status and trends of detroit lake water quality
TRANSCRIPT
Norman Buccola
Margaret Kennedy
Portland District
Oct 26, 2019
STATUS AND TRENDS OF
DETROIT LAKE WATER
QUALITY
2
GOALS OF STATUS AND TRENDS ANALYSIS
1. Organize USACE synoptic survey data (2007
to present) into database (Aquarius Samples)
2. Better understand typical algal growth patterns
and how they may relate to climatic conditions,
watershed land management, and/or Detroit
Dam operations
3. Relate current conditions to historic; observe
trends for Portland District Lakes
3
OUTLINE
–Portland District Water
Management and Water
Quality
–Detroit Lake background
–Brief history of data
collection efforts
–Status and Trends • Temperature
• Nutrients
• Trophic State Index
• Planktonic growth trends
4
WATER MANAGEMENT AND WATER QUALITY
There are 22 USACE reservoirs, each one is
managed and monitored with respect to its
authorized purpose(s)
Naturally occurring lakes positioned similarly to
Detroit Reservoir tend to be nutrient poor,
minimal productivity
Changing average annual water temperatures
and adjusted management practices may be
influencing reservoir productivity
5
DETROIT LAKE PHYSICAL FEATURES
Drainage area: 437 mi² (1,132 km²)
Lake Elevation
– Maximum pool: 1,574 ft (480 m)
– Full pool: 1,569 ft (478 m)
– Usable storage (1,425.0 to 1,563.5 ft) =
321,000 acre feet (396,000,000 m3)
– Max Depth: 450 ft (137 m)
Image Credit: Detroit Recreation Area Business Association
URL: https://www.detroitlakeoregon.org/
6
TYPICAL OPERATION
–Flood Risk Management
(Oct-June)
–Conservation season
(May-November)• Coincides with Chinook spawning
– (flow targets, temperature operations)
• Coincides with recreation period
• Coincides with peak biologic productivity
7
HISTORY OF DATA COLLECTION EFFORTS
1953: Detroit Dam Constructed
1980:
• Oregon Lakes Atlas study (EPA-
funded)
1996:
• Larson Limnological Reports (pre-1996)
• Includes Initial biological studies (60’s-
80’s)
2000-Present:
• Continuous monitoring (temperature and
dissolved gas) at gages begins
2010-Present:
• City of Salem regular sampling
(weekly/monthly)
• USACE synoptic sampling (every 3-5 yrs)
8
HISTORY OF DATA COLLECTION EFFORTS
1953: Detroit Dam Constructed
1980:
• Oregon Lakes Atlas study (EPA-
funded)
1996:
• Larson Limnological Reports (pre-1996)
• Includes Initial biological studies (60’s-
80’s)
2000-Present:
• Continuous monitoring (temperature and
dissolved gas) at gages begins
2010-Present:
• City of Salem regular sampling
(weekly/monthly)
• USACE synoptic sampling (every 3-5 yrs)
9
HISTORY OF DATA COLLECTION EFFORTS
1953: Detroit Dam Constructed
1980:
• Oregon Lakes Atlas study (EPA-
funded)
1996:
• Larson Limnological Reports (pre-1996)
• Includes Initial biological studies (60’s-
80’s)
2000-Present:
• Continuous monitoring (temperature and
dissolved gas) at gages begins
2010-Present:
• City of Salem regular sampling
(weekly/monthly)
• USACE synoptic sampling (every 3-5 yrs)
10
ANNUAL PEAK EPILIMNETIC TEMPERATURE
Data before 2000 hand-
extracted from data
sheets (fewer samples)
Data 2010-2018 from
continuous data loggers
Size of font indicates
relative number of samples
per year
11
CALCULATING TROPHIC STATE
Utilize method developed by the state of Florida
• Older TSI (Carlson, 1977) calculation
methods utilize one parameter to solve
for final TSI
• This approach uses three parameters
to solve for a final TSI that accounts for
the limiting nutrient in the reservoir
• Will allow analysis of nutrient availability
and overall water quality over time
0-59: good
60-69: fair
70-100: poor
Figure Credit: Table 2-8 1996 WATER-QUALITY ASSESSMENT FOR THE STATE
OF FLORIDA SECTION 305(B) MAIN REPORT
URL for Resource:
http://www.pinellas.wateratlas.usf.edu/shared/learnmore.asp?toolsection=lm_tsi
12
PEAK TN:TP RATIO NEAR LAKE SURFACE
• Values 2011-2019 from
City of Salem
• Lack of long-term data
make trends difficult to
assess
Phosphorus limited
Size of font indicates relative
number of samples per year
Nitrogen limited
Transition zone
13
ANNUAL PEAK TROPHIC STATE
• Values prior to 2011
are self-reported
• Values 2011-2019
calculated from City of
Salem and USACE
data
• Data gaps make
trends difficult to
assess
Size of font indicates
relative number of samples
per year
14
TYPICAL BLOOM TIMING
Typical May/June bloom
coinciding with full pool
Second bloom can be as
big as first
15
BLOOM TIMING BY YEAR
Typical May/June bloom
coinciding with full pool
Wet years (2011): delayed
Dry years (2015): can
have second bloom in late
summer
16
DOMINANT PLANKTON SPECIES BY YEAR
• Typical May/June bloom
of Dolichospermum
• Drier years:
Second bloom of
Aphanizomenon
• Wet years:
Preceded by Asterionella
(2011, 2012)
or Followed by Chroococcus
(2014, 2017)
17
Plankton Species Description
Aphanizomenon sp Cyanobacteria;
potentially toxin-
producing
Chroococcus
microscopicus
Cyanobacteria
Dolichospermum sp. Cyanobacteria;
potentially toxin-
producing
Heteroleibleinia sp Cyanobacteria
Plankton
Species
Description
Asterionella
formosa
Diatom
Melosira Diatom
Rhodomonas
minuta
Cryptomonad;
free-
swimming
with
cholorplasts
PLANKTON SPECIES
Birger Skjelbred
Jacob Kann - USGSApothecia
greenwaterlab.com
greenwaterlab.com
Kristian Peters
ncma.bigelow.org
National Park Service
greenwaterlab.com
18
SUMMARY
Photo of Detroit Marina in fall, 2015 Photo credit: By Twelvizm: https://www.flickr.com/photos/twelvizm/20258652110/in/dateposted-public/, CC BY-SA 3.0,
https://commons.wikimedia.org/w/index.php?curid=42236165
• Typically 1 large algal bloom in
May/June (Dolichospermum)
• Dry years: can have another
cyano bloom in late summer
• Wet years: delayed bloom, can be
dominated by diatoms
• Suggestions for future analysis?
Detroit algae bloom in October, 2015 Photo credit: USACE
19
Brandin Hilbrandt (City of Salem)
Kurt Carpenter (USGS)
Contacts:
Norm Buccola
Margaret Kennedy
Holly Bellringer
Tina Lundell
THANK YOU
20
ANNUAL PEAK BY MONTH FOR EACH PARAMETER
Data prior to 2010 hand-
extracted from data
sheets (field trips per
year)
Temperature data 2010-
2018 from data loggers
Caveats: Fewer samples
prior to 2000.
Numbers indicate
number of sample
years
21
DETERMINATION OF DEPTH TO THERMOCLINE
Identification of thermocline in historic data sets
through two main approaches:
[ 1 ] Direct Inspection of Numeric Result
• Identifying the first significant drop in
temperature (relative to your data set)
[ 2 ] Inspection via Construction of Graph
• Identifying the first significant drop in
temperature (relative to your data set)
Reported information:
Depth to Thermocline and Temperature at the
bottom of the epiliminion
22
DETERMINATION OF DEPTH TO THERMOCLINE
Identification of thermocline in historic data sets
through two main approaches:
[ 1 ] Direct Inspection of Numeric Result
• Identifying the first significant drop in
temperature (relative to your data set)
[ 2 ] Inspection via Construction of Graph
• Identifying the first significant drop in
temperature (relative to your data set)
Reported information:
Depth to Thermocline and Temperature at the
bottom of the epiliminion
23
DETERMINATION OF DEPTH TO THERMOCLINE
Identification of thermocline in historic data sets
through two main approaches:
[ 1 ] Direct Inspection of Numeric Result
• Identifying the first significant drop in
temperature (relative to your data set)
[ 2 ] Inspection via Construction of Graph
• Identifying the first significant drop in
temperature (relative to your data set)
Reported information:
Depth to Thermocline and Temperature at the
bottom of the epiliminion
6
8
10
12
14
16
18
20
0 10 20 30 40 50
Depth (m) v. Temp (c)
EPILI
MNION
METALIMNION
H Y P O L I M N I O N
24
DEPTH TO THERMOCLINE