The Long Lake LMD is actively engaged in
aquatic plant removal due to the overabundance of both invasive and native species (Lake
Management District #21, 2017). It is recommended that future studies incorporate DO and pH
readings at depth to further investigate nutrient dynamics in conjunction with aquatic plant
removal in Long Lake.
5.2 Actionable Nutrient Load Allocation Limits
There was not enough data to conclude that the nutrient concentrations of either storm
drains or lake samples were statistically significant when compared with the action level for
nutrients. Nonetheless, it can be observed that the samples analyzed were often above designated
action levels or nutrient allocation limits set for TN, TP, and SRP. Furthermore, the nutrient
concentrations of TP were consistently much higher than its designated action level specifically
during storm events. Baseline concentrations of TP dropped below the action level suggestive of
its dilution in the larger lake water body. Future mitigation options targeting stormwater can
hopefully reduce TP inputs to make TP reductions and other mitigation efforts (i.e., alum
treatment) most effective.
Nutrient criteria do not exist for TN and SRP in Washington State (personal
communication, Washington Department of Ecology, 2021). Nutrient load allocation limits for
TN (ammonia and organic nitrogen in this study) was derived from TMDL reporting for a nearby
watershed (Washington State Department of Ecology, 2012). Additionally, the action level for TP
(0.02 mg/L) was used for SRP as the Washington Administrative Code for surface water does not
differentiate between the different forms of phosphorus. It is recommended that future studies

80

continue analyzing for nutrients and include all inorganic forms of nitrogen (ammonia, nitrite,
nitrate).
5.3 Temporal Variability of Storm Events
A total of three storm events were sampled over the course of the study period
(November 2020 – March 2021). Nutrient concentrations varied considerably between these three
events suggesting a temporal difference in nutrient accumulation and discharge. When compared
to each other, it is apparent that the November 3 storm event was the greatest contributor of TP
and SRP across all sites sampled. TP and SRP concentrations decreased by the December 16
storm event and further still by the February 22 storm event (Table 19). Nevertheless, TP
concentrations were greater than or equal to the 0.02 mg/L nutrient action level across all sites
during each storm event. TN does not distinctly follow this trend as the December 16 storm
contributed more TN than the November 3 storm event, followed by the February 22 event (Table
19).
Higher nutrient concentrations in November could have resulted from fall leaf litter. Soil
and organic material contribute significant concentrations of nutrients in urban runoff in areas
with high tree or vegetation cover. It was estimated that 50% of the annual export of N and P
from an urban watershed in Saint Paul, Minnesota was due to leaf litter transported through
winter snowmelt (Bratt et al., 2017). However, while there are trees and vegetation amongst the
houses surrounding Long Lake, the area around Long Lake is heavily urbanized, and no natural
shoreline exists. It may be more likely that the summer accumulation of pollutants on impervious
surfaces played a more significant role than leaf litter. In order to test this idea fully, it is
recommended that sampling occur earlier in the fall season, as the first sample taken for this
study was done on November 3, 2020. The size and shape of lawns, connectivity of impervious
surfaces, and type of stormwater infrastructure can be more predictive of water quality
considering this specific watershed than that of an area densely forested (Yang & Lusk, 2018).

81

5.4 Storm Drain Effluent
Nutrient concentrations from storm drain runoff were noticeably higher than samples
taken from the lake sites during storm events. Casino Drain appeared to be the greatest
contributor of nutrients overall with higher levels of TN, TP and SRP during the November 3 and
December 16 storm events. Lorna Drain also contained higher levels of SRP on November 3 and
December 16. SRP concentrations are noticeably higher than baseline levels during the
November 3 and December 16 storm events suggestive of the influence storm events and
stormwater outfalls have on transporting this nutrient.
5.5 Inlet vs. Outlet
Nutrient concentrations of TP and TN appeared to increase as water passed through the
Long Lake system with equal variability in concentrations between baseline and storm event
sampling. However, further study is necessary to achieve the statistic power to assess the
significance of this hypothesis. TN concentrations increase from inlet to outlet during most
periods with the exception of the February 22 storm event and March 23 baseline sampling.
While both Lake Lois and RR Outlet were both considered “outlet” sites for Long Lake, the Lake
Lois site was located within Long Lake whereas RR Outlet is truly the beginning of Woodland
Creek. It is possible that nutrient concentrations increased as a result of water flowing through the
wetland structure between these two sites. Primary production and decomposition occurring in
the wetland could result in nutrients being carried downstream unless otherwise absorbed. The
opposite trend was true for SRP concentrations as it was highest entering the Long Lake system
from Pattison Inlet and decreased as it exited the lake. This may be due to its form and
availability which is ready for uptake by organisms within the lake as well as the wetland itself.
Water leaving Long Lake forms the Woodland Creek tributary and eventually flows into
Henderson Inlet. The residential influence on this waterway is significant as a Washington
Department of Ecology study found the nitrate and nitrite concentrations in Woodland Creek to

82

be some of the highest of any creeks that discharge to Henderson Inlet, and attributed the excess
nutrients to stormwater discharge from a local community development (Woodland Creek
Estates) (Hempleman, 2006). It is important to analyze for nitrites and nitrates in future Long
Lake studies, to understand possible residential effects on N export into the lake.
5.6 Study Issues
The storm drains and lake sites were visited in both the wet and dry seasons; nonetheless,
on the sampling date February 22 it was discovered that the Lorna Drain site was submerged as a
result of increased precipitation and the basin’s rising water level. As a result, the sample was
collected from the stormwater catchment at street level.
There are several issues with extrapolating load allocation limits for TN as these limits
were calculated for the specific ecosystem interactions of Budd Inlet not Henderson Inlet.
Nonetheless, these hypothetical limits were used as a reference mark to possibly detrimental
levels of incoming nutrients. It is recommended that future water samples be analyzed for nitrate
and nitrite as they were lacking in this study. Such samples would aid water quality mangers in
more conclusive efforts to identify and mitigate nitrogen inputs entering Long Lake. Finally, it is
unfortunate that more data points were not collected over the duration of this study which would
have aided in giving the study greater statistical power. Capturing more storm events from more
storm drains would provide a bigger picture of the storm drain nutrient influence on Long Lake.

83

6. CONCLUSION & FUTURE WORK
6.1 CyanoHAB Assessment & Management
The increasing presence of freshwater HABs globally has provoked researchers to
petition for greater comprehensive analysis, monitoring, and management of blooms (Anderson et
al., 2002; Weirich & Miller, 2014). Brooks et al. and Hudnell suggest that a national directive is
needed to adequately prioritize the mounting danger of freshwater HABs to water quality.
National prioritization would make more funding available for the research necessary to
understand cyanoHAB causes and consequences. Both articles encourage collaboration amongst
the sciences as the environmental, toxicological, and medical effects of cyanoHABs on water
quality requires a multifaceted scientific approach to assess and manage this risk more
effectively. Prioritizing research on freshwater HABs equally to those in marine waters would
sanction broader analytical and testing standards to be made available. Understanding both
environments is necessary to determine guidance levels considered safe during acute, short term,
sub-chronic, and chronic exposure periods to HABs.
There is still a lot to learn and understand about cyanoHABs, and a major point of
argument from Brooks et al. (2016) is how limited our understanding is of these blooms are
across spatiotemporal scales. Research published by the Environmental Protection Agency (EPA)
suggests that it may be possible to produce guidance for the purpose of operating at multiple
scales and curbing HAB incidences nationally (King et al., 2019). King et al. found in their study
that lakes, wetlands, and streams showed similar responses to nutrient and biotic properties at a
national scale. Their research suggests freshwater ecosystems may also respond similarly to
future global changes, and while climate was not analyzed in this study, it is another variable of
HAB growth that is predicted to have an overarching effect (Yindong et al., 2021; Zhang et al.,
2016).

84

6.2 Long Lake Management
The effects cyanoHABs pose to the water quality experienced by Lacey residents are felt
acutely. Brooks et al. call for national prescription, but local officials and lake management
districts are limited by financial constraints. One type of treatment that has been utilized in the
past and is the projected future treatment is the application of Aluminum sulfate to the lake
surface. An Aluminum (alum) sulfate treatment removes phosphates through precipitation when
added to a lake’s surface. The bound particulates, known as a floc, become heavier in the water
forcing the phosphates to settle on the lake bottom while also creating a barrier that retards
sediment phosphorus release (North American Lake Management Society, 2004).
This type of treatment is effective at absorbing phosphates, but may only last between 515 years before the cyanobacteria spores present in the benthic sediment are released from their
torpid state (Huser et al., 2016; North American Lake Management Society, 2004). A costly reapplication every 10 or so years would be required for long-term maintenance. This approach
may be sustainable for those with thousands of dollars on hand but is not the resolute answer to
excess nutrients also. Thus, a multifaceted approach is needed. One that includes continued
algae treatments, decreasing nutrient inputs and helpful behavioral changes by local residents. It
is imperative that external loading of nutrients be reduced to make any impact on reducing
internal loading within the lake.
Cyanobacterial harmful algal blooms have consistently presented Long Lake residents
with interrupted use of their precious lake. As such, their lake management district has resolved
to address this issue through their own water quality management program. Such a program
includes aquatic vegetation control, aluminum sulfate treatments, and now stormwater
monitoring, of which this study examined for the first time. The data collected this year will
contribute to the creation of a more robust phosphorus model of this system. With the stormwater
monitoring program goal in mind, the LLMD and Thurston County can look at the 2020-2021
water year to assess which sampling sites will be best suited for permanent monitoring locations.

85

The grab sampling technique is reproduceable by the residents themselves, so more frequent
sampling can be done at little to no cost. Analysis of the samples will be a continuous cost, but
the LLMD is willing and able to make this project a priority through sustained funding. Longer
and more frequent rainstorms led to many of the stormwater outfalls becoming submerged under
water. As such, it is likely that additional equipment will be installed to gather data when the
outfalls become unusable.
The premise and drive behind the LLMD have been and will continue to be grounded in
the community engagement that leads it. The Lake Management District contract is based on the
community’s commitment to fund raising and mutual management of this communal resource
with Thurston County aquatic resource specialists. Additionally, LMDs can authorize private
consultants and vendors to provide services to meet their needs through contract with Thurston
County. The funding process includes petitions which are mailed to the LLMD community. If the
potential action is agreed to, the action is authorized. Monthly meetings keep Long Lake residents
informed of the progress on current projects and present relevant science as it is understood and
uncovered by Long Lake’s own scientific studies.
In conclusion, this research has highlighted the importance of storm drain transport of
nutrients (especially SRP) and has also highlighted the low dissolved oxygen levels present in the
lake during the winter. This information is critical towards developing an effective management
plan to restoring Long Lake back to a period where the general public can once again recreate in
it.

86

{References or Notes}

87

Bibliography
Abrams, M. M., & Jarrell, W. M. (1995). Soil Phosphorus as a Potential Nonpoint Source for
Elevated Stream Phosphorus Levels. Journal of Environmental Quality, 24(1), 132–138.
https://doi.org/10.2134/jeq1995.00472425002400010019x
Adrian, R., O’Reilly, C. M., Zagarese, H., Baines, S. B., Hessen, D. O., Keller, W., Livingstone,
D. M., Sommaruga, R., Straile, D., Van Donk, E., Weyhenmeyer, G. A., & Winder, M.
(2009). Lakes as sentinels of climate change. Limnology and Oceanography, 54(6 PART 2),
2283–2297. https://doi.org/10.4319/lo.2009.54.6_part_2.2283
Allan, J. D., & Castillo, M. M. (2007). Stream Ecology: Structure and function of running waters
- J. David Allan, María M. Castillo - Google Books (2nd ed.). Springer.
https://books.google.com/books/about/Stream_Ecology.html?id=4tDNEFcQh7IC
American Chemical Society. (2021). Chapter 3: Temperature and Density. Middle School
Chemistry. https://www.middleschoolchemistry.com/lessonplans/chapter3/lesson6
American Water Works Association, & Economic and Engineering Services, I. (2002).
Nitrification. http://www.epa.gov/safewater/disinfection/tcr/regulation_revisions.html
Anderson, D. M., Glibert, P. M., & Burkholder, J. M. (2002). Harmful algal blooms and
eutrophication: Nutrient sources, composition, and consequences. Estuaries, 25(4), 704–
726. https://doi.org/10.1007/BF02804901
Aronstam, R. S., & Witkopt, B. (1981). Anatoxin-a interactions with cholinergic synaptic
molecules (acetylcholine receptors/ion channels/histrionicotoxin/phencyclidine). In
Neurobiology (Vol. 78, Issue 7).
Bach, P. M., McCarthy, D. T., & Deletic, A. (2010). Redefining the stormwater first flush
phenomenon. Water Research, 44(8), 2487–2498.
https://doi.org/10.1016/j.watres.2010.01.022
Baird, R. B., & Eaton, A. D. (2017). 4500-N(Org) C. Semi-Micro-Kjeldahl. In E. W. Rice (Ed.),
Standard Methods For the Examination of Water and Wastewater (23rd ed.). Water

88

Environment Federation; American Public Health Association.
https://doi.org/10.2105/SMWW.2882.003
Barko, J. W., & James, W. F. (1998). Effects of Submerged Aquatic Macrophytes on Nutrient
Dynamics, Sedimentation, and Resuspension (pp. 197–214). Springer, New York, NY.
https://doi.org/10.1007/978-1-4612-0695-8_10
Bell-McKinnon, M. (2010). An Assessment of Washington Lakes - National Lake Assessment
Results (Issue 10). Washington State Department of Ecology.
Bettez, N. D., & Groffman, P. M. (2012). Denitrification potential in stormwater control
structures and natural riparian zones in an urban landscape. Environmental Science and
Technology, 46(20), 10909–10917. https://doi.org/10.1021/es301409z
Beversdorf, L. J., Weirich, C. A., Bartlett, S. L., & Miller, T. R. (2017). Variable cyanobacterial
toxin and metabolite profiles across six eutrophic lakes of differing physiochemical
characteristics. Toxins, 9(2), 62. https://doi.org/10.3390/toxins9020062
Bhateria, R., & Jain, D. (2016). Water quality assessment of lake water: a review. Sustainable
Water Resources Management, 2(2), 161–173. https://doi.org/10.1007/s40899-015-0014-7
Boundless. (2021). 5.9B: Nitrate Reduction and Denitrification - Biology LibreTexts. In General
Microbiology. Open Education Resource LibreTexts Project.
https://bio.libretexts.org/Bookshelves/Microbiology/Book%3A_Microbiology_(Boundless)/
5%3A_Microbial_Metabolism/5.09%3A_Anaerobic_Respiration/5.9B%3A_Nitrate_Reduct
ion_and_Denitrification
Bratt, A. R., Finlay, J. C., Hobbie, S. E., Janke, B. D., Worm, A. C., & Kemmitt, K. L. (2017).
Contribution of Leaf Litter to Nutrient Export during Winter Months in an Urban
Residential Watershed. Environmental Science and Technology, 51(6), 3138–3147.
https://doi.org/10.1021/acs.est.6b06299
Brooks, B. W., Lazorchak, J. M., Howard, M. D. A., Johnson, M. V. V., Morton, S. L., Perkins,
D. A. K., Reavie, E. D., Scott, G. I., Smith, S. A., & Steevens, J. A. (2016). Are harmful

89

algal blooms becoming the greatest inland water quality threat to public health and aquatic
ecosystems? Environmental Toxicology and Chemistry, 35(1), 6–13.
https://doi.org/10.1002/etc.3220
Burton, J. . G. A., & Pitt, R. (2001). Stormwater Effects Handbook. In Stormwater Effects
Handbook. https://doi.org/10.1201/9781420036244
Butkus, S. (2004). Trophic State Census of Washington State Lakes by Satellite Imagery. In
Department of Ecology (Issues 04-03–011).
https://fortress.wa.gov/ecy/publications/publications/0403011.pdf
Carlson, R. E., & Simpson, J. (1996). A Coordinator’s Guide to Volunteer Lake Monitoring
Methods. North American Lake Management Society, 96.
https://www.nalms.org/secchidipin/monitoring-methods/trophic-state-equations/
Carmichael, W. (1991). Cyanobacterial secondary metabolites-the cyanotoxins. The Journal of
Applied Bacteriology, 724(45), 1–56.
https://www.researchgate.net/publication/286387885_Cyanobacterial_secondary_metabolite
s-the_cyanotoxins
Carpenter, S.R., Caraco, N. F., Correll, D. L., Howarth, R. W., Sharpley, A. N., & Smith, V. H.
(1998). Nonpoint Pollution of Surface Waters with Phosphorus and Nitrogen. Ecological
Applications, 8(3), 559–568.
Carpenter, Stephen R., & Cottingham, K. L. (1997). Resilience and restoration of lakes. Ecology
and Society, 1(1). https://doi.org/10.5751/es-00020-010102
Carpenter, Stephen R, Kitchell, J. F., Hodgson, J. R., Carpenter, S. R., Kitchell, J. F., & Hodgson,
J. R. (1985). Cascading Trophic Interactions and Lake Productivity. BioScience, 35(10),
634–639.
Carrick, H. J., Aldridge, F. J., & Schelske, C. L. (1993). Wind influences phytoplankton biomass
and composition in a shallow, productive lake. In Limnol. Oceanogr (Vol. 38, Issue 6).
City of Lacey. (2015). Shoreline Inventory for the Cities of Lacey, Olympia, and Tumwater and

90

their Urban Growth Areas. www.trpc.org
City of Lacey Department of Public Works. (2016). City of Lacey 2016 Stormwater Design
Manual.
Comings, K. J., Booth, D. B., & Horner, R. R. (2000). Storm Water Pollutant Removal by Two
Wet Ponds in Bellevue, Washington. Journal of Environmental Engineering, 126(4), 321–
330. https://doi.org/10.1061/(asce)0733-9372(2000)126:4(321)
Conway, T. M., & Lathrop, R. G. (2005). Alternative land use regulations and environmental
impacts: Assessing future land use in an urbanizing watershed. Landscape and Urban
Planning, 71(1), 1–15. https://doi.org/10.1016/j.landurbplan.2003.08.005
Corbel, S., Mougin, C., & Bouaïcha, N. (2014). Cyanobacterial toxins: Modes of actions, fate in
aquatic and soil ecosystems, phytotoxicity and bioaccumulation in agricultural crops.
Chemosphere, 96, 1–15. https://doi.org/10.1016/j.chemosphere.2013.07.056
Cottingham, K. L., Ewing, H. A., Greer, M. L., Carey, C. C., & Weathers, K. C. (2015).
Cyanobacteria as biological drivers of lake nitrogen and phosphorus cycling. Ecosphere,
6(1), 1–19. https://doi.org/10.1890/ES14-00174.1
Cracknell, P. (2020). Draft Stormwater Long 2020 Study (p. 11). Thurston County Public Works.
Dean, W. (1999). The Carbon Cycle and Biogeochemical Dynamics in Lake Sediments. Journal
of Paleolimnology, 21, 375–393. https://doi.org/10.1023/A
Déry, P., & Anderson, B. (2007). Peak Phosphorus. Energy Bulletin.
Dodson, S. I., Everhart, W. R., Jandl, A. K., & Krauskopf, S. J. (2007). Effect of watershed land
use and lake age on zooplankton species richness. Hydrobiologia, 579(1), 393–399.
https://doi.org/10.1007/s10750-006-0392-9
Dziallas, C., & Grossart, H.-P. (2011). Increasing Oxygen Radicals and Water Temperature
Select for Toxic Microcystis sp. PLoS ONE, 6(9), 1–8.
https://doi.org/10.1371/journal.pone.0025569
Entranco. (1994). Long Lake Phosphorus Control Strategy.

91

EnviroVision Corp. (2004). Technical Memorandum: Harvesting and Phosphorus Control in
Long Lake, Thurston County. Long Lake, Thurston County Integrated Aquatic Vegetation
Management Plan, Attachment II, September, 39 pp.
http://www.co.thurston.wa.us/waterresources/lakes/long/lakes-long-plan.html
Eyre, B. D., Maher, D. T., & Squire, P. (2013). Quantity and quality of organic matter (detritus)
drives N 2 effluxes (net denitrification) across seasons, benthic habitats, and estuaries.
Global Biogeochemical Cycles, 27, 1083–1095. https://doi.org/10.1002/2013GB004631
Feng, W., Yang, F., Zhang, C., Liu, J., Song, F., Chen, H., Zhu, Y., Liu, S., & Giesy, J. P. (2020).
Composition characterization and biotransformation of dissolved, particulate and algae
organic phosphorus in eutrophic lakes. https://doi.org/10.1016/j.envpol.2020.114838
Gold, A. C., Thompson, S. P., & Piehler, M. F. (2019). Nitrogen cycling processes within
stormwater control measures: A review and call for research. Water Research, 149, 578–
587. https://doi.org/10.1016/j.watres.2018.10.036
Golterman, H. L. (2001). Phosphate release from anoxic sediments or `What did Mortimer really
write?’. Hydrobiologia, 450, 99–106.
https://doi.org/https://doi.org/10.1023/A:1017559903404
Griffith, A. W., & Gobler, C. J. (2020). Harmful algal blooms: A climate change co-stressor in
marine and freshwater ecosystems. Harmful Algae, 91(May 2019), 101590.
https://doi.org/10.1016/j.hal.2019.03.008
Hallegraeff, G. M. (2010). Ocean climate change, phytoplankton community responses, and
harmful algal blooms: A formidable predictive challenge. In Journal of Phycology (Vol. 46,
Issue 2, pp. 220–235). John Wiley & Sons, Ltd. https://doi.org/10.1111/j.15298817.2010.00815.x
Hardy, F. J., Johnson, A., Hamel, K., & Preece, E. (2015). Cyanotoxin bioaccumulation in
freshwater fish, Washington State, USA. Environmental Monitoring and Assessment,
187(11). https://doi.org/10.1007/s10661-015-4875-x

92

Harrison, J. A., Maranger, R. J., Alexander, R. B., Giblin, A. E., Jacinthe, P.-A., Mayorga, E.,
Seitzinger, S. P., Sobota, D. J., & Wollheim, W. M. (2009). The regional and global
significance of nitrogen removal in lakes and reservoirs. 93(1), 143–157.
https://doi.org/10.1007/S10533-008-9272-X
Hempleman, C. (2006). Henderson Inlet Watershed Fecal Coliform Bacteria, Dissolved Oxygen,
Temperature, and pH Total Maximum Daily Load: Water Quality Improvement Report
Implementation Strategy, Vol. II.
https://fortress.wa.gov/ecy/publications/documents/0610058.pdf
Ho, J. C., & Michalak, A. M. (2015). Challenges in tracking harmful algal blooms: A synthesis of
evidence from Lake Erie. Journal of Great Lakes Research, 41(2), 317–325.
https://doi.org/10.1016/j.jglr.2015.01.001
Housecroft, C. (2006). Chemistry: an introduction to organic, inorganic, and physical chemistry.
Pearson Education.
Howarth, R. (2009). Nitrogen in Freshwater Systems and Estuaries. In Reference Module in Earth
Systems and Environmental Sciences. Elsevier. https://doi.org/10.1016/b978-0-12-4095489.09401-x
Howarth, RW. (2002). The Nitrogen Cycle. In H. Mooney, J. Candell, & T. Munn (Eds.),
Encyclopedia of Global Environmental Change, Volume 2, The Earth System: Biological
and Ecological Dimensions of Global Environmental Change (Vol. 2, pp. 429–435). Wiley.
https://www.wiley.com/enus/Encyclopedia+of+Global+Environmental+Change%2C+Volume+2%2C+The+Earth+Sy
stem%3A+Biological+and+Ecological+Dimensions+of+Global+Environmental+Change-p9780470853610
Hudnell, H. K. (2009). The state of U.S. freshwater harmful algal blooms assessments, policy and
legislation. Elsevier Ltd., 55(2010), 1024–1034.
https://doi.org/10.1016/j.toxicon.2009.07.021

93

Hupfer, M., & Lewandowski, J. (2008). Oxygen controls the phosphorus release from lake
sediments - A long-lasting paradigm in limnology. International Review of Hydrobiology,
93(4–5), 415–432. https://doi.org/10.1002/iroh.200711054
Huser, B. J., Egemose, S., Harper, H., Hupfer, M., Jensen, H., Pilgrim, K. M., Reitzel, K., Rydin,
E., & Futter, M. (2016). Longevity and effectiveness of aluminum addition to reduce
sediment phosphorus release and restore lake water quality. Water Research, 97, 122–132.
https://doi.org/10.1016/j.watres.2015.06.051
Illinois State Environmental Protection Agency. (n.d.). Lake Stratification and Mixing. Retrieved
December 18, 2020, from http://www.epa.state.il.us/water/conservation/lake-notes/lakestratification-and-mixing/lake-stratification.pdf
Jacoby, J. M., Collier, D. C., Welch, E. B., Hardy, F. J., & Crayton, M. (2000). Environmental
factors associated with a toxic bloom of Microcystis aeruginosa. Canadian Journal of
Fisheries and Aquatic Sciences, 57(1), 231–240. https://doi.org/10.1139/f99-234
Kelly, C. A., Rudd, J. W. M., Hesslein, R. H., Schindler, D. W., Dillon, P. J., Driscoll, C. T.,
Gherini, S. A., & Hecky, R. E. (1987). Prediction of Biological Acid Neutralization in AcidSensitive Lakes (Vol. 3, Issue 1). https://about.jstor.org/terms
Kim, G., Yur, J., & Kim, J. (2007). Diffuse pollution loading from urban stormwater runoff in
Daejeon city, Korea. Journal of Environmental Management, 85, 9–16.
https://doi.org/10.1016/j.jenvman.2006.07.009
King, K., Cheruvelil, K. S., & Pollard, A. (2019). Drivers and spatial structure of abiotic and
biotic properties of lakes, wetlands, and streams at the national scale. In Ecological
Applications (Vol. 29, Issue 7). Ecological Society of America.
https://doi.org/10.1002/eap.1957
Kleeberg, A., & Dudel, G. E. (1997). Changes in extent of phosphorus release in a shallow lake
(Lake Grosser Muggelsee; Germany, Berlin) due to climatic factors and load. Marine
Geology, 139(1–4), 61–75. https://doi.org/10.1016/S0025-3227(96)00099-0

94

Lake Management District #21. (2017). Long Lake News: Summer 2017. Long Lake News, 1–8.
https://www.co.thurston.wa.us/tcweeds/docs/LongLake_Summer2017.pdf
Lamarra, V. A. J. (1975). Digestive activities of carp as a major contributor to the nutrient
loading of lakes. SIL Proceedings 1922-2010, 19(3), 2461–2468.
https://doi.org/10.1080/03680770.1974.11896330
Lathrop, R. C., Carpenter, S. R., Stow, C. A., Soranno, P. A., & Panuska, J. C. (1998).
Phosphorus loading reductions needed to control blue-green algal blooms in Lake Mendota.
Canadian Journal of Fisheries and Aquatic Sciences, 55(5), 1169–1178.
https://doi.org/10.1139/cjfas-55-5-1169
Lee, J. H., & Bang, K. W. (2000). Characterization of urban stormwater runoff. Water Research,
34(6), 1773–1780. https://doi.org/10.1016/S0043-1354(99)00325-5
Li, Y., Chen, J. an, Zhao, Q., Pu, C., Qiu, Z., Zhang, R., & Shu, W. (2011). A cross-sectional
investigation of chronic exposure to microcystin in relationship to childhood liver damage
in the three gorges reservoir region, China. Environmental Health Perspectives, 119(10),
1483–1488. https://doi.org/10.1289/ehp.1002412
Long Lake Management District #21. (2019). Community Meeting Presentation. Thurston
County.
Lusk, M. G., Toor, G. S., & Inglett, P. W. (2020). Organic nitrogen in residential stormwater
runoff: Implications for stormwater management in urban watersheds. Science of the Total
Environment, 707, 135962. https://doi.org/10.1016/j.scitotenv.2019.135962
Mattson, N., Leatherwood, R., & Peters, C. (2009). Nitrogen: All Forms Are Not Equal Nitrogen
form. http://greenhouse.cornell.edu/crops/factsheets/nitrogen_form.pdf
McGrane, S. J. (2016). Impacts of urbanisation on hydrological and water quality dynamics, and
urban water management: a review. Hydrological Sciences Journal, 61(13), 2295–2311.
https://doi.org/10.1080/02626667.2015.1128084
Michalak, A. M., Anderson, E. J., Beletsky, D., Boland, S., Bosch, N. S., Bridgeman, T. B.,

95

Chaffin, J. D., Cho, K., Confesor, R., Dalo Glu, I., Depinto, J. V, Evans, M. A., Fahnenstiel,
G. L., He, L., Ho, J. C., Jenkins, L., Johengen, T. H., Kuo, K. C., Laporte, E., … Zagorski,
M. A. (2013). Record-setting algal bloom in Lake Erie caused by agricultural and
meteorological trends consistent with expected future conditions. Proceedings of the
National Academy of Sciences of the United States of America, 110(16), 6448–6452.
https://doi.org/10.1073/pnas.1216006110
Mohamedali, T., Roberts, M., & Sackmann, B. (2011). Puget Sound Dissolved Oxygen Model
Nutrient Load Summary for 1999-2008. In Washington Department of Ecology (Issue 11).
https://fortress.wa.gov/ecy/publications/documents/1103057.pdf
Moore, A., & Hicks, M. (2004). Water Quality Standards for Surface Waters of the State of
Washington.
Moore, T. L. C., Hunt, W. F., Burchell, M. R., & Hathaway, J. M. (2011). Organic nitrogen
exports from urban stormwater wetlands in North Carolina. Ecological Engineering, 37(4),
589–594. https://doi.org/10.1016/j.ecoleng.2010.12.015
Mortimer, C. H. (1941). The Exchange of Dissolved Substances Between Mud and Water in
Lakes. The Journal of Ecology, 29(2), 280. https://doi.org/10.2307/2256395
Niirnberg, G. K. (1994). Phosphorus relase from anoxic sediments: What we know and how we
can deal with it.
North American Lake Management Society. (2004). The Use of Alum for Lake Management.
https://www.nalms.org/nalms-position-papers/the-use-of-alum-for-lake-management/
O’Driscoll, M., Clinton, S., Jefferson, A., Manda, A., & Mcmillan, S. (2010). Urbanization
Effects on Watershed Hydrology and In-Stream Processes in the Southern United States. 2,
605–648. https://doi.org/10.3390/w2030605
O’Reilly, C. M., Sharma, S., Gray, D. K., Hampton, S. E., Read, J. S., Rowley, R. J., Schneider,
P., Lenters, J. D., McIntyre, P. B., Kraemer, B. M., Weyhenmeyer, G. A., Straile, D., Dong,
B., Adrian, R., Allan, M. G., Anneville, O., Arvola, L., Austin, J., Bailey, J. L., … Zhang,

96

G. (2015). Rapid and highly variable warming of lake surface waters around the globe.
Geophysical Research Letters, 42(24), 10773–10781.
https://doi.org/10.1002/2015GL066235
Paerl, H. W. (2017). Controlling harmful cyanobacterial blooms in a climatically more extreme
world: Management options and research needs. Journal of Plankton Research, 39(5), 763–
771. https://doi.org/10.1093/plankt/fbx042
Paerl, H. W., Bland, P. T., Dean Bowles, N., & Haibach, M. E. (1985). Adaptation to HighIntensity, Low-Wavelength Light among Surface Blooms of the Cyanobacterium
Microcystis aeruginosa Downloaded from. In APPLIED AND ENVIRONMENTAL
MICROBIOLOGY (Vol. 49, Issue 5). http://aem.asm.org/
Paerl, H. W., & Paul, V. J. (2011). Climate change: Links to global expansion of harmful
cyanobacteria. https://doi.org/10.1016/j.watres.2011.08.002
Palmstrom, N. S., Carlson, R. E., & Dennis Cooke, G. (2009). Lake and Reservoir Management
Potential Links Between Eutrophication and the Formation of Carcinogens in Drinking
Water. https://doi.org/10.1080/07438148809354809
Panawala, L. (2017). Difference Between Chlorophyll A and B. Pediaa, April.
https://www.researchgate.net/publication/316584030
Pavluk, T., & De Vaate, A. (2018). Trophic index and efficiency. Encyclopedia of Ecology, 495–
502. https://doi.org/10.1016/B978-0-12-409548-9.00608-4
Percival, S. L., Yates, M. V., Williams, D. W., Chalmers, R. M., & Gray, N. F. (2014).
Microbiology of Waterborne Diseases. In Microbiology of Waterborne Diseases (2nd ed.).
Academic Press. https://doi.org/https://doi-org.evergreen.idm.oclc.org/10.1016/B978-0-12415846-7.00005-6
Phillips, R., Jeswani, H. K., Azapagic, A., & Apul, D. (2018). Are stormwater pollution impacts
significant in life cycle assessment? A new methodology for quantifying embedded urban
stormwater impacts. Science of the Total Environment, 636(2018), 115–123.

97

https://doi.org/10.1016/j.scitotenv.2018.04.200
Phosphorus Cycle. (2016). Lake Simcoe Region Conservation Authority.
https://www.lsrca.on.ca/Pages/Phosphorus-Cycle.aspx
Piccolroaz, S., Woolway, R. I., & Merchant, C. J. (2020). Global reconstruction of twentieth
century lake surface water temperature reveals different warming trends depending on the
climatic zone. Climatic Change, 160(3), 427–442. https://doi.org/10.1007/s10584-02002663-z
Pick, F. R., & Lean, D. R. S. (2010). The role of macronutrients (C, N, P) in controlling
cyanobacterial dominance in temperate lakes. New Zealand Journal of Marine and
Freshwater Research, 21, 425–435. https://doi.org/10.1080/00288330.1987.9516238
Plumbing the Depths. (2002, March 12). NASA Earth Observatory; NASA Earth Observatory.
Polyakov, V., Fares, A., & Ryder, M. H. (2005). Precision riparian buffers for the control of
nonpoint source pollutant loading into surface water: A review. Environmental Reviews,
13(3), 129–144. https://doi.org/10.2307/envirevi.13.3.129
Preisendorfer, R. W., & Duntly, S. Q. (1952). The Visibility of Submerged Objects (Ch. 1-4).
Qin, H. peng, He, K. mao, & Fu, G. (2016). Modeling middle and final flush effects of urban
runoff pollution in an urbanizing catchment. Journal of Hydrology, 534, 638–647.
https://doi.org/10.1016/j.jhydrol.2016.01.038
R Core Team. (2021). A Language and Environment for Statistical Computing. R Foundation for
Statistical Computing. https://www.r-project.org/
Rigler, F. H. (1973). A dynamic view of the phosphorus cycle in lakes. In E. J. Griffith, A.
Beeton, J. M. Spencer, & D. T. Mitchell (Eds.), Environmental Phosphorus Handbook. John
Wiley & Sons, Ltd.
Rigosi, A., Carey, C. C., Ibelings, B. W., & Brookes, J. D. (2014). The interaction between
climate warming and eutrophication to promote cyanobacteria is dependent on trophic state
and varies among taxa. Limnology and Oceanography, 59(1), 99–114.

98

https://doi.org/10.4319/lo.2014.59.1.0099
Ripple, W. J., Estes, J. A., Schmitz, O. J., Constant, V., Kaylor, M. J., Lenz, A., Motley, J. L.,
Self, K. E., Taylor, D. S., & Wolf, C. (2016). What is a Trophic Cascade? Trends in
Ecology and Evolution, 31(11), 842–849. https://doi.org/10.1016/j.tree.2016.08.010
Rodríguez-Rojas, M. I., Huertas-Fernández, F., Moreno, B., Martínez, G., & Grindlay, A. L.
(2018). A study of the application of permeable pavements as a sustainable technique for the
mitigation of soil sealing in cities: A case study in the south of Spain. Journal of
Environmental Management, 205, 151–162. https://doi.org/10.1016/j.jenvman.2017.09.075
Rohrlack, T., Dittmann, E., Henning, M., Börner, T., & Kohl, J. G. (1999). Role of microcystins
in poisoning and food ingestion inhibition of Daphnia galeata caused by the cyanobacterium
Microcystis aeruginosa. Applied and Environmental Microbiology, 65(2), 737–739.
https://doi.org/10.1128/aem.65.2.737-739.1999
Saunders, D. L., & Kalff, J. (2001). Denitrification Rates in the Sediments of Lake
Memphremagog, Canada-USA. Water Research, 35(8), 1897–1904.
Schindler, D. W., & Vallentyne, J. R. (2008). The Algal Bowl: Overfertilization of the World’s
Freshwaters and Estuaries. University of Alberta Press.
https://www.uap.ualberta.ca/titles/55-9780888644848-algal-bowl
Schueler, T. R., Fraley-McNeal, L., & Cappiella, K. (2009). Is Impervious Cover Still Important?
Review of Recent Research. Journal of Hydrologic Engineering, 14(4), 309–315.
https://doi.org/10.1061/(asce)1084-0699(2009)14:4(309)
Scottish Environment Protection Agency (SEPA). (2021). Diffuse pollution.
https://www.sepa.org.uk/regulations/water/diffuse-pollution/
Seehausen, O., Van Alphen, J. J. M., & Witte, F. (1997). Cichlid Fish Diversity Threatened by
Eutrophication That Curbs Sexual Selection. www.sciencemag.org
Seitzinger, S., Harrison, J. A., Böhlke, J. K., Bouwman, A. F., Lowrance, R., Peterson, B.,
Tobias, C., & Van Drecht, G. (2006). Denitrification across Landscapes and Waterscapes:

99

A Synthesis (Vol. 16, Issue 6).
Siewicki, T. C., Pullaro, T., Pan, W., McDaniel, S., Glenn, R., & Stewart, J. (2007). Models of
total and presumed wildlife sources of fecal coliform bacteria in coastal ponds. Journal of
Environmental Management, 82(1), 120–132.
https://doi.org/10.1016/j.jenvman.2005.12.010
Silva, T. F. G., Vinçon-Leite, B., Lemaire, B. J., Petrucci, G., Giani, A., Figueredo, C. C., De, N.,
& Nascimento, O. (2019). Impact of Urban Stormwater Runoff on Cyanobacteria Dynamics
in A Tropical Urban Lake. 11, 946. https://doi.org/10.3390/w11050946
Smith, J. S., Winston, R. J., Tirpak, R. A., Wituszynski, D. M., Boening, K. M., & Martin, J. F.
(2020). The seasonality of nutrients and sediment in residential stormwater runoff:
Implications for nutrient-sensitive waters. Journal of Environmental Management, 276,
111248. https://doi.org/10.1016/j.jenvman.2020.111248
Song, K., Winters, C., Xenopoulos, M. A., Marsalek, J., & Frost, P. C. (2017). Phosphorus
cycling in urban aquatic ecosystems: connecting biological processes and water chemistry to
sediment P fractions in urban stormwater management ponds. Biogeochemistry, 132(1–2),
203–212. https://doi.org/10.1007/s10533-017-0293-1
Spears, B. M., Carvalho, L., Perkins, R., Kirika, A., & Paterson, D. M. (2007). Sediment
phosphorus cycling in a large shallow lake: Spatio-temporal variation in phosphorus pools
and release. Hydrobiologia, 584(1), 37–48. https://doi.org/10.1007/s10750-007-0610-0
State Department of Ecology, W. (2018). Collecting Grab Samples from Stormwater Discharges
Standard Operating Procedure Version 1.1. www.ecology.wa.gov
Stein, L. Y., & Klotz, M. G. (2016). The nitrogen cycle. Current Biology, 26(3), R94–R98.
https://doi.org/10.1016/j.cub.2015.12.021
Tammeorg, O., Möls, T., Niemistö, J., Holmroos, H., & Horppila, J. (2017). The actual role of
oxygen deficit in the linkage of the water quality and benthic phosphorus release: Potential
implications for lake restoration. Science of the Total Environment, 599–600, 732–738.

100

https://doi.org/10.1016/j.scitotenv.2017.04.244
Thurston County. (1995a). Woodland-Woodard Creek Drainage Basin Plan. In Department of
Water and Waste Management. https://www.thurstoncountywa.gov/sw/Pages/basin-planwoodland.aspx
Thurston County. (1995b). Woodland-Woodard Creek Drainage Basin Plan. In Department of
Water and Waste Management. https://www.thurstoncountywa.gov/sw/Pages/basin-planwoodland.aspx
Thurston County Environmental Health Division. (2017). 2018 Long Lake Water Quality Report.
http://www.thurstoncountywa.gov/sw/Pages/monito
Thurston County Environmental Health Division. (2018). 2018 Long Lake Water Quality Report.
Thurston County Environmental Health Division. (2019). 2019 Long Lake Water Quality Report.
http://www.thurstoncountywa.gov/sw/Pages/monito
Tian, Z., Zhao, H., Peter, K. T., Gonzalez, M., Wetzel, J., Wu, C., Hu, X., Prat, J., Mudrock, E.,
Hettinger, R., Cortina, A. E., Biswas, R. G., Kock, F. V. C., Soong, R., Jenne, A., Du, B.,
Hou, F., He, H., Lundeen, R., … Kolodziej, E. P. (2021). A ubiquitous tire rubber–derived
chemical induces acute mortality in coho salmon. Science, 371(6525), 185–189.
https://doi.org/10.1126/science.abd6951
Tundisi, J. G., & Tundisi, T. M. (2011). Limnology (1st ed.). CRC Press. https://bok.cc/book/2524032/790efd
Turner, B. L., Frossard, E., & Baldwin, D. (2005). Organic phosphorus in the environment (B. L.
Turner, E. Frossard, & D. S. Baldwin (Eds.)). CABI.
https://doi.org/10.1079/9780851998220.0000
United States Environmental Protection Agency. (1993). Method 365.1, Revision 2.0:
Determination of Phosphorus By Semi-Automated Colorimetry. In J. W. O’Dell (Ed.),
Environmental Monitoring Systems Laboratory (2.0, Issue August, pp. 1–15). U.S.
Environmental Protection Agency. https://www.epa.gov/sites/production/files/2015-

101

08/documents/method_365-1_1993.pdf
United States Environmental Protection Agency. (1998). 1998 National Water Quality Inventory
Report to Congress. https://www.epa.gov/sites/production/files/201509/documents/1998_national_water_quality_inventory_report_to_congress.pdf
Federal Water Pollution Control Act, (2002).
United States Environmental Protection Agency. (2004). The National Water Quality Inventory:
Report to Congress for the 2004 Reporting Cycle - A Profile.
http://www.epa.gov/owow/monitoring/nationalsurveys.html.
United States Environmental Protection Agency. (2012). National Lakes Assessment 2012 Key
Findings. https://www.epa.gov/national-aquatic-resource-surveys/national-lakesassessment-2012-key-findings
United States Environmental Protection Agency. (2013). Wastewater Sampling.
https://www.epa.gov/sites/production/files/2015-06/documents/Wastewater-Sampling.pdf
United States Environmental Protection Agency. (2020a). Stormwater Discharges from
Municipal Sources. https://www.epa.gov/npdes/stormwater-discharges-municipal-sources
United States Environmental Protection Agency. (2020b). Summary of the Clean Water Act.
https://www.epa.gov/laws-regulations/summary-clean-water-act
United States Environmental Protection Agency. (2020c). Standards for Water Body Health.
https://www.epa.gov/standards-water-body-health
United States Environmental Protection Agency. (2021a). Great Lakes Chlorophyll-a Monitoring.
https://www.epa.gov/great-lakes-monitoring/great-lakes-chlorophyllmonitoring#:~:text=Chlorophyll-a in the algae,chlorophyll-a in the water.
United States Environmental Protection Agency. (2021b). Learn about Cyanobacteria and
Cyanotoxins. https://www.epa.gov/cyanohabs/learn-about-cyanobacteria-and-cyanotoxins
United States Geological Survey. (1989). A regional rainfall-runoff simulation model for the
Puget Sound area of Washington State by R.S. Dinicola.

102

United States Geological Survey. (2020). National Geologic Map Database.
https://ngmdb.usgs.gov/topoview/viewer/#14/47.0209/-122.7741
University of Hawai’i. (2021). Light in the Ocean.
https://manoa.hawaii.edu/exploringourfluidearth/physical/ocean-depths/light-ocean
US Environmental Protection Agency. (n.d.). Basic Information about Nonpoint Source (NPS)
Pollution. Retrieved March 30, 2021, from https://www.epa.gov/nps/basic-informationabout-nonpoint-source-nps-pollution
Vallentyne, J. R. (1974). The Algal Bowl (Miscellane). Department of the Environment Fisheries
and Marine Service.
WAC 173-201A-600, (1992).
Wallace, J. M., & Hobbs, P. V. (2006). Atmospheric Science: An Introductory Survey: Second
Edition. In Atmospheric Science: An Introductory Survey: Second Edition. Elsevier Inc.
https://doi.org/10.1016/C2009-0-00034-8
Walsh, C. J., Roy, A. H., Feminella, J. W., Cottingham, P. D., Groffman, P. M., & Morgan, R. P.
(2005). The urban stream syndrome: Current knowledge and the search for a cure. Journal
of the North American Benthological Society, 24(3), 706–723. https://doi.org/10.1899/04028.1
Washington Department of Ecology. (2010). Protecting Washington’s waters from stormwater
pollution. 1–8.
Washington State Department of Ecology. (2012). Deschutes River, Capitol Lake, and Budd Inlet
Temperature, Fecal Coliform Bacteria, Dissolved Oxygen, pH, and Fine Sediment Total
Maximum Daily Load Technical Report - Water Quality Study Findings (Issue 12).
Washington State Department of Ecology. (2015). Deschutes River, Percival Creek, and Budd
Inlet Tributaries Temperature, Fecal Coliform Bacteria, Dissolved Oxygen, pH, and Fine
Sediment Total Maximum Daily Load: Water Quality Improvement Report and
Implementation Plan (Issue 15).

103

Washington State Freshwater Algae Control Program. (2020). Historical Chart: Long Lake,
Thurston County. In NW Toxic Algae. https://www.nwtoxicalgae.org/HistoricalCharts.aspx
Shoreline Management Act of 1971, Chapter 90.58 RCW 90.58.010 (1971).
https://apps.leg.wa.gov/RCW/default.aspx?cite=90.58
WAC 173-201A-230, (2006).
Watzer, B., & Forchhammer, K. (2018). Cyanophycin: A Nitrogen-Rich Reserve Polymer. In A.
Tiwari (Ed.), Cyanobacteria (pp. 85–107). IntechOpen.
https://doi.org/10.5772/intechopen.77049
Wehr, D., Sheath, R. G., & Kociolek, J. P. (2015). Freshwater Algae of North America.
Freshwater Algae of North America. https://doi.org/10.1016/c2010-0-66664-8
Weirich, C. A., & Miller, T. R. (2014). Freshwater harmful algal blooms: Toxins and children’s
health. Current Problems in Pediatric and Adolescent Health Care, 44(1), 2–24.
https://doi.org/10.1016/j.cppeds.2013.10.007
Welch, E. B., Cooke, G. D., Nichols, S. A., & Peterson, S. A. (2005). Restoration and
Management of Lakes and Reservoirs (Third). Taylor & Francis.
Welch, E. B., & Jacoby, J. M. (2001). On determining the principal source of phosphorus causing
summer algal blooms in Western Washington Lakes. Lake and Reservoir Management,
17(1), 55–65. https://doi.org/10.1080/07438140109353973
Wetzel, R. G. (2001). Limnology: Lake and River Ecosystems (3rd ed.). Academic Press.
Whitlock, M. C., & Schluter, D. (2015). The Analysis of Biological Data (2nd ed.). Ben Roberts.
https://whitlockschluter.zoology.ubc.ca/
Whitton, B.A., & Carr, N. G. (1982). Cyanobacteria: Current Perspectives. In N. G. Carr & B. A.
Whitton (Eds.), The Biology of Cyanobacteria (Vol. 19, p. 688). Blackwell Scientific
Publications. https://trove.nla.gov.au/work/14300108
Whitton, Brian A., & Potts, M. (2000). The Biology and Ecology of Cyanobacteria. Blackwell
Scientific Publications.

104

https://www.researchgate.net/publication/284603746_Introduction_to_the_cyanobacteria_in
_the_Ecology_of_Cyanobacteria_Their_Diversity_in_Time_and_Space_Eds_B
Wium-Andersen, T., Nielsen, A. H., Hvitved-Jacobsen, T., Brix, H., Arias, C. A., & Vollertsen, J.
(2013). Modeling the eutrophication of two mature planted stormwater ponds for runoff
control. Ecological Engineering, 61, 601–613.
https://doi.org/10.1016/j.ecoleng.2013.07.032
Wu, J., & Malmström, M. E. (2015). Nutrient loadings from urban catchments under climate
change scenarios: Case studies in Stockholm, Sweden. Science of the Total Environment,
518–519, 393–406. https://doi.org/10.1016/j.scitotenv.2015.02.041
Yang, Y. Y., & Lusk, M. G. (2018). Nutrients in Urban Stormwater Runoff: Current State of the
Science and Potential Mitigation Options. Current Pollution Reports, 4(2), 112–127.
https://doi.org/10.1007/s40726-018-0087-7
Yindong, T., Xiwen, X., Miao, Q., Jingjing, S., Yiyan, Z., Wei, Z., Mengzhu, W., Xuejun, W., &
Yang, Z. (2021). Lake warming intensifies the seasonal pattern of internal nutrient cycling
in the eutrophic lake and potential impacts on algal blooms. Water Research, 188.
https://doi.org/10.1016/j.watres.2020.116570
Yuan, H., Li, Q., Kukkadapu, R. K., Liu, E., Yu, J., Fang, H., Li, H., & Jaisi, D. P. (2019).
Identifying sources and cycling of phosphorus in the sediment of a shallow freshwater lake
in China using phosphate oxygen isotopes. https://doi.org/10.1016/j.scitotenv.2019.04.322
Zhang, Y., Shi, K., Liu, J., Deng, J., Qin, B., Zhu, G., & Zhou, Y. (2016). Meteorological and
hydrological conditions driving the formation and disappearance of black blooms, an
ecological disaster phenomena of eutrophication and algal blooms. Science of the Total
Environment, 569, 1517–1529. https://doi.org/10.1016/j.scitotenv.2016.06.244

105

Appendices

106

Media

Thesis_MES_2021_Converse.pdf