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A Cascade of Models: Deadwood River, Idaho
Daniele Tonina, Andrew W. Tranmer, Peter Goodwin, Rohan Benjankar, Matthew G. Tiedemann, Paul Woods, Allyn Meuleman, Leticia C. De Vilhena, Dana Weigel,
J. Imberger, Claire McGrath
Center for Ecohydraulics Research, University of Idaho,
322 E. Front St., Boise, Idaho, 83702, USA
Upper Basin – maintains migratory lake salmonids
Lower Basin – questionable populations of bull trout
Deadwood
Very Remote and Inaccessible
Extreme Weather
Reversal of hydrologic regime due to dam
Very few bulltrout remaining
Integrated cascading models
Can basin wide processes be scaled down to model impacts on individual fish and aquatic insect populations?
What tools can be developed to facilitate management decisions at both the reach and basin scale?
Example Deadwood River Basin (614 km2)
Systems Approach
Lake Diagnostic System
EAARL: Experimental Advanced Airborne Lidar
Green spectrum wavelengths used in lieu of red wavelengths penetrates water
Provides a contiguous topographic surface through vegetation and water
Ideal for watershed-scale nested models
1D Hydraulic models2D Hydraulic modelsHyporheic modelsRiparian vegetation studies
Continuous 1m Model Domain
LiDAR Detail Well Preserved
Trapping and tagging [8-15 per year]
• Five of the tags had temperature and depth sensors
• Movement Patterns
• Bull trout seek 12oC water in summer
Telemetry
Linking Fish Behavior with Physical Conditions
Reservoir River
ELCOM - CAEDYM MIKE11
Discharge Temp Water Quality
Velocity Temperature Water Quality Shear stress Food Availability
Bioenergetics & Foodweb Models
Consumption Respiration Excretion Growth
Temp Water
Quality1º, 2º
Production
Green
LiDAR
Bioenergetics &
Foodweb Models
Green
LiDAR
Habitat Model (2-D or 3-D)
Modeled 3D reservoir parameters
1D and 2D river hydraulic models
1D temperature model
1D water quality model
1D biological response model
2D hyporheic model
2D hydraulic habitat model
Practical application: Dam Operations
Deadwood Reservoir, Idaho
How does hydrology impact systems and individual components
-6
-4
-2
0
2
4
6
8
10
12
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20
22
10
/1/0
2
11
/30
/02
1/3
0/0
3
4/1
/03
6/1
/03
8/1
/03
10
/1/0
3
12
/1/0
3
1/3
1/0
4
Tem
pera
ture
(oC
)
Time period
Natural FlowFast ramping down (3 day)Slow ramping down (6 day)
Temperature Regime Can Be Modified
Spawning Migration
Populations of macroinvertebrates are similar across sites
Basis of food web is unaffected by current dam operations
Thalweg profile from EAARL bathymetry
The Lower Deadwood River
0
5
10
15
20
6/15 12/14 6/15 12/14
Tem
pera
ture
(°C
)
Bull Trout Locations and Related Temperaturesin the Deadwood Basin
Future Dam OperationsGreater reliance on existing dams and new construction of large dams globally for mitigating effects of climate change on food webs and species (i.e. China, Turkey, Patagonia). This is to allow species time to adapt where possible
Real-time operations to deal with greater uncertainty from climate change• Maximize beneficial uses of systems• Selective reservoir withdrawal to manage river temperatures• Limnologic monitoring or modeling provides operations guidance• Fish passage structures designed for multiple species, not just for
those of interested as they all are interdependent• Real-time monitoring allows fish behavior, shifts in food web to be
detected and adjustments made throughout the yearSmart dams can be built/modified to account for reservoir conditions and adapt their operations according to numerical simulations of hydrologic and limnologic scenarios
Lessons Learned1) All investigators should be familiar with the system2) Easier to work among teams in different continents than
across discipline! We need more understanding of different scientific approaches among disciplines and meaning of terms.
3) Define a common use of terms among all the participants: biologists, scientists, engineers, economists, sociologists and stakeholders
4) Develop a conceptual model of the entire system5) Invest in field data collection efforts for understanding the
system and model validation (both conceptual and numerical later)
6) Integration of the models should be done at the beginning with the consensus of all the stakeholders
7) Model integration will help guiding field data collection8) Standardize the data collection and develop metadata
information
Lessons Learned9. Have one common repository or web services that links
repositories seamlessly10. Model entire watershed, not just pieces of a watershed as
all things are connected and traceable in all directions and through time1) River systems below dams perform very differently
under variable hydrologic conditions2) Easily measured physical indicators of water quality,
such as those that the EPA targets like temperature, turbidity, etc., may not be the limiting aspects of ecosystem health and robust communities
11. Both Unregulated and regulated streams in the west can experience pulse flows in the winter. Challenged wisdom of constant base flows in winter.
12. Monitor the system afterward to make sure predictions are validated by observations.