What will happen to the fish? - Dry Creek Experimental Watershed

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Dry Creek Experimental Watershed
Climate and Fish
The Problem
Streams need snow
Fish need streams
Snow is changing
What will happen to the fish?
Dry Creek Experimental Watershed
Climate and Fish
Dry Creek Experimental Watershed
Beyond the Blue
Dry Creek Experimental Watershed (DCEW) mission is to
provide temporally continuous and spatially distributed
hydrometeorological and geographical data from point to
watershed scales for researchers and educators.
15 Year
Hydrometeorological
Record
Long-tem water
balance closure to
support campaign
investigations
Data Types and Availability
Hydroclimatic Data
•
Meteorologic (5)
• Air Temperature
• Relative Humidity
• Wind Speed/Direction
• Solar Radiation
• Net Radiation
• Soil Moisture
• Soil Temperature
• Precipitation
• Snow Depth
• …
•
Eddy Covariance Station (1)
•
Streamflow (7)
• Stage, Temp, EC
•
Soil Moisture (8+)
Geospatial Data
•
Lidar elevation (1m)
•
Modeled soil depth
•
All the typical geospatial coverages
Catchment Area: 28 km2
Elevation Range: 1030-2130 m
Grasses,
shrubs, and
conifer
forests vary
with aspect
and elevation
Low Elevation
Grass
High Elevation
Forest
Mid Elevation
Shrub
Dry Creek Precipitation-Elevation
Boise Front annual precipitation 1999-2009
1200
precipitation (mm)
1100
1000
900
2000
2002
2004
2006
2008
2001
2003
2005
2007
2009
800
700
600
500
400
300
200
100
800
1000
1200
1400
1600
elevation (m)
1800
2000
Dry Creek Snow-Rain
Precipitation
precipitation
(mm)
precipitation
(mm)(mm)
200
150
963 mm
77% Snow
100
50
0
october
january
april
200
july
335 mm
32% Snow
Rain
150
Snow
100
50
0
october
january
april
2008 Water Year
july
A Typical Annual Hydrograph
Annual Water Balance
Precipitation
(mm)
Streamflow
(mm)
Groundwater
Recharge
(mm)
ET (mm)
635
169
37
429
1
0.23
0.09
0.69
Aishlin, (2005)
Distributed Water Balance
40% of annual Precipitation
BG
TL
Catchment Partitioning of Precipitation 2005-2009
C1W
100%
C1E
C2M C2E
80%
LG
60%
Evapotranspiration
40%
Groundwater Recharge
20%
Streamflow
0%
BG
TL
C1E
C2E
C2M
LG
Snow is melting earlier
Figure source: Climate Impacts Group, University of Washington.
What is happening to Low Flow?
Fish Need Water
Not too hot
Not too fast
Not too low
Not too suffocating
Redband Trout
Dry Creek hosts a genetically pure population of Columbia River Redband Trout
“Pure” because Dry Creek is artificially isolated from the Boise River. Rainbow
Trout can’t get to Dry Creek
Should we restore Dry Creek-Boise River connectivity?
Redband Habitat in Dry Creek
What do they need?
Spring is taking water from summer
July
March
June
April
May
Change in
Proportion of Annual Flow
Change in Contribution to Annual Flow
( % per Decade )
pe (% / decade)
Average
Proportion of Annual Flow
5
Reynolds Creek
4
Theil Sen estimator
3
2
1
0
-1
-2
Jan
Mar
May
Jul
Sep
Redband Trout
Low Flow Matters
Spring High Flow
Low Flow Habitat
Summer No Flow
Courtesy of Chris Walser
What will happen to the fish?
200
precipitation
(mm)
• What habitat properties are
important to redband?
150
100
50
0
october
• How are habitat properties
related to hydrology?
• How will hydrology change as
snow pack changes?
january
april
july
flow
Precipitation
EcoHydrologic Modeling
time
time
Hydrologic
Model
Fish Habitat
Climate and Fish Case Study
The Scale and Distribution Problem
Climate and Fish Case Study
Goal: Assess the impact of climate warming on fish
habitat in an upland watershed.
Modeling Challenges:
• How will warming temperatures change the spatial and temporal
distribution of snow in the watershed?
• How will altered snow conditions impact streamflow?
• What specific habitat metrics may be sensitive to climate-driven
hydrologic change?
• How will altered streamflow impacts habitat metrics?
• How do we CONNECT the models?
Climate and Fish Case Study
• Resources:
– Description:
http://earth.boisestate.edu/drycreek/education/i
nterdisciplinary-modeling-exercise-climate-andfish/
– Data: earth.boisestate.edu/drycreek/data
– Models: Up to you
– Science: Up to you
Dry Creek Field Trip
• Objective: Think about spatial and temporal
variability of ecohydrologic processes
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