vii. references
DESCRIPTION
Fiber-optic distributed temperature sensing network deployed in Waquoit Bay, MA (courtesy of USGS). Longitudinal temperature profile of Shenandoah River, VA (courtesy of USGS). Steelhead, Turtles, and Frogs: Temperature Dynamics of Stream Habitat - PowerPoint PPT PresentationTRANSCRIPT
VII. ReferencesVII. ReferencesDanehy, R.J., et al. 2005. Patterns and sources of thermal heterogeneity in small mountain streams within a
forested setting. Forest Ecology & Management 208:287-302.Fellers, G.M., et al. 2001. Overwintering tadpoles in the California Red-Legged Frog (Rana aurora draytonii).
Herpetological Review 32:156-157.Johnson, S.L. 2004. Factors influencing stream temperatures in small streams: substrate effects and a
shading experiment. Canadian Journal of Fisheries and Aquatic Sciences 61:913-923.Malcolm, I.A., et al. 2004. The influence of riparian woodland on the spatial and temporal variability of stream
water temperatures in an upland salmon stream. Hydrology and Earth System Sciences 8:449-459.Moore, R.D., D.L. Spittlehouse, and A. Story. 2005. Riparian microclimate and stream temperature response
to forest harvesting: A review. Journal of the American Water Resources Association 41:813-834.Rich, P.M. 1990. Characterizing plant canopies with hemispherical photography. Remote Sensing Reviews
5:13-29.Ringold, P.L., et al. 2003. Use of hemispheric imagery for estimating stream solar exposure. Journal of the
American Water Resources Association 39:1373-1384.
Steelhead, Turtles, and Frogs: Steelhead, Turtles, and Frogs: Temperature Dynamics of Stream HabitatTemperature Dynamics of Stream Habitat
Paul M. Rich1, Stuart B. Weiss2, and Alan E. Launer3
1Creekide Center for Earth Observation, [email protected] Center for Earth Observation, [email protected]
3Stanford University, Land Use and Environmental Planning, [email protected]
AbstractAbstractAvailability of stream habitat with suitable temperature regimes is required by many species of conservation concern. Water temperature is determined by a complex interplay of prevailing meteorology, local riparian canopy structure and solar exposure, streambed morphology, and surface and subsurface flow patterns. We developed a technique for spatial-temporal analysis of temperature regimes for San Francisquito Creek (San Francisco Peninsula, California), which comprises habitat for steelhead (Oncorhynchus mykiss), California red-legged frog (Rana aurora draytonii) and western pond turtle (Clemmys marmorata). Steelhead requires relatively cool conditions, whereas the frog and turtle require warmer conditions. Our approach synthesized measurements of temperature from a network of inexpensive sensors (IButton Thermochron), riparian canopy structure and solar exposure from hemispherical (fisheye) photography, stream morphology from field characterization and geographic information system (GIS) analysis, stream flow and water temperature from gauging stations, and meteorology from nearby weather stations. We employed the RTemp Model (Washington State Department of Ecology) to predict time series of water temperature in response to heat fluxes. Water temperature co-varied with air temperature, diurnally with a lag of several hours, and over longer periods. Stream reaches with high solar exposure displayed relatively high temperature variability (up to 5° C differential from baseline), whereas shaded reaches displayed only modest temperature variability (0.5-1.0° C differential). Subsurface flow through gravel beds decreased temperature (2-3° C decrease). Our approach can be applied to a broad spectrum of streams for habitat characterization, for conservation management to ensure habitat heterogeneity, and for examination of potential impacts of climate change.
II. MethodsII. Methods
III. ResultsIII. Results
I. IntroductionI. Introduction
IV. Temperature ModelIV. Temperature Model
VIII. AcknowledgementsVIII. Acknowledgements
VI. PerspectiveVI. Perspective
• Nina Allmendinger• Linda Chamberlin• Nona Chiariello• Trevor Hébert• Ryan Navratil• Bijan Osmani• Brian Scoles• Pam Sturner
• Jasper Ridge Biological Preserve• National Fish and Wildlife
Foundation• San Francisquito Watershed
Council• Stanford University, Land Use and
Environmental Planning
Creek monkeys
Goal: Conserve species with different temperature requirements
• Cooler temperature: Steelhead Trout (Oncorhyncus mykiss)
• Warmer temperature: Northern red-legged frog (Rana aurora) and Western pond turtle (Clemmys marmorata)
Study Area: San Francisquito Watershed, California
• Headwaters in Santa Cruz Mountains, drains into San Francisco Bay (37°27’ N, 120°00’ W)
• 123 sq km, 3 tributaries, 24 creeks
Conservation Concerns• Changes in solar exposure: riparian
vegetation modification • Changes in runoff / flow: watershed
development and stream channel modification
• Climate change: shifts in energy balance
Our Approach• Develop sampling protocol and energy
balance model to characterize water temperature dynamics
• Analyze relationships between solar exposure and temperature regimes
• Relate temperature heterogeneity tohabitat suitability for different species
Long-Term Monitoring• Flow and water temperature from
gauging stations• Meteorology from nearby weather
stations
Intensive Field Measurements• Solar exposure using
hemispherical photography• Water temperature using sensor
network of iButton Thermochrons
Analysis and Modeling• Spatiotemporal patterns• Temperature model
A) Temperature Regimes• Water temperature co-varies with
air temperature, with lags• Variance explained by solar
exposure and flow patterns
B) Riparian Canopy Effects• Stream reaches with high solar exposure display
high temperature variability (up to 5° C differential from baseline)
• Shaded reaches display modest temperature variability (0.5–1.0° C differential)
C) Diurnal Canopy Effects• Water temperature closely tracks air
temperature when direct solar exposure• Lower diurnal variation in heavily shaded
reaches, and peak water temperature lags >4 hr after peak air temperature
D) Subsurface Flow Effects• Subsurface flow through gravel beds can decrease temperature 2 - 3° C
E) Solar Exposure• Solar radiation from hemiphotos every 2.5 m
along 100 meter transects • Insolation increases >3-fold between October
and June/July• Less riparian vegetation for “Dennis Martin”
than “Lunar Rocks” reaches, leading to higher insolation
F) Spatial Autocorrelation• Spatial autocorrelation used to calculate appropriate hemispherical photography sampling interval
• Semivariance peaks at 10-15 m, with pseudoperiodicity
• Implication: sample interval of 10-20 m
G) Simulated Tree Removal• Large California bay laurel
(Umbellularia californica) removed using image editing
• Tree removal increased solar exposure 2-3x, with effects 7.5 m downstream and 12.5 m upstream
Energy Balance• Predict water temperature based on energy balance
using modified rTemp model (State of Washington, http://www.ecy.wa.gov/programs/eap/models.html)
• Inputs: air temperature, solar radiation, canopy cover, water depth, etc.
• Output: water temperature as a function of time
Simulation of Riparian Canopy Change• Riparian canopy cover varied from 0 to 100%• Increased solar exposure leads to proportional
increase in daytime water temperature
V. Future WorkV. Future Work
Fiber-optic distributed temperature sensing network deployed in Waquoit Bay, MA
(courtesy of USGS)
Characterization and Modeling• Complete hemispherical photography and temperature sensor characterization• Characterize stream morphology (collaboration
with Balance Hydrologics)• Develop comprehensive temperature model
New Technologies• Use LIDAR for riparian canopy characterization
(collaboration with Stanford/Carnegie)• Apply fiber-optic technique for distributed temperature
sensing (collaboration with USGS)
Longitudinal temperature profile of Shenandoah River, VA (courtesy of USGS)
Water temperature key determinant of habitat• Steelhead Trout prefer cooler conditions• Red-Legged Frogs and Western Pond Turtles prefer warmer conditions
Synthetic Approach• Monitoring of flow, water temperature, meteorology,
geomorphology, etc.• Solar exposure from hemispherical photographs• Observed temperature from Thermochron sensor network• Predicted temperature from energy balance model
Applicable for broad spectrum of streams
Day
06-Sep-06 13-Sep-06 20-Sep-06 27-Sep-06 04-Oct-06
Te
mpe
ratu
re (
°C)
12
14
16
18
20
22 Open Canopy (morning sun)Closed Canopy
Time of Day (hour)
00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00
Te
mp
erat
ure
(°C
)
10
12
14
16
18
20
22
24AirOpen Canopy (morning sun)Closed Canopy
Dam
Day
04-S
ep
11-S
ep
18-S
ep
25-S
ep
02-O
ct
Te
mp
era
ture
(°C
)
8
10
12
14
16
18
20
22
24OutletCM Mouth
Lunar Rocks Semivariogram
Distance (m)
0 5 10 15 20 25
Se
miv
aria
nce
0
2000
4000
6000June/JulyAugust September October
"Dennis Martin" Reach
Position (m)
0 20 40 60 80 100
Inso
latio
n (
MJ/
m2/d
ay)
0
5
10
15
20
25
30
June/JulyAugustSeptemberOctober
"Lunar Rocks" Reach
Position (m)
0 20 40 60 80 100
Inso
latio
n (
MJ/
m2/d
ay)
0
5
10
15
20
25
30
June/JulyAugustSeptemberOctober
June
Position (m)
60 70 80 90 100
Inso
latio
n (
MJ/
m2/d
ay)
0
5
10
15
20
25
30
Without Tree
With Tree
Air Temperature
04-
Se
p
11-
Se
p
18-
Se
p
25-
Se
p
02-
Oct
Tem
pera
ture
(°C
)
0
5
10
15
20
25
30
35
40
45Lunar Air Dennis Martin Air LT Ladera Air Dam Air Confluence Air
Dennis Martin
04-S
ep
11-S
ep
18-S
ep
25-S
ep
02-O
ct
Tem
pera
ture
(°C
)
10
12
14
16
18
20
22
24
DM2
DM Pool
DM US
DM1
Lunar Rocks
04
-Se
p
11
-Se
p
18
-Se
p
25
-Se
p
02
-Oct
Te
mp
era
ture
(°C
)
10
12
14
16
18
20
22
24
Lunar 1
Lunar 3... Lunar 2
DM Downstream
04-S
ep
11-S
ep
18-S
ep
25-S
ep
02-O
ct
Tem
pera
ture
(°C
)
10
12
14
16
18
20
22
24
DM DS3 SF Piers Br
DM DS1 DM DS2
SF Webb Br.
Dam
04-S
ep
11-S
ep
18-S
ep
25-S
ep
02-O
ct
Tem
pera
ture
(°C
)
10
12
14
16
18
20
22
24Outlet Trout Pool CM Mouth
Los Trancos 1
04-
Se
p
11-
Se
p
18-
Se
p
25-
Se
p
02-
Oct
Te
mp
era
ture
(°C
)
10
12
14
16
18
20
22
24
LT Mouth
LT Divers
LT DS Ladera LT Ladera Br.
September 2006 Mean Daily Values
Hour
0:0
0
2:0
0
4:0
0
6:0
0
8:0
0
10:
00
12:
00
14:
00
16:
00
18:
00
20:
00
22:
00
0:0
0
Tem
pera
ture
(°C
)
10
15
20
25
30
Solar R
adiation (W/m
2)
0
100
200
300
400
500
600
700
800
900
1000
Air Temperature
Observed Water Temperature
Solar Radiation
Predicted WaterTemperature
Predicted Water Temperature
Hour
0:0
0
2:0
0
4:0
0
6:0
0
8:0
0
10:
00
12:
00
14:
00
16:
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18:
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20:
00
22:
00
0:0
0
Tem
pera
ture
(°C
)
10
15
20
25
30 100% Solar Exposure75% Solar Exposure50% Solar Exposure25% Solar ExposureNo Solar Exposure