Floodplain Operational Loss Assessment on the Kootenai River Watershed Downstream from Libby Dam

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Floodplain Operational Loss Assessment on the
Kootenai River Watershed Downstream from Libby Dam

• Participants
• Kootenai Tribe of Idaho
• Montana Fish Wildlife, Parks
• U of Idaho, Ecohydraulics Research Group
• Bahman Shafii SCS
• Paul Anders SP Cramer Associates
• Tim Hatten U of Idaho
• GeoEngineers
• Research Design Review Team (multiple parties)

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Floods averaged 1 out of every 4 years
1894, 1903, 1913, 1916, 1927, 1928, 1933, 1938,
1947, 1948, 1950, 1954, 1956, 1959, 1961, 1964,
1966, 1967, 1971, 1974, 1976, 1981, 1987, 1996,
and 1997
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Flooding in Kootenai River Valley still a threat
until 1973
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Location
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Central Paradigm 1
Ecological processes, communities, and habitats
are dynamically connected in natural large
river- floodplain ecosystems.
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Central Paradigm 1
Riparian
Aquatic
Requires a Multidisciplinary Approach
Terrestrial
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Central Paradigm 3
Loss assessments for past wildlife mitigation
programs generally included area-based
approaches.
However, a quantifiable, transferable ecological
function-based loss assessment approach is more
informative.
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Project Goals

• Goal 1 Develop a scientifically valid and
  regionally acceptable assessment tool (OLA) to
  quantify habitat and ecological function loss due
  to the operation of Libby Dam.

• Goal 2 Ensure this OLA tool is transferable to
  evaluate operational losses of the Federal
  Columbia River Hydropower System outside the
  Kootenai River Subbasin.

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• PROJECT OBJECTIVES
• Identify ecological and habitat parameters needed
  to meaningfully assess ecological change.
• Quantify pre- and post-development ecological
  conditions with relevant parameters and
  statistical methods.
• Develop, implement, and refine an Index of
  Ecological Integrity (IEI) that incorporates the
  pre- and post-development ecological conditions
  to quantify habitat and ecological function loss
  at the ecosystem level.
• Meet with regional fish and wildlife managers and
  scientists as needed to ensure transferability of
  the OLA tool.

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OLA Project Conceptual Framework
Historical
Community Level Indices
Index of Hydrologic Alteration
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OLA Project Conceptual Framework Index of
Biologic Integrity (IBI)
Index of Hydrologic Alteration
Aquatic Primary Productivity
Terrestrial Primary Productivity
Aquatic Invertebrate Community
Terrestrial Invertebrate Community
Fish, Avian Communities.
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OLA Project Conceptual Framework
Historical
Post-development
Index of Hydrologic Alteration
Aquatic Primary Productivity
Terrestrial Primary Productivity
Aquatic Invertebrate Community
Terrestrial Invertebrate Community
Fish, Avian Communities.
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OLA Project Conceptual Framework
-
Historical
Post-development Loss
Index of Hydrologic Alteration
Aquatic Primary Productivity
Terrestrial Primary Productivity
Aquatic Invertebrate Community
Terrestrial Invertebrate Community
Fish, Avian Communities.
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OLA Project Conceptual Framework
Index of Ecological Integrity (IEI)
Community Index Changes
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Aquatic Multi-trophic Biomonitoring Program
Water Quality
Periphyton
Macroinvertebrates
Fish Community Dynamics
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NUTRIENT SUMMARY ABOVE BELOW LIBBY D.2003
data (n209)
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CHLOROPHYLL a
20-30 mg/m2 PRODUCTIVE NW RIVERS
2.43 mg/ m2 IDAHO SITES
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MACROINVERTEBRATE BIOMASS
LARGE RIVER REFERENCE SITE MEAN, 9 g/m2, 17 ID
RIVERS (Minshall 1997)
IDAHO SITES
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FISH BIOMASS
IDAHO SITES
MT SITE
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LiDAR Instrumentation
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Multiple Returns
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LiDAR Outputs
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River Cross Sections(1 D Modeling)
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1991
1954

• 40 day period where recruitment
• box criteria are satisfied.
• recruitment band of approx. 0.6m

• longest recruitment period is 5 days due to
  flashy recession.
• recruitment band lt 0.1m

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1 2 D Hydraulic Modeling
Composite-1954,1955,1956,1957,1962
Composite-1986,1991,1993,1994,1996
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Normalized Difference Vegetation Index

• NDVI uses red and near infra red bands of
  satellite imagery to compute an index providing
  information on canopy cover, leaf area index and
  net primary productivity.
• Chlorophyll absorbs blue and red light energy for
  photosynthesis leaves appear green because of
  this.
• Leaves also reflect near infra-red (NIR).
• NDVI uses the relative differences in reflective
  values of two spectral segments (red and nir) to
  create a quantitative index of vegetation
  condition using satellite imagery.
• NDVI NIR-RED / NIR-RED
• NDVI is influenced by the amount of bare soil or
  water in the same pixel as the vegetation.
• NDVI is related to Leaf Area Index, net primary
  productivity and biomass.

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Raw NDVI image
Key
Bright areas show actively growing vegetation
Vegetation has NDVI values gt 0
Water and exposed soil have values lt 0 and
appear dark.
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LANDSAT/Gap Cover Type Classification
Riparian Cover Types BDR Broadleaf Dominated
Riparian BDRW Broadleaf Dominated Riparian
Woodland MR Mixed Riparian SDR Shrub
Dominated Riparian NDR Needleleaf Dominated
Riparian GFDR Wet Graminoid-Forb Dominated
(perennially wet). GFDR Moist Graminoid Forb
Dominated (moist surface) GFDR Dry Graminoid
Forb Dominated (Dry surface). W - Water WE
Water Edge UC Urban/Cobble
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Mean NDVI Values by Cover Type, June 22, 2001500
Year Floodplain of the Kootenai River Braided
and Meander Reaches, rescaled from -100 to 100
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Why use avian communities as a measure of
ecological health?

• Landbirds are the most visible vertebrate group
  and are relatively easy (inexpensive) to monitor
  (Hutto 1998)
• Patterns of occurrence in the field are easily
  uncovered (Hutto 1998)
• A single method collects data on a large number
  of species (Hutto 1998)
• Birds are closely associated with specific
  habitats or habitat features (such as cavities)
  that might be difficult to locate or measure.
• birds are useful as indicators because they are
  everywhere, and different species vary in their
  sensitivity to physical, chemical, and biological
  threats

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Why use insect communities as a measure of
ecological health?

• are very diverse!
• perform a disproportionate number of ecological
  functions (e.g. nutrient cycling, pollination,
  population regulation, pest control, etc.)
• numerous representatives in several trophic
  levels
• are easily sampled and identified
• are often habitat specific, sensitive to
  disturbance, and hence useful bio-indicators
  (Price 1997)

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Ecological components of OLA Hydraulic/geomorph
ology Water Quality/Nutrients Algae/periphyton
Benthic invertebrates Fishes Vegetation
Primary Productivity Terrestrial vegetation
(classification, modeling) Terrestrial
invertebrates Birds
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• Current Working Objectives
• Refine hydraulic modeling, related Biotic
  Integrity (BI) measures and the relationships to
  IEI framework
• Characterize, analyze and interpret the Index of
  Ecological Integrity (IEI) framework and
  contributing community level indices
  (geomorphic/hydraulic, terrestrial and aquatic)
  as a model for characterizing ecological function
  change and loss for operational loss assessments.
• Determine, analyze and monitor a framework for
  more sophisticated statistical analyses and
  modeling efforts concerning biotic and abiotic
  multi-trophic level data.
• Meet with regional fish and wildlife managers and
  scientists as needed to ensure transferability of
  the OLA tool.